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Hello World! 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(Derek Smith, 17Jan 10:51 AM)":"\"be5314b7cb886378ca61152127667433\"","1.01 Hello World! (Dylan Pagillo, 16Jan 11:30 PM)":"\"00f8f5673ceb6ef1f39d32e244d306ed\"","1.01 Hello World! (Elizabeth Simonelli, 16Jan 9:55 PM)":"\"9e813dd45f3a95b8a84ebd9b26c84553\"","1.01 Hello World! (Eric Brown, 18Jan 10:22 AM)":"\"09cec77c14297b0944f7ddca3cf3dd5c\"","1.01 Hello World! (Gladson Natarajan, 17Jan 2:26 PM)":"\"e46bd62b7df7f62aaa3cbe948c0c1a10\"","1.01 Hello World! (Gladson Natarajan, 17Jan 2:29 PM)":"\"0e6863c806c5f50a96650ead40a3b737\"","1.01 Hello World! (James Ward, 18Jan 9:24 AM)":"\"6e99e363cc28c78084b590d25a97188c\"","1.01 Hello World! (Jared Duquette, 17Jan 12:03 PM)":"\"aa12a306200cf8b2cc1eee8a9f5ece02\"","1.01 Hello World! (Jared Duquette, 21Jan 9:48 PM)":"\"f1b2e4adc86a033c9afc71589a8c20ab\"","1.01 Hello World! (Jillian Christiano, 17Jan 4:27 PM)":"\"be375740a4625e94d25c03087c3aacca\"","1.01 Hello World! 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(Michael, 18Jan 10:21 AM)":"\"7d3600c1666668c20a4236f02b1edd50\"","1.01 Hello World! (Mickey, 17Jan 8:33 PM)":"\"9a00fb6053ccc6bb2945de95513cccba\"","1.01 Hello World! (Nell Evangeline, 18Jan 10:03 AM)":"\"7a38d35e7b04c88321b076af9db187c0\"","1.01 Hello World! (Orinthea Sommersell, 17Jan 5:58 PM)":"\"d29424ac310728c3339173e779200875\"","1.01 Hello World! (PattyV, 27Jan 10:27 AM)":"\"0bc3875c2b1c18785b5c380d600d0223\"","1.01 Hello World! (Ray Buckley, 18Jan 10:10 AM)":"\"6aa3f67d32ac13e081de769f55e89b43\"","1.01 Hello World! (Ryan Maher, 17Jan 11:18 AM)":"\"b498a8d567aad4209adec39864f6a024\"","1.01 Hello World! (SeanH, 16Jan 11:00 PM)":"\"04320bc63c9adcde24b454929b576bfc\"","1.01 Hello World! (Shannon MacColl, 18Jan 8:37 PM)":"\"9987341a2f1367561d74df31202e969b\"","1.01 Hello World! (Sharon Healy, 17Jan 5:54 PM)":"\"649073ca13b0ef20a78797cfc7481cfb\"","1.01 Hello World! (Steve, 17Jan 4:57 PM)":"\"1cba6275f1ba043eba44fc4dc65ab83f\"","1.01 Hello World! 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AM)":"\"d9d1faea84f16b5a5291e8d3e268846d\"","1.02 About Me (Marguerite Fraine, 26Jan 4:51 PM)":"\"e909dbe0378a110ef35485af251ab551\"","1.02 About Me (Marvin Pierre, 22Jan 2:55 AM)":"\"bfb8db18d8991a20c2bedb54b9394d09\"","1.02 About Me (Marvin Pierre, 22Jan 4:10 PM)":"\"5ada6be2d41a5ad907ac0adf4ef80654\"","1.02 About Me (Max Nadel, 22Jan 7:23 PM)":"\"272b720688673b161192072e15605b5b\"","1.02 About Me (Megan, 18Jan 11:42 AM)":"\"46c3c08f5e4749295f81b806945f3149\"","1.02 About Me (Michael, 18Jan 11:51 AM)":"\"bea47b28c0eb0a4dac02901b6137d242\"","1.02 About Me (Mickey, 18Jan 11:43 AM)":"\"3f26bb0a53bef5dd5ea862f6273ad39a\"","1.02 About Me (Nell Evangeline, 28Jan 7:10 PM)":"\"6770b6f4ecddc5f23456891ed8e423bb\"","1.02 About Me (Orinthea Sommersell, 20Jan 12:10 PM)":"\"7d86723fcbdd5bd5de45f10a73b2ee7f\"","1.02 About Me (PattyV, 31Jan 6:51 PM)":"\"0fb68d51c8fe2197de8cd7a133f8d4a6\"","1.02 About Me (Ray Buckley, 18Jan 11:52 AM)":"\"10e843f54767ee8d3d01554ab81c122d\"","1.02 About Me (Ryan Maher, 18Jan 1:32 PM)":"\"b5f2da46ab29765a3240b968cca6cfa1\"","1.02 About Me (SHallenbeck, 22Jan 9:41 PM)":"\"6675b760db7b396b4901cbd5e5ccf5e9\"","1.02 About Me (Shannon MacColl, 19Jan 5:43 PM)":"\"935f9ec999ea2cea874a95087c4e94d1\"","1.02 About Me (Shannon MacColl, 22Jan 8:01 AM)":"\"47d2090e34e6b4d3009f2950fd4a3452\"","1.02 About Me (Sharon Healy, 22Jan 11:12 AM)":"\"86e2bd456d78d01895649b3a6578ad05\"","1.02 About Me (Sharon Healy, 22Jan 6:25 AM)":"\"9c4a969acf9da4b749083a13cb28bf01\"","1.02 About Me (Steve Beckwith, 18Jan 11:42 AM)":"\"c4bca37b83c2dd3a572a6ac4d2339b5d\"","1.02 About Me (Tristan Retzke, 20Jan 11:04 PM)":"\"2c0175cb49f7c0109df27631bb2f2d4d\"","1.02 About Me (Tristan Retzke, 21Jan 6:05 PM)":"\"4ae46e72a0020f920d5ef7b11ed0a751\"","1.02 About Me (Tristan Retzke, 21Jan 6:11 PM)":"\"df8eea1889ea0888f83e259aab3349f6\"","1.02 About Me (Tristan Retzke, 21Jan 6:29 PM)":"\"7c129a4acdf5bc445c21788d2ae045dc\"","1.02 About Me (Tristan Retzke, 21Jan 6:33 PM)":"\"a76ab54aa93a1e2b7d1192afc6a53351\"","1.02 About Me (Tristan Retzke, 21Jan 9:21 PM)":"\"be5e0da99c15732213eb2a26ed22ad6e\"","1.02 About Me (Tristan Retzke, 23Jan 2:21 PM)":"\"8f848a4587a817607189bff41f0c2f3c\"","11th January 2018":"\"a096529b16b4b91bac96058b48b01d5d\"","13th December 2017":"\"a9323198b8e43bd41b39cb19e8042096\"","14th January 2018":"\"8368ae6876bc7b1e32d428b3eecaf6ec\"","15.1":"\"40fa12c4755c7f4fe77ad5a745763aeb\"","15.10":"\"e8f7e004fc8a2722158dc99de0efdfe0\"","15.11":"\"a11df7a2ad7e3d87eb253962f275c0be\"","15.12":"\"24c2c298d98a1f20b3a36ade6106185e\"","15.13":"\"4351cba055f849a9c5409d8ccd84d3d9\"","15.14":"\"9335de8fb204b3d05805ca5ef71409f3\"","15.15":"\"f45ad90f130c8e7c206a2b3c55708026\"","15.16":"\"9dbe082f72d2187e7c167444dbec2139\"","15.17":"\"fc5866676a2bbcdb2f53952ec7d591f9\"","15.18":"\"5edefd87e97b0c6c80208cc70c75ea02\"","15.19":"\"9a50bbbe2d91c1252ea34eb812713c3f\"","15.2":"\"079adc531d76ba1171e6fdf7c53dd83b\"","15.3":"\"7fdd440f8c019288af4ab332d2523ac8\"","15.4":"\"05a536f9b7725f2fbdefd61dfd1fff41\"","15.5":"\"bf7b434776455b2842bc2495c6513e81\"","15.6":"\"11a238a45019e0eaed663eb2b6f65309\"","15.7":"\"3e10960ee32385ba3303faeb6d09e995\"","15.8":"\"110aa5cf2dac95367367e7422bd18b4c\"","15.9":"\"93fda404880825243e0652c49a195a9c\"","18th December 2017":"\"9a2e716a2f24ded878512421e419957e\"","19th December 2017":"\"863c8b5e5a5524fe8849883caa242505\"","2.01 Shapes (Alicia Bower (Flinn, 25Jan 4:03 PM)":"\"66e445a133f81e37ac50fc2d343719d9\"","2.01 Shapes (Amber Goodfriend, 24Jan 1:36 PM)":"\"3026fa9d5f0172890e28d0c03b710d57\"","2.01 Shapes (Andrew Houde, 28Jan 2:55 PM)":"\"ebb2224532e2e48c58bd79d640720762\"","2.01 Shapes (Benjamin Furbeck, 23Jan 12:49 PM)":"\"b727c69abe4b861a15019e437820630e\"","2.01 Shapes (Brandon Helsing, 27Jan 5:35 PM)":"\"6f46af91a1628bc3ab6263da1afbe70d\"","2.01 Shapes (Carson Palmer, 23Jan 11:20 AM)":"\"2f01d73ee9b04696ccaf06c2668005e4\"","2.01 Shapes (Chris Copeland, 23Jan 2:13 PM)":"\"638fe53f7cc75cc72e468c7a569ca80a\"","2.01 Shapes (Derek Smith, 28Jan 2:51 PM)":"\"381d4c36c8edb0ce7c5efa2e29d55242\"","2.01 Shapes (Dylan Pagillo, 28Jan 7:38 PM)":"\"017813120cf56ea0770b354ee0c0a0c1\"","2.01 Shapes (Elizabeth Simonelli, 23Jan 11:40 AM)":"\"272cc2e49d26360f0b7e40b7caeb84cc\"","2.01 Shapes (Eric Brown, 23Jan 11:49 AM)":"\"2ded25e8eafff284226099cd496d4235\"","2.01 Shapes (Gladson natarajan, 24Jan 2:40 PM)":"\"37f8b5f0170f0f9ffddab1fc800e780e\"","2.01 Shapes (Jared Duquette, 28Jan 10:36 PM)":"\"115f722974addb4a42f33c20bc360ba8\"","2.01 Shapes (Jillian Christiano, 23Jan 11:44 AM)":"\"3348a66dbe0f213e13991f6328ffb467\"","2.01 Shapes (Justin Cushing, 28Jan 8:38 PM)":"\"55830a68531300b870020d11b2b5d9b4\"","2.01 Shapes (Karina, 25Jan 11:07 PM)":"\"90e8fddf6056d77d38a4290a00559ec0\"","2.01 Shapes (Malyka, 28Jan 4:39 PM)":"\"fbdf834b98646ea1bac77c0ee69fc28f\"","2.01 Shapes (Marcus Spratley, 24Jan 11:03 PM)":"\"2695865f9110dc905bb8e47b0c818f4b\"","2.01 Shapes (Marguerite Fraine, 29Jan 10:49 PM)":"\"467403385fcd08816bab19ccd535f7d2\"","2.01 Shapes (Marvin Pierre, 28Jan 4:24 AM)":"\"d67fc09b375fb94757316a8febc89667\"","2.01 Shapes (Max Nadel, 28Jan 8:55 PM)":"\"7e94505746a6e65e27078962b47fabdc\"","2.01 Shapes (Megan, 23Jan 11:35 AM)":"\"e1be1c748847cdc67f5cbe744c033156\"","2.01 Shapes (Michael, 23Jan 11:20 AM)":"\"e02ac15a54bb88f85377da3520010dbd\"","2.01 Shapes (Mickey, 23Jan 11:25 AM)":"\"9678bd2ead1beff607b7dd492743ea0c\"","2.01 Shapes (Nell Evangeline Morrissey, 07Feb 10:53 PM)":"\"4d043646d7ac28cffb1dae36dd9511d7\"","2.01 Shapes (Orinthea, 28Jan 3:49 PM)":"\"342289024dd002554635d08ec76adbea\"","2.01 Shapes (PattyV, 11Feb 12:37 PM)":"\"016d5a89deb27cd82bbd6b9bf31cad1f\"","2.01 Shapes (Ray Buckley, 30Jan 10:01 AM)":"\"9bf773fff21dd61df1a61e7c94dc4ae0\"","2.01 Shapes (Ryan Maher, 23Jan 6:06 PM)":"\"f3883a7b725744e66494f2e92db30e33\"","2.01 Shapes (SHallenbeck, 27Jan 10:55 AM)":"\"7732621e73151b1826dffd8e5cfd22cf\"","2.01 Shapes (Shannon MacColl, 24Jan 9:49 PM)":"\"21969603a4578d9bbdcfa4266d2fb794\"","2.01 Shapes (Steve B, 23Jan 11:20 AM)":"\"00342deb7ec73dbd8f945eabff7f2922\"","2.01 Shapes (Tristan Retzke, 23Jan 2:22 PM)":"\"0dc748c8c73739fb47417325158c63dd\"","2.02 Objects (Alicia Bower (Flinn), 28Jan 11:23 PM)":"\"847a61705e2ea1c1a79f0bac9be7ce4d\"","2.02 Objects (Andrew Houde, 28Jan 6:41 PM)":"\"2c4b426958feb5e73f7cda8f949ef769\"","2.02 Objects (Benjamin Furbeck, 25Jan 7:50 PM)":"\"642fe88fecd57627148d5b7a0938f39a\"","2.02 Objects (Brandon Helsing, 28Jan 10:33 PM)":"\"00c447c5fc84c38df84f817827665833\"","2.02 Objects (Chris Copeland, 25Jan 5:22 PM)":"\"b443e63a89ca62d85bdcc4de9a819cec\"","2.02 Objects (Derek Smith, 28Jan 10:31 PM)":"\"57d45359e6a6707b5238392addb8a02d\"","2.02 Objects (Dylan Pagillo, 29Jan 12:38 AM)":"\"6d9ad53879b2a4ca3b59c6a95b549086\"","2.02 Objects (Eric Brown, 30Jan 10:11 AM)":"\"4f16e347a807bd4b2fdc907f3a5f8b80\"","2.02 Objects (Gladson natarajan, 28Jan 7:59 AM)":"\"644a042d3582d202c51200b4c511b672\"","2.02 Objects (Jillian Christiano, 27Jan 11:20 AM)":"\"4829137bc7eceb83585c9bf09634755f\"","2.02 Objects (Justin Cushing, 29Jan 12:05 AM)":"\"abd525fa80e6ad4acfffe07660a9cce1\"","2.02 Objects (Karina, 29Jan 8:36 PM)":"\"9894029aacb9b28da3526c6c6fb2093e\"","2.02 Objects (Malyka, 28Jan 4:03 PM)":"\"3f913d1f7d2ecb910dccd7d787e1d759\"","2.02 Objects (Marcus Spratley, 29Jan 12:15 AM)":"\"3aa0d4d541078bd8e70214a1d0ede01b\"","2.02 Objects (Marvin Pierre, 28Jan 5:25 PM)":"\"6f7fec0b7f570c28fa987372fc19f3ff\"","2.02 Objects (Max Nadel, 30Jan 5:25 PM)":"\"75362a75c834576a0f6044d73af4397e\"","2.02 Objects (Megan, 25Jan 5:03 PM)":"\"c7fc9d6c47612385aacb9b5df6685ed0\"","2.02 Objects (Michael C. Miller, 29Jan 4:16 PM)":"\"49bd12c86a94f30100e6a06b11003982\"","2.02 Objects (Mickey, 05Feb 7:39 PM)":"\"3188d3b4712067d09a121a7dc4159f7b\"","2.02 Objects (Orinthea, 28Jan 3:51 PM)":"\"bbbf087fa447ae6d273cca258fd5ef23\"","2.02 Objects (PattyV, 17Feb 7:17 PM)":"\"d8d957c82592f277fc1c2b02d0d42675\"","2.02 Objects (PattyV, 19Feb 10:10 AM)":"\"2f05fd890bf3a98fa972c361bde610b3\"","2.02 Objects (Ryan Maher, 28Jan 10:28 PM)":"\"9e080f39ff0b762b18fe456c33e67ac1\"","2.02 Objects (SHallenbeck, 27Jan 10:13 PM)":"\"7265b0a39194cc1e02e8f6248cb0de04\"","2.02 Objects (Shannon MacColl, 28Jan 1:21 AM)":"\"5fe9866d3c0ab1973d3c6371ffced0e7\"","2.02 Objects (Steve B, 25Jan 11:48 AM)":"\"a1e780ec513ab1673f1d2f48cdc8bcca\"","2.02 Objects (Tristan Retzke, 28Jan 8:30 AM)":"\"7573262e47802ec94db81a3b02c8c800\"","20171128180633154":"\"0d8c8a30f696d2ed1283c45785505c5c\"","20171128191203385":"\"b33e6f4ad54fc6af9d19e8e7c1e63eb7\"","3.01 Reverse Engineering Google News (Alicia Bower (Flinn), 02Feb 4:37 PM)":"\"f48059df83fde9df5ba522149bb06db0\"","3.01 Reverse Engineering Google News (Andrew Houde, 04Feb 4:41 PM)":"\"465c4241099ddaa4dc8fc5fefdd38609\"","3.01 Reverse Engineering Google News (Benjamin Furbeck, 31Jan 7:43 AM)":"\"ffbadb3ebe8377c8bd725cae23a74156\"","3.01 Reverse Engineering Google News (Brandon Helsing, 05Feb 12:09 AM)":"\"6ab6f1f597c8fba661f2224f6f80b701\"","3.01 Reverse Engineering Google News (Carson Palmer, 05Feb 4:09 AM)":"\"5530cc521fcfd9a176ad3e832fb1e58d\"","3.01 Reverse Engineering Google News (Chris Copeland, 30Jan 2:57 PM)":"\"08ea9dd547db0067aa840ce8127026fe\"","3.01 Reverse Engineering Google News (Derek Smith, 04Feb 4:29 PM)":"\"12c3fdd0505c47aa5c372ef720890f40\"","3.01 Reverse Engineering Google News (Dylan Pagillo, 07Feb 3:40 PM)":"\"5d29df37d8fb8a42c7243c46d41c2ae5\"","3.01 Reverse Engineering Google News (Eric Brown, 01Feb 9:59 AM)":"\"1e22d90a1b9c39b2868151a0f6b7123f\"","3.01 Reverse Engineering Google News (Gladson Natarajan, 04Feb 9:20 AM)":"\"915cc4a68159239da8a445df066f62d9\"","3.01 Reverse Engineering Google News (Jared Duquette, 23Feb 10:17 PM)":"\"d8739b02cdbbe9951c9a6f9581e9d1f4\"","3.01 Reverse Engineering Google News (Jillian Christiano, 01Feb 11:34 AM)":"\"ce5868d676e34fc6ae21863c0b6ebf85\"","3.01 Reverse Engineering Google News (Jillian Christiano, 06Feb 10:14 AM)":"\"7f1251d00d9d7e52d21a55b54b6b735d\"","3.01 Reverse Engineering Google News (Justin Cushing, 04Feb 3:15 PM)":"\"b81646268714a716d650edb6324e8ee2\"","3.01 Reverse Engineering Google News (Malyka, 04Feb 7:11 PM)":"\"d41138aea98ae6b940674b2b1cba6198\"","3.01 Reverse Engineering Google News (Malyka, 17Feb 2:16 PM)":"\"454bce59326ad93e8712fbb0e4d8776a\"","3.01 Reverse Engineering Google News (Marcus Spratley, 04Feb 11:55 PM)":"\"a8b18f2678ad5cd40ab1a9b4aa572fa7\"","3.01 Reverse Engineering Google News (Marcus Spratley, 05Feb 1:13 AM)":"\"482176fe4d312f7cf8e107a790f4aa68\"","3.01 Reverse Engineering Google News (Marguerite Fraine, 06Feb 10:34 PM)":"\"b61da0b858b370495d8a63e5561f05cd\"","3.01 Reverse Engineering Google News (Marvin Pierre, 04Feb 5:27 AM)":"\"1d36b6056ceb2c93df75def9f3ac67c8\"","3.01 Reverse Engineering Google News (Max Nadel, 04Feb 4:27 PM)":"\"d58e4c01d8e9d7a4c4d75dcbe6fd161b\"","3.01 Reverse Engineering Google News (Megan, 01Feb 9:24 AM)":"\"2f0ec8d2aa77c48765d3f86c15c3ad73\"","3.01 Reverse Engineering Google News (Michael C. Miller, 05Feb 2:19 PM)":"\"e7e1a8aa5af768c77eca2e2db0c9eefb\"","3.01 Reverse Engineering Google News (Mickey, 07Feb 8:02 PM)":"\"a0e5ab84119bc61c412a5a60f9eded79\"","3.01 Reverse Engineering Google News (Orinthea Sommersell, 04Feb 6:17 PM)":"\"3739f1f937a2049433466c348028979d\"","3.01 Reverse Engineering Google News (Orinthea, 04Feb 6:12 PM)":"\"0d968fab5c8870a37c1ee0cea011b669\"","3.01 Reverse Engineering Google News (Ryan Maher, 04Feb 4:26 PM)":"\"112a64688d24ca3902acb9d7f50365e0\"","3.01 Reverse Engineering Google News (SHallenbeck, 03Feb 8:55 PM)":"\"f26263d010d3a88199d00c352892d21c\"","3.01 Reverse Engineering Google News (Shannon MacColl, 04Feb 1:09 AM)":"\"d91adb00dc2f05f85c63d7834feaa896\"","3.01 Reverse Engineering Google News (Steve B, 31Jan 4:34 PM)":"\"001ee8053c37deb48529c6c1d956c401\"","3.02 Reverse Engineering Wikipedia (Eric Brown, 13Mar 1:17 AM)":"\"03e446c95f2d84e198dadbd194400c32\"","3.02 Reverse Engineering Wikipedia (Jared Duquette, 04Mar 10:31 PM)":"\"95c0406859deaee5f74cc37d8dbf8930\"","3.02 Reverse Engineering Wikipedia (Jillian Christiano, 20Feb 10:02 AM)":"\"b68aeb476815bb7b54430f4c91efd7a9\"","3.02 Reverse Engineering Wikipedia (Justin Cushing, 16Feb 9:40 PM)":"\"8ddd1f536387e2d270028e50881dc734\"","3.02 Reverse Engineering Wikipedia (Justin Cushing, 19Feb 8:01 PM)":"\"017b1c237a72d9ce50c7b2cfbe0efc0e\"","3.02 Reverse Engineering Wikipedia (Malyka, 17Feb 2:17 PM)":"\"fe46725b0c2fb577cdebd8d8f180fd1c\"","3.02 Reverse Engineering Wikipedia Tables (Alicia Bower, 02Feb 5:29 PM)":"\"8fc1a1b0bf07a34327f20edb2000e4ed\"","3.02 Reverse Engineering Wikipedia Tables (Andrew Houde, 05Feb 12:03 AM)":"\"50785d88b6b6a9faebf7a5136d695edb\"","3.02 Reverse Engineering Wikipedia Tables (Benjamin Furbeck, 04Feb 11:03 AM)":"\"bc9f858b7c9a6f9c112ed9ad9378480e\"","3.02 Reverse Engineering Wikipedia Tables (Brandon Helsing, 05Feb 12:26 AM)":"\"d5f089c16d3d0e96867f0f23e5ca6d3c\"","3.02 Reverse Engineering Wikipedia Tables (Chris Copeland, 01Feb 2:51 PM)":"\"f30b340b9862ec6011a1043da722695f\"","3.02 Reverse Engineering Wikipedia Tables (Derek Smith, 05Feb 1:43 AM)":"\"1a80f71ee3fdc55761b81de9a99742d1\"","3.02 Reverse Engineering Wikipedia Tables (Dylan Pagillo, 08Feb 12:00 PM)":"\"67d860a3560a4836d079bb09ef0005f9\"","3.02 Reverse Engineering Wikipedia Tables (Eric Brown, 06Feb 9:55 AM)":"\"998f01697362f2f752c489994eabdbd9\"","3.02 Reverse Engineering Wikipedia Tables (Gladson Natarajan, 04Feb 10:35 AM)":"\"8409216bc4740e4362aedaddc70f0a3f\"","3.02 Reverse Engineering Wikipedia Tables (Gladson Natarajan, 04Feb 11:01 AM)":"\"7adb1379aea6a66401beb870e21706ef\"","3.02 Reverse Engineering Wikipedia Tables (Jillian Christiano, 03Feb 1:55 PM)":"\"e5d059ed72505d71a12d0dec5c9986c9\"","3.02 Reverse Engineering Wikipedia Tables (Justin Cushing, 04Feb 6:46 PM)":"\"8a92d94912e30159acf40cf64b6f3808\"","3.02 Reverse Engineering Wikipedia Tables (Malyka, 04Feb 7:43 PM)":"\"c1f3bab44b650c9cfd255fb8f279fb61\"","3.02 Reverse Engineering Wikipedia Tables (Marcus, 05Feb 1:25 AM)":"\"06cbae8585f31427f4166709efc3baa4\"","3.02 Reverse Engineering Wikipedia Tables (Marguerite Fraine, 06Feb 11:27 PM)":"\"a5f1b1e7413df478ab32e4d669ee4041\"","3.02 Reverse Engineering Wikipedia Tables (Marvin Pierre, 04Feb 5:23 AM)":"\"1d34727b2fa58e77a8220e56b67f0791\"","3.02 Reverse Engineering Wikipedia Tables (Max Nadel, 06Feb 3:21 PM)":"\"fcadbfdd2f51baa0ff5cf74d0bcb04bf\"","3.02 Reverse Engineering Wikipedia Tables (Megan, 01Feb 4:28 PM)":"\"f73212685f2aa4c7aeb5ef74a805e2b2\"","3.02 Reverse Engineering Wikipedia Tables (Michael C. Miller, 05Feb 3:48 PM)":"\"84306fa6035d780b2a7f287de314e241\"","3.02 Reverse Engineering Wikipedia Tables (Mickey, 12Feb 9:20 PM)":"\"45460339962fafcfb5dae49fbbbfe9ab\"","3.02 Reverse Engineering Wikipedia Tables (Orinthea Sommersell, 04Feb 6:15 PM)":"\"d387fc3e84a67e8d9bdbd1b5cfaa5c99\"","3.02 Reverse Engineering Wikipedia Tables (Orinthea Sommersell, 04Feb 7:12 PM)":"\"92f9c65bd85424f4dee2b2a5e8d3cc70\"","3.02 Reverse Engineering Wikipedia Tables (SHallenbeck, 05Feb 11:11 AM)":"\"9642bb7b9a4e4f3852f6a55f842fa8a8\"","3.02 Reverse Engineering Wikipedia Tables (Shannon MacColl, 04Feb 2:33 AM)":"\"8f65617956308fb34cac285c6d148048\"","3.02 Reverse Engineering Wikipedia Tables (Steve B, 04Feb 8:51 PM)":"\"4f8c92e5da26aa5afe4d63bc2336ee1e\"","3.02 Reverse Engineering Wikipedia Tables (Tristan Retzke, 10Feb 8:02 PM)":"\"43a4b3c7799738342b86ea3158371738\"","3.03 Importing Wikipedia Tables (Alicia Bower (Flinn), 14Feb 6:24 PM)":"\"72efa177386e49c25c017519608a78e0\"","3.03 Importing Wikipedia Tables (Andrew Houde, 18Feb 1:56 PM)":"\"c57e0261ed824a75e6b99ca273ef798b\"","3.03 Importing Wikipedia Tables (Benjamin Furbeck, 15Feb 12:28 PM)":"\"ee12296ebb5c0cb77e18302951556cca\"","3.03 Importing Wikipedia Tables (Brandon Helsing, 18Feb 11:20 PM)":"\"212e6881a43b8fdc8bef63c149e73b6c\"","3.03 Importing Wikipedia Tables (Derek Smith, 18Feb 8:15 PM)":"\"30d003ac11585232a5b8ab26afd6aaea\"","3.03 Importing Wikipedia Tables (Gladson Natarajan, 18Feb 11:00 AM)":"\"3834df90d57ecbafaa85b89353569457\"","3.03 Importing Wikipedia Tables (Gladson Natarajan, 18Feb 11:32 AM)":"\"2d4ba3961d0dd4b5e997e91296cc2778\"","3.03 Importing Wikipedia Tables (Jillian Christiano, 20Feb 10:11 AM)":"\"1484a15f04da5a6f2178a7bf91770b42\"","3.03 Importing Wikipedia Tables (Justin Cushing, 19Feb 7:04 PM)":"\"89a00e149845c52a362d34fe019ea9dd\"","3.03 Importing Wikipedia Tables (Malyka, 19Feb 12:14 PM)":"\"c385ba6f989727198cb6a59928bc3ebd\"","3.03 Importing Wikipedia Tables (Marcus Spratley, 19Feb 3:46 AM)":"\"6dd1a03525c09b261a856be2e15ad6eb\"","3.03 Importing Wikipedia Tables (Marguerite Fraine, 14Feb 1:41 PM)":"\"fb0fd222eb7a3eaf21962912ca207c94\"","3.03 Importing Wikipedia Tables (Marvin Pierre, 10Mar 6:04 AM)":"\"5b6b518ddf17524e9778c034dbd32db6\"","3.03 Importing Wikipedia Tables (Max Nadel, 19Feb 9:33 PM)":"\"cb7d56f957ba5123cb907ce8b351ff1b\"","3.03 Importing Wikipedia Tables (Megan, 14Feb 8:39 AM)":"\"f208729a71196afb0c362e79eb249f12\"","3.03 Importing Wikipedia Tables (Michael C. Miller, 18Feb 10:56 PM)":"\"e62ced2d5721111cff0d38bcc693b7f1\"","3.03 Importing Wikipedia Tables (Mickey, 14Feb 11:41 PM)":"\"81efb05dea838d1b60bb32837bc5a014\"","3.03 Importing Wikipedia Tables (Orinthea Sommersell, 18Feb 12:36 PM)":"\"9afca01f4f665375818a895ed73c48b9\"","3.03 Importing Wikipedia Tables (SHallenbeck, 18Feb 12:43 PM)":"\"62006cb21599304aaca6fd8eae3a526c\"","3.03 Importing Wikipedia Tables (Shannon MacColl, 16Feb 7:54 PM)":"\"dc3340e1d980963cc22db39b4b784afc\"","3.03 Importing Wikipedia Tables (Steve B, 20Feb 10:07 AM)":"\"05e3c08af176ff8768a0c13337444811\"","3.03 Importing Wikipedia Tables (Tristan Retzke, 21Feb 2:41 AM)":"\"bf2163c4972eade7ee8ee6ca81ba4028\"","3/1/2018 10:35:16":"\"3118215e4e30e68bcc66ed07c8421985\"","3/1/2018 10:35:46":"\"85a552734cfc50625334aa7f47005fab\"","3/1/2018 10:36:31":"\"e9df3866fd0b2b286a0fd634ef2d8a6f\"","3/1/2018 10:36:44":"\"4ce98c90e881976d15027d1d09f44fca\"","3/1/2018 10:37:23":"\"9e856462bf77b0b89f78a3c02c2d43bc\"","3/1/2018 10:37:55":"\"6b54ba85ef43a603a08b970e25f4175e\"","3/1/2018 10:38:00":"\"dc4f5fa4658ac2353187023f374ea8fe\"","3/1/2018 10:38:09":"\"11261427e115dc9eba915eba633658fe\"","3/1/2018 10:39:01":"\"3e772888ee8105e5f084c420e8885024\"","3/1/2018 10:39:45":"\"961bc48e7a50a1c074c98ba758b000b5\"","3/1/2018 10:40:02":"\"dc78948153e5835c3711bfa8441aa70c\"","3/1/2018 10:40:04":"\"34499742d6f43807f3d328498c6ba59a\"","3/1/2018 10:40:19":"\"44c0d186908cc1ec3179aba6efad9662\"","3/1/2018 10:40:26":"\"789b99623d051738836b6c6fdf320ca4\"","30th November 2017":"\"23bf8e87b4ec4ae385bb318dd0f7991d\"","3rd January 2018":"\"5bc003f4266a2d875639c366299bc9f7\"","4.01 Annotations (Andrew Houde, 11Feb 9:55 PM)":"\"2553ec894e313e9273d8dfdc5d79250b\"","4.01 Annotations (Brandon Helsing, 12Feb 1:30 AM)":"\"2a9ff10d9b67a186c8d2c68a47a6e844\"","4.01 Annotations (Chris Copeland, 12Feb 1:20 PM)":"\"86fafc7e98bbf857f3617f5ac088a0ba\"","4.01 Annotations (Derek Smith, 12Feb 2:55 AM)":"\"c0b830f9852ad00632f0a195e217007d\"","4.01 Annotations (Gladson Natarajan, 11Feb 1:44 PM)":"\"fda49b13ee11198c1e6e13f9ba7c3de6\"","4.01 Annotations (Gladson Natarajan, 11Feb 3:07 PM)":"\"777bc601e7c5193b9c8c2b65fc6d18a6\"","4.01 Annotations (Jillian Christiano, 20Feb 10:09 AM)":"\"510857a402f60f3af7256d19d6250d91\"","4.01 Annotations (Jillian Christiano, 20Feb 11:20 AM)":"\"c9b048166da5c20e1f4d276cc85d0fc0\"","4.01 Annotations (Justin Cushing, 10Feb 6:55 PM)":"\"2a8775be902093c998f0dcf8c0958e26\"","4.01 Annotations (Karina, 12Feb 7:17 PM)":"\"c3117a6f63a8624847ec28d02750eaba\"","4.01 Annotations (Malyka, 11Feb 11:08 PM)":"\"268c5b65fdee4f2d3bd35fd60d6b929f\"","4.01 Annotations (Malyka, 17Feb 4:22 PM)":"\"69b9fa468b721a79436a13c9b0c025d8\"","4.01 Annotations (Marcus Spratley, 12Feb 12:47 AM)":"\"544b1b85b40e0d7de76a480a8049c33d\"","4.01 Annotations (Marguerite Fraine, 19Feb 11:28 PM)":"\"8c0fd40e940ea689888ed2e31dee4950\"","4.01 Annotations (Marvin Pierre, 12Feb 5:54 PM)":"\"57a2cf5e6fd51515f6204e1fada4cfb5\"","4.01 Annotations (Max Nadel, 12Feb 8:48 PM)":"\"a0f447690f01642f2b2131472d02c0ac\"","4.01 Annotations (Michael C. Miller, 11Feb 10:13 PM)":"\"0d85debb673380fb5c38cb168e1302a8\"","4.01 Annotations (Michael C. Miller, 20Feb 8:40 AM)":"\"bcd45a5ebcfcf1d4380172ba72cf2d52\"","4.01 Annotations (Mickey, 22Feb 1:12 PM)":"\"3ed7927bb4a9263b41d7164958eced67\"","4.01 Annotations (Orinthea Sommersell, 11Feb 10:19 AM)":"\"4f5d4ff6b53e1226aa23f8aa02180fd9\"","4.01 Annotations (Orinthea Sommersell, 11Feb 10:21 AM)":"\"94bff43c73675a5b38b28aa640adbe67\"","4.01 Annotations (Ryan Maher, 20Feb 10:11 AM)":"\"85e9fafa2352307a13888dfff88cbbe7\"","4.01 Annotations (SHallenbeck, 10Feb 12:40 PM)":"\"0fe22a3960fbc217b66171695ec66e71\"","4.01 Annotations (Shannon MacColl, 11Feb 7:16 PM)":"\"9cfac886325ff35af14361b22175f129\"","4.01 Annotations (Steve B, 12Feb 8:25 AM)":"\"b6fd2f8fab2c417c6a92e67f593601f0\"","4.01 Annotations (Tristan Retzke, 16Feb 1:08 AM)":"\"9cb1b1d47e3c1e0e9a40e4e4c50dd5e0\"","4.02 Bibliographic Exploration (Alicia Bower (Flinn), 21Feb 3:50 PM)":"\"bc76ba2adb7e7d0fcdc81cb1a42b72c3\"","4.02 Bibliographic Exploration (Andrew Houde, 20Feb 4:04 AM)":"\"65612439a51d1ca165d596902996e1f1\"","4.02 Bibliographic Exploration (Benjamin Furbeck, 17Feb 6:56 PM)":"\"308a783723706e2f49d79cd09aa1a47f\"","4.02 Bibliographic Exploration (Brandon Helsing, 20Feb 10:40 PM)":"\"7e8810035c584639278d73618cec8a29\"","4.02 Bibliographic Exploration (Chris Copeland, 18Feb 7:40 PM)":"\"349a772796c29b88f2276131a4f2a8fb\"","4.02 Bibliographic Exploration (Chris Copeland, 27Feb 10:40 AM)":"\"0e8aeec132bcf5f3b66059e392d45cb6\"","4.02 Bibliographic Exploration (Gladson Natarajan, 20Feb 7:53 PM)":"\"c3277f00fe3043fbc2ecf5ff09572a18\"","4.02 Bibliographic Exploration (Jillian Christiano, 22Feb 11:41 AM)":"\"9cdfab925748d76ecb017f0e5948346f\"","4.02 Bibliographic Exploration (Justin Cushing, 20Feb 10:15 PM)":"\"f19131abb927eb9d400fd8be521cc36c\"","4.02 Bibliographic Exploration (Malyka, 20Feb 9:27 PM)":"\"80b44e9e58e4f69941e71c5883f564ee\"","4.02 Bibliographic Exploration (Marcus Spratley, 21Feb 3:19 AM)":"\"5052d465052e63d04458838001193b22\"","4.02 Bibliographic Exploration (Marguerite Fraine, 27Feb 12:02 PM)":"\"fb9f89f7778c1283537b77d6ad73b79a\"","4.02 Bibliographic Exploration (Marvin Pierre, 20Feb 5:23 AM)":"\"5b17c6c920f8b742ae7e45464e56e2a9\"","4.02 Bibliographic Exploration (Megan, 22Feb 10:18 AM)":"\"70cb64fb9db4a3b826fca167bf5cb14d\"","4.02 Bibliographic Exploration (Michael C. Miller, 20Feb 8:40 AM)":"\"14999f458b63ba58f82900a02e2e43b9\"","4.02 Bibliographic Exploration (Mickey, 25Feb 5:13 PM)":"\"8069498cf24cb865184b521487bd8388\"","4.02 Bibliographic Exploration (Orinthea Sommersell, 20Feb 8:17 PM)":"\"3e20a09cf0ab099c595d8403310bf035\"","4.02 Bibliographic Exploration (Scharem , 19Feb 9:40 PM)":"\"ef8a68fdf7c8167618c2e70090883e8f\"","4.02 Bibliographic Exploration (Shannon MacColl, 20Feb 4:04 PM)":"\"6c1e6c16f05c68d48b7e90299a3af525\"","4.03 Writing a Narrative Essay (Alicia Bower (Flinn), 22Feb 10:51 AM)":"\"97fa9ffe4597fcc7d922ad5d429dfeb4\"","4.03 Writing a Narrative Essay (Benjamin Furbeck, 13Mar 7:40 AM)":"\"0d1b48dacef968430038dca5e23cdc00\"","4.03 Writing a Narrative Essay (Brandon Helsing, 26Feb 1:03 AM)":"\"8f730f0b1c05fe6427f6be73f041411d\"","4.03 Writing a Narrative Essay (Chris Copeland, 27Feb 10:40 AM)":"\"dbcde9345b9e43209834c94fc25d05bf\"","4.03 Writing a Narrative Essay (Gladson Natarajan, 21Feb 3:13 PM)":"\"b9a61e1a956518429017c300d8223ca2\"","4.03 Writing a Narrative Essay (Jillian Christiano, 07Mar 1:32 PM)":"\"27c3f242c0dee1cf71e2b4726fca62c5\"","4.03 Writing a Narrative Essay (Justin Cushing, 25Feb 3:16 PM)":"\"5e175555aed4103c4a78ea441c2f51a5\"","4.03 Writing a Narrative Essay (Malyka, 09Mar 10:05 PM)":"\"b1828caa0490499bbb426e30314dba2b\"","4.03 Writing a Narrative Essay (Marcus Spratley, 26Feb 1:32 AM)":"\"21243fb5276bf582d44efa2cb07e4136\"","4.03 Writing a Narrative Essay (Megan, 25Feb 12:59 PM)":"\"a2b6a3751d6c16699287f2dbeec76e8f\"","4.03 Writing a Narrative Essay (Orinthea Sommersell, 04Mar 2:21 PM)":"\"1e3011e7c7c0d217515d03cc26409fa9\"","4.03 Writing a Narrative Essay (Orinthea Sommersell, 25Feb 8:31 PM)":"\"79198784876c057cc01d297e0871ec70\"","4.03 Writing a Narrative Essay (SHallenbeck, 25Feb 4:42 PM)":"\"bd45725e1c2fc6eab1848770b18685cb\"","4.03 Writing a Narrative Essay (Shannon MacColl, 25Feb 6:04 AM)":"\"d6863fd2011ca5063d78ca1c6d25b3e4\"","4.03 Writing a Narrative Essay (Steve B, 20Feb 10:49 AM)":"\"93cdeefad81545e94791cea28fc694f3\"","4.04 Hypertext in the 21st Century (Andrew Houde, 04Mar 11:49 PM)":"\"a660c1f5cba7db7dc90301dd6e55e70e\"","4.04 Hypertext in the 21st Century (Brandon Helsing, 04Mar 11:13 PM)":"\"09a7a1837e75af5693668fc80f8a9e95\"","4.04 Hypertext in the 21st Century (Chris Copeland, 03Mar 1:03 PM)":"\"070b8194cad9ed34833e0f6b393e2359\"","4.04 Hypertext in the 21st Century (Eric Brown, 13Mar 1:14 AM)":"\"ecd71eec0ed2c9744c50da913de0988d\"","4.04 Hypertext in the 21st Century (Eric Brown, 13Mar 1:16 AM)":"\"a121f68942c2a2c7719bdc24cb836a76\"","4.04 Hypertext in the 21st Century (Gladson Natarajan, 07Mar 5:36 PM)":"\"58ba4f1a221834e237f4b61da7337c31\"","4.04 Hypertext in the 21st Century (Jillian Christiano, 07Mar 3:18 PM)":"\"37a1625bb28dbb434e4dc48ae6633123\"","4.04 Hypertext in the 21st Century (Justin Cushing, 04Mar 7:44 PM)":"\"35f4c2d830b97850b6e7989dcaeef37a\"","4.04 Hypertext in the 21st Century (Malyka, 04Mar 2:45 PM)":"\"0805165fc02a3db8e935def988861d5b\"","4.04 Hypertext in the 21st Century (Marcus Spratley, 05Mar 9:04 AM)":"\"503f14060fc7808bdcdeccb34fc0a478\"","4.04 Hypertext in the 21st Century (Megan, 26Feb 1:38 PM)":"\"34b22a52d49d68eb94de405ebe8776db\"","4.04 Hypertext in the 21st Century (Mickey, 12Mar 9:11 PM)":"\"b624c472b6dc5b6f8cd5cc9235e56ba7\"","4.04 Hypertext in the 21st Century (Orinthea Sommersell, 04Mar 2:22 PM)":"\"6a6f659ddd45d65b6a923f53fe817420\"","4.04 Hypertext in the 21st Century (Scharem, 04Mar 7:24 PM)":"\"2813955fe4813842e378bc90a6601ba2\"","4.04 Hypertext in the 21st Century (Shannon MacColl, 05Mar 8:30 PM)":"\"78050c923b931637fdf60ce5aa78d6ba\"","4MoreWords-Designing, Writing,  Interactivity, Texts: The Idea of Hypertext: Screencast Chunk":"\"1313a4b1644f3859e12df1547525e735\"","4Words-Text, Hyper, Wiki, Tiddly: The Idea of Hypertext: Screencast Chunk":"\"d9752b434f388efef58dacbb9f02f8aa\"","4th December 2017":"\"6c795e71fc4b9fe52d69fefe914f31a7\"","5.0X 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Composition Classroom (Cripps)":"\"4fa442c1ec80f6dea81bd9680ee29536\"","Hypertext TiddlyWiki (from IDT507)":"\"840a3609f671a2c799ac1fcd54048319\"","Hypertext in Theory and Practice":"\"3ae0a31df1d3bd2ba51d25db61582fbf\"","Hypertext(ual) Bibliography":"\"95fcfd444f71aa9b6d900e671f24175f\"","Hypertext, Before Today: The Idea of Hypertext: Screencast Chunk":"\"5e2d763a9d34610740c67d3e957d32df\"","Hypertext/Hypermedia Handbook":"\"5fe2b154f8627a2e53ad1a844f4a504d\"","Hypertextual Practices":"\"11465308840567161cc8687de024d90c\"","Hypertextual readings about hypertext":"\"681b0a50642e7f3f9c5fe2ec2f766864\"","Hypertextuality: The Podcast":"\"d238c72dd179b76c18160e923b4f911a\"","IDT 553 Module":"\"a292375ab5d85e4f4114cf6bf83953ac\"","IDT 575 Assignments":"\"365bf2c4ed7644b686d4524929952426\"","Iconic Representation":"\"dd714311d26fdad66414210aecebedae\"","Ideas for exercises":"\"8acd9d61df0091c9d5e3ce6ad33f2303\"","Illustration 1":"\"d2a62ba6814860662a98a57d52cc3b10\"","Illustration 10":"\"d16328fc1d2bcf2ef8b89a827d2d1a94\"","Illustration 11":"\"fe7fba172e9a3a8dd1c654e7def0ebe8\"","Illustration 12":"\"14014fb3eee04657baeab8d0804293cc\"","Illustration 13a":"\"96f369936028ca0b329542e69176571e\"","Illustration 13b":"\"f739179ee3ec0399acb5a92417ccbfd5\"","Illustration 13c":"\"68be9d195d7984a2e87145e857a248f9\"","Illustration 13d":"\"3092d1187623b715f606cd5cacf32d5b\"","Illustration 14":"\"e29ae9e24be1e0397a74484cbe631c93\"","Illustration 16":"\"0b225148ed67c9ccec88f87b24d29332\"","Illustration 18":"\"99dc2e0a29fd28c4a61b11fbb6a1898e\"","Illustration 19":"\"fae73f22ca8226f029e66aeb0d18d749\"","Illustration 2":"\"f3813abfe8c484a7186e229fcf30174d\"","Illustration 20":"\"9022ec2bfd947b688eafadd3b44b7708\"","Illustration 21":"\"0a88061d0e1131dc500aa915d1b23351\"","Illustration 22":"\"f345e9b698ec7cb16b3f9f71088e7709\"","Illustration 23":"\"8d0003be9cfdca13537779be269de9ca\"","Illustration 25":"\"58b3fc3a0d414973ebde4fe649e2ebe0\"","Illustration 25c":"\"e1a009d3a44677271c64b5e582b73294\"","Illustration 25d":"\"bb823fa99a62be6695c87ca4e2e15d74\"","Illustration 27":"\"ebbe062f25a0d5b95cb403113215f7a2\"","Illustration 27a":"\"06a1c0ca42b35821b023c04c18127f31\"","Illustration 28":"\"b3b64c04ffbac679ef1ff635d1916ea3\"","Illustration 3":"\"87426d2a1859fbf1ff57995ad2dd21aa\"","Illustration 30":"\"d13b8dfc99ee74a1d4ef58938174f1de\"","Illustration 33":"\"04be40635bfd22ee32658a499f0e0f1a\"","Illustration 33a":"\"bd542924d1f54cf39f0709ba59d150dc\"","Illustration 4":"\"245370ff9c0941241c5ebb675cd4611a\"","Illustration 5":"\"9fbe8071a9d3555d0ad5b16dfbefec44\"","Illustration 6":"\"f3368ed10973c1c9833a90da36c4eee2\"","Illustration 8":"\"39827ef0fc1dcc6a41c32da02acd39a7\"","Immersion":"\"5ecf92f71a316e33c0ab5c1a7dd5eae6\"","Importing XLSX files":"\"a80548b59c7c7025ed845403756bd000\"","Inattentional Blindness":"\"2f7643d3243b290ddd94b7f4e960ddec\"","Instruct":"\"e3345a3c2290d4fef06ba1fefbc7420d\"","Interactive":"\"bb4c7fc1375bc0feb1109b76ea1cf87a\"","Interactive Literature / Poetry":"\"c6045887fc21c4eba931dfe708150a61\"","Interactive Texts in the Wild":"\"ab982df6b43a376ce369e1d9446f653e\"","Interactivity":"\"2dba2418654f45cbf5f00eaa7ffb4fa0\"","Interesting use of svg in a slider":"\"f2542e7ae78a54f49648e889848d18d3\"","Interference Effects":"\"52fbb31bd869e3873067d7e6c276ab50\"","Intermediate Interactive Texts":"\"ab2cfdf7b076e9079500c2850eba9b41\"","Introduction to Computer Lib / Dream Machines (Nelson)":"\"44b13acf412e3903aefa57bce781339f\"","Introductory Interactive Texts":"\"248a6e5c29c43fce745bbd384a4a4411\"","Inverted Pyramid":"\"ac3bed22fed5b6a78cae8c23e63dc9ca\"","Is this a General Purpose YouTube Clipper?":"\"b1a653c7127433a45aca07b25e08be9f\"","Iteration":"\"7dfe23346f833ef3e0cf7e6ff70b40af\"","James Ward Final Presentation":"\"a2828f95a1c55d676b87f10afb5988b8\"","Jan-May 2018 Calendar":"\"1551f869def3f19817c71f0a5d978e80\"","Jeremy Ruston Bio":"\"f0f01373d53367bbf9df13287479b1ff\"","Jillian Christiano Final Presentation":"\"dfb3482b8ea392a5efbb3e5667d434ed\"","Journal":"\"ebba5328cb531a7e88d019a04182b75b\"","Justin Cushing":"\"abcbdea952da7cd959ac63b7aa26c01a\"","Justin Cushing Final Presentation":"\"cb28ce2dcac523aa6147a83d95de8e99\"","Karina Benninger Final Presentation":"\"1fa004f6d41c518cd06a7638d11b86d1\"","Key concepts related to interactive texts":"\"0604a2ba2aba709e1a8fd1aefa4a0274\"","LastSlide":"\"dd2ec44611d74194ee42300e4e3dd714\"","LastSlide 1":"\"cc6bbe268d968f56f56dd746e2235f77\"","LastSlide 2":"\"61a8c420a12fea9c1514528b5fb287f8\"","LastSlide 3":"\"d55c1f6ad1f1b32a736d7aa626ef5254\"","LastSlide 4":"\"1cca85e355b3fe73a654144369e34ba0\"","Law of Prägnanz":"\"0dc5c3447122f8946a4c2c1c1fe5a8bc\"","Layering":"\"c4df2f4d966a2780dcdc5dd371a818ad\"","LearningCommunities":"\"d913ad8a96aa6534d5a8df5c9f5d852a\"","Legibility":"\"759a59327b40698e337c95addc571fab\"","Life Cycle":"\"3173d1fd104a4ca9918cba7de3ce8b79\"","Linear Text":"\"b6264efe693b08be26edfd72f174a243\"","Linking":"\"0e699f6f95a3331df8dc8b656e5b2657\"","Linking in TiddlyWiki":"\"c1591dd585913a60780739445fa03237\"","Listing":"\"0b36b02d93b1e34120c33be961e9d70c\"","Listing in TiddlyWiki":"\"c9787fa93228d9ca120a6ca6a6903202\"","Literary Machines (Nelson)":"\"241e6c1f8b7fb7763ba5e3fc149b2e1c\"","Mac OS X Chrome Workflow: Saving using TiddlyDrive":"\"960edf76343d5236f6bedb0cd260b26f\"","Mac OS X Chrome Workflow: Saving using saveTiddlers":"\"e1bce4a2d2291590eef04a3c71f517bc\"","Mac OS X Workflow: Serving via ftp.sunyit.edu":"\"b85c726ce1387eb2cdf7553066f4383f\"","Mac OS X and Windows Chrome Saving & Serving Workflow: Tiddlyspot TW Creator":"\"3a9661ad802a18b03c4e85e7fd074cd1\"","Madlibs (or other word games)":"\"ac5c484c88824af17b7f835b5266179f\"","Maintaining Contemporary Citations":"\"225a92435609e196d186c3874bfcfc81\"","Making a crit":"\"3d1be185986d953ecf32a4b7f7062525\"","Malyka Hamilton Final Presentation":"\"a9dc2f29467dc176950db04522afa6c9\"","Mapping":"\"4fb99c7610bbf6824eff9cb463498836\"","Marcus Spratley":"\"81962ff7917b94778798063f1d11bcaa\"","Marcus Spratley Final Presentation":"\"d33acec26b9da295c4973b555352bda8\"","Marguerite Final Presentation":"\"6a4cf3fd2d96d9ee035ff09cd78c93e8\"","Marvin Pierre Final Presentation":"\"df900913d1ce54b66e52b75579583c00\"","McGuffin 2004 Comparison of hyperstructures":"\"fa94f9a0e01009eb23b8af74737f3879\"","Medium":"\"ff50623a0b964c995cd3334756825be9\"","Medium Blue Circle":"\"68b4f89277336e2988c945b455a228e0\"","Medium Blue Square":"\"23d7be6d7adb21fb1ba7c5f56bee237e\"","Megan Final Presentation":"\"0112209a22f0fad088005b7e78533f1d\"","Mental Model":"\"59fea20f995153597bc7da235bdf0fec\"","Michael C. Miller Final Presentation":"\"43ea803d883285fa6e8d4a02f0d4d53b\"","Michael s. Final Presentation":"\"1d24096ef4ceff61b53f3fde10168171\"","Mickey Heljic Final Presentation":"\"2bf5095ee4f809958a9dc3e4fa61271c\"","Mimicry":"\"117c4eb83c8e9907c58f5d36b7968be5\"","Mini-projects for Summer":"\"cd528f925680bcbea8fbae01dbdd991f\"","Mnemonic Device":"\"c004eb9f0d21d0bb9eb5605fcd9f0451\"","Modularity":"\"ea21450dab920bb7b8c9ffe893eef4e1\"","More Topics to Come":"\"a8dccaa76f2be08f8160908e8cbabd64\"","Most Advanced Yet Acceptable":"\"05eeb9a34f29b1fb3e0c55afff16ca5a\"","Most Average Facial Appearance Effect":"\"cec508b0d76ae8f75e4975d33533e878\"","Multi-dimensional Slide Show":"\"d5157197819075f16ec4f25cd1631aee\"","MultiDim Slides: Multi-dimensional Slide Show":"\"014f2a26cac5d6c15b62614300f48866\"","MultiNav: Multidimensional navigation among tiddlers":"\"9da33afabc34f8d2731c751c3cfa3783\"","Multimedia":"\"02d0ddf5cb67afe76b39034da3bb0498\"","MyTextTiddler":"\"1ed9c07bee05241aea63156b20a306da\"","Naming the Unnameable: An Approach to Poetry for New Generations":"\"7db73120b6c6cfef5b5b42fc7024a289\"","Navigating Through A Set of Images":"\"cffa5e195f438a3608fdfbea05e4540d\"","Navigating Through A Set of Tiddlers":"\"ace3e468ede74b102d591b0ad8a1e754\"","Navigation among tiddlers with buttons":"\"7c3698fbdfd1d5e9842e674b804cf7f9\"","Navigation-Help":"\"0d1f6f5f26fb045b52a0bc9a5a785f52\"","Nelson 1999 Xanalogical Structure":"\"2ea6a1d4406c3f9c2d27bf97668b0cec\"","Nelson File Structure for the Complex, the Changing and the Indeterminate":"\"f8905217b3fd06b66ca99aa963302e02\"","Nelson on Transclusion":"\"359df6714498328ee915e4748460e104\"","Nelson-Computer Lib/Dream Machines":"\"36f155171d8f0724d1eabd6a412e8706\"","Nelson: Discrete or Chunk Style Hypertexts":"\"4020db2da5c43bb8c92ea672fc49c485\"","New Here":"\"96327443c98cf5aaff058dd076bd9439\"","New Tiddler 1":"\"773a537bb4a1c035d22140f861bf4d93\"","New Tiddler 10":"\"8fc1594ddcfaebc11efa104345772558\"","New Tiddler 11":"\"8a5d9608ddb5bcff027f1e0b3dec29c4\"","New Tiddler 12":"\"7e1adb28913be230399afacd503a4f97\"","New Tiddler 2":"\"c4f152bea803225536f92d8ffd438791\"","New Tiddler 3":"\"ed2e8ba6c90747a2dd5b334c5ed0d0b4\"","New Tiddler 4":"\"f067b3fd2a172205a5cdf8564754a872\"","New Tiddler 5":"\"6e1c2fe0c13f002cc7a07e6ad30574ad\"","New Tiddler 6":"\"675372d5832bf9dc9eaaa3f3f4fc3577\"","New Tiddler 7":"\"d0d4caf604061bfe182e32e1e031a00b\"","New Tiddler 8":"\"4b4c64868ea5ab2df09d47628811cf30\"","New Tiddler 9":"\"5132c66fff33c79aff2065ddccf26865\"","New workflow for setting up tiddlywiki files for critique":"\"a1f9397673a8682cdecd72e0e0b5c85c\"","NewAtDesignWriteStudio":"\"b26f83cce6bfda518515736ff03b1999\"","Next In Hypertext: The Idea of Hypertext: Screencast Chunk":"\"cb86486e66f46871a62beb1e037242b2\"","Noon Wednesdays Utica Time":"\"28dcf4ea76e10ddeeee846e277fb2841\"","Normal Distribution":"\"af8304e712b3840d9f49f2364e07d5de\"","Not Invented Here":"\"c9504e310f8497e936c2e35e7f5c1e2d\"","Note to IDT 575 Students":"\"4e3f78b21e35f22246f7378d6b5a67f0\"","Notes from OER Conference":"\"abaa9433173a4e17e18af3c50e047795\"","Nudge":"\"610f7bbf545c3dcbd573fc4763ec66a9\"","Objectives":"\"794ee068dd71886c83c0445bcb8c4f39\"","Ockham’s Razor":"\"f71b2883f9fe3caa953054bce2bd55b8\"","Online Synchronous Workshops":"\"f8f71ab9bd8c4c045970742c6baa5ab2\"","Open Class: Summer 2021":"\"682712917df38b6131762dd2b9aa6a13\"","Open Course":"\"3d51c78ee6f75e02a0f0e24e9c5dd57e\"","Open Course Spring 2018":"\"322c5144dd48bf8dbb3b53fca0350c10\"","Open Education Research Lab":"\"5a6e6a2ee755260323519a9edb8e316c\"","Open Source":"\"2774319d29c2486e5d5b7fb91514c196\"","Open Students":"\"7bec2ecff1497c01b00fe01c840c4a1b\"","Operant Conditioning":"\"b2076e0ac3acc2bbd753d0b0b276c299\"","Orientation Sensitivity":"\"8a7fd1b9b3c04456ab23a2114a1a7386\"","Origins of the word":"\"d7830a94890dc14d8bd95850b50fd2b6\"","Orinthea Sommersell Final Presentation":"\"37b21dc35d79d6e1b76080d63ce8791c\"","Outcomes":"\"2ee92c694f2f13d2fa0f250582959f46\"","Paragraph Template":"\"67829e2fc2153d0d02c62cf888655847\"","Performance Load":"\"392feb49dcde7252242d11a7af99cf52\"","Performance Versus Preference":"\"c0fda9547616340b3bc1fdebe116a687\"","Personas":"\"0eab31316fed071b8e216a96e815c67c\"","Picture Superiority Effect":"\"b22246430295bd944886312f0fd990f0\"","Plugin for bookmarks in tiddlywiki":"\"26a32c7f92a7a4299e620ba69dc8301b\"","Portraits of Hope: Refugees Starting Over":"\"1af7d5528eca205d87c47beb62a2db6f\"","Practices and Techniques":"\"30dbf1f64b345e141f1033b17b94a28d\"","Presentation:":"\"c4d9d2e543d18b8c52d8cba147b5c78f\"","Presentation: Annotation":"\"e65e4a11d0e7119f4e1c9c6d40458545\"","Presentation: Annotation & References":"\"0c276b8a6eb3d1a367bee36caa57741f\"","Presentation: Designing Interactive Texts I":"\"06b1180d516995fefe116cceb5d778fd\"","Presentation: Filtering":"\"444c6ca43cb26b8b89e8be56f9a4d494\"","Presentation: Hypertextual Practices: Reading I":"\"9bf5eeef9b854a59ae615ad40c1abc0d\"","Presentation: Hypertextual Practices: Reading II":"\"66d5a19abffbac1c047bac2a364fb602\"","Presentation: Hypertextual Practices: Writing I":"\"c398ae269f76cd8d74241b2e299cc3f4\"","Presentation: Hypertextual Practices: Writing II":"\"ff6b5b5af62c43dfb5c9fabacecdd63b\"","Presentation: Hypertextual Techniques (Reprise)":"\"e817eb3dcea7cf769c0720d8227a72d1\"","Presentation: Linking":"\"a09191c3a2f80ac2c0b6c5ee6530a977\"","Presentation: Tagging":"\"0bc45775ab0577e683e0cc0b97dfa8bf\"","Presentation: Techniques for Hypertextual Writing in TiddlyWiki":"\"7a7b31356001a9ad17bd0de7265d102d\"","Presentation: Templating":"\"1ddbd3499e2e8544894e3f0fd26e997d\"","Presentation: Text, Hyper, Wiki, Tiddly":"\"7c2ab38aac10ceff169a0900710ced72\"","Presentation: Text, Interactivity, Writing and Designing":"\"934d6e1182560dad5c91e00e05f52189\"","Presentation: To Be Determined (Apr03)":"\"39c5b39282583761e5c4b2ff7f5dd13e\"","Presentation: To Be Determined (Apr05)":"\"b38268d57b26f209af27bc7621cc76c3\"","Presentation: To Be Determined (Apr10)":"\"82338781b9b0bb8b2758921af8e3c418\"","Presentation: To Be Determined (Apr12)":"\"baa06624c014beff65f0df6ad5e051ec\"","Presentation: To Be Determined (Apr17)":"\"f96ad8a5f7120a752e25906a9b179e2d\"","Presentation: To Be Determined (Apr19)":"\"3f57f831190db5476aba3506624d18d0\"","Presentation: To Be Determined (Apr24)":"\"d8950111e14d6309ed4f806c9477c034\"","Presentation: To Be Determined (Apr26)":"\"011dad5ce095ed35b8e467429b58222c\"","Presentation: To Be Determined (Mar13)":"\"219acdcf3b4afe4f3d6ebb2f5a71ef35\"","Presentation: To Be Determined (Mar15)":"\"ecdea901ced25a1be5ac95c291bbb2d6\"","Presentation: To Be Determined (Mar20)":"\"47a12f1730b1bb1db2f5ff2b0b33c17c\"","Presentation: To Be Determined (Mar22)":"\"e4fa0c763d539301f1fa80ab1e73d228\"","Presentation: To Be Determined (Mar27)":"\"42aa0ee1e061b5ad12148595d623d38f\"","Presentation: To Be Determined (Mar29)":"\"2cfce3c29a88ad578030f67e320e0fd4\"","Presentation: Transcluding":"\"09d86057f2766d7e84859b2832b8e2ef\"","Presentation: Welcome to Designing & Writing Interactive Texts":"\"13e30ddf6e02864f100db2fc7dae4064\"","Presentation: What is Hypertext?":"\"e60b30acc06f6ede56cc43ed0a7a0c65\"","Presentations":"\"d1405440d2d26cad7d0bbb7a96b9f715\"","Priming":"\"6454da3d652d99b91876bbadd939954f\"","Priority Development Projects: Summer 2021":"\"0dba1c2d36d76b60f78848a10f7031b3\"","Process API results into a TW":"\"5dcdc5245206a22f59f151719b92b22d\"","Processes involved in creating Interactive Texts":"\"c41b55a4bc1245f3d0fca209bce6b025\"","Progressive Disclosure":"\"772937a2b4dc8d69af21b57e245f163b\"","Propositional 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Essay":"\"b6449314a6d8cd7d64823693dad864ab\"","Workshop: CSS I":"\"501b064e774dc3c8296cbc80ba45412c\"","Workshop: CSS II":"\"d8e4c0f5cfbe4a7868c0698626b1387d\"","Workshop: Creating narratives, objects, fields, templates":"\"db10c0f9d416f475408501c987e575bc\"","Workshop: Critique Self-Designed Exercises":"\"6b2bd893f03aa503a656bc7f6fca4cd7\"","Workshop: Engaging in Hypertextual Practices":"\"d09fd982d11381eed7503b0871645c5e\"","Workshop: Intro SVG & Images":"\"94d0bfc3c171b801748c96728345df0d\"","Workshop: Lists & Filters":"\"215974271a7bc4ff0039b4fcb554c744\"","Workshop: New Tiddlers, Tagging, Linking":"\"44036e01b2ce21be7e50255d7378a09d\"","Workshop: Open Topics (Jan 17)":"\"70c95e4a70a51ac746f49ecfc473e5e3\"","Workshop: Plugins":"\"40809f91e7dd71152707baa3167f5bca\"","Workshop: Reference Tiddlers. 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macro":"\"b4a2d026ed4669060ffaecb8117739ec\"","new-tiddler.png":"\"febd8b24ef083a6ec0df8ce56633ca53\"","new-tiddler2.png":"\"5c02e8bbdeffcd55a05effe25a451859\"","newhere":"\"2e48736dae671c0bf1f2eec4a88b07bb\"","nextButton.jpeg":"\"731e01b47cfafe499ff64e14155d70b2\"","number":"\"d476b883dfdcf7ca423f605855b0a468\"","object":"\"2fc73baf1ec48946851a7dc2b6ec36c5\"","objectives":"\"8dbc85fa9c8e3b27d32f713a012414ee\"","original":"\"295bcee79419e77eae4a00a8ef4041ed\"","presentation template":"\"3fd1d29079a04450c56111a8102a119a\"","punchshow macro tiddlers":"\"243f5023fd3b3422d2d2c1a70289b769\"","quick build of a collaborative (kind of) wiki":"\"567921e0c1ce79ef1bc9288e8ce27906\"","readings template":"\"020a67e26d2a603e3849090e3e20cf77\"","reload-wiki.png":"\"fc38956b8c1dfdfc680c699db04c29f4\"","reviews":"\"6f99295f9a1d892ba114a13dbf4e4643\"","save-tidders.png":"\"9a98186761c8b1c94a5410b0324d4fb5\"","screenshot of studio definition":"\"c2f9756a266b0da78b2423094fb44112\"","self-designed exercise 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https://3ra8f69t8l.execute-api.eu-west-2.amazonaws.com/prod/

7dt020qa8e7mu1oqeqqc0sdss4

eu-west-2:a8912c43-2425-4dc8-b508-26f00b4c2342

designwritestudio

eu-west-2

eu-west-2_ozdiUBB1W

 Screencast Chunk: Hypertext: Hypertext in the 2020s: Opportunities 3

<$list filter="[prefix[jkIII]]">
<$transclude/>
<hr>
</$list>

# [[jkIII-on-google-news.png]]
# [[jkIII-on-google-news-more-button.png]]
# [[jkIII-on-google-news-expanded.png]]

/*\
title: $:/.tb/modules/startup/hide-sidebar.js
type: application/javascript
module-type: startup
created: 20151010151732122
creator: Tobias Beer
modified: 20151010151750739

Hides the sidebar on startup when the config tiddler [[$:/config/hide-sidebar-on-startup]] contains "yes"

\*/
(function(){

/*jslint node: true, browser: true */
/*global $tw: false */
"use strict";

// Export name and synchronous status
exports.name = "hide-sidebar-on-startup";
exports.platforms = ["browser"];
exports.after = ["startup"];
exports.synchronous = true;

exports.startup = function() {
	var conf = $tw.wiki.getTiddler("$:/config/HideSidebarOnStartup"),
		value = (conf ? conf.getFieldString("text") : "").toLowerCase(),
		state = value == "yes" ? "no" : "yes";
	$tw.wiki.setText("$:/state/sidebar", "text", undefined, state);
};

})();

The DesignWriteStudio is a participatory, collaborative and open learning space focused on designing and writing interactive texts. We use the TiddlyWiki platform to explore the practices and techniques of hypertext and hypertextuality. 

The [[DesignWriteStudio TiddlyWiki]] (which you are likely viewing now, and is available on the Web at http://designwritestudio.com) serves as the web presence of the Studio, and as a demonstration of TiddlyWiki.

[[About January-May 2018]]

Steven M. Schneider<br>
Director, Principal Investigator<br>
Contact: steve@sunyit.edu<br>

Try setting your default tiddler to ``[[My First Wiki]]`` that should render properly.

Nice!

Very nice! Looks like you played a bit with fonts and palettes! Enjoy

Nice!

Very Nice! Looks like you played a bit with palettes and fonts. Have fun!

Nice. Looks like you are moving this into the About Me exercise, which is fine. But note this in the group, and I'll write some suggestions about how to handle things like default tiddlers.

Looks like you morphed this into [[About Me]] which is fine, but let's discuss this in the group. Start a new thread on "Using the Same TiddlySpot for Multiple Exercises" and we can discuss there.

Didn't see any tiddlers in your wiki...

I don't see any tiddlers in your wiki. Doesn't look like you de-activated sideeditor plugin. 

Nice!

Very nice! Looks like you've played around quite a bit. Good to see! Enjoy!

Didn't change the title of the wiki, but otherwise, Nice!

Nice!

Nice. Maybe you could write a short tiddler here that explains how you are serving this in bigfishmedia.com...pretty cool!

Need to finish through on demo. Not exactly sure where you are here. But something isn't right.

Nice!

Nice!

Nice!

Nice!

Nice!

Nice!

Nice!

Great! Love to see the exploration. We'll learn it, but if you'd like to go faster, go to [[tiddlywiki.com|http://tiddlywiki.com]] and work through the "Learning" section. How did you change the default font?

set default tiddler to ``Hello there, world.`` in  $:/ControlPanel

Nice!

Nice!

See your default tiddler to ``[[MyFirstWiki]]`` in  $:/ControlPanel

Nice!

Nice!

Nice!

Nice!

Nice!

Nice! Glad to see you ''not'' following silly instructions for things like $:/SiteSubtitle and names of tiddlers. And you are right: the first tiddlers should be called ``MyFirstTiddler!``

Nice!

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Nicely done. A few errors that you could correct someday, mostly in syntax. For example in ``About Me in Tags`` you have ``<< tag "Weedsport School District>>`` which fails to render as desired; try ``<<tag "Weedsport School District">>`` instead.

√ ``About Me`` X ``About Me in Tags`` X ``<<list-links>>`` macro • Need to complete next steps as outlined in [[Exercise 1.02 Directions]]

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Good to see palette work and customization of tools menu • Hey, and thannks for finding the refresh button {{$:/core/ui/Buttons/refresh}}

√ ``About Me`` X ``About Me in Tags`` √ ``<<list-links>>`` macro • Create an [[About Me in Tags]] tiddler - you're all ready to go!

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Nice work on palette • Excellent work  in ``About Me`` to render narrative with links such as `` [[college experience|Education]]`` 

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- -- implement in tiddlers such as ``parents`` like this: ``<<list-links "[tag[parents]]">>`` • Nice use of longish links like ``[[Mom, my sister Cory, my brother Nolan, my other brother Davis, and our pet dog Karma|family]]`` to link to ``family`` •  In future, check [[GoogleForm for SharedWiki Submissions]] to see if your response has been received; no need to submit multiple entries)

√ ``About Me`` X ``About Me in Tags`` √ ``<<list-links>>`` macro • I didn't find the [[About Me in Tags]] tiddler • Very interesting use of tags, including of ``all`` and the intersection between tags

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- -- implement in tiddlers such as ``extra curricular activities`` like this: ``<<list-links "[tag[extra curricular activities]]">>`` • Make an appointment with James or with me via the group to work on your saving issues

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- implement in tiddlers such as ``Occupations/Trades`` like this: ``<<list-links "[tag[Occupations/Trades]]">>`` • Check default tiddler; you call for ``[[about me]]`` not ``[[About Me]]`` • Similar issues with respect to ``Hobbies`` versus ``hobbies``

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro. Nice job!

X ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro implement in tiddlers such as ``Chapter`` like this: <<list-links "[tag[Chapter]]">> -- basically, just like you used ``<<tabs>>`` • Interesting color palette choices • Keep on exploring!

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Not sure why ``working`` is tagged with ``occupations`` • In future, check [[GoogleForm for SharedWiki Submissions]] to see if your response has been received; no need to submit multiple entries)

Interesting way to use iframe to show other web pages • NIce use of HTML5 code to format images in [[Main|http://thebigfishmedia.com/tiddler/index.html#Main]] • Not really an [[About Me]] demonstrating tags and tagging...but that's ok...especially for "open" and advanced students, do as you please and I'll respond...

√ ``About Me`` X ``About Me in Tags`` X ``<<list-links>>`` macro • Also didn't follow through on creating tiddlers referenced in [[About Me]]

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro - -- implement in tiddlers such as ``occupations`` like this: ``<<list-links "[tag[occupations]]">>`` - you started this in ``Occupation`` but, due to case-sensitivity, it didn't render as you intended.

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Interesting use of tags, especially on ``further information`` which is kind of a jumping off point for a future narrative

√ ``About Me`` X ``About Me in Tags`` X ``<<list-links>>`` macro • In your tag tiddlers (such as ``personal life``) you hard-coded the links; instead, use the ``<<list-links>>`` as requested in [[Exercise 1.02 Directions]] • Also, when you referenced ``personal life`` in ``About Me in Tags`` you put ``<<tag "Personal Life">>`` rather than ``<<tag "personal life">>`` (everything is case sensitive). 

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Very different use of tags than proposed in exercise instructions - much more open-ended than instrumental • Very intriguing use of multiple tags as in ``binge-watcher`` which will be helpful in spinning narratives moving forward

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro - -- implement in tiddlers such as ``locations`` like this: ``<<list-links "[tag[locations]]">>`` • You might find it helpful to disable the sideeditor plugin, and so set a default tiddler, as shown in the demo

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- implement in tiddlers such as ``unhealthy snacks`` like this: ``<<list-links "[tag[unhealthy snacks]]">>`` • Interesting question if "order matters" - it doesn't from a technical perspective, but it might from a cognitive perspective • you tagged places such s ``Latin America`` as ``travelling`` not ``Travelling`` as you referenced in ``[[About Me in Tags]]`` • Lots of countries! Perfect source material for projects.

But, you still haven't demonstrated use of ``<<list-links>>`` macro that I could find...

√ ``About Me`` X ``About Me in Tags`` X ``<<list-links>>`` macro -- implement in tiddlers such as ``Work`` like this: ``<<list-links "[tag[Work]]">>`` • Max, you didn't use the ``<<list-links>>`` macro in your tags. None of your tags gather multiple tiddlers under s common tag; there seems to be a disconnect in understanding what tags do. 

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Might have tagged ``dad`` to ``Air National Guard``. Not sure why ``dan`` is tagged ``volleyball`` • Nice palette work.

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • An interesting and somewhat different use of tags, but you get the concept. For example, not sure why you've got things tagged to ``Michael`` -- 

√ ``About Me`` X ``About Me in Tags`` √ ``<<list-links>>`` macro • Create an [[About Me in Tags]] tiddler and populate it with references to your tags such as ``Occupations`` • Interesting to see you using two tags for objects such as ``Blue Honda Civic`` - we'll be using that technique in [[Exercise 2.01]]

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro • Love to see colored tags. And the change in the way tag displays (how did you do that?). You have a space after ``About Me`` in your default; that's why that didn't work. The value of tags for concepts like ``born`` is not clear. But you are ready for stretch text - start a new thread in the group ``How do I use stretch text?`` and I'll write a brief set of instructions!

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- implement in tiddlers such as ``Work`` like this: ``<<list-links "[tag[Work]]">>`` • Why not use the tag ``Video games`` instead of ``recreation``? • Interesting use of ``Work`` tag to tag both places of employment (``Hannaford``), jobs (``front end associate``) as well as other aspects of working: ``number of years``, ``part time jobs`` etc. If we get to in class, we'll work with [[RenameTags]] as a demo...

You did a nice job building tiddlers. Love to see some images. Pay attention to the default tiddler; as you've got it set, the wiki reopens where you left off (which is a choice...). Most importantly, let's look at your tagging strategy. For example, you tag ``[[Grey Nisan Altima]]`` to ``[[Driving]]`` but then list it on ``[[Cars I have owned]]``. This works sort of for now, but will fail you in the next exercise. Similarly, the code for ``[[Jobs]]`` is ``<<list-links filter:"[tag[Job]]">>
`` which means that when you type ``<<tag Jobs>>`` in ''[[About Me in Tags]]`` it doesn't populate the tag pill.

√ ``About Me`` √ ``About Me in Tags``√ ``<<list-links>>`` macro. You got it! Nice colors :)

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -- implement in tiddlers such as ``activities`` like this: ``<<list-links "[tag[activities]]">>`` • I was hoping to see at least two (better, three) things associated (tagged) to each of your dimensions (tags); probably should have specified in instructions • (check [[GoogleForm for SharedWiki Submissions]] to see if your response has been received; no need to submit multiple entries)

It worked! • In future, check [[GoogleForm for SharedWiki Submissions]] to see if your response has been received; no need to submit multiple entries)

√ ``About Me`` √ ``About Me in Tags`` √ ``<<list-links>>`` macro. • (Sharon - nice to see you!)

√ ``About Me`` X ``About Me in Tags`` √ ``<<list-links>>`` macro • Add [[About Me in Tags]] to complete assignments • Naming wikis up to you - as you see, I just ingest from google form what you submit. 

√ ``About Me`` √ ``About Me in Tags`` X ``<<list-links>>`` macro -
 implement in tiddlers such as ``cars`` like this: ``<<list-links "[tag[cars]]">>`` • In future, check [[GoogleForm for SharedWiki Submissions]] to see if your response has been received; no need to submit multiple entries)

See [[critique|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-flinna-objects.html]] where I do some work with Aiicia's objects and weave them into a story.

[[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-houdea-objects.html]] extends your work a bit. Nice job.

Nice! See [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-furbecb-objects.html]] for ways to use your games template

Nice job. You wrote on dogs (which is fine) so all of the provided templates and lists worked flawlessly! No external crit wiki.

Nice job.  See [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-copelac-objects.html]] that discusses the implications of the 1:1 relationship you build between ``Meme`` and ``source``

excellent. see other critiques for demo of 2-stage listing process using ``[[each]]`` which could be applied to yours, like [[this one|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/smaccoll-objects.tiddlyspot.com]]

Very interesting. I'll be sure to review this in class. See the [[critique|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-dylan-objects1.tiddlyspot.com.html]] for some detail.

This looks pretty good, actually. A bit more work needed on the 2nd order filter, which is complicated. See [[Crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-cushinj-objects-critique.htm]]

see [[critique|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-bennink-objects.tiddlyspot.com.html]] to hopefully get you unlost

You noted that "length of tenure" was not an acceptable field name - but length-of-tenure would have worked fine • Because your field "years" was text instead of numeric, it sorts alpha not numerically • Template looks good! • Use the google group https://groups.google.com/forum/#!forum/designwrite for issues like not being able to save in TiddlySpot!

Good start. I did some work in [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-sommero-objects.html]] to illustrate what we could do with these fields.

See [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-maherr-narratives.tiddlyspot.com.html]] for suggestions

Works! (short step to more complexity, as shown in [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-hallensp-objects.html]].

Nice job! good reflection. see [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/smaccoll-objects.tiddlyspot.com.html]] for a demo...

Excellent! you got it...

See [[crit|http://people.sunyit.edu/~steve/dwit/tiddlywiki/critiques/sunypoly-retzket-objects.tiddlyspot.com.htm]] for some ideas; nicely done.

<<crit-link>> has some comments. Not 100% sure what you did; I should have asked for a journal.

See https://designwritestudio.updog.co/crits/shallenbeck-401.html

 for a crit of this exercise. I demo use of tabs, and ways to integrate annotations into an article that you just annotated using ``<$list>`` commands.

See <<crit-link>> for extensive comments, including ways of bibliographic entrys into multiple tiddlers, and ways of approaching an essay. Lots of good literature here, by the way.

See <<crit-link>> for some modifications. Like the way you are marking text with ``@@`` though this has its problems. Overall nice work.

<<crit-link>> shows some additional development, including a way to have two-way links between the text and the footnotes. Note new macro for handling footnotes.

https://designwritestudio.updog.co/crits/sunypoly-natarag-essay-myfirstwiki.tiddlyspot.com.html#crit

<<crit-link>> demos how to do a regexp search, and how to begin to gather text from annotations into a presentation.

See [[crit|http://sunypoly-critiques.updog.co/smacoll11.tiddlyspot.html]] for ideas of how to use code to illustrate annotations and to display references

Nice work. See my [[critique|https://sunypoly-critiques.updog.co/stachebrown.home.tiddlyspot.com.html]] where I demo some additional code to begin to make an essay...

See <<crit-link>> for some comments - nice job using two-level tabs.

[[DesignWriteStudio:Summer 2021]]

\define makeExportFilter2()
[prefix[$:/SharedWikisImporter]]
\end

! Doesn't quite work yet (19 Jan):


# To download tiddlers needed to import shared responses, ''choose one'' of the following:
#*  click this button <$macrocall $name="exportButton" exportFilter=<<makeExportFilter2>> lingoBase="$:/language/Buttons/ExportTiddler/" baseFilename=<<currentTiddler>>/>
#** or
#* Go to $:/AdvancedSearch and paste ``[prefix[$:/SharedWikisImporter]]`` in the filter tab
# Choose json and save the file.
# Go to your wiki
## Click on import in the Tools menu. 
## Import the tiddlers.
<hr>
These are the tiddlers involved:

<$list filter="[prefix[$:/SharedWikisImporter]]">
<$link><<currentTiddler>></$link><br>
</$list>

steve@sunyit.edu || http://designwritestudio.com

DesignWriteStudio

* ''Tiddler titles:'' <$radio  tiddler="$:/core/ui/ViewTemplate/title" field="tags" value="">Hide</$radio>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<$radio  tiddler="$:/core/ui/ViewTemplate/title" field="tags" value="$:/tags/ViewTemplate">Show</$radio>
* ''Tiddler subtitles:'' <$radio  tiddler="$:/core/ui/ViewTemplate/subtitle" field="tags" value="">Hide</$radio>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<$radio  tiddler="$:/core/ui/ViewTemplate/subtitle" field="tags" value="$:/tags/ViewTemplate">Show</$radio>
* ''Tiddler tags:'' <$radio  tiddler="$:/core/ui/ViewTemplate/tags" field="tags" value="">Hide</$radio>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<$radio  tiddler="$:/core/ui/ViewTemplate/tags" field="tags" value="$:/tags/ViewTemplate">Show</$radio>

<hr>

[img width="10px"[$:/_Icon/code-elements]] <small>''Tab source:'' [[$:/_Menu/Home/Configuration/Options]]</small>

<pre>
.stretch-closed {
  display:inline-block;
  padding: 0 3px 0 2px;
  margin:0px -2px 0 -1px;
  line-height:96%;
  background: none;
  border: 1px solid lightgray; 
/*  box-shadow: inset 0 0 5px #b3b3b3; */
  margin-right:2px; 
}

.stretch-open {
  display:inline-block;
  padding: 0px 3px; /*0 3*/
  margin:0 -2px;
  background:#f4f4f4;
  border: 1px solid transparent; border-bottom:1px solid silver;
}

.stretch-outline {
   display:inline-block;
/* box-shadow: inset 0 0 2px gray; */
   padding-right:2px; padding-left:0px; /*2*/
   -webkit-animation: revealoutline 3.5s ease 1 running;
   animation: revealoutline 3.5s ease 1 running;
   outline: solid 0px red; 
   outline-offset:1px;
/* margin-right:0px; */
}

@-webkit-keyframes revealoutline {
  0%  { outline: transparent solid 1px; }
  25.0%  { outline: silver solid 1px; }
  50.0%  { outline: silver solid 1px; }
  100.0%  { outline: transparent solid 1px; }
}
@keyframes revealoutline {
  0%  {outline: transparent solid 1px; }
  25.0%  { outline: silver solid 1px; }
  50.0%  { outline: silver solid 1px; }
  100.0%  { outline: transparent solid 1px; }
}

.stretch-open:hover + .stretch-outline { outline:silver solid 1px; }

.stretch-content { 
  padding: 0 0px; /*0 3 */
  white-space: pre-wrap; 
/*   margin-right:-6px;  -6 */
   -webkit-animation: revealcontent .4s ease 1 running;
   animation: revealcontent .4s ease 1 running;
   opacity:1;
}

@-webkit-keyframes revealcontent {
  0%  {opacity:0;} 100.0% {opacity:1;}
}
@keyframes revealcontent {
  0%  {opacity:0;} 100.0% {opacity:1;}
}

</pre>

\define cont() $(content)$

\define stretch(label, restornothing, content)
<$vars restornothing="""$restornothing$""" content="""$content$""">
<$set name="contentToReveal" filter="[<content>regexp[^$]]"
          value=<<restornothing>> emptyValue=<<content>>>
<$set name="rest" filter="[<content>regexp[^$]]"
          value="" emptyValue=<<restornothing>>>
<$set name="qualstate" value=<<qualify "$:/state/$label$">> >
   <$reveal type="nomatch" state=<<qualstate>> text="show" animate="yes">
      <$button set=<<qualstate>> setTo="show" class="stretch-closed" >
         <$list filter="[[$label$]splitbefore[_]removesuffix[_]] [[$label$]splitbefore[_]] +[first[]]" variable="lab"><<lab>></$list>
      </$button>"""<<rest>>"""
   </$reveal><$reveal type="match" state=<<qualstate>> text="show" animate="yes">
      <$button set=<<qualstate>> setTo="hide" class="stretch-open" >
         <$action-setfield $tiddler=<<qualstate>>/>
         <$list filter="[[$label$]splitbefore[_]removesuffix[_]] [[$label$]splitbefore[_]] +[first[]]" variable="lab"><<lab>></$list>
      </$button> """<<rest>>"""<span class="stretch-outline">
         <span class="stretch-content"><<contentToReveal>></span>
      </span></$reveal>
</$set>
</$set>
</$set>
</$vars>
\end

\define ref(content:"empty")
<$macrocall $name="strex" content="""$content$""" label="&#x200b;" start="start" end="&#x200b;" class="hint numbers"/> 
\end

\define strex(content:"TextStretch", label:"…", start:"[", end:"]", class:"", id:"_false_")
<$vars content="""$content$""" id="""$id$""">
<$set name="uid" filter="[<id>!prefix[_false_]]" value=<<id>> emptyValue=<<content>> >
<span class="strex-container $class$"><$macrocall $name="strexx" content=<<content>> label="""$label$""" start="""$start$""" end="""$end$""" class="""$class$""" uid=<<uid>>/></span>
</$set>
</$vars>
\end

\define strexx(content, label, start, end, class, uid)
<$set name="xuid" filter="[<uid>prefix[_false_]]" value="error: xuid hashing" emptyValue=<<HashStr """$uid$""">> >
<$macrocall $name="strexxx" content="""$content$""" label="""$label$""" start="""$start$""" end="""$end$""" class="""$class$""" xuid=<<xuid>>/>
</$set>
\end

\define strexxx(content, label, start, end, class, xuid)
<$vars content="""$content$""" label="""$label$""" start="""$start$""" end="""$end$""" class="""$class$""" xuid="""$xuid$""">
<$set name="qualstate" value=<<qualify "$:/state/strex_$xuid$_">> >
<$vars openclass="strex-open $class$" contentclass="strex-content $class$" startclass="strex-close strex-start $class$" endclass="strex-close strex-end $class$">
<$reveal type="nomatch" state=<<qualstate>> text="visible" animate="yes"><$button set=<<qualstate>> setTo="visible" class=<<openclass>> tooltip="show text part"><<label>></$button></$reveal><$reveal type="match" state=<<qualstate>> text="visible" animate="yes">
<span class="strex-all $class$"><span class="strex-inner $class$"><$button class=<<startclass>> tooltip="hide text part">$start$<$action-deletetiddler $tiddler=<<qualstate>>/></$button><span class=<<contentclass>> > <<content>> </span></span><$button class=<<endclass>> tooltip="hide text part">$end$<$action-deletetiddler $tiddler=<<qualstate>>/></$button></span></$reveal>
</$vars>
</$set>
</$vars>
\end

<!-- step 1 (x): check for id, replace with content if param is empty -->
<!-- step 2 (xx): hash id -->
<!-- step 3 (xxx): generate output, use state with hashed id -->

/* strex standard styling */

.strex-container, .strex-container .tc-reveal, .strex-all {
   position:relative;
}

.strex-open, .strex-start, .strex-end {
  color: <<colour tiddler-link-foreground>>;
  padding: 0 6px 3px 6px;
  line-height: 96%;
  background-color: #f0f0f0;
  border: 1px solid lightgray; 
}

.strex-open:hover, .strex-start:hover, .strex-end:hover {
  border: 1px solid black; 
}

.strex-open:active, .strex-start:active, .strex-end:active, 
.strex-open:focus, .strex-start:focus, .strex-end:focus {
  border: 1px solid lightgray; 
}

.strex-content .tc-reveal .strex-close {
  color: <<colour foreground>>;
}

.strex-content { 
  color: #c44;
  display:inline;
  -webkit-animation: expandtext 1s ease 0s running;
  animation-name: expandtext;
  animation-duration: 1s;
  animation-timing-function: ease;
  animation-delay: 0s;
  animation-iteration-count: 1;
  animation-direction: normal;
}
.strex-content .tc-reveal .strex-content { 
  color: #766;
}


/* * * * * * * * * * * *
** Footnotes with Numbers
* * * * * * * * * * * * */

body {
   counter-reset: notenr;  /* set counter to 0 */
}
div .tc-tiddler-frame {
   counter-reset: tidnotenr;
}
.strex-container.storynumbers {
   counter-increment: notenr; /* counter +1 */
}
.strex-container.numbers {
   counter-increment: tidnotenr;
}
button.strex-open.storynumbers::before, 
button.strex-start.storynumbers::before {
   content: counter(notenr); /* Display the counter */
   font-size: xx-small;
   vertical-align: top;
}
button.strex-end.storynumbers::after {
   content: counter(notenr);
   font-size: xx-small;
   vertical-align: top;
}
button.strex-open.numbers::before, 
button.strex-start.numbers::before {
   content: counter(tidnotenr);
}
button.strex-end.numbers::after {
   content: counter(tidnotenr);
}


/* Footer Collection as Numbered List `<ol>` */

.footnotes p ol {
    list-style-type: none;
    margin: 0;
    padding: 0;
    counter-reset: li-counter;
}

.footnotes p ol span > li {
   position: relative;
   margin-bottom: 0.6em;
   margin-left: 2.25rem;
   padding: 0.2em;
   background-color: <<colour sidebar-tab-background-selected>>;
   min-height: 2.1em;
}

.footnotes p ol span > li:before {
   position: absolute;
   top: 0;
   width: 1.75rem;
   height: 1.75rem;
   font-size: 0.75rem;
   line-height: 1;
   text-align: right;
   color: <<colour sidebar-tab-foreground>>;
   background-color: <<colour sidebar-tab-background>>;
   content: counter(li-counter);
   counter-increment: li-counter;
   padding: 0.1em 0.2em 0.2em 0.1em;
   margin-left: -2.5rem;
}


/* * * * * * * * * * * *
** Special Styles
* * * * * * * * * * * * */

/* hidden parts */

.strex-content.nocontent, .strex-start.nostart, .strex-end.noend, .strex-close.noclose {
  display: none;
}


/* standard text color */

.strex-content.standardcolor {
  color: <<colour foreground>>;
}

/* block */

.strex-content.block, .strex-inner.blockinner, 
.strex-container.blockcontainer {
   display: block;
}

/* hint */

.strex-inner.hint {
    position: absolute;
    min-width: 220px;
    background-color: rgb(252, 254, 211);
    border: 1px solid black;
    box-shadow: 5px 5px 10px #aaa;
    padding: 15px 13px 12px 15px;
    margin: 24px 0 0 -5px;
    z-index: 998;
}

.strexXX-inner.hint {
    display: block;
}
.strex-start.hint {
   letter-spacing: -0.5em;
   color: rgba(1,1,1,0) !important;
   background-color: transparent;
   border: 0;
   position: absolute;
   padding: 0 6px 3px;
   right: 10px;
   top: 5px;
}
.strex-inner.hint button::before {
   content: " &#215;";
   font-size: 1.2em;
   color: <<colour tiddler-link-foreground>>;
}
.strex-content.hint {
   padding-right: 10px;
}

/* note top right */

.strex-inner.note {
   background-color: rgb(252, 254, 211);
   border: 1px solid black;
   box-shadow: 5px 5px 10px #aaa;
   display: block;
   min-width: 220px;
   padding: 26px 10px 15px 15px;
   position: fixed;
   right: 5%;
   top: 5%;
   z-index: 998;
}
.strex-start.note {
   position: absolute;
   padding: 0 6px 3px;
   right: 5px;
   top: 5px;
}
.strex-content.note {
   padding-right: 10px;
}

/* note flex */

.strex-inner.noteflex {
   background-color: rgb(252, 254, 211);
   border: 1px solid black;
   box-shadow: 5px 5px 10px #aaa;
   display: flex;
   flex-flow: column wrap;
   min-width: 220px;
   padding: 10px 15px 15px 15px;
   position: fixed;
   right: 5%;
   top: 5%;
   z-index: 999;
   justify-content: center;
}
.strex-start.noteflex {
   display: flex;
   order: 2;
   margin: 10px auto 1px;
   order: 2;
   padding: 3px 10px 5px;
}
.strex-content.noteflex {
   display: flex;
   order: 1;
   margin-top: 8px;
   width: 100%;
}


/* * * * * * * * * * * *
** stretch animation
* * * * * * * * * * * * */

@keyframes expandtext {
  0% { 
      letter-spacing: -0.48em; 
      rotateY(88deg);
      opacity: 0;
  }
  70.0% {
      opacity: 0.35;
  }
  100.0% {
      letter-spacing: 0; 
      rotateY(0deg);
      opacity: 1;
  }
}

@-webkit-keyframes expandtext {
  0% { 
      letter-spacing: -0.48em; 
      rotateY(88deg);
      opacity: 0;
  }
  100.0% {
      letter-spacing: 0; 
      rotateY(0deg);
      opacity: 1;
  }
}

/*\
title: $:/core/modules/macros/HashStr.js
type: application/javascript
module-type: macro

Generate a numeric hash from a string
uses $:/core/modules/utils/utils.js
\*/

(function(){
   /*jslint node: true, browser: true */
   /*global $tw: false */
   "use strict";

/*
Information about this macro
*/
   exports.name = "HashStr";
   exports.params = [
      {name: "str"}
   ];

/*
Run the macro
*/
   exports.run = function(str) {
      var hash = $tw.utils.hashString(str);
      return hash;
   };
})();

Tabs for each primary section

0

Contents

no

tags

show

show

show

show

show

show

yes

yes

show

show

hide

$:/_ExcelImporter/ImportSpecifiers/Workbook 2

\define makeExportFilter()
[[$(currentTiddler)$]]
\end
<$macrocall $name="exportButton" exportFilter=<<makeExportFilter>> lingoBase="$:/language/Buttons/ExportTiddler/" baseFilename=<<currentTiddler>>/>

\define config-title()
$:/config/ViewToolbarButtons/Visibility/$(listItem)$
\end
<$button popup=<<qualify "$:/state/popup/more">> tooltip={{$:/language/Buttons/More/Hint}} aria-label={{$:/language/Buttons/More/Caption}} class=<<tv-config-toolbar-class>> selectedClass="tc-selected">
<$list filter="[<tv-config-toolbar-icons>prefix[yes]]">
{{$:/core/images/down-arrow}}
</$list>
<$list filter="[<tv-config-toolbar-text>prefix[yes]]">
<span class="tc-btn-text"><$text text={{$:/language/Buttons/More/Caption}}/></span>
</$list>
</$button><$reveal state=<<qualify "$:/state/popup/more">> type="popup" position="below" animate="yes">

<div class="tc-drop-down">

<$set name="tv-config-toolbar-icons" value="yes">

<$set name="tv-config-toolbar-text" value="yes">

<$set name="tv-config-toolbar-class" value="tc-btn-invisible">

<$list filter="[all[shadows+tiddlers]tag[$:/tags/ViewToolbar]!has[draft.of]] -[[$:/core/ui/Buttons/more-tiddler-actions]]" variable="listItem">

<$reveal type="match" state=<<config-title>> text="hide">

<$transclude tiddler=<<listItem>> mode="inline"/>

</$reveal>

</$list>

</$set>

</$set>

</$set>

</div>

</$reveal>

<span class="tc-tag-list-item">
<$set name="transclusion" value=<<currentTiddler>>>
<!--
<$macrocall $name="tag-pill-body" tag=<<currentTiddler>> icon={{!!icon}} colour={{!!color}} palette={{$:/palette}} element-tag="""$button""" element-attributes="""popup=<<qualify "$:/state/popup/tag">>
dragFilter='[all[current]tagging[]]' tag='span'"""/>
 -->
<$link to=<<currentTiddler>>><<currentTiddler>></$link>
<$reveal state=<<qualify "$:/state/popup/tag">> type="popup" position="below" animate="yes" class="tc-drop-down">
<$transclude tiddler="$:/core/ui/ListItemTemplate"/>
<$list filter="[all[shadows+tiddlers]tag[$:/tags/TagDropdown]!has[draft.of]]" variable="listItem"> 
<$transclude tiddler=<<listItem>>/> 
</$list>
<hr>
<$macrocall $name="list-tagged-draggable" tag=<<currentTiddler>>/>
</$reveal>
</$set>
</span>

<$list filter={{$:/core/Filters/Missing!!filter}} template="$:/core/ui/MissingTemplate"/>

<div class="tc-more-sidebar">
<<tabs "[all[shadows+tiddlers]tag[$:/tags/MoreSideBar]!has[draft.of]]" "$:/core/ui/MoreSideBar/Tags" "$:/state/tab/moresidebar" "tc-vertical">>
</div>

\define lingo-base() $:/language/CloseAll/

\define drop-actions()
<$action-listops $tiddler="$:/StoryList" $subfilter="+[insertbefore:currentTiddler<actionTiddler>]"/>
\end

<$list filter="[list[$:/StoryList]]" history="$:/HistoryList" storyview="pop">
<div style="position: relative;">
<$droppable actions=<<drop-actions>>>
<div class="tc-droppable-placeholder">
&nbsp;
</div>
<div>
<$button message="tm-close-tiddler" tooltip={{$:/language/Buttons/Close/Hint}} aria-label={{$:/language/Buttons/Close/Caption}} class="tc-btn-invisible tc-btn-mini">&times;</$button> <$link to={{!!title}}><$view field="title"/></$link>
</div>
</$droppable>
</div>
</$list>
<$tiddler tiddler="">
<$droppable actions=<<drop-actions>>>
<div class="tc-droppable-placeholder">
&nbsp;
</div>
<$button message="tm-close-all-tiddlers" class="tc-btn-invisible tc-btn-mini"><<lingo Button>></$button>
</$droppable>
</$tiddler>

<$macrocall $name="timeline" format={{$:/language/RecentChanges/DateFormat}}/>

\define lingo-base() $:/language/ControlPanel/
\define config-title()
$:/config/PageControlButtons/Visibility/$(listItem)$
\end

<<lingo Basics/Version/Prompt>> <<version>>

<$set name="tv-config-toolbar-icons" value="yes">

<$set name="tv-config-toolbar-text" value="yes">

<$set name="tv-config-toolbar-class" value="">

<$list filter="[all[shadows+tiddlers]tag[$:/tags/PageControls]!has[draft.of]]" variable="listItem">

<div style="position:relative;">

<$checkbox tiddler=<<config-title>> field="text" checked="show" unchecked="hide" default="show"/> <$transclude tiddler=<<listItem>>/> <i class="tc-muted"><$transclude tiddler=<<listItem>> field="description"/></i>

</div>

</$list>

</$set>

</$set>

</$set>

{{GoogleGroup}} {{Share}}{{ZoomRoom}} <!--<<tag "Days">><<tag "Projects">><<tag More>>-->{{$:/core/ui/Buttons/home}}
<$reveal state="$:/state/sidebar" type="nomatch" text="no">
<$button set="$:/state/sidebar" setTo="no" tooltip={{$:/language/Buttons/HideSideBar/Hint}} aria-label={{$:/language/Buttons/HideSideBar/Caption}} class="tc-btn-invisible">{{$:/core/images/chevron-right}}</$button>
</$reveal>
<$reveal state="$:/state/sidebar" type="match" text="no">
<$button set="$:/state/sidebar" setTo="yes" tooltip={{$:/language/Buttons/ShowSideBar/Hint}} aria-label={{$:/language/Buttons/ShowSideBar/Caption}} class="tc-btn-invisible">{{$:/core/images/chevron-left}}</$button>
</$reveal>

\define frame-classes()
tc-tiddler-frame tc-tiddler-view-frame $(missingTiddlerClass)$ $(shadowTiddlerClass)$ $(systemTiddlerClass)$ $(tiddlerTagClasses)$
\end
\define frame-styles()
background-color: $(backgroundColour)$;
border-color: $(backgroundColour)$;
\end
<$set name="storyTiddler" value=<<currentTiddler>>><$set name="tiddlerInfoState" value=<<qualify "$:/state/popup/tiddler-info">>><$set name="backgroundColour" value={{!!background-color}}><$tiddler tiddler=<<currentTiddler>>><div class=<<frame-classes>> style=<<frame-styles>>><$list filter="[all[shadows+tiddlers]tag[$:/tags/ViewTemplate]!has[draft.of]]" variable="listItem"><$transclude tiddler=<<listItem>>/></$list>
</div>
</$tiddler></$set></$set></$set>

<div class="tc-next" style="margin-left:-30px;margin-top:-20px;">
<<endslideshow>>
</div>

<div class="tc-next" style="margin-left:-30px;margin-top:-30px;">

<$list filter="[all[current]next[$:/StoryList]]">

<$link to={{!!title}}>

{{$:/core/images/down-arrow}}

</$link>

</$list>

</div>

<div class="tc-next" style="margin-left:-30px;margin-top:-30px;">

<$list filter="[all[current]previous[$:/StoryList]]">

<$link to={{!!title}}>

{{$:/core/images/up-arrow}}

</$link>

</$list>

</div>

Illustration 13b

DesignWriteStudio

Appears and tabs for each primary section

Designing

Tue Jan16

Vmxkd1NrNVhVbk5pTTJ4c1VqTm9WRlJVUW5kTmJIQkhZVVZLVVZWVU1Eaz0=

<svg class="tc-image-fold tc-image-button" width="22pt" height="22pt" viewBox="0 0 128 128">
<!--source view-source of https://upload.wikimedia.org/wikipedia/commons/d/d4/Share_font_awesome.svg-->
<svg
   xmlns:dc="http://purl.org/dc/elements/1.1/"
   xmlns:cc="http://creativecommons.org/ns#"
   xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
   xmlns:svg="http://www.w3.org/2000/svg"
   xmlns="http://www.w3.org/2000/svg"
   xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
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   id="svg2"
   version="1.1"
   inkscape:version="0.48.3.1 r9886"
   width="100%"
   height="100%"
   sodipodi:docname="share_font_awesome.svg">
  <metadata
     id="metadata12">
    <rdf:RDF>
      <cc:Work
         rdf:about="">
        <dc:format>image/svg+xml</dc:format>
        <dc:type
           rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
      </cc:Work>
    </rdf:RDF>
  </metadata>
  <defs
     id="defs10" />
  <sodipodi:namedview
     pagecolor="#ffffff"
     bordercolor="#666666"
     borderopacity="1"
     objecttolerance="10"
     gridtolerance="10"
     guidetolerance="10"
     inkscape:pageopacity="0"
     inkscape:pageshadow="2"
     inkscape:window-width="640"
     inkscape:window-height="480"
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

Hello There

Designing and Writing Interactive Texts

Draft of 'Creating a self-designed exercise'

Hello There

$:/palettes/DWS

alert-background: #ffe476
alert-border: #b99e2f
alert-highlight: #881122
alert-muted-foreground: #b99e2f
background: #ffffff
blockquote-bar: <<colour muted-foreground>>
button-background: 
button-foreground: 
button-border: 
code-background: #f7f7f9
code-border: #e1e1e8
code-foreground: #dd1144
dirty-indicator: #ff0000
download-background: #66cccc
download-foreground: <<colour background>>
dragger-background: <<colour foreground>>
dragger-foreground: <<colour background>>
dropdown-background: <<colour background>>
dropdown-border: <<colour muted-foreground>>
dropdown-tab-background-selected: #fff
dropdown-tab-background: #ececec
dropzone-background: rgba(0,200,0,0.7)
external-link-background-hover: inherit
external-link-background-visited: inherit
external-link-background: inherit
external-link-foreground-hover: inherit
external-link-foreground-visited: #0000aa
external-link-foreground: #0000ee
foreground: #333333
message-background: #ecf2ff
message-border: #cfd6e6
message-foreground: #547599
modal-backdrop: <<colour foreground>>
modal-background: <<colour background>>
modal-border: #999999
modal-footer-background: #f5f5f5
modal-footer-border: #dddddd
modal-header-border: #eeeeee
muted-foreground: #999999
notification-background: #ffffdd
notification-border: #999999
page-background: #ffffff
pre-background: #f5f5f5
pre-border: #cccccc
primary: #7897f3
sidebar-button-foreground: <<colour foreground>>
sidebar-controls-foreground-hover: #000000
sidebar-controls-foreground: #ccc
sidebar-foreground-shadow: rgba(255,255,255, 0.8)
sidebar-foreground: #acacac
sidebar-muted-foreground-hover: #444444
sidebar-muted-foreground: #c0c0c0
sidebar-tab-background-selected: #fec26e
sidebar-tab-background: <<colour tab-background>>
sidebar-tab-border-selected: <<colour tab-border-selected>>
sidebar-tab-border: <<colour tab-border>>
sidebar-tab-divider: <<colour tab-divider>>
sidebar-tab-foreground-selected: 
sidebar-tab-foreground: <<colour tab-foreground>>
sidebar-tiddler-link-foreground-hover: #444444
sidebar-tiddler-link-foreground: #7897f3
site-title-foreground: <<colour tiddler-title-foreground>>
static-alert-foreground: #aaaaaa
tab-background-selected: #ecb535
tab-background: #f2e7c9
tab-border-selected: #e6a82a
tab-border: #7d95f2
tab-divider: #d8d8d8
tab-foreground-selected: #000
tab-foreground: #000
table-border: #dddddd
table-footer-background: #a8a8a8
table-header-background: #f0f0f0
tag-background: #ffeedd
tag-foreground: #000
tiddler-background: <<colour background>>
tiddler-border: #eee
tiddler-controls-foreground-hover: #888888
tiddler-controls-foreground-selected: #444444
tiddler-controls-foreground: #cccccc
tiddler-editor-background: #f8f8f8
tiddler-editor-border-image: #ffffff
tiddler-editor-border: #cccccc
tiddler-editor-fields-even: #e0e8e0
tiddler-editor-fields-odd: #f0f4f0
tiddler-info-background: #f8f8f8
tiddler-info-border: #dddddd
tiddler-info-tab-background: #f8f8f8
tiddler-link-background: <<colour background>>
tiddler-link-foreground: <<colour primary>>
tiddler-subtitle-foreground: #c0c0c0
tiddler-title-foreground: #ff9900
toolbar-new-button: 
toolbar-options-button: 
toolbar-save-button: 
toolbar-info-button: 
toolbar-edit-button: 
toolbar-close-button: 
toolbar-delete-button: 
toolbar-cancel-button: 
toolbar-done-button: 
untagged-background: #999999
very-muted-foreground: #888888
1: #DEFF65
2: #FF62f9
3: #FF7575
4: #5AD3FF
5: #A7FF7B
6: #DEFF65
7: #FF62f9
8: #FF7575
9: #5AD3FF
10: #A7FF7B
11: #FF62f9
12: #FF9563
13: #FF7575
14: #5AD3FF
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Creating a self-designed exercise

{
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            "text": "\\define annotate($from-tiddler$)\n<$action-sendmessage $message=\"tm-new-tiddler\" tags=\"Annotation $from-tiddler$\" from-tiddler=\"$from-tiddler$\"/>\n\\end\n\n\n\\define annotation-nav(essay paragraph)\n<$set name=essay value=<<essay>>>\n<$set name=paragraph value=<<paragraph>>>\n<$button>\n<<essay>>\n<$action-navigate $to=<<essay>>/>\n</$button>\nParagraph <$count filter=\"[list<essay>allbefore:include<paragraph>]\"/> of <$count filter=\"[list<essay>]\"/> ||\n<$list filter=\"[list<currentTiddler>first[]]\">\n<$link to=<<currentTiddler>>>First</$link> ||\n</$list>\n<$list filter=\"[list<essay>before<paragraph>]\">\n<$link to=<<currentTiddler>>>Previous</$link> ||\n</$list>\n<$list filter=\"[list<essay>after<paragraph>]\">\n<$link to=<<currentTiddler>>>Next</$link> ||\n</$list>\n<$list filter=\"[list<currentTiddler>last[]]\">\n<$link to=<<currentTiddler>>>Last</$link> \n</$list>\n</$set>\n</$set>\n\\end\n\n\n\n<$list filter=\"[is[current]field:toc-type[paragraph]]\">\n<!--show the annotator-nav bar-->\n<$set name=\"paragraph\" value=<<currentTiddler>> >\n<!--fetch the name of the essay to which this paragraph belongs-->\n<$list filter=\"[<currentTiddler>listed[]field:toc-type[heading]]\">\n<$set name=\"essay\" value=<<currentTiddler>> >\n<$macrocall $name=\"annotation-nav\" essay=<<essay>> paragraph=<<paragraph>>/>\n<br>\n<$button>\n<$macrocall $name=\"annotate\" from-tiddler=<<paragraph>>/>\nNew Annotation of <<paragraph>>\n</$button>\n<ul>\n<$list filter=\"[tag<paragraph>]\">\n<li>Annotation: <$link><<currentTiddler>></$link></li>\n</$list>\n</ul>\n</$set>\n</$list>\n</$set>\n</$list>\n\n\n\n\n",
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            "title": "Paragraph Template",
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        "Essay Template": {
            "text": "<$list filter=\"[is[current]field:toc-type[heading]]\">\n<$macrocall $name=\"essay-nav-first\" essay=<<currentTiddler>>/><br>\n\n<$list filter=\"[list<currentTiddler>]\">\n<$set name=\"paragraph\" value=<<currentTiddler>> >\n<!--generate an annotate button-->\n<$macrocall $name=\"newhere-annotate\" from-tiddler=<<paragraph>>/>\n<$link><<currentTiddler>></$link>\n<$transclude/>\n<!--show the annotation-->\n<$macrocall $name=\"show-annotation\" of-tiddler=<<paragraph>>/>\n<hr>\n\n",
            "type": "text/vnd.tiddlywiki",
            "title": "Essay Template",
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            "revision": "0",
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        },
        "8.1": {
            "text": "Unlike hieroglyphic writing, whose pictographic component gives it a visual,\nspectacular aspect, alphabetic writing was conceived as a transcription of\nspeech and was from its inception associated with the linearity of orality. This\nlinearity is aptly symbolized in the arrangement used in early Greek writing, in\nwhich the characters in the first line were aligned from left to right, and those\nin the next line, from right to left, with the characters sometimes inverted,\nimitating the path of a plow working a field, a metaphor that gave this type of\nwriting its name: houstrophedon.1 Readers were supposed to follow with their\neyes the uninterrupted movement the hand of the scribe had traced.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.1",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145326998",
            "created": "20170420145051618",
            "bag": "default"
        },
        "8.10": {
            "text": "This incunabulum from Thomas Aquinas’s Summa Theologica, printed in 1477 in Venice,\nfollows the manuscript tradition. The decorated initials and paragraph marks are hand—\ndrawn. The first lines are in larger letters. There is no pagination. The layout of the text in\ntwo columns and its organization in the form of questions and answers, however, make\nit very readable. The illuminations are intensely symbolic. The first page (bottom left) is\nillustrated with an image that depicts the teaching of Thomas Aquinas. At the base of the\ncolumn, an image depicts the reception of the work by angels (bottom right).",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.10",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145601215",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.11": {
            "text": "In the fifteenth century, the printing revolution was another time of in-\ntense reflection on the organization of the book. Febvre and Martin8 note\nthat the title page made its appearance—finally!——around 1480. After the\ninfancy of the modern book, the period of incunahula—books that imitated\nmanuscripts as faithfully as possible—printers quickly saw the full potential\nof the page as a discrete semiotic space.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.11",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145608307",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.12": {
            "text": "Page numbering, which became common in the mid-sixteenth century,\nenabled readers to better control the duration and pace of their reading and\nfacilitated the discussion of texts by making it possible for readers of the same\nedition to refer to the same passage. Once this step was taken, the move-\nment toward tabularization intensified, and sophisticated techniques allowing\nmultiple points of entry into the text became widely used, such as paragraph\nsummaries in the margin and the running head. It was now possible for\nreaders to precisely locate the point they had reached in their reading and to\ncompare the relative size of different sections—in short, to control their read-\ning progress. They could also forget the details of what they had read earlier,\nsince they could quickly find them again by referring to a table of contents\nor index. They could read only the parts of a book that interested them.\nEspecially if a book is long, readers often construct the meaning on the\nbasis of clues of various types. Typographical markers such as bold, capitals,\nitalics, or color allow them to quickly classify the elements they read and to\navoid ambiguity; for example, the italicization of foreign words prevents con-\nfusion with homonyms. When justified by the material, an index of proper\nnames, a detailed index, or a bibliography permits readers to choose the way\nof accessing the text that best suits their information needs of the moment.\nThese reading aids did not come into use all at once but were slowly refined,\nin a process that culminated in the golden age of print in the nineteenth cen-\ntury, when the progress of mechanization heralded the triumph of the printed\npage. The table of contents, for example, appeared in the twelfth century. The\nparagraph break, the concept of which had been expressed through the use\nof the pilcrow in manuscripts of the eleventh century, was finally indicated\nby a line break, as seen in an edition of Gargantua printed in Lyon in 1537.\nThus shaped by the ergonomics of the codex, the text was no longer a linear\nthread that was unreeled, but a surface whose content could be perceived from\nvarious perspectives. These reading aids, which allow readers to consider the\ntext the same way they look at a painting or tableau, are here called tabular.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.12",
            "tags": "Annotator",
            "revision": "0",
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            "created": "20170420145051619",
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        },
        "8.13": {
            "text": "With the introduction of printing, the art of publishing fluctuated between\nthe temptations of textual continuity and those of pictorial page layout. On\nthe one hand, an austere layout in which the text was rigidly aligned within\nthe frame of the page was best for emphasizing the mechanical perfection of\nprinting and the linear aspect of language and reading; on the other hand,\npublishers could also be tempted by a complex layout in which the text was\npresented in different visual blocks among which readers could pick and\nchoose as they wished, exploring their relationships in nonsequential order.\nThese fluctuations in the ideal of the book can be observed across different\nperiods. In this regard, it is informative to compare some of the printing\nmanuals studied by the typography expert Fernand Baudin. A manual pub-\nlished by the printer Fertel in 1723, entitled La science pratique de l’imprimerie,\nis a model of complex layout in which marginal glosses sometimes spill over\ninto the space of the main text. In contrast, a manual published forty years\nlater, written by Fournier, presents the text in a single, rather narrow column\nand seems to have gone back to the linear order. As for the book by Baudin,\nwho was himself a typ ographer and wished to give an account of an art that\nwas the passion of his life, it is in large format, with a column of glosses and\ncross-references systematically running down one side of the main column\nand sometimes even framing it, as Fertel’s glosses do.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.13",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145623367",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.15": {
            "text": "For Walter Ong, this segmentation shows that reading did not focus on\nthe visual aspect of the words grasped globally, but was still based on oral\npractices; the presentation of the text was independent of its semantic aspect.\nIt is also likely that such practices involved a kind of playful allusion to a way\nof reading that was already seen as outmoded.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.15",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145639921",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.14": {
            "text": "The challenge of printed text, in short, is to strike a balance between se-\nmantic and visual demands, the ideal obviously being a combination of these\ntwo modes of access to the text around a coherent focus. We can still ob—\nserve the naive triumph of the visual over the semantic in even the titles of\nsixteenth-century books, in which printers did not hesitate to cut out words\nin order to create a symmetrical effect.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.14",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145631402",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.16": {
            "text": "Today, publishers make such effort to enable the reader to perceive com~\nplete words that they sometimes hesitate to break a word at the end of a line,\nand thus to use justified text, although that was the typographical ideal for\ncenturies, beginning in the time of the volumen. This concern with match\ning the semantic unit with the unit of visual perception is also evident in\nmagazines, which tend increasingly to make the text of articles fit into the\nspace of the page or double page.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.16",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145648917",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.17": {
            "text": "It is now commonly acknowledged that the revolution of the codex was\nnot limited to ergonomics, but that it also had an impact on the nature of\ncontent and the evolution of mentalities in general. Indeed, once a text is\nperceived as a visual entity, and no longer as primarily oral, it lends itself\nmuch more readily to criticism. The eye, given the richness of optic nerve\nendings in the cortex, can mobilize the analytical faculties more easily and\nmore precisely than the ear. As historian Henri-Jean Martin notes on the\nrevolution of printing in the sixteenth century: “By the same token, any\nreasoned argument was as if detached from the realms of God and men and\ntook on an objective existence. The written text became amoral because it\ndetached from the writing process and no longer demanded that the reader\ntake on responsibility for it by reading it aloud. This may have facilitated\nheretical propositions.”",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.17",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145657081",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.18": {
            "text": "The process by which the text became an autonomous object crossed a new\nthreshold during the Enlightenment, when the last barriers to its generali-\nzed objectification collapsed. That era coincided precisely with spectacular\ngrowth in reading in Europe. We will come back to this question.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.18",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145704994",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.19": {
            "text": "With the advent of newspapers and the mass-circulation press, which\nunderwent rapid expansion in the nineteenth century, the formatting of\ntext became even more tabular. In a radical departure from the original\nlinearity of speech, text was now presented in the form of visual blocks that\ncomplemented and responded to each other on the eye-catching surface of\nthe page. McLuhan gave a name to the metaphor implicit in this arrange—\nment: the “mosaic” text. Indeed, newspapers provide a textual mosaic, in\nwhich the reading of various types of information is subtly influenced by the\nsurrounding news, as has been pointed out by analysts of newspaper layout:\n“For about a century, newspapers have been laid out in such a way that each\nitem of information, though flat on the page, stands out by virtue of the mere\nfact of its coexistence with other items of information on the page, which\nin turn acquire their value from this competition? ’1” The same authors note\nthat until the end of the nineteenth century, newspapers consisted simply\nof vertically aligned columns, each of which theoretically constituted a page\nthat went on without interruption. “This type of layout naturally favored a\ntemporal sequence of discourse: there were no interruptions for turning\npages, no illustrations to create a break or suspension of reading, and no\nlead or subheading introducing secondary material. This form corresponds\nexactly to the temporal logic of discourse: It is the presentation of logos in\nmovement, and not the staging of an event.”11",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.19",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145714420",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.2": {
            "text": "Orality thus extended its influence over the medium of text. The scribe\nlined up columns of text on sheets of papyrus—which had been in use since\n3000 BCE—until he came to the end of the scroll. Despite the characteristics\nthat made the papyrus scroll the quintessential book for three millennia, the\nfact that it was rolled up into a volumen placed serious limitations on the\nexpansion of writing and helped maintain the book’s dependence on oral\nlanguage. It was taken for granted that readers would read from the first line\nto the last and that they had no choice but to immerse themselves in the text,\nunrolling the volumen as a storyteller recounts a story in a strictly linear con—\ntinuous order. In addition, readers needed both hands to unroll the papyrus,\nwhich made it impossible to take notes or annotate the text. Worse still, as\nMartial observed, readers would often have to use their chin when rerolling\nthe volumen, leaving marks on the edge that were rather off-putting to other\nlibrary users (“Sic noua nec mento sordida charta iuuat” [“How pleasant is\na new exemplar unsoiled by chins”] .2",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.2",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145435762",
            "created": "20170420145051618",
            "bag": "default"
        },
        "8.20": {
            "text": "The sudden appearance of banner headlines was the beginning of a new\nkind of layout, one'no longer guided by the logic of discourse, but by a spa-\ntial logic. “The number of columns, the use of rules, the weight of the type,\nthe font, the position of illustrations, and the use of color make it possible\nto bring together or move apart, to select, and to separate the units that, in\nthe newspaper, are units of information. Layout then emerges as a rheto-\nric of space that destructures the order of discourse (its temporal logic) to\nreconstitute an original discourse, which is precisely the discourse of the\nnewspaper.”12",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.20",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145722830",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.21": {
            "text": "Today, there is no doubt that tabularity meets the formatting requirements\nof information texts in that it allows the reader to apprehend them most\neffectively. This is especially apparent in magazines, where the dominant\nmodel involves framing textual material by means of a hierarchy of titles:\nsection heading, main heading and subheadings. A more substantial article\nwill often be presented in the form of a feature story that, in addition to the\nmain text, includes one or more sidebars elaborating on points raised in the\nmain text. Such fragmented layouts are sometimes criticized. Their primary\nfunction is clearly to hold on to readers whose attention span is unsteady or\nshort, unlike a linear format, which is intended for the “serious reader.” This\nway of breaking up text into different elements is also very well suited for\ncommunicating a variety of information that readers can select according\nto their interests. On the other hand, popular magazines may diverge a bit\nfrom this ideal and give predominance to glossy ads and photographs in or—\nder to entice the reader to leaf through their pages and absorb the discourse\nof advertising.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.21",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145729589",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.22": {
            "text": "When tabularity is taken into account, then, printed text is not exclusively\nlinear and tends to incorporate characteristics of the visual realm. Readers\nare thus able to free themselves from the thread of the text and go directly\nto relevant elements. A book may thus be said to be tabular when it involves\nthe simultaneous spatial presentation and highlighting of various elements\nthat may help readers identify the connections and find information that\ninterests them as quickly as possible.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.22",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145737474",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.23": {
            "text": "The concept of tabularity thus covers at least two distinct phenomena—4n\naddition to designating an internal arrangement of data. On the one hand,\nit refers to the various organizational means that facilitate access to the con—\ntent of the text: This is functional tabularity, as shown in tables of contents,\nindexes, and division into chapters and paragraphs. On the other hand,\ntabularity also suggests that the page may be viewed in the same way as a\npainting and may include data from various hierarchical levels: This is visual\ntabularity, which enables readers to switch from reading the main text to\nreading notes, glosses, figures, or illustrations, all of which are present within\nthe space of the double page. This visual tabularity, which is seen primarily\nin newspapers and magazines, is also found in varying degrees in scholarly\nbooks, which may present various types of text juxtaposed on a single page.\nIt is obviously highly developed in electronic publishing, as seen on the\nWeb pages of major newspapers, magazines, and encyclopedias. In addi-\ntion, through a hybridization of publishing techniques, the layout of books\nor magazines increasingly borrows from the methods of electronic publish—\ning, such as the use of color, underlining, and marking of text elements, with\ncross-references to thumbnails or sidebars. In this type of tabularity, the text\nis shaped like visual material, with blocks referring to each other on the page\nsurface and sometimes incorporating illustrations.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.23",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145745438",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.24": {
            "text": "The spatial projection of the thread of the text obviously depends on the\nformat of the book. The smaller the book, the less manipulation of the visual\nblocks is possible; readers are confined to a continuous movement through a\nsingle column of text with no interruption. This format, which was adopted,\nfor example, by the famous French collection Bibliotheque de la Pléiade, tends\nto reinforce the ideal of a linear typography with nothing to break its regular-\nity. It is especially well suited to novels, which are read for content. National\ntraditions prevent French publishers from placing the table of contents at\nthe front of the book as it is in the English-speaking world, a position better\nsuited to the tabular ideal and to readers’ needs.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.24",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145758051",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.25": {
            "text": "It should be added, however, that the degree of tabularity of a book will\nalso depend on its content and intended use. Thus, children’s books often do\nnot have page numbers: young readers have no need for them, since these\nbooks are designed to be read or looked at from cover to cover and there is\nno expectation of a reflective reading with note taking or references. Schol-\narly books, which are intended for readers for whom time is valuable, have\nmany tabular guideposts: volumes, chapters, sections, paragraphs, headers,\nnotes, introductory summaries, detailed index, index of proper names, and\nbibliography. But the linear thread may still be a justifiable choice for devel-\noping an argument, insofar as the author wishes to ensure that the reader\nfollows the entire proof. On the other hand, the novel, which is derived from\nthe ancient art of the storyteller, generally demands sustained reading and\ndoes not require elaborate tabular clues. The large number of chapters and\nthe hierarchy of sections in Victor Hugo’s novels, which often have a very\nlinear narrative thread, may be explained by the fact that these novels were\ninitially published in serial form in newspapers. Today, some writers, anxious\nto make their readers read continuously and to have their work seen as high\nliterature, as different as possible from the tabular format of the magazine,\ndispense altogether with chapters, and even paragraphs and punctuation.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.25",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145805616",
            "created": "20170420145051620",
            "bag": "default"
        },
        "8.3": {
            "text": "The advent of the codex was a radical break with this old order, and it\nbrought about a revolution in the reader’s relationship to the text. A codex\nconsists of pages folded and bound to form what we today call a book. These\npages were made of papyrus or parchmentmpaper having appeared in Eu-\nrope only in the 11005. The codex emerged in classical Rome, several decades\nbefore the Common Era, at the time of Horace, who used one himself as a\nnotebook. Smaller and easier to handle than a scroll, the codex was also more\neconomical, because it allowed scribes to write on both sides and even to\nscrape off the surface and write on it again. But because of its antiquity, the\nscroll was still considered to have greater dignity and was preferred by the\ncultured elite, a status the codex did not acquire for several centuries. The\ntransition really took place only in the fourth century in the Roman Empire.\nAnd it took even longer for the new medium to free itself from the model of\nthe volumenfljust as it took the automobile several decades to completely\nrid itself of the model of the horse-drawn carriage. Such is the inertia of\ndominant cultural representations.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.3",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145444057",
            "created": "20170420145051618",
            "bag": "default"
        },
        "8.4": {
            "text": "Christians were the first to adopt the codex, which they used to spread the\nGospels. The new format, which was smaller, more compact, and easier to\nhide and to handle than the scroll, also had the advantage of representing a\nsharp break with the tradition of the Jewish Bible. Historians find more and\nmore evidence that the latter reason was in part responsible for the choice\nof the codex format by the Christians, but the wide adoption of the codex\nover the following centuries was essentially due to “the twin advantages of\ncomprehensiveness and convenience.”",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.4",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145454927",
            "created": "20170420145051618",
            "bag": "default"
        },
        "8.5": {
            "text": "The new element the codex introduced into the economy of the book was\nthe page. I will look at the problem of the integration of this important in-\nnovation into the digital order in the section “The End of the Page? [chapter\n34]” It was the page that made it possible for text to break away from the\ncontinuity and linearity of the scroll and allowed it to be much more easily\nmanipulated. Over the course of a slow but irreversible evolution, the page\nmade text part of the tabular order.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.5",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145503381",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.6": {
            "text": "The codex is the quintessential book, without which the pursuit and dis-\nsemination of knowledge in our civilization could not have developed as fully\nas they have. The codex gave rise to a new relationship between reader and\ntext. As one historian of the book writes, “This was a crucial development\nin the history of the book, perhaps even more important than that brought\nabout by Gutenberg, because it modified the form of the book and required '\nreaders to completely change their physical position.”4 The codex left one\nof the reader’s hands free, allowing him or her to take part in the cycle of\nwriting by making annotations, thus becoming more than a mere recipient\nof the text. Readers could also now access the text directly at any point. A\nbookmark let them take up reading where they left off, further altering their\nrelationship to the text. As another historian notes, it took “twenty centuries\nfor us to realize that the fundamental importance of the codex for our civili-\nzation was to enable selective, noncontinuous reading, thus contributing to\nthe development of mental structures in which the text is dissociated from\nspeech and its rhythms.”5",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.6",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145517200",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.7": {
            "text": "When the potential of this union of form and content in the page became\napparent, various types of visual markers were gradually added to the organi-\nzation of the book to help readers find their bearings more easily in the mass\nof text and make reading easier and more efficient. Since the page constitutes\na visual unit of information related to the preceding and the following pages,\nallowing it to be numbered and given a header, it has an autonomy that the\ncolumn of text in the volumen did not. Thanks to the page, it is possible to leaf\nthrough a book and quickly know its contents, or at least the essentials.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.7",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145535927",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.8": {
            "text": "The page can be displayed for all to see, inviting monks in scriptoria to\ncombine text and images. While the papyrus was rolled up again after read-\ning, the codex can remain open to a double page, as demonstrated by the big\npsalters of the Middle Ages that were displayed on their lecterns in churches.\nThe page was thus the place where the text, which was previously seen as a\nmere transcription of the voice, entered the visual order. From then on, it\nwould increasingly be handled like a painting and enriched with illumina-\ntions, something that was profoundly foreign to the papyrus scroll. One can-\nnot see these illuminated manuscripts without being struck by their fusion of\nletter and image. Reading becomes a polysemiotic experience in which the\nperception of the image, which is far from a mere illustration, enables readers\nto recreate in their own mental space the tensions and emotions experienced\nby the artist. The readable gradually moves into the realm of the visible.6",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.8",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145541799",
            "created": "20170420145051619",
            "bag": "default"
        },
        "8.9": {
            "text": "The sight of the codex open on its lectern is emblematic of a religion whose\nideal was that all people should be able to read the sacred texts and share the\nRevelation. Various other innovations gave rise to a change in the reader’s\nrelationship to the text and to reading. They include the insertion of spaces\nbetween the words in Latin texts, which began about 700 CE in Irish scripto-\nria (Book of Kells) and led to decisive changes in the formatting of text.7 The\nperiod from the eleventh to the thirteenth century saw the consolidation of\nmany features that allowed readers to escape the original linearity of speech,\nsuch as the table of contents, the index, and the header. Paragraph breaks\nindicated in the text by a pilcrow (9) made it easier for readers to deal with\nunits of meaning and helped them to follow the main divisions in the text.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "8.9",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215145552871",
            "created": "20170420145051619",
            "bag": "default"
        },
        "15.1": {
            "text": "In computer science, the concept of hypertext designates a way of making\ndirect connections among various pieces of information, textual or nontex-\ntual, that may or may not be located in the same file (or on the same “page”\nby means of embedded links. Using an interface based primarily on visual\nand intuitive elements such as color and icons, hypertext users can identify\nthe places in a document where additional information is attached and ac-\ncess them directly with a mouse click.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.1",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155440805",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.10": {
            "text": "Selection, association, and contiguity. In addition to the above-men-\ntioned modes of navigation, the blocks of information are here ac-\ncessible sequentially, like the pages of a book. This model is suitable\nfor an essay or a scientific article and would be used, for example, for\nadaptations of printed books. It corresponds to a simple transposi-\ntion of codex format to electronic format. For example, in a hyper-\ntext adaptation of an essay such as Marvin Minsky’s Society of Mind,\nreaders can choose to select a title in the table of contents, search\nfor a word in the index, or move from section to section by scroll-\ning. The contiguity mode is useful only if a document is divided into\npages and sections that are supposed to be read in a specific order—\nas is usually the case with a book.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.10",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155801568",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.11": {
            "text": "Selection, association, contiguity, and stratification. In addition to being\naccessible by the above-mentioned modes, the elements of informa-\ntion can be distributed in two or three hierarchical levels accord-\ning to their degree of complexity. This makes it possible to meet the\nneeds of various categories of readers or to satisfy different informa-\ntion needs for a single reader. This hypertext model best combines\nthe advantages of the codex with the possibilities opened up by the\ncomputer by taking into account a new dimension of the text, that of\ndepth. By superimposing different layers of text on a single subject,\nor to use another metaphor, by encircling a central nucleus with vari-\nous supplementary documents, the uses of which are well defined, a\nstratified hypertext provides several books in one.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.11",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155814498",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.12": {
            "text": "Users of such a hypertext could scroll through pages in a main\nwindow, while at the same time being able to open one or more\nsecondary windows, providing more theoretical or more popular-\nized discourse. There are many fields in which this type of structure\nwith two or three layers, offering a basic discourse and additional\nwindows accessible on demand, is desirable. This is the case for self—\nteaching textbooks and learning situations, for example, in which the\nlearner is confronted with a mass of interrelated concepts that may\nnot all be familiar. It is also the case for technical manuals in which\nthe user may at any time want to consult supplementary information\non a specific element.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.12",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155826939",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.13": {
            "text": "These four modes of navigation may also be combined in the electronic edi-\ntion of a work, opening up new perspectives for critical editions of works on\npap er. The main thread of reading would thus be the final version of the text,\ndominating the layers of the previous versions, which the reader could also\nchoose to display in parallel windows. The different pages of the text would\nbe accessed by contiguity or by selection in a table of contents. Finally, com-\nments, notes, and illustrations would be accessible through connections or\nassociative links. Because of the richness and diversity of the links provided,\nI will call this ideal type of hypertext a “stratified” or “tabular” hypertext.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.13",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155837967",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.15": {
            "text": "In creating an arrangement capable of working in depth and not only on\nthe surface of the thread of discourse, the author of a tabular hypertext must\ntake the utmost care in establishing the different layers and distributing the\ninformation between the base level and the other layers. These choices will\nvary with the type of text and target audience. The levels of information may\nbe distributed on the axis of concrete/ abstract or divided between narrative\nand documents or between scholarly text, experimental data, and reference\nworks, or between didactic text, examples, and exercises, and so on.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.15",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155905077",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.14": {
            "text": "The success of a tool of this kind obviously depends on the consistency\nand interest of the base layer. While this is relatively easy to determine in\nthe case of a critical edition, the same is not true for other documents. In a\ntextbook aimed at a diverse readership, the various strata of information it\nshould contain would have to be established. The base layer would contain\nthe main thread of the text, consisting of the minimum information at a\nmedium level of difficulty. On every page where needed, hyperlinks would\nopen one or two supplementary windows, such as a “novice” window for\nusers whose knowledge is insufficient for them to grasp the main ideas and\nan “expert” window for those who already possess the basic knowledge and\nwant to know more.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.14",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155850956",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.16": {
            "text": "Generally speaking, it does not seem desirable to create more than two\nlayers in addition to the base level. Increasing the number of layers will result\nin a proliferation of cross—references, and reading would quickly become dif-\nficult. It is important to remember that in a reader-based textual economy,\nreference markers should be provided that allow readers to predict the re—\nsults of their actions when moving the mouse pointer over the surface of the\nscreen. The presence of a “novice” or an “expert” layer linked to a particular\nword or page should thus always be indicated in the same way, by an icon\nor the use of a color. Novice readers who click on an icon hoping to find an\nexplanation at their level would quickly become discouraged if, instead of\ngetting what they wanted, they encountered material intended for experts.\nTo be effective, reading must be based on stable conventions that enable\nmaximum concentration on the content.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.16",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155918752",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.17": {
            "text": "Stratified hypertext will undoubtedly develop its own conventions just as\nthe print media did, and these will become part of readers’ culture. In spite\nof the problems, this is where the most promising future for hypertext lies\nif it is to move beyond the stage of utopian dreams of liberation to become\na productive working tool. However, these modes of organization of hyper—\ntext may lead to methods of navigation that are very different depending on\nthe degree of opacity or tabularity of the presentation of data. A literary or\ngame hypertext may opt for greater opacity in navigation and allow users to\nproduce events on the screen without knowing where they are or where they\nare going. In this case, there are no obvious “movements,” since everything\noccurs within the same visual framework. This form of opaque hypertext\nmay be suited to an experimental narrative such as Stuart Moulthrop’s He-\ngirascope3 or to an adventure game such as Myst, in which the players have\nno idea of their position in relation to the puzzles to be solved. For an infor-\nmational document, however, the most satisfying option for readers is one\nthat gives them a clear view of the distribution of information and enables\nthem to directly access all the blocks, with full control of their movement.\nIn this regard, it is significant that some games allow players to choose the\nepisode they want and allow them to display the percentage of the episode\ncompleted at any time.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.17",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155936863",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.18": {
            "text": "One area where the user’s route cannot be left to chance is learning. In-\nstructional programs and textbooks are based precisely on the principle that\nthe acquisition of knowledge cannot take place in random order guided only\nby the learner’s associations. The first computer-assisted learning (CAL) pro-\ngrams took this principle of the sequential path to the limit, locking students\ninto programmed paths in which access to each exercise was conditional on\nsuccess in the previous one. Students were expected to move forward blindly,\nwithout knowing how many steps they would have to go through or even,\nsometimes, what they would actually learn from the program. Hypertext,\ntoo, can be used in an opaque manner, to totally control users’ progress,\nallowing them to follow only branchings accepted by the logic of the pro-\ngram, thus reinforcing traditional practices of computer- assisted learning. I\nbelieve, however, that hypertext should adopt some of the characteristics of\nthe age—old technology of the book to create a new product that will satisfy\nthe needs of demanding readers who use it as a tool for informational or\neducational purposes.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.18",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155949106",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.19": {
            "text": "As we can see, the production of a hypertext requires constant strategic\nchoices by the author. The distribution of elements of information also poses\nthe problem of identifying every primary textual unit with a title. If these\ntitles are meaningful to the users, it will be easier for them not only to find\nthe information they want, but also to keep track of which pages they have\nread when they exit from the hypertext. In this way, readers will be able to\nhave real control over the text instead of being controlled by it or groping\ntheir way through it.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.19",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215160002303",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.2": {
            "text": "Literary theory also uses the term hypertext, but in a very different sense.\nFor Gérard Genette, for example, hypertext is “any text derived from a previ—\nous text either through simple transformation . . . or through indirect trans-\nformation.”1 In this sense, James Joyce’s Ulysses is a hypertext of Homer’s\nOdyssey. The current concept of hypertext, as it comes to us from computer\nscience and the Web, is closer to that of intertext as first proposed by Julia\nKristeva and redefined by Michael Riffaterre: “the perception, by the reader,\nof a relationship between a work and others that have either preceded or fol-\nlowed it.” But the two concepts do not coincide completely, since the intertext,\nin this meaning, results from the act of reading, while the hypertext we are\ntalking about is a computer construct of links and data corresponding to files\nor parts of files that can be displayed in windows of various dimensions.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.2",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155454381",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.3": {
            "text": "There are many hypertext software programs. Among the pioneers are\nHypercard, Hyperties, KMS, Intermedia, and Notecards. Since the advent\nof the Web, hypertext has been based mainly on HTML (HyperText Markup\nLanguage), XML (Extensible Markup Language), and XHTML.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.3",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155506922",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.4": {
            "text": "Historically, the term hypertext was created in 1965 by Ted Nelson, who\nused it to designate a new way of writing on the computer, in which the\nunits of text could be accessed nonsequentially. The text thus created would\nreproduce the nonlinear structure of ideas as opposed to the “linear” format\nof books, films, or speech. Nelson himself was indebted to a Visionary article\nby Vannevar Bush, who in 1945 already envisaged a huge storage system for\nhuman knowledge that anyone would be able to connect to and that would\nallow them to annotate documents of interest. Even before the introduction\nof the personal computer, Nelson had attempted to realize Bush’s dream us-\ning a computer system called Xanadu—the name of Mongol emperor Kublai\nKhan’s palace, immortalized in a poem by Coleridge as a symbol of memory\nand its accumulated treasures. Nelson’s Xanadu was supposed to lead to a\nhuge universal library system (docuverse), which could be consulted on\nworkstations by making “micropayments” for each information node ac-\ncessed. Despite its commercial implications, Nelson’s model had a profound\ninfluence on the evolution of hypertext, and the World Wide Web may be\nseen as its culmination in an unrestricted form.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.4",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155522381",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.5": {
            "text": "Hypertext can be used to manipulate data of all kinds, not only linguistic\ndata but also images, sound, video, and animation. It makes it possible to\nregulate a reader’s interaction with a document by programming various\nbehavior into objects on the screen in relation to the reader’s movements\nof the mouse: the author of a computer program can stipulate, for example,\nthat touching a certain word with the mouse pointer will change its form\nor color or trigger a process that will lead to a new text. Through these fea-\ntures, hypertext creates a radically new form of electronic dialogue in written\nlanguage. Even more numerous than the many forms of books, hypertext\nproducts vary substantially in appearance and internal organization. Indeed,\ncomputer technology can give digitized text any form imaginable.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.5",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155700747",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.6": {
            "text": "In a text on paper, the paragraphs or blocks of information are arranged\nin sequence, and the reader can access them essentially through contiguity,\nrelying on a number of tabular elements. In a hypertext, the various blocks\nof information may be distinct and autonomous and may be located on a\nsingle “page” or on separate “pages.” In accordance with the nature of the\ndocument and the target readers, the author of a hypertext can provide ac—\ncess by means of selection, association, contiguity, or stratification, and these\nmodes can exist alone or in different combinations.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.6",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155712367",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.7": {
            "text": "Selection. In the simplest case, selection, readers select the block of\ninformation they want to read from a list or enter a letter on the\nkeyboard. The various blocks of information are distinct units with\nno essential links among them. Readers are guided by a specific need\nfor information, which exists only until it is satisfied. This model is\ntypical of the catalogue, the entire organization of which is based on\nthe principle of expansion, with each word of the index leading to\na detailed description. Dictionaries also work on this principle, but\neach of their entries can also contain references to other entries such\nas synonyms, antonyms, and so on. The user may also select from the\nlist of pages already consulted in the document during the work ses-\nsion or may choose from a table of contents or from a tree diagram\nin which the various branchings are accessible at different hierarchi-\ncal levels. Finally, the most frequent mode of selection is by means of\nhyperlinks indicated by a particular color, on which the user clicks in\norder to explore the content behind them.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.7",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155722395",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.8": {
            "text": "Applied to a text of a certain scope, the principle of selection is\nalso characteristic of hypertext fiction in which each screen page\nincludes several links to other pages, making Jorge Luis Borges’s\nideal of forking paths a reality. Similarly, in the case of a philosophi-\ncal essay, every block of text could be followed by a number of icons,\neach one corresponding to a possible continuation of the text accor—\nding to the anticipated reactions of the reader insofar as the author\ncould predict them. After reading a segment of text, the reader could\nselect the most relevant continuation. In so doing, he or she would\nbecome actively involved in reading, making choices, and expressing\nopinions at every step through each section read. But the number\nof combinations can easily skyrocket. If a block of text gives rise to\nthree choices, and each of these gives rise to another three, there\nwould be nine possible continuations of the initial text at the third\nlevel, twenty—seven at the fourth level, and eighty—one at the fifth. As\na result, 121 texts would have to be written for a sequence of five pa—\nragraphs to be accessible in perfectly “free” hypertext mode. Thus the\nidea of providing choices at every level has to be abandoned, or their\nproliferation would lead the reader into endless movement and force\nthe author to rigorously explore every logical alternative at each\npoint in the argument. Moreover, the freedom given the reader is pu-\nrely artificial; it only reinforces the dominant position of the author,\nwho is the master of all possible outcomes.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.8",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155733082",
            "created": "20170420145051623",
            "bag": "default"
        },
        "15.9": {
            "text": "Selection and association. In this mode, readers choose the element they\nwish to consult but can also navigate among the blocks of informa-\ntion, letting themselves be guided by the associations of ideas that\narise as they navigate and by the links offered them. This model is\ntypical of encyclopedias.",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "paragraph",
            "title": "15.9",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180215155749950",
            "created": "20170420145051623",
            "bag": "default"
        },
        "Essay 15: Varieties of Hypertext": {
            "text": "",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "heading",
            "toc-heading-level": "h1",
            "title": "Essay 15: Varieties of Hypertext",
            "tags": "Annotator [[Vandendorpe Essays]]",
            "revision": "0",
            "modified": "20180215160134832",
            "list": "15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.8 15.9 15.10 15.11 15.12 15.13 15.14 15.15 15.16 15.17 15.18 15.19 paragraph-essay-16-context-hypertext",
            "created": "20170420145051623",
            "bag": "default"
        },
        "Essay 8: Toward the Tabular Text": {
            "text": "",
            "type": "text/vnd.tiddlywiki",
            "toc-type": "heading",
            "toc-heading-level": "h1",
            "title": "Essay 8: Toward the Tabular Text",
            "tags": "[[Vandendorpe Essays]] Annotator",
            "revision": "0",
            "modified": "20180215160124214",
            "list": "8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19 8.20 8.21 8.22 8.23 8.24 8.25",
            "created": "20170420145051618",
            "bag": "default"
        },
        "Annotator": {
            "text": "# Use advanced search {{$:/core/ui/Buttons/advanced-search}}  to filter  all tiddlers associated with the Annotator.\n# Paste  ``[tag[Annotator]]`` into the <$button class=\"tc-btn-invisible tc-tiddlylink\"><$action-setfield $tiddler=\"$:/state/tab-1749438305\" text=\" $:/AdvancedSearch/Filter\"/><$action-navigate $to=\"$:/AdvancedSearch\"/>Advanced Search - filter </$button> tab\n# Export as .tid file\n# Import into your Annotator wiki. You should see these tiddlers imported into your wiki<br><$list filter=\"[tag[Annotator]]\">\n<$link><<currentTiddler>></$link><br>\n</$list>",
            "whats-new": "This tiddler functions as a set of directions that will allow you to import a set of tools that you can use to annotate a set of readings, in order to do [[Exercise 4.02]]",
            "type": "text/vnd.tiddlywiki",
            "title": "Annotator",
            "tags": "NewAtDesignWriteStudio",
            "revision": "0",
            "modified": "20180228155633637",
            "created": "20180213143747399",
            "bag": "default"
        },
        "Annotation": {
            "text": "These are my annotations so far<br>\n<$list filter=\"[tag[Annotation]]\">\n<$link><<currentTiddler>></$link><br>\n</$list>\n",
            "type": "text/vnd.tiddlywiki",
            "title": "Annotation",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180217164535837",
            "created": "20180217164414951",
            "bag": "default"
        },
        "Hypertextual Practices": {
            "text": "<<tag \"Hypertextual Practices\">>\n<<tabs \"[tag{!!title}]\">>",
            "type": "text/vnd.tiddlywiki",
            "title": "Hypertextual Practices",
            "tags": "Annotator",
            "revision": "0",
            "modified": "20180226194357334",
            "created": "20180217162522116",
            "bag": "default"
        },
        "Linking": {
            "text": "Engaging in the practice of linking involves creating an opportunity to move, either within a text or to another text.",
            "type": "text/vnd.tiddlywiki",
            "title": "Linking",
            "tags": "[[Hypertextual Practices]]",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180217162407124",
            "definition": "Creating an opportunity for a reader (or the author) to move either within a text or to another text.",
            "creator": "stevesunypoly",
            "created": "20150721195646236",
            "bag": "default"
        },
        "Listing": {
            "text": "Engaging in the practice of listing involves manipulating the range of nodes to present them as possible choices that can be selected in a given context.",
            "type": "application/x-tiddler",
            "title": "Listing",
            "tags": "[[Hypertextual Practices]]",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180217162407122",
            "definition": "Manipulating the range of nodes (tiddlers) presented as possible choices that can be selected in a given context",
            "creator": "stevesunypoly",
            "created": "20150721195608432",
            "bag": "default"
        },
        "Tagging": {
            "text": "Engaging in the practice of tagging involves adding a label with semantic meaning to an object",
            "type": "text/vnd.tiddlywiki",
            "title": "Tagging",
            "tags": "[[Hypertextual Practices]]",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180217162407119",
            "definition": "Adding a tag to a tiddler",
            "creator": "stevesunypoly",
            "created": "20170104213659532",
            "bag": "default"
        },
        "Templating": {
            "text": "Engaging in the practice of templating involves creating a frameworks or set of instructions governing the presentation of an object",
            "type": "text/vnd.tiddlywiki",
            "title": "Templating",
            "tags": "[[Hypertextual Practices]]",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180217162407116",
            "definition": "Creating a frameworks or set of instructions governing the display of information for a set of filtered tiddlers.",
            "creator": "stevesunypoly",
            "created": "20151115060703454",
            "bag": "default"
        },
        "Transcluding": {
            "text": "Engaging in the practice of transcluding involves referencing one object (\"A\") in another (\"B\") such that the content of \"A\" appears to be a part of \"B\".",
            "type": "text/vnd.tiddlywiki",
            "title": "Transcluding",
            "tags": "[[Hypertextual Practices]]",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180217162407111",
            "definition": "Referencing contents in one tiddler to be presented in another",
            "creator": "stevesunypoly",
            "created": "20150721195705760",
            "bag": "default"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/designwritestudio/showNotes": {
            "text": "{\n    \"tiddlers\": {\n        \"$:/plugins/DesignWriteStudio/showNotes/read.me\": {\n            \"created\": \"20180228150618937\",\n            \"creator\": \"steve\",\n            \"text\": \"This plugin includes a macro and a stylesheet to support the use of overlayed documentation within tiddlers.\\n\\n\\nThis plugin originates from the [[DesignWriteStudio|http://designwritestudio.com]] community.\",\n            \"title\": \"$:/plugins/DesignWriteStudio/showNotes/read.me\",\n            \"tags\": \"showNotes\",\n            \"modified\": \"20180228151046505\",\n            \"modifier\": \"steve\"\n        },\n        \"$:/plugins/DesignWriteStudio/showNotes/showNotesMacro\": {\n            \"created\": \"20180220144143011\",\n            \"creator\": \"steve\",\n            \"text\": \"\\\\define show(text)\\n<$list filter=\\\"[title[ShowNotesMacro]field:dox[yes]]\\\">\\n<span class=\\\"yellow-hilite\\\">\\n$text$\\n</span><br>\\n</$list>\\n\\\\end\\n\\n<$checkbox tiddler=\\\"ShowNotesMacro\\\" field=\\\"dox\\\" checked=\\\"yes\\\" unchecked=\\\"no\\\" default=\\\"yes\\\"> show dox?</$checkbox><br>''status:'' {{!!dox}}\\n\\n<<show \\\"this is what it is about\\\">>\\n\\nThis macro requires:\\n\\n<<list-links \\\"[tag[ShowNotes]]\\\">>\",\n            \"whats-new\": \"Use this macro to add documentation to your wiki\",\n            \"type\": \"text/vnd.tiddlywiki\",\n            \"title\": \"$:/plugins/DesignWriteStudio/showNotes/showNotesMacro\",\n            \"tags\": \"showNotes $:/tags/Macro\",\n            \"revision\": \"0\",\n            \"modifier\": \"steve\",\n            \"modified\": \"20180228150602083\",\n            \"dox\": \"no\",\n            \"bag\": \"default\"\n        },\n        \"$:/plugins/DesignWriteStudio/showNotes/showNotesStyleSheet\": {\n            \"created\": \"20170727202737911\",\n            \"creator\": \"steve\",\n            \"text\": \".orange-hilite {\\n    background-color: orange;\\n}\\n\\n.yellow-hilite {\\n    background-color: yellow;\\n}\\n\\n\",\n            \"type\": \"text/vnd.tiddlywiki\",\n            \"title\": \"$:/plugins/DesignWriteStudio/showNotes/showNotesStyleSheet\",\n            \"tags\": \"showNotes $:/tags/Stylesheet\",\n            \"revision\": \"0\",\n            \"modifier\": \"steve\",\n            \"modified\": \"20180228150536399\",\n            \"bag\": \"default\"\n        },\n        \"$:/plugins/DesignWriteStudio/showNotes/TopLeftBar\": {\n            \"created\": \"20180228150843748\",\n            \"creator\": \"steve\",\n            \"text\": \"<$checkbox tiddler=\\\"ShowNotesMacro\\\" field=\\\"dox\\\" checked=\\\"yes\\\" unchecked=\\\"no\\\" default=\\\"yes\\\"> show dox?</$checkbox> \\n\",\n            \"type\": \"text/vnd.tiddlywiki\",\n            \"title\": \"$:/plugins/DesignWriteStudio/showNotes/TopLeftBar\",\n            \"tags\": \"showNotes $:/tags/TopLeftBar\",\n            \"revision\": \"0\",\n            \"modifier\": \"steve\",\n            \"modified\": \"20180228151007122\",\n            \"bag\": \"default\"\n        }\n    }\n}",
            "version": "0.5.1",
            "type": "application/json",
            "title": "$:/plugins/designwritestudio/showNotes",
            "plugin-type": "DesignWriteStudio",
            "name": "showNotes",
            "list": "$:/plugins/DesignWriteStudio/showNotes/read.me",
            "description": "Supports use of <<show>> macro and a top left menu bar to make comments and documentation visible at the tiddler level",
            "author": "Steve Schneider"
        },
        "$:/plugins/DesignWriteStudio/showNotes/read.me": {
            "created": "20180228152134603",
            "creator": "steve",
            "title": "$:/plugins/DesignWriteStudio/showNotes/read.me",
            "modified": "20180228152237430",
            "modifier": "steve",
            "text": "This plugin supports the use of the <<show>> macro to share notes or comments. Visibility of the notes is controlled by the show dox checkbox in the top left menu.\n\nThis plugin is from the [[DesignWriteStudio|http://designwritestudio.com]] community."
        },
        "$:/plugins/DesignWriteStudio/showNotes/showNotesMacro": {
            "created": "20180228151922069",
            "creator": "steve",
            "text": "\\define show(text)\n<$list filter=\"[title[ShowNotesMacro]field:dox[yes]]\">\n<span class=\"yellow-hilite\">\n$text$\n</span><br>\n</$list>\n\\end\n\n<$checkbox tiddler=\"ShowNotesMacro\" field=\"dox\" checked=\"yes\" unchecked=\"no\" default=\"yes\"> show dox?</$checkbox><br>''status:'' {{!!dox}}\n\n<<show \"this is what it is about\">>\n\nThis macro requires:\n\n<<list-links \"[tag[ShowNotes]]\">>",
            "whats-new": "Use this macro to add documentation to your wiki",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/DesignWriteStudio/showNotes/showNotesMacro",
            "tags": "showNotes $:/tags/Macro",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180228151935973",
            "dox": "yes",
            "bag": "default"
        },
        "$:/plugins/DesignWriteStudio/showNotes/showNotesStyleSheet": {
            "created": "20180228151954351",
            "creator": "steve",
            "text": ".orange-hilite {\n    background-color: orange;\n}\n\n.yellow-hilite {\n    background-color: yellow;\n}\n\n",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/DesignWriteStudio/showNotes/showNotesStyleSheet",
            "tags": "showNotes $:/tags/Stylesheet",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180228152016214",
            "bag": "default"
        },
        "$:/plugins/DesignWriteStudio/showNotes/TopLeftBar": {
            "created": "20180228151818119",
            "creator": "steve",
            "text": "<$checkbox tiddler=\"ShowNotesMacro\" field=\"dox\" checked=\"yes\" unchecked=\"no\" default=\"yes\"> show dox?</$checkbox> ",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/DesignWriteStudio/showNotes/TopLeftBar",
            "tags": "$:/tags/TopLeftBar showNotes",
            "revision": "0",
            "modifier": "steve",
            "modified": "20180228152115140",
            "bag": "default"
        }
    }
}

This plugin supports the use of the ``<<show>>`` macro to share notes or comments. Visibility of the notes is controlled by the show dox checkbox in the top left menu.

This plugin is from the [[DesignWriteStudio|http://designwritestudio.com]] community.

{
    "tiddlers": {
        "$:/core/macros/tabs": {
            "text": "\\define tabs(tabsList,default,state:\"$:/state/tab\",class,template)\n<div class=\"tc-tab-set $class$\">\n<div class=\"tc-tab-buttons $class$\">\n<$list filter=\"$tabsList$\" variable=\"currentTab\"><$set name=\"save-currentTiddler\" value=<<currentTiddler>>><$tiddler tiddler=<<currentTab>>><$button set=<<qualify \"$state$\">> setTo=<<currentTab>> default=\"$default$\" selectedClass=\"tc-tab-selected\" tooltip={{!!tooltip}}>\n<$tiddler tiddler=<<save-currentTiddler>>><<tablink>>\n<$set name=\"tv-wikilinks\" value=\"no\">\n<$transclude tiddler=<<currentTab>> field=\"caption\">\n<$macrocall $name=\"currentTab\" $type=\"text/plain\" $output=\"text/plain\"/>\n</$transclude>\n</$set></$tiddler></$button></$tiddler></$set></$list>\n</div>\n<div class=\"tc-tab-divider $class$\"/>\n<div class=\"tc-tab-content $class$\">\n<$list filter=\"$tabsList$\" variable=\"currentTab\">\n\n<$reveal type=\"match\" state=<<qualify \"$state$\">> text=<<currentTab>> default=\"$default$\">\n\n<$transclude tiddler=\"$template$\" mode=\"block\">\n\n<$transclude tiddler=<<currentTab>> mode=\"block\"/>\n\n</$transclude>\n\n</$reveal>\n\n</$list>\n</div>\n</div>\n\\end\n",
            "title": "$:/core/macros/tabs",
            "tags": "$:/tags/Macro",
            "modifier": "twMat",
            "modified": "20170304123501677",
            "creator": "twMat",
            "created": "20170303214346165"
        },
        "$:/plugins/TWaddle/TabLinks/macro": {
            "created": "20160806203109547",
            "creator": "twMat",
            "text": "\\define tablink()\n<div class=\"tablink\">\n<$tiddler tiddler=<<currentTab>>>\n<$link to=<<currentTab>> tooltip=\"go to tab\" >\n  <span class=\"tablink-btn\">{{$:/core/images/preview-open}}</span>\n</$link>\n<$button message=\"tm-edit-tiddler\" param=<<currentTab>> tooltip=\"edit tab\">\n  <span class=\"tablink-btn\">{{$:/core/images/edit-button}}</span>\n</$button>\n</$tiddler>\n</div>\n\\end",
            "title": "$:/plugins/TWaddle/TabLinks/macro",
            "tags": "$:/tags/Macro",
            "modifier": "twMat",
            "modified": "20170304132153989"
        },
        "$:/plugins/TWaddle/TabLinks/Stylesheet": {
            "created": "20170304101100313",
            "creator": "twMat",
            "text": "<pre>\n.tablink {display:none;}\n\n.tc-tab-selected .tablink {\n  display:{{$:/plugins/TWaddle/TabLinks/Stylesheet!!display}};\n  position:absolute;\n  margin:-1.5rem 0 0 -7px;\n  font-size:1rem;\n  background:white;\n  padding:0 5px;\n  border:1px solid silver;\n  border-radius:2px;\n  visibility:hidden;\n  opacity:0;\n}\n.tc-tab-selected:hover .tablink {\n  visibility:visible;\n  opacity:1;\n    -webkit-transition:opacity 0.9s;\n    -moz-transition:opacity 0.9s;\n    -ms-transition:opacity 0.9s; \n    -o-transition:opacity 0.9s;\n    transition:opacity 0.9s;\n  -webkit-transition-timing-function: ease-in; /* Safari and Chrome */\n  transition-timing-function: ease-in;\n}\n.tc-tab-buttons .tablink button, .tablink-btn {\n  border:0;\n  background:transparent;\n  padding: 2px 1px;\n  margin:0;\n}\n\n.tablink-btn { opacity:.4; }\n\n.tablink-btn:hover { opacity:1; } \n\n.tablink a:hover {  text-decoration:none; }\n</pre>",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/TWaddle/TabLinks/Stylesheet",
            "tags": "$:/tags/Stylesheet",
            "modifier": "twMat",
            "modified": "20170304153832912",
            "display": "inline-block",
            "list-after": "$:/themes/tiddlywiki/vanilla/base"
        },
        "$:/plugins/TWaddle/TabLinks/Toggle": {
            "created": "20170115223014606",
            "creator": "twMat",
            "text": "<<toggle  \"$:/plugins/TWaddle/TabLinks/Stylesheet!!display\" inline-block none>>In tabs, display shortcut links to the content tiddler, //when hovering// on the active tab.\n\n",
            "title": "$:/plugins/TWaddle/TabLinks/Toggle",
            "tags": "$:/tags/ControlPanel/Settings",
            "modifier": "twMat",
            "modified": "20170304132100553",
            "list-before": "",
            "caption": "TabLinks"
        }
    }
}

<<toggle  "$:/plugins/TWaddle/TabLinks/Stylesheet!!display" inline-block none>>In tabs, display shortcut links to the content tiddler, //when hovering// on the active tab.

