{"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":2050,"title":"remove nans fast","description":"There are several ways to locate and remove nans in a matrix, and return an 1d row vector. \r\n\r\nIn this problem the challenge is to do it within a set time as measured by tic-toc.\r\n\r\nThe problem will be run numerous times and an average time tested.\r\n\r\nNote: I noticed a rare failure depending on when I ran the testsuite, so you _might_ have to resubmit your code if it runs faster on your machine than the limit set here.","description_html":"\u003cp\u003eThere are several ways to locate and remove nans in a matrix, and return an 1d row vector.\u003c/p\u003e\u003cp\u003eIn this problem the challenge is to do it within a set time as measured by tic-toc.\u003c/p\u003e\u003cp\u003eThe problem will be run numerous times and an average time tested.\u003c/p\u003e\u003cp\u003eNote: I noticed a rare failure depending on when I ran the testsuite, so you \u003ci\u003emight\u003c/i\u003e have to resubmit your code if it runs faster on your machine than the limit set here.\u003c/p\u003e","function_template":"function nanless = removenan(m)\r\nloc=find(nan);\r\nnanless= removenan(m,loc);\r\nend","test_suite":"%% T1\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(100,100,100);\r\n m(m\u003e0.7)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(100,100,100);\r\nm(m\u003e0.7)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n\r\n%% T2\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(100,10000);\r\n m(m\u003e0.71)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(100,10000);\r\nm(m\u003e0.71)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n\r\n%% T3\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(2,500000);\r\n m(m\u003e0.69)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(2,500000);\r\nm(m\u003e0.69)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":17471,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":"2013-12-15T04:17:20.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-12-15T03:36:48.000Z","updated_at":"2026-02-13T18:32:27.000Z","published_at":"2013-12-15T04:15:46.000Z","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\u003eThere are several ways to locate and remove nans in a matrix, and return an 1d row vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem the challenge is to do it within a set time as measured by tic-toc.\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 problem will be run numerous times and an average time tested.\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\u003eNote: I noticed a rare failure depending on when I ran the testsuite, so you\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\u003emight\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e have to resubmit your code if it runs faster on your machine than the limit set here.\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":44242,"title":"Replace Nan!","description":"Replace Nan in the given vector(v) with 9999.","description_html":"\u003cp\u003eReplace Nan in the given vector(v) with 9999.\u003c/p\u003e","function_template":"function y = ReplaceNan(v)\r\n  y = v;\r\nend","test_suite":"%%\r\nx=[1 2 3 0/0 4];\r\ny_correct = [1 2 3 9999 4];\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n\r\n%%\r\nx=[5:9];\r\ny_correct =[5:9];\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n\r\n%%\r\nx=repmat(0/0,1,10);\r\ny_correct = repmat(9999,1,10);\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":102298,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":87,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-06-27T13:30:08.000Z","updated_at":"2026-02-13T18:08:24.000Z","published_at":"2017-06-27T13:33:17.000Z","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\",\"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\u003eReplace Nan in the given vector(v) with 9999.\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":42481,"title":"Low level NaN","description":"I have a dataset. Columns represents different variables.\r\nA variable may start with NaN or any double type number.\r\nIf it starts with double number it continues with double type numbers.\r\nIf it starts with NaN, we do not know when it ends.\r\nReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\r\nInput\r\n[ 1 NaN 5 NaN 2\r\n2 NaN 4 4 8\r\n6 NaN 8 2 4\r\n0 0 0 0 0]\r\nshould return 3 because last NaN is observed in third row.\r\nTest suite may be changed!","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: 325.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 162.583px; transform-origin: 407px 162.583px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 102.167px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 51.0833px; transform-origin: 391px 51.0833px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 178.5px 8px; transform-origin: 178.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eI have a dataset. Columns represents different variables.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 180px 8px; transform-origin: 180px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA variable may start with NaN or any double type number.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 214.5px 8px; transform-origin: 214.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf it starts with double number it continues with double type numbers.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 153.5px 8px; transform-origin: 153.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf it starts with NaN, we do not know when it ends.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 275.5px 8px; transform-origin: 275.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\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: 15.5px 8px; transform-origin: 15.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eInput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2px 8.5px; transform-origin: 2px 8.5px; \"\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: 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: 52px 8px; transform-origin: 52px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 52px 8.5px; transform-origin: 52px 8.5px; \"\u003e1 NaN 5 NaN 2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 44px 8px; transform-origin: 44px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 44px 8.5px; transform-origin: 44px 8.5px; \"\u003e2 NaN 4 4 8\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 44px 8px; transform-origin: 44px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 44px 8.5px; transform-origin: 44px 8.5px; \"\u003e6 NaN 8 2 4\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 36px 8px; transform-origin: 36px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e0 0 0 0 0\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=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2px 8.5px; transform-origin: 2px 8.5px; \"\u003e]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 181.5px 8px; transform-origin: 181.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eshould return 3 because last NaN is observed in third row.\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: 87px 8px; transform-origin: 87px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTest suite may be changed!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = lowestLevelNaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1\tNaN\t0\t0\r\n2\tNaN\t0\t0\r\n3\tNaN\t1\t0\r\n4\t3\t2\t1\r\n5\t4\t3\t2\r\n6\t5\t4\t3];\r\ny_correct = 3;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [1\tNaN\t0\tNaN\r\n2\tNaN\t0\tNaN\r\n3\tNaN\t1\tNaN\r\n4\t3\t2\tNaN\r\n5.7\t4\t3\tNaN\r\n6\t5\t4\t3];\r\ny_correct = 5;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n\r\n%%\r\nx = [NaN\tNaN\t0\tNaN\r\nNaN\tNaN\t0\tNaN\r\nNaN\tNaN\t1\tNaN\r\nNaN\t3\t2\t-4.5\r\n5.7\t4\t3\t0.0\r\n6\t5\t4\t3];\r\ny_correct = 4;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [NaN];\r\ny_correct = 1;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n\r\n%%\r\nx = [NaN\tNaN\tNaN\tNaN\r\nNaN\tNaN\tNaN\tNaN\r\nNaN\tNaN\tNaN\tNaN\r\nNaN\t3\tNaN\tNaN\r\n5.7\t4\tNaN\tNaN\r\n6\t5\tNaN\tNaN\r\n4\t0\t0\t0];\r\ny_correct = 6;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [1\tNaN\r\n1\tNaN\r\n1\tNaN\r\n1\tNaN\r\n5.7\tNaN\r\n6\tNaN\r\n-1.0\tNaN\r\n4\tNaN\r\n4\tNaN\r\n4\tNaN\r\n4\tNaN];\r\ny_correct = 11;\r\nassert(isequal(lowestLevelNaN(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":8703,"edited_by":223089,"edited_at":"2022-10-23T10:32:55.000Z","deleted_by":null,"deleted_at":null,"solvers_count":66,"test_suite_updated_at":"2015-08-01T02:31:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-07-31T17:19:52.000Z","updated_at":"2026-02-26T12:21:33.000Z","published_at":"2015-07-31T17:47:04.000Z","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=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI have a dataset. Columns represents different variables.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA variable may start with NaN or any double type number.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf it starts with double number it continues with double type numbers.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf it starts with NaN, we do not know when it ends.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\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\u003eInput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e1 NaN 5 NaN 2\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e2 NaN 4 4 8\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e6 NaN 8 2 4\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e0 0 0 0 0\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eshould return 3 because last NaN is observed in third row.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTest suite may be changed!\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":42261,"title":"Determine if a row vector has NaN","description":"Determine if a row vector x has NaN","description_html":"\u003cp\u003eDetermine if a row vector x has NaN\u003c/p\u003e","function_template":"function y = NaNis(x)\r\n  y = NaNis;\r\nend","test_suite":"%%\r\nx = [1,2,3,4,NaN];\r\ny = 1;\r\nassert(isequal(NaNis(x),y))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":38003,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":136,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-04-24T07:02:25.000Z","updated_at":"2026-02-16T16:46:47.000Z","published_at":"2015-04-24T07:02:29.000Z","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\u003eDetermine if a row vector x has NaN\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":43708,"title":"Replace all odd numbers with NaN","description":"Replace all odd numbers in the vector or matrix with NaN. For example, if\r\n\r\n x = [1 3 4 5 8 11];\r\n\r\nthen return\r\n\r\n y = [NaN NaN 4 NaN 8 Nan];","description_html":"\u003cp\u003eReplace all odd numbers in the vector or matrix with NaN. For example, if\u003c/p\u003e\u003cpre\u003e x = [1 3 4 5 8 11];\u003c/pre\u003e\u003cp\u003ethen return\u003c/p\u003e\u003cpre\u003e y = [NaN NaN 4 NaN 8 Nan];\u003c/pre\u003e","function_template":"function y = replace_odd_with_NaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 3 4 5 8 11];\r\ny_correct = [NaN NaN 4 NaN 8 NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = magic(4);\r\ny_correct = [16 2 NaN NaN; NaN NaN 10 8; NaN NaN 6 12; 4 14 NaN NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = 1:20;\r\ny_correct = [NaN(1,10); 2:2:20];\r\ny_correct = y_correct(:)';\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = pascal(2);\r\ny_correct = [NaN NaN; NaN 2];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = eye(3);\r\ny_correct = [NaN 0 0; 0 NaN 0; 0 0 NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":9,"created_by":88437,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":83,"test_suite_updated_at":"2016-12-05T17:06:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-04T13:23:09.000Z","updated_at":"2026-02-17T14:35:28.000Z","published_at":"2016-12-04T13:23:09.000Z","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\u003eReplace all odd numbers in the vector or matrix with NaN. For 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[ x = [1 3 4 5 8 11];]]\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\u003ethen return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [NaN NaN 4 NaN 8 Nan];]]\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":1406,"title":"Generate a NaN...on purpose","description":"The goal is to create a function that will return a single \"NaN\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\r\n\r\n","description_html":"\u003cp\u003eThe goal is to create a function that will return a single \"NaN\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\u003c/p\u003e","function_template":"function y = GenerateNAN\r\n  y = 0;\r\nend","test_suite":"%%\r\nassert(isnan(GenerateNAN))\r\n\r\n%%\r\nfiletext = fileread('GenerateNAN.m');\r\nassert(isempty(strfind(filetext, 'regexp')))\r\nassert(isempty(strfind(filetext, 'nan')))\r\nassert(isempty(strfind(filetext, 'NaN')))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":4,"created_by":3096,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":326,"test_suite_updated_at":"2013-04-01T16:51:00.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-01T16:46:28.000Z","updated_at":"2026-03-09T20:29:02.000Z","published_at":"2013-04-01T16:51:00.000Z","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\u003eThe goal is to create a function that will return a single \\\"NaN\\\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\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":1194,"title":"Replace multiples of 5 with NaN","description":"It is required to replace all values in a vector that are multiples of 5 with NaN.\r\n\r\nExample:\r\n\r\n input:   x = [1 2 5 12 10 7]\r\n output:  y = [1 2 NaN 12 NaN 7]","description_html":"\u003cp\u003eIt is required to replace all values in a vector that are multiples of 5 with NaN.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e input:   x = [1 2 5 12 10 7]\r\n output:  y = [1 2 NaN 12 NaN 7]\u003c/pre\u003e","function_template":"function y = repnan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 2 5 12 10 7];\r\ny_correct = [1 2 NaN 12 NaN 7];\r\nassert(isequaln(repnan(x),y_correct))\r\n\r\n%%\r\nx = [-1 7 -15 20 11 3];\r\ny_correct = [-1 7 NaN NaN 11 3];\r\nassert(isequaln(repnan(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3399,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":468,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-10T19:04:51.000Z","updated_at":"2026-03-05T11:40:16.000Z","published_at":"2013-01-10T19:07:36.000Z","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\u003eIt is required to replace all values in a vector that are multiples of 5 with NaN.\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:\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 = [1 2 5 12 10 7]\\n output:  y = [1 2 NaN 12 NaN 7]]]\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":42480,"title":"Go back n times","description":"You will be given a column vector (such as x =  [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\r\n\r\n [ 1 NaN NaN NaN\r\n   2   1 NaN NaN\r\n   3   2   1 NaN\r\n   4   3   2   1\r\n   5   4   3   2 \r\n   6   5   4   3 ]","description_html":"\u003cp\u003eYou will be given a column vector (such as x =  [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\u003c/p\u003e\u003cpre\u003e [ 1 NaN NaN NaN\r\n   2   1 NaN NaN\r\n   3   2   1 NaN\r\n   4   3   2   1\r\n   5   4   3   2 \r\n   6   5   4   3 ]\u003c/pre\u003e","function_template":"function y = goNtimes(x,n)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1:6]';\r\nn = 3;\r\ny_correct = [1\tNaN\tNaN\tNaN\r\n2\t1\tNaN\tNaN\r\n3\t2\t1\tNaN\r\n4\t3\t2\t1\r\n5\t4\t3\t2\r\n6\t5\t4\t3];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [17;23;4;10;11];\r\nn = 4;\r\ny_correct = [17\tNaN\tNaN\tNaN\tNaN\r\n23\t17\tNaN\tNaN\tNaN\r\n4\t23\t17\tNaN\tNaN\r\n10\t4\t23\t17\tNaN\r\n11\t10\t4\t23\t17];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [35;3;31;8;30;4];\r\nn = 1;\r\ny_correct = [35\tNaN\r\n3\t35\r\n31\t3\r\n8\t31\r\n30\t8\r\n4\t30];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n\r\n%%\r\nx = [35;3;31;8;30;4];\r\nn = 2;\r\ny_correct = [35\tNaN\tNaN\r\n3\t35\tNaN\r\n31\t3\t35\r\n8\t31\t3\r\n30\t8\t31\r\n4\t30\t8];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [30;38;46;5;13;21;22];\r\nn = 4;\r\ny_correct = [30\tNaN\tNaN\tNaN\tNaN\r\n38\t30\tNaN\tNaN\tNaN\r\n46\t38\t30\tNaN\tNaN\r\n5\t46\t38\t30\tNaN\r\n13\t5\t46\t38\t30\r\n21\t13\t5\t46\t38\r\n22\t21\t13\t5\t46];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":4,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":48,"test_suite_updated_at":"2015-08-01T03:34:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-07-31T17:09:57.000Z","updated_at":"2026-03-02T14:38:21.000Z","published_at":"2015-07-31T18:07:11.000Z","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\u003eYou will be given a column vector (such as x = [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\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 NaN NaN NaN\\n   2   1 NaN NaN\\n   3   2   1 NaN\\n   4   3   2   1\\n   5   4   3   2 \\n   6   5   4   3 ]]]\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":802,"title":"Create a matrix from a cell","description":"In this problem , you must convert a cell into a matrix and pad each cell with NaN. \r\n\r\n\r\n*Example 1:* \r\n\r\nIf you have the input cell:\r\n\r\n  C = {[1 2 3],[]}\r\n\r\nthe output must be the matrix :\r\n\r\n    output = [  1     2     3\r\n               NaN   NaN   NaN]\r\n\r\n\r\n\r\n\r\n*Example 2:* \r\n\r\n  C = {[1 2 3],8,[],[15  3]}\r\n\r\nthe output must be the matrix :\r\n  \r\n       1     2     3\r\n       8   NaN   NaN\r\n     NaN   NaN   NaN\r\n      15     3   NaN\r\n\r\n\r\n\r\n\r\n\r\n","description_html":"\u003cp\u003eIn this problem , you must convert a cell into a matrix and pad each cell with NaN.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample 1:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIf you have the input cell:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eC = {[1 2 3],[]}\r\n\u003c/pre\u003e\u003cp\u003ethe output must be the matrix :\u003c/p\u003e\u003cpre\u003e    output = [  1     2     3\r\n               NaN   NaN   NaN]\u003c/pre\u003e\u003cp\u003e\u003cb\u003eExample 2:\u003c/b\u003e\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eC = {[1 2 3],8,[],[15  3]}\r\n\u003c/pre\u003e\u003cp\u003ethe output must be the matrix :\u003c/p\u003e\u003cpre\u003e       1     2     3\r\n       8   NaN   NaN\r\n     NaN   NaN   NaN\r\n      15     3   NaN\u003c/pre\u003e","function_template":"function output= your_fcn_name(C)\r\n  output = C;\r\nend","test_suite":"%% example 1\r\nC = {[1 2 3],[]};\r\n output = [  1     2     3\r\n               NaN   NaN   NaN];\r\nassert(isequalwithequalnans(your_fcn_name(C),output))\r\n\r\n%% example 2\r\nC = {[1 2 3],8,[],[15  3]};\r\ny_correct = [ 1     2     3\r\n     8   NaN   NaN\r\n   NaN   NaN   NaN\r\n    15     3   NaN];\r\n\r\nassert(isequalwithequalnans(your_fcn_name(C),y_correct))\r\n\r\n\r\n%%\r\ntcell = {ones(1,4), [1 2 3 4 5], 1:8, 1, [],0};\r\ny_correct = [   1     1     1     1   NaN   NaN   NaN   NaN\r\n     1     2     3     4     5   NaN   NaN   NaN\r\n     1     2     3     4     5     6     7     8\r\n     1   NaN   NaN   NaN   NaN   NaN   NaN   NaN\r\n   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN\r\n     0   NaN   NaN   NaN   NaN   NaN   NaN   NaN];\r\nassert(isequalwithequalnans(your_fcn_name(tcell),y_correct))\r\n\r\n%%\r\nC = {[]}\r\nassert(isempty(your_fcn_name(C)))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":639,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":75,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-28T10:25:57.000Z","updated_at":"2026-03-06T12:32:57.000Z","published_at":"2012-06-28T10:25:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem , you must convert a cell into a matrix and pad each cell with NaN.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample 1:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf you have the input cell:\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[C = {[1 2 3],[]}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ethe output must be the 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[    output = [  1     2     3\\n               NaN   NaN   NaN]]]\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\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[C = {[1 2 3],8,[],[15  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\u003ethe output must be the 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[       1     2     3\\n       8   NaN   NaN\\n     NaN   NaN   NaN\\n      15     3   NaN]]\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":1216,"title":"Mean ignoring NaNs","description":"Define a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).","description_html":"\u003cp\u003eDefine a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).\u003c/p\u003e","function_template":"function y=average(x,d)\r\ny=0;\r\n","test_suite":"%%\r\nx=[1 5 9;2 6 10;3 nan 11;nan nan nan];\r\ny_correct=[2 5.5 10];\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=[5;6;7;nan];\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=x;\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n%%\r\nx=cat(3,[1 5 9;NaN 6 10;NaN 7 NaN;4 8 12],...\r\n [13 17 21;14 18 22;15 19 NaN;16 20 24]);\r\ny_correct=cat(3,[15 39 62]/6,[87 111 134]/6);\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=cat(3,[5;8;7;8],[17;18;17;20]);\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=[7 11 15;14 12 16;15 13 NaN;10 14 18];\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n%%\r\nx=zeros(2,1,0);\r\ny_correct=mean(x);\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=mean(x,2);\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=mean(x,3);\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":245,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-19T20:54:55.000Z","updated_at":"2026-03-05T14:17:40.000Z","published_at":"2013-01-19T21:44:47.000Z","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\u003eDefine a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).\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":2529,"title":"Solving Quadratic Equations (Version 2)","description":"Before attempting this problem, solve version 1:  \u003chttps://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003e.\r\n\r\nIn this version, the discriminant can have any value.  Complete the function so if the discriminant is negative, the function returns values of NaN --- \"Not a Number\" --- for x1 and x2.  Otherwise, the function computes x1 and x2 as before using the formula\r\n\r\n\u003c\u003chttps://dl.dropboxusercontent.com/u/57773343/__IMAGES/QuadraticSolution1.gif\u003e\u003e\r\n","description_html":"\u003cp\u003eBefore attempting this problem, solve version 1:  \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\"\u003ehttps://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eIn this version, the discriminant can have any value.  Complete the function so if the discriminant is negative, the function returns values of NaN --- \"Not a Number\" --- for x1 and x2.  Otherwise, the function computes x1 and x2 as before using the formula\u003c/p\u003e\u003cimg src = \"https://dl.dropboxusercontent.com/u/57773343/__IMAGES/QuadraticSolution1.gif\"\u003e","function_template":"function [x1, x2] = SolveQuadraticEquation(a, b, c)\r\n\r\nend","test_suite":"%%\r\nqe_correct1_1 = -1;\r\nqe_correct1_2 = -2;\r\n[qe_result1_1, qe_result1_2] = SolveQuadraticEquation(1, 3, 2);\r\nassert( (abs(qe_result1_1 - qe_correct1_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result1_2 - qe_correct1_2) \u003c 0.0001) || ...\r\n        (abs(qe_result1_1 - qe_correct1_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result1_2 - qe_correct1_1) \u003c 0.0001) );\r\n%%\r\nqe_correct2_1 = 0.224745;\r\nqe_correct2_2 = -2.22474;\r\n[qe_result2_1, qe_result2_2] = SolveQuadraticEquation(2, 4, -1);\r\nassert( (abs(qe_result2_1 - qe_correct2_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result2_2 - qe_correct2_2) \u003c 0.0001) || ...\r\n        (abs(qe_result2_1 - qe_correct2_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result2_2 - qe_correct2_1) \u003c 0.0001) );\r\n%%\r\nqe_correct3_1 = -1;\r\nqe_correct3_2 = -1;\r\n[qe_result3_1, qe_result3_2] = SolveQuadraticEquation(2, 4, 2);\r\nassert( (abs(qe_result3_1 - qe_correct3_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result3_2 - qe_correct3_2) \u003c 0.0001) || ...\r\n        (abs(qe_result3_1 - qe_correct3_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result3_2 - qe_correct3_1) \u003c 0.0001) );\r\n%%\r\n[qe_result4_1, qe_result4_2] = SolveQuadraticEquation(4, 4, 4);\r\nassert( isnan(qe_result4_1) \u0026\u0026 isnan(qe_result4_2) );\r\n%%\r\n[qe_result5_1, qe_result5_2] = SolveQuadraticEquation(9.1, 12, 4.1);\r\nassert( isnan(qe_result5_1) \u0026\u0026 isnan(qe_result5_2) );\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":24594,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":90,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-08-25T23:26:04.000Z","updated_at":"2026-03-16T12:13:52.000Z","published_at":"2014-08-25T23:42:27.000Z","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\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/media/image1.gif\"}],\"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\u003eBefore attempting this problem, solve version 1: \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=\\\"https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;.\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\u003eIn this version, the discriminant can have any value. Complete the function so if the discriminant is negative, the function returns values of NaN --- \\\"Not a Number\\\" --- for x1 and x2. Otherwise, the function computes x1 and x2 as before using the formula\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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\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\"},{\"partUri\":\"/media/image1.gif\",\"contentType\":\"image/gif\",\"content\":\"data:image/gif;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAC1QTFRFeHh4k5OT9vb2gYGBnJycwMDAt7e3ioqK0tLS7e3t29vb5OTkycnJ////b29vvCMpXwAAAKZJREFUeNq8k0sWwyAIAEXzh3D/41ZrahASklXZ6cxTEAz8EOGFsDvxTyECM0RHgJIwOEIt6VFYX19BAd0kKe8vTpn0vY9uheXoQjGYrICtf9mg3Qgo+kt12fE4sxQwaGFQXCdJmmshaV4EnKYxmgMO/pvJVJ92NrwNbSpnrJafUz1kYbRcjP121ii4EKDVIPnVx+n4hdBzKyhuBM21YLgSLOePAAMAW0UziCh1I3kAAAAASUVORK5CYII=\"}]}"},{"id":49647,"title":"Original coordinate of the min element of a subset of elements","description":null,"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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; 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 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=\"\"\u003eFind the smallest element in a subset (marked by a logical matrix) of the given matrix, return its coordinate in the original matrix. Ignore NaN elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Row,Column] = MinCoordinateOfSubset(OriginalMatrix,SubsetMarker)\r\n  Row=0;\r\n  Column=0;\r\nend","test_suite":"%%\r\nOriginalMatrix= [   60    40   NaN   NaN   NaN   NaN\r\n    20   NaN   NaN    20    80   NaN\r\n   NaN   NaN   100    40   NaN   NaN\r\n   NaN    80   NaN   NaN   NaN   NaN\r\n    20   NaN   NaN   NaN   NaN    40];\r\nSubsetMarker=logical([   0   1   0   0   0   0\r\n   1   0   0   0   0   0\r\n   0   0   0   1   0   0\r\n   0   0   0   0   0   0\r\n   0   0   0   0   0   0]);\r\n[Row,Column]=MinCoordinateOfSubset(OriginalMatrix,SubsetMarker);\r\nassert(Row==2\u0026\u0026Column==1);\r\n%%\r\nOriginalMatrix=[    0.7948    0.9390       NaN    0.1707       NaN    0.4087\r\n    0.6443       NaN    0.4709    0.2277    0.9049    0.5949\r\n    0.3786    0.5502    0.2305       NaN       NaN       NaN\r\n    0.8116       NaN       NaN       NaN       NaN    0.6028\r\n       NaN       NaN       NaN    0.9234       NaN       NaN\r\n    0.3507    0.2077       NaN    0.4302    0.2581    0.2217];\r\nSubsetMarker=logical( [   1   1   0   0   0   0\r\n   1   1   0   1   0   0\r\n   0   0   0   0   1   0\r\n   1   0   1   1   0   1\r\n   1   1   1   1   0   1\r\n   1   0   0   0   0   0]);\r\n[Row,Column]=MinCoordinateOfSubset(OriginalMatrix,SubsetMarker);\r\nassert(Row==2\u0026\u0026Column==4);","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":362068,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":21,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-28T08:28:17.000Z","updated_at":"2026-01-20T14:03:31.000Z","published_at":"2020-12-28T08:28:17.000Z","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 smallest element in a subset (marked by a logical matrix) of the given matrix, return its coordinate in the original matrix. Ignore NaN elements.\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":42671,"title":"unique with nan","description":"input\r\n\r\n x = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8 -2  7 6  -2;\r\n      7  4  8 5  4];\r\n\r\noutput\r\n\r\n y_correct = \r\n [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8 -2  7 6;\r\n  7  4  8 5];","description_html":"\u003cp\u003einput\u003c/p\u003e\u003cpre\u003e x = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8 -2  7 6  -2;\r\n      7  4  8 5  4];\u003c/pre\u003e\u003cp\u003eoutput\u003c/p\u003e\u003cpre\u003e y_correct = \r\n [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8 -2  7 6;\r\n  7  4  8 5];\u003c/pre\u003e","function_template":"function y = unique_with_nan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8  -2 7 6  -2;\r\n      7  4  8 5  4];;\r\ny_correct =  [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8  -2 7 6;\r\n  7  4  8 5];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n\r\n%%\r\nx = [1 0 0 1;NaN 1 0 NaN;NaN 0 1 NaN;0 0 0 0];\r\ny_correct = [1 0 0;NaN 1 0;NaN 0 1;0 0 0];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n\r\n%%\r\nx = [1 0 1 1 1 1 0;0 1 1 1 1 1 0;0 0 NaN NaN NaN NaN 0;0 0 NaN NaN NaN NaN 0;0 0 NaN NaN NaN NaN 0;0 0 0 0 0 0 0;0 0 0 0 0 0 1];\r\ny_correct = [1 0 1 0;0 1 1 0;0 0 NaN 0;0 0 NaN 0;0 0 NaN 0;0 0 0 0;0 0 0 1];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n%%\r\nx = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8  pi 7 6  pi;\r\n      7  eps  8 5  eps];\r\ny_correct =  [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8  pi 7 6;\r\n  7  eps  8 5];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":6,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":"2015-11-03T12:04:01.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-23T20:20:54.000Z","updated_at":"2025-12-07T19:56:45.000Z","published_at":"2015-10-23T20:20:54.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput\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 = [2 NaN 3 5 NaN;\\n      1 NaN 4 9 NaN;\\n      8 -2  7 6  -2;\\n      7  4  8 5  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\u003eoutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y_correct = \\n [2 NaN 3 5;\\n  1 NaN 4 9;\\n  8 -2  7 6;\\n  7  4  8 5];]]\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":42669,"title":"replace nan values iteratively.","description":"replace nan values with the average of two neighbour non-nan value iteratively as follow;\r\n\r\n x = [2; 4; 6; nan; nan; nan; 10];\r\n x = [2; 4; 6;   8; nan; nan; 10];\r\n x = [2; 4; 6;   8;   9; nan; 10];\r\n x = [2; 4; 6;   8;   9; 9.5; 10];   \r\n","description_html":"\u003cp\u003ereplace nan values with the average of two neighbour non-nan value iteratively as follow;\u003c/p\u003e\u003cpre\u003e x = [2; 4; 6; nan; nan; nan; 10];\r\n x = [2; 4; 6;   8; nan; nan; 10];\r\n x = [2; 4; 6;   8;   9; nan; 10];\r\n x = [2; 4; 6;   8;   9; 9.5; 10];   \u003c/pre\u003e","function_template":"function y = replaceNaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [2; 4; 6; nan; nan; nan; 10];\r\ny_correct = [2; 4; 6;   8;   9; 9.5; 10]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [1; 2; 3; 4; nan; 6];\r\ny_correct = [1; 2; 3; 4; 5; 6];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [360; nan; nan; nan; nan; 120];\r\ny_correct = [360; 240; 180; 150; 135; 120];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; 4; 6; nan; nan; nan; 10; 360; nan; nan; nan; nan; 120];\r\ny_correct = [2; 4; 6;   8;   9; 9.5; 10; 360; 240; 180; 150; 135; 120]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; 4; 10; nan; 12; -20; nan; -40];\r\ny_correct = [2; 3; 4; 10; 11; 12; -20; -30; -40]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; nan; 6];\r\ny_correct = [2; 4; 5; 6];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; 8; 10; nan; 12; -20; nan; -40];\r\ny_correct = [2; 5; 8; 10; 11; 12; -20; -30; -40]; \r\nassert(isequal(replaceNaN(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":29,"test_suite_updated_at":"2015-10-21T09:57:01.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-21T08:15:04.000Z","updated_at":"2025-12-30T12:39:26.000Z","published_at":"2015-10-21T08:15:04.000Z","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\u003ereplace nan values with the average of two neighbour non-nan value iteratively as follow;\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 = [2; 4; 6; nan; nan; nan; 10];\\n x = [2; 4; 6;   8; nan; nan; 10];\\n x = [2; 4; 6;   8;   9; nan; 10];\\n x = [2; 4; 6;   8;   9; 9.5; 10];]]\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":3108,"title":"Don't Try, give up and return NaN.","description":"This is another version of \u003chttp://www.mathworks.com/matlabcentral/cody/problems/3107-try-and-catch-simple-example problem 3107.\u003e\r\n\r\nThe goal is to return values of an array _A_ given index _N_, but return _NaN_ for incorrect index.\r\n\r\nExample:\r\n\r\n    \u003e\u003e A = 1:5;\r\n    \u003e\u003e N = [-1 2 6];\r\n    \u003e\u003e values = giveup(A, N)\r\n    values =\r\n       NaN     2     NaN\r\n    \r\n\r\n","description_html":"\u003cp\u003eThis is another version of \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/3107-try-and-catch-simple-example\"\u003eproblem 3107.\u003c/a\u003e\u003c/p\u003e\u003cp\u003eThe goal is to return values of an array \u003ci\u003eA\u003c/i\u003e given index \u003ci\u003eN\u003c/i\u003e, but return \u003ci\u003eNaN\u003c/i\u003e for incorrect index.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e    \u0026gt;\u0026gt; A = 1:5;\r\n    \u0026gt;\u0026gt; N = [-1 2 6];\r\n    \u0026gt;\u0026gt; values = giveup(A, N)\r\n    values =\r\n       NaN     2     NaN\u003c/pre\u003e","function_template":"function values = giveup(A,N)\r\n  values = A(N);\r\nend","test_suite":"A = 1:5;\r\nN = [-1 2 6];\r\nvalues = [NaN 2 NaN];\r\nassert(isequaln(giveup(A,N),values))\r\n%%\r\nA = 10:-2:2;\r\nN = 5:-1:1;\r\ny_correct = 2:2:10;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [1 2 3 4 10];\r\nN = 5;\r\ny_correct = 10;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = 10:-2:2;\r\nN = -1;\r\ny_correct = NaN;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [4 5 6];\r\nN = [6 2];\r\ny_correct = [NaN 5];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = 4:randi([20 30]) ;\r\nN = randi(length(A)+20,1,10);\r\nK = N+3 ; K(K\u003emax(A)) = NaN; \r\ny_correct = K;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [-23 4 56 0 44 11];\r\nN = [7:-1.5:-2];\r\ny_correct = [NaN NaN 0 NaN -23 NaN NaN];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(3);\r\nN = magic(4);\r\ny_correct = [\r\n   NaN     3     4   NaN\r\n     5   NaN   NaN     7\r\n     2     6     9   NaN\r\n     1   NaN   NaN     8];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(3);\r\nN = magic(4)-1;\r\ny_correct = [\r\n   NaN     8     3   NaN\r\n     1   NaN     2     6\r\n     7     9     5   NaN\r\n     4   NaN   NaN   NaN];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(4);\r\nN = magic(3)-1;\r\ny_correct = [\r\n   7   NaN     2\r\n   5     4    11\r\n   9    14    16];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":14358,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":"2015-03-23T11:48:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-03-23T11:29:25.000Z","updated_at":"2025-09-05T19:49:46.000Z","published_at":"2015-03-23T11:29:25.000Z","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\u003eThis is another version of\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/matlabcentral/cody/problems/3107-try-and-catch-simple-example\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 3107.\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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe goal is to return values of an array\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\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e given index\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, but return\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\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e for incorrect index.\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:\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\u003e A = 1:5;\\n    \u003e\u003e N = [-1 2 6];\\n    \u003e\u003e values = giveup(A, N)\\n    values =\\n       NaN     2     NaN]]\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":61140,"title":"Calculating Swimming Stroke Index (SI)","description":"In competitive swimming, speed () is only one part of the equation. High efficiency is defined by moving fast while maintaining a high Distance Per Stroke (DPS). The Stroke Index (SI) is a common metric used by coaches to quantify this efficiency.\r\nYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the glide distance after the wall push-off, as no strokes are taken during that phase.\r\n\r\nWhere:\r\n is the velocity over the entire length (m/s).\r\nDPS is the distance covered per stroke during the swimming phase only.\r\nConstraint:If the glide distance (pushOff) is greater than or equal to the pool length (poolLength), the scenario is physically impossible for this calculation. In such cases, the function must return NaN.\r\nInputs\r\npoolLength: Pool length in meters (e.g., 50).\r\ntime: Time taken to complete the length in seconds.\r\nstrokeCount: Total number of individual arm strokes taken.\r\npushOff: Glide distance (meters) covered before the first stroke begins.\r\nOutput\r\nSI: The Stroke Index rounded to two decimal place","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 483.562px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 241.781px; transform-origin: 408px 241.781px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn competitive swimming, speed (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDistance Per Stroke (DPS)\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. 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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eStroke Index (SI)\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a common metric used by coaches to quantify this efficiency.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for 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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eglide distance\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e after the wall push-off, as no strokes are taken during that phase.\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"82\" height=\"18\" alt=\"SI = v*DPS\" style=\"width: 82px; height: 18px;\"\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhere:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.875px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 20.4375px; transform-origin: 391px 20.4375px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity over the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eentire\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em/s\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eDPS\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance covered per stroke during the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eswimming phase only\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 43px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21.5px; text-align: left; transform-origin: 384px 21.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eConstraint:\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the glide distance (\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is greater than or equal to the pool length (\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eNaN\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInputs\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 83.75px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 41.875px; transform-origin: 391px 41.875px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Pool length in meters (e.g., 50).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003etime\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Time taken to complete the length in seconds.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003estrokeCount\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Total number of individual arm strokes taken.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 20.9375px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 10.4688px; transform-origin: 391px 10.4688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eSI\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: The Stroke Index rounded to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo decimal place\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function SI = calculateStrokeIndex(poolLength, time, strokeCount, pushOff)\r\n  SI = 1;\r\nend","test_suite":"%% Test Case 1:\r\nassert(isequal(calculateStrokeIndex(50, 35, 30, 5), 2.14));\r\n\r\n%% Test Case 2: Short Course Sprint\r\nassert(isequal(calculateStrokeIndex(25, 15, 12, 6), 2.64));\r\n\r\n%% Test Case 3:\r\nresult = calculateStrokeIndex(25, 10, 15, 30);\r\nassert(isnan(result), 'Function should return NaN when glide distance exceeds pool length');\r\n\r\n%% Test Case 4:\r\nresult = calculateStrokeIndex(50, 40, 20, 50);\r\nassert(isnan(result));\r\n\r\n%% Test Case 5:\r\nfor i = 1:5\r\n    L_rand = 50;\r\n    T_rand = 30 + rand*20;\r\n    S_rand = 20 + randi(20);\r\n    G_rand = rand*10;\r\n    \r\n    v = L_rand / T_rand;\r\n    DPS = (L_rand - G_rand) / S_rand;\r\n    expected = round(v * DPS, 2);\r\n    \r\n    assert(abs(calculateStrokeIndex(L_rand, T_rand, S_rand, G_rand) - expected) \u003c 1e-8);\r\nend","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4996329,"edited_by":4996329,"edited_at":"2025-12-18T10:10:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-18T09:56:54.000Z","updated_at":"2026-04-10T15:35:54.000Z","published_at":"2025-12-18T10:03:46.000Z","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\u003eIn competitive swimming, speed (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDistance Per Stroke (DPS)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eStroke Index (SI)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a common metric used by coaches to quantify this efficiency.\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 task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eglide distance\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e after the wall push-off, as no strokes are taken during that phase.\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=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"SI = v*DPS\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$$SI = v \\\\cdot DPS$$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\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\u003eWhere:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity over the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eentire\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em/s\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=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDPS\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance covered per stroke during the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eswimming phase only\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=\\\"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\u003eConstraint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eIf the glide distance (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) is greater than or equal to the pool length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\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=\\\"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\u003eInputs\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Pool length in meters (e.g., 50).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etime\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Time taken to complete the length in seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estrokeCount\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Total number of individual arm strokes taken.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSI\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: The Stroke Index rounded to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etwo decimal place\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":56483,"title":"Cricket - Average Partnership Contribution","description":"The (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-n matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for n innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be NaNs for the partnerships that did not occur. (This means the total team score is the last non-NaN value in each column.) The average across the n sample innings should ignore NaNs.\r\nIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\r\n\r\nx = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\r\nx =\r\n     0    50\r\n    20    80\r\n    30   120\r\n    70   130\r\n    70   140\r\n    80   180\r\n   100   180\r\n   110   200\r\n   140   NaN\r\n   150   NaN\r\n\r\navg = partnershipcontrib(x)\r\navg =\r\n    0.1250\r\n    0.1417\r\n    0.1333\r\n    0.1583\r\n    0.0250\r\n    0.1333\r\n    0.0667\r\n    0.0833\r\n    0.2000\r\n    0.0667","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: 1289.83px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 644.917px; transform-origin: 407px 644.917px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 127.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 63.75px; text-align: left; transform-origin: 384px 63.75px; 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: 365px 8px; transform-origin: 365px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 256.5px 8px; transform-origin: 256.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 28px 8px; transform-origin: 28px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003es for the partnerships that did not occur. (This means the total team score is the last non-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 117.5px 8px; transform-origin: 117.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e value in each column.) The average across 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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 96px 8px; transform-origin: 96px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e sample innings should ignore \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 5.5px 8px; transform-origin: 5.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003es.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 369.5px 8px; transform-origin: 369.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 581.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 290.75px; text-align: left; transform-origin: 384px 290.75px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 969px;height: 576px\" 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/ZFEYefysmfhZ0L+OYVr+f+3xtFV9y4rjnzcNTOfdwoThxtMHPx7f2QOBLsdu1mh0IsJ2Qx3kn9pTxA59ee4RCtH9hPSsmfqnfxjvsD+CofWAJ/AC0P/4DsJ+ysarrs2zUWicthYj8r2xJq2yv+f+vo+fCkXEI5hJNc9Ldqorffsw+e5ac4+AI9DBvFR+sq+k0iQnae9E9GfV0/Yu0ch34iOuW++5RSHvQefW5MEaRlIWq87rNaFDsINHBPmibPB1xRw4muJ+vGcdQ7YX2P51bXvww8x7q95UMfS+GsdZrJ/Iu75r63ozFgAaGfviinpFBCI7jf55kw8tLplyZGVZc95/yFOxOixS+hkT2Dr89pwt2+b9IrhJJ4wb8qGHAoczpXYtu/krum6ex+Dlj3RNOsF9iGVkAUfxvWRfwgPiyvn0oij68pOxXVzkagYNtaju9w69mO5xXLGRAyPM2lUSpLzUxjJdU+LNsfGS7T5zlURjm1lp2IfgKexuqJsL8S9x5G9+oFsr0RXiM03Py7nG3t/W5xwCgGxJzuvSyJEPFF2T2yXT3OHUutyB+EWzjr5WELZvfj15UzM7ye+mv3rll2B3e7dS9yvcq5XjP9Yu3LwgPVCjAWAZnaOmLLztK3dwf0OdYnNwYuOvB3eR41dpFF3b/69hZ19w3XBbOtfTTiRzdA092D7/evuQ2O51n7fsmdhm7oC24MSsuCzkIF/cJ4qWtKIFteNOw+RRPYFkrChnXGIofvu7S613VS75UIaRtS2SrTZhZt9sNl9c0256IRmiuOFAR5EHPAn55K9pxlXdp7n4ejO0Q+q843N23Y74zlyYDqkXmVGdu5v2dba6CDcxWEKOFpc9qXvYXo/6eCQHZHthWv573mY746dLrQGd9kGgGqO7n1kn/DJrsQxdy67a19y5Il4eH9siwfHM+L+7eJry9Olk5bFXiz712DydQor27nHA+t+2Z6RO+9bLntmTlfe+n8+APC3uTzw5cSCM20u3uK6cd8+PmznK2FjPbpLrfcx9HTGdq2ke6fcfCINI1r3tGiz9eB0/00Rb823Ptn2AXgQZ4EbifsPS1irc5xax5ASG68h5uRb53Zbw+T+u2PnQ9tJO8eT7crW606rg3Afh4Ly7rWtoTkdE99xDlhPrRo3W0zPTiHphWI30lMAoMyWXyXsY+7qrImXbT67i8YlR56Ih/cHc5Eitl0vvl47ubTsXy9Q6oUcS8OSsJ2bmXpkc0b27S+27Amkt1gflekLPgoZ91mvy5ELDhProfVzbi2uG9vuA0QpbGxHd9fexdDkjO1iskO7gJCGEa17SrNN9xbuvx7adlWENoDnEEfweWJdh7xsC7Lz6DXRmaJ/recmviX7V0eMd1ei1Hqr9NB6VhoiGlubHYQ72afSq8nX0Ky9hN8lABfbrC98Ddal5nJECeFygJQToJWsSj5mULJTc7ItRdsOFv1+O7y/xxoNZHtFdq/7/yPbaVfis8hmsRfxmGwmrOeebxNvst8vfd/fZtkzUYp8unUA/ihx4MtmLcVwkqQRLa4b2+4jUfFu69FdSrrF0GPQnFmvFk9QLiCkYUTrntIsMcGO9GnWPTWhDeAxrCNbtjf0oR315WFvdKa4sz7fKLjhGiJke8962now/r51Mdytres7CPeyvZs1usdXoM4lQjxNbxOP/ke2t1WR/AtPj6xnpdMOABRZw/eB9RcjhKKvr5fYfLPgyAHNY7OhIl5eNgvLZfEa8RKlXlhBYz03aSD799c83Tew7JlQEtfiMwD8WaKTy2Yt2dgwE49Gj1xdN3E92b9zXS0MlMLGdnR38TUAFsPjuXtpYEjDiNa9tNnaYTWYrUdle9tRYR+A53COBBuJEyzIzoPjyK7VvWS7It+It1fCQDykZQNr3+It8g4akGNbh2SzooNwM9urjCaXTf1VCtIk0yYZuvm1oHWYyeYBOVTqCAAorBme8PPz9Z0mW6Ugv7nxNjkVHDkQD+8vF2+RzHAnlRzP1VI5aRojVLEXcigXNfLnyv79/ZXJaNmjdzPNnAE+gWIcySNnZU47pxEtrqtFomLYWI/uguQaQ2X7hBw8dy8bZXdhROte2iwWk/bxZ8c5suafT/YTleCRyPjV/FCOnLwuusJuxOe8RXOKU75xPnWHHNE99Bw/ytlBvMs5nlR0EO5mk8nHbf1VLsTXnXtL8XgcuvGaSns5ot5NLlPqCQAoRBcs563SKOPH8RqbAxYcORAP76esGPxlc+PUON5s2TpxPFbsRbzOPz9pujoRz02DinR0f1Fl17JHy4Vn5GjGPgB/kuh066fHqohn5bwlHhdfa3FdLRIVw8Z6dBcwjf5lupdG3Lrupc2W7XwMl8PxhHjRqtAG8BRk+KrjNw76U94gO3cOJjvWa0Tvlc0jx2Px/qljxYukRwLnvsXrHLx+Q47G1g0dhNtZlyCXVx0XMEvpdXzdsplwjtfxFukwLy2YxHFCcAdoJMbYokouep92OO/IM/Hw/qbZWHFqXIwpckyaFnsRD058KdNRPJw+snRgf1Fl17InG/qsyAjwByl6ZBbLWU5pRIvrxrb7SFTuZDy6ixnlHDjXvTTo1HUvaRYbZW6f2C/fPu0AwGNYRm85NTi6Uuq60VeSHbJ5RI6JK+ebFi+SdFy2cm54ulhDB+F+4utY3p5s5F78jJyRj7rL8fUiZ9W8EUfzPz8ackzaAkAl0bGKcdRqJIc3t8078kw8vL9e1olPjWWrGAjktuVexMaBVCfnz1WCmrJr2ZMzQJ3ZAf4YMuzbpmrFvY4sx+NVW1xXi0TlsBGP7rLt6MyymSCH5XrKBYS67iXN1EZ7Yv9OHaixD8BTiMNcH77x6PpT+Auyd/Vd2dyuITtq8o24uWztkQM5xzoGEGvV6xRuZKumg/AGxOTL65F/F+1vtjm98Pz4iA2LSFsAqCQ6Vpqz7Ti5aYIc3tzWCPTx8P6m2Qzt1Fi2ishtjV7EKWThlGNqXVxQOqrsWvZkzZpPlQH+LpfSNvOcY3xqcV2tbTlsxKO7eCG3z+XAp9sqFxDqupc0s6Lz2YDqRWfSDgA8hWXwmhyHfXQe8Y3T5oTsKCKt8+6zHMhElM0jly0rNzj5u2wVyd0Y/JFRMMd3cwEzIG3y7yi+cLlKfnzEWxcp9gUAEk4eqGNlT3J883Mj0GvBI3uPY+O4VUQuYvTiHFQOJtC6uKB0VNm17MmbVY4zfcEnEcNNNpRoyDm1aUSL62pty2FDOSq3zz5T7N6ylb98XfeSZsfLa0gDOUO96IwSxwCeQXQDi1MYkb3iPbKx+VJ0liLiMFn3iRfJRbB4fNmy/PnYuqWD8Abi6wsvO78guWG3ObUwVznLlPoCACnRp4u+Y2VPcpFtEjA8XzucvcexcdwqIhcxepHMMPt7589VOqrsWvZkZzo78wf4g8i4zztGiunGmRBR47pa2/L94tGdxkzC34lj2qtcQKjrXtJMiT4nji3yz2dfCWBQZPDaHB0vOue8N26kmUwRcZis++Q9TpDjy8YxXCgcjrd0EN7Afkkk/juN9Rt2m1OL/AlVLlDqCwCkHCaJHFb2JBfZ5hbD87XD2XscG8etInIRoxeB+PjC1jJ/rtJRZdeyx5zpUMnwUcSJPBtLUmw31kNEjetqbcv3i0d3GW8S/k4c017lAkJd95JmSvQ5cWyRfz77SgBjcprJC5z8VPbO3ikOsJu2o7MUEYfJuk/e4wQ5vmwcw4XC4XhLB+ENxGWLMMzM5ZEJu82pRf6EOHyLlPoCACkxJBd9x8qekjTR8HztcPYex8Zxq4hcxOjFwnF2Xeex/LlKR5Vdyx5zpkMlw0exuptsV2C7sR4ialxXa1u+Xzy6y3iT8HciPvOypVxAqOte0kyJPieOLfLPZ18JYExk7NYgZwjROyd3iP/ceXJ0liLiMFn3yXucIMeXjWO4UDgcb+kgOPH9+/WTez9x2SIMov2/c9htTgMiv+ZC/Aa4geiB2WXOgBW3xTs3P8878ox2OOvhx8ZxKzvh7DB6IXzHp5uRnYVzlY4qu5Y92VvXdQ3gryG+0jCVR1+pTSNaXFdrW/bNeHQXgOT22Sc63la5gFDXvaRZtKhsKkgDMWD++dIOADyCKrEonAKJ7P1X9aS8t6Zk3SfvcQvx+LJlZVvH1i0dBA9+5T3L5pk4EudRtv93DrPNaUDk11yskQMAF4iOVQyylvdJ2Nj83Fg81Q5np5hTY9kqxh3B6MXKd5wdJ+J18+cqHVV2LXuy3aztGsDfIsaSKg9eME84xqcW19Xaln0zHt1lvJXhUW6rXECo617SzLr92YD551PiGMATkKFbh5wjRP/5jo5xCDTavgx591kOZC/yHzm+bOX9cyEel03ZqukgeBCHWmbNIw6n+XBNRF2aFOL36SL5NRd7JgCAZg4+ncNar5TDW6DOO/KMdjgbT06NZatmUjB6sWOnk+Me2UzPVTqq7Fr2ZLtZZXaAv8fqatVjX9rXphEtrqu1LYeNeHQXC63kRA6fulcjUtWunJvF22dD4ukq+edLOwDwCJaRawgEaXMe+bL3S4b/8RqyrybfyLvPciDrWKcAIltW7iCbslXTQfDAiLdydInv6pA6Ea+Xy67Poye/imKtrwDABUwXDaiLrBtp2DDcVTucnWJOjRsyuZagEVPHOIPmz1U6oOxa9mS7WRM9Af4gq6fVuPBMYxrR4rpa23LYiEd3mbbRv3iGhMfT5g45YHQvfYplO2/PU//yz6fEMYAHEOfT8tBdQ49sC9E/hKNjNvhEvmm8g2yeib2XTdnK3VIOx9Y47btZDJ6x+HGMxRefyZxn4hm5NnF0xOOxfbrKaV0JAC4Q3Th1uT3SKBPlz25ccuQZ7XA22J8an2aUEkYvjpziWf5cpaPKrmVPrpv5TBngjxM9uDqxi76Y85Z4wQuuq7Uth414dKcxjVQodk82Y2hIW6cH1K4kT3G+wYkYbOLxFvsAPIFl4JpZgbQ6Df3oEILsFQzn2pN3HyPLkqPxHuVbrr2V7YYOggvR4mq8//d4ULaKb0eaZEbHOXwXVjnLd/v6ygw/ACgR47ficjvKreTgLmoUHDmgHc5OMafG5ZT0Z7/b6MUJaSwdyJ+rdFTZtexRp8yJOqsD/EVk8OecY4dM69K8Mo1ocV2tbTlsxKO7vkRvzvRPDq6pi2wmqYwS2dSuJE8RT8yYU9qv122xD8ADMDxgJdNudeDAKbFQvHLHId/Iu090Ob1/0UFjRCjfMn6Jua71oYPgQmYUzaxrGDIXxHdbGpml6ylXyK9ylsdCbj8AFIl+pSd4keiY/8r2gTXIbz5YcOSAdjg7xZwby2aSZAamp/nZLmr04sSxA/lzlY4qu5Y9E9rN48XVZwD426zDf++sGr/iIG1pRIvram3z5wfi0Z3GjN3T+3fu3rpDNleUUKx2JX2KZUemx/Ea69H886VXBngAy7jNLWztkHansb+6SED2rcjuinyj4D7LkYyHyrHtFrKp3nLrq+xo6CD4IAbX3rQcWd9GEn33/C474xqKOnLibLGN7fwq53Yl5dhyIQYDQCsxNTPmF2mlLUatnrk7WHDkgHY4O8WcG8ewoYSUpel6wOjF1ED+/5ljB/LnKh1Vdi17JpRunj+VA/BRROeaKM3aU2xa/rG215wpxoPVVVtcV2ubPz8Qj+46HmOoesrad9nOh9z4ILIZULuSPkVigh3r/df2+edLrwwwPtGj7IEbW55m3s2D02tE51IuvnjSeqDgPusNZHvP6r3rwcIt19yhqvWpg+DD+sYSy65H1uC67klnut+4L3897VB+lXNrnpaz1gvJNgBUEsN3KVudWKN80m63DvueWvJ6w3xXpCPlXoSftJR/zkhj81ylo8quZU+gEPn0jgH8cVYP0NxDmP8spfx7bV9wpvVQi+tqbcthIx7dacxdjp2cE5vvbrrukm0hXmX/iGpX8k+h3H8VyVuH1YvOpFcGGJ8YA+xV59VTjoN/c6BURGROmViPyH1L7rMc0g7Gzk/Inu3CBbGjtDY7CE6IWc+vcwu2u2EkO9JXPwV8icnre0rabK9bdkzkVzl3V8peKB2AAFAk5maay+2RZknDXWDYxeKSI09oh7NTTNJ4dfhsV2S6KPXia16T3d0tGkIeIn+u0lFl17Jn5vxIa1KdPivAR7D68ITqBrNGXnODpjSixXW1tqWwsR3dpaSrQ0+cTpLHmNgdkD3HZ4nXPWS0alfSp9hZ4ZQpr1etCs7KlQFGJ/pfzbg9TfOR0pysuXBg8y1xupL7ZG+w1YZ3IWy95bn15uhaa6uD4MQu4u/i6m7v7k1se/9NQnt8L9v8dhiY6m3WxupL3QbI/vA2DdX4CADsiY5oxdHNj/8je2Z2frz35KIj64fFj1MvThpvXTkstW5diSGq0As5sl1hnVFkO3+u0lFl17Jn4dDNLWApaSrAZ7B5wcQhfQicvXHn83Ya0eK6WttC2JiIR9U8aOJw1nZkHxvWvbvAsGW0smNG7YoSbXbm3H8NcRdrdpdtsQ/A8MRRfo4iGnHwH9wsu3tmPWblG0X3WY5NHL8nvPPQ3c23Wx4utvdntbXRQfBi/yJ+vr5+f7/Xv7YdOIzE3YGp6bwrCur1xRxOXr6uvNRxhP0wiFOF/lbl4MQ60PZdYygAtBJDqek9O09bf1FeHDke2mJD2ZHVw3KRdIpJG2/hf73lfh1vvUShF2tzCSXr9npB2U7PVTqq7Fr2RNZfmtz3czMXwKexpXYzPzGo/O5dZMsEd+HHSiNaXFdrWwgbE/FojIET+w5PnMPjjOxakH0T0naXxxyigtoVJdocrCmmPNhxf4UW+wCMThzPmsJNiZ52mn3FWdShr8zZar5RdJ+dh6oBIiC7J7Z4sImdeM94THZP1HYQ3Ni9oJSTwfNt46s1rne8YBxJ28l7jvPqz4T8c0Y/BwAKxGBqus/J+/7deV88tE08ZUdWD8vl0oiuND44/jkQbFco9UIOBQ7ny+HCuUpHlV3Lnn+29PdgsUD6pACfw/fRHXSk7US59d6ZWlxXa1sKG9vRncaMMTQeUpz9qEh3GeyZY1RQu5I+xcR2b5W651OvDDA00dPqhu3qKLItyG7ZOnHw5Xy+UXafo9PvI8RPPCQtA8db7MOJ3TrbQfDjYOIjicGzbXfTQuF6pwuWV3G3RSOFzCkAUGDN8GQ7T9b7vldJKC2rHXl/WKJEGtILjTV2Fyj1IvM0a9P8uUpHlV3Lnskkua6mDwrwURS8OCItA6XWB2dqcV2tbSlsbEd3GnNNW7NS9Xyp/LMcW6pdSZ8iEJuqHM7PP59+ZYCRWQZtTuEmSOtdtjIzj/3cyM/76/4Uw31yF/nZAsgOn9YTePM9ZE1+GliBXNv9QmX+FZ7eYH6VcyE7C2XPAIACMeRWOFDG+6Yz5V9vqyUXQsr+/GIv1KfZzs6fq3RU2bXsCSbRu5o+J8CHYZeTpeFMvvHRmVpcV2tbDBvr0Z3G3NLWePBEticJp5ZqV9KnmMncO3C8av75MlcGGJfoSrWjNnrrSVXPXiH/Tsn56+GulvvoF5maa7rXpfVErVmglYzJ08XHicxMd2ibC+DnC5ZXcScyC6aMBIBLxJCbdbkdxx+PEMKJ8s/31ZLrQlS5F0os2d08f67SUWXXsmc2idZVIhbAFH4yfrxwWpWvTCNaXFdrWxc2dhpzl7bGowe0C+nPfW6pdkWJNgsZW54b5p8ve2WAUVnGbM5dFaT9eZVoGvyFgZ/xrTrHjKwCfUdorepe9ZZtrSeqrQLNaNL3NGVtaO/+PARz4+NIfpVzRbnQ+tM4ANBG9KeCy+1IvG/5aQnZ2PzQcGTtcHaKyVxLDVHHNlYvzlfYzyj5c5WOKruWPYtJ0pjF3AUwk9fJipNUpREtrqu1LYeNeHTXu9ir8O80LKURbUZ5lOOv3wbUrijRRlArFokZW+wDMDbRj+oH7ep5si1MbiH/UqnIN2z3SS9ySBDmNhtpaJx9OdO6ooPgzNnmRSV6fp1f9gSnStvyKq5QcyEAqCF6U9HlNr4P3hd9TzY3TzQcWTssISSdYrLXSkLUuYUZTmK+OHO8c/5cpaPKrmVPNMkxZhGxADYUofyjpRCBitm/xXW1tuWwEY/u8s/Yp2XrGJZ+Ms9xDqUNj6JEmxUzJk602AdgbJYh2zKpxvF/doAfY9ybvlXjPqfosOw8BpAdx8h4SiaWrR01zg/OfH0tv5X28/Vrm1vahta5xt/TBZcmLyrb6ULzdaZ7vXYhAGgk/mW4EZanYkT55+vijCCh5NWIlDL3ajd3x/h4taMAf5gpqGwJRNlF3NKI29gipNHB9Y9sej5KTNsKmRgAnKlROa/mGxPxT+tW+vyaOKw3zKrkCY8OAgAA3MwyV1E2BgAAABdKKhkAAOAByEyGSgYAAAAPUMkAAPBwZCZDJQMAAIAH8eumsgkAAPA0lpkMlQwAAACVfP/7MyObJ1DJAADwcJaZDJUMAAAAlfy7JA8ZHRx/n0s2AQAAnsYykzGVAQAAQCXlbx7LQVILAAB4KkxlAAAA0ERRJX/LQf7SEwAAPBWZylDJAAAAUEcUwmr28CsHZRMAAOBxyFSGSgYAAIBKJHtQv5gsX0tGJQMAwGORqQyVDAAAAJVEJaykD8U6MwAAwBNgLgMAAIA24heT//mVHRvy+9d8LRkAAJ6LzGWoZAAAAKglFpMTmbwekG0AAIDnIXMZKhkAAABqWYvJxwzidxXJlJIBAOC5yGSGSgYAAIBqVjn8z8+aQ/xu2ln9XS8AAIBnILMZKhkAAADqkQRi4Scg/56hlAwAAA9GZjNUMgAAANQTf8taJf1RLwAAgOcg0xkqGQAAABr4lRRCgUoyAAA8GpnPUMkAAADQxOEz1juoJAMAwLORCQ2VDAAAAG18aTr5h0oyAAA8HJnSUMkAAADQSqKTv9DIAADweOKkJpsAAAAADXx9yc9b/3whkQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC7zz8T/+3///r9/p//4P+v/+X+zXQ67+D/T/wlm+VeGDoDCf09D5L8LQ+hT/8/sOpljH/x/5uEiQwdAIbjOfx8GDf/n2v9ZYnPuKP+n/v8ES/4/GZ8ACrOz5UcQ/6f6/0yG7Ko6/k/oAEAD5LRQQEYJQC1EFCggowRgKAhbUEBGCbjQ09lQydAKkwMUkFECUI0MHQAFGSQAYyHjE0BBBgm4gEqGJ4FKhgIySgCqkaEDoCCDBGAoSISggIwScKGrs80d+BdOLN8ihDPBLHwdBwqEIUJESZBfOoAT83CRoQOgEL7gx2TsQTAklvQgGJKwBQXmISLDBV4hWLKn6phryf+RDVj5Cnb5P7IBKyHX/5F/AyiEnPZ/5N+w8v+FiPItG7DyM5mF3wOEAkw6XoR8E0t6gCXBIIQtEiEPuk8A0/1RySmzSv7/yQaskLCAASpZBZWsE9JNPp0CBcIQYSHFgzB9Y0kPGJNgQK7sRW9LUkvWQSXr4PlgEDwHlZyAStYh3QQDJh0vqIB6wXoDGIRyAc7mQfcJYLo/KjkFlayD54MBtWSVWSX/ygashE9cU0uGAiykeIG284IxCQYs7nnRW3VQS9ZBJevg+WCASlb5vyGiUEtOIN0EAyYdL3A2LxiTYEAi5EV3Z5vuj0pOQSXrMDmAAZODCrVknZC4U0uGAmg7L8L0jSU9YEyCAbmyF70tSS1ZB5WsgwQCA4aICt9L1iHdBAPSTS+Cs2FJDxiTYMAQ8aJ7SjndH5WcgkrWwfPBAJWsQi1Zh+8lgwELKV6E6RtLesCYBANyZS96W5Jasg4qWQfPB4PgOajkBL6XrEO6CQZMOl5QS/aC9QYwCOUCnM2D7hPAdH9UcgoqWYeEBQyoJatQS9ahlgwGLKR4gbbzgjEJBuTKXvS2JLVkHVSyDutjYIBKVuF7yTqkm2CAtvMCZ/MCCQQGJEJedFcd0/1RySmoZB0mBzBgclChlqwTEndqyVAAbecF6w1eMCbBgFzZi96WpJasg0rWwfPBAJWswveSdUg3wYBJx4vgbFjSA9YbwICw5UV3S073RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdoOy8Yk2DQ/XPCf4beqoNasg4qWQfPB4PgOajkBL6XrEO6CQYszXqBs3nBmAQDhogX3VXHdH9UcgoqWQfPBwNqySrUknVC4k4tGQqg7bwI0zeW9IAxCQbkyl70tiS1ZB1Usg6eDwaoZBW+l6xDugkGTDpeBGfDkh4wJsGARMiL7s423R+VnIJK1mFyAAMmBxVqyTp8LxkMWEjxIkzfWNIDxiQYkCt70duS1JJ1UMk63b8hAKODSlahlqxDugkGaDsvqCV7wZgEA3JlL7pbcro/KjkFlazD+hgYoJJVqCXrUEsGAxZSvEDbecGYBANyZS96W5Jasg4qWQfPB4PgOajkBH7jWod0EwyYdLzA2bxgTIIBQ8SL7pac7o9KTkEl6+D5YEAtWYVask5I3KklQwG0nRdh+saSHjAmwYBPXHvRW3VQS9ZBJevg+WCASlbhe8k6pJtgwNKsF8HZsKQHrDeAAWHLi+6qY7o/KjkFlayD54MBKlmFWrIO30sGAxZSvEDbecGYBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vECZ/OCMQkGJEJedHe26f6o5BRUsg6TAxgwOahQS9YJiTu1ZCiAtvMiTN9Y0gPGJBiQK3vR25LUknVQyTrdvyEAoxM8B5WcwG9c65BuggHazovgbEzfHiCBwIBc2Yvulpzuj0pOQSXrMDmAAbVkFWrJOnwvGQxYSPGC9QYvGJNgQK7sRW9LUkvWQSXr4PlggEpW4XvJOqSbYMCk4wW1ZC9YbwADwpYX3S053R+VnIJK1sHzwQCVrEItWYdaMhiwkOIF2s4LxiQY8IlrL3qrDmrJOqhkHTwfDFDJKtSSdUg3wYClWS9wNi8Yk2DAEPGiu+qY7o9KTkEl6+D5YIBKVqGWrBMSd2rJUABt50WYvrGkB4xJMCBX9qK3Jakl66CSdfB8MAieg0pO4DeudUg3wYBJx4vgbFjSA9YbwIBygRfdJ4Dp/qjkFFSyDgkLGDA5qFBL1uF7yWDAQooXaDsvGJNgQK7sRW9LUkvWQSXrdP+GAIwOKlmF7yXrkG6CAdrOC5zNCyQQGJAre9HdktP9UckpqGQdJgcwQCWrUEvWCYk7tWQogLbzgvUGLxiTYECu7EVvS1JL1kEl6+D5YIBKVqGWrEO6CQZMOl4EZ8OSHjAmwYAh4kV3S073RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdh+saSHjAmwYBPXHvRW3VQS9ZBJevg+WAQPAeVnMBvXOuQboIBS7NeUEv2gvUGMCBsedFddUz3RyWnoJJ18HwwoJasQi1Zh1oyGLCQ4gXazgvGJBiQK3vR25LUknVQyTp4PhigklX4XrIO6SYYMOl4gbN5wZgEAxIhL7o723R/VHIKKlmHyQEMmBxUqCXrhMSdWjIUQNt5EaZvLOkBYxIMyJW96G1Jask6qGSd7t8QgNFBJatQS9Yh3QQDtJ0XwdmYvj1gTIIBubIX3S053R+VnIJK1mF9DAxQySrUknX4XjIYsJDiBdrOC8YkGJAre9HbktSSdVDJOng+GATPQSUn8BvXOqSbYMCk4wXO5gVjEgwYIl50t+R0f1RyCipZB88HA2rJKtSSdULiTi0ZCqDtvAjTN5b0gDEJBnzi2oveqoNasg4qWQfPBwNUsgrfS9Yh3QQDlma9CM6GJT1gTIIBQ8SL7qpjuj8qOQWVrIPngwEqWYVasg7fSwYDFlK8CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GqGQVask6pJtgwKTjBbVkL1hvAAMSIS+6TwDT/S+o5K+fUAL455+vrz9aHXmPSv7+Wsz48/Ule0aHhAUMrk0Ov6sr/NE1u/fUkjczPiWiUEsGg2sLKc+bXO/nmrbzsmTMGn++fh+/XMjiHhhcy5U7ha31tj9f4/lmb9VxpZYs9oz8yfrINZU8n6WhveLfY+tnaM/u3xCA0QmDuVElP9IVGrn2G9d/P6KQboLBBW33CRHlAheczcuS50hmh0JpmDJCxkm5AAwu5Mo+znbUZxVi+/d4RsV9z968cotPdFcd4cmaVPL3yaJT//9gPXkeBc0qOTFNRHnF6Th7wpI3kwMYtNeSU1f4g/Xka7Xkvx9RQuJOLRkKtGu7Z7rC/bSvNzhZUotjxoW+pVnKCPkmi3tg0J4r+zjb6SrmJTRH+zFWolryktfprTqaa8npi5z4e+Xk+TGbVfJsDI3kFadrDRM9B0IlqGQwaFXJ54XMmb83xq59L3k2hkZioKeakXQTDFonnQ+JKBcIztZiCKc0JSd4i+FQzTRnRqklE7agQGvY8tIEcmbEUsnaXSfKN5ZGKRf6a9NddYQna1DJl0z6QC6p5HxcP9vn0rQxAqhkMGhUyb/zwE/5ax9QuVRLfj2iDG/GMKNQS4YCjQspj51c76dR2zlZMpM0TpSikzRRoJYMD6Dxc8JeYevsbWWVnLtruev1eYkLvVVHYy05G+96PsMd3KuSc8pg/Jm8+zcEYHTaVHLeFf6YTL5US/6AiEK6CQZtSdJzXeF+2pzNyZJ5kVx8rdJCYYT3SLkADPqErUT2FlVy/q4T+Ru/WSV3Vx3hyapV8j7e/UzIPwN/LGJcUsn56eBoncNAPtlxcG3A5AAGTSr5EKWf5QqNXKolf0BECYk7tWQo0KTtHuwK9xOm73dbMh/DAtlkIsn2N0Z4jSzugUFTruwWthJ3K6nkgpMFsjfO+/Qt4qC36miqJW8p7Y+YfvdR+r+1UHtJJc92UDm+4hBhF+Kvrm9rMz0HQwWoZDAIo7haJW/x43Gu0Mil37ie7aDyZyIK6SYYNGm7B7vC/QTjVBvBx5L7RHxJG78Pv+SbC4n7Nidao+gdkAiBQVO5wCtspfq1pJK3u8b7xr8INZO9sRxXuMUnujtbeLL/lX8bbPFuF6a2nX9qoXYeoo0qOQ5r2cyyDsP9i1d3jgefuAaDlsnhya7QyJVa8idElNBNaslQIORytSr5gyLKBVrWG5wsKe0ndqd87zRwJibK0eLnRTvSMibhI2nRdneELTm54EE7L9xJup1Ozty4Ni/xordKbqklrwsPh7W8tcDc8zHcmcdBo0qWwWXZIWOwdWgerDsaLKGCQYNKtlzhLy28XfleslNEGdqMpJtg0DDpPHpyvZ/gbO+15Nr+dMJWXdH7E28/6gtrWW+Aj6ShonRL2JJz8yp5veu5mzmnjcjxyod7ne61ufC0dSp5XXg4JV1rvPtLOe0VlTwbwV79lGbJa49Dc+jYi0oGgwaVPI/3iZwr/KWRdqWWPBvh9YgytBlDJ6klQ4GGhZR5vE/kXOHDhU2Dtlvs9bIlpXUa+rYv66lB8d3lqlZY3AODhlx5HuoTrmFLzs1nD6uiS3q5HtFvLAetvMSN3qqjoZYc31iyvLAuScj2X+CCSq6M69Fa6VuPBn7b4LtAy8dp4SOpHyLPdoVGLtSSPyKikG6CQX2S9FER5QL1zuZkyTXdTiNfvIMe3+TQsK+LcgEY9A5b5qnSQOtkvK96dmVe4kd3ZwtPW6WSo2kKJv1DxeT5adtUsljBeptLK23aiEX5ruPBgMkBDOpV8jzaJ57pCo1cqCV/REQJiTu1ZChQr+3m0T7xERHlAmH6fqslpa2abMcLaVExHktvPwgs7oFB/eeE56E+4Ru25NSsSl5XsGT7QNR02o0r8xI/equO+lpyNJts7lnDnWz/AS6o5NkC5qpPXDbSmkUTG5foCSoZDMIIrlLJD3eFRi78xvVsgb8eUUg3waBa231WRLlAcLaq6dvJkoXSykThQvFE2RyP+vUG+FCqc+WbwpZ1phzXk5KSppMjF7p0kfr1hpsIj1ujkmPYUk0TD/6dYnK7So7Dyhg70koP/3JsYBmKSgaD6lryPNYnZPOIHPs7iUh7LfkzIkpIA6glQ4HqhZR5rE/I5hE59tGzV7W2W2z1siXLOX6hUBZPlM3xYHEPDKpz5XmkT8jmETl2IWzJmbn0wahtRg9MU5bKvMSR3qqjupZcDlty8H12u5t2lVy3+llaNqq9Rk+6r+rA6NSq5Ke7QiPt30v+jIhCugkGtUnSh0WUC9Q6m5clDbErR5XDckC//whQLgCD3omQnJjzofJt1/umh98fSLs7W3jcmr+XHNpNZPr652ag+YGaVLJMCMbLjIbKpMtylMkBHkvt5PB0V2ikvZb8GRElJO7UkqFArbb7sIhygTB9v9OS0jAXwuJtZHMjZvDjfjiRxT0wqM2V7wpbxonGbfOn1+UlnvRWHbW1ZMOksQifs/jjmJ+3SSXPz28OZmmVe+XvH4CNoJLBoFYlzyP9wa7QSHsteX7+Px9RSDfBoHbSmUf650SUCwRne6MljXLVejwJi1n5PAwkQmBQ+7nLeaS/7mwJy3lZ55PrZn0se99lv5WXeFJrydsIz1uhkq1XtRx+p+XupVkl18V1azVh+Nmh+3iF0alUyY93hUaaa8kfElHCzEItGQpULqR8WkS5QNB2b7Tk99dC7jrxPklYlP0Dp5Ms7oFB5ULKbWFLzss5kfhm1sdykq9DGO29JFVbSw7NJrJd/Wsz0Pw8LSrZWkZYiGbKZstyfNjpgSVUMAjjt0Il/ye0m3isKzTS/BvXdRHl8WYk3QSDSm33+Mn1fiprye+yZK6WnK0xj0PlmITPpTJXvs3Zrp4n5PKPurzEle6qIzywrZLjekfW4tlVwYfSrJLnpzeHpIyw/GJChyHYBCoZDCpryY93hUaaa8nz0//9iBL6Ry0ZClQupHxaRLlApbZ7lyWjQJDNldz+gWBxDwwqP3d5m7Mtp11WybnTc/tvpLfqqKwl22FLGrzTdnfSqpKjgb6+vn5+fr6+fvV8OLaSzZTR5wc+cQ0GlSp5HuZPdoVGWr+X/CkRhXQTDCqTpHmYf1BEuUClsy1mut+SucvI7inqSeyT/QNBuQAMeoctOS1/4TKZ02Nvom9+v8E5u6uO8MC2SraXM5YGl1/JaMxjoUElxwWhHUpst76C4Db93AaTAxjUqeTnu0IjrbXkT4koIXGnlgwF6rTdx0WUC4TpeyBLZtLKeP8dP6MllizugUFdrnyfs8lpFz0n9uucc2h5Sb7vPvRWHZW1ZFsl/7EZaH6c11SyktVWfN9GWoy62oBKBoM6lfx8V2iktZb8KRGFdBMM6iadj4soFwjONo4lY8547lG8/4HBdHLdegN8ML0ToYunCXJ20i89Lyn03oHuqiM8o/33kkOriYLBP1wlz8+eckpqK4wkLcaaEjZQyWBQNzk83xUaaa0lz8+e8uciSph1qSVDgbqFlI+LKBeo03bvsmRMuM9Xifc/MVTeweIeGNTlyvc528XTFtbPc8j2iuw+05DZtNP7E9d1teSK9Y6KJk9iHrv1KjkT18/vVqaF0guvaNKT3uMVhicMX1slP98VGmn8jeuPiSikm2BQp+0+LqJcoM7Z3mTJtWQs2yuyO+XWVLwNygVgUJcr3+dsy1kXVXKIFNrZlXmJL92dLTygqZIr1jtyH2N/KI0qWcaxwmFOkn2lcesx/dwIkwMY1NWS51H+aFdopLGW/DERJUzH1JKhQJ22m0f5J0WUC9StNyxWut2SMcSdL6J+4HphnOySxT0wqMuV53F9i7MtZxWvnGUtJZ89Ljptyo1RtbfqqKslV6jkl97JeDSq5PnRdfZvV3aVbFRj6o6gksHATSUP7gqNNH4veX5ynb8VUUg3wcAt3fxbEeUCwdlGseSab8v2Sry2xjAfVSQRAoPeYUvOKl05x7pQlZws+zXuc4e6lPJGwuOhkhPmJ65WyWKfn+VL7L/fhzi/Gzyy5+bp5074xDUYoJJV2mrJnxNRQrJMLRkKuNWS/1ZEuUBI3Aex5JqIJ+mE7P/6nWPf99ehfDVKNZnFPTCoy5XnUX2Ls8lZpSvnWF3uvColXTHzEl96L0nV1ZLFaMWOLk0uvZMBmd9+tUqe7XOwzvqJhYnVJDXf3X59+rkVllDBoEol/wFXaKStlvw5EYV0EwyqJp3PiygXqHK2t1gy3iS9xHLkcPO9TpZdvalbb4APpnfYkrMuKLLV35JzK/MSZ7qrjvBw5m9ci9WKHa1p8xzmgVmtksNzn4d5HNoTcf2z5rvbNW06gkoGgyqV/AdcoZG2WvLU9kMiSpg3qCVDgSpt93kR5QJV2u4tlswn4iHMnXd+r81HyT5Y3AODqlz5RmeTs9qla34Fy8pLSlr/BXqrDr9a8ger5Kmx8thxbG8Ha9aNatp0hE9cg0EYvS615MFdoZGm37j+oIhCugkGVdru8yLKBYKzmdP3Oyy5qt60N9NO5aqbTB5jiYNyARi4fajuorPJWc0qOd5OuWFtXuJMd9URng2VnNCoktWn3gaPBPaaNaGaNh1hcgADaskqTbXkD4ooIXGnlgwFqCV7UbXe8AZLFkTylJGqFy2d0gEW98CgKle+0dnkrFaVHO+m3a82L3Gmt+qglqzTpJJ/MwNxXZQRo9y4bvQuUMlg0HsJdVCavpf8QRGFdBMMqiadz4soFxiklhzPVs9ffhgoZZXJQ7y9qvUG+GSqKqA3Opuc1aqSQ4yYUfpem5c40111hEdDJSc0qeQs6xrLssRy47rRu0AlgwG1ZJXGv5ec4e9FlDBvUEuGAtSSvajSdrdbMp7ceHqUyUOIUxb3wKAqV77R2eSsRpW8LkY1pfmrS9+yhNX7E9d+fy8ZlawQh5yM1OOWymuLtLfTe7zC8FSp5D/gCo00/r3kHH8uopBugkHd0uw8yD8polygztkWI91nSTm3fIeUNROX7a5QLgCD3mFLzmpzsij1Wr3slJf40t3ZwpOZv3Fdo5KlyS1Wej9OKvkU2GWjZKMaU3eEyQEM3FTy4K7QiE8t+e9FlJC4U0uGAm7a7m9FlAuE6bu7Ja9VqyZuzcQbYXEPDOoqSvOIvsXZ5Kwmb4mCvFmS37qE1Vt1+NWSpckIEcyB+YlfV8nRKmI52bhr+nkDqGQwCKMXlZzQ9BvXBWaTTBy2HmxG0k0wGELb/QmCs/VM3AOXRfJ601LH3gWJEBjUDZF5RN/ibHJWi7dcFsnr3W6Jrd0/wRoezFTJcaGgVAqRJiNEMAfmgemgko+Wkwmi9MIHn8j5xDUY1NWSn+8KjTjVkv9cRAlPQC0ZCtQtpHxcRLlA3XrDrZaMZ145t6Jj74LFPTCoU8n3OZuc1aLI5JQrMq5GI16l95JUXS254oPxL31RZTzmgemgkqNZllFX4REDTQQaLKGCgZtKHtwVGnH6XvKfiyikm2Dglm7+rYhyAbf1hsuWfKFatd51hFWOuvUG+GB6J0LLWS2CN/rXlQh5zEt86a46woOZKrnC4H9smdZLJR8tV2EkaXHHWPMAlQwGdZPD812hEa9a8l+LKGFmppYMBeq03cdFlAvUabsbLbl+ffFSKKzo2LtgcQ8M6nLl+5yt+bRXRPKtwbW36qirJVdY4OJ6x6jMY9dDJR/sYnvE6CV5PnENBl4qeXRXaMSrlvzXIgrpJhh4pZt/LKJcIDhbV0uGDsxcSiKixh7gBVIuAIO6XPk+Z5PTqmVrvM9F/7pRAXZXHeHBzN+4rniVqGSdo12WjcLAvfPT/R4wOYBBnUp+vis04lZL/mMRJeTN1JKhQOVCyjzMPyiiXCBM3z0tKbHrag4x0AtkcQ8MKnPleUTf4WxyWv7CRzaRfM29blSAvVVHZS05quT8IoM0qH0lo3OvSs6/cXs5oi+oZDAIw7deJT/XFRrx+o3rvxZRSDfBoE3bfUxEuUDbeoO7JeNpV1/BQB8GqByT8Lm0qWT/sCWn1UoyaX5Zw/1hlTzbxlbJ5nLGX5uA5ufxV8nmSFqOj7vYgEoGg8pa8uNdoZGbasmPN2N4AGrJUKBS231aRLlApba7yZIvfqSTWjI8icrPCd8WttrOk25UdVnFfI7r9P7EdWUt2bR4tLFsPh43lTxbZTWctZgQ55Fmj3gX3b8hAKNTqZIf7wqNuH0vebbK34kopJtgULk0+2kR5QLB2bpZMp51PQxa/XojlAvAoHfYajovRIaZy4Nazr8junZ3tvBgFSrZepVy+M/Ejfl5/VWyNZSimQdYLNVhcgCDSpX8eFdo5J7fuH6+GcP0TC0ZCtQupMwD/XMiygXC9N3Nki9Xq9b7ymZPWNwDg9pceR7SN4QtOS933QPxUxovLOTL+VW3a6S36qitJccFjYwN45u8w0RdmB/IQSVHw0S7GR9LWI4OMQ3ooJLBoFYlP90VGvGqJf+1iEK6CQa1k86HRZQLBGfrZUm5Zl0HdF6+gB8kQmDQOxGS82o02esf80jyEk+6f4I1PJj9G9eryTP5TIyAsvl8vFTy2TBxLOkLQ3FFZ9zFhu7jFUandnJ4uis04lVL/msRJTwPtWQoULuQ8mER5QJB23WyZIxbL6QPlz97egMs7oFB7ULKXWGr/sRNJF9PUO6UgL2XpGpryeur1JcK5ODf0U/z49ap5N/CMIzDbzNMsmPPf+ToHesxPrCECgZhANeo5Ke7QiMNv3H9URGFdBMMarXdh0WUC1Q722IqR0vWVqtKvYuJ+AhvsHpMwqdSXVGaB7V/2JITK1Ry5QpWW17iSHfVEZ6sRiUXlzRGCl8+1Kvk6dnzCzDRMJvV4h7ZPBBt3HVAlEElg0FtLfnprtBIfS35syJK6D61ZChQre0+K6JcoFrbeVuyslo1NctfNd5X7dS7YXEPDKpz5ZvClpxpq+R4f+MmU7OWvMSR3qqjupYcba4Z6tZ1hD5Uq+QwOrLPHQvwu/Efd2nnhMgbGHixgU9cg0G1Sn64KzRS/b3kD4sopJtgUJ0kfVZEuUAwQhdLyilGFj0nktlMfD5/4pZEvBXKBWDQO2zJmaa7rDlFefmpNS9xpLvqCE9WpZILixq3riP0YX7rFSp5efTMG1wXUPfHo7HSyWCotdIMTA5gUK2SH+4KjdTWkj8tooQ0gFoyFAhDpG4h5aMiygXC9N3DkvFq5dxBolsmSK7XqAii91M/JuFDqdd294QtOdNSZWtOUVbiSx9b8hI/equO+lpyfimvtBTyVCpVchze6qNvw092zORXXWT/0KvdqGQwqFfJz3aFRipryR8XUUg3waB+0vmoiHKBemdztWS47UzxLa7RTZXB6zXGqMXUrzfAh9I7bMmphr80ieSmvMSP7qojPFrNb1zvljVOQWw10V+agOZxa6rkbXQo73C11+lgbrwVx+EooJLBoF4lP9sVGqmrJW8RRUnB/mRECZ2klgwFGhZSPimiXKBB2zlachUB5SQ6XlkNk9vBMdJMFvfAoCFXdnS2DTnXUMnSymh3KS9xo/cnrhtqyVugOgSxNQT2fAx36lTyLnb/nCP7NjWcDLOOqcP+3/VSQy829B6vMDxhDFeq5Ee7QiOVv3FdiCjx1y7/VkQh3QSDBm33SRHlAsHZKqfvdkt+Tcg/D2wZdtn6W7skY99uO8obpFwABg3lAj9n2yHnlputtzAG8+aA9XmJG92dLTxcpUpeX+W+x5v1ZMffoFIlbyY5jZ6vzS7JEN8ObWdsM4Q19vvC5AAGDZPDo12hkcrvJX9cRAmJO7VkKNCykPJBEeUCDesNzZZc2qcRrt76uwh3yEl/t4rDMMkHi3tg0JIreznbnrmJ4XXbfWVHjkt5iRe9VUdLLXn32v75mg31FWKFMMganxOVKnlvkonFKgezaIbZxtXPPIRHnAUyoJLBoEUlP9kVGqn9jetPiyikm2DQNOl8TkS5QJOztVkyRqgkc98ukyWec2i63PRw14HeIIkQGDR97tLJ2fZIm8WNdI7Jhkq8+aW8xInun2ANT1erknefIk74YxFjftIKlXxYY1HRBrIc0hh8saH7eIXRaVLJD3aFRqr/XvKHRZSQHlBLhgJtCynzoNf5WxHlAkHb3WPJNTU8J+UVInmLaFbjcVKPtjEJH0jbQso8vnXqne2A3aZCJG9PcCkv8aH3klRTLbkQxf6acqpWydZIUyfm/IAbfR5nCRUM2lTyc12hkeq/l/xhEYV0EwzaJp2PiSgXCM52jyW3zFB2CIdiU47tcmWZPFDm0bbeAB/IfWEr52xHpEleJdeI5N0TXMlLfOiuOsLz1f3G9Uwmig0UvnyoV8mF4T3ZJbO+kjvnvuUYJ1DJYNCmkp/rCo1U15I/LKKEGYVaMhRoXEj5lIhygUZt12DJTOJeCmUbu+uVZHKxcvZmWNwDg8bPXb7ubCekSd5rSr62snuCkjPn8hIXequOxlpyxlJ/b5G2QSXvPgBxphDWtRH6APnJJ67BIIzkBpX8WFdopPI3rhc+KKKQboJBo7b7lIhygbZa8kS1JdeIdThaVa06hsVv7ZaBn6GyTMoFYNA8RF50tjPSJpsy5BztyOEWV/ISB7qrjvCILSpZiWK3LiN0Yh4OtSr5v77V0VN+r+kp9440H5gcwKCxljzxTFdopKGWPPE5ESUk7tSSoUD7QspHRJQLNK83VFtyrZ4cDtcl4qewuP/V3I3BKjEs7oFBe678mrOdMdpUrmAdn+BKXvI6vVVHcy154qiT5acI/xjzYKhWycroqTDL8ZSvRxTkUclg0K6Sn+kKjdR/L3nhUyIK6SYYXJl0PiCiXOCKs1VaUpLuw3uqFMlJWEx08njvr329AT6MGxMhzdkSljY5lVwpkpN7XMlLXqW76gjP2aiSg6WWOPbzNyXyxDwUGlTyRDRKsEqlWaYzFjs+ZhZHJYPBlcnhia7QSFsteeYjIkroLrVkKHBtIeXPR5QLXNN2dZYM6bNfPhjvOV1yyPfH4h4YXMuVezhbIxfyktfo/YnrK7XkT+CCSv4Ieo9XGJ5rKvnP01pL/hRIN8GApVkvgrNhSQ8Yk2BAruxFd2eb7t/yG9efAipZh8kBDFDJKhdqyR9BSNypJUMBFlK8CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GwXNQyQlNv3H9QZBuggHazguczQsSITBgiHjRvSo/3R+VnIJK1uFTJGBALVmFWrJO+IYTtWQogLbzgvUGLxiTYECu7EXv9QZqyTqoZB3Wx8AAlazC95J1SDfBgEnHi+BsWNID1hvAgLDlRXdLTvdHJaegknXwfDBAJatQS9ahlgwGLKR4gbbzgjEJBuTKXvS2JLVkHVSyDp8iAQNUsgq1ZB3STTAg3fQCZ/OCMQkGJEJedFcd0/35jesUVLIOkwMYMDmoUEvWCYk7tWQogLbzIkzfWNIDxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtggLbzIjgb07cHjEkw4HOXXnRXHdP9UckpqGQdVDIYUEtWoZasw/eSwYCFFC/Qdl4wJsGAXNmL3usN1JJ1UMk6rI+BASpZhe8l65BuggHpphfUkr1gTIIBQ8SL7pac7o9KTkEl6+D5YIBKVqGWrBMSd2rJUICFFC/C9I0lPWBMggEVJS96qw5qyTqoZB1UMhigklWoJeuQboIBk44XOJsXjEkwYIh40X29Ybo/v3GdgkrWYX0MDFDJKtSSdfheMhig7bwIiTuW9IAxCQaoZC96W5Jasg4qWQfPB4PgOajkBH7jWod0EwzQdl4EZ2P69oAxCQaUC7zorjqm+6OSU1DJOqhkMGByUKGWrEMtGQxYSPECbecFYxIMyJW96G1Jask6qGQdPnENBqhkFb6XrEO6CQakm17gbF4wJsGAXNmL7pac7o9KTkEl6zA5gAEqWYVask5I3KklQwG0nRdh+saSHjAmwYBc2YvelqSWrINK1sHzwQCVrEItWYd0EwyYdLwIzoYlPWC9AQwIW150t+R0f37jOgWVrIPngwEqWYVasg7fSwYDFlK8QNt5wZgEAz5x7UVvS1JL1kEl6+D5YBA8B5WcwG9c65BuggHazguczQvKBWDAEPGiuyWn+6OSU1DJOng+GFBLVqGWrBMSd2rJUABt5wXrDV4wJsGAXNmL3paklqyDStbB88EAlazC95J1SDfBgEnHi+BsWNIDxiQYkAh50f0TrNP9UckpqGQdPnENBkwOKtSSdfheMhiwkOJF0HZY0gPGJBiwkOJFb0tSS9ZBJevg+WCASlahlqxDugkGTDpeUEv2gvUGMKCi5EX3CWC6P79xnYJK1iFhAQNUsgq1ZB1qyWDAQooXaDsvGJNgQK7sRW9LUkvWQSXrsD4GBsFzUMkJ/Ma1DukmGKDtvMDZvEACgQFDxIvuqmO6Pyo5BZWsg+eDAbVkFWrJOiFxp5YMBdB2XrDe4AVjEgyoKHnRW3VQS9ZBJeugksEAlazC95J1SDfBgEnHi+BsWNID1hvAgLDlRXdLTvdHJaegknXwfDBAJatQS9bhe8lgwEKKF2g7LxiTYECu7EXvqjy1ZB1Usg6fIgEDVLIKtWQd0k0wIN30AmfzgjEJBiRCXnR3tun+/MZ1CipZh8kBDJgcVKgl64TEnVoyFEDbeRGmbyzpAWMSDMiVvehtSWrJOqhkHTwfDILnoJIT+I1rHdJNMEDbeRGcjenbAxIhMOBzl150t+R0f1RyCipZB88HA2rJKtSSdfheMhiwkOIF6w1eMCbBgIUUL3pbklqyDipZB88HA1SyCt9L1iHdBAMmHS9wNi9YbwADwpYX3S053R+VnIJK1sHzwQCVrEItWYdaMhig7bxA23nBmAQDPnfpRW/VQS1ZB5Wsg+eDASpZhVqyDukmGLA060VwNizpAWMSDBgiXnRXHdP9+Y3rFFSyDp4PBqhkFWrJOiFxp5YMBVhI8SJM31jSA8YkGJAre9HbktSSdVDJOng+GATPQSUn8BvXOqSbYIC284JasheMSTCgXOBFd9Ux3R+VnIJK1kElgwGTgwq1ZB2+lwwGLKR4gbbzgjEJBuTKXvT+xDW1ZB1Usk73bwjA6KCSVfhesg7pJhiQbnqBs3nBmAQDcmUvujvbdH9UcgoqWYfJAQxQySrUknVC4k4tGQqg7bwI0zeW9IAxCQbkyl70tiS1ZB1Usg6eDwaoZBVqyTqkm2DApONFcDYs6QFjEgwYIl50r8pP9+c3rlNQyTp8igQMUMkq1JJ1+F4yGLCQ4kVI3LGkB4xJMCBX9qL3egO1ZB1Usg7rY2AQPAeVnMBvXOuQboIB2s4LnM0LxiQYkCt70d2S0/1RySmoZB08HwyoJatQS9ahlgwGaDsv0HZeMCbBgFzZi96WpJasg0rW4VMkYIBKVuF7yTqkm2BAuulFcDYs6QFjEgxIhLzorjqm+6OSU1DJOkwOYMDkoEItWSck7tSSoQALKV6E6RtLesCYBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vECZ/OC9QYw6F4B/TN0nwCm+/Mb1ymoZB0SFjBAJatQS9bhe8lggLbzAm3nBWMSDMiVvei93kAtWQeVrMP6GBgEz0ElJ/Ab1zqkm2CAtvMiOBvTtwdIIDBgiHjR3ZLT/VHJKahkHTwfDKglq1BL1gmJO7VkKMBCihesN3jBmAQDKkpe9FYd1JJ1UMk6qGQwQCWr8L1kHdJNMGDS8YJasheMSTBgiHjRfb1huj8qOQWVrMP6GBigklWoJevwvWQwYCHFi5C4Y0kPGJNggEr2orclqSXroJJ18HwwQCWrUEvWId0EAyYdL3A2L1hvAAMSIS+6TwDT/f/5n2848b/BLv+fbMAKtWQwmIeIDBdYmdfd/q9swEpI3KklQ4F5iMhwgVeYtZ38G14BlQwGOJsXvVXH/2+6P0AL/y1jB0BBRglANTJ0ABRkkAAMBYkQFJBRAi70dLb5E9cADTA5QAEZJQDVyNABUJBBAjAWMj4BFGSQgAuoZHgSqGQoIKMEoBoZOgAKMkgAhoJECArIKAEXUMnwJJgcoICMEoBqZOgAKMggARgLGZ8ACjJIwIXuKvnn//u//5f/Dv/9T7DLV7L74//j17vAIHjOv6dhw3//3/x7gP857+W/8Bsn/HoXFJiHyHnc8N+F/8L0jSU9/guW5Ne7oADO5vVfd9Ux3Z+/BJXCX4LSCQkLKhkKhJDGH0BImP9eMn8JKoHfuAYD/n6RF1jSCywJBuTKXvRWyfy9ZB1Usg6eDwaoZJX57yX/ygaskG6CAZOOF8GSOJsHjEkw6F4B/TN0d7bp/qjkFFSyDp4PBqhkFWrJOj+TWaglQwEWUrzAkl5gSTBgIcWL3paklqyDStbB88EgeA4qOQGVrEO6CQZh0mGIeMD07QWWBIMwREiEPOhem5vuj0pOQSXrMDmAAbVklVkl84nrBGrJYMBCihdY0gssCQZ87tKL3qqDWrIOKlkHzwcDVLLK/L1kaskJpJtgwNKsF1jSi2BJwhYUwNm86G7J6f6o5BRUsg6eDwaoZBVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhe8k6pJtgwKTjRbAkzuYBYxIM+NylF90tOd0flZyCStZhcgADVLIKtWQdvpcMBiykeIElvcCSYECu7EVvS1JL1kEl67A+BgbBc1DJCXwvWYd0EwyogHpB4u4FYxIMKBd40T1sTfdHJaegknWYZsGAyUGFWrIOtWQwYCHFCyzpBZYEA3JlL3rX5qgl66CSdfB8MEAlq/C9ZB3STTBg0vECS3qBJcGAIeJFd0tO90clp6CSdfjENRigklWoJesElUwtGQqwkOIFlvQCS4IBubIXvVUytWQdVLIO62NggEpW4XvJOqSbYMCk40WwJM7mAWMSDBgiXnRfb5juj0pOQSXr4PlggEpWoZasw/eSwYCFFC+wpBdYEgzIlb3obUlqyTqoZB0+RQIGwXNQyQl8L1mHdBMMQpLEEPGAxN0LxiQYkCt70T1sTfdHJaegknWYZsGAWrIKtWQdaslgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp4PBqhkFb6XrEO6CQZMOl5gSS+wJBiQCHnRvSo/3R+VnIJK1mFyAAMmBxVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJet0X9WB0UElq1BL1iHdBAPSTS+CJXE2D7AkGBC2vOhuyen+qOQUVLIOng8GqGQVask6fC8ZDFhI8QJLeoElwYCKkhe9LUktWQeVrINKBoPgOajkBH7jWod0Ewyo23nB9O0FlgQDhogX3S053R+VnIJK1mF9DAyoJatQS9ahlgwGLKR4gSW9wJJggEr2orclqSXroJJ18HwwQCWr8L1kHdJNMGDS8QJLeoElwYCKkhfdLTndH5WcgkrWYXIAA1SyCrVknaCSqSVDARZSvMCSXmBJMCBX9qK3Jakl66CSdVgfAwNUsgq1ZB3STTAg3fQiWBJn8wBLggGJkBfdJ4Dp/qjkFFSyDgkLGDA5qFBL1uF7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GwXNQyQn8xrUO6SYYhEmHIeIB07cXWBIMGCJedP8E63R/VHIKKlkHzwcDaskq1JJ1qCWDAQspXmBJL7AkGHTXdn+G3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXdLTvdHJaegknXwfDBAJatQS9YJKplaMhRgIcULLOkFlgQDcmUvetfmqCXroJJ18HwwQCWrUEvWId0EAyYdL4IlcTYPGJNgwOcuvejubNP9UckpqGQdPB8MUMkq1JJ1+F4yGLCQ4gWW9AJLggELKV70tiS1ZB1Usg6eDwbBc1DJCfzGtQ7pJhiESYch4gHTtxdYEgwoF3jRvTY33R+VnIJK1mFyAAMmBxVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQdPnENBqhkFb6XrEO6CQakm15gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrBJVMLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGKCSVagl65BuggGTjhfBkjibB4xJMGCIeNF9vWG6Pyo5BZWsg+eDASpZhVqyDt9LBgMWUrzAkl5gSTAgV/aityWpJeugknX4FAkYBM9BJSfwG9c6pJtgEJIkhogHJO5eMCbBgFzZi+5ha7o/KjkFlazDNAsG1JJVqCXrUEsGAxZSvMCSXmBJMCBX9qL3egO1ZB1Usg6eDwaoZBW+l6xDugkGTDpeYEkvsCQYkAh50d3ZpvujklNQyTp8igQMmBxUqCXrBJVMLRkKsJDiBZb0AkuCAQspXvS2JLVkHVSyDp4PBqhkFWrJOqSbYMCk40WwJM7mAWMSDBgiXnSvzU33RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdY0gssCQZ87tKL3qqDWrIOKlkHzweD4Dmo5AR+41qHdBMMqIB6wSK3F4xJMMDZvOhuyen+qOQUVLIOng8G1JJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq/C9ZB3STTBg0vECS3qBJcGAz1160d2S0/1RySmoZB0mBzBAJatQS9YJKplaMhRgIcULLOkFlgSDp+fKv1/yj+70tuTFWvLXT/ig3NT1r9+q8khs//X1kDzxokre2UX2FPn9is2HGZAGrI+BwTWV/PsV8o5pcP1b5zr/eVpEuVZLniLEH48opJtgcC1J6uMKv9/xtj9Vt2108NbLnwiWbHe25wWV+7lmSfggriZCozjbpQhzC93XG8ILaVTJs4LcYUV3ee2RR2S1V1Ty6TmtWe/3aMdnaM/u4xVG58Lk8Hv0HDP9eGJEuVBLPpvlpy2iPCOJC89ILRkKXFhI8ZlcTxO67C1wTo2MU74bHbzx8inPseSENE4ZId6zuAcGF3Llfs6W8p07s+ry51BVxHLo3rW59lryKbDPlF7EOdWbnvcB386bX3KTSlaGRXF8pu2vDud3gkoGgzCUm1TybzjjRClfVCLKCHmTQftvXGuRtvSgz4wopJtg0F6383GF01XMS6iBTI5paA5eiBCtl1don777WDKgPe7CCPkjiRAYPMnZUib308+su3z6KHnMHnZ3ttDLBpX8HdorZLM31VrjJ7VztxtU8nlVWMg+qNr+AVGXT1yDQWstWfecfFr80IjSWkvOJIlZ50vXDiYeID9Dt6klQ4HWhRSvyVXOjFjJXCaQ5Xy+1cEbL6/yEEvO5PPsEYI9i3tg0Jor93S2lKkz+ply2Ujm8i0qWU7J01slN9aSM5F6IrO+lzmh5yNX0aiSs+ueGbPk2o+wSlqEJVQwaFPJWc/JDbOQnigMPygbv5ecj7R6jpiz4wgZZRHSTTBonHS8JtezC5bTzdZA1ujgzXFS5RGWFKStwghZEokQGDzJ2RKCAFLPrLx8g0q2H7B7bS50s1ol5yN75imyJ4weYNpUcq7CPqFOefn2oye1TA5g0KSS88nfhOYM2YgyutJqqyWXIq12kedGlKCSqSVDgbaFFC9XSK5TTDcLKYA6YTY6eOvlMzzBkhFpqzBCSGNxDwzacuW+znZmvop2Zu3l61VyhYl6q46mWnIpsquPsT/hZ0L+Gej50BU0qeRDqn96Tm2lpNR+hHXSAt1XdWB0WlRyUSRr80NITiInzxl8WDbVks8RQv4lpFd5cEQh3QSDpiTJzRX2oWammG4eXPTssWnnWx380Bn78jmCJaudrZMlhbxqGCKiNVkSPpGmXLmvsyXMV9HOrL18vUqueLreKnlesftf+bfBPm4tvxL++703RpLTbifEHxXfffR+hAXBPE0qeX6eGeU5lU/dbwe/ZIhsZhw88nYfrzA6LSp5PxcsvhD/0slMMtIeHFGaasnz88ysz7mLtGmMeHBECV2nlgwFQmZWPYq9XGEXhgTxRJWdd6633V0h8XvZP1Hl4K2Xz/EAS0Z2j3xmhEDfZEn4RJpy5b7Odma5t3Jm9eUL7nukpnu9VUdLLTk0Xdj1eB/c5fVGtuWR3YEtzz21Hov5qSpV8jpy9j/evT1nMgy29rIjoO4cD1QyGIRBXKmS9dixy/9OQ82IKEPL5JbfuN4MsD9B3xtYF3gfGFFIN8EgTDq1Q0Qd9S+6gpxcyOe2wLS/w25NT/ZEGh289fJZWqbvPpZcaWjaAxIhMLhULujjbCck3pTPXNpcddA19ZPtIt0/wRo6WqeSczF8C9anmWw94ZC9rs2HTo1aVPL8NBOn96g//m7KO7bPNR8LJgcwqJ8c9ORvYgs1R2cwIsrQA7Olljw/zcTpgbZIKzuEjAGeEVFCL6klQ4GGhZRbJlc5t5APrjnfSd6u9z2dK3trHbz18lnGt2QkmuL0xMPA4h4YNOTKnZ3tTNWZVY1yrJGu6sl6q46GWnJoOXMOXNvfIDkcyYX2dUSMGgADDSo5Pn3yGuOB0ziSvUn77HVGovuqDoxOvUpeI0QyovQjj44oDd9LzkaC9UGPc4vsTNo/IqKQboJBQ5I0j/cJV1eQc/P5YD4A6fe1HfxwodbL5xnekisx1svmcARLEragwHOc7UT0vfKZVY1ytD1Yb5U8P2uVSl5T1FT960ug0RBJ+7W5bI/I/LR1Knl+lAnZ3NCfM+5N33o02LVx9x66j1cYnXqVPI/2CWVARV84OMOjI0pDLXl+lIlUU6shIibRz4woQSVTS4YC9Qsp90yu5qkxN0pvq0cm2Vfr4K2XzzO8JVfqW/aBxT0wqK8o9Xa2I+uiXPnMqkYZ1riVRkCN3rW5+lpyaBjQrLLadZcF5kP7+urrTNSFepUcn1OxSzx0eE7Zpzx83lfGAZUMBtUqObqHmuLFGLEbbBURpU6FdqG+lpxXvXpWLLseGlFIN8GgftKZR/uEryvIqfl8sJDQaGluq4M3Xr5AsGSdsy2XfbslI9FEyiOPAYkQGAwftjLIedaZVY0yyLktYaurs4W+1qjkQoo6oQTruEs296hTwVjMj9ukkmXzgBza2zeGf218NE55Pei9qgPDU62S57E+oWZCSox4dkSpryXHiKKFgXhsd6H47A+NKKGL1JKhQPVCyk2Tq3mmNCjlAPtJs9HBWy9fYHhLRkpZ1RCwuAcG1dqut7MdiXe0zqxqpBO9u9a9e6vk6lpy+W2lSx6lmUCdCsZi7mGVShbDqC9RnnN/bNmTGR9yrOeAMGAJFQzCCK5RyXFuyITKGHDWGFEVUYatPTT8xnV8ctk8EI22u5DseWpEId0EgzDpVA2ReaxPyOYROXbBFeTMbD5YynK1/KDRwVsvX6B6+l6u+nZLrpRMNAQkQmBQXVGaR/qEbB6RY3c624E1LbPOrGqkst6iNlvrXpsLna35e8lG2JKj2+Fyezl4wcJvolklq48Sc3fZnCgVfrT2o8HkAAa1teSyK6SiuCqiVH15pAv1teQfQTYPpEYr5tAPiCjhtVJLhgK1Cyl3Ta5yYiZQTVcWh1W9Wwlb0rzSwZsvX2B0S65UN+wFi3tgUJsrd3e2A3JWoHxmVSOVGLOqhURv1VFdSw7tJnJ9Td6lbGfaD5+8zR2sUsnzc2SWReL4l82J/8iezCqKHB13cuAT12BQq5JjDMgtKMrh1Rdk+6kRpeE3rkvMD7mPEIYZ5ei4EYV0Ewxqk6S7JtfLJwZaA5M0r71Z2+WfYkmloj4YwZKELShQmwgNFbaigg2Uz6xqpNFcSu6ukudnrVDJ5fWO7Xhc7zRyt3Pz4Zj736KS1SeJ40E2J2RH7pXLGO06Iop0H68wOrWTg1UFOfnC0yNKy99LLjA/5D4Oy47HRpSgkqklQ4HahZR5pN/gCst5F/LBwFAq+SmWbDXa+2FxDwxqc+V5pA8StlYFGyifWdVIQ05sSIZ6q47aWvLv10JO/p8X/6xXuxy+YOI30aySVcMkwd5aIx1+dkAlg0F1LVmQzYRTCHl6RLmplvz4iEK6CQaVk85triDnXQstrXeV5rU3a7t8sGSFs3W3ZG27fpAIgcEDw1bsy0L5zKpGCvF5Gryn+ydYQ38dvsx3LuXIZvbRLr/6NzH3r0Ulq4NFnnKzQnzs7DKKHB92emByAINalWxxksXL1nMjim8teb3Q4yNKeM3UkqFA5ULKba5w9byZJAcwWJpXR4q2yz/EksN/MIjFPTCp1HYjhS3JuYTymVWNUqJvt1QMequO+r+XXCa+atmMaxJZE1oLKL2Zn6dKJZ+e/EBS/4qjUDZTkjMGo/uqDoxOGL8eKjlcZ0JCyOMjSv1vXJdIos3jIwrpJhhUVkBvc4XltOZ8cKHx5FI6oSHNKy9fmW72tmSrETpQOSbhc3mIs+04lpKNM6sapYT5vvW83ip5ftaa37g2OMU1O8xJAweBfgvzAzSpZGUpKB7aBkSy44xtuL50H68wOl615NkPVl95fETxqSUnM+ay/eCIEp6IWjIUqFxImYf5Ha4gp+UvXCCWTmrXxxpT4sbLP8SS0uzn6+vr5+ffr68Ba8os7oFBZa48D/UhwtZa5hXKZ1Y1SljvIdtV9K7NedWST8HdjvVLg1Ybv415ZFap5HX9RbZ3iBW2I3a9a/ScFpUMBk4q+ZT/PT6i+HwveX7E3UM+P6KQboJB3aRznyvIaZciS+s9pXntvRov/wxLrinVxs9oYZ1ECAzqtN1AYSuWeaNuKZ9Z1ShBzmrLhLo7W+jx6yo5vsj4KHZOe/XVv4m5e1UqeX3vycPGwbYdiJl/YW1UWow2KUT4xDUYOKnk2Q0mxFceH1FcaskxpKzXeX5ECVMztWQoULeQcp8rXDwtEHPg2jkzcfAyrZd/hiXj/Q/8O1YAY3EPDOq03ThhKyZQ/9SdWdXozFko1tFbJTvVkmNwjyY7bSr8HZW8xvTTe4w22Vmh4qGlRdvYex8soYKBj0pe6wmyLVvPjSgeteQYUjYPfH5EId0Eg7pJ5z5XuHjaxBrFKh0/dfAirZefLWk7W29LxvufGCrvIBECg7pEaJiwtQsm8o/ymVWNTjQHrIXutbnQ5ZdV8jmljcKxYIuKJZSezGO3TiXH4XJ6katI3u2VfaUXXtGkJ0wOYOCjkqP7SBB+fkRxqCWvIWWzwvMjSugetWQoULeQcp8rLGc1Z6n5BfQc0r/aJLL18k+xpLRKGSi0s7gHBnW58jBhKwafqf32rwJVjU7s7tFCb9XhU0uODx+f5D+yLZsaUVi3LSq8jRaVvE5W//ysYfw3muTwhLKnNEYuesS76L6qA6MThu/LKvm86Pj8iPLqb1x/hbxsYeeAsufBEYV0EwzqKqDzKL/FFZazWlO7311JtMbvv7aUoaaDrZefqUs3l4t2s+Qa+1PGie11YxI+mEc428oaTqZ/y7/KZ1Y1OnKuptbSWyXPz/rqb1yv4V22az5FcMXIb6RFJW8DbHqX30Eo7ya8wwMqu87UmK4j3ccrjI5HLXldeIqu8vyI8kItOfzS6/xoC3v/k10PjijhyaglQ4G6hZR5kN/iCnJWfWD5nTxWTpqx3L7g4Bqtl994hCXjtTWuBdAbYHEPDOoqSvOw7h+2DmUJ+Wf5zKpGR+SUZi/urTo8asmrgdcHqXmt0qTFyG9kfoJalbwtE6QcXq7su8Ej3gUqGQw8VPJaN43Fg+dHlOvfSz7VVv5YRCHdBAO3osxFV5Cz6gPLKR+wvL7k4BqNl9/xCEvGRnPB4b++r64I3AuJEBg8KmxJ46X1/t9ZqhodiM/R7DfdP8Eaev2aSt4+cCw71jBefLClSYuR38n8QqtV8vr+Ew6PFy1VivQXPeJdMDmAgYNKXvOi1X2eH1Gu15K3ABs4mOAPRJSgkqklQ4GqhZQbXUHOqg8sRxlrOn3BwVUaL7/jCZZcbn+Q/vsHll29YXEPDKpy5UHCVrzF0l/ZKJ9Z1WjPoVzdRG/V4VBLDvFiZrNXTU5b06Yf86ipV8mniS7ycxwPcZiURkm8UPNIeg/dV3VgdF5XyVttRXb8hYjiVEv+cxGFdBMMqpKkG11BzqrPB/eqriIcFRxcpfHyO4IlTWfrbMnwExTnBt/bIw8S3qssCZ9MVa48RthaI9ByC9kon1nVaE/04fozIr1V8vysL6nkNX7tHkP2FR+spk0/WlXyOpIPnBaIYpvSulFNm450H68wOi+r5C1p3Jzg+RHFqZZ8nGL+QEQJb41aMhRwq4BedAU5qz0fDJxWyjUKDq7SePkdT7DkdFx5pu2Zx4hjLO6BQVWuPEbYkqax7XErQ1WjHbFcfeHTIL1rcy/XktdK8v4pavLVmjb9aFTJu5+0PrD96HWgZt2opk1HUMlgEEbvKyp5E8k7H3h+RLn+G9ebQWb21/gDEYV0Ewyq6nY3uoKcVZ0P7iRdwAxIBQdXabz8jqrpu7MlMxddH3qM+E4iBAZV5YIhwlb0rTigZdNVJa9BrvEpAt2dLfT7hd+43pZB9w9fk6/WtOlHm0o+TlsH9oPoxnWjd9F7VQeG59VaspoOPT+ieH0v+XCRPxBRwlujlgwFHl1LnrAiUsHBVRovv+MJlvzKXHN96sZ73gOLe2BQpe1GCFuJgJXN8plVjTai+15Jz3qr5Bdryat9jysEYpHig9W06UeTSj7MWj+HP+pweMAb143eBUuoYPCiSl695zDMnh9Rrn8vOfCt/3nUPxBRSDfBoGrSudEV5Kx6lRzY/zZzRUjKOHiWxssLj7RkJD7wEAGeRAgMHuNs0nBred5WqWq0Ep+h9SFmutfmQsevq+Rw9szRVjHgy6bK2Dlti0repqt/fsQO37spb/eEsqc0sC6uG70LJgcweE0lb44jOxaeH1Fe+HvJwmaa7TKy48ERJahkaslQoG4hZR7kt7iCnFW6ssr2m1N1y0CagxdovfzEUy05E+954YuN/rC4BwZ12m4e0V2dLYaRra+yo3xmVaMVaX3N9XurjtdqySFUzJweoSanlSaXrHY/8xPUqeRtbttbYferjNvglh2lZ64xXUe6r+rA6Lykktclx9Oa4/Mjymu15Jk1TdzMINsPjiikm2BQlyTNg/wWV5CzLgSWNQmoO1dx8CKNl18s6aKS327JQHzci6e7UmdJ+GAeEraUKq/sKJ9Z1SgSH+FaFtJbJc/PelUlr0H6/AQ1r1WajBDxFOYnqFPJ82METinwNuWtMlm2b/CId9F9vMLovKKSN5F8Wjd9fkR5vZa8CynrM563FQaPKGESoZYMBdwqoBddQc66EljWFEm2DVIHL9N4+SdbciLe9OLprrC4BwbPUMlryNnlJrKnfGZVI2HN664lQL1Vxyu15Pjy0tcXjVIqnUiTESKewvxsVSp5naiSh12HxvqM0rb0wi96xLtAJYNBGL1XVXI4d+YcFp4fUa7/xvWONaTI9h+IKKSbYBAmHXuI3OcKctalwBLTg8qTEwc3aLx83fQ9piUnKjr2LkiEwKDuc5e9nS3Mv4F9B2RX+cyqRkIMUxc9pvsnWEPfr/3G9RrQ09wvrk8UVg4qmvRkHphVKnl+ignlQZJlmgqPGGgi0GByAIMXaskxmKZD7PkRxaOWvE2YfyeihO5RS4YCdQsp97nCctZFbScn197z7OAW0rzy8o+25HrXERb8WNwDA7clqTudbdUoexEnu9xUsnqTBnqrjuu15IJIrrHgxfWRd1GtkuNzqC8xRvVoh4qHlhY1Y68H3Vd1YHSuq+S4rKmNMDny3Iji8L3kiTjf/J2IQroJBnVJ0n2ucPG0hUZld3Zwi7bLP9qSQ4X4YEnCFhSoS4T6Otuq4g6Ziewr37Cq0YI0vez3vVXy/ACXVHIMz2r35VDBKhfXR97FPHZrVHJxllrXUGTb9oh4xqAFsf7jFUbnskpeveXautvgEcWnlnwOIc+PKEElU0uGAnULKfe5gpx2McdrPNt+jCPSvO7yz7bkSLGMxT0w8FqSutPZonw59lN2lt20qtFMfMTLqVnv2tzlWnJRJFe8+r+ikuenyD7H2Q6ymR9ZcW3n5aLTTaCSweCqSi5+OOX5EcWnlrzaIU6ZsvnciEK6CQaVk848zO9wBTmtIh/UkLNr41J08NpOSvO6ywdLVjjbcsnhLDlSLCMRAoMHhK0YbE5plewsu2lVo0Ds/3W37e5sofcXVPJqXj1tPedyKdLgary8m/kBKlRyXOfJPMd5GUg28288Gk42h6P3qg4Mz1WVPI/7gOpLj48oTrXkGFHijCObz40oYXGDWjIUqFxImYf5Ha4gp12MLI2rd62Vo6bLP9uSl6tqN8DiHhhU5srziO7jbDn9KnvLblrVKCAR6rLX91fJF2vJq3kz6wPm8sfoudvcvwqVbDzH2Q7mlLYcf2FA3QxLqGAQxu8FlRzSjhl9eD0+orj8xvXE/JBbhHh8RCHdBIMw6VQMkdtc4ep5C62BSZrX3q3p8pXT96CWtCeB90EiBAbjO5vcOrm37C7fsarRxKoVZfsC3WtzofvNv3G9Pnh2VU8OZ00Y349sDoeTSj7bwWoeDWsOvV4wOYDBtVpyDAjZ0SWHHxtRnGrJfy6ihPdGLRkKVC6k3OYKV89bsLp1RprX3q3p8s+2ZLMpb4TFPTCozJX7OVu8c3Jr2V2+Y1WjCWn3ytJWb9VxrZZsprTmq5fDwwquuf/+KtkaWvFyAyyW6vCJazC4pJLjVJAf+k+PKE7fS/5zEYV0Ewxqk6R5oN/gCnJe7roGVuA6I81r79Z0+WdbstmUNxIsSdiCArW58jykOzjbmnMlV5b9ZTetarR1/5XErLdKnp+1VSXbItn6Bkk03dVweTtzB29QyWK6nOGWo0NMAzrdxyuMzhWVvInkbLX16RHlplry4yNKUMnUkqFA7ULKXa4g510MLVaKcEaa196t6fLPtmQ8fYQEhMU9MKjNlXs5mxxXGmQP7KlqVJDiDfRWHVdqySFAzJQ6Xm4iA6P9zb+LWpUcB0FmDMTD61CKc5qeLifNhwOVDAYXVPImkguxVFo8NaLU1pK//v2Zkc0zfy6ikG6CQe2kc5crGCcGh53+X+7wOTLNDj79P9k8k3Rzahr+q718kWDJGmfrZEmDkYIZiRAY1CZCnZwt3tYkc4Hy0UgMTy/5bG1V/jbCE7Sp5FjUKed85VcvB8cNM3P3K1RyNEZmEKRWkB36k5eNNgJMDmBwQSXHUFocWg+PKLW1ZCMG/LmIEt49tWQoUL2QMg91f1eQE3OJnhzO9VAOr51qdXDZzkU24/CRwS05UepdnCZGCGYs7oFBda48D+p3O1tU3zaZC5SPCqtYlO1r9FYd7bXkzbrFwkhxCSSGu4rSSifmsVmhkuNYyYyC+KCyOZHu2Yg26zkgDLqv6sDohBHcppKjT5RH1sMjSu1vXBcf8w9GFNJNMKitgN7lCnJmLh8s3VVZR2918MbLF6lON/tYMlw6f9V434wl3kv1mIRPZWxnk6MVlC9QDjzS6MW8rLdKnh+j6TeuwwkzRlyWVtoayAtv/l00q2R1qSeuA+0eVNm1Er1l3FS//3iF0WmuJUeXsNIfafTQiFJbSzZWX+Xg34kooYvUkqFA9ULKTa4gZ+YSnnhl/Xjs0+r6rQ7eePkig1tyDuPZJ5lPnTASz/fA4h4YVFeUejhbvG4FGX8rH10oPVkDvWtzzbXkEB1mrF7HyUBpV477QzC/3hqVHMeBOufJocODxodPJ4Oh1kozoJLBoFUlr8PemgmeHVGqf+N6fpAJta32oM+OKKSbYFA/6dzjCnJmLrgUU0HlvrKj1sFbL19ibEvKlTMyOfboimDwh0QIDEZ2tvW6FWS8tXx0Zr3Liy7b3dnCMzSo5DVU2Z2WhqkZnRYYbqVaJa8rw8rTrMaS7Zm8rJb9uVliCPjENRg0quQtXpvjXto9M6JU/8Z1PkBkJs1nR5SgkqklQ4H6hZR7XEFOzeaDclxtEHOA3bFWB5c9tZcvMbQl12dXr7wmU5WPejMs7oFBvbZ7v7PJsSoyDlc+OtMYnbL0VsmNteT1dWoR/sSqH09v2GuB4VbmB61RyVv0Tl5j5kjcfW6f2z8ULKGCQaNKnsd8wA6lj44o1bXk9WlSP8scenREId0Eg4ZJ5xZXkHOzASpeXMll10M7z2918MbLlwiWrHS2nMVy+6uQc3VLrg+jaYIQJhbGCPIkQmDQUFF6t7N9zX9GI4uc+c+ylXE4aVNI29ZoJtuX6V6bCw9RrZLXx64KVauxD0FvFdpDx5h6lbym7ucH2oL+0VjrCYfp6ndtPsYskIHJAQzaVPIWkWVHiSdHlPq/l7w9z6l5Lvw+OqKEXlJLhgINCyntrvA1If/MIefmm0mDtIke3VodXPbVXr7A0JbcMqmkwXbbuhB6PyzugUFDrtwnbGWpOtNuJC1ed9neqqOplrwF8SrLb1Fv94TbmqDsGJN6lbzNeYfhsNt7fr9axG80bTe6r+rA6IRBXK2S28LBkyNK7W9c57PFLW78pYhCugkGDRXQZldYokc5j5ublPxo55n7K233PTp+q4M3Xr5AS7r5fktudzw2+S0kU71oGZPwkbSUC97vbCWqzjQbRa993WV7q+T5WWt/43ofxTIc3tt+NpgPfO2uUBvY+9CgkuNwmZHn3IV15fVuVviZx9iIs0CG7uMVRqdlcthFiByHVOTBEaW+lnywyvKYU4zYB99l144HR5TQdWrJUKBpIaXNFWLromNKm0LSuHPO5a7TfXci9nxqq4PvLy8ljdLl8wxuyb0J4pPu76rdtxNNloRPpClXfr+zFag602q0BqjX87LeqqOllnyIYRmOFjkEuCPDhDudueeVKnk/Xykog0SOaIyd6qOSwaJBJRueM3Mcbc+NKNXfS544RdrdN4Vm/lREId0Eg7ZJZx70OokrrOGkmBDabU6rfWeHTTp/dvB/yw5+vvypeb1tRrfkyS4J48R4EiEwGD9s5ag602oUffnC/c90/wRreI46lWxFsJnT4kb2nNEDTItKPk9iR7TlnvwJxcWhAWByAIN6lVwjks+j7bERpaGWbMTavxVRgkqmlgwF2hZSWlxh8zPZoSJNSuleMQVQQlOjg7dePsfwlizaZaQYz+IeGLRpuy5hK0PVmUajNbmT7VforTrqa8lVKW2y7JGJegOFO50mlVywTeYH4nIn6K0HovuqDoxOvUoup0TCebQ9NaK01JJ3q8UJfy2ikG6CQWOS1OAKfunm4QPTR9TzGh289fIZgiUbnK2DJfPP2fakd9NoSfg8nhC2dKrONBrJYZcEpLdKnh+mRiXn3uGJZN1DXSLxsNy9tKnkC7m7dsLwmf4A4xVGp1ollxKijWS0PTSiNNWS80vLfy6ihG5TS4YCzQsp1a6watWio0gbI93MhbNMaGp18MbL6zzAkt+5B839RZo+sLgHBs25cpewpVF1ZrlRdOMmA+ToXZurriXnYteJNJKlq6BjhTudVpWsTnrFB11H+sqF4fx2UMlgEIZyjUquXHdLR9szI0r9b1wLaYD4kxGFdBMMwqTTNkRqXWGNQUVPqWkzoeq7wkmNDt56eY326buDJfe/yLgxWIgnEQKDdm3XJWwpVJ1pNVoexsVtuztbeJKK37hWA5eCViw5hvf4G5BjM7/iFpU8PeZpjJup+7H912DTgA6fuAaDylpypUhWR9sTI0pjLTlwnjRNx3tiRAmvkloyFLiykFLpCrK4XfaspU1FupkIWcMDGx289fIpD7FkopPHC2Us7oHBFW3XJWwlVJ1pN5q8+MLNFXqr5Ka/l3yZ768l7v08I6GdmEdrm0qe+JbwPj1n1YNOZlns8oyEdoIlVDCo/sT1KzwvorR9L1n4/o2PWfmcz4sopJtgcG3SqXOF8BdXPGPIlALEwFTjga0O3nj5M8+xZLzndMkhQxmJEBhcS4T6hK17+HbykO61ufBCblfJz+OaSv77MDmAwVtU8vO4UEv+CIJKppYMBVhI8QJLeoElwYBc2YvelnxPLfl5oJJ1uq/qwOigklUu1ZI/ANJNMCDd9CJYEmfzAEuCAWHLi+6WnO6PSk5BJevg+WCASlahlqwTPl5GLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGATPQSUnNP/G9YdAugkGYdJhiHjA9O0FlgQDhogX3dcbpvvX/Mb1p4FK1sHzwYBasgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOnyIBA1SyCt9L1iHdBAPSTS+wpBfBkoQtKECu7EX3sDXdH5WcgkrWYZoFA1SyCrVknaCSqSVDARZSvMCSXmBJMCBX9qL3egO1ZB1Usg6eDwaoZBVqyTqkm2DApONFsCTO5gFjEgxIhLzo7mzT/VHJKahkHT5FAgZMDirUknX4XjIYsJDiBZb0AkuCAQspXvS2JLVkHVSyDp4PBsFzUMkJ/Ma1DukmGIRJhyHiAdO3F1gSDBgiXnSvzU335zeuU1DJOng+GFBLVqGWrEMtGQxYSPECS3qBJcGAz1160Vt1UEvWQSXr4PlggEpW4XvJOqSbYMDSrBdY0otgScIWFMDZvOhuyen+qOQUVLIOng8GqGQVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XgRL4mweMCbBgM9detHdktP9UckpqGQdJgcwQCWrUEvW4XvJYMBCihdY0gssCQbkyl70tiS1ZB1Usg7rY2AQPAeVnMBvXOuQboIBFVAvSNy9YEyCAeUCL7qHren+/MZ1CipZh2kWDJgcVKgl61BLBgMWUrzAkl5gSTAgV/aid22OWrIOKlkHzwcDVLIK30vWId0EAyYdL7CkF1gSDBgiXnS35HR/VHIKKlmHT1yDASpZhVqyTlDJ1JKhAAspXmBJL7AkGJAre9FbJVNL1kEl67A+BgaoZBVqyTqkm2DApONFsCTO5gFjEgwYIl50X2+Y7o9KTkEl6+D5YIBKVqGWrMP3ksGAhRQvsKQXWBIMyJW96G1Jask6qGQdPkUCBsFzUMkJ/Ma1DukmGIQkiSHiAYm7F4xJMCBX9qJ72Jruz29cp6CSdZhmwYBasgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GqGQVvpesQ7oJBkw6XmBJL7AkGJAIedG9Kj/dH5WcgkrWYXIAAyYHFWrJOkElU0uGAiykeIElvcCSYECu7EVvS1JL1kEl63Rf1YHRQSWrUEvWId0EA9JNL4IlcTYPsCQYELa86G7J6f6o5BRUsg6eDwaoZBVqyTp8LxkMWEjxAkt6gSXBgIqSF70tSS1ZB5Wsg0oGg+A5qOQEfuNah3QTDKjbecH07QWWBAOGiBfdLTndn9+4TkEl67A+BgbUklWoJetQSwYDFlK8wJJeYEkwQCV70duS1JJ1UMk6eD4YoJJV+F6yDukmGDDpeIElvcCSYEBFyYvulpzuj0pOQSXrMDmAASpZhVqyTlDJ1JKhAAspXmBJL7AkGJAre9HbktSSdVDJOqyPgQEqWYVasg7pJhiQbnoRLImzeYAlwYBEyIvuE8B0f1RyCipZh4QFDJgcVKgl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlkHzweD4Dmo5AR+41qHdBMMwqTDEPGA6dsLLAkGDBEvun+Cdbo/v3GdgkrWwfPBgFqyCrVkHWrJYMBCihdY0gssCQbdtd2fobfqoJasg0rWwfPBAJWswveSdUg3wYClWS+wpBfBkoQtKICzedHdktP9UckpqGQdPB8MUMkq1JJ1gkqmlgwFWEjxAkt6gSXBgFzZi961OWrJOqhkHTwfDFDJKtSSdUg3wYBJx4tgSZzNA8YkGPC5Sy+6O9t0f1RyCipZB88HA1SyCrVkHb6XDAYspHiBJb3AkmDAQooXvS1JLVkHlayD54NB8BxUcgK/ca1DugkGYdJhiHjA9O0FlgQDygVedK/NTffnN65TUMk6TA5gwOSgQi1Zh1oyGLCQ4gWW9AJLggG5she9LUktWQeVrMMnrsEAlazC95J1SDfBgHTTCyzpRbAkYQsK4GxedLfkdH9UcgoqWQfPBwNUsgq1ZJ2gkqklQwEWUrzAkl5gSTCgouRFb9VBLVkHlayDSgYDVLIKtWQd0k0wYNLxIlgSZ/OAMQkGDBEvuq83TPdHJaegknXwfDBAJatQS9bhe8lgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp8iAYPgOajkBH7jWod0EwxCksQQ8YDE3QvGJBiQK3vRPWxN9+c3rlNQyTpMs2BALVmFWrIOtWQwYCHFCyzpBZYEA3JlL3qvN1BL1kEl6+D5YIBKVuF7yTqkm2DApOMFlvQCS4IBiZAX3Z1tuj8qOQWVrMOnSMCAyUGFWrJOUMnUkqEACyleYEkvsCQYsJDiRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XgRL4mweMCbBgCHiRffa3HR/VHIKKlkHzwcDVLIKtWQdvpcMBiykeIElvcCSYMDnLr3orTqoJeugknXwfDAInoNKTuA3rnVIN8GACqgXLHJ7wZgEA5zNi+6WnO7Pb1ynoJJ18HwwoJasQi1Zh1oyGLCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWYXvJeuQboIBk44XWNILLAkGfO7Si+6WnO6PSk5BJeswOYABKlmFWrJOUMnUkqEACyleYEkvsCQYkCt70duScy35//3v/0BkssX//s//hiD4j2xAYLFLMAuTAxQIQ2SKKLjOgSWi/MgWTCwRJSyq/LcMHQCFeYgQT15h8bX/wZIvs7Mki3tQYBohs7TC2a6zeFuwZE/VMatkgAbIaaGAjBKAamToACjIIAEYCxmfAAoySMCFnqoDlQytoJKhgIwSgGpk6AAoyCABGAoSISggowRcQCXDk2BygAIySgCqkaEDoCCDBGAsZHwCKMggARcGUMn/zf/W/8l/2OX0P/lv+j8ydgAUZsdZBgv/2/4XzcL/jv+brSJDB0BhHiO7IcP/2v8n/2HJl/8n/wU7yvgEUJjHiAwa/vfK/2Y7ilW7EDrAb1wnzL9x/X9kA1b43T4wCEGN37hOmH/jmr8ElcDfSwaD8MN3TDoe8MvMXmBJMCBX9mKI37hGJSfwl6B0ggTC86FA8BxUcgIqWYd0EwxCksQQ8YDE3QssCQaUC7wIztbVktP9UckpqGQdJgcwYHJQ4e8l61BLBgMWUrzAkl5gSTAgV/aid22OWrIOKlkHzwcDVLIKtWQd0k0wYNLxAkt6ESxJ2IICfO7Si+5ha7o/KjkFlazDNAsGqGQVask61JLBgIUUL7CkF1gSDMiVvehtSWrJOqhkHdbHwACVrPJ/Q0ShlpxAugkGpJteBEvibB4wJsGAIeJFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSfwvWQd0k0wYNLxAkt6gSXBIAwREiEPujvbdH9UcgoqWYfJAQyoJatQS9YJKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlmHT5GAASpZhe8l65BugkFIkhgiHpC4e8GYBANyZS+6W3K6Pyo5BZWswzQLBqhkFWrJOnwvGQxYSPECS3qBJcGAXNmL3paklqyDStbB88EAlazC95J1SDfBgEnHCyzpBZYEA2rJXnR3tun+qOQUVLIOkwMYoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdVgfA4PgOajkBL6XrEO6CQakm14ES+JsHmBJMAhDhETIg+6qY7o/KjkFlaxDwgIG1JJVqCXrBJVMLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGKCSVfhesg7pJhgw6XiBJb3AkmDAEPGiuyWn+6OSU1DJOng+GKCSVagl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlmHT5GAASpZhe8l65BugkFIkhgiHpC4e4ElwYBc2Yvulpzuj0pOQSXrMDmAASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWQfPB4PgOajkBGrJOqSbYMCk4wWW9CJYkrAFBSgXeNE9bE33RyWnoJJ1mGbBgMlBhVqyTlDJ1JKhAAspXmBJL7AkGJAre9HbktSSdVDJOnzXAgxQySr8xrUO6SYYkG56ESyJs3nAmAQDhogX3VXHdH9UcgoqWQfPBwNUsgq1ZB2+lwwGLKR4gSW9wJJgQEXJi96qg1qyDipZB5UMBqhkFb6XrEO6CQZMOl5gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfgUCRgEz0ElJ1BL1iHdBIOQJDFEPCBx9wJLggHlAi+6q47p/qjkFFSyDpMDGDA5qFBL1gkqmVoyFGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgq/ca1DugkGTDpeYEkvsCQY8LlLL7o723R/VHIKKlmHyQEMUMkq1JJ1+F4yGLCQ4gWW9AJLggG5she9LUktWQeVrMP6GBigklX4XrIO6SYYkG56ESyJs3mAJcGAsOVFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSdQS9Yh3QQDJh0vsKQXWBIMGCJedLfkdH9UcgoqWQfPBwNqySrUknWCSqaWDAVYSPECS3qBJcGAXNmL3paklqyDStbhUyRggEpW4TeudUg3wSAkSQwRD0jcvWBMggGJkBfdVcd0f1RyCipZh2kWDJgcVKgl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlkHzwcDVLIK30vWId0EAyYdL7CkF1gSDLpXQP8M3Z1tuj8qOQWVrMPkAAaoZBVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQd1sfAIHgOKjmBWrIO6SYYkG56ESyJs3nAmAQDhogX3VXHdH9UcgoqWQfPBwNqySrUknWCSqaWDAVYSPECS3qBJcGAipIXvVUHtWQdVLIOKhkMUMkq/Ma1DukmGDDpeIElvQiWJGxBAZzNi+6WnO6PSk5BJevg+WCASlahlqzD95LBgIUUL7CkF1gSDMiVvehtSWrJOqhkHT5FAgaoZBW+l6xDugkGIUliiHhA4u4FlgQDEiEvuquO6f6o5BRUsg6TAxgwOahQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZxALVmHdBMMmHS8wJJeBEsStqAAn7v0onvYmu6PSk5BJeswzYIBtWQVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFX7jWod0EwxIN70IlsTZPGBMggFDxIvuqmO6Pyo5BZWsg+eDASpZhVqyDt9LBgMWUrzAkl5gSTCgouRFb9VBLVkHlayDSgYDVLIK30vWId0EAyYdL7CkF1gSDBgiXnS35HR/VHIKKlkHzwcDVLKKXy35b/kftWQwYCHFCyzpBZYEA3JlL3pb8lot+ffrJyQ3U9e/6vK+2P6rsn133qOSv7/EjD9fVVWmzYy9ilJ8igQMwgC9XyX/52kRxa2W/PuP/ENjisyzWX6+vmTP6JBugkFIktqHyDq5vugKL0y6X41T5e2fNbmWbnpbcsp2Hv/Vk2tjEj6Ia+UCL2dr43tNHH6qbjv1cvVl2VWi9fInuquO0PU2lfy9PO/KjxXxxECRRwTIdpV8fMiKsZDYUfbnGMKMrI+BQfPk8DuP5xXZW+KJEcWtlvyTtdDvHLVWnuGnQSVTS4YCFxZSvp1c4aVI8z3duEX3TvdK84bjgxhY/etpSblA5O4FgZthcQ8MLuTKPs52jFkVUuTsm8YprQqw8fIpvVVHey35ZKGZUsT7TU5omjk6Mb/YFpV8GgnmQDhJg5mSYQYxIyoZDJpV8jyaN2RvHsUVHqCTvX7jenp4+deZ82R0YTrqAOkmGLRPOk6ucE4HGyfd+Yz6G8+dTkJZ+ih5zHsFS7Y5m5MlE0NOPCE6ZSERAoP2CqiPs52uYl7iWxruKfVb8+WScpEmexo9p7uzhT43qGTtkSfyj6AG+fGT2rnbLSp5fq4Na2hqI20ia8dRzNj9sw8wOq0q+Ty0ZXeWh0YUp1pymNLkn0fStYOJB7hq6Da1ZCjQupDi5QovRhrpRe0SXkxWT6mD2okMckqeTpbU8vBAj3V+J1jcA4NWbZeuyU1cCFtyZuSiFMlFrYwvZ/uZuXyT6/dWyY215MwjT2SMmjmh5yNXMc9NDSr5/JzloZmbNbKGGcaMLKGCQaNKTtbdZH+OkJ4oDD8onb6XHK4i/zyQWb4cf/mAdBMMGicdL0324qS7eqRsW8TbXVfJ9gP2sWTGkBOvx8NeBEsStqBAo7PlZvBXw5avFGn05dxDNVmmf20udLhaJedNlEnHsid0feYKGlVyMtaKQzM/Mic0O45jRlQyGDSq5GRsy/4MWVcYPWXxqSXPjy//3pMPKaPL5PBE1JKhQNtCSj4xa3OFFyfd1SMrs9x4u/PV61VyRb+6WDJryInH5hIs7oFBm7bzmsH9pIjW95IvK/1svXyG3qqjqZZ8iJo/8iNnK8pssG8xtT9sSpNBaVTJyeApDc385DOT2nEgM7Z+nBY+jjAs64dI6gxyQGdfSX5WRHGpJS/Wko0d58i8t8ur97wZ0k0waKrbHRKzF1zh1UlX2hqlnJVVDMv2Sr1Krni6pnTTyZL701IGj9pZKBeAQdMQcZvBE3crBqBD6+Ndtc6feyn/EtJ+7tO1isvn6O5sobu1Kjm0XYi/573/Tbb0MbYwu7bf7DR2jaNNJZ9Gy0RpaO5bL7+jHn/9fSbJB0YyI5MDGDQtpKQiuaiSHxxRXGrJ83MqFtqMEP8wwxaYB5egYSKllgwFmhZSnFzh1UgTG1dOluvtkkyzWiWXUo5IB0tuhoym/D38ku/YUTsLi3tg0JQrl5ytJeHerhMpxYWdI6633V0h8U3ZP7FGxd0lEn8wLp/Euhy9VUdLLXl7vv3jbXvPNt0y4F37LWhW26gH8/tt+fWuyPxoxaG5Gzo7E+xGz2k8DGVGVDIYXP24QfQL2dQwXGHohMvjN64lRsjWxho79q6p7hwP0k0waJl0nFzh1Ul3Pb/S44MXBNp9dU0nZLtIsGStszlZUtpP7E7Z59YvxsROkAiBQUsi5ORsB+TkghTZotz+DluYO9937dDBafW9E62Xz9L22fUbCL2tVMmhaeDU3+2pZUdktd4he12bD50a3aeSs4NkG2zHbN8w43tHD5MDGNyokodyhUYcask5C62z0dEAurVGI/SSWjIUaFhIycSCZlcwIo3Vm7Vh5f3i7dojWNud3m/Jtf0phV4vP3YemIXFPTBoyJWdnO2InFtTsDvJ2/W+p3Nl7/mpNl+WHULr5bP0Vh0NteT4bEl3M+umORu1LrN2Ye78LSp5NUtiR/2IacZLHnSV7qs6MDr3qWTTFUaOKA7fS56fcUI2V2R34pjZiD0SpJtg0JAkzeN94kVXeDXSSKvaNHC9nWw30PZg77ektE4ttv2RqZGjdpZgScIWFGjIlWc/mHjR2Y7IufkYtKrbxAP1+2Z7o4fFfLBsfazeKnk2ZZ1KDi0DaVCLD318H3FvouLWlyPbIzLPW7eoZGmgvfVoscPZY5mx+3iF0blPJT86orxeS17Dg2xH4tOnfhnPqEzWuxD6SC0ZCtQvpHi5wouRJp5eOVO+sMq39qfu1LdbctX/aeRbuz5y1M7C4h4Y1OfKXmHriHlqdM70tnqYk30FBXhQkq2Xz9O7NldfS46hXOmt+tB5G602bZ8U3sbc+ztU8jptyPYBZXYdzIyoZDAIQ/IWlVzhCi+p0Ht5uZa8Ro6zhWSvcvH87DsOpJtgUF+3m0f7xIuu8GKkaVW9yrRfi5xZm0XXT9/LZV+2pLRV+/fC4kB/SITA4O3OdkJOzYeGgoCIh/YntyrAxssX6O5soa9VKjnOHNqDxWP7qSMaQjb3qDYdi/mJ7lDJclyfGRTDDGZGPnENBrfVkp8dUV6tJa855fkh4wEt5DTORj0IKplaMhSoXkjxcoXXIs3qqZXeHu92YV6NMbM27r3bkrF/+qM9IDplYXEPDKpz5ZtmcPNMaaAGDzm07390Zu2C8dg+5Mmu2ssX6K2S62vJhZljfc076VcyqWrTsZh7eINKXmdQ2T4RjbwassqMquK+B5ZQweAulTyaKzTy6m9cx9AwIXsE2anbTY4N7LKkm2BQPenMY31CNo/IsYoLvRhpoqdWOt2aErQHh+ZTgyWrnG257MuWLOf4ccVh4OiUpdqS8Km8O2ydkTNzUqQozqPn7m8bnVk2DygKsPXyBa6mlG6EvtapZEE2D8RwtzNIyaT2C+zOPBfeoJIVS+1J5ufRzIhKBoO7VHKVK1SFsi68WEuO1gnIroVyRLGM2p/wWqklQ4HahRQvV3gt0sSzK6fJ2OkrsaHxVqNZMppy4OiUhcU9MKjNle+aweXErDr4EkWnBh7Fc6V5rQJsvXyB3qqj5e8lFwhXmdjZSPZknm345G3u4A0qOT54bvFXDq+ny/YwZqz+FAl8KnepZDn81Ijy2veS16pRQPYt/Ed2Zi4tR7NTZXdIN8GgNknycgVpeC3StNZ3w/gPXJhVW281miXHD9p5KBeAQW0idNcMfvnEQKtrSvPam7Vdvruzha7eoJKjFTJvPi49DPuR67n/N6hkaw1FjschMZwZmRzA4CaV/PSI8lotOcaNGdm3IPtyTnkKKOMROkgtGQrULqTMI/11V3gp0qzKtdLVo2NfcVA5tSGqvNmSSoXpwPBBOw+Le2BQmyvPLvC6syUs56GSX+euWrL1apfDF9/gG5jf4h21ZEE2E052G86MqGQwCAPyBpX89IjyUi1ZHl6QnTMxK89duXW2ezukm2AQJp2KIeLlCi9FmuiplZNkezl4Iz5Pw3xcOX17WfJXsp3cdaz7DAyJEBhUfu7ythlczruWEbXeVZrX3qzt8t0/wRq66qaStzVB2ZF9tMuv/k3M/btBJVucZuhlayAzMjmAwU21ZDn62IjySi15zaUXZO9MfOzsleX4sKsHQSVTS4YClQspXq4gzS5FmnU5S7YNYjH1inuu5zZozDdb0oJaMvxdKnPl25zt6nkz0qvqXH9pXu3JbZfvrTp8asnJvBHTuuwbGn0VcX6iDir5ePp4Zuy+qgOjc49KfnxEeeU3ro+l5IOF4iHZTDmtuw0H6SYYVCZJTq7wSqSJh2odPQz+wBXvjOe2pBrBkhXO9q6gUg75Q1NpSfhc3hu2UpbTmuLDRuPJrZ4szSsv31slz919WSUn79E2mjR4vYx9D2Oo5PHM2H28wujco5IfH1FeqCXHeTQiu2dkVz7e2IbrS3g4aslQoHIhZR7mr7vCC5FmFcmVfh4d+8qMupaSZbuK91rSZPTYVIDFPTCorCjNHnCHs8lp+QsXiNGldlm/Uck3Xr53bc6nlhwuMrG9D9toS4Nrr/ANzCPz/Sr5NHrGMyMqGQzuUcmPjyjXv5e85t4xqZb9gUJdSxg9EyXdBIO6ScfLFV6INNFBK2fI1srzATm17dz3WtLENvWwkAiBQW9nk9MuJUSt95TmtfdqvHx3Zwt9fVUlx8lhW0G1w59TnL2LuXvvV8lydrTkeGbsvaoDw9NLJQ8eUa7XkuenmvhSnrDim33SYtTVg/BiqSVDgbqFFC9XuB5p4v7aECStL7lmvFfbZPxeS1pce4YxYHEPDOq03X3OdvG0QJTutZ4pMbM2v2m9fG+V7FFLjibaPYfsKbyg3EwzCHP33q6S18Vl2ZatgczIEioYhOHor5Ll4HMjyuVa8hZelSeseGhpcS0i3Q/pJhiEScceIl6uYDfK3GmdvSu9XMmbqmm9l1A3fb8rqEQDjBqaStSNSfhg6soF9znbxdMmbo5kzcHrauHFjdDZ11RyNNHumU8fHNaoWELpyTx2366ST9PGgGZEJYPBLbXk50eUq7Xk3cqZYiGJGCWXrGjSk6CSqSVDgbqFFCdXuBxpttzv92u+0c+/xSxAOjP15utnaf9VHx7iyY15xlstabGLbM+DxT0wqMuV73O25awLUiTGt9o7xmBUipk7Wi/fX3W8Wkte5oOZ3WP8R3bJpkYMkXWGfTtdVPJ5jWVAM/KJazC4RSU/P6Jc/Y3r+ZkmpoiiWEj2lMKNR0J7I6SbYFCXJM2j/HVXKIahBT3SrJnQlhJN/84K33Wy3zevzRvWk2W7lroK6HLp24NKfPBH5hOUC8CgLleeXeAWZ1vOqg0pkd8YACdq0hVdAWZpvfxMd2cLvb2mkr9kCVTYP0XFTHPxHb6L+QnerJLXNZZ48oBmZHIAg1tU8vMjysVa8j6VVIwge0rPXGO6joQHpJYMBeoWUuZB/rorXI008bwzudlSDidUhQhp2xxP3mpJgzV5lO1nweIeGLgt7l10NjmrdOUjv5Okk5NmrOhSUIAarZff6K06rteS1+XMhcNDXJ1pxmF+gjer5BB4Z+Iay4BmRCWDASpZ5dr3kuNzzw+uGEH2lJ65xnQdId0Eg7emmxcjzSkd2qNmg4d88UDF9Br72DwT907cd2y1dNnxLEiEwKC3s8lZpSsfOcUkK1kpKUCNxsvv6P4J1tDfSyp5rXzOHJ9B7FF8sKVJwzt8K/PAfK9KXgfReu6AZmRyAINbVPLzI8q1WvL8RBPzlJJaSP+G5JHXE9pbCW+WWjIUqFpI8XKFa5GmIJLViLRO9gr5T2kL682aF93easkiW/ooOx4Gi3tgUKXtbnQ2Oas+HzoGJSsK7Vw4YKuCxsvv6K06nGrJp3BdM9PUtOnHPDDfqpI3e8qOIc3YfVUHRicMxy4qeeyIcqmWLI8kz5RaKAaN0nXjZNacUr8H0k0wCEmSOUS8XOFapImOqpNc7JA8pRiuGm/WnmRUpZtvCSrB7WfaH2IIqsYkfDK9nU3OuqaSzY6fglhF3xovv6O3Sp5N+Xot+fQm0lkkpaZNP96ukjdzbossA5qx+3iF0elWSx47olypJUeTiE1SC8WoUbpuTZuOhHSZWjIUcKuA1rS5FGm22VvnnA7IBbJIM51TVGjhrZYssRrgqckEi3tgUJUr3+hsctZFlWzL3kPQq7hL4+V39K7NuX0v+fDUySyiUNOmH+9WyZs1d4Yc0IyoZDBAJatc+I3rNSjIaamFalaia9p0hHQTDNyKMjVtrkSa1VEDX99zNlv6pZr9oZ+vuTffq/YNlO6+3uyCQwdLms7mZckCwelnBg3WNiRCYFCVCN3obHLWNZVcMbrXQLRg9q7x8ju6O1vosMP3ko/zwHkW0ahp0493q+R1BO3tMaAZ+cQ1GKCSVS7UkmNQiE+UWujGleh3ER6SWjIUGL6WHB11YtG8Czvhe7jcLr382SUK37vLFHoYW12Jc4PUkuPZl1V2f1jcA4MqbXejs8lZV1Wy2ffNixes7jVefkdvlfza30v+zvz1K7FH8cFq2vTjzSp5HUAHcwxoRpZQwQCVrNL+veQ1tsq2YqEbV6LfBekmGFRNOl6ucCHSbKr3/EFCaTixTwj0vRO7vFP2pKw3u+LPb7Vkls1el04fgmBJwhYUqKoo3ehsclabFPlu+/vHOQWYo/HyQvfaXOjuZZUc2Ky0rSUUE17hNNMMxvwEb1PJmw1lx8KAZkQlg8EtKvn5EaW5lrzmkuvkoxhB9pTCzcWV6HcR3hq1ZChQt5AyD/LXXeFCpJFNLfSsh3bX27RwklZuh7KPIccbMwzhrZbMIudefIYxYHEPDOpy5dkRbnE2OavZybbPtNQN8BgxKzvYevmJ3qrjtVryzBbZZUfdTCNNBg2U8xO8SyXn1lYHNGP3VR0YnTAcu6hkaTJoRGmuJcfJZHM3xQiyp/TMNabrCOkmGNTV7eZB/rortEeadfrWJsY1Jdz6FUb8jBINtlRAdpyJ3bvmzm6J+ytBZX3+JycSlAvAoLezyVmlK2dQglYJRQEWabz8AM4WOvuaSt6MtD50+0wzGvMTvEklbzPjaS1mQDMyOYBBt1qyNBk0orTWklORrBlB9pSeucZ0HQk5M7VkKFC3kDIP8tddoT3SxDP0eXFNCWV7PVsPBmkydWDNFRrrSsJbLZlhNcij84g6S8IHU1dRml3hFmeTs0pXzpEGrSJG0EpovHx31eFQS96Fbtled5RKJ9Lkyjt8A/PAfJNKllPSkwY0IyoZDG5Ryc+PKI2/cb3G1N0pioVkvim55AsJ7Tsg3QSDuknHyRXaI41sZc5IMsjYiUxHyxlkPHpxDg6WtJ3t1qASzxw2INVBIgQGbw1bCnLWpXwoxpnKk9dsRbYtGi/f/ROsoa+vquT1NcYFzjgzFBY8K5r0ZH6i96jkOGLScTCgGZkcwOAWlfz8iNJYS45RYe9sioUq5tiKJj0J3aOWDAXqFlKcXKE50sSt3JQvN12Px23ZPBMvpx5fD9Yvtx14qyVV1nz66iMMAot7YOCmki8623JWixTZISfX3vOsAC2keeXle6sOl1pyOlGct1OKOXF/3qeSQ7idUYaBHBnIjN1XdWB0blHJz48obd9Ljqn0wdeUJ6x4aGlRH5HeC+kmGNQlSV6uYDc63uk/spX1bTken+C0mRCvrl1PDl125vdaUuGviOTZkoQtKFCXCN3nbBdPW4gJiGxaWEuFZ9ou31slz6Z8WSUnr1o2Cza7uD7yLuYHeodKXleHtWlDjgxkxu7jFUanl0oePKI01ZK1z1urFrLn2Bhg6svY7yW8NmrJUKBuIcXLFaRRdaRZNgr3lebSIHYze/3YSyUri+dejnHvtaRCtMXjkwgW98DAa0nqqrPJadVS5Ejj2fZjHJHmdZfvXZvzqSWvNopJnW2zwXPa+QHeoJLLa6vjmRGVDAZhPPqr5MdHlKZa8vwkE8cwotlAduXjTYwwtbd+N6SbYFBZt5uH+euu0Bpplo3CbY8XtC8vDdIL6mtnLVRO38tdbggqf0YkkwiBRaW2m/3hDmeT0/IXLiJn147xGNZqOynN6y7f3dlCV/9X/n2d83JHtFl++UMaXHyFtzM/wBtUsjTPnDCeGXuv6sDw3FNLfnxEaaklx2Ty5GmahWRX3ifLZu1PUMnUkqFA5ULKPMxfd4XGSGNXeo4XtBfzlgZKixgWroe491oyIZ42bjSqhsU9MGhbknJ3tmOYasaOUwdaC95Nl++tkp1qyec3Yi5/XH3z72Lu3/0qOc57mTEwnhlZQgWDe1Ty4yNKw29cx2c9N9ce0ZxtluMvZNY3Q7oJBpWTjpMrNEYas/maQC4t7PQw12INC7J9gWDJCme7KaisD1AZB0em0pLwubw3bKVcPW+hNZ+S5rV3a7p899pc6Km/SjZtJkPjhYB/L/NLvF0lRytkh4AcHseMqGQwuEclPz6iNNSS5+eYOD+rZiFrtomZaV1A6kB4b9SSoUDlQoqXK1jNjpHGLqIcW8jZhUk012LZ/ZLEfLMlj2wiubbgNDAs7oFBpba7bQa/et6C1a0z0rz2bk2X7606bqolm0aQw8MKrrn/d6vkbdrITXzDmbH7qg6Mzk0q+ekRpf57yTELTx5FNYHsywWceM6w1RvSTTCoTZLmgf66K7RFGjuJjS2W+x41tkZGJcduvRLh3mzJI/HJX3qCUaBcAAZdnW1CzssHpiJWFDwjzWvv1nT57s4WenqDSjZWWKONLr7B+5k7eLNKrlhbHc6MTA5gcJNKfnpEqa4lxydJDaFaKFd5Epaj9ZPd2wn9p5YMBWoXUpxcoTHSnDZTjm6rOvEBaXC64JotvLLe9WZLHvhTIpnFPbCozZXvmsHlvIsZkR2njkjz2rs1Xb636qitJX/9LMjmmXRBVXZkTogRUzbHY36J96rkTSQX5j1pMYwZUclgEAbkDSr56RGlupY8P0YNS/NoNj2nTwPzaJBugkGYdGqGiJcrSMPKSGMkuefAFruRDwXS4NTPeNuXPLl2+r4hqAQ/n/kb6QOJEBjUlgvumsGNE/+d5Nz0/3KHz2HuS9rL5pmkm1PT8F/t5Yt0/wRr6GmNSg7tJoz11e1w+QQ5OG6Ymbt/r0qO46RohdHMyOQABjfVkp8eUWpryWtYMJETZEt/8rLRRiBkz9SSoUD1Qso81F93hbZIY+Z7clxSglipzmYIehyMWWhdWpnj3ZbciI/9Wi18HFjcA4PqXHl2C/8ZXE7MBRo5nBvEcnjtlNGP5LBs5wxgHD7SW3XU1pKNFY10piieEJuPGzDnl36rSq4SycOZsfuqDozOXSr54RGl8jeuoxUqkDPS2LsRbTawy5JugkF1kuTkCm2RJnpsbsqPx+MJspmNc3L41E/Z+2KAC5ascjbvoBLPGTlCN1FtSfhUqnPlm2ZwOTMXl0p3VRbzikFRuVrj5Yv0VsmzKSv+XvK6FCjbJ+Tg/klkl7b28MKbfxe3q+QtG5YdGaTRKGbsPl5hdO5SyQ+PKHW15PggNcgp0W7as8epauDUNHSRWjIUqF5I8XIFaVoZaWRPLnDJ0fVw7GQmRdAPl56sgbdbMiKn1KbF48PiHhhU58rezibImTmPi1fWj8c+rSGwVQE2Xr5I79pc9W9ch3YB9W1pFolWVZ6ubMAhmN/ijSp5y4aN4T+YGVHJYHCbSn52RKn7XnJ8kBrklPWcdMZZo4xsjwjpJhjUTzpOrtAWaeIuvYvJCWtP1AxR7+e690KyvOftlhSCk8/U3fwBkAiBQS9ni8iZuZyopM21+8qOWgXYevkS3Z0tdLVGJceH1p5Lf2bZl76lov0GYe7jfSp5tZg+Ve6RdoOYsfeqDgzPbSr52RGlqpYcH6QKOWc7SbY3ZL8dZDoS5ldqyVCgfiHFyxWkcWWkkX1q+Fl7tN1Y2bUhh07XSpPQa7zfkjOx+38odWBxDwzqc2VXZ1uRU7MxQ46rDZSAk++krgBlT+3lS/RWydW15NUOaW8zh9YS/ekNr81fXBe9lXlI3KeSpVXNMBnLjCyhgkEYk/eo5EdHlKpa8vx3BLLMzzghm3LONuecHTO3fyhIN8EgTDqVQ8TJFdoizeaYsmNjTS13E/168TQc/K6Xkh0L621l+zIN07eTJQOrEV7u/zg0jEn4TPo424acm5UYa6xJJfh6aBeh1iCUdkY91Hj5Et1rc6GvNSp5C3U/p6fOBn3dTNt1ZMeQzL28TSWvlqmxwVBmRCWDwX215EdHlOq/l5wnZ6E1Ah/Sti3jrpyL+hBUMrVkKNCwkNLuCl8T8s8dbZFG9qYRaL3MwWfXy5zjwZptnvIH2fli+Ji425JqJrk91dCBqA0W98CgIVf2ClsH5Nx8M2mQNlnve+j+Fv2yYevQT9lXe/kCvVVHdS15J4aPTx3CxcL5ObYzdke25rJjTOYRcZdKbrPBUGbkE9dgcKNKfnJEqfyN6xJZC23J+DZ/5TLu0Qivj3QTCrQkSa2usESPRH62RZpMbrSp4ZPjb53cJ5xbUnx62nid1yfeYMlaZ3Oy5GMCURuUC8CgJRHycrY9c5OS1+lhaHffY9jKRLn9ZWTPQuPlC3R3ttDZKpW8N9I/X/LYu8CuJG97s84nfO2av5Yw3s2dKnlvyAyHmWwkMzI5gMGNKvnJEeXGWvJhQpojz+8uQR/cXUPXqSVDgaaFlDZXiK0Tx2yLNPsp/d/ltvv7JunA7lpy+d/99Y8evqaVrwe4HpbcP1eG18JiF5osCZ9IU67s5Gx7pM059uzYueZy1xC3ZEfgdOo+yi1Ra2q/d+9l18r+8qIxS5fP01t11NeSk3D3s31RbkaJ4fuJ4kTPh65g7vk9Knk/TnIcrTOQGVHJYHCnSn5wRKn7jesiBQvJEY2xFw9IN8GibdKZB71O4gprOEnn67ZIc8qNTiQn7PNNhWM/47Wrk8o8HSxZtszC4CFKg0QIDNo+dzk7gk5L2NphtzmFobOiSzp/8uWff487zv08X/7UvN42bZa8gdDdir+XPFMMeOqyRvaM0QPMPA5vUck1IvlsnnHMyOQABreq5OdGlFtryYW0e/Q6TXih1JKhQNtCSosrbNFEduxoizRr4qqgnPCdvfrEsZ9rwiDbr/B+S5aec2X0GKXA4h4YtOXKXmFrQ5qUlHT+phNK34venPaz9fI5equOllpyaSr4ySwHZsza85GruE8lV00bZ/sMY8buqzowOmFg3qeSHxtR7q0lZxffhi/TkG6CQUiSGoZIgytswUR27GmLNPmMUM8FsnnAOZWS3S6e3Jhuvm7JqprA+EEqpXFMwufxdmc7IU1KKvn4gekj6nmNCrD18hl6q+TZlNUqOTsV5B9BPWP8qHibSs4Pmz2JPUcxY/fxCqNzby35sRHl3lryhBZZHuCqQSVTS4YCzQsp1a6wJn3q0cZIk5nacydkcqlzT2LV2cWV323JOpFMLRn+IM0VJaewFZE2hhzNRK1c2MpErWxPGi+v07s211ZLnlhf0I5cIXkmXU4oNh+E+TFvUMmV00Y6JAYxIyoZDO5WyQ+NKHf+xvVCGppb1mt7QboJBu2TTq0rrNNx5nBbpNE+Rl1ywbSX6vWXZi4hLliyzdles6RiEI0HhO8zJEJg0C1sCTVtJtQvfxROUqJWKSy2Xl6ju7OFPreo5NRKZvePdoo/pjY280P6q+RKkazadAgz8olrMLhdJT8zotxeS544huavRySf4VVSS4YCVxZSKl1BSiPZKa0x0pxTQqv9sZfZZHO6qk+Me7MlT9bIQi0Z/h5XtJ1T2JpZ2lREjnPUslatTlHLesjWy6f0VsnNteTAt/zZgp+fygT1+yue4BPs72ceCFdU8p0MYEaWUMHgqkpu4nkRxeF7yRVMZlns8gyJPEG6CQbXJp06Vwh/caUYQ1ojze62NeJvd/lCN7+d5tyulvxTBEsStqDAtUSoj7N9x7uWbxtpVYCNlz/TvTYX+t6qkj+AIVXyAKCSweAtKvl5ONSS/yRh9qSWDAVYSPECS3qBJcGAXNmL3pa8VEv+AFDJOt1XdWB0guegkhPeU0t+HqSbYEDdzgsSdy+wJBiQK3vR3dmm+1f/veQPApWsw+QABtSSVagl6wSVTC0ZCrCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWcXhN67/JKSbYMCk40WwJM7mAWMSDBgiXnSvyk/3RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdY0gssCQZ84tqL3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXdLTvdHJaegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRe/aHLVkHVSyDp4PBsFzUMkJ1JJ1SDfBIEw6DBEPmL69wJJgQLnAi+7ONt0flZyCStbhE9dgwOSgQi1ZJ6hkaslQgIUUL7CkF1gSDFhI8aK3Jakl66CSdfB8MEAlq/Ab1zqkm2DApONFsCTO5gGWBAMqSl50t+R0f/5ecgoqWYeEBQxQySrUknX4XjIYsJDiBZb0AkuCAbmyF70tSS1ZB5Wsw/oYGKCSVfhesg7pJhiQbnqBJb3AkmDAEPGiuyWn+6OSU1DJOng+GKCSVagl61BLBgMWUrzAkl5gSTCgouRFb9VBLVkHlayDSgaD4Dmo5ARqyTqkm2AQJh2GiAdM315gSTBgiHjRfb1huj8qOQWVrIPngwG1ZBVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJevwKRIwQCWr8BvXOqSbYEC66UWwJM7mAZYEAxIhL7pPANP9+Y3rFFSyDgkLGDA5qFBL1uF7yWDAQooXWNILLAkG5Mpe9K7NUUvWQSXr4PlggEpW4XvJOqSbYMCk4wWW9AJLgkFvbfd36O5s0/1RySmoZB08HwxQySrUknWoJYMBCyleYEkvsCQYsJDiRW9LUkvWQSXr4PlgEDwHlZxALVmHdBMMwqTDEPGA6dsLxiQY4GxedK/NTfdHJaegknXwfDCglqxCLVknqGRqyVCAhRQvsKQXWBIM+NylF71VB7VkHVSyDp4PBqhkFX7jWod0EwxYmvWCCqgXjEkwYIh40d2S0/35jesUVLIOng8GqGQVask6fC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1sHzwQCVrML3knVIN8GASccLLOkFlgQDEiEvun+Cdbo/KjkFlazD5AAGTA4q1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOt1XdWB0guegkhOoJeuQboJBSJIYIh6QuHvBmAQDcmUvuoet6f6o5BRUsg7TLBhQS1ahlqwTVDK1ZCjAQooXWNILLAkG5Mpe9F5voJasg0rWwfPBAJWswm9c65BuggGTjhfBkjibB4xJMGCIeNHdktP9+Y3rFFSyDp8iAQNUsgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW+VTC1ZB5Wsw/oYGKCSVfhesg7pJhgw6XiBJb0IliRsQQGczYvu6w3T/VHJKahkHTwfDFDJKtSSdaglgwELKV5gSS+wJBiQK3vR25LUknVQyTp8igQMguegkhOoJeuQboIBdTsvSNy9wJJgQLnAi+7ONt0flZyCStZhcgADJgcVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpW4TeudUg3wYBJx4tgSZzNA8YkGPC5Sy+6W3K6P79xnYJK1mFyAANUsgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFb6XrEO6CQakm15gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMKCi5EVvS1JL1kEl66CSwSB4Dio5gVqyDukmGFC384Lp2wssCQYMES+6W3K6Pyo5BZWsw/oYGFBLVqGWrBNUMrVkKMBCihdY0gssCQaoZC96W5Jasg4qWQfPBwNUsgq/ca1DugkGTDpeBEvibB5gSTAgEfKie21uuj+/cZ2CStYhYQEDJgcVask6fC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1um+qgOjg0pW4XvJOqSbYEC66QWW9AJLggG5shfdnW26Pyo5BZWsw+QABqhkFWrJOtSSwYCFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE6gl65BugkGYdBgiHjB9e4ElwYAh4kX3qvx0f1RyCipZB88HA2rJKtSSdYJKppYMBVhI8QJLeoElwYBPXHvRW3VQS9ZBJevg+WCASlbhN651SDfBgKVZL4IlcTYPsCQYELa86G7J6f78xnUKKlkHzwcDVLIKtWQdvpcMBiykeIElvcCSYECu7EXv2hy1ZB1Usg6eDwaoZBW+l6xDugkGTDpeYEkvsCQYkAh50d3ZpvujklNQyTq9V3VgeJgcVKgl61BLBgMWUrzAkl5gSTBgIcWL3paklqyDStbB88EgeA4qOYFasg7pJhiESYch4gHTtxeMSTCgouRFd0tO90clp6CSdZhmwYBasgq1ZJ2gkqklQwEWUrzAkl5gSTAgV/aityWpJeugknVYHwMDVLIKv3GtQ7oJBqSbXlAB9YIxCQYMES+6W3K6P79xnYJK1sHzwQCVrEItWYfvJYMBCyleYEkvsCQYUFHyorfqoJasg0rWQSWDASpZhe8l65BuggGTjhdY0gssCQYMES+6rzdM90clp6CSdfB8MEAlq1BL1qGWDAYspHiBJb3AkmBAruxFb0vOteT//a//81//h/+W/5b/LSpZNvhv+W/6H58iAYPgOf+zOE4ygj74v7mW/Hve++n//df/Id0Eg5Ak/Us8eeU/+R+WfPk/+d9iSYAsS648Dxf+u/xf+N8QKhmggf+WsQOgIKMEoBoZOgAKMkgAxkLGJ4CCDBJwoafqQCVDK6hkKCCjBKAaGToACjJIAIaCRAgKyCgBF1DJ8CSYHKCAjBKAamToACjIIAEYCxmfAAoySMAFVDI8CVQyFJBRAlCNDB0ABRkkAENBIgQFZJSAC12dLXTg3//AifCbMv/8r2zASvhFAn60AgoEz/l/MlxgJfyW8z//IxuwEiIKv3ENBcKPt/y3DBd4heBsWNIDwhYYzENEhgu8Qm/VMdeS+UtQCfwlKJ0wXvmNaygQhgh/CSph/ktQ/L3kBP4SFBj0/onTvwOW9AJLggG5shfdLTndH5WcgkrWYXIAA1SyCn8vWSd8ageVDAX4Y2FeYEkvsCQYkCt70duS1JJ1UMk6eD4YBM9BJSdQS9Yh3QQDJh0vgiVxNg+wJBgQtrzobsnp/qjkFFSyDp4PBtSSVagl6/CJazBgIcULLOkFlgQDPnHtRW/VQS1ZB5Wsg+eDASpZ5f+GiEItOYF0EwxYmvUCS3qBJcGAIeJFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmF7yXrkG6CQZh0GCIeMH17wZgEAxIhL7qHren+qOQUVLIO0ywYMDmoUEvWCSqZWjIUYCHFCyzpBZYEA3JlL3pbklqyDipZp/s3BGB0guegkhP4XrIO6SYYkG56gSW9wJJgQK7sRXdLTvdHJaegknWYHMCAWrIKtWQdvpcMBiykeIElvcCSYECu7EVvS1JL1kEl6+D5YIBKVuF7yTqkm2DApONFsCTO5gFjEgwYIl50t+R0f1RyCipZB88HA1SyCrVkHWrJYMBCihdY0gssCQZ84tqL3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXfVMd0flZyCStbB88EAlaxCLVknqGRqyVCAhRQvsKQXWBIMyJW96G1Jask6qGQdPB8MguegkhP4XrIO6SYYhEmHIeIB07cXWBIMKBd40d3ZpvujklNQyTpMDmDA5KBCLVmH7yWDAQspXmBJL7AkGJAre9HbktSSdVDJOt2/IQCjg0pW4XvJOqSbYEC66QWW9CJYkrAFBciVvehuyen+qOQUVLIO0ywYoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBAMmHS+CJXE2DxiTYMAQ8aK7Jaf7o5JTUMk6eD4YoJJVqCXrBJVMLRkKsJDiBZb0AkuCAZ+49qK36qCWrINK1sHzwSB4Dio5gd+41iHdBAOWZr3Akl5gSTBgiHjRXXVM90clp6CSdfB8MKCWrEItWYfvJYMBCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJV+F6yDukmGIRJhyHiAdO3F4xJMCAR8qJ72Jruj0pOQSXrMM2CAZODCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usk73bwjA6KCSVagl65BuggHpphdY0gssCQbkyl50t+R0f1RyCipZh8kBDFDJKtSSdYJKppYMBVhI8QJLeoElwYBc2YvelqSWrINK1sHzwSB4Dio5gd+41iHdBAMmHS+CJXE2D7AkGBC2vOhuyen+qOQUVLIOng8G1JJVqCXr8L1kMGAhxQss6QWWBAM+ce1Fb9VBLVkHlayD54MBKlmF7yXrkG6CAUuzXmBJL7AkGDBEvOiuOqb7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBIMw6TBEPGD69gJLggGJkBfdnW26Pyo5BZWsw+QABkwOKtSSdYJKppYMBVhI8QJLeoElwYBc2YvelqSWrINK1un+DQEYneA5qOQEfuNah3QTDEg3vcCSXgRLEragALmyF90tOd0flZyCStZhmgUDaskq1JJ1+F4yGLCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWYXvJeuQboIBk44XwZI4mweMSTBgiHjR3ZLT/VHJKahkHTwfDFDJKtSSdaglgwELKV5gSS+wJBjwiWsveqsOask6qGQdPB8MUMkq1JJ1SDfBgKVZL7CkF8GShC0ogLN50V11TPdHJaegknXwfDBAJatQS9YJKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlkHzweD4Dmo5AR+41qHdBMMwqTDEPGA6dsLLAkGlAu86O5s0/1RySmoZB0mBzBgclChlqzD95LBgIUUL7CkF1gSDMiVvehtSWrJOqhkne7fEIDRQSWr8L1kHdJNMCDd9AJLeoElwYBc2Yvulpzuj0pOQSXrMDmAASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vEiWBJn8wBLggFhy4vulpzuj0pOQSXr4PlggEpWoZasE1QytWQowEKKF1jSCywJBnzi2oveqoNasg4qWQfPB4PgOajkBH7jWod0EwxYmvUCS3qBJcGAIeJFd9Ux3R+VnIJK1sHzwYBasgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpW4XvJOqSbYBAmHYaIB0zfXjAmwYBEyIvuYWu6Pyo5BZWswzQLBkwOKtSSdaglgwELKV5gSS+wJBiQK3vR25LUknVQyTrdvyEAo+Omkn+/5B9/AmrJOqSbYEC66QWW9AJLggG5shfdLTnd/w0q+esnlAz++efr6yHVlLeo5N/vr8UsPz91gmAzY690m8kBDNxUctEpvv59WER5Ty35N0aUr6csMQSVTC0ZClxbSFkn1xddIU66P1+/rbPuV+NUefsq2hiW7Je++MHiHhhcy5W9nO1mtqhY48vNSudIb9VRW0sOzWo5P48YKPKICNmuko8PWTEW5lvssE4ZwoyoZDAIg9NDJf/mPeI/R1d4hE5u/43r5ojyewwpz/BT0k0wuDDpeLnCeZJucuDf6cYtJ0wOn3r5uQdFrLsFSzY6m5slm9MXaZnS9BJugkQIDLqFrebEYUIap2jOdvJlSyifQ1hdj3Z0d7bQa2eVLKcI30eLTvw8IKudX2yLSj6NBHMgfEvDPaWBMIgZmRzAwKmWPKWYGSf6fWREaa4lt0YUJZ9uno46EF4mtWQo0L6Q4uQKSaCZaLhQY/u504msTh8lj3mvbpa8kL5oGdLCCNGexT0waP+csI+zna5SdYkWZ1MiUukerUpHobfquKGWfLSYGuRHWAwsM3e7RSXPz7VhDU1t/p3IGmYUM/JdCzBwUsmTh+hOpLrC+DK5+XvJ83NtWBElXTuYeICrkm6CQUiSWoaIkyvkMsdaJ5Ze1C7h/S7Nz46uhrsMckqe1nTTK6hcSV/yD94h70loHZPwcbQ6W7qSNHHB2eTMiJU4zNQ7mxoSCj6pN2/z4e6qI/TYVSUfnyZjo66PXMM8ahpU8vk5y0Mzv3KTMcwwZuy9qgPD46OSgwOqTpRxheEzltZacltEyYaU4ZcPwnNSS4YCjQspr6pbIRNoJup8au2GbFvE+11XyfYDOlmyNahkTFlOJKSRwggxjcU9MGjMlZ3CVmvisCBtFU7OlutlximzzZtURG/V4V9LPrzU7EwzutJqVMnJYCgOzbhqrKEaZhwzopLBwEUlzy6iOVHITlRGH5WNteQkRpQnu3xIaZ1k3w3pJhi0TTpOrpCdcydqOrN2o/Ku8X7na9er5IpedbHkxfRF2iiMENJIhMCgLRHycrY2KRKRtgrHu+d7qXaz0LzFe7o7W+ivp0o+PMw+PP5MyD8Dg0eYRpWczAPFoXlofTSLapiBzNj9sw8wOi4qeR7jihMVXGFwqdVYS94/2UwxohymxpNdRqi8FAgqmVoyFGhaSHFyhcT/DlRMgdKyLkndiWHZXqlXyRXZdA9LXkxfkmx/Y4SIxuIeGDRpO7cZPAlcNQGo1tlKvdS6eTh+at6gI3qrDvdasrSf2VYS4u9/7z56P8KCYJ42lZyMzOLQ3M178dfh9j8alxhmJDOyhAoGYVS+qpIXF0md6MERpe03rtsiypyzLawRRbaHd1fSTTBomnR8XGFfBFlCzffh92dNR44OXHnL9X7Jhfd3LVIMEEKwZLWzOQWVYszOC4DCc5vGfwNNloRPpEnbec3gjYmDUOtssm9C8eX0qyW7y1YpnRzdVUfobYVKtgiXCexfybbwsDPHtnOEFcEs8/tt+fWuyPxoxaG5WWD/4re959g7lBlRyWDgUEuWxCpxoi3hel5Eaf6N68j8aOXJbp159q6p7hyP0E1qyVCgZSHFyRWk/cTulO9d1md48hqUKjPB2MN2X137JNtFOljyavoix0thryctloSPpCVXdnK2A3JyjQdVNt06pPry+fTd+pjsCWztq/2nt+qorSUbRPMdHmVdHjnMFKvpej62yY0qeZ3WThPoOgRP5w5lRj5xDQYOKnke2IoTrS7ywIjS/BvXkfnRihElY4DVWkOvHpBugkFD3c5yhUoHXNufTtgyvHKsWbvReL/2CLb2qOpODemmkyWvpi+xQe1t3g3lAjDo4GwH5NxC4hCpdTZpdn6qtZunRKNV6WRxSClfI3T2ZZWshurVRifbrY1HTt7uU8mrQySPr0+VY5mRyQEMXg9pccifnejREeXGWrK0SBxTDyiDETpJLRkKNCykzON9IucKjZdJHHb7gGHRlaVNbRq4BjbZbqDNx99vyasxO54nm8PB4h4YNFSU5qE+8aKzHZFzK2JQpbNlY008cLxV3sXbglZ/1eFTS1afOu5MFihWnSjbIzKPm1tUchyR6VtfR5VsL4xlRlQyGLyskteBfXaiR0eU+2rJ8elTv4wGq5gou0G6CQb1k46TK6zSLvXXNdSUYk28WeVMuV6zPTysOUPdqW+35OWYLQeHjVwkQmDwfmc7Un9qZUtplnqsrlxalU6e7s4W+vqqSl4nFdmeydtoffXF5di+zL2/RSVnpw3dJQYzI5MDGLyskudBHTg50bMjyn21ZGmgRJQ4G43ssUElU0uGAvULKfNon3jRFaSt6nNrhpf35VbVG6PXBTeVMwvR4cDbLXk1ZsebVFrw/bC4Bwb1ufI81Cd8Z3A51Q4Nlc4WfVm5YDx08OXo4Mpl46HKsNVbdbjUksM1AodnjoaQzT3rRCPbAzK/9ltUsjRQn10O7QfEYGZs+BQJfCZhRL6ikuOIT5woJCYB2dzzgIjS9hvXO+bnKkSUmJNrDRpnox6QboJBdZLk5AoFaTdhXuiNIjn2tDbuBUtWOZtXUIltZXNPMWb/p3BsCKotCZ9Kdbngphm8+swYRWQzR6mZHDrcS/aV2leGvO6qI/T1RZWsRvloUvUdxYPjln7mHt6hkuPcoDYQS+4MOZoZe6/qwPC8WEtec8zzoH94RLmtlizH9TlOjg3ssiHmUUuGAtULKfNYn5DNI3KswhXKmWmcwbMXUvOhPK2iescqNGvjyrsteTlmRxvK5niwuAcG1bnyPNInZPOIHKsMJnvkzGzisFLpbNJM7Yn48v5Yo9Ip0Vt1ONSS9ShftrwctF9gL+a3fodK/gp/i3tCnRJTo41mRlQyGLyokucRvXAc1w+PKHd9L7m0EL1lorI5IKSbYFBbt/NyhXKkWSOUbJ6JZ1dOky+I5Nl3AtUzcu30/R5LykHtJoVDY0AiBAa1FdC7ZnA50fahyobizGozpZf/aVM6Jbo7W+jqaypZnxXUnSvDJ29zB2/5xHWJ1CyyYxgzdv/sA4zOayo5RpPA0Ylk51Mjyl215PjgmSRbjl6LR+8gvHBqyVCgdiHFyxWkYW6eK4eaVtWrp09VrKXkaoE9liXzhoxPNu5Hg1jcA4NabXfXDF57Yq2zSTO1m/EasmlSjqFnequO12vJ8XmPT2G8+WjU6vD+bub+91fJw5mRJVQweEklrzlm4OBET48od9WS5XDOKSUJH9dnSTfBoHbSmUf6665Qru1sx1VnfqNIjs/bEFXebMnLMXv4ryXPliRsQYE3O1vCcp4tRWqdTZoVw55smiRKp0h31RG6+pJKDhcIHI1nvdrl8EUx+Qbmt9hfJQ9nxu7jFUbnFZV8EMnHYV3pCi/+xsJ93FRLtlYH2qajDgSVTC0ZClQupHi5wvfXQu468T6qM0uYqp0kW0X1nvg8DfPxmy15OWbLgWHTQxb3wKSyAnrbDC7nmU7U2E4Ne62dbGvfW3W8XEvOzAr63o3Lr/5NzP3rpZI3qy3bA5mx92cfYHjCeLyqkmM0WTg4kex7bES56Teu40JwVn/L8WsB6Q2QboJBZZIUI8DdrlCqJa8BTLYNVpF8oU9XBHawZIWzeVlSmjXH7JKFB4FyARj0DluV51U7m7RTrycPUe0Rbe27q47Q1xdUclwIOQW6uDv7horrsQMwv8W3q+TzyeOZkckBDF6oJa/RZGE/7GMsf2xEuamWHNNy2Uyx6jm9Cf2jlgwFKhdS3uUKOW030apcY5evdCmem42ICu+15OX0pWDhUWBxDwwqc2UnZ0tZTjPjQ7WzlRq29nFpXhu7equOV2vJIVgETo9rW14atIT4dzI/wLtVcpw01il2PDOiksHgukpec0xhP6ofH1Fu+l5y+eiEbbi+kG6CQZh0KobIPMzf4Ar5y7xTJK/3ku0qKqfv5cIvW9L+wqM0ON9Idv98fYU/CfL1NeDKJ4kQGFQmQvNQvyNsyWn5Cy9IM9vZYj+U4BYPWfeKJEqnTHdnC329rpKjdc6PYC8tLA2qzfpu5gd7t0pO3GE8MzI5gMF1lbwmjfL/70f14yPKPbVke7pJgspghBdLLRkK1C2kvM0V8qFoDWCybdAqqg/IqW0h5b2WvBqz4/13/IwW1lncA4O6XPm+sCWnGZ5T72xrS9neEQOfbJo0PlJv1fFiLTmcHTi/Yjs+Dp68zd17s0qOk+ZmtfHM2P0bAjA6l1VyHMv/aE70+IhyTy05xozChaXFlYj0Dkg3waAuSXqXK8Q4k/ZoC2B1SOtL/cn3osR7LXk1Zq+rB3sG08nBkoQtKFCXK98XtupOa3A2OZg+VBTJtcEo3rO2fXfVETp7WSVnrSP7Cy9o8Jx27t57VfK6VLP5i+wYyIy9V3VgeK6q5DVcf2vjXtl1YvCIck8tueKhpcWFiPQWgkqmlgwF6hZS3uUKMelJrrILYFW05pZ7Wu8lvNeSdiP9TnHviaHyDhb3wKAuV74vbNWdlnE2bWyvCuX0VDGQ1fZQUTplequOl2rJa6iW7ZV4oGCFiiY9mcfOW1XyasxtOAxoRlQyGITheEUl77LP7V+R50eUe37jWoxWcsmKJj0h3QSDuknnTa6wztOyvbIe+P79mm/0Uy5/Smem3nz9LO0bvn8bT27MM4IlbWerMFNFk+sxW3amXFlkvAkSITDoHbaWs6wQIa1SFGeTI6euxFhU28E1UFY/UHdnC729qpKjeZL3ULE+EtcTBgp8e96skn93KzqbRQY0I5+4BoOLteTVA6Z/y792TvT8iHJPLbl4cOHiHPsuQveoJUOBuoWUeZTf7wox6UkuEg+sP6sQ+Ml6/JYryv8/U5k3rNUY2a7lrZa8GrNXy6SME9tZ3AODulx5Hte3hK3lLCOkNDnbGnZ2ce13i181NQBd6Rj0Vh2v1JLj86b9r4iPde+wG/MTvEUl/359hYi7shtqA5qRJVQwuKaS12gdxr/8czeonx9R7vlecvHgQo3pOkK6CQZ1FdB5kN/uCmtOKNsr8dpncrOlHE6oSh2lbXM8qZu+l2u/bMmrMTtnycCVAHoLdWMSPpi3OpuCnFW6cquz7Vr//IZItXxqZqF8o6LSMeiuOkJ3L6rkcGogb0zZVJEmlmk7MT/BW1TybpgF9pPkgGbsPl5hdK6p5HkUT8wDef/vhedHlG615BrTdSTEP2rJUMCtAvq6K2Q/LdhaAD1N+zsqptf4HM0z8VsteTVmx32/c2L5vU/Er0XQO2BxDwweoZJjo0pny4ct+1FP5zZ4cm/V8UItOT600n05VHywpYnxDrsxD8wOKvmw4jCgGXt/9gGG55JKPuZ9srEb1M+PKLfUkmNuXrruxTn2XZBugkFVkvQWV9i0sOyIFESy6rrHWf9I/lPawnqz5nDyVktejNnL7Q8331tLdvWGcgEYVCVCXs6mIGcV86FmZ4t9SbDTrmPMa4ld3VVH6PD/yr+bKH01piY+1rTpxzwY3q6ST8YY0IxMDmBwRSWf8j7Z2DnR8yPKLbXkmu9i17TpSFDJ1JKhQNVCyltcYZ2sz964HlBJOr/GOx2jf/Fm9UlG5K2WvBizQ+p1frLvzb6DhHcW98CgKle+MWzJWcUo0e5ssTNHfipE73bZVi/urTqu15LDiQHtJVyMjwPRSSUfx9qAZkQlg0EYjq0qOZwTELc5bgWeH1Fu+Y3rmpXomjYdId0Eg6pJ5x2usM7V594Yqjdx3vVCGaSZzlrOke0GgiVNZ/Oy5MWYPW0qV90s1qgVboJECAyqKqA3hi05qyhFpuOtzqbGupqu7YNejare6O5soctXVHJ8ZLXzSuxLqGnTjz4q+WSOAc3I5AAGF2rJ0QfiyJLNv6eSr2R480NlIsqNK9HvIrw1aslQYJRacgxTSYg51FfkK36lb/jtD/18zc2/V+0bKMWwNUu98BRPqCVnLpo1fh9Y3AODqlz5xrAlZxkqudHZdj9pfcD8msgx6rW5cW/VcbWWvIZqdU1AiX0JNW360UslH+wxoBm7f0MARqddJSfBRDb/lEru9r3kmjYdId0Eg5Akva0CmmcNU8n5YQwLi+Zd2AnfQ1DaLjRpZNk3sfukYykhjq2uxLmqdNPLkhdj9t6Ce1brlO75NqrGJHwyb3U2BTmrKEVanW3dn2JKntO5DfGru+oI/b2gkuMT632Xo8UHq2nTj/ep5MD+p+V2BhnQjL1XdWB42lXyPIInVqc5b/+FiEItWSe8NWrJUGCMWnI8OT19O3L+IKGEpIm9++p7J7YL5T9NvbZpzJlnnlBLzhLNNoQ4ZXEPDKq0nZezKchZauJgojvbFrkmfn4Om1VOnFE6Br1Vx8Va8rpKKtsn4mHZVBFr9Xz4Au9VyRPbQvJmkQHNiEoGg2aVHEf+Nq5kx86Jnh9Ruv295Isr0e+CdBMM6iadeZDf6ApyrnKHtZScdnKd1XeRK/ZC6cd2KPsYcrz4nFneaknvmL2uD8h2V0iEwKB32JKzLgUK3dnWQDc9mFx2/02ROn/QlI5Bd2cLvW1XyeGsQOYN1MRHaXLtHd7O/ATvVMm7CXU9d0Azdv/sA4xOq0peM8NtEpAdu0H9/IjC30vWCTMvtWQoULeQMg/y+1whn9utCaU2Maaz+rZLiQbrtXJ9jI9wzZ3fakn3mB0NV9f6XuosCR+Mm0q+GLbkrIveojjbGnsOj7X7okhleqPExDK9Vce1WnJ8zFzP3ePj25mf4L0qeRs8sj2iGVlCBYMwHBtUsiKSlUH9/Ihyy29c1zxzjek6QroJBr3TzcA6OacdiVfVu5jM6rGjejBYw6H+HFq0bCBY8rkqOV6wrvW91FkSPpi6csE8om8JW3LWRW9RnE32JMFnW9prlcmybdFddYS+tv69ZDNUR7OVjCZNRoh4CvMYebNKXgdPPHlAM6KSwaCxlhwH/X5Uya7doH5+RLmnlizWK7nkxTn2XYQnoJYMBeoWUm51hXimdq4cyGRDawoZHTheKtPRGA/1TmrRsoG3WtI/Zld07F2wuAcGdbnyfWFLzrqaDyUdi7EndegkxlnES1W27606LtWS4zNmOx5ldGHBs6JJT+aB+W6VHE+Odh3QjHziGgzaVLK64ia7dk70/Ihyz/eSK+bYiiY9Id0Eg7q63Z2usEYpxYPjsdyUH7OleDxuy+aZNeOU7QNqtGzALXGvsaR/zDZM904oF4BBXa7s5GwKy1kXpYjibLKtOesal2rLANK88pG6q47Q10aVvK6ryraCNCi8oIvrI++ij0o+D0zZHMiMTA5g0KSS9fAq+/bjXtl1YvCIck8tueKhpcW1iHQ/IeZRS4YCdQspN7rCqlw1B473zfq2HI/T5mkzoXQ9OXTZmd9rSbtRxZ32NDa/Exb3wKAuV/ZytpSLp0XOHYvb6iNF5VJ7s0SCF+mtOq7UksMpgcICoLQo2EzM1PPZS8xD4u0q+Xz2aVPh3WZEJYNBk0qO0fI4pmTnftwru04MHlHuqSXbc2xjuebtkG6CgVe6edkVwhid0Xohh/L3PWaEsZvZSBZ7qTQoJqo1vNeS0sgvZsfVigFiGYkQGPQOW3Jawf2KnL8wcQxjJ4qfgNGQ5nWd6+5soattKllPbI/Yr37wnHZ+gG4qOVplPDMyOYBBi0qOA/w0wmXn3okeH1HuqSXb8eY82Y1GUCDUkqFA5ULKPMzvcIWY8eixRY7lb3sMXXYgkwbpBWO6fF0lvteS7jF7oFjG4h4YVH5OeB7Rd4QtOS1/4TLxtjHYyGbmiWxfPyLN6zy/t+poryWvoVq2VaLN8uFcGlx9hXczP8D7VfJp1hjPjN2/IQCjE8ZjpUrOpX2ydz+qHx9R7vmN63g075Ot09e7Id0Eg8okaR7mN7hCPE0/0a70HEOXLQyXBkqLqNavh7hgyXqV/Koljw+uIQ1qH+hqVe0GKi0Jn0vnsNXqXGeis4k4j5uZy7W6ZtP6WHfVEbrapJKrQrW5/HH1zb+LuX/vV8kns4xnxt6rOjA8DbXkGEvOI0p2753o8RHlplqyOdssx68GpPsJD0AtGQpULqTc5Aox/8tkgHal59jC7GW2xdoR2b7Aey3pHrNtW78NFvfAoDJXvilsvTzzR2eTqGf4aqtrNrl+b9XRXEuOT2d0Wlpl35AMjWFz2vkxu6vk8cyISgaDepUcR3syfGX3Ydhr+/aMHlHu+V6yOdsYS8D9Id0EgzDpVAyRe1zBEMnr8bxrH1uYSXG2xbL7WhARKqdvL0tazVpjttWvN0IiBAaVidBtM/jV84RTv6xuyuHauzW5cndnCz1t+XvJoX3ACNWVNh02zsz976+ShzMjn7gGg2qVvOafSSyR/QcnenpEuamWbB2OZhug/KITMmVqyVCgdiFlHujerhCVXC6yxCJKfsY/lllsZZhRybH7r0S4N1vSO2Zb13sjLO6BQa22m4f0DTO4nJcPTGVOzlbpy7V3a3Ll3qqjtZYcY7zVZ2OFNdro6hu8nbmD/VXycGZkCRUMqlXyPHQn0tGrHXh6RLmplpzLqSPL0SESSx3STTConXTucIWY8OQ7IMfzgec4qZ+n+BRpcLpgfk2xgTdb0jtmS/uaJ7ibYEnCFhSo1XZ3zeBy3tWMSE6P3bLilhyuvZsdBnd0Vx2hp/UqeQ3Vsp1H2mUCSZx7ZHM85pd4g0r++fn3Z/p/2cNyumyOZ0ZUMhjUquQYJ00kPMnWUyPKXbXkaEb90nalqzdBJVNLhgK1Cyk3uEIMK4VJT5rkGxwTwtiNvNiVBqd+xp685MnvtqQ0dIrZMfscIZixuAcGtbnyXTP45RNnzs5mxK2km61Kp0Rv1dFYS64P1fHV60aVg+Pqrbn7N6hkOZx78OTwaGbs/dkHGJ4wIitU8rrgZiK+9PCIctNvXBtP/h85euXG74F0Ewyqk6R5qHu6whak8meZ+Z4cFwc2pV6Mc7IprD2R7WsES1Y523Kvly3ZHrNLvYuWHiGYUS4Ag35ha0FOzAaaNmcz4lbi6bKdM4Bx+Eh31RG6Wq2SoykqelxcAhkp3OnMT3pHLVmOy+aJ1GijmZHJAQwqa8nzyK1Cxv7DI8pdteRiSIk2G9hlQ/epJUOB6oUUb1fYRHLBcWNSlHPQeDxeQjazclcOn/opey9FkI13W7I1Zk8Gz181XixruXfC4h4YVGu7m2ZwOTObODQ6m2xnvC95htJDGYEhobfqaKslh8aBmlxUmmphPU4+PR/c4G6VrB+PE+rOvrJnFDOiksGgTiVHR6gg+opsPjSi3PW95DVoaM8ecrnAuIsHpJtgESadqiHi7QpyipHMSZtMPpgcjp3MXFM/XHqyBqqnby9LStPKmD3vyq4DzK0nii/jXZAIgcHbne2EnJlzl1Znkx16T9JHaFY6Bbo7W+hqrUqOD17V4cIiSNmAQzC/xRtUcskh1nljP98OZkYmBzCoUsnrUK8gju9nR5Tbasnrw6cXTxeExyP0nloyFKhfSPF1hXg1Y8aLzfRW8ejqv2tP1GCg5QC7vReS5T1vt2RTzJanzATJ9W1kjr+XekvCh1KfKzs52wk5M5M4NDtblC5qV+TQ7mbNSqdAb9XRUktufDRpnL6lov0G4S6VnLfKRDpvTMi+QczY/RsCMDpVKnkeuZWsI1+2B3GFRm6rJa9Pn8Zl2f9qbn0rpJtgUJ8kubpCLOOY95Zmaru1R9uNlV0bcuh0LTUzuMD7LSmNa2L2ml+qmfv6Nl61gQ/BkoQtKFD3obqAa9hakVN1f2l3tvUMJYCsolq2A7JHvX9jPOuuOkJfK/9ecuOj5dZMV2tfefPvYh63d6jkdTylo1M/NJYZe6/qwPDUTA5fP0XmcT2xbK0D/9ER5b5a8ho4zo6Z2z8UYUKmlgwFGhZSHF1hTV3T3PXEFq9kx8Z6kZ37rmEsDQe/66Vkx8Ia4GT7Mu+3ZEPMXp9dC5PbwTGCfIMl4TNpyJWdnO2InKsnDhecbd2bjPv1yL6f6870BoVDKr1VR0MtOV38M9Btsc4bPR/b5DaVHBukTdb1m5NhhjIjKhkMwqCsW0LNEi4xkTjRkyPKbb9xvctEDwbYMu6RFw9IN8GiYdJpd4WvCfnngVXGVbiPNEx7ud73oG/XgHW+9HbPY5dk5+uOHCxZ6WxelqyP2dvqQRLsttu+bgMfSITAoKEC6he2dsi5erMLzradcnqqVbkc28u+9AY5pZOlu7OFztap5NAyUB2mVKtub0B2jMl9KnkzwFYkm9gmyLOBhzJj988+wOjUf9AoyzywFSd6ckS5sZa8M8F2g1zGPRqh79SSoUDLQkqrKyztU79scp9Myrmp4dOcvnVynwPsstPjFBuv8/rE28GSDTF723vMSX93hhwl+WBxDwxatJ2Tsx2Ym2Tj1wVn2x3Z3TnbfrtDpdLJ0lt11NeS4zM39HZnj6/ZTl/bqkO92O7C/OpvUcn74fkjzX53lkpPHcmMLKGCwY0q+ckR5b7vJU/sJqS53Yh5ZQbSTTBoqIC2ukIMH/s0bmY3S+fYnbOfv+W2+/smzru/+hLIfr/2++ZGkfXirwe4punbyZINMftgdEmODnYcJ5g1jUn4RHo42x5pc449kQvOJvtnxJf3J5zb7+4g1zeUTo7uqiP0tkYlr08n21UcbH6k60PbzD2/RyXvFp4D/25fw5xRDDOQGbuPVxidO1XygyPKnbXk4/x1YuzFg3kqpZYMBdoWUuZBr5O4whpOzt51nJN19s5cbp+EplMOcEbXjtVJZZ4OlmyK2ZbZx4nxbZaED6StAjqPb50WZ9thtWl3tqawdUXpZOitOqpryddCdfZFjBPudOZxeI9KPiw8J6iGGceMvT/7AMNzq0p+bkS5tZZcmL+u3PKdkG6CQVuS1OIKWzSRHUKs1RQ5XK4gBbW+7z5dnXLs56X6RIb3WzLQELNLZhkqxlMuAIM+zrYhTfKJQ7uzFaVL2s92paPTXXWE/lao5DgJtPY18yK6PnINd6rk//rOD8/MecOYkckBDO5VyY+NKPfWkrOT7JU7vpUgSKglQ4HGhZQGV9iCiexYyGese47Xy5+je242Bzh8iW9Cdrt48tstudAQs7NmmTBC4FthcQ8MGnNlL2dbkSYFr2l3tnyUO4etmXalo9JbddTWkqNKTtcLDFSzNl/l7dyqkvPDM2uYUcyISgaDMDJvVMlPjSg3/sb1ghZTHuCqpJtg0DzpVLvCWgE+HC2WQDbOzpyZ1HM+n0k4z/2MVWcXVw6WbHK2Fy0ZaYjZ2cT6Z6gYTyIEBs3lAidni0ibUuJwwdkyZ+R6krtBkzN3d7bQ45q/l7zY80JX0xehrjoMxs0qWR+ebeO5ixmZHMDg5lryUyPKzbXkiXXuXLHP6U94mdSSoUD7QkqtK6zq7XBYm5sVEmfWJvWSC6a9VLPTpZmLRny3JVdaYvbhd8xWhtLILO6BSXuu7ORsQk2bC86mrXgVVrCalY5Cb9XR8PeSg3Xkn20c7RR/7Wxs5vF6o0pWRo81DQxhxu7fEIDRuV0lPzOi3Pu95IXjLPs1WGKpQ7oJBiFJah0ila4gZePDlKaldRrKNc+TuuW0p7Q4l2xOV/WJcVfSzRcsuaclZiep+3ih7MqYhI/iSq7s5GwzSxs7BjU723dl2BKalU5Cd9URel2nkid7Xg3V31/Lq/h5RkI7MY+DKyq5he+v5VffJrNUDZwBzNh7VQeGx0El2zwvolyuJTcxmWWxy3h5ZYbQXWrJUODaQkqdK4SMzzWGbLf9rXHBXSArNP92mnO7WrIpZsd7TpccMpSxuAcG13JlJ2drot3ZJumynDCdIbtKtCqdE71VR0Mt+aN4i0p+IKhkMHiLSn4el2vJfxzSTTBg0vECS3qBJcGAIeJFd0tO90clp6CSdbp/9gFGB5Ws8p5a8vMIKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwCJ6DSk64/BvXfxzSTTBg0vEiWBJn8wBLggFhy4vulpzuj0pOQSXr4PlgQC1ZhVqyTvi+ErVkKMBCihdY0gssCQbkyl70tiS1ZB1Usg6fIgEDVLIK30vWId0Eg5AkMUQ8IHH3AkuCAYmQF91Vx3T/qr+X/GGgknWYHMCAyUGFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLeoElwaB7BfTP0N3ZpvujklNQyTpMDmCASlahlqwTVDK1ZCjAQooXWNILLAkG5Mpe9LYktWQdVLIO62NgEDwHlZzAb1zrkG6CAemmF8GSOJsHWBIMCFtedFcd0/1RySmoZB08HwyoJatQS9bhe8lgwEKKF1jSCywJBlSUvOitOqgl66CSdVDJYIBKVuF7yTqkm2BA3c4Lpm8vsCQYMES86G7J6f78xnUKKlmH9TEwQCWrUEvWoZYMBiykeIElvcCSYIBK9qK36qCWrINK1sHzwQCVrEItWYd0EwyYdLzAkl4ESxK2oACJkBfdw9Z0f1RyCipZh2kWDJgcVKgl6wSVTC0ZCrCQ4gWW9AJLggG5she9LUktWQeVrNP7sw8wPMFzUMkJ/Ma1DukmGJBuehEsibN5wJgEA3JlL7pbcro/KjkFlazD5AAG1JJVqCXr8L1kMGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgrfS9Yh3QSDMOkwRDxg+vYCS4IBQ8SL7pac7s9vXKegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgwCeuveitOqgl66CSdfB8MEAlq1BL1iHdBAOWZr3Akl4ESxK2oADO5kV31THdH5WcgkrWwfPBAJWsQi1ZJ6hkaslQgIUUL7CkF1gSDMiVvehtSWrJOqhkHTwfDILnoJIT+I1rHdJNMGDS8SJYEmfzgDEJBpQLvOjubNP9UckpqGQdPnENBkwOKtSSdfheMhiwkOIFlvQCS4IBCyle9FYd1JJ1UMk6eD4YoJJV+F6yDukmGFAB9YLp2wvGJBhQUfKie9ia7s9vXKegknWYZsEAlaxCLVmHWjIYsJDiBZb0AkuCAbmyF70tSS1ZB5Wsw/oYGKCSVagl65BuggHpphdY0gssCQYMES+6q47p/qjkFFSyDp4PBqhkFWrJOkElU0uGAiykeIElvcCSYEBFyYveqoNasg4qWQeVDAbBc1DJCfzGtQ7pJhgw6XgRLImzecCYBAOGiBfdLTndH5WcgkrWwfPBgFqyCrVkHb6XDAYspHiBJb3AkmBAruxFb0tSS9ZBJevwKRIwQCWr8L1kHdJNMAhJEkPEAxJ3LxiTYEAi5EV31THdn9+4TkEl6zDNggGTgwq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GqGQVask6pJtgwKTjBZb0AkuCQfcK6J+hu7NN90clp6CSdfB8MEAlq1BL1gkqmVoyFGAhxQss6QWWBAMWUrzorTqoJeugknXwfDAInoNKTuA3rnVIN8GASceLYEmczQMsCQaELS+6W3K6Pyo5BZWsg+eDAbVkFWrJOnwvGQxYSPECS3qBJcGAz1160Vt1UEvWQSXr4PlggEpW4XvJOqSbYEDdzgsWub3AkmDAEPGiu+qY7s9vXKegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XmBJL7AkGJAIedHd2ab7o5JTUMk6TA5gwOSgQi1ZJ6hkaslQgIUUL7CkF1gSDMiVvehtSWrJOqhkne7fEIDRCZ6DSk7gN651SDfBgHTTi2BJnM0DLAkG5MpedLfkdH9UcgoqWYeE5f/P3t8ry64jaZpw21nXUJdQ2lZaXWpZibWVuoG2qZ4Rj5RmM2mWwicfLc1K65v9CIaDf3DCAYaDAGM9T53s3iRBgvSAO/yFB2OBAbVkFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhvWQd0k0woG7nBdO3F1gSDBgiXnS35NQ/v3GdgkrW4VskYIBKVqGWrEMtGQxYSPECS3qBJcGAXNmL3paklqyDStZhfQwMUMkq1JJ1SDfBgEnHCyzpRbAkYQsy4GxedLfk1D8qOQWVrIPngwEqWYVask5QydSSIQMLKV5gSS+wJBiQK3vR25LUknVQyTp8iwQMguegkhP4jWsd0k0wIN30IlgSZ/OAMQkGlAu86K46pv5RySmoZB0mBzBgclChlqzDe8lgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp4PBqhkFd5L1iHdBIMw6TBEPGD69gJLggHfu/Siu7NN/fMb1ymoZB0mBzBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFWrJOqSbYEC66QWW9CJYkrAFGXA2L7qrjql/VHIKKlkHzwcDVLIKtWSdoJKpJUMGFlK8wJJeYEkwoKLkRW/VQS1ZB5Wsg0oGg+A5qOQEfuNah3QTDJh0vAiWxNk8YEyCAUPEi+6WnPpHJaegknVYHwMDaskq1JJ1eC8ZDFhI8QJLeoElwQCV7EVv1UEtWQeVrIPngwEqWYX3knVIN8EgTDoMEQ+Yvr1gTIIBiZAX3cPW1D+/cZ2CStZhmgUDJgcVask61JLBgIUUL7CkF1gSDMiVvehtSWrJOqhknd7ffYDhQSWrUEvWId0EA9JNL7CkF1gSDMiVvehuyan/P76/4ECocPzxp2zAAp4PBsFz/pLhAgv/Eezyn7IBCyHd/HcZOgAKYYj8mwwXeIfZ2eTf8A7zmJTxCaAQcmXClge9Vce/Tv0D1EBOCxlklAAUI0MHQEEGCcBQkAhBBhkl4EJPZ5u/cQ1QAZMDZJBRAlCMDB0ABRkkAGMh4xNAQQYJuIBKhieBSoYMMkoAipGhA6AggwRgKEiEIIOMEnABlQxPgskBMsgoAShGhg6AggwSgLGQ8QmgIIMEXOiukv/zX+HAn8Euv2QDFvj1LjAInvP9LzJeIDL/xvX/kg1Y4DeuwWAeIjJc4B3Cb079RWx2IFiSRAgyzENEhgu8wxC/cc1fgkrgL0HpMDmAQQhp/CWohPnvJfOXoBKCBOLHYiHDrO3k3/AOLEl5gSXBgIqSF71VB38vWQeVrINKBgNUsgp/L1mHdBMMmHS8YL3BCywJBoQtL7pbcuoflZyCStZhfQwMUMkqcy35t2zAQvjL9NSSIQMLKV5gSS+wJBigkr3orTqoJeugknXwfDAInoNKTuAb1zqkm2BA3c4Lpm8vsCQYUFHyoruzTf2jklNQyTpMDmBALVmFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZBwkEBgwRFd5L1iHdBAPSTS+wpBdYEgxIhLzobsmpf1RyCipZh8kBDJgcVKgl61BLBgMWUrzAkl5gSTAgV/aityWpJeugknXwfDBAJavwXrIO6SYYMOl4ESyJs3mAJcGAsOVFd0tO/aOSU1DJOng+GKCSVagl6wSVTC0ZMrCQ4gWW9AJLgkFIhMiVPeitOqgl66CSdfB8MAieg0pO4L1kHdJNMGBp1gss6QWWBAOGiBfdVcfUPyo5BZWsg+eDAbVkFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhvWQd0k0wCJMOQ8QDpm8vGJNgQCLkRfewNfWPSk5BJevwjWswYHJQoZasQy0ZDFhI8QJLeoElwYAlKS96W5Jasg4qWQfPBwNUsgrvJeuQboIBk44XWNILLAkGVJS86G7JqX9UcgoqWYfJAQxQySrUknWCSqaWDBlYSPECS3qBJcGAXNmL3paklqyDStZBAoFB8ByGSALvJeuQboIB6aYXwZI4mweMSTBgiHjR3ZJT/6jkFFSyDp4PBiykqFBL1uG9ZDBgIcULLOkFlgQDvnHtRW/VQS1ZB5Wsg0oGA1SyCu8l65BuggGTjhdY0otgScIWZMDZvOi+3jD1j0pOQSXr4PlggEpWoZasQy0ZDFhI8QJLeoElwYBc2YvelqSWrINK1uFbJGCASlahlqxDugkG1O28IHH3AkuCAYmQF92dbeoflZyCStZhcgADJgcVask6QSVTS4YMLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZzAb1zrkG6CAZOOF1jSi2BJwhZk4HuXXnS35NQ/KjkFlayD54MBtWQVask6vJcMBiykeIElvcCSYMCSlBe9LUktWQeVrIPngwEqWYX3knVIN8GASccLKqBeMCbBgCHiRXdLTv2jklNQyTp4PhigklWoJetQSwYDFlK8wJJeYEkw4HuXXvRWHdSSdVDJOkggMGCIqFBL1iHdBAOWZr3Akl5gSTBgiHjRfb1h6h+VnIJK1sHzwQCVrEItWSeoZGrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE/iNax3STTAIkw5DxAOmby8Yk2BAucCL7mFr6h+VnIJK1mGaBQMmBxVqyTq8lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrdH9DAEYHlazCe8k6pJtgQLrpBZb0AkuCAbmyF90tOfWPSk5BJeswOYABKlmFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8SJYEmfzAEuCAWHLi+6WnPpHJaegknX4FgkYoJJVqCXrBJVMLRkysJDiBZb0AkuCAbmyF71VMrVkHVSyDutjYBA8B5WcwG9c65BuggGTjhdY0gssCQYMES+6rzdM/aOSU1DJOng+GFBLVqGWrMN7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIOEggMGCIqvJesQ7oJBiFJYoh4QOLuBZYEAxIhL7o729Q/KjkFlazD5AAGTA4q1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVagl65BuggGTjhdY0otgScIWZAiJEM7mQXdLTv2jklNQyTpMs2CASlahlqwTVDK1ZMjAQooXWNILLAkG5Mpe9LYktWQdVLIO62NgEDwHlZzAb1zrkG6CAemmF1RAvWBMggFDxIvulpz6RyWnoJJ18HwwoJasQi1Zh/eSwYCFFC+wpBdYEgyoKHnRW3VQS9ZBJeugksEAlazCe8k6pJtgwKTjBZb0IliSsAUZcDYvuq83TP2jklNQyTqsj4EBKlmFWrIOtWQwYCHFCyzpBZYEA1SyF70tSS1ZB5Wsg+eDASpZhVqyDukmGFC384Lp2wssCQYkQl50d7apf1RyCipZh8kBDJgcVKgl6wSVTC0ZMrCQ4gWW9AJLggG5she9LUktWQeVrIMEAoPgOQyRBH7jWod0EwxIN73Akl5gSTAIuTJDxIPulpz6RyWnoJJ1mBzAgIUUFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9bpppJ/fck/xgTPBwNUsgrvJeuQboIBk44XwZI4mwdYEgwIW150t+TU/w0q+es7lAz++OPr6yHVlG4q+a+cSu5vRjwfDK6p5N9fr6H9/fWha3b31JJXM4692rZCLRkMri2k/HqcK7SnryXX9OX5q4Us7oHBte8Jd3K2pdvvAZ2zt+oorSWHZqUcn0fsH3lEhKxXyfuHvDrCf52fOYQZu78hAKNzQSX/nt1t4SMHWH0tuTqiPNKMpJtgcKFu9xMiygUupJtelqxPX6RlyggZJOUCMHiOs/3eNy/od3+fG5r4RHfVEZ7MWSXLKcKvwycwPe8D6snzKKhRyYdhc1El/zo98ziQO5mRyQEM6lVyGnI/sJ5cXUuujiipGS9GoVsJKplaMmSoX0h5piu0p5slL2SBUy50wgj5I4t7YFCfK/dxNs3Rvg1hnfQQaSIOequOBrXk/QebfvATIywG5plvu0Ylz8+1cnFSnmKvfuYoZkQlg0EYmTUqOV3/mfi8MVb9G9ezHVasiPJUM5JugkHtpPNDIsoFelnySvqinjMzQvoYLEnYggy15YJU3E60dzat14l8x9IopUmY7a46wpO5quT901z6CAagViUfn/OaSg69qmcOY0a+cQ0GlZPD73kkp4xQMPCktpZcGVHOKi/DmzE8J7VkyFC5kHLmCiOIq844WbI2qFxKX6SRwggxjcU9MKjUdn2c7Sz9yt/6+QpWE3HQWyX715J3c9HJJ9b3mUuoVMnJCL+kkucRq505jhm7r+rA6NSp5PMoPby+q6PyveTELvmIcm7G0bUB6SYY1E06z3WF9gRLljublyWvpS/SRmGEz5FECAzqKkp9nO2814nzjm9Wyd1rc+HJPFXy7mG2n9j3hPwz0PWhbSpVcjI0L6nk+SrKmQOZkckBDKpU8i5KH8b2Z8nkylpyXUTZrdI9y4zhVqklQ4aqhZQHu0J7ulhye97hMplU4qy0NjHCx8jiHhhU5cp9nC3jZIHTjreX3dNEHPRWHe61ZGk/s6bA35Ljbb56P/bCbp1KTgfNFZX8WqBJzxzJjN1XdWB0qlTyOpDjHyBYlyk/a5zV1ZIrI0rI2V48zoykm2BQVQF9sCu0pyrddLJkNn05FwBrXwnFUbQhlAvA4AHOtvYa+41/EWrmtGM5rtDEJ7o7W3iyApVsES4T2OZy60LFJqytO0dYETxlHqI1v94VmR9tb4dCxDLJmUOZkckBDGpU8hKRt2NK3fl4Lv+95NkU+YjyZDOGiZpaMmQIQ6RUJf+giHKBDpa8mr7I8QuJ1C3UWBJ+JDUVpT7OtlmJ2rTf6OSTjuN5stmc3qqjtJZsEO26e5RloWLzCWxWO3o+tkkHlXx25lBmRCWDQRiUhSr5ZBAvUXrohbRKqn/jOjJbIhtRHm1G0k0wqJh0LFe44oAfRAdLXkxfYoNRP7BgScIWZBje2Zb9xwNLvycdy/HCh3uf7t9gDU/7tkpeViu2Rl0WKg5J2tJ45OTtfpUczXU8cywzopLBoKKWPI/fieOIilH6k0Zaw1qytHimGcNNUkuGDBULKfN4nzhzhR8ubO635NX0JZ4nm8PB4h4YVOTK81CfuNfZlubJXS5H9I7lYL3IuUhv1eFTS1bTsbgzWY5YljBke0TmYXKnSl6McjxzLDN2X9WB0SlXyXEEpwMqDvrb4nB7Kn/jemU2RM4UzzYj6SYYlCdJPyqiXCBYsszZvCx5NX2Rg8N+XJQLwOD+RKjS2WSfNo7jldSOb1/B6u5s4WnfVcnLyoNsz8SdmY/gSmXlJm5XyXJecuZgZmRyAIPyyWEevROpdoyLnx801NrVkqXBQ80Yohi1ZMhQvpAyj/aJHxFRLnC7Ja+mL7GTtPtBYHEPDMpz5XmoT9zrbLG5qnbjCVrHcqzs2TzorTpcasnhGoFdIhfNLJtb4kd/32JENXer5Git5MzBzIhKBoNilRwXODVficO+1o/GpVkt+eFmJN0EgzDpFA2RnxVRLlA8fXtZ8mr68mfm2BAUj0n4qRR/77KTs8kePSnJeaccuS+SFluyFeFx31TJ8cPZPUdcqFBNGQ+OW0y+WSVHP5nYnzmaGbuPVxidYpU8j90J2dwjxz4nEWlWS5bjWTMO7LJBJVNLhgzFCynzWJ+QzT1y7EfPXndb8nL6kkn4x4DFPTAoXpKaR/qEbO6RY/7OZhTZogem3hlPPM1I3Oldm3OoJS8Kb7cmkQ9zcvA+O9cyD6r7VLKcFdifOZoZe49XGJ4wIktUcm4FdY3qsvl8Wv3G9dPNSLoJBqWTzg+LKBe425KX05fMoTEgEQKDwZ0t3+3Sb3r4/kDa3dnC476nkuOHs38MdefC8DPWfIO3qeRowsD+TNk5jBmZHMCgtJYcB++JcpSjdY40MK1qyU83Y4h91JIhQ+lCyg+LKBe425LSsDp9ieWqK/HyHljcA4PS7112cjaj2/N+Ra3cKAN6q473a8nR2PunMD6CGAXPPqHuzPd/l0qOqzozuzOHMyPfuAaDUpU8j9zz0XR/LG5Lq/eS5fBjzUi6CQalSdI80n9ORLlAsGSJs70s9bYlL6cvw7+WTLkALG4OW7XOJtc99bHTfl/76yTOe3RXHeF531LJ4QKB/YdjfbSvw3dauo47VXIcvy92Zw5nRiYHMChUydYKTwz6svl4GtWSH2/GEOKoJUOGwoWUnxZRLnCzJQvTlzT/lAPDpocs7oFJYa7cy9m+BNlMOLtehzDaW3W8XUsWWx4fQt+7MvqMNd/fTSo5BNyV3ZmybxwzopLBoFAlx3LBqXCU4wNnSlU0qiU/3oykm2AQJp2CIRInw58SUS5QOH17WVKaVacv8ct1V8LlTRSOSfi5FCZCvZ3tjDOVbKnxBnRXHeGB31DJcSHkYPu4+/STjQ1Oh0Zn5iF1j0peTPhie+Z4ZkQlg0Hh5BCX12QzpUM0bkmjWvLjzRhUMrVkyFC4kPLTIsoF7rXk5fSlNqHvAIt7YFCYK/d2tjOkeXK9s/0N6a063q0lh2ARONjMDnPS4E5b13CfSt69lDyxPXM8M3Z/QwBGJ4zHApUcmk2cj9wHpEo1NPqN6/zRidHNSLoJBoVJ0jzMf1BEucC9lrTfLpYGx45k9/fX19f39/T/DlhLoVwABoW58jzU33c2u5U0OO9oz0nz2E/0zV83OGd31REe+LpKjiY7PoK9/PFqUPyR3c38YLeo5LiUFP//7ZnjmZHJAQzKaslxZfNcN5ZNDo+hTS35+WYMMY5aMmQoW0j5cRHlAvda8mr6Evvf8H1bhlMIi3tgUJYr93a2M+J9HVOWqFM2fJ3fuw+9VcebteRwduBoJvsjG3zGmm/vDpUc7fCHduZ4ZkQlg0GZSi549UxajJYfXaTNe8nPNyPpJhiUTTo/LqJcIFjSdjYvS15NX45fr5sZTCeXWRJ+MPeGLW+tII2T+1JU8nRrmbt3oLvqCM94WSVHiyVPIPszn+vd8q6S+fZuUMnLhPBLO1PZdeBuM/KNazAoU8kFA1dalLrS4LSpJT/fjGEOoZYMGcoWUn5cRLnAvZa0G+k9xb0Hhso7WNwDg7JcubeznbB8n0O2F2T3kabfu+6tOt6qJS8ST7YXCtZHCpr0ZB5RN6jkuM4wtV//FRnQjN1XdWB0ylSyvfRZ0uRBtKklP9+MpJtgUFa3+3ER5QJl07eTJS+nL7Iz5YZXIEshEQKDZzjbCWFaDhzTjpMVrLbO0N3ZwgNeVcny6aUJXMGqxdnX3gfhJpW8jLnp3/KvzZkDmpHJAQzKVPI8avN+UjI5PIc2teTswReDmzFMx9SSIUPZQso8yn9SRLnArZa8mr7EbF5hnGyRxT0wKMuV53Hdz9lOWErJx8ZyLwoNo2pv1fFOLTl+MOn9F3xkJaOjI/MTNFfJy3wQlnfkn5szBzRj7+8+wPCE4eiikkuG/3No8xvX2YMvBjcj6SYYuKWbnxVRLnCrJa+mL/E8jSsBtAmUC8DArVzQ0tl0FmGStJX9Gu3cocySDQmPd1Elh1MDaeTy/ch6MD9Bc5UsjV+tt/9+MaAZmRzA4NbJ4Tl0qyUPbsawOE0tGTK4VUA/K6Jc4FZLXk1f4r7fc2L562tXvhqlmsziHhg8YklKZ3G5o7aTbr5fP9f1+1fsdqaZMOitOt6oJUdLKrcvh7IP9mpS8pH1YP70W6vkOMRedpKNzZkDmhGVDAZFKrnkHZmSwP8cmryX/AFmJN0Eg6JJ5+dFlAsES5rO5mXJi+nLq/td50vSPiG7elNkSfjJFH3vsrOz6Sz+ljSdj+w6Wb6bPdFKhXRXHeHh/lP+XcViHdneUvKRlbTpxzwwG6vk6CDiIbKxOXNAM6KSwaBIJZe8I1PzHs34NKklf4AZQwCjlgwZihZSfl5EucCtlryYvoTU6xjsfkm7iUGyDxb3wKAoV+7sbCqLMEm13bTv+yjoo4ifyGn9N+itOq7XksOJAS178/zI+nCHSpamse1+KzCgGYvWx+An41ZLLmnzHLrVkgc3I+kmGBTV7X5eRLlAUbrpZcmL6cu0qVxVGk6MscRBuQAMnuBsGrE7pcNJFilnRxXfzCO6q47wbFdUcoxa6s07fmSduEElHy0om2OrZCYHMKCWrEItWSeoZGrJkIFashdPqCWfXDSmS4OkHyzugUGRtuvsbAqrSE77+9JPjjeYv8Xr9FYdV2a0dB4AAP/0SURBVGvJiynV9Q2/j6wX7VVyYkHZRCXDownDkVpyQpPfuP4AM5JugsGtRZmP5gnlrdcPA6VI00E+vWBJwhZkeIKzKSx+prT7faJr4h3az3uJ7qojPNoFlRxNqd+730fWi/YqWRquLY/bQ5qRb1yDAbVkFWrJOiGAUUuGDNSSvXhCLfkUaTuGOGVxDwyKtN1wzha9rMwnI/EW2yxh9VYdF2vJs4gMyPaBeFg2VWri4/00V8lxMK7PLzs2Zw5oxu6rOjA6RSq5xE9KllCfQ5P3kj/AjKSbYFA26cyD/CdFlAsES9rO9jLS25b0Tl+WTFy2u0IiBAa3JkJezhavU+tlUc/knuMy3Z0tPFm9Sg5nBU5sUvKRSZMmVn2f+QkaquQ48DcjX3ZszhzQjEwOYOA2OZQM/+fA30vWCdMrtWTIULaQMg/ynxRRLnCrJd3Tl6aZeCUs7oGB2+Lejc626JLalcSmS1i9Vce1WnIMV2d37h4fb2d+gnYqWRHJypkDmrH3dx9geFDJKt1qyYObkXQTDEKShEr24ImJ+0q8YFnrtlAuAIOyXHke0aM422WRvFy8SWztrjrCg9X+vWRN4+0o+SK9NBkh4inMg66dStaWGWTX5swBzcjkAAZlKlk8IDeWSgL/c2hTS36+GYNKppYMGcoWUn5cRLnArZb0T18KbuwuWNwDg7JceShnkxZX9ETJDVylt+q4VEuWD/b8xqOMzixIFDTpyTwwm6lkdZlBdm3OHNCMqGQwCMPRRSUPlBM50OQ3rj/AjKSbYOCWbn5WRLnArZb0T1+k1xFWOYIlCVuQ4XnOFv2r4LYT4tXr9bVNd9URHqxSJceljUywkgYZiw2+rNtUJcdll/26i+zbnqnsOnC3GbuPVxidslpywcCVFi3Cbgfa1JKfb8YwM1NLhgxlCyk/LqJc4F5L2o0q05fK5i1hcQ8Myr4nPJCzvSOSmwbX3qrjSi05nBLILFtIi4zFStZHOjKPqFYqOUTYwP7hZef2TGXXgbvN2P0NARgdL5VcWWcYnTbvJT/fjKSbYFCWJP24iHKBYEkPlVxmSWnkl77E8sIAHyDlAjC4N2xJozecLfZz0b8aSpHuqiM8WJ1KFmtkb9v+6O+Wd5XMD9BIJUfjHKwjO7dnjmdGJgcwKFPJtqO0fNGlA21qyc83Y4hg1JIhQ+FCyjzMf1BEucC9lnRPXwb6AFncA4PCXHke0QM42yqSr7lXQynSW3XU15IXY8q2SvzIzhclpMH52OjL/ABtVPJiwINxZO/2zPHMiEoGgzqVfD6Y7LD/KNrUkp9vRtJNMAiTTrm2+zER5QJ1ifu7lnRPX8qqardQOCbh53JvIvS2s8nhy2Lig1XybJsqlSzGyNvSXP4YfcKa76+NSo4GPH7ssnt75nhm7P7dBxidwsnBDKqv41dj9nA0qiU/3oxBJVNLhgyFCyk/LaJc4F5Luqcv1JLhORRqu0GcTW6j6JZVzOe4Tm/VUV1LjrY2blpanX6y8TORzeFop5KjAZNHl927M7V9W243Y/dVHRidMB4LVLKVIcW6gTE5PIY2v3H9fDOSboJB4aTz0yLKBW62pNWsNn2x7utGSITAoFDbjeFsYRqeuTyo5fwW0bW7s4UHq/l7yaF9wMj3rI9eDg8bZ+b7b6GS45hPDSj7d2cOZ0YmBzAorCVbnhKH/gB1Axca1ZIfb8YweVNLhgylCynzQP85EeUCN1vSO32xrncjLO6BQWmuPA/pzs4WK9FvvM0g5589xjv0Vh21teS4IGHdcxSDJzaPn2gLk7ow32ALlSzHlQbageHMyDeuwaBUJUsoORtNr6NDZEQuNHov+fFmJN0Eg9Ik6YdFlAsES5Y4m5MlvdMXaV8yFlpDuQAMbg5b7zjbUru7lKHMxOtfvkCG7qojPFi5Sl6sKdvnSLuTkCwDY9wJq5VKjmPJRC4gW8OYkckBDEpVcnQFfY00Lm4WZ1Cj06qW/HQzhhhGLRkylC6k/LCIcoG7LSkNndKXmH2O8AmyuAcGpdquv7OtIvlKgvKipRbprToqa8nRFPZHFj96fWlBDo6rt+bb91fJ63C0kAuMZkZUMhiUquT86P1TjrZYmuxCq1ry081IugkGYdIpGiLzUP8xEeUCxdP3y1RvW7I+fcl9zjH7HOETLB6T8FMZ39ki0bGM2/2dkX1R2RQ9cC3dVUd4smKVHD+HgjvOLoGMFO50GqlkOVqAXGA0M3YfrzA6xSo5Dl/Z3BHH/eeMtVa15KebMahkasmQoXgh5WdFlAvcbcna9GXKtc+vGi/WpFxVC4t7YFCcK3dytoV4zOhkanaev8RrnKYp79BbddTVkkPjQIksk6aaYZuuO/jQRiUvw9EmXkA2RzFj9zcEYHTCkCxSybk1t5CEBMZdR6ul0W9cP96MpJtgUJwk/ayIcoHbLSlNC9OXeddpJj63nmiSiNdCuQAMissFfZxtIXZvLD8F8XI64pdryLYv3VVHeLJSlRxFXtENZxZBmq47+DB/6t4qOQ7VEuIFBjMjkwMYFE8OywBOo/pQZQMfmtWSH27GcPfUkiFD+ULKj4ooF7jdklXpi+RHJ0Eytr8URN0ptyT8UMpz5R7OtrCqkqwSf13h5HmWa7TRBr1VR00teTGFbBtI4/SDyS2djEITlSzHilguINuDmBGVDAblKvl8AVL2f1Lhp9l7yQ83I+kmGJRPOj8qolwgWLLM2bwsKY1L0pclv1RlcCyqZQLhnZRbEn4o5RXQDs62UCWSTx5ovYbscKa76giPVvj3kjPrERrLMsgh6C0mHXnCmoeVs0r++s4iZ/7x2lqMNpYZu3/3AUanXCWfht5sSH4o7WrJzzZjuElqyZChYiHlJ0WUC9xvyYr0JV5ZDZPrwTHSRhb3wKBC293vbAtyxJB1qw5WBv3Sbel91tJbdVTUkjPrETpLYNt9Zsu6Sc/HNmmhkg3OzhzKjN1XdT6U/0v+/w+gQiUv4XU3pH4vI37kdbRa2tWSn21G0s1GfE5Iqajb/aSIcoGK6bvekl8T8s8N5enLmmwnwW7tdpRPkESoDR+UCA3tbJHlDONOVwdcC3hC/BXu4qetpruzhYcrU8mhZaA4TK1Rb/OEq7Vlx5gMpJKHMiOTQxv+63/LP55PhUreDOM19K7LlhecaFwa1pIfbcagkqklN+BzQkrNQsoPiigXaGnJV/skwlWkL+vefU76e0nzx0k+WNxrw4clQqXD9X5ne5E7tmO98nTtbb9fG69ttYLVW3WU15KjMSrudv2Y//iaDfsVYoswyJrgCQOp5KHM2Pu7D5/Kf/3fHzM7hFFZqpI3Ufp7HvgjJkQ+NPuN68CDzUi62YjPCSlVSdLPiSgXaGjJmJMkmXtF+rL2OPHqdNfrQJ8g5YI2fFAiNLizBTbNz4id75u+Lr67ekMt0l11hKcrUcmLkWS7iF2A2zN4hJnvfBCVPJIZmRza8F//98fMDjW15GXUa9y8ANSYlrXkJ5sxpAfUkhvwOSElpGLlCynzoNf5rIhygXaWXHKUNE5VpC87mawwTupRZ0ko5YMSobpceR7fOo2crUgkr2dtq8kqV5KbMnqrjuJacoxfdfLvNOqNE+505sE2ikoeyIyo5DZMk8OnzA51Kvk89n5YStvwveSJ55qRdLMRnxNS6iadHxNRLhAsWe5sNZZcUxTZsaEifTltOjNQ5lFnSSiFRCihmbOViOTNaUbzhtG1u+oIz1egkuMSRe29nnxmA4U7nbFU8jhmRCW3IUwOHzI71E0Op7NDu5XJPrStJT/XjCG0UUtuwOeElMqFlJ8SUS7QzpK5xL0mfTlpOnMhqWoGi3tt+KBEqDJXvt/Zcr62sDnv7A4DyW96edJbdZTWkqNKrl4wUC07/qLuYCp5GDN2f0PgQ5knh8+YHSpVsh6sP2+Mta0lTzzUjKSbjfickFJdt/sZEeUC1elmsSVjgqgfrUhffp3l7t9DZY2UC9rwYYnQyM525mh7dl0sHR9pu4DVXXWERyz5e8mv4HXhVtOo13TZwYnRVPIoZmRyaMNrcviI2aFaJSuxt23Q7ULjWvLEM80YVDK15AZ8TkipX0j5ERHlAu0suaTmJ4cr0pftr+auDKWRWdxrxQclQvW58q3OVvR96+MT/EpvcaK1IuitOir+XnL4aOSfdew/NPnpwsGZB8NIKnkQM6KS2yCTwyfMDmF01qnk4/TwNVhG5ELT37gWnmhG0s1GfE5IuTLp/ICIcoGGlpSk+/TqNelLopPH+/yCJQlb/nxQIjS2sxWK5KSPRCffoES6q47wnGUqefoIr9rj19cr7n0/QyJPzEPhikpuyQBm5BvXbYiTwwfMDvW15MA0tF9j+1MT2su15CqeZ8Zwu9SSG/A5IeXaQsrHR5QLtLRkSJ+ziUlV+hL7nC455OfH4l4bPiwRqs+VezhbJfHa4eK3KJHeqqOilvyjGFIlD0D3VZ0PZZkcnj87XFPJH8/l95I/HNLNRnxOSGHS8YIKqBeMyTZ8UCLEEPGiuyWn/lHJKahkHTy/Devk8PjZAZWsck8t+XmEVWlqyQ34nJDCQooXWNILLNmGD0qEyJW96G1Jask6qGSd3t99+FQ2k8PTZwdUsgq1ZB3SzUZ8TkgJSRJDxAMSdy+wZBtIhCChu+qY+kclp6CSdZgc2rCdHB4+OzA5qFBL1gkqmVpyAz4npLCQ4gWW9AJLtuGDEiFyZS96W5Jasg4qWQfPb8Nucnj27BA8B5WccPk3rj8c0s1GfE5IYdLxAkt6ESxJ2PLngxIhvnfpRfewNfVf9PeSfxioZB2m2TbsJ4dHzw7UklWoJevwXnIjPieksJDiBZb0Aku24YMSIXJlL3pbklqyDipZh/WxNhwmhyfPDqhkFd5L1iHdbMTnhBTSTS+CJXE2DxiTbfigRIgh4kV31TH1j0pOQSXr4PltOE4OD54dUMkq1JJ1qCU34nNCCgspXmBJL7BkGz4sESJX9qC36qCWrINK1kEltyGZHJ47O6CSVagl65BuNuJzQkqYdBgiHjB9e8GYbMMHJUI4mxfdLTn1j0pOQSXrsD7WhnRyeOzsgEpWoZasE1QyteQGfE5IYSHFCyzpBZZswwclQqhkL3qrDmrJOqhkHTy/Dcrk8NTZIXgOKjmB37jWId1sxOeEFCYdL7CkF1iyDR+UCFEu8KK7s0398xvXKahkHSaHNmiTw0NnByYHFWrJOryX3IjPCSkspHiBJb3Akm34oESIXNmL3paklqyDStbhG9dtUCeHZ84OqGQV3kvWId1sxOeEFNJNL4IlcTYPGJNt+LBEiCHiQXdLTv2jklNQyTpMDm3QJ4dHzg6oZBVqyTrUkhvxOSGFhRQvsKQXWLINH5QIkSt70duS1JJ1UMk6eH4bTiaHJ84OqGQVask6pJuN+JyQEiYdhogHTN9eMCbb8EGJEM7mRXdLTv2jklNQyTp4fhvOJocHzg6oZBVqyTpBJVNLbsDnhBQWUrzAkl5gyTZ8WCJEruxBb9VBLVkHlayD57fhdHJ43uwQPAeVnMBvXOuQbjbic0IKS7NeYEkvsGQbPigRYoh40V11TP3zG9cpqGQdPL8N55PD42YHaskq1JJ1eC+5EZ8TUlhI8QJLeoEl2/BBiRC5she9LUktWQeVrIPntyEzOTxtdkAlq/Besg7pZiM+J6Qw6XgRLImzeYAl20AiBAndJ4Cpf1RyCipZh29ctyE3OTxsdmByUKGWrEMtuRGfE1JYSPECS3qBJdvwQYkQi3te9FYd1JJ1UMk6eH4bspPDs2YHVLIKtWQd0s1GfE5IoW7nBdO3F1iyDR+WCDFEPOjubFP/qOQUVLIOk0Mb8pPDo2YHVLIKtWSdoJKpJTfgc0IKCyleYEkvsGQbPigRIlf2orclqSXroJJ1WB9rgzE5PGl2CJ6DSk7gN651SDcb8TkhhXTTCyzpBZZswwclQgwRL7qrjql/fuM6BZWsg+e3wZocHjQ7UEtWoZasw3vJjfickMJCihdY0gss2YYPS4TIlT3orTqoJeugknXGUcn/+7OQOeCcx8wOqGQV3kvWGSjdFFf8FCRwnPOUkMLSrBfBkmg7D8axpHj7pyCx6ZzHJEKELS+6W3LqH5WcgkrWGcfzJWb+HJ4yO6CSVagl6wxUSxZH+zk8JKRQt/MCS3oxjiXFl38OLO79NHpbklqyDipZZ5xvkUjI/EE8ZHZAJatQS9YZKHEXP/tBPCOkhCQJbecBibsXlAv6QSL0w+iuOqb+UckpqGQdJoeOPGN2YHJQoZasE1QyteRePCKkUAH1Akt6QS25I89Z3GNJyoPelqSWrINK1kEl9+QRs0PwHFRyAr9xrUMtuStPCCmkm15gSS+CJVHJvXhEIjTO9y6fTvewNfXPb1ynoJJ1xvF8iZc/iyfMDtSSVagl6/Becl8eEFKogHqBJb2gltwVFvd+Er1VB7VkHVSyzjieL+Hyh/GA2QGVrMJ7yTrUkjszfkgh3fRinAro0yER6ssDEiHClhfdLTn1j0pOQSXrMDl0ZvzZAZWsQi1Zh1pyb4YPKVRAvcCSXlBL7swzEiFUsge9VQe1ZB1Uss44ni/B8scx/OyASlahlqxDLbk7o4eUkCSh7TygvOUF5YLeDJ8I4WxedFcdU/+o5BRUsg6TQ3dGnx1QySrUknWCSqaW3JfBQwoVUC+wpBfUkrvzhMU9VLIHvS1JLVkHlayDSu7P4LND8BxUcgK/ca1DLXkAxg4ppJteYEkvgiVRyX0ZPBGiXOBF97A19c9vXKegknVQyQMw9uzA5KBCLVmH95JHYOiQQgXUCyzpBbXkAWBx72fQ25LUknVQyTrd3xBYkED5Ixl6dkAlq/Besg615CEYOaSQbnoRLIlK9oBywQgMnwgRtjzobsmpf1RyCipZh8lhCEaeHVDJKtSSdaglj8HAIYUKqBdY0gtqyUPA4t5PoLclqSXroJJ1UMljMPDsgEpWoZasQy15EMYNKWHSQdt5QOLuxThjUtz3hzJwIoSzedHdklP/qOQUVLLOON8ikSj5Uxl3dkAlq1BL1gkqmVryCAwbUqiAeoElvaCWPAhjJ0KoZA96W5Jasg4qWWec9TEJkj+WYWeH4Dmo5AR+41qHWvIwjBpSKMp4gSW9IBEahWETIZzNi+6WnPrnN65TUMk6TA7DMOrsQC1ZhVqyDu8lj8OgIYUKqBdY0gtqycPA4t6n09uS1JJ1UMk6fON6HAadHVDJKryXrEMteSDGDCmkm14ES6KSPaBcMA4kQh9Od9Ux9Y9KTkEl6zA5DMSYswOTgwq1ZB1qySMxZEihAuoFlvSCWvJAsLj32fS2JLVkHVSyDip5JIacHVDJKtSSdaglD8WIISVMOmg7D0jcvRhnTIrj/miGTYRwNg+6h62pf1RyCipZB5U8FCPODqhkFWrJOkElU0sehwFDChVQL7CkF9SSh2LUxT1Usge9LUktWQeVrDPO+piExx/OgLND8BxUcgK/ca1DLXkwxgsppJteYEkvKBeMxYCJEM7mRXfVMfXPb1ynoJJ1mBwGY7zZgVqyCrVkHd5LHo3hQgoVUC+wpBfUkgdjzEQIlexBb9VBLVkHlayDSh6N4WYHVLIK7yXrUEsejtFCCkUZL4IlUckejGNJcdofz3CJEGHLi+6WnPpHJaegknX4xvVwjDY7oJJVqCXrUEsej8FCChVQL7CkF9SSh4PFvU+lt+qglqyDStYZx/MlNMJoswMqWYVasg615AEZK6SMU7d7OiTuXpAIjQeJ0IfS3dmm/lHJKahkHSaHARlrdmByUKGWrBNUMrXk0RgqpFAB9QJLekEteUDGW9xjScqD3paklqyDStbp/d2HFQmMMDHU7BA8B5WcwG9c61BLHpKRQgrpphdY0gvKBSMyVCI0Tq78dLpbcuqf37hOQSXrMDkMyUizA7VkFWrJOryXPCYDhRQqoF5gSS+oJQ8Ji3ufSG9LUkvWQSXroJLHZKDZAZWswnvJOtSSB2WckEK66UWwJCrZg3EsKe4KMwMlQoQtL7pbcuoflZyCStYZx/MlKsKLcWYHVLIKtWQdasmjMkxIoQLqBZb0glryoIyVCKGSPeitOuZa8h//9u//Pv3H/8J/8/+Fj+WPP2Qr/PfT/zf/N/3fPFpk7PRFgiIIw8wOs+v8G65z/F8wy/wP/ov/hf+bzSJDpzPiSSCMElLCEJlylBhQ+O/Sf9P/vdKa1ZL8r/5/L+vNlhwjbImzgjBYIjQPF/67/F/4v9mQYtUevFQyQDlMDkMyVE4LUIEMnc6II0FkkJAigwRgKEiEhoRE6BPp6WyoZKiFyWFM/kss0xkZJQDFyNDpjPgRLIwRUmSQAIyFjM++iKvCAonQB4JKhieBSh4SllDhqcjQ6Yw4EkSoJQOcQiI0JCRCn0h3lfxv3//xzX/hv+V/83sn0/8fd/Df9N/0v3m4yNjpi4REEEaZG+bJ4d9fo4X/1v/Cz7388ddxL/+Fl47GSDcJKQdGCSnzEDmOG/6r/W8CS3r9FyxJIjQiwyVC/Pfuf8GSXZ0t3AC/cZ0w/90WfuM6Iawe8BvXAzLM3MBvXOvMv3HNX4JKCAtvg/zsrrgSvBgmpPDLzF6E6RtLesBvXA/KOInQOLny0+ltybmWjEpO4C9B6YTxOoYEkqAIM+PMDahkHVSyTkg3xyjKEFJ2kG5+HsHZsKQH46w3iLvCzECJ0Di58tPpbsmpf1RyCipZZ5yERaIiBAaaG1DJOvy9ZB3+XvKYDBRSqCV7MY62ezrUkodkpERonFz56YSUklryeKCSdXqP1xUJizAx0twwr7uhkhOoJesMJIHEm2CCdPMTYb3BC8oFIzJUIjROrvx0ujvb1D8qOQWVrMPkMCBDzQ3UknWoJeuExJ1a8mgMFVLQdl6E6RtLekAteUDGSoRY3POityWpJeugknVQyeMx1tyAStaZfw+QWnICteQBId38TIKzYUkPxllvEJcFEqFPpXtVfuoflZyCStZBJQ/HYHMDk4MOtWQd3ksej8FCCrVkL8bRdk+HWvJwjJYIsbjnRW9LUkvWQSXrdF/VWZDQ+OMZbW5AJevwXrIOteThIN38VKgle0G5YDSGS4QIW150t+TUPyo5BZWsw+QwGMPNDahkHWrJOtSSR2O4kEIt2YswfWNJD6glD8aYiRAq2YPeqoNasg4qWQeVPBbjzQ38xrUO7yXrUEsejPFCCtrOC9YbvCARGosBE6FxhsjT6b7eMPWPSk5BJeswOQzFgHMDtWQdask6IXGnljwOA4YUtJ0XrDd4QS15KEZMhFDJXvS2JLVkHVSyzjjfIpHw+KMZcW5AJevwXrIOteShIN38ZIKzYUkPxllvEMf90QybCOFsHnSfAKb+UckpqGSdcRIWiY8/mSHnBlSyDrVkHd5LHokhQwq1ZC/G0XZPh1ryQIyZCLG450VvS1JL1kEl66CSx2HMuQGVrMN7yTrUkgeCdPOzYb3BCxKhcSAR+nC6V+Wn/lHJKahkHSaHYRh0bmBy0KGWrEMteRwGDSloOy/C9I0lPaCWPAyjJkIs7nnR25LUknVQyTrdV3UWJET+WEadG/iNax3eS9ahljwMpJufTnA2LOnBOOsN4rw/lmETIcKWF90tOfWPSk5BJeuM4/kSI38qw84N1JJ1qCXrhMSdWvIIDBtSqCV7MY62ezrUkgdh7EQIlexBb9VBLVkHlayDSh6DcecGVLIO7yXrUEsehHFDCtrOC2rJXpAIjcHAidA4Q+TpdF9vmPpHJaegknWYHIZg4LkBlaxDLVmH95LHYOCQQi3ZC9YbvKCWPAQjJ0KoZC96W5Jasg4qWWecb5FImPyRjDw3oJJ1qCXrUEseAtLNnwDrDV5QLhgBEqEfQXdnm/pHJaegknWYHAZg6LmByUGHWrIOteQRGDqkoO28CNM3lvSAWvIAjJ0IsbjnRW9LUkvWQSXroJL7M/bcwG9c6/Ab1zrUkgeAdPNnEJwNS3owznqDuPAPZPBEaJzvXT6d7pac+kclp6CSdVDJ3Rl8bqCWrEMtWSck7tSS+zJ4SKGW7MU42u7pUEvuzuiJEIt7XvS2JLVkHVSyzjjrYxIqfxyjzw2oZB3eS9ahltwd0s2fAusNXlAu6M3wiRBhy4vulpz6RyWnoJJ1mBw6M/zcgErWoZasw3vJvRk+pKDtvAjTN5b0gFpyZ56RCKGSPeitOqgl66CSdVDJfRl/bkAl61BL1qGW3JnxQwrazovgbCTuHowzJsWNfxgPSITGyZWfTvf1hql/VHIKKlkHldyVB8wNqGQdask61JL78oCQQi3ZC9YbvKCW3JUnJEKoZC96W5Jasg4qWWecb5FIuPxRPGFu4DeudfiNax1qyV0h3fxJUEv2gnJBTx6RCFEu8KK7s039o5JTUMk6TA4decTcwOSgQy1ZJyTu1JJ78YiQQi3ZizB9Y0kPqCV35BmJEIt7XvS2JLVkHVSyDiq5H8+YG1DJOryXrEMtuSOkmz8L1hu8IBHqx4MSIcKWB90tOfWPSk5BJeswOXTjIXMDKlmHWrIO7yX34yEhBW3nRZi+saQH1JK78ZREiMU9L3pbklqyDipZZ5z1sf/9UcgEkOEpcwMqWYdass5AEkh88UOQuJGBdPOnEZwNS3owznqDuPuHIKEpw2MSIcKWF90tOfWPSk5BJevg+W34L5kCTnnM3IBK1qGWrDNQLfmz+JyQQi3Zi3G03dNhTLbhwxIhcmUPeqsOask6qGQdVHIbrMnhOXMDv3Gtw29c65BuNuJzQgrazguczQsSoTZ8UCLEEPGi+3rD1D8qOQWVrIPnt8GYHB40N1BL1qGWrBMSd2rJDfickIK284L1Bi8Yk234oESIXNmL3paklqyDStbhWyRtyE8OT5obUMk6vJesQ7rZiM8JKaSbXgRnw5IesN7QBhIhSOg+AUz9o5JTUMk6JCxtyE4Oj5obmBx0qCXr8F5yIz4npLCQ4gXazgvGZBs+KBEiV/aityWpJeugknXw/DbkJodnzQ2oZB1qyTqkm434nJDCpOMFtWQvGJNt+LBEiCHiQXdLTv2jklNQyTpMDm3ITA4PmxtQyTrUknWoJTfic0IKCylehOkbS3rAmGzDByVC5Mpe9LYktWQdVLIO62NtOJ8cnjY38BvXOvzGtQ7pZiM+J6SQbnqBs3nBmGzDByVCDBEvulty6h+VnIJK1sHz23A6OTxubqCWrEMtWSck7tSSG/A5IQVt50WYvrGkB4zJNnxYIkSu7EFv1UEtWQeVrINKbsPZ5PC8uQGVrMN7yTqkm434nJCCtvMiOBvTtweMyTZ8UCJEruxF9/WGqX9UcgoqWQfPb8PJ5PDAuQGVrEMtWYf3khvxOSGFhRQv0HZeMCbb8EGJELmyF70tSS1ZB5Wsw7dI2qBPDk+cG1DJOtSSdUg3G/E5IYV00wuczQvGZBtIhCChu7NN/aOSU1DJOkwObVAnh0fODUwOOtSSdaglN+JzQgrazoswfWNJDxiTbfigRIhc2YvelqSWrINK1sHz26BNDs+cG/iNax1+41qHdLMRnxNSmHS8CM6GJT1gvaENH5QI8b1LL7pbcuoflZyCStYhYWmDMjk8dG6glqxDLVknJO7UkhvwOSGFhRQv0HZeMCbb8EGJELmyF70tSS1ZB5Wsw/pYG9LJ4alzAypZh/eSdUg3G/E5IYV00wtqyV4wJtvwQYkQQ8SL7pac+kclp6CSdfD8NiSTw2PnBlSyjl8t+bP8j/eSG/E5IYWFFC/C9I0lPWBMtuHDEiFyZQ96q46LteSv75DcTLf+VZb3xfZfhe27c49K/vUlZvz+kj15VjP2KkqhkttwnByeOzfcpJL/fFpEcasl//5D/qHxO0aUr7KI0h/SzUZ8Tki5pu2WyfVNV3hj0v2qnCqbf9fkmrN5W/L769fjXz0hEWrDByVC14aIl7PV8WtJHMqkyHSXiy/Lrhy1lz/Qfb0h3HqlSpYHjphp6qH9IwJkvUo+GEX2Zvg197FgDp8hzMj6WBsOk8OD54Z6lfx7Hs8LsjfHEyOKWy35+9RCvw8RRXaPTfgoqSU34HNCygVtd5xcZXc1b0WaX1PHNbp36itNAvYPYmDd34X1BjdLygUirRcEGsPiXhs+KBG6oJJ9nG0fswqkyNE3jVN+7Tv449sIO5WXT+m9JFVfSz4+8kT2qX8fTDo97wMC5PyUNSr5YBZzIKRmydvlODI7mZEl1DbsJ4cnzw31v3EdTtgge89RIsoDdLLXb1xPDy//OpJG5urpqAOkm434nJBSP+k4ucKbk+58RnnH800noSx9lHPMvoKzdbFkmu08IzqdcmG9AQr4oESo/kt1Ps52uIp5iV/ScEsuSGi+nAmLhyLITKWE6K46wj1XqOR03pg5z1LVID9+Ujvfdo1Knp9rxRqaqlkyI2EUM6KS27CbHB49N1RPDsehLbtPeWhEcaolhylN/rlHWXZ7hKuGxJ1acgM+J6TULqR4ucKbkUbuonQJLyarh9RBzxR05JRzarWdmu7VW1LLwwM91vmdYHGvDR+UCNXmyk7OVitFtF4nzqLWiS+f3ufJ5atcv7fqqKwla+sCM2cPfWKjno9cxDw3Vajk43MaQ/PELKd2GcaM9etjUMJ2cnj23FA7RJKQIvvPCOmJwvARxem95HAV+eeOs8g8/PIB6WYjPiekVCZJXprszUl38UjZtojdXVfJ9gNWOttZUKm05Fm24xEPe0G5oA0flghVDBEnZ0u8LS9FzoLl2a1X+vLZQ9U5T6Ul/Qk3XKySz016ko2d2nT0AFOpkhPD5Ifm+VCrHJq3m5HJoQ2byeHhc0OtSk7Gtuw/4dQVRldaPrXk+fHl31vOI/PoMjk8EbXkBnxOSKnTdueJWZ0rvDnpLh5ZmOXG7o5XL1fJBfcVpu9ySzoFlVNDTjw2l2Bxrw0flAjV5cpeM3idFDnvVb/3nC8r91l7+RN6q46qWvJu/vmekH/OaJPBtsGh/eDhsVIlJ4MnOzR3rQvsMpAZUcltWCeHp88NlSo5zWnlgM62ktzZFSpxqSW/rCUbG3KR+d0+G0O62YjPCSlV2m6XmL3hCu9OutLWWC9fWMSwbC+Uq+SCpwvOVhwnnYLK9rSUpyYTdesNUMoHJUJVubLbDJ64W5UUkX+9SG/+eJfyLyG9z226VnD5M7qrjnC7/yn/tghtX8QfZN5+lf61Z8s6YSntx65x1Knkw2iZyA3NzbwXf0Z9u+u1Z8NIZkQlt2GZHB4/N9Sp5F3YfSFHVB4cUVxqyfNzKhZajZBGlMFzuXDr1JIb8DkhpWohxckV3o00sXHhZLl0l2Sam9QgTy7liFRpOx9LroaMpvy9+yXfsaP2KSzuteHDEqHiXDnnbDUJ93qdSC4ubBxx6XZzhcQ3Zf/EEhU3l0j8wbh8EuvO6K06amrJy/Ntf+hxDYLJp7FmwGr7Yhv1YP58a369KzI/WnZo6hZbB4/sWBjKjN3fEPhQ4uTw/Llh9oArr67HkCqbGoYrDJ1wefzGtQQJ2VpZI7PsCKg7x4N0sxGfE1JqkiQnV3h30l3OL/T4WHSp99UlE5XtLKGbmy0p7Sc2p2xz6zdjYicoF7ThgxKhDmFrh5yckSJrlNv2sIa5Y7/LDe2cVt87UXv5U7qrjnC3hSo5NA0c7ncx0jFJ1Q8sRho6NWqokpcJYj+mFrucDk3djPeOHiaHNsjk8AFzQ+U3rlcKVPJQrlCJQy35zELLbLQ3wGlgHoqQuFNLbsDnhJSKhZSTWFDtCm/mLkvDwv5id/URrK6nMH3fa8ml/Vm6M3bUPoXFvTZ8UCJUkSs7OdseObdeiqz9Hs6VvcenWn1Zdgi1lz+lt+qoqCXHZ0tuNx44PPOZjWqXWbsw33wTlXz6+MsB2RZMM17yoKugktvwmhw+YW5oqJIfHVEc3kuen3FCNhdkd+KYpxF7JEg3G/E5IaVi0pnH+8SbrvBupJFWpWng0p1sV1D3YBXO9rrs25aU1qnF1j/XdWsC4wWJUBt+ZiI0+8HEm862R849j0GLuk2imd7v6d3oYfE8WNY+VndnCzdbppJDy4BsrizGlm0hmiIJgifth2Ket5qo5Dgjpi2iwfZHxjIj37huwzw5fMTc0FAlPzqivF9Ljo9/fMr49Klf6hFlLMI9UktuwOeElHJt5+UKb0aaeHrhTPnGKt9yP2WnhnTzVksu+j+NfMutjxy1T2Fxrw0flAiVazuvsLXHPDU6Z9qtHuZknxJr4m3ulGTt5c/prTrKa8nn6m45tLPeuY0Wm9ZPCrcx330TlSwNtAEiR3YWG8yMLKG2IUwOnzE3tFPJBa7wlgpty9u15Pj4iYVkr3Lx89l3HEg3G/E5IaVc282jfeJNV3gz0tSq3njNC24qZ5Zm0cHZynp5XfZtS0pb9f7eWBzoT/mYhBo+LBG61dkOyKnnoSEjIOKh7cnRX5V7UWVv5eUzdFcd4V6rVLJs7pBDu2eOhpDNLapNx2J+2pYqWWugmXgwM6KS2zBNDh8yN7RTyc+OKO/Wkpec8viQ8YAWUSpnox6EW6SW3IDPCSnFCylervBepFk8tdDbY28X5tUYM0vjXrG2c7JkvD/90Wo+ktFgca8NH5QIFefKjWZw80xpoAYPObS9/+jM2gXjsW3Ik12ll8/QW3WU15Ll41JvVmxUalLVpmMx32ELlRw9Ql0/TY8VmVG9Vht6f/fhU/mvj5kb5kHcQiWP5gqVvPsb13G6nJA9guzU7SbHBnZZ0s1GfE5IKU6S5rE+IZt75FjBhd6MNNFTC51uEdX1waH61GJne132bUvmc/y44jBwdDqFckEbPigRujtsHZEzTSmiNlDkXnRm2dyhyJray2e4WnhxI9xr0d9LlufKzhyyGciZ1P4AuzM/UQuVHGcG2dwjxzYnj2ZGJoc2/NfHzA3NaslFrlD2Ews9eLOWHK0TkF0vYkDRg4Bl1P6ExJ1acgM+J6SUajsvV3gv0sSzC6fJpTh9ITZUdvWavsexZDTlwNHpFBb32vBhiVCJZ7aaweXEU3Xw9f1CDTyK50pz9ZGUZ6i9fIbeqqO8lhwaTqirltFGshmQPSfPNnzyNt9gC5UsT67bRcbO5uTXjnHMiEpuw/8l//8H0Eoly+GnRpT33kteqkYB2ffiT9l5cmk5ehqPukO62YjPCSmlk46XK0jDa5Gmtr4bxn/gwqxa29Wrs3EsOX7QPqd0vQHq+KBE6O6wdeTyiYFa15TmpZ3VXb676gi3WqOS1ZWBGK5lcyJa4eSTj7L6em2lMfP991fJw5kRlQwGjVTy0yPKe7XkuPY6I/teyL4zp5QTx/XZcIPUkiFD6ULKPNLfd4W3Is2iXAtdPTr2FQeVUyuiSqm2e133bUtGU51lQ8MH7XNY3AOD0lx5doH3nS3hdR4q+X18asnpM1sf7evwxU/wBuYnul0lv45tTh7OjKXfIoEfSyOV/PSI8lYtWR5ekJ0zMSs/u3LddNQB0k0wKNR2Xq7wVqSJnlo4SdaXg1fi81TMx4W1ZC9L/v56cXYdq5+BoVwABoWJULMZXM67lhHV9irNSzuru3x31RFutUYlq2aQZ948yGvH+aNd/uhvYr6/hipZf3A5ti6tyo5xzMjkAAaNVLIcfWxEeaeWvOTSL2TvTHzs0yvL8Wtz5Q0EWUEtGTIULqR4uYI0uxRpluUs2TaIxdQr7rmcW6ExC9cb7goq1JLhcynMlZs529XzZuSuinP9V/NiT667fG/VUf/3kmVzR7L6GtO6009o9FXE+WlbqORcgzhpLEYZz4yoZDAI49FfJT8+orzzG9dL7v1C9s7EQ7KZksTmwSDdBIPCScfJFd6JNPFQqaOHwR+44p3x3PNUI6XQ2e4KKvmQPzQkQmBQWAFt5myv06riw0rlybWeLM0LL9/d2cK9VqlkZbUgHlqf2TaaNCjqugPzA7RUydqHLodWq41nxu7ffYDRaVNLfnxEeaOWHOfRiOyekV3n8cY2XF9C4k4tGTIUart5mL/vCm9EmkUkF/p5dOwrM+pSSpbtIkK6eZ8lTUaPTRkKxyT8XAq13ewBLZxNTju/cIakYGdQqeQrL99bdZTXkpcZQLY3pKshttFeDa59hDcwj8wmKjkaK22RLmKPZ0aWUMGgjUp+fES5/l7yEnnTOLscO7/w6Jko6SYYlE06Xq7wRqSJDlo4Qy6OfSUsyKl15wZnu8+SJraph6VwvQF+LveGrRQ57VJCVNunNC/tq/Ly3VVHuNeiv5e8hOXkdpW5wQ5/TnG2FfPtNVHJ8cGT9eZlcXg9MJ4ZUclg0EslDx5RrteS56ea+FKeMAaNzIWlxairB+GDpZYMGcoWUrxc4XqkiftLQ5C0vuSasa+6ybhM290VVK49wxiwuAcGZRXQds528bRAlO6lnikxszS/qb18b9VRXkteVdzhfqOFth9HuufI2UwzCPPtNVHJq732q0fLwvLGJLJjIDP2/u4DDE8blSwHnxtRLteSY7z41p6w4KGlRcZyXSHdBIMybeflCnajk56WGbzQy1fHrqe2L6HM2e4KKtEAo4amHJQLwKBsiLRztounTTSOZNXB62pK6Ua42cJX+ULTmZ0xFtG32RsFdcYKBUsoPZnHbhuVHN1i/+zLGsTGaAOakckBDJqo5OdHlKu15GVKUS0k0TfnkgVNehJuj1oyZCjTdk6ucDnSrLnf76+5o++/sgmq3Mx0N1/fr/Zf5eEhnlyZApetNxSYqaCJySayPQ8W98CgLFdu52yvsy6o5BjfSnuMwSgXMzfUXr6/6qioJa9P98f3Es5/LxbamuhP2SWbGjFElhn2dhqq5HVQbVpFi+1Gw4BmRCWDQRiO7ir5+RHl6m9cz880McUKxUKypyDcjOq1pJtgUDbpzKP8fVfIhqEXeqRZpvV1fp/+fSp8F424bZ69+w3LybJdSnC22yxpER981MiUpWy9AX4wZeWC2QWaONvrrNKQEvkdA+BESbryWhGcKbnB2svPdFcd4W4LVfIygUx8/wrhf2Oh3YdRMNNc/AzvYn6CRio5tgnMy8fbkbO12YBmRCWDQZNa8vMjysVa8jaVVIwge3LPXGK6joTEnVoyZChbSJkH+fuucDXSxPOOnM2WcjihKERI2+p4UqbtXtduHVSW3FG2nwWLe2Dgtrh30dnkrNyV9/z+2go6O7pMzbftrWetvfxKb9VRU0veBLaU3UNcnWnGYX6CVip5LcqnbNdXBjRjkEA9xysMDypZ5dp7yfG55wdXjCB7cs9cYrqOkG6Cwa3p5sVIs1R3U9Rs8DyVKphe4z1Wz8S3rjfkWWvpsuNZUC4Ag7JcefaBJs4mZ+WuvOcQk6xk5RDyzEetvPyG7qoj3G+xSl4+r4T9RyH2yD7Yq0nFZ3gr84O2Usn/49fZHLn/gtaAZmRyAIMmKvn5EeVaLXl+ool5SkktpL8huefiHHsX4ZOllgwZirSdlytcizQZkaxGpLMEIHD+LW1h6ax60S1M37dZMstaKZAdD4PFPTAoypUbOpucVZ4P7YOSFYU2LhywVUHl5Tf0Vh11teSjZSLfh3BdMtOUtOnHPDCbqeSzWfJw1oBmRCWDQTeVPHZEuVRLjmHi9UyphWK+nLtuDNnVKfU9kG6CQZG283KFa5EmOqpOcrGsqDZdNXZWnv9GgrOZ8fGWoBLuZKb+IYaARAgMioZIQ2eTs66p5IKxvQtiBfdWefkN3Z0t3HLZ30t+ocrk47pAOouklLTpR2uVvBsykaMtBjRj9+8+wOigklWu1JKjScQmqYViNM5dt6RNR8KnRi0ZMrjVkkvaXIo0ala04ZgOyAVOkWY6h6hQQ9F6wx1BZTHAU5MJFvfAoChXbuhsctZFlWzL3l3QK+il8vIbequOylry5ietdxy+JCSt6maaoWiskpeJ7sD+tAHNyBIqGIThiEpOuPAb18tirZyWWqhkJbqkTUdIN8HArShT0uZKpFkcNfA1/7Dp7pdNjwnu9tD313w3v3YpQa73pbMLDu1WSy5pk2GpJJs3MypF6w3wk7k1bCnIWddUcsWtC+bdVV5+Q3fVEW7Y49e7dp+FtMs+WEmbfjRVyYfhtWW33DCgGVHJYEAtWeVCLVkeaHmi1EJ3lH0aExJmasmQoWghxcsVrkSa6KgTL837YiN8d5fbzP/fm0Rh+2slmTs8RoUairRd+6ASz76ssvvD4h4YFOXKDZ1Nzrqqks17X734hXV7lZff0Ft1VNWSd4/5vfsV8P1TyJHsg5W06UdLlbwXyUc7buaNAc3IN67BAJWsUv9e8pJky7ZioZJV5pI2HSHdBIOiJMnLFS5EmnVCP/mBloltQqDvndjknbInZensij8XOZuXJU9Z7XXp9CGgXAAGRYlQQ2eTs8pVcuBX3d8//lX5948rLy90Vx3hdgtV8vp8yxLo9ntCm8fIJryCXG3QSDM/QRuVvF2CiSvP269nrUsyA5qRyQEMmqjk50eU6lrykksuk49iBNmTmwkvrkTfRfjUqCVDhrKFlHmQv+8KFyLNMnmnoWc5tLnemgAkaeV66PQx5Hhl8iuE6fs2S54i5158hjFgcQ8MynLl2RGaOJucVe1k63daygZ4jJiFN1h7+YneqqOilrwaY3vDm68JrTYqmWmkyaCBcn6CNipZWkxsJ0nNugOaEZUMBt1UsjQZNKJU15JjYM3GA9mTe+YS03WEdBMM3LRdiSvUR5plOUubGJf0aL2vMOJnlGiwllllx5F4e9fcOXRtT9+vDpoFleX5n5xIlI1J+MGUVUBnT2jibHJW7sonKEErx7q2JzsMKi8/gOoIN1umkkPLmUNwX220yOT6mWY05idoopKXae74sS9jZzkwoBlRyWCASlaprSWnIlkzguzJPXOJ6ToSnpNaMmQoW0iZB/n7rlAfaeIZ+ry4TOuyvZytB4Mlm9KfY1HRFZFkw63rDSekec4TYXEPDMpy5dkVmjibnJW78hlp0MpiBK2Eyst3Vx3lteTlyZIV0CVyLzaKe3KlE2ly5TO8gXlgtlDJmYXnZOwMaMbubwjA6ITh6K6Snx9RKn/jeokTm1MUC0nMyLnkGwntHZBugkFZkuTkCvWRRrZOzkgyyHgTJzeazyDj0YtzcJmzNQ0q8cxhA1IZlAvA4NawpSBnXcqHYpwpPHnJVmTbovLy3VVHuNeiv5ccGgaURcxlIojH4o7MgmdBk57MA7OFSs7NkccpcEAzMjmAQZNa8vMjSmUt+RgLAoqFCubYgiY9CYk7tWTI4KbtSlyhOtLErbMpP3pyPB63ZfNIvJx6fDlYvty2I0zft1lSZcmnrz7CILC4BwZl2q6ds73OKlWiB+Tk0j5jalKa4Ejzwsv3Vh3FteSculsC//KBHLdTsjlxf+bba6GS5bg6RyQTpGwOZEZUMhg0UcnPjyh17yXHiLrzNeUJCx5aWmQs1xXSTTAom3S8XMFutO/pT9k69W05Hp/gsJkQr65dTw5ddubgbPdZUuFTRDKJEFjcG7ZSLp72IiYgsmlhLRUeqbt8d2cLt1qikrOPdUHeyfVGDTTz2G2gkvOjKRo5Hj1sKtxtRr5xDQa9VPLgEaWqlqx931q1kD3HxohTXsa+l/CxUUuGDGULKV6uII2KI81rI9NvnNVfW/E2T68f71LJyuK5l2NcSDfvs6RCtMXjkwgW98DASyVfdTY5LRPIclSebT/GHmledvneqqO4lhzaTZzc69FGts0Gz2nnB2igko2FZzkazx7PjCyhgkEblfz4iFJVS56fZGIfRjQbyK7z2abkPcuekG6CQZm283KF2kjz2sh0u7+gfXlpkF5QXzurodDZXr00CCofI5JLxyT8XAoTodkfWjibnHZ+4SxydqmjxrBWepPSvOzy3VVHuNUClRzXM05MflzuiDY7X/6QBhc/wubMD9BAJcdpQjaPHDL98cyISgaDtir5sRGlppYco8TB0zQLya5zn8ybtT/hWaklQ4Y6bfeuK1RGGrvSs7/gYYpXeDVQWsSwcD3E1a03uAeVeNq40agYFvfAoDBXnv2hgbPtw1Q1dpzaUVvwrrp8b9VRWks2Pqnjcoe5/HH1k7+L+f4aqGTj8GHsjGfG3t99gOEJ49FfJT8+olT8xnV81mNz7RHN2eZ1/I3MujGkm2BQmCQ5uUJlpDGbLwnkq4WdHp61WMKCbF8gONt9ljyyPEBhHBwZygVgUJgrN5vBr573ojafkualvVVdvrvqCHf6vkpObHTcPiJD442A35b5ee9XyUczy+Y4ZmRyAIM2teTHR5SKWvL8HBPHZ9UsZAXmmJme2q03IXGnlgwZChdSvFzBaraPNHYRZd/CTIpPW7x2vyUxw/R9oyX3rCK5tOA0MCzugUFhrtxsBr963gvrto5I89Leqi7fW3U41ZITGxW2H1ZwzfffXyUPZ0ZUMhg0UslPjyjl7yXHLDx5FNUEss+KKMNWb0g3waB00pkH+vuuUBdp7CQ2tnj1a6/mnajkeFvvRLjCWnKboBKf/K0nGIXC9Qb4udwcthLkvPPAlMWKgkekeWlvVZfvrjrCnRb8vWTroeTwYiNjhTVe7uIn2J75Bvur5OHMiEoGg0Yq+ekRpbiWHJ8kNYRqobPKk/A6eh64uxPun1oyZChdSHFyhcpIc9hM2but6sQ7pMHhgksl9p31rlJt1yKofJRIZnEPLEq/J9xqBpfzLmZEdpzaI81Le6u6fG/VUVpL3q+HJqQLqrLj5NlixJTN8Zg/xHa/3nX2kSd2ke1hzNj9DQEYnUYq+ekRpbiWPD9GCa/m0Wx6Tm9XunpDugkGpdrOyxWkYWGkMab0Y2AzMqkJaXC4z9jtW55c6mwNgkroeuYz0gfKBWBQOkRazeDGiX99f39P/zs7fAxzX9JeNo8ktzk1Df+VXj5Ld9UR7vT937hOP+j8Ry8Hxw0z8+23U8lng0OOrnYZzYxMDmDQSiU/PKKU1pJjhLCRE2RLf/K80UYgPC+1ZMhQvJAyD/X3XaEu0pj5nhyXlMDIpM7iYMxCz7spoXS9wT+oxMd+rxY+DizugUFxrjy7hf8MLieeBRo5fDaI5fByU8Z9JIdl+8wAxuE9vVVH7d9LPgnS6UyRXQKJzccNmPOH3kAlx8GkH09n0NHMiEoGgzAiW6jkh0eUwt+4jlYoQM7IZenRZgO7LOkmGBRPOk6uUBdp8lP6ejyeIJuncU4OH+5T9r4Z4IKz3WnJhXjOyBG6ChIhMCguFzSaweXMs7iU61WRItmgqFyt8vJZujtbuNUalawuJcSJYPsksks74Y1P/i7mJ2qokvVHl4Nbm8meUczIN67BoFUt+eERpayWHB+kBDklF1LiVDVwahoSd2rJkKF4IcXLFaRpYaSRPWeBS44uh+NNnqQI+uHck1UQ0s1bLRmRU0rT4vFhcQ8MirWdt7MJcuaZx8Ur68fjPS0hcPkyiGwfkIPrI1RePktv1VFcS46PpRpJDu0sEq2qPF3egEMwP24DlayaKqLZeDAzsoQKBs1U8rMjStl7yfFBSpBTlnPSGWfR3LI9IqSbYFA+6Ti5Ql2kibv0W0xOWO5EzRD1+1z2vrncVe5svkEl9DvzMblD8XoD/FTKtZ2vs0XkzLOcKOZb6i0q/coOPQSlYbH28jm6q45wqwW/cb0uJSh3G020f2bZl35KWfsNwnyPLVTyYquMR+xOln2DmBGVDAbNVPKzI0pRLTk+SBFyznqSbK/IfrPbnoSASC0ZMpRrOy9XkMaFkUb2qeFnuaO1Y2XXihw6XCtNQq9Rru1cg8qS9HxO6sDiHhiU58quzrYgp57GDDmuNlACzvlN6qpX9pRePkdv1VFcS85EupMji64+fMKLRd9cF23KPCRaqOTFKsnjL3bZHxnLjL2/+wDD004lPzqiFNWSv7PMzzghm3LOGoCPjnm2fyhIN8GgXNt5uUJdpFkdU3asLKnlJiE4TwH+x+/lUrLjxdKtbF8mOFuhCZwsGViM8Pb9jwPlAjCoGCKOzrYi555KkSXWpBJ8ObSJUEsQSm9GPVR5+RzdVUe41yKVvMb2w/0uj3x8Zt1MS8js+tgWzVTyxlz70WPbdwQzMjmAQTuV/OiIUvz3ks85s9ASOnZSYs24C+eiPoS7pJYMGSoWUupd4WtC/rmhLtLI3jQCLZfZ+exymWM8WLLNQ/4gO98MHxMV6w2XLKlmkutTDR2I6mBxDwwqtJ1X2Noh5543kwZpk6Xf3e2v0e80bO3uU/aVXj5Db9VRXkvexPZttN7sPT6HqvtCdHkhO8ZkfqwmKnkdPFuzrA6RuMRQZkQlg0EYlI1U8pMjSuFvXOc4tdAaPNbIfJZxjwbpJhjUTDq1rvCKHon8rIs0a+tdD5vcaO/4601uE85NDrB/2nid9yfeGmdzsuRjAlEdFesN8DPpELZ2zE1yXqeHoU2/+7B1EuW2l5E9Lyovn6G76gg3W6aSN/JuMtP83F+beUB5jK1ZX+1Xw72ZMLZmfrA2Knlns9n0v7d2yc3Y/c2ISgaDhrXkJ0eUhrXk3YQ0R57fmyAzuLuG+Z5aMmSo0XaVrhBbvznpblr/8der222/STqwuZZcfp8DzI0iS1r5foCr0nZOltw+1wnvhcUuVI1J+IlU5cpOzrZF2hxjz4aNa756DXFLdgQOp26j3CtqTe237v3atbC9vGjM3OXP6a06KmrJ20UADSWGbyeKAz0fuoD5ztuoZGPaUAwzkBm7vyEAo9NSJT84opT9xnWWjIXkiMbYiwekm2BRlyTNg14ncYUlnKTzdV2kqZzTt/mmwv4+47WLk8pzgrPdbMm8ZV4MHqI0KBeAQV0iNDuCTk3Y2mC3OYSh7/WnT2aS8X3w5e+/9juO93m8/KF5uft0Vx3hdkt+4zqQje3qssZpiBw9wMzjsJFKzk4cqmHGMSOTAxg0VcnPjShNa8mZ0Dx6nSZ8oNSSIUPdQkqNK6zRRHZsqIs0S+KqoJzw6/TqE/v7XIoTsv0OYfq+15K551wYPUYpsLgHBnW5slfYWpEmOSmSVXTKvWe9Ob3P2suf0Vt11NSSc9Xk75PlwBOz9nzkIpqq5MxgOzlvGDOiksGgrUp+bERpW0s+Dc3Dl2lIN8GgTtvVuMIaTGTHlrpIc54R6nP6aQ5wTKVkt4sn19WSHSx5njFuGT5IpZAIgUFlBdQrbC1Ik6wU2X1heo963vlioKoAay9/QndnCzdcrJJrZ44JdfIYPyq2VcmnU+qpYUYxY/fvPsDoNFbJT40obWvJE1pofoCrhtumlgwZqhdSil1hSfrUo5WR5iQ3OjvhJAc43kmsOru4cuV6w9uWLBPJ1JLhA6nWdk5hKyJtDClyErXOwtaZcjm7k8rL6/RWHXW15AnNSmeF5Jl0OSHbfBDmcdhOJeujJ3fSIGZkCRUMwthsqZIfGlFa/sb1i2XuXKhZr+0F6SYY1E86pa6wqLiTw3WRRvsadc4F07tUr/9q5hLi6p3tPUtqWY7CA8L3ker1BvhpdAtbQkmbCfXlj8xJStTKhcXay2t0Vx3hnmtU8vTYBzOZKereTvHH1MZmfsaWKnnq4jB86kZzJzOiksGgdS154okRpXkteWIfmb8ekXyGxJ1aMmS4spBS6Aqy6H86pVVGmmNKaLXf3+VpKjVd1SfGXdF2b1jyYI1TqCXD53GlAuoUtmZebQoixzFqWatWh6hlPWTt5VN6q47qWvLML1F439/mn7ae+fX1OmFqL3tGZx4IV1RyFV/yo3KTGUtGzgBm5BvXYHBVJVfxvIji8F5yAZNZXnZ5hkSeIN0Eg2tJUpkrhL+4ko0htZFm022J+NtcPnObv5zm3OBs3Sz5UVAuAIOuYauSSdEVhKGFX/KH674Lo2Ll5Y90Vx3h3kt/4/oHcY9Kfh5MDmBwi0p+Hg615I8kzJ7UkiEDCylehOkbS3rAmAQDcmUvelvyWi3580El6+D5YIBKVrmnlvw8SDfBAG3nBc7mBWMSDEiEvOiuOqb+UckpqGQdVDIYMDmoUEvWoZYMBmg7L9B2XjAmwYBc2YvelqSWrINK1un+hgCMTvAcVHKCw29cfySkm2BAuulFcDYs6QFjEgzIlb3obsmpf1RyCipZh8kBDKglq1BL1gmJO7VkyMBCihdh+saSHjAmwYBc2YvelqSWrINK1sHzwQCVrMJ7yTqkm2DApOMFzuYFYxIMGCJedLfk1D+/cZ2CStbhWyRggEpWoZasw3vJYIC28yKkm1jSA8YkGJAre9HbktSSdVDJOqyPgQEqWYVasg7pJhig7bwIzsb07QFjEgzIlb3obsmpf1RyCipZB88HA1SyCrVkHWrJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJevwLRIwCJ6DSk7gN651SDfBgHTTC2rJXjAmwYBygRfdVcfUPyo5BZWsw+QABkwOKtSSdULiTi0ZMrCQ4kWYvrGkB4xJMCBX9qK3Jakl66CSdfB8MEAlq/Besg7pJhgw6XiBs3nBegMY8L1LL7pPAFP//MZ1CipZh4QFDFDJKtSSdXgvGQzQdl6g7bxgTIIBubIXvS1JLVkHlazD+hgYoJJVqCXrkG6CAdrOi+BsTN8eIIHAgCHiRXfVMfWPSk5BJevg+WCASlahlqxDLRkMWEjxgvUGLxiTYEBFyYveqoNasg4qWQeVDAbBc1DJCfzGtQ7pJhgw6XiBs3nBmAQDhogX3S059Y9KTkEl67A+BgbUklWoJeuExJ1aMmRA23kR0k0s6QFjEgxQyV70Vh3UknVQyTp4PhigklV4L1mHdBMMmHS8CM6GJT1gvQEMSIS86D4BTP3zG9cpqGQdEhYwYHJQoZasw3vJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJev0/u4DDA8qWYVasg7pJhig7bzA2bxAAoEBubIX3S059Y9KTkEl6zA5gAEqWYVasg61ZDBA23nBeoMXjEkwIFf2orclqSXroJJ18HwwCJ6DSk7gN651SDfBgEnHi+BsWNID1hvAgLDlRXdLTv2jklNQyTp4PhhQS1ahlqwTEndqyZCBhRQv0HZeMCbBgG9ce9FbdVBL1kEl6+D5YIBKVuG9ZB3STTBgadYLasleMCbBgCHiRXfVMfXPb1ynoJJ18HwwQCWrUEvW4b1kMGAhxYswfWNJDxiTYECu7EVvS1JL1kEl6+D5YIBKVqGWrEO6CQZoOy9wNi9IhMCARMiL7s429Y9KTkEl63T/7gOMDpODCrVkHWrJYIC284L1Bi8Yk2DAQooXvVUHtWQdVLIOng8GwXNQyQn8xrUO6SYYMOl4EZwNS3rAegMYUFHyovsEMPWPSk5BJeuQsIABtWQVask6IXGnlgwZWEjxAm3nBWMSDMiVvehtSWrJOqhkHdbHwACVrMJ7yTqkm2BAuukFzuYFYxIMGCJedFcdU//8xnUKKlkHzwcDVLIKtWQd3ksGA7SdF2H6xpIeMCbBgIqSF71VB7VkHVSyDioZDFDJKtSSdUg3wQBt50VwNqZvDxiTYECu7EV3S079o5JTUMk6eD4YoJJVqCXrUEsGAxZSvEDbecGYBANyZS96W5Jasg4qWYdvkYBB8BxUcgK/ca1DugkGpJte4GxeMCbBgHKBF91Vx9Q/KjkFlazD5AAGTA4q1JJ1QuJOLRkyoO28CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GqGQV3kvWId0EAyYdL4KzYUkPGJNgwPcuvejubFP//MZ1CipZB88HA1SyCrVkHd5LBgMWUrwI6SaW9IAxCQYspHjRW3VQS9ZBJevg+WCASlahlqxDugkGaDsvqCV7wZgEA3JlL7pbcuoflZyCStbB88EAlaxCLVmHWjIYsJDiBdrOC8YkGPC9Sy96qw5qyTqoZB08HwyC56CSE/iNax3STTBgadYLnM0LxiQYMES86K46pv5RySmoZB08HwyoJatQS9YJiTu1ZMiAtvMiTN9Y0gPGJBiQK3vR25LUknVQyTp4PhigklV4L1mHdBMMmHS8CM6GJT1gvQEMSIS86D4BTP3zG9cpqGQdEhYwYHJQoZasw3vJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJet0f0MARgeVrEItWYd0EwzQdl7gbF4ggcCAXNmL7pac+kclp6CSdZgcwACVrEItWYdaMhig7bxgvcELxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtgwKTjRXA2LOkBYxIMGCJedLfk1D8qOQWVrMO3SMCAWrIKtWSdkLhTS4YMLKR4EdJNLOkBYxIMyJW96G1Jask6qGQd1sfAAJWswnvJOqSbYMCk4wXO5gXrDWBA2PKiuyWn/vmN6xRUsg6eDwaoZBVqyTq8lwwGaDsv0HZeMCbBgFzZi96WpJasg0rW4VskYIBKVqGWrEO6CQZoOy+CszF9e4AEAgMSIS+6q46pf1RyCipZh8kBDJgcVKgl61BLBgMWUrxgvcELxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtgwKTjBbVkL1hvAAO+d+lF9wlg6h+VnIJK1iFhAQNqySrUknVC4k4tGTKwkOIF2s4LxiQYkCt70duS1JJ1UMk6rI+BASpZhfeSdUg3wYB00wuczQvGJBgwRLzorjqm/vmN6xRUsg6eDwaoZBVqyTq8lwwGaDsvwvSNJT1gTIIBFSUvequOuZb8H7//1+//xX+v/+b/+/0fwS7/U7aOTX7gf/J/v/F8MAie8/07Dhn+e/33+z+DXb6S/T/5v/n/wgyISoYM8xCRiMJ/F/6T//s9O9tfry3+u/afWDIkQqhkyDAPEcLWW/+9vK236phVMkAF/y5jB0BBRglAMTJ0ABRkkACMhYxPAAUZJOBCT9WBSoZaUMmQQUYJQDEydAAUZJAADAWJEGSQUQIuoJLhSTA5QAYZJQDFyNABUJBBAjAWMj4BFGSQgAuoZHgSqGTIIKMEoBgZOgAKMkgAhoJECDLIKAEXujpbuIH5t3b4b/vf/Fs7/zPZ/dP/49e7wCJ4TviFGP7b/fdnsMvXYSf/8etdYPH69a7DwOG/C/9hSa//5t9Bk/EJoCC/3nUcOfxX+98Yv97F30tOmP8S1L/IBiygksEgDBH+ElTC/Jeg+HvJCfxJFTBgiHiBtvMiWJJECDIwRLzorjqm/lHJKfy9ZB08HwxQySr8vWQd/l4yGKDtvGC9wQssCQbkyl70tiS1ZB1Usg6eDwaoZJX/GSIKteQE0k0wCEOESccDpm8vWLkBA7536UX3sDX1j0pOQSXrMM2CASpZhVqyTpBA1JIhA4rEC5akvMCSYECu7EVvS1JL1kEl67A+BgbBc1DJCbyXrEO6CQbUkr1gvcELJBAYkCt70d2SU/+o5BRUsg6TAxhQS1ahlqzDe8lggLbzgiUpL7AkGJAre9HbktSSdVDJOng+GKCSVXgvWYd0EwxQyV4wfXvBmASDMERIhDzoHram/lHJKahkHb5FAgaoZBVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQdFqPBAJWswnvJOqSbYMCk4wWW9AJLggFDxIvulpz6RyWnoJJ18HwwQCWrUEvWCSqZWjJkYCHFCyzpBZYEA3JlL3pbklqyDipZh2+RgEHwHFRyAu8l65BugkFIkhgiHmBJL5BAYECu7EV3S079o5JTUMk6TA5gQC1ZhVqyDu8lgwELKV5gSS+wJBiQK3vR25LUknVQyTp4PhigklWoJeuQboIBk44XWNKLYEnCFmSgluxF97A19Y9KTkEl6zDNggEqWYVasg61ZDBgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwQCWr8BvXOqSbYEC66QWW9AJLgkEYIiRCHnRXHVP/qOQUVLIOkwMYoJJVqCXrBJVMLRkysJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGATPQSUn8F6yDukmGIRJhyHiAZb0AkuCAbmyF90tOfWPSk5BJeuwPgYG1JJVqCXr8F4yGLCQ4gWW9AJLggEq2YveqoNasg4qWQfPBwNUsgq1ZB3STTBg0vECS3qBJcGAipIX3Z1t6h+VnIJK1mFyAANUsgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIO62NggEpW4TeudUg3wYB00wss6QWWBANyZS+6W3LqH5WcgkrWYXIAA1SyCrVknaCSqSVDBhZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MAieg0pO4L1kHdJNMAiTDkPEAyzpBZYEgzBESIQ86K46pv5RySmoZJ3u4xVGh1qyCrVkHd5LBgMWUrzAkl5gSTDgG9de9FYd1JJ1UMk6eD4YoJJVqCXrkG6CAUuzXmBJL7AkGDBEvOiuOqb+UckpqGQdPB8MUMkq1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVfiNax3STTBg0vECS3oRLEnYggx879KL7mFr6h+VnIJK1sHzwQCVrEItWSeoZGrJkIGFFC+wpBdYEgxYkvKit+qglqyDStbB88EgeA4qOYH3knVIN8GAup0XWNILEiEwoKLkRXdnm/pHJaegknWYHMCAWrIKtWQd3ksGAxZSvMCSXmBJMCBX9qK3Jakl66CSdVgfAwNUsgq1ZB3STTAg3fQCS3qBJcEgDBESIQ+6q46pf1RyCipZh8kBDFDJKtSSdaglgwELKV5gSS+wJBhQUfKit+qglqyDStZBJYMBKlmF37jWId0EAyYdL7CkF8GShC3IgLN50d2SU/+o5BRUsg6eDwaoZBVqyTpBJVNLhgwspHiBJb3AkmBAruxFb0tSS9ZBJevwLRIwCJ6DSk7gvWQd0k0wCEkSQ8QDLOkFEggMyJW96G7JqX9UcgoqWYfJAQyoJatQS9bhvWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLehEsSdiCDNSSvegetqb+UckpqGQdPB8MUMkq1JJ1qCWDAQspXmBJL7AkGLAk5UVv1UEtWQeVrIPngwEqWYXfuNYh3QQDJh0vsKQXWBIMwhAhEfKgu7NN/aOSU1DJOkwOYIBKVqGWrBNUMrVkyMBCihdY0gssCQZ879KL3qqDWrIOKlkHzweD4Dmo5ATeS9Yh3QSDkCQxRDzAkl5QLgADhogX3VXH1D8qOQWVrIPngwG1ZBVqyTq8lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XmBJL4IlCVuQge9detE9bE39o5JTUMk6TLNggEpWoZasQy0ZDFhI8QJLeoElwYBc2YvelqSWrINK1mF9DAxQySr8xrUO6SYYkG56gSW9wJJgQK7sRXdLTv2jklNQyTpMDmCASlahlqwTVDK1ZMjAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GwXNQyQm8l6xDugkGYdJhiHiAJb3AkmAQhgiJkAfdVcfUPyo5BZWsw7dIwIBasgq1ZB3eSwYDFlK8wJJeYEkwIFf2orclqSXroJJ1uq/qwOigklWoJeuQboIBk44XWNILLAkGDBEvulty6v8Glfz1HUoGf/zx9VVUTfn99Wr+/fUle+7mHpW8POd32XNWmrEBeD4YXFPJiyv8VTa2v/7q7QqVXKwl93f5xoTHo5YMGa4tpPRJIn5VzulT83ibJQ5ee/kDT7Lk2LC4BwbXcmUvZ3sjcfiqvOvmX5HrrTrqa8kv20dKPkn52COWSX/PCnWhj3XqVXK1XY7PaZ1SacY28C0SMLigkn/vh7Y5wv4cwRUqufIb10O4fGNIN8HgQpLkk0RUz+n7Xs1TkrhneHjl5VO6WfLjoFwABhdyZS9neytx+D11XHPG1FcaiI6hKovVW3fVEW6yRiUfnt6O08eZwPoIUvNWzwUOzHdRo5Jr7ZKaJW+XWjM2gskBDKpV8hSVE3KDexBXqKS+lvzM56wlqGRqyZChfiHFJ4montOl4ZbcZJmmANkIUXt5hV6W/DxY3AOD+lzZydneTBzmM8o7nm866SB9lHPMvnqrjupacmi/wXxA1VrnJRVFPHYx0HzbNSp5vtEVyy76IDp/0EozNgOVDAZhZNao5JBvKJyOMtUVxpeP1e8lj+LyjSHdBIMw6dQMEa8kQs6MWHO61uvEWWjSRO/E6X1WXl6llyU/j1pLwo+jtgLq5WxvJg5yF6XCOoaxQ3TUBY6OnHJOd9UR7rJCJR8/yIszx1l8+SXHj9yeBM8fcoVKrrTLiVlOh0KlGduBSgaDulrySa44cTK4h3GFSmpryU99zlrCc1JLhgyVCyleScTRA/Nz+nkg0+fLE/+eUO+z9vI6nSz5gbC4BwaVuXKrsCWUDtblNmTbInZ3XSXbAr636qisJSex+qIaPHnm86ng7hpKpUqutMv5DFk5o94+dLq/IQCjU6WSzz1+QpsfTirP44/KylryOC7fGNJNMKhLkrySiLo5PRfItHs/TwHU+6y9/Al9LPmJUC4AgzBEPMoFdc72ZuKw3EZhr7G749XLVXLBfXVXHeE+y1Vy8hGUq8HvCflnQHvo3UA5tL95+bJSJdfZZde6wC6743bzljA5gEGNSs4lfxOp02dcYXCpVVdLHsjlGxMejVoyZKhaSNmVZA6uU5VEbE+cqZrT5V8vUpc93qX8S8jHvYLLn9HHkp8Ii3tgUKXtvJxte97hMkX3Im0NYbewiGHZXihXyQVyvLfqqKsl74NzoHB9Nf6A86/1CspHvx78EtOttr7ZSHUquc4umwGUPqdyZq0ZW4JKBoMalbx1nJcv/Nr+PGMy0rKuULj62Ymq37geyeUbQ7oJBlWTThhPL95LIrah6UXtnL65QuKysn9icfDNJZL7NC5fHPm6WPIjCZYkbEGGHs72buIQGxd2uXSXRKBNxMqTi6qR7qoj3GjNr3dFwnkTuWdcl0c2Nlx3Jp/Z8nFuDaLubM/8Idf8eldkvtesXdaBvG20jmXZsVBrxqZ0/+4DjE6FSt6E0s3Y3uR/h6G2us4ArlBJTS15KJdvTEgPqCVDhpqFlBZJhJxcNKdve1g99tjvGuE2Dr7Ze/Bw6/LFcq23JT+HGkvCj6RG2zk527uJw7nq1Yl3WB8NltRPtrP0Vh31fy9ZCOdN5FTysjyyM/nyQRwf++TAMlRuzQ0bquRlfOxH4jKWj3apNGNbuq/qwOiEQVmmkvXkb2Lx+YPTL/tHcIVKat5LHsrlG0O6CQYVdbsmSYScWz+nr/0ezpW9R09e81nZIdRe/pTelvwcSITAoELbeTnbm4nD0rAwT4n3V+8IS6Qr6qm7s4U7baOSl9B++IgXAx32y97EHNc/ijdop5LPHn89INtCrRnbwuQABuW15GVoJyNKPzKWK1RSUUt+9HPWEsI7tWTIULGQMrvHhGsSIedemNNP+j29G/1CtZc/p7clPwcW98CgIleePWriTWd7N3GQVqWLbkt3sl1B3YP1Vh0Na8nREMlqwbJiIdsv4t7UGvFChZ+dC/MAaKKS49BKW+jPWWnGxvCNazAoV8nz6J1QBlQc9TtnGMsVKqmoJT/6OWsh3QSD8iSpTRJhnhrn9LTbJT+V7ReyTwkH6m3+KTtLL39Ob0t+DpQLwKA8V/ZytjcTh3h64bheLlqW1WxZ4lbZqd1VR7jVJir5fOZYPo3dyobsU+wWTXqnndqpZGmgjVc5snvOWjM2hskBDIpVchzaauhWIvZgrlBJeS352c9ZS3gkasmQoXwhZXaOCd8kQk49n9OjWyo5Xzy0PTlzL6rsrbx8ht6W/BxY3AOD8lx59qeJN53tzcShVvXGa14IBHJmadjqrTra1ZKjDWVzizYVxI9Iu2DlVODBPOBaqmStQRzlsjlTacbWoJLBoFglz2N3Qg3KyuAOicl+z0IPV6ik/DeuB3P5xpBugkHxpNMoiTDPlAaqV8qh7f3HeT6XA2wjhewqvXyG3pb8HIIlCVuQIQyRokTIy9neSxxuFMkxyJWmMd1VR7jXFio5NxMsBzcrG7JHt5scu9FQ8x22UMlxuKpDUY5tzFJrxtZ0H68wOqUqeYnKsn0gBuFlcI/mCpUU15If/py1BJVMLRkyFC+kzK4xIZt75NiF2UvONOd0tYHEsW23mWx2udbGwWsvn6G3JT8HFvfAoPh7wrM3TcjmHjlWcKE3E4dK1Vsrqjcskr00i+mtOprVknMzgXJ2bjll/Yhl8wbmHluo5PigsrlHjm1OrjRjc7q/IQCjE0ZkiUrOJn9KzB/NFSopfi/54c9ZC+kmGJTW7VolEXLiqc/9+f1C9W7FnaW5Oo8qz1B7+Qy9Lfk5UC4Ag9Ih4uVs7yUO8ezCQR1v+oJInqf8QLH/dFcd4W5bqGQ5fvJsyUcfd5zYXI6e9ubOfD8tVLI8qG4XGambk187is3YHCYHMCitJRsun3iSbA/jCpUU15Lnx3juc9YSYh61ZMhQupBiRBQ5Wp9EXD4xUOuw0ry0s7rL97bk58DiHhiU5speziYNryUOtaq3UlRvWUrJhV31Vx2tasnGJx8NtRyW7TNTyGdyn6Xm+++vkmvN2BxUMhiUquQYZ2Uz4eDzw7lCJaW15Kc/Zy2km2BQOunMjnHe9HIS8TrvoiiM/iybJtK8tLO6y/e25OcQLEnYggylFdDZl953trcShxtFcnzeihSmu+oIt9tAJVsf7evw0rOV+9VONW8zd3i7Sn4d25xcaMZr8/cV+MY1GBTXkgXZTDiM/cqIMhylteThXL4x4XmpJUOGwoWUZkmEnHfN5Wp7lealndVdvrclPwcW98CgUNt5OdtbCZKcXHK/gXe+bx2fp7CrQG/V0aqWLIdPH+3w0ce/CHiaRcrx23LD+f4aqmR9zMuxdejJjlIztqf7qg6MTqlKtjhE/dfWQK5QSelvXM8P8eDnrIV0EwwKJ51mScTV82bEX4snzVfz4vSz7vK9Lfk5kAiBQaG283I2aXbaYy5xiCK5MKtYRPKFAHBFYHd3tnC//io5ro+cWjE2kKERP6XXloK1UOLNPKRaqORcg4NR6s3YHiYHMPBSyfPAXsZ+DK7juEIlhbXk8Vy+MUElU0uGDIULKc2SiNdp5y6ZpfLk2kUwaV54+d6W/BxY3AODwlzZydneSRzu/L51PLcmmvZWHY1qyXaslwZy/n5LoXbyeJfmKln70OXQ+pC1ZmxP7+8+wPCE8eivksdzhUoK30t+/HPWQroJBiFJKhgis1vkHONqEiGnXfK4mJuWVk4q9Wfl5Xtb8nOgXAAGYYgUJEKzI73vbLEkLZsK0iDt6E6RvPQl20V0Vx3hhv1Vsh3rXw3kfDvW3x2W5/6aqOTztZR0NajSjDfA5AAGTrXkw9LneK5QSWEt+fHPWUt4YGrJkKFsIaVdEiGnXfK42j6leWlflZfvbcnPgcU9MCjTdl7O9kbiIKeWJvZXvjO9IKfWfRWut+poVEu2P7LdRx/tnjG7tLgrN5xvr4lKjg+ejBNl8FWa8QZQyWDgpJLnYT0h3jCeK1RSWEt+/HPWQroJBmWTTrsk4uJpgXhTpXNmTFjtQDFTe/nelvwcgiUJW5DhXme7njgsikS2LaT1JeePfZUGrBfdVUe4ZX+VnD8a2H1kBYmftLgrLM931EQlLxPhQSZHb9laQXaUmvEGuo9XGB0flRyXWOPIlq2BXKGSwlry/AhPfs5aQjiklgwZyhZS2iURF0+bWKJYoeqNuUHhFFt7+e6W/BxY3AODslzZy9nsRic9LcKjTYzaUduX0Ft1tKklF6yP7JrY6yAlTTyZR1QblRwH6948q0he99aa8Qa6vyEAo+OjkkMWEhBHGtAVKin7jevnP2ctpJtgUJYktUsiXmcZWapGdNXSHmPQK/Tt2sv3t+TnQLkADMpyZSdnu5w4LEHk1++vuaPv72ygk5uZ7ubr+9X+q/zb0/HkylDaXXWEe3ZXyQXrI3EZdLaw/Dtnu5KR4khDlbwMlW2rVTpvnrDWjDfA5AAGLip5qZLIwB7QFSopqyU//zlrCcqAWjJkKFtImZ2iSRLxOit7ZYXf65xe5KuvHHWm5AZrLz/T25KfA4t7YFCWK89+9L6zXU4clqizhp/p36cRZV2Zk/9/pjA0LlmdbJfSW3W0qSUXfGS7C2z/fULJJR2Zu2ukkmObwLwOs53wtg9Ya8YbQCWDQRiO76rkJRbHcT2gK1RS9l7y85+zFtJNMAiTjou2K/EuBTmr3OF+f32FYb1guf3UfJejyu4zai+/0tuSn0OZJeEHU1YBnd3ofWe7mjjE846c3bgcTihaqJO2FQHrRXfVEW4alZwwd9dKJS9LKgrbAXR15Dek+3cfYHQ8aslLzhjdYUBXqMStljz4c9YSPmpqyZDBrQJ6MYmQs8odbldnsb1+WRN8Yc6vlZff0NuSnwOLe2BQpu1mN3rf2S4mDofQs0UNK4fQs6FAFcR7rBYQvVVHm1qy2DL7YK8m8wXiR5VbYrg5LM/dtVLJ/+P32WD73pmg0ox30H1VB0bHQSUv7rEM6wFdoZKyWvLzn7MW0k0wKJp0GiYRcla5w+2nd9Pp96mqPb1WXn5Db0t+DiRCYBCGiJkIeTnbtcRhH3kOKPFuH3n2nH9LW1g6q4lYM92dLdx1F5W8aVPypt3Nb+O1Vclnw+1wVqUZ74DJAQzeV8lr7JYdQ7pCJWW15Oc/Zy3haaglQ4aihZSGSYScZc3pK+KhMwVuuvtuWUEKWXn5Db0t+TmwuAcGRRVQL2e7ljhsI0lKMr6zotoMBrGz8jga6a06+tWSN21K1lNK2jjSWiWr4/Nor0oz3kHv7z7A8LytktdYvDr7gK5QSdlvXD//OWsh3QSDoiSpYRIhZ11UyXZna8CbKOil8vIbelvyc6BcAAa3OtulxGEXeBSOsWgbeDSkmU6siF/4/kl31RFum1pyQmOVvIyYA/vTLo38tjA5gMG7KnkN3RtfH9AVKqGWrBNUMrVkyPDoWnKBo8bbEkqDhFATB6gle8HiHhgU5cpeznYlcdjFna/fswjf/NL+xL7H7aHvr7n5r52SyfW+pHUXQkZv1UEtWaepSs4s4ey+3F9pxjtAJYNBGI7vqOQlFm/H2YCuUInfe8ljP2ctpJtgECYdc4g0TCLkrKsq2fTUYz5g3V7l5Tf0tuTnUGRJ+MkUVUC9nO1K4hCmXuGleV9shO/ucpswtf2Tyr824SijgGOrimi10F11hBunlpzQUiXvlnD++H79be6FzQNWmvEOUMlg8GYtefGG3TAb0BUqoZasE56GWjJkeFwtOfCr7u8f/95WZQrur/LyArVkL1jcA4OiXNnL2S4kDvGy056D/l5Dyzbm6Xsn1gudf5t6aXNlXa236uj395K3H9nrn9lp6ObFy4YqebMksyzhbL/nsPpCrRlvoPsbAjA676nkNVeUHS8GdIVK/P5e8tjPWQvpJhiUJUmzUzRJIuSs3JVV1ipLma+usa9IfNZefqK3JT8HygVgUJYrz270vrNdSByWUnJ6k0tk2Vxv1S3JfayHTh9DjtcH0UB31RHuvItKlibzBbb/PqHkko7M3bVRydJiYjva1hlyHQ61ZrwBJgcweEsln4XiAV2hEv5esk6YkKklQ4ayhZTZKZokEXLWBYdbss2yc9eijOwwqLx8f0t+DizugYHbklSJs9UnDkuw0e5RiSzLLiWJMQNXvL1rAaO36uhXS5Ym8wW2/z7h5rA8d9dEJS/j5fixL6NwOVBrxhtAJYPBOyr5dL1yQFeopOw3rp//nLWQboLBremmgpx1xeGWSV22DZb4V9hX5eW7W/JzCJYkbEGGMETsRGh2o/edrT5xiGfo8SCNLLKt5zBG4FoOmwmQSnfVEW7dXSXHpYVc6USazBeQjyRniJvD8txdC5W8jJf0YZOBWWvGG+j+3QcYnXdU8jyWA8fxPKArVFJWS37+c9YSVDK1ZMhQtpDSLomQsy45XJzUC09eijKybVF5+d6W/BxY3AODslzZydnqEwfZOhGuSyCKkSXexMmNxkCk32Q8aptDpbfqaFNLjlIws3Kwa1IwUgqaeNJMJecG23Es1ZrxBrqv6sDohOF4USUvoTYZYgO6QiVl7yU//zlrId0Eg7K6Xbsk4nVWqRI9ICeX9hnzA3M9TZDmhZfvbcnPgUQIDMqGiJOzVScOcessqkmny/G4LZtHsst7sa+rOUt3Zwv37q6SC+aV3frIbkNHWlybqeppppLluDpekpEmm6VmvAEmBzC4XkuOgVgbYXJkIFeopKyW/PznrCV86NSSIUPZQkq7JOLiaS+M7PJIzAFKO6u7fG9Lfg4s7oFBWa7s5Wx2o31Pces0JZHj8QkOmwm568mhy+Git+poU0su+Mgkur+e3R4pdxdQ5jtqoJLzKzhxyotHD5sKOzPeAN+4BoPLKnlZcdS8XI4M5AqVlNWSn/+ctZBugoFXunk1iZDTMj6Zo/Js+zH2SPOyy/e25OdAuQAMynJlL2eTRsWJw2sj028UI6+teJun188om3juZX/prjrC3furZPujVz+y84+45Gv3nswP0EAlR8OcjHg5Gs+uNWN7mBzA4KpKXkWy5uTjuUIlhbXkxz9nLeFxqCVDhsKFlNktWiQRctr5hbPI2aX+GgNA6U1K87LL97bk58DiHhgU5sqzI73vbLWJw2sj0+3+gvblpUF6wSWxu7ym1lt1NKolR5ue20UayPmydW4J+0PyZe6vgUqWkXr2HIcMuNaM7UElg8FVlTwP5IA6mMdzhUrKfuP6+c9ZC+kmGNSlm/5JhJx20eMqV7Vqy7RVl+9tyc8hWJKwBRkKK6CzI73vbJWJgx1m9he0w8yrgdIiap7rGUt31RFu318lm8sfh0/e/Axex+9LDef7a6CSjcMHO9SasT2oZDC4qJJjLD0ZXuO5QiWFteTHP2ctQSVTS4YMhQspzZKIq+e9qHVYaV7aW9Xle1vyc2BxDwwKc2UnZ6tMHMzmhxbmXZ62WErJsn2B3qqjUS3Z/GTFpNFyVqiPlr4tLM83dL9KPtpBNkvN2J7ubwjA6ITxWK+SQ9Yxcza65PA4rlBJ4XvJj3/OWkg3waCwbtcsibh63gvrto5I89Leqi7f25KfA+UCMAhDpCAR8nI2q9k+cYhXPc9I9i3k7MyQP2vx2l2U+5zRXXWE+2+gkq2PXg4vjy7b1uXsWowTc4f9VXKtGZvD5AAGl2rJceHyPJgO5wqVFNaSH/+ctYTJlVoyZChdSJkdo0ESIeedXdfAcugj0ry0t6rL97bk58DiHhiUarvZld53NisQyGG5o5hwnYcZtZacCTMnKjne1jsJS2/V0aqWbCxVRNMtpxtLFa+j5TPN28w32F8l15qxOahkMLiikuM4z6w4DucKlZTWkp/+nLWQboJB6aTTKomQ8y663HFOt5Dmpb1VXb63JT+HYEnCFmS42dkqE4fDZso+sNhhRhocLrhkdgWpzyndVUd4gAYqOR4/CSQyMFabxw9BXzCxFz68me+n3a93nX3kiV1ku9SMzeEb12BwQSWvIjmzYCothnGFSkpryU9/zlrCA1FLhgylCymtkgjjxO/vv76n/xlT/uKxX9JeNo8kt1l5+Sy9Lfk5sLgHBqXazsvZpGFh4iDb5zcYb+u1FW/jXOxKg8N9xm7fihW9VUerWvJiY92qcnDz5OmeDX/K0XfWI+qYb7+dSj6b0+ToaoVaM7am+6oOjM4FlRy9Iju0RnOFSgp/4/rxz1kL6SYYFE86s2uctb2eRMiJZ3O6HD67w+PhvH+nh2W79PJZelvycyARAoNibTc70/vOVpc4GEpkOUGiXixkmIJPNoWl/iHb1+jubOEJWqjk7BJI/IQ2n2fuQ4vXutFQ82feQCXHsaQfT41Wa8bWMDmAQb1KLhLJw7lCJcW15Ic/Zy1BJVNLhgzFCymNkgg5U5+z870q7mzkm8nVKi+fpbclPwcW98CgOFd2crZsKIh9LIlDXomsx2PKIpsnYWg5frhP2VuU+JzTW3U0qyXn7BPnie2Dxw9FM0aISIEbU8PWKln/zOXg9kFlT6kZW9P7uw8wPGFIVqnk6BPnEfiFNBrFFSopfS/56c9ZC+kmGIQkqWiINEoi5MyzOT0moPrxeE9LvzGZPYl2cnB9hMrLZ+ltyc+BcgEYFOfKXs4mTQsTB9lzlnTJ0eVwvMmTKKgfzj1ZBd1VR3iGJio5swiixv24M/2IjWmlCfPH20AlL4NPaxDH1PZBa83YGCYHMKitJccAbs4Eg7lCJcW15Ic/Zy3hkaglQ4byhZQ2SYSceeZ02VRwiW6yPSE79GCQenjt5XP0tuTnUG5J+KGU58pOzlaXOMRd+i0mJyx3ooYtPQ4te99cUOutOtrVks/1oB72NYn4QvbfunY5300LlRxHnzLYljG1O1n2lZqxMahkMKhUycuot/1b2g3iCpWU15Kf/Zy1kG6CQfmk0yaJkFNP53Q5rjZQ0tPzm9SzTdlTevkcvS35OQRLErYgQxgiZYmQl7NJ4zQaqImD7FMDwnJHa8fKrhU5dLhWZXQ6pbvqCA/RRiWfLT6cLTBEkx7Ncba/KfOQaKGSF6skMvnkSK0Z29J9vMLoVKrkeQwH7FA6litUUl5LfvZz1hLCO7VkyFCxkNIkiZBzTwNUvLji3tqhxb3Tm1k8fHuo8vI5elvyc2BxDwwqvifs5Gx1icMSPNKrL4p4E/OWi6fB5vdyKdnxYulWti/TW3U0rCWvn8LOqssHcHxsffJYP4BbU8NmKnm1yuGBliF1NEylGdvS/Q0BGJ06lbyM7pJRNZQrVFL8G9cTT37OWkg3waAiSapPIr4m5J9nyLnnzaRB2iQM7pnd7ayOfMg31xxgd5+yr/TyGZpa8kdBuQAMOoStusRB9qZ3uVxmp2+XyxxvZw1b+1uSne+Hiu6qIzxFI5W8Lj5snlD/AGbWQ+tnfPYBtGYeEU1U8jo2t8nh6hDJoKo1Y1OYHMCgSiXXjeOhXKGSilryo5+zlpDpU0uGDDULKauXlCURr/Z5v5yb5Ob0tdOd7l373c/pq3vvr7m5jOx5UXn5DC0t+bOosST8SGpy5Vpne7VPwlZd4nASh1Y1fIgrehzaSJf908brlNrgnN6qo2UteRvGv2azfi2Ln2pg35h7vu7vzed1s5EaquTNQy3PuT65YphaM7YElQwGYVSWquTN0D5jN9pGcoVKKt5LfvRz1kK6CQZh0ikeInVJRHSrTdaXIm0yc/pm/n71OvW7jW2HU3eHpOvtOvkxna28/DkNLfnDqLIk/ESqKqBOYasucdjGEOl2228SV7Yh6nX5vXSZG0WWi7+fr3RXHeExWqnknSA8oD60HNO4OTWc77yNSt6NtRTFMLVmbAjfuAaDilryNkqfsR9tA7lCJTW15Cc/Zy0hGlJLhgx1Cymzk+gkScTiZtk8xm6zqcoE/vrez/GJyx5SgGP7433WXv6Udpb8adRZEn4gddpudiudmrBVlzgc4tCB5IRDHDqyv8947bxELKK36mhaS858Cvozn38Kd0flebA1UsnZsakaptKMDem+qgOjU66SS0TycbSN4wqVVNWSH/yctZBugkHdpFOTRKxeJjtUpEluTs+GMuXecymAcp+1lz+jnSV/GiRCYFCn7bzCVl3ikBHV2gm7L7wc2d/nErJk+x26O1t4jnYq+ewzO3vks6FSXIPxoqlKzsyRJ+dVmrEdTA5gUK6ScyF34TjahnGFSupqyc99zlrCc1JLhgyVCykVScTqZLJDRZpk5/Rf58FMPe88PT3+pNdM7eVPaGfJnwaLe2BQmSt7ha2TSHFyJ+fiXI8rp3HoGLZkt0us6K06GteSTz6FzFKk9il0MFBblXw6Nk8NU2vGVvT+7gMMT7FKPk/8tiSjbRRXqKTmN65nHvqctZBugkF1klScRCxaNXt5aWPM6Wfh7MRlz1KAszupvLxOO0v+NCgXgEEYIqU/0DLjFLYqE4eTwHJ2wkncOt5JrDq7+Eh31RGepKVKVlZB1cXShXSR1e7Dn8YqWR+buZNqzdgIJgcwKFXJRd+31kbbIK5QSW0t+anPWUtQydSSIUP9QkppErGkfNn5uqTNhFrvzZyU3uTk4efZbO3lNdpZ8qfB4h4Y1Gs7p7BVmThogSXn5Erc0sLWq1nVIt4ZvVVH81ryxP5TiD/SeM7+U/hysXMt8z20VMlTF4fBaZ1Sa8YmoJLBIIzOApVcKJLV0TaEK1RS+V7yzBOfsxbSTTAIk07tEClMIiQK5ae0V5uCOT3JNw1/P+abxsxae/mUhpb8YVyxJPworuTKTmGrMnE4Bhar/SFunS3tTVf1SVm6q47wlFdUchW/vl6S8Lsw0Zuav9p3i8nzOLiikquQx5yes+hBa83YgO7jFUan+BvX7zCAK1RSX0sOPO85awmPRy0ZMlxbSClLIn5NM72nb/2KvZblLr+n9q/mZTdRefkjLS35s2BxDwyu5cpOYeu65Ppd4uSby2ea/3KSCr1Vx+Va8odzj0p+Ht3fEIDRuUUlP48rteSfAOkmGLA06wWW9AJLggG5shfdLTn1j0pOQSXrMDmAASpZ5Vot+fMJS9LUkiEDCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJVqn/j+odAugkGTDpeYEkvgiUJW5CBWrIX3cPW1D8qOQWVrIPngwEqWYVask5QydSSIQMLKV5gSS+wJBiwJOVFb9VBLVkHlayD54NB8BxUcgLvJeuQboIBdTsvsKQXJEJgEIYIiZAH3Z1t6v+P/5R/wwIqWYfJAQyoJatQS9bhvWQwYCHFCyzpBZYEA7536UVv1UEtWQeVrIPngwEqWYVasg7pJhiwNOsFlvQCS4IBQ8SL7qpj6h+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmF37jWId0EAyYdL7CkF8GShC3IwPcuvegetqb+UckpqGQdplkwQCWrUEvWCSqZWjJkYCHFCyzpBZYEA3JlL3pbklqyDipZh/UxMAieg0pO4L1kHdJNMKBu5wWW9AIJBAbkyl50t+TUP79xnYJK1mFyAANqySrUknV4LxkMWEjxAkt6gSXBgFzZi96WpJasg0rWwfPBAJWsQi1Zh3QTDJh0vMCSXgRLErYgQxgiJEIedA9bU/+o5BRUsg7fIgEDVLIKtWQdaslgwEKKF1jSCywJBuTKXvS2JLVkHVSyDovRYIBKVuE3rnVIN8GASccLLOkFlgQDhogX3S059Y9KTkEl6+D5YIBKVqGWrBNUMrVkyMBCihdY0gssCQbkyl70tiS1ZB1Usg7fIgGD4Dmo5ATeS9Yh3QSDkCQxRDzAkl4ggcCAXNmL7pac+uc3rlNQyTpMDmBALVmFWrIO7yWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVagl65BuggGTjhdY0otgScIWZKCW7EX3sDX1j0pOQSXrMM2CASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWYf1MTBAJavwG9c6pJtgQLrpBZb0AkuCQRgiJEIedFcdU/+o5BRUsg6TAxigklWoJesElUwtGTKwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSfwXrIO6SYYhEmHIeIBlvQCS4IBubIX3S059c9vXKegknVYHwMDaskq1JJ1eC8ZDFhI8QJLeoElwQCV7EVv1UEtWQeVrIPngwEqWYVasg7pJhgw6XiBJb3AkmBARcmL7s429Y9KTkEl6zA5gAEqWYVasg61ZDBgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwQCWr8BvXOqSbYEC66QWW9AJLggG5shfdLTn1j0pOQSXrMDmAASpZhVqyTlDJ1JIhAwspXmBJL7AkGJAre9HbktSSdVDJOng+GATPQSUn8F6yDukmGIRJhyHiAZb0AkuCQRgiJEIedFcdU//8xnUKKlmn+3iF0aGWrEItWYf3ksGAhRQvsKQXWBIM+Ma1F71VB7VkHVSyDp4PBqhkFWrJOqSbYMDSrBdY0gssCQYMES+6q46pf1RyCipZB88HA1SyCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usg6eDwaoZBV+41qHdBMMmHS8wJJeBEsStiAD37v0onvYmvpHJaegknXwfDBAJatQS9YJKplaMmRgIcULLOkFlgQDlqS86K06qCXroJJ18HwwCJ6DSk7gvWQd0k0woG7nBZb0gkQIDKgoedHd2ab++Y3rFFSyDpMDGFBLVqGWrMN7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIO62NggEpWoZasQ7oJBqSbXmBJL7AkGIQhQiLkQXfVMfWPSk5BJeswOYABKlmFWrIOtWQwYCHFCyzpBZYEAypKXvRWHdSSdVDJOqhkMEAlq/Ab1zqkm2DApOMFlvQiWJKwBRlwNi+6W3LqH5WcgkrWwfPBAJWsQi1ZJ6hkasmQgYUUL7CkF1gSDMiVvehtSWrJOqhkHb5FAgbBc1DJCbyXrEO6CQYhSWKIeIAlvUACgQG5shfdLTn1z29cp6CSdZgcwIBasgq1ZB3eSwYDFlK8wJJeYEkwIFf2orclqSXroJJ18HwwQCWrUEvWId0EAyYdL7CkF8GShC3IQC3Zi+5ha+oflZyCStbB88EAlaxCLVmHWjIYsJDiBZb0AkuCAUtSXvRWHdSSdVDJOng+GKCSVfiNax3STTBg0vECS3qBJcEgDBESIQ+6O9vUPyo5BZWsw+QABqhkFWrJOkElU0uGDCykeIElvcCSYMD3Lr3orTqoJeugknXwfDAInoNKTuC9ZB3STTAISRJDxAMs6QXlAjBgiHjRXXVM/fMb1ymoZB08HwyoJatQS9bhvWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLehEsSdiCDHzv0ovuYWvqH5WcgkrWYZoFA1SyCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usg7rY2CASlbhN651SDfBgHTTCyzpBZYEA3JlL7pbcuoflZyCStZhcgADVLIKtWSdoJKpJUMGFlK8wJJeYEkwIFf2orclqSXroJJ18HwwCJ6DSk7gvWQd0k0wCJMOQ8QDLOkFlgSDMERIhDzorjqm/vmN6xRUsg7fIgEDaskq1JJ1eC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1um+qgOjg0pWoZasQ7oJBkw6XmBJL7AkGDBEvOhuyan/P/7tGw6Ez+UP+TeszMNFhg6AQhgi/y7DBRaCGvzjL9mAhbCo8u8ydAAU5iEiwwXeAUt6QdgCg2mE4GwuBEv2VB3/Gm4AoAImB8ggowSgGBk6AAoySACGgkQIMsgoARd6Otv8jWuACpgcIIOMEoBiZOgAKMggARgLGZ8ACjJIwAVUMjwJVDJkkFECUIwMHQAFGSQAQ0EiBBlklIALXZ1tvoF//7d/+zf+t/1feO3kj3//G2z4P3/7P/8nmIX3kiFDGCJ/TE40M3kT/83/vSLKce9P/+/f5h+AIN2EDLPrSDThf2/8b3a2YEntIP8r/x9hC0yis01MY4b/rv0XmA0pVu0Bv3GtM//G9f/7/8GBIJP53T7IEHJa/rZcwvyXoPiN6wT+EhQYhCyJSceD8BOCWNIDfpofDELY4o99eNB9Apj6RyWnoJJ1/tZ7vMLoBJXM5JCAStYh3QQDhogXId3Ekh5gSTBgcc+L3paklqyDStahlgwGqGSVWSX/lg1YCBKIWjJkIN30gvUGL4IlGZOQISRCDBEPulty6h+VnIJK1sHzwQCVrEItWYdvXIMB2s4LKqBeYEkwYHHPC2rJY4JK1qGWDAbBc1DJCf8z2AWVnIAEAgPSTS+ogHpB2AIDKkpedJ8Apv5RySmoZB1UMhhQS1bhG9c6Id2klgwZUCReUAH1AkuCAYt7XvS2JLVkHVSyTpBA/4/YCEABlazCN651kEBgQLrpBbVkL7AkGISwRSLkQfeq/NQ/KjkFlaxDLRkMUMkq1JJ1eC8ZDFhI8YIKqBdYEgy6a7uPgVrymKCSdVDJYIBKVuG9ZB0kEBigSLzA2bzAkmDQW9t9Dt0tOfWPSk5BJeuwPgYGqGQVask61JLBAEXiBesNXmBJMEAle9HbktSSdVDJOtSSwSB4Dio5gfeSdZBAYEC66UVwNizpAZYEAypKXnS35NQ/KjkFlayDSgYDaskq1JJ1QrpJLRkysJDiBRVQL7AkGLC45wW15DFBJesECfTfYiMABVSyCu8l6yCBwIB00wuczQssCQYkQl50nwCm/lHJKahkHWrJYMDkoEItWYf3ksEAReIFFVAvsCQYsLjnRW9LUkvWQSXr/G0yC38vGTKgklV4L1kHCQQGpJteBGfDkh5gSTAgbHkRUsqulpz6RyWnoJJ1qCWDASpZhVqyDrVkMGAhxQsqoF5gSTDoru0+BmrJY4JK1sHzwSB4Dio5gfeSdZBAYIAi8YIKqBeELTCgluxFd0tO/aOSU1DJOtSSwYBasgq1ZJ2QblJLhgwoEi9Yb/ACS4IBKtmL3paklqyDStbhvWQwQCWrUEvWQQKBAemmFzibF8GSjEnIQCLkRfdvsE79o5JTUMk61JLBgMlBhVqyDu8lgwHazgsqoF5gSTBgcc8LasljgkrW6b6qA6ODSlbhN651kEBgQLrpBRVQLwhbYECu7EX3CWDqH5WcgkrWoZYMBqhkFWrJOtSSwQBF4gUVUC+wJBiwuOdFb0tSS9ZBJesElcx7yZAheA4qOYH3knWQQGBAuukFzuYFVXkwIGx50b0qP/WPSk5BJevwLRIwoJasQi1ZJ6Sb1JIhA9rOCyqgXmBJMCBX9oJa8pigknX4xjUYoJJVqCXrIIHAAEXiBRVQLwhbYEAt2Yvulpz6RyWnoJJ1UMlggEpWoZasw3vJYIAi8YL1Bi+wJBigkr3obUlqyTqoZJ0ggXgvGTKgklX4jWsdJBAYkG56QS3ZCywJBiRCXgRLdnW2qX9UcgoqWYdaMhgwOahQS9ahlgwGLKR4QQXUCywJBizueUEteUxQyTp/6zxeYXiC56CSE3gvWQcJBAakm17gbF5gSTDoXgH9GLpPAFP/qOQUVLIOtWQwoJasQi1ZJ6Sb1JIhA4rECyqgXmBJMGBxz4velqSWrINK1gm1ZN5LhgyoZBVqyTpIIDAg3fQiOBuW9ABLggFhywveSx4TVLIOtWQwQCWrUEvW4b1kMGAhxQsqoF5gSTDgG9deUEseE1SyDp4PBqhkFX7jWgcJBAYoEi9wNi+wJBhQS/aiuyWn/lHJKahkHWrJYIBKVqGWrEMtGQxQJF6w3uAFlgQDVLIXvS1JLVkHlawTVDLvJUOG4Dmo5ATeS9ZBAoEB6aYXwdmwpAdYEgwoF3jR/RusU/+o5BRUsg5/CQoMmBxUqCXrhHSTWjJkYCHFCyqgXmBJMGBxzwtqyWOCStZBJYMBKlmFWrIOEggMSDe9oALqBWELDLpXQD+G7hPA1D8qOQWVrMN7yWCASlahlqzDe8lggCLxggqoF1gSDFjc86K3Jakl66CSdYIE+m+xEYACKlmF37jWQQKBAemmFzibF1TlwYCw5UX3qvzUPyo5BZWsQy0ZDFDJKtSSdaglgwHazgsqoF5gSTDoru0+BmrJY4JK1gnvJfMb15AheA4qOYH3knWQQGCAIvGCCqgXhC0woJbsRXdLTv2jklNQyTrUksGAWrIKtWSdkG5SS4YMKBIvWG/wAkuCASrZi96WpJasg0rW4VskYIBKVqGWrIMEAgPSTS9wNi+CJRmTkIFEyIvuqmPqH5WcgkrWoZYMBkwOKtSSdXgvGQzQdl5QAfUCS4IBi3teUEseE1SyDu8lgwEqWYXfuNZBAoEB6aYXVEC9IGyBQfcK6MfQfQKY+kclp6CSdaglgwEqWYVasg61ZDBAkXhBBdQLLAkGLO550duS1JJ1UMk6rI+BQfAcVHIC7yXrIIHAgHTTC2rJXmBJMCBsedFddUz9o5JTUMk61JLBgFqyCrVknZBuUkuGDCykeEEF1AssCQZUlLygljwmqGSdoJJ5LxkyoJJVqCXrIIHAAEXiBc7mBZYEA2rJXnS35NT/eCr591d4W22yzNeX7Lmbiyr57//853zj//z7P/4hu3L84++x+d9lT554+b//veTqLWB9DAzuUclff71CxNfXQ+qzF2vJX98xFP4uObl/5KyF95LB4Joi+eXkCtEDv76q17i+KqfK5qto19YbvCz5SbByAwbXtF2nsLV0+13U7dQ83mbJ5X9XXv5Ab5VcX0t+PW3Efuba9lOiJ21f9LHOFZX89/l+Vwwl+499+3/K7lNEUUf66GS+cQ0G1Sr59zyeF2Rvjj/3QeUROvnKb1zvI6H5oENEzlooyoDBhSTJyxUkuYvU+e8U2L5rzpj6SvOjYwzIYvUWnK2LJauzwNG5YEn4WVwoF3QKW8duDf/8vb+6GeSOIaza/bvX5sJd16jkwxObD1zbXpkVesTU+S6qVPJew77IVYiPmjrf+v/7R3L9f/bQyahkMKieHObRvCJ7zzkG6WlEPkAn19eSk8ecyMXCMSJnLeEpqSVDhvqFFCdX+PVepJnPKO94vukk40wf5Ryzr/oKqI8lD1d5QlwyoJYMBvWLe33CVto8r3u1vCRz/V/SZEulhHhcLTm032B+itIuYrVPM+CJDgaax2uFSv7HfKMpZ0o2Fb0TmXJyqqknOsjkIIF4LxkyhJFZo5KPU4PsPiWdSibGl8m17yUfKuwLZ086SuSshVoyGNQmSV6uoEaacheWuygV1tHhDymSehMnyCnn1DqbkkBfsqScGfkAlUzYAoPaCqiXs1WGLT3AnParid6J0/baQ01UZEL9VfIcvypU8vGZrXhX2f7kI7g/CZ6HTrlK1jTvC13J1orqk+ub39J2h1oyGFTWkhM1KPvPOIm6w2cslbXkk8ec0K8xTOSsJaSb1JIhQ6Ui8XKFExcsnf6W25Bti9jddZVsZ56VFdAzS1aluBOVWeATqLQk/DwqtV2nsHWWaJy0P2t+cp9nD1WnInqr5MpacpLSGvGusv1Z/aQ+Lr9LnUo+F8m6kj0TyWcy+fT6t8vkv02d9hyvMDyVKjkJu7L/hJAxq4w+KutqyeeTkf6k40TOWijKgEGdIvFyhVMXLIs0y20U9hq7O169XCUX3FdwtvJA6WXJJFX+AJVcZ0n4gdRpu05h6zzRUNvn8hLlPs8fqsp7aqvy7oT7LVfJiZGMeFfXfhdNvyfkn4GbayJVKjknkjUluxPJ/5yQfwY0mbw9fmh+t0ymlgwGdSo5jaNyQGcbEg4RYnCpVVVLTuLmjtQBd1bsGzlrCbdKLRkyVC2keCUR2/MOlymaAKVtqSJcxLBsL5Sr5IJsumq9wS0d25448wEquW7lBn4gVdquU9jauabd/niX8i8hvc/j5eVfL4pt87Ba8sEqE/l4V9l+rRPFnxdfp4ibjVSjkrei95/zT3D9Y/f71YnwXWVu/ItOa3NF9q7Xf1192rNe4ew72o0ItWTeS4YMVSpZWWyUIypr8/g7jJuXeerWXO+m5jeut1Z5Peiv3c9QJtPRaoTukbMWaslgUJUkOSUR70aa2Liwy6W75NJbv8+ST8VeVFVAvdKxyizwGRC2wOABYWsTXNJuFTeVAxPL5Tftk/vULr+JBun9nNBbJde+l7wQzpsojncF7Rf7bQ2i7mzP/PkWquT59mY2Enerkw9KdpG4W0Ws7pxZRfLmOurOG6CWDAaV37heiCFVNjXWOWATYNf1zaoCx93U1JLnp5nZ+Np2PjpcZ6TIWUu4TWrJkKFGkTi5whpUrkWapWlhJhjvsN5Xl6gg21lqKqBOltwhJxdnjeNSY0n4kdRouz5ha82nth65dJuElPXINqytew/X30h22RNYb6fYf3p/47r+7yUL4bwJR5W82HRvj+UzKJxvfKhQyWd13U0JWPa8WPbvdy+XOcpe/cDJVVrTe7zC8IRB2Ugl67HgJHAMRsV7yfpktJ1f9k9qRc5Cbd4HijJgUJFueiURS2nnWqRZGhb2F++v8Ck31MnxCmfzsuQOOfcDVHKwZP2nBT+IinJBp7C1rLDtr7/ElGN72X3cv+YlskM4ufz6WKVxgFrygrRIzBFtemsqVaGS55sLHOXt+r3o3RHZl8jb2Pqwf6lJHy6/yORjt02hlgwG7WrJS9Q9yL4lSo8sBytqyfOzBI7N129P7Y7IvtPIObTDhomdWjJkqNB283ifeDOJeDfSSKvS9GjpTrYrqPPxigro67JvW3KPnPsBKplaMhhUaLvZKybuDVun0Ww5INvCaazRL3QeLOuCVn+VPE4tOS54pNaINr0zts7jrUgln6nYibWaLDsCcWdaA44yWV4+FuLe5PLL1WX7FoJK5r1kyNBOJcdAkKysLoulsj0i5bXkZa5LWy8Pun3SsSJnLRUSCH4m5YrEyxXejDTx9MLMbrloUXjYsWSiZaeWV0DbBJU3Th0MwhYYlH/vslPYiolGenG9W9mpxBq1fbx8+lQnKvyU7t9gDfc6hEqWBspHEG16p53KVfJ8axN7bftCq/fKnoyo3unnKMKVL1af6ueG8JegwKCZSj6PukuUTlYtx6G8ljw/yYQWK7X1WdkzSOSsJXx01JIhQ7kimUf7xJuu8GakqVW98ZoX3FTOLM3DytcbXpf1DipyanHWOC7UksGgvAI6O8XEzWFL9mkZlxzZXSlzL/HQ7lKxTyUKxkMVYavMkm0YppYcZxatQaVNPShWyRkVO5GWh6MU1kS1VkyO+2RzS49iMioZDJqp5JAsnzRQo/RYFP/GdWaum0hj4WCRsxaKMmBQnCR5uUJsK5tbCiLNjSI5xorSuFfsbI2CyvUzRyNYkkQIMgwftmSXdmktGYv7cu23IU92qbFJDhV6UG+VPN/uCCpZjuvhXo7daKj5Uy9RyZqyXUnLw7JDV7ZybKO4owhXLx8P3lhM5r1kMGilknNBejk4bjG5uJacnxfTBV3ZMUrkrCU8LrVkyFCs7eaxPiGbe+RYgSu8GWmiAxc6Xa2o3rDkvqVhL6Sbd1ryiJxZnDWOS7El4adS/D3h2ScmZHOPHGsQtmL0UOOOHNsGlowIX66lXF69HblWYQjprZJHqSXnllPWj1g2b2DusUYly+YROboczpWSV9krmxP5y8tB/WJNCJ7/32IjAIUwIluo5FyQro9Ht1P8XnL+OeODLodHi5y1UEsGg9IkycsV3os08ezCtO4NkTz7TqA4gyytgLYKKnLiuFG6GMIWGIwetmK/srlHjm3v6VuQzR3KM/wpzdW4ZiQ5B4rXG1oRbnUAlRzHwslUIUeLe3ub+X5KVPJ8X2dfuE51r1H+laOr7JUdJ5dPVXVrqCWDQatashw+GX3XM7ebKK4lz49x7mXHBx0tctYS0k1qyZChVJF4uYI0vBZpalVvpajespSSC7sqr4C2CiqXTxwOaslgUKqSe4Ut2aO3l7BU7Kmv5sXtjSB6oNSSrRilliyHz0whn9l9lpo/xQKVnK8Nr8ejKpbNM1EtpePlsCGqj1dvT3gvmd+4hgyNVHI8fDKXZL8+NAKlteT8yvJ6PF5KNoeJnLVQlAGDUkUyj/T3XeGtSHOjSI7PW9rVRGkt+XXdty2Z8DqvPGscl1JLwo+lNBGaXeJ9Z6sOW3KCfmHp1UvfHTGSvQO9VfL8dP1VspXj1hnVgbnDEpX89xdnOvWgYy1ZeywOH1XzkdfhG79yTS0ZDBqpZGuyeB2+FMtuobSW/OvrxVkojKFSLjVc5KwlfK7UkiFD4UKKlyu8FWnk5NJJslZUb4nPUzEfF643NAsqct4HqOTSlRv4sRRqu25hSy6sn/A6NohK7v2N60FqydFop1mkHL8tvM43VPKNa4ODLDZqw4nslc1TlXz7V657j1cYnkYqWY6eDr66uHs/xb9xbXCoJf8pm8NEzlqoJYNBYbrplURIs0uRJorkwjC0iOQL7nlFYBc6m5clE66eNx6ELTAozJW7ha1cHItXK44tle2l7wLzBKglz8TJRTZTrIUSb+ZP0UElH2Ss8Vtfx+Jx1NinteLbv3JNLRkM2qjkmBOeBpxDjXU4it9LNjiYabjIWUu4P2rJkKFQkTi5QgwkVyJNrXKNt3zFO+O5xSnYRGEF1MmSKa/Tqm55UKglg0GhtnNytgthS3ZoZ9RmU/nkLUWaFwaC3ip5kFpy/uhE7afwLo1Usmydf0N6394uFUuD275yzXvJYBDGo79KtgOANCiOSDdT/BvXBgdDyNY4kbMWijJgUJgkzcP8fVeI386QTQVpkHZ0p0he+pLtIoKz3WfJFDlt1BhdQaEl4edyb9iyW0mDtSPZod2jHCp28MplsyjCC+Nk92+whnvtrpJto92d6839OahkvTZ8Xvrd62LrteT7VTK1ZDBoU0u2w/CrwbAZmFcteW+I8SJnLSHdpJYMGcoWUrxc4Y1IU6l6r3xnekFOrQspZRXQdkFFThs1RldQZkn4wZRpu45hK4ar1B3jTRU7amX7yvhBLTkQp4vMbCEtivt7k/ljfF8lR9FbrJL3stdWyXa12ZfuqzowOr1U8tXM7SacasnxKcUQ40XOWqglg0GZIvFyheuRJu4vDUHS+pJrHuJAIWXO1i6oXDxtQAhbYFCm7TqGrSVeHVfa4j0V5ytRbxe2j9cvDV69VfL8CXRXyWfTzgZpcVd8ne/ofZUc30OWWm+BppUWrxN2Gyp3q2RqyWDQRiXLwYz/FwSRnjjVkg/rv+NFzlrCA1FLhgxlisTLFexGJz3V5pbRla/Mp9V57Iuy9YZ2QeXiaQNSZkn4wZRpu55hK0agQ16yBJfcTW2pjGSxUl0cvHqr5DFqyWLlnCEKmngyj6i3VXKsHUcRa9eGd00KSs93/3xXUMm8lwwZmqjkGLgzcbWgSU98fuN6mcBke7zIWQtFGTAoS5KcXOFypFlc89fvr7mj7+9sdiQ3M93N1/er/Vf5Ilo8uTj/ehGc7TZLKrzOqr3rESmzJPxgyhIhJ2e7FLZiyrU/bQlkuYttCb4wU9Z+uX6x/3T/Bmu42+4qOXvwxcWwfBUflRxLyVEWy2buLeKtSi4oFN+tkruPVxidJio5e/BFXKF8v17bBJ9asoTBxQdlc6DIWUu4PWrJkKFsIWUe5e+7wuVIE13zj+UfE9+nHr/mivL/zxTmU0s1RrZLKauAvi7dIqi8zip9ypGhlgwGZYt7s0P0Cltr7Fn7j1cq9O7XiuBMSfvf6+XLsyFqyYHswRcFo8CTubt3VXIUyYvMlc2cSt4q45KvU0uT3CU94RvXYBCGYw+VXB2S7sXlveRlRpLtASNnLdSSwcAt3SxxhauRJp535OzG5XBCUeoobavjidt6w8WgImcNGqJrIGyBQVlFaXaIbmFLdgXmb7JsRazp3F9ff60S2X7W31N7aTpTHrx6q+TZTKjkhLm7N1Xy8n3r5RvWso1Khs+lVy25OiTdi0ctOf2ukmwPFDlrCRMntWTIcKu2uxhp1q8pJqhOv00v9xRMr/Eeq2fisgro6+ItgoqcNWiIrqHMkvCDecLi3vKlFAVLxR5Cnvmoh5BXkQv1/gbrELXkaO7cx3IxLF9l7u49lbyI5EXllnw9equMC15jvlslh/HKe8mQoYlKlgibDZWvJqOmYA615HVakh0jRs5aKMqAQZEi8XKFa5HmkDHuUSLSuUieurbyx6Wz6nASnM1MNxsGFTlr0BBdQ5El4SdTpJL7hq2p/7NI9G0Gl33Ms51h31NN7Cpbb2hIuOHeKrnkjcKSNo7MA/M9lbx833pRsCUqedumRCWXtHGEWjIYdFPJJW364VBLXqaZJYoOGDlrCQ9FLRkyFC2keLnCtUizuKZKcvNZUW26auysXmwWrTc0DCpyVv2ND0eRJeEnU1QB7Ru2AnroKnDReFszBaJ325Fplx29VfJjasklbRx5XyUvInkVsB+gkv829dVzvMLwoJJV3v+N62WWWZ9wwMhZC7VkMHArypS0uRRp4oXPOKY9iyufIM10YqCsLeROuNWSLwYVOesDVDJhCwzGD1svtGBk3vfELugVuPS2H7tSvaVovaEl4ZapJSe8rZIVkUwtGX4AqGSVt2vJyySzecABI2ct4bGoJUOG4WvJ8bozX7/nDHDz268T+x63h76/5ua/Fu0byPW+JKcXHJpashfUksGgSCX3DFszu7izwfbRXdQrCAW7gGhbZkORJRtCLVnnXZUcxe5OEn9ILZn3kiFDGI6o5IR330teV243FxkwctZCUQYMhi/KhDEsvDTvi00Curvc6sqTRpZ9E782aWQm5YytrsS5ImdrGFTkrA9QycGSVz4B+DEUlQt6hq2JTSg6Uv7zCIIVCzbhLVDhPb1V8hy3qCUnvKmSVZH8CSqZWjIYUEtWebOWvC7cbq8xYOSsJaSb1JIhQ5G283KFC5Fm9c3jFwnXxHCb+Oh7J9YLnX+bemlTKVBniiqgXpZUkLM+QCUXWRJ+MkXazsvZLoStiSWYzHx/r5EpUODcv7ffgSlo/6vyzyu/6K2SH/P3ki8uXl7lTZU832pg/9vT6s49W5Vc8pegblbJ3d8QgNFpopKzB4WSiaIfb9aS50cL7IOkunPPzZGzliIJBD+ZMkUyD/L3XeFCpAlDeCYNPWtOKDsm1hpMch/rodPHkOPZ5zylrAL66qBFUJGzLt37WBC2wKAsV54dokvY2oab6Qbk6ts3RcrWwGLXhe3Xr8zYxhG6q45wt09QySWjwJG5u8sqWaRrIl5lb04l8/eS4dl0U8nSZNAU7L1a8tnMInsHipy1hCejlgwZyhTJPMjfd4X6SLMUZLSJcXHc9b6WXUo0WIs7suNIvL1r7uy23nAxqMhZuSs/BGrJYFBWAZ0dokfYmpAdE1sBvoSY0kzfDFoHlJiYh1pyIHvwxcWwfJW5u6sq+Uwkf4hK5r1kyIBKVnnrN67PRPKAkbMWijJgMHi6Gc/Qb3FxXdleztaDwVLe0Z9jOXwtkty63qAgZ+Wu/BDKqvLwgxleJcdzkrs8TTdOMIJWQhoT8/RWybPluqtksVrOEBfD8lXm7i6q5ChuU3lb8PXorTIueY9ZmtylkvlLUGDQRCWXvJojTYpD0r28U0teprPEOONFzlrCE1BLhgxl2s7JFeojjWydCNel0BLjUryJkxvNZ5Dx6MU5OKSbt1lSQc4aNETXUGZJ+MGUfU+4W9hatW3adz4IpSxBTrYt4vULA0Hvb1yPUUsuGCkFTTyZB+Y1laz/ctdMgUreNilQySVC2hNUMhiE4eiukmNEz5RQCpr05I33kpfpLD1/vMhZC7VkMCgrJTi5QnWkiVtnqZB0uhyP27J5JJtwLpHgYpArq4A6WVLhdVZ51jguhC0wGDts5ZfrYpAqdfB4rdIygDQvvDy15EDBYom0uCu+XlfJGZFc8hVqafGqDe82VEq+lO0J7yWDQZNacoH/FwSRnlyvJS95s3L6eJGzlpBuUkuGDGWKxMsV7Eb7nuLWqW/L8ThtHjYTcteTQ5eduawC2i6oXDxtQKglg0GZtusVttZgognr2uJwbF/q2VGFy6ZBb5U8Ri3ZHikFSyWuzHd0SSWfvpQ8YWvafW1YNjIquaA67UqQQP8tNgJQ6KWSL5Y37uJ6LTmIhBnl0caLnLVQlAEDL21X5grSqDjSvDYy/e4zwnibp9ePd6k0iOdejnFe6w1Xg4qclrHtUwiWHHWqgSEoS4R6ha1cnJmIQavUVe3H2CPNyy7f+xvX8912V8n21eJaxaVizAXmD/2KSs6J5ALZu1fJtqq+WyVTSwaDNirZjsKDq+TLteQ4X+lPJsfGiZy1hMejlgwZChdS5mH+vivURprXRqbb/QXty0uD9IIxr72+4lVYAX310iCoyGnnF34M1JLBoLACOnvE/WFrOeEkmMjRUleNVyuNCNK8LFujljwjR88tYY8BX+b+LqjkqGtPlK0cOxe1e10ct87fOpYGd/141/xeMr9xDRnaquTzBFEajJqBXf2N6/jgJ4aRY+NEzlqoJYNBXbr5ritURhq70rO/oL2Y92qgtIjrZddDXGEF9NXN25ZMkdNGjdEVELbAoLACOnvE+85WGbbWaCKbR+w4taP22yVVl++tkmfT9VfJps1ex+8Lr/OYq1fJuZeSA2bp93U8ql7zt7nsYrMz1JLBoI1KNhdUryZud3GxlrzUj07mn+EiZy3hAaglQ4ZCReLkCpWRxq707FvY6eFZiyUUyPYFCiugzYLK1fPGo9CS8HMp1HZ9wpZ5WTtO7Xk1L3btqnStt0oepJZs2SxOEMXdvct8Q9Uq2RLJpqqNF4i14cNmQvx+t2y2p/sbAjA6YTz6q2Qz4EhUfyOFbMu195ItkTxe5KyFogwYFCZJXq5gNdtHmnjVc9fet7Czz7MWr90XgshKYS25WVC5et54FFoSfi5Dhy2zvXVbR6R5qWtXXb676gh32l8ll35k9bWYi8wdVqvk/EvJATl+JnuPX7G2VLUcvu21ZGrJYNGmlmyGVTk87OC8VkuOU9v5c8nxYSJnLSHdpJYMGUoXUuaB/r4r1EWaWMM5z4TUWnImPTxRyfG23olwpRXQV0/+QUXOO7fVYyi1JPxYSrXd7BJ3h63ibmXTRJqXunbV5aklvzhbPxVeR8s/sreZP8RalWyLZOsr16+jqyo2vnIdRfRtryXzXjJYNFLJRs0mnl0ckO7mUi3ZFsnDRc5aqCWDQakicXKFykhz2EzZBzYjzE1Ig8MF4129U0oudrZWQUXOGzZIl0PYAoNSbdcnbFm+aMepPdK81LWrLt9bJc8PN4BKjkbTF0zs9Vpv5vupVMkFIjkpFu85fuHaKhbf/oVraslg0UglxwhykppEPSmb43GllhwfKudyo0XOWsIzUkuGDKWKxMsVpGFhpDGS3GNgi7dxLnalweE+Y7dveXLpekOroHL5xOEotST8WEq1XZ+wZcWtY/uv7++/vqf/yeaR5Dal+dltJ7eTo/c3rkepJcfjui3+lKPvLKPWMY/cOpVsvpQ8I0102Ztq6LyqloMZVe5N7/EKw9NKJcfjehCQg+OOzQu/cb2Uj7LnSZNRImctFGXAoLiUMA/1912hLtKY+Z4cl9QnOvVpJqTHwSUWyPY1grPdackjcmJx1jguxZaEn0pxIjT7xN1hy4pbcnRpn796eli2z3zEOLyHWrKQ+8ziOsWNhpo/9CqVXCaSs+XfeImN6k2ryxvitbId+kItGQxaqeTsomoMH/WJ213U15JXkZw9bbDIWUu4fWrJkKF4IcXJFeoiTYxbZ6lNPB6dWDZP45wcPtyn7K2LIAnFFdBGQUXOLM4ax4VaMhgUa7suYcuIW8nFjNW95BlyD2Xca0JvlTxMLTl+ZpoxwiwZuDEFnm+nSiXPdxjIvyQci8Na/VdTvbJLU8KKqG5OUMm8lwwZwpBsoZJziWIM4T1DqUH9e8nzEwXyQXawyFlLsQSCn0pxkuTlCtK0MNLInrPAJUeXw/EmT7xaP5x7sgqKna1RUJEzi7PGcSFsgUHx9y77hK18SJGDa79R156EOTm4XiyqZN3XY+dlMaT7N1jDrY6gkherph+x8fk0Yf4Ua1RyyUvJM+cF4KUaLdszGSkcr3Tfb3fxjWswaVVLXuKAMv7yIXkIqmvJ8ZlMfxsrctYS0gBqyZChXJE4uUJdpIm7dD9NTljuRA0GyxdIZPvFsveCMt1SXgFtE1TkzIHDdCnUksGgvALaJWxFZ1S9MSZjm35lhx620utnRbge5U6hlhxRPhdB9r87Q1RRq5KLRfJSTE6/cy37D/pZdqZaOFeVbgbfuAaDZir5PKxnI/Ig1NaS4yKy/VBjRc5aKMqAQbki8XIFaVwYaWSf6qnLHa0dK7tW5NDhWlqSe4XgbGVBsk1QkVPffYwBKLck/FDKtV2fsBWDiqJ7FxW7udL5TeqqV/aozl4Zz3qr5PlZhlDJi+WO5jjb35R5SJSr5EX6FvzcdBTUR3V7sn+pMB+Kz2f724JKBoN2KvmsCuNVaWlKZS15mZMy9ogMFTlrCTdJLRkyVCykOLlCXaSJF1euvrjxJvFZLp6Gg9/LpWTHi8rSyznl6w1eltwj5xZnjeNSYUn4mVR879LJ2erC1nkcUo8sO9ObWa6/PbSEsiTK5Q6p9FbJ49SSTz6Fdd64NQWuU8mLYi2RrEvjnRz+x1KNPl5CP7Do8ltLyfM3rnkvGTK0U8kn0XXJRHsGUpO637he5p2SU4aKnLVQSwaDiiSp3hW+JuSfG+oijexN73K5zC6qLZc53s7q9ftbkp3vO3KFs3lZcoecW5w1jgthCwyGD1trdNpffw1DuxPWyxzE7UmyIvtSdw++M1NonZr1hjaEmx1DJW8+tPVTOJs3WjOPiFKVvIrkoleEF9m70b2ZS6yHNoJ4vYbsuAlqyWDQUCUvk8l2DK5hQ3aMSVUtuTLsjRQ5awn3Ti0ZMtQoklpXeLVP/LIu0qytdz2saviQhq4X2iaca1J8mGLjdd6feGsqoE6W3DE3GT0iFUEtGQxqKqBOzlaZIMnuic1Q3oShfdg6iXKb6++fdrN/e6PrYyniX6fGki0YqJa8M+vc7vdmmrnZSFUqeZWsp+zqwGv7f86a+B/rF7a10vAqk//4+3ydv286PFaeG/O3qcue4xWGJ4zKRip5G2G/5sj7taxLlsfcPlS9l7yZqM7YzZADRc5aKMqAQVWSVOcKMXwk+WZdpNm0jt1u+03Snq1/vy7/+2u7b24UWS7+foALz3C3JbdIm6M5HkiVJeEnUlUu6BK2tiEqdrsNQ4cTtlHudfVp32nY2kW519Wn5rtrvPbZ9FbJc9waRSXHRhrvzxBVzOOnUCUXiOSDmJWdGprq3YjoI/d+35paMpg0rCXv4/qBwYdlTS15O/Ocsb+U7NS4OXLWEmZxasmQIQyR8oWUedDrnKeJaV5SF2nyHpucsCnLaOzvM167ONc6p64C+upWpcaSG0raPIM6S8IPpE7bzY6hM0zYOjT/63u/43ifhyh3bF5um97fuB6qlpyZPJKB0ph5sJWp5BKRfBC/m+rwAb00fNrF3SJ5riXzXjJkaKqSz+N6zyhaQkUtebP8e87+UuNEzlrqJBD8QOoUSY0rrNFEdmyoizSZ7FQ7YVeCObK/z6X6ItvvEJytPFB6WXJFmnyASiZsgUGdtusTtnJhSDkh11y5z23hOKHcNNSS95wNlcIajB/lKvlc8W45qN+zk3SRfCqTbxfJ1JLBoq1KPgvUww/K8lry+Xy55XCpYSJnLeHzpJYMGSoVSYUrrMFEdmypizTnXqvnPKcJ5/G3cWS3iydXVkC9LLkgTT5AJVNLBoNKbdcnbJ2GId1JzxcDj2Fr5lfl5U/orZLHqiVPaGbtYKBilVwmklP5q+nejOhVuznT1A3p/d0HGJ7GKlmfTdJ1zNEo/o3r7ALsSnKpQSJnLRRlwKA6SSp2hSXpU49WRpqTjPDshJOs+Hgnsers4srVzuZkyYi0+QCVXFeVhx/IM8LWmTg/OeGs+dmDngTFTBhV6K46wh2PpJLXEbDQI6bOd1Gikou+b60J2vRl4+wPZK9/KSryzw4imVoyWLRWycoCpbqOORjFteSzeeVAeqkxImct4XGpJUOG+oWUUldYcr6Tw3WRRquc5Fwwvcs/vpXs8dWsKq08o74C6mRJoaTNM6i3JPww6rVdn7ClJRwZD1Wilhq2BLWcXBkAqCWn7D+GL5fpoZb5HgpUcqFIVsu+e538+vnqDHud/Pp17NsJKpn3kiFDGJ1NVfIx8sbfTxyb0veStUlFQ7vUCJGzFmrJYHAlSSp0BfnixunVKyPNMSW02u/v8jTZnK7qE+OuVECdLDnzauP0MF0hbIHBc8LW7oetJ4z2h6hlPWSik6vzkt4qeY5bV1RyU76+Xj+H9t0t0ZsHQtmvd73B3//+z1n6/tOUyDP/mNrPzTtJ5An+EhQYXK0lV/FrChHBFb6fIZEnqv5e8mX6R85aQrpJLRkyXFMkZa7wa5rpszGkNtKs3f4uccHN5TPNfznNudcqoE6W/CiuWRJ+ENe0Xa+w9ep1umhJ5vD7V7x62eWn5vFuSoLikd4q+XIt+cO5RyU/D1QyGNyikp9H1d9L/kFQlAEDFIkXOJsXwZIkQpCBRMiL+u+uOzP1j0pOQSXr8F4yGDA5qNxTS34eYY2ZWjJkQNt5wXqDF1gSDHpXQD8HasljgkrWCRLov8VGAAqoZJXi37j+YSCBwIB00wsqoF4QtsCgewX0Y+g+AUz9o5JTUMk61JLBAJWsQi1Zh1oyGKBIvKAC6gWWBAMW97zovd5ALVkHlawT3kvmN64hQ/AcVHIC7yXrIIHAgHTTC5zNC6ryYEDY8qK7Jaf+UckpqGQdaslgQC1ZhVqyTkg3qSVDBrSdF1RAvcCSYMA3rr3orZKpJeugknXwfDBAJatQS9ZBAoEBisQLKqBeELbAoHsF9GPorjqm/v/4T/k3LKCSdaglgwEqWYVasg7vJYMBisQL1hu8wJJggEr2orclqSXroJJ1eC8ZDFDJKvzGtQ4SCAxIN72gluwFlgQDEiEvuk8AU/+o5BRUsg61ZDBgclChlqxDLRkMWEjxggqoF1gSDFjc86K3Jakl66CSdbq/IQCjEzwHlZzAe8k6SCAwIN30AmfzAkuCAbmyF90tOfWPSk5BJetQSwYDaskq1JJ1QrpJLRkyoEi8oALqBZYEAxb3vKCWPCaoZJ2gknkvGTKgklWoJesggcAAReJFcDYSdw+wJBigkr3obsmpf37jOgWVrMO3SMAAlaxCLVmH95LBgIUUL1hv8AJLggG5she9LUktWQeVrMM3rsEAlazCb1zrIIHAgKKMFzibF1gSDAhbXgxRS0YlJ6CSdVDJYIBKVqGWrEMtGQxQJF5QAfUCS4IBKtmL3paklqyDStYJEoj3kiFD8BxUcgLvJesggcCAdNOL4GxY0gMsCQaUC7zo/Y1rask6qGQdaslgwOSgQi1ZJ6Sb1JIhAwspXlAB9QJLggGLe15QSx4TVLLO3zqPVxgeVLIKtWQdJBAYoEi8wNm8wJJg0L0C+jF0X2+Y+uc3rlNQyTrUksEAlaxCLVmH95LBAEXiBesNXmBJMOiu7T6G3paklqyDStYJtWTeS4YMqGQVfuNaBwkEBqSbXgRnw5IeYEkwIGx50b0qP/WPSk5BJetQSwYDVLIKtWQdaslgwEKKF1RAvcCSYMA3rr2gljwmqGQdPB8MguegkhN4L1kHCQQGFGW8oALqBWELDAhbXnS35NQ/KjkFlaxDLRkMqCWrUEvWCekmtWTIgCLxggqoF1gSDFDJXvSuzVFL1kEl6wSVzHvJkAGVrEItWQcJBAYoEi9wNi+CJZFAkIFEyIshasn8xnUCKlmHvwQFBkwOKtSSdXgvGQzQdl6w3uAFlgQDasle9LYktWQdVLIOKhkMUMkq/Ma1DhIIDEg3vaAC6gVhCwx6f0/4c+huyal/VHIKKlmH95LBAJWsQi1Zh1oyGKBIvKAC6gWWBAMW97ygljwmqGSdIIH+W2wEoBA8B5WcwHvJOkggMCDd9AJn84KqPBgQtrzobsmpf1RyCipZh1oyGFBLVqGWrBPSTWrJkAFt50VIN7GkB1gSDPjGtRe9VTK1ZB1Usk54L5nfuIYMqGQVask6SCAwQJF4QQXUC8IWGHSvgH4M3dcbpv75jesUVLIOtWQwQCWrUEvW4b1kMECReMF6gxdYEgxQyV70tiS1ZB1Usg7fIgEDVLIKv3GtgwQCA9JNL3A2L6jKgwGJkBfdJ4Cpf1RyCipZh1oyGDA5qFBL1qGWDAZoOy+ogHqBJcGAxT0vetfmqCXroJJ1eC8ZDILnoJITeC9ZBwkEBqSbXlAB9YKwBQZ879ILasljgkrWoZYMBtSSVagl64R0k1oyZECReEEF1AssCQYs7nnR25LUknVQyTqsj4EBKlmFWrIOEggMUCReUEv2AkuCASrZi+6qY+qf37hOQSXrUEsGA1SyCrVkHd5LBgMWUrxgvcELLAkGVJS8oJY8JqhknaCSeS8ZMqCSVfiNax0kEBhQlPECZ/MCS4IBYcuL7pac+kclp6CSdVgfAwNUsgq1ZB1qyWCAIvGCCqgXWBIMUMle9LYktWQdVLIO37gGg+A5qOQE3kvWQQKBAemmF8HZsKQHWBIMKBd40b02N/WPSk5BJeugksGAyUGFWrJOSDepJUMGFlK8oALqBZYEAxb3vKCWPCaoZJ0ggXgvGTKgklWoJesggcAAReIFzuYFlgSD7hXQj6H7esPUP79xnYJK1qGWDAaoZBVqyTq8lwwGKBIvWG/wAkuCQXdt9zH0Xm+glqyDStb5W+fxCsODSlbhN651kEBgQLrpRXA2LOkBlgQDwpYX3S059Y9KTkEl61BLBgNUsgq1ZB1qyWDAQooXVEC9wJJgwDeuveitkqkl66CSdUItmfeSIUPwHFRyAu8l6yCBwICijBc4mxdYEgwIW150X2+Y+kclp6CSdaglgwG1ZBVqyToh3aSWDBlQJF5QAfUCS4IBKtmL3paklqyDStbhWyRggEpWoZasgwQCAxSJF8HZmL49wJJgQCLkRff1hql/fuM6BZWsQy0ZDJgcVKgl6/BeMhiwkOIF6w1eYEkw6K7tPobelqSWrINK1gkqmfeSIQMqWYXfuNZBAoEB6aYXVEC9IGyBAd+79KK7Jaf+UckpqGQd/hIUGKCSVagl61BLBgMUiRdUQL3AkmDA4p4X1JLHBJWsg0oGg+A5qOQE3kvWQQKBAemmFzibF1TlwYCw5UV3S079o5JTUMk6vJcMBtSSVagl64R0k1oyZEDbeRHSTSzpAZYEA75x7UVvS1JL1kEl64Tx+t9iIwAFVLIKtWQdJBAYoEi8oALqBWELDKglezFELfk//xUO/Bns8o//F/b8//jGNRjMC3/iRrAwq+T/JRsQ+RdqyWAwKxIZL/AG/zKvN8gGvMHLkjI+ARRmbSfjBd7gX3rXkv916h+ghn+XsQOgIKMEoBgZOgAKMkgAhoJECDLIKAEXejrb/I1rgAqYHCCDjBKAYmToACjIIAEYCxmfAAoySMAFVDI8CVQyZJBRAlCMDB0ABRkkAENBIgQZZJSAC6hkeBJMDpBBRglAMTJ0ABRkkACMhYxPAAUZJOBCd5X81xcc+A52+VM2YKH3e/QwPEQUlf8IdvlP2YCF8Bsn/HoXZJiHiAwXeIcwfWNJD4Il+fUuyICzedFddUz985egUua/BPUvsgEL8+/2yb8BFEJI4y9BJcx/L5m/BJXAb1yDAX91xwss6QWWBANyZS96W5K/l6wzq+R/lQ1Y6L6qA6ODSlZBJeuQboIB6aYXwZI4mweMSTAgV/aCWvKYoJJ1mBzAAJWsMqvk37IBC+HdFmrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE6gl65BugkGYdBgiHjB9e8GYBAPKBV50D1tT/6jkFFSyDtMsGDA5qFBL1qGWDAYspHiBJb3AkmBAruxFb0tSS9ZBJevwrgUYoJJV/meIKNSSE0g3wYB00wss6QWWBAOGiBfdVcfUPyo5BZWsg+eDASpZhVqyDrVkMGAhxQss6QWWBAMqSl70Vh3UknVQyTqoZDBAJavwXrIO6SYYMOl4gSW9CJYkbEEGnM2L7pac+kclp6CSdVgfAwNUsgq1ZJ2gkqklQwYWUrzAkl5gSTBAJXvR25LUknVQyTp4PhgEz0ElJ/Besg7pJhgw6XiBJb3AkmBAucCL7rW5qX9UcgoqWYfJAQyYHFSoJevwXjIYsJDiBZb0AkuCAbmyF70tSS1ZB5WsgwQCA4aICu8l65BugkFIkhgiHmBJL5BAYNC9AvoxdHe2qX9UcgoqWYfJAQxQySrUknWoJYMBCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJVeC9Zh3QTDJh0vMCSXgRLErYgA87mRfeq/NQ/KjkFlayD54MBKlmFWrJOUMnUkiEDCyleYEkvsCQY8I1rL3qrDmrJOqhkHTwfDILnoJITeC9Zh3QTDFia9QJLeoElwYAh4kV3S079o5JTUMk6eD4YUEtWoZasw3vJYMBCihdY0gssCQbkyl70tiS1ZB1Usg6eDwaoZBXeS9Yh3QSDMOkwRDxg+vaCMQkGJEJedP8G69Q/KjkFlazDN67BgMlBhVqyDrVkMGAhxQss6QWWBAOWpLzobUlqyTqoZB08HwxQySrUknVIN8GASccLKqBeMCbBgIqSF92dbeoflZyCStZhcgADVLIKtWSdoJKpJUMGFlK8wJJeYEkwIFf2orclqSXroJJ1kEBgEDyHIZLAb1zrkG6CAemmF1jSCywJBgwRL7pX5af+UckpqGQdPB8MWEhRoZasw3vJYMBCihdY0gssCQZ849qL3qqDWrIOKlkHlQwGqGQV3kvWId0EgzDpMEQ8YPr2gjEJBjibF90tOfWPSk5BJevg+WCASlahlqxDLRkMWEjxAkt6gSXBgFzZi96WpJasg0rW4VskYIBKVqGWrEO6CQakm15gSS+wJBiQCHnRXXVM/aOSU1DJOkwOYMDkoEItWSeoZGrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE/iNax3STTBg0vEiWBJn8wBLggHfu/Si+wQw9Y9KTkEl6+D5YEAtWYVasg7vJYMBCyleYEkvsCQYsLjnRW9LUkvWQSXr4PlggEpW4b1kHdJNMKBu5wXTtxdYEgwYIl50r81N/aOSU1DJOng+GKCSVagl61BLBgMWUrzAkl5gSTDge5de9FYd1JJ1UMk6SCAwYIioUEvWId0EA5ZmvcCSXmBJMGCIeNHdklP/qOQUVLIOng8GqGQVask6QSVTS4YMLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZzAb1zrkG6CAZOOF1jSi2BJwhZkoFzgRffvrk/9o5JTUMk6TLNgwOSgQi1Zh/eSwYCFFC+wpBdYEgzIlb3obUlqyTqoZJ3uqzowOqhkFd5L1iHdBAPqdl5gSS+QQGBAruxFd2eb+kclp6CSdZgcwACVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmFWrIO6SYYMOl4gSW9CJYkbEEGnM2L7lX5qX9UcgoqWYdvkYABKlmFWrJOUMnUkiEDCyleYEkvsCQYkCt70Xu9gVqyDipZh/UxMAieg0pO4DeudUg3wYBJxwss6QWWBAOGiBfdLTn1j0pOQSXr4PlgQC1ZhVqyDu8lgwELKV5gSS+wJBiQK3vR25LUknVQyTpIIDBgiKjwXrIO6SYYhCSJIeIBibsXWBIMSIS86P7d9al/VHIKKlmHyQEMmBxUqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBAMmHS+CJXE2D7AkGHSvgH4M3SeAqX9UcgoqWYeEBQxQySrUknWCSqaWDBlYSPECS3qBJcGAXNmL3paklqyDStZhfQwMguegkhP4jWsd0k0wIN30Akt6gSXBgCHiRXfVMfWPSk5BJevg+WBALVmFWrIO7yWDAQspXmBJL7AkGFBR8qK36qCWrFOskr/k/7+HX73TbFQyGKCSVYrfS743ovzuXd4m3QSDMOkwRDwonb5vzjPuDXkuMCbBgFzZi+6WnPrvo5LHHj/FKvn71uf43fs7m6yPgQEqWaW4lnxvRPnVu75NLRkMWEjxotSSN+cZ94Y8FxiTYIBK9qK3JbvVkn//If/Q+P0VcqfJMl+9VhnLVfKtH9+v3q824vlgcEkl//79FfKOaXD9Vebyf36/QsTX10O+xVxcS743ovzuHVFIN8Hg2qTzyymJ+JJI8/3V/Ztcb1NqyZvzjHtDngskQmBwrVxA2ErpXpsLhqxSyS/bRy5/kt+nKvn3rFAX+linQiVX3WG0nmzWMs1eNbWf0Dzgt9bA5AAGFyaHvcfbAUkmksgjZoHyWvLIEWUS1TN+ESWoZGrJkOHCQsovpyTiGJn6rii9Taklb84z7g15LrC4BwYXcmXClkpv1VFdSz7Y/424KP86cvyAPTOycua7KFTJNTf4ZoCfk1T5dwH+OS1fpwWDMOCqhkgcpVtyMfF3dKKF7wfo5OLfuB46ovivu5FugkF9kuSURCSBZsJv5HcgWLLE2W7OM+4NeS5QLgCD+gooYUunu7MFC9ao5NB+w0Xjh2RL/rnnl/YJdzBQlUquWKp5M8DPSWq5OfxzWiYHMKhdSNE8fuJU+KZTycT4MrmmllzzPPdGFP91t3D/1JIhQ+1CilMSEWfPIw8uzNTUkm/MM+bP67YkygUW98CgNlcmbJ3RW3XU1pKPH+TFuBhOlX/u0MpKgds/4TqVXH5/bwb4l32KB4x/TotKBoM6lXzm8afDLKQnCsMPyor3kktbztwbUd7Nh1NIN8EgTDoVQ8QpiTimOiu3ZyNulE7fN+cZ94Y8FyrHJPw8KnNlwtYp9VV5Z4L5ylVysk5xLS7On6T8e8vZMsj9taJKlVx8f28GeDFQ6Yjxz2lRyWBQpZLPpoaAmoScTgKjpyx1teRRI8q7+XBKuH9qyZChbiHFKYk4DTQTj50Bq2rJ9+UZ94Y8F1jcA4M6bUfYOqe36qisJSeFnEtx8ZVqycaGXcr8PSH/DNy8EFKrkkvv780AHy1UOGT8c9ruqzowOlUqeRfU9x6vDrRtADpEiMGHZWUtedCI8m4+nEK6CQZVSZJTErGPREeeOgWWWvLmPOPekOcC5QIwIGx50d3ZgvGKVXL6GVyKi69TZWPDevkvGRjrO4g3J1LVKrlwxSc2l81algWnsjHjn9MyOYBBjUpe/Xt1+U2QSXxqXXD9ljG9eZmnas31dmpryWNGlHfz4ZSgkqklQ4aqhZQ1HryTRKyBJoaa37vfnx071pxSasmb84x7Q54LLO6BQVWuTNjK0Ls2d/nvJYfzJq7ERRkQsrWyDJStQdSd7ZmHVpVKLlvxic1ls5Z1xanIHP45LSoZDMKAK1TJ+nBeQ/1xpK3tN862Nh96Dqj6jesXRc9zb0R5Nx9OId0Eg5pJR80X1J1ZpP3E5pRtwlk02w9HsGSJs92cZ6wh744kyoVSS8KPpaZcQNjK0V11BNPdq5LjZyabC0tk3ttjGSq35sAXVHLRDb4Z4DdrRSWjxj+n5RvXYFAxOSzh+xC8F6c6DFw9FixOMfTArK8ljxhR3s2HU8L9U0uGDBULKSexQA8c56w+uI9Mq7c8cxKsriWXPWhs/r5KviPkucDiHhhUaDvCVpbeKrlDLVnOTGKc7E7MET/6W810RSWXLNS8GeDXNd4ie/jntN1XdWB0ylXyMpoTx9F9/kxUn19nIKrfSw4MF1HezYdTSDfBoKJuNw/OieNQ1gPKKdI6dcD1b7UXJq5jUTp935xn3BvyXCARAoOKitI8nCeOzQlbMzVV+SYEy92qkpfPS7YjMf9KB0Q8wy8zs7mkkguGYGwum7Wsi0ITtuv457RMDmBQHtKi6k0H1DLOZftFdJ7EzfTmY3GlljxeRHk3H04J908tGTKUL6TE0fxmErEsx6Xut/qL7HgUF2rJd+QZ94Y8F1jcA4PyXJmwlae36ri9lrx8ksePS/Yqa4nnY6gd11SyPQTfDPDbNd4C4/vntBXrY/AzKVfJ0RmU8oE2O5yL6qV5iQrtxKVa8nAR5d18OIV0EwzKk6R5bE68mURIW3WULw5T4sujUWrJm/OMe0OeC5QLwICw5UV3ZwuGu1Elb8Kv7BFygTZGxatB+AIXVbL5Ub4Z4NcloRlLFPjntEwOYFCukuexOSGbO+TQdqxlfGfxC9kekGu15NEiyrv5cEpQydSSIUPxQopTEpFZjpuouNBwXKolt88z7g15LrC4BwbFFSXClkFv1XF3LXkTD2WPIDv1yCfHbjTURZVs3uKbAX6zyDBjLAz557SoZDAIA65IJWdHpzjKZqzFSUBtHg+Ou1J64TeuZ8aKKP7rbqSbYFA86cxDc0I298ixggtFl9IHeXSBJ06DwZIlznZznnFvyHOh1JLwYyFsedH9G6zBcPep5JjMBmTXi3z2FU+TzRu4qpKtD/PNAB/NtJBf5fXPaVHJYFBcS/4Kfzx/Qh3DqaPkXUcOXgll93CxlmzmYvdGFP91t3D/1JIhQ20F9N0kwnApOXrV43pysZbcOs84hry2SZQLLO6BQWmuTNiy6K067q0l75YoZd+LP2XnyaKlHPXLzSwuq2Tj03wzwB/XeI3pyz+n7b6qA6NT/o3rHOnkIDtORl/5ZNKJi+8lT4wUUd7Nh1NIN8GgtG7nlURIwzO/Gz7UnFOabt6cZ9wb8lygXAAGpYkQYcuiu7MFu92mknfRUPa9kH1nppAT77NUtUpeHy17k28G+JikbgyZm778c1omBzBopJLjjpO5JA71fNGjI9W15CEjiv+6W+iYWjJkKF1ImUfmubvIEDenL2vWHD7UnFNbSy6MCpbFLGI3a3ctQ54LLO6BQWmuPI/l86aEre61uVtryZuYOyE7Z2LydVZruX0dpFolbx4u93m+GeCXJDUO+YnMqPfPaVHJYNBIJVuTxeuw41B3prqWPGREeTcfTiHdBIPCSccrifj99eLsOlY/A1M6fd+cZ9wb8lwIliRsQYZCbUfYMumuOoLdblLJm4gbkL0zcSScRmI5flsOXK+SyyL8mwF+TVKLpi//nLb3qg4Mj6tKXsfaa/t88JVOJr2oriVvI0omH7s3orybD6cElUwtGTIULqTclURERylx5sGorSXflGdoIa9dEuUCi3tgUKjtCFsmvVXynbXkEFg2yN4ZM+5Jg9tMdUElF0X4NwP8JkmN/5w4Hff+OW33VR0YnTDg3lfJ4SoTy8g1h3JsMOpSafVvXG/+OU5EeTcfTiHdBIPCScf0BGnw7vw1+npchmDJEmerjAqb5pe4N+S5QCIEBoQtL7rX5oLd7lHJa/x7IbtnZNf51e7+iK+o5M0Tnn6kpkvk2SapBau8/jktkwMYuNSSk4VPOwBIgyvB7A4u1JIHjCjv5sMp4f6pJUOGwoWUeWDekEQ8ON2sryUXRYVt8yvcG/JcYHEPDAq13TyUCVs5equO+2rJy5qkEuPisfNSy90f8dxfrUreRPgzu7wZ4HdJ6mLR08v557R84xoMXFRy4u/iOJmx92rgONZ9qX8vebsxSkR5Nx9OId0Eg7IKaBy8zZMIOxQNS2m6WRkVds0vcG/Ic4FyARiUDRHClk13ZwuGu0Ulywl/fCkfesy9MqUWaeGXneW5ppI3Ef7kUd4M8PskdV3lPRlC/jktkwMYeKjkOHWsQ82O8U6TSSsu1ZKHiyjv5sMp4f6pJUOGsoWUOHZbJxExzjxxGrxSSy6ICvvm9dwb8lxgcQ8MynJlwpZNb9VxWy05RrZvLZstSHClxXsjpZz5jupV8ibC62tDmQD/W9YPvr/OH/KQpMbNszHkn9OiksHAQSUv43p1ItmRGckFQaQn12rJ24iiz6P3RpR38+EU0k0wKJt07koiosP5ucB9lE7flVHh0HzH19fLYF9f5zrgNORVJ1G3ESxJ2IIMZYkQYcum+zdYg+FuUMlLnFWHhXyCOUMUNPFkvskLKjnaZUKdFE4D/O94ZEbMmpjqmKTGBicR2z+nRSWDwfsqOQ7bzUiLuzIyMzbJLMr25GItebCIksuHrxFUMrVkyFC2kCLDvXUSsclknse1WvIbecZ64sS3BDDZXFt7hbwbYXEPDMpyZcKWTW/VcVctWZqH9kmiVnQxj5FSwXyTV1RynDAmtAh/EuD3GW1gPjkxVZKkrudplvHPabuv6sDohAH3hkr+vUmsVk38p+yRTY042EvqtR248hvXM0NFlPN8+Cqkm2BQliTN47J9EhH945GzYGkF1CnP2ITyF6+TZWNtHa8umxdD3q1QLgCDslx5HsmErSzdnS1Yrr1K3n5GSaJWdDHlrJbM3V1RyUaE1wN8MptMqKZKk9R4QXUY+ee0TA5gcL2W/OtP+XaesPGfEveXJn6D3ZXLteShIor/ulvojloyZChbSJnHZX5klkQRg8U7ZPtZXK0lG1FBzzN+reeshAgm/0wvLpvXQt69sLgHBm6Lez8+bPWuzd1TS15ytu3GfOSF7Gk8UmqYu7ukkpdEciKN8GqAX4bwjmlYJA+tJKnryek48s9pUclgcF0lh8xjw7bwWuL+0sRvsLty9b3kiYEiip4PvwPpJhiESWcQlby44jMnwdLp2yPP2EStLVMIlH+trT1C3s2UjUn4wQykkn9I2GpGMF1zlSyNX0li+pnH1EtZNlx4f6RUMXd3TSVnF0K1AL/OP3uUHzrTktT19CRq++e0fOMaDK6r5L0j7HxHDmWH3quJ42B35XoteaSIoubDbxE6o5YMGYoWUuJAbppErI4oOx7G9VpyNipozVdTHfidBmolhm1OLwp5d8PiHhgU5cpxnBO2MvRWybfUkmNUez1o+pnH1CtXaYkfdEk1xoH5Ji+q5NxCqNI82uPF94T8U/mjWWqSurRPRpJ/Ttt9VQdGx0clHwaZHMoOvZI2/XijljxQRIlh2C+ikG6CQdGkEwdy0yQiDNYZv/F/K6XTt0OeIbtebGPQH0UquTLk3Q6JEBgQtrzoXpsLtmuskpekbb/52grEUZBbTylp48h8k1dV8nKzE4f7TZtvZoPv6Abx9cykdbzw3uyxWTKU9ObvwOQABk4qeT8lRIeQTZWSNv14p5Y8TkTR8uH3CDM4tWTIULSQEgdyyyRicYunToGlS1KVUUFpvrZd9v6SzC8eWlvHPbL5Il50wgx591NqSfixFOXKhK0CequOG2rJS9ImGVuqkkvWU0raOPKeSt4mqrJHSJvLjondoy0jOyD7TpPUtfH+wEnzN+i+qgOjEwacxzeud8NMDmWHXkmbflz+jesXg0QUPX1+B9JNMHArypS0yRCG6sxjZ8BgyRJnq4wKafOY5B1stVG+29Zvh7z7oVwABkXlAsJWAd2dLVivrUqOMS0+ZqqS71hPqeRNlbyZDvafbtJ8mU6OoyC2DMiu8yR1bbyzz1nz6zA5gIFPLXliO87kUHbolbTpx3u15FEiykn6/AahI2rJkKFoISUO5HZJxOqBF9PV/pQuSVVGhbS57EhMtdpw2zqJYS/WxkbI6wCLe2BQlCvHMU7YytBbdbSvJS9Jm2wrKvmG9ZRa3lXJy/0ePt5j86VZOgjWGWm9+GmSujbeutJp88ugksHgukoO/Nr8MajNQJOd2aFX0qYfb72XHBgiosQp1y+ikG6CQZh0zCESB3KzJGL1v5tykAaUTt+VUSFpvjRLTLVacXPxYwyLrI2zIa8HRWMSfjJF37uMQ5ywlaH7N1iD+Vqq5OVDWj6jVCWXXOy99ZRq3lbJ6+rALpgemy+tZHvLMtWsB8+TVDkwsbGQf06LSgaD91TyxPp3NlfPUYJGgpw26PB8t5Y8RkSJ4dwvooR7opYMGcoWUuZx2TCJkHM9x/7tvFtLLs0zZFszVWy7PfhmyOsBi3tgUJYrzyM5H1R+fNjqrTqa15JjRFsfUkl4ZU/uYiVpsiNzd2+p5OXI7gM+NpdNfZ1Hjm0ufp6krpPPxpn8c9ruqzowOm+r5I3rLAO3xP2lid9gd+XtWvIQESXJh9+GdBMM3NLNd5KIME5nnjz9laabb+YZ0c5qV/Hg5uJvhrweUC4AA8KWF92dLRiwoUqOAW3zjMpnLntajZQLzN29p5LVCH9oHuccfQgsF5DtbJKqTV/+OS2TAxg4qOR05Je4vzTxG+yuvF9LHiGi+K+7hWmcWjJkKFtImcdlfmS+kUQsnvPo2a90SaoyKhybR2OpK3XLBdaLH2LYlsXu5yGvC6WWhB9LWUVpHsmErSy9a3ONa8kxqdrGS+Uzl88yZ4g3RsoV5u7eVMlahD80j091UmOSo+vFc0nqYut1+vLPaVHJYBAG3LsqefGTOHLjSM4VY6WJ32B35c3fuH7RPaJk0ueLkG6CQdmkI47QJomIZ145dyCCJUucrTIqHJvL5slHEW25Xvy9kNeFUkvCj4Ww5UV31REs2E4lx3i2fUTlMy8YKQVNPJlv8l2VvBxcA+qhefZs5XA2SU1Xef1zWr5xDQYeteQk0YojeSlfpBQ06YlHLbl/RMmlz9cId0QtGTKULaTI0G6SRKzKsGSda1wcaslaVDg0z56tHc4GrXjwNOR1gcU9MHBTyT8+bPVWyW1ryTGc7Z5QUckFiyXSIt+fHz4qeTm6mODQXLbORkBil3ySujqFTF/+OW33VR0YHR+VfPQr2cyM5IIg0hOH95IDnSOKkQBfgHQTDMKkYw+RhknE6gbPzjaLp+/KqHBoHj+JM2PJ4fXi74W8LpAIgUFZIkTYsulemws2bKWSl09p9yEpw8IeKTE7k8XL5sx39L5KTiL8oblsnVkxsUvhKu3EbCj/nJbJAQx8VPLRNQ6bCuJao45On1py74iST5+vEO6fWjJkKFtIaZhELD739KnPpZacRoVDc+uTkMPrxd8LeV1gcQ8MynJlwpZNb9XRtJYsbQ6NtGEhu86vFrOzuxZF5pt0UMmbCD/f+r659VTRP2TTTlKXdYnXoPLPabuv6sDo+KrkONjsyURca9TR6VRL3kaUedq8N6Ic8mEHSDfBoDBJmgdmiyRi8bjHz3yl6WZlVDg0tyKxHF8vvo9hKcsHoCVRfaBcAAaFufI8lAlbObo7W7BiI5UcP6XD82VU8rkl7CTZFzeVvInwIandNzdXieS4bBUkqbHBy5b+OS2TAxg4qWTxlDjYYgA4X1CVBn5j3RevWnLfiGKlz/UElUwtGTIULqTMA7NBEhFPqz5xPJxqyceocGh+CN0JYtD14m+FvD6wuAcGdYt7hK1zequOhrXkZb3xsAaifehWXL09BZ5v0kUlbyL8ZIh9c3OVSI7LVkmSulg9GNM/p0Ulg0EYcA4q+RAmTFe5OJfchstvXL/oGFHM9Lka0k0wKJx0xBO8k4h1/Jd479gES5Y4W2VUODS3PggJ1evF3wp5fSi1JPxYCFtedP8GazBjG5UsLZImWjprpbh21HZmviEflbwuu/7x+9A8HvKr/Gznk+8GOS0qGQycasnHkCCbp0N5hNQph18t+bMiSrg6tWTIULiQ0iaJWLPNEucdHLdacjYqyCFPlRx7mDiGvD6wuAcGhdqOsGXSW3W0qyXHUJY8nToqZN/Z5eI5ty2LzB36qOTNgP3j16G5bJ09djxTNss8JnYxmf6ag+XovqoDo9NIJVuTiRwednC6vZc88UkRhXQTDErrdvPIPB+b15KIZfB/wrRXmm6+FxWsUC1nrhc/xDCN2MXEMeR1gXIBGJQOkXksE7YydHe2YMgWKjl+tmkoU2OofKhnpngdvTEuzjfppJK3C6GH5rJ1ZsV4omwWrfFuHGTpLdu8CiYHMGikkuPQP1kajc39hrozjrXkj4oo4YrUkiFD6UKKDE7XJGIZ+h8x6znWkjNRQc3wNkjz9eLxfNlUOQ95XWBxDwxKc2UZzoStU3rX5prVkuW4zat5DKx6GulfwbBwVcnbhVBBDhgOkkw3ZYZYXCTiZzdUMhiUquS/vr/Df2djM3Es2T4ZfUV+2BPPWvInRRTSTTAonXQaJBFhdM58xqRXasn3okI8+yzayeH14u+FvC4ESxK2IENpIkTYsuiuOoIpG6jkJICeIifIlm6L/Dhqwdyjm0reLoS+kP3G2XJ0PVy0xptav8rDsvRe1YHhKZ0c5pF5PpqSw/kgIAfHHZuuteQPiihhQqeWDBmKF1LmoemZRKxeVvd9x1EpteR7USGefZJXxg9ivfh7Ia8LxWMSfirF2m4ezIStc3qr5Ea15PjRFiBn5AJlXE650VDzA/ip5GQhVHanE8aW5STZLl9YOkxfVvNyuq/qwOiEAVeikvOek+Zp2bEfLzburOD4G9cznxJRSDfBoHjSyblOHOg1s9fqY5+Rbc6WLHG2N6OCbJ6EsHjSevH3Ql4XSITAoLiiRNgy6F6bC7Z0V8nHcJZDTonZnWaMOIpu/My9VfJxIVT2RjPqQyDaZL14qh1OiLf1wmxeDJMDGJTWkuMQ1QdnHPubJVTZo62qXplLbsa5lvwxESVcl1oyZCheSPFOIuQUz+HeF+da8llUUIL3Bjm4ufibIa8HLO6BQXGuTNgy6K062tSS97Ezj5yynJNG1kVzy/YdzAPXUyUfVg5kZ+apt2fIjnWXPfx3H4Gft/CNazAoVcm5uUH1+ZgjKSfE0T7wtOD7XnLgMyIK6SYYlFZAc4NfCygWYWjOfMyMV5puvhkV4ulqV8sZ68XjLtk8Zw1gAdnZBcoFYFA+RAhbebo7W7Cmt0qO+W8Rcs56kmyvyH4172uFv0reL4TKvsxTbycg2VGxxrs9u6h5IUwOYFCqkhe/1kZnHL27Y7IvPSEruAfBvZb8IRElXJVaMmQoX0hxTSKW8f45E16pJd+NCrKtnb8K3fVgvIZsZlBDXg9Y3AOD8ooSYStPb9XRpJb8nUXO/EM25Zz10z2a42x/U+Zx66uSdwuhsmt1g/TpFkNtWsdLFMxe2/NLmpeBSgaDYpW8DNB0ClgO7YqvS4p0OGFxrBtfyajGv5b8GRGFdBMMKiadOESPzc/2Z1hS1xJPfAillnw3Kiy2S0L7JmStF4+XkM0casjrQLAkYQsyELa86P4N1mBO/1/vyhE/RtlcWHLgXfD5vQThW1PgFip5M4DX5su+MwcJyK6qNd41Xb70KZ2ASgaDYpW8DtDj+FzG/mGoLft3ydepCw1Fg1ryR0SUoJKpJUOGioWU+iTi6+tLzX9WOTby2lslDWrJelSQHecLmhNr63dDXgdY3AODilyZsJWlt+po9veSz4lhTjZX1ixuDa3rh+6Xl5Uw36S3St48oeyYWPZ9byeU1UECsnM1R5ExFtdztF33VR0YnTDgylTyOsb3Y192Thwi/TqiN2Mw5CsvZMeYeP/G9YvnRxTSTTCoSZLWUV6WRLyix9ZRXvRKPNoSLFnibG9HhZNIsZG42yNvh7z7oVwABuXlAsJWnu7OFgw6iEreDJXv+bq/N0H1ZiO1UcnrE8r2xDqfyFNPxAdPLh4bl5l9ubSfxzA5gEHF5LA6/B/fEoR+r3FeGbcbZ/map4ivzSXGXjxtUkv+gIgS7ohaMmSoWkhZA0JJEhFbJ465XuaUEmcejFJLvh8VNvZ7ReoJCdbx0No67pFNg+XSst0FFvfAoCpXXv2FsJXQuzY3Ui15uajGzSnwfJP+KllrvhvY4U1t+WfwF/mHtJx8R3YUmr2yeQGoZDCoUMkbPRf4/msf5JWBtpk7jgw+LFu8lxx4ekQh3QSDMOmUD5F5fOok7reEk+N43gcinbFX5VRKp+/3o8I+tH9vQ3sqwZUYlqOyeRPqxiT8QOq03TyidQhb0213Te+C3YZRyYesecPdCyDzTTZQybG9bM2cDe3v1FTpBJNH2l/4lE7ovaoDw1OhkjMOP6GOs9N5YPRR2aiW/PiIEu6VWjJkqFtIOY8pqfetjiI7hDMH2vHAokybWrIaFU4/hl9p7hjNLZsm0l62usDiHhjUaTvC1jm9VfJYteRlUfLI7esfzVSynCAbL/TBPQ2LxFTVpZzXCRc+pRO6r+rA6NSo5MPbsjtOBu3JCcMPyla15KdHFNJNMKicdCqSiNVPZMeLsyvs+eCijEdUODHiZDX519raI+TdDIkQGBC2vOhemwt2G0cl6/ldBwO1U8mvM+TfQjTJlvDQialq13jljAuf0glMDmBQpZJ1hw+cBnN10XX80N+slvzwiBJUMrVkyFC9kKLFFHXWWtxkd7Qs26SWvEWJCr+0jyEYTf65tnYJeffC4h4YVGs7wtYJvVXHYLXkiTS/88vIypnvoo1Knk+Rf0bSCWV+6MRU0REqTBJO8bNg91UdGJ0wPitUsp5M5UZsWn/+fsD6aJvfuH7x5IhCugkG9UlSaRKxJJa7w1pAUnhgUSZYssTZnKJC8jG8ArVsrK19Qt6tUC4AA8KWF92dLdhtKJV8HCtfXT7V+R4aqeRwjvxrZftjvctDJ6aqX+Odz7nwKZ3A5AAGlbXkiUTRWS6/P2H5IeehaVhLfnRECXdJLRkyXFlIKUwiZPjvprSd32SglrxDiwq/dh9DDNSyubb2Cnk3wuIeGFzJlQlbGr1Vx+VaclO+vl6/y/rdRyJPzKO1RCVf4lsN8PLQ7usCvx1zWlQyGNSr5Ilf0eMLXf7XFCKkvewZneL3ki/x3IhCugkGYdKpHyJlSUT4iyuPiSFv03T61qPCFNnDp+BvZD3k3cX/v727WXZcxxLFXJH7Ge4j1CzDE8/2zNHRI0fnpF/gPsEZd3bkwNUTR5yR84Zd5e7rhzUpASQlLhKgBIp7c39fnT6doiD+4AAgFhalfKxN8oU8NBEybAUOf4K1/w/y4aLk4+0bJX9/7QDfsDuJkil47OZwetW55Id83hGlnxLIJbPCQkor+9bka6ftLx7y7miTFJgrt3J0TX7MXPLx9o2S//Lipx7apZIOX9XhoxMlh/bNJX/eEcV0kwLTzVZ2rsn9hrfIoY+OapMUmCu3cnhn644vSp7bOUr+tNwcKBAlh/bNJX9efZQsl8wKCymtqMlW1CQF5sqtHL3eIJccEyXH9HwK+p4jSp6p/o3rL8Z0kwI3nVb6mtTZWlCTFBi2Wjm8Jrvji5LnRMkxT5FQIJcckkuO+V4yBRZSWlGTrahJCsyVWzk6SpZLjomSY9bHKBAlh3b+XvKnZbpJgbxdK27frahJCjSRVg5fb+iO/+1f058ZiJJjej4FouSQXHJMLpkCCymtqMlW1CQF5sqtHF2TcskxUXLMUyQUiJJDcskx000KTDdbUZOtqEkKTIRaObyzdccXJc+JkmNuDhS4OYTkkmN9lCyXzAoLKa2oyVbUJAXmyq0cXZNyyTFRckzPp6DvOaLkGb9xHTPdpMBNp5W+JnW2FtQkBZ67bOXwmuyOL0qeEyXHTFgokEsOySXHfC+ZAgsprajJVtQkBebKrRxdk3LJMVFyzPoYBaLkkO8lx0w3KZC3a8XEvRU1SYEm0srhNdkd329cz4mSY3o+BaLkkFxyTC6ZAgsprajJVtQkBTJKrRxdk3LJMVFyTJRMgSg5JJccM92kwE2nFTXZSl+Thi1W6GytHF6T3fFFyXOi5Jj1MQpEySG55FgfJcsls8JCSitqshU1SYEouZWja1IuOSZKjun5FPQ9R5Q84zeuY6abFLjptNLXpM7WgjZJgXRBK4fn5rrji5LnRMkxNwcK3BxCcskx30umwEJKK2qyFTVJgblyK0fXpFxyTJQc88Q1BaLkkO8lx0w3KZABbcXEvRU1SYG5ciuHd7bu+H7jek6UHHNzoECUHJJLjsklU2AhpRU12YqapMBcuZWja1IuOSZKjun5FIiSQ3LJMdNNCtx0WlGTrfQ1adhihc7WyuFZ+e74ouQ5UXJMz6dAlBySS471UbJcMisspLSiJltRkxR44rqVo6MOueSYKDmm51PQ9xxR8ozfuI6ZblJgabYVGdBWtEkKNJFWDq/J7vii5DlRckzPp0AuOSSXHPO9ZAospLSiJltRkxSYK7dydG5OLjkmSo7p+RSIkkO+lxwz3aSgv+loIi24fbeiTVJgItTK4cNWd3y/cT0nSo554poCN4eQXHJMLpkCCymtqMlW1CQFlqRaObom5ZJjouSYnk+BKDkklxwz3aTATacVNdmKmqRARqmVw2uyO74oeU6UHHNzoECUHJJLjvVRslwyKyyktKImW1GTFJgrt3J0Tcolx0TJMetjFPQ9R5Q84zeuY6abFJhuttLXpM7WgjZJgSbSyuE12R1flDwnSo7p+RTIJYfkkmO+l0yBhZRW1GQrapICGaVWjo465JJjouSYKJkCUXLI95JjppsU9DcdTaQFt+9WtEkKdLZWDl9v6I7vN67nRMkxPZ8CUXJILjkml0yBhZRW1GQrapICc+VWjq5JueSYKDnmKRIKRMkhueSY6SYFpputqMlW1CQFJkKtHN7ZuuOLkudEyTE3BwrcHEJyybE+SpZLZoWFlFbUZCtqkgJz5VaOzs3JJcdEyTE9n4K+54iSZ/zGdcx0kwI3nVb6mtTZWlCTFHjuspXDbwDd8UXJc6LkmJ5PgVxySC455nvJFFhIaUVNtqImKbC418rRNSmXHBMlx/R8CkTJId9LjpluUiBv14rbdytqkgJNpJXDc3Pd8f3G9ZwoOabnUyBKDsklx+SSKbCQ0oqabEVNUuC5y1aOjjrkkmOi5JieT4EoOSSXHDPdpMDSbCtqshU1SYEm0srhNdkdX5Q8J0qO6fkUiJJDcsmxPkqWS2aFhZRW1GQrapICc+VWjq5JueSYKDmm51PQ9xxR8ozfuI6ZblLgptNKX5M6WwtqkgLpglYOf4K1O74oeU6UHDNhocDNISSXHPO9ZAospLSiJltRkxSYK7dydE3KJcdEybHDV3X46ETJId9LjpluUiBv14qJeytqkgJz5VYO72zd8f3G9ZwoOebmQIEoOSSXHJNLpsBCSitqshU1SYG5citHrzfIJcdEyTE9nwJRckguOWa6SYGbTitqspW+Jg1brNDZWjm8Jrvji5LnRMkxT5FQIEoOySXH+ihZLpkVFlJaUZOtqEkKzJVbOTpKlkuOiZJj1sco6HuOKHnGb1zHTDcpcNNppa9Jna0FbZICTaSVw9cbuuOLkudEyTE9nwK55JBccsz3kimwkNKKmmxFTVJgrtzK0TUplxwTJcc8RUKBKDnke8kx000K+kmSJtKCiXsrapICE6FWDu9s3fH9xvWcKDnm5kCBm0NILjkml0yBhZRW1GQrapICc+VWjq5JueSYKDmm51MgSg7JJcdMNylw02lFTbbS16RhixWeu2zl8Jrsji9KnhMlx9xmKRAlh+SSY32ULJfMCgsprajJVtQkBebKrRxdk3LJMVFyzPoYBX3PESXP+I3rmOkmBaabrciAtqJNUqCJtHJ4TXbHFyXPiZJjej4FcskhueSY7yVTYCGlFTXZipqkQEaplaNrUi45JkqOiZIpECWHfC85ZrpJQX/T0URacPtuRZukQGdr5fCa7I7vN67nRMkx62MUiJJDcskxuWQKLKS0oiZbUZMUiJJbObomL7nkP//441/9k/+56AfBb5cX07e++D+dPgRyc2BF33P+6dJYUrvxv74a+mjw27/kruSf6z/XEUWUzIpLEzGcPPG/bKjJfpt/HvvnwkSIgrvO5n/b/9f/0+kq8tDOdomSYYN/Tm0HAqmVQLXUdCCQGgl8LKl9QiA1Epo4MuoQJbOVKJkVqZVAtdR0IJAaCXwoJkKsSK2EJkTJfCZuDqxIrQSqpaYDgdRI4GNJ7RMCqZHQhCiZz0SUzIrUSqBaajoQSI0EPhQTIVakVkITh3a2/gT+8//4N/+7/d/f+nr5/pe//Lfuf/41/svv9lHQ/2jFv0yajH9d/nX5m6B+3G7zLz8WS9GliSw2IP+q/1d/+1aTLf51qcnUPiFwmSsvNB//2vKvD/Eb1//xb9y5RMn+JqiZPgQSJbOi7zn+JqiZy98E5e9LnulDIL9xzQpLs62oyVbUJAXmyq0cXpPd8UXJcz/7ehElz7g5UHDNJXPH35cck0umQBNpRU22oiYpMFdu5eialEuOySXHrI9RIEoOXZ64lkuekUumwHSzlb4mxXYtqEkKzJVbOXxK2R3/23+l0JCBXHLMhIUCUXJILjn23lWLKJkV8natqMlW1CQF5sqtHF2TcskxueSYnk9B33NEyTO+lxwz3aRA3q4Vt+9W1CQFmkgrh9dkd3y55Dm55JieT4FcckguOeaJawospLSiJltRkxR44rqVo2tSLjkmlxzT8ykQJYd8LzlmukmBpdlW+prU2VrQJinQRFo5vCa748slz8klx/R8CkTJIbnkmO8lU2AhpRU12YqapMBcuZWja1IuOSaXHBMCUaCJhHwvOWa6SYHpZitqspW+Jg1brDARaqWvyUOHre74cslzcskxt1kK3BxCcskxuWQKLKS0oiZbUZMUmCu3cnRNyiXH5JJjej4Ffc8RJc/4XnLMdJMCebtW3L5bUZMUHJ4BPY3DEy/d8eWS5+SSY3o+BXLJIbnkWB8lyyWzwkJKK2qyFTVJgYWUVo6uSbnkmFxyTM+nQJQckkuOmW5S4KbTSl+TOlsLapICw1Yrh9dkd3y55Dm55JieT4EoOSSXHPO9ZAospLSiJltRkxR47rKVo2tSLjkmlxzT8ykQJYf8xnXMdJMCS7OtqMlW1CQFmkgrh9dkd3y55Dm55JieT4EoOSSXHJNLpsBCSitqshU1SYG5citH16RcckwuOSYEoqDvOZrIjO8lx0w3KegnSZpICyburahJCsyVWzn8Cdbu+HLJc3LJMTcHCtwcQnLJsT5KlktmhYWUVtRkK2qSAnPlVo6uSbnkmFxyTM+nQJQckkuOmW5S4KbTSl+TOlsLapKCwzOgp3H4lLI7vlzynFxyTM+nQJQckkuO+V4yBRZSWlGTrahJCizutXJ0Tcolx+SSY3o+BaLkkN+4jpluUuCm04qabEVNUqCJtHJ4TXbHl0uek0uO6fkUiJJDcskxuWQKLKS0oiZbUZMUeO6ylaNrUi45Jpcc0/Mp6HuOKHnG95JjppsU9EuzmkgLFrlb0SYp0NlaObwmu+PLJc/JJcf0fArkkkNyybE+SpZLZoWFlFbUZCtqkgJz5VaOrkm55JhcckwIRIEmEpJLjpluUmC62UpfkzpbC9okBSZCrRz+BGt3fLnkObnkmJsDBW4OIbnkmO8lU2AhpRU12YqapMBcuZWja1IuOSaXHNPzKRAlh/zGdcx0kwI3nVbUZCtqkoLDM6CncfiUsju+XPKcXHJMz6dAlBySS47JJVNgIaUVNdmKmqTAQkorR9ekXHJMLjmm51PQ9xxR8ozvJcdMNynobzqaSAtu361okxTobK0cXpPd8eWS5+SSY3o+BXLJIbnkWB8lyyWzwkJKK2qyFTVJgecuWzm6JuWSY3LJMT2fAlFySC45ZrpJgaXZVmRAW9EmKdBEWjm8JrvjyyXPySXH9HwKRMkhueSY7yVTYCGlFTXZipqkwFy5laNrUi45JpccEwJRoImE/MZ1zHSTAtPNVtRkK31NGrZYYSLUSl+Thw5b3fHlkufkkmNusxS4OYTkkmNyyRRYSGlFTbaiJikwV27l6JqUS47JJcf0fAr6niNKnvG95JjpJgXydq24fbeiJik4PAN6GocnXrrjyyXPySXH9HwK5JJDcsmxPkqWS2aFhZRW1GQrapICCymtHF2TcskxueSYnk+BKDkklxwz3aTATaeVviZ1tha0SQo0kVYOr8nu+HLJc3LJMT2fAlFySC455nvJFFhIaUVNtqImKfDcZStH16RcckwuOabnUyBKDvmN65jpJgWWZltRk630NWnYYoXO1srhNdkdXy55Ti45pudTIEoOySXH5JIpsJDSippsRU1SYK7cytE1KZcck0uOCYEo6HuOJjLje8kx000K+kmSJtKCiXsrapICc+VWDn+CtTu+XPKcXHLMzYECN4eQXHKsj5LlkllhIaUVNdmKmqTAXLmVo2tSLjkmlxzT8ykQJYfkkmOmmxS46bTS16TO1oKapODwDOhpHD6l7I4vlzwnlxzT8ykQJYfkkmO+l0yBhZRW1GQrapICi3utHF2TcskxueSYnk+BKDnkN65jppsUuOm0oiZbUZMUaCKtHF6T3fHlkufkkmN6PgWi5JBcckwumQILKa2oyVbUJAWeu2zl6JqUS45V55Lf0v9/jR9HT7P1fAr6niNKnqn+XvIXG1FMNynol2Y1kRZqF7lfPCq8dshrQrqAAk2klcNrsju+XPJcdS75/aW37+9HZ6P0fArkkkPVueQvNqL0UbJcMisspLRSW5MvHhVeO+Q1oU1SYK7cytE1+TFzyb/+4+/9eX37+9/+lra8WnUu+f2l//l+HP3VRiEQBa9pIn+894/qfvv29nZwlFerOpf8xUYU000KHpsk/Xi7jhDvb8+lKt/+fHikedvYsHePTfuarDmnF48Krx3ymqitSb6sxyZChq25w59g7StyUy75Gr9mdQH2JeaM/CMVmPp1Wzoqsr/6XPK2/37XlvvtW3q51ffuoxuaZHezu2j3RJP1MQo23xxyK03S1jXpRpLtPUg3UZ9L/lojSn/+csmseGAh5cfbpZlmD8czT400XWd53/KJ7ljzfnV7IQWlo9Xnkl86Krx2yGvC4h4FD8yVDVuho6OOzbnku4D3Z9q87jaynvidCkz8R3prdEQ+eUMuedPN4ckB/nI7Sn+u0H5OK0qmYHOUfGmio7R12Y/bW0Bn06B+kOrfuP5iI4rpJgXbbzrzOdpDDfbJkebyifoDX056doAt083isWpr8sWjwmuHvCZMhCjYngE1bMUey8o31J/lllxyX36iLoJNhef+ngoMfv1O70wdkE7ekkveslbz5ADfr/Fu6HmX4p1H715zhz/7wEe3dUi7H0/T5kXh+LvlLnCMLbnkrzSi9Ocvl8yKrQsp81li54GVmCdHmnQWtTPUhVBzy3QzfWTZllzyC0eF1w55TVjco2DrQopha8nRS1Jbc8n/6MtPVOWSFx+4/vbvqUT2K22/9yu9/zKbcskbvsTz5AB/bZLVDebZNd45S6gU9A1uQ5Sc2+ggbV/ST08CH75Rbvhecm3Ji88+ophuUtDfdDY0kdmIktRPFK+eHGmG00ivS3JHfny6WR4zam/fLx4VXjvkNbGxTfL1bJwrG7YWHR519KdZn0ueRbFVueTlKPkul7wUJL8+TN6WS65vyk8O8GnRtnZ4bp/5Oby98tFtzCXnHjFI2xfMimcffcqyLZf8dUaU/qYul8yKbQspuYnObZtvLo40dfe/4TQqg798uPu91083K86rtiZfPCq8dshrYlub5Ava9tylYWvZ0U+wbswlz75gXJVLXvxa8l0u+SZI/t1Jf+y9OEzemEuubspPDvB5oaeyyTy7xjvniWsKtkXJ8xXU9EZsulD63kl/7H3wZrkxl/xlRhTTTQo2Lc3eDCh3Q0R1trJzM7Q8MNKksrU9ZZhVpteD+ulmxdXVZkBfPCq8dshrQrqAAsNWlcph69DO1p9ndS55Hu5W5ZJT2cBtLnnc/c8UFF9Suhcv/m7y1lxy7Qj/5AA/rPTUtZln13jn3Bwo2BQl39wcrtI7oXHB9T216e/jfWDbmuurbc0lf5URpT9/uWRWbFpIGceDtzT/GidsG1ZjxoHpsZEmF668WQ6Hm80Zq6ebNV1yYy75VaPCULMvGfKasLhHwaa5smFrxdFRx8N/X3L/uU5NLjk/cJ1eLhq+8zz95eshnxz8HPaONueSK0f4Jwf4SSdIW1bl4o/evea2JQr5gh5tInlcTS8jY/OfjMpj5Fw3xzrIpt+4vvoSI4rpJgVbJklD75l+INy46tmRZvh8TY/v5DOsPsHBMB1Nr1fV1uSLR4XXDnlNSBdQsGUiZNha09fkoZ2tP9FNf19y0n+uU5NLToFuKcwdnre+LTiEyS995np7LrluhH9ygB8b/KYl4XZzWjcHCnaMkofOdtPVhk7xoRvm9lzy1xhR+vOXS2bFhoWUYZp3OxbEA8eKJ0ea4TQqj5cPt30EG06p6kibc8mvGRWG2n7JkNeExT0KNsyVDVurjo46XpFLriyais2i6Rwmz/7WqD09kEuu+i/+5AA/NONORbPJxUXJvEzf4PaJkof1x7uVzqFXVK6AHmLz95J7X2BEMd2koL/pVDaRS+Ps3DfljfO5Z0eaVKq2m2xKrNzadmG1t+8XjwqvHfKa2NAm+Zo2ZEAvzblzX9ywdfFo4qWZ/lT3zSVXPnCdU8nzlHMOk+v+buY2Hskl14zwTw7wkzXemhb27Brv3OHPPvDR7ZdLzp1n1s2GbpFef0SP5JK/wojSR8lyyayoX0jJzXPekHM3qWu4T440+eOVd8raSWxgOJ+6jz6QS37FqPDaIa8Ji3sU1GeUDFvrjs7NvSCXnH6Tq/TA9bVU9GD1cvy8n4dyyRXj9pMD/HSNt6LrPLvGO3d0e+XD2y1KzgWC9rd4e/g4Hsolf4ERxXSTgvqbzqVtdub9bHkiGnhypNk6fcz7fODGmj5Z2x9rM6AvHhVeO+Q1YSJEgWFrUfrklmHr0M7Wn+u+ueS6kjkUjsLuA5LJj+WSy/8pnxzghzWYq1JQkIu3m9O6OVCwW5S80neGfpFef0CP5ZLPP6L05y+XzIrqhZS1aC33k5qW+9xIM8w2a3p7Jx/tgftqHjNre/9DueT9R4VcA1d7D3lNWNyjoPq5S8NWwdFPsO6fS14LfydSqfi57PTeC5PJD+aSi/8tnxzgh5acFBr0Wvd7zNHtlQ9vryg5vx825vxm5TLoAR74jeuLs48oppsUVC/NXppmJ728ld6r2NGTI83G6ePQA7ePXZs/WluTLx4VXjvkNdHXpGGLFYatBbsNW7vpT3bXXHLd15LXY+n81yanly/wYC65OHI+OcDfrfGWbl/PrvHOHd5e+ej2ipLXu05684/08uN5MJd8+hGlP3+5ZFZszYDGjbM0voyeG2nypytvk0MHrBkb7mw81MO55L1HhXwd2b5DXhMW9yionSsbtkqOjjr2zyXXfS05x9ILf91Tevd1j1w/mksu/dd8coC/X+MtNNJn13jnHg2B+DL6BrdHlJzeXuhf9TeTgzz4veTOuUcU000K+klSTRP549I0F3tZerfcdFPBx0aarYmSvv33HpgFbj1U/XTzxaPCa4e8JqQLKKidKxu2Sg5/grU/211zyXUFU6mlWDp9M/l1fxnU5lzyONCv/ud8coDPKziT28ra7evZNd45NwcKdsol57cXhtbc1B9Y2nyNzbnkLzKi9LdbuWRW1C6kXFrmcndJTbx4+3pqpBmmgJUD0dDb0+st0kc3jHm1NfniUWGohPT/C9WRi6WXh6itSb6s2rnypS0vF02t/SsPW0dHHbvnkrc9cL2QSn79I9ebc8nDH9b/ez45wA+LtrnNd1Ya21A8vX6eKJmCnaLk0s3i+nbDpt7Y5lzyFxlRTDcpqLzp5La51MkKA8zgqZEmd8fKm2Q+56qR4U6+nspD9fqarOlsLx4VXjvkNWEiREFlBtSwVfTolLKZ/nz3zCWnLPBzD1xvSF03sjmXPP5p9T705AA/LtpW3b7G4q0c/uwDH91OUXJ6d7Hx1d5MjrI5l/xFRpT+/OWSWVG5kJJHgMXWm94vtd1U7KGRZuiy6XXBMNt8oD89MlPdmkt+0ajw2iGvCYt7FFQupBi2io5ekto9l1xXLn15eTlXXBdst7M9lzwd4Zf/iz45wOcm1rXOobWt9K9J8UYsoVKwT5RcbMq5wAOrmy+x+TeuJ38884hiuklB5U2n2BNSgcKunhlphi5UOQrlU37klpo/u6Ur1t6+J3UwXNKOo8Lkv1z+445DXhN9TRq2WGHYiuTP7jFs7aY/4R1zyTlJ/Leff/v9++9/+9uvOFucSi3H0q9+5PqBXPL455X/pNPiD5gu2las8j67xjt3eHvlo9snSl5/t5cKfNRfuX4gl/wlRpT+/OWSWVG5kHJpmGtNszyG9J4YaYbZZk0/7+S++8gddeis6XWV7bnkl4wKrx3ymrC4R0Hlc5eXpmzYWnP0E6x755Jzknjib/NAufS15NdHyY/kkqcj/FKbf3KAv1kwGhr34u5uijdxdHvlw+sbXPsoOXWclbZ3LdCwrbe1/XvJ0xfnHVFMNymoy9vlprncx+qmm0+MNLkvVt4hh+5WmcK5kT667bO1i9wvHhVeO+Q1IV1AQV0TMWyVHd7Z+jPeMZecnpS+NYuTy1Fy7fFaeSiXPB3hF5Zlnhzgbxdtx1XehSb07BrvnJsDBfvkkss3gbqbyWEeyiV/gRGlj5LlkllRt5CSm+ZKH0sl1hvv4yNN3l7bF1PphzpTPta2m/EjueQXjAqvHfKasLhHQd1c2bBVdnTUsXcuORW7dxcO5+ey08tIKvGqKPmxXHJ5hF8Z4H+8XZvQ+9ty87tbtB1XeeM29Owa79yjIRBfxj5RcnpzpSWvf/5wj+WSzz+imG5SUDdJquj/qcR64y0XWjjS0Hcq8yS55z4y/9t6rKSvyZrO1nBUeHvre3j33ttyHNBuyHuZ2prky6qbCBm2yg5/grU/5f1yyTn8nflHKnBV8dtcL/4bkx/MJQ+NtROO8IsD/I/x1tBJbX3Wru8XbXOBhRH72TXeuaNXdfjwdomSc0teGV0rFmWP9GAu+fQjSn+WcsmsqFtISc197e5UUeTxkWacAf54uxzo/c/VXpK75/tf3t4vf/5zJY68lz+8sR8+lkt+YlQYP9h5T9eXXo6l89Wklw8PeS9kcY+CurlyasyGrRVHRx0755KDryUnN+Fu2ra2sxQl/3t6ubdHc8lDU+xEjee+eHI7o+1dPjyb084WbcfPRa1oVvxpomQKdomS/1h78yo39m3LlC/zyG9cX5x8RDHdpKDupnNpl+stM7Xt1X09PNIMHWfa83JgOJd3clO8tl8NH06va9XevhuNCjcxcu/64fRiLJ33nl4+OOS9lIkQBXUZ0EtLNmytenRK2Ux/zvvlklOpyDSbnDatRckv/vmuh3PJhRF+Vvxidjfp9H1iNqfNO5/fYMJONC/+rMOffeCj2yVKXn0zSUXaNfamHs4ln3xE6Q8nl8yKuoWUS7tcb5k1o8ijI03U43pLd8v09kzNEDF8uKrwxKO55IdGhflCXac/4/TH+c7Ty8eGvNeyuEdBs8W9Lz9sHb0ktW8uOT1w/fvn5XvIv37lUPdi8nx12vKBouSHc8mTBZOoNYQDfD/iznXNYtb0g0Xb8VY0b0dB8SdZQqWgb3Ci5JlHv5fcOfWIYrpJQX/T+ehR8qSP3gvnhGMnu1dxe83nuPlOXHv7bjEqLNRIVxvpT2PpFkPei5kIUVDXRC4t2bC16vDO1p/1brnky2PSN982zr9m3RuC84qfuP48ueT1hdBogF9qee/zph8t2o4fn80k4jXeZ7g5ULBLLjk18tWmdy3SsLE39Xgu+dwjSh8lyyWzomohJbfMtS5WM5V8bKRZmW2GnWWph/aWH3dMhoNt/nJJ7ZJUg1FhsUa+z6sv7zq97OVddqqGvFezuEdB1XOXhq0KRz/Bum8uuSvw+z70neST81s1UXJNmYaeyCXftL37lhMUz33g6r2T/vgt/UTtpHTe800DHpvufUsKiz/FE9cUHBYl15Q5zhO55FOPKKabFFQtzeaWudbF8pR0rUzNKDIvM/aYyGxnk/4cKcw388G2d8K+Jms6W4NRIW26mo5B36qi5GkVVQx5L1dbk3xZhq1b+WCPDVvFmtxTf9p75ZK7UDP42eoxnZx/wesDRsnP5JLXFkLnxSct7z13g+uPzXUbrv9vLJ13fNvQcrFZU4qLP+Pw9spHJ0oOPZNLPvOI0h9KLpkVzXLJNWVyR0kvQ7Myk+4Zuu8uY/+KpWKxYREsvd7gmVzytlFhcoV56/d04vmtsXTekl5eTeq0OOS9nsU9CqrmyjVDUk2Z1CfOOWwdHXXsmkv+W/x3O41hcgp5P2CU/FQu+WaimrYk8+JpQ+dmqeimQaZt437vmu9Y+PaNheJPeDQE4ssQJYce/o3rq9OOKKabFDRLytSUqRlF7stMOmfXNb5fZrN5XerqdoI7fev97XI2OYS8Wjv6cLCaweRO7XRzoZvXjwrj1dwc7mZaPpbO+00vk0mtpi1JXPy1pAsoqJoI5UZu2FrR1+Shna0/771yyb8WYughTE7J5A8YJT+XS57eDm7/686KD63svhVMm2TaNO72fpI6Fr5p10vFH+fmQIEoOfRcLvm8I0p/ILlkVnz4XPKkZ10nj1eTGeTN7iaz0/dJR/o+2c3KGeZSq2e44Llc8vRCC6NC2jCbE+eSvbF03m16mY2Fb691ofhLWdyjoGquXDMk1ZRJfWL1ePdlxt78wYeto6OOnf++5AVDmHyNeT9glPxkLnnapG7+894XH4rNG8Gk8aUtY/H7u9ek8LShLhZ/mCiZgr7BiZJnnvpecu+kI4rpJgX9TafYRHLLXOtiNWVqRpG7MkOXG7/hkIydaNph4q2dSQyZtswNB6sZS+7V3r4Xu3nlqDAUm53kWFeTnefi6eVgUrFpy8VS8VeqapN8ZVUZ0NzEDVsrHk28NNOf+H5/X/KSy49fjx9Pr9ZC7k+WS56uyEwH0/viQ6n0empslWnD2B5nd6/JY5aT29dy8Ucd/uwDH90uueTVN5PUXz5o83w2l3zWEaWPkuWSWVG3kHJpl+stM7fetW74wEgzdKv50BP0uOEsghnj+NbiZaT3H+uBz+aSa0eF9Do6yegS78ewQd2QdwSLexTULUldWvJ6d85d5ssOW0fn5o7JJY/J5OvL9GJtZ/mnsdPLvT2dS562tMl/4Pvi6WW8wpLem+w8r8jM29rYUCedabn4o45ur3x4h0XJqUi7xt7U07nkk44oppsUNJtu1owi20eaIU0SnePQZ8fz6lv8RdBFh30tHT+f3ur5LarNgD45KuSTDP+jDVcw7vzJIe8IJkIUGLZGzw9bh3a2/sxfn0vOH/+wUfLzueR4hL8rnu85cRMYdpBej+WDPhXdvlaKP8jNgQJRcuj5XPI5R5T+lOSSWVG3kHJpl+stc5/pZv5EbZdLr+PBYOh08XUM09GakWSudknqyVEhX3O4Uhdc4d0YNjVU3/KQdwiLexTUPXd5aclL3f3qyw9bRz/BelAu+e4B6r9fX4S/iJ18vlxyOMLfFf8jvVzIMaV3x53fL9pOjes5Q1tcK/6Yo9srH94uUXJuyQsd5SIVadfYm3ryN66vTjiimG5SULc0mzrCWsGaqeT2kSa9WvjEbP64Pjsdu3h6fSu/++A9uHaR+8lRIb1cOFKugHHnd2PYjaE+xt2tFX8V6QIKDFuD/O6DPebwztaf+wG55BwlXz//79cXa1Fy+iZz/iuW99YilzxpOsM88K746qeDt+8XbW8MDXu4fa0Wf4ibAwW7RMm5Ja+sRVYUOVKLXPIZR5T+jOSSWVG3kJKa9trdqaLI9pGm1CVyl8vvz7rgraHPpdc3hjfXJsMrGuSSJyexNCqsxdid+c5XqyS/uTjkHcLiHgXNouSKIkOnOuWwdXTUcVQu+TbKvmRuO5cXsVTi4eNt1CSXPL47/Ee+K55eLbWAWeCwfv+ZrfIWblcPeDQE4svoG1zzKPluHTRSs+J6oAbfS+6dbkQx3aSgnySVm0hF/08l1htvudDtkQpPb8y65N3Lmbz3aH/prYe7X+1087lRYe0KeuntcefPDXmHqGuTfGF1c2XDVtnhT7D2J39ALvk2N1x+nPrFP3HdKJc8H+HviqdXS61n1oMKC0DDmk26fZXWi7Y7elWHD2+XXHKpp3RS1/qorbNNLvl8I0p8eWvSAAA0aklEQVQfJcsls6JuIWV9/OjlxrveC1Oh6pHm+mLluLc9NJ/m4v7zWf6RXk/kzz48xjXJJRdHhdJ/ifT2uPPnhrxDWNyjoG6ubNgqOzrqOCyXnKLkf7++ur5Y2duro+RGueTpCH9p5LfF8xrs0npObnnpZTmVM67yXhpVqfh2omQK9omSyzeT25vAh9Mol3y6EcV0k4LKm86lYa41zVLnuNo60lxfrBz2dofl3acC8x0OfbFmGAn1NVnT2Z4bFUojcXp/3PntGDaX3w+HvGOYCFFQmQG9NOW18cOw9eiUspn+7A/MJaevIl9frHwx+cU/3tUsl3w/wt8WL64SpffTq/EDi207F7h2hmLxzQ5/9oGPbt8oebGrlIf9Y7XKJZ9tROnPXy6ZFZULKZeGuXZ7Ks/0ehtHmmKPu9th6q8rN9FrgaBE7uqPd75GueTCqFC6xFQh485vx7BALhANecewuEfBtsW95ZKGraOXpI7OJae4uPgj19f3X/a15Ha55OkI//2+eHGVKL2fXs0WbQPDwk3frMrFt7KESsE+UXKxq9TdS47T5Deur041ophuUlB500k9Ybnk9f1S29040hSLDxPSa4niWS6WGDpiev2A2tt3uZsPJ9Pv76546RJTBY47vx3DIrlEMOQdo69JwxYrDFsXw0iRXj/g8KijP/0jcsm3ny+lim9/EvsF2uWSJ8uu337cFS8u6KT306vxAys9Jh+hb1cVxTc6vL3y0e0TJRfvFeWOeKx2ueRzjSj93uWSWVG5kFJaJ7uL5RaVim3scXcl0qcfmG5eN69NbIua5ZJXR4XSJT4QJecjdO6HvGNY3KOg8rlLw1bR0U+wHv0b1/nzdy/v5Sj6VV9LbplLHhdTupZyVzy9WmrZ+ZPpZV2PyYfoGlZtB6t3dHvlw+sb3A5Rculmkt7+sI2z2feSO2caUUw3KajN211a5nLbzCNIqRNuG2nKPSKXuEnKrHTvVOJ+JMun9cwIV7vI/dyoUKrA9Mlx5+U6Gc6ocz/kHUK6gILaJnJpy4atFYd3tv4CDsgl34e9tw9gz1zffd3Xklvmkm8WQu+Kp1dLTTV/ML0cNyy37U4+xni01eKbuDlQsFMuubD4mT/drqk31jCXfKoRpY+S5ZJZUbuQkhrn0v3p+u56x+ptHGnuXs7dDmyFYa6TCtztcAgTa1baljTMJa+MCqVLTMXHnefPp5eh5SHvEBb3KKidK6fmbNhadHTUcVQuOUXFQ9ib/8bkOFmcH7h+2deSm+aSbxZCk/RGoYPMmmZ5BaiXz2mwXnyLR0MgvoydouQ8Ci/0lY8wc1rVMpd8phHFdJOC2klSbtzxPLGupfdSwcqRptDj7vtcPo3loSAVuDvPfNinel5fkzWd7blRoXSJ6e1x5/dVGsp7HaU3DiFdQEHtRMiwVXL4E6z9FeyTS/61EnznsHfMHc82TL38geu2ueSbhdCrtL3w6fTu+HbVGu+42+ypJnrDzYGCvaLk9ZtJevPjts2mueQTjSj9nuWSWVG9kHJpmkuDwPr4MbVtpCn21/R+6jLFDhePg0OMmF4/pmkueXFUyJ8O/urUXr7AcefFKrxYGvIOYXGPguq58qUxG7aWHR117JdL/sdaUJt+03ry8fvk8tQ8pt5d21zyfCE0bZ7fMKbmTSxvWWyryd3tq1S8niiZgr2i5NW2nxv8M8/17Kvhb1xfnGVEMd2koPqms9Z1ckOv2NG2kWa9x43v5w+kl4v9O719d55p65MDXG1NPjkqpJcLl5g/NO587b/bxDB6JWnzIfqaNGyxojoDatgqeHRK2Ux/CXvkkvuo9x/pzzM5NzyJifOmKBLOEfTrUsmtc8mzhdC0daFtJbmhjjuvXOMdT+uqWLza4c8+8NHtFSUPI26wVrrhXnKUxrnk04wo/X7lkllRvZCSm3fU+HP7rZmvpaKVI03astRh07vD2/kkF7pQ/PbalW3QOJe8NCrks13Nak12/uSQdwSLexRUL+4ZtgqOzs3tlUv+x+XdheRvzg3fvL8cCg/F0+tXaJ1LHtvpVdo4fDy6n4yfSBvGTcW71+3tq1y81tHtlQ+vb3C7RMl5jhS0v9za2zX05tp+L7l3jhHFdJOC+rzdcuMfmn56vWrbSJM3xffF2QeGMwljyPg8h63P5WSqb99Pjgr54+Ghhk+MO8+b0stlQz1cpI2HMBGioL6J5PZv2Iod3tn6a2ifS84hb5hNHqLem7A3yC8nafsrU8ntc8l3C6Fp2xAaRJ/Pu568mfdRvntNPl1VvJKbAwW75ZKH5c1Zc260ZLmr5rnkk4wofZQsl8yK+oWU5caftlf1wK0jTdoWDj/DGY0HDjaN0lt3+8pd79lu1zyXvDAqpNfR58dAd3zzySHvCBb3KKh/7tKwte7oJ1j3ySWPcXCQTV56M0fW9x9Z2r6r9rnk6f1hUjy9DhrB5PaTtoy7qGl2k88/20pHnrimYL8oeZgi3Y3TrZYsd9U+l3yOEcV0k4INS7O5id4XX9q+YNtIM/SL+d6HqeWkw4yR3mw4+DHsKm24Gg6bXj+sr8mazvbsqLA8o54MWePO8y7SyzWTzz9dG8+orUm+LMNW2thk2Kqsgn30F7FfLvnbt3/cZ4Dz3/k0C3vD57D/7dewq1emkvfIJU/a3qT4sG2pg/TSprGl1ty9hulyZfEqh7dXPrr9ouSxT9zcBRa70IeyQy75FCNKf1ZyyazYsJAyTOVuyo+zuPky1dvbW/BbzNtGmrR1rculDRdjr12azd71r7SxavhYtUMuOR4V0oaVK5yWztWUXq6KhrwDWNyjYMNc2bC16uioY6fvJY/54m/f/j4Nb/9jjJ9nYe/41vjOuKPlX9Pewx655Lj1Ddvep41p7CC9tHFsj1V3r6Hr1RWv8mgIxJexY5Q8tujJmNnPV67Sho+p9W9cX33+EcV0k4Itk6SxlY+Nf2kW17uOHrN53LaRZix9c4RJQHfb8ceTnHbRSQ+9vdq8n+cnirU1+fSosDBSTGpk+k6+8PRy3VhLacMhpAso2DIRMmyt6Wvy0M7WX8YOv3E9DZO7MPwa9v4t/wVQF/Pc8Bgm/77ExL+G7yq/+HnrnXLJk3aWXncmTfU9t9UfqYHNdp4Lz7tNZNh1XfEabg4U7Bgl34zrl4H6bRyiq0LQ4+ySSz7BiNKfkVwyKzYtpIwDwrXx55bfm9+5cumV+WbNSDMp/e3P62Gnx511l8m+0u5/TPd/2/eH2fLzA1xtTT4/Kkyu5nqBnXSJ+a2xdN6SXhYMu06vD7GpTfIVbZorj/3FsDVzdNSx29+XfBsmB+ZB8rDTSFR8R/vkksPi02b27b2T/tj3l/SHVHJseffNd8HG4hVEyRT0DW6vKPk2GXHrgzfLPb6X3PvsI4rpJgX9Tae+iVzaZ2zW/YbhZN6et400N11uZvaB6fQ0cHueed8N+lzt7fv5UeH2Ct/f/xxrKL81ls7vpZclG4vvwkSIgm0Z0EuLjn35YevRxEsz/XXs8fcll8LkMOpd/syLg+S9cslD+fTqYqmpvg9NPhUcm2lty0vlGzTU5PBnH/jo9swlr4zrH71V7pRL/vQjSh8lyyWzYttCyvJUbt77xo6SNkxsG2lWZqfRB74v7r1ze545BK0eEFbsk0sOR4XF/wzfc0Awls6VkV4WpfLp1SEs7lGwbSHFsLXs6CWp3XLJ62Hy74Wod+kzrw6Sd8sl5w+kF1dx0+uaxWxOuzmVc/1AuzmtJVQK9o2Sl+4CH75R7pVL/uwjiukmBRtvOsP87E7Q+cZ+kjZMbRtplme5cV9Z2Hu3/7vzTJurxo6SviZrOluLUWHhP0N3GelPY+lcF+ll2fUD6cUhamuSL8uw1Ws1bG2oyfb6C9kll9yZfK341kpsPfl1r8GLv5Pc2y2XnD6R/pxEKzp9q5jNaXObrr57XT9RX7zk8PbKR7dzlByP6y3G4n3tlkv+5CNKf/JyyazYvJCSu9BUeNcaukn47saRJjpqZ+kD4d7nZ5LTN03uunvlksNRIUw89SNg+uNYOhdMLytcPpH+fAiLexRsfu4y6i+Grc7RT7DumEvuTH9+a7Qe9M4/sn6MfeyXS75+JP0xm99QLreQ2Zx28xrv9SMbihcc3V758PaOku9+rbl3v475Ee3zG9dXn3lEMd2kYPvS7DCNHMQNdsjfLLy9baSJwsK1jjI/y3D/12JNhrjammw0Kswu8Hp56cVYus2Q91LSBRQYtjovHbZ201/JXrnkzixOvv569arbj/x8+dPWvR1zyZfPpD+Nbn4r7tvbtXHl9nh50du+xnv5zJbi69wcKNg9Sr4f14cfcv7Qdswlf+oRpT9LuWRWPLKQcjuVS61/LjX/xVvaxpHmfsJZKn97louT2W6vbTrcfrnkeFT4fnOBufrSy7F0rrX0skr3mfSnQ1jco+CRubJhK3J01PFwLrner58/r49R//79szIt3H3i8pHfx4TInepc8kPewwH+Lf0Y7WLfeNCPRm2192gIxJfRN+Hdm8j3t2sQ+P45QuRO9feSH/J5RxTTTQr6SdL2JtKNENchYrX193/zyeoYsnWkmRy2Zk1ssvuV0/zeaI6463QzHhW+p9W65gN1POS9ymNtki/ksbmyYWvu8CdY+0t9JJd8ctW55Id8f+0A3/AGdfSqDh+ehZRQdS75IZ93ROmjZLlkVlhIaWXfmmweCK968ZB3R5ukwFy5laNr8gW55E9p31zyX3abLcfaHU7Pp0CUHNo3l/x5RxTTTQrcdFrpa3LHzvbaQejFQ94tbZKCwzOgp3H4lLI7vlzy3L655M9Lz6dAlBzaN5f8efUPbskls8JCSitqshU1SYGFlFaOrkm55NjOueRPS8+nQJQcqv6N6y/GdJMCN51W1GQrapICTaSVw2uyO75c8pxcckzPp0CUHJJLjsklU2AhpRU12YqapMBzl60cXZNyyTG55JieT0Hfc0TJMzt/L/nTMt2koF+a1URasMjdijZJgc7WyuE12R1fLnlOLjmm51MglxySS471UbJcMisspLSiJltRkxSYK7dydE3KJcfkkmNCIAo0kZBccsx0kwLTzVb6mtTZWtAmKTARauXwJ1i748slz8klx9wcKHBzCMklx3wvmQILKa2oyVbUJAXmyq0cXZNyyTG55JieT4EoOeQ3rmOmmxS46bSiJlvpa9KwxYrDM6CncfiUsju+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alt=\"A two-column matrix of nondecreasing values, with the last non-NaN value highlighted in each column. This is converted to another 2-column matrix of the differences from row to row. The total score is shown below, being the highlighted values from before. The matrix is again converted to a new 2-column matrix where each value is the proportion of the total (given by the total score values from before). Finally, a column vector is calculated from the matrix by averaging across the columns.\" data-image-state=\"image-loaded\" width=\"969\" height=\"576\"\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 510.833px; 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 255.417px; transform-origin: 404px 255.417px; 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: 304px 8.5px; tab-size: 4; transform-origin: 304px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex =\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e     0    50\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    20    80\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    30   120\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    70   130\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    70   140\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    80   180\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   100   180\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   110   200\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   140   NaN\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   150   NaN\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: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eavg = partnershipcontrib(x)\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: 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; \"\u003eavg =\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    0.1250\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    0.1417\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    0.1333\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    0.1583\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    0.0250\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    0.1333\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    0.0667\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    0.0833\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    0.2000\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    0.0667\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function avg = partnershipcontrib(s)\r\n\r\navg = mean(s);\r\n\r\nend","test_suite":"%% 12 innings\r\nx = [93 10 9 14 5 46 165 7 42 14 8 88;164 44 10 31 58 55 169 24 72 18 9 98;227 53 10 34 100 144 173 31 145 63 10 228;NaN 58 25 63 NaN 178 241 35 158 69 32 356;NaN 67 143 178 NaN 195 497 58 180 84 45 372;NaN 67 151 342 NaN 277 592 69 188 88 60 379;NaN 88 224 370 NaN 311 592 75 206 151 102 476;NaN 90 NaN 376 NaN 319 643 131 226 185 102 502;NaN 93 NaN 396 NaN 325 668 131 NaN 219 105 522;NaN 101 NaN 431 NaN 326 707 136 NaN 253 109 554];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.127561166808451;0.12977999987294;0.155703562754948;0.0927761241656379;0.177085480116408;0.108446996646594;0.163626020105591;0.0902197552243652;0.0409854550106841;0.0605319499146062])) \u003c 1e-5 )\r\n%% 15 innings\r\nx = [0 36 0 16 40 2 107 49 0 58 15 0 31 35 15;47 149 13 35 43 14 115 92 0 136 106 6 62 51 35;68 204 255 96 102 23 197 183 49 136 133 45 141 72 50;71 237 382 300 114 29 211 199 55 173 137 71 142 78 102;118 308 NaN 507 132 85 217 304 62 173 204 79 162 78 133;132 319 NaN 542 251 96 238 321 67 173 248 87 181 157 150;172 NaN NaN 566 251 143 276 350 67 208 248 99 182 225 183;NaN NaN NaN 572 266 166 NaN 414 71 237 264 117 194 252 197;NaN NaN NaN 572 275 171 NaN 433 75 239 277 119 195 282 197;NaN NaN NaN 606 282 213 NaN 436 90 248 278 129 221 282 250];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.0935178799346019;0.123522199506716;0.214786109140686;0.107581946541405;0.144429580185992;0.105164272050944;0.100678940349023;0.0802158893817775;0.0295136677949011;0.0817011534864528])) \u003c 1e-5 )\r\n%% 10 innings\r\nx = [2 61 9 66 70 24 30 34 2 11;144 176 174 66 126 83 46 82 27 16;NaN 225 259 66 149 159 90 122 74 42;NaN 228 277 153 184 193 100 156 80 43;NaN 229 279 NaN 189 198 133 282 81 51;NaN 261 480 NaN 194 284 163 336 81 82;NaN 263 508 NaN 219 286 197 359 93 124;NaN 263 NaN NaN 220 299 214 466 98 159;NaN 269 NaN NaN 236 300 238 468 105 165;NaN 276 NaN NaN 239 313 239 526 112 193];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.131857056901008;0.25577103343828;0.166489867398518;0.115025818107455;0.0590566909925436;0.149512322121404;0.0855127326608772;0.0780370592130176;0.0413840570886391;0.0573537352490243])) \u003c 1e-5 )\r\n%% 17 innings\r\nx = [47 132 4 29 4 33 14 1 185 16 80 10 39 96 22 49 44;48 175 8 30 11 86 14 20 189 28 139 44 53 NaN 33 113 101;49 260 15 31 13 139 44 131 289 244 142 51 124 NaN NaN 179 103;60 277 70 77 13 161 187 143 321 331 146 55 124 NaN NaN 201 134;90 355 85 88 15 209 200 171 322 339 149 85 124 NaN NaN NaN 142;179 444 114 180 18 294 204 210 347 345 180 106 126 NaN NaN NaN 142;237 510 119 199 21 311 236 255 354 346 181 119 130 NaN NaN NaN 158;248 520 124 205 21 410 320 293 361 350 182 155 156 NaN NaN NaN 159;252 NaN 124 225 21 442 337 301 381 363 227 159 165 NaN NaN NaN 185;257 NaN 124 246 47 NaN 337 312 382 365 233 167 168 NaN NaN NaN 190];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.240994776523359;0.124242738355593;0.166998542784811;0.123630511079241;0.0693601120017177;0.133635916354558;0.0730614634765755;0.0807820974677455;0.0569861900798804;0.0682662046838182])) \u003c 1e-5 )\r\n%% 16 innings\r\nx = [38 32 56 7 87 67 6 0 42 53 8 78 28 0 19 6;140 NaN 75 51 87 100 320 21 55 119 196 100 28 63 47 48;168 NaN 92 148 87 110 329 130 55 122 218 101 32 89 101 48;213 NaN 136 283 219 115 337 176 65 167 318 117 43 196 121 85;266 NaN 150 306 252 169 339 182 86 226 357 373 50 215 121 89;290 NaN 160 347 331 NaN 379 230 106 254 415 439 61 246 130 189;NaN NaN 206 375 333 NaN 418 261 202 301 424 452 64 345 165 197;NaN NaN 206 384 333 NaN 418 273 210 314 455 494 69 353 172 239;NaN NaN 240 394 362 NaN 446 305 237 388 466 NaN 85 353 173 252;NaN NaN 248 403 NaN NaN 453 305 286 419 466 NaN 89 365 181 254];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.182240310458828;0.175892478952746;0.0875416554422805;0.152836201456442;0.112910555705271;0.12396440347931;0.113191687593507;0.0426419111443832;0.0783210269004195;0.0404773549272449])) \u003c 1e-5 )\r\n%% 6 innings\r\nx = [132 23 8 4 1 5;175 52 8 4 10 18;260 68 63 4 33 18;277 80 74 36 36 64;355 80 177 125 43 71;444 112 208 147 43 108;510 113 216 208 43 109;520 148 231 240 52 119;NaN 149 251 253 82 166;NaN 155 265 253 82 167];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.0817279080428618;0.0762315818040129;0.125787053267087;0.0983562962636804;0.169623320455451;0.13384999984987;0.0684430187318784;0.0996265908248745;0.156119498902202;0.0195055780101392])) \u003c 1e-5 )\r\n%% 2 innings\r\nx = [0 79;23 144;40 167;47 177;53 215;68 249;77 249;108 261;110 284;132 320];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.1234375;0.188683712121212;0.100331439393939;0.0421401515151515;0.0821022727272727;0.109943181818182;0.0340909090909091;0.136174242424242;0.0435132575757576;0.139583333333333])) \u003c 1e-5 )\r\n%% 7 innings\r\nx = [82 77 39 17 25 16 9;100 77 146 28 88 57 35;146 91 262 102 119 242 35;163 98 279 114 286 242 39;247 103 305 168 362 277 47;503 173 307 172 368 299 50;557 206 364 194 489 304 59;559 220 605 258 493 309 73;570 267 615 277 554 314 83;NaN NaN 631 293 556 315 86];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.107497876929982;0.11206962590314;0.173226871930385;0.0672585891886349;0.104632115131127;0.120518985511512;0.103128650710132;0.120309237160835;0.0739838287054595;0.0243239063603082])) \u003c 1e-5 )\r\n%% Only one partnership (non-NaN)\r\nx = [51 135 80 56 0 73 12 95 25 158 19 13 10 164 3 1 49 5;99 162 NaN 75 35 146 12 117 115 249 53 63 20 208 34 34 90 39;100 165 NaN 92 73 161 49 117 163 267 80 142 21 218 54 34 99 90;NaN 225 NaN 136 73 351 76 311 NaN 310 92 170 51 330 115 59 128 113;NaN 241 NaN 150 74 389 205 313 NaN 321 143 188 94 364 115 90 152 119;NaN 281 NaN 160 84 394 224 315 NaN 326 170 196 100 388 137 127 208 170;NaN 288 NaN 206 123 422 233 376 NaN 370 178 196 100 396 185 149 241 203;NaN 294 NaN 206 181 449 245 434 NaN 447 178 205 100 408 210 173 267 239;NaN 312 NaN 240 193 475 258 451 NaN 460 226 205 104 424 210 200 283 270;NaN 343 NaN 248 202 481 270 460 NaN NaN 226 231 104 424 210 200 426 271];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.211390656192859;0.168194620890675;0.0927330577536002;0.177194557307618;0.114920288442186;0.0786823138140911;0.0873894127938098;0.0799241281835184;0.0661291359874339;0.0496857216889986])) \u003c 1e-5 )\r\n%% No NaNs at all\r\nx = [2 114;9 116;18 195;20 266;50 294;206 316;215 326;229 340;242 390;247 422];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.139119673043345;0.0165397087322755;0.111820519216379;0.0881718057447666;0.0939041003895082;0.341855824395111;0.0300669647140089;0.0449277586967784;0.0855574956348217;0.0480361494330065])) \u003c 1e-5 )\r\n%% Only one innings - no NaNs\r\nx = [20;35;39;111;123;123;128;133;149;153];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.130718954248366;0.0980392156862745;0.0261437908496732;0.470588235294118;0.0784313725490196;0;0.0326797385620915;0.0326797385620915;0.104575163398693;0.0261437908496732])) \u003c 1e-5 )\r\n%% Only one innings - with NaNs\r\nx = [107;152;204;250;NaN;NaN;NaN;NaN;NaN;NaN];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.428;0.18;0.208;0.184;NaN;NaN;NaN;NaN;NaN;NaN])) \u003c 1e-5 )","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":287,"edited_by":287,"edited_at":"2022-11-08T20:18:04.000Z","deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-11-07T18:20:52.000Z","updated_at":"2025-12-06T12:44:27.000Z","published_at":"2022-11-08T15:10:27.000Z","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\u003eThe (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-\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 matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for \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 innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003es for the partnerships that did not occur. (This means the total team score is the last non-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e value in each column.) The average across the \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 sample innings should ignore \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003es.\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\u003eIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\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=\\\"576\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"969\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"A two-column matrix of nondecreasing values, with the last non-NaN value highlighted in each column. This is converted to another 2-column matrix of the differences from row to row. The total score is shown below, being the highlighted values from before. The matrix is again converted to a new 2-column matrix where each value is the proportion of the total (given by the total score values from before). Finally, a column vector is calculated from the matrix by averaging across the columns.\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\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 = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\\nx =\\n     0    50\\n    20    80\\n    30   120\\n    70   130\\n    70   140\\n    80   180\\n   100   180\\n   110   200\\n   140   NaN\\n   150   NaN\\n\\navg = partnershipcontrib(x)\\navg =\\n    0.1250\\n    0.1417\\n    0.1333\\n    0.1583\\n    0.0250\\n    0.1333\\n    0.0667\\n    0.0833\\n    0.2000\\n    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average ignoring NaN values","description":"Given a matrix, calculate the block average of each disjoint sub-matrix while ignoring *NaN* values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\r\n\r\n* Input: matrix *A* and the size of each sub-matrix *subsz*\r\n* Output: *B = blknanavg(A,subsz)*\r\n    \r\n\r\nExample:\r\n\r\n    A = [1 2 3 4 5 6 7 8 NaN];\r\n    subsz = [1  3];\r\n    B = [2  5  (7+8)/2];\r\n\r\nHint: this is related to \u003chttp://www.mathworks.com/matlabcentral/cody/problems/42856-block-average Problem 42856. Block average\u003e.","description_html":"\u003cp\u003eGiven a matrix, calculate the block average of each disjoint sub-matrix while ignoring \u003cb\u003eNaN\u003c/b\u003e values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\u003c/p\u003e\u003cul\u003e\u003cli\u003eInput: matrix \u003cb\u003eA\u003c/b\u003e and the size of each sub-matrix \u003cb\u003esubsz\u003c/b\u003e\u003c/li\u003e\u003cli\u003eOutput: \u003cb\u003eB = blknanavg(A,subsz)\u003c/b\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e    A = [1 2 3 4 5 6 7 8 NaN];\r\n    subsz = [1  3];\r\n    B = [2  5  (7+8)/2];\u003c/pre\u003e\u003cp\u003eHint: this is related to \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/42856-block-average\"\u003eProblem 42856. Block average\u003c/a\u003e.\u003c/p\u003e","function_template":"function B = blknanavg(A)\r\n  B = A;\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8 NaN];\r\nsubsz = [1  3];\r\nB = [2  5  (7+8)/2];\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = [1 2 3 4 NaN 6 7 NaN 9].';\r\nsubsz = [3,1];\r\nB = [2 5 8].';\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = [1       1     1       2     NaN       2\r\n     1     NaN     1     NaN       2     NaN\r\n     3       3     3     NaN     NaN     4\r\n     3       3     3     NaN       4     4];\r\nsubsz = [2   3];\r\nB = [1    2\r\n     3    4];\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = rand(100,300);\r\nA(randperm(numel(A),10)) = NaN;\r\nsubsz = size(A);\r\nB = mean(A(:),'omitnan');\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nsubsz = [4,6];\r\nB = 10*rand(10,20);\r\nA = repelem(B,subsz(1),subsz(2));\r\nA(randperm(numel(A),10)) = NaN;\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12569,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":24,"created_at":"2016-05-21T19:53:06.000Z","updated_at":"2026-04-06T19:37:34.000Z","published_at":"2016-05-21T20:04:51.000Z","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, calculate the block average of each disjoint sub-matrix while ignoring\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\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput: matrix\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\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and the size of each sub-matrix\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\u003esubsz\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput:\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\u003eB = blknanavg(A,subsz)\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:\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 5 6 7 8 NaN];\\n    subsz = [1  3];\\n    B = [2  5  (7+8)/2];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: this is related to\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/matlabcentral/cody/problems/42856-block-average\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 42856. Block average\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":690,"title":"Remove the two elements next to NaN value","description":"The aim is to *remove the two elements next to NaN values* inside a vector.\r\n\r\nFor example:\r\n\r\n x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]\r\n\r\nThe output y will be:\r\n\r\n y = [6 10 5 8 9 7 3 21 43 7 8]\r\n\r\nNan values and the 2 next elements after the NaN (23-9  and 4-6) have been removed.\r\n\r\nThere will be always NaN values in the input vector followed by at least 2 integers.","description_html":"\u003cp\u003eThe aim is to \u003cb\u003eremove the two elements next to NaN values\u003c/b\u003e inside a vector.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre\u003e x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]\u003c/pre\u003e\u003cp\u003eThe output y will be:\u003c/p\u003e\u003cpre\u003e y = [6 10 5 8 9 7 3 21 43 7 8]\u003c/pre\u003e\u003cp\u003eNan values and the 2 next elements after the NaN (23-9  and 4-6) have been removed.\u003c/p\u003e\u003cp\u003eThere will be always NaN values in the input vector followed by at least 2 integers.\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8];\r\ny_correct = [6 10 5 8 9 7 3 21 43 7 8];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [25 NaN 1 3];\r\ny_correct = 25;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [ NaN 15 15 17 ]\r\ny_correct = 17;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":9,"comments_count":7,"created_by":639,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":703,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":12,"created_at":"2012-05-15T09:33:34.000Z","updated_at":"2026-02-10T12:07:16.000Z","published_at":"2012-05-15T09:33:34.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe aim is to\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\u003eremove the two elements next to NaN values\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e inside a vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output y will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [6 10 5 8 9 7 3 21 43 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNan values and the 2 next elements after the NaN (23-9 and 4-6) have been removed.\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 will be always NaN values in the input vector followed by at least 2 integers.\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":44430,"title":"remove every row\u0026col for every nan","description":"for a given matrix, remove the row and column of every nan. Example\r\n\r\n  x=[1     2   NaN\r\n     4     5     6\r\n     7     8     9]\r\n\r\n  y= [4     5\r\n      7     8]","description_html":"\u003cp\u003efor a given matrix, remove the row and column of every nan. Example\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex=[1     2   NaN\r\n   4     5     6\r\n   7     8     9]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003ey= [4     5\r\n    7     8]\r\n\u003c/pre\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%test 1\r\nx = [1 2 3 nan];\r\ny_correct =[]\r\nassert(isequal(isempty(your_fcn_name(x)),isempty(y_correct)))\r\n%%test 2\r\nx = [nan nan 5;8 nan 2];\r\ny_correct = []\r\nassert(isequal(isempty(your_fcn_name(x)),isempty(y_correct)))\r\n%%test 3\r\nx = [nan nan 5;1 2 3;7 8 9];\r\ny_correct = [3;9]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%test 3\r\nx = [1 2 3;1 2 3;7 8 9];\r\ny_correct = [1 2 3;1 2 3;7 8 9]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%test 3\r\nx = [1 2 nan;nan 2 3;7 8 9];\r\ny_correct = 8\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":302,"test_suite_updated_at":"2017-12-03T12:45:32.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-02T15:49:05.000Z","updated_at":"2026-04-02T18:04:09.000Z","published_at":"2017-12-02T15:49:05.000Z","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\u003efor a given matrix, remove the row and column of every nan. Example\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[x=[1     2   NaN\\n   4     5     6\\n   7     8     9]\\n\\ny= [4     5\\n    7     8]]]\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":2803,"title":"Split up vector or matrix delimited by NaNs","description":"Given several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\r\nGiven several matrices combined in one matrix delimited by all-NaN rows , return each matrix as an element of a cell vector.","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: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; 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: 383px 8px; transform-origin: 383px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 210.5px 8px; transform-origin: 210.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven several matrices combined in one matrix delimited by all-NaN\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: 14.5px 8px; transform-origin: 14.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003erows\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: 138px 8px; transform-origin: 138px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e , return each matrix as an element of a cell vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function c = split_nan_delimited(x)\r\n  c = x;\r\nend","test_suite":"%%\r\nx = 7;\r\nc_correct = {7};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = nan;\r\nassert(isempty(split_nan_delimited(x)) \u0026\u0026 iscell(split_nan_delimited(x)))\r\n\r\n%%\r\nx = [nan; 7; 0; nan];\r\nc_correct = {[7; 0]};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = rand(66,1);\r\nc_correct = {x};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = (1:20);\r\nc_correct = {x};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [1 76 -inf 0 3 nan 16 7 2 1 0 0 inf 13]';\r\nc_correct = {x(1:5) x(7:end)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [2 nan 3 nan 5 nan 7 nan 11 nan 13 nan 17];\r\nc_correct = {x(1) x(3) x(5) x(7) x(9) x(11) x(13)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = (1:34)';\r\nx([6:7 19:21 30]) = nan;\r\nc_correct = {x(1:5) x(8:18) x(22:29) x(31:end)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = 10*rand(55,6)-5;\r\nx([1:2 6 13:15 40],:) = nan; \r\nc_correct = {x(3:5,:) x(7:12,:) x(16:39,:) x(41:end,:)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [nan(4); magic(4); nan(1,4); inf(4); ones(4)];\r\nc_correct = {magic(4) [inf(4); ones(4)]};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = nan(6);\r\nc_correct = {};\r\nassert(isempty(split_nan_delimited(x)) \u0026\u0026 iscell(split_nan_delimited(x)))\r\n\r\n%%\r\nx = [nan(4); ones(1,4)];\r\nc_correct = {ones(1,4)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))","published":true,"deleted":false,"likes_count":1,"comments_count":5,"created_by":10139,"edited_by":223089,"edited_at":"2022-09-24T10:12:37.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2022-09-24T10:12:37.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-12-29T20:31:28.000Z","updated_at":"2025-03-02T14:20:21.000Z","published_at":"2014-12-29T21:07:56.000Z","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\u003eGiven several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven several matrices combined in one matrix delimited by all-NaN\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\u003erows\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e , return each matrix as an element of a cell vector.\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":2010,"title":"Wrap a vector, but insert NaN's at the wrap-positions.","description":"When you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\r\nThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\r\nThe modulo of the wrapping range is explicitly entered into the function.\r\nFor example, if we wrap a vector [1:20] at 3, this will result in [1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2].\r\nAs (almost) always, regexp and eval are not appreciated.","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: 184px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 92px; transform-origin: 407px 92px; 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: 363px 8px; transform-origin: 363px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhen you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\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: 291px 8px; transform-origin: 291px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\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: 224.5px 8px; transform-origin: 224.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe modulo of the wrapping range is explicitly entered into the function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 43px; 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 21.5px; text-align: left; transform-origin: 384px 21.5px; 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: 101.5px 8px; transform-origin: 101.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, if we wrap a vector\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: 24px 8px; transform-origin: 24px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 24px 8.5px; transform-origin: 24px 8.5px; \"\u003e[1:20]\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: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e at\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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e3\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: 53px 8px; transform-origin: 53px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, this will result in\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: 180px 8px; transform-origin: 180px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 180px 8.5px; transform-origin: 180px 8.5px; \"\u003e[1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 179px 8px; transform-origin: 179px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAs (almost) always, regexp and eval are not appreciated.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = wrapnan(x,m)\r\n  y = mod(x,m);\r\nend","test_suite":"%%\r\nx = 1:20;\r\nm = 3;\r\ny = wrapnan(x,m);\r\ny_correct = [1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2];\r\nassert(isequaln(y,y_correct))\r\nfiletext = fileread('wrapnan.m');\r\nassert(isempty(strfind(filetext, 'regexp')),'regexp* command is forbidden');\r\nassert(isempty(strfind(filetext, 'eval')),'eval* command is forbidden');\r\nassert(isempty(strfind(filetext, 'inline')),'inline command is forbidden');\r\n\r\n%%\r\nx = [1 50 95 105 195 205 190 310 290 250 201 10];\r\nm = 100;\r\ny = wrapnan(x,m);\r\ny_correct = [1 50 95 nan 5 95 nan 5 nan 90 nan 10 nan 90 50 1 nan 10];\r\nassert(isequaln(y,y_correct))\r\n\r\n%%\r\nx = [0.25 0.45 0.80 0.90 1.25 0.60 0.10 0.20 1.70 1.60 1.50 1.80 1.40 0.10];\r\nm = 0.5;\r\ny = wrapnan(x,m);\r\ny_correct = [0.25 0.45  NaN 0.30 0.40  NaN 0.25  NaN 0.10  NaN 0.10 0.20  NaN 0.20 0.10 0.00 0.30  NaN 0.40  NaN 0.10];\r\nassert(isequaln(round(y,2),round(y_correct,2)))","published":true,"deleted":false,"likes_count":1,"comments_count":7,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":21,"test_suite_updated_at":"2021-06-26T18:48:50.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-20T23:54:45.000Z","updated_at":"2026-01-20T15:42:31.000Z","published_at":"2013-11-21T00:10:43.000Z","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\u003eWhen you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\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 modulo of the wrapping range is explicitly entered into the 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:r\u003e\u003cw:t\u003eFor example, if we wrap a vector\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1:20]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e at\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, this will result in\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2]\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAs (almost) always, regexp and eval are not appreciated.\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":42672,"title":"Longest Sequence of NaNs","description":"In an array return the length of longest sequence of nans for each column. \r\n\r\n x = \r\n [ 2   3   1   2   5   6;\r\n  nan nan  5  nan  6  -9;\r\n   5  nan  8  nan  6   5;\r\n   8  nan  7   -5 5.8  5;\r\n  nan  0   0  nan  5   7;\r\n  nan  5   9  nan  7  nan;\r\n  nan nan 10   0  nan  6;\r\n  nan nan  0   1  nan  9];\r\n\r\n y_correct = \r\n [ 4   3   0   2   2   1];\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: 271px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 343px 135.5px; transform-origin: 343px 135.5px; 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: 320px 10.5px; text-align: left; transform-origin: 320px 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=\"\"\u003eIn an array return the length of longest sequence of nans for each column.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 240px; border-bottom-left-radius: 4px; border-bottom-right-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: 340px 120px; transform-origin: 340px 120px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e x = \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e     [ 2   3   1   2   5   6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan  5  nan  6  -9;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e       5  nan  8  nan  6   5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e       8  nan  7   -5 5.8  5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan  0   0  nan  5   7;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan  5   9  nan  7  nan;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan 10   0  nan  6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan  0   1  nan  9]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e y_correct = \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e     [ 4   3   0   2   2   1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = longnan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\n x = [ 2   3   1   2   5   6;\r\n nan nan  5  nan  6  -9;\r\n 5  nan  8  nan  6   5;\r\n 8  nan  7   -5 5.8  5;\r\n nan  0   0  nan  5   7;\r\n nan  5   9  nan  7  nan;\r\n nan nan 10   0  nan  6;\r\n nan nan  0   1  nan  9];\r\n\r\n y_correct = [ 4   3   0   2   2   1];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n%%\r\nx = eye(3);\r\ny_correct = [0 0 0];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = eye(3);\r\nx(1,1) = nan;\r\ny_correct = [1 0 0];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = [30\t39\tNaN\t1\t10\tNaN\t28\r\n38\t47\tNaN\t9\t18\t27\tNaN\r\n46\tNaN\tNaN\t17\tNaN\tNaN\t37\r\n5\tNaN\tNaN\t25\tNaN\t36\tNaN\r\n13\t15\tNaN\t33\tNaN\tNaN\tNaN\r\n21\tNaN\t32\t41\t43\t3\tNaN\r\n22\t31\tNaN\t49\t2\tNaN\tNaN];\r\ny_correct = [0 2 5 0 3 1 4];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = nan(10);\r\ny_correct = repmat(10,1,10);\r\nassert(isequal(longnan(x),y_correct));","published":true,"deleted":false,"likes_count":1,"comments_count":4,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2015-10-24T10:53:06.000Z","rescore_all_solutions":false,"group_id":39,"created_at":"2015-10-24T06:43:30.000Z","updated_at":"2026-04-02T08:04:49.000Z","published_at":"2015-10-24T06:43:30.000Z","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\u003eIn an array return the length of longest sequence of nans for each column.\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 = \\n     [ 2   3   1   2   5   6;\\n      nan nan  5  nan  6  -9;\\n       5  nan  8  nan  6   5;\\n       8  nan  7   -5 5.8  5;\\n      nan  0   0  nan  5   7;\\n      nan  5   9  nan  7  nan;\\n      nan nan 10   0  nan  6;\\n      nan nan  0   1  nan  9]\\n\\n y_correct = \\n     [ 4   3   0   2   2   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":58339,"title":"Remove runs of at least n consecutive NaNs","description":"This problem is inspired by Dyuman Joshi's problem 58329. Given a row vector x and a natural number n, remove all runs of at least n consecutive NaNs from x, leaving all shorter runs as well as all non-NaN elements intact.\r\n\r\nFor instance, given\r\n\r\nx = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]\r\n\r\nthe results would be as follows:\r\n\r\n\u003e\u003e removenans1n(x, 1)\r\nans =\r\n     1     2     3     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 2)\r\nans =\r\n     1   NaN     2     3     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 3)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 4)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\r\n\u003e\u003e removenans1n(x, 5)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN\r\n\r\nwith no changes in output for even higher n (since x only contains runs of NaNs up to length four).\r\n\r\nTo make this challenging, provide a vectorized solution: no loops, no arrayfun (in fact, no fun at all, though you're still allowed to have fun), and no recursion. Regular expressions are also outlawed (I don't think that this is a problem that is naturally solved using regular expressions, so I don't feel too bad about doing so). \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: 765.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 490px 382.833px; transform-origin: 490.005px 382.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 43.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 21.6667px; text-align: left; transform-origin: 384.5px 21.6667px; 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 inspired by Dyuman Joshi's \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/58329\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eproblem 58329\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. Given a row vector \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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 and a natural number \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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, remove all runs of at least \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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 consecutive NaNs from \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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, leaving all shorter runs as well as all non-NaN elements intact.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor instance, given\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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-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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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; 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; \"\u003ex = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]\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: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ethe results would be as follows:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 306.562px; 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: 487px 153.281px; transform-origin: 487.005px 153.281px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1     2     3     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 3)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 4)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 5)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN\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: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.8333px; text-align: left; transform-origin: 384.5px 10.8333px; 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=\"\"\u003ewith no changes in output for even higher \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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 (since \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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 only contains runs of NaNs up to length four).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 31.8333px; text-align: left; transform-origin: 384.5px 31.8333px; 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 make this challenging, \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; \"\u003eprovide a vectorized solution:\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 no loops, no \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003earrayfun\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 (in fact, no \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efun\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 at all, though you're still allowed to have fun), and no recursion. Regular expressions are also outlawed (I don't think that this is a problem that is naturally solved using regular expressions, so I don't feel too bad about doing so). \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = removenans1n(x, n)\r\n\r\nend\r\n","test_suite":"%%\r\nfiletext = fileread('removenans1n.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'while') || contains(filetext, 'for') || ...\r\n          contains(filetext, 'cellfun') || contains(filetext, 'arrayfun') || ...\r\n          contains(filetext, 'rowfun') || contains(filetext, 'structfun') || ...\r\n          contains(filetext, 'varfun'); \r\nassert(~illegal)\r\n\r\nrecursion = contains(filetext(find(filetext == char(13)) + 1:end), \"removenans1n\");\r\nassert(~recursion)\r\n\r\n%%\r\nx = [NaN NaN 1 NaN 2 NaN NaN 3 NaN NaN NaN NaN NaN NaN 7 NaN NaN NaN -2 NaN NaN NaN];\r\nassert(isequaln(removenans1n(x, 1), [1 2 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 2), [1 NaN 2 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 3), [NaN NaN 1 NaN 2 NaN NaN 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 4), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nassert(isequaln(removenans1n(x, 5), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nassert(isequaln(removenans1n(x, 6), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nfor i = 7:255\r\n    assert(isequaln(removenans1n(x, i), [NaN NaN 1 NaN 2 NaN NaN 3 NaN NaN NaN NaN NaN NaN 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nend\r\n\r\n%%\r\nx = [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17 NaN NaN NaN NaN];\r\nassert(isequaln(removenans1n(x, 1), [3 56 1 1 438 1 2 6 5 1 38 2 3 4 17]))\r\nassert(isequaln(removenans1n(x, 2), [3 56 1 1 438 NaN 1 2 NaN 6 5 1 38 2 3 4 NaN 17]))\r\nassert(isequaln(removenans1n(x, 3), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 5 1 38 2 3 4 NaN 17]))\r\nassert(isequaln(removenans1n(x, 4), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17]))\r\nfor i = 5:255\r\n    assert(isequaln(removenans1n(x, i), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17 NaN NaN NaN NaN]))\r\nend\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":332395,"edited_by":332395,"edited_at":"2023-05-19T16:49:43.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-05-19T16:33:16.000Z","updated_at":"2025-09-19T01:20:54.000Z","published_at":"2023-05-19T16:33:16.000Z","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 inspired by Dyuman Joshi's \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/58329\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 58329\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Given a row vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and a natural number \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, remove all runs of at least \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e consecutive NaNs from \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, leaving all shorter runs as well as all non-NaN elements intact.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor instance, given\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[x = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]]]\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\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 results would be as follows:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[\u003e\u003e removenans1n(x, 1)\\nans =\\n     1     2     3     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 2)\\nans =\\n     1   NaN     2     3     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 3)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 4)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\\n\u003e\u003e removenans1n(x, 5)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN]]\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\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\u003ewith no changes in output for even higher \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e (since \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e only contains runs of NaNs up to length four).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo make this challenging, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eprovide a vectorized solution:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e no loops, no \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003earrayfun\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (in fact, no \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efun\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e at all, though you're still allowed to have fun), and no recursion. Regular expressions are also outlawed (I don't think that this is a problem that is naturally solved using regular expressions, so I don't feel too bad about doing so). \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\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\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":2050,"title":"remove nans fast","description":"There are several ways to locate and remove nans in a matrix, and return an 1d row vector. \r\n\r\nIn this problem the challenge is to do it within a set time as measured by tic-toc.\r\n\r\nThe problem will be run numerous times and an average time tested.\r\n\r\nNote: I noticed a rare failure depending on when I ran the testsuite, so you _might_ have to resubmit your code if it runs faster on your machine than the limit set here.","description_html":"\u003cp\u003eThere are several ways to locate and remove nans in a matrix, and return an 1d row vector.\u003c/p\u003e\u003cp\u003eIn this problem the challenge is to do it within a set time as measured by tic-toc.\u003c/p\u003e\u003cp\u003eThe problem will be run numerous times and an average time tested.\u003c/p\u003e\u003cp\u003eNote: I noticed a rare failure depending on when I ran the testsuite, so you \u003ci\u003emight\u003c/i\u003e have to resubmit your code if it runs faster on your machine than the limit set here.\u003c/p\u003e","function_template":"function nanless = removenan(m)\r\nloc=find(nan);\r\nnanless= removenan(m,loc);\r\nend","test_suite":"%% T1\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(100,100,100);\r\n m(m\u003e0.7)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(100,100,100);\r\nm(m\u003e0.7)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n\r\n%% T2\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(100,10000);\r\n m(m\u003e0.71)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(100,10000);\r\nm(m\u003e0.71)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n\r\n%% T3\r\ntm=[];\r\nfor t=1:100\r\n rng('default');\r\n m=rand(2,500000);\r\n m(m\u003e0.69)=nan;\r\n tic\r\n  o=removenan(m);\r\n tm(t)=toc;\r\nend\r\nrng('default');\r\nm=rand(2,500000);\r\nm(m\u003e0.69)=nan;\r\nm(isnan(m))=[];\r\nt_correct=0.019;\r\nassert(mean(tm)\u003ct_correct)\r\nassert(isequal(o,m'))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":17471,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":"2013-12-15T04:17:20.