{
    "tiddlers": {
        "$:/plugins/ahahn/tinka/docs/Help Tab": {
            "title": "$:/plugins/ahahn/tinka/docs/Help Tab",
            "type": "text/vnd.tiddlywiki",
            "text": "!!Using the Help Tab\n\nWhen working on a plugin, it is often handy to be able to navigate quickly between the plugin tiddlers. That is what the Help Tab is for.\nAfter enabling it in the \"Tinka Plugin Management\" tab for a specific plugin in the Control Panel, it gives you an additional sidebar tab, that contains a list of all the tiddlers that are contained in the plugin in question. Furthermore, it also shows you tiddlers that live in the same \"directory\" which are likely tiddlers that you want to add to the plugin eventually.\n\nIf you have tiddlers whose names aren't prefixed by the plugin path, you can use the Filter search included in the help tab to select those. For example, if the rest of your tiddlers is scattered somewhere in the wiki, but tagged with <span class=\"tc-tag-label\">myPlugin</span>, you could use the filter: `[tag[myPlugin]]` to select them.\n\nAlso included in the Help Tab is a button to quickly add a new tiddler to a plugin without having to type out the whole `$:/plugins.../...` path and an option to disable the Help Tab again. Lastly, the \"Quick Package\" button gives you the option of quickly integrating changes you made to individual tiddlers into the plugin. Note that the \"Quick Package\" Button will only integrate the changes you made to tiddlers already contained in the plugin into the plugin tiddler itself, you can't add new tiddlers to a plugin this way. For those tasks, you will still have to use the control panel menu.\n"
        },
        "$:/plugins/ahahn/tinka/docs/How to create a new plugin": {
            "title": "$:/plugins/ahahn/tinka/docs/How to create a new plugin",
            "type": "text/vnd.tiddlywiki",
            "text": "!! How to create a new plugin\n\nTo create a completely new plugin, first go to the Control Panel extension Tinka provides and click on the \"Create new Plugin\" button. Next enter the ''plugin type'' of the plugin you want to create or choose a type from the dropdown menu. Usually you will want to use either the value \"''plugin''\" or \"''theme''\", as this covers most cases of plugins.\n\nNext is the ''plugin path'': This is the name of the tiddler where the finished plugin is going to be stored in. TiddlyWiki uses a special naming theme for these, so you will mostly find that the actual tiddlers that contain a plugin are named in this scheme:\n\n`$:/plugins/myOrganisation/pluginName`. \n\nThis ensures that plugins can be not only immideately recognized, but are also separate from other tiddlers in the wiki.\n\nAfter also entering a title for your new plugin or theme, you are basically good to go. These three fields: ''plugin type'', ''plugin path'' and the ''plugin title'' are all the fields that are required for a functioning plugin. In theory, you could now go ahead and press the \"''Package Plugin''\" button, which will give you an empty plugin shell to which you can add tiddlers later.\n\nIn most cases however it is desired to also fill out the rest of the metadata fields. In detail, these are:\n\n* ''Author:'' Name of the plugin author.\n* ''Source:'' Website or URL of the plugin, also the place where updates are found.\n* ''Dependents:'' List of plugins this plugin depends on (usually empty, but e.g. `$:/core`)\n* ''List'': List of tiddlers contained in the plugin, that will serve as readme tiddlers, when inspecting a plugin via the control panel. (e.g. `$:/plugins/ahahn/tinka/readme`)\n* ''Version:'' Version of your plugin in the format: X.X.X\n* ''Core-Version:'' Usually the minimal TiddlyWiki version your plugin requires in order for it to work (e.g //>=5.1.8//)\n\nDepending on the plugin type you chose, you might also come across the following metadata fields:\n\n* ''Description:'' For plugins, this contains the plugin title that is shown in the control panel.\n* ''Name:'' For themes, this contains the theme title that is shown in the control panel.\n\nAfter entering the metadata, all that is left is to select the tiddlers you want to include in the plugin. You can search for these via the default search field, but you can also use a filter to find them (e.g. based on a tag). In most cases it is sufficient to enter the name of the plugin into the default search in order to find the tiddlers that belong to the plugin. Lastly, just click the \"''Package Plugin''\" button and you're done, you have now created your first plugin. A save&refresh will be required for it to be loaded into TiddlyWiki.\n"
        },
        "$:/plugins/ahahn/tinka/icon": {
            "title": "$:/plugins/ahahn/tinka/icon",
            "type": "image/svg+xml",
            "text": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!-- Created with Inkscape (http://www.inkscape.org/) -->\n\n<svg\n   xmlns:dc=\"http://purl.org/dc/elements/1.1/\"\n   xmlns:cc=\"http://creativecommons.org/ns#\"\n   xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"\n   xmlns:svg=\"http://www.w3.org/2000/svg\"\n   xmlns=\"http://www.w3.org/2000/svg\"\n   xmlns:sodipodi=\"http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd\"\n   xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\"\n   width=\"28\"\n   height=\"28\"\n   id=\"svg2\"\n   version=\"1.1\"\n   inkscape:version=\"0.48.4 r9939\"\n   sodipodi:docname=\"tinka_logo.svg\">\n  <defs\n     id=\"defs4\" />\n  <sodipodi:namedview\n     id=\"base\"\n     pagecolor=\"#ffffff\"\n     bordercolor=\"#666666\"\n     borderopacity=\"1.0\"\n     inkscape:pageopacity=\"0.0\"\n     inkscape:pageshadow=\"2\"\n     inkscape:zoom=\"22.627417\"\n     inkscape:cx=\"12.192879\"\n     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        "$:/plugins/ahahn/tinka/tinka-backupPlugin.js": {
            "text": "/*\\\r\ntitle: $:/plugins/ahahn/tinka/tinka-backupPlugin.js\r\ntype: application/javascript\r\nmodule-type: widget\r\n\r\nTinka's backup action widget to backup a plugin.\r\n    \r\nBacks up the specified plugin tiddler and modifies the \r\n'plugin-type' and 'title' field accordingly.\r\n\r\n\\*/\r\n(function(){\r\n\r\n/*jslint node: true, browser: true */\r\n/*global $tw: false */\r\n\"use strict\";\r\n\r\nvar CommonAction = require(\"$:/plugins/ahahn/tinka/tinkaCommonAction.js\").tinkaCommonAction;\r\n\r\nvar BackupPluginWidget = function(parseTreeNode,options) {\r\n\tthis.initialise(parseTreeNode,options);\r\n    this.setup(false,false,{\r\n        \"$plugin\": \"\",\r\n        \"$restore\": \"no\"\r\n    },false);\r\n};\r\n\r\n/*\r\nInherit from the base widget class\r\n*/\r\nBackupPluginWidget.prototype = new CommonAction();\r\n\r\n/*\r\nSmall string table\r\n*/\r\nBackupPluginWidget.prototype.CONFIRM_OVERRIDE = \"You are about to restore a backup, but another version of this plugin is already active. Do you want to backup the current version (if not already existing) and restore this backup anyway ?\"; \r\n\r\n/*\r\nInvoke the action associated with this widget\r\n*/\r\nBackupPluginWidget.prototype.invokeAction = function(triggeringWidget,event) {\r\n    this.actionPlugin = this.param[\"$plugin\"];\r\n    this.actionRestore = this.param[\"$restore\"];\r\n\r\n\tif(this.actionPlugin) {\r\n      \tif(this.actionRestore == \"yes\") {\r\n          \tvar backupTiddler = this.wiki.getTiddler(this.actionPlugin);\r\n          \tvar operationConfirmed = true;\r\n          \tif(backupTiddler instanceof $tw.Tiddler) {      \r\n      \t\t\tif(this.checkIfExists(backupTiddler.fields[\"original-title\"])) {\r\n                  \toperationConfirmed = confirm(this.CONFIRM_OVERRIDE);\r\n                  \tif(operationConfirmed) {\r\n                      // after backing up, delete current $original-title Tiddler\r\n                      this.backupPlugin(backupTiddler.fields[\"original-title\"]);\r\n                      this.wiki.deleteTiddler(backupTiddler.fields[\"original-title\"]);  \t\r\n                    }\r\n                }\r\n              \r\n              \tif(operationConfirmed) {\r\n                  var pluginType = this.determinePluginType(backupTiddler.fields[\"plugin-type\"]);\r\n                  this.wiki.addTiddler(new $tw.Tiddler(backupTiddler,{\r\n                      \"title\": backupTiddler.fields[\"original-title\"],\r\n                      \"original-title\": undefined,\r\n                      \"plugin-type\": pluginType\r\n                  }));\r\n              \t}\r\n            }\r\n        }\r\n       \telse {\r\n    \t\tthis.backupPlugin(this.actionPlugin);\r\n       \t}\r\n    }\r\n  \treturn true; // Action was invoked\r\n};\r\n\r\nBackupPluginWidget.prototype.determinePluginType = function(name) {\r\n\tvar reg = /(.*)-backup/;\r\n  \tvar matches = name.match(reg);\r\n  \t\r\n  \tif(matches != null) {\r\n  \t\treturn matches[1]; \r\n    }\r\n  \r\n  \treturn \"plugin\";\r\n}\r\n\r\n\r\nBackupPluginWidget.prototype.backupPlugin = function(plugin) {\r\n\tvar pluginTiddler = this.wiki.getTiddler(plugin);\r\n    var didBackup = false;\r\n      \tif(pluginTiddler instanceof $tw.Tiddler) {\r\n            var backupTitle = this.getBackupTitle(pluginTiddler.fields.title,pluginTiddler.fields.version);\r\n            didBackup = true;\r\n          \r\n          \t//Don't make a backup if a backup already exists\r\n          \tif(!this.checkIfExists(backupTitle)) {\r\n              var backupTiddler = new $tw.Tiddler(pluginTiddler,{\r\n                  \"title\": backupTitle,\r\n                  \"original-title\": pluginTiddler.fields.title,\r\n                  \"plugin-type\": \"\" + pluginTiddler.fields[\"plugin-type\"] + \"-backup\"\r\n              });\r\n\r\n              this.wiki.addTiddler(backupTiddler);           \r\n          \t}\r\n        }\r\n  \treturn didBackup;\r\n}\r\n\r\nBackupPluginWidget.prototype.getBackupTitle = function(title,version) {\r\n \treturn \"\" + title + \"-\" + version + \"-backup\";\r\n};\r\n  \r\nBackupPluginWidget.prototype.checkIfExists = function(tiddler) {\r\n\treturn this.wiki.getTiddler(tiddler) != undefined;\r\n}\r\n\r\nexports[\"tinka-backupPlugin\"] = BackupPluginWidget;\r\n\r\n})();\r\n",
            "title": "$:/plugins/ahahn/tinka/tinka-backupPlugin.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/tinka-check.js": {
            "text": "/*\\\ntitle: $:/plugins/ahahn/tinka/tinka-check.js\ntype: application/javascript\nmodule-type: widget\n\nChecks param \"text\" for match with \"pattern\".\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar TinkaCommonActionWidget = require(\"$:/plugins/ahahn/tinka/tinkaCommonAction.js\").tinkaCommonAction;\n\nvar CheckAction = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.setup(false,true,[\"text\", \"pattern\"],true);\n};\n\nCheckAction.prototype = new TinkaCommonActionWidget();\n/*\nInvoke the action associated with this widget\n*/\nCheckAction.prototype.invokeAction = function(triggeringWidget,event) {\n\t//important: recompute Attributes\n\tthis.processAttributes();\n\tvar regexp = new RegExp(this.param[\"pattern\"]);\n\t\n\tif(regexp.test(this.param[\"text\"])) {\n\t\tvar ev = {};\n\t\tev.verb = \"pass\";\n\t\tev.data = event;\n\t\tthis.invokeActions(triggeringWidget,ev); \n\t}\n\telse {\n\t\tvar ev = {};\n\t\tev.verb = \"fail\";\n\t\tev.data = event;\n\t\tthis.invokeActions(triggeringWidget,ev);\n\t}\n\t\n\treturn true; // Action was invoked\n};\n\nexports[\"tinka-check\"] = CheckAction;\n\n})();\n",
            "title": "$:/plugins/ahahn/tinka/tinka-check.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/tinka-filter.js": {
            "text": "/*\\\ntitle: $:/plugins/ahahn/tinka/tinka-filter.js\ntype: application/javascript\nmodule-type: widget\n\nWidgets to filters actions according to their verb.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar TinkaCommonActionWidget = require(\"$:/plugins/ahahn/tinka/tinkaCommonAction.js\").tinkaCommonAction;\n\nvar FilterAction = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n\tthis.setup(false, true, [\"verb\"], true);\n};\n\nFilterAction.prototype = new TinkaCommonActionWidget();\n/*\nInvoke the action associated with this widget\n*/\nFilterAction.prototype.invokeAction = function(triggeringWidget,event) {\n\tif (event.verb === this.param[\"verb\"]) {\n\t\tthis.invokeActions(triggeringWidget, event);\n\t}\n\treturn true; // Action was invoked\n};\n\nexports[\"tinka-filter\"] = FilterAction;\n\n})();\n",
            "title": "$:/plugins/ahahn/tinka/tinka-filter.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/tinka-repackagePlugin.js": {
            "text": "/*\\\r\ntitle: $:/plugins/ahahn/tinka/tinka-repackagePlugin.js\r\ntype: application/javascript\r\nmodule-type: widget\r\n\r\nrepackagePlugin action widget\r\n\r\n<$repackagePlugin $plugin=<<target>> $repackage=\"yes\" $diff=<<qualified-modify-diff>> />\r\n\r\n\\*/\r\n(function(){\r\n\r\n/*jslint node: true, browser: true */\r\n/*global $tw: false */\r\n\"use strict\";\r\n\r\nvar CommonAction = require(\"$:/plugins/ahahn/tinka/tinkaCommonAction.js\").tinkaCommonAction;\r\n\r\n  \r\nvar repackagePluginWidget = function(parseTreeNode,options) {\r\n\tthis.initialise(parseTreeNode,options);\r\n    this.setup(false,false,[\"$plugin\",\"$create\",\"$diff\"],false);\r\n};\r\n\r\n/*\r\nInherit from the base widget class\r\n*/\r\nrepackagePluginWidget.prototype = new CommonAction();\r\n\r\n/*\r\nInvoke the action associated with this widget\r\n*/\r\nrepackagePluginWidget.prototype.invokeAction = function(triggeringWidget,event) {\r\n  \tvar diff = {};\r\n  \tvar title = \"\";\r\n\tthis.actionPlugin = this.param[\"$plugin\"];\r\n\tthis.actionCreate = this.param[\"$create\"];\r\n  \tthis.actionDiff = this.param[\"$diff\"];\r\n\r\n  \tif(this.actionPlugin) {\r\n      title = this.actionPlugin;\r\n      if(this.actionDiff) {\r\n     \tvar tid = this.wiki.getTiddler(this.actionDiff);\r\n        diff = tid || {};\r\n      }\r\n      \r\n      if(this.actionCreate == \"yes\") {\r\n        //create new plugin Tiddler with the data from the diff tiddler\r\n        var pluginTid = {};\r\n        \r\n        title = diff.fields[\"create-title\"] || this.actionPlugin;\r\n        pluginTid.title = title;\r\n        pluginTid[\"text\"] =\t\"{\\\"tiddlers\\\": {}}\";\r\n        pluginTid[\"type\"] = \"application/json\";\r\n        pluginTid[\"author\"] = diff.fields[\"create-author\"];\r\n        pluginTid[\"description\"] = diff.fields[\"create-description\"];\r\n\t\tpluginTid[\"name\"] = diff.fields[\"create-name\"];\r\n        pluginTid[\"list\"] = diff.fields[\"create-list\"];\r\n        pluginTid[\"plugin-type\"] = diff.fields[\"create-plugin-type\"];\r\n        pluginTid[\"dependents\"] = diff.fields[\"create-dependents\"];\r\n        pluginTid[\"version\"] = diff.fields[\"create-version\"];\r\n        pluginTid[\"core-version\"] = diff.fields[\"create-core-version\"];\r\n        this.wiki.addTiddler(new $tw.Tiddler(pluginTid));\r\n      }\r\n      \r\n      //execute repackaging\r\n      $tw.utils.repackPlugin(title,diff.fields.addTiddlers,diff.fields.removeTiddlers);\r\n  \t}\r\n};\r\n\r\nexports[\"tinka-repackagePlugin\"] = repackagePluginWidget;\r\n\r\n})();\r\n",
            "title": "$:/plugins/ahahn/tinka/tinka-repackagePlugin.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/tinka-saveTaglistToField.js": {
            "text": "/*\\\r\ntitle: $:/plugins/ahahn/tinka/tinka-saveTaglistToField.js\r\ntype: application/javascript\r\nmodule-type: widget\r\n\r\nSaves a tiddlers list of tags to a csv field.\r\n\r\n\\*/\r\n(function(){\r\n\r\n/*jslint node: true, browser: true */\r\n/*global $tw: false */\r\n\"use strict\";\r\n\r\nvar CommonAction = require(\"$:/plugins/ahahn/tinka/tinkaCommonAction.js\").tinkaCommonAction;\r\n\r\nvar SaveTaglistToFieldWidget = function(parseTreeNode,options) {\r\n\tthis.initialise(parseTreeNode,options);\r\n    this.setup(false,false,[\"$target\",\"$tiddler\",\"$field\"],false);\r\n};\r\n\r\n/*\r\nInherit from the base widget class\r\n*/\r\nSaveTaglistToFieldWidget.prototype = new CommonAction();\r\n\r\n/*\r\nInvoke the action associated with this widget\r\n*/\r\nSaveTaglistToFieldWidget.prototype.invokeAction = function(triggeringWidget,event) {\r\n\tvar taglist = [];\r\n  \tvar field = \"text\";\r\n  \r\n    if(this.param[\"$target\"]) {\r\n    \tvar targetTags = this.wiki.getTiddler(this.param[\"$target\"]);\r\n      \t\r\n      \tif(targetTags) {\r\n      \t\ttaglist = targetTags.fields.tags || [];\r\n      \t}\r\n    }\r\n  \r\n  \tif(this.param[\"$field\"]) {\r\n  \t\tfield = this.param[\"$field\"];\r\n  \t}\r\n  \r\n  \tif(this.param[\"$tiddler\"]) {\r\n  \t\t//save taglist in field on tiddler\r\n      \tthis.wiki.setTextReference(this.param[\"$tiddler\"]+ \"!!\" +field,taglist,this.getVariable(\"currentTiddler\")); \r\n \t}\r\n\r\n  return true; // Action was invoked\r\n};\r\n\r\nexports[\"tinka-saveTaglistToField\"] = SaveTaglistToFieldWidget;\r\n\r\n})();\r\n",
            "title": "$:/plugins/ahahn/tinka/tinka-saveTaglistToField.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/tinkaCommonAction.js": {
            "text": "/*\\\ntitle: $:/plugins/ahahn/tinka/tinkaCommonAction.js\ntype: application/javascript\nmodule-type: widget\n\nTinka common action widget\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar CommonActionWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nCommonActionWidget.prototype = new Widget();\n\n/*\nSetup an action widget with these properties\n*/\nCommonActionWidget.prototype.setup = function(allowPropagation,doRenderChildren,preparedParams,refreshOnAttributeChange) {\n\tthis.doRenderChildren = doRenderChildren;\n\tthis.preparedParams = preparedParams;\n\tthis.allowPropagation = allowPropagation;\n\tthis.refreshOnAttributeChange = refreshOnAttributeChange;\n};\n  \n  \n/*\nRender this widget into the DOM\n*/\nCommonActionWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n  \tif(this.doRenderChildren) {\n\t\tthis.renderChildren(parent,nextSibling);\n  \t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nCommonActionWidget.prototype.execute = function() {\n    this.processAttributes();\n\t// Construct the child widgets\n\tif(this.doRenderChildren) {\n\t\tthis.makeChildWidgets();\n\t}\n};\n\t\n/*\nCompute the values of our attributes\n*/\nCommonActionWidget.prototype.processAttributes = function() {\n\tvar self = this;\n\tthis.computeAttributes();\n\tthis.param = {};\n\n    if(this.isObject(this.preparedParams) && !this.isArray(this.preparedParams)) {\n        $tw.utils.each(this.preparedParams,function(def, name) {\n            self.param[name] = self.getAttribute(name,def);\n        });\n    }\n    else {\n        $tw.utils.each(this.preparedParams,function(name) {\n            self.param[name] = self.getAttribute(name);\n        });\n    }\n};\n\nCommonActionWidget.prototype.allowActionPropagation = function() {\n\treturn this.allowPropagation;\t\n};\n\nCommonActionWidget.prototype.isEmptyObject = function(obj) {\n\tfor(var prop in obj) {\n        if(obj.hasOwnProperty(prop))\n            return false;\n    }\n\n    return true;\n};\n\nCommonActionWidget.prototype.isObject = function(obj) {\n    return ((obj !== null) && (typeof obj === 'object'));\n};\n\nCommonActionWidget.prototype.isArray = function(obj) {\n    return (Object.prototype.toString.call(obj) === '[object Array]');\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nCommonActionWidget.prototype.refresh = function(changedTiddlers) {\n  \tvar changedAttributes = this.computeAttributes();\n\t\t\n\tif(!this.isEmptyObject(changedAttributes) && this.refreshOnAttributeChange) {\n\t\tthis.refreshSelf();\n\t\treturn true;\n    }\n\telse if (!this.isEmptyObject(changedAttributes)) {\n\t\tthis.processAttributes();\n\t}\n\t\n\treturn this.refreshChildren(changedTiddlers);\t\t\n};\n\nexports.tinkaCommonAction = CommonActionWidget;\n\n})();\n",
            "title": "$:/plugins/ahahn/tinka/tinkaCommonAction.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/ahahn/tinka/license": {
            "title": "$:/plugins/ahahn/tinka/license",
            "type": "text/vnd.tiddlywiki",
            "caption": "license",
            "text": "Tinka Plugin for Tiddlywiki5\n\nCopyright (c) 2017 Andreas Hahn <tinka.plugin@gmail.com>\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\r\nof this software and associated documentation files (the \"Software\"), to deal\r\nin the Software without restriction, including without limitation the rights\r\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\r\ncopies of the Software, and to permit persons to whom the Software is\r\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\r\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\r\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\r\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\r\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\r\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\r\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\r\nSOFTWARE.\r\n"
        },
        "$:/plugins/ahahn/tinka/emptyDiff": {
            "title": "$:/plugins/ahahn/tinka/emptyDiff",
            "type": "text/vnd.tiddlywiki",
            "text": ""
        },
        "$:/plugins/ahahn/tinka/tinka-export": {
            "tags": "$:/tags/Macro",
            "title": "$:/plugins/ahahn/tinka/tinka-export",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define tinkaExportButtonFilename(baseFilename)\n$baseFilename$$(extension)$\n\\end\n\n\\define tinkaExportQualifiedState()\n$:/state/popup/tinkaExport-$(currentTiddler)$\n\\end\n\n\\define tinkaExportButton(exportFilter:\"[!is[system]sort[title]]\",lingoBase,baseFilename:\"tiddlers\")\n<span class=\"tc-popup-keep\">\n<$button popup=<<tinkaExportQualifiedState>> tooltip={{$lingoBase$Hint}} aria-label={{$lingoBase$Caption}} class=<<tv-config-toolbar-class>> selectedClass=\"tc-selected\">\n<$list filter=\"[<tv-config-toolbar-icons>prefix[yes]]\">\n{{$:/core/images/export-button}}\n</$list>\n<$list filter=\"[<tv-config-toolbar-text>prefix[yes]]\">\n<span class=\"tc-btn-text\"><$text text={{$lingoBase$Caption}}/></span>\n</$list>\n</$button>\n</span>\n<$reveal state=<<tinkaExportQualifiedState>> type=\"popup\" position=\"below\" animate=\"yes\">\n<div class=\"tc-drop-down\">\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/Exporter]]\">\n<$set name=\"extension\" value={{!!extension}}>\n<$button class=\"tc-btn-invisible\">\n<$action-sendmessage $message=\"tm-download-file\" $param=<<currentTiddler>> exportFilter=\"\"\"$exportFilter$\"\"\" filename=<<exportButtonFilename \"\"\"$baseFilename$\"\"\">>/>\n<$action-deletetiddler $tiddler=<<tinkaExportQualifiedState>>/>\n<$transclude field=\"description\"/>\n</$button>\n</$set>\n</$list>\n</div>\n</$reveal>\n\\end\n"
        },
        "$:/plugins/ahahn/tinka/readme": {
            "title": "$:/plugins/ahahn/tinka/readme",
            "type": "text/vnd.tiddlywiki",
            "text": "This is a Control Panel extension that aims to simplify the plugin creation and editing process. After installing, you will find a new tab in your control panel that makes creating and modifying plugins a little bit easier.\n\n<a target=\"blank\" href=\"http://tinkaplugin.github.io\">Project Homepage on tinkaplugin.github.io</a>\n\n!! Version History\n\n!!! 2017-05-13 Release of version 0.4.0\n\nThis release fixes the following bugs:\n\n''Changelog''\n\n* Themes will now get the correct prefix `$:/themes/` when packaging\n* Fixed search results not linking properly\n* Added description field when creating a new theme\n\n\n!!! 2017-03-01 Release of version 0.3.0\n\nAfter more than a year, Tinka is now on <a target=\"blank\" href=\"http://tinkaplugin.github.io\">github</a> and also released under the [[MIT license|$:/plugins/ahahn/tinka/license]].\n\n''Changelog''\n\n* Packaging success now produces a modal that actively reminds the user to refresh the wiki.\n* The search tab state is now kept in a temporary system tiddler.\n* Added warning when repackaging themes that are not active.\n* The 'Help Tab' functionality is now also available for plugins that do not follow the `$:/plugins/...` naming convention. In particular this applies to themes and core plugins.\n* Fixed wrong headings for some modal dialogs.\n* Older action widgets remodeled to use the (new) CommonAction widget as a base.\n* Fixed error check that prevented users to enter a minimal core version dependency when creating a new plugin.\n\n!!! 2015-09-20 Release of version 0.2.0-beta\n\n''Changelog''\n\n* Added Help-Tab capabilities to quickly navigate between plugin tiddlers.\n* Moved Create-Plugin wizard to its own tab.\n* Redid Create-Plugin UI to be easier and more accessible.\n* Backups can now also be downloaded/exported.\n* Added more documentation.\n\n!!! 2015-05-18 Release of version 0.1.0\n\n''Changelog''\n\n* The metadata section now include edit fields for the `name` and `source` fields.\n* The //default search// box now only searches for title matches.\n* Backups can now be exported/downloaded.\n* <div>Backups can now be restored and made active again. If another version of the plugin is already active, the option is given to back it up,before restoring the backup.\n\n\n''Warning: For this mechanism to work, there has to be an 'original-title' field present in the backup tiddler. This is automatically added by Tinka, however earlier versions of Tinka did not add this field. If you want to restore a backup from an earlier version of Tinka, you will have to add the 'original-title' field manually and populate it with the former title of the plugin tiddler, in order for the restore function to work.''\n</div>\n\n!!! 2015-04-30 Release of version 0.0.2\n\n''Changelog''\n\n* The list of plugin tiddlers is now hidden by default, since some lists can get very long.\n* Added a different search option (default/filter)\n* Improved Documentation slightly\n* Added a backup option, so a plugin can be backed up before repackaging.\n\n   \n!!! 2015-04-29 Release of version 0.0.1\n"
        },
        "$:/plugins/ahahn/tinka/style": {
            "list-after": "$:/themes/tiddlywiki/vanilla/base",
            "tags": "$:/tags/Stylesheet",
            "title": "$:/plugins/ahahn/tinka/style",
            "type": "text/vnd.tiddlywiki",
            "text": "\n/* ==button styles== */\n\nbutton.tinka-blue, button.tinka-orange {\n  font-weight: normal;\n  font-size: 1em;\n  color: #fff;\n  fill: #fff;\n}\n\n.tinka-blue {\n  background-color: #5E9FCA;\n}\n\n.tinka-orange {\n  background-color: #FF8C19;\n}\n\n.tinka-archive-buttons {\n  padding-left: 30px;\n  display: inline-block;\n}\n\nbutton.tinka-sidebar-button, button.tinka-invisible  {\n  color: #acacac;\n  fill: #acacac;\n}\n\n.tinka-enlarge {\n  font-size: 1.5em;\n  padding: 1.5em;\n}\n\n.tinka-enlarge svg {\n  font-size: 3em;\n}\n\n.tinka-orb {\n  border-radius: 10pt;\n}\n\n.tc-dirty .tinka-button-refresh {\n  display: none;\n}\n\n/* ==container styles== */\n\n.tinka-centered-container {\n  text-align: center;\n  padding: 1em;\n}\n\n.tinka-note {\n  display:block;\n  padding-left: 5px;\n  background-color: #FFF9B0;\n  color: #7F7A32;\n  border: 1px solid #7F7A32;\n  border-radius: 5px;\n  font-style: italic;\n  font-size: 0.8em;\n}\n\n.tinka-note-red {\n  display:block;\n  padding-left: 5px;\n  background-color: #E8DEE0;\n  color: #E82C0C;\n  border: 1px solid #E82C0C;\n  border-radius: 5px;\n  font-style: italic;\n  font-size: 0.8em;\n}\n\n/* ==text formatting== */\n\n.tinka-list-item {\n\tlist-style: none;\n}\n\n.tinka-saving {\n  display: none;\n}\n\n.tc-dirty .tinka-saving {\n  display: inline;\n}\n\n.tinka-success {\n  color: #26CC50;\n}\n\n.tinka-success .tc-image-done-button, .tinka-success .tc-image-save-button {\n  fill: #26CC50;\n}\n\n.tinka-error {\n  color: #F00;\n}\n\n.tinka-error .tc-image-close-button {\n  fill: #F00;\n}\n\ntable.tinka-meta-table tr td {\n  padding: 5px;\n}\n\n/* ==forms style== */\n.tc-control-panel input.tinka-inline-edit {\n  width: 30%;\n  min-width: 30pt;\n}\n\n.tc-control-panel input.tinka-full-edit,  input.tinka-full-edit {\n  width: 100%;\n}\n"
        },
        "$:/plugins/ahahn/tinka/backupList": {
            "caption": "Archive",
            "list-after": "$:/plugins/ahahn/tinka/pluginManagement",
            "tags": "$:/tags/tinka/ControlPanel",
            "title": "$:/plugins/ahahn/tinka/backupList",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define plugin-export()\n[title[$(currentTiddler)$]]\n\\end\n\n\\define plugin-icon-title()\n$(currentTiddler)$/icon\n\\end\n\n\\define plugin-disable-title()\n$:/config/Plugins/Disabled/$(currentTiddler)$\n\\end\n\n\\define plugin-table-body(type,disabledMessage)\n<div class=\"tc-plugin-info-chunk\">\n<$transclude tiddler=<<currentTiddler>> subtiddler=<<plugin-icon-title>>>\n<$transclude tiddler=\"$:/core/images/plugin-generic-$type$\"/>\n</$transclude></div>\n<div class=\"tc-plugin-info-chunk\">\n<h1>''<$view field=\"description\"><$view field=\"title\"/></$view>'' $disabledMessage$\n</h1>\n<h2>\n<$view field=\"title\"/>\n</h2>\n<h2>\n<div><em><$view field=\"version\"/></em></div>\n</h2></div>\n<div class=\"tinka-archive-buttons\">\n<$macrocall $name=\"tinkaExportButton\" exportFilter=<<plugin-export>> />\n<$button class=\"tc-btn-big-green tinka-blue\">\n<$tinka-backupPlugin $plugin=<<currentTiddler>> $restore=\"yes\"/>\n<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/restoreSuccess\" />Restore</$button>\n</div>\n\\end\n\n\\define plugin-table(type)\n<$list filter=\"[!has[draft.of]plugin-type[$type$]sort[description]]\" emptyMessage=<<lingo \"Empty/Hint\">>>\n<$link to={{!!title}} class=\"tc-plugin-info\">\n<<plugin-table-body type:\"$type$\">>\n</$link>\n</$list>\n\\end\n\n!!Backups\n\n<<plugin-table plugin-backup>>\n<<plugin-table theme-backup>>\n<<plugin-table language-backup>>\n"
        },
        "$:/plugins/ahahn/tinka/controlPanelExtension": {
            "caption": "Tinka Plugin Management",
            "tags": "$:/tags/ControlPanel",
            "title": "$:/plugins/ahahn/tinka/controlPanelExtension",
            "type": "text/vnd.tiddlywiki",
            "text": "<<tabs \"[[$:/plugins/ahahn/tinka/pluginManagement]] [[$:/plugins/ahahn/tinka/createDialog]] [[$:/plugins/ahahn/tinka/backupList]]\" \"$:/plugins/ahahn/tinka/pluginManagement\" \"$:/temp/tinka/cpTabs\">>\n"
        },
        "$:/plugins/ahahn/tinka/createDialog": {
            "caption": "Create a new Plugin",
            "tags": "$:/tags/tinka/ControlPanel",
            "title": "$:/plugins/ahahn/tinka/createDialog",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define plugin-tiddler-selection()\n[[$(target)$]plugintiddlers[]]\n\\end\n\n\\define qualified-modify-add()\n$(qualifiedTiddler)$-$(target)$-add\n\\end\n\n\\define qualified-modify-diff()\n$(qualifiedTiddler)$-$(target)$-diff\n\\end\n\n\\define diff-plugin-title()\n$(qualifiedTiddler)$-$(target)$-diff!!create-title\n\\end\n\n\\define added-filter()\n[[$(addedTiddlers)$]tags[]]\n\\end\n\n\\define concatPluginTitle(prefix, sep)\n$prefix$$(createTitleOrg)$$sep$$(createTitleName)$\n\\end\n\n\\define tiddlerReference(ref)\n$(currentTiddler)$$ref$\n\\end\n\n\\define varsReference(ref)\n$(TinkaVars)$$ref$\n\\end\n\n\n!! Create New Plugin\n\n<span class=\"tinka-note\">Usage: Enter the necessary metadata for your plugin and use the Filter selection below to pick the tiddlers that should be added to the plugin. After selecting the tiddlers, press 'Package Plugin'. Refer to the [[Documentation|$:/plugins/ahahn/tinka/usage]] for further help.</span>\n\n<$set name=\"target\" value=\"skeleton\">\n<$set name=\"qualifiedTiddler\" value=<<qualify \"$:/temp/tinka/modify\">> >\n\n!!! Step 1: Enter Metadata\n\n\n<$set name=\"currentTiddler\" value=<<qualified-modify-diff>>>\n\t<$transclude mode=\"block\" tiddler=\"$:/plugins/ahahn/tinka/createMetadata\"/>\n</$set>\n\n!!! Step 2: Add Tiddlers\n\nUse the search box below to select the tiddlers you want to add to the plugin.\n\n{{$:/plugins/ahahn/tinka/searchDisplay}}\n\n\n''Added Tiddlers''\n\n<$set name=\"addedTiddlers\" value=<<qualified-modify-add>> >\n<ul>\n<$list filter=<<added-filter>> emptyMessage=\"<i>No tiddlers added.</i>\">\n\t\t<li class=\"tinka-list-item\">\n        <$checkbox tiddler=<<qualified-modify-add>> tag={{!!title}} />\n        <$link to={{!!title}}>{{!!title}}</$link>\n        </li>\n</$list>\n</ul>\n</$set>\n\n\n<$button class=\"tc-btn-big-green tinka-orange\">\n<$set name=\"TinkaVars\" value=\"$:/temp/tinka/CreateVars\">\n<$set name=\"currentTiddler\" value=<<qualified-modify-diff>>>\n\t<$action-deletetiddler $tiddler=<<TinkaVars>> />\n\t<$action-setfield $tiddler=<<TinkaVars>> result=\"false\" />\n\n\t<!-- Check whether a plugin title was given -->\n\t<$tinka-check text={{!!create-title-org}} pattern=\"^[^\\s]+$\">\n\t\t<$tinka-filter verb=\"fail\">\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorTitle=\"The plugin title is not allowed to be empty or contain whitespaces.\"/>\n\t\t</$tinka-filter>\n\t</$tinka-check>\n\t\t\n\t<$tinka-check text={{!!create-title-name}} pattern=\"^[^\\s]+$\">\n\t\t<$tinka-filter verb=\"fail\">\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorTitle=\"The plugin path is not allowed to be empty or contain whitespaces.\"/>\n\t\t</$tinka-filter>\n\t</$tinka-check>\n\t\t\n\t<!-- Check whether a plugin type is set-->\n\t<$tinka-check text={{!!create-plugin-type}} pattern=\"^.+$\">\n\t\t<$tinka-filter verb=\"fail\">\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorType=\"You have to set a plugin type.\"/>\n\t\t</$tinka-filter>\n\t</$tinka-check>\n\t\t\n\t\t<!-- Check whether a name was given, depending on the plugin type-->\n\t\t<$reveal state=<<tiddlerReference \"!!create-plugin-type\">> type=\"match\" text=\"plugin\">\n\t\t\t<$tinka-check text={{!!create-description}} pattern=\"^.+$\">\n\t\t\t\t<$tinka-filter verb=\"fail\">\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorPlugin=\"You have to enter a plugin title.\"/>\n\t\t\t\t</$tinka-filter>\n\t\t\t</$tinka-check>\n\t\t</$reveal>\n\t\t<$reveal state=<<tiddlerReference \"!!create-plugin-type\">> type=\"match\" text=\"theme\">\n\t\t\t<$tinka-check text={{!!create-name}} pattern=\"^.+$\">\n\t\t\t\t<$tinka-filter verb=\"fail\">\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorTheme=\"You have to enter a theme title.\"/>\n\t\t\t\t</$tinka-filter>\n\t\t\t</$tinka-check>\n\t\t</$reveal>\n\t\t\n\t\t<!--Check Version numbers, if entered-->\n\t\t<$reveal state=<<tiddlerReference \"!!create-version\">> type=\"nomatch\" text=\"\">\n\t\t\t<$tinka-check text={{!!create-version}} pattern=\"^(\\d)+\\.(\\d)+\\.(\\d)+(-\\w+)?$\">\n\t\t\t\t<$tinka-filter verb=\"fail\">\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorVersion=\"Version numbers must have the following format: X.X.X (e.g. 1.0.0).\"/>\n\t\t\t\t</$tinka-filter>\n\t\t\t</$tinka-check>\n\t\t</$reveal>\n\t\t\n\t\t<$reveal state=<<tiddlerReference \"!!create-core-version\">> type=\"nomatch\" text=\"\">\n\t\t\t<$tinka-check text={{!!create-core-version}} pattern=\"^(>|>=|<|<=)?(\\d)+\\.(\\d)+\\.(\\d)+(-\\w+)?$\">\n\t\t\t\t<$tinka-filter verb=\"fail\">\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> result=\"true\"/>\n\t\t\t\t\t<$action-setfield $tiddler=<<TinkaVars>> errorCoreVersion=\"The core version number must have the following format: [>|>=|<|<=|]X.X.X-AAAA (e.g. >=5.1.8).\"/>\n\t\t\t\t</$tinka-filter>\n\t\t\t</$tinka-check>\n\t\t</$reveal>\n\n\t<$set name=\"currentTiddler\" value=<<TinkaVars>> >\n\t<$tinka-check text={{!!result}} pattern=\"^false$\">\n\t<$set name=\"currentTiddler\" value=<<qualified-modify-diff>>>\n\t<$tinka-filter verb=\"pass\">\n\t<!--Compute the plugin title (create-title> from the create-title-org and create-title-name fields -->\n\n\t\t<$set name=\"createTitleOrg\" value={{!!create-title-org}}>\n\t\t\t<$set name=\"createTitleName\" value={{!!create-title-name}}>\n                <!--If the plugin is a theme, use a different plugin-prefix -->\n                <$reveal state=<<tiddlerReference \"!!create-plugin-type\">> type=\"match\" text=\"theme\">\n\t\t\t\t    <$action-setfield create-title=<<concatPluginTitle \"$:/themes/\" \"/\">> />\n                </$reveal>\n\n                <$reveal state=<<tiddlerReference \"!!create-plugin-type\">> type=\"nomatch\" text=\"theme\">\n\t\t\t\t    <$action-setfield create-title=<<concatPluginTitle \"$:/plugins/\" \"/\">> />\n                </$reveal>\n\t\t\t</$set>\n\t\t</$set>\n\t\n\t\t<$tinka-saveTaglistToField $target=<<qualified-modify-add>> $tiddler=<<qualified-modify-diff>> $field=\"addTiddlers\"/>\n\t\t<$tinka-repackagePlugin $plugin=\"$:/plugins/unknown/newPlugin\" $create=\"yes\" $diff=<<qualified-modify-diff>> />\n\t\t<$action-deletetiddler $tiddler=<<qualified-modify-add>>/>\n\t\t<$action-deletetiddler $tiddler=<<qualified-modify-diff>>/>\n\t\t<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/packageSuccess\" />\n\t</$tinka-filter>\n\t<$tinka-filter verb=\"fail\">\n\t\t<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/packageErrors\" errorVars=<<TinkaVars>>/>\n\t</$tinka-filter>\n\t</$set>\n\t</$tinka-check>\n\t</$set>\n</$set>\n</$set>\nPackage plugin</$button>\n\n\n</$set>\n</$set>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata/noSpecialPluginType": {
            "title": "$:/plugins/ahahn/tinka/createMetadata/noSpecialPluginType",
            "type": "text/vnd.tiddlywiki",
            "text": "<tr>\n    \t<td>Description:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" placeholder=\"e.g. Tinka - Plugin Packer\" field=\"create-description\"/></td>\n        \n        <td>Name:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" field=\"create-name\"/></td>\n</tr>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata/pluginPluginType": {
            "title": "$:/plugins/ahahn/tinka/createMetadata/pluginPluginType",
            "type": "text/vnd.tiddlywiki",
            "text": "<tr>\n    \t<td>''Plugin Title:''</td>\n        <td colspan=\"3\"><$edit-text class=\"tinka-full-edit\" tag=\"input\" type=\"text\" placeholder=\"e.g. Tinka - Plugin Packer\" field=\"create-description\"/></td>\n</tr>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata/tableEnd": {
            "title": "$:/plugins/ahahn/tinka/createMetadata/tableEnd",
            "type": "text/vnd.tiddlywiki",
            "text": "<tr>\n        <td>Version:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" field=\"create-version\"/></td>\n        \n\t\t<td>Core-Version:</td>\n        <td><$edit-text type=\"text\" placeholder=\"e.g. >=5.1.8\" tag=\"input\" field=\"create-core-version\"/></td>\n\t</tr>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata/tableHead": {
            "title": "$:/plugins/ahahn/tinka/createMetadata/tableHead",
            "type": "text/vnd.tiddlywiki",
            "text": "\t<tr>\n\t\t<td>''Plugin Path:''</td>\n        <td colspan=\"3\">`$:/plugins/`<$edit-text class=\"tinka-inline-edit\" type=\"text\" placeholder=\"e.g. myName\" tag=\"input\" field=\"create-title-org\"/>`/`<$edit-text type=\"text\" class=\"tinka-inline-edit\" placeholder=\"e.g. myPlugin\" tag=\"input\" field=\"create-title-name\" /></td> \n\t</tr>\n    \n    <tr>\n\t\t<td>Author:</td>\n        <td><$edit-text type=\"text\" placeholder=\"e.g. John Doe\" tag=\"input\" field=\"create-author\"/></td>\n\t\t\n\t\t<td>Source:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" placeholder=\"e.g. http://twguides.org\" field=\"source\"/></td>\n\t</tr>\n\n\t<tr>\n\t\t<td>Dependents:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" field=\"create-dependents\"/></td>\n        \n        <td>List:</td>\n        <td><$edit-text tag=\"input\" type=\"text\" placeholder=\"e.g. readme usage\" field=\"create-list\"/></td>\n  \t</tr>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata/themePluginType": {
            "title": "$:/plugins/ahahn/tinka/createMetadata/themePluginType",
            "type": "text/vnd.tiddlywiki",
            "text": "<tr>\n    <td>''Theme Title:''</td>\n    <td colspan=\"3\"><$edit-text  class=\"tinka-full-edit\" tag=\"input\" type=\"text\" placeholder=\"e.g. My cool theme\" field=\"create-name\"/></td>\n</tr>\n\n<tr>\n        <td>Description:</td>\n        <td colspan=\"3\"><$edit-text class=\"tinka-full-edit\" tag=\"input\" type=\"text\" placeholder=\"e.g. My description\" field=\"create-description\"/></td>\n</tr>\n"
        },
        "$:/plugins/ahahn/tinka/createMetadata": {
            "create-plugin-type": "plugin",
            "create-title": "",
            "created": "20150429174811520",
            "modified": "20170225181341996",
            "tags": "",
            "title": "$:/plugins/ahahn/tinka/createMetadata",
            "type": "text/vnd.tiddlywiki",
            "text": "''Plugin-Type:'' <$edit-text tag=\"input\" type=\"text\" field=\"create-plugin-type\"/>\n        <$button popup=\"$:/temp/tinka/NewPluginPopup\" class=\"tc-btn-invisible tc-btn-dropdown\">{{$:/core/images/down-arrow}}</$button>\n\t\n\t\t<$reveal state=\"$:/temp/tinka/NewPluginPopup\" type=\"popup\" position=\"below\">\n\t\t<div class=\"tc-block-dropdown tc-edit-type-dropdown\">\n\t\t<$linkcatcher to=\"!!create-plugin-type\">\n\t\t\t<$link to=\"plugin\">Plugin</$link>\n\t\t\t<$link to=\"theme\">Theme</$link>\n\t\t</$linkcatcher>\n\t\t</div>\n\t\t</$reveal>\n\n<$reveal state=\"!!create-plugin-type\" type=\"nomatch\" text=\"plugin\" >\n\t<$reveal state=\"!!create-plugin-type\" type=\"nomatch\" text=\"theme\" >\n\t\t<table class=\"tinka-meta-table\">\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableHead\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/noSpecialPluginType\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableEnd\" />\n\t\t</table>\n\t</$reveal>\n</$reveal>\n\n<$reveal state=\"!!create-plugin-type\" type=\"match\" text=\"plugin\">\n\t\t<table class=\"tinka-meta-table\">\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableHead\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/pluginPluginType\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableEnd\" />\n\t\t</table>\n</$reveal>\n\n<$reveal state=\"!!create-plugin-type\" type=\"match\" text=\"theme\">\n\t\t<table class=\"tinka-meta-table\">\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableHead\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/themePluginType\" />\n\t\t<$transclude tiddler=\"$:/plugins/ahahn/tinka/createMetadata/tableEnd\" />\n\t\t</table>\n</$reveal>\n\n''bold'' = //required field//\n"
        },
        "$:/plugins/ahahn/tinka/dropdownManage": {
            "title": "$:/plugins/ahahn/tinka/dropdownManage",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define plugin-tiddler-selection()\n[[$(target)$]plugintiddlers[]]\n\\end\n\n\\define qualified-remove-popup()\n$:/state/popup/$(qualifiedTiddler)$-$(target)$-remove-popup\n\\end\n\n\\define qualified-modify-remove()\n$(qualifiedTiddler)$-$(target)$-remove\n\\end\n\n\\define qualified-modify-add()\n$(qualifiedTiddler)$-$(target)$-add\n\\end\n\n\\define qualified-modify-diff()\n$(qualifiedTiddler)$-$(target)$-diff\n\\end\n\n\\define target-type()\n$(target)$!!plugin-type\n\\end\n\n\\define added-filter()\n[[$(addedTiddlers)$]tags[]]\n\\end\n\n\\define pluginSuffixFilter()\n[[$(target)$]prefix[$:/plugins/]removeprefix[$:/plugins/]] [[$(target)$]!prefix[$:/plugins/]]\n\\end\n\n\\define sideTabNameBuilder()\n$:/plugins/ahahn/tinka/temp/$(pluginSuffix)$ - Help Tab\n\\end\n\n\\define helpTabCaption()\n$(pluginSuffix)$ - Help Tab\n\\end\n\n\\define helpTabText()\n<$set name=\"pluginPrefix\" value=\"$(target)$\" >\n<$set name=\"currentTiddler\" value=\"$(sideTabName)$\" >\n\n<$transclude tiddler=\"$:/plugins/ahahn/tinka/pluginSidePanel\" />\n\n</$set>\n</$set>\n\\end\n\n<$set name=\"qualifiedTiddler\" value=<<qualify \"$:/temp/tinka/modify\">> >\n\n<$list filter=<<pluginSuffixFilter>> variable=\"pluginSuffix\">\n<<SidebarTabName>>\n<$set name=\"sideTabName\" value=<<sideTabNameBuilder>> >\n\n<$reveal state=<<sideTabName>> type=\"match\" text=\"\">\n<$button>Enable Help-Tab\n<$action-setfield $tiddler=<<sideTabName>> text=<<helpTabText>> caption=<<helpTabCaption>> tags=\"$:/tags/SideBar\" />\n</$button>\n\n</$reveal>\n\n<$reveal state=<<sideTabName>> type=\"nomatch\" text=\"\">\n<$button>Disable Help-Tab\n<$action-deletetiddler $tiddler=<<sideTabName>> />\n</$button>\n</$reveal>\n</$set>\n</$list>\n\nIf you have edited the shadow tiddlers that belong to the plugin, just repackage without making any changes. That way the packaged plugin will incorporate the changes made to the individual tiddlers. Refer to the [[Documentation|$:/plugins/ahahn/tinka/usage]] for help.\n\nIt is recommended to create a backup before repackaging a plugin.\n\n!!! Edit Metadata\n<span class=\"tinka-note\">Note: Changes will be committed immediately.</span>\n\n<$set name=\"currentTiddler\" value=<<target>>>\n\t<$transclude mode=\"block\" tiddler=\"$:/plugins/ahahn/tinka/editMetadata\"/>\n</$set>\n\n!!! Remove Tiddlers\n<span class=\"tinka-note\">Note: Re-packaging required for changes to take effect.</span>\n\n<$reveal type=\"match\" text=\"\" state=<<qualified-remove-popup>> ><$button set=<<qualified-remove-popup>> setTo=\"show\" class=\"tc-btn-invisible\">{{$:/core/images/right-arrow}} Show plugin tiddlers</$button></$reveal>\n<$reveal type=\"nomatch\" text=\"\" state=<<qualified-remove-popup>> >\n<$button set=<<qualified-remove-popup>> setTo=\"\" class=\"tc-btn-invisible\">{{$:/core/images/down-arrow}} Hide plugin tiddlers</$button>\n<ul>\n\t<$list filter=<<plugin-tiddler-selection>> emptyMessage=\"<i>No tiddlers in plugin.</i>\">\n\t\t<li class=\"tinka-list-item\">\n        <$checkbox tiddler=<<qualified-modify-remove>> tag={{!!title}} />\n        <$link to={{!!title}}><$text text={{!!title}} /></$link></li>\n\t</$list>\n</ul>\n</$reveal>\n\n!!! Add Tiddlers\n<span class=\"tinka-note\">Note: Re-packaging required for changes to take effect.</span>\n\nUse the search box below to select the tiddlers you want to add to the plugin.\n\n{{$:/plugins/ahahn/tinka/searchDisplay}}\n\n\n''Added Tiddlers''\n\n<$set name=\"addedTiddlers\" value=<<qualified-modify-add>> >\n<ul>\n<$list filter=<<added-filter>> emptyMessage=\"<i>No tiddlers added.</i>\">\n\t\t<li class=\"tinka-list-item\">\n        <$checkbox tiddler=<<qualified-modify-add>> tag={{!!title}} />\n        <$link to={{!!title}}>{{!!title}}</$link>\n        </li>\n</$list>\n</ul>\n</$set>\n\n<$reveal state=<<target-type>> type=\"match\" text=\"theme\">\n<span class=\"tinka-note-red\">Warning: Themes can only be repackaged if the theme is currently active or loaded as a dependant!</span>\n</$reveal>\n\n\n<$button class=\"tc-btn-big-green tinka-orange\">\n<$tinka-saveTaglistToField $target=<<qualified-modify-remove>> $tiddler=<<qualified-modify-diff>> $field=\"removeTiddlers\"/>\n<$tinka-saveTaglistToField $target=<<qualified-modify-add>> $tiddler=<<qualified-modify-diff>> $field=\"addTiddlers\"/>\n<$tinka-repackagePlugin $plugin=<<target>> $create=\"no\" $diff=<<qualified-modify-diff>> />\n<$action-deletetiddler $tiddler=<<qualified-modify-remove>>/>\n<$action-deletetiddler $tiddler=<<qualified-modify-add>>/>\n<$action-deletetiddler $tiddler=<<qualified-modify-diff>>/>\n<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/packageSuccess\" />Re-package plugin</$button>\n<$button class=\"tc-btn-big-green tinka-blue\">\n<$tinka-backupPlugin $plugin=<<target>> />\n<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/backupSuccess\" />Create Backup</$button>\n\n</$set>\n"
        },
        "$:/plugins/ahahn/tinka/editMetadata": {
            "title": "$:/plugins/ahahn/tinka/editMetadata",
            "type": "text/vnd.tiddlywiki",
            "text": "|tinka-meta-table|k\n|Author:|<$edit-text type=\"text\" tag=\"input\" field=\"author\"/>|Description:|<$edit-text tag=\"input\" type=\"text\" field=\"description\"/>|\n|Dependents:|<$edit-text tag=\"input\" type=\"text\" field=\"dependents\"/>|List:|<$edit-text tag=\"input\" type=\"text\" field=\"list\"/>|\n|Plugin-Type:|<$edit-text tag=\"input\" type=\"text\" field=\"plugin-type\"/>|Version:|<$edit-text tag=\"input\" type=\"text\" field=\"version\"/>|\n|Source:|<$edit-text tag=\"input\" type=\"text\" field=\"source\"/>|Name:|<$edit-text tag=\"input\" type=\"text\" field=\"name\"/>|\n|Core-Version:|<$edit-text tag=\"input\" type=\"text\" field=\"core-version\"/>|||\n"
        },
        "$:/plugins/ahahn/tinka/backupSuccess": {
            "caption": "Backup Success",
            "subtitle": "Backup Success",
            "title": "$:/plugins/ahahn/tinka/backupSuccess",
            "type": "text/vnd.tiddlywiki",
            "text": "<div class=\"tinka-success\">\n\n!!{{$:/core/images/done-button}} Backup Success !\n\nA backup of the plugin was successfully created.\n\n</div>\n"
        },
        "$:/plugins/ahahn/tinka/packageErrors": {
            "caption": "Packaging Errors!",
            "subtitle": "Packaging Errors!",
            "title": "$:/plugins/ahahn/tinka/packageErrors",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define errorFilter()\n[[$(errorVars)$]fields[]prefix[error]]\n\\end\n\n\n<div class=\"tinka-error\">\n\n!!{{$:/core/images/close-button}} There were some errors !\n\nThe follwoing errors occured whilst processing your request:\n\n<ul>\n\t<$list filter=<<errorFilter>> variable=\"errorField\">\n\t\t<li><$view tiddler=<<errorVars>> field=<<errorField>> /></li>\n\t</$list>\n</ul>\n</div>\n"
        },
        "$:/plugins/ahahn/tinka/packageSuccess": {
            "caption": "Packaging Success",
            "subtitle": "Packaging Success",
            "title": "$:/plugins/ahahn/tinka/packageSuccess",
            "type": "text/vnd.tiddlywiki",
            "text": "<div class=\"tinka-success\">\n\n!!{{$:/core/images/done-button}} (Re-)Packaging Success !\n\nThe plugin was successfully (re-)packaged. It is recommended to <u>save and reload</u> the wiki now in order to avoid plugins to misbehave.\n\n    <div class=\"tinka-centered-container\">\n        <span class=\"tinka-saving\">{{$:/core/images/save-button}} Saving...<br/><sub>(If your wiki doesn't save automatically, please save&reload manually.)</sub></span>\n        <$button class=\"tc-btn-big-green tinka-enlarge tinka-orb tinka-button-refresh\">\n            <$action-sendmessage $message=\"tm-browser-refresh\" />\n            {{$:/core/images/refresh-button}}\n            <p>\n                <b>RELOAD NOW!</b>\n            </p>\n        </$button>\n    </div>\n</div>\n"
        },
        "$:/plugins/ahahn/tinka/restoreSuccess": {
            "caption": "Restore Successful",
            "subtitle": "Restore Successful",
            "title": "$:/plugins/ahahn/tinka/restoreSuccess",
            "type": "text/vnd.tiddlywiki",
            "text": "<div class=\"tinka-success\">\n\n!!{{$:/core/images/done-button}} Restore Success !\n\nThe backup was successfully restored!\n\n</div>\n"
        },
        "$:/plugins/ahahn/tinka/pluginManagement": {
            "caption": "Installed",
            "tags": "$:/tags/tinka/ControlPanel",
            "title": "$:/plugins/ahahn/tinka/pluginManagement",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define popup-state-macro()\n$:/state/popup-$(qualified-state)$-$(currentTiddler)$\n\\end\n\n\\define tabs-state-macro()\n$(popup-state)$-$(pluginInfoType)$\n\\end\n\n\\define plugin-icon-title()\n$(currentTiddler)$/icon\n\\end\n\n\\define plugin-disable-title()\n$:/config/Plugins/Disabled/$(currentTiddler)$\n\\end\n\n\\define plugin-table-body(type,disabledMessage)\n<div class=\"tc-plugin-info-chunk tc-small-icon\">\n<$reveal type=\"nomatch\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"yes\">\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n<$reveal type=\"match\" state=<<popup-state>> text=\"yes\">\n<$button class=\"tc-btn-invisible tc-btn-dropdown\" set=<<popup-state>> setTo=\"no\">\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<$transclude tiddler=<<currentTiddler>> subtiddler=<<plugin-icon-title>>>\n<$transclude tiddler=\"$:/core/images/plugin-generic-$type$\"/>\n</$transclude>\n</div>\n<div class=\"tc-plugin-info-chunk\">\n<h1>\n''<$view field=\"description\"><$view field=\"title\"/></$view>'' $disabledMessage$\n</h1>\n<h2>\n<$view field=\"title\"/>\n</h2>\n<h2>\n<div><em><$view field=\"version\"/></em></div>\n</h2>\n</div>\n\\end\n\n\\define plugin-table(type)\n<$set name=\"qualified-state\" value=<<qualify \"$:/state/plugin-info\">>>\n<$list filter=\"[!has[draft.of]plugin-type[$type$]sort[description]]\" emptyMessage=<<lingo \"Empty/Hint\">>>\n<$set name=\"popup-state\" value=<<popup-state-macro>>>\n<$link to={{!!title}} class=\"tc-plugin-info\">\n<<plugin-table-body type:\"$type$\">>\n</$link>\n<$reveal type=\"match\" text=\"yes\" state=<<popup-state>>>\n<div class=\"tc-plugin-info-dropdown\">\n<div class=\"tc-plugin-info-dropdown-body\">\n<$set name=\"target\" value={{!!title}}>\n\n{{$:/plugins/ahahn/tinka/dropdownManage}}\n\n</$set>\n</div>\n</div>\n</$reveal>\n</$set>\n</$list>\n</$set>\n\\end\n\n!!Installed Plugins\n\n<<plugin-table plugin>>\n\n!!Installed Themes\n\n<<plugin-table theme>>\n"
        },
        "$:/plugins/ahahn/tinka/pluginSidePanel": {
            "title": "$:/plugins/ahahn/tinka/pluginSidePanel",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define pluginFilter()\n[[$(pluginPrefix)$]plugintiddlers[]sort[]]\n\\end\n\n\\define pluginDirFilter()\n[all[tiddlers]prefix[$(pluginPrefix)$]sort[]]\n\\end\n\n\\define newPluginTiddler()\n$(pluginPrefix)$/New Tiddler\n\\end\n\n<$button class=\"tc-btn-invisible tinka-invisible\">\n<$action-sendmessage $message=\"tm-new-tiddler\" $param=<<newPluginTiddler>> />''\n{{$:/core/images/new-button}} Add Tiddler''</$button>\n\n!!!Shadow tiddlers contained in the plugin:\n\n<$list filter=<<pluginFilter>> template=\"$:/core/ui/ListItemTemplate\"/>\n\n!!!Normal tiddlers in the plugin directory:\n<$list filter=<<pluginDirFilter>> template=\"$:/core/ui/ListItemTemplate\"/>\n\n<$reveal state=\"!!extender\" type=\"nomatch\" text=\"open\">\n<$button set=\"!!extender\" setTo=\"open\" class=\"tc-btn-invisible tinka-sidebar-button\"><h3>{{$:/core/images/chevron-right}} Filter search</h3></$button>\n</$reveal>\n<$reveal state=\"!!extender\" type=\"match\" text=\"open\">\n<$button set=\"!!extender\" setTo=\"close\" class=\"tc-btn-invisible tinka-sidebar-button\"><h3>{{$:/core/images/chevron-down}} Filter search</h3></$button>\n<div>\n<$edit-text type=\"search\" tiddler=\"$:/plugins/ahahn/tinka/temp/helpTabSearch\" field=\"filterSearch\" />\n<$list filter={{$:/plugins/ahahn/tinka/temp/helpTabSearch!!filterSearch}} template=\"$:/core/ui/ListItemTemplate\"/>\n</div>\n</$reveal>\n\n<$button class=\"tc-btn-big-green tinka-orange\">\n<$tinka-repackagePlugin $plugin=<<pluginPrefix>> $create=\"no\" $diff=\"$:/plugins/ahahn/tinka/emptyDiff\" />\n<$action-sendmessage $message=\"tm-modal\" $param=\"$:/plugins/ahahn/tinka/packageSuccess\" />Quick-Package</$button>\n<$button class=\"tc-btn-big-green tinka-blue\">\n<$action-deletetiddler $tiddler=<<currentTiddler>> />\nDisable Help Tab</$button>\n"
        },
        "$:/plugins/ahahn/tinka/search-default": {
            "caption": "Default search",
            "tags": "$:/tags/TinkaSearch",
            "title": "$:/plugins/ahahn/tinka/search-default",
            "type": "text/vnd.tiddlywiki",
            "text": "\\define searchstring()\n[all[tiddlers]search:title{$(searchTiddler)$}sort[title]]\n\\end\n\nEnter search term: <$edit-text tiddler=\"$:/temp/tinka/search\" type=\"search\" default=\"\" tag=\"input\"/> <$reveal state=\"$:/temp/tinka/search\" type=\"nomatch\" text=\"\"><$button class=\"tc-btn-invisible\" set=\"$:/temp/tinka/search\" setTo=\"\">{{$:/core/images/close-button}}</$button></$reveal>\n\n<$reveal state=\"$:/temp/tinka/search\" type=\"nomatch\" text=\"\">\n    <$set name=\"searchTiddler\" value=\"$:/temp/tinka/search\">\n    <ul>\n    <$list filter=<<searchstring>> emptyMessage=\"<li class='tinka-list-item'><i>No Tiddlers selected.</i></li>\">\n            <li class=\"tinka-list-item\">\n            <$checkbox tiddler=<<qualified-modify-add>> tag={{!!title}} />\n            <$link to={{!!title}}><$text text={{!!title}} /></$link>\n            </li>\n    </$list>\n    </ul>\n    </$set>\n</$reveal>\n\n<!--Empty search string would list all tiddlers-->\n<$reveal state=\"$:/temp/tinka/search\" type=\"match\" text=\"\">\n    <ul>\n        <li class=\"tinka-list-item\"><i>No Tiddlers selected.</i></li>\n    </ul>\n</$reveal>\n\n\n"
        },
        "$:/plugins/ahahn/tinka/search-filter": {
            "caption": "Filter search",
            "list-after": "$:/plugins/ahahn/tinka/search-default",
            "tags": "$:/tags/TinkaSearch",
            "title": "$:/plugins/ahahn/tinka/search-filter",
            "type": "text/vnd.tiddlywiki",
            "text": "Enter Filterstring to select tiddlers: <$edit-text tiddler=\"$:/temp/tinka/search\" type=\"search\" default=\"\" tag=\"input\"/> <$reveal state=\"$:/temp/tinka/search\" type=\"nomatch\" text=\"\"><$button class=\"tc-btn-invisible\" set=\"$:/temp/tinka/search\" setTo=\"\">{{$:/core/images/close-button}}</$button></$reveal>\n<ul>\n<$list filter={{$:/temp/tinka/search}} emptyMessage=\"<li class='tinka-list-item'><i>No Tiddlers selected.</i></li>\">\n\t\t<li class=\"tinka-list-item\">\n        <$checkbox tiddler=<<qualified-modify-add>> tag={{!!title}} />\n        <$link to={{!!title}}><$text text={{!!title}} /></$link>\n        </li>\n</$list>\n</ul>\n"
        },
        "$:/plugins/ahahn/tinka/searchDisplay": {
            "title": "$:/plugins/ahahn/tinka/searchDisplay",
            "type": "text/vnd.tiddlywiki",
            "text": "<<tabs \"[[$:/plugins/ahahn/tinka/search-default]] [[$:/plugins/ahahn/tinka/search-filter]]\" \"$:/plugins/ahahn/tinka/search-default\" \"$:/temp/tinka/searchTab\">>\n"
        },
        "$:/plugins/ahahn/tinka/usage": {
            "caption": "Usage/Help",
            "created": "20150430092825762",
            "modified": "20170225181342015",
            "tags": "",
            "title": "$:/plugins/ahahn/tinka/usage",
            "type": "text/vnd.tiddlywiki",
            "text": "{{$:/plugins/ahahn/tinka/docs/How to create a new plugin}}\n\n{{$:/plugins/ahahn/tinka/docs/Help Tab}}\n\n!! Notes\n\nWhen packaging or repackaging a plugin, the version number of the plugin is automatically increased. This might not be wanted in all cases and has to be manually corrected after packaging.\n\nAlso version suffixes such as:\n\n* -prerelease\n* -beta\n\nare supported and will be appended to the new version number when present.\n\n!! Plugin mechanism\nFor more information about how the plugin mechanism in TiddlyWiki works, see the official documentation: http://tiddlywiki.com/#PluginMechanism\n\n!! Filter language\nFilters are useful to select a subset of tiddlers from a wiki. If you are new to filters, learn more about them here: http://tiddlywiki.com/#Filters"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/ebalster/formula/coerce.js": {
            "text": "/*\\\ntitle: $:/plugins/ebalster/formula/coerce.js\ntype: application/javascript\nmodule-type: macro\n\nType coercion logic for formulas.\nSupported types for coercion:\n\n* text\n* number\n* boolean\n* array\n* date\n\nAdditional types that may be coerced:\n\n* undefined\n* regular expression\n\n\\*/\n(function(){\n\n\"use strict\";\n\n\n// Value-to-text coercion.\nvar _ToText = {\n\t\"undefined\" : function(v,ctx) {return \"undefined\";},\n\t\"string\"    : function(v,ctx) {return v;},\n\t\"number\"    : function(v,ctx) {return ctx.formats.number(v);},\n\t\"symbol\"    : function(v,ctx) {return String(v);},\n\t\"function\"  : function(v,ctx) {return \"function\" + (v.formulaSrc || \" [built-in]\");},\n\t\"boolean\"   : function(v,ctx) {return (v ? \"TRUE\" : \"FALSE\");},\n\t\"object\"    : function(v,ctx) {\n\t\tif (v instanceof Date)   return ctx.formats.date(v);\n\t\tif (v instanceof Array)  return ctx.formats.array(v,ctx);\n\t\tif (v instanceof RegExp) return String(v);\n\t\tif (v instanceof Error)  throw v;\n\t\treturn JSON.stringify(v); // Last resort\n\t},\n};\n\n// Value-to-number coercion.\nvar _ToNum = {\n\t\"undefined\" : function(v,ctx) {throw \"Cannot convert undefined value to number!\";},\n\t\"string\"    : function(v,ctx) {\n\t\tvar n = Number(v);\n\t\tif (isNaN(n)) throw \"Cannot convert \\\"\"+v+\"\\\" to number!\";\n\t\treturn n;\n\t},\n\t\"number\"    : function(v,ctx) {return v;},\n\t\"symbol\"    : function(v,ctx) {throw \"Cannot convert symbol to number!\";},\n\t\"function\"  : function(v,ctx) {throw \"Cannot convert function to number!\";},\n\t\"boolean\"   : function(v,ctx) {return (v ? 1 : 0);},\n\t\"object\"    : function(v,ctx) {throw \"Cannot convert \\\"\" + _ToText.object(v,ctx) + \"\\\" to number!\";},\n};\n\n// Value-to-boolean coercion.\nvar _ToBool = {\n\t\"undefined\" : function(v,ctx) {return false;},\n\t\"string\"    : function(v,ctx) {return !(/^\\s*(undefined|false|null|0+|0*\\.0+|0+\\.0*|)\\s*$/i.test(v));},\n\t\"number\"    : function(v,ctx) {return Boolean(v);},\n\t\"symbol\"    : function(v,ctx) {return Boolean(v);},\n\t\"function\"  : function(v,ctx) {return true;},\n\t\"boolean\"   : function(v,ctx) {return v;},\n\t\"object\"    : function(v,ctx) {return Boolean(v);},\n};\n\nexports.ToSelf = function ToSelf(v,ctx) {return v;};\nexports.ToText = function ToText(v,ctx) {return _ToText[typeof v](v,ctx);};\nexports.ToNum  = function ToNum (v,ctx) {return _ToNum [typeof v](v,ctx);};\nexports.ToBool = function ToBool(v,ctx) {return _ToBool[typeof v](v,ctx);};\n\nexports.ToDate = function ToDate(v,ctx) {\n\tif (v instanceof Date) return v;\n\tthrow \"Cannot auto-convert \\\"\" + exports.ToText(v,ctx) + \"\\\" to a date!\";\n};\n\nvar rxJsRegex = /^\\/((?:[^\\\\\\/\\[]|\\[(?:[^\\]]|\\\\\\])*\\]|\\\\.)+)\\/([a-z]*)$/;\nvar rxTwRegexFlags = /^\\(\\?[a-z]*\\)|\\(\\?[a-z]*\\)$/i;\n\nexports.ToRegex = function ToRegex(v,ctx) {\n\tif (v instanceof RegExp) return v;\n\tif (typeof v === \"string\") {\n\t\tv = v.trim();\n\t\t// Try JavaScript style regex\n\t\tvar match = rxJsRegex.exec(v);\n\t\tif (match) {\n\t\t\treturn new RegExp(term[1].replace(\"\\\\/\", \"/\"), term[2]);\n\t\t}\n\t\t// Try TiddlyWiki style regex\n\t\tmatch = rxTwRegexFlags.exec(v);\n\t\tif (match) {\n\t\t\tvar flagLen = match[0].length;\n\t\t\tvar flags = match[0].substr(2, match[0].length-3);\n\t\t\tif (match.index == 0) return new RegExp(v.substr(flagLen), flags);\n\t\t\telse                  return new RegExp(v.substr(0, v.length-flagLen), flags);\n\t\t}\n\t\treturn new RegExp(v, \"g\");\n\t\t\n\t}\n\tthrow \"Cannot auto-convert \\\"\" + exports.ToText(v,ctx) + \"\\\" to a regular expression!\";\n};\nexports.ToArray = function ToArray(v,ctx) {\n\tif (v instanceof Array) return v;\n\tthrow \"Cannot auto-convert \\\"\" + exports.ToText(v,ctx) + \"\\\" to an array!\";\n};\nexports.ToFunc = function ToFunc(v,ctx) {\n\tif (v instanceof Function) return v;\n\tthrow \"Cannot convert \\\"\" + exports.ToText(v,ctx) + \"\\\" to a function!\";\n};\n// Maybe add ToRegex\n\n\n// Build a coerce rule from a source string.\nvar CoerceFuncs = {\n\tT: exports.ToText,\n\tN: exports.ToNum,\n\tB: exports.ToBool,\n\tA: exports.ToArray,\n\tD: exports.ToDate,\n\tR: exports.ToRegex,\n\tF: exports.ToFunc,\n\t_: exports.ToSelf,\n};\n\nfunction BuildCoerceRule(src) {\n\tvar rule = {\n\t\tmain: [],\n\t\textra: [],\n\t};\n\tvar i = 0, func;\n\t// Main part\n\twhile (i < src.length) {\n\t\tfunc = CoerceFuncs[src[i]]; ++i;\n\t\tif (func) {rule.main.push(func); continue;}\n\t\tif (src[i-1] == '+') break;\n\t\tthrow \"Unknown coerce rule: '\"+src[i-1]+\"'\";\n\t}\n\t// Extra arguments (loops)\n\twhile (i < src.length) {\n\t\tfunc = CoerceFuncs[src[i]]; ++i;\n\t\tif (func) {rule.extra.push(func); continue;}\n\t\tthrow \"Unknown coerce rule: '\"+src[i-1]+\"'\";\n\t}\n\treturn rule;\n}\n\nvar NoCoerce = {rule: {main:[], extra:[]}, gen: []};\nvar CoerceCache = {'': NoCoerce};\n\nfunction GetCoerceCache(src) {\n\tif (!CoerceCache[src]) {\n\t\ttry {\n\t\t\tCoerceCache[src] = {rule: BuildCoerceRule(src), gen: []};\n\t\t}\n\t\tcatch (err) {\n\t\t\tthrow err + \" in rule string '\" + src + \"'\";\n\t\t}\n\t}\n\treturn CoerceCache[src];\n}\n\n// Generate the coercing function array.\nfunction GenCoerceFuncs(rule,len) {\n\tvar result = [], i = 0, x = 0;\n\tresult = rule.main;\n\tif (rule.extra.length) {\n\t\twhile (result.length < len) result = result.concat(rule.extra);\n\t}\n\treturn result;\n}\n\n// Get an array of coercing (ToXXX) functions based on the function.\nexports.GetCoerceFuncs = function GetCoerceFuncs(func,args) {\n\t// Possibly set up coercion for this function.\n\tif (!func._coerce) {\n\t\tif (func.inCast) {\n\t\t\ttry {\n\t\t\t\tfunc._coerce = GetCoerceCache(func.inCast);\n\t\t\t}\n\t\t\tcatch (err) {\n\t\t\t\tthrow err + \" for function \" + func.toString();\n\t\t\t}\n\t\t}\n\t\telse {\n\t\t\tfunc._coerce = NoCoerce;\n\t\t}\n\t}\n\tvar gen = func._coerce.gen[args.length];\n\tif (gen) return gen;\n\tgen = GenCoerceFuncs(func._coerce.rule, args.length);\n\tfunc._coerce.gen[args.length] = gen;\n\treturn gen;\n};\n\n\n// Coerce\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/coerce.js",
            "tags": "",
            "module-type": "library",
            "modified": "20180112071139424",
            "description": "",
            "created": "20180113183000431"
        },
        "$:/plugins/ebalster/formula/compile.js": {
            "text": "(function(){\n\n\"use strict\";\n\nvar Nodes  = require(\"$:/plugins/ebalster/formula/nodes.js\");\n\nvar rxDatumIsFormula      = /^\\s*\\(=.*=\\)\\s*$/;\nvar rxDatumIsTrue         = /^s*TRUE\\s*$/i;\nvar rxDatumIsFalse        = /^s*FALSE\\s*$/i;\n\nvar rxLet               = /let/gi;\n\nvar rxSkipInert         = /(\\s*|\\/\\/.*?([\\r\\n]|$)|\\/\\*[\\s\\S]*?\\*\\/)*/g;\nvar rxNotWhitespace     = /[^\\s]+/g;\nvar rxOperandFilter     = /\\[(([^\\[\\]]|\\[[^\\[\\]]*\\])+(\\](\\s*[+-])?\\s*\\[)?)+\\]/g;\nvar rxOperandTransclusion =     /\\{\\{([^\\{\\}]+)\\}\\}/g;\nvar rxDatumIsTransclusion = /^\\s*\\{\\{([^\\{\\}]+)\\}\\}\\s*$/;\nvar rxOperandVariable     =     /<<([^<>]+)>>/g;\nvar rxDatumIsVariable     = /^\\s*<<[^<>]+>>\\s*$/;\nvar rxCellName            = /\\$?([A-Z]{1,2})\\$?([0-9]+)/g;\nvar rxCellRange           = /\\$?([A-Z]{1,2})\\$?([0-9]+):\\$?([A-Z]{1,2})\\$?([0-9]+)/g;\nvar rxIdentifier          = /[_a-zA-Z][_a-zA-Z0-9]*/g;\nvar rxKeyword             = /(function|let|for|foreach|if|then|else|while|do|this|self|currentTiddler)/gi;\n\nvar rxUnsignedDecimal =          /((\\d+(\\.\\d*)?)|(\\.\\d+))/g;\nvar rxDecimal         =     /[+-]?((\\d+(\\.\\d*)?)|(\\.\\d+))/g;\nvar rxDatumIsDecimal  = /^\\s*[+-]?((\\d+(\\.\\d*)?)|(\\.\\d+))\\s*$/;\n\nvar rxDate            =     /\\d{2,4}-\\d{2}-\\d{2}(\\s*\\d{1,2}:\\d{2}(:\\d{2}(.\\d+)?)?)?/g;\nvar rxDatumIsDate     = /^\\s*\\d{2,4}-\\d{2}-\\d{2}(\\s*\\d{1,2}:\\d{2}(:\\d{2}(.\\d{3})?)?)?\\s*$/;\nvar rxRegex           =     /\\/((?:[^\\\\\\/\\[]|\\[(?:[^\\]]|\\\\\\])*\\]|\\\\.)+)\\/([a-z]*)/g;\nvar rxDatumIsRegex    = /^\\s*\\/((?:[^\\\\\\/\\[]|\\[(?:[^\\]]|\\\\\\])*\\]|\\\\.)+)\\/([a-z]*)\\s*$/;\nvar rxDatumIsTwDate   = /^([0-9]{4})(1[0-2]|0[1-9])(3[01]|[12][0-9]|0[1-9])(2[0-3]|[01][0-9])([0-5][0-9])([0-5][0-9])([0-9]{3})?$/;\nvar rxDateFragment    = /\\d+/g;\n\nvar rxString          = /(\"(\\\\.|[^\"\\\\])*\"|'(\\\\.|[^'\\\\])*')/g;\nvar rxEscapeSequence  = /\\\\([a-tv-z0\"'\\\\]|u[a-fA-F0-9]{0,4}|$)/g;\n\nvar formulaFunctions   = null;\nvar operatorsUnaryPre  = null;\nvar operatorsUnaryPost = null;\nvar operatorsBinary    = null;\nvar operatorsTernary   = null;\n\nfunction Parser(src)\n{\n\tthis.src = src;\n\tthis.pos = 0;\n\tthis.end = src.length;\n\tthis.locals = {};\n\tthis.localStack = [];\n\tthis.assignStack = [];\n}\nParser.prototype.getChar = function()\n{\n\treturn this.src.charAt(this.pos);\n};\nParser.prototype.nextGlyph = function()\n{\n\tthis.skipInert();\n\tif (this.pos >= this.end) return '';\n\t++this.pos;\n\treturn this.src.charAt(this.pos-1);\n};\nParser.prototype.remaining = function()\n{\n\treturn this.src.substring(this.pos, this.end);\n};\nParser.prototype.nextToken = function()\n{\n\tthis.skipInert();\n\trxNotWhitespace.lastIndex = this.pos;\n\trxNotWhitespace.test(this.src);\n\treturn this.src.substring(this.pos, rxNotWhitespace.lastIndex);\n};\nParser.prototype.match_here = function(regex)\n{\n\t// TODO this is doing much more work than is necessary\n\tregex.lastIndex = this.pos;\n\tvar result = regex.exec(this.src);\n\tif (!result || result.index != this.pos || result.index+result[0].length > this.end) return null;\n\tthis.pos = regex.lastIndex;\n\treturn result;\n};\nParser.prototype.skipInert = function()\n{\n\trxSkipInert.lastIndex = this.pos;\n\trxSkipInert.test(this.src);\n\tthis.pos = Math.min(rxSkipInert.lastIndex, this.end);\n};\n\n// Push a new set of local variables onto the parser's stack.\nParser.prototype.pushLocals = function(assigns) {\n\tvar id;\n\tvar newLocals = {};\n\tthis.localStack.push(this.locals); for (id in this.locals) newLocals[id] = 0;\n\tthis.assignStack.push(assigns);    for (id in assigns)     newLocals[id] = 0;\n\tthis.locals = newLocals;\n};\n\n// Pop the last set of local variables off the parser's stack and return usage-counts.\nParser.prototype.popLocals = function() {\n\tvar id, count, usage = {captures: {}, assigns: {}},\n\t\tassigns = this.assignStack.pop(),\n\t\toldLocals = this.localStack.pop();\n\tfor (id in this.locals) {\n\t\tcount = this.locals[id];\n\t\tif (count > 0) {\n\t\t\tif (assigns[id]) {\n\t\t\t\tusage.assigns[id] = count;\n\t\t\t}\n\t\t\telse {\n\t\t\t\tusage.captures[id] = count;\n\t\t\t\toldLocals[id] += count;\n\t\t\t}\n\t\t}\n\t}\n\tthis.locals = oldLocals;\n\treturn usage;\n};\n\nvar initialize = function() {\n\tformulaFunctions = {};\n\tvar operators = {};\n\t$tw.modules.applyMethods(\"formula-function\", formulaFunctions);\n\t$tw.modules.applyMethods(\"formula-operator\", operators);\n\n\toperatorsUnaryPre = {};\n\toperatorsUnaryPost = {};\n\toperatorsBinary = {}; //{}; //{plus: {arity: 2, precedence: 10,   operator: \"+\", function: \"add\"}};\n\toperatorsTernary = {};\n\tfor (var opName in operators)\n\t{\n\t\tvar op = operators[opName];\n\n\t\t// Bind the associated function.  \n\t\tvar func = formulaFunctions[op.function];\n\t\tif (!func) continue;\n\t\top.func_bind = func;\n\n\t\t// Sort the op by arity and position.\n\t\tswitch (op.arity)\n\t\t{\n\t\tcase 2:           operatorsBinary  [opName] = op; break;\n\t\tcase 3:           operatorsTernary [opName] = op; break;\n\t\tcase 1:\n\t\t\tswitch (op.position)\n\t\t\t{\n\t\t\t\tcase \"pre\":  operatorsUnaryPre [opName] = op; break;\n\t\t\t\tcase \"post\": operatorsUnaryPost[opName] = op; break;\n\t\t\t}\n\t\t\tbreak;\n\t\t}\n\t}\n};\n\n\nexports.compileExpression = function(expression) {\n\n\t// Create a parser and process the formula as an expression.\n\tvar parser = new Parser(expression);\n\n\tvar operand = buildExpression(parser);\n\n\treturn operand;\n};\n\nexports.compileDatum = function(datum) {\n\t\n\tvar parser, term;\n\n\t// Short-hand formula\n\tif (datum.charAt(0) == \"=\") {\n\t\tparser = new Parser(datum);\n\t\tparser.pos = 1;\n\t\treturn buildExpression(parser);\n\t}\n\n\t// Could be a TiddlyWiki date?\n\tif (rxDatumIsTwDate.test(datum)) {\n\t\treturn new Nodes.Date($tw.utils.parseDate(datum));\n\t}\n\n\t// Could be a number?\n\tif (rxDatumIsDecimal.test(datum)) {\n\t\t// Treat as a number constant\n\t\treturn new Nodes.Number(Number(datum));\n\t}\n\n\t// Could be a formula?\n\tif (rxDatumIsFormula.test(datum)) {\n\t\t// Parse contents as a formula\n\t\tparser = new Parser(datum);\n\t\tparser.pos = datum.indexOf(\"=\")+1;\n\t\tparser.end = datum.lastIndexOf(\"=\");\n\t\treturn buildExpression(parser);\n\t}\n\n\t// Could be a transclusion or variable?\n\tif (rxDatumIsTransclusion.test(datum) ||\n\t\t\trxDatumIsVariable.test(datum)) {\n\t\t// Defer to the operand parser...\n\t\tparser = new Parser(datum);\n\t\treturn buildOperand(parser);\n\t}\n\n\t// Booleans?\n\tif (rxDatumIsFalse.test(datum)) return new Nodes.Bool(false);\n\tif (rxDatumIsTrue .test(datum)) return new Nodes.Bool(true);\n\n\t// Date?\n\tif (rxDatumIsDate.test(datum))\n\t{\n\t\trxDateFragment.lastIndex = 0;\n\t\tvar parts = [];\n\t\twhile (true)\n\t\t{\n\t\t\tvar res = rxDateFragment.exec(datum);\n\t\t\tif (!res) break;\n\t\t\tparts.push(parseInt(res[0]));\n\t\t}\n\t\tif (parts.length)\n\t\t{\n\t\t\treturn new Nodes.Date(new Date(\n\t\t\t\tparts[0], (parts[1] || 1)-1, parts[2] || 1,\n\t\t\t\tparts[3] || 0, parts[4] || 0, parts[5] || 0, parts[6] || 0));\n\t\t}\n\t}\n\n\t// Regex?\n\tif ((term = rxDatumIsRegex.exec(datum))) {\n\t\treturn new Nodes.Regex(new RegExp(term[1].replace(\"\\\\/\", \"/\"), term[2]));\n\t}\n\n\t// Otherwise, treat as a string constant\n\treturn new Nodes.Text(datum);\n};\n\nexports.compileFormula = function(formulaString)\n{\n\t// Process the formula string into a root operand\n\ttry {\n\t\treturn exports.compileExpression(formulaString);\n\t}\n\tcatch (err) {\n\t\tthrow \"CompileError: \" + err;\n\t}\n};\n\n\n// Compile an operator\nfunction parseOperator(parser, operatorGroup) {\n\n\t// Skip more whitespace\n\tparser.skipInert();\n\n\tvar result = null;\n\n\t// Find the longest operator matching the current text.\n\tfor (var opName in operatorGroup)\n\t{\n\t\tvar op = operatorGroup[opName];\n\t\tif (parser.src.substr(parser.pos, op.operator.length) == op.operator\n\t\t\t&& parser.pos+op.operator.length <= parser.end)\n\t\t{\n\t\t\tif (!result || result.operator.length < op.operator.length) result = op;\n\t\t}\n\t}\n\n\tif (result) parser.pos += result.operator.length;\n\n\treturn result;\n}\n\n// Parse a text reference.  This function is pased on $tw.utils.getTextReference.\nfunction buildTextReference(textReference) {\n\tvar tr = $tw.utils.parseTextReference(textReference);\n\tvar title;\n\tif (tr.title) title = new Nodes.Text(tr.title);\n\telse          title = new Nodes.Variable(new Nodes.Text(\"currentTiddler\"));\n\tif (tr.field) {\n\t\tif (tr.field == \"title\") {\n\t\t\treturn title;\n\t\t}\n\t\telse {\n\t\t\treturn new Nodes.TranscludeField(title, new Nodes.Text(tr.field));\n\t\t}\n\t}\n\telse if (tr.index) {\n\t\treturn new Nodes.TranscludeIndex(title, new Nodes.Text(tr.index));\n\t}\n\telse {\n\t\treturn new Nodes.TranscludeText(title);\n\t}\n}\n\n// Parse a formula.\nfunction buildExpression(parser, nested) {\n\t\n\t// Make sure math functions are initialized\n\tif (!formulaFunctions) initialize();\n\n\tparser.skipInert();\n\n\t// Expression compiler state\n\tvar operands = [];\n\tvar operators = [];\n\tvar precedences = [];\n\tvar operand = null, callArgs;\n\t\n\t// Unary stacking function\n\tvar applyUnary = function(unary) {\n\t\toperand = new Nodes.CallJS(unary.func_bind, [operand]);\n\t};\n\n\twhile (true)\n\t{\n\t\tvar unaries = [];\n\n\t\t// Prefix operators\n\t\twhile (true)\n\t\t{\n\t\t\tvar prefix = parseOperator(parser, operatorsUnaryPre);\n\t\t\tif (prefix) unaries.unshift(prefix);\n\t\t\telse break;\n\t\t}\n\n\t\t// Grab the operand\n\t\toperand = buildOperand(parser);\n\n\t\t// Missing operand is an error\n\t\tif (operand === null)\n\t\t{\n\t\t\tvar token = parser.nextToken();\n\t\t\tif (token && token[0] != \")\" && token[0] != \",\")\n\t\t\t\tthrow \"invalid operand \\\"\" + token + \"\\\"\";\n\t\t\telse if (operators.length)\n\t\t\t\tthrow \"missing operand after \\\"\" + operators[operators.length-1].operator + \"\\\"\";\n\t\t\telse throw \"empty expression\";\n\t\t}\n\n\t\t// Check for a function call (precedes all operators).\n\t\tcallArgs = buildArguments(parser);\n\t\tif (callArgs) operand = new Nodes.CallFunc(operand, callArgs);\n\n\t\t// Postfix operators\n\t\twhile (true)\n\t\t{\n\t\t\tvar postfix = parseOperator(parser, operatorsUnaryPost);\n\t\t\tif (postfix) unaries.push(postfix);\n\t\t\telse break;\n\t\t}\n\n\t\tunaries.forEach(applyUnary);\n\n\t\t// Operand is complete.\n\t\toperands.push(operand);\n\n\t\t// Infix operators\n\t\tvar operator = parseOperator(parser, operatorsBinary);\n\n\t\t// Missing operator ends the expression\n\t\tif (operator === null) break;\n\n\t\t// Add the operator and its precedence level.\n\t\toperators.push(operator);\n\t\tvar precedence = operator.precedence;\n\t\tif (precedences.indexOf(precedence || 0) == -1) precedences.push(precedence);\n\t}\n\n\t// Sanity check\n\tif (operands.length != operators.length+1)\n\t\tthrow \"internal error: operator/operand parsing inconsistency\";\n\n\t// Resolve operators by precedence\n\tprecedences.sort(function(a,b) {return (a>b)?-1:1;});\n\n\tfor (var j = 0; j < precedences.length; ++j)\n\t{\n\t\tvar prec = precedences[j];\n\t\tfor (var i = 0; i < operators.length; )\n\t\t{\n\t\t\t// Process only operators at the current precedence level.\n\t\t\tvar op = operators[i];\n\t\t\tif (op.precedence != prec) {++i; continue;}\n\n\t\t\t// Collapse the previous and next operands with this operator.\n\t\t\toperands[i] = new Nodes.CallJS(op.func_bind, [operands[i], operands[i+1]]);\n\t\t\toperators.splice(i, 1);\n\t\t\toperands.splice(i+1, 1);\n\t\t}\n\t}\n\n\t// Sanity check\n\tif (operators.length !== 0 || operands.length != 1)\n\t\tthrow \"internal error: resoving failed; \" + operands.length + \" operands and \" + operators.length + \" operators remain\";\n\n\t// For non-nested expressions, throw if any tokens remain.\n\tif (!nested)\n\t{\n\t\tparser.skipInert();\n\n\t\tif (parser.pos < parser.end)\n\t\t{\n\t\t\tthrow \"expected operator, got \\\"\" + parser.nextToken() + \"\\\"\";\n\t\t}\n\t}\n\t\n\t// Otherwise return the operand directly\n\treturn operands[0];\n}\n\n// Compile a list expression, which could be function arguments or an array...\nfunction buildCommaList(parser, braces, afterHint) {\n\n\t// Is an open-brace present?\n\tparser.skipInert();\n\tif (parser.getChar() !== braces[0]) return null;\n\t++parser.pos;\n\n\t// Zero arguments?\n\tparser.skipInert();\n\tif (parser.getChar() === braces[1]) {++parser.pos; return [];}\n\t\n\tvar nodeList = [];\n\n\twhile (true)\n\t{\n\t\t// Compile an expression.\n\t\tnodeList.push(buildExpression(parser, true));\n\n\t\t// Expect close-brace or , after argument.\n\t\tvar char = parser.nextGlyph();\n\t\tif (char === braces[1]) break;\n\t\tif (char !== \",\") throw \"Expect ',' or '\" + braces[1] + \"' after \" + afterHint;\n\t}\n\n\treturn nodeList;\n}\n\n// Build an argument list.\nfunction buildArguments(parser) {\n\treturn buildCommaList(parser, \"()\", \"function argument.\");\n}\n\n// Build an array literal.\nfunction buildArrayLiteral(parser) {\n\tvar array = buildCommaList(parser, \"{}\", \"array element (use {{double braces}} for transclusions).\");\n\tif (!array) throw \"Expect '{' to begin array literal.\";\n\treturn array;\n}\n\n// Build a let or foreach expression (parser starts after the keyword)\nfunction buildLetExpression(parser) {\n\n\tif (parser.nextGlyph() !== \"(\") throw \"Expect '(' after LET.\";\n\n\t// Gradually push locals.\n\tvar assigns = {}, id, c;\n\tparser.pushLocals(assigns);\n\twhile (true) {\n\t\t// Look for a name (identifier)\n\t\tparser.skipInert();\n\t\tid = parser.match_here(rxIdentifier);\n\t\tif (!id) throw \"Expected name in LET assignment, got '\" + parser.nextToken() + \"'.\";\n\t\tid = id[0];\n\t\tif (rxKeyword.test(id)) throw \"Illegal name for LET: \" + id;\n\t\t\n\t\t// Look for an equals, then an expression.\n\t\tif (parser.nextGlyph() !== '=') throw \"Expect '=' after LET value.\";\n\n\t\t// Build the expression...  Each let can use the ones before it.\n\t\ttry {\n\t\t\tassigns[id] = buildExpression(parser, true);\n\t\t}\n\t\tcatch (err) {\n\t\t\tthrow \"compiling LET '\" + id + \"': \" + err;\n\t\t}\n\t\tparser.locals[id] = 0;\n\n\t\t// Expect ) or , after argument.\n\t\tvar char = parser.nextGlyph();\n\t\tif (char == \")\") break;\n\t\tif (char != \",\") throw \"Expect ',' or ')' after LET assignment.\";\n\t}\n\n\tif (parser.nextGlyph() !== \":\") throw \"Expect ':' after LET assignment list.\";\n\tif (parser.nextGlyph() !== \"(\") throw \"Expect LET expression in parentheses after ':'.\";\n\n\t// Compile the body expression, with additional locals.\n\tvar body = buildExpression(parser, true);\n\tvar usage = parser.popLocals();\n\n\t// TODO could examine usage.assigns and letLocals to see if any values were unused.\n\n\tif (parser.nextGlyph() !== \")\") throw \"Expect ')' after LET expression.\";\n\n\treturn new Nodes.LetVars(assigns,body);\n}\n\n// Build a function (parser starts after the keyword \"function\")\nfunction buildFunction(parser) {\n\t\n\tvar srcBegin = parser.pos;\n\n\tif (parser.nextGlyph() !== \"(\") throw \"Expect '(' after 'function'.\";\n\n\tparser.skipInert();\n\n\t// Build the parameter list, if any.\n\tvar params = [], assigns = {};\n\tif (parser.getChar() === \")\") {++parser.pos;}\n\telse while (true)\n\t{\n\t\t// Get a parameter name (identifier).\n\t\tvar param = parser.match_here(rxIdentifier);\n\t\tif (!param) throw \"Expect list of parameter names after 'function'.\";\n\t\tparam = param[0];\n\t\tif (rxKeyword.test(param)) throw \"Illegal parameter name: \" + param;\n\t\tparams.push(param);\n\t\tif (assigns[param]) throw \"Parameter name used twice: \" + param;\n\t\tassigns[param] = true;\n\n\t\t// Expect ) or , after argument.\n\t\tvar char = parser.nextGlyph();\n\t\tif (char == \")\") break;\n\t\tif (char != \",\") throw \"Expect ',' or ')' after function parameter name.\";\n\n\t\t// Skip inert stuff\n\t\tparser.skipInert();\n\t}\n\n\tif (parser.nextGlyph() !== \":\") throw \"Expect ':' after function parameter list.\";\n\tif (parser.nextGlyph() !== \"(\") throw \"Expect function body beginning with '(' after ':'.\";\n\n\t// Compile the body expression, with parameters as locals.  Closures are NOT currently supported.\n\tparser.pushLocals(assigns);\n\tvar body = buildExpression(parser, true);\n\tvar usage = parser.popLocals();\n\tvar captures = usage.captures;\n\n\tif (parser.nextGlyph() !== \")\") throw \"Expect ')' after function body.\";\n\n\t// Create the function object (must be called with this = context)\n\tvar func = function() {\n\t\tvar locals = Object.assign({}, func.captured || {});\n\t\tfor (var i = 0; i < arguments.length; ++i) locals[params[i]] = arguments[i];\n\t\treturn body.compute(this.let(locals));\n\t};\n\t//func.params = params;\n\tfunc.min_args = params.length;\n\tfunc.max_args = params.length;\n\tfunc.formulaSrc = parser.src.substring(srcBegin, parser.pos);\n\treturn new Nodes.Function(func, captures);\n}\n\n// Compile an operand into a function returning the operand value.\nfunction buildOperand(parser) {\n\n\tvar term;\n\t\n\t// Skip whitespace & comments\n\tparser.skipInert();\n\n\tif (parser.pos == parser.end) return null;\n\n\tvar char = parser.getChar();\n\n\tif (char.match(/[0-9\\.+]/i))\n\t{\n\t\t// Number constant\n\t\tterm = parser.match_here(rxDecimal);\n\t\tif (term) return new Nodes.Number(Number(term[0]));\n\t\tthrow \"Invalid number: \" + parser.nextToken();\n\t}\n\telse if (char.match(/[$a-z_]/i))\n\t{\n\t\t// Cell range?\n\t\tterm = parser.match_here(rxCellRange);\n\t\tif (term) throw \"Cell ranges are currently unsupported!\";\n\n\t\t// Cell name?\n\t\tterm = parser.match_here(rxCellName);\n\t\tif (term) return new Nodes.Datum(\n\t\t\tnew Nodes.TranscludeIndex(\n\t\t\t\tnew Nodes.Variable(new Nodes.Text(\"currentTiddler\")),\n\t\t\t\tnew Nodes.Text(term[1]+term[2])));\n\n\t\t// Identifier?\n\t\tterm = parser.match_here(rxIdentifier);\n\t\tif (!term) return null;\n\n\t\tif (parser.locals[term] != undefined)\n\t\t{\n\t\t\t// Scoped variable.  We count up references to each.\n\t\t\t++parser.locals[term];\n\t\t\treturn new Nodes.ScopeVar(term[0]);\n\t\t}\n\n\t\tvar termLower = term[0].toLowerCase();\n\t\tswitch (termLower)\n\t\t{\n\t\tcase \"let\":\n\t\t\t// LET expression.\n\t\t\treturn buildLetExpression(parser);\n\n\t\tcase \"function\":\n\t\t\t// Function declaration.\n\t\t\treturn buildFunction(parser);\n\n\t\tdefault:\n\t\t\t// Function call.\n\t\t\tvar func = formulaFunctions[termLower];\n\n\t\t\tif (!func) throw \"unknown function: \" + term[0];\n\n\t\t\tvar args = buildArguments(parser);\n\n\t\t\t// Omitting arguments is only OK for constant functions\n\t\t\tif (args === null)\n\t\t\t{\n\t\t\t\tif (!func.isConstant) throw \"Expected '(' after \" + term[0];\n\t\t\t\targs = [];\n\t\t\t}\n\n\t\t\tif (func instanceof Function) {\n\t\t\t\t// Check parameter count\n\t\t\t\tif (args.length > func.length && !func.variadic)\n\t\t\t\t\tthrow \"too many arguments for \" + term[0] + \" (requires \" + func.length + \")\";\n\t\t\t\tif (args.length < func.length)\n\t\t\t\t\tthrow \"too few arguments for \" + term[0] + (func.variadic?\" (min \":\" (requires \") + func.length + \")\";\n\t\t\t}\n\t\t\telse if (func.select || func.construct) {\n\t\t\t\t// Check argument range\n\t\t\t\tif (func.max_args && args.length > func.max_args)\n\t\t\t\t\tthrow \"too many arguments for \" + term[0] + \" (max \" + func.max_args + \")\";\n\t\t\t\tif (func.min_args && args.length < func.min_args)\n\t\t\t\t\tthrow \"too few arguments for \" + term[0] + \" (min \" + func.min_args + \")\";\n\t\t\t\t\n\t\t\t\t// If a construct function is present, use it to generate an operand.\n\t\t\t\tif (func.construct) return func.construct(args);\n\n\t\t\t\t// If a select function is present, prepare to bind it with a CallJS.\n\t\t\t\tfunc = func.select(args);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tthrow \"Function \" + term[0] + \" seems to be unusable.\";\n\t\t\t}\n\n\t\t\treturn new Nodes.CallJS(func, args);\n\t\t}\n\t}\n\telse switch (char)\n\t{\n\tcase \"(\": // Parenthesized expression\n\t\t++parser.pos;\n\t\tvar parentheses = buildExpression(parser, true);\n\t\tparser.skipInert();\n\t\tif (parser.getChar() !== \")\")\n\t\t{\n\t\t\tif (parser.pos == parser.end) throw \"missing ')' at end of formula\";\n\t\t\telse                          throw \"expected ')', got \\\"\" + parser.nextToken() + \"\\\"\";\n\t\t}\n\t\t++parser.pos;\n\t\treturn parentheses;\n\n\tcase \"'\":\n\tcase \"\\\"\": // String constant\n\t\tterm = parser.match_here(rxString);\n\t\tif (!term) throw \"Invalid string: \" + parser.nextToken();\n\t\tterm = term[0].substr(1, term[0].length-2);\n\t\tterm = term.replace(rxEscapeSequence, function(esc) {\n\t\t\tswitch (esc.charAt(1)) {\n\t\t\t\tcase '\"': return '\"';\n\t\t\t\tcase '\\'': return '\\'';\n\t\t\t\tcase '\\\\': return '\\\\';\n\t\t\t\tcase 'n': return '\\n';\n\t\t\t\tcase 'r': return '\\r';\n\t\t\t\tcase 'b': return '\\b';\n\t\t\t\tcase 'f': return '\\f';\n\t\t\t\tcase 't': return '\\t';\n\t\t\t\tcase 'v': return '\\v';\n\t\t\t\tcase '0': return '\\0';\n\t\t\t\tcase 'u':\n\t\t\t\t\tif (esc.length < 6) throw \"Invalid escape sequence: \" + esc;\n\t\t\t\t\treturn String.fromCharCode(parseInt(esc.substr(2), 16));\n\t\t\t\tdefault: throw \"Invalid escape sequence: \" + esc;\n\t\t\t}\n\t\t});\n\t\treturn new Nodes.Text(term);\n\n\tcase \"[\": // Filter operand\n\t\tterm = parser.match_here(rxOperandFilter);\n\t\tif (term) return new Nodes.Filter(term[0]);\n\t\tbreak;\n\n\tcase \"{\": // Transclusion or array\n\t\t++parser.pos;\n\t\tchar = parser.getChar();\n\t\t--parser.pos;\n\t\tif (char == '{') {\n\t\t\t// Possible transclusion operand\n\t\t\tterm = parser.match_here(rxOperandTransclusion);\n\t\t\tif (term) return new Nodes.Datum(buildTextReference(term[1]));\n\t\t}\n\t\t// Array operand\n\t\treturn new Nodes.ArrayDef(buildArrayLiteral(parser));\n\n\tcase \"<\": // Variable operand\n\t\tterm = parser.match_here(rxOperandVariable);\n\t\tif (term) return new Nodes.Datum(\n\t\t\tnew Nodes.Variable(new Nodes.Text(term[1])));\n\t\tbreak;\n\n\tcase \"/\": // Regular expression?\n\t\tterm = parser.match_here(rxRegex);\n\t\tif (term) return new Nodes.Regex(new RegExp(term[1].replace(\"\\\\/\", \"/\"), term[2]));\n\t\t\tbreak;\n\t}\n\n\t// Didn't recognize the operand\n\treturn null;\n}\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/compile.js",
            "tags": "",
            "module-type": "library",
            "modified": "20171211181652443",
            "description": "",
            "created": "20171210195223539"
        },
        "$:/plugins/ebalster/formula/compute.js": {
            "text": "(function(){\n\n\"use strict\";\n\nvar Nodes    = require(\"$:/plugins/ebalster/formula/nodes.js\");\nvar Compiler = require(\"$:/plugins/ebalster/formula/compile.js\");\nvar Coerce   = require(\"$:/plugins/ebalster/formula/coerce.js\");\n\nvar Numeral  = require(\"$:/plugins/ebalster/formula/lib/numeral.js\");\n\n// TiddlyWiki array format\nfunction arrayFormatTW(arr,ctx) {\n\tvar result = \"\";\n\tfor (var i = 0; i < arr.length; ++i) {\n\t\tvar part = Coerce.ToText(arr[i],ctx);\n\t\tif (i && part.length) result += \" \";\n\t\tif (part.indexOf(/\\s/g) >= 0) result += \"[[\" + part + \"]]\";\n\t\telse result += part;\n\t}\n\treturn result;\n}\n\n// Number format functions...\n\n// SANE number formatting: if we find five consecutive 9s or 0s after the decimal point, round them off.\nfunction NumberStringSane(n) {\n\tvar s = String(n);\n\tvar parse = /^(0\\.0*[1-9]\\d*?|\\d*\\.\\d*?)(0{5}\\d*|9{5}\\d*)(|e[+-]\\d*)$/.exec(s);\n\tif (!parse) return s;\n\tvar kept = parse[1], exp = parse[3];\n\tvar end = kept.slice(-1);\n\tif (parse[2][0] === '0') return ((end === '.') ? kept.substr(0,kept.length-1) : kept) + exp;\n\tif (end === '.') return (Number(kept.substr(0,kept.length-1))+1) + exp;\n\treturn kept.substr(0,kept.length-1) + (Number(end)+1) + exp;\n}\nvar numeralFormat      = function(fmt)      {return function(num) {return Numeral(num).format(fmt);};};\nvar numeralFormatPrec  = function(fmt,digs) {return function(num) {return Numeral(num.toPrecision(digs)).format(fmt);};};\nvar numberFormatFixed  = function(prec)     {return function(num) {return num.toFixed    (prec);};};\nvar numberFormatPrec   = function(digs)     {return function(num) {return num.toPrecision(digs);};};\nvar numberFormatSelect = function(settings)\n{\n\tif (settings.precision == \"true\" || settings.precision > 100) return String;\n\tif (typeof settings.numberFormat == \"string\") {\n\t\t// Use numeral\n\t\treturn isNaN(settings.precision) ?\n\t\t\tnumeralFormat    (settings.numberFormat) :\n\t\t\tnumeralFormatPrec(settings.numberFormat, settings.precision);\n\t}\n\tif (!isNaN(settings.fixed))     return numberFormatFixed(settings.fixed);\n\tif (!isNaN(settings.precision)) return numberFormatPrec (settings.precision);\n\treturn NumberStringSane;\n\t// return String;\n};\n\nexports.computeFormula = function(compiledFormula, widget, formatOptions, debug) {\n\t\n\tvar value, context;\n\t\n\tformatOptions = formatOptions || {};\n\n\tvar dateFormat = formatOptions.dateFormat || \"0hh:0mm, DDth MMM YYYY\";\n\n\t// Specify format.  These are all required!\n\tvar formats = {\n\t\tnumber: numberFormatSelect(formatOptions),\n\t\tdate:   function(date) {return $tw.utils.formatDateString(date, dateFormat);},\n\t\tarray:  arrayFormatTW,\n\t};\n\n\tcontext = new Nodes.Context(widget, formats);\n\n\t// Compute a value from the root node of the compiled formula.\n\ttry {\n\t\tvalue = compiledFormula.computeText(context);\n\t}\n\tcatch (err) {\n\t\tthrow \"ComputeError: \" + String(err) + (err.fileName || \"\") + (err.lineNumber || \"\")\n\t\t\t+ (debug ? \"\\nNodes: \" + JSON.stringify(compiledFormula) : \"\");\n\t}\n\n\t// Format the root node as a string.\n\tif (debug) return value + \"\\n - Val:\" + String(value) + \", Op:\" + compiledFormula.name;\n\telse       return value;\n};\n\nexports.evalFormula = function(formulaString, widget, formatOptions, debug) {\n\t\n\tvar compiledFormula;\n\n\t// Compile the formula\n\ttry {\n\t\tcompiledFormula = Compiler.compileExpression(formulaString);\n\t}\n\tcatch (err) {\n\t\tthrow \"CompileError: \" + String(err);\n\t}\n\n\t// Compute the formula\n\treturn exports.computeFormula(compiledFormula, widget, formatOptions, debug);\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/compute.js",
            "tags": "",
            "module-type": "library",
            "modified": "20180114170348576",
            "description": "",
            "created": "20180114170308058"
        },
        "$:/plugins/ebalster/formula/filters/range.js": {
            "text": "/*\\\ntitle: $:/plugins/ebalster/formula/filters/range.js\ntype: application/javascript\nmodule-type: filteroperator\n\nFilter operator for generating a numeric range.\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nExport our filter function\n*/\nexports.range = function(source,operator,options) {\n\tvar results = [];\n\n\t// Split the operand into numbers delimited by these symbols\n\tvar parts = operator.operand.split(/[,:;]/g), beg, end, inc, i, fixed = 0;\n\n\tfor (i = 0; i < parts.length; ++i) {\n\t\t// Validate real number\n\t\tif (!/^\\s*[+-]?((\\d+(\\.\\d*)?)|(\\.\\d+))\\s*$/.test(parts[i]))\n\t\t\treturn [\"range: bad number \\\"\"+parts[i]+\"\\\"\"];\n\n\t\t// Count digits; the most precise number determines decimal places in output.\n\t\tvar frac = /\\.\\d+/.exec(parts[i]);\n\t\tif (frac) fixed = Math.max(fixed, frac[0].length-1);\n\t\t\n\t\tparts[i] = parseFloat(parts[i]);\n\t}\n\n\tswitch (parts.length) {\n\t\tcase 1:\n\t\t\tbeg = 0;\n\t\t\tend = parts[0];\n\t\t\tinc = 1;\n\t\t\tbreak;\n\t\tcase 2:\n\t\t\tbeg = parts[0];\n\t\t\tend = parts[1];\n\t\t\tinc = 1;\n\t\t\tbreak;\n\t\tcase 3:\n\t\t\tbeg = parts[0];\n\t\t\tend = parts[1];\n\t\t\tinc = Math.abs(parts[2]);\n\t\t\tbreak;\n\t}\n\n\tif (inc === 0) return [\"range: increment 0 causes infinite loop\"];\n\n\t// May need to count backwards\n\tvar direction = ((end<beg) ? -1 : 1);\n\tinc *= direction;\n\n\t// Estimate number of resulting elements\n\tif ((end-beg)/inc > 10000) return [\"range: too many steps (over 10K)\"];\n\n\t// Avoid rounding error on last step\n\tend += direction * 0.5 * Math.pow(0.1, fixed);\n\n\tvar safety = 10010;\n\n\t// Enumerate the range\n\tif (end<beg) {for (i = beg; i > end; i += inc) {results.push(i.toFixed(fixed)); if (--safety<0) break;}}\n\telse         {for (i = beg; i < end; i += inc) {results.push(i.toFixed(fixed)); if (--safety<0) break;}}\n\n\tif (safety<0) return [\"range: unexpectedly large output\"];\n\n\t// Reverse?\n\tif (operator.prefix === \"!\") results.reverse();\n\n\treturn results;\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/filters/range.js",
            "tags": "",
            "module-type": "filteroperator",
            "modified": "20171221181907646",
            "created": "20171221181646560"
        },
        "$:/plugins/ebalster/formula/functions/arithmetic.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\n// Unary sign operators\nexports.uplus  = function(a)    {return a;};\nexports.uminus = function(a)    {return -a;};\nexports.uminus.inCast = 'N';\n\n// Add\nexports.add = function(a, b)    {return a + b;};\nexports.add.inCast = 'NN';\nexports.sub = function(a, b)    {return a - b;};\nexports.sub.inCast = 'NN';\n\n// Multiply\nexports.mul = function(a, b)    {return a * b;};\nexports.mul.inCast = 'NN';\nexports.div = function(a, b)    {return a / b;};\nexports.div.inCast = 'NN';\n\n// Percent -- TODO make this a different value-type\nexports.percent = function(a)    {return a / 100;};\nexports.percent.inCast = 'N';\n\n\n// Aliases\nexports.subtract = exports.sub;\nexports.minus    = exports.sub;\nexports.multiply = exports.mul;\nexports.divide   = exports.div;\nexports.quotient = exports.div;\nexports.power    = exports.pow;\n\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/functions/arithmetic.js",
            "tags": "",
            "module-type": "formula-function",
            "modified": "20171212223526867",
            "created": "20171211192843088"
        },
        "$:/plugins/ebalster/formula/functions/arrays.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\n// Array constructor function\nexports.array = function() {\n\treturn Array.prototype.slice.call(arguments);\n};\nexports.array.variadic = true;\n\n\nexports.nth = function(a, i) {\n\ti = Math.floor(i);\n\tif (i < 1 || i > a.length) return undefined;\n\treturn a[i-1];\n};\nexports.nth.inCast = 'AN';\n\nexports.first = function(a) {\n\tif (a.length) return a[0];\n\treturn undefined;\n};\nexports.first.inCast = 'A';\n\nexports.last = function(a) {\n\tif (a.length) return a[a.length-1];\n\treturn undefined;\n};\nexports.last.inCast = 'A';\n\n// MAP function\nexports.map = function(f, a) {\n\tif (f.min_args > 1 || f.max_args < 1) throw \"MAP requires single-argument function.\";\n\tvar result = [];\n\tvar func = f.bind(this);\n\tfor (var i = 0; i < a.length; ++i) result.push(func(a[i]));\n\treturn result;\n};\nexports.map.inCast = 'FA';\n\n\n/*\n\tCounting subroutines...\n\t\tcountA counts every non-array value\n\t\tcountS counts every non-array value but null, undefined and empty strings.\n*/\nfunction countS(a) {\n\tif (!(a instanceof Array)) return (a == null || a.length === 0) ? 0 : 1;\n\tvar n = 0;\n\tfor (var i = 0; i < a.length; ++i) n += countS(a[i]);\n\treturn n;\n}\nfunction countA(a) {\n\tif (!(a instanceof Array)) return 1;\n\tvar n = 0;\n\tfor (var i = 0; i < a.length; ++i) n += countA(a[i]);\n\treturn n;\n}\nfunction countS_multi() {\n\tvar n = 0;\n\tfor (var i = 0; i < arguments.length; ++i) n += countS(arguments[i]);\n\treturn n;\n}\nfunction countA_multi() {\n\tvar n = 0;\n\tfor (var i = 0; i < arguments.length; ++i) n += countA(arguments[i]);\n\treturn n;\n}\nexports.count =\n{\n\tmin_args : 1,\n\tselect : function(operands)\n\t{\n\t\tswitch (operands)\n\t\t{\n\t\tcase 1: return countS;\n\t\tdefault: return countS_multi;\n\t\t}\n\t}\n};\nexports.counta =\n{\n\tmin_args : 1,\n\tselect : function(operands)\n\t{\n\t\tswitch (operands)\n\t\t{\n\t\tcase 1: return countA;\n\t\tdefault: return countA_multi;\n\t\t}\n\t}\n};\n\n// COUNTA function, currently counts everything\nexports.counta = exports.count;\n\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/functions/arrays.js",
            "tags": "",
            "module-type": "formula-function",
            "modified": "20171219014910148",
            "created": "20171219014903147"
        },
        "$:/plugins/ebalster/formula/functions/compare.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\n// Equality\nexports.eq  = function(a, b)    {return a == b;};\nexports.ne  = function(a, b)    {return a != b;};\n\n// Inequality\nexports.gt  = function(a, b)    {return a >  b;};\nexports.gte = function(a, b)    {return a >= b;};\nexports.lt  = function(a, b)    {return a <  b;};\nexports.lte = function(a, b)    {return a <= b;};\n\n\n// Aliases\nexports.equal            = exports.eq;\nexports.not_equal        = exports.ne;\nexports.greater          = exports.gt;\nexports.greater_or_equal = exports.gte;\nexports.less             = exports.lt;\nexports.less_or_equal    = exports.lte;\n\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/functions/compare.js",
            "tags": "",
            "module-type": "formula-function",
            "modified": "20171214050803365",
            "created": "20171214050022626"
        },
        "$:/plugins/ebalster/formula/functions/datetime.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\nvar MS_PER_DAY = 86400000;\nvar MS_PER_HOUR = 3600000;\nvar MS_PER_MINUTE = 60000;\nvar MS_PER_SECOND =  1000;\n\nvar UNIX_EPOCH_JULIAN_DAY = 2440587;\n\n\n/*!\n * isoWeekNum from pikaday <https://github.com/actano/Pikaday>\n */\nfunction isoWeekOfYear(date, dayInFirstWeek) {\n\tdayInFirstWeek = dayInFirstWeek || 4;\n\tdate = date instanceof Date ? date : new Date();\n\tdate.setHours(0, 0, 0, 0);\n\tvar yearDay        = date.getDate(),\n\t\tweekDay        = date.getDay(),\n\t\tdayShift       = dayInFirstWeek - 1, // counting starts at 0\n\t\tprevWeekDay    = function(day) { return (day + 7 - 1) % 7; };\n\tdate.setDate(yearDay + dayShift - prevWeekDay(weekDay));\n\tvar jan4th      = new Date(date.getFullYear(), 0, dayInFirstWeek),\n\t\tdaysBetween = (date.getTime() - jan4th.getTime()) / MS_PER_DAY,\n\t\tweekNum     = 1 + Math.round((daysBetween - dayShift + prevWeekDay(jan4th.getDay())) / 7);\n\treturn weekNum;\n}\nfunction isLeapYear(year) {\n\treturn year % 400 === 0 || (year % 100 !== 0 && year % 4 === 0);\n}\nfunction daysInYear(year) {\n\treturn isLeapYear(year) ? 366 : 365;\n}\nfunction daysInMonth(year, monthIndex) {\n\tswitch (monthIndex) {\n\tcase  0: case  2: case  4: case  6: case  7: case  9: case 11:return 31;\n\tcase  3: case  5: case  8: case 10: return 30;\n\tcase  1: return (isLeapYear(year) ? 29 : 28);\n\tdefault: throw \"days_in_month: invalid monthIndex: \" + monthIndex;\n\t}\n}\n\n// Utility: Add some months or years to a date\nfunction dateAddMonths(date, monthDiff, yearDiff) {\n\tyearDiff = yearDiff || 0;\n\tvar newMonth = date.getMonth() + Math.round(monthDiff);\n\tvar newYear = date.getFullYear() + Math.round(yearDiff);\n\n\tvar yearShift = ((newMonth < 0) ? -Math.floor(-(newMonth-11)/12) : Math.floor(newMonth/12));\n\tnewYear  += yearShift;\n\tnewMonth -= 12*yearShift;\n\n\treturn new Date(newYear, newMonth,\n\t\tMath.min(date.getDate(), daysInMonth(newYear, newMonth)),\n\t\tdate.getHours(), date.getMinutes(), date.getSeconds(), date.getMilliseconds());\n}\n\n// Utility: Get date difference in whole years and months\nfunction dateDelta(date1, date2) {\n\tif (date2.getTime() < date1.getTime())\n\t{\n\t\tvar d = dateDelta(date2, date1);\n\t\treturn {years: -d.years, months: -d.months};\n\t}\n\tvar dMonths = 12*(date2.getYear()-date1.getYear()) + (date2.getMonth()-date1.getMonth());\n\tif (date2.getDate() < date1.getDate()) dMonths -= 1;\n\tvar dYears = Math.floor(dMonths/12);\n\t//dMonths -= dYears*12;\n\t/*var dDays = (new Date(\n\t\tdate1.getFullYear()+dYears, date1.getMonth()+dMonths, date2.getDate(),\n\t\tdate2.getHours(), date2.getMinutes(), date2.getSeconds(), date2.getMilliseconds()\n\t\t).getTime() - date1.getTime()) / MS_PER_DAY;*/\n\treturn {years: dYears, months: dMonths};\n}\n\n\n// Get the current time\nexports.now         = function()     {return new Date(Date.now());};\n\n// Decompose dates\nexports.year        = function(d)    {return (d.getFullYear());};\nexports.year.inCast = 'D';\nexports.month       = function(d)    {return (d.getMonth()+1);};\nexports.month.inCast = 'D';\nexports.day         = function(d)    {return (d.getDate());};\nexports.day.inCast = 'D';\nexports.hour        = function(d)    {return (d.getHours());};\nexports.hour.inCast = 'D';\nexports.minute      = function(d)    {return (d.getMinutes());};\nexports.minute.inCast = 'D';\nexports.second      = function(d)    {return (d.getSeconds());};\nexports.second.inCast = 'D';\nexports.millisecond = function(d)    {return (d.getMilliseconds());};\nexports.millisecond.inCast = 'D';\n\n// Week functions\nexports.weekday     = function(d)    {return (d.getDay()+1);};\nexports.weekday.inCast = 'D';\nexports.weeknum     = function(d)    {return (isoWeekOfYear(d, 1));};\nexports.weeknum.inCast = 'D';\nexports.isoweekday  = function(d)    {return ((d.getDay()+6) % 7 + 1);};\nexports.isoweekday.inCast = 'D';\nexports.isoweeknum  = function(d)    {return (isoWeekOfYear(d));};\nexports.isoweeknum.inCast = 'D';\n\n\n/*\n\tDate math\n*/\nfunction makeTimeDiffFunction(milliseconds) {\n\tvar f = function(a, b) {return (b.getTime() - a.getTime()) / milliseconds;};\n\tf.inCast = 'DD';\n\treturn f;\n}\nfunction makeTimeAddFunction(milliseconds) {\n\tvar f = function(a, b) {return new Date(a.getTime() + b * milliseconds);};\n\tf.inCast = 'DN';\n\treturn f;\n}\n\nexports.years  = function(a, b) {return dateDelta(a, b).years;};\nexports.years.inCast = 'DD';\nexports.months = function(a, b) {return dateDelta(a, b).months;};\nexports.months.inCast = 'DD';\nexports.days            = makeTimeDiffFunction(MS_PER_DAY);\nexports.hours           = makeTimeDiffFunction(MS_PER_HOUR);\nexports.minutes         = makeTimeDiffFunction(MS_PER_MINUTE);\nexports.seconds         = makeTimeDiffFunction(MS_PER_SECOND);\nexports.milliseconds    = makeTimeDiffFunction(1);\n\nexports.add_years  = function(a, b) {return dateAddMonths(a, 0, b);};\nexports.add_years.inCast = 'DN';\nexports.add_months = function(a, b) {return dateAddMonths(a, b);};\nexports.add_months.inCast = 'DN';\nexports.add_days         = makeTimeAddFunction(MS_PER_DAY);\nexports.add_hours        = makeTimeAddFunction(MS_PER_HOUR);\nexports.add_minutes      = makeTimeAddFunction(MS_PER_MINUTE);\nexports.add_seconds      = makeTimeAddFunction(MS_PER_SECOND);\nexports.add_milliseconds = makeTimeAddFunction(1);\n\nexports.is_leap_year  = function(year)       {return (isLeapYear(year));};\nexports.is_leap_year.inCast = 'N';\nexports.days_in_year  = function(year)       {return (daysInYear(year));};\nexports.days_in_year.inCast = 'N';\nexports.days_in_month = function(yr, mon)    {return (daysInMonth(yr, mon-1));};\nexports.days_in_month.inCast = 'NN';\n\n/*exports.datedif = function(a, b, c) {\n\tswitch (c.toUpperCase())\n\t{\n\tcase \"D\": return ((b.getTime() - a.getTime()) / MS_PER_DAY);\n\tcase \"M\": {var d=dateDelta(a, b); return d.months+12*d.years;}\n\tcase \"Y\": return dateDelta(a, b).years;\n\tcase \"YM\": return dateDelta(a, b).months;\n\tcase \"MD\": return dateDelta(a, b).days;\n\t}\n};\nexports.datedif.inCast = 'DDT';*/\n\n\n// Parse TiddlyWiki date\nexports.tw_date = function(timestamp) {\n\tvar date = $tw.utils.parseDate(timestamp);\n\tif (!date) throw \"Bad timestamp: \\\"\" + date + \"\\\"\";\n\treturn (date);\n};\nexports.tw_date.inCast = 'T';\n\n// Stringify as TiddlyWiki date\nexports.to_tw_date = function(date) {\n\treturn $tw.utils.stringifyDate(date);\n};\nexports.to_tw_date.inCast = 'D';\n\n// Create ISO date\nexports.make_date = function(year, month, day) {\n\treturn (new Date(year, month-1, day));\n};\nexports.make_date.inCast = 'NNN';\n\n// Create ISO time\nexports.make_time = function(hour, minute, second) {\n\treturn (new Date(0, 0, 0, hour, minute, second));\n};\nexports.make_time.inCast = 'NNN';\n\n// Create from julian\nexports.julian = function(julian) {\n\treturn (new Date((julian - UNIX_EPOCH_JULIAN_DAY) * MS_PER_DAY));\n};\nexports.julian.inCast = 'N';\n\n// Convert to julian\nexports.to_julian = function(date) {\n\treturn (UNIX_EPOCH_JULIAN_DAY + (date.getTime() / MS_PER_DAY));\n};\nexports.to_julian.inCast = 'D';\n\nexports.time = exports.make_time;\n\n\n// Cast the incoming value into a date.\nfunction interpret_date(a) {\n\tif (a instanceof Date) return a;\n\treturn exports.tw_date(a);\n}\ninterpret_date.inCast = 'D';\n\n\n// Consruct a date from a TiddlyWiki timestamp or a set of parts\nexports.date = {\n\tmin_args: 1, max_args: 3,\n\tselect: function(operands) {\n\t\tswitch (operands.length) {\n\t\tcase 1: return interpret_date;\n\t\tcase 3: return exports.make_date;\n\t\tdefault: throw \"Bad arguments to DATE. Should be (timestamp) or (year, month, day).\";\n\t\t}\n\t}\n};\n\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/functions/datetime.js",
            "tags": "",
            "module-type": "formula-function",
            "modified": "20171217192149101",
            "created": "20171217192129179"
        },
        "$:/plugins/ebalster/formula/functions/logic.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Node = require(\"$:/plugins/ebalster/formula/nodes.js\").Node;\n\n\n// Constants\nexports.true  = function()    {return true;};\nexports.false = function()    {return false;};\n\nexports.true.isConstant = true;\nexports.false.isConstant = true;\n\n// Logical operators\nexports.not = function(a)       {return !a;};\nexports.not.inCast = 'B';\nexports.and = function(a, b)    {return a && b;};\nexports.and.inCast = 'BB';\nexports.or  = function(a, b)    {return a || b;};\nexports.or .inCast = 'BB';\nexports.xor = function(a, b)    {return a ? !b : b;};\nexports.xor.inCast = 'BB';\n\n// Ternary\nfunction IfNode(pred, tval, fval) {\n\tthis.pred = pred;\n\tthis.tval = tval;\n\tthis.fval = fval;\n}\nIfNode.prototype = new Node();\nIfNode.prototype.name = \"if\";\nIfNode.prototype.compute = (function(ctx) {\n\treturn (this.pred.computeBool(ctx) ? this.tval.compute(ctx) : this.fval.compute(ctx));\n});\nexports.if = {\n\tmin_args: 3, max_args: 3,\n\tconstruct: function(operands) {\n\t\treturn new IfNode(operands[0], operands[1], operands[2]);\n\t}\n};\n\n\n// IFERROR\n/*exports.iferror = {\n\tmin_args = 2, max_args = 2,\n\tfunc = function(a, b) {\n\tselect: function(operands) {\n\t\ttry {return a.compute();}\n\t\tcatch (err) {return b.compute();}\n\t}\n\t};*/\n\n\n// SWITCH (variadic)\nexports.switch =\n{\n\tmin_args: 3,\n\tselect: function(operands)\n\t{\n\t\tswitch (operands.length % 2)\n\t\t{\n\t\tdefault:\n\t\tcase 0: return function(a) // Switch with default\n\t\t\t{\n\t\t\t\tvar value = a;\n\t\t\t\tfor (var i = 1; i+1 < arguments.length; i += 2)\n\t\t\t\t\t{if (arguments[i] == value) return arguments[i+1];}\n\t\t\t\treturn arguments[arguments.length-1];\n\t\t\t};\n\t\tcase 1: return function(a) // Switch, no default\n\t\t\t{\n\t\t\t\tvar value = a;\n\t\t\t\tfor (var i = 1; i+1 < arguments.length; i += 2)\n\t\t\t\t\t{if (arguments[i] == value) return arguments[i+1];}\n\t\t\t\treturn undefined;\n\t\t\t};\n\t\t}\n\t}\n};\n\n// CHOOSE (variadic)\nexports.choose = function(a, b)\n{\n\tvar index = Math.floor(a);\n\tvar result = arguments[index];\n\tif (index < 1 || !result) return undefined;\n\treturn result;\n};\nexports.choose.inCast = 'N';\nexports.choose.variadic = true;\n\n// IFS function (variadic)\nfunction ifsFunc() {\n\tfor (var i = 0; i < arguments.length; i += 2)\n\t\t{if (arguments[i]) return arguments[i+1];}\n\treturn undefined;\n};\nifsFunc.inCast = '+B_';\n\nexports.ifs =\n{\n\tmin_args : 2,\n\tinput: '+B_',\n\tselect : function(operands) {\n\t\tif (operands.length % 2 !== 0) throw \"Odd number of arguments to IFS\";\n\t\treturn ifsFunc;\n\t}\n};\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/functions/logic.js",
            "tags": "",
            "module-type": "formula-function",
            "modified": "20171214060456114",
            "created": "20171214054240274"
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        "$:/plugins/ebalster/formula/functions/math.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Coerce = require(\"$:/plugins/ebalster/formula/coerce.js\");\n\n\n// Constants\nexports.pi = function()    {return (Math.PI);};\nexports._e = function()    {return (Math.E);};\n\nexports.pi.isConstant = true;\nexports._e.isConstant = true;\n\n\n// Random\nexports.rand        = function()        {return Math.random();};\nexports.randbetween = function(a, b)    {return (a+(b-a)*Math.random());};\nexports.randbetween.inCast = 'NN';\nexports.random = exports.rand;\n\n\n// Sign and absolute value\nexports.abs  = function(a)    {return Math.abs(a);};\nexports.abs.inCast = 'N';\nexports.sign = function(x)    {return (((x > 0) - (x < 0)) || +x);};\nexports.sign.inCast = 'N';\n\n// Min/max\nexports.min = function(a)\n{\n\tvar min = a;\n\tfor (var i = 1; i < arguments.length; ++i) min = Math.min(min, arguments[i]);\n\treturn min;\n};\nexports.min.variadic = true;\nexports.min.inCast = '+N';\n\nexports.max = function(a)\n{\n\tvar max = a;\n\tfor (var i = 1; i < arguments.length; ++i) max = Math.max(max, arguments[i]);\n\treturn max;\n};\nexports.max.variadic = true;\nexports.max.inCast = '+N';\n\nexports.clamp = function(a, min, max) {\n\treturn (Math.min(Math.max(a, min), max));\n};\nexports.clamp.inCast = 'NNN';\n\n\n/*\n\tSeries arithmetic\n*/\nfunction Count(a) {\n\tif (a instanceof Array) {\n\t\tvar n = 0;\n\t\tfor (var i = 0; i < a.length; ++i) n += Count(a[i]);\n\t\treturn n;\n\t}\n\treturn 1;\n}\nfunction Sum(a) {\n\tif (a instanceof Array) {\n\t\tvar n = 0;\n\t\tfor (var i = 0; i < a.length; ++i) n += Sum(a[i]);\n\t\treturn n;\n\t}\n\treturn Coerce.ToNum(a,this);\n}\nfunction Product(a) {\n\tif (a instanceof Array) {\n\t\tvar n = 1;\n\t\tfor (var i = 0; i < a.length; ++i) n *= Product(a[i]);\n\t\treturn n;\n\t}\n\treturn Coerce.ToNum(a,this);\n}\nfunction Average(a) {\n\treturn Sum(a) / Count(a);\n}\n\nfunction GenSeriesFunc(func) {\n\treturn {\n\t\tmin_args : 1,\n\t\tselect : function(operands) {\n\t\t\tswitch (operands.length) {\n\t\t\tcase 1: return func;\n\t\t\tdefault: return function() {return func(Array.prototype.slice.call(arguments));};\n\t\t\t}\n\t\t}\n\t};\n}\n\nexports.sum     = GenSeriesFunc(Sum);\nexports.average = GenSeriesFunc(Average);\nexports.product = GenSeriesFunc(Product);\n\n\n/*\n\tExponential\n*/\n\n// Exponentiation and logarithm\nexports.pow   = function(a, b)    {return (Math.pow(a, b));};\nexports.pow.inCast = 'NN';\nexports.log   = function(a, b)    {return (Math.log(a) / Math.log(b));};\nexports.log.inCast = 'NN';\nexports.exp   = function(a)       {return (Math.exp(a));};\nexports.exp.inCast = 'N';\nexports.ln    = function(a)       {return (Math.log(a));};\nexports.ln.inCast = 'N';\nexports.log2  = function(a)       {return (Math.log2(a));};\nexports.log2.inCast = 'N';\nexports.log10 = function(a)       {return (Math.log10(a));};\nexports.log10.inCast = 'N';\n\nexports.power = exports.pow;\n\n// Precise exponentiation and logarithm\nexports.expm1 = function(a)       {return (Math.expm1(a));};\nexports.expm1.inCast = 'N';\nexports.log1p = function(a)       {return (Math.log1p(a));};\nexports.log1p.inCast = 'N';\n\n// Roots\nexports.sqrt = function(a)    {return (Math.sqrt(a));};\nexports.sqrt.inCast = 'N';\nexports.cbrt = function(a)    {return (Math.cbrt(a));};\nexports.cbrt.inCast = 'N';\n\n\n/*\n\tTrigonometry\n*/\n\n// Conversion\nexports.radians = function(a)    {return (Math.PI*a/180);};\nexports.radians.inCast = 'N';\nexports.degrees = function(a)    {return (180*a/Math.PI);};\nexports.degrees.inCast = 'N';\n\n// Trigonometry\nexports.sin = function(a)    {return (  Math.sin(a));};\nexports.sin.inCast = 'N';\nexports.cos = function(a)    {return (  Math.cos(a));};\nexports.cos.inCast = 'N';\nexports.tan = function(a)    {return (  Math.tan(a));};\nexports.tan.inCast = 'N';\nexports.csc = function(a)    {return (1/Math.sin(a));};\nexports.csc.inCast = 'N';\nexports.sec = function(a)    {return (1/Math.cos(a));};\nexports.sec.inCast = 'N';\nexports.cot = function(a)    {return (1/Math.tan(a));};\nexports.cot.inCast = 'N';\n\n// Inverse Trigonometry\nexports.asin = function(a)    {return (Math.asin(  a));};\nexports.asin.inCast = 'N';\nexports.acos = function(a)    {return (Math.acos(  a));};\nexports.acos.inCast = 'N';\nexports.atan = function(a)    {return (Math.atan(  a));};\nexports.atan.inCast = 'N';\nexports.acsc = function(a)    {return (Math.asin(1/a));};\nexports.acsc.inCast = 'N';\nexports.asec = function(a)    {return (Math.acos(1/a));};\nexports.asec.inCast = 'N';\nexports.acot = function(a)    {return (Math.atan(1/a));};\nexports.acot.inCast = 'N';\nexports.atan2 = function(y,x)    {return (Math.atan2(y, x));};\nexports.atan2.inCast = 'NN';\n\n// Hyperbolic Trigonometry\nexports.sinh = function(a)    {return (  Math.sinh(a));};\nexports.sinh.inCast = 'N';\nexports.cosh = function(a)    {return (  Math.cosh(a));};\nexports.cosh.inCast = 'N';\nexports.tanh = function(a)    {return (  Math.tanh(a));};\nexports.tanh.inCast = 'N';\nexports.csch = function(a)    {return (1/Math.sinh(a));};\nexports.csch.inCast = 'N';\nexports.sech = function(a)    {return (1/Math.cosh(a));};\nexports.sech.inCast = 'N';\nexports.coth = function(a)    {return (1/Math.tanh(a));};\nexports.coth.inCast = 'N';\n\n// Inverse Hyperbolic Trigonometry\nexports.asinh = function(a)    {return (Math.asinh(  a));};\nexports.asinh.inCast = 'N';\nexports.acosh = function(a)    {return (Math.acosh(  a));};\nexports.acosh.inCast = 'N';\nexports.atanh = function(a)    {return (Math.atanh(  a));};\nexports.atanh.inCast = 'N';\nexports.acsch = function(a)    {return (Math.asinh(1/a));};\nexports.acsch.inCast = 'N';\nexports.asech = function(a)    {return (Math.acosh(1/a));};\nexports.asech.inCast = 'N';\nexports.acoth = function(a)    {return (Math.atanh(1/a));};\nexports.acoth.inCast = 'N';\n\n/*\n\tRounding, ceiling 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            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\n// Compile regex.  TODO: Precompile these where possible\n/*var TW_RX_FLAGS = /^\\(\\?[a-z]*\\)|\\(\\?[a-z]*\\)$/i;\n\nfunction tw_regex(rx_str, defaultFlags) {\n\tif (!rx_str) throw \"Empty regular expression\";\n\tvar flagPart = TW_RX_FLAGS.exec(rx_str);\n\tif (flagPart) {\n\t\tvar flagLen = flagPart[0].length;\n\t\tvar flags = flagPart[0].substr(2, flagPart[0].length-3);\n\t\tif (flagPart.index == 0) return new RegExp(rx_str.substr(flagLen), flags);\n\t\telse                     return new RegExp(rx_str.substr(0, rx_str.length-flagLen), flags);\n\t}\n\treturn new RegExp(rx_str, defaultFlags);\n}*/\n\n\n// Regex replace\nexports.regexreplace = function(s, rx, b) {\n\t//rx = tw_regex(rx, \"g\");\n\trx.lastIndex = 0;\n\treturn s.replace(rx, b);\n};\nexports.regexreplace.inCast = 'TRT';\n\n// Regex match\nexports.regexmatch = function(s, rx) {\n\t//rx = tw_regex(rx, \"\");\n\trx.lastIndex = 0;\n\treturn rx.test(s);\n};\nexports.regexmatch.inCast = 'TR';\n\n// Regex extract\nfunction regexextract(s, rx) {\n\t//rx = tw_regex(rx, \"g\");\n\trx.lastIndex = 0;\n\ts = s;\n\tvar captureIndex = arguments[2] || 0;\n\tvar matches = [];\n\tvar match;\n\twhile ((match = rx.exec(s)) != null) {\n\t\tif (match[0].length == 0) ++rx.lastIndex;\n\t\tmatches.push(match[captureIndex] || \"\");\n\t\tif (!rx.global) break;\n\t}\n\treturn matches;\n}\nregexextract.inCast = 'TRN';\n\nexports.regexextract = {\n\tmin_args: 2, max_args: 3,\n\tselect: function(operands) {return regexextract;}\n};\n\n// Regex extract, single argument\nfunction regexextract1(s, rx, dfl) {\n\t//rx = tw_regex(rx, \"\");\n\trx.lastIndex = 0;\n\ts = s;\n\tvar captureIndex = arguments[3] || 0;\n\tvar match = rx.exec(s);\n\treturn (match && match[captureIndex]) ? match[captureIndex] : dfl;\n}\nregexextract1.inCast = 'TRTN';\n\nexports.regexextract1 = {\n\tmin_args: 3, max_args: 4,\n\tselect: function(operands) {return regexextract1;}\n};\n\n})();",
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            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Coerce = require(\"$:/plugins/ebalster/formula/coerce.js\");\n\n\n// Cast to text.  Second argument not yet supported.\nexports.t = function(a)    {return a;};\nexports.t.inCast = 'T';\n\nfunction t_format(a, format) {return a;}\nt_format.inCast = 'TT';\n\nexports.text = {\n\tmin_args: 1, max_args: 1,\n\tinput: 'TT',\n\tselect: function(operands) {\n\t\tif (operands.length == 1) return exports.t;\n\t\treturn t_format;\n\t}\n};\n\n// Cast string to number.\nexports.value = function(a)    {return a;};\nexports.inCast = 'N';\n\n// Array to string\nvar JoinFunc = function(delimiter, ignore_empty, array, startIndex) {\n\tvar join = \"\", part;\n\tfor (var i = startIndex; i < array.length; ++i)\n\t{\n\t\tvar arg = array[i];\n\t\tif (arg instanceof Array) {\n\t\t\tpart = JoinFunc(delimiter, ignore_empty, arg, 0);\n\t\t}\n\t\telse {\n\t\t\tpart = Coerce.ToText(arg,this);\n\t\t}\n\t\tif (part.length || !ignore_empty) {\n\t\t\tif (join.length) join += delimiter;\n\t\t\tjoin += part;\n\t\t}\n\t}\n\treturn join;\n};\n\n// Join\nexports.join = function(delimiter) {\n\treturn JoinFunc.call(this, delimiter, false, arguments, 1);\n};\nexports.join.variadic = true;\nexports.join.inCast = 'T';\n\n// Textjoin\nexports.textjoin = function(delimiter, ignore_empty) {\n\treturn JoinFunc.call(this, delimiter, ignore_empty, arguments, 2);\n};\nexports.textjoin.variadic = true;\nexports.textjoin.inCast = 'T';\n\n// Split string to array\nexports.split = function(str, delimiter) {\n\treturn str.split(delimiter);\n};\nexports.split.inCast = 'T';\n\n// String length\nexports.len = function(str)     {return str.length;};\nexports.len.inCast = 'T';\n\n// String exact match\nexports.exact = function(a, b)    {return a === b;};\nexports.exact.inCast = 'TT';\n\n\n// Substrings\nexports.mid = function(str, i, n)    {return str.substr(i-1, n);};\nexports.exact.inCast = 'TNN';\n\nexports.substr = exports.mid;\n\n\n// Substitute\nexports.substitute = function(s, f, r)    {return s.split(f).join(r);};\nexports.substitute.inCast = 'TTT';\n\n// Replace (N/I)\n//exports.replace = function(s, p, l, r)    {return (s.splice(a, b));};\n\n\n// Concatenate\nexports.cat = function(a, b)    {return a + b;};\nexports.cat.inCast = 'TT';\n\n// Trim space\nexports.trim = function(a)      {return a.split(/^\\s+|\\s+$/g).join(\"\");};\nexports.trim.inCast = 'T';\n\n\n// Aliases\nexports.concatenate = exports.cat;\n\n\n})();",
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            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Nodes = require(\"$:/plugins/ebalster/formula/nodes.js\");\n\n\n// Get variable string by name.\nexports.transclude = {\n\tmin_args: 1, max_args: 2,\n\tconstruct: function(operands) {\n\t\tswitch (operands.length) {\n\t\t\tcase 1: return new Nodes.TranscludeText(operands[0]);\n\t\t\tcase 2: return new Nodes.TranscludeField(operands[0], operands[1]);\n\t\t}\n\t}\n};\n\n// Transclude tiddler text string by name.\nexports.transclude_index = {\n\tmin_args: 2, max_args: 2,\n\tconstruct: function(operands) {return new Nodes.TranscludeIndex(operands[0], operands[1]);}\n};\n\n// Transclude field string by name.\nexports.variable = {\n\tmin_args: 1, max_args: 1,\n\tconstruct: function(operands) {return new Nodes.Variable(operands[0]);}\n};\n\n// Interpret value as a datum.\nexports.datum = {\n\tmin_args: 1, max_args: 1,\n\tconstruct: function(operands) {return new Nodes.Datum(operands[0]);}\n};\n\n\n})();",
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            "text": "/*! @preserve\n * numeral.js\n * version : 2.0.6\n * author : Adam Draper\n * license : MIT\n * http://adamwdraper.github.com/Numeral-js/\n */\n!function(a,b){\"function\"==typeof define&&define.amd?define(b):\"object\"==typeof module&&module.exports?module.exports=b():a.numeral=b()}(this,function(){function a(a,b){this._input=a,this._value=b}var b,c,d=\"2.0.6\",e={},f={},g={currentLocale:\"en\",zeroFormat:null,nullFormat:null,defaultFormat:\"0,0\",scalePercentBy100:!0},h={currentLocale:g.currentLocale,zeroFormat:g.zeroFormat,nullFormat:g.nullFormat,defaultFormat:g.defaultFormat,scalePercentBy100:g.scalePercentBy100};return b=function(d){var f,g,i,j;if(b.isNumeral(d))f=d.value();else if(0===d||\"undefined\"==typeof d)f=0;else if(null===d||c.isNaN(d))f=null;else if(\"string\"==typeof d)if(h.zeroFormat&&d===h.zeroFormat)f=0;else if(h.nullFormat&&d===h.nullFormat||!d.replace(/[^0-9]+/g,\"\").length)f=null;else{for(g in e)if(j=\"function\"==typeof 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            "bag": "default",
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            "title": "$:/plugins/ebalster/formula/lib/numeral.js",
            "module-type": "library",
            "modified": "20180114171115244",
            "created": "20180114171007227"
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        "$:/plugins/ebalster/formula/license": {
            "text": "!!The MIT License (MIT)\n\nCopyright (c) 2017 Evan Balster\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \"Software\"), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of\nthe Software, and to permit persons to whom the Software is furnished to do so,\nsubject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS\nFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR\nCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER\nIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN\nCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.",
            "bag": "default",
            "revision": "0",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/ebalster/formula/license",
            "tags": "",
            "modified": "20171220211838536",
            "created": "20171220071005710",
            "caption": "license"
        },
        "$:/plugins/ebalster/formula/macros/formula.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Compute = require(\"$:/plugins/ebalster/formula/compute.js\");\n\n/*\n\tInformation about this macro\n*/\n\nexports.name = \"formula\";\nexports.params = [{\"name\": \"formula\"}];\n\n/*\nRun the macro\n*/\nexports.run = function(formula) {\n\n\ttry {\n\t\treturn Compute.evalFormula(formula, this);\n\t}\n\tcatch (err) {\n\t\treturn \"`\" + String(err) + \"`\";\n\t}\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/macros/formula.js",
            "tags": "",
            "module-type": "macro",
            "modified": "20171212194124031",
            "created": "20171210215758530"
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        "$:/plugins/ebalster/formula/nodes.js": {
            "text": "/*\\\ntitle: $:/plugins/ebalster/formula/nodes.js\ntype: application/javascript\nmodule-type: macro\n\nLibrary defining computation \"nodes\" used to build compiled formulas.\nOperands represent some value within the formula: an expression, datum, operator, constant or query...\nOperands may be constant, allowing the formula compiler to optimize them away.\n\n\\*/\n(function(){\n\n\"use strict\";\n\nvar Coerce = require(\"$:/plugins/ebalster/formula/coerce.js\");\n\n\n// A Context has all the information necessary for computations.\nexports.Context = function(widget, formats, locals, depth, maxDepth) {\n\tthis.widget = widget;\n\tthis.formats = formats || {};\n\tthis.locals = locals || {};\n\tthis.depth = depth || 1;\n\tthis.maxDepth = maxDepth || 256;\n\tif (this.maxDepth < this.depth) throw \"Formula recursion exceeds limit of \" + this.maxDepth + \".  Infinite regress?\";\n};\nexports.Context.prototype.sub          = function()        {return new exports.Context(this.widget,this.formats,null,this.depth+1,this.maxDepth);};\nexports.Context.prototype.let          = function(locals)  {return new exports.Context(this.widget,this.formats,locals,this.depth,this.maxDepth);};\nexports.Context.prototype.wiki         = function()        {return this.widget.wiki;};\nexports.Context.prototype.wikiVariable = function(name)    {return this.widget.getVariable(name);};\n\n\nexports.Node = function() {\n};\nexports.Node.prototype.is_constant = false;\nexports.Node.prototype.name = \"unknown-operand\";\nexports.Node.prototype.toString = function()    {return \"[Node \" + this.name + \"]\";};\n\n// Compute the Node's value.\nexports.Node.prototype.compute = function(ctx) {return undefined;};\n\n// Compute a specific type of value, with coercion if necessary.\nexports.Node.prototype.computeNum   = function(ctx) {return Coerce.ToNum  (this.compute(ctx), ctx);};\nexports.Node.prototype.computeText  = function(ctx) {return Coerce.ToText (this.compute(ctx), ctx);};\nexports.Node.prototype.computeBool  = function(ctx) {return Coerce.ToBool (this.compute(ctx), ctx);};\nexports.Node.prototype.computeDate  = function(ctx) {return Coerce.ToDate (this.compute(ctx), ctx);};\nexports.Node.prototype.computeArray = function(ctx) {return Coerce.ToArray(this.compute(ctx), ctx);};\nexports.Node.prototype.computeFunc  = function(ctx) {return Coerce.ToFunc (this.compute(ctx), ctx);};\n\n\n// An operand that just throws an error.\nexports.ThrowError = function(exception) {\n\tthis.exception = exception;\n};\nexports.ThrowError.prototype = new exports.Node();\nexports.ThrowError.prototype.name = \"error\";\nexports.ThrowError.prototype.compute = function(ctx)\n{\n\t// Throw up\n\tthrow this.exception;\n};\n\n// Scoped variable node.\nexports.ScopeVar = function(name) {\n\tthis.name = name;\n};\nexports.ScopeVar.prototype = new exports.Node();\n//exports.ScopeVar.prototype.name = \"scope-var\";\nexports.ScopeVar.prototype.compute = function(ctx) {return ctx.locals[this.name];};\n\n// Scoped variable assignment node.\nexports.LetVars = function(assigns, expr) {\n\tthis.assigns = assigns;\n\tthis.expr = expr;\n};\nexports.LetVars.prototype = new exports.Node();\nexports.LetVars.prototype.name = \"let\";\nexports.LetVars.prototype.compute = function(ctx) {\n\t// Each let-expression can access the ones before it.\n\tvar locals = Object.assign({}, ctx.locals);\n\tctx = ctx.let(locals);\n\tfor (var id in this.assigns) {\n\t\ttry {\n\t\t\tlocals[id] = this.assigns[id].compute(ctx);\n\t\t}\n\t\tcatch (err) {\n\t\t\tthrow \"computing LET '\" + id + \"': \" + err;\n\t\t}\n\t}\n\treturn this.expr.compute(ctx);\n};\n\n// Call a function by reference.\nexports.CallFunc = function CallFunc(func, args) {\n\tthis.func = func;\n\tthis.args = args;\n};\nexports.CallFunc.prototype = new exports.Node();\nexports.CallFunc.prototype.name = \"function-builtin\";\nexports.CallFunc.prototype.compute = (function(ctx) {\n\t// Check the function parameters.\n\tvar func = this.func.computeFunc(ctx);\n\tif (this.args.length < func.min_args) throw \"Too few parameters for function\";\n\tif (this.args.length > func.max_args) throw \"Too many parameters for function\";\n\t// Compute arguments.\n\tvar vals = [];\n\tfor (var i = 0; i < this.args.length; ++i) vals.push(this.args[i].compute(ctx));\n\t// Call the function!\n\treturn func.apply(ctx, vals);\n});\n\n// JavaScript function call with possible coercion.\nexports.CallJS = function CallJS(func, args) {\n\tthis.func = func;\n\tthis.args = args;\n\tthis.coerce = Coerce.GetCoerceFuncs(func, args);\n\tthis.n_coerce = Math.min(this.args.length, this.coerce.length);\n};\nexports.CallJS.prototype = new exports.Node();\nexports.CallJS.prototype.name = \"function-builtin\";\nexports.CallJS.prototype.compute = function(ctx) {\n\tvar vals = [];\n\tvar i = 0;\n\tfor (; i < this.n_coerce; ++i) vals.push(this.coerce[i](this.args[i].compute(ctx), ctx));\n\tfor (; i < this.args.length; ++i) vals.push(this.args[i].compute(ctx));\n\treturn this.func.apply(ctx, vals);\n};\n\n// Call a function by reference.\nexports.ArrayDef = function ArrayDef(elems) {\n\tthis.elems = elems;\n};\nexports.ArrayDef.prototype = new exports.Node();\nexports.ArrayDef.prototype.name = \"function-builtin\";\nexports.ArrayDef.prototype.compute = (function(ctx) {\n\t// Compute elements.\n\tvar elems = [];\n\tfor (var i = 0; i < this.elems.length; ++i) elems.push(this.elems[i].compute(ctx));\n\treturn elems;\n});\n\n\n// Function declaration operand.\nexports.Function = function(func, captures) {\n\tthis.func = func;\n\tthis.captures = captures;\n};\nexports.Function.prototype = new exports.Node();\nexports.Function.prototype.name = \"function\";\nexports.Function.prototype.is_constant = true;\nexports.Function.prototype.compute = function(ctx) {\n\tthis.func.captured = {};\n\tif (this.captures) {\n\t\tfor (var name in this.captures) {\n\t\t\tthis.func.captured[name] = ctx.locals[name];\n\t\t}\n\t}\n\treturn this.func;\n};\n\n// String constant operand.\nexports.Text = function(value) {this.value = value;};\nexports.Text.prototype = new exports.Node();\nexports.Text.prototype.name = \"string\";\nexports.Text.prototype.is_constant = true;\nexports.Text.prototype.compute = function(ctx) {return this.value;};\n\n// Date constant operand.\nexports.Date = function(value) {this.value = value;};\nexports.Date.prototype = new exports.Node();\nexports.Date.prototype.name = \"date\";\nexports.Date.prototype.is_constant = true;\nexports.Date.prototype.compute = function(ctx) {return this.value;};\n\n// Boolean constant operand.\nexports.Bool = function(value) {this.value = value;};\nexports.Bool.prototype = new exports.Node();\nexports.Bool.prototype.name = \"boolean\";\nexports.Bool.prototype.is_constant = true;\nexports.Bool.prototype.compute = function(ctx) {return this.value;};\n\n// Number constant operand.\nexports.Number = function(value) {this.value = value;};\nexports.Number.prototype = new exports.Node();\nexports.Number.prototype.name = \"number\";\nexports.Number.prototype.is_constant = true;\nexports.Number.prototype.compute = function(ctx) {return this.value;};\n\n// Regex constant operand.\nexports.Regex = function(value) {this.value = value;};\nexports.Regex.prototype = new exports.Node();\nexports.Regex.prototype.name = \"regex\";\nexports.Regex.prototype.is_constant = true;\nexports.Regex.prototype.compute = function(ctx) {return this.value;};\n\n\nvar Compile = require(\"$:/plugins/ebalster/formula/compile.js\");\n\n\n// \"Automatic\" operand; a compiled string value\nexports.Datum = function(origin) {\n\tthis.origin = origin;\n\tthis.text = null;\n\tthis.op = null;\n};\nexports.Datum.prototype = new exports.Node();\nexports.Datum.prototype.name = \"automatic\";\n\nexports.Datum.prototype.compute = function(ctx) {\n\n\tvar newText = this.origin.computeText(ctx);\n\n\tif (newText != this.text)\n\t{\n\t\tthis.text = newText;\n\t\ttry {\n\t\t\tthis.op = Compile.compileDatum(newText);\n\t\t}\n\t\tcatch (err) {\n\t\t\t// Save the error\n\t\t\tthis.op = new exports.ThrowError(\n\t\t\t\terr + \"\\n  source: \\\"\" + this.datum + \"\\\"\\n  from \" + origin.name);\n\t\t}\n\t}\n\n\treturn this.op.compute(ctx.sub());\n};\n\n\n// Transcluded text operand.\nexports.TranscludeText = function(title) {\n\tthis.title = title;\n};\nexports.TranscludeText.prototype = new exports.Node();\nexports.TranscludeText.prototype.name = \"transclude\";\n\nexports.TranscludeText.prototype.compute = function(ctx) {\n\treturn ctx.wiki().getTiddlerText(this.title.computeText(ctx),\"\");\n};\n\n// Transcluded field operand.\nexports.TranscludeField = function(title, field) {\n\tthis.title = title;\n\tthis.field = field;\n};\nexports.TranscludeField.prototype = new exports.Node();\nexports.TranscludeField.prototype.name = \"transclude-field\";\n\nexports.TranscludeField.prototype.compute = function(ctx) {\n\tvar tiddler = ctx.wiki().getTiddler(this.title.computeText(ctx)),\n\t\tfield = this.field.computeText(ctx);\n\treturn (tiddler && $tw.utils.hop(tiddler.fields,field)) ? tiddler.getFieldString(field) : \"\";\n};\n\n// Transcluded index operand.\nexports.TranscludeIndex = function(title, index) {\n\tthis.title = title;\n\tthis.index = index;\n};\nexports.TranscludeIndex.prototype = new exports.Node();\nexports.TranscludeIndex.prototype.name = \"transclude-index\";\n\nexports.TranscludeIndex.prototype.compute = function(ctx) {\n\treturn ctx.wiki().extractTiddlerDataItem(\n\t\tthis.title.computeText(ctx),\n\t\tthis.index.computeText(ctx),\"\");\n};\n\n\n// Variable operand.\nexports.Variable = function(variable) {\n\tthis.variable = variable;\n};\nexports.Variable.prototype = new exports.Node();\nexports.Variable.prototype.name = \"variable\";\n\nexports.Variable.prototype.compute = function(ctx) {\n\treturn ctx.wikiVariable(this.variable.computeText(ctx)) || \"\";\n};\n\n\n// Filter operand, with some lazy-compile optimizations.\nexports.Filter = function(filter) {\n\tthis.filter = filter;\n\tthis.elements = {}; // Each has count, op, value\n\t//this.array = [];\n\tthis.compileError = null;\n};\nexports.Filter.prototype = new exports.Node();\nexports.Filter.prototype.name = \"filter\";\n\nexports.Filter.prototype.compute = function(ctx) {\n\t// Apply the filter and compile each result\n\tvar i, expr, elem, exprs = ctx.wiki().filterTiddlers(this.filter, ctx.widget);\n\n\t// Clear the array and mark all existing elements for removal\n\tfor (expr in this.elements) this.elements[expr].count = 0;\n\t//this.array = [];\n\n\t// Selectively re-compile any filter results that have changed\n\tfor (i = 0; i < exprs.length; ++i)\n\t{\n\t\texpr = exprs[i];\n\t\telem = this.elements[expr];\n\t\t//this.array.push(expr);\n\t\t\n\t\tif (elem) ++elem.count;\n\t\telse try {\n\t\t\tthis.elements[expr] = {count: 1, op: Compile.compileDatum(expr), value: null};\n\t\t}\n\t\tcatch (err) {\n\t\t\t// Save the error\n\t\t\tthis.elements[expr] = new exports.ThrowError(\n\t\t\t\terr + \"\\n  source: \\\"\" + expr + \"\\\"\\n  from \\\"\" + this.filter + \"\\\"\");\n\t\t}\n\t}\n\n\t// Compute (unique) values.  Delete any elements with no copies left.\n\tfor (expr in this.elements) {\n\t\telem = this.elements[expr];\n\t\tif (elem.count === 0) delete this.elements[expr];\n\t\telse elem.val = elem.op.compute(ctx.sub());\n\t}\n\n\t// Return value computes an array of datum values.\n\tvar results = [];\n\tfor (i = 0; i < exprs.length; ++i) {\n\t\texpr = exprs[i];\n\t\tresults.push(this.elements[expr].val);\n\t}\n\treturn results;\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/nodes.js",
            "tags": "",
            "module-type": "library",
            "modified": "20180112071139424",
            "description": "",
            "created": "20171211183000431"
        },
        "$:/plugins/ebalster/formula/operators/arithmetic.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Unary sign operators\nexports.uplus    = {arity: 1, position: \"pre\",  operator: \"+\", function: \"uplus\"};\nexports.uminus   = {arity: 1, position: \"pre\",  operator: \"-\", function: \"uminus\"};\n\n// Add\nexports.plus     = {arity: 2, precedence: 10,   operator: \"+\", function: \"add\"};\nexports.minus    = {arity: 2, precedence: 10,   operator: \"-\", function: \"sub\"};\n\n// Multiply\nexports.multiply = {arity: 2, precedence: 20,   operator: \"*\", function: \"mul\"};\nexports.divide   = {arity: 2, precedence: 20,   operator: \"/\", function: \"div\"};\n\n// Exponential\nexports.pow      = {arity: 2, precedence: 30,   operator: \"^\", function: \"pow\", associativity: \"right\"};\n\n// Percentage\nexports.percent  = {arity: 1, position: \"post\", operator: \"%\", function: \"percent\"};\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/operators/arithmetic.js",
            "tags": "",
            "module-type": "formula-operator",
            "modified": "20171212223539769",
            "created": "20171212223503019"
        },
        "$:/plugins/ebalster/formula/operators/compare.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Equality\nexports.eq  = {arity: 2, precedence: 0,   operator: \"=\",  function: \"eq\"};\nexports.ne  = {arity: 2, precedence: 0,   operator: \"<>\", function: \"ne\"};\n\n// Inequality\nexports.gt  = {arity: 2, precedence: 0,   operator: \">\",  function: \"gt\"};\nexports.gte = {arity: 2, precedence: 0,   operator: \">=\", function: \"gte\"};\nexports.lt  = {arity: 2, precedence: 0,   operator: \"<\",  function: \"lt\"};\nexports.lte = {arity: 2, precedence: 0,   operator: \"<=\", function: \"lte\"};\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/operators/compare.js",
            "tags": "",
            "module-type": "formula-operator",
            "modified": "20171214050739104",
            "created": "20171214050556123"
        },
        "$:/plugins/ebalster/formula/operators/strings.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\n// Concatenate\nexports.concatenate = {arity: 2, precedence: 4, operator: \"&\", function: \"cat\"};\n\n})();",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/operators/strings.js",
            "tags": "",
            "module-type": "formula-operator",
            "modified": "20171213003346943",
            "created": "20171213003246267"
        },
        "$:/plugins/ebalster/formula/readme": {
            "text": "''Formula'' for TiddlyWiki, version {{$:/plugins/ebalster/formula!!version}}, by Evan Balster.\n\nFormulas are written between `(=` mushroom brackets `=)`.  Where possible, their functions and syntax are designed to emulate popular spreadsheet software (Microsoft Excel and Google Sheets).  They //also// support WikiText-like syntax for `{{`transclusion`}}`, `[`filters`]`, `<<`variables`>>`, and a large number of functions.\n\nFormulas can also be evaluated by the `$formula` widget, the `$formula-vars` widget and the `<<formula>>` macro.\n\nFurther documentation is available here: [[https://evanbalster.com/tiddlywiki/formulas.html]].\n\nThis plugin is a work in progress; please report any issues on GitHub: [[https://github.com/EvanBalster/TiddlyWikiFormula/issues]].",
            "bag": "default",
            "revision": "0",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/ebalster/formula/readme",
            "tags": "",
            "modified": "20171220212520970",
            "created": "20171220042006170",
            "caption": "readme"
        },
        "$:/plugins/ebalster/formula/settings": {
            "text": "Currently no global settings are implemented, but formulas can be controlled by setting some global macros.  For example:\n\n|Macro|Meaning|h\n|`\\define formulaFixed() 2`|makes numbers display with 2 decimal points.|\n|`\\define formulaPrecision() 4`|makes numbers display with 4 significant digits (but `formulafixed` takes priority.|\n|`\\define formulaDateFormat() YYYY-MM-0DD`|Sets a date display format using the same rules as TiddlyWiki.|\n\nPlace these at the top of the tiddler where they should take effect, or create a tiddler tagged with <<tag $:/tags/Macro>> to make them apply to all tiddlers.\n\nIn the future, we'll probably add some global settings here...",
            "bag": "default",
            "revision": "0",
            "type": "text/vnd.tiddlywiki",
            "title": "$:/plugins/ebalster/formula/settings",
            "tags": "",
            "modified": "20171221002035357",
            "created": "20171221001634811",
            "caption": "readme"
        },
        "$:/plugins/ebalster/formula/value.js": {
            "text": "(function(){\n\n\"use strict\";\n\n\nexports.NumberFormatFunc = null;\n\nexports.DateFormat = \"0hh:0mm, DDth MMM YYYY\";\n\n\n// Base type for formula values\nexports.Value = function() {\n  this.name = \"unknown-value\";\n};\n\n// Get the value payload\nexports.Value.prototype.get = function()    {return undefined;};\n\n// Describe the value\nexports.Value.prototype.describe = function()    {return this.name + \" (\" + String(this.get()) + \")\";};\n\nexports.Value.prototype.toString = function()    {return \"[Value \" + this.describe() + \"]\";};\n\n// Get the value as a number (generic implementation)\nexports.Value.prototype.asNum = function() {\n  var v = this.get();\n  var n = Number(v);\n  if (isNaN(n)) throw \"Cannot convert \" + this.describe() + \" to a number!\";\n  return n;\n};\n\n// Get the value as a number, summing arrays (generic implementation)\nexports.Value.prototype.asSum = function() {\n  var v = this.get();\n  var n;\n  if (Array.isArray(v)) {n = 0; for (var i = 0; i < v.length; ++i) n += Number(v[i]);}\n  else                  n = Number(v);\n  if (isNaN(n)) throw \"Cannot sum \" + this.describe() + \" to a number!\";\n  return n;\n};\n\n// More convertsions\nexports.Value.prototype.asString = function() {\n  return String(this.get());\n};\nexports.Value.prototype.asArray = function() {\n  var v = this.get();\n  if (Array.isArray(v)) return v;\n  else return [v];\n};\nexports.Value.prototype.asDate = function() {\n  throw \"Cannot convert \" + this.describe() + \" to a date!\";\n};\n\n\n// Undefined value.\nexports.V_Undefined = function() {\n  this.name = \"undefined\";\n};\nexports.V_Undefined.prototype = new exports.Value();\nexports.V_Undefined.prototype.get = function()    {return undefined;};\n\n\n// Array value.\nexports.V_Array = function(value) {\n  this.name = \"array\";\n\n  this.value = value;\n};\nexports.V_Array.prototype = new exports.Value();\nexports.V_Array.prototype.get   = function() {return this.value;};\nexports.V_Array.prototype.asNum = function() {throw \"Cannot convert \" + this.describe() + \" to number!\";};\nexports.V_Array.prototype.asSum = function() {\n  var n = 0;\n  for (var i = 0; i < this.value.length; ++i) n += this.value[i].asNum();\n  if (isNaN(n)) throw \"Cannot sum \" + this.describe() + \" to a number!\";\n  return n;\n};\nexports.V_Array.prototype.asString     = function() {\n  var result = \"\";\n  for (var i = 0; i < this.value.length; ++i) {\n    var part = this.value[i].asString();\n    if (i && part.length) result += \" \";\n    if (part.indexOf(/\\s/g) >= 0) result += \"[[\" + part + \"]]\";\n    else result += part;\n  }\n  return result;\n};\n\n\n// String value.\nexports.V_Text = function(value) {\n  this.name = \"string\";\n\n  this.value = value;\n};\nexports.V_Text.prototype = new exports.Value();\nexports.V_Text.prototype.get    = function()    {return this.value;};\n//exports.V_Text.prototype.asDate = function() {return $tw.utils.parseDate();}\n\n\n// Date value.\nexports.V_Date = function(value) {\n  this.name = \"date\";\n\n  this.value = value;\n};\nexports.V_Date.prototype = new exports.Value();\nexports.V_Date.prototype.get      = function()    {return this.value;};\nexports.V_Date.prototype.asString = function()    {return $tw.utils.formatDateString(this.value, exports.DateFormat);};\nexports.V_Date.prototype.asNum    = function()    {throw \"Date-to-Number conversion usupported\";};\nexports.V_Date.prototype.asSum    = function()    {throw \"Date-to-Number conversion usupported\";};\nexports.V_Date.prototype.asDate   = function()    {return this.value;};\n\n\n// Boolean value.\nexports.V_Bool = function(value) {\n  this.name = \"boolean\";\n\n  this.value = value;\n};\nexports.V_Bool.prototype = new exports.Value();\nexports.V_Bool.prototype.get      = function()    {return this.value;};\nexports.V_Bool.prototype.asString = function()    {return this.value ? \"TRUE\" : \"FALSE\";};\nexports.V_Bool.prototype.asNum    = function()    {return this.value ? 1 : 0;};\nexports.V_Bool.prototype.asSum    = function()    {return this.value ? 1 : 0;};\n\n\n// Number value.\nexports.V_Num = function(value) {\n  this.name = \"number\";\n\n  this.value = value;\n};\nexports.V_Num.prototype = new exports.Value();\nexports.V_Num.prototype.get      = function()    {return this.value;};\nexports.V_Num.prototype.asString = function()    {return (exports.NumberFormatFunc || String)(this.value);};\nexports.V_Num.prototype.asNum    = function()    {return this.value;};\nexports.V_Num.prototype.asSum    = function()    {return this.value;};\n\n\n// Percentage value.\nexports.V_Percent = function(value) {\n  this.name = \"percentage\";\n\n  this.value = value;\n};\nexports.V_Percent.prototype = new exports.V_Num();\nexports.V_Percent.prototype.asString = function()\n{\n  return (exports.NumberFormatFunc || String)(100*this.value) + \"%\";\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/value.js",
            "tags": "",
            "module-type": "library",
            "modified": "20171211195014088",
            "description": "",
            "created": "20171211195003728"
        },
        "$:/plugins/ebalster/formula/widgets/attributes/formula.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Compile = require(\"$:/plugins/ebalster/formula/compile.js\");\nvar Compute = require(\"$:/plugins/ebalster/formula/compute.js\");\nvar Nodes   = require(\"$:/plugins/ebalster/formula/nodes.js\");\n\nvar FormulaAttribute = function(widget, node) {\n\tthis.widget = widget;\n\tthis.formula = node.formula;\n\ttry {\n\t\tthis.compiledFormula = Compile.compileFormula(this.formula);\n\t}\n\tcatch (err) {\n\t\tthis.compiledFormula = new Nodes.ThrowError(err);\n\t}\n\tthis.value = this.compute();\n};\n\n/*\nInherit from the base ??? class\n*/\n//FormulaAttribute.prototype = new Attribute();\n\nFormulaAttribute.prototype.compute = function() {\n\t// Compute options\n\tthis.formatOptions =\n\t{\n\t\tfixed:        (this.widget.getVariable(\"formulaFixed\")),\n\t\tprecision:    (this.widget.getVariable(\"formulaPrecision\")),\n\t\tnumberFormat: (this.widget.getVariable(\"formulaNumberFormat\")),\n\t\tdateFormat:   (this.widget.getVariable(\"formulaDateFormat\")),\n\t};\n\t// Execute the formula.\n\ttry {\n\t\treturn Compute.computeFormula(this.compiledFormula, this.widget, this.formatOptions);\n\t}\n\tcatch (err) {\n\t\treturn \"\";\n\t}\n};\n\nFormulaAttribute.prototype.refresh = function(changedTiddlers) {\n\tthis.value = this.compute();\n\treturn this.value;\n};\n\n\nexports.formula = FormulaAttribute;\n\n})();\n\t",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/widgets/attributes/formula.js",
            "tags": "",
            "module-type": "attributevalue",
            "modified": "20171225035808674",
            "description": "Evaluates a formula as an attribute value string.",
            "created": "20171225035721011"
        },
        "$:/plugins/ebalster/formula/widgets/formula-vars.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar Compile = require(\"$:/plugins/ebalster/formula/compile.js\");\nvar Compute = require(\"$:/plugins/ebalster/formula/compute.js\");\n\nvar FormulaVarsWidget = function(parseTreeNode,options) {\n\t// Call the constructor\n\tWidget.call(this);\n\t// Initialise\t\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nFormulaVarsWidget.prototype = Object.create(Widget.prototype);\n\n/*\nRender this widget into the DOM\n*/\nFormulaVarsWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\n\tif (this.formulaError) {\n\t\t// Show an error.\n\t\tvar parseTreeNodes = [{type: \"element\", tag: \"span\", attributes: {\n\t\t\t\"class\": {type: \"string\", value: \"tc-error\"}\n\t\t}, children: [\n\t\t\t{type: \"text\", text: this.formulaError}\n\t\t]}];\n\t\tthis.makeChildWidgets(parseTreeNodes);\n\t}\n\telse {\n\t\t// Construct and render the child widgets.\n\t\tthis.makeChildWidgets();\n\t}\n\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nRecompute formulas\n*/\nFormulaVarsWidget.prototype.formula_recompute = function() {\n\t// Parse variables\n\tvar self = this;\n\n\tthis.formatOptions =\n\t{\n\t\tfixed:        (this.getAttribute(\"$fixed\")        || this.parentWidget.getVariable(\"formulaFixed\")),\n\t\tprecision:    (this.getAttribute(\"$precision\")    || this.parentWidget.getVariable(\"formulaPrecision\")),\n\t\tnumberFormat: (this.getAttribute(\"$numberFormat\") || this.parentWidget.getVariable(\"formulaNumberFormat\")),\n\t\tdateFormat:   (this.getAttribute(\"$dateFormat\")   || this.parentWidget.getVariable(\"formulaDateFormat\")),\n\t};\n\n\t// Deprecation\n\tif (this.getAttribute(\"$toFixed\")) {this.formulaError = \"Change '$toFixed' to '$fixed'.\"; return;}\n\tif (this.getAttribute(\"$toPrecision\")) {this.formulaError = \"Change '$toPrecision' to '$precision'.\"; return;}\n\n\tif (!this.currentValues)\n\t{\n\t\t// Initial values\n\t\tthis.currentValues = {};\n\t\tthis.formulaSrc = {};\n\t\tthis.formulaComp = {};\n\t}\n\n\tthis.formulaError = null;\n\n\ttry {\n\t\tif (this.getAttribute(\"$noRefresh\")) throw \"Illegal $noRefresh attribute; use $noRebuild instead.\";\n\n\t\t$tw.utils.each(this.attributes,function(val,key) {\n\t\t\tif(key.charAt(0) !== \"$\") {\n\t\t\t\t// Recompile if necessary\n\t\t\t\tif (self.formulaSrc[key] != val) {\n\t\t\t\t\tself.formulaSrc[key] = val;\n\t\t\t\t\ttry {\n\t\t\t\t\t\tself.formulaComp[key] = Compile.compileFormula(self.formulaSrc[key]);\n\t\t\t\t\t}\n\t\t\t\t\tcatch (err) {\n\t\t\t\t\t\tself.formulaSrc[key] = null;\n\t\t\t\t\t\tthrow \"Variable \" + key + \": \" + String(err);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t// Recompute the formula\n\t\t\t\tif (self.formulaComp[key]) {\n\t\t\t\t\ttry {\n\t\t\t\t\t\tself.currentValues[key] = Compute.computeFormula(\n\t\t\t\t\t\t\tself.formulaComp[key], self, self.formatOptions);\n\t\t\t\t\t}\n\t\t\t\t\tcatch (err) {\n\t\t\t\t\t\tthrow \"Variable \" + key + \": \" + String(err);\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tthrow \"Variable \" + key + \": Formula not assigned\";\n\t\t\t\t}\n\t\t\t}\n\t\t});\n\t}\n\tcatch (err) {\n\t\tthis.formulaError = String(err);\n\t}\n};\n\n/*\nCompute the internal state of the widget\n*/\nFormulaVarsWidget.prototype.execute = function() {\n\t// Recompute formulas\n\tthis.formula_recompute();\n\n\tif (!this.formulaError) {\n\t\tfor (var key in this.currentValues) {\n\t\t\tthis.setVariable(key, this.currentValues[key]);\n\t\t}\n\t}\n};\n\n/*\nRefresh the widget by ensuring our attributes are up to date\n*/\nFormulaVarsWidget.prototype.refresh = function formulaVarsRefresh(changedTiddlers) {\n\tthis.computeAttributes();\n\tvar oldValues = Object.assign({}, this.currentValues || {}), oldError = this.formulaError;\n\tthis.formula_recompute();\n\n\t// Did any computed values change?\n\tvar changedValues = false;\n\tfor (var key in this.currentValues) {\n\t\tif (this.currentValues[key] !== oldValues[key]) {\n\t\t\tthis.setVariable(key, this.currentValues[key]);\n\t\t\tchangedValues = true;\n\t\t}\n\t}\n\n\t// Option to suppress full refreshing\n\tif (this.getAttribute(\"$noRebuild\") === \"true\") changedValues = false;\n\tif (this.formulaError !== oldError) changedValues = true;\n\n\tif(changedValues) {\n\t\t// Regenerate and rerender the widget and replace the existing DOM node\n\t\tthis.refreshSelf();\n\t\treturn true;\n\t} else {\n\t\treturn this.refreshChildren(changedTiddlers);\n\t}\n};\n\nexports[\"formula-vars\"] = FormulaVarsWidget;\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/widgets/formula-vars.js",
            "tags": "",
            "module-type": "widget",
            "modified": "20171222071557661",
            "description": "As the $vars widget, but each attribute is interpreted as a formula.",
            "created": "20171216003055342"
        },
        "$:/plugins/ebalster/formula/widgets/formula.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar Widget = require(\"$:/core/modules/widgets/widget.js\").widget;\n\nvar Compile = require(\"$:/plugins/ebalster/formula/compile.js\");\nvar Compute = require(\"$:/plugins/ebalster/formula/compute.js\");\n\nvar FormulaWidget = function(parseTreeNode,options) {\n\tthis.initialise(parseTreeNode,options);\n};\n\n/*\nInherit from the base widget class\n*/\nFormulaWidget.prototype = new Widget();\n\n/*\nRender this widget into the DOM\n*/\nFormulaWidget.prototype.render = function(parent,nextSibling) {\n\tthis.parentDomNode = parent;\n\tthis.computeAttributes();\n\tthis.execute();\n\tthis.rerender(parent,nextSibling);\n};\n\nFormulaWidget.prototype.rerender = function(parent, nextSibling) {\n\n\tthis.removeChildDomNodes();\n\n\tvar parseTreeNodes;\n\n\tif (this.formulaError) {\n\t\t// Show an error as a tc-error span.\n\t\tparseTreeNodes = [{type: \"element\", tag: \"span\", attributes: {\n\t\t\t\"class\": {type: \"string\", value: \"tc-error\"}\n\t\t}, children: [\n\t\t\t{type: \"text\", text: this.formulaError}\n\t\t]}];\n\t}\n\telse {\n\t\t// Parse the value, or, failing this, produce a text node.\n\t\tvar parser = this.wiki.parseText(\n\t\t\tthis.wikifyType, this.currentValue,\n\t\t\t{parseAsInline: this.wikifyMode === \"inline\"});\n\t\tparseTreeNodes = (parser ? parser.tree : [{type: \"text\", text: this.currentValue}]);\n\t}\n\n\t// Construct and render the child widgets.\n\tthis.makeChildWidgets(parseTreeNodes);\n\tthis.renderChildren(parent,nextSibling);\n};\n\n/*\nCompute the internal state of the widget\n*/\nFormulaWidget.prototype.execute = function() {\n\n\tvar oldFormula = this.formula;\n\n\t// Get parameters from our attributes\n\tthis.formula   = this.getAttribute(\"formula\");\n\tthis.debug     = this.getAttribute(\"debug\");\n\n\tthis.wikifyType = this.getAttribute(\"outputType\");\n\tthis.wikifyMode = this.getAttribute(\"outputMode\",\"inline\");\n\n\tthis.formatOptions =\n\t{\n\t\tfixed:        (this.getAttribute(\"fixed\")        || this.getVariable(\"formulaFixed\")),\n\t\tprecision:    (this.getAttribute(\"precision\")    || this.getVariable(\"formulaPrecision\")),\n\t\tnumberFormat: (this.getAttribute(\"numberFormat\") || this.getVariable(\"formulaNumberFormat\")),\n\t\tdateFormat:   (this.getAttribute(\"dateFormat\")   || this.getVariable(\"formulaDateFormat\")),\n\t};\n\n\t// Deprecation\n\tif (this.getAttribute(\"toFixed\")) {this.formulaError = \"Change 'toFixed' to 'fixed'.\"; return;}\n\tif (this.getAttribute(\"toPrecision\")) {this.formulaError = \"Change 'toPrecision' to 'precision'.\"; return;}\n\n\t// Compile the formula, if it has changed, yielding compiledFormula\n\tif(this.formula !== oldFormula) {\n\t\t// Clear the error flag\n\t\tthis.formulaError = null;\n\t\tthis.compiledFormula = null;\n\t\tif (this.formula) {\n\t\t\ttry {\n\t\t\t\tthis.compiledFormula = Compile.compileFormula(this.formula);\n\t\t\t}\n\t\t\tcatch (err) {\n\t\t\t\tthis.formulaError = String(err);\n\t\t\t\tthis.formula = null;\n\t\t\t\treturn;\n\t\t\t}\n\t\t}\n\t}\n\n\t// Compute the formula, yielding currentValue\n\tif(this.compiledFormula) {\n\t\ttry {\n\t\t\tthis.currentValue = Compute.computeFormula(this.compiledFormula, this, this.formatOptions, Boolean(this.debug));\n\t\t}\n\t\tcatch (err) {\n\t\t\tthis.formulaError = String(err);\n\t\t}\n\t}\n\telse {\n\t\tthis.formulaError = \"Error: formula not assigned\";\n\t}\n};\n\n/*\nSelectively refreshes the widget if needed. Returns true if the widget or any of its children needed re-rendering\n*/\nFormulaWidget.prototype.refresh = function(changedTiddlers) {\n\t// Re-execute the filter to get the count\n\tthis.computeAttributes();\n\tvar oldValue = this.currentValue, oldError = this.formulaError;\n\tthis.execute();\n\tif(this.oldError !== this.formulaError || this.currentValue !== oldValue) {\n\t\t// Regenerate and rerender the widget and replace the existing DOM node\n\t\t//   We DON'T call refreshSelf() because it call execute() again\n\t\tvar nextSibling = this.findNextSiblingDomNode();\n\t\tthis.rerender(this.parentDomNode,nextSibling);\n\t\treturn true;\n\t} else {\n\t\treturn false;\n\t}\n\n};\n\nexports.formula = FormulaWidget;\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/widgets/formula.js",
            "tags": "",
            "module-type": "widget",
            "modified": "20171212194059701",
            "description": "Evaluates a formula.",
            "created": "20171210232543292"
        },
        "$:/plugins/ebalster/formula/wikiparser/attributes/formula.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n\nexports.formula = function(source, pos, node) {\n\t// Is it a formula?\n\tvar reFormulaValue = /\\(=(([^=]+|=[^\\)])*)=\\)/g;\n\n\tvar value = $tw.utils.parseTokenRegExp(source,pos,reFormulaValue);\n\tif (!value) return null;\n\n\tnode.type = \"formula\";\n\tnode.formula = value.match[1];\n\tnode.end = value.end;\n\treturn node;\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/wikiparser/attributes/formula.js",
            "tags": "",
            "module-type": "attributerule",
            "modified": "20171225042523039",
            "description": "Tag attribute rule for formulas.  Ex. `(= 2+2 =)`",
            "created": "20171224060415431"
        },
        "$:/plugins/ebalster/formula/wikiparser/formula.js": {
            "text": "(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.name = \"formula\";\nexports.types = {inline: true};\n\nexports.init = function(parser) {\n\tthis.parser = parser;\n\t// Regexp to match\n\tthis.matchRegExp = /\\(=/mg;\n\tthis.endMatchRegExp = /=\\)/mg;\n};\n\nexports.parse = function() {\n\t// Move past the match\n\tthis.parser.pos = this.matchRegExp.lastIndex;\n\t// Look for the end marker\n\tthis.endMatchRegExp.lastIndex = this.parser.pos;\n\tvar match = this.endMatchRegExp.exec(this.parser.source),\n\t\ttext;\n\t// Process the text\n\tif(match) {\n\t\ttext = this.parser.source.substring(this.parser.pos,match.index);\n\t\tthis.parser.pos = match.index + match[0].length;\n\t} else {\n\t\ttext = this.parser.source.substr(this.parser.pos);\n\t\tthis.parser.pos = this.parser.sourceLength;\n\t}\n\treturn [{\n\t\ttype: \"formula\",\n\t\tattributes: {\n\t\t\tformula: {type: \"string\", value: text},\n\t\t}\n\t}];\n};\n\n})();\n",
            "bag": "default",
            "revision": "0",
            "type": "application/javascript",
            "title": "$:/plugins/ebalster/formula/wikiparser/formula.js",
            "tags": "",
            "module-type": "wikirule",
            "modified": "20171211181716654",
            "description": "Wiki text inline rule for formulas.  Ex. `((=2+2))`",
            "created": "20171211033327565"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/tiddlywiki/excel-utils/deserializer.js": {
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/excel-utils/deserializer.js\ntype: application/javascript\nmodule-type: tiddlerdeserializer\n\nXLSX file deserializer\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar bibtexParse = require(\"$:/plugins/tiddlywiki/bibtex/bibtexParse.js\");\n\n/*\nParse an XLSX file into tiddlers\n*/\nexports[\"application/x-bibtex\"] = function(text,fields) {\n\tvar data,\n\t\tresults = [];\n\t// Parse the text\n\ttry {\n\t\tdata = bibtexParse.toJSON(text)\n\t} catch(ex) {\n\t\tdata = ex.toString();\n\t}\n\tif(typeof data === \"string\") {\n\t\treturn [{\n\t\t\ttitle: \"BibTeX import error: \" + data,\n\t\t}];\n\t}\n\t// Convert each entry\n\t$tw.utils.each(data,function(entry) {\n\t\tvar fields = {\n\t\t\ttitle: entry.citationKey,\n\t\t\t\"bibtex-entry-type\": entry.entryType\n\t\t};\n\t\t$tw.utils.each(entry.entryTags,function(value,name) {\n\t\t\tfields[\"bibtex-\" + name] = value;\n\t\t});\n\t\tresults.push(fields);\n\t});\n\t// Return the output tiddlers\n\treturn results;\n};\n\n})();\n",
            "title": "$:/plugins/tiddlywiki/excel-utils/deserializer.js",
            "type": "application/javascript",
            "module-type": "tiddlerdeserializer"
        },
        "$:/plugins/tiddlywiki/bibtex/readme": {
            "title": "$:/plugins/tiddlywiki/bibtex/readme",
            "text": "The BibTeX plugin provides a deserializer that can convert bibliographic entries in `.bib` files into individual tiddlers.\n\nYou can use it in the browser by dragging and dropping a `.bib` file into the TiddlyWiki window. Under Node.js, use the `--load` command to load a `.bib` file.\n\nThe conversion is as follows:\n\n* `title` comes from citationKey\n* `bibtex-entry-type` comes from entryType\n* all `entryTags` are assigned to fields with the prefix `bibtex-`\n\nThe BibTeX plugin is based on the library [[bibtexParseJs by Henrik Muehe and Mikola Lysenko|https://github.com/ORCID/bibtexParseJs]].\n"
        },
        "$:/plugins/tiddlywiki/bibtex/bibtexParse.js": {
            "text": "/* start bibtexParse 0.0.22 */\n\n//Original work by Henrik Muehe (c) 2010\n//\n//CommonJS port by Mikola Lysenko 2013\n//\n//Port to Browser lib by ORCID / RCPETERS\n//\n//Issues:\n//no comment handling within strings\n//no string concatenation\n//no variable values yet\n//Grammar implemented here:\n//bibtex -> (string | preamble | comment | entry)*;\n//string -> '@STRING' '{' key_equals_value '}';\n//preamble -> '@PREAMBLE' '{' value '}';\n//comment -> '@COMMENT' '{' value '}';\n//entry -> '@' key '{' key ',' key_value_list '}';\n//key_value_list -> key_equals_value (',' key_equals_value)*;\n//key_equals_value -> key '=' value;\n//value -> value_quotes | value_braces | key;\n//value_quotes -> '\"' .*? '\"'; // not quite\n//value_braces -> '{' .*? '\"'; // not quite\n(function(exports) {\n\n    function BibtexParser() {\n        \n        this.months = [\"jan\", \"feb\", \"mar\", \"apr\", \"may\", \"jun\", \"jul\", \"aug\", \"sep\", \"oct\", \"nov\", \"dec\"];\n        this.notKey = [',','{','}',' ','='];\n        this.pos = 0;\n        this.input = \"\";\n        this.entries = new Array();\n\n        this.currentEntry = \"\";\n\n        this.setInput = function(t) {\n            this.input = t;\n        };\n\n        this.getEntries = function() {\n            return this.entries;\n        };\n\n        this.isWhitespace = function(s) {\n            return (s == ' ' || s == '\\r' || s == '\\t' || s == '\\n');\n        };\n\n        this.match = function(s, canCommentOut) {\n            if (canCommentOut == undefined || canCommentOut == null)\n                canCommentOut = true;\n            this.skipWhitespace(canCommentOut);\n            if (this.input.substring(this.pos, this.pos + s.length) == s) {\n                this.pos += s.length;\n            } else {\n                throw \"Token mismatch, expected \" + s + \", found \"\n                        + this.input.substring(this.pos);\n            };\n            this.skipWhitespace(canCommentOut);\n        };\n\n        this.tryMatch = function(s, canCommentOut) {\n            if (canCommentOut == undefined || canCommentOut == null)\n                canCommentOut = true;\n            this.skipWhitespace(canCommentOut);\n            if (this.input.substring(this.pos, this.pos + s.length) == s) {\n                return true;\n            } else {\n                return false;\n            };\n            this.skipWhitespace(canCommentOut);\n        };\n\n        /* when search for a match all text can be ignored, not just white space */\n        this.matchAt = function() {\n            while (this.input.length > this.pos && this.input[this.pos] != '@') {\n                this.pos++;\n            };\n\n            if (this.input[this.pos] == '@') {\n                return true;\n            };\n            return false;\n        };\n\n        this.skipWhitespace = function(canCommentOut) {\n            while (this.isWhitespace(this.input[this.pos])) {\n                this.pos++;\n            };\n            if (this.input[this.pos] == \"%\" && canCommentOut == true) {\n                while (this.input[this.pos] != \"\\n\") {\n                    this.pos++;\n                };\n                this.skipWhitespace(canCommentOut);\n            };\n        };\n\n        this.value_braces = function() {\n            var bracecount = 0;\n            this.match(\"{\", false);\n            var start = this.pos;\n            var escaped = false;\n            while (true) {\n                if (!escaped) {\n                    if (this.input[this.pos] == '}') {\n                        if (bracecount > 0) {\n                            bracecount--;\n                        } else {\n                            var end = this.pos;\n                            this.match(\"}\", false);\n                            return this.input.substring(start, end);\n                        };\n                    } else if (this.input[this.pos] == '{') {\n                        bracecount++;\n                    } else if (this.pos >= this.input.length - 1) {\n                        throw \"Unterminated value\";\n                    };\n                };\n                if (this.input[this.pos] == '\\\\' && escaped == false)\n                    escaped = true;\n                else\n                    escaped = false;\n                this.pos++;\n            };\n        };\n\n        this.value_comment = function() {\n            var str = '';\n            var brcktCnt = 0;\n            while (!(this.tryMatch(\"}\", false) && brcktCnt == 0)) {\n                str = str + this.input[this.pos];\n                if (this.input[this.pos] == '{')\n                    brcktCnt++;\n                if (this.input[this.pos] == '}')\n                    brcktCnt--;\n                if (this.pos >= this.input.length - 1) {\n                    throw \"Unterminated value:\" + this.input.substring(start);\n                };\n                this.pos++;\n            };\n            return str;\n        };\n\n        this.value_quotes = function() {\n            this.match('\"', false);\n            var start = this.pos;\n            var escaped = false;\n            while (true) {\n                if (!escaped) {\n                    if (this.input[this.pos] == '\"') {\n                        var end = this.pos;\n                        this.match('\"', false);\n                        return this.input.substring(start, end);\n                    } else if (this.pos >= this.input.length - 1) {\n                        throw \"Unterminated value:\" + this.input.substring(start);\n                    };\n                }\n                if (this.input[this.pos] == '\\\\' && escaped == false)\n                    escaped = true;\n                else\n                    escaped = false;\n                this.pos++;\n            };\n        };\n\n        this.single_value = function() {\n            var start = this.pos;\n            if (this.tryMatch(\"{\")) {\n                return this.value_braces();\n            } else if (this.tryMatch('\"')) {\n                return this.value_quotes();\n            } else {\n                var k = this.key();\n                if (k.match(\"^[0-9]+$\"))\n                    return k;\n                else if (this.months.indexOf(k.toLowerCase()) >= 0)\n                    return k.toLowerCase();\n                else\n                    throw \"Value expected:\" + this.input.substring(start) + ' for key: ' + k;\n            \n            };\n        };\n\n        this.value = function() {\n            var values = [];\n            values.push(this.single_value());\n            while (this.tryMatch(\"#\")) {\n                this.match(\"#\");\n                values.push(this.single_value());\n            };\n            return values.join(\"\");\n        };\n\n        this.key = function(optional) {\n            var start = this.pos;\n            while (true) {\n                if (this.pos >= this.input.length) {\n                    throw \"Runaway key\";\n                };\n                                // а-яА-Я is Cyrillic\n                //console.log(this.input[this.pos]);\n                if (this.notKey.indexOf(this.input[this.pos]) >= 0) {\n                    if (optional && this.input[this.pos] != ',') {\n                        this.pos = start;\n                        return null;\n                    };\n                    return this.input.substring(start, this.pos);\n                } else {\n                    this.pos++;\n                    \n                };\n            };\n        };\n\n        this.key_equals_value = function() {\n            var key = this.key();\n            if (this.tryMatch(\"=\")) {\n                this.match(\"=\");\n                var val = this.value();\n                return [ key, val ];\n            } else {\n                throw \"... = value expected, equals sign missing:\"\n                        + this.input.substring(this.pos);\n            };\n        };\n\n        this.key_value_list = function() {\n            var kv = this.key_equals_value();\n            this.currentEntry['entryTags'] = {};\n            this.currentEntry['entryTags'][kv[0]] = kv[1];\n            while (this.tryMatch(\",\")) {\n                this.match(\",\");\n                // fixes problems with commas at the end of a list\n                if (this.tryMatch(\"}\")) {\n                    break;\n                }\n                ;\n                kv = this.key_equals_value();\n                this.currentEntry['entryTags'][kv[0]] = kv[1];\n            };\n        };\n\n        this.entry_body = function(d) {\n            this.currentEntry = {};\n            this.currentEntry['citationKey'] = this.key(true);\n            this.currentEntry['entryType'] = d.substring(1);\n            if (this.currentEntry['citationKey'] != null) {            \n                this.match(\",\");\n            }\n            this.key_value_list();\n            this.entries.push(this.currentEntry);\n        };\n\n        this.directive = function() {\n            this.match(\"@\");\n            return \"@\" + this.key();\n        };\n\n        this.preamble = function() {\n            this.currentEntry = {};\n            this.currentEntry['entryType'] = 'PREAMBLE';\n            this.currentEntry['entry'] = this.value_comment();\n            this.entries.push(this.currentEntry);\n        };\n\n        this.comment = function() {\n            this.currentEntry = {};\n            this.currentEntry['entryType'] = 'COMMENT';\n            this.currentEntry['entry'] = this.value_comment();\n            this.entries.push(this.currentEntry);\n        };\n\n        this.entry = function(d) {\n            this.entry_body(d);\n        };\n\n        this.alernativeCitationKey = function () {\n            this.entries.forEach(function (entry) {\n                if (!entry.citationKey && entry.entryTags) {\n                    entry.citationKey = '';\n                    if (entry.entryTags.author) {\n                        entry.citationKey += entry.entryTags.author.split(',')[0] += ', ';\n                    }\n                    entry.citationKey += entry.entryTags.year;\n                }\n            });\n        }\n\n        this.bibtex = function() {\n            while (this.matchAt()) {\n                var d = this.directive();\n                this.match(\"{\");\n                if (d == \"@STRING\") {\n                    this.string();\n                } else if (d == \"@PREAMBLE\") {\n                    this.preamble();\n                } else if (d == \"@COMMENT\") {\n                    this.comment();\n                } else {\n                    this.entry(d);\n                }\n                this.match(\"}\");\n            };\n\n            this.alernativeCitationKey();\n        };\n    };\n    \n    exports.toJSON = function(bibtex) {\n        var b = new BibtexParser();\n        b.setInput(bibtex);\n        b.bibtex();\n        return b.entries;\n    };\n\n    /* added during hackathon don't hate on me */\n    exports.toBibtex = function(json) {\n        var out = '';\n        for ( var i in json) {\n            out += \"@\" + json[i].entryType;\n            out += '{';\n            if (json[i].citationKey)\n                out += json[i].citationKey + ', ';\n            if (json[i].entry)\n                out += json[i].entry ;\n            if (json[i].entryTags) {\n                var tags = '';\n                for (var jdx in json[i].entryTags) {\n                    if (tags.length != 0)\n                        tags += ', ';\n                    tags += jdx + '= {' + json[i].entryTags[jdx] + '}';\n                }\n                out += tags;\n            }\n            out += '}\\n\\n';\n        }\n        return out;\n        \n    };\n\n})(typeof exports === 'undefined' ? this['bibtexParse'] = {} : exports);\n\n/* end bibtexParse */\n",
            "type": "application/javascript",
            "title": "$:/plugins/tiddlywiki/bibtex/bibtexParse.js",
            "module-type": "library"
        },
        "$:/plugins/tiddlywiki/bibtex/license": {
            "text": "\nThe MIT License (MIT)\nCopyright (c) 2013 ORCID, Inc.\n\nCopyright (c) 2010 Henrik Muehe\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in\nall copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\nTHE SOFTWARE.\n",
            "type": "text/plain",
            "title": "$:/plugins/tiddlywiki/bibtex/license"
        }
    }
}

{
    "tiddlers": {
        "$:/config/Comments/EnableFilter": {
            "title": "$:/config/Comments/EnableFilter",
            "text": "[all[current]!is[system]]\n"
        },
        "$:/plugins/tiddlywiki/comments/above-story": {
            "title": "$:/plugins/tiddlywiki/comments/above-story",
            "tags": "$:/tags/AboveStory",
            "text": "<$reveal state=\"$:/config/Comments/EnableWikiComments\" type=\"match\" text=\"yes\" default=\"no\">\n<$tiddler tiddler=\"$:/SiteTitle\">\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/comments-template\" mode=\"inline\"/>\n</$tiddler>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/add-comment-button-actions": {
            "title": "$:/plugins/tiddlywiki/comments/add-comment-button-actions",
            "text": "<$set name=\"username\" value={{$:/status/UserName}} emptyValue=\"(anonymous)\">\n<$set name=\"target\" filter=\"[<currentTiddler>]\">\n<$action-createtiddler $basetitle={{{ [[Comment by ']addsuffix<username>addsuffix[' on ']addsuffix<currentTiddler>addsuffix[']] }}} role=\"comment\" list=<<target>> text=\"\" edit-mode=\"yes\"/>\n</$set>\n</$set>\n"
        },
        "$:/plugins/tiddlywiki/comments/add-comment-button": {
            "title": "$:/plugins/tiddlywiki/comments/add-comment-button",
            "text": "<$reveal state=\"$:/status/IsReadOnly\" type=\"match\" text=\"no\" default=\"no\" tag=\"div\" class=\"tc-comment-button\">\n<$button class=\"tc-btn-invisible\" actions={{$:/plugins/tiddlywiki/comments/add-comment-button-actions}}>\nadd comment {{$:/core/images/add-comment}}\n</$button>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/comments-template": {
            "title": "$:/plugins/tiddlywiki/comments/comments-template",
            "text": "<div class=\"tc-comments\">\n<ol class=\"tc-comment-list\">\n<$list filter=\"[all[tiddlers+shadows]role[comment]contains<currentTiddler>sort[created]!has[draft.of]]\">\n<li>\n<div class=\"tc-comment-entry\">\n<div class=\"tc-comment-entry-heading\">\n<$link>{{!!creator}} at <$view field=\"modified\" format=\"date\" template=\"0hh:0mm:0ss DDD DDth MMM YYYY\"/></$link>\n<$list filter=\"[all[shadows+tiddlers]tag[$:/tags/CommentToolbarButton]!has[draft.of]]\" variable=\"listItem\">\n<$transclude tiddler=<<listItem>> mode=\"inline\"/>\n</$list>\n</div>\n<div class=\"tc-comment-entry-body\">\n<$reveal type=\"match\" state=\"!!edit-mode\" text=\"yes\">\n<$edit-text tiddler=<<currentTiddler>> tag=\"textarea\" focus=\"true\"/>\n</$reveal>\n<$reveal type=\"nomatch\" state=\"!!edit-mode\" text=\"yes\">\n<$transclude tiddler=<<currentTiddler>> mode=\"block\"/>\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/add-comment-button\" mode=\"inline\"/>\n</$reveal>\n</div>\n</div>\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/comments-template\" mode=\"inline\"/>\n</li>\n</$list>\n</ol>\n</div>\n"
        },
        "$:/plugins/tiddlywiki/comments/config": {
            "title": "$:/plugins/tiddlywiki/comments/config",
            "text": "\\define select(description,filter)\n<$button>\n<$action-setfield $tiddler=\"$:/config/Comments/EnableFilter\" $value=<<__filter__>>/>\n$description$\n</$button>\n\\end\n\n! Wiki Comments\n\n<$checkbox tiddler=\"$:/config/Comments/EnableWikiComments\" field=\"text\" checked=\"yes\" unchecked=\"no\" default=\"no\"> <$link to=\"$:/config/Comments/EnableWikiComments\">Allow wiki-level comments as well as tiddler comments</$link> </$checkbox>\n\n! Tiddler Comments\n\nThis filter expression determines which tiddlers will have commenting enabled:\n\n<$edit-text tiddler=\"$:/config/Comments/EnableFilter\" tag=\"input\"/>\n\nOr you can choose a preselected filter:\n\n* <<select \"All tiddlers except system tiddlers\" \"[all[current]!is[system]]\">>\n* <<select \"Only tiddlers tagged 'commentable'\" \"[all[current]tag[commentable]]\">>\n* <<select \"Disable all commenting\" \"\">>\n"
        },
        "$:/plugins/tiddlywiki/comments/filter-all-comments": {
            "title": "$:/plugins/tiddlywiki/comments/filter-all-comments",
            "tags": "$:/tags/Filter",
            "filter": "[role[comment]!sort[modified]]",
            "description": "All comments",
            "text": ""
        },
        "$:/plugins/tiddlywiki/comments/footer-view-template-segment": {
            "title": "$:/plugins/tiddlywiki/comments/footer-view-template-segment",
            "tags": "$:/tags/ViewTemplate",
            "list-after": "$:/core/ui/ViewTemplate/body",
            "text": "<$list filter={{$:/config/Comments/EnableFilter}} variable=\"ignore\">\n<div class=\"tc-comments-segment\">\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/add-comment-button\" mode=\"inline\"/>\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/comments-template\" mode=\"inline\"/>\n</div>\n</$list>"
        },
        "$:/plugins/tiddlywiki/comments/header-view-template-segment": {
            "title": "$:/plugins/tiddlywiki/comments/header-view-template-segment",
            "tags": "$:/tags/ViewTemplate",
            "list-before": "$:/core/ui/ViewTemplate/body",
            "text": "<$list filter=\"[all[current]role[comment]]\" variable=\"ignore\">\n<div class=\"tc-is-comment-header\">\nThis tiddler is a comment on:\n<ul>\n<$list filter=\"[list<currentTiddler>sort[title]]\">\n<li>\n<$link to=<<currentTiddler>>><$text text=<<currentTiddler>>/></$link>\n</li>\n</$list>\n</ul>\n</div>\n</$list>\n"
        },
        "$:/plugins/tiddlywiki/comments/readme": {
            "title": "$:/plugins/tiddlywiki/comments/readme",
            "text": "This plugin provides a simple means for adding threaded comments to tiddlers.\n\n* Click the \"add comment\" button to make a new comment, and then click the \"save\" button to save it\n* You can comment on a tiddler itself, or add a comment to an existing comment\n* The sidebar tab ''Comments'' lists a timeline of all comments\n* Comments are attributed to the username stored in the system tiddler [[$:/status/UserName]]\n* By default, comments are available on all non-system tiddlers. The ''config'' tab lets you customise which tiddlers can accept comments by specifying a filter extension\n* The buttons for adding and editing comments are only available if the system tiddler [[$:/status/IsReadOnly]] is not set to `yes`\n* Use the \"All comments\" option in the $:/AdvancedSearch ''Filter'' tab to see or export all comments\n\n!! Data Model\n\nThe data model employed by the comments plugin is very simple:\n\n* Comment tiddlers are identified by the `role` field being set to `comment`\n* The `list` field of comment tiddlers lists the tiddlers to which this comment applies\n** It is thus possible for a comment to be applied to multiple tiddlers at once\n** The links between comments can be preserved when renaming them by using the relink checkbox in the edit template\n* The `edit-mode` field of comment tiddlers is set to `yes` to display it in edit mode, or `no` to display it in view mode\n* The `saved-text` field is updated when switching to edit mode so that it can be restored if the user cancels\n\n"
        },
        "$:/plugins/tiddlywiki/comments/sidebar-segment": {
            "title": "$:/plugins/tiddlywiki/comments/sidebar-segment",
            "tags": "$:/tags/SideBarSegment",
            "list-after": "$:/core/ui/SideBarSegments/site-subtitle",
            "text": "<$reveal state=\"$:/config/Comments/EnableWikiComments\" type=\"match\" text=\"yes\" default=\"no\">\n<$tiddler tiddler=\"$:/SiteTitle\">\n<$transclude tiddler=\"$:/plugins/tiddlywiki/comments/add-comment-button\" mode=\"inline\"/>\n</$tiddler>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/sidebar": {
            "title": "$:/plugins/tiddlywiki/comments/sidebar",
            "tags": "$:/tags/SideBar",
            "caption": "Comments",
            "text": "<div class=\"tc-timeline\">\n<$list filter=\"[all[tiddlers+shadows]role[comment]has[modified]!sort[modified]eachday[modified]]\">\n<div class=\"tc-menu-list-item\">\n<$view field=\"modified\" format=\"date\" template=\"DDth MMM YYYY\"/>\n<$list filter=\"[all[tiddlers+shadows]role[comment]sameday:modified{!!modified}!sort[modified]]\">\n<div class=\"tc-menu-list-subitem\">\n<$link>Comment by '<$view field=\"modifier\">(anonymous)</$view>'</$link> on\n<$list filter=\"[list<currentTiddler>sort[title]]\">\n<$link to=<<currentTiddler>>><$text text=<<currentTiddler>>/></$link>\n</$list>\n</div>\n</$list>\n</div>\n</$list>\n</div>\n"
        },
        "$:/plugins/tiddlywiki/comments/styles": {
            "title": "$:/plugins/tiddlywiki/comments/styles",
            "tags": "[[$:/tags/Stylesheet]]",
            "text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\n.tc-is-comment-header {\n\tbackground: #c1e1e9;\n\tpadding: 0.25em;\n}\n\n.tc-comments-segment {\n\tborder-top: 2px solid #c1e1e9;\n}\n\n.tc-comment-button button {\n\twidth: 100%;\n\ttext-align: right;\n}\n\n.tc-sidebar-scrollable .tc-comment-button button {\n\twidth: auto;\n\ttext-align: right;\n}\n\n.tc-comment-button button svg {\n\tfill: #26cb56;\n\theight: 2em;\n\twidth: 2em;\n}\n\n.tc-comments {\n}\n\n.tc-comment-list {\n\tlist-style: none;\n     padding-left: 0;\n}\n\n.tc-comment-list .tc-comments {\n\tpadding-left: 1em;\n}\n\n.tc-comment-entry {\n\tborder: 1px solid #c1e1ea;\n\tmargin: 0.5em 0 0 0;\n\tbackground: #dbf6ff;\n}\n\n.tc-comment-entry-heading {\n\tfont-size: 0.7em;\n\tfont-weight: bold;\n\ttext-transform: uppercase;\n\tbackground: #c1e1ea;\n\tcolor: #5B6D80;\n\tpadding: 0 0.5em;\n}\n\n.tc-comment-entry-body {\n\tfont-size: 0.8em;\n\tpadding: 0 0.5em;\n}\n\n.tc-comment-entry-body textarea {\n\tfont-size: 1.1em;\n\twidth: 100%\n}\n"
        },
        "$:/tags/CommentToolbarButton": {
            "title": "$:/tags/CommentToolbarButton",
            "list": "[[$:/plugins/tiddlywiki/comments/toolbar-button-cancel]] [[$:/plugins/tiddlywiki/comments/toolbar-button-delete]] [[$:/plugins/tiddlywiki/comments/toolbar-button-save]] [[$:/plugins/tiddlywiki/comments/toolbar-button-edit]]"
        },
        "$:/plugins/tiddlywiki/comments/toolbar-button-cancel": {
            "title": "$:/plugins/tiddlywiki/comments/toolbar-button-cancel",
            "tags": "$:/tags/CommentToolbarButton",
            "text": "<$reveal state=\"$:/status/IsReadOnly\" type=\"match\" text=\"no\" default=\"no\" tag=\"span\">\n<$reveal type=\"match\" state=\"!!edit-mode\" text=\"yes\">\n<$button>\n<$action-setfield $tiddler=<<currentTiddler>> $field=\"edit-mode\" $value=\"no\"/>\n<$action-setfield $tiddler=<<currentTiddler>> $field=\"text\" $value={{!!saved-text}}/>\ncancel\n</$button>\n</$reveal>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/toolbar-button-delete": {
            "title": "$:/plugins/tiddlywiki/comments/toolbar-button-delete",
            "tags": "$:/tags/CommentToolbarButton",
            "text": "<$reveal state=\"$:/status/IsReadOnly\" type=\"match\" text=\"no\" default=\"no\" tag=\"span\">\n<$reveal type=\"match\" state=\"!!edit-mode\" text=\"yes\">\n<$button>\n<$action-deletetiddler $tiddler=<<currentTiddler>>/>\ndelete\n</$button>\n</$reveal>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/toolbar-button-edit": {
            "title": "$:/plugins/tiddlywiki/comments/toolbar-button-edit",
            "tags": "$:/tags/CommentToolbarButton",
            "text": "<$reveal state=\"$:/status/IsReadOnly\" type=\"match\" text=\"no\" default=\"no\" tag=\"span\">\n<$reveal type=\"nomatch\" state=\"!!edit-mode\" text=\"yes\">\n<$button>\n<$action-setfield $tiddler=<<currentTiddler>> $field=\"edit-mode\" $value=\"yes\"/>\n<$action-setfield $tiddler=<<currentTiddler>> $field=\"saved-text\" $value={{!!text}}/>\nedit\n</$button>\n</$reveal>\n</$reveal>\n"
        },
        "$:/plugins/tiddlywiki/comments/toolbar-button-save": {
            "title": "$:/plugins/tiddlywiki/comments/toolbar-button-save",
            "tags": "$:/tags/CommentToolbarButton",
            "text": "<$reveal state=\"$:/status/IsReadOnly\" type=\"match\" text=\"no\" default=\"no\" tag=\"span\">\n<$reveal type=\"match\" state=\"!!edit-mode\" text=\"yes\">\n<$button>\n<$action-setfield $tiddler=<<currentTiddler>> $field=\"edit-mode\" $value=\"no\"/>\nsave\n</$button>\n</$reveal>\n</$reveal>\n"
        }
    }
}

{
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            "title": "$:/config/HighlightPlugin/TypeMappings/application/javascript",
            "text": "javascript"
        },
        "$:/config/HighlightPlugin/TypeMappings/application/json": {
            "title": "$:/config/HighlightPlugin/TypeMappings/application/json",
            "text": "json"
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        "$:/config/HighlightPlugin/TypeMappings/text/css": {
            "title": "$:/config/HighlightPlugin/TypeMappings/text/css",
            "text": "css"
        },
        "$:/config/HighlightPlugin/TypeMappings/text/html": {
            "title": "$:/config/HighlightPlugin/TypeMappings/text/html",
            "text": "html"
        },
        "$:/config/HighlightPlugin/TypeMappings/image/svg+xml": {
            "title": "$:/config/HighlightPlugin/TypeMappings/image/svg+xml",
            "text": "xml"
        },
        "$:/config/HighlightPlugin/TypeMappings/text/x-markdown": {
            "title": "$:/config/HighlightPlugin/TypeMappings/text/x-markdown",
            "text": "markdown"
        },
        "$:/plugins/tiddlywiki/highlight/highlight.js": {
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            "text": "/*\n\nOriginal style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>\n\n*/\n\n.hljs {\n  display: block;\n  overflow-x: auto;\n  padding: 0.5em;\n  background: #f0f0f0;\n  -webkit-text-size-adjust: none;\n}\n\n.hljs,\n.hljs-subst,\n.hljs-tag .hljs-title,\n.nginx .hljs-title {\n  color: black;\n}\n\n.hljs-string,\n.hljs-title,\n.hljs-constant,\n.hljs-parent,\n.hljs-tag .hljs-value,\n.hljs-rule .hljs-value,\n.hljs-preprocessor,\n.hljs-pragma,\n.hljs-name,\n.haml .hljs-symbol,\n.ruby .hljs-symbol,\n.ruby .hljs-symbol .hljs-string,\n.hljs-template_tag,\n.django .hljs-variable,\n.smalltalk .hljs-class,\n.hljs-addition,\n.hljs-flow,\n.hljs-stream,\n.bash .hljs-variable,\n.pf .hljs-variable,\n.apache .hljs-tag,\n.apache .hljs-cbracket,\n.tex .hljs-command,\n.tex .hljs-special,\n.erlang_repl .hljs-function_or_atom,\n.asciidoc .hljs-header,\n.markdown .hljs-header,\n.coffeescript .hljs-attribute,\n.tp .hljs-variable {\n  color: #800;\n}\n\n.smartquote,\n.hljs-comment,\n.hljs-annotation,\n.diff .hljs-header,\n.hljs-chunk,\n.asciidoc .hljs-blockquote,\n.markdown .hljs-blockquote {\n  color: #888;\n}\n\n.hljs-number,\n.hljs-date,\n.hljs-regexp,\n.hljs-literal,\n.hljs-hexcolor,\n.smalltalk .hljs-symbol,\n.smalltalk .hljs-char,\n.go .hljs-constant,\n.hljs-change,\n.lasso .hljs-variable,\n.makefile .hljs-variable,\n.asciidoc .hljs-bullet,\n.markdown .hljs-bullet,\n.asciidoc .hljs-link_url,\n.markdown .hljs-link_url {\n  color: #080;\n}\n\n.hljs-label,\n.ruby .hljs-string,\n.hljs-decorator,\n.hljs-filter .hljs-argument,\n.hljs-localvars,\n.hljs-array,\n.hljs-attr_selector,\n.hljs-important,\n.hljs-pseudo,\n.hljs-pi,\n.haml .hljs-bullet,\n.hljs-doctype,\n.hljs-deletion,\n.hljs-envvar,\n.hljs-shebang,\n.apache .hljs-sqbracket,\n.nginx .hljs-built_in,\n.tex .hljs-formula,\n.erlang_repl .hljs-reserved,\n.hljs-prompt,\n.asciidoc .hljs-link_label,\n.markdown .hljs-link_label,\n.vhdl .hljs-attribute,\n.clojure .hljs-attribute,\n.asciidoc .hljs-attribute,\n.lasso .hljs-attribute,\n.coffeescript .hljs-property,\n.hljs-phony {\n  color: #88f;\n}\n\n.hljs-keyword,\n.hljs-id,\n.hljs-title,\n.hljs-built_in,\n.css .hljs-tag,\n.hljs-doctag,\n.smalltalk .hljs-class,\n.hljs-winutils,\n.bash .hljs-variable,\n.pf .hljs-variable,\n.apache .hljs-tag,\n.hljs-type,\n.hljs-typename,\n.tex .hljs-command,\n.asciidoc .hljs-strong,\n.markdown .hljs-strong,\n.hljs-request,\n.hljs-status,\n.tp .hljs-data,\n.tp .hljs-io {\n  font-weight: bold;\n}\n\n.asciidoc .hljs-emphasis,\n.markdown .hljs-emphasis,\n.tp .hljs-units {\n  font-style: italic;\n}\n\n.nginx .hljs-built_in {\n  font-weight: normal;\n}\n\n.coffeescript .javascript,\n.javascript .xml,\n.lasso .markup,\n.tex .hljs-formula,\n.xml .javascript,\n.xml .vbscript,\n.xml .css,\n.xml .hljs-cdata {\n  opacity: 0.5;\n}\n",
            "type": "text/css",
            "title": "$:/plugins/tiddlywiki/highlight/highlight.css",
            "tags": "[[$:/tags/Stylesheet]]"
        },
        "$:/plugins/tiddlywiki/highlight/highlightblock.js": {
            "title": "$:/plugins/tiddlywiki/highlight/highlightblock.js",
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/highlight/highlightblock.js\ntype: application/javascript\nmodule-type: widget\n\nWraps up the fenced code blocks parser for highlight and use in TiddlyWiki5\n\n\\*/\n(function() {\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar TYPE_MAPPINGS_BASE = \"$:/config/HighlightPlugin/TypeMappings/\";\n\nvar CodeBlockWidget = require(\"$:/core/modules/widgets/codeblock.js\").codeblock;\n\nvar hljs = require(\"$:/plugins/tiddlywiki/highlight/highlight.js\");\n\nhljs.configure({tabReplace: \"    \"});\t\n\nCodeBlockWidget.prototype.postRender = function() {\n\tvar domNode = this.domNodes[0],\n\t\tlanguage = this.language,\n\t\ttiddler = this.wiki.getTiddler(TYPE_MAPPINGS_BASE + language);\n\tif(tiddler) {\n\t\tlanguage = tiddler.fields.text || \"\";\n\t}\n\tif(language && hljs.listLanguages().indexOf(language) !== -1) {\n\t\tdomNode.className = language.toLowerCase() + \" hljs\";\n\t\tif($tw.browser && !domNode.isTiddlyWikiFakeDom) {\n\t\t\thljs.highlightBlock(domNode);\t\t\t\n\t\t} else {\n\t\t\tvar text = domNode.textContent;\n\t\t\tdomNode.children[0].innerHTML = hljs.fixMarkup(hljs.highlight(language,text).value);\n\t\t\t// If we're using the fakedom then specially save the original raw text\n\t\t\tif(domNode.isTiddlyWikiFakeDom) {\n\t\t\t\tdomNode.children[0].textInnerHTML = text;\n\t\t\t}\n\t\t}\n\t}\t\n};\n\n})();\n",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/tiddlywiki/highlight/license": {
            "title": "$:/plugins/tiddlywiki/highlight/license",
            "type": "text/plain",
            "text": "Copyright (c) 2006, Ivan Sagalaev\nAll rights reserved.\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n    * Redistributions of source code must retain the above copyright\n      notice, this list of conditions and the following disclaimer.\n    * Redistributions in binary form must reproduce the above copyright\n      notice, this list of conditions and the following disclaimer in the\n      documentation and/or other materials provided with the distribution.\n    * Neither the name of highlight.js nor the names of its contributors\n      may be used to endorse or promote products derived from this software\n      without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY\nEXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY\nDIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND\nON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n"
        },
        "$:/plugins/tiddlywiki/highlight/readme": {
            "title": "$:/plugins/tiddlywiki/highlight/readme",
            "text": "This plugin provides syntax highlighting of code blocks using v8.8.0 of [[highlight.js|https://github.com/isagalaev/highlight.js]] from Ivan Sagalaev.\n\n! Usage\n\nWhen the plugin is installed it automatically applies highlighting to all codeblocks defined with triple backticks or with the CodeBlockWidget.\n\nThe language can optionally be specified after the opening triple braces:\n\n<$codeblock code=\"\"\"```css\n * { margin: 0; padding: 0; } /* micro reset */\n\nhtml { font-size: 62.5%; }\nbody { font-size: 14px; font-size: 1.4rem; } /* =14px */\nh1   { font-size: 24px; font-size: 2.4rem; } /* =24px */\n```\"\"\"/>\n\nIf no language is specified highlight.js will attempt to automatically detect the language.\n\n! Built-in Language Brushes\n\nThe plugin includes support for the following languages (referred to as \"brushes\" by highlight.js):\n\n* apache\n* bash\n* coffeescript\n* cpp\n* cs\n* css\n* diff\n* http\n* ini\n* java\n* javascript\n* json\n* makefile\n* markdown\n* nginx\n* objectivec\n* perl\n* php\n* python\n* ruby\n* sql\n* xml\n\nYou can also specify the language as a MIME content type (eg `text/html` or `text/css`). The mapping is accomplished via mapping tiddlers whose titles start with `$:/config/HighlightPlugin/TypeMappings/`.\n"
        },
        "$:/plugins/tiddlywiki/highlight/styles": {
            "title": "$:/plugins/tiddlywiki/highlight/styles",
            "tags": "[[$:/tags/Stylesheet]]",
            "text": ".hljs{display:block;overflow-x:auto;padding:.5em;color:#333;background:#f8f8f8;-webkit-text-size-adjust:none}.hljs-comment,.diff .hljs-header,.hljs-javadoc{color:#998;font-style:italic}.hljs-keyword,.css .rule .hljs-keyword,.hljs-winutils,.nginx .hljs-title,.hljs-subst,.hljs-request,.hljs-status{color:#333;font-weight:bold}.hljs-number,.hljs-hexcolor,.ruby .hljs-constant{color:teal}.hljs-string,.hljs-tag .hljs-value,.hljs-phpdoc,.hljs-dartdoc,.tex .hljs-formula{color:#d14}.hljs-title,.hljs-id,.scss .hljs-preprocessor{color:#900;font-weight:bold}.hljs-list .hljs-keyword,.hljs-subst{font-weight:normal}.hljs-class .hljs-title,.hljs-type,.vhdl .hljs-literal,.tex .hljs-command{color:#458;font-weight:bold}.hljs-tag,.hljs-tag .hljs-title,.hljs-rule .hljs-property,.django .hljs-tag .hljs-keyword{color:navy;font-weight:normal}.hljs-attribute,.hljs-variable,.lisp .hljs-body,.hljs-name{color:teal}.hljs-regexp{color:#009926}.hljs-symbol,.ruby .hljs-symbol .hljs-string,.lisp .hljs-keyword,.clojure .hljs-keyword,.scheme .hljs-keyword,.tex .hljs-special,.hljs-prompt{color:#990073}.hljs-built_in{color:#0086b3}.hljs-preprocessor,.hljs-pragma,.hljs-pi,.hljs-doctype,.hljs-shebang,.hljs-cdata{color:#999;font-weight:bold}.hljs-deletion{background:#fdd}.hljs-addition{background:#dfd}.diff .hljs-change{background:#0086b3}.hljs-chunk{color:#aaa}"
        },
        "$:/plugins/tiddlywiki/highlight/usage": {
            "title": "$:/plugins/tiddlywiki/highlight/usage",
            "text": "! Usage\n\nFenced code blocks can have a language specifier added to trigger highlighting in a specific language. Otherwise heuristics are used to detect the language.\n\n```\n ```js\n var a = b + c; // Highlighted as JavaScript\n ```\n```\n! Adding Themes\n\nYou can add themes from highlight.js by copying the CSS to a new tiddler and tagging it with [[$:/tags/Stylesheet]]. The available themes can be found on GitHub:\n\nhttps://github.com/isagalaev/highlight.js/tree/master/src/styles\n"
        }
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}

{
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See https://raw.github.com/Stuk/jszip/master/LICENSE.markdown.\n\nJSZip uses the library pako released under the MIT license :\nhttps://github.com/nodeca/pako/blob/master/LICENSE\n*/\n!function(a){if(\"object\"==typeof exports&&\"undefined\"!=typeof module)module.exports=a();else if(\"function\"==typeof define&&define.amd)define([],a);else{var b;\"undefined\"!=typeof window?b=window:\"undefined\"!=typeof global?b=global:\"undefined\"!=typeof self&&(b=self),b.JSZip=a()}}(function(){return function a(b,c,d){function e(g,h){if(!c[g]){if(!b[g]){var i=\"function\"==typeof require&&require;if(!h&&i)return i(g,!0);if(f)return f(g,!0);throw new Error(\"Cannot find module '\"+g+\"'\")}var j=c[g]={exports:{}};b[g][0].call(j.exports,function(a){var c=b[g][1][a];return e(c?c:a)},j,j.exports,a,b,c,d)}return c[g].exports}for(var f=\"function\"==typeof require&&require,g=0;g<d.length;g++)e(d[g]);return e}({1:[function(a,b,c){\"use strict\";var 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a,b,c,d=this.zip64EndOfCentralSize-44,e=0;d>e;)a=this.reader.readInt(2),b=this.reader.readInt(4),c=this.reader.readString(b),this.zip64ExtensibleData[a]={id:a,length:b,value:c}},readBlockZip64EndOfCentralLocator:function(){if(this.diskWithZip64CentralDirStart=this.reader.readInt(4),this.relativeOffsetEndOfZip64CentralDir=this.reader.readInt(8),this.disksCount=this.reader.readInt(4),this.disksCount>1)throw new Error(\"Multi-volumes zip are not supported\")},readLocalFiles:function(){var a,b;for(a=0;a<this.files.length;a++)b=this.files[a],this.reader.setIndex(b.localHeaderOffset),this.checkSignature(h.LOCAL_FILE_HEADER),b.readLocalPart(this.reader),b.handleUTF8(),b.processAttributes()},readCentralDir:function(){var a;for(this.reader.setIndex(this.centralDirOffset);this.reader.readString(4)===h.CENTRAL_FILE_HEADER;)a=new i({zip64:this.zip64},this.loadOptions),a.readCentralPart(this.reader),this.files.push(a)},readEndOfCentral:function(){var a=this.reader.lastIndexOfSignature(h.CENTRAL_DIRECTORY_END);if(-1===a){var b=!0;try{this.reader.setIndex(0),this.checkSignature(h.LOCAL_FILE_HEADER),b=!1}catch(c){}throw new Error(b?\"Can't find end of central directory : is this a zip file ? If it is, see http://stuk.github.io/jszip/documentation/howto/read_zip.html\":\"Corrupted zip : can't find end of central directory\")}if(this.reader.setIndex(a),this.checkSignature(h.CENTRAL_DIRECTORY_END),this.readBlockEndOfCentral(),this.diskNumber===g.MAX_VALUE_16BITS||this.diskWithCentralDirStart===g.MAX_VALUE_16BITS||this.centralDirRecordsOnThisDisk===g.MAX_VALUE_16BITS||this.centralDirRecords===g.MAX_VALUE_16BITS||this.centralDirSize===g.MAX_VALUE_32BITS||this.centralDirOffset===g.MAX_VALUE_32BITS){if(this.zip64=!0,a=this.reader.lastIndexOfSignature(h.ZIP64_CENTRAL_DIRECTORY_LOCATOR),-1===a)throw new Error(\"Corrupted zip : can't find the ZIP64 end of central directory locator\");this.reader.setIndex(a),this.checkSignature(h.ZIP64_CENTRAL_DIRECTORY_LOCATOR),this.readBlockZip64EndOfCentralLocator(),this.reader.setIndex(this.relativeOffsetEndOfZip64CentralDir),this.checkSignature(h.ZIP64_CENTRAL_DIRECTORY_END),this.readBlockZip64EndOfCentral()}},prepareReader:function(a){var b=g.getTypeOf(a);this.reader=\"string\"!==b||j.uint8array?\"nodebuffer\"===b?new e(a):new f(g.transformTo(\"uint8array\",a)):new d(a,this.loadOptions.optimizedBinaryString)},load:function(a){this.prepareReader(a),this.readEndOfCentral(),this.readCentralDir(),this.readLocalFiles()}},b.exports=c},{\"./nodeBufferReader\":12,\"./object\":13,\"./signature\":14,\"./stringReader\":15,\"./support\":17,\"./uint8ArrayReader\":18,\"./utils\":21,\"./zipEntry\":23}],23:[function(a,b){\"use strict\";function c(a,b){this.options=a,this.loadOptions=b}var d=a(\"./stringReader\"),e=a(\"./utils\"),f=a(\"./compressedObject\"),g=a(\"./object\"),h=0,i=3;c.prototype={isEncrypted:function(){return 1===(1&this.bitFlag)},useUTF8:function(){return 2048===(2048&this.bitFlag)},prepareCompressedContent:function(a,b,c){return function(){var d=a.index;a.setIndex(b);var e=a.readData(c);return a.setIndex(d),e}},prepareContent:function(a,b,c,d,f){return function(){var a=e.transformTo(d.uncompressInputType,this.getCompressedContent()),b=d.uncompress(a);if(b.length!==f)throw new Error(\"Bug : uncompressed data size mismatch\");return b}},readLocalPart:function(a){var b,c;if(a.skip(22),this.fileNameLength=a.readInt(2),c=a.readInt(2),this.fileName=a.readString(this.fileNameLength),a.skip(c),-1==this.compressedSize||-1==this.uncompressedSize)throw new Error(\"Bug or corrupted zip : didn't get enough informations from the central directory (compressedSize == -1 || uncompressedSize == -1)\");if(b=e.findCompression(this.compressionMethod),null===b)throw new Error(\"Corrupted zip : compression \"+e.pretty(this.compressionMethod)+\" unknown (inner file : \"+this.fileName+\")\");if(this.decompressed=new f,this.decompressed.compressedSize=this.compressedSize,this.decompressed.uncompressedSize=this.uncompressedSize,this.decompressed.crc32=this.crc32,this.decompressed.compressionMethod=this.compressionMethod,this.decompressed.getCompressedContent=this.prepareCompressedContent(a,a.index,this.compressedSize,b),this.decompressed.getContent=this.prepareContent(a,a.index,this.compressedSize,b,this.uncompressedSize),this.loadOptions.checkCRC32&&(this.decompressed=e.transformTo(\"string\",this.decompressed.getContent()),g.crc32(this.decompressed)!==this.crc32))throw new Error(\"Corrupted zip : CRC32 mismatch\")},readCentralPart:function(a){if(this.versionMadeBy=a.readInt(2),this.versionNeeded=a.readInt(2),this.bitFlag=a.readInt(2),this.compressionMethod=a.readString(2),this.date=a.readDate(),this.crc32=a.readInt(4),this.compressedSize=a.readInt(4),this.uncompressedSize=a.readInt(4),this.fileNameLength=a.readInt(2),this.extraFieldsLength=a.readInt(2),this.fileCommentLength=a.readInt(2),this.diskNumberStart=a.readInt(2),this.internalFileAttributes=a.readInt(2),this.externalFileAttributes=a.readInt(4),this.localHeaderOffset=a.readInt(4),this.isEncrypted())throw new Error(\"Encrypted zip are not supported\");this.fileName=a.readString(this.fileNameLength),this.readExtraFields(a),this.parseZIP64ExtraField(a),this.fileComment=a.readString(this.fileCommentLength)},processAttributes:function(){this.unixPermissions=null,this.dosPermissions=null;var a=this.versionMadeBy>>8;this.dir=16&this.externalFileAttributes?!0:!1,a===h&&(this.dosPermissions=63&this.externalFileAttributes),a===i&&(this.unixPermissions=this.externalFileAttributes>>16&65535),this.dir||\"/\"!==this.fileName.slice(-1)||(this.dir=!0)},parseZIP64ExtraField:function(){if(this.extraFields[1]){var a=new d(this.extraFields[1].value);this.uncompressedSize===e.MAX_VALUE_32BITS&&(this.uncompressedSize=a.readInt(8)),this.compressedSize===e.MAX_VALUE_32BITS&&(this.compressedSize=a.readInt(8)),this.localHeaderOffset===e.MAX_VALUE_32BITS&&(this.localHeaderOffset=a.readInt(8)),this.diskNumberStart===e.MAX_VALUE_32BITS&&(this.diskNumberStart=a.readInt(4))}},readExtraFields:function(a){var b,c,d,e=a.index;for(this.extraFields=this.extraFields||{};a.index<e+this.extraFieldsLength;)b=a.readInt(2),c=a.readInt(2),d=a.readString(c),this.extraFields[b]={id:b,length:c,value:d}},handleUTF8:function(){if(this.useUTF8())this.fileName=g.utf8decode(this.fileName),this.fileComment=g.utf8decode(this.fileComment);else{var a=this.findExtraFieldUnicodePath();null!==a&&(this.fileName=a);var b=this.findExtraFieldUnicodeComment();null!==b&&(this.fileComment=b)}},findExtraFieldUnicodePath:function(){var a=this.extraFields[28789];if(a){var b=new d(a.value);return 1!==b.readInt(1)?null:g.crc32(this.fileName)!==b.readInt(4)?null:g.utf8decode(b.readString(a.length-5))\n}return null},findExtraFieldUnicodeComment:function(){var a=this.extraFields[25461];if(a){var b=new d(a.value);return 1!==b.readInt(1)?null:g.crc32(this.fileComment)!==b.readInt(4)?null:g.utf8decode(b.readString(a.length-5))}return null}},b.exports=c},{\"./compressedObject\":2,\"./object\":13,\"./stringReader\":15,\"./utils\":21}],24:[function(a,b){\"use strict\";var c=a(\"./lib/utils/common\").assign,d=a(\"./lib/deflate\"),e=a(\"./lib/inflate\"),f=a(\"./lib/zlib/constants\"),g={};c(g,d,e,f),b.exports=g},{\"./lib/deflate\":25,\"./lib/inflate\":26,\"./lib/utils/common\":27,\"./lib/zlib/constants\":30}],25:[function(a,b,c){\"use strict\";function d(a,b){var c=new s(b);if(c.push(a,!0),c.err)throw c.msg;return c.result}function e(a,b){return b=b||{},b.raw=!0,d(a,b)}function f(a,b){return b=b||{},b.gzip=!0,d(a,b)}var g=a(\"./zlib/deflate.js\"),h=a(\"./utils/common\"),i=a(\"./utils/strings\"),j=a(\"./zlib/messages\"),k=a(\"./zlib/zstream\"),l=0,m=4,n=0,o=1,p=-1,q=0,r=8,s=function(a){this.options=h.assign({level:p,method:r,chunkSize:16384,windowBits:15,memLevel:8,strategy:q,to:\"\"},a||{});var b=this.options;b.raw&&b.windowBits>0?b.windowBits=-b.windowBits:b.gzip&&b.windowBits>0&&b.windowBits<16&&(b.windowBits+=16),this.err=0,this.msg=\"\",this.ended=!1,this.chunks=[],this.strm=new k,this.strm.avail_out=0;var c=g.deflateInit2(this.strm,b.level,b.method,b.windowBits,b.memLevel,b.strategy);if(c!==n)throw new Error(j[c]);b.header&&g.deflateSetHeader(this.strm,b.header)};s.prototype.push=function(a,b){var c,d,e=this.strm,f=this.options.chunkSize;if(this.ended)return!1;d=b===~~b?b:b===!0?m:l,e.input=\"string\"==typeof a?i.string2buf(a):a,e.next_in=0,e.avail_in=e.input.length;do{if(0===e.avail_out&&(e.output=new h.Buf8(f),e.next_out=0,e.avail_out=f),c=g.deflate(e,d),c!==o&&c!==n)return this.onEnd(c),this.ended=!0,!1;(0===e.avail_out||0===e.avail_in&&d===m)&&this.onData(\"string\"===this.options.to?i.buf2binstring(h.shrinkBuf(e.output,e.next_out)):h.shrinkBuf(e.output,e.next_out))}while((e.avail_in>0||0===e.avail_out)&&c!==o);return d===m?(c=g.deflateEnd(this.strm),this.onEnd(c),this.ended=!0,c===n):!0},s.prototype.onData=function(a){this.chunks.push(a)},s.prototype.onEnd=function(a){a===n&&(this.result=\"string\"===this.options.to?this.chunks.join(\"\"):h.flattenChunks(this.chunks)),this.chunks=[],this.err=a,this.msg=this.strm.msg},c.Deflate=s,c.deflate=d,c.deflateRaw=e,c.gzip=f},{\"./utils/common\":27,\"./utils/strings\":28,\"./zlib/deflate.js\":32,\"./zlib/messages\":37,\"./zlib/zstream\":39}],26:[function(a,b,c){\"use strict\";function d(a,b){var c=new m(b);if(c.push(a,!0),c.err)throw c.msg;return c.result}function e(a,b){return b=b||{},b.raw=!0,d(a,b)}var f=a(\"./zlib/inflate.js\"),g=a(\"./utils/common\"),h=a(\"./utils/strings\"),i=a(\"./zlib/constants\"),j=a(\"./zlib/messages\"),k=a(\"./zlib/zstream\"),l=a(\"./zlib/gzheader\"),m=function(a){this.options=g.assign({chunkSize:16384,windowBits:0,to:\"\"},a||{});var b=this.options;b.raw&&b.windowBits>=0&&b.windowBits<16&&(b.windowBits=-b.windowBits,0===b.windowBits&&(b.windowBits=-15)),!(b.windowBits>=0&&b.windowBits<16)||a&&a.windowBits||(b.windowBits+=32),b.windowBits>15&&b.windowBits<48&&0===(15&b.windowBits)&&(b.windowBits|=15),this.err=0,this.msg=\"\",this.ended=!1,this.chunks=[],this.strm=new k,this.strm.avail_out=0;var c=f.inflateInit2(this.strm,b.windowBits);if(c!==i.Z_OK)throw new Error(j[c]);this.header=new l,f.inflateGetHeader(this.strm,this.header)};m.prototype.push=function(a,b){var c,d,e,j,k,l=this.strm,m=this.options.chunkSize;if(this.ended)return!1;d=b===~~b?b:b===!0?i.Z_FINISH:i.Z_NO_FLUSH,l.input=\"string\"==typeof a?h.binstring2buf(a):a,l.next_in=0,l.avail_in=l.input.length;do{if(0===l.avail_out&&(l.output=new g.Buf8(m),l.next_out=0,l.avail_out=m),c=f.inflate(l,i.Z_NO_FLUSH),c!==i.Z_STREAM_END&&c!==i.Z_OK)return this.onEnd(c),this.ended=!0,!1;l.next_out&&(0===l.avail_out||c===i.Z_STREAM_END||0===l.avail_in&&d===i.Z_FINISH)&&(\"string\"===this.options.to?(e=h.utf8border(l.output,l.next_out),j=l.next_out-e,k=h.buf2string(l.output,e),l.next_out=j,l.avail_out=m-j,j&&g.arraySet(l.output,l.output,e,j,0),this.onData(k)):this.onData(g.shrinkBuf(l.output,l.next_out)))}while(l.avail_in>0&&c!==i.Z_STREAM_END);return c===i.Z_STREAM_END&&(d=i.Z_FINISH),d===i.Z_FINISH?(c=f.inflateEnd(this.strm),this.onEnd(c),this.ended=!0,c===i.Z_OK):!0},m.prototype.onData=function(a){this.chunks.push(a)},m.prototype.onEnd=function(a){a===i.Z_OK&&(this.result=\"string\"===this.options.to?this.chunks.join(\"\"):g.flattenChunks(this.chunks)),this.chunks=[],this.err=a,this.msg=this.strm.msg},c.Inflate=m,c.inflate=d,c.inflateRaw=e,c.ungzip=d},{\"./utils/common\":27,\"./utils/strings\":28,\"./zlib/constants\":30,\"./zlib/gzheader\":33,\"./zlib/inflate.js\":35,\"./zlib/messages\":37,\"./zlib/zstream\":39}],27:[function(a,b,c){\"use strict\";var d=\"undefined\"!=typeof Uint8Array&&\"undefined\"!=typeof Uint16Array&&\"undefined\"!=typeof Int32Array;c.assign=function(a){for(var b=Array.prototype.slice.call(arguments,1);b.length;){var c=b.shift();if(c){if(\"object\"!=typeof c)throw new TypeError(c+\"must be non-object\");for(var d in c)c.hasOwnProperty(d)&&(a[d]=c[d])}}return a},c.shrinkBuf=function(a,b){return a.length===b?a:a.subarray?a.subarray(0,b):(a.length=b,a)};var e={arraySet:function(a,b,c,d,e){if(b.subarray&&a.subarray)return void a.set(b.subarray(c,c+d),e);for(var f=0;d>f;f++)a[e+f]=b[c+f]},flattenChunks:function(a){var b,c,d,e,f,g;for(d=0,b=0,c=a.length;c>b;b++)d+=a[b].length;for(g=new Uint8Array(d),e=0,b=0,c=a.length;c>b;b++)f=a[b],g.set(f,e),e+=f.length;return g}},f={arraySet:function(a,b,c,d,e){for(var f=0;d>f;f++)a[e+f]=b[c+f]},flattenChunks:function(a){return[].concat.apply([],a)}};c.setTyped=function(a){a?(c.Buf8=Uint8Array,c.Buf16=Uint16Array,c.Buf32=Int32Array,c.assign(c,e)):(c.Buf8=Array,c.Buf16=Array,c.Buf32=Array,c.assign(c,f))},c.setTyped(d)},{}],28:[function(a,b,c){\"use strict\";function d(a,b){if(65537>b&&(a.subarray&&g||!a.subarray&&f))return String.fromCharCode.apply(null,e.shrinkBuf(a,b));for(var c=\"\",d=0;b>d;d++)c+=String.fromCharCode(a[d]);return c}var e=a(\"./common\"),f=!0,g=!0;try{String.fromCharCode.apply(null,[0])}catch(h){f=!1}try{String.fromCharCode.apply(null,new Uint8Array(1))}catch(h){g=!1}for(var i=new e.Buf8(256),j=0;256>j;j++)i[j]=j>=252?6:j>=248?5:j>=240?4:j>=224?3:j>=192?2:1;i[254]=i[254]=1,c.string2buf=function(a){var b,c,d,f,g,h=a.length,i=0;for(f=0;h>f;f++)c=a.charCodeAt(f),55296===(64512&c)&&h>f+1&&(d=a.charCodeAt(f+1),56320===(64512&d)&&(c=65536+(c-55296<<10)+(d-56320),f++)),i+=128>c?1:2048>c?2:65536>c?3:4;for(b=new e.Buf8(i),g=0,f=0;i>g;f++)c=a.charCodeAt(f),55296===(64512&c)&&h>f+1&&(d=a.charCodeAt(f+1),56320===(64512&d)&&(c=65536+(c-55296<<10)+(d-56320),f++)),128>c?b[g++]=c:2048>c?(b[g++]=192|c>>>6,b[g++]=128|63&c):65536>c?(b[g++]=224|c>>>12,b[g++]=128|c>>>6&63,b[g++]=128|63&c):(b[g++]=240|c>>>18,b[g++]=128|c>>>12&63,b[g++]=128|c>>>6&63,b[g++]=128|63&c);return b},c.buf2binstring=function(a){return d(a,a.length)},c.binstring2buf=function(a){for(var b=new e.Buf8(a.length),c=0,d=b.length;d>c;c++)b[c]=a.charCodeAt(c);return b},c.buf2string=function(a,b){var c,e,f,g,h=b||a.length,j=new Array(2*h);for(e=0,c=0;h>c;)if(f=a[c++],128>f)j[e++]=f;else if(g=i[f],g>4)j[e++]=65533,c+=g-1;else{for(f&=2===g?31:3===g?15:7;g>1&&h>c;)f=f<<6|63&a[c++],g--;g>1?j[e++]=65533:65536>f?j[e++]=f:(f-=65536,j[e++]=55296|f>>10&1023,j[e++]=56320|1023&f)}return d(j,e)},c.utf8border=function(a,b){var c;for(b=b||a.length,b>a.length&&(b=a.length),c=b-1;c>=0&&128===(192&a[c]);)c--;return 0>c?b:0===c?b:c+i[a[c]]>b?c:b}},{\"./common\":27}],29:[function(a,b){\"use strict\";function c(a,b,c,d){for(var e=65535&a|0,f=a>>>16&65535|0,g=0;0!==c;){g=c>2e3?2e3:c,c-=g;do e=e+b[d++]|0,f=f+e|0;while(--g);e%=65521,f%=65521}return e|f<<16|0}b.exports=c},{}],30:[function(a,b){b.exports={Z_NO_FLUSH:0,Z_PARTIAL_FLUSH:1,Z_SYNC_FLUSH:2,Z_FULL_FLUSH:3,Z_FINISH:4,Z_BLOCK:5,Z_TREES:6,Z_OK:0,Z_STREAM_END:1,Z_NEED_DICT:2,Z_ERRNO:-1,Z_STREAM_ERROR:-2,Z_DATA_ERROR:-3,Z_BUF_ERROR:-5,Z_NO_COMPRESSION:0,Z_BEST_SPEED:1,Z_BEST_COMPRESSION:9,Z_DEFAULT_COMPRESSION:-1,Z_FILTERED:1,Z_HUFFMAN_ONLY:2,Z_RLE:3,Z_FIXED:4,Z_DEFAULT_STRATEGY:0,Z_BINARY:0,Z_TEXT:1,Z_UNKNOWN:2,Z_DEFLATED:8}},{}],31:[function(a,b){\"use strict\";function c(){for(var a,b=[],c=0;256>c;c++){a=c;for(var d=0;8>d;d++)a=1&a?3988292384^a>>>1:a>>>1;b[c]=a}return b}function d(a,b,c,d){var f=e,g=d+c;a=-1^a;for(var h=d;g>h;h++)a=a>>>8^f[255&(a^b[h])];return-1^a}var e=c();b.exports=d},{}],32:[function(a,b,c){\"use strict\";function d(a,b){return a.msg=G[b],b}function e(a){return(a<<1)-(a>4?9:0)}function f(a){for(var b=a.length;--b>=0;)a[b]=0}function g(a){var b=a.state,c=b.pending;c>a.avail_out&&(c=a.avail_out),0!==c&&(C.arraySet(a.output,b.pending_buf,b.pending_out,c,a.next_out),a.next_out+=c,b.pending_out+=c,a.total_out+=c,a.avail_out-=c,b.pending-=c,0===b.pending&&(b.pending_out=0))}function h(a,b){D._tr_flush_block(a,a.block_start>=0?a.block_start:-1,a.strstart-a.block_start,b),a.block_start=a.strstart,g(a.strm)}function i(a,b){a.pending_buf[a.pending++]=b}function j(a,b){a.pending_buf[a.pending++]=b>>>8&255,a.pending_buf[a.pending++]=255&b}function k(a,b,c,d){var e=a.avail_in;return e>d&&(e=d),0===e?0:(a.avail_in-=e,C.arraySet(b,a.input,a.next_in,e,c),1===a.state.wrap?a.adler=E(a.adler,b,e,c):2===a.state.wrap&&(a.adler=F(a.adler,b,e,c)),a.next_in+=e,a.total_in+=e,e)}function l(a,b){var c,d,e=a.max_chain_length,f=a.strstart,g=a.prev_length,h=a.nice_match,i=a.strstart>a.w_size-jb?a.strstart-(a.w_size-jb):0,j=a.window,k=a.w_mask,l=a.prev,m=a.strstart+ib,n=j[f+g-1],o=j[f+g];a.prev_length>=a.good_match&&(e>>=2),h>a.lookahead&&(h=a.lookahead);do if(c=b,j[c+g]===o&&j[c+g-1]===n&&j[c]===j[f]&&j[++c]===j[f+1]){f+=2,c++;do;while(j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&j[++f]===j[++c]&&m>f);if(d=ib-(m-f),f=m-ib,d>g){if(a.match_start=b,g=d,d>=h)break;n=j[f+g-1],o=j[f+g]}}while((b=l[b&k])>i&&0!==--e);return g<=a.lookahead?g:a.lookahead}function m(a){var b,c,d,e,f,g=a.w_size;do{if(e=a.window_size-a.lookahead-a.strstart,a.strstart>=g+(g-jb)){C.arraySet(a.window,a.window,g,g,0),a.match_start-=g,a.strstart-=g,a.block_start-=g,c=a.hash_size,b=c;do d=a.head[--b],a.head[b]=d>=g?d-g:0;while(--c);c=g,b=c;do d=a.prev[--b],a.prev[b]=d>=g?d-g:0;while(--c);e+=g}if(0===a.strm.avail_in)break;if(c=k(a.strm,a.window,a.strstart+a.lookahead,e),a.lookahead+=c,a.lookahead+a.insert>=hb)for(f=a.strstart-a.insert,a.ins_h=a.window[f],a.ins_h=(a.ins_h<<a.hash_shift^a.window[f+1])&a.hash_mask;a.insert&&(a.ins_h=(a.ins_h<<a.hash_shift^a.window[f+hb-1])&a.hash_mask,a.prev[f&a.w_mask]=a.head[a.ins_h],a.head[a.ins_h]=f,f++,a.insert--,!(a.lookahead+a.insert<hb)););}while(a.lookahead<jb&&0!==a.strm.avail_in)}function n(a,b){var c=65535;for(c>a.pending_buf_size-5&&(c=a.pending_buf_size-5);;){if(a.lookahead<=1){if(m(a),0===a.lookahead&&b===H)return sb;if(0===a.lookahead)break}a.strstart+=a.lookahead,a.lookahead=0;var d=a.block_start+c;if((0===a.strstart||a.strstart>=d)&&(a.lookahead=a.strstart-d,a.strstart=d,h(a,!1),0===a.strm.avail_out))return sb;if(a.strstart-a.block_start>=a.w_size-jb&&(h(a,!1),0===a.strm.avail_out))return sb}return a.insert=0,b===K?(h(a,!0),0===a.strm.avail_out?ub:vb):a.strstart>a.block_start&&(h(a,!1),0===a.strm.avail_out)?sb:sb}function o(a,b){for(var c,d;;){if(a.lookahead<jb){if(m(a),a.lookahead<jb&&b===H)return sb;if(0===a.lookahead)break}if(c=0,a.lookahead>=hb&&(a.ins_h=(a.ins_h<<a.hash_shift^a.window[a.strstart+hb-1])&a.hash_mask,c=a.prev[a.strstart&a.w_mask]=a.head[a.ins_h],a.head[a.ins_h]=a.strstart),0!==c&&a.strstart-c<=a.w_size-jb&&(a.match_length=l(a,c)),a.match_length>=hb)if(d=D._tr_tally(a,a.strstart-a.match_start,a.match_length-hb),a.lookahead-=a.match_length,a.match_length<=a.max_lazy_match&&a.lookahead>=hb){a.match_length--;do a.strstart++,a.ins_h=(a.ins_h<<a.hash_shift^a.window[a.strstart+hb-1])&a.hash_mask,c=a.prev[a.strstart&a.w_mask]=a.head[a.ins_h],a.head[a.ins_h]=a.strstart;while(0!==--a.match_length);a.strstart++}else a.strstart+=a.match_length,a.match_length=0,a.ins_h=a.window[a.strstart],a.ins_h=(a.ins_h<<a.hash_shift^a.window[a.strstart+1])&a.hash_mask;else 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sb;if(0===a.lookahead)break}if(c=0,a.lookahead>=hb&&(a.ins_h=(a.ins_h<<a.hash_shift^a.window[a.strstart+hb-1])&a.hash_mask,c=a.prev[a.strstart&a.w_mask]=a.head[a.ins_h],a.head[a.ins_h]=a.strstart),a.prev_length=a.match_length,a.prev_match=a.match_start,a.match_length=hb-1,0!==c&&a.prev_length<a.max_lazy_match&&a.strstart-c<=a.w_size-jb&&(a.match_length=l(a,c),a.match_length<=5&&(a.strategy===S||a.match_length===hb&&a.strstart-a.match_start>4096)&&(a.match_length=hb-1)),a.prev_length>=hb&&a.match_length<=a.prev_length){e=a.strstart+a.lookahead-hb,d=D._tr_tally(a,a.strstart-1-a.prev_match,a.prev_length-hb),a.lookahead-=a.prev_length-1,a.prev_length-=2;do++a.strstart<=e&&(a.ins_h=(a.ins_h<<a.hash_shift^a.window[a.strstart+hb-1])&a.hash_mask,c=a.prev[a.strstart&a.w_mask]=a.head[a.ins_h],a.head[a.ins_h]=a.strstart);while(0!==--a.prev_length);if(a.match_available=0,a.match_length=hb-1,a.strstart++,d&&(h(a,!1),0===a.strm.avail_out))return sb}else if(a.match_available){if(d=D._tr_tally(a,0,a.window[a.strstart-1]),d&&h(a,!1),a.strstart++,a.lookahead--,0===a.strm.avail_out)return sb}else a.match_available=1,a.strstart++,a.lookahead--}return a.match_available&&(d=D._tr_tally(a,0,a.window[a.strstart-1]),a.match_available=0),a.insert=a.strstart<hb-1?a.strstart:hb-1,b===K?(h(a,!0),0===a.strm.avail_out?ub:vb):a.last_lit&&(h(a,!1),0===a.strm.avail_out)?sb:tb}function q(a,b){for(var c,d,e,f,g=a.window;;){if(a.lookahead<=ib){if(m(a),a.lookahead<=ib&&b===H)return sb;if(0===a.lookahead)break}if(a.match_length=0,a.lookahead>=hb&&a.strstart>0&&(e=a.strstart-1,d=g[e],d===g[++e]&&d===g[++e]&&d===g[++e])){f=a.strstart+ib;do;while(d===g[++e]&&d===g[++e]&&d===g[++e]&&d===g[++e]&&d===g[++e]&&d===g[++e]&&d===g[++e]&&d===g[++e]&&f>e);a.match_length=ib-(f-e),a.match_length>a.lookahead&&(a.match_length=a.lookahead)}if(a.match_length>=hb?(c=D._tr_tally(a,1,a.match_length-hb),a.lookahead-=a.match_length,a.strstart+=a.match_length,a.match_length=0):(c=D._tr_tally(a,0,a.window[a.strstart]),a.lookahead--,a.strstart++),c&&(h(a,!1),0===a.strm.avail_out))return sb}return a.insert=0,b===K?(h(a,!0),0===a.strm.avail_out?ub:vb):a.last_lit&&(h(a,!1),0===a.strm.avail_out)?sb:tb}function r(a,b){for(var c;;){if(0===a.lookahead&&(m(a),0===a.lookahead)){if(b===H)return sb;break}if(a.match_length=0,c=D._tr_tally(a,0,a.window[a.strstart]),a.lookahead--,a.strstart++,c&&(h(a,!1),0===a.strm.avail_out))return sb}return a.insert=0,b===K?(h(a,!0),0===a.strm.avail_out?ub:vb):a.last_lit&&(h(a,!1),0===a.strm.avail_out)?sb:tb}function s(a){a.window_size=2*a.w_size,f(a.head),a.max_lazy_match=B[a.level].max_lazy,a.good_match=B[a.level].good_length,a.nice_match=B[a.level].nice_length,a.max_chain_length=B[a.level].max_chain,a.strstart=0,a.block_start=0,a.lookahead=0,a.insert=0,a.match_length=a.prev_length=hb-1,a.match_available=0,a.ins_h=0}function t(){this.strm=null,this.status=0,this.pending_buf=null,this.pending_buf_size=0,this.pending_out=0,this.pending=0,this.wrap=0,this.gzhead=null,this.gzindex=0,this.method=Y,this.last_flush=-1,this.w_size=0,this.w_bits=0,this.w_mask=0,this.window=null,this.window_size=0,this.prev=null,this.head=null,this.ins_h=0,this.hash_size=0,this.hash_bits=0,this.hash_mask=0,this.hash_shift=0,this.block_start=0,this.match_length=0,this.prev_match=0,this.match_available=0,this.strstart=0,this.match_start=0,this.lookahead=0,this.prev_length=0,this.max_chain_length=0,this.max_lazy_match=0,this.level=0,this.strategy=0,this.good_match=0,this.nice_match=0,this.dyn_ltree=new C.Buf16(2*fb),this.dyn_dtree=new C.Buf16(2*(2*db+1)),this.bl_tree=new C.Buf16(2*(2*eb+1)),f(this.dyn_ltree),f(this.dyn_dtree),f(this.bl_tree),this.l_desc=null,this.d_desc=null,this.bl_desc=null,this.bl_count=new C.Buf16(gb+1),this.heap=new C.Buf16(2*cb+1),f(this.heap),this.heap_len=0,this.heap_max=0,this.depth=new C.Buf16(2*cb+1),f(this.depth),this.l_buf=0,this.lit_bufsize=0,this.last_lit=0,this.d_buf=0,this.opt_len=0,this.static_len=0,this.matches=0,this.insert=0,this.bi_buf=0,this.bi_valid=0}function u(a){var b;return a&&a.state?(a.total_in=a.total_out=0,a.data_type=X,b=a.state,b.pending=0,b.pending_out=0,b.wrap<0&&(b.wrap=-b.wrap),b.status=b.wrap?lb:qb,a.adler=2===b.wrap?0:1,b.last_flush=H,D._tr_init(b),M):d(a,O)}function v(a){var b=u(a);return b===M&&s(a.state),b}function w(a,b){return a&&a.state?2!==a.state.wrap?O:(a.state.gzhead=b,M):O}function x(a,b,c,e,f,g){if(!a)return O;var h=1;if(b===R&&(b=6),0>e?(h=0,e=-e):e>15&&(h=2,e-=16),1>f||f>Z||c!==Y||8>e||e>15||0>b||b>9||0>g||g>V)return d(a,O);8===e&&(e=9);var i=new t;return a.state=i,i.strm=a,i.wrap=h,i.gzhead=null,i.w_bits=e,i.w_size=1<<i.w_bits,i.w_mask=i.w_size-1,i.hash_bits=f+7,i.hash_size=1<<i.hash_bits,i.hash_mask=i.hash_size-1,i.hash_shift=~~((i.hash_bits+hb-1)/hb),i.window=new C.Buf8(2*i.w_size),i.head=new C.Buf16(i.hash_size),i.prev=new C.Buf16(i.w_size),i.lit_bufsize=1<<f+6,i.pending_buf_size=4*i.lit_bufsize,i.pending_buf=new C.Buf8(i.pending_buf_size),i.d_buf=i.lit_bufsize>>1,i.l_buf=3*i.lit_bufsize,i.level=b,i.strategy=g,i.method=c,v(a)}function y(a,b){return x(a,b,Y,$,_,W)}function z(a,b){var c,h,k,l;if(!a||!a.state||b>L||0>b)return a?d(a,O):O;if(h=a.state,!a.output||!a.input&&0!==a.avail_in||h.status===rb&&b!==K)return d(a,0===a.avail_out?Q:O);if(h.strm=a,c=h.last_flush,h.last_flush=b,h.status===lb)if(2===h.wrap)a.adler=0,i(h,31),i(h,139),i(h,8),h.gzhead?(i(h,(h.gzhead.text?1:0)+(h.gzhead.hcrc?2:0)+(h.gzhead.extra?4:0)+(h.gzhead.name?8:0)+(h.gzhead.comment?16:0)),i(h,255&h.gzhead.time),i(h,h.gzhead.time>>8&255),i(h,h.gzhead.time>>16&255),i(h,h.gzhead.time>>24&255),i(h,9===h.level?2:h.strategy>=T||h.level<2?4:0),i(h,255&h.gzhead.os),h.gzhead.extra&&h.gzhead.extra.length&&(i(h,255&h.gzhead.extra.length),i(h,h.gzhead.extra.length>>8&255)),h.gzhead.hcrc&&(a.adler=F(a.adler,h.pending_buf,h.pending,0)),h.gzindex=0,h.status=mb):(i(h,0),i(h,0),i(h,0),i(h,0),i(h,0),i(h,9===h.level?2:h.strategy>=T||h.level<2?4:0),i(h,wb),h.status=qb);else{var m=Y+(h.w_bits-8<<4)<<8,n=-1;n=h.strategy>=T||h.level<2?0:h.level<6?1:6===h.level?2:3,m|=n<<6,0!==h.strstart&&(m|=kb),m+=31-m%31,h.status=qb,j(h,m),0!==h.strstart&&(j(h,a.adler>>>16),j(h,65535&a.adler)),a.adler=1}if(h.status===mb)if(h.gzhead.extra){for(k=h.pending;h.gzindex<(65535&h.gzhead.extra.length)&&(h.pending!==h.pending_buf_size||(h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),g(a),k=h.pending,h.pending!==h.pending_buf_size));)i(h,255&h.gzhead.extra[h.gzindex]),h.gzindex++;h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),h.gzindex===h.gzhead.extra.length&&(h.gzindex=0,h.status=nb)}else h.status=nb;if(h.status===nb)if(h.gzhead.name){k=h.pending;do{if(h.pending===h.pending_buf_size&&(h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),g(a),k=h.pending,h.pending===h.pending_buf_size)){l=1;break}l=h.gzindex<h.gzhead.name.length?255&h.gzhead.name.charCodeAt(h.gzindex++):0,i(h,l)}while(0!==l);h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),0===l&&(h.gzindex=0,h.status=ob)}else h.status=ob;if(h.status===ob)if(h.gzhead.comment){k=h.pending;do{if(h.pending===h.pending_buf_size&&(h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),g(a),k=h.pending,h.pending===h.pending_buf_size)){l=1;break}l=h.gzindex<h.gzhead.comment.length?255&h.gzhead.comment.charCodeAt(h.gzindex++):0,i(h,l)}while(0!==l);h.gzhead.hcrc&&h.pending>k&&(a.adler=F(a.adler,h.pending_buf,h.pending-k,k)),0===l&&(h.status=pb)}else h.status=pb;if(h.status===pb&&(h.gzhead.hcrc?(h.pending+2>h.pending_buf_size&&g(a),h.pending+2<=h.pending_buf_size&&(i(h,255&a.adler),i(h,a.adler>>8&255),a.adler=0,h.status=qb)):h.status=qb),0!==h.pending){if(g(a),0===a.avail_out)return h.last_flush=-1,M}else if(0===a.avail_in&&e(b)<=e(c)&&b!==K)return d(a,Q);if(h.status===rb&&0!==a.avail_in)return d(a,Q);if(0!==a.avail_in||0!==h.lookahead||b!==H&&h.status!==rb){var o=h.strategy===T?r(h,b):h.strategy===U?q(h,b):B[h.level].func(h,b);if((o===ub||o===vb)&&(h.status=rb),o===sb||o===ub)return 0===a.avail_out&&(h.last_flush=-1),M;if(o===tb&&(b===I?D._tr_align(h):b!==L&&(D._tr_stored_block(h,0,0,!1),b===J&&(f(h.head),0===h.lookahead&&(h.strstart=0,h.block_start=0,h.insert=0))),g(a),0===a.avail_out))return h.last_flush=-1,M}return b!==K?M:h.wrap<=0?N:(2===h.wrap?(i(h,255&a.adler),i(h,a.adler>>8&255),i(h,a.adler>>16&255),i(h,a.adler>>24&255),i(h,255&a.total_in),i(h,a.total_in>>8&255),i(h,a.total_in>>16&255),i(h,a.total_in>>24&255)):(j(h,a.adler>>>16),j(h,65535&a.adler)),g(a),h.wrap>0&&(h.wrap=-h.wrap),0!==h.pending?M:N)}function A(a){var b;return a&&a.state?(b=a.state.status,b!==lb&&b!==mb&&b!==nb&&b!==ob&&b!==pb&&b!==qb&&b!==rb?d(a,O):(a.state=null,b===qb?d(a,P):M)):O}var B,C=a(\"../utils/common\"),D=a(\"./trees\"),E=a(\"./adler32\"),F=a(\"./crc32\"),G=a(\"./messages\"),H=0,I=1,J=3,K=4,L=5,M=0,N=1,O=-2,P=-3,Q=-5,R=-1,S=1,T=2,U=3,V=4,W=0,X=2,Y=8,Z=9,$=15,_=8,ab=29,bb=256,cb=bb+1+ab,db=30,eb=19,fb=2*cb+1,gb=15,hb=3,ib=258,jb=ib+hb+1,kb=32,lb=42,mb=69,nb=73,ob=91,pb=103,qb=113,rb=666,sb=1,tb=2,ub=3,vb=4,wb=3,xb=function(a,b,c,d,e){this.good_length=a,this.max_lazy=b,this.nice_length=c,this.max_chain=d,this.func=e};B=[new xb(0,0,0,0,n),new xb(4,4,8,4,o),new xb(4,5,16,8,o),new xb(4,6,32,32,o),new xb(4,4,16,16,p),new xb(8,16,32,32,p),new xb(8,16,128,128,p),new xb(8,32,128,256,p),new xb(32,128,258,1024,p),new xb(32,258,258,4096,p)],c.deflateInit=y,c.deflateInit2=x,c.deflateReset=v,c.deflateResetKeep=u,c.deflateSetHeader=w,c.deflate=z,c.deflateEnd=A,c.deflateInfo=\"pako deflate (from Nodeca project)\"},{\"../utils/common\":27,\"./adler32\":29,\"./crc32\":31,\"./messages\":37,\"./trees\":38}],33:[function(a,b){\"use strict\";function c(){this.text=0,this.time=0,this.xflags=0,this.os=0,this.extra=null,this.extra_len=0,this.name=\"\",this.comment=\"\",this.hcrc=0,this.done=!1}b.exports=c},{}],34:[function(a,b){\"use strict\";var c=30,d=12;b.exports=function(a,b){var e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x,y,z,A,B,C;e=a.state,f=a.next_in,B=a.input,g=f+(a.avail_in-5),h=a.next_out,C=a.output,i=h-(b-a.avail_out),j=h+(a.avail_out-257),k=e.dmax,l=e.wsize,m=e.whave,n=e.wnext,o=e.window,p=e.hold,q=e.bits,r=e.lencode,s=e.distcode,t=(1<<e.lenbits)-1,u=(1<<e.distbits)-1;a:do{15>q&&(p+=B[f++]<<q,q+=8,p+=B[f++]<<q,q+=8),v=r[p&t];b:for(;;){if(w=v>>>24,p>>>=w,q-=w,w=v>>>16&255,0===w)C[h++]=65535&v;else{if(!(16&w)){if(0===(64&w)){v=r[(65535&v)+(p&(1<<w)-1)];continue b}if(32&w){e.mode=d;break a}a.msg=\"invalid literal/length code\",e.mode=c;break a}x=65535&v,w&=15,w&&(w>q&&(p+=B[f++]<<q,q+=8),x+=p&(1<<w)-1,p>>>=w,q-=w),15>q&&(p+=B[f++]<<q,q+=8,p+=B[f++]<<q,q+=8),v=s[p&u];c:for(;;){if(w=v>>>24,p>>>=w,q-=w,w=v>>>16&255,!(16&w)){if(0===(64&w)){v=s[(65535&v)+(p&(1<<w)-1)];continue c}a.msg=\"invalid distance code\",e.mode=c;break a}if(y=65535&v,w&=15,w>q&&(p+=B[f++]<<q,q+=8,w>q&&(p+=B[f++]<<q,q+=8)),y+=p&(1<<w)-1,y>k){a.msg=\"invalid distance too far 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e(){this.mode=0,this.last=!1,this.wrap=0,this.havedict=!1,this.flags=0,this.dmax=0,this.check=0,this.total=0,this.head=null,this.wbits=0,this.wsize=0,this.whave=0,this.wnext=0,this.window=null,this.hold=0,this.bits=0,this.length=0,this.offset=0,this.extra=0,this.lencode=null,this.distcode=null,this.lenbits=0,this.distbits=0,this.ncode=0,this.nlen=0,this.ndist=0,this.have=0,this.next=null,this.lens=new r.Buf16(320),this.work=new r.Buf16(288),this.lendyn=null,this.distdyn=null,this.sane=0,this.back=0,this.was=0}function f(a){var b;return a&&a.state?(b=a.state,a.total_in=a.total_out=b.total=0,a.msg=\"\",b.wrap&&(a.adler=1&b.wrap),b.mode=K,b.last=0,b.havedict=0,b.dmax=32768,b.head=null,b.hold=0,b.bits=0,b.lencode=b.lendyn=new r.Buf32(ob),b.distcode=b.distdyn=new r.Buf32(pb),b.sane=1,b.back=-1,C):F}function g(a){var b;return a&&a.state?(b=a.state,b.wsize=0,b.whave=0,b.wnext=0,f(a)):F}function h(a,b){var c,d;return a&&a.state?(d=a.state,0>b?(c=0,b=-b):(c=(b>>4)+1,48>b&&(b&=15)),b&&(8>b||b>15)?F:(null!==d.window&&d.wbits!==b&&(d.window=null),d.wrap=c,d.wbits=b,g(a))):F}function i(a,b){var c,d;return a?(d=new e,a.state=d,d.window=null,c=h(a,b),c!==C&&(a.state=null),c):F}function j(a){return i(a,rb)}function k(a){if(sb){var b;for(p=new r.Buf32(512),q=new r.Buf32(32),b=0;144>b;)a.lens[b++]=8;for(;256>b;)a.lens[b++]=9;for(;280>b;)a.lens[b++]=7;for(;288>b;)a.lens[b++]=8;for(v(x,a.lens,0,288,p,0,a.work,{bits:9}),b=0;32>b;)a.lens[b++]=5;v(y,a.lens,0,32,q,0,a.work,{bits:5}),sb=!1}a.lencode=p,a.lenbits=9,a.distcode=q,a.distbits=5}function l(a,b,c,d){var e,f=a.state;return null===f.window&&(f.wsize=1<<f.wbits,f.wnext=0,f.whave=0,f.window=new r.Buf8(f.wsize)),d>=f.wsize?(r.arraySet(f.window,b,c-f.wsize,f.wsize,0),f.wnext=0,f.whave=f.wsize):(e=f.wsize-f.wnext,e>d&&(e=d),r.arraySet(f.window,b,c-d,e,f.wnext),d-=e,d?(r.arraySet(f.window,b,c-d,d,0),f.wnext=d,f.whave=f.wsize):(f.wnext+=e,f.wnext===f.wsize&&(f.wnext=0),f.whave<f.wsize&&(f.whave+=e))),0}function m(a,b){var c,e,f,g,h,i,j,m,n,o,p,q,ob,pb,qb,rb,sb,tb,ub,vb,wb,xb,yb,zb,Ab=0,Bb=new r.Buf8(4),Cb=[16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15];if(!a||!a.state||!a.output||!a.input&&0!==a.avail_in)return F;c=a.state,c.mode===V&&(c.mode=W),h=a.next_out,f=a.output,j=a.avail_out,g=a.next_in,e=a.input,i=a.avail_in,m=c.hold,n=c.bits,o=i,p=j,xb=C;a:for(;;)switch(c.mode){case K:if(0===c.wrap){c.mode=W;break}for(;16>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(2&c.wrap&&35615===m){c.check=0,Bb[0]=255&m,Bb[1]=m>>>8&255,c.check=t(c.check,Bb,2,0),m=0,n=0,c.mode=L;break}if(c.flags=0,c.head&&(c.head.done=!1),!(1&c.wrap)||(((255&m)<<8)+(m>>8))%31){a.msg=\"incorrect header check\",c.mode=lb;break}if((15&m)!==J){a.msg=\"unknown compression method\",c.mode=lb;break}if(m>>>=4,n-=4,wb=(15&m)+8,0===c.wbits)c.wbits=wb;else if(wb>c.wbits){a.msg=\"invalid window size\",c.mode=lb;break}c.dmax=1<<wb,a.adler=c.check=1,c.mode=512&m?T:V,m=0,n=0;break;case L:for(;16>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(c.flags=m,(255&c.flags)!==J){a.msg=\"unknown compression method\",c.mode=lb;break}if(57344&c.flags){a.msg=\"unknown header flags set\",c.mode=lb;break}c.head&&(c.head.text=m>>8&1),512&c.flags&&(Bb[0]=255&m,Bb[1]=m>>>8&255,c.check=t(c.check,Bb,2,0)),m=0,n=0,c.mode=M;case M:for(;32>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.head&&(c.head.time=m),512&c.flags&&(Bb[0]=255&m,Bb[1]=m>>>8&255,Bb[2]=m>>>16&255,Bb[3]=m>>>24&255,c.check=t(c.check,Bb,4,0)),m=0,n=0,c.mode=N;case N:for(;16>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.head&&(c.head.xflags=255&m,c.head.os=m>>8),512&c.flags&&(Bb[0]=255&m,Bb[1]=m>>>8&255,c.check=t(c.check,Bb,2,0)),m=0,n=0,c.mode=O;case O:if(1024&c.flags){for(;16>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.length=m,c.head&&(c.head.extra_len=m),512&c.flags&&(Bb[0]=255&m,Bb[1]=m>>>8&255,c.check=t(c.check,Bb,2,0)),m=0,n=0}else c.head&&(c.head.extra=null);c.mode=P;case P:if(1024&c.flags&&(q=c.length,q>i&&(q=i),q&&(c.head&&(wb=c.head.extra_len-c.length,c.head.extra||(c.head.extra=new Array(c.head.extra_len)),r.arraySet(c.head.extra,e,g,q,wb)),512&c.flags&&(c.check=t(c.check,e,q,g)),i-=q,g+=q,c.length-=q),c.length))break a;c.length=0,c.mode=Q;case Q:if(2048&c.flags){if(0===i)break a;q=0;do wb=e[g+q++],c.head&&wb&&c.length<65536&&(c.head.name+=String.fromCharCode(wb));while(wb&&i>q);if(512&c.flags&&(c.check=t(c.check,e,q,g)),i-=q,g+=q,wb)break a}else c.head&&(c.head.name=null);c.length=0,c.mode=R;case R:if(4096&c.flags){if(0===i)break a;q=0;do wb=e[g+q++],c.head&&wb&&c.length<65536&&(c.head.comment+=String.fromCharCode(wb));while(wb&&i>q);if(512&c.flags&&(c.check=t(c.check,e,q,g)),i-=q,g+=q,wb)break a}else c.head&&(c.head.comment=null);c.mode=S;case S:if(512&c.flags){for(;16>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(m!==(65535&c.check)){a.msg=\"header crc mismatch\",c.mode=lb;break}m=0,n=0}c.head&&(c.head.hcrc=c.flags>>9&1,c.head.done=!0),a.adler=c.check=0,c.mode=V;break;case T:for(;32>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}a.adler=c.check=d(m),m=0,n=0,c.mode=U;case U:if(0===c.havedict)return a.next_out=h,a.avail_out=j,a.next_in=g,a.avail_in=i,c.hold=m,c.bits=n,E;a.adler=c.check=1,c.mode=V;case V:if(b===A||b===B)break a;case W:if(c.last){m>>>=7&n,n-=7&n,c.mode=ib;break}for(;3>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}switch(c.last=1&m,m>>>=1,n-=1,3&m){case 0:c.mode=X;break;case 1:if(k(c),c.mode=bb,b===B){m>>>=2,n-=2;break a}break;case 2:c.mode=$;break;case 3:a.msg=\"invalid block type\",c.mode=lb}m>>>=2,n-=2;break;case X:for(m>>>=7&n,n-=7&n;32>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if((65535&m)!==(m>>>16^65535)){a.msg=\"invalid stored block lengths\",c.mode=lb;break}if(c.length=65535&m,m=0,n=0,c.mode=Y,b===B)break a;case Y:c.mode=Z;case Z:if(q=c.length){if(q>i&&(q=i),q>j&&(q=j),0===q)break a;r.arraySet(f,e,g,q,h),i-=q,g+=q,j-=q,h+=q,c.length-=q;break}c.mode=V;break;case $:for(;14>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(c.nlen=(31&m)+257,m>>>=5,n-=5,c.ndist=(31&m)+1,m>>>=5,n-=5,c.ncode=(15&m)+4,m>>>=4,n-=4,c.nlen>286||c.ndist>30){a.msg=\"too many length or distance symbols\",c.mode=lb;break}c.have=0,c.mode=_;case _:for(;c.have<c.ncode;){for(;3>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.lens[Cb[c.have++]]=7&m,m>>>=3,n-=3}for(;c.have<19;)c.lens[Cb[c.have++]]=0;if(c.lencode=c.lendyn,c.lenbits=7,yb={bits:c.lenbits},xb=v(w,c.lens,0,19,c.lencode,0,c.work,yb),c.lenbits=yb.bits,xb){a.msg=\"invalid code lengths set\",c.mode=lb;break}c.have=0,c.mode=ab;case ab:for(;c.have<c.nlen+c.ndist;){for(;Ab=c.lencode[m&(1<<c.lenbits)-1],qb=Ab>>>24,rb=Ab>>>16&255,sb=65535&Ab,!(n>=qb);){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(16>sb)m>>>=qb,n-=qb,c.lens[c.have++]=sb;else{if(16===sb){for(zb=qb+2;zb>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(m>>>=qb,n-=qb,0===c.have){a.msg=\"invalid bit length repeat\",c.mode=lb;break}wb=c.lens[c.have-1],q=3+(3&m),m>>>=2,n-=2}else if(17===sb){for(zb=qb+3;zb>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}m>>>=qb,n-=qb,wb=0,q=3+(7&m),m>>>=3,n-=3}else{for(zb=qb+7;zb>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}m>>>=qb,n-=qb,wb=0,q=11+(127&m),m>>>=7,n-=7}if(c.have+q>c.nlen+c.ndist){a.msg=\"invalid bit length repeat\",c.mode=lb;break}for(;q--;)c.lens[c.have++]=wb}}if(c.mode===lb)break;if(0===c.lens[256]){a.msg=\"invalid code -- missing end-of-block\",c.mode=lb;break}if(c.lenbits=9,yb={bits:c.lenbits},xb=v(x,c.lens,0,c.nlen,c.lencode,0,c.work,yb),c.lenbits=yb.bits,xb){a.msg=\"invalid literal/lengths set\",c.mode=lb;break}if(c.distbits=6,c.distcode=c.distdyn,yb={bits:c.distbits},xb=v(y,c.lens,c.nlen,c.ndist,c.distcode,0,c.work,yb),c.distbits=yb.bits,xb){a.msg=\"invalid distances set\",c.mode=lb;break}if(c.mode=bb,b===B)break a;case bb:c.mode=cb;case cb:if(i>=6&&j>=258){a.next_out=h,a.avail_out=j,a.next_in=g,a.avail_in=i,c.hold=m,c.bits=n,u(a,p),h=a.next_out,f=a.output,j=a.avail_out,g=a.next_in,e=a.input,i=a.avail_in,m=c.hold,n=c.bits,c.mode===V&&(c.back=-1);\nbreak}for(c.back=0;Ab=c.lencode[m&(1<<c.lenbits)-1],qb=Ab>>>24,rb=Ab>>>16&255,sb=65535&Ab,!(n>=qb);){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(rb&&0===(240&rb)){for(tb=qb,ub=rb,vb=sb;Ab=c.lencode[vb+((m&(1<<tb+ub)-1)>>tb)],qb=Ab>>>24,rb=Ab>>>16&255,sb=65535&Ab,!(n>=tb+qb);){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}m>>>=tb,n-=tb,c.back+=tb}if(m>>>=qb,n-=qb,c.back+=qb,c.length=sb,0===rb){c.mode=hb;break}if(32&rb){c.back=-1,c.mode=V;break}if(64&rb){a.msg=\"invalid literal/length code\",c.mode=lb;break}c.extra=15&rb,c.mode=db;case db:if(c.extra){for(zb=c.extra;zb>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.length+=m&(1<<c.extra)-1,m>>>=c.extra,n-=c.extra,c.back+=c.extra}c.was=c.length,c.mode=eb;case eb:for(;Ab=c.distcode[m&(1<<c.distbits)-1],qb=Ab>>>24,rb=Ab>>>16&255,sb=65535&Ab,!(n>=qb);){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(0===(240&rb)){for(tb=qb,ub=rb,vb=sb;Ab=c.distcode[vb+((m&(1<<tb+ub)-1)>>tb)],qb=Ab>>>24,rb=Ab>>>16&255,sb=65535&Ab,!(n>=tb+qb);){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}m>>>=tb,n-=tb,c.back+=tb}if(m>>>=qb,n-=qb,c.back+=qb,64&rb){a.msg=\"invalid distance code\",c.mode=lb;break}c.offset=sb,c.extra=15&rb,c.mode=fb;case fb:if(c.extra){for(zb=c.extra;zb>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}c.offset+=m&(1<<c.extra)-1,m>>>=c.extra,n-=c.extra,c.back+=c.extra}if(c.offset>c.dmax){a.msg=\"invalid distance too far back\",c.mode=lb;break}c.mode=gb;case gb:if(0===j)break a;if(q=p-j,c.offset>q){if(q=c.offset-q,q>c.whave&&c.sane){a.msg=\"invalid distance too far back\",c.mode=lb;break}q>c.wnext?(q-=c.wnext,ob=c.wsize-q):ob=c.wnext-q,q>c.length&&(q=c.length),pb=c.window}else pb=f,ob=h-c.offset,q=c.length;q>j&&(q=j),j-=q,c.length-=q;do f[h++]=pb[ob++];while(--q);0===c.length&&(c.mode=cb);break;case hb:if(0===j)break a;f[h++]=c.length,j--,c.mode=cb;break;case ib:if(c.wrap){for(;32>n;){if(0===i)break a;i--,m|=e[g++]<<n,n+=8}if(p-=j,a.total_out+=p,c.total+=p,p&&(a.adler=c.check=c.flags?t(c.check,f,p,h-p):s(c.check,f,p,h-p)),p=j,(c.flags?m:d(m))!==c.check){a.msg=\"incorrect data check\",c.mode=lb;break}m=0,n=0}c.mode=jb;case jb:if(c.wrap&&c.flags){for(;32>n;){if(0===i)break a;i--,m+=e[g++]<<n,n+=8}if(m!==(4294967295&c.total)){a.msg=\"incorrect length check\",c.mode=lb;break}m=0,n=0}c.mode=kb;case kb:xb=D;break a;case lb:xb=G;break a;case mb:return H;case nb:default:return F}return a.next_out=h,a.avail_out=j,a.next_in=g,a.avail_in=i,c.hold=m,c.bits=n,(c.wsize||p!==a.avail_out&&c.mode<lb&&(c.mode<ib||b!==z))&&l(a,a.output,a.next_out,p-a.avail_out)?(c.mode=mb,H):(o-=a.avail_in,p-=a.avail_out,a.total_in+=o,a.total_out+=p,c.total+=p,c.wrap&&p&&(a.adler=c.check=c.flags?t(c.check,f,p,a.next_out-p):s(c.check,f,p,a.next_out-p)),a.data_type=c.bits+(c.last?64:0)+(c.mode===V?128:0)+(c.mode===bb||c.mode===Y?256:0),(0===o&&0===p||b===z)&&xb===C&&(xb=I),xb)}function n(a){if(!a||!a.state)return F;var b=a.state;return b.window&&(b.window=null),a.state=null,C}function o(a,b){var c;return a&&a.state?(c=a.state,0===(2&c.wrap)?F:(c.head=b,b.done=!1,C)):F}var p,q,r=a(\"../utils/common\"),s=a(\"./adler32\"),t=a(\"./crc32\"),u=a(\"./inffast\"),v=a(\"./inftrees\"),w=0,x=1,y=2,z=4,A=5,B=6,C=0,D=1,E=2,F=-2,G=-3,H=-4,I=-5,J=8,K=1,L=2,M=3,N=4,O=5,P=6,Q=7,R=8,S=9,T=10,U=11,V=12,W=13,X=14,Y=15,Z=16,$=17,_=18,ab=19,bb=20,cb=21,db=22,eb=23,fb=24,gb=25,hb=26,ib=27,jb=28,kb=29,lb=30,mb=31,nb=32,ob=852,pb=592,qb=15,rb=qb,sb=!0;c.inflateReset=g,c.inflateReset2=h,c.inflateResetKeep=f,c.inflateInit=j,c.inflateInit2=i,c.inflate=m,c.inflateEnd=n,c.inflateGetHeader=o,c.inflateInfo=\"pako inflate (from Nodeca project)\"},{\"../utils/common\":27,\"./adler32\":29,\"./crc32\":31,\"./inffast\":34,\"./inftrees\":36}],36:[function(a,b){\"use strict\";var 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error\",\"-2\":\"stream error\",\"-3\":\"data error\",\"-4\":\"insufficient memory\",\"-5\":\"buffer error\",\"-6\":\"incompatible version\"}},{}],38:[function(a,b,c){\"use strict\";function d(a){for(var b=a.length;--b>=0;)a[b]=0}function e(a){return 256>a?gb[a]:gb[256+(a>>>7)]}function f(a,b){a.pending_buf[a.pending++]=255&b,a.pending_buf[a.pending++]=b>>>8&255}function g(a,b,c){a.bi_valid>V-c?(a.bi_buf|=b<<a.bi_valid&65535,f(a,a.bi_buf),a.bi_buf=b>>V-a.bi_valid,a.bi_valid+=c-V):(a.bi_buf|=b<<a.bi_valid&65535,a.bi_valid+=c)}function h(a,b,c){g(a,c[2*b],c[2*b+1])}function i(a,b){var c=0;do c|=1&a,a>>>=1,c<<=1;while(--b>0);return c>>>1}function j(a){16===a.bi_valid?(f(a,a.bi_buf),a.bi_buf=0,a.bi_valid=0):a.bi_valid>=8&&(a.pending_buf[a.pending++]=255&a.bi_buf,a.bi_buf>>=8,a.bi_valid-=8)}function k(a,b){var c,d,e,f,g,h,i=b.dyn_tree,j=b.max_code,k=b.stat_desc.static_tree,l=b.stat_desc.has_stree,m=b.stat_desc.extra_bits,n=b.stat_desc.extra_base,o=b.stat_desc.max_length,p=0;for(f=0;U>=f;f++)a.bl_count[f]=0;for(i[2*a.heap[a.heap_max]+1]=0,c=a.heap_max+1;T>c;c++)d=a.heap[c],f=i[2*i[2*d+1]+1]+1,f>o&&(f=o,p++),i[2*d+1]=f,d>j||(a.bl_count[f]++,g=0,d>=n&&(g=m[d-n]),h=i[2*d],a.opt_len+=h*(f+g),l&&(a.static_len+=h*(k[2*d+1]+g)));if(0!==p){do{for(f=o-1;0===a.bl_count[f];)f--;a.bl_count[f]--,a.bl_count[f+1]+=2,a.bl_count[o]--,p-=2}while(p>0);for(f=o;0!==f;f--)for(d=a.bl_count[f];0!==d;)e=a.heap[--c],e>j||(i[2*e+1]!==f&&(a.opt_len+=(f-i[2*e+1])*i[2*e],i[2*e+1]=f),d--)}}function l(a,b,c){var d,e,f=new Array(U+1),g=0;for(d=1;U>=d;d++)f[d]=g=g+c[d-1]<<1;for(e=0;b>=e;e++){var h=a[2*e+1];0!==h&&(a[2*e]=i(f[h]++,h))}}function m(){var a,b,c,d,e,f=new 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            "type": "application/javascript",
            "title": "$:/plugins/tiddlywiki/jszip/jszip.js",
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            "text": "JSZip is dual licensed. You may use it under the MIT license *or* the GPLv3\nlicense.\n\nThe MIT License\n===============\n\nCopyright (c) 2009-2014 Stuart Knightley, David Duponchel, Franz Buchinger, António Afonso\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in\nall copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\nTHE SOFTWARE.\n\n\nGPL version 3\n=============\n\n                    GNU GENERAL PUBLIC LICENSE\n                       Version 3, 29 June 2007\n\n Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>\n Everyone is permitted to copy and distribute verbatim copies\n of this license document, but changing it is not allowed.\n\n                            Preamble\n\n  The GNU General Public License is a free, copyleft license for\nsoftware and other kinds of works.\n\n  The licenses for most software and other practical works are designed\nto take away your freedom to share and change the works.  By contrast,\nthe GNU General Public License is intended to guarantee your freedom to\nshare and change all versions of a program--to make sure it remains free\nsoftware for all its users.  We, the Free Software Foundation, use the\nGNU General Public License for most of our software; it applies also to\nany other work released this way by its authors.  You can apply it to\nyour programs, too.\n\n  When we speak of free software, we are referring to freedom, not\nprice.  Our General Public Licenses are designed to make sure that you\nhave the freedom to distribute copies of free software (and charge for\nthem if you wish), that you receive source code or can get it if you\nwant it, that you can change the software or use pieces of it in new\nfree programs, and that you know you can do these things.\n\n  To protect your rights, we need to prevent others from denying you\nthese rights or asking you to surrender the rights.  Therefore, you have\ncertain responsibilities if you distribute copies of the software, or if\nyou modify it: responsibilities to respect the freedom of others.\n\n  For example, if you distribute copies of such a program, whether\ngratis or for a fee, you must pass on to the recipients the same\nfreedoms that you received.  You must make sure that they, too, receive\nor can get the source code.  And you must show them these terms so they\nknow their rights.\n\n  Developers that use the GNU GPL protect your rights with two steps:\n(1) assert copyright on the software, and (2) offer you this License\ngiving you legal permission to copy, distribute and/or modify it.\n\n  For the developers' and authors' protection, the GPL clearly explains\nthat there is no warranty for this free software.  For both users' and\nauthors' sake, the GPL requires that modified versions be marked as\nchanged, so that their problems will not be attributed erroneously to\nauthors of previous versions.\n\n  Some devices are designed to deny users access to install or run\nmodified versions of the software inside them, although the manufacturer\ncan do so.  This is fundamentally incompatible with the aim of\nprotecting users' freedom to change the software.  The systematic\npattern of such abuse occurs in the area of products for individuals to\nuse, which is precisely where it is most unacceptable.  Therefore, we\nhave designed this version of the GPL to prohibit the practice for those\nproducts.  If such problems arise substantially in other domains, we\nstand ready to extend this provision to those domains in future versions\nof the GPL, as needed to protect the freedom of users.\n\n  Finally, every program is threatened constantly by software patents.\nStates should not allow patents to restrict development and use of\nsoftware on general-purpose computers, but in those that do, we wish to\navoid the special danger that patents applied to a free program could\nmake it effectively proprietary.  To prevent this, the GPL assures that\npatents cannot be used to render the program non-free.\n\n  The precise terms and conditions for copying, distribution and\nmodification follow.\n\n                       TERMS AND CONDITIONS\n\n  0. Definitions.\n\n  \"This License\" refers to version 3 of the GNU General Public License.\n\n  \"Copyright\" also means copyright-like laws that apply to other kinds of\nworks, such as semiconductor masks.\n\n  \"The Program\" refers to any copyrightable work licensed under this\nLicense.  Each licensee is addressed as \"you\".  \"Licensees\" and\n\"recipients\" may be individuals or organizations.\n\n  To \"modify\" a work means to copy from or adapt all or part of the work\nin a fashion requiring copyright permission, other than the making of an\nexact copy.  The resulting work is called a \"modified version\" of the\nearlier work or a work \"based on\" the earlier work.\n\n  A \"covered work\" means either the unmodified Program or a work based\non the Program.\n\n  To \"propagate\" a work means to do anything with it that, without\npermission, would make you directly or secondarily liable for\ninfringement under applicable copyright law, except executing it on a\ncomputer or modifying a private copy.  Propagation includes copying,\ndistribution (with or without modification), making available to the\npublic, and in some countries other activities as well.\n\n  To \"convey\" a work means any kind of propagation that enables other\nparties to make or receive copies.  Mere interaction with a user through\na computer network, with no transfer of a copy, is not conveying.\n\n  An interactive user interface displays \"Appropriate Legal Notices\"\nto the extent that it includes a convenient and prominently visible\nfeature that (1) displays an appropriate copyright notice, and (2)\ntells the user that there is no warranty for the work (except to the\nextent that warranties are provided), that licensees may convey the\nwork under this License, and how to view a copy of this License.  If\nthe interface presents a list of user commands or options, such as a\nmenu, a prominent item in the list meets this criterion.\n\n  1. Source Code.\n\n  The \"source code\" for a work means the preferred form of the work\nfor making modifications to it.  \"Object code\" means any non-source\nform of a work.\n\n  A \"Standard Interface\" means an interface that either is an official\nstandard defined by a recognized standards body, or, in the case of\ninterfaces specified for a particular programming language, one that\nis widely used among developers working in that language.\n\n  The \"System Libraries\" of an executable work include anything, other\nthan the work as a whole, that (a) is included in the normal form of\npackaging a Major Component, but which is not part of that Major\nComponent, and (b) serves only to enable use of the work with that\nMajor Component, or to implement a Standard Interface for which an\nimplementation is available to the public in source code form.  A\n\"Major Component\", in this context, means a major essential component\n(kernel, window system, and so on) of the specific operating system\n(if any) on which the executable work runs, or a compiler used to\nproduce the work, or an object code interpreter used to run it.\n\n  The \"Corresponding Source\" for a work in object code form means all\nthe source code needed to generate, install, and (for an executable\nwork) run the object code and to modify the work, including scripts to\ncontrol those activities.  However, it does not include the work's\nSystem Libraries, or general-purpose tools or generally available free\nprograms which are used unmodified in performing those activities but\nwhich are not part of the work.  For example, Corresponding Source\nincludes interface definition files associated with source files for\nthe work, and the source code for shared libraries and dynamically\nlinked subprograms that the work is specifically designed to require,\nsuch as by intimate data communication or control flow between those\nsubprograms and other parts of the work.\n\n  The Corresponding Source need not include anything that users\ncan regenerate automatically from other parts of the Corresponding\nSource.\n\n  The Corresponding Source for a work in source code form is that\nsame work.\n\n  2. Basic Permissions.\n\n  All rights granted under this License are granted for the term of\ncopyright on the Program, and are irrevocable provided the stated\nconditions are met.  This License explicitly affirms your unlimited\npermission to run the unmodified Program.  The output from running a\ncovered work is covered by this License only if the output, given its\ncontent, constitutes a covered work.  This License acknowledges your\nrights of fair use or other equivalent, as provided by copyright law.\n\n  You may make, run and propagate covered works that you do not\nconvey, without conditions so long as your license otherwise remains\nin force.  You may convey covered works to others for the sole purpose\nof having them make modifications exclusively for you, or provide you\nwith facilities for running those works, provided that you comply with\nthe terms of this License in conveying all material for which you do\nnot control copyright.  Those thus making or running the covered works\nfor you must do so exclusively on your behalf, under your direction\nand control, on terms that prohibit them from making any copies of\nyour copyrighted material outside their relationship with you.\n\n  Conveying under any other circumstances is permitted solely under\nthe conditions stated below.  Sublicensing is not allowed; section 10\nmakes it unnecessary.\n\n  3. Protecting Users' Legal Rights From Anti-Circumvention Law.\n\n  No covered work shall be deemed part of an effective technological\nmeasure under any applicable law fulfilling obligations under article\n11 of the WIPO copyright treaty adopted on 20 December 1996, or\nsimilar laws prohibiting or restricting circumvention of such\nmeasures.\n\n  When you convey a covered work, you waive any legal power to forbid\ncircumvention of technological measures to the extent such circumvention\nis effected by exercising rights under this License with respect to\nthe covered work, and you disclaim any intention to limit operation or\nmodification of the work as a means of enforcing, against the work's\nusers, your or third parties' legal rights to forbid circumvention of\ntechnological measures.\n\n  4. Conveying Verbatim Copies.\n\n  You may convey verbatim copies of the Program's source code as you\nreceive it, in any medium, provided that you conspicuously and\nappropriately publish on each copy an appropriate copyright notice;\nkeep intact all notices stating that this License and any\nnon-permissive terms added in accord with section 7 apply to the code;\nkeep intact all notices of the absence of any warranty; and give all\nrecipients a copy of this License along with the Program.\n\n  You may charge any price or no price for each copy that you convey,\nand you may offer support or warranty protection for a fee.\n\n  5. Conveying Modified Source Versions.\n\n  You may convey a work based on the Program, or the modifications to\nproduce it from the Program, in the form of source code under the\nterms of section 4, provided that you also meet all of these conditions:\n\n    a) The work must carry prominent notices stating that you modified\n    it, and giving a relevant date.\n\n    b) The work must carry prominent notices stating that it is\n    released under this License and any conditions added under section\n    7.  This requirement modifies the requirement in section 4 to\n    \"keep intact all notices\".\n\n    c) You must license the entire work, as a whole, under this\n    License to anyone who comes into possession of a copy.  This\n    License will therefore apply, along with any applicable section 7\n    additional terms, to the whole of the work, and all its parts,\n    regardless of how they are packaged.  This License gives no\n    permission to license the work in any other way, but it does not\n    invalidate such permission if you have separately received it.\n\n    d) If the work has interactive user interfaces, each must display\n    Appropriate Legal Notices; however, if the Program has interactive\n    interfaces that do not display Appropriate Legal Notices, your\n    work need not make them do so.\n\n  A compilation of a covered work with other separate and independent\nworks, which are not by their nature extensions of the covered work,\nand which are not combined with it such as to form a larger program,\nin or on a volume of a storage or distribution medium, is called an\n\"aggregate\" if the compilation and its resulting copyright are not\nused to limit the access or legal rights of the compilation's users\nbeyond what the individual works permit.  Inclusion of a covered work\nin an aggregate does not cause this License to apply to the other\nparts of the aggregate.\n\n  6. Conveying Non-Source Forms.\n\n  You may convey a covered work in object code form under the terms\nof sections 4 and 5, provided that you also convey the\nmachine-readable Corresponding Source under the terms of this License,\nin one of these ways:\n\n    a) Convey the object code in, or embodied in, a physical product\n    (including a physical distribution medium), accompanied by the\n    Corresponding Source fixed on a durable physical medium\n    customarily used for software interchange.\n\n    b) Convey the object code in, or embodied in, a physical product\n    (including a physical distribution medium), accompanied by a\n    written offer, valid for at least three years and valid for as\n    long as you offer spare parts or customer support for that product\n    model, to give anyone who possesses the object code either (1) a\n    copy of the Corresponding Source for all the software in the\n    product that is covered by this License, on a durable physical\n    medium customarily used for software interchange, for a price no\n    more than your reasonable cost of physically performing this\n    conveying of source, or (2) access to copy the\n    Corresponding Source from a network server at no charge.\n\n    c) Convey individual copies of the object code with a copy of the\n    written offer to provide the Corresponding Source.  This\n    alternative is allowed only occasionally and noncommercially, and\n    only if you received the object code with such an offer, in accord\n    with subsection 6b.\n\n    d) Convey the object code by offering access from a designated\n    place (gratis or for a charge), and offer equivalent access to the\n    Corresponding Source in the same way through the same place at no\n    further charge.  You need not require recipients to copy the\n    Corresponding Source along with the object code.  If the place to\n    copy the object code is a network server, the Corresponding Source\n    may be on a different server (operated by you or a third party)\n    that supports equivalent copying facilities, provided you maintain\n    clear directions next to the object code saying where to find the\n    Corresponding Source.  Regardless of what server hosts the\n    Corresponding Source, you remain obligated to ensure that it is\n    available for as long as needed to satisfy these requirements.\n\n    e) Convey the object code using peer-to-peer transmission, provided\n    you inform other peers where the object code and Corresponding\n    Source of the work are being offered to the general public at no\n    charge under subsection 6d.\n\n  A separable portion of the object code, whose source code is excluded\nfrom the Corresponding Source as a System Library, need not be\nincluded in conveying the object code work.\n\n  A \"User Product\" is either (1) a \"consumer product\", which means any\ntangible personal property which is normally used for personal, family,\nor household purposes, or (2) anything designed or sold for incorporation\ninto a dwelling.  In determining whether a product is a consumer product,\ndoubtful cases shall be resolved in favor of coverage.  For a particular\nproduct received by a particular user, \"normally used\" refers to a\ntypical or common use of that class of product, regardless of the status\nof the particular user or of the way in which the particular user\nactually uses, or expects or is expected to use, the product.  A product\nis a consumer product regardless of whether the product has substantial\ncommercial, industrial or non-consumer uses, unless such uses represent\nthe only significant mode of use of the product.\n\n  \"Installation Information\" for a User Product means any methods,\nprocedures, authorization keys, or other information required to install\nand execute modified versions of a covered work in that User Product from\na modified version of its Corresponding Source.  The information must\nsuffice to ensure that the continued functioning of the modified object\ncode is in no case prevented or interfered with solely because\nmodification has been made.\n\n  If you convey an object code work under this section in, or with, or\nspecifically for use in, a User Product, and the conveying occurs as\npart of a transaction in which the right of possession and use of the\nUser Product is transferred to the recipient in perpetuity or for a\nfixed term (regardless of how the transaction is characterized), the\nCorresponding Source conveyed under this section must be accompanied\nby the Installation Information.  But this requirement does not apply\nif neither you nor any third party retains the ability to install\nmodified object code on the User Product (for example, the work has\nbeen installed in ROM).\n\n  The requirement to provide Installation Information does not include a\nrequirement to continue to provide support service, warranty, or updates\nfor a work that has been modified or installed by the recipient, or for\nthe User Product in which it has been modified or installed.  Access to a\nnetwork may be denied when the modification itself materially and\nadversely affects the operation of the network or violates the rules and\nprotocols for communication across the network.\n\n  Corresponding Source conveyed, and Installation Information provided,\nin accord with this section must be in a format that is publicly\ndocumented (and with an implementation available to the public in\nsource code form), and must require no special password or key for\nunpacking, reading or copying.\n\n  7. Additional Terms.\n\n  \"Additional permissions\" are terms that supplement the terms of this\nLicense by making exceptions from one or more of its conditions.\nAdditional permissions that are applicable to the entire Program shall\nbe treated as though they were included in this License, to the extent\nthat they are valid under applicable law.  If additional permissions\napply only to part of the Program, that part may be used separately\nunder those permissions, but the entire Program remains governed by\nthis License without regard to the additional permissions.\n\n  When you convey a copy of a covered work, you may at your option\nremove any additional permissions from that copy, or from any part of\nit.  (Additional permissions may be written to require their own\nremoval in certain cases when you modify the work.)  You may place\nadditional permissions on material, added by you to a covered work,\nfor which you have or can give appropriate copyright permission.\n\n  Notwithstanding any other provision of this License, for material you\nadd to a covered work, you may (if authorized by the copyright holders of\nthat material) supplement the terms of this License with terms:\n\n    a) Disclaiming warranty or limiting liability differently from the\n    terms of sections 15 and 16 of this License; or\n\n    b) Requiring preservation of specified reasonable legal notices or\n    author attributions in that material or in the Appropriate Legal\n    Notices displayed by works containing it; or\n\n    c) Prohibiting misrepresentation of the origin of that material, or\n    requiring that modified versions of such material be marked in\n    reasonable ways as different from the original version; or\n\n    d) Limiting the use for publicity purposes of names of licensors or\n    authors of the material; or\n\n    e) Declining to grant rights under trademark law for use of some\n    trade names, trademarks, or service marks; or\n\n    f) Requiring indemnification of licensors and authors of that\n    material by anyone who conveys the material (or modified versions of\n    it) with contractual assumptions of liability to the recipient, for\n    any liability that these contractual assumptions directly impose on\n    those licensors and authors.\n\n  All other non-permissive additional terms are considered \"further\nrestrictions\" within the meaning of section 10.  If the Program as you\nreceived it, or any part of it, contains a notice stating that it is\ngoverned by this License along with a term that is a further\nrestriction, you may remove that term.  If a license document contains\na further restriction but permits relicensing or conveying under this\nLicense, you may add to a covered work material governed by the terms\nof that license document, provided that the further restriction does\nnot survive such relicensing or conveying.\n\n  If you add terms to a covered work in accord with this section, you\nmust place, in the relevant source files, a statement of the\nadditional terms that apply to those files, or a notice indicating\nwhere to find the applicable terms.\n\n  Additional terms, permissive or non-permissive, may be stated in the\nform of a separately written license, or stated as exceptions;\nthe above requirements apply either way.\n\n  8. Termination.\n\n  You may not propagate or modify a covered work except as expressly\nprovided under this License.  Any attempt otherwise to propagate or\nmodify it is void, and will automatically terminate your rights under\nthis License (including any patent licenses granted under the third\nparagraph of section 11).\n\n  However, if you cease all violation of this License, then your\nlicense from a particular copyright holder is reinstated (a)\nprovisionally, unless and until the copyright holder explicitly and\nfinally terminates your license, and (b) permanently, if the copyright\nholder fails to notify you of the violation by some reasonable means\nprior to 60 days after the cessation.\n\n  Moreover, your license from a particular copyright holder is\nreinstated permanently if the copyright holder notifies you of the\nviolation by some reasonable means, this is the first time you have\nreceived notice of violation of this License (for any work) from that\ncopyright holder, and you cure the violation prior to 30 days after\nyour receipt of the notice.\n\n  Termination of your rights under this section does not terminate the\nlicenses of parties who have received copies or rights from you under\nthis License.  If your rights have been terminated and not permanently\nreinstated, you do not qualify to receive new licenses for the same\nmaterial under section 10.\n\n  9. Acceptance Not Required for Having Copies.\n\n  You are not required to accept this License in order to receive or\nrun a copy of the Program.  Ancillary propagation of a covered work\noccurring solely as a consequence of using peer-to-peer transmission\nto receive a copy likewise does not require acceptance.  However,\nnothing other than this License grants you permission to propagate or\nmodify any covered work.  These actions infringe copyright if you do\nnot accept this License.  Therefore, by modifying or propagating a\ncovered work, you indicate your acceptance of this License to do so.\n\n  10. Automatic Licensing of Downstream Recipients.\n\n  Each time you convey a covered work, the recipient automatically\nreceives a license from the original licensors, to run, modify and\npropagate that work, subject to this License.  You are not responsible\nfor enforcing compliance by third parties with this License.\n\n  An \"entity transaction\" is a transaction transferring control of an\norganization, or substantially all assets of one, or subdividing an\norganization, or merging organizations.  If propagation of a covered\nwork results from an entity transaction, each party to that\ntransaction who receives a copy of the work also receives whatever\nlicenses to the work the party's predecessor in interest had or could\ngive under the previous paragraph, plus a right to possession of the\nCorresponding Source of the work from the predecessor in interest, if\nthe predecessor has it or can get it with reasonable efforts.\n\n  You may not impose any further restrictions on the exercise of the\nrights granted or affirmed under this License.  For example, you may\nnot impose a license fee, royalty, or other charge for exercise of\nrights granted under this License, and you may not initiate litigation\n(including a cross-claim or counterclaim in a lawsuit) alleging that\nany patent claim is infringed by making, using, selling, offering for\nsale, or importing the Program or any portion of it.\n\n  11. Patents.\n\n  A \"contributor\" is a copyright holder who authorizes use under this\nLicense of the Program or a work on which the Program is based.  The\nwork thus licensed is called the contributor's \"contributor version\".\n\n  A contributor's \"essential patent claims\" are all patent claims\nowned or controlled by the contributor, whether already acquired or\nhereafter acquired, that would be infringed by some manner, permitted\nby this License, of making, using, or selling its contributor version,\nbut do not include claims that would be infringed only as a\nconsequence of further modification of the contributor version.  For\npurposes of this definition, \"control\" includes the right to grant\npatent sublicenses in a manner consistent with the requirements of\nthis License.\n\n  Each contributor grants you a non-exclusive, worldwide, royalty-free\npatent license under the contributor's essential patent claims, to\nmake, use, sell, offer for sale, import and otherwise run, modify and\npropagate the contents of its contributor version.\n\n  In the following three paragraphs, a \"patent license\" is any express\nagreement or commitment, however denominated, not to enforce a patent\n(such as an express permission to practice a patent or covenant not to\nsue for patent infringement).  To \"grant\" such a patent license to a\nparty means to make such an agreement or commitment not to enforce a\npatent against the party.\n\n  If you convey a covered work, knowingly relying on a patent license,\nand the Corresponding Source of the work is not available for anyone\nto copy, free of charge and under the terms of this License, through a\npublicly available network server or other readily accessible means,\nthen you must either (1) cause the Corresponding Source to be so\navailable, or (2) arrange to deprive yourself of the benefit of the\npatent license for this particular work, or (3) arrange, in a manner\nconsistent with the requirements of this License, to extend the patent\nlicense to downstream recipients.  \"Knowingly relying\" means you have\nactual knowledge that, but for the patent license, your conveying the\ncovered work in a country, or your recipient's use of the covered work\nin a country, would infringe one or more identifiable patents in that\ncountry that you have reason to believe are valid.\n\n  If, pursuant to or in connection with a single transaction or\narrangement, you convey, or propagate by procuring conveyance of, a\ncovered work, and grant a patent license to some of the parties\nreceiving the covered work authorizing them to use, propagate, modify\nor convey a specific copy of the covered work, then the patent license\nyou grant is automatically extended to all recipients of the covered\nwork and works based on it.\n\n  A patent license is \"discriminatory\" if it does not include within\nthe scope of its coverage, prohibits the exercise of, or is\nconditioned on the non-exercise of one or more of the rights that are\nspecifically granted under this License.  You may not convey a covered\nwork if you are a party to an arrangement with a third party that is\nin the business of distributing software, under which you make payment\nto the third party based on the extent of your activity of conveying\nthe work, and under which the third party grants, to any of the\nparties who would receive the covered work from you, a discriminatory\npatent license (a) in connection with copies of the covered work\nconveyed by you (or copies made from those copies), or (b) primarily\nfor and in connection with specific products or compilations that\ncontain the covered work, unless you entered into that arrangement,\nor that patent license was granted, prior to 28 March 2007.\n\n  Nothing in this License shall be construed as excluding or limiting\nany implied license or other defenses to infringement that may\notherwise be available to you under applicable patent law.\n\n  12. No Surrender of Others' Freedom.\n\n  If conditions are imposed on you (whether by court order, agreement or\notherwise) that contradict the conditions of this License, they do not\nexcuse you from the conditions of this License.  If you cannot convey a\ncovered work so as to satisfy simultaneously your obligations under this\nLicense and any other pertinent obligations, then as a consequence you may\nnot convey it at all.  For example, if you agree to terms that obligate you\nto collect a royalty for further conveying from those to whom you convey\nthe Program, the only way you could satisfy both those terms and this\nLicense would be to refrain entirely from conveying the Program.\n\n  13. Use with the GNU Affero General Public License.\n\n  Notwithstanding any other provision of this License, you have\npermission to link or combine any covered work with a work licensed\nunder version 3 of the GNU Affero General Public License into a single\ncombined work, and to convey the resulting work.  The terms of this\nLicense will continue to apply to the part which is the covered work,\nbut the special requirements of the GNU Affero General Public License,\nsection 13, concerning interaction through a network will apply to the\ncombination as such.\n\n  14. Revised Versions of this License.\n\n  The Free Software Foundation may publish revised and/or new versions of\nthe GNU General Public License from time to time.  Such new versions will\nbe similar in spirit to the present version, but may differ in detail to\naddress new problems or concerns.\n\n  Each version is given a distinguishing version number.  If the\nProgram specifies that a certain numbered version of the GNU General\nPublic License \"or any later version\" applies to it, you have the\noption of following the terms and conditions either of that numbered\nversion or of any later version published by the Free Software\nFoundation.  If the Program does not specify a version number of the\nGNU General Public License, you may choose any version ever published\nby the Free Software Foundation.\n\n  If the Program specifies that a proxy can decide which future\nversions of the GNU General Public License can be used, that proxy's\npublic statement of acceptance of a version permanently authorizes you\nto choose that version for the Program.\n\n  Later license versions may give you additional or different\npermissions.  However, no additional obligations are imposed on any\nauthor or copyright holder as a result of your choosing to follow a\nlater version.\n\n  15. Disclaimer of Warranty.\n\n  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY\nAPPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT\nHOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM \"AS IS\" WITHOUT WARRANTY\nOF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,\nTHE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR\nPURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM\nIS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF\nALL NECESSARY SERVICING, REPAIR OR CORRECTION.\n\n  16. Limitation of Liability.\n\n  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING\nWILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS\nTHE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY\nGENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE\nUSE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF\nDATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD\nPARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),\nEVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF\nSUCH DAMAGES.\n\n  17. Interpretation of Sections 15 and 16.\n\n  If the disclaimer of warranty and limitation of liability provided\nabove cannot be given local legal effect according to their terms,\nreviewing courts shall apply local law that most closely approximates\nan absolute waiver of all civil liability in connection with the\nProgram, unless a warranty or assumption of liability accompanies a\ncopy of the Program in return for a fee.\n\n                     END OF TERMS AND CONDITIONS\n",
            "type": "text/plain",
            "title": "$:/plugins/tiddlywiki/jszip/license"
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        "$:/plugins/tiddlywiki/jszip/readme": {
            "title": "$:/plugins/tiddlywiki/jszip/readme",
            "text": "This plugin packages [[JSZip|https://stuk.github.io/jszip/]] for use by other plugins. It does not provide any end-user visible features.\n"
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{
    "tiddlers": {
        "$:/plugins/tiddlywiki/xlsx-utils/controls": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/controls",
            "caption": "XLSX Utilities",
            "tags": "$:/tags/ControlPanel",
            "text": "\\define help-button(state)\n<$button popup=\"\"\"$:/state/expand-help/$state$\"\"\" class=\"tc-btn-invisible tc-popup-keep\">\n{{$:/core/images/help}}\n</$button>\n\\end\n\n\\define help-content(type,state)\n<$reveal tag=\"span\" state=\"\"\"$:/state/expand-help/$state$\"\"\" type=\"popup\" position=\"below\">\n<div class=\"tc-drop-down tc-popup-keep\" style=\"padding: 0.5em; max-width: 30em; white-space: normal;\">\n<$transclude tiddler=\"\"\"$:/plugins/tiddlywiki/xlsx-utils/docs/$type$\"\"\" mode=\"block\"/>\n</div>\n</$reveal>\n\\end\n\n\\define renameProxyTitle()\n$:/state/plugins/tiddlywiki/xlsx-utils/rename-$(currentTiddler)$\n\\end\n\n\\define rename-current-tiddler()\n<$edit-text tag=\"input\" tiddler=<<renameProxyTitle>> placeholder=\"Rename\" default=<<currentTiddler>> size=\"50\"/>\n<$reveal type=\"nomatch\" state=\"\"\"$(renameProxyTitle)$\"\"\" text=<<currentTiddler>> default=<<currentTiddler>> tag=\"span\">\n<$button>\n<$action-deletetiddler $tiddler=<<renameProxyTitle>>/>\ncancel\n</$button>\n<$button>\n<$action-sendmessage $message=\"tm-rename-tiddler\" from=<<currentTiddler>> to={{$(renameProxyTitle)$}}/>\n<$action-deletetiddler $tiddler=<<renameProxyTitle>>/>\nrename\n</$button>\n<$set name=\"proxy-title\" value={{$(renameProxyTitle)$}}>\n<$list filter=\"\"\"[<proxy-title>is[tiddler]]\"\"\">\nWarning: tiddler already exists\n</$list>\n</$set>\n</$reveal>\n\\end\n\n\\define expand-collapse-button(state)\n<$reveal state=\"\"\"$:/state/expand/$state$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"span\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"\"\"$:/state/expand/$state$\"\"\" $value=\"no\"/>\n{{$:/core/images/down-arrow}}\n</$button>\n</$reveal>\n<$reveal state=\"\"\"$:/state/expand/$state$\"\"\" type=\"nomatch\" text=\"yes\" default=\"no\" tag=\"span\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"\"\"$:/state/expand/$state$\"\"\" $value=\"yes\"/>\n{{$:/core/images/right-arrow}}\n</$button>\n</$reveal>\n\\end\n\n\\define expand-collapse-content(state,content,class)\n<$reveal state=\"\"\"$:/state/expand/$state$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"div\" class=\"\"\"$class$\"\"\" animate=\"yes\" retain=\"yes\">\n$content$\n</$reveal>\n\\end\n\n\\define up-down-buttons(parent,child)\n<$list filter=\"[list<$parent$>butfirst[]field:title<$child$>limit[1]]\" variable=\"listItem\">\n<$button class=\"tc-btn-invisible\">\n<$action-listops $tiddler=<<$parent$>> $subfilter=\"+[move:-1<$child$>]\"/>\n{{$:/core/images/chevron-up}}\n</$button>\n</$list>\n<$list filter=\"[list<$parent$>butlast[]field:title<$child$>limit[1]]\" variable=\"listItem\">\n<$button class=\"tc-btn-invisible\">\n<$action-listops $tiddler=<<$parent$>> $subfilter=\"+[move:1<$child$>]\"/>\n{{$:/core/images/chevron-down}}\n</$button>\n</$list>\n\\end\n\n\\define edit-button(state)\n<$reveal state=\"\"\"$:/state/edit/$state$\"\"\" type=\"nomatch\" text=\"yes\" default=\"no\" tag=\"span\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"\"\"$:/state/edit/$state$\"\"\" $value=\"yes\"/>\n<$action-setfield $tiddler=\"\"\"$:/state/expand/$state$\"\"\" $value=\"yes\"/>\n{{$:/core/images/edit-button}}\n</$button>\n</$reveal>\n<$reveal state=\"\"\"$:/state/edit/$state$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"span\">\n<$button class=\"tc-btn-invisible\">\n<$action-setfield $tiddler=\"\"\"$:/state/edit/$state$\"\"\" $value=\"no\"/>\n{{$:/core/images/done-button}} Finish editing\n</$button>\n</$reveal>\n\\end\n\n\\define delete-item-button(filter,parent,title,prompt)\n<$button class=\"tc-btn-invisible\">\n<$action-deletetiddler $filter=\"\"\"$filter$\"\"\"/>\n<$action-listops $tiddler=\"\"\"$parent$\"\"\" $subfilter=\"-[[$title$]]\"/>\n{{$:/core/images/delete-button}}$prompt$\n</$button>\n\\end\n\n\\define edit-field()\n<$select tiddler=<<field>> field=\"import-field-list-op\" default=\"none\">\n<option value=\"none\">Set field</option>\n<option value=\"append\">Append to list field</option>\n</$select>\n<$edit-text tiddler=<<field>> field=\"import-field-name\" size=\"10\" tag=\"input\" placeholder=\"field name\"default=\"\"/>\n<$reveal state=\"\"\"$(field)$!!import-field-list-op\"\"\" type=\"match\" text=\"none\" default=\"none\" tag=\"span\">\nto\n</$reveal>\n<$reveal state=\"\"\"$(field)$!!import-field-list-op\"\"\" type=\"match\" text=\"append\" default=\"none\" tag=\"span\">\nthe\n</$reveal>\n<$select tiddler=<<field>> field=\"import-field-type\" default=\"string\">\n<option value=\"date\">date</option>\n<option value=\"string\">string</option>\n</$select>\n<$select tiddler=<<field>> field=\"import-field-source\" default=\"column\">\n<option value=\"column\">from column</option>\n<option value=\"constant\">constant</option>\n</$select>\n<$reveal state=\"\"\"$(field)$!!import-field-source\"\"\" type=\"match\" text=\"column\" default=\"column\" tag=\"span\">\n<$edit-text tiddler=<<field>> field=\"import-field-column\" tag=\"input\" placeholder=\"column\" default=\"\"/>\nprefixed\n<$edit-text tiddler=<<field>> field=\"import-field-prefix\" tag=\"input\" placeholder=\"prefix\" default=\"\"/>,\nsuffixed\n<$edit-text tiddler=<<field>> field=\"import-field-suffix\" tag=\"input\" placeholder=\"suffix\" default=\"\"/>\n</$reveal>\n<$reveal state=\"\"\"$(field)$!!import-field-source\"\"\" type=\"match\" text=\"constant\" default=\"column\" tag=\"span\">\n<$edit-text tiddler=<<field>> field=\"import-field-value\" tag=\"input\" placeholder=\"constant\" default=\"\"/>\n</$reveal>\n<$checkbox tiddler=<<field>> field=\"import-field-skip-tiddler-if-blank\" checked=\"yes\" unchecked=\"no\" default=\"no\">\nSkip this tiddler when field blank\n<br/>\nTitle:\n<$tiddler tiddler=<<field>>>\n<<rename-current-tiddler>>\n</$tiddler>\n\\end\n\n\\define view-field()\n<$link to=<<field>>>\n<$list filter=\"[<field>!has[import-field-list-op]]\" variable=\"listItem\">\nSet field ''<$view tiddler=<<field>> field=\"import-field-name\"/>'' to\n</$list>\n<$list filter=\"[<field>get[import-field-list-op]prefix[append]]\" variable=\"listItem\">\nAppend to list field ''<$view tiddler=<<field>> field=\"import-field-name\"/>''\n</$list>\n<$list filter=\"[<field>has[import-field-prefix]]\" variable=\"listItem\">\n''<code><$view tiddler=<<field>> field=\"import-field-prefix\"/></code>'' +\n</$list>\n<$list filter=\"[<field>get[import-field-type]prefix[date]]\" variable=\"listItem\">\ndate\n</$list>\n<$list filter=\"[<field>get[import-field-source]prefix[column]]\" variable=\"listItem\">\nvalue from column ''<$view tiddler=<<field>> field=\"import-field-column\"/>''\n</$list>\n<$list filter=\"[<field>get[import-field-source]prefix[constant]]\" variable=\"listItem\">\nconstant ''<code><$view tiddler=<<field>> field=\"import-field-value\"/></code>''\n</$list>\n<$list filter=\"[<field>has[import-field-suffix]]\" variable=\"listItem\">\n+ ''<code><$view tiddler=<<field>> field=\"import-field-suffix\"/></code>''\n</$list>\n</$link>\n\\end\n\n\\define list-fields()\n<ul class=\"tc-import-spec-row-list\">\n<$list filter=\"[list<row>]\" variable=\"field\" emptyMessage=\"<div>(No field import specifiers)</div>\">\n<li class=\"tc-import-spec-field-wrapper\">\n<$reveal state=\"\"\"$:/state/edit/$(row)$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"span\">\n<<edit-field>>\n<<up-down-buttons parent:\"row\" child:\"field\">>\n<$macrocall $name=\"delete-item-button\" filter=\"[<field>]\" parent=<<row>> title=<<field>>/>\n</$reveal>\n<$reveal state=\"\"\"$:/state/edit/$(row)$\"\"\" type=\"nomatch\" text=\"yes\" default=\"no\" tag=\"span\">\n<<view-field>>\n</$reveal>\n</li>\n</$list>\n</ul>\n\\end\n\n\\define view-row-content()\n<$reveal state=\"\"\"$:/state/edit/$(row)$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"ul\" class=\"tc-import-spec-row-controls\" animate=\"yes\" retain=\"yes\">\n<li>\n<$macrocall $name=\"delete-item-button\" filter=\"[<row>] [<row>getlist[]]\" parent=<<sheet>> title=<<row>> prompt=\" Delete this row\"/>\n</li>\n<li>\nTitle:\n<$tiddler tiddler=<<row>>>\n<<rename-current-tiddler>>\n</$tiddler>\n</li>\n<li>\nRow type:\n<$select tiddler=<<row>> field=\"import-row-type\" default=\"by-field\">\n<option value=\"by-field\">By field</option>\n<option value=\"by-column\">By column</option>\n</$select>\n</li>\n<li>\n<$button class=\"tc-btn-invisible\">\n<$action-createtiddler $basetitle=\"$:/_ExcelImporter/ImportSpecifiers/Field\" $savetitle=\"$:/temp/newtiddler\" import-spec-role=\"field\" import-field-name=\"fieldname\" import-field-type=\"string\" import-field-source=\"column\" import-field-column=\"Column Name\" />\n<$action-listops $tiddler=<<row>> $subfilter=\"[{$:/temp/newtiddler}] +[putfirst[]]\"/>\n{{$:/core/images/new-button}} Add new field\n</$button>\n</li>\n</$reveal>\n<<list-fields>>\n\\end\n\n\\define view-row()\n<div class=\"tc-import-spec-row-wrapper\">\n<h5>\n<$macrocall $name=\"expand-collapse-button\" state=<<row>>/>\nEach row: <$list filter=\"[list<row>import-field-name[title]]\" variable=\"field\" emptyMessage=\"\n<$link to=<<field>>>(title field not set)</$link>\"><<view-field>></$list>\n<$macrocall $name=\"edit-button\" state=<<row>>/>\n<<up-down-buttons parent:\"sheet\" child:\"row\">>\n<$macrocall $name=\"help-button\" state=<<row>>/>\n</h5>\n<$macrocall $name=\"help-content\" type=\"row\" state=<<row>>/>\n<$macrocall $name=\"expand-collapse-content\" state=<<row>> content=<<view-row-content>> class=\"tc-import-spec-row\"/>\n</div>\n\\end\n\n\\define list-rows()\n<div class=\"tc-import-spec-sheet-list\">\n<$list filter=\"[list<sheet>]\" variable=\"row\" emptyMessage=\"<div>(No row import specifiers)</div>\">\n<<view-row>>\n</$list>\n\\end\n\n\\define view-sheet-content()\n<$reveal state=\"\"\"$:/state/edit/$(sheet)$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"ul\" class=\"tc-import-spec-sheet-controls\" animate=\"yes\" retain=\"yes\">\n<li>\n<$macrocall $name=\"delete-item-button\" filter=\"[<sheet>] [<sheet>getlist[]] [<sheet>getlist[]getlist[]]\" parent=<<workbook>> title=<<sheet>> prompt=\" Delete this sheet\"/>\n</li>\n<li>\nTitle:\n<$tiddler tiddler=<<sheet>>>\n<<rename-current-tiddler>>\n</$tiddler>\n</li>\n<li>\nImport sheet name:\n<$edit-text tiddler=<<sheet>> field=\"import-sheet-name\" size=\"50\"/>\n</li>\n<li>\n<$button class=\"tc-btn-invisible\">\n<$action-createtiddler $basetitle=\"$:/_ExcelImporter/ImportSpecifiers/Row\" $savetitle=\"$:/temp/newtiddler\" import-spec-role=\"row\"/>\n<$action-listops $tiddler=<<sheet>> $subfilter=\"[{$:/temp/newtiddler}] +[putfirst[]]\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/edit/]] }}} $value=\"yes\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/expand/]] }}} $value=\"yes\"/>\n{{$:/core/images/new-button}} Add new row\n</$button>\n</li>\n</$reveal>\n<<list-rows>>\n\\end\n\n\\define view-sheet()\n<div class=\"tc-import-spec-sheet-wrapper\">\n<h4>\n<$macrocall $name=\"expand-collapse-button\" state=<<sheet>>/>\nSheet: <$link to=<<sheet>>><$view tiddler=<<sheet>> field=\"import-sheet-name\"/></$link>\n<$macrocall $name=\"edit-button\" state=<<sheet>>/>\n<<up-down-buttons parent:\"workbook\" child:\"sheet\">>\n<$macrocall $name=\"help-button\" state=<<sheet>>/>\n</h4>\n<$macrocall $name=\"help-content\" type=\"sheet\" state=<<sheet>>/>\n<$macrocall $name=\"expand-collapse-content\" state=<<sheet>> content=<<view-sheet-content>> class=\"tc-import-spec-sheet\"/>\n</div>\n\\end\n\n\\define list-sheets()\n<div class=\"tc-import-spec-workbook-list\">\n<$list filter=\"[list<workbook>]\" variable=\"sheet\" emptyMessage=\"<div>(No sheet import specifiers)</div>\">\n<<view-sheet>>\n</$list>\n</div>\n\\end\n\n\\define view-workbook-content()\n<$reveal state=\"\"\"$:/state/edit/$(workbook)$\"\"\" type=\"match\" text=\"yes\" default=\"no\" tag=\"ul\" class=\"tc-import-spec-workbook-controls\" animate=\"yes\" retain=\"yes\">\n<li>\n<$macrocall $name=\"delete-item-button\" filter=\"[<workbook>] [<workbook>getlist[]] [<workbook>getlist[]getlist[]] [<workbook>getlist[]getlist[]getlist[]]\" prompt=\" Delete this workbook\"/>\n</li>\n<li>\nTitle:\n<$tiddler tiddler=<<workbook>>>\n<<rename-current-tiddler>>\n</$tiddler>\n</li>\n<li>\nCaption:\n<$edit-text tiddler=<<workbook>> field=\"caption\" size=\"50\"/>\n</li>\n<li>\n<$button class=\"tc-btn-invisible\">\n<$action-createtiddler $basetitle=\"$:/_ExcelImporter/ImportSpecifiers/Sheet\" $savetitle=\"$:/temp/newtiddler\" import-spec-role=\"sheet\" import-sheet-name=\"Sheet name\"/>\n<$action-listops $tiddler=<<workbook>> $subfilter=\"[{$:/temp/newtiddler}] +[putfirst[]]\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/edit/]] }}} $value=\"yes\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/expand/]] }}} $value=\"yes\"/>\n{{$:/core/images/new-button}} Add new sheet\n</$button>\n</li>\n</$reveal>\n<<list-sheets>>\n\\end\n\n\\define view-workbook()\n<div class=\"tc-import-spec-workbook-wrapper\">\n<h3>\n<$macrocall $name=\"expand-collapse-button\" state=<<workbook>>/>\nWorkbook: <$link to=<<workbook>>><$view tiddler=<<workbook>> field=\"caption\"/></$link>\n<$macrocall $name=\"edit-button\" state=<<workbook>>/>\n<$macrocall $name=\"help-button\" state=<<workbook>>/>\n</h3>\n<$macrocall $name=\"help-content\" type=\"workbook\" state=<<workbook>>/>\n<$macrocall $name=\"expand-collapse-content\" state=<<workbook>> content=<<view-workbook-content>> class=\"tc-import-spec-workbook\"/>\n</div>\n\\end\n\n\\define list-workbooks()\n<ul class=\"tc-import-spec-editor-controls\">\n<li>\n<$button class=\"tc-btn-invisible\">\n<$action-createtiddler $basetitle=\"$:/_ExcelImporter/ImportSpecifiers/Workbook\" $savetitle=\"$:/temp/newtiddler\" import-spec-role=\"workbook\" caption=\"New workbook\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/edit/]] }}} $value=\"yes\"/>\n<$action-setfield $tiddler={{{ [{$:/temp/newtiddler}addprefix[$:/state/expand/]] }}} $value=\"yes\"/>\n{{$:/core/images/new-button}} Add new workbook\n</$button>\n</li>\n</ul>\n<div class=\"tc-import-spec-editor-list\">\n<$list filter=\"[all[shadows+tiddlers]import-spec-role[workbook]sort[caption]]\" variable=\"workbook\">\n<<view-workbook>>\n</$list>\n</div>\n\\end\n\n<h1>\nControls for XLSX Spreadsheet Utilities\n</h1>\n\n<div class=\"tc-import-spec-selector\">\n<h2>\nCurrent Import Specification\n</h2>\n<$list filter=\"[all[shadows+tiddlers]import-spec-role[workbook]limit[1]]\" emptyMessage=\"\"\"\nThere are no import specifications available. Use the controls below to create one\n\"\"\">\nThis is the import specification that will be used for the next import of an `.XLSX` file\n<$select tiddler=\"$:/config/plugins/tiddlywiki/xlsx-utils/default-import-spec\">\n<$list filter=\"[all[shadows+tiddlers]import-spec-role[workbook]sort[caption]]\">\n<option value=<<currentTiddler>>><$text text={{!!caption}}/></option>\n</$list>\n</$select>\n</$list>\n</div>\n\n<div class=\"tc-import-spec-editor-wrapper\">\n<h2>\n Import Specifications\n<$macrocall $name=\"help-button\" state=\"\"/>\n</h2>\n<$macrocall $name=\"help-content\" type=\"editor\" state=\"\"/>\n<div class=\"tc-import-spec-editor\">\n<<list-workbooks>>\n</div>\n</div>\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/deserializer.js": {
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/xlsx-utils/deserializer.js\ntype: application/javascript\nmodule-type: tiddlerdeserializer\n\nXLSX file deserializer\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n/*\nParse an XLSX file into tiddlers\n*/\nexports[\"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\"] = function(text,fields) {\n\t// Collect output tiddlers in an array\n\tvar results = [],\n\t\tXLSXImporter = require(\"$:/plugins/tiddlywiki/xlsx-utils/importer.js\").XLSXImporter,\n\t\timporter = new XLSXImporter({\n\t\t\ttext: text\n\t\t});\n\t// Return the output tiddlers\n\treturn importer.getResults();\n};\n\n})();\n",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/deserializer.js",
            "type": "application/javascript",
            "module-type": "tiddlerdeserializer"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/docs/editor": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/docs/editor",
            "text": "!!! Import Specifications\n\nImport specifications govern how spreadsheets are converted into individual tiddlers.\n\nEach \"workbook\" describes how spreadsheets of a particular format should be converted.\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/docs/row": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/docs/row",
            "text": "!!! Row Import Specifications\n\nEach row import specification describes how one tiddler should be extracted from each row of the current sheet.\n\nNote that using multiple row import specifications within a sheet enables multiple tiddlers to be created from each row of the sheet.\n\nRows contain a list of field import specifications that describe how each field of the tiddler should be created.\n\n!!! Field Import Specifications\n\nField import specifications describe the value given to a particular field of a tiddler.\n\nThey follow a rich syntax for describing how each field of the tiddler is created. For example:\n\n* Set field `title` to string from column `Organization`\n* Set field `role` to string constant `organization`\n* Append to list field `list` the string from column `Country` prefixed with `Map:`\n\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/docs/sheet": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/docs/sheet",
            "text": "!!! Sheet Import Specifications\n\nEach sheet import specification describes how a named sheet within a workbook should be converted into individual tiddlers.\n\nSheets contain a list of row import specifications that describe how individual rows of the sheet should be handled.\n\nEach sheet has the name of the sheet that it handles.\n\nNote that the first row of each sheet is interpreted as the title of each column.\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/docs/workbook": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/docs/workbook",
            "text": "!!! Workbook Import Specifications\n\nEach workbook import specification describes how spreadsheets of a particular format should be converted into individual tiddlers.\n\nCreate a new workbook for each type of spreadsheet that you will be working with.\n\nWorkbooks contain a list of sheet import specifications that describe how individual sheets of the workbook should be handled.\n\nEach workbook has a caption that you can use to describe its purpose.\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/xlsx.js": {