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-12-15T03:36:48.000Z","updated_at":"2026-02-13T18:32:27.000Z","published_at":"2013-12-15T04:15:46.000Z","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\u003eThere are several ways to locate and remove nans in a matrix, and return an 1d row vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem the challenge is to do it within a set time as measured by tic-toc.\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 problem will be run numerous times and an average time tested.\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\u003eNote: I noticed a rare failure depending on when I ran the testsuite, so you\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\u003emight\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e have to resubmit your code if it runs faster on your machine than the limit set here.\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":44242,"title":"Replace Nan!","description":"Replace Nan in the given vector(v) with 9999.","description_html":"\u003cp\u003eReplace Nan in the given vector(v) with 9999.\u003c/p\u003e","function_template":"function y = ReplaceNan(v)\r\n  y = v;\r\nend","test_suite":"%%\r\nx=[1 2 3 0/0 4];\r\ny_correct = [1 2 3 9999 4];\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n\r\n%%\r\nx=[5:9];\r\ny_correct =[5:9];\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n\r\n%%\r\nx=repmat(0/0,1,10);\r\ny_correct = repmat(9999,1,10);\r\nassert(isequal(ReplaceNan(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":102298,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":87,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-06-27T13:30:08.000Z","updated_at":"2026-02-13T18:08:24.000Z","published_at":"2017-06-27T13:33:17.000Z","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\",\"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\u003eReplace Nan in the given vector(v) with 9999.\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":42481,"title":"Low level NaN","description":"I have a dataset. Columns represents different variables.\r\nA variable may start with NaN or any double type number.\r\nIf it starts with double number it continues with double type numbers.\r\nIf it starts with NaN, we do not know when it ends.\r\nReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\r\nInput\r\n[ 1 NaN 5 NaN 2\r\n2 NaN 4 4 8\r\n6 NaN 8 2 4\r\n0 0 0 0 0]\r\nshould return 3 because last NaN is observed in third row.\r\nTest suite may be changed!","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: 325.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 162.583px; transform-origin: 407px 162.583px; vertical-align: baseline; \"\u003e\u003cul style=\"block-size: 102.167px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 391px 51.0833px; transform-origin: 391px 51.0833px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 178.5px 8px; transform-origin: 178.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eI have a dataset. Columns represents different variables.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 180px 8px; transform-origin: 180px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA variable may start with NaN or any double type number.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 214.5px 8px; transform-origin: 214.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf it starts with double number it continues with double type numbers.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 153.5px 8px; transform-origin: 153.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf it starts with NaN, we do not know when it ends.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2167px; text-align: left; transform-origin: 363px 10.2167px; white-space: pre-wrap; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 275.5px 8px; transform-origin: 275.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\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: 15.5px 8px; transform-origin: 15.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eInput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2px 8.5px; transform-origin: 2px 8.5px; \"\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: 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: 52px 8px; transform-origin: 52px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 52px 8.5px; transform-origin: 52px 8.5px; \"\u003e1 NaN 5 NaN 2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 44px 8px; transform-origin: 44px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 44px 8.5px; transform-origin: 44px 8.5px; \"\u003e2 NaN 4 4 8\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 44px 8px; transform-origin: 44px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 44px 8.5px; transform-origin: 44px 8.5px; \"\u003e6 NaN 8 2 4\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 36px 8px; transform-origin: 36px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e0 0 0 0 0\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=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2px 8.5px; transform-origin: 2px 8.5px; \"\u003e]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 181.5px 8px; transform-origin: 181.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eshould return 3 because last NaN is observed in third row.\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: 87px 8px; transform-origin: 87px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eTest suite may be changed!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = lowestLevelNaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1\tNaN\t0\t0\r\n2\tNaN\t0\t0\r\n3\tNaN\t1\t0\r\n4\t3\t2\t1\r\n5\t4\t3\t2\r\n6\t5\t4\t3];\r\ny_correct = 3;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [1\tNaN\t0\tNaN\r\n2\tNaN\t0\tNaN\r\n3\tNaN\t1\tNaN\r\n4\t3\t2\tNaN\r\n5.7\t4\t3\tNaN\r\n6\t5\t4\t3];\r\ny_correct = 5;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n\r\n%%\r\nx = [NaN\tNaN\t0\tNaN\r\nNaN\tNaN\t0\tNaN\r\nNaN\tNaN\t1\tNaN\r\nNaN\t3\t2\t-4.5\r\n5.7\t4\t3\t0.0\r\n6\t5\t4\t3];\r\ny_correct = 4;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [NaN];\r\ny_correct = 1;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n\r\n%%\r\nx = [NaN\tNaN\tNaN\tNaN\r\nNaN\tNaN\tNaN\tNaN\r\nNaN\tNaN\tNaN\tNaN\r\nNaN\t3\tNaN\tNaN\r\n5.7\t4\tNaN\tNaN\r\n6\t5\tNaN\tNaN\r\n4\t0\t0\t0];\r\ny_correct = 6;\r\nassert(isequal(lowestLevelNaN(x),y_correct))\r\n\r\n%%\r\nx = [1\tNaN\r\n1\tNaN\r\n1\tNaN\r\n1\tNaN\r\n5.7\tNaN\r\n6\tNaN\r\n-1.0\tNaN\r\n4\tNaN\r\n4\tNaN\r\n4\tNaN\r\n4\tNaN];\r\ny_correct = 11;\r\nassert(isequal(lowestLevelNaN(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":8703,"edited_by":223089,"edited_at":"2022-10-23T10:32:55.000Z","deleted_by":null,"deleted_at":null,"solvers_count":66,"test_suite_updated_at":"2015-08-01T02:31:46.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-07-31T17:19:52.000Z","updated_at":"2026-02-26T12:21:33.000Z","published_at":"2015-07-31T17:47:04.000Z","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=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI have a dataset. Columns represents different variables.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA variable may start with NaN or any double type number.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf it starts with double number it continues with double type numbers.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf it starts with NaN, we do not know when it ends.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eReturn the row index where last NaN is observed in overall dataset. (Think column-wise)\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\u003eInput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e1 NaN 5 NaN 2\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e2 NaN 4 4 8\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e6 NaN 8 2 4\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e0 0 0 0 0\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eshould return 3 because last NaN is observed in third row.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTest suite may be changed!\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":42261,"title":"Determine if a row vector has NaN","description":"Determine if a row vector x has NaN","description_html":"\u003cp\u003eDetermine if a row vector x has NaN\u003c/p\u003e","function_template":"function y = NaNis(x)\r\n  y = NaNis;\r\nend","test_suite":"%%\r\nx = [1,2,3,4,NaN];\r\ny = 1;\r\nassert(isequal(NaNis(x),y))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":38003,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":136,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-04-24T07:02:25.000Z","updated_at":"2026-02-16T16:46:47.000Z","published_at":"2015-04-24T07:02:29.000Z","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\u003eDetermine if a row vector x has NaN\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":43708,"title":"Replace all odd numbers with NaN","description":"Replace all odd numbers in the vector or matrix with NaN. For example, if\r\n\r\n x = [1 3 4 5 8 11];\r\n\r\nthen return\r\n\r\n y = [NaN NaN 4 NaN 8 Nan];","description_html":"\u003cp\u003eReplace all odd numbers in the vector or matrix with NaN. For example, if\u003c/p\u003e\u003cpre\u003e x = [1 3 4 5 8 11];\u003c/pre\u003e\u003cp\u003ethen return\u003c/p\u003e\u003cpre\u003e y = [NaN NaN 4 NaN 8 Nan];\u003c/pre\u003e","function_template":"function y = replace_odd_with_NaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 3 4 5 8 11];\r\ny_correct = [NaN NaN 4 NaN 8 NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = magic(4);\r\ny_correct = [16 2 NaN NaN; NaN NaN 10 8; NaN NaN 6 12; 4 14 NaN NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = 1:20;\r\ny_correct = [NaN(1,10); 2:2:20];\r\ny_correct = y_correct(:)';\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = pascal(2);\r\ny_correct = [NaN NaN; NaN 2];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n\r\n%%\r\nx = eye(3);\r\ny_correct = [NaN 0 0; 0 NaN 0; 0 0 NaN];\r\nassert(isequaln(replace_odd_with_NaN(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":9,"created_by":88437,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":83,"test_suite_updated_at":"2016-12-05T17:06:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-12-04T13:23:09.000Z","updated_at":"2026-02-17T14:35:28.000Z","published_at":"2016-12-04T13:23:09.000Z","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\u003eReplace all odd numbers in the vector or matrix with NaN. For 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[ x = [1 3 4 5 8 11];]]\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\u003ethen return\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [NaN NaN 4 NaN 8 Nan];]]\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":1406,"title":"Generate a NaN...on purpose","description":"The goal is to create a function that will return a single \"NaN\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\r\n\r\n","description_html":"\u003cp\u003eThe goal is to create a function that will return a single \"NaN\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\u003c/p\u003e","function_template":"function y = GenerateNAN\r\n  y = 0;\r\nend","test_suite":"%%\r\nassert(isnan(GenerateNAN))\r\n\r\n%%\r\nfiletext = fileread('GenerateNAN.m');\r\nassert(isempty(strfind(filetext, 'regexp')))\r\nassert(isempty(strfind(filetext, 'nan')))\r\nassert(isempty(strfind(filetext, 'NaN')))\r\n","published":true,"deleted":false,"likes_count":6,"comments_count":4,"created_by":3096,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":326,"test_suite_updated_at":"2013-04-01T16:51:00.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-04-01T16:46:28.000Z","updated_at":"2026-03-09T20:29:02.000Z","published_at":"2013-04-01T16:51:00.000Z","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\u003eThe goal is to create a function that will return a single \\\"NaN\\\" without using the nan function. I am interested to see how many different ways this can be done, so be creative and submit more than one solution if you have lots of ideas!\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":1194,"title":"Replace multiples of 5 with NaN","description":"It is required to replace all values in a vector that are multiples of 5 with NaN.\r\n\r\nExample:\r\n\r\n input:   x = [1 2 5 12 10 7]\r\n output:  y = [1 2 NaN 12 NaN 7]","description_html":"\u003cp\u003eIt is required to replace all values in a vector that are multiples of 5 with NaN.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e input:   x = [1 2 5 12 10 7]\r\n output:  y = [1 2 NaN 12 NaN 7]\u003c/pre\u003e","function_template":"function y = repnan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1 2 5 12 10 7];\r\ny_correct = [1 2 NaN 12 NaN 7];\r\nassert(isequaln(repnan(x),y_correct))\r\n\r\n%%\r\nx = [-1 7 -15 20 11 3];\r\ny_correct = [-1 7 NaN NaN 11 3];\r\nassert(isequaln(repnan(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3399,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":468,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-10T19:04:51.000Z","updated_at":"2026-03-05T11:40:16.000Z","published_at":"2013-01-10T19:07:36.000Z","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\u003eIt is required to replace all values in a vector that are multiples of 5 with NaN.\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:\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 = [1 2 5 12 10 7]\\n output:  y = [1 2 NaN 12 NaN 7]]]\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":42480,"title":"Go back n times","description":"You will be given a column vector (such as x =  [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\r\n\r\n [ 1 NaN NaN NaN\r\n   2   1 NaN NaN\r\n   3   2   1 NaN\r\n   4   3   2   1\r\n   5   4   3   2 \r\n   6   5   4   3 ]","description_html":"\u003cp\u003eYou will be given a column vector (such as x =  [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\u003c/p\u003e\u003cpre\u003e [ 1 NaN NaN NaN\r\n   2   1 NaN NaN\r\n   3   2   1 NaN\r\n   4   3   2   1\r\n   5   4   3   2 \r\n   6   5   4   3 ]\u003c/pre\u003e","function_template":"function y = goNtimes(x,n)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [1:6]';\r\nn = 3;\r\ny_correct = [1\tNaN\tNaN\tNaN\r\n2\t1\tNaN\tNaN\r\n3\t2\t1\tNaN\r\n4\t3\t2\t1\r\n5\t4\t3\t2\r\n6\t5\t4\t3];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [17;23;4;10;11];\r\nn = 4;\r\ny_correct = [17\tNaN\tNaN\tNaN\tNaN\r\n23\t17\tNaN\tNaN\tNaN\r\n4\t23\t17\tNaN\tNaN\r\n10\t4\t23\t17\tNaN\r\n11\t10\t4\t23\t17];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [35;3;31;8;30;4];\r\nn = 1;\r\ny_correct = [35\tNaN\r\n3\t35\r\n31\t3\r\n8\t31\r\n30\t8\r\n4\t30];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n\r\n%%\r\nx = [35;3;31;8;30;4];\r\nn = 2;\r\ny_correct = [35\tNaN\tNaN\r\n3\t35\tNaN\r\n31\t3\t35\r\n8\t31\t3\r\n30\t8\t31\r\n4\t30\t8];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))\r\n\r\n%%\r\nx = [30;38;46;5;13;21;22];\r\nn = 4;\r\ny_correct = [30\tNaN\tNaN\tNaN\tNaN\r\n38\t30\tNaN\tNaN\tNaN\r\n46\t38\t30\tNaN\tNaN\r\n5\t46\t38\t30\tNaN\r\n13\t5\t46\t38\t30\r\n21\t13\t5\t46\t38\r\n22\t21\t13\t5\t46];\r\nassert(isequalwithequalnans(goNtimes(x,n),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":4,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":48,"test_suite_updated_at":"2015-08-01T03:34:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-07-31T17:09:57.000Z","updated_at":"2026-03-02T14:38:21.000Z","published_at":"2015-07-31T18:07:11.000Z","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\u003eYou will be given a column vector (such as x = [1; 2; 3; 4; 5; 6]). If (n=3) you will return following;\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 NaN NaN NaN\\n   2   1 NaN NaN\\n   3   2   1 NaN\\n   4   3   2   1\\n   5   4   3   2 \\n   6   5   4   3 ]]]\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":802,"title":"Create a matrix from a cell","description":"In this problem , you must convert a cell into a matrix and pad each cell with NaN. \r\n\r\n\r\n*Example 1:* \r\n\r\nIf you have the input cell:\r\n\r\n  C = {[1 2 3],[]}\r\n\r\nthe output must be the matrix :\r\n\r\n    output = [  1     2     3\r\n               NaN   NaN   NaN]\r\n\r\n\r\n\r\n\r\n*Example 2:* \r\n\r\n  C = {[1 2 3],8,[],[15  3]}\r\n\r\nthe output must be the matrix :\r\n  \r\n       1     2     3\r\n       8   NaN   NaN\r\n     NaN   NaN   NaN\r\n      15     3   NaN\r\n\r\n\r\n\r\n\r\n\r\n","description_html":"\u003cp\u003eIn this problem , you must convert a cell into a matrix and pad each cell with NaN.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample 1:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIf you have the input cell:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eC = {[1 2 3],[]}\r\n\u003c/pre\u003e\u003cp\u003ethe output must be the matrix :\u003c/p\u003e\u003cpre\u003e    output = [  1     2     3\r\n               NaN   NaN   NaN]\u003c/pre\u003e\u003cp\u003e\u003cb\u003eExample 2:\u003c/b\u003e\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eC = {[1 2 3],8,[],[15  3]}\r\n\u003c/pre\u003e\u003cp\u003ethe output must be the matrix :\u003c/p\u003e\u003cpre\u003e       1     2     3\r\n       8   NaN   NaN\r\n     NaN   NaN   NaN\r\n      15     3   NaN\u003c/pre\u003e","function_template":"function output= your_fcn_name(C)\r\n  output = C;\r\nend","test_suite":"%% example 1\r\nC = {[1 2 3],[]};\r\n output = [  1     2     3\r\n               NaN   NaN   NaN];\r\nassert(isequalwithequalnans(your_fcn_name(C),output))\r\n\r\n%% example 2\r\nC = {[1 2 3],8,[],[15  3]};\r\ny_correct = [ 1     2     3\r\n     8   NaN   NaN\r\n   NaN   NaN   NaN\r\n    15     3   NaN];\r\n\r\nassert(isequalwithequalnans(your_fcn_name(C),y_correct))\r\n\r\n\r\n%%\r\ntcell = {ones(1,4), [1 2 3 4 5], 1:8, 1, [],0};\r\ny_correct = [   1     1     1     1   NaN   NaN   NaN   NaN\r\n     1     2     3     4     5   NaN   NaN   NaN\r\n     1     2     3     4     5     6     7     8\r\n     1   NaN   NaN   NaN   NaN   NaN   NaN   NaN\r\n   NaN   NaN   NaN   NaN   NaN   NaN   NaN   NaN\r\n     0   NaN   NaN   NaN   NaN   NaN   NaN   NaN];\r\nassert(isequalwithequalnans(your_fcn_name(tcell),y_correct))\r\n\r\n%%\r\nC = {[]}\r\nassert(isempty(your_fcn_name(C)))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":639,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":75,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-28T10:25:57.000Z","updated_at":"2026-03-06T12:32:57.000Z","published_at":"2012-06-28T10:25:57.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem , you must convert a cell into a matrix and pad each cell with NaN.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample 1:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf you have the input cell:\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[C = {[1 2 3],[]}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ethe output must be the 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[    output = [  1     2     3\\n               NaN   NaN   NaN]]]\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\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[C = {[1 2 3],8,[],[15  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\u003ethe output must be the 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[       1     2     3\\n       8   NaN   NaN\\n     NaN   NaN   NaN\\n      15     3   NaN]]\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":1216,"title":"Mean ignoring NaNs","description":"Define a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).","description_html":"\u003cp\u003eDefine a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).\u003c/p\u003e","function_template":"function y=average(x,d)\r\ny=0;\r\n","test_suite":"%%\r\nx=[1 5 9;2 6 10;3 nan 11;nan nan nan];\r\ny_correct=[2 5.5 10];\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=[5;6;7;nan];\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=x;\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n%%\r\nx=cat(3,[1 5 9;NaN 6 10;NaN 7 NaN;4 8 12],...\r\n [13 17 21;14 18 22;15 19 NaN;16 20 24]);\r\ny_correct=cat(3,[15 39 62]/6,[87 111 134]/6);\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=cat(3,[5;8;7;8],[17;18;17;20]);\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=[7 11 15;14 12 16;15 13 NaN;10 14 18];\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n%%\r\nx=zeros(2,1,0);\r\ny_correct=mean(x);\r\ny=average(x);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny=average(x,1);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=mean(x,2);\r\ny=average(x,2);\r\nassert(isequalwithequalnans(y,y_correct))\r\ny_correct=mean(x,3);\r\ny=average(x,3);\r\nassert(isequalwithequalnans(y,y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":245,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":52,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-01-19T20:54:55.000Z","updated_at":"2026-03-05T14:17:40.000Z","published_at":"2013-01-19T21:44:47.000Z","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\u003eDefine a function that behaves in the same way as mean(x) and mean(x,d) except that it ignores NaNs (unless all of the values being averaged are NaNs, in which case the result for those values should be NaN).\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":2529,"title":"Solving Quadratic Equations (Version 2)","description":"Before attempting this problem, solve version 1:  \u003chttps://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003e.\r\n\r\nIn this version, the discriminant can have any value.  Complete the function so if the discriminant is negative, the function returns values of NaN --- \"Not a Number\" --- for x1 and x2.  Otherwise, the function computes x1 and x2 as before using the formula\r\n\r\n\u003c\u003chttps://dl.dropboxusercontent.com/u/57773343/__IMAGES/QuadraticSolution1.gif\u003e\u003e\r\n","description_html":"\u003cp\u003eBefore attempting this problem, solve version 1:  \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\"\u003ehttps://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eIn this version, the discriminant can have any value.  Complete the function so if the discriminant is negative, the function returns values of NaN --- \"Not a Number\" --- for x1 and x2.  Otherwise, the function computes x1 and x2 as before using the formula\u003c/p\u003e\u003cimg src = \"https://dl.dropboxusercontent.com/u/57773343/__IMAGES/QuadraticSolution1.gif\"\u003e","function_template":"function [x1, x2] = SolveQuadraticEquation(a, b, c)\r\n\r\nend","test_suite":"%%\r\nqe_correct1_1 = -1;\r\nqe_correct1_2 = -2;\r\n[qe_result1_1, qe_result1_2] = SolveQuadraticEquation(1, 3, 2);\r\nassert( (abs(qe_result1_1 - qe_correct1_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result1_2 - qe_correct1_2) \u003c 0.0001) || ...\r\n        (abs(qe_result1_1 - qe_correct1_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result1_2 - qe_correct1_1) \u003c 0.0001) );\r\n%%\r\nqe_correct2_1 = 0.224745;\r\nqe_correct2_2 = -2.22474;\r\n[qe_result2_1, qe_result2_2] = SolveQuadraticEquation(2, 4, -1);\r\nassert( (abs(qe_result2_1 - qe_correct2_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result2_2 - qe_correct2_2) \u003c 0.0001) || ...\r\n        (abs(qe_result2_1 - qe_correct2_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result2_2 - qe_correct2_1) \u003c 0.0001) );\r\n%%\r\nqe_correct3_1 = -1;\r\nqe_correct3_2 = -1;\r\n[qe_result3_1, qe_result3_2] = SolveQuadraticEquation(2, 4, 2);\r\nassert( (abs(qe_result3_1 - qe_correct3_1) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result3_2 - qe_correct3_2) \u003c 0.0001) || ...\r\n        (abs(qe_result3_1 - qe_correct3_2) \u003c 0.0001  \u0026\u0026 ...\r\n         abs(qe_result3_2 - qe_correct3_1) \u003c 0.0001) );\r\n%%\r\n[qe_result4_1, qe_result4_2] = SolveQuadraticEquation(4, 4, 4);\r\nassert( isnan(qe_result4_1) \u0026\u0026 isnan(qe_result4_2) );\r\n%%\r\n[qe_result5_1, qe_result5_2] = SolveQuadraticEquation(9.1, 12, 4.1);\r\nassert( isnan(qe_result5_1) \u0026\u0026 isnan(qe_result5_2) );\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":24594,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":90,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-08-25T23:26:04.000Z","updated_at":"2026-03-16T12:13:52.000Z","published_at":"2014-08-25T23:42:27.000Z","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\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/media/image1.gif\"}],\"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\u003eBefore attempting this problem, solve version 1: \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=\\\"https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://www.mathworks.com/matlabcentral/cody/problems/2510-solving-quadratic-equations-version-1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;.\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\u003eIn this version, the discriminant can have any value. Complete the function so if the discriminant is negative, the function returns values of NaN --- \\\"Not a Number\\\" --- for x1 and x2. Otherwise, the function computes x1 and x2 as before using the formula\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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\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\"},{\"partUri\":\"/media/image1.gif\",\"contentType\":\"image/gif\",\"content\":\"data:image/gif;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAAGXRFWHRTb2Z0d2FyZQBBZG9iZSBJbWFnZVJlYWR5ccllPAAAAC1QTFRFeHh4k5OT9vb2gYGBnJycwMDAt7e3ioqK0tLS7e3t29vb5OTkycnJ////b29vvCMpXwAAAKZJREFUeNq8k0sWwyAIAEXzh3D/41ZrahASklXZ6cxTEAz8EOGFsDvxTyECM0RHgJIwOEIt6VFYX19BAd0kKe8vTpn0vY9uheXoQjGYrICtf9mg3Qgo+kt12fE4sxQwaGFQXCdJmmshaV4EnKYxmgMO/pvJVJ92NrwNbSpnrJafUz1kYbRcjP121ii4EKDVIPnVx+n4hdBzKyhuBM21YLgSLOePAAMAW0UziCh1I3kAAAAASUVORK5CYII=\"}]}"},{"id":49647,"title":"Original coordinate of the min element of a subset of elements","description":null,"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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; 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 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=\"\"\u003eFind the smallest element in a subset (marked by a logical matrix) of the given matrix, return its coordinate in the original matrix. Ignore NaN elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Row,Column] = MinCoordinateOfSubset(OriginalMatrix,SubsetMarker)\r\n  Row=0;\r\n  Column=0;\r\nend","test_suite":"%%\r\nOriginalMatrix= [   60    40   NaN   NaN   NaN   NaN\r\n    20   NaN   NaN    20    80   NaN\r\n   NaN   NaN   100    40   NaN   NaN\r\n   NaN    80   NaN   NaN   NaN   NaN\r\n    20   NaN   NaN   NaN   NaN    40];\r\nSubsetMarker=logical([   0   1   0   0   0   0\r\n   1   0   0   0   0   0\r\n   0   0   0   1   0   0\r\n   0   0   0   0   0   0\r\n   0   0   0   0   0   0]);\r\n[Row,Column]=MinCoordinateOfSubset(OriginalMatrix,SubsetMarker);\r\nassert(Row==2\u0026\u0026Column==1);\r\n%%\r\nOriginalMatrix=[    0.7948    0.9390       NaN    0.1707       NaN    0.4087\r\n    0.6443       NaN    0.4709    0.2277    0.9049    0.5949\r\n    0.3786    0.5502    0.2305       NaN       NaN       NaN\r\n    0.8116       NaN       NaN       NaN       NaN    0.6028\r\n       NaN       NaN       NaN    0.9234       NaN       NaN\r\n    0.3507    0.2077       NaN    0.4302    0.2581    0.2217];\r\nSubsetMarker=logical( [   1   1   0   0   0   0\r\n   1   1   0   1   0   0\r\n   0   0   0   0   1   0\r\n   1   0   1   1   0   1\r\n   1   1   1   1   0   1\r\n   1   0   0   0   0   0]);\r\n[Row,Column]=MinCoordinateOfSubset(OriginalMatrix,SubsetMarker);\r\nassert(Row==2\u0026\u0026Column==4);","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":362068,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":21,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-28T08:28:17.000Z","updated_at":"2026-01-20T14:03:31.000Z","published_at":"2020-12-28T08:28:17.000Z","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 smallest element in a subset (marked by a logical matrix) of the given matrix, return its coordinate in the original matrix. Ignore NaN elements.\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":42671,"title":"unique with nan","description":"input\r\n\r\n x = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8 -2  7 6  -2;\r\n      7  4  8 5  4];\r\n\r\noutput\r\n\r\n y_correct = \r\n [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8 -2  7 6;\r\n  7  4  8 5];","description_html":"\u003cp\u003einput\u003c/p\u003e\u003cpre\u003e x = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8 -2  7 6  -2;\r\n      7  4  8 5  4];\u003c/pre\u003e\u003cp\u003eoutput\u003c/p\u003e\u003cpre\u003e y_correct = \r\n [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8 -2  7 6;\r\n  7  4  8 5];\u003c/pre\u003e","function_template":"function y = unique_with_nan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8  -2 7 6  -2;\r\n      7  4  8 5  4];;\r\ny_correct =  [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8  -2 7 6;\r\n  7  4  8 5];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n\r\n%%\r\nx = [1 0 0 1;NaN 1 0 NaN;NaN 0 1 NaN;0 0 0 0];\r\ny_correct = [1 0 0;NaN 1 0;NaN 0 1;0 0 0];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n\r\n%%\r\nx = [1 0 1 1 1 1 0;0 1 1 1 1 1 0;0 0 NaN NaN NaN NaN 0;0 0 NaN NaN NaN NaN 0;0 0 NaN NaN NaN NaN 0;0 0 0 0 0 0 0;0 0 0 0 0 0 1];\r\ny_correct = [1 0 1 0;0 1 1 0;0 0 NaN 0;0 0 NaN 0;0 0 NaN 0;0 0 0 0;0 0 0 1];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))\r\n\r\n%%\r\nx = [2 NaN 3 5 NaN;\r\n      1 NaN 4 9 NaN;\r\n      8  pi 7 6  pi;\r\n      7  eps  8 5  eps];\r\ny_correct =  [2 NaN 3 5;\r\n  1 NaN 4 9;\r\n  8  pi 7 6;\r\n  7  eps  8 5];\r\nassert(isequalwithequalnans(unique_with_nan(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":6,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":"2015-11-03T12:04:01.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-23T20:20:54.000Z","updated_at":"2025-12-07T19:56:45.000Z","published_at":"2015-10-23T20:20:54.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput\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 = [2 NaN 3 5 NaN;\\n      1 NaN 4 9 NaN;\\n      8 -2  7 6  -2;\\n      7  4  8 5  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\u003eoutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y_correct = \\n [2 NaN 3 5;\\n  1 NaN 4 9;\\n  8 -2  7 6;\\n  7  4  8 5];]]\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":42669,"title":"replace nan values iteratively.","description":"replace nan values with the average of two neighbour non-nan value iteratively as follow;\r\n\r\n x = [2; 4; 6; nan; nan; nan; 10];\r\n x = [2; 4; 6;   8; nan; nan; 10];\r\n x = [2; 4; 6;   8;   9; nan; 10];\r\n x = [2; 4; 6;   8;   9; 9.5; 10];   \r\n","description_html":"\u003cp\u003ereplace nan values with the average of two neighbour non-nan value iteratively as follow;\u003c/p\u003e\u003cpre\u003e x = [2; 4; 6; nan; nan; nan; 10];\r\n x = [2; 4; 6;   8; nan; nan; 10];\r\n x = [2; 4; 6;   8;   9; nan; 10];\r\n x = [2; 4; 6;   8;   9; 9.5; 10];   \u003c/pre\u003e","function_template":"function y = replaceNaN(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [2; 4; 6; nan; nan; nan; 10];\r\ny_correct = [2; 4; 6;   8;   9; 9.5; 10]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [1; 2; 3; 4; nan; 6];\r\ny_correct = [1; 2; 3; 4; 5; 6];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [360; nan; nan; nan; nan; 120];\r\ny_correct = [360; 240; 180; 150; 135; 120];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; 4; 6; nan; nan; nan; 10; 360; nan; nan; nan; nan; 120];\r\ny_correct = [2; 4; 6;   8;   9; 9.5; 10; 360; 240; 180; 150; 135; 120]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; 4; 10; nan; 12; -20; nan; -40];\r\ny_correct = [2; 3; 4; 10; 11; 12; -20; -30; -40]; \r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; nan; 6];\r\ny_correct = [2; 4; 5; 6];\r\nassert(isequal(replaceNaN(x),y_correct))\r\n\r\n%%\r\nx = [2; nan; 8; 10; nan; 12; -20; nan; -40];\r\ny_correct = [2; 5; 8; 10; 11; 12; -20; -30; -40]; \r\nassert(isequal(replaceNaN(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":29,"test_suite_updated_at":"2015-10-21T09:57:01.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-21T08:15:04.000Z","updated_at":"2025-12-30T12:39:26.000Z","published_at":"2015-10-21T08:15:04.000Z","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\u003ereplace nan values with the average of two neighbour non-nan value iteratively as follow;\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 = [2; 4; 6; nan; nan; nan; 10];\\n x = [2; 4; 6;   8; nan; nan; 10];\\n x = [2; 4; 6;   8;   9; nan; 10];\\n x = [2; 4; 6;   8;   9; 9.5; 10];]]\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":3108,"title":"Don't Try, give up and return NaN.","description":"This is another version of \u003chttp://www.mathworks.com/matlabcentral/cody/problems/3107-try-and-catch-simple-example problem 3107.\u003e\r\n\r\nThe goal is to return values of an array _A_ given index _N_, but return _NaN_ for incorrect index.\r\n\r\nExample:\r\n\r\n    \u003e\u003e A = 1:5;\r\n    \u003e\u003e N = [-1 2 6];\r\n    \u003e\u003e values = giveup(A, N)\r\n    values =\r\n       NaN     2     NaN\r\n    \r\n\r\n","description_html":"\u003cp\u003eThis is another version of \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/3107-try-and-catch-simple-example\"\u003eproblem 3107.\u003c/a\u003e\u003c/p\u003e\u003cp\u003eThe goal is to return values of an array \u003ci\u003eA\u003c/i\u003e given index \u003ci\u003eN\u003c/i\u003e, but return \u003ci\u003eNaN\u003c/i\u003e for incorrect index.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e    \u0026gt;\u0026gt; A = 1:5;\r\n    \u0026gt;\u0026gt; N = [-1 2 6];\r\n    \u0026gt;\u0026gt; values = giveup(A, N)\r\n    values =\r\n       NaN     2     NaN\u003c/pre\u003e","function_template":"function values = giveup(A,N)\r\n  values = A(N);\r\nend","test_suite":"A = 1:5;\r\nN = [-1 2 6];\r\nvalues = [NaN 2 NaN];\r\nassert(isequaln(giveup(A,N),values))\r\n%%\r\nA = 10:-2:2;\r\nN = 5:-1:1;\r\ny_correct = 2:2:10;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [1 2 3 4 10];\r\nN = 5;\r\ny_correct = 10;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = 10:-2:2;\r\nN = -1;\r\ny_correct = NaN;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [4 5 6];\r\nN = [6 2];\r\ny_correct = [NaN 5];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = 4:randi([20 30]) ;\r\nN = randi(length(A)+20,1,10);\r\nK = N+3 ; K(K\u003emax(A)) = NaN; \r\ny_correct = K;\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = [-23 4 56 0 44 11];\r\nN = [7:-1.5:-2];\r\ny_correct = [NaN NaN 0 NaN -23 NaN NaN];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(3);\r\nN = magic(4);\r\ny_correct = [\r\n   NaN     3     4   NaN\r\n     5   NaN   NaN     7\r\n     2     6     9   NaN\r\n     1   NaN   NaN     8];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(3);\r\nN = magic(4)-1;\r\ny_correct = [\r\n   NaN     8     3   NaN\r\n     1   NaN     2     6\r\n     7     9     5   NaN\r\n     4   NaN   NaN   NaN];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n%%\r\nA = magic(4);\r\nN = magic(3)-1;\r\ny_correct = [\r\n   7   NaN     2\r\n   5     4    11\r\n   9    14    16];\r\nassert(isequaln(giveup(A,N),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":14358,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":"2015-03-23T11:48:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-03-23T11:29:25.000Z","updated_at":"2025-09-05T19:49:46.000Z","published_at":"2015-03-23T11:29:25.000Z","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\u003eThis is another version of\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/matlabcentral/cody/problems/3107-try-and-catch-simple-example\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 3107.\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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe goal is to return values of an array\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\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e given index\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, but return\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\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e for incorrect index.\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:\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\u003e A = 1:5;\\n    \u003e\u003e N = [-1 2 6];\\n    \u003e\u003e values = giveup(A, N)\\n    values =\\n       NaN     2     NaN]]\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":61140,"title":"Calculating Swimming Stroke Index (SI)","description":"In competitive swimming, speed () is only one part of the equation. High efficiency is defined by moving fast while maintaining a high Distance Per Stroke (DPS). The Stroke Index (SI) is a common metric used by coaches to quantify this efficiency.\r\nYour task is to calculate the Stroke Index based on a single pool length. However, you must account for the glide distance after the wall push-off, as no strokes are taken during that phase.\r\n\r\nWhere:\r\n is the velocity over the entire length (m/s).\r\nDPS is the distance covered per stroke during the swimming phase only.\r\nConstraint:If the glide distance (pushOff) is greater than or equal to the pool length (poolLength), the scenario is physically impossible for this calculation. In such cases, the function must return NaN.\r\nInputs\r\npoolLength: Pool length in meters (e.g., 50).\r\ntime: Time taken to complete the length in seconds.\r\nstrokeCount: Total number of individual arm strokes taken.\r\npushOff: Glide distance (meters) covered before the first stroke begins.\r\nOutput\r\nSI: The Stroke Index rounded to two decimal place","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 483.562px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408px 241.781px; transform-origin: 408px 241.781px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn competitive swimming, speed (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDistance Per Stroke (DPS)\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. 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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eStroke Index (SI)\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a common metric used by coaches to quantify this efficiency.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYour task is to calculate the Stroke Index based on a single pool length. However, you must account for 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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eglide distance\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e after the wall push-off, as no strokes are taken during that phase.\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"82\" height=\"18\" alt=\"SI = v*DPS\" style=\"width: 82px; height: 18px;\"\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhere:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.875px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 20.4375px; transform-origin: 391px 20.4375px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the velocity over the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eentire\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e length (\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003em/s\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.2188px; text-align: left; transform-origin: 363px 10.2188px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eDPS\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance covered per stroke during the \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eswimming phase only\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 43px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 21.5px; text-align: left; transform-origin: 384px 21.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eConstraint:\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the glide distance (\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is greater than or equal to the pool length (\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; font-weight: 700; \"\u003eNaN\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eInputs\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 83.75px; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 41.875px; transform-origin: 391px 41.875px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epoolLength\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Pool length in meters (e.g., 50).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003etime\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Time taken to complete the length in seconds.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003estrokeCount\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Total number of individual arm strokes taken.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.9375px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003epushOff\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eOutput\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 20.9375px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 391px 10.4688px; transform-origin: 391px 10.4688px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 363px 10.4688px; text-align: left; transform-origin: 363px 10.4688px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eSI\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e: The Stroke Index rounded to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003etwo decimal place\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function SI = calculateStrokeIndex(poolLength, time, strokeCount, pushOff)\r\n  SI = 1;\r\nend","test_suite":"%% Test Case 1:\r\nassert(isequal(calculateStrokeIndex(50, 35, 30, 5), 2.14));\r\n\r\n%% Test Case 2: Short Course Sprint\r\nassert(isequal(calculateStrokeIndex(25, 15, 12, 6), 2.64));\r\n\r\n%% Test Case 3:\r\nresult = calculateStrokeIndex(25, 10, 15, 30);\r\nassert(isnan(result), 'Function should return NaN when glide distance exceeds pool length');\r\n\r\n%% Test Case 4:\r\nresult = calculateStrokeIndex(50, 40, 20, 50);\r\nassert(isnan(result));\r\n\r\n%% Test Case 5:\r\nfor i = 1:5\r\n    L_rand = 50;\r\n    T_rand = 30 + rand*20;\r\n    S_rand = 20 + randi(20);\r\n    G_rand = rand*10;\r\n    \r\n    v = L_rand / T_rand;\r\n    DPS = (L_rand - G_rand) / S_rand;\r\n    expected = round(v * DPS, 2);\r\n    \r\n    assert(abs(calculateStrokeIndex(L_rand, T_rand, S_rand, G_rand) - expected) \u003c 1e-8);\r\nend","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4996329,"edited_by":4996329,"edited_at":"2025-12-18T10:10:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-18T09:56:54.000Z","updated_at":"2026-04-10T15:35:54.000Z","published_at":"2025-12-18T10:03:46.000Z","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\u003eIn competitive swimming, speed (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is only one part of the equation. High efficiency is defined by moving fast while maintaining a high \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDistance Per Stroke (DPS)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. The \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eStroke Index (SI)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is a common metric used by coaches to quantify this efficiency.\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 task is to calculate the Stroke Index based on a single pool length. However, you must account for the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eglide distance\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e after the wall push-off, as no strokes are taken during that phase.\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=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"SI = v*DPS\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$$SI = v \\\\cdot DPS$$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\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\u003eWhere:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$v$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the velocity over the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eentire\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003em/s\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=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDPS\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance covered per stroke during the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eswimming phase only\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=\\\"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\u003eConstraint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eIf the glide distance (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e) is greater than or equal to the pool length (\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e), the scenario is physically impossible for this calculation. In such cases, the function must return \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\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=\\\"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\u003eInputs\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epoolLength\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Pool length in meters (e.g., 50).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etime\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Time taken to complete the length in seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estrokeCount\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Total number of individual arm strokes taken.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003epushOff\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: Glide distance (meters) covered before the first stroke begins.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSI\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e: The Stroke Index rounded to \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003etwo decimal place\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":56483,"title":"Cricket - Average Partnership Contribution","description":"The (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-n matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for n innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be NaNs for the partnerships that did not occur. (This means the total team score is the last non-NaN value in each column.) The average across the n sample innings should ignore NaNs.\r\nIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\r\n\r\nx = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\r\nx =\r\n     0    50\r\n    20    80\r\n    30   120\r\n    70   130\r\n    70   140\r\n    80   180\r\n   100   180\r\n   110   200\r\n   140   NaN\r\n   150   NaN\r\n\r\navg = partnershipcontrib(x)\r\navg =\r\n    0.1250\r\n    0.1417\r\n    0.1333\r\n    0.1583\r\n    0.0250\r\n    0.1333\r\n    0.0667\r\n    0.0833\r\n    0.2000\r\n    0.0667","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: 1289.83px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 644.917px; transform-origin: 407px 644.917px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 127.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 63.75px; text-align: left; transform-origin: 384px 63.75px; 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: 365px 8px; transform-origin: 365px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 256.5px 8px; transform-origin: 256.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 257px 8px; transform-origin: 257px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 28px 8px; transform-origin: 28px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003es for the partnerships that did not occur. (This means the total team score is the last non-\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 117.5px 8px; transform-origin: 117.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e value in each column.) The average across 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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003en\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: 96px 8px; transform-origin: 96px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e sample innings should ignore \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 12px 8px; transform-origin: 12px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eNaN\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: 5.5px 8px; transform-origin: 5.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003es.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 369.5px 8px; transform-origin: 369.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 581.5px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 290.75px; text-align: left; transform-origin: 384px 290.75px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 969px;height: 576px\" 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alt=\"A two-column matrix of nondecreasing values, with the last non-NaN value highlighted in each column. This is converted to another 2-column matrix of the differences from row to row. The total score is shown below, being the highlighted values from before. The matrix is again converted to a new 2-column matrix where each value is the proportion of the total (given by the total score values from before). Finally, a column vector is calculated from the matrix by averaging across the columns.\" data-image-state=\"image-loaded\" width=\"969\" height=\"576\"\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 510.833px; 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 255.417px; transform-origin: 404px 255.417px; 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: 304px 8.5px; tab-size: 4; transform-origin: 304px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex =\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e     0    50\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    20    80\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    30   120\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    70   130\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    70   140\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    80   180\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   100   180\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   110   200\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   140   NaN\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: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e   150   NaN\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: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eavg = partnershipcontrib(x)\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: 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; \"\u003eavg =\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    0.1250\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    0.1417\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    0.1333\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    0.1583\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    0.0250\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    0.1333\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    0.0667\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    0.0833\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    0.2000\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    0.0667\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function avg = partnershipcontrib(s)\r\n\r\navg = mean(s);\r\n\r\nend","test_suite":"%% 12 innings\r\nx = [93 10 9 14 5 46 165 7 42 14 8 88;164 44 10 31 58 55 169 24 72 18 9 98;227 53 10 34 100 144 173 31 145 63 10 228;NaN 58 25 63 NaN 178 241 35 158 69 32 356;NaN 67 143 178 NaN 195 497 58 180 84 45 372;NaN 67 151 342 NaN 277 592 69 188 88 60 379;NaN 88 224 370 NaN 311 592 75 206 151 102 476;NaN 90 NaN 376 NaN 319 643 131 226 185 102 502;NaN 93 NaN 396 NaN 325 668 131 NaN 219 105 522;NaN 101 NaN 431 NaN 326 707 136 NaN 253 109 554];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.127561166808451;0.12977999987294;0.155703562754948;0.0927761241656379;0.177085480116408;0.108446996646594;0.163626020105591;0.0902197552243652;0.0409854550106841;0.0605319499146062])) \u003c 1e-5 )\r\n%% 15 innings\r\nx = [0 36 0 16 40 2 107 49 0 58 15 0 31 35 15;47 149 13 35 43 14 115 92 0 136 106 6 62 51 35;68 204 255 96 102 23 197 183 49 136 133 45 141 72 50;71 237 382 300 114 29 211 199 55 173 137 71 142 78 102;118 308 NaN 507 132 85 217 304 62 173 204 79 162 78 133;132 319 NaN 542 251 96 238 321 67 173 248 87 181 157 150;172 NaN NaN 566 251 143 276 350 67 208 248 99 182 225 183;NaN NaN NaN 572 266 166 NaN 414 71 237 264 117 194 252 197;NaN NaN NaN 572 275 171 NaN 433 75 239 277 119 195 282 197;NaN NaN NaN 606 282 213 NaN 436 90 248 278 129 221 282 250];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.0935178799346019;0.123522199506716;0.214786109140686;0.107581946541405;0.144429580185992;0.105164272050944;0.100678940349023;0.0802158893817775;0.0295136677949011;0.0817011534864528])) \u003c 1e-5 )\r\n%% 10 innings\r\nx = [2 61 9 66 70 24 30 34 2 11;144 176 174 66 126 83 46 82 27 16;NaN 225 259 66 149 159 90 122 74 42;NaN 228 277 153 184 193 100 156 80 43;NaN 229 279 NaN 189 198 133 282 81 51;NaN 261 480 NaN 194 284 163 336 81 82;NaN 263 508 NaN 219 286 197 359 93 124;NaN 263 NaN NaN 220 299 214 466 98 159;NaN 269 NaN NaN 236 300 238 468 105 165;NaN 276 NaN NaN 239 313 239 526 112 193];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.131857056901008;0.25577103343828;0.166489867398518;0.115025818107455;0.0590566909925436;0.149512322121404;0.0855127326608772;0.0780370592130176;0.0413840570886391;0.0573537352490243])) \u003c 1e-5 )\r\n%% 17 innings\r\nx = [47 132 4 29 4 33 14 1 185 16 80 10 39 96 22 49 44;48 175 8 30 11 86 14 20 189 28 139 44 53 NaN 33 113 101;49 260 15 31 13 139 44 131 289 244 142 51 124 NaN NaN 179 103;60 277 70 77 13 161 187 143 321 331 146 55 124 NaN NaN 201 134;90 355 85 88 15 209 200 171 322 339 149 85 124 NaN NaN NaN 142;179 444 114 180 18 294 204 210 347 345 180 106 126 NaN NaN NaN 142;237 510 119 199 21 311 236 255 354 346 181 119 130 NaN NaN NaN 158;248 520 124 205 21 410 320 293 361 350 182 155 156 NaN NaN NaN 159;252 NaN 124 225 21 442 337 301 381 363 227 159 165 NaN NaN NaN 185;257 NaN 124 246 47 NaN 337 312 382 365 233 167 168 NaN NaN NaN 190];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.240994776523359;0.124242738355593;0.166998542784811;0.123630511079241;0.0693601120017177;0.133635916354558;0.0730614634765755;0.0807820974677455;0.0569861900798804;0.0682662046838182])) \u003c 1e-5 )\r\n%% 16 innings\r\nx = [38 32 56 7 87 67 6 0 42 53 8 78 28 0 19 6;140 NaN 75 51 87 100 320 21 55 119 196 100 28 63 47 48;168 NaN 92 148 87 110 329 130 55 122 218 101 32 89 101 48;213 NaN 136 283 219 115 337 176 65 167 318 117 43 196 121 85;266 NaN 150 306 252 169 339 182 86 226 357 373 50 215 121 89;290 NaN 160 347 331 NaN 379 230 106 254 415 439 61 246 130 189;NaN NaN 206 375 333 NaN 418 261 202 301 424 452 64 345 165 197;NaN NaN 206 384 333 NaN 418 273 210 314 455 494 69 353 172 239;NaN NaN 240 394 362 NaN 446 305 237 388 466 NaN 85 353 173 252;NaN NaN 248 403 NaN NaN 453 305 286 419 466 NaN 89 365 181 254];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.182240310458828;0.175892478952746;0.0875416554422805;0.152836201456442;0.112910555705271;0.12396440347931;0.113191687593507;0.0426419111443832;0.0783210269004195;0.0404773549272449])) \u003c 1e-5 )\r\n%% 6 innings\r\nx = [132 23 8 4 1 5;175 52 8 4 10 18;260 68 63 4 33 18;277 80 74 36 36 64;355 80 177 125 43 71;444 112 208 147 43 108;510 113 216 208 43 109;520 148 231 240 52 119;NaN 149 251 253 82 166;NaN 155 265 253 82 167];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.0817279080428618;0.0762315818040129;0.125787053267087;0.0983562962636804;0.169623320455451;0.13384999984987;0.0684430187318784;0.0996265908248745;0.156119498902202;0.0195055780101392])) \u003c 1e-5 )\r\n%% 2 innings\r\nx = [0 79;23 144;40 167;47 177;53 215;68 249;77 249;108 261;110 284;132 320];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.1234375;0.188683712121212;0.100331439393939;0.0421401515151515;0.0821022727272727;0.109943181818182;0.0340909090909091;0.136174242424242;0.0435132575757576;0.139583333333333])) \u003c 1e-5 )\r\n%% 7 innings\r\nx = [82 77 39 17 25 16 9;100 77 146 28 88 57 35;146 91 262 102 119 242 35;163 98 279 114 286 242 39;247 103 305 168 362 277 47;503 173 307 172 368 299 50;557 206 364 194 489 304 59;559 220 605 258 493 309 73;570 267 615 277 554 314 83;NaN NaN 631 293 556 315 86];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.107497876929982;0.11206962590314;0.173226871930385;0.0672585891886349;0.104632115131127;0.120518985511512;0.103128650710132;0.120309237160835;0.0739838287054595;0.0243239063603082])) \u003c 1e-5 )\r\n%% Only one partnership (non-NaN)\r\nx = [51 135 80 56 0 73 12 95 25 158 19 13 10 164 3 1 49 5;99 162 NaN 75 35 146 12 117 115 249 53 63 20 208 34 34 90 39;100 165 NaN 92 73 161 49 117 163 267 80 142 21 218 54 34 99 90;NaN 225 NaN 136 73 351 76 311 NaN 310 92 170 51 330 115 59 128 113;NaN 241 NaN 150 74 389 205 313 NaN 321 143 188 94 364 115 90 152 119;NaN 281 NaN 160 84 394 224 315 NaN 326 170 196 100 388 137 127 208 170;NaN 288 NaN 206 123 422 233 376 NaN 370 178 196 100 396 185 149 241 203;NaN 294 NaN 206 181 449 245 434 NaN 447 178 205 100 408 210 173 267 239;NaN 312 NaN 240 193 475 258 451 NaN 460 226 205 104 424 210 200 283 270;NaN 343 NaN 248 202 481 270 460 NaN NaN 226 231 104 424 210 200 426 271];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.211390656192859;0.168194620890675;0.0927330577536002;0.177194557307618;0.114920288442186;0.0786823138140911;0.0873894127938098;0.0799241281835184;0.0661291359874339;0.0496857216889986])) \u003c 1e-5 )\r\n%% No NaNs at all\r\nx = [2 114;9 116;18 195;20 266;50 294;206 316;215 326;229 340;242 390;247 422];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.139119673043345;0.0165397087322755;0.111820519216379;0.0881718057447666;0.0939041003895082;0.341855824395111;0.0300669647140089;0.0449277586967784;0.0855574956348217;0.0480361494330065])) \u003c 1e-5 )\r\n%% Only one innings - no NaNs\r\nx = [20;35;39;111;123;123;128;133;149;153];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.130718954248366;0.0980392156862745;0.0261437908496732;0.470588235294118;0.0784313725490196;0;0.0326797385620915;0.0326797385620915;0.104575163398693;0.0261437908496732])) \u003c 1e-5 )\r\n%% Only one innings - with NaNs\r\nx = [107;152;204;250;NaN;NaN;NaN;NaN;NaN;NaN];\r\navg = partnershipcontrib(x);\r\nassert( max(abs(avg - [0.428;0.18;0.208;0.184;NaN;NaN;NaN;NaN;NaN;NaN])) \u003c 1e-5 )","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":287,"edited_by":287,"edited_at":"2022-11-08T20:18:04.000Z","deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-11-07T18:20:52.000Z","updated_at":"2025-12-06T12:44:27.000Z","published_at":"2022-11-08T15:10:27.000Z","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\u003eThe (infamous) Duckworth-Lewis method uses statistical models of how much each wicket partnership is worth to an innings (on average). Given an 10-by-\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 matrix representing the score at the end of each partnership (either by the fall of a wicket or the innings ending) for \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 innings, return a 10-element vector that gives the average proportion of the total score each wicket contributes. For innings that are completed without all 10 wickets falling, there will be \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003es for the partnerships that did not occur. (This means the total team score is the last non-\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e value in each column.) The average across the \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 sample innings should ignore \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003es.\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\u003eIf the total innings score is 200 and the first wicket fell at a score of 40, the first wicket was worth 0.2 of the total. If the second wicket fell at 60, it was worth 20 runs = 0.1 of the total. And so on.\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=\\\"576\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"969\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"A two-column matrix of nondecreasing values, with the last non-NaN value highlighted in each column. This is converted to another 2-column matrix of the differences from row to row. The total score is shown below, being the highlighted values from before. The matrix is again converted to a new 2-column matrix where each value is the proportion of the total (given by the total score values from before). Finally, a column vector is calculated from the matrix by averaging across the columns.\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\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 = [0 50;20 80;30 120;70 130;70 140;80 180;100 180;110 200;140 NaN;150 NaN]\\nx =\\n     0    50\\n    20    80\\n    30   120\\n    70   130\\n    70   140\\n    80   180\\n   100   180\\n   110   200\\n   140   NaN\\n   150   NaN\\n\\navg = partnershipcontrib(x)\\navg =\\n    0.1250\\n    0.1417\\n    0.1333\\n    0.1583\\n    0.0250\\n    0.1333\\n    0.0667\\n    0.0833\\n    0.2000\\n    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S+OmY8f2G9Qbzjkekmqu5tal3XQXDm+KIDavjUX+XEbg44fZPowPGi8V1/Hy8bh1nhQqcsGgBqiH6+z9n2NeNtfzYQf6cqeXXko8uGBspl5vPknj9p4AnocUJh37DQiwktdKVPm8l7jylu7LtsBpY907202wTUcArwl4nOIJtN5BwpcHAmw3XXVCEXicphIx7dZRxr2qpcceEQXWVfmrIcw0iue1q0mcjeO3AIV7GlZR+AxxF9Ubx1Jg70o8esw1+2d8iB1W0KvrW/5uqYy/8vrC1y8mVT1dJwpql1ZQfBnTRd3Y+8hfzMtcXa0ux2WuuIA/f40uN73kf1n6+J/ZWJ7QDtRC9f/Od7/ZFEYefysmfhZ0L+OYVr+f+3xtFV9y4rjnzcNTOfdwoThxtMHPx7f2QOBLsdu1mh0IsJ2Qx3kn9pTxA59ee4RCtH9hPSsmfqnfxjvsD+CofWAJ/AC0P/4DsJ+ysarrs2zUWicthYj8r2xJq2yv+f+vo+fCkXEI5hJNc9Ldqorffsw+e5ac4+AI9DBvFR+sq+k0iQnae9E9GfV0/Yu0ch34iOuW++5RSHvQefW5MEaRlIWq87rNaFDsINHBPmibPB1xRw4muJ+vGcdQ7YX2P51bXvww8x7q95UMfS+GsdZrJ/Iu75r63ozFgAaGfviinpFBCI7jf55kw8tLplyZGVZc95/yFOxOixS+hkT2Dr89pwt2+b9IrhJJ4wb8qGHAoczpXYtu/krum6ex+Dlj3RNOsF9iGVkAUfxvWRfwgPiyvn0oij68pOxXVzkagYNtaju9w69mO5xXLGRAyPM2lUSpLzUxjJdU+LNsfGS7T5zlURjm1lp2IfgKexuqJsL8S9x5G9+oFsr0RXiM03Py7nG3t/W5xwCgGxJzuvSyJEPFF2T2yXT3OHUutyB+EWzjr5WELZvfj15UzM7ye+mv3rll2B3e7dS9yvcq5XjP9Yu3LwgPVCjAWAZnaOmLLztK3dwf0OdYnNwYuOvB3eR41dpFF3b/69hZ19w3XBbOtfTTiRzdA092D7/evuQ2O51n7fsmdhm7oC24MSsuCzkIF/cJ4qWtKIFteNOw+RRPYFkrChnXGIofvu7S613VS75UIaRtS2SrTZhZt9sNl9c0256IRmiuOFAR5EHPAn55K9pxlXdp7n4ejO0Q+q843N23Y74zlyYDqkXmVGdu5v2dba6CDcxWEKOFpc9qXvYXo/6eCQHZHthWv573mY746dLrQGd9kGgGqO7n1kn/DJrsQxdy67a19y5Il4eH9siwfHM+L+7eJry9Olk5bFXiz712DydQor27nHA+t+2Z6RO+9bLntmTlfe+n8+APC3uTzw5cSCM20u3uK6cd8+PmznK2FjPbpLrfcx9HTGdq2ke6fcfCINI1r3tGiz9eB0/00Rb823Ptn2AXgQZ4EbifsPS1irc5xax5ASG68h5uRb53Zbw+T+u2PnQ9tJO8eT7crW606rg3Afh4Ly7rWtoTkdE99xDlhPrRo3W0zPTiHphWI30lMAoMyWXyXsY+7qrImXbT67i8YlR56Ih/cHc5Eitl0vvl47ubTsXy9Q6oUcS8OSsJ2bmXpkc0b27S+27Amkt1gflekLPgoZ91mvy5ELDhProfVzbi2uG9vuA0QpbGxHd9fexdDkjO1iskO7gJCGEa17SrNN9xbuvx7adlWENoDnEEfweWJdh7xsC7Lz6DXRmaJ/recmviX7V0eMd1ei1Hqr9NB6VhoiGlubHYQ72afSq8nX0Ky9hN8lABfbrC98Ddal5nJECeFygJQToJWsSj5mULJTc7ItRdsOFv1+O7y/xxoNZHtFdq/7/yPbaVfis8hmsRfxmGwmrOeebxNvst8vfd/fZtkzUYp8unUA/ihx4MtmLcVwkqQRLa4b2+4jUfFu69FdSrrF0GPQnFmvFk9QLiCkYUTrntIsMcGO9GnWPTWhDeAxrCNbtjf0oR315WFvdKa4sz7fKLjhGiJke8962now/r51Mdytres7CPeyvZs1usdXoM4lQjxNbxOP/ke2t1WR/AtPj6xnpdMOABRZw/eB9RcjhKKvr5fYfLPgyAHNY7OhIl5eNgvLZfEa8RKlXlhBYz03aSD799c83Tew7JlQEtfiMwD8WaKTy2Yt2dgwE49Gj1xdN3E92b9zXS0MlMLGdnR38TUAFsPjuXtpYEjDiNa9tNnaYTWYrUdle9tRYR+A53COBBuJEyzIzoPjyK7VvWS7It+It1fCQDykZQNr3+It8g4akGNbh2SzooNwM9urjCaXTf1VCtIk0yYZuvm1oHWYyeYBOVTqCAAorBme8PPz9Z0mW6Ugv7nxNjkVHDkQD+8vF2+RzHAnlRzP1VI5aRojVLEXcigXNfLnyv79/ZXJaNmjdzPNnAE+gWIcySNnZU47pxEtrqtFomLYWI/uguQaQ2X7hBw8dy8bZXdhROte2iwWk/bxZ8c5suafT/YTleCRyPjV/FCOnLwuusJuxOe8RXOKU75xPnWHHNE99Bw/ytlBvMs5nlR0EO5mk8nHbf1VLsTXnXtL8XgcuvGaSns5ot5NLlPqCQAoRBcs563SKOPH8RqbAxYcORAP76esGPxlc+PUON5s2TpxPFbsRbzOPz9pujoRz02DinR0f1Fl17JHy4Vn5GjGPgB/kuh066fHqohn5bwlHhdfa3FdLRIVw8Z6dBcwjf5lupdG3Lrupc2W7XwMl8PxhHjRqtAG8BRk+KrjNw76U94gO3cOJjvWa0Tvlc0jx2Px/qljxYukRwLnvsXrHLx+Q47G1g0dhNtZlyCXVx0XMEvpdXzdsplwjtfxFukwLy2YxHFCcAdoJMbYokouep92OO/IM/Hw/qbZWHFqXIwpckyaFnsRD058KdNRPJw+snRgf1Fl17InG/qsyAjwByl6ZBbLWU5pRIvrxrb7SFTuZDy6ixnlHDjXvTTo1HUvaRYbZW6f2C/fPu0AwGNYRm85NTi6Uuq60VeSHbJ5RI6JK+ebFi+SdFy2cm54ulhDB+F+4utY3p5s5F78jJyRj7rL8fUiZ9W8EUfzPz8ackzaAkAl0bGKcdRqJIc3t8078kw8vL9e1olPjWWrGAjktuVexMaBVCfnz1WCmrJr2ZMzQJ3ZAf4YMuzbpmrFvY4sx+NVW1xXi0TlsBGP7rLt6MyymSCH5XrKBYS67iXN1EZ7Yv9OHaixD8BTiMNcH77x6PpT+Auyd/Vd2dyuITtq8o24uWztkQM5xzoGEGvV6xRuZKumg/AGxOTL65F/F+1vtjm98Pz4iA2LSFsAqCQ6Vpqz7Ti5aYIc3tzWCPTx8P6m2Qzt1Fi2ishtjV7EKWThlGNqXVxQOqrsWvZkzZpPlQH+LpfSNvOcY3xqcV2tbTlsxKO7eCG3z+XAp9sqFxDqupc0s6Lz2YDqRWfSDgA8hWXwmhyHfXQe8Y3T5oTsKCKt8+6zHMhElM0jly0rNzj5u2wVyd0Y/JFRMMd3cwEzIG3y7yi+cLlKfnzEWxcp9gUAEk4eqGNlT3J883Mj0GvBI3uPY+O4VUQuYvTiHFQOJtC6uKB0VNm17MmbVY4zfcEnEcNNNpRoyDm1aUSL62pty2FDOSq3zz5T7N6ylb98XfeSZsfLa0gDOUO96IwSxwCeQXQDi1MYkb3iPbKx+VJ0liLiMFn3iRfJRbB4fNmy/PnYuqWD8Abi6wsvO78guWG3ObUwVznLlPoCACnRp4u+Y2VPcpFtEjA8XzucvcexcdwqIhcxepHMMPt7589VOqrsWvZkZzo78wf4g8i4zztGiunGmRBR47pa2/L94tGdxkzC34lj2qtcQKjrXtJMiT4nji3yz2dfCWBQZPDaHB0vOue8N26kmUwRcZis++Q9TpDjy8YxXCgcjrd0EN7Afkkk/juN9Rt2m1OL/AlVLlDqCwCkHCaJHFb2JBfZ5hbD87XD2XscG8etInIRoxeB+PjC1jJ/rtJRZdeyx5zpUMnwUcSJPBtLUmw31kNEjetqbcv3i0d3GW8S/k4c017lAkJd95JmSvQ5cWyRfz77SgBjcprJC5z8VPbO3ikOsJu2o7MUEYfJuk/e4wQ5vmwcw4XC4XhLB+ENxGWLMMzM5ZEJu82pRf6EOHyLlPoCACkxJBd9x8qekjTR8HztcPYex8Zxq4hcxOjFwnF2Xeex/LlKR5Vdyx5zpkMlw0exuptsV2C7sR4ialxXa1u+Xzy6y3iT8HciPvOypVxAqOte0kyJPieOLfLPZ18JYExk7NYgZwjROyd3iP/ceXJ0liLiMFn3yXucIMeXjWO4UDgcb+kgOPH9+/WTez9x2SIMov2/c9htTgMiv+ZC/Aa4geiB2WXOgBW3xTs3P8878ox2OOvhx8ZxKzvh7DB6IXzHp5uRnYVzlY4qu5Y92VvXdQ3gryG+0jCVR1+pTSNaXFdrW/bNeHQXgOT22Sc63la5gFDXvaRZtKhsKkgDMWD++dIOADyCKrEonAKJ7P1X9aS8t6Zk3SfvcQvx+LJlZVvH1i0dBA9+5T3L5pk4EudRtv93DrPNaUDk11yskQMAF4iOVQyylvdJ2Nj83Fg81Q5np5hTY9kqxh3B6MXKd5wdJ+J18+cqHVV2LXuy3aztGsDfIsaSKg9eME84xqcW19Xaln0zHt1lvJXhUW6rXECo617SzLr92YD551PiGMATkKFbh5wjRP/5jo5xCDTavgx591kOZC/yHzm+bOX9cyEel03ZqukgeBCHWmbNIw6n+XBNRF2aFOL36SL5NRd7JgCAZg4+ncNar5TDW6DOO/KMdjgbT06NZatmUjB6sWOnk+Me2UzPVTqq7Fr2ZLtZZXaAv8fqatVjX9rXphEtrqu1LYeNeHQXC63kRA6fulcjUtWunJvF22dD4ukq+edLOwDwCJaRawgEaXMe+bL3S4b/8RqyrybfyLvPciDrWKcAIltW7iCbslXTQfDAiLdydInv6pA6Ea+Xy67Poye/imKtrwDABUwXDaiLrBtp2DDcVTucnWJOjRsyuZagEVPHOIPmz1U6oOxa9mS7WRM9Af4gq6fVuPBMYxrR4rpa23LYiEd3mbbRv3iGhMfT5g45YHQvfYplO2/PU//yz6fEMYAHEOfT8tBdQ49sC9E/hKNjNvhEvmm8g2yeib2XTdnK3VIOx9Y47btZDJ6x+HGMxRefyZxn4hm5NnF0xOOxfbrKaV0JAC4Q3Th1uT3SKBPlz25ccuQZ7XA22J8an2aUEkYvjpziWf5cpaPKrmVPrpv5TBngjxM9uDqxi76Y85Z4wQuuq7Uth414dKcxjVQodk82Y2hIW6cH1K4kT3G+wYkYbOLxFvsAPIFl4JpZgbQ6Df3oEILsFQzn2pN3HyPLkqPxHuVbrr2V7YYOggvR4mq8//d4ULaKb0eaZEbHOXwXVjnLd/v6ygw/ACgR47ficjvKreTgLmoUHDmgHc5OMafG5ZT0Z7/b6MUJaSwdyJ+rdFTZtexRp8yJOqsD/EVk8OecY4dM69K8Mo1ocV2tbTlsxKO7vkRvzvRPDq6pi2wmqYwS2dSuJE8RT8yYU9qv122xD8ADMDxgJdNudeDAKbFQvHLHId/Iu090Ob1/0UFjRCjfMn6Jua71oYPgQmYUzaxrGDIXxHdbGpml6ylXyK9ylsdCbj8AFIl+pSd4keiY/8r2gTXIbz5YcOSAdjg7xZwby2aSZAamp/nZLmr04sSxA/lzlY4qu5Y9E9rN48XVZwD426zDf++sGr/iIG1pRIvram3z5wfi0Z3GjN3T+3fu3rpDNleUUKx2JX2KZUemx/Ea69H886VXBngAy7jNLWztkHansb+6SED2rcjuinyj4D7LkYyHyrHtFrKp3nLrq+xo6CD4IAbX3rQcWd9GEn33/C474xqKOnLibLGN7fwq53Yl5dhyIQYDQCsxNTPmF2mlLUatnrk7WHDkgHY4O8WcG8ewoYSUpel6wOjF1ED+/5ljB/LnKh1Vdi17JpRunj+VA/BRROeaKM3aU2xa/rG215wpxoPVVVtcV2ubPz8Qj+46HmOoesrad9nOh9z4ILIZULuSPkVigh3r/df2+edLrwwwPtGj7IEbW55m3s2D02tE51IuvnjSeqDgPusNZHvP6r3rwcIt19yhqvWpg+DD+sYSy65H1uC67klnut+4L3897VB+lXNrnpaz1gvJNgBUEsN3KVudWKN80m63DvueWvJ6w3xXpCPlXoSftJR/zkhj81ylo8quZU+gEPn0jgH8cVYP0NxDmP8spfx7bV9wpvVQi+tqbcthIx7dacxdjp2cE5vvbrrukm0hXmX/iGpX8k+h3H8VyVuH1YvOpFcGGJ8YA+xV59VTjoN/c6BURGROmViPyH1L7rMc0g7Gzk/Inu3CBbGjtDY7CE6IWc+vcwu2u2EkO9JXPwV8icnre0rabK9bdkzkVzl3V8peKB2AAFAk5maay+2RZknDXWDYxeKSI09oh7NTTNJ4dfhsV2S6KPXia16T3d0tGkIeIn+u0lFl17Jn5vxIa1KdPivAR7D68ITqBrNGXnODpjSixXW1tqWwsR3dpaSrQ0+cTpLHmNgdkD3HZ4nXPWS0alfSp9hZ4ZQpr1etCs7KlQFGJ/pfzbg9TfOR0pysuXBg8y1xupL7ZG+w1YZ3IWy95bn15uhaa6uD4MQu4u/i6m7v7k1se/9NQnt8L9v8dhiY6m3WxupL3QbI/vA2DdX4CADsiY5oxdHNj/8je2Z2frz35KIj64fFj1MvThpvXTkstW5diSGq0As5sl1hnVFkO3+u0lFl17Jn4dDNLWApaSrAZ7B5wcQhfQicvXHn83Ya0eK6WttC2JiIR9U8aOJw1nZkHxvWvbvAsGW0smNG7YoSbXbm3H8NcRdrdpdtsQ/A8MRRfo4iGnHwH9wsu3tmPWblG0X3WY5NHL8nvPPQ3c23Wx4utvdntbXRQfBi/yJ+vr5+f7/Xv7YdOIzE3YGp6bwrCur1xRxOXr6uvNRxhP0wiFOF/lbl4MQ60PZdYygAtBJDqek9O09bf1FeHDke2mJD2ZHVw3KRdIpJG2/hf73lfh1vvUShF2tzCSXr9npB2U7PVTqq7Fr2RNZfmtz3czMXwKexpXYzPzGo/O5dZMsEd+HHSiNaXFdrWwgbE/FojIET+w5PnMPjjOxakH0T0naXxxyigtoVJdocrCmmPNhxf4UW+wCMThzPmsJNiZ52mn3FWdShr8zZar5RdJ+dh6oBIiC7J7Z4sImdeM94THZP1HYQ3Ni9oJSTwfNt46s1rne8YBxJ28l7jvPqz4T8c0Y/BwAKxGBqus/J+/7deV88tE08ZUdWD8vl0oiuND44/jkQbFco9UIOBQ7ny+HCuUpHlV3Lnn+29PdgsUD6pACfw/fRHXSk7US59d6ZWlxXa1sKG9vRncaMMTQeUpz9qEh3GeyZY1RQu5I+xcR2b5W651OvDDA00dPqhu3qKLItyG7ZOnHw5Xy+UXafo9PvI8RPPCQtA8db7MOJ3TrbQfDjYOIjicGzbXfTQuF6pwuWV3G3RSOFzCkAUGDN8GQ7T9b7vldJKC2rHXl/WKJEGtILjTV2Fyj1IvM0a9P8uUpHlV3Lnskkua6mDwrwURS8OCItA6XWB2dqcV2tbSlsbEd3GnNNW7NS9Xyp/LMcW6pdSZ8iEJuqHM7PP59+ZYCRWQZtTuEmSOtdtjIzj/3cyM/76/4Uw31yF/nZAsgOn9YTePM9ZE1+GliBXNv9QmX+FZ7eYH6VcyE7C2XPAIACMeRWOFDG+6Yz5V9vqyUXQsr+/GIv1KfZzs6fq3RU2bXsCSbRu5o+J8CHYZeTpeFMvvHRmVpcV2tbDBvr0Z3G3NLWePBEticJp5ZqV9KnmMncO3C8av75MlcGGJfoSrWjNnrrSVXPXiH/Tsn56+GulvvoF5maa7rXpfVErVmglYzJ08XHicxMd2ibC+DnC5ZXcScyC6aMBIBLxJCbdbkdxx+PEMKJ8s/31ZLrQlS5F0os2d08f67SUWXXsmc2idZVIhbAFH4yfrxwWpWvTCNaXFdrWxc2dhpzl7bGowe0C+nPfW6pdkWJNgsZW54b5p8ve2WAUVnGbM5dFaT9eZVoGvyFgZ/xrTrHjKwCfUdorepe9ZZtrSeqrQLNaNL3NGVtaO/+PARz4+NIfpVzRbnQ+tM4ANBG9KeCy+1IvG/5aQnZ2PzQcGTtcHaKyVxLDVHHNlYvzlfYzyj5c5WOKruWPYtJ0pjF3AUwk9fJipNUpREtrqu1LYeNeHTXu9ir8O80LKURbUZ5lOOv3wbUrijRRlArFokZW+wDMDbRj+oH7ep5si1MbiH/UqnIN2z3SS9ySBDmNhtpaJx9OdO6ooPgzNnmRSV6fp1f9gSnStvyKq5QcyEAqCF6U9HlNr4P3hd9TzY3TzQcWTssISSdYrLXSkLUuYUZTmK+OHO8c/5cpaPKrmVPNMkxZhGxADYUofyjpRCBitm/xXW1tuWwEY/u8s/Yp2XrGJZ+Ms9xDqUNj6JEmxUzJk602AdgbJYh2zKpxvF/doAfY9ybvlXjPqfosOw8BpAdx8h4SiaWrR01zg/OfH0tv5X28/Vrm1vahta5xt/TBZcmLyrb6ULzdaZ7vXYhAGgk/mW4EZanYkT55+vijCCh5NWIlDL3ajd3x/h4taMAf5gpqGwJRNlF3NKI29gipNHB9Y9sej5KTNsKmRgAnKlROa/mGxPxT+tW+vyaOKw3zKrkCY8OAgAA3MwyV1E2BgAAABdKKhkAAOAByEyGSgYAAAAPUMkAAPBwZCZDJQMAAIAH8eumsgkAAPA0lpkMlQwAAACVfP/7MyObJ1DJAADwcJaZDJUMAAAAlfy7JA8ZHRx/n0s2AQAAnsYykzGVAQAAQCXlbx7LQVILAAB4KkxlAAAA0ERRJX/LQf7SEwAAPBWZylDJAAAAUEcUwmr28CsHZRMAAOBxyFSGSgYAAIBKJHtQv5gsX0tGJQMAwGORqQyVDAAAAJVEJaykD8U6MwAAwBNgLgMAAIA24heT//mVHRvy+9d8LRkAAJ6LzGWoZAAAAKglFpMTmbwekG0AAIDnIXMZKhkAAABqWYvJxwzidxXJlJIBAOC5yGSGSgYAAIBqVjn8z8+aQ/xu2ln9XS8AAIBnILMZKhkAAADqkQRi4Scg/56hlAwAAA9GZjNUMgAAANQTf8taJf1RLwAAgOcg0xkqGQAAABr4lRRCgUoyAAA8GpnPUMkAAADQxOEz1juoJAMAwLORCQ2VDAAAAG18aTr5h0oyAAA8HJnSUMkAAADQSqKTv9DIAADweOKkJpsAAAAADXx9yc9b/3whkQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC7zz8T/+3///r9/p//4P+v/+X+zXQ67+D/T/wlm+VeGDoDCf09D5L8LQ+hT/8/sOpljH/x/5uEiQwdAIbjOfx8GDf/n2v9ZYnPuKP+n/v8ES/4/GZ8ACrOz5UcQ/6f6/0yG7Ko6/k/oAEAD5LRQQEYJQC1EFCggowRgKAhbUEBGCbjQ09lQydAKkwMUkFECUI0MHQAFGSQAYyHjE0BBBgm4gEqGJ4FKhgIySgCqkaEDoCCDBGAoSISggIwScKGrs80d+BdOLN8ihDPBLHwdBwqEIUJESZBfOoAT83CRoQOgEL7gx2TsQTAklvQgGJKwBQXmISLDBV4hWLKn6phryf+RDVj5Cnb5P7IBKyHX/5F/AyiEnPZ/5N+w8v+FiPItG7DyM5mF3wOEAkw6XoR8E0t6gCXBIIQtEiEPuk8A0/1RySmzSv7/yQaskLCAASpZBZWsE9JNPp0CBcIQYSHFgzB9Y0kPGJNgQK7sRW9LUkvWQSXr4PlgEDwHlZyAStYh3QQDJh0vqIB6wXoDGIRyAc7mQfcJYLo/KjkFlayD54MBtWSVWSX/ygashE9cU0uGAiykeIG284IxCQYs7nnRW3VQS9ZBJevg+WCASlb5vyGiUEtOIN0EAyYdL3A2LxiTYEAi5EV3Z5vuj0pOQSXrMDmAAZODCrVknZC4U0uGAmg7L8L0jSU9YEyCAbmyF70tSS1ZB5WsgwQCA4aICt9L1iHdBAPSTS+Cs2FJDxiTYMAQ8aJ7SjndH5WcgkrWwfPBAJWsQi1Zh+8lgwELKV6E6RtLesCYBANyZS96W5Jasg4qWQfPB4PgOajkBL6XrEO6CQZMOl5QS/aC9QYwCOUCnM2D7hPAdH9UcgoqWYeEBQyoJatQS9ahlgwGLKR4gbbzgjEJBuTKXvS2JLVkHVSyDutjYIBKVuF7yTqkm2CAtvMCZ/MCCQQGJEJedFcd0/1RySmoZB0mBzBgclChlqwTEndqyVAAbecF6w1eMCbBgFzZi96WpJasg0rWwfPBAJWswveSdUg3wYBJx4vgbFjSA9YbwICw5UV3S073RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdoOy8Yk2DQ/XPCf4beqoNasg4qWQfPB4PgOajkBL6XrEO6CQYszXqBs3nBmAQDhogX3VXHdH9UcgoqWQfPBwNqySrUknVC4k4tGQqg7bwI0zeW9IAxCQbkyl70tiS1ZB1Usg6eDwaoZBW+l6xDugkGTDpeBGfDkh4wJsGARMiL7s423R+VnIJK1mFyAAMmBxVqyTp8LxkMWEjxIkzfWNIDxiQYkCt70duS1JJ1UMk63b8hAKODSlahlqxDugkGaDsvqCV7wZgEA3JlL7pbcro/KjkFlazD+hgYoJJVqCXrUEsGAxZSvEDbecGYBANyZS96W5Jasg4qWQfPB4PgOajkBH7jWod0EwyYdLzA2bxgTIIBQ8SL7pac7o9KTkEl6+D5YEAtWYVask5I3KklQwG0nRdh+saSHjAmwYBPXHvRW3VQS9ZBJevg+WCASlbhe8k6pJtgwNKsF8HZsKQHrDeAAWHLi+6qY7o/KjkFlayD54MBKlmFWrIO30sGAxZSvEDbecGYBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vECZ/OCMQkGJEJedHe26f6o5BRUsg6TAxgwOahQS9YJiTu1ZCiAtvMiTN9Y0gPGJBiQK3vR25LUknVQyTrdvyEAoxM8B5WcwG9c65BuggHazovgbEzfHiCBwIBc2Yvulpzuj0pOQSXrMDmAAbVkFWrJOnwvGQxYSPGC9QYvGJNgQK7sRW9LUkvWQSXr4PlggEpW4XvJOqSbYMCk4wW1ZC9YbwADwpYX3S053R+VnIJK1sHzwQCVrEItWYdaMhiwkOIF2s4LxiQY8IlrL3qrDmrJOqhkHTwfDFDJKtSSdUg3wYClWS9wNi8Yk2DAEPGiu+qY7o9KTkEl6+D5YIBKVqGWrBMSd2rJUABt50WYvrGkB4xJMCBX9qK3Jakl66CSdfB8MAieg0pO4DeudUg3wYBJx4vgbFjSA9YbwIBygRfdJ4Dp/qjkFFSyDgkLGDA5qFBL1uF7yWDAQooXaDsvGJNgQK7sRW9LUkvWQSXrdP+GAIwOKlmF7yXrkG6CAdrOC5zNCyQQGJAre9HdktP9UckpqGQdJgcwQCWrUEvWCYk7tWQogLbzgvUGLxiTYECu7EVvS1JL1kEl6+D5YIBKVqGWrEO6CQZMOl4EZ8OSHjAmwYAh4kV3S073RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdh+saSHjAmwYBPXHvRW3VQS9ZBJevg+WAQPAeVnMBvXOuQboIBS7NeUEv2gvUGMCBsedFddUz3RyWnoJJ18HwwoJasQi1Zh1oyGLCQ4gXazgvGJBiQK3vR25LUknVQyTp4PhigklX4XrIO6SYYMOl4gbN5wZgEAxIhL7o723R/VHIKKlmHyQEMmBxUqCXrhMSdWjIUQNt5EaZvLOkBYxIMyJW96G1Jask6qGSd7t8QgNFBJatQS9Yh3QQDtJ0XwdmYvj1gTIIBubIX3S053R+VnIJK1mF9DAxQySrUknX4XjIYsJDiBdrOC8YkGJAre9HbktSSdVDJOng+GATPQSUn8BvXOqSbYMCk4wXO5gVjEgwYIl50t+R0f1RyCipZB88HA2rJKtSSdULiTi0ZCqDtvAjTN5b0gDEJBnzi2oveqoNasg4qWQfPBwNUsgrfS9Yh3QQDlma9CM6GJT1gTIIBQ8SL7qpjuj8qOQWVrIPngwEqWYVasg7fSwYDFlK8CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GqGQVask6pJtgwKTjBbVkL1hvAAMSIS+6TwDT/S+o5K+fUAL455+vrz9aHXmPSv7+Wsz48/Ule0aHhAUMrk0Ov6sr/NE1u/fUkjczPiWiUEsGg2sLKc+bXO/nmrbzsmTMGn++fh+/XMjiHhhcy5U7ha31tj9f4/lmb9VxpZYs9oz8yfrINZU8n6WhveLfY+tnaM/u3xCA0QmDuVElP9IVGrn2G9d/P6KQboLBBW33CRHlAheczcuS50hmh0JpmDJCxkm5AAwu5Mo+znbUZxVi+/d4RsV9z968cotPdFcd4cmaVPL3yaJT//9gPXkeBc0qOTFNRHnF6Th7wpI3kwMYtNeSU1f4g/Xka7Xkvx9RQuJOLRkKtGu7Z7rC/bSvNzhZUotjxoW+pVnKCPkmi3tg0J4r+zjb6SrmJTRH+zFWolryktfprTqaa8npi5z4e+Xk+TGbVfJsDI3kFadrDRM9B0IlqGQwaFXJ54XMmb83xq59L3k2hkZioKeakXQTDFonnQ+JKBcIztZiCKc0JSd4i+FQzTRnRqklE7agQGvY8tIEcmbEUsnaXSfKN5ZGKRf6a9NddYQna1DJl0z6QC6p5HxcP9vn0rQxAqhkMGhUyb/zwE/5ax9QuVRLfj2iDG/GMKNQS4YCjQspj51c76dR2zlZMpM0TpSikzRRoJYMD6Dxc8JeYevsbWWVnLtruev1eYkLvVVHYy05G+96PsMd3KuSc8pg/Jm8+zcEYHTaVHLeFf6YTL5US/6AiEK6CQZtSdJzXeF+2pzNyZJ5kVx8rdJCYYT3SLkADPqErUT2FlVy/q4T+Ru/WSV3Vx3hyapV8j7e/UzIPwN/LGJcUsn56eBoncNAPtlxcG3A5AAGTSr5EKWf5QqNXKolf0BECYk7tWQo0KTtHuwK9xOm73dbMh/DAtlkIsn2N0Z4jSzugUFTruwWthJ3K6nkgpMFsjfO+/Qt4qC36miqJW8p7Y+YfvdR+r+1UHtJJc92UDm+4hBhF+Kvrm9rMz0HQwWoZDAIo7haJW/x43Gu0Mil37ie7aDyZyIK6SYYNGm7B7vC/QTjVBvBx5L7RHxJG78Pv+SbC4n7Nidao+gdkAiBQVO5wCtspfq1pJK3u8b7xr8INZO9sRxXuMUnujtbeLL/lX8bbPFuF6a2nX9qoXYeoo0qOQ5r2cyyDsP9i1d3jgefuAaDlsnhya7QyJVa8idElNBNaslQIORytSr5gyLKBVrWG5wsKe0ndqd87zRwJibK0eLnRTvSMibhI2nRdneELTm54EE7L9xJup1Ozty4Ni/xordKbqklrwsPh7W8tcDc8zHcmcdBo0qWwWXZIWOwdWgerDsaLKGCQYNKtlzhLy28XfleslNEGdqMpJtg0DDpPHpyvZ/gbO+15Nr+dMJWXdH7E28/6gtrWW+Aj6ShonRL2JJz8yp5veu5mzmnjcjxyod7ne61ufC0dSp5XXg4JV1rvPtLOe0VlTwbwV79lGbJa49Dc+jYi0oGgwaVPI/3iZwr/KWRdqWWPBvh9YgytBlDJ6klQ4GGhZR5vE/kXOHDhU2Dtlvs9bIlpXUa+rYv66lB8d3lqlZY3AODhlx5HuoTrmFLzs1nD6uiS3q5HtFvLAetvMSN3qqjoZYc31iyvLAuScj2X+CCSq6M69Fa6VuPBn7b4LtAy8dp4SOpHyLPdoVGLtSSPyKikG6CQX2S9FER5QL1zuZkyTXdTiNfvIMe3+TQsK+LcgEY9A5b5qnSQOtkvK96dmVe4kd3ZwtPW6WSo2kKJv1DxeT5adtUsljBeptLK23aiEX5ruPBgMkBDOpV8jzaJ57pCo1cqCV/REQJiTu1ZChQr+3m0T7xERHlAmH6fqslpa2abMcLaVExHktvPwgs7oFB/eeE56E+4Ru25NSsSl5XsGT7QNR02o0r8xI/equO+lpyNJts7lnDnWz/AS6o5NkC5qpPXDbSmkUTG5foCSoZDMIIrlLJD3eFRi78xvVsgb8eUUg3waBa231WRLlAcLaq6dvJkoXSykThQvFE2RyP+vUG+FCqc+WbwpZ1phzXk5KSppMjF7p0kfr1hpsIj1ujkmPYUk0TD/6dYnK7So7Dyhg70koP/3JsYBmKSgaD6lryPNYnZPOIHPs7iUh7LfkzIkpIA6glQ4HqhZR5rE/I5hE59tGzV7W2W2z1siXLOX6hUBZPlM3xYHEPDKpz5XmkT8jmETl2IWzJmbn0wahtRg9MU5bKvMSR3qqjupZcDlty8H12u5t2lVy3+llaNqq9Rk+6r+rA6NSq5Ke7QiPt30v+jIhCugkGtUnSh0WUC9Q6m5clDbErR5XDckC//whQLgCD3omQnJjzofJt1/umh98fSLs7W3jcmr+XHNpNZPr652ag+YGaVLJMCMbLjIbKpMtylMkBHkvt5PB0V2ikvZb8GRElJO7UkqFArbb7sIhygTB9v9OS0jAXwuJtZHMjZvDjfjiRxT0wqM2V7wpbxonGbfOn1+UlnvRWHbW1ZMOksQifs/jjmJ+3SSXPz28OZmmVe+XvH4CNoJLBoFYlzyP9wa7QSHsteX7+Px9RSDfBoHbSmUf650SUCwRne6MljXLVejwJi1n5PAwkQmBQ+7nLeaS/7mwJy3lZ55PrZn0se99lv5WXeFJrydsIz1uhkq1XtRx+p+XupVkl18V1azVh+Nmh+3iF0alUyY93hUaaa8kfElHCzEItGQpULqR8WkS5QNB2b7Tk99dC7jrxPklYlP0Dp5Ms7oFB5ULKbWFLzss5kfhm1sdykq9DGO29JFVbSw7NJrJd/Wsz0Pw8LSrZWkZYiGbKZstyfNjpgSVUMAjjt0Il/ye0m3isKzTS/BvXdRHl8WYk3QSDSm33+Mn1fiprye+yZK6WnK0xj0PlmITPpTJXvs3Zrp4n5PKPurzEle6qIzywrZLjekfW4tlVwYfSrJLnpzeHpIyw/GJChyHYBCoZDCpryY93hUaaa8nz0//9iBL6Ry0ZClQupHxaRLlApbZ7lyWjQJDNldz+gWBxDwwqP3d5m7Mtp11WybnTc/tvpLfqqKwl22FLGrzTdnfSqpKjgb6+vn5+fr6+fvV8OLaSzZTR5wc+cQ0GlSp5HuZPdoVGWr+X/CkRhXQTDCqTpHmYf1BEuUClsy1mut+SucvI7inqSeyT/QNBuQAMeoctOS1/4TKZ02Nvom9+v8E5u6uO8MC2SraXM5YGl1/JaMxjoUElxwWhHUpst76C4Db93AaTAxjUqeTnu0IjrbXkT4koIXGnlgwF6rTdx0WUC4TpeyBLZtLKeP8dP6MllizugUFdrnyfs8lpFz0n9uucc2h5Sb7vPvRWHZW1ZFsl/7EZaH6c11SyktVWfN9GWoy62oBKBoM6lfx8V2iktZb8KRGFdBMM6iadj4soFwjONo4lY8547lG8/4HBdHLdegN8ML0ToYunCXJ20i89Lyn03oHuqiM8o/33kkOriYLBP1wlz8+eckpqK4wkLcaaEjZQyWBQNzk83xUaaa0lz8+e8uciSph1qSVDgbqFlI+LKBeo03bvsmRMuM9Xifc/MVTeweIeGNTlyvc528XTFtbPc8j2iuw+05DZtNP7E9d1teSK9Y6KJk9iHrv1KjkT18/vVqaF0guvaNKT3uMVhicMX1slP98VGmn8jeuPiSikm2BQp+0+LqJcoM7Z3mTJtWQs2yuyO+XWVLwNygVgUJcr3+dsy1kXVXKIFNrZlXmJL92dLTygqZIr1jtyH2N/KI0qWcaxwmFOkn2lcesx/dwIkwMY1NWS51H+aFdopLGW/DERJUzH1JKhQJ22m0f5J0WUC9StNyxWut2SMcSdL6J+4HphnOySxT0wqMuV53F9i7MtZxWvnGUtJZ89Ljptyo1RtbfqqKslV6jkl97JeDSq5PnRdfZvV3aVbFRj6o6gksHATSUP7gqNNH4veX5ynb8VUUg3wcAt3fxbEeUCwdlGseSab8v2Sry2xjAfVSQRAoPeYUvOKl05x7pQlZws+zXuc4e6lPJGwuOhkhPmJ65WyWKfn+VL7L/fhzi/Gzyy5+bp5074xDUYoJJV2mrJnxNRQrJMLRkKuNWS/1ZEuUBI3Aex5JqIJ+mE7P/6nWPf99ehfDVKNZnFPTCoy5XnUX2Ls8lZpSvnWF3uvColXTHzEl96L0nV1ZLFaMWOLk0uvZMBmd9+tUqe7XOwzvqJhYnVJDXf3X59+rkVllDBoEol/wFXaKStlvw5EYV0EwyqJp3PiygXqHK2t1gy3iS9xHLkcPO9TpZdvalbb4APpnfYkrMuKLLV35JzK/MSZ7qrjvBw5m9ci9WKHa1p8xzmgVmtksNzn4d5HNoTcf2z5rvbNW06gkoGgyqV/AdcoZG2WvLU9kMiSpg3qCVDgSpt93kR5QJV2u4tlswn4iHMnXd+r81HyT5Y3AODqlz5RmeTs9qla34Fy8pLSlr/BXqrDr9a8ger5Kmx8thxbG8Ha9aNatp0hE9cg0EYvS615MFdoZGm37j+oIhCugkGVdru8yLKBYKzmdP3Oyy5qt60N9NO5aqbTB5jiYNyARi4fajuorPJWc0qOd5OuWFtXuJMd9URng2VnNCoktWn3gaPBPaaNaGaNh1hcgADaskqTbXkD4ooIXGnlgwFqCV7UbXe8AZLFkTylJGqFy2d0gEW98CgKle+0dnkrFaVHO+m3a82L3Gmt+qglqzTpJJ/MwNxXZQRo9y4bvQuUMlg0HsJdVCavpf8QRGFdBMMqiadz4soFxiklhzPVs9ffhgoZZXJQ7y9qvUG+GSqKqA3Opuc1aqSQ4yYUfpem5c40111hEdDJSc0qeQs6xrLssRy47rRu0AlgwG1ZJXGv5ec4e9FlDBvUEuGAtSSvajSdrdbMp7ceHqUyUOIUxb3wKAqV77R2eSsRpW8LkY1pfmrS9+yhNX7E9d+fy8ZlawQh5yM1OOWymuLtLfTe7zC8FSp5D/gCo00/r3kHH8uopBugkHd0uw8yD8polygztkWI91nSTm3fIeUNROX7a5QLgCD3mFLzmpzsij1Wr3slJf40t3ZwpOZv3Fdo5KlyS1Wej9OKvkU2GWjZKMaU3eEyQEM3FTy4K7QiE8t+e9FlJC4U0uGAm7a7m9FlAuE6bu7Ja9VqyZuzcQbYXEPDOoqSvOIvsXZ5Kwmb4mCvFmS37qE1Vt1+NWSpckIEcyB+YlfV8nRKmI52bhr+nkDqGQwCKMXlZzQ9BvXBWaTTBy2HmxG0k0wGELb/QmCs/VM3AOXRfJ601LH3gWJEBjUDZF5RN/ibHJWi7dcFsnr3W6Jrd0/wRoezFTJcaGgVAqRJiNEMAfmgemgko+Wkwmi9MIHn8j5xDUY1NWSn+8KjTjVkv9cRAlPQC0ZCtQtpHxcRLlA3XrDrZaMZ145t6Jj74LFPTCoU8n3OZuc1aLI5JQrMq5GI16l95JUXS254oPxL31RZTzmgemgkqNZllFX4REDTQQaLKGCgZtKHtwVGnH6XvKfiyikm2Dglm7+rYhyAbf1hsuWfKFatd51hFWOuvUG+GB6J0LLWS2CN/rXlQh5zEt86a46woOZKrnC4H9smdZLJR8tV2EkaXHHWPMAlQwGdZPD812hEa9a8l+LKGFmppYMBeq03cdFlAvUabsbLbl+ffFSKKzo2LtgcQ8M6nLl+5yt+bRXRPKtwbW36qirJVdY4OJ6x6jMY9dDJR/sYnvE6CV5PnENBl4qeXRXaMSrlvzXIgrpJhh4pZt/LKJcIDhbV0uGDsxcSiKixh7gBVIuAIO6XPk+Z5PTqmVrvM9F/7pRAXZXHeHBzN+4rniVqGSdo12WjcLAvfPT/R4wOYBBnUp+vis04lZL/mMRJeTN1JKhQOVCyjzMPyiiXCBM3z0tKbHrag4x0AtkcQ8MKnPleUTf4WxyWv7CRzaRfM29blSAvVVHZS05quT8IoM0qH0lo3OvSs6/cXs5oi+oZDAIw7deJT/XFRrx+o3rvxZRSDfBoE3bfUxEuUDbeoO7JeNpV1/BQB8GqByT8Lm0qWT/sCWn1UoyaX5Zw/1hlTzbxlbJ5nLGX5uA5ufxV8nmSFqOj7vYgEoGg8pa8uNdoZGbasmPN2N4AGrJUKBS231aRLlApba7yZIvfqSTWjI8icrPCd8WttrOk25UdVnFfI7r9P7EdWUt2bR4tLFsPh43lTxbZTWctZgQ55Fmj3gX3b8hAKNTqZIf7wqNuH0vebbK34kopJtgULk0+2kR5QLB2bpZMp51PQxa/XojlAvAoHfYajovRIaZy4Nazr8junZ3tvBgFSrZepVy+M/Ejfl5/VWyNZSimQdYLNVhcgCDSpX8eFdo5J7fuH6+GcP0TC0ZCtQupMwD/XMiygXC9N3Nki9Xq9b7ymZPWNwDg9pceR7SN4QtOS933QPxUxovLOTL+VW3a6S36qitJccFjYwN45u8w0RdmB/IQSVHw0S7GR9LWI4OMQ3ooJLBoFYlP90VGvGqJf+1iEK6CQa1k86HRZQLBGfrZUm5Zl0HdF6+gB8kQmDQOxGS82o02esf80jyEk+6f4I1PJj9G9eryTP5TIyAsvl8vFTy2TBxLOkLQ3FFZ9zFhu7jFUandnJ4uis04lVL/msRJTwPtWQoULuQ8mER5QJB23WyZIxbL6QPlz97egMs7oFB7ULKXWGr/sRNJF9PUO6UgL2XpGpryeur1JcK5ODf0U/z49ap5N/CMIzDbzNMsmPPf+ToHesxPrCECgZhANeo5Ke7QiMNv3H9URGFdBMMarXdh0WUC1Q722IqR0vWVqtKvYuJ+AhvsHpMwqdSXVGaB7V/2JITK1Ry5QpWW17iSHfVEZ6sRiUXlzRGCl8+1Kvk6dnzCzDRMJvV4h7ZPBBt3HVAlEElg0FtLfnprtBIfS35syJK6D61ZChQre0+K6JcoFrbeVuyslo1NctfNd5X7dS7YXEPDKpz5ZvClpxpq+R4f+MmU7OWvMSR3qqjupYcba4Z6tZ1hD5Uq+QwOrLPHQvwu/Efd2nnhMgbGHixgU9cg0G1Sn64KzRS/b3kD4sopJtgUJ0kfVZEuUAwQhdLyilGFj0nktlMfD5/4pZEvBXKBWDQO2zJmaa7rDlFefmpNS9xpLvqCE9WpZILixq3riP0YX7rFSp5efTMG1wXUPfHo7HSyWCotdIMTA5gUK2SH+4KjdTWkj8tooQ0gFoyFAhDpG4h5aMiygXC9N3DkvFq5dxBolsmSK7XqAii91M/JuFDqdd294QtOdNSZWtOUVbiSx9b8hI/equO+lpyfimvtBTyVCpVchze6qNvw092zORXXWT/0KvdqGQwqFfJz3aFRipryR8XUUg3waB+0vmoiHKBemdztWS47UzxLa7RTZXB6zXGqMXUrzfAh9I7bMmphr80ieSmvMSP7qojPFrNb1zvljVOQWw10V+agOZxa6rkbXQo73C11+lgbrwVx+EooJLBoF4lP9sVGqmrJW8RRUnB/mRECZ2klgwFGhZSPimiXKBB2zlachUB5SQ6XlkNk9vBMdJMFvfAoCFXdnS2DTnXUMnSymh3KS9xo/cnrhtqyVugOgSxNQT2fAx36lTyLnb/nCP7NjWcDLOOqcP+3/VSQy829B6vMDxhDFeq5Ee7QiOVv3FdiCjx1y7/VkQh3QSDBm33SRHlAsHZKqfvdkt+Tcg/D2wZdtn6W7skY99uO8obpFwABg3lAj9n2yHnlputtzAG8+aA9XmJG92dLTxcpUpeX+W+x5v1ZMffoFIlbyY5jZ6vzS7JEN8ObWdsM4Q19vvC5AAGDZPDo12hkcrvJX9cRAmJO7VkKNCykPJBEeUCDesNzZZc2qcRrt76uwh3yEl/t4rDMMkHi3tg0JIreznbnrmJ4XXbfWVHjkt5iRe9VUdLLXn32v75mg31FWKFMMganxOVKnlvkonFKgezaIbZxtXPPIRHnAUyoJLBoEUlP9kVGqn9jetPiyikm2DQNOl8TkS5QJOztVkyRqgkc98ukyWec2i63PRw14HeIIkQGDR97tLJ2fZIm8WNdI7Jhkq8+aW8xInun2ANT1erknefIk74YxFjftIKlXxYY1HRBrIc0hh8saH7eIXRaVLJD3aFRqr/XvKHRZSQHlBLhgJtCynzoNf5WxHlAkHb3WPJNTU8J+UVInmLaFbjcVKPtjEJH0jbQso8vnXqne2A3aZCJG9PcCkv8aH3klRTLbkQxf6acqpWydZIUyfm/IAbfR5nCRUM2lTyc12hkeq/l/xhEYV0EwzaJp2PiSgXCM52jyW3zFB2CIdiU47tcmWZPFDm0bbeAB/IfWEr52xHpEleJdeI5N0TXMlLfOiuOsLz1f3G9Uwmig0UvnyoV8mF4T3ZJbO+kjvnvuUYJ1DJYNCmkp/rCo1U15I/LKKEGYVaMhRoXEj5lIhygUZt12DJTOJeCmUbu+uVZHKxcvZmWNwDg8bPXb7ubCekSd5rSr62snuCkjPn8hIXequOxlpyxlJ/b5G2QSXvPgBxphDWtRH6APnJJ67BIIzkBpX8WFdopPI3rhc+KKKQboJBo7b7lIhygbZa8kS1JdeIdThaVa06hsVv7ZaBn6GyTMoFYNA8RF50tjPSJpsy5BztyOEWV/ISB7qrjvCILSpZiWK3LiN0Yh4OtSr5v77V0VN+r+kp9440H5gcwKCxljzxTFdopKGWPPE5ESUk7tSSoUD7QspHRJQLNK83VFtyrZ4cDtcl4qewuP/V3I3BKjEs7oFBe678mrOdMdpUrmAdn+BKXvI6vVVHcy154qiT5acI/xjzYKhWycroqTDL8ZSvRxTkUclg0K6Sn+kKjdR/L3nhUyIK6SYYXJl0PiCiXOCKs1VaUpLuw3uqFMlJWEx08njvr329AT6MGxMhzdkSljY5lVwpkpN7XMlLXqW76gjP2aiSg6WWOPbzNyXyxDwUGlTyRDRKsEqlWaYzFjs+ZhZHJYPBlcnhia7QSFsteeYjIkroLrVkKHBtIeXPR5QLXNN2dZYM6bNfPhjvOV1yyPfH4h4YXMuVezhbIxfyktfo/YnrK7XkT+CCSv4Ieo9XGJ5rKvnP01pL/hRIN8GApVkvgrNhSQ8Yk2BAruxFd2eb7t/yG9efAipZh8kBDFDJKhdqyR9BSNypJUMBFlK8CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GwXNQyQlNv3H9QZBuggHazguczQsSITBgiHjRvSo/3R+VnIJK1uFTJGBALVmFWrJO+IYTtWQogLbzgvUGLxiTYECu7EXv9QZqyTqoZB3Wx8AAlazC95J1SDfBgEnHi+BsWNID1hvAgLDlRXdLTvdHJaegknXwfDBAJatQS9ahlgwGLKR4gbbzgjEJBuTKXvS2JLVkHVSyDp8iAQNUsgq1ZB3STTAg3fQCZ/OCMQkGJEJedFcd0/35jesUVLIOkwMYMDmoUEvWCYk7tWQogLbzIkzfWNIDxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtggLbzIjgb07cHjEkw4HOXXnRXHdP9UckpqGQdVDIYUEtWoZasw/eSwYCFFC/Qdl4wJsGAXNmL3usN1JJ1UMk6rI+BASpZhe8l65BuggHpphfUkr1gTIIBQ8SL7pac7o9KTkEl6+D5YIBKVqGWrBMSd2rJUICFFC/C9I0lPWBMggEVJS96qw5qyTqoZB1UMhigklWoJeuQboIBk44XOJsXjEkwYIh40X29Ybo/v3GdgkrWYX0MDFDJKtSSdfheMhig7bwIiTuW9IAxCQaoZC96W5Jasg4qWQfPB4PgOajkBH7jWod0EwzQdl4EZ2P69oAxCQaUC7zorjqm+6OSU1DJOqhkMGByUKGWrEMtGQxYSPECbecFYxIMyJW96G1Jask6qGQdPnENBqhkFb6XrEO6CQakm17gbF4wJsGAXNmL7pac7o9KTkEl6zA5gAEqWYVask5I3KklQwG0nRdh+saSHjAmwYBc2YvelqSWrINK1sHzwQCVrEItWYd0EwyYdLwIzoYlPWC9AQwIW150t+R0f37jOgWVrIPngwEqWYVasg7fSwYDFlK8QNt5wZgEAz5x7UVvS1JL1kEl6+D5YBA8B5WcwG9c65BuggHazguczQvKBWDAEPGiuyWn+6OSU1DJOng+GFBLVqGWrBMSd2rJUABt5wXrDV4wJsGAXNmL3paklqyDStbB88EAlazC95J1SDfBgEnHi+BsWNIDxiQYkAh50f0TrNP9UckpqGQdPnENBkwOKtSSdfheMhiwkOJF0HZY0gPGJBiwkOJFb0tSS9ZBJevg+WCASlahlqxDugkGTDpeUEv2gvUGMKCi5EX3CWC6P79xnYJK1iFhAQNUsgq1ZB1qyWDAQooXaDsvGJNgQK7sRW9LUkvWQSXrsD4GBsFzUMkJ/Ma1DukmGKDtvMDZvEACgQFDxIvuqmO6Pyo5BZWsg+eDAbVkFWrJOiFxp5YMBdB2XrDe4AVjEgyoKHnRW3VQS9ZBJeugksEAlazC95J1SDfBgEnHi+BsWNID1hvAgLDlRXdLTvdHJaegknXwfDBAJatQS9bhe8lgwEKKF2g7LxiTYECu7EXvqjy1ZB1Usg6fIgEDVLIKtWQd0k0wIN30AmfzgjEJBiRCXnR3tun+/MZ1CipZh8kBDJgcVKgl64TEnVoyFEDbeRGmbyzpAWMSDMiVvehtSWrJOqhkHTwfDILnoJIT+I1rHdJNMEDbeRGcjenbAxIhMOBzl150t+R0f1RyCipZB88HA2rJKtSSdfheMhiwkOIF6w1eMCbBgIUUL3pbklqyDipZB88HA1SyCt9L1iHdBAMmHS9wNi9YbwADwpYX3S053R+VnIJK1sHzwQCVrEItWYdaMhig7bxA23nBmAQDPnfpRW/VQS1ZB5Wsg+eDASpZhVqyDukmGLA060VwNizpAWMSDBgiXnRXHdP9+Y3rFFSyDp4PBqhkFWrJOiFxp5YMBVhI8SJM31jSA8YkGJAre9HbktSSdVDJOng+GATPQSUn8BvXOqSbYIC284JasheMSTCgXOBFd9Ux3R+VnIJK1kElgwGTgwq1ZB2+lwwGLKR4gbbzgjEJBuTKXvT+xDW1ZB1Usk73bwjA6KCSVfhesg7pJhiQbnqBs3nBmAQDcmUvujvbdH9UcgoqWYfJAQxQySrUknVC4k4tGQqg7bwI0zeW9IAxCQbkyl70tiS1ZB1Usg6eDwaoZBVqyTqkm2DApONFcDYs6QFjEgwYIl50r8pP9+c3rlNQyTp8igQMUMkq1JJ1+F4yGLCQ4kVI3LGkB4xJMCBX9qL3egO1ZB1Usg7rY2AQPAeVnMBvXOuQboIB2s4LnM0LxiQYkCt70d2S0/1RySmoZB08HwyoJatQS9ahlgwGaDsv0HZeMCbBgFzZi96WpJasg0rW4VMkYIBKVuF7yTqkm2BAuulFcDYs6QFjEgxIhLzorjqm+6OSU1DJOkwOYMDkoEItWSck7tSSoQALKV6E6RtLesCYBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vECZ/OC9QYw6F4B/TN0nwCm+/Mb1ymoZB0SFjBAJatQS9bhe8lggLbzAm3nBWMSDMiVvei93kAtWQeVrMP6GBgEz0ElJ/Ab1zqkm2CAtvMiOBvTtwdIIDBgiHjR3ZLT/VHJKahkHTwfDKglq1BL1gmJO7VkKMBCihesN3jBmAQDKkpe9FYd1JJ1UMk6qGQwQCWr8L1kHdJNMGDS8YJasheMSTBgiHjRfb1huj8qOQWVrMP6GBigklWoJevwvWQwYCHFi5C4Y0kPGJNggEr2orclqSXroJJ18HwwQCWrUEvWId0EAyYdL3A2L1hvAAMSIS+6TwDT/f/5n2848b/BLv+fbMAKtWQwmIeIDBdYmdfd/q9swEpI3KklQ4F5iMhwgVeYtZ38G14BlQwGOJsXvVXH/2+6P0AL/y1jB0BBRglANTJ0ABRkkAAMBYkQFJBRAi70dLb5E9cADTA5QAEZJQDVyNABUJBBAjAWMj4BFGSQgAuoZHgSqGQoIKMEoBoZOgAKMkgAhoJECArIKAEXUMnwJJgcoICMEoBqZOgAKMggARgLGZ8ACjJIwIXuKvnn//u//5f/Dv/9T7DLV7L74//j17vAIHjOv6dhw3//3/x7gP857+W/8Bsn/HoXFJiHyHnc8N+F/8L0jSU9/guW5Ne7oADO5vVfd9Ux3Z+/BJXCX4LSCQkLKhkKhJDGH0BImP9eMn8JKoHfuAYD/n6RF1jSCywJBuTKXvRWyfy9ZB1Usg6eDwaoZJX57yX/ygaskG6CAZOOF8GSOJsHjEkw6F4B/TN0d7bp/qjkFFSyDp4PBqhkFWrJOj+TWaglQwEWUrzAkl5gSTBgIcWL3paklqyDStbB88EgeA4qOQGVrEO6CQZh0mGIeMD07QWWBIMwREiEPOhem5vuj0pOQSXrMDmAAbVklVkl84nrBGrJYMBCihdY0gssCQZ87tKL3qqDWrIOKlkHzwcDVLLK/L1kaskJpJtgwNKsF1jSi2BJwhYUwNm86G7J6f6o5BRUsg6eDwaoZBVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhe8k6pJtgwKTjRbAkzuYBYxIM+NylF90tOd0flZyCStZhcgADVLIKtWQdvpcMBiykeIElvcCSYECu7EVvS1JL1kEl67A+BgbBc1DJCXwvWYd0EwyogHpB4u4FYxIMKBd40T1sTfdHJaegknWYZsGAyUGFWrIOtWQwYCHFCyzpBZYEA3JlL3rX5qgl66CSdfB8MEAlq/C9ZB3STTBg0vECS3qBJcGAIeJFd0tO90clp6CSdfjENRigklWoJesElUwtGQqwkOIFlvQCS4IBubIXvVUytWQdVLIO62NggEpW4XvJOqSbYMCk40WwJM7mAWMSDBgiXnRfb5juj0pOQSXr4PlggEpWoZasw/eSwYCFFC+wpBdYEgzIlb3obUlqyTqoZB0+RQIGwXNQyQl8L1mHdBMMQpLEEPGAxN0LxiQYkCt70T1sTfdHJaegknWYZsGAWrIKtWQdaslgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp4PBqhkFb6XrEO6CQZMOl5gSS+wJBiQCHnRvSo/3R+VnIJK1mFyAAMmBxVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJet0X9WB0UElq1BL1iHdBAPSTS+CJXE2D7AkGBC2vOhuyen+qOQUVLIOng8GqGQVask6fC8ZDFhI8QJLeoElwYCKkhe9LUktWQeVrINKBoPgOajkBH7jWod0Ewyo23nB9O0FlgQDhogX3S053R+VnIJK1mF9DAyoJatQS9ahlgwGLKR4gSW9wJJggEr2orclqSXroJJ18HwwQCWr8L1kHdJNMGDS8QJLeoElwYCKkhfdLTndH5WcgkrWYXIAA1SyCrVknaCSqSVDARZSvMCSXmBJMCBX9qK3Jakl66CSdVgfAwNUsgq1ZB3STTAg3fQiWBJn8wBLggGJkBfdJ4Dp/qjkFFSyDgkLGDA5qFBL1uF7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GwXNQyQn8xrUO6SYYhEmHIeIB07cXWBIMGCJedP8E63R/VHIKKlkHzwcDaskq1JJ1qCWDAQspXmBJL7AkGHTXdn+G3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXdLTvdHJaegknXwfDBAJatQS9YJKplaMhRgIcULLOkFlgQDcmUvetfmqCXroJJ18HwwQCWrUEvWId0EAyYdL4IlcTYPGJNgwOcuvejubNP9UckpqGQdPB8MUMkq1JJ1+F4yGLCQ4gWW9AJLggELKV70tiS1ZB1Usg6eDwbBc1DJCfzGtQ7pJhiESYch4gHTtxdYEgwoF3jRvTY33R+VnIJK1mFyAAMmBxVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQdPnENBqhkFb6XrEO6CQakm15gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrBJVMLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGKCSVagl65BuggGTjhfBkjibB4xJMGCIeNF9vWG6Pyo5BZWsg+eDASpZhVqyDt9LBgMWUrzAkl5gSTAgV/aityWpJeugknX4FAkYBM9BJSfwG9c6pJtgEJIkhogHJO5eMCbBgFzZi+5ha7o/KjkFlazDNAsG1JJVqCXrUEsGAxZSvMCSXmBJMCBX9qL3egO1ZB1Usg6eDwaoZBW+l6xDugkGTDpeYEkvsCQYkAh50d3ZpvujklNQyTp8igQMmBxUqCXrBJVMLRkKsJDiBZb0AkuCAQspXvS2JLVkHVSyDp4PBqhkFWrJOqSbYMCk40WwJM7mAWMSDBgiXnSvzU33RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdY0gssCQZ87tKL3qqDWrIOKlkHzweD4Dmo5AR+41qHdBMMqIB6wSK3F4xJMMDZvOhuyen+qOQUVLIOng8G1JJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq/C9ZB3STTBg0vECS3qBJcGAz1160d2S0/1RySmoZB0mBzBAJatQS9YJKplaMhRgIcULLOkFlgSDp+fKv1/yj+70tuTFWvLXT/ig3NT1r9+q8khs//X1kDzxokre2UX2FPn9is2HGZAGrI+BwTWV/PsV8o5pcP1b5zr/eVpEuVZLniLEH48opJtgcC1J6uMKv9/xtj9Vt2108NbLnwiWbHe25wWV+7lmSfggriZCozjbpQhzC93XG8ILaVTJs4LcYUV3ee2RR2S1V1Ty6TmtWe/3aMdnaM/u4xVG58Lk8Hv0HDP9eGJEuVBLPpvlpy2iPCOJC89ILRkKXFhI8ZlcTxO67C1wTo2MU74bHbzx8inPseSENE4ZId6zuAcGF3Llfs6W8p07s+ry51BVxHLo3rW59lryKbDPlF7EOdWbnvcB386bX3KTSlaGRXF8pu2vDud3gkoGgzCUm1TybzjjRClfVCLKCHmTQftvXGuRtvSgz4wopJtg0F6383GF01XMS6iBTI5paA5eiBCtl1don777WDKgPe7CCPkjiRAYPMnZUib308+su3z6KHnMHnZ3ttDLBpX8HdorZLM31VrjJ7VztxtU8nlVWMg+qNr+AVGXT1yDQWstWfecfFr80IjSWkvOJIlZ50vXDiYeID9Dt6klQ4HWhRSvyVXOjFjJXCaQ5Xy+1cEbL6/yEEvO5PPsEYI9i3tg0Jor93S2lKkz+ply2Ujm8i0qWU7J01slN9aSM5F6IrO+lzmh5yNX0aiSs+ueGbPk2o+wSlqEJVQwaFPJWc/JDbOQnigMPygbv5ecj7R6jpiz4wgZZRHSTTBonHS8JtezC5bTzdZA1ujgzXFS5RGWFKStwghZEokQGDzJ2RKCAFLPrLx8g0q2H7B7bS50s1ol5yN75imyJ4weYNpUcq7CPqFOefn2oye1TA5g0KSS88nfhOYM2YgyutJqqyWXIq12kedGlKCSqSVDgbaFFC9XSK5TTDcLKYA6YTY6eOvlMzzBkhFpqzBCSGNxDwzacuW+znZmvop2Zu3l61VyhYl6q46mWnIpsquPsT/hZ0L+Gej50BU0qeRDqn96Tm2lpNR+hHXSAt1XdWB0WlRyUSRr80NITiInzxl8WDbVks8RQv4lpFd5cEQh3QSDpiTJzRX2oWammG4eXPTssWnnWx380Bn78jmCJaudrZMlhbxqGCKiNVkSPpGmXLmvsyXMV9HOrL18vUqueLreKnlesftf+bfBPm4tvxL++703RpLTbifEHxXfffR+hAXBPE0qeX6eGeU5lU/dbwe/ZIhsZhw88nYfrzA6LSp5PxcsvhD/0slMMtIeHFGaasnz88ysz7mLtGmMeHBECV2nlgwFQmZWPYq9XGEXhgTxRJWdd6633V0h8XvZP1Hl4K2Xz/EAS0Z2j3xmhEDfZEn4RJpy5b7Odma5t3Jm9eUL7nukpnu9VUdLLTk0Xdj1eB/c5fVGtuWR3YEtzz21Hov5qSpV8jpy9j/evT1nMgy29rIjoO4cD1QyGIRBXKmS9dixy/9OQ82IKEPL5JbfuN4MsD9B3xtYF3gfGFFIN8EgTDq1Q0Qd9S+6gpxcyOe2wLS/w25NT/ZEGh289fJZWqbvPpZcaWjaAxIhMLhULujjbCck3pTPXNpcddA19ZPtIt0/wRo6WqeSczF8C9anmWw94ZC9rs2HTo1aVPL8NBOn96g//m7KO7bPNR8LJgcwqJ8c9ORvYgs1R2cwIsrQA7Olljw/zcTpgbZIKzuEjAGeEVFCL6klQ4GGhZRbJlc5t5APrjnfSd6u9z2dK3trHbz18lnGt2QkmuL0xMPA4h4YNOTKnZ3tTNWZVY1yrJGu6sl6q46GWnJoOXMOXNvfIDkcyYX2dUSMGgADDSo5Pn3yGuOB0ziSvUn77HVGovuqDoxOvUpeI0QyovQjj44oDd9LzkaC9UGPc4vsTNo/IqKQboJBQ5I0j/cJV1eQc/P5YD4A6fe1HfxwodbL5xnekisx1svmcARLEragwHOc7UT0vfKZVY1ytD1Yb5U8P2uVSl5T1FT960ug0RBJ+7W5bI/I/LR1Knl+lAnZ3NCfM+5N33o02LVx9x66j1cYnXqVPI/2CWVARV84OMOjI0pDLXl+lIlUU6shIibRz4woQSVTS4YC9Qsp90yu5qkxN0pvq0cm2Vfr4K2XzzO8JVfqW/aBxT0wqK8o9Xa2I+uiXPnMqkYZ1riVRkCN3rW5+lpyaBjQrLLadZcF5kP7+urrTNSFepUcn1OxSzx0eE7Zpzx83lfGAZUMBtUqObqHmuLFGLEbbBURpU6FdqG+lpxXvXpWLLseGlFIN8GgftKZR/uEryvIqfl8sJDQaGluq4M3Xr5AsGSdsy2XfbslI9FEyiOPAYkQGAwftjLIedaZVY0yyLktYaurs4W+1qjkQoo6oQTruEs296hTwVjMj9ukkmXzgBza2zeGf218NE55Pei9qgPDU62S57E+oWZCSox4dkSpryXHiKKFgXhsd6H47A+NKKGL1JKhQPVCyk2Tq3mmNCjlAPtJs9HBWy9fYHhLRkpZ1RCwuAcG1dqut7MdiXe0zqxqpBO9u9a9e6vk6lpy+W2lSx6lmUCdCsZi7mGVShbDqC9RnnN/bNmTGR9yrOeAMGAJFQzCCK5RyXFuyITKGHDWGFEVUYatPTT8xnV8ctk8EI22u5DseWpEId0EgzDpVA2ReaxPyOYROXbBFeTMbD5YynK1/KDRwVsvX6B6+l6u+nZLrpRMNAQkQmBQXVGaR/qEbB6RY3c624E1LbPOrGqkst6iNlvrXpsLna35e8lG2JKj2+Fyezl4wcJvolklq48Sc3fZnCgVfrT2o8HkAAa1teSyK6SiuCqiVH15pAv1teQfQTYPpEYr5tAPiCjhtVJLhgK1Cyl3Ta5yYiZQTVcWh1W9Wwlb0rzSwZsvX2B0S65UN+wFi3tgUJsrd3e2A3JWoHxmVSOVGLOqhURv1VFdSw7tJnJ9Td6lbGfaD5+8zR2sUsnzc2SWReL4l82J/8iezCqKHB13cuAT12BQq5JjDMgtKMrh1Rdk+6kRpeE3rkvMD7mPEIYZ5ei4EYV0Ewxqk6S7JtfLJwZaA5M0r71Z2+WfYkmloj4YwZKELShQmwgNFbaigg2Uz6xqpNFcSu6ukudnrVDJ5fWO7Xhc7zRyt3Pz4Zj736KS1SeJ40E2J2RH7pXLGO06Iop0H68wOrWTg1UFOfnC0yNKy99LLjA/5D4Oy47HRpSgkqklQ4HahZR5pN/gCst5F/LBwFAq+SmWbDXa+2FxDwxqc+V5pA8StlYFGyifWdVIQ05sSIZ6q47aWvLv10JO/p8X/6xXuxy+YOI30aySVcMkwd5aIx1+dkAlg0F1LVmQzYRTCHl6RLmplvz4iEK6CQaVk85triDnXQstrXeV5rU3a7t8sGSFs3W3ZG27fpAIgcEDw1bsy0L5zKpGCvF5Gryn+ydYQ38dvsx3LuXIZvbRLr/6NzH3r0Ulq4NFnnKzQnzs7DKKHB92emByAINalWxxksXL1nMjim8teb3Q4yNKeM3UkqFA5ULKba5w9byZJAcwWJpXR4q2yz/EksN/MIjFPTCp1HYjhS3JuYTymVWNUqJvt1QMequO+r+XXCa+atmMaxJZE1oLKL2Zn6dKJZ+e/EBS/4qjUDZTkjMGo/uqDoxOGL8eKjlcZ0JCyOMjSv1vXJdIos3jIwrpJhhUVkBvc4XltOZ8cKHx5FI6oSHNKy9fmW72tmSrETpQOSbhc3mIs+04lpKNM6sapYT5vvW83ip5ftaa37g2OMU1O8xJAweBfgvzAzSpZGUpKB7aBkSy44xtuL50H68wOl615NkPVl95fETxqSUnM+ay/eCIEp6IWjIUqFxImYf5Ha4gp+UvXCCWTmrXxxpT4sbLP8SS0uzn6+vr5+ffr68Ba8os7oFBZa48D/UhwtZa5hXKZ1Y1SljvIdtV9K7NedWST8HdjvVLg1Ybv415ZFap5HX9RbZ3iBW2I3a9a/ScFpUMBk4q+ZT/PT6i+HwveX7E3UM+P6KQboJB3aRznyvIaZciS+s9pXntvRov/wxLrinVxs9oYZ1ECAzqtN1AYSuWeaNuKZ9Z1ShBzmrLhLo7W+jx6yo5vsj4KHZOe/XVv4m5e1UqeX3vycPGwbYdiJl/YW1UWow2KUT4xDUYOKnk2Q0mxFceH1FcaskxpKzXeX5ECVMztWQoULeQcp8rXDwtEHPg2jkzcfAyrZd/hiXj/Q/8O1YAY3EPDOq03ThhKyZQ/9SdWdXozFko1tFbJTvVkmNwjyY7bSr8HZW8xvTTe4w22Vmh4qGlRdvYex8soYKBj0pe6wmyLVvPjSgeteQYUjYPfH5EId0Eg7pJ5z5XuHjaxBrFKh0/dfAirZefLWk7W29LxvufGCrvIBECg7pEaJiwtQsm8o/ymVWNTjQHrIXutbnQ5ZdV8jmljcKxYIuKJZSezGO3TiXH4XJ6katI3u2VfaUXXtGkJ0wOYOCjkqP7SBB+fkRxqCWvIWWzwvMjSugetWQoULeQcp8rLGc1Z6n5BfQc0r/aJLL18k+xpLRKGSi0s7gHBnW58jBhKwafqf32rwJVjU7s7tFCb9XhU0uODx+f5D+yLZsaUVi3LSq8jRaVvE5W//ysYfw3muTwhLKnNEYuesS76L6qA6MThu/LKvm86Pj8iPLqb1x/hbxsYeeAsufBEYV0EwzqKqDzKL/FFZazWlO7311JtMbvv7aUoaaDrZefqUs3l4t2s+Qa+1PGie11YxI+mEc428oaTqZ/y7/KZ1Y1OnKuptbSWyXPz/rqb1yv4V22az5FcMXIb6RFJW8DbHqX30Eo7ya8wwMqu87UmK4j3ccrjI5HLXldeIqu8vyI8kItOfzS6/xoC3v/k10PjijhyaglQ4G6hZR5kN/iCnJWfWD5nTxWTpqx3L7g4Bqtl994hCXjtTWuBdAbYHEPDOoqSvOw7h+2DmUJ+Wf5zKpGR+SUZi/urTo8asmrgdcHqXmt0qTFyG9kfoJalbwtE6QcXq7su8Ej3gUqGQw8VPJaN43Fg+dHlOvfSz7VVv5YRCHdBAO3osxFV5Cz6gPLKR+wvL7k4BqNl9/xCEvGRnPB4b++r64I3AuJEBg8KmxJ46X1/t9ZqhodiM/R7DfdP8Eaev2aSt4+cCw71jBefLClSYuR38n8QqtV8vr+Ew6PFy1VivQXPeJdMDmAgYNKXvOi1X2eH1Gu15K3ABs4mOAPRJSgkqklQ4GqhZQbXUHOqg8sRxlrOn3BwVUaL7/jCZZcbn+Q/vsHll29YXEPDKpy5UHCVrzF0l/ZKJ9Z1WjPoVzdRG/V4VBLDvFiZrNXTU5b06Yf86ipV8mniS7ycxwPcZiURkm8UPNIeg/dV3VgdF5XyVttRXb8hYjiVEv+cxGFdBMMqpKkG11BzqrPB/eqriIcFRxcpfHyO4IlTWfrbMnwExTnBt/bIw8S3qssCZ9MVa48RthaI9ByC9kon1nVaE/04fozIr1V8vysL6nkNX7tHkP2FR+spk0/WlXyOpIPnBaIYpvSulFNm450H68wOi+r5C1p3Jzg+RHFqZZ8nGL+QEQJb41aMhRwq4BedAU5qz0fDJxWyjUKDq7SePkdT7DkdFx5pu2Zx4hjLO6BQVWuPEbYkqax7XErQ1WjHbFcfeHTIL1rcy/XktdK8v4pavLVmjb9aFTJu5+0PrD96HWgZt2opk1HUMlgEEbvKyp5E8k7H3h+RLn+G9ebQWb21/gDEYV0Ewyq6nY3uoKcVZ0P7iRdwAxIBQdXabz8jqrpu7MlMxddH3qM+E4iBAZV5YIhwlb0rTigZdNVJa9BrvEpAt2dLfT7hd+43pZB9w9fk6/WtOlHm0o+TlsH9oPoxnWjd9F7VQeG59VaspoOPT+ieH0v+XCRPxBRwlujlgwFHl1LnrAiUsHBVRovv+MJlvzKXHN96sZ73gOLe2BQpe1GCFuJgJXN8plVjTai+15Jz3qr5Bdryat9jysEYpHig9W06UeTSj7MWj+HP+pweMAb143eBUuoYPCiSl695zDMnh9Rrn8vOfCt/3nUPxBRSDfBoGrSudEV5Kx6lRzY/zZzRUjKOHiWxssLj7RkJD7wEAGeRAgMHuNs0nBred5WqWq0Ep+h9SFmutfmQsevq+Rw9szRVjHgy6bK2Dlti0repqt/fsQO37spb/eEsqc0sC6uG70LJgcweE0lb44jOxaeH1Fe+HvJwmaa7TKy48ERJahkaslQoG4hZR7kt7iCnFW6ssr2m1N1y0CagxdovfzEUy05E+954YuN/rC4BwZ12m4e0V2dLYaRra+yo3xmVaMVaX3N9XurjtdqySFUzJweoSanlSaXrHY/8xPUqeRtbttbYferjNvglh2lZ64xXUe6r+rA6Lykktclx9Oa4/Mjymu15Jk1TdzMINsPjiikm2BQlyTNg/wWV5CzLgSWNQmoO1dx8CKNl18s6aKS327JQHzci6e7UmdJ+GAeEraUKq/sKJ9Z1SgSH+FaFtJbJc/PelUlr0H6/AQ1r1WajBDxFOYnqFPJ82METinwNuWtMlm2b/CId9F9vMLovKKSN5F8Wjd9fkR5vZa8CynrM563FQaPKGESoZYMBdwqoBddQc66EljWFEm2DVIHL9N4+SdbciLe9OLprrC4BwbPUMlryNnlJrKnfGZVI2HN664lQL1Vxyu15Pjy0tcXjVIqnUiTESKewvxsVSp5naiSh12HxvqM0rb0wi96xLtAJYNBGL1XVXI4d+YcFp4fUa7/xvWONaTI9h+IKKSbYBAmHXuI3OcKctalwBLTg8qTEwc3aLx83fQ9piUnKjr2LkiEwKDuc5e9nS3Mv4F9B2RX+cyqRkIMUxc9pvsnWEPfr/3G9RrQ09wvrk8UVg4qmvRkHphVKnl+ignlQZJlmgqPGGgi0GByAIMXaskxmKZD7PkRxaOWvE2YfyeihO5RS4YCdQsp97nCctZFbScn197z7OAW0rzy8o+25HrXERb8WNwDA7clqTudbdUoexEnu9xUsnqTBnqrjuu15IJIrrHgxfWRd1GtkuNzqC8xRvVoh4qHlhY1Y68H3Vd1YHSuq+S4rKmNMDny3Iji8L3kiTjf/J2IQroJBnVJ0n2ucPG0hUZld3Zwi7bLP9qSQ4X4YEnCFhSoS4T6Otuq4g6Ziewr37Cq0YI0vez3vVXy/ACXVHIMz2r35VDBKhfXR97FPHZrVHJxllrXUGTb9oh4xqAFsf7jFUbnskpeveXautvgEcWnlnwOIc+PKEElU0uGAnULKfe5gpx2McdrPNt+jCPSvO7yz7bkSLGMxT0w8FqSutPZonw59lN2lt20qtFMfMTLqVnv2tzlWnJRJFe8+r+ikuenyD7H2Q6ymR9ZcW3n5aLTTaCSweCqSi5+OOX5EcWnlrzaIU6ZsvnciEK6CQaVk848zO9wBTmtIh/UkLNr41J08NpOSvO6ywdLVjjbcsnhLDlSLCMRAoMHhK0YbE5plewsu2lVo0Ds/3W37e5sofcXVPJqXj1tPedyKdLgary8m/kBKlRyXOfJPMd5GUg28288Gk42h6P3qg4Mz1WVPI/7gOpLj48oTrXkGFHijCObz40oYXGDWjIUqFxImYf5Ha4gp12MLI2rd62Vo6bLP9uSl6tqN8DiHhhU5srziO7jbDn9KnvLblrVKCAR6rLX91fJF2vJq3kz6wPm8sfoudvcvwqVbDzH2Q7mlLYcf2FA3QxLqGAQxu8FlRzSjhl9eD0+orj8xvXE/JBbhHh8RCHdBIMw6VQMkdtc4ep5C62BSZrX3q3p8pXT96CWtCeB90EiBAbjO5vcOrm37C7fsarRxKoVZfsC3WtzofvNv3G9Pnh2VU8OZ00Y349sDoeTSj7bwWoeDWsOvV4wOYDBtVpyDAjZ0SWHHxtRnGrJfy6ihPdGLRkKVC6k3OYKV89bsLp1RprX3q3p8s+2ZLMpb4TFPTCozJX7OVu8c3Jr2V2+Y1WjCWn3ytJWb9VxrZZsprTmq5fDwwquuf/+KtkaWvFyAyyW6vCJazC4pJLjVJAf+k+PKE7fS/5zEYV0Ewxqk6R5oN/gCnJe7roGVuA6I81r79Z0+WdbstmUNxIsSdiCArW58jykOzjbmnMlV5b9ZTetarR1/5XErLdKnp+1VSXbItn6Bkk03dVweTtzB29QyWK6nOGWo0NMAzrdxyuMzhWVvInkbLX16RHlplry4yNKUMnUkqFA7ULKXa4g510MLVaKcEaa196t6fLPtmQ8fYQEhMU9MKjNlXs5mxxXGmQP7KlqVJDiDfRWHVdqySFAzJQ6Xm4iA6P9zb+LWpUcB0FmDMTD61CKc5qeLifNhwOVDAYXVPImkguxVFo8NaLU1pK//v2Zkc0zfy6ikG6CQe2kc5crGCcGh53+X+7wOTLNDj79P9k8k3Rzahr+q718kWDJGmfrZEmDkYIZiRAY1CZCnZwt3tYkc4Hy0UgMTy/5bG1V/jbCE7Sp5FjUKed85VcvB8cNM3P3K1RyNEZmEKRWkB36k5eNNgJMDmBwQSXHUFocWg+PKLW1ZCMG/LmIEt49tWQoUL2QMg91f1eQE3OJnhzO9VAOr51qdXDZzkU24/CRwS05UepdnCZGCGYs7oFBda48D+p3O1tU3zaZC5SPCqtYlO1r9FYd7bXkzbrFwkhxCSSGu4rSSifmsVmhkuNYyYyC+KCyOZHu2Yg26zkgDLqv6sDohBHcppKjT5RH1sMjSu1vXBcf8w9GFNJNMKitgN7lCnJmLh8s3VVZR2918MbLF6lON/tYMlw6f9V434wl3kv1mIRPZWxnk6MVlC9QDjzS6MW8rLdKnh+j6TeuwwkzRlyWVtoayAtv/l00q2R1qSeuA+0eVNm1Er1l3FS//3iF0WmuJUeXsNIfafTQiFJbSzZWX+Xg34kooYvUkqFA9ULKTa4gZ+YSnnhl/Xjs0+r6rQ7eePkig1tyDuPZJ5lPnTASz/fA4h4YVFeUejhbvG4FGX8rH10oPVkDvWtzzbXkEB1mrF7HyUBpV477QzC/3hqVHMeBOufJocODxodPJ4Oh1kozoJLBoFUlr8PemgmeHVGqf+N6fpAJta32oM+OKKSbYFA/6dzjCnJmLrgUU0HlvrKj1sFbL19ibEvKlTMyOfboimDwh0QIDEZ2tvW6FWS8tXx0Zr3Liy7b3dnCMzSo5DVU2Z2WhqkZnRYYbqVaJa8rw8rTrMaS7Zm8rJb9uVliCPjENRg0quQtXpvjXto9M6JU/8Z1PkBkJs1nR5SgkqklQ4H6hZR7XEFOzeaDclxtEHOA3bFWB5c9tZcvMbQl12dXr7wmU5WPejMs7oFBvbZ7v7PJsSoyDlc+OtMYnbL0VsmNteT1dWoR/sSqH09v2GuB4VbmB61RyVv0Tl5j5kjcfW6f2z8ULKGCQaNKnsd8wA6lj44o1bXk9WlSP8scenREId0Eg4ZJ5xZXkHOzASpeXMll10M7z2918MbLlwiWrHS2nMVy+6uQc3VLrg+jaYIQJhbGCPIkQmDQUFF6t7N9zX9GI4uc+c+ylXE4aVNI29ZoJtuX6V6bCw9RrZLXx64KVauxD0FvFdpDx5h6lbym7ucH2oL+0VjrCYfp6ndtPsYskIHJAQzaVPIWkWVHiSdHlPq/l7w9z6l5Lvw+OqKEXlJLhgINCyntrvA1If/MIefmm0mDtIke3VodXPbVXr7A0JbcMqmkwXbbuhB6PyzugUFDrtwnbGWpOtNuJC1ed9neqqOplrwF8SrLb1Fv94TbmqDsGJN6lbzNeYfhsNt7fr9axG80bTe6r+rA6IRBXK2S28LBkyNK7W9c57PFLW78pYhCugkGDRXQZldYokc5j5ublPxo55n7K233PTp+q4M3Xr5AS7r5fktudzw2+S0kU71oGZPwkbSUC97vbCWqzjQbRa993WV7q+T5WWt/43ofxTIc3tt+NpgPfO2uUBvY+9CgkuNwmZHn3IV15fVuVviZx9iIs0CG7uMVRqdlcthFiByHVOTBEaW+lnywyvKYU4zYB99l144HR5TQdWrJUKBpIaXNFWLromNKm0LSuHPO5a7TfXci9nxqq4PvLy8ljdLl8wxuyb0J4pPu76rdtxNNloRPpClXfr+zFag602q0BqjX87LeqqOllnyIYRmOFjkEuCPDhDudueeVKnk/Xykog0SOaIyd6qOSwaJBJRueM3Mcbc+NKNXfS544RdrdN4Vm/lREId0Eg7ZJZx70OokrrOGkmBDabU6rfWeHTTp/dvB/yw5+vvypeb1tRrfkyS4J48R4EiEwGD9s5ag602oUffnC/c90/wRreI46lWxFsJnT4kb2nNEDTItKPk9iR7TlnvwJxcWhAWByAIN6lVwjks+j7bERpaGWbMTavxVRgkqmlgwF2hZSWlxh8zPZoSJNSuleMQVQQlOjg7dePsfwlizaZaQYz+IeGLRpuy5hK0PVmUajNbmT7VforTrqa8lVKW2y7JGJegOFO50mlVywTeYH4nIn6K0HovuqDoxOvUoup0TCebQ9NaK01JJ3q8UJfy2ikG6CQWOS1OAKfunm4QPTR9TzGh289fIZgiUbnK2DJfPP2fakd9NoSfg8nhC2dKrONBrJYZcEpLdKnh+mRiXn3uGJZN1DXSLxsNy9tKnkC7m7dsLwmf4A4xVGp1ollxKijWS0PTSiNNWS80vLfy6ihG5TS4YCzQsp1a6watWio0gbI93MhbNMaGp18MbL6zzAkt+5B839RZo+sLgHBs25cpewpVF1ZrlRdOMmA+ToXZurriXnYteJNJKlq6BjhTudVpWsTnrFB11H+sqF4fx2UMlgEIZyjUquXHdLR9szI0r9b1wLaYD4kxGFdBMMwqTTNkRqXWGNQUVPqWkzoeq7wkmNDt56eY326buDJfe/yLgxWIgnEQKDdm3XJWwpVJ1pNVoexsVtuztbeJKK37hWA5eCViw5hvf4G5BjM7/iFpU8PeZpjJup+7H912DTgA6fuAaDylpypUhWR9sTI0pjLTlwnjRNx3tiRAmvkloyFLiykFLpCrK4XfaspU1FupkIWcMDGx289fIpD7FkopPHC2Us7oHBFW3XJWwlVJ1pN5q8+MLNFXqr5Ka/l3yZ768l7v08I6GdmEdrm0qe+JbwPj1n1YNOZlns8oyEdoIlVDCo/sT1KzwvorR9L1n4/o2PWfmcz4sopJtgcG3SqXOF8BdXPGPIlALEwFTjga0O3nj5M8+xZLzndMkhQxmJEBhcS4T6hK17+HbykO61ufBCblfJz+OaSv77MDmAwVtU8vO4UEv+CIJKppYMBVhI8QJLeoElwYBc2YvelnxPLfl5oJJ1uq/qwOigklUu1ZI/ANJNMCDd9CJYEmfzAEuCAWHLi+6WnO6PSk5BJevg+WCASlahlqwTPl5GLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGATPQSUnNP/G9YdAugkGYdJhiHjA9O0FlgQDhogX3dcbpvvX/Mb1p4FK1sHzwYBasgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOnyIBA1SyCt9L1iHdBAPSTS+wpBfBkoQtKECu7EX3sDXdH5WcgkrWYZoFA1SyCrVknaCSqSVDARZSvMCSXmBJMCBX9qL3egO1ZB1Usg6eDwaoZBVqyTqkm2DApONFsCTO5gFjEgxIhLzo7mzT/VHJKahkHT5FAgZMDirUknX4XjIYsJDiBZb0AkuCAQspXvS2JLVkHVSyDp4PBsFzUMkJ/Ma1DukmGIRJhyHiAdO3F1gSDBgiXnSvzU335zeuU1DJOng+GFBLVqGWrEMtGQxYSPECS3qBJcGAz1160Vt1UEvWQSXr4PlggEpW4XvJOqSbYMDSrBdY0otgScIWFMDZvOhuyen+qOQUVLIOng8GqGQVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XgRL4mweMCbBgM9detHdktP9UckpqGQdJgcwQCWrUEvW4XvJYMBCihdY0gssCQbkyl70tiS1ZB1Usg7rY2AQPAeVnMBvXOuQboIBFVAvSNy9YEyCAeUCL7qHren+/MZ1CipZh2kWDJgcVKgl61BLBgMWUrzAkl5gSTAgV/aid22OWrIOKlkHzwcDVLIK30vWId0EAyYdL7CkF1gSDBgiXnS35HR/VHIKKlmHT1yDASpZhVqyTlDJ1JKhAAspXmBJL7AkGJAre9FbJVNL1kEl67A+BgaoZBVqyTqkm2DApONFsCTO5gFjEgwYIl50X2+Y7o9KTkEl6+D5YIBKVqGWrMP3ksGAhRQvsKQXWBIMyJW96G1Jask6qGQdPkUCBsFzUMkJ/Ma1DukmGIQkiSHiAYm7F4xJMCBX9qJ72Jruz29cp6CSdZhmwYBasgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GqGQVvpesQ7oJBkw6XmBJL7AkGJAIedG9Kj/dH5WcgkrWYXIAAyYHFWrJOkElU0uGAiykeIElvcCSYECu7EVvS1JL1kEl63Rf1YHRQSWrUEvWId0EA9JNL4IlcTYPsCQYELa86G7J6f6o5BRUsg6eDwaoZBVqyTp8LxkMWEjxAkt6gSXBgIqSF70tSS1ZB5Wsg0oGg+A5qOQEfuNah3QTDKjbecH07QWWBAOGiBfdLTndn9+4TkEl67A+BgbUklWoJetQSwYDFlK8wJJeYEkwQCV70duS1JJ1UMk6eD4YoJJV+F6yDukmGDDpeIElvcCSYEBFyYvulpzuj0pOQSXrMDmAASpZhVqyTlDJ1JKhAAspXmBJL7AkGJAre9HbktSSdVDJOqyPgQEqWYVasg7pJhiQbnoRLImzeYAlwYBEyIvuE8B0f1RyCipZh4QFDJgcVKgl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlkHzweD4Dmo5AR+41qHdBMMwqTDEPGA6dsLLAkGDBEvun+Cdbo/v3GdgkrWwfPBgFqyCrVkHWrJYMBCihdY0gssCQbdtd2fobfqoJasg0rWwfPBAJWswveSdUg3wYClWS+wpBfBkoQtKICzedHdktP9UckpqGQdPB8MUMkq1JJ1gkqmlgwFWEjxAkt6gSXBgFzZi961OWrJOqhkHTwfDFDJKtSSdUg3wYBJx4tgSZzNA8YkGPC5Sy+6O9t0f1RyCipZB88HA1SyCrVkHb6XDAYspHiBJb3AkmDAQooXvS1JLVkHlayD54NB8BxUcgK/ca1DugkGYdJhiHjA9O0FlgQDygVedK/NTffnN65TUMk6TA5gwOSgQi1Zh1oyGLCQ4gWW9AJLggG5she9LUktWQeVrMMnrsEAlazC95J1SDfBgHTTCyzpRbAkYQsK4GxedLfkdH9UcgoqWQfPBwNUsgq1ZJ2gkqklQwEWUrzAkl5gSTCgouRFb9VBLVkHlayDSgYDVLIKtWQd0k0wYNLxIlgSZ/OAMQkGDBEvuq83TPdHJaegknXwfDBAJatQS9bhe8lgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp8iAYPgOajkBH7jWod0EwxCksQQ8YDE3QvGJBiQK3vRPWxN9+c3rlNQyTpMs2BALVmFWrIOtWQwYCHFCyzpBZYEA3JlL3qvN1BL1kEl6+D5YIBKVuF7yTqkm2DApOMFlvQCS4IBiZAX3Z1tuj8qOQWVrMOnSMCAyUGFWrJOUMnUkqEACyleYEkvsCQYsJDiRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XgRL4mweMCbBgCHiRffa3HR/VHIKKlkHzwcDVLIKtWQdvpcMBiykeIElvcCSYMDnLr3orTqoJeugknXwfDAInoNKTuA3rnVIN8GACqgXLHJ7wZgEA5zNi+6WnO7Pb1ynoJJ18HwwoJasQi1Zh1oyGLCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWYXvJeuQboIBk44XWNILLAkGfO7Si+6WnO6PSk5BJeswOYABKlmFWrJOUMnUkqEACyleYEkvsCQYkCt70duScy35//3v/0BkssX//s//hiD4j2xAYLFLMAuTAxQIQ2SKKLjOgSWi/MgWTCwRJSyq/LcMHQCFeYgQT15h8bX/wZIvs7Mki3tQYBohs7TC2a6zeFuwZE/VMatkgAbIaaGAjBKAamToACjIIAEYCxmfAAoySMCFnqoDlQytoJKhgIwSgGpk6AAoyCABGAoSISggowRcQCXDk2BygAIySgCqkaEDoCCDBGAsZHwCKMggARcGUMn/zf/W/8l/2OX0P/lv+j8ydgAUZsdZBgv/2/4XzcL/jv+brSJDB0BhHiO7IcP/2v8n/2HJl/8n/wU7yvgEUJjHiAwa/vfK/2Y7ilW7EDrAb1wnzL9x/X9kA1b43T4wCEGN37hOmH/jmr8ElcDfSwaD8MN3TDoe8MvMXmBJMCBX9mKI37hGJSfwl6B0ggTC86FA8BxUcgIqWYd0EwxCksQQ8YDE3QssCQaUC7wIztbVktP9UckpqGQdJgcwYHJQ4e8l61BLBgMWUrzAkl5gSTAgV/aid22OWrIOKlkHzwcDVLIKtWQd0k0wYNLxAkt6ESxJ2IICfO7Si+5ha7o/KjkFlazDNAsGqGQVask61JLBgIUUL7CkF1gSDMiVvehtSWrJOqhkHdbHwACVrPJ/Q0ShlpxAugkGpJteBEvibB4wJsGAIeJFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSfwvWQd0k0wYNLxAkt6gSXBIAwREiEPujvbdH9UcgoqWYfJAQyoJatQS9YJKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlmHT5GAASpZhe8l65BugkFIkhgiHpC4e8GYBANyZS+6W3K6Pyo5BZWswzQLBqhkFWrJOnwvGQxYSPECS3qBJcGAXNmL3paklqyDStbB88EAlazC95J1SDfBgEnHCyzpBZYEA2rJXnR3tun+qOQUVLIOkwMYoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdVgfA4PgOajkBL6XrEO6CQakm14ES+JsHmBJMAhDhETIg+6qY7o/KjkFlaxDwgIG1JJVqCXrBJVMLRkKsJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGKCSVfhesg7pJhgw6XiBJb3AkmDAEPGiuyWn+6OSU1DJOng+GKCSVagl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlmHT5GAASpZhe8l65BugkFIkhgiHpC4e4ElwYBc2Yvulpzuj0pOQSXrMDmAASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWQfPB4PgOajkBGrJOqSbYMCk4wWW9CJYkrAFBSgXeNE9bE33RyWnoJJ1mGbBgMlBhVqyTlDJ1JKhAAspXmBJL7AkGJAre9HbktSSdVDJOnzXAgxQySr8xrUO6SYYkG56ESyJs3nAmAQDhogX3VXHdH9UcgoqWQfPBwNUsgq1ZB2+lwwGLKR4gSW9wJJgQEXJi96qg1qyDipZB5UMBqhkFb6XrEO6CQZMOl5gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfgUCRgEz0ElJ1BL1iHdBIOQJDFEPCBx9wJLggHlAi+6q47p/qjkFFSyDpMDGDA5qFBL1gkqmVoyFGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgq/ca1DugkGTDpeYEkvsCQY8LlLL7o723R/VHIKKlmHyQEMUMkq1JJ1+F4yGLCQ4gWW9AJLggG5she9LUktWQeVrMP6GBigklX4XrIO6SYYkG56ESyJs3mAJcGAsOVFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSdQS9Yh3QQDJh0vsKQXWBIMGCJedLfkdH9UcgoqWQfPBwNqySrUknWCSqaWDAVYSPECS3qBJcGAXNmL3paklqyDStbhUyRggEpW4TeudUg3wSAkSQwRD0jcvWBMggGJkBfdVcd0f1RyCipZh2kWDJgcVKgl6/C9ZDBgIcULLOkFlgQDcmUveluSWrIOKlkHzwcDVLIK30vWId0EAyYdL7CkF1gSDLpXQP8M3Z1tuj8qOQWVrMPkAAaoZBVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQd1sfAIHgOKjmBWrIO6SYYkG56ESyJs3nAmAQDhogX3VXHdH9UcgoqWQfPBwNqySrUknWCSqaWDAVYSPECS3qBJcGAipIXvVUHtWQdVLIOKhkMUMkq/Ma1DukmGDDpeIElvQiWJGxBAZzNi+6WnO6PSk5BJevg+WCASlahlqzD95LBgIUUL7CkF1gSDMiVvehtSWrJOqhkHT5FAgaoZBW+l6xDugkGIUliiHhA4u4FlgQDEiEvuquO6f6o5BRUsg6TAxgwOahQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZxALVmHdBMMmHS8wJJeBEsStqAAn7v0onvYmu6PSk5BJeswzYIBtWQVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFX7jWod0EwxIN70IlsTZPGBMggFDxIvuqmO6Pyo5BZWsg+eDASpZhVqyDt9LBgMWUrzAkl5gSTCgouRFb9VBLVkHlayDSgYDVLIK30vWId0EAyYdL7CkF1gSDBgiXnS35HR/VHIKKlkHzwcDVLKKXy35b/kftWQwYCHFCyzpBZYEA3JlL3pb8lot+ffrJyQ3U9e/6vK+2P6rsn133qOSv7/EjD9fVVWmzYy9ilJ8igQMwgC9XyX/52kRxa2W/PuP/ENjisyzWX6+vmTP6JBugkFIktqHyDq5vugKL0y6X41T5e2fNbmWbnpbcsp2Hv/Vk2tjEj6Ia+UCL2dr43tNHH6qbjv1cvVl2VWi9fInuquO0PU2lfy9PO/KjxXxxECRRwTIdpV8fMiKsZDYUfbnGMKMrI+BQfPk8DuP5xXZW+KJEcWtlvyTtdDvHLVWnuGnQSVTS4YCFxZSvp1c4aVI8z3duEX3TvdK84bjgxhY/etpSblA5O4FgZthcQ8MLuTKPs52jFkVUuTsm8YprQqw8fIpvVVHey35ZKGZUsT7TU5omjk6Mb/YFpV8GgnmQDhJg5mSYQYxIyoZDJpV8jyaN2RvHsUVHqCTvX7jenp4+deZ82R0YTrqAOkmGLRPOk6ucE4HGyfd+Yz6G8+dTkJZ+ih5zHsFS7Y5m5MlE0NOPCE6ZSERAoP2CqiPs52uYl7iWxruKfVb8+WScpEmexo9p7uzhT43qGTtkSfyj6AG+fGT2rnbLSp5fq4Na2hqI20ia8dRzNj9sw8wOq0q+Ty0ZXeWh0YUp1pymNLkn0fStYOJB7hq6Da1ZCjQupDi5QovRhrpRe0SXkxWT6mD2okMckqeTpbU8vBAj3V+J1jcA4NWbZeuyU1cCFtyZuSiFMlFrYwvZ/uZuXyT6/dWyY215MwjT2SMmjmh5yNXMc9NDSr5/JzloZmbNbKGGcaMLKGCQaNKTtbdZH+OkJ4oDD8onb6XHK4i/zyQWb4cf/mAdBMMGicdL0324qS7eqRsW8TbXVfJ9gP2sWTGkBOvx8NeBEsStqBAo7PlZvBXw5avFGn05dxDNVmmf20udLhaJedNlEnHsid0feYKGlVyMtaKQzM/Mic0O45jRlQyGDSq5GRsy/4MWVcYPWXxqSXPjy//3pMPKaPL5PBE1JKhQNtCSj4xa3OFFyfd1SMrs9x4u/PV61VyRb+6WDJryInH5hIs7oFBm7bzmsH9pIjW95IvK/1svXyG3qqjqZZ8iJo/8iNnK8pssG8xtT9sSpNBaVTJyeApDc385DOT2nEgM7Z+nBY+jjAs64dI6gxyQGdfSX5WRHGpJS/Wko0d58i8t8ur97wZ0k0waKrbHRKzF1zh1UlX2hqlnJVVDMv2Sr1Krni6pnTTyZL701IGj9pZKBeAQdMQcZvBE3crBqBD6+Ndtc6feyn/EtJ+7tO1isvn6O5sobu1Kjm0XYi/573/Tbb0MbYwu7bf7DR2jaNNJZ9Gy0RpaO5bL7+jHn/9fSbJB0YyI5MDGDQtpKQiuaiSHxxRXGrJ83MqFtqMEP8wwxaYB5egYSKllgwFmhZSnFzh1UgTG1dOluvtkkyzWiWXUo5IB0tuhoym/D38ku/YUTsLi3tg0JQrl5ytJeHerhMpxYWdI6633V0h8U3ZP7FGxd0lEn8wLp/Euhy9VUdLLXl7vv3jbXvPNt0y4F37LWhW26gH8/tt+fWuyPxoxaG5Gzo7E+xGz2k8DGVGVDIYXP24QfQL2dQwXGHohMvjN64lRsjWxho79q6p7hwP0k0waJl0nFzh1Ul3Pb/S44MXBNp9dU0nZLtIsGStszlZUtpP7E7Z59YvxsROkAiBQUsi5ORsB+TkghTZotz+DluYO9937dDBafW9E62Xz9L22fUbCL2tVMmhaeDU3+2pZUdktd4he12bD50a3aeSs4NkG2zHbN8w43tHD5MDGNyokodyhUYcask5C62z0dEAurVGI/SSWjIUaFhIycSCZlcwIo3Vm7Vh5f3i7dojWNud3m/Jtf0phV4vP3YemIXFPTBoyJWdnO2InFtTsDvJ2/W+p3Nl7/mpNl+WHULr5bP0Vh0NteT4bEl3M+umORu1LrN2Ye78LSp5NUtiR/2IacZLHnSV7qs6MDr3qWTTFUaOKA7fS56fcUI2V2R34pjZiD0SpJtg0JAkzeN94kVXeDXSSKvaNHC9nWw30PZg77ektE4ttv2RqZGjdpZgScIWFGjIlWc/mHjR2Y7IufkYtKrbxAP1+2Z7o4fFfLBsfazeKnk2ZZ1KDi0DaVCLD318H3FvouLWlyPbIzLPW7eoZGmgvfVoscPZY5mx+3iF0blPJT86orxeS17Dg2xH4tOnfhnPqEzWuxD6SC0ZCtQvpHi5wouRJp5eOVO+sMq39qfu1LdbctX/aeRbuz5y1M7C4h4Y1OfKXmHriHlqdM70tnqYk30FBXhQkq2Xz9O7NldfS46hXOmt+tB5G602bZ8U3sbc+ztU8jptyPYBZXYdzIyoZDAIQ/IWlVzhCi+p0Ht5uZa8Ro6zhWSvcvH87DsOpJtgUF+3m0f7xIuu8GKkaVW9yrRfi5xZm0XXT9/LZV+2pLRV+/fC4kB/SITA4O3OdkJOzYeGgoCIh/YntyrAxssX6O5soa9VKjnOHNqDxWP7qSMaQjb3qDYdi/mJ7lDJclyfGRTDDGZGPnENBrfVkp8dUV6tJa855fkh4wEt5DTORj0IKplaMhSoXkjxcoXXIs3qqZXeHu92YV6NMbM27r3bkrF/+qM9IDplYXEPDKpz5ZtmcPNMaaAGDzm07390Zu2C8dg+5Mmu2ssX6K2S62vJhZljfc076VcyqWrTsZh7eINKXmdQ2T4RjbwassqMquK+B5ZQweAulTyaKzTy6m9cx9AwIXsE2anbTY4N7LKkm2BQPenMY31CNo/IsYoLvRhpoqdWOt2aErQHh+ZTgyWrnG257MuWLOf4ccVh4OiUpdqS8Km8O2ydkTNzUqQozqPn7m8bnVk2DygKsPXyBa6mlG6EvtapZEE2D8RwtzNIyaT2C+zOPBfeoJIVS+1J5ufRzIhKBoO7VHKVK1SFsi68WEuO1gnIroVyRLGM2p/wWqklQ4HahRQvV3gt0sSzK6fJ2OkrsaHxVqNZMppy4OiUhcU9MKjNle+aweXErDr4EkWnBh7Fc6V5rQJsvXyB3qqj5e8lFwhXmdjZSPZknm345G3u4A0qOT54bvFXDq+ny/YwZqz+FAl8KnepZDn81Ijy2veS16pRQPYt/Ed2Zi4tR7NTZXdIN8GgNknycgVpeC3StNZ3w/gPXJhVW281miXHD9p5KBeAQW0idNcMfvnEQKtrSvPam7Vdvruzha7eoJKjFTJvPi49DPuR67n/N6hkaw1FjschMZwZmRzA4CaV/PSI8lotOcaNGdm3IPtyTnkKKOMROkgtGQrULqTMI/11V3gp0qzKtdLVo2NfcVA5tSGqvNmSSoXpwPBBOw+Le2BQmyvPLvC6syUs56GSX+euWrL1apfDF9/gG5jf4h21ZEE2E052G86MqGQwCAPyBpX89IjyUi1ZHl6QnTMxK89duXW2ezukm2AQJp2KIeLlCi9FmuiplZNkezl4Iz5Pw3xcOX17WfJXsp3cdaz7DAyJEBhUfu7ythlczruWEbXeVZrX3qzt8t0/wRq66qaStzVB2ZF9tMuv/k3M/btBJVucZuhlayAzMjmAwU21ZDn62IjySi15zaUXZO9MfOzsleX4sKsHQSVTS4YClQspXq4gzS5FmnU5S7YNYjH1inuu5zZozDdb0oJaMvxdKnPl25zt6nkz0qvqXH9pXu3JbZfvrTp8asnJvBHTuuwbGn0VcX6iDir5ePp4Zuy+qgOjc49KfnxEeeU3ro+l5IOF4iHZTDmtuw0H6SYYVCZJTq7wSqSJh2odPQz+wBXvjOe2pBrBkhXO9q6gUg75Q1NpSfhc3hu2UpbTmuLDRuPJrZ4szSsv31slz919WSUn79E2mjR4vYx9D2Oo5PHM2H28wujco5IfH1FeqCXHeTQiu2dkVz7e2IbrS3g4aslQoHIhZR7mr7vCC5FmFcmVfh4d+8qMupaSZbuK91rSZPTYVIDFPTCorCjNHnCHs8lp+QsXiNGldlm/Uck3Xr53bc6nlhwuMrG9D9toS4Nrr/ANzCPz/Sr5NHrGMyMqGQzuUcmPjyjXv5e85t4xqZb9gUJdSxg9EyXdBIO6ScfLFV6INNFBK2fI1srzATm17dz3WtLENvWwkAiBQW9nk9MuJUSt95TmtfdqvHx3Zwt9fVUlx8lhW0G1w59TnL2LuXvvV8lydrTkeGbsvaoDw9NLJQ8eUa7XkuenmvhSnrDim33SYtTVg/BiqSVDgbqFFC9XuB5p4v7aECStL7lmvFfbZPxeS1pce4YxYHEPDOq03X3OdvG0QJTutZ4pMbM2v2m9fG+V7FFLjibaPYfsKbyg3EwzCHP33q6S18Vl2ZatgczIEioYhOHor5Ll4HMjyuVa8hZelSeseGhpcS0i3Q/pJhiEScceIl6uYDfK3GmdvSu9XMmbqmm9l1A3fb8rqEQDjBqaStSNSfhg6soF9znbxdMmbo5kzcHrauHFjdDZ11RyNNHumU8fHNaoWELpyTx2366ST9PGgGZEJYPBLbXk50eUq7Xk3cqZYiGJGCWXrGjSk6CSqSVDgbqFFCdXuBxpttzv92u+0c+/xSxAOjP15utnaf9VHx7iyY15xlstabGLbM+DxT0wqMuV73O25awLUiTGt9o7xmBUipk7Wi/fX3W8Wkte5oOZ3WP8R3bJpkYMkXWGfTtdVPJ5jWVAM/KJazC4RSU/P6Jc/Y3r+ZkmpoiiWEj2lMKNR0J7I6SbYFCXJM2j/HVXKIahBT3SrJnQlhJN/84K33Wy3zevzRvWk2W7lroK6HLp24NKfPBH5hOUC8CgLleeXeAWZ1vOqg0pkd8YACdq0hVdAWZpvfxMd2cLvb2mkr9kCVTYP0XFTHPxHb6L+QnerJLXNZZ48oBmZHIAg1tU8vMjysVa8j6VVIwge0rPXGO6joQHpJYMBeoWUuZB/rorXI008bwzudlSDidUhQhp2xxP3mpJgzV5lO1nweIeGLgt7l10NjmrdOUjv5Okk5NmrOhSUIAarZff6K06rteS1+XMhcNDXJ1pxmF+gjer5BB4Z+Iay4BmRCWDASpZ5dr3kuNzzw+uGEH2lJ65xnQdId0Eg7emmxcjzSkd2qNmg4d88UDF9Br72DwT907cd2y1dNnxLEiEwKC3s8lZpSsfOcUkK1kpKUCNxsvv6P4J1tDfSyp5rXzOHJ9B7FF8sKVJwzt8K/PAfK9KXgfReu6AZmRyAINbVPLzI8q1WvL8RBPzlJJaSP+G5JHXE9pbCW+WWjIUqFpI8XKFa5GmIJLViLRO9gr5T2kL682aF93easkiW/ooOx4Gi3tgUKXtbnQ2Oas+HzoGJSsK7Vw4YKuCxsvv6K06nGrJp3BdM9PUtOnHPDDfqpI3e8qOIc3YfVUHRicMxy4qeeyIcqmWLI8kz5RaKAaN0nXjZNacUr8H0k0wCEmSOUS8XOFapImOqpNc7JA8pRiuGm/WnmRUpZtvCSrB7WfaH2IIqsYkfDK9nU3OuqaSzY6fglhF3xovv6O3Sp5N+Xot+fQm0lkkpaZNP96ukjdzbossA5qx+3iF0elWSx47olypJUeTiE1SC8WoUbpuTZuOhHSZWjIUcKuA1rS5FGm22VvnnA7IBbJIM51TVGjhrZYssRrgqckEi3tgUJUr3+hsctZFlWzL3kPQq7hL4+V39K7NuX0v+fDUySyiUNOmH+9WyZs1d4Yc0IyoZDBAJatc+I3rNSjIaamFalaia9p0hHQTDNyKMjVtrkSa1VEDX99zNlv6pZr9oZ+vuTffq/YNlO6+3uyCQwdLms7mZckCwelnBg3WNiRCYFCVCN3obHLWNZVcMbrXQLRg9q7x8ju6O1vosMP3ko/zwHkW0ahp0493q+R1BO3tMaAZ+cQ1GKCSVS7UkmNQiE+UWujGleh3ER6SWjIUGL6WHB11YtG8Czvhe7jcLr382SUK37vLFHoYW12Jc4PUkuPZl1V2f1jcA4MqbXejs8lZV1Wy2ffNixes7jVefkdvlfza30v+zvz1K7FH8cFq2vTjzSp5HUAHcwxoRpZQwQCVrNL+veQ1tsq2YqEbV6LfBekmGFRNOl6ucCHSbKr3/EFCaTixTwj0vRO7vFP2pKw3u+LPb7Vkls1el04fgmBJwhYUqKoo3ehsclabFPlu+/vHOQWYo/HyQvfaXOjuZZUc2Ky0rSUUE17hNNMMxvwEb1PJmw1lx8KAZkQlg8EtKvn5EaW5lrzmkuvkoxhB9pTCzcWV6HcR3hq1ZChQt5AyD/LXXeFCpJFNLfSsh3bX27RwklZuh7KPIccbMwzhrZbMIudefIYxYHEPDOpy5dkRbnE2OavZybbPtNQN8BgxKzvYevmJ3qrjtVryzBbZZUfdTCNNBg2U8xO8SyXn1lYHNGP3VR0YnTAcu6hkaTJoRGmuJcfJZHM3xQiyp/TMNabrCOkmGNTV7eZB/rortEeadfrWJsY1Jdz6FUb8jBINtlRAdpyJ3bvmzm6J+ytBZX3+JycSlAvAoLezyVmlK2dQglYJRQEWabz8AM4WOvuaSt6MtD50+0wzGvMTvEklbzPjaS1mQDMyOYBBt1qyNBk0orTWklORrBlB9pSeucZ0HQk5M7VkKFC3kDIP8tddoT3SxDP0eXFNCWV7PVsPBmkydWDNFRrrSsJbLZlhNcij84g6S8IHU1dRml3hFmeTs0pXzpEGrSJG0EpovHx31eFQS96Fbtled5RKJ9Lkyjt8A/PAfJNKllPSkwY0IyoZDG5Ryc+PKI2/cb3G1N0pioVkvim55AsJ7Tsg3QSDuknHyRXaI41sZc5IMsjYiUxHyxlkPHpxDg6WtJ3t1qASzxw2INVBIgQGbw1bCnLWpXwoxpnKk9dsRbYtGi/f/ROsoa+vquT1NcYFzjgzFBY8K5r0ZH6i96jkOGLScTCgGZkcwOAWlfz8iNJYS45RYe9sioUq5tiKJj0J3aOWDAXqFlKcXKE50sSt3JQvN12Px23ZPBMvpx5fD9Yvtx14qyVV1nz66iMMAot7YOCmki8623JWixTZISfX3vOsAC2keeXle6sOl1pyOlGct1OKOXF/3qeSQ7idUYaBHBnIjN1XdWB0blHJz48obd9Ljqn0wdeUJ6x4aGlRH5HeC+kmGNQlSV6uYDc63uk/spX1bTken+C0mRCvrl1PDl125vdaUuGviOTZkoQtKFCXCN3nbBdPW4gJiGxaWEuFZ9ou31slz6Z8WSUnr1o2Cza7uD7yLuYHeodKXleHtWlDjgxkxu7jFUanl0oePKI01ZK1z1urFrLn2Bhg6svY7yW8NmrJUKBuIcXLFaRRdaRZNgr3lebSIHYze/3YSyUri+dejnHvtaRCtMXjkwgW98DAa0nqqrPJadVS5Ejj2fZjHJHmdZfvXZvzqSWvNopJnW2zwXPa+QHeoJLLa6vjmRGVDAZhPPqr5MdHlKZa8vwkE8cwotlAduXjTYwwtbd+N6SbYFBZt5uH+euu0Bpplo3CbY8XtC8vDdIL6mtnLVRO38tdbggqf0YkkwiBRaW2m/3hDmeT0/IXLiJn147xGNZqOynN6y7f3dlCV/9X/n2d83JHtFl++UMaXHyFtzM/wBtUsjTPnDCeGXuv6sDw3FNLfnxEaaklx2Ty5GmahWRX3ifLZu1PUMnUkqFA5ULKPMxfd4XGSGNXeo4XtBfzlgZKixgWroe491oyIZ42bjSqhsU9MGhbknJ3tmOYasaOUwdaC95Nl++tkp1qyec3Yi5/XH3z72Lu3/0qOc57mTEwnhlZQgWDe1Ty4yNKw29cx2c9N9ce0ZxtluMvZNY3Q7oJBpWTjpMrNEYas/maQC4t7PQw12INC7J9gWDJCme7KaisD1AZB0em0pLwubw3bKVcPW+hNZ+S5rV3a7p899pc6Km/SjZtJkPjhYB/L/NLvF0lRytkh4AcHseMqGQwuEclPz6iNNSS5+eYOD+rZiFrtomZaV1A6kB4b9SSoUDlQoqXK1jNjpHGLqIcW8jZhUk012LZ/ZLEfLMlj2wiubbgNDAs7oFBpba7bQa/et6C1a0z0rz2bk2X7606bqolm0aQw8MKrrn/d6vkbdrITXzDmbH7qg6Mzk0q+ekRpf57yTELTx5FNYHsywWceM6w1RvSTTCoTZLmgf66K7RFGjuJjS2W+x41tkZGJcduvRLh3mzJI/HJX3qCUaBcAAZdnW1CzssHpiJWFDwjzWvv1nT57s4WenqDSjZWWKONLr7B+5k7eLNKrlhbHc6MTA5gcJNKfnpEqa4lxydJDaFaKFd5Epaj9ZPd2wn9p5YMBWoXUpxcoTHSnDZTjm6rOvEBaXC64JotvLLe9WZLHvhTIpnFPbCozZXvmsHlvIsZkR2njkjz2rs1Xb636qitJX/9LMjmmXRBVXZkTogRUzbHY36J96rkTSQX5j1pMYwZUclgEAbkDSr56RGlupY8P0YNS/NoNj2nTwPzaJBugkGYdGqGiJcrSMPKSGMkuefAFruRDwXS4NTPeNuXPLl2+r4hqAQ/n/kb6QOJEBjUlgvumsGNE/+d5Nz0/3KHz2HuS9rL5pmkm1PT8F/t5Yt0/wRr6GmNSg7tJoz11e1w+QQ5OG6Ymbt/r0qO46RohdHMyOQABjfVkp8eUWpryWtYMJETZEt/8rLRRiBkz9SSoUD1Qso81F93hbZIY+Z7clxSglipzmYIehyMWWhdWpnj3ZbciI/9Wi18HFjcA4PqXHl2C/8ZXE7MBRo5nBvEcnjtlNGP5LBs5wxgHD7SW3XU1pKNFY10piieEJuPGzDnl36rSq4SycOZsfuqDozOXSr54RGl8jeuoxUqkDPS2LsRbTawy5JugkF1kuTkCm2RJnpsbsqPx+MJspmNc3L41E/Z+2KAC5ascjbvoBLPGTlCN1FtSfhUqnPlm2ZwOTMXl0p3VRbzikFRuVrj5Yv0VsmzKSv+XvK6FCjbJ+Tg/klkl7b28MKbfxe3q+QtG5YdGaTRKGbsPl5hdO5SyQ+PKHW15PggNcgp0W7as8epauDUNHSRWjIUqF5I8XIFaVoZaWRPLnDJ0fVw7GQmRdAPl56sgbdbMiKn1KbF48PiHhhU58rezibImTmPi1fWj8c+rSGwVQE2Xr5I79pc9W9ch3YB9W1pFolWVZ6ubMAhmN/ijSp5y4aN4T+YGVHJYHCbSn52RKn7XnJ8kBrklPWcdMZZo4xsjwjpJhjUTzpOrtAWaeIuvYvJCWtP1AxR7+e690KyvOftlhSCk8/U3fwBkAiBQS9ni8iZuZyopM21+8qOWgXYevkS3Z0tdLVGJceH1p5Lf2bZl76lov0GYe7jfSp5tZg+Ve6RdoOYsfeqDgzPbSr52RGlqpYcH6QKOWc7SbY3ZL8dZDoS5ldqyVCgfiHFyxWkcWWkkX1q+Fl7tN1Y2bUhh07XSpPQa7zfkjOx+38odWBxDwzqc2VXZ1uRU7MxQ46rDZSAk++krgBlT+3lS/RWydW15NUOaW8zh9YS/ekNr81fXBe9lXlI3KeSpVXNMBnLjCyhgkEYk/eo5EdHlKpa8vx3BLLMzzghm3LONuecHTO3fyhIN8EgTDqVQ8TJFdoizeaYsmNjTS13E/168TQc/K6Xkh0L621l+zIN07eTJQOrEV7u/zg0jEn4TPo424acm5UYa6xJJfh6aBeh1iCUdkY91Hj5Et1rc6GvNSp5C3U/p6fOBn3dTNt1ZMeQzL28TSWvlqmxwVBmRCWDwX215EdHlOq/l5wnZ6E1Ah/Sti3jrpyL+hBUMrVkKNCwkNLuCl8T8s8dbZFG9qYRaL3MwWfXy5zjwZptnvIH2fli+Ji425JqJrk91dCBqA0W98CgIVf2ClsH5Nx8M2mQNlnve+j+Fv2yYevQT9lXe/kCvVVHdS15J4aPTx3CxcL5ObYzdke25rJjTOYRcZdKbrPBUGbkE9dgcKNKfnJEqfyN6xJZC23J+DZ/5TLu0Qivj3QTCrQkSa2usESPRH62RZpMbrSp4ZPjb53cJ5xbUnx62nid1yfeYMlaZ3Oy5GMCURuUC8CgJRHycrY9c5OS1+lhaHffY9jKRLn9ZWTPQuPlC3R3ttDZKpW8N9I/X/LYu8CuJG97s84nfO2av5Yw3s2dKnlvyAyHmWwkMzI5gMGNKvnJEeXGWvJhQpojz+8uQR/cXUPXqSVDgaaFlDZXiK0Tx2yLNPsp/d/ltvv7JunA7lpy+d/99Y8evqaVrwe4HpbcP1eG18JiF5osCZ9IU67s5Gx7pM059uzYueZy1xC3ZEfgdOo+yi1Ra2q/d+9l18r+8qIxS5fP01t11NeSk3D3s31RbkaJ4fuJ4kTPh65g7vk9Knk/TnIcrTOQGVHJYHCnSn5wRKn7jesiBQvJEY2xFw9IN8GibdKZB71O4gprOEnn67ZIc8qNTiQn7PNNhWM/47Wrk8o8HSxZtszC4CFKg0QIDNo+dzk7gk5L2NphtzmFobOiSzp/8uWff487zv08X/7UvN42bZa8gdDdir+XPFMMeOqyRvaM0QPMPA5vUck1IvlsnnHMyOQABreq5OdGlFtryYW0e/Q6TXih1JKhQNtCSosrbNFEduxoizRr4qqgnPCdvfrEsZ9rwiDbr/B+S5aec2X0GKXA4h4YtOXKXmFrQ5qUlHT+phNK34venPaz9fI5equOllpyaSr4ySwHZsza85GruE8lV00bZ/sMY8buqzowOmFg3qeSHxtR7q0lZxffhi/TkG6CQUiSGoZIgytswUR27GmLNPmMUM8FsnnAOZWS3S6e3Jhuvm7JqprA+EEqpXFMwufxdmc7IU1KKvn4gekj6nmNCrD18hl6q+TZlNUqOTsV5B9BPWP8qHibSs4Pmz2JPUcxY/fxCqNzby35sRHl3lryhBZZHuCqQSVTS4YCzQsp1a6wJn3q0cZIk5nacydkcqlzT2LV2cWV323JOpFMLRn+IM0VJaewFZE2hhzNRK1c2MpErWxPGi+v07s211ZLnlhf0I5cIXkmXU4oNh+E+TFvUMmV00Y6JAYxIyoZDO5WyQ+NKHf+xvVCGppb1mt7QboJBu2TTq0rrNNx5nBbpNE+Rl1ywbSX6vWXZi4hLliyzdles6RiEI0HhO8zJEJg0C1sCTVtJtQvfxROUqJWKSy2Xl6ju7OFPreo5NRKZvePdoo/pjY280P6q+RKkazadAgz8olrMLhdJT8zotxeS544huavRySf4VVSS4YCVxZSKl1BSiPZKa0x0pxTQqv9sZfZZHO6qk+Me7MlT9bIQi0Z/h5XtJ1T2JpZ2lREjnPUslatTlHLesjWy6f0VsnNteTAt/zZgp+fygT1+yue4BPs72ceCFdU8p0MYEaWUMHgqkpu4nkRxeF7yRVMZlns8gyJPEG6CQbXJp06Vwh/caUYQ1ojze62NeJvd/lCN7+d5tyulvxTBEsStqDAtUSoj7N9x7uWbxtpVYCNlz/TvTYX+t6qkj+AIVXyAKCSweAtKvl5ONSS/yRh9qSWDAVYSPECS3qBJcGAXNmL3pa8VEv+AFDJOt1XdWB0guegkhPeU0t+HqSbYEDdzgsSdy+wJBiQK3vR3dmm+1f/veQPApWsw+QABtSSVagl6wSVTC0ZCrCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWcXhN67/JKSbYMCk40WwJM7mAWMSDBgiXnSvyk/3RyWnoJJ18HwwQCWrUEvW4XvJYMBCihdY0gssCQZ84tqL3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXdLTvdHJaegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRe/aHLVkHVSyDp4PBsFzUMkJ1JJ1SDfBIEw6DBEPmL69wJJgQLnAi+7ONt0flZyCStbhE9dgwOSgQi1ZJ6hkaslQgIUUL7CkF1gSDFhI8aK3Jakl66CSdfB8MEAlq/Ab1zqkm2DApONFsCTO5gGWBAMqSl50t+R0f/5ecgoqWYeEBQxQySrUknX4XjIYsJDiBZb0AkuCAbmyF70tSS1ZB5Wsw/oYGKCSVfhesg7pJhiQbnqBJb3AkmDAEPGiuyWn+6OSU1DJOng+GKCSVagl61BLBgMWUrzAkl5gSTCgouRFb9VBLVkHlayDSgaD4Dmo5ARqyTqkm2AQJh2GiAdM315gSTBgiHjRfb1huj8qOQWVrIPngwG1ZBVqyTpBJVNLhgIspHiBJb3AkmBAruxFb0tSS9ZBJevwKRIwQCWr8BvXOqSbYEC66UWwJM7mAZYEAxIhL7pPANP9+Y3rFFSyDgkLGDA5qFBL1uF7yWDAQooXWNILLAkG5Mpe9K7NUUvWQSXr4PlggEpW4XvJOqSbYMCk4wWW9AJLgkFvbfd36O5s0/1RySmoZB08HwxQySrUknWoJYMBCyleYEkvsCQYsJDiRW9LUkvWQSXr4PlgEDwHlZxALVmHdBMMwqTDEPGA6dsLxiQY4GxedK/NTfdHJaegknXwfDCglqxCLVknqGRqyVCAhRQvsKQXWBIM+NylF71VB7VkHVSyDp4PBqhkFX7jWod0EwxYmvWCCqgXjEkwYIh40d2S0/35jesUVLIOng8GqGQVask6fC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1sHzwQCVrML3knVIN8GASccLLOkFlgQDEiEvun+Cdbo/KjkFlazD5AAGTA4q1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOt1XdWB0guegkhOoJeuQboJBSJIYIh6QuHvBmAQDcmUvuoet6f6o5BRUsg7TLBhQS1ahlqwTVDK1ZCjAQooXWNILLAkG5Mpe9F5voJasg0rWwfPBAJWswm9c65BuggGTjhfBkjibB4xJMGCIeNHdktP9+Y3rFFSyDp8iAQNUsgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW+VTC1ZB5Wsw/oYGKCSVfhesg7pJhgw6XiBJb0IliRsQQGczYvu6w3T/VHJKahkHTwfDFDJKtSSdaglgwELKV5gSS+wJBiQK3vR25LUknVQyTp8igQMguegkhOoJeuQboIBdTsvSNy9wJJgQLnAi+7ONt0flZyCStZhcgADJgcVask6QSVTS4YCLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpW4TeudUg3wYBJx4tgSZzNA8YkGPC5Sy+6W3K6P79xnYJK1mFyAANUsgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFb6XrEO6CQakm15gSS+CJQlbUABn86K7Jaf7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMKCi5EVvS1JL1kEl66CSwSB4Dio5gVqyDukmGFC384Lp2wssCQYMES+6W3K6Pyo5BZWsw/oYGFBLVqGWrBNUMrVkKMBCihdY0gssCQaoZC96W5Jasg4qWQfPBwNUsgq/ca1DugkGTDpeBEvibB5gSTAgEfKie21uuj+/cZ2CStYhYQEDJgcVask6fC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1um+qgOjg0pW4XvJOqSbYEC66QWW9AJLggG5shfdnW26Pyo5BZWsw+QABqhkFWrJOtSSwYCFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE6gl65BugkGYdBgiHjB9e4ElwYAh4kX3qvx0f1RyCipZB88HA2rJKtSSdYJKppYMBVhI8QJLeoElwYBPXHvRW3VQS9ZBJevg+WCASlbhN651SDfBgKVZL4IlcTYPsCQYELa86G7J6f78xnUKKlkHzwcDVLIKtWQdvpcMBiykeIElvcCSYECu7EXv2hy1ZB1Usg6eDwaoZBW+l6xDugkGTDpeYEkvsCQYkAh50d3ZpvujklNQyTq9V3VgeJgcVKgl61BLBgMWUrzAkl5gSTBgIcWL3paklqyDStbB88EgeA4qOYFasg7pJhiESYch4gHTtxeMSTCgouRFd0tO90clp6CSdZhmwYBasgq1ZJ2gkqklQwEWUrzAkl5gSTAgV/aityWpJeugknVYHwMDVLIKv3GtQ7oJBqSbXlAB9YIxCQYMES+6W3K6P79xnYJK1sHzwQCVrEItWYfvJYMBCyleYEkvsCQYUFHyorfqoJasg0rWQSWDASpZhe8l65BuggGTjhdY0gssCQYMES+6rzdM90clp6CSdfB8MEAlq1BL1qGWDAYspHiBJb3AkmBAruxFb0vOteT//a//81//h/+W/5b/LSpZNvhv+W/6H58iAYPgOf+zOE4ygj74v7mW/Hve++n//df/Id0Eg5Ak/Us8eeU/+R+WfPk/+d9iSYAsS648Dxf+u/xf+N8QKhmggf+WsQOgIKMEoBoZOgAKMkgAxkLGJ4CCDBJwoafqQCVDK6hkKCCjBKAaGToACjJIAIaCRAgKyCgBF1DJ8CSYHKCAjBKAamToACjIIAEYCxmfAAoySMAFVDI8CVQyFJBRAlCNDB0ABRkkAENBIgQFZJSAC12dLXTg3//AifCbMv/8r2zASvhFAn60AgoEz/l/MlxgJfyW8z//IxuwEiIKv3ENBcKPt/y3DBd4heBsWNIDwhYYzENEhgu8Qm/VMdeS+UtQCfwlKJ0wXvmNaygQhgh/CSph/ktQ/L3kBP4SFBj0/onTvwOW9AJLggG5shfdLTndH5WcgkrWYXIAA1SyCn8vWSd8ageVDAX4Y2FeYEkvsCQYkCt70duS1JJ1UMk6eD4YBM9BJSdQS9Yh3QQDJh0vgiVxNg+wJBgQtrzobsnp/qjkFFSyDp4PBtSSVagl6/CJazBgIcULLOkFlgQDPnHtRW/VQS1ZB5Wsg+eDASpZ5f+GiEItOYF0EwxYmvUCS3qBJcGAIeJFd9Ux3R+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmF7yXrkG6CQZh0GCIeMH17wZgEAxIhL7qHren+qOQUVLIO0ywYMDmoUEvWCSqZWjIUYCHFCyzpBZYEA3JlL3pbklqyDipZp/s3BGB0guegkhP4XrIO6SYYkG56gSW9wJJgQK7sRXdLTvdHJaegknWYHMCAWrIKtWQdvpcMBiykeIElvcCSYECu7EVvS1JL1kEl6+D5YIBKVuF7yTqkm2DApONFsCTO5gFjEgwYIl50t+R0f1RyCipZB88HA1SyCrVkHWrJYMBCihdY0gssCQZ84tqL3qqDWrIOKlkHzwcDVLIK30vWId0EA5ZmvcCSXgRLEragAM7mRXfVMd0flZyCStbB88EAlaxCLVknqGRqyVCAhRQvsKQXWBIMyJW96G1Jask6qGQdPB8MguegkhP4XrIO6SYYhEmHIeIB07cXWBIMKBd40d3ZpvujklNQyTpMDmDA5KBCLVmH7yWDAQspXmBJL7AkGJAre9HbktSSdVDJOt2/IQCjg0pW4XvJOqSbYEC66QWW9CJYkrAFBciVvehuyen+qOQUVLIO0ywYoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBAMmHS+CJXE2DxiTYMAQ8aK7Jaf7o5JTUMk6eD4YoJJVqCXrBJVMLRkKsJDiBZb0AkuCAZ+49qK36qCWrINK1sHzwSB4Dio5gd+41iHdBAOWZr3Akl5gSTBgiHjRXXVM90clp6CSdfB8MKCWrEItWYfvJYMBCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJV+F6yDukmGIRJhyHiAdO3F4xJMCAR8qJ72Jruj0pOQSXrMM2CAZODCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usk73bwjA6KCSVagl65BuggHpphdY0gssCQbkyl50t+R0f1RyCipZh8kBDFDJKtSSdYJKppYMBVhI8QJLeoElwYBc2YvelqSWrINK1sHzwSB4Dio5gd+41iHdBAMmHS+CJXE2D7AkGBC2vOhuyen+qOQUVLIOng8G1JJVqCXr8L1kMGAhxQss6QWWBAM+ce1Fb9VBLVkHlayD54MBKlmF7yXrkG6CAUuzXmBJL7AkGDBEvOiuOqb7o5JTUMk6eD4YoJJVqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBIMw6TBEPGD69gJLggGJkBfdnW26Pyo5BZWsw+QABkwOKtSSdYJKppYMBVhI8QJLeoElwYBc2YvelqSWrINK1un+DQEYneA5qOQEfuNah3QTDEg3vcCSXgRLEragALmyF90tOd0flZyCStZhmgUDaskq1JJ1+F4yGLCQ4gWW9AJLggG5she9LUktWQeVrIPngwEqWYXvJeuQboIBk44XwZI4mweMSTBgiHjR3ZLT/VHJKahkHTwfDFDJKtSSdaglgwELKV5gSS+wJBjwiWsveqsOask6qGQdPB8MUMkq1JJ1SDfBgKVZL7CkF8GShC0ogLN50V11TPdHJaegknXwfDBAJatQS9YJKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlkHzweD4Dmo5AR+41qHdBMMwqTDEPGA6dsLLAkGlAu86O5s0/1RySmoZB0mBzBgclChlqzD95LBgIUUL7CkF1gSDMiVvehtSWrJOqhkne7fEIDRQSWr8L1kHdJNMCDd9AJLeoElwYBc2Yvulpzuj0pOQSXrMDmAASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgq1ZB3STTBg0vEiWBJn8wBLggFhy4vulpzuj0pOQSXr4PlggEpWoZasE1QytWQowEKKF1jSCywJBnzi2oveqoNasg4qWQfPB4PgOajkBH7jWod0EwxYmvUCS3qBJcGAIeJFd9Ux3R+VnIJK1sHzwYBasgq1ZB2+lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpW4XvJOqSbYBAmHYaIB0zfXjAmwYBEyIvuYWu6Pyo5BZWswzQLBkwOKtSSdaglgwELKV5gSS+wJBiQK3vR25LUknVQyTrdvyEAo+Omkn+/5B9/AmrJOqSbYEC66QWW9AJLggG5shfdLTnd/w0q+esnlAz++efr6yHVlLeo5N/vr8UsPz91gmAzY690m8kBDNxUctEpvv59WER5Ty35N0aUr6csMQSVTC0ZClxbSFkn1xddIU66P1+/rbPuV+NUefsq2hiW7Je++MHiHhhcy5W9nO1mtqhY48vNSudIb9VRW0sOzWo5P48YKPKICNmuko8PWTEW5lvssE4ZwoyoZDAIg9NDJf/mPeI/R1d4hE5u/43r5ojyewwpz/BT0k0wuDDpeLnCeZJucuDf6cYtJ0wOn3r5uQdFrLsFSzY6m5slm9MXaZnS9BJugkQIDLqFrebEYUIap2jOdvJlSyifQ1hdj3Z0d7bQa2eVLKcI30eLTvw8IKudX2yLSj6NBHMgfEvDPaWBMIgZmRzAwKmWPKWYGSf6fWREaa4lt0YUJZ9uno46EF4mtWQo0L6Q4uQKSaCZaLhQY/u504msTh8lj3mvbpa8kL5oGdLCCNGexT0waP+csI+zna5SdYkWZ1MiUukerUpHobfquKGWfLSYGuRHWAwsM3e7RSXPz7VhDU1t/p3IGmYUM/JdCzBwUsmTh+hOpLrC+DK5+XvJ83NtWBElXTuYeICrkm6CQUiSWoaIkyvkMsdaJ5Ze1C7h/S7Nz46uhrsMckqe1nTTK6hcSV/yD94h70loHZPwcbQ6W7qSNHHB2eTMiJU4zNQ7mxoSCj6pN2/z4e6qI/TYVSUfnyZjo66PXMM8ahpU8vk5y0Mzv3KTMcwwZuy9qgPD46OSgwOqTpRxheEzltZacltEyYaU4ZcPwnNSS4YCjQspr6pbIRNoJup8au2GbFvE+11XyfYDOlmyNahkTFlOJKSRwggxjcU9MGjMlZ3CVmvisCBtFU7OlutlximzzZtURG/V4V9LPrzU7EwzutJqVMnJYCgOzbhqrKEaZhwzopLBwEUlzy6iOVHITlRGH5WNteQkRpQnu3xIaZ1k3w3pJhi0TTpOrpCdcydqOrN2o/Ku8X7na9er5IpedbHkxfRF2iiMENJIhMCgLRHycrY2KRKRtgrHu+d7qXaz0LzFe7o7W+ivp0o+PMw+PP5MyD8Dg0eYRpWczAPFoXlofTSLapiBzNj9sw8wOi4qeR7jihMVXGFwqdVYS94/2UwxohymxpNdRqi8FAgqmVoyFGhaSHFyhcT/DlRMgdKyLkndiWHZXqlXyRXZdA9LXkxfkmx/Y4SIxuIeGDRpO7cZPAlcNQGo1tlKvdS6eTh+at6gI3qrDvdasrSf2VYS4u9/7z56P8KCYJ42lZyMzOLQ3M178dfh9j8alxhmJDOyhAoGYVS+qpIXF0md6MERpe03rtsiypyzLawRRbaHd1fSTTBomnR8XGFfBFlCzffh92dNR44OXHnL9X7Jhfd3LVIMEEKwZLWzOQWVYszOC4DCc5vGfwNNloRPpEnbec3gjYmDUOtssm9C8eX0qyW7y1YpnRzdVUfobYVKtgiXCexfybbwsDPHtnOEFcEs8/tt+fWuyPxoxaG5WWD/4re959g7lBlRyWDgUEuWxCpxoi3hel5Eaf6N68j8aOXJbp159q6p7hyP0E1qyVCgZSHFyRWk/cTulO9d1md48hqUKjPB2MN2X137JNtFOljyavoix0thryctloSPpCVXdnK2A3JyjQdVNt06pPry+fTd+pjsCWztq/2nt+qorSUbRPMdHmVdHjnMFKvpej62yY0qeZ3WThPoOgRP5w5lRj5xDQYOKnke2IoTrS7ywIjS/BvXkfnRihElY4DVWkOvHpBugkFD3c5yhUoHXNufTtgyvHKsWbvReL/2CLb2qOpODemmkyWvpi+xQe1t3g3lAjDo4GwH5NxC4hCpdTZpdn6qtZunRKNV6WRxSClfI3T2ZZWshurVRifbrY1HTt7uU8mrQySPr0+VY5mRyQEMXg9pccifnejREeXGWrK0SBxTDyiDETpJLRkKNCykzON9IucKjZdJHHb7gGHRlaVNbRq4BjbZbqDNx99vyasxO54nm8PB4h4YNFSU5qE+8aKzHZFzK2JQpbNlY008cLxV3sXbglZ/1eFTS1afOu5MFihWnSjbIzKPm1tUchyR6VtfR5VsL4xlRlQyGLyskteBfXaiR0eU+2rJ8elTv4wGq5gou0G6CQb1k46TK6zSLvXXNdSUYk28WeVMuV6zPTysOUPdqW+35OWYLQeHjVwkQmDwfmc7Un9qZUtplnqsrlxalU6e7s4W+vqqSl4nFdmeydtoffXF5di+zL2/RSVnpw3dJQYzI5MDGLyskudBHTg50bMjyn21ZGmgRJQ4G43ssUElU0uGAvULKfNon3jRFaSt6nNrhpf35VbVG6PXBTeVMwvR4cDbLXk1ZsebVFrw/bC4Bwb1ufI81Cd8Z3A51Q4Nlc4WfVm5YDx08OXo4Mpl46HKsNVbdbjUksM1AodnjoaQzT3rRCPbAzK/9ltUsjRQn10O7QfEYGZs+BQJfCZhRL6ikuOIT5woJCYB2dzzgIjS9hvXO+bnKkSUmJNrDRpnox6QboJBdZLk5AoFaTdhXuiNIjn2tDbuBUtWOZtXUIltZXNPMWb/p3BsCKotCZ9Kdbngphm8+swYRWQzR6mZHDrcS/aV2leGvO6qI/T1RZWsRvloUvUdxYPjln7mHt6hkuPcoDYQS+4MOZoZe6/qwPC8WEtec8zzoH94RLmtlizH9TlOjg3ssiHmUUuGAtULKfNYn5DNI3KswhXKmWmcwbMXUvOhPK2iescqNGvjyrsteTlmRxvK5niwuAcG1bnyPNInZPOIHKsMJnvkzGzisFLpbNJM7Yn48v5Yo9Ip0Vt1ONSS9ShftrwctF9gL+a3fodK/gp/i3tCnRJTo41mRlQyGLyokucRvXAc1w+PKHd9L7m0EL1lorI5IKSbYFBbt/NyhXKkWSOUbJ6JZ1dOky+I5Nl3AtUzcu30/R5LykHtJoVDY0AiBAa1FdC7ZnA50fahyobizGozpZf/aVM6Jbo7W+jqaypZnxXUnSvDJ29zB2/5xHWJ1CyyYxgzdv/sA4zOayo5RpPA0Ylk51Mjyl215PjgmSRbjl6LR+8gvHBqyVCgdiHFyxWkYW6eK4eaVtWrp09VrKXkaoE9liXzhoxPNu5Hg1jcA4NabXfXDF57Yq2zSTO1m/EasmlSjqFnequO12vJ8XmPT2G8+WjU6vD+bub+91fJw5mRJVQweEklrzlm4OBET48od9WS5XDOKSUJH9dnSTfBoHbSmUf6665Qru1sx1VnfqNIjs/bEFXebMnLMXv4ryXPliRsQYE3O1vCcp4tRWqdTZoVw55smiRKp0h31RG6+pJKDhcIHI1nvdrl8EUx+Qbmt9hfJQ9nxu7jFUbnFZV8EMnHYV3pCi/+xsJ93FRLtlYH2qajDgSVTC0ZClQupHi5wvfXQu468T6qM0uYqp0kW0X1nvg8DfPxmy15OWbLgWHTQxb3wKSyAnrbDC7nmU7U2E4Ne62dbGvfW3W8XEvOzAr63o3Lr/5NzP3rpZI3qy3bA5mx92cfYHjCeLyqkmM0WTg4kex7bES56Teu40JwVn/L8WsB6Q2QboJBZZIUI8DdrlCqJa8BTLYNVpF8oU9XBHawZIWzeVlSmjXH7JKFB4FyARj0DluV51U7m7RTrycPUe0Rbe27q47Q1xdUclwIOQW6uDv7horrsQMwv8W3q+TzyeOZkckBDF6oJa/RZGE/7GMsf2xEuamWHNNy2Uyx6jm9Cf2jlgwFKhdS3uUKOW030apcY5evdCmem42ICu+15OX0pWDhUWBxDwwqc2UnZ0tZTjPjQ7WzlRq29nFpXhu7equOV2vJIVgETo9rW14atIT4dzI/wLtVcpw01il2PDOiksHgukpec0xhP6ofH1Fu+l5y+eiEbbi+kG6CQZh0KobIPMzf4Ar5y7xTJK/3ku0qKqfv5cIvW9L+wqM0ON9Idv98fYU/CfL1NeDKJ4kQGFQmQvNQvyNsyWn5Cy9IM9vZYj+U4BYPWfeKJEqnTHdnC329rpKjdc6PYC8tLA2qzfpu5gd7t0pO3GE8MzI5gMF1lbwmjfL/70f14yPKPbVke7pJgspghBdLLRkK1C2kvM0V8qFoDWCybdAqqg/IqW0h5b2WvBqz4/13/IwW1lncA4O6XPm+sCWnGZ5T72xrS9neEQOfbJo0PlJv1fFiLTmcHTi/Yjs+Dp68zd17s0qOk+ZmtfHM2P0bAjA6l1VyHMv/aE70+IhyTy05xozChaXFlYj0Dkg3waAuSXqXK8Q4k/ZoC2B1SOtL/cn3osR7LXk1Zq+rB3sG08nBkoQtKFCXK98XtupOa3A2OZg+VBTJtcEo3rO2fXfVETp7WSVnrSP7Cy9o8Jx27t57VfK6VLP5i+wYyIy9V3VgeK6q5DVcf2vjXtl1YvCIck8tueKhpcWFiPQWgkqmlgwF6hZS3uUKMelJrrILYFW05pZ7Wu8lvNeSdiP9TnHviaHyDhb3wKAuV74vbNWdlnE2bWyvCuX0VDGQ1fZQUTplequOl2rJa6iW7ZV4oGCFiiY9mcfOW1XyasxtOAxoRlQyGITheEUl77LP7V+R50eUe37jWoxWcsmKJj0h3QSDuknnTa6wztOyvbIe+P79mm/0Uy5/Smem3nz9LO0bvn8bT27MM4IlbWerMFNFk+sxW3amXFlkvAkSITDoHbaWs6wQIa1SFGeTI6euxFhU28E1UFY/UHdnC729qpKjeZL3ULE+EtcTBgp8e96skn93KzqbRQY0I5+4BoOLteTVA6Z/y792TvT8iHJPLbl4cOHiHPsuQveoJUOBuoWUeZTf7wox6UkuEg+sP6sQ+Ml6/JYryv8/U5k3rNUY2a7lrZa8GrNXy6SME9tZ3AODulx5Hte3hK3lLCOkNDnbGnZ2ce13i181NQBd6Rj0Vh2v1JLj86b9r4iPde+wG/MTvEUl/359hYi7shtqA5qRJVQwuKaS12gdxr/8czeonx9R7vlecvHgQo3pOkK6CQZ1FdB5kN/uCmtOKNsr8dpncrOlHE6oSh2lbXM8qZu+l2u/bMmrMTtnycCVAHoLdWMSPpi3OpuCnFW6cquz7Vr//IZItXxqZqF8o6LSMeiuOkJ3L6rkcGogb0zZVJEmlmk7MT/BW1TybpgF9pPkgGbsPl5hdK6p5HkUT8wDef/vhedHlG615BrTdSTEP2rJUMCtAvq6K2Q/LdhaAD1N+zsqptf4HM0z8VsteTVmx32/c2L5vU/Er0XQO2BxDwweoZJjo0pny4ct+1FP5zZ4cm/V8UItOT600n05VHywpYnxDrsxD8wOKvmw4jCgGXt/9gGG55JKPuZ9srEb1M+PKLfUkmNuXrruxTn2XZBugkFVkvQWV9i0sOyIFESy6rrHWf9I/lPawnqz5nDyVktejNnL7Q8331tLdvWGcgEYVCVCXs6mIGcV86FmZ4t9SbDTrmPMa4ld3VVH6PD/yr+bKH01piY+1rTpxzwY3q6ST8YY0IxMDmBwRSWf8j7Z2DnR8yPKLbXkmu9i17TpSFDJ1JKhQNVCyltcYZ2sz964HlBJOr/GOx2jf/Fm9UlG5K2WvBizQ+p1frLvzb6DhHcW98CgKle+MWzJWcUo0e5ssTNHfipE73bZVi/urTqu15LDiQHtJVyMjwPRSSUfx9qAZkQlg0EYjq0qOZwTELc5bgWeH1Fu+Y3rmpXomjYdId0Eg6pJ5x2usM7V594Yqjdx3vVCGaSZzlrOke0GgiVNZ/Oy5MWYPW0qV90s1qgVboJECAyqKqA3hi05qyhFpuOtzqbGupqu7YNejare6O5soctXVHJ8ZLXzSuxLqGnTjz4q+WSOAc3I5AAGF2rJ0QfiyJLNv6eSr2R480NlIsqNK9HvIrw1aslQYJRacgxTSYg51FfkK36lb/jtD/18zc2/V+0bKMWwNUu98BRPqCVnLpo1fh9Y3AODqlz5xrAlZxkqudHZdj9pfcD8msgx6rW5cW/VcbWWvIZqdU1AiX0JNW360UslH+wxoBm7f0MARqddJSfBRDb/lEru9r3kmjYdId0Eg5Akva0CmmcNU8n5YQwLi+Zd2AnfQ1DaLjRpZNk3sfukYykhjq2uxLmqdNPLkhdj9t6Ce1brlO75NqrGJHwyb3U2BTmrKEVanW3dn2JKntO5DfGru+oI/b2gkuMT632Xo8UHq2nTj/ep5MD+p+V2BhnQjL1XdWB42lXyPIInVqc5b/+FiEItWSe8NWrJUGCMWnI8OT19O3L+IKGEpIm9++p7J7YL5T9NvbZpzJlnnlBLzhLNNoQ4ZXEPDKq0nZezKchZauJgojvbFrkmfn4Om1VOnFE6Br1Vx8Va8rpKKtsn4mHZVBFr9Xz4Au9VyRPbQvJmkQHNiEoGg2aVHEf+Nq5kx86Jnh9Ruv295Isr0e+CdBMM6iadeZDf6ApyrnKHtZScdnKd1XeRK/ZC6cd2KPsYcrz4nFneaknvmL2uD8h2V0iEwKB32JKzLgUK3dnWQDc9mFx2/02ROn/QlI5Bd2cLvW1XyeGsQOYN1MRHaXLtHd7O/ATvVMm7CXU9d0Azdv/sA4xOq0peM8NtEpAdu0H9/IjC30vWCTMvtWQoULeQMg/y+1whn9utCaU2Maaz+rZLiQbrtXJ9jI9wzZ3fakn3mB0NV9f6XuosCR+Mm0q+GLbkrIveojjbGnsOj7X7okhleqPExDK9Vce1WnJ8zFzP3ePj25mf4L0qeRs8sj2iGVlCBYMwHBtUsiKSlUH9/Ihyy29c1zxzjek6QroJBr3TzcA6OacdiVfVu5jM6rGjejBYw6H+HFq0bCBY8rkqOV6wrvW91FkSPpi6csE8om8JW3LWRW9RnE32JMFnW9prlcmybdFddYS+tv69ZDNUR7OVjCZNRoh4CvMYebNKXgdPPHlAM6KSwaCxlhwH/X5Uya7doH5+RLmnlizWK7nkxTn2XYQnoJYMBeoWUm51hXimdq4cyGRDawoZHTheKtPRGA/1TmrRsoG3WtI/Zld07F2wuAcGdbnyfWFLzrqaDyUdi7EndegkxlnES1W27606LtWS4zNmOx5ldGHBs6JJT+aB+W6VHE+Odh3QjHziGgzaVLK64ia7dk70/Ihyz/eSK+bYiiY9Id0Eg7q63Z2usEYpxYPjsdyUH7OleDxuy+aZNeOU7QNqtGzALXGvsaR/zDZM904oF4BBXa7s5GwKy1kXpYjibLKtOesal2rLANK88pG6q47Q10aVvK6ryraCNCi8oIvrI++ij0o+D0zZHMiMTA5g0KSS9fAq+/bjXtl1YvCIck8tueKhpcW1iHQ/IeZRS4YCdQspN7rCqlw1B473zfq2HI/T5mkzoXQ9OXTZmd9rSbtRxZ32NDa/Exb3wKAuV/ZytpSLp0XOHYvb6iNF5VJ7s0SCF+mtOq7UksMpgcICoLQo2EzM1PPZS8xD4u0q+Xz2aVPh3WZEJYNBk0qO0fI4pmTnftwru04MHlHuqSXbc2xjuebtkG6CgVe6edkVwhid0Xohh/L3PWaEsZvZSBZ7qTQoJqo1vNeS0sgvZsfVigFiGYkQGPQOW3Jawf2KnL8wcQxjJ4qfgNGQ5nWd6+5soattKllPbI/Yr37wnHZ+gG4qOVplPDMyOYBBi0qOA/w0wmXn3okeH1HuqSXb8eY82Y1GUCDUkqFA5ULKPMzvcIWY8eixRY7lb3sMXXYgkwbpBWO6fF0lvteS7jF7oFjG4h4YVH5OeB7Rd4QtOS1/4TLxtjHYyGbmiWxfPyLN6zy/t+poryWvoVq2VaLN8uFcGlx9hXczP8D7VfJp1hjPjN2/IQCjE8ZjpUrOpX2ydz+qHx9R7vmN63g075Ot09e7Id0Eg8okaR7mN7hCPE0/0a70HEOXLQyXBkqLqNavh7hgyXqV/Koljw+uIQ1qH+hqVe0GKi0Jn0vnsNXqXGeis4k4j5uZy7W6ZtP6WHfVEbrapJKrQrW5/HH1zb+LuX/vV8kns4xnxt6rOjA8DbXkGEvOI0p2753o8RHlplqyOdssx68GpPsJD0AtGQpULqTc5Aox/8tkgHal59jC7GW2xdoR2b7Aey3pHrNtW78NFvfAoDJXvilsvTzzR2eTqGf4aqtrNrl+b9XRXEuOT2d0Wlpl35AMjWFz2vkxu6vk8cyISgaDepUcR3syfGX3Ydhr+/aMHlHu+V6yOdsYS8D9Id0EgzDpVAyRe1zBEMnr8bxrH1uYSXG2xbL7WhARKqdvL0tazVpjttWvN0IiBAaVidBtM/jV84RTv6xuyuHauzW5cndnCz1t+XvJoX3ACNWVNh02zsz976+ShzMjn7gGg2qVvOafSSyR/QcnenpEuamWbB2OZhug/KITMmVqyVCgdiFlHujerhCVXC6yxCJKfsY/lllsZZhRybH7r0S4N1vSO2Zb13sjLO6BQa22m4f0DTO4nJcPTGVOzlbpy7V3a3Ll3qqjtZYcY7zVZ2OFNdro6hu8nbmD/VXycGZkCRUMqlXyPHQn0tGrHXh6RLmplpzLqSPL0SESSx3STTConXTucIWY8OQ7IMfzgec4qZ+n+BRpcLpgfk2xgTdb0jtmS/uaJ7ibYEnCFhSo1XZ3zeBy3tWMSE6P3bLilhyuvZsdBnd0Vx2hp/UqeQ3Vsp1H2mUCSZx7ZHM85pd4g0r++fn3Z/p/2cNyumyOZ0ZUMhjUquQYJ00kPMnWUyPKXbXkaEb90nalqzdBJVNLhgK1Cyk3uEIMK4VJT5rkGxwTwtiNvNiVBqd+xp685MnvtqQ0dIrZMfscIZixuAcGtbnyXTP45RNnzs5mxK2km61Kp0Rv1dFYS64P1fHV60aVg+Pqrbn7N6hkOZx78OTwaGbs/dkHGJ4wIitU8rrgZiK+9PCIctNvXBtP/h85euXG74F0Ewyqk6R5qHu6whak8meZ+Z4cFwc2pV6Mc7IprD2R7WsES1Y523Kvly3ZHrNLvYuWHiGYUS4Ag35ha0FOzAaaNmcz4lbi6bKdM4Bx+Eh31RG6Wq2SoykqelxcAhkp3OnMT3pHLVmOy+aJ1GijmZHJAQwqa8nzyK1Cxv7DI8pdteRiSIk2G9hlQ/epJUOB6oUUb1fYRHLBcWNSlHPQeDxeQjazclcOn/opey9FkI13W7I1Zk8Gz181XixruXfC4h4YVGu7m2ZwOTObODQ6m2xnvC95htJDGYEhobfqaKslh8aBmlxUmmphPU4+PR/c4G6VrB+PE+rOvrJnFDOiksGgTiVHR6gg+opsPjSi3PW95DVoaM8ecrnAuIsHpJtgESadqiHi7QpyipHMSZtMPpgcjp3MXFM/XHqyBqqnby9LStPKmD3vyq4DzK0nii/jXZAIgcHbne2EnJlzl1Znkx16T9JHaFY6Bbo7W+hqrUqOD17V4cIiSNmAQzC/xRtUcskh1nljP98OZkYmBzCoUsnrUK8gju9nR5Tbasnrw6cXTxeExyP0nloyFKhfSPF1hXg1Y8aLzfRW8ejqv2tP1GCg5QC7vReS5T1vt2RTzJanzATJ9W1kjr+XekvCh1KfKzs52wk5M5M4NDtblC5qV+TQ7mbNSqdAb9XRUktufDRpnL6lov0G4S6VnLfKRDpvTMi+QczY/RsCMDpVKnkeuZWsI1+2B3GFRm6rJa9Pn8Zl2f9qbn0rpJtgUJ8kubpCLOOY95Zmaru1R9uNlV0bcuh0LTUzuMD7LSmNa2L2ml+qmfv6Nl61gQ/BkoQtKFD3obqAa9hakVN1f2l3tvUMJYCsolq2A7JHvX9jPOuuOkJfK/9ecuOj5dZMV2tfefPvYh63d6jkdTylo1M/NJYZe6/qwPDUTA5fP0XmcT2xbK0D/9ER5b5a8ho4zo6Z2z8UYUKmlgwFGhZSHF1hTV3T3PXEFq9kx8Z6kZ37rmEsDQe/66Vkx8Ia4GT7Mu+3ZEPMXp9dC5PbwTGCfIMl4TNpyJWdnO2InKsnDhecbd2bjPv1yL6f6870BoVDKr1VR0MtOV38M9Btsc4bPR/b5DaVHBukTdb1m5NhhjIjKhkMwqCsW0LNEi4xkTjRkyPKbb9xvctEDwbYMu6RFw9IN8GiYdJpd4WvCfnngVXGVbiPNEx7ud73oG/XgHW+9HbPY5dk5+uOHCxZ6WxelqyP2dvqQRLsttu+bgMfSITAoKEC6he2dsi5erMLzradcnqqVbkc28u+9AY5pZOlu7OFztap5NAyUB2mVKtub0B2jMl9KnkzwFYkm9gmyLOBhzJj988+wOjUf9AoyzywFSd6ckS5sZa8M8F2g1zGPRqh79SSoUDLQkqrKyztU79scp9Myrmp4dOcvnVynwPsstPjFBuv8/rE28GSDTF723vMSX93hhwl+WBxDwxatJ2Tsx2Ym2Tj1wVn2x3Z3TnbfrtDpdLJ0lt11NeS4zM39HZnj6/ZTl/bqkO92O7C/OpvUcn74fkjzX53lkpPHcmMLKGCwY0q+ckR5b7vJU/sJqS53Yh5ZQbSTTBoqIC2ukIMH/s0bmY3S+fYnbOfv+W2+/smzru/+hLIfr/2++ZGkfXirwe4punbyZINMftgdEmODnYcJ5g1jUn4RHo42x5pc449kQvOJvtnxJf3J5zb7+4g1zeUTo7uqiP0tkYlr08n21UcbH6k60PbzD2/RyXvFp4D/25fw5xRDDOQGbuPVxidO1XygyPKnbXk4/x1YuzFg3kqpZYMBdoWUuZBr5O4whpOzt51nJN19s5cbp+EplMOcEbXjtVJZZ4OlmyK2ZbZx4nxbZaED6StAjqPb50WZ9thtWl3tqawdUXpZOitOqpryddCdfZFjBPudOZxeI9KPiw8