            "text": "var old_exports = exports,JSZip = require(\"$:/plugins/tiddlywiki/jszip/jszip.js\");exports = {};if($tw.browser){module.exports=undefined;};/* xlsx.js (C) 2013-2015 SheetJS -- http://sheetjs.com */\n/* vim: set ts=2: */\n/*jshint -W041 */\n/*jshint funcscope:true, eqnull:true */\nvar XLSX = {};\n(function make_xlsx(XLSX){\nXLSX.version = '0.8.0';\nvar current_codepage = 1200, current_cptable;\nif(typeof module !== \"undefined\" && typeof require !== 'undefined') {\n\tif(typeof cptable === 'undefined') cptable = require('./dist/cpexcel');\n\tcurrent_cptable = cptable[current_codepage];\n}\nfunction reset_cp() { set_cp(1200); }\nvar set_cp = function(cp) { current_codepage = cp; };\n\nfunction char_codes(data) { var o = []; for(var i = 0, len = data.length; i < len; ++i) o[i] = data.charCodeAt(i); return o; }\nvar debom_xml = function(data) { return data; };\n\nvar _getchar = function _gc1(x) { return String.fromCharCode(x); };\nif(typeof cptable !== 'undefined') {\n\tset_cp = function(cp) { current_codepage = cp; current_cptable = cptable[cp]; };\n\tdebom_xml = function(data) {\n\t\tif(data.charCodeAt(0) === 0xFF && data.charCodeAt(1) === 0xFE) { return cptable.utils.decode(1200, char_codes(data.substr(2))); }\n\t\treturn data;\n\t};\n\t_getchar = function _gc2(x) {\n\t\tif(current_codepage === 1200) return String.fromCharCode(x);\n\t\treturn cptable.utils.decode(current_codepage, [x&255,x>>8])[0];\n\t};\n}\nvar Base64 = (function make_b64(){\n\tvar map = \"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=\";\n\treturn {\n\t\tencode: function(input, utf8) {\n\t\t\tvar o = \"\";\n\t\t\tvar c1, c2, c3, e1, e2, e3, e4;\n\t\t\tfor(var i = 0; i < input.length; ) {\n\t\t\t\tc1 = input.charCodeAt(i++);\n\t\t\t\tc2 = input.charCodeAt(i++);\n\t\t\t\tc3 = input.charCodeAt(i++);\n\t\t\t\te1 = c1 >> 2;\n\t\t\t\te2 = (c1 & 3) << 4 | c2 >> 4;\n\t\t\t\te3 = (c2 & 15) << 2 | c3 >> 6;\n\t\t\t\te4 = c3 & 63;\n\t\t\t\tif (isNaN(c2)) { e3 = e4 = 64; }\n\t\t\t\telse if (isNaN(c3)) { e4 = 64; }\n\t\t\t\to += map.charAt(e1) + map.charAt(e2) + map.charAt(e3) + map.charAt(e4);\n\t\t\t}\n\t\t\treturn o;\n\t\t},\n\t\tdecode: function b64_decode(input, utf8) {\n\t\t\tvar o = \"\";\n\t\t\tvar c1, c2, c3;\n\t\t\tvar e1, e2, e3, e4;\n\t\t\tinput = input.replace(/[^A-Za-z0-9\\+\\/\\=]/g, \"\");\n\t\t\tfor(var i = 0; i < input.length;) {\n\t\t\t\te1 = map.indexOf(input.charAt(i++));\n\t\t\t\te2 = map.indexOf(input.charAt(i++));\n\t\t\t\te3 = map.indexOf(input.charAt(i++));\n\t\t\t\te4 = map.indexOf(input.charAt(i++));\n\t\t\t\tc1 = e1 << 2 | e2 >> 4;\n\t\t\t\tc2 = (e2 & 15) << 4 | e3 >> 2;\n\t\t\t\tc3 = (e3 & 3) << 6 | e4;\n\t\t\t\to += String.fromCharCode(c1);\n\t\t\t\tif (e3 != 64) { o += String.fromCharCode(c2); }\n\t\t\t\tif (e4 != 64) { o += String.fromCharCode(c3); }\n\t\t\t}\n\t\t\treturn o;\n\t\t}\n\t};\n})();\nvar has_buf = (typeof Buffer !== 'undefined');\n\nfunction new_raw_buf(len) {\n\t/* jshint -W056 */\n\treturn new (has_buf ? Buffer : Array)(len);\n\t/* jshint +W056 */\n}\n\nfunction s2a(s) {\n\tif(has_buf) return new Buffer(s, \"binary\");\n\treturn s.split(\"\").map(function(x){ return x.charCodeAt(0) & 0xff; });\n}\n\nvar bconcat = function(bufs) { return [].concat.apply([], bufs); };\n\nvar chr0 = /\\u0000/g, chr1 = /[\\u0001-\\u0006]/;\n/* ssf.js (C) 2013-2014 SheetJS -- http://sheetjs.com */\n/*jshint -W041 */\nvar SSF = {};\nvar make_ssf = function make_ssf(SSF){\nSSF.version = '0.8.1';\nfunction _strrev(x) { var o = \"\", i = x.length-1; while(i>=0) o += x.charAt(i--); return o; }\nfunction fill(c,l) { var o = \"\"; while(o.length < l) o+=c; return o; }\nfunction pad0(v,d){var t=\"\"+v; return t.length>=d?t:fill('0',d-t.length)+t;}\nfunction pad_(v,d){var t=\"\"+v;return t.length>=d?t:fill(' ',d-t.length)+t;}\nfunction rpad_(v,d){var t=\"\"+v; return t.length>=d?t:t+fill(' ',d-t.length);}\nfunction pad0r1(v,d){var t=\"\"+Math.round(v); return t.length>=d?t:fill('0',d-t.length)+t;}\nfunction pad0r2(v,d){var t=\"\"+v; return t.length>=d?t:fill('0',d-t.length)+t;}\nvar p2_32 = Math.pow(2,32);\nfunction pad0r(v,d){if(v>p2_32||v<-p2_32) return pad0r1(v,d); var i = Math.round(v); return pad0r2(i,d); }\nfunction isgeneral(s, i) { return s.length >= 7 + i && (s.charCodeAt(i)|32) === 103 && (s.charCodeAt(i+1)|32) === 101 && (s.charCodeAt(i+2)|32) === 110 && (s.charCodeAt(i+3)|32) === 101 && (s.charCodeAt(i+4)|32) === 114 && (s.charCodeAt(i+5)|32) === 97 && (s.charCodeAt(i+6)|32) === 108; }\n/* Options */\nvar opts_fmt = [\n\t[\"date1904\", 0],\n\t[\"output\", \"\"],\n\t[\"WTF\", false]\n];\nfunction fixopts(o){\n\tfor(var y = 0; y != opts_fmt.length; ++y) if(o[opts_fmt[y][0]]===undefined) o[opts_fmt[y][0]]=opts_fmt[y][1];\n}\nSSF.opts = opts_fmt;\nvar table_fmt = {\n\t0:  'General',\n\t1:  '0',\n\t2:  '0.00',\n\t3:  '#,##0',\n\t4:  '#,##0.00',\n\t9:  '0%',\n\t10: '0.00%',\n\t11: '0.00E+00',\n\t12: '# ?/?',\n\t13: '# ??/??',\n\t14: 'm/d/yy',\n\t15: 'd-mmm-yy',\n\t16: 'd-mmm',\n\t17: 'mmm-yy',\n\t18: 'h:mm AM/PM',\n\t19: 'h:mm:ss AM/PM',\n\t20: 'h:mm',\n\t21: 'h:mm:ss',\n\t22: 'm/d/yy h:mm',\n\t37: '#,##0 ;(#,##0)',\n\t38: '#,##0 ;[Red](#,##0)',\n\t39: '#,##0.00;(#,##0.00)',\n\t40: '#,##0.00;[Red](#,##0.00)',\n\t45: 'mm:ss',\n\t46: '[h]:mm:ss',\n\t47: 'mmss.0',\n\t48: '##0.0E+0',\n\t49: '@',\n\t56: '\"上午/下午 \"hh\"時\"mm\"分\"ss\"秒 \"',\n\t65535: 'General'\n};\nvar days = [\n\t['Sun', 'Sunday'],\n\t['Mon', 'Monday'],\n\t['Tue', 'Tuesday'],\n\t['Wed', 'Wednesday'],\n\t['Thu', 'Thursday'],\n\t['Fri', 'Friday'],\n\t['Sat', 'Saturday']\n];\nvar months = [\n\t['J', 'Jan', 'January'],\n\t['F', 'Feb', 'February'],\n\t['M', 'Mar', 'March'],\n\t['A', 'Apr', 'April'],\n\t['M', 'May', 'May'],\n\t['J', 'Jun', 'June'],\n\t['J', 'Jul', 'July'],\n\t['A', 'Aug', 'August'],\n\t['S', 'Sep', 'September'],\n\t['O', 'Oct', 'October'],\n\t['N', 'Nov', 'November'],\n\t['D', 'Dec', 'December']\n];\nfunction frac(x, D, mixed) {\n\tvar sgn = x < 0 ? -1 : 1;\n\tvar B = x * sgn;\n\tvar P_2 = 0, P_1 = 1, P = 0;\n\tvar Q_2 = 1, Q_1 = 0, Q = 0;\n\tvar A = Math.floor(B);\n\twhile(Q_1 < D) {\n\t\tA = Math.floor(B);\n\t\tP = A * P_1 + P_2;\n\t\tQ = A * Q_1 + Q_2;\n\t\tif((B - A) < 0.0000000005) break;\n\t\tB = 1 / (B - A);\n\t\tP_2 = P_1; P_1 = P;\n\t\tQ_2 = Q_1; Q_1 = Q;\n\t}\n\tif(Q > D) { Q = Q_1; P = P_1; }\n\tif(Q > D) { Q = Q_2; P = P_2; }\n\tif(!mixed) return [0, sgn * P, Q];\n\tif(Q===0) throw \"Unexpected state: \"+P+\" \"+P_1+\" \"+P_2+\" \"+Q+\" \"+Q_1+\" \"+Q_2;\n\tvar q = Math.floor(sgn * P/Q);\n\treturn [q, sgn*P - q*Q, Q];\n}\nfunction general_fmt_int(v, opts) { return \"\"+v; }\nSSF._general_int = general_fmt_int;\nvar general_fmt_num = (function make_general_fmt_num() {\nvar gnr1 = /\\.(\\d*[1-9])0+$/, gnr2 = /\\.0*$/, gnr4 = /\\.(\\d*[1-9])0+/, gnr5 = /\\.0*[Ee]/, gnr6 = /(E[+-])(\\d)$/;\nfunction gfn2(v) {\n\tvar w = (v<0?12:11);\n\tvar o = gfn5(v.toFixed(12)); if(o.length <= w) return o;\n\to = v.toPrecision(10); if(o.length <= w) return o;\n\treturn v.toExponential(5);\n}\nfunction gfn3(v) {\n\tvar o = v.toFixed(11).replace(gnr1,\".$1\");\n\tif(o.length > (v<0?12:11)) o = v.toPrecision(6);\n\treturn o;\n}\nfunction gfn4(o) {\n\tfor(var i = 0; i != o.length; ++i) if((o.charCodeAt(i) | 0x20) === 101) return o.replace(gnr4,\".$1\").replace(gnr5,\"E\").replace(\"e\",\"E\").replace(gnr6,\"$10$2\");\n\treturn o;\n}\nfunction gfn5(o) {\n\t//for(var i = 0; i != o.length; ++i) if(o.charCodeAt(i) === 46) return o.replace(gnr2,\"\").replace(gnr1,\".$1\");\n\t//return o;\n\treturn o.indexOf(\".\") > -1 ? o.replace(gnr2,\"\").replace(gnr1,\".$1\") : o;\n}\nreturn function general_fmt_num(v, opts) {\n\tvar V = Math.floor(Math.log(Math.abs(v))*Math.LOG10E), o;\n\tif(V >= -4 && V <= -1) o = v.toPrecision(10+V);\n\telse if(Math.abs(V) <= 9) o = gfn2(v);\n\telse if(V === 10) o = v.toFixed(10).substr(0,12);\n\telse o = gfn3(v);\n\treturn gfn5(gfn4(o));\n};})();\nSSF._general_num = general_fmt_num;\nfunction general_fmt(v, opts) {\n\tswitch(typeof v) {\n\t\tcase 'string': return v;\n\t\tcase 'boolean': return v ? \"TRUE\" : \"FALSE\";\n\t\tcase 'number': return (v|0) === v ? general_fmt_int(v, opts) : general_fmt_num(v, opts);\n\t}\n\tthrow new Error(\"unsupported value in General format: \" + v);\n}\nSSF._general = general_fmt;\nfunction fix_hijri(date, o) { return 0; }\nfunction parse_date_code(v,opts,b2) {\n\tif(v > 2958465 || v < 0) return null;\n\tvar date = (v|0), time = Math.floor(86400 * (v - date)), dow=0;\n\tvar dout=[];\n\tvar out={D:date, T:time, u:86400*(v-date)-time,y:0,m:0,d:0,H:0,M:0,S:0,q:0};\n\tif(Math.abs(out.u) < 1e-6) out.u = 0;\n\tfixopts(opts != null ? opts : (opts=[]));\n\tif(opts.date1904) date += 1462;\n\tif(out.u > 0.999) {\n\t\tout.u = 0;\n\t\tif(++time == 86400) { time = 0; ++date; }\n\t}\n\tif(date === 60) {dout = b2 ? [1317,10,29] : [1900,2,29]; dow=3;}\n\telse if(date === 0) {dout = b2 ? [1317,8,29] : [1900,1,0]; dow=6;}\n\telse {\n\t\tif(date > 60) --date;\n\t\t/* 1 = Jan 1 1900 */\n\t\tvar d = new Date(1900,0,1);\n\t\td.setDate(d.getDate() + date - 1);\n\t\tdout = [d.getFullYear(), d.getMonth()+1,d.getDate()];\n\t\tdow = d.getDay();\n\t\tif(date < 60) dow = (dow + 6) % 7;\n\t\tif(b2) dow = fix_hijri(d, dout);\n\t}\n\tout.y = dout[0]; out.m = dout[1]; out.d = dout[2];\n\tout.S = time % 60; time = Math.floor(time / 60);\n\tout.M = time % 60; time = Math.floor(time / 60);\n\tout.H = time;\n\tout.q = dow;\n\treturn out;\n}\nSSF.parse_date_code = parse_date_code;\n/*jshint -W086 */\nfunction write_date(type, fmt, val, ss0) {\n\tvar o=\"\", ss=0, tt=0, y = val.y, out, outl = 0;\n\tswitch(type) {\n\t\tcase 98: /* 'b' buddhist year */\n\t\t\ty = val.y + 543;\n\t\t\t/* falls through */\n\t\tcase 121: /* 'y' year */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = y % 100; outl = 2; break;\n\t\t\tdefault: out = y % 10000; outl = 4; break;\n\t\t} break;\n\t\tcase 109: /* 'm' month */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = val.m; outl = fmt.length; break;\n\t\t\tcase 3: return months[val.m-1][1];\n\t\t\tcase 5: return months[val.m-1][0];\n\t\t\tdefault: return months[val.m-1][2];\n\t\t} break;\n\t\tcase 100: /* 'd' day */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = val.d; outl = fmt.length; break;\n\t\t\tcase 3: return days[val.q][0];\n\t\t\tdefault: return days[val.q][1];\n\t\t} break;\n\t\tcase 104: /* 'h' 12-hour */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = 1+(val.H+11)%12; outl = fmt.length; break;\n\t\t\tdefault: throw 'bad hour format: ' + fmt;\n\t\t} break;\n\t\tcase 72: /* 'H' 24-hour */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = val.H; outl = fmt.length; break;\n\t\t\tdefault: throw 'bad hour format: ' + fmt;\n\t\t} break;\n\t\tcase 77: /* 'M' minutes */\n\t\tswitch(fmt.length) {\n\t\t\tcase 1: case 2: out = val.M; outl = fmt.length; break;\n\t\t\tdefault: throw 'bad minute format: ' + fmt;\n\t\t} break;\n\t\tcase 115: /* 's' seconds */\n\t\tif(val.u === 0) switch(fmt) {\n\t\t\tcase 's': case 'ss': return pad0(val.S, fmt.length);\n\t\t\tcase '.0': case '.00': case '.000':\n\t\t}\n\t\tswitch(fmt) {\n\t\t\tcase 's': case 'ss': case '.0': case '.00': case '.000':\n\t\t\t\tif(ss0 >= 2) tt = ss0 === 3 ? 1000 : 100;\n\t\t\t\telse tt = ss0 === 1 ? 10 : 1;\n\t\t\t\tss = Math.round((tt)*(val.S + val.u));\n\t\t\t\tif(ss >= 60*tt) ss = 0;\n\t\t\t\tif(fmt === 's') return ss === 0 ? \"0\" : \"\"+ss/tt;\n\t\t\t\to = pad0(ss,2 + ss0);\n\t\t\t\tif(fmt === 'ss') return o.substr(0,2);\n\t\t\t\treturn \".\" + o.substr(2,fmt.length-1);\n\t\t\tdefault: throw 'bad second format: ' + fmt;\n\t\t}\n\t\tcase 90: /* 'Z' absolute time */\n\t\tswitch(fmt) {\n\t\t\tcase '[h]': case '[hh]': out = val.D*24+val.H; break;\n\t\t\tcase '[m]': case '[mm]': out = (val.D*24+val.H)*60+val.M; break;\n\t\t\tcase '[s]': case '[ss]': out = ((val.D*24+val.H)*60+val.M)*60+Math.round(val.S+val.u); break;\n\t\t\tdefault: throw 'bad abstime format: ' + fmt;\n\t\t} outl = fmt.length === 3 ? 1 : 2; break;\n\t\tcase 101: /* 'e' era */\n\t\t\tout = y; outl = 1;\n\t}\n\tif(outl > 0) return pad0(out, outl); else return \"\";\n}\n/*jshint +W086 */\nfunction commaify(s) {\n\tif(s.length <= 3) return s;\n\tvar j = (s.length % 3), o = s.substr(0,j);\n\tfor(; j!=s.length; j+=3) o+=(o.length > 0 ? \",\" : \"\") + s.substr(j,3);\n\treturn o;\n}\nvar write_num = (function make_write_num(){\nvar pct1 = /%/g;\nfunction write_num_pct(type, fmt, val){\n\tvar sfmt = fmt.replace(pct1,\"\"), mul = fmt.length - sfmt.length;\n\treturn write_num(type, sfmt, val * Math.pow(10,2*mul)) + fill(\"%\",mul);\n}\nfunction write_num_cm(type, fmt, val){\n\tvar idx = fmt.length - 1;\n\twhile(fmt.charCodeAt(idx-1) === 44) --idx;\n\treturn write_num(type, fmt.substr(0,idx), val / Math.pow(10,3*(fmt.length-idx)));\n}\nfunction write_num_exp(fmt, val){\n\tvar o;\n\tvar idx = fmt.indexOf(\"E\") - fmt.indexOf(\".\") - 1;\n\tif(fmt.match(/^#+0.0E\\+0$/)) {\n\t\tvar period = fmt.indexOf(\".\"); if(period === -1) period=fmt.indexOf('E');\n\t\tvar ee = Math.floor(Math.log(Math.abs(val))*Math.LOG10E)%period;\n\t\tif(ee < 0) ee += period;\n\t\to = (val/Math.pow(10,ee)).toPrecision(idx+1+(period+ee)%period);\n\t\tif(o.indexOf(\"e\") === -1) {\n\t\t\tvar fakee = Math.floor(Math.log(Math.abs(val))*Math.LOG10E);\n\t\t\tif(o.indexOf(\".\") === -1) o = o[0] + \".\" + o.substr(1) + \"E+\" + (fakee - o.length+ee);\n\t\t\telse o += \"E+\" + (fakee - ee);\n\t\t\twhile(o.substr(0,2) === \"0.\") {\n\t\t\t\to = o[0] + o.substr(2,period) + \".\" + o.substr(2+period);\n\t\t\t\to = o.replace(/^0+([1-9])/,\"$1\").replace(/^0+\\./,\"0.\");\n\t\t\t}\n\t\t\to = o.replace(/\\+-/,\"-\");\n\t\t}\n\t\to = o.replace(/^([+-]?)(\\d*)\\.(\\d*)[Ee]/,function($$,$1,$2,$3) { return $1 + $2 + $3.substr(0,(period+ee)%period) + \".\" + $3.substr(ee) + \"E\"; });\n\t} else o = val.toExponential(idx);\n\tif(fmt.match(/E\\+00$/) && o.match(/e[+-]\\d$/)) o = o.substr(0,o.length-1) + \"0\" + o[o.length-1];\n\tif(fmt.match(/E\\-/) && o.match(/e\\+/)) o = o.replace(/e\\+/,\"e\");\n\treturn o.replace(\"e\",\"E\");\n}\nvar frac1 = /# (\\?+)( ?)\\/( ?)(\\d+)/;\nfunction write_num_f1(r, aval, sign) {\n\tvar den = parseInt(r[4]), rr = Math.round(aval * den), base = Math.floor(rr/den);\n\tvar myn = (rr - base*den), myd = den;\n\treturn sign + (base === 0 ? \"\" : \"\"+base) + \" \" + (myn === 0 ? fill(\" \", r[1].length + 1 + r[4].length) : pad_(myn,r[1].length) + r[2] + \"/\" + r[3] + pad0(myd,r[4].length));\n}\nfunction write_num_f2(r, aval, sign) {\n\treturn sign + (aval === 0 ? \"\" : \"\"+aval) + fill(\" \", r[1].length + 2 + r[4].length);\n}\nvar dec1 = /^#*0*\\.(0+)/;\nvar closeparen = /\\).*[0#]/;\nvar phone = /\\(###\\) ###\\\\?-####/;\nfunction hashq(str) {\n\tvar o = \"\", cc;\n\tfor(var i = 0; i != str.length; ++i) switch((cc=str.charCodeAt(i))) {\n\t\tcase 35: break;\n\t\tcase 63: o+= \" \"; break;\n\t\tcase 48: o+= \"0\"; break;\n\t\tdefault: o+= String.fromCharCode(cc);\n\t}\n\treturn o;\n}\nfunction rnd(val, d) { var dd = Math.pow(10,d); return \"\"+(Math.round(val * dd)/dd); }\nfunction dec(val, d) { return Math.round((val-Math.floor(val))*Math.pow(10,d)); }\nfunction flr(val) { if(val < 2147483647 && val > -2147483648) return \"\"+(val >= 0 ? (val|0) : (val-1|0)); return \"\"+Math.floor(val); }\nfunction write_num_flt(type, fmt, val) {\n\tif(type.charCodeAt(0) === 40 && !fmt.match(closeparen)) {\n\t\tvar ffmt = fmt.replace(/\\( */,\"\").replace(/ \\)/,\"\").replace(/\\)/,\"\");\n\t\tif(val >= 0) return write_num_flt('n', ffmt, val);\n\t\treturn '(' + write_num_flt('n', ffmt, -val) + ')';\n\t}\n\tif(fmt.charCodeAt(fmt.length - 1) === 44) return write_num_cm(type, fmt, val);\n\tif(fmt.indexOf('%') !== -1) return write_num_pct(type, fmt, val);\n\tif(fmt.indexOf('E') !== -1) return write_num_exp(fmt, val);\n\tif(fmt.charCodeAt(0) === 36) return \"$\"+write_num_flt(type,fmt.substr(fmt[1]==' '?2:1),val);\n\tvar o, oo;\n\tvar r, ri, ff, aval = Math.abs(val), sign = val < 0 ? \"-\" : \"\";\n\tif(fmt.match(/^00+$/)) return sign + pad0r(aval,fmt.length);\n\tif(fmt.match(/^[#?]+$/)) {\n\t\to = pad0r(val,0); if(o === \"0\") o = \"\";\n\t\treturn o.length > fmt.length ? o : hashq(fmt.substr(0,fmt.length-o.length)) + o;\n\t}\n\tif((r = fmt.match(frac1)) !== null) return write_num_f1(r, aval, sign);\n\tif(fmt.match(/^#+0+$/) !== null) return sign + pad0r(aval,fmt.length - fmt.indexOf(\"0\"));\n\tif((r = fmt.match(dec1)) !== null) {\n\t\to = rnd(val, r[1].length).replace(/^([^\\.]+)$/,\"$1.\"+r[1]).replace(/\\.$/,\".\"+r[1]).replace(/\\.(\\d*)$/,function($$, $1) { return \".\" + $1 + fill(\"0\", r[1].length-$1.length); });\n\t\treturn fmt.indexOf(\"0.\") !== -1 ? o : o.replace(/^0\\./,\".\");\n\t}\n\tfmt = fmt.replace(/^#+([0.])/, \"$1\");\n\tif((r = fmt.match(/^(0*)\\.(#*)$/)) !== null) {\n\t\treturn sign + rnd(aval, r[2].length).replace(/\\.(\\d*[1-9])0*$/,\".$1\").replace(/^(-?\\d*)$/,\"$1.\").replace(/^0\\./,r[1].length?\"0.\":\".\");\n\t}\n\tif((r = fmt.match(/^#,##0(\\.?)$/)) !== null) return sign + commaify(pad0r(aval,0));\n\tif((r = fmt.match(/^#,##0\\.([#0]*0)$/)) !== null) {\n\t\treturn val < 0 ? \"-\" + write_num_flt(type, fmt, -val) : commaify(\"\"+(Math.floor(val))) + \".\" + pad0(dec(val, r[1].length),r[1].length);\n\t}\n\tif((r = fmt.match(/^#,#*,#0/)) !== null) return write_num_flt(type,fmt.replace(/^#,#*,/,\"\"),val);\n\tif((r = fmt.match(/^([0#]+)(\\\\?-([0#]+))+$/)) !== null) {\n\t\to = _strrev(write_num_flt(type, fmt.replace(/[\\\\-]/g,\"\"), val));\n\t\tri = 0;\n\t\treturn _strrev(_strrev(fmt.replace(/\\\\/g,\"\")).replace(/[0#]/g,function(x){return ri<o.length?o[ri++]:x==='0'?'0':\"\";}));\n\t}\n\tif(fmt.match(phone) !== null) {\n\t\to = write_num_flt(type, \"##########\", val);\n\t\treturn \"(\" + o.substr(0,3) + \") \" + o.substr(3, 3) + \"-\" + o.substr(6);\n\t}\n\tvar oa = \"\";\n\tif((r = fmt.match(/^([#0?]+)( ?)\\/( ?)([#0?]+)/)) !== null) {\n\t\tri = Math.min(r[4].length,7);\n\t\tff = frac(aval, Math.pow(10,ri)-1, false);\n\t\to = \"\" + sign;\n\t\toa = write_num(\"n\", r[1], ff[1]);\n\t\tif(oa[oa.length-1] == \" \") oa = oa.substr(0,oa.length-1) + \"0\";\n\t\to += oa + r[2] + \"/\" + r[3];\n\t\toa = rpad_(ff[2],ri);\n\t\tif(oa.length < r[4].length) oa = hashq(r[4].substr(r[4].length-oa.length)) + oa;\n\t\to += oa;\n\t\treturn o;\n\t}\n\tif((r = fmt.match(/^# ([#0?]+)( ?)\\/( ?)([#0?]+)/)) !== null) {\n\t\tri = Math.min(Math.max(r[1].length, r[4].length),7);\n\t\tff = frac(aval, Math.pow(10,ri)-1, true);\n\t\treturn sign + (ff[0]||(ff[1] ? \"\" : \"0\")) + \" \" + (ff[1] ? pad_(ff[1],ri) + r[2] + \"/\" + r[3] + rpad_(ff[2],ri): fill(\" \", 2*ri+1 + r[2].length + r[3].length));\n\t}\n\tif((r = fmt.match(/^[#0?]+$/)) !== null) {\n\t\to = pad0r(val, 0);\n\t\tif(fmt.length <= o.length) return o;\n\t\treturn hashq(fmt.substr(0,fmt.length-o.length)) + o;\n\t}\n  if((r = fmt.match(/^([#0?]+)\\.([#0]+)$/)) !== null) {\n\t\to = \"\" + val.toFixed(Math.min(r[2].length,10)).replace(/([^0])0+$/,\"$1\");\n\t\tri = o.indexOf(\".\");\n\t\tvar lres = fmt.indexOf(\".\") - ri, rres = fmt.length - o.length - lres;\n\t\treturn hashq(fmt.substr(0,lres) + o + fmt.substr(fmt.length-rres));\n\t}\n\tif((r = fmt.match(/^00,000\\.([#0]*0)$/)) !== null) {\n\t\tri = dec(val, r[1].length);\n\t\treturn val < 0 ? \"-\" + write_num_flt(type, fmt, -val) : commaify(flr(val)).replace(/^\\d,\\d{3}$/,\"0$&\").replace(/^\\d*$/,function($$) { return \"00,\" + ($$.length < 3 ? pad0(0,3-$$.length) : \"\") + $$; }) + \".\" + pad0(ri,r[1].length);\n\t}\n\tswitch(fmt) {\n\t\tcase \"#,###\": var x = commaify(pad0r(aval,0)); return x !== \"0\" ? sign + x : \"\";\n\t\tdefault:\n\t}\n\tthrow new Error(\"unsupported format |\" + fmt + \"|\");\n}\nfunction write_num_cm2(type, fmt, val){\n\tvar idx = fmt.length - 1;\n\twhile(fmt.charCodeAt(idx-1) === 44) --idx;\n\treturn write_num(type, fmt.substr(0,idx), val / Math.pow(10,3*(fmt.length-idx)));\n}\nfunction write_num_pct2(type, fmt, val){\n\tvar sfmt = fmt.replace(pct1,\"\"), mul = fmt.length - sfmt.length;\n\treturn write_num(type, sfmt, val * Math.pow(10,2*mul)) + fill(\"%\",mul);\n}\nfunction write_num_exp2(fmt, val){\n\tvar o;\n\tvar idx = fmt.indexOf(\"E\") - fmt.indexOf(\".\") - 1;\n\tif(fmt.match(/^#+0.0E\\+0$/)) {\n\t\tvar period = fmt.indexOf(\".\"); if(period === -1) period=fmt.indexOf('E');\n\t\tvar ee = Math.floor(Math.log(Math.abs(val))*Math.LOG10E)%period;\n\t\tif(ee < 0) ee += period;\n\t\to = (val/Math.pow(10,ee)).toPrecision(idx+1+(period+ee)%period);\n\t\tif(!o.match(/[Ee]/)) {\n\t\t\tvar fakee = Math.floor(Math.log(Math.abs(val))*Math.LOG10E);\n\t\t\tif(o.indexOf(\".\") === -1) o = o[0] + \".\" + o.substr(1) + \"E+\" + (fakee - o.length+ee);\n\t\t\telse o += \"E+\" + (fakee - ee);\n\t\t\to = o.replace(/\\+-/,\"-\");\n\t\t}\n\t\to = o.replace(/^([+-]?)(\\d*)\\.(\\d*)[Ee]/,function($$,$1,$2,$3) { return $1 + $2 + $3.substr(0,(period+ee)%period) + \".\" + $3.substr(ee) + \"E\"; });\n\t} else o = val.toExponential(idx);\n\tif(fmt.match(/E\\+00$/) && o.match(/e[+-]\\d$/)) o = o.substr(0,o.length-1) + \"0\" + o[o.length-1];\n\tif(fmt.match(/E\\-/) && o.match(/e\\+/)) o = o.replace(/e\\+/,\"e\");\n\treturn o.replace(\"e\",\"E\");\n}\nfunction write_num_int(type, fmt, val) {\n\tif(type.charCodeAt(0) === 40 && !fmt.match(closeparen)) {\n\t\tvar ffmt = fmt.replace(/\\( */,\"\").replace(/ \\)/,\"\").replace(/\\)/,\"\");\n\t\tif(val >= 0) return write_num_int('n', ffmt, val);\n\t\treturn '(' + write_num_int('n', ffmt, -val) + ')';\n\t}\n\tif(fmt.charCodeAt(fmt.length - 1) === 44) return write_num_cm2(type, fmt, val);\n\tif(fmt.indexOf('%') !== -1) return write_num_pct2(type, fmt, val);\n\tif(fmt.indexOf('E') !== -1) return write_num_exp2(fmt, val);\n\tif(fmt.charCodeAt(0) === 36) return \"$\"+write_num_int(type,fmt.substr(fmt[1]==' '?2:1),val);\n\tvar o;\n\tvar r, ri, ff, aval = Math.abs(val), sign = val < 0 ? \"-\" : \"\";\n\tif(fmt.match(/^00+$/)) return sign + pad0(aval,fmt.length);\n\tif(fmt.match(/^[#?]+$/)) {\n\t\to = (\"\"+val); if(val === 0) o = \"\";\n\t\treturn o.length > fmt.length ? o : hashq(fmt.substr(0,fmt.length-o.length)) + o;\n\t}\n\tif((r = fmt.match(frac1)) !== null) return write_num_f2(r, aval, sign);\n\tif(fmt.match(/^#+0+$/) !== null) return sign + pad0(aval,fmt.length - fmt.indexOf(\"0\"));\n\tif((r = fmt.match(dec1)) !== null) {\n\t\to = (\"\"+val).replace(/^([^\\.]+)$/,\"$1.\"+r[1]).replace(/\\.$/,\".\"+r[1]).replace(/\\.(\\d*)$/,function($$, $1) { return \".\" + $1 + fill(\"0\", r[1].length-$1.length); });\n\t\treturn fmt.indexOf(\"0.\") !== -1 ? o : o.replace(/^0\\./,\".\");\n\t}\n\tfmt = fmt.replace(/^#+([0.])/, \"$1\");\n\tif((r = fmt.match(/^(0*)\\.(#*)$/)) !== null) {\n\t\treturn sign + (\"\"+aval).replace(/\\.(\\d*[1-9])0*$/,\".$1\").replace(/^(-?\\d*)$/,\"$1.\").replace(/^0\\./,r[1].length?\"0.\":\".\");\n\t}\n\tif((r = fmt.match(/^#,##0(\\.?)$/)) !== null) return sign + commaify((\"\"+aval));\n\tif((r = fmt.match(/^#,##0\\.([#0]*0)$/)) !== null) {\n\t\treturn val < 0 ? \"-\" + write_num_int(type, fmt, -val) : commaify((\"\"+val)) + \".\" + fill('0',r[1].length);\n\t}\n\tif((r = fmt.match(/^#,#*,#0/)) !== null) return write_num_int(type,fmt.replace(/^#,#*,/,\"\"),val);\n\tif((r = fmt.match(/^([0#]+)(\\\\?-([0#]+))+$/)) !== null) {\n\t\to = _strrev(write_num_int(type, fmt.replace(/[\\\\-]/g,\"\"), val));\n\t\tri = 0;\n\t\treturn _strrev(_strrev(fmt.replace(/\\\\/g,\"\")).replace(/[0#]/g,function(x){return ri<o.length?o[ri++]:x==='0'?'0':\"\";}));\n\t}\n\tif(fmt.match(phone) !== null) {\n\t\to = write_num_int(type, \"##########\", val);\n\t\treturn \"(\" + o.substr(0,3) + \") \" + o.substr(3, 3) + \"-\" + o.substr(6);\n\t}\n\tvar oa = \"\";\n\tif((r = fmt.match(/^([#0?]+)( ?)\\/( ?)([#0?]+)/)) !== null) {\n\t\tri = Math.min(r[4].length,7);\n\t\tff = frac(aval, Math.pow(10,ri)-1, false);\n\t\to = \"\" + sign;\n\t\toa = write_num(\"n\", r[1], ff[1]);\n\t\tif(oa[oa.length-1] == \" \") oa = oa.substr(0,oa.length-1) + \"0\";\n\t\to += oa + r[2] + \"/\" + r[3];\n\t\toa = rpad_(ff[2],ri);\n\t\tif(oa.length < r[4].length) oa = hashq(r[4].substr(r[4].length-oa.length)) + oa;\n\t\to += oa;\n\t\treturn o;\n\t}\n\tif((r = fmt.match(/^# ([#0?]+)( ?)\\/( ?)([#0?]+)/)) !== null) {\n\t\tri = Math.min(Math.max(r[1].length, r[4].length),7);\n\t\tff = frac(aval, Math.pow(10,ri)-1, true);\n\t\treturn sign + (ff[0]||(ff[1] ? \"\" : \"0\")) + \" \" + (ff[1] ? pad_(ff[1],ri) + r[2] + \"/\" + r[3] + rpad_(ff[2],ri): fill(\" \", 2*ri+1 + r[2].length + r[3].length));\n\t}\n\tif((r = fmt.match(/^[#0?]+$/)) !== null) {\n\t\to = \"\" + val;\n\t\tif(fmt.length <= o.length) return o;\n\t\treturn hashq(fmt.substr(0,fmt.length-o.length)) + o;\n\t}\n\tif((r = fmt.match(/^([#0]+)\\.([#0]+)$/)) !== null) {\n\t\to = \"\" + val.toFixed(Math.min(r[2].length,10)).replace(/([^0])0+$/,\"$1\");\n\t\tri = o.indexOf(\".\");\n\t\tvar lres = fmt.indexOf(\".\") - ri, rres = fmt.length - o.length - lres;\n\t\treturn hashq(fmt.substr(0,lres) + o + fmt.substr(fmt.length-rres));\n\t}\n\tif((r = fmt.match(/^00,000\\.([#0]*0)$/)) !== null) {\n\t\treturn val < 0 ? \"-\" + write_num_int(type, fmt, -val) : commaify(\"\"+val).replace(/^\\d,\\d{3}$/,\"0$&\").replace(/^\\d*$/,function($$) { return \"00,\" + ($$.length < 3 ? pad0(0,3-$$.length) : \"\") + $$; }) + \".\" + pad0(0,r[1].length);\n\t}\n\tswitch(fmt) {\n\t\tcase \"#,###\": var x = commaify(\"\"+aval); return x !== \"0\" ? sign + x : \"\";\n\t\tdefault:\n\t}\n\tthrow new Error(\"unsupported format |\" + fmt + \"|\");\n}\nreturn function write_num(type, fmt, val) {\n\treturn (val|0) === val ? write_num_int(type, fmt, val) : write_num_flt(type, fmt, val);\n};})();\nfunction split_fmt(fmt) {\n\tvar out = [];\n\tvar in_str = false, cc;\n\tfor(var i = 0, j = 0; i < fmt.length; ++i) switch((cc=fmt.charCodeAt(i))) {\n\t\tcase 34: /* '\"' */\n\t\t\tin_str = !in_str; break;\n\t\tcase 95: case 42: case 92: /* '_' '*' '\\\\' */\n\t\t\t++i; break;\n\t\tcase 59: /* ';' */\n\t\t\tout[out.length] = fmt.substr(j,i-j);\n\t\t\tj = i+1;\n\t}\n\tout[out.length] = fmt.substr(j);\n\tif(in_str === true) throw new Error(\"Format |\" + fmt + \"| unterminated string \");\n\treturn out;\n}\nSSF._split = split_fmt;\nvar abstime = /\\[[HhMmSs]*\\]/;\nfunction eval_fmt(fmt, v, opts, flen) {\n\tvar out = [], o = \"\", i = 0, c = \"\", lst='t', q, dt, j, cc;\n\tvar hr='H';\n\t/* Tokenize */\n\twhile(i < fmt.length) {\n\t\tswitch((c = fmt[i])) {\n\t\t\tcase 'G': /* General */\n\t\t\t\tif(!isgeneral(fmt, i)) throw new Error('unrecognized character ' + c + ' in ' +fmt);\n\t\t\t\tout[out.length] = {t:'G', v:'General'}; i+=7; break;\n\t\t\tcase '\"': /* Literal text */\n\t\t\t\tfor(o=\"\";(cc=fmt.charCodeAt(++i)) !== 34 && i < fmt.length;) o += String.fromCharCode(cc);\n\t\t\t\tout[out.length] = {t:'t', v:o}; ++i; break;\n\t\t\tcase '\\\\': var w = fmt[++i], t = (w === \"(\" || w === \")\") ? w : 't';\n\t\t\t\tout[out.length] = {t:t, v:w}; ++i; break;\n\t\t\tcase '_': out[out.length] = {t:'t', v:\" \"}; i+=2; break;\n\t\t\tcase '@': /* Text Placeholder */\n\t\t\t\tout[out.length] = {t:'T', v:v}; ++i; break;\n\t\t\tcase 'B': case 'b':\n\t\t\t\tif(fmt[i+1] === \"1\" || fmt[i+1] === \"2\") {\n          if(dt==null) { dt=parse_date_code(v, opts, fmt[i+1] === \"2\"); if(dt==null) return \"\"; }\n\t\t\t\t\tout[out.length] = {t:'X', v:fmt.substr(i,2)}; lst = c; i+=2; break;\n\t\t\t\t}\n\t\t\t\t/* falls through */\n\t\t\tcase 'M': case 'D': case 'Y': case 'H': case 'S': case 'E':\n\t\t\t\tc = c.toLowerCase();\n\t\t\t\t/* falls through */\n\t\t\tcase 'm': case 'd': case 'y': case 'h': case 's': case 'e': case 'g':\n\t\t\t\tif(v < 0) return \"\";\n\t\t\t\tif(dt==null) { dt=parse_date_code(v, opts); if(dt==null) return \"\"; }\n\t\t\t\to = c; while(++i<fmt.length && fmt[i].toLowerCase() === c) o+=c;\n\t\t\t\tif(c === 'm' && lst.toLowerCase() === 'h') c = 'M'; /* m = minute */\n\t\t\t\tif(c === 'h') c = hr;\n\t\t\t\tout[out.length] = {t:c, v:o}; lst = c; break;\n\t\t\tcase 'A':\n\t\t\t\tq={t:c, v:\"A\"};\n\t\t\t\tif(dt==null) dt=parse_date_code(v, opts);\n        if(fmt.substr(i, 3) === \"A/P\") { if(dt!=null) q.v = dt.H >= 12 ? \"P\" : \"A\"; q.t = 'T'; hr='h';i+=3;}\n        else if(fmt.substr(i,5) === \"AM/PM\") { if(dt!=null) q.v = dt.H >= 12 ? \"PM\" : \"AM\"; q.t = 'T'; i+=5; hr='h'; }\n\t\t\t\telse { q.t = \"t\"; ++i; }\n\t\t\t\tif(dt==null && q.t === 'T') return \"\";\n\t\t\t\tout[out.length] = q; lst = c; break;\n\t\t\tcase '[':\n\t\t\t\to = c;\n\t\t\t\twhile(fmt[i++] !== ']' && i < fmt.length) o += fmt[i];\n\t\t\t\tif(o.substr(-1) !== ']') throw 'unterminated \"[\" block: |' + o + '|';\n\t\t\t\tif(o.match(abstime)) {\n\t\t\t\t\tif(dt==null) { dt=parse_date_code(v, opts); if(dt==null) return \"\"; }\n\t\t\t\t\tout[out.length] = {t:'Z', v:o.toLowerCase()};\n\t\t\t\t} else { o=\"\"; }\n\t\t\t\tbreak;\n\t\t\t/* Numbers */\n\t\t\tcase '.':\n\t\t\t\tif(dt != null) {\n\t\t\t\t\to = c; while((c=fmt[++i]) === \"0\") o += c;\n\t\t\t\t\tout[out.length] = {t:'s', v:o}; break;\n\t\t\t\t}\n\t\t\t\t/* falls through */\n\t\t\tcase '0': case '#':\n\t\t\t\to = c; while(\"0#?.,E+-%\".indexOf(c=fmt[++i]) > -1 || c=='\\\\' && fmt[i+1] == \"-\" && \"0#\".indexOf(fmt[i+2])>-1) o += c;\n\t\t\t\tout[out.length] = {t:'n', v:o}; break;\n\t\t\tcase '?':\n\t\t\t\to = c; while(fmt[++i] === c) o+=c;\n\t\t\t\tq={t:c, v:o}; out[out.length] = q; lst = c; break;\n\t\t\tcase '*': ++i; if(fmt[i] == ' ' || fmt[i] == '*') ++i; break; // **\n\t\t\tcase '(': case ')': out[out.length] = {t:(flen===1?'t':c), v:c}; ++i; break;\n\t\t\tcase '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9':\n\t\t\t\to = c; while(\"0123456789\".indexOf(fmt[++i]) > -1) o+=fmt[i];\n\t\t\t\tout[out.length] = {t:'D', v:o}; break;\n\t\t\tcase ' ': out[out.length] = {t:c, v:c}; ++i; break;\n\t\t\tdefault:\n\t\t\t\tif(\",$-+/():!^&'~{}<>=€acfijklopqrtuvwxz\".indexOf(c) === -1) throw new Error('unrecognized character ' + c + ' in ' + fmt);\n\t\t\t\tout[out.length] = {t:'t', v:c}; ++i; break;\n\t\t}\n\t}\n\tvar bt = 0, ss0 = 0, ssm;\n\tfor(i=out.length-1, lst='t'; i >= 0; --i) {\n\t\tswitch(out[i].t) {\n\t\t\tcase 'h': case 'H': out[i].t = hr; lst='h'; if(bt < 1) bt = 1; break;\n\t\t\tcase 's':\n\t\t\t\tif((ssm=out[i].v.match(/\\.0+$/))) ss0=Math.max(ss0,ssm[0].length-1);\n\t\t\t\tif(bt < 3) bt = 3;\n\t\t\t/* falls through */\n\t\t\tcase 'd': case 'y': case 'M': case 'e': lst=out[i].t; break;\n\t\t\tcase 'm': if(lst === 's') { out[i].t = 'M'; if(bt < 2) bt = 2; } break;\n\t\t\tcase 'X': if(out[i].v === \"B2\");\n\t\t\t\tbreak;\n\t\t\tcase 'Z':\n\t\t\t\tif(bt < 1 && out[i].v.match(/[Hh]/)) bt = 1;\n\t\t\t\tif(bt < 2 && out[i].v.match(/[Mm]/)) bt = 2;\n\t\t\t\tif(bt < 3 && out[i].v.match(/[Ss]/)) bt = 3;\n\t\t}\n\t}\n\tswitch(bt) {\n\t\tcase 0: break;\n\t\tcase 1:\n\t\t\tif(dt.u >= 0.5) { dt.u = 0; ++dt.S; }\n\t\t\tif(dt.S >=  60) { dt.S = 0; ++dt.M; }\n\t\t\tif(dt.M >=  60) { dt.M = 0; ++dt.H; }\n\t\t\tbreak;\n\t\tcase 2:\n\t\t\tif(dt.u >= 0.5) { dt.u = 0; ++dt.S; }\n\t\t\tif(dt.S >=  60) { dt.S = 0; ++dt.M; }\n\t\t\tbreak;\n\t}\n\t/* replace fields */\n\tvar nstr = \"\", jj;\n\tfor(i=0; i < out.length; ++i) {\n\t\tswitch(out[i].t) {\n\t\t\tcase 't': case 'T': case ' ': case 'D': break;\n\t\t\tcase 'X': out[i] = undefined; break;\n\t\t\tcase 'd': case 'm': case 'y': case 'h': case 'H': case 'M': case 's': case 'e': case 'b': case 'Z':\n\t\t\t\tout[i].v = write_date(out[i].t.charCodeAt(0), out[i].v, dt, ss0);\n\t\t\t\tout[i].t = 't'; break;\n\t\t\tcase 'n': case '(': case '?':\n\t\t\t\tjj = i+1;\n\t\t\t\twhile(out[jj] != null && (\n\t\t\t\t\t(c=out[jj].t) === \"?\" || c === \"D\" ||\n\t\t\t\t\t(c === \" \" || c === \"t\") && out[jj+1] != null && (out[jj+1].t === '?' || out[jj+1].t === \"t\" && out[jj+1].v === '/') ||\n\t\t\t\t\tout[i].t === '(' && (c === ' ' || c === 'n' || c === ')') ||\n\t\t\t\t\tc === 't' && (out[jj].v === '/' || '$€'.indexOf(out[jj].v) > -1 || out[jj].v === ' ' && out[jj+1] != null && out[jj+1].t == '?')\n\t\t\t\t)) {\n\t\t\t\t\tout[i].v += out[jj].v;\n\t\t\t\t\tout[jj] = undefined; ++jj;\n\t\t\t\t}\n\t\t\t\tnstr += out[i].v;\n\t\t\t\ti = jj-1; break;\n\t\t\tcase 'G': out[i].t = 't'; out[i].v = general_fmt(v,opts); break;\n\t\t}\n\t}\n\tvar vv = \"\", myv, ostr;\n\tif(nstr.length > 0) {\n\t\tmyv = (v<0&&nstr.charCodeAt(0) === 45 ? -v : v); /* '-' */\n\t\tostr = write_num(nstr.charCodeAt(0) === 40 ? '(' : 'n', nstr, myv); /* '(' */\n\t\tjj=ostr.length-1;\n\t\tvar decpt = out.length;\n\t\tfor(i=0; i < out.length; ++i) if(out[i] != null && out[i].v.indexOf(\".\") > -1) { decpt = i; break; }\n\t\tvar lasti=out.length;\n\t\tif(decpt === out.length && ostr.indexOf(\"E\") === -1) {\n\t\t\tfor(i=out.length-1; i>= 0;--i) {\n\t\t\t\tif(out[i] == null || 'n?('.indexOf(out[i].t) === -1) continue;\n\t\t\t\tif(jj>=out[i].v.length-1) { jj -= out[i].v.length; out[i].v = ostr.substr(jj+1, out[i].v.length); }\n\t\t\t\telse if(jj < 0) out[i].v = \"\";\n\t\t\t\telse { out[i].v = ostr.substr(0, jj+1); jj = -1; }\n\t\t\t\tout[i].t = 't';\n\t\t\t\tlasti = i;\n\t\t\t}\n\t\t\tif(jj>=0 && lasti<out.length) out[lasti].v = ostr.substr(0,jj+1) + out[lasti].v;\n\t\t}\n\t\telse if(decpt !== out.length && ostr.indexOf(\"E\") === -1) {\n\t\t\tjj = ostr.indexOf(\".\")-1;\n\t\t\tfor(i=decpt; i>= 0; --i) {\n\t\t\t\tif(out[i] == null || 'n?('.indexOf(out[i].t) === -1) continue;\n\t\t\t\tj=out[i].v.indexOf(\".\")>-1&&i===decpt?out[i].v.indexOf(\".\")-1:out[i].v.length-1;\n\t\t\t\tvv = out[i].v.substr(j+1);\n\t\t\t\tfor(; j>=0; --j) {\n\t\t\t\t\tif(jj>=0 && (out[i].v[j] === \"0\" || out[i].v[j] === \"#\")) vv = ostr[jj--] + vv;\n\t\t\t\t}\n\t\t\t\tout[i].v = vv;\n\t\t\t\tout[i].t = 't';\n\t\t\t\tlasti = i;\n\t\t\t}\n\t\t\tif(jj>=0 && lasti<out.length) out[lasti].v = ostr.substr(0,jj+1) + out[lasti].v;\n\t\t\tjj = ostr.indexOf(\".\")+1;\n\t\t\tfor(i=decpt; i<out.length; ++i) {\n\t\t\t\tif(out[i] == null || 'n?('.indexOf(out[i].t) === -1 && i !== decpt ) continue;\n\t\t\t\tj=out[i].v.indexOf(\".\")>-1&&i===decpt?out[i].v.indexOf(\".\")+1:0;\n\t\t\t\tvv = out[i].v.substr(0,j);\n\t\t\t\tfor(; j<out[i].v.length; ++j) {\n\t\t\t\t\tif(jj<ostr.length) vv += ostr[jj++];\n\t\t\t\t}\n\t\t\t\tout[i].v = vv;\n\t\t\t\tout[i].t = 't';\n\t\t\t\tlasti = i;\n\t\t\t}\n\t\t}\n\t}\n\tfor(i=0; i<out.length; ++i) if(out[i] != null && 'n(?'.indexOf(out[i].t)>-1) {\n\t\tmyv = (flen >1 && v < 0 && i>0 && out[i-1].v === \"-\" ? -v:v);\n\t\tout[i].v = write_num(out[i].t, out[i].v, myv);\n\t\tout[i].t = 't';\n\t}\n\tvar retval = \"\";\n\tfor(i=0; i !== out.length; ++i) if(out[i] != null) retval += out[i].v;\n\treturn retval;\n}\nSSF._eval = eval_fmt;\nvar cfregex = /\\[[=<>]/;\nvar cfregex2 = /\\[([=<>]*)(-?\\d+\\.?\\d*)\\]/;\nfunction chkcond(v, rr) {\n\tif(rr == null) return false;\n\tvar thresh = parseFloat(rr[2]);\n\tswitch(rr[1]) {\n\t\tcase \"=\":  if(v == thresh) return true; break;\n\t\tcase \">\":  if(v >  thresh) return true; break;\n\t\tcase \"<\":  if(v <  thresh) return true; break;\n\t\tcase \"<>\": if(v != thresh) return true; break;\n\t\tcase \">=\": if(v >= thresh) return true; break;\n\t\tcase \"<=\": if(v <= thresh) return true; break;\n\t}\n\treturn false;\n}\nfunction choose_fmt(f, v) {\n\tvar fmt = split_fmt(f);\n\tvar l = fmt.length, lat = fmt[l-1].indexOf(\"@\");\n\tif(l<4 && lat>-1) --l;\n\tif(fmt.length > 4) throw \"cannot find right format for |\" + fmt + \"|\";\n\tif(typeof v !== \"number\") return [4, fmt.length === 4 || lat>-1?fmt[fmt.length-1]:\"@\"];\n\tswitch(fmt.length) {\n\t\tcase 1: fmt = lat>-1 ? [\"General\", \"General\", \"General\", fmt[0]] : [fmt[0], fmt[0], fmt[0], \"@\"]; break;\n\t\tcase 2: fmt = lat>-1 ? [fmt[0], fmt[0], fmt[0], fmt[1]] : [fmt[0], fmt[1], fmt[0], \"@\"]; break;\n\t\tcase 3: fmt = lat>-1 ? [fmt[0], fmt[1], fmt[0], fmt[2]] : [fmt[0], fmt[1], fmt[2], \"@\"]; break;\n\t\tcase 4: break;\n\t}\n\tvar ff = v > 0 ? fmt[0] : v < 0 ? fmt[1] : fmt[2];\n\tif(fmt[0].indexOf(\"[\") === -1 && fmt[1].indexOf(\"[\") === -1) return [l, ff];\n\tif(fmt[0].match(cfregex) != null || fmt[1].match(cfregex) != null) {\n\t\tvar m1 = fmt[0].match(cfregex2);\n\t\tvar m2 = fmt[1].match(cfregex2);\n\t\treturn chkcond(v, m1) ? [l, fmt[0]] : chkcond(v, m2) ? [l, fmt[1]] : [l, fmt[m1 != null && m2 != null ? 2 : 1]];\n\t}\n\treturn [l, ff];\n}\nfunction format(fmt,v,o) {\n\tfixopts(o != null ? o : (o=[]));\n\tvar sfmt = \"\";\n\tswitch(typeof fmt) {\n\t\tcase \"string\": sfmt = fmt; break;\n\t\tcase \"number\": sfmt = (o.table != null ? o.table : table_fmt)[fmt]; break;\n\t}\n\tif(isgeneral(sfmt,0)) return general_fmt(v, o);\n\tvar f = choose_fmt(sfmt, v);\n\tif(isgeneral(f[1])) return general_fmt(v, o);\n\tif(v === true) v = \"TRUE\"; else if(v === false) v = \"FALSE\";\n\telse if(v === \"\" || v == null) return \"\";\n\treturn eval_fmt(f[1], v, o, f[0]);\n}\nSSF._table = table_fmt;\nSSF.load = function load_entry(fmt, idx) { table_fmt[idx] = fmt; };\nSSF.format = format;\nSSF.get_table = function get_table() { return table_fmt; };\nSSF.load_table = function load_table(tbl) { for(var i=0; i!=0x0188; ++i) if(tbl[i] !== undefined) SSF.load(tbl[i], i); };\n};\nmake_ssf(SSF);\n/* map from xlml named formats to SSF TODO: localize */\nvar XLMLFormatMap = {\n\t\"General Number\": \"General\",\n\t\"General Date\": SSF._table[22],\n\t\"Long Date\": \"dddd, mmmm dd, yyyy\",\n\t\"Medium Date\": SSF._table[15],\n\t\"Short Date\": SSF._table[14],\n\t\"Long Time\": SSF._table[19],\n\t\"Medium Time\": SSF._table[18],\n\t\"Short Time\": SSF._table[20],\n\t\"Currency\": '\"$\"#,##0.00_);[Red]\\\\(\"$\"#,##0.00\\\\)',\n\t\"Fixed\": SSF._table[2],\n\t\"Standard\": SSF._table[4],\n\t\"Percent\": SSF._table[10],\n\t\"Scientific\": SSF._table[11],\n\t\"Yes/No\": '\"Yes\";\"Yes\";\"No\";@',\n\t\"True/False\": '\"True\";\"True\";\"False\";@',\n\t\"On/Off\": '\"Yes\";\"Yes\";\"No\";@'\n};\n\nvar DO_NOT_EXPORT_CFB = true;\n/* cfb.js (C) 2013-2014 SheetJS -- http://sheetjs.com */\n/* vim: set ts=2: */\n/*jshint eqnull:true */\n\n/* [MS-CFB] v20130118 */\nvar CFB = (function _CFB(){\nvar exports = {};\nexports.version = '0.10.2';\nfunction parse(file) {\nvar mver = 3; // major version\nvar ssz = 512; // sector size\nvar nmfs = 0; // number of mini FAT sectors\nvar ndfs = 0; // number of DIFAT sectors\nvar dir_start = 0; // first directory sector location\nvar minifat_start = 0; // first mini FAT sector location\nvar difat_start = 0; // first mini FAT sector location\n\nvar fat_addrs = []; // locations of FAT sectors\n\n/* [MS-CFB] 2.2 Compound File Header */\nvar blob = file.slice(0,512);\nprep_blob(blob, 0);\n\n/* major version */\nvar mv = check_get_mver(blob);\nmver = mv[0];\nswitch(mver) {\n\tcase 3: ssz = 512; break; case 4: ssz = 4096; break;\n\tdefault: throw \"Major Version: Expected 3 or 4 saw \" + mver;\n}\n\n/* reprocess header */\nif(ssz !== 512) { blob = file.slice(0,ssz); prep_blob(blob, 28 /* blob.l */); }\n/* Save header for final object */\nvar header = file.slice(0,ssz);\n\ncheck_shifts(blob, mver);\n\n// Number of Directory Sectors\nvar nds = blob.read_shift(4, 'i');\nif(mver === 3 && nds !== 0) throw '# Directory Sectors: Expected 0 saw ' + nds;\n\n// Number of FAT Sectors\n//var nfs = blob.read_shift(4, 'i');\nblob.l += 4;\n\n// First Directory Sector Location\ndir_start = blob.read_shift(4, 'i');\n\n// Transaction Signature\nblob.l += 4;\n\n// Mini Stream Cutoff Size\nblob.chk('00100000', 'Mini Stream Cutoff Size: ');\n\n// First Mini FAT Sector Location\nminifat_start = blob.read_shift(4, 'i');\n\n// Number of Mini FAT Sectors\nnmfs = blob.read_shift(4, 'i');\n\n// First DIFAT sector location\ndifat_start = blob.read_shift(4, 'i');\n\n// Number of DIFAT Sectors\nndfs = blob.read_shift(4, 'i');\n\n// Grab FAT Sector Locations\nfor(var q, j = 0; j < 109; ++j) { /* 109 = (512 - blob.l)>>>2; */\n\tq = blob.read_shift(4, 'i');\n\tif(q<0) break;\n\tfat_addrs[j] = q;\n}\n\n/** Break the file up into sectors */\nvar sectors = sectorify(file, ssz);\n\nsleuth_fat(difat_start, ndfs, sectors, ssz, fat_addrs);\n\n/** Chains */\nvar sector_list = make_sector_list(sectors, dir_start, fat_addrs, ssz);\n\nsector_list[dir_start].name = \"!Directory\";\nif(nmfs > 0 && minifat_start !== ENDOFCHAIN) sector_list[minifat_start].name = \"!MiniFAT\";\nsector_list[fat_addrs[0]].name = \"!FAT\";\nsector_list.fat_addrs = fat_addrs;\nsector_list.ssz = ssz;\n\n/* [MS-CFB] 2.6.1 Compound File Directory Entry */\nvar files = {}, Paths = [], FileIndex = [], FullPaths = [], FullPathDir = {};\nread_directory(dir_start, sector_list, sectors, Paths, nmfs, files, FileIndex);\n\nbuild_full_paths(FileIndex, FullPathDir, FullPaths, Paths);\n\nvar root_name = Paths.shift();\nPaths.root = root_name;\n\n/* [MS-CFB] 2.6.4 (Unicode 3.0.1 case conversion) */\nvar find_path = make_find_path(FullPaths, Paths, FileIndex, files, root_name);\n\nreturn {\n\traw: {header: header, sectors: sectors},\n\tFileIndex: FileIndex,\n\tFullPaths: FullPaths,\n\tFullPathDir: FullPathDir,\n\tfind: find_path\n};\n} // parse\n\n/* [MS-CFB] 2.2 Compound File Header -- read up to major version */\nfunction check_get_mver(blob) {\n\t// header signature 8\n\tblob.chk(HEADER_SIGNATURE, 'Header Signature: ');\n\n\t// clsid 16\n\tblob.chk(HEADER_CLSID, 'CLSID: ');\n\n\t// minor version 2\n\tvar mver = blob.read_shift(2, 'u');\n\n\treturn [blob.read_shift(2,'u'), mver];\n}\nfunction check_shifts(blob, mver) {\n\tvar shift = 0x09;\n\n\t// Byte Order\n\tblob.chk('feff', 'Byte Order: ');\n\n\t// Sector Shift\n\tswitch((shift = blob.read_shift(2))) {\n\t\tcase 0x09: if(mver !== 3) throw 'MajorVersion/SectorShift Mismatch'; break;\n\t\tcase 0x0c: if(mver !== 4) throw 'MajorVersion/SectorShift Mismatch'; break;\n\t\tdefault: throw 'Sector Shift: Expected 9 or 12 saw ' + shift;\n\t}\n\n\t// Mini Sector Shift\n\tblob.chk('0600', 'Mini Sector Shift: ');\n\n\t// Reserved\n\tblob.chk('000000000000', 'Reserved: ');\n}\n\n/** Break the file up into sectors */\nfunction sectorify(file, ssz) {\n\tvar nsectors = Math.ceil(file.length/ssz)-1;\n\tvar sectors = new Array(nsectors);\n\tfor(var i=1; i < nsectors; ++i) sectors[i-1] = file.slice(i*ssz,(i+1)*ssz);\n\tsectors[nsectors-1] = file.slice(nsectors*ssz);\n\treturn sectors;\n}\n\n/* [MS-CFB] 2.6.4 Red-Black Tree */\nfunction build_full_paths(FI, FPD, FP, Paths) {\n\tvar i = 0, L = 0, R = 0, C = 0, j = 0, pl = Paths.length;\n\tvar dad = new Array(pl), q = new Array(pl);\n\n\tfor(; i < pl; ++i) { dad[i]=q[i]=i; FP[i]=Paths[i]; }\n\n\tfor(; j < q.length; ++j) {\n\t\ti = q[j];\n\t\tL = FI[i].L; R = FI[i].R; C = FI[i].C;\n\t\tif(dad[i] === i) {\n\t\t\tif(L !== -1 /*NOSTREAM*/ && dad[L] !== L) dad[i] = dad[L];\n\t\t\tif(R !== -1 && dad[R] !== R) dad[i] = dad[R];\n\t\t}\n\t\tif(C !== -1 /*NOSTREAM*/) dad[C] = i;\n\t\tif(L !== -1) { dad[L] = dad[i]; q.push(L); }\n\t\tif(R !== -1) { dad[R] = dad[i]; q.push(R); }\n\t}\n\tfor(i=1; i !== pl; ++i) if(dad[i] === i) {\n\t\tif(R !== -1 /*NOSTREAM*/ && dad[R] !== R) dad[i] = dad[R];\n\t\telse if(L !== -1 && dad[L] !== L) dad[i] = dad[L];\n\t}\n\n\tfor(i=1; i < pl; ++i) {\n\t\tif(FI[i].type === 0 /* unknown */) continue;\n\t\tj = dad[i];\n\t\tif(j === 0) FP[i] = FP[0] + \"/\" + FP[i];\n\t\telse while(j !== 0) {\n\t\t\tFP[i] = FP[j] + \"/\" + FP[i];\n\t\t\tj = dad[j];\n\t\t}\n\t\tdad[i] = 0;\n\t}\n\n\tFP[0] += \"/\";\n\tfor(i=1; i < pl; ++i) {\n\t\tif(FI[i].type !== 2 /* stream */) FP[i] += \"/\";\n\t\tFPD[FP[i]] = FI[i];\n\t}\n}\n\n/* [MS-CFB] 2.6.4 */\nfunction make_find_path(FullPaths, Paths, FileIndex, files, root_name) {\n\tvar UCFullPaths = new Array(FullPaths.length);\n\tvar UCPaths = new Array(Paths.length), i;\n\tfor(i = 0; i < FullPaths.length; ++i) UCFullPaths[i] = FullPaths[i].toUpperCase().replace(chr0,'').replace(chr1,'!');\n\tfor(i = 0; i < Paths.length; ++i) UCPaths[i] = Paths[i].toUpperCase().replace(chr0,'').replace(chr1,'!');\n\treturn function find_path(path) {\n\t\tvar k;\n\t\tif(path.charCodeAt(0) === 47 /* \"/\" */) { k=true; path = root_name + path; }\n\t\telse k = path.indexOf(\"/\") !== -1;\n\t\tvar UCPath = path.toUpperCase().replace(chr0,'').replace(chr1,'!');\n\t\tvar w = k === true ? UCFullPaths.indexOf(UCPath) : UCPaths.indexOf(UCPath);\n\t\tif(w === -1) return null;\n\t\treturn k === true ? FileIndex[w] : files[Paths[w]];\n\t};\n}\n\n/** Chase down the rest of the DIFAT chain to build a comprehensive list\n    DIFAT chains by storing the next sector number as the last 32 bytes */\nfunction sleuth_fat(idx, cnt, sectors, ssz, fat_addrs) {\n\tvar q;\n\tif(idx === ENDOFCHAIN) {\n\t\tif(cnt !== 0) throw \"DIFAT chain shorter than expected\";\n\t} else if(idx !== -1 /*FREESECT*/) {\n\t\tvar sector = sectors[idx], m = (ssz>>>2)-1;\n\t\tfor(var i = 0; i < m; ++i) {\n\t\t\tif((q = __readInt32LE(sector,i*4)) === ENDOFCHAIN) break;\n\t\t\tfat_addrs.push(q);\n\t\t}\n\t\tsleuth_fat(__readInt32LE(sector,ssz-4),cnt - 1, sectors, ssz, fat_addrs);\n\t}\n}\n\n/** Follow the linked list of sectors for a given starting point */\nfunction get_sector_list(sectors, start, fat_addrs, ssz, chkd) {\n\tvar sl = sectors.length;\n\tvar buf, buf_chain;\n\tif(!chkd) chkd = new Array(sl);\n\tvar modulus = ssz - 1, j, jj;\n\tbuf = [];\n\tbuf_chain = [];\n\tfor(j=start; j>=0;) {\n\t\tchkd[j] = true;\n\t\tbuf[buf.length] = j;\n\t\tbuf_chain.push(sectors[j]);\n\t\tvar addr = fat_addrs[Math.floor(j*4/ssz)];\n\t\tjj = ((j*4) & modulus);\n\t\tif(ssz < 4 + jj) throw \"FAT boundary crossed: \" + j + \" 4 \"+ssz;\n\t\tj = __readInt32LE(sectors[addr], jj);\n\t}\n\treturn {nodes: buf, data:__toBuffer([buf_chain])};\n}\n\n/** Chase down the sector linked lists */\nfunction make_sector_list(sectors, dir_start, fat_addrs, ssz) {\n\tvar sl = sectors.length, sector_list = new Array(sl);\n\tvar chkd = new Array(sl), buf, buf_chain;\n\tvar modulus = ssz - 1, i, j, k, jj;\n\tfor(i=0; i < sl; ++i) {\n\t\tbuf = [];\n\t\tk = (i + dir_start); if(k >= sl) k-=sl;\n\t\tif(chkd[k] === true) continue;\n\t\tbuf_chain = [];\n\t\tfor(j=k; j>=0;) {\n\t\t\tchkd[j] = true;\n\t\t\tbuf[buf.length] = j;\n\t\t\tbuf_chain.push(sectors[j]);\n\t\t\tvar addr = fat_addrs[Math.floor(j*4/ssz)];\n\t\t\tjj = ((j*4) & modulus);\n\t\t\tif(ssz < 4 + jj) throw \"FAT boundary crossed: \" + j + \" 4 \"+ssz;\n\t\t\tj = __readInt32LE(sectors[addr], jj);\n\t\t}\n\t\tsector_list[k] = {nodes: buf, data:__toBuffer([buf_chain])};\n\t}\n\treturn sector_list;\n}\n\n/* [MS-CFB] 2.6.1 Compound File Directory Entry */\nfunction read_directory(dir_start, sector_list, sectors, Paths, nmfs, files, FileIndex) {\n\tvar blob;\n\tvar minifat_store = 0, pl = (Paths.length?2:0);\n\tvar sector = sector_list[dir_start].data;\n\tvar i = 0, namelen = 0, name, o, ctime, mtime;\n\tfor(; i < sector.length; i+= 128) {\n\t\tblob = sector.slice(i, i+128);\n\t\tprep_blob(blob, 64);\n\t\tnamelen = blob.read_shift(2);\n\t\tif(namelen === 0) continue;\n\t\tname = __utf16le(blob,0,namelen-pl);\n\t\tPaths.push(name);\n\t\to = {\n\t\t\tname:  name,\n\t\t\ttype:  blob.read_shift(1),\n\t\t\tcolor: blob.read_shift(1),\n\t\t\tL:     blob.read_shift(4, 'i'),\n\t\t\tR:     blob.read_shift(4, 'i'),\n\t\t\tC:     blob.read_shift(4, 'i'),\n\t\t\tclsid: blob.read_shift(16),\n\t\t\tstate: blob.read_shift(4, 'i')\n\t\t};\n\t\tctime = blob.read_shift(2) + blob.read_shift(2) + blob.read_shift(2) + blob.read_shift(2);\n\t\tif(ctime !== 0) {\n\t\t\to.ctime = ctime; o.ct = read_date(blob, blob.l-8);\n\t\t}\n\t\tmtime = blob.read_shift(2) + blob.read_shift(2) + blob.read_shift(2) + blob.read_shift(2);\n\t\tif(mtime !== 0) {\n\t\t\to.mtime = mtime; o.mt = read_date(blob, blob.l-8);\n\t\t}\n\t\to.start = blob.read_shift(4, 'i');\n\t\to.size = blob.read_shift(4, 'i');\n\t\tif(o.type === 5) { /* root */\n\t\t\tminifat_store = o.start;\n\t\t\tif(nmfs > 0 && minifat_store !== ENDOFCHAIN) sector_list[minifat_store].name = \"!StreamData\";\n\t\t\t/*minifat_size = o.size;*/\n\t\t} else if(o.size >= 4096 /* MSCSZ */) {\n\t\t\to.storage = 'fat';\n\t\t\tif(sector_list[o.start] === undefined) sector_list[o.start] = get_sector_list(sectors, o.start, sector_list.fat_addrs, sector_list.ssz);\n\t\t\tsector_list[o.start].name = o.name;\n\t\t\to.content = sector_list[o.start].data.slice(0,o.size);\n\t\t\tprep_blob(o.content, 0);\n\t\t} else {\n\t\t\to.storage = 'minifat';\n\t\t\tif(minifat_store !== ENDOFCHAIN && o.start !== ENDOFCHAIN) {\n\t\t\t\to.content = sector_list[minifat_store].data.slice(o.start*MSSZ,o.start*MSSZ+o.size);\n\t\t\t\tprep_blob(o.content, 0);\n\t\t\t}\n\t\t}\n\t\tfiles[name] = o;\n\t\tFileIndex.push(o);\n\t}\n}\n\nfunction read_date(blob, offset) {\n\treturn new Date(( ( (__readUInt32LE(blob,offset+4)/1e7)*Math.pow(2,32)+__readUInt32LE(blob,offset)/1e7 ) - 11644473600)*1000);\n}\n\nvar fs;\nfunction readFileSync(filename, options) {\n\tif(fs === undefined) fs = require('fs');\n\treturn parse(fs.readFileSync(filename), options);\n}\n\nfunction readSync(blob, options) {\n\tswitch(options !== undefined && options.type !== undefined ? options.type : \"base64\") {\n\t\tcase \"file\": return readFileSync(blob, options);\n\t\tcase \"base64\": return parse(s2a(Base64.decode(blob)), options);\n\t\tcase \"binary\": return parse(s2a(blob), options);\n\t}\n\treturn parse(blob);\n}\n\n/** CFB Constants */\nvar MSSZ = 64; /* Mini Sector Size = 1<<6 */\n//var MSCSZ = 4096; /* Mini Stream Cutoff Size */\n/* 2.1 Compound File Sector Numbers and Types */\nvar ENDOFCHAIN = -2;\n/* 2.2 Compound File Header */\nvar HEADER_SIGNATURE = 'd0cf11e0a1b11ae1';\nvar HEADER_CLSID = '00000000000000000000000000000000';\nvar consts = {\n\t/* 2.1 Compund File Sector Numbers and Types */\n\tMAXREGSECT: -6,\n\tDIFSECT: -4,\n\tFATSECT: -3,\n\tENDOFCHAIN: ENDOFCHAIN,\n\tFREESECT: -1,\n\t/* 2.2 Compound File Header */\n\tHEADER_SIGNATURE: HEADER_SIGNATURE,\n\tHEADER_MINOR_VERSION: '3e00',\n\tMAXREGSID: -6,\n\tNOSTREAM: -1,\n\tHEADER_CLSID: HEADER_CLSID,\n\t/* 2.6.1 Compound File Directory Entry */\n\tEntryTypes: ['unknown','storage','stream','lockbytes','property','root']\n};\n\nexports.read = readSync;\nexports.parse = parse;\nexports.utils = {\n\tReadShift: ReadShift,\n\tCheckField: CheckField,\n\tprep_blob: prep_blob,\n\tbconcat: bconcat,\n\tconsts: consts\n};\n\nreturn exports;\n})();\n\nif(typeof require !== 'undefined' && typeof module !== 'undefined' && typeof DO_NOT_EXPORT_CFB === 'undefined') { module.exports = CFB; }\nfunction isval(x) { return x !== undefined && x !== null; }\n\nfunction keys(o) { return Object.keys(o); }\n\nfunction evert_key(obj, key) {\n\tvar o = [], K = keys(obj);\n\tfor(var i = 0; i !== K.length; ++i) o[obj[K[i]][key]] = K[i];\n\treturn o;\n}\n\nfunction evert(obj) {\n\tvar o = [], K = keys(obj);\n\tfor(var i = 0; i !== K.length; ++i) o[obj[K[i]]] = K[i];\n\treturn o;\n}\n\nfunction evert_num(obj) {\n\tvar o = [], K = keys(obj);\n\tfor(var i = 0; i !== K.length; ++i) o[obj[K[i]]] = parseInt(K[i],10);\n\treturn o;\n}\n\nfunction evert_arr(obj) {\n\tvar o = [], K = keys(obj);\n\tfor(var i = 0; i !== K.length; ++i) {\n\t\tif(o[obj[K[i]]] == null) o[obj[K[i]]] = [];\n\t\to[obj[K[i]]].push(K[i]);\n\t}\n\treturn o;\n}\n\n/* TODO: date1904 logic */\nfunction datenum(v, date1904) {\n\tif(date1904) v+=1462;\n\tvar epoch = Date.parse(v);\n\treturn (epoch + 2209161600000) / (24 * 60 * 60 * 1000);\n}\n\nfunction cc2str(arr) {\n\tvar o = \"\";\n\tfor(var i = 0; i != arr.length; ++i) o += String.fromCharCode(arr[i]);\n\treturn o;\n}\n\nfunction getdata(data) {\n\tif(!data) return null;\n\tif(data.name.substr(-4) === \".bin\") {\n\t\tif(data.data) return char_codes(data.data);\n\t\tif(data.asNodeBuffer && has_buf) return data.asNodeBuffer();\n\t\tif(data._data && data._data.getContent) return Array.prototype.slice.call(data._data.getContent());\n\t} else {\n\t\tif(data.data) return data.name.substr(-4) !== \".bin\" ? debom_xml(data.data) : char_codes(data.data);\n\t\tif(data.asNodeBuffer && has_buf) return debom_xml(data.asNodeBuffer().toString('binary'));\n\t\tif(data.asBinary) return debom_xml(data.asBinary());\n\t\tif(data._data && data._data.getContent) return debom_xml(cc2str(Array.prototype.slice.call(data._data.getContent(),0)));\n\t}\n\treturn null;\n}\n\nfunction safegetzipfile(zip, file) {\n\tvar f = file; if(zip.files[f]) return zip.files[f];\n\tf = file.toLowerCase(); if(zip.files[f]) return zip.files[f];\n\tf = f.replace(/\\//g,'\\\\'); if(zip.files[f]) return zip.files[f];\n\treturn null;\n}\n\nfunction getzipfile(zip, file) {\n\tvar o = safegetzipfile(zip, file);\n\tif(o == null) throw new Error(\"Cannot find file \" + file + \" in zip\");\n\treturn o;\n}\n\nfunction getzipdata(zip, file, safe) {\n\tif(!safe) return getdata(getzipfile(zip, file));\n\tif(!file) return null;\n\ttry { return getzipdata(zip, file); } catch(e) { return null; }\n}\n\nvar _fs, jszip;\nif(typeof JSZip !== 'undefined') jszip = JSZip;\nif (typeof exports !== 'undefined') {\n\tif (typeof module !== 'undefined' && module.exports) {\n\t\tif(has_buf && typeof jszip === 'undefined') jszip = require('js'+'zip');\n\t\tif(typeof jszip === 'undefined') jszip = require('./js'+'zip').JSZip;\n\t\t_fs = require('f'+'s');\n\t}\n}\nvar attregexg=/([\\w:]+)=((?:\")([^\"]*)(?:\")|(?:')([^']*)(?:'))/g;\nvar tagregex=/<[^>]*>/g;\nvar nsregex=/<\\w*:/, nsregex2 = /<(\\/?)\\w+:/;\nfunction parsexmltag(tag, skip_root) {\n\tvar z = [];\n\tvar eq = 0, c = 0;\n\tfor(; eq !== tag.length; ++eq) if((c = tag.charCodeAt(eq)) === 32 || c === 10 || c === 13) break;\n\tif(!skip_root) z[0] = tag.substr(0, eq);\n\tif(eq === tag.length) return z;\n\tvar m = tag.match(attregexg), j=0, w=\"\", v=\"\", i=0, q=\"\", cc=\"\";\n\tif(m) for(i = 0; i != m.length; ++i) {\n\t\tcc = m[i];\n\t\tfor(c=0; c != cc.length; ++c) if(cc.charCodeAt(c) === 61) break;\n\t\tq = cc.substr(0,c); v = cc.substring(c+2, cc.length-1);\n\t\tfor(j=0;j!=q.length;++j) if(q.charCodeAt(j) === 58) break;\n\t\tif(j===q.length) z[q] = v;\n\t\telse z[(j===5 && q.substr(0,5)===\"xmlns\"?\"xmlns\":\"\")+q.substr(j+1)] = v;\n\t}\n\treturn z;\n}\nfunction strip_ns(x) { return x.replace(nsregex2, \"<$1\"); }\n\nvar encodings = {\n\t'&quot;': '\"',\n\t'&apos;': \"'\",\n\t'&gt;': '>',\n\t'&lt;': '<',\n\t'&amp;': '&'\n};\nvar rencoding = evert(encodings);\nvar rencstr = \"&<>'\\\"\".split(\"\");\n\n// TODO: CP remap (need to read file version to determine OS)\nvar unescapexml = (function() {\n\tvar encregex = /&[a-z]*;/g, coderegex = /_x([\\da-fA-F]+)_/g;\n\treturn function unescapexml(text){\n\t\tvar s = text + '';\n\t\treturn s.replace(encregex, function($$) { return encodings[$$]; }).replace(coderegex,function(m,c) {return String.fromCharCode(parseInt(c,16));});\n\t};\n})();\n\nvar decregex=/[&<>'\"]/g, charegex = /[\\u0000-\\u0008\\u000b-\\u001f]/g;\nfunction escapexml(text){\n\tvar s = text + '';\n\treturn s.replace(decregex, function(y) { return rencoding[y]; }).replace(charegex,function(s) { return \"_x\" + (\"000\"+s.charCodeAt(0).toString(16)).substr(-4) + \"_\";});\n}\n\n/* TODO: handle codepages */\nvar xlml_fixstr = (function() {\n\tvar entregex = /&#(\\d+);/g;\n\tfunction entrepl($$,$1) { return String.fromCharCode(parseInt($1,10)); }\n\treturn function xlml_fixstr(str) { return str.replace(entregex,entrepl); };\n})();\n\nfunction parsexmlbool(value, tag) {\n\tswitch(value) {\n\t\tcase '1': case 'true': case 'TRUE': return true;\n\t\t/* case '0': case 'false': case 'FALSE':*/\n\t\tdefault: return false;\n\t}\n}\n\nvar utf8read = function utf8reada(orig) {\n\tvar out = \"\", i = 0, c = 0, d = 0, e = 0, f = 0, w = 0;\n\twhile (i < orig.length) {\n\t\tc = orig.charCodeAt(i++);\n\t\tif (c < 128) { out += String.fromCharCode(c); continue; }\n\t\td = orig.charCodeAt(i++);\n\t\tif (c>191 && c<224) { out += String.fromCharCode(((c & 31) << 6) | (d & 63)); continue; }\n\t\te = orig.charCodeAt(i++);\n\t\tif (c < 240) { out += String.fromCharCode(((c & 15) << 12) | ((d & 63) << 6) | (e & 63)); continue; }\n\t\tf = orig.charCodeAt(i++);\n\t\tw = (((c & 7) << 18) | ((d & 63) << 12) | ((e & 63) << 6) | (f & 63))-65536;\n\t\tout += String.fromCharCode(0xD800 + ((w>>>10)&1023));\n\t\tout += String.fromCharCode(0xDC00 + (w&1023));\n\t}\n\treturn out;\n};\n\n\nif(has_buf) {\n\tvar utf8readb = function utf8readb(data) {\n\t\tvar out = new Buffer(2*data.length), w, i, j = 1, k = 0, ww=0, c;\n\t\tfor(i = 0; i < data.length; i+=j) {\n\t\t\tj = 1;\n\t\t\tif((c=data.charCodeAt(i)) < 128) w = c;\n\t\t\telse if(c < 224) { w = (c&31)*64+(data.charCodeAt(i+1)&63); j=2; }\n\t\t\telse if(c < 240) { w=(c&15)*4096+(data.charCodeAt(i+1)&63)*64+(data.charCodeAt(i+2)&63); j=3; }\n\t\t\telse { j = 4;\n\t\t\t\tw = (c & 7)*262144+(data.charCodeAt(i+1)&63)*4096+(data.charCodeAt(i+2)&63)*64+(data.charCodeAt(i+3)&63);\n\t\t\t\tw -= 65536; ww = 0xD800 + ((w>>>10)&1023); w = 0xDC00 + (w&1023);\n\t\t\t}\n\t\t\tif(ww !== 0) { out[k++] = ww&255; out[k++] = ww>>>8; ww = 0; }\n\t\t\tout[k++] = w%256; out[k++] = w>>>8;\n\t\t}\n\t\tout.length = k;\n\t\treturn out.toString('ucs2');\n\t};\n\tvar corpus = \"foo bar baz\\u00e2\\u0098\\u0083\\u00f0\\u009f\\u008d\\u00a3\";\n\tif(utf8read(corpus) == utf8readb(corpus)) utf8read = utf8readb;\n\tvar utf8readc = function utf8readc(data) { return Buffer(data, 'binary').toString('utf8'); };\n\tif(utf8read(corpus) == utf8readc(corpus)) utf8read = utf8readc;\n}\n\n// matches <foo>...</foo> extracts content\nvar matchtag = (function() {\n\tvar mtcache = {};\n\treturn function matchtag(f,g) {\n\t\tvar t = f+\"|\"+g;\n\t\tif(mtcache[t] !== undefined) return mtcache[t];\n\t\treturn (mtcache[t] = new RegExp('<(?:\\\\w+:)?'+f+'(?: xml:space=\"preserve\")?(?:[^>]*)>([^\\u2603]*)</(?:\\\\w+:)?'+f+'>',(g||\"\")));\n\t};\n})();\n\nvar vtregex = (function(){ var vt_cache = {};\n\treturn function vt_regex(bt) {\n\t\tif(vt_cache[bt] !== undefined) return vt_cache[bt];\n\t\treturn (vt_cache[bt] = new RegExp(\"<vt:\" + bt + \">(.*?)</vt:\" + bt + \">\", 'g') );\n};})();\nvar vtvregex = /<\\/?vt:variant>/g, vtmregex = /<vt:([^>]*)>(.*)</;\nfunction parseVector(data) {\n\tvar h = parsexmltag(data);\n\n\tvar matches = data.match(vtregex(h.baseType))||[];\n\tif(matches.length != h.size) throw \"unexpected vector length \" + matches.length + \" != \" + h.size;\n\tvar res = [];\n\tmatches.forEach(function(x) {\n\t\tvar v = x.replace(vtvregex,\"\").match(vtmregex);\n\t\tres.push({v:v[2], t:v[1]});\n\t});\n\treturn res;\n}\n\nvar wtregex = /(^\\s|\\s$|\\n)/;\nfunction writetag(f,g) {return '<' + f + (g.match(wtregex)?' xml:space=\"preserve\"' : \"\") + '>' + g + '</' + f + '>';}\n\nfunction wxt_helper(h) { return keys(h).map(function(k) { return \" \" + k + '=\"' + h[k] + '\"';}).join(\"\"); }\nfunction writextag(f,g,h) { return '<' + f + (isval(h) ? wxt_helper(h) : \"\") + (isval(g) ? (g.match(wtregex)?' xml:space=\"preserve\"' : \"\") + '>' + g + '</' + f : \"/\") + '>';}\n\nfunction write_w3cdtf(d, t) { try { return d.toISOString().replace(/\\.\\d*/,\"\"); } catch(e) { if(t) throw e; } }\n\nfunction write_vt(s) {\n\tswitch(typeof s) {\n\t\tcase 'string': return writextag('vt:lpwstr', s);\n\t\tcase 'number': return writextag((s|0)==s?'vt:i4':'vt:r8', String(s));\n\t\tcase 'boolean': return writextag('vt:bool',s?'true':'false');\n\t}\n\tif(s instanceof Date) return writextag('vt:filetime', write_w3cdtf(s));\n\tthrow new Error(\"Unable to serialize \" + s);\n}\n\nvar XML_HEADER = '<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?>\\r\\n';\nvar XMLNS = {\n\t'dc': 'http://purl.org/dc/elements/1.1/',\n\t'dcterms': 'http://purl.org/dc/terms/',\n\t'dcmitype': 'http://purl.org/dc/dcmitype/',\n\t'mx': 'http://schemas.microsoft.com/office/mac/excel/2008/main',\n\t'r': 'http://schemas.openxmlformats.org/officeDocument/2006/relationships',\n\t'sjs': 'http://schemas.openxmlformats.org/package/2006/sheetjs/core-properties',\n\t'vt': 'http://schemas.openxmlformats.org/officeDocument/2006/docPropsVTypes',\n\t'xsi': 'http://www.w3.org/2001/XMLSchema-instance',\n\t'xsd': 'http://www.w3.org/2001/XMLSchema'\n};\n\nXMLNS.main = [\n\t'http://schemas.openxmlformats.org/spreadsheetml/2006/main',\n\t'http://purl.oclc.org/ooxml/spreadsheetml/main',\n\t'http://schemas.microsoft.com/office/excel/2006/main',\n\t'http://schemas.microsoft.com/office/excel/2006/2'\n];\n\nfunction readIEEE754(buf, idx, isLE, nl, ml) {\n\tif(isLE === undefined) isLE = true;\n\tif(!nl) nl = 8;\n\tif(!ml && nl === 8) ml = 52;\n\tvar e, m, el = nl * 8 - ml - 1, eMax = (1 << el) - 1, eBias = eMax >> 1;\n\tvar bits = -7, d = isLE ? -1 : 1, i = isLE ? (nl - 1) : 0, s = buf[idx + i];\n\n\ti += d;\n\te = s & ((1 << (-bits)) - 1); s >>>= (-bits); bits += el;\n\tfor (; bits > 0; e = e * 256 + buf[idx + i], i += d, bits -= 8);\n\tm = e & ((1 << (-bits)) - 1); e >>>= (-bits); bits += ml;\n\tfor (; bits > 0; m = m * 256 + buf[idx + i], i += d, bits -= 8);\n\tif (e === eMax) return m ? NaN : ((s ? -1 : 1) * Infinity);\n\telse if (e === 0) e = 1 - eBias;\n\telse { m = m + Math.pow(2, ml); e = e - eBias; }\n\treturn (s ? -1 : 1) * m * Math.pow(2, e - ml);\n}\n\nvar __toBuffer, ___toBuffer;\n__toBuffer = ___toBuffer = function toBuffer_(bufs) { var x = []; for(var i = 0; i < bufs[0].length; ++i) { x.push.apply(x, bufs[0][i]); } return x; };\nvar __utf16le, ___utf16le;\n__utf16le = ___utf16le = function utf16le_(b,s,e) { var ss=[]; for(var i=s; i<e; i+=2) ss.push(String.fromCharCode(__readUInt16LE(b,i))); return ss.join(\"\"); };\nvar __hexlify, ___hexlify;\n__hexlify = ___hexlify = function hexlify_(b,s,l) { return b.slice(s,(s+l)).map(function(x){return (x<16?\"0\":\"\") + x.toString(16);}).join(\"\"); };\nvar __utf8, ___utf8;\n__utf8 = ___utf8 = function(b,s,e) { var ss=[]; for(var i=s; i<e; i++) ss.push(String.fromCharCode(__readUInt8(b,i))); return ss.join(\"\"); };\nvar __lpstr, ___lpstr;\n__lpstr = ___lpstr = function lpstr_(b,i) { var len = __readUInt32LE(b,i); return len > 0 ? __utf8(b, i+4,i+4+len-1) : \"\";};\nvar __lpwstr, ___lpwstr;\n__lpwstr = ___lpwstr = function lpwstr_(b,i) { var len = 2*__readUInt32LE(b,i); return len > 0 ? __utf8(b, i+4,i+4+len-1) : \"\";};\nvar __double, ___double;\n__double = ___double = function(b, idx) { return readIEEE754(b, idx);};\n\nvar is_buf = function is_buf_a(a) { return Array.isArray(a); };\nif(has_buf) {\n\t__utf16le = function utf16le_b(b,s,e) { if(!Buffer.isBuffer(b)) return ___utf16le(b,s,e); return b.toString('utf16le',s,e); };\n\t__hexlify = function(b,s,l) { return Buffer.isBuffer(b) ? b.toString('hex',s,s+l) : ___hexlify(b,s,l); };\n\t__lpstr = function lpstr_b(b,i) { if(!Buffer.isBuffer(b)) return ___lpstr(b, i); var len = b.readUInt32LE(i); return len > 0 ? b.toString('utf8',i+4,i+4+len-1) : \"\";};\n\t__lpwstr = function lpwstr_b(b,i) { if(!Buffer.isBuffer(b)) return ___lpwstr(b, i); var len = 2*b.readUInt32LE(i); return b.toString('utf16le',i+4,i+4+len-1);};\n\t__utf8 = function utf8_b(s,e) { return this.toString('utf8',s,e); };\n\t__toBuffer = function(bufs) { return (bufs[0].length > 0 && Buffer.isBuffer(bufs[0][0])) ? Buffer.concat(bufs[0]) : ___toBuffer(bufs);};\n\tbconcat = function(bufs) { return Buffer.isBuffer(bufs[0]) ? Buffer.concat(bufs) : [].concat.apply([], bufs); };\n\t__double = function double_(b,i) { if(Buffer.isBuffer(b)) return b.readDoubleLE(i); return ___double(b,i); };\n\tis_buf = function is_buf_b(a) { return Buffer.isBuffer(a) || Array.isArray(a); };\n}\n\n/* from js-xls */\nif(typeof cptable !== 'undefined') {\n\t__utf16le = function(b,s,e) { return cptable.utils.decode(1200, b.slice(s,e)); };\n\t__utf8 = function(b,s,e) { return cptable.utils.decode(65001, b.slice(s,e)); };\n\t__lpstr = function(b,i) { var len = __readUInt32LE(b,i); return len > 0 ? cptable.utils.decode(current_codepage, b.slice(i+4, i+4+len-1)) : \"\";};\n\t__lpwstr = function(b,i) { var len = 2*__readUInt32LE(b,i); return len > 0 ? cptable.utils.decode(1200, b.slice(i+4,i+4+len-1)) : \"\";};\n}\n\nvar __readUInt8 = function(b, idx) { return b[idx]; };\nvar __readUInt16LE = function(b, idx) { return b[idx+1]*(1<<8)+b[idx]; };\nvar __readInt16LE = function(b, idx) { var u = b[idx+1]*(1<<8)+b[idx]; return (u < 0x8000) ? u : (0xffff - u + 1) * -1; };\nvar __readUInt32LE = function(b, idx) { return b[idx+3]*(1<<24)+(b[idx+2]<<16)+(b[idx+1]<<8)+b[idx]; };\nvar __readInt32LE = function(b, idx) { return (b[idx+3]<<24)|(b[idx+2]<<16)|(b[idx+1]<<8)|b[idx]; };\n\nvar ___unhexlify = function(s) { return s.match(/../g).map(function(x) { return parseInt(x,16);}); };\nvar __unhexlify = typeof Buffer !== \"undefined\" ? function(s) { return Buffer.isBuffer(s) ? new Buffer(s, 'hex') : ___unhexlify(s); } : ___unhexlify;\n\nfunction ReadShift(size, t) {\n\tvar o=\"\", oI, oR, oo=[], w, vv, i, loc;\n\tswitch(t) {\n\t\tcase 'dbcs':\n\t\t\tloc = this.l;\n\t\t\tif(has_buf && Buffer.isBuffer(this)) o = this.slice(this.l, this.l+2*size).toString(\"utf16le\");\n\t\t\telse for(i = 0; i != size; ++i) { o+=String.fromCharCode(__readUInt16LE(this, loc)); loc+=2; }\n\t\t\tsize *= 2;\n\t\t\tbreak;\n\n\t\tcase 'utf8': o = __utf8(this, this.l, this.l + size); break;\n\t\tcase 'utf16le': size *= 2; o = __utf16le(this, this.l, this.l + size); break;\n\n\t\t/* [MS-OLEDS] 2.1.4 LengthPrefixedAnsiString */\n\t\tcase 'lpstr': o = __lpstr(this, this.l); size = 5 + o.length; break;\n\t\t/* [MS-OLEDS] 2.1.5 LengthPrefixedUnicodeString */\n\t\tcase 'lpwstr': o = __lpwstr(this, this.l); size = 5 + o.length; if(o[o.length-1] == '\\u0000') size += 2; break;\n\n\t\tcase 'cstr': size = 0; o = \"\";\n\t\t\twhile((w=__readUInt8(this, this.l + size++))!==0) oo.push(_getchar(w));\n\t\t\to = oo.join(\"\"); break;\n\t\tcase 'wstr': size = 0; o = \"\";\n\t\t\twhile((w=__readUInt16LE(this,this.l +size))!==0){oo.push(_getchar(w));size+=2;}\n\t\t\tsize+=2; o = oo.join(\"\"); break;\n\n\t\t/* sbcs and dbcs support continue records in the SST way TODO codepages */\n\t\tcase 'dbcs-cont': o = \"\"; loc = this.l;\n\t\t\tfor(i = 0; i != size; ++i) {\n\t\t\t\tif(this.lens && this.lens.indexOf(loc) !== -1) {\n\t\t\t\t\tw = __readUInt8(this, loc);\n\t\t\t\t\tthis.l = loc + 1;\n\t\t\t\t\tvv = ReadShift.call(this, size-i, w ? 'dbcs-cont' : 'sbcs-cont');\n\t\t\t\t\treturn oo.join(\"\") + vv;\n\t\t\t\t}\n\t\t\t\too.push(_getchar(__readUInt16LE(this, loc)));\n\t\t\t\tloc+=2;\n\t\t\t} o = oo.join(\"\"); size *= 2; break;\n\n\t\tcase 'sbcs-cont': o = \"\"; loc = this.l;\n\t\t\tfor(i = 0; i != size; ++i) {\n\t\t\t\tif(this.lens && this.lens.indexOf(loc) !== -1) {\n\t\t\t\t\tw = __readUInt8(this, loc);\n\t\t\t\t\tthis.l = loc + 1;\n\t\t\t\t\tvv = ReadShift.call(this, size-i, w ? 'dbcs-cont' : 'sbcs-cont');\n\t\t\t\t\treturn oo.join(\"\") + vv;\n\t\t\t\t}\n\t\t\t\too.push(_getchar(__readUInt8(this, loc)));\n\t\t\t\tloc+=1;\n\t\t\t} o = oo.join(\"\"); break;\n\n\t\tdefault:\n\tswitch(size) {\n\t\tcase 1: oI = __readUInt8(this, this.l); this.l++; return oI;\n\t\tcase 2: oI = (t === 'i' ? __readInt16LE : __readUInt16LE)(this, this.l); this.l += 2; return oI;\n\t\tcase 4:\n\t\t\tif(t === 'i' || (this[this.l+3] & 0x80)===0) { oI = __readInt32LE(this, this.l); this.l += 4; return oI; }\n\t\t\telse { oR = __readUInt32LE(this, this.l); this.l += 4; return oR; } break;\n\t\tcase 8: if(t === 'f') { oR = __double(this, this.l); this.l += 8; return oR; }\n\t\t/* falls through */\n\t\tcase 16: o = __hexlify(this, this.l, size); break;\n\t}}\n\tthis.l+=size; return o;\n}\n\nfunction WriteShift(t, val, f) {\n\tvar size, i;\n\tif(f === 'dbcs') {\n\t\tfor(i = 0; i != val.length; ++i) this.writeUInt16LE(val.charCodeAt(i), this.l + 2 * i);\n\t\tsize = 2 * val.length;\n\t} else switch(t) {\n\t\tcase  1: size = 1; this[this.l] = val&255; break;\n\t\tcase  3: size = 3; this[this.l+2] = val & 255; val >>>= 8; this[this.l+1] = val&255; val >>>= 8; this[this.l] = val&255; break;\n\t\tcase  4: size = 4; this.writeUInt32LE(val, this.l); break;\n\t\tcase  8: size = 8; if(f === 'f') { this.writeDoubleLE(val, this.l); break; }\n\t\t/* falls through */\n\t\tcase 16: break;\n\t\tcase -4: size = 4; this.writeInt32LE(val, this.l); break;\n\t}\n\tthis.l += size; return this;\n}\n\nfunction CheckField(hexstr, fld) {\n\tvar m = __hexlify(this,this.l,hexstr.length>>1);\n\tif(m !== hexstr) throw fld + 'Expected ' + hexstr + ' saw ' + m;\n\tthis.l += hexstr.length>>1;\n}\n\nfunction prep_blob(blob, pos) {\n\tblob.l = pos;\n\tblob.read_shift = ReadShift;\n\tblob.chk = CheckField;\n\tblob.write_shift = WriteShift;\n}\n\nfunction parsenoop(blob, length) { blob.l += length; }\n\nfunction writenoop(blob, length) { blob.l += length; }\n\nfunction new_buf(sz) {\n\tvar o = new_raw_buf(sz);\n\tprep_blob(o, 0);\n\treturn o;\n}\n\n/* [MS-XLSB] 2.1.4 Record */\nfunction recordhopper(data, cb, opts) {\n\tvar tmpbyte, cntbyte, length;\n\tprep_blob(data, data.l || 0);\n\twhile(data.l < data.length) {\n\t\tvar RT = data.read_shift(1);\n\t\tif(RT & 0x80) RT = (RT & 0x7F) + ((data.read_shift(1) & 0x7F)<<7);\n\t\tvar R = XLSBRecordEnum[RT] || XLSBRecordEnum[0xFFFF];\n\t\ttmpbyte = data.read_shift(1);\n\t\tlength = tmpbyte & 0x7F;\n\t\tfor(cntbyte = 1; cntbyte <4 && (tmpbyte & 0x80); ++cntbyte) length += ((tmpbyte = data.read_shift(1)) & 0x7F)<<(7*cntbyte);\n\t\tvar d = R.f(data, length, opts);\n\t\tif(cb(d, R, RT)) return;\n\t}\n}\n\n/* control buffer usage for fixed-length buffers */\nfunction buf_array() {\n\tvar bufs = [], blksz = 2048;\n\tvar newblk = function ba_newblk(sz) {\n\t\tvar o = new_buf(sz);\n\t\tprep_blob(o, 0);\n\t\treturn o;\n\t};\n\n\tvar curbuf = newblk(blksz);\n\n\tvar endbuf = function ba_endbuf() {\n\t\tcurbuf.length = curbuf.l;\n\t\tif(curbuf.length > 0) bufs.push(curbuf);\n\t\tcurbuf = null;\n\t};\n\n\tvar next = function ba_next(sz) {\n\t\tif(sz < curbuf.length - curbuf.l) return curbuf;\n\t\tendbuf();\n\t\treturn (curbuf = newblk(Math.max(sz+1, blksz)));\n\t};\n\n\tvar end = function ba_end() {\n\t\tendbuf();\n\t\treturn __toBuffer([bufs]);\n\t};\n\n\tvar push = function ba_push(buf) { endbuf(); curbuf = buf; next(blksz); };\n\n\treturn { next:next, push:push, end:end, _bufs:bufs };\n}\n\nfunction write_record(ba, type, payload, length) {\n\tvar t = evert_RE[type], l;\n\tif(!length) length = XLSBRecordEnum[t].p || (payload||[]).length || 0;\n\tl = 1 + (t >= 0x80 ? 1 : 0) + 1 + length;\n\tif(length >= 0x80) ++l; if(length >= 0x4000) ++l; if(length >= 0x200000) ++l;\n\tvar o = ba.next(l);\n\tif(t <= 0x7F) o.write_shift(1, t);\n\telse {\n\t\to.write_shift(1, (t & 0x7F) + 0x80);\n\t\to.write_shift(1, (t >> 7));\n\t}\n\tfor(var i = 0; i != 4; ++i) {\n\t\tif(length >= 0x80) { o.write_shift(1, (length & 0x7F)+0x80); length >>= 7; }\n\t\telse { o.write_shift(1, length); break; }\n\t}\n\tif(length > 0 && is_buf(payload)) ba.push(payload);\n}\n/* XLS ranges enforced */\nfunction shift_cell_xls(cell, tgt) {\n\tif(tgt.s) {\n\t\tif(cell.cRel) cell.c += tgt.s.c;\n\t\tif(cell.rRel) cell.r += tgt.s.r;\n\t} else {\n\t\tcell.c += tgt.c;\n\t\tcell.r += tgt.r;\n\t}\n\tcell.cRel = cell.rRel = 0;\n\twhile(cell.c >= 0x100) cell.c -= 0x100;\n\twhile(cell.r >= 0x10000) cell.r -= 0x10000;\n\treturn cell;\n}\n\nfunction shift_range_xls(cell, range) {\n\tcell.s = shift_cell_xls(cell.s, range.s);\n\tcell.e = shift_cell_xls(cell.e, range.s);\n\treturn cell;\n}\n\nvar OFFCRYPTO = {};\nvar make_offcrypto = function(O, _crypto) {\n\tvar crypto;\n\tif(typeof _crypto !== 'undefined') crypto = _crypto;\n\telse if(typeof require !== 'undefined') {\n\t\ttry { crypto = require('cry'+'pto'); }\n\t\tcatch(e) { crypto = null; }\n\t}\n\n\tO.rc4 = function(key, data) {\n\t\tvar S = new Array(256);\n\t\tvar c = 0, i = 0, j = 0, t = 0;\n\t\tfor(i = 0; i != 256; ++i) S[i] = i;\n\t\tfor(i = 0; i != 256; ++i) {\n\t\t\tj = (j + S[i] + (key[i%key.length]).charCodeAt(0))&255;\n\t\t\tt = S[i]; S[i] = S[j]; S[j] = t;\n\t\t}\n\t\ti = j = 0; out = Buffer(data.length);\n\t\tfor(c = 0; c != data.length; ++c) {\n\t\t\ti = (i + 1)&255;\n\t\t\tj = (j + S[i])%256;\n\t\t\tt = S[i]; S[i] = S[j]; S[j] = t;\n\t\t\tout[c] = (data[c] ^ S[(S[i]+S[j])&255]);\n\t\t}\n\t\treturn out;\n\t};\n\n\tif(crypto) {\n\t\tO.md5 = function(hex) { return crypto.createHash('md5').update(hex).digest('hex'); };\n\t} else {\n\t\tO.md5 = function(hex) { throw \"unimplemented\"; };\n\t}\n};\nmake_offcrypto(OFFCRYPTO, typeof crypto !== \"undefined\" ? crypto : undefined);\n\n\n/* [MS-XLSB] 2.5.143 */\nfunction parse_StrRun(data, length) {\n\treturn { ich: data.read_shift(2), ifnt: data.read_shift(2) };\n}\n\n/* [MS-XLSB] 2.1.7.121 */\nfunction parse_RichStr(data, length) {\n\tvar start = data.l;\n\tvar flags = data.read_shift(1);\n\tvar str = parse_XLWideString(data);\n\tvar rgsStrRun = [];\n\tvar z = { t: str, h: str };\n\tif((flags & 1) !== 0) { /* fRichStr */\n\t\t/* TODO: formatted string */\n\t\tvar dwSizeStrRun = data.read_shift(4);\n\t\tfor(var i = 0; i != dwSizeStrRun; ++i) rgsStrRun.push(parse_StrRun(data));\n\t\tz.r = rgsStrRun;\n\t}\n\telse z.r = \"<t>\" + escapexml(str) + \"</t>\";\n\tif((flags & 2) !== 0) { /* fExtStr */\n\t\t/* TODO: phonetic string */\n\t}\n\tdata.l = start + length;\n\treturn z;\n}\nfunction write_RichStr(str, o) {\n\t/* TODO: formatted string */\n\tif(o == null) o = new_buf(5+2*str.t.length);\n\to.write_shift(1,0);\n\twrite_XLWideString(str.t, o);\n\treturn o;\n}\n\n/* [MS-XLSB] 2.5.9 */\nfunction parse_XLSBCell(data) {\n\tvar col = data.read_shift(4);\n\tvar iStyleRef = data.read_shift(2);\n\tiStyleRef += data.read_shift(1) <<16;\n\tvar fPhShow = data.read_shift(1);\n\treturn { c:col, iStyleRef: iStyleRef };\n}\nfunction write_XLSBCell(cell, o) {\n\tif(o == null) o = new_buf(8);\n\to.write_shift(-4, cell.c);\n\to.write_shift(3, cell.iStyleRef === undefined ? cell.iStyleRef : cell.s);\n\to.write_shift(1, 0); /* fPhShow */\n\treturn o;\n}\n\n\n/* [MS-XLSB] 2.5.21 */\nfunction parse_XLSBCodeName (data, length) { return parse_XLWideString(data, length); }\n\n/* [MS-XLSB] 2.5.166 */\nfunction parse_XLNullableWideString(data) {\n\tvar cchCharacters = data.read_shift(4);\n\treturn cchCharacters === 0 || cchCharacters === 0xFFFFFFFF ? \"\" : data.read_shift(cchCharacters, 'dbcs');\n}\nfunction write_XLNullableWideString(data, o) {\n\tif(!o) o = new_buf(127);\n\to.write_shift(4, data.length > 0 ? data.length : 0xFFFFFFFF);\n\tif(data.length > 0) o.write_shift(0, data, 'dbcs');\n\treturn o;\n}\n\n/* [MS-XLSB] 2.5.168 */\nfunction parse_XLWideString(data) {\n\tvar cchCharacters = data.read_shift(4);\n\treturn cchCharacters === 0 ? \"\" : data.read_shift(cchCharacters, 'dbcs');\n}\nfunction write_XLWideString(data, o) {\n\tif(o == null) o = new_buf(4+2*data.length);\n\to.write_shift(4, data.length);\n\tif(data.length > 0) o.write_shift(0, data, 'dbcs');\n\treturn o;\n}\n\n/* [MS-XLSB] 2.5.114 */\nvar parse_RelID = parse_XLNullableWideString;\nvar write_RelID = write_XLNullableWideString;\n\n\n/* [MS-XLSB] 2.5.122 */\n/* [MS-XLS] 2.5.217 */\nfunction parse_RkNumber(data) {\n\tvar b = data.slice(data.l, data.l+4);\n\tvar fX100 = b[0] & 1, fInt = b[0] & 2;\n\tdata.l+=4;\n\tb[0] &= 0xFC; // b[0] &= ~3;\n\tvar RK = fInt === 0 ? __double([0,0,0,0,b[0],b[1],b[2],b[3]],0) : __readInt32LE(b,0)>>2;\n\treturn fX100 ? RK/100 : RK;\n}\n\n/* [MS-XLSB] 2.5.153 */\nfunction parse_UncheckedRfX(data) {\n\tvar cell = {s: {}, e: {}};\n\tcell.s.r = data.read_shift(4);\n\tcell.e.r = data.read_shift(4);\n\tcell.s.c = data.read_shift(4);\n\tcell.e.c = data.read_shift(4);\n\treturn cell;\n}\n\nfunction write_UncheckedRfX(r, o) {\n\tif(!o) o = new_buf(16);\n\to.write_shift(4, r.s.r);\n\to.write_shift(4, r.e.r);\n\to.write_shift(4, r.s.c);\n\to.write_shift(4, r.e.c);\n\treturn o;\n}\n\n/* [MS-XLSB] 2.5.171 */\n/* [MS-XLS] 2.5.342 */\nfunction parse_Xnum(data, length) { return data.read_shift(8, 'f'); }\nfunction write_Xnum(data, o) { return (o || new_buf(8)).write_shift(8, 'f', data); }\n\n/* [MS-XLSB] 2.5.198.2 */\nvar BErr = {\n\t0x00: \"#NULL!\",\n\t0x07: \"#DIV/0!\",\n\t0x0F: \"#VALUE!\",\n\t0x17: \"#REF!\",\n\t0x1D: \"#NAME?\",\n\t0x24: \"#NUM!\",\n\t0x2A: \"#N/A\",\n\t0x2B: \"#GETTING_DATA\",\n\t0xFF: \"#WTF?\"\n};\nvar RBErr = evert_num(BErr);\n\n/* [MS-XLSB] 2.4.321 BrtColor */\nfunction parse_BrtColor(data, length) {\n\tvar out = {};\n\tvar d = data.read_shift(1);\n\tout.fValidRGB = d & 1;\n\tout.xColorType = d >>> 1;\n\tout.index = data.read_shift(1);\n\tout.nTintAndShade = data.read_shift(2, 'i');\n\tout.bRed   = data.read_shift(1);\n\tout.bGreen = data.read_shift(1);\n\tout.bBlue  = data.read_shift(1);\n\tout.bAlpha = data.read_shift(1);\n}\n\n/* [MS-XLSB] 2.5.52 */\nfunction parse_FontFlags(data, length) {\n\tvar d = data.read_shift(1);\n\tdata.l++;\n\tvar out = {\n\t\tfItalic: d & 0x2,\n\t\tfStrikeout: d & 0x8,\n\t\tfOutline: d & 0x10,\n\t\tfShadow: d & 0x20,\n\t\tfCondense: d & 0x40,\n\t\tfExtend: d & 0x80\n\t};\n\treturn out;\n}\n/* [MS-OLEPS] 2.2 PropertyType */\n{\n\tvar VT_EMPTY    = 0x0000;\n\tvar VT_NULL     = 0x0001;\n\tvar VT_I2       = 0x0002;\n\tvar VT_I4       = 0x0003;\n\tvar VT_R4       = 0x0004;\n\tvar VT_R8       = 0x0005;\n\tvar VT_CY       = 0x0006;\n\tvar VT_DATE     = 0x0007;\n\tvar VT_BSTR     = 0x0008;\n\tvar VT_ERROR    = 0x000A;\n\tvar VT_BOOL     = 0x000B;\n\tvar VT_VARIANT  = 0x000C;\n\tvar VT_DECIMAL  = 0x000E;\n\tvar VT_I1       = 0x0010;\n\tvar VT_UI1      = 0x0011;\n\tvar VT_UI2      = 0x0012;\n\tvar VT_UI4      = 0x0013;\n\tvar VT_I8       = 0x0014;\n\tvar VT_UI8      = 0x0015;\n\tvar VT_INT      = 0x0016;\n\tvar VT_UINT     = 0x0017;\n\tvar VT_LPSTR    = 0x001E;\n\tvar VT_LPWSTR   = 0x001F;\n\tvar VT_FILETIME = 0x0040;\n\tvar VT_BLOB     = 0x0041;\n\tvar VT_STREAM   = 0x0042;\n\tvar VT_STORAGE  = 0x0043;\n\tvar VT_STREAMED_Object  = 0x0044;\n\tvar VT_STORED_Object    = 0x0045;\n\tvar VT_BLOB_Object      = 0x0046;\n\tvar VT_CF       = 0x0047;\n\tvar VT_CLSID    = 0x0048;\n\tvar VT_VERSIONED_STREAM = 0x0049;\n\tvar VT_VECTOR   = 0x1000;\n\tvar VT_ARRAY    = 0x2000;\n\n\tvar VT_STRING   = 0x0050; // 2.3.3.1.11 VtString\n\tvar VT_USTR     = 0x0051; // 2.3.3.1.12 VtUnalignedString\n\tvar VT_CUSTOM   = [VT_STRING, VT_USTR];\n}\n\n/* [MS-OSHARED] 2.3.3.2.2.1 Document Summary Information PIDDSI */\nvar DocSummaryPIDDSI = {\n\t0x01: { n: 'CodePage', t: VT_I2 },\n\t0x02: { n: 'Category', t: VT_STRING },\n\t0x03: { n: 'PresentationFormat', t: VT_STRING },\n\t0x04: { n: 'ByteCount', t: VT_I4 },\n\t0x05: { n: 'LineCount', t: VT_I4 },\n\t0x06: { n: 'ParagraphCount', t: VT_I4 },\n\t0x07: { n: 'SlideCount', t: VT_I4 },\n\t0x08: { n: 'NoteCount', t: VT_I4 },\n\t0x09: { n: 'HiddenCount', t: VT_I4 },\n\t0x0a: { n: 'MultimediaClipCount', t: VT_I4 },\n\t0x0b: { n: 'Scale', t: VT_BOOL },\n\t0x0c: { n: 'HeadingPair', t: VT_VECTOR | VT_VARIANT },\n\t0x0d: { n: 'DocParts', t: VT_VECTOR | VT_LPSTR },\n\t0x0e: { n: 'Manager', t: VT_STRING },\n\t0x0f: { n: 'Company', t: VT_STRING },\n\t0x10: { n: 'LinksDirty', t: VT_BOOL },\n\t0x11: { n: 'CharacterCount', t: VT_I4 },\n\t0x13: { n: 'SharedDoc', t: VT_BOOL },\n\t0x16: { n: 'HLinksChanged', t: VT_BOOL },\n\t0x17: { n: 'AppVersion', t: VT_I4, p: 'version' },\n\t0x1A: { n: 'ContentType', t: VT_STRING },\n\t0x1B: { n: 'ContentStatus', t: VT_STRING },\n\t0x1C: { n: 'Language', t: VT_STRING },\n\t0x1D: { n: 'Version', t: VT_STRING },\n\t0xFF: {}\n};\n\n/* [MS-OSHARED] 2.3.3.2.1.1 Summary Information Property Set PIDSI */\nvar SummaryPIDSI = {\n\t0x01: { n: 'CodePage', t: VT_I2 },\n\t0x02: { n: 'Title', t: VT_STRING },\n\t0x03: { n: 'Subject', t: VT_STRING },\n\t0x04: { n: 'Author', t: VT_STRING },\n\t0x05: { n: 'Keywords', t: VT_STRING },\n\t0x06: { n: 'Comments', t: VT_STRING },\n\t0x07: { n: 'Template', t: VT_STRING },\n\t0x08: { n: 'LastAuthor', t: VT_STRING },\n\t0x09: { n: 'RevNumber', t: VT_STRING },\n\t0x0A: { n: 'EditTime', t: VT_FILETIME },\n\t0x0B: { n: 'LastPrinted', t: VT_FILETIME },\n\t0x0C: { n: 'CreatedDate', t: VT_FILETIME },\n\t0x0D: { n: 'ModifiedDate', t: VT_FILETIME },\n\t0x0E: { n: 'PageCount', t: VT_I4 },\n\t0x0F: { n: 'WordCount', t: VT_I4 },\n\t0x10: { n: 'CharCount', t: VT_I4 },\n\t0x11: { n: 'Thumbnail', t: VT_CF },\n\t0x12: { n: 'ApplicationName', t: VT_LPSTR },\n\t0x13: { n: 'DocumentSecurity', t: VT_I4 },\n\t0xFF: {}\n};\n\n/* [MS-OLEPS] 2.18 */\nvar SpecialProperties = {\n\t0x80000000: { n: 'Locale', t: VT_UI4 },\n\t0x80000003: { n: 'Behavior', t: VT_UI4 },\n\t0x72627262: {}\n};\n\n(function() {\n\tfor(var y in SpecialProperties) if(SpecialProperties.hasOwnProperty(y))\n\tDocSummaryPIDDSI[y] = SummaryPIDSI[y] = SpecialProperties[y];\n})();\n\n/* [MS-XLS] 2.4.63 Country/Region codes */\nvar CountryEnum = {\n\t0x0001: \"US\", // United States\n\t0x0002: \"CA\", // Canada\n\t0x0003: \"\", // Latin America (except Brazil)\n\t0x0007: \"RU\", // Russia\n\t0x0014: \"EG\", // Egypt\n\t0x001E: \"GR\", // Greece\n\t0x001F: \"NL\", // Netherlands\n\t0x0020: \"BE\", // Belgium\n\t0x0021: \"FR\", // France\n\t0x0022: \"ES\", // Spain\n\t0x0024: \"HU\", // Hungary\n\t0x0027: \"IT\", // Italy\n\t0x0029: \"CH\", // Switzerland\n\t0x002B: \"AT\", // Austria\n\t0x002C: \"GB\", // United Kingdom\n\t0x002D: \"DK\", // Denmark\n\t0x002E: \"SE\", // Sweden\n\t0x002F: \"NO\", // Norway\n\t0x0030: \"PL\", // Poland\n\t0x0031: \"DE\", // Germany\n\t0x0034: \"MX\", // Mexico\n\t0x0037: \"BR\", // Brazil\n\t0x003d: \"AU\", // Australia\n\t0x0040: \"NZ\", // New Zealand\n\t0x0042: \"TH\", // Thailand\n\t0x0051: \"JP\", // Japan\n\t0x0052: \"KR\", // Korea\n\t0x0054: \"VN\", // Viet Nam\n\t0x0056: \"CN\", // China\n\t0x005A: \"TR\", // Turkey\n\t0x0069: \"JS\", // Ramastan\n\t0x00D5: \"DZ\", // Algeria\n\t0x00D8: \"MA\", // Morocco\n\t0x00DA: \"LY\", // Libya\n\t0x015F: \"PT\", // Portugal\n\t0x0162: \"IS\", // Iceland\n\t0x0166: \"FI\", // Finland\n\t0x01A4: \"CZ\", // Czech Republic\n\t0x0376: \"TW\", // Taiwan\n\t0x03C1: \"LB\", // Lebanon\n\t0x03C2: \"JO\", // Jordan\n\t0x03C3: \"SY\", // Syria\n\t0x03C4: \"IQ\", // Iraq\n\t0x03C5: \"KW\", // Kuwait\n\t0x03C6: \"SA\", // Saudi Arabia\n\t0x03CB: \"AE\", // United Arab Emirates\n\t0x03CC: \"IL\", // Israel\n\t0x03CE: \"QA\", // Qatar\n\t0x03D5: \"IR\", // Iran\n\t0xFFFF: \"US\"  // United States\n};\n\n/* [MS-XLS] 2.5.127 */\nvar XLSFillPattern = [\n\tnull,\n\t'solid',\n\t'mediumGray',\n\t'darkGray',\n\t'lightGray',\n\t'darkHorizontal',\n\t'darkVertical',\n\t'darkDown',\n\t'darkUp',\n\t'darkGrid',\n\t'darkTrellis',\n\t'lightHorizontal',\n\t'lightVertical',\n\t'lightDown',\n\t'lightUp',\n\t'lightGrid',\n\t'lightTrellis',\n\t'gray125',\n\t'gray0625'\n];\n\nfunction rgbify(arr) { return arr.map(function(x) { return [(x>>16)&255,(x>>8)&255,x&255]; }); }\n\n/* [MS-XLS] 2.5.161 */\nvar XLSIcv = rgbify([\n\t/* Color Constants */\n\t0x000000,\n\t0xFFFFFF,\n\t0xFF0000,\n\t0x00FF00,\n\t0x0000FF,\n\t0xFFFF00,\n\t0xFF00FF,\n\t0x00FFFF,\n\n\t/* Defaults */\n\t0x000000,\n\t0xFFFFFF,\n\t0xFF0000,\n\t0x00FF00,\n\t0x0000FF,\n\t0xFFFF00,\n\t0xFF00FF,\n\t0x00FFFF,\n\n\t0x800000,\n\t0x008000,\n\t0x000080,\n\t0x808000,\n\t0x800080,\n\t0x008080,\n\t0xC0C0C0,\n\t0x808080,\n\t0x9999FF,\n\t0x993366,\n\t0xFFFFCC,\n\t0xCCFFFF,\n\t0x660066,\n\t0xFF8080,\n\t0x0066CC,\n\t0xCCCCFF,\n\n\t0x000080,\n\t0xFF00FF,\n\t0xFFFF00,\n\t0x00FFFF,\n\t0x800080,\n\t0x800000,\n\t0x008080,\n\t0x0000FF,\n\t0x00CCFF,\n\t0xCCFFFF,\n\t0xCCFFCC,\n\t0xFFFF99,\n\t0x99CCFF,\n\t0xFF99CC,\n\t0xCC99FF,\n\t0xFFCC99,\n\n\t0x3366FF,\n\t0x33CCCC,\n\t0x99CC00,\n\t0xFFCC00,\n\t0xFF9900,\n\t0xFF6600,\n\t0x666699,\n\t0x969696,\n\t0x003366,\n\t0x339966,\n\t0x003300,\n\t0x333300,\n\t0x993300,\n\t0x993366,\n\t0x333399,\n\t0x333333,\n\n\t/* Sheet */\n\t0xFFFFFF,\n\t0x000000\n]);\n\n/* Parts enumerated in OPC spec, MS-XLSB and MS-XLSX */\n/* 12.3 Part Summary <SpreadsheetML> */\n/* 14.2 Part Summary <DrawingML> */\n/* [MS-XLSX] 2.1 Part Enumerations */\n/* [MS-XLSB] 2.1.7 Part Enumeration */\nvar ct2type = {\n\t/* Workbook */\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet.main+xml\": \"workbooks\",\n\n\t/* Worksheet */\n\t\"application/vnd.ms-excel.binIndexWs\": \"TODO\", /* Binary Index */\n\n\t/* Chartsheet */\n\t\"application/vnd.ms-excel.chartsheet\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.chartsheet+xml\": \"TODO\",\n\n\t/* Dialogsheet */\n\t\"application/vnd.ms-excel.dialogsheet\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.dialogsheet+xml\": \"TODO\",\n\n\t/* Macrosheet */\n\t\"application/vnd.ms-excel.macrosheet\": \"TODO\",\n\t\"application/vnd.ms-excel.macrosheet+xml\": \"TODO\",\n\t\"application/vnd.ms-excel.intlmacrosheet\": \"TODO\",\n\t\"application/vnd.ms-excel.binIndexMs\": \"TODO\", /* Binary Index */\n\n\t/* File Properties */\n\t\"application/vnd.openxmlformats-package.core-properties+xml\": \"coreprops\",\n\t\"application/vnd.openxmlformats-officedocument.custom-properties+xml\": \"custprops\",\n\t\"application/vnd.openxmlformats-officedocument.extended-properties+xml\": \"extprops\",\n\n\t/* Custom Data Properties */\n\t\"application/vnd.openxmlformats-officedocument.customXmlProperties+xml\": \"TODO\",\n\n\t/* Comments */\n\t\"application/vnd.ms-excel.comments\": \"comments\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.comments+xml\": \"comments\",\n\n\t/* PivotTable */\n\t\"application/vnd.ms-excel.pivotTable\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.pivotTable+xml\": \"TODO\",\n\n\t/* Calculation Chain */\n\t\"application/vnd.ms-excel.calcChain\": \"calcchains\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.calcChain+xml\": \"calcchains\",\n\n\t/* Printer Settings */\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.printerSettings\": \"TODO\",\n\n\t/* ActiveX */\n\t\"application/vnd.ms-office.activeX\": \"TODO\",\n\t\"application/vnd.ms-office.activeX+xml\": \"TODO\",\n\n\t/* Custom Toolbars */\n\t\"application/vnd.ms-excel.attachedToolbars\": \"TODO\",\n\n\t/* External Data Connections */\n\t\"application/vnd.ms-excel.connections\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.connections+xml\": \"TODO\",\n\n\t/* External Links */\n\t\"application/vnd.ms-excel.externalLink\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.externalLink+xml\": \"TODO\",\n\n\t/* Metadata */\n\t\"application/vnd.ms-excel.sheetMetadata\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.sheetMetadata+xml\": \"TODO\",\n\n\t/* PivotCache */\n\t\"application/vnd.ms-excel.pivotCacheDefinition\": \"TODO\",\n\t\"application/vnd.ms-excel.pivotCacheRecords\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.pivotCacheDefinition+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.pivotCacheRecords+xml\": \"TODO\",\n\n\t/* Query Table */\n\t\"application/vnd.ms-excel.queryTable\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.queryTable+xml\": \"TODO\",\n\n\t/* Shared Workbook */\n\t\"application/vnd.ms-excel.userNames\": \"TODO\",\n\t\"application/vnd.ms-excel.revisionHeaders\": \"TODO\",\n\t\"application/vnd.ms-excel.revisionLog\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.revisionHeaders+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.revisionLog+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.userNames+xml\": \"TODO\",\n\n\t/* Single Cell Table */\n\t\"application/vnd.ms-excel.tableSingleCells\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.tableSingleCells+xml\": \"TODO\",\n\n\t/* Slicer */\n\t\"application/vnd.ms-excel.slicer\": \"TODO\",\n\t\"application/vnd.ms-excel.slicerCache\": \"TODO\",\n\t\"application/vnd.ms-excel.slicer+xml\": \"TODO\",\n\t\"application/vnd.ms-excel.slicerCache+xml\": \"TODO\",\n\n\t/* Sort Map */\n\t\"application/vnd.ms-excel.wsSortMap\": \"TODO\",\n\n\t/* Table */\n\t\"application/vnd.ms-excel.table\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.table+xml\": \"TODO\",\n\n\t/* Themes */\n\t\"application/vnd.openxmlformats-officedocument.theme+xml\": \"themes\",\n\n\t/* Timeline */\n\t\"application/vnd.ms-excel.Timeline+xml\": \"TODO\", /* verify */\n\t\"application/vnd.ms-excel.TimelineCache+xml\": \"TODO\", /* verify */\n\n\t/* VBA */\n\t\"application/vnd.ms-office.vbaProject\": \"vba\",\n\t\"application/vnd.ms-office.vbaProjectSignature\": \"vba\",\n\n\t/* Volatile Dependencies */\n\t\"application/vnd.ms-office.volatileDependencies\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.spreadsheetml.volatileDependencies+xml\": \"TODO\",\n\n\t/* Control Properties */\n\t\"application/vnd.ms-excel.controlproperties+xml\": \"TODO\",\n\n\t/* Data Model */\n\t\"application/vnd.openxmlformats-officedocument.model+data\": \"TODO\",\n\n\t/* Survey */\n\t\"application/vnd.ms-excel.Survey+xml\": \"TODO\",\n\n\t/* Drawing */\n\t\"application/vnd.openxmlformats-officedocument.drawing+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.chart+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.chartshapes+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.diagramColors+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.diagramData+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.diagramLayout+xml\": \"TODO\",\n\t\"application/vnd.openxmlformats-officedocument.drawingml.diagramStyle+xml\": \"TODO\",\n\n\t/* VML */\n\t\"application/vnd.openxmlformats-officedocument.vmlDrawing\": \"TODO\",\n\n\t\"application/vnd.openxmlformats-package.relationships+xml\": \"rels\",\n\t\"application/vnd.openxmlformats-officedocument.oleObject\": \"TODO\",\n\n\t\"sheet\": \"js\"\n};\n\nvar CT_LIST = (function(){\n\tvar o = {\n\t\tworkbooks: {\n\t\t\txlsx: \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet.main+xml\",\n\t\t\txlsm: \"application/vnd.ms-excel.sheet.macroEnabled.main+xml\",\n\t\t\txlsb: \"application/vnd.ms-excel.sheet.binary.macroEnabled.main\",\n\t\t\txltx: \"application/vnd.openxmlformats-officedocument.spreadsheetml.template.main+xml\"\n\t\t},\n\t\tstrs: { /* Shared Strings */\n\t\t\txlsx: \"application/vnd.openxmlformats-officedocument.spreadsheetml.sharedStrings+xml\",\n\t\t\txlsb: \"application/vnd.ms-excel.sharedStrings\"\n\t\t},\n\t\tsheets: {\n\t\t\txlsx: \"application/vnd.openxmlformats-officedocument.spreadsheetml.worksheet+xml\",\n\t\t\txlsb: \"application/vnd.ms-excel.worksheet\"\n\t\t},\n\t\tstyles: {/* Styles */\n\t\t\txlsx: \"application/vnd.openxmlformats-officedocument.spreadsheetml.styles+xml\",\n\t\t\txlsb: \"application/vnd.ms-excel.styles\"\n\t\t}\n\t};\n\tkeys(o).forEach(function(k) { if(!o[k].xlsm) o[k].xlsm = o[k].xlsx; });\n\tkeys(o).forEach(function(k){ keys(o[k]).forEach(function(v) { ct2type[o[k][v]] = k; }); });\n\treturn o;\n})();\n\nvar type2ct = evert_arr(ct2type);\n\nXMLNS.CT = 'http://schemas.openxmlformats.org/package/2006/content-types';\n\nfunction parse_ct(data, opts) {\n\tvar ctext = {};\n\tif(!data || !data.match) return data;\n\tvar ct = { workbooks: [], sheets: [], calcchains: [], themes: [], styles: [],\n\t\tcoreprops: [], extprops: [], custprops: [], strs:[], comments: [], vba: [],\n\t\tTODO:[], rels:[], xmlns: \"\" };\n\t(data.match(tagregex)||[]).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(y[0].replace(nsregex,\"<\")) {\n\t\t\tcase '<?xml': break;\n\t\t\tcase '<Types': ct.xmlns = y['xmlns' + (y[0].match(/<(\\w+):/)||[\"\",\"\"])[1] ]; break;\n\t\t\tcase '<Default': ctext[y.Extension] = y.ContentType; break;\n\t\t\tcase '<Override':\n\t\t\t\tif(ct[ct2type[y.ContentType]] !== undefined) ct[ct2type[y.ContentType]].push(y.PartName);\n\t\t\t\telse if(opts.WTF) console.error(y);\n\t\t\t\tbreak;\n\t\t}\n\t});\n\tif(ct.xmlns !== XMLNS.CT) throw new Error(\"Unknown Namespace: \" + ct.xmlns);\n\tct.calcchain = ct.calcchains.length > 0 ? ct.calcchains[0] : \"\";\n\tct.sst = ct.strs.length > 0 ? ct.strs[0] : \"\";\n\tct.style = ct.styles.length > 0 ? ct.styles[0] : \"\";\n\tct.defaults = ctext;\n\tdelete ct.calcchains;\n\treturn ct;\n}\n\nvar CTYPE_XML_ROOT = writextag('Types', null, {\n\t'xmlns': XMLNS.CT,\n\t'xmlns:xsd': XMLNS.xsd,\n\t'xmlns:xsi': XMLNS.xsi\n});\n\nvar CTYPE_DEFAULTS = [\n\t['xml', 'application/xml'],\n\t['bin', 'application/vnd.ms-excel.sheet.binary.macroEnabled.main'],\n\t['rels', type2ct.rels[0]]\n].map(function(x) {\n\treturn writextag('Default', null, {'Extension':x[0], 'ContentType': x[1]});\n});\n\nfunction write_ct(ct, opts) {\n\tvar o = [], v;\n\to[o.length] = (XML_HEADER);\n\to[o.length] = (CTYPE_XML_ROOT);\n\to = o.concat(CTYPE_DEFAULTS);\n\tvar f1 = function(w) {\n\t\tif(ct[w] && ct[w].length > 0) {\n\t\t\tv = ct[w][0];\n\t\t\to[o.length] = (writextag('Override', null, {\n\t\t\t\t'PartName': (v[0] == '/' ? \"\":\"/\") + v,\n\t\t\t\t'ContentType': CT_LIST[w][opts.bookType || 'xlsx']\n\t\t\t}));\n\t\t}\n\t};\n\tvar f2 = function(w) {\n\t\tct[w].forEach(function(v) {\n\t\t\to[o.length] = (writextag('Override', null, {\n\t\t\t\t'PartName': (v[0] == '/' ? \"\":\"/\") + v,\n\t\t\t\t'ContentType': CT_LIST[w][opts.bookType || 'xlsx']\n\t\t\t}));\n\t\t});\n\t};\n\tvar f3 = function(t) {\n\t\t(ct[t]||[]).forEach(function(v) {\n\t\t\to[o.length] = (writextag('Override', null, {\n\t\t\t\t'PartName': (v[0] == '/' ? \"\":\"/\") + v,\n\t\t\t\t'ContentType': type2ct[t][0]\n\t\t\t}));\n\t\t});\n\t};\n\tf1('workbooks');\n\tf2('sheets');\n\tf3('themes');\n\t['strs', 'styles'].forEach(f1);\n\t['coreprops', 'extprops', 'custprops'].forEach(f3);\n\tif(o.length>2){ o[o.length] = ('</Types>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* 9.3.2 OPC Relationships Markup */\nvar RELS = {\n\tWB: \"http://schemas.openxmlformats.org/officeDocument/2006/relationships/officeDocument\",\n\tSHEET: \"http://sheetjs.openxmlformats.org/officeDocument/2006/relationships/officeDocument\"\n};\n\nfunction parse_rels(data, currentFilePath) {\n\tif (!data) return data;\n\tif (currentFilePath.charAt(0) !== '/') {\n\t\tcurrentFilePath = '/'+currentFilePath;\n\t}\n\tvar rels = {};\n\tvar hash = {};\n\tvar resolveRelativePathIntoAbsolute = function (to) {\n\t\tvar toksFrom = currentFilePath.split('/');\n\t\ttoksFrom.pop(); // folder path\n\t\tvar toksTo = to.split('/');\n\t\tvar reversed = [];\n\t\twhile (toksTo.length !== 0) {\n\t\t\tvar tokTo = toksTo.shift();\n\t\t\tif (tokTo === '..') {\n\t\t\t\ttoksFrom.pop();\n\t\t\t} else if (tokTo !== '.') {\n\t\t\t\ttoksFrom.push(tokTo);\n\t\t\t}\n\t\t}\n\t\treturn toksFrom.join('/');\n\t};\n\n\tdata.match(tagregex).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\t/* 9.3.2.2 OPC_Relationships */\n\t\tif (y[0] === '<Relationship') {\n\t\t\tvar rel = {}; rel.Type = y.Type; rel.Target = y.Target; rel.Id = y.Id; rel.TargetMode = y.TargetMode;\n\t\t\tvar canonictarget = y.TargetMode === 'External' ? y.Target : resolveRelativePathIntoAbsolute(y.Target);\n\t\t\trels[canonictarget] = rel;\n\t\t\thash[y.Id] = rel;\n\t\t}\n\t});\n\trels[\"!id\"] = hash;\n\treturn rels;\n}\n\nXMLNS.RELS = 'http://schemas.openxmlformats.org/package/2006/relationships';\n\nvar RELS_ROOT = writextag('Relationships', null, {\n\t//'xmlns:ns0': XMLNS.RELS,\n\t'xmlns': XMLNS.RELS\n});\n\n/* TODO */\nfunction write_rels(rels) {\n\tvar o = [];\n\to[o.length] = (XML_HEADER);\n\to[o.length] = (RELS_ROOT);\n\tkeys(rels['!id']).forEach(function(rid) { var rel = rels['!id'][rid];\n\t\to[o.length] = (writextag('Relationship', null, rel));\n\t});\n\tif(o.length>2){ o[o.length] = ('</Relationships>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* ECMA-376 Part II 11.1 Core Properties Part */\n/* [MS-OSHARED] 2.3.3.2.[1-2].1 (PIDSI/PIDDSI) */\nvar CORE_PROPS = [\n\t[\"cp:category\", \"Category\"],\n\t[\"cp:contentStatus\", \"ContentStatus\"],\n\t[\"cp:keywords\", \"Keywords\"],\n\t[\"cp:lastModifiedBy\", \"LastAuthor\"],\n\t[\"cp:lastPrinted\", \"LastPrinted\"],\n\t[\"cp:revision\", \"RevNumber\"],\n\t[\"cp:version\", \"Version\"],\n\t[\"dc:creator\", \"Author\"],\n\t[\"dc:description\", \"Comments\"],\n\t[\"dc:identifier\", \"Identifier\"],\n\t[\"dc:language\", \"Language\"],\n\t[\"dc:subject\", \"Subject\"],\n\t[\"dc:title\", \"Title\"],\n\t[\"dcterms:created\", \"CreatedDate\", 'date'],\n\t[\"dcterms:modified\", \"ModifiedDate\", 'date']\n];\n\nXMLNS.CORE_PROPS = \"http://schemas.openxmlformats.org/package/2006/metadata/core-properties\";\nRELS.CORE_PROPS  = 'http://schemas.openxmlformats.org/package/2006/relationships/metadata/core-properties';\n\nvar CORE_PROPS_REGEX = (function() {\n\tvar r = new Array(CORE_PROPS.length);\n\tfor(var i = 0; i < CORE_PROPS.length; ++i) {\n\t\tvar f = CORE_PROPS[i];\n\t\tvar g = \"(?:\"+ f[0].substr(0,f[0].indexOf(\":\")) +\":)\"+ f[0].substr(f[0].indexOf(\":\")+1);\n\t\tr[i] = new RegExp(\"<\" + g + \"[^>]*>(.*)<\\/\" + g + \">\");\n\t}\n\treturn r;\n})();\n\nfunction parse_core_props(data) {\n\tvar p = {};\n\n\tfor(var i = 0; i < CORE_PROPS.length; ++i) {\n\t\tvar f = CORE_PROPS[i], cur = data.match(CORE_PROPS_REGEX[i]);\n\t\tif(cur != null && cur.length > 0) p[f[1]] = cur[1];\n\t\tif(f[2] === 'date' && p[f[1]]) p[f[1]] = new Date(p[f[1]]);\n\t}\n\n\treturn p;\n}\n\nvar CORE_PROPS_XML_ROOT = writextag('cp:coreProperties', null, {\n\t//'xmlns': XMLNS.CORE_PROPS,\n\t'xmlns:cp': XMLNS.CORE_PROPS,\n\t'xmlns:dc': XMLNS.dc,\n\t'xmlns:dcterms': XMLNS.dcterms,\n\t'xmlns:dcmitype': XMLNS.dcmitype,\n\t'xmlns:xsi': XMLNS.xsi\n});\n\nfunction cp_doit(f, g, h, o, p) {\n\tif(p[f] != null || g == null || g === \"\") return;\n\tp[f] = g;\n\to[o.length] = (h ? writextag(f,g,h) : writetag(f,g));\n}\n\nfunction write_core_props(cp, opts) {\n\tvar o = [XML_HEADER, CORE_PROPS_XML_ROOT], p = {};\n\tif(!cp) return o.join(\"\");\n\n\n\tif(cp.CreatedDate != null) cp_doit(\"dcterms:created\", typeof cp.CreatedDate === \"string\" ? cp.CreatedDate : write_w3cdtf(cp.CreatedDate, opts.WTF), {\"xsi:type\":\"dcterms:W3CDTF\"}, o, p);\n\tif(cp.ModifiedDate != null) cp_doit(\"dcterms:modified\", typeof cp.ModifiedDate === \"string\" ? cp.ModifiedDate : write_w3cdtf(cp.ModifiedDate, opts.WTF), {\"xsi:type\":\"dcterms:W3CDTF\"}, o, p);\n\n\tfor(var i = 0; i != CORE_PROPS.length; ++i) { var f = CORE_PROPS[i]; cp_doit(f[0], cp[f[1]], null, o, p); }\n\tif(o.length>2){ o[o.length] = ('</cp:coreProperties>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* 15.2.12.3 Extended File Properties Part */\n/* [MS-OSHARED] 2.3.3.2.[1-2].1 (PIDSI/PIDDSI) */\nvar EXT_PROPS = [\n\t[\"Application\", \"Application\", \"string\"],\n\t[\"AppVersion\", \"AppVersion\", \"string\"],\n\t[\"Company\", \"Company\", \"string\"],\n\t[\"DocSecurity\", \"DocSecurity\", \"string\"],\n\t[\"Manager\", \"Manager\", \"string\"],\n\t[\"HyperlinksChanged\", \"HyperlinksChanged\", \"bool\"],\n\t[\"SharedDoc\", \"SharedDoc\", \"bool\"],\n\t[\"LinksUpToDate\", \"LinksUpToDate\", \"bool\"],\n\t[\"ScaleCrop\", \"ScaleCrop\", \"bool\"],\n\t[\"HeadingPairs\", \"HeadingPairs\", \"raw\"],\n\t[\"TitlesOfParts\", \"TitlesOfParts\", \"raw\"]\n];\n\nXMLNS.EXT_PROPS = \"http://schemas.openxmlformats.org/officeDocument/2006/extended-properties\";\nRELS.EXT_PROPS  = 'http://schemas.openxmlformats.org/officeDocument/2006/relationships/extended-properties';\n\nfunction parse_ext_props(data, p) {\n\tvar q = {}; if(!p) p = {};\n\n\tEXT_PROPS.forEach(function(f) {\n\t\tswitch(f[2]) {\n\t\t\tcase \"string\": p[f[1]] = (data.match(matchtag(f[0]))||[])[1]; break;\n\t\t\tcase \"bool\": p[f[1]] = (data.match(matchtag(f[0]))||[])[1] === \"true\"; break;\n\t\t\tcase \"raw\":\n\t\t\t\tvar cur = data.match(new RegExp(\"<\" + f[0] + \"[^>]*>(.*)<\\/\" + f[0] + \">\"));\n\t\t\t\tif(cur && cur.length > 0) q[f[1]] = cur[1];\n\t\t\t\tbreak;\n\t\t}\n\t});\n\n\tif(q.HeadingPairs && q.TitlesOfParts) {\n\t\tvar v = parseVector(q.HeadingPairs);\n\t\tvar j = 0, widx = 0;\n\t\tfor(var i = 0; i !== v.length; ++i) {\n\t\t\tswitch(v[i].v) {\n\t\t\t\tcase \"Worksheets\": widx = j; p.Worksheets = +(v[++i].v); break;\n\t\t\t\tcase \"Named Ranges\": ++i; break; // TODO: Handle Named Ranges\n\t\t\t}\n\t\t}\n\t\tvar parts = parseVector(q.TitlesOfParts).map(function(x) { return utf8read(x.v); });\n\t\tp.SheetNames = parts.slice(widx, widx + p.Worksheets);\n\t}\n\treturn p;\n}\n\nvar EXT_PROPS_XML_ROOT = writextag('Properties', null, {\n\t'xmlns': XMLNS.EXT_PROPS,\n\t'xmlns:vt': XMLNS.vt\n});\n\nfunction write_ext_props(cp, opts) {\n\tvar o = [], p = {}, W = writextag;\n\tif(!cp) cp = {};\n\tcp.Application = \"SheetJS\";\n\to[o.length] = (XML_HEADER);\n\to[o.length] = (EXT_PROPS_XML_ROOT);\n\n\tEXT_PROPS.forEach(function(f) {\n\t\tif(cp[f[1]] === undefined) return;\n\t\tvar v;\n\t\tswitch(f[2]) {\n\t\t\tcase 'string': v = cp[f[1]]; break;\n\t\t\tcase 'bool': v = cp[f[1]] ? 'true' : 'false'; break;\n\t\t}\n\t\tif(v !== undefined) o[o.length] = (W(f[0], v));\n\t});\n\n\t/* TODO: HeadingPairs, TitlesOfParts */\n\to[o.length] = (W('HeadingPairs', W('vt:vector', W('vt:variant', '<vt:lpstr>Worksheets</vt:lpstr>')+W('vt:variant', W('vt:i4', String(cp.Worksheets))), {size:2, baseType:\"variant\"})));\n\to[o.length] = (W('TitlesOfParts', W('vt:vector', cp.SheetNames.map(function(s) { return \"<vt:lpstr>\" + s + \"</vt:lpstr>\"; }).join(\"\"), {size: cp.Worksheets, baseType:\"lpstr\"})));\n\tif(o.length>2){ o[o.length] = ('</Properties>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* 15.2.12.2 Custom File Properties Part */\nXMLNS.CUST_PROPS = \"http://schemas.openxmlformats.org/officeDocument/2006/custom-properties\";\nRELS.CUST_PROPS  = 'http://schemas.openxmlformats.org/officeDocument/2006/relationships/custom-properties';\n\nvar custregex = /<[^>]+>[^<]*/g;\nfunction parse_cust_props(data, opts) {\n\tvar p = {}, name;\n\tvar m = data.match(custregex);\n\tif(m) for(var i = 0; i != m.length; ++i) {\n\t\tvar x = m[i], y = parsexmltag(x);\n\t\tswitch(y[0]) {\n\t\t\tcase '<?xml': break;\n\t\t\tcase '<Properties':\n\t\t\t\tif(y.xmlns !== XMLNS.CUST_PROPS) throw \"unrecognized xmlns \" + y.xmlns;\n\t\t\t\tif(y.xmlnsvt && y.xmlnsvt !== XMLNS.vt) throw \"unrecognized vt \" + y.xmlnsvt;\n\t\t\t\tbreak;\n\t\t\tcase '<property': name = y.name; break;\n\t\t\tcase '</property>': name = null; break;\n\t\t\tdefault: if (x.indexOf('<vt:') === 0) {\n\t\t\t\tvar toks = x.split('>');\n\t\t\t\tvar type = toks[0].substring(4), text = toks[1];\n\t\t\t\t/* 22.4.2.32 (CT_Variant). Omit the binary types from 22.4 (Variant Types) */\n\t\t\t\tswitch(type) {\n\t\t\t\t\tcase 'lpstr': case 'lpwstr': case 'bstr': case 'lpwstr':\n\t\t\t\t\t\tp[name] = unescapexml(text);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase 'bool':\n\t\t\t\t\t\tp[name] = parsexmlbool(text, '<vt:bool>');\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase 'i1': case 'i2': case 'i4': case 'i8': case 'int': case 'uint':\n\t\t\t\t\t\tp[name] = parseInt(text, 10);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase 'r4': case 'r8': case 'decimal':\n\t\t\t\t\t\tp[name] = parseFloat(text);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase 'filetime': case 'date':\n\t\t\t\t\t\tp[name] = new Date(text);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tcase 'cy': case 'error':\n\t\t\t\t\t\tp[name] = unescapexml(text);\n\t\t\t\t\t\tbreak;\n\t\t\t\t\tdefault:\n\t\t\t\t\t\tif(typeof console !== 'undefined') console.warn('Unexpected', x, type, toks);\n\t\t\t\t}\n\t\t\t} else if(x.substr(0,2) === \"</\") {\n\t\t\t} else if(opts.WTF) throw new Error(x);\n\t\t}\n\t}\n\treturn p;\n}\n\nvar CUST_PROPS_XML_ROOT = writextag('Properties', null, {\n\t'xmlns': XMLNS.CUST_PROPS,\n\t'xmlns:vt': XMLNS.vt\n});\n\nfunction write_cust_props(cp, opts) {\n\tvar o = [XML_HEADER, CUST_PROPS_XML_ROOT];\n\tif(!cp) return o.join(\"\");\n\tvar pid = 1;\n\tkeys(cp).forEach(function custprop(k) { ++pid;\n\t\to[o.length] = (writextag('property', write_vt(cp[k]), {\n\t\t\t'fmtid': '{D5CDD505-2E9C-101B-9397-08002B2CF9AE}',\n\t\t\t'pid': pid,\n\t\t\t'name': k\n\t\t}));\n\t});\n\tif(o.length>2){ o[o.length] = '</Properties>'; o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\nfunction xlml_set_prop(Props, tag, val) {\n\t/* TODO: Normalize the properties */\n\tswitch(tag) {\n\t\tcase 'Description': tag = 'Comments'; break;\n\t}\n\tProps[tag] = val;\n}\n\n/* [MS-DTYP] 2.3.3 FILETIME */\n/* [MS-OLEDS] 2.1.3 FILETIME (Packet Version) */\n/* [MS-OLEPS] 2.8 FILETIME (Packet Version) */\nfunction parse_FILETIME(blob) {\n\tvar dwLowDateTime = blob.read_shift(4), dwHighDateTime = blob.read_shift(4);\n\treturn new Date(((dwHighDateTime/1e7*Math.pow(2,32) + dwLowDateTime/1e7) - 11644473600)*1000).toISOString().replace(/\\.000/,\"\");\n}\n\n/* [MS-OSHARED] 2.3.3.1.4 Lpstr */\nfunction parse_lpstr(blob, type, pad) {\n\tvar str = blob.read_shift(0, 'lpstr');\n\tif(pad) blob.l += (4 - ((str.length+1) & 3)) & 3;\n\treturn str;\n}\n\n/* [MS-OSHARED] 2.3.3.1.6 Lpwstr */\nfunction parse_lpwstr(blob, type, pad) {\n\tvar str = blob.read_shift(0, 'lpwstr');\n\tif(pad) blob.l += (4 - ((str.length+1) & 3)) & 3;\n\treturn str;\n}\n\n\n/* [MS-OSHARED] 2.3.3.1.11 VtString */\n/* [MS-OSHARED] 2.3.3.1.12 VtUnalignedString */\nfunction parse_VtStringBase(blob, stringType, pad) {\n\tif(stringType === 0x1F /*VT_LPWSTR*/) return parse_lpwstr(blob);\n\treturn parse_lpstr(blob, stringType, pad);\n}\n\nfunction parse_VtString(blob, t, pad) { return parse_VtStringBase(blob, t, pad === false ? 0: 4); }\nfunction parse_VtUnalignedString(blob, t) { if(!t) throw new Error(\"dafuq?\"); return parse_VtStringBase(blob, t, 0); }\n\n/* [MS-OSHARED] 2.3.3.1.9 VtVecUnalignedLpstrValue */\nfunction parse_VtVecUnalignedLpstrValue(blob) {\n\tvar length = blob.read_shift(4);\n\tvar ret = [];\n\tfor(var i = 0; i != length; ++i) ret[i] = blob.read_shift(0, 'lpstr');\n\treturn ret;\n}\n\n/* [MS-OSHARED] 2.3.3.1.10 VtVecUnalignedLpstr */\nfunction parse_VtVecUnalignedLpstr(blob) {\n\treturn parse_VtVecUnalignedLpstrValue(blob);\n}\n\n/* [MS-OSHARED] 2.3.3.1.13 VtHeadingPair */\nfunction parse_VtHeadingPair(blob) {\n\tvar headingString = parse_TypedPropertyValue(blob, VT_USTR);\n\tvar headerParts = parse_TypedPropertyValue(blob, VT_I4);\n\treturn [headingString, headerParts];\n}\n\n/* [MS-OSHARED] 2.3.3.1.14 VtVecHeadingPairValue */\nfunction parse_VtVecHeadingPairValue(blob) {\n\tvar cElements = blob.read_shift(4);\n\tvar out = [];\n\tfor(var i = 0; i != cElements / 2; ++i) out.push(parse_VtHeadingPair(blob));\n\treturn out;\n}\n\n/* [MS-OSHARED] 2.3.3.1.15 VtVecHeadingPair */\nfunction parse_VtVecHeadingPair(blob) {\n\t// NOTE: When invoked, wType & padding were already consumed\n\treturn parse_VtVecHeadingPairValue(blob);\n}\n\n/* [MS-OLEPS] 2.18.1 Dictionary (uses 2.17, 2.16) */\nfunction parse_dictionary(blob,CodePage) {\n\tvar cnt = blob.read_shift(4);\n\tvar dict = {};\n\tfor(var j = 0; j != cnt; ++j) {\n\t\tvar pid = blob.read_shift(4);\n\t\tvar len = blob.read_shift(4);\n\t\tdict[pid] = blob.read_shift(len, (CodePage === 0x4B0 ?'utf16le':'utf8')).replace(chr0,'').replace(chr1,'!');\n\t}\n\tif(blob.l & 3) blob.l = (blob.l>>2+1)<<2;\n\treturn dict;\n}\n\n/* [MS-OLEPS] 2.9 BLOB */\nfunction parse_BLOB(blob) {\n\tvar size = blob.read_shift(4);\n\tvar bytes = blob.slice(blob.l,blob.l+size);\n\tif(size & 3 > 0) blob.l += (4 - (size & 3)) & 3;\n\treturn bytes;\n}\n\n/* [MS-OLEPS] 2.11 ClipboardData */\nfunction parse_ClipboardData(blob) {\n\t// TODO\n\tvar o = {};\n\to.Size = blob.read_shift(4);\n\t//o.Format = blob.read_shift(4);\n\tblob.l += o.Size;\n\treturn o;\n}\n\n/* [MS-OLEPS] 2.14 Vector and Array Property Types */\nfunction parse_VtVector(blob, cb) {\n\t/* [MS-OLEPS] 2.14.2 VectorHeader */\n/*\tvar Length = blob.read_shift(4);\n\tvar o = [];\n\tfor(var i = 0; i != Length; ++i) {\n\t\to.push(cb(blob));\n\t}\n\treturn o;*/\n}\n\n/* [MS-OLEPS] 2.15 TypedPropertyValue */\nfunction parse_TypedPropertyValue(blob, type, _opts) {\n\tvar t = blob.read_shift(2), ret, opts = _opts||{};\n\tblob.l += 2;\n\tif(type !== VT_VARIANT)\n\tif(t !== type && VT_CUSTOM.indexOf(type)===-1) throw new Error('Expected type ' + type + ' saw ' + t);\n\tswitch(type === VT_VARIANT ? t : type) {\n\t\tcase 0x02 /*VT_I2*/: ret = blob.read_shift(2, 'i'); if(!opts.raw) blob.l += 2; return ret;\n\t\tcase 0x03 /*VT_I4*/: ret = blob.read_shift(4, 'i'); return ret;\n\t\tcase 0x0B /*VT_BOOL*/: return blob.read_shift(4) !== 0x0;\n\t\tcase 0x13 /*VT_UI4*/: ret = blob.read_shift(4); return ret;\n\t\tcase 0x1E /*VT_LPSTR*/: return parse_lpstr(blob, t, 4).replace(chr0,'');\n\t\tcase 0x1F /*VT_LPWSTR*/: return parse_lpwstr(blob);\n\t\tcase 0x40 /*VT_FILETIME*/: return parse_FILETIME(blob);\n\t\tcase 0x41 /*VT_BLOB*/: return parse_BLOB(blob);\n\t\tcase 0x47 /*VT_CF*/: return parse_ClipboardData(blob);\n\t\tcase 0x50 /*VT_STRING*/: return parse_VtString(blob, t, !opts.raw && 4).replace(chr0,'');\n\t\tcase 0x51 /*VT_USTR*/: return parse_VtUnalignedString(blob, t, 4).replace(chr0,'');\n\t\tcase 0x100C /*VT_VECTOR|VT_VARIANT*/: return parse_VtVecHeadingPair(blob);\n\t\tcase 0x101E /*VT_LPSTR*/: return parse_VtVecUnalignedLpstr(blob);\n\t\tdefault: throw new Error(\"TypedPropertyValue unrecognized type \" + type + \" \" + t);\n\t}\n}\n/* [MS-OLEPS] 2.14.2 VectorHeader */\n/*function parse_VTVectorVariant(blob) {\n\tvar Length = blob.read_shift(4);\n\n\tif(Length & 1 !== 0) throw new Error(\"VectorHeader Length=\" + Length + \" must be even\");\n\tvar o = [];\n\tfor(var i = 0; i != Length; ++i) {\n\t\to.push(parse_TypedPropertyValue(blob, VT_VARIANT));\n\t}\n\treturn o;\n}*/\n\n/* [MS-OLEPS] 2.20 PropertySet */\nfunction parse_PropertySet(blob, PIDSI) {\n\tvar start_addr = blob.l;\n\tvar size = blob.read_shift(4);\n\tvar NumProps = blob.read_shift(4);\n\tvar Props = [], i = 0;\n\tvar CodePage = 0;\n\tvar Dictionary = -1, DictObj;\n\tfor(i = 0; i != NumProps; ++i) {\n\t\tvar PropID = blob.read_shift(4);\n\t\tvar Offset = blob.read_shift(4);\n\t\tProps[i] = [PropID, Offset + start_addr];\n\t}\n\tvar PropH = {};\n\tfor(i = 0; i != NumProps; ++i) {\n\t\tif(blob.l !== Props[i][1]) {\n\t\t\tvar fail = true;\n\t\t\tif(i>0 && PIDSI) switch(PIDSI[Props[i-1][0]].t) {\n\t\t\t\tcase 0x02 /*VT_I2*/: if(blob.l +2 === Props[i][1]) { blob.l+=2; fail = false; } break;\n\t\t\t\tcase 0x50 /*VT_STRING*/: if(blob.l <= Props[i][1]) { blob.l=Props[i][1]; fail = false; } break;\n\t\t\t\tcase 0x100C /*VT_VECTOR|VT_VARIANT*/: if(blob.l <= Props[i][1]) { blob.l=Props[i][1]; fail = false; } break;\n\t\t\t}\n\t\t\tif(!PIDSI && blob.l <= Props[i][1]) { fail=false; blob.l = Props[i][1]; }\n\t\t\tif(fail) throw new Error(\"Read Error: Expected address \" + Props[i][1] + ' at ' + blob.l + ' :' + i);\n\t\t}\n\t\tif(PIDSI) {\n\t\t\tvar piddsi = PIDSI[Props[i][0]];\n\t\t\tPropH[piddsi.n] = parse_TypedPropertyValue(blob, piddsi.t, {raw:true});\n\t\t\tif(piddsi.p === 'version') PropH[piddsi.n] = String(PropH[piddsi.n] >> 16) + \".\" + String(PropH[piddsi.n] & 0xFFFF);\n\t\t\tif(piddsi.n == \"CodePage\") switch(PropH[piddsi.n]) {\n\t\t\t\tcase 0: PropH[piddsi.n] = 1252;\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase 10000: // OSX Roman\n\t\t\t\tcase 1252: // Windows Latin\n\n\t\t\t\tcase 874: // SB Windows Thai\n\t\t\t\tcase 1250: // SB Windows Central Europe\n\t\t\t\tcase 1251: // SB Windows Cyrillic\n\t\t\t\tcase 1253: // SB Windows Greek\n\t\t\t\tcase 1254: // SB Windows Turkish\n\t\t\t\tcase 1255: // SB Windows Hebrew\n\t\t\t\tcase 1256: // SB Windows Arabic\n\t\t\t\tcase 1257: // SB Windows Baltic\n\t\t\t\tcase 1258: // SB Windows Vietnam\n\n\t\t\t\tcase 932: // DB Windows Japanese Shift-JIS\n\t\t\t\tcase 936: // DB Windows Simplified Chinese GBK\n\t\t\t\tcase 949: // DB Windows Korean\n\t\t\t\tcase 950: // DB Windows Traditional Chinese Big5\n\n\t\t\t\tcase 1200: // UTF16LE\n\t\t\t\tcase 1201: // UTF16BE\n\t\t\t\tcase 65000: case -536: // UTF-7\n\t\t\t\tcase 65001: case -535: // UTF-8\n\t\t\t\t\tset_cp(CodePage = PropH[piddsi.n]); break;\n\t\t\t\tdefault: throw new Error(\"Unsupported CodePage: \" + PropH[piddsi.n]);\n\t\t\t}\n\t\t} else {\n\t\t\tif(Props[i][0] === 0x1) {\n\t\t\t\tCodePage = PropH.CodePage = parse_TypedPropertyValue(blob, VT_I2);\n\t\t\t\tset_cp(CodePage);\n\t\t\t\tif(Dictionary !== -1) {\n\t\t\t\t\tvar oldpos = blob.l;\n\t\t\t\t\tblob.l = Props[Dictionary][1];\n\t\t\t\t\tDictObj = parse_dictionary(blob,CodePage);\n\t\t\t\t\tblob.l = oldpos;\n\t\t\t\t}\n\t\t\t} else if(Props[i][0] === 0) {\n\t\t\t\tif(CodePage === 0) { Dictionary = i; blob.l = Props[i+1][1]; continue; }\n\t\t\t\tDictObj = parse_dictionary(blob,CodePage);\n\t\t\t} else {\n\t\t\t\tvar name = DictObj[Props[i][0]];\n\t\t\t\tvar val;\n\t\t\t\t/* [MS-OSHARED] 2.3.3.2.3.1.2 + PROPVARIANT */\n\t\t\t\tswitch(blob[blob.l]) {\n\t\t\t\t\tcase 0x41 /*VT_BLOB*/: blob.l += 4; val = parse_BLOB(blob); break;\n\t\t\t\t\tcase 0x1E /*VT_LPSTR*/: blob.l += 4; val = parse_VtString(blob, blob[blob.l-4]); break;\n\t\t\t\t\tcase 0x1F /*VT_LPWSTR*/: blob.l += 4; val = parse_VtString(blob, blob[blob.l-4]); break;\n\t\t\t\t\tcase 0x03 /*VT_I4*/: blob.l += 4; val = blob.read_shift(4, 'i'); break;\n\t\t\t\t\tcase 0x13 /*VT_UI4*/: blob.l += 4; val = blob.read_shift(4); break;\n\t\t\t\t\tcase 0x05 /*VT_R8*/: blob.l += 4; val = blob.read_shift(8, 'f'); break;\n\t\t\t\t\tcase 0x0B /*VT_BOOL*/: blob.l += 4; val = parsebool(blob, 4); break;\n\t\t\t\t\tcase 0x40 /*VT_FILETIME*/: blob.l += 4; val = new Date(parse_FILETIME(blob)); break;\n\t\t\t\t\tdefault: throw new Error(\"unparsed value: \" + blob[blob.l]);\n\t\t\t\t}\n\t\t\t\tPropH[name] = val;\n\t\t\t}\n\t\t}\n\t}\n\tblob.l = start_addr + size; /* step ahead to skip padding */\n\treturn PropH;\n}\n\n/* [MS-OLEPS] 2.21 PropertySetStream */\nfunction parse_PropertySetStream(file, PIDSI) {\n\tvar blob = file.content;\n\tprep_blob(blob, 0);\n\n\tvar NumSets, FMTID0, FMTID1, Offset0, Offset1;\n\tblob.chk('feff', 'Byte Order: ');\n\n\tvar vers = blob.read_shift(2); // TODO: check version\n\tvar SystemIdentifier = blob.read_shift(4);\n\tblob.chk(CFB.utils.consts.HEADER_CLSID, 'CLSID: ');\n\tNumSets = blob.read_shift(4);\n\tif(NumSets !== 1 && NumSets !== 2) throw \"Unrecognized #Sets: \" + NumSets;\n\tFMTID0 = blob.read_shift(16); Offset0 = blob.read_shift(4);\n\n\tif(NumSets === 1 && Offset0 !== blob.l) throw \"Length mismatch\";\n\telse if(NumSets === 2) { FMTID1 = blob.read_shift(16); Offset1 = blob.read_shift(4); }\n\tvar PSet0 = parse_PropertySet(blob, PIDSI);\n\n\tvar rval = { SystemIdentifier: SystemIdentifier };\n\tfor(var y in PSet0) rval[y] = PSet0[y];\n\t//rval.blob = blob;\n\trval.FMTID = FMTID0;\n\t//rval.PSet0 = PSet0;\n\tif(NumSets === 1) return rval;\n\tif(blob.l !== Offset1) throw \"Length mismatch 2: \" + blob.l + \" !== \" + Offset1;\n\tvar PSet1;\n\ttry { PSet1 = parse_PropertySet(blob, null); } catch(e) { }\n\tfor(y in PSet1) rval[y] = PSet1[y];\n\trval.FMTID = [FMTID0, FMTID1]; // TODO: verify FMTID0/1\n\treturn rval;\n}\n\n\nfunction parsenoop2(blob, length) { blob.read_shift(length); return null; }\n\nfunction parslurp(blob, length, cb) {\n\tvar arr = [], target = blob.l + length;\n\twhile(blob.l < target) arr.push(cb(blob, target - blob.l));\n\tif(target !== blob.l) throw new Error(\"Slurp error\");\n\treturn arr;\n}\n\nfunction parslurp2(blob, length, cb) {\n\tvar arr = [], target = blob.l + length, len = blob.read_shift(2);\n\twhile(len-- !== 0) arr.push(cb(blob, target - blob.l));\n\tif(target !== blob.l) throw new Error(\"Slurp error\");\n\treturn arr;\n}\n\nfunction parsebool(blob, length) { return blob.read_shift(length) === 0x1; }\n\nfunction parseuint16(blob) { return blob.read_shift(2, 'u'); }\nfunction parseuint16a(blob, length) { return parslurp(blob,length,parseuint16);}\n\n/* --- 2.5 Structures --- */\n\n/* [MS-XLS] 2.5.14 Boolean */\nvar parse_Boolean = parsebool;\n\n/* [MS-XLS] 2.5.10 Bes (boolean or error) */\nfunction parse_Bes(blob) {\n\tvar v = blob.read_shift(1), t = blob.read_shift(1);\n\treturn t === 0x01 ? v : v === 0x01;\n}\n\n/* [MS-XLS] 2.5.240 ShortXLUnicodeString */\nfunction parse_ShortXLUnicodeString(blob, length, opts) {\n\tvar cch = blob.read_shift(1);\n\tvar width = 1, encoding = 'sbcs-cont';\n\tvar cp = current_codepage;\n\tif(opts && opts.biff >= 8) current_codepage = 1200;\n\tif(opts === undefined || opts.biff !== 5) {\n\t\tvar fHighByte = blob.read_shift(1);\n\t\tif(fHighByte) { width = 2; encoding = 'dbcs-cont'; }\n\t}\n\tvar o = cch ? blob.read_shift(cch, encoding) : \"\";\n\tcurrent_codepage = cp;\n\treturn o;\n}\n\n/* 2.5.293 XLUnicodeRichExtendedString */\nfunction parse_XLUnicodeRichExtendedString(blob) {\n\tvar cp = current_codepage;\n\tcurrent_codepage = 1200;\n\tvar cch = blob.read_shift(2), flags = blob.read_shift(1);\n\tvar fHighByte = flags & 0x1, fExtSt = flags & 0x4, fRichSt = flags & 0x8;\n\tvar width = 1 + (flags & 0x1); // 0x0 -> utf8, 0x1 -> dbcs\n\tvar cRun, cbExtRst;\n\tvar z = {};\n\tif(fRichSt) cRun = blob.read_shift(2);\n\tif(fExtSt) cbExtRst = blob.read_shift(4);\n\tvar encoding = (flags & 0x1) ? 'dbcs-cont' : 'sbcs-cont';\n\tvar msg = cch === 0 ? \"\" : blob.read_shift(cch, encoding);\n\tif(fRichSt) blob.l += 4 * cRun; //TODO: parse this\n\tif(fExtSt) blob.l += cbExtRst; //TODO: parse this\n\tz.t = msg;\n\tif(!fRichSt) { z.raw = \"<t>\" + z.t + \"</t>\"; z.r = z.t; }\n\tcurrent_codepage = cp;\n\treturn z;\n}\n\n/* 2.5.296 XLUnicodeStringNoCch */\nfunction parse_XLUnicodeStringNoCch(blob, cch, opts) {\n\tvar retval;\n\tvar fHighByte = blob.read_shift(1);\n\tif(fHighByte===0) { retval = blob.read_shift(cch, 'sbcs-cont'); }\n\telse { retval = blob.read_shift(cch, 'dbcs-cont'); }\n\treturn retval;\n}\n\n/* 2.5.294 XLUnicodeString */\nfunction parse_XLUnicodeString(blob, length, opts) {\n\tvar cch = blob.read_shift(opts !== undefined && opts.biff > 0 && opts.biff < 8 ? 1 : 2);\n\tif(cch === 0) { blob.l++; return \"\"; }\n\treturn parse_XLUnicodeStringNoCch(blob, cch, opts);\n}\n/* BIFF5 override */\nfunction parse_XLUnicodeString2(blob, length, opts) {\n\tif(opts.biff !== 5 && opts.biff !== 2) return parse_XLUnicodeString(blob, length, opts);\n\tvar cch = blob.read_shift(1);\n\tif(cch === 0) { blob.l++; return \"\"; }\n\treturn blob.read_shift(cch, 'sbcs-cont');\n}\n\n/* [MS-XLS] 2.5.61 ControlInfo */\nvar parse_ControlInfo = parsenoop;\n\n/* [MS-OSHARED] 2.3.7.6 URLMoniker TODO: flags */\nvar parse_URLMoniker = function(blob, length) {\n\tvar len = blob.read_shift(4), start = blob.l;\n\tvar extra = false;\n\tif(len > 24) {\n\t\t/* look ahead */\n\t\tblob.l += len - 24;\n\t\tif(blob.read_shift(16) === \"795881f43b1d7f48af2c825dc4852763\") extra = true;\n\t\tblob.l = start;\n\t}\n\tvar url = blob.read_shift((extra?len-24:len)>>1, 'utf16le').replace(chr0,\"\");\n\tif(extra) blob.l += 24;\n\treturn url;\n};\n\n/* [MS-OSHARED] 2.3.7.8 FileMoniker TODO: all fields */\nvar parse_FileMoniker = function(blob, length) {\n\tvar cAnti = blob.read_shift(2);\n\tvar ansiLength = blob.read_shift(4);\n\tvar ansiPath = blob.read_shift(ansiLength, 'cstr');\n\tvar endServer = blob.read_shift(2);\n\tvar versionNumber = blob.read_shift(2);\n\tvar cbUnicodePathSize = blob.read_shift(4);\n\tif(cbUnicodePathSize === 0) return ansiPath.replace(/\\\\/g,\"/\");\n\tvar cbUnicodePathBytes = blob.read_shift(4);\n\tvar usKeyValue = blob.read_shift(2);\n\tvar unicodePath = blob.read_shift(cbUnicodePathBytes>>1, 'utf16le').replace(chr0,\"\");\n\treturn unicodePath;\n};\n\n/* [MS-OSHARED] 2.3.7.2 HyperlinkMoniker TODO: all the monikers */\nvar parse_HyperlinkMoniker = function(blob, length) {\n\tvar clsid = blob.read_shift(16); length -= 16;\n\tswitch(clsid) {\n\t\tcase \"e0c9ea79f9bace118c8200aa004ba90b\": return parse_URLMoniker(blob, length);\n\t\tcase \"0303000000000000c000000000000046\": return parse_FileMoniker(blob, length);\n\t\tdefault: throw \"unsupported moniker \" + clsid;\n\t}\n};\n\n/* [MS-OSHARED] 2.3.7.9 HyperlinkString */\nvar parse_HyperlinkString = function(blob, length) {\n\tvar len = blob.read_shift(4);\n\tvar o = blob.read_shift(len, 'utf16le').replace(chr0, \"\");\n\treturn o;\n};\n\n/* [MS-OSHARED] 2.3.7.1 Hyperlink Object TODO: unify params with XLSX */\nvar parse_Hyperlink = function(blob, length) {\n\tvar end = blob.l + length;\n\tvar sVer = blob.read_shift(4);\n\tif(sVer !== 2) throw new Error(\"Unrecognized streamVersion: \" + sVer);\n\tvar flags = blob.read_shift(2);\n\tblob.l += 2;\n\tvar displayName, targetFrameName, moniker, oleMoniker, location, guid, fileTime;\n\tif(flags & 0x0010) displayName = parse_HyperlinkString(blob, end - blob.l);\n\tif(flags & 0x0080) targetFrameName = parse_HyperlinkString(blob, end - blob.l);\n\tif((flags & 0x0101) === 0x0101) moniker = parse_HyperlinkString(blob, end - blob.l);\n\tif((flags & 0x0101) === 0x0001) oleMoniker = parse_HyperlinkMoniker(blob, end - blob.l);\n\tif(flags & 0x0008) location = parse_HyperlinkString(blob, end - blob.l);\n\tif(flags & 0x0020) guid = blob.read_shift(16);\n\tif(flags & 0x0040) fileTime = parse_FILETIME(blob, 8);\n\tblob.l = end;\n\tvar target = (targetFrameName||moniker||oleMoniker);\n\tif(location) target+=\"#\"+location;\n\treturn {Target: target};\n};\n\n/* 2.5.178 LongRGBA */\nfunction parse_LongRGBA(blob, length) { var r = blob.read_shift(1), g = blob.read_shift(1), b = blob.read_shift(1), a = blob.read_shift(1); return [r,g,b,a]; }\n\n/* 2.5.177 LongRGB */\nfunction parse_LongRGB(blob, length) { var x = parse_LongRGBA(blob, length); x[3] = 0; return x; }\n\n\n/* --- MS-XLS --- */\n\n/* 2.5.19 */\nfunction parse_XLSCell(blob, length) {\n\tvar rw = blob.read_shift(2); // 0-indexed\n\tvar col = blob.read_shift(2);\n\tvar ixfe = blob.read_shift(2);\n\treturn {r:rw, c:col, ixfe:ixfe};\n}\n\n/* 2.5.134 */\nfunction parse_frtHeader(blob) {\n\tvar rt = blob.read_shift(2);\n\tvar flags = blob.read_shift(2); // TODO: parse these flags\n\tblob.l += 8;\n\treturn {type: rt, flags: flags};\n}\n\n\n\nfunction parse_OptXLUnicodeString(blob, length, opts) { return length === 0 ? \"\" : parse_XLUnicodeString2(blob, length, opts); }\n\n/* 2.5.158 */\nvar HIDEOBJENUM = ['SHOWALL', 'SHOWPLACEHOLDER', 'HIDEALL'];\nvar parse_HideObjEnum = parseuint16;\n\n/* 2.5.344 */\nfunction parse_XTI(blob, length) {\n\tvar iSupBook = blob.read_shift(2), itabFirst = blob.read_shift(2,'i'), itabLast = blob.read_shift(2,'i');\n\treturn [iSupBook, itabFirst, itabLast];\n}\n\n/* 2.5.218 */\nfunction parse_RkRec(blob, length) {\n\tvar ixfe = blob.read_shift(2);\n\tvar RK = parse_RkNumber(blob);\n\t//console.log(\"::\", ixfe, RK,\";;\");\n\treturn [ixfe, RK];\n}\n\n/* 2.5.1 */\nfunction parse_AddinUdf(blob, length) {\n\tblob.l += 4; length -= 4;\n\tvar l = blob.l + length;\n\tvar udfName = parse_ShortXLUnicodeString(blob, length);\n\tvar cb = blob.read_shift(2);\n\tl -= blob.l;\n\tif(cb !== l) throw \"Malformed AddinUdf: padding = \" + l + \" != \" + cb;\n\tblob.l += cb;\n\treturn udfName;\n}\n\n/* 2.5.209 TODO: Check sizes */\nfunction parse_Ref8U(blob, length) {\n\tvar rwFirst = blob.read_shift(2);\n\tvar rwLast = blob.read_shift(2);\n\tvar colFirst = blob.read_shift(2);\n\tvar colLast = blob.read_shift(2);\n\treturn {s:{c:colFirst, r:rwFirst}, e:{c:colLast,r:rwLast}};\n}\n\n/* 2.5.211 */\nfunction parse_RefU(blob, length) {\n\tvar rwFirst = blob.read_shift(2);\n\tvar rwLast = blob.read_shift(2);\n\tvar colFirst = blob.read_shift(1);\n\tvar colLast = blob.read_shift(1);\n\treturn {s:{c:colFirst, r:rwFirst}, e:{c:colLast,r:rwLast}};\n}\n\n/* 2.5.207 */\nvar parse_Ref = parse_RefU;\n\n/* 2.5.143 */\nfunction parse_FtCmo(blob, length) {\n\tblob.l += 4;\n\tvar ot = blob.read_shift(2);\n\tvar id = blob.read_shift(2);\n\tvar flags = blob.read_shift(2);\n\tblob.l+=12;\n\treturn [id, ot, flags];\n}\n\n/* 2.5.149 */\nfunction parse_FtNts(blob, length) {\n\tvar out = {};\n\tblob.l += 4;\n\tblob.l += 16; // GUID TODO\n\tout.fSharedNote = blob.read_shift(2);\n\tblob.l += 4;\n\treturn out;\n}\n\n/* 2.5.142 */\nfunction parse_FtCf(blob, length) {\n\tvar out = {};\n\tblob.l += 4;\n\tblob.cf = blob.read_shift(2);\n\treturn out;\n}\n\n/* 2.5.140 - 2.5.154 and friends */\nvar FtTab = {\n\t0x15: parse_FtCmo,\n\t0x13: parsenoop,                                /* FtLbsData */\n\t0x12: function(blob, length) { blob.l += 12; }, /* FtCblsData */\n\t0x11: function(blob, length) { blob.l += 8; },  /* FtRboData */\n\t0x10: parsenoop,                                /* FtEdoData */\n\t0x0F: parsenoop,                                /* FtGboData */\n\t0x0D: parse_FtNts,                              /* FtNts */\n\t0x0C: function(blob, length) { blob.l += 24; }, /* FtSbs */\n\t0x0B: function(blob, length) { blob.l += 10; }, /* FtRbo */\n\t0x0A: function(blob, length) { blob.l += 16; }, /* FtCbls */\n\t0x09: parsenoop,                                /* FtPictFmla */\n\t0x08: function(blob, length) { blob.l += 6; },  /* FtPioGrbit */\n\t0x07: parse_FtCf,                               /* FtCf */\n\t0x06: function(blob, length) { blob.l += 6; },  /* FtGmo */\n\t0x04: parsenoop,                                /* FtMacro */\n\t0x00: function(blob, length) { blob.l += 4; }   /* FtEnding */\n};\nfunction parse_FtArray(blob, length, ot) {\n\tvar s = blob.l;\n\tvar fts = [];\n\twhile(blob.l < s + length) {\n\t\tvar ft = blob.read_shift(2);\n\t\tblob.l-=2;\n\t\ttry {\n\t\t\tfts.push(FtTab[ft](blob, s + length - blob.l));\n\t\t} catch(e) { blob.l = s + length; return fts; }\n\t}\n\tif(blob.l != s + length) blob.l = s + length; //throw \"bad Object Ft-sequence\";\n\treturn fts;\n}\n\n/* 2.5.129 */\nvar parse_FontIndex = parseuint16;\n\n/* --- 2.4 Records --- */\n\n/* 2.4.21 */\nfunction parse_BOF(blob, length) {\n\tvar o = {};\n\to.BIFFVer = blob.read_shift(2); length -= 2;\n\tswitch(o.BIFFVer) {\n\t\tcase 0x0600: /* BIFF8 */\n\t\tcase 0x0500: /* BIFF5 */\n\t\tcase 0x0002: case 0x0007: /* BIFF2 */\n\t\t\tbreak;\n\t\tdefault: throw \"Unexpected BIFF Ver \" + o.BIFFVer;\n\t}\n\tblob.read_shift(length);\n\treturn o;\n}\n\n\n/* 2.4.146 */\nfunction parse_InterfaceHdr(blob, length) {\n\tif(length === 0) return 0x04b0;\n\tvar q;\n\tif((q=blob.read_shift(2))!==0x04b0) throw 'InterfaceHdr codePage ' + q;\n\treturn 0x04b0;\n}\n\n\n/* 2.4.349 */\nfunction parse_WriteAccess(blob, length, opts) {\n\tif(opts.enc) { blob.l += length; return \"\"; }\n\tvar l = blob.l;\n\t// TODO: make sure XLUnicodeString doesnt overrun\n\tvar UserName = parse_XLUnicodeString(blob, 0, opts);\n\tblob.read_shift(length + l - blob.l);\n\treturn UserName;\n}\n\n/* 2.4.28 */\nfunction parse_BoundSheet8(blob, length, opts) {\n\tvar pos = blob.read_shift(4);\n\tvar hidden = blob.read_shift(1) >> 6;\n\tvar dt = blob.read_shift(1);\n\tswitch(dt) {\n\t\tcase 0: dt = 'Worksheet'; break;\n\t\tcase 1: dt = 'Macrosheet'; break;\n\t\tcase 2: dt = 'Chartsheet'; break;\n\t\tcase 6: dt = 'VBAModule'; break;\n\t}\n\tvar name = parse_ShortXLUnicodeString(blob, 0, opts);\n\tif(name.length === 0) name = \"Sheet1\";\n\treturn { pos:pos, hs:hidden, dt:dt, name:name };\n}\n\n/* 2.4.265 TODO */\nfunction parse_SST(blob, length) {\n\tvar cnt = blob.read_shift(4);\n\tvar ucnt = blob.read_shift(4);\n\tvar strs = [];\n\tfor(var i = 0; i != ucnt; ++i) {\n\t\tstrs.push(parse_XLUnicodeRichExtendedString(blob));\n\t}\n\tstrs.Count = cnt; strs.Unique = ucnt;\n\treturn strs;\n}\n\n/* 2.4.107 */\nfunction parse_ExtSST(blob, length) {\n\tvar extsst = {};\n\textsst.dsst = blob.read_shift(2);\n\tblob.l += length-2;\n\treturn extsst;\n}\n\n\n/* 2.4.221 TODO*/\nfunction parse_Row(blob, length) {\n\tvar rw = blob.read_shift(2), col = blob.read_shift(2), Col = blob.read_shift(2), rht = blob.read_shift(2);\n\tblob.read_shift(4); // reserved(2), unused(2)\n\tvar flags = blob.read_shift(1); // various flags\n\tblob.read_shift(1); // reserved\n\tblob.read_shift(2); //ixfe, other flags\n\treturn {r:rw, c:col, cnt:Col-col};\n}\n\n\n/* 2.4.125 */\nfunction parse_ForceFullCalculation(blob, length) {\n\tvar header = parse_frtHeader(blob);\n\tif(header.type != 0x08A3) throw \"Invalid Future Record \" + header.type;\n\tvar fullcalc = blob.read_shift(4);\n\treturn fullcalc !== 0x0;\n}\n\n\nvar parse_CompressPictures = parsenoop2; /* 2.4.55 Not interesting */\n\n\n\n/* 2.4.215 rt */\nfunction parse_RecalcId(blob, length) {\n\tblob.read_shift(2);\n\treturn blob.read_shift(4);\n}\n\n/* 2.4.87 */\nfunction parse_DefaultRowHeight (blob, length) {\n\tvar f = blob.read_shift(2), miyRw;\n\tmiyRw = blob.read_shift(2); // flags & 0x02 -> hidden, else empty\n\tvar fl = {Unsynced:f&1,DyZero:(f&2)>>1,ExAsc:(f&4)>>2,ExDsc:(f&8)>>3};\n\treturn [fl, miyRw];\n}\n\n/* 2.4.345 TODO */\nfunction parse_Window1(blob, length) {\n\tvar xWn = blob.read_shift(2), yWn = blob.read_shift(2), dxWn = blob.read_shift(2), dyWn = blob.read_shift(2);\n\tvar flags = blob.read_shift(2), iTabCur = blob.read_shift(2), iTabFirst = blob.read_shift(2);\n\tvar ctabSel = blob.read_shift(2), wTabRatio = blob.read_shift(2);\n\treturn { Pos: [xWn, yWn], Dim: [dxWn, dyWn], Flags: flags, CurTab: iTabCur,\n\t\tFirstTab: iTabFirst, Selected: ctabSel, TabRatio: wTabRatio };\n}\n\n/* 2.4.122 TODO */\nfunction parse_Font(blob, length, opts) {\n\tblob.l += 14;\n\tvar name = parse_ShortXLUnicodeString(blob, 0, opts);\n\treturn name;\n}\n\n/* 2.4.149 */\nfunction parse_LabelSst(blob, length) {\n\tvar cell = parse_XLSCell(blob);\n\tcell.isst = blob.read_shift(4);\n\treturn cell;\n}\n\n/* 2.4.148 */\nfunction parse_Label(blob, length, opts) {\n\tvar cell = parse_XLSCell(blob, 6);\n\tvar str = parse_XLUnicodeString(blob, length-6, opts);\n\tcell.val = str;\n\treturn cell;\n}\n\n/* 2.4.126 Number Formats */\nfunction parse_Format(blob, length, opts) {\n\tvar ifmt = blob.read_shift(2);\n\tvar fmtstr = parse_XLUnicodeString2(blob, 0, opts);\n\treturn [ifmt, fmtstr];\n}\n\n/* 2.4.90 */\nfunction parse_Dimensions(blob, length) {\n\tvar w = length === 10 ? 2 : 4;\n\tvar r = blob.read_shift(w), R = blob.read_shift(w),\n\t    c = blob.read_shift(2), C = blob.read_shift(2);\n\tblob.l += 2;\n\treturn {s: {r:r, c:c}, e: {r:R, c:C}};\n}\n\n/* 2.4.220 */\nfunction parse_RK(blob, length) {\n\tvar rw = blob.read_shift(2), col = blob.read_shift(2);\n\tvar rkrec = parse_RkRec(blob);\n\treturn {r:rw, c:col, ixfe:rkrec[0], rknum:rkrec[1]};\n}\n\n/* 2.4.175 */\nfunction parse_MulRk(blob, length) {\n\tvar target = blob.l + length - 2;\n\tvar rw = blob.read_shift(2), col = blob.read_shift(2);\n\tvar rkrecs = [];\n\twhile(blob.l < target) rkrecs.push(parse_RkRec(blob));\n\tif(blob.l !== target) throw \"MulRK read error\";\n\tvar lastcol = blob.read_shift(2);\n\tif(rkrecs.length != lastcol - col + 1) throw \"MulRK length mismatch\";\n\treturn {r:rw, c:col, C:lastcol, rkrec:rkrecs};\n}\n\n/* 2.5.20 2.5.249 TODO */\nfunction parse_CellStyleXF(blob, length, style) {\n\tvar o = {};\n\tvar a = blob.read_shift(4), b = blob.read_shift(4);\n\tvar c = blob.read_shift(4), d = blob.read_shift(2);\n\to.patternType = XLSFillPattern[c >> 26];\n\to.icvFore = d & 0x7F;\n\to.icvBack = (d >> 7) & 0x7F;\n\treturn o;\n}\nfunction parse_CellXF(blob, length) {return parse_CellStyleXF(blob,length,0);}\nfunction parse_StyleXF(blob, length) {return parse_CellStyleXF(blob,length,1);}\n\n/* 2.4.353 TODO: actually do this right */\nfunction parse_XF(blob, length) {\n\tvar o = {};\n\to.ifnt = blob.read_shift(2); o.ifmt = blob.read_shift(2); o.flags = blob.read_shift(2);\n\to.fStyle = (o.flags >> 2) & 0x01;\n\tlength -= 6;\n\to.data = parse_CellStyleXF(blob, length, o.fStyle);\n\treturn o;\n}\n\n/* 2.4.134 */\nfunction parse_Guts(blob, length) {\n\tblob.l += 4;\n\tvar out = [blob.read_shift(2), blob.read_shift(2)];\n\tif(out[0] !== 0) out[0]--;\n\tif(out[1] !== 0) out[1]--;\n\tif(out[0] > 7 || out[1] > 7) throw \"Bad Gutters: \" + out;\n\treturn out;\n}\n\n/* 2.4.24 */\nfunction parse_BoolErr(blob, length) {\n\tvar cell = parse_XLSCell(blob, 6);\n\tvar val = parse_Bes(blob, 2);\n\tcell.val = val;\n\tcell.t = (val === true || val === false) ? 'b' : 'e';\n\treturn cell;\n}\n\n/* 2.4.180 Number */\nfunction parse_Number(blob, length) {\n\tvar cell = parse_XLSCell(blob, 6);\n\tvar xnum = parse_Xnum(blob, 8);\n\tcell.val = xnum;\n\treturn cell;\n}\n\nvar parse_XLHeaderFooter = parse_OptXLUnicodeString; // TODO: parse 2.4.136\n\n/* 2.4.271 */\nfunction parse_SupBook(blob, length, opts) {\n\tvar end = blob.l + length;\n\tvar ctab = blob.read_shift(2);\n\tvar cch = blob.read_shift(2);\n\tvar virtPath;\n\tif(cch >=0x01 && cch <=0xff) virtPath = parse_XLUnicodeStringNoCch(blob, cch);\n\tvar rgst = blob.read_shift(end - blob.l);\n\topts.sbcch = cch;\n\treturn [cch, ctab, virtPath, rgst];\n}\n\n/* 2.4.105 TODO */\nfunction parse_ExternName(blob, length, opts) {\n\tvar flags = blob.read_shift(2);\n\tvar body;\n\tvar o = {\n\t\tfBuiltIn: flags & 0x01,\n\t\tfWantAdvise: (flags >>> 1) & 0x01,\n\t\tfWantPict: (flags >>> 2) & 0x01,\n\t\tfOle: (flags >>> 3) & 0x01,\n\t\tfOleLink: (flags >>> 4) & 0x01,\n\t\tcf: (flags >>> 5) & 0x3FF,\n\t\tfIcon: flags >>> 15 & 0x01\n\t};\n\tif(opts.sbcch === 0x3A01) body = parse_AddinUdf(blob, length-2);\n\t//else throw new Error(\"unsupported SupBook cch: \" + opts.sbcch);\n\to.body = body || blob.read_shift(length-2);\n\treturn o;\n}\n\n/* 2.4.150 TODO */\nfunction parse_Lbl(blob, length, opts) {\n\tif(opts.biff < 8) return parse_Label(blob, length, opts);\n\tvar target = blob.l + length;\n\tvar flags = blob.read_shift(2);\n\tvar chKey = blob.read_shift(1);\n\tvar cch = blob.read_shift(1);\n\tvar cce = blob.read_shift(2);\n\tblob.l += 2;\n\tvar itab = blob.read_shift(2);\n\tblob.l += 4;\n\tvar name = parse_XLUnicodeStringNoCch(blob, cch, opts);\n\tvar rgce = parse_NameParsedFormula(blob, target - blob.l, opts, cce);\n\treturn {\n\t\tchKey: chKey,\n\t\tName: name,\n\t\trgce: rgce\n\t};\n}\n\n/* 2.4.106 TODO: verify supbook manipulation */\nfunction parse_ExternSheet(blob, length, opts) {\n\tif(opts.biff < 8) return parse_ShortXLUnicodeString(blob, length, opts);\n\tvar o = parslurp2(blob,length,parse_XTI);\n\tvar oo = [];\n\tif(opts.sbcch === 0x0401) {\n\t\tfor(var i = 0; i != o.length; ++i) oo.push(opts.snames[o[i][1]]);\n\t\treturn oo;\n\t}\n\telse return o;\n}\n\n/* 2.4.260 */\nfunction parse_ShrFmla(blob, length, opts) {\n\tvar ref = parse_RefU(blob, 6);\n\tblob.l++;\n\tvar cUse = blob.read_shift(1);\n\tlength -= 8;\n\treturn [parse_SharedParsedFormula(blob, length, opts), cUse];\n}\n\n/* 2.4.4 TODO */\nfunction parse_Array(blob, length, opts) {\n\tvar ref = parse_Ref(blob, 6);\n\tblob.l += 6; length -= 12; /* TODO: fAlwaysCalc */\n\treturn [ref, parse_ArrayParsedFormula(blob, length, opts, ref)];\n}\n\n/* 2.4.173 */\nfunction parse_MTRSettings(blob, length) {\n\tvar fMTREnabled = blob.read_shift(4) !== 0x00;\n\tvar fUserSetThreadCount = blob.read_shift(4) !== 0x00;\n\tvar cUserThreadCount = blob.read_shift(4);\n\treturn [fMTREnabled, fUserSetThreadCount, cUserThreadCount];\n}\n\n/* 2.5.186 TODO: BIFF5 */\nfunction parse_NoteSh(blob, length, opts) {\n\tif(opts.biff < 8) return;\n\tvar row = blob.read_shift(2), col = blob.read_shift(2);\n\tvar flags = blob.read_shift(2), idObj = blob.read_shift(2);\n\tvar stAuthor = parse_XLUnicodeString2(blob, 0, opts);\n\tif(opts.biff < 8) blob.read_shift(1);\n\treturn [{r:row,c:col}, stAuthor, idObj, flags];\n}\n\n/* 2.4.179 */\nfunction parse_Note(blob, length, opts) {\n\t/* TODO: Support revisions */\n\treturn parse_NoteSh(blob, length, opts);\n}\n\n/* 2.4.168 */\nfunction parse_MergeCells(blob, length) {\n\tvar merges = [];\n\tvar cmcs = blob.read_shift(2);\n\twhile (cmcs--) merges.push(parse_Ref8U(blob,length));\n\treturn merges;\n}\n\n/* 2.4.181 TODO: parse all the things! */\nfunction parse_Obj(blob, length) {\n\tvar cmo = parse_FtCmo(blob, 22); // id, ot, flags\n\tvar fts = parse_FtArray(blob, length-22, cmo[1]);\n\treturn { cmo: cmo, ft:fts };\n}\n\n/* 2.4.329 TODO: parse properly */\nfunction parse_TxO(blob, length, opts) {\n\tvar s = blob.l;\ntry {\n\tblob.l += 4;\n\tvar ot = (opts.lastobj||{cmo:[0,0]}).cmo[1];\n\tvar controlInfo;\n\tif([0,5,7,11,12,14].indexOf(ot) == -1) blob.l += 6;\n\telse controlInfo = parse_ControlInfo(blob, 6, opts);\n\tvar cchText = blob.read_shift(2);\n\tvar cbRuns = blob.read_shift(2);\n\tvar ifntEmpty = parse_FontIndex(blob, 2);\n\tvar len = blob.read_shift(2);\n\tblob.l += len;\n\t//var fmla = parse_ObjFmla(blob, s + length - blob.l);\n\n\tvar texts = \"\";\n\tfor(var i = 1; i < blob.lens.length-1; ++i) {\n\t\tif(blob.l-s != blob.lens[i]) throw \"TxO: bad continue record\";\n\t\tvar hdr = blob[blob.l];\n\t\tvar t = parse_XLUnicodeStringNoCch(blob, blob.lens[i+1]-blob.lens[i]-1);\n\t\ttexts += t;\n\t\tif(texts.length >= (hdr ? cchText : 2*cchText)) break;\n\t}\n\tif(texts.length !== cchText && texts.length !== cchText*2) {\n\t\tthrow \"cchText: \" + cchText + \" != \" + texts.length;\n\t}\n\n\tblob.l = s + length;\n\t/* 2.5.272 TxORuns */\n//\tvar rgTxoRuns = [];\n//\tfor(var j = 0; j != cbRuns/8-1; ++j) blob.l += 8;\n//\tvar cchText2 = blob.read_shift(2);\n//\tif(cchText2 !== cchText) throw \"TxOLastRun mismatch: \" + cchText2 + \" \" + cchText;\n//\tblob.l += 6;\n//\tif(s + length != blob.l) throw \"TxO \" + (s + length) + \", at \" + blob.l;\n\treturn { t: texts };\n} catch(e) { blob.l = s + length; return { t: texts||\"\" }; }\n}\n\n/* 2.4.140 */\nvar parse_HLink = function(blob, length) {\n\tvar ref = parse_Ref8U(blob, 8);\n\tblob.l += 16; /* CLSID */\n\tvar hlink = parse_Hyperlink(blob, length-24);\n\treturn [ref, hlink];\n};\n\n/* 2.4.141 */\nvar parse_HLinkTooltip = function(blob, length) {\n\tvar end = blob.l + length;\n\tblob.read_shift(2);\n\tvar ref = parse_Ref8U(blob, 8);\n\tvar wzTooltip = blob.read_shift((length-10)/2, 'dbcs-cont');\n\twzTooltip = wzTooltip.replace(chr0,\"\");\n\treturn [ref, wzTooltip];\n};\n\n/* 2.4.63 */\nfunction parse_Country(blob, length) {\n\tvar o = [], d;\n\td = blob.read_shift(2); o[0] = CountryEnum[d] || d;\n\td = blob.read_shift(2); o[1] = CountryEnum[d] || d;\n\treturn o;\n}\n\n/* 2.4.50 ClrtClient */\nfunction parse_ClrtClient(blob, length) {\n\tvar ccv = blob.read_shift(2);\n\tvar o = [];\n\twhile(ccv-->0) o.push(parse_LongRGB(blob, 8));\n\treturn o;\n}\n\n/* 2.4.188 */\nfunction parse_Palette(blob, length) {\n\tvar ccv = blob.read_shift(2);\n\tvar o = [];\n\twhile(ccv-->0) o.push(parse_LongRGB(blob, 8));\n\treturn o;\n}\n\n/* 2.4.354 */\nfunction parse_XFCRC(blob, length) {\n\tblob.l += 2;\n\tvar o = {cxfs:0, crc:0};\n\to.cxfs = blob.read_shift(2);\n\to.crc = blob.read_shift(4);\n\treturn o;\n}\n\n\nvar parse_Style = parsenoop;\nvar parse_StyleExt = parsenoop;\n\nvar parse_ColInfo = parsenoop;\n\nvar parse_Window2 = parsenoop;\n\n\nvar parse_Backup = parsebool; /* 2.4.14 */\nvar parse_Blank = parse_XLSCell; /* 2.4.20 Just the cell */\nvar parse_BottomMargin = parse_Xnum; /* 2.4.27 */\nvar parse_BuiltInFnGroupCount = parseuint16; /* 2.4.30 0x0E or 0x10 but excel 2011 generates 0x11? */\nvar parse_CalcCount = parseuint16; /* 2.4.31 #Iterations */\nvar parse_CalcDelta = parse_Xnum; /* 2.4.32 */\nvar parse_CalcIter = parsebool;  /* 2.4.33 1=iterative calc */\nvar parse_CalcMode = parseuint16; /* 2.4.34 0=manual, 1=auto (def), 2=table */\nvar parse_CalcPrecision = parsebool; /* 2.4.35 */\nvar parse_CalcRefMode = parsenoop2; /* 2.4.36 */\nvar parse_CalcSaveRecalc = parsebool; /* 2.4.37 */\nvar parse_CodePage = parseuint16; /* 2.4.52 */\nvar parse_Compat12 = parsebool; /* 2.4.54 true = no compatibility check */\nvar parse_Date1904 = parsebool; /* 2.4.77 - 1=1904,0=1900 */\nvar parse_DefColWidth = parseuint16; /* 2.4.89 */\nvar parse_DSF = parsenoop2; /* 2.4.94 -- MUST be ignored */\nvar parse_EntExU2 = parsenoop2; /* 2.4.102 -- Explicitly says to ignore */\nvar parse_EOF = parsenoop2; /* 2.4.103 */\nvar parse_Excel9File = parsenoop2; /* 2.4.104 -- Optional and unused */\nvar parse_FeatHdr = parsenoop2; /* 2.4.112 */\nvar parse_FontX = parseuint16; /* 2.4.123 */\nvar parse_Footer = parse_XLHeaderFooter; /* 2.4.124 */\nvar parse_GridSet = parseuint16; /* 2.4.132, =1 */\nvar parse_HCenter = parsebool; /* 2.4.135 sheet centered horizontal on print */\nvar parse_Header = parse_XLHeaderFooter; /* 2.4.136 */\nvar parse_HideObj = parse_HideObjEnum; /* 2.4.139 */\nvar parse_InterfaceEnd = parsenoop2; /* 2.4.145 -- noop */\nvar parse_LeftMargin = parse_Xnum; /* 2.4.151 */\nvar parse_Mms = parsenoop2; /* 2.4.169 -- Explicitly says to ignore */\nvar parse_ObjProtect = parsebool; /* 2.4.183 -- must be 1 if present */\nvar parse_Password = parseuint16; /* 2.4.191 */\nvar parse_PrintGrid = parsebool; /* 2.4.202 */\nvar parse_PrintRowCol = parsebool; /* 2.4.203 */\nvar parse_PrintSize = parseuint16; /* 2.4.204 0:3 */\nvar parse_Prot4Rev = parsebool; /* 2.4.205 */\nvar parse_Prot4RevPass = parseuint16; /* 2.4.206 */\nvar parse_Protect = parsebool; /* 2.4.207 */\nvar parse_RefreshAll = parsebool; /* 2.4.217 -- must be 0 if not template */\nvar parse_RightMargin = parse_Xnum; /* 2.4.219 */\nvar parse_RRTabId = parseuint16a; /* 2.4.241 */\nvar parse_ScenarioProtect = parsebool; /* 2.4.245 */\nvar parse_Scl = parseuint16a; /* 2.4.247 num, den */\nvar parse_String = parse_XLUnicodeString; /* 2.4.268 */\nvar parse_SxBool = parsebool; /* 2.4.274 */\nvar parse_TopMargin = parse_Xnum; /* 2.4.328 */\nvar parse_UsesELFs = parsebool; /* 2.4.337 -- should be 0 */\nvar parse_VCenter = parsebool; /* 2.4.342 */\nvar parse_WinProtect = parsebool; /* 2.4.347 */\nvar parse_WriteProtect = parsenoop; /* 2.4.350 empty record */\n\n\n/* ---- */\nvar parse_VerticalPageBreaks = parsenoop;\nvar parse_HorizontalPageBreaks = parsenoop;\nvar parse_Selection = parsenoop;\nvar parse_Continue = parsenoop;\nvar parse_Pane = parsenoop;\nvar parse_Pls = parsenoop;\nvar parse_DCon = parsenoop;\nvar parse_DConRef = parsenoop;\nvar parse_DConName = parsenoop;\nvar parse_XCT = parsenoop;\nvar parse_CRN = parsenoop;\nvar parse_FileSharing = parsenoop;\nvar parse_Uncalced = parsenoop;\nvar parse_Template = parsenoop;\nvar parse_Intl = parsenoop;\nvar parse_WsBool = parsenoop;\nvar parse_Sort = parsenoop;\nvar parse_Sync = parsenoop;\nvar parse_LPr = parsenoop;\nvar parse_DxGCol = parsenoop;\nvar parse_FnGroupName = parsenoop;\nvar parse_FilterMode = parsenoop;\nvar parse_AutoFilterInfo = parsenoop;\nvar parse_AutoFilter = parsenoop;\nvar parse_Setup = parsenoop;\nvar parse_ScenMan = parsenoop;\nvar parse_SCENARIO = parsenoop;\nvar parse_SxView = parsenoop;\nvar parse_Sxvd = parsenoop;\nvar parse_SXVI = parsenoop;\nvar parse_SxIvd = parsenoop;\nvar parse_SXLI = parsenoop;\nvar parse_SXPI = parsenoop;\nvar parse_DocRoute = parsenoop;\nvar parse_RecipName = parsenoop;\nvar parse_MulBlank = parsenoop;\nvar parse_SXDI = parsenoop;\nvar parse_SXDB = parsenoop;\nvar parse_SXFDB = parsenoop;\nvar parse_SXDBB = parsenoop;\nvar parse_SXNum = parsenoop;\nvar parse_SxErr = parsenoop;\nvar parse_SXInt = parsenoop;\nvar parse_SXString = parsenoop;\nvar parse_SXDtr = parsenoop;\nvar parse_SxNil = parsenoop;\nvar parse_SXTbl = parsenoop;\nvar parse_SXTBRGIITM = parsenoop;\nvar parse_SxTbpg = parsenoop;\nvar parse_ObProj = parsenoop;\nvar parse_SXStreamID = parsenoop;\nvar parse_DBCell = parsenoop;\nvar parse_SXRng = parsenoop;\nvar parse_SxIsxoper = parsenoop;\nvar parse_BookBool = parsenoop;\nvar parse_DbOrParamQry = parsenoop;\nvar parse_OleObjectSize = parsenoop;\nvar parse_SXVS = parsenoop;\nvar parse_BkHim = parsenoop;\nvar parse_MsoDrawingGroup = parsenoop;\nvar parse_MsoDrawing = parsenoop;\nvar parse_MsoDrawingSelection = parsenoop;\nvar parse_PhoneticInfo = parsenoop;\nvar parse_SxRule = parsenoop;\nvar parse_SXEx = parsenoop;\nvar parse_SxFilt = parsenoop;\nvar parse_SxDXF = parsenoop;\nvar parse_SxItm = parsenoop;\nvar parse_SxName = parsenoop;\nvar parse_SxSelect = parsenoop;\nvar parse_SXPair = parsenoop;\nvar parse_SxFmla = parsenoop;\nvar parse_SxFormat = parsenoop;\nvar parse_SXVDEx = parsenoop;\nvar parse_SXFormula = parsenoop;\nvar parse_SXDBEx = parsenoop;\nvar parse_RRDInsDel = parsenoop;\nvar parse_RRDHead = parsenoop;\nvar parse_RRDChgCell = parsenoop;\nvar parse_RRDRenSheet = parsenoop;\nvar parse_RRSort = parsenoop;\nvar parse_RRDMove = parsenoop;\nvar parse_RRFormat = parsenoop;\nvar parse_RRAutoFmt = parsenoop;\nvar parse_RRInsertSh = parsenoop;\nvar parse_RRDMoveBegin = parsenoop;\nvar parse_RRDMoveEnd = parsenoop;\nvar parse_RRDInsDelBegin = parsenoop;\nvar parse_RRDInsDelEnd = parsenoop;\nvar parse_RRDConflict = parsenoop;\nvar parse_RRDDefName = parsenoop;\nvar parse_RRDRstEtxp = parsenoop;\nvar parse_LRng = parsenoop;\nvar parse_CUsr = parsenoop;\nvar parse_CbUsr = parsenoop;\nvar parse_UsrInfo = parsenoop;\nvar parse_UsrExcl = parsenoop;\nvar parse_FileLock = parsenoop;\nvar parse_RRDInfo = parsenoop;\nvar parse_BCUsrs = parsenoop;\nvar parse_UsrChk = parsenoop;\nvar parse_UserBView = parsenoop;\nvar parse_UserSViewBegin = parsenoop; // overloaded\nvar parse_UserSViewEnd = parsenoop;\nvar parse_RRDUserView = parsenoop;\nvar parse_Qsi = parsenoop;\nvar parse_CondFmt = parsenoop;\nvar parse_CF = parsenoop;\nvar parse_DVal = parsenoop;\nvar parse_DConBin = parsenoop;\nvar parse_Lel = parsenoop;\nvar parse_XLSCodeName = parse_XLUnicodeString;\nvar parse_SXFDBType = parsenoop;\nvar parse_ObNoMacros = parsenoop;\nvar parse_Dv = parsenoop;\nvar parse_Index = parsenoop;\nvar parse_Table = parsenoop;\nvar parse_BigName = parsenoop;\nvar parse_ContinueBigName = parsenoop;\nvar parse_WebPub = parsenoop;\nvar parse_QsiSXTag = parsenoop;\nvar parse_DBQueryExt = parsenoop;\nvar parse_ExtString = parsenoop;\nvar parse_TxtQry = parsenoop;\nvar parse_Qsir = parsenoop;\nvar parse_Qsif = parsenoop;\nvar parse_RRDTQSIF = parsenoop;\nvar parse_OleDbConn = parsenoop;\nvar parse_WOpt = parsenoop;\nvar parse_SXViewEx = parsenoop;\nvar parse_SXTH = parsenoop;\nvar parse_SXPIEx = parsenoop;\nvar parse_SXVDTEx = parsenoop;\nvar parse_SXViewEx9 = parsenoop;\nvar parse_ContinueFrt = parsenoop;\nvar parse_RealTimeData = parsenoop;\nvar parse_ChartFrtInfo = parsenoop;\nvar parse_FrtWrapper = parsenoop;\nvar parse_StartBlock = parsenoop;\nvar parse_EndBlock = parsenoop;\nvar parse_StartObject = parsenoop;\nvar parse_EndObject = parsenoop;\nvar parse_CatLab = parsenoop;\nvar parse_YMult = parsenoop;\nvar parse_SXViewLink = parsenoop;\nvar parse_PivotChartBits = parsenoop;\nvar parse_FrtFontList = parsenoop;\nvar parse_SheetExt = parsenoop;\nvar parse_BookExt = parsenoop;\nvar parse_SXAddl = parsenoop;\nvar parse_CrErr = parsenoop;\nvar parse_HFPicture = parsenoop;\nvar parse_Feat = parsenoop;\nvar parse_DataLabExt = parsenoop;\nvar parse_DataLabExtContents = parsenoop;\nvar parse_CellWatch = parsenoop;\nvar parse_FeatHdr11 = parsenoop;\nvar parse_Feature11 = parsenoop;\nvar parse_DropDownObjIds = parsenoop;\nvar parse_ContinueFrt11 = parsenoop;\nvar parse_DConn = parsenoop;\nvar parse_List12 = parsenoop;\nvar parse_Feature12 = parsenoop;\nvar parse_CondFmt12 = parsenoop;\nvar parse_CF12 = parsenoop;\nvar parse_CFEx = parsenoop;\nvar parse_AutoFilter12 = parsenoop;\nvar parse_ContinueFrt12 = parsenoop;\nvar parse_MDTInfo = parsenoop;\nvar parse_MDXStr = parsenoop;\nvar parse_MDXTuple = parsenoop;\nvar parse_MDXSet = parsenoop;\nvar parse_MDXProp = parsenoop;\nvar parse_MDXKPI = parsenoop;\nvar parse_MDB = parsenoop;\nvar parse_PLV = parsenoop;\nvar parse_DXF = parsenoop;\nvar parse_TableStyles = parsenoop;\nvar parse_TableStyle = parsenoop;\nvar parse_TableStyleElement = parsenoop;\nvar parse_NamePublish = parsenoop;\nvar parse_NameCmt = parsenoop;\nvar parse_SortData = parsenoop;\nvar parse_GUIDTypeLib = parsenoop;\nvar parse_FnGrp12 = parsenoop;\nvar parse_NameFnGrp12 = parsenoop;\nvar parse_HeaderFooter = parsenoop;\nvar parse_CrtLayout12 = parsenoop;\nvar parse_CrtMlFrt = parsenoop;\nvar parse_CrtMlFrtContinue = parsenoop;\nvar parse_ShapePropsStream = parsenoop;\nvar parse_TextPropsStream = parsenoop;\nvar parse_RichTextStream = parsenoop;\nvar parse_CrtLayout12A = parsenoop;\nvar parse_Units = parsenoop;\nvar parse_Chart = parsenoop;\nvar parse_Series = parsenoop;\nvar parse_DataFormat = parsenoop;\nvar parse_LineFormat = parsenoop;\nvar parse_MarkerFormat = parsenoop;\nvar parse_AreaFormat = parsenoop;\nvar parse_PieFormat = parsenoop;\nvar parse_AttachedLabel = parsenoop;\nvar parse_SeriesText = parsenoop;\nvar parse_ChartFormat = parsenoop;\nvar parse_Legend = parsenoop;\nvar parse_SeriesList = parsenoop;\nvar parse_Bar = parsenoop;\nvar parse_Line = parsenoop;\nvar parse_Pie = parsenoop;\nvar parse_Area = parsenoop;\nvar parse_Scatter = parsenoop;\nvar parse_CrtLine = parsenoop;\nvar parse_Axis = parsenoop;\nvar parse_Tick = parsenoop;\nvar parse_ValueRange = parsenoop;\nvar parse_CatSerRange = parsenoop;\nvar parse_AxisLine = parsenoop;\nvar parse_CrtLink = parsenoop;\nvar parse_DefaultText = parsenoop;\nvar parse_Text = parsenoop;\nvar parse_ObjectLink = parsenoop;\nvar parse_Frame = parsenoop;\nvar parse_Begin = parsenoop;\nvar parse_End = parsenoop;\nvar parse_PlotArea = parsenoop;\nvar parse_Chart3d = parsenoop;\nvar parse_PicF = parsenoop;\nvar parse_DropBar = parsenoop;\nvar parse_Radar = parsenoop;\nvar parse_Surf = parsenoop;\nvar parse_RadarArea = parsenoop;\nvar parse_AxisParent = parsenoop;\nvar parse_LegendException = parsenoop;\nvar parse_ShtProps = parsenoop;\nvar parse_SerToCrt = parsenoop;\nvar parse_AxesUsed = parsenoop;\nvar parse_SBaseRef = parsenoop;\nvar parse_SerParent = parsenoop;\nvar parse_SerAuxTrend = parsenoop;\nvar parse_IFmtRecord = parsenoop;\nvar parse_Pos = parsenoop;\nvar parse_AlRuns = parsenoop;\nvar parse_BRAI = parsenoop;\nvar parse_SerAuxErrBar = parsenoop;\nvar parse_SerFmt = parsenoop;\nvar parse_Chart3DBarShape = parsenoop;\nvar parse_Fbi = parsenoop;\nvar parse_BopPop = parsenoop;\nvar parse_AxcExt = parsenoop;\nvar parse_Dat = parsenoop;\nvar parse_PlotGrowth = parsenoop;\nvar parse_SIIndex = parsenoop;\nvar parse_GelFrame = parsenoop;\nvar parse_BopPopCustom = parsenoop;\nvar parse_Fbi2 = parsenoop;\n\n/* --- Specific to versions before BIFF8 --- */\nfunction parse_BIFF5String(blob) {\n\tvar len = blob.read_shift(1);\n\treturn blob.read_shift(len, 'sbcs-cont');\n}\n\n/* BIFF2_??? where ??? is the name from [XLS] */\nfunction parse_BIFF2STR(blob, length, opts) {\n\tvar cell = parse_XLSCell(blob, 6);\n\t++blob.l;\n\tvar str = parse_XLUnicodeString2(blob, length-7, opts);\n\tcell.val = str;\n\treturn cell;\n}\n\nfunction parse_BIFF2NUM(blob, length, opts) {\n\tvar cell = parse_XLSCell(blob, 6);\n\t++blob.l;\n\tvar num = parse_Xnum(blob, 8);\n\tcell.val = num;\n\treturn cell;\n}\n\n/* 18.4.1 charset to codepage mapping */\nvar CS2CP = {\n\t0:    1252, /* ANSI */\n\t1:   65001, /* DEFAULT */\n\t2:   65001, /* SYMBOL */\n\t77:  10000, /* MAC */\n\t128:   932, /* SHIFTJIS */\n\t129:   949, /* HANGUL */\n\t130:  1361, /* JOHAB */\n\t134:   936, /* GB2312 */\n\t136:   950, /* CHINESEBIG5 */\n\t161:  1253, /* GREEK */\n\t162:  1254, /* TURKISH */\n\t163:  1258, /* VIETNAMESE */\n\t177:  1255, /* HEBREW */\n\t178:  1256, /* ARABIC */\n\t186:  1257, /* BALTIC */\n\t204:  1251, /* RUSSIAN */\n\t222:   874, /* THAI */\n\t238:  1250, /* EASTEUROPE */\n\t255:  1252, /* OEM */\n\t69:   6969  /* MISC */\n};\n\n/* Parse a list of <r> tags */\nvar parse_rs = (function parse_rs_factory() {\n\tvar tregex = matchtag(\"t\"), rpregex = matchtag(\"rPr\"), rregex = /<r>/g, rend = /<\\/r>/, nlregex = /\\r\\n/g;\n\t/* 18.4.7 rPr CT_RPrElt */\n\tvar parse_rpr = function parse_rpr(rpr, intro, outro) {\n\t\tvar font = {}, cp = 65001;\n\t\tvar m = rpr.match(tagregex), i = 0;\n\t\tif(m) for(;i!=m.length; ++i) {\n\t\t\tvar y = parsexmltag(m[i]);\n\t\t\tswitch(y[0]) {\n\t\t\t\t/* 18.8.12 condense CT_BooleanProperty */\n\t\t\t\t/* ** not required . */\n\t\t\t\tcase '<condense': break;\n\t\t\t\t/* 18.8.17 extend CT_BooleanProperty */\n\t\t\t\t/* ** not required . */\n\t\t\t\tcase '<extend': break;\n\t\t\t\t/* 18.8.36 shadow CT_BooleanProperty */\n\t\t\t\t/* ** not required . */\n\t\t\t\tcase '<shadow':\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<shadow/>': break;\n\n\t\t\t\t/* 18.4.1 charset CT_IntProperty TODO */\n\t\t\t\tcase '<charset':\n\t\t\t\t\tif(y.val == '1') break;\n\t\t\t\t\tcp = CS2CP[parseInt(y.val, 10)];\n\t\t\t\t\tbreak;\n\n\t\t\t\t/* 18.4.2 outline CT_BooleanProperty TODO */\n\t\t\t\tcase '<outline':\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<outline/>': break;\n\n\t\t\t\t/* 18.4.5 rFont CT_FontName */\n\t\t\t\tcase '<rFont': font.name = y.val; break;\n\n\t\t\t\t/* 18.4.11 sz CT_FontSize */\n\t\t\t\tcase '<sz': font.sz = y.val; break;\n\n\t\t\t\t/* 18.4.10 strike CT_BooleanProperty */\n\t\t\t\tcase '<strike':\n\t\t\t\t\tif(!y.val) break;\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<strike/>': font.strike = 1; break;\n\t\t\t\tcase '</strike>': break;\n\n\t\t\t\t/* 18.4.13 u CT_UnderlineProperty */\n\t\t\t\tcase '<u':\n\t\t\t\t\tif(!y.val) break;\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<u/>': font.u = 1; break;\n\t\t\t\tcase '</u>': break;\n\n\t\t\t\t/* 18.8.2 b */\n\t\t\t\tcase '<b':\n\t\t\t\t\tif(!y.val) break;\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<b/>': font.b = 1; break;\n\t\t\t\tcase '</b>': break;\n\n\t\t\t\t/* 18.8.26 i */\n\t\t\t\tcase '<i':\n\t\t\t\t\tif(!y.val) break;\n\t\t\t\t\t/* falls through */\n\t\t\t\tcase '<i/>': font.i = 1; break;\n\t\t\t\tcase '</i>': break;\n\n\t\t\t\t/* 18.3.1.15 color CT_Color TODO: tint, theme, auto, indexed */\n\t\t\t\tcase '<color':\n\t\t\t\t\tif(y.rgb) font.color = y.rgb.substr(2,6);\n\t\t\t\t\tbreak;\n\n\t\t\t\t/* 18.8.18 family ST_FontFamily */\n\t\t\t\tcase '<family': font.family = y.val; break;\n\n\t\t\t\t/* 18.4.14 vertAlign CT_VerticalAlignFontProperty TODO */\n\t\t\t\tcase '<vertAlign': break;\n\n\t\t\t\t/* 18.8.35 scheme CT_FontScheme TODO */\n\t\t\t\tcase '<scheme': break;\n\n\t\t\t\tdefault:\n\t\t\t\t\tif(y[0].charCodeAt(1) !== 47) throw 'Unrecognized rich format ' + y[0];\n\t\t\t}\n\t\t}\n\t\t/* TODO: These should be generated styles, not inline */\n\t\tvar style = [];\n\t\tif(font.b) style.push(\"font-weight: bold;\");\n\t\tif(font.i) style.push(\"font-style: italic;\");\n\t\tintro.push('<span style=\"' + style.join(\"\") + '\">');\n\t\toutro.push(\"</span>\");\n\t\treturn cp;\n\t};\n\n\t/* 18.4.4 r CT_RElt */\n\tfunction parse_r(r) {\n\t\tvar terms = [[],\"\",[]];\n\t\t/* 18.4.12 t ST_Xstring */\n\t\tvar t = r.match(tregex), cp = 65001;\n\t\tif(!isval(t)) return \"\";\n\t\tterms[1] = t[1];\n\n\t\tvar rpr = r.match(rpregex);\n\t\tif(isval(rpr)) cp = parse_rpr(rpr[1], terms[0], terms[2]);\n\n\t\treturn terms[0].join(\"\") + terms[1].replace(nlregex,'<br/>') + terms[2].join(\"\");\n\t}\n\treturn function parse_rs(rs) {\n\t\treturn rs.replace(rregex,\"\").split(rend).map(parse_r).join(\"\");\n\t};\n})();\n\n/* 18.4.8 si CT_Rst */\nvar sitregex = /<t[^>]*>([^<]*)<\\/t>/g, sirregex = /<r>/;\nfunction parse_si(x, opts) {\n\tvar html = opts ? opts.cellHTML : true;\n\tvar z = {};\n\tif(!x) return null;\n\tvar y;\n\t/* 18.4.12 t ST_Xstring (Plaintext String) */\n\tif(x.charCodeAt(1) === 116) {\n\t\tz.t = utf8read(unescapexml(x.substr(x.indexOf(\">\")+1).split(/<\\/t>/)[0]));\n\t\tz.r = x;\n\t\tif(html) z.h = z.t;\n\t}\n\t/* 18.4.4 r CT_RElt (Rich Text Run) */\n\telse if((y = x.match(sirregex))) {\n\t\tz.r = x;\n\t\tz.t = utf8read(unescapexml(x.match(sitregex).join(\"\").replace(tagregex,\"\")));\n\t\tif(html) z.h = parse_rs(x);\n\t}\n\t/* 18.4.3 phoneticPr CT_PhoneticPr (TODO: needed for Asian support) */\n\t/* 18.4.6 rPh CT_PhoneticRun (TODO: needed for Asian support) */\n\treturn z;\n}\n\n/* 18.4 Shared String Table */\nvar sstr0 = /<sst([^>]*)>([\\s\\S]*)<\\/sst>/;\nvar sstr1 = /<(?:si|sstItem)>/g;\nvar sstr2 = /<\\/(?:si|sstItem)>/;\nfunction parse_sst_xml(data, opts) {\n\tvar s = [], ss;\n\t/* 18.4.9 sst CT_Sst */\n\tvar sst = data.match(sstr0);\n\tif(isval(sst)) {\n\t\tss = sst[2].replace(sstr1,\"\").split(sstr2);\n\t\tfor(var i = 0; i != ss.length; ++i) {\n\t\t\tvar o = parse_si(ss[i], opts);\n\t\t\tif(o != null) s[s.length] = o;\n\t\t}\n\t\tsst = parsexmltag(sst[1]); s.Count = sst.count; s.Unique = sst.uniqueCount;\n\t}\n\treturn s;\n}\n\nRELS.SST = \"http://schemas.openxmlformats.org/officeDocument/2006/relationships/sharedStrings\";\nvar straywsregex = /^\\s|\\s$|[\\t\\n\\r]/;\nfunction write_sst_xml(sst, opts) {\n\tif(!opts.bookSST) return \"\";\n\tvar o = [XML_HEADER];\n\to[o.length] = (writextag('sst', null, {\n\t\txmlns: XMLNS.main[0],\n\t\tcount: sst.Count,\n\t\tuniqueCount: sst.Unique\n\t}));\n\tfor(var i = 0; i != sst.length; ++i) { if(sst[i] == null) continue;\n\t\tvar s = sst[i];\n\t\tvar sitag = \"<si>\";\n\t\tif(s.r) sitag += s.r;\n\t\telse {\n\t\t\tsitag += \"<t\";\n\t\t\tif(s.t.match(straywsregex)) sitag += ' xml:space=\"preserve\"';\n\t\t\tsitag += \">\" + escapexml(s.t) + \"</t>\";\n\t\t}\n\t\tsitag += \"</si>\";\n\t\to[o.length] = (sitag);\n\t}\n\tif(o.length>2){ o[o.length] = ('</sst>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* [MS-XLSB] 2.4.219 BrtBeginSst */\nfunction parse_BrtBeginSst(data, length) {\n\treturn [data.read_shift(4), data.read_shift(4)];\n}\n\n/* [MS-XLSB] 2.1.7.45 Shared Strings */\nfunction parse_sst_bin(data, opts) {\n\tvar s = [];\n\tvar pass = false;\n\trecordhopper(data, function hopper_sst(val, R, RT) {\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtBeginSst': s.Count = val[0]; s.Unique = val[1]; break;\n\t\t\tcase 'BrtSSTItem': s.push(val); break;\n\t\t\tcase 'BrtEndSst': return true;\n\t\t\t/* TODO: produce a test case with a future record */\n\t\t\tcase 'BrtFRTBegin': pass = true; break;\n\t\t\tcase 'BrtFRTEnd': pass = false; break;\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + RT + \" \" + R.n);\n\t\t}\n\t});\n\treturn s;\n}\n\nfunction write_BrtBeginSst(sst, o) {\n\tif(!o) o = new_buf(8);\n\to.write_shift(4, sst.Count);\n\to.write_shift(4, sst.Unique);\n\treturn o;\n}\n\nvar write_BrtSSTItem = write_RichStr;\n\nfunction write_sst_bin(sst, opts) {\n\tvar ba = buf_array();\n\twrite_record(ba, \"BrtBeginSst\", write_BrtBeginSst(sst));\n\tfor(var i = 0; i < sst.length; ++i) write_record(ba, \"BrtSSTItem\", write_BrtSSTItem(sst[i]));\n\twrite_record(ba, \"BrtEndSst\");\n\treturn ba.end();\n}\nfunction _JS2ANSI(str) { if(typeof cptable !== 'undefined') return cptable.utils.encode(1252, str); return str.split(\"\").map(function(x) { return x.charCodeAt(0); }); }\n\n/* [MS-OFFCRYPTO] 2.1.4 Version */\nfunction parse_Version(blob, length) {\n\tvar o = {};\n\to.Major = blob.read_shift(2);\n\to.Minor = blob.read_shift(2);\n\treturn o;\n}\n/* [MS-OFFCRYPTO] 2.3.2 Encryption Header */\nfunction parse_EncryptionHeader(blob, length) {\n\tvar o = {};\n\to.Flags = blob.read_shift(4);\n\n\t// Check if SizeExtra is 0x00000000\n\tvar tmp = blob.read_shift(4);\n\tif(tmp !== 0) throw 'Unrecognized SizeExtra: ' + tmp;\n\n\to.AlgID = blob.read_shift(4);\n\tswitch(o.AlgID) {\n\t\tcase 0: case 0x6801: case 0x660E: case 0x660F: case 0x6610: break;\n\t\tdefault: throw 'Unrecognized encryption algorithm: ' + o.AlgID;\n\t}\n\tparsenoop(blob, length-12);\n\treturn o;\n}\n\n/* [MS-OFFCRYPTO] 2.3.3 Encryption Verifier */\nfunction parse_EncryptionVerifier(blob, length) {\n\treturn parsenoop(blob, length);\n}\n/* [MS-OFFCRYPTO] 2.3.5.1 RC4 CryptoAPI Encryption Header */\nfunction parse_RC4CryptoHeader(blob, length) {\n\tvar o = {};\n\tvar vers = o.EncryptionVersionInfo = parse_Version(blob, 4); length -= 4;\n\tif(vers.Minor != 2) throw 'unrecognized minor version code: ' + vers.Minor;\n\tif(vers.Major > 4 || vers.Major < 2) throw 'unrecognized major version code: ' + vers.Major;\n\to.Flags = blob.read_shift(4); length -= 4;\n\tvar sz = blob.read_shift(4); length -= 4;\n\to.EncryptionHeader = parse_EncryptionHeader(blob, sz); length -= sz;\n\to.EncryptionVerifier = parse_EncryptionVerifier(blob, length);\n\treturn o;\n}\n/* [MS-OFFCRYPTO] 2.3.6.1 RC4 Encryption Header */\nfunction parse_RC4Header(blob, length) {\n\tvar o = {};\n\tvar vers = o.EncryptionVersionInfo = parse_Version(blob, 4); length -= 4;\n\tif(vers.Major != 1 || vers.Minor != 1) throw 'unrecognized version code ' + vers.Major + ' : ' + vers.Minor;\n\to.Salt = blob.read_shift(16);\n\to.EncryptedVerifier = blob.read_shift(16);\n\to.EncryptedVerifierHash = blob.read_shift(16);\n\treturn o;\n}\n\n/* [MS-OFFCRYPTO] 2.3.7.1 Binary Document Password Verifier Derivation */\nfunction crypto_CreatePasswordVerifier_Method1(Password) {\n\tvar Verifier = 0x0000, PasswordArray;\n\tvar PasswordDecoded = _JS2ANSI(Password);\n\tvar len = PasswordDecoded.length + 1, i, PasswordByte;\n\tvar Intermediate1, Intermediate2, Intermediate3;\n\tPasswordArray = new_raw_buf(len);\n\tPasswordArray[0] = PasswordDecoded.length;\n\tfor(i = 1; i != len; ++i) PasswordArray[i] = PasswordDecoded[i-1];\n\tfor(i = len-1; i >= 0; --i) {\n\t\tPasswordByte = PasswordArray[i];\n\t\tIntermediate1 = ((Verifier & 0x4000) === 0x0000) ? 0 : 1;\n\t\tIntermediate2 = (Verifier << 1) & 0x7FFF;\n\t\tIntermediate3 = Intermediate1 | Intermediate2;\n\t\tVerifier = Intermediate3 ^ PasswordByte;\n\t}\n\treturn Verifier ^ 0xCE4B;\n}\n\n/* [MS-OFFCRYPTO] 2.3.7.2 Binary Document XOR Array Initialization */\nvar crypto_CreateXorArray_Method1 = (function() {\n\tvar PadArray = [0xBB, 0xFF, 0xFF, 0xBA, 0xFF, 0xFF, 0xB9, 0x80, 0x00, 0xBE, 0x0F, 0x00, 0xBF, 0x0F, 0x00];\n\tvar InitialCode = [0xE1F0, 0x1D0F, 0xCC9C, 0x84C0, 0x110C, 0x0E10, 0xF1CE, 0x313E, 0x1872, 0xE139, 0xD40F, 0x84F9, 0x280C, 0xA96A, 0x4EC3];\n\tvar XorMatrix = [0xAEFC, 0x4DD9, 0x9BB2, 0x2745, 0x4E8A, 0x9D14, 0x2A09, 0x7B61, 0xF6C2, 0xFDA5, 0xEB6B, 0xC6F7, 0x9DCF, 0x2BBF, 0x4563, 0x8AC6, 0x05AD, 0x0B5A, 0x16B4, 0x2D68, 0x5AD0, 0x0375, 0x06EA, 0x0DD4, 0x1BA8, 0x3750, 0x6EA0, 0xDD40, 0xD849, 0xA0B3, 0x5147, 0xA28E, 0x553D, 0xAA7A, 0x44D5, 0x6F45, 0xDE8A, 0xAD35, 0x4A4B, 0x9496, 0x390D, 0x721A, 0xEB23, 0xC667, 0x9CEF, 0x29FF, 0x53FE, 0xA7FC, 0x5FD9, 0x47D3, 0x8FA6, 0x0F6D, 0x1EDA, 0x3DB4, 0x7B68, 0xF6D0, 0xB861, 0x60E3, 0xC1C6, 0x93AD, 0x377B, 0x6EF6, 0xDDEC, 0x45A0, 0x8B40, 0x06A1, 0x0D42, 0x1A84, 0x3508, 0x6A10, 0xAA51, 0x4483, 0x8906, 0x022D, 0x045A, 0x08B4, 0x1168, 0x76B4, 0xED68, 0xCAF1, 0x85C3, 0x1BA7, 0x374E, 0x6E9C, 0x3730, 0x6E60, 0xDCC0, 0xA9A1, 0x4363, 0x86C6, 0x1DAD, 0x3331, 0x6662, 0xCCC4, 0x89A9, 0x0373, 0x06E6, 0x0DCC, 0x1021, 0x2042, 0x4084, 0x8108, 0x1231, 0x2462, 0x48C4];\n\tvar Ror = function(Byte) { return ((Byte/2) | (Byte*128)) & 0xFF; };\n\tvar XorRor = function(byte1, byte2) { return Ror(byte1 ^ byte2); };\n\tvar CreateXorKey_Method1 = function(Password) {\n\t\tvar XorKey = InitialCode[Password.length - 1];\n\t\tvar CurrentElement = 0x68;\n\t\tfor(var i = Password.length-1; i >= 0; --i) {\n\t\t\tvar Char = Password[i];\n\t\t\tfor(var j = 0; j != 7; ++j) {\n\t\t\t\tif(Char & 0x40) XorKey ^= XorMatrix[CurrentElement];\n\t\t\t\tChar *= 2; --CurrentElement;\n\t\t\t}\n\t\t}\n\t\treturn XorKey;\n\t};\n\treturn function(password) {\n\t\tvar Password = _JS2ANSI(password);\n\t\tvar XorKey = CreateXorKey_Method1(Password);\n\t\tvar Index = Password.length;\n\t\tvar ObfuscationArray = new_raw_buf(16);\n\t\tfor(var i = 0; i != 16; ++i) ObfuscationArray[i] = 0x00;\n\t\tvar Temp, PasswordLastChar, PadIndex;\n\t\tif((Index & 1) === 1) {\n\t\t\tTemp = XorKey >> 8;\n\t\t\tObfuscationArray[Index] = XorRor(PadArray[0], Temp);\n\t\t\t--Index;\n\t\t\tTemp = XorKey & 0xFF;\n\t\t\tPasswordLastChar = Password[Password.length - 1];\n\t\t\tObfuscationArray[Index] = XorRor(PasswordLastChar, Temp);\n\t\t}\n\t\twhile(Index > 0) {\n\t\t\t--Index;\n\t\t\tTemp = XorKey >> 8;\n\t\t\tObfuscationArray[Index] = XorRor(Password[Index], Temp);\n\t\t\t--Index;\n\t\t\tTemp = XorKey & 0xFF;\n\t\t\tObfuscationArray[Index] = XorRor(Password[Index], Temp);\n\t\t}\n\t\tIndex = 15;\n\t\tPadIndex = 15 - Password.length;\n\t\twhile(PadIndex > 0) {\n\t\t\tTemp = XorKey >> 8;\n\t\t\tObfuscationArray[Index] = XorRor(PadArray[PadIndex], Temp);\n\t\t\t--Index;\n\t\t\t--PadIndex;\n\t\t\tTemp = XorKey & 0xFF;\n\t\t\tObfuscationArray[Index] = XorRor(Password[Index], Temp);\n\t\t\t--Index;\n\t\t\t--PadIndex;\n\t\t}\n\t\treturn ObfuscationArray;\n\t};\n})();\n\n/* [MS-OFFCRYPTO] 2.3.7.3 Binary Document XOR Data Transformation Method 1 */\nvar crypto_DecryptData_Method1 = function(password, Data, XorArrayIndex, XorArray, O) {\n\t/* If XorArray is set, use it; if O is not set, make changes in-place */\n\tif(!O) O = Data;\n\tif(!XorArray) XorArray = crypto_CreateXorArray_Method1(password);\n\tvar Index, Value;\n\tfor(Index = 0; Index != Data.length; ++Index) {\n\t\tValue = Data[Index];\n\t\tValue ^= XorArray[XorArrayIndex];\n\t\tValue = ((Value>>5) | (Value<<3)) & 0xFF;\n\t\tO[Index] = Value;\n\t\t++XorArrayIndex;\n\t}\n\treturn [O, XorArrayIndex, XorArray];\n};\n\nvar crypto_MakeXorDecryptor = function(password) {\n\tvar XorArrayIndex = 0, XorArray = crypto_CreateXorArray_Method1(password);\n\treturn function(Data) {\n\t\tvar O = crypto_DecryptData_Method1(null, Data, XorArrayIndex, XorArray);\n\t\tXorArrayIndex = O[1];\n\t\treturn O[0];\n\t};\n};\n\n/* 2.5.343 */\nfunction parse_XORObfuscation(blob, length, opts, out) {\n\tvar o = { key: parseuint16(blob), verificationBytes: parseuint16(blob) };\n\tif(opts.password) o.verifier = crypto_CreatePasswordVerifier_Method1(opts.password);\n\tout.valid = o.verificationBytes === o.verifier;\n\tif(out.valid) out.insitu_decrypt = crypto_MakeXorDecryptor(opts.password);\n\treturn o;\n}\n\n/* 2.4.117 */\nfunction parse_FilePassHeader(blob, length, oo) {\n\tvar o = oo || {}; o.Info = blob.read_shift(2); blob.l -= 2;\n\tif(o.Info === 1) o.Data = parse_RC4Header(blob, length);\n\telse o.Data = parse_RC4CryptoHeader(blob, length);\n\treturn o;\n}\nfunction parse_FilePass(blob, length, opts) {\n\tvar o = { Type: blob.read_shift(2) }; /* wEncryptionType */\n\tif(o.Type) parse_FilePassHeader(blob, length-2, o);\n\telse parse_XORObfuscation(blob, length-2, opts, o);\n\treturn o;\n}\n\n\nfunction hex2RGB(h) {\n\tvar o = h.substr(h[0]===\"#\"?1:0,6);\n\treturn [parseInt(o.substr(0,2),16),parseInt(o.substr(0,2),16),parseInt(o.substr(0,2),16)];\n}\nfunction rgb2Hex(rgb) {\n\tfor(var i=0,o=1; i!=3; ++i) o = o*256 + (rgb[i]>255?255:rgb[i]<0?0:rgb[i]);\n\treturn o.toString(16).toUpperCase().substr(1);\n}\n\nfunction rgb2HSL(rgb) {\n\tvar R = rgb[0]/255, G = rgb[1]/255, B=rgb[2]/255;\n\tvar M = Math.max(R, G, B), m = Math.min(R, G, B), C = M - m;\n\tif(C === 0) return [0, 0, R];\n\n\tvar H6 = 0, S = 0, L2 = (M + m);\n\tS = C / (L2 > 1 ? 2 - L2 : L2);\n\tswitch(M){\n\t\tcase R: H6 = ((G - B) / C + 6)%6; break;\n\t\tcase G: H6 = ((B - R) / C + 2); break;\n\t\tcase B: H6 = ((R - G) / C + 4); break;\n\t}\n\treturn [H6 / 6, S, L2 / 2];\n}\n\nfunction hsl2RGB(hsl){\n\tvar H = hsl[0], S = hsl[1], L = hsl[2];\n\tvar C = S * 2 * (L < 0.5 ? L : 1 - L), m = L - C/2;\n\tvar rgb = [m,m,m], h6 = 6*H;\n\n\tvar X;\n\tif(S !== 0) switch(h6|0) {\n\t\tcase 0: case 6: X = C * h6; rgb[0] += C; rgb[1] += X; break;\n\t\tcase 1: X = C * (2 - h6);   rgb[0] += X; rgb[1] += C; break;\n\t\tcase 2: X = C * (h6 - 2);   rgb[1] += C; rgb[2] += X; break;\n\t\tcase 3: X = C * (4 - h6);   rgb[1] += X; rgb[2] += C; break;\n\t\tcase 4: X = C * (h6 - 4);   rgb[2] += C; rgb[0] += X; break;\n\t\tcase 5: X = C * (6 - h6);   rgb[2] += X; rgb[0] += C; break;\n\t}\n\tfor(var i = 0; i != 3; ++i) rgb[i] = Math.round(rgb[i]*255);\n\treturn rgb;\n}\n\n/* 18.8.3 bgColor tint algorithm */\nfunction rgb_tint(hex, tint) {\n\tif(tint === 0) return hex;\n\tvar hsl = rgb2HSL(hex2RGB(hex));\n\tif (tint < 0) hsl[2] = hsl[2] * (1 + tint);\n\telse hsl[2] = 1 - (1 - hsl[2]) * (1 - tint);\n\treturn rgb2Hex(hsl2RGB(hsl));\n}\n\n/* 18.3.1.13 width calculations */\nvar DEF_MDW = 7, MAX_MDW = 15, MIN_MDW = 1, MDW = DEF_MDW;\nfunction width2px(width) { return (( width + ((128/MDW)|0)/256 )* MDW )|0; }\nfunction px2char(px) { return (((px - 5)/MDW * 100 + 0.5)|0)/100; }\nfunction char2width(chr) { return (((chr * MDW + 5)/MDW*256)|0)/256; }\nfunction cycle_width(collw) { return char2width(px2char(width2px(collw))); }\nfunction find_mdw(collw, coll) {\n\tif(cycle_width(collw) != collw) {\n\t\tfor(MDW=DEF_MDW; MDW>MIN_MDW; --MDW) if(cycle_width(collw) === collw) break;\n\t\tif(MDW === MIN_MDW) for(MDW=DEF_MDW+1; MDW<MAX_MDW; ++MDW) if(cycle_width(collw) === collw) break;\n\t\tif(MDW === MAX_MDW) MDW = DEF_MDW;\n\t}\n}\n\n/* [MS-EXSPXML3] 2.4.54 ST_enmPattern */\nvar XLMLPatternTypeMap = {\n\t\"None\": \"none\",\n\t\"Solid\": \"solid\",\n\t\"Gray50\": \"mediumGray\",\n\t\"Gray75\": \"darkGray\",\n\t\"Gray25\": \"lightGray\",\n\t\"HorzStripe\": \"darkHorizontal\",\n\t\"VertStripe\": \"darkVertical\",\n\t\"ReverseDiagStripe\": \"darkDown\",\n\t\"DiagStripe\": \"darkUp\",\n\t\"DiagCross\": \"darkGrid\",\n\t\"ThickDiagCross\": \"darkTrellis\",\n\t\"ThinHorzStripe\": \"lightHorizontal\",\n\t\"ThinVertStripe\": \"lightVertical\",\n\t\"ThinReverseDiagStripe\": \"lightDown\",\n\t\"ThinHorzCross\": \"lightGrid\"\n};\n\nvar styles = {}; // shared styles\n\nvar themes = {}; // shared themes\n\n/* 18.8.21 fills CT_Fills */\nfunction parse_fills(t, opts) {\n\tstyles.Fills = [];\n\tvar fill = {};\n\tt[0].match(tagregex).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(y[0]) {\n\t\t\tcase '<fills': case '<fills>': case '</fills>': break;\n\n\t\t\t/* 18.8.20 fill CT_Fill */\n\t\t\tcase '<fill>': break;\n\t\t\tcase '</fill>': styles.Fills.push(fill); fill = {}; break;\n\n\t\t\t/* 18.8.32 patternFill CT_PatternFill */\n\t\t\tcase '<patternFill':\n\t\t\t\tif(y.patternType) fill.patternType = y.patternType;\n\t\t\t\tbreak;\n\t\t\tcase '<patternFill/>': case '</patternFill>': break;\n\n\t\t\t/* 18.8.3 bgColor CT_Color */\n\t\t\tcase '<bgColor':\n\t\t\t\tif(!fill.bgColor) fill.bgColor = {};\n\t\t\t\tif(y.indexed) fill.bgColor.indexed = parseInt(y.indexed, 10);\n\t\t\t\tif(y.theme) fill.bgColor.theme = parseInt(y.theme, 10);\n\t\t\t\tif(y.tint) fill.bgColor.tint = parseFloat(y.tint);\n\t\t\t\t/* Excel uses ARGB strings */\n\t\t\t\tif(y.rgb) fill.bgColor.rgb = y.rgb.substring(y.rgb.length - 6);\n\t\t\t\tbreak;\n\t\t\tcase '<bgColor/>': case '</bgColor>': break;\n\n\t\t\t/* 18.8.19 fgColor CT_Color */\n\t\t\tcase '<fgColor':\n\t\t\t\tif(!fill.fgColor) fill.fgColor = {};\n\t\t\t\tif(y.theme) fill.fgColor.theme = parseInt(y.theme, 10);\n\t\t\t\tif(y.tint) fill.fgColor.tint = parseFloat(y.tint);\n\t\t\t\t/* Excel uses ARGB strings */\n\t\t\t\tif(y.rgb) fill.fgColor.rgb = y.rgb.substring(y.rgb.length - 6);\n\t\t\t\tbreak;\n\t\t\tcase '<fgColor/>': case '</fgColor>': break;\n\n\t\t\tdefault: if(opts.WTF) throw 'unrecognized ' + y[0] + ' in fills';\n\t\t}\n\t});\n}\n\n/* 18.8.31 numFmts CT_NumFmts */\nfunction parse_numFmts(t, opts) {\n\tstyles.NumberFmt = [];\n\tvar k = keys(SSF._table);\n\tfor(var i=0; i < k.length; ++i) styles.NumberFmt[k[i]] = SSF._table[k[i]];\n\tvar m = t[0].match(tagregex);\n\tfor(i=0; i < m.length; ++i) {\n\t\tvar y = parsexmltag(m[i]);\n\t\tswitch(y[0]) {\n\t\t\tcase '<numFmts': case '</numFmts>': case '<numFmts/>': case '<numFmts>': break;\n\t\t\tcase '<numFmt': {\n\t\t\t\tvar f=unescapexml(utf8read(y.formatCode)), j=parseInt(y.numFmtId,10);\n\t\t\t\tstyles.NumberFmt[j] = f; if(j>0) SSF.load(f,j);\n\t\t\t} break;\n\t\t\tdefault: if(opts.WTF) throw 'unrecognized ' + y[0] + ' in numFmts';\n\t\t}\n\t}\n}\n\nfunction write_numFmts(NF, opts) {\n\tvar o = [\"<numFmts>\"];\n\t[[5,8],[23,26],[41,44],[63,66],[164,392]].forEach(function(r) {\n\t\tfor(var i = r[0]; i <= r[1]; ++i) if(NF[i] !== undefined) o[o.length] = (writextag('numFmt',null,{numFmtId:i,formatCode:escapexml(NF[i])}));\n\t});\n\tif(o.length === 1) return \"\";\n\to[o.length] = (\"</numFmts>\");\n\to[0] = writextag('numFmts', null, { count:o.length-2 }).replace(\"/>\", \">\");\n\treturn o.join(\"\");\n}\n\n/* 18.8.10 cellXfs CT_CellXfs */\nfunction parse_cellXfs(t, opts) {\n\tstyles.CellXf = [];\n\tt[0].match(tagregex).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(y[0]) {\n\t\t\tcase '<cellXfs': case '<cellXfs>': case '<cellXfs/>': case '</cellXfs>': break;\n\n\t\t\t/* 18.8.45 xf CT_Xf */\n\t\t\tcase '<xf': delete y[0];\n\t\t\t\tif(y.numFmtId) y.numFmtId = parseInt(y.numFmtId, 10);\n\t\t\t\tif(y.fillId) y.fillId = parseInt(y.fillId, 10);\n\t\t\t\tstyles.CellXf.push(y); break;\n\t\t\tcase '</xf>': break;\n\n\t\t\t/* 18.8.1 alignment CT_CellAlignment */\n\t\t\tcase '<alignment': case '<alignment/>': break;\n\n\t\t\t/* 18.8.33 protection CT_CellProtection */\n\t\t\tcase '<protection': case '</protection>': case '<protection/>': break;\n\n\t\t\tcase '<extLst': case '</extLst>': break;\n\t\t\tcase '<ext': break;\n\t\t\tdefault: if(opts.WTF) throw 'unrecognized ' + y[0] + ' in cellXfs';\n\t\t}\n\t});\n}\n\nfunction write_cellXfs(cellXfs) {\n\tvar o = [];\n\to[o.length] = (writextag('cellXfs',null));\n\tcellXfs.forEach(function(c) { o[o.length] = (writextag('xf', null, c)); });\n\to[o.length] = (\"</cellXfs>\");\n\tif(o.length === 2) return \"\";\n\to[0] = writextag('cellXfs',null, {count:o.length-2}).replace(\"/>\",\">\");\n\treturn o.join(\"\");\n}\n\n/* 18.8 Styles CT_Stylesheet*/\nvar parse_sty_xml= (function make_pstyx() {\nvar numFmtRegex = /<numFmts([^>]*)>.*<\\/numFmts>/;\nvar cellXfRegex = /<cellXfs([^>]*)>.*<\\/cellXfs>/;\nvar fillsRegex = /<fills([^>]*)>.*<\\/fills>/;\n\nreturn function parse_sty_xml(data, opts) {\n\t/* 18.8.39 styleSheet CT_Stylesheet */\n\tvar t;\n\n\t/* numFmts CT_NumFmts ? */\n\tif((t=data.match(numFmtRegex))) parse_numFmts(t, opts);\n\n\t/* fonts CT_Fonts ? */\n\t/*if((t=data.match(/<fonts([^>]*)>.*<\\/fonts>/))) parse_fonts(t, opts);*/\n\n\t/* fills CT_Fills */\n\tif((t=data.match(fillsRegex))) parse_fills(t, opts);\n\n\t/* borders CT_Borders ? */\n\t/* cellStyleXfs CT_CellStyleXfs ? */\n\n\t/* cellXfs CT_CellXfs ? */\n\tif((t=data.match(cellXfRegex))) parse_cellXfs(t, opts);\n\n\t/* dxfs CT_Dxfs ? */\n\t/* tableStyles CT_TableStyles ? */\n\t/* colors CT_Colors ? */\n\t/* extLst CT_ExtensionList ? */\n\n\treturn styles;\n};\n})();\n\nvar STYLES_XML_ROOT = writextag('styleSheet', null, {\n\t'xmlns': XMLNS.main[0],\n\t'xmlns:vt': XMLNS.vt\n});\n\nRELS.STY = \"http://schemas.openxmlformats.org/officeDocument/2006/relationships/styles\";\n\nfunction write_sty_xml(wb, opts) {\n\tvar o = [XML_HEADER, STYLES_XML_ROOT], w;\n\tif((w = write_numFmts(wb.SSF)) != null) o[o.length] = w;\n\to[o.length] = ('<fonts count=\"1\"><font><sz val=\"12\"/><color theme=\"1\"/><name val=\"Calibri\"/><family val=\"2\"/><scheme val=\"minor\"/></font></fonts>');\n\to[o.length] = ('<fills count=\"2\"><fill><patternFill patternType=\"none\"/></fill><fill><patternFill patternType=\"gray125\"/></fill></fills>');\n\to[o.length] = ('<borders count=\"1\"><border><left/><right/><top/><bottom/><diagonal/></border></borders>');\n\to[o.length] = ('<cellStyleXfs count=\"1\"><xf numFmtId=\"0\" fontId=\"0\" fillId=\"0\" borderId=\"0\"/></cellStyleXfs>');\n\tif((w = write_cellXfs(opts.cellXfs))) o[o.length] = (w);\n\to[o.length] = ('<cellStyles count=\"1\"><cellStyle name=\"Normal\" xfId=\"0\" builtinId=\"0\"/></cellStyles>');\n\to[o.length] = ('<dxfs count=\"0\"/>');\n\to[o.length] = ('<tableStyles count=\"0\" defaultTableStyle=\"TableStyleMedium9\" defaultPivotStyle=\"PivotStyleMedium4\"/>');\n\n\tif(o.length>2){ o[o.length] = ('</styleSheet>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* [MS-XLSB] 2.4.651 BrtFmt */\nfunction parse_BrtFmt(data, length) {\n\tvar ifmt = data.read_shift(2);\n\tvar stFmtCode = parse_XLWideString(data,length-2);\n\treturn [ifmt, stFmtCode];\n}\n\n/* [MS-XLSB] 2.4.653 BrtFont TODO */\nfunction parse_BrtFont(data, length) {\n\tvar out = {flags:{}};\n\tout.dyHeight = data.read_shift(2);\n\tout.grbit = parse_FontFlags(data, 2);\n\tout.bls = data.read_shift(2);\n\tout.sss = data.read_shift(2);\n\tout.uls = data.read_shift(1);\n\tout.bFamily = data.read_shift(1);\n\tout.bCharSet = data.read_shift(1);\n\tdata.l++;\n\tout.brtColor = parse_BrtColor(data, 8);\n\tout.bFontScheme = data.read_shift(1);\n\tout.name = parse_XLWideString(data, length - 21);\n\n\tout.flags.Bold = out.bls === 0x02BC;\n\tout.flags.Italic = out.grbit.fItalic;\n\tout.flags.Strikeout = out.grbit.fStrikeout;\n\tout.flags.Outline = out.grbit.fOutline;\n\tout.flags.Shadow = out.grbit.fShadow;\n\tout.flags.Condense = out.grbit.fCondense;\n\tout.flags.Extend = out.grbit.fExtend;\n\tout.flags.Sub = out.sss & 0x2;\n\tout.flags.Sup = out.sss & 0x1;\n\treturn out;\n}\n\n/* [MS-XLSB] 2.4.816 BrtXF */\nfunction parse_BrtXF(data, length) {\n\tvar ixfeParent = data.read_shift(2);\n\tvar ifmt = data.read_shift(2);\n\tparsenoop(data, length-4);\n\treturn {ixfe:ixfeParent, ifmt:ifmt };\n}\n\n/* [MS-XLSB] 2.1.7.50 Styles */\nfunction parse_sty_bin(data, opts) {\n\tstyles.NumberFmt = [];\n\tfor(var y in SSF._table) styles.NumberFmt[y] = SSF._table[y];\n\n\tstyles.CellXf = [];\n\tvar state = \"\"; /* TODO: this should be a stack */\n\tvar pass = false;\n\trecordhopper(data, function hopper_sty(val, R, RT) {\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtFmt':\n\t\t\t\tstyles.NumberFmt[val[0]] = val[1]; SSF.load(val[1], val[0]);\n\t\t\t\tbreak;\n\t\t\tcase 'BrtFont': break; /* TODO */\n\t\t\tcase 'BrtKnownFonts': break; /* TODO */\n\t\t\tcase 'BrtFill': break; /* TODO */\n\t\t\tcase 'BrtBorder': break; /* TODO */\n\t\t\tcase 'BrtXF':\n\t\t\t\tif(state === \"CELLXFS\") {\n\t\t\t\t\tstyles.CellXf.push(val);\n\t\t\t\t}\n\t\t\t\tbreak; /* TODO */\n\t\t\tcase 'BrtStyle': break; /* TODO */\n\t\t\tcase 'BrtDXF': break; /* TODO */\n\t\t\tcase 'BrtMRUColor': break; /* TODO */\n\t\t\tcase 'BrtIndexedColor': break; /* TODO */\n\t\t\tcase 'BrtBeginStyleSheet': break;\n\t\t\tcase 'BrtEndStyleSheet': break;\n\t\t\tcase 'BrtBeginTableStyle': break;\n\t\t\tcase 'BrtTableStyleElement': break;\n\t\t\tcase 'BrtEndTableStyle': break;\n\t\t\tcase 'BrtBeginFmts': state = \"FMTS\"; break;\n\t\t\tcase 'BrtEndFmts': state = \"\"; break;\n\t\t\tcase 'BrtBeginFonts': state = \"FONTS\"; break;\n\t\t\tcase 'BrtEndFonts': state = \"\"; break;\n\t\t\tcase 'BrtACBegin': state = \"ACFONTS\"; break;\n\t\t\tcase 'BrtACEnd': state = \"\"; break;\n\t\t\tcase 'BrtBeginFills': state = \"FILLS\"; break;\n\t\t\tcase 'BrtEndFills': state = \"\"; break;\n\t\t\tcase 'BrtBeginBorders': state = \"BORDERS\"; break;\n\t\t\tcase 'BrtEndBorders': state = \"\"; break;\n\t\t\tcase 'BrtBeginCellStyleXFs': state = \"CELLSTYLEXFS\"; break;\n\t\t\tcase 'BrtEndCellStyleXFs': state = \"\"; break;\n\t\t\tcase 'BrtBeginCellXFs': state = \"CELLXFS\"; break;\n\t\t\tcase 'BrtEndCellXFs': state = \"\"; break;\n\t\t\tcase 'BrtBeginStyles': state = \"STYLES\"; break;\n\t\t\tcase 'BrtEndStyles': state = \"\"; break;\n\t\t\tcase 'BrtBeginDXFs': state = \"DXFS\"; break;\n\t\t\tcase 'BrtEndDXFs': state = \"\"; break;\n\t\t\tcase 'BrtBeginTableStyles': state = \"TABLESTYLES\"; break;\n\t\t\tcase 'BrtEndTableStyles': state = \"\"; break;\n\t\t\tcase 'BrtBeginColorPalette': state = \"COLORPALETTE\"; break;\n\t\t\tcase 'BrtEndColorPalette': state = \"\"; break;\n\t\t\tcase 'BrtBeginIndexedColors': state = \"INDEXEDCOLORS\"; break;\n\t\t\tcase 'BrtEndIndexedColors': state = \"\"; break;\n\t\t\tcase 'BrtBeginMRUColors': state = \"MRUCOLORS\"; break;\n\t\t\tcase 'BrtEndMRUColors': state = \"\"; break;\n\t\t\tcase 'BrtFRTBegin': pass = true; break;\n\t\t\tcase 'BrtFRTEnd': pass = false; break;\n\t\t\tcase 'BrtBeginStyleSheetExt14': break;\n\t\t\tcase 'BrtBeginSlicerStyles': break;\n\t\t\tcase 'BrtEndSlicerStyles': break;\n\t\t\tcase 'BrtBeginTimelineStylesheetExt15': break;\n\t\t\tcase 'BrtEndTimelineStylesheetExt15': break;\n\t\t\tcase 'BrtBeginTimelineStyles': break;\n\t\t\tcase 'BrtEndTimelineStyles': break;\n\t\t\tcase 'BrtEndStyleSheetExt14': break;\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + RT + \" \" + R.n);\n\t\t}\n\t});\n\treturn styles;\n}\n\n/* [MS-XLSB] 2.1.7.50 Styles */\nfunction write_sty_bin(data, opts) {\n\tvar ba = buf_array();\n\twrite_record(ba, \"BrtBeginStyleSheet\");\n\t/* [FMTS] */\n\t/* [FONTS] */\n\t/* [FILLS] */\n\t/* [BORDERS] */\n\t/* CELLSTYLEXFS */\n\t/* CELLXFS*/\n\t/* STYLES */\n\t/* DXFS */\n\t/* TABLESTYLES */\n\t/* [COLORPALETTE] */\n\t/* FRTSTYLESHEET*/\n\twrite_record(ba, \"BrtEndStyleSheet\");\n\treturn ba.end();\n}\nRELS.THEME = \"http://schemas.openxmlformats.org/officeDocument/2006/relationships/theme\";\n\n/* 20.1.6.2 clrScheme CT_ColorScheme */\nfunction parse_clrScheme(t, opts) {\n\tthemes.themeElements.clrScheme = [];\n\tvar color = {};\n\tt[0].match(tagregex).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(y[0]) {\n\t\t\tcase '<a:clrScheme': case '</a:clrScheme>': break;\n\n\t\t\t/* 20.1.2.3.32 srgbClr CT_SRgbColor */\n\t\t\tcase '<a:srgbClr': color.rgb = y.val; break;\n\n\t\t\t/* 20.1.2.3.33 sysClr CT_SystemColor */\n\t\t\tcase '<a:sysClr': color.rgb = y.lastClr; break;\n\n\t\t\t/* 20.1.4.1.9 dk1 (Dark 1) */\n\t\t\tcase '<a:dk1>':\n\t\t\tcase '</a:dk1>':\n\t\t\t/* 20.1.4.1.10 dk2 (Dark 2) */\n\t\t\tcase '<a:dk2>':\n\t\t\tcase '</a:dk2>':\n\t\t\t/* 20.1.4.1.22 lt1 (Light 1) */\n\t\t\tcase '<a:lt1>':\n\t\t\tcase '</a:lt1>':\n\t\t\t/* 20.1.4.1.23 lt2 (Light 2) */\n\t\t\tcase '<a:lt2>':\n\t\t\tcase '</a:lt2>':\n\t\t\t/* 20.1.4.1.1 accent1 (Accent 1) */\n\t\t\tcase '<a:accent1>':\n\t\t\tcase '</a:accent1>':\n\t\t\t/* 20.1.4.1.2 accent2 (Accent 2) */\n\t\t\tcase '<a:accent2>':\n\t\t\tcase '</a:accent2>':\n\t\t\t/* 20.1.4.1.3 accent3 (Accent 3) */\n\t\t\tcase '<a:accent3>':\n\t\t\tcase '</a:accent3>':\n\t\t\t/* 20.1.4.1.4 accent4 (Accent 4) */\n\t\t\tcase '<a:accent4>':\n\t\t\tcase '</a:accent4>':\n\t\t\t/* 20.1.4.1.5 accent5 (Accent 5) */\n\t\t\tcase '<a:accent5>':\n\t\t\tcase '</a:accent5>':\n\t\t\t/* 20.1.4.1.6 accent6 (Accent 6) */\n\t\t\tcase '<a:accent6>':\n\t\t\tcase '</a:accent6>':\n\t\t\t/* 20.1.4.1.19 hlink (Hyperlink) */\n\t\t\tcase '<a:hlink>':\n\t\t\tcase '</a:hlink>':\n\t\t\t/* 20.1.4.1.15 folHlink (Followed Hyperlink) */\n\t\t\tcase '<a:folHlink>':\n\t\t\tcase '</a:folHlink>':\n\t\t\t\tif (y[0][1] === '/') {\n\t\t\t\t\tthemes.themeElements.clrScheme.push(color);\n\t\t\t\t\tcolor = {};\n\t\t\t\t} else {\n\t\t\t\t\tcolor.name = y[0].substring(3, y[0].length - 1);\n\t\t\t\t}\n\t\t\t\tbreak;\n\n\t\t\tdefault: if(opts.WTF) throw 'unrecognized ' + y[0] + ' in clrScheme';\n\t\t}\n\t});\n}\n\n/* 20.1.4.1.18 fontScheme CT_FontScheme */\nfunction parse_fontScheme(t, opts) { }\n\n/* 20.1.4.1.15 fmtScheme CT_StyleMatrix */\nfunction parse_fmtScheme(t, opts) { }\n\nvar clrsregex = /<a:clrScheme([^>]*)>[^\\u2603]*<\\/a:clrScheme>/;\nvar fntsregex = /<a:fontScheme([^>]*)>[^\\u2603]*<\\/a:fontScheme>/;\nvar fmtsregex = /<a:fmtScheme([^>]*)>[^\\u2603]*<\\/a:fmtScheme>/;\n\n/* 20.1.6.10 themeElements CT_BaseStyles */\nfunction parse_themeElements(data, opts) {\n\tthemes.themeElements = {};\n\n\tvar t;\n\n\t[\n\t\t/* clrScheme CT_ColorScheme */\n\t\t['clrScheme', clrsregex, parse_clrScheme],\n\t\t/* fontScheme CT_FontScheme */\n\t\t['fontScheme', fntsregex, parse_fontScheme],\n\t\t/* fmtScheme CT_StyleMatrix */\n\t\t['fmtScheme', fmtsregex, parse_fmtScheme]\n\t].forEach(function(m) {\n\t\tif(!(t=data.match(m[1]))) throw m[0] + ' not found in themeElements';\n\t\tm[2](t, opts);\n\t});\n}\n\nvar themeltregex = /<a:themeElements([^>]*)>[^\\u2603]*<\\/a:themeElements>/;\n\n/* 14.2.7 Theme Part */\nfunction parse_theme_xml(data, opts) {\n\t/* 20.1.6.9 theme CT_OfficeStyleSheet */\n\tif(!data || data.length === 0) return themes;\n\n\tvar t;\n\n\t/* themeElements CT_BaseStyles */\n\tif(!(t=data.match(themeltregex))) throw 'themeElements not found in theme';\n\tparse_themeElements(t[0], opts);\n\n\treturn themes;\n}\n\nfunction write_theme() { return '<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?>\\n<a:theme xmlns:a=\"http://schemas.openxmlformats.org/drawingml/2006/main\" name=\"Office Theme\"><a:themeElements><a:clrScheme name=\"Office\"><a:dk1><a:sysClr val=\"windowText\" lastClr=\"000000\"/></a:dk1><a:lt1><a:sysClr val=\"window\" lastClr=\"FFFFFF\"/></a:lt1><a:dk2><a:srgbClr val=\"1F497D\"/></a:dk2><a:lt2><a:srgbClr val=\"EEECE1\"/></a:lt2><a:accent1><a:srgbClr val=\"4F81BD\"/></a:accent1><a:accent2><a:srgbClr val=\"C0504D\"/></a:accent2><a:accent3><a:srgbClr val=\"9BBB59\"/></a:accent3><a:accent4><a:srgbClr val=\"8064A2\"/></a:accent4><a:accent5><a:srgbClr val=\"4BACC6\"/></a:accent5><a:accent6><a:srgbClr val=\"F79646\"/></a:accent6><a:hlink><a:srgbClr val=\"0000FF\"/></a:hlink><a:folHlink><a:srgbClr val=\"800080\"/></a:folHlink></a:clrScheme><a:fontScheme name=\"Office\"><a:majorFont><a:latin typeface=\"Cambria\"/><a:ea typeface=\"\"/><a:cs typeface=\"\"/><a:font script=\"Jpan\" typeface=\"ＭＳ Ｐゴシック\"/><a:font script=\"Hang\" typeface=\"맑은 고딕\"/><a:font script=\"Hans\" typeface=\"宋体\"/><a:font script=\"Hant\" typeface=\"新細明體\"/><a:font script=\"Arab\" typeface=\"Times New Roman\"/><a:font script=\"Hebr\" typeface=\"Times New Roman\"/><a:font script=\"Thai\" typeface=\"Tahoma\"/><a:font script=\"Ethi\" typeface=\"Nyala\"/><a:font script=\"Beng\" typeface=\"Vrinda\"/><a:font script=\"Gujr\" typeface=\"Shruti\"/><a:font script=\"Khmr\" typeface=\"MoolBoran\"/><a:font script=\"Knda\" typeface=\"Tunga\"/><a:font script=\"Guru\" typeface=\"Raavi\"/><a:font script=\"Cans\" typeface=\"Euphemia\"/><a:font script=\"Cher\" typeface=\"Plantagenet Cherokee\"/><a:font script=\"Yiii\" typeface=\"Microsoft Yi Baiti\"/><a:font script=\"Tibt\" typeface=\"Microsoft Himalaya\"/><a:font script=\"Thaa\" typeface=\"MV Boli\"/><a:font script=\"Deva\" typeface=\"Mangal\"/><a:font script=\"Telu\" typeface=\"Gautami\"/><a:font script=\"Taml\" typeface=\"Latha\"/><a:font script=\"Syrc\" typeface=\"Estrangelo Edessa\"/><a:font script=\"Orya\" typeface=\"Kalinga\"/><a:font script=\"Mlym\" typeface=\"Kartika\"/><a:font script=\"Laoo\" typeface=\"DokChampa\"/><a:font script=\"Sinh\" typeface=\"Iskoola Pota\"/><a:font script=\"Mong\" typeface=\"Mongolian Baiti\"/><a:font script=\"Viet\" typeface=\"Times New Roman\"/><a:font script=\"Uigh\" typeface=\"Microsoft Uighur\"/><a:font script=\"Geor\" typeface=\"Sylfaen\"/></a:majorFont><a:minorFont><a:latin typeface=\"Calibri\"/><a:ea typeface=\"\"/><a:cs typeface=\"\"/><a:font script=\"Jpan\" typeface=\"ＭＳ Ｐゴシック\"/><a:font script=\"Hang\" typeface=\"맑은 고딕\"/><a:font script=\"Hans\" typeface=\"宋体\"/><a:font script=\"Hant\" typeface=\"新細明體\"/><a:font script=\"Arab\" typeface=\"Arial\"/><a:font script=\"Hebr\" typeface=\"Arial\"/><a:font script=\"Thai\" typeface=\"Tahoma\"/><a:font script=\"Ethi\" typeface=\"Nyala\"/><a:font script=\"Beng\" typeface=\"Vrinda\"/><a:font script=\"Gujr\" typeface=\"Shruti\"/><a:font script=\"Khmr\" typeface=\"DaunPenh\"/><a:font script=\"Knda\" typeface=\"Tunga\"/><a:font script=\"Guru\" typeface=\"Raavi\"/><a:font script=\"Cans\" typeface=\"Euphemia\"/><a:font script=\"Cher\" typeface=\"Plantagenet Cherokee\"/><a:font script=\"Yiii\" typeface=\"Microsoft Yi Baiti\"/><a:font script=\"Tibt\" typeface=\"Microsoft Himalaya\"/><a:font script=\"Thaa\" typeface=\"MV Boli\"/><a:font script=\"Deva\" typeface=\"Mangal\"/><a:font script=\"Telu\" typeface=\"Gautami\"/><a:font script=\"Taml\" typeface=\"Latha\"/><a:font script=\"Syrc\" typeface=\"Estrangelo Edessa\"/><a:font script=\"Orya\" typeface=\"Kalinga\"/><a:font script=\"Mlym\" typeface=\"Kartika\"/><a:font script=\"Laoo\" typeface=\"DokChampa\"/><a:font script=\"Sinh\" typeface=\"Iskoola Pota\"/><a:font script=\"Mong\" typeface=\"Mongolian Baiti\"/><a:font script=\"Viet\" typeface=\"Arial\"/><a:font script=\"Uigh\" typeface=\"Microsoft Uighur\"/><a:font script=\"Geor\" typeface=\"Sylfaen\"/></a:minorFont></a:fontScheme><a:fmtScheme name=\"Office\"><a:fillStyleLst><a:solidFill><a:schemeClr val=\"phClr\"/></a:solidFill><a:gradFill rotWithShape=\"1\"><a:gsLst><a:gs pos=\"0\"><a:schemeClr val=\"phClr\"><a:tint val=\"50000\"/><a:satMod val=\"300000\"/></a:schemeClr></a:gs><a:gs pos=\"35000\"><a:schemeClr val=\"phClr\"><a:tint val=\"37000\"/><a:satMod val=\"300000\"/></a:schemeClr></a:gs><a:gs pos=\"100000\"><a:schemeClr val=\"phClr\"><a:tint val=\"15000\"/><a:satMod val=\"350000\"/></a:schemeClr></a:gs></a:gsLst><a:lin ang=\"16200000\" scaled=\"1\"/></a:gradFill><a:gradFill rotWithShape=\"1\"><a:gsLst><a:gs pos=\"0\"><a:schemeClr val=\"phClr\"><a:tint val=\"100000\"/><a:shade val=\"100000\"/><a:satMod val=\"130000\"/></a:schemeClr></a:gs><a:gs pos=\"100000\"><a:schemeClr val=\"phClr\"><a:tint val=\"50000\"/><a:shade val=\"100000\"/><a:satMod val=\"350000\"/></a:schemeClr></a:gs></a:gsLst><a:lin ang=\"16200000\" scaled=\"0\"/></a:gradFill></a:fillStyleLst><a:lnStyleLst><a:ln w=\"9525\" cap=\"flat\" cmpd=\"sng\" algn=\"ctr\"><a:solidFill><a:schemeClr val=\"phClr\"><a:shade val=\"95000\"/><a:satMod val=\"105000\"/></a:schemeClr></a:solidFill><a:prstDash val=\"solid\"/></a:ln><a:ln w=\"25400\" cap=\"flat\" cmpd=\"sng\" algn=\"ctr\"><a:solidFill><a:schemeClr val=\"phClr\"/></a:solidFill><a:prstDash val=\"solid\"/></a:ln><a:ln w=\"38100\" cap=\"flat\" cmpd=\"sng\" algn=\"ctr\"><a:solidFill><a:schemeClr val=\"phClr\"/></a:solidFill><a:prstDash val=\"solid\"/></a:ln></a:lnStyleLst><a:effectStyleLst><a:effectStyle><a:effectLst><a:outerShdw blurRad=\"40000\" dist=\"20000\" dir=\"5400000\" rotWithShape=\"0\"><a:srgbClr val=\"000000\"><a:alpha val=\"38000\"/></a:srgbClr></a:outerShdw></a:effectLst></a:effectStyle><a:effectStyle><a:effectLst><a:outerShdw blurRad=\"40000\" dist=\"23000\" dir=\"5400000\" rotWithShape=\"0\"><a:srgbClr val=\"000000\"><a:alpha val=\"35000\"/></a:srgbClr></a:outerShdw></a:effectLst></a:effectStyle><a:effectStyle><a:effectLst><a:outerShdw blurRad=\"40000\" dist=\"23000\" dir=\"5400000\" rotWithShape=\"0\"><a:srgbClr val=\"000000\"><a:alpha val=\"35000\"/></a:srgbClr></a:outerShdw></a:effectLst><a:scene3d><a:camera prst=\"orthographicFront\"><a:rot lat=\"0\" lon=\"0\" rev=\"0\"/></a:camera><a:lightRig rig=\"threePt\" dir=\"t\"><a:rot lat=\"0\" lon=\"0\" rev=\"1200000\"/></a:lightRig></a:scene3d><a:sp3d><a:bevelT w=\"63500\" h=\"25400\"/></a:sp3d></a:effectStyle></a:effectStyleLst><a:bgFillStyleLst><a:solidFill><a:schemeClr val=\"phClr\"/></a:solidFill><a:gradFill rotWithShape=\"1\"><a:gsLst><a:gs pos=\"0\"><a:schemeClr val=\"phClr\"><a:tint val=\"40000\"/><a:satMod val=\"350000\"/></a:schemeClr></a:gs><a:gs pos=\"40000\"><a:schemeClr val=\"phClr\"><a:tint val=\"45000\"/><a:shade val=\"99000\"/><a:satMod val=\"350000\"/></a:schemeClr></a:gs><a:gs pos=\"100000\"><a:schemeClr val=\"phClr\"><a:shade val=\"20000\"/><a:satMod val=\"255000\"/></a:schemeClr></a:gs></a:gsLst><a:path path=\"circle\"><a:fillToRect l=\"50000\" t=\"-80000\" r=\"50000\" b=\"180000\"/></a:path></a:gradFill><a:gradFill rotWithShape=\"1\"><a:gsLst><a:gs pos=\"0\"><a:schemeClr val=\"phClr\"><a:tint val=\"80000\"/><a:satMod val=\"300000\"/></a:schemeClr></a:gs><a:gs pos=\"100000\"><a:schemeClr val=\"phClr\"><a:shade val=\"30000\"/><a:satMod val=\"200000\"/></a:schemeClr></a:gs></a:gsLst><a:path path=\"circle\"><a:fillToRect l=\"50000\" t=\"50000\" r=\"50000\" b=\"50000\"/></a:path></a:gradFill></a:bgFillStyleLst></a:fmtScheme></a:themeElements><a:objectDefaults><a:spDef><a:spPr/><a:bodyPr/><a:lstStyle/><a:style><a:lnRef idx=\"1\"><a:schemeClr val=\"accent1\"/></a:lnRef><a:fillRef idx=\"3\"><a:schemeClr val=\"accent1\"/></a:fillRef><a:effectRef idx=\"2\"><a:schemeClr val=\"accent1\"/></a:effectRef><a:fontRef idx=\"minor\"><a:schemeClr val=\"lt1\"/></a:fontRef></a:style></a:spDef><a:lnDef><a:spPr/><a:bodyPr/><a:lstStyle/><a:style><a:lnRef idx=\"2\"><a:schemeClr val=\"accent1\"/></a:lnRef><a:fillRef idx=\"0\"><a:schemeClr val=\"accent1\"/></a:fillRef><a:effectRef idx=\"1\"><a:schemeClr val=\"accent1\"/></a:effectRef><a:fontRef idx=\"minor\"><a:schemeClr val=\"tx1\"/></a:fontRef></a:style></a:lnDef></a:objectDefaults><a:extraClrSchemeLst/></a:theme>'; }\n/* [MS-XLS] 2.4.326 TODO: payload is a zip file */\nfunction parse_Theme(blob, length) {\n\tvar dwThemeVersion = blob.read_shift(4);\n\tif(dwThemeVersion === 124226) return;\n\tblob.l += length-4;\n}\n\n/* 2.5.49 */\nfunction parse_ColorTheme(blob, length) { return blob.read_shift(4); }\n\n/* 2.5.155 */\nfunction parse_FullColorExt(blob, length) {\n\tvar o = {};\n\to.xclrType = blob.read_shift(2);\n\to.nTintShade = blob.read_shift(2);\n\tswitch(o.xclrType) {\n\t\tcase 0: blob.l += 4; break;\n\t\tcase 1: o.xclrValue = parse_IcvXF(blob, 4); break;\n\t\tcase 2: o.xclrValue = parse_LongRGBA(blob, 4); break;\n\t\tcase 3: o.xclrValue = parse_ColorTheme(blob, 4); break;\n\t\tcase 4: blob.l += 4; break;\n\t}\n\tblob.l += 8;\n\treturn o;\n}\n\n/* 2.5.164 TODO: read 7 bits*/\nfunction parse_IcvXF(blob, length) {\n\treturn parsenoop(blob, length);\n}\n\n/* 2.5.280 */\nfunction parse_XFExtGradient(blob, length) {\n\treturn parsenoop(blob, length);\n}\n\n/* 2.5.108 */\nfunction parse_ExtProp(blob, length) {\n\tvar extType = blob.read_shift(2);\n\tvar cb = blob.read_shift(2);\n\tvar o = [extType];\n\tswitch(extType) {\n\t\tcase 0x04: case 0x05: case 0x07: case 0x08:\n\t\tcase 0x09: case 0x0A: case 0x0B: case 0x0D:\n\t\t\to[1] = parse_FullColorExt(blob, cb); break;\n\t\tcase 0x06: o[1] = parse_XFExtGradient(blob, cb); break;\n\t\tcase 0x0E: case 0x0F: o[1] = blob.read_shift(cb === 5 ? 1 : 2); break;\n\t\tdefault: throw new Error(\"Unrecognized ExtProp type: \" + extType + \" \" + cb);\n\t}\n\treturn o;\n}\n\n/* 2.4.355 */\nfunction parse_XFExt(blob, length) {\n\tvar end = blob.l + length;\n\tblob.l += 2;\n\tvar ixfe = blob.read_shift(2);\n\tblob.l += 2;\n\tvar cexts = blob.read_shift(2);\n\tvar ext = [];\n\twhile(cexts-- > 0) ext.push(parse_ExtProp(blob, end-blob.l));\n\treturn {ixfe:ixfe, ext:ext};\n}\n\n/* xf is an XF, see parse_XFExt for xfext */\nfunction update_xfext(xf, xfext) {\n\txfext.forEach(function(xfe) {\n\t\tswitch(xfe[0]) { /* 2.5.108 extPropData */\n\t\t\tcase 0x04: break; /* foreground color */\n\t\t\tcase 0x05: break; /* background color */\n\t\t\tcase 0x07: case 0x08: case 0x09: case 0x0a: break;\n\t\t\tcase 0x0d: break; /* text color */\n\t\t\tcase 0x0e: break; /* font scheme */\n\t\t\tdefault: throw \"bafuq\" + xfe[0].toString(16);\n\t\t}\n\t});\n}\n\n/* 18.6 Calculation Chain */\nfunction parse_cc_xml(data, opts) {\n\tvar d = [];\n\tvar l = 0, i = 1;\n\t(data.match(tagregex)||[]).forEach(function(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(y[0]) {\n\t\t\tcase '<?xml': break;\n\t\t\t/* 18.6.2  calcChain CT_CalcChain 1 */\n\t\t\tcase '<calcChain': case '<calcChain>': case '</calcChain>': break;\n\t\t\t/* 18.6.1  c CT_CalcCell 1 */\n\t\t\tcase '<c': delete y[0]; if(y.i) i = y.i; else y.i = i; d.push(y); break;\n\t\t}\n\t});\n\treturn d;\n}\n\nfunction write_cc_xml(data, opts) { }\n/* [MS-XLSB] 2.6.4.1 */\nfunction parse_BrtCalcChainItem$(data, length) {\n\tvar out = {};\n\tout.i = data.read_shift(4);\n\tvar cell = {};\n\tcell.r = data.read_shift(4);\n\tcell.c = data.read_shift(4);\n\tout.r = encode_cell(cell);\n\tvar flags = data.read_shift(1);\n\tif(flags & 0x2) out.l = '1';\n\tif(flags & 0x8) out.a = '1';\n\treturn out;\n}\n\n/* 18.6 Calculation Chain */\nfunction parse_cc_bin(data, opts) {\n\tvar out = [];\n\tvar pass = false;\n\trecordhopper(data, function hopper_cc(val, R, RT) {\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtCalcChainItem$': out.push(val); break;\n\t\t\tcase 'BrtBeginCalcChain$': break;\n\t\t\tcase 'BrtEndCalcChain$': break;\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + RT + \" \" + R.n);\n\t\t}\n\t});\n\treturn out;\n}\n\nfunction write_cc_bin(data, opts) { }\n\nfunction parse_comments(zip, dirComments, sheets, sheetRels, opts) {\n\tfor(var i = 0; i != dirComments.length; ++i) {\n\t\tvar canonicalpath=dirComments[i];\n\t\tvar comments=parse_cmnt(getzipdata(zip, canonicalpath.replace(/^\\//,''), true), canonicalpath, opts);\n\t\tif(!comments || !comments.length) continue;\n\t\t// find the sheets targeted by these comments\n\t\tvar sheetNames = keys(sheets);\n\t\tfor(var j = 0; j != sheetNames.length; ++j) {\n\t\t\tvar sheetName = sheetNames[j];\n\t\t\tvar rels = sheetRels[sheetName];\n\t\t\tif(rels) {\n\t\t\t\tvar rel = rels[canonicalpath];\n\t\t\t\tif(rel) insertCommentsIntoSheet(sheetName, sheets[sheetName], comments);\n\t\t\t}\n\t\t}\n\t}\n}\n\nfunction insertCommentsIntoSheet(sheetName, sheet, comments) {\n\tcomments.forEach(function(comment) {\n\t\tvar cell = sheet[comment.ref];\n\t\tif (!cell) {\n\t\t\tcell = {};\n\t\t\tsheet[comment.ref] = cell;\n\t\t\tvar range = safe_decode_range(sheet[\"!ref\"]||\"BDWGO1000001:A1\");\n\t\t\tvar thisCell = decode_cell(comment.ref);\n\t\t\tif(range.s.r > thisCell.r) range.s.r = thisCell.r;\n\t\t\tif(range.e.r < thisCell.r) range.e.r = thisCell.r;\n\t\t\tif(range.s.c > thisCell.c) range.s.c = thisCell.c;\n\t\t\tif(range.e.c < thisCell.c) range.e.c = thisCell.c;\n\t\t\tvar encoded = encode_range(range);\n\t\t\tif (encoded !== sheet[\"!ref\"]) sheet[\"!ref\"] = encoded;\n\t\t}\n\n\t\tif (!cell.c) cell.c = [];\n\t\tvar o = {a: comment.author, t: comment.t, r: comment.r};\n\t\tif(comment.h) o.h = comment.h;\n\t\tcell.c.push(o);\n\t});\n}\n\n/* 18.7.3 CT_Comment */\nfunction parse_comments_xml(data, opts) {\n\tif(data.match(/<(?:\\w+:)?comments *\\/>/)) return [];\n\tvar authors = [];\n\tvar commentList = [];\n\tdata.match(/<(?:\\w+:)?authors>([^\\u2603]*)<\\/(?:\\w+:)?authors>/)[1].split(/<\\/\\w*:?author>/).forEach(function(x) {\n\t\tif(x === \"\" || x.trim() === \"\") return;\n\t\tauthors.push(x.match(/<(?:\\w+:)?author[^>]*>(.*)/)[1]);\n\t});\n\t(data.match(/<(?:\\w+:)?commentList>([^\\u2603]*)<\\/(?:\\w+:)?commentList>/)||[\"\",\"\"])[1].split(/<\\/\\w*:?comment>/).forEach(function(x, index) {\n\t\tif(x === \"\" || x.trim() === \"\") return;\n\t\tvar y = parsexmltag(x.match(/<(?:\\w+:)?comment[^>]*>/)[0]);\n\t\tvar comment = { author: y.authorId && authors[y.authorId] ? authors[y.authorId] : undefined, ref: y.ref, guid: y.guid };\n\t\tvar cell = decode_cell(y.ref);\n\t\tif(opts.sheetRows && opts.sheetRows <= cell.r) return;\n\t\tvar textMatch = x.match(/<text>([^\\u2603]*)<\\/text>/);\n\t\tif (!textMatch || !textMatch[1]) return; // a comment may contain an empty text tag.\n\t\tvar rt = parse_si(textMatch[1]);\n\t\tcomment.r = rt.r;\n\t\tcomment.t = rt.t;\n\t\tif(opts.cellHTML) comment.h = rt.h;\n\t\tcommentList.push(comment);\n\t});\n\treturn commentList;\n}\n\nfunction write_comments_xml(data, opts) { }\n/* [MS-XLSB] 2.4.28 BrtBeginComment */\nfunction parse_BrtBeginComment(data, length) {\n\tvar out = {};\n\tout.iauthor = data.read_shift(4);\n\tvar rfx = parse_UncheckedRfX(data, 16);\n\tout.rfx = rfx.s;\n\tout.ref = encode_cell(rfx.s);\n\tdata.l += 16; /*var guid = parse_GUID(data); */\n\treturn out;\n}\n\n/* [MS-XLSB] 2.4.324 BrtCommentAuthor */\nvar parse_BrtCommentAuthor = parse_XLWideString;\n\n/* [MS-XLSB] 2.4.325 BrtCommentText */\nvar parse_BrtCommentText = parse_RichStr;\n\n/* [MS-XLSB] 2.1.7.8 Comments */\nfunction parse_comments_bin(data, opts) {\n\tvar out = [];\n\tvar authors = [];\n\tvar c = {};\n\tvar pass = false;\n\trecordhopper(data, function hopper_cmnt(val, R, RT) {\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtCommentAuthor': authors.push(val); break;\n\t\t\tcase 'BrtBeginComment': c = val; break;\n\t\t\tcase 'BrtCommentText': c.t = val.t; c.h = val.h; c.r = val.r; break;\n\t\t\tcase 'BrtEndComment':\n\t\t\t\tc.author = authors[c.iauthor];\n\t\t\t\tdelete c.iauthor;\n\t\t\t\tif(opts.sheetRows && opts.sheetRows <= c.rfx.r) break;\n\t\t\t\tdelete c.rfx; out.push(c); break;\n\t\t\tcase 'BrtBeginComments': break;\n\t\t\tcase 'BrtEndComments': break;\n\t\t\tcase 'BrtBeginCommentAuthors': break;\n\t\t\tcase 'BrtEndCommentAuthors': break;\n\t\t\tcase 'BrtBeginCommentList': break;\n\t\t\tcase 'BrtEndCommentList': break;\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + RT + \" \" + R.n);\n\t\t}\n\t});\n\treturn out;\n}\n\nfunction write_comments_bin(data, opts) { }\n/* TODO: it will be useful to parse the function str */\nvar rc_to_a1 = (function(){\n\tvar rcregex = /(^|[^A-Za-z])R(\\[?)(-?\\d+|)\\]?C(\\[?)(-?\\d+|)\\]?/g;\n\tvar rcbase;\n\tfunction rcfunc($$,$1,$2,$3,$4,$5) {\n\t\tvar R = $3.length>0?parseInt($3,10)|0:0, C = $5.length>0?parseInt($5,10)|0:0;\n\t\tif(C<0 && $4.length === 0) C=0;\n\t\tif($4.length > 0) C += rcbase.c;\n\t\tif($2.length > 0) R += rcbase.r;\n\t\treturn $1 + encode_col(C) + encode_row(R);\n\t}\n\treturn function rc_to_a1(fstr, base) {\n\t\trcbase = base;\n\t\treturn fstr.replace(rcregex, rcfunc);\n\t};\n})();\n\n/* --- formula references point to MS-XLS --- */\n/* Small helpers */\nfunction parseread(l) { return function(blob, length) { blob.l+=l; return; }; }\nfunction parseread1(blob, length) { blob.l+=1; return; }\n\n/* Rgce Helpers */\n\n/* 2.5.51 */\nfunction parse_ColRelU(blob, length) {\n\tvar c = blob.read_shift(2);\n\treturn [c & 0x3FFF, (c >> 14) & 1, (c >> 15) & 1];\n}\n\n/* 2.5.198.105 */\nfunction parse_RgceArea(blob, length) {\n\tvar r=blob.read_shift(2), R=blob.read_shift(2);\n\tvar c=parse_ColRelU(blob, 2);\n\tvar C=parse_ColRelU(blob, 2);\n\treturn { s:{r:r, c:c[0], cRel:c[1], rRel:c[2]}, e:{r:R, c:C[0], cRel:C[1], rRel:C[2]} };\n}\n\n/* 2.5.198.105 TODO */\nfunction parse_RgceAreaRel(blob, length) {\n\tvar r=blob.read_shift(2), R=blob.read_shift(2);\n\tvar c=parse_ColRelU(blob, 2);\n\tvar C=parse_ColRelU(blob, 2);\n\treturn { s:{r:r, c:c[0], cRel:c[1], rRel:c[2]}, e:{r:R, c:C[0], cRel:C[1], rRel:C[2]} };\n}\n\n/* 2.5.198.109 */\nfunction parse_RgceLoc(blob, length) {\n\tvar r = blob.read_shift(2);\n\tvar c = parse_ColRelU(blob, 2);\n\treturn {r:r, c:c[0], cRel:c[1], rRel:c[2]};\n}\n\n/* 2.5.198.111 */\nfunction parse_RgceLocRel(blob, length) {\n\tvar r = blob.read_shift(2);\n\tvar cl = blob.read_shift(2);\n\tvar cRel = (cl & 0x8000) >> 15, rRel = (cl & 0x4000) >> 14;\n\tcl &= 0x3FFF;\n\tif(cRel !== 0) while(cl >= 0x100) cl -= 0x100;\n\treturn {r:r,c:cl,cRel:cRel,rRel:rRel};\n}\n\n/* Ptg Tokens */\n\n/* 2.5.198.27 */\nfunction parse_PtgArea(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tvar area = parse_RgceArea(blob, 8);\n\treturn [type, area];\n}\n\n/* 2.5.198.28 */\nfunction parse_PtgArea3d(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tvar ixti = blob.read_shift(2);\n\tvar area = parse_RgceArea(blob, 8);\n\treturn [type, ixti, area];\n}\n\n/* 2.5.198.29 */\nfunction parse_PtgAreaErr(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tblob.l += 8;\n\treturn [type];\n}\n/* 2.5.198.30 */\nfunction parse_PtgAreaErr3d(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tvar ixti = blob.read_shift(2);\n\tblob.l += 8;\n\treturn [type, ixti];\n}\n\n/* 2.5.198.31 */\nfunction parse_PtgAreaN(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tvar area = parse_RgceAreaRel(blob, 8);\n\treturn [type, area];\n}\n\n/* 2.5.198.32 -- ignore this and look in PtgExtraArray for shape + values */\nfunction parse_PtgArray(blob, length) {\n\tvar type = (blob[blob.l++] & 0x60) >> 5;\n\tblob.l += 7;\n\treturn [type];\n}\n\n/* 2.5.198.33 */\nfunction parse_PtgAttrBaxcel(blob, length) {\n\tvar bitSemi = blob[blob.l+1] & 0x01; /* 1 = volatile */\n\tvar bitBaxcel = 1;\n\tblob.l += 4;\n\treturn [bitSemi, bitBaxcel];\n}\n\n/* 2.5.198.34 */\nfunction parse_PtgAttrChoose(blob, length) {\n\tblob.l +=2;\n\tvar offset = blob.read_shift(2);\n\tvar o = [];\n\t/* offset is 1 less than the number of elements */\n\tfor(var i = 0; i <= offset; ++i) o.push(blob.read_shift(2));\n\treturn o;\n}\n\n/* 2.5.198.35 */\nfunction parse_PtgAttrGoto(blob, length) {\n\tvar bitGoto = (blob[blob.l+1] & 0xFF) ? 1 : 0;\n\tblob.l += 2;\n\treturn [bitGoto, blob.read_shift(2)];\n}\n\n/* 2.5.198.36 */\nfunction parse_PtgAttrIf(blob, length) {\n\tvar bitIf = (blob[blob.l+1] & 0xFF) ? 1 : 0;\n\tblob.l += 2;\n\treturn [bitIf, blob.read_shift(2)];\n}\n\n/* 2.5.198.37 */\nfunction parse_PtgAttrSemi(blob, length) {\n\tvar bitSemi = (blob[blob.l+1] & 0xFF) ? 1 : 0;\n\tblob.l += 4;\n\treturn [bitSemi];\n}\n\n/* 2.5.198.40 (used by PtgAttrSpace and PtgAttrSpaceSemi) */\nfunction parse_PtgAttrSpaceType(blob, length) {\n\tvar type = blob.read_shift(1), cch = blob.read_shift(1);\n\treturn [type, cch];\n}\n\n/* 2.5.198.38 */\nfunction parse_PtgAttrSpace(blob, length) {\n\tblob.read_shift(2);\n\treturn parse_PtgAttrSpaceType(blob, 2);\n}\n\n/* 2.5.198.39 */\nfunction parse_PtgAttrSpaceSemi(blob, length) {\n\tblob.read_shift(2);\n\treturn parse_PtgAttrSpaceType(blob, 2);\n}\n\n/* 2.5.198.84 TODO */\nfunction parse_PtgRef(blob, length) {\n\tvar ptg = blob[blob.l] & 0x1F;\n\tvar type = (blob[blob.l] & 0x60)>>5;\n\tblob.l += 1;\n\tvar loc = parse_RgceLoc(blob,4);\n\treturn [type, loc];\n}\n\n/* 2.5.198.88 TODO */\nfunction parse_PtgRefN(blob, length) {\n\tvar ptg = blob[blob.l] & 0x1F;\n\tvar type = (blob[blob.l] & 0x60)>>5;\n\tblob.l += 1;\n\tvar loc = parse_RgceLocRel(blob,4);\n\treturn [type, loc];\n}\n\n/* 2.5.198.85 TODO */\nfunction parse_PtgRef3d(blob, length) {\n\tvar ptg = blob[blob.l] & 0x1F;\n\tvar type = (blob[blob.l] & 0x60)>>5;\n\tblob.l += 1;\n\tvar ixti = blob.read_shift(2); // XtiIndex\n\tvar loc = parse_RgceLoc(blob,4);\n\treturn [type, ixti, loc];\n}\n\n\n/* 2.5.198.62 TODO */\nfunction parse_PtgFunc(blob, length) {\n\tvar ptg = blob[blob.l] & 0x1F;\n\tvar type = (blob[blob.l] & 0x60)>>5;\n\tblob.l += 1;\n\tvar iftab = blob.read_shift(2);\n\treturn [FtabArgc[iftab], Ftab[iftab]];\n}\n/* 2.5.198.63 TODO */\nfunction parse_PtgFuncVar(blob, length) {\n\tblob.l++;\n\tvar cparams = blob.read_shift(1), tab = parsetab(blob);\n\treturn [cparams, (tab[0] === 0 ? Ftab : Cetab)[tab[1]]];\n}\n\nfunction parsetab(blob, length) {\n\treturn [blob[blob.l+1]>>7, blob.read_shift(2) & 0x7FFF];\n}\n\n/* 2.5.198.41 */\nvar parse_PtgAttrSum = parseread(4);\n/* 2.5.198.43 */\nvar parse_PtgConcat = parseread1;\n\n/* 2.5.198.58 */\nfunction parse_PtgExp(blob, length) {\n\tblob.l++;\n\tvar row = blob.read_shift(2);\n\tvar col = blob.read_shift(2);\n\treturn [row, col];\n}\n\n/* 2.5.198.57 */\nfunction parse_PtgErr(blob, length) { blob.l++; return BErr[blob.read_shift(1)]; }\n\n/* 2.5.198.66 TODO */\nfunction parse_PtgInt(blob, length) { blob.l++; return blob.read_shift(2); }\n\n/* 2.5.198.42 */\nfunction parse_PtgBool(blob, length) { blob.l++; return blob.read_shift(1)!==0;}\n\n/* 2.5.198.79 */\nfunction parse_PtgNum(blob, length) { blob.l++; return parse_Xnum(blob, 8); }\n\n/* 2.5.198.89 */\nfunction parse_PtgStr(blob, length) { blob.l++; return parse_ShortXLUnicodeString(blob); }\n\n/* 2.5.192.112 + 2.5.192.11{3,4,5,6,7} */\nfunction parse_SerAr(blob) {\n\tvar val = [];\n\tswitch((val[0] = blob.read_shift(1))) {\n\t\t/* 2.5.192.113 */\n\t\tcase 0x04: /* SerBool -- boolean */\n\t\t\tval[1] = parsebool(blob, 1) ? 'TRUE' : 'FALSE';\n\t\t\tblob.l += 7; break;\n\t\t/* 2.5.192.114 */\n\t\tcase 0x10: /* SerErr -- error */\n\t\t\tval[1] = BErr[blob[blob.l]];\n\t\t\tblob.l += 8; break;\n\t\t/* 2.5.192.115 */\n\t\tcase 0x00: /* SerNil -- honestly, I'm not sure how to reproduce this */\n\t\t\tblob.l += 8; break;\n\t\t/* 2.5.192.116 */\n\t\tcase 0x01: /* SerNum -- Xnum */\n\t\t\tval[1] = parse_Xnum(blob, 8); break;\n\t\t/* 2.5.192.117 */\n\t\tcase 0x02: /* SerStr -- XLUnicodeString (<256 chars) */\n\t\t\tval[1] = parse_XLUnicodeString(blob); break;\n\t\t// default: throw \"Bad SerAr: \" + val[0]; /* Unreachable */\n\t}\n\treturn val;\n}\n\n/* 2.5.198.61 */\nfunction parse_PtgExtraMem(blob, cce) {\n\tvar count = blob.read_shift(2);\n\tvar out = [];\n\tfor(var i = 0; i != count; ++i) out.push(parse_Ref8U(blob, 8));\n\treturn out;\n}\n\n/* 2.5.198.59 */\nfunction parse_PtgExtraArray(blob) {\n\tvar cols = 1 + blob.read_shift(1); //DColByteU\n\tvar rows = 1 + blob.read_shift(2); //DRw\n\tfor(var i = 0, o=[]; i != rows && (o[i] = []); ++i)\n\t\tfor(var j = 0; j != cols; ++j) o[i][j] = parse_SerAr(blob);\n\treturn o;\n}\n\n/* 2.5.198.76 */\nfunction parse_PtgName(blob, length) {\n\tvar type = (blob.read_shift(1) >>> 5) & 0x03;\n\tvar nameindex = blob.read_shift(4);\n\treturn [type, 0, nameindex];\n}\n\n/* 2.5.198.77 */\nfunction parse_PtgNameX(blob, length) {\n\tvar type = (blob.read_shift(1) >>> 5) & 0x03;\n\tvar ixti = blob.read_shift(2); // XtiIndex\n\tvar nameindex = blob.read_shift(4);\n\treturn [type, ixti, nameindex];\n}\n\n/* 2.5.198.70 */\nfunction parse_PtgMemArea(blob, length) {\n\tvar type = (blob.read_shift(1) >>> 5) & 0x03;\n\tblob.l += 4;\n\tvar cce = blob.read_shift(2);\n\treturn [type, cce];\n}\n\n/* 2.5.198.72 */\nfunction parse_PtgMemFunc(blob, length) {\n\tvar type = (blob.read_shift(1) >>> 5) & 0x03;\n\tvar cce = blob.read_shift(2);\n\treturn [type, cce];\n}\n\n\n/* 2.5.198.86 */\nfunction parse_PtgRefErr(blob, length) {\n\tvar type = (blob.read_shift(1) >>> 5) & 0x03;\n\tblob.l += 4;\n\treturn [type];\n}\n\n/* 2.5.198.26 */\nvar parse_PtgAdd = parseread1;\n/* 2.5.198.45 */\nvar parse_PtgDiv = parseread1;\n/* 2.5.198.56 */\nvar parse_PtgEq = parseread1;\n/* 2.5.198.64 */\nvar parse_PtgGe = parseread1;\n/* 2.5.198.65 */\nvar parse_PtgGt = parseread1;\n/* 2.5.198.67 */\nvar parse_PtgIsect = parseread1;\n/* 2.5.198.68 */\nvar parse_PtgLe = parseread1;\n/* 2.5.198.69 */\nvar parse_PtgLt = parseread1;\n/* 2.5.198.74 */\nvar parse_PtgMissArg = parseread1;\n/* 2.5.198.75 */\nvar parse_PtgMul = parseread1;\n/* 2.5.198.78 */\nvar parse_PtgNe = parseread1;\n/* 2.5.198.80 */\nvar parse_PtgParen = parseread1;\n/* 2.5.198.81 */\nvar parse_PtgPercent = parseread1;\n/* 2.5.198.82 */\nvar parse_PtgPower = parseread1;\n/* 2.5.198.83 */\nvar parse_PtgRange = parseread1;\n/* 2.5.198.90 */\nvar parse_PtgSub = parseread1;\n/* 2.5.198.93 */\nvar parse_PtgUminus = parseread1;\n/* 2.5.198.94 */\nvar parse_PtgUnion = parseread1;\n/* 2.5.198.95 */\nvar parse_PtgUplus = parseread1;\n\n/* 2.5.198.71 */\nvar parse_PtgMemErr = parsenoop;\n/* 2.5.198.73 */\nvar parse_PtgMemNoMem = parsenoop;\n/* 2.5.198.87 */\nvar parse_PtgRefErr3d = parsenoop;\n/* 2.5.198.92 */\nvar parse_PtgTbl = parsenoop;\n\n/* 2.5.198.25 */\nvar PtgTypes = {\n\t0x01: { n:'PtgExp', f:parse_PtgExp },\n\t0x02: { n:'PtgTbl', f:parse_PtgTbl },\n\t0x03: { n:'PtgAdd', f:parse_PtgAdd },\n\t0x04: { n:'PtgSub', f:parse_PtgSub },\n\t0x05: { n:'PtgMul', f:parse_PtgMul },\n\t0x06: { n:'PtgDiv', f:parse_PtgDiv },\n\t0x07: { n:'PtgPower', f:parse_PtgPower },\n\t0x08: { n:'PtgConcat', f:parse_PtgConcat },\n\t0x09: { n:'PtgLt', f:parse_PtgLt },\n\t0x0A: { n:'PtgLe', f:parse_PtgLe },\n\t0x0B: { n:'PtgEq', f:parse_PtgEq },\n\t0x0C: { n:'PtgGe', f:parse_PtgGe },\n\t0x0D: { n:'PtgGt', f:parse_PtgGt },\n\t0x0E: { n:'PtgNe', f:parse_PtgNe },\n\t0x0F: { n:'PtgIsect', f:parse_PtgIsect },\n\t0x10: { n:'PtgUnion', f:parse_PtgUnion },\n\t0x11: { n:'PtgRange', f:parse_PtgRange },\n\t0x12: { n:'PtgUplus', f:parse_PtgUplus },\n\t0x13: { n:'PtgUminus', f:parse_PtgUminus },\n\t0x14: { n:'PtgPercent', f:parse_PtgPercent },\n\t0x15: { n:'PtgParen', f:parse_PtgParen },\n\t0x16: { n:'PtgMissArg', f:parse_PtgMissArg },\n\t0x17: { n:'PtgStr', f:parse_PtgStr },\n\t0x1C: { n:'PtgErr', f:parse_PtgErr },\n\t0x1D: { n:'PtgBool', f:parse_PtgBool },\n\t0x1E: { n:'PtgInt', f:parse_PtgInt },\n\t0x1F: { n:'PtgNum', f:parse_PtgNum },\n\t0x20: { n:'PtgArray', f:parse_PtgArray },\n\t0x21: { n:'PtgFunc', f:parse_PtgFunc },\n\t0x22: { n:'PtgFuncVar', f:parse_PtgFuncVar },\n\t0x23: { n:'PtgName', f:parse_PtgName },\n\t0x24: { n:'PtgRef', f:parse_PtgRef },\n\t0x25: { n:'PtgArea', f:parse_PtgArea },\n\t0x26: { n:'PtgMemArea', f:parse_PtgMemArea },\n\t0x27: { n:'PtgMemErr', f:parse_PtgMemErr },\n\t0x28: { n:'PtgMemNoMem', f:parse_PtgMemNoMem },\n\t0x29: { n:'PtgMemFunc', f:parse_PtgMemFunc },\n\t0x2A: { n:'PtgRefErr', f:parse_PtgRefErr },\n\t0x2B: { n:'PtgAreaErr', f:parse_PtgAreaErr },\n\t0x2C: { n:'PtgRefN', f:parse_PtgRefN },\n\t0x2D: { n:'PtgAreaN', f:parse_PtgAreaN },\n\t0x39: { n:'PtgNameX', f:parse_PtgNameX },\n\t0x3A: { n:'PtgRef3d', f:parse_PtgRef3d },\n\t0x3B: { n:'PtgArea3d', f:parse_PtgArea3d },\n\t0x3C: { n:'PtgRefErr3d', f:parse_PtgRefErr3d },\n\t0x3D: { n:'PtgAreaErr3d', f:parse_PtgAreaErr3d },\n\t0xFF: {}\n};\n/* These are duplicated in the PtgTypes table */\nvar PtgDupes = {\n\t0x40: 0x20, 0x60: 0x20,\n\t0x41: 0x21, 0x61: 0x21,\n\t0x42: 0x22, 0x62: 0x22,\n\t0x43: 0x23, 0x63: 0x23,\n\t0x44: 0x24, 0x64: 0x24,\n\t0x45: 0x25, 0x65: 0x25,\n\t0x46: 0x26, 0x66: 0x26,\n\t0x47: 0x27, 0x67: 0x27,\n\t0x48: 0x28, 0x68: 0x28,\n\t0x49: 0x29, 0x69: 0x29,\n\t0x4A: 0x2A, 0x6A: 0x2A,\n\t0x4B: 0x2B, 0x6B: 0x2B,\n\t0x4C: 0x2C, 0x6C: 0x2C,\n\t0x4D: 0x2D, 0x6D: 0x2D,\n\t0x59: 0x39, 0x79: 0x39,\n\t0x5A: 0x3A, 0x7A: 0x3A,\n\t0x5B: 0x3B, 0x7B: 0x3B,\n\t0x5C: 0x3C, 0x7C: 0x3C,\n\t0x5D: 0x3D, 0x7D: 0x3D\n};\n(function(){for(var y in PtgDupes) PtgTypes[y] = PtgTypes[PtgDupes[y]];})();\n\nvar Ptg18 = {};\nvar Ptg19 = {\n\t0x01: { n:'PtgAttrSemi', f:parse_PtgAttrSemi },\n\t0x02: { n:'PtgAttrIf', f:parse_PtgAttrIf },\n\t0x04: { n:'PtgAttrChoose', f:parse_PtgAttrChoose },\n\t0x08: { n:'PtgAttrGoto', f:parse_PtgAttrGoto },\n\t0x10: { n:'PtgAttrSum', f:parse_PtgAttrSum },\n\t0x20: { n:'PtgAttrBaxcel', f:parse_PtgAttrBaxcel },\n\t0x40: { n:'PtgAttrSpace', f:parse_PtgAttrSpace },\n\t0x41: { n:'PtgAttrSpaceSemi', f:parse_PtgAttrSpaceSemi },\n\t0xFF: {}\n};\n\n/* 2.4.127 TODO */\nfunction parse_Formula(blob, length, opts) {\n\tvar cell = parse_XLSCell(blob, 6);\n\tvar val = parse_FormulaValue(blob,8);\n\tvar flags = blob.read_shift(1);\n\tblob.read_shift(1);\n\tvar chn = blob.read_shift(4);\n\tvar cbf = \"\";\n\tif(opts.biff === 5) blob.l += length-20;\n\telse cbf = parse_XLSCellParsedFormula(blob, length-20, opts);\n\treturn {cell:cell, val:val[0], formula:cbf, shared: (flags >> 3) & 1, tt:val[1]};\n}\n\n/* 2.5.133 TODO: how to emit empty strings? */\nfunction parse_FormulaValue(blob) {\n\tvar b;\n\tif(__readUInt16LE(blob,blob.l + 6) !== 0xFFFF) return [parse_Xnum(blob),'n'];\n\tswitch(blob[blob.l]) {\n\t\tcase 0x00: blob.l += 8; return [\"String\", 's'];\n\t\tcase 0x01: b = blob[blob.l+2] === 0x1; blob.l += 8; return [b,'b'];\n\t\tcase 0x02: b = blob[blob.l+2]; blob.l += 8; return [b,'e'];\n\t\tcase 0x03: blob.l += 8; return [\"\",'s'];\n\t}\n}\n\n/* 2.5.198.103 */\nfunction parse_RgbExtra(blob, length, rgce, opts) {\n\tif(opts.biff < 8) return parsenoop(blob, length);\n\tvar target = blob.l + length;\n\tvar o = [];\n\tfor(var i = 0; i !== rgce.length; ++i) {\n\t\tswitch(rgce[i][0]) {\n\t\t\tcase 'PtgArray': /* PtgArray -> PtgExtraArray */\n\t\t\t\trgce[i][1] = parse_PtgExtraArray(blob);\n\t\t\t\to.push(rgce[i][1]);\n\t\t\t\tbreak;\n\t\t\tcase 'PtgMemArea': /* PtgMemArea -> PtgExtraMem */\n\t\t\t\trgce[i][2] = parse_PtgExtraMem(blob, rgce[i][1]);\n\t\t\t\to.push(rgce[i][2]);\n\t\t\t\tbreak;\n\t\t\tdefault: break;\n\t\t}\n\t}\n\tlength = target - blob.l;\n\tif(length !== 0) o.push(parsenoop(blob, length));\n\treturn o;\n}\n\n/* 2.5.198.21 */\nfunction parse_NameParsedFormula(blob, length, opts, cce) {\n\tvar target = blob.l + length;\n\tvar rgce = parse_Rgce(blob, cce);\n\tvar rgcb;\n\tif(target !== blob.l) rgcb = parse_RgbExtra(blob, target - blob.l, rgce, opts);\n\treturn [rgce, rgcb];\n}\n\n/* 2.5.198.3 TODO */\nfunction parse_XLSCellParsedFormula(blob, length, opts) {\n\tvar target = blob.l + length;\n\tvar rgcb, cce = blob.read_shift(2); // length of rgce\n\tif(cce == 0xFFFF) return [[],parsenoop(blob, length-2)];\n\tvar rgce = parse_Rgce(blob, cce);\n\tif(length !== cce + 2) rgcb = parse_RgbExtra(blob, length - cce - 2, rgce, opts);\n\treturn [rgce, rgcb];\n}\n\n/* 2.5.198.118 TODO */\nfunction parse_SharedParsedFormula(blob, length, opts) {\n\tvar target = blob.l + length;\n\tvar rgcb, cce = blob.read_shift(2); // length of rgce\n\tvar rgce = parse_Rgce(blob, cce);\n\tif(cce == 0xFFFF) return [[],parsenoop(blob, length-2)];\n\tif(length !== cce + 2) rgcb = parse_RgbExtra(blob, target - cce - 2, rgce, opts);\n\treturn [rgce, rgcb];\n}\n\n/* 2.5.198.1 TODO */\nfunction parse_ArrayParsedFormula(blob, length, opts, ref) {\n\tvar target = blob.l + length;\n\tvar rgcb, cce = blob.read_shift(2); // length of rgce\n\tif(cce == 0xFFFF) return [[],parsenoop(blob, length-2)];\n\tvar rgce = parse_Rgce(blob, cce);\n\tif(length !== cce + 2) rgcb = parse_RgbExtra(blob, target - cce - 2, rgce, opts);\n\treturn [rgce, rgcb];\n}\n\n/* 2.5.198.104 */\nfunction parse_Rgce(blob, length) {\n\tvar target = blob.l + length;\n\tvar R, id, ptgs = [];\n\twhile(target != blob.l) {\n\t\tlength = target - blob.l;\n\t\tid = blob[blob.l];\n\t\tR = PtgTypes[id];\n\t\t//console.log(\"ptg\", id, R)\n\t\tif(id === 0x18 || id === 0x19) {\n\t\t\tid = blob[blob.l + 1];\n\t\t\tR = (id === 0x18 ? Ptg18 : Ptg19)[id];\n\t\t}\n\t\tif(!R || !R.f) { ptgs.push(parsenoop(blob, length)); }\n\t\telse { ptgs.push([R.n, R.f(blob, length)]); }\n\t}\n\treturn ptgs;\n}\n\nfunction mapper(x) { return x.map(function f2(y) { return y[1];}).join(\",\");}\n\n/* 2.2.2 + Magic TODO */\nfunction stringify_formula(formula, range, cell, supbooks, opts) {\n\tif(opts !== undefined && opts.biff === 5) return \"BIFF5??\";\n\tvar _range = range !== undefined ? range : {s:{c:0, r:0}};\n\tvar stack = [], e1, e2, type, c, ixti, nameidx, r;\n\tif(!formula[0] || !formula[0][0]) return \"\";\n\t//console.log(\"--\",cell,formula[0])\n\tfor(var ff = 0, fflen = formula[0].length; ff < fflen; ++ff) {\n\t\tvar f = formula[0][ff];\n\t\t//console.log(\"++\",f, stack)\n\t\tswitch(f[0]) {\n\t\t/* 2.2.2.1 Unary Operator Tokens */\n\t\t\t/* 2.5.198.93 */\n\t\t\tcase 'PtgUminus': stack.push(\"-\" + stack.pop()); break;\n\t\t\t/* 2.5.198.95 */\n\t\t\tcase 'PtgUplus': stack.push(\"+\" + stack.pop()); break;\n\t\t\t/* 2.5.198.81 */\n\t\t\tcase 'PtgPercent': stack.push(stack.pop() + \"%\"); break;\n\n\t\t/* 2.2.2.1 Binary Value Operator Token */\n\t\t\t/* 2.5.198.26 */\n\t\t\tcase 'PtgAdd':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"+\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.90 */\n\t\t\tcase 'PtgSub':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"-\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.75 */\n\t\t\tcase 'PtgMul':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"*\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.45 */\n\t\t\tcase 'PtgDiv':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"/\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.82 */\n\t\t\tcase 'PtgPower':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"^\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.43 */\n\t\t\tcase 'PtgConcat':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"&\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.69 */\n\t\t\tcase 'PtgLt':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"<\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.68 */\n\t\t\tcase 'PtgLe':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"<=\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.56 */\n\t\t\tcase 'PtgEq':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"=\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.64 */\n\t\t\tcase 'PtgGe':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\">=\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.65 */\n\t\t\tcase 'PtgGt':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\">\"+e1);\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.78 */\n\t\t\tcase 'PtgNe':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\"<>\"+e1);\n\t\t\t\tbreak;\n\n\t\t/* 2.2.2.1 Binary Reference Operator Token */\n\t\t\t/* 2.5.198.67 */\n\t\t\tcase 'PtgIsect':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\" \"+e1);\n\t\t\t\tbreak;\n\t\t\tcase 'PtgUnion':\n\t\t\t\te1 = stack.pop(); e2 = stack.pop();\n\t\t\t\tstack.push(e2+\",\"+e1);\n\t\t\t\tbreak;\n\t\t\tcase 'PtgRange': break;\n\n\t\t/* 2.2.2.3 Control Tokens \"can be ignored\" */\n\t\t\t/* 2.5.198.34 */\n\t\t\tcase 'PtgAttrChoose': break;\n\t\t\t/* 2.5.198.35 */\n\t\t\tcase 'PtgAttrGoto': break;\n\t\t\t/* 2.5.198.36 */\n\t\t\tcase 'PtgAttrIf': break;\n\n\n\t\t\t/* 2.5.198.84 */\n\t\t\tcase 'PtgRef':\n\t\t\t\ttype = f[1][0]; c = shift_cell_xls(decode_cell(encode_cell(f[1][1])), _range);\n\t\t\t\tstack.push(encode_cell(c));\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.88 */\n\t\t\tcase 'PtgRefN':\n\t\t\t\ttype = f[1][0]; c = shift_cell_xls(decode_cell(encode_cell(f[1][1])), cell);\n\t\t\t\tstack.push(encode_cell(c));\n\t\t\t\tbreak;\n\t\t\tcase 'PtgRef3d': // TODO: lots of stuff\n\t\t\t\ttype = f[1][0]; ixti = f[1][1]; c = shift_cell_xls(f[1][2], _range);\n\t\t\t\tstack.push(supbooks[1][ixti+1]+\"!\"+encode_cell(c));\n\t\t\t\tbreak;\n\n\t\t/* Function Call */\n\t\t\t/* 2.5.198.62 */\n\t\t\tcase 'PtgFunc':\n\t\t\t/* 2.5.198.63 */\n\t\t\tcase 'PtgFuncVar':\n\t\t\t\t/* f[1] = [argc, func] */\n\t\t\t\tvar argc = f[1][0], func = f[1][1];\n\t\t\t\tif(!argc) argc = 0;\n\t\t\t\tvar args = stack.slice(-argc);\n\t\t\t\tstack.length -= argc;\n\t\t\t\tif(func === 'User') func = args.shift();\n\t\t\t\tstack.push(func + \"(\" + args.join(\",\") + \")\");\n\t\t\t\tbreak;\n\n\t\t\t/* 2.5.198.42 */\n\t\t\tcase 'PtgBool': stack.push(f[1] ? \"TRUE\" : \"FALSE\"); break;\n\t\t\t/* 2.5.198.66 */\n\t\t\tcase 'PtgInt': stack.push(f[1]); break;\n\t\t\t/* 2.5.198.79 TODO: precision? */\n\t\t\tcase 'PtgNum': stack.push(String(f[1])); break;\n\t\t\t/* 2.5.198.89 */\n\t\t\tcase 'PtgStr': stack.push('\"' + f[1] + '\"'); break;\n\t\t\t/* 2.5.198.57 */\n\t\t\tcase 'PtgErr': stack.push(f[1]); break;\n\t\t\t/* 2.5.198.27 TODO: fixed points */\n\t\t\tcase 'PtgArea':\n\t\t\t\ttype = f[1][0]; r = shift_range_xls(f[1][1], _range);\n\t\t\t\tstack.push(encode_range(r));\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.28 */\n\t\t\tcase 'PtgArea3d': // TODO: lots of stuff\n\t\t\t\ttype = f[1][0]; ixti = f[1][1]; r = f[1][2];\n\t\t\t\tstack.push(supbooks[1][ixti+1]+\"!\"+encode_range(r));\n\t\t\t\tbreak;\n\t\t\t/* 2.5.198.41 */\n\t\t\tcase 'PtgAttrSum':\n\t\t\t\tstack.push(\"SUM(\" + stack.pop() + \")\");\n\t\t\t\tbreak;\n\n\t\t/* Expression Prefixes */\n\t\t\t/* 2.5.198.37 */\n\t\t\tcase 'PtgAttrSemi': break;\n\n\t\t\t/* 2.5.97.60 TODO: do something different for revisions */\n\t\t\tcase 'PtgName':\n\t\t\t\t/* f[1] = type, 0, nameindex */\n\t\t\t\tnameidx = f[1][2];\n\t\t\t\tvar lbl = supbooks[0][nameidx];\n\t\t\t\tvar name = lbl.Name;\n\t\t\t\tif(name in XLSXFutureFunctions) name = XLSXFutureFunctions[name];\n\t\t\t\tstack.push(name);\n\t\t\t\tbreak;\n\n\t\t\t/* 2.5.97.61 TODO: do something different for revisions */\n\t\t\tcase 'PtgNameX':\n\t\t\t\t/* f[1] = type, ixti, nameindex */\n\t\t\t\tvar bookidx = f[1][1]; nameidx = f[1][2]; var externbook;\n\t\t\t\t/* TODO: Properly handle missing values */\n\t\t\t\tif(supbooks[bookidx+1]) externbook = supbooks[bookidx+1][nameidx];\n\t\t\t\telse if(supbooks[bookidx-1]) externbook = supbooks[bookidx-1][nameidx];\n\t\t\t\tif(!externbook) externbook = {body: \"??NAMEX??\"};\n\t\t\t\tstack.push(externbook.body);\n\t\t\t\tbreak;\n\n\t\t/* 2.2.2.4 Display Tokens */\n\t\t\t/* 2.5.198.80 */\n\t\t\tcase 'PtgParen': stack.push('(' + stack.pop() + ')'); break;\n\n\t\t\t/* 2.5.198.86 */\n\t\t\tcase 'PtgRefErr': stack.push('#REF!'); break;\n\n\t\t/* */\n\t\t\t/* 2.5.198.58 TODO */\n\t\t\tcase 'PtgExp':\n\t\t\t\tc = {c:f[1][1],r:f[1][0]};\n\t\t\t\tvar q = {c: cell.c, r:cell.r};\n\t\t\t\tif(supbooks.sharedf[encode_cell(c)]) {\n\t\t\t\t\tvar parsedf = (supbooks.sharedf[encode_cell(c)]);\n\t\t\t\t\tstack.push(stringify_formula(parsedf, _range, q, supbooks, opts));\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tvar fnd = false;\n\t\t\t\t\tfor(e1=0;e1!