J6iGGceMvT/7AMNzq0p+bkS5tZZcmL+u3PKdkG6CQVuS1OIKWzSRHUKs1RQ5XK4gBbW+7z5dnXLs56X6RIb3WzLQELNLZhkqxlMuAIM+zrYhTfKJQ7uzFaVL2s92paPTXXWE/lao5DgJtPY18yK6PnINd6rk//rOD8/MecOYkckBDO5VyY+NKPfWkrOT7JU7vpUgSKglQ4HGhZQGV9iCiexYyGese47Xy5+je242Bzh8iW9Cdrt48tstudAQs7NmmTBC4FthcQ8MGnNlL2dbkSYFr2l3tnyUO4etmXalo9JbddTWkqNKTtcLDFSzNl/l7dyqkvPDM2uYUcyISgaDMDJvVMlPjSg3/sb1ghZTHuCqpJtg0DzpVLvCWgE+HC2WQDbOzpyZ1HM+n0k4z/2MVWcXVw6WbHK2Fy0ZaYjZ2cT6Z6gYTyIEBs3lAidni0ibUuJwwdkyZ+R6krtBkzN3d7bQ45q/l7zY80JX0xehrjoMxs0qWR+ebeO5ixmZHMDg5lryUyPKzbXkiXXuXLHP6U94mdSSoUD7QkqtK6zq7XBYm5sVEmfWJvWSC6a9VLPTpZmLRny3JVdaYvbhd8xWhtLILO6BSXuu7ORsQk2bC86mrXgVVrCalY5Cb9XR8PeSg3Xkn20c7RR/7Wxs5vF6o0pWRo81DQxhxu7fEIDRuV0lPzOi3Pu95IXjLPs1WGKpQ7oJBiFJah0ila4gZePDlKaldRrKNc+TuuW0p7Q4l2xOV/WJcVfSzRcsuaclZiep+3ih7MqYhI/iSq7s5GwzSxs7BjU723dl2BKalU5Cd9URel2nkid7Xg3V31/Lq/h5RkI7MY+DKyq5he+v5VffJrNUDZwBzNh7VQeGx0El2zwvolyuJTcxmWWxy3h5ZYbQXWrJUODaQkqdK4SMzzWGbLf9rXHBXSArNP92mnO7WrIpZsd7TpccMpSxuAcG13JlJ2drot3ZJumynDCdIbtKtCqdE71VR0Mt+aN4i0p+IKhkMHiLSn4el2vJfxzSTTBg0vECS3qBJcGAIeJFd0tO90clp6CSdbp/9gFGB5Ws8p5a8vMIKplaMhRgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwCJ6DSk64/BvXfxzSTTBg0vEiWBJn8wBLggFhy4vulpzuj0pOQSXr4PlgQC1ZhVqyTvi+ErVkKMBCihdY0gssCQbkyl70tiS1ZB1Usg6fIgEDVLIK30vWId0Eg5AkMUQ8IHH3AkuCAYmQF91Vx3T/qr+X/GGgknWYHMCAyUGFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLeoElwaB7BfTP0N3ZpvujklNQyTpMDmCASlahlqwTVDK1ZCjAQooXWNILLAkG5Mpe9LYktWQdVLIO62NgEDwHlZzAb1zrkG6CAemmF8GSOJsHWBIMCFtedFcd0/1RySmoZB08HwyoJatQS9bhe8lgwEKKF1jSCywJBlSUvOitOqgl66CSdVDJYIBKVuF7yTqkm2BA3c4Lpm8vsCQYMES86G7J6f78xnUKKlmH9TEwQCWrUEvWoZYMBiykeIElvcCSYIBK9qK36qCWrINK1sHzwQCVrEItWYd0EwyYdLzAkl4ESxK2oACJkBfdw9Z0f1RyCipZh2kWDJgcVKgl6wSVTC0ZCrCQ4gWW9AJLggG5she9LUktWQeVrNP7sw8wPMFzUMkJ/Ma1DukmGJBuehEsibN5wJgEA3JlL7pbcro/KjkFlazD5AAG1JJVqCXr8L1kMGAhxQss6QWWBANyZS96W5Jasg4qWQfPBwNUsgrfS9Yh3QSDMOkwRDxg+vYCS4IBQ8SL7pac7s9vXKegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgwCeuveitOqgl66CSdfB8MEAlq1BL1iHdBAOWZr3Akl4ESxK2oADO5kV31THdH5WcgkrWwfPBAJWsQi1ZJ6hkaslQgIUUL7CkF1gSDMiVvehtSWrJOqhkHTwfDILnoJIT+I1rHdJNMGDS8SJYEmfzgDEJBpQLvOjubNP9UckpqGQdPnENBkwOKtSSdfheMhiwkOIFlvQCS4IBCyle9FYd1JJ1UMk6eD4YoJJV+F6yDukmGFAB9YLp2wvGJBhQUfKie9ia7s9vXKegknWYZsEAlaxCLVmHWjIYsJDiBZb0AkuCAbmyF70tSS1ZB5Wsw/oYGKCSVagl65BuggHpphdY0gssCQYMES+6q47p/qjkFFSyDp4PBqhkFWrJOkElU0uGAiykeIElvcCSYEBFyYveqoNasg4qWQeVDAbBc1DJCfzGtQ7pJhgw6XgRLImzecCYBAOGiBfdLTndH5WcgkrWwfPBgFqyCrVkHb6XDAYspHiBJb3AkmBAruxFb0tSS9ZBJevwKRIwQCWr8L1kHdJNMAhJEkPEAxJ3LxiTYEAi5EV31THdn9+4TkEl6zDNggGTgwq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GqGQVask6pJtgwKTjBZb0AkuCQfcK6J+hu7NN90clp6CSdfB8MEAlq1BL1gkqmVoyFGAhxQss6QWWBAMWUrzorTqoJeugknXwfDAInoNKTuA3rnVIN8GASceLYEmczQMsCQaELS+6W3K6Pyo5BZWsg+eDAbVkFWrJOnwvGQxYSPECS3qBJcGAz1160Vt1UEvWQSXr4PlggEpW4XvJOqSbYEDdzgsWub3AkmDAEPGiu+qY7s9vXKegknXwfDBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XmBJL7AkGJAIedHd2ab7o5JTUMk6TA5gwOSgQi1ZJ6hkaslQgIUUL7CkF1gSDMiVvehtSWrJOqhkne7fEIDRCZ6DSk7gN651SDfBgHTTi2BJnM0DLAkG5MpedLfkdH9UcgoqWYeE5f/P3t8ry64jaZpw21nXUJdQ2lZaXWpZibWVuoG2qZ4Rj5RmM2mWwicfLc1K65v9CIaDf3DCAYaDAGM9T53s3iRBgvSAO/yFB2OBAbVkFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhvWQd0k0woG7nBdO3F1gSDBgiXnS35NQ/v3GdgkrW4VskYIBKVqGWrEMtGQxYSPECS3qBJcGAXNmL3paklqyDStZhfQwMUMkq1JJ1SDfBgEnHCyzpRbAkYQsy4GxedLfk1D8qOQWVrIPngwEqWYVask5QydSSIQMLKV5gSS+wJBiQK3vR25LUknVQyTp8iwQMguegkhP4jWsd0k0wIN30IlgSZ/OAMQkGlAu86K46pv5RySmoZB0mBzBgclChlqzDe8lgwEKKF1jSCywJBuTKXvS2JLVkHVSyDp4PBqhkFd5L1iHdBIMw6TBEPGD69gJLggHfu/Siu7NN/fMb1ymoZB0mBzBAJatQS9ahlgwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrsD4GBqhkFWrJOqSbYEC66QWW9CJYkrAFGXA2L7qrjql/VHIKKlkHzwcDVLIKtWSdoJKpJUMGFlK8wJJeYEkwoKLkRW/VQS1ZB5Wsg0oGg+A5qOQEfuNah3QTDJh0vAiWxNk8YEyCAUPEi+6WnPpHJaegknVYHwMDaskq1JJ1eC8ZDFhI8QJLeoElwQCV7EVv1UEtWQeVrIPngwEqWYX3knVIN8EgTDoMEQ+Yvr1gTIIBiZAX3cPW1D+/cZ2CStZhmgUDJgcVask61JLBgIUUL7CkF1gSDMiVvehtSWrJOqhknd7ffYDhQSWrUEvWId0EA9JNL7CkF1gSDMiVvehuyan/P76/4ECocPzxp2zAAp4PBsFz/pLhAgv/Eezyn7IBCyHd/HcZOgAKYYj8mwwXeIfZ2eTf8A7zmJTxCaAQcmXClge9Vce/Tv0D1EBOCxlklAAUI0MHQEEGCcBQkAhBBhkl4EJPZ5u/cQ1QAZMDZJBRAlCMDB0ABRkkAGMh4xNAQQYJuIBKhieBSoYMMkoAipGhA6AggwRgKEiEIIOMEnABlQxPgskBMsgoAShGhg6AggwSgLGQ8QmgIIMEXOiukv/zX+HAn8Euv2QDFvj1LjAInvP9LzJeIDL/xvX/kg1Y4DeuwWAeIjJc4B3Cb079RWx2IFiSRAgyzENEhgu8wxC/cc1fgkrgL0HpMDmAQQhp/CWohPnvJfOXoBKCBOLHYiHDrO3k3/AOLEl5gSXBgIqSF71VB38vWQeVrINKBgNUsgp/L1mHdBMMmHS8YL3BCywJBoQtL7pbcuoflZyCStZhfQwMUMkqcy35t2zAQvjL9NSSIQMLKV5gSS+wJBigkr3orTqoJeugknXwfDAInoNKTuAb1zqkm2BA3c4Lpm8vsCQYUFHyoruzTf2jklNQyTpMDmBALVmFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZBwkEBgwRFd5L1iHdBAPSTS+wpBdYEgxIhLzobsmpf1RyCipZh8kBDJgcVKgl61BLBgMWUrzAkl5gSTAgV/aityWpJeugknXwfDBAJavwXrIO6SYYMOl4ESyJs3mAJcGAsOVFd0tO/aOSU1DJOng+GKCSVagl6wSVTC0ZMrCQ4gWW9AJLgkFIhMiVPeitOqgl66CSdfB8MAieg0pO4L1kHdJNMGBp1gss6QWWBAOGiBfdVcfUPyo5BZWsg+eDAbVkFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9ZBJevg+WCASlbhvWQd0k0wCJMOQ8QDpm8vGJNgQCLkRfewNfWPSk5BJevwjWswYHJQoZasQy0ZDFhI8QJLeoElwYAlKS96W5Jasg4qWQfPBwNUsgrvJeuQboIBk44XWNILLAkGVJS86G7JqX9UcgoqWYfJAQxQySrUknWCSqaWDBlYSPECS3qBJcGAXNmL3paklqyDStZBAoFB8ByGSALvJeuQboIB6aYXwZI4mweMSTBgiHjR3ZJT/6jkFFSyDp4PBiykqFBL1uG9ZDBgIcULLOkFlgQDvnHtRW/VQS1ZB5Wsg0oGA1SyCu8l65BuggGTjhdY0otgScIWZMDZvOi+3jD1j0pOQSXr4PlggEpWoZasQy0ZDFhI8QJLeoElwYBc2YvelqSWrINK1uFbJGCASlahlqxDugkG1O28IHH3AkuCAYmQF92dbeoflZyCStZhcgADJgcVask6QSVTS4YMLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZzAb1zrkG6CAZOOF1jSi2BJwhZk4HuXXnS35NQ/KjkFlayD54MBtWQVask6vJcMBiykeIElvcCSYMCSlBe9LUktWQeVrIPngwEqWYX3knVIN8GASccLKqBeMCbBgCHiRXdLTv2jklNQyTp4PhigklWoJetQSwYDFlK8wJJeYEkw4HuXXvRWHdSSdVDJOkggMGCIqFBL1iHdBAOWZr3Akl5gSTBgiHjRfb1h6h+VnIJK1sHzwQCVrEItWSeoZGrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE/iNax3STTAIkw5DxAOmby8Yk2BAucCL7mFr6h+VnIJK1mGaBQMmBxVqyTq8lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXrdH9DAEYHlazCe8k6pJtgQLrpBZb0AkuCAbmyF90tOfWPSk5BJeswOYABKlmFWrIOtWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8SJYEmfzAEuCAWHLi+6WnPpHJaegknX4FgkYoJJVqCXrBJVMLRkysJDiBZb0AkuCAbmyF71VMrVkHVSyDutjYBA8B5WcwG9c65BuggGTjhdY0gssCQYMES+6rzdM/aOSU1DJOng+GFBLVqGWrMN7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIOEggMGCIqvJesQ7oJBiFJYoh4QOLuBZYEAxIhL7o729Q/KjkFlazD5AAGTA4q1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVagl65BuggGTjhdY0otgScIWZAiJEM7mQXdLTv2jklNQyTpMs2CASlahlqwTVDK1ZMjAQooXWNILLAkG5Mpe9LYktWQdVLIO62NgEDwHlZzAb1zrkG6CAemmF1RAvWBMggFDxIvulpz6RyWnoJJ18HwwoJasQi1Zh/eSwYCFFC+wpBdYEgyoKHnRW3VQS9ZBJeugksEAlazCe8k6pJtgwKTjBZb0IliSsAUZcDYvuq83TP2jklNQyTqsj4EBKlmFWrIOtWQwYCHFCyzpBZYEA1SyF70tSS1ZB5Wsg+eDASpZhVqyDukmGFC384Lp2wssCQYkQl50d7apf1RyCipZh8kBDJgcVKgl6wSVTC0ZMrCQ4gWW9AJLggG5she9LUktWQeVrIMEAoPgOQyRBH7jWod0EwxIN73Akl5gSTAIuTJDxIPulpz6RyWnoJJ1mBzAgIUUFWrJOryXDAYspHiBJb3AkmBAruxFb0tSS9bpppJ/fck/xgTPBwNUsgrvJeuQboIBk44XwZI4mwdYEgwIW150t+TU/w0q+es7lAz++OPr6yHVlG4q+a+cSu5vRjwfDK6p5N9fr6H9/fWha3b31JJXM4692rZCLRkMri2k/HqcK7SnryXX9OX5q4Us7oHBte8Jd3K2pdvvAZ2zt+oorSWHZqUcn0fsH3lEhKxXyfuHvDrCf52fOYQZu78hAKNzQSX/nt1t4SMHWH0tuTqiPNKMpJtgcKFu9xMiygUupJtelqxPX6RlyggZJOUCMHiOs/3eNy/od3+fG5r4RHfVEZ7MWSXLKcKvwycwPe8D6snzKKhRyYdhc1El/zo98ziQO5mRyQEM6lVyGnI/sJ5cXUuujiipGS9GoVsJKplaMmSoX0h5piu0p5slL2SBUy50wgj5I4t7YFCfK/dxNs3Rvg1hnfQQaSIOequOBrXk/QebfvATIywG5plvu0Ylz8+1cnFSnmKvfuYoZkQlg0EYmTUqOV3/mfi8MVb9G9ezHVasiPJUM5JugkHtpPNDIsoFelnySvqinjMzQvoYLEnYggy15YJU3E60dzat14l8x9IopUmY7a46wpO5quT901z6CAagViUfn/OaSg69qmcOY0a+cQ0GlZPD73kkp4xQMPCktpZcGVHOKi/DmzE8J7VkyFC5kHLmCiOIq844WbI2qFxKX6SRwggxjcU9MKjUdn2c7Sz9yt/6+QpWE3HQWyX715J3c9HJJ9b3mUuoVMnJCL+kkucRq505jhm7r+rA6NSp5PMoPby+q6PyveTELvmIcm7G0bUB6SYY1E06z3WF9gRLljublyWvpS/SRmGEz5FECAzqKkp9nO2814nzjm9Wyd1rc+HJPFXy7mG2n9j3hPwz0PWhbSpVcjI0L6nk+SrKmQOZkckBDKpU8i5KH8b2Z8nkylpyXUTZrdI9y4zhVqklQ4aqhZQHu0J7ulhye97hMplU4qy0NjHCx8jiHhhU5cp9nC3jZIHTjreX3dNEHPRWHe61ZGk/s6bA35Ljbb56P/bCbp1KTgfNFZX8WqBJzxzJjN1XdWB0qlTyOpDjHyBYlyk/a5zV1ZIrI0rI2V48zoykm2BQVQF9sCu0pyrddLJkNn05FwBrXwnFUbQhlAvA4AHOtvYa+41/EWrmtGM5rtDEJ7o7W3iyApVsES4T2OZy60LFJqytO0dYETxlHqI1v94VmR9tb4dCxDLJmUOZkckBDGpU8hKRt2NK3fl4Lv+95NkU+YjyZDOGiZpaMmQIQ6RUJf+giHKBDpa8mr7I8QuJ1C3UWBJ+JDUVpT7OtlmJ2rTf6OSTjuN5stmc3qqjtJZsEO26e5RloWLzCWxWO3o+tkkHlXx25lBmRCWDQRiUhSr5ZBAvUXrohbRKqn/jOjJbIhtRHm1G0k0wqJh0LFe44oAfRAdLXkxfYoNRP7BgScIWZBje2Zb9xwNLvycdy/HCh3uf7t9gDU/7tkpeViu2Rl0WKg5J2tJ45OTtfpUczXU8cywzopLBoKKWPI/fieOIilH6k0Zaw1qytHimGcNNUkuGDBULKfN4nzhzhR8ubO635NX0JZ4nm8PB4h4YVOTK81CfuNfZlubJXS5H9I7lYL3IuUhv1eFTS1bTsbgzWY5YljBke0TmYXKnSl6McjxzLDN2X9WB0SlXyXEEpwMqDvrb4nB7Kn/jemU2RM4UzzYj6SYYlCdJPyqiXCBYsszZvCx5NX2Rg8N+XJQLwOD+RKjS2WSfNo7jldSOb1/B6u5s4WnfVcnLyoNsz8SdmY/gSmXlJm5XyXJecuZgZmRyAIPyyWEevROpdoyLnx801NrVkqXBQ80Yohi1ZMhQvpAyj/aJHxFRLnC7Ja+mL7GTtPtBYHEPDMpz5XmoT9zrbLG5qnbjCVrHcqzs2TzorTpcasnhGoFdIhfNLJtb4kd/32JENXer5Git5MzBzIhKBoNilRwXODVficO+1o/GpVkt+eFmJN0EgzDpFA2RnxVRLlA8fXtZ8mr68mfm2BAUj0n4qRR/77KTs8kePSnJeaccuS+SFluyFeFx31TJ8cPZPUdcqFBNGQ+OW0y+WSVHP5nYnzmaGbuPVxidYpU8j90J2dwjxz4nEWlWS5bjWTMO7LJBJVNLhgzFCynzWJ+QzT1y7EfPXndb8nL6kkn4x4DFPTAoXpKaR/qEbO6RY/7OZhTZogem3hlPPM1I3Oldm3OoJS8Kb7cmkQ9zcvA+O9cyD6r7VLKcFdifOZoZe49XGJ4wIktUcm4FdY3qsvl8Wv3G9dPNSLoJBqWTzg+LKBe425KX05fMoTEgEQKDwZ0t3+3Sb3r4/kDa3dnC476nkuOHs38MdefC8DPWfIO3qeRowsD+TNk5jBmZHMCgtJYcB++JcpSjdY40MK1qyU83Y4h91JIhQ+lCyg+LKBe425LSsDp9ieWqK/HyHljcA4PS7112cjaj2/N+Ra3cKAN6q473a8nR2PunMD6CGAXPPqHuzPd/l0qOqzozuzOHMyPfuAaDUpU8j9zz0XR/LG5Lq/eS5fBjzUi6CQalSdI80n9ORLlAsGSJs70s9bYlL6cvw7+WTLkALG4OW7XOJtc99bHTfl/76yTOe3RXHeF531LJ4QKB/YdjfbSvw3dauo47VXIcvy92Zw5nRiYHMChUydYKTwz6svl4GtWSH2/GEOKoJUOGwoWUnxZRLnCzJQvTlzT/lAPDpocs7oFJYa7cy9m+BNlMOLtehzDaW3W8XUsWWx4fQt+7MvqMNd/fTSo5BNyV3ZmybxwzopLBoFAlx3LBqXCU4wNnSlU0qiU/3oykm2AQJp2CIRInw58SUS5QOH17WVKaVacv8ct1V8LlTRSOSfi5FCZCvZ3tjDOVbKnxBnRXHeGB31DJcSHkYPu4+/STjQ1Oh0Zn5iF1j0peTPhie+Z4ZkQlg0Hh5BCX12QzpUM0bkmjWvLjzRhUMrVkyFC4kPLTIsoF7rXk5fSlNqHvAIt7YFCYK/d2tjOkeXK9s/0N6a063q0lh2ARONjMDnPS4E5b13CfSt69lDyxPXM8M3Z/QwBGJ4zHApUcmk2cj9wHpEo1NPqN6/zRidHNSLoJBoVJ0jzMf1BEucC9lrTfLpYGx45k9/fX19f39/T/DlhLoVwABoW58jzU33c2u5U0OO9oz0nz2E/0zV83OGd31REe+LpKjiY7PoK9/PFqUPyR3c38YLeo5LiUFP//7ZnjmZHJAQzKaslxZfNcN5ZNDo+hTS35+WYMMY5aMmQoW0j5cRHlAvda8mr6Evvf8H1bhlMIi3tgUJYr93a2M+J9HVOWqFM2fJ3fuw+9VcebteRwduBoJvsjG3zGmm/vDpUc7fCHduZ4ZkQlg0GZSi549UxajJYfXaTNe8nPNyPpJhiUTTo/LqJcIFjSdjYvS15NX45fr5sZTCeXWRJ+MPeGLW+tII2T+1JU8nRrmbt3oLvqCM94WSVHiyVPIPszn+vd8q6S+fZuUMnLhPBLO1PZdeBuM/KNazAoU8kFA1dalLrS4LSpJT/fjGEOoZYMGcoWUn5cRLnAvZa0G+k9xb0Hhso7WNwDg7JcubeznbB8n0O2F2T3kabfu+6tOt6qJS8ST7YXCtZHCpr0ZB5RN6jkuM4wtV//FRnQjN1XdWB0ylSyvfRZ0uRBtKklP9+MpJtgUFa3+3ER5QJl07eTJS+nL7Iz5YZXIEshEQKDZzjbCWFaDhzTjpMVrLbO0N3ZwgNeVcny6aUJXMGqxdnX3gfhJpW8jLnp3/KvzZkDmpHJAQzKVPI8avN+UjI5PIc2teTswReDmzFMx9SSIUPZQso8yn9SRLnArZa8mr7EbF5hnGyRxT0wKMuV53Hdz9lOWErJx8ZyLwoNo2pv1fFOLTl+MOn9F3xkJaOjI/MTNFfJy3wQlnfkn5szBzRj7+8+wPCE4eiikkuG/3No8xvX2YMvBjcj6SYYuKWbnxVRLnCrJa+mL/E8jSsBtAmUC8DArVzQ0tl0FmGStJX9Gu3cocySDQmPd1Elh1MDaeTy/ch6MD9Bc5UsjV+tt/9+MaAZmRzA4NbJ4Tl0qyUPbsawOE0tGTK4VUA/K6Jc4FZLXk1f4r7fc2L562tXvhqlmsziHhg8YklKZ3G5o7aTbr5fP9f1+1fsdqaZMOitOt6oJUdLKrcvh7IP9mpS8pH1YP70W6vkOMRedpKNzZkDmhGVDAZFKrnkHZmSwP8cmryX/AFmJN0Eg6JJ5+dFlAsES5rO5mXJi+nLq/td50vSPiG7elNkSfjJFH3vsrOz6Sz+ljSdj+w6Wb6bPdFKhXRXHeHh/lP+XcViHdneUvKRlbTpxzwwG6vk6CDiIbKxOXNAM6KSwaBIJZe8I1PzHs34NKklf4AZQwCjlgwZihZSfl5EucCtlryYvoTU6xjsfkm7iUGyDxb3wKAoV+7sbCqLMEm13bTv+yjoo4ifyGn9N+itOq7XksOJAS178/zI+nCHSpamse1+KzCgGYvWx+An41ZLLmnzHLrVkgc3I+kmGBTV7X5eRLlAUbrpZcmL6cu0qVxVGk6MscRBuQAMnuBsGrE7pcNJFilnRxXfzCO6q47wbFdUcoxa6s07fmSduEElHy0om2OrZCYHMKCWrEItWSeoZGrJkIFashdPqCWfXDSmS4OkHyzugUGRtuvsbAqrSE77+9JPjjeYv8Xr9FYdV2a0dB4AAP/0SURBVGvJiynV9Q2/j6wX7VVyYkHZRCXDownDkVpyQpPfuP4AM5JugsGtRZmP5gnlrdcPA6VI00E+vWBJwhZkeIKzKSx+prT7faJr4h3az3uJ7qojPNoFlRxNqd+730fWi/YqWRquLY/bQ5qRb1yDAbVkFWrJOiGAUUuGDNSSvXhCLfkUaTuGOGVxDwyKtN1wzha9rMwnI/EW2yxh9VYdF2vJs4gMyPaBeFg2VWri4/00V8lxMK7PLzs2Zw5oxu6rOjA6RSq5xE9KllCfQ5P3kj/AjKSbYFA26cyD/CdFlAsES9rO9jLS25b0Tl+WTFy2u0IiBAa3JkJezhavU+tlUc/knuMy3Z0tPFm9Sg5nBU5sUvKRSZMmVn2f+QkaquQ48DcjX3ZszhzQjEwOYOA2OZQM/+fA30vWCdMrtWTIULaQMg/ynxRRLnCrJd3Tl6aZeCUs7oGB2+Lejc626JLalcSmS1i9Vce1WnIMV2d37h4fb2d+gnYqWRHJypkDmrH3dx9geFDJKt1qyYObkXQTDEKShEr24ImJ+0q8YFnrtlAuAIOyXHke0aM422WRvFy8SWztrjrCg9X+vWRN4+0o+SK9NBkh4inMg66dStaWGWTX5swBzcjkAAZlKlk8IDeWSgL/c2hTS36+GYNKppYMGcoWUn5cRLnArZb0T18KbuwuWNwDg7JceShnkxZX9ETJDVylt+q4VEuWD/b8xqOMzixIFDTpyTwwm6lkdZlBdm3OHNCMqGQwCMPRRSUPlBM50OQ3rj/AjKSbYOCWbn5WRLnArZb0T1+k1xFWOYIlCVuQ4XnOFv2r4LYT4tXr9bVNd9URHqxSJceljUywkgYZiw2+rNtUJcdll/26i+zbnqnsOnC3GbuPVxidslpywcCVFi3Cbgfa1JKfb8YwM1NLhgxlCyk/LqJc4F5L2o0q05fK5i1hcQ8Myr4nPJCzvSOSmwbX3qrjSi05nBLILFtIi4zFStZHOjKPqFYqOUTYwP7hZef2TGXXgbvN2P0NARgdL5VcWWcYnTbvJT/fjKSbYFCWJP24iHKBYEkPlVxmSWnkl77E8sIAHyDlAjC4N2xJozecLfZz0b8aSpHuqiM8WJ1KFmtkb9v+6O+Wd5XMD9BIJUfjHKwjO7dnjmdGJgcwKFPJtqO0fNGlA21qyc83Y4hg1JIhQ+FCyjzMf1BEucC9lnRPXwb6AFncA4PCXHke0QM42yqSr7lXQynSW3XU15IXY8q2SvzIzhclpMH52OjL/ABtVPJiwINxZO/2zPHMiEoGgzqVfD6Y7LD/KNrUkp9vRtJNMAiTTrm2+zER5QJ1ifu7lnRPX8qqardQOCbh53JvIvS2s8nhy2Lig1XybJsqlSzGyNvSXP4YfcKa76+NSo4GPH7ssnt75nhm7P7dBxidwsnBDKqv41dj9nA0qiU/3oxBJVNLhgyFCyk/LaJc4F5Luqcv1JLhORRqu0GcTW6j6JZVzOe4Tm/VUV1LjrY2blpanX6y8TORzeFop5KjAZNHl927M7V9W243Y/dVHRidMB4LVLKVIcW6gTE5PIY2v3H9fDOSboJB4aTz0yLKBW62pNWsNn2x7utGSITAoFDbjeFsYRqeuTyo5fwW0bW7s4UHq/l7yaF9wMj3rI9eDg8bZ+b7b6GS45hPDSj7d2cOZ0YmBzAorCVbnhKH/gB1Axca1ZIfb8YweVNLhgylCynzQP85EeUCN1vSO32xrncjLO6BQWmuPA/pzs4WK9FvvM0g5589xjv0Vh21teS4IGHdcxSDJzaPn2gLk7ow32ALlSzHlQbageHMyDeuwaBUJUsoORtNr6NDZEQuNHov+fFmJN0Eg9Ik6YdFlAsES5Y4m5MlvdMXaV8yFlpDuQAMbg5b7zjbUru7lKHMxOtfvkCG7qojPFi5Sl6sKdvnSLuTkCwDY9wJq5VKjmPJRC4gW8OYkckBDEpVcnQFfY00Lm4WZ1Cj06qW/HQzhhhGLRkylC6k/LCIcoG7LSkNndKXmH2O8AmyuAcGpdquv7OtIvlKgvKipRbprToqa8nRFPZHFj96fWlBDo6rt+bb91fJ63C0kAuMZkZUMhiUquT86P1TjrZYmuxCq1ry081IugkGYdIpGiLzUP8xEeUCxdP3y1RvW7I+fcl9zjH7HOETLB6T8FMZ39ki0bGM2/2dkX1R2RQ9cC3dVUd4smKVHD+HgjvOLoGMFO50GqlkOVqAXGA0M3YfrzA6xSo5Dl/Z3BHH/eeMtVa15KebMahkasmQoXgh5WdFlAvcbcna9GXKtc+vGi/WpFxVC4t7YFCcK3dytoV4zOhkanaev8RrnKYp79BbddTVkkPjQIksk6aaYZuuO/jQRiUvw9EmXkA2RzFj9zcEYHTCkCxSybk1t5CEBMZdR6ul0W9cP96MpJtgUJwk/ayIcoHbLSlNC9OXeddpJj63nmiSiNdCuQAMissFfZxtIXZvLD8F8XI64pdryLYv3VVHeLJSlRxFXtENZxZBmq47+DB/6t4qOQ7VEuIFBjMjkwMYFE8OywBOo/pQZQMfmtWSH27GcPfUkiFD+ULKj4ooF7jdklXpi+RHJ0Eytr8URN0ptyT8UMpz5R7OtrCqkqwSf13h5HmWa7TRBr1VR00teTGFbBtI4/SDyS2djEITlSzHilguINuDmBGVDAblKvl8AVL2f1Lhp9l7yQ83I+kmGJRPOj8qolwgWLLM2bwsKY1L0pclv1RlcCyqZQLhnZRbEn4o5RXQDs62UCWSTx5ovYbscKa76giPVvj3kjPrERrLMsgh6C0mHXnCmoeVs0r++s4iZ/7x2lqMNpYZu3/3AUanXCWfht5sSH4o7WrJzzZjuElqyZChYiHlJ0WUC9xvyYr0JV5ZDZPrwTHSRhb3wKBC293vbAtyxJB1qw5WBv3Sbel91tJbdVTUkjPrETpLYNt9Zsu6Sc/HNmmhkg3OzhzKjN1XdT6U/0v+/w+gQiUv4XU3pH4vI37kdbRa2tWSn21G0s1GfE5Iqajb/aSIcoGK6bvekl8T8s8N5enLmmwnwW7tdpRPkESoDR+UCA3tbJHlDONOVwdcC3hC/BXu4qetpruzhYcrU8mhZaA4TK1Rb/OEq7Vlx5gMpJKHMiOTQxv+63/LP55PhUreDOM19K7LlhecaFwa1pIfbcagkqklN+BzQkrNQsoPiigXaGnJV/skwlWkL+vefU76e0nzx0k+WNxrw4clQqXD9X5ne5E7tmO98nTtbb9fG69ttYLVW3WU15KjMSrudv2Y//iaDfsVYoswyJrgCQOp5KHM2Pu7D5/Kf/3fHzM7hFFZqpI3Ufp7HvgjJkQ+NPuN68CDzUi62YjPCSlVSdLPiSgXaGjJmJMkmXtF+rL2OPHqdNfrQJ8g5YI2fFAiNLizBTbNz4id75u+Lr67ekMt0l11hKcrUcmLkWS7iF2A2zN4hJnvfBCVPJIZmRza8F//98fMDjW15GXUa9y8ANSYlrXkJ5sxpAfUkhvwOSElpGLlCynzoNf5rIhygXaWXHKUNE5VpC87mawwTupRZ0ko5YMSobpceR7fOo2crUgkr2dtq8kqV5KbMnqrjuJacoxfdfLvNOqNE+505sE2ikoeyIyo5DZMk8OnzA51Kvk89n5YStvwveSJ55qRdLMRnxNS6iadHxNRLhAsWe5sNZZcUxTZsaEifTltOjNQ5lFnSSiFRCihmbOViOTNaUbzhtG1u+oIz1egkuMSRe29nnxmA4U7nbFU8jhmRCW3IUwOHzI71E0Op7NDu5XJPrStJT/XjCG0UUtuwOeElMqFlJ8SUS7QzpK5xL0mfTlpOnMhqWoGi3tt+KBEqDJXvt/Zcr62sDnv7A4DyW96edJbdZTWkqNKrl4wUC07/qLuYCp5GDN2f0PgQ5knh8+YHSpVsh6sP2+Mta0lTzzUjKSbjfickFJdt/sZEeUC1elmsSVjgqgfrUhffp3l7t9DZY2UC9rwYYnQyM525mh7dl0sHR9pu4DVXXWERyz5e8mv4HXhVtOo13TZwYnRVPIoZmRyaMNrcviI2aFaJSuxt23Q7ULjWvLEM80YVDK15AZ8TkipX0j5ERHlAu0suaTmJ4cr0pftr+auDKWRWdxrxQclQvW58q3OVvR96+MT/EpvcaK1IuitOir+XnL4aOSfdew/NPnpwsGZB8NIKnkQM6KS2yCTwyfMDmF01qnk4/TwNVhG5ELT37gWnmhG0s1GfE5IuTLp/ICIcoGGlpSk+/TqNelLopPH+/yCJQlb/nxQIjS2sxWK5KSPRCffoES6q47wnGUqefoIr9rj19cr7n0/QyJPzEPhikpuyQBm5BvXbYiTwwfMDvW15MA0tF9j+1MT2su15CqeZ8Zwu9SSG/A5IeXaQsrHR5QLtLRkSJ+ziUlV+hL7nC455OfH4l4bPiwRqs+VezhbJfHa4eK3KJHeqqOilvyjGFIlD0D3VZ0PZZkcnj87XFPJH8/l95I/HNLNRnxOSGHS8YIKqBeMyTZ8UCLEEPGiuyWn/lHJKahkHTy/Devk8PjZAZWsck8t+XmEVWlqyQ34nJDCQooXWNILLNmGD0qEyJW96G1Jask6qGSd3t99+FQ2k8PTZwdUsgq1ZB3SzUZ8TkgJSRJDxAMSdy+wZBtIhCChu+qY+kclp6CSdZgc2rCdHB4+OzA5qFBL1gkqmVpyAz4npLCQ4gWW9AJLtuGDEiFyZS96W5Jasg4qWQfPb8Nucnj27BA8B5WccPk3rj8c0s1GfE5IYdLxAkt6ESxJ2PLngxIhvnfpRfewNfVf9PeSfxioZB2m2TbsJ4dHzw7UklWoJevwXnIjPieksJDiBZb0Aku24YMSIXJlL3pbklqyDipZh/WxNhwmhyfPDqhkFd5L1iHdbMTnhBTSTS+CJXE2DxiTbfigRIgh4kV31TH1j0pOQSXr4PltOE4OD54dUMkq1JJ1qCU34nNCCgspXmBJL7BkGz4sESJX9qC36qCWrINK1kEltyGZHJ47O6CSVagl65BuNuJzQkqYdBgiHjB9e8GYbMMHJUI4mxfdLTn1j0pOQSXrsD7WhnRyeOzsgEpWoZasE1QyteQGfE5IYSHFCyzpBZZswwclQqhkL3qrDmrJOqhkHTy/Dcrk8NTZIXgOKjmB37jWId1sxOeEFCYdL7CkF1iyDR+UCFEu8KK7s0398xvXKahkHSaHNmiTw0NnByYHFWrJOryX3IjPCSkspHiBJb3Akm34oESIXNmL3paklqyDStbhG9dtUCeHZ84OqGQV3kvWId1sxOeEFNJNL4IlcTYPGJNt+LBEiCHiQXdLTv2jklNQyTpMDm3QJ4dHzg6oZBVqyTrUkhvxOSGFhRQvsKQXWLINH5QIkSt70duS1JJ1UMk6eH4bTiaHJ84OqGQVask6pJuN+JyQEiYdhogHTN9eMCbb8EGJEM7mRXdLTv2jklNQyTp4fhvOJocHzg6oZBVqyTpBJVNLbsDnhBQWUrzAkl5gyTZ8WCJEruxBb9VBLVkHlayD57fhdHJ43uwQPAeVnMBvXOuQbjbic0IKS7NeYEkvsGQbPigRYoh40V11TP3zG9cpqGQdPL8N55PD42YHaskq1JJ1eC+5EZ8TUlhI8QJLeoEl2/BBiRC5she9LUktWQeVrIPntyEzOTxtdkAlq/Besg7pZiM+J6Qw6XgRLImzeYAl20AiBAndJ4Cpf1RyCipZh29ctyE3OTxsdmByUKGWrEMtuRGfE1JYSPECS3qBJdvwQYkQi3te9FYd1JJ1UMk6eH4bspPDs2YHVLIKtWQd0s1GfE5IoW7nBdO3F1iyDR+WCDFEPOjubFP/qOQUVLIOk0Mb8pPDo2YHVLIKtWSdoJKpJTfgc0IKCyleYEkvsGQbPigRIlf2orclqSXroJJ1WB9rgzE5PGl2CJ6DSk7gN651SDcb8TkhhXTTCyzpBZZswwclQgwRL7qrjql/fuM6BZWsg+e3wZocHjQ7UEtWoZasw3vJjfickMJCihdY0gss2YYPS4TIlT3orTqoJeugknXGUcn/+7OQOeCcx8wOqGQV3kvWGSjdFFf8FCRwnPOUkMLSrBfBkmg7D8axpHj7pyCx6ZzHJEKELS+6W3LqH5WcgkrWGcfzJWb+HJ4yO6CSVagl6wxUSxZH+zk8JKRQt/MCS3oxjiXFl38OLO79NHpbklqyDipZZ5xvkUjI/EE8ZHZAJatQS9YZKHEXP/tBPCOkhCQJbecBibsXlAv6QSL0w+iuOqb+UckpqGQdJoeOPGN2YHJQoZasE1QyteRePCKkUAH1Akt6QS25I89Z3GNJyoPelqSWrINK1kEl9+QRs0PwHFRyAr9xrUMtuStPCCmkm15gSS+CJVHJvXhEIjTO9y6fTvewNfXPb1ynoJJ1xvF8iZc/iyfMDtSSVagl6/Becl8eEFKogHqBJb2gltwVFvd+Er1VB7VkHVSyzjieL+Hyh/GA2QGVrMJ7yTrUkjszfkgh3fRinAro0yER6ssDEiHClhfdLTn1j0pOQSXrMDl0ZvzZAZWsQi1Zh1pyb4YPKVRAvcCSXlBL7swzEiFUsge9VQe1ZB1Uss44ni/B8scx/OyASlahlqxDLbk7o4eUkCSh7TygvOUF5YLeDJ8I4WxedFcdU/+o5BRUsg6TQ3dGnx1QySrUknWCSqaW3JfBQwoVUC+wpBfUkrvzhMU9VLIHvS1JLVkHlayDSu7P4LND8BxUcgK/ca1DLXkAxg4ppJteYEkvgiVRyX0ZPBGiXOBF97A19c9vXKegknVQyQMw9uzA5KBCLVmH95JHYOiQQgXUCyzpBbXkAWBx72fQ25LUknVQyTrd3xBYkED5Ixl6dkAlq/Besg615CEYOaSQbnoRLIlK9oBywQgMnwgRtjzobsmpf1RyCipZh8lhCEaeHVDJKtSSdaglj8HAIYUKqBdY0gtqyUPA4t5PoLclqSXroJJ1UMljMPDsgEpWoZasQy15EMYNKWHSQdt5QOLuxThjUtz3hzJwIoSzedHdklP/qOQUVLLOON8ikSj5Uxl3dkAlq1BL1gkqmVryCAwbUqiAeoElvaCWPAhjJ0KoZA96W5Jasg4qWWec9TEJkj+WYWeH4Dmo5AR+41qHWvIwjBpSKMp4gSW9IBEahWETIZzNi+6WnPrnN65TUMk6TA7DMOrsQC1ZhVqyDu8lj8OgIYUKqBdY0gtqycPA4t6n09uS1JJ1UMk6fON6HAadHVDJKryXrEMteSDGDCmkm14ES6KSPaBcMA4kQh9Od9Ux9Y9KTkEl6zA5DMSYswOTgwq1ZB1qySMxZEihAuoFlvSCWvJAsLj32fS2JLVkHVSyDip5JIacHVDJKtSSdaglD8WIISVMOmg7D0jcvRhnTIrj/miGTYRwNg+6h62pf1RyCipZB5U8FCPODqhkFWrJOkElU0sehwFDChVQL7CkF9SSh2LUxT1Usge9LUktWQeVrDPO+piExx/OgLND8BxUcgK/ca1DLXkwxgsppJteYEkvKBeMxYCJEM7mRXfVMfXPb1ynoJJ1mBwGY7zZgVqyCrVkHd5LHo3hQgoVUC+wpBfUkgdjzEQIlexBb9VBLVkHlayDSh6N4WYHVLIK7yXrUEsejtFCCkUZL4IlUckejGNJcdofz3CJEGHLi+6WnPpHJaegknX4xvVwjDY7oJJVqCXrUEsej8FCChVQL7CkF9SSh4PFvU+lt+qglqyDStYZx/MlNMJoswMqWYVasg615AEZK6SMU7d7OiTuXpAIjQeJ0IfS3dmm/lHJKahkHSaHARlrdmByUKGWrBNUMrXk0RgqpFAB9QJLekEteUDGW9xjScqD3paklqyDStbp/d2HFQmMMDHU7BA8B5WcwG9c61BLHpKRQgrpphdY0gvKBSMyVCI0Tq78dLpbcuqf37hOQSXrMDkMyUizA7VkFWrJOryXPCYDhRQqoF5gSS+oJQ8Ji3ufSG9LUkvWQSXroJLHZKDZAZWswnvJOtSSB2WckEK66UWwJCrZg3EsKe4KMwMlQoQtL7pbcuoflZyCStYZx/MlKsKLcWYHVLIKtWQdasmjMkxIoQLqBZb0glryoIyVCKGSPeitOuZa8h//9u//Pv3H/8J/8/+Fj+WPP2Qr/PfT/zf/N/3fPFpk7PRFgiIIw8wOs+v8G65z/F8wy/wP/ov/hf+bzSJDpzPiSSCMElLCEJlylBhQ+O/Sf9P/vdKa1ZL8r/5/L+vNlhwjbImzgjBYIjQPF/67/F/4v9mQYtUevFQyQDlMDkMyVE4LUIEMnc6II0FkkJAigwRgKEiEhoRE6BPp6WyoZKiFyWFM/kss0xkZJQDFyNDpjPgRLIwRUmSQAIyFjM++iKvCAonQB4JKhieBSh4SllDhqcjQ6Yw4EkSoJQOcQiI0JCRCn0h3lfxv3//xzX/hv+V/83sn0/8fd/Df9N/0v3m4yNjpi4REEEaZG+bJ4d9fo4X/1v/Cz7388ddxL/+Fl47GSDcJKQdGCSnzEDmOG/6r/W8CS3r9FyxJIjQiwyVC/Pfuf8GSXZ0t3AC/cZ0w/90WfuM6Iawe8BvXAzLM3MBvXOvMv3HNX4JKCAtvg/zsrrgSvBgmpPDLzF6E6RtLesBvXA/KOInQOLny0+ltybmWjEpO4C9B6YTxOoYEkqAIM+PMDahkHVSyTkg3xyjKEFJ2kG5+HsHZsKQH46w3iLvCzECJ0Di58tPpbsmpf1RyCipZZ5yERaIiBAaaG1DJOvy9ZB3+XvKYDBRSqCV7MY62ezrUkodkpERonFz56YSUklryeKCSdXqP1xUJizAx0twwr7uhkhOoJesMJIHEm2CCdPMTYb3BC8oFIzJUIjROrvx0ujvb1D8qOQWVrMPkMCBDzQ3UknWoJeuExJ1a8mgMFVLQdl6E6RtLekAteUDGSoRY3POityWpJeugknVQyeMx1tyAStaZfw+QWnICteQBId38TIKzYUkPxllvEJcFEqFPpXtVfuoflZyCStZBJQ/HYHMDk4MOtWQd3ksej8FCCrVkL8bRdk+HWvJwjJYIsbjnRW9LUkvWQSXrdF/VWZDQ+OMZbW5AJevwXrIOteThIN38VKgle0G5YDSGS4QIW150t+TUPyo5BZWsw+QwGMPNDahkHWrJOtSSR2O4kEIt2YswfWNJD6glD8aYiRAq2YPeqoNasg4qWQeVPBbjzQ38xrUO7yXrUEsejPFCCtrOC9YbvCARGosBE6FxhsjT6b7eMPWPSk5BJeswOQzFgHMDtWQdask6IXGnljwOA4YUtJ0XrDd4QS15KEZMhFDJXvS2JLVkHVSyzjjfIpHw+KMZcW5AJevwXrIOteShIN38ZIKzYUkPxllvEMf90QybCOFsHnSfAKb+UckpqGSdcRIWiY8/mSHnBlSyDrVkHd5LHokhQwq1ZC/G0XZPh1ryQIyZCLG450VvS1JL1kEl66CSx2HMuQGVrMN7yTrUkgeCdPOzYb3BCxKhcSAR+nC6V+Wn/lHJKahkHSaHYRh0bmBy0KGWrEMteRwGDSloOy/C9I0lPaCWPAyjJkIs7nnR25LUknVQyTrdV3UWJET+WEadG/iNax3eS9ahljwMpJufTnA2LOnBOOsN4rw/lmETIcKWF90tOfWPSk5BJeuM4/kSI38qw84N1JJ1qCXrhMSdWvIIDBtSqCV7MY62ezrUkgdh7EQIlexBb9VBLVkHlayDSh6DcecGVLIO7yXrUEsehHFDCtrOC2rJXpAIjcHAidA4Q+TpdF9vmPpHJaegknWYHIZg4LkBlaxDLVmH95LHYOCQQi3ZC9YbvKCWPAQjJ0KoZC96W5Jasg4qWWecb5FImPyRjDw3oJJ1qCXrUEseAtLNnwDrDV5QLhgBEqEfQXdnm/pHJaegknWYHAZg6LmByUGHWrIOteQRGDqkoO28CNM3lvSAWvIAjJ0IsbjnRW9LUkvWQSXroJL7M/bcwG9c6/Ab1zrUkgeAdPNnEJwNS3owznqDuPAPZPBEaJzvXT6d7pac+kclp6CSdVDJ3Rl8bqCWrEMtWSck7tSS+zJ4SKGW7MU42u7pUEvuzuiJEIt7XvS2JLVkHVSyzjjrYxIqfxyjzw2oZB3eS9ahltwd0s2fAusNXlAu6M3wiRBhy4vulpz6RyWnoJJ1mBw6M/zcgErWoZasw3vJvRk+pKDtvAjTN5b0gFpyZ56RCKGSPeitOqgl66CSdVDJfRl/bkAl61BL1qGW3JnxQwrazovgbCTuHowzJsWNfxgPSITGyZWfTvf1hql/VHIKKlkHldyVB8wNqGQdask61JL78oCQQi3ZC9YbvKCW3JUnJEKoZC96W5Jasg4qWWecb5FIuPxRPGFu4DeudfiNax1qyV0h3fxJUEv2gnJBTx6RCFEu8KK7s039o5JTUMk6TA4decTcwOSgQy1ZJyTu1JJ78YiQQi3ZizB9Y0kPqCV35BmJEIt7XvS2JLVkHVSyDiq5H8+YG1DJOryXrEMtuSOkmz8L1hu8IBHqx4MSIcKWB90tOfWPSk5BJeswOXTjIXMDKlmHWrIO7yX34yEhBW3nRZi+saQH1JK78ZREiMU9L3pbklqyDipZZ5z1sf/9UcgEkOEpcwMqWYdass5AEkh88UOQuJGBdPOnEZwNS3owznqDuPuHIKEpw2MSIcKWF90tOfWPSk5BJevg+W34L5kCTnnM3IBK1qGWrDNQLfmz+JyQQi3Zi3G03dNhTLbhwxIhcmUPeqsOask6qGQdVHIbrMnhOXMDv3Gtw29c65BuNuJzQgrazguczQsSoTZ8UCLEEPGi+3rD1D8qOQWVrIPnt8GYHB40N1BL1qGWrBMSd2rJDfickIK284L1Bi8Yk234oESIXNmL3paklqyDStbhWyRtyE8OT5obUMk6vJesQ7rZiM8JKaSbXgRnw5IesN7QBhIhSOg+AUz9o5JTUMk6JCxtyE4Oj5obmBx0qCXr8F5yIz4npLCQ4gXazgvGZBs+KBEiV/aityWpJeugknXw/DbkJodnzQ2oZB1qyTqkm434nJDCpOMFtWQvGJNt+LBEiCHiQXdLTv2jklNQyTpMDm3ITA4PmxtQyTrUknWoJTfic0IKCylehOkbS3rAmGzDByVC5Mpe9LYktWQdVLIO62NtOJ8cnjY38BvXOvzGtQ7pZiM+J6SQbnqBs3nBmGzDByVCDBEvulty6h+VnIJK1sHz23A6OTxubqCWrEMtWSck7tSSG/A5IQVt50WYvrGkB4zJNnxYIkSu7EFv1UEtWQeVrINKbsPZ5PC8uQGVrMN7yTqkm434nJCCtvMiOBvTtweMyTZ8UCJEruxF9/WGqX9UcgoqWQfPb8PJ5PDAuQGVrEMtWYf3khvxOSGFhRQv0HZeMCbb8EGJELmyF70tSS1ZB5Wsw7dI2qBPDk+cG1DJOtSSdUg3G/E5IYV00wuczQvGZBtIhCChu7NN/aOSU1DJOkwObVAnh0fODUwOOtSSdaglN+JzQgrazoswfWNJDxiTbfigRIhc2YvelqSWrINK1sHz26BNDs+cG/iNax1+41qHdLMRnxNSmHS8CM6GJT1gvaENH5QI8b1LL7pbcuoflZyCStYhYWmDMjk8dG6glqxDLVknJO7UkhvwOSGFhRQv0HZeMCbb8EGJELmyF70tSS1ZB5Wsw/pYG9LJ4alzAypZh/eSdUg3G/E5IYV00wtqyV4wJtvwQYkQQ8SL7pac+kclp6CSdfD8NiSTw2PnBlSyjl8t+bP8j/eSG/E5IYWFFC/C9I0lPWBMtuHDEiFyZQ96q46LteSv75DcTLf+VZb3xfZfhe27c49K/vUlZvz+kj15VjP2KkqhkttwnByeOzfcpJL/fFpEcasl//5D/qHxO0aUr7KI0h/SzUZ8Tki5pu2WyfVNV3hj0v2qnCqbf9fkmrN5W/L769fjXz0hEWrDByVC14aIl7PV8WtJHMqkyHSXiy/Lrhy1lz/Qfb0h3HqlSpYHjphp6qH9IwJkvUo+GEX2Zvg197FgDp8hzMj6WBsOk8OD54Z6lfx7Hs8LsjfHEyOKWy35+9RCvw8RRXaPTfgoqSU34HNCygVtd5xcZXc1b0WaX1PHNbp36itNAvYPYmDd34X1BjdLygUirRcEGsPiXhs+KBG6oJJ9nG0fswqkyNE3jVN+7Tv449sIO5WXT+m9JFVfSz4+8kT2qX8fTDo97wMC5PyUNSr5YBZzIKRmydvlODI7mZEl1DbsJ4cnzw31v3EdTtgge89RIsoDdLLXb1xPDy//OpJG5urpqAOkm434nJBSP+k4ucKbk+58RnnH800noSx9lHPMvoKzdbFkmu08IzqdcmG9AQr4oESo/kt1Ps52uIp5iV/ScEsuSGi+nAmLhyLITKWE6K46wj1XqOR03pg5z1LVID9+Ujvfdo1Knp9rxRqaqlkyI2EUM6KS27CbHB49N1RPDsehLbtPeWhEcaolhylN/rlHWXZ7hKuGxJ1acgM+J6TULqR4ucKbkUbuonQJLyarh9RBzxR05JRzarWdmu7VW1LLwwM91vmdYHGvDR+UCNXmyk7OVitFtF4nzqLWiS+f3ufJ5atcv7fqqKwla+sCM2cPfWKjno9cxDw3Vajk43MaQ/PELKd2GcaM9etjUMJ2cnj23FA7RJKQIvvPCOmJwvARxem95HAV+eeOs8g8/PIB6WYjPiekVCZJXprszUl38UjZtojdXVfJ9gNWOttZUKm05Fm24xEPe0G5oA0flghVDBEnZ0u8LS9FzoLl2a1X+vLZQ9U5T6Ul/Qk3XKySz016ko2d2nT0AFOpkhPD5Ifm+VCrHJq3m5HJoQ2byeHhc0OtSk7Gtuw/4dQVRldaPrXk+fHl31vOI/PoMjk8EbXkBnxOSKnTdueJWZ0rvDnpLh5ZmOXG7o5XL1fJBfcVpu9ySzoFlVNDTjw2l2Bxrw0flAjV5cpeM3idFDnvVb/3nC8r91l7+RN6q46qWvJu/vmekH/OaJPBtsGh/eDhsVIlJ4MnOzR3rQvsMpAZUcltWCeHp88NlSo5zWnlgM62ktzZFSpxqSW/rCUbG3KR+d0+G0O62YjPCSlV2m6XmL3hCu9OutLWWC9fWMSwbC+Uq+SCpwvOVhwnnYLK9rSUpyYTdesNUMoHJUJVubLbDJ64W5UUkX+9SG/+eJfyLyG9z226VnD5M7qrjnC7/yn/tghtX8QfZN5+lf61Z8s6YSntx65x1Knkw2iZyA3NzbwXf0Z9u+u1Z8NIZkQlt2GZHB4/N9Sp5F3YfSFHVB4cUVxqyfNzKhZajZBGlMFzuXDr1JIb8DkhpWohxckV3o00sXHhZLl0l2Sam9QgTy7liFRpOx9LroaMpvy9+yXfsaP2KSzuteHDEqHiXDnnbDUJ93qdSC4ubBxx6XZzhcQ3Zf/EEhU3l0j8wbh8EuvO6K06amrJy/Ntf+hxDYLJp7FmwGr7Yhv1YP58a369KzI/WnZo6hZbB4/sWBjKjN3fEPhQ4uTw/Llh9oArr67HkCqbGoYrDJ1wefzGtQQJ2VpZI7PsCKg7x4N0sxGfE1JqkiQnV3h30l3OL/T4WHSp99UlE5XtLKGbmy0p7Sc2p2xz6zdjYicoF7ThgxKhDmFrh5yckSJrlNv2sIa5Y7/LDe2cVt87UXv5U7qrjnC3hSo5NA0c7ncx0jFJ1Q8sRho6NWqokpcJYj+mFrucDk3djPeOHiaHNsjk8AFzQ+U3rlcKVPJQrlCJQy35zELLbLQ3wGlgHoqQuFNLbsDnhJSKhZSTWFDtCm/mLkvDwv5id/URrK6nMH3fa8ml/Vm6M3bUPoXFvTZ8UCJUkSs7OdseObdeiqz9Hs6VvcenWn1Zdgi1lz+lt+qoqCXHZ0tuNx44PPOZjWqXWbsw33wTlXz6+MsB2RZMM17yoKugktvwmhw+YW5oqJIfHVEc3kuen3FCNhdkd+KYpxF7JEg3G/E5IaVi0pnH+8SbrvBupJFWpWng0p1sV1D3YBXO9rrs25aU1qnF1j/XdWsC4wWJUBt+ZiI0+8HEm862R849j0GLuk2imd7v6d3oYfE8WNY+VndnCzdbppJDy4BsrizGlm0hmiIJgifth2Ket5qo5Dgjpi2iwfZHxjIj37huwzw5fMTc0FAlPzqivF9Ljo9/fMr49Klf6hFlLMI9UktuwOeElHJt5+UKb0aaeHrhTPnGKt9yP2WnhnTzVksu+j+NfMutjxy1T2Fxrw0flAiVazuvsLXHPDU6Z9qtHuZknxJr4m3ulGTt5c/prTrKa8nn6m45tLPeuY0Wm9ZPCrcx330TlSwNtAEiR3YWG8yMLKG2IUwOnzE3tFPJBa7wlgpty9u15Pj4iYVkr3Lx89l3HEg3G/E5IaVc282jfeJNV3gz0tSq3njNC24qZ5Zm0cHZynp5XfZtS0pb9f7eWBzoT/mYhBo+LBG61dkOyKnnoSEjIOKh7cnRX5V7UWVv5eUzdFcd4V6rVLJs7pBDu2eOhpDNLapNx2J+2pYqWWugmXgwM6KS2zBNDh8yN7RTyc+OKO/Wkpec8viQ8YAWUSpnox6EW6SW3IDPCSnFCylervBepFk8tdDbY28X5tUYM0vjXrG2c7JkvD/90Wo+ktFgca8NH5QIFefKjWZw80xpoAYPObS9/+jM2gXjsW3Ik12ll8/QW3WU15Ll41JvVmxUalLVpmMx32ELlRw9Ql0/TY8VmVG9Vht6f/fhU/mvj5kb5kHcQiWP5gqVvPsb13G6nJA9guzU7SbHBnZZ0s1GfE5IKU6S5rE+IZt75FjBhd6MNNFTC51uEdX1waH61GJne132bUvmc/y44jBwdDqFckEbPigRujtsHZEzTSmiNlDkXnRm2dyhyJray2e4WnhxI9xr0d9LlufKzhyyGciZ1P4AuzM/UQuVHGcG2dwjxzYnj2ZGJoc2/NfHzA3NaslFrlD2Ews9eLOWHK0TkF0vYkDRg4Bl1P6ExJ1acgM+J6SUajsvV3gv0sSzC6fJpTh9ITZUdvWavsexZDTlwNHpFBb32vBhiVCJZ7aaweXEU3Xw9f1CDTyK50pz9ZGUZ6i9fIbeqqO8lhwaTqirltFGshmQPSfPNnzyNt9gC5UsT67bRcbO5uTXjnHMiEpuw/8l//8H0Eoly+GnRpT33kteqkYB2ffiT9l5cmk5ehqPukO62YjPCSmlk46XK0jDa5Gmtr4bxn/gwqxa29Wrs3EsOX7QPqd0vQHq+KBE6O6wdeTyiYFa15TmpZ3VXb676gi3WqOS1ZWBGK5lcyJa4eSTj7L6em2lMfP991fJw5kRlQwGjVTy0yPKe7XkuPY6I/teyL4zp5QTx/XZcIPUkiFD6ULKPNLfd4W3Is2iXAtdPTr2FQeVUyuiSqm2e133bUtGU51lQ8MH7XNY3AOD0lx5doH3nS3hdR4q+X18asnpM1sf7evwxU/wBuYnul0lv45tTh7OjKXfIoEfSyOV/PSI8lYtWR5ekJ0zMSs/u3LddNQB0k0wKNR2Xq7wVqSJnlo4SdaXg1fi81TMx4W1ZC9L/v56cXYdq5+BoVwABoWJULMZXM67lhHV9irNSzuru3x31RFutUYlq2aQZ948yGvH+aNd/uhvYr6/hipZf3A5ti6tyo5xzMjkAAaNVLIcfWxEeaeWvOTSL2TvTHzs0yvL8Wtz5Q0EWUEtGTIULqR4uYI0uxRpluUs2TaIxdQr7rmcW6ExC9cb7goq1JLhcynMlZs529XzZuSuinP9V/NiT667fG/VUf/3kmVzR7L6GtO6009o9FXE+WlbqORcgzhpLEYZz4yoZDAI49FfJT8+orzzG9dL7v1C9s7EQ7KZksTmwSDdBIPCScfJFd6JNPFQqaOHwR+44p3x3PNUI6XQ2e4KKvmQPzQkQmBQWAFt5myv06riw0rlybWeLM0LL9/d2cK9VqlkZbUgHlqf2TaaNCjqugPzA7RUydqHLodWq41nxu7ffYDRaVNLfnxEeaOWHOfRiOyekV3n8cY2XF9C4k4tGTIUart5mL/vCm9EmkUkF/p5dOwrM+pSSpbtIkK6eZ8lTUaPTRkKxyT8XAq13ewBLZxNTju/cIakYGdQqeQrL99bdZTXkpcZQLY3pKshttFeDa59hDcwj8wmKjkaK22RLmKPZ0aWUMGgjUp+fES5/l7yEnnTOLscO7/w6Jko6SYYlE06Xq7wRqSJDlo4Qy6OfSUsyKl15wZnu8+SJraph6VwvQF+LveGrRQ57VJCVNunNC/tq/Ly3VVHuNeiv5e8hOXkdpW5wQ5/TnG2FfPtNVHJ8cGT9eZlcXg9MJ4ZUclg0EslDx5RrteS56ea+FKeMAaNzIWlxairB+GDpZYMGcoWUrxc4XqkiftLQ5C0vuSasa+6ybhM290VVK49wxiwuAcGZRXQds528bRAlO6lnikxszS/qb18b9VRXkteVdzhfqOFth9HuufI2UwzCPPtNVHJq732q0fLwvLGJLJjIDP2/u4DDE8blSwHnxtRLteSY7z41p6w4KGlRcZyXSHdBIMybeflCnajk56WGbzQy1fHrqe2L6HM2e4KKtEAo4amHJQLwKBsiLRztounTTSOZNXB62pK6Ua42cJX+ULTmZ0xFtG32RsFdcYKBUsoPZnHbhuVHN1i/+zLGsTGaAOakckBDJqo5OdHlKu15GVKUS0k0TfnkgVNehJuj1oyZCjTdk6ucDnSrLnf76+5o++/sgmq3Mx0N1/fr/Zf5eEhnlyZApetNxSYqaCJySayPQ8W98CgLFdu52yvsy6o5BjfSnuMwSgXMzfUXr6/6qioJa9P98f3Es5/LxbamuhP2SWbGjFElhn2dhqq5HVQbVpFi+1Gw4BmRCWDQRiO7ir5+RHl6m9cz880McUKxUKypyDcjOq1pJtgUDbpzKP8fVfIhqEXeqRZpvV1fp/+fSp8F424bZ69+w3LybJdSnC22yxpER981MiUpWy9AX4wZeWC2QWaONvrrNKQEvkdA+BESbryWhGcKbnB2svPdFcd4W4LVfIygUx8/wrhf2Oh3YdRMNNc/AzvYn6CRio5tgnMy8fbkbO12YBmRCWDQZNa8vMjysVa8jaVVIwge3LPXGK6joTEnVoyZChbSJkH+fuucDXSxPOOnM2WcjihKERI2+p4UqbtXtduHVSW3FG2nwWLe2Dgtrh30dnkrNyV9/z+2go6O7pMzbftrWetvfxKb9VRU0veBLaU3UNcnWnGYX6CVip5LcqnbNdXBjRjkEA9xysMDypZ5dp7yfG55wdXjCB7cs9cYrqOkG6Cwa3p5sVIs1R3U9Rs8DyVKphe4z1Wz8S3rjfkWWvpsuNZUC4Ag7JcefaBJs4mZ+WuvOcQk6xk5RDyzEetvPyG7qoj3G+xSl4+r4T9RyH2yD7Yq0nFZ3gr84O2Usn/49fZHLn/gtaAZmRyAIMmKvn5EeVaLXl+ool5SkktpL8huefiHHsX4ZOllgwZirSdlytcizQZkaxGpLMEIHD+LW1h6ax60S1M37dZMstaKZAdD4PFPTAoypUbOpucVZ4P7YOSFYU2LhywVUHl5Tf0Vh11teSjZSLfh3BdMtOUtOnHPDCbqeSzWfJw1oBmRCWDQTeVPHZEuVRLjmHi9UyphWK+nLtuDNnVKfU9kG6CQZG283KFa5EmOqpOcrGsqDZdNXZWnv9GgrOZ8fGWoBLuZKb+IYaARAgMioZIQ2eTs66p5IKxvQtiBfdWefkN3Z0t3HLZ30t+ocrk47pAOouklLTpR2uVvBsykaMtBjRj9+8+wOigklWu1JKjScQmqYViNM5dt6RNR8KnRi0ZMrjVkkvaXIo0ala04ZgOyAVOkWY6h6hQQ9F6wx1BZTHAU5MJFvfAoChXbuhsctZFlWzL3l3QK+il8vIbequOylry5ietdxy+JCSt6maaoWiskpeJ7sD+tAHNyBIqGIThiEpOuPAb18tirZyWWqhkJbqkTUdIN8HArShT0uZKpFkcNfA1/7Dp7pdNjwnu9tD313w3v3YpQa73pbMLDu1WSy5pk2GpJJs3MypF6w3wk7k1bCnIWddUcsWtC+bdVV5+Q3fVEW7Y49e7dp+FtMs+WEmbfjRVyYfhtWW33DCgGVHJYEAtWeVCLVkeaHmi1EJ3lH0aExJmasmQoWghxcsVrkSa6KgTL837YiN8d5fbzP/fm0Rh+2slmTs8RoUairRd+6ASz76ssvvD4h4YFOXKDZ1Nzrqqks17X734hXV7lZff0Ft1VNWSd4/5vfsV8P1TyJHsg5W06UdLlbwXyUc7buaNAc3IN67BAJWsUv9e8pJky7ZioZJV5pI2HSHdBIOiJMnLFS5EmnVCP/mBloltQqDvndjknbInZensij8XOZuXJU9Z7XXp9CGgXAAGRYlQQ2eTs8pVcuBX3d8//lX5948rLy90Vx3hdgtV8vp8yxLo9ntCm8fIJryCXG3QSDM/QRuVvF2CiSvP269nrUsyA5qRyQEMmqjk50eU6lrykksuk49iBNmTmwkvrkTfRfjUqCVDhrKFlHmQv+8KFyLNMnmnoWc5tLnemgAkaeV66PQx5Hhl8iuE6fs2S54i5158hjFgcQ8MynLl2RGaOJucVe1k63daygZ4jJiFN1h7+YneqqOilrwaY3vDm68JrTYqmWmkyaCBcn6CNipZWkxsJ0nNugOaEZUMBt1UsjQZNKJU15JjYM3GA9mTe+YS03WEdBMM3LRdiSvUR5plOUubGJf0aL2vMOJnlGiwllllx5F4e9fcOXRtT9+vDpoFleX5n5xIlI1J+MGUVUBnT2jibHJW7sonKEErx7q2JzsMKi8/gOoIN1umkkPLmUNwX220yOT6mWY05idoopKXae74sS9jZzkwoBlRyWCASlaprSWnIlkzguzJPXOJ6ToSnpNaMmQoW0iZB/n7rlAfaeIZ+ry4TOuyvZytB4Mlm9KfY1HRFZFkw63rDSekec4TYXEPDMpy5dkVmjibnJW78hlp0MpiBK2Eyst3Vx3lteTlyZIV0CVyLzaKe3KlE2ly5TO8gXlgtlDJmYXnZOwMaMbubwjA6ITh6K6Snx9RKn/jeokTm1MUC0nMyLnkGwntHZBugkFZkuTkCvWRRrZOzkgyyHgTJzeazyDj0YtzcJmzNQ0q8cxhA1IZlAvA4NawpSBnXcqHYpwpPHnJVmTbovLy3VVHuNeiv5ccGgaURcxlIojH4o7MgmdBk57MA7OFSs7NkccpcEAzMjmAQZNa8vMjSmUt+RgLAoqFCubYgiY9CYk7tWTI4KbtSlyhOtLErbMpP3pyPB63ZfNIvJx6fDlYvty2I0zft1lSZcmnrz7CILC4BwZl2q6ds73OKlWiB+Tk0j5jalKa4Ejzwsv3Vh3FteSculsC//KBHLdTsjlxf+bba6GS5bg6RyQTpGwOZEZUMhg0UcnPjyh17yXHiLrzNeUJCx5aWmQs1xXSTTAom3S8XMFutO/pT9k69W05Hp/gsJkQr65dTw5ddubgbPdZUuFTRDKJEFjcG7ZSLp72IiYgsmlhLRUeqbt8d2cLt1qikrOPdUHeyfVGDTTz2G2gkvOjKRo5Hj1sKtxtRr5xDQa9VPLgEaWqlqx931q1kD3HxohTXsa+l/CxUUuGDGULKV6uII2KI81rI9NvnNVfW/E2T68f71LJyuK5l2NcSDfvs6RCtMXjkwgW98DASyVfdTY5LRPIclSebT/GHmledvneqqO4lhzaTZzc69FGts0Gz2nnB2igko2FZzkazx7PjCyhgkEblfz4iFJVS56fZGIfRjQbyK7z2abkPcuekG6CQZm283KF2kjz2sh0u7+gfXlpkF5QXzurodDZXr00CCofI5JLxyT8XAoTodkfWjibnHZ+4SxydqmjxrBWepPSvOzy3VVHuNUClRzXM05MflzuiDY7X/6QBhc/wubMD9BAJcdpQjaPHDL98cyISgaDtir5sRGlppYco8TB0zQLya5zn8ybtT/hWaklQ4Y6bfeuK1RGGrvSs7/gYYpXeDVQWsSwcD3E1a03uAeVeNq40agYFvfAoDBXnv2hgbPtw1Q1dpzaUVvwrrp8b9VRWks2Pqnjcoe5/HH1k7+L+f4aqGTj8GHsjGfG3t99gOEJ49FfJT8+olT8xnV81mNz7RHN2eZ1/I3MujGkm2BQmCQ5uUJlpDGbLwnkq4WdHp61WMKCbF8gONt9ljyyPEBhHBwZygVgUJgrN5vBr573ojafkualvVVdvrvqCHf6vkpObHTcPiJD442A35b5ee9XyUczy+Y4ZmRyAIM2teTHR5SKWvL8HBPHZ9UsZAXmmJme2q03IXGnlgwZChdSvFzBaraPNHYRZd/CTIpPW7x2vyUxw/R9oyX3rCK5tOA0MCzugUFhrtxsBr963gvrto5I89Leqi7fW3U41ZITGxW2H1ZwzfffXyUPZ0ZUMhg0UslPjyjl7yXHLDx5FNUEss+KKMNWb0g3waB00pkH+vuuUBdp7CQ2tnj1a6/mnajkeFvvRLjCWnKboBKf/K0nGIXC9Qb4udwcthLkvPPAlMWKgkekeWlvVZfvrjrCnRb8vWTroeTwYiNjhTVe7uIn2J75Bvur5OHMiEoGg0Yq+ekRpbiWHJ8kNYRqobPKk/A6eh64uxPun1oyZChdSHFyhcpIc9hM2but6sQ7pMHhgksl9p31rlJt1yKofJRIZnEPLEq/J9xqBpfzLmZEdpzaI81Le6u6fG/VUVpL3q+HJqQLqrLj5NlixJTN8Zg/xHa/3nX2kSd2ke1hzNj9DQEYnUYq+ekRpbiWPD9GCa/m0Wx6Tm9XunpDugkGpdrOyxWkYWGkMab0Y2AzMqkJaXC4z9jtW55c6mwNgkroeuYz0gfKBWBQOkRazeDGiX99f39P/zs7fAxzX9JeNo8ktzk1Df+VXj5Ld9UR7vT937hOP+j8Ry8Hxw0z8+23U8lng0OOrnYZzYxMDmDQSiU/PKKU1pJjhLCRE2RLf/K80UYgPC+1ZMhQvJAyD/X3XaEu0pj5nhyXlMDIpM7iYMxCz7spoXS9wT+oxMd+rxY+DizugUFxrjy7hf8MLieeBRo5fDaI5fByU8Z9JIdl+8wAxuE9vVVH7d9LPgnS6UyRXQKJzccNmPOH3kAlx8GkH09n0NHMiEoGgzAiW6jkh0eUwt+4jlYoQM7IZenRZgO7LOkmGBRPOk6uUBdp8lP6ejyeIJuncU4OH+5T9r4Z4IKz3WnJhXjOyBG6ChIhMCguFzSaweXMs7iU61WRItmgqFyt8vJZujtbuNUalawuJcSJYPsksks74Y1P/i7mJ2qokvVHl4Nbm8meUczIN67BoFUt+eERpayWHB+kBDklF1LiVDVwahoSd2rJkKF4IcXLFaRpYaSRPWeBS44uh+NNnqQI+uHck1UQ0s1bLRmRU0rT4vFhcQ8MirWdt7MJcuaZx8Ur68fjPS0hcPkyiGwfkIPrI1RePktv1VFcS46PpRpJDu0sEq2qPF3egEMwP24DlayaKqLZeDAzsoQKBs1U8rMjStl7yfFBSpBTlnPSGWfR3LI9IqSbYFA+6Ti5Ql2kibv0W0xOWO5EzRD1+1z2vrncVe5svkEl9DvzMblD8XoD/FTKtZ2vs0XkzLOcKOZb6i0q/coOPQSlYbH28jm6q45wqwW/cb0uJSh3G020f2bZl35KWfsNwnyPLVTyYquMR+xOln2DmBGVDAbNVPKzI0pRLTk+SBFyznqSbK/IfrPbnoSASC0ZMpRrOy9XkMaFkUb2qeFnuaO1Y2XXihw6XCtNQq9Rru1cg8qS9HxO6sDiHhiU58quzrYgp57GDDmuNlACzvlN6qpX9pRePkdv1VFcS85EupMji64+fMKLRd9cF23KPCRaqOTFKsnjL3bZHxnLjL2/+wDD004lPzqiFNWSv7PMzzghm3LOGoCPjnm2fyhIN8GgXNt5uUJdpFkdU3asLKnlJiE4TwH+x+/lUrLjxdKtbF8mOFuhCZwsGViM8Pb9jwPlAjCoGCKOzrYi555KkSXWpBJ8ObSJUEsQSm9GPVR5+RzdVUe41yKVvMb2w/0uj3x8Zt1MS8js+tgWzVTyxlz70WPbdwQzMjmAQTuV/OiIUvz3ks85s9ASOnZSYs24C+eiPoS7pJYMGSoWUupd4WtC/rmhLtLI3jQCLZfZ+exymWM8WLLNQ/4gO98MHxMV6w2XLKlmkutTDR2I6mBxDwwqtJ1X2Noh5543kwZpk6Xf3e2v0e80bO3uU/aVXj5Db9VRXkvexPZttN7sPT6HqvtCdHkhO8ZkfqwmKnkdPFuzrA6RuMRQZkQlg0EYlI1U8pMjSuFvXOc4tdAaPNbIfJZxjwbpJhjUTDq1rvCKHon8rIs0a+tdD5vcaO/4601uE85NDrB/2nid9yfeGmdzsuRjAlEdFesN8DPpELZ2zE1yXqeHoU2/+7B1EuW2l5E9Lyovn6G76gg3W6aSN/JuMtP83F+beUB5jK1ZX+1Xw72ZMLZmfrA2Knlns9n0v7d2yc3Y/c2ISgaDhrXkJ0eUhrXk3YQ0R57fmyAzuLuG+Z5aMmSo0XaVrhBbvznpblr/8der222/STqwuZZcfp8DzI0iS1r5foCr0nZOltw+1wnvhcUuVI1J+IlU5cpOzrZF2hxjz4aNa756DXFLdgQOp26j3CtqTe237v3atbC9vGjM3OXP6a06KmrJ20UADSWGbyeKAz0fuoD5ztuoZGPaUAwzkBm7vyEAo9NSJT84opT9xnWWjIXkiMbYiwekm2BRlyTNg14ncYUlnKTzdV2kqZzTt/mmwv4+47WLk8pzgrPdbMm8ZV4MHqI0KBeAQV0iNDuCTk3Y2mC3OYSh7/WnT2aS8X3w5e+/9juO93m8/KF5uft0Vx3hdkt+4zqQje3qssZpiBw9wMzjsJFKzk4cqmHGMSOTAxg0VcnPjShNa8mZ0Dx6nSZ8oNSSIUPdQkqNK6zRRHZsqIs0S+KqoJzw6/TqE/v7XIoTsv0OYfq+15K551wYPUYpsLgHBnW5slfYWpEmOSmSVXTKvWe9Ob3P2suf0Vt11NSSc9Xk75PlwBOz9nzkIpqq5MxgOzlvGDOiksGgrUp+bERpW0s+Dc3Dl2lIN8GgTtvVuMIaTGTHlrpIc54R6nP6aQ5wTKVkt4sn19WSHSx5njFuGT5IpZAIgUFlBdQrbC1Ik6wU2X1heo963vlioKoAay9/QndnCzdcrJJrZ44JdfIYPyq2VcmnU+qpYUYxY/fvPsDoNFbJT40obWvJE1pofoCrhtumlgwZqhdSil1hSfrUo5WR5iQ3OjvhJAc43kmsOru4cuV6w9uWLBPJ1JLhA6nWdk5hKyJtDClyErXOwtaZcjm7k8rL6/RWHXW15AnNSmeF5Jl0OSHbfBDmcdhOJeujJ3fSIGZkCRUMwthsqZIfGlFa/sb1i2XuXKhZr+0F6SYY1E86pa6wqLiTw3WRRvsadc4F07tUr/9q5hLi6p3tPUtqWY7CA8L3ker1BvhpdAtbQkmbCfXlj8xJStTKhcXay2t0Vx3hnmtU8vTYBzOZKereTvHH1MZmfsaWKnnq4jB86kZzJzOiksGgdS154okRpXkteWIfmb8ekXyGxJ1aMmS4spBS6Aqy6H86pVVGmmNKaLXf3+VpKjVd1SfGXdF2b1jyYI1TqCXD53GlAuoUtmZebQoixzFqWatWh6hlPWTt5VN6q47qWvLML1F439/mn7ae+fX1OmFqL3tGZx4IV1RyFV/yo3KTGUtGzgBm5BvXYHBVJVfxvIji8F5yAZNZXnZ5hkSeIN0Eg2tJUpkrhL+4ko0htZFm022J+NtcPnObv5zm3OBs3Sz5UVAuAIOuYauSSdEVhKGFX/KH674Lo2Ll5Y90Vx3h3kt/4/oHcY9Kfh5MDmBwi0p+Hg615I8kzJ7UkiEDCylehOkbS3rAmAQDcmUvelvyWi3580El6+D5YIBKVrmnlvw8SDfBAG3nBc7mBWMSDEiEvOiuOqb+UckpqGQdVDIYMDmoUEvWoZYMBmg7L9B2XjAmwYBc2YvelqSWrINK1un+hgCMTvAcVHKCw29cfySkm2BAuulFcDYs6QFjEgzIlb3obsmpf1RyCipZh8kBDKglq1BL1gmJO7VkyMBCihdh+saSHjAmwYBc2YvelqSWrINK1sHzwQCVrMJ7yTqkm2DApOMFzuYFYxIMGCJedLfk1D+/cZ2CStbhWyRggEpWoZasw3vJYIC28yKkm1jSA8YkGJAre9HbktSSdVDJOqyPgQEqWYVasg7pJhig7bwIzsb07QFjEgzIlb3obsmpf1RyCipZB88HA1SyCrVkHWrJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJevwLRIwCJ6DSk7gN651SDfBgHTTC2rJXjAmwYBygRfdVcfUPyo5BZWsw+QABkwOKtSSdULiTi0ZMrCQ4kWYvrGkB4xJMCBX9qK3Jakl66CSdfB8MEAlq/Besg7pJhgw6XiBs3nBegMY8L1LL7pPAFP//MZ1CipZh4QFDFDJKtSSdXgvGQzQdl6g7bxgTIIBubIXvS1JLVkHlazD+hgYoJJVqCXrkG6CAdrOi+BsTN8eIIHAgCHiRXfVMfWPSk5BJevg+WCASlahlqxDLRkMWEjxgvUGLxiTYEBFyYveqoNasg4qWQeVDAbBc1DJCfzGtQ7pJhgw6XiBs3nBmAQDhogX3S059Y9KTkEl67A+BgbUklWoJeuExJ1aMmRA23kR0k0s6QFjEgxQyV70Vh3UknVQyTp4PhigklV4L1mHdBMMmHS8CM6GJT1gvQEMSIS86D4BTP3zG9cpqGQdEhYwYHJQoZasw3vJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJev0/u4DDA8qWYVasg7pJhig7bzA2bxAAoEBubIX3S059Y9KTkEl6zA5gAEqWYVasg61ZDBA23nBeoMXjEkwIFf2orclqSXroJJ18HwwCJ6DSk7gN651SDfBgEnHi+BsWNID1hvAgLDlRXdLTv2jklNQyTp4PhhQS1ahlqwTEndqyZCBhRQv0HZeMCbBgG9ce9FbdVBL1kEl6+D5YIBKVuG9ZB3STTBgadYLasleMCbBgCHiRXfVMfXPb1ynoJJ18HwwQCWrUEvW4b1kMGAhxYswfWNJDxiTYECu7EVvS1JL1kEl6+D5YIBKVqGWrEO6CQZoOy9wNi9IhMCARMiL7s429Y9KTkEl63T/7gOMDpODCrVkHWrJYIC284L1Bi8Yk2DAQooXvVUHtWQdVLIOng8GwXNQyQn8xrUO6SYYMOl4EZwNS3rAegMYUFHyovsEMPWPSk5BJeuQsIABtWQVask6IXGnlgwZWEjxAm3nBWMSDMiVvehtSWrJOqhkHdbHwACVrMJ7yTqkm2BAuukFzuYFYxIMGCJedFcdU//8xnUKKlkHzwcDVLIKtWQd3ksGA7SdF2H6xpIeMCbBgIqSF71VB7VkHVSyDioZDFDJKtSSdUg3wQBt50VwNqZvDxiTYECu7EV3S079o5JTUMk6eD4YoJJVqCXrUEsGAxZSvEDbecGYBANyZS96W5Jasg4qWYdvkYBB8BxUcgK/ca1DugkGpJte4GxeMCbBgHKBF91Vx9Q/KjkFlazD5AAGTA4q1JJ1QuJOLRkyoO28CNM3lvSAMQkG5Mpe9LYktWQdVLIOng8GqGQV3kvWId0EAyYdL4KzYUkPGJNgwPcuvejubFP//MZ1CipZB88HA1SyCrVkHd5LBgMWUrwI6SaW9IAxCQYspHjRW3VQS9ZBJevg+WCASlahlqxDugkGaDsvqCV7wZgEA3JlL7pbcuoflZyCStbB88EAlaxCLVmHWjIYsJDiBdrOC8YkGPC9Sy96qw5qyTqoZB08HwyC56CSE/iNax3STTBgadYLnM0LxiQYMES86K46pv5RySmoZB08HwyoJatQS9YJiTu1ZMiAtvMiTN9Y0gPGJBiQK3vR25LUknVQyTp4PhigklV4L1mHdBMMmHS8CM6GJT1gvQEMSIS86D4BTP3zG9cpqGQdEhYwYHJQoZasw3vJYMBCihdoOy8Yk2BAruxFb0tSS9ZBJet0f0MARgeVrEItWYd0EwzQdl7gbF4ggcCAXNmL7pac+kclp6CSdZgcwACVrEItWYdaMhig7bxgvcELxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtgwKTjRXA2LOkBYxIMGCJedLfk1D8qOQWVrMO3SMCAWrIKtWSdkLhTS4YMLKR4EdJNLOkBYxIMyJW96G1Jask6qGQd1sfAAJWswnvJOqSbYMCk4wXO5gXrDWBA2PKiuyWn/vmN6xRUsg6eDwaoZBVqyTq8lwwGaDsv0HZeMCbBgFzZi96WpJasg0rW4VskYIBKVqGWrEO6CQZoOy+CszF9e4AEAgMSIS+6q46pf1RyCipZh8kBDJgcVKgl61BLBgMWUrxgvcELxiQYkCt70duS1JJ1UMk6eD4YBM9BJSfwG9c6pJtgwKTjBbVkL1hvAAO+d+lF9wlg6h+VnIJK1iFhAQNqySrUknVC4k4tGTKwkOIF2s4LxiQYkCt70duS1JJ1UMk6rI+BASpZhfeSdUg3wYB00wuczQvGJBgwRLzorjqm/vmN6xRUsg6eDwaoZBVqyTq8lwwGaDsvwvSNJT1gTIIBFSUvequOuZb8H7//1+//xX+v/+b/+/0fwS7/U7aOTX7gf/J/v/F8MAie8/07Dhn+e/33+z+DXb6S/T/5v/n/wgyISoYM8xCRiMJ/F/6T//s9O9tfry3+u/afWDIkQqhkyDAPEcLWW/+9vK236phVMkAF/y5jB0BBRglAMTJ0ABRkkACMhYxPAAUZJOBCT9WBSoZaUMmQQUYJQDEydAAUZJAADAWJEGSQUQIuoJLhSTA5QAYZJQDFyNABUJBBAjAWMj4BFGSQgAuoZHgSqGTIIKMEoBgZOgAKMkgAhoJECDLIKAEXujpbuIH5t3b4b/vf/Fs7/zPZ/dP/49e7wCJ4TviFGP7b/fdnsMvXYSf/8etdYPH69a7DwOG/C/9hSa//5t9Bk/EJoCC/3nUcOfxX+98Yv97F30tOmP8S1L/IBiygksEgDBH+ElTC/Jeg+HvJCfxJFTBgiHiBtvMiWJJECDIwRLzorjqm/lHJKfy9ZB08HwxQySr8vWQd/l4yGKDtvGC9wQssCQbkyl70tiS1ZB1Usg6eDwaoZJX/GSIKteQE0k0wCEOESccDpm8vWLkBA7536UX3sDX1j0pOQSXrMM2CASpZhVqyTpBA1JIhA4rEC5akvMCSYECu7EVvS1JL1kEl67A+BgbBc1DJCbyXrEO6CQbUkr1gvcELJBAYkCt70d2SU/+o5BRUsg6TAxhQS1ahlqzDe8lggLbzgiUpL7AkGJAre9HbktSSdVDJOng+GKCSVXgvWYd0EwxQyV4wfXvBmASDMERIhDzoHram/lHJKahkHb5FAgaoZBVqyTrUksGAhRQvsKQXWBIMyJW96G1Jask6qGQdFqPBAJWswnvJOqSbYMCk4wWW9AJLggFDxIvulpz6RyWnoJJ18HwwQCWrUEvWCSqZWjJkYCHFCyzpBZYEA3JlL3pbklqyDipZh2+RgEHwHFRyAu8l65BugkFIkhgiHmBJL5BAYECu7EV3S079o5JTUMk6TA5gQC1ZhVqyDu8lgwELKV5gSS+wJBiQK3vR25LUknVQyTp4PhigklWoJeuQboIBk44XWNKLYEnCFmSgluxF97A19Y9KTkEl6zDNggEqWYVasg61ZDBgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwQCWr8BvXOqSbYEC66QWW9AJLgkEYIiRCHnRXHVP/qOQUVLIOkwMYoJJVqCXrBJVMLRkysJDiBZb0AkuCARUlL3qrDmrJOqhkHVQyGATPQSUn8F6yDukmGIRJhyHiAZb0AkuCAbmyF90tOfWPSk5BJeuwPgYG1JJVqCXr8F4yGLCQ4gWW9AJLggEq2YveqoNasg4qWQfPBwNUsgq1ZB3STTBg0vECS3qBJcGAipIX3Z1t6h+VnIJK1mFyAANUsgq1ZB1qyWDAQooXWNILLAkG5Mpe9LYktWQdVLIO62NggEpW4TeudUg3wYB00wss6QWWBANyZS+6W3LqH5WcgkrWYXIAA1SyCrVknaCSqSVDBhZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MAieg0pO4L1kHdJNMAiTDkPEAyzpBZYEgzBESIQ86K46pv5RySmoZJ3u4xVGh1qyCrVkHd5LBgMWUrzAkl5gSTDgG9de9FYd1JJ1UMk6eD4YoJJVqCXrkG6CAUuzXmBJL7AkGDBEvOiuOqb+UckpqGQdPB8MUMkq1JJ1qCWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVfiNax3STTBg0vECS3oRLEnYggx879KL7mFr6h+VnIJK1sHzwQCVrEItWSeoZGrJkIGFFC+wpBdYEgxYkvKit+qglqyDStbB88EgeA4qOYH3knVIN8GAup0XWNILEiEwoKLkRXdnm/pHJaegknWYHMCAWrIKtWQd3ksGAxZSvMCSXmBJMCBX9qK3Jakl66CSdVgfAwNUsgq1ZB3STTAg3fQCS3qBJcEgDBESIQ+6q46pf1RyCipZh8kBDFDJKtSSdaglgwELKV5gSS+wJBhQUfKit+qglqyDStZBJYMBKlmF37jWId0EAyYdL7CkF8GShC3IgLN50d2SU/+o5BRUsg6eDwaoZBVqyTpBJVNLhgwspHiBJb3AkmBAruxFb0tSS9ZBJevwLRIwCJ6DSk7gvWQd0k0wCEkSQ8QDLOkFEggMyJW96G7JqX9UcgoqWYfJAQyoJatQS9bhvWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLehEsSdiCDNSSvegetqb+UckpqGQdPB8MUMkq1JJ1qCWDAQspXmBJL7AkGLAk5UVv1UEtWQeVrIPngwEqWYXfuNYh3QQDJh0vsKQXWBIMwhAhEfKgu7NN/aOSU1DJOkwOYIBKVqGWrBNUMrVkyMBCihdY0gssCQZ879KL3qqDWrIOKlkHzweD4Dmo5ATeS9Yh3QSDkCQxRDzAkl5QLgADhogX3VXH1D8qOQWVrIPngwG1ZBVqyTq8lwwGLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlggEpWoZasQ7oJBkw6XmBJL4IlCVuQge9detE9bE39o5JTUMk6TLNggEpWoZasQy0ZDFhI8QJLeoElwYBc2YvelqSWrINK1mF9DAxQySr8xrUO6SYYkG56gSW9wJJgQK7sRXdLTv2jklNQyTpMDmCASlahlqwTVDK1ZMjAQooXWNILLAkG5Mpe9LYktWQdVLIOng8GwXNQyQm8l6xDugkGYdJhiHiAJb3AkmAQhgiJkAfdVcfUPyo5BZWsw7dIwIBasgq1ZB3eSwYDFlK8wJJeYEkwIFf2orclqSXroJJ1uq/qwOigklWoJeuQboIBk44XWNILLAkGDBEvulty6v8Glfz1HUoGf/zx9VVUTfn99Wr+/fUle+7mHpW8POd32XNWmrEBeD4YXFPJiyv8VTa2v/7q7QqVXKwl93f5xoTHo5YMGa4tpPRJIn5VzulT83ibJQ5ee/kDT7Lk2LC4BwbXcmUvZ3sjcfiqvOvmX5HrrTrqa8kv20dKPkn52COWSX/PCnWhj3XqVXK1XY7PaZ1SacY28C0SMLigkn/vh7Y5wv4cwRUqufIb10O4fGNIN8HgQpLkk0RUz+n7Xs1TkrhneHjl5VO6WfLjoFwABhdyZS9neytx+D11XHPG1FcaiI6hKovVW3fVEW6yRiUfnt6O08eZwPoIUvNWzwUOzHdRo5Jr7ZKaJW+XWjM2gskBDKpV8hSVE3KDexBXqKS+lvzM56wlqGRqyZChfiHFJ4montOl4ZbcZJmmANkIUXt5hV6W/DxY3AOD+lzZydneTBzmM8o7nm866SB9lHPMvnqrjupacmi/wXxA1VrnJRVFPHYx0HzbNSp5vtEVyy76IDp/0EozNgOVDAZhZNao5JBvKJyOMtUVxpeP1e8lj+LyjSHdBIMw6dQMEa8kQs6MWHO61uvEWWjSRO/E6X1WXl6llyU/j1pLwo+jtgLq5WxvJg5yF6XCOoaxQ3TUBY6OnHJOd9UR7rJCJR8/yIszx1l8+SXHj9yeBM8fcoVKrrTLiVlOh0KlGduBSgaDulrySa44cTK4h3GFSmpryU99zlrCc1JLhgyVCyleScTRA/Nz+nkg0+fLE/+eUO+z9vI6nSz5gbC4BwaVuXKrsCWUDtblNmTbInZ3XSXbAr636qisJSex+qIaPHnm86ng7hpKpUqutMv5DFk5o94+dLq/IQCjU6WSzz1+QpsfTirP44/KylryOC7fGNJNMKhLkrySiLo5PRfItHs/TwHU+6y9/Al9LPmJUC4AgzBEPMoFdc72ZuKw3EZhr7G749XLVXLBfXVXHeE+y1Vy8hGUq8HvCflnQHvo3UA5tL95+bJSJdfZZde6wC6743bzljA5gEGNSs4lfxOp02dcYXCpVVdLHsjlGxMejVoyZKhaSNmVZA6uU5VEbE+cqZrT5V8vUpc93qX8S8jHvYLLn9HHkp8Ii3tgUKXtvJxte97hMkX3Im0NYbewiGHZXihXyQVyvLfqqKsl74NzoHB9Nf6A86/1CspHvx78EtOttr7ZSHUquc4umwGUPqdyZq0ZW4JKBoMalbx1nJcv/Nr+PGMy0rKuULj62Ymq37geyeUbQ7oJBlWTThhPL95LIrah6UXtnL65QuKysn9icfDNJZL7NC5fHPm6WPIjCZYkbEGGHs72buIQGxd2uXSXRKBNxMqTi6qR7qoj3GjNr3dFwnkTuWdcl0c2Nlx3Jp/Z8nFuDaLubM/8Idf8eldkvtesXdaBvG20jmXZsVBrxqZ0/+4DjE6FSt6E0s3Y3uR/h6G2us4ArlBJTS15KJdvTEgPqCVDhpqFlBZJhJxcNKdve1g99tjvGuE2Dr7Ze/Bw6/LFcq23JT+HGkvCj6RG2zk527uJw7nq1Yl3WB8NltRPtrP0Vh31fy9ZCOdN5FTysjyyM/nyQRwf++TAMlRuzQ0bquRlfOxH4jKWj3apNGNbuq/qwOiEQVmmkvXkb2Lx+YPTL/tHcIVKat5LHsrlG0O6CQYVdbsmSYScWz+nr/0ezpW9R09e81nZIdRe/pTelvwcSITAoELbeTnbm4nD0rAwT4n3V+8IS6Qr6qm7s4U7baOSl9B++IgXAx32y97EHNc/ijdop5LPHn89INtCrRnbwuQABuW15GVoJyNKPzKWK1RSUUt+9HPWEsI7tWTIULGQMrvHhGsSIedemNNP+j29G/1CtZc/p7clPwcW98CgIleePWriTWd7N3GQVqWLbkt3sl1B3YP1Vh0Na8nREMlqwbJiIdsv4t7UGvFChZ+dC/MAaKKS49BKW+jPWWnGxvCNazAoV8nz6J1QBlQc9TtnGMsVKqmoJT/6OWsh3QSD8iSpTRJhnhrn9LTbJT+V7ReyTwkH6m3+KTtLL39Ob0t+DpQLwKA8V/ZytjcTh3h64bheLlqW1WxZ4lbZqd1VR7jVJir5fOZYPo3dyobsU+wWTXqnndqpZGmgjVc5snvOWjM2hskBDIpVchzaauhWIvZgrlBJeS352c9ZS3gkasmQoXwhZXaOCd8kQk49n9OjWyo5Xzy0PTlzL6rsrbx8ht6W/BxY3AOD8lx59qeJN53tzcShVvXGa14IBHJmadjqrTra1ZKjDWVzizYVxI9Iu2DlVODBPOBaqmStQRzlsjlTacbWoJLBoFglz2N3Qg3KyuAOicl+z0IPV6ik/DeuB3P5xpBugkHxpNMoiTDPlAaqV8qh7f3HeT6XA2wjhewqvXyG3pb8HIIlCVuQIQyRokTIy9neSxxuFMkxyJWmMd1VR7jXFio5NxMsBzcrG7JHt5scu9FQ8x22UMlxuKpDUY5tzFJrxtZ0H68wOqUqeYnKsn0gBuFlcI/mCpUU15If/py1BJVMLRkyFC+kzK4xIZt75NiF2UvONOd0tYHEsW23mWx2udbGwWsvn6G3JT8HFvfAoPh7wrM3TcjmHjlWcKE3E4dK1Vsrqjcskr00i+mtOprVknMzgXJ2bjll/Yhl8wbmHluo5PigsrlHjm1OrjRjc7q/IQCjE0ZkiUrOJn9KzB/NFSopfi/54c9ZC+kmGJTW7VolEXLiqc/9+f1C9W7FnaW5Oo8qz1B7+Qy9Lfk5UC4Ag9Ih4uVs7yUO8ezCQR1v+oJInqf8QLH/dFcd4W5bqGQ5fvJsyUcfd5zYXI6e9ubOfD8tVLI8qG4XGambk187is3YHCYHMCitJRsun3iSbA/jCpUU15Lnx3juc9YSYh61ZMhQupBiRBQ5Wp9EXD4xUOuw0ry0s7rL97bk58DiHhiU5speziYNryUOtaq3UlRvWUrJhV31Vx2tasnGJx8NtRyW7TNTyGdyn6Xm+++vkmvN2BxUMhiUquQYZ2Uz4eDzw7lCJaW15Kc/Zy2km2BQOunMjnHe9HIS8TrvoiiM/iybJtK8tLO6y/e25OcQLEnYggylFdDZl953trcShxtFcnzeihSmu+oIt9tAJVsf7evw0rOV+9VONW8zd3i7Sn4d25xcaMZr8/cV+MY1GBTXkgXZTDiM/cqIMhylteThXL4x4XmpJUOGwoWUZkmEnHfN5Wp7lealndVdvrclPwcW98CgUNt5OdtbCZKcXHK/gXe+bx2fp7CrQG/V0aqWLIdPH+3w0ce/CHiaRcrx23LD+f4aqmR9zMuxdejJjlIztqf7qg6MTqlKtjhE/dfWQK5QSelvXM8P8eDnrIV0EwwKJ51mScTV82bEX4snzVfz4vSz7vK9Lfk5kAiBQaG283I2aXbaYy5xiCK5MKtYRPKFAHBFYHd3tnC//io5ro+cWjE2kKERP6XXloK1UOLNPKRaqORcg4NR6s3YHiYHMPBSyfPAXsZ+DK7juEIlhbXk8Vy+MUElU0uGDIULKc2SiNdp5y6ZpfLk2kUwaV54+d6W/BxY3AODwlzZydneSRzu/L51PLcmmvZWHY1qyXaslwZy/n5LoXbyeJfmKln70OXQ+pC1ZmxP7+8+wPCE8eivksdzhUoK30t+/HPWQroJBiFJKhgis1vkHONqEiGnXfK4mJuWVk4q9Wfl5Xtb8nOgXAAGYYgUJEKzI73vbLEkLZsK0iDt6E6RvPQl20V0Vx3hhv1Vsh3rXw3kfDvW3x2W5/6aqOTztZR0NajSjDfA5AAGTrXkw9LneK5QSWEt+fHPWUt4YGrJkKFsIaVdEiGnXfK42j6leWlflZfvbcnPgcU9MCjTdl7O9kbiIKeWJvZXvjO9IKfWfRWut+poVEu2P7LdRx/tnjG7tLgrN5xvr4lKjg+ejBNl8FWa8QZQyWDgpJLnYT0h3jCeK1RSWEt+/HPWQroJBmWTTrsk4uJpgXhTpXNmTFjtQDFTe/nelvwcgiUJW5DhXme7njgsikS2LaT1JeePfZUGrBfdVUe4ZX+VnD8a2H1kBYmftLgrLM931EQlLxPhQSZHb9laQXaUmvEGuo9XGB0flRyXWOPIlq2BXKGSwlry/AhPfs5aQjiklgwZyhZS2iURF0+bWKJYoeqNuUHhFFt7+e6W/BxY3AODslzZy9nsRic9LcKjTYzaUduX0Ft1tKklF6yP7JrY6yAlTTyZR1QblRwH6948q0he99aa8Qa6vyEAo+OjkkMWEhBHGtAVKin7jevnP2ctpJtgUJYktUsiXmcZWapGdNXSHmPQK/Tt2sv3t+TnQLkADMpyZSdnu5w4LEHk1++vuaPv72ygk5uZ7ubr+9X+q/zb0/HkylDaXXWEe3ZXyQXrI3EZdLaw/Dtnu5KR4khDlbwMlW2rVTpvnrDWjDfA5AAGLip5qZLIwB7QFSopqyU//zlrCcqAWjJkKFtImZ2iSRLxOit7ZYXf65xe5KuvHHWm5AZrLz/T25KfA4t7YFCWK89+9L6zXU4clqizhp/p36cRZV2Zk/9/pjA0LlmdbJfSW3W0qSUXfGS7C2z/fULJJR2Zu2ukkmObwLwOs53wtg9Ya8YbQCWDQRiO76rkJRbHcT2gK1RS9l7y85+zFtJNMAiTjou2K/EuBTmr3OF+f32FYb1guf3UfJejyu4zai+/0tuSn0OZJeEHU1YBnd3ofWe7mjjE846c3bgcTihaqJO2FQHrRXfVEW4alZwwd9dKJS9LKgrbAXR15Dek+3cfYHQ8aslLzhjdYUBXqMStljz4c9YSPmpqyZDBrQJ6MYmQs8odbldnsb1+WRN8Yc6vlZff0NuSnwOLe2BQpu1mN3rf2S4mDofQs0UNK4fQs6FAFcR7rBYQvVVHm1qy2DL7YK8m8wXiR5VbYrg5LM/dtVLJ/+P32WD73pmg0ox30H1VB0bHQSUv7rEM6wFdoZKyWvLzn7MW0k0wKJp0GiYRcla5w+2nd9Pp96mqPb1WXn5Db0t+DiRCYBCGiJkIeTnbtcRhH3kOKPFuH3n2nH9LW1g6q4lYM92dLdx1F5W8aVPypt3Nb+O1Vclnw+1wVqUZ74DJAQzeV8lr7JYdQ7pCJWW15Oc/Zy3haaglQ4aihZSGSYScZc3pK+KhMwVuuvtuWUEKWXn5Db0t+TmwuAcGRRVQL2e7ljhsI0lKMr6zotoMBrGz8jga6a06+tWSN21K1lNK2jjSWiWr4/Nor0oz3kHv7z7A8LytktdYvDr7gK5QSdlvXD//OWsh3QSDoiSpYRIhZ11UyXZna8CbKOil8vIbelvyc6BcAAa3OtulxGEXeBSOsWgbeDSkmU6siF/4/kl31RFum1pyQmOVvIyYA/vTLo38tjA5gMG7KnkN3RtfH9AVKqGWrBNUMrVkyPDoWnKBo8bbEkqDhFATB6gle8HiHhgU5cpeznYlcdjFna/fswjf/NL+xL7H7aHvr7n5r52SyfW+pHUXQkZv1UEtWaepSs4s4ey+3F9pxjtAJYNBGI7vqOQlFm/H2YCuUInfe8ljP2ctpJtgECYdc4g0TCLkrKsq2fTUYz5g3V7l5Tf0tuTnUGRJ+MkUVUC9nO1K4hCmXuGleV9shO/ucpswtf2Tyr824SijgGOrimi10F11hBunlpzQUiXvlnD++H79be6FzQNWmvEOUMlg8GYtefGG3TAb0BUqoZasE56GWjJkeFwtOfCr7u8f/95WZQrur/LyArVkL1jcA4OiXNnL2S4kDvGy056D/l5Dyzbm6Xsn1gudf5t6aXNlXa236uj395K3H9nrn9lp6ObFy4YqebMksyzhbL/nsPpCrRlvoPsbAjA676nkNVeUHS8GdIVK/P5e8tjPWQvpJhiUJUmzUzRJIuSs3JVV1ipLma+usa9IfNZefqK3JT8HygVgUJYrz270vrNdSByWUnJ6k0tk2Vxv1S3JfayHTh9DjtcH0UB31RHuvItKlibzBbb/PqHkko7M3bVRydJiYjva1hlyHQ61ZrwBJgcweEsln4XiAV2hEv5esk6YkKklQ4ayhZTZKZokEXLWBYdbss2yc9eijOwwqLx8f0t+DizugYHbklSJs9UnDkuw0e5RiSzLLiWJMQNXvL1rAaO36uhXS5Ym8wW2/z7h5rA8d9dEJS/j5fixL6NwOVBrxhtAJYPBOyr5dL1yQFeopOw3rp//nLWQboLBremmgpx1xeGWSV22DZb4V9hX5eW7W/JzCJYkbEGGMETsRGh2o/edrT5xiGfo8SCNLLKt5zBG4FoOmwmQSnfVEW7dXSXHpYVc6USazBeQjyRniJvD8txdC5W8jJf0YZOBWWvGG+j+3QcYnXdU8jyWA8fxPKArVFJWS37+c9YSVDK1ZMhQtpDSLomQsy45XJzUC09eijKybVF5+d6W/BxY3AODslzZydnqEwfZOhGuSyCKkSXexMmNxkCk32Q8aptDpbfqaFNLjlIws3Kwa1IwUgqaeNJMJecG23Es1ZrxBrqv6sDohOF4USUvoTYZYgO6QiVl7yU//zlrId0Eg7K6Xbsk4nVWqRI9ICeX9hnzA3M9TZDmhZfvbcnPgUQIDMqGiJOzVScOcessqkmny/G4LZtHsst7sa+rOUt3Zwv37q6SC+aV3frIbkNHWlybqeppppLluDpekpEmm6VmvAEmBzC4XkuOgVgbYXJkIFeopKyW/PznrCV86NSSIUPZQkq7JOLiaS+M7PJIzAFKO6u7fG9Lfg4s7oFBWa7s5Wx2o31Pces0JZHj8QkOmwm568mhy+Git+poU0su+Mgkur+e3R4pdxdQ5jtqoJLzKzhxyotHD5sKOzPeAN+4BoPLKnlZcdS8XI4M5AqVlNWSn/+ctZBugoFXunk1iZDTMj6Zo/Js+zH2SPOyy/e25OdAuQAMynJlL2eTRsWJw2sj028UI6+teJun188om3juZX/prjrC3furZPujVz+y84+45Gv3nswP0EAlR8OcjHg5Gs+uNWN7mBzA4KpKXkWy5uTjuUIlhbXkxz9nLeFxqCVDhsKFlNktWiQRctr5hbPI2aX+GgNA6U1K87LL97bk58DiHhgU5sqzI73vbLWJw2sj0+3+gvblpUF6wSWxu7ym1lt1NKolR5ue20UayPmydW4J+0PyZe6vgUqWkXr2HIcMuNaM7UElg8FVlTwP5IA6mMdzhUrKfuP6+c9ZC+kmGNSlm/5JhJx20eMqV7Vqy7RVl+9tyc8hWJKwBRkKK6CzI73vbJWJgx1m9he0w8yrgdIiap7rGUt31RFu318lm8sfh0/e/Axex+9LDef7a6CSjcMHO9SasT2oZDC4qJJjLD0ZXuO5QiWFteTHP2ctQSVTS4YMhQspzZKIq+e9qHVYaV7aW9Xle1vyc2BxDwwKc2UnZ6tMHMzmhxbmXZ62WErJsn2B3qqjUS3Z/GTFpNFyVqiPlr4tLM83dL9KPtpBNkvN2J7ubwjA6ITxWK+SQ9Yxcza65PA4rlBJ4XvJj3/OWkg3waCwbtcsibh63gvrto5I89Leqi7f25KfA+UCMAhDpCAR8nI2q9k+cYhXPc9I9i3k7MyQP2vx2l2U+5zRXXWE+2+gkq2PXg4vjy7b1uXsWowTc4f9VXKtGZvD5AAGl2rJceHyPJgO5wqVFNaSH/+ctYTJlVoyZChdSJkdo0ESIeedXdfAcugj0ry0t6rL97bk58DiHhiUarvZld53NisQyGG5o5hwnYcZtZacCTMnKjne1jsJS2/V0aqWbCxVRNMtpxtLFa+j5TPN28w32F8l15qxOahkMLiikuM4z6w4DucKlZTWkp/+nLWQboJB6aTTKomQ8y663HFOt5Dmpb1VXb63JT+HYEnCFmS42dkqE4fDZso+sNhhRhocLrhkdgWpzyndVUd4gAYqOR4/CSQyMFabxw9BXzCxFz68me+n3a93nX3kiV1ku9SMzeEb12BwQSWvIjmzYCothnGFSkpryU9/zlrCA1FLhgylCymtkgjjxO/vv76n/xlT/uKxX9JeNo8kt1l5+Sy9Lfk5sLgHBqXazsvZpGFh4iDb5zcYb+u1FW/jXOxKg8N9xm7fihW9VUerWvJiY92qcnDz5OmeDX/K0XfWI+qYb7+dSj6b0+ToaoVaM7am+6oOjM4FlRy9Iju0RnOFSgp/4/rxz1kL6SYYFE86s2uctb2eRMiJZ3O6HD67w+PhvH+nh2W79PJZelvycyARAoNibTc70/vOVpc4GEpkOUGiXixkmIJPNoWl/iHb1+jubOEJWqjk7BJI/IQ2n2fuQ4vXutFQ82feQCXHsaQfT41Wa8bWMDmAQb1KLhLJw7lCJcW15Ic/Zy1BJVNLhgzFCymNkgg5U5+z870q7mzkm8nVKi+fpbclPwcW98CgOFd2crZsKIh9LIlDXomsx2PKIpsnYWg5frhP2VuU+JzTW3U0qyXn7BPnie2Dxw9FM0aISIEbU8PWKln/zOXg9kFlT6kZW9P7uw8wPGFIVqnk6BPnEfiFNBrFFSopfS/56c9ZC+kmGIQkqWiINEoi5MyzOT0moPrxeE9LvzGZPYl2cnB9hMrLZ+ltyc+BcgEYFOfKXs4mTQsTB9lzlnTJ0eVwvMmTKKgfzj1ZBd1VR3iGJio5swiixv24M/2IjWmlCfPH20AlL4NPaxDH1PZBa83YGCYHMKitJccAbs4Eg7lCJcW15Ic/Zy3hkaglQ4byhZQ2SYSceeZ02VRwiW6yPSE79GCQenjt5XP0tuTnUG5J+KGU58pOzlaXOMRd+i0mJyx3ooYtPQ4te99cUOutOtrVks/1oB72NYn4QvbfunY5300LlRxHnzLYljG1O1n2lZqxMahkMKhUycuot/1b2g3iCpWU15Kf/Zy1kG6CQfmk0yaJkFNP53Q5rjZQ0tPzm9SzTdlTevkcvS35OQRLErYgQxgiZYmQl7NJ4zQaqImD7FMDwnJHa8fKrhU5dLhWZXQ6pbvqCA/RRiWfLT6cLTBEkx7Ncba/KfOQaKGSF6skMvnkSK0Z29J9vMLoVKrkeQwH7FA6litUUl5LfvZz1hLCO7VkyFCxkNIkiZBzTwNUvLji3tqhxb3Tm1k8fHuo8vI5elvyc2BxDwwqvifs5Gx1icMSPNKrL4p4E/OWi6fB5vdyKdnxYulWti/TW3U0rCWvn8LOqssHcHxsffJYP4BbU8NmKnm1yuGBliF1NEylGdvS/Q0BGJ06lbyM7pJRNZQrVFL8G9cTT37OWkg3waAiSapPIr4m5J9nyLnnzaRB2iQM7pnd7ayOfMg31xxgd5+yr/TyGZpa8kdBuQAMOoStusRB9qZ3uVxmp2+XyxxvZw1b+1uSne+Hiu6qIzxFI5W8Lj5snlD/AGbWQ+tnfPYBtGYeEU1U8jo2t8nh6hDJoKo1Y1OYHMCgSiXXjeOhXKGSilryo5+zlpDpU0uGDDULKauXlCURr/Z5v5yb5Ob0tdOd7l373c/pq3vvr7m5jOx5UXn5DC0t+bOosST8SGpy5Vpne7VPwlZd4nASh1Y1fIgrehzaSJf908brlNrgnN6qo2UteRvGv2azfi2Ln2pg35h7vu7vzed1s5EaquTNQy3PuT65YphaM7YElQwGYVSWquTN0D5jN9pGcoVKKt5LfvRz1kK6CQZh0ikeInVJRHSrTdaXIm0yc/pm/n71OvW7jW2HU3eHpOvtOvkxna28/DkNLfnDqLIk/ESqKqBOYasucdjGEOl2228SV7Yh6nX5vXSZG0WWi7+fr3RXHeExWqnknSA8oD60HNO4OTWc77yNSt6NtRTFMLVmbAjfuAaDilryNkqfsR9tA7lCJTW15Cc/Zy0hGlJLhgx1Cymzk+gkScTiZtk8xm6zqcoE/vrez/GJyx5SgGP7433WXv6Udpb8adRZEn4gddpudiudmrBVlzgc4tCB5IRDHDqyv8947bxELKK36mhaS858Cvozn38Kd0flebA1UsnZsakaptKMDem+qgOjU66SS0TycbSN4wqVVNWSH/yctZBugkHdpFOTRKxeJjtUpEluTs+GMuXecymAcp+1lz+jnSV/GiRCYFCn7bzCVl3ikBHV2gm7L7wc2d/nErJk+x26O1t4jnYq+ewzO3vks6FSXIPxoqlKzsyRJ+dVmrEdTA5gUK6ScyF34TjahnGFSupqyc99zlrCc1JLhgyVCykVScTqZLJDRZpk5/Rf58FMPe88PT3+pNdM7eVPaGfJnwaLe2BQmSt7ha2TSHFyJ+fiXI8rp3HoGLZkt0us6K06GteSTz6FzFKk9il0MFBblXw6Nk8NU2vGVvT+7gMMT7FKPk/8tiSjbRRXqKTmN65nHvqctZBugkF1klScRCxaNXt5aWPM6Wfh7MRlz1KAszupvLxOO0v+NCgXgEEYIqU/0DLjFLYqE4eTwHJ2wkncOt5JrDq7+Eh31RGepKVKVlZB1cXShXSR1e7Dn8YqWR+buZNqzdgIJgcwKFXJRd+31kbbIK5QSW0t+anPWUtQydSSIUP9QkppErGkfNn5uqTNhFrvzZyU3uTk4efZbO3lNdpZ8qfB4h4Y1Gs7p7BVmThogSXn5Erc0sLWq1nVIt4ZvVVH81ryxP5TiD/SeM7+U/hysXMt8z20VMlTF4fBaZ1Sa8YmoJLBIIzOApVcKJLV0TaEK1RS+V7yzBOfsxbSTTAIk07tEClMIiQK5ae0V5uCOT3JNw1/P+abxsxae/mUhpb8YVyxJPworuTKTmGrMnE4Bhar/SFunS3tTVf1SVm6q47wlFdUchW/vl6S8Lsw0Zuav9p3i8nzOLiikquQx5yes+hBa83YgO7jFUan+BvX7zCAK1RSX0sOPO85awmPRy0ZMlxbSClLIn5NM72nb/2KvZblLr+n9q/mZTdRefkjLS35s2BxDwyu5cpOYeu65Ppd4uSby2ea/3KSCr1Vx+Va8odzj0p+Ht3fEIDRuUUlP48rteSfAOkmGLA06wWW9AJLggG5shfdLTn1j0pOQSXrMDmAASpZ5Vot+fMJS9LUkiEDCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJVqn/j+odAugkGTDpeYEkvgiUJW5CBWrIX3cPW1D8qOQWVrIPngwEqWYVask5QydSSIQMLKV5gSS+wJBiwJOVFb9VBLVkHlayD54NB8BxUcgLvJeuQboIBdTsvsKQXJEJgEIYIiZAH3Z1t6v+P/5R/wwIqWYfJAQyoJatQS9bhvWQwYCHFCyzpBZYEA7536UVv1UEtWQeVrIPngwEqWYVasg7pJhiwNOsFlvQCS4IBQ8SL7qpj6h+VnIJK1sHzwQCVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmF37jWId0EAyYdL7CkF8GShC3IwPcuvegetqb+UckpqGQdplkwQCWrUEvWCSqZWjJkYCHFCyzpBZYEA3JlL3pbklqyDipZh/UxMAieg0pO4L1kHdJNMKBu5wWW9AIJBAbkyl50t+TUP79xnYJK1mFyAANqySrUknV4LxkMWEjxAkt6gSXBgFzZi96WpJasg0rWwfPBAJWsQi1Zh3QTDJh0vMCSXgRLErYgQxgiJEIedA9bU/+o5BRUsg7fIgEDVLIKtWQdaslgwEKKF1jSCywJBuTKXvS2JLVkHVSyDovRYIBKVuE3rnVIN8GASccLLOkFlgQDhogX3S059Y9KTkEl6+D5YIBKVqGWrBNUMrVkyMBCihdY0gssCQbkyl70tiS1ZB1Usg7fIgGD4Dmo5ATeS9Yh3QSDkCQxRDzAkl4ggcCAXNmL7pac+uc3rlNQyTpMDmBALVmFWrIO7yWDAQspXmBJL7AkGJAre9HbktSSdVDJOng+GKCSVagl65BuggGTjhdY0otgScIWZKCW7EX3sDX1j0pOQSXrMM2CASpZhVqyDrVkMGAhxQss6QWWBANyZS96W5Jasg4qWYf1MTBAJavwG9c6pJtgQLrpBZb0AkuCQRgiJEIedFcdU/+o5BRUsg6TAxigklWoJesElUwtGTKwkOIFlvQCS4IBFSUveqsOask6qGQdVDIYBM9BJSfwXrIO6SYYhEmHIeIBlvQCS4IBubIX3S059c9vXKegknVYHwMDaskq1JJ1eC8ZDFhI8QJLeoElwQCV7EVv1UEtWQeVrIPngwEqWYVasg7pJhgw6XiBJb3AkmBARcmL7s429Y9KTkEl6zA5gAEqWYVasg61ZDBgIcULLOkFlgQDcmUveluSWrIOKlmH9TEwQCWr8BvXOqSbYEC66QWW9AJLggG5shfdLTn1j0pOQSXrMDmAASpZhVqyTlDJ1JIhAwspXmBJL7AkGJAre9HbktSSdVDJOng+GATPQSUn8F6yDukmGIRJhyHiAZb0AkuCQRgiJEIedFcdU//8xnUKKlmn+3iF0aGWrEItWYf3ksGAhRQvsKQXWBIM+Ma1F71VB7VkHVSyDp4PBqhkFWrJOqSbYMDSrBdY0gssCQYMES+6q46pf1RyCipZB88HA1SyCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usg6eDwaoZBV+41qHdBMMmHS8wJJeBEsStiAD37v0onvYmvpHJaegknXwfDBAJatQS9YJKplaMmRgIcULLOkFlgQDlqS86K06qCXroJJ18HwwCJ6DSk7gvWQd0k0woG7nBZb0gkQIDKgoedHd2ab++Y3rFFSyDpMDGFBLVqGWrMN7yWDAQooXWNILLAkG5Mpe9LYktWQdVLIO62NggEpWoZasQ7oJBqSbXmBJL7AkGIQhQiLkQXfVMfWPSk5BJeswOYABKlmFWrIOtWQwYCHFCyzpBZYEAypKXvRWHdSSdVDJOqhkMEAlq/Ab1zqkm2DApOMFlvQiWJKwBRlwNi+6W3LqH5WcgkrWwfPBAJWsQi1ZJ6hkasmQgYUUL7CkF1gSDMiVvehtSWrJOqhkHb5FAgbBc1DJCbyXrEO6CQYhSWKIeIAlvUACgQG5shfdLTn1z29cp6CSdZgcwIBasgq1ZB3eSwYDFlK8wJJeYEkwIFf2orclqSXroJJ18HwwQCWrUEvWId0EAyYdL7CkF8GShC3IQC3Zi+5ha+oflZyCStbB88EAlaxCLVmHWjIYsJDiBZb0AkuCAUtSXvRWHdSSdVDJOng+GKCSVfiNax3STTBg0vECS3qBJcEgDBESIQ+6O9vUPyo5BZWsw+QABqhkFWrJOkElU0uGDCykeIElvcCSYMD3Lr3orTqoJeugknXwfDAInoNKTuC9ZB3STTAISRJDxAMs6QXlAjBgiHjRXXVM/fMb1ymoZB08HwyoJatQS9bhvWQwYCHFCyzpBZYEA3JlL3pbklqyDipZB88HA1SyCrVkHdJNMGDS8QJLehEsSdiCDHzv0ovuYWvqH5WcgkrWYZoFA1SyCrVkHWrJYMBCihdY0gssCQbkyl70tiS1ZB1Usg7rY2CASlbhN651SDfBgHTTCyzpBZYEA3JlL7pbcuoflZyCStZhcgADVLIKtWSdoJKpJUMGFlK8wJJeYEkwIFf2orclqSXroJJ18HwwCJ6DSk7gvWQd0k0wCJMOQ8QDLOkFlgSDMERIhDzorjqm/vmN6xRUsg7fIgEDaskq1JJ1eC8ZDFhI8QJLeoElwYBc2YvelqSWrINK1um+qgOjg0pWoZasQ7oJBkw6XmBJL7AkGDBEvOhuyan/P/7tGw6Ez+UP+TeszMNFhg6AQhgi/y7DBRaCGvzjL9mAhbCo8u8ydAAU5iEiwwXeAUt6QdgCg2mE4GwuBEv2VB3/Gm4AoAImB8ggowSgGBk6AAoySACGgkQIMsgoARd6Otv8jWuACpgcIIOMEoBiZOgAKMggARgLGZ8ACjJIwAVUMjwJVDJkkFECUIwMHQAFGSQAQ0EiBBlklIALXZ1tvoF//7d/+zf+t/1feO3kj3//G2z4P3/7P/8nmIX3kiFDGCJ/TE40M3kT/83/vSLKce9P/+/f5h+AIN2EDLPrSDThf2/8b3a2YEntIP8r/x9hC0yis01MY4b/rv0XmA0pVu0Bv3GtM//G9f/7/8GBIJP53T7IEHJa/rZcwvyXoPiN6wT+EhQYhCyJSceD8BOCWNIDfpofDELY4o99eNB9Apj6RyWnoJJ1/tZ7vMLoBJXM5JCAStYh3QQDhogXId3Ekh5gSTBgcc+L3paklqyDStahlgwGqGSVWSX/lg1YCBKIWjJkIN30gvUGL4IlGZOQISRCDBEPulty6h+VnIJK1sHzwQCVrEItWYdvXIMB2s4LKqBeYEkwYHHPC2rJY4JK1qGWDAbBc1DJCf8z2AWVnIAEAgPSTS+ogHpB2AIDKkpedJ8Apv5RySmoZB1UMhhQS1bhG9c6Id2klgwZUCReUAH1AkuCAYt7XvS2JLVkHVSyTpBA/4/YCEABlazCN651kEBgQLrpBbVkL7AkGISwRSLkQfeq/NQ/KjkFlaxDLRkMUMkq1JJ1eC8ZDFhI8YIKqBdYEgy6a7uPgVrymKCSdVDJYIBKVuG9ZB0kEBigSLzA2bzAkmDQW9t9Dt0tOfWPSk5BJeuwPgYGqGQVask61JLBAEXiBesNXmBJMEAle9HbktSSdVDJOtSSwSB4Dio5gfeSdZBAYEC66UVwNizpAZYEAypKXnS35NQ/KjkFlayDSgYDaskq1JJ1QrpJLRkysJDiBRVQL7AkGLC45wW15DFBJesECfTfYiMABVSyCu8l6yCBwIB00wuczQssCQYkQl50nwCm/lHJKahkHWrJYMDkoEItWYf3ksEAReIFFVAvsCQYsLjnRW9LUkvWQSXr/G0yC38vGTKgklV4L1kHCQQGpJteBGfDkh5gSTAgbHkRUsqulpz6RyWnoJJ1qCWDASpZhVqyDrVkMGAhxQsqoF5gSTDoru0+BmrJY4JK1sHzwSB4Dio5gfeSdZBAYIAi8YIKqBeELTCgluxFd0tO/aOSU1DJOtSSwYBasgq1ZJ2QblJLhgwoEi9Yb/ACS4IBKtmL3paklqyDStbhvWQwQCWrUEvWQQKBAemmFzibF8GSjEnIQCLkRfdvsE79o5JTUMk61JLBgMlBhVqyDu8lgwHazgsqoF5gSTBgcc8LasljgkrW6b6qA6ODSlbhN651kEBgQLrpBRVQLwhbYECu7EX3CWDqH5WcgkrWoZYMBqhkFWrJOtSSwQBF4gUVUC+wJBiwuOdFb0tSS9ZBJesElcx7yZAheA4qOYH3knWQQGBAuukFzuYFVXkwIGx50b0qP/WPSk5BJevwLRIwoJasQi1ZJ6Sb1JIhA9rOCyqgXmBJMCBX9oJa8pigknX4xjUYoJJVqCXrIIHAAEXiBRVQLwhbYEAt2Yvulpz6RyWnoJJ1UMlggEpWoZasw3vJYIAi8YL1Bi+wJBigkr3obUlqyTqoZJ0ggXgvGTKgklX4jWsdJBAYkG56QS3ZCywJBiRCXgRLdnW2qX9UcgoqWYdaMhgwOahQS9ahlgwGLKR4QQXUCywJBizueUEteUxQyTp/6zxeYXiC56CSE3gvWQcJBAakm17gbF5gSTDoXgH9GLpPAFP/qOQUVLIOtWQwoJasQi1ZJ6Sb1JIhA4rECyqgXmBJMGBxz4velqSWrINK1gm1ZN5LhgyoZBVqyTpIIDAg3fQiOBuW9ABLggFhywveSx4TVLIOtWQwQCWrUEvW4b1kMGAhxQsqoF5gSTDgG9deUEseE1SyDp4PBqhkFX7jWgcJBAYoEi9wNi+wJBhQS/aiuyWn/lHJKahkHWrJYIBKVqGWrEMtGQxQJF6w3uAFlgQDVLIXvS1JLVkHlawTVDLvJUOG4Dmo5ATeS9ZBAoEB6aYXwdmwpAdYEgwoF3jR/RusU/+o5BRUsg5/CQoMmBxUqCXrhHSTWjJkYCHFCyqgXmBJMGBxzwtqyWOCStZBJYMBKlmFWrIOEggMSDe9oALqBWELDLpXQD+G7hPA1D8qOQWVrMN7yWCASlahlqzDe8lggCLxggqoF1gSDFjc86K3Jakl66CSdYIE+m+xEYACKlmF37jWQQKBAemmFzibF1TlwYCw5UX3qvzUPyo5BZWsQy0ZDFDJKtSSdaglgwHazgsqoF5gSTDoru0+BmrJY4JK1gnvJfMb15AheA4qOYH3knWQQGCAIvGCCqgXhC0woJbsRXdLTv2jklNQyTrUksGAWrIKtWSdkG5SS4YMKBIvWG/wAkuCASrZi96WpJasg0rW4VskYIBKVqGWrIMEAgPSTS9wNi+CJRmTkIFEyIvuqmPqH5WcgkrWoZYMBkwOKtSSdXgvGQzQdl5QAfUCS4IBi3teUEseE1SyDu8lgwEqWYXfuNZBAoEB6aYXVEC9IGyBQfcK6MfQfQKY+kclp6CSdaglgwEqWYVasg61ZDBAkXhBBdQLLAkGLO550duS1JJ1UMk6rI+BQfAcVHIC7yXrIIHAgHTTC2rJXmBJMCBsedFddUz9o5JTUMk61JLBgFqyCrVknZBuUkuGDCykeEEF1AssCQZUlLygljwmqGSdoJJ5LxkyoJJVqCXrIIHAAEXiBc7mBZYEA2rJXnS35NT/eCr591d4W22yzNeX7Lmbiyr57//853zj//z7P/4hu3L84++x+d9lT554+b//veTqLWB9DAzuUclff71CxNfXQ+qzF2vJX98xFP4uObl/5KyF95LB4Joi+eXkCtEDv76q17i+KqfK5qto19YbvCz5SbByAwbXtF2nsLV0+13U7dQ83mbJ5X9XXv5Ab5VcX0t+PW3Efuba9lOiJ21f9LHOFZX89/l+Vwwl+499+3/K7lNEUUf66GS+cQ0G1Sr59zyeF2Rvjj/3QeUROvnKb1zvI6H5oENEzlooyoDBhSTJyxUkuYvU+e8U2L5rzpj6SvOjYwzIYvUWnK2LJauzwNG5YEn4WVwoF3QKW8duDf/8vb+6GeSOIaza/bvX5sJd16jkwxObD1zbXpkVesTU+S6qVPJew77IVYiPmjrf+v/7R3L9f/bQyahkMKieHObRvCJ7zzkG6WlEPkAn19eSk8ecyMXCMSJnLeEpqSVDhvqFFCdX+PVepJnPKO94vukk40wf5Ryzr/oKqI8lD1d5QlwyoJYMBvWLe33CVto8r3u1vCRz/V/SZEulhHhcLTm032B+itIuYrVPM+CJDgaax2uFSv7HfKMpZ0o2Fb0TmXJyqqknOsjkIIF4LxkyhJFZo5KPU4PsPiWdSibGl8m17yUfKuwLZ086SuSshVoyGNQmSV6uoEaacheWuygV1tHhDymSehMnyCnn1DqbkkBfsqScGfkAlUzYAoPaCqiXs1WGLT3AnParid6J0/baQ01UZEL9VfIcvypU8vGZrXhX2f7kI7g/CZ6HTrlK1jTvC13J1orqk+ub39J2h1oyGFTWkhM1KPvPOIm6w2cslbXkk8ec0K8xTOSsJaSb1JIhQ6Ui8XKFExcsnf6W25Bti9jddZVsZ56VFdAzS1aluBOVWeATqLQk/DwqtV2nsHWWaJy0P2t+cp9nD1WnInqr5MpacpLSGvGusv1Z/aQ+Lr9LnUo+F8m6kj0TyWcy+fT6t8vkv02d9hyvMDyVKjkJu7L/hJAxq4w+KutqyeeTkf6k40TOWijKgEGdIvFyhVMXLIs0y20U9hq7O169XCUX3FdwtvJA6WXJJFX+AJVcZ0n4gdRpu05h6zzRUNvn8hLlPs8fqsp7aqvy7oT7LVfJiZGMeFfXfhdNvyfkn4GbayJVKjknkjUluxPJ/5yQfwY0mbw9fmh+t0ymlgwGdSo5jaNyQGcbEg4RYnCpVVVLTuLmjtQBd1bsGzlrCbdKLRkyVC2keCUR2/MOlymaAKVtqSJcxLBsL5Sr5IJsumq9wS0d25448wEquW7lBn4gVdquU9jauabd/niX8i8hvc/j5eVfL4pt87Ba8sEqE/l4V9l+rRPFnxdfp4ibjVSjkrei95/zT3D9Y/f71YnwXWVu/ItOa3NF9q7Xf1192rNe4ew72o0ItWTeS4YMVSpZWWyUIypr8/g7jJuXeerWXO+m5jeut1Z5Peiv3c9QJtPRaoTukbMWaslgUJUkOSUR70aa2Liwy6W75NJbv8+ST8VeVFVAvdKxyizwGRC2wOABYWsTXNJuFTeVAxPL5Tftk/vULr+JBun9nNBbJde+l7wQzpsojncF7Rf7bQ2i7mzP/PkWquT59mY2Enerkw9KdpG4W0Ws7pxZRfLmOurOG6CWDAaV37heiCFVNjXWOWATYNf1zaoCx93U1JLnp5nZ+Np2PjpcZ6TIWUu4TWrJkKFGkTi5whpUrkWapWlhJhjvsN5Xl6gg21lqKqBOltwhJxdnjeNSY0n4kdRouz5ha82nth65dJuElPXINqytew/X30h22RNYb6fYf3p/47r+7yUL4bwJR5W82HRvj+UzKJxvfKhQyWd13U0JWPa8WPbvdy+XOcpe/cDJVVrTe7zC8IRB2Ugl67HgJHAMRsV7yfpktJ1f9k9qRc5Cbd4HijJgUJFueiURS2nnWqRZGhb2F++v8Ck31MnxCmfzsuQOOfcDVHKwZP2nBT+IinJBp7C1rLDtr7/ElGN72X3cv+YlskM4ufz6WKVxgFrygrRIzBFtemsqVaGS55sLHOXt+r3o3RHZl8jb2Pqwf6lJHy6/yORjt02hlgwG7WrJS9Q9yL4lSo8sBytqyfOzBI7N129P7Y7IvtPIObTDhomdWjJkqNB283ifeDOJeDfSSKvS9GjpTrYrqPPxigro67JvW3KPnPsBKplaMhhUaLvZKybuDVun0Ww5INvCaazRL3QeLOuCVn+VPE4tOS54pNaINr0zts7jrUgln6nYibWaLDsCcWdaA44yWV4+FuLe5PLL1WX7FoJK5r1kyNBOJcdAkKysLoulsj0i5bXkZa5LWy8Pun3SsSJnLRUSCH4m5YrEyxXejDTx9MLMbrloUXjYsWSiZaeWV0DbBJU3Th0MwhYYlH/vslPYiolGenG9W9mpxBq1fbx8+lQnKvyU7t9gDfc6hEqWBspHEG16p53KVfJ8axN7bftCq/fKnoyo3unnKMKVL1af6ueG8JegwKCZSj6PukuUTlYtx6G8ljw/yYQWK7X1WdkzSOSsJXx01JIhQ7kimUf7xJuu8GakqVW98ZoX3FTOLM3DytcbXpf1DipyanHWOC7UksGgvAI6O8XEzWFL9mkZlxzZXSlzL/HQ7lKxTyUKxkMVYavMkm0YppYcZxatQaVNPShWyRkVO5GWh6MU1kS1VkyO+2RzS49iMioZDJqp5JAsnzRQo/RYFP/GdWaum0hj4WCRsxaKMmBQnCR5uUJsK5tbCiLNjSI5xorSuFfsbI2CyvUzRyNYkkQIMgwftmSXdmktGYv7cu23IU92qbFJDhV6UG+VPN/uCCpZjuvhXo7daKj5Uy9RyZqyXUnLw7JDV7ZybKO4owhXLx8P3lhM5r1kMGilknNBejk4bjG5uJacnxfTBV3ZMUrkrCU8LrVkyFCs7eaxPiGbe+RYgSu8GWmiAxc6Xa2o3rDkvqVhL6Sbd1ryiJxZnDWOS7El4adS/D3h2ScmZHOPHGsQtmL0UOOOHNsGlowIX66lXF69HblWYQjprZJHqSXnllPWj1g2b2DusUYly+YROboczpWSV9krmxP5y8tB/WJNCJ7/32IjAIUwIluo5FyQro9Ht1P8XnL+OeODLodHi5y1UEsGg9IkycsV3os08ezCtO4NkTz7TqA4gyytgLYKKnLiuFG6GMIWGIwetmK/srlHjm3v6VuQzR3KM/wpzdW4ZiQ5B4rXG1oRbnUAlRzHwslUIUeLe3ub+X5KVPJ8X2dfuE51r1H+laOr7JUdJ5dPVXVrqCWDQatashw+GX3XM7ebKK4lz49x7mXHBx0tctYS0k1qyZChVJF4uYI0vBZpalVvpajespSSC7sqr4C2CiqXTxwOaslgUKqSe4Ut2aO3l7BU7Kmv5sXtjSB6oNSSrRilliyHz0whn9l9lpo/xQKVnK8Nr8ejKpbNM1EtpePlsCGqj1dvT3gvmd+4hgyNVHI8fDKXZL8+NAKlteT8yvJ6PF5KNoeJnLVQlAGDUkUyj/T3XeGtSHOjSI7PW9rVRGkt+XXdty2Z8DqvPGscl1JLwo+lNBGaXeJ9Z6sOW3KCfmHp1UvfHTGSvQO9VfL8dP1VspXj1hnVgbnDEpX89xdnOvWgYy1ZeywOH1XzkdfhG79yTS0ZDBqpZGuyeB2+FMtuobSW/OvrxVkojKFSLjVc5KwlfK7UkiFD4UKKlyu8FWnk5NJJslZUb4nPUzEfF643NAsqct4HqOTSlRv4sRRqu25hSy6sn/A6NohK7v2N60FqydFop1mkHL8tvM43VPKNa4ODLDZqw4nslc1TlXz7V657j1cYnkYqWY6eDr66uHs/xb9xbXCoJf8pm8NEzlqoJYNBYbrplURIs0uRJorkwjC0iOQL7nlFYBc6m5clE66eNx6ELTAozJW7ha1cHItXK44tle2l7wLzBKglz8TJRTZTrIUSb+ZP0UElH2Ss8Vtfx+Jx1NinteLbv3JNLRkM2qjkmBOeBpxDjXU4it9LNjiYabjIWUu4P2rJkKFQkTi5QgwkVyJNrXKNt3zFO+O5xSnYRGEF1MmSKa/Tqm55UKglg0GhtnNytgthS3ZoZ9RmU/nkLUWaFwaC3ip5kFpy/uhE7afwLo1Usmydf0N6394uFUuD275yzXvJYBDGo79KtgOANCiOSDdT/BvXBgdDyNY4kbMWijJgUJgkzcP8fVeI386QTQVpkHZ0p0he+pLtIoKz3WfJFDlt1BhdQaEl4edyb9iyW0mDtSPZod2jHCp28MplsyjCC+Nk92+whnvtrpJto92d6839OahkvTZ8Xvrd62LrteT7VTK1ZDBoU0u2w/CrwbAZmFcteW+I8SJnLSHdpJYMGcoWUrxc4Y1IU6l6r3xnekFOrQspZRXQdkFFThs1RldQZkn4wZRpu45hK4ar1B3jTRU7amX7yvhBLTkQp4vMbCEtivt7k/ljfF8lR9FbrJL3stdWyXa12ZfuqzowOr1U8tXM7SacasnxKcUQ40XOWqglg0GZIvFyheuRJu4vDUHS+pJrHuJAIWXO1i6oXDxtQAhbYFCm7TqGrSVeHVfa4j0V5ytRbxe2j9cvDV69VfL8CXRXyWfTzgZpcVd8ne/ofZUc30OWWm+BppUWrxN2Gyp3q2RqyWDQRiXLwYz/FwSRnjjVkg/rv+NFzlrCA1FLhgxlisTLFexGJz3V5pbRla/Mp9V57Iuy9YZ2QeXiaQNSZkn4wZRpu55hK0agQ16yBJfcTW2pjGSxUl0cvHqr5DFqyWLlnCEKmngyj6i3VXKsHUcRa9eGd00KSs93/3xXUMm8lwwZmqjkGLgzcbWgSU98fuN6mcBke7zIWQtFGTAoS5KcXOFypFlc89fvr7mj7+9sdiQ3M93N1/er/Vf5Ilo8uTj/ehGc7TZLKrzOqr3rESmzJPxgyhIhJ2e7FLZiyrU/bQlkuYttCb4wU9Z+uX6x/3T/Bmu42+4qOXvwxcWwfBUflRxLyVEWy2buLeKtSi4oFN+tkruPVxidJio5e/BFXKF8v17bBJ9asoTBxQdlc6DIWUu4PWrJkKFsIWUe5e+7wuVIE13zj+UfE9+nHr/mivL/zxTmU0s1RrZLKauAvi7dIqi8zip9ypGhlgwGZYt7s0P0Cltr7Fn7j1cq9O7XiuBMSfvf6+XLsyFqyYHswRcFo8CTubt3VXIUyYvMlc2cSt4q45KvU0uT3CU94RvXYBCGYw+VXB2S7sXlveRlRpLtASNnLdSSwcAt3SxxhauRJp535OzG5XBCUeoobavjidt6w8WgImcNGqJrIGyBQVlFaXaIbmFLdgXmb7JsRazp3F9ff60S2X7W31N7aTpTHrx6q+TZTKjkhLm7N1Xy8n3r5RvWso1Khs+lVy25OiTdi0ctOf2ukmwPFDlrCRMntWTIcKu2uxhp1q8pJqhOv00v9xRMr/Eeq2fisgro6+ItgoqcNWiIrqHMkvCDecLi3vKlFAVLxR5Cnvmoh5BXkQv1/gbrELXkaO7cx3IxLF9l7u49lbyI5EXllnw9equMC15jvlslh/HKe8mQoYlKlgibDZWvJqOmYA615HVakh0jRs5aKMqAQZEi8XKFa5HmkDHuUSLSuUieurbyx6Wz6nASnM1MNxsGFTlr0BBdQ5El4SdTpJL7hq2p/7NI9G0Gl33Ms51h31NN7Cpbb2hIuOHeKrnkjcKSNo7MA/M9lbx833pRsCUqedumRCWXtHGEWjIYdFPJJW364VBLXqaZJYoOGDlrCQ9FLRkyFC2keLnCtUizuKZKcvNZUW26auysXmwWrTc0DCpyVv2ND0eRJeEnU1QB7Ru2AnroKnDReFszBaJ325Fplx29VfJjasklbRx5XyUvInkVsB+gkv829dVzvMLwoJJV3v+N62WWWZ9wwMhZC7VkMHArypS0uRRp4oXPOKY9iyufIM10YqCsLeROuNWSLwYVOesDVDJhCwzGD1svtGBk3vfELugVuPS2H7tSvaVovaEl4ZapJSe8rZIVkUwtGX4AqGSVt2vJyySzecABI2ct4bGoJUOG4WvJ8bozX7/nDHDz268T+x63h76/5ua/Fu0byPW+JKcXHJpashfUksGgSCX3DFszu7izwfbRXdQrCAW7gGhbZkORJRtCLVnnXZUcxe5OEn9ILZn3kiFDGI6o5IR330teV243FxkwctZCUQYMhi/KhDEsvDTvi00Curvc6sqTRpZ9E782aWQm5YytrsS5ImdrGFTkrA9QycGSVz4B+DEUlQt6hq2JTSg6Uv7zCIIVCzbhLVDhPb1V8hy3qCUnvKmSVZH8CSqZWjIYUEtWebOWvC7cbq8xYOSsJaSb1JIhQ5G283KFC5Fm9c3jFwnXxHCb+Oh7J9YLnX+bemlTKVBniiqgXpZUkLM+QCUXWRJ+MkXazsvZLoStiSWYzHx/r5EpUODcv7ffgSlo/6vyzyu/6K2SH/P3ki8uXl7lTZU832pg/9vT6s49W5Vc8pegblbJ3d8QgNFpopKzB4WSiaIfb9aS50cL7IOkunPPzZGzliIJBD+ZMkUyD/L3XeFCpAlDeCYNPWtOKDsm1hpMch/rodPHkOPZ5zylrAL66qBFUJGzLt37WBC2wKAsV54dokvY2oab6Qbk6ts3RcrWwGLXhe3Xr8zYxhG6q45wt09QySWjwJG5u8sqWaRrIl5lb04l8/eS4dl0U8nSZNAU7L1a8tnMInsHipy1hCejlgwZyhTJPMjfd4X6SLMUZLSJcXHc9b6WXUo0WIs7suNIvL1r7uy23nAxqMhZuSs/BGrJYFBWAZ0dokfYmpAdE1sBvoSY0kzfDFoHlJiYh1pyIHvwxcWwfJW5u6sq+Uwkf4hK5r1kyIBKVnnrN67PRPKAkbMWijJgMHi6Gc/Qb3FxXdleztaDwVLe0Z9jOXwtkty63qAgZ+Wu/BDKqvLwgxleJcdzkrs8TTdOMIJWQhoT8/RWybPluqtksVrOEBfD8lXm7i6q5ChuU3lb8PXorTIueY9ZmtylkvlLUGDQRCWXvJojTYpD0r28U0teprPEOONFzlrCE1BLhgxl2s7JFeojjWydCNel0BLjUryJkxvNZ5Dx6MU5OKSbt1lSQc4aNETXUGZJ+MGUfU+4W9hatW3adz4IpSxBTrYt4vULA0Hvb1yPUUsuGCkFTTyZB+Y1laz/ctdMgUreNilQySVC2hNUMhiE4eiukmNEz5RQCpr05I33kpfpLD1/vMhZC7VkMCgrJTi5QnWkiVtnqZB0uhyP27J5JJtwLpHgYpArq4A6WVLhdVZ51jguhC0wGDts5ZfrYpAqdfB4rdIygDQvvDy15EDBYom0uCu+XlfJGZFc8hVqafGqDe82VEq+lO0J7yWDQZNacoH/FwSRnlyvJS95s3L6eJGzlpBuUkuGDGWKxMsV7Eb7nuLWqW/L8ThtHjYTcteTQ5eduawC2i6oXDxtQKglg0GZtusVttZgognr2uJwbF/q2VGFy6ZBb5U8Ri3ZHikFSyWuzHd0SSWfvpQ8YWvafW1YNjIquaA67UqQQP8tNgJQ6KWSL5Y37uJ6LTmIhBnl0caLnLVQlAEDL21X5grSqDjSvDYy/e4zwnibp9ePd6k0iOdejnFe6w1Xg4qclrHtUwiWHHWqgSEoS4R6ha1cnJmIQavUVe3H2CPNyy7f+xvX8912V8n21eJaxaVizAXmD/2KSs6J5ALZu1fJtqq+WyVTSwaDNirZjsKDq+TLteQ4X+lPJsfGiZy1hMejlgwZChdS5mH+vivURprXRqbb/QXty0uD9IIxr72+4lVYAX310iCoyGnnF34M1JLBoLACOnvE/WFrOeEkmMjRUleNVyuNCNK8LFujljwjR88tYY8BX+b+LqjkqGtPlK0cOxe1e10ct87fOpYGd/141/xeMr9xDRnaquTzBFEajJqBXf2N6/jgJ4aRY+NEzlqoJYNBXbr5ritURhq70rO/oL2Y92qgtIjrZddDXGEF9NXN25ZMkdNGjdEVELbAoLACOnvE+85WGbbWaCKbR+w4taP22yVVl++tkmfT9VfJps1ex+8Lr/OYq1fJuZeSA2bp93U8ql7zt7nsYrMz1JLBoI1KNhdUryZud3GxlrzUj07mn+EiZy3hAaglQ4ZCReLkCpWRxq707FvY6eFZiyUUyPYFCiugzYLK1fPGo9CS8HMp1HZ9wpZ5WTtO7Xk1L3btqnStt0oepJZs2SxOEMXdvct8Q9Uq2RLJpqqNF4i14cNmQvx+t2y2p/sbAjA6YTz6q2Qz4EhUfyOFbMu195ItkTxe5KyFogwYFCZJXq5gNdtHmnjVc9fet7Czz7MWr90XgshKYS25WVC5et54FFoSfi5Dhy2zvXVbR6R5qWtXXb676gh32l8ll35k9bWYi8wdVqvk/EvJATl+JnuPX7G2VLUcvu21ZGrJYNGmlmyGVTk87OC8VkuOU9v5c8nxYSJnLSHdpJYMGUoXUuaB/r4r1EWaWMM5z4TUWnImPTxRyfG23olwpRXQV0/+QUXOO7fVYyi1JPxYSrXd7BJ3h63ibmXTRJqXunbV5aklvzhbPxVeR8s/sreZP8RalWyLZOsr16+jqyo2vnIdRfRtryXzXjJYNFLJRs0mnl0ckO7mUi3ZFsnDRc5aqCWDQakicXKFykhz2EzZBzYjzE1Ig8MF4129U0oudrZWQUXOGzZIl0PYAoNSbdcnbFm+aMepPdK81LWrLt9bJc8PN4BKjkbTF0zs9Vpv5vupVMkFIjkpFu85fuHaKhbf/oVraslg0UglxwhykppEPSmb43GllhwfKudyo0XOWsIzUkuGDKWKxMsVpGFhpDGS3GNgi7dxLnalweE+Y7dveXLpekOroHL5xOEotST8WEq1XZ+wZcWtY/uv7++/vqf/yeaR5Dal+dltJ7eTo/c3rkepJcfjui3+lKPvLKPWMY/cOpVsvpQ8I0102Ztq6LyqloMZVe5N7/EKw9NKJcfjehCQg+OOzQu/cb2Uj7LnSZNRImctFGXAoLiUMA/1912hLtKY+Z4cl9QnOvVpJqTHwSUWyPY1grPdackjcmJx1jguxZaEn0pxIjT7xN1hy4pbcnRpn796eli2z3zEOLyHWrKQ+8ziOsWNhpo/9CqVXCaSs+XfeImN6k2ryxvitbId+kItGQxaqeTsomoMH/WJ213U15JXkZw9bbDIWUu4fWrJkKF4IcXJFeoiTYxbZ6lNPB6dWDZP45wcPtyn7K2LIAnFFdBGQUXOLM4ax4VaMhgUa7suYcuIW8nFjNW95BlyD2Xca0JvlTxMLTl+ZpoxwiwZuDEFnm+nSiXPdxjIvyQci8Na/VdTvbJLU8KKqG5OUMm8lwwZwpBsoZJziWIM4T1DqUH9e8nzEwXyQXawyFlLsQSCn0pxkuTlCtK0MNLInrPAJUeXw/EmT7xaP5x7sgqKna1RUJEzi7PGcSFsgUHx9y77hK18SJGDa79R156EOTm4XiyqZN3XY+dlMaT7N1jDrY6gkherph+x8fk0Yf4Ua1RyyUvJM+cF4KUaLdszGSkcr3Tfb3fxjWswaVVLXuKAMv7yIXkIqmvJ8ZlMfxsrctYS0gBqyZChXJE4uUJdpIm7dD9NTljuRA0GyxdIZPvFsveCMt1SXgFtE1TkzIHDdCnUksGgvALaJWxFZ1S9MSZjm35lhx620utnRbge5U6hlhxRPhdB9r87Q1RRq5KLRfJSTE6/cy37D/pZdqZaOFeVbgbfuAaDZir5PKxnI/Ig1NaS4yKy/VBjRc5aKMqAQbki8XIFaVwYaWSf6qnLHa0dK7tW5NDhWlqSe4XgbGVBsk1QkVPffYwBKLck/FDKtV2fsBWDiqJ7FxW7udL5TeqqV/aozl4Zz3qr5PlZhlDJi+WO5jjb35R5SJSr5EX6FvzcdBTUR3V7sn+pMB+Kz2f724JKBoN2KvmsCuNVaWlKZS15mZMy9ogMFTlrCTdJLRkyVCykOLlCXaSJF1euvrjxJvFZLp6Gg9/LpWTHi8rSyznl6w1eltwj5xZnjeNSYUn4mVR879LJ2erC1nkcUo8sO9ObWa6/PbSEsiTK5Q6p9FbJ49SSTz6Fdd64NQWuU8mLYi2RrEvjnRz+x1KNPl5CP7Do8ltLyfM3rnkvGTK0U8kn0XXJRHsGUpO637he5p2SU4aKnLVQSwaDiiSp3hW+JuSfG+oijexN73K5zC6qLZc53s7q9ftbkp3vO3KFs3lZcoecW5w1jgthCwyGD1trdNpffw1DuxPWyxzE7UmyIvtSdw++M1NonZr1hjaEmx1DJW8+tPVTOJs3WjOPiFKVvIrkoleEF9m70b2ZS6yHNoJ4vYbsuAlqyWDQUCUvk8l2DK5hQ3aMSVUtuTLsjRQ5awn3Ti0ZMtQoklpXeLVP/LIu0qytdz2saviQhq4X2iaca1J8mGLjdd6feGsqoE6W3DE3GT0iFUEtGQxqKqBOzlaZIMnuic1Q3oShfdg6iXKb6++fdrN/e6PrYyniX6fGki0YqJa8M+vc7vdmmrnZSFUqeZWsp+zqwGv7f86a+B/rF7a10vAqk//4+3ydv286PFaeG/O3qcue4xWGJ4zKRip5G2G/5sj7taxLlsfcPlS9l7yZqM7YzZADRc5aKMqAQVWSVOcKMXwk+WZdpNm0jt1u+03Snq1/vy7/+2u7b24UWS7+foALz3C3JbdIm6M5HkiVJeEnUlUu6BK2tiEqdrsNQ4cTtlHudfVp32nY2kW519Wn5rtrvPbZ9FbJc9waRSXHRhrvzxBVzOOnUCUXiOSDmJWdGprq3YjoI/d+35paMpg0rCXv4/qBwYdlTS15O/Ocsb+U7NS4OXLWEmZxasmQIQyR8oWUedDrnKeJaV5SF2nyHpucsCnLaOzvM167ONc6p64C+upWpcaSG0raPIM6S8IPpE7bzY6hM0zYOjT/63u/43ifhyh3bF5um97fuB6qlpyZPJKB0ph5sJWp5BKRfBC/m+rwAb00fNrF3SJ5riXzXjJkaKqSz+N6zyhaQkUtebP8e87+UuNEzlrqJBD8QOoUSY0rrNFEdmyoizSZ7FQ7YVeCObK/z6X6ItvvEJytPFB6WXJFmnyASiZsgUGdtusTtnJhSDkh11y5z23hOKHcNNSS95wNlcIajB/lKvlc8W45qN+zk3SRfCqTbxfJ1JLBoq1KPgvUww/K8lry+Xy55XCpYSJnLeHzpJYMGSoVSYUrrMFEdmypizTnXqvnPKcJ5/G3cWS3iydXVkC9LLkgTT5AJVNLBoNKbdcnbJ2GId1JzxcDj2Fr5lfl5U/orZLHqiVPaGbtYKBilVwmklP5q+nejOhVuznT1A3p/d0HGJ7GKlmfTdJ1zNEo/o3r7ALsSnKpQSJnLRRlwKA6SSp2hSXpU49WRpqTjPDshJOs+Hgnsers4srVzuZkyYi0+QCVXFeVhx/IM8LWmTg/OeGs+dmDngTFTBhV6K46wh2PpJLXEbDQI6bOd1Gikou+b60J2vRl4+wPZK9/KSryzw4imVoyWLRWycoCpbqOORjFteSzeeVAeqkxImct4XGpJUOG+oWUUldYcr6Tw3WRRquc5Fwwvcs/vpXs8dWsKq08o74C6mRJoaTNM6i3JPww6rVdn7ClJRwZD1Wilhq2BLWcXBkAqCWn7D+GL5fpoZb5HgpUcqFIVsu+e538+vnqDHud/Pp17NsJKpn3kiFDGJ1NVfIx8sbfTxyb0veStUlFQ7vUCJGzFmrJYHAlSSp0BfnixunVKyPNMSW02u/v8jTZnK7qE+OuVECdLDnzauP0MF0hbIHBc8LW7oetJ4z2h6hlPWSik6vzkt4qeY5bV1RyU76+Xj+H9t0t0ZsHQtmvd73B3//+z1n6/tOUyDP/mNrPzTtJ5An+EhQYXK0lV/FrChHBFb6fIZEnqv5e8mX6R85aQrpJLRkyXFMkZa7wa5rpszGkNtKs3f4uccHN5TPNfznNudcqoE6W/CiuWRJ+ENe0Xa+w9ep1umhJ5vD7V7x62eWn5vFuSoLikd4q+XIt+cO5RyU/D1QyGNyikp9H1d9L/kFQlAEDFIkXOJsXwZIkQpCBRMiL+u+uOzP1j0pOQSXr8F4yGDA5qNxTS34eYY2ZWjJkQNt5wXqDF1gSDHpXQD8HasljgkrWCRLov8VGAAqoZJXi37j+YSCBwIB00wsqoF4QtsCgewX0Y+g+AUz9o5JTUMk61JLBAJWsQi1Zh1oyGKBIvKAC6gWWBAMW97zovd5ALVkHlawT3kvmN64hQ/AcVHIC7yXrIIHAgHTTC5zNC6ryYEDY8qK7Jaf+UckpqGQdaslgQC1ZhVqyTkg3qSVDBrSdF1RAvcCSYMA3rr3orZKpJeugknXwfDBAJatQS9ZBAoEBisQLKqBeELbAoHsF9GPorjqm/v/4T/k3LKCSdaglgwEqWYVasg7vJYMBisQL1hu8wJJggEr2orclqSXroJJ1eC8ZDFDJKvzGtQ4SCAxIN72gluwFlgQDEiEvuk8AU/+o5BRUsg61ZDBgclChlqxDLRkMWEjxggqoF1gSDFjc86K3Jakl66CSdbq/IQCjEzwHlZzAe8k6SCAwIN30AmfzAkuCAbmyF90tOfWPSk5BJetQSwYDaskq1JJ1QrpJLRkyoEi8oALqBZYEAxb3vKCWPCaoZJ2gknkvGTKgklWoJesggcAAReJFcDYSdw+wJBigkr3obsmpf37jOgWVrMO3SMAAlaxCLVmH95LBgIUUL1hv8AJLggG5she9LUktWQeVrMM3rsEAlazCb1zrIIHAgKKMFzibF1gSDAhbXgxRS0YlJ6CSdVDJYIBKVqGWrEMtGQxQJF5QAfUCS4IBKtmL3paklqyDStYJEoj3kiFD8BxUcgLvJesggcCAdNOL4GxY0gMsCQaUC7zo/Y1rask6qGQdaslgwOSgQi1ZJ6Sb1JIhAwspXlAB9QJLggGLe15QSx4TVLLO3zqPVxgeVLIKtWQdJBAYoEi8wNm8wJJg0L0C+jF0X2+Y+uc3rlNQyTrUksEAlaxCLVmH95LBAEXiBesNXmBJMOiu7T6G3paklqyDStYJtWTeS4YMqGQVfuNaBwkEBqSbXgRnw5IeYEkwIGx50b0qP/WPSk5BJetQSwYDVLIKtWQdaslgwEKKF1RAvcCSYMA3rr2gljwmqGQdPB8MguegkhN4L1kHCQQGFGW8oALqBWELDAhbXnS35NQ/KjkFlaxDLRkMqCWrUEvWCekmtWTIgCLxggqoF1gSDFDJXvSuzVFL1kEl6wSVzHvJkAGVrEItWQcJBAYoEi9wNi+CJZFAkIFEyIshasn8xnUCKlmHvwQFBkwOKtSSdXgvGQzQdl6w3uAFlgQDasle9LYktWQdVLIOKhkMUMkq/Ma1DhIIDEg3vaAC6gVhCwx6f0/4c+huyal/VHIKKlmH95LBAJWsQi1Zh1oyGKBIvKAC6gWWBAMW97ygljwmqGSdIIH+W2wEoBA8B5WcwHvJOkggMCDd9AJn84KqPBgQtrzobsmpf1RyCipZh1oyGFBLVqGWrBPSTWrJkAFt50VIN7GkB1gSDPjGtRe9VTK1ZB1Usk54L5nfuIYMqGQVask6SCAwQJF4QQXUC8IWGHSvgH4M3dcbpv75jesUVLIOtWQwQCWrUEvW4b1kMECReMF6gxdYEgxQyV70tiS1ZB1Usg7fIgEDVLIKv3GtgwQCA9JNL3A2L6jKgwGJkBfdJ4Cpf1RyCipZh1oyGDA5qFBL1qGWDAZoOy+ogHqBJcGAxT0vetfmqCXroJJ1eC8ZDILnoJITeC9ZBwkEBqSbXlAB9YKwBQZ879ILasljgkrWoZYMBtSSVagl64R0k1oyZECReEEF1AssCQYs7nnR25LUknVQyTqsj4EBKlmFWrIOEggMUCReUEv2AkuCASrZi+6qY+qf37hOQSXrUEsGA1SyCrVkHd5LBgMWUrxgvcELLAkGVJS8oJY8JqhknaCSeS8ZMqCSVfiNax0kEBhQlPECZ/MCS4IBYcuL7pac+kclp6CSdVgfAwNUsgq1ZB1qyWCAIvGCCqgXWBIMUMle9LYktWQdVLIO37gGg+A5qOQE3kvWQQKBAemmF8HZsKQHWBIMKBd40b02N/WPSk5BJeugksGAyUGFWrJOSDepJUMGFlK8oALqBZYEAxb3vKCWPCaoZJ0ggXgvGTKgklWoJesggcAAReIFzuYFlgSD7hXQj6H7esPUP79xnYJK1qGWDAaoZBVqyTq8lwwGKBIvWG/wAkuCQXdt9zH0Xm+glqyDStb5W+fxCsODSlbhN651kEBgQLrpRXA2LOkBlgQDwpYX3S059Y9KTkEl61BLBgNUsgq1ZB1qyWDAQooXVEC9wJJgwDeuveitkqkl66CSdUItmfeSIUPwHFRyAu8l6yCBwICijBc4mxdYEgwIW150X2+Y+kclp6CSdaglgwG1ZBVqyToh3aSWDBlQJF5QAfUCS4IBKtmL3paklqyDStbhWyRggEpWoZasgwQCAxSJF8HZmL49wJJgQCLkRff1hql/fuM6BZWsQy0ZDJgcVKgl6/BeMhiwkOIF6w1eYEkw6K7tPobelqSWrINK1gkqmfeSIQMqWYXfuNZBAoEB6aYXVEC9IGyBAd+79KK7Jaf+UckpqGQd/hIUGKCSVagl61BLBgMUiRdUQL3AkmDA4p4X1JLHBJWsg0oGg+A5qOQE3kvWQQKBAemmFzibF1TlwYCw5UV3S079o5JTUMk6vJcMBtSSVagl64R0k1oyZEDbeRHSTSzpAZYEA75x7UVvS1JL1kEl64Tx+t9iIwAFVLIKtWQdJBAYoEi8oALqBWELDKglezFELfk//xUO/Bns8o//F/b8//jGNRjMC3/iRrAwq+T/JRsQ+RdqyWAwKxIZL/AG/zKvN8gGvMHLkjI+ARRmbSfjBd7gX3rXkv916h+ghn+XsQOgIKMEoBgZOgAKMkgAhoJECDLIKAEXejrb/I1rgAqYHCCDjBKAYmToACjIIAEYCxmfAAoySMAFVDI8CVQyZJBRAlCMDB0ABRkkAENBIgQZZJSAC6hkeBJMDpBBRglAMTJ0ABRkkACMhYxPAAUZJOBCd5X81xcc+A52+VM2YKH3e/QwPEQUlf8IdvlP2YCF8Bsn/HoXZJiHiAwXeIcwfWNJD4Il+fUuyICzedFddUz985egUua/BPUvsgEL8+/2yb8BFEJI4y9BJcx/L5m/BJXAb1yDAX91xwss6QWWBANyZS96W5K/l6wzq+R/lQ1Y6L6qA6ODSlZBJeuQboIB6aYXwZI4mweMSTAgV/aCWvKYoJJ1mBzAAJWsMqvk37IBC+HdFmrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE6gl65BugkGYdBgiHjB9e8GYBAPKBV50D1tT/6jkFFSyDtMsGDA5qFBL1qGWDAYspHiBJb3AkmBAruxFb0tSS9ZBJevwrgUYoJJV/meIKNSSE0g3wYB00wss6QWWBAOGiBfdVcfUPyo5BZWsg+eDASpZhVqyDrVkMGAhxQss6QWWBAMqSl70Vh3UknVQyTqoZDBAJavwXrIO6SYYMOl4gSW9CJYkbEEGnM2L7pac+kclp6CSdVgfAwNUsgq1ZJ2gkqklQwYWUrzAkl5gSTBAJXvR25LUknVQyTp4PhgEz0ElJ/Besg7pJhgw6XiBJb3AkmBAucCL7rW5qX9UcgoqWYfJAQyYHFSoJevwXjIYsJDiBZb0AkuCAbmyF70tSS1ZB5WsgwQCA4aICu8l65BugkFIkhgiHmBJL5BAYNC9AvoxdHe2qX9UcgoqWYfJAQxQySrUknWoJYMBCyleYEkvsCQYkCt70duS1JJ1UMk6eD4YoJJVeC9Zh3QTDJh0vMCSXgRLErYgA87mRfeq/NQ/KjkFlayD54MBKlmFWrJOUMnUkiEDCyleYEkvsCQY8I1rL3qrDmrJOqhkHTwfDILnoJITeC9Zh3QTDFia9QJLeoElwYAh4kV3S079o5JTUMk6eD4YUEtWoZasw3vJYMBCihdY0gssCQbkyl70tiS1ZB1Usg6eDwaoZBXeS9Yh3QSDMOkwRDxg+vaCMQkGJEJedP8G69Q/KjkFlazDN67BgMlBhVqyDrVkMGAhxQss6QWWBAOWpLzobUlqyTqoZB08HwxQySrUknVIN8GASccLKqBeMCbBgIqSF92dbeoflZyCStZhcgADVLIKtWSdoJKpJUMGFlK8wJJeYEkwIFf2orclqSXroJJ1kEBgEDyHIZLAb1zrkG6CAemmF1jSCywJBgwRL7pX5af+UckpqGQdPB8MWEhRoZasw3vJYMBCihdY0gssCQZ849qL3qqDWrIOKlkHlQwGqGQV3kvWId0EgzDpMEQ8YPr2gjEJBjibF90tOfWPSk5BJevg+WCASlahlqxDLRkMWEjxAkt6gSXBgFzZi96WpJasg0rW4VskYIBKVqGWrEO6CQakm15gSS+wJBiQCHnRXXVM/aOSU1DJOkwOYMDkoEItWSeoZGrJkIGFFC+wpBdYEgzIlb3obUlqyTqoZB08HwyC56CSE/iNax3STTBg0vEiWBJn8wBLggHfu/Si+wQw9Y9KTkEl6+D5YEAtWYVasg7vJYMBCyleYEkvsCQYsLjnRW9LUkvWQSXr4PlggEpW4b1kHdJNMKBu5wXTtxdYEgwYIl50r81N/aOSU1DJOng+GKCSVagl61BLBgMWUrzAkl5gSTDge5de9FYd1JJ1UMk6SCAwYIioUEvWId0EA5ZmvcCSXmBJMGCIeNHdklP/qOQUVLIOng8GqGQVask6QSVTS4YMLKR4gSW9wJJgQK7sRW9LUkvWQSXr4PlgEDwHlZzAb1zrkG6CAZOOF1jSi2BJwhZkoFzgRffvrk/9o5JTUMk6TLNgwOSgQi1Zh/eSwYCFFC+wpBdYEgzIlb3obUlqyTqoZJ3uqzowOqhkFd5L1iHdBAPqdl5gSS+QQGBAruxFd2eb+kclp6CSdZgcwACVrEItWYdaMhiwkOIFlvQCS4IBubIXvS1JLVkHlayD54MBKlmFWrIO6SYYMOl4gSW9CJYkbEEGnM2L7lX5qX9UcgoqWYdvkYABKlmFWrJOUMnUkiEDCyleYEkvsCQYkCt70Xu9gVqyDipZh/UxMAieg0pO4DeudUg3wYBJxwss6QWWBAOGiBfdLTn1j0pOQSXr4PlgQC1ZhVqyDu8lgwELKV5gSS+wJBiQK3vR25LUknVQyTpIIDBgiKjwXrIO6SYYhCSJIeIBibsXWBIMSIS86P7d9al/VHIKKlmHyQEMmBxUqCXrUEsGAxZSvMCSXmBJMCBX9qK3Jakl66CSdfB8MEAlq1BL1iHdBAMmHS+CJXE2D7AkGHSvgH4M3SeAqX9UcgoqWYeEBQxQySrUknWCSqaWDBlYSPECS3qBJcGAXNmL3paklqyDStZhfQwMguegkhP4jWsd0k0wIN30Akt6gSXBgCHiRXfVMfWPSk5BJevg+WBALVmFWrIO7yWDAQspXmBJL7AkGFBR8qK36qCWrFOskr/k/7+HX73TbFQyGKCSVYrfS743ovzuXd4m3QSDMOkwRDwonb5vzjPuDXkuMCbBgFzZi+6WnPrvo5LHHj/FKvn71uf43fs7m6yPgQEqWaW4lnxvRPnVu75NLRkMWEjxotSSN+cZ94Y8FxiTYIBK9qK3JbvVkn//If/Q+P0VcqfJMl+9VhnLVfKtH9+v3q824vlgcEkl//79FfKOaXD9Vebyf36/QsTX10O+xVxcS743ovzuHVFIN8Hg2qTzyymJ+JJI8/3V/Ztcb1NqyZvzjHtDngskQmBwrVxA2ErpXpsLhqxSyS/bRy5/kt+nKvn3rFAX+linQiVX3WG0nmzWMs1eNbWf0Dzgt9bA5AAGFyaHvcfbAUkmksgjZoHyWvLIEWUS1TN+ESWoZGrJkOHCQsovpyTiGJn6rii9Taklb84z7g15LrC4BwYXcmXClkpv1VFdSz7Y/424KP86cvyAPTOycua7KFTJNTf4ZoCfk1T5dwH+OS1fpwWDMOCqhkgcpVtyMfF3dKKF7wfo5OLfuB46ovivu5FugkF9kuSURCSBZsJv5HcgWLLE2W7OM+4NeS5QLgCD+gooYUunu7MFC9ao5NB+w0Xjh2RL/rnnl/YJdzBQlUquWKp5M8DPSWq5OfxzWiYHMKhdSNE8fuJU+KZTycT4MrmmllzzPPdGFP91t3D/1JIhQ+1CilMSEWfPIw8uzNTUkm/MM+bP67YkygUW98CgNlcmbJ3RW3XU1pKPH+TFuBhOlX/u0MpKgds/4TqVXH5/bwb4l32KB4x/TotKBoM6lXzm8afDLKQnCsMPyor3kktbztwbUd7Nh1NIN8EgTDoVQ8QpiTimOiu3ZyNulE7fN+cZ94Y8FyrHJPw8KnNlwtYp9VV5Z4L5ylVysk5xLS7On6T8e8vZMsj9taJKlVx8f28GeDFQ6Yjxz2lRyWBQpZLPpoaAmoScTgKjpyx1teRRI8q7+XBKuH9qyZChbiHFKYk4DTQTj50Bq2rJ9+UZ94Y8F1jcA4M6bUfYOqe36qisJSeFnEtx8ZVqycaGXcr8PSH/DNy8EFKrkkvv780AHy1UOGT8c9ruqzowOlUqeRfU9x6vDrRtADpEiMGHZWUtedCI8m4+nEK6CQZVSZJTErGPREeeOgWWWvLmPOPekOcC5QIwIGx50d3ZgvGKVXL6GVyKi69TZWPDevkvGRjrO4g3J1LVKrlwxSc2l81algWnsjHjn9MyOYBBjUpe/Xt1+U2QSXxqXXD9ljG9eZmnas31dmpryWNGlHfz4ZSgkqklQ4aqhZQ1HryTRKyBJoaa37vfnx071pxSasmb84x7Q54LLO6BQVWuTNjK0Ls2d/nvJYfzJq7ERRkQsrWyDJStQdSd7ZmHVpVKLlvxic1ls5Z1xanIHP45LSoZDMKAK1TJ+nBeQ/1xpK3tN862Nh96Dqj6jesXRc9zb0R5Nx9OId0Eg5pJR80X1J1ZpP3E5pRtwlk02w9HsGSJs92cZ6wh744kyoVSS8KPpaZcQNjK0V11BNPdq5LjZyabC0tk3ttjGSq35sAXVHLRDb4Z4DdrRSWjxj+n5RvXYFAxOSzh+xC8F6c6DFw9FixOMfTArK8ljxhR3s2HU8L9U0uGDBULKSexQA8c56w+uI9Mq7c8cxKsriWXPWhs/r5KviPkucDiHhhUaDvCVpbeKrlDLVnOTGKc7E7MET/6W810RSWXLNS8GeDXNd4ie/jntN1XdWB0ylXyMpoTx9F9/kxUn19nIKrfSw4MF1HezYdTSDfBoKJuNw/OieNQ1gPKKdI6dcD1b7UXJq5jUTp935xn3BvyXCARAoOKitI8nCeOzQlbMzVV+SYEy92qkpfPS7YjMf9KB0Q8wy8zs7mkkguGYGwum7Wsi0ITtuv457RMDmBQHtKi6k0H1DLOZftFdJ7EzfTmY3GlljxeRHk3H04J908tGTKUL6TE0fxmErEsx6Xut/qL7HgUF2rJd+QZ94Y8F1jcA4PyXJmwlae36ri9lrx8ksePS/Yqa4nnY6gd11SyPQTfDPDbNd4C4/vntBXrY/AzKVfJ0RmU8oE2O5yL6qV5iQrtxKVa8nAR5d18OIV0EwzKk6R5bE68mURIW3WULw5T4sujUWrJm/OMe0OeC5QLwICw5UV3ZwuGu1Elb8Kv7BFygTZGxatB+AIXVbL5Ub4Z4NcloRlLFPjntEwOYFCukuexOSGbO+TQdqxlfGfxC9kekGu15NEiyrv5cEpQydSSIUPxQopTEpFZjpuouNBwXKolt88z7g15LrC4BwbFFSXClkFv1XF3LXkTD2WPIDv1yCfHbjTURZVs3uKbAX6zyDBjLAz557SoZDAIA65IJWdHpzjKZqzFSUBtHg+Ou1J64TeuZ8aKKP7rbqSbYFA86cxDc0I298ixggtFl9IHeXSBJ06DwZIlznZznnFvyHOh1JLwYyFsedH9G6zBcPep5JjMBmTXi3z2FU+TzRu4qpKtD/PNAB/NtJBf5fXPaVHJYFBcS/4Kfzx/Qh3DqaPkXUcOXgll93CxlmzmYvdGFP91t3D/1JIhQ20F9N0kwnApOXrV43pysZbcOs84hry2SZQLLO6BQWmuTNiy6K067q0l75YoZd+LP2XnyaKlHPXLzSwuq2Tj03wzwB/XeI3pyz+n7b6qA6NT/o3rHOnkIDtORl/5ZNKJi+8lT4wUUd7Nh1NIN8GgtG7nlURIwzO/Gz7UnFOabt6cZ9wb8lygXAAGpYkQYcuiu7MFu92mknfRUPa9kH1nppAT77NUtUpeHy17k28G+JikbgyZm778c1omBzBopJLjjpO5JA71fNGjI9W15CEjiv+6W+iYWjJkKF1ImUfmubvIEDenL2vWHD7UnFNbSy6MCpbFLGI3a3ctQ54LLO6BQWmuPI/l86aEre61uVtryZuYOyE7Z2LydVZruX0dpFolbx4u93m+GeCXJDUO+YnMqPfPaVHJYNBIJVuTxeuw41B3prqWPGREeTcfTiHdBIPCSccrifj99eLsOlY/A1M6fd+cZ9wb8lwIliRsQYZCbUfYMumuOoLdblLJm4gbkL0zcSScRmI5flsOXK+SyyL8mwF+TVKLpi//nLb3qg4Mj6tKXsfaa/t88JVOJr2oriVvI0omH7s3orybD6cElUwtGTIULqTclURERylx5sGorSXflGdoIa9dEuUCi3tgUKjtCFsmvVXynbXkEFg2yN4ZM+5Jg9tMdUElF0X4NwP8JkmN/5w4Hff+OW33VR0YnTDg3lfJ4SoTy8g1h3JsMOpSafVvXG/+OU5EeTcfTiHdBIPCScf0BGnw7vw1+npchmDJEmerjAqb5pe4N+S5QCIEBoQtL7rX5oLd7lHJa/x7IbtnZNf51e7+iK+o5M0Tnn6kpkvk2SapBau8/jktkwMYuNSSk4VPOwBIgyvB7A4u1JIHjCjv5sMp4f6pJUOGwoWUeWDekEQ8ON2sryUXRYVt8yvcG/JcYHEPDAq13TyUCVs5equO+2rJy5qkEuPisfNSy90f8dxfrUreRPgzu7wZ4HdJ6mLR08v557R84xoMXFRy4u/iOJmx92rgONZ9qX8vebsxSkR5Nx9OId0Eg7IKaBy8zZMIOxQNS2m6WRkVds0vcG/Ic4FyARiUDRHClk13ZwuGu0Ulywl/fCkfesy9MqUWaeGXneW5ppI3Ef7kUd4M8PskdV3lPRlC/jktkwMYeKjkOHWsQ82O8U6TSSsu1ZKHiyjv5sMp4f6pJUOGsoWUOHZbJxExzjxxGrxSSy6ICvvm9dwb8lxgcQ8MynJlwpZNb9VxWy05RrZvLZstSHClxXsjpZz5jupV8ibC62tDmQD/W9YPvr/OH/KQpMbNszHkn9OiksHAQSUv43p1ItmRGckFQaQn12rJ24iiz6P3RpR38+EU0k0wKJt07koiosP5ucB9lE7flVHh0HzH19fLYF9f5zrgNORVJ1G3ESxJ2IIMZYkQYcum+zdYg+FuUMlLnFWHhXyCOUMUNPFkvskLKjnaZUKdFE4D/O94ZEbMmpjqmKTGBicR2z+nRSWDwfsqOQ7bzUiLuzIyMzbJLMr25GItebCIksuHrxFUMrVkyFC2kCLDvXUSsclknse1WvIbecZ64sS3BDDZXFt7hbwbYXEPDMpyZcKWTW/VcVctWZqH9kmiVnQxj5FSwXyTV1RynDAmtAh/EuD3GW1gPjkxVZKkrudplvHPabuv6sDohAH3hkr+vUmsVk38p+yRTY042EvqtR248hvXM0NFlPN8+Cqkm2BQliTN47J9EhH945GzYGkF1CnP2ITyF6+TZWNtHa8umxdD3q1QLgCDslx5HsmErSzdnS1Yrr1K3n5GSaJWdDHlrJbM3V1RyUaE1wN8MptMqKZKk9R4QXUY+ee0TA5gcL2W/OtP+XaesPGfEveXJn6D3ZXLteShIor/ulvojloyZChbSJnHZX5klkQRg8U7ZPtZXK0lG1FBzzN+reeshAgm/0wvLpvXQt69sLgHBm6Lez8+bPWuzd1TS15ytu3GfOSF7Gk8UmqYu7ukkpdEciKN8GqAX4bwjmlYJA+tJKnryek48s9pUclgcF0lh8xjw7bwWuL+0sRvsLty9b3kiYEiip4PvwPpJhiESWcQlby44jMnwdLp2yPP2EStLVMIlH+trT1C3s2UjUn4wQykkn9I2GpGMF1zlSyNX0li+pnH1EtZNlx4f6RUMXd3TSVnF0K1AL/OP3uUHzrTktT19CRq++e0fOMaDK6r5L0j7HxHDmWH3quJ42B35XoteaSIoubDbxE6o5YMGYoWUuJAbppErI4oOx7G9VpyNipozVdTHfidBmolhm1OLwp5d8PiHhgU5cpxnBO2MvRWybfUkmNUez1o+pnH1CtXaYkfdEk1xoH5Ji+q5NxCqNI82uPF94T8U/mjWWqSurRPRpJ/Ttt9VQdGx0clHwaZHMoOvZI2/XijljxQRIlh2C+ikG6CQdGkEwdy0yQiDNYZv/F/K6XTt0OeIbtebGPQH0UquTLk3Q6JEBgQtrzoXpsLtmuskpekbb/52grEUZBbTylp48h8k1dV8nKzE4f7TZtvZoPv6Abx9cykdbzw3uyxWTKU9ObvwOQABk4qeT8lRIeQTZWSNv14p5Y8TkTR8uH3CDM4tWTIULSQEgdyyyRicYunToGlS1KVUUFpvrZd9v6SzC8eWlvHPbL5Il50wgx591NqSfixFOXKhK0CequOG2rJS9ImGVuqkkvWU0raOPKeSt4mqrJHSJvLjondoy0jOyD7TpPUtfH+wEnzN+i+qgOjEwacxzeud8NMDmWHXkmbflz+jesXg0QUPX1+B9JNMHArypS0yRCG6sxjZ8BgyRJnq4wKafOY5B1stVG+29Zvh7z7oVwABkXlAsJWAd2dLVivrUqOMS0+ZqqS71hPqeRNlbyZDvafbtJ8mU6OoyC2DMiu8yR1bbyzz1nz6zA5gIFPLXliO87kUHbolbTpx3u15FEiykn6/AahI2rJkKFoISUO5HZJxOqBF9PV/pQuSVVGhbS57EhMtdpw2zqJYS/WxkbI6wCLe2BQlCvHMU7YytBbdbSvJS9Jm2wrKvmG9ZRa3lXJy/0ePt5j86VZOgjWGWm9+GmSujbeutJp88ugksHgukoO/Nr8MajNQJOd2aFX0qYfb72XHBgiosQp1y+ikG6CQZh0zCESB3KzJGL1v5tykAaUTt+VUSFpvjRLTLVacXPxYwyLrI2zIa8HRWMSfjJF37uMQ5ywlaH7N1iD+Vqq5OVDWj6jVCWXXOy99ZRq3lbJ6+rALpgemy+tZHvLMtWsB8+TVDkwsbGQf06LSgaD91TyxPp3NlfPUYJGgpw26PB8t5Y8RkSJ4dwvooR7opYMGcoWUuZx2TCJkHM9x/7tvFtLLs0zZFszVWy7PfhmyOsBi3tgUJYrzyM5H1R+fNjqrTqa15JjRFsfUkl4ZU/uYiVpsiNzd2+p5OXI7gM+NpdNfZ1Hjm0ufp6krpPPxpn8c9ruqzowOm+r5I3rLAO3xP2lid9gd+XtWvIQESXJh9+GdBMM3NLNd5KIME5nnjz9laabb+YZ0c5qV/Hg5uJvhrweUC4AA8KWF92dLRiwoUqOAW3zjMpnLntajZQLzN29p5LVCH9oHuccfQgsF5DtbJKqTV/+OS2TAxg4qOR05Je4vzTxG+yuvF9LHiGi+K+7hWmcWjJkKFtImcdlfmS+kUQsnvPo2a90SaoyKhybR2OpK3XLBdaLH2LYlsXu5yGvC6WWhB9LWUVpHsmErSy9a3ONa8kxqdrGS+Uzl88yZ4g3RsoV5u7eVMlahD80j091UmOSo+vFc0nqYut1+vLPaVHJYBAG3LsqefGTOHLjSM4VY6WJ32B35c3fuH7RPaJk0ueLkG6CQdmkI47QJomIZ145dyCCJUucrTIqHJvL5slHEW25Xvy9kNeFUkvCj4Ww5UV31REs2E4lx3i2fUTlMy8YKQVNPJlv8l2VvBxcA+qhefZs5XA2SU1Xef1zWr5xDQYeteQk0YojeSlfpBQ06YlHLbl/RMmlz9cId0QtGTKULaTI0G6SRKzKsGSda1wcaslaVDg0z56tHc4GrXjwNOR1gcU9MHBTyT8+bPVWyW1ryTGc7Z5QUckFiyXSIt+fHz4qeTm6mODQXLbORkBil3ySujqFTF/+OW33VR0YHR+VfPQr2cyM5IIg0hOH95IDnSOKkQBfgHQTDMKkYw+RhknE6gbPzjaLp+/KqHBoHj+JM2PJ4fXi74W8LpAIgUFZIkTYsulemws2bKWSl09p9yEpw8IeKTE7k8XL5sx39L5KTiL8oblsnVkxsUvhKu3EbCj/nJbJAQx8VPLRNQ6bCuJao45On1py74iST5+vEO6fWjJkKFtIaZhELD739KnPpZacRoVDc+uTkMPrxd8LeV1gcQ8MynJlwpZNb9XRtJYsbQ6NtGEhu86vFrOzuxZF5pt0UMmbCD/f+r659VTRP2TTTlKXdYnXoPLPabuv6sDo+KrkONjsyURca9TR6VRL3kaUedq8N6Ic8mEHSDfBoDBJmgdmiyRi8bjHz3yl6WZlVDg0tyKxHF8vvo9hKcsHoCVRfaBcAAaFufI8lAlbObo7W7BiI5UcP6XD82VU8rkl7CTZFzeVvInwIandNzdXieS4bBUkqbHBy5b+OS2TAxg4qWTxlDjYYgA4X1CVBn5j3RevWnLfiGKlz/UElUwtGTIULqTMA7NBEhFPqz5xPJxqyceocGh+CN0JYtD14m+FvD6wuAcGdYt7hK1zequOhrXkZb3xsAaifehWXL09BZ5v0kUlbyL8ZIh9c3OVSI7LVkmSulg9GNM/p0Ulg0EYcA4q+RAmTFe5OJfchstvXL/oGFHM9Lka0k0wKJx0xBO8k4h1/Jd479gES5Y4W2VUODS3PggJ1evF3wp5fSi1JPxYCFtedP8GazBjG5UsLZImWjprpbh21HZmviEflbwuu/7x+9A8HvKr/Gznk+8GOS0qGQycasnHkCCbp0N5hNQph18t+bMiSrg6tWTIULiQ0iaJWLPNEucdHLdacjYqyCFPlRx7mDiGvD6wuAcGhdqOsGXSW3W0qyXHUJY8nToqZN/Z5eI5ty2LzB36qOTNgP3j16G5bJ09djxTNss8JnYxmf6ag+XovqoDo9NIJVuTiRwednC6vZc88UkRhXQTDErrdvPIPB+b15KIZfB/wrRXmm6+FxWsUC1nrhc/xDCN2MXEMeR1gXIBGJQOkXksE7YydHe2YMgWKjl+tmkoU2OofKhnpngdvTEuzjfppJK3C6GH5rJ1ZsV4omwWrfFuHGTpLdu8CiYHMGikkuPQP1kajc39hrozjrXkj4oo4YrUkiFD6UKKDE7XJGIZ+h8x6znWkjNRQc3wNkjz9eLxfNlUOQ95XWBxDwxKc2UZzoStU3rX5prVkuW4zat5DKx6GulfwbBwVcnbhVBBDhgOkkw3ZYZYXCTiZzdUMhiUquS/vr/Df2djM3Es2T4ZfUV+2BPPWvInRRTSTTAonXQaJBFhdM58xqRXasn3okI8+yzayeH14u+FvC4ESxK2IENpIkTYsuiuOoIpG6jkJICeIifIlm6L/Dhqwdyjm0reLoS+kP3G2XJ0PVy0xptav8rDsvRe1YHhKZ0c5pF5PpqSw/kgIAfHHZuuteQPiihhQqeWDBmKF1LmoemZRKxeVvd9x1EpteR7USGefZJXxg9ivfh7Ia8LxWMSfirF2m4ezIStc3qr5Ea15PjRFiBn5AJlXE650VDzA/ip5GQhVHanE8aW5STZLl9YOkxfVvNyuq/qwOiEAVeikvOek+Zp2bEfLzburOD4G9cznxJRSDfBoHjSyblOHOg1s9fqY5+Rbc6WLHG2N6OCbJ6EsHjSevH3Ql4XSITAoLiiRNgy6F6bC7Z0V8nHcJZDTonZnWaMOIpu/My9VfJxIVT2RjPqQyDaZL14qh1OiLf1wmxeDJMDGJTWkuMQ1QdnHPubJVTZo62qXplLbsa5lvwxESVcl1oyZCheSPFOIuQUz+HeF+da8llUUIL3Bjm4ufibIa8HLO6BQXGuTNgy6K062tSS97Ezj5yynJNG1kVzy/YdzAPXUyUfVg5kZ+apt2fIjnWXPfx3H4Gft/CNazAoVcm5uUH1+ZgjKSfE0T7wtOD7XnLgMyIK6SYYlFZAc4NfCygWYWjOfMyMV5puvhkV4ulqV8sZ68XjLtk8Zw1gAdnZBcoFYFA+RAhbebo7W7Cmt0qO+W8Rcs56kmyvyH4172uFv0reL4TKvsxTbycg2VGxxrs9u6h5IUwOYFCqkhe/1kZnHL27Y7IvPSEruAfBvZb8IRElXJVaMmQoX0hxTSKW8f45E16pJd+NCrKtnb8K3fVgvIZsZlBDXg9Y3AOD8ooSYStPb9XRpJb8nUXO/EM25Zz10z2a42x/U+Zx66uSdwuhsmt1g/TpFkNtWsdLFMxe2/NLmpeBSgaDYpW8DNB0ClgO7YqvS4p0OGFxrBtfyajGv5b8GRGFdBMMKiadOESPzc/2Z1hS1xJPfAillnw3Kiy2S0L7JmStF4+XkM0casjrQLAkYQsyELa86P4N1mBO/1/vyhE/RtlcWHLgXfD5vQThW1PgFip5M4DX5su+MwcJyK6qNd41Xb70KZ2ASgaDYpW8DtDj+FzG/mGoLft3ydepCw1Fg1ryR0SUoJKpJUOGioWU+iTi6+tLzX9WOTby2lslDWrJelSQHecLmhNr63dDXgdY3AODilyZsJWlt+po9veSz4lhTjZX1ixuDa3rh+6Xl5Uw36S3St48oeyYWPZ9byeU1UECsnM1R5ExFtdztF33VR0YnTDgylTyOsb3Y192Thwi/TqiN2Mw5CsvZMeYeP/G9YvnRxTSTTCoSZLWUV6WRLyix9ZRXvRKPNoSLFnibG9HhZNIsZG42yNvh7z7oVwABuXlAsJWnu7OFgw6iEreDJXv+bq/N0H1ZiO1UcnrE8r2xDqfyFNPxAdPLh4bl5l9ubSfxzA5gEHF5LA6/B/fEoR+r3FeGbcbZ/map4ivzSXGXjxtUkv+gIgS7ohaMmSoWkhZA0JJEhFbJ465XuaUEmcejFJLvh8VNvZ7ReoJCdbx0No67pFNg+XSst0FFvfAoCpXXv2FsJXQuzY3Ui15uajGzSnwfJP+KllrvhvY4U1t+WfwF/mHtJx8R3YUmr2yeQGoZDCoUMkbPRf4/msf5JWBtpk7jgw+LFu8lxx4ekQh3QSDMOmUD5F5fOok7reEk+N43gcinbFX5VRKp+/3o8I+tH9vQ3sqwZUYlqOyeRPqxiT8QOq03TyidQhb0213Te+C3YZRyYesecPdCyDzTTZQybG9bM2cDe3v1FTpBJNH2l/4lE7ovaoDw1OhkjMOP6GOs9N5YPRR2aiW/PiIEu6VWjJkqFtIOY8pqfetjiI7hDMH2vHAokybWrIaFU4/hl9p7hjNLZsm0l62usDiHhjUaTvC1jm9VfJYteRlUfLI7esfzVSynCAbL/TBPQ2LxFTVpZzXCRc+pRO6r+rA6NSo5MPbsjtOBu3JCcMPyla15KdHFNJNMKicdCqSiNVPZMeLsyvs+eCijEdUODHiZDX519raI+TdDIkQGBC2vOhemwt2G0cl6/ldBwO1U8mvM+TfQjTJlvDQialq13jljAuf0glMDmBQpZJ1hw+cBnN10XX80N+slvzwiBJUMrVkyFC9kKLFFHXWWtxkd7Qs26SWvEWJCr+0jyEYTf65tnYJeffC4h4YVGs7wtYJvVXHYLXkiTS/88vIypnvoo1Knk+Rf0bSCWV+6MRU0REqTBJO8bNg91UdGJ0wPitUsp5M5UZsWn/+fsD6aJvfuH7x5IhCugkG9UlSaRKxJJa7w1pAUnhgUSZYssTZnKJC8jG8ArVsrK19Qt6tUC4AA8KWF92dLdhtKJV8HCtfXT7V+R4aqeRwjvxrZftjvctDJ6aqX+Odz7nwKZ3A5AAGlbXkiUTRWS6/P2H5IeehaVhLfnRECXdJLRkyXFlIKUwiZPjvprSd32SglrxDiwq/dh9DDNSyubb2Cnk3wuIeGFzJlQlbGr1Vx+VaclO+vl6/y/rdRyJPzKO1RCVf4lsN8PLQ7usCvx1zWlQyGNSr5Ilf0eMLXf7XFCKkvewZneL3ki/x3IhCugkGYdKpHyJlSUT4iyuPiSFv03T61qPCFNnDp+BvZD3k3cX/v727WXZcxxLFXJH7Ge4j1CzDE8/2zNHRI0fnpF/gPsEZd3bkwNUTR5yR84Zd5e7rhzUpASQlLhKgBIp7c39fnT6doiD+4AAgFhalfKxN8oU8NBEybAUOf4K1/w/y4aLk4+0bJX9/7QDfsDuJkil47OZwetW55Id83hGlnxLIJbPCQkor+9bka6ftLx7y7miTFJgrt3J0TX7MXPLx9o2S//Lipx7apZIOX9XhoxMlh/bNJX/eEcV0kwLTzVZ2rsn9hrfIoY+OapMUmCu3cnhn644vSp7bOUr+tNwcKBAlh/bNJX9efZQsl8wKCymtqMlW1CQF5sqtHL3eIJccEyXH9HwK+p4jSp6p/o3rL8Z0kwI3nVb6mtTZWlCTFBi2Wjm8Jrvji5LnRMkxT5FQIJcckkuO+V4yBRZSWlGTrahJCsyVWzk6SpZLjomSY9bHKBAlh3b+XvKnZbpJgbxdK27frahJCjSRVg5fb+iO/+1f058ZiJJjej4FouSQXHJMLpkCCymtqMlW1CQF5sqtHF2TcskxUXLMUyQUiJJDcskx000KTDdbUZOtqEkKTIRaObyzdccXJc+JkmNuDhS4OYTkkmN9lCyXzAoLKa2oyVbUJAXmyq0cXZNyyTFRckzPp6DvOaLkGb9xHTPdpMBNp5W+JnW2FtQkBZ67bOXwmuyOL0qeEyXHTFgokEsOySXHfC+ZAgsprajJVtQkBebKrRxdk3LJMVFyzPoYBaLkkO8lx0w3KZC3a8XEvRU1SYEm0srhNdkd329cz4mSY3o+BaLkkFxyTC6ZAgsprajJVtQkBTJKrRxdk3LJMVFyTJRMgSg5JJccM92kwE2nFTXZSl+Thi1W6GytHF6T3fFFyXOi5Jj1MQpEySG55FgfJcsls8JCSitqshU1SYEouZWja1IuOSZKjun5FPQ9R5Q84zeuY6abFLjptNLXpM7WgjZJgXRBK4fn5rrji5LnRMkxNwcK3BxCcskx30umwEJKK2qyFTVJgblyK0fXpFxyTJQc88Q1BaLkkO8lx0w3KZABbcXEvRU1SYG5ciuHd7bu+H7jek6UHHNzoECUHJJLjsklU2AhpRU12YqapMBcuZWja1IuOSZKjun5FIiSQ3LJMdNNCtx0WlGTrfQ1adhihc7WyuFZ+e74ouQ5UXJMz6dAlBySS471UbJcMisspLSiJltRkxR44rqVo6MOueSYKDmm51PQ9xxR8ozfuI6ZblJgabYVGdBWtEkKNJFWDq/J7vii5DlRckzPp0AuOSSXHPO9ZAospLSiJltRkxSYK7dydG5OLjkmSo7p+RSIkkO+lxwz3aSgv+loIi24fbeiTVJgItTK4cNWd3y/cT0nSo554poCN4eQXHJMLpkCCymtqMlW1CQFlqRaObom5ZJjouSYnk+BKDkklxwz3aTATacVNdmKmqRARqmVw2uyO74oeU6UHHNzoECUHJJLjvVRslwyKyyktKImW1GTFJgrt3J0Tcolx0TJMetjFPQ9R5Q84zeuY6abFJhuttLXpM7WgjZJgSbSyuE12R1flDwnSo7p+RTIJYfkkmO+l0yBhZRW1GQrapICGaVWjo465JJjouSYKJkCUXLI95JjppsU9DcdTaQFt+9WtEkKdLZWDl9v6I7vN67nRMkxPZ8CUXJILjkml0yBhZRW1GQrapICc+VWjq5JueSYKDnmKRIKRMkhueSY6SYFpputqMlW1CQFJkKtHN7ZuuOLkudEyTE3BwrcHEJyybE+SpZLZoWFlFbUZCtqkgJz5VaOzs3JJcdEyTE9n4K+54iSZ/zGdcx0kwI3nVb6mtTZWlCTFHjuspXDbwDd8UXJc6LkmJ5PgVxySC455nvJFFhIaUVNtqImKbC418rRNSmXHBMlx/R8CkTJId9LjpluUiBv14rbdytqkgJNpJXDc3Pd8f3G9ZwoOabnUyBKDsklx+SSKbCQ0oqabEVNUuC5y1aOjjrkkmOi5JieT4EoOSSXHDPdpMDSbCtqshU1SYEm0srhNdkdX5Q8J0qO6fkUiJJDcsmxPkqWS2aFhZRW1GQrapICc+VWjq5JueSYKDmm51PQ9xxR8ozfuI6ZblLgptNKX5M6WwtqkgLpglYOf4K1O74oeU6UHDNhocDNISSXHPO9ZAospLSiJltRkxSYK7dydE3KJcdEybHDV3X46ETJId9LjpluUiBv14qJeytqkgJz5VYO72zd8f3G9ZwoOebmQIEoOSSXHJNLpsBCSitqshU1SYG5citHrzfIJcdEyTE9nwJRckguOWa6SYGbTitqspW+Jg1brNDZWjm8Jrvji5LnRMkxT5FQIEoOySXH+ihZLpkVFlJaUZOtqEkKzJVbOTpKlkuOiZJj1sco6HuOKHnGb1zHTDcpcNNppa9Jna0FbZICTaSVw9cbuuOLkudEyTE9nwK55JBccsz3kimwkNKKmmxFTVJgrtzK0TUplxwTJcc8RUKBKDnke8kx000K+kmSJtKCiXsrapICE6FWDu9s3fH9xvWcKDnm5kCBm0NILjkml0yBhZRW1GQrapICc+VWjq5JueSYKDmm51MgSg7JJcdMNylw02lFTbbS16RhixWeu2zl8Jrsji9KnhMlx9xmKRAlh+SSY32ULJfMCgsprajJVtQkBebKrRxdk3LJMVFyzPoYBX3PESXP+I3rmOkmBaabrciAtqJNUqCJtHJ4TXbHFyXPiZJjej4FcskhueSY7yVTYCGlFTXZipqkQEaplaNrUi45JkqOiZIpECWHfC85ZrpJQX/T0URacPtuRZukQGdr5fCa7I7vN67nRMkx62MUiJJDcskxuWQKLKS0oiZbUZMUiJJbObomL7nkP//441/9k/+56AfBb5cX07e++D+dPgRyc2BF33P+6dJYUrvxv74a+mjw27/kruSf6z/XEUWUzIpLEzGcPPG/bKjJfpt/HvvnwkSIgrvO5n/b/9f/0+kq8tDOdomSYYN/Tm0HAqmVQLXUdCCQGgl8LKl9QiA1Epo4MuoQJbOVKJkVqZVAtdR0IJAaCXwoJkKsSK2EJkTJfCZuDqxIrQSqpaYDgdRI4GNJ7RMCqZHQhCiZz0SUzIrUSqBaajoQSI0EPhQTIVakVkITh3a2/gT+8//4N/+7/d/f+nr5/pe//Lfuf/41/svv9lHQ/2jFv0yajH9d/nX5m6B+3G7zLz8WS9GliSw2IP+q/1d/+1aTLf51qcnUPiFwmSsvNB//2vKvD/Eb1//xb9y5RMn+JqiZPgQSJbOi7zn+JqiZy98E5e9LnulDIL9xzQpLs62oyVbUJAXmyq0cXpPd8UXJcz/7ehElz7g5UHDNJXPH35cck0umQBNpRU22oiYpMFdu5eialEuOySXHrI9RIEoOXZ64lkuekUumwHSzlb4mxXYtqEkKzJVbOXxK2R3/23+l0JCBXHLMhIUCUXJILjn23lWLKJkV8natqMlW1CQF5sqtHF2TcskxueSYnk9B33NEyTO+lxwz3aRA3q4Vt+9W1CQFmkgrh9dkd3y55Dm55JieT4FcckguOeaJawospLSiJltRkxR44rqVo2tSLjkmlxzT8ykQJYd8LzlmukmBpdlW+prU2VrQJinQRFo5vCa748slz8klx/R8CkTJIbnkmO8lU2AhpRU12YqapMBcuZWja1IuOSaXHBMCUaCJhHwvOWa6SYHpZitqspW+Jg1brDARaqWvyUOHre74cslzcskxt1kK3BxCcskxuWQKLKS0oiZbUZMUmCu3cnRNyiXH5JJjej4Ffc8RJc/4XnLMdJMCebtW3L5bUZMUHJ4BPY3DEy/d8eWS5+SSY3o+BXLJIbnkWB8lyyWzwkJKK2qyFTVJgYWUVo6uSbnkmFxyTM+nQJQckkuOmW5S4KbTSl+TOlsLapICw1Yrh9dkd3y55Dm55JieT4EoOSSXHPO9ZAospLSiJltRkxR47rKVo2tSLjkmlxzT8ykQJYf8xnXMdJMCS7OtqMlW1CQFmkgrh9dkd3y55Dm55JieT4EoOSSXHJNLpsBCSitqshU1SYG5citH16RcckwuOSYEoqDvOZrIjO8lx0w3KegnSZpICyburahJCsyVWzn8Cdbu+HLJc3LJMTcHCtwcQnLJsT5KlktmhYWUVtRkK2qSAnPlVo6uSbnkmFxyTM+nQJQckkuOmW5S4KbTSl+TOlsLapKCwzOgp3H4lLI7vlzynFxyTM+nQJQckkuO+V4yBRZSWlGTrahJCizutXJ0Tcolx+SSY3o+BaLkkN+4jpluUuCm04qabEVNUqCJtHJ4TXbHl0uek0uO6fkUiJJDcskxuWQKLKS0oiZbUZMUeO6ylaNrUi45Jpcc0/Mp6HuOKHnG95JjppsU9EuzmkgLFrlb0SYp0NlaObwmu+PLJc/JJcf0fArkkkNyybE+SpZLZoWFlFbUZCtqkgJz5VaOrkm55JhcckwIRIEmEpJLjpluUmC62UpfkzpbC9okBSZCrRz+BGt3fLnkObnkmJsDBW4OIbnkmO8lU2AhpRU12YqapMBcuZWja1IuOSaXHNPzKRAlh/zGdcx0kwI3nVbUZCtqkoLDM6CncfiUsju+XPKcXHJMz6dAlBySS47JJVNgIaUVNdmKmqTAQkorR9ekXHJMLjmm51PQ9xxR8ozvJcdMNynobzqaSAtu361okxTobK0cXpPd8eWS5+SSY3o+BXLJIbnkWB8lyyWzwkJKK2qyFTVJgecuWzm6JuWSY3LJMT2fAlFySC45ZrpJgaXZVmRAW9EmKdBEWjm8JrvjyyXPySXH9HwKRMkhueSY7yVTYCGlFTXZipqkwFy5laNrUi45JpccEwJRoImE/MZ1zHSTAtPNVtRkK31NGrZYYSLUSl+Thw5b3fHlkufkkmNusxS4OYTkkmNyyRRYSGlFTbaiJikwV27l6JqUS47JJcf0fAr6niNKnvG95JjpJgXydq24fbeiJik4PAN6GocnXrrjyyXPySXH9HwK5JJDcsmxPkqWS2aFhZRW1GQrapICCymtHF2TcskxueSYnk+BKDkklxwz3aTATaeVviZ1tha0SQo0kVYOr8nu+HLJc3LJMT2fAlFySC455nvJFFhIaUVNtqImKfDcZStH16RcckwuOabnUyBKDvmN65jpJgWWZltRk630NWnYYoXO1srhNdkdXy55Ti45pudTIEoOySXH5JIpsJDSippsRU1SYK7cytE1KZcck0uOCYEo6HuOJjLje8kx000K+kmSJtKCiXsrapICc+VWDn+CtTu+XPKcXHLMzYECN4eQXHKsj5LlkllhIaUVNdmKmqTAXLmVo2tSLjkmlxzT8ykQJYfkkmOmmxS46bTS16TO1oKapODwDOhpHD6l7I4vlzwnlxzT8ykQJYfkkmO+l0yBhZRW1GQrapICi3utHF2TcskxueSYnk+BKDnkN65jppsUuOm0oiZbUZMUaCKtHF6T3fHlkufkkmN6PgWi5JBcckwumQILKa2oyVbUJAWeu2zl6JqUS45V55Lf0v9/jR9HT7P1fAr6niNKnqn+XvIXG1FMNynol2Y1kRZqF7lfPCq8dshrQrqAAk2klcNrsju+XPJcdS75/aW37+9HZ6P0fArkkkPVueQvNqL0UbJcMisspLRSW5MvHhVeO+Q1oU1SYK7cytE1+TFzyb/+4+/9eX37+9/+lra8WnUu+f2l//l+HP3VRiEQBa9pIn+894/qfvv29nZwlFerOpf8xUYU000KHpsk/Xi7jhDvb8+lKt/+fHikedvYsHePTfuarDmnF48Krx3ymqitSb6sxyZChq25w59g7StyUy75Gr9mdQH2JeaM/CMVmPp1Wzoqsr/6XPK2/37XlvvtW3q51ffuoxuaZHezu2j3RJP1MQo23xxyK03S1jXpRpLtPUg3UZ9L/lojSn/+csmseGAh5cfbpZlmD8czT400XWd53/KJ7ljzfnV7IQWlo9Xnkl86Krx2yGvC4h4FD8yVDVuho6OOzbnku4D3Z9q87jaynvidCkz8R3prdEQ+eUMuedPN4ckB/nI7Sn+u0H5OK0qmYHOUfGmio7R12Y/bW0Bn06B+kOrfuP5iI4rpJgXbbzrzOdpDDfbJkebyifoDX056doAt083isWpr8sWjwmuHvCZMhCjYngE1bMUey8o31J/lllxyX36iLoJNhef+ngoMfv1O70wdkE7ekkveslbz5ADfr/Fu6HmX4p1H715zhz/7wEe3dUi7H0/T5kXh+LvlLnCMLbnkrzSi9Ocvl8yKrQsp81li54GVmCdHmnQWtTPUhVBzy3QzfWTZllzyC0eF1w55TVjco2DrQopha8nRS1Jbc8n/6MtPVOWSFx+4/vbvqUT2K22/9yu9/zKbcskbvsTz5AB/bZLVDebZNd45S6gU9A1uQ5Sc2+ggbV/ST08CH75Rbvhecm3Ji88+ophuUtDfdDY0kdmIktRPFK+eHGmG00ivS3JHfny6WR4zam/fLx4VXjvkNbGxTfL1bJwrG7YWHR519KdZn0ueRbFVueTlKPkul7wUJL8+TN6WS65vyk8O8GnRtnZ4bp/5Oby98tFtzCXnHjFI2xfMimcffcqyLZf8dUaU/qYul8yKbQspuYnObZtvLo40dfe/4TQqg798uPu91083K86rtiZfPCq8dshrYlub5Ava9tylYWvZ0U+wbswlz75gXJVLXvxa8l0u+SZI/t1Jf+y9OEzemEuubspPDvB5oaeyyTy7xjvniWsKtkXJ8xXU9EZsulD63kl/7H3wZrkxl/xlRhTTTQo2Lc3eDCh3Q0R1trJzM7Q8MNKksrU9ZZhVpteD+ulmxdXVZkBfPCq8dshrQrqAAsNWlcph69DO1p9ndS55Hu5W5ZJT2cBtLnnc/c8UFF9Suhcv/m7y1lxy7Qj/5AA/rPTUtZln13jn3Bwo2BQl39wcrtI7oXHB9T216e/jfWDbmuurbc0lf5URpT9/uWRWbFpIGceDtzT/GidsG1ZjxoHpsZEmF668WQ6Hm80Zq6ebNV1yYy75VaPCULMvGfKasLhHwaa5smFrxdFRx8N/X3L/uU5NLjk/cJ1eLhq+8zz95eshnxz8HPaONueSK0f4Jwf4SSdIW1bl4o/evea2JQr5gh5tInlcTS8jY/OfjMpj5Fw3xzrIpt+4vvoSI4rpJgVbJklD75l+INy46tmRZvh8TY/v5DOsPsHBMB1Nr1fV1uSLR4XXDnlNSBdQsGUiZNha09fkoZ2tP9FNf19y0n+uU5NLToFuKcwdnre+LTiEyS995np7LrluhH9ygB8b/KYl4XZzWjcHCnaMkofOdtPVhk7xoRvm9lzy1xhR+vOXS2bFhoWUYZp3OxbEA8eKJ0ea4TQqj5cPt30EG06p6kibc8mvGRWG2n7JkNeExT0KNsyVDVurjo46XpFLriyais2i6Rwmz/7WqD09kEuu+i/+5AA/NONORbPJxUXJvEzf4PaJkof1x7uVzqFXVK6AHmLz95J7X2BEMd2koL/pVDaRS+Ps3DfljfO5Z0eaVKq2m2xKrNzadmG1t+8XjwqvHfKa2NAm+Zo2ZEAvzblzX9ywdfFo4qWZ/lT3zSVXPnCdU8nzlHMOk+v+buY2Hskl14zwTw7wkzXemhb27Brv3OHPPvDR7ZdLzp1n1s2GbpFef0SP5JK/wojSR8lyyayoX0jJzXPekHM3qWu4T440+eOVd8raSWxgOJ+6jz6QS37FqPDaIa8Ji3sU1GeUDFvrjs7NvSCXnH6Tq/TA9bVU9GD1cvy8n4dyyRXj9pMD/HSNt6LrPLvGO3d0e+XD2y1KzgWC9rd4e/g4Hsolf4ERxXSTgvqbzqVtdub9bHkiGnhypNk6fcz7fODGmj5Z2x9rM6AvHhVeO+Q1YSJEgWFrUfrklmHr0M7Wn+u+ueS6kjkUjsLuA5LJj+WSy/8pnxzghzWYq1JQkIu3m9O6OVCwW5S80neGfpFef0CP5ZLPP6L05y+XzIrqhZS1aC33k5qW+9xIM8w2a3p7Jx/tgftqHjNre/9DueT9R4VcA1d7D3lNWNyjoPq5S8NWwdFPsO6fS14LfydSqfi57PTeC5PJD+aSi/8tnxzgh5acFBr0Wvd7zNHtlQ9vryg5vx825vxm5TLoAR74jeuLs48oppsUVC/NXppmJ728ld6r2NGTI83G6ePQA7ePXZs/WluTLx4VXjvkNdHXpGGLFYatBbsNW7vpT3bXXHLd15LXY+n81yanly/wYC65OHI+OcDfrfGWbl/PrvHOHd5e+ej2ipLXu05684/08uN5MJd8+hGlP3+5ZFZszYDGjbM0voyeG2nypytvk0MHrBkb7mw81MO55L1HhXwd2b5DXhMW9yionSsbtkqOjjr2zyXXfS05x9ILf91Tevd1j1w/mksu/dd8coC/X+MtNNJn13jnHg2B+DL6BrdHlJzeXuhf9TeTgzz4veTOuUcU000K+klSTRP549I0F3tZerfcdFPBx0aarYmSvv33HpgFbj1U/XTzxaPCa4e8JqQLKKidKxu2Sg5/grU/211zyXUFU6mlWDp9M/l1fxnU5lzyONCv/ud8coDPKziT28ra7evZNd45NwcKdsol57cXhtbc1B9Y2nyNzbnkLzKi9LdbuWRW1C6kXFrmcndJTbx4+3pqpBmmgJUD0dDb0+st0kc3jHm1NfniUWGohPT/C9WRi6WXh6itSb6s2rnypS0vF02t/SsPW0dHHbvnkrc9cL2QSn79I9ebc8nDH9b/ez45wA+LtrnNd1Ya21A8vX6eKJmCnaLk0s3i+nbDpt7Y5lzyFxlRTDcpqLzp5La51MkKA8zgqZEmd8fKm2Q+56qR4U6+nspD9fqarOlsLx4VXjvkNWEiREFlBtSwVfTolLKZ/nz3zCWnLPBzD1xvSF03sjmXPP5p9T705AA/LtpW3b7G4q0c/uwDH91OUXJ6d7Hx1d5MjrI5l/xFRpT+/OWSWVG5kJJHgMXWm94vtd1U7KGRZuiy6XXBMNt8oD89MlPdmkt+0ajw2iGvCYt7FFQupBi2io5ekto9l1xXLn15eTlXXBdst7M9lzwd4Zf/iz45wOcm1rXOobWt9K9J8UYsoVKwT5RcbMq5wAOrmy+x+TeuJ38884hiuklB5U2n2BNSgcKunhlphi5UOQrlU37klpo/u6Ur1t6+J3UwXNKOo8Lkv1z+445DXhN9TRq2WGHYiuTP7jFs7aY/4R1zyTlJ/Leff/v9++9/+9uvOFucSi3H0q9+5PqBXPL455X/pNPiD5gu2las8j67xjt3eHvlo9snSl5/t5cKfNRfuX4gl/wlRpT+/OWSWVG5kHJpmGtNszyG9J4YaYbZZk0/7+S++8gddeis6XWV7bnkl4wKrx3ymrC4R0Hlc5eXpmzYWnP0E6x755Jzknjib/NAufS15NdHyY/kkqcj/FKbf3KAv1kwGhr34u5uijdxdHvlw+sbXPsoOXWclbZ3LdCwrbe1/XvJ0xfnHVFMNymoy9vlprncx+qmm0+MNLkvVt4hh+5WmcK5kT667bO1i9wvHhVeO+Q1IV1AQV0TMWyVHd7Z+jPeMZecnpS+NYuTy1Fy7fFaeSiXPB3hF5Zlnhzgbxdtx1XehSb07BrvnJsDBfvkkss3gbqbyWEeyiV/gRGlj5LlkllRt5CSm+ZKH0sl1hvv4yNN3l7bF1PphzpTPta2m/EjueQXjAqvHfKasLhHQd1c2bBVdnTUsXcuORW7dxcO5+ey08tIKvGqKPmxXHJ5hF8Z4H+8XZvQ+9ty87tbtB1XeeM29Owa79yjIRBfxj5RcnpzpSWvf/5wj+WSzz+imG5SUDdJquj/qcR64y0XWjjS0Hcq8yS55z4y/9t6rKSvyZrO1nBUeHvre3j33ttyHNBuyHuZ2prky6qbCBm2yg5/grU/5f1yyTn8nflHKnBV8dtcL/4bkx/MJQ+NtROO8IsD/I/x1tBJbX3Wru8XbXOBhRH72TXeuaNXdfjwdomSc0teGV0rFmWP9GAu+fQjSn+WcsmsqFtISc197e5UUeTxkWacAf54uxzo/c/VXpK75/tf3t4vf/5zJY68lz+8sR8+lkt+YlQYP9h5T9eXXo6l89Wklw8PeS9kcY+CurlyasyGrRVHRx0755KDryUnN+Fu2ra2sxQl/3t6ubdHc8lDU+xEjee+eHI7o+1dPjyb084WbcfPRa1oVvxpomQKdomS/1h78yo39m3LlC/zyG9cX5x8RDHdpKDupnNpl+stM7Xt1X09PNIMHWfa83JgOJd3clO8tl8NH06va9XevhuNCjcxcu/64fRiLJ33nl4+OOS9lIkQBXUZ0EtLNmytenRK2Ux/zvvlklOpyDSbnDatRckv/vmuh3PJhRF+Vvxidjfp9H1iNqfNO5/fYMJONC/+rMOffeCj2yVKXn0zSUXaNfamHs4ln3xE6Q8nl8yKuoWUS7tcb5k1o8ijI03U43pLd8v09kzNEDF8uKrwxKO55IdGhflCXac/4/TH+c7Ty8eGvNeyuEdBs8W9Lz9sHb0ktW8uOT1w/fvn5XvIv37lUPdi8nx12vKBouSHc8mTBZOoNYQDfD/iznXNYtb0g0Xb8VY0b0dB8SdZQqWgb3Ci5JlHv5fcOfWIYrpJQX/T+ehR8qSP3gvnhGMnu1dxe83nuPlOXHv7bjEqLNRIVxvpT2PpFkPei5kIUVDXRC4t2bC16vDO1p/1brnky2PSN982zr9m3RuC84qfuP48ueT1hdBogF9qee/zph8t2o4fn80k4jXeZ7g5ULBLLjk18tWmdy3SsLE39Xgu+dwjSh8lyyWzomohJbfMtS5WM5V8bKRZmW2GnWWph/aWH3dMhoNt/nJJ7ZJUg1FhsUa+z6sv7zq97OVddqqGvFezuEdB1XOXhq0KRz/Bum8uuSvw+z70neST81s1UXJNmYaeyCXftL37lhMUz33g6r2T/vgt/UTtpHTe800DHpvufUsKiz/FE9cUHBYl15Q5zhO55FOPKKabFFQtzeaWudbF8pR0rUzNKDIvM/aYyGxnk/4cKcw388G2d8K+Jms6W4NRIW26mo5B36qi5GkVVQx5L1dbk3xZhq1b+WCPDVvFmtxTf9p75ZK7UDP42eoxnZx/wesDRsnP5JLXFkLnxSct7z13g+uPzXUbrv9vLJ13fNvQcrFZU4qLP+Pw9spHJ0oOPZNLPvOI0h9KLpkVzXLJNWVyR0kvQ7Myk+4Zuu8uY/+KpWKxYREsvd7gmVzytlFhcoV56/d04vmtsXTekl5eTeq0OOS9nsU9CqrmyjVDUk2Z1CfOOWwdHXXsmkv+W/x3O41hcgp5P2CU/FQu+WaimrYk8+JpQ+dmqeimQaZt437vmu9Y+PaNheJPeDQE4ssQJYce/o3rq9OOKKabFDRLytSUqRlF7stMOmfXNb5fZrN5XerqdoI7fev97XI2OYS8Wjv6cLCaweRO7XRzoZvXjwrj1dwc7mZaPpbO+00vk0mtpi1JXPy1pAsoqJoI5UZu2FrR1+Shna0/771yyb8WYughTE7J5A8YJT+XS57eDm7/686KD63svhVMm2TaNO72fpI6Fr5p10vFH+fmQIEoOfRcLvm8I0p/ILlkVnz4XPKkZ10nj1eTGeTN7iaz0/dJR/o+2c3KGeZSq2e44Llc8vRCC6NC2jCbE+eSvbF03m16mY2Fb691ofhLWdyjoGquXDMk1ZRJfWL1ePdlxt78wYeto6OOnf++5AVDmHyNeT9glPxkLnnapG7+894XH4rNG8Gk8aUtY/H7u9ek8LShLhZ/mCiZgr7BiZJnnvpecu+kI4rpJgX9TafYRHLLXOtiNWVqRpG7MkOXG7/hkIydaNph4q2dSQyZtswNB6sZS+7V3r4Xu3nlqDAUm53kWFeTnefi6eVgUrFpy8VS8VeqapN8ZVUZ0NzEDVsrHk28NNOf+H5/X/KSy49fjx9Pr9ZC7k+WS56uyEwH0/viQ6n0empslWnD2B5nd6/JY5aT29dy8Ucd/uwDH90uueTVN5PUXz5o83w2l3zWEaWPkuWSWVG3kHJpl+stM7fetW74wEgzdKv50BP0uOEsghnj+NbiZaT3H+uBz+aSa0eF9Do6yegS78ewQd2QdwSLexTULUldWvJ6d85d5ssOW0fn5o7JJY/J5OvL9GJtZ/mnsdPLvT2dS562tMl/4Pvi6WW8wpLem+w8r8jM29rYUCedabn4o45ur3x4h0XJqUi7xt7U07nkk44oppsUNJtu1owi20eaIU0SnePQZ8fz6lv8RdBFh30tHT+f3ur5LarNgD45KuSTDP+jDVcw7vzJIe8IJkIUGLZGzw9bh3a2/sxfn0vOH/+wUfLzueR4hL8rnu85cRMYdpBej+WDPhXdvlaKP8jNgQJRcuj5XPI5R5T+lOSSWVG3kHJpl+stc5/pZv5EbZdLr+PBYOh08XUM09GakWSudknqyVEhX3O4Uhdc4d0YNjVU3/KQdwiLexTUPXd5aclL3f3qyw9bRz/BelAu+e4B6r9fX4S/iJ18vlxyOMLfFf8jvVzIMaV3x53fL9pOjes5Q1tcK/6Yo9srH94uUXJuyQsd5SIVadfYm3ryN66vTjiimG5SULc0mzrCWsGaqeT2kSa9WvjEbP64Pjsdu3h6fSu/++A9uHaR+8lRIb1cOFKugHHnd2PYjaE+xt2tFX8V6QIKDFuD/O6DPebwztaf+wG55BwlXz//79cXa1Fy+iZz/iuW99YilzxpOsM88K746qeDt+8XbW8MDXu4fa0Wf4ibAwW7RMm5Ja+sRVYUOVKLXPIZR5T+jOSSWVG3kJKa9trdqaLI9pGm1CVyl8vvz7rgraHPpdc3hjfXJsMrGuSSJyexNCqsxdid+c5XqyS/uTjkHcLiHgXNouSKIkOnOuWwdXTUcVQu+TbKvmRuO5cXsVTi4eNt1CSXPL47/Ee+K55eLbWAWeCwfv+ZrfIWblcPeDQE4svoG1zzKPluHTRSs+J6oAbfS+6dbkQx3aSgnySVm0hF/08l1htvudDtkQpPb8y65N3Lmbz3aH/prYe7X+1087lRYe0KeuntcefPDXmHqGuTfGF1c2XDVtnhT7D2J39ALvk2N1x+nPrFP3HdKJc8H+HviqdXS61n1oMKC0DDmk26fZXWi7Y7elWHD2+XXHKpp3RS1/qorbNNLvl8I0p8eWvSAAA0aklEQVQfJcsls6JuIWV9/OjlxrveC1Oh6pHm+mLluLc9NJ/m4v7zWf6RXk/kzz48xjXJJRdHhdJ/ifT2uPPnhrxDWNyjoG6ubNgqOzrqOCyXnKLkf7++ur5Y2duro+RGueTpCH9p5LfF8xrs0npObnnpZTmVM67yXhpVqfh2omQK9omSyzeT25vAh9Mol3y6EcV0k4LKm86lYa41zVLnuNo60lxfrBz2dofl3acC8x0OfbFmGAn1NVnT2Z4bFUojcXp/3PntGDaX3w+HvGOYCFFQmQG9NOW18cOw9eiUspn+7A/MJaevIl9frHwx+cU/3tUsl3w/wt8WL64SpffTq/EDi207F7h2hmLxzQ5/9oGPbt8oebGrlIf9Y7XKJZ9tROnPXy6ZFZULKZeGuXZ7Ks/0ehtHmmKPu9th6q8rN9FrgaBE7uqPd75GueTCqFC6xFQh485vx7BALhANecewuEfBtsW95ZKGraOXpI7OJae4uPgj19f3X/a15Ha55OkI//2+eHGVKL2fXs0WbQPDwk3frMrFt7KESsE+UXKxq9TdS47T5Deur041ophuUlB500k9Ybnk9f1S29040hSLDxPSa4niWS6WGDpiev2A2tt3uZsPJ9Pv76546RJTBY47vx3DIrlEMOQdo69JwxYrDFsXw0iRXj/g8KijP/0jcsm3ny+lim9/EvsF2uWSJ8uu337cFS8u6KT306vxAys9Jh+hb1cVxTc6vL3y0e0TJRfvFeWOeKx2ueRzjSj93uWSWVG5kFJaJ7uL5RaVim3scXcl0qcfmG5eN69NbIua5ZJXR4XSJT4QJecjdO6HvGNY3KOg8rlLw1bR0U+wHv0b1/nzdy/v5Sj6VV9LbplLHhdTupZyVzy9WmrZ+ZPpZV2PyYfoGlZtB6t3dHvlw+sb3A5Rculmkt7+sI2z2feSO2caUUw3KajN211a5nLbzCNIqRNuG2nKPSKXuEnKrHTvVOJ+JMun9cwIV7vI/dyoUKrA9Mlx5+U6Gc6ocz/kHUK6gILaJnJpy4atFYd3tv4CDsgl34e9tw9gz1zffd3Xklvmkm8WQu+Kp1dLTTV/ML0cNyy37U4+xni01eKbuDlQsFMuubD4mT/drqk31jCXfKoRpY+S5ZJZUbuQkhrn0v3p+u56x+ptHGnuXs7dDmyFYa6TCtztcAgTa1baljTMJa+MCqVLTMXHnefPp5eh5SHvEBb3KKidK6fmbNhadHTUcVQuOUXFQ9ib/8bkOFmcH7h+2deSm+aSbxZCk/RGoYPMmmZ5BaiXz2mwXnyLR0MgvoydouQ8Ci/0lY8wc1rVMpd8phHFdJOC2klSbtzxPLGupfdSwcqRptDj7vtcPo3loSAVuDvPfNinel5fkzWd7blRoXSJ6e1x5/dVGsp7HaU3DiFdQEHtRMiwVXL4E6z9FeyTS/61EnznsHfMHc82TL38geu2ueSbhdCrtL3w6fTu+HbVGu+42+ypJnrDzYGCvaLk9ZtJevPjts2mueQTjSj9nuWSWVG9kHJpmkuDwPr4MbVtpCn21/R+6jLFDhePg0OMmF4/pmkueXFUyJ8O/urUXr7AcefFKrxYGvIOYXGPguq58qUxG7aWHR117JdL/sdaUJt+03ry8fvk8tQ8pt5d21zyfCE0bZ7fMKbmTSxvWWyryd3tq1S8niiZgr2i5NW2nxv8M8/17Kvhb1xfnGVEMd2koPqms9Z1ckOv2NG2kWa9x43v5w+kl4v9O719d55p65MDXG1NPjkqpJcLl5g/NO587b/bxDB6JWnzIfqaNGyxojoDatgqeHRK2Ux/CXvkkvuo9x/pzzM5NzyJifOmKBLOEfTrUsmtc8mzhdC0daFtJbmhjjuvXOMdT+uqWLza4c8+8NHtFSUPI26wVrrhXnKUxrnk04wo/X7lkllRvZCSm3fU+HP7rZmvpaKVI03astRh07vD2/kkF7pQ/PbalW3QOJe8NCrks13Nak12/uSQdwSLexRUL+4ZtgqOzs3tlUv+x+XdheRvzg3fvL8cCg/F0+tXaJ1LHtvpVdo4fDy6n4yfSBvGTcW71+3tq1y81tHtlQ+vb3C7RMl5jhS0v9za2zX05tp+L7l3jhHFdJOC+rzdcuMfmn56vWrbSJM3xffF2QeGMwljyPg8h63P5WSqb99Pjgr54+Ghhk+MO8+b0stlQz1cpI2HMBGioL6J5PZv2Iod3tn6a2ifS84hb5hNHqLem7A3yC8nafsrU8ntc8l3C6Fp2xAaRJ/Pu568mfdRvntNPl1VvJKbAwW75ZKH5c1Zc260ZLmr5rnkk4wofZQsl8yK+oWU5caftlf1wK0jTdoWDj/DGY0HDjaN0lt3+8pd79lu1zyXvDAqpNfR58dAd3zzySHvCBb3KKh/7tKwte7oJ1j3ySWPcXCQTV56M0fW9x9Z2r6r9rnk6f1hUjy9DhrB5PaTtoy7qGl2k88/20pHnrimYL8oeZgi3Y3TrZYsd9U+l3yOEcV0k4INS7O5id4XX9q+YNtIM/SL+d6HqeWkw4yR3mw4+DHsKm24Gg6bXj+sr8mazvbsqLA8o54MWePO8y7SyzWTzz9dG8+orUm+LMNW2thk2Kqsgn30F7FfLvnbt3/cZ4Dz3/k0C3vD57D/7dewq1emkvfIJU/a3qT4sG2pg/TSprGl1ty9hulyZfEqh7dXPrr9ouSxT9zcBRa70IeyQy75FCNKf1ZyyazYsJAyTOVuyo+zuPky1dvbW/BbzNtGmrR1rculDRdjr12azd71r7SxavhYtUMuOR4V0oaVK5yWztWUXq6KhrwDWNyjYMNc2bC16uioY6fvJY/54m/f/j4Nb/9jjJ9nYe/41vjOuKPlX9Pewx655Lj1Ddvep41p7CC9tHFsj1V3r6Hr1RWv8mgIxJexY5Q8tujJmNnPV67Sho+p9W9cX33+EcV0k4Itk6SxlY+Nf2kW17uOHrN53LaRZix9c4RJQHfb8ceTnHbRSQ+9vdq8n+cnirU1+fSosDBSTGpk+k6+8PRy3VhLacMhpAso2DIRMmyt6Wvy0M7WX8YOv3E9DZO7MPwa9v4t/wVQF/Pc8Bgm/77ExL+G7yq/+HnrnXLJk3aWXncmTfU9t9UfqYHNdp4Lz7tNZNh1XfEabg4U7Bgl34zrl4H6bRyiq0LQ4+ySSz7BiNKfkVwyKzYtpIwDwrXx55bfm9+5cumV+WbNSDMp/e3P62Gnx511l8m+0u5/TPd/2/eH2fLzA1xtTT4/Kkyu5nqBnXSJ+a2xdN6SXhYMu06vD7GpTfIVbZorj/3FsDVzdNSx29+XfBsmB+ZB8rDTSFR8R/vkksPi02b27b2T/tj3l/SHVHJseffNd8HG4hVEyRT0DW6vKPk2GXHrgzfLPb6X3PvsI4rpJgX9Tae+iVzaZ2zW/YbhZN6et400N11uZvaB6fQ0cHueed8N+lzt7fv5UeH2Ct/f/xxrKL81ls7vpZclG4vvwkSIgm0Z0EuLjn35YevRxEsz/XXs8fcll8LkMOpd/syLg+S9cslD+fTqYqmpvg9NPhUcm2lty0vlGzTU5PBnH/jo9swlr4zrH71V7pRL/vQjSh8lyyWzYttCyvJUbt77xo6SNkxsG2lWZqfRB74v7r1ze545BK0eEFbsk0sOR4XF/wzfc0Awls6VkV4WpfLp1SEs7lGwbSHFsLXs6CWp3XLJ62Hy74Wod+kzrw6Sd8sl5w+kF1dx0+uaxWxOuzmVc/1AuzmtJVQK9o2Sl+4CH75R7pVL/uwjiukmBRtvOsP87E7Q+cZ+kjZMbRtplme5cV9Z2Hu3/7vzTJurxo6SviZrOluLUWHhP0N3GelPY+lcF+ll2fUD6cUhamuSL8uw1Ws1bG2oyfb6C9kll9yZfK341kpsPfl1r8GLv5Pc2y2XnD6R/pxEKzp9q5jNaXObrr57XT9RX7zk8PbKR7dzlByP6y3G4n3tlkv+5CNKf/JyyazYvJCSu9BUeNcaukn47saRJjpqZ+kD4d7nZ5LTN03uunvlksNRIUw89SNg+uNYOhdMLytcPpH+fAiLexRsfu4y6i+Grc7RT7DumEvuTH9+a7Qe9M4/sn6MfeyXS75+JP0xm99QLreQ2Zx28xrv9SMbihcc3V758PaOku9+rbl3v475Ee3zG9dXn3lEMd2kYPvS7DCNHMQNdsjfLLy9baSJwsK1jjI/y3D/12JNhrjammw0Kswu8Hp56cVYus2Q91LSBRQYtjovHbZ201/JXrnkzixOvv569arbj/x8+dPWvR1zyZfPpD+Nbn4r7tvbtXHl9nh50du+xnv5zJbi69wcKNg9Sr4f14cfcv7Qdswlf+oRpT9LuWRWPLKQcjuVS61/LjX/xVvaxpHmfsJZKn97louT2W6vbTrcfrnkeFT4fnOBufrSy7F0rrX0skr3mfSnQ1jco+CRubJhK3J01PFwLrner58/r49R//79szIt3H3i8pHfx4TInepc8kPewwH+Lf0Y7WLfeNCPRm2192gIxJfRN+Hdm8j3t2sQ+P45QuRO9feSH/J5RxTTTQr6SdL2JtKNENchYrX193/zyeoYsnWkmRy2Zk1ssvuV0/zeaI6463QzHhW+p9W65gN1POS9ymNtki/ksbmyYWvu8CdY+0t9JJd8ctW55Id8f+0A3/AGdfSqDh+ehZRQdS75IZ93ROmjZLlkVlhIaWXfmmweCK968ZB3R5ukwFy5laNr8gW55E9p31zyX3abLcfaHU7Pp0CUHNo3l/x5RxTTTQrcdFrpa3LHzvbaQejFQ94tbZKCwzOgp3H4lLI7vlzy3L655M9Lz6dAlBzaN5f8efUPbskls8JCSitqshU1SYGFlF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average ignoring NaN values","description":"Given a matrix, calculate the block average of each disjoint sub-matrix while ignoring *NaN* values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\r\n\r\n* Input: matrix *A* and the size of each sub-matrix *subsz*\r\n* Output: *B = blknanavg(A,subsz)*\r\n    \r\n\r\nExample:\r\n\r\n    A = [1 2 3 4 5 6 7 8 NaN];\r\n    subsz = [1  3];\r\n    B = [2  5  (7+8)/2];\r\n\r\nHint: this is related to \u003chttp://www.mathworks.com/matlabcentral/cody/problems/42856-block-average Problem 42856. Block average\u003e.","description_html":"\u003cp\u003eGiven a matrix, calculate the block average of each disjoint sub-matrix while ignoring \u003cb\u003eNaN\u003c/b\u003e values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\u003c/p\u003e\u003cul\u003e\u003cli\u003eInput: matrix \u003cb\u003eA\u003c/b\u003e and the size of each sub-matrix \u003cb\u003esubsz\u003c/b\u003e\u003c/li\u003e\u003cli\u003eOutput: \u003cb\u003eB = blknanavg(A,subsz)\u003c/b\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e    A = [1 2 3 4 5 6 7 8 NaN];\r\n    subsz = [1  3];\r\n    B = [2  5  (7+8)/2];\u003c/pre\u003e\u003cp\u003eHint: this is related to \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/42856-block-average\"\u003eProblem 42856. Block average\u003c/a\u003e.\u003c/p\u003e","function_template":"function B = blknanavg(A)\r\n  B = A;\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8 NaN];\r\nsubsz = [1  3];\r\nB = [2  5  (7+8)/2];\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = [1 2 3 4 NaN 6 7 NaN 9].';\r\nsubsz = [3,1];\r\nB = [2 5 8].';\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = [1       1     1       2     NaN       2\r\n     1     NaN     1     NaN       2     NaN\r\n     3       3     3     NaN     NaN     4\r\n     3       3     3     NaN       4     4];\r\nsubsz = [2   3];\r\nB = [1    2\r\n     3    4];\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nA = rand(100,300);\r\nA(randperm(numel(A),10)) = NaN;\r\nsubsz = size(A);\r\nB = mean(A(:),'omitnan');\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)\r\n\r\n%%\r\nsubsz = [4,6];\r\nB = 10*rand(10,20);\r\nA = repelem(B,subsz(1),subsz(2));\r\nA(randperm(numel(A),10)) = NaN;\r\nassert(norm(B-blknanavg(A,subsz)) \u003c 1e-10)","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12569,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":24,"created_at":"2016-05-21T19:53:06.000Z","updated_at":"2026-04-06T19:37:34.000Z","published_at":"2016-05-21T20:04:51.000Z","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, calculate the block average of each disjoint sub-matrix while ignoring\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\u003eNaN\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e values. Assume that the size of the matrix along each dimension is an integer multiple of the size of the sub-matrix along the same dimension.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInput: matrix\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\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and the size of each sub-matrix\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\u003esubsz\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput:\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\u003eB = blknanavg(A,subsz)\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:\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 5 6 7 8 NaN];\\n    subsz = [1  3];\\n    B = [2  5  (7+8)/2];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: this is related to\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/matlabcentral/cody/problems/42856-block-average\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 42856. Block average\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":690,"title":"Remove the two elements next to NaN value","description":"The aim is to *remove the two elements next to NaN values* inside a vector.\r\n\r\nFor example:\r\n\r\n x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]\r\n\r\nThe output y will be:\r\n\r\n y = [6 10 5 8 9 7 3 21 43 7 8]\r\n\r\nNan values and the 2 next elements after the NaN (23-9  and 4-6) have been removed.\r\n\r\nThere will be always NaN values in the input vector followed by at least 2 integers.","description_html":"\u003cp\u003eThe aim is to \u003cb\u003eremove the two elements next to NaN values\u003c/b\u003e inside a vector.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre\u003e x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]\u003c/pre\u003e\u003cp\u003eThe output y will be:\u003c/p\u003e\u003cpre\u003e y = [6 10 5 8 9 7 3 21 43 7 8]\u003c/pre\u003e\u003cp\u003eNan values and the 2 next elements after the NaN (23-9  and 4-6) have been removed.\u003c/p\u003e\u003cp\u003eThere will be always NaN values in the input vector followed by at least 2 integers.\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8];\r\ny_correct = [6 10 5 8 9 7 3 21 43 7 8];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [25 NaN 1 3];\r\ny_correct = 25;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [ NaN 15 15 17 ]\r\ny_correct = 17;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":9,"comments_count":7,"created_by":639,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":703,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":12,"created_at":"2012-05-15T09:33:34.000Z","updated_at":"2026-02-10T12:07:16.000Z","published_at":"2012-05-15T09:33:34.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe aim is to\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\u003eremove the two elements next to NaN values\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e inside a vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ x = [6 10 5 8 9 NaN 23 9 7 3 21 43 NaN 4 6 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe output y will be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ y = [6 10 5 8 9 7 3 21 43 7 8]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNan values and the 2 next elements after the NaN (23-9 and 4-6) have been removed.\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 will be always NaN values in the input vector followed by at least 2 integers.\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":44430,"title":"remove every row\u0026col for every nan","description":"for a given matrix, remove the row and column of every nan. Example\r\n\r\n  x=[1     2   NaN\r\n     4     5     6\r\n     7     8     9]\r\n\r\n  y= [4     5\r\n      7     8]","description_html":"\u003cp\u003efor a given matrix, remove the row and column of every nan. Example\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex=[1     2   NaN\r\n   4     5     6\r\n   7     8     9]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003ey= [4     5\r\n    7     8]\r\n\u003c/pre\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%test 1\r\nx = [1 2 3 nan];\r\ny_correct =[]\r\nassert(isequal(isempty(your_fcn_name(x)),isempty(y_correct)))\r\n%%test 2\r\nx = [nan nan 5;8 nan 2];\r\ny_correct = []\r\nassert(isequal(isempty(your_fcn_name(x)),isempty(y_correct)))\r\n%%test 3\r\nx = [nan nan 5;1 2 3;7 8 9];\r\ny_correct = [3;9]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%test 3\r\nx = [1 2 3;1 2 3;7 8 9];\r\ny_correct = [1 2 3;1 2 3;7 8 9]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%test 3\r\nx = [1 2 nan;nan 2 3;7 8 9];\r\ny_correct = 8\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":156466,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":302,"test_suite_updated_at":"2017-12-03T12:45:32.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-02T15:49:05.000Z","updated_at":"2026-04-02T18:04:09.000Z","published_at":"2017-12-02T15:49:05.000Z","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\u003efor a given matrix, remove the row and column of every nan. Example\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[x=[1     2   NaN\\n   4     5     6\\n   7     8     9]\\n\\ny= [4     5\\n    7     8]]]\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":2803,"title":"Split up vector or matrix delimited by NaNs","description":"Given several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\r\nGiven several matrices combined in one matrix delimited by all-NaN rows , return each matrix as an element of a cell vector.","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: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 46.5px; transform-origin: 407px 46.5px; 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: 383px 8px; transform-origin: 383px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 210.5px 8px; transform-origin: 210.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven several matrices combined in one matrix delimited by all-NaN\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: 14.5px 8px; transform-origin: 14.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003erows\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: 138px 8px; transform-origin: 138px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e , return each matrix as an element of a cell vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function c = split_nan_delimited(x)\r\n  c = x;\r\nend","test_suite":"%%\r\nx = 7;\r\nc_correct = {7};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = nan;\r\nassert(isempty(split_nan_delimited(x)) \u0026\u0026 iscell(split_nan_delimited(x)))\r\n\r\n%%\r\nx = [nan; 7; 0; nan];\r\nc_correct = {[7; 0]};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = rand(66,1);\r\nc_correct = {x};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = (1:20);\r\nc_correct = {x};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [1 76 -inf 0 3 nan 16 7 2 1 0 0 inf 13]';\r\nc_correct = {x(1:5) x(7:end)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [2 nan 3 nan 5 nan 7 nan 11 nan 13 nan 17];\r\nc_correct = {x(1) x(3) x(5) x(7) x(9) x(11) x(13)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = (1:34)';\r\nx([6:7 19:21 30]) = nan;\r\nc_correct = {x(1:5) x(8:18) x(22:29) x(31:end)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = 10*rand(55,6)-5;\r\nx([1:2 6 13:15 40],:) = nan; \r\nc_correct = {x(3:5,:) x(7:12,:) x(16:39,:) x(41:end,:)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = [nan(4); magic(4); nan(1,4); inf(4); ones(4)];\r\nc_correct = {magic(4) [inf(4); ones(4)]};\r\nassert(isequal(split_nan_delimited(x), c_correct ))\r\n\r\n%%\r\nx = nan(6);\r\nc_correct = {};\r\nassert(isempty(split_nan_delimited(x)) \u0026\u0026 iscell(split_nan_delimited(x)))\r\n\r\n%%\r\nx = [nan(4); ones(1,4)];\r\nc_correct = {ones(1,4)};\r\nassert(isequal(split_nan_delimited(x), c_correct ))","published":true,"deleted":false,"likes_count":1,"comments_count":5,"created_by":10139,"edited_by":223089,"edited_at":"2022-09-24T10:12:37.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2022-09-24T10:12:37.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-12-29T20:31:28.000Z","updated_at":"2025-03-02T14:20:21.000Z","published_at":"2014-12-29T21:07:56.000Z","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\u003eGiven several vectors contained within one vector delimited by NaNs, return each individual vector as an element of a cell vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven several matrices combined in one matrix delimited by all-NaN\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\u003erows\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e , return each matrix as an element of a cell vector.\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":2010,"title":"Wrap a vector, but insert NaN's at the wrap-positions.","description":"When you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\r\nThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\r\nThe modulo of the wrapping range is explicitly entered into the function.\r\nFor example, if we wrap a vector [1:20] at 3, this will result in [1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2].\r\nAs (almost) always, regexp and eval are not appreciated.","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: 184px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 92px; transform-origin: 407px 92px; 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: 363px 8px; transform-origin: 363px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhen you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\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: 291px 8px; transform-origin: 291px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\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: 224.5px 8px; transform-origin: 224.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe modulo of the wrapping range is explicitly entered into the function.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 43px; 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 21.5px; text-align: left; transform-origin: 384px 21.5px; 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: 101.5px 8px; transform-origin: 101.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, if we wrap a vector\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: 24px 8px; transform-origin: 24px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 24px 8.5px; transform-origin: 24px 8.5px; \"\u003e[1:20]\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: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e at\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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e3\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: 53px 8px; transform-origin: 53px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, this will result in\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: 180px 8px; transform-origin: 180px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 180px 8.5px; transform-origin: 180px 8.5px; \"\u003e[1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 179px 8px; transform-origin: 179px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAs (almost) always, regexp and eval are not appreciated.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = wrapnan(x,m)\r\n  y = mod(x,m);\r\nend","test_suite":"%%\r\nx = 1:20;\r\nm = 3;\r\ny = wrapnan(x,m);\r\ny_correct = [1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2];\r\nassert(isequaln(y,y_correct))\r\nfiletext = fileread('wrapnan.m');\r\nassert(isempty(strfind(filetext, 'regexp')),'regexp* command is forbidden');\r\nassert(isempty(strfind(filetext, 'eval')),'eval* command is forbidden');\r\nassert(isempty(strfind(filetext, 'inline')),'inline command is forbidden');\r\n\r\n%%\r\nx = [1 50 95 105 195 205 190 310 290 250 201 10];\r\nm = 100;\r\ny = wrapnan(x,m);\r\ny_correct = [1 50 95 nan 5 95 nan 5 nan 90 nan 10 nan 90 50 1 nan 10];\r\nassert(isequaln(y,y_correct))\r\n\r\n%%\r\nx = [0.25 0.45 0.80 0.90 1.25 0.60 0.10 0.20 1.70 1.60 1.50 1.80 1.40 0.10];\r\nm = 0.5;\r\ny = wrapnan(x,m);\r\ny_correct = [0.25 0.45  NaN 0.30 0.40  NaN 0.25  NaN 0.10  NaN 0.10 0.20  NaN 0.20 0.10 0.00 0.30  NaN 0.40  NaN 0.10];\r\nassert(isequaln(round(y,2),round(y_correct,2)))","published":true,"deleted":false,"likes_count":1,"comments_count":7,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":21,"test_suite_updated_at":"2021-06-26T18:48:50.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-20T23:54:45.000Z","updated_at":"2026-01-20T15:42:31.000Z","published_at":"2013-11-21T00:10:43.000Z","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\u003eWhen you plot a line that wraps, and do not want the sawtooth shape to show up in the plot, you can either draw all separate lines, or you can insert NaN's between the segments. The plot command does not draw a line between NaN's.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis assignment is to create a function that wraps a vector, and inserts NaN's where it wraps.\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 modulo of the wrapping range is explicitly entered into the 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:r\u003e\u003cw:t\u003eFor example, if we wrap a vector\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1:20]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e at\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e3\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, this will result in\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2 nan 0 1 2]\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAs (almost) always, regexp and eval are not appreciated.\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":42672,"title":"Longest Sequence of NaNs","description":"In an array return the length of longest sequence of nans for each column. \r\n\r\n x = \r\n [ 2   3   1   2   5   6;\r\n  nan nan  5  nan  6  -9;\r\n   5  nan  8  nan  6   5;\r\n   8  nan  7   -5 5.8  5;\r\n  nan  0   0  nan  5   7;\r\n  nan  5   9  nan  7  nan;\r\n  nan nan 10   0  nan  6;\r\n  nan nan  0   1  nan  9];\r\n\r\n y_correct = \r\n [ 4   3   0   2   2   1];\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: 271px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 343px 135.5px; transform-origin: 343px 135.5px; 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: 320px 10.5px; text-align: left; transform-origin: 320px 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=\"\"\u003eIn an array return the length of longest sequence of nans for each column.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 240px; border-bottom-left-radius: 4px; border-bottom-right-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: 340px 120px; transform-origin: 340px 120px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e x = \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e     [ 2   3   1   2   5   6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan  5  nan  6  -9;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e       5  nan  8  nan  6   5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e       8  nan  7   -5 5.8  5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan  0   0  nan  5   7;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan  5   9  nan  7  nan;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan 10   0  nan  6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e      nan nan  0   1  nan  9]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e y_correct = \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-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-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: 340px 10px; transform-origin: 340px 10px; 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; \"\u003e     [ 4   3   0   2   2   1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = longnan(x)\r\n  y = x;\r\nend","test_suite":"%%\r\n x = [ 2   3   1   2   5   6;\r\n nan nan  5  nan  6  -9;\r\n 5  nan  8  nan  6   5;\r\n 8  nan  7   -5 5.8  5;\r\n nan  0   0  nan  5   7;\r\n nan  5   9  nan  7  nan;\r\n nan nan 10   0  nan  6;\r\n nan nan  0   1  nan  9];\r\n\r\n y_correct = [ 4   3   0   2   2   1];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n%%\r\nx = eye(3);\r\ny_correct = [0 0 0];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = eye(3);\r\nx(1,1) = nan;\r\ny_correct = [1 0 0];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = [30\t39\tNaN\t1\t10\tNaN\t28\r\n38\t47\tNaN\t9\t18\t27\tNaN\r\n46\tNaN\tNaN\t17\tNaN\tNaN\t37\r\n5\tNaN\tNaN\t25\tNaN\t36\tNaN\r\n13\t15\tNaN\t33\tNaN\tNaN\tNaN\r\n21\tNaN\t32\t41\t43\t3\tNaN\r\n22\t31\tNaN\t49\t2\tNaN\tNaN];\r\ny_correct = [0 2 5 0 3 1 4];\r\nassert(isequal(longnan(x),y_correct));\r\n\r\n\r\n%%\r\nx = nan(10);\r\ny_correct = repmat(10,1,10);\r\nassert(isequal(longnan(x),y_correct));","published":true,"deleted":false,"likes_count":1,"comments_count":4,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":73,"test_suite_updated_at":"2015-10-24T10:53:06.000Z","rescore_all_solutions":false,"group_id":39,"created_at":"2015-10-24T06:43:30.000Z","updated_at":"2026-04-02T08:04:49.000Z","published_at":"2015-10-24T06:43:30.000Z","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\u003eIn an array return the length of longest sequence of nans for each column.\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 = \\n     [ 2   3   1   2   5   6;\\n      nan nan  5  nan  6  -9;\\n       5  nan  8  nan  6   5;\\n       8  nan  7   -5 5.8  5;\\n      nan  0   0  nan  5   7;\\n      nan  5   9  nan  7  nan;\\n      nan nan 10   0  nan  6;\\n      nan nan  0   1  nan  9]\\n\\n y_correct = \\n     [ 4   3   0   2   2   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":58339,"title":"Remove runs of at least n consecutive NaNs","description":"This problem is inspired by Dyuman Joshi's problem 58329. Given a row vector x and a natural number n, remove all runs of at least n consecutive NaNs from x, leaving all shorter runs as well as all non-NaN elements intact.\r\n\r\nFor instance, given\r\n\r\nx = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]\r\n\r\nthe results would be as follows:\r\n\r\n\u003e\u003e removenans1n(x, 1)\r\nans =\r\n     1     2     3     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 2)\r\nans =\r\n     1   NaN     2     3     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 3)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\r\n\u003e\u003e removenans1n(x, 4)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\r\n\u003e\u003e removenans1n(x, 5)\r\nans =\r\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN\r\n\r\nwith no changes in output for even higher n (since x only contains runs of NaNs up to length four).\r\n\r\nTo make this challenging, provide a vectorized solution: no loops, no arrayfun (in fact, no fun at all, though you're still allowed to have fun), and no recursion. Regular expressions are also outlawed (I don't think that this is a problem that is naturally solved using regular expressions, so I don't feel too bad about doing so). \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: 765.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 490px 382.833px; transform-origin: 490.005px 382.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 43.3333px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 21.6667px; text-align: left; transform-origin: 384.5px 21.6667px; 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 inspired by Dyuman Joshi's \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/58329\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eproblem 58329\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. Given a row vector \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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 and a natural number \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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, remove all runs of at least \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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 consecutive NaNs from \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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, leaving all shorter runs as well as all non-NaN elements intact.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor instance, given\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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-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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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; 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; \"\u003ex = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]\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: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ethe results would be as follows:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 306.562px; 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: 487px 153.281px; transform-origin: 487.005px 153.281px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1     2     3     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 3)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 4)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e\u0026gt;\u0026gt; removenans1n(x, 5)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003eans =\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; 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: 487px 10.2188px; transform-origin: 487.005px 10.2188px; 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; \"\u003e     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN\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: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.8333px; text-align: left; transform-origin: 384.5px 10.8333px; 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=\"\"\u003ewith no changes in output for even higher \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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 (since \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\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 only contains runs of NaNs up to length four).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63.6667px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 31.8333px; text-align: left; transform-origin: 384.5px 31.8333px; 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 make this challenging, \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; \"\u003eprovide a vectorized solution:\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 no loops, no \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003earrayfun\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 (in fact, no \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-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efun\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 at all, though you're still allowed to have fun), and no recursion. Regular expressions are also outlawed (I don't think that this is a problem that is naturally solved using regular expressions, so I don't feel too bad about doing so). \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = removenans1n(x, n)\r\n\r\nend\r\n","test_suite":"%%\r\nfiletext = fileread('removenans1n.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') || ...\r\n          contains(filetext, 'while') || contains(filetext, 'for') || ...\r\n          contains(filetext, 'cellfun') || contains(filetext, 'arrayfun') || ...\r\n          contains(filetext, 'rowfun') || contains(filetext, 'structfun') || ...\r\n          contains(filetext, 'varfun'); \r\nassert(~illegal)\r\n\r\nrecursion = contains(filetext(find(filetext == char(13)) + 1:end), \"removenans1n\");\r\nassert(~recursion)\r\n\r\n%%\r\nx = [NaN NaN 1 NaN 2 NaN NaN 3 NaN NaN NaN NaN NaN NaN 7 NaN NaN NaN -2 NaN NaN NaN];\r\nassert(isequaln(removenans1n(x, 1), [1 2 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 2), [1 NaN 2 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 3), [NaN NaN 1 NaN 2 NaN NaN 3 7 -2]))\r\nassert(isequaln(removenans1n(x, 4), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nassert(isequaln(removenans1n(x, 5), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nassert(isequaln(removenans1n(x, 6), [NaN NaN 1 NaN 2 NaN NaN 3 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nfor i = 7:255\r\n    assert(isequaln(removenans1n(x, i), [NaN NaN 1 NaN 2 NaN NaN 3 NaN NaN NaN NaN NaN NaN 7 NaN NaN NaN -2 NaN NaN NaN]))\r\nend\r\n\r\n%%\r\nx = [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17 NaN NaN NaN NaN];\r\nassert(isequaln(removenans1n(x, 1), [3 56 1 1 438 1 2 6 5 1 38 2 3 4 17]))\r\nassert(isequaln(removenans1n(x, 2), [3 56 1 1 438 NaN 1 2 NaN 6 5 1 38 2 3 4 NaN 17]))\r\nassert(isequaln(removenans1n(x, 3), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 5 1 38 2 3 4 NaN 17]))\r\nassert(isequaln(removenans1n(x, 4), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17]))\r\nfor i = 5:255\r\n    assert(isequaln(removenans1n(x, i), [3 56 NaN NaN 1 1 438 NaN 1 2 NaN 6 NaN NaN NaN 5 NaN NaN NaN 1 38 2 3 4 NaN 17 NaN NaN NaN NaN]))\r\nend\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":332395,"edited_by":332395,"edited_at":"2023-05-19T16:49:43.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-05-19T16:33:16.000Z","updated_at":"2025-09-19T01:20:54.000Z","published_at":"2023-05-19T16:33:16.000Z","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 inspired by Dyuman Joshi's \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/58329\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eproblem 58329\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Given a row vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and a natural number \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, remove all runs of at least \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e consecutive NaNs from \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, leaving all shorter runs as well as all non-NaN elements intact.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor instance, given\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[x = [1 NaN 2 3 NaN NaN 4 5 6 NaN NaN NaN 7 8 9 10 NaN NaN NaN NaN]]]\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\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 results would be as follows:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[\u003e\u003e removenans1n(x, 1)\\nans =\\n     1     2     3     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 2)\\nans =\\n     1   NaN     2     3     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 3)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6     7     8     9    10\\n\u003e\u003e removenans1n(x, 4)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10\\n\u003e\u003e removenans1n(x, 5)\\nans =\\n     1   NaN     2     3   NaN   NaN     4     5     6   NaN   NaN   NaN     7     8     9    10   NaN   NaN   NaN   NaN]]\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\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\u003ewith no changes in output for even higher \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts 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