=supbooks.arrayf.length; ++e1) {\n\t\t\t\t\t\t/* TODO: should be something like range_has */\n\t\t\t\t\t\te2 = supbooks.arrayf[e1];\n\t\t\t\t\t\tif(c.c < e2[0].s.c || c.c > e2[0].e.c) continue;\n\t\t\t\t\t\tif(c.r < e2[0].s.r || c.r > e2[0].e.r) continue;\n\t\t\t\t\t\tstack.push(stringify_formula(e2[1], _range, q, supbooks, opts));\n\t\t\t\t\t}\n\t\t\t\t\tif(!fnd) stack.push(f[1]);\n\t\t\t\t}\n\t\t\t\tbreak;\n\n\t\t\t/* 2.5.198.32 TODO */\n\t\t\tcase 'PtgArray':\n\t\t\t\tstack.push(\"{\" + f[1].map(mapper).join(\";\") + \"}\");\n\t\t\t\tbreak;\n\n\t\t/* 2.2.2.5 Mem Tokens */\n\t\t\t/* 2.5.198.70 TODO: confirm this is a non-display */\n\t\t\tcase 'PtgMemArea':\n\t\t\t\t//stack.push(\"(\" + f[2].map(encode_range).join(\",\") + \")\");\n\t\t\t\tbreak;\n\n\t\t\t/* 2.5.198.38 TODO */\n\t\t\tcase 'PtgAttrSpace': break;\n\n\t\t\t/* 2.5.198.92 TODO */\n\t\t\tcase 'PtgTbl': break;\n\n\t\t\t/* 2.5.198.71 */\n\t\t\tcase 'PtgMemErr': break;\n\n\t\t\t/* 2.5.198.74 */\n\t\t\tcase 'PtgMissArg':\n\t\t\t\tstack.push(\"\");\n\t\t\t\tbreak;\n\n\t\t\t/* 2.5.198.29 TODO */\n\t\t\tcase 'PtgAreaErr': break;\n\n\t\t\t/* 2.5.198.31 TODO */\n\t\t\tcase 'PtgAreaN': stack.push(\"\"); break;\n\n\t\t\t/* 2.5.198.87 TODO */\n\t\t\tcase 'PtgRefErr3d': break;\n\n\t\t\t/* 2.5.198.72 TODO */\n\t\t\tcase 'PtgMemFunc': break;\n\n\t\t\tdefault: throw 'Unrecognized Formula Token: ' + f;\n\t\t}\n\t\t//console.log(\"::\",f, stack)\n\t}\n\t//console.log(\"--\",stack);\n\treturn stack[0];\n}\n\n/* [MS-XLSB] 2.5.97.4 CellParsedFormula TODO: use similar logic to js-xls */\nfunction parse_XLSBCellParsedFormula(data, length) {\n\tvar cce = data.read_shift(4);\n\treturn parsenoop(data, length-4);\n}\n/* [MS-XLS] 2.5.198.44 */\nvar PtgDataType = {\n\t0x1: \"REFERENCE\", // reference to range\n\t0x2: \"VALUE\", // single value\n\t0x3: \"ARRAY\" // array of values\n};\n\n/* [MS-XLS] 2.5.198.4 */\nvar Cetab = {\n\t0x0000: 'BEEP',\n\t0x0001: 'OPEN',\n\t0x0002: 'OPEN.LINKS',\n\t0x0003: 'CLOSE.ALL',\n\t0x0004: 'SAVE',\n\t0x0005: 'SAVE.AS',\n\t0x0006: 'FILE.DELETE',\n\t0x0007: 'PAGE.SETUP',\n\t0x0008: 'PRINT',\n\t0x0009: 'PRINTER.SETUP',\n\t0x000A: 'QUIT',\n\t0x000B: 'NEW.WINDOW',\n\t0x000C: 'ARRANGE.ALL',\n\t0x000D: 'WINDOW.SIZE',\n\t0x000E: 'WINDOW.MOVE',\n\t0x000F: 'FULL',\n\t0x0010: 'CLOSE',\n\t0x0011: 'RUN',\n\t0x0016: 'SET.PRINT.AREA',\n\t0x0017: 'SET.PRINT.TITLES',\n\t0x0018: 'SET.PAGE.BREAK',\n\t0x0019: 'REMOVE.PAGE.BREAK',\n\t0x001A: 'FONT',\n\t0x001B: 'DISPLAY',\n\t0x001C: 'PROTECT.DOCUMENT',\n\t0x001D: 'PRECISION',\n\t0x001E: 'A1.R1C1',\n\t0x001F: 'CALCULATE.NOW',\n\t0x0020: 'CALCULATION',\n\t0x0022: 'DATA.FIND',\n\t0x0023: 'EXTRACT',\n\t0x0024: 'DATA.DELETE',\n\t0x0025: 'SET.DATABASE',\n\t0x0026: 'SET.CRITERIA',\n\t0x0027: 'SORT',\n\t0x0028: 'DATA.SERIES',\n\t0x0029: 'TABLE',\n\t0x002A: 'FORMAT.NUMBER',\n\t0x002B: 'ALIGNMENT',\n\t0x002C: 'STYLE',\n\t0x002D: 'BORDER',\n\t0x002E: 'CELL.PROTECTION',\n\t0x002F: 'COLUMN.WIDTH',\n\t0x0030: 'UNDO',\n\t0x0031: 'CUT',\n\t0x0032: 'COPY',\n\t0x0033: 'PASTE',\n\t0x0034: 'CLEAR',\n\t0x0035: 'PASTE.SPECIAL',\n\t0x0036: 'EDIT.DELETE',\n\t0x0037: 'INSERT',\n\t0x0038: 'FILL.RIGHT',\n\t0x0039: 'FILL.DOWN',\n\t0x003D: 'DEFINE.NAME',\n\t0x003E: 'CREATE.NAMES',\n\t0x003F: 'FORMULA.GOTO',\n\t0x0040: 'FORMULA.FIND',\n\t0x0041: 'SELECT.LAST.CELL',\n\t0x0042: 'SHOW.ACTIVE.CELL',\n\t0x0043: 'GALLERY.AREA',\n\t0x0044: 'GALLERY.BAR',\n\t0x0045: 'GALLERY.COLUMN',\n\t0x0046: 'GALLERY.LINE',\n\t0x0047: 'GALLERY.PIE',\n\t0x0048: 'GALLERY.SCATTER',\n\t0x0049: 'COMBINATION',\n\t0x004A: 'PREFERRED',\n\t0x004B: 'ADD.OVERLAY',\n\t0x004C: 'GRIDLINES',\n\t0x004D: 'SET.PREFERRED',\n\t0x004E: 'AXES',\n\t0x004F: 'LEGEND',\n\t0x0050: 'ATTACH.TEXT',\n\t0x0051: 'ADD.ARROW',\n\t0x0052: 'SELECT.CHART',\n\t0x0053: 'SELECT.PLOT.AREA',\n\t0x0054: 'PATTERNS',\n\t0x0055: 'MAIN.CHART',\n\t0x0056: 'OVERLAY',\n\t0x0057: 'SCALE',\n\t0x0058: 'FORMAT.LEGEND',\n\t0x0059: 'FORMAT.TEXT',\n\t0x005A: 'EDIT.REPEAT',\n\t0x005B: 'PARSE',\n\t0x005C: 'JUSTIFY',\n\t0x005D: 'HIDE',\n\t0x005E: 'UNHIDE',\n\t0x005F: 'WORKSPACE',\n\t0x0060: 'FORMULA',\n\t0x0061: 'FORMULA.FILL',\n\t0x0062: 'FORMULA.ARRAY',\n\t0x0063: 'DATA.FIND.NEXT',\n\t0x0064: 'DATA.FIND.PREV',\n\t0x0065: 'FORMULA.FIND.NEXT',\n\t0x0066: 'FORMULA.FIND.PREV',\n\t0x0067: 'ACTIVATE',\n\t0x0068: 'ACTIVATE.NEXT',\n\t0x0069: 'ACTIVATE.PREV',\n\t0x006A: 'UNLOCKED.NEXT',\n\t0x006B: 'UNLOCKED.PREV',\n\t0x006C: 'COPY.PICTURE',\n\t0x006D: 'SELECT',\n\t0x006E: 'DELETE.NAME',\n\t0x006F: 'DELETE.FORMAT',\n\t0x0070: 'VLINE',\n\t0x0071: 'HLINE',\n\t0x0072: 'VPAGE',\n\t0x0073: 'HPAGE',\n\t0x0074: 'VSCROLL',\n\t0x0075: 'HSCROLL',\n\t0x0076: 'ALERT',\n\t0x0077: 'NEW',\n\t0x0078: 'CANCEL.COPY',\n\t0x0079: 'SHOW.CLIPBOARD',\n\t0x007A: 'MESSAGE',\n\t0x007C: 'PASTE.LINK',\n\t0x007D: 'APP.ACTIVATE',\n\t0x007E: 'DELETE.ARROW',\n\t0x007F: 'ROW.HEIGHT',\n\t0x0080: 'FORMAT.MOVE',\n\t0x0081: 'FORMAT.SIZE',\n\t0x0082: 'FORMULA.REPLACE',\n\t0x0083: 'SEND.KEYS',\n\t0x0084: 'SELECT.SPECIAL',\n\t0x0085: 'APPLY.NAMES',\n\t0x0086: 'REPLACE.FONT',\n\t0x0087: 'FREEZE.PANES',\n\t0x0088: 'SHOW.INFO',\n\t0x0089: 'SPLIT',\n\t0x008A: 'ON.WINDOW',\n\t0x008B: 'ON.DATA',\n\t0x008C: 'DISABLE.INPUT',\n\t0x008E: 'OUTLINE',\n\t0x008F: 'LIST.NAMES',\n\t0x0090: 'FILE.CLOSE',\n\t0x0091: 'SAVE.WORKBOOK',\n\t0x0092: 'DATA.FORM',\n\t0x0093: 'COPY.CHART',\n\t0x0094: 'ON.TIME',\n\t0x0095: 'WAIT',\n\t0x0096: 'FORMAT.FONT',\n\t0x0097: 'FILL.UP',\n\t0x0098: 'FILL.LEFT',\n\t0x0099: 'DELETE.OVERLAY',\n\t0x009B: 'SHORT.MENUS',\n\t0x009F: 'SET.UPDATE.STATUS',\n\t0x00A1: 'COLOR.PALETTE',\n\t0x00A2: 'DELETE.STYLE',\n\t0x00A3: 'WINDOW.RESTORE',\n\t0x00A4: 'WINDOW.MAXIMIZE',\n\t0x00A6: 'CHANGE.LINK',\n\t0x00A7: 'CALCULATE.DOCUMENT',\n\t0x00A8: 'ON.KEY',\n\t0x00A9: 'APP.RESTORE',\n\t0x00AA: 'APP.MOVE',\n\t0x00AB: 'APP.SIZE',\n\t0x00AC: 'APP.MINIMIZE',\n\t0x00AD: 'APP.MAXIMIZE',\n\t0x00AE: 'BRING.TO.FRONT',\n\t0x00AF: 'SEND.TO.BACK',\n\t0x00B9: 'MAIN.CHART.TYPE',\n\t0x00BA: 'OVERLAY.CHART.TYPE',\n\t0x00BB: 'SELECT.END',\n\t0x00BC: 'OPEN.MAIL',\n\t0x00BD: 'SEND.MAIL',\n\t0x00BE: 'STANDARD.FONT',\n\t0x00BF: 'CONSOLIDATE',\n\t0x00C0: 'SORT.SPECIAL',\n\t0x00C1: 'GALLERY.3D.AREA',\n\t0x00C2: 'GALLERY.3D.COLUMN',\n\t0x00C3: 'GALLERY.3D.LINE',\n\t0x00C4: 'GALLERY.3D.PIE',\n\t0x00C5: 'VIEW.3D',\n\t0x00C6: 'GOAL.SEEK',\n\t0x00C7: 'WORKGROUP',\n\t0x00C8: 'FILL.GROUP',\n\t0x00C9: 'UPDATE.LINK',\n\t0x00CA: 'PROMOTE',\n\t0x00CB: 'DEMOTE',\n\t0x00CC: 'SHOW.DETAIL',\n\t0x00CE: 'UNGROUP',\n\t0x00CF: 'OBJECT.PROPERTIES',\n\t0x00D0: 'SAVE.NEW.OBJECT',\n\t0x00D1: 'SHARE',\n\t0x00D2: 'SHARE.NAME',\n\t0x00D3: 'DUPLICATE',\n\t0x00D4: 'APPLY.STYLE',\n\t0x00D5: 'ASSIGN.TO.OBJECT',\n\t0x00D6: 'OBJECT.PROTECTION',\n\t0x00D7: 'HIDE.OBJECT',\n\t0x00D8: 'SET.EXTRACT',\n\t0x00D9: 'CREATE.PUBLISHER',\n\t0x00DA: 'SUBSCRIBE.TO',\n\t0x00DB: 'ATTRIBUTES',\n\t0x00DC: 'SHOW.TOOLBAR',\n\t0x00DE: 'PRINT.PREVIEW',\n\t0x00DF: 'EDIT.COLOR',\n\t0x00E0: 'SHOW.LEVELS',\n\t0x00E1: 'FORMAT.MAIN',\n\t0x00E2: 'FORMAT.OVERLAY',\n\t0x00E3: 'ON.RECALC',\n\t0x00E4: 'EDIT.SERIES',\n\t0x00E5: 'DEFINE.STYLE',\n\t0x00F0: 'LINE.PRINT',\n\t0x00F3: 'ENTER.DATA',\n\t0x00F9: 'GALLERY.RADAR',\n\t0x00FA: 'MERGE.STYLES',\n\t0x00FB: 'EDITION.OPTIONS',\n\t0x00FC: 'PASTE.PICTURE',\n\t0x00FD: 'PASTE.PICTURE.LINK',\n\t0x00FE: 'SPELLING',\n\t0x0100: 'ZOOM',\n\t0x0103: 'INSERT.OBJECT',\n\t0x0104: 'WINDOW.MINIMIZE',\n\t0x0109: 'SOUND.NOTE',\n\t0x010A: 'SOUND.PLAY',\n\t0x010B: 'FORMAT.SHAPE',\n\t0x010C: 'EXTEND.POLYGON',\n\t0x010D: 'FORMAT.AUTO',\n\t0x0110: 'GALLERY.3D.BAR',\n\t0x0111: 'GALLERY.3D.SURFACE',\n\t0x0112: 'FILL.AUTO',\n\t0x0114: 'CUSTOMIZE.TOOLBAR',\n\t0x0115: 'ADD.TOOL',\n\t0x0116: 'EDIT.OBJECT',\n\t0x0117: 'ON.DOUBLECLICK',\n\t0x0118: 'ON.ENTRY',\n\t0x0119: 'WORKBOOK.ADD',\n\t0x011A: 'WORKBOOK.MOVE',\n\t0x011B: 'WORKBOOK.COPY',\n\t0x011C: 'WORKBOOK.OPTIONS',\n\t0x011D: 'SAVE.WORKSPACE',\n\t0x0120: 'CHART.WIZARD',\n\t0x0121: 'DELETE.TOOL',\n\t0x0122: 'MOVE.TOOL',\n\t0x0123: 'WORKBOOK.SELECT',\n\t0x0124: 'WORKBOOK.ACTIVATE',\n\t0x0125: 'ASSIGN.TO.TOOL',\n\t0x0127: 'COPY.TOOL',\n\t0x0128: 'RESET.TOOL',\n\t0x0129: 'CONSTRAIN.NUMERIC',\n\t0x012A: 'PASTE.TOOL',\n\t0x012E: 'WORKBOOK.NEW',\n\t0x0131: 'SCENARIO.CELLS',\n\t0x0132: 'SCENARIO.DELETE',\n\t0x0133: 'SCENARIO.ADD',\n\t0x0134: 'SCENARIO.EDIT',\n\t0x0135: 'SCENARIO.SHOW',\n\t0x0136: 'SCENARIO.SHOW.NEXT',\n\t0x0137: 'SCENARIO.SUMMARY',\n\t0x0138: 'PIVOT.TABLE.WIZARD',\n\t0x0139: 'PIVOT.FIELD.PROPERTIES',\n\t0x013A: 'PIVOT.FIELD',\n\t0x013B: 'PIVOT.ITEM',\n\t0x013C: 'PIVOT.ADD.FIELDS',\n\t0x013E: 'OPTIONS.CALCULATION',\n\t0x013F: 'OPTIONS.EDIT',\n\t0x0140: 'OPTIONS.VIEW',\n\t0x0141: 'ADDIN.MANAGER',\n\t0x0142: 'MENU.EDITOR',\n\t0x0143: 'ATTACH.TOOLBARS',\n\t0x0144: 'VBAActivate',\n\t0x0145: 'OPTIONS.CHART',\n\t0x0148: 'VBA.INSERT.FILE',\n\t0x014A: 'VBA.PROCEDURE.DEFINITION',\n\t0x0150: 'ROUTING.SLIP',\n\t0x0152: 'ROUTE.DOCUMENT',\n\t0x0153: 'MAIL.LOGON',\n\t0x0156: 'INSERT.PICTURE',\n\t0x0157: 'EDIT.TOOL',\n\t0x0158: 'GALLERY.DOUGHNUT',\n\t0x015E: 'CHART.TREND',\n\t0x0160: 'PIVOT.ITEM.PROPERTIES',\n\t0x0162: 'WORKBOOK.INSERT',\n\t0x0163: 'OPTIONS.TRANSITION',\n\t0x0164: 'OPTIONS.GENERAL',\n\t0x0172: 'FILTER.ADVANCED',\n\t0x0175: 'MAIL.ADD.MAILER',\n\t0x0176: 'MAIL.DELETE.MAILER',\n\t0x0177: 'MAIL.REPLY',\n\t0x0178: 'MAIL.REPLY.ALL',\n\t0x0179: 'MAIL.FORWARD',\n\t0x017A: 'MAIL.NEXT.LETTER',\n\t0x017B: 'DATA.LABEL',\n\t0x017C: 'INSERT.TITLE',\n\t0x017D: 'FONT.PROPERTIES',\n\t0x017E: 'MACRO.OPTIONS',\n\t0x017F: 'WORKBOOK.HIDE',\n\t0x0180: 'WORKBOOK.UNHIDE',\n\t0x0181: 'WORKBOOK.DELETE',\n\t0x0182: 'WORKBOOK.NAME',\n\t0x0184: 'GALLERY.CUSTOM',\n\t0x0186: 'ADD.CHART.AUTOFORMAT',\n\t0x0187: 'DELETE.CHART.AUTOFORMAT',\n\t0x0188: 'CHART.ADD.DATA',\n\t0x0189: 'AUTO.OUTLINE',\n\t0x018A: 'TAB.ORDER',\n\t0x018B: 'SHOW.DIALOG',\n\t0x018C: 'SELECT.ALL',\n\t0x018D: 'UNGROUP.SHEETS',\n\t0x018E: 'SUBTOTAL.CREATE',\n\t0x018F: 'SUBTOTAL.REMOVE',\n\t0x0190: 'RENAME.OBJECT',\n\t0x019C: 'WORKBOOK.SCROLL',\n\t0x019D: 'WORKBOOK.NEXT',\n\t0x019E: 'WORKBOOK.PREV',\n\t0x019F: 'WORKBOOK.TAB.SPLIT',\n\t0x01A0: 'FULL.SCREEN',\n\t0x01A1: 'WORKBOOK.PROTECT',\n\t0x01A4: 'SCROLLBAR.PROPERTIES',\n\t0x01A5: 'PIVOT.SHOW.PAGES',\n\t0x01A6: 'TEXT.TO.COLUMNS',\n\t0x01A7: 'FORMAT.CHARTTYPE',\n\t0x01A8: 'LINK.FORMAT',\n\t0x01A9: 'TRACER.DISPLAY',\n\t0x01AE: 'TRACER.NAVIGATE',\n\t0x01AF: 'TRACER.CLEAR',\n\t0x01B0: 'TRACER.ERROR',\n\t0x01B1: 'PIVOT.FIELD.GROUP',\n\t0x01B2: 'PIVOT.FIELD.UNGROUP',\n\t0x01B3: 'CHECKBOX.PROPERTIES',\n\t0x01B4: 'LABEL.PROPERTIES',\n\t0x01B5: 'LISTBOX.PROPERTIES',\n\t0x01B6: 'EDITBOX.PROPERTIES',\n\t0x01B7: 'PIVOT.REFRESH',\n\t0x01B8: 'LINK.COMBO',\n\t0x01B9: 'OPEN.TEXT',\n\t0x01BA: 'HIDE.DIALOG',\n\t0x01BB: 'SET.DIALOG.FOCUS',\n\t0x01BC: 'ENABLE.OBJECT',\n\t0x01BD: 'PUSHBUTTON.PROPERTIES',\n\t0x01BE: 'SET.DIALOG.DEFAULT',\n\t0x01BF: 'FILTER',\n\t0x01C0: 'FILTER.SHOW.ALL',\n\t0x01C1: 'CLEAR.OUTLINE',\n\t0x01C2: 'FUNCTION.WIZARD',\n\t0x01C3: 'ADD.LIST.ITEM',\n\t0x01C4: 'SET.LIST.ITEM',\n\t0x01C5: 'REMOVE.LIST.ITEM',\n\t0x01C6: 'SELECT.LIST.ITEM',\n\t0x01C7: 'SET.CONTROL.VALUE',\n\t0x01C8: 'SAVE.COPY.AS',\n\t0x01CA: 'OPTIONS.LISTS.ADD',\n\t0x01CB: 'OPTIONS.LISTS.DELETE',\n\t0x01CC: 'SERIES.AXES',\n\t0x01CD: 'SERIES.X',\n\t0x01CE: 'SERIES.Y',\n\t0x01CF: 'ERRORBAR.X',\n\t0x01D0: 'ERRORBAR.Y',\n\t0x01D1: 'FORMAT.CHART',\n\t0x01D2: 'SERIES.ORDER',\n\t0x01D3: 'MAIL.LOGOFF',\n\t0x01D4: 'CLEAR.ROUTING.SLIP',\n\t0x01D5: 'APP.ACTIVATE.MICROSOFT',\n\t0x01D6: 'MAIL.EDIT.MAILER',\n\t0x01D7: 'ON.SHEET',\n\t0x01D8: 'STANDARD.WIDTH',\n\t0x01D9: 'SCENARIO.MERGE',\n\t0x01DA: 'SUMMARY.INFO',\n\t0x01DB: 'FIND.FILE',\n\t0x01DC: 'ACTIVE.CELL.FONT',\n\t0x01DD: 'ENABLE.TIPWIZARD',\n\t0x01DE: 'VBA.MAKE.ADDIN',\n\t0x01E0: 'INSERTDATATABLE',\n\t0x01E1: 'WORKGROUP.OPTIONS',\n\t0x01E2: 'MAIL.SEND.MAILER',\n\t0x01E5: 'AUTOCORRECT',\n\t0x01E9: 'POST.DOCUMENT',\n\t0x01EB: 'PICKLIST',\n\t0x01ED: 'VIEW.SHOW',\n\t0x01EE: 'VIEW.DEFINE',\n\t0x01EF: 'VIEW.DELETE',\n\t0x01FD: 'SHEET.BACKGROUND',\n\t0x01FE: 'INSERT.MAP.OBJECT',\n\t0x01FF: 'OPTIONS.MENONO',\n\t0x0205: 'MSOCHECKS',\n\t0x0206: 'NORMAL',\n\t0x0207: 'LAYOUT',\n\t0x0208: 'RM.PRINT.AREA',\n\t0x0209: 'CLEAR.PRINT.AREA',\n\t0x020A: 'ADD.PRINT.AREA',\n\t0x020B: 'MOVE.BRK',\n\t0x0221: 'HIDECURR.NOTE',\n\t0x0222: 'HIDEALL.NOTES',\n\t0x0223: 'DELETE.NOTE',\n\t0x0224: 'TRAVERSE.NOTES',\n\t0x0225: 'ACTIVATE.NOTES',\n\t0x026C: 'PROTECT.REVISIONS',\n\t0x026D: 'UNPROTECT.REVISIONS',\n\t0x0287: 'OPTIONS.ME',\n\t0x028D: 'WEB.PUBLISH',\n\t0x029B: 'NEWWEBQUERY',\n\t0x02A1: 'PIVOT.TABLE.CHART',\n\t0x02F1: 'OPTIONS.SAVE',\n\t0x02F3: 'OPTIONS.SPELL',\n\t0x0328: 'HIDEALL.INKANNOTS'\n};\n\n/* [MS-XLS] 2.5.198.17 */\nvar Ftab = {\n\t0x0000: 'COUNT',\n\t0x0001: 'IF',\n\t0x0002: 'ISNA',\n\t0x0003: 'ISERROR',\n\t0x0004: 'SUM',\n\t0x0005: 'AVERAGE',\n\t0x0006: 'MIN',\n\t0x0007: 'MAX',\n\t0x0008: 'ROW',\n\t0x0009: 'COLUMN',\n\t0x000A: 'NA',\n\t0x000B: 'NPV',\n\t0x000C: 'STDEV',\n\t0x000D: 'DOLLAR',\n\t0x000E: 'FIXED',\n\t0x000F: 'SIN',\n\t0x0010: 'COS',\n\t0x0011: 'TAN',\n\t0x0012: 'ATAN',\n\t0x0013: 'PI',\n\t0x0014: 'SQRT',\n\t0x0015: 'EXP',\n\t0x0016: 'LN',\n\t0x0017: 'LOG10',\n\t0x0018: 'ABS',\n\t0x0019: 'INT',\n\t0x001A: 'SIGN',\n\t0x001B: 'ROUND',\n\t0x001C: 'LOOKUP',\n\t0x001D: 'INDEX',\n\t0x001E: 'REPT',\n\t0x001F: 'MID',\n\t0x0020: 'LEN',\n\t0x0021: 'VALUE',\n\t0x0022: 'TRUE',\n\t0x0023: 'FALSE',\n\t0x0024: 'AND',\n\t0x0025: 'OR',\n\t0x0026: 'NOT',\n\t0x0027: 'MOD',\n\t0x0028: 'DCOUNT',\n\t0x0029: 'DSUM',\n\t0x002A: 'DAVERAGE',\n\t0x002B: 'DMIN',\n\t0x002C: 'DMAX',\n\t0x002D: 'DSTDEV',\n\t0x002E: 'VAR',\n\t0x002F: 'DVAR',\n\t0x0030: 'TEXT',\n\t0x0031: 'LINEST',\n\t0x0032: 'TREND',\n\t0x0033: 'LOGEST',\n\t0x0034: 'GROWTH',\n\t0x0035: 'GOTO',\n\t0x0036: 'HALT',\n\t0x0037: 'RETURN',\n\t0x0038: 'PV',\n\t0x0039: 'FV',\n\t0x003A: 'NPER',\n\t0x003B: 'PMT',\n\t0x003C: 'RATE',\n\t0x003D: 'MIRR',\n\t0x003E: 'IRR',\n\t0x003F: 'RAND',\n\t0x0040: 'MATCH',\n\t0x0041: 'DATE',\n\t0x0042: 'TIME',\n\t0x0043: 'DAY',\n\t0x0044: 'MONTH',\n\t0x0045: 'YEAR',\n\t0x0046: 'WEEKDAY',\n\t0x0047: 'HOUR',\n\t0x0048: 'MINUTE',\n\t0x0049: 'SECOND',\n\t0x004A: 'NOW',\n\t0x004B: 'AREAS',\n\t0x004C: 'ROWS',\n\t0x004D: 'COLUMNS',\n\t0x004E: 'OFFSET',\n\t0x004F: 'ABSREF',\n\t0x0050: 'RELREF',\n\t0x0051: 'ARGUMENT',\n\t0x0052: 'SEARCH',\n\t0x0053: 'TRANSPOSE',\n\t0x0054: 'ERROR',\n\t0x0055: 'STEP',\n\t0x0056: 'TYPE',\n\t0x0057: 'ECHO',\n\t0x0058: 'SET.NAME',\n\t0x0059: 'CALLER',\n\t0x005A: 'DEREF',\n\t0x005B: 'WINDOWS',\n\t0x005C: 'SERIES',\n\t0x005D: 'DOCUMENTS',\n\t0x005E: 'ACTIVE.CELL',\n\t0x005F: 'SELECTION',\n\t0x0060: 'RESULT',\n\t0x0061: 'ATAN2',\n\t0x0062: 'ASIN',\n\t0x0063: 'ACOS',\n\t0x0064: 'CHOOSE',\n\t0x0065: 'HLOOKUP',\n\t0x0066: 'VLOOKUP',\n\t0x0067: 'LINKS',\n\t0x0068: 'INPUT',\n\t0x0069: 'ISREF',\n\t0x006A: 'GET.FORMULA',\n\t0x006B: 'GET.NAME',\n\t0x006C: 'SET.VALUE',\n\t0x006D: 'LOG',\n\t0x006E: 'EXEC',\n\t0x006F: 'CHAR',\n\t0x0070: 'LOWER',\n\t0x0071: 'UPPER',\n\t0x0072: 'PROPER',\n\t0x0073: 'LEFT',\n\t0x0074: 'RIGHT',\n\t0x0075: 'EXACT',\n\t0x0076: 'TRIM',\n\t0x0077: 'REPLACE',\n\t0x0078: 'SUBSTITUTE',\n\t0x0079: 'CODE',\n\t0x007A: 'NAMES',\n\t0x007B: 'DIRECTORY',\n\t0x007C: 'FIND',\n\t0x007D: 'CELL',\n\t0x007E: 'ISERR',\n\t0x007F: 'ISTEXT',\n\t0x0080: 'ISNUMBER',\n\t0x0081: 'ISBLANK',\n\t0x0082: 'T',\n\t0x0083: 'N',\n\t0x0084: 'FOPEN',\n\t0x0085: 'FCLOSE',\n\t0x0086: 'FSIZE',\n\t0x0087: 'FREADLN',\n\t0x0088: 'FREAD',\n\t0x0089: 'FWRITELN',\n\t0x008A: 'FWRITE',\n\t0x008B: 'FPOS',\n\t0x008C: 'DATEVALUE',\n\t0x008D: 'TIMEVALUE',\n\t0x008E: 'SLN',\n\t0x008F: 'SYD',\n\t0x0090: 'DDB',\n\t0x0091: 'GET.DEF',\n\t0x0092: 'REFTEXT',\n\t0x0093: 'TEXTREF',\n\t0x0094: 'INDIRECT',\n\t0x0095: 'REGISTER',\n\t0x0096: 'CALL',\n\t0x0097: 'ADD.BAR',\n\t0x0098: 'ADD.MENU',\n\t0x0099: 'ADD.COMMAND',\n\t0x009A: 'ENABLE.COMMAND',\n\t0x009B: 'CHECK.COMMAND',\n\t0x009C: 'RENAME.COMMAND',\n\t0x009D: 'SHOW.BAR',\n\t0x009E: 'DELETE.MENU',\n\t0x009F: 'DELETE.COMMAND',\n\t0x00A0: 'GET.CHART.ITEM',\n\t0x00A1: 'DIALOG.BOX',\n\t0x00A2: 'CLEAN',\n\t0x00A3: 'MDETERM',\n\t0x00A4: 'MINVERSE',\n\t0x00A5: 'MMULT',\n\t0x00A6: 'FILES',\n\t0x00A7: 'IPMT',\n\t0x00A8: 'PPMT',\n\t0x00A9: 'COUNTA',\n\t0x00AA: 'CANCEL.KEY',\n\t0x00AB: 'FOR',\n\t0x00AC: 'WHILE',\n\t0x00AD: 'BREAK',\n\t0x00AE: 'NEXT',\n\t0x00AF: 'INITIATE',\n\t0x00B0: 'REQUEST',\n\t0x00B1: 'POKE',\n\t0x00B2: 'EXECUTE',\n\t0x00B3: 'TERMINATE',\n\t0x00B4: 'RESTART',\n\t0x00B5: 'HELP',\n\t0x00B6: 'GET.BAR',\n\t0x00B7: 'PRODUCT',\n\t0x00B8: 'FACT',\n\t0x00B9: 'GET.CELL',\n\t0x00BA: 'GET.WORKSPACE',\n\t0x00BB: 'GET.WINDOW',\n\t0x00BC: 'GET.DOCUMENT',\n\t0x00BD: 'DPRODUCT',\n\t0x00BE: 'ISNONTEXT',\n\t0x00BF: 'GET.NOTE',\n\t0x00C0: 'NOTE',\n\t0x00C1: 'STDEVP',\n\t0x00C2: 'VARP',\n\t0x00C3: 'DSTDEVP',\n\t0x00C4: 'DVARP',\n\t0x00C5: 'TRUNC',\n\t0x00C6: 'ISLOGICAL',\n\t0x00C7: 'DCOUNTA',\n\t0x00C8: 'DELETE.BAR',\n\t0x00C9: 'UNREGISTER',\n\t0x00CC: 'USDOLLAR',\n\t0x00CD: 'FINDB',\n\t0x00CE: 'SEARCHB',\n\t0x00CF: 'REPLACEB',\n\t0x00D0: 'LEFTB',\n\t0x00D1: 'RIGHTB',\n\t0x00D2: 'MIDB',\n\t0x00D3: 'LENB',\n\t0x00D4: 'ROUNDUP',\n\t0x00D5: 'ROUNDDOWN',\n\t0x00D6: 'ASC',\n\t0x00D7: 'DBCS',\n\t0x00D8: 'RANK',\n\t0x00DB: 'ADDRESS',\n\t0x00DC: 'DAYS360',\n\t0x00DD: 'TODAY',\n\t0x00DE: 'VDB',\n\t0x00DF: 'ELSE',\n\t0x00E0: 'ELSE.IF',\n\t0x00E1: 'END.IF',\n\t0x00E2: 'FOR.CELL',\n\t0x00E3: 'MEDIAN',\n\t0x00E4: 'SUMPRODUCT',\n\t0x00E5: 'SINH',\n\t0x00E6: 'COSH',\n\t0x00E7: 'TANH',\n\t0x00E8: 'ASINH',\n\t0x00E9: 'ACOSH',\n\t0x00EA: 'ATANH',\n\t0x00EB: 'DGET',\n\t0x00EC: 'CREATE.OBJECT',\n\t0x00ED: 'VOLATILE',\n\t0x00EE: 'LAST.ERROR',\n\t0x00EF: 'CUSTOM.UNDO',\n\t0x00F0: 'CUSTOM.REPEAT',\n\t0x00F1: 'FORMULA.CONVERT',\n\t0x00F2: 'GET.LINK.INFO',\n\t0x00F3: 'TEXT.BOX',\n\t0x00F4: 'INFO',\n\t0x00F5: 'GROUP',\n\t0x00F6: 'GET.OBJECT',\n\t0x00F7: 'DB',\n\t0x00F8: 'PAUSE',\n\t0x00FB: 'RESUME',\n\t0x00FC: 'FREQUENCY',\n\t0x00FD: 'ADD.TOOLBAR',\n\t0x00FE: 'DELETE.TOOLBAR',\n\t0x00FF: 'User',\n\t0x0100: 'RESET.TOOLBAR',\n\t0x0101: 'EVALUATE',\n\t0x0102: 'GET.TOOLBAR',\n\t0x0103: 'GET.TOOL',\n\t0x0104: 'SPELLING.CHECK',\n\t0x0105: 'ERROR.TYPE',\n\t0x0106: 'APP.TITLE',\n\t0x0107: 'WINDOW.TITLE',\n\t0x0108: 'SAVE.TOOLBAR',\n\t0x0109: 'ENABLE.TOOL',\n\t0x010A: 'PRESS.TOOL',\n\t0x010B: 'REGISTER.ID',\n\t0x010C: 'GET.WORKBOOK',\n\t0x010D: 'AVEDEV',\n\t0x010E: 'BETADIST',\n\t0x010F: 'GAMMALN',\n\t0x0110: 'BETAINV',\n\t0x0111: 'BINOMDIST',\n\t0x0112: 'CHIDIST',\n\t0x0113: 'CHIINV',\n\t0x0114: 'COMBIN',\n\t0x0115: 'CONFIDENCE',\n\t0x0116: 'CRITBINOM',\n\t0x0117: 'EVEN',\n\t0x0118: 'EXPONDIST',\n\t0x0119: 'FDIST',\n\t0x011A: 'FINV',\n\t0x011B: 'FISHER',\n\t0x011C: 'FISHERINV',\n\t0x011D: 'FLOOR',\n\t0x011E: 'GAMMADIST',\n\t0x011F: 'GAMMAINV',\n\t0x0120: 'CEILING',\n\t0x0121: 'HYPGEOMDIST',\n\t0x0122: 'LOGNORMDIST',\n\t0x0123: 'LOGINV',\n\t0x0124: 'NEGBINOMDIST',\n\t0x0125: 'NORMDIST',\n\t0x0126: 'NORMSDIST',\n\t0x0127: 'NORMINV',\n\t0x0128: 'NORMSINV',\n\t0x0129: 'STANDARDIZE',\n\t0x012A: 'ODD',\n\t0x012B: 'PERMUT',\n\t0x012C: 'POISSON',\n\t0x012D: 'TDIST',\n\t0x012E: 'WEIBULL',\n\t0x012F: 'SUMXMY2',\n\t0x0130: 'SUMX2MY2',\n\t0x0131: 'SUMX2PY2',\n\t0x0132: 'CHITEST',\n\t0x0133: 'CORREL',\n\t0x0134: 'COVAR',\n\t0x0135: 'FORECAST',\n\t0x0136: 'FTEST',\n\t0x0137: 'INTERCEPT',\n\t0x0138: 'PEARSON',\n\t0x0139: 'RSQ',\n\t0x013A: 'STEYX',\n\t0x013B: 'SLOPE',\n\t0x013C: 'TTEST',\n\t0x013D: 'PROB',\n\t0x013E: 'DEVSQ',\n\t0x013F: 'GEOMEAN',\n\t0x0140: 'HARMEAN',\n\t0x0141: 'SUMSQ',\n\t0x0142: 'KURT',\n\t0x0143: 'SKEW',\n\t0x0144: 'ZTEST',\n\t0x0145: 'LARGE',\n\t0x0146: 'SMALL',\n\t0x0147: 'QUARTILE',\n\t0x0148: 'PERCENTILE',\n\t0x0149: 'PERCENTRANK',\n\t0x014A: 'MODE',\n\t0x014B: 'TRIMMEAN',\n\t0x014C: 'TINV',\n\t0x014E: 'MOVIE.COMMAND',\n\t0x014F: 'GET.MOVIE',\n\t0x0150: 'CONCATENATE',\n\t0x0151: 'POWER',\n\t0x0152: 'PIVOT.ADD.DATA',\n\t0x0153: 'GET.PIVOT.TABLE',\n\t0x0154: 'GET.PIVOT.FIELD',\n\t0x0155: 'GET.PIVOT.ITEM',\n\t0x0156: 'RADIANS',\n\t0x0157: 'DEGREES',\n\t0x0158: 'SUBTOTAL',\n\t0x0159: 'SUMIF',\n\t0x015A: 'COUNTIF',\n\t0x015B: 'COUNTBLANK',\n\t0x015C: 'SCENARIO.GET',\n\t0x015D: 'OPTIONS.LISTS.GET',\n\t0x015E: 'ISPMT',\n\t0x015F: 'DATEDIF',\n\t0x0160: 'DATESTRING',\n\t0x0161: 'NUMBERSTRING',\n\t0x0162: 'ROMAN',\n\t0x0163: 'OPEN.DIALOG',\n\t0x0164: 'SAVE.DIALOG',\n\t0x0165: 'VIEW.GET',\n\t0x0166: 'GETPIVOTDATA',\n\t0x0167: 'HYPERLINK',\n\t0x0168: 'PHONETIC',\n\t0x0169: 'AVERAGEA',\n\t0x016A: 'MAXA',\n\t0x016B: 'MINA',\n\t0x016C: 'STDEVPA',\n\t0x016D: 'VARPA',\n\t0x016E: 'STDEVA',\n\t0x016F: 'VARA',\n\t0x0170: 'BAHTTEXT',\n\t0x0171: 'THAIDAYOFWEEK',\n\t0x0172: 'THAIDIGIT',\n\t0x0173: 'THAIMONTHOFYEAR',\n\t0x0174: 'THAINUMSOUND',\n\t0x0175: 'THAINUMSTRING',\n\t0x0176: 'THAISTRINGLENGTH',\n\t0x0177: 'ISTHAIDIGIT',\n\t0x0178: 'ROUNDBAHTDOWN',\n\t0x0179: 'ROUNDBAHTUP',\n\t0x017A: 'THAIYEAR',\n\t0x017B: 'RTD'\n};\nvar FtabArgc = {\n\t0x0002: 1, /* ISNA */\n\t0x0003: 1, /* ISERROR */\n\t0x000F: 1, /* SIN */\n\t0x0010: 1, /* COS */\n\t0x0011: 1, /* TAN */\n\t0x0012: 1, /* ATAN */\n\t0x0014: 1, /* SQRT */\n\t0x0015: 1, /* EXP */\n\t0x0016: 1, /* LN */\n\t0x0017: 1, /* LOG10 */\n\t0x0018: 1, /* ABS */\n\t0x0019: 1, /* INT */\n\t0x001A: 1, /* SIGN */\n\t0x001B: 2, /* ROUND */\n\t0x001E: 2, /* REPT */\n\t0x001F: 3, /* MID */\n\t0x0020: 1, /* LEN */\n\t0x0021: 1, /* VALUE */\n\t0x0026: 1, /* NOT */\n\t0x0027: 2, /* MOD */\n\t0x0028: 3, /* DCOUNT */\n\t0x0029: 3, /* DSUM */\n\t0x002A: 3, /* DAVERAGE */\n\t0x002B: 3, /* DMIN */\n\t0x002C: 3, /* DMAX */\n\t0x002D: 3, /* DSTDEV */\n\t0x002F: 3, /* DVAR */\n\t0x0030: 2, /* TEXT */\n\t0x0035: 1, /* GOTO */\n\t0x003D: 3, /* MIRR */\n\t0x0041: 3, /* DATE */\n\t0x0042: 3, /* TIME */\n\t0x0043: 1, /* DAY */\n\t0x0044: 1, /* MONTH */\n\t0x0045: 1, /* YEAR */\n\t0x0047: 1, /* HOUR */\n\t0x0048: 1, /* MINUTE */\n\t0x0049: 1, /* SECOND */\n\t0x004B: 1, /* AREAS */\n\t0x004C: 1, /* ROWS */\n\t0x004D: 1, /* COLUMNS */\n\t0x004F: 2, /* ABSREF */\n\t0x0050: 2, /* RELREF */\n\t0x0053: 1, /* TRANSPOSE */\n\t0x0056: 1, /* TYPE */\n\t0x005A: 1, /* DEREF */\n\t0x0061: 2, /* ATAN2 */\n\t0x0062: 1, /* ASIN */\n\t0x0063: 1, /* ACOS */\n\t0x0069: 1, /* ISREF */\n\t0x006F: 1, /* CHAR */\n\t0x0070: 1, /* LOWER */\n\t0x0071: 1, /* UPPER */\n\t0x0072: 1, /* PROPER */\n\t0x0075: 2, /* EXACT */\n\t0x0076: 1, /* TRIM */\n\t0x0077: 4, /* REPLACE */\n\t0x0079: 1, /* CODE */\n\t0x007E: 1, /* ISERR */\n\t0x007F: 1, /* ISTEXT */\n\t0x0080: 1, /* ISNUMBER */\n\t0x0081: 1, /* ISBLANK */\n\t0x0082: 1, /* T */\n\t0x0083: 1, /* N */\n\t0x0085: 1, /* FCLOSE */\n\t0x0086: 1, /* FSIZE */\n\t0x0087: 1, /* FREADLN */\n\t0x0088: 2, /* FREAD */\n\t0x0089: 2, /* FWRITELN */\n\t0x008A: 2, /* FWRITE */\n\t0x008C: 1, /* DATEVALUE */\n\t0x008D: 1, /* TIMEVALUE */\n\t0x008E: 3, /* SLN */\n\t0x008F: 4, /* SYD */\n\t0x00A2: 1, /* CLEAN */\n\t0x00A3: 1, /* MDETERM */\n\t0x00A4: 1, /* MINVERSE */\n\t0x00A5: 2, /* MMULT */\n\t0x00AC: 1, /* WHILE */\n\t0x00AF: 2, /* INITIATE */\n\t0x00B0: 2, /* REQUEST */\n\t0x00B1: 3, /* POKE */\n\t0x00B2: 2, /* EXECUTE */\n\t0x00B3: 1, /* TERMINATE */\n\t0x00B8: 1, /* FACT */\n\t0x00BD: 3, /* DPRODUCT */\n\t0x00BE: 1, /* ISNONTEXT */\n\t0x00C3: 3, /* DSTDEVP */\n\t0x00C4: 3, /* DVARP */\n\t0x00C6: 1, /* ISLOGICAL */\n\t0x00C7: 3, /* DCOUNTA */\n\t0x00C9: 1, /* UNREGISTER */\n\t0x00CF: 4, /* REPLACEB */\n\t0x00D2: 3, /* MIDB */\n\t0x00D3: 1, /* LENB */\n\t0x00D4: 2, /* ROUNDUP */\n\t0x00D5: 2, /* ROUNDDOWN */\n\t0x00D6: 1, /* ASC */\n\t0x00D7: 1, /* DBCS */\n\t0x00E5: 1, /* SINH */\n\t0x00E6: 1, /* COSH */\n\t0x00E7: 1, /* TANH */\n\t0x00E8: 1, /* ASINH */\n\t0x00E9: 1, /* ACOSH */\n\t0x00EA: 1, /* ATANH */\n\t0x00EB: 3, /* DGET */\n\t0x00F4: 1, /* INFO */\n\t0x00FC: 2, /* FREQUENCY */\n\t0x0101: 1, /* EVALUATE */\n\t0x0105: 1, /* ERROR.TYPE */\n\t0x010F: 1, /* GAMMALN */\n\t0x0111: 4, /* BINOMDIST */\n\t0x0112: 2, /* CHIDIST */\n\t0x0113: 2, /* CHIINV */\n\t0x0114: 2, /* COMBIN */\n\t0x0115: 3, /* CONFIDENCE */\n\t0x0116: 3, /* CRITBINOM */\n\t0x0117: 1, /* EVEN */\n\t0x0118: 3, /* EXPONDIST */\n\t0x0119: 3, /* FDIST */\n\t0x011A: 3, /* FINV */\n\t0x011B: 1, /* FISHER */\n\t0x011C: 1, /* FISHERINV */\n\t0x011D: 2, /* FLOOR */\n\t0x011E: 4, /* GAMMADIST */\n\t0x011F: 3, /* GAMMAINV */\n\t0x0120: 2, /* CEILING */\n\t0x0121: 4, /* HYPGEOMDIST */\n\t0x0122: 3, /* LOGNORMDIST */\n\t0x0123: 3, /* LOGINV */\n\t0x0124: 3, /* NEGBINOMDIST */\n\t0x0125: 4, /* NORMDIST */\n\t0x0126: 1, /* NORMSDIST */\n\t0x0127: 3, /* NORMINV */\n\t0x0128: 1, /* NORMSINV */\n\t0x0129: 3, /* STANDARDIZE */\n\t0x012A: 1, /* ODD */\n\t0x012B: 2, /* PERMUT */\n\t0x012C: 3, /* POISSON */\n\t0x012D: 3, /* TDIST */\n\t0x012E: 4, /* WEIBULL */\n\t0x012F: 2, /* SUMXMY2 */\n\t0x0130: 2, /* SUMX2MY2 */\n\t0x0131: 2, /* SUMX2PY2 */\n\t0x0132: 2, /* CHITEST */\n\t0x0133: 2, /* CORREL */\n\t0x0134: 2, /* COVAR */\n\t0x0135: 3, /* FORECAST */\n\t0x0136: 2, /* FTEST */\n\t0x0137: 2, /* INTERCEPT */\n\t0x0138: 2, /* PEARSON */\n\t0x0139: 2, /* RSQ */\n\t0x013A: 2, /* STEYX */\n\t0x013B: 2, /* SLOPE */\n\t0x013C: 4, /* TTEST */\n\t0x0145: 2, /* LARGE */\n\t0x0146: 2, /* SMALL */\n\t0x0147: 2, /* QUARTILE */\n\t0x0148: 2, /* PERCENTILE */\n\t0x014B: 2, /* TRIMMEAN */\n\t0x014C: 2, /* TINV */\n\t0x0151: 2, /* POWER */\n\t0x0156: 1, /* RADIANS */\n\t0x0157: 1, /* DEGREES */\n\t0x015A: 2, /* COUNTIF */\n\t0x015B: 1, /* COUNTBLANK */\n\t0x015E: 4, /* ISPMT */\n\t0x015F: 3, /* DATEDIF */\n\t0x0160: 1, /* DATESTRING */\n\t0x0161: 2, /* NUMBERSTRING */\n\t0x0168: 1, /* PHONETIC */\n\t0x0170: 1, /* BAHTTEXT */\n\t0x0171: 1, /* THAIDAYOFWEEK */\n\t0x0172: 1, /* THAIDIGIT */\n\t0x0173: 1, /* THAIMONTHOFYEAR */\n\t0x0174: 1, /* THAINUMSOUND */\n\t0x0175: 1, /* THAINUMSTRING */\n\t0x0176: 1, /* THAISTRINGLENGTH */\n\t0x0177: 1, /* ISTHAIDIGIT */\n\t0x0178: 1, /* ROUNDBAHTDOWN */\n\t0x0179: 1, /* ROUNDBAHTUP */\n\t0x017A: 1, /* THAIYEAR */\n\t0xFFFF: 0\n};\n/* [MS-XLSX] 2.2.3 Functions */\nvar XLSXFutureFunctions = {\n\t\"_xlfn.ACOT\": \"ACOT\",\n\t\"_xlfn.ACOTH\": \"ACOTH\",\n\t\"_xlfn.AGGREGATE\": \"AGGREGATE\",\n\t\"_xlfn.ARABIC\": \"ARABIC\",\n\t\"_xlfn.AVERAGEIF\": \"AVERAGEIF\",\n\t\"_xlfn.AVERAGEIFS\": \"AVERAGEIFS\",\n\t\"_xlfn.BASE\": \"BASE\",\n\t\"_xlfn.BETA.DIST\": \"BETA.DIST\",\n\t\"_xlfn.BETA.INV\": \"BETA.INV\",\n\t\"_xlfn.BINOM.DIST\": \"BINOM.DIST\",\n\t\"_xlfn.BINOM.DIST.RANGE\": \"BINOM.DIST.RANGE\",\n\t\"_xlfn.BINOM.INV\": \"BINOM.INV\",\n\t\"_xlfn.BITAND\": \"BITAND\",\n\t\"_xlfn.BITLSHIFT\": \"BITLSHIFT\",\n\t\"_xlfn.BITOR\": \"BITOR\",\n\t\"_xlfn.BITRSHIFT\": \"BITRSHIFT\",\n\t\"_xlfn.BITXOR\": \"BITXOR\",\n\t\"_xlfn.CEILING.MATH\": \"CEILING.MATH\",\n\t\"_xlfn.CEILING.PRECISE\": \"CEILING.PRECISE\",\n\t\"_xlfn.CHISQ.DIST\": \"CHISQ.DIST\",\n\t\"_xlfn.CHISQ.DIST.RT\": \"CHISQ.DIST.RT\",\n\t\"_xlfn.CHISQ.INV\": \"CHISQ.INV\",\n\t\"_xlfn.CHISQ.INV.RT\": \"CHISQ.INV.RT\",\n\t\"_xlfn.CHISQ.TEST\": \"CHISQ.TEST\",\n\t\"_xlfn.COMBINA\": \"COMBINA\",\n\t\"_xlfn.CONFIDENCE.NORM\": \"CONFIDENCE.NORM\",\n\t\"_xlfn.CONFIDENCE.T\": \"CONFIDENCE.T\",\n\t\"_xlfn.COT\": \"COT\",\n\t\"_xlfn.COTH\": \"COTH\",\n\t\"_xlfn.COUNTIFS\": \"COUNTIFS\",\n\t\"_xlfn.COVARIANCE.P\": \"COVARIANCE.P\",\n\t\"_xlfn.COVARIANCE.S\": \"COVARIANCE.S\",\n\t\"_xlfn.CSC\": \"CSC\",\n\t\"_xlfn.CSCH\": \"CSCH\",\n\t\"_xlfn.DAYS\": \"DAYS\",\n\t\"_xlfn.DECIMAL\": \"DECIMAL\",\n\t\"_xlfn.ECMA.CEILING\": \"ECMA.CEILING\",\n\t\"_xlfn.ERF.PRECISE\": \"ERF.PRECISE\",\n\t\"_xlfn.ERFC.PRECISE\": \"ERFC.PRECISE\",\n\t\"_xlfn.EXPON.DIST\": \"EXPON.DIST\",\n\t\"_xlfn.F.DIST\": \"F.DIST\",\n\t\"_xlfn.F.DIST.RT\": \"F.DIST.RT\",\n\t\"_xlfn.F.INV\": \"F.INV\",\n\t\"_xlfn.F.INV.RT\": \"F.INV.RT\",\n\t\"_xlfn.F.TEST\": \"F.TEST\",\n\t\"_xlfn.FILTERXML\": \"FILTERXML\",\n\t\"_xlfn.FLOOR.MATH\": \"FLOOR.MATH\",\n\t\"_xlfn.FLOOR.PRECISE\": \"FLOOR.PRECISE\",\n\t\"_xlfn.FORMULATEXT\": \"FORMULATEXT\",\n\t\"_xlfn.GAMMA\": \"GAMMA\",\n\t\"_xlfn.GAMMA.DIST\": \"GAMMA.DIST\",\n\t\"_xlfn.GAMMA.INV\": \"GAMMA.INV\",\n\t\"_xlfn.GAMMALN.PRECISE\": \"GAMMALN.PRECISE\",\n\t\"_xlfn.GAUSS\": \"GAUSS\",\n\t\"_xlfn.HYPGEOM.DIST\": \"HYPGEOM.DIST\",\n\t\"_xlfn.IFNA\": \"IFNA\",\n\t\"_xlfn.IFERROR\": \"IFERROR\",\n\t\"_xlfn.IMCOSH\": \"IMCOSH\",\n\t\"_xlfn.IMCOT\": \"IMCOT\",\n\t\"_xlfn.IMCSC\": \"IMCSC\",\n\t\"_xlfn.IMCSCH\": \"IMCSCH\",\n\t\"_xlfn.IMSEC\": \"IMSEC\",\n\t\"_xlfn.IMSECH\": \"IMSECH\",\n\t\"_xlfn.IMSINH\": \"IMSINH\",\n\t\"_xlfn.IMTAN\": \"IMTAN\",\n\t\"_xlfn.ISFORMULA\": \"ISFORMULA\",\n\t\"_xlfn.ISO.CEILING\": \"ISO.CEILING\",\n\t\"_xlfn.ISOWEEKNUM\": \"ISOWEEKNUM\",\n\t\"_xlfn.LOGNORM.DIST\": \"LOGNORM.DIST\",\n\t\"_xlfn.LOGNORM.INV\": \"LOGNORM.INV\",\n\t\"_xlfn.MODE.MULT\": \"MODE.MULT\",\n\t\"_xlfn.MODE.SNGL\": \"MODE.SNGL\",\n\t\"_xlfn.MUNIT\": \"MUNIT\",\n\t\"_xlfn.NEGBINOM.DIST\": \"NEGBINOM.DIST\",\n\t\"_xlfn.NETWORKDAYS.INTL\": \"NETWORKDAYS.INTL\",\n\t\"_xlfn.NIGBINOM\": \"NIGBINOM\",\n\t\"_xlfn.NORM.DIST\": \"NORM.DIST\",\n\t\"_xlfn.NORM.INV\": \"NORM.INV\",\n\t\"_xlfn.NORM.S.DIST\": \"NORM.S.DIST\",\n\t\"_xlfn.NORM.S.INV\": \"NORM.S.INV\",\n\t\"_xlfn.NUMBERVALUE\": \"NUMBERVALUE\",\n\t\"_xlfn.PDURATION\": \"PDURATION\",\n\t\"_xlfn.PERCENTILE.EXC\": \"PERCENTILE.EXC\",\n\t\"_xlfn.PERCENTILE.INC\": \"PERCENTILE.INC\",\n\t\"_xlfn.PERCENTRANK.EXC\": \"PERCENTRANK.EXC\",\n\t\"_xlfn.PERCENTRANK.INC\": \"PERCENTRANK.INC\",\n\t\"_xlfn.PERMUTATIONA\": \"PERMUTATIONA\",\n\t\"_xlfn.PHI\": \"PHI\",\n\t\"_xlfn.POISSON.DIST\": \"POISSON.DIST\",\n\t\"_xlfn.QUARTILE.EXC\": \"QUARTILE.EXC\",\n\t\"_xlfn.QUARTILE.INC\": \"QUARTILE.INC\",\n\t\"_xlfn.QUERYSTRING\": \"QUERYSTRING\",\n\t\"_xlfn.RANK.AVG\": \"RANK.AVG\",\n\t\"_xlfn.RANK.EQ\": \"RANK.EQ\",\n\t\"_xlfn.RRI\": \"RRI\",\n\t\"_xlfn.SEC\": \"SEC\",\n\t\"_xlfn.SECH\": \"SECH\",\n\t\"_xlfn.SHEET\": \"SHEET\",\n\t\"_xlfn.SHEETS\": \"SHEETS\",\n\t\"_xlfn.SKEW.P\": \"SKEW.P\",\n\t\"_xlfn.STDEV.P\": \"STDEV.P\",\n\t\"_xlfn.STDEV.S\": \"STDEV.S\",\n\t\"_xlfn.SUMIFS\": \"SUMIFS\",\n\t\"_xlfn.T.DIST\": \"T.DIST\",\n\t\"_xlfn.T.DIST.2T\": \"T.DIST.2T\",\n\t\"_xlfn.T.DIST.RT\": \"T.DIST.RT\",\n\t\"_xlfn.T.INV\": \"T.INV\",\n\t\"_xlfn.T.INV.2T\": \"T.INV.2T\",\n\t\"_xlfn.T.TEST\": \"T.TEST\",\n\t\"_xlfn.UNICHAR\": \"UNICHAR\",\n\t\"_xlfn.UNICODE\": \"UNICODE\",\n\t\"_xlfn.VAR.P\": \"VAR.P\",\n\t\"_xlfn.VAR.S\": \"VAR.S\",\n\t\"_xlfn.WEBSERVICE\": \"WEBSERVICE\",\n\t\"_xlfn.WEIBULL.DIST\": \"WEIBULL.DIST\",\n\t\"_xlfn.WORKDAY.INTL\": \"WORKDAY.INTL\",\n\t\"_xlfn.XOR\": \"XOR\",\n\t\"_xlfn.Z.TEST\": \"Z.TEST\"\n};\n\nvar strs = {}; // shared strings\nvar _ssfopts = {}; // spreadsheet formatting options\n\nRELS.WS = \"http://schemas.openxmlformats.org/officeDocument/2006/relationships/worksheet\";\n\nfunction get_sst_id(sst, str) {\n\tfor(var i = 0, len = sst.length; i < len; ++i) if(sst[i].t === str) { sst.Count ++; return i; }\n\tsst[len] = {t:str}; sst.Count ++; sst.Unique ++; return len;\n}\n\nfunction get_cell_style(styles, cell, opts) {\n\tvar z = opts.revssf[cell.z != null ? cell.z : \"General\"];\n\tfor(var i = 0, len = styles.length; i != len; ++i) if(styles[i].numFmtId === z) return i;\n\tstyles[len] = {\n\t\tnumFmtId:z,\n\t\tfontId:0,\n\t\tfillId:0,\n\t\tborderId:0,\n\t\txfId:0,\n\t\tapplyNumberFormat:1\n\t};\n\treturn len;\n}\n\nfunction safe_format(p, fmtid, fillid, opts) {\n\ttry {\n\t\tif(p.t === 'e') p.w = p.w || BErr[p.v];\n\t\telse if(fmtid === 0) {\n\t\t\tif(p.t === 'n') {\n\t\t\t\tif((p.v|0) === p.v) p.w = SSF._general_int(p.v,_ssfopts);\n\t\t\t\telse p.w = SSF._general_num(p.v,_ssfopts);\n\t\t\t}\n\t\t\telse if(p.t === 'd') {\n\t\t\t\tvar dd = datenum(p.v);\n\t\t\t\tif((dd|0) === dd) p.w = SSF._general_int(dd,_ssfopts);\n\t\t\t\telse p.w = SSF._general_num(dd,_ssfopts);\n\t\t\t}\n\t\t\telse if(p.v === undefined) return \"\";\n\t\t\telse p.w = SSF._general(p.v,_ssfopts);\n\t\t}\n\t\telse if(p.t === 'd') p.w = SSF.format(fmtid,datenum(p.v),_ssfopts);\n\t\telse p.w = SSF.format(fmtid,p.v,_ssfopts);\n\t\tif(opts.cellNF) p.z = SSF._table[fmtid];\n\t} catch(e) { if(opts.WTF) throw e; }\n\tif(fillid) try {\n\t\tp.s = styles.Fills[fillid];\n\t\tif (p.s.fgColor && p.s.fgColor.theme) {\n\t\t\tp.s.fgColor.rgb = rgb_tint(themes.themeElements.clrScheme[p.s.fgColor.theme].rgb, p.s.fgColor.tint || 0);\n\t\t\tif(opts.WTF) p.s.fgColor.raw_rgb = themes.themeElements.clrScheme[p.s.fgColor.theme].rgb;\n\t\t}\n\t\tif (p.s.bgColor && p.s.bgColor.theme) {\n\t\t\tp.s.bgColor.rgb = rgb_tint(themes.themeElements.clrScheme[p.s.bgColor.theme].rgb, p.s.bgColor.tint || 0);\n\t\t\tif(opts.WTF) p.s.bgColor.raw_rgb = themes.themeElements.clrScheme[p.s.bgColor.theme].rgb;\n\t\t}\n\t} catch(e) { if(opts.WTF) throw e; }\n}\nfunction parse_ws_xml_dim(ws, s) {\n\tvar d = safe_decode_range(s);\n\tif(d.s.r<=d.e.r && d.s.c<=d.e.c && d.s.r>=0 && d.s.c>=0) ws[\"!ref\"] = encode_range(d);\n}\nvar mergecregex = /<mergeCell ref=\"[A-Z0-9:]+\"\\s*\\/>/g;\nvar sheetdataregex = /<(?:\\w+:)?sheetData>([^\\u2603]*)<\\/(?:\\w+:)?sheetData>/;\nvar hlinkregex = /<hyperlink[^>]*\\/>/g;\nvar dimregex = /\"(\\w*:\\w*)\"/;\nvar colregex = /<col[^>]*\\/>/g;\n/* 18.3 Worksheets */\nfunction parse_ws_xml(data, opts, rels) {\n\tif(!data) return data;\n\t/* 18.3.1.99 worksheet CT_Worksheet */\n\tvar s = {};\n\n\t/* 18.3.1.35 dimension CT_SheetDimension ? */\n\tvar ridx = data.indexOf(\"<dimension\");\n\tif(ridx > 0) {\n\t\tvar ref = data.substr(ridx,50).match(dimregex);\n\t\tif(ref != null) parse_ws_xml_dim(s, ref[1]);\n\t}\n\n\t/* 18.3.1.55 mergeCells CT_MergeCells */\n\tvar mergecells = [];\n\tif(data.indexOf(\"</mergeCells>\")!==-1) {\n\t\tvar merges = data.match(mergecregex);\n\t\tfor(ridx = 0; ridx != merges.length; ++ridx)\n\t\t\tmergecells[ridx] = safe_decode_range(merges[ridx].substr(merges[ridx].indexOf(\"\\\"\")+1));\n\t}\n\n\t/* 18.3.1.17 cols CT_Cols */\n\tvar columns = [];\n\tif(opts.cellStyles && data.indexOf(\"</cols>\")!==-1) {\n\t\t/* 18.3.1.13 col CT_Col */\n\t\tvar cols = data.match(colregex);\n\t\tparse_ws_xml_cols(columns, cols);\n\t}\n\n\tvar refguess = {s: {r:1000000, c:1000000}, e: {r:0, c:0} };\n\n\t/* 18.3.1.80 sheetData CT_SheetData ? */\n\tvar mtch=data.match(sheetdataregex);\n\tif(mtch) parse_ws_xml_data(mtch[1], s, opts, refguess);\n\n\t/* 18.3.1.48 hyperlinks CT_Hyperlinks */\n\tif(data.indexOf(\"</hyperlinks>\")!==-1) parse_ws_xml_hlinks(s, data.match(hlinkregex), rels);\n\n\tif(!s[\"!ref\"] && refguess.e.c >= refguess.s.c && refguess.e.r >= refguess.s.r) s[\"!ref\"] = encode_range(refguess);\n\tif(opts.sheetRows > 0 && s[\"!ref\"]) {\n\t\tvar tmpref = safe_decode_range(s[\"!ref\"]);\n\t\tif(opts.sheetRows < +tmpref.e.r) {\n\t\t\ttmpref.e.r = opts.sheetRows - 1;\n\t\t\tif(tmpref.e.r > refguess.e.r) tmpref.e.r = refguess.e.r;\n\t\t\tif(tmpref.e.r < tmpref.s.r) tmpref.s.r = tmpref.e.r;\n\t\t\tif(tmpref.e.c > refguess.e.c) tmpref.e.c = refguess.e.c;\n\t\t\tif(tmpref.e.c < tmpref.s.c) tmpref.s.c = tmpref.e.c;\n\t\t\ts[\"!fullref\"] = s[\"!ref\"];\n\t\t\ts[\"!ref\"] = encode_range(tmpref);\n\t\t}\n\t}\n\tif(mergecells.length > 0) s[\"!merges\"] = mergecells;\n\tif(columns.length > 0) s[\"!cols\"] = columns;\n\treturn s;\n}\n\nfunction write_ws_xml_merges(merges) {\n\tif(merges.length == 0) return \"\";\n\tvar o = '<mergeCells count=\"' + merges.length + '\">';\n\tfor(var i = 0; i != merges.length; ++i) o += '<mergeCell ref=\"' + encode_range(merges[i]) + '\"/>';\n\treturn o + '</mergeCells>';\n}\n\nfunction parse_ws_xml_hlinks(s, data, rels) {\n\tfor(var i = 0; i != data.length; ++i) {\n\t\tvar val = parsexmltag(data[i], true);\n\t\tif(!val.ref) return;\n\t\tvar rel = rels ? rels['!id'][val.id] : null;\n\t\tif(rel) {\n\t\t\tval.Target = rel.Target;\n\t\t\tif(val.location) val.Target += \"#\"+val.location;\n\t\t\tval.Rel = rel;\n\t\t} else {\n\t\t\tval.Target = val.location;\n\t\t\trel = {Target: val.location, TargetMode: 'Internal'};\n\t\t\tval.Rel = rel;\n\t\t}\n\t\tvar rng = safe_decode_range(val.ref);\n\t\tfor(var R=rng.s.r;R<=rng.e.r;++R) for(var C=rng.s.c;C<=rng.e.c;++C) {\n\t\t\tvar addr = encode_cell({c:C,r:R});\n\t\t\tif(!s[addr]) s[addr] = {t:\"stub\",v:undefined};\n\t\t\ts[addr].l = val;\n\t\t}\n\t}\n}\n\nfunction parse_ws_xml_cols(columns, cols) {\n\tvar seencol = false;\n\tfor(var coli = 0; coli != cols.length; ++coli) {\n\t\tvar coll = parsexmltag(cols[coli], true);\n\t\tvar colm=parseInt(coll.min, 10)-1, colM=parseInt(coll.max,10)-1;\n\t\tdelete coll.min; delete coll.max;\n\t\tif(!seencol && coll.width) { seencol = true; find_mdw(+coll.width, coll); }\n\t\tif(coll.width) {\n\t\t\tcoll.wpx = width2px(+coll.width);\n\t\t\tcoll.wch = px2char(coll.wpx);\n\t\t\tcoll.MDW = MDW;\n\t\t}\n\t\twhile(colm <= colM) columns[colm++] = coll;\n\t}\n}\n\nfunction write_ws_xml_cols(ws, cols) {\n\tvar o = [\"<cols>\"], col, width;\n\tfor(var i = 0; i != cols.length; ++i) {\n\t\tif(!(col = cols[i])) continue;\n\t\tvar p = {min:i+1,max:i+1};\n\t\t/* wch (chars), wpx (pixels) */\n\t\twidth = -1;\n\t\tif(col.wpx) width = px2char(col.wpx);\n\t\telse if(col.wch) width = col.wch;\n\t\tif(width > -1) { p.width = char2width(width); p.customWidth= 1; }\n\t\to[o.length] = (writextag('col', null, p));\n\t}\n\to[o.length] = \"</cols>\";\n\treturn o.join(\"\");\n}\n\nfunction write_ws_xml_cell(cell, ref, ws, opts, idx, wb) {\n\tif(cell.v === undefined) return \"\";\n\tvar vv = \"\";\n\tvar oldt = cell.t, oldv = cell.v;\n\tswitch(cell.t) {\n\t\tcase 'b': vv = cell.v ? \"1\" : \"0\"; break;\n\t\tcase 'n': vv = ''+cell.v; break;\n\t\tcase 'e': vv = BErr[cell.v]; break;\n\t\tcase 'd':\n\t\t\tif(opts.cellDates) vv = new Date(cell.v).toISOString();\n\t\t\telse {\n\t\t\t\tcell.t = 'n';\n\t\t\t\tvv = ''+(cell.v = datenum(cell.v));\n\t\t\t\tif(typeof cell.z === 'undefined') cell.z = SSF._table[14];\n\t\t\t}\n\t\t\tbreak;\n\t\tdefault: vv = cell.v; break;\n\t}\n\tvar v = writetag('v', escapexml(vv)), o = {r:ref};\n\t/* TODO: cell style */\n\tvar os = get_cell_style(opts.cellXfs, cell, opts);\n\tif(os !== 0) o.s = os;\n\tswitch(cell.t) {\n\t\tcase 'n': break;\n\t\tcase 'd': o.t = \"d\"; break;\n\t\tcase 'b': o.t = \"b\"; break;\n\t\tcase 'e': o.t = \"e\"; break;\n\t\tdefault:\n\t\t\tif(opts.bookSST) {\n\t\t\t\tv = writetag('v', ''+get_sst_id(opts.Strings, cell.v));\n\t\t\t\to.t = \"s\"; break;\n\t\t\t}\n\t\t\to.t = \"str\"; break;\n\t}\n\tif(cell.t != oldt) { cell.t = oldt; cell.v = oldv; }\n\treturn writextag('c', v, o);\n}\n\nvar parse_ws_xml_data = (function parse_ws_xml_data_factory() {\n\tvar cellregex = /<(?:\\w+:)?c[ >]/, rowregex = /<\\/(?:\\w+:)?row>/;\n\tvar rregex = /r=[\"']([^\"']*)[\"']/, isregex = /<is>([\\S\\s]*?)<\\/is>/;\n\tvar match_v = matchtag(\"v\"), match_f = matchtag(\"f\");\n\nreturn function parse_ws_xml_data(sdata, s, opts, guess) {\n\tvar ri = 0, x = \"\", cells = [], cref = [], idx = 0, i=0, cc=0, d=\"\", p;\n\tvar tag, tagr = 0, tagc = 0;\n\tvar sstr;\n\tvar fmtid = 0, fillid = 0, do_format = Array.isArray(styles.CellXf), cf;\n\tfor(var marr = sdata.split(rowregex), mt = 0, marrlen = marr.length; mt != marrlen; ++mt) {\n\t\tx = marr[mt].trim();\n\t\tvar xlen = x.length;\n\t\tif(xlen === 0) continue;\n\n\t\t/* 18.3.1.73 row CT_Row */\n\t\tfor(ri = 0; ri < xlen; ++ri) if(x.charCodeAt(ri) === 62) break; ++ri;\n\t\ttag = parsexmltag(x.substr(0,ri), true);\n\t\t/* SpreadSheetGear uses implicit r/c */\n\t\ttagr = typeof tag.r !== 'undefined' ? parseInt(tag.r, 10) : tagr+1; tagc = -1;\n\t\tif(opts.sheetRows && opts.sheetRows < tagr) continue;\n\t\tif(guess.s.r > tagr - 1) guess.s.r = tagr - 1;\n\t\tif(guess.e.r < tagr - 1) guess.e.r = tagr - 1;\n\n\t\t/* 18.3.1.4 c CT_Cell */\n\t\tcells = x.substr(ri).split(cellregex);\n\t\tfor(ri = typeof tag.r === 'undefined' ? 0 : 1; ri != cells.length; ++ri) {\n\t\t\tx = cells[ri].trim();\n\t\t\tif(x.length === 0) continue;\n\t\t\tcref = x.match(rregex); idx = ri; i=0; cc=0;\n\t\t\tx = \"<c \" + (x.substr(0,1)==\"<\"?\">\":\"\") + x;\n\t\t\tif(cref !== null && cref.length === 2) {\n\t\t\t\tidx = 0; d=cref[1];\n\t\t\t\tfor(i=0; i != d.length; ++i) {\n\t\t\t\t\tif((cc=d.charCodeAt(i)-64) < 1 || cc > 26) break;\n\t\t\t\t\tidx = 26*idx + cc;\n\t\t\t\t}\n\t\t\t\t--idx;\n\t\t\t\ttagc = idx;\n\t\t\t} else ++tagc;\n\t\t\tfor(i = 0; i != x.length; ++i) if(x.charCodeAt(i) === 62) break; ++i;\n\t\t\ttag = parsexmltag(x.substr(0,i), true);\n\t\t\tif(!tag.r) tag.r = utils.encode_cell({r:tagr-1, c:tagc});\n\t\t\td = x.substr(i);\n\t\t\tp = {t:\"\"};\n\n\t\t\tif((cref=d.match(match_v))!== null && cref[1] !== '') p.v=unescapexml(cref[1]);\n\t\t\tif(opts.cellFormula && (cref=d.match(match_f))!== null) p.f=unescapexml(cref[1]);\n\n\t\t\t/* SCHEMA IS ACTUALLY INCORRECT HERE.  IF A CELL HAS NO T, EMIT \"\" */\n\t\t\tif(tag.t === undefined && p.v === undefined) {\n\t\t\t\tif(!opts.sheetStubs) continue;\n\t\t\t\tp.t = \"stub\";\n\t\t\t}\n\t\t\telse p.t = tag.t || \"n\";\n\t\t\tif(guess.s.c > idx) guess.s.c = idx;\n\t\t\tif(guess.e.c < idx) guess.e.c = idx;\n\t\t\t/* 18.18.11 t ST_CellType */\n\t\t\tswitch(p.t) {\n\t\t\t\tcase 'n': p.v = parseFloat(p.v); break;\n\t\t\t\tcase 's':\n\t\t\t\t\tsstr = strs[parseInt(p.v, 10)];\n\t\t\t\t\tp.v = sstr.t;\n\t\t\t\t\tp.r = sstr.r;\n\t\t\t\t\tif(opts.cellHTML) p.h = sstr.h;\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'str':\n\t\t\t\t\tp.t = \"s\";\n\t\t\t\t\tp.v = (p.v!=null) ? utf8read(p.v) : '';\n\t\t\t\t\tif(opts.cellHTML) p.h = p.v;\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'inlineStr':\n\t\t\t\t\tcref = d.match(isregex);\n\t\t\t\t\tp.t = 's';\n\t\t\t\t\tif(cref !== null) { sstr = parse_si(cref[1]); p.v = sstr.t; } else p.v = \"\";\n\t\t\t\t\tbreak; // inline string\n\t\t\t\tcase 'b': p.v = parsexmlbool(p.v); break;\n\t\t\t\tcase 'd':\n\t\t\t\t\tif(!opts.cellDates) { p.v = datenum(p.v); p.t = 'n'; }\n\t\t\t\t\tbreak;\n\t\t\t\t/* error string in .v, number in .v */\n\t\t\t\tcase 'e': p.w = p.v; p.v = RBErr[p.v]; break;\n\t\t\t}\n\t\t\t/* formatting */\n\t\t\tfmtid = fillid = 0;\n\t\t\tif(do_format && tag.s !== undefined) {\n\t\t\t\tcf = styles.CellXf[tag.s];\n\t\t\t\tif(cf != null) {\n\t\t\t\t\tif(cf.numFmtId != null) fmtid = cf.numFmtId;\n\t\t\t\t\tif(opts.cellStyles && cf.fillId != null) fillid = cf.fillId;\n\t\t\t\t}\n\t\t\t}\n\t\t\tsafe_format(p, fmtid, fillid, opts);\n\t\t\ts[tag.r] = p;\n\t\t}\n\t}\n}; })();\n\nfunction write_ws_xml_data(ws, opts, idx, wb) {\n\tvar o = [], r = [], range = safe_decode_range(ws['!ref']), cell, ref, rr = \"\", cols = [], R, C;\n\tfor(C = range.s.c; C <= range.e.c; ++C) cols[C] = encode_col(C);\n\tfor(R = range.s.r; R <= range.e.r; ++R) {\n\t\tr = [];\n\t\trr = encode_row(R);\n\t\tfor(C = range.s.c; C <= range.e.c; ++C) {\n\t\t\tref = cols[C] + rr;\n\t\t\tif(ws[ref] === undefined) continue;\n\t\t\tif((cell = write_ws_xml_cell(ws[ref], ref, ws, opts, idx, wb)) != null) r.push(cell);\n\t\t}\n\t\tif(r.length > 0) o[o.length] = (writextag('row', r.join(\"\"), {r:rr}));\n\t}\n\treturn o.join(\"\");\n}\n\nvar WS_XML_ROOT = writextag('worksheet', null, {\n\t'xmlns': XMLNS.main[0],\n\t'xmlns:r': XMLNS.r\n});\n\nfunction write_ws_xml(idx, opts, wb) {\n\tvar o = [XML_HEADER, WS_XML_ROOT];\n\tvar s = wb.SheetNames[idx], sidx = 0, rdata = \"\";\n\tvar ws = wb.Sheets[s];\n\tif(ws === undefined) ws = {};\n\tvar ref = ws['!ref']; if(ref === undefined) ref = 'A1';\n\to[o.length] = (writextag('dimension', null, {'ref': ref}));\n\n\tif(ws['!cols'] !== undefined && ws['!cols'].length > 0) o[o.length] = (write_ws_xml_cols(ws, ws['!cols']));\n\to[sidx = o.length] = '<sheetData/>';\n\tif(ws['!ref'] !== undefined) {\n\t\trdata = write_ws_xml_data(ws, opts, idx, wb);\n\t\tif(rdata.length > 0) o[o.length] = (rdata);\n\t}\n\tif(o.length>sidx+1) { o[o.length] = ('</sheetData>'); o[sidx]=o[sidx].replace(\"/>\",\">\"); }\n\n\tif(ws['!merges'] !== undefined && ws['!merges'].length > 0) o[o.length] = (write_ws_xml_merges(ws['!merges']));\n\n\tif(o.length>2) { o[o.length] = ('</worksheet>'); o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n\n/* [MS-XLSB] 2.4.718 BrtRowHdr */\nfunction parse_BrtRowHdr(data, length) {\n\tvar z = [];\n\tz.r = data.read_shift(4);\n\tdata.l += length-4;\n\treturn z;\n}\n\n/* [MS-XLSB] 2.4.812 BrtWsDim */\nvar parse_BrtWsDim = parse_UncheckedRfX;\nvar write_BrtWsDim = write_UncheckedRfX;\n\n/* [MS-XLSB] 2.4.815 BrtWsProp */\nfunction parse_BrtWsProp(data, length) {\n\tvar z = {};\n\t/* TODO: pull flags */\n\tdata.l += 19;\n\tz.name = parse_XLSBCodeName(data, length - 19);\n\treturn z;\n}\n\n/* [MS-XLSB] 2.4.303 BrtCellBlank */\nfunction parse_BrtCellBlank(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\treturn [cell];\n}\nfunction write_BrtCellBlank(cell, val, o) {\n\tif(o == null) o = new_buf(8);\n\treturn write_XLSBCell(val, o);\n}\n\n\n/* [MS-XLSB] 2.4.304 BrtCellBool */\nfunction parse_BrtCellBool(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar fBool = data.read_shift(1);\n\treturn [cell, fBool, 'b'];\n}\n\n/* [MS-XLSB] 2.4.305 BrtCellError */\nfunction parse_BrtCellError(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar fBool = data.read_shift(1);\n\treturn [cell, fBool, 'e'];\n}\n\n/* [MS-XLSB] 2.4.308 BrtCellIsst */\nfunction parse_BrtCellIsst(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar isst = data.read_shift(4);\n\treturn [cell, isst, 's'];\n}\n\n/* [MS-XLSB] 2.4.310 BrtCellReal */\nfunction parse_BrtCellReal(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = parse_Xnum(data);\n\treturn [cell, value, 'n'];\n}\n\n/* [MS-XLSB] 2.4.311 BrtCellRk */\nfunction parse_BrtCellRk(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = parse_RkNumber(data);\n\treturn [cell, value, 'n'];\n}\n\n/* [MS-XLSB] 2.4.314 BrtCellSt */\nfunction parse_BrtCellSt(data, length) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = parse_XLWideString(data);\n\treturn [cell, value, 'str'];\n}\n\n/* [MS-XLSB] 2.4.647 BrtFmlaBool */\nfunction parse_BrtFmlaBool(data, length, opts) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = data.read_shift(1);\n\tvar o = [cell, value, 'b'];\n\tif(opts.cellFormula) {\n\t\tvar formula = parse_XLSBCellParsedFormula(data, length-9);\n\t\to[3] = \"\"; /* TODO */\n\t}\n\telse data.l += length-9;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.4.648 BrtFmlaError */\nfunction parse_BrtFmlaError(data, length, opts) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = data.read_shift(1);\n\tvar o = [cell, value, 'e'];\n\tif(opts.cellFormula) {\n\t\tvar formula = parse_XLSBCellParsedFormula(data, length-9);\n\t\to[3] = \"\"; /* TODO */\n\t}\n\telse data.l += length-9;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.4.649 BrtFmlaNum */\nfunction parse_BrtFmlaNum(data, length, opts) {\n\tvar cell = parse_XLSBCell(data);\n\tvar value = parse_Xnum(data);\n\tvar o = [cell, value, 'n'];\n\tif(opts.cellFormula) {\n\t\tvar formula = parse_XLSBCellParsedFormula(data, length - 16);\n\t\to[3] = \"\"; /* TODO */\n\t}\n\telse data.l += length-16;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.4.650 BrtFmlaString */\nfunction parse_BrtFmlaString(data, length, opts) {\n\tvar start = data.l;\n\tvar cell = parse_XLSBCell(data);\n\tvar value = parse_XLWideString(data);\n\tvar o = [cell, value, 'str'];\n\tif(opts.cellFormula) {\n\t\tvar formula = parse_XLSBCellParsedFormula(data, start + length - data.l);\n\t}\n\telse data.l = start + length;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.4.676 BrtMergeCell */\nvar parse_BrtMergeCell = parse_UncheckedRfX;\n\n/* [MS-XLSB] 2.4.656 BrtHLink */\nfunction parse_BrtHLink(data, length, opts) {\n\tvar end = data.l + length;\n\tvar rfx = parse_UncheckedRfX(data, 16);\n\tvar relId = parse_XLNullableWideString(data);\n\tvar loc = parse_XLWideString(data);\n\tvar tooltip = parse_XLWideString(data);\n\tvar display = parse_XLWideString(data);\n\tdata.l = end;\n\treturn {rfx:rfx, relId:relId, loc:loc, tooltip:tooltip, display:display};\n}\n\n/* [MS-XLSB] 2.1.7.61 Worksheet */\nfunction parse_ws_bin(data, opts, rels) {\n\tif(!data) return data;\n\tif(!rels) rels = {'!id':{}};\n\tvar s = {};\n\n\tvar ref;\n\tvar refguess = {s: {r:1000000, c:1000000}, e: {r:0, c:0} };\n\n\tvar pass = false, end = false;\n\tvar row, p, cf, R, C, addr, sstr, rr;\n\tvar mergecells = [];\n\trecordhopper(data, function ws_parse(val, R) {\n\t\tif(end) return;\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtWsDim': ref = val; break;\n\t\t\tcase 'BrtRowHdr':\n\t\t\t\trow = val;\n\t\t\t\tif(opts.sheetRows && opts.sheetRows <= row.r) end=true;\n\t\t\t\trr = encode_row(row.r);\n\t\t\t\tbreak;\n\n\t\t\tcase 'BrtFmlaBool':\n\t\t\tcase 'BrtFmlaError':\n\t\t\tcase 'BrtFmlaNum':\n\t\t\tcase 'BrtFmlaString':\n\t\t\tcase 'BrtCellBool':\n\t\t\tcase 'BrtCellError':\n\t\t\tcase 'BrtCellIsst':\n\t\t\tcase 'BrtCellReal':\n\t\t\tcase 'BrtCellRk':\n\t\t\tcase 'BrtCellSt':\n\t\t\t\tp = {t:val[2]};\n\t\t\t\tswitch(val[2]) {\n\t\t\t\t\tcase 'n': p.v = val[1]; break;\n\t\t\t\t\tcase 's': sstr = strs[val[1]]; p.v = sstr.t; p.r = sstr.r; break;\n\t\t\t\t\tcase 'b': p.v = val[1] ? true : false; break;\n\t\t\t\t\tcase 'e': p.v = val[1]; p.w = BErr[p.v]; break;\n\t\t\t\t\tcase 'str': p.t = 's'; p.v = utf8read(val[1]); break;\n\t\t\t\t}\n\t\t\t\tif(opts.cellFormula && val.length > 3) p.f = val[3];\n\t\t\t\tif((cf = styles.CellXf[val[0].iStyleRef])) safe_format(p,cf.ifmt,null,opts);\n\t\t\t\ts[encode_col(C=val[0].c) + rr] = p;\n\t\t\t\tif(refguess.s.r > row.r) refguess.s.r = row.r;\n\t\t\t\tif(refguess.s.c > C) refguess.s.c = C;\n\t\t\t\tif(refguess.e.r < row.r) refguess.e.r = row.r;\n\t\t\t\tif(refguess.e.c < C) refguess.e.c = C;\n\t\t\t\tbreak;\n\n\t\t\tcase 'BrtCellBlank': if(!opts.sheetStubs) break;\n\t\t\t\tp = {t:'s',v:undefined};\n\t\t\t\ts[encode_col(C=val[0].c) + rr] = p;\n\t\t\t\tif(refguess.s.r > row.r) refguess.s.r = row.r;\n\t\t\t\tif(refguess.s.c > C) refguess.s.c = C;\n\t\t\t\tif(refguess.e.r < row.r) refguess.e.r = row.r;\n\t\t\t\tif(refguess.e.c < C) refguess.e.c = C;\n\t\t\t\tbreak;\n\n\t\t\t/* Merge Cells */\n\t\t\tcase 'BrtBeginMergeCells': break;\n\t\t\tcase 'BrtEndMergeCells': break;\n\t\t\tcase 'BrtMergeCell': mergecells.push(val); break;\n\n\t\t\tcase 'BrtHLink':\n\t\t\t\tvar rel = rels['!id'][val.relId];\n\t\t\t\tif(rel) {\n\t\t\t\t\tval.Target = rel.Target;\n\t\t\t\t\tif(val.loc) val.Target += \"#\"+val.loc;\n\t\t\t\t\tval.Rel = rel;\n\t\t\t\t}\n\t\t\t\tfor(R=val.rfx.s.r;R<=val.rfx.e.r;++R) for(C=val.rfx.s.c;C<=val.rfx.e.c;++C) {\n\t\t\t\t\taddr = encode_cell({c:C,r:R});\n\t\t\t\t\tif(!s[addr]) s[addr] = {t:'s',v:undefined};\n\t\t\t\t\ts[addr].l = val;\n\t\t\t\t}\n\t\t\t\tbreak;\n\n\t\t\tcase 'BrtArrFmla': break; // TODO\n\t\t\tcase 'BrtShrFmla': break; // TODO\n\t\t\tcase 'BrtBeginSheet': break;\n\t\t\tcase 'BrtWsProp': break; // TODO\n\t\t\tcase 'BrtSheetCalcProp': break; // TODO\n\t\t\tcase 'BrtBeginWsViews': break; // TODO\n\t\t\tcase 'BrtBeginWsView': break; // TODO\n\t\t\tcase 'BrtPane': break; // TODO\n\t\t\tcase 'BrtSel': break; // TODO\n\t\t\tcase 'BrtEndWsView': break; // TODO\n\t\t\tcase 'BrtEndWsViews': break; // TODO\n\t\t\tcase 'BrtACBegin': break; // TODO\n\t\t\tcase 'BrtRwDescent': break; // TODO\n\t\t\tcase 'BrtACEnd': break; // TODO\n\t\t\tcase 'BrtWsFmtInfoEx14': break; // TODO\n\t\t\tcase 'BrtWsFmtInfo': break; // TODO\n\t\t\tcase 'BrtBeginColInfos': break; // TODO\n\t\t\tcase 'BrtColInfo': break; // TODO\n\t\t\tcase 'BrtEndColInfos': break; // TODO\n\t\t\tcase 'BrtBeginSheetData': break; // TODO\n\t\t\tcase 'BrtEndSheetData': break; // TODO\n\t\t\tcase 'BrtSheetProtection': break; // TODO\n\t\t\tcase 'BrtPrintOptions': break; // TODO\n\t\t\tcase 'BrtMargins': break; // TODO\n\t\t\tcase 'BrtPageSetup': break; // TODO\n\t\t\tcase 'BrtFRTBegin': pass = true; break;\n\t\t\tcase 'BrtFRTEnd': pass = false; break;\n\t\t\tcase 'BrtEndSheet': break; // TODO\n\t\t\tcase 'BrtDrawing': break; // TODO\n\t\t\tcase 'BrtLegacyDrawing': break; // TODO\n\t\t\tcase 'BrtLegacyDrawingHF': break; // TODO\n\t\t\tcase 'BrtPhoneticInfo': break; // TODO\n\t\t\tcase 'BrtBeginHeaderFooter': break; // TODO\n\t\t\tcase 'BrtEndHeaderFooter': break; // TODO\n\t\t\tcase 'BrtBrk': break; // TODO\n\t\t\tcase 'BrtBeginRwBrk': break; // TODO\n\t\t\tcase 'BrtEndRwBrk': break; // TODO\n\t\t\tcase 'BrtBeginColBrk': break; // TODO\n\t\t\tcase 'BrtEndColBrk': break; // TODO\n\t\t\tcase 'BrtBeginUserShViews': break; // TODO\n\t\t\tcase 'BrtBeginUserShView': break; // TODO\n\t\t\tcase 'BrtEndUserShView': break; // TODO\n\t\t\tcase 'BrtEndUserShViews': break; // TODO\n\t\t\tcase 'BrtBkHim': break; // TODO\n\t\t\tcase 'BrtBeginOleObjects': break; // TODO\n\t\t\tcase 'BrtOleObject': break; // TODO\n\t\t\tcase 'BrtEndOleObjects': break; // TODO\n\t\t\tcase 'BrtBeginListParts': break; // TODO\n\t\t\tcase 'BrtListPart': break; // TODO\n\t\t\tcase 'BrtEndListParts': break; // TODO\n\t\t\tcase 'BrtBeginSortState': break; // TODO\n\t\t\tcase 'BrtBeginSortCond': break; // TODO\n\t\t\tcase 'BrtEndSortCond': break; // TODO\n\t\t\tcase 'BrtEndSortState': break; // TODO\n\t\t\tcase 'BrtBeginConditionalFormatting': break; // TODO\n\t\t\tcase 'BrtEndConditionalFormatting': break; // TODO\n\t\t\tcase 'BrtBeginCFRule': break; // TODO\n\t\t\tcase 'BrtEndCFRule': break; // TODO\n\t\t\tcase 'BrtBeginDVals': break; // TODO\n\t\t\tcase 'BrtDVal': break; // TODO\n\t\t\tcase 'BrtEndDVals': break; // TODO\n\t\t\tcase 'BrtRangeProtection': break; // TODO\n\t\t\tcase 'BrtBeginDCon': break; // TODO\n\t\t\tcase 'BrtEndDCon': break; // TODO\n\t\t\tcase 'BrtBeginDRefs': break;\n\t\t\tcase 'BrtDRef': break;\n\t\t\tcase 'BrtEndDRefs': break;\n\n\t\t\t/* ActiveX */\n\t\t\tcase 'BrtBeginActiveXControls': break;\n\t\t\tcase 'BrtActiveX': break;\n\t\t\tcase 'BrtEndActiveXControls': break;\n\n\t\t\t/* AutoFilter */\n\t\t\tcase 'BrtBeginAFilter': break;\n\t\t\tcase 'BrtEndAFilter': break;\n\t\t\tcase 'BrtBeginFilterColumn': break;\n\t\t\tcase 'BrtBeginFilters': break;\n\t\t\tcase 'BrtFilter': break;\n\t\t\tcase 'BrtEndFilters': break;\n\t\t\tcase 'BrtEndFilterColumn': break;\n\t\t\tcase 'BrtDynamicFilter': break;\n\t\t\tcase 'BrtTop10Filter': break;\n\t\t\tcase 'BrtBeginCustomFilters': break;\n\t\t\tcase 'BrtCustomFilter': break;\n\t\t\tcase 'BrtEndCustomFilters': break;\n\n\t\t\t/* Smart Tags */\n\t\t\tcase 'BrtBeginSmartTags': break;\n\t\t\tcase 'BrtBeginCellSmartTags': break;\n\t\t\tcase 'BrtBeginCellSmartTag': break;\n\t\t\tcase 'BrtCellSmartTagProperty': break;\n\t\t\tcase 'BrtEndCellSmartTag': break;\n\t\t\tcase 'BrtEndCellSmartTags': break;\n\t\t\tcase 'BrtEndSmartTags': break;\n\n\t\t\t/* Cell Watch */\n\t\t\tcase 'BrtBeginCellWatches': break;\n\t\t\tcase 'BrtCellWatch': break;\n\t\t\tcase 'BrtEndCellWatches': break;\n\n\t\t\t/* Table */\n\t\t\tcase 'BrtTable': break;\n\n\t\t\t/* Ignore Cell Errors */\n\t\t\tcase 'BrtBeginCellIgnoreECs': break;\n\t\t\tcase 'BrtCellIgnoreEC': break;\n\t\t\tcase 'BrtEndCellIgnoreECs': break;\n\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + R.n);\n\t\t}\n\t}, opts);\n\tif(!s[\"!ref\"] && (refguess.s.r < 1000000 || ref.e.r > 0 || ref.e.c > 0 || ref.s.r > 0 || ref.s.c > 0)) s[\"!ref\"] = encode_range(ref);\n\tif(opts.sheetRows && s[\"!ref\"]) {\n\t\tvar tmpref = safe_decode_range(s[\"!ref\"]);\n\t\tif(opts.sheetRows < +tmpref.e.r) {\n\t\t\ttmpref.e.r = opts.sheetRows - 1;\n\t\t\tif(tmpref.e.r > refguess.e.r) tmpref.e.r = refguess.e.r;\n\t\t\tif(tmpref.e.r < tmpref.s.r) tmpref.s.r = tmpref.e.r;\n\t\t\tif(tmpref.e.c > refguess.e.c) tmpref.e.c = refguess.e.c;\n\t\t\tif(tmpref.e.c < tmpref.s.c) tmpref.s.c = tmpref.e.c;\n\t\t\ts[\"!fullref\"] = s[\"!ref\"];\n\t\t\ts[\"!ref\"] = encode_range(tmpref);\n\t\t}\n\t}\n\tif(mergecells.length > 0) s[\"!merges\"] = mergecells;\n\treturn s;\n}\n\n/* TODO: something useful -- this is a stub */\nfunction write_ws_bin_cell(ba, cell, R, C, opts) {\n\tif(cell.v === undefined) return \"\";\n\tvar vv = \"\";\n\tswitch(cell.t) {\n\t\tcase 'b': vv = cell.v ? \"1\" : \"0\"; break;\n\t\tcase 'n': case 'e': vv = ''+cell.v; break;\n\t\tdefault: vv = cell.v; break;\n\t}\n\tvar o = {r:R, c:C};\n\t/* TODO: cell style */\n\to.s = get_cell_style(opts.cellXfs, cell, opts);\n\tswitch(cell.t) {\n\t\tcase 's': case 'str':\n\t\t\tif(opts.bookSST) {\n\t\t\t\tvv = get_sst_id(opts.Strings, cell.v);\n\t\t\t\to.t = \"s\"; break;\n\t\t\t}\n\t\t\to.t = \"str\"; break;\n\t\tcase 'n': break;\n\t\tcase 'b': o.t = \"b\"; break;\n\t\tcase 'e': o.t = \"e\"; break;\n\t}\n\twrite_record(ba, \"BrtCellBlank\", write_BrtCellBlank(cell, o));\n}\n\nfunction write_CELLTABLE(ba, ws, idx, opts, wb) {\n\tvar range = safe_decode_range(ws['!ref'] || \"A1\"), ref, rr = \"\", cols = [];\n\twrite_record(ba, 'BrtBeginSheetData');\n\tfor(var R = range.s.r; R <= range.e.r; ++R) {\n\t\trr = encode_row(R);\n\t\t/* [ACCELLTABLE] */\n\t\t/* BrtRowHdr */\n\t\tfor(var C = range.s.c; C <= range.e.c; ++C) {\n\t\t\t/* *16384CELL */\n\t\t\tif(R === range.s.r) cols[C] = encode_col(C);\n\t\t\tref = cols[C] + rr;\n\t\t\tif(!ws[ref]) continue;\n\t\t\t/* write cell */\n\t\t\twrite_ws_bin_cell(ba, ws[ref], R, C, opts);\n\t\t}\n\t}\n\twrite_record(ba, 'BrtEndSheetData');\n}\n\nfunction write_ws_bin(idx, opts, wb) {\n\tvar ba = buf_array();\n\tvar s = wb.SheetNames[idx], ws = wb.Sheets[s] || {};\n\tvar r = safe_decode_range(ws['!ref'] || \"A1\");\n\twrite_record(ba, \"BrtBeginSheet\");\n\t/* [BrtWsProp] */\n\twrite_record(ba, \"BrtWsDim\", write_BrtWsDim(r));\n\t/* [WSVIEWS2] */\n\t/* [WSFMTINFO] */\n\t/* *COLINFOS */\n\twrite_CELLTABLE(ba, ws, idx, opts, wb);\n\t/* [BrtSheetCalcProp] */\n\t/* [[BrtSheetProtectionIso] BrtSheetProtection] */\n\t/* *([BrtRangeProtectionIso] BrtRangeProtection) */\n\t/* [SCENMAN] */\n\t/* [AUTOFILTER] */\n\t/* [SORTSTATE] */\n\t/* [DCON] */\n\t/* [USERSHVIEWS] */\n\t/* [MERGECELLS] */\n\t/* [BrtPhoneticInfo] */\n\t/* *CONDITIONALFORMATTING */\n\t/* [DVALS] */\n\t/* *BrtHLink */\n\t/* [BrtPrintOptions] */\n\t/* [BrtMargins] */\n\t/* [BrtPageSetup] */\n\t/* [HEADERFOOTER] */\n\t/* [RWBRK] */\n\t/* [COLBRK] */\n\t/* *BrtBigName */\n\t/* [CELLWATCHES] */\n\t/* [IGNOREECS] */\n\t/* [SMARTTAGS] */\n\t/* [BrtDrawing] */\n\t/* [BrtLegacyDrawing] */\n\t/* [BrtLegacyDrawingHF] */\n\t/* [BrtBkHim] */\n\t/* [OLEOBJECTS] */\n\t/* [ACTIVEXCONTROLS] */\n\t/* [WEBPUBITEMS] */\n\t/* [LISTPARTS] */\n\t/* FRTWORKSHEET */\n\twrite_record(ba, \"BrtEndSheet\");\n\treturn ba.end();\n}\n/* 18.2.28 (CT_WorkbookProtection) Defaults */\nvar WBPropsDef = [\n\t['allowRefreshQuery', '0'],\n\t['autoCompressPictures', '1'],\n\t['backupFile', '0'],\n\t['checkCompatibility', '0'],\n\t['codeName', ''],\n\t['date1904', '0'],\n\t['dateCompatibility', '1'],\n\t//['defaultThemeVersion', '0'],\n\t['filterPrivacy', '0'],\n\t['hidePivotFieldList', '0'],\n\t['promptedSolutions', '0'],\n\t['publishItems', '0'],\n\t['refreshAllConnections', false],\n\t['saveExternalLinkValues', '1'],\n\t['showBorderUnselectedTables', '1'],\n\t['showInkAnnotation', '1'],\n\t['showObjects', 'all'],\n\t['showPivotChartFilter', '0']\n\t//['updateLinks', 'userSet']\n];\n\n/* 18.2.30 (CT_BookView) Defaults */\nvar WBViewDef = [\n\t['activeTab', '0'],\n\t['autoFilterDateGrouping', '1'],\n\t['firstSheet', '0'],\n\t['minimized', '0'],\n\t['showHorizontalScroll', '1'],\n\t['showSheetTabs', '1'],\n\t['showVerticalScroll', '1'],\n\t['tabRatio', '600'],\n\t['visibility', 'visible']\n\t//window{Height,Width}, {x,y}Window\n];\n\n/* 18.2.19 (CT_Sheet) Defaults */\nvar SheetDef = [\n\t['state', 'visible']\n];\n\n/* 18.2.2  (CT_CalcPr) Defaults */\nvar CalcPrDef = [\n\t['calcCompleted', 'true'],\n\t['calcMode', 'auto'],\n\t['calcOnSave', 'true'],\n\t['concurrentCalc', 'true'],\n\t['fullCalcOnLoad', 'false'],\n\t['fullPrecision', 'true'],\n\t['iterate', 'false'],\n\t['iterateCount', '100'],\n\t['iterateDelta', '0.001'],\n\t['refMode', 'A1']\n];\n\n/* 18.2.3 (CT_CustomWorkbookView) Defaults */\nvar CustomWBViewDef = [\n\t['autoUpdate', 'false'],\n\t['changesSavedWin', 'false'],\n\t['includeHiddenRowCol', 'true'],\n\t['includePrintSettings', 'true'],\n\t['maximized', 'false'],\n\t['minimized', 'false'],\n\t['onlySync', 'false'],\n\t['personalView', 'false'],\n\t['showComments', 'commIndicator'],\n\t['showFormulaBar', 'true'],\n\t['showHorizontalScroll', 'true'],\n\t['showObjects', 'all'],\n\t['showSheetTabs', 'true'],\n\t['showStatusbar', 'true'],\n\t['showVerticalScroll', 'true'],\n\t['tabRatio', '600'],\n\t['xWindow', '0'],\n\t['yWindow', '0']\n];\n\nfunction push_defaults_array(target, defaults) {\n\tfor(var j = 0; j != target.length; ++j) { var w = target[j];\n\t\tfor(var i=0; i != defaults.length; ++i) { var z = defaults[i];\n\t\t\tif(w[z[0]] == null) w[z[0]] = z[1];\n\t\t}\n\t}\n}\nfunction push_defaults(target, defaults) {\n\tfor(var i = 0; i != defaults.length; ++i) { var z = defaults[i];\n\t\tif(target[z[0]] == null) target[z[0]] = z[1];\n\t}\n}\n\nfunction parse_wb_defaults(wb) {\n\tpush_defaults(wb.WBProps, WBPropsDef);\n\tpush_defaults(wb.CalcPr, CalcPrDef);\n\n\tpush_defaults_array(wb.WBView, WBViewDef);\n\tpush_defaults_array(wb.Sheets, SheetDef);\n\n\t_ssfopts.date1904 = parsexmlbool(wb.WBProps.date1904, 'date1904');\n}\n/* 18.2 Workbook */\nvar wbnsregex = /<\\w+:workbook/;\nfunction parse_wb_xml(data, opts) {\n\tvar wb = { AppVersion:{}, WBProps:{}, WBView:[], Sheets:[], CalcPr:{}, xmlns: \"\" };\n\tvar pass = false, xmlns = \"xmlns\";\n\tdata.match(tagregex).forEach(function xml_wb(x) {\n\t\tvar y = parsexmltag(x);\n\t\tswitch(strip_ns(y[0])) {\n\t\t\tcase '<?xml': break;\n\n\t\t\t/* 18.2.27 workbook CT_Workbook 1 */\n\t\t\tcase '<workbook':\n\t\t\t\tif(x.match(wbnsregex)) xmlns = \"xmlns\" + x.match(/<(\\w+):/)[1];\n\t\t\t\twb.xmlns = y[xmlns];\n\t\t\t\tbreak;\n\t\t\tcase '</workbook>': break;\n\n\t\t\t/* 18.2.13 fileVersion CT_FileVersion ? */\n\t\t\tcase '<fileVersion': delete y[0]; wb.AppVersion = y; break;\n\t\t\tcase '<fileVersion/>': break;\n\n\t\t\t/* 18.2.12 fileSharing CT_FileSharing ? */\n\t\t\tcase '<fileSharing': case '<fileSharing/>': break;\n\n\t\t\t/* 18.2.28 workbookPr CT_WorkbookPr ? */\n\t\t\tcase '<workbookPr': delete y[0]; wb.WBProps = y; break;\n\t\t\tcase '<workbookPr/>': delete y[0]; wb.WBProps = y; break;\n\n\t\t\t/* 18.2.29 workbookProtection CT_WorkbookProtection ? */\n\t\t\tcase '<workbookProtection': break;\n\t\t\tcase '<workbookProtection/>': break;\n\n\t\t\t/* 18.2.1  bookViews CT_BookViews ? */\n\t\t\tcase '<bookViews>': case '</bookViews>': break;\n\t\t\t/* 18.2.30   workbookView CT_BookView + */\n\t\t\tcase '<workbookView': delete y[0]; wb.WBView.push(y); break;\n\n\t\t\t/* 18.2.20 sheets CT_Sheets 1 */\n\t\t\tcase '<sheets>': case '</sheets>': break; // aggregate sheet\n\t\t\t/* 18.2.19   sheet CT_Sheet + */\n\t\t\tcase '<sheet': delete y[0]; y.name = utf8read(y.name); wb.Sheets.push(y); break;\n\n\t\t\t/* 18.2.15 functionGroups CT_FunctionGroups ? */\n\t\t\tcase '<functionGroups': case '<functionGroups/>': break;\n\t\t\t/* 18.2.14   functionGroup CT_FunctionGroup + */\n\t\t\tcase '<functionGroup': break;\n\n\t\t\t/* 18.2.9  externalReferences CT_ExternalReferences ? */\n\t\t\tcase '<externalReferences': case '</externalReferences>': case '<externalReferences>': break;\n\t\t\t/* 18.2.8    externalReference CT_ExternalReference + */\n\t\t\tcase '<externalReference': break;\n\n\t\t\t/* 18.2.6  definedNames CT_DefinedNames ? */\n\t\t\tcase '<definedNames/>': break;\n\t\t\tcase '<definedNames>': case '<definedNames': pass=true; break;\n\t\t\tcase '</definedNames>': pass=false; break;\n\t\t\t/* 18.2.5    definedName CT_DefinedName + */\n\t\t\tcase '<definedName': case '<definedName/>': case '</definedName>': break;\n\n\t\t\t/* 18.2.2  calcPr CT_CalcPr ? */\n\t\t\tcase '<calcPr': delete y[0]; wb.CalcPr = y; break;\n\t\t\tcase '<calcPr/>': delete y[0]; wb.CalcPr = y; break;\n\n\t\t\t/* 18.2.16 oleSize CT_OleSize ? (ref required) */\n\t\t\tcase '<oleSize': break;\n\n\t\t\t/* 18.2.4  customWorkbookViews CT_CustomWorkbookViews ? */\n\t\t\tcase '<customWorkbookViews>': case '</customWorkbookViews>': case '<customWorkbookViews': break;\n\t\t\t/* 18.2.3    customWorkbookView CT_CustomWorkbookView + */\n\t\t\tcase '<customWorkbookView': case '</customWorkbookView>': break;\n\n\t\t\t/* 18.2.18 pivotCaches CT_PivotCaches ? */\n\t\t\tcase '<pivotCaches>': case '</pivotCaches>': case '<pivotCaches': break;\n\t\t\t/* 18.2.17 pivotCache CT_PivotCache ? */\n\t\t\tcase '<pivotCache': break;\n\n\t\t\t/* 18.2.21 smartTagPr CT_SmartTagPr ? */\n\t\t\tcase '<smartTagPr': case '<smartTagPr/>': break;\n\n\t\t\t/* 18.2.23 smartTagTypes CT_SmartTagTypes ? */\n\t\t\tcase '<smartTagTypes': case '<smartTagTypes>': case '</smartTagTypes>': break;\n\t\t\t/* 18.2.22   smartTagType CT_SmartTagType ? */\n\t\t\tcase '<smartTagType': break;\n\n\t\t\t/* 18.2.24 webPublishing CT_WebPublishing ? */\n\t\t\tcase '<webPublishing': case '<webPublishing/>': break;\n\n\t\t\t/* 18.2.11 fileRecoveryPr CT_FileRecoveryPr ? */\n\t\t\tcase '<fileRecoveryPr': case '<fileRecoveryPr/>': break;\n\n\t\t\t/* 18.2.26 webPublishObjects CT_WebPublishObjects ? */\n\t\t\tcase '<webPublishObjects>': case '<webPublishObjects': case '</webPublishObjects>': break;\n\t\t\t/* 18.2.25 webPublishObject CT_WebPublishObject ? */\n\t\t\tcase '<webPublishObject': break;\n\n\t\t\t/* 18.2.10 extLst CT_ExtensionList ? */\n\t\t\tcase '<extLst>': case '</extLst>': case '<extLst/>': break;\n\t\t\t/* 18.2.7    ext CT_Extension + */\n\t\t\tcase '<ext': pass=true; break; //TODO: check with versions of excel\n\t\t\tcase '</ext>': pass=false; break;\n\n\t\t\t/* Others */\n\t\t\tcase '<ArchID': break;\n\t\t\tcase '<AlternateContent': pass=true; break;\n\t\t\tcase '</AlternateContent>': pass=false; break;\n\n\t\t\tdefault: if(!pass && opts.WTF) throw 'unrecognized ' + y[0] + ' in workbook';\n\t\t}\n\t});\n\tif(XMLNS.main.indexOf(wb.xmlns) === -1) throw new Error(\"Unknown Namespace: \" + wb.xmlns);\n\n\tparse_wb_defaults(wb);\n\n\treturn wb;\n}\n\nvar WB_XML_ROOT = writextag('workbook', null, {\n\t'xmlns': XMLNS.main[0],\n\t//'xmlns:mx': XMLNS.mx,\n\t//'xmlns:s': XMLNS.main[0],\n\t'xmlns:r': XMLNS.r\n});\n\nfunction safe1904(wb) {\n\t/* TODO: store date1904 somewhere else */\n\ttry { return parsexmlbool(wb.Workbook.WBProps.date1904) ? \"true\" : \"false\"; } catch(e) { return \"false\"; }\n}\n\nfunction write_wb_xml(wb, opts) {\n\tvar o = [XML_HEADER];\n\to[o.length] = WB_XML_ROOT;\n\to[o.length] = (writextag('workbookPr', null, {date1904:safe1904(wb)}));\n\to[o.length] = \"<sheets>\";\n\tfor(var i = 0; i != wb.SheetNames.length; ++i)\n\t\to[o.length] = (writextag('sheet',null,{name:wb.SheetNames[i].substr(0,31), sheetId:\"\"+(i+1), \"r:id\":\"rId\"+(i+1)}));\n\to[o.length] = \"</sheets>\";\n\tif(o.length>2){ o[o.length] = '</workbook>'; o[1]=o[1].replace(\"/>\",\">\"); }\n\treturn o.join(\"\");\n}\n/* [MS-XLSB] 2.4.301 BrtBundleSh */\nfunction parse_BrtBundleSh(data, length) {\n\tvar z = {};\n\tz.hsState = data.read_shift(4); //ST_SheetState\n\tz.iTabID = data.read_shift(4);\n\tz.strRelID = parse_RelID(data,length-8);\n\tz.name = parse_XLWideString(data);\n\treturn z;\n}\nfunction write_BrtBundleSh(data, o) {\n\tif(!o) o = new_buf(127);\n\to.write_shift(4, data.hsState);\n\to.write_shift(4, data.iTabID);\n\twrite_RelID(data.strRelID, o);\n\twrite_XLWideString(data.name.substr(0,31), o);\n\treturn o;\n}\n\n/* [MS-XLSB] 2.4.807 BrtWbProp */\nfunction parse_BrtWbProp(data, length) {\n\tdata.read_shift(4);\n\tvar dwThemeVersion = data.read_shift(4);\n\tvar strName = (length > 8) ? parse_XLWideString(data) : \"\";\n\treturn [dwThemeVersion, strName];\n}\nfunction write_BrtWbProp(data, o) {\n\tif(!o) o = new_buf(8);\n\to.write_shift(4, 0);\n\to.write_shift(4, 0);\n\treturn o;\n}\n\nfunction parse_BrtFRTArchID$(data, length) {\n\tvar o = {};\n\tdata.read_shift(4);\n\to.ArchID = data.read_shift(4);\n\tdata.l += length - 8;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.1.7.60 Workbook */\nfunction parse_wb_bin(data, opts) {\n\tvar wb = { AppVersion:{}, WBProps:{}, WBView:[], Sheets:[], CalcPr:{}, xmlns: \"\" };\n\tvar pass = false, z;\n\n\trecordhopper(data, function hopper_wb(val, R) {\n\t\tswitch(R.n) {\n\t\t\tcase 'BrtBundleSh': wb.Sheets.push(val); break;\n\n\t\t\tcase 'BrtBeginBook': break;\n\t\t\tcase 'BrtFileVersion': break;\n\t\t\tcase 'BrtWbProp': break;\n\t\t\tcase 'BrtACBegin': break;\n\t\t\tcase 'BrtAbsPath15': break;\n\t\t\tcase 'BrtACEnd': break;\n\t\t\tcase 'BrtWbFactoid': break;\n\t\t\t/*case 'BrtBookProtectionIso': break;*/\n\t\t\tcase 'BrtBookProtection': break;\n\t\t\tcase 'BrtBeginBookViews': break;\n\t\t\tcase 'BrtBookView': break;\n\t\t\tcase 'BrtEndBookViews': break;\n\t\t\tcase 'BrtBeginBundleShs': break;\n\t\t\tcase 'BrtEndBundleShs': break;\n\t\t\tcase 'BrtBeginFnGroup': break;\n\t\t\tcase 'BrtEndFnGroup': break;\n\t\t\tcase 'BrtBeginExternals': break;\n\t\t\tcase 'BrtSupSelf': break;\n\t\t\tcase 'BrtSupBookSrc': break;\n\t\t\tcase 'BrtExternSheet': break;\n\t\t\tcase 'BrtEndExternals': break;\n\t\t\tcase 'BrtName': break;\n\t\t\tcase 'BrtCalcProp': break;\n\t\t\tcase 'BrtUserBookView': break;\n\t\t\tcase 'BrtBeginPivotCacheIDs': break;\n\t\t\tcase 'BrtBeginPivotCacheID': break;\n\t\t\tcase 'BrtEndPivotCacheID': break;\n\t\t\tcase 'BrtEndPivotCacheIDs': break;\n\t\t\tcase 'BrtWebOpt': break;\n\t\t\tcase 'BrtFileRecover': break;\n\t\t\tcase 'BrtFileSharing': break;\n\t\t\t/*case 'BrtBeginWebPubItems': break;\n\t\t\tcase 'BrtBeginWebPubItem': break;\n\t\t\tcase 'BrtEndWebPubItem': break;\n\t\t\tcase 'BrtEndWebPubItems': break;*/\n\n\t\t\t/* Smart Tags */\n\t\t\tcase 'BrtBeginSmartTagTypes': break;\n\t\t\tcase 'BrtSmartTagType': break;\n\t\t\tcase 'BrtEndSmartTagTypes': break;\n\n\t\t\tcase 'BrtFRTBegin': pass = true; break;\n\t\t\tcase 'BrtFRTArchID$': break;\n\t\t\tcase 'BrtWorkBookPr15': break;\n\t\t\tcase 'BrtFRTEnd': pass = false; break;\n\t\t\tcase 'BrtEndBook': break;\n\t\t\tdefault: if(!pass || opts.WTF) throw new Error(\"Unexpected record \" + R.n);\n\t\t}\n\t});\n\n\tparse_wb_defaults(wb);\n\n\treturn wb;\n}\n\n/* [MS-XLSB] 2.1.7.60 Workbook */\nfunction write_BUNDLESHS(ba, wb, opts) {\n\twrite_record(ba, \"BrtBeginBundleShs\");\n\tfor(var idx = 0; idx != wb.SheetNames.length; ++idx) {\n\t\tvar d = { hsState: 0, iTabID: idx+1, strRelID: 'rId' + (idx+1), name: wb.SheetNames[idx] };\n\t\twrite_record(ba, \"BrtBundleSh\", write_BrtBundleSh(d));\n\t}\n\twrite_record(ba, \"BrtEndBundleShs\");\n}\n\n/* [MS-XLSB] 2.4.643 BrtFileVersion */\nfunction write_BrtFileVersion(data, o) {\n\tif(!o) o = new_buf(127);\n\tfor(var i = 0; i != 4; ++i) o.write_shift(4, 0);\n\twrite_XLWideString(\"SheetJS\", o);\n\twrite_XLWideString(XLSX.version, o);\n\twrite_XLWideString(XLSX.version, o);\n\twrite_XLWideString(\"7262\", o);\n\to.length = o.l;\n\treturn o;\n}\n\n/* [MS-XLSB] 2.1.7.60 Workbook */\nfunction write_BOOKVIEWS(ba, wb, opts) {\n\twrite_record(ba, \"BrtBeginBookViews\");\n\t/* 1*(BrtBookView *FRT) */\n\twrite_record(ba, \"BrtEndBookViews\");\n}\n\n/* [MS-XLSB] 2.4.302 BrtCalcProp */\nfunction write_BrtCalcProp(data, o) {\n\tif(!o) o = new_buf(26);\n\to.write_shift(4,0); /* force recalc */\n\to.write_shift(4,1);\n\to.write_shift(4,0);\n\twrite_Xnum(0, o);\n\to.write_shift(-4, 1023);\n\to.write_shift(1, 0x33);\n\to.write_shift(1, 0x00);\n\treturn o;\n}\n\nfunction write_BrtFileRecover(data, o) {\n\tif(!o) o = new_buf(1);\n\to.write_shift(1,0);\n\treturn o;\n}\n\n/* [MS-XLSB] 2.1.7.60 Workbook */\nfunction write_wb_bin(wb, opts) {\n\tvar ba = buf_array();\n\twrite_record(ba, \"BrtBeginBook\");\n\twrite_record(ba, \"BrtFileVersion\", write_BrtFileVersion());\n\t/* [[BrtFileSharingIso] BrtFileSharing] */\n\twrite_record(ba, \"BrtWbProp\", write_BrtWbProp());\n\t/* [ACABSPATH] */\n\t/* [[BrtBookProtectionIso] BrtBookProtection] */\n\twrite_BOOKVIEWS(ba, wb, opts);\n\twrite_BUNDLESHS(ba, wb, opts);\n\t/* [FNGROUP] */\n\t/* [EXTERNALS] */\n\t/* *BrtName */\n\twrite_record(ba, \"BrtCalcProp\", write_BrtCalcProp());\n\t/* [BrtOleSize] */\n\t/* *(BrtUserBookView *FRT) */\n\t/* [PIVOTCACHEIDS] */\n\t/* [BrtWbFactoid] */\n\t/* [SMARTTAGTYPES] */\n\t/* [BrtWebOpt] */\n\twrite_record(ba, \"BrtFileRecover\", write_BrtFileRecover());\n\t/* [WEBPUBITEMS] */\n\t/* [CRERRS] */\n\t/* FRTWORKBOOK */\n\twrite_record(ba, \"BrtEndBook\");\n\n\treturn ba.end();\n}\nfunction parse_wb(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? parse_wb_bin : parse_wb_xml)(data, opts);\n}\n\nfunction parse_ws(data, name, opts, rels) {\n\treturn (name.substr(-4)===\".bin\" ? parse_ws_bin : parse_ws_xml)(data, opts, rels);\n}\n\nfunction parse_sty(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? parse_sty_bin : parse_sty_xml)(data, opts);\n}\n\nfunction parse_theme(data, name, opts) {\n\treturn parse_theme_xml(data, opts);\n}\n\nfunction parse_sst(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? parse_sst_bin : parse_sst_xml)(data, opts);\n}\n\nfunction parse_cmnt(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? parse_comments_bin : parse_comments_xml)(data, opts);\n}\n\nfunction parse_cc(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? parse_cc_bin : parse_cc_xml)(data, opts);\n}\n\nfunction write_wb(wb, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? write_wb_bin : write_wb_xml)(wb, opts);\n}\n\nfunction write_ws(data, name, opts, wb) {\n\treturn (name.substr(-4)===\".bin\" ? write_ws_bin : write_ws_xml)(data, opts, wb);\n}\n\nfunction write_sty(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? write_sty_bin : write_sty_xml)(data, opts);\n}\n\nfunction write_sst(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? write_sst_bin : write_sst_xml)(data, opts);\n}\n/*\nfunction write_cmnt(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? write_comments_bin : write_comments_xml)(data, opts);\n}\n\nfunction write_cc(data, name, opts) {\n\treturn (name.substr(-4)===\".bin\" ? write_cc_bin : write_cc_xml)(data, opts);\n}\n*/\nvar attregexg2=/([\\w:]+)=((?:\")([^\"]*)(?:\")|(?:')([^']*)(?:'))/g;\nvar attregex2=/([\\w:]+)=((?:\")(?:[^\"]*)(?:\")|(?:')(?:[^']*)(?:'))/;\nvar _chr = function(c) { return String.fromCharCode(c); };\nfunction xlml_parsexmltag(tag, skip_root) {\n\tvar words = tag.split(/\\s+/);\n\tvar z = []; if(!skip_root) z[0] = words[0];\n\tif(words.length === 1) return z;\n\tvar m = tag.match(attregexg2), y, j, w, i;\n\tif(m) for(i = 0; i != m.length; ++i) {\n\t\ty = m[i].match(attregex2);\n\t\tif((j=y[1].indexOf(\":\")) === -1) z[y[1]] = y[2].substr(1,y[2].length-2);\n\t\telse {\n\t\t\tif(y[1].substr(0,6) === \"xmlns:\") w = \"xmlns\"+y[1].substr(6);\n\t\t\telse w = y[1].substr(j+1);\n\t\t\tz[w] = y[2].substr(1,y[2].length-2);\n\t\t}\n\t}\n\treturn z;\n}\nfunction xlml_parsexmltagobj(tag) {\n\tvar words = tag.split(/\\s+/);\n\tvar z = {};\n\tif(words.length === 1) return z;\n\tvar m = tag.match(attregexg2), y, j, w, i;\n\tif(m) for(i = 0; i != m.length; ++i) {\n\t\ty = m[i].match(attregex2);\n\t\tif((j=y[1].indexOf(\":\")) === -1) z[y[1]] = y[2].substr(1,y[2].length-2);\n\t\telse {\n\t\t\tif(y[1].substr(0,6) === \"xmlns:\") w = \"xmlns\"+y[1].substr(6);\n\t\t\telse w = y[1].substr(j+1);\n\t\t\tz[w] = y[2].substr(1,y[2].length-2);\n\t\t}\n\t}\n\treturn z;\n}\n\n// ----\n\nfunction xlml_format(format, value) {\n\tvar fmt = XLMLFormatMap[format] || unescapexml(format);\n\tif(fmt === \"General\") return SSF._general(value);\n\treturn SSF.format(fmt, value);\n}\n\nfunction xlml_set_custprop(Custprops, Rn, cp, val) {\n\tswitch((cp[0].match(/dt:dt=\"([\\w.]+)\"/)||[\"\",\"\"])[1]) {\n\t\tcase \"boolean\": val = parsexmlbool(val); break;\n\t\tcase \"i2\": case \"int\": val = parseInt(val, 10); break;\n\t\tcase \"r4\": case \"float\": val = parseFloat(val); break;\n\t\tcase \"date\": case \"dateTime.tz\": val = new Date(val); break;\n\t\tcase \"i8\": case \"string\": case \"fixed\": case \"uuid\": case \"bin.base64\": break;\n\t\tdefault: throw \"bad custprop:\" + cp[0];\n\t}\n\tCustprops[unescapexml(Rn[3])] = val;\n}\n\nfunction safe_format_xlml(cell, nf, o) {\n\ttry {\n\t\tif(cell.t === 'e') { cell.w = cell.w || BErr[cell.v]; }\n\t\telse if(nf === \"General\") {\n\t\t\tif(cell.t === 'n') {\n\t\t\t\tif((cell.v|0) === cell.v) cell.w = SSF._general_int(cell.v);\n\t\t\t\telse cell.w = SSF._general_num(cell.v);\n\t\t\t}\n\t\t\telse cell.w = SSF._general(cell.v);\n\t\t}\n\t\telse cell.w = xlml_format(nf||\"General\", cell.v);\n\t\tif(o.cellNF) cell.z = XLMLFormatMap[nf]||nf||\"General\";\n\t} catch(e) { if(o.WTF) throw e; }\n}\n\nfunction process_style_xlml(styles, stag, opts) {\n\tif(opts.cellStyles) {\n\t\tif(stag.Interior) {\n\t\t\tvar I = stag.Interior;\n\t\t\tif(I.Pattern) I.patternType = XLMLPatternTypeMap[I.Pattern] || I.Pattern;\n\t\t}\n\t}\n\tstyles[stag.ID] = stag;\n}\n\n/* TODO: there must exist some form of OSP-blessed spec */\nfunction parse_xlml_data(xml, ss, data, cell, base, styles, csty, row, o) {\n\tvar nf = \"General\", sid = cell.StyleID, S = {}; o = o || {};\n\tvar interiors = [];\n\tif(sid === undefined && row) sid = row.StyleID;\n\tif(sid === undefined && csty) sid = csty.StyleID;\n\twhile(styles[sid] !== undefined) {\n\t\tif(styles[sid].nf) nf = styles[sid].nf;\n\t\tif(styles[sid].Interior) interiors.push(styles[sid].Interior);\n\t\tif(!styles[sid].Parent) break;\n\t\tsid = styles[sid].Parent;\n\t}\n\tswitch(data.Type) {\n\t\tcase 'Boolean':\n\t\t\tcell.t = 'b';\n\t\t\tcell.v = parsexmlbool(xml);\n\t\t\tbreak;\n\t\tcase 'String':\n\t\t\tcell.t = 's'; cell.r = xlml_fixstr(unescapexml(xml));\n\t\t\tcell.v = xml.indexOf(\"<\") > -1 ? ss : cell.r;\n\t\t\tbreak;\n\t\tcase 'DateTime':\n\t\t\tcell.v = (Date.parse(xml) - new Date(Date.UTC(1899, 11, 30))) / (24 * 60 * 60 * 1000);\n\t\t\tif(cell.v !== cell.v) cell.v = unescapexml(xml);\n\t\t\telse if(cell.v >= 1 && cell.v<60) cell.v = cell.v -1;\n\t\t\tif(!nf || nf == \"General\") nf = \"yyyy-mm-dd\";\n\t\t\t/* falls through */\n\t\tcase 'Number':\n\t\t\tif(cell.v === undefined) cell.v=+xml;\n\t\t\tif(!cell.t) cell.t = 'n';\n\t\t\tbreak;\n\t\tcase 'Error': cell.t = 'e'; cell.v = RBErr[xml]; cell.w = xml; break;\n\t\tdefault: cell.t = 's'; cell.v = xlml_fixstr(ss); break;\n\t}\n\tsafe_format_xlml(cell, nf, o);\n\tif(o.cellFormula != null && cell.Formula) {\n\t\tcell.f = rc_to_a1(unescapexml(cell.Formula), base);\n\t\tcell.Formula = undefined;\n\t}\n\tif(o.cellStyles) {\n\t\tinteriors.forEach(function(x) {\n\t\t\tif(!S.patternType && x.patternType) S.patternType = x.patternType;\n\t\t});\n\t\tcell.s = S;\n\t}\n\tcell.ixfe = cell.StyleID !== undefined ? cell.StyleID : 'Default';\n}\n\nfunction xlml_clean_comment(comment) {\n\tcomment.t = comment.v;\n\tcomment.v = comment.w = comment.ixfe = undefined;\n}\n\nfunction xlml_normalize(d) {\n\tif(has_buf && Buffer.isBuffer(d)) return d.toString('utf8');\n\tif(typeof d === 'string') return d;\n\tthrow \"badf\";\n}\n\n/* TODO: Everything */\nvar xlmlregex = /<(\\/?)([a-z0-9]*:|)(\\w+)[^>]*>/mg;\nfunction parse_xlml_xml(d, opts) {\n\tvar str = xlml_normalize(d);\n\tvar Rn;\n\tvar state = [], tmp;\n\tvar sheets = {}, sheetnames = [], cursheet = {}, sheetname = \"\";\n\tvar table = {}, cell = {}, row = {}, dtag, didx;\n\tvar c = 0, r = 0;\n\tvar refguess = {s: {r:1000000, c:1000000}, e: {r:0, c:0} };\n\tvar styles = {}, stag = {};\n\tvar ss = \"\", fidx = 0;\n\tvar mergecells = [];\n\tvar Props = {}, Custprops = {}, pidx = 0, cp = {};\n\tvar comments = [], comment = {};\n\tvar cstys = [], csty;\n\txlmlregex.lastIndex = 0;\n\twhile((Rn = xlmlregex.exec(str))) switch(Rn[3]) {\n\t\tcase 'Data':\n\t\t\tif(state[state.length-1][1]) break;\n\t\t\tif(Rn[1]==='/') parse_xlml_data(str.slice(didx, Rn.index), ss, dtag, state[state.length-1][0]==\"Comment\"?comment:cell, {c:c,r:r}, styles, cstys[c], row, opts);\n\t\t\telse { ss = \"\"; dtag = xlml_parsexmltag(Rn[0]); didx = Rn.index + Rn[0].length; }\n\t\t\tbreak;\n\t\tcase 'Cell':\n\t\t\tif(Rn[1]==='/'){\n\t\t\t\tif(comments.length > 0) cell.c = comments;\n\t\t\t\tif((!opts.sheetRows || opts.sheetRows > r) && cell.v !== undefined) cursheet[encode_col(c) + encode_row(r)] = cell;\n\t\t\t\tif(cell.HRef) {\n\t\t\t\t\tcell.l = {Target:cell.HRef, tooltip:cell.HRefScreenTip};\n\t\t\t\t\tcell.HRef = cell.HRefScreenTip = undefined;\n\t\t\t\t}\n\t\t\t\tif(cell.MergeAcross || cell.MergeDown) {\n\t\t\t\t\tvar cc = c + (parseInt(cell.MergeAcross,10)|0);\n\t\t\t\t\tvar rr = r + (parseInt(cell.MergeDown,10)|0);\n\t\t\t\t\tmergecells.push({s:{c:c,r:r},e:{c:cc,r:rr}});\n\t\t\t\t}\n\t\t\t\t++c;\n\t\t\t\tif(cell.MergeAcross) c += +cell.MergeAcross;\n\t\t\t} else {\n\t\t\t\tcell = xlml_parsexmltagobj(Rn[0]);\n\t\t\t\tif(cell.Index) c = +cell.Index - 1;\n\t\t\t\tif(c < refguess.s.c) refguess.s.c = c;\n\t\t\t\tif(c > refguess.e.c) refguess.e.c = c;\n\t\t\t\tif(Rn[0].substr(-2) === \"/>\") ++c;\n\t\t\t\tcomments = [];\n\t\t\t}\n\t\t\tbreak;\n\t\tcase 'Row':\n\t\t\tif(Rn[1]==='/' || Rn[0].substr(-2) === \"/>\") {\n\t\t\t\tif(r < refguess.s.r) refguess.s.r = r;\n\t\t\t\tif(r > refguess.e.r) refguess.e.r = r;\n\t\t\t\tif(Rn[0].substr(-2) === \"/>\") {\n\t\t\t\t\trow = xlml_parsexmltag(Rn[0]);\n\t\t\t\t\tif(row.Index) r = +row.Index - 1;\n\t\t\t\t}\n\t\t\t\tc = 0; ++r;\n\t\t\t} else {\n\t\t\t\trow = xlml_parsexmltag(Rn[0]);\n\t\t\t\tif(row.Index) r = +row.Index - 1;\n\t\t\t}\n\t\t\tbreak;\n\t\tcase 'Worksheet': /* TODO: read range from FullRows/FullColumns */\n\t\t\tif(Rn[1]==='/'){\n\t\t\t\tif((tmp=state.pop())[0]!==Rn[3]) throw \"Bad state: \"+tmp;\n\t\t\t\tsheetnames.push(sheetname);\n\t\t\t\tif(refguess.s.r <= refguess.e.r && refguess.s.c <= refguess.e.c) cursheet[\"!ref\"] = encode_range(refguess);\n\t\t\t\tif(mergecells.length) cursheet[\"!merges\"] = mergecells;\n\t\t\t\tsheets[sheetname] = cursheet;\n\t\t\t} else {\n\t\t\t\trefguess = {s: {r:1000000, c:1000000}, e: {r:0, c:0} };\n\t\t\t\tr = c = 0;\n\t\t\t\tstate.push([Rn[3], false]);\n\t\t\t\ttmp = xlml_parsexmltag(Rn[0]);\n\t\t\t\tsheetname = tmp.Name;\n\t\t\t\tcursheet = {};\n\t\t\t\tmergecells = [];\n\t\t\t}\n\t\t\tbreak;\n\t\tcase 'Table':\n\t\t\tif(Rn[1]==='/'){if((tmp=state.pop())[0]!==Rn[3]) throw \"Bad state: \"+tmp;}\n\t\t\telse if(Rn[0].slice(-2) == \"/>\") break;\n\t\t\telse {\n\t\t\t\ttable = xlml_parsexmltag(Rn[0]);\n\t\t\t\tstate.push([Rn[3], false]);\n\t\t\t\tcstys = [];\n\t\t\t}\n\t\t\tbreak;\n\n\t\tcase 'Style':\n\t\t\tif(Rn[1]==='/') process_style_xlml(styles, stag, opts);\n\t\t\telse stag = xlml_parsexmltag(Rn[0]);\n\t\t\tbreak;\n\n\t\tcase 'NumberFormat':\n\t\t\tstag.nf = xlml_parsexmltag(Rn[0]).Format || \"General\";\n\t\t\tbreak;\n\n\t\tcase 'Column':\n\t\t\tif(state[state.length-1][0] !== 'Table') break;\n\t\t\tcsty = xlml_parsexmltag(Rn[0]);\n\t\t\tcstys[(csty.Index-1||cstys.length)] = csty;\n\t\t\tfor(var i = 0; i < +csty.Span; ++i) cstys[cstys.length] = csty;\n\t\t\tbreak;\n\n\t\tcase 'NamedRange': break;\n\t\tcase 'NamedCell': break;\n\t\tcase 'B': break;\n\t\tcase 'I': break;\n\t\tcase 'U': break;\n\t\tcase 'S': break;\n\t\tcase 'Sub': break;\n\t\tcase 'Sup': break;\n\t\tcase 'Span': break;\n\t\tcase 'Border': break;\n\t\tcase 'Alignment': break;\n\t\tcase 'Borders': break;\n\t\tcase 'Font':\n\t\t\tif(Rn[0].substr(-2) === \"/>\") break;\n\t\t\telse if(Rn[1]===\"/\") ss += str.slice(fidx, Rn.index);\n\t\t\telse fidx = Rn.index + Rn[0].length;\n\t\t\tbreak;\n\t\tcase 'Interior':\n\t\t\tif(!opts.cellStyles) break;\n\t\t\tstag.Interior = xlml_parsexmltag(Rn[0]);\n\t\t\tbreak;\n\t\tcase 'Protection': break;\n\n\t\tcase 'Author':\n\t\tcase 'Title':\n\t\tcase 'Description':\n\t\tcase 'Created':\n\t\tcase 'Keywords':\n\t\tcase 'Subject':\n\t\tcase 'Category':\n\t\tcase 'Company':\n\t\tcase 'LastAuthor':\n\t\tcase 'LastSaved':\n\t\tcase 'LastPrinted':\n\t\tcase 'Version':\n\t\tcase 'Revision':\n\t\tcase 'TotalTime':\n\t\tcase 'HyperlinkBase':\n\t\tcase 'Manager':\n\t\t\tif(Rn[0].substr(-2) === \"/>\") break;\n\t\t\telse if(Rn[1]===\"/\") xlml_set_prop(Props, Rn[3], str.slice(pidx, Rn.index));\n\t\t\telse pidx = Rn.index + Rn[0].length;\n\t\t\tbreak;\n\t\tcase 'Paragraphs': break;\n\n\t\tcase 'Styles':\n\t\tcase 'Workbook':\n\t\t\tif(Rn[1]==='/'){if((tmp=state.pop())[0]!==Rn[3]) throw \"Bad state: \"+tmp;}\n\t\t\telse state.push([Rn[3], false]);\n\t\t\tbreak;\n\n\t\tcase 'Comment':\n\t\t\tif(Rn[1]==='/'){\n\t\t\t\tif((tmp=state.pop())[0]!==Rn[3]) throw \"Bad state: \"+tmp;\n\t\t\t\txlml_clean_comment(comment);\n\t\t\t\tcomments.push(comment);\n\t\t\t} else {\n\t\t\t\tstate.push([Rn[3], false]);\n\t\t\t\ttmp = xlml_parsexmltag(Rn[0]);\n\t\t\t\tcomment = {a:tmp.Author};\n\t\t\t}\n\t\t\tbreak;\n\n\t\tcase 'Name': break;\n\n\t\tcase 'ComponentOptions':\n\t\tcase 'DocumentProperties':\n\t\tcase 'CustomDocumentProperties':\n\t\tcase 'OfficeDocumentSettings':\n\t\tcase 'PivotTable':\n\t\tcase 'PivotCache':\n\t\tcase 'Names':\n\t\tcase 'MapInfo':\n\t\tcase 'PageBreaks':\n\t\tcase 'QueryTable':\n\t\tcase 'DataValidation':\n\t\tcase 'AutoFilter':\n\t\tcase 'Sorting':\n\t\tcase 'Schema':\n\t\tcase 'data':\n\t\tcase 'ConditionalFormatting':\n\t\tcase 'SmartTagType':\n\t\tcase 'SmartTags':\n\t\tcase 'ExcelWorkbook':\n\t\tcase 'WorkbookOptions':\n\t\tcase 'WorksheetOptions':\n\t\t\tif(Rn[1]==='/'){if((tmp=state.pop())[0]!==Rn[3]) throw \"Bad state: \"+tmp;}\n\t\t\telse if(Rn[0].charAt(Rn[0].length-2) !== '/') state.push([Rn[3], true]);\n\t\t\tbreak;\n\n\t\tdefault:\n\t\t\tvar seen = true;\n\t\t\tswitch(state[state.length-1][0]) {\n\t\t\t\t/* OfficeDocumentSettings */\n\t\t\t\tcase 'OfficeDocumentSettings': switch(Rn[3]) {\n\t\t\t\t\tcase 'AllowPNG': break;\n\t\t\t\t\tcase 'RemovePersonalInformation': break;\n\t\t\t\t\tcase 'DownloadComponents': break;\n\t\t\t\t\tcase 'LocationOfComponents': break;\n\t\t\t\t\tcase 'Colors': break;\n\t\t\t\t\tcase 'Color': break;\n\t\t\t\t\tcase 'Index': break;\n\t\t\t\t\tcase 'RGB': break;\n\t\t\t\t\tcase 'PixelsPerInch': break;\n\t\t\t\t\tcase 'TargetScreenSize': break;\n\t\t\t\t\tcase 'ReadOnlyRecommended': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* ComponentOptions */\n\t\t\t\tcase 'ComponentOptions': switch(Rn[3]) {\n\t\t\t\t\tcase 'Toolbar': break;\n\t\t\t\t\tcase 'HideOfficeLogo': break;\n\t\t\t\t\tcase 'SpreadsheetAutoFit': break;\n\t\t\t\t\tcase 'Label': break;\n\t\t\t\t\tcase 'Caption': break;\n\t\t\t\t\tcase 'MaxHeight': break;\n\t\t\t\t\tcase 'MaxWidth': break;\n\t\t\t\t\tcase 'NextSheetNumber': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* ExcelWorkbook */\n\t\t\t\tcase 'ExcelWorkbook': switch(Rn[3]) {\n\t\t\t\t\tcase 'WindowHeight': break;\n\t\t\t\t\tcase 'WindowWidth': break;\n\t\t\t\t\tcase 'WindowTopX': break;\n\t\t\t\t\tcase 'WindowTopY': break;\n\t\t\t\t\tcase 'TabRatio': break;\n\t\t\t\t\tcase 'ProtectStructure': break;\n\t\t\t\t\tcase 'ProtectWindows': break;\n\t\t\t\t\tcase 'ActiveSheet': break;\n\t\t\t\t\tcase 'DisplayInkNotes': break;\n\t\t\t\t\tcase 'FirstVisibleSheet': break;\n\t\t\t\t\tcase 'SupBook': break;\n\t\t\t\t\tcase 'SheetName': break;\n\t\t\t\t\tcase 'SheetIndex': break;\n\t\t\t\t\tcase 'SheetIndexFirst': break;\n\t\t\t\t\tcase 'SheetIndexLast': break;\n\t\t\t\t\tcase 'Dll': break;\n\t\t\t\t\tcase 'AcceptLabelsInFormulas': break;\n\t\t\t\t\tcase 'DoNotSaveLinkValues': break;\n\t\t\t\t\tcase 'Date1904': break;\n\t\t\t\t\tcase 'Iteration': break;\n\t\t\t\t\tcase 'MaxIterations': break;\n\t\t\t\t\tcase 'MaxChange': break;\n\t\t\t\t\tcase 'Path': break;\n\t\t\t\t\tcase 'Xct': break;\n\t\t\t\t\tcase 'Count': break;\n\t\t\t\t\tcase 'SelectedSheets': break;\n\t\t\t\t\tcase 'Calculation': break;\n\t\t\t\t\tcase 'Uncalced': break;\n\t\t\t\t\tcase 'StartupPrompt': break;\n\t\t\t\t\tcase 'Crn': break;\n\t\t\t\t\tcase 'ExternName': break;\n\t\t\t\t\tcase 'Formula': break;\n\t\t\t\t\tcase 'ColFirst': break;\n\t\t\t\t\tcase 'ColLast': break;\n\t\t\t\t\tcase 'WantAdvise': break;\n\t\t\t\t\tcase 'Boolean': break;\n\t\t\t\t\tcase 'Error': break;\n\t\t\t\t\tcase 'Text': break;\n\t\t\t\t\tcase 'OLE': break;\n\t\t\t\t\tcase 'NoAutoRecover': break;\n\t\t\t\t\tcase 'PublishObjects': break;\n\t\t\t\t\tcase 'DoNotCalculateBeforeSave': break;\n\t\t\t\t\tcase 'Number': break;\n\t\t\t\t\tcase 'RefModeR1C1': break;\n\t\t\t\t\tcase 'EmbedSaveSmartTags': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* WorkbookOptions */\n\t\t\t\tcase 'WorkbookOptions': switch(Rn[3]) {\n\t\t\t\t\tcase 'OWCVersion': break;\n\t\t\t\t\tcase 'Height': break;\n\t\t\t\t\tcase 'Width': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* WorksheetOptions */\n\t\t\t\tcase 'WorksheetOptions': switch(Rn[3]) {\n\t\t\t\t\tcase 'Unsynced': break;\n\t\t\t\t\tcase 'Visible': break;\n\t\t\t\t\tcase 'Print': break;\n\t\t\t\t\tcase 'Panes': break;\n\t\t\t\t\tcase 'Scale': break;\n\t\t\t\t\tcase 'Pane': break;\n\t\t\t\t\tcase 'Number': break;\n\t\t\t\t\tcase 'Layout': break;\n\t\t\t\t\tcase 'Header': break;\n\t\t\t\t\tcase 'Footer': break;\n\t\t\t\t\tcase 'PageSetup': break;\n\t\t\t\t\tcase 'PageMargins': break;\n\t\t\t\t\tcase 'Selected': break;\n\t\t\t\t\tcase 'ProtectObjects': break;\n\t\t\t\t\tcase 'EnableSelection': break;\n\t\t\t\t\tcase 'ProtectScenarios': break;\n\t\t\t\t\tcase 'ValidPrinterInfo': break;\n\t\t\t\t\tcase 'HorizontalResolution': break;\n\t\t\t\t\tcase 'VerticalResolution': break;\n\t\t\t\t\tcase 'NumberofCopies': break;\n\t\t\t\t\tcase 'ActiveRow': break;\n\t\t\t\t\tcase 'ActiveCol': break;\n\t\t\t\t\tcase 'ActivePane': break;\n\t\t\t\t\tcase 'TopRowVisible': break;\n\t\t\t\t\tcase 'TopRowBottomPane': break;\n\t\t\t\t\tcase 'LeftColumnVisible': break;\n\t\t\t\t\tcase 'LeftColumnRightPane': break;\n\t\t\t\t\tcase 'FitToPage': break;\n\t\t\t\t\tcase 'RangeSelection': break;\n\t\t\t\t\tcase 'PaperSizeIndex': break;\n\t\t\t\t\tcase 'PageLayoutZoom': break;\n\t\t\t\t\tcase 'PageBreakZoom': break;\n\t\t\t\t\tcase 'FilterOn': break;\n\t\t\t\t\tcase 'DoNotDisplayGridlines': break;\n\t\t\t\t\tcase 'SplitHorizontal': break;\n\t\t\t\t\tcase 'SplitVertical': break;\n\t\t\t\t\tcase 'FreezePanes': break;\n\t\t\t\t\tcase 'FrozenNoSplit': break;\n\t\t\t\t\tcase 'FitWidth': break;\n\t\t\t\t\tcase 'FitHeight': break;\n\t\t\t\t\tcase 'CommentsLayout': break;\n\t\t\t\t\tcase 'Zoom': break;\n\t\t\t\t\tcase 'LeftToRight': break;\n\t\t\t\t\tcase 'Gridlines': break;\n\t\t\t\t\tcase 'AllowSort': break;\n\t\t\t\t\tcase 'AllowFilter': break;\n\t\t\t\t\tcase 'AllowInsertRows': break;\n\t\t\t\t\tcase 'AllowDeleteRows': break;\n\t\t\t\t\tcase 'AllowInsertCols': break;\n\t\t\t\t\tcase 'AllowDeleteCols': break;\n\t\t\t\t\tcase 'AllowInsertHyperlinks': break;\n\t\t\t\t\tcase 'AllowFormatCells': break;\n\t\t\t\t\tcase 'AllowSizeCols': break;\n\t\t\t\t\tcase 'AllowSizeRows': break;\n\t\t\t\t\tcase 'NoSummaryRowsBelowDetail': break;\n\t\t\t\t\tcase 'TabColorIndex': break;\n\t\t\t\t\tcase 'DoNotDisplayHeadings': break;\n\t\t\t\t\tcase 'ShowPageLayoutZoom': break;\n\t\t\t\t\tcase 'NoSummaryColumnsRightDetail': break;\n\t\t\t\t\tcase 'BlackAndWhite': break;\n\t\t\t\t\tcase 'DoNotDisplayZeros': break;\n\t\t\t\t\tcase 'DisplayPageBreak': break;\n\t\t\t\t\tcase 'RowColHeadings': break;\n\t\t\t\t\tcase 'DoNotDisplayOutline': break;\n\t\t\t\t\tcase 'NoOrientation': break;\n\t\t\t\t\tcase 'AllowUsePivotTables': break;\n\t\t\t\t\tcase 'ZeroHeight': break;\n\t\t\t\t\tcase 'ViewableRange': break;\n\t\t\t\t\tcase 'Selection': break;\n\t\t\t\t\tcase 'ProtectContents': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* PivotTable */\n\t\t\t\tcase 'PivotTable': case 'PivotCache': switch(Rn[3]) {\n\t\t\t\t\tcase 'ImmediateItemsOnDrop': break;\n\t\t\t\t\tcase 'ShowPageMultipleItemLabel': break;\n\t\t\t\t\tcase 'CompactRowIndent': break;\n\t\t\t\t\tcase 'Location': break;\n\t\t\t\t\tcase 'PivotField': break;\n\t\t\t\t\tcase 'Orientation': break;\n\t\t\t\t\tcase 'LayoutForm': break;\n\t\t\t\t\tcase 'LayoutSubtotalLocation': break;\n\t\t\t\t\tcase 'LayoutCompactRow': break;\n\t\t\t\t\tcase 'Position': break;\n\t\t\t\t\tcase 'PivotItem': break;\n\t\t\t\t\tcase 'DataType': break;\n\t\t\t\t\tcase 'DataField': break;\n\t\t\t\t\tcase 'SourceName': break;\n\t\t\t\t\tcase 'ParentField': break;\n\t\t\t\t\tcase 'PTLineItems': break;\n\t\t\t\t\tcase 'PTLineItem': break;\n\t\t\t\t\tcase 'CountOfSameItems': break;\n\t\t\t\t\tcase 'Item': break;\n\t\t\t\t\tcase 'ItemType': break;\n\t\t\t\t\tcase 'PTSource': break;\n\t\t\t\t\tcase 'CacheIndex': break;\n\t\t\t\t\tcase 'ConsolidationReference': break;\n\t\t\t\t\tcase 'FileName': break;\n\t\t\t\t\tcase 'Reference': break;\n\t\t\t\t\tcase 'NoColumnGrand': break;\n\t\t\t\t\tcase 'NoRowGrand': break;\n\t\t\t\t\tcase 'BlankLineAfterItems': break;\n\t\t\t\t\tcase 'Hidden': break;\n\t\t\t\t\tcase 'Subtotal': break;\n\t\t\t\t\tcase 'BaseField': break;\n\t\t\t\t\tcase 'MapChildItems': break;\n\t\t\t\t\tcase 'Function': break;\n\t\t\t\t\tcase 'RefreshOnFileOpen': break;\n\t\t\t\t\tcase 'PrintSetTitles': break;\n\t\t\t\t\tcase 'MergeLabels': break;\n\t\t\t\t\tcase 'DefaultVersion': break;\n\t\t\t\t\tcase 'RefreshName': break;\n\t\t\t\t\tcase 'RefreshDate': break;\n\t\t\t\t\tcase 'RefreshDateCopy': break;\n\t\t\t\t\tcase 'VersionLastRefresh': break;\n\t\t\t\t\tcase 'VersionLastUpdate': break;\n\t\t\t\t\tcase 'VersionUpdateableMin': break;\n\t\t\t\t\tcase 'VersionRefreshableMin': break;\n\t\t\t\t\tcase 'Calculation': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* PageBreaks */\n\t\t\t\tcase 'PageBreaks': switch(Rn[3]) {\n\t\t\t\t\tcase 'ColBreaks': break;\n\t\t\t\t\tcase 'ColBreak': break;\n\t\t\t\t\tcase 'RowBreaks': break;\n\t\t\t\t\tcase 'RowBreak': break;\n\t\t\t\t\tcase 'ColStart': break;\n\t\t\t\t\tcase 'ColEnd': break;\n\t\t\t\t\tcase 'RowEnd': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* AutoFilter */\n\t\t\t\tcase 'AutoFilter': switch(Rn[3]) {\n\t\t\t\t\tcase 'AutoFilterColumn': break;\n\t\t\t\t\tcase 'AutoFilterCondition': break;\n\t\t\t\t\tcase 'AutoFilterAnd': break;\n\t\t\t\t\tcase 'AutoFilterOr': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* QueryTable */\n\t\t\t\tcase 'QueryTable': switch(Rn[3]) {\n\t\t\t\t\tcase 'Id': break;\n\t\t\t\t\tcase 'AutoFormatFont': break;\n\t\t\t\t\tcase 'AutoFormatPattern': break;\n\t\t\t\t\tcase 'QuerySource': break;\n\t\t\t\t\tcase 'QueryType': break;\n\t\t\t\t\tcase 'EnableRedirections': break;\n\t\t\t\t\tcase 'RefreshedInXl9': break;\n\t\t\t\t\tcase 'URLString': break;\n\t\t\t\t\tcase 'HTMLTables': break;\n\t\t\t\t\tcase 'Connection': break;\n\t\t\t\t\tcase 'CommandText': break;\n\t\t\t\t\tcase 'RefreshInfo': break;\n\t\t\t\t\tcase 'NoTitles': break;\n\t\t\t\t\tcase 'NextId': break;\n\t\t\t\t\tcase 'ColumnInfo': break;\n\t\t\t\t\tcase 'OverwriteCells': break;\n\t\t\t\t\tcase 'DoNotPromptForFile': break;\n\t\t\t\t\tcase 'TextWizardSettings': break;\n\t\t\t\t\tcase 'Source': break;\n\t\t\t\t\tcase 'Number': break;\n\t\t\t\t\tcase 'Decimal': break;\n\t\t\t\t\tcase 'ThousandSeparator': break;\n\t\t\t\t\tcase 'TrailingMinusNumbers': break;\n\t\t\t\t\tcase 'FormatSettings': break;\n\t\t\t\t\tcase 'FieldType': break;\n\t\t\t\t\tcase 'Delimiters': break;\n\t\t\t\t\tcase 'Tab': break;\n\t\t\t\t\tcase 'Comma': break;\n\t\t\t\t\tcase 'AutoFormatName': break;\n\t\t\t\t\tcase 'VersionLastEdit': break;\n\t\t\t\t\tcase 'VersionLastRefresh': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* Sorting */\n\t\t\t\tcase 'Sorting':\n\t\t\t\t/* ConditionalFormatting */\n\t\t\t\tcase 'ConditionalFormatting':\n\t\t\t\t/* DataValidation */\n\t\t\t\tcase 'DataValidation': switch(Rn[3]) {\n\t\t\t\t\tcase 'Range': break;\n\t\t\t\t\tcase 'Type': break;\n\t\t\t\t\tcase 'Min': break;\n\t\t\t\t\tcase 'Max': break;\n\t\t\t\t\tcase 'Sort': break;\n\t\t\t\t\tcase 'Descending': break;\n\t\t\t\t\tcase 'Order': break;\n\t\t\t\t\tcase 'CaseSensitive': break;\n\t\t\t\t\tcase 'Value': break;\n\t\t\t\t\tcase 'ErrorStyle': break;\n\t\t\t\t\tcase 'ErrorMessage': break;\n\t\t\t\t\tcase 'ErrorTitle': break;\n\t\t\t\t\tcase 'CellRangeList': break;\n\t\t\t\t\tcase 'InputMessage': break;\n\t\t\t\t\tcase 'InputTitle': break;\n\t\t\t\t\tcase 'ComboHide': break;\n\t\t\t\t\tcase 'InputHide': break;\n\t\t\t\t\tcase 'Condition': break;\n\t\t\t\t\tcase 'Qualifier': break;\n\t\t\t\t\tcase 'UseBlank': break;\n\t\t\t\t\tcase 'Value1': break;\n\t\t\t\t\tcase 'Value2': break;\n\t\t\t\t\tcase 'Format': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* MapInfo (schema) */\n\t\t\t\tcase 'MapInfo': case 'Schema': case 'data': switch(Rn[3]) {\n\t\t\t\t\tcase 'Map': break;\n\t\t\t\t\tcase 'Entry': break;\n\t\t\t\t\tcase 'Range': break;\n\t\t\t\t\tcase 'XPath': break;\n\t\t\t\t\tcase 'Field': break;\n\t\t\t\t\tcase 'XSDType': break;\n\t\t\t\t\tcase 'FilterOn': break;\n\t\t\t\t\tcase 'Aggregate': break;\n\t\t\t\t\tcase 'ElementType': break;\n\t\t\t\t\tcase 'AttributeType': break;\n\t\t\t\t/* These are from xsd (XML Schema Definition) */\n\t\t\t\t\tcase 'schema':\n\t\t\t\t\tcase 'element':\n\t\t\t\t\tcase 'complexType':\n\t\t\t\t\tcase 'datatype':\n\t\t\t\t\tcase 'all':\n\t\t\t\t\tcase 'attribute':\n\t\t\t\t\tcase 'extends': break;\n\n\t\t\t\t\tcase 'row': break;\n\t\t\t\t\tdefault: seen = false;\n\t\t\t\t} break;\n\n\t\t\t\t/* SmartTags (can be anything) */\n\t\t\t\tcase 'SmartTags': break;\n\n\t\t\t\tdefault: seen = false; break;\n\t\t\t}\n\t\t\tif(seen) break;\n\t\t\t/* CustomDocumentProperties */\n\t\t\tif(!state[state.length-1][1]) throw 'Unrecognized tag: ' + Rn[3] + \"|\" + state.join(\"|\");\n\t\t\tif(state[state.length-1][0]==='CustomDocumentProperties') {\n\t\t\t\tif(Rn[0].substr(-2) === \"/>\") break;\n\t\t\t\telse if(Rn[1]===\"/\") xlml_set_custprop(Custprops, Rn, cp, str.slice(pidx, Rn.index));\n\t\t\t\telse { cp = Rn; pidx = Rn.index + Rn[0].length; }\n\t\t\t\tbreak;\n\t\t\t}\n\t\t\tif(opts.WTF) throw 'Unrecognized tag: ' + Rn[3] + \"|\" + state.join(\"|\");\n\t}\n\tvar out = {};\n\tif(!opts.bookSheets && !opts.bookProps) out.Sheets = sheets;\n\tout.SheetNames = sheetnames;\n\tout.SSF = SSF.get_table();\n\tout.Props = Props;\n\tout.Custprops = Custprops;\n\treturn out;\n}\n\nfunction parse_xlml(data, opts) {\n\tfix_read_opts(opts=opts||{});\n\tswitch(opts.type||\"base64\") {\n\t\tcase \"base64\": return parse_xlml_xml(Base64.decode(data), opts);\n\t\tcase \"binary\": case \"buffer\": case \"file\": return parse_xlml_xml(data, opts);\n\t\tcase \"array\": return parse_xlml_xml(data.map(_chr).join(\"\"), opts);\n\t}\n}\n\nfunction write_xlml(wb, opts) { }\n\n/* [MS-OLEDS] 2.3.8 CompObjStream */\nfunction parse_compobj(obj) {\n\tvar v = {};\n\tvar o = obj.content;\n\n\t/* [MS-OLEDS] 2.3.7 CompObjHeader -- All fields MUST be ignored */\n\tvar l = 28, m;\n\tm = __lpstr(o, l);\n\tl += 4 + __readUInt32LE(o,l);\n\tv.UserType = m;\n\n\t/* [MS-OLEDS] 2.3.1 ClipboardFormatOrAnsiString */\n\tm = __readUInt32LE(o,l); l+= 4;\n\tswitch(m) {\n\t\tcase 0x00000000: break;\n\t\tcase 0xffffffff: case 0xfffffffe: l+=4; break;\n\t\tdefault:\n\t\t\tif(m > 0x190) throw new Error(\"Unsupported Clipboard: \" + m.toString(16));\n\t\t\tl += m;\n\t}\n\n\tm = __lpstr(o, l); l += m.length === 0 ? 0 : 5 + m.length; v.Reserved1 = m;\n\n\tif((m = __readUInt32LE(o,l)) !== 0x71b2e9f4) return v;\n\tthrow \"Unsupported Unicode Extension\";\n}\n\n/* 2.4.58 Continue logic */\nfunction slurp(R, blob, length, opts) {\n\tvar l = length;\n\tvar bufs = [];\n\tvar d = blob.slice(blob.l,blob.l+l);\n\tif(opts && opts.enc && opts.enc.insitu_decrypt) switch(R.n) {\n\tcase 'BOF': case 'FilePass': case 'FileLock': case 'InterfaceHdr': case 'RRDInfo': case 'RRDHead': case 'UsrExcl': break;\n\tdefault:\n\t\tif(d.length === 0) break;\n\t\topts.enc.insitu_decrypt(d);\n\t}\n\tbufs.push(d);\n\tblob.l += l;\n\tvar next = (XLSRecordEnum[__readUInt16LE(blob,blob.l)]);\n\twhile(next != null && next.n === 'Continue') {\n\t\tl = __readUInt16LE(blob,blob.l+2);\n\t\tbufs.push(blob.slice(blob.l+4,blob.l+4+l));\n\t\tblob.l += 4+l;\n\t\tnext = (XLSRecordEnum[__readUInt16LE(blob, blob.l)]);\n\t}\n\tvar b = bconcat(bufs);\n\tprep_blob(b, 0);\n\tvar ll = 0; b.lens = [];\n\tfor(var j = 0; j < bufs.length; ++j) { b.lens.push(ll); ll += bufs[j].length; }\n\treturn R.f(b, b.length, opts);\n}\n\nfunction safe_format_xf(p, opts, date1904) {\n\tif(!p.XF) return;\n\ttry {\n\t\tvar fmtid = p.XF.ifmt||0;\n\t\tif(p.t === 'e') { p.w = p.w || BErr[p.v]; }\n\t\telse if(fmtid === 0) {\n\t\t\tif(p.t === 'n') {\n\t\t\t\tif((p.v|0) === p.v) p.w = SSF._general_int(p.v);\n\t\t\t\telse p.w = SSF._general_num(p.v);\n\t\t\t}\n\t\t\telse p.w = SSF._general(p.v);\n\t\t}\n\t\telse p.w = SSF.format(fmtid,p.v, {date1904:date1904||false});\n\t\tif(opts.cellNF) p.z = SSF._table[fmtid];\n\t} catch(e) { if(opts.WTF) throw e; }\n}\n\nfunction make_cell(val, ixfe, t) {\n\treturn {v:val, ixfe:ixfe, t:t};\n}\n\n// 2.3.2\nfunction parse_workbook(blob, options) {\n\tvar wb = {opts:{}};\n\tvar Sheets = {};\n\tvar out = {};\n\tvar Directory = {};\n\tvar found_sheet = false;\n\tvar range = {};\n\tvar last_formula = null;\n\tvar sst = [];\n\tvar cur_sheet = \"\";\n\tvar Preamble = {};\n\tvar lastcell, last_cell, cc, cmnt, rng, rngC, rngR;\n\tvar shared_formulae = {};\n\tvar array_formulae = []; /* TODO: something more clever */\n\tvar temp_val;\n\tvar country;\n\tvar cell_valid = true;\n\tvar XFs = []; /* XF records */\n\tvar palette = [];\n\tvar get_rgb = function getrgb(icv) {\n\t\tif(icv < 8) return XLSIcv[icv];\n\t\tif(icv < 64) return palette[icv-8] || XLSIcv[icv];\n\t\treturn XLSIcv[icv];\n\t};\n\tvar process_cell_style = function pcs(cell, line) {\n\t\tvar xfd = line.XF.data;\n\t\tif(!xfd || !xfd.patternType) return;\n\t\tline.s = {};\n\t\tline.s.patternType = xfd.patternType;\n\t\tvar t;\n\t\tif((t = rgb2Hex(get_rgb(xfd.icvFore)))) { line.s.fgColor = {rgb:t}; }\n\t\tif((t = rgb2Hex(get_rgb(xfd.icvBack)))) { line.s.bgColor = {rgb:t}; }\n\t};\n\tvar addcell = function addcell(cell, line, options) {\n\t\tif(!cell_valid) return;\n\t\tif(options.cellStyles && line.XF && line.XF.data) process_cell_style(cell, line);\n\t\tlastcell = cell;\n\t\tlast_cell = encode_cell(cell);\n\t\tif(range.s) {\n\t\t\tif(cell.r < range.s.r) range.s.r = cell.r;\n\t\t\tif(cell.c < range.s.c) range.s.c = cell.c;\n\t\t}\n\t\tif(range.e) {\n\t\t\tif(cell.r + 1 > range.e.r) range.e.r = cell.r + 1;\n\t\t\tif(cell.c + 1 > range.e.c) range.e.c = cell.c + 1;\n\t\t}\n\t\tif(options.sheetRows && lastcell.r >= options.sheetRows) cell_valid = false;\n\t\telse out[last_cell] = line;\n\t};\n\tvar opts = {\n\t\tenc: false, // encrypted\n\t\tsbcch: 0, // cch in the preceding SupBook\n\t\tsnames: [], // sheetnames\n\t\tsharedf: shared_formulae, // shared formulae by address\n\t\tarrayf: array_formulae, // array formulae array\n\t\trrtabid: [], // RRTabId\n\t\tlastuser: \"\", // Last User from WriteAccess\n\t\tbiff: 8, // BIFF version\n\t\tcodepage: 0, // CP from CodePage record\n\t\twinlocked: 0, // fLockWn from WinProtect\n\t\twtf: false\n\t};\n\tif(options.password) opts.password = options.password;\n\tvar mergecells = [];\n\tvar objects = [];\n\tvar supbooks = [[]]; // 1-indexed, will hold extern names\n\tvar sbc = 0, sbci = 0, sbcli = 0;\n\tsupbooks.SheetNames = opts.snames;\n\tsupbooks.sharedf = opts.sharedf;\n\tsupbooks.arrayf = opts.arrayf;\n\tvar last_Rn = '';\n\tvar file_depth = 0; /* TODO: make a real stack */\n\n\t/* explicit override for some broken writers */\n\topts.codepage = 1200;\n\tset_cp(1200);\n\n\twhile(blob.l < blob.length - 1) {\n\t\tvar s = blob.l;\n\t\tvar RecordType = blob.read_shift(2);\n\t\tif(RecordType === 0 && last_Rn === 'EOF') break;\n\t\tvar length = (blob.l === blob.length ? 0 : blob.read_shift(2)), y;\n\t\tvar R = XLSRecordEnum[RecordType];\n\t\tif(R && R.f) {\n\t\t\tif(options.bookSheets) {\n\t\t\t\tif(last_Rn === 'BoundSheet8' && R.n !== 'BoundSheet8') break;\n\t\t\t}\n\t\t\tlast_Rn = R.n;\n\t\t\tif(R.r === 2 || R.r == 12) {\n\t\t\t\tvar rt = blob.read_shift(2); length -= 2;\n\t\t\t\tif(!opts.enc && rt !== RecordType) throw \"rt mismatch\";\n\t\t\t\tif(R.r == 12){ blob.l += 10; length -= 10; } // skip FRT\n\t\t\t}\n\t\t\t//console.error(R,blob.l,length,blob.length);\n\t\t\tvar val;\n\t\t\tif(R.n === 'EOF') val = R.f(blob, length, opts);\n\t\t\telse val = slurp(R, blob, length, opts);\n\t\t\tvar Rn = R.n;\n\t\t\t/* BIFF5 overrides */\n\t\t\tif(opts.biff === 5 || opts.biff === 2) switch(Rn) {\n\t\t\t\tcase 'Lbl': Rn = 'Label'; break;\n\t\t\t}\n\t\t\t/* nested switch statements to workaround V8 128 limit */\n\t\t\tswitch(Rn) {\n\t\t\t\t/* Workbook Options */\n\t\t\t\tcase 'Date1904': wb.opts.Date1904 = val; break;\n\t\t\t\tcase 'WriteProtect': wb.opts.WriteProtect = true; break;\n\t\t\t\tcase 'FilePass':\n\t\t\t\t\tif(!opts.enc) blob.l = 0;\n\t\t\t\t\topts.enc = val;\n\t\t\t\t\tif(opts.WTF) console.error(val);\n\t\t\t\t\tif(!options.password) throw new Error(\"File is password-protected\");\n\t\t\t\t\tif(val.Type !== 0) throw new Error(\"Encryption scheme unsupported\");\n\t\t\t\t\tif(!val.valid) throw new Error(\"Password is incorrect\");\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'WriteAccess': opts.lastuser = val; break;\n\t\t\t\tcase 'FileSharing': break; //TODO\n\t\t\t\tcase 'CodePage':\n\t\t\t\t\t/* overrides based on test cases */\n\t\t\t\t\tif(val === 0x5212) val = 1200;\n\t\t\t\t\telse if(val === 0x8001) val = 1252;\n\t\t\t\t\topts.codepage = val;\n\t\t\t\t\tset_cp(val);\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'RRTabId': opts.rrtabid = val; break;\n\t\t\t\tcase 'WinProtect': opts.winlocked = val; break;\n\t\t\t\tcase 'Template': break; // TODO\n\t\t\t\tcase 'RefreshAll': wb.opts.RefreshAll = val; break;\n\t\t\t\tcase 'BookBool': break; // TODO\n\t\t\t\tcase 'UsesELFs': /* if(val) console.error(\"Unsupported ELFs\"); */ break;\n\t\t\t\tcase 'MTRSettings': {\n\t\t\t\t\tif(val[0] && val[1]) throw \"Unsupported threads: \" + val;\n\t\t\t\t} break; // TODO: actually support threads\n\t\t\t\tcase 'CalcCount': wb.opts.CalcCount = val; break;\n\t\t\t\tcase 'CalcDelta': wb.opts.CalcDelta = val; break;\n\t\t\t\tcase 'CalcIter': wb.opts.CalcIter = val; break;\n\t\t\t\tcase 'CalcMode': wb.opts.CalcMode = val; break;\n\t\t\t\tcase 'CalcPrecision': wb.opts.CalcPrecision = val; break;\n\t\t\t\tcase 'CalcSaveRecalc': wb.opts.CalcSaveRecalc = val; break;\n\t\t\t\tcase 'CalcRefMode': opts.CalcRefMode = val; break; // TODO: implement R1C1\n\t\t\t\tcase 'Uncalced': break;\n\t\t\t\tcase 'ForceFullCalculation': wb.opts.FullCalc = val; break;\n\t\t\t\tcase 'WsBool': break; // TODO\n\t\t\t\tcase 'XF': XFs.push(val); break;\n\t\t\t\tcase 'ExtSST': break; // TODO\n\t\t\t\tcase 'BookExt': break; // TODO\n\t\t\t\tcase 'RichTextStream': break;\n\t\t\t\tcase 'BkHim': break;\n\n\t\t\t\tcase 'SupBook': supbooks[++sbc] = [val]; sbci = 0; break;\n\t\t\t\tcase 'ExternName': supbooks[sbc][++sbci] = val; break;\n\t\t\t\tcase 'Index': break; // TODO\n\t\t\t\tcase 'Lbl': supbooks[0][++sbcli] = val; break;\n\t\t\t\tcase 'ExternSheet': supbooks[sbc] = supbooks[sbc].concat(val); sbci += val.length; break;\n\n\t\t\t\tcase 'Protect': out[\"!protect\"] = val; break; /* for sheet or book */\n\t\t\t\tcase 'Password': if(val !== 0 && opts.WTF) console.error(\"Password verifier: \" + val); break;\n\t\t\t\tcase 'Prot4Rev': case 'Prot4RevPass': break; /*TODO: Revision Control*/\n\n\t\t\t\tcase 'BoundSheet8': {\n\t\t\t\t\tDirectory[val.pos] = val;\n\t\t\t\t\topts.snames.push(val.name);\n\t\t\t\t} break;\n\t\t\t\tcase 'EOF': {\n\t\t\t\t\tif(--file_depth) break;\n\t\t\t\t\tif(range.e) {\n\t\t\t\t\t\tout[\"!range\"] = range;\n\t\t\t\t\t\tif(range.e.r > 0 && range.e.c > 0) {\n\t\t\t\t\t\t\trange.e.r--; range.e.c--;\n\t\t\t\t\t\t\tout[\"!ref\"] = encode_range(range);\n\t\t\t\t\t\t\trange.e.r++; range.e.c++;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif(mergecells.length > 0) out[\"!merges\"] = mergecells;\n\t\t\t\t\t\tif(objects.length > 0) out[\"!objects\"] = objects;\n\t\t\t\t\t}\n\t\t\t\t\tif(cur_sheet === \"\") Preamble = out; else Sheets[cur_sheet] = out;\n\t\t\t\t\tout = {};\n\t\t\t\t} break;\n\t\t\t\tcase 'BOF': {\n\t\t\t\t\tif(opts.biff !== 8);\n\t\t\t\t\telse if(val.BIFFVer === 0x0500) opts.biff = 5;\n\t\t\t\t\telse if(val.BIFFVer === 0x0002) opts.biff = 2;\n\t\t\t\t\telse if(val.BIFFVer === 0x0007) opts.biff = 2;\n\t\t\t\t\tif(file_depth++) break;\n\t\t\t\t\tcell_valid = true;\n\t\t\t\t\tout = {};\n\t\t\t\t\tif(opts.biff === 2) {\n\t\t\t\t\t\tif(cur_sheet === \"\") cur_sheet = \"Sheet1\";\n\t\t\t\t\t\trange = {s:{r:0,c:0},e:{r:0,c:0}};\n\t\t\t\t\t}\n\t\t\t\t\telse cur_sheet = (Directory[s] || {name:\"\"}).name;\n\t\t\t\t\tmergecells = [];\n\t\t\t\t\tobjects = [];\n\t\t\t\t} break;\n\t\t\t\tcase 'Number': case 'BIFF2NUM': {\n\t\t\t\t\ttemp_val = {ixfe: val.ixfe, XF: XFs[val.ixfe], v:val.val, t:'n'};\n\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\taddcell({c:val.c, r:val.r}, temp_val, options);\n\t\t\t\t} break;\n\t\t\t\tcase 'BoolErr': {\n\t\t\t\t\ttemp_val = {ixfe: val.ixfe, XF: XFs[val.ixfe], v:val.val, t:val.t};\n\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\taddcell({c:val.c, r:val.r}, temp_val, options);\n\t\t\t\t} break;\n\t\t\t\tcase 'RK': {\n\t\t\t\t\ttemp_val = {ixfe: val.ixfe, XF: XFs[val.ixfe], v:val.rknum, t:'n'};\n\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\taddcell({c:val.c, r:val.r}, temp_val, options);\n\t\t\t\t} break;\n\t\t\t\tcase 'MulRk': {\n\t\t\t\t\tfor(var j = val.c; j <= val.C; ++j) {\n\t\t\t\t\t\tvar ixfe = val.rkrec[j-val.c][0];\n\t\t\t\t\t\ttemp_val= {ixfe:ixfe, XF:XFs[ixfe], v:val.rkrec[j-val.c][1], t:'n'};\n\t\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\t\taddcell({c:j, r:val.r}, temp_val, options);\n\t\t\t\t\t}\n\t\t\t\t} break;\n\t\t\t\tcase 'Formula': {\n\t\t\t\t\tswitch(val.val) {\n\t\t\t\t\t\tcase 'String': last_formula = val; break;\n\t\t\t\t\t\tcase 'Array Formula': throw \"Array Formula unsupported\";\n\t\t\t\t\t\tdefault:\n\t\t\t\t\t\t\ttemp_val = {v:val.val, ixfe:val.cell.ixfe, t:val.tt};\n\t\t\t\t\t\t\ttemp_val.XF = XFs[temp_val.ixfe];\n\t\t\t\t\t\t\tif(options.cellFormula) temp_val.f = \"=\"+stringify_formula(val.formula,range,val.cell,supbooks, opts);\n\t\t\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\t\t\taddcell(val.cell, temp_val, options);\n\t\t\t\t\t\t\tlast_formula = val;\n\t\t\t\t\t}\n\t\t\t\t} break;\n\t\t\t\tcase 'String': {\n\t\t\t\t\tif(last_formula) {\n\t\t\t\t\t\tlast_formula.val = val;\n\t\t\t\t\t\ttemp_val = {v:last_formula.val, ixfe:last_formula.cell.ixfe, t:'s'};\n\t\t\t\t\t\ttemp_val.XF = XFs[temp_val.ixfe];\n\t\t\t\t\t\tif(options.cellFormula) temp_val.f = \"=\"+stringify_formula(last_formula.formula, range, last_formula.cell, supbooks, opts);\n\t\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\t\taddcell(last_formula.cell, temp_val, options);\n\t\t\t\t\t\tlast_formula = null;\n\t\t\t\t\t}\n\t\t\t\t} break;\n\t\t\t\tcase 'Array': {\n\t\t\t\t\tarray_formulae.push(val);\n\t\t\t\t} break;\n\t\t\t\tcase 'ShrFmla': {\n\t\t\t\t\tif(!cell_valid) break;\n\t\t\t\t\t//if(options.cellFormula) out[last_cell].f = stringify_formula(val[0], range, lastcell, supbooks, opts);\n\t\t\t\t\t/* TODO: capture range */\n\t\t\t\t\tshared_formulae[encode_cell(last_formula.cell)]= val[0];\n\t\t\t\t} break;\n\t\t\t\tcase 'LabelSst':\n\t\t\t\t\t//temp_val={v:sst[val.isst].t, ixfe:val.ixfe, t:'s'};\n\t\t\t\t\ttemp_val=make_cell(sst[val.isst].t, val.ixfe, 's');\n\t\t\t\t\ttemp_val.XF = XFs[temp_val.ixfe];\n\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\taddcell({c:val.c, r:val.r}, temp_val, options);\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'Label': case 'BIFF2STR':\n\t\t\t\t\t/* Some writers erroneously write Label */\n\t\t\t\t\ttemp_val=make_cell(val.val, val.ixfe, 's');\n\t\t\t\t\ttemp_val.XF = XFs[temp_val.ixfe];\n\t\t\t\t\tif(temp_val.XF) safe_format_xf(temp_val, options, wb.opts.Date1904);\n\t\t\t\t\taddcell({c:val.c, r:val.r}, temp_val, options);\n\t\t\t\t\tbreak;\n\t\t\t\tcase 'Dimensions': {\n\t\t\t\t\tif(file_depth === 1) range = val; /* TODO: stack */\n\t\t\t\t} break;\n\t\t\t\tcase 'SST': {\n\t\t\t\t\tsst = val;\n\t\t\t\t} break;\n\t\t\t\tcase 'Format': { /* val = [id, fmt] */\n\t\t\t\t\tSSF.load(val[1], val[0]);\n\t\t\t\t} break;\n\n\t\t\t\tcase 'MergeCells': mergecells = mergecells.concat(val); break;\n\n\t\t\t\tcase 'Obj': objects[val.cmo[0]] = opts.lastobj = val; break;\n\t\t\t\tcase 'TxO': opts.lastobj.TxO = val; break;\n\n\t\t\t\tcase 'HLink': {\n\t\t\t\t\tfor(rngR = val[0].s.r; rngR <= val[0].e.r; ++rngR)\n\t\t\t\t\t\tfor(rngC = val[0].s.c; rngC <= val[0].e.c; ++rngC)\n\t\t\t\t\t\t\tif(out[encode_cell({c:rngC,r:rngR})])\n\t\t\t\t\t\t\t\tout[encode_cell({c:rngC,r:rngR})].l = val[1];\n\t\t\t\t} break;\n\t\t\t\tcase 'HLinkTooltip': {\n\t\t\t\t\tfor(rngR = val[0].s.r; rngR <= val[0].e.r; ++rngR)\n\t\t\t\t\t\tfor(rngC = val[0].s.c; rngC <= val[0].e.c; ++rngC)\n\t\t\t\t\t\t\tif(out[encode_cell({c:rngC,r:rngR})])\n\t\t\t\t\t\t\t\tout[encode_cell({c:rngC,r:rngR})].l.tooltip = val[1];\n\t\t\t\t} break;\n\n\t\t\t\t/* Comments */\n\t\t\t\tcase 'Note': {\n\t\t\t\t\tif(opts.biff <= 5 && opts.biff >= 2) break; /* TODO: BIFF5 */\n\t\t\t\t\tcc = out[encode_cell(val[0])];\n\t\t\t\t\tvar noteobj = objects[val[2]];\n\t\t\t\t\tif(!cc) break;\n\t\t\t\t\tif(!cc.c) cc.c = [];\n\t\t\t\t\tcmnt = {a:val[1],t:noteobj.TxO.t};\n\t\t\t\t\tcc.c.push(cmnt);\n\t\t\t\t} break;\n\n\t\t\t\tdefault: switch(R.n) { /* nested */\n\t\t\t\tcase 'ClrtClient': break;\n\t\t\t\tcase 'XFExt': update_xfext(XFs[val.ixfe], val.ext); break;\n\n\t\t\t\tcase 'NameCmt': break;\n\t\t\t\tcase 'Header': break; // TODO\n\t\t\t\tcase 'Footer': break; // TODO\n\t\t\t\tcase 'HCenter': break; // TODO\n\t\t\t\tcase 'VCenter': break; // TODO\n\t\t\t\tcase 'Pls': break; // TODO\n\t\t\t\tcase 'Setup': break; // TODO\n\t\t\t\tcase 'DefColWidth': break; // TODO\n\t\t\t\tcase 'GCW': break;\n\t\t\t\tcase 'LHRecord': break;\n\t\t\t\tcase 'ColInfo': break; // TODO\n\t\t\t\tcase 'Row': break; // TODO\n\t\t\t\tcase 'DBCell': break; // TODO\n\t\t\t\tcase 'MulBlank': break; // TODO\n\t\t\t\tcase 'EntExU2': break; // TODO\n\t\t\t\tcase 'SxView': break; // TODO\n\t\t\t\tcase 'Sxvd': break; // TODO\n\t\t\t\tcase 'SXVI': break; // TODO\n\t\t\t\tcase 'SXVDEx': break; // TODO\n\t\t\t\tcase 'SxIvd': break; // TODO\n\t\t\t\tcase 'SXDI': break; // TODO\n\t\t\t\tcase 'SXLI': break; // TODO\n\t\t\t\tcase 'SXEx': break; // TODO\n\t\t\t\tcase 'QsiSXTag': break; // TODO\n\t\t\t\tcase 'Selection': break;\n\t\t\t\tcase 'Feat': break;\n\t\t\t\tcase 'FeatHdr': case 'FeatHdr11': break;\n\t\t\t\tcase 'Feature11': case 'Feature12': case 'List12': break;\n\t\t\t\tcase 'Blank': break;\n\t\t\t\tcase 'Country': country = val; break;\n\t\t\t\tcase 'RecalcId': break;\n\t\t\t\tcase 'DefaultRowHeight': case 'DxGCol': break; // TODO: htmlify\n\t\t\t\tcase 'Fbi': case 'Fbi2': case 'GelFrame': break;\n\t\t\t\tcase 'Font': break; // TODO\n\t\t\t\tcase 'XFCRC': break; // TODO\n\t\t\t\tcase 'Style': break; // TODO\n\t\t\t\tcase 'StyleExt': break; // TODO\n\t\t\t\tcase 'Palette': palette = val; break; // TODO\n\t\t\t\tcase 'Theme': break; // TODO\n\t\t\t\t/* Protection */\n\t\t\t\tcase 'ScenarioProtect': break;\n\t\t\t\tcase 'ObjProtect': break;\n\n\t\t\t\t/* Conditional Formatting */\n\t\t\t\tcase 'CondFmt12': break;\n\n\t\t\t\t/* Table */\n\t\t\t\tcase 'Table': break; // TODO\n\t\t\t\tcase 'TableStyles': break; // TODO\n\t\t\t\tcase 'TableStyle': break; // TODO\n\t\t\t\tcase 'TableStyleElement': break; // TODO\n\n\t\t\t\t/* PivotTable */\n\t\t\t\tcase 'SXStreamID': break; // TODO\n\t\t\t\tcase 'SXVS': break; // TODO\n\t\t\t\tcase 'DConRef': break; // TODO\n\t\t\t\tcase 'SXAddl': break; // TODO\n\t\t\t\tcase 'DConBin': break; // TODO\n\t\t\t\tcase 'DConName': break; // TODO\n\t\t\t\tcase 'SXPI': break; // TODO\n\t\t\t\tcase 'SxFormat': break; // TODO\n\t\t\t\tcase 'SxSelect': break; // TODO\n\t\t\t\tcase 'SxRule': break; // TODO\n\t\t\t\tcase 'SxFilt': break; // TODO\n\t\t\t\tcase 'SxItm': break; // TODO\n\t\t\t\tcase 'SxDXF': break; // TODO\n\n\t\t\t\t/* Scenario Manager */\n\t\t\t\tcase 'ScenMan': break;\n\n\t\t\t\t/* Data Consolidation */\n\t\t\t\tcase 'DCon': break;\n\n\t\t\t\t/* Watched Cell */\n\t\t\t\tcase 'CellWatch': break;\n\n\t\t\t\t/* Print Settings */\n\t\t\t\tcase 'PrintRowCol': break;\n\t\t\t\tcase 'PrintGrid': break;\n\t\t\t\tcase 'PrintSize': break;\n\n\t\t\t\tcase 'XCT': break;\n\t\t\t\tcase 'CRN': break;\n\n\t\t\t\tcase 'Scl': {\n\t\t\t\t\t//console.log(\"Zoom Level:\", val[0]/val[1],val);\n\t\t\t\t} break;\n\t\t\t\tcase 'SheetExt': {\n\n\t\t\t\t} break;\n\t\t\t\tcase 'SheetExtOptional': {\n\n\t\t\t\t} break;\n\n\t\t\t\t/* VBA */\n\t\t\t\tcase 'ObNoMacros': {\n\n\t\t\t\t} break;\n\t\t\t\tcase 'ObProj': {\n\n\t\t\t\t} break;\n\t\t\t\tcase 'CodeName': {\n\n\t\t\t\t} break;\n\t\t\t\tcase 'GUIDTypeLib': {\n\n\t\t\t\t} break;\n\n\t\t\t\tcase 'WOpt': break; // TODO: WTF?\n\t\t\t\tcase 'PhoneticInfo': break;\n\n\t\t\t\tcase 'OleObjectSize': break;\n\n\t\t\t\t/* Differential Formatting */\n\t\t\t\tcase 'DXF': case 'DXFN': case 'DXFN12': case 'DXFN12List': case 'DXFN12NoCB': break;\n\n\t\t\t\t/* Data Validation */\n\t\t\t\tcase 'Dv': case 'DVal': break;\n\n\t\t\t\t/* Data Series */\n\t\t\t\tcase 'BRAI': case 'Series': case 'SeriesText': break;\n\n\t\t\t\t/* Data Connection */\n\t\t\t\tcase 'DConn': break;\n\t\t\t\tcase 'DbOrParamQry': break;\n\t\t\t\tcase 'DBQueryExt': break;\n\n\t\t\t\t/* Formatting */\n\t\t\t\tcase 'IFmtRecord': break;\n\t\t\t\tcase 'CondFmt': case 'CF': case 'CF12': case 'CFEx': break;\n\n\t\t\t\t/* Explicitly Ignored */\n\t\t\t\tcase 'Excel9File': break;\n\t\t\t\tcase 'Units': break;\n\t\t\t\tcase 'InterfaceHdr': case 'Mms': case 'InterfaceEnd': case 'DSF': case 'BuiltInFnGroupCount':\n\t\t\t\t/* View Stuff */\n\t\t\t\tcase 'Window1': case 'Window2': case 'HideObj': case 'GridSet': case 'Guts':\n\t\t\t\tcase 'UserBView': case 'UserSViewBegin': case 'UserSViewEnd':\n\t\t\t\tcase 'Pane': break;\n\t\t\t\tdefault: switch(R.n) { /* nested */\n\t\t\t\t/* Chart */\n\t\t\t\tcase 'Dat':\n\t\t\t\tcase 'Begin': case 'End':\n\t\t\t\tcase 'StartBlock': case 'EndBlock':\n\t\t\t\tcase 'Frame': case 'Area':\n\t\t\t\tcase 'Axis': case 'AxisLine': case 'Tick': break;\n\t\t\t\tcase 'AxesUsed':\n\t\t\t\tcase 'CrtLayout12': case 'CrtLayout12A': case 'CrtLink': case 'CrtLine': case 'CrtMlFrt': case 'CrtMlFrtContinue': break;\n\t\t\t\tcase 'LineFormat': case 'AreaFormat':\n\t\t\t\tcase 'Chart': case 'Chart3d': case 'Chart3DBarShape': case 'ChartFormat': case 'ChartFrtInfo': break;\n\t\t\t\tcase 'PlotArea': case 'PlotGrowth': break;\n\t\t\t\tcase 'SeriesList': case 'SerParent': case 'SerAuxTrend': break;\n\t\t\t\tcase 'DataFormat': case 'SerToCrt': case 'FontX': break;\n\t\t\t\tcase 'CatSerRange': case 'AxcExt': case 'SerFmt': break;\n\t\t\t\tcase 'ShtProps': break;\n\t\t\t\tcase 'DefaultText': case 'Text': case 'CatLab': break;\n\t\t\t\tcase 'DataLabExtContents': break;\n\t\t\t\tcase 'Legend': case 'LegendException': break;\n\t\t\t\tcase 'Pie': case 'Scatter': break;\n\t\t\t\tcase 'PieFormat': case 'MarkerFormat': break;\n\t\t\t\tcase 'StartObject': case 'EndObject': break;\n\t\t\t\tcase 'AlRuns': case 'ObjectLink': break;\n\t\t\t\tcase 'SIIndex': break;\n\t\t\t\tcase 'AttachedLabel': case 'YMult': break;\n\n\t\t\t\t/* Chart Group */\n\t\t\t\tcase 'Line': case 'Bar': break;\n\t\t\t\tcase 'Surf': break;\n\n\t\t\t\t/* Axis Group */\n\t\t\t\tcase 'AxisParent': break;\n\t\t\t\tcase 'Pos': break;\n\t\t\t\tcase 'ValueRange': break;\n\n\t\t\t\t/* Pivot Chart */\n\t\t\t\tcase 'SXViewEx9': break; // TODO\n\t\t\t\tcase 'SXViewLink': break;\n\t\t\t\tcase 'PivotChartBits': break;\n\t\t\t\tcase 'SBaseRef': break;\n\t\t\t\tcase 'TextPropsStream': break;\n\n\t\t\t\t/* Chart Misc */\n\t\t\t\tcase 'LnExt': break;\n\t\t\t\tcase 'MkrExt': break;\n\t\t\t\tcase 'CrtCoopt': break;\n\n\t\t\t\t/* Query Table */\n\t\t\t\tcase 'Qsi': case 'Qsif': case 'Qsir': case 'QsiSXTag': break;\n\t\t\t\tcase 'TxtQry': break;\n\n\t\t\t\t/* Filter */\n\t\t\t\tcase 'FilterMode': break;\n\t\t\t\tcase 'AutoFilter': case 'AutoFilterInfo': break;\n\t\t\t\tcase 'AutoFilter12': break;\n\t\t\t\tcase 'DropDownObjIds': break;\n\t\t\t\tcase 'Sort': break;\n\t\t\t\tcase 'SortData': break;\n\n\t\t\t\t/* Drawing */\n\t\t\t\tcase 'ShapePropsStream': break;\n\t\t\t\tcase 'MsoDrawing': case 'MsoDrawingGroup': case 'MsoDrawingSelection': break;\n\t\t\t\tcase 'ImData': break;\n\t\t\t\t/* Pub Stuff */\n\t\t\t\tcase 'WebPub': case 'AutoWebPub':\n\n\t\t\t\t/* Print Stuff */\n\t\t\t\tcase 'RightMargin': case 'LeftMargin': case 'TopMargin': case 'BottomMargin':\n\t\t\t\tcase 'HeaderFooter': case 'HFPicture': case 'PLV':\n\t\t\t\tcase 'HorizontalPageBreaks': case 'VerticalPageBreaks':\n\t\t\t\t/* Behavioral */\n\t\t\t\tcase 'Backup': case 'CompressPictures': case 'Compat12': break;\n\n\t\t\t\t/* Should not Happen */\n\t\t\t\tcase 'Continue': case 'ContinueFrt12': break;\n\n\t\t\t\t/* Future Records */\n\t\t\t\tcase 'FrtFontList': case 'FrtWrapper': break;\n\n\t\t\t\t/* BIFF5 records */\n\t\t\t\tcase 'ExternCount': break;\n\t\t\t\tcase 'RString': break;\n\t\t\t\tcase 'TabIdConf': case 'Radar': case 'RadarArea': case 'DropBar': case 'Intl': case 'CoordList': case 'SerAuxErrBar': break;\n\n\t\t\t\tdefault: switch(R.n) { /* nested */\n\t\t\t\t/* Miscellaneous */\n\t\t\t\tcase 'SCENARIO': case 'DConBin': case 'PicF': case 'DataLabExt':\n\t\t\t\tcase 'Lel': case 'BopPop': case 'BopPopCustom': case 'RealTimeData':\n\t\t\t\tcase 'Name': break;\n\t\t\t\tdefault: if(options.WTF) throw 'Unrecognized Record ' + R.n;\n\t\t\t}}}}\n\t\t} else blob.l += length;\n\t}\n\tvar sheetnamesraw = opts.biff === 2 ? ['Sheet1'] : Object.keys(Directory).sort(function(a,b) { return Number(a) - Number(b); }).map(function(x){return Directory[x].name;});\n\tvar sheetnames = sheetnamesraw.slice();\n\twb.Directory=sheetnamesraw;\n\twb.SheetNames=sheetnamesraw;\n\tif(!options.bookSheets) wb.Sheets=Sheets;\n\twb.Preamble=Preamble;\n\twb.Strings = sst;\n\twb.SSF = SSF.get_table();\n\tif(opts.enc) wb.Encryption = opts.enc;\n\twb.Metadata = {};\n\tif(country !== undefined) wb.Metadata.Country = country;\n\treturn wb;\n}\n\nfunction parse_xlscfb(cfb, options) {\nif(!options) options = {};\nfix_read_opts(options);\nreset_cp();\nvar CompObj, Summary, Workbook;\nif(cfb.find) {\n\tCompObj = cfb.find('!CompObj');\n\tSummary = cfb.find('!SummaryInformation');\n\tWorkbook = cfb.find('/Workbook');\n} else {\n\tprep_blob(cfb, 0);\n\tWorkbook = {content: cfb};\n}\n\nif(!Workbook) Workbook = cfb.find('/Book');\nvar CompObjP, SummaryP, WorkbookP;\n\nif(CompObj) CompObjP = parse_compobj(CompObj);\nif(options.bookProps && !options.bookSheets) WorkbookP = {};\nelse {\n\tif(Workbook) WorkbookP = parse_workbook(Workbook.content, options, !!Workbook.find);\n\telse throw new Error(\"Cannot find Workbook stream\");\n}\n\nif(cfb.find) parse_props(cfb);\n\nvar props = {};\nfor(var y in cfb.Summary) props[y] = cfb.Summary[y];\nfor(y in cfb.DocSummary) props[y] = cfb.DocSummary[y];\nWorkbookP.Props = WorkbookP.Custprops = props; /* TODO: split up properties */\nif(options.bookFiles) WorkbookP.cfb = cfb;\nWorkbookP.CompObjP = CompObjP;\nreturn WorkbookP;\n}\n\n/* TODO: WTF */\nfunction parse_props(cfb) {\n\t/* [MS-OSHARED] 2.3.3.2.2 Document Summary Information Property Set */\n\tvar DSI = cfb.find('!DocumentSummaryInformation');\n\tif(DSI) try { cfb.DocSummary = parse_PropertySetStream(DSI, DocSummaryPIDDSI); } catch(e) {}\n\n\t/* [MS-OSHARED] 2.3.3.2.1 Summary Information Property Set*/\n\tvar SI = cfb.find('!SummaryInformation');\n\tif(SI) try { cfb.Summary = parse_PropertySetStream(SI, SummaryPIDSI); } catch(e) {}\n}\n\n/* [MS-XLSB] 2.3 Record Enumeration */\nvar XLSBRecordEnum = {\n\t0x0000: { n:\"BrtRowHdr\", f:parse_BrtRowHdr },\n\t0x0001: { n:\"BrtCellBlank\", f:parse_BrtCellBlank },\n\t0x0002: { n:\"BrtCellRk\", f:parse_BrtCellRk },\n\t0x0003: { n:\"BrtCellError\", f:parse_BrtCellError },\n\t0x0004: { n:\"BrtCellBool\", f:parse_BrtCellBool },\n\t0x0005: { n:\"BrtCellReal\", f:parse_BrtCellReal },\n\t0x0006: { n:\"BrtCellSt\", f:parse_BrtCellSt },\n\t0x0007: { n:\"BrtCellIsst\", f:parse_BrtCellIsst },\n\t0x0008: { n:\"BrtFmlaString\", f:parse_BrtFmlaString },\n\t0x0009: { n:\"BrtFmlaNum\", f:parse_BrtFmlaNum },\n\t0x000A: { n:\"BrtFmlaBool\", f:parse_BrtFmlaBool },\n\t0x000B: { n:\"BrtFmlaError\", f:parse_BrtFmlaError },\n\t0x0010: { n:\"BrtFRTArchID$\", f:parse_BrtFRTArchID$ },\n\t0x0013: { n:\"BrtSSTItem\", f:parse_RichStr },\n\t0x0014: { n:\"BrtPCDIMissing\", f:parsenoop },\n\t0x0015: { n:\"BrtPCDINumber\", f:parsenoop },\n\t0x0016: { n:\"BrtPCDIBoolean\", f:parsenoop },\n\t0x0017: { n:\"BrtPCDIError\", f:parsenoop },\n\t0x0018: { n:\"BrtPCDIString\", f:parsenoop },\n\t0x0019: { n:\"BrtPCDIDatetime\", f:parsenoop },\n\t0x001A: { n:\"BrtPCDIIndex\", f:parsenoop },\n\t0x001B: { n:\"BrtPCDIAMissing\", f:parsenoop },\n\t0x001C: { n:\"BrtPCDIANumber\", f:parsenoop },\n\t0x001D: { n:\"BrtPCDIABoolean\", f:parsenoop },\n\t0x001E: { n:\"BrtPCDIAError\", f:parsenoop },\n\t0x001F: { n:\"BrtPCDIAString\", f:parsenoop },\n\t0x0020: { n:\"BrtPCDIADatetime\", f:parsenoop },\n\t0x0021: { n:\"BrtPCRRecord\", f:parsenoop },\n\t0x0022: { n:\"BrtPCRRecordDt\", f:parsenoop },\n\t0x0023: { n:\"BrtFRTBegin\", f:parsenoop },\n\t0x0024: { n:\"BrtFRTEnd\", f:parsenoop },\n\t0x0025: { n:\"BrtACBegin\", f:parsenoop },\n\t0x0026: { n:\"BrtACEnd\", f:parsenoop },\n\t0x0027: { n:\"BrtName\", f:parsenoop },\n\t0x0028: { n:\"BrtIndexRowBlock\", f:parsenoop },\n\t0x002A: { n:\"BrtIndexBlock\", f:parsenoop },\n\t0x002B: { n:\"BrtFont\", f:parse_BrtFont },\n\t0x002C: { n:\"BrtFmt\", f:parse_BrtFmt },\n\t0x002D: { n:\"BrtFill\", f:parsenoop },\n\t0x002E: { n:\"BrtBorder\", f:parsenoop },\n\t0x002F: { n:\"BrtXF\", f:parse_BrtXF },\n\t0x0030: { n:\"BrtStyle\", f:parsenoop },\n\t0x0031: { n:\"BrtCellMeta\", f:parsenoop },\n\t0x0032: { n:\"BrtValueMeta\", f:parsenoop },\n\t0x0033: { n:\"BrtMdb\", f:parsenoop },\n\t0x0034: { n:\"BrtBeginFmd\", f:parsenoop },\n\t0x0035: { n:\"BrtEndFmd\", f:parsenoop },\n\t0x0036: { n:\"BrtBeginMdx\", f:parsenoop },\n\t0x0037: { n:\"BrtEndMdx\", f:parsenoop },\n\t0x0038: { n:\"BrtBeginMdxTuple\", f:parsenoop },\n\t0x0039: { n:\"BrtEndMdxTuple\", f:parsenoop },\n\t0x003A: { n:\"BrtMdxMbrIstr\", f:parsenoop },\n\t0x003B: { n:\"BrtStr\", f:parsenoop },\n\t0x003C: { n:\"BrtColInfo\", f:parsenoop },\n\t0x003E: { n:\"BrtCellRString\", f:parsenoop },\n\t0x003F: { n:\"BrtCalcChainItem$\", f:parse_BrtCalcChainItem$ },\n\t0x0040: { n:\"BrtDVal\", f:parsenoop },\n\t0x0041: { n:\"BrtSxvcellNum\", f:parsenoop },\n\t0x0042: { n:\"BrtSxvcellStr\", f:parsenoop },\n\t0x0043: { n:\"BrtSxvcellBool\", f:parsenoop },\n\t0x0044: { n:\"BrtSxvcellErr\", f:parsenoop },\n\t0x0045: { n:\"BrtSxvcellDate\", f:parsenoop },\n\t0x0046: { n:\"BrtSxvcellNil\", f:parsenoop },\n\t0x0080: { n:\"BrtFileVersion\", f:parsenoop },\n\t0x0081: { n:\"BrtBeginSheet\", f:parsenoop },\n\t0x0082: { n:\"BrtEndSheet\", f:parsenoop },\n\t0x0083: { n:\"BrtBeginBook\", f:parsenoop, p:0 },\n\t0x0084: { n:\"BrtEndBook\", f:parsenoop },\n\t0x0085: { n:\"BrtBeginWsViews\", f:parsenoop },\n\t0x0086: { n:\"BrtEndWsViews\", f:parsenoop },\n\t0x0087: { n:\"BrtBeginBookViews\", f:parsenoop },\n\t0x0088: { n:\"BrtEndBookViews\", f:parsenoop },\n\t0x0089: { n:\"BrtBeginWsView\", f:parsenoop },\n\t0x008A: { n:\"BrtEndWsView\", f:parsenoop },\n\t0x008B: { n:\"BrtBeginCsViews\", f:parsenoop },\n\t0x008C: { n:\"BrtEndCsViews\", f:parsenoop },\n\t0x008D: { n:\"BrtBeginCsView\", f:parsenoop },\n\t0x008E: { n:\"BrtEndCsView\", f:parsenoop },\n\t0x008F: { n:\"BrtBeginBundleShs\", f:parsenoop },\n\t0x0090: { n:\"BrtEndBundleShs\", f:parsenoop },\n\t0x0091: { n:\"BrtBeginSheetData\", f:parsenoop },\n\t0x0092: { n:\"BrtEndSheetData\", f:parsenoop },\n\t0x0093: { n:\"BrtWsProp\", f:parse_BrtWsProp },\n\t0x0094: { n:\"BrtWsDim\", f:parse_BrtWsDim, p:16 },\n\t0x0097: { n:\"BrtPane\", f:parsenoop },\n\t0x0098: { n:\"BrtSel\", f:parsenoop },\n\t0x0099: { n:\"BrtWbProp\", f:parse_BrtWbProp },\n\t0x009A: { n:\"BrtWbFactoid\", f:parsenoop },\n\t0x009B: { n:\"BrtFileRecover\", f:parsenoop },\n\t0x009C: { n:\"BrtBundleSh\", f:parse_BrtBundleSh },\n\t0x009D: { n:\"BrtCalcProp\", f:parsenoop },\n\t0x009E: { n:\"BrtBookView\", f:parsenoop },\n\t0x009F: { n:\"BrtBeginSst\", f:parse_BrtBeginSst },\n\t0x00A0: { n:\"BrtEndSst\", f:parsenoop },\n\t0x00A1: { n:\"BrtBeginAFilter\", f:parsenoop },\n\t0x00A2: { n:\"BrtEndAFilter\", f:parsenoop },\n\t0x00A3: { n:\"BrtBeginFilterColumn\", f:parsenoop },\n\t0x00A4: { n:\"BrtEndFilterColumn\", f:parsenoop },\n\t0x00A5: { n:\"BrtBeginFilters\", f:parsenoop },\n\t0x00A6: { n:\"BrtEndFilters\", f:parsenoop },\n\t0x00A7: { n:\"BrtFilter\", f:parsenoop },\n\t0x00A8: { n:\"BrtColorFilter\", f:parsenoop },\n\t0x00A9: { n:\"BrtIconFilter\", f:parsenoop },\n\t0x00AA: { n:\"BrtTop10Filter\", f:parsenoop },\n\t0x00AB: { n:\"BrtDynamicFilter\", f:parsenoop },\n\t0x00AC: { n:\"BrtBeginCustomFilters\", f:parsenoop },\n\t0x00AD: { n:\"BrtEndCustomFilters\", f:parsenoop },\n\t0x00AE: { n:\"BrtCustomFilter\", f:parsenoop },\n\t0x00AF: { n:\"BrtAFilterDateGroupItem\", f:parsenoop },\n\t0x00B0: { n:\"BrtMergeCell\", f:parse_BrtMergeCell },\n\t0x00B1: { n:\"BrtBeginMergeCells\", f:parsenoop },\n\t0x00B2: { n:\"BrtEndMergeCells\", f:parsenoop },\n\t0x00B3: { n:\"BrtBeginPivotCacheDef\", f:parsenoop },\n\t0x00B4: { n:\"BrtEndPivotCacheDef\", f:parsenoop },\n\t0x00B5: { n:\"BrtBeginPCDFields\", f:parsenoop },\n\t0x00B6: { n:\"BrtEndPCDFields\", f:parsenoop },\n\t0x00B7: { n:\"BrtBeginPCDField\", f:parsenoop },\n\t0x00B8: { n:\"BrtEndPCDField\", f:parsenoop },\n\t0x00B9: { n:\"BrtBeginPCDSource\", f:parsenoop },\n\t0x00BA: { n:\"BrtEndPCDSource\", f:parsenoop },\n\t0x00BB: { n:\"BrtBeginPCDSRange\", f:parsenoop },\n\t0x00BC: { n:\"BrtEndPCDSRange\", f:parsenoop },\n\t0x00BD: { n:\"BrtBeginPCDFAtbl\", f:parsenoop },\n\t0x00BE: { n:\"BrtEndPCDFAtbl\", f:parsenoop },\n\t0x00BF: { n:\"BrtBeginPCDIRun\", f:parsenoop },\n\t0x00C0: { n:\"BrtEndPCDIRun\", f:parsenoop },\n\t0x00C1: { n:\"BrtBeginPivotCacheRecords\", f:parsenoop },\n\t0x00C2: { n:\"BrtEndPivotCacheRecords\", f:parsenoop },\n\t0x00C3: { n:\"BrtBeginPCDHierarchies\", f:parsenoop },\n\t0x00C4: { n:\"BrtEndPCDHierarchies\", f:parsenoop },\n\t0x00C5: { n:\"BrtBeginPCDHierarchy\", f:parsenoop },\n\t0x00C6: { n:\"BrtEndPCDHierarchy\", f:parsenoop },\n\t0x00C7: { n:\"BrtBeginPCDHFieldsUsage\", f:parsenoop },\n\t0x00C8: { n:\"BrtEndPCDHFieldsUsage\", f:parsenoop },\n\t0x00C9: { n:\"BrtBeginExtConnection\", f:parsenoop },\n\t0x00CA: { n:\"BrtEndExtConnection\", f:parsenoop },\n\t0x00CB: { n:\"BrtBeginECDbProps\", f:parsenoop },\n\t0x00CC: { n:\"BrtEndECDbProps\", f:parsenoop },\n\t0x00CD: { n:\"BrtBeginECOlapProps\", f:parsenoop },\n\t0x00CE: { n:\"BrtEndECOlapProps\", f:parsenoop },\n\t0x00CF: { n:\"BrtBeginPCDSConsol\", f:parsenoop },\n\t0x00D0: { n:\"BrtEndPCDSConsol\", f:parsenoop },\n\t0x00D1: { n:\"BrtBeginPCDSCPages\", f:parsenoop },\n\t0x00D2: { n:\"BrtEndPCDSCPages\", f:parsenoop },\n\t0x00D3: { n:\"BrtBeginPCDSCPage\", f:parsenoop },\n\t0x00D4: { n:\"BrtEndPCDSCPage\", f:parsenoop },\n\t0x00D5: { n:\"BrtBeginPCDSCPItem\", f:parsenoop },\n\t0x00D6: { n:\"BrtEndPCDSCPItem\", f:parsenoop },\n\t0x00D7: { n:\"BrtBeginPCDSCSets\", f:parsenoop },\n\t0x00D8: { n:\"BrtEndPCDSCSets\", f:parsenoop },\n\t0x00D9: { n:\"BrtBeginPCDSCSet\", f:parsenoop },\n\t0x00DA: { n:\"BrtEndPCDSCSet\", f:parsenoop },\n\t0x00DB: { n:\"BrtBeginPCDFGroup\", f:parsenoop },\n\t0x00DC: { n:\"BrtEndPCDFGroup\", f:parsenoop },\n\t0x00DD: { n:\"BrtBeginPCDFGItems\", f:parsenoop },\n\t0x00DE: { n:\"BrtEndPCDFGItems\", f:parsenoop },\n\t0x00DF: { n:\"BrtBeginPCDFGRange\", f:parsenoop },\n\t0x00E0: { n:\"BrtEndPCDFGRange\", f:parsenoop },\n\t0x00E1: { n:\"BrtBeginPCDFGDiscrete\", f:parsenoop },\n\t0x00E2: { n:\"BrtEndPCDFGDiscrete\", f:parsenoop },\n\t0x00E3: { n:\"BrtBeginPCDSDTupleCache\", f:parsenoop },\n\t0x00E4: { n:\"BrtEndPCDSDTupleCache\", f:parsenoop },\n\t0x00E5: { n:\"BrtBeginPCDSDTCEntries\", f:parsenoop },\n\t0x00E6: { n:\"BrtEndPCDSDTCEntries\", f:parsenoop },\n\t0x00E7: { n:\"BrtBeginPCDSDTCEMembers\", f:parsenoop },\n\t0x00E8: { n:\"BrtEndPCDSDTCEMembers\", f:parsenoop },\n\t0x00E9: { n:\"BrtBeginPCDSDTCEMember\", f:parsenoop },\n\t0x00EA: { n:\"BrtEndPCDSDTCEMember\", f:parsenoop },\n\t0x00EB: { n:\"BrtBeginPCDSDTCQueries\", f:parsenoop },\n\t0x00EC: { n:\"BrtEndPCDSDTCQueries\", f:parsenoop },\n\t0x00ED: { n:\"BrtBeginPCDSDTCQuery\", f:parsenoop },\n\t0x00EE: { n:\"BrtEndPCDSDTCQuery\", f:parsenoop },\n\t0x00EF: { n:\"BrtBeginPCDSDTCSets\", f:parsenoop },\n\t0x00F0: { n:\"BrtEndPCDSDTCSets\", f:parsenoop },\n\t0x00F1: { n:\"BrtBeginPCDSDTCSet\", f:parsenoop },\n\t0x00F2: { n:\"BrtEndPCDSDTCSet\", f:parsenoop },\n\t0x00F3: { n:\"BrtBeginPCDCalcItems\", f:parsenoop },\n\t0x00F4: { n:\"BrtEndPCDCalcItems\", f:parsenoop },\n\t0x00F5: { n:\"BrtBeginPCDCalcItem\", f:parsenoop },\n\t0x00F6: { n:\"BrtEndPCDCalcItem\", f:parsenoop },\n\t0x00F7: { n:\"BrtBeginPRule\", f:parsenoop },\n\t0x00F8: { n:\"BrtEndPRule\", f:parsenoop },\n\t0x00F9: { n:\"BrtBeginPRFilters\", f:parsenoop },\n\t0x00FA: { n:\"BrtEndPRFilters\", f:parsenoop },\n\t0x00FB: { n:\"BrtBeginPRFilter\", f:parsenoop },\n\t0x00FC: { n:\"BrtEndPRFilter\", f:parsenoop },\n\t0x00FD: { n:\"BrtBeginPNames\", f:parsenoop },\n\t0x00FE: { n:\"BrtEndPNames\", f:parsenoop },\n\t0x00FF: { n:\"BrtBeginPName\", f:parsenoop },\n\t0x0100: { n:\"BrtEndPName\", f:parsenoop },\n\t0x0101: { n:\"BrtBeginPNPairs\", f:parsenoop },\n\t0x0102: { 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f:parsenoop },\n\t0x0492: { n:\"BrtEndCellIgnoreECs14\", f:parsenoop },\n\t0x0493: { n:\"BrtDxf14\", f:parsenoop },\n\t0x0494: { n:\"BrtBeginDxF14s\", f:parsenoop },\n\t0x0495: { n:\"BrtEndDxf14s\", f:parsenoop },\n\t0x0499: { n:\"BrtFilter14\", f:parsenoop },\n\t0x049A: { n:\"BrtBeginCustomFilters14\", f:parsenoop },\n\t0x049C: { n:\"BrtCustomFilter14\", f:parsenoop },\n\t0x049D: { n:\"BrtIconFilter14\", f:parsenoop },\n\t0x049E: { n:\"BrtPivotCacheConnectionName\", f:parsenoop },\n\t0x0800: { n:\"BrtBeginDecoupledPivotCacheIDs\", f:parsenoop },\n\t0x0801: { n:\"BrtEndDecoupledPivotCacheIDs\", f:parsenoop },\n\t0x0802: { n:\"BrtDecoupledPivotCacheID\", f:parsenoop },\n\t0x0803: { n:\"BrtBeginPivotTableRefs\", f:parsenoop },\n\t0x0804: { n:\"BrtEndPivotTableRefs\", f:parsenoop },\n\t0x0805: { n:\"BrtPivotTableRef\", f:parsenoop },\n\t0x0806: { n:\"BrtSlicerCacheBookPivotTables\", f:parsenoop },\n\t0x0807: { n:\"BrtBeginSxvcells\", f:parsenoop },\n\t0x0808: { n:\"BrtEndSxvcells\", f:parsenoop },\n\t0x0809: { n:\"BrtBeginSxRow\", f:parsenoop },\n\t0x080A: { n:\"BrtEndSxRow\", f:parsenoop },\n\t0x080C: { n:\"BrtPcdCalcMem15\", f:parsenoop },\n\t0x0813: { n:\"BrtQsi15\", f:parsenoop },\n\t0x0814: { n:\"BrtBeginWebExtensions\", f:parsenoop },\n\t0x0815: { n:\"BrtEndWebExtensions\", f:parsenoop },\n\t0x0816: { n:\"BrtWebExtension\", f:parsenoop },\n\t0x0817: { n:\"BrtAbsPath15\", f:parsenoop },\n\t0x0818: { n:\"BrtBeginPivotTableUISettings\", f:parsenoop },\n\t0x0819: { n:\"BrtEndPivotTableUISettings\", f:parsenoop },\n\t0x081B: { n:\"BrtTableSlicerCacheIDs\", f:parsenoop },\n\t0x081C: { n:\"BrtTableSlicerCacheID\", f:parsenoop },\n\t0x081D: { n:\"BrtBeginTableSlicerCache\", f:parsenoop },\n\t0x081E: { n:\"BrtEndTableSlicerCache\", f:parsenoop },\n\t0x081F: { n:\"BrtSxFilter15\", f:parsenoop },\n\t0x0820: { n:\"BrtBeginTimelineCachePivotCacheIDs\", f:parsenoop },\n\t0x0821: { n:\"BrtEndTimelineCachePivotCacheIDs\", f:parsenoop },\n\t0x0822: { n:\"BrtTimelineCachePivotCacheID\", f:parsenoop },\n\t0x0823: { n:\"BrtBeginTimelineCacheIDs\", f:parsenoop },\n\t0x0824: { n:\"BrtEndTimelineCacheIDs\", f:parsenoop },\n\t0x0825: { n:\"BrtBeginTimelineCacheID\", f:parsenoop },\n\t0x0826: { n:\"BrtEndTimelineCacheID\", f:parsenoop },\n\t0x0827: { n:\"BrtBeginTimelinesEx\", f:parsenoop },\n\t0x0828: { n:\"BrtEndTimelinesEx\", f:parsenoop },\n\t0x0829: { n:\"BrtBeginTimelineEx\", f:parsenoop },\n\t0x082A: { n:\"BrtEndTimelineEx\", f:parsenoop },\n\t0x082B: { n:\"BrtWorkBookPr15\", f:parsenoop },\n\t0x082C: { n:\"BrtPCDH15\", f:parsenoop },\n\t0x082D: { n:\"BrtBeginTimelineStyle\", f:parsenoop },\n\t0x082E: { n:\"BrtEndTimelineStyle\", f:parsenoop },\n\t0x082F: { n:\"BrtTimelineStyleElement\", f:parsenoop },\n\t0x0830: { n:\"BrtBeginTimelineStylesheetExt15\", f:parsenoop },\n\t0x0831: { n:\"BrtEndTimelineStylesheetExt15\", f:parsenoop },\n\t0x0832: { n:\"BrtBeginTimelineStyles\", f:parsenoop },\n\t0x0833: { n:\"BrtEndTimelineStyles\", f:parsenoop },\n\t0x0834: { n:\"BrtBeginTimelineStyleElements\", f:parsenoop },\n\t0x0835: { n:\"BrtEndTimelineStyleElements\", f:parsenoop },\n\t0x0836: { n:\"BrtDxf15\", f:parsenoop },\n\t0x0837: { n:\"BrtBeginDxfs15\", f:parsenoop },\n\t0x0838: { n:\"brtEndDxfs15\", f:parsenoop },\n\t0x0839: { n:\"BrtSlicerCacheHideItemsWithNoData\", f:parsenoop },\n\t0x083A: { n:\"BrtBeginItemUniqueNames\", f:parsenoop },\n\t0x083B: { n:\"BrtEndItemUniqueNames\", f:parsenoop },\n\t0x083C: { n:\"BrtItemUniqueName\", f:parsenoop },\n\t0x083D: { n:\"BrtBeginExtConn15\", f:parsenoop },\n\t0x083E: { n:\"BrtEndExtConn15\", f:parsenoop },\n\t0x083F: { n:\"BrtBeginOledbPr15\", f:parsenoop },\n\t0x0840: { n:\"BrtEndOledbPr15\", f:parsenoop },\n\t0x0841: { n:\"BrtBeginDataFeedPr15\", f:parsenoop },\n\t0x0842: { n:\"BrtEndDataFeedPr15\", f:parsenoop },\n\t0x0843: { n:\"BrtTextPr15\", f:parsenoop },\n\t0x0844: { n:\"BrtRangePr15\", f:parsenoop },\n\t0x0845: { n:\"BrtDbCommand15\", f:parsenoop },\n\t0x0846: { n:\"BrtBeginDbTables15\", f:parsenoop },\n\t0x0847: { n:\"BrtEndDbTables15\", f:parsenoop },\n\t0x0848: { n:\"BrtDbTable15\", f:parsenoop },\n\t0x0849: { n:\"BrtBeginDataModel\", f:parsenoop },\n\t0x084A: { n:\"BrtEndDataModel\", f:parsenoop },\n\t0x084B: { n:\"BrtBeginModelTables\", f:parsenoop },\n\t0x084C: { n:\"BrtEndModelTables\", f:parsenoop },\n\t0x084D: { n:\"BrtModelTable\", f:parsenoop },\n\t0x084E: { n:\"BrtBeginModelRelationships\", f:parsenoop },\n\t0x084F: { n:\"BrtEndModelRelationships\", f:parsenoop },\n\t0x0850: { n:\"BrtModelRelationship\", f:parsenoop },\n\t0x0851: { n:\"BrtBeginECTxtWiz15\", f:parsenoop },\n\t0x0852: { n:\"BrtEndECTxtWiz15\", f:parsenoop },\n\t0x0853: { n:\"BrtBeginECTWFldInfoLst15\", f:parsenoop },\n\t0x0854: { n:\"BrtEndECTWFldInfoLst15\", f:parsenoop },\n\t0x0855: { n:\"BrtBeginECTWFldInfo15\", f:parsenoop },\n\t0x0856: { n:\"BrtFieldListActiveItem\", f:parsenoop },\n\t0x0857: { n:\"BrtPivotCacheIdVersion\", f:parsenoop },\n\t0x0858: { n:\"BrtSXDI15\", f:parsenoop },\n\t0xFFFF: { n:\"\", f:parsenoop }\n};\n\nvar evert_RE = evert_key(XLSBRecordEnum, 'n');\n\n/* [MS-XLS] 2.3 Record Enumeration */\nvar XLSRecordEnum = {\n\t0x0003: { n:\"BIFF2NUM\", f:parse_BIFF2NUM },\n\t0x0004: { n:\"BIFF2STR\", f:parse_BIFF2STR },\n\t0x0006: { n:\"Formula\", f:parse_Formula },\n\t0x0009: { n:'BOF', f:parse_BOF },\n\t0x000a: { n:'EOF', f:parse_EOF },\n\t0x000c: { n:\"CalcCount\", f:parse_CalcCount },\n\t0x000d: { n:\"CalcMode\", f:parse_CalcMode },\n\t0x000e: { n:\"CalcPrecision\", f:parse_CalcPrecision },\n\t0x000f: { n:\"CalcRefMode\", f:parse_CalcRefMode },\n\t0x0010: { n:\"CalcDelta\", f:parse_CalcDelta },\n\t0x0011: { n:\"CalcIter\", f:parse_CalcIter },\n\t0x0012: { n:\"Protect\", f:parse_Protect },\n\t0x0013: { n:\"Password\", f:parse_Password },\n\t0x0014: { n:\"Header\", f:parse_Header },\n\t0x0015: { n:\"Footer\", f:parse_Footer },\n\t0x0017: { n:\"ExternSheet\", f:parse_ExternSheet },\n\t0x0018: { n:\"Lbl\", f:parse_Lbl },\n\t0x0019: { n:\"WinProtect\", f:parse_WinProtect },\n\t0x001a: { n:\"VerticalPageBreaks\", f:parse_VerticalPageBreaks },\n\t0x001b: { n:\"HorizontalPageBreaks\", f:parse_HorizontalPageBreaks },\n\t0x001c: { n:\"Note\", f:parse_Note },\n\t0x001d: { n:\"Selection\", f:parse_Selection },\n\t0x0022: { n:\"Date1904\", f:parse_Date1904 },\n\t0x0023: { n:\"ExternName\", f:parse_ExternName },\n\t0x0026: { n:\"LeftMargin\", f:parse_LeftMargin },\n\t0x0027: { n:\"RightMargin\", f:parse_RightMargin },\n\t0x0028: { n:\"TopMargin\", f:parse_TopMargin },\n\t0x0029: { n:\"BottomMargin\", f:parse_BottomMargin },\n\t0x002a: { n:\"PrintRowCol\", f:parse_PrintRowCol },\n\t0x002b: { n:\"PrintGrid\", f:parse_PrintGrid },\n\t0x002f: { n:\"FilePass\", f:parse_FilePass },\n\t0x0031: { n:\"Font\", f:parse_Font },\n\t0x0033: { n:\"PrintSize\", f:parse_PrintSize },\n\t0x003c: { n:\"Continue\", f:parse_Continue },\n\t0x003d: { n:\"Window1\", f:parse_Window1 },\n\t0x0040: { n:\"Backup\", f:parse_Backup },\n\t0x0041: { n:\"Pane\", f:parse_Pane },\n\t0x0042: { n:'CodePage', f:parse_CodePage },\n\t0x004d: { n:\"Pls\", f:parse_Pls },\n\t0x0050: { n:\"DCon\", f:parse_DCon },\n\t0x0051: { n:\"DConRef\", f:parse_DConRef },\n\t0x0052: { n:\"DConName\", f:parse_DConName },\n\t0x0055: { n:\"DefColWidth\", f:parse_DefColWidth },\n\t0x0059: { n:\"XCT\", f:parse_XCT },\n\t0x005a: { n:\"CRN\", f:parse_CRN },\n\t0x005b: { n:\"FileSharing\", f:parse_FileSharing },\n\t0x005c: { n:'WriteAccess', f:parse_WriteAccess },\n\t0x005d: { n:\"Obj\", f:parse_Obj },\n\t0x005e: { n:\"Uncalced\", f:parse_Uncalced },\n\t0x005f: { n:\"CalcSaveRecalc\", f:parse_CalcSaveRecalc },\n\t0x0060: { n:\"Template\", f:parse_Template },\n\t0x0061: { n:\"Intl\", f:parse_Intl },\n\t0x0063: { n:\"ObjProtect\", f:parse_ObjProtect },\n\t0x007d: { n:\"ColInfo\", f:parse_ColInfo },\n\t0x0080: { n:\"Guts\", f:parse_Guts },\n\t0x0081: { n:\"WsBool\", f:parse_WsBool },\n\t0x0082: { n:\"GridSet\", f:parse_GridSet },\n\t0x0083: { n:\"HCenter\", f:parse_HCenter },\n\t0x0084: { n:\"VCenter\", f:parse_VCenter },\n\t0x0085: { n:'BoundSheet8', f:parse_BoundSheet8 },\n\t0x0086: { n:\"WriteProtect\", f:parse_WriteProtect },\n\t0x008c: { n:\"Country\", f:parse_Country },\n\t0x008d: { n:\"HideObj\", f:parse_HideObj },\n\t0x0090: { n:\"Sort\", f:parse_Sort },\n\t0x0092: { n:\"Palette\", f:parse_Palette },\n\t0x0097: { n:\"Sync\", f:parse_Sync },\n\t0x0098: { n:\"LPr\", f:parse_LPr },\n\t0x0099: { n:\"DxGCol\", f:parse_DxGCol },\n\t0x009a: { n:\"FnGroupName\", f:parse_FnGroupName },\n\t0x009b: { n:\"FilterMode\", f:parse_FilterMode },\n\t0x009c: { n:\"BuiltInFnGroupCount\", f:parse_BuiltInFnGroupCount },\n\t0x009d: { n:\"AutoFilterInfo\", f:parse_AutoFilterInfo },\n\t0x009e: { n:\"AutoFilter\", f:parse_AutoFilter },\n\t0x00a0: { n:\"Scl\", f:parse_Scl },\n\t0x00a1: { n:\"Setup\", f:parse_Setup },\n\t0x00ae: { n:\"ScenMan\", f:parse_ScenMan },\n\t0x00af: { n:\"SCENARIO\", f:parse_SCENARIO },\n\t0x00b0: { n:\"SxView\", f:parse_SxView },\n\t0x00b1: { n:\"Sxvd\", f:parse_Sxvd },\n\t0x00b2: { n:\"SXVI\", f:parse_SXVI },\n\t0x00b4: { n:\"SxIvd\", f:parse_SxIvd },\n\t0x00b5: { n:\"SXLI\", f:parse_SXLI },\n\t0x00b6: { n:\"SXPI\", f:parse_SXPI },\n\t0x00b8: { n:\"DocRoute\", f:parse_DocRoute },\n\t0x00b9: { n:\"RecipName\", f:parse_RecipName },\n\t0x00bd: { n:\"MulRk\", f:parse_MulRk },\n\t0x00be: { n:\"MulBlank\", f:parse_MulBlank },\n\t0x00c1: { n:'Mms', f:parse_Mms },\n\t0x00c5: { n:\"SXDI\", f:parse_SXDI },\n\t0x00c6: { n:\"SXDB\", f:parse_SXDB },\n\t0x00c7: { n:\"SXFDB\", f:parse_SXFDB },\n\t0x00c8: { n:\"SXDBB\", f:parse_SXDBB },\n\t0x00c9: { n:\"SXNum\", f:parse_SXNum },\n\t0x00ca: { n:\"SxBool\", f:parse_SxBool },\n\t0x00cb: { n:\"SxErr\", f:parse_SxErr },\n\t0x00cc: { n:\"SXInt\", f:parse_SXInt },\n\t0x00cd: { n:\"SXString\", f:parse_SXString },\n\t0x00ce: { n:\"SXDtr\", f:parse_SXDtr },\n\t0x00cf: { n:\"SxNil\", f:parse_SxNil },\n\t0x00d0: { n:\"SXTbl\", f:parse_SXTbl },\n\t0x00d1: { n:\"SXTBRGIITM\", f:parse_SXTBRGIITM },\n\t0x00d2: { n:\"SxTbpg\", f:parse_SxTbpg },\n\t0x00d3: { n:\"ObProj\", f:parse_ObProj },\n\t0x00d5: { n:\"SXStreamID\", f:parse_SXStreamID },\n\t0x00d7: { n:\"DBCell\", f:parse_DBCell },\n\t0x00d8: { n:\"SXRng\", f:parse_SXRng },\n\t0x00d9: { n:\"SxIsxoper\", f:parse_SxIsxoper },\n\t0x00da: { n:\"BookBool\", f:parse_BookBool },\n\t0x00dc: { n:\"DbOrParamQry\", f:parse_DbOrParamQry },\n\t0x00dd: { n:\"ScenarioProtect\", f:parse_ScenarioProtect },\n\t0x00de: { n:\"OleObjectSize\", f:parse_OleObjectSize },\n\t0x00e0: { n:\"XF\", f:parse_XF },\n\t0x00e1: { n:'InterfaceHdr', f:parse_InterfaceHdr },\n\t0x00e2: { n:'InterfaceEnd', f:parse_InterfaceEnd },\n\t0x00e3: { n:\"SXVS\", f:parse_SXVS },\n\t0x00e5: { n:\"MergeCells\", f:parse_MergeCells },\n\t0x00e9: { n:\"BkHim\", f:parse_BkHim },\n\t0x00eb: { n:\"MsoDrawingGroup\", f:parse_MsoDrawingGroup },\n\t0x00ec: { n:\"MsoDrawing\", f:parse_MsoDrawing },\n\t0x00ed: { n:\"MsoDrawingSelection\", f:parse_MsoDrawingSelection },\n\t0x00ef: { n:\"PhoneticInfo\", f:parse_PhoneticInfo },\n\t0x00f0: { n:\"SxRule\", f:parse_SxRule },\n\t0x00f1: { n:\"SXEx\", f:parse_SXEx },\n\t0x00f2: { n:\"SxFilt\", f:parse_SxFilt },\n\t0x00f4: { n:\"SxDXF\", f:parse_SxDXF },\n\t0x00f5: { n:\"SxItm\", f:parse_SxItm },\n\t0x00f6: { n:\"SxName\", f:parse_SxName },\n\t0x00f7: { n:\"SxSelect\", f:parse_SxSelect },\n\t0x00f8: { n:\"SXPair\", f:parse_SXPair },\n\t0x00f9: { n:\"SxFmla\", f:parse_SxFmla },\n\t0x00fb: { n:\"SxFormat\", f:parse_SxFormat },\n\t0x00fc: { n:\"SST\", f:parse_SST },\n\t0x00fd: { n:\"LabelSst\", f:parse_LabelSst },\n\t0x00ff: { n:\"ExtSST\", f:parse_ExtSST },\n\t0x0100: { n:\"SXVDEx\", f:parse_SXVDEx },\n\t0x0103: { n:\"SXFormula\", f:parse_SXFormula },\n\t0x0122: { n:\"SXDBEx\", f:parse_SXDBEx },\n\t0x0137: { n:\"RRDInsDel\", f:parse_RRDInsDel },\n\t0x0138: { n:\"RRDHead\", f:parse_RRDHead },\n\t0x013b: { n:\"RRDChgCell\", f:parse_RRDChgCell },\n\t0x013d: { n:\"RRTabId\", f:parse_RRTabId },\n\t0x013e: { n:\"RRDRenSheet\", f:parse_RRDRenSheet },\n\t0x013f: { n:\"RRSort\", f:parse_RRSort },\n\t0x0140: { n:\"RRDMove\", f:parse_RRDMove },\n\t0x014a: { n:\"RRFormat\", f:parse_RRFormat },\n\t0x014b: { n:\"RRAutoFmt\", f:parse_RRAutoFmt },\n\t0x014d: { n:\"RRInsertSh\", f:parse_RRInsertSh },\n\t0x014e: { n:\"RRDMoveBegin\", f:parse_RRDMoveBegin },\n\t0x014f: { n:\"RRDMoveEnd\", f:parse_RRDMoveEnd },\n\t0x0150: { n:\"RRDInsDelBegin\", f:parse_RRDInsDelBegin },\n\t0x0151: { n:\"RRDInsDelEnd\", f:parse_RRDInsDelEnd },\n\t0x0152: { n:\"RRDConflict\", f:parse_RRDConflict },\n\t0x0153: { n:\"RRDDefName\", f:parse_RRDDefName },\n\t0x0154: { n:\"RRDRstEtxp\", f:parse_RRDRstEtxp },\n\t0x015f: { n:\"LRng\", f:parse_LRng },\n\t0x0160: { n:\"UsesELFs\", f:parse_UsesELFs },\n\t0x0161: { n:\"DSF\", f:parse_DSF },\n\t0x0191: { n:\"CUsr\", f:parse_CUsr },\n\t0x0192: { n:\"CbUsr\", f:parse_CbUsr },\n\t0x0193: { n:\"UsrInfo\", f:parse_UsrInfo },\n\t0x0194: { n:\"UsrExcl\", f:parse_UsrExcl },\n\t0x0195: { n:\"FileLock\", f:parse_FileLock },\n\t0x0196: { n:\"RRDInfo\", f:parse_RRDInfo },\n\t0x0197: { n:\"BCUsrs\", f:parse_BCUsrs },\n\t0x0198: { n:\"UsrChk\", f:parse_UsrChk },\n\t0x01a9: { n:\"UserBView\", f:parse_UserBView },\n\t0x01aa: { n:\"UserSViewBegin\", f:parse_UserSViewBegin },\n\t0x01ab: { n:\"UserSViewEnd\", f:parse_UserSViewEnd },\n\t0x01ac: { n:\"RRDUserView\", f:parse_RRDUserView },\n\t0x01ad: { n:\"Qsi\", f:parse_Qsi },\n\t0x01ae: { n:\"SupBook\", f:parse_SupBook },\n\t0x01af: { n:\"Prot4Rev\", f:parse_Prot4Rev },\n\t0x01b0: { n:\"CondFmt\", f:parse_CondFmt },\n\t0x01b1: { n:\"CF\", f:parse_CF },\n\t0x01b2: { n:\"DVal\", f:parse_DVal },\n\t0x01b5: { n:\"DConBin\", f:parse_DConBin },\n\t0x01b6: { n:\"TxO\", f:parse_TxO },\n\t0x01b7: { n:\"RefreshAll\", f:parse_RefreshAll },\n\t0x01b8: { n:\"HLink\", f:parse_HLink },\n\t0x01b9: { n:\"Lel\", f:parse_Lel },\n\t0x01ba: { n:\"CodeName\", f:parse_XLSCodeName },\n\t0x01bb: { n:\"SXFDBType\", f:parse_SXFDBType },\n\t0x01bc: { n:\"Prot4RevPass\", f:parse_Prot4RevPass },\n\t0x01bd: { n:\"ObNoMacros\", f:parse_ObNoMacros },\n\t0x01be: { n:\"Dv\", f:parse_Dv },\n\t0x01c0: { n:\"Excel9File\", f:parse_Excel9File },\n\t0x01c1: { n:\"RecalcId\", f:parse_RecalcId, r:2},\n\t0x01c2: { n:\"EntExU2\", f:parse_EntExU2 },\n\t0x0200: { n:\"Dimensions\", f:parse_Dimensions },\n\t0x0201: { n:\"Blank\", f:parse_Blank },\n\t0x0203: { n:\"Number\", f:parse_Number },\n\t0x0204: { n:\"Label\", f:parse_Label },\n\t0x0205: { n:\"BoolErr\", f:parse_BoolErr },\n\t0x0207: { n:\"String\", f:parse_String },\n\t0x0208: { n:'Row', f:parse_Row },\n\t0x020b: { n:\"Index\", f:parse_Index },\n\t0x0221: { n:\"Array\", f:parse_Array },\n\t0x0225: { n:\"DefaultRowHeight\", f:parse_DefaultRowHeight },\n\t0x0236: { n:\"Table\", f:parse_Table },\n\t0x023e: { n:\"Window2\", f:parse_Window2 },\n\t0x027e: { n:\"RK\", f:parse_RK },\n\t0x0293: { n:\"Style\", f:parse_Style },\n\t0x0418: { n:\"BigName\", f:parse_BigName },\n\t0x041e: { n:\"Format\", f:parse_Format },\n\t0x043c: { n:\"ContinueBigName\", f:parse_ContinueBigName },\n\t0x04bc: { n:\"ShrFmla\", f:parse_ShrFmla },\n\t0x0800: { n:\"HLinkTooltip\", f:parse_HLinkTooltip },\n\t0x0801: { n:\"WebPub\", f:parse_WebPub },\n\t0x0802: { n:\"QsiSXTag\", f:parse_QsiSXTag },\n\t0x0803: { n:\"DBQueryExt\", f:parse_DBQueryExt },\n\t0x0804: { n:\"ExtString\", f:parse_ExtString },\n\t0x0805: { n:\"TxtQry\", f:parse_TxtQry },\n\t0x0806: { n:\"Qsir\", f:parse_Qsir },\n\t0x0807: { n:\"Qsif\", f:parse_Qsif },\n\t0x0808: { n:\"RRDTQSIF\", f:parse_RRDTQSIF },\n\t0x0809: { n:'BOF', f:parse_BOF },\n\t0x080a: { n:\"OleDbConn\", f:parse_OleDbConn },\n\t0x080b: { n:\"WOpt\", f:parse_WOpt },\n\t0x080c: { n:\"SXViewEx\", f:parse_SXViewEx },\n\t0x080d: { n:\"SXTH\", f:parse_SXTH },\n\t0x080e: { n:\"SXPIEx\", f:parse_SXPIEx },\n\t0x080f: { n:\"SXVDTEx\", f:parse_SXVDTEx },\n\t0x0810: { n:\"SXViewEx9\", f:parse_SXViewEx9 },\n\t0x0812: { n:\"ContinueFrt\", f:parse_ContinueFrt },\n\t0x0813: { n:\"RealTimeData\", f:parse_RealTimeData },\n\t0x0850: { n:\"ChartFrtInfo\", f:parse_ChartFrtInfo },\n\t0x0851: { n:\"FrtWrapper\", f:parse_FrtWrapper },\n\t0x0852: { n:\"StartBlock\", f:parse_StartBlock },\n\t0x0853: { n:\"EndBlock\", f:parse_EndBlock },\n\t0x0854: { n:\"StartObject\", f:parse_StartObject },\n\t0x0855: { n:\"EndObject\", f:parse_EndObject },\n\t0x0856: { n:\"CatLab\", f:parse_CatLab },\n\t0x0857: { n:\"YMult\", f:parse_YMult },\n\t0x0858: { n:\"SXViewLink\", f:parse_SXViewLink },\n\t0x0859: { n:\"PivotChartBits\", f:parse_PivotChartBits },\n\t0x085a: { n:\"FrtFontList\", f:parse_FrtFontList },\n\t0x0862: { n:\"SheetExt\", f:parse_SheetExt },\n\t0x0863: { n:\"BookExt\", f:parse_BookExt, r:12},\n\t0x0864: { n:\"SXAddl\", f:parse_SXAddl },\n\t0x0865: { n:\"CrErr\", f:parse_CrErr },\n\t0x0866: { n:\"HFPicture\", f:parse_HFPicture },\n\t0x0867: { n:'FeatHdr', f:parse_FeatHdr },\n\t0x0868: { n:\"Feat\", f:parse_Feat },\n\t0x086a: { n:\"DataLabExt\", f:parse_DataLabExt },\n\t0x086b: { n:\"DataLabExtContents\", f:parse_DataLabExtContents },\n\t0x086c: { n:\"CellWatch\", f:parse_CellWatch },\n\t0x0871: { n:\"FeatHdr11\", f:parse_FeatHdr11 },\n\t0x0872: { n:\"Feature11\", f:parse_Feature11 },\n\t0x0874: { n:\"DropDownObjIds\", f:parse_DropDownObjIds },\n\t0x0875: { n:\"ContinueFrt11\", f:parse_ContinueFrt11 },\n\t0x0876: { n:\"DConn\", f:parse_DConn },\n\t0x0877: { n:\"List12\", f:parse_List12 },\n\t0x0878: { n:\"Feature12\", f:parse_Feature12 },\n\t0x0879: { n:\"CondFmt12\", f:parse_CondFmt12 },\n\t0x087a: { n:\"CF12\", f:parse_CF12 },\n\t0x087b: { n:\"CFEx\", f:parse_CFEx },\n\t0x087c: { n:\"XFCRC\", f:parse_XFCRC, r:12 },\n\t0x087d: { n:\"XFExt\", f:parse_XFExt, r:12 },\n\t0x087e: { n:\"AutoFilter12\", f:parse_AutoFilter12 },\n\t0x087f: { n:\"ContinueFrt12\", f:parse_ContinueFrt12 },\n\t0x0884: { n:\"MDTInfo\", f:parse_MDTInfo },\n\t0x0885: { n:\"MDXStr\", f:parse_MDXStr },\n\t0x0886: { n:\"MDXTuple\", f:parse_MDXTuple },\n\t0x0887: { n:\"MDXSet\", f:parse_MDXSet },\n\t0x0888: { n:\"MDXProp\", f:parse_MDXProp },\n\t0x0889: { n:\"MDXKPI\", f:parse_MDXKPI },\n\t0x088a: { n:\"MDB\", f:parse_MDB },\n\t0x088b: { n:\"PLV\", f:parse_PLV },\n\t0x088c: { n:\"Compat12\", f:parse_Compat12, r:12 },\n\t0x088d: { n:\"DXF\", f:parse_DXF },\n\t0x088e: { n:\"TableStyles\", f:parse_TableStyles, r:12 },\n\t0x088f: { n:\"TableStyle\", f:parse_TableStyle },\n\t0x0890: { n:\"TableStyleElement\", f:parse_TableStyleElement },\n\t0x0892: { n:\"StyleExt\", f:parse_StyleExt },\n\t0x0893: { n:\"NamePublish\", f:parse_NamePublish },\n\t0x0894: { n:\"NameCmt\", f:parse_NameCmt },\n\t0x0895: { n:\"SortData\", f:parse_SortData },\n\t0x0896: { n:\"Theme\", f:parse_Theme, r:12 },\n\t0x0897: { n:\"GUIDTypeLib\", f:parse_GUIDTypeLib },\n\t0x0898: { n:\"FnGrp12\", f:parse_FnGrp12 },\n\t0x0899: { n:\"NameFnGrp12\", f:parse_NameFnGrp12 },\n\t0x089a: { n:\"MTRSettings\", f:parse_MTRSettings, r:12 },\n\t0x089b: { n:\"CompressPictures\", f:parse_CompressPictures },\n\t0x089c: { n:\"HeaderFooter\", f:parse_HeaderFooter },\n\t0x089d: { n:\"CrtLayout12\", f:parse_CrtLayout12 },\n\t0x089e: { n:\"CrtMlFrt\", f:parse_CrtMlFrt },\n\t0x089f: { n:\"CrtMlFrtContinue\", f:parse_CrtMlFrtContinue },\n\t0x08a3: { n:\"ForceFullCalculation\", f:parse_ForceFullCalculation },\n\t0x08a4: { n:\"ShapePropsStream\", f:parse_ShapePropsStream },\n\t0x08a5: { n:\"TextPropsStream\", f:parse_TextPropsStream },\n\t0x08a6: { n:\"RichTextStream\", f:parse_RichTextStream },\n\t0x08a7: { n:\"CrtLayout12A\", f:parse_CrtLayout12A },\n\t0x1001: { n:\"Units\", f:parse_Units },\n\t0x1002: { n:\"Chart\", f:parse_Chart },\n\t0x1003: { n:\"Series\", f:parse_Series },\n\t0x1006: { n:\"DataFormat\", f:parse_DataFormat },\n\t0x1007: { n:\"LineFormat\", f:parse_LineFormat },\n\t0x1009: { n:\"MarkerFormat\", f:parse_MarkerFormat },\n\t0x100a: { n:\"AreaFormat\", f:parse_AreaFormat },\n\t0x100b: { n:\"PieFormat\", f:parse_PieFormat },\n\t0x100c: { n:\"AttachedLabel\", f:parse_AttachedLabel },\n\t0x100d: { n:\"SeriesText\", f:parse_SeriesText },\n\t0x1014: { n:\"ChartFormat\", f:parse_ChartFormat },\n\t0x1015: { n:\"Legend\", f:parse_Legend },\n\t0x1016: { n:\"SeriesList\", f:parse_SeriesList },\n\t0x1017: { n:\"Bar\", f:parse_Bar },\n\t0x1018: { n:\"Line\", f:parse_Line },\n\t0x1019: { n:\"Pie\", f:parse_Pie },\n\t0x101a: { n:\"Area\", f:parse_Area },\n\t0x101b: { n:\"Scatter\", f:parse_Scatter },\n\t0x101c: { n:\"CrtLine\", f:parse_CrtLine },\n\t0x101d: { n:\"Axis\", f:parse_Axis },\n\t0x101e: { n:\"Tick\", f:parse_Tick },\n\t0x101f: { n:\"ValueRange\", f:parse_ValueRange },\n\t0x1020: { n:\"CatSerRange\", f:parse_CatSerRange },\n\t0x1021: { n:\"AxisLine\", f:parse_AxisLine },\n\t0x1022: { n:\"CrtLink\", f:parse_CrtLink },\n\t0x1024: { n:\"DefaultText\", f:parse_DefaultText },\n\t0x1025: { n:\"Text\", f:parse_Text },\n\t0x1026: { n:\"FontX\", f:parse_FontX },\n\t0x1027: { n:\"ObjectLink\", f:parse_ObjectLink },\n\t0x1032: { n:\"Frame\", f:parse_Frame },\n\t0x1033: { n:\"Begin\", f:parse_Begin },\n\t0x1034: { n:\"End\", f:parse_End },\n\t0x1035: { n:\"PlotArea\", f:parse_PlotArea },\n\t0x103a: { n:\"Chart3d\", f:parse_Chart3d },\n\t0x103c: { n:\"PicF\", f:parse_PicF },\n\t0x103d: { n:\"DropBar\", f:parse_DropBar },\n\t0x103e: { n:\"Radar\", f:parse_Radar },\n\t0x103f: { n:\"Surf\", f:parse_Surf },\n\t0x1040: { n:\"RadarArea\", f:parse_RadarArea },\n\t0x1041: { n:\"AxisParent\", f:parse_AxisParent },\n\t0x1043: { n:\"LegendException\", f:parse_LegendException },\n\t0x1044: { n:\"ShtProps\", f:parse_ShtProps },\n\t0x1045: { n:\"SerToCrt\", f:parse_SerToCrt },\n\t0x1046: { n:\"AxesUsed\", f:parse_AxesUsed },\n\t0x1048: { n:\"SBaseRef\", f:parse_SBaseRef },\n\t0x104a: { n:\"SerParent\", f:parse_SerParent },\n\t0x104b: { n:\"SerAuxTrend\", f:parse_SerAuxTrend },\n\t0x104e: { n:\"IFmtRecord\", f:parse_IFmtRecord },\n\t0x104f: { n:\"Pos\", f:parse_Pos },\n\t0x1050: { n:\"AlRuns\", f:parse_AlRuns },\n\t0x1051: { n:\"BRAI\", f:parse_BRAI },\n\t0x105b: { n:\"SerAuxErrBar\", f:parse_SerAuxErrBar },\n\t0x105c: { n:\"ClrtClient\", f:parse_ClrtClient },\n\t0x105d: { n:\"SerFmt\", f:parse_SerFmt },\n\t0x105f: { n:\"Chart3DBarShape\", f:parse_Chart3DBarShape },\n\t0x1060: { n:\"Fbi\", f:parse_Fbi },\n\t0x1061: { n:\"BopPop\", f:parse_BopPop },\n\t0x1062: { n:\"AxcExt\", f:parse_AxcExt },\n\t0x1063: { n:\"Dat\", f:parse_Dat },\n\t0x1064: { n:\"PlotGrowth\", f:parse_PlotGrowth },\n\t0x1065: { n:\"SIIndex\", f:parse_SIIndex },\n\t0x1066: { n:\"GelFrame\", f:parse_GelFrame },\n\t0x1067: { n:\"BopPopCustom\", f:parse_BopPopCustom },\n\t0x1068: { n:\"Fbi2\", f:parse_Fbi2 },\n\n\t/* These are specified in an older version of the spec */\n\t0x0016: { n:\"ExternCount\", f:parsenoop },\n\t0x007e: { n:\"RK\", f:parsenoop }, /* Not necessarily same as 0x027e */\n\t0x007f: { n:\"ImData\", f:parsenoop },\n\t0x0087: { n:\"Addin\", f:parsenoop },\n\t0x0088: { n:\"Edg\", f:parsenoop },\n\t0x0089: { n:\"Pub\", f:parsenoop },\n\t0x0091: { n:\"Sub\", f:parsenoop },\n\t0x0094: { n:\"LHRecord\", f:parsenoop },\n\t0x0095: { n:\"LHNGraph\", f:parsenoop },\n\t0x0096: { n:\"Sound\", f:parsenoop },\n\t0x00a9: { n:\"CoordList\", f:parsenoop },\n\t0x00ab: { n:\"GCW\", f:parsenoop },\n\t0x00bc: { n:\"ShrFmla\", f:parsenoop }, /* Not necessarily same as 0x04bc */\n\t0x00c2: { n:\"AddMenu\", f:parsenoop },\n\t0x00c3: { n:\"DelMenu\", f:parsenoop },\n\t0x00d6: { n:\"RString\", f:parsenoop },\n\t0x00df: { n:\"UDDesc\", f:parsenoop },\n\t0x00ea: { n:\"TabIdConf\", f:parsenoop },\n\t0x0162: { n:\"XL5Modify\", f:parsenoop },\n\t0x01a5: { n:\"FileSharing2\", f:parsenoop },\n\t0x0218: { n:\"Name\", f:parsenoop },\n\t0x0223: { n:\"ExternName\", f:parse_ExternName },\n\t0x0231: { n:\"Font\", f:parsenoop },\n\t0x0406: { n:\"Formula\", f:parse_Formula },\n\t0x086d: { n:\"FeatInfo\", f:parsenoop },\n\t0x0873: { n:\"FeatInfo11\", f:parsenoop },\n\t0x0881: { n:\"SXAddl12\", f:parsenoop },\n\t0x08c0: { n:\"AutoWebPub\", f:parsenoop },\n\t0x08c1: { n:\"ListObj\", f:parsenoop },\n\t0x08c2: { n:\"ListField\", f:parsenoop },\n\t0x08c3: { n:\"ListDV\", f:parsenoop },\n\t0x08c4: { n:\"ListCondFmt\", f:parsenoop },\n\t0x08c5: { n:\"ListCF\", f:parsenoop },\n\t0x08c6: { n:\"FMQry\", f:parsenoop },\n\t0x08c7: { n:\"FMSQry\", f:parsenoop },\n\t0x08c8: { n:\"PLV\", f:parsenoop }, /* supposedly PLV for Excel 11 */\n\t0x08c9: { n:\"LnExt\", f:parsenoop },\n\t0x08ca: { n:\"MkrExt\", f:parsenoop },\n\t0x08cb: { n:\"CrtCoopt\", f:parsenoop },\n\n\t0x0000: {}\n};\n\n\n/* Helper function to call out to ODS parser */\nfunction parse_ods(zip, opts) {\n\tif(typeof module !== \"undefined\" && typeof require !== 'undefined' && typeof ODS === 'undefined') ODS = require('./od' + 's');\n\tif(typeof ODS === 'undefined' || !ODS.parse_ods) throw new Error(\"Unsupported ODS\");\n\treturn ODS.parse_ods(zip, opts);\n}\nfunction fix_opts_func(defaults) {\n\treturn function fix_opts(opts) {\n\t\tfor(var i = 0; i != defaults.length; ++i) {\n\t\t\tvar d = defaults[i];\n\t\t\tif(opts[d[0]] === undefined) opts[d[0]] = d[1];\n\t\t\tif(d[2] === 'n') opts[d[0]] = Number(opts[d[0]]);\n\t\t}\n\t};\n}\n\nvar fix_read_opts = fix_opts_func([\n\t['cellNF', false], /* emit cell number format string as .z */\n\t['cellHTML', true], /* emit html string as .h */\n\t['cellFormula', true], /* emit formulae as .f */\n\t['cellStyles', false], /* emits style/theme as .s */\n\t['cellDates', false], /* emit date cells with type `d` */\n\n\t['sheetStubs', false], /* emit empty cells */\n\t['sheetRows', 0, 'n'], /* read n rows (0 = read all rows) */\n\n\t['bookDeps', false], /* parse calculation chains */\n\t['bookSheets', false], /* only try to get sheet names (no Sheets) */\n\t['bookProps', false], /* only try to get properties (no Sheets) */\n\t['bookFiles', false], /* include raw file structure (keys, files, cfb) */\n\t['bookVBA', false], /* include vba raw data (vbaraw) */\n\n\t['password',''], /* password */\n\t['WTF', false] /* WTF mode (throws errors) */\n]);\n\n\nvar fix_write_opts = fix_opts_func([\n\t['cellDates', false], /* write date cells with type `d` */\n\n\t['bookSST', false], /* Generate Shared String Table */\n\n\t['bookType', 'xlsx'], /* Type of workbook (xlsx/m/b) */\n\n\t['WTF', false] /* WTF mode (throws errors) */\n]);\nfunction safe_parse_wbrels(wbrels, sheets) {\n\tif(!wbrels) return 0;\n\ttry {\n\t\twbrels = sheets.map(function pwbr(w) { return [w.name, wbrels['!id'][w.id].Target]; });\n\t} catch(e) { return null; }\n\treturn !wbrels || wbrels.length === 0 ? null : wbrels;\n}\n\nfunction safe_parse_ws(zip, path, relsPath, sheet, sheetRels, sheets, opts) {\n\ttry {\n\t\tsheetRels[sheet]=parse_rels(getzipdata(zip, relsPath, true), path);\n\t\tsheets[sheet]=parse_ws(getzipdata(zip, path),path,opts,sheetRels[sheet]);\n\t} catch(e) { if(opts.WTF) throw e; }\n}\n\nvar nodirs = function nodirs(x){return x.substr(-1) != '/';};\nfunction parse_zip(zip, opts) {\n\tmake_ssf(SSF);\n\topts = opts || {};\n\tfix_read_opts(opts);\n\treset_cp();\n\n\t/* OpenDocument Part 3 Section 2.2.1 OpenDocument Package */\n\tif(safegetzipfile(zip, 'META-INF/manifest.xml')) return parse_ods(zip, opts);\n\n\tvar entries = keys(zip.files).filter(nodirs).sort();\n\tvar dir = parse_ct(getzipdata(zip, '[Content_Types].xml'), opts);\n\tvar xlsb = false;\n\tvar sheets, binname;\n\tif(dir.workbooks.length === 0) {\n\t\tbinname = \"xl/workbook.xml\";\n\t\tif(getzipdata(zip,binname, true)) dir.workbooks.push(binname);\n\t}\n\tif(dir.workbooks.length === 0) {\n\t\tbinname = \"xl/workbook.bin\";\n\t\tif(!getzipfile(zip,binname,true)) throw new Error(\"Could not find workbook\");\n\t\tdir.workbooks.push(binname);\n\t\txlsb = true;\n\t}\n\tif(dir.workbooks[0].substr(-3) == \"bin\") xlsb = true;\n\tif(xlsb) set_cp(1200);\n\n\tif(!opts.bookSheets && !opts.bookProps) {\n\t\tstrs = [];\n\t\tif(dir.sst) strs=parse_sst(getzipdata(zip, dir.sst.replace(/^\\//,'')), dir.sst, opts);\n\n\t\tstyles = {};\n\t\tif(dir.style) styles = parse_sty(getzipdata(zip, dir.style.replace(/^\\//,'')),dir.style, opts);\n\n\t\tthemes = {};\n\t\tif(opts.cellStyles && dir.themes.length) themes = parse_theme(getzipdata(zip, dir.themes[0].replace(/^\\//,''), true),dir.themes[0], opts);\n\t}\n\n\tvar wb = parse_wb(getzipdata(zip, dir.workbooks[0].replace(/^\\//,'')), dir.workbooks[0], opts);\n\n\tvar props = {}, propdata = \"\";\n\n\tif(dir.coreprops.length !== 0) {\n\t\tpropdata = getzipdata(zip, dir.coreprops[0].replace(/^\\//,''), true);\n\t\tif(propdata) props = parse_core_props(propdata);\n\t\tif(dir.extprops.length !== 0) {\n\t\t\tpropdata = getzipdata(zip, dir.extprops[0].replace(/^\\//,''), true);\n\t\t\tif(propdata) parse_ext_props(propdata, props);\n\t\t}\n\t}\n\n\tvar custprops = {};\n\tif(!opts.bookSheets || opts.bookProps) {\n\t\tif (dir.custprops.length !== 0) {\n\t\t\tpropdata = getzipdata(zip, dir.custprops[0].replace(/^\\//,''), true);\n\t\t\tif(propdata) custprops = parse_cust_props(propdata, opts);\n\t\t}\n\t}\n\n\tvar out = {};\n\tif(opts.bookSheets || opts.bookProps) {\n\t\tif(props.Worksheets && props.SheetNames.length > 0) sheets=props.SheetNames;\n\t\telse if(wb.Sheets) sheets = wb.Sheets.map(function pluck(x){ return x.name; });\n\t\tif(opts.bookProps) { out.Props = props; out.Custprops = custprops; }\n\t\tif(typeof sheets !== 'undefined') out.SheetNames = sheets;\n\t\tif(opts.bookSheets ? out.SheetNames : opts.bookProps) return out;\n\t}\n\tsheets = {};\n\n\tvar deps = {};\n\tif(opts.bookDeps && dir.calcchain) deps=parse_cc(getzipdata(zip, dir.calcchain.replace(/^\\//,'')),dir.calcchain,opts);\n\n\tvar i=0;\n\tvar sheetRels = {};\n\tvar path, relsPath;\n\tif(!props.Worksheets) {\n\t\tvar wbsheets = wb.Sheets;\n\t\tprops.Worksheets = wbsheets.length;\n\t\tprops.SheetNames = [];\n\t\tfor(var j = 0; j != wbsheets.length; ++j) {\n\t\t\tprops.SheetNames[j] = wbsheets[j].name;\n\t\t}\n\t}\n\n\tvar wbext = xlsb ? \"bin\" : \"xml\";\n\tvar wbrelsfile = 'xl/_rels/workbook.' + wbext + '.rels';\n\tvar wbrels = parse_rels(getzipdata(zip, wbrelsfile, true), wbrelsfile);\n\tif(wbrels) wbrels = safe_parse_wbrels(wbrels, wb.Sheets);\n\t/* Numbers iOS hack */\n\tvar nmode = (getzipdata(zip,\"xl/worksheets/sheet.xml\",true))?1:0;\n\tfor(i = 0; i != props.Worksheets; ++i) {\n\t\tif(wbrels) path = 'xl/' + (wbrels[i][1]).replace(/[\\/]?xl\\//, \"\");\n\t\telse {\n\t\t\tpath = 'xl/worksheets/sheet'+(i+1-nmode)+\".\" + wbext;\n\t\t\tpath = path.replace(/sheet0\\./,\"sheet.\");\n\t\t}\n\t\trelsPath = path.replace(/^(.*)(\\/)([^\\/]*)$/, \"$1/_rels/$3.rels\");\n\t\tsafe_parse_ws(zip, path, relsPath, props.SheetNames[i], sheetRels, sheets, opts);\n\t}\n\n\tif(dir.comments) parse_comments(zip, dir.comments, sheets, sheetRels, opts);\n\n\tout = {\n\t\tDirectory: dir,\n\t\tWorkbook: wb,\n\t\tProps: props,\n\t\tCustprops: custprops,\n\t\tDeps: deps,\n\t\tSheets: sheets,\n\t\tSheetNames: props.SheetNames,\n\t\tStrings: strs,\n\t\tStyles: styles,\n\t\tThemes: themes,\n\t\tSSF: SSF.get_table()\n\t};\n\tif(opts.bookFiles) {\n\t\tout.keys = entries;\n\t\tout.files = zip.files;\n\t}\n\tif(opts.bookVBA) {\n\t\tif(dir.vba.length > 0) out.vbaraw = getzipdata(zip,dir.vba[0],true);\n\t\telse if(dir.defaults.bin === 'application/vnd.ms-office.vbaProject') out.vbaraw = getzipdata(zip,'xl/vbaProject.bin',true);\n\t}\n\treturn out;\n}\nfunction add_rels(rels, rId, f, type, relobj) {\n\tif(!relobj) relobj = {};\n\tif(!rels['!id']) rels['!id'] = {};\n\trelobj.Id = 'rId' + rId;\n\trelobj.Type = type;\n\trelobj.Target = f;\n\tif(rels['!id'][relobj.Id]) throw new Error(\"Cannot rewrite rId \" + rId);\n\trels['!id'][relobj.Id] = relobj;\n\trels[('/' + relobj.Target).replace(\"//\",\"/\")] = relobj;\n}\n\nfunction write_zip(wb, opts) {\n\tif(wb && !wb.SSF) {\n\t\twb.SSF = SSF.get_table();\n\t}\n\tif(wb && wb.SSF) {\n\t\tmake_ssf(SSF); SSF.load_table(wb.SSF);\n\t\topts.revssf = evert_num(wb.SSF); opts.revssf[wb.SSF[65535]] = 0;\n\t}\n\topts.rels = {}; opts.wbrels = {};\n\topts.Strings = []; opts.Strings.Count = 0; opts.Strings.Unique = 0;\n\tvar wbext = opts.bookType == \"xlsb\" ? \"bin\" : \"xml\";\n\tvar ct = { workbooks: [], sheets: [], calcchains: [], themes: [], styles: [],\n\t\tcoreprops: [], extprops: [], custprops: [], strs:[], comments: [], vba: [],\n\t\tTODO:[], rels:[], xmlns: \"\" };\n\tfix_write_opts(opts = opts || {});\n\tvar zip = new jszip();\n\tvar f = \"\", rId = 0;\n\n\topts.cellXfs = [];\n\tget_cell_style(opts.cellXfs, {}, {revssf:{\"General\":0}});\n\n\tf = \"docProps/core.xml\";\n\tzip.file(f, write_core_props(wb.Props, opts));\n\tct.coreprops.push(f);\n\tadd_rels(opts.rels, 2, f, RELS.CORE_PROPS);\n\n\tf = \"docProps/app.xml\";\n\tif(!wb.Props) wb.Props = {};\n\twb.Props.SheetNames = wb.SheetNames;\n\twb.Props.Worksheets = wb.SheetNames.length;\n\tzip.file(f, write_ext_props(wb.Props, opts));\n\tct.extprops.push(f);\n\tadd_rels(opts.rels, 3, f, RELS.EXT_PROPS);\n\n\tif(wb.Custprops !== wb.Props && keys(wb.Custprops||{}).length > 0) {\n\t\tf = \"docProps/custom.xml\";\n\t\tzip.file(f, write_cust_props(wb.Custprops, opts));\n\t\tct.custprops.push(f);\n\t\tadd_rels(opts.rels, 4, f, RELS.CUST_PROPS);\n\t}\n\n\tf = \"xl/workbook.\" + wbext;\n\tzip.file(f, write_wb(wb, f, opts));\n\tct.workbooks.push(f);\n\tadd_rels(opts.rels, 1, f, RELS.WB);\n\n\tfor(rId=1;rId <= wb.SheetNames.length; ++rId) {\n\t\tf = \"xl/worksheets/sheet\" + rId + \".\" + wbext;\n\t\tzip.file(f, write_ws(rId-1, f, opts, wb));\n\t\tct.sheets.push(f);\n\t\tadd_rels(opts.wbrels, rId, \"worksheets/sheet\" + rId + \".\" + wbext, RELS.WS);\n\t}\n\n\tif(opts.Strings != null && opts.Strings.length > 0) {\n\t\tf = \"xl/sharedStrings.\" + wbext;\n\t\tzip.file(f, write_sst(opts.Strings, f, opts));\n\t\tct.strs.push(f);\n\t\tadd_rels(opts.wbrels, ++rId, \"sharedStrings.\" + wbext, RELS.SST);\n\t}\n\n\t/* TODO: something more intelligent with themes */\n\n\tf = \"xl/theme/theme1.xml\";\n\tzip.file(f, write_theme());\n\tct.themes.push(f);\n\tadd_rels(opts.wbrels, ++rId, \"theme/theme1.xml\", RELS.THEME);\n\n\t/* TODO: something more intelligent with styles */\n\n\tf = \"xl/styles.\" + wbext;\n\tzip.file(f, write_sty(wb, f, opts));\n\tct.styles.push(f);\n\tadd_rels(opts.wbrels, ++rId, \"styles.\" + wbext, RELS.STY);\n\n\tzip.file(\"[Content_Types].xml\", write_ct(ct, opts));\n\tzip.file('_rels/.rels', write_rels(opts.rels));\n\tzip.file('xl/_rels/workbook.' + wbext + '.rels', write_rels(opts.wbrels));\n\treturn zip;\n}\nfunction firstbyte(f,o) {\n\tswitch((o||{}).type || \"base64\") {\n\t\tcase 'buffer': return f[0];\n\t\tcase 'base64': return Base64.decode(f.substr(0,12)).charCodeAt(0);\n\t\tcase 'binary': return f.charCodeAt(0);\n\t\tcase 'array': return f[0];\n\t\tdefault: throw new Error(\"Unrecognized type \" + o.type);\n\t}\n}\n\nfunction read_zip(data, opts) {\n\tvar zip, d = data;\n\tvar o = opts||{};\n\tif(!o.type) o.type = (has_buf && Buffer.isBuffer(data)) ? \"buffer\" : \"base64\";\n\tswitch(o.type) {\n\t\tcase \"base64\": zip = new jszip(d, { base64:true }); break;\n\t\tcase \"binary\": case \"array\": zip = new jszip(d, { base64:false }); break;\n\t\tcase \"buffer\": zip = new jszip(d); break;\n\t\tcase \"file\": zip=new jszip(d=_fs.readFileSync(data)); break;\n\t\tdefault: throw new Error(\"Unrecognized type \" + o.type);\n\t}\n\treturn parse_zip(zip, o);\n}\n\nfunction readSync(data, opts) {\n\tvar zip, d = data, isfile = false, n;\n\tvar o = opts||{};\n\tif(!o.type) o.type = (has_buf && Buffer.isBuffer(data)) ? \"buffer\" : \"base64\";\n\tif(o.type == \"file\") { isfile = true; o.type = \"buffer\"; d = _fs.readFileSync(data); }\n\tswitch((n = firstbyte(d, o))) {\n\t\tcase 0xD0:\n\t\t\tif(isfile) o.type = \"file\";\n\t\t\treturn parse_xlscfb(CFB.read(data, o), o);\n\t\tcase 0x09: return parse_xlscfb(s2a(o.type === 'base64' ? Base64.decode(data) : data), o);\n\t\tcase 0x3C: return parse_xlml(d, o);\n\t\tcase 0x50:\n\t\t\tif(isfile) o.type = \"file\";\n\t\t\treturn read_zip(data, opts);\n\t\tdefault: throw new Error(\"Unsupported file \" + n);\n\t}\n}\n\nfunction readFileSync(data, opts) {\n\tvar o = opts||{}; o.type = 'file';\n\treturn readSync(data, o);\n}\nfunction write_zip_type(wb, opts) {\n\tvar o = opts||{};\n\tvar z = write_zip(wb, o);\n\tswitch(o.type) {\n\t\tcase \"base64\": return z.generate({type:\"base64\"});\n\t\tcase \"binary\": return z.generate({type:\"string\"});\n\t\tcase \"buffer\": return z.generate({type:\"nodebuffer\"});\n\t\tcase \"file\": return _fs.writeFileSync(o.file, z.generate({type:\"nodebuffer\"}));\n\t\tdefault: throw new Error(\"Unrecognized type \" + o.type);\n\t}\n}\n\nfunction writeSync(wb, opts) {\n\tvar o = opts||{};\n\tswitch(o.bookType) {\n\t\tcase 'xml': return write_xlml(wb, o);\n\t\tdefault: return write_zip_type(wb, o);\n\t}\n}\n\nfunction writeFileSync(wb, filename, opts) {\n\tvar o = opts||{}; o.type = 'file';\n\to.file = filename;\n\tswitch(o.file.substr(-5).toLowerCase()) {\n\t\tcase '.xlsx': o.bookType = 'xlsx'; break;\n\t\tcase '.xlsm': o.bookType = 'xlsm'; break;\n\t\tcase '.xlsb': o.bookType = 'xlsb'; break;\n\tdefault: switch(o.file.substr(-4).toLowerCase()) {\n\t\tcase '.xls': o.bookType = 'xls'; break;\n\t\tcase '.xml': o.bookType = 'xml'; break;\n\t}}\n\treturn writeSync(wb, o);\n}\n\nfunction decode_row(rowstr) { return parseInt(unfix_row(rowstr),10) - 1; }\nfunction encode_row(row) { return \"\" + (row + 1); }\nfunction fix_row(cstr) { return cstr.replace(/([A-Z]|^)(\\d+)$/,\"$1$$$2\"); }\nfunction unfix_row(cstr) { return cstr.replace(/\\$(\\d+)$/,\"$1\"); }\n\nfunction decode_col(colstr) { var c = unfix_col(colstr), d = 0, i = 0; for(; i !== c.length; ++i) d = 26*d + c.charCodeAt(i) - 64; return d - 1; }\nfunction encode_col(col) { var s=\"\"; for(++col; col; col=Math.floor((col-1)/26)) s = String.fromCharCode(((col-1)%26) + 65) + s; return s; }\nfunction fix_col(cstr) { return cstr.replace(/^([A-Z])/,\"$$$1\"); }\nfunction unfix_col(cstr) { return cstr.replace(/^\\$([A-Z])/,\"$1\"); }\n\nfunction split_cell(cstr) { return cstr.replace(/(\\$?[A-Z]*)(\\$?\\d*)/,\"$1,$2\").split(\",\"); }\nfunction decode_cell(cstr) { var splt = split_cell(cstr); return { c:decode_col(splt[0]), r:decode_row(splt[1]) }; }\nfunction encode_cell(cell) { return encode_col(cell.c) + encode_row(cell.r); }\nfunction fix_cell(cstr) { return fix_col(fix_row(cstr)); }\nfunction unfix_cell(cstr) { return unfix_col(unfix_row(cstr)); }\nfunction decode_range(range) { var x =range.split(\":\").map(decode_cell); return {s:x[0],e:x[x.length-1]}; }\nfunction encode_range(cs,ce) {\n\tif(ce === undefined || typeof ce === 'number') return encode_range(cs.s, cs.e);\n\tif(typeof cs !== 'string') cs = encode_cell(cs); if(typeof ce !== 'string') ce = encode_cell(ce);\n\treturn cs == ce ? cs : cs + \":\" + ce;\n}\n\nfunction safe_decode_range(range) {\n\tvar o = {s:{c:0,r:0},e:{c:0,r:0}};\n\tvar idx = 0, i = 0, cc = 0;\n\tvar len = range.length;\n\tfor(idx = 0; i < len; ++i) {\n\t\tif((cc=range.charCodeAt(i)-64) < 1 || cc > 26) break;\n\t\tidx = 26*idx + cc;\n\t}\n\to.s.c = --idx;\n\n\tfor(idx = 0; i < len; ++i) {\n\t\tif((cc=range.charCodeAt(i)-48) < 0 || cc > 9) break;\n\t\tidx = 10*idx + cc;\n\t}\n\to.s.r = --idx;\n\n\tif(i === len || range.charCodeAt(++i) === 58) { o.e.c=o.s.c; o.e.r=o.s.r; return o; }\n\n\tfor(idx = 0; i != len; ++i) {\n\t\tif((cc=range.charCodeAt(i)-64) < 1 || cc > 26) break;\n\t\tidx = 26*idx + cc;\n\t}\n\to.e.c = --idx;\n\n\tfor(idx = 0; i != len; ++i) {\n\t\tif((cc=range.charCodeAt(i)-48) < 0 || cc > 9) break;\n\t\tidx = 10*idx + cc;\n\t}\n\to.e.r = --idx;\n\treturn o;\n}\n\nfunction safe_format_cell(cell, v) {\n\tif(cell.z !== undefined) try { return (cell.w = SSF.format(cell.z, v)); } catch(e) { }\n\tif(!cell.XF) return v;\n\ttry { return (cell.w = SSF.format(cell.XF.ifmt||0, v)); } catch(e) { return ''+v; }\n}\n\nfunction format_cell(cell, v) {\n\tif(cell == null || cell.t == null) return \"\";\n\tif(cell.w !== undefined) return cell.w;\n\tif(v === undefined) return safe_format_cell(cell, cell.v);\n\treturn safe_format_cell(cell, v);\n}\n\nfunction sheet_to_json(sheet, opts){\n\tvar val, row, range, header = 0, offset = 1, r, hdr = [], isempty, R, C, v;\n\tvar o = opts != null ? opts : {};\n\tvar raw = o.raw;\n\tif(sheet == null || sheet[\"!ref\"] == null) return [];\n\trange = o.range !== undefined ? o.range : sheet[\"!ref\"];\n\tif(o.header === 1) header = 1;\n\telse if(o.header === \"A\") header = 2;\n\telse if(Array.isArray(o.header)) header = 3;\n\tswitch(typeof range) {\n\t\tcase 'string': r = safe_decode_range(range); break;\n\t\tcase 'number': r = safe_decode_range(sheet[\"!ref\"]); r.s.r = range; break;\n\t\tdefault: r = range;\n\t}\n\tif(header > 0) offset = 0;\n\tvar rr = encode_row(r.s.r);\n\tvar cols = new Array(r.e.c-r.s.c+1);\n\tvar out = new Array(r.e.r-r.s.r-offset+1);\n\tvar outi = 0;\n\tfor(C = r.s.c; C <= r.e.c; ++C) {\n\t\tcols[C] = encode_col(C);\n\t\tval = sheet[cols[C] + rr];\n\t\tswitch(header) {\n\t\t\tcase 1: hdr[C] = C; break;\n\t\t\tcase 2: hdr[C] = cols[C]; break;\n\t\t\tcase 3: hdr[C] = o.header[C - r.s.c]; break;\n\t\t\tdefault:\n\t\t\t\tif(val === undefined) continue;\n\t\t\t\thdr[C] = format_cell(val);\n\t\t}\n\t}\n\n\tfor (R = r.s.r + offset; R <= r.e.r; ++R) {\n\t\trr = encode_row(R);\n\t\tisempty = true;\n\t\tif(header === 1) row = [];\n\t\telse {\n\t\t\trow = {};\n\t\t\tif(Object.defineProperty) Object.defineProperty(row, '__rowNum__', {value:R, enumerable:false});\n\t\t\telse row.__rowNum__ = R;\n\t\t}\n\t\tfor (C = r.s.c; C <= r.e.c; ++C) {\n\t\t\tval = sheet[cols[C] + rr];\n\t\t\tif(val === undefined || val.t === undefined) continue;\n\t\t\tv = val.v;\n\t\t\tswitch(val.t){\n\t\t\t\tcase 'e': continue;\n\t\t\t\tcase 's': break;\n\t\t\t\tcase 'b': case 'n': break;\n\t\t\t\tdefault: throw 'unrecognized type ' + val.t;\n\t\t\t}\n\t\t\tif(v !== undefined) {\n\t\t\t\trow[hdr[C]] = raw ? v : format_cell(val,v);\n\t\t\t\tisempty = false;\n\t\t\t}\n\t\t}\n\t\tif(isempty === false || header === 1) out[outi++] = row;\n\t}\n\tout.length = outi;\n\treturn out;\n}\n\nfunction sheet_to_row_object_array(sheet, opts) { return sheet_to_json(sheet, opts != null ? opts : {}); }\n\nfunction sheet_to_csv(sheet, opts) {\n\tvar out = \"\", txt = \"\", qreg = /\"/g;\n\tvar o = opts == null ? {} : opts;\n\tif(sheet == null || sheet[\"!ref\"] == null) return \"\";\n\tvar r = safe_decode_range(sheet[\"!ref\"]);\n\tvar FS = o.FS !== undefined ? o.FS : \",\", fs = FS.charCodeAt(0);\n\tvar RS = o.RS !== undefined ? o.RS : \"\\n\", rs = RS.charCodeAt(0);\n\tvar row = \"\", rr = \"\", cols = [];\n\tvar i = 0, cc = 0, val;\n\tvar R = 0, C = 0;\n\tfor(C = r.s.c; C <= r.e.c; ++C) cols[C] = encode_col(C);\n\tfor(R = r.s.r; R <= r.e.r; ++R) {\n\t\trow = \"\";\n\t\trr = encode_row(R);\n\t\tfor(C = r.s.c; C <= r.e.c; ++C) {\n\t\t\tval = sheet[cols[C] + rr];\n\t\t\ttxt = val !== undefined ? ''+format_cell(val) : \"\";\n\t\t\tfor(i = 0, cc = 0; i !== txt.length; ++i) if((cc = txt.charCodeAt(i)) === fs || cc === rs || cc === 34) {\n\t\t\t\ttxt = \"\\\"\" + txt.replace(qreg, '\"\"') + \"\\\"\"; break; }\n\t\t\trow += (C === r.s.c ? \"\" : FS) + txt;\n\t\t}\n\t\tout += row + RS;\n\t}\n\treturn out;\n}\nvar make_csv = sheet_to_csv;\n\nfunction sheet_to_formulae(sheet) {\n\tvar cmds, y = \"\", x, val=\"\";\n\tif(sheet == null || sheet[\"!ref\"] == null) return \"\";\n\tvar r = safe_decode_range(sheet['!ref']), rr = \"\", cols = [], C;\n\tcmds = new Array((r.e.r-r.s.r+1)*(r.e.c-r.s.c+1));\n\tvar i = 0;\n\tfor(C = r.s.c; C <= r.e.c; ++C) cols[C] = encode_col(C);\n\tfor(var R = r.s.r; R <= r.e.r; ++R) {\n\t\trr = encode_row(R);\n\t\tfor(C = r.s.c; C <= r.e.c; ++C) {\n\t\t\ty = cols[C] + rr;\n\t\t\tx = sheet[y];\n\t\t\tval = \"\";\n\t\t\tif(x === undefined) continue;\n\t\t\tif(x.f != null) val = x.f;\n\t\t\telse if(x.w !== undefined) val = \"'\" + x.w;\n\t\t\telse if(x.v === undefined) continue;\n\t\t\telse val = \"\"+x.v;\n\t\t\tcmds[i++] = y + \"=\" + val;\n\t\t}\n\t}\n\tcmds.length = i;\n\treturn cmds;\n}\n\nvar utils = {\n\tencode_col: encode_col,\n\tencode_row: encode_row,\n\tencode_cell: encode_cell,\n\tencode_range: encode_range,\n\tdecode_col: decode_col,\n\tdecode_row: decode_row,\n\tsplit_cell: split_cell,\n\tdecode_cell: decode_cell,\n\tdecode_range: decode_range,\n\tformat_cell: format_cell,\n\tget_formulae: sheet_to_formulae,\n\tmake_csv: sheet_to_csv,\n\tmake_json: sheet_to_json,\n\tmake_formulae: sheet_to_formulae,\n\tsheet_to_csv: sheet_to_csv,\n\tsheet_to_json: sheet_to_json,\n\tsheet_to_formulae: sheet_to_formulae,\n\tsheet_to_row_object_array: sheet_to_row_object_array\n};\nXLSX.parse_xlscfb = parse_xlscfb;\nXLSX.parse_zip = parse_zip;\nXLSX.read = readSync; //xlsread\nXLSX.readFile = readFileSync; //readFile\nXLSX.readFileSync = readFileSync;\nXLSX.write = writeSync;\nXLSX.writeFile = writeFileSync;\nXLSX.writeFileSync = writeFileSync;\nXLSX.utils = utils;\nXLSX.CFB = CFB;\nXLSX.SSF = SSF;\n})(typeof exports !== 'undefined' ? exports : XLSX);\nvar XLS = XLSX;\n$tw.utils.extend(old_exports,exports);exports = old_exports;module.exports=exports;",
            "type": "application/javascript",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/xlsx.js",
            "module-type": "library"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/dist/cpexcel.js": {
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j != D[131].length; ++j) if(D[131][j].charCodeAt(0) !== 0xFFFD) { e[D[131][j]] = 33536 + j; d[33536 + j] = D[131][j];}\nD[132] = \"����������������������������������������������������������������АБВГДЕЁЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ���������������абвгдеёжзийклмн�опрстуфхцчшщъыьэюя�������������─│┌┐┘└├┬┤┴┼━┃┏┓┛┗┣┳┫┻╋┠┯┨┷┿┝┰┥┸╂�����������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[132].length; ++j) if(D[132][j].charCodeAt(0) !== 0xFFFD) { e[D[132][j]] = 33792 + j; d[33792 + j] = D[132][j];}\nD[135] = \"����������������������������������������������������������������①②③④⑤⑥⑦⑧⑨⑩⑪⑫⑬⑭⑮⑯⑰⑱⑲⑳ⅠⅡⅢⅣⅤⅥⅦⅧⅨⅩ�㍉㌔㌢㍍㌘㌧㌃㌶㍑㍗㌍㌦㌣㌫㍊㌻㎜㎝㎞㎎㎏㏄㎡��������㍻�〝〟№㏍℡㊤㊥㊦㊧㊨㈱㈲㈹㍾㍽㍼≒≡∫∮∑√⊥∠∟⊿∵∩∪���������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[135].length; ++j) if(D[135][j].charCodeAt(0) !== 0xFFFD) { e[D[135][j]] = 34560 + j; d[34560 + j] = D[135][j];}\nD[136] = \"���������������������������������������������������������������������������������������������������������������������������������������������������������������亜唖娃阿哀愛挨姶逢葵茜穐悪握渥旭葦芦鯵梓圧斡扱宛姐虻飴絢綾鮎或粟袷安庵按暗案闇鞍杏以伊位依偉囲夷委威尉惟意慰易椅為畏異移維緯胃萎衣謂違遺医井亥域育郁磯一壱溢逸稲茨芋鰯允印咽員因姻引飲淫胤蔭���\".split(\"\");\nfor(j = 0; 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j != D[139].length; ++j) if(D[139][j].charCodeAt(0) !== 0xFFFD) { e[D[139][j]] = 35584 + j; d[35584 + j] = D[139][j];}\nD[140] = \"����������������������������������������������������������������掘窟沓靴轡窪熊隈粂栗繰桑鍬勲君薫訓群軍郡卦袈祁係傾刑兄啓圭珪型契形径恵慶慧憩掲携敬景桂渓畦稽系経継繋罫茎荊蛍計詣警軽頚鶏芸迎鯨�劇戟撃激隙桁傑欠決潔穴結血訣月件倹倦健兼券剣喧圏堅嫌建憲懸拳捲検権牽犬献研硯絹県肩見謙賢軒遣鍵険顕験鹸元原厳幻弦減源玄現絃舷言諺限乎個古呼固姑孤己庫弧戸故枯湖狐糊袴股胡菰虎誇跨鈷雇顧鼓五互伍午呉吾娯後御悟梧檎瑚碁語誤護醐乞鯉交佼侯候倖光公功効勾厚口向���\".split(\"\");\nfor(j = 0; j != D[140].length; ++j) if(D[140][j].charCodeAt(0) !== 0xFFFD) { e[D[140][j]] = 35840 + j; d[35840 + j] = D[140][j];}\nD[141] = \"����������������������������������������������������������������后喉坑垢好孔孝宏工巧巷幸広庚康弘恒慌抗拘控攻昂晃更杭校梗構江洪浩港溝甲皇硬稿糠紅紘絞綱耕考肯肱腔膏航荒行衡講貢購郊酵鉱砿鋼閤降�項香高鴻剛劫号合壕拷濠豪轟麹克刻告国穀酷鵠黒獄漉腰甑忽惚骨狛込此頃今困坤墾婚恨懇昏昆根梱混痕紺艮魂些佐叉唆嵯左差査沙瑳砂詐鎖裟坐座挫債催再最哉塞妻宰彩才採栽歳済災采犀砕砦祭斎細菜裁載際剤在材罪財冴坂阪堺榊肴咲崎埼碕鷺作削咋搾昨朔柵窄策索錯桜鮭笹匙冊刷���\".split(\"\");\nfor(j = 0; j != D[141].length; ++j) if(D[141][j].charCodeAt(0) !== 0xFFFD) { e[D[141][j]] = 36096 + j; d[36096 + j] = D[141][j];}\nD[142] = \"����������������������������������������������������������������察拶撮擦札殺薩雑皐鯖捌錆鮫皿晒三傘参山惨撒散桟燦珊産算纂蚕讃賛酸餐斬暫残仕仔伺使刺司史嗣四士始姉姿子屍市師志思指支孜斯施旨枝止�死氏獅祉私糸紙紫肢脂至視詞詩試誌諮資賜雌飼歯事似侍児字寺慈持時次滋治爾璽痔磁示而耳自蒔辞汐鹿式識鴫竺軸宍雫七叱執失嫉室悉湿漆疾質実蔀篠偲柴芝屡蕊縞舎写射捨赦斜煮社紗者謝車遮蛇邪借勺尺杓灼爵酌釈錫若寂弱惹主取守手朱殊狩珠種腫趣酒首儒受呪寿授樹綬需囚収周���\".split(\"\");\nfor(j = 0; j != D[142].length; ++j) if(D[142][j].charCodeAt(0) !== 0xFFFD) { e[D[142][j]] = 36352 + j; d[36352 + j] = D[142][j];}\nD[143] = \"����������������������������������������������������������������宗就州修愁拾洲秀秋終繍習臭舟蒐衆襲讐蹴輯週酋酬集醜什住充十従戎柔汁渋獣縦重銃叔夙宿淑祝縮粛塾熟出術述俊峻春瞬竣舜駿准循旬楯殉淳�準潤盾純巡遵醇順処初所暑曙渚庶緒署書薯藷諸助叙女序徐恕鋤除傷償勝匠升召哨商唱嘗奨妾娼宵将小少尚庄床廠彰承抄招掌捷昇昌昭晶松梢樟樵沼消渉湘焼焦照症省硝礁祥称章笑粧紹肖菖蒋蕉衝裳訟証詔詳象賞醤鉦鍾鐘障鞘上丈丞乗冗剰城場壌嬢常情擾条杖浄状畳穣蒸譲醸錠嘱埴飾���\".split(\"\");\nfor(j = 0; j != D[143].length; ++j) if(D[143][j].charCodeAt(0) !== 0xFFFD) { e[D[143][j]] = 36608 + j; d[36608 + j] = D[143][j];}\nD[144] = \"����������������������������������������������������������������拭植殖燭織職色触食蝕辱尻伸信侵唇娠寝審心慎振新晋森榛浸深申疹真神秦紳臣芯薪親診身辛進針震人仁刃塵壬尋甚尽腎訊迅陣靭笥諏須酢図厨�逗吹垂帥推水炊睡粋翠衰遂酔錐錘随瑞髄崇嵩数枢趨雛据杉椙菅頗雀裾澄摺寸世瀬畝是凄制勢姓征性成政整星晴棲栖正清牲生盛精聖声製西誠誓請逝醒青静斉税脆隻席惜戚斥昔析石積籍績脊責赤跡蹟碩切拙接摂折設窃節説雪絶舌蝉仙先千占宣専尖川戦扇撰栓栴泉浅洗染潜煎煽旋穿箭線���\".split(\"\");\nfor(j = 0; j != D[144].length; ++j) if(D[144][j].charCodeAt(0) !== 0xFFFD) { e[D[144][j]] = 36864 + j; d[36864 + j] = D[144][j];}\nD[145] = \"����������������������������������������������������������������繊羨腺舛船薦詮賎践選遷銭銑閃鮮前善漸然全禅繕膳糎噌塑岨措曾曽楚狙疏疎礎祖租粗素組蘇訴阻遡鼠僧創双叢倉喪壮奏爽宋層匝惣想捜掃挿掻�操早曹巣槍槽漕燥争痩相窓糟総綜聡草荘葬蒼藻装走送遭鎗霜騒像増憎臓蔵贈造促側則即息捉束測足速俗属賊族続卒袖其揃存孫尊損村遜他多太汰詑唾堕妥惰打柁舵楕陀駄騨体堆対耐岱帯待怠態戴替泰滞胎腿苔袋貸退逮隊黛鯛代台大第醍題鷹滝瀧卓啄宅托択拓沢濯琢託鐸濁諾茸凧蛸只���\".split(\"\");\nfor(j = 0; j != D[145].length; ++j) if(D[145][j].charCodeAt(0) !== 0xFFFD) { e[D[145][j]] = 37120 + j; d[37120 + j] = D[145][j];}\nD[146] = \"����������������������������������������������������������������叩但達辰奪脱巽竪辿棚谷狸鱈樽誰丹単嘆坦担探旦歎淡湛炭短端箪綻耽胆蛋誕鍛団壇弾断暖檀段男談値知地弛恥智池痴稚置致蜘遅馳築畜竹筑蓄�逐秩窒茶嫡着中仲宙忠抽昼柱注虫衷註酎鋳駐樗瀦猪苧著貯丁兆凋喋寵帖帳庁弔張彫徴懲挑暢朝潮牒町眺聴脹腸蝶調諜超跳銚長頂鳥勅捗直朕沈珍賃鎮陳津墜椎槌追鎚痛通塚栂掴槻佃漬柘辻蔦綴鍔椿潰坪壷嬬紬爪吊釣鶴亭低停偵剃貞呈堤定帝底庭廷弟悌抵挺提梯汀碇禎程締艇訂諦蹄逓���\".split(\"\");\nfor(j = 0; j != D[146].length; ++j) if(D[146][j].charCodeAt(0) !== 0xFFFD) { e[D[146][j]] = 37376 + j; d[37376 + j] = D[146][j];}\nD[147] = \"����������������������������������������������������������������邸鄭釘鼎泥摘擢敵滴的笛適鏑溺哲徹撤轍迭鉄典填天展店添纏甜貼転顛点伝殿澱田電兎吐堵塗妬屠徒斗杜渡登菟賭途都鍍砥砺努度土奴怒倒党冬�凍刀唐塔塘套宕島嶋悼投搭東桃梼棟盗淘湯涛灯燈当痘祷等答筒糖統到董蕩藤討謄豆踏逃透鐙陶頭騰闘働動同堂導憧撞洞瞳童胴萄道銅峠鴇匿得徳涜特督禿篤毒独読栃橡凸突椴届鳶苫寅酉瀞噸屯惇敦沌豚遁頓呑曇鈍奈那内乍凪薙謎灘捺鍋楢馴縄畷南楠軟難汝二尼弐迩匂賑肉虹廿日乳入���\".split(\"\");\nfor(j = 0; j != D[147].length; ++j) if(D[147][j].charCodeAt(0) !== 0xFFFD) { e[D[147][j]] = 37632 + j; d[37632 + j] = D[147][j];}\nD[148] = \"����������������������������������������������������������������如尿韮任妊忍認濡禰祢寧葱猫熱年念捻撚燃粘乃廼之埜嚢悩濃納能脳膿農覗蚤巴把播覇杷波派琶破婆罵芭馬俳廃拝排敗杯盃牌背肺輩配倍培媒梅�楳煤狽買売賠陪這蝿秤矧萩伯剥博拍柏泊白箔粕舶薄迫曝漠爆縛莫駁麦函箱硲箸肇筈櫨幡肌畑畠八鉢溌発醗髪伐罰抜筏閥鳩噺塙蛤隼伴判半反叛帆搬斑板氾汎版犯班畔繁般藩販範釆煩頒飯挽晩番盤磐蕃蛮匪卑否妃庇彼悲扉批披斐比泌疲皮碑秘緋罷肥被誹費避非飛樋簸備尾微枇毘琵眉美���\".split(\"\");\nfor(j = 0; j != D[148].length; ++j) if(D[148][j].charCodeAt(0) !== 0xFFFD) { e[D[148][j]] = 37888 + j; d[37888 + j] = D[148][j];}\nD[149] = \"����������������������������������������������������������������鼻柊稗匹疋髭彦膝菱肘弼必畢筆逼桧姫媛紐百謬俵彪標氷漂瓢票表評豹廟描病秒苗錨鋲蒜蛭鰭品彬斌浜瀕貧賓頻敏瓶不付埠夫婦富冨布府怖扶敷�斧普浮父符腐膚芙譜負賦赴阜附侮撫武舞葡蕪部封楓風葺蕗伏副復幅服福腹複覆淵弗払沸仏物鮒分吻噴墳憤扮焚奮粉糞紛雰文聞丙併兵塀幣平弊柄並蔽閉陛米頁僻壁癖碧別瞥蔑箆偏変片篇編辺返遍便勉娩弁鞭保舗鋪圃捕歩甫補輔穂募墓慕戊暮母簿菩倣俸包呆報奉宝峰峯崩庖抱捧放方朋���\".split(\"\");\nfor(j = 0; j != D[149].length; ++j) if(D[149][j].charCodeAt(0) !== 0xFFFD) { e[D[149][j]] = 38144 + j; d[38144 + j] = D[149][j];}\nD[150] = \"����������������������������������������������������������������法泡烹砲縫胞芳萌蓬蜂褒訪豊邦鋒飽鳳鵬乏亡傍剖坊妨帽忘忙房暴望某棒冒紡肪膨謀貌貿鉾防吠頬北僕卜墨撲朴牧睦穆釦勃没殆堀幌奔本翻凡盆�摩磨魔麻埋妹昧枚毎哩槙幕膜枕鮪柾鱒桝亦俣又抹末沫迄侭繭麿万慢満漫蔓味未魅巳箕岬密蜜湊蓑稔脈妙粍民眠務夢無牟矛霧鵡椋婿娘冥名命明盟迷銘鳴姪牝滅免棉綿緬面麺摸模茂妄孟毛猛盲網耗蒙儲木黙目杢勿餅尤戻籾貰問悶紋門匁也冶夜爺耶野弥矢厄役約薬訳躍靖柳薮鑓愉愈油癒���\".split(\"\");\nfor(j = 0; j != D[150].length; ++j) if(D[150][j].charCodeAt(0) !== 0xFFFD) { e[D[150][j]] = 38400 + j; d[38400 + j] = D[150][j];}\nD[151] = \"����������������������������������������������������������������諭輸唯佑優勇友宥幽悠憂揖有柚湧涌猶猷由祐裕誘遊邑郵雄融夕予余与誉輿預傭幼妖容庸揚揺擁曜楊様洋溶熔用窯羊耀葉蓉要謡踊遥陽養慾抑欲�沃浴翌翼淀羅螺裸来莱頼雷洛絡落酪乱卵嵐欄濫藍蘭覧利吏履李梨理璃痢裏裡里離陸律率立葎掠略劉流溜琉留硫粒隆竜龍侶慮旅虜了亮僚両凌寮料梁涼猟療瞭稜糧良諒遼量陵領力緑倫厘林淋燐琳臨輪隣鱗麟瑠塁涙累類令伶例冷励嶺怜玲礼苓鈴隷零霊麗齢暦歴列劣烈裂廉恋憐漣煉簾練聯���\".split(\"\");\nfor(j = 0; j != D[151].length; ++j) if(D[151][j].charCodeAt(0) !== 0xFFFD) { e[D[151][j]] = 38656 + j; d[38656 + j] = D[151][j];}\nD[152] = \"����������������������������������������������������������������蓮連錬呂魯櫓炉賂路露労婁廊弄朗楼榔浪漏牢狼篭老聾蝋郎六麓禄肋録論倭和話歪賄脇惑枠鷲亙亘鰐詫藁蕨椀湾碗腕��������������������������������������������弌丐丕个丱丶丼丿乂乖乘亂亅豫亊舒弍于亞亟亠亢亰亳亶从仍仄仆仂仗仞仭仟价伉佚估佛佝佗佇佶侈侏侘佻佩佰侑佯來侖儘俔俟俎俘俛俑俚俐俤俥倚倨倔倪倥倅伜俶倡倩倬俾俯們倆偃假會偕偐偈做偖偬偸傀傚傅傴傲���\".split(\"\");\nfor(j = 0; j != D[152].length; ++j) if(D[152][j].charCodeAt(0) !== 0xFFFD) { e[D[152][j]] = 38912 + j; d[38912 + j] = D[152][j];}\nD[153] = \"����������������������������������������������������������������僉僊傳僂僖僞僥僭僣僮價僵儉儁儂儖儕儔儚儡儺儷儼儻儿兀兒兌兔兢竸兩兪兮冀冂囘册冉冏冑冓冕冖冤冦冢冩冪冫决冱冲冰况冽凅凉凛几處凩凭�凰凵凾刄刋刔刎刧刪刮刳刹剏剄剋剌剞剔剪剴剩剳剿剽劍劔劒剱劈劑辨辧劬劭劼劵勁勍勗勞勣勦飭勠勳勵勸勹匆匈甸匍匐匏匕匚匣匯匱匳匸區卆卅丗卉卍凖卞卩卮夘卻卷厂厖厠厦厥厮厰厶參簒雙叟曼燮叮叨叭叺吁吽呀听吭吼吮吶吩吝呎咏呵咎呟呱呷呰咒呻咀呶咄咐咆哇咢咸咥咬哄哈咨���\".split(\"\");\nfor(j = 0; j != D[153].length; ++j) if(D[153][j].charCodeAt(0) !== 0xFFFD) { e[D[153][j]] = 39168 + j; d[39168 + j] = D[153][j];}\nD[154] = \"����������������������������������������������������������������咫哂咤咾咼哘哥哦唏唔哽哮哭哺哢唹啀啣啌售啜啅啖啗唸唳啝喙喀咯喊喟啻啾喘喞單啼喃喩喇喨嗚嗅嗟嗄嗜嗤嗔嘔嗷嘖嗾嗽嘛嗹噎噐營嘴嘶嘲嘸�噫噤嘯噬噪嚆嚀嚊嚠嚔嚏嚥嚮嚶嚴囂嚼囁囃囀囈囎囑囓囗囮囹圀囿圄圉圈國圍圓團圖嗇圜圦圷圸坎圻址坏坩埀垈坡坿垉垓垠垳垤垪垰埃埆埔埒埓堊埖埣堋堙堝塲堡塢塋塰毀塒堽塹墅墹墟墫墺壞墻墸墮壅壓壑壗壙壘壥壜壤壟壯壺壹壻壼壽夂夊夐夛梦夥夬夭夲夸夾竒奕奐奎奚奘奢奠奧奬奩���\".split(\"\");\nfor(j = 0; j != D[154].length; ++j) if(D[154][j].charCodeAt(0) !== 0xFFFD) { e[D[154][j]] = 39424 + j; d[39424 + j] = D[154][j];}\nD[155] = \"����������������������������������������������������������������奸妁妝佞侫妣妲姆姨姜妍姙姚娥娟娑娜娉娚婀婬婉娵娶婢婪媚媼媾嫋嫂媽嫣嫗嫦嫩嫖嫺嫻嬌嬋嬖嬲嫐嬪嬶嬾孃孅孀孑孕孚孛孥孩孰孳孵學斈孺宀�它宦宸寃寇寉寔寐寤實寢寞寥寫寰寶寳尅將專對尓尠尢尨尸尹屁屆屎屓屐屏孱屬屮乢屶屹岌岑岔妛岫岻岶岼岷峅岾峇峙峩峽峺峭嶌峪崋崕崗嵜崟崛崑崔崢崚崙崘嵌嵒嵎嵋嵬嵳嵶嶇嶄嶂嶢嶝嶬嶮嶽嶐嶷嶼巉巍巓巒巖巛巫已巵帋帚帙帑帛帶帷幄幃幀幎幗幔幟幢幤幇幵并幺麼广庠廁廂廈廐廏���\".split(\"\");\nfor(j = 0; j != D[155].length; ++j) if(D[155][j].charCodeAt(0) !== 0xFFFD) { e[D[155][j]] = 39680 + j; d[39680 + j] = D[155][j];}\nD[156] = \"����������������������������������������������������������������廖廣廝廚廛廢廡廨廩廬廱廳廰廴廸廾弃弉彝彜弋弑弖弩弭弸彁彈彌彎弯彑彖彗彙彡彭彳彷徃徂彿徊很徑徇從徙徘徠徨徭徼忖忻忤忸忱忝悳忿怡恠�怙怐怩怎怱怛怕怫怦怏怺恚恁恪恷恟恊恆恍恣恃恤恂恬恫恙悁悍惧悃悚悄悛悖悗悒悧悋惡悸惠惓悴忰悽惆悵惘慍愕愆惶惷愀惴惺愃愡惻惱愍愎慇愾愨愧慊愿愼愬愴愽慂慄慳慷慘慙慚慫慴慯慥慱慟慝慓慵憙憖憇憬憔憚憊憑憫憮懌懊應懷懈懃懆憺懋罹懍懦懣懶懺懴懿懽懼懾戀戈戉戍戌戔戛���\".split(\"\");\nfor(j = 0; j != D[156].length; ++j) if(D[156][j].charCodeAt(0) !== 0xFFFD) { e[D[156][j]] = 39936 + j; d[39936 + j] = D[156][j];}\nD[157] = \"����������������������������������������������������������������戞戡截戮戰戲戳扁扎扞扣扛扠扨扼抂抉找抒抓抖拔抃抔拗拑抻拏拿拆擔拈拜拌拊拂拇抛拉挌拮拱挧挂挈拯拵捐挾捍搜捏掖掎掀掫捶掣掏掉掟掵捫�捩掾揩揀揆揣揉插揶揄搖搴搆搓搦搶攝搗搨搏摧摯摶摎攪撕撓撥撩撈撼據擒擅擇撻擘擂擱擧舉擠擡抬擣擯攬擶擴擲擺攀擽攘攜攅攤攣攫攴攵攷收攸畋效敖敕敍敘敞敝敲數斂斃變斛斟斫斷旃旆旁旄旌旒旛旙无旡旱杲昊昃旻杳昵昶昴昜晏晄晉晁晞晝晤晧晨晟晢晰暃暈暎暉暄暘暝曁暹曉暾暼���\".split(\"\");\nfor(j = 0; j != D[157].length; ++j) if(D[157][j].charCodeAt(0) !== 0xFFFD) { e[D[157][j]] = 40192 + j; d[40192 + j] = D[157][j];}\nD[158] = \"����������������������������������������������������������������曄暸曖曚曠昿曦曩曰曵曷朏朖朞朦朧霸朮朿朶杁朸朷杆杞杠杙杣杤枉杰枩杼杪枌枋枦枡枅枷柯枴柬枳柩枸柤柞柝柢柮枹柎柆柧檜栞框栩桀桍栲桎�梳栫桙档桷桿梟梏梭梔條梛梃檮梹桴梵梠梺椏梍桾椁棊椈棘椢椦棡椌棍棔棧棕椶椒椄棗棣椥棹棠棯椨椪椚椣椡棆楹楷楜楸楫楔楾楮椹楴椽楙椰楡楞楝榁楪榲榮槐榿槁槓榾槎寨槊槝榻槃榧樮榑榠榜榕榴槞槨樂樛槿權槹槲槧樅榱樞槭樔槫樊樒櫁樣樓橄樌橲樶橸橇橢橙橦橈樸樢檐檍檠檄檢檣���\".split(\"\");\nfor(j = 0; j != D[158].length; ++j) if(D[158][j].charCodeAt(0) !== 0xFFFD) { e[D[158][j]] = 40448 + j; d[40448 + j] = D[158][j];}\nD[159] = \"����������������������������������������������������������������檗蘗檻櫃櫂檸檳檬櫞櫑櫟檪櫚櫪櫻欅蘖櫺欒欖鬱欟欸欷盜欹飮歇歃歉歐歙歔歛歟歡歸歹歿殀殄殃殍殘殕殞殤殪殫殯殲殱殳殷殼毆毋毓毟毬毫毳毯�麾氈氓气氛氤氣汞汕汢汪沂沍沚沁沛汾汨汳沒沐泄泱泓沽泗泅泝沮沱沾沺泛泯泙泪洟衍洶洫洽洸洙洵洳洒洌浣涓浤浚浹浙涎涕濤涅淹渕渊涵淇淦涸淆淬淞淌淨淒淅淺淙淤淕淪淮渭湮渮渙湲湟渾渣湫渫湶湍渟湃渺湎渤滿渝游溂溪溘滉溷滓溽溯滄溲滔滕溏溥滂溟潁漑灌滬滸滾漿滲漱滯漲滌���\".split(\"\");\nfor(j = 0; j != D[159].length; ++j) if(D[159][j].charCodeAt(0) !== 0xFFFD) { e[D[159][j]] = 40704 + j; d[40704 + j] = D[159][j];}\nD[224] = \"����������������������������������������������������������������漾漓滷澆潺潸澁澀潯潛濳潭澂潼潘澎澑濂潦澳澣澡澤澹濆澪濟濕濬濔濘濱濮濛瀉瀋濺瀑瀁瀏濾瀛瀚潴瀝瀘瀟瀰瀾瀲灑灣炙炒炯烱炬炸炳炮烟烋烝�烙焉烽焜焙煥煕熈煦煢煌煖煬熏燻熄熕熨熬燗熹熾燒燉燔燎燠燬燧燵燼燹燿爍爐爛爨爭爬爰爲爻爼爿牀牆牋牘牴牾犂犁犇犒犖犢犧犹犲狃狆狄狎狒狢狠狡狹狷倏猗猊猜猖猝猴猯猩猥猾獎獏默獗獪獨獰獸獵獻獺珈玳珎玻珀珥珮珞璢琅瑯琥珸琲琺瑕琿瑟瑙瑁瑜瑩瑰瑣瑪瑶瑾璋璞璧瓊瓏瓔珱���\".split(\"\");\nfor(j = 0; j != D[224].length; ++j) if(D[224][j].charCodeAt(0) !== 0xFFFD) { e[D[224][j]] = 57344 + j; d[57344 + j] = D[224][j];}\nD[225] = \"����������������������������������������������������������������瓠瓣瓧瓩瓮瓲瓰瓱瓸瓷甄甃甅甌甎甍甕甓甞甦甬甼畄畍畊畉畛畆畚畩畤畧畫畭畸當疆疇畴疊疉疂疔疚疝疥疣痂疳痃疵疽疸疼疱痍痊痒痙痣痞痾痿�痼瘁痰痺痲痳瘋瘍瘉瘟瘧瘠瘡瘢瘤瘴瘰瘻癇癈癆癜癘癡癢癨癩癪癧癬癰癲癶癸發皀皃皈皋皎皖皓皙皚皰皴皸皹皺盂盍盖盒盞盡盥盧盪蘯盻眈眇眄眩眤眞眥眦眛眷眸睇睚睨睫睛睥睿睾睹瞎瞋瞑瞠瞞瞰瞶瞹瞿瞼瞽瞻矇矍矗矚矜矣矮矼砌砒礦砠礪硅碎硴碆硼碚碌碣碵碪碯磑磆磋磔碾碼磅磊磬���\".split(\"\");\nfor(j = 0; j != D[225].length; ++j) if(D[225][j].charCodeAt(0) !== 0xFFFD) { e[D[225][j]] = 57600 + j; d[57600 + j] = D[225][j];}\nD[226] = \"����������������������������������������������������������������磧磚磽磴礇礒礑礙礬礫祀祠祗祟祚祕祓祺祿禊禝禧齋禪禮禳禹禺秉秕秧秬秡秣稈稍稘稙稠稟禀稱稻稾稷穃穗穉穡穢穩龝穰穹穽窈窗窕窘窖窩竈窰�窶竅竄窿邃竇竊竍竏竕竓站竚竝竡竢竦竭竰笂笏笊笆笳笘笙笞笵笨笶筐筺笄筍笋筌筅筵筥筴筧筰筱筬筮箝箘箟箍箜箚箋箒箏筝箙篋篁篌篏箴篆篝篩簑簔篦篥籠簀簇簓篳篷簗簍篶簣簧簪簟簷簫簽籌籃籔籏籀籐籘籟籤籖籥籬籵粃粐粤粭粢粫粡粨粳粲粱粮粹粽糀糅糂糘糒糜糢鬻糯糲糴糶糺紆���\".split(\"\");\nfor(j = 0; j != D[226].length; ++j) if(D[226][j].charCodeAt(0) !== 0xFFFD) { e[D[226][j]] = 57856 + j; d[57856 + j] = D[226][j];}\nD[227] = \"����������������������������������������������������������������紂紜紕紊絅絋紮紲紿紵絆絳絖絎絲絨絮絏絣經綉絛綏絽綛綺綮綣綵緇綽綫總綢綯緜綸綟綰緘緝緤緞緻緲緡縅縊縣縡縒縱縟縉縋縢繆繦縻縵縹繃縷�縲縺繧繝繖繞繙繚繹繪繩繼繻纃緕繽辮繿纈纉續纒纐纓纔纖纎纛纜缸缺罅罌罍罎罐网罕罔罘罟罠罨罩罧罸羂羆羃羈羇羌羔羞羝羚羣羯羲羹羮羶羸譱翅翆翊翕翔翡翦翩翳翹飜耆耄耋耒耘耙耜耡耨耿耻聊聆聒聘聚聟聢聨聳聲聰聶聹聽聿肄肆肅肛肓肚肭冐肬胛胥胙胝胄胚胖脉胯胱脛脩脣脯腋���\".split(\"\");\nfor(j = 0; j != D[227].length; ++j) if(D[227][j].charCodeAt(0) !== 0xFFFD) { e[D[227][j]] = 58112 + j; d[58112 + j] = D[227][j];}\nD[228] = \"����������������������������������������������������������������隋腆脾腓腑胼腱腮腥腦腴膃膈膊膀膂膠膕膤膣腟膓膩膰膵膾膸膽臀臂膺臉臍臑臙臘臈臚臟臠臧臺臻臾舁舂舅與舊舍舐舖舩舫舸舳艀艙艘艝艚艟艤�艢艨艪艫舮艱艷艸艾芍芒芫芟芻芬苡苣苟苒苴苳苺莓范苻苹苞茆苜茉苙茵茴茖茲茱荀茹荐荅茯茫茗茘莅莚莪莟莢莖茣莎莇莊荼莵荳荵莠莉莨菴萓菫菎菽萃菘萋菁菷萇菠菲萍萢萠莽萸蔆菻葭萪萼蕚蒄葷葫蒭葮蒂葩葆萬葯葹萵蓊葢蒹蒿蒟蓙蓍蒻蓚蓐蓁蓆蓖蒡蔡蓿蓴蔗蔘蔬蔟蔕蔔蓼蕀蕣蕘蕈���\".split(\"\");\nfor(j = 0; j != D[228].length; ++j) if(D[228][j].charCodeAt(0) !== 0xFFFD) { e[D[228][j]] = 58368 + j; d[58368 + j] = D[228][j];}\nD[229] = \"����������������������������������������������������������������蕁蘂蕋蕕薀薤薈薑薊薨蕭薔薛藪薇薜蕷蕾薐藉薺藏薹藐藕藝藥藜藹蘊蘓蘋藾藺蘆蘢蘚蘰蘿虍乕虔號虧虱蚓蚣蚩蚪蚋蚌蚶蚯蛄蛆蚰蛉蠣蚫蛔蛞蛩蛬�蛟蛛蛯蜒蜆蜈蜀蜃蛻蜑蜉蜍蛹蜊蜴蜿蜷蜻蜥蜩蜚蝠蝟蝸蝌蝎蝴蝗蝨蝮蝙蝓蝣蝪蠅螢螟螂螯蟋螽蟀蟐雖螫蟄螳蟇蟆螻蟯蟲蟠蠏蠍蟾蟶蟷蠎蟒蠑蠖蠕蠢蠡蠱蠶蠹蠧蠻衄衂衒衙衞衢衫袁衾袞衵衽袵衲袂袗袒袮袙袢袍袤袰袿袱裃裄裔裘裙裝裹褂裼裴裨裲褄褌褊褓襃褞褥褪褫襁襄褻褶褸襌褝襠襞���\".split(\"\");\nfor(j = 0; j != D[229].length; ++j) if(D[229][j].charCodeAt(0) !== 0xFFFD) { e[D[229][j]] = 58624 + j; d[58624 + j] = D[229][j];}\nD[230] = \"����������������������������������������������������������������襦襤襭襪襯襴襷襾覃覈覊覓覘覡覩覦覬覯覲覺覽覿觀觚觜觝觧觴觸訃訖訐訌訛訝訥訶詁詛詒詆詈詼詭詬詢誅誂誄誨誡誑誥誦誚誣諄諍諂諚諫諳諧�諤諱謔諠諢諷諞諛謌謇謚諡謖謐謗謠謳鞫謦謫謾謨譁譌譏譎證譖譛譚譫譟譬譯譴譽讀讌讎讒讓讖讙讚谺豁谿豈豌豎豐豕豢豬豸豺貂貉貅貊貍貎貔豼貘戝貭貪貽貲貳貮貶賈賁賤賣賚賽賺賻贄贅贊贇贏贍贐齎贓賍贔贖赧赭赱赳趁趙跂趾趺跏跚跖跌跛跋跪跫跟跣跼踈踉跿踝踞踐踟蹂踵踰踴蹊���\".split(\"\");\nfor(j = 0; j != D[230].length; ++j) if(D[230][j].charCodeAt(0) !== 0xFFFD) { e[D[230][j]] = 58880 + j; d[58880 + j] = D[230][j];}\nD[231] = \"����������������������������������������������������������������蹇蹉蹌蹐蹈蹙蹤蹠踪蹣蹕蹶蹲蹼躁躇躅躄躋躊躓躑躔躙躪躡躬躰軆躱躾軅軈軋軛軣軼軻軫軾輊輅輕輒輙輓輜輟輛輌輦輳輻輹轅轂輾轌轉轆轎轗轜�轢轣轤辜辟辣辭辯辷迚迥迢迪迯邇迴逅迹迺逑逕逡逍逞逖逋逧逶逵逹迸遏遐遑遒逎遉逾遖遘遞遨遯遶隨遲邂遽邁邀邊邉邏邨邯邱邵郢郤扈郛鄂鄒鄙鄲鄰酊酖酘酣酥酩酳酲醋醉醂醢醫醯醪醵醴醺釀釁釉釋釐釖釟釡釛釼釵釶鈞釿鈔鈬鈕鈑鉞鉗鉅鉉鉤鉈銕鈿鉋鉐銜銖銓銛鉚鋏銹銷鋩錏鋺鍄錮���\".split(\"\");\nfor(j = 0; j != D[231].length; ++j) if(D[231][j].charCodeAt(0) !== 0xFFFD) { e[D[231][j]] = 59136 + j; d[59136 + j] = D[231][j];}\nD[232] = \"����������������������������������������������������������������錙錢錚錣錺錵錻鍜鍠鍼鍮鍖鎰鎬鎭鎔鎹鏖鏗鏨鏥鏘鏃鏝鏐鏈鏤鐚鐔鐓鐃鐇鐐鐶鐫鐵鐡鐺鑁鑒鑄鑛鑠鑢鑞鑪鈩鑰鑵鑷鑽鑚鑼鑾钁鑿閂閇閊閔閖閘閙�閠閨閧閭閼閻閹閾闊濶闃闍闌闕闔闖關闡闥闢阡阨阮阯陂陌陏陋陷陜陞陝陟陦陲陬隍隘隕隗險隧隱隲隰隴隶隸隹雎雋雉雍襍雜霍雕雹霄霆霈霓霎霑霏霖霙霤霪霰霹霽霾靄靆靈靂靉靜靠靤靦靨勒靫靱靹鞅靼鞁靺鞆鞋鞏鞐鞜鞨鞦鞣鞳鞴韃韆韈韋韜韭齏韲竟韶韵頏頌頸頤頡頷頽顆顏顋顫顯顰���\".split(\"\");\nfor(j = 0; j != D[232].length; ++j) if(D[232][j].charCodeAt(0) !== 0xFFFD) { e[D[232][j]] = 59392 + j; d[59392 + j] = D[232][j];}\nD[233] = \"����������������������������������������������������������������顱顴顳颪颯颱颶飄飃飆飩飫餃餉餒餔餘餡餝餞餤餠餬餮餽餾饂饉饅饐饋饑饒饌饕馗馘馥馭馮馼駟駛駝駘駑駭駮駱駲駻駸騁騏騅駢騙騫騷驅驂驀驃�騾驕驍驛驗驟驢驥驤驩驫驪骭骰骼髀髏髑髓體髞髟髢髣髦髯髫髮髴髱髷髻鬆鬘鬚鬟鬢鬣鬥鬧鬨鬩鬪鬮鬯鬲魄魃魏魍魎魑魘魴鮓鮃鮑鮖鮗鮟鮠鮨鮴鯀鯊鮹鯆鯏鯑鯒鯣鯢鯤鯔鯡鰺鯲鯱鯰鰕鰔鰉鰓鰌鰆鰈鰒鰊鰄鰮鰛鰥鰤鰡鰰鱇鰲鱆鰾鱚鱠鱧鱶鱸鳧鳬鳰鴉鴈鳫鴃鴆鴪鴦鶯鴣鴟鵄鴕鴒鵁鴿鴾鵆鵈���\".split(\"\");\nfor(j = 0; j != D[233].length; ++j) if(D[233][j].charCodeAt(0) !== 0xFFFD) { e[D[233][j]] = 59648 + j; d[59648 + j] = D[233][j];}\nD[234] = \"����������������������������������������������������������������鵝鵞鵤鵑鵐鵙鵲鶉鶇鶫鵯鵺鶚鶤鶩鶲鷄鷁鶻鶸鶺鷆鷏鷂鷙鷓鷸鷦鷭鷯鷽鸚鸛鸞鹵鹹鹽麁麈麋麌麒麕麑麝麥麩麸麪麭靡黌黎黏黐黔黜點黝黠黥黨黯�黴黶黷黹黻黼黽鼇鼈皷鼕鼡鼬鼾齊齒齔齣齟齠齡齦齧齬齪齷齲齶龕龜龠堯槇遙瑤凜熙�������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[234].length; ++j) if(D[234][j].charCodeAt(0) !== 0xFFFD) { e[D[234][j]] = 59904 + j; d[59904 + j] = D[234][j];}\nD[237] = \"����������������������������������������������������������������纊褜鍈銈蓜俉炻昱棈鋹曻彅丨仡仼伀伃伹佖侒侊侚侔俍偀倢俿倞偆偰偂傔僴僘兊兤冝冾凬刕劜劦勀勛匀匇匤卲厓厲叝﨎咜咊咩哿喆坙坥垬埈埇﨏�塚增墲夋奓奛奝奣妤妺孖寀甯寘寬尞岦岺峵崧嵓﨑嵂嵭嶸嶹巐弡弴彧德忞恝悅悊惞惕愠惲愑愷愰憘戓抦揵摠撝擎敎昀昕昻昉昮昞昤晥晗晙晴晳暙暠暲暿曺朎朗杦枻桒柀栁桄棏﨓楨﨔榘槢樰橫橆橳橾櫢櫤毖氿汜沆汯泚洄涇浯涖涬淏淸淲淼渹湜渧渼溿澈澵濵瀅瀇瀨炅炫焏焄煜煆煇凞燁燾犱���\".split(\"\");\nfor(j = 0; j != D[237].length; ++j) if(D[237][j].charCodeAt(0) !== 0xFFFD) { e[D[237][j]] = 60672 + j; d[60672 + j] = D[237][j];}\nD[238] = \"����������������������������������������������������������������犾猤猪獷玽珉珖珣珒琇珵琦琪琩琮瑢璉璟甁畯皂皜皞皛皦益睆劯砡硎硤硺礰礼神祥禔福禛竑竧靖竫箞精絈絜綷綠緖繒罇羡羽茁荢荿菇菶葈蒴蕓蕙�蕫﨟薰蘒﨡蠇裵訒訷詹誧誾諟諸諶譓譿賰賴贒赶﨣軏﨤逸遧郞都鄕鄧釚釗釞釭釮釤釥鈆鈐鈊鈺鉀鈼鉎鉙鉑鈹鉧銧鉷鉸鋧鋗鋙鋐﨧鋕鋠鋓錥錡鋻﨨錞鋿錝錂鍰鍗鎤鏆鏞鏸鐱鑅鑈閒隆﨩隝隯霳霻靃靍靏靑靕顗顥飯飼餧館馞驎髙髜魵魲鮏鮱鮻鰀鵰鵫鶴鸙黑��ⅰⅱⅲⅳⅴⅵⅶⅷⅸⅹ￢￤＇＂���\".split(\"\");\nfor(j = 0; j != D[238].length; ++j) if(D[238][j].charCodeAt(0) !== 0xFFFD) { e[D[238][j]] = 60928 + j; d[60928 + j] = D[238][j];}\nD[250] = \"����������������������������������������������������������������ⅰⅱⅲⅳⅴⅵⅶⅷⅸⅹⅠⅡⅢⅣⅤⅥⅦⅧⅨⅩ￢￤＇＂㈱№℡∵纊褜鍈銈蓜俉炻昱棈鋹曻彅丨仡仼伀伃伹佖侒侊侚侔俍偀倢俿倞偆偰偂傔僴僘兊�兤冝冾凬刕劜劦勀勛匀匇匤卲厓厲叝﨎咜咊咩哿喆坙坥垬埈埇﨏塚增墲夋奓奛奝奣妤妺孖寀甯寘寬尞岦岺峵崧嵓﨑嵂嵭嶸嶹巐弡弴彧德忞恝悅悊惞惕愠惲愑愷愰憘戓抦揵摠撝擎敎昀昕昻昉昮昞昤晥晗晙晴晳暙暠暲暿曺朎朗杦枻桒柀栁桄棏﨓楨﨔榘槢樰橫橆橳橾櫢櫤毖氿汜沆汯泚洄涇浯���\".split(\"\");\nfor(j = 0; j != D[250].length; ++j) if(D[250][j].charCodeAt(0) !== 0xFFFD) { e[D[250][j]] = 64000 + j; d[64000 + j] = D[250][j];}\nD[251] = \"����������������������������������������������������������������涖涬淏淸淲淼渹湜渧渼溿澈澵濵瀅瀇瀨炅炫焏焄煜煆煇凞燁燾犱犾猤猪獷玽珉珖珣珒琇珵琦琪琩琮瑢璉璟甁畯皂皜皞皛皦益睆劯砡硎硤硺礰礼神�祥禔福禛竑竧靖竫箞精絈絜綷綠緖繒罇羡羽茁荢荿菇菶葈蒴蕓蕙蕫﨟薰蘒﨡蠇裵訒訷詹誧誾諟諸諶譓譿賰賴贒赶﨣軏﨤逸遧郞都鄕鄧釚釗釞釭釮釤釥鈆鈐鈊鈺鉀鈼鉎鉙鉑鈹鉧銧鉷鉸鋧鋗鋙鋐﨧鋕鋠鋓錥錡鋻﨨錞鋿錝錂鍰鍗鎤鏆鏞鏸鐱鑅鑈閒隆﨩隝隯霳霻靃靍靏靑靕顗顥飯飼餧館馞驎髙���\".split(\"\");\nfor(j = 0; j != D[251].length; ++j) if(D[251][j].charCodeAt(0) !== 0xFFFD) { e[D[251][j]] = 64256 + j; d[64256 + j] = D[251][j];}\nD[252] = \"����������������������������������������������������������������髜魵魲鮏鮱鮻鰀鵰鵫鶴鸙黑������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[252].length; ++j) if(D[252][j].charCodeAt(0) !== 0xFFFD) { e[D[252][j]] = 64512 + j; d[64512 + j] = D[252][j];}\nreturn {\"enc\": e, \"dec\": d }; })();\ncptable[936] = (function(){ var d = [], e = {}, D = [], j;\nD[0] = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[0].length; ++j) if(D[0][j].charCodeAt(0) !== 0xFFFD) { e[D[0][j]] = 0 + j; d[0 + j] = D[0][j];}\nD[129] = \"����������������������������������������������������������������丂丄丅丆丏丒丗丟丠両丣並丩丮丯丱丳丵丷丼乀乁乂乄乆乊乑乕乗乚乛乢乣乤乥乧乨乪乫乬乭乮乯乲乴乵乶乷乸乹乺乻乼乽乿亀亁亂亃亄亅亇亊�亐亖亗亙亜亝亞亣亪亯亰亱亴亶亷亸亹亼亽亾仈仌仏仐仒仚仛仜仠仢仦仧仩仭仮仯仱仴仸仹仺仼仾伀伂伃伄伅伆伇伈伋伌伒伓伔伕伖伜伝伡伣伨伩伬伭伮伱伳伵伷伹伻伾伿佀佁佂佄佅佇佈佉佊佋佌佒佔佖佡佢佦佨佪佫佭佮佱佲併佷佸佹佺佽侀侁侂侅來侇侊侌侎侐侒侓侕侖侘侙侚侜侞侟価侢�\".split(\"\");\nfor(j = 0; j != D[129].length; ++j) if(D[129][j].charCodeAt(0) !== 0xFFFD) { e[D[129][j]] = 33024 + j; d[33024 + j] = D[129][j];}\nD[130] = \"����������������������������������������������������������������侤侫侭侰侱侲侳侴侶侷侸侹侺侻侼侽侾俀俁係俆俇俈俉俋俌俍俒俓俔俕俖俙俛俠俢俤俥俧俫俬俰俲俴俵俶俷俹俻俼俽俿倀倁倂倃倄倅倆倇倈倉倊�個倎倐們倓倕倖倗倛倝倞倠倢倣値倧倫倯倰倱倲倳倴倵倶倷倸倹倻倽倿偀偁偂偄偅偆偉偊偋偍偐偑偒偓偔偖偗偘偙偛偝偞偟偠偡偢偣偤偦偧偨偩偪偫偭偮偯偰偱偲偳側偵偸偹偺偼偽傁傂傃傄傆傇傉傊傋傌傎傏傐傑傒傓傔傕傖傗傘備傚傛傜傝傞傟傠傡傢傤傦傪傫傭傮傯傰傱傳傴債傶傷傸傹傼�\".split(\"\");\nfor(j = 0; j != D[130].length; ++j) if(D[130][j].charCodeAt(0) !== 0xFFFD) { e[D[130][j]] = 33280 + j; d[33280 + j] = D[130][j];}\nD[131] = \"����������������������������������������������������������������傽傾傿僀僁僂僃僄僅僆僇僈僉僊僋僌働僎僐僑僒僓僔僕僗僘僙僛僜僝僞僟僠僡僢僣僤僥僨僩僪僫僯僰僱僲僴僶僷僸價僺僼僽僾僿儀儁儂儃億儅儈�儉儊儌儍儎儏儐儑儓儔儕儖儗儘儙儚儛儜儝儞償儠儢儣儤儥儦儧儨儩優儫儬儭儮儯儰儱儲儳儴儵儶儷儸儹儺儻儼儽儾兂兇兊兌兎兏児兒兓兗兘兙兛兝兞兟兠兡兣兤兦內兩兪兯兲兺兾兿冃冄円冇冊冋冎冏冐冑冓冔冘冚冝冞冟冡冣冦冧冨冩冪冭冮冴冸冹冺冾冿凁凂凃凅凈凊凍凎凐凒凓凔凕凖凗�\".split(\"\");\nfor(j = 0; j != D[131].length; ++j) if(D[131][j].charCodeAt(0) !== 0xFFFD) { e[D[131][j]] = 33536 + j; d[33536 + j] = D[131][j];}\nD[132] = \"����������������������������������������������������������������凘凙凚凜凞凟凢凣凥処凧凨凩凪凬凮凱凲凴凷凾刄刅刉刋刌刏刐刓刔刕刜刞刟刡刢刣別刦刧刪刬刯刱刲刴刵刼刾剄剅剆則剈剉剋剎剏剒剓剕剗剘�剙剚剛剝剟剠剢剣剤剦剨剫剬剭剮剰剱剳剴創剶剷剸剹剺剻剼剾劀劃劄劅劆劇劉劊劋劌劍劎劏劑劒劔劕劖劗劘劙劚劜劤劥劦劧劮劯劰労劵劶劷劸効劺劻劼劽勀勁勂勄勅勆勈勊勌勍勎勏勑勓勔動勗務勚勛勜勝勞勠勡勢勣勥勦勧勨勩勪勫勬勭勮勯勱勲勳勴勵勶勷勸勻勼勽匁匂匃匄匇匉匊匋匌匎�\".split(\"\");\nfor(j = 0; j != D[132].length; ++j) if(D[132][j].charCodeAt(0) !== 0xFFFD) { e[D[132][j]] = 33792 + j; d[33792 + j] = D[132][j];}\nD[133] = \"����������������������������������������������������������������匑匒匓匔匘匛匜匞匟匢匤匥匧匨匩匫匬匭匯匰匱匲匳匴匵匶匷匸匼匽區卂卄卆卋卌卍卐協単卙卛卝卥卨卪卬卭卲卶卹卻卼卽卾厀厁厃厇厈厊厎厏�厐厑厒厓厔厖厗厙厛厜厞厠厡厤厧厪厫厬厭厯厰厱厲厳厴厵厷厸厹厺厼厽厾叀參叄叅叆叇収叏叐叒叓叕叚叜叝叞叡叢叧叴叺叾叿吀吂吅吇吋吔吘吙吚吜吢吤吥吪吰吳吶吷吺吽吿呁呂呄呅呇呉呌呍呎呏呑呚呝呞呟呠呡呣呥呧呩呪呫呬呭呮呯呰呴呹呺呾呿咁咃咅咇咈咉咊咍咑咓咗咘咜咞咟咠咡�\".split(\"\");\nfor(j = 0; j != D[133].length; ++j) if(D[133][j].charCodeAt(0) !== 0xFFFD) { e[D[133][j]] = 34048 + j; d[34048 + j] = D[133][j];}\nD[134] = \"����������������������������������������������������������������咢咥咮咰咲咵咶咷咹咺咼咾哃哅哊哋哖哘哛哠員哢哣哤哫哬哯哰哱哴哵哶哷哸哹哻哾唀唂唃唄唅唈唊唋唌唍唎唒唓唕唖唗唘唙唚唜唝唞唟唡唥唦�唨唩唫唭唲唴唵唶唸唹唺唻唽啀啂啅啇啈啋啌啍啎問啑啒啓啔啗啘啙啚啛啝啞啟啠啢啣啨啩啫啯啰啱啲啳啴啹啺啽啿喅喆喌喍喎喐喒喓喕喖喗喚喛喞喠喡喢喣喤喥喦喨喩喪喫喬喭單喯喰喲喴営喸喺喼喿嗀嗁嗂嗃嗆嗇嗈嗊嗋嗎嗏嗐嗕嗗嗘嗙嗚嗛嗞嗠嗢嗧嗩嗭嗮嗰嗱嗴嗶嗸嗹嗺嗻嗼嗿嘂嘃嘄嘅�\".split(\"\");\nfor(j = 0; j != D[134].length; ++j) if(D[134][j].charCodeAt(0) !== 0xFFFD) { e[D[134][j]] = 34304 + j; d[34304 + j] = D[134][j];}\nD[135] = \"����������������������������������������������������������������嘆嘇嘊嘋嘍嘐嘑嘒嘓嘔嘕嘖嘗嘙嘚嘜嘝嘠嘡嘢嘥嘦嘨嘩嘪嘫嘮嘯嘰嘳嘵嘷嘸嘺嘼嘽嘾噀噁噂噃噄噅噆噇噈噉噊噋噏噐噑噒噓噕噖噚噛噝噞噟噠噡�噣噥噦噧噭噮噯噰噲噳噴噵噷噸噹噺噽噾噿嚀嚁嚂嚃嚄嚇嚈嚉嚊嚋嚌嚍嚐嚑嚒嚔嚕嚖嚗嚘嚙嚚嚛嚜嚝嚞嚟嚠嚡嚢嚤嚥嚦嚧嚨嚩嚪嚫嚬嚭嚮嚰嚱嚲嚳嚴嚵嚶嚸嚹嚺嚻嚽嚾嚿囀囁囂囃囄囅囆囇囈囉囋囌囍囎囏囐囑囒囓囕囖囘囙囜団囥囦囧囨囩囪囬囮囯囲図囶囷囸囻囼圀圁圂圅圇國圌圍圎圏圐圑�\".split(\"\");\nfor(j = 0; j != D[135].length; ++j) if(D[135][j].charCodeAt(0) !== 0xFFFD) { e[D[135][j]] = 34560 + j; d[34560 + j] = D[135][j];}\nD[136] = \"����������������������������������������������������������������園圓圔圕圖圗團圙圚圛圝圞圠圡圢圤圥圦圧圫圱圲圴圵圶圷圸圼圽圿坁坃坄坅坆坈坉坋坒坓坔坕坖坘坙坢坣坥坧坬坮坰坱坲坴坵坸坹坺坽坾坿垀�垁垇垈垉垊垍垎垏垐垑垔垕垖垗垘垙垚垜垝垞垟垥垨垪垬垯垰垱垳垵垶垷垹垺垻垼垽垾垿埀埁埄埅埆埇埈埉埊埌埍埐埑埓埖埗埛埜埞埡埢埣埥埦埧埨埩埪埫埬埮埰埱埲埳埵埶執埻埼埾埿堁堃堄堅堈堉堊堌堎堏堐堒堓堔堖堗堘堚堛堜堝堟堢堣堥堦堧堨堩堫堬堭堮堯報堲堳場堶堷堸堹堺堻堼堽�\".split(\"\");\nfor(j = 0; j != D[136].length; ++j) if(D[136][j].charCodeAt(0) !== 0xFFFD) { e[D[136][j]] = 34816 + j; d[34816 + j] = D[136][j];}\nD[137] = \"����������������������������������������������������������������堾堿塀塁塂塃塅塆塇塈塉塊塋塎塏塐塒塓塕塖塗塙塚塛塜塝塟塠塡塢塣塤塦塧塨塩塪塭塮塯塰塱塲塳塴塵塶塷塸塹塺塻塼塽塿墂墄墆墇墈墊墋墌�墍墎墏墐墑墔墕墖増墘墛墜墝墠墡墢墣墤墥墦墧墪墫墬墭墮墯墰墱墲墳墴墵墶墷墸墹墺墻墽墾墿壀壂壃壄壆壇壈壉壊壋壌壍壎壏壐壒壓壔壖壗壘壙壚壛壜壝壞壟壠壡壢壣壥壦壧壨壩壪壭壯壱売壴壵壷壸壺壻壼壽壾壿夀夁夃夅夆夈変夊夋夌夎夐夑夒夓夗夘夛夝夞夠夡夢夣夦夨夬夰夲夳夵夶夻�\".split(\"\");\nfor(j = 0; j != D[137].length; ++j) if(D[137][j].charCodeAt(0) !== 0xFFFD) { e[D[137][j]] = 35072 + j; d[35072 + j] = D[137][j];}\nD[138] = \"����������������������������������������������������������������夽夾夿奀奃奅奆奊奌奍奐奒奓奙奛奜奝奞奟奡奣奤奦奧奨奩奪奫奬奭奮奯奰奱奲奵奷奺奻奼奾奿妀妅妉妋妌妎妏妐妑妔妕妘妚妛妜妝妟妠妡妢妦�妧妬妭妰妱妳妴妵妶妷妸妺妼妽妿姀姁姂姃姄姅姇姈姉姌姍姎姏姕姖姙姛姞姟姠姡姢姤姦姧姩姪姫姭姮姯姰姱姲姳姴姵姶姷姸姺姼姽姾娀娂娊娋娍娎娏娐娒娔娕娖娗娙娚娛娝娞娡娢娤娦娧娨娪娫娬娭娮娯娰娳娵娷娸娹娺娻娽娾娿婁婂婃婄婅婇婈婋婌婍婎婏婐婑婒婓婔婖婗婘婙婛婜婝婞婟婠�\".split(\"\");\nfor(j = 0; j != D[138].length; ++j) if(D[138][j].charCodeAt(0) !== 0xFFFD) { e[D[138][j]] = 35328 + j; d[35328 + j] = D[138][j];}\nD[139] = \"����������������������������������������������������������������婡婣婤婥婦婨婩婫婬婭婮婯婰婱婲婳婸婹婻婼婽婾媀媁媂媃媄媅媆媇媈媉媊媋媌媍媎媏媐媑媓媔媕媖媗媘媙媜媝媞媟媠媡媢媣媤媥媦媧媨媩媫媬�媭媮媯媰媱媴媶媷媹媺媻媼媽媿嫀嫃嫄嫅嫆嫇嫈嫊嫋嫍嫎嫏嫐嫑嫓嫕嫗嫙嫚嫛嫝嫞嫟嫢嫤嫥嫧嫨嫪嫬嫭嫮嫯嫰嫲嫳嫴嫵嫶嫷嫸嫹嫺嫻嫼嫽嫾嫿嬀嬁嬂嬃嬄嬅嬆嬇嬈嬊嬋嬌嬍嬎嬏嬐嬑嬒嬓嬔嬕嬘嬙嬚嬛嬜嬝嬞嬟嬠嬡嬢嬣嬤嬥嬦嬧嬨嬩嬪嬫嬬嬭嬮嬯嬰嬱嬳嬵嬶嬸嬹嬺嬻嬼嬽嬾嬿孁孂孃孄孅孆孇�\".split(\"\");\nfor(j = 0; j != D[139].length; ++j) if(D[139][j].charCodeAt(0) !== 0xFFFD) { e[D[139][j]] = 35584 + j; d[35584 + j] = D[139][j];}\nD[140] = \"����������������������������������������������������������������孈孉孊孋孌孍孎孏孒孖孞孠孡孧孨孫孭孮孯孲孴孶孷學孹孻孼孾孿宂宆宊宍宎宐宑宒宔宖実宧宨宩宬宭宮宯宱宲宷宺宻宼寀寁寃寈寉寊寋寍寎寏�寑寔寕寖寗寘寙寚寛寜寠寢寣實寧審寪寫寬寭寯寱寲寳寴寵寶寷寽対尀専尃尅將專尋尌對導尐尒尓尗尙尛尞尟尠尡尣尦尨尩尪尫尭尮尯尰尲尳尵尶尷屃屄屆屇屌屍屒屓屔屖屗屘屚屛屜屝屟屢層屧屨屩屪屫屬屭屰屲屳屴屵屶屷屸屻屼屽屾岀岃岄岅岆岇岉岊岋岎岏岒岓岕岝岞岟岠岡岤岥岦岧岨�\".split(\"\");\nfor(j = 0; j != D[140].length; ++j) if(D[140][j].charCodeAt(0) !== 0xFFFD) { e[D[140][j]] = 35840 + j; d[35840 + j] = D[140][j];}\nD[141] = \"����������������������������������������������������������������岪岮岯岰岲岴岶岹岺岻岼岾峀峂峃峅峆峇峈峉峊峌峍峎峏峐峑峓峔峕峖峗峘峚峛峜峝峞峟峠峢峣峧峩峫峬峮峯峱峲峳峴峵島峷峸峹峺峼峽峾峿崀�崁崄崅崈崉崊崋崌崍崏崐崑崒崓崕崗崘崙崚崜崝崟崠崡崢崣崥崨崪崫崬崯崰崱崲崳崵崶崷崸崹崺崻崼崿嵀嵁嵂嵃嵄嵅嵆嵈嵉嵍嵎嵏嵐嵑嵒嵓嵔嵕嵖嵗嵙嵚嵜嵞嵟嵠嵡嵢嵣嵤嵥嵦嵧嵨嵪嵭嵮嵰嵱嵲嵳嵵嵶嵷嵸嵹嵺嵻嵼嵽嵾嵿嶀嶁嶃嶄嶅嶆嶇嶈嶉嶊嶋嶌嶍嶎嶏嶐嶑嶒嶓嶔嶕嶖嶗嶘嶚嶛嶜嶞嶟嶠�\".split(\"\");\nfor(j = 0; j != D[141].length; ++j) if(D[141][j].charCodeAt(0) !== 0xFFFD) { e[D[141][j]] = 36096 + j; d[36096 + j] = D[141][j];}\nD[142] = \"����������������������������������������������������������������嶡嶢嶣嶤嶥嶦嶧嶨嶩嶪嶫嶬嶭嶮嶯嶰嶱嶲嶳嶴嶵嶶嶸嶹嶺嶻嶼嶽嶾嶿巀巁巂巃巄巆巇巈巉巊巋巌巎巏巐巑巒巓巔巕巖巗巘巙巚巜巟巠巣巤巪巬巭�巰巵巶巸巹巺巻巼巿帀帄帇帉帊帋帍帎帒帓帗帞帟帠帡帢帣帤帥帨帩帪師帬帯帰帲帳帴帵帶帹帺帾帿幀幁幃幆幇幈幉幊幋幍幎幏幐幑幒幓幖幗幘幙幚幜幝幟幠幣幤幥幦幧幨幩幪幫幬幭幮幯幰幱幵幷幹幾庁庂広庅庈庉庌庍庎庒庘庛庝庡庢庣庤庨庩庪庫庬庮庯庰庱庲庴庺庻庼庽庿廀廁廂廃廄廅�\".split(\"\");\nfor(j = 0; j != D[142].length; ++j) if(D[142][j].charCodeAt(0) !== 0xFFFD) { e[D[142][j]] = 36352 + j; d[36352 + j] = D[142][j];}\nD[143] = \"����������������������������������������������������������������廆廇廈廋廌廍廎廏廐廔廕廗廘廙廚廜廝廞廟廠廡廢廣廤廥廦廧廩廫廬廭廮廯廰廱廲廳廵廸廹廻廼廽弅弆弇弉弌弍弎弐弒弔弖弙弚弜弝弞弡弢弣弤�弨弫弬弮弰弲弳弴張弶強弸弻弽弾弿彁彂彃彄彅彆彇彈彉彊彋彌彍彎彏彑彔彙彚彛彜彞彟彠彣彥彧彨彫彮彯彲彴彵彶彸彺彽彾彿徃徆徍徎徏徑従徔徖徚徛徝從徟徠徢徣徤徥徦徧復徫徬徯徰徱徲徳徴徶徸徹徺徻徾徿忀忁忂忇忈忊忋忎忓忔忕忚忛応忞忟忢忣忥忦忨忩忬忯忰忲忳忴忶忷忹忺忼怇�\".split(\"\");\nfor(j = 0; j != D[143].length; ++j) if(D[143][j].charCodeAt(0) !== 0xFFFD) { e[D[143][j]] = 36608 + j; d[36608 + j] = D[143][j];}\nD[144] = \"����������������������������������������������������������������怈怉怋怌怐怑怓怗怘怚怞怟怢怣怤怬怭怮怰怱怲怳怴怶怷怸怹怺怽怾恀恄恅恆恇恈恉恊恌恎恏恑恓恔恖恗恘恛恜恞恟恠恡恥恦恮恱恲恴恵恷恾悀�悁悂悅悆悇悈悊悋悎悏悐悑悓悕悗悘悙悜悞悡悢悤悥悧悩悪悮悰悳悵悶悷悹悺悽悾悿惀惁惂惃惄惇惈惉惌惍惎惏惐惒惓惔惖惗惙惛惞惡惢惣惤惥惪惱惲惵惷惸惻惼惽惾惿愂愃愄愅愇愊愋愌愐愑愒愓愔愖愗愘愙愛愜愝愞愡愢愥愨愩愪愬愭愮愯愰愱愲愳愴愵愶愷愸愹愺愻愼愽愾慀慁慂慃慄慅慆�\".split(\"\");\nfor(j = 0; j != D[144].length; ++j) if(D[144][j].charCodeAt(0) !== 0xFFFD) { e[D[144][j]] = 36864 + j; d[36864 + j] = D[144][j];}\nD[145] = \"����������������������������������������������������������������慇慉態慍慏慐慒慓慔慖慗慘慙慚慛慜慞慟慠慡慣慤慥慦慩慪慫慬慭慮慯慱慲慳慴慶慸慹慺慻慼慽慾慿憀憁憂憃憄憅憆憇憈憉憊憌憍憏憐憑憒憓憕�憖憗憘憙憚憛憜憞憟憠憡憢憣憤憥憦憪憫憭憮憯憰憱憲憳憴憵憶憸憹憺憻憼憽憿懀懁懃懄懅懆懇應懌懍懎懏懐懓懕懖懗懘懙懚懛懜懝懞懟懠懡懢懣懤懥懧懨懩懪懫懬懭懮懯懰懱懲懳懴懶懷懸懹懺懻懼懽懾戀戁戂戃戄戅戇戉戓戔戙戜戝戞戠戣戦戧戨戩戫戭戯戰戱戲戵戶戸戹戺戻戼扂扄扅扆扊�\".split(\"\");\nfor(j = 0; j != D[145].length; ++j) if(D[145][j].charCodeAt(0) !== 0xFFFD) { e[D[145][j]] = 37120 + j; d[37120 + j] = D[145][j];}\nD[146] = \"����������������������������������������������������������������扏扐払扖扗扙扚扜扝扞扟扠扡扢扤扥扨扱扲扴扵扷扸扺扻扽抁抂抃抅抆抇抈抋抌抍抎抏抐抔抙抜抝択抣抦抧抩抪抭抮抯抰抲抳抴抶抷抸抺抾拀拁�拃拋拏拑拕拝拞拠拡拤拪拫拰拲拵拸拹拺拻挀挃挄挅挆挊挋挌挍挏挐挒挓挔挕挗挘挙挜挦挧挩挬挭挮挰挱挳挴挵挶挷挸挻挼挾挿捀捁捄捇捈捊捑捒捓捔捖捗捘捙捚捛捜捝捠捤捥捦捨捪捫捬捯捰捲捳捴捵捸捹捼捽捾捿掁掃掄掅掆掋掍掑掓掔掕掗掙掚掛掜掝掞掟採掤掦掫掯掱掲掵掶掹掻掽掿揀�\".split(\"\");\nfor(j = 0; j != D[146].length; ++j) if(D[146][j].charCodeAt(0) !== 0xFFFD) { e[D[146][j]] = 37376 + j; d[37376 + j] = D[146][j];}\nD[147] = \"����������������������������������������������������������������揁揂揃揅揇揈揊揋揌揑揓揔揕揗揘揙揚換揜揝揟揢揤揥揦揧揨揫揬揮揯揰揱揳揵揷揹揺揻揼揾搃搄搆搇搈搉搊損搎搑搒搕搖搗搘搙搚搝搟搢搣搤�搥搧搨搩搫搮搯搰搱搲搳搵搶搷搸搹搻搼搾摀摂摃摉摋摌摍摎摏摐摑摓摕摖摗摙摚摛摜摝摟摠摡摢摣摤摥摦摨摪摫摬摮摯摰摱摲摳摴摵摶摷摻摼摽摾摿撀撁撃撆撈撉撊撋撌撍撎撏撐撓撔撗撘撚撛撜撝撟撠撡撢撣撥撦撧撨撪撫撯撱撲撳撴撶撹撻撽撾撿擁擃擄擆擇擈擉擊擋擌擏擑擓擔擕擖擙據�\".split(\"\");\nfor(j = 0; j != D[147].length; ++j) if(D[147][j].charCodeAt(0) !== 0xFFFD) { e[D[147][j]] = 37632 + j; d[37632 + j] = D[147][j];}\nD[148] = \"����������������������������������������������������������������擛擜擝擟擠擡擣擥擧擨擩擪擫擬擭擮擯擰擱擲擳擴擵擶擷擸擹擺擻擼擽擾擿攁攂攃攄攅攆攇攈攊攋攌攍攎攏攐攑攓攔攕攖攗攙攚攛攜攝攞攟攠攡�攢攣攤攦攧攨攩攪攬攭攰攱攲攳攷攺攼攽敀敁敂敃敄敆敇敊敋敍敎敐敒敓敔敗敘敚敜敟敠敡敤敥敧敨敩敪敭敮敯敱敳敵敶數敹敺敻敼敽敾敿斀斁斂斃斄斅斆斈斉斊斍斎斏斒斔斕斖斘斚斝斞斠斢斣斦斨斪斬斮斱斲斳斴斵斶斷斸斺斻斾斿旀旂旇旈旉旊旍旐旑旓旔旕旘旙旚旛旜旝旞旟旡旣旤旪旫�\".split(\"\");\nfor(j = 0; j != D[148].length; ++j) if(D[148][j].charCodeAt(0) !== 0xFFFD) { e[D[148][j]] = 37888 + j; d[37888 + j] = D[148][j];}\nD[149] = \"����������������������������������������������������������������旲旳旴旵旸旹旻旼旽旾旿昁昄昅昇昈昉昋昍昐昑昒昖昗昘昚昛昜昞昡昢昣昤昦昩昪昫昬昮昰昲昳昷昸昹昺昻昽昿晀時晄晅晆晇晈晉晊晍晎晐晑晘�晙晛晜晝晞晠晢晣晥晧晩晪晫晬晭晱晲晳晵晸晹晻晼晽晿暀暁暃暅暆暈暉暊暋暍暎暏暐暒暓暔暕暘暙暚暛暜暞暟暠暡暢暣暤暥暦暩暪暫暬暭暯暰暱暲暳暵暶暷暸暺暻暼暽暿曀曁曂曃曄曅曆曇曈曉曊曋曌曍曎曏曐曑曒曓曔曕曖曗曘曚曞曟曠曡曢曣曤曥曧曨曪曫曬曭曮曯曱曵曶書曺曻曽朁朂會�\".split(\"\");\nfor(j = 0; j != D[149].length; ++j) if(D[149][j].charCodeAt(0) !== 0xFFFD) { e[D[149][j]] = 38144 + j; d[38144 + j] = D[149][j];}\nD[150] = \"����������������������������������������������������������������朄朅朆朇朌朎朏朑朒朓朖朘朙朚朜朞朠朡朢朣朤朥朧朩朮朰朲朳朶朷朸朹朻朼朾朿杁杄杅杇杊杋杍杒杔杕杗杘杙杚杛杝杢杣杤杦杧杫杬杮東杴杶�杸杹杺杻杽枀枂枃枅枆枈枊枌枍枎枏枑枒枓枔枖枙枛枟枠枡枤枦枩枬枮枱枲枴枹枺枻枼枽枾枿柀柂柅柆柇柈柉柊柋柌柍柎柕柖柗柛柟柡柣柤柦柧柨柪柫柭柮柲柵柶柷柸柹柺査柼柾栁栂栃栄栆栍栐栒栔栕栘栙栚栛栜栞栟栠栢栣栤栥栦栧栨栫栬栭栮栯栰栱栴栵栶栺栻栿桇桋桍桏桒桖桗桘桙桚桛�\".split(\"\");\nfor(j = 0; j != D[150].length; ++j) if(D[150][j].charCodeAt(0) !== 0xFFFD) { e[D[150][j]] = 38400 + j; d[38400 + j] = D[150][j];}\nD[151] = \"����������������������������������������������������������������桜桝桞桟桪桬桭桮桯桰桱桲桳桵桸桹桺桻桼桽桾桿梀梂梄梇梈梉梊梋梌梍梎梐梑梒梔梕梖梘梙梚梛梜條梞梟梠梡梣梤梥梩梪梫梬梮梱梲梴梶梷梸�梹梺梻梼梽梾梿棁棃棄棅棆棇棈棊棌棎棏棐棑棓棔棖棗棙棛棜棝棞棟棡棢棤棥棦棧棨棩棪棫棬棭棯棲棳棴棶棷棸棻棽棾棿椀椂椃椄椆椇椈椉椊椌椏椑椓椔椕椖椗椘椙椚椛検椝椞椡椢椣椥椦椧椨椩椪椫椬椮椯椱椲椳椵椶椷椸椺椻椼椾楀楁楃楄楅楆楇楈楉楊楋楌楍楎楏楐楑楒楓楕楖楘楙楛楜楟�\".split(\"\");\nfor(j = 0; j != D[151].length; ++j) if(D[151][j].charCodeAt(0) !== 0xFFFD) { e[D[151][j]] = 38656 + j; d[38656 + j] = D[151][j];}\nD[152] = \"����������������������������������������������������������������楡楢楤楥楧楨楩楪楬業楯楰楲楳楴極楶楺楻楽楾楿榁榃榅榊榋榌榎榏榐榑榒榓榖榗榙榚榝榞榟榠榡榢榣榤榥榦榩榪榬榮榯榰榲榳榵榶榸榹榺榼榽�榾榿槀槂槃槄槅槆槇槈槉構槍槏槑槒槓槕槖槗様槙槚槜槝槞槡槢槣槤槥槦槧槨槩槪槫槬槮槯槰槱槳槴槵槶槷槸槹槺槻槼槾樀樁樂樃樄樅樆樇樈樉樋樌樍樎樏樐樑樒樓樔樕樖標樚樛樜樝樞樠樢樣樤樥樦樧権樫樬樭樮樰樲樳樴樶樷樸樹樺樻樼樿橀橁橂橃橅橆橈橉橊橋橌橍橎橏橑橒橓橔橕橖橗橚�\".split(\"\");\nfor(j = 0; j != D[152].length; ++j) if(D[152][j].charCodeAt(0) !== 0xFFFD) { e[D[152][j]] = 38912 + j; d[38912 + j] = D[152][j];}\nD[153] = \"����������������������������������������������������������������橜橝橞機橠橢橣橤橦橧橨橩橪橫橬橭橮橯橰橲橳橴橵橶橷橸橺橻橽橾橿檁檂檃檅檆檇檈檉檊檋檌檍檏檒檓檔檕檖檘檙檚檛檜檝檞檟檡檢檣檤檥檦�檧檨檪檭檮檯檰檱檲檳檴檵檶檷檸檹檺檻檼檽檾檿櫀櫁櫂櫃櫄櫅櫆櫇櫈櫉櫊櫋櫌櫍櫎櫏櫐櫑櫒櫓櫔櫕櫖櫗櫘櫙櫚櫛櫜櫝櫞櫟櫠櫡櫢櫣櫤櫥櫦櫧櫨櫩櫪櫫櫬櫭櫮櫯櫰櫱櫲櫳櫴櫵櫶櫷櫸櫹櫺櫻櫼櫽櫾櫿欀欁欂欃欄欅欆欇欈欉權欋欌欍欎欏欐欑欒欓欔欕欖欗欘欙欚欛欜欝欞欟欥欦欨欩欪欫欬欭欮�\".split(\"\");\nfor(j = 0; j != D[153].length; ++j) if(D[153][j].charCodeAt(0) !== 0xFFFD) { e[D[153][j]] = 39168 + j; d[39168 + j] = D[153][j];}\nD[154] = \"����������������������������������������������������������������欯欰欱欳欴欵欶欸欻欼欽欿歀歁歂歄歅歈歊歋歍歎歏歐歑歒歓歔歕歖歗歘歚歛歜歝歞歟歠歡歨歩歫歬歭歮歯歰歱歲歳歴歵歶歷歸歺歽歾歿殀殅殈�殌殎殏殐殑殔殕殗殘殙殜殝殞殟殠殢殣殤殥殦殧殨殩殫殬殭殮殯殰殱殲殶殸殹殺殻殼殽殾毀毃毄毆毇毈毉毊毌毎毐毑毘毚毜毝毞毟毠毢毣毤毥毦毧毨毩毬毭毮毰毱毲毴毶毷毸毺毻毼毾毿氀氁氂氃氄氈氉氊氋氌氎氒気氜氝氞氠氣氥氫氬氭氱氳氶氷氹氺氻氼氾氿汃汄汅汈汋汌汍汎汏汑汒汓汖汘�\".split(\"\");\nfor(j = 0; j != D[154].length; ++j) if(D[154][j].charCodeAt(0) !== 0xFFFD) { e[D[154][j]] = 39424 + j; d[39424 + j] = D[154][j];}\nD[155] = \"����������������������������������������������������������������汙汚汢汣汥汦汧汫汬汭汮汯汱汳汵汷汸決汻汼汿沀沄沇沊沋沍沎沑沒沕沖沗沘沚沜沝沞沠沢沨沬沯沰沴沵沶沷沺泀況泂泃泆泇泈泋泍泎泏泑泒泘�泙泚泜泝泟泤泦泧泩泬泭泲泴泹泿洀洂洃洅洆洈洉洊洍洏洐洑洓洔洕洖洘洜洝洟洠洡洢洣洤洦洨洩洬洭洯洰洴洶洷洸洺洿浀浂浄浉浌浐浕浖浗浘浛浝浟浡浢浤浥浧浨浫浬浭浰浱浲浳浵浶浹浺浻浽浾浿涀涁涃涄涆涇涊涋涍涏涐涒涖涗涘涙涚涜涢涥涬涭涰涱涳涴涶涷涹涺涻涼涽涾淁淂淃淈淉淊�\".split(\"\");\nfor(j = 0; j != D[155].length; ++j) if(D[155][j].charCodeAt(0) !== 0xFFFD) { e[D[155][j]] = 39680 + j; d[39680 + j] = D[155][j];}\nD[156] = \"����������������������������������������������������������������淍淎淏淐淒淓淔淕淗淚淛淜淟淢淣淥淧淨淩淪淭淯淰淲淴淵淶淸淺淽淾淿渀渁渂渃渄渆渇済渉渋渏渒渓渕渘渙減渜渞渟渢渦渧渨渪測渮渰渱渳渵�渶渷渹渻渼渽渾渿湀湁湂湅湆湇湈湉湊湋湌湏湐湑湒湕湗湙湚湜湝湞湠湡湢湣湤湥湦湧湨湩湪湬湭湯湰湱湲湳湴湵湶湷湸湹湺湻湼湽満溁溂溄溇溈溊溋溌溍溎溑溒溓溔溕準溗溙溚溛溝溞溠溡溣溤溦溨溩溫溬溭溮溰溳溵溸溹溼溾溿滀滃滄滅滆滈滉滊滌滍滎滐滒滖滘滙滛滜滝滣滧滪滫滬滭滮滯�\".split(\"\");\nfor(j = 0; j != D[156].length; ++j) if(D[156][j].charCodeAt(0) !== 0xFFFD) { e[D[156][j]] = 39936 + j; d[39936 + j] = D[156][j];}\nD[157] = \"����������������������������������������������������������������滰滱滲滳滵滶滷滸滺滻滼滽滾滿漀漁漃漄漅漇漈漊漋漌漍漎漐漑漒漖漗漘漙漚漛漜漝漞漟漡漢漣漥漦漧漨漬漮漰漲漴漵漷漸漹漺漻漼漽漿潀潁潂�潃潄潅潈潉潊潌潎潏潐潑潒潓潔潕潖潗潙潚潛潝潟潠潡潣潤潥潧潨潩潪潫潬潯潰潱潳潵潶潷潹潻潽潾潿澀澁澂澃澅澆澇澊澋澏澐澑澒澓澔澕澖澗澘澙澚澛澝澞澟澠澢澣澤澥澦澨澩澪澫澬澭澮澯澰澱澲澴澵澷澸澺澻澼澽澾澿濁濃濄濅濆濇濈濊濋濌濍濎濏濐濓濔濕濖濗濘濙濚濛濜濝濟濢濣濤濥�\".split(\"\");\nfor(j = 0; j != D[157].length; ++j) if(D[157][j].charCodeAt(0) !== 0xFFFD) { e[D[157][j]] = 40192 + j; d[40192 + j] = D[157][j];}\nD[158] = \"����������������������������������������������������������������濦濧濨濩濪濫濬濭濰濱濲濳濴濵濶濷濸濹濺濻濼濽濾濿瀀瀁瀂瀃瀄瀅瀆瀇瀈瀉瀊瀋瀌瀍瀎瀏瀐瀒瀓瀔瀕瀖瀗瀘瀙瀜瀝瀞瀟瀠瀡瀢瀤瀥瀦瀧瀨瀩瀪�瀫瀬瀭瀮瀯瀰瀱瀲瀳瀴瀶瀷瀸瀺瀻瀼瀽瀾瀿灀灁灂灃灄灅灆灇灈灉灊灋灍灎灐灑灒灓灔灕灖灗灘灙灚灛灜灝灟灠灡灢灣灤灥灦灧灨灩灪灮灱灲灳灴灷灹灺灻災炁炂炃炄炆炇炈炋炌炍炏炐炑炓炗炘炚炛炞炟炠炡炢炣炤炥炦炧炨炩炪炰炲炴炵炶為炾炿烄烅烆烇烉烋烌烍烎烏烐烑烒烓烔烕烖烗烚�\".split(\"\");\nfor(j = 0; j != D[158].length; ++j) if(D[158][j].charCodeAt(0) !== 0xFFFD) { e[D[158][j]] = 40448 + j; d[40448 + j] = D[158][j];}\nD[159] = \"����������������������������������������������������������������烜烝烞烠烡烢烣烥烪烮烰烱烲烳烴烵烶烸烺烻烼烾烿焀焁焂焃焄焅焆焇焈焋焌焍焎焏焑焒焔焗焛焜焝焞焟焠無焢焣焤焥焧焨焩焪焫焬焭焮焲焳焴�焵焷焸焹焺焻焼焽焾焿煀煁煂煃煄煆煇煈煉煋煍煏煐煑煒煓煔煕煖煗煘煙煚煛煝煟煠煡煢煣煥煩煪煫煬煭煯煰煱煴煵煶煷煹煻煼煾煿熀熁熂熃熅熆熇熈熉熋熌熍熎熐熑熒熓熕熖熗熚熛熜熝熞熡熢熣熤熥熦熧熩熪熫熭熮熯熰熱熲熴熶熷熸熺熻熼熽熾熿燀燁燂燄燅燆燇燈燉燊燋燌燍燏燐燑燒燓�\".split(\"\");\nfor(j = 0; j != D[159].length; ++j) if(D[159][j].charCodeAt(0) !== 0xFFFD) { e[D[159][j]] = 40704 + j; d[40704 + j] = D[159][j];}\nD[160] = \"����������������������������������������������������������������燖燗燘燙燚燛燜燝燞營燡燢燣燤燦燨燩燪燫燬燭燯燰燱燲燳燴燵燶燷燸燺燻燼燽燾燿爀爁爂爃爄爅爇爈爉爊爋爌爍爎爏爐爑爒爓爔爕爖爗爘爙爚�爛爜爞爟爠爡爢爣爤爥爦爧爩爫爭爮爯爲爳爴爺爼爾牀牁牂牃牄牅牆牉牊牋牎牏牐牑牓牔牕牗牘牚牜牞牠牣牤牥牨牪牫牬牭牰牱牳牴牶牷牸牻牼牽犂犃犅犆犇犈犉犌犎犐犑犓犔犕犖犗犘犙犚犛犜犝犞犠犡犢犣犤犥犦犧犨犩犪犫犮犱犲犳犵犺犻犼犽犾犿狀狅狆狇狉狊狋狌狏狑狓狔狕狖狘狚狛�\".split(\"\");\nfor(j = 0; j != D[160].length; ++j) if(D[160][j].charCodeAt(0) !== 0xFFFD) { e[D[160][j]] = 40960 + j; d[40960 + j] = D[160][j];}\nD[161] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������　、。·ˉˇ¨〃々—～‖…‘’“”〔〕〈〉《》「」『』〖〗【】±×÷∶∧∨∑∏∪∩∈∷√⊥∥∠⌒⊙∫∮≡≌≈∽∝≠≮≯≤≥∞∵∴♂♀°′″℃＄¤￠￡‰§№☆★○●◎◇◆□■△▲※→←↑↓〓�\".split(\"\");\nfor(j = 0; j != D[161].length; ++j) if(D[161][j].charCodeAt(0) !== 0xFFFD) { e[D[161][j]] = 41216 + j; d[41216 + j] = D[161][j];}\nD[162] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������ⅰⅱⅲⅳⅴⅵⅶⅷⅸⅹ������⒈⒉⒊⒋⒌⒍⒎⒏⒐⒑⒒⒓⒔⒕⒖⒗⒘⒙⒚⒛⑴⑵⑶⑷⑸⑹⑺⑻⑼⑽⑾⑿⒀⒁⒂⒃⒄⒅⒆⒇①②③④⑤⑥⑦⑧⑨⑩��㈠㈡㈢㈣㈤㈥㈦㈧㈨㈩��ⅠⅡⅢⅣⅤⅥⅦⅧⅨⅩⅪⅫ���\".split(\"\");\nfor(j = 0; j != D[162].length; ++j) if(D[162][j].charCodeAt(0) !== 0xFFFD) { e[D[162][j]] = 41472 + j; d[41472 + j] = D[162][j];}\nD[163] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������！＂＃￥％＆＇（）＊＋，－．／０１２３４５６７８９：；＜＝＞？＠ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺ［＼］＾＿｀ａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚ｛｜｝￣�\".split(\"\");\nfor(j = 0; j != D[163].length; ++j) if(D[163][j].charCodeAt(0) !== 0xFFFD) { e[D[163][j]] = 41728 + j; d[41728 + j] = D[163][j];}\nD[164] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������ぁあぃいぅうぇえぉおかがきぎくぐけげこごさざしじすずせぜそぞただちぢっつづてでとどなにぬねのはばぱひびぴふぶぷへべぺほぼぽまみむめもゃやゅゆょよらりるれろゎわゐゑをん������������\".split(\"\");\nfor(j = 0; j != D[164].length; ++j) if(D[164][j].charCodeAt(0) !== 0xFFFD) { e[D[164][j]] = 41984 + j; d[41984 + j] = D[164][j];}\nD[165] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������ァアィイゥウェエォオカガキギクグケゲコゴサザシジスズセゼソゾタダチヂッツヅテデトドナニヌネノハバパヒビピフブプヘベペホボポマミムメモャヤュユョヨラリルレロヮワヰヱヲンヴヵヶ���������\".split(\"\");\nfor(j = 0; j != D[165].length; ++j) if(D[165][j].charCodeAt(0) !== 0xFFFD) { e[D[165][j]] = 42240 + j; d[42240 + j] = D[165][j];}\nD[166] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������ΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩ��������αβγδεζηθικλμνξοπρστυφχψω�������︵︶︹︺︿﹀︽︾﹁﹂﹃﹄��︻︼︷︸︱�︳︴����������\".split(\"\");\nfor(j = 0; j != D[166].length; ++j) if(D[166][j].charCodeAt(0) !== 0xFFFD) { e[D[166][j]] = 42496 + j; d[42496 + j] = D[166][j];}\nD[167] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������АБВГДЕЁЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ���������������абвгдеёжзийклмнопрстуфхцчшщъыьэюя��������������\".split(\"\");\nfor(j = 0; j != D[167].length; ++j) if(D[167][j].charCodeAt(0) !== 0xFFFD) { e[D[167][j]] = 42752 + j; d[42752 + j] = D[167][j];}\nD[168] = \"����������������������������������������������������������������ˊˋ˙–―‥‵℅℉↖↗↘↙∕∟∣≒≦≧⊿═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳▁▂▃▄▅▆▇�█▉▊▋▌▍▎▏▓▔▕▼▽◢◣◤◥☉⊕〒〝〞�����������āáǎàēéěèīíǐìōóǒòūúǔùǖǘǚǜüêɑ�ńň�ɡ����ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩ����������������������\".split(\"\");\nfor(j = 0; j != D[168].length; ++j) if(D[168][j].charCodeAt(0) !== 0xFFFD) { e[D[168][j]] = 43008 + j; d[43008 + j] = D[168][j];}\nD[169] = \"����������������������������������������������������������������〡〢〣〤〥〦〧〨〩㊣㎎㎏㎜㎝㎞㎡㏄㏎㏑㏒㏕︰￢￤�℡㈱�‐���ー゛゜ヽヾ〆ゝゞ﹉﹊﹋﹌﹍﹎﹏﹐﹑﹒﹔﹕﹖﹗﹙﹚﹛﹜﹝﹞﹟﹠﹡�﹢﹣﹤﹥﹦﹨﹩﹪﹫�������������〇�������������─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋����������������\".split(\"\");\nfor(j = 0; j != D[169].length; ++j) if(D[169][j].charCodeAt(0) !== 0xFFFD) { e[D[169][j]] = 43264 + j; d[43264 + j] = D[169][j];}\nD[170] = \"����������������������������������������������������������������狜狝狟狢狣狤狥狦狧狪狫狵狶狹狽狾狿猀猂猄猅猆猇猈猉猋猌猍猏猐猑猒猔猘猙猚猟猠猣猤猦猧猨猭猯猰猲猳猵猶猺猻猼猽獀獁獂獃獄獅獆獇獈�獉獊獋獌獎獏獑獓獔獕獖獘獙獚獛獜獝獞獟獡獢獣獤獥獦獧獨獩獪獫獮獰獱�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[170].length; ++j) if(D[170][j].charCodeAt(0) !== 0xFFFD) { e[D[170][j]] = 43520 + j; d[43520 + j] = D[170][j];}\nD[171] = \"����������������������������������������������������������������獲獳獴獵獶獷獸獹獺獻獼獽獿玀玁玂玃玅玆玈玊玌玍玏玐玒玓玔玕玗玘玙玚玜玝玞玠玡玣玤玥玦玧玨玪玬玭玱玴玵玶玸玹玼玽玾玿珁珃珄珅珆珇�珋珌珎珒珓珔珕珖珗珘珚珛珜珝珟珡珢珣珤珦珨珪珫珬珮珯珰珱珳珴珵珶珷�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[171].length; ++j) if(D[171][j].charCodeAt(0) !== 0xFFFD) { e[D[171][j]] = 43776 + j; d[43776 + j] = D[171][j];}\nD[172] = \"����������������������������������������������������������������珸珹珺珻珼珽現珿琀琁琂琄琇琈琋琌琍琎琑琒琓琔琕琖琗琘琙琜琝琞琟琠琡琣琤琧琩琫琭琯琱琲琷琸琹琺琻琽琾琿瑀瑂瑃瑄瑅瑆瑇瑈瑉瑊瑋瑌瑍�瑎瑏瑐瑑瑒瑓瑔瑖瑘瑝瑠瑡瑢瑣瑤瑥瑦瑧瑨瑩瑪瑫瑬瑮瑯瑱瑲瑳瑴瑵瑸瑹瑺�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[172].length; ++j) if(D[172][j].charCodeAt(0) !== 0xFFFD) { e[D[172][j]] = 44032 + j; d[44032 + j] = D[172][j];}\nD[173] = \"����������������������������������������������������������������瑻瑼瑽瑿璂璄璅璆璈璉璊璌璍璏璑璒璓璔璕璖璗璘璙璚璛璝璟璠璡璢璣璤璥璦璪璫璬璭璮璯環璱璲璳璴璵璶璷璸璹璻璼璽璾璿瓀瓁瓂瓃瓄瓅瓆瓇�瓈瓉瓊瓋瓌瓍瓎瓏瓐瓑瓓瓔瓕瓖瓗瓘瓙瓚瓛瓝瓟瓡瓥瓧瓨瓩瓪瓫瓬瓭瓰瓱瓲�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[173].length; ++j) if(D[173][j].charCodeAt(0) !== 0xFFFD) { e[D[173][j]] = 44288 + j; d[44288 + j] = D[173][j];}\nD[174] = \"����������������������������������������������������������������瓳瓵瓸瓹瓺瓻瓼瓽瓾甀甁甂甃甅甆甇甈甉甊甋甌甎甐甒甔甕甖甗甛甝甞甠甡產産甤甦甧甪甮甴甶甹甼甽甿畁畂畃畄畆畇畉畊畍畐畑畒畓畕畖畗畘�畝畞畟畠畡畢畣畤畧畨畩畫畬畭畮畯異畱畳畵當畷畺畻畼畽畾疀疁疂疄疅疇�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[174].length; ++j) if(D[174][j].charCodeAt(0) !== 0xFFFD) { e[D[174][j]] = 44544 + j; d[44544 + j] = D[174][j];}\nD[175] = \"����������������������������������������������������������������疈疉疊疌疍疎疐疓疕疘疛疜疞疢疦疧疨疩疪疭疶疷疺疻疿痀痁痆痋痌痎痏痐痑痓痗痙痚痜痝痟痠痡痥痩痬痭痮痯痲痳痵痶痷痸痺痻痽痾瘂瘄瘆瘇�瘈瘉瘋瘍瘎瘏瘑瘒瘓瘔瘖瘚瘜瘝瘞瘡瘣瘧瘨瘬瘮瘯瘱瘲瘶瘷瘹瘺瘻瘽癁療癄�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[175].length; ++j) if(D[175][j].charCodeAt(0) !== 0xFFFD) { e[D[175][j]] = 44800 + j; d[44800 + j] = D[175][j];}\nD[176] = \"����������������������������������������������������������������癅癆癇癈癉癊癋癎癏癐癑癒癓癕癗癘癙癚癛癝癟癠癡癢癤癥癦癧癨癩癪癬癭癮癰癱癲癳癴癵癶癷癹発發癿皀皁皃皅皉皊皌皍皏皐皒皔皕皗皘皚皛�皜皝皞皟皠皡皢皣皥皦皧皨皩皪皫皬皭皯皰皳皵皶皷皸皹皺皻皼皽皾盀盁盃啊阿埃挨哎唉哀皑癌蔼矮艾碍爱隘鞍氨安俺按暗岸胺案肮昂盎凹敖熬翱袄傲奥懊澳芭捌扒叭吧笆八疤巴拔跋靶把耙坝霸罢爸白柏百摆佰败拜稗斑班搬扳般颁板版扮拌伴瓣半办绊邦帮梆榜膀绑棒磅蚌镑傍谤苞胞包褒剥�\".split(\"\");\nfor(j = 0; j != D[176].length; ++j) if(D[176][j].charCodeAt(0) !== 0xFFFD) { e[D[176][j]] = 45056 + j; d[45056 + j] = D[176][j];}\nD[177] = \"����������������������������������������������������������������盄盇盉盋盌盓盕盙盚盜盝盞盠盡盢監盤盦盧盨盩盪盫盬盭盰盳盵盶盷盺盻盽盿眀眂眃眅眆眊県眎眏眐眑眒眓眔眕眖眗眘眛眜眝眞眡眣眤眥眧眪眫�眬眮眰眱眲眳眴眹眻眽眾眿睂睄睅睆睈睉睊睋睌睍睎睏睒睓睔睕睖睗睘睙睜薄雹保堡饱宝抱报暴豹鲍爆杯碑悲卑北辈背贝钡倍狈备惫焙被奔苯本笨崩绷甭泵蹦迸逼鼻比鄙笔彼碧蓖蔽毕毙毖币庇痹闭敝弊必辟壁臂避陛鞭边编贬扁便变卞辨辩辫遍标彪膘表鳖憋别瘪彬斌濒滨宾摈兵冰柄丙秉饼炳�\".split(\"\");\nfor(j = 0; j != D[177].length; ++j) if(D[177][j].charCodeAt(0) !== 0xFFFD) { e[D[177][j]] = 45312 + j; d[45312 + j] = D[177][j];}\nD[178] = \"����������������������������������������������������������������睝睞睟睠睤睧睩睪睭睮睯睰睱睲睳睴睵睶睷睸睺睻睼瞁瞂瞃瞆瞇瞈瞉瞊瞋瞏瞐瞓瞔瞕瞖瞗瞘瞙瞚瞛瞜瞝瞞瞡瞣瞤瞦瞨瞫瞭瞮瞯瞱瞲瞴瞶瞷瞸瞹瞺�瞼瞾矀矁矂矃矄矅矆矇矈矉矊矋矌矎矏矐矑矒矓矔矕矖矘矙矚矝矞矟矠矡矤病并玻菠播拨钵波博勃搏铂箔伯帛舶脖膊渤泊驳捕卜哺补埠不布步簿部怖擦猜裁材才财睬踩采彩菜蔡餐参蚕残惭惨灿苍舱仓沧藏操糙槽曹草厕策侧册测层蹭插叉茬茶查碴搽察岔差诧拆柴豺搀掺蝉馋谗缠铲产阐颤昌猖�\".split(\"\");\nfor(j = 0; j != D[178].length; ++j) if(D[178][j].charCodeAt(0) !== 0xFFFD) { e[D[178][j]] = 45568 + j; d[45568 + j] = D[178][j];}\nD[179] = \"����������������������������������������������������������������矦矨矪矯矰矱矲矴矵矷矹矺矻矼砃砄砅砆砇砈砊砋砎砏砐砓砕砙砛砞砠砡砢砤砨砪砫砮砯砱砲砳砵砶砽砿硁硂硃硄硆硈硉硊硋硍硏硑硓硔硘硙硚�硛硜硞硟硠硡硢硣硤硥硦硧硨硩硯硰硱硲硳硴硵硶硸硹硺硻硽硾硿碀碁碂碃场尝常长偿肠厂敞畅唱倡超抄钞朝嘲潮巢吵炒车扯撤掣彻澈郴臣辰尘晨忱沉陈趁衬撑称城橙成呈乘程惩澄诚承逞骋秤吃痴持匙池迟弛驰耻齿侈尺赤翅斥炽充冲虫崇宠抽酬畴踌稠愁筹仇绸瞅丑臭初出橱厨躇锄雏滁除楚�\".split(\"\");\nfor(j = 0; j != D[179].length; ++j) if(D[179][j].charCodeAt(0) !== 0xFFFD) { e[D[179][j]] = 45824 + j; d[45824 + j] = D[179][j];}\nD[180] = \"����������������������������������������������������������������碄碅碆碈碊碋碏碐碒碔碕碖碙碝碞碠碢碤碦碨碩碪碫碬碭碮碯碵碶碷碸確碻碼碽碿磀磂磃磄磆磇磈磌磍磎磏磑磒磓磖磗磘磚磛磜磝磞磟磠磡磢磣�磤磥磦磧磩磪磫磭磮磯磰磱磳磵磶磸磹磻磼磽磾磿礀礂礃礄礆礇礈礉礊礋礌础储矗搐触处揣川穿椽传船喘串疮窗幢床闯创吹炊捶锤垂春椿醇唇淳纯蠢戳绰疵茨磁雌辞慈瓷词此刺赐次聪葱囱匆从丛凑粗醋簇促蹿篡窜摧崔催脆瘁粹淬翠村存寸磋撮搓措挫错搭达答瘩打大呆歹傣戴带殆代贷袋待逮�\".split(\"\");\nfor(j = 0; j != D[180].length; ++j) if(D[180][j].charCodeAt(0) !== 0xFFFD) { e[D[180][j]] = 46080 + j; d[46080 + j] = D[180][j];}\nD[181] = \"����������������������������������������������������������������礍礎礏礐礑礒礔礕礖礗礘礙礚礛礜礝礟礠礡礢礣礥礦礧礨礩礪礫礬礭礮礯礰礱礲礳礵礶礷礸礹礽礿祂祃祄祅祇祊祋祌祍祎祏祐祑祒祔祕祘祙祡祣�祤祦祩祪祫祬祮祰祱祲祳祴祵祶祹祻祼祽祾祿禂禃禆禇禈禉禋禌禍禎禐禑禒怠耽担丹单郸掸胆旦氮但惮淡诞弹蛋当挡党荡档刀捣蹈倒岛祷导到稻悼道盗德得的蹬灯登等瞪凳邓堤低滴迪敌笛狄涤翟嫡抵底地蒂第帝弟递缔颠掂滇碘点典靛垫电佃甸店惦奠淀殿碉叼雕凋刁掉吊钓调跌爹碟蝶迭谍叠�\".split(\"\");\nfor(j = 0; j != D[181].length; ++j) if(D[181][j].charCodeAt(0) !== 0xFFFD) { e[D[181][j]] = 46336 + j; d[46336 + j] = D[181][j];}\nD[182] = \"����������������������������������������������������������������禓禔禕禖禗禘禙禛禜禝禞禟禠禡禢禣禤禥禦禨禩禪禫禬禭禮禯禰禱禲禴禵禶禷禸禼禿秂秄秅秇秈秊秌秎秏秐秓秔秖秗秙秚秛秜秝秞秠秡秢秥秨秪�秬秮秱秲秳秴秵秶秷秹秺秼秾秿稁稄稅稇稈稉稊稌稏稐稑稒稓稕稖稘稙稛稜丁盯叮钉顶鼎锭定订丢东冬董懂动栋侗恫冻洞兜抖斗陡豆逗痘都督毒犊独读堵睹赌杜镀肚度渡妒端短锻段断缎堆兑队对墩吨蹲敦顿囤钝盾遁掇哆多夺垛躲朵跺舵剁惰堕蛾峨鹅俄额讹娥恶厄扼遏鄂饿恩而儿耳尔饵洱二�\".split(\"\");\nfor(j = 0; j != D[182].length; ++j) if(D[182][j].charCodeAt(0) !== 0xFFFD) { e[D[182][j]] = 46592 + j; d[46592 + j] = D[182][j];}\nD[183] = \"����������������������������������������������������������������稝稟稡稢稤稥稦稧稨稩稪稫稬稭種稯稰稱稲稴稵稶稸稺稾穀穁穂穃穄穅穇穈穉穊穋穌積穎穏穐穒穓穔穕穖穘穙穚穛穜穝穞穟穠穡穢穣穤穥穦穧穨�穩穪穫穬穭穮穯穱穲穳穵穻穼穽穾窂窅窇窉窊窋窌窎窏窐窓窔窙窚窛窞窡窢贰发罚筏伐乏阀法珐藩帆番翻樊矾钒繁凡烦反返范贩犯饭泛坊芳方肪房防妨仿访纺放菲非啡飞肥匪诽吠肺废沸费芬酚吩氛分纷坟焚汾粉奋份忿愤粪丰封枫蜂峰锋风疯烽逢冯缝讽奉凤佛否夫敷肤孵扶拂辐幅氟符伏俘服�\".split(\"\");\nfor(j = 0; j != D[183].length; ++j) if(D[183][j].charCodeAt(0) !== 0xFFFD) { e[D[183][j]] = 46848 + j; d[46848 + j] = D[183][j];}\nD[184] = \"����������������������������������������������������������������窣窤窧窩窪窫窮窯窰窱窲窴窵窶窷窸窹窺窻窼窽窾竀竁竂竃竄竅竆竇竈竉竊竌竍竎竏竐竑竒竓竔竕竗竘竚竛竜竝竡竢竤竧竨竩竪竫竬竮竰竱竲竳�竴竵競竷竸竻竼竾笀笁笂笅笇笉笌笍笎笐笒笓笖笗笘笚笜笝笟笡笢笣笧笩笭浮涪福袱弗甫抚辅俯釜斧脯腑府腐赴副覆赋复傅付阜父腹负富讣附妇缚咐噶嘎该改概钙盖溉干甘杆柑竿肝赶感秆敢赣冈刚钢缸肛纲岗港杠篙皋高膏羔糕搞镐稿告哥歌搁戈鸽胳疙割革葛格蛤阁隔铬个各给根跟耕更庚羹�\".split(\"\");\nfor(j = 0; j != D[184].length; ++j) if(D[184][j].charCodeAt(0) !== 0xFFFD) { e[D[184][j]] = 47104 + j; d[47104 + j] = D[184][j];}\nD[185] = \"����������������������������������������������������������������笯笰笲笴笵笶笷笹笻笽笿筀筁筂筃筄筆筈筊筍筎筓筕筗筙筜筞筟筡筣筤筥筦筧筨筩筪筫筬筭筯筰筳筴筶筸筺筼筽筿箁箂箃箄箆箇箈箉箊箋箌箎箏�箑箒箓箖箘箙箚箛箞箟箠箣箤箥箮箯箰箲箳箵箶箷箹箺箻箼箽箾箿節篂篃範埂耿梗工攻功恭龚供躬公宫弓巩汞拱贡共钩勾沟苟狗垢构购够辜菇咕箍估沽孤姑鼓古蛊骨谷股故顾固雇刮瓜剐寡挂褂乖拐怪棺关官冠观管馆罐惯灌贯光广逛瑰规圭硅归龟闺轨鬼诡癸桂柜跪贵刽辊滚棍锅郭国果裹过哈�\".split(\"\");\nfor(j = 0; j != D[185].length; ++j) if(D[185][j].charCodeAt(0) !== 0xFFFD) { e[D[185][j]] = 47360 + j; d[47360 + j] = D[185][j];}\nD[186] = \"����������������������������������������������������������������篅篈築篊篋篍篎篏篐篒篔篕篖篗篘篛篜篞篟篠篢篣篤篧篨篩篫篬篭篯篰篲篳篴篵篶篸篹篺篻篽篿簀簁簂簃簄簅簆簈簉簊簍簎簐簑簒簓簔簕簗簘簙�簚簛簜簝簞簠簡簢簣簤簥簨簩簫簬簭簮簯簰簱簲簳簴簵簶簷簹簺簻簼簽簾籂骸孩海氦亥害骇酣憨邯韩含涵寒函喊罕翰撼捍旱憾悍焊汗汉夯杭航壕嚎豪毫郝好耗号浩呵喝荷菏核禾和何合盒貉阂河涸赫褐鹤贺嘿黑痕很狠恨哼亨横衡恒轰哄烘虹鸿洪宏弘红喉侯猴吼厚候后呼乎忽瑚壶葫胡蝴狐糊湖�\".split(\"\");\nfor(j = 0; j != D[186].length; ++j) if(D[186][j].charCodeAt(0) !== 0xFFFD) { e[D[186][j]] = 47616 + j; d[47616 + j] = D[186][j];}\nD[187] = \"����������������������������������������������������������������籃籄籅籆籇籈籉籊籋籌籎籏籐籑籒籓籔籕籖籗籘籙籚籛籜籝籞籟籠籡籢籣籤籥籦籧籨籩籪籫籬籭籮籯籰籱籲籵籶籷籸籹籺籾籿粀粁粂粃粄粅粆粇�粈粊粋粌粍粎粏粐粓粔粖粙粚粛粠粡粣粦粧粨粩粫粬粭粯粰粴粵粶粷粸粺粻弧虎唬护互沪户花哗华猾滑画划化话槐徊怀淮坏欢环桓还缓换患唤痪豢焕涣宦幻荒慌黄磺蝗簧皇凰惶煌晃幌恍谎灰挥辉徽恢蛔回毁悔慧卉惠晦贿秽会烩汇讳诲绘荤昏婚魂浑混豁活伙火获或惑霍货祸击圾基机畸稽积箕�\".split(\"\");\nfor(j = 0; j != D[187].length; ++j) if(D[187][j].charCodeAt(0) !== 0xFFFD) { e[D[187][j]] = 47872 + j; d[47872 + j] = D[187][j];}\nD[188] = \"����������������������������������������������������������������粿糀糂糃糄糆糉糋糎糏糐糑糒糓糔糘糚糛糝糞糡糢糣糤糥糦糧糩糪糫糬糭糮糰糱糲糳糴糵糶糷糹糺糼糽糾糿紀紁紂紃約紅紆紇紈紉紋紌納紎紏紐�紑紒紓純紕紖紗紘紙級紛紜紝紞紟紡紣紤紥紦紨紩紪紬紭紮細紱紲紳紴紵紶肌饥迹激讥鸡姬绩缉吉极棘辑籍集及急疾汲即嫉级挤几脊己蓟技冀季伎祭剂悸济寄寂计记既忌际妓继纪嘉枷夹佳家加荚颊贾甲钾假稼价架驾嫁歼监坚尖笺间煎兼肩艰奸缄茧检柬碱硷拣捡简俭剪减荐槛鉴践贱见键箭件�\".split(\"\");\nfor(j = 0; j != D[188].length; ++j) if(D[188][j].charCodeAt(0) !== 0xFFFD) { e[D[188][j]] = 48128 + j; d[48128 + j] = D[188][j];}\nD[189] = \"����������������������������������������������������������������紷紸紹紺紻紼紽紾紿絀絁終絃組絅絆絇絈絉絊絋経絍絎絏結絑絒絓絔絕絖絗絘絙絚絛絜絝絞絟絠絡絢絣絤絥給絧絨絩絪絫絬絭絯絰統絲絳絴絵絶�絸絹絺絻絼絽絾絿綀綁綂綃綄綅綆綇綈綉綊綋綌綍綎綏綐綑綒經綔綕綖綗綘健舰剑饯渐溅涧建僵姜将浆江疆蒋桨奖讲匠酱降蕉椒礁焦胶交郊浇骄娇嚼搅铰矫侥脚狡角饺缴绞剿教酵轿较叫窖揭接皆秸街阶截劫节桔杰捷睫竭洁结解姐戒藉芥界借介疥诫届巾筋斤金今津襟紧锦仅谨进靳晋禁近烬浸�\".split(\"\");\nfor(j = 0; j != D[189].length; ++j) if(D[189][j].charCodeAt(0) !== 0xFFFD) { e[D[189][j]] = 48384 + j; d[48384 + j] = D[189][j];}\nD[190] = \"����������������������������������������������������������������継続綛綜綝綞綟綠綡綢綣綤綥綧綨綩綪綫綬維綯綰綱網綳綴綵綶綷綸綹綺綻綼綽綾綿緀緁緂緃緄緅緆緇緈緉緊緋緌緍緎総緐緑緒緓緔緕緖緗緘緙�線緛緜緝緞緟締緡緢緣緤緥緦緧編緩緪緫緬緭緮緯緰緱緲緳練緵緶緷緸緹緺尽劲荆兢茎睛晶鲸京惊精粳经井警景颈静境敬镜径痉靖竟竞净炯窘揪究纠玖韭久灸九酒厩救旧臼舅咎就疚鞠拘狙疽居驹菊局咀矩举沮聚拒据巨具距踞锯俱句惧炬剧捐鹃娟倦眷卷绢撅攫抉掘倔爵觉决诀绝均菌钧军君峻�\".split(\"\");\nfor(j = 0; j != D[190].length; ++j) if(D[190][j].charCodeAt(0) !== 0xFFFD) { e[D[190][j]] = 48640 + j; d[48640 + j] = D[190][j];}\nD[191] = \"����������������������������������������������������������������緻緼緽緾緿縀縁縂縃縄縅縆縇縈縉縊縋縌縍縎縏縐縑縒縓縔縕縖縗縘縙縚縛縜縝縞縟縠縡縢縣縤縥縦縧縨縩縪縫縬縭縮縯縰縱縲縳縴縵縶縷縸縹�縺縼總績縿繀繂繃繄繅繆繈繉繊繋繌繍繎繏繐繑繒繓織繕繖繗繘繙繚繛繜繝俊竣浚郡骏喀咖卡咯开揩楷凯慨刊堪勘坎砍看康慷糠扛抗亢炕考拷烤靠坷苛柯棵磕颗科壳咳可渴克刻客课肯啃垦恳坑吭空恐孔控抠口扣寇枯哭窟苦酷库裤夸垮挎跨胯块筷侩快宽款匡筐狂框矿眶旷况亏盔岿窥葵奎魁傀�\".split(\"\");\nfor(j = 0; j != D[191].length; ++j) if(D[191][j].charCodeAt(0) !== 0xFFFD) { e[D[191][j]] = 48896 + j; d[48896 + j] = D[191][j];}\nD[192] = \"����������������������������������������������������������������繞繟繠繡繢繣繤繥繦繧繨繩繪繫繬繭繮繯繰繱繲繳繴繵繶繷繸繹繺繻繼繽繾繿纀纁纃纄纅纆纇纈纉纊纋續纍纎纏纐纑纒纓纔纕纖纗纘纙纚纜纝纞�纮纴纻纼绖绤绬绹缊缐缞缷缹缻缼缽缾缿罀罁罃罆罇罈罉罊罋罌罍罎罏罒罓馈愧溃坤昆捆困括扩廓阔垃拉喇蜡腊辣啦莱来赖蓝婪栏拦篮阑兰澜谰揽览懒缆烂滥琅榔狼廊郎朗浪捞劳牢老佬姥酪烙涝勒乐雷镭蕾磊累儡垒擂肋类泪棱楞冷厘梨犁黎篱狸离漓理李里鲤礼莉荔吏栗丽厉励砾历利傈例俐�\".split(\"\");\nfor(j = 0; j != D[192].length; ++j) if(D[192][j].charCodeAt(0) !== 0xFFFD) { e[D[192][j]] = 49152 + j; d[49152 + j] = D[192][j];}\nD[193] = \"����������������������������������������������������������������罖罙罛罜罝罞罠罣罤罥罦罧罫罬罭罯罰罳罵罶罷罸罺罻罼罽罿羀羂羃羄羅羆羇羈羉羋羍羏羐羑羒羓羕羖羗羘羙羛羜羠羢羣羥羦羨義羪羫羬羭羮羱�羳羴羵羶羷羺羻羾翀翂翃翄翆翇翈翉翋翍翏翐翑習翓翖翗翙翚翛翜翝翞翢翣痢立粒沥隶力璃哩俩联莲连镰廉怜涟帘敛脸链恋炼练粮凉梁粱良两辆量晾亮谅撩聊僚疗燎寥辽潦了撂镣廖料列裂烈劣猎琳林磷霖临邻鳞淋凛赁吝拎玲菱零龄铃伶羚凌灵陵岭领另令溜琉榴硫馏留刘瘤流柳六龙聋咙笼窿�\".split(\"\");\nfor(j = 0; j != D[193].length; ++j) if(D[193][j].charCodeAt(0) !== 0xFFFD) { e[D[193][j]] = 49408 + j; d[49408 + j] = D[193][j];}\nD[194] = \"����������������������������������������������������������������翤翧翨翪翫翬翭翯翲翴翵翶翷翸翹翺翽翾翿耂耇耈耉耊耎耏耑耓耚耛耝耞耟耡耣耤耫耬耭耮耯耰耲耴耹耺耼耾聀聁聄聅聇聈聉聎聏聐聑聓聕聖聗�聙聛聜聝聞聟聠聡聢聣聤聥聦聧聨聫聬聭聮聯聰聲聳聴聵聶職聸聹聺聻聼聽隆垄拢陇楼娄搂篓漏陋芦卢颅庐炉掳卤虏鲁麓碌露路赂鹿潞禄录陆戮驴吕铝侣旅履屡缕虑氯律率滤绿峦挛孪滦卵乱掠略抡轮伦仑沦纶论萝螺罗逻锣箩骡裸落洛骆络妈麻玛码蚂马骂嘛吗埋买麦卖迈脉瞒馒蛮满蔓曼慢漫�\".split(\"\");\nfor(j = 0; j != D[194].length; ++j) if(D[194][j].charCodeAt(0) !== 0xFFFD) { e[D[194][j]] = 49664 + j; d[49664 + j] = D[194][j];}\nD[195] = \"����������������������������������������������������������������聾肁肂肅肈肊肍肎肏肐肑肒肔肕肗肙肞肣肦肧肨肬肰肳肵肶肸肹肻胅胇胈胉胊胋胏胐胑胒胓胔胕胘胟胠胢胣胦胮胵胷胹胻胾胿脀脁脃脄脅脇脈脋�脌脕脗脙脛脜脝脟脠脡脢脣脤脥脦脧脨脩脪脫脭脮脰脳脴脵脷脹脺脻脼脽脿谩芒茫盲氓忙莽猫茅锚毛矛铆卯茂冒帽貌贸么玫枚梅酶霉煤没眉媒镁每美昧寐妹媚门闷们萌蒙檬盟锰猛梦孟眯醚靡糜迷谜弥米秘觅泌蜜密幂棉眠绵冕免勉娩缅面苗描瞄藐秒渺庙妙蔑灭民抿皿敏悯闽明螟鸣铭名命谬摸�\".split(\"\");\nfor(j = 0; j != D[195].length; ++j) if(D[195][j].charCodeAt(0) !== 0xFFFD) { e[D[195][j]] = 49920 + j; d[49920 + j] = D[195][j];}\nD[196] = \"����������������������������������������������������������������腀腁腂腃腄腅腇腉腍腎腏腒腖腗腘腛腜腝腞腟腡腢腣腤腦腨腪腫腬腯腲腳腵腶腷腸膁膃膄膅膆膇膉膋膌膍膎膐膒膓膔膕膖膗膙膚膞膟膠膡膢膤膥�膧膩膫膬膭膮膯膰膱膲膴膵膶膷膸膹膼膽膾膿臄臅臇臈臉臋臍臎臏臐臑臒臓摹蘑模膜磨摩魔抹末莫墨默沫漠寞陌谋牟某拇牡亩姆母墓暮幕募慕木目睦牧穆拿哪呐钠那娜纳氖乃奶耐奈南男难囊挠脑恼闹淖呢馁内嫩能妮霓倪泥尼拟你匿腻逆溺蔫拈年碾撵捻念娘酿鸟尿捏聂孽啮镊镍涅您柠狞凝宁�\".split(\"\");\nfor(j = 0; j != D[196].length; ++j) if(D[196][j].charCodeAt(0) !== 0xFFFD) { e[D[196][j]] = 50176 + j; d[50176 + j] = D[196][j];}\nD[197] = \"����������������������������������������������������������������臔臕臖臗臘臙臚臛臜臝臞臟臠臡臢臤臥臦臨臩臫臮臯臰臱臲臵臶臷臸臹臺臽臿舃與興舉舊舋舎舏舑舓舕舖舗舘舙舚舝舠舤舥舦舧舩舮舲舺舼舽舿�艀艁艂艃艅艆艈艊艌艍艎艐艑艒艓艔艕艖艗艙艛艜艝艞艠艡艢艣艤艥艦艧艩拧泞牛扭钮纽脓浓农弄奴努怒女暖虐疟挪懦糯诺哦欧鸥殴藕呕偶沤啪趴爬帕怕琶拍排牌徘湃派攀潘盘磐盼畔判叛乓庞旁耪胖抛咆刨炮袍跑泡呸胚培裴赔陪配佩沛喷盆砰抨烹澎彭蓬棚硼篷膨朋鹏捧碰坯砒霹批披劈琵毗�\".split(\"\");\nfor(j = 0; j != D[197].length; ++j) if(D[197][j].charCodeAt(0) !== 0xFFFD) { e[D[197][j]] = 50432 + j; d[50432 + j] = D[197][j];}\nD[198] = \"����������������������������������������������������������������艪艫艬艭艱艵艶艷艸艻艼芀芁芃芅芆芇芉芌芐芓芔芕芖芚芛芞芠芢芣芧芲芵芶芺芻芼芿苀苂苃苅苆苉苐苖苙苚苝苢苧苨苩苪苬苭苮苰苲苳苵苶苸�苺苼苽苾苿茀茊茋茍茐茒茓茖茘茙茝茞茟茠茡茢茣茤茥茦茩茪茮茰茲茷茻茽啤脾疲皮匹痞僻屁譬篇偏片骗飘漂瓢票撇瞥拼频贫品聘乒坪苹萍平凭瓶评屏坡泼颇婆破魄迫粕剖扑铺仆莆葡菩蒲埔朴圃普浦谱曝瀑期欺栖戚妻七凄漆柒沏其棋奇歧畦崎脐齐旗祈祁骑起岂乞企启契砌器气迄弃汽泣讫掐�\".split(\"\");\nfor(j = 0; j != D[198].length; ++j) if(D[198][j].charCodeAt(0) !== 0xFFFD) { e[D[198][j]] = 50688 + j; d[50688 + j] = D[198][j];}\nD[199] = \"����������������������������������������������������������������茾茿荁荂荄荅荈荊荋荌荍荎荓荕荖荗荘荙荝荢荰荱荲荳荴荵荶荹荺荾荿莀莁莂莃莄莇莈莊莋莌莍莏莐莑莔莕莖莗莙莚莝莟莡莢莣莤莥莦莧莬莭莮�莯莵莻莾莿菂菃菄菆菈菉菋菍菎菐菑菒菓菕菗菙菚菛菞菢菣菤菦菧菨菫菬菭恰洽牵扦钎铅千迁签仟谦乾黔钱钳前潜遣浅谴堑嵌欠歉枪呛腔羌墙蔷强抢橇锹敲悄桥瞧乔侨巧鞘撬翘峭俏窍切茄且怯窃钦侵亲秦琴勤芹擒禽寝沁青轻氢倾卿清擎晴氰情顷请庆琼穷秋丘邱球求囚酋泅趋区蛆曲躯屈驱渠�\".split(\"\");\nfor(j = 0; j != D[199].length; ++j) if(D[199][j].charCodeAt(0) !== 0xFFFD) { e[D[199][j]] = 50944 + j; d[50944 + j] = D[199][j];}\nD[200] = \"����������������������������������������������������������������菮華菳菴菵菶菷菺菻菼菾菿萀萂萅萇萈萉萊萐萒萓萔萕萖萗萙萚萛萞萟萠萡萢萣萩萪萫萬萭萮萯萰萲萳萴萵萶萷萹萺萻萾萿葀葁葂葃葄葅葇葈葉�葊葋葌葍葎葏葐葒葓葔葕葖葘葝葞葟葠葢葤葥葦葧葨葪葮葯葰葲葴葷葹葻葼取娶龋趣去圈颧权醛泉全痊拳犬券劝缺炔瘸却鹊榷确雀裙群然燃冉染瓤壤攘嚷让饶扰绕惹热壬仁人忍韧任认刃妊纫扔仍日戎茸蓉荣融熔溶容绒冗揉柔肉茹蠕儒孺如辱乳汝入褥软阮蕊瑞锐闰润若弱撒洒萨腮鳃塞赛三叁�\".split(\"\");\nfor(j = 0; j != D[200].length; ++j) if(D[200][j].charCodeAt(0) !== 0xFFFD) { e[D[200][j]] = 51200 + j; d[51200 + j] = D[200][j];}\nD[201] = \"����������������������������������������������������������������葽葾葿蒀蒁蒃蒄蒅蒆蒊蒍蒏蒐蒑蒒蒓蒔蒕蒖蒘蒚蒛蒝蒞蒟蒠蒢蒣蒤蒥蒦蒧蒨蒩蒪蒫蒬蒭蒮蒰蒱蒳蒵蒶蒷蒻蒼蒾蓀蓂蓃蓅蓆蓇蓈蓋蓌蓎蓏蓒蓔蓕蓗�蓘蓙蓚蓛蓜蓞蓡蓢蓤蓧蓨蓩蓪蓫蓭蓮蓯蓱蓲蓳蓴蓵蓶蓷蓸蓹蓺蓻蓽蓾蔀蔁蔂伞散桑嗓丧搔骚扫嫂瑟色涩森僧莎砂杀刹沙纱傻啥煞筛晒珊苫杉山删煽衫闪陕擅赡膳善汕扇缮墒伤商赏晌上尚裳梢捎稍烧芍勺韶少哨邵绍奢赊蛇舌舍赦摄射慑涉社设砷申呻伸身深娠绅神沈审婶甚肾慎渗声生甥牲升绳�\".split(\"\");\nfor(j = 0; j != D[201].length; ++j) if(D[201][j].charCodeAt(0) !== 0xFFFD) { e[D[201][j]] = 51456 + j; d[51456 + j] = D[201][j];}\nD[202] = \"����������������������������������������������������������������蔃蔄蔅蔆蔇蔈蔉蔊蔋蔍蔎蔏蔐蔒蔔蔕蔖蔘蔙蔛蔜蔝蔞蔠蔢蔣蔤蔥蔦蔧蔨蔩蔪蔭蔮蔯蔰蔱蔲蔳蔴蔵蔶蔾蔿蕀蕁蕂蕄蕅蕆蕇蕋蕌蕍蕎蕏蕐蕑蕒蕓蕔蕕�蕗蕘蕚蕛蕜蕝蕟蕠蕡蕢蕣蕥蕦蕧蕩蕪蕫蕬蕭蕮蕯蕰蕱蕳蕵蕶蕷蕸蕼蕽蕿薀薁省盛剩胜圣师失狮施湿诗尸虱十石拾时什食蚀实识史矢使屎驶始式示士世柿事拭誓逝势是嗜噬适仕侍释饰氏市恃室视试收手首守寿授售受瘦兽蔬枢梳殊抒输叔舒淑疏书赎孰熟薯暑曙署蜀黍鼠属术述树束戍竖墅庶数漱�\".split(\"\");\nfor(j = 0; j != D[202].length; ++j) if(D[202][j].charCodeAt(0) !== 0xFFFD) { e[D[202][j]] = 51712 + j; d[51712 + j] = D[202][j];}\nD[203] = \"����������������������������������������������������������������薂薃薆薈薉薊薋薌薍薎薐薑薒薓薔薕薖薗薘薙薚薝薞薟薠薡薢薣薥薦薧薩薫薬薭薱薲薳薴薵薶薸薺薻薼薽薾薿藀藂藃藄藅藆藇藈藊藋藌藍藎藑藒�藔藖藗藘藙藚藛藝藞藟藠藡藢藣藥藦藧藨藪藫藬藭藮藯藰藱藲藳藴藵藶藷藸恕刷耍摔衰甩帅栓拴霜双爽谁水睡税吮瞬顺舜说硕朔烁斯撕嘶思私司丝死肆寺嗣四伺似饲巳松耸怂颂送宋讼诵搜艘擞嗽苏酥俗素速粟僳塑溯宿诉肃酸蒜算虽隋随绥髓碎岁穗遂隧祟孙损笋蓑梭唆缩琐索锁所塌他它她塔�\".split(\"\");\nfor(j = 0; j != D[203].length; ++j) if(D[203][j].charCodeAt(0) !== 0xFFFD) { e[D[203][j]] = 51968 + j; d[51968 + j] = D[203][j];}\nD[204] = \"����������������������������������������������������������������藹藺藼藽藾蘀蘁蘂蘃蘄蘆蘇蘈蘉蘊蘋蘌蘍蘎蘏蘐蘒蘓蘔蘕蘗蘘蘙蘚蘛蘜蘝蘞蘟蘠蘡蘢蘣蘤蘥蘦蘨蘪蘫蘬蘭蘮蘯蘰蘱蘲蘳蘴蘵蘶蘷蘹蘺蘻蘽蘾蘿虀�虁虂虃虄虅虆虇虈虉虊虋虌虒虓處虖虗虘虙虛虜虝號虠虡虣虤虥虦虧虨虩虪獭挞蹋踏胎苔抬台泰酞太态汰坍摊贪瘫滩坛檀痰潭谭谈坦毯袒碳探叹炭汤塘搪堂棠膛唐糖倘躺淌趟烫掏涛滔绦萄桃逃淘陶讨套特藤腾疼誊梯剔踢锑提题蹄啼体替嚏惕涕剃屉天添填田甜恬舔腆挑条迢眺跳贴铁帖厅听烃�\".split(\"\");\nfor(j = 0; j != D[204].length; ++j) if(D[204][j].charCodeAt(0) !== 0xFFFD) { e[D[204][j]] = 52224 + j; d[52224 + j] = D[204][j];}\nD[205] = \"����������������������������������������������������������������虭虯虰虲虳虴虵虶虷虸蚃蚄蚅蚆蚇蚈蚉蚎蚏蚐蚑蚒蚔蚖蚗蚘蚙蚚蚛蚞蚟蚠蚡蚢蚥蚦蚫蚭蚮蚲蚳蚷蚸蚹蚻蚼蚽蚾蚿蛁蛂蛃蛅蛈蛌蛍蛒蛓蛕蛖蛗蛚蛜�蛝蛠蛡蛢蛣蛥蛦蛧蛨蛪蛫蛬蛯蛵蛶蛷蛺蛻蛼蛽蛿蜁蜄蜅蜆蜋蜌蜎蜏蜐蜑蜔蜖汀廷停亭庭挺艇通桐酮瞳同铜彤童桶捅筒统痛偷投头透凸秃突图徒途涂屠土吐兔湍团推颓腿蜕褪退吞屯臀拖托脱鸵陀驮驼椭妥拓唾挖哇蛙洼娃瓦袜歪外豌弯湾玩顽丸烷完碗挽晚皖惋宛婉万腕汪王亡枉网往旺望忘妄威�\".split(\"\");\nfor(j = 0; j != D[205].length; ++j) if(D[205][j].charCodeAt(0) !== 0xFFFD) { e[D[205][j]] = 52480 + j; d[52480 + j] = D[205][j];}\nD[206] = \"����������������������������������������������������������������蜙蜛蜝蜟蜠蜤蜦蜧蜨蜪蜫蜬蜭蜯蜰蜲蜳蜵蜶蜸蜹蜺蜼蜽蝀蝁蝂蝃蝄蝅蝆蝊蝋蝍蝏蝐蝑蝒蝔蝕蝖蝘蝚蝛蝜蝝蝞蝟蝡蝢蝦蝧蝨蝩蝪蝫蝬蝭蝯蝱蝲蝳蝵�蝷蝸蝹蝺蝿螀螁螄螆螇螉螊螌螎螏螐螑螒螔螕螖螘螙螚螛螜螝螞螠螡螢螣螤巍微危韦违桅围唯惟为潍维苇萎委伟伪尾纬未蔚味畏胃喂魏位渭谓尉慰卫瘟温蚊文闻纹吻稳紊问嗡翁瓮挝蜗涡窝我斡卧握沃巫呜钨乌污诬屋无芜梧吾吴毋武五捂午舞伍侮坞戊雾晤物勿务悟误昔熙析西硒矽晰嘻吸锡牺�\".split(\"\");\nfor(j = 0; j != D[206].length; ++j) if(D[206][j].charCodeAt(0) !== 0xFFFD) { e[D[206][j]] = 52736 + j; d[52736 + j] = D[206][j];}\nD[207] = \"����������������������������������������������������������������螥螦螧螩螪螮螰螱螲螴螶螷螸螹螻螼螾螿蟁蟂蟃蟄蟅蟇蟈蟉蟌蟍蟎蟏蟐蟔蟕蟖蟗蟘蟙蟚蟜蟝蟞蟟蟡蟢蟣蟤蟦蟧蟨蟩蟫蟬蟭蟯蟰蟱蟲蟳蟴蟵蟶蟷蟸�蟺蟻蟼蟽蟿蠀蠁蠂蠄蠅蠆蠇蠈蠉蠋蠌蠍蠎蠏蠐蠑蠒蠔蠗蠘蠙蠚蠜蠝蠞蠟蠠蠣稀息希悉膝夕惜熄烯溪汐犀檄袭席习媳喜铣洗系隙戏细瞎虾匣霞辖暇峡侠狭下厦夏吓掀锨先仙鲜纤咸贤衔舷闲涎弦嫌显险现献县腺馅羡宪陷限线相厢镶香箱襄湘乡翔祥详想响享项巷橡像向象萧硝霄削哮嚣销消宵淆晓�\".split(\"\");\nfor(j = 0; j != D[207].length; ++j) if(D[207][j].charCodeAt(0) !== 0xFFFD) { e[D[207][j]] = 52992 + j; d[52992 + j] = D[207][j];}\nD[208] = \"����������������������������������������������������������������蠤蠥蠦蠧蠨蠩蠪蠫蠬蠭蠮蠯蠰蠱蠳蠴蠵蠶蠷蠸蠺蠻蠽蠾蠿衁衂衃衆衇衈衉衊衋衎衏衐衑衒術衕衖衘衚衛衜衝衞衟衠衦衧衪衭衯衱衳衴衵衶衸衹衺�衻衼袀袃袆袇袉袊袌袎袏袐袑袓袔袕袗袘袙袚袛袝袞袟袠袡袣袥袦袧袨袩袪小孝校肖啸笑效楔些歇蝎鞋协挟携邪斜胁谐写械卸蟹懈泄泻谢屑薪芯锌欣辛新忻心信衅星腥猩惺兴刑型形邢行醒幸杏性姓兄凶胸匈汹雄熊休修羞朽嗅锈秀袖绣墟戌需虚嘘须徐许蓄酗叙旭序畜恤絮婿绪续轩喧宣悬旋玄�\".split(\"\");\nfor(j = 0; j != D[208].length; ++j) if(D[208][j].charCodeAt(0) !== 0xFFFD) { e[D[208][j]] = 53248 + j; d[53248 + j] = D[208][j];}\nD[209] = \"����������������������������������������������������������������袬袮袯袰袲袳袴袵袶袸袹袺袻袽袾袿裀裃裄裇裈裊裋裌裍裏裐裑裓裖裗裚裛補裝裞裠裡裦裧裩裪裫裬裭裮裯裲裵裶裷裺裻製裿褀褁褃褄褅褆複褈�褉褋褌褍褎褏褑褔褕褖褗褘褜褝褞褟褠褢褣褤褦褧褨褩褬褭褮褯褱褲褳褵褷选癣眩绚靴薛学穴雪血勋熏循旬询寻驯巡殉汛训讯逊迅压押鸦鸭呀丫芽牙蚜崖衙涯雅哑亚讶焉咽阉烟淹盐严研蜒岩延言颜阎炎沿奄掩眼衍演艳堰燕厌砚雁唁彦焰宴谚验殃央鸯秧杨扬佯疡羊洋阳氧仰痒养样漾邀腰妖瑶�\".split(\"\");\nfor(j = 0; j != D[209].length; ++j) if(D[209][j].charCodeAt(0) !== 0xFFFD) { e[D[209][j]] = 53504 + j; d[53504 + j] = D[209][j];}\nD[210] = \"����������������������������������������������������������������褸褹褺褻褼褽褾褿襀襂襃襅襆襇襈襉襊襋襌襍襎襏襐襑襒襓襔襕襖襗襘襙襚襛襜襝襠襡襢襣襤襥襧襨襩襪襫襬襭襮襯襰襱襲襳襴襵襶襷襸襹襺襼�襽襾覀覂覄覅覇覈覉覊見覌覍覎規覐覑覒覓覔覕視覗覘覙覚覛覜覝覞覟覠覡摇尧遥窑谣姚咬舀药要耀椰噎耶爷野冶也页掖业叶曳腋夜液一壹医揖铱依伊衣颐夷遗移仪胰疑沂宜姨彝椅蚁倚已乙矣以艺抑易邑屹亿役臆逸肄疫亦裔意毅忆义益溢诣议谊译异翼翌绎茵荫因殷音阴姻吟银淫寅饮尹引隐�\".split(\"\");\nfor(j = 0; j != D[210].length; ++j) if(D[210][j].charCodeAt(0) !== 0xFFFD) { e[D[210][j]] = 53760 + j; d[53760 + j] = D[210][j];}\nD[211] = \"����������������������������������������������������������������覢覣覤覥覦覧覨覩親覫覬覭覮覯覰覱覲観覴覵覶覷覸覹覺覻覼覽覾覿觀觃觍觓觔觕觗觘觙觛觝觟觠觡觢觤觧觨觩觪觬觭觮觰觱觲觴觵觶觷觸觹觺�觻觼觽觾觿訁訂訃訄訅訆計訉訊訋訌訍討訏訐訑訒訓訔訕訖託記訙訚訛訜訝印英樱婴鹰应缨莹萤营荧蝇迎赢盈影颖硬映哟拥佣臃痈庸雍踊蛹咏泳涌永恿勇用幽优悠忧尤由邮铀犹油游酉有友右佑釉诱又幼迂淤于盂榆虞愚舆余俞逾鱼愉渝渔隅予娱雨与屿禹宇语羽玉域芋郁吁遇喻峪御愈欲狱育誉�\".split(\"\");\nfor(j = 0; j != D[211].length; ++j) if(D[211][j].charCodeAt(0) !== 0xFFFD) { e[D[211][j]] = 54016 + j; d[54016 + j] = D[211][j];}\nD[212] = \"����������������������������������������������������������������訞訟訠訡訢訣訤訥訦訧訨訩訪訫訬設訮訯訰許訲訳訴訵訶訷訸訹診註証訽訿詀詁詂詃詄詅詆詇詉詊詋詌詍詎詏詐詑詒詓詔評詖詗詘詙詚詛詜詝詞�詟詠詡詢詣詤詥試詧詨詩詪詫詬詭詮詯詰話該詳詴詵詶詷詸詺詻詼詽詾詿誀浴寓裕预豫驭鸳渊冤元垣袁原援辕园员圆猿源缘远苑愿怨院曰约越跃钥岳粤月悦阅耘云郧匀陨允运蕴酝晕韵孕匝砸杂栽哉灾宰载再在咱攒暂赞赃脏葬遭糟凿藻枣早澡蚤躁噪造皂灶燥责择则泽贼怎增憎曾赠扎喳渣札轧�\".split(\"\");\nfor(j = 0; j != D[212].length; ++j) if(D[212][j].charCodeAt(0) !== 0xFFFD) { e[D[212][j]] = 54272 + j; d[54272 + j] = D[212][j];}\nD[213] = \"����������������������������������������������������������������誁誂誃誄誅誆誇誈誋誌認誎誏誐誑誒誔誕誖誗誘誙誚誛誜誝語誟誠誡誢誣誤誥誦誧誨誩說誫説読誮誯誰誱課誳誴誵誶誷誸誹誺誻誼誽誾調諀諁諂�諃諄諅諆談諈諉諊請諌諍諎諏諐諑諒諓諔諕論諗諘諙諚諛諜諝諞諟諠諡諢諣铡闸眨栅榨咋乍炸诈摘斋宅窄债寨瞻毡詹粘沾盏斩辗崭展蘸栈占战站湛绽樟章彰漳张掌涨杖丈帐账仗胀瘴障招昭找沼赵照罩兆肇召遮折哲蛰辙者锗蔗这浙珍斟真甄砧臻贞针侦枕疹诊震振镇阵蒸挣睁征狰争怔整拯正政�\".split(\"\");\nfor(j = 0; j != D[213].length; ++j) if(D[213][j].charCodeAt(0) !== 0xFFFD) { e[D[213][j]] = 54528 + j; d[54528 + j] = D[213][j];}\nD[214] = \"����������������������������������������������������������������諤諥諦諧諨諩諪諫諬諭諮諯諰諱諲諳諴諵諶諷諸諹諺諻諼諽諾諿謀謁謂謃謄謅謆謈謉謊謋謌謍謎謏謐謑謒謓謔謕謖謗謘謙謚講謜謝謞謟謠謡謢謣�謤謥謧謨謩謪謫謬謭謮謯謰謱謲謳謴謵謶謷謸謹謺謻謼謽謾謿譀譁譂譃譄譅帧症郑证芝枝支吱蜘知肢脂汁之织职直植殖执值侄址指止趾只旨纸志挚掷至致置帜峙制智秩稚质炙痔滞治窒中盅忠钟衷终种肿重仲众舟周州洲诌粥轴肘帚咒皱宙昼骤珠株蛛朱猪诸诛逐竹烛煮拄瞩嘱主著柱助蛀贮铸筑�\".split(\"\");\nfor(j = 0; j != D[214].length; ++j) if(D[214][j].charCodeAt(0) !== 0xFFFD) { e[D[214][j]] = 54784 + j; d[54784 + j] = D[214][j];}\nD[215] = \"����������������������������������������������������������������譆譇譈證譊譋譌譍譎譏譐譑譒譓譔譕譖譗識譙譚譛譜譝譞譟譠譡譢譣譤譥譧譨譩譪譫譭譮譯議譱譲譳譴譵譶護譸譹譺譻譼譽譾譿讀讁讂讃讄讅讆�讇讈讉變讋讌讍讎讏讐讑讒讓讔讕讖讗讘讙讚讛讜讝讞讟讬讱讻诇诐诪谉谞住注祝驻抓爪拽专砖转撰赚篆桩庄装妆撞壮状椎锥追赘坠缀谆准捉拙卓桌琢茁酌啄着灼浊兹咨资姿滋淄孜紫仔籽滓子自渍字鬃棕踪宗综总纵邹走奏揍租足卒族祖诅阻组钻纂嘴醉最罪尊遵昨左佐柞做作坐座������\".split(\"\");\nfor(j = 0; j != D[215].length; ++j) if(D[215][j].charCodeAt(0) !== 0xFFFD) { e[D[215][j]] = 55040 + j; d[55040 + j] = D[215][j];}\nD[216] = \"����������������������������������������������������������������谸谹谺谻谼谽谾谿豀豂豃豄豅豈豊豋豍豎豏豐豑豒豓豔豖豗豘豙豛豜豝豞豟豠豣豤豥豦豧豨豩豬豭豮豯豰豱豲豴豵豶豷豻豼豽豾豿貀貁貃貄貆貇�貈貋貍貎貏貐貑貒貓貕貖貗貙貚貛貜貝貞貟負財貢貣貤貥貦貧貨販貪貫責貭亍丌兀丐廿卅丕亘丞鬲孬噩丨禺丿匕乇夭爻卮氐囟胤馗毓睾鼗丶亟鼐乜乩亓芈孛啬嘏仄厍厝厣厥厮靥赝匚叵匦匮匾赜卦卣刂刈刎刭刳刿剀剌剞剡剜蒯剽劂劁劐劓冂罔亻仃仉仂仨仡仫仞伛仳伢佤仵伥伧伉伫佞佧攸佚佝�\".split(\"\");\nfor(j = 0; j != D[216].length; ++j) if(D[216][j].charCodeAt(0) !== 0xFFFD) { e[D[216][j]] = 55296 + j; d[55296 + j] = D[216][j];}\nD[217] = \"����������������������������������������������������������������貮貯貰貱貲貳貴貵貶買貸貹貺費貼貽貾貿賀賁賂賃賄賅賆資賈賉賊賋賌賍賎賏賐賑賒賓賔賕賖賗賘賙賚賛賜賝賞賟賠賡賢賣賤賥賦賧賨賩質賫賬�賭賮賯賰賱賲賳賴賵賶賷賸賹賺賻購賽賾賿贀贁贂贃贄贅贆贇贈贉贊贋贌贍佟佗伲伽佶佴侑侉侃侏佾佻侪佼侬侔俦俨俪俅俚俣俜俑俟俸倩偌俳倬倏倮倭俾倜倌倥倨偾偃偕偈偎偬偻傥傧傩傺僖儆僭僬僦僮儇儋仝氽佘佥俎龠汆籴兮巽黉馘冁夔勹匍訇匐凫夙兕亠兖亳衮袤亵脔裒禀嬴蠃羸冫冱冽冼�\".split(\"\");\nfor(j = 0; j != D[217].length; ++j) if(D[217][j].charCodeAt(0) !== 0xFFFD) { e[D[217][j]] = 55552 + j; d[55552 + j] = D[217][j];}\nD[218] = \"����������������������������������������������������������������贎贏贐贑贒贓贔贕贖贗贘贙贚贛贜贠赑赒赗赟赥赨赩赪赬赮赯赱赲赸赹赺赻赼赽赾赿趀趂趃趆趇趈趉趌趍趎趏趐趒趓趕趖趗趘趙趚趛趜趝趞趠趡�趢趤趥趦趧趨趩趪趫趬趭趮趯趰趲趶趷趹趻趽跀跁跂跅跇跈跉跊跍跐跒跓跔凇冖冢冥讠讦讧讪讴讵讷诂诃诋诏诎诒诓诔诖诘诙诜诟诠诤诨诩诮诰诳诶诹诼诿谀谂谄谇谌谏谑谒谔谕谖谙谛谘谝谟谠谡谥谧谪谫谮谯谲谳谵谶卩卺阝阢阡阱阪阽阼陂陉陔陟陧陬陲陴隈隍隗隰邗邛邝邙邬邡邴邳邶邺�\".split(\"\");\nfor(j = 0; j != D[218].length; ++j) if(D[218][j].charCodeAt(0) !== 0xFFFD) { e[D[218][j]] = 55808 + j; d[55808 + j] = D[218][j];}\nD[219] = \"����������������������������������������������������������������跕跘跙跜跠跡跢跥跦跧跩跭跮跰跱跲跴跶跼跾跿踀踁踂踃踄踆踇踈踋踍踎踐踑踒踓踕踖踗踘踙踚踛踜踠踡踤踥踦踧踨踫踭踰踲踳踴踶踷踸踻踼踾�踿蹃蹅蹆蹌蹍蹎蹏蹐蹓蹔蹕蹖蹗蹘蹚蹛蹜蹝蹞蹟蹠蹡蹢蹣蹤蹥蹧蹨蹪蹫蹮蹱邸邰郏郅邾郐郄郇郓郦郢郜郗郛郫郯郾鄄鄢鄞鄣鄱鄯鄹酃酆刍奂劢劬劭劾哿勐勖勰叟燮矍廴凵凼鬯厶弁畚巯坌垩垡塾墼壅壑圩圬圪圳圹圮圯坜圻坂坩垅坫垆坼坻坨坭坶坳垭垤垌垲埏垧垴垓垠埕埘埚埙埒垸埴埯埸埤埝�\".split(\"\");\nfor(j = 0; j != D[219].length; ++j) if(D[219][j].charCodeAt(0) !== 0xFFFD) { e[D[219][j]] = 56064 + j; d[56064 + j] = D[219][j];}\nD[220] = \"����������������������������������������������������������������蹳蹵蹷蹸蹹蹺蹻蹽蹾躀躂躃躄躆躈躉躊躋躌躍躎躑躒躓躕躖躗躘躙躚躛躝躟躠躡躢躣躤躥躦躧躨躩躪躭躮躰躱躳躴躵躶躷躸躹躻躼躽躾躿軀軁軂�軃軄軅軆軇軈軉車軋軌軍軏軐軑軒軓軔軕軖軗軘軙軚軛軜軝軞軟軠軡転軣軤堋堍埽埭堀堞堙塄堠塥塬墁墉墚墀馨鼙懿艹艽艿芏芊芨芄芎芑芗芙芫芸芾芰苈苊苣芘芷芮苋苌苁芩芴芡芪芟苄苎芤苡茉苷苤茏茇苜苴苒苘茌苻苓茑茚茆茔茕苠苕茜荑荛荜茈莒茼茴茱莛荞茯荏荇荃荟荀茗荠茭茺茳荦荥�\".split(\"\");\nfor(j = 0; j != D[220].length; ++j) if(D[220][j].charCodeAt(0) !== 0xFFFD) { e[D[220][j]] = 56320 + j; d[56320 + j] = D[220][j];}\nD[221] = \"����������������������������������������������������������������軥軦軧軨軩軪軫軬軭軮軯軰軱軲軳軴軵軶軷軸軹軺軻軼軽軾軿輀輁輂較輄輅輆輇輈載輊輋輌輍輎輏輐輑輒輓輔輕輖輗輘輙輚輛輜輝輞輟輠輡輢輣�輤輥輦輧輨輩輪輫輬輭輮輯輰輱輲輳輴輵輶輷輸輹輺輻輼輽輾輿轀轁轂轃轄荨茛荩荬荪荭荮莰荸莳莴莠莪莓莜莅荼莶莩荽莸荻莘莞莨莺莼菁萁菥菘堇萘萋菝菽菖萜萸萑萆菔菟萏萃菸菹菪菅菀萦菰菡葜葑葚葙葳蒇蒈葺蒉葸萼葆葩葶蒌蒎萱葭蓁蓍蓐蓦蒽蓓蓊蒿蒺蓠蒡蒹蒴蒗蓥蓣蔌甍蔸蓰蔹蔟蔺�\".split(\"\");\nfor(j = 0; j != D[221].length; ++j) if(D[221][j].charCodeAt(0) !== 0xFFFD) { e[D[221][j]] = 56576 + j; d[56576 + j] = D[221][j];}\nD[222] = \"����������������������������������������������������������������轅轆轇轈轉轊轋轌轍轎轏轐轑轒轓轔轕轖轗轘轙轚轛轜轝轞轟轠轡轢轣轤轥轪辀辌辒辝辠辡辢辤辥辦辧辪辬辭辮辯農辳辴辵辷辸辺辻込辿迀迃迆�迉迊迋迌迍迏迒迖迗迚迠迡迣迧迬迯迱迲迴迵迶迺迻迼迾迿逇逈逌逎逓逕逘蕖蔻蓿蓼蕙蕈蕨蕤蕞蕺瞢蕃蕲蕻薤薨薇薏蕹薮薜薅薹薷薰藓藁藜藿蘧蘅蘩蘖蘼廾弈夼奁耷奕奚奘匏尢尥尬尴扌扪抟抻拊拚拗拮挢拶挹捋捃掭揶捱捺掎掴捭掬掊捩掮掼揲揸揠揿揄揞揎摒揆掾摅摁搋搛搠搌搦搡摞撄摭撖�\".split(\"\");\nfor(j = 0; j != D[222].length; ++j) if(D[222][j].charCodeAt(0) !== 0xFFFD) { e[D[222][j]] = 56832 + j; d[56832 + j] = D[222][j];}\nD[223] = \"����������������������������������������������������������������這逜連逤逥逧逨逩逪逫逬逰週進逳逴逷逹逺逽逿遀遃遅遆遈遉遊運遌過達違遖遙遚遜遝遞遟遠遡遤遦遧適遪遫遬遯遰遱遲遳遶遷選遹遺遻遼遾邁�還邅邆邇邉邊邌邍邎邏邐邒邔邖邘邚邜邞邟邠邤邥邧邨邩邫邭邲邷邼邽邿郀摺撷撸撙撺擀擐擗擤擢攉攥攮弋忒甙弑卟叱叽叩叨叻吒吖吆呋呒呓呔呖呃吡呗呙吣吲咂咔呷呱呤咚咛咄呶呦咝哐咭哂咴哒咧咦哓哔呲咣哕咻咿哌哙哚哜咩咪咤哝哏哞唛哧唠哽唔哳唢唣唏唑唧唪啧喏喵啉啭啁啕唿啐唼�\".split(\"\");\nfor(j = 0; j != D[223].length; ++j) if(D[223][j].charCodeAt(0) !== 0xFFFD) { e[D[223][j]] = 57088 + j; d[57088 + j] = D[223][j];}\nD[224] = \"����������������������������������������������������������������郂郃郆郈郉郋郌郍郒郔郕郖郘郙郚郞郟郠郣郤郥郩郪郬郮郰郱郲郳郵郶郷郹郺郻郼郿鄀鄁鄃鄅鄆鄇鄈鄉鄊鄋鄌鄍鄎鄏鄐鄑鄒鄓鄔鄕鄖鄗鄘鄚鄛鄜�鄝鄟鄠鄡鄤鄥鄦鄧鄨鄩鄪鄫鄬鄭鄮鄰鄲鄳鄴鄵鄶鄷鄸鄺鄻鄼鄽鄾鄿酀酁酂酄唷啖啵啶啷唳唰啜喋嗒喃喱喹喈喁喟啾嗖喑啻嗟喽喾喔喙嗪嗷嗉嘟嗑嗫嗬嗔嗦嗝嗄嗯嗥嗲嗳嗌嗍嗨嗵嗤辔嘞嘈嘌嘁嘤嘣嗾嘀嘧嘭噘嘹噗嘬噍噢噙噜噌噔嚆噤噱噫噻噼嚅嚓嚯囔囗囝囡囵囫囹囿圄圊圉圜帏帙帔帑帱帻帼�\".split(\"\");\nfor(j = 0; j != D[224].length; ++j) if(D[224][j].charCodeAt(0) !== 0xFFFD) { e[D[224][j]] = 57344 + j; d[57344 + j] = D[224][j];}\nD[225] = \"����������������������������������������������������������������酅酇酈酑酓酔酕酖酘酙酛酜酟酠酦酧酨酫酭酳酺酻酼醀醁醂醃醄醆醈醊醎醏醓醔醕醖醗醘醙醜醝醞醟醠醡醤醥醦醧醨醩醫醬醰醱醲醳醶醷醸醹醻�醼醽醾醿釀釁釂釃釄釅釆釈釋釐釒釓釔釕釖釗釘釙釚釛針釞釟釠釡釢釣釤釥帷幄幔幛幞幡岌屺岍岐岖岈岘岙岑岚岜岵岢岽岬岫岱岣峁岷峄峒峤峋峥崂崃崧崦崮崤崞崆崛嵘崾崴崽嵬嵛嵯嵝嵫嵋嵊嵩嵴嶂嶙嶝豳嶷巅彳彷徂徇徉後徕徙徜徨徭徵徼衢彡犭犰犴犷犸狃狁狎狍狒狨狯狩狲狴狷猁狳猃狺�\".split(\"\");\nfor(j = 0; j != D[225].length; ++j) if(D[225][j].charCodeAt(0) !== 0xFFFD) { e[D[225][j]] = 57600 + j; d[57600 + j] = D[225][j];}\nD[226] = \"����������������������������������������������������������������釦釧釨釩釪釫釬釭釮釯釰釱釲釳釴釵釶釷釸釹釺釻釼釽釾釿鈀鈁鈂鈃鈄鈅鈆鈇鈈鈉鈊鈋鈌鈍鈎鈏鈐鈑鈒鈓鈔鈕鈖鈗鈘鈙鈚鈛鈜鈝鈞鈟鈠鈡鈢鈣鈤�鈥鈦鈧鈨鈩鈪鈫鈬鈭鈮鈯鈰鈱鈲鈳鈴鈵鈶鈷鈸鈹鈺鈻鈼鈽鈾鈿鉀鉁鉂鉃鉄鉅狻猗猓猡猊猞猝猕猢猹猥猬猸猱獐獍獗獠獬獯獾舛夥飧夤夂饣饧饨饩饪饫饬饴饷饽馀馄馇馊馍馐馑馓馔馕庀庑庋庖庥庠庹庵庾庳赓廒廑廛廨廪膺忄忉忖忏怃忮怄忡忤忾怅怆忪忭忸怙怵怦怛怏怍怩怫怊怿怡恸恹恻恺恂�\".split(\"\");\nfor(j = 0; j != D[226].length; ++j) if(D[226][j].charCodeAt(0) !== 0xFFFD) { e[D[226][j]] = 57856 + j; d[57856 + j] = D[226][j];}\nD[227] = \"����������������������������������������������������������������鉆鉇鉈鉉鉊鉋鉌鉍鉎鉏鉐鉑鉒鉓鉔鉕鉖鉗鉘鉙鉚鉛鉜鉝鉞鉟鉠鉡鉢鉣鉤鉥鉦鉧鉨鉩鉪鉫鉬鉭鉮鉯鉰鉱鉲鉳鉵鉶鉷鉸鉹鉺鉻鉼鉽鉾鉿銀銁銂銃銄銅�銆銇銈銉銊銋銌銍銏銐銑銒銓銔銕銖銗銘銙銚銛銜銝銞銟銠銡銢銣銤銥銦銧恪恽悖悚悭悝悃悒悌悛惬悻悱惝惘惆惚悴愠愦愕愣惴愀愎愫慊慵憬憔憧憷懔懵忝隳闩闫闱闳闵闶闼闾阃阄阆阈阊阋阌阍阏阒阕阖阗阙阚丬爿戕氵汔汜汊沣沅沐沔沌汨汩汴汶沆沩泐泔沭泷泸泱泗沲泠泖泺泫泮沱泓泯泾�\".split(\"\");\nfor(j = 0; j != D[227].length; ++j) if(D[227][j].charCodeAt(0) !== 0xFFFD) { e[D[227][j]] = 58112 + j; d[58112 + j] = D[227][j];}\nD[228] = \"����������������������������������������������������������������銨銩銪銫銬銭銯銰銱銲銳銴銵銶銷銸銹銺銻銼銽銾銿鋀鋁鋂鋃鋄鋅鋆鋇鋉鋊鋋鋌鋍鋎鋏鋐鋑鋒鋓鋔鋕鋖鋗鋘鋙鋚鋛鋜鋝鋞鋟鋠鋡鋢鋣鋤鋥鋦鋧鋨�鋩鋪鋫鋬鋭鋮鋯鋰鋱鋲鋳鋴鋵鋶鋷鋸鋹鋺鋻鋼鋽鋾鋿錀錁錂錃錄錅錆錇錈錉洹洧洌浃浈洇洄洙洎洫浍洮洵洚浏浒浔洳涑浯涞涠浞涓涔浜浠浼浣渚淇淅淞渎涿淠渑淦淝淙渖涫渌涮渫湮湎湫溲湟溆湓湔渲渥湄滟溱溘滠漭滢溥溧溽溻溷滗溴滏溏滂溟潢潆潇漤漕滹漯漶潋潴漪漉漩澉澍澌潸潲潼潺濑�\".split(\"\");\nfor(j = 0; j != D[228].length; ++j) if(D[228][j].charCodeAt(0) !== 0xFFFD) { e[D[228][j]] = 58368 + j; d[58368 + j] = D[228][j];}\nD[229] = \"����������������������������������������������������������������錊錋錌錍錎錏錐錑錒錓錔錕錖錗錘錙錚錛錜錝錞錟錠錡錢錣錤錥錦錧錨錩錪錫錬錭錮錯錰錱録錳錴錵錶錷錸錹錺錻錼錽錿鍀鍁鍂鍃鍄鍅鍆鍇鍈鍉�鍊鍋鍌鍍鍎鍏鍐鍑鍒鍓鍔鍕鍖鍗鍘鍙鍚鍛鍜鍝鍞鍟鍠鍡鍢鍣鍤鍥鍦鍧鍨鍩鍫濉澧澹澶濂濡濮濞濠濯瀚瀣瀛瀹瀵灏灞宀宄宕宓宥宸甯骞搴寤寮褰寰蹇謇辶迓迕迥迮迤迩迦迳迨逅逄逋逦逑逍逖逡逵逶逭逯遄遑遒遐遨遘遢遛暹遴遽邂邈邃邋彐彗彖彘尻咫屐屙孱屣屦羼弪弩弭艴弼鬻屮妁妃妍妩妪妣�\".split(\"\");\nfor(j = 0; j != D[229].length; ++j) if(D[229][j].charCodeAt(0) !== 0xFFFD) { e[D[229][j]] = 58624 + j; d[58624 + j] = D[229][j];}\nD[230] = \"����������������������������������������������������������������鍬鍭鍮鍯鍰鍱鍲鍳鍴鍵鍶鍷鍸鍹鍺鍻鍼鍽鍾鍿鎀鎁鎂鎃鎄鎅鎆鎇鎈鎉鎊鎋鎌鎍鎎鎐鎑鎒鎓鎔鎕鎖鎗鎘鎙鎚鎛鎜鎝鎞鎟鎠鎡鎢鎣鎤鎥鎦鎧鎨鎩鎪鎫�鎬鎭鎮鎯鎰鎱鎲鎳鎴鎵鎶鎷鎸鎹鎺鎻鎼鎽鎾鎿鏀鏁鏂鏃鏄鏅鏆鏇鏈鏉鏋鏌鏍妗姊妫妞妤姒妲妯姗妾娅娆姝娈姣姘姹娌娉娲娴娑娣娓婀婧婊婕娼婢婵胬媪媛婷婺媾嫫媲嫒嫔媸嫠嫣嫱嫖嫦嫘嫜嬉嬗嬖嬲嬷孀尕尜孚孥孳孑孓孢驵驷驸驺驿驽骀骁骅骈骊骐骒骓骖骘骛骜骝骟骠骢骣骥骧纟纡纣纥纨纩�\".split(\"\");\nfor(j = 0; j != D[230].length; ++j) if(D[230][j].charCodeAt(0) !== 0xFFFD) { e[D[230][j]] = 58880 + j; d[58880 + j] = D[230][j];}\nD[231] = \"����������������������������������������������������������������鏎鏏鏐鏑鏒鏓鏔鏕鏗鏘鏙鏚鏛鏜鏝鏞鏟鏠鏡鏢鏣鏤鏥鏦鏧鏨鏩鏪鏫鏬鏭鏮鏯鏰鏱鏲鏳鏴鏵鏶鏷鏸鏹鏺鏻鏼鏽鏾鏿鐀鐁鐂鐃鐄鐅鐆鐇鐈鐉鐊鐋鐌鐍�鐎鐏鐐鐑鐒鐓鐔鐕鐖鐗鐘鐙鐚鐛鐜鐝鐞鐟鐠鐡鐢鐣鐤鐥鐦鐧鐨鐩鐪鐫鐬鐭鐮纭纰纾绀绁绂绉绋绌绐绔绗绛绠绡绨绫绮绯绱绲缍绶绺绻绾缁缂缃缇缈缋缌缏缑缒缗缙缜缛缟缡缢缣缤缥缦缧缪缫缬缭缯缰缱缲缳缵幺畿巛甾邕玎玑玮玢玟珏珂珑玷玳珀珉珈珥珙顼琊珩珧珞玺珲琏琪瑛琦琥琨琰琮琬�\".split(\"\");\nfor(j = 0; j != D[231].length; ++j) if(D[231][j].charCodeAt(0) !== 0xFFFD) { e[D[231][j]] = 59136 + j; d[59136 + j] = D[231][j];}\nD[232] = \"����������������������������������������������������������������鐯鐰鐱鐲鐳鐴鐵鐶鐷鐸鐹鐺鐻鐼鐽鐿鑀鑁鑂鑃鑄鑅鑆鑇鑈鑉鑊鑋鑌鑍鑎鑏鑐鑑鑒鑓鑔鑕鑖鑗鑘鑙鑚鑛鑜鑝鑞鑟鑠鑡鑢鑣鑤鑥鑦鑧鑨鑩鑪鑬鑭鑮鑯�鑰鑱鑲鑳鑴鑵鑶鑷鑸鑹鑺鑻鑼鑽鑾鑿钀钁钂钃钄钑钖钘铇铏铓铔铚铦铻锜锠琛琚瑁瑜瑗瑕瑙瑷瑭瑾璜璎璀璁璇璋璞璨璩璐璧瓒璺韪韫韬杌杓杞杈杩枥枇杪杳枘枧杵枨枞枭枋杷杼柰栉柘栊柩枰栌柙枵柚枳柝栀柃枸柢栎柁柽栲栳桠桡桎桢桄桤梃栝桕桦桁桧桀栾桊桉栩梵梏桴桷梓桫棂楮棼椟椠棹�\".split(\"\");\nfor(j = 0; j != D[232].length; ++j) if(D[232][j].charCodeAt(0) !== 0xFFFD) { e[D[232][j]] = 59392 + j; d[59392 + j] = D[232][j];}\nD[233] = \"����������������������������������������������������������������锧锳锽镃镈镋镕镚镠镮镴镵長镸镹镺镻镼镽镾門閁閂閃閄閅閆閇閈閉閊開閌閍閎閏閐閑閒間閔閕閖閗閘閙閚閛閜閝閞閟閠閡関閣閤閥閦閧閨閩閪�閫閬閭閮閯閰閱閲閳閴閵閶閷閸閹閺閻閼閽閾閿闀闁闂闃闄闅闆闇闈闉闊闋椤棰椋椁楗棣椐楱椹楠楂楝榄楫榀榘楸椴槌榇榈槎榉楦楣楹榛榧榻榫榭槔榱槁槊槟榕槠榍槿樯槭樗樘橥槲橄樾檠橐橛樵檎橹樽樨橘橼檑檐檩檗檫猷獒殁殂殇殄殒殓殍殚殛殡殪轫轭轱轲轳轵轶轸轷轹轺轼轾辁辂辄辇辋�\".split(\"\");\nfor(j = 0; j != D[233].length; ++j) if(D[233][j].charCodeAt(0) !== 0xFFFD) { e[D[233][j]] = 59648 + j; d[59648 + j] = D[233][j];}\nD[234] = \"����������������������������������������������������������������闌闍闎闏闐闑闒闓闔闕闖闗闘闙闚闛關闝闞闟闠闡闢闣闤闥闦闧闬闿阇阓阘阛阞阠阣阤阥阦阧阨阩阫阬阭阯阰阷阸阹阺阾陁陃陊陎陏陑陒陓陖陗�陘陙陚陜陝陞陠陣陥陦陫陭陮陯陰陱陳陸陹険陻陼陽陾陿隀隁隂隃隄隇隉隊辍辎辏辘辚軎戋戗戛戟戢戡戥戤戬臧瓯瓴瓿甏甑甓攴旮旯旰昊昙杲昃昕昀炅曷昝昴昱昶昵耆晟晔晁晏晖晡晗晷暄暌暧暝暾曛曜曦曩贲贳贶贻贽赀赅赆赈赉赇赍赕赙觇觊觋觌觎觏觐觑牮犟牝牦牯牾牿犄犋犍犏犒挈挲掰�\".split(\"\");\nfor(j = 0; j != D[234].length; ++j) if(D[234][j].charCodeAt(0) !== 0xFFFD) { e[D[234][j]] = 59904 + j; d[59904 + j] = D[234][j];}\nD[235] = \"����������������������������������������������������������������隌階隑隒隓隕隖隚際隝隞隟隠隡隢隣隤隥隦隨隩險隫隬隭隮隯隱隲隴隵隷隸隺隻隿雂雃雈雊雋雐雑雓雔雖雗雘雙雚雛雜雝雞雟雡離難雤雥雦雧雫�雬雭雮雰雱雲雴雵雸雺電雼雽雿霂霃霅霊霋霌霐霑霒霔霕霗霘霙霚霛霝霟霠搿擘耄毪毳毽毵毹氅氇氆氍氕氘氙氚氡氩氤氪氲攵敕敫牍牒牖爰虢刖肟肜肓肼朊肽肱肫肭肴肷胧胨胩胪胛胂胄胙胍胗朐胝胫胱胴胭脍脎胲胼朕脒豚脶脞脬脘脲腈腌腓腴腙腚腱腠腩腼腽腭腧塍媵膈膂膑滕膣膪臌朦臊膻�\".split(\"\");\nfor(j = 0; j != D[235].length; ++j) if(D[235][j].charCodeAt(0) !== 0xFFFD) { e[D[235][j]] = 60160 + j; d[60160 + j] = D[235][j];}\nD[236] = \"����������������������������������������������������������������霡霢霣霤霥霦霧霨霩霫霬霮霯霱霳霴霵霶霷霺霻霼霽霿靀靁靂靃靄靅靆靇靈靉靊靋靌靍靎靏靐靑靔靕靗靘靚靜靝靟靣靤靦靧靨靪靫靬靭靮靯靰靱�靲靵靷靸靹靺靻靽靾靿鞀鞁鞂鞃鞄鞆鞇鞈鞉鞊鞌鞎鞏鞐鞓鞕鞖鞗鞙鞚鞛鞜鞝臁膦欤欷欹歃歆歙飑飒飓飕飙飚殳彀毂觳斐齑斓於旆旄旃旌旎旒旖炀炜炖炝炻烀炷炫炱烨烊焐焓焖焯焱煳煜煨煅煲煊煸煺熘熳熵熨熠燠燔燧燹爝爨灬焘煦熹戾戽扃扈扉礻祀祆祉祛祜祓祚祢祗祠祯祧祺禅禊禚禧禳忑忐�\".split(\"\");\nfor(j = 0; j != D[236].length; ++j) if(D[236][j].charCodeAt(0) !== 0xFFFD) { e[D[236][j]] = 60416 + j; d[60416 + j] = D[236][j];}\nD[237] = \"����������������������������������������������������������������鞞鞟鞡鞢鞤鞥鞦鞧鞨鞩鞪鞬鞮鞰鞱鞳鞵鞶鞷鞸鞹鞺鞻鞼鞽鞾鞿韀韁韂韃韄韅韆韇韈韉韊韋韌韍韎韏韐韑韒韓韔韕韖韗韘韙韚韛韜韝韞韟韠韡韢韣�韤韥韨韮韯韰韱韲韴韷韸韹韺韻韼韽韾響頀頁頂頃頄項順頇須頉頊頋頌頍頎怼恝恚恧恁恙恣悫愆愍慝憩憝懋懑戆肀聿沓泶淼矶矸砀砉砗砘砑斫砭砜砝砹砺砻砟砼砥砬砣砩硎硭硖硗砦硐硇硌硪碛碓碚碇碜碡碣碲碹碥磔磙磉磬磲礅磴礓礤礞礴龛黹黻黼盱眄眍盹眇眈眚眢眙眭眦眵眸睐睑睇睃睚睨�\".split(\"\");\nfor(j = 0; j != D[237].length; ++j) if(D[237][j].charCodeAt(0) !== 0xFFFD) { e[D[237][j]] = 60672 + j; d[60672 + j] = D[237][j];}\nD[238] = \"����������������������������������������������������������������頏預頑頒頓頔頕頖頗領頙頚頛頜頝頞頟頠頡頢頣頤頥頦頧頨頩頪頫頬頭頮頯頰頱頲頳頴頵頶頷頸頹頺頻頼頽頾頿顀顁顂顃顄顅顆顇顈顉顊顋題額�顎顏顐顑顒顓顔顕顖顗願顙顚顛顜顝類顟顠顡顢顣顤顥顦顧顨顩顪顫顬顭顮睢睥睿瞍睽瞀瞌瞑瞟瞠瞰瞵瞽町畀畎畋畈畛畲畹疃罘罡罟詈罨罴罱罹羁罾盍盥蠲钅钆钇钋钊钌钍钏钐钔钗钕钚钛钜钣钤钫钪钭钬钯钰钲钴钶钷钸钹钺钼钽钿铄铈铉铊铋铌铍铎铐铑铒铕铖铗铙铘铛铞铟铠铢铤铥铧铨铪�\".split(\"\");\nfor(j = 0; j != D[238].length; ++j) if(D[238][j].charCodeAt(0) !== 0xFFFD) { e[D[238][j]] = 60928 + j; d[60928 + j] = D[238][j];}\nD[239] = \"����������������������������������������������������������������顯顰顱顲顳顴颋颎颒颕颙颣風颩颪颫颬颭颮颯颰颱颲颳颴颵颶颷颸颹颺颻颼颽颾颿飀飁飂飃飄飅飆飇飈飉飊飋飌飍飏飐飔飖飗飛飜飝飠飡飢飣飤�飥飦飩飪飫飬飭飮飯飰飱飲飳飴飵飶飷飸飹飺飻飼飽飾飿餀餁餂餃餄餅餆餇铩铫铮铯铳铴铵铷铹铼铽铿锃锂锆锇锉锊锍锎锏锒锓锔锕锖锘锛锝锞锟锢锪锫锩锬锱锲锴锶锷锸锼锾锿镂锵镄镅镆镉镌镎镏镒镓镔镖镗镘镙镛镞镟镝镡镢镤镥镦镧镨镩镪镫镬镯镱镲镳锺矧矬雉秕秭秣秫稆嵇稃稂稞稔�\".split(\"\");\nfor(j = 0; j != D[239].length; ++j) if(D[239][j].charCodeAt(0) !== 0xFFFD) { e[D[239][j]] = 61184 + j; d[61184 + j] = D[239][j];}\nD[240] = \"����������������������������������������������������������������餈餉養餋餌餎餏餑餒餓餔餕餖餗餘餙餚餛餜餝餞餟餠餡餢餣餤餥餦餧館餩餪餫餬餭餯餰餱餲餳餴餵餶餷餸餹餺餻餼餽餾餿饀饁饂饃饄饅饆饇饈饉�饊饋饌饍饎饏饐饑饒饓饖饗饘饙饚饛饜饝饞饟饠饡饢饤饦饳饸饹饻饾馂馃馉稹稷穑黏馥穰皈皎皓皙皤瓞瓠甬鸠鸢鸨鸩鸪鸫鸬鸲鸱鸶鸸鸷鸹鸺鸾鹁鹂鹄鹆鹇鹈鹉鹋鹌鹎鹑鹕鹗鹚鹛鹜鹞鹣鹦鹧鹨鹩鹪鹫鹬鹱鹭鹳疒疔疖疠疝疬疣疳疴疸痄疱疰痃痂痖痍痣痨痦痤痫痧瘃痱痼痿瘐瘀瘅瘌瘗瘊瘥瘘瘕瘙�\".split(\"\");\nfor(j = 0; j != D[240].length; ++j) if(D[240][j].charCodeAt(0) !== 0xFFFD) { e[D[240][j]] = 61440 + j; d[61440 + j] = D[240][j];}\nD[241] = \"����������������������������������������������������������������馌馎馚馛馜馝馞馟馠馡馢馣馤馦馧馩馪馫馬馭馮馯馰馱馲馳馴馵馶馷馸馹馺馻馼馽馾馿駀駁駂駃駄駅駆駇駈駉駊駋駌駍駎駏駐駑駒駓駔駕駖駗駘�駙駚駛駜駝駞駟駠駡駢駣駤駥駦駧駨駩駪駫駬駭駮駯駰駱駲駳駴駵駶駷駸駹瘛瘼瘢瘠癀瘭瘰瘿瘵癃瘾瘳癍癞癔癜癖癫癯翊竦穸穹窀窆窈窕窦窠窬窨窭窳衤衩衲衽衿袂袢裆袷袼裉裢裎裣裥裱褚裼裨裾裰褡褙褓褛褊褴褫褶襁襦襻疋胥皲皴矜耒耔耖耜耠耢耥耦耧耩耨耱耋耵聃聆聍聒聩聱覃顸颀颃�\".split(\"\");\nfor(j = 0; j != D[241].length; ++j) if(D[241][j].charCodeAt(0) !== 0xFFFD) { e[D[241][j]] = 61696 + j; d[61696 + j] = D[241][j];}\nD[242] = \"����������������������������������������������������������������駺駻駼駽駾駿騀騁騂騃騄騅騆騇騈騉騊騋騌騍騎騏騐騑騒験騔騕騖騗騘騙騚騛騜騝騞騟騠騡騢騣騤騥騦騧騨騩騪騫騬騭騮騯騰騱騲騳騴騵騶騷騸�騹騺騻騼騽騾騿驀驁驂驃驄驅驆驇驈驉驊驋驌驍驎驏驐驑驒驓驔驕驖驗驘驙颉颌颍颏颔颚颛颞颟颡颢颥颦虍虔虬虮虿虺虼虻蚨蚍蚋蚬蚝蚧蚣蚪蚓蚩蚶蛄蚵蛎蚰蚺蚱蚯蛉蛏蚴蛩蛱蛲蛭蛳蛐蜓蛞蛴蛟蛘蛑蜃蜇蛸蜈蜊蜍蜉蜣蜻蜞蜥蜮蜚蜾蝈蜴蜱蜩蜷蜿螂蜢蝽蝾蝻蝠蝰蝌蝮螋蝓蝣蝼蝤蝙蝥螓螯螨蟒�\".split(\"\");\nfor(j = 0; j != D[242].length; ++j) if(D[242][j].charCodeAt(0) !== 0xFFFD) { e[D[242][j]] = 61952 + j; d[61952 + j] = D[242][j];}\nD[243] = \"����������������������������������������������������������������驚驛驜驝驞驟驠驡驢驣驤驥驦驧驨驩驪驫驲骃骉骍骎骔骕骙骦骩骪骫骬骭骮骯骲骳骴骵骹骻骽骾骿髃髄髆髇髈髉髊髍髎髏髐髒體髕髖髗髙髚髛髜�髝髞髠髢髣髤髥髧髨髩髪髬髮髰髱髲髳髴髵髶髷髸髺髼髽髾髿鬀鬁鬂鬄鬅鬆蟆螈螅螭螗螃螫蟥螬螵螳蟋蟓螽蟑蟀蟊蟛蟪蟠蟮蠖蠓蟾蠊蠛蠡蠹蠼缶罂罄罅舐竺竽笈笃笄笕笊笫笏筇笸笪笙笮笱笠笥笤笳笾笞筘筚筅筵筌筝筠筮筻筢筲筱箐箦箧箸箬箝箨箅箪箜箢箫箴篑篁篌篝篚篥篦篪簌篾篼簏簖簋�\".split(\"\");\nfor(j = 0; j != D[243].length; ++j) if(D[243][j].charCodeAt(0) !== 0xFFFD) { e[D[243][j]] = 62208 + j; d[62208 + j] = D[243][j];}\nD[244] = \"����������������������������������������������������������������鬇鬉鬊鬋鬌鬍鬎鬐鬑鬒鬔鬕鬖鬗鬘鬙鬚鬛鬜鬝鬞鬠鬡鬢鬤鬥鬦鬧鬨鬩鬪鬫鬬鬭鬮鬰鬱鬳鬴鬵鬶鬷鬸鬹鬺鬽鬾鬿魀魆魊魋魌魎魐魒魓魕魖魗魘魙魚�魛魜魝魞魟魠魡魢魣魤魥魦魧魨魩魪魫魬魭魮魯魰魱魲魳魴魵魶魷魸魹魺魻簟簪簦簸籁籀臾舁舂舄臬衄舡舢舣舭舯舨舫舸舻舳舴舾艄艉艋艏艚艟艨衾袅袈裘裟襞羝羟羧羯羰羲籼敉粑粝粜粞粢粲粼粽糁糇糌糍糈糅糗糨艮暨羿翎翕翥翡翦翩翮翳糸絷綦綮繇纛麸麴赳趄趔趑趱赧赭豇豉酊酐酎酏酤�\".split(\"\");\nfor(j = 0; j != D[244].length; ++j) if(D[244][j].charCodeAt(0) !== 0xFFFD) { e[D[244][j]] = 62464 + j; d[62464 + j] = D[244][j];}\nD[245] = \"����������������������������������������������������������������魼魽魾魿鮀鮁鮂鮃鮄鮅鮆鮇鮈鮉鮊鮋鮌鮍鮎鮏鮐鮑鮒鮓鮔鮕鮖鮗鮘鮙鮚鮛鮜鮝鮞鮟鮠鮡鮢鮣鮤鮥鮦鮧鮨鮩鮪鮫鮬鮭鮮鮯鮰鮱鮲鮳鮴鮵鮶鮷鮸鮹鮺�鮻鮼鮽鮾鮿鯀鯁鯂鯃鯄鯅鯆鯇鯈鯉鯊鯋鯌鯍鯎鯏鯐鯑鯒鯓鯔鯕鯖鯗鯘鯙鯚鯛酢酡酰酩酯酽酾酲酴酹醌醅醐醍醑醢醣醪醭醮醯醵醴醺豕鹾趸跫踅蹙蹩趵趿趼趺跄跖跗跚跞跎跏跛跆跬跷跸跣跹跻跤踉跽踔踝踟踬踮踣踯踺蹀踹踵踽踱蹉蹁蹂蹑蹒蹊蹰蹶蹼蹯蹴躅躏躔躐躜躞豸貂貊貅貘貔斛觖觞觚觜�\".split(\"\");\nfor(j = 0; j != D[245].length; ++j) if(D[245][j].charCodeAt(0) !== 0xFFFD) { e[D[245][j]] = 62720 + j; d[62720 + j] = D[245][j];}\nD[246] = \"����������������������������������������������������������������鯜鯝鯞鯟鯠鯡鯢鯣鯤鯥鯦鯧鯨鯩鯪鯫鯬鯭鯮鯯鯰鯱鯲鯳鯴鯵鯶鯷鯸鯹鯺鯻鯼鯽鯾鯿鰀鰁鰂鰃鰄鰅鰆鰇鰈鰉鰊鰋鰌鰍鰎鰏鰐鰑鰒鰓鰔鰕鰖鰗鰘鰙鰚�鰛鰜鰝鰞鰟鰠鰡鰢鰣鰤鰥鰦鰧鰨鰩鰪鰫鰬鰭鰮鰯鰰鰱鰲鰳鰴鰵鰶鰷鰸鰹鰺鰻觥觫觯訾謦靓雩雳雯霆霁霈霏霎霪霭霰霾龀龃龅龆龇龈龉龊龌黾鼋鼍隹隼隽雎雒瞿雠銎銮鋈錾鍪鏊鎏鐾鑫鱿鲂鲅鲆鲇鲈稣鲋鲎鲐鲑鲒鲔鲕鲚鲛鲞鲟鲠鲡鲢鲣鲥鲦鲧鲨鲩鲫鲭鲮鲰鲱鲲鲳鲴鲵鲶鲷鲺鲻鲼鲽鳄鳅鳆鳇鳊鳋�\".split(\"\");\nfor(j = 0; j != D[246].length; ++j) if(D[246][j].charCodeAt(0) !== 0xFFFD) { e[D[246][j]] = 62976 + j; d[62976 + j] = D[246][j];}\nD[247] = \"����������������������������������������������������������������鰼鰽鰾鰿鱀鱁鱂鱃鱄鱅鱆鱇鱈鱉鱊鱋鱌鱍鱎鱏鱐鱑鱒鱓鱔鱕鱖鱗鱘鱙鱚鱛鱜鱝鱞鱟鱠鱡鱢鱣鱤鱥鱦鱧鱨鱩鱪鱫鱬鱭鱮鱯鱰鱱鱲鱳鱴鱵鱶鱷鱸鱹鱺�鱻鱽鱾鲀鲃鲄鲉鲊鲌鲏鲓鲖鲗鲘鲙鲝鲪鲬鲯鲹鲾鲿鳀鳁鳂鳈鳉鳑鳒鳚鳛鳠鳡鳌鳍鳎鳏鳐鳓鳔鳕鳗鳘鳙鳜鳝鳟鳢靼鞅鞑鞒鞔鞯鞫鞣鞲鞴骱骰骷鹘骶骺骼髁髀髅髂髋髌髑魅魃魇魉魈魍魑飨餍餮饕饔髟髡髦髯髫髻髭髹鬈鬏鬓鬟鬣麽麾縻麂麇麈麋麒鏖麝麟黛黜黝黠黟黢黩黧黥黪黯鼢鼬鼯鼹鼷鼽鼾齄�\".split(\"\");\nfor(j = 0; j != D[247].length; ++j) if(D[247][j].charCodeAt(0) !== 0xFFFD) { e[D[247][j]] = 63232 + j; d[63232 + j] = D[247][j];}\nD[248] = \"����������������������������������������������������������������鳣鳤鳥鳦鳧鳨鳩鳪鳫鳬鳭鳮鳯鳰鳱鳲鳳鳴鳵鳶鳷鳸鳹鳺鳻鳼鳽鳾鳿鴀鴁鴂鴃鴄鴅鴆鴇鴈鴉鴊鴋鴌鴍鴎鴏鴐鴑鴒鴓鴔鴕鴖鴗鴘鴙鴚鴛鴜鴝鴞鴟鴠鴡�鴢鴣鴤鴥鴦鴧鴨鴩鴪鴫鴬鴭鴮鴯鴰鴱鴲鴳鴴鴵鴶鴷鴸鴹鴺鴻鴼鴽鴾鴿鵀鵁鵂�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[248].length; ++j) if(D[248][j].charCodeAt(0) !== 0xFFFD) { e[D[248][j]] = 63488 + j; d[63488 + j] = D[248][j];}\nD[249] = \"����������������������������������������������������������������鵃鵄鵅鵆鵇鵈鵉鵊鵋鵌鵍鵎鵏鵐鵑鵒鵓鵔鵕鵖鵗鵘鵙鵚鵛鵜鵝鵞鵟鵠鵡鵢鵣鵤鵥鵦鵧鵨鵩鵪鵫鵬鵭鵮鵯鵰鵱鵲鵳鵴鵵鵶鵷鵸鵹鵺鵻鵼鵽鵾鵿鶀鶁�鶂鶃鶄鶅鶆鶇鶈鶉鶊鶋鶌鶍鶎鶏鶐鶑鶒鶓鶔鶕鶖鶗鶘鶙鶚鶛鶜鶝鶞鶟鶠鶡鶢�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[249].length; ++j) if(D[249][j].charCodeAt(0) !== 0xFFFD) { e[D[249][j]] = 63744 + j; d[63744 + j] = D[249][j];}\nD[250] = \"����������������������������������������������������������������鶣鶤鶥鶦鶧鶨鶩鶪鶫鶬鶭鶮鶯鶰鶱鶲鶳鶴鶵鶶鶷鶸鶹鶺鶻鶼鶽鶾鶿鷀鷁鷂鷃鷄鷅鷆鷇鷈鷉鷊鷋鷌鷍鷎鷏鷐鷑鷒鷓鷔鷕鷖鷗鷘鷙鷚鷛鷜鷝鷞鷟鷠鷡�鷢鷣鷤鷥鷦鷧鷨鷩鷪鷫鷬鷭鷮鷯鷰鷱鷲鷳鷴鷵鷶鷷鷸鷹鷺鷻鷼鷽鷾鷿鸀鸁鸂�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[250].length; ++j) if(D[250][j].charCodeAt(0) !== 0xFFFD) { e[D[250][j]] = 64000 + j; d[64000 + j] = D[250][j];}\nD[251] = \"����������������������������������������������������������������鸃鸄鸅鸆鸇鸈鸉鸊鸋鸌鸍鸎鸏鸐鸑鸒鸓鸔鸕鸖鸗鸘鸙鸚鸛鸜鸝鸞鸤鸧鸮鸰鸴鸻鸼鹀鹍鹐鹒鹓鹔鹖鹙鹝鹟鹠鹡鹢鹥鹮鹯鹲鹴鹵鹶鹷鹸鹹鹺鹻鹼鹽麀�麁麃麄麅麆麉麊麌麍麎麏麐麑麔麕麖麗麘麙麚麛麜麞麠麡麢麣麤麥麧麨麩麪�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[251].length; ++j) if(D[251][j].charCodeAt(0) !== 0xFFFD) { e[D[251][j]] = 64256 + j; d[64256 + j] = D[251][j];}\nD[252] = \"����������������������������������������������������������������麫麬麭麮麯麰麱麲麳麵麶麷麹麺麼麿黀黁黂黃黅黆黇黈黊黋黌黐黒黓黕黖黗黙黚點黡黣黤黦黨黫黬黭黮黰黱黲黳黴黵黶黷黸黺黽黿鼀鼁鼂鼃鼄鼅�鼆鼇鼈鼉鼊鼌鼏鼑鼒鼔鼕鼖鼘鼚鼛鼜鼝鼞鼟鼡鼣鼤鼥鼦鼧鼨鼩鼪鼫鼭鼮鼰鼱�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[252].length; ++j) if(D[252][j].charCodeAt(0) !== 0xFFFD) { e[D[252][j]] = 64512 + j; d[64512 + j] = D[252][j];}\nD[253] = \"����������������������������������������������������������������鼲鼳鼴鼵鼶鼸鼺鼼鼿齀齁齂齃齅齆齇齈齉齊齋齌齍齎齏齒齓齔齕齖齗齘齙齚齛齜齝齞齟齠齡齢齣齤齥齦齧齨齩齪齫齬齭齮齯齰齱齲齳齴齵齶齷齸�齹齺齻齼齽齾龁龂龍龎龏龐龑龒龓龔龕龖龗龘龜龝龞龡龢龣龤龥郎凉秊裏隣�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[253].length; ++j) if(D[253][j].charCodeAt(0) !== 0xFFFD) { e[D[253][j]] = 64768 + j; d[64768 + j] = D[253][j];}\nD[254] = \"����������������������������������������������������������������兀嗀﨎﨏﨑﨓﨔礼﨟蘒﨡﨣﨤﨧﨨﨩��������������������������������������������������������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[254].length; ++j) if(D[254][j].charCodeAt(0) !== 0xFFFD) { e[D[254][j]] = 65024 + j; d[65024 + j] = D[254][j];}\nreturn {\"enc\": e, \"dec\": d }; })();\ncptable[949] = (function(){ var d = [], e = {}, D = [], j;\nD[0] = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~��������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[0].length; ++j) if(D[0][j].charCodeAt(0) !== 0xFFFD) { e[D[0][j]] = 0 + j; d[0 + j] = D[0][j];}\nD[129] = \"�����������������������������������������������������������������갂갃갅갆갋갌갍갎갏갘갞갟갡갢갣갥갦갧갨갩갪갫갮갲갳갴������갵갶갷갺갻갽갾갿걁걂걃걄걅걆걇걈걉걊걌걎걏걐걑걒걓걕������걖걗걙걚걛걝걞걟걠걡걢걣걤걥걦걧걨걩걪걫걬걭걮걯걲걳걵걶걹걻걼걽걾걿겂겇겈겍겎겏겑겒겓겕겖겗겘겙겚겛겞겢겣겤겥겦겧겫겭겮겱겲겳겴겵겶겷겺겾겿곀곂곃곅곆곇곉곊곋곍곎곏곐곑곒곓곔곖곘곙곚곛곜곝곞곟곢곣곥곦곩곫곭곮곲곴곷곸곹곺곻곾곿괁괂괃괅괇괈괉괊괋괎괐괒괓�\".split(\"\");\nfor(j = 0; j != D[129].length; ++j) if(D[129][j].charCodeAt(0) !== 0xFFFD) { e[D[129][j]] = 33024 + j; d[33024 + j] = D[129][j];}\nD[130] = \"�����������������������������������������������������������������괔괕괖괗괙괚괛괝괞괟괡괢괣괤괥괦괧괨괪괫괮괯괰괱괲괳������괶괷괹괺괻괽괾괿굀굁굂굃굆굈굊굋굌굍굎굏굑굒굓굕굖굗������굙굚굛굜굝굞굟굠굢굤굥굦굧굨굩굪굫굮굯굱굲굷굸굹굺굾궀궃궄궅궆궇궊궋궍궎궏궑궒궓궔궕궖궗궘궙궚궛궞궟궠궡궢궣궥궦궧궨궩궪궫궬궭궮궯궰궱궲궳궴궵궶궸궹궺궻궼궽궾궿귂귃귅귆귇귉귊귋귌귍귎귏귒귔귕귖귗귘귙귚귛귝귞귟귡귢귣귥귦귧귨귩귪귫귬귭귮귯귰귱귲귳귴귵귶귷�\".split(\"\");\nfor(j = 0; j != D[130].length; ++j) if(D[130][j].charCodeAt(0) !== 0xFFFD) { e[D[130][j]] = 33280 + j; d[33280 + j] = D[130][j];}\nD[131] = \"�����������������������������������������������������������������귺귻귽귾긂긃긄긅긆긇긊긌긎긏긐긑긒긓긕긖긗긘긙긚긛긜������긝긞긟긠긡긢긣긤긥긦긧긨긩긪긫긬긭긮긯긲긳긵긶긹긻긼������긽긾긿깂깄깇깈깉깋깏깑깒깓깕깗깘깙깚깛깞깢깣깤깦깧깪깫깭깮깯깱깲깳깴깵깶깷깺깾깿꺀꺁꺂꺃꺆꺇꺈꺉꺊꺋꺍꺎꺏꺐꺑꺒꺓꺔꺕꺖꺗꺘꺙꺚꺛꺜꺝꺞꺟꺠꺡꺢꺣꺤꺥꺦꺧꺨꺩꺪꺫꺬꺭꺮꺯꺰꺱꺲꺳꺴꺵꺶꺷꺸꺹꺺꺻꺿껁껂껃껅껆껇껈껉껊껋껎껒껓껔껕껖껗껚껛껝껞껟껠껡껢껣껤껥�\".split(\"\");\nfor(j = 0; j != D[131].length; ++j) if(D[131][j].charCodeAt(0) !== 0xFFFD) { e[D[131][j]] = 33536 + j; d[33536 + j] = D[131][j];}\nD[132] = \"�����������������������������������������������������������������껦껧껩껪껬껮껯껰껱껲껳껵껶껷껹껺껻껽껾껿꼀꼁꼂꼃꼄꼅������꼆꼉꼊꼋꼌꼎꼏꼑꼒꼓꼔꼕꼖꼗꼘꼙꼚꼛꼜꼝꼞꼟꼠꼡꼢꼣������꼤꼥꼦꼧꼨꼩꼪꼫꼮꼯꼱꼳꼵꼶꼷꼸꼹꼺꼻꼾꽀꽄꽅꽆꽇꽊꽋꽌꽍꽎꽏꽑꽒꽓꽔꽕꽖꽗꽘꽙꽚꽛꽞꽟꽠꽡꽢꽣꽦꽧꽨꽩꽪꽫꽬꽭꽮꽯꽰꽱꽲꽳꽴꽵꽶꽷꽸꽺꽻꽼꽽꽾꽿꾁꾂꾃꾅꾆꾇꾉꾊꾋꾌꾍꾎꾏꾒꾓꾔꾖꾗꾘꾙꾚꾛꾝꾞꾟꾠꾡꾢꾣꾤꾥꾦꾧꾨꾩꾪꾫꾬꾭꾮꾯꾰꾱꾲꾳꾴꾵꾶꾷꾺꾻꾽꾾�\".split(\"\");\nfor(j = 0; j != D[132].length; ++j) if(D[132][j].charCodeAt(0) !== 0xFFFD) { e[D[132][j]] = 33792 + j; d[33792 + j] = D[132][j];}\nD[133] = \"�����������������������������������������������������������������꾿꿁꿂꿃꿄꿅꿆꿊꿌꿏꿐꿑꿒꿓꿕꿖꿗꿘꿙꿚꿛꿝꿞꿟꿠꿡������꿢꿣꿤꿥꿦꿧꿪꿫꿬꿭꿮꿯꿲꿳꿵꿶꿷꿹꿺꿻꿼꿽꿾꿿뀂뀃������뀅뀆뀇뀈뀉뀊뀋뀍뀎뀏뀑뀒뀓뀕뀖뀗뀘뀙뀚뀛뀞뀟뀠뀡뀢뀣뀤뀥뀦뀧뀩뀪뀫뀬뀭뀮뀯뀰뀱뀲뀳뀴뀵뀶뀷뀸뀹뀺뀻뀼뀽뀾뀿끀끁끂끃끆끇끉끋끍끏끐끑끒끖끘끚끛끜끞끟끠끡끢끣끤끥끦끧끨끩끪끫끬끭끮끯끰끱끲끳끴끵끶끷끸끹끺끻끾끿낁낂낃낅낆낇낈낉낊낋낎낐낒낓낔낕낖낗낛낝낞낣낤�\".split(\"\");\nfor(j = 0; j != D[133].length; ++j) if(D[133][j].charCodeAt(0) !== 0xFFFD) { e[D[133][j]] = 34048 + j; d[34048 + j] = D[133][j];}\nD[134] = \"�����������������������������������������������������������������낥낦낧낪낰낲낶낷낹낺낻낽낾낿냀냁냂냃냆냊냋냌냍냎냏냒������냓냕냖냗냙냚냛냜냝냞냟냡냢냣냤냦냧냨냩냪냫냬냭냮냯냰������냱냲냳냴냵냶냷냸냹냺냻냼냽냾냿넀넁넂넃넄넅넆넇넊넍넎넏넑넔넕넖넗넚넞넟넠넡넢넦넧넩넪넫넭넮넯넰넱넲넳넶넺넻넼넽넾넿녂녃녅녆녇녉녊녋녌녍녎녏녒녓녖녗녙녚녛녝녞녟녡녢녣녤녥녦녧녨녩녪녫녬녭녮녯녰녱녲녳녴녵녶녷녺녻녽녾녿놁놃놄놅놆놇놊놌놎놏놐놑놕놖놗놙놚놛놝�\".split(\"\");\nfor(j = 0; j != D[134].length; ++j) if(D[134][j].charCodeAt(0) !== 0xFFFD) { e[D[134][j]] = 34304 + j; d[34304 + j] = D[134][j];}\nD[135] = \"�����������������������������������������������������������������놞놟놠놡놢놣놤놥놦놧놩놪놫놬놭놮놯놰놱놲놳놴놵놶놷놸������놹놺놻놼놽놾놿뇀뇁뇂뇃뇄뇅뇆뇇뇈뇉뇊뇋뇍뇎뇏뇑뇒뇓뇕������뇖뇗뇘뇙뇚뇛뇞뇠뇡뇢뇣뇤뇥뇦뇧뇪뇫뇭뇮뇯뇱뇲뇳뇴뇵뇶뇷뇸뇺뇼뇾뇿눀눁눂눃눆눇눉눊눍눎눏눐눑눒눓눖눘눚눛눜눝눞눟눡눢눣눤눥눦눧눨눩눪눫눬눭눮눯눰눱눲눳눵눶눷눸눹눺눻눽눾눿뉀뉁뉂뉃뉄뉅뉆뉇뉈뉉뉊뉋뉌뉍뉎뉏뉐뉑뉒뉓뉔뉕뉖뉗뉙뉚뉛뉝뉞뉟뉡뉢뉣뉤뉥뉦뉧뉪뉫뉬뉭뉮�\".split(\"\");\nfor(j = 0; j != D[135].length; ++j) if(D[135][j].charCodeAt(0) !== 0xFFFD) { e[D[135][j]] = 34560 + j; d[34560 + j] = D[135][j];}\nD[136] = \"�����������������������������������������������������������������뉯뉰뉱뉲뉳뉶뉷뉸뉹뉺뉻뉽뉾뉿늀늁늂늃늆늇늈늊늋늌늍늎������늏늒늓늕늖늗늛늜늝늞늟늢늤늧늨늩늫늭늮늯늱늲늳늵늶늷������늸늹늺늻늼늽늾늿닀닁닂닃닄닅닆닇닊닋닍닎닏닑닓닔닕닖닗닚닜닞닟닠닡닣닧닩닪닰닱닲닶닼닽닾댂댃댅댆댇댉댊댋댌댍댎댏댒댖댗댘댙댚댛댝댞댟댠댡댢댣댤댥댦댧댨댩댪댫댬댭댮댯댰댱댲댳댴댵댶댷댸댹댺댻댼댽댾댿덀덁덂덃덄덅덆덇덈덉덊덋덌덍덎덏덐덑덒덓덗덙덚덝덠덡덢덣�\".split(\"\");\nfor(j = 0; j != D[136].length; ++j) if(D[136][j].charCodeAt(0) !== 0xFFFD) { e[D[136][j]] = 34816 + j; d[34816 + j] = D[136][j];}\nD[137] = \"�����������������������������������������������������������������덦덨덪덬덭덯덲덳덵덶덷덹덺덻덼덽덾덿뎂뎆뎇뎈뎉뎊뎋뎍������뎎뎏뎑뎒뎓뎕뎖뎗뎘뎙뎚뎛뎜뎝뎞뎟뎢뎣뎤뎥뎦뎧뎩뎪뎫뎭������뎮뎯뎰뎱뎲뎳뎴뎵뎶뎷뎸뎹뎺뎻뎼뎽뎾뎿돀돁돂돃돆돇돉돊돍돏돑돒돓돖돘돚돜돞돟돡돢돣돥돦돧돩돪돫돬돭돮돯돰돱돲돳돴돵돶돷돸돹돺돻돽돾돿됀됁됂됃됄됅됆됇됈됉됊됋됌됍됎됏됑됒됓됔됕됖됗됙됚됛됝됞됟됡됢됣됤됥됦됧됪됬됭됮됯됰됱됲됳됵됶됷됸됹됺됻됼됽됾됿둀둁둂둃둄�\".split(\"\");\nfor(j = 0; j != D[137].length; ++j) if(D[137][j].charCodeAt(0) !== 0xFFFD) { e[D[137][j]] = 35072 + j; d[35072 + j] = D[137][j];}\nD[138] = \"�����������������������������������������������������������������둅둆둇둈둉둊둋둌둍둎둏둒둓둕둖둗둙둚둛둜둝둞둟둢둤둦������둧둨둩둪둫둭둮둯둰둱둲둳둴둵둶둷둸둹둺둻둼둽둾둿뒁뒂������뒃뒄뒅뒆뒇뒉뒊뒋뒌뒍뒎뒏뒐뒑뒒뒓뒔뒕뒖뒗뒘뒙뒚뒛뒜뒞뒟뒠뒡뒢뒣뒥뒦뒧뒩뒪뒫뒭뒮뒯뒰뒱뒲뒳뒴뒶뒸뒺뒻뒼뒽뒾뒿듁듂듃듅듆듇듉듊듋듌듍듎듏듑듒듓듔듖듗듘듙듚듛듞듟듡듢듥듧듨듩듪듫듮듰듲듳듴듵듶듷듹듺듻듼듽듾듿딀딁딂딃딄딅딆딇딈딉딊딋딌딍딎딏딐딑딒딓딖딗딙딚딝�\".split(\"\");\nfor(j = 0; j != D[138].length; ++j) if(D[138][j].charCodeAt(0) !== 0xFFFD) { e[D[138][j]] = 35328 + j; d[35328 + j] = D[138][j];}\nD[139] = \"�����������������������������������������������������������������딞딟딠딡딢딣딦딫딬딭딮딯딲딳딵딶딷딹딺딻딼딽딾딿땂땆������땇땈땉땊땎땏땑땒땓땕땖땗땘땙땚땛땞땢땣땤땥땦땧땨땩땪������땫땬땭땮땯땰땱땲땳땴땵땶땷땸땹땺땻땼땽땾땿떀떁떂떃떄떅떆떇떈떉떊떋떌떍떎떏떐떑떒떓떔떕떖떗떘떙떚떛떜떝떞떟떢떣떥떦떧떩떬떭떮떯떲떶떷떸떹떺떾떿뗁뗂뗃뗅뗆뗇뗈뗉뗊뗋뗎뗒뗓뗔뗕뗖뗗뗙뗚뗛뗜뗝뗞뗟뗠뗡뗢뗣뗤뗥뗦뗧뗨뗩뗪뗫뗭뗮뗯뗰뗱뗲뗳뗴뗵뗶뗷뗸뗹뗺뗻뗼뗽뗾뗿�\".split(\"\");\nfor(j = 0; j != D[139].length; ++j) if(D[139][j].charCodeAt(0) !== 0xFFFD) { e[D[139][j]] = 35584 + j; d[35584 + j] = D[139][j];}\nD[140] = \"�����������������������������������������������������������������똀똁똂똃똄똅똆똇똈똉똊똋똌똍똎똏똒똓똕똖똗똙똚똛똜똝������똞똟똠똡똢똣똤똦똧똨똩똪똫똭똮똯똰똱똲똳똵똶똷똸똹똺������똻똼똽똾똿뙀뙁뙂뙃뙄뙅뙆뙇뙉뙊뙋뙌뙍뙎뙏뙐뙑뙒뙓뙔뙕뙖뙗뙘뙙뙚뙛뙜뙝뙞뙟뙠뙡뙢뙣뙥뙦뙧뙩뙪뙫뙬뙭뙮뙯뙰뙱뙲뙳뙴뙵뙶뙷뙸뙹뙺뙻뙼뙽뙾뙿뚀뚁뚂뚃뚄뚅뚆뚇뚈뚉뚊뚋뚌뚍뚎뚏뚐뚑뚒뚓뚔뚕뚖뚗뚘뚙뚚뚛뚞뚟뚡뚢뚣뚥뚦뚧뚨뚩뚪뚭뚮뚯뚰뚲뚳뚴뚵뚶뚷뚸뚹뚺뚻뚼뚽뚾뚿뛀뛁뛂�\".split(\"\");\nfor(j = 0; j != D[140].length; ++j) if(D[140][j].charCodeAt(0) !== 0xFFFD) { e[D[140][j]] = 35840 + j; d[35840 + j] = D[140][j];}\nD[141] = \"�����������������������������������������������������������������뛃뛄뛅뛆뛇뛈뛉뛊뛋뛌뛍뛎뛏뛐뛑뛒뛓뛕뛖뛗뛘뛙뛚뛛뛜뛝������뛞뛟뛠뛡뛢뛣뛤뛥뛦뛧뛨뛩뛪뛫뛬뛭뛮뛯뛱뛲뛳뛵뛶뛷뛹뛺������뛻뛼뛽뛾뛿뜂뜃뜄뜆뜇뜈뜉뜊뜋뜌뜍뜎뜏뜐뜑뜒뜓뜔뜕뜖뜗뜘뜙뜚뜛뜜뜝뜞뜟뜠뜡뜢뜣뜤뜥뜦뜧뜪뜫뜭뜮뜱뜲뜳뜴뜵뜶뜷뜺뜼뜽뜾뜿띀띁띂띃띅띆띇띉띊띋띍띎띏띐띑띒띓띖띗띘띙띚띛띜띝띞띟띡띢띣띥띦띧띩띪띫띬띭띮띯띲띴띶띷띸띹띺띻띾띿랁랂랃랅랆랇랈랉랊랋랎랓랔랕랚랛랝랞�\".split(\"\");\nfor(j = 0; j != D[141].length; ++j) if(D[141][j].charCodeAt(0) !== 0xFFFD) { e[D[141][j]] = 36096 + j; d[36096 + j] = D[141][j];}\nD[142] = \"�����������������������������������������������������������������랟랡랢랣랤랥랦랧랪랮랯랰랱랲랳랶랷랹랺랻랼랽랾랿럀럁������럂럃럄럅럆럈럊럋럌럍럎럏럐럑럒럓럔럕럖럗럘럙럚럛럜럝������럞럟럠럡럢럣럤럥럦럧럨럩럪럫럮럯럱럲럳럵럶럷럸럹럺럻럾렂렃렄렅렆렊렋렍렎렏렑렒렓렔렕렖렗렚렜렞렟렠렡렢렣렦렧렩렪렫렭렮렯렰렱렲렳렶렺렻렼렽렾렿롁롂롃롅롆롇롈롉롊롋롌롍롎롏롐롒롔롕롖롗롘롙롚롛롞롟롡롢롣롥롦롧롨롩롪롫롮롰롲롳롴롵롶롷롹롺롻롽롾롿뢀뢁뢂뢃뢄�\".split(\"\");\nfor(j = 0; j != D[142].length; ++j) if(D[142][j].charCodeAt(0) !== 0xFFFD) { e[D[142][j]] = 36352 + j; d[36352 + j] = D[142][j];}\nD[143] = \"�����������������������������������������������������������������뢅뢆뢇뢈뢉뢊뢋뢌뢎뢏뢐뢑뢒뢓뢔뢕뢖뢗뢘뢙뢚뢛뢜뢝뢞뢟������뢠뢡뢢뢣뢤뢥뢦뢧뢩뢪뢫뢬뢭뢮뢯뢱뢲뢳뢵뢶뢷뢹뢺뢻뢼뢽������뢾뢿룂룄룆룇룈룉룊룋룍룎룏룑룒룓룕룖룗룘룙룚룛룜룞룠룢룣룤룥룦룧룪룫룭룮룯룱룲룳룴룵룶룷룺룼룾룿뤀뤁뤂뤃뤅뤆뤇뤈뤉뤊뤋뤌뤍뤎뤏뤐뤑뤒뤓뤔뤕뤖뤗뤙뤚뤛뤜뤝뤞뤟뤡뤢뤣뤤뤥뤦뤧뤨뤩뤪뤫뤬뤭뤮뤯뤰뤱뤲뤳뤴뤵뤶뤷뤸뤹뤺뤻뤾뤿륁륂륃륅륆륇륈륉륊륋륍륎륐륒륓륔륕륖륗�\".split(\"\");\nfor(j = 0; j != D[143].length; ++j) if(D[143][j].charCodeAt(0) !== 0xFFFD) { e[D[143][j]] = 36608 + j; d[36608 + j] = D[143][j];}\nD[144] = \"�����������������������������������������������������������������륚륛륝륞륟륡륢륣륤륥륦륧륪륬륮륯륰륱륲륳륶륷륹륺륻륽������륾륿릀릁릂릃릆릈릋릌릏릐릑릒릓릔릕릖릗릘릙릚릛릜릝릞������릟릠릡릢릣릤릥릦릧릨릩릪릫릮릯릱릲릳릵릶릷릸릹릺릻릾맀맂맃맄맅맆맇맊맋맍맓맔맕맖맗맚맜맟맠맢맦맧맩맪맫맭맮맯맰맱맲맳맶맻맼맽맾맿먂먃먄먅먆먇먉먊먋먌먍먎먏먐먑먒먓먔먖먗먘먙먚먛먜먝먞먟먠먡먢먣먤먥먦먧먨먩먪먫먬먭먮먯먰먱먲먳먴먵먶먷먺먻먽먾먿멁멃멄멅멆�\".split(\"\");\nfor(j = 0; j != D[144].length; ++j) if(D[144][j].charCodeAt(0) !== 0xFFFD) { e[D[144][j]] = 36864 + j; d[36864 + j] = D[144][j];}\nD[145] = \"�����������������������������������������������������������������멇멊멌멏멐멑멒멖멗멙멚멛멝멞멟멠멡멢멣멦멪멫멬멭멮멯������멲멳멵멶멷멹멺멻멼멽멾멿몀몁몂몆몈몉몊몋몍몎몏몐몑몒������몓몔몕몖몗몘몙몚몛몜몝몞몟몠몡몢몣몤몥몦몧몪몭몮몯몱몳몴몵몶몷몺몼몾몿뫀뫁뫂뫃뫅뫆뫇뫉뫊뫋뫌뫍뫎뫏뫐뫑뫒뫓뫔뫕뫖뫗뫚뫛뫜뫝뫞뫟뫠뫡뫢뫣뫤뫥뫦뫧뫨뫩뫪뫫뫬뫭뫮뫯뫰뫱뫲뫳뫴뫵뫶뫷뫸뫹뫺뫻뫽뫾뫿묁묂묃묅묆묇묈묉묊묋묌묎묐묒묓묔묕묖묗묙묚묛묝묞묟묡묢묣묤묥묦묧�\".split(\"\");\nfor(j = 0; j != D[145].length; ++j) if(D[145][j].charCodeAt(0) !== 0xFFFD) { e[D[145][j]] = 37120 + j; d[37120 + j] = D[145][j];}\nD[146] = \"�����������������������������������������������������������������묨묪묬묭묮묯묰묱묲묳묷묹묺묿뭀뭁뭂뭃뭆뭈뭊뭋뭌뭎뭑뭒������뭓뭕뭖뭗뭙뭚뭛뭜뭝뭞뭟뭠뭢뭤뭥뭦뭧뭨뭩뭪뭫뭭뭮뭯뭰뭱������뭲뭳뭴뭵뭶뭷뭸뭹뭺뭻뭼뭽뭾뭿뮀뮁뮂뮃뮄뮅뮆뮇뮉뮊뮋뮍뮎뮏뮑뮒뮓뮔뮕뮖뮗뮘뮙뮚뮛뮜뮝뮞뮟뮠뮡뮢뮣뮥뮦뮧뮩뮪뮫뮭뮮뮯뮰뮱뮲뮳뮵뮶뮸뮹뮺뮻뮼뮽뮾뮿믁믂믃믅믆믇믉믊믋믌믍믎믏믑믒믔믕믖믗믘믙믚믛믜믝믞믟믠믡믢믣믤믥믦믧믨믩믪믫믬믭믮믯믰믱믲믳믴믵믶믷믺믻믽믾밁�\".split(\"\");\nfor(j = 0; j != D[146].length; ++j) if(D[146][j].charCodeAt(0) !== 0xFFFD) { e[D[146][j]] = 37376 + j; d[37376 + j] = D[146][j];}\nD[147] = \"�����������������������������������������������������������������밃밄밅밆밇밊밎밐밒밓밙밚밠밡밢밣밦밨밪밫밬밮밯밲밳밵������밶밷밹밺밻밼밽밾밿뱂뱆뱇뱈뱊뱋뱎뱏뱑뱒뱓뱔뱕뱖뱗뱘뱙������뱚뱛뱜뱞뱟뱠뱡뱢뱣뱤뱥뱦뱧뱨뱩뱪뱫뱬뱭뱮뱯뱰뱱뱲뱳뱴뱵뱶뱷뱸뱹뱺뱻뱼뱽뱾뱿벀벁벂벃벆벇벉벊벍벏벐벑벒벓벖벘벛벜벝벞벟벢벣벥벦벩벪벫벬벭벮벯벲벶벷벸벹벺벻벾벿볁볂볃볅볆볇볈볉볊볋볌볎볒볓볔볖볗볙볚볛볝볞볟볠볡볢볣볤볥볦볧볨볩볪볫볬볭볮볯볰볱볲볳볷볹볺볻볽�\".split(\"\");\nfor(j = 0; j != D[147].length; ++j) if(D[147][j].charCodeAt(0) !== 0xFFFD) { e[D[147][j]] = 37632 + j; d[37632 + j] = D[147][j];}\nD[148] = \"�����������������������������������������������������������������볾볿봀봁봂봃봆봈봊봋봌봍봎봏봑봒봓봕봖봗봘봙봚봛봜봝������봞봟봠봡봢봣봥봦봧봨봩봪봫봭봮봯봰봱봲봳봴봵봶봷봸봹������봺봻봼봽봾봿뵁뵂뵃뵄뵅뵆뵇뵊뵋뵍뵎뵏뵑뵒뵓뵔뵕뵖뵗뵚뵛뵜뵝뵞뵟뵠뵡뵢뵣뵥뵦뵧뵩뵪뵫뵬뵭뵮뵯뵰뵱뵲뵳뵴뵵뵶뵷뵸뵹뵺뵻뵼뵽뵾뵿붂붃붅붆붋붌붍붎붏붒붔붖붗붘붛붝붞붟붠붡붢붣붥붦붧붨붩붪붫붬붭붮붯붱붲붳붴붵붶붷붹붺붻붼붽붾붿뷀뷁뷂뷃뷄뷅뷆뷇뷈뷉뷊뷋뷌뷍뷎뷏뷐뷑�\".split(\"\");\nfor(j = 0; j != D[148].length; ++j) if(D[148][j].charCodeAt(0) !== 0xFFFD) { e[D[148][j]] = 37888 + j; d[37888 + j] = D[148][j];}\nD[149] = \"�����������������������������������������������������������������뷒뷓뷖뷗뷙뷚뷛뷝뷞뷟뷠뷡뷢뷣뷤뷥뷦뷧뷨뷪뷫뷬뷭뷮뷯뷱������뷲뷳뷵뷶뷷뷹뷺뷻뷼뷽뷾뷿븁븂븄븆븇븈븉븊븋븎븏븑븒븓������븕븖븗븘븙븚븛븞븠븡븢븣븤븥븦븧븨븩븪븫븬븭븮븯븰븱븲븳븴븵븶븷븸븹븺븻븼븽븾븿빀빁빂빃빆빇빉빊빋빍빏빐빑빒빓빖빘빜빝빞빟빢빣빥빦빧빩빫빬빭빮빯빲빶빷빸빹빺빾빿뺁뺂뺃뺅뺆뺇뺈뺉뺊뺋뺎뺒뺓뺔뺕뺖뺗뺚뺛뺜뺝뺞뺟뺠뺡뺢뺣뺤뺥뺦뺧뺩뺪뺫뺬뺭뺮뺯뺰뺱뺲뺳뺴뺵뺶뺷�\".split(\"\");\nfor(j = 0; j != D[149].length; ++j) if(D[149][j].charCodeAt(0) !== 0xFFFD) { e[D[149][j]] = 38144 + j; d[38144 + j] = D[149][j];}\nD[150] = \"�����������������������������������������������������������������뺸뺹뺺뺻뺼뺽뺾뺿뻀뻁뻂뻃뻄뻅뻆뻇뻈뻉뻊뻋뻌뻍뻎뻏뻒뻓������뻕뻖뻙뻚뻛뻜뻝뻞뻟뻡뻢뻦뻧뻨뻩뻪뻫뻭뻮뻯뻰뻱뻲뻳뻴뻵������뻶뻷뻸뻹뻺뻻뻼뻽뻾뻿뼀뼂뼃뼄뼅뼆뼇뼊뼋뼌뼍뼎뼏뼐뼑뼒뼓뼔뼕뼖뼗뼚뼞뼟뼠뼡뼢뼣뼤뼥뼦뼧뼨뼩뼪뼫뼬뼭뼮뼯뼰뼱뼲뼳뼴뼵뼶뼷뼸뼹뼺뼻뼼뼽뼾뼿뽂뽃뽅뽆뽇뽉뽊뽋뽌뽍뽎뽏뽒뽓뽔뽖뽗뽘뽙뽚뽛뽜뽝뽞뽟뽠뽡뽢뽣뽤뽥뽦뽧뽨뽩뽪뽫뽬뽭뽮뽯뽰뽱뽲뽳뽴뽵뽶뽷뽸뽹뽺뽻뽼뽽뽾뽿뾀뾁뾂�\".split(\"\");\nfor(j = 0; j != D[150].length; ++j) if(D[150][j].charCodeAt(0) !== 0xFFFD) { e[D[150][j]] = 38400 + j; d[38400 + j] = D[150][j];}\nD[151] = \"�����������������������������������������������������������������뾃뾄뾅뾆뾇뾈뾉뾊뾋뾌뾍뾎뾏뾐뾑뾒뾓뾕뾖뾗뾘뾙뾚뾛뾜뾝������뾞뾟뾠뾡뾢뾣뾤뾥뾦뾧뾨뾩뾪뾫뾬뾭뾮뾯뾱뾲뾳뾴뾵뾶뾷뾸������뾹뾺뾻뾼뾽뾾뾿뿀뿁뿂뿃뿄뿆뿇뿈뿉뿊뿋뿎뿏뿑뿒뿓뿕뿖뿗뿘뿙뿚뿛뿝뿞뿠뿢뿣뿤뿥뿦뿧뿨뿩뿪뿫뿬뿭뿮뿯뿰뿱뿲뿳뿴뿵뿶뿷뿸뿹뿺뿻뿼뿽뿾뿿쀀쀁쀂쀃쀄쀅쀆쀇쀈쀉쀊쀋쀌쀍쀎쀏쀐쀑쀒쀓쀔쀕쀖쀗쀘쀙쀚쀛쀜쀝쀞쀟쀠쀡쀢쀣쀤쀥쀦쀧쀨쀩쀪쀫쀬쀭쀮쀯쀰쀱쀲쀳쀴쀵쀶쀷쀸쀹쀺쀻쀽쀾쀿�\".split(\"\");\nfor(j = 0; j != D[151].length; ++j) if(D[151][j].charCodeAt(0) !== 0xFFFD) { e[D[151][j]] = 38656 + j; d[38656 + j] = D[151][j];}\nD[152] = \"�����������������������������������������������������������������쁀쁁쁂쁃쁄쁅쁆쁇쁈쁉쁊쁋쁌쁍쁎쁏쁐쁒쁓쁔쁕쁖쁗쁙쁚쁛������쁝쁞쁟쁡쁢쁣쁤쁥쁦쁧쁪쁫쁬쁭쁮쁯쁰쁱쁲쁳쁴쁵쁶쁷쁸쁹������쁺쁻쁼쁽쁾쁿삀삁삂삃삄삅삆삇삈삉삊삋삌삍삎삏삒삓삕삖삗삙삚삛삜삝삞삟삢삤삦삧삨삩삪삫삮삱삲삷삸삹삺삻삾샂샃샄샆샇샊샋샍샎샏샑샒샓샔샕샖샗샚샞샟샠샡샢샣샦샧샩샪샫샭샮샯샰샱샲샳샶샸샺샻샼샽샾샿섁섂섃섅섆섇섉섊섋섌섍섎섏섑섒섓섔섖섗섘섙섚섛섡섢섥섨섩섪섫섮�\".split(\"\");\nfor(j = 0; j != D[152].length; ++j) if(D[152][j].charCodeAt(0) !== 0xFFFD) { e[D[152][j]] = 38912 + j; d[38912 + j] = D[152][j];}\nD[153] = \"�����������������������������������������������������������������섲섳섴섵섷섺섻섽섾섿셁셂셃셄셅셆셇셊셎셏셐셑셒셓셖셗������셙셚셛셝셞셟셠셡셢셣셦셪셫셬셭셮셯셱셲셳셵셶셷셹셺셻������셼셽셾셿솀솁솂솃솄솆솇솈솉솊솋솏솑솒솓솕솗솘솙솚솛솞솠솢솣솤솦솧솪솫솭솮솯솱솲솳솴솵솶솷솸솹솺솻솼솾솿쇀쇁쇂쇃쇅쇆쇇쇉쇊쇋쇍쇎쇏쇐쇑쇒쇓쇕쇖쇙쇚쇛쇜쇝쇞쇟쇡쇢쇣쇥쇦쇧쇩쇪쇫쇬쇭쇮쇯쇲쇴쇵쇶쇷쇸쇹쇺쇻쇾쇿숁숂숃숅숆숇숈숉숊숋숎숐숒숓숔숕숖숗숚숛숝숞숡숢숣�\".split(\"\");\nfor(j = 0; j != D[153].length; ++j) if(D[153][j].charCodeAt(0) !== 0xFFFD) { e[D[153][j]] = 39168 + j; d[39168 + j] = D[153][j];}\nD[154] = \"�����������������������������������������������������������������숤숥숦숧숪숬숮숰숳숵숶숷숸숹숺숻숼숽숾숿쉀쉁쉂쉃쉄쉅������쉆쉇쉉쉊쉋쉌쉍쉎쉏쉒쉓쉕쉖쉗쉙쉚쉛쉜쉝쉞쉟쉡쉢쉣쉤쉦������쉧쉨쉩쉪쉫쉮쉯쉱쉲쉳쉵쉶쉷쉸쉹쉺쉻쉾슀슂슃슄슅슆슇슊슋슌슍슎슏슑슒슓슔슕슖슗슙슚슜슞슟슠슡슢슣슦슧슩슪슫슮슯슰슱슲슳슶슸슺슻슼슽슾슿싀싁싂싃싄싅싆싇싈싉싊싋싌싍싎싏싐싑싒싓싔싕싖싗싘싙싚싛싞싟싡싢싥싦싧싨싩싪싮싰싲싳싴싵싷싺싽싾싿쌁쌂쌃쌄쌅쌆쌇쌊쌋쌎쌏�\".split(\"\");\nfor(j = 0; j != D[154].length; ++j) if(D[154][j].charCodeAt(0) !== 0xFFFD) { e[D[154][j]] = 39424 + j; d[39424 + j] = D[154][j];}\nD[155] = \"�����������������������������������������������������������������쌐쌑쌒쌖쌗쌙쌚쌛쌝쌞쌟쌠쌡쌢쌣쌦쌧쌪쌫쌬쌭쌮쌯쌰쌱쌲������쌳쌴쌵쌶쌷쌸쌹쌺쌻쌼쌽쌾쌿썀썁썂썃썄썆썇썈썉썊썋썌썍������썎썏썐썑썒썓썔썕썖썗썘썙썚썛썜썝썞썟썠썡썢썣썤썥썦썧썪썫썭썮썯썱썳썴썵썶썷썺썻썾썿쎀쎁쎂쎃쎅쎆쎇쎉쎊쎋쎍쎎쎏쎐쎑쎒쎓쎔쎕쎖쎗쎘쎙쎚쎛쎜쎝쎞쎟쎠쎡쎢쎣쎤쎥쎦쎧쎨쎩쎪쎫쎬쎭쎮쎯쎰쎱쎲쎳쎴쎵쎶쎷쎸쎹쎺쎻쎼쎽쎾쎿쏁쏂쏃쏄쏅쏆쏇쏈쏉쏊쏋쏌쏍쏎쏏쏐쏑쏒쏓쏔쏕쏖쏗쏚�\".split(\"\");\nfor(j = 0; j != D[155].length; ++j) if(D[155][j].charCodeAt(0) !== 0xFFFD) { e[D[155][j]] = 39680 + j; d[39680 + j] = D[155][j];}\nD[156] = \"�����������������������������������������������������������������쏛쏝쏞쏡쏣쏤쏥쏦쏧쏪쏫쏬쏮쏯쏰쏱쏲쏳쏶쏷쏹쏺쏻쏼쏽쏾������쏿쐀쐁쐂쐃쐄쐅쐆쐇쐉쐊쐋쐌쐍쐎쐏쐑쐒쐓쐔쐕쐖쐗쐘쐙쐚������쐛쐜쐝쐞쐟쐠쐡쐢쐣쐥쐦쐧쐨쐩쐪쐫쐭쐮쐯쐱쐲쐳쐵쐶쐷쐸쐹쐺쐻쐾쐿쑀쑁쑂쑃쑄쑅쑆쑇쑉쑊쑋쑌쑍쑎쑏쑐쑑쑒쑓쑔쑕쑖쑗쑘쑙쑚쑛쑜쑝쑞쑟쑠쑡쑢쑣쑦쑧쑩쑪쑫쑭쑮쑯쑰쑱쑲쑳쑶쑷쑸쑺쑻쑼쑽쑾쑿쒁쒂쒃쒄쒅쒆쒇쒈쒉쒊쒋쒌쒍쒎쒏쒐쒑쒒쒓쒕쒖쒗쒘쒙쒚쒛쒝쒞쒟쒠쒡쒢쒣쒤쒥쒦쒧쒨쒩�\".split(\"\");\nfor(j = 0; j != D[156].length; ++j) if(D[156][j].charCodeAt(0) !== 0xFFFD) { e[D[156][j]] = 39936 + j; d[39936 + j] = D[156][j];}\nD[157] = \"�����������������������������������������������������������������쒪쒫쒬쒭쒮쒯쒰쒱쒲쒳쒴쒵쒶쒷쒹쒺쒻쒽쒾쒿쓀쓁쓂쓃쓄쓅������쓆쓇쓈쓉쓊쓋쓌쓍쓎쓏쓐쓑쓒쓓쓔쓕쓖쓗쓘쓙쓚쓛쓜쓝쓞쓟������쓠쓡쓢쓣쓤쓥쓦쓧쓨쓪쓫쓬쓭쓮쓯쓲쓳쓵쓶쓷쓹쓻쓼쓽쓾씂씃씄씅씆씇씈씉씊씋씍씎씏씑씒씓씕씖씗씘씙씚씛씝씞씟씠씡씢씣씤씥씦씧씪씫씭씮씯씱씲씳씴씵씶씷씺씼씾씿앀앁앂앃앆앇앋앏앐앑앒앖앚앛앜앟앢앣앥앦앧앩앪앫앬앭앮앯앲앶앷앸앹앺앻앾앿얁얂얃얅얆얈얉얊얋얎얐얒얓얔�\".split(\"\");\nfor(j = 0; j != D[157].length; ++j) if(D[157][j].charCodeAt(0) !== 0xFFFD) { e[D[157][j]] = 40192 + j; d[40192 + j] = D[157][j];}\nD[158] = \"�����������������������������������������������������������������얖얙얚얛얝얞얟얡얢얣얤얥얦얧얨얪얫얬얭얮얯얰얱얲얳얶������얷얺얿엀엁엂엃엋엍엏엒엓엕엖엗엙엚엛엜엝엞엟엢엤엦엧������엨엩엪엫엯엱엲엳엵엸엹엺엻옂옃옄옉옊옋옍옎옏옑옒옓옔옕옖옗옚옝옞옟옠옡옢옣옦옧옩옪옫옯옱옲옶옸옺옼옽옾옿왂왃왅왆왇왉왊왋왌왍왎왏왒왖왗왘왙왚왛왞왟왡왢왣왤왥왦왧왨왩왪왫왭왮왰왲왳왴왵왶왷왺왻왽왾왿욁욂욃욄욅욆욇욊욌욎욏욐욑욒욓욖욗욙욚욛욝욞욟욠욡욢욣욦�\".split(\"\");\nfor(j = 0; j != D[158].length; ++j) if(D[158][j].charCodeAt(0) !== 0xFFFD) { e[D[158][j]] = 40448 + j; d[40448 + j] = D[158][j];}\nD[159] = \"�����������������������������������������������������������������욨욪욫욬욭욮욯욲욳욵욶욷욻욼욽욾욿웂웄웆웇웈웉웊웋웎������웏웑웒웓웕웖웗웘웙웚웛웞웟웢웣웤웥웦웧웪웫웭웮웯웱웲������웳웴웵웶웷웺웻웼웾웿윀윁윂윃윆윇윉윊윋윍윎윏윐윑윒윓윖윘윚윛윜윝윞윟윢윣윥윦윧윩윪윫윬윭윮윯윲윴윶윸윹윺윻윾윿읁읂읃읅읆읇읈읉읋읎읐읙읚읛읝읞읟읡읢읣읤읥읦읧읩읪읬읭읮읯읰읱읲읳읶읷읹읺읻읿잀잁잂잆잋잌잍잏잒잓잕잙잛잜잝잞잟잢잧잨잩잪잫잮잯잱잲잳잵잶잷�\".split(\"\");\nfor(j = 0; j != D[159].length; ++j) if(D[159][j].charCodeAt(0) !== 0xFFFD) { e[D[159][j]] = 40704 + j; d[40704 + j] = D[159][j];}\nD[160] = \"�����������������������������������������������������������������잸잹잺잻잾쟂쟃쟄쟅쟆쟇쟊쟋쟍쟏쟑쟒쟓쟔쟕쟖쟗쟙쟚쟛쟜������쟞쟟쟠쟡쟢쟣쟥쟦쟧쟩쟪쟫쟭쟮쟯쟰쟱쟲쟳쟴쟵쟶쟷쟸쟹쟺������쟻쟼쟽쟾쟿젂젃젅젆젇젉젋젌젍젎젏젒젔젗젘젙젚젛젞젟젡젢젣젥젦젧젨젩젪젫젮젰젲젳젴젵젶젷젹젺젻젽젾젿졁졂졃졄졅졆졇졊졋졎졏졐졑졒졓졕졖졗졘졙졚졛졜졝졞졟졠졡졢졣졤졥졦졧졨졩졪졫졬졭졮졯졲졳졵졶졷졹졻졼졽졾졿좂좄좈좉좊좎좏좐좑좒좓좕좖좗좘좙좚좛좜좞좠좢좣좤�\".split(\"\");\nfor(j = 0; j != D[160].length; ++j) if(D[160][j].charCodeAt(0) !== 0xFFFD) { e[D[160][j]] = 40960 + j; d[40960 + j] = D[160][j];}\nD[161] = \"�����������������������������������������������������������������좥좦좧좩좪좫좬좭좮좯좰좱좲좳좴좵좶좷좸좹좺좻좾좿죀죁������죂죃죅죆죇죉죊죋죍죎죏죐죑죒죓죖죘죚죛죜죝죞죟죢죣죥������죦죧죨죩죪죫죬죭죮죯죰죱죲죳죴죶죷죸죹죺죻죾죿줁줂줃줇줈줉줊줋줎　、。·‥…¨〃­―∥＼∼‘’“”〔〕〈〉《》「」『』【】±×÷≠≤≥∞∴°′″℃Å￠￡￥♂♀∠⊥⌒∂∇≡≒§※☆★○●◎◇◆□■△▲▽▼→←↑↓↔〓≪≫√∽∝∵∫∬∈∋⊆⊇⊂⊃∪∩∧∨￢�\".split(\"\");\nfor(j = 0; j != D[161].length; ++j) if(D[161][j].charCodeAt(0) !== 0xFFFD) { e[D[161][j]] = 41216 + j; d[41216 + j] = D[161][j];}\nD[162] = \"�����������������������������������������������������������������줐줒줓줔줕줖줗줙줚줛줜줝줞줟줠줡줢줣줤줥줦줧줨줩줪줫������줭줮줯줰줱줲줳줵줶줷줸줹줺줻줼줽줾줿쥀쥁쥂쥃쥄쥅쥆쥇������쥈쥉쥊쥋쥌쥍쥎쥏쥒쥓쥕쥖쥗쥙쥚쥛쥜쥝쥞쥟쥢쥤쥥쥦쥧쥨쥩쥪쥫쥭쥮쥯⇒⇔∀∃´～ˇ˘˝˚˙¸˛¡¿ː∮∑∏¤℉‰◁◀▷▶♤♠♡♥♧♣⊙◈▣◐◑▒▤▥▨▧▦▩♨☏☎☜☞¶†‡↕↗↙↖↘♭♩♪♬㉿㈜№㏇™㏂㏘℡€®������������������������\".split(\"\");\nfor(j = 0; j != D[162].length; ++j) if(D[162][j].charCodeAt(0) !== 0xFFFD) { e[D[162][j]] = 41472 + j; d[41472 + j] = D[162][j];}\nD[163] = \"�����������������������������������������������������������������쥱쥲쥳쥵쥶쥷쥸쥹쥺쥻쥽쥾쥿즀즁즂즃즄즅즆즇즊즋즍즎즏������즑즒즓즔즕즖즗즚즜즞즟즠즡즢즣즤즥즦즧즨즩즪즫즬즭즮������즯즰즱즲즳즴즵즶즷즸즹즺즻즼즽즾즿짂짃짅짆짉짋짌짍짎짏짒짔짗짘짛！＂＃＄％＆＇（）＊＋，－．／０１２３４５６７８９：；＜＝＞？＠ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺ［￦］＾＿｀ａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚ｛｜｝￣�\".split(\"\");\nfor(j = 0; j != D[163].length; ++j) if(D[163][j].charCodeAt(0) !== 0xFFFD) { e[D[163][j]] = 41728 + j; d[41728 + j] = D[163][j];}\nD[164] = \"�����������������������������������������������������������������짞짟짡짣짥짦짨짩짪짫짮짲짳짴짵짶짷짺짻짽짾짿쨁쨂쨃쨄������쨅쨆쨇쨊쨎쨏쨐쨑쨒쨓쨕쨖쨗쨙쨚쨛쨜쨝쨞쨟쨠쨡쨢쨣쨤쨥������쨦쨧쨨쨪쨫쨬쨭쨮쨯쨰쨱쨲쨳쨴쨵쨶쨷쨸쨹쨺쨻쨼쨽쨾쨿쩀쩁쩂쩃쩄쩅쩆ㄱㄲㄳㄴㄵㄶㄷㄸㄹㄺㄻㄼㄽㄾㄿㅀㅁㅂㅃㅄㅅㅆㅇㅈㅉㅊㅋㅌㅍㅎㅏㅐㅑㅒㅓㅔㅕㅖㅗㅘㅙㅚㅛㅜㅝㅞㅟㅠㅡㅢㅣㅤㅥㅦㅧㅨㅩㅪㅫㅬㅭㅮㅯㅰㅱㅲㅳㅴㅵㅶㅷㅸㅹㅺㅻㅼㅽㅾㅿㆀㆁㆂㆃㆄㆅㆆㆇㆈㆉㆊㆋㆌㆍㆎ�\".split(\"\");\nfor(j = 0; j != D[164].length; ++j) if(D[164][j].charCodeAt(0) !== 0xFFFD) { e[D[164][j]] = 41984 + j; d[41984 + j] = D[164][j];}\nD[165] = \"�����������������������������������������������������������������쩇쩈쩉쩊쩋쩎쩏쩑쩒쩓쩕쩖쩗쩘쩙쩚쩛쩞쩢쩣쩤쩥쩦쩧쩩쩪������쩫쩬쩭쩮쩯쩰쩱쩲쩳쩴쩵쩶쩷쩸쩹쩺쩻쩼쩾쩿쪀쪁쪂쪃쪅쪆������쪇쪈쪉쪊쪋쪌쪍쪎쪏쪐쪑쪒쪓쪔쪕쪖쪗쪙쪚쪛쪜쪝쪞쪟쪠쪡쪢쪣쪤쪥쪦쪧ⅰⅱⅲⅳⅴⅵⅶⅷⅸⅹ�����ⅠⅡⅢⅣⅤⅥⅦⅧⅨⅩ�������ΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩ��������αβγδεζηθικλμνξοπρστυφχψω�������\".split(\"\");\nfor(j = 0; j != D[165].length; ++j) if(D[165][j].charCodeAt(0) !== 0xFFFD) { e[D[165][j]] = 42240 + j; d[42240 + j] = D[165][j];}\nD[166] = \"�����������������������������������������������������������������쪨쪩쪪쪫쪬쪭쪮쪯쪰쪱쪲쪳쪴쪵쪶쪷쪸쪹쪺쪻쪾쪿쫁쫂쫃쫅������쫆쫇쫈쫉쫊쫋쫎쫐쫒쫔쫕쫖쫗쫚쫛쫜쫝쫞쫟쫡쫢쫣쫤쫥쫦쫧������쫨쫩쫪쫫쫭쫮쫯쫰쫱쫲쫳쫵쫶쫷쫸쫹쫺쫻쫼쫽쫾쫿쬀쬁쬂쬃쬄쬅쬆쬇쬉쬊─│┌┐┘└├┬┤┴┼━┃┏┓┛┗┣┳┫┻╋┠┯┨┷┿┝┰┥┸╂┒┑┚┙┖┕┎┍┞┟┡┢┦┧┩┪┭┮┱┲┵┶┹┺┽┾╀╁╃╄╅╆╇╈╉╊���������������������������\".split(\"\");\nfor(j = 0; j != D[166].length; ++j) if(D[166][j].charCodeAt(0) !== 0xFFFD) { e[D[166][j]] = 42496 + j; d[42496 + j] = D[166][j];}\nD[167] = \"�����������������������������������������������������������������쬋쬌쬍쬎쬏쬑쬒쬓쬕쬖쬗쬙쬚쬛쬜쬝쬞쬟쬢쬣쬤쬥쬦쬧쬨쬩������쬪쬫쬬쬭쬮쬯쬰쬱쬲쬳쬴쬵쬶쬷쬸쬹쬺쬻쬼쬽쬾쬿쭀쭂쭃쭄������쭅쭆쭇쭊쭋쭍쭎쭏쭑쭒쭓쭔쭕쭖쭗쭚쭛쭜쭞쭟쭠쭡쭢쭣쭥쭦쭧쭨쭩쭪쭫쭬㎕㎖㎗ℓ㎘㏄㎣㎤㎥㎦㎙㎚㎛㎜㎝㎞㎟㎠㎡㎢㏊㎍㎎㎏㏏㎈㎉㏈㎧㎨㎰㎱㎲㎳㎴㎵㎶㎷㎸㎹㎀㎁㎂㎃㎄㎺㎻㎼㎽㎾㎿㎐㎑㎒㎓㎔Ω㏀㏁㎊㎋㎌㏖㏅㎭㎮㎯㏛㎩㎪㎫㎬㏝㏐㏓㏃㏉㏜㏆����������������\".split(\"\");\nfor(j = 0; j != D[167].length; ++j) if(D[167][j].charCodeAt(0) !== 0xFFFD) { e[D[167][j]] = 42752 + j; d[42752 + j] = D[167][j];}\nD[168] = \"�����������������������������������������������������������������쭭쭮쭯쭰쭱쭲쭳쭴쭵쭶쭷쭺쭻쭼쭽쭾쭿쮀쮁쮂쮃쮄쮅쮆쮇쮈������쮉쮊쮋쮌쮍쮎쮏쮐쮑쮒쮓쮔쮕쮖쮗쮘쮙쮚쮛쮝쮞쮟쮠쮡쮢쮣������쮤쮥쮦쮧쮨쮩쮪쮫쮬쮭쮮쮯쮰쮱쮲쮳쮴쮵쮶쮷쮹쮺쮻쮼쮽쮾쮿쯀쯁쯂쯃쯄ÆЪĦ�IJ�ĿŁØŒºÞŦŊ�㉠㉡㉢㉣㉤㉥㉦㉧㉨㉩㉪㉫㉬㉭㉮㉯㉰㉱㉲㉳㉴㉵㉶㉷㉸㉹㉺㉻ⓐⓑⓒⓓⓔⓕⓖⓗⓘⓙⓚⓛⓜⓝⓞⓟⓠⓡⓢⓣⓤⓥⓦⓧⓨⓩ①②③④⑤⑥⑦⑧⑨⑩⑪⑫⑬⑭⑮½⅓⅔¼¾⅛⅜⅝⅞�\".split(\"\");\nfor(j = 0; j != D[168].length; ++j) if(D[168][j].charCodeAt(0) !== 0xFFFD) { e[D[168][j]] = 43008 + j; d[43008 + j] = D[168][j];}\nD[169] = \"�����������������������������������������������������������������쯅쯆쯇쯈쯉쯊쯋쯌쯍쯎쯏쯐쯑쯒쯓쯕쯖쯗쯘쯙쯚쯛쯜쯝쯞쯟������쯠쯡쯢쯣쯥쯦쯨쯪쯫쯬쯭쯮쯯쯰쯱쯲쯳쯴쯵쯶쯷쯸쯹쯺쯻쯼������쯽쯾쯿찀찁찂찃찄찅찆찇찈찉찊찋찎찏찑찒찓찕찖찗찘찙찚찛찞찟찠찣찤æđðħıijĸŀłøœßþŧŋʼn㈀㈁㈂㈃㈄㈅㈆㈇㈈㈉㈊㈋㈌㈍㈎㈏㈐㈑㈒㈓㈔㈕㈖㈗㈘㈙㈚㈛⒜⒝⒞⒟⒠⒡⒢⒣⒤⒥⒦⒧⒨⒩⒪⒫⒬⒭⒮⒯⒰⒱⒲⒳⒴⒵⑴⑵⑶⑷⑸⑹⑺⑻⑼⑽⑾⑿⒀⒁⒂¹²³⁴ⁿ₁₂₃₄�\".split(\"\");\nfor(j = 0; j != D[169].length; ++j) if(D[169][j].charCodeAt(0) !== 0xFFFD) { e[D[169][j]] = 43264 + j; d[43264 + j] = D[169][j];}\nD[170] = \"�����������������������������������������������������������������찥찦찪찫찭찯찱찲찳찴찵찶찷찺찿챀챁챂챃챆챇챉챊챋챍챎������챏챐챑챒챓챖챚챛챜챝챞챟챡챢챣챥챧챩챪챫챬챭챮챯챱챲������챳챴챶챷챸챹챺챻챼챽챾챿첀첁첂첃첄첅첆첇첈첉첊첋첌첍첎첏첐첑첒첓ぁあぃいぅうぇえぉおかがきぎくぐけげこごさざしじすずせぜそぞただちぢっつづてでとどなにぬねのはばぱひびぴふぶぷへべぺほぼぽまみむめもゃやゅゆょよらりるれろゎわゐゑをん������������\".split(\"\");\nfor(j = 0; j != D[170].length; ++j) if(D[170][j].charCodeAt(0) !== 0xFFFD) { e[D[170][j]] = 43520 + j; d[43520 + j] = D[170][j];}\nD[171] = \"�����������������������������������������������������������������첔첕첖첗첚첛첝첞첟첡첢첣첤첥첦첧첪첮첯첰첱첲첳첶첷첹������첺첻첽첾첿쳀쳁쳂쳃쳆쳈쳊쳋쳌쳍쳎쳏쳑쳒쳓쳕쳖쳗쳘쳙쳚������쳛쳜쳝쳞쳟쳠쳡쳢쳣쳥쳦쳧쳨쳩쳪쳫쳭쳮쳯쳱쳲쳳쳴쳵쳶쳷쳸쳹쳺쳻쳼쳽ァアィイゥウェエォオカガキギクグケゲコゴサザシジスズセゼソゾタダチヂッツヅテデトドナニヌネノハバパヒビピフブプヘベペホボポマミムメモャヤュユョヨラリルレロヮワヰヱヲンヴヵヶ���������\".split(\"\");\nfor(j = 0; j != D[171].length; ++j) if(D[171][j].charCodeAt(0) !== 0xFFFD) { e[D[171][j]] = 43776 + j; d[43776 + j] = D[171][j];}\nD[172] = \"�����������������������������������������������������������������쳾쳿촀촂촃촄촅촆촇촊촋촍촎촏촑촒촓촔촕촖촗촚촜촞촟촠������촡촢촣촥촦촧촩촪촫촭촮촯촰촱촲촳촴촵촶촷촸촺촻촼촽촾������촿쵀쵁쵂쵃쵄쵅쵆쵇쵈쵉쵊쵋쵌쵍쵎쵏쵐쵑쵒쵓쵔쵕쵖쵗쵘쵙쵚쵛쵝쵞쵟АБВГДЕЁЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ���������������абвгдеёжзийклмнопрстуфхцчшщъыьэюя��������������\".split(\"\");\nfor(j = 0; j != D[172].length; ++j) if(D[172][j].charCodeAt(0) !== 0xFFFD) { e[D[172][j]] = 44032 + j; d[44032 + j] = D[172][j];}\nD[173] = \"�����������������������������������������������������������������쵡쵢쵣쵥쵦쵧쵨쵩쵪쵫쵮쵰쵲쵳쵴쵵쵶쵷쵹쵺쵻쵼쵽쵾쵿춀������춁춂춃춄춅춆춇춉춊춋춌춍춎춏춐춑춒춓춖춗춙춚춛춝춞춟������춠춡춢춣춦춨춪춫춬춭춮춯춱춲춳춴춵춶춷춸춹춺춻춼춽춾춿췀췁췂췃췅�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[173].length; ++j) if(D[173][j].charCodeAt(0) !== 0xFFFD) { e[D[173][j]] = 44288 + j; d[44288 + j] = D[173][j];}\nD[174] = \"�����������������������������������������������������������������췆췇췈췉췊췋췍췎췏췑췒췓췔췕췖췗췘췙췚췛췜췝췞췟췠췡������췢췣췤췥췦췧췩췪췫췭췮췯췱췲췳췴췵췶췷췺췼췾췿츀츁츂������츃츅츆츇츉츊츋츍츎츏츐츑츒츓츕츖츗츘츚츛츜츝츞츟츢츣츥츦츧츩츪츫�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[174].length; ++j) if(D[174][j].charCodeAt(0) !== 0xFFFD) { e[D[174][j]] = 44544 + j; d[44544 + j] = D[174][j];}\nD[175] = \"�����������������������������������������������������������������츬츭츮츯츲츴츶츷츸츹츺츻츼츽츾츿칀칁칂칃칄칅칆칇칈칉������칊칋칌칍칎칏칐칑칒칓칔칕칖칗칚칛칝칞칢칣칤칥칦칧칪칬������칮칯칰칱칲칳칶칷칹칺칻칽칾칿캀캁캂캃캆캈캊캋캌캍캎캏캒캓캕캖캗캙�����������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[175].length; ++j) if(D[175][j].charCodeAt(0) !== 0xFFFD) { e[D[175][j]] = 44800 + j; d[44800 + j] = D[175][j];}\nD[176] = \"�����������������������������������������������������������������캚캛캜캝캞캟캢캦캧캨캩캪캫캮캯캰캱캲캳캴캵캶캷캸캹캺������캻캼캽캾캿컀컂컃컄컅컆컇컈컉컊컋컌컍컎컏컐컑컒컓컔컕������컖컗컘컙컚컛컜컝컞컟컠컡컢컣컦컧컩컪컭컮컯컰컱컲컳컶컺컻컼컽컾컿가각간갇갈갉갊감갑값갓갔강갖갗같갚갛개객갠갤갬갭갯갰갱갸갹갼걀걋걍걔걘걜거걱건걷걸걺검겁것겄겅겆겉겊겋게겐겔겜겝겟겠겡겨격겪견겯결겸겹겻겼경곁계곈곌곕곗고곡곤곧골곪곬곯곰곱곳공곶과곽관괄괆�\".split(\"\");\nfor(j = 0; j != D[176].length; ++j) if(D[176][j].charCodeAt(0) !== 0xFFFD) { e[D[176][j]] = 45056 + j; d[45056 + j] = D[176][j];}\nD[177] = \"�����������������������������������������������������������������켂켃켅켆켇켉켊켋켌켍켎켏켒켔켖켗켘켙켚켛켝켞켟켡켢켣������켥켦켧켨켩켪켫켮켲켳켴켵켶켷켹켺켻켼켽켾켿콀콁콂콃콄������콅콆콇콈콉콊콋콌콍콎콏콐콑콒콓콖콗콙콚콛콝콞콟콠콡콢콣콦콨콪콫콬괌괍괏광괘괜괠괩괬괭괴괵괸괼굄굅굇굉교굔굘굡굣구국군굳굴굵굶굻굼굽굿궁궂궈궉권궐궜궝궤궷귀귁귄귈귐귑귓규균귤그극근귿글긁금급긋긍긔기긱긴긷길긺김깁깃깅깆깊까깍깎깐깔깖깜깝깟깠깡깥깨깩깬깰깸�\".split(\"\");\nfor(j = 0; j != D[177].length; ++j) if(D[177][j].charCodeAt(0) !== 0xFFFD) { e[D[177][j]] = 45312 + j; d[45312 + j] = D[177][j];}\nD[178] = \"�����������������������������������������������������������������콭콮콯콲콳콵콶콷콹콺콻콼콽콾콿쾁쾂쾃쾄쾆쾇쾈쾉쾊쾋쾍������쾎쾏쾐쾑쾒쾓쾔쾕쾖쾗쾘쾙쾚쾛쾜쾝쾞쾟쾠쾢쾣쾤쾥쾦쾧쾩������쾪쾫쾬쾭쾮쾯쾱쾲쾳쾴쾵쾶쾷쾸쾹쾺쾻쾼쾽쾾쾿쿀쿁쿂쿃쿅쿆쿇쿈쿉쿊쿋깹깻깼깽꺄꺅꺌꺼꺽꺾껀껄껌껍껏껐껑께껙껜껨껫껭껴껸껼꼇꼈꼍꼐꼬꼭꼰꼲꼴꼼꼽꼿꽁꽂꽃꽈꽉꽐꽜꽝꽤꽥꽹꾀꾄꾈꾐꾑꾕꾜꾸꾹꾼꿀꿇꿈꿉꿋꿍꿎꿔꿜꿨꿩꿰꿱꿴꿸뀀뀁뀄뀌뀐뀔뀜뀝뀨끄끅끈끊끌끎끓끔끕끗끙�\".split(\"\");\nfor(j = 0; j != D[178].length; ++j) if(D[178][j].charCodeAt(0) !== 0xFFFD) { e[D[178][j]] = 45568 + j; d[45568 + j] = D[178][j];}\nD[179] = \"�����������������������������������������������������������������쿌쿍쿎쿏쿐쿑쿒쿓쿔쿕쿖쿗쿘쿙쿚쿛쿜쿝쿞쿟쿢쿣쿥쿦쿧쿩������쿪쿫쿬쿭쿮쿯쿲쿴쿶쿷쿸쿹쿺쿻쿽쿾쿿퀁퀂퀃퀅퀆퀇퀈퀉퀊������퀋퀌퀍퀎퀏퀐퀒퀓퀔퀕퀖퀗퀙퀚퀛퀜퀝퀞퀟퀠퀡퀢퀣퀤퀥퀦퀧퀨퀩퀪퀫퀬끝끼끽낀낄낌낍낏낑나낙낚난낟날낡낢남납낫났낭낮낯낱낳내낵낸낼냄냅냇냈냉냐냑냔냘냠냥너넉넋넌널넒넓넘넙넛넜넝넣네넥넨넬넴넵넷넸넹녀녁년녈념녑녔녕녘녜녠노녹논놀놂놈놉놋농높놓놔놘놜놨뇌뇐뇔뇜뇝�\".split(\"\");\nfor(j = 0; j != D[179].length; ++j) if(D[179][j].charCodeAt(0) !== 0xFFFD) { e[D[179][j]] = 45824 + j; d[45824 + j] = D[179][j];}\nD[180] = \"�����������������������������������������������������������������퀮퀯퀰퀱퀲퀳퀶퀷퀹퀺퀻퀽퀾퀿큀큁큂큃큆큈큊큋큌큍큎큏������큑큒큓큕큖큗큙큚큛큜큝큞큟큡큢큣큤큥큦큧큨큩큪큫큮큯������큱큲큳큵큶큷큸큹큺큻큾큿킀킂킃킄킅킆킇킈킉킊킋킌킍킎킏킐킑킒킓킔뇟뇨뇩뇬뇰뇹뇻뇽누눅눈눋눌눔눕눗눙눠눴눼뉘뉜뉠뉨뉩뉴뉵뉼늄늅늉느늑는늘늙늚늠늡늣능늦늪늬늰늴니닉닌닐닒님닙닛닝닢다닥닦단닫달닭닮닯닳담답닷닸당닺닻닿대댁댄댈댐댑댓댔댕댜더덕덖던덛덜덞덟덤덥�\".split(\"\");\nfor(j = 0; j != D[180].length; ++j) if(D[180][j].charCodeAt(0) !== 0xFFFD) { e[D[180][j]] = 46080 + j; d[46080 + j] = D[180][j];}\nD[181] = \"�����������������������������������������������������������������킕킖킗킘킙킚킛킜킝킞킟킠킡킢킣킦킧킩킪킫킭킮킯킰킱킲������킳킶킸킺킻킼킽킾킿탂탃탅탆탇탊탋탌탍탎탏탒탖탗탘탙탚������탛탞탟탡탢탣탥탦탧탨탩탪탫탮탲탳탴탵탶탷탹탺탻탼탽탾탿턀턁턂턃턄덧덩덫덮데덱덴델뎀뎁뎃뎄뎅뎌뎐뎔뎠뎡뎨뎬도독돈돋돌돎돐돔돕돗동돛돝돠돤돨돼됐되된될됨됩됫됴두둑둔둘둠둡둣둥둬뒀뒈뒝뒤뒨뒬뒵뒷뒹듀듄듈듐듕드득든듣들듦듬듭듯등듸디딕딘딛딜딤딥딧딨딩딪따딱딴딸�\".split(\"\");\nfor(j = 0; j != D[181].length; ++j) if(D[181][j].charCodeAt(0) !== 0xFFFD) { e[D[181][j]] = 46336 + j; d[46336 + j] = D[181][j];}\nD[182] = \"�����������������������������������������������������������������턅턆턇턈턉턊턋턌턎턏턐턑턒턓턔턕턖턗턘턙턚턛턜턝턞턟������턠턡턢턣턤턥턦턧턨턩턪턫턬턭턮턯턲턳턵턶턷턹턻턼턽턾������턿텂텆텇텈텉텊텋텎텏텑텒텓텕텖텗텘텙텚텛텞텠텢텣텤텥텦텧텩텪텫텭땀땁땃땄땅땋때땍땐땔땜땝땟땠땡떠떡떤떨떪떫떰떱떳떴떵떻떼떽뗀뗄뗌뗍뗏뗐뗑뗘뗬또똑똔똘똥똬똴뙈뙤뙨뚜뚝뚠뚤뚫뚬뚱뛔뛰뛴뛸뜀뜁뜅뜨뜩뜬뜯뜰뜸뜹뜻띄띈띌띔띕띠띤띨띰띱띳띵라락란랄람랍랏랐랑랒랖랗�\".split(\"\");\nfor(j = 0; j != D[182].length; ++j) if(D[182][j].charCodeAt(0) !== 0xFFFD) { e[D[182][j]] = 46592 + j; d[46592 + j] = D[182][j];}\nD[183] = \"�����������������������������������������������������������������텮텯텰텱텲텳텴텵텶텷텸텹텺텻텽텾텿톀톁톂톃톅톆톇톉톊������톋톌톍톎톏톐톑톒톓톔톕톖톗톘톙톚톛톜톝톞톟톢톣톥톦톧������톩톪톫톬톭톮톯톲톴톶톷톸톹톻톽톾톿퇁퇂퇃퇄퇅퇆퇇퇈퇉퇊퇋퇌퇍퇎퇏래랙랜랠램랩랫랬랭랴략랸럇량러럭런럴럼럽럿렀렁렇레렉렌렐렘렙렛렝려력련렬렴렵렷렸령례롄롑롓로록론롤롬롭롯롱롸롼뢍뢨뢰뢴뢸룀룁룃룅료룐룔룝룟룡루룩룬룰룸룹룻룽뤄뤘뤠뤼뤽륀륄륌륏륑류륙륜률륨륩�\".split(\"\");\nfor(j = 0; j != D[183].length; ++j) if(D[183][j].charCodeAt(0) !== 0xFFFD) { e[D[183][j]] = 46848 + j; d[46848 + j] = D[183][j];}\nD[184] = \"�����������������������������������������������������������������퇐퇑퇒퇓퇔퇕퇖퇗퇙퇚퇛퇜퇝퇞퇟퇠퇡퇢퇣퇤퇥퇦퇧퇨퇩퇪������퇫퇬퇭퇮퇯퇰퇱퇲퇳퇵퇶퇷퇹퇺퇻퇼퇽퇾퇿툀툁툂툃툄툅툆������툈툊툋툌툍툎툏툑툒툓툔툕툖툗툘툙툚툛툜툝툞툟툠툡툢툣툤툥툦툧툨툩륫륭르륵른를름릅릇릉릊릍릎리릭린릴림립릿링마막만많맏말맑맒맘맙맛망맞맡맣매맥맨맬맴맵맷맸맹맺먀먁먈먕머먹먼멀멂멈멉멋멍멎멓메멕멘멜멤멥멧멨멩며멱면멸몃몄명몇몌모목몫몬몰몲몸몹못몽뫄뫈뫘뫙뫼�\".split(\"\");\nfor(j = 0; j != D[184].length; ++j) if(D[184][j].charCodeAt(0) !== 0xFFFD) { e[D[184][j]] = 47104 + j; d[47104 + j] = D[184][j];}\nD[185] = \"�����������������������������������������������������������������툪툫툮툯툱툲툳툵툶툷툸툹툺툻툾퉀퉂퉃퉄퉅퉆퉇퉉퉊퉋퉌������퉍퉎퉏퉐퉑퉒퉓퉔퉕퉖퉗퉘퉙퉚퉛퉝퉞퉟퉠퉡퉢퉣퉥퉦퉧퉨������퉩퉪퉫퉬퉭퉮퉯퉰퉱퉲퉳퉴퉵퉶퉷퉸퉹퉺퉻퉼퉽퉾퉿튂튃튅튆튇튉튊튋튌묀묄묍묏묑묘묜묠묩묫무묵묶문묻물묽묾뭄뭅뭇뭉뭍뭏뭐뭔뭘뭡뭣뭬뮈뮌뮐뮤뮨뮬뮴뮷므믄믈믐믓미믹민믿밀밂밈밉밋밌밍및밑바박밖밗반받발밝밞밟밤밥밧방밭배백밴밸뱀뱁뱃뱄뱅뱉뱌뱍뱐뱝버벅번벋벌벎범법벗�\".split(\"\");\nfor(j = 0; j != D[185].length; ++j) if(D[185][j].charCodeAt(0) !== 0xFFFD) { e[D[185][j]] = 47360 + j; d[47360 + j] = D[185][j];}\nD[186] = \"�����������������������������������������������������������������튍튎튏튒튓튔튖튗튘튙튚튛튝튞튟튡튢튣튥튦튧튨튩튪튫튭������튮튯튰튲튳튴튵튶튷튺튻튽튾틁틃틄틅틆틇틊틌틍틎틏틐틑������틒틓틕틖틗틙틚틛틝틞틟틠틡틢틣틦틧틨틩틪틫틬틭틮틯틲틳틵틶틷틹틺벙벚베벡벤벧벨벰벱벳벴벵벼벽변별볍볏볐병볕볘볜보복볶본볼봄봅봇봉봐봔봤봬뵀뵈뵉뵌뵐뵘뵙뵤뵨부북분붇불붉붊붐붑붓붕붙붚붜붤붰붸뷔뷕뷘뷜뷩뷰뷴뷸븀븃븅브븍븐블븜븝븟비빅빈빌빎빔빕빗빙빚빛빠빡빤�\".split(\"\");\nfor(j = 0; j != D[186].length; ++j) if(D[186][j].charCodeAt(0) !== 0xFFFD) { e[D[186][j]] = 47616 + j; d[47616 + j] = D[186][j];}\nD[187] = \"�����������������������������������������������������������������틻틼틽틾틿팂팄팆팇팈팉팊팋팏팑팒팓팕팗팘팙팚팛팞팢팣������팤팦팧팪팫팭팮팯팱팲팳팴팵팶팷팺팾팿퍀퍁퍂퍃퍆퍇퍈퍉������퍊퍋퍌퍍퍎퍏퍐퍑퍒퍓퍔퍕퍖퍗퍘퍙퍚퍛퍜퍝퍞퍟퍠퍡퍢퍣퍤퍥퍦퍧퍨퍩빨빪빰빱빳빴빵빻빼빽뺀뺄뺌뺍뺏뺐뺑뺘뺙뺨뻐뻑뻔뻗뻘뻠뻣뻤뻥뻬뼁뼈뼉뼘뼙뼛뼜뼝뽀뽁뽄뽈뽐뽑뽕뾔뾰뿅뿌뿍뿐뿔뿜뿟뿡쀼쁑쁘쁜쁠쁨쁩삐삑삔삘삠삡삣삥사삭삯산삳살삵삶삼삽삿샀상샅새색샌샐샘샙샛샜생샤�\".split(\"\");\nfor(j = 0; j != D[187].length; ++j) if(D[187][j].charCodeAt(0) !== 0xFFFD) { e[D[187][j]] = 47872 + j; d[47872 + j] = D[187][j];}\nD[188] = \"�����������������������������������������������������������������퍪퍫퍬퍭퍮퍯퍰퍱퍲퍳퍴퍵퍶퍷퍸퍹퍺퍻퍾퍿펁펂펃펅펆펇������펈펉펊펋펎펒펓펔펕펖펗펚펛펝펞펟펡펢펣펤펥펦펧펪펬펮������펯펰펱펲펳펵펶펷펹펺펻펽펾펿폀폁폂폃폆폇폊폋폌폍폎폏폑폒폓폔폕폖샥샨샬샴샵샷샹섀섄섈섐섕서석섞섟선섣설섦섧섬섭섯섰성섶세섹센셀셈셉셋셌셍셔셕션셜셤셥셧셨셩셰셴셸솅소속솎손솔솖솜솝솟송솥솨솩솬솰솽쇄쇈쇌쇔쇗쇘쇠쇤쇨쇰쇱쇳쇼쇽숀숄숌숍숏숑수숙순숟술숨숩숫숭�\".split(\"\");\nfor(j = 0; j != D[188].length; ++j) if(D[188][j].charCodeAt(0) !== 0xFFFD) { e[D[188][j]] = 48128 + j; d[48128 + j] = D[188][j];}\nD[189] = \"�����������������������������������������������������������������폗폙폚폛폜폝폞폟폠폢폤폥폦폧폨폩폪폫폮폯폱폲폳폵폶폷������폸폹폺폻폾퐀퐂퐃퐄퐅퐆퐇퐉퐊퐋퐌퐍퐎퐏퐐퐑퐒퐓퐔퐕퐖������퐗퐘퐙퐚퐛퐜퐞퐟퐠퐡퐢퐣퐤퐥퐦퐧퐨퐩퐪퐫퐬퐭퐮퐯퐰퐱퐲퐳퐴퐵퐶퐷숯숱숲숴쉈쉐쉑쉔쉘쉠쉥쉬쉭쉰쉴쉼쉽쉿슁슈슉슐슘슛슝스슥슨슬슭슴습슷승시식신싣실싫심십싯싱싶싸싹싻싼쌀쌈쌉쌌쌍쌓쌔쌕쌘쌜쌤쌥쌨쌩썅써썩썬썰썲썸썹썼썽쎄쎈쎌쏀쏘쏙쏜쏟쏠쏢쏨쏩쏭쏴쏵쏸쐈쐐쐤쐬쐰�\".split(\"\");\nfor(j = 0; j != D[189].length; ++j) if(D[189][j].charCodeAt(0) !== 0xFFFD) { e[D[189][j]] = 48384 + j; d[48384 + j] = D[189][j];}\nD[190] = \"�����������������������������������������������������������������퐸퐹퐺퐻퐼퐽퐾퐿푁푂푃푅푆푇푈푉푊푋푌푍푎푏푐푑푒푓������푔푕푖푗푘푙푚푛푝푞푟푡푢푣푥푦푧푨푩푪푫푬푮푰푱푲������푳푴푵푶푷푺푻푽푾풁풃풄풅풆풇풊풌풎풏풐풑풒풓풕풖풗풘풙풚풛풜풝쐴쐼쐽쑈쑤쑥쑨쑬쑴쑵쑹쒀쒔쒜쒸쒼쓩쓰쓱쓴쓸쓺쓿씀씁씌씐씔씜씨씩씬씰씸씹씻씽아악안앉않알앍앎앓암압앗았앙앝앞애액앤앨앰앱앳앴앵야약얀얄얇얌얍얏양얕얗얘얜얠얩어억언얹얻얼얽얾엄업없엇었엉엊엌엎�\".split(\"\");\nfor(j = 0; j != D[190].length; ++j) if(D[190][j].charCodeAt(0) !== 0xFFFD) { e[D[190][j]] = 48640 + j; d[48640 + j] = D[190][j];}\nD[191] = \"�����������������������������������������������������������������풞풟풠풡풢풣풤풥풦풧풨풪풫풬풭풮풯풰풱풲풳풴풵풶풷풸������풹풺풻풼풽풾풿퓀퓁퓂퓃퓄퓅퓆퓇퓈퓉퓊퓋퓍퓎퓏퓑퓒퓓퓕������퓖퓗퓘퓙퓚퓛퓝퓞퓠퓡퓢퓣퓤퓥퓦퓧퓩퓪퓫퓭퓮퓯퓱퓲퓳퓴퓵퓶퓷퓹퓺퓼에엑엔엘엠엡엣엥여역엮연열엶엷염엽엾엿였영옅옆옇예옌옐옘옙옛옜오옥온올옭옮옰옳옴옵옷옹옻와왁완왈왐왑왓왔왕왜왝왠왬왯왱외왹왼욀욈욉욋욍요욕욘욜욤욥욧용우욱운울욹욺움웁웃웅워웍원월웜웝웠웡웨�\".split(\"\");\nfor(j = 0; j != D[191].length; ++j) if(D[191][j].charCodeAt(0) !== 0xFFFD) { e[D[191][j]] = 48896 + j; d[48896 + j] = D[191][j];}\nD[192] = \"�����������������������������������������������������������������퓾퓿픀픁픂픃픅픆픇픉픊픋픍픎픏픐픑픒픓픖픘픙픚픛픜픝������픞픟픠픡픢픣픤픥픦픧픨픩픪픫픬픭픮픯픰픱픲픳픴픵픶픷������픸픹픺픻픾픿핁핂핃핅핆핇핈핉핊핋핎핐핒핓핔핕핖핗핚핛핝핞핟핡핢핣웩웬웰웸웹웽위윅윈윌윔윕윗윙유육윤율윰윱윳융윷으윽은을읊음읍읏응읒읓읔읕읖읗의읜읠읨읫이익인일읽읾잃임입잇있잉잊잎자작잔잖잗잘잚잠잡잣잤장잦재잭잰잴잼잽잿쟀쟁쟈쟉쟌쟎쟐쟘쟝쟤쟨쟬저적전절젊�\".split(\"\");\nfor(j = 0; j != D[192].length; ++j) if(D[192][j].charCodeAt(0) !== 0xFFFD) { e[D[192][j]] = 49152 + j; d[49152 + j] = D[192][j];}\nD[193] = \"�����������������������������������������������������������������핤핦핧핪핬핮핯핰핱핲핳핶핷핹핺핻핽핾핿햀햁햂햃햆햊햋������햌햍햎햏햑햒햓햔햕햖햗햘햙햚햛햜햝햞햟햠햡햢햣햤햦햧������햨햩햪햫햬햭햮햯햰햱햲햳햴햵햶햷햸햹햺햻햼햽햾햿헀헁헂헃헄헅헆헇점접젓정젖제젝젠젤젬젭젯젱져젼졀졈졉졌졍졔조족존졸졺좀좁좃종좆좇좋좌좍좔좝좟좡좨좼좽죄죈죌죔죕죗죙죠죡죤죵주죽준줄줅줆줌줍줏중줘줬줴쥐쥑쥔쥘쥠쥡쥣쥬쥰쥴쥼즈즉즌즐즘즙즛증지직진짇질짊짐집짓�\".split(\"\");\nfor(j = 0; j != D[193].length; ++j) if(D[193][j].charCodeAt(0) !== 0xFFFD) { e[D[193][j]] = 49408 + j; d[49408 + j] = D[193][j];}\nD[194] = \"�����������������������������������������������������������������헊헋헍헎헏헑헓헔헕헖헗헚헜헞헟헠헡헢헣헦헧헩헪헫헭헮������헯헰헱헲헳헶헸헺헻헼헽헾헿혂혃혅혆혇혉혊혋혌혍혎혏혒������혖혗혘혙혚혛혝혞혟혡혢혣혥혦혧혨혩혪혫혬혮혯혰혱혲혳혴혵혶혷혺혻징짖짙짚짜짝짠짢짤짧짬짭짯짰짱째짹짼쨀쨈쨉쨋쨌쨍쨔쨘쨩쩌쩍쩐쩔쩜쩝쩟쩠쩡쩨쩽쪄쪘쪼쪽쫀쫄쫌쫍쫏쫑쫓쫘쫙쫠쫬쫴쬈쬐쬔쬘쬠쬡쭁쭈쭉쭌쭐쭘쭙쭝쭤쭸쭹쮜쮸쯔쯤쯧쯩찌찍찐찔찜찝찡찢찧차착찬찮찰참찹찻�\".split(\"\");\nfor(j = 0; j != D[194].length; ++j) if(D[194][j].charCodeAt(0) !== 0xFFFD) { e[D[194][j]] = 49664 + j; d[49664 + j] = D[194][j];}\nD[195] = \"�����������������������������������������������������������������혽혾혿홁홂홃홄홆홇홊홌홎홏홐홒홓홖홗홙홚홛홝홞홟홠홡������홢홣홤홥홦홨홪홫홬홭홮홯홲홳홵홶홷홸홹홺홻홼홽홾홿횀������횁횂횄횆횇횈횉횊횋횎횏횑횒횓횕횖횗횘횙횚횛횜횞횠횢횣횤횥횦횧횩횪찼창찾채책챈챌챔챕챗챘챙챠챤챦챨챰챵처척천철첨첩첫첬청체첵첸첼쳄쳅쳇쳉쳐쳔쳤쳬쳰촁초촉촌촐촘촙촛총촤촨촬촹최쵠쵤쵬쵭쵯쵱쵸춈추축춘출춤춥춧충춰췄췌췐취췬췰췸췹췻췽츄츈츌츔츙츠측츤츨츰츱츳층�\".split(\"\");\nfor(j = 0; j != D[195].length; ++j) if(D[195][j].charCodeAt(0) !== 0xFFFD) { e[D[195][j]] = 49920 + j; d[49920 + j] = D[195][j];}\nD[196] = \"�����������������������������������������������������������������횫횭횮횯횱횲횳횴횵횶횷횸횺횼횽횾횿훀훁훂훃훆훇훉훊훋������훍훎훏훐훒훓훕훖훘훚훛훜훝훞훟훡훢훣훥훦훧훩훪훫훬훭������훮훯훱훲훳훴훶훷훸훹훺훻훾훿휁휂휃휅휆휇휈휉휊휋휌휍휎휏휐휒휓휔치칙친칟칠칡침칩칫칭카칵칸칼캄캅캇캉캐캑캔캘캠캡캣캤캥캬캭컁커컥컨컫컬컴컵컷컸컹케켁켄켈켐켑켓켕켜켠켤켬켭켯켰켱켸코콕콘콜콤콥콧콩콰콱콴콸쾀쾅쾌쾡쾨쾰쿄쿠쿡쿤쿨쿰쿱쿳쿵쿼퀀퀄퀑퀘퀭퀴퀵퀸퀼�\".split(\"\");\nfor(j = 0; j != D[196].length; ++j) if(D[196][j].charCodeAt(0) !== 0xFFFD) { e[D[196][j]] = 50176 + j; d[50176 + j] = D[196][j];}\nD[197] = \"�����������������������������������������������������������������휕휖휗휚휛휝휞휟휡휢휣휤휥휦휧휪휬휮휯휰휱휲휳휶휷휹������휺휻휽휾휿흀흁흂흃흅흆흈흊흋흌흍흎흏흒흓흕흚흛흜흝흞������흟흢흤흦흧흨흪흫흭흮흯흱흲흳흵흶흷흸흹흺흻흾흿힀힂힃힄힅힆힇힊힋큄큅큇큉큐큔큘큠크큭큰클큼큽킁키킥킨킬킴킵킷킹타탁탄탈탉탐탑탓탔탕태택탠탤탬탭탯탰탱탸턍터턱턴털턺텀텁텃텄텅테텍텐텔템텝텟텡텨텬텼톄톈토톡톤톨톰톱톳통톺톼퇀퇘퇴퇸툇툉툐투툭툰툴툼툽툿퉁퉈퉜�\".split(\"\");\nfor(j = 0; j != D[197].length; ++j) if(D[197][j].charCodeAt(0) !== 0xFFFD) { e[D[197][j]] = 50432 + j; d[50432 + j] = D[197][j];}\nD[198] = \"�����������������������������������������������������������������힍힎힏힑힒힓힔힕힖힗힚힜힞힟힠힡힢힣������������������������������������������������������������������������������퉤튀튁튄튈튐튑튕튜튠튤튬튱트특튼튿틀틂틈틉틋틔틘틜틤틥티틱틴틸팀팁팃팅파팍팎판팔팖팜팝팟팠팡팥패팩팬팰팸팹팻팼팽퍄퍅퍼퍽펀펄펌펍펏펐펑페펙펜펠펨펩펫펭펴편펼폄폅폈평폐폘폡폣포폭폰폴폼폽폿퐁�\".split(\"\");\nfor(j = 0; j != D[198].length; ++j) if(D[198][j].charCodeAt(0) !== 0xFFFD) { e[D[198][j]] = 50688 + j; d[50688 + j] = D[198][j];}\nD[199] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������퐈퐝푀푄표푠푤푭푯푸푹푼푿풀풂품풉풋풍풔풩퓌퓐퓔퓜퓟퓨퓬퓰퓸퓻퓽프픈플픔픕픗피픽핀필핌핍핏핑하학한할핥함합핫항해핵핸핼햄햅햇했행햐향허헉헌헐헒험헙헛헝헤헥헨헬헴헵헷헹혀혁현혈혐협혓혔형혜혠�\".split(\"\");\nfor(j = 0; j != D[199].length; ++j) if(D[199][j].charCodeAt(0) !== 0xFFFD) { e[D[199][j]] = 50944 + j; d[50944 + j] = D[199][j];}\nD[200] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������혤혭호혹혼홀홅홈홉홋홍홑화확환활홧황홰홱홴횃횅회획횐횔횝횟횡효횬횰횹횻후훅훈훌훑훔훗훙훠훤훨훰훵훼훽휀휄휑휘휙휜휠휨휩휫휭휴휵휸휼흄흇흉흐흑흔흖흗흘흙흠흡흣흥흩희흰흴흼흽힁히힉힌힐힘힙힛힝�\".split(\"\");\nfor(j = 0; j != D[200].length; ++j) if(D[200][j].charCodeAt(0) !== 0xFFFD) { e[D[200][j]] = 51200 + j; d[51200 + j] = D[200][j];}\nD[202] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������伽佳假價加可呵哥嘉嫁家暇架枷柯歌珂痂稼苛茄街袈訶賈跏軻迦駕刻却各恪慤殼珏脚覺角閣侃刊墾奸姦干幹懇揀杆柬桿澗癎看磵稈竿簡肝艮艱諫間乫喝曷渴碣竭葛褐蝎鞨勘坎堪嵌感憾戡敢柑橄減甘疳監瞰紺邯鑑鑒龕�\".split(\"\");\nfor(j = 0; j != D[202].length; ++j) if(D[202][j].charCodeAt(0) !== 0xFFFD) { e[D[202][j]] = 51712 + j; d[51712 + j] = D[202][j];}\nD[203] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������匣岬甲胛鉀閘剛堈姜岡崗康强彊慷江畺疆糠絳綱羌腔舡薑襁講鋼降鱇介价個凱塏愷愾慨改槪漑疥皆盖箇芥蓋豈鎧開喀客坑更粳羹醵倨去居巨拒据據擧渠炬祛距踞車遽鉅鋸乾件健巾建愆楗腱虔蹇鍵騫乞傑杰桀儉劍劒檢�\".split(\"\");\nfor(j = 0; j != D[203].length; ++j) if(D[203][j].charCodeAt(0) !== 0xFFFD) { e[D[203][j]] = 51968 + j; d[51968 + j] = D[203][j];}\nD[204] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������瞼鈐黔劫怯迲偈憩揭擊格檄激膈覡隔堅牽犬甄絹繭肩見譴遣鵑抉決潔結缺訣兼慊箝謙鉗鎌京俓倞傾儆勁勍卿坰境庚徑慶憬擎敬景暻更梗涇炅烱璟璥瓊痙硬磬竟競絅經耕耿脛莖警輕逕鏡頃頸驚鯨係啓堺契季屆悸戒桂械�\".split(\"\");\nfor(j = 0; j != D[204].length; ++j) if(D[204][j].charCodeAt(0) !== 0xFFFD) { e[D[204][j]] = 52224 + j; d[52224 + j] = D[204][j];}\nD[205] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������棨溪界癸磎稽系繫繼計誡谿階鷄古叩告呱固姑孤尻庫拷攷故敲暠枯槁沽痼皐睾稿羔考股膏苦苽菰藁蠱袴誥賈辜錮雇顧高鼓哭斛曲梏穀谷鵠困坤崑昆梱棍滾琨袞鯤汨滑骨供公共功孔工恐恭拱控攻珙空蚣貢鞏串寡戈果瓜�\".split(\"\");\nfor(j = 0; j != D[205].length; ++j) if(D[205][j].charCodeAt(0) !== 0xFFFD) { e[D[205][j]] = 52480 + j; d[52480 + j] = D[205][j];}\nD[206] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������科菓誇課跨過鍋顆廓槨藿郭串冠官寬慣棺款灌琯瓘管罐菅觀貫關館刮恝括适侊光匡壙廣曠洸炚狂珖筐胱鑛卦掛罫乖傀塊壞怪愧拐槐魁宏紘肱轟交僑咬喬嬌嶠巧攪敎校橋狡皎矯絞翹膠蕎蛟較轎郊餃驕鮫丘久九仇俱具勾�\".split(\"\");\nfor(j = 0; j != D[206].length; ++j) if(D[206][j].charCodeAt(0) !== 0xFFFD) { e[D[206][j]] = 52736 + j; d[52736 + j] = D[206][j];}\nD[207] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������區口句咎嘔坵垢寇嶇廐懼拘救枸柩構歐毆毬求溝灸狗玖球瞿矩究絿耉臼舅舊苟衢謳購軀逑邱鉤銶駒驅鳩鷗龜國局菊鞠鞫麴君窘群裙軍郡堀屈掘窟宮弓穹窮芎躬倦券勸卷圈拳捲權淃眷厥獗蕨蹶闕机櫃潰詭軌饋句晷歸貴�\".split(\"\");\nfor(j = 0; j != D[207].length; ++j) if(D[207][j].charCodeAt(0) !== 0xFFFD) { e[D[207][j]] = 52992 + j; d[52992 + j] = D[207][j];}\nD[208] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������鬼龜叫圭奎揆槻珪硅窺竅糾葵規赳逵閨勻均畇筠菌鈞龜橘克剋劇戟棘極隙僅劤勤懃斤根槿瑾筋芹菫覲謹近饉契今妗擒昑檎琴禁禽芩衾衿襟金錦伋及急扱汲級給亘兢矜肯企伎其冀嗜器圻基埼夔奇妓寄岐崎己幾忌技旗旣�\".split(\"\");\nfor(j = 0; j != D[208].length; ++j) if(D[208][j].charCodeAt(0) !== 0xFFFD) { e[D[208][j]] = 53248 + j; d[53248 + j] = D[208][j];}\nD[209] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������朞期杞棋棄機欺氣汽沂淇玘琦琪璂璣畸畿碁磯祁祇祈祺箕紀綺羈耆耭肌記譏豈起錡錤飢饑騎騏驥麒緊佶吉拮桔金喫儺喇奈娜懦懶拏拿癩羅蘿螺裸邏那樂洛烙珞落諾酪駱亂卵暖欄煖爛蘭難鸞捏捺南嵐枏楠湳濫男藍襤拉�\".split(\"\");\nfor(j = 0; j != D[209].length; ++j) if(D[209][j].charCodeAt(0) !== 0xFFFD) { e[D[209][j]] = 53504 + j; d[53504 + j] = D[209][j];}\nD[210] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������納臘蠟衲囊娘廊朗浪狼郎乃來內奈柰耐冷女年撚秊念恬拈捻寧寗努勞奴弩怒擄櫓爐瑙盧老蘆虜路露駑魯鷺碌祿綠菉錄鹿論壟弄濃籠聾膿農惱牢磊腦賂雷尿壘屢樓淚漏累縷陋嫩訥杻紐勒肋凜凌稜綾能菱陵尼泥匿溺多茶�\".split(\"\");\nfor(j = 0; j != D[210].length; ++j) if(D[210][j].charCodeAt(0) !== 0xFFFD) { e[D[210][j]] = 53760 + j; d[53760 + j] = D[210][j];}\nD[211] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������丹亶但單團壇彖斷旦檀段湍短端簞緞蛋袒鄲鍛撻澾獺疸達啖坍憺擔曇淡湛潭澹痰聃膽蕁覃談譚錟沓畓答踏遝唐堂塘幢戇撞棠當糖螳黨代垈坮大對岱帶待戴擡玳臺袋貸隊黛宅德悳倒刀到圖堵塗導屠島嶋度徒悼挑掉搗桃�\".split(\"\");\nfor(j = 0; j != D[211].length; ++j) if(D[211][j].charCodeAt(0) !== 0xFFFD) { e[D[211][j]] = 54016 + j; d[54016 + j] = D[211][j];}\nD[212] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������棹櫂淘渡滔濤燾盜睹禱稻萄覩賭跳蹈逃途道都鍍陶韜毒瀆牘犢獨督禿篤纛讀墩惇敦旽暾沌焞燉豚頓乭突仝冬凍動同憧東桐棟洞潼疼瞳童胴董銅兜斗杜枓痘竇荳讀豆逗頭屯臀芚遁遯鈍得嶝橙燈登等藤謄鄧騰喇懶拏癩羅�\".split(\"\");\nfor(j = 0; j != D[212].length; ++j) if(D[212][j].charCodeAt(0) !== 0xFFFD) { e[D[212][j]] = 54272 + j; d[54272 + j] = D[212][j];}\nD[213] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������蘿螺裸邏樂洛烙珞絡落諾酪駱丹亂卵欄欒瀾爛蘭鸞剌辣嵐擥攬欖濫籃纜藍襤覽拉臘蠟廊朗浪狼琅瑯螂郞來崍徠萊冷掠略亮倆兩凉梁樑粮粱糧良諒輛量侶儷勵呂廬慮戾旅櫚濾礪藜蠣閭驢驪麗黎力曆歷瀝礫轢靂憐戀攣漣�\".split(\"\");\nfor(j = 0; j != D[213].length; ++j) if(D[213][j].charCodeAt(0) !== 0xFFFD) { e[D[213][j]] = 54528 + j; d[54528 + j] = D[213][j];}\nD[214] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������煉璉練聯蓮輦連鍊冽列劣洌烈裂廉斂殮濂簾獵令伶囹寧岺嶺怜玲笭羚翎聆逞鈴零靈領齡例澧禮醴隷勞怒撈擄櫓潞瀘爐盧老蘆虜路輅露魯鷺鹵碌祿綠菉錄鹿麓論壟弄朧瀧瓏籠聾儡瀨牢磊賂賚賴雷了僚寮廖料燎療瞭聊蓼�\".split(\"\");\nfor(j = 0; j != D[214].length; ++j) if(D[214][j].charCodeAt(0) !== 0xFFFD) { e[D[214][j]] = 54784 + j; d[54784 + j] = D[214][j];}\nD[215] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������遼鬧龍壘婁屢樓淚漏瘻累縷蔞褸鏤陋劉旒柳榴流溜瀏琉瑠留瘤硫謬類六戮陸侖倫崙淪綸輪律慄栗率隆勒肋凜凌楞稜綾菱陵俚利厘吏唎履悧李梨浬犁狸理璃異痢籬罹羸莉裏裡里釐離鯉吝潾燐璘藺躪隣鱗麟林淋琳臨霖砬�\".split(\"\");\nfor(j = 0; j != D[215].length; ++j) if(D[215][j].charCodeAt(0) !== 0xFFFD) { e[D[215][j]] = 55040 + j; d[55040 + j] = D[215][j];}\nD[216] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������立笠粒摩瑪痲碼磨馬魔麻寞幕漠膜莫邈万卍娩巒彎慢挽晩曼滿漫灣瞞萬蔓蠻輓饅鰻唜抹末沫茉襪靺亡妄忘忙望網罔芒茫莽輞邙埋妹媒寐昧枚梅每煤罵買賣邁魅脈貊陌驀麥孟氓猛盲盟萌冪覓免冕勉棉沔眄眠綿緬面麵滅�\".split(\"\");\nfor(j = 0; j != D[216].length; ++j) if(D[216][j].charCodeAt(0) !== 0xFFFD) { e[D[216][j]] = 55296 + j; d[55296 + j] = D[216][j];}\nD[217] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������蔑冥名命明暝椧溟皿瞑茗蓂螟酩銘鳴袂侮冒募姆帽慕摸摹暮某模母毛牟牡瑁眸矛耗芼茅謀謨貌木沐牧目睦穆鶩歿沒夢朦蒙卯墓妙廟描昴杳渺猫竗苗錨務巫憮懋戊拇撫无楙武毋無珷畝繆舞茂蕪誣貿霧鵡墨默們刎吻問文�\".split(\"\");\nfor(j = 0; j != D[217].length; ++j) if(D[217][j].charCodeAt(0) !== 0xFFFD) { e[D[217][j]] = 55552 + j; d[55552 + j] = D[217][j];}\nD[218] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������汶紊紋聞蚊門雯勿沕物味媚尾嵋彌微未梶楣渼湄眉米美薇謎迷靡黴岷悶愍憫敏旻旼民泯玟珉緡閔密蜜謐剝博拍搏撲朴樸泊珀璞箔粕縛膊舶薄迫雹駁伴半反叛拌搬攀斑槃泮潘班畔瘢盤盼磐磻礬絆般蟠返頒飯勃拔撥渤潑�\".split(\"\");\nfor(j = 0; j != D[218].length; ++j) if(D[218][j].charCodeAt(0) !== 0xFFFD) { e[D[218][j]] = 55808 + j; d[55808 + j] = D[218][j];}\nD[219] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������發跋醱鉢髮魃倣傍坊妨尨幇彷房放方旁昉枋榜滂磅紡肪膀舫芳蒡蚌訪謗邦防龐倍俳北培徘拜排杯湃焙盃背胚裴裵褙賠輩配陪伯佰帛柏栢白百魄幡樊煩燔番磻繁蕃藩飜伐筏罰閥凡帆梵氾汎泛犯範范法琺僻劈壁擘檗璧癖�\".split(\"\");\nfor(j = 0; j != D[219].length; ++j) if(D[219][j].charCodeAt(0) !== 0xFFFD) { e[D[219][j]] = 56064 + j; d[56064 + j] = D[219][j];}\nD[220] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������碧蘗闢霹便卞弁變辨辯邊別瞥鱉鼈丙倂兵屛幷昞昺柄棅炳甁病秉竝輧餠騈保堡報寶普步洑湺潽珤甫菩補褓譜輔伏僕匐卜宓復服福腹茯蔔複覆輹輻馥鰒本乶俸奉封峯峰捧棒烽熢琫縫蓬蜂逢鋒鳳不付俯傅剖副否咐埠夫婦�\".split(\"\");\nfor(j = 0; j != D[220].length; ++j) if(D[220][j].charCodeAt(0) !== 0xFFFD) { e[D[220][j]] = 56320 + j; d[56320 + j] = D[220][j];}\nD[221] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������孚孵富府復扶敷斧浮溥父符簿缶腐腑膚艀芙莩訃負賦賻赴趺部釜阜附駙鳧北分吩噴墳奔奮忿憤扮昐汾焚盆粉糞紛芬賁雰不佛弗彿拂崩朋棚硼繃鵬丕備匕匪卑妃婢庇悲憊扉批斐枇榧比毖毗毘沸泌琵痺砒碑秕秘粃緋翡肥�\".split(\"\");\nfor(j = 0; j != D[221].length; ++j) if(D[221][j].charCodeAt(0) !== 0xFFFD) { e[D[221][j]] = 56576 + j; d[56576 + j] = D[221][j];}\nD[222] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������脾臂菲蜚裨誹譬費鄙非飛鼻嚬嬪彬斌檳殯浜濱瀕牝玭貧賓頻憑氷聘騁乍事些仕伺似使俟僿史司唆嗣四士奢娑寫寺射巳師徙思捨斜斯柶査梭死沙泗渣瀉獅砂社祀祠私篩紗絲肆舍莎蓑蛇裟詐詞謝賜赦辭邪飼駟麝削數朔索�\".split(\"\");\nfor(j = 0; j != D[222].length; ++j) if(D[222][j].charCodeAt(0) !== 0xFFFD) { e[D[222][j]] = 56832 + j; d[56832 + j] = D[222][j];}\nD[223] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������傘刪山散汕珊産疝算蒜酸霰乷撒殺煞薩三參杉森渗芟蔘衫揷澁鈒颯上傷像償商喪嘗孀尙峠常床庠廂想桑橡湘爽牀狀相祥箱翔裳觴詳象賞霜塞璽賽嗇塞穡索色牲生甥省笙墅壻嶼序庶徐恕抒捿敍暑曙書栖棲犀瑞筮絮緖署�\".split(\"\");\nfor(j = 0; j != D[223].length; ++j) if(D[223][j].charCodeAt(0) !== 0xFFFD) { e[D[223][j]] = 57088 + j; d[57088 + j] = D[223][j];}\nD[224] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������胥舒薯西誓逝鋤黍鼠夕奭席惜昔晳析汐淅潟石碩蓆釋錫仙僊先善嬋宣扇敾旋渲煽琁瑄璇璿癬禪線繕羨腺膳船蘚蟬詵跣選銑鐥饍鮮卨屑楔泄洩渫舌薛褻設說雪齧剡暹殲纖蟾贍閃陝攝涉燮葉城姓宬性惺成星晟猩珹盛省筬�\".split(\"\");\nfor(j = 0; j != D[224].length; ++j) if(D[224][j].charCodeAt(0) !== 0xFFFD) { e[D[224][j]] = 57344 + j; d[57344 + j] = D[224][j];}\nD[225] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������聖聲腥誠醒世勢歲洗稅笹細說貰召嘯塑宵小少巢所掃搔昭梳沼消溯瀟炤燒甦疏疎瘙笑篠簫素紹蔬蕭蘇訴逍遡邵銷韶騷俗屬束涑粟續謖贖速孫巽損蓀遜飡率宋悚松淞訟誦送頌刷殺灑碎鎖衰釗修受嗽囚垂壽嫂守岫峀帥愁�\".split(\"\");\nfor(j = 0; j != D[225].length; ++j) if(D[225][j].charCodeAt(0) !== 0xFFFD) { e[D[225][j]] = 57600 + j; d[57600 + j] = D[225][j];}\nD[226] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������戍手授搜收數樹殊水洙漱燧狩獸琇璲瘦睡秀穗竪粹綏綬繡羞脩茱蒐蓚藪袖誰讐輸遂邃酬銖銹隋隧隨雖需須首髓鬚叔塾夙孰宿淑潚熟琡璹肅菽巡徇循恂旬栒楯橓殉洵淳珣盾瞬筍純脣舜荀蓴蕣詢諄醇錞順馴戌術述鉥崇崧�\".split(\"\");\nfor(j = 0; j != D[226].length; ++j) if(D[226][j].charCodeAt(0) !== 0xFFFD) { e[D[226][j]] = 57856 + j; d[57856 + j] = D[226][j];}\nD[227] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������嵩瑟膝蝨濕拾習褶襲丞乘僧勝升承昇繩蠅陞侍匙嘶始媤尸屎屍市弑恃施是時枾柴猜矢示翅蒔蓍視試詩諡豕豺埴寔式息拭植殖湜熄篒蝕識軾食飾伸侁信呻娠宸愼新晨燼申神紳腎臣莘薪藎蜃訊身辛辰迅失室實悉審尋心沁�\".split(\"\");\nfor(j = 0; j != D[227].length; ++j) if(D[227][j].charCodeAt(0) !== 0xFFFD) { e[D[227][j]] = 58112 + j; d[58112 + j] = D[227][j];}\nD[228] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������沈深瀋甚芯諶什十拾雙氏亞俄兒啞娥峨我牙芽莪蛾衙訝阿雅餓鴉鵝堊岳嶽幄惡愕握樂渥鄂鍔顎鰐齷安岸按晏案眼雁鞍顔鮟斡謁軋閼唵岩巖庵暗癌菴闇壓押狎鴨仰央怏昻殃秧鴦厓哀埃崖愛曖涯碍艾隘靄厄扼掖液縊腋額�\".split(\"\");\nfor(j = 0; j != D[228].length; ++j) if(D[228][j].charCodeAt(0) !== 0xFFFD) { e[D[228][j]] = 58368 + j; d[58368 + j] = D[228][j];}\nD[229] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������櫻罌鶯鸚也倻冶夜惹揶椰爺耶若野弱掠略約若葯蒻藥躍亮佯兩凉壤孃恙揚攘敭暘梁楊樣洋瀁煬痒瘍禳穰糧羊良襄諒讓釀陽量養圄御於漁瘀禦語馭魚齬億憶抑檍臆偃堰彦焉言諺孼蘖俺儼嚴奄掩淹嶪業円予余勵呂女如廬�\".split(\"\");\nfor(j = 0; j != D[229].length; ++j) if(D[229][j].charCodeAt(0) !== 0xFFFD) { e[D[229][j]] = 58624 + j; d[58624 + j] = D[229][j];}\nD[230] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������旅歟汝濾璵礖礪與艅茹輿轝閭餘驪麗黎亦力域役易曆歷疫繹譯轢逆驛嚥堧姸娟宴年延憐戀捐挻撚椽沇沿涎涓淵演漣烟然煙煉燃燕璉硏硯秊筵緣練縯聯衍軟輦蓮連鉛鍊鳶列劣咽悅涅烈熱裂說閱厭廉念捻染殮炎焰琰艶苒�\".split(\"\");\nfor(j = 0; j != D[230].length; ++j) if(D[230][j].charCodeAt(0) !== 0xFFFD) { e[D[230][j]] = 58880 + j; d[58880 + j] = D[230][j];}\nD[231] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������簾閻髥鹽曄獵燁葉令囹塋寧嶺嶸影怜映暎楹榮永泳渶潁濚瀛瀯煐營獰玲瑛瑩瓔盈穎纓羚聆英詠迎鈴鍈零霙靈領乂倪例刈叡曳汭濊猊睿穢芮藝蘂禮裔詣譽豫醴銳隸霓預五伍俉傲午吾吳嗚塢墺奧娛寤悟惡懊敖旿晤梧汚澳�\".split(\"\");\nfor(j = 0; j != D[231].length; ++j) if(D[231][j].charCodeAt(0) !== 0xFFFD) { e[D[231][j]] = 59136 + j; d[59136 + j] = D[231][j];}\nD[232] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������烏熬獒筽蜈誤鰲鼇屋沃獄玉鈺溫瑥瘟穩縕蘊兀壅擁瓮甕癰翁邕雍饔渦瓦窩窪臥蛙蝸訛婉完宛梡椀浣玩琓琬碗緩翫脘腕莞豌阮頑曰往旺枉汪王倭娃歪矮外嵬巍猥畏了僚僥凹堯夭妖姚寥寮尿嶢拗搖撓擾料曜樂橈燎燿瑤療�\".split(\"\");\nfor(j = 0; j != D[232].length; ++j) if(D[232][j].charCodeAt(0) !== 0xFFFD) { e[D[232][j]] = 59392 + j; d[59392 + j] = D[232][j];}\nD[233] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������窈窯繇繞耀腰蓼蟯要謠遙遼邀饒慾欲浴縟褥辱俑傭冗勇埇墉容庸慂榕涌湧溶熔瑢用甬聳茸蓉踊鎔鏞龍于佑偶優又友右宇寓尤愚憂旴牛玗瑀盂祐禑禹紆羽芋藕虞迂遇郵釪隅雨雩勖彧旭昱栯煜稶郁頊云暈橒殞澐熉耘芸蕓�\".split(\"\");\nfor(j = 0; j != D[233].length; ++j) if(D[233][j].charCodeAt(0) !== 0xFFFD) { e[D[233][j]] = 59648 + j; d[59648 + j] = D[233][j];}\nD[234] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������運隕雲韻蔚鬱亐熊雄元原員圓園垣媛嫄寃怨愿援沅洹湲源爰猿瑗苑袁轅遠阮院願鴛月越鉞位偉僞危圍委威尉慰暐渭爲瑋緯胃萎葦蔿蝟衛褘謂違韋魏乳侑儒兪劉唯喩孺宥幼幽庾悠惟愈愉揄攸有杻柔柚柳楡楢油洧流游溜�\".split(\"\");\nfor(j = 0; j != D[234].length; ++j) if(D[234][j].charCodeAt(0) !== 0xFFFD) { e[D[234][j]] = 59904 + j; d[59904 + j] = D[234][j];}\nD[235] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������濡猶猷琉瑜由留癒硫紐維臾萸裕誘諛諭踰蹂遊逾遺酉釉鍮類六堉戮毓肉育陸倫允奫尹崙淪潤玧胤贇輪鈗閏律慄栗率聿戎瀜絨融隆垠恩慇殷誾銀隱乙吟淫蔭陰音飮揖泣邑凝應膺鷹依倚儀宜意懿擬椅毅疑矣義艤薏蟻衣誼�\".split(\"\");\nfor(j = 0; j != D[235].length; ++j) if(D[235][j].charCodeAt(0) !== 0xFFFD) { e[D[235][j]] = 60160 + j; d[60160 + j] = D[235][j];}\nD[236] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������議醫二以伊利吏夷姨履已弛彛怡易李梨泥爾珥理異痍痢移罹而耳肄苡荑裏裡貽貳邇里離飴餌匿溺瀷益翊翌翼謚人仁刃印吝咽因姻寅引忍湮燐璘絪茵藺蚓認隣靭靷鱗麟一佚佾壹日溢逸鎰馹任壬妊姙恁林淋稔臨荏賃入卄�\".split(\"\");\nfor(j = 0; j != D[236].length; ++j) if(D[236][j].charCodeAt(0) !== 0xFFFD) { e[D[236][j]] = 60416 + j; d[60416 + j] = D[236][j];}\nD[237] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������立笠粒仍剩孕芿仔刺咨姉姿子字孜恣慈滋炙煮玆瓷疵磁紫者自茨蔗藉諮資雌作勺嚼斫昨灼炸爵綽芍酌雀鵲孱棧殘潺盞岑暫潛箴簪蠶雜丈仗匠場墻壯奬將帳庄張掌暲杖樟檣欌漿牆狀獐璋章粧腸臟臧莊葬蔣薔藏裝贓醬長�\".split(\"\");\nfor(j = 0; j != D[237].length; ++j) if(D[237][j].charCodeAt(0) !== 0xFFFD) { e[D[237][j]] = 60672 + j; d[60672 + j] = D[237][j];}\nD[238] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������障再哉在宰才材栽梓渽滓災縡裁財載齋齎爭箏諍錚佇低儲咀姐底抵杵楮樗沮渚狙猪疽箸紵苧菹著藷詛貯躇這邸雎齟勣吊嫡寂摘敵滴狄炙的積笛籍績翟荻謫賊赤跡蹟迪迹適鏑佃佺傳全典前剪塡塼奠專展廛悛戰栓殿氈澱�\".split(\"\");\nfor(j = 0; j != D[238].length; ++j) if(D[238][j].charCodeAt(0) !== 0xFFFD) { e[D[238][j]] = 60928 + j; d[60928 + j] = D[238][j];}\nD[239] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������煎琠田甸畑癲筌箋箭篆纏詮輾轉鈿銓錢鐫電顚顫餞切截折浙癤竊節絶占岾店漸点粘霑鮎點接摺蝶丁井亭停偵呈姃定幀庭廷征情挺政整旌晶晸柾楨檉正汀淀淨渟湞瀞炡玎珽町睛碇禎程穽精綎艇訂諪貞鄭酊釘鉦鋌錠霆靖�\".split(\"\");\nfor(j = 0; j != D[239].length; ++j) if(D[239][j].charCodeAt(0) !== 0xFFFD) { e[D[239][j]] = 61184 + j; d[61184 + j] = D[239][j];}\nD[240] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������靜頂鼎制劑啼堤帝弟悌提梯濟祭第臍薺製諸蹄醍除際霽題齊俎兆凋助嘲弔彫措操早晁曺曹朝條棗槽漕潮照燥爪璪眺祖祚租稠窕粗糟組繰肇藻蚤詔調趙躁造遭釣阻雕鳥族簇足鏃存尊卒拙猝倧宗從悰慫棕淙琮種終綜縱腫�\".split(\"\");\nfor(j = 0; j != D[240].length; ++j) if(D[240][j].charCodeAt(0) !== 0xFFFD) { e[D[240][j]] = 61440 + j; d[61440 + j] = D[240][j];}\nD[241] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������踪踵鍾鐘佐坐左座挫罪主住侏做姝胄呪周嗾奏宙州廚晝朱柱株注洲湊澍炷珠疇籌紂紬綢舟蛛註誅走躊輳週酎酒鑄駐竹粥俊儁准埈寯峻晙樽浚準濬焌畯竣蠢逡遵雋駿茁中仲衆重卽櫛楫汁葺增憎曾拯烝甑症繒蒸證贈之只�\".split(\"\");\nfor(j = 0; j != D[241].length; ++j) if(D[241][j].charCodeAt(0) !== 0xFFFD) { e[D[241][j]] = 61696 + j; d[61696 + j] = D[241][j];}\nD[242] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������咫地址志持指摯支旨智枝枳止池沚漬知砥祉祗紙肢脂至芝芷蜘誌識贄趾遲直稙稷織職唇嗔塵振搢晉晋桭榛殄津溱珍瑨璡畛疹盡眞瞋秦縉縝臻蔯袗診賑軫辰進鎭陣陳震侄叱姪嫉帙桎瓆疾秩窒膣蛭質跌迭斟朕什執潗緝輯�\".split(\"\");\nfor(j = 0; j != D[242].length; ++j) if(D[242][j].charCodeAt(0) !== 0xFFFD) { e[D[242][j]] = 61952 + j; d[61952 + j] = D[242][j];}\nD[243] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������鏶集徵懲澄且侘借叉嗟嵯差次此磋箚茶蹉車遮捉搾着窄錯鑿齪撰澯燦璨瓚竄簒纂粲纘讚贊鑽餐饌刹察擦札紮僭參塹慘慙懺斬站讒讖倉倡創唱娼廠彰愴敞昌昶暢槍滄漲猖瘡窓脹艙菖蒼債埰寀寨彩採砦綵菜蔡采釵冊柵策�\".split(\"\");\nfor(j = 0; j != D[243].length; ++j) if(D[243][j].charCodeAt(0) !== 0xFFFD) { e[D[243][j]] = 62208 + j; d[62208 + j] = D[243][j];}\nD[244] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������責凄妻悽處倜刺剔尺慽戚拓擲斥滌瘠脊蹠陟隻仟千喘天川擅泉淺玔穿舛薦賤踐遷釧闡阡韆凸哲喆徹撤澈綴輟轍鐵僉尖沾添甛瞻簽籤詹諂堞妾帖捷牒疊睫諜貼輒廳晴淸聽菁請靑鯖切剃替涕滯締諦逮遞體初剿哨憔抄招梢�\".split(\"\");\nfor(j = 0; j != D[244].length; ++j) if(D[244][j].charCodeAt(0) !== 0xFFFD) { e[D[244][j]] = 62464 + j; d[62464 + j] = D[244][j];}\nD[245] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������椒楚樵炒焦硝礁礎秒稍肖艸苕草蕉貂超酢醋醮促囑燭矗蜀觸寸忖村邨叢塚寵悤憁摠總聰蔥銃撮催崔最墜抽推椎楸樞湫皺秋芻萩諏趨追鄒酋醜錐錘鎚雛騶鰍丑畜祝竺筑築縮蓄蹙蹴軸逐春椿瑃出朮黜充忠沖蟲衝衷悴膵萃�\".split(\"\");\nfor(j = 0; j != D[245].length; ++j) if(D[245][j].charCodeAt(0) !== 0xFFFD) { e[D[245][j]] = 62720 + j; d[62720 + j] = D[245][j];}\nD[246] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������贅取吹嘴娶就炊翠聚脆臭趣醉驟鷲側仄厠惻測層侈値嗤峙幟恥梔治淄熾痔痴癡稚穉緇緻置致蚩輜雉馳齒則勅飭親七柒漆侵寢枕沈浸琛砧針鍼蟄秤稱快他咤唾墮妥惰打拖朶楕舵陀馱駝倬卓啄坼度托拓擢晫柝濁濯琢琸託�\".split(\"\");\nfor(j = 0; j != D[246].length; ++j) if(D[246][j].charCodeAt(0) !== 0xFFFD) { e[D[246][j]] = 62976 + j; d[62976 + j] = D[246][j];}\nD[247] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������鐸呑嘆坦彈憚歎灘炭綻誕奪脫探眈耽貪塔搭榻宕帑湯糖蕩兌台太怠態殆汰泰笞胎苔跆邰颱宅擇澤撑攄兎吐土討慟桶洞痛筒統通堆槌腿褪退頹偸套妬投透鬪慝特闖坡婆巴把播擺杷波派爬琶破罷芭跛頗判坂板版瓣販辦鈑�\".split(\"\");\nfor(j = 0; j != D[247].length; ++j) if(D[247][j].charCodeAt(0) !== 0xFFFD) { e[D[247][j]] = 63232 + j; d[63232 + j] = D[247][j];}\nD[248] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������阪八叭捌佩唄悖敗沛浿牌狽稗覇貝彭澎烹膨愎便偏扁片篇編翩遍鞭騙貶坪平枰萍評吠嬖幣廢弊斃肺蔽閉陛佈包匍匏咆哺圃布怖抛抱捕暴泡浦疱砲胞脯苞葡蒲袍褒逋鋪飽鮑幅暴曝瀑爆輻俵剽彪慓杓標漂瓢票表豹飇飄驃�\".split(\"\");\nfor(j = 0; j != D[248].length; ++j) if(D[248][j].charCodeAt(0) !== 0xFFFD) { e[D[248][j]] = 63488 + j; d[63488 + j] = D[248][j];}\nD[249] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������品稟楓諷豊風馮彼披疲皮被避陂匹弼必泌珌畢疋筆苾馝乏逼下何厦夏廈昰河瑕荷蝦賀遐霞鰕壑學虐謔鶴寒恨悍旱汗漢澣瀚罕翰閑閒限韓割轄函含咸啣喊檻涵緘艦銜陷鹹合哈盒蛤閤闔陜亢伉姮嫦巷恒抗杭桁沆港缸肛航�\".split(\"\");\nfor(j = 0; j != D[249].length; ++j) if(D[249][j].charCodeAt(0) !== 0xFFFD) { e[D[249][j]] = 63744 + j; d[63744 + j] = D[249][j];}\nD[250] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������行降項亥偕咳垓奚孩害懈楷海瀣蟹解該諧邂駭骸劾核倖幸杏荇行享向嚮珦鄕響餉饗香噓墟虛許憲櫶獻軒歇險驗奕爀赫革俔峴弦懸晛泫炫玄玹現眩睍絃絢縣舷衒見賢鉉顯孑穴血頁嫌俠協夾峽挾浹狹脅脇莢鋏頰亨兄刑型�\".split(\"\");\nfor(j = 0; j != D[250].length; ++j) if(D[250][j].charCodeAt(0) !== 0xFFFD) { e[D[250][j]] = 64000 + j; d[64000 + j] = D[250][j];}\nD[251] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������形泂滎瀅灐炯熒珩瑩荊螢衡逈邢鎣馨兮彗惠慧暳蕙蹊醯鞋乎互呼壕壺好岵弧戶扈昊晧毫浩淏湖滸澔濠濩灝狐琥瑚瓠皓祜糊縞胡芦葫蒿虎號蝴護豪鎬頀顥惑或酷婚昏混渾琿魂忽惚笏哄弘汞泓洪烘紅虹訌鴻化和嬅樺火畵�\".split(\"\");\nfor(j = 0; j != D[251].length; ++j) if(D[251][j].charCodeAt(0) !== 0xFFFD) { e[D[251][j]] = 64256 + j; d[64256 + j] = D[251][j];}\nD[252] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������禍禾花華話譁貨靴廓擴攫確碻穫丸喚奐宦幻患換歡晥桓渙煥環紈還驩鰥活滑猾豁闊凰幌徨恍惶愰慌晃晄榥況湟滉潢煌璜皇篁簧荒蝗遑隍黃匯回廻徊恢悔懷晦會檜淮澮灰獪繪膾茴蛔誨賄劃獲宖橫鐄哮嚆孝效斅曉梟涍淆�\".split(\"\");\nfor(j = 0; j != D[252].length; ++j) if(D[252][j].charCodeAt(0) !== 0xFFFD) { e[D[252][j]] = 64512 + j; d[64512 + j] = D[252][j];}\nD[253] = \"�����������������������������������������������������������������������������������������������������������������������������������������������������������������爻肴酵驍侯候厚后吼喉嗅帿後朽煦珝逅勛勳塤壎焄熏燻薰訓暈薨喧暄煊萱卉喙毁彙徽揮暉煇諱輝麾休携烋畦虧恤譎鷸兇凶匈洶胸黑昕欣炘痕吃屹紇訖欠欽歆吸恰洽翕興僖凞喜噫囍姬嬉希憙憘戱晞曦熙熹熺犧禧稀羲詰�\".split(\"\");\nfor(j = 0; j != D[253].length; ++j) if(D[253][j].charCodeAt(0) !== 0xFFFD) { e[D[253][j]] = 64768 + j; d[64768 + j] = D[253][j];}\nreturn {\"enc\": e, \"dec\": d }; })();\ncptable[950] = (function(){ var d = [], e = {}, D = [], j;\nD[0] = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~��������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[0].length; ++j) if(D[0][j].charCodeAt(0) !== 0xFFFD) { e[D[0][j]] = 0 + j; d[0 + j] = D[0][j];}\nD[161] = \"����������������������������������������������������������������　，、。．‧；：？！︰…‥﹐﹑﹒·﹔﹕﹖﹗｜–︱—︳╴︴﹏（）︵︶｛｝︷︸〔〕︹︺【】︻︼《》︽︾〈〉︿﹀「」﹁﹂『』﹃﹄﹙﹚����������������������������������﹛﹜﹝﹞‘’“”〝〞‵′＃＆＊※§〃○●△▲◎☆★◇◆□■▽▼㊣℅¯￣＿ˍ﹉﹊﹍﹎﹋﹌﹟﹠﹡＋－×÷±√＜＞＝≦≧≠∞≒≡﹢﹣﹤﹥﹦～∩∪⊥∠∟⊿㏒㏑∫∮∵∴♀♂⊕⊙↑↓←→↖↗↙↘∥∣／�\".split(\"\");\nfor(j = 0; j != D[161].length; ++j) if(D[161][j].charCodeAt(0) !== 0xFFFD) { e[D[161][j]] = 41216 + j; d[41216 + j] = D[161][j];}\nD[162] = \"����������������������������������������������������������������＼∕﹨＄￥〒￠￡％＠℃℉﹩﹪﹫㏕㎜㎝㎞㏎㎡㎎㎏㏄°兙兛兞兝兡兣嗧瓩糎▁▂▃▄▅▆▇█▏▎▍▌▋▊▉┼┴┬┤├▔─│▕┌┐└┘╭����������������������������������╮╰╯═╞╪╡◢◣◥◤╱╲╳０１２３４５６７８９ⅠⅡⅢⅣⅤⅥⅦⅧⅨⅩ〡〢〣〤〥〦〧〨〩十卄卅ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖ�\".split(\"\");\nfor(j = 0; j != D[162].length; ++j) if(D[162][j].charCodeAt(0) !== 0xFFFD) { e[D[162][j]] = 41472 + j; d[41472 + j] = D[162][j];}\nD[163] = \"����������������������������������������������������������������ｗｘｙｚΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡΣΤΥΦΧΨΩαβγδεζηθικλμνξοπρστυφχψωㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏ����������������������������������ㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩ˙ˉˊˇˋ���������������������������������€������������������������������\".split(\"\");\nfor(j = 0; j != D[163].length; ++j) if(D[163][j].charCodeAt(0) !== 0xFFFD) { e[D[163][j]] = 41728 + j; d[41728 + j] = D[163][j];}\nD[164] = \"����������������������������������������������������������������一乙丁七乃九了二人儿入八几刀刁力匕十卜又三下丈上丫丸凡久么也乞于亡兀刃勺千叉口土士夕大女子孑孓寸小尢尸山川工己已巳巾干廾弋弓才����������������������������������丑丐不中丰丹之尹予云井互五亢仁什仃仆仇仍今介仄元允內六兮公冗凶分切刈勻勾勿化匹午升卅卞厄友及反壬天夫太夭孔少尤尺屯巴幻廿弔引心戈戶手扎支文斗斤方日曰月木欠止歹毋比毛氏水火爪父爻片牙牛犬王丙�\".split(\"\");\nfor(j = 0; j != D[164].length; ++j) if(D[164][j].charCodeAt(0) !== 0xFFFD) { e[D[164][j]] = 41984 + j; d[41984 + j] = D[164][j];}\nD[165] = \"����������������������������������������������������������������世丕且丘主乍乏乎以付仔仕他仗代令仙仞充兄冉冊冬凹出凸刊加功包匆北匝仟半卉卡占卯卮去可古右召叮叩叨叼司叵叫另只史叱台句叭叻四囚外����������������������������������央失奴奶孕它尼巨巧左市布平幼弁弘弗必戊打扔扒扑斥旦朮本未末札正母民氐永汁汀氾犯玄玉瓜瓦甘生用甩田由甲申疋白皮皿目矛矢石示禾穴立丞丟乒乓乩亙交亦亥仿伉伙伊伕伍伐休伏仲件任仰仳份企伋光兇兆先全�\".split(\"\");\nfor(j = 0; j != D[165].length; ++j) if(D[165][j].charCodeAt(0) !== 0xFFFD) { e[D[165][j]] = 42240 + j; d[42240 + j] = D[165][j];}\nD[166] = \"����������������������������������������������������������������共再冰列刑划刎刖劣匈匡匠印危吉吏同吊吐吁吋各向名合吃后吆吒因回囝圳地在圭圬圯圩夙多夷夸妄奸妃好她如妁字存宇守宅安寺尖屹州帆并年����������������������������������式弛忙忖戎戌戍成扣扛托收早旨旬旭曲曳有朽朴朱朵次此死氖汝汗汙江池汐汕污汛汍汎灰牟牝百竹米糸缶羊羽老考而耒耳聿肉肋肌臣自至臼舌舛舟艮色艾虫血行衣西阡串亨位住佇佗佞伴佛何估佐佑伽伺伸佃佔似但佣�\".split(\"\");\nfor(j = 0; j != D[166].length; ++j) if(D[166][j].charCodeAt(0) !== 0xFFFD) { e[D[166][j]] = 42496 + j; d[42496 + j] = D[166][j];}\nD[167] = \"����������������������������������������������������������������作你伯低伶余佝佈佚兌克免兵冶冷別判利刪刨劫助努劬匣即卵吝吭吞吾否呎吧呆呃吳呈呂君吩告吹吻吸吮吵吶吠吼呀吱含吟听囪困囤囫坊坑址坍����������������������������������均坎圾坐坏圻壯夾妝妒妨妞妣妙妖妍妤妓妊妥孝孜孚孛完宋宏尬局屁尿尾岐岑岔岌巫希序庇床廷弄弟彤形彷役忘忌志忍忱快忸忪戒我抄抗抖技扶抉扭把扼找批扳抒扯折扮投抓抑抆改攻攸旱更束李杏材村杜杖杞杉杆杠�\".split(\"\");\nfor(j = 0; j != D[167].length; ++j) if(D[167][j].charCodeAt(0) !== 0xFFFD) { e[D[167][j]] = 42752 + j; d[42752 + j] = D[167][j];}\nD[168] = \"����������������������������������������������������������������杓杗步每求汞沙沁沈沉沅沛汪決沐汰沌汨沖沒汽沃汲汾汴沆汶沍沔沘沂灶灼災灸牢牡牠狄狂玖甬甫男甸皂盯矣私秀禿究系罕肖肓肝肘肛肚育良芒����������������������������������芋芍見角言谷豆豕貝赤走足身車辛辰迂迆迅迄巡邑邢邪邦那酉釆里防阮阱阪阬並乖乳事些亞享京佯依侍佳使佬供例來侃佰併侈佩佻侖佾侏侑佺兔兒兕兩具其典冽函刻券刷刺到刮制剁劾劻卒協卓卑卦卷卸卹取叔受味呵�\".split(\"\");\nfor(j = 0; j != D[168].length; ++j) if(D[168][j].charCodeAt(0) !== 0xFFFD) { e[D[168][j]] = 43008 + j; d[43008 + j] = D[168][j];}\nD[169] = \"����������������������������������������������������������������咖呸咕咀呻呷咄咒咆呼咐呱呶和咚呢周咋命咎固垃坷坪坩坡坦坤坼夜奉奇奈奄奔妾妻委妹妮姑姆姐姍始姓姊妯妳姒姅孟孤季宗定官宜宙宛尚屈居����������������������������������屆岷岡岸岩岫岱岳帘帚帖帕帛帑幸庚店府底庖延弦弧弩往征彿彼忝忠忽念忿怏怔怯怵怖怪怕怡性怩怫怛或戕房戾所承拉拌拄抿拂抹拒招披拓拔拋拈抨抽押拐拙拇拍抵拚抱拘拖拗拆抬拎放斧於旺昔易昌昆昂明昀昏昕昊�\".split(\"\");\nfor(j = 0; j != D[169].length; ++j) if(D[169][j].charCodeAt(0) !== 0xFFFD) { e[D[169][j]] = 43264 + j; d[43264 + j] = D[169][j];}\nD[170] = \"����������������������������������������������������������������昇服朋杭枋枕東果杳杷枇枝林杯杰板枉松析杵枚枓杼杪杲欣武歧歿氓氛泣注泳沱泌泥河沽沾沼波沫法泓沸泄油況沮泗泅泱沿治泡泛泊沬泯泜泖泠����������������������������������炕炎炒炊炙爬爭爸版牧物狀狎狙狗狐玩玨玟玫玥甽疝疙疚的盂盲直知矽社祀祁秉秈空穹竺糾罔羌羋者肺肥肢肱股肫肩肴肪肯臥臾舍芳芝芙芭芽芟芹花芬芥芯芸芣芰芾芷虎虱初表軋迎返近邵邸邱邶采金長門阜陀阿阻附�\".split(\"\");\nfor(j = 0; j != D[170].length; ++j) if(D[170][j].charCodeAt(0) !== 0xFFFD) { e[D[170][j]] = 43520 + j; d[43520 + j] = D[170][j];}\nD[171] = \"����������������������������������������������������������������陂隹雨青非亟亭亮信侵侯便俠俑俏保促侶俘俟俊俗侮俐俄係俚俎俞侷兗冒冑冠剎剃削前剌剋則勇勉勃勁匍南卻厚叛咬哀咨哎哉咸咦咳哇哂咽咪品����������������������������������哄哈咯咫咱咻咩咧咿囿垂型垠垣垢城垮垓奕契奏奎奐姜姘姿姣姨娃姥姪姚姦威姻孩宣宦室客宥封屎屏屍屋峙峒巷帝帥帟幽庠度建弈弭彥很待徊律徇後徉怒思怠急怎怨恍恰恨恢恆恃恬恫恪恤扁拜挖按拼拭持拮拽指拱拷�\".split(\"\");\nfor(j = 0; j != D[171].length; ++j) if(D[171][j].charCodeAt(0) !== 0xFFFD) { e[D[171][j]] = 43776 + j; d[43776 + j] = D[171][j];}\nD[172] = \"����������������������������������������������������������������拯括拾拴挑挂政故斫施既春昭映昧是星昨昱昤曷柿染柱柔某柬架枯柵柩柯柄柑枴柚查枸柏柞柳枰柙柢柝柒歪殃殆段毒毗氟泉洋洲洪流津洌洱洞洗����������������������������������活洽派洶洛泵洹洧洸洩洮洵洎洫炫為炳炬炯炭炸炮炤爰牲牯牴狩狠狡玷珊玻玲珍珀玳甚甭畏界畎畋疫疤疥疢疣癸皆皇皈盈盆盃盅省盹相眉看盾盼眇矜砂研砌砍祆祉祈祇禹禺科秒秋穿突竿竽籽紂紅紀紉紇約紆缸美羿耄�\".split(\"\");\nfor(j = 0; j != D[172].length; ++j) if(D[172][j].charCodeAt(0) !== 0xFFFD) { e[D[172][j]] = 44032 + j; d[44032 + j] = D[172][j];}\nD[173] = \"����������������������������������������������������������������耐耍耑耶胖胥胚胃胄背胡胛胎胞胤胝致舢苧范茅苣苛苦茄若茂茉苒苗英茁苜苔苑苞苓苟苯茆虐虹虻虺衍衫要觔計訂訃貞負赴赳趴軍軌述迦迢迪迥����������������������������������迭迫迤迨郊郎郁郃酋酊重閂限陋陌降面革韋韭音頁風飛食首香乘亳倌倍倣俯倦倥俸倩倖倆值借倚倒們俺倀倔倨俱倡個候倘俳修倭倪俾倫倉兼冤冥冢凍凌准凋剖剜剔剛剝匪卿原厝叟哨唐唁唷哼哥哲唆哺唔哩哭員唉哮哪�\".split(\"\");\nfor(j = 0; j != D[173].length; ++j) if(D[173][j].charCodeAt(0) !== 0xFFFD) { e[D[173][j]] = 44288 + j; d[44288 + j] = D[173][j];}\nD[174] = \"����������������������������������������������������������������哦唧唇哽唏圃圄埂埔埋埃堉夏套奘奚娑娘娜娟娛娓姬娠娣娩娥娌娉孫屘宰害家宴宮宵容宸射屑展屐峭峽峻峪峨峰島崁峴差席師庫庭座弱徒徑徐恙����������������������������������恣恥恐恕恭恩息悄悟悚悍悔悌悅悖扇拳挈拿捎挾振捕捂捆捏捉挺捐挽挪挫挨捍捌效敉料旁旅時晉晏晃晒晌晅晁書朔朕朗校核案框桓根桂桔栩梳栗桌桑栽柴桐桀格桃株桅栓栘桁殊殉殷氣氧氨氦氤泰浪涕消涇浦浸海浙涓�\".split(\"\");\nfor(j = 0; j != D[174].length; ++j) if(D[174][j].charCodeAt(0) !== 0xFFFD) { e[D[174][j]] = 44544 + j; d[44544 + j] = D[174][j];}\nD[175] = \"����������������������������������������������������������������浬涉浮浚浴浩涌涊浹涅浥涔烊烘烤烙烈烏爹特狼狹狽狸狷玆班琉珮珠珪珞畔畝畜畚留疾病症疲疳疽疼疹痂疸皋皰益盍盎眩真眠眨矩砰砧砸砝破砷����������������������������������砥砭砠砟砲祕祐祠祟祖神祝祗祚秤秣秧租秦秩秘窄窈站笆笑粉紡紗紋紊素索純紐紕級紜納紙紛缺罟羔翅翁耆耘耕耙耗耽耿胱脂胰脅胭胴脆胸胳脈能脊胼胯臭臬舀舐航舫舨般芻茫荒荔荊茸荐草茵茴荏茲茹茶茗荀茱茨荃�\".split(\"\");\nfor(j = 0; j != D[175].length; ++j) if(D[175][j].charCodeAt(0) !== 0xFFFD) { e[D[175][j]] = 44800 + j; d[44800 + j] = D[175][j];}\nD[176] = \"����������������������������������������������������������������虔蚊蚪蚓蚤蚩蚌蚣蚜衰衷袁袂衽衹記訐討訌訕訊託訓訖訏訑豈豺豹財貢起躬軒軔軏辱送逆迷退迺迴逃追逅迸邕郡郝郢酒配酌釘針釗釜釙閃院陣陡����������������������������������陛陝除陘陞隻飢馬骨高鬥鬲鬼乾偺偽停假偃偌做偉健偶偎偕偵側偷偏倏偯偭兜冕凰剪副勒務勘動匐匏匙匿區匾參曼商啪啦啄啞啡啃啊唱啖問啕唯啤唸售啜唬啣唳啁啗圈國圉域堅堊堆埠埤基堂堵執培夠奢娶婁婉婦婪婀�\".split(\"\");\nfor(j = 0; j != D[176].length; ++j) if(D[176][j].charCodeAt(0) !== 0xFFFD) { e[D[176][j]] = 45056 + j; d[45056 + j] = D[176][j];}\nD[177] = \"����������������������������������������������������������������娼婢婚婆婊孰寇寅寄寂宿密尉專將屠屜屝崇崆崎崛崖崢崑崩崔崙崤崧崗巢常帶帳帷康庸庶庵庾張強彗彬彩彫得徙從徘御徠徜恿患悉悠您惋悴惦悽����������������������������������情悻悵惜悼惘惕惆惟悸惚惇戚戛扈掠控捲掖探接捷捧掘措捱掩掉掃掛捫推掄授掙採掬排掏掀捻捩捨捺敝敖救教敗啟敏敘敕敔斜斛斬族旋旌旎晝晚晤晨晦晞曹勗望梁梯梢梓梵桿桶梱梧梗械梃棄梭梆梅梔條梨梟梡梂欲殺�\".split(\"\");\nfor(j = 0; j != D[177].length; ++j) if(D[177][j].charCodeAt(0) !== 0xFFFD) { e[D[177][j]] = 45312 + j; d[45312 + j] = D[177][j];}\nD[178] = \"����������������������������������������������������������������毫毬氫涎涼淳淙液淡淌淤添淺清淇淋涯淑涮淞淹涸混淵淅淒渚涵淚淫淘淪深淮淨淆淄涪淬涿淦烹焉焊烽烯爽牽犁猜猛猖猓猙率琅琊球理現琍瓠瓶����������������������������������瓷甜產略畦畢異疏痔痕疵痊痍皎盔盒盛眷眾眼眶眸眺硫硃硎祥票祭移窒窕笠笨笛第符笙笞笮粒粗粕絆絃統紮紹紼絀細紳組累終紲紱缽羞羚翌翎習耜聊聆脯脖脣脫脩脰脤舂舵舷舶船莎莞莘荸莢莖莽莫莒莊莓莉莠荷荻荼�\".split(\"\");\nfor(j = 0; j != D[178].length; ++j) if(D[178][j].charCodeAt(0) !== 0xFFFD) { e[D[178][j]] = 45568 + j; d[45568 + j] = D[178][j];}\nD[179] = \"����������������������������������������������������������������莆莧處彪蛇蛀蚶蛄蚵蛆蛋蚱蚯蛉術袞袈被袒袖袍袋覓規訪訝訣訥許設訟訛訢豉豚販責貫貨貪貧赧赦趾趺軛軟這逍通逗連速逝逐逕逞造透逢逖逛途����������������������������������部郭都酗野釵釦釣釧釭釩閉陪陵陳陸陰陴陶陷陬雀雪雩章竟頂頃魚鳥鹵鹿麥麻傢傍傅備傑傀傖傘傚最凱割剴創剩勞勝勛博厥啻喀喧啼喊喝喘喂喜喪喔喇喋喃喳單喟唾喲喚喻喬喱啾喉喫喙圍堯堪場堤堰報堡堝堠壹壺奠�\".split(\"\");\nfor(j = 0; j != D[179].length; ++j) if(D[179][j].charCodeAt(0) !== 0xFFFD) { e[D[179][j]] = 45824 + j; d[45824 + j] = D[179][j];}\nD[180] = \"����������������������������������������������������������������婷媚婿媒媛媧孳孱寒富寓寐尊尋就嵌嵐崴嵇巽幅帽幀幃幾廊廁廂廄弼彭復循徨惑惡悲悶惠愜愣惺愕惰惻惴慨惱愎惶愉愀愒戟扉掣掌描揀揩揉揆揍����������������������������������插揣提握揖揭揮捶援揪換摒揚揹敞敦敢散斑斐斯普晰晴晶景暑智晾晷曾替期朝棺棕棠棘棗椅棟棵森棧棹棒棲棣棋棍植椒椎棉棚楮棻款欺欽殘殖殼毯氮氯氬港游湔渡渲湧湊渠渥渣減湛湘渤湖湮渭渦湯渴湍渺測湃渝渾滋�\".split(\"\");\nfor(j = 0; j != D[180].length; ++j) if(D[180][j].charCodeAt(0) !== 0xFFFD) { e[D[180][j]] = 46080 + j; d[46080 + j] = D[180][j];}\nD[181] = \"����������������������������������������������������������������溉渙湎湣湄湲湩湟焙焚焦焰無然煮焜牌犄犀猶猥猴猩琺琪琳琢琥琵琶琴琯琛琦琨甥甦畫番痢痛痣痙痘痞痠登發皖皓皴盜睏短硝硬硯稍稈程稅稀窘����������������������������������窗窖童竣等策筆筐筒答筍筋筏筑粟粥絞結絨絕紫絮絲絡給絢絰絳善翔翕耋聒肅腕腔腋腑腎脹腆脾腌腓腴舒舜菩萃菸萍菠菅萋菁華菱菴著萊菰萌菌菽菲菊萸萎萄菜萇菔菟虛蛟蛙蛭蛔蛛蛤蛐蛞街裁裂袱覃視註詠評詞証詁�\".split(\"\");\nfor(j = 0; j != D[181].length; ++j) if(D[181][j].charCodeAt(0) !== 0xFFFD) { e[D[181][j]] = 46336 + j; d[46336 + j] = D[181][j];}\nD[182] = \"����������������������������������������������������������������詔詛詐詆訴診訶詖象貂貯貼貳貽賁費賀貴買貶貿貸越超趁跎距跋跚跑跌跛跆軻軸軼辜逮逵週逸進逶鄂郵鄉郾酣酥量鈔鈕鈣鈉鈞鈍鈐鈇鈑閔閏開閑����������������������������������間閒閎隊階隋陽隅隆隍陲隄雁雅雄集雇雯雲韌項順須飧飪飯飩飲飭馮馭黃黍黑亂傭債傲傳僅傾催傷傻傯僇剿剷剽募勦勤勢勣匯嗟嗨嗓嗦嗎嗜嗇嗑嗣嗤嗯嗚嗡嗅嗆嗥嗉園圓塞塑塘塗塚塔填塌塭塊塢塒塋奧嫁嫉嫌媾媽媼�\".split(\"\");\nfor(j = 0; j != D[182].length; ++j) if(D[182][j].charCodeAt(0) !== 0xFFFD) { e[D[182][j]] = 46592 + j; d[46592 + j] = D[182][j];}\nD[183] = \"����������������������������������������������������������������媳嫂媲嵩嵯幌幹廉廈弒彙徬微愚意慈感想愛惹愁愈慎慌慄慍愾愴愧愍愆愷戡戢搓搾搞搪搭搽搬搏搜搔損搶搖搗搆敬斟新暗暉暇暈暖暄暘暍會榔業����������������������������������楚楷楠楔極椰概楊楨楫楞楓楹榆楝楣楛歇歲毀殿毓毽溢溯滓溶滂源溝滇滅溥溘溼溺溫滑準溜滄滔溪溧溴煎煙煩煤煉照煜煬煦煌煥煞煆煨煖爺牒猷獅猿猾瑯瑚瑕瑟瑞瑁琿瑙瑛瑜當畸瘀痰瘁痲痱痺痿痴痳盞盟睛睫睦睞督�\".split(\"\");\nfor(j = 0; j != D[183].length; ++j) if(D[183][j].charCodeAt(0) !== 0xFFFD) { e[D[183][j]] = 46848 + j; d[46848 + j] = D[183][j];}\nD[184] = \"����������������������������������������������������������������睹睪睬睜睥睨睢矮碎碰碗碘碌碉硼碑碓硿祺祿禁萬禽稜稚稠稔稟稞窟窠筷節筠筮筧粱粳粵經絹綑綁綏絛置罩罪署義羨群聖聘肆肄腱腰腸腥腮腳腫����������������������������������腹腺腦舅艇蒂葷落萱葵葦葫葉葬葛萼萵葡董葩葭葆虞虜號蛹蜓蜈蜇蜀蛾蛻蜂蜃蜆蜊衙裟裔裙補裘裝裡裊裕裒覜解詫該詳試詩詰誇詼詣誠話誅詭詢詮詬詹詻訾詨豢貊貉賊資賈賄貲賃賂賅跡跟跨路跳跺跪跤跦躲較載軾輊�\".split(\"\");\nfor(j = 0; j != D[184].length; ++j) if(D[184][j].charCodeAt(0) !== 0xFFFD) { e[D[184][j]] = 47104 + j; d[47104 + j] = D[184][j];}\nD[185] = \"����������������������������������������������������������������辟農運遊道遂達逼違遐遇遏過遍遑逾遁鄒鄗酬酪酩釉鈷鉗鈸鈽鉀鈾鉛鉋鉤鉑鈴鉉鉍鉅鈹鈿鉚閘隘隔隕雍雋雉雊雷電雹零靖靴靶預頑頓頊頒頌飼飴����������������������������������飽飾馳馱馴髡鳩麂鼎鼓鼠僧僮僥僖僭僚僕像僑僱僎僩兢凳劃劂匱厭嗾嘀嘛嘗嗽嘔嘆嘉嘍嘎嗷嘖嘟嘈嘐嗶團圖塵塾境墓墊塹墅塽壽夥夢夤奪奩嫡嫦嫩嫗嫖嫘嫣孵寞寧寡寥實寨寢寤察對屢嶄嶇幛幣幕幗幔廓廖弊彆彰徹慇�\".split(\"\");\nfor(j = 0; j != D[185].length; ++j) if(D[185][j].charCodeAt(0) !== 0xFFFD) { e[D[185][j]] = 47360 + j; d[47360 + j] = D[185][j];}\nD[186] = \"����������������������������������������������������������������愿態慷慢慣慟慚慘慵截撇摘摔撤摸摟摺摑摧搴摭摻敲斡旗旖暢暨暝榜榨榕槁榮槓構榛榷榻榫榴槐槍榭槌榦槃榣歉歌氳漳演滾漓滴漩漾漠漬漏漂漢����������������������������������滿滯漆漱漸漲漣漕漫漯澈漪滬漁滲滌滷熔熙煽熊熄熒爾犒犖獄獐瑤瑣瑪瑰瑭甄疑瘧瘍瘋瘉瘓盡監瞄睽睿睡磁碟碧碳碩碣禎福禍種稱窪窩竭端管箕箋筵算箝箔箏箸箇箄粹粽精綻綰綜綽綾綠緊綴網綱綺綢綿綵綸維緒緇綬�\".split(\"\");\nfor(j = 0; j != D[186].length; ++j) if(D[186][j].charCodeAt(0) !== 0xFFFD) { e[D[186][j]] = 47616 + j; d[47616 + j] = D[186][j];}\nD[187] = \"����������������������������������������������������������������罰翠翡翟聞聚肇腐膀膏膈膊腿膂臧臺與舔舞艋蓉蒿蓆蓄蒙蒞蒲蒜蓋蒸蓀蓓蒐蒼蓑蓊蜿蜜蜻蜢蜥蜴蜘蝕蜷蜩裳褂裴裹裸製裨褚裯誦誌語誣認誡誓誤����������������������������������說誥誨誘誑誚誧豪貍貌賓賑賒赫趙趕跼輔輒輕輓辣遠遘遜遣遙遞遢遝遛鄙鄘鄞酵酸酷酴鉸銀銅銘銖鉻銓銜銨鉼銑閡閨閩閣閥閤隙障際雌雒需靼鞅韶頗領颯颱餃餅餌餉駁骯骰髦魁魂鳴鳶鳳麼鼻齊億儀僻僵價儂儈儉儅凜�\".split(\"\");\nfor(j = 0; j != D[187].length; ++j) if(D[187][j].charCodeAt(0) !== 0xFFFD) { e[D[187][j]] = 47872 + j; d[47872 + j] = D[187][j];}\nD[188] = \"����������������������������������������������������������������劇劈劉劍劊勰厲嘮嘻嘹嘲嘿嘴嘩噓噎噗噴嘶嘯嘰墀墟增墳墜墮墩墦奭嬉嫻嬋嫵嬌嬈寮寬審寫層履嶝嶔幢幟幡廢廚廟廝廣廠彈影德徵慶慧慮慝慕憂����������������������������������慼慰慫慾憧憐憫憎憬憚憤憔憮戮摩摯摹撞撲撈撐撰撥撓撕撩撒撮播撫撚撬撙撢撳敵敷數暮暫暴暱樣樟槨樁樞標槽模樓樊槳樂樅槭樑歐歎殤毅毆漿潼澄潑潦潔澆潭潛潸潮澎潺潰潤澗潘滕潯潠潟熟熬熱熨牖犛獎獗瑩璋璃�\".split(\"\");\nfor(j = 0; j != D[188].length; ++j) if(D[188][j].charCodeAt(0) !== 0xFFFD) { e[D[188][j]] = 48128 + j; d[48128 + j] = D[188][j];}\nD[189] = \"����������������������������������������������������������������瑾璀畿瘠瘩瘟瘤瘦瘡瘢皚皺盤瞎瞇瞌瞑瞋磋磅確磊碾磕碼磐稿稼穀稽稷稻窯窮箭箱範箴篆篇篁箠篌糊締練緯緻緘緬緝編緣線緞緩綞緙緲緹罵罷羯����������������������������������翩耦膛膜膝膠膚膘蔗蔽蔚蓮蔬蔭蔓蔑蔣蔡蔔蓬蔥蓿蔆螂蝴蝶蝠蝦蝸蝨蝙蝗蝌蝓衛衝褐複褒褓褕褊誼諒談諄誕請諸課諉諂調誰論諍誶誹諛豌豎豬賠賞賦賤賬賭賢賣賜質賡赭趟趣踫踐踝踢踏踩踟踡踞躺輝輛輟輩輦輪輜輞�\".split(\"\");\nfor(j = 0; j != D[189].length; ++j) if(D[189][j].charCodeAt(0) !== 0xFFFD) { e[D[189][j]] = 48384 + j; d[48384 + j] = D[189][j];}\nD[190] = \"����������������������������������������������������������������輥適遮遨遭遷鄰鄭鄧鄱醇醉醋醃鋅銻銷鋪銬鋤鋁銳銼鋒鋇鋰銲閭閱霄霆震霉靠鞍鞋鞏頡頫頜颳養餓餒餘駝駐駟駛駑駕駒駙骷髮髯鬧魅魄魷魯鴆鴉����������������������������������鴃麩麾黎墨齒儒儘儔儐儕冀冪凝劑劓勳噙噫噹噩噤噸噪器噥噱噯噬噢噶壁墾壇壅奮嬝嬴學寰導彊憲憑憩憊懍憶憾懊懈戰擅擁擋撻撼據擄擇擂操撿擒擔撾整曆曉暹曄曇暸樽樸樺橙橫橘樹橄橢橡橋橇樵機橈歙歷氅濂澱澡�\".split(\"\");\nfor(j = 0; j != D[190].length; ++j) if(D[190][j].charCodeAt(0) !== 0xFFFD) { e[D[190][j]] = 48640 + j; d[48640 + j] = D[190][j];}\nD[191] = \"����������������������������������������������������������������濃澤濁澧澳激澹澶澦澠澴熾燉燐燒燈燕熹燎燙燜燃燄獨璜璣璘璟璞瓢甌甍瘴瘸瘺盧盥瞠瞞瞟瞥磨磚磬磧禦積穎穆穌穋窺篙簑築篤篛篡篩篦糕糖縊����������������������������������縑縈縛縣縞縝縉縐罹羲翰翱翮耨膳膩膨臻興艘艙蕊蕙蕈蕨蕩蕃蕉蕭蕪蕞螃螟螞螢融衡褪褲褥褫褡親覦諦諺諫諱謀諜諧諮諾謁謂諷諭諳諶諼豫豭貓賴蹄踱踴蹂踹踵輻輯輸輳辨辦遵遴選遲遼遺鄴醒錠錶鋸錳錯錢鋼錫錄錚�\".split(\"\");\nfor(j = 0; j != D[191].length; ++j) if(D[191][j].charCodeAt(0) !== 0xFFFD) { e[D[191][j]] = 48896 + j; d[48896 + j] = D[191][j];}\nD[192] = \"����������������������������������������������������������������錐錦錡錕錮錙閻隧隨險雕霎霑霖霍霓霏靛靜靦鞘頰頸頻頷頭頹頤餐館餞餛餡餚駭駢駱骸骼髻髭鬨鮑鴕鴣鴦鴨鴒鴛默黔龍龜優償儡儲勵嚎嚀嚐嚅嚇����������������������������������嚏壕壓壑壎嬰嬪嬤孺尷屨嶼嶺嶽嶸幫彌徽應懂懇懦懋戲戴擎擊擘擠擰擦擬擱擢擭斂斃曙曖檀檔檄檢檜櫛檣橾檗檐檠歜殮毚氈濘濱濟濠濛濤濫濯澀濬濡濩濕濮濰燧營燮燦燥燭燬燴燠爵牆獰獲璩環璦璨癆療癌盪瞳瞪瞰瞬�\".split(\"\");\nfor(j = 0; j != D[192].length; ++j) if(D[192][j].charCodeAt(0) !== 0xFFFD) { e[D[192][j]] = 49152 + j; d[49152 + j] = D[192][j];}\nD[193] = \"����������������������������������������������������������������瞧瞭矯磷磺磴磯礁禧禪穗窿簇簍篾篷簌篠糠糜糞糢糟糙糝縮績繆縷縲繃縫總縱繅繁縴縹繈縵縿縯罄翳翼聱聲聰聯聳臆臃膺臂臀膿膽臉膾臨舉艱薪����������������������������������薄蕾薜薑薔薯薛薇薨薊虧蟀蟑螳蟒蟆螫螻螺蟈蟋褻褶襄褸褽覬謎謗謙講謊謠謝謄謐豁谿豳賺賽購賸賻趨蹉蹋蹈蹊轄輾轂轅輿避遽還邁邂邀鄹醣醞醜鍍鎂錨鍵鍊鍥鍋錘鍾鍬鍛鍰鍚鍔闊闋闌闈闆隱隸雖霜霞鞠韓顆颶餵騁�\".split(\"\");\nfor(j = 0; j != D[193].length; ++j) if(D[193][j].charCodeAt(0) !== 0xFFFD) { e[D[193][j]] = 49408 + j; d[49408 + j] = D[193][j];}\nD[194] = \"����������������������������������������������������������������駿鮮鮫鮪鮭鴻鴿麋黏點黜黝黛鼾齋叢嚕嚮壙壘嬸彝懣戳擴擲擾攆擺擻擷斷曜朦檳檬櫃檻檸櫂檮檯歟歸殯瀉瀋濾瀆濺瀑瀏燻燼燾燸獷獵璧璿甕癖癘����������������������������������癒瞽瞿瞻瞼礎禮穡穢穠竄竅簫簧簪簞簣簡糧織繕繞繚繡繒繙罈翹翻職聶臍臏舊藏薩藍藐藉薰薺薹薦蟯蟬蟲蟠覆覲觴謨謹謬謫豐贅蹙蹣蹦蹤蹟蹕軀轉轍邇邃邈醫醬釐鎔鎊鎖鎢鎳鎮鎬鎰鎘鎚鎗闔闖闐闕離雜雙雛雞霤鞣鞦�\".split(\"\");\nfor(j = 0; j != D[194].length; ++j) if(D[194][j].charCodeAt(0) !== 0xFFFD) { e[D[194][j]] = 49664 + j; d[49664 + j] = D[194][j];}\nD[195] = \"����������������������������������������������������������������鞭韹額顏題顎顓颺餾餿餽餮馥騎髁鬃鬆魏魎魍鯊鯉鯽鯈鯀鵑鵝鵠黠鼕鼬儳嚥壞壟壢寵龐廬懲懷懶懵攀攏曠曝櫥櫝櫚櫓瀛瀟瀨瀚瀝瀕瀘爆爍牘犢獸����������������������������������獺璽瓊瓣疇疆癟癡矇礙禱穫穩簾簿簸簽簷籀繫繭繹繩繪羅繳羶羹羸臘藩藝藪藕藤藥藷蟻蠅蠍蟹蟾襠襟襖襞譁譜識證譚譎譏譆譙贈贊蹼蹲躇蹶蹬蹺蹴轔轎辭邊邋醱醮鏡鏑鏟鏃鏈鏜鏝鏖鏢鏍鏘鏤鏗鏨關隴難霪霧靡韜韻類�\".split(\"\");\nfor(j = 0; j != D[195].length; ++j) if(D[195][j].charCodeAt(0) !== 0xFFFD) { e[D[195][j]] = 49920 + j; d[49920 + j] = D[195][j];}\nD[196] = \"����������������������������������������������������������������願顛颼饅饉騖騙鬍鯨鯧鯖鯛鶉鵡鵲鵪鵬麒麗麓麴勸嚨嚷嚶嚴嚼壤孀孃孽寶巉懸懺攘攔攙曦朧櫬瀾瀰瀲爐獻瓏癢癥礦礪礬礫竇競籌籃籍糯糰辮繽繼����������������������������������纂罌耀臚艦藻藹蘑藺蘆蘋蘇蘊蠔蠕襤覺觸議譬警譯譟譫贏贍躉躁躅躂醴釋鐘鐃鏽闡霰飄饒饑馨騫騰騷騵鰓鰍鹹麵黨鼯齟齣齡儷儸囁囀囂夔屬巍懼懾攝攜斕曩櫻欄櫺殲灌爛犧瓖瓔癩矓籐纏續羼蘗蘭蘚蠣蠢蠡蠟襪襬覽譴�\".split(\"\");\nfor(j = 0; j != D[196].length; ++j) if(D[196][j].charCodeAt(0) !== 0xFFFD) { e[D[196][j]] = 50176 + j; d[50176 + j] = D[196][j];}\nD[197] = \"����������������������������������������������������������������護譽贓躊躍躋轟辯醺鐮鐳鐵鐺鐸鐲鐫闢霸霹露響顧顥饗驅驃驀騾髏魔魑鰭鰥鶯鶴鷂鶸麝黯鼙齜齦齧儼儻囈囊囉孿巔巒彎懿攤權歡灑灘玀瓤疊癮癬����������������������������������禳籠籟聾聽臟襲襯觼讀贖贗躑躓轡酈鑄鑑鑒霽霾韃韁顫饕驕驍髒鬚鱉鰱鰾鰻鷓鷗鼴齬齪龔囌巖戀攣攫攪曬欐瓚竊籤籣籥纓纖纔臢蘸蘿蠱變邐邏鑣鑠鑤靨顯饜驚驛驗髓體髑鱔鱗鱖鷥麟黴囑壩攬灞癱癲矗罐羈蠶蠹衢讓讒�\".split(\"\");\nfor(j = 0; j != D[197].length; ++j) if(D[197][j].charCodeAt(0) !== 0xFFFD) { e[D[197][j]] = 50432 + j; d[50432 + j] = D[197][j];}\nD[198] = \"����������������������������������������������������������������讖艷贛釀鑪靂靈靄韆顰驟鬢魘鱟鷹鷺鹼鹽鼇齷齲廳欖灣籬籮蠻觀躡釁鑲鑰顱饞髖鬣黌灤矚讚鑷韉驢驥纜讜躪釅鑽鑾鑼鱷鱸黷豔鑿鸚爨驪鬱鸛鸞籲���������������������������������������������������������������������������������������������������������������������������������\".split(\"\");\nfor(j = 0; j != D[198].length; ++j) if(D[198][j].charCodeAt(0) !== 0xFFFD) { e[D[198][j]] = 50688 + j; d[50688 + j] = D[198][j];}\nD[201] = \"����������������������������������������������������������������乂乜凵匚厂万丌乇亍囗兀屮彳丏冇与丮亓仂仉仈冘勼卬厹圠夃夬尐巿旡殳毌气爿丱丼仨仜仩仡仝仚刌匜卌圢圣夗夯宁宄尒尻屴屳帄庀庂忉戉扐氕����������������������������������氶汃氿氻犮犰玊禸肊阞伎优伬仵伔仱伀价伈伝伂伅伢伓伄仴伒冱刓刉刐劦匢匟卍厊吇囡囟圮圪圴夼妀奼妅奻奾奷奿孖尕尥屼屺屻屾巟幵庄异弚彴忕忔忏扜扞扤扡扦扢扙扠扚扥旯旮朾朹朸朻机朿朼朳氘汆汒汜汏汊汔汋�\".split(\"\");\nfor(j = 0; j != D[201].length; ++j) if(D[201][j].charCodeAt(0) !== 0xFFFD) { e[D[201][j]] = 51456 + j; d[51456 + j] = D[201][j];}\nD[202] = \"����������������������������������������������������������������汌灱牞犴犵玎甪癿穵网艸艼芀艽艿虍襾邙邗邘邛邔阢阤阠阣佖伻佢佉体佤伾佧佒佟佁佘伭伳伿佡冏冹刜刞刡劭劮匉卣卲厎厏吰吷吪呔呅吙吜吥吘����������������������������������吽呏呁吨吤呇囮囧囥坁坅坌坉坋坒夆奀妦妘妠妗妎妢妐妏妧妡宎宒尨尪岍岏岈岋岉岒岊岆岓岕巠帊帎庋庉庌庈庍弅弝彸彶忒忑忐忭忨忮忳忡忤忣忺忯忷忻怀忴戺抃抌抎抏抔抇扱扻扺扰抁抈扷扽扲扴攷旰旴旳旲旵杅杇�\".split(\"\");\nfor(j = 0; j != D[202].length; ++j) if(D[202][j].charCodeAt(0) !== 0xFFFD) { e[D[202][j]] = 51712 + j; d[51712 + j] = D[202][j];}\nD[203] = \"����������������������������������������������������������������杙杕杌杈杝杍杚杋毐氙氚汸汧汫沄沋沏汱汯汩沚汭沇沕沜汦汳汥汻沎灴灺牣犿犽狃狆狁犺狅玕玗玓玔玒町甹疔疕皁礽耴肕肙肐肒肜芐芏芅芎芑芓����������������������������������芊芃芄豸迉辿邟邡邥邞邧邠阰阨阯阭丳侘佼侅佽侀侇佶佴侉侄佷佌侗佪侚佹侁佸侐侜侔侞侒侂侕佫佮冞冼冾刵刲刳剆刱劼匊匋匼厒厔咇呿咁咑咂咈呫呺呾呥呬呴呦咍呯呡呠咘呣呧呤囷囹坯坲坭坫坱坰坶垀坵坻坳坴坢�\".split(\"\");\nfor(j = 0; j != D[203].length; ++j) if(D[203][j].charCodeAt(0) !== 0xFFFD) { e[D[203][j]] = 51968 + j; d[51968 + j] = D[203][j];}\nD[204] = \"����������������������������������������������������������������坨坽夌奅妵妺姏姎妲姌姁妶妼姃姖妱妽姀姈妴姇孢孥宓宕屄屇岮岤岠岵岯岨岬岟岣岭岢岪岧岝岥岶岰岦帗帔帙弨弢弣弤彔徂彾彽忞忥怭怦怙怲怋����������������������������������怴怊怗怳怚怞怬怢怍怐怮怓怑怌怉怜戔戽抭抴拑抾抪抶拊抮抳抯抻抩抰抸攽斨斻昉旼昄昒昈旻昃昋昍昅旽昑昐曶朊枅杬枎枒杶杻枘枆构杴枍枌杺枟枑枙枃杽极杸杹枔欥殀歾毞氝沓泬泫泮泙沶泔沭泧沷泐泂沺泃泆泭泲�\".split(\"\");\nfor(j = 0; j != D[204].length; ++j) if(D[204][j].charCodeAt(0) !== 0xFFFD) { e[D[204][j]] = 52224 + j; d[52224 + j] = D[204][j];}\nD[205] = \"����������������������������������������������������������������泒泝沴沊沝沀泞泀洰泍泇沰泹泏泩泑炔炘炅炓炆炄炑炖炂炚炃牪狖狋狘狉狜狒狔狚狌狑玤玡玭玦玢玠玬玝瓝瓨甿畀甾疌疘皯盳盱盰盵矸矼矹矻矺����������������������������������矷祂礿秅穸穻竻籵糽耵肏肮肣肸肵肭舠芠苀芫芚芘芛芵芧芮芼芞芺芴芨芡芩苂芤苃芶芢虰虯虭虮豖迒迋迓迍迖迕迗邲邴邯邳邰阹阽阼阺陃俍俅俓侲俉俋俁俔俜俙侻侳俛俇俖侺俀侹俬剄剉勀勂匽卼厗厖厙厘咺咡咭咥哏�\".split(\"\");\nfor(j = 0; j != D[205].length; ++j) if(D[205][j].charCodeAt(0) !== 0xFFFD) { e[D[205][j]] = 52480 + j; d[52480 + j] = D[205][j];}\nD[206] = \"����������������������������������������������������������������哃茍咷咮哖咶哅哆咠呰咼咢咾呲哞咰垵垞垟垤垌垗垝垛垔垘垏垙垥垚垕壴复奓姡姞姮娀姱姝姺姽姼姶姤姲姷姛姩姳姵姠姾姴姭宨屌峐峘峌峗峋峛����������������������������������峞峚峉峇峊峖峓峔峏峈峆峎峟峸巹帡帢帣帠帤庰庤庢庛庣庥弇弮彖徆怷怹恔恲恞恅恓恇恉恛恌恀恂恟怤恄恘恦恮扂扃拏挍挋拵挎挃拫拹挏挌拸拶挀挓挔拺挕拻拰敁敃斪斿昶昡昲昵昜昦昢昳昫昺昝昴昹昮朏朐柁柲柈枺�\".split(\"\");\nfor(j = 0; j != D[206].length; ++j) if(D[206][j].charCodeAt(0) !== 0xFFFD) { e[D[206][j]] = 52736 + j; d[52736 + j] = D[206][j];}\nD[207] = \"����������������������������������������������������������������柜枻柸柘柀枷柅柫柤柟枵柍枳柷柶柮柣柂枹柎柧柰枲柼柆柭柌枮柦柛柺柉柊柃柪柋欨殂殄殶毖毘毠氠氡洨洴洭洟洼洿洒洊泚洳洄洙洺洚洑洀洝浂����������������������������������洁洘洷洃洏浀洇洠洬洈洢洉洐炷炟炾炱炰炡炴炵炩牁牉牊牬牰牳牮狊狤狨狫狟狪狦狣玅珌珂珈珅玹玶玵玴珫玿珇玾珃珆玸珋瓬瓮甮畇畈疧疪癹盄眈眃眄眅眊盷盻盺矧矨砆砑砒砅砐砏砎砉砃砓祊祌祋祅祄秕种秏秖秎窀�\".split(\"\");\nfor(j = 0; j != D[207].length; ++j) if(D[207][j].charCodeAt(0) !== 0xFFFD) { e[D[207][j]] = 52992 + j; d[52992 + j] = D[207][j];}\nD[208] = \"����������������������������������������������������������������穾竑笀笁籺籸籹籿粀粁紃紈紁罘羑羍羾耇耎耏耔耷胘胇胠胑胈胂胐胅胣胙胜胊胕胉胏胗胦胍臿舡芔苙苾苹茇苨茀苕茺苫苖苴苬苡苲苵茌苻苶苰苪����������������������������������苤苠苺苳苭虷虴虼虳衁衎衧衪衩觓訄訇赲迣迡迮迠郱邽邿郕郅邾郇郋郈釔釓陔陏陑陓陊陎倞倅倇倓倢倰倛俵俴倳倷倬俶俷倗倜倠倧倵倯倱倎党冔冓凊凄凅凈凎剡剚剒剞剟剕剢勍匎厞唦哢唗唒哧哳哤唚哿唄唈哫唑唅哱�\".split(\"\");\nfor(j = 0; j != D[208].length; ++j) if(D[208][j].charCodeAt(0) !== 0xFFFD) { e[D[208][j]] = 53248 + j; d[53248 + j] = D[208][j];}\nD[209] = \"����������������������������������������������������������������唊哻哷哸哠唎唃唋圁圂埌堲埕埒垺埆垽垼垸垶垿埇埐垹埁夎奊娙娖娭娮娕娏娗娊娞娳孬宧宭宬尃屖屔峬峿峮峱峷崀峹帩帨庨庮庪庬弳弰彧恝恚恧����������������������������������恁悢悈悀悒悁悝悃悕悛悗悇悜悎戙扆拲挐捖挬捄捅挶捃揤挹捋捊挼挩捁挴捘捔捙挭捇挳捚捑挸捗捀捈敊敆旆旃旄旂晊晟晇晑朒朓栟栚桉栲栳栻桋桏栖栱栜栵栫栭栯桎桄栴栝栒栔栦栨栮桍栺栥栠欬欯欭欱欴歭肂殈毦毤�\".split(\"\");\nfor(j = 0; j != D[209].length; ++j) if(D[209][j].charCodeAt(0) !== 0xFFFD) { e[D[209][j]] = 53504 + j; d[53504 + j] = D[209][j];}\nD[210] = \"����������������������������������������������������������������毨毣毢毧氥浺浣浤浶洍浡涒浘浢浭浯涑涍淯浿涆浞浧浠涗浰浼浟涂涘洯浨涋浾涀涄洖涃浻浽浵涐烜烓烑烝烋缹烢烗烒烞烠烔烍烅烆烇烚烎烡牂牸����������������������������������牷牶猀狺狴狾狶狳狻猁珓珙珥珖玼珧珣珩珜珒珛珔珝珚珗珘珨瓞瓟瓴瓵甡畛畟疰痁疻痄痀疿疶疺皊盉眝眛眐眓眒眣眑眕眙眚眢眧砣砬砢砵砯砨砮砫砡砩砳砪砱祔祛祏祜祓祒祑秫秬秠秮秭秪秜秞秝窆窉窅窋窌窊窇竘笐�\".split(\"\");\nfor(j = 0; j != D[210].length; ++j) if(D[210][j].charCodeAt(0) !== 0xFFFD) { e[D[210][j]] = 53760 + j; d[53760 + j] = D[210][j];}\nD[211] = \"����������������������������������������������������������������笄笓笅笏笈笊笎笉笒粄粑粊粌粈粍粅紞紝紑紎紘紖紓紟紒紏紌罜罡罞罠罝罛羖羒翃翂翀耖耾耹胺胲胹胵脁胻脀舁舯舥茳茭荄茙荑茥荖茿荁茦茜茢����������������������������������荂荎茛茪茈茼荍茖茤茠茷茯茩荇荅荌荓茞茬荋茧荈虓虒蚢蚨蚖蚍蚑蚞蚇蚗蚆蚋蚚蚅蚥蚙蚡蚧蚕蚘蚎蚝蚐蚔衃衄衭衵衶衲袀衱衿衯袃衾衴衼訒豇豗豻貤貣赶赸趵趷趶軑軓迾迵适迿迻逄迼迶郖郠郙郚郣郟郥郘郛郗郜郤酐�\".split(\"\");\nfor(j = 0; j != D[211].length; ++j) if(D[211][j].charCodeAt(0) !== 0xFFFD) { e[D[211][j]] = 54016 + j; d[54016 + j] = D[211][j];}\nD[212] = \"����������������������������������������������������������������酎酏釕釢釚陜陟隼飣髟鬯乿偰偪偡偞偠偓偋偝偲偈偍偁偛偊偢倕偅偟偩偫偣偤偆偀偮偳偗偑凐剫剭剬剮勖勓匭厜啵啶唼啍啐唴唪啑啢唶唵唰啒啅����������������������������������唌唲啥啎唹啈唭唻啀啋圊圇埻堔埢埶埜埴堀埭埽堈埸堋埳埏堇埮埣埲埥埬埡堎埼堐埧堁堌埱埩埰堍堄奜婠婘婕婧婞娸娵婭婐婟婥婬婓婤婗婃婝婒婄婛婈媎娾婍娹婌婰婩婇婑婖婂婜孲孮寁寀屙崞崋崝崚崠崌崨崍崦崥崏�\".split(\"\");\nfor(j = 0; j != D[212].length; ++j) if(D[212][j].charCodeAt(0) !== 0xFFFD) { e[D[212][j]] = 54272 + j; d[54272 + j] = D[212][j];}\nD[213] = \"����������������������������������������������������������������崰崒崣崟崮帾帴庱庴庹庲庳弶弸徛徖徟悊悐悆悾悰悺惓惔惏惤惙惝惈悱惛悷惊悿惃惍惀挲捥掊掂捽掽掞掭掝掗掫掎捯掇掐据掯捵掜捭掮捼掤挻掟����������������������������������捸掅掁掑掍捰敓旍晥晡晛晙晜晢朘桹梇梐梜桭桮梮梫楖桯梣梬梩桵桴梲梏桷梒桼桫桲梪梀桱桾梛梖梋梠梉梤桸桻梑梌梊桽欶欳欷欸殑殏殍殎殌氪淀涫涴涳湴涬淩淢涷淶淔渀淈淠淟淖涾淥淜淝淛淴淊涽淭淰涺淕淂淏淉�\".split(\"\");\nfor(j = 0; j != D[213].length; ++j) if(D[213][j].charCodeAt(0) !== 0xFFFD) { e[D[213][j]] = 54528 + j; d[54528 + j] = D[213][j];}\nD[214] = \"����������������������������������������������������������������淐淲淓淽淗淍淣涻烺焍烷焗烴焌烰焄烳焐烼烿焆焓焀烸烶焋焂焎牾牻牼牿猝猗猇猑猘猊猈狿猏猞玈珶珸珵琄琁珽琇琀珺珼珿琌琋珴琈畤畣痎痒痏����������������������������������痋痌痑痐皏皉盓眹眯眭眱眲眴眳眽眥眻眵硈硒硉硍硊硌砦硅硐祤祧祩祪祣祫祡离秺秸秶秷窏窔窐笵筇笴笥笰笢笤笳笘笪笝笱笫笭笯笲笸笚笣粔粘粖粣紵紽紸紶紺絅紬紩絁絇紾紿絊紻紨罣羕羜羝羛翊翋翍翐翑翇翏翉耟�\".split(\"\");\nfor(j = 0; j != D[214].length; ++j) if(D[214][j].charCodeAt(0) !== 0xFFFD) { e[D[214][j]] = 54784 + j; d[54784 + j] = D[214][j];}\nD[215] = \"����������������������������������������������������������������耞耛聇聃聈脘脥脙脛脭脟脬脞脡脕脧脝脢舑舸舳舺舴舲艴莐莣莨莍荺荳莤荴莏莁莕莙荵莔莩荽莃莌莝莛莪莋荾莥莯莈莗莰荿莦莇莮荶莚虙虖蚿蚷����������������������������������蛂蛁蛅蚺蚰蛈蚹蚳蚸蛌蚴蚻蚼蛃蚽蚾衒袉袕袨袢袪袚袑袡袟袘袧袙袛袗袤袬袌袓袎覂觖觙觕訰訧訬訞谹谻豜豝豽貥赽赻赹趼跂趹趿跁軘軞軝軜軗軠軡逤逋逑逜逌逡郯郪郰郴郲郳郔郫郬郩酖酘酚酓酕釬釴釱釳釸釤釹釪�\".split(\"\");\nfor(j = 0; j != D[215].length; ++j) if(D[215][j].charCodeAt(0) !== 0xFFFD) { e[D[215][j]] = 55040 + j; d[55040 + j] = D[215][j];}\nD[216] = \"����������������������������������������������������������������釫釷釨釮镺閆閈陼陭陫陱陯隿靪頄飥馗傛傕傔傞傋傣傃傌傎傝偨傜傒傂傇兟凔匒匑厤厧喑喨喥喭啷噅喢喓喈喏喵喁喣喒喤啽喌喦啿喕喡喎圌堩堷����������������������������������堙堞堧堣堨埵塈堥堜堛堳堿堶堮堹堸堭堬堻奡媯媔媟婺媢媞婸媦婼媥媬媕媮娷媄媊媗媃媋媩婻婽媌媜媏媓媝寪寍寋寔寑寊寎尌尰崷嵃嵫嵁嵋崿崵嵑嵎嵕崳崺嵒崽崱嵙嵂崹嵉崸崼崲崶嵀嵅幄幁彘徦徥徫惉悹惌惢惎惄愔�\".split(\"\");\nfor(j = 0; j != D[216].length; ++j) if(D[216][j].charCodeAt(0) !== 0xFFFD) { e[D[216][j]] = 55296 + j; d[55296 + j] = D[216][j];}\nD[217] = \"����������������������������������������������������������������惲愊愖愅惵愓惸惼惾惁愃愘愝愐惿愄愋扊掔掱掰揎揥揨揯揃撝揳揊揠揶揕揲揵摡揟掾揝揜揄揘揓揂揇揌揋揈揰揗揙攲敧敪敤敜敨敥斌斝斞斮旐旒����������������������������������晼晬晻暀晱晹晪晲朁椌棓椄棜椪棬棪棱椏棖棷棫棤棶椓椐棳棡椇棌椈楰梴椑棯棆椔棸棐棽棼棨椋椊椗棎棈棝棞棦棴棑椆棔棩椕椥棇欹欻欿欼殔殗殙殕殽毰毲毳氰淼湆湇渟湉溈渼渽湅湢渫渿湁湝湳渜渳湋湀湑渻渃渮湞�\".split(\"\");\nfor(j = 0; j != D[217].length; ++j) if(D[217][j].charCodeAt(0) !== 0xFFFD) { e[D[217][j]] = 55552 + j; d[55552 + j] = D[217][j];}\nD[218] = \"����������������������������������������������������������������湨湜湡渱渨湠湱湫渹渢渰湓湥渧湸湤湷湕湹湒湦渵渶湚焠焞焯烻焮焱焣焥焢焲焟焨焺焛牋牚犈犉犆犅犋猒猋猰猢猱猳猧猲猭猦猣猵猌琮琬琰琫琖����������������������������������琚琡琭琱琤琣琝琩琠琲瓻甯畯畬痧痚痡痦痝痟痤痗皕皒盚睆睇睄睍睅睊睎睋睌矞矬硠硤硥硜硭硱硪确硰硩硨硞硢祴祳祲祰稂稊稃稌稄窙竦竤筊笻筄筈筌筎筀筘筅粢粞粨粡絘絯絣絓絖絧絪絏絭絜絫絒絔絩絑絟絎缾缿罥�\".split(\"\");\nfor(j = 0; j != D[218].length; ++j) if(D[218][j].charCodeAt(0) !== 0xFFFD) { e[D[218][j]] = 55808 + j; d[55808 + j] = D[218][j];}\nD[219] = \"����������������������������������������������������������������罦羢羠羡翗聑聏聐胾胔腃腊腒腏腇脽腍脺臦臮臷臸臹舄舼舽舿艵茻菏菹萣菀菨萒菧菤菼菶萐菆菈菫菣莿萁菝菥菘菿菡菋菎菖菵菉萉萏菞萑萆菂菳����������������������������������菕菺菇菑菪萓菃菬菮菄菻菗菢萛菛菾蛘蛢蛦蛓蛣蛚蛪蛝蛫蛜蛬蛩蛗蛨蛑衈衖衕袺裗袹袸裀袾袶袼袷袽袲褁裉覕覘覗觝觚觛詎詍訹詙詀詗詘詄詅詒詈詑詊詌詏豟貁貀貺貾貰貹貵趄趀趉跘跓跍跇跖跜跏跕跙跈跗跅軯軷軺�\".split(\"\");\nfor(j = 0; j != D[219].length; ++j) if(D[219][j].charCodeAt(0) !== 0xFFFD) { e[D[219][j]] = 56064 + j; d[56064 + j] = D[219][j];}\nD[220] = \"����������������������������������������������������������������軹軦軮軥軵軧軨軶軫軱軬軴軩逭逴逯鄆鄬鄄郿郼鄈郹郻鄁鄀鄇鄅鄃酡酤酟酢酠鈁鈊鈥鈃鈚鈦鈏鈌鈀鈒釿釽鈆鈄鈧鈂鈜鈤鈙鈗鈅鈖镻閍閌閐隇陾隈����������������������������������隉隃隀雂雈雃雱雰靬靰靮頇颩飫鳦黹亃亄亶傽傿僆傮僄僊傴僈僂傰僁傺傱僋僉傶傸凗剺剸剻剼嗃嗛嗌嗐嗋嗊嗝嗀嗔嗄嗩喿嗒喍嗏嗕嗢嗖嗈嗲嗍嗙嗂圔塓塨塤塏塍塉塯塕塎塝塙塥塛堽塣塱壼嫇嫄嫋媺媸媱媵媰媿嫈媻嫆�\".split(\"\");\nfor(j = 0; j != D[220].length; ++j) if(D[220][j].charCodeAt(0) !== 0xFFFD) { e[D[220][j]] = 56320 + j; d[56320 + j] = D[220][j];}\nD[221] = \"����������������������������������������������������������������媷嫀嫊媴媶嫍媹媐寖寘寙尟尳嵱嵣嵊嵥嵲嵬嵞嵨嵧嵢巰幏幎幊幍幋廅廌廆廋廇彀徯徭惷慉慊愫慅愶愲愮慆愯慏愩慀戠酨戣戥戤揅揱揫搐搒搉搠搤����������������������������������搳摃搟搕搘搹搷搢搣搌搦搰搨摁搵搯搊搚摀搥搧搋揧搛搮搡搎敯斒旓暆暌暕暐暋暊暙暔晸朠楦楟椸楎楢楱椿楅楪椹楂楗楙楺楈楉椵楬椳椽楥棰楸椴楩楀楯楄楶楘楁楴楌椻楋椷楜楏楑椲楒椯楻椼歆歅歃歂歈歁殛嗀毻毼�\".split(\"\");\nfor(j = 0; j != D[221].length; ++j) if(D[221][j].charCodeAt(0) !== 0xFFFD) { e[D[221][j]] = 56576 + j; d[56576 + j] = D[221][j];}\nD[222] = \"����������������������������������������������������������������毹毷毸溛滖滈溏滀溟溓溔溠溱溹滆滒溽滁溞滉溷溰滍溦滏溲溾滃滜滘溙溒溎溍溤溡溿溳滐滊溗溮溣煇煔煒煣煠煁煝煢煲煸煪煡煂煘煃煋煰煟煐煓����������������������������������煄煍煚牏犍犌犑犐犎猼獂猻猺獀獊獉瑄瑊瑋瑒瑑瑗瑀瑏瑐瑎瑂瑆瑍瑔瓡瓿瓾瓽甝畹畷榃痯瘏瘃痷痾痼痹痸瘐痻痶痭痵痽皙皵盝睕睟睠睒睖睚睩睧睔睙睭矠碇碚碔碏碄碕碅碆碡碃硹碙碀碖硻祼禂祽祹稑稘稙稒稗稕稢稓�\".split(\"\");\nfor(j = 0; j != D[222].length; ++j) if(D[222][j].charCodeAt(0) !== 0xFFFD) { e[D[222][j]] = 56832 + j; d[56832 + j] = D[222][j];}\nD[223] = \"����������������������������������������������������������������稛稐窣窢窞竫筦筤筭筴筩筲筥筳筱筰筡筸筶筣粲粴粯綈綆綀綍絿綅絺綎絻綃絼綌綔綄絽綒罭罫罧罨罬羦羥羧翛翜耡腤腠腷腜腩腛腢腲朡腞腶腧腯����������������������������������腄腡舝艉艄艀艂艅蓱萿葖葶葹蒏蒍葥葑葀蒆葧萰葍葽葚葙葴葳葝蔇葞萷萺萴葺葃葸萲葅萩菙葋萯葂萭葟葰萹葎葌葒葯蓅蒎萻葇萶萳葨葾葄萫葠葔葮葐蜋蜄蛷蜌蛺蛖蛵蝍蛸蜎蜉蜁蛶蜍蜅裖裋裍裎裞裛裚裌裐覅覛觟觥觤�\".split(\"\");\nfor(j = 0; j != D[223].length; ++j) if(D[223][j].charCodeAt(0) !== 0xFFFD) { e[D[223][j]] = 57088 + j; d[57088 + j] = D[223][j];}\nD[224] = \"����������������������������������������������������������������觡觠觢觜触詶誆詿詡訿詷誂誄詵誃誁詴詺谼豋豊豥豤豦貆貄貅賌赨赩趑趌趎趏趍趓趔趐趒跰跠跬跱跮跐跩跣跢跧跲跫跴輆軿輁輀輅輇輈輂輋遒逿����������������������������������遄遉逽鄐鄍鄏鄑鄖鄔鄋鄎酮酯鉈鉒鈰鈺鉦鈳鉥鉞銃鈮鉊鉆鉭鉬鉏鉠鉧鉯鈶鉡鉰鈱鉔鉣鉐鉲鉎鉓鉌鉖鈲閟閜閞閛隒隓隑隗雎雺雽雸雵靳靷靸靲頏頍頎颬飶飹馯馲馰馵骭骫魛鳪鳭鳧麀黽僦僔僗僨僳僛僪僝僤僓僬僰僯僣僠�\".split(\"\");\nfor(j = 0; j != D[224].length; ++j) if(D[224][j].charCodeAt(0) !== 0xFFFD) { e[D[224][j]] = 57344 + j; d[57344 + j] = D[224][j];}\nD[225] = \"����������������������������������������������������������������凘劀劁勩勫匰厬嘧嘕嘌嘒嗼嘏嘜嘁嘓嘂嗺嘝嘄嗿嗹墉塼墐墘墆墁塿塴墋塺墇墑墎塶墂墈塻墔墏壾奫嫜嫮嫥嫕嫪嫚嫭嫫嫳嫢嫠嫛嫬嫞嫝嫙嫨嫟孷寠����������������������������������寣屣嶂嶀嵽嶆嵺嶁嵷嶊嶉嶈嵾嵼嶍嵹嵿幘幙幓廘廑廗廎廜廕廙廒廔彄彃彯徶愬愨慁慞慱慳慒慓慲慬憀慴慔慺慛慥愻慪慡慖戩戧戫搫摍摛摝摴摶摲摳摽摵摦撦摎撂摞摜摋摓摠摐摿搿摬摫摙摥摷敳斠暡暠暟朅朄朢榱榶槉�\".split(\"\");\nfor(j = 0; j != D[225].length; ++j) if(D[225][j].charCodeAt(0) !== 0xFFFD) { e[D[225][j]] = 57600 + j; d[57600 + j] = D[225][j];}\nD[226] = \"����������������������������������������������������������������榠槎榖榰榬榼榑榙榎榧榍榩榾榯榿槄榽榤槔榹槊榚槏榳榓榪榡榞槙榗榐槂榵榥槆歊歍歋殞殟殠毃毄毾滎滵滱漃漥滸漷滻漮漉潎漙漚漧漘漻漒滭漊����������������������������������漶潳滹滮漭潀漰漼漵滫漇漎潃漅滽滶漹漜滼漺漟漍漞漈漡熇熐熉熀熅熂熏煻熆熁熗牄牓犗犕犓獃獍獑獌瑢瑳瑱瑵瑲瑧瑮甀甂甃畽疐瘖瘈瘌瘕瘑瘊瘔皸瞁睼瞅瞂睮瞀睯睾瞃碲碪碴碭碨硾碫碞碥碠碬碢碤禘禊禋禖禕禔禓�\".split(\"\");\nfor(j = 0; j != D[226].length; ++j) if(D[226][j].charCodeAt(0) !== 0xFFFD) { e[D[226][j]] = 57856 + j; d[57856 + j] = D[226][j];}\nD[227] = \"����������������������������������������������������������������禗禈禒禐稫穊稰稯稨稦窨窫窬竮箈箜箊箑箐箖箍箌箛箎箅箘劄箙箤箂粻粿粼粺綧綷緂綣綪緁緀緅綝緎緄緆緋緌綯綹綖綼綟綦綮綩綡緉罳翢翣翥翞����������������������������������耤聝聜膉膆膃膇膍膌膋舕蒗蒤蒡蒟蒺蓎蓂蒬蒮蒫蒹蒴蓁蓍蒪蒚蒱蓐蒝蒧蒻蒢蒔蓇蓌蒛蒩蒯蒨蓖蒘蒶蓏蒠蓗蓔蓒蓛蒰蒑虡蜳蜣蜨蝫蝀蜮蜞蜡蜙蜛蝃蜬蝁蜾蝆蜠蜲蜪蜭蜼蜒蜺蜱蜵蝂蜦蜧蜸蜤蜚蜰蜑裷裧裱裲裺裾裮裼裶裻�\".split(\"\");\nfor(j = 0; j != D[227].length; ++j) if(D[227][j].charCodeAt(0) !== 0xFFFD) { e[D[227][j]] = 58112 + j; d[58112 + j] = D[227][j];}\nD[228] = \"����������������������������������������������������������������裰裬裫覝覡覟覞觩觫觨誫誙誋誒誏誖谽豨豩賕賏賗趖踉踂跿踍跽踊踃踇踆踅跾踀踄輐輑輎輍鄣鄜鄠鄢鄟鄝鄚鄤鄡鄛酺酲酹酳銥銤鉶銛鉺銠銔銪銍����������������������������������銦銚銫鉹銗鉿銣鋮銎銂銕銢鉽銈銡銊銆銌銙銧鉾銇銩銝銋鈭隞隡雿靘靽靺靾鞃鞀鞂靻鞄鞁靿韎韍頖颭颮餂餀餇馝馜駃馹馻馺駂馽駇骱髣髧鬾鬿魠魡魟鳱鳲鳵麧僿儃儰僸儆儇僶僾儋儌僽儊劋劌勱勯噈噂噌嘵噁噊噉噆噘�\".split(\"\");\nfor(j = 0; j != D[228].length; ++j) if(D[228][j].charCodeAt(0) !== 0xFFFD) { e[D[228][j]] = 58368 + j; d[58368 + j] = D[228][j];}\nD[229] = \"����������������������������������������������������������������噚噀嘳嘽嘬嘾嘸嘪嘺圚墫墝墱墠墣墯墬墥墡壿嫿嫴嫽嫷嫶嬃嫸嬂嫹嬁嬇嬅嬏屧嶙嶗嶟嶒嶢嶓嶕嶠嶜嶡嶚嶞幩幝幠幜緳廛廞廡彉徲憋憃慹憱憰憢憉����������������������������������憛憓憯憭憟憒憪憡憍慦憳戭摮摰撖撠撅撗撜撏撋撊撌撣撟摨撱撘敶敺敹敻斲斳暵暰暩暲暷暪暯樀樆樗槥槸樕槱槤樠槿槬槢樛樝槾樧槲槮樔槷槧橀樈槦槻樍槼槫樉樄樘樥樏槶樦樇槴樖歑殥殣殢殦氁氀毿氂潁漦潾澇濆澒�\".split(\"\");\nfor(j = 0; j != D[229].length; ++j) if(D[229][j].charCodeAt(0) !== 0xFFFD) { e[D[229][j]] = 58624 + j; d[58624 + j] = D[229][j];}\nD[230] = \"����������������������������������������������������������������澍澉澌潢潏澅潚澖潶潬澂潕潲潒潐潗澔澓潝漀潡潫潽潧澐潓澋潩潿澕潣潷潪潻熲熯熛熰熠熚熩熵熝熥熞熤熡熪熜熧熳犘犚獘獒獞獟獠獝獛獡獚獙����������������������������������獢璇璉璊璆璁瑽璅璈瑼瑹甈甇畾瘥瘞瘙瘝瘜瘣瘚瘨瘛皜皝皞皛瞍瞏瞉瞈磍碻磏磌磑磎磔磈磃磄磉禚禡禠禜禢禛歶稹窲窴窳箷篋箾箬篎箯箹篊箵糅糈糌糋緷緛緪緧緗緡縃緺緦緶緱緰緮緟罶羬羰羭翭翫翪翬翦翨聤聧膣膟�\".split(\"\");\nfor(j = 0; j != D[230].length; ++j) if(D[230][j].charCodeAt(0) !== 0xFFFD) { e[D[230][j]] = 58880 + j; d[58880 + j] = D[230][j];}\nD[231] = \"����������������������������������������������������������������膞膕膢膙膗舖艏艓艒艐艎艑蔤蔻蔏蔀蔩蔎蔉蔍蔟蔊蔧蔜蓻蔫蓺蔈蔌蓴蔪蓲蔕蓷蓫蓳蓼蔒蓪蓩蔖蓾蔨蔝蔮蔂蓽蔞蓶蔱蔦蓧蓨蓰蓯蓹蔘蔠蔰蔋蔙蔯虢����������������������������������蝖蝣蝤蝷蟡蝳蝘蝔蝛蝒蝡蝚蝑蝞蝭蝪蝐蝎蝟蝝蝯蝬蝺蝮蝜蝥蝏蝻蝵蝢蝧蝩衚褅褌褔褋褗褘褙褆褖褑褎褉覢覤覣觭觰觬諏諆誸諓諑諔諕誻諗誾諀諅諘諃誺誽諙谾豍貏賥賟賙賨賚賝賧趠趜趡趛踠踣踥踤踮踕踛踖踑踙踦踧�\".split(\"\");\nfor(j = 0; j != D[231].length; ++j) if(D[231][j].charCodeAt(0) !== 0xFFFD) { e[D[231][j]] = 59136 + j; d[59136 + j] = D[231][j];}\nD[232] = \"����������������������������������������������������������������踔踒踘踓踜踗踚輬輤輘輚輠輣輖輗遳遰遯遧遫鄯鄫鄩鄪鄲鄦鄮醅醆醊醁醂醄醀鋐鋃鋄鋀鋙銶鋏鋱鋟鋘鋩鋗鋝鋌鋯鋂鋨鋊鋈鋎鋦鋍鋕鋉鋠鋞鋧鋑鋓����������������������������������銵鋡鋆銴镼閬閫閮閰隤隢雓霅霈霂靚鞊鞎鞈韐韏頞頝頦頩頨頠頛頧颲餈飺餑餔餖餗餕駜駍駏駓駔駎駉駖駘駋駗駌骳髬髫髳髲髱魆魃魧魴魱魦魶魵魰魨魤魬鳼鳺鳽鳿鳷鴇鴀鳹鳻鴈鴅鴄麃黓鼏鼐儜儓儗儚儑凞匴叡噰噠噮�\".split(\"\");\nfor(j = 0; j != D[232].length; ++j) if(D[232][j].charCodeAt(0) !== 0xFFFD) { e[D[232][j]] = 59392 + j; d[59392 + j] = D[232][j];}\nD[233] = \"����������������������������������������������������������������噳噦噣噭噲噞噷圜圛壈墽壉墿墺壂墼壆嬗嬙嬛嬡嬔嬓嬐嬖嬨嬚嬠嬞寯嶬嶱嶩嶧嶵嶰嶮嶪嶨嶲嶭嶯嶴幧幨幦幯廩廧廦廨廥彋徼憝憨憖懅憴懆懁懌憺����������������������������������憿憸憌擗擖擐擏擉撽撉擃擛擳擙攳敿敼斢曈暾曀曊曋曏暽暻暺曌朣樴橦橉橧樲橨樾橝橭橶橛橑樨橚樻樿橁橪橤橐橏橔橯橩橠樼橞橖橕橍橎橆歕歔歖殧殪殫毈毇氄氃氆澭濋澣濇澼濎濈潞濄澽澞濊澨瀄澥澮澺澬澪濏澿澸�\".split(\"\");\nfor(j = 0; j != D[233].length; ++j) if(D[233][j].charCodeAt(0) !== 0xFFFD) { e[D[233][j]] = 59648 + j; d[59648 + j] = D[233][j];}\nD[234] = \"����������������������������������������������������������������澢濉澫濍澯澲澰燅燂熿熸燖燀燁燋燔燊燇燏熽燘熼燆燚燛犝犞獩獦獧獬獥獫獪瑿璚璠璔璒璕璡甋疀瘯瘭瘱瘽瘳瘼瘵瘲瘰皻盦瞚瞝瞡瞜瞛瞢瞣瞕瞙����������������������������������瞗磝磩磥磪磞磣磛磡磢磭磟磠禤穄穈穇窶窸窵窱窷篞篣篧篝篕篥篚篨篹篔篪篢篜篫篘篟糒糔糗糐糑縒縡縗縌縟縠縓縎縜縕縚縢縋縏縖縍縔縥縤罃罻罼罺羱翯耪耩聬膱膦膮膹膵膫膰膬膴膲膷膧臲艕艖艗蕖蕅蕫蕍蕓蕡蕘�\".split(\"\");\nfor(j = 0; j != D[234].length; ++j) if(D[234][j].charCodeAt(0) !== 0xFFFD) { e[D[234][j]] = 59904 + j; d[59904 + j] = D[234][j];}\nD[235] = \"����������������������������������������������������������������蕀蕆蕤蕁蕢蕄蕑蕇蕣蔾蕛蕱蕎蕮蕵蕕蕧蕠薌蕦蕝蕔蕥蕬虣虥虤螛螏螗螓螒螈螁螖螘蝹螇螣螅螐螑螝螄螔螜螚螉褞褦褰褭褮褧褱褢褩褣褯褬褟觱諠����������������������������������諢諲諴諵諝謔諤諟諰諈諞諡諨諿諯諻貑貒貐賵賮賱賰賳赬赮趥趧踳踾踸蹀蹅踶踼踽蹁踰踿躽輶輮輵輲輹輷輴遶遹遻邆郺鄳鄵鄶醓醐醑醍醏錧錞錈錟錆錏鍺錸錼錛錣錒錁鍆錭錎錍鋋錝鋺錥錓鋹鋷錴錂錤鋿錩錹錵錪錔錌�\".split(\"\");\nfor(j = 0; j != D[235].length; ++j) if(D[235][j].charCodeAt(0) !== 0xFFFD) { e[D[235][j]] = 60160 + j; d[60160 + j] = D[235][j];}\nD[236] = \"����������������������������������������������������������������錋鋾錉錀鋻錖閼闍閾閹閺閶閿閵閽隩雔霋霒霐鞙鞗鞔韰韸頵頯頲餤餟餧餩馞駮駬駥駤駰駣駪駩駧骹骿骴骻髶髺髹髷鬳鮀鮅鮇魼魾魻鮂鮓鮒鮐魺鮕����������������������������������魽鮈鴥鴗鴠鴞鴔鴩鴝鴘鴢鴐鴙鴟麈麆麇麮麭黕黖黺鼒鼽儦儥儢儤儠儩勴嚓嚌嚍嚆嚄嚃噾嚂噿嚁壖壔壏壒嬭嬥嬲嬣嬬嬧嬦嬯嬮孻寱寲嶷幬幪徾徻懃憵憼懧懠懥懤懨懞擯擩擣擫擤擨斁斀斶旚曒檍檖檁檥檉檟檛檡檞檇檓檎�\".split(\"\");\nfor(j = 0; j != D[236].length; ++j) if(D[236][j].charCodeAt(0) !== 0xFFFD) { e[D[236][j]] = 60416 + j; d[60416 + j] = D[236][j];}\nD[237] = \"����������������������������������������������������������������檕檃檨檤檑橿檦檚檅檌檒歛殭氉濌澩濴濔濣濜濭濧濦濞濲濝濢濨燡燱燨燲燤燰燢獳獮獯璗璲璫璐璪璭璱璥璯甐甑甒甏疄癃癈癉癇皤盩瞵瞫瞲瞷瞶����������������������������������瞴瞱瞨矰磳磽礂磻磼磲礅磹磾礄禫禨穜穛穖穘穔穚窾竀竁簅簏篲簀篿篻簎篴簋篳簂簉簃簁篸篽簆篰篱簐簊糨縭縼繂縳顈縸縪繉繀繇縩繌縰縻縶繄縺罅罿罾罽翴翲耬膻臄臌臊臅臇膼臩艛艚艜薃薀薏薧薕薠薋薣蕻薤薚薞�\".split(\"\");\nfor(j = 0; j != D[237].length; ++j) if(D[237][j].charCodeAt(0) !== 0xFFFD) { e[D[237][j]] = 60672 + j; d[60672 + j] = D[237][j];}\nD[238] = \"����������������������������������������������������������������蕷蕼薉薡蕺蕸蕗薎薖薆薍薙薝薁薢薂薈薅蕹蕶薘薐薟虨螾螪螭蟅螰螬螹螵螼螮蟉蟃蟂蟌螷螯蟄蟊螴螶螿螸螽蟞螲褵褳褼褾襁襒褷襂覭覯覮觲觳謞����������������������������������謘謖謑謅謋謢謏謒謕謇謍謈謆謜謓謚豏豰豲豱豯貕貔賹赯蹎蹍蹓蹐蹌蹇轃轀邅遾鄸醚醢醛醙醟醡醝醠鎡鎃鎯鍤鍖鍇鍼鍘鍜鍶鍉鍐鍑鍠鍭鎏鍌鍪鍹鍗鍕鍒鍏鍱鍷鍻鍡鍞鍣鍧鎀鍎鍙闇闀闉闃闅閷隮隰隬霠霟霘霝霙鞚鞡鞜�\".split(\"\");\nfor(j = 0; j != D[238].length; ++j) if(D[238][j].charCodeAt(0) !== 0xFFFD) { e[D[238][j]] = 60928 + j; d[60928 + j] = D[238][j];}\nD[239] = \"����������������������������������������������������������������鞞鞝韕韔韱顁顄顊顉顅顃餥餫餬餪餳餲餯餭餱餰馘馣馡騂駺駴駷駹駸駶駻駽駾駼騃骾髾髽鬁髼魈鮚鮨鮞鮛鮦鮡鮥鮤鮆鮢鮠鮯鴳鵁鵧鴶鴮鴯鴱鴸鴰����������������������������������鵅鵂鵃鴾鴷鵀鴽翵鴭麊麉麍麰黈黚黻黿鼤鼣鼢齔龠儱儭儮嚘嚜嚗嚚嚝嚙奰嬼屩屪巀幭幮懘懟懭懮懱懪懰懫懖懩擿攄擽擸攁攃擼斔旛曚曛曘櫅檹檽櫡櫆檺檶檷櫇檴檭歞毉氋瀇瀌瀍瀁瀅瀔瀎濿瀀濻瀦濼濷瀊爁燿燹爃燽獶�\".split(\"\");\nfor(j = 0; j != D[239].length; ++j) if(D[239][j].charCodeAt(0) !== 0xFFFD) { e[D[239][j]] = 61184 + j; d[61184 + j] = D[239][j];}\nD[240] = \"����������������������������������������������������������������璸瓀璵瓁璾璶璻瓂甔甓癜癤癙癐癓癗癚皦皽盬矂瞺磿礌礓礔礉礐礒礑禭禬穟簜簩簙簠簟簭簝簦簨簢簥簰繜繐繖繣繘繢繟繑繠繗繓羵羳翷翸聵臑臒����������������������������������臐艟艞薴藆藀藃藂薳薵薽藇藄薿藋藎藈藅薱薶藒蘤薸薷薾虩蟧蟦蟢蟛蟫蟪蟥蟟蟳蟤蟔蟜蟓蟭蟘蟣螤蟗蟙蠁蟴蟨蟝襓襋襏襌襆襐襑襉謪謧謣謳謰謵譇謯謼謾謱謥謷謦謶謮謤謻謽謺豂豵貙貘貗賾贄贂贀蹜蹢蹠蹗蹖蹞蹥蹧�\".split(\"\");\nfor(j = 0; j != D[240].length; ++j) if(D[240][j].charCodeAt(0) !== 0xFFFD) { e[D[240][j]] = 61440 + j; d[61440 + j] = D[240][j];}\nD[241] = \"����������������������������������������������������������������蹛蹚蹡蹝蹩蹔轆轇轈轋鄨鄺鄻鄾醨醥醧醯醪鎵鎌鎒鎷鎛鎝鎉鎧鎎鎪鎞鎦鎕鎈鎙鎟鎍鎱鎑鎲鎤鎨鎴鎣鎥闒闓闑隳雗雚巂雟雘雝霣霢霥鞬鞮鞨鞫鞤鞪����������������������������������鞢鞥韗韙韖韘韺顐顑顒颸饁餼餺騏騋騉騍騄騑騊騅騇騆髀髜鬈鬄鬅鬩鬵魊魌魋鯇鯆鯃鮿鯁鮵鮸鯓鮶鯄鮹鮽鵜鵓鵏鵊鵛鵋鵙鵖鵌鵗鵒鵔鵟鵘鵚麎麌黟鼁鼀鼖鼥鼫鼪鼩鼨齌齕儴儵劖勷厴嚫嚭嚦嚧嚪嚬壚壝壛夒嬽嬾嬿巃幰�\".split(\"\");\nfor(j = 0; j != D[241].length; ++j) if(D[241][j].charCodeAt(0) !== 0xFFFD) { e[D[241][j]] = 61696 + j; d[61696 + j] = D[241][j];}\nD[242] = \"����������������������������������������������������������������徿懻攇攐攍攉攌攎斄旞旝曞櫧櫠櫌櫑櫙櫋櫟櫜櫐櫫櫏櫍櫞歠殰氌瀙瀧瀠瀖瀫瀡瀢瀣瀩瀗瀤瀜瀪爌爊爇爂爅犥犦犤犣犡瓋瓅璷瓃甖癠矉矊矄矱礝礛����������������������������������礡礜礗礞禰穧穨簳簼簹簬簻糬糪繶繵繸繰繷繯繺繲繴繨罋罊羃羆羷翽翾聸臗臕艤艡艣藫藱藭藙藡藨藚藗藬藲藸藘藟藣藜藑藰藦藯藞藢蠀蟺蠃蟶蟷蠉蠌蠋蠆蟼蠈蟿蠊蠂襢襚襛襗襡襜襘襝襙覈覷覶觶譐譈譊譀譓譖譔譋譕�\".split(\"\");\nfor(j = 0; j != D[242].length; ++j) if(D[242][j].charCodeAt(0) !== 0xFFFD) { e[D[242][j]] = 61952 + j; d[61952 + j] = D[242][j];}\nD[243] = \"����������������������������������������������������������������譑譂譒譗豃豷豶貚贆贇贉趬趪趭趫蹭蹸蹳蹪蹯蹻軂轒轑轏轐轓辴酀鄿醰醭鏞鏇鏏鏂鏚鏐鏹鏬鏌鏙鎩鏦鏊鏔鏮鏣鏕鏄鏎鏀鏒鏧镽闚闛雡霩霫霬霨霦����������������������������������鞳鞷鞶韝韞韟顜顙顝顗颿颽颻颾饈饇饃馦馧騚騕騥騝騤騛騢騠騧騣騞騜騔髂鬋鬊鬎鬌鬷鯪鯫鯠鯞鯤鯦鯢鯰鯔鯗鯬鯜鯙鯥鯕鯡鯚鵷鶁鶊鶄鶈鵱鶀鵸鶆鶋鶌鵽鵫鵴鵵鵰鵩鶅鵳鵻鶂鵯鵹鵿鶇鵨麔麑黀黼鼭齀齁齍齖齗齘匷嚲�\".split(\"\");\nfor(j = 0; j != D[243].length; ++j) if(D[243][j].charCodeAt(0) !== 0xFFFD) { e[D[243][j]] = 62208 + j; d[62208 + j] = D[243][j];}\nD[244] = \"����������������������������������������������������������������嚵嚳壣孅巆巇廮廯忀忁懹攗攖攕攓旟曨曣曤櫳櫰櫪櫨櫹櫱櫮櫯瀼瀵瀯瀷瀴瀱灂瀸瀿瀺瀹灀瀻瀳灁爓爔犨獽獼璺皫皪皾盭矌矎矏矍矲礥礣礧礨礤礩����������������������������������禲穮穬穭竷籉籈籊籇籅糮繻繾纁纀羺翿聹臛臙舋艨艩蘢藿蘁藾蘛蘀藶蘄蘉蘅蘌藽蠙蠐蠑蠗蠓蠖襣襦覹觷譠譪譝譨譣譥譧譭趮躆躈躄轙轖轗轕轘轚邍酃酁醷醵醲醳鐋鐓鏻鐠鐏鐔鏾鐕鐐鐨鐙鐍鏵鐀鏷鐇鐎鐖鐒鏺鐉鏸鐊鏿�\".split(\"\");\nfor(j = 0; j != D[244].length; ++j) if(D[244][j].charCodeAt(0) !== 0xFFFD) { e[D[244][j]] = 62464 + j; d[62464 + j] = D[244][j];}\nD[245] = \"����������������������������������������������������������������鏼鐌鏶鐑鐆闞闠闟霮霯鞹鞻韽韾顠顢顣顟飁飂饐饎饙饌饋饓騲騴騱騬騪騶騩騮騸騭髇髊髆鬐鬒鬑鰋鰈鯷鰅鰒鯸鱀鰇鰎鰆鰗鰔鰉鶟鶙鶤鶝鶒鶘鶐鶛����������������������������������鶠鶔鶜鶪鶗鶡鶚鶢鶨鶞鶣鶿鶩鶖鶦鶧麙麛麚黥黤黧黦鼰鼮齛齠齞齝齙龑儺儹劘劗囃嚽嚾孈孇巋巏廱懽攛欂櫼欃櫸欀灃灄灊灈灉灅灆爝爚爙獾甗癪矐礭礱礯籔籓糲纊纇纈纋纆纍罍羻耰臝蘘蘪蘦蘟蘣蘜蘙蘧蘮蘡蘠蘩蘞蘥�\".split(\"\");\nfor(j = 0; j != D[245].length; ++j) if(D[245][j].charCodeAt(0) !== 0xFFFD) { e[D[245][j]] = 62720 + j; d[62720 + j] = D[245][j];}\nD[246] = \"����������������������������������������������������������������蠩蠝蠛蠠蠤蠜蠫衊襭襩襮襫觺譹譸譅譺譻贐贔趯躎躌轞轛轝酆酄酅醹鐿鐻鐶鐩鐽鐼鐰鐹鐪鐷鐬鑀鐱闥闤闣霵霺鞿韡顤飉飆飀饘饖騹騽驆驄驂驁騺����������������������������������騿髍鬕鬗鬘鬖鬺魒鰫鰝鰜鰬鰣鰨鰩鰤鰡鶷鶶鶼鷁鷇鷊鷏鶾鷅鷃鶻鶵鷎鶹鶺鶬鷈鶱鶭鷌鶳鷍鶲鹺麜黫黮黭鼛鼘鼚鼱齎齥齤龒亹囆囅囋奱孋孌巕巑廲攡攠攦攢欋欈欉氍灕灖灗灒爞爟犩獿瓘瓕瓙瓗癭皭礵禴穰穱籗籜籙籛籚�\".split(\"\");\nfor(j = 0; j != D[246].length; ++j) if(D[246][j].charCodeAt(0) !== 0xFFFD) { e[D[246][j]] = 62976 + j; d[62976 + j] = D[246][j];}\nD[247] = \"����������������������������������������������������������������糴糱纑罏羇臞艫蘴蘵蘳蘬蘲蘶蠬蠨蠦蠪蠥襱覿覾觻譾讄讂讆讅譿贕躕躔躚躒躐躖躗轠轢酇鑌鑐鑊鑋鑏鑇鑅鑈鑉鑆霿韣顪顩飋饔饛驎驓驔驌驏驈驊����������������������������������驉驒驐髐鬙鬫鬻魖魕鱆鱈鰿鱄鰹鰳鱁鰼鰷鰴鰲鰽鰶鷛鷒鷞鷚鷋鷐鷜鷑鷟鷩鷙鷘鷖鷵鷕鷝麶黰鼵鼳鼲齂齫龕龢儽劙壨壧奲孍巘蠯彏戁戃戄攩攥斖曫欑欒欏毊灛灚爢玂玁玃癰矔籧籦纕艬蘺虀蘹蘼蘱蘻蘾蠰蠲蠮蠳襶襴襳觾�\".split(\"\");\nfor(j = 0; j != D[247].length; ++j) if(D[247][j].charCodeAt(0) !== 0xFFFD) { e[D[247][j]] = 63232 + j; d[63232 + j] = D[247][j];}\nD[248] = \"����������������������������������������������������������������讌讎讋讈豅贙躘轤轣醼鑢鑕鑝鑗鑞韄韅頀驖驙鬞鬟鬠鱒鱘鱐鱊鱍鱋鱕鱙鱌鱎鷻鷷鷯鷣鷫鷸鷤鷶鷡鷮鷦鷲鷰鷢鷬鷴鷳鷨鷭黂黐黲黳鼆鼜鼸鼷鼶齃齏����������������������������������齱齰齮齯囓囍孎屭攭曭曮欓灟灡灝灠爣瓛瓥矕礸禷禶籪纗羉艭虃蠸蠷蠵衋讔讕躞躟躠躝醾醽釂鑫鑨鑩雥靆靃靇韇韥驞髕魙鱣鱧鱦鱢鱞鱠鸂鷾鸇鸃鸆鸅鸀鸁鸉鷿鷽鸄麠鼞齆齴齵齶囔攮斸欘欙欗欚灢爦犪矘矙礹籩籫糶纚�\".split(\"\");\nfor(j = 0; j != D[248].length; ++j) if(D[248][j].charCodeAt(0) !== 0xFFFD) { e[D[248][j]] = 63488 + j; d[63488 + j] = D[248][j];}\nD[249] = \"����������������������������������������������������������������纘纛纙臠臡虆虇虈襹襺襼襻觿讘讙躥躤躣鑮鑭鑯鑱鑳靉顲饟鱨鱮鱭鸋鸍鸐鸏鸒鸑麡黵鼉齇齸齻齺齹圞灦籯蠼趲躦釃鑴鑸鑶鑵驠鱴鱳鱱鱵鸔鸓黶鼊����������������������������������龤灨灥糷虪蠾蠽蠿讞貜躩軉靋顳顴飌饡馫驤驦驧鬤鸕鸗齈戇欞爧虌躨钂钀钁驩驨鬮鸙爩虋讟钃鱹麷癵驫鱺鸝灩灪麤齾齉龘碁銹裏墻恒粧嫺╔╦╗╠╬╣╚╩╝╒╤╕╞╪╡╘╧╛╓╥╖╟╫╢╙╨╜║═╭╮╰╯▓�\".split(\"\");\nfor(j = 0; j != D[249].length; ++j) if(D[249][j].charCodeAt(0) !== 0xFFFD) { e[D[249][j]] = 63744 + j; d[63744 + j] = D[249][j];}\nreturn {\"enc\": e, \"dec\": d }; })();\ncptable[1250] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚�„…†‡�‰Š‹ŚŤŽŹ�‘’“”•–—�™š›śťžź ˇ˘Ł¤Ą¦§¨©Ş«¬­®Ż°±˛ł´µ¶·¸ąş»Ľ˝ľżŔÁÂĂÄĹĆÇČÉĘËĚÍÎĎĐŃŇÓÔŐÖ×ŘŮÚŰÜÝŢßŕáâăäĺćçčéęëěíîďđńňóôőö÷řůúűüýţ˙\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1251] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ЂЃ‚ѓ„…†‡€‰Љ‹ЊЌЋЏђ‘’“”•–—�™љ›њќћџ ЎўЈ¤Ґ¦§Ё©Є«¬­®Ї°±Ііґµ¶·ё№є»јЅѕїАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюя\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1252] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚ƒ„…†‡ˆ‰Š‹Œ�Ž��‘’“”•–—˜™š›œ�žŸ ¡¢£¤¥¦§¨©ª«¬­®¯°±²³´µ¶·¸¹º»¼½¾¿ÀÁÂÃÄÅÆÇÈÉÊËÌÍÎÏÐÑÒÓÔÕÖ×ØÙÚÛÜÝÞßàáâãäåæçèéêëìíîïðñòóôõö÷øùúûüýþÿ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1253] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚ƒ„…†‡�‰�‹�����‘’“”•–—�™�›���� ΅Ά£¤¥¦§¨©�«¬­®―°±²³΄µ¶·ΈΉΊ»Ό½ΎΏΐΑΒΓΔΕΖΗΘΙΚΛΜΝΞΟΠΡ�ΣΤΥΦΧΨΩΪΫάέήίΰαβγδεζηθικλμνξοπρςστυφχψωϊϋόύώ�\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1254] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚ƒ„…†‡ˆ‰Š‹Œ����‘’“”•–—˜™š›œ��Ÿ ¡¢£¤¥¦§¨©ª«¬­®¯°±²³´µ¶·¸¹º»¼½¾¿ÀÁÂÃÄÅÆÇÈÉÊËÌÍÎÏĞÑÒÓÔÕÖ×ØÙÚÛÜİŞßàáâãäåæçèéêëìíîïğñòóôõö÷øùúûüışÿ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1255] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚ƒ„…†‡ˆ‰�‹�����‘’“”•–—˜™�›���� ¡¢£₪¥¦§¨©×«¬­®¯°±²³´µ¶·¸¹÷»¼½¾¿ְֱֲֳִֵֶַָֹ�ֻּֽ־ֿ׀ׁׂ׃װױײ׳״�������אבגדהוזחטיךכלםמןנסעףפץצקרשת��‎‏�\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1256] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€پ‚ƒ„…†‡ˆ‰ٹ‹Œچژڈگ‘’“”•–—ک™ڑ›œ‌‍ں ،¢£¤¥¦§¨©ھ«¬­®¯°±²³´µ¶·¸¹؛»¼½¾؟ہءآأؤإئابةتثجحخدذرزسشصض×طظعغـفقكàلâمنهوçèéêëىيîïًٌٍَôُِ÷ّùْûü‎‏ے\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1257] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚�„…†‡�‰�‹�¨ˇ¸�‘’“”•–—�™�›�¯˛� �¢£¤�¦§Ø©Ŗ«¬­®Æ°±²³´µ¶·ø¹ŗ»¼½¾æĄĮĀĆÄÅĘĒČÉŹĖĢĶĪĻŠŃŅÓŌÕÖ×ŲŁŚŪÜŻŽßąįāćäåęēčéźėģķīļšńņóōõö÷ųłśūüżž˙\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[1258] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~€�‚ƒ„…†‡ˆ‰�‹Œ����‘’“”•–—˜™�›œ��Ÿ ¡¢£¤¥¦§¨©ª«¬­®¯°±²³´µ¶·¸¹º»¼½¾¿ÀÁÂĂÄÅÆÇÈÉÊË̀ÍÎÏĐÑ̉ÓÔƠÖ×ØÙÚÛÜỮßàáâăäåæçèéêë́íîïđṇ̃óôơö÷øùúûüư₫ÿ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10000] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ÄÅÇÉÑÖÜáàâäãåçéèêëíìîïñóòôöõúùûü†°¢£§•¶ß®©™´¨≠ÆØ∞±≤≥¥µ∂∑∏π∫ªºΩæø¿¡¬√ƒ≈∆«»… ÀÃÕŒœ–—“”‘’÷◊ÿŸ⁄¤‹›fifl‡·‚„‰ÂÊÁËÈÍÎÏÌÓÔ�ÒÚÛÙıˆ˜¯˘˙˚¸˝˛ˇ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10006] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~Ĺ²É³ÖÜ΅àâä΄¨çéèê룙î‰ôö¦­ùûü†ΓΔΘΛΞΠß®©ΣΪ§≠°·Α±≤≥¥ΒΕΖΗΙΚΜΦΫΨΩάΝ¬ΟΡ≈Τ«»… ΥΧΆΈœ–―“”‘’÷ΉΊΌΎέήίόΏύαβψδεφγηιξκλμνοπώρστθωςχυζϊϋΐΰ�\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10007] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯ†°¢£§•¶І®©™Ђђ≠Ѓѓ∞±≤≥іµ∂ЈЄєЇїЉљЊњјЅ¬√ƒ≈∆«»… ЋћЌќѕ–—“”‘’÷„ЎўЏџ№Ёёяабвгдежзийклмнопрстуфхцчшщъыьэю¤\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10029] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ÄĀāÉĄÖÜáąČäčĆć鏟ĎíďĒēĖóėôöõúĚěü†°Ę£§•¶ß®©™ę¨≠ģĮįĪ≤≥īĶ∂∑łĻļĽľĹĺŅņѬ√ńŇ∆«»… ňŐÕőŌ–—“”‘’÷◊ōŔŕŘ‹›řŖŗŠ‚„šŚśÁŤťÍŽžŪÓÔūŮÚůŰűŲųÝýķŻŁżĢˇ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10079] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ÄÅÇÉÑÖÜáàâäãåçéèêëíìîïñóòôöõúùûüÝ°¢£§•¶ß®©™´¨≠ÆØ∞±≤≥¥µ∂∑∏π∫ªºΩæø¿¡¬√ƒ≈∆«»… ÀÃÕŒœ–—“”‘’÷◊ÿŸ⁄¤ÐðÞþý·‚„‰ÂÊÁËÈÍÎÏÌÓÔ�ÒÚÛÙıˆ˜¯˘˙˚¸˝˛ˇ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\ncptable[10081] = (function(){ var d = \"\\u0000\\u0001\\u0002\\u0003\\u0004\\u0005\\u0006\\u0007\\b\\t\\n\\u000b\\f\\r\\u000e\\u000f\\u0010\\u0011\\u0012\\u0013\\u0014\\u0015\\u0016\\u0017\\u0018\\u0019\\u001a\\u001b\\u001c\\u001d\\u001e\\u001f !\\\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\\\]^_`abcdefghijklmnopqrstuvwxyz{|}~ÄÅÇÉÑÖÜáàâäãåçéèêëíìîïñóòôöõúùûü†°¢£§•¶ß®©™´¨≠ÆØ∞±≤≥¥µ∂∑∏π∫ªºΩæø¿¡¬√ƒ≈∆«»… ÀÃÕŒœ–—“”‘’÷◊ÿŸĞğİıŞş‡·‚„‰ÂÊÁËÈÍÎÏÌÓÔ�ÒÚÛÙ�ˆ˜¯˘˙˚¸˝˛ˇ\", D = [], e = {}; for(var i=0;i!=d.length;++i) { if(d.charCodeAt(i) !== 0xFFFD) e[d[i]] = i; D[i] = d.charAt(i); } return {\"enc\": e, \"dec\": D }; })();\nif (typeof module !== 'undefined' && module.exports) module.exports = cptable;\n/* cputils.js (C) 2013-2014 SheetJS -- http://sheetjs.com */\n/*jshint newcap: false */\n(function(root, factory){\n  \"use strict\";\n  if(typeof cptable === \"undefined\") {\n    if(typeof require !== \"undefined\"){\n      var cpt = require('./cpt' + 'able');\n      if (typeof module !== 'undefined' && module.exports) module.exports = factory(cpt);\n      else root.cptable = factory(cpt);\n    } else throw new Error(\"cptable not found\");\n  } else cptable = factory(cptable);\n}(this, function(cpt){\n  \"use strict\";\n  var magic = {\n    \"1200\":\"utf16le\",\n    \"1201\":\"utf16be\",\n    \"12000\":\"utf32le\",\n    \"12001\":\"utf32be\",\n    \"16969\":\"utf64le\",\n    \"20127\":\"ascii\",\n    \"65000\":\"utf7\",\n    \"65001\":\"utf8\"\n  };\n\n  var sbcs_cache = [874,1250,1251,1252,1253,1254,1255,1256,10000];\n  var dbcs_cache = [932,936,949,950];\n  var magic_cache = [65001];\n  var magic_decode = {};\n  var magic_encode = {};\n  var cpecache = {};\n  var cpdcache = {};\n\n  var sfcc = function sfcc(x) { return String.fromCharCode(x); };\n  var cca = function cca(x){ return x.charCodeAt(0); };\n\n  var has_buf = (typeof Buffer !== 'undefined');\n  if(has_buf) {\n    var mdl = 1024, mdb = new Buffer(mdl);\n    var make_EE = function make_EE(E){\n      var EE = new Buffer(65536);\n      for(var i = 0; i < 65536;++i) EE[i] = 0;\n      var keys = Object.keys(E), len = keys.length;\n      for(var ee = 0, e = keys[ee]; ee < len; ++ee) {\n        if(!(e = keys[ee])) continue;\n        EE[e.charCodeAt(0)] = E[e];\n      }\n      return EE;\n    };\n    var sbcs_encode = function make_sbcs_encode(cp) {\n      var EE = make_EE(cpt[cp].enc);\n      return function sbcs_e(data, ofmt) {\n        var len = data.length;\n        var out, i, j, D, w;\n        if(typeof data === 'string') {\n          out = Buffer(len);\n          for(i = 0; i < len; ++i) out[i] = EE[data.charCodeAt(i)];\n        } else if(Buffer.isBuffer(data)) {\n          out = Buffer(2*len);\n          j = 0;\n          for(i = 0; i < len; ++i) {\n            D = data[i];\n            if(D < 128) out[j++] = EE[D];\n            else if(D < 224) { out[j++] = EE[((D&31)<<6)+(data[i+1]&63)]; ++i; }\n            else if(D < 240) { out[j++] = EE[((D&15)<<12)+((data[i+1]&63)<<6)+(data[i+2]&63)]; i+=2; }\n            else {\n              w = ((D&7)<<18)+((data[i+1]&63)<<12)+((data[i+2]&63)<<6)+(data[i+3]&63); i+=3;\n              if(w < 65536) out[j++] = EE[w];\n              else { w -= 65536; out[j++] = EE[0xD800 + ((w>>10)&1023)]; out[j++] = EE[0xDC00 + (w&1023)]; }\n            }\n          }\n          out.length = j;\n          out = out.slice(0,j);\n        } else {\n          out = Buffer(len);\n          for(i = 0; i < len; ++i) out[i] = EE[data[i].charCodeAt(0)];\n        }\n        if(ofmt === undefined || ofmt === 'buf') return out;\n        if(ofmt !== 'arr') return out.toString('binary');\n        return [].slice.call(out);\n      };\n    };\n    var sbcs_decode = function make_sbcs_decode(cp) {\n      var D = cpt[cp].dec;\n      var DD = new Buffer(131072), d=0, c;\n      for(d=0;d<D.length;++d) {\n        if(!(c=D[d])) continue;\n        var w = c.charCodeAt(0);\n        DD[2*d] = w&255; DD[2*d+1] = w>>8;\n      }\n      return function sbcs_d(data) {\n        var len = data.length, i=0, j;\n        if(2 * len > mdl) { mdl = 2 * len; mdb = new Buffer(mdl); }\n        if(Buffer.isBuffer(data)) {\n          for(i = 0; i < len; i++) {\n            j = 2*data[i];\n            mdb[2*i] = DD[j]; mdb[2*i+1] = DD[j+1];\n          }\n        } else if(typeof data === \"string\") {\n          for(i = 0; i < len; i++) {\n            j = 2*data.charCodeAt(i);\n            mdb[2*i] = DD[j]; mdb[2*i+1] = DD[j+1];\n          }\n        } else {\n          for(i = 0; i < len; i++) {\n            j = 2*data[i];\n            mdb[2*i] = DD[j]; mdb[2*i+1] = DD[j+1];\n          }\n        }\n        mdb.length = 2 * len;\n        return mdb.toString('ucs2');\n      };\n    };\n    var dbcs_encode = function make_dbcs_encode(cp) {\n      var E = cpt[cp].enc;\n      var EE = new Buffer(131072);\n      for(var i = 0; i < 131072; ++i) EE[i] = 0;\n      var keys = Object.keys(E);\n      for(var ee = 0, e = keys[ee]; ee < keys.length; ++ee) {\n        if(!(e = keys[ee])) continue;\n        var f = e.charCodeAt(0);\n        EE[2*f] = E[e] & 255; EE[2*f+1] = E[e]>>8;\n      }\n      return function dbcs_e(data, ofmt) {\n        var len = data.length, out = new Buffer(2*len), i, j, jj, k, D;\n        if(typeof data === 'string') {\n          for(i = k = 0; i < len; ++i) {\n            j = data.charCodeAt(i)*2;\n            out[k++] = EE[j+1] || EE[j]; if(EE[j+1] > 0) out[k++] = EE[j];\n          }\n          out.length = k;\n          out = out.slice(0,k);\n        } else if(Buffer.isBuffer(data)) {\n          for(i = k = 0; i < len; ++i) {\n            D = data[i];\n            if(D < 128) j = D;\n            else if(D < 224) { j = ((D&31)<<6)+(data[i+1]&63); ++i; }\n            else if(D < 240) { j = ((D&15)<<12)+((data[i+1]&63)<<6)+(data[i+2]&63); i+=2; }\n            else { j = ((D&7)<<18)+((data[i+1]&63)<<12)+((data[i+2]&63)<<6)+(data[i+3]&63); i+=3; }\n            if(j<65536) { j*=2; out[k++] = EE[j+1] || EE[j]; if(EE[j+1] > 0) out[k++] = EE[j]; }\n            else { jj = j-65536;\n              j=2*(0xD800 + ((jj>>10)&1023)); out[k++] = EE[j+1] || EE[j]; if(EE[j+1] > 0) out[k++] = EE[j];\n              j=2*(0xDC00 + (jj&1023)); out[k++] = EE[j+1] || EE[j]; if(EE[j+1] > 0) out[k++] = EE[j];\n            }\n          }\n          out.length = k;\n          out = out.slice(0,k);\n        } else {\n          for(i = k = 0; i < len; i++) {\n            j = data[i].charCodeAt(0)*2;\n            out[k++] = EE[j+1] || EE[j]; if(EE[j+1] > 0) out[k++] = EE[j];\n          }\n        }\n        if(ofmt === undefined || ofmt === 'buf') return out;\n        if(ofmt !== 'arr') return out.toString('binary');\n        return [].slice.call(out);\n      };\n    };\n    var dbcs_decode = function make_dbcs_decode(cp) {\n      var D = cpt[cp].dec;\n      var DD = new Buffer(131072), d=0, c, w=0, j=0, i=0;\n      for(i = 0; i < 65536; ++i) { DD[2*i] = 0xFF; DD[2*i+1] = 0xFD;}\n      for(d = 0; d < D.length; ++d) {\n        if(!(c=D[d])) continue;\n        w = c.charCodeAt(0);\n        j = 2*d;\n        DD[j] = w&255; DD[j+1] = w>>8;\n      }\n      return function dbcs_d(data) {\n        var len = data.length, out = new Buffer(2*len), i, j, k=0;\n        if(Buffer.isBuffer(data)) {\n          for(i = 0; i < len; i++) {\n            j = 2*data[i];\n            if(DD[j]===0xFF && DD[j+1]===0xFD) { j=2*((data[i]<<8)+data[i+1]); ++i; }\n            out[k++] = DD[j]; out[k++] = DD[j+1];\n          }\n        } else if(typeof data === \"string\") {\n          for(i = 0; i < len; i++) {\n            j = 2*data.charCodeAt(i);\n            if(DD[j]===0xFF && DD[j+1]===0xFD) { j=2*((data.charCodeAt(i)<<8)+data.charCodeAt(i+1)); ++i; }\n            out[k++] = DD[j]; out[k++] = DD[j+1];\n          }\n        } else {\n          for(i = 0; i < len; i++) {\n            j = 2*data[i];\n            if(DD[j]===0xFF && DD[j+1]===0xFD) { j=2*((data[i]<<8)+data[i+1]); ++i; }\n            out[k++] = DD[j]; out[k++] = DD[j+1];\n          }\n        }\n        out.length = k;\n        return out.toString('ucs2');\n      };\n    };\n    magic_decode[65001] = function utf8_d(data) {\n      var len = data.length, w = 0, ww = 0;\n      if(4 * len > mdl) { mdl = 4 * len; mdb = new Buffer(mdl); }\n      mdb.length = 0;\n      var i = 0;\n      if(len >= 3 && data[0] == 0xEF) if(data[1] == 0xBB && data[2] == 0xBF) i = 3;\n      for(var j = 1, k = 0, D = 0; i < len; i+=j) {\n        j = 1; D = data[i];\n        if(D < 128) w = D;\n        else if(D < 224) { w=(D&31)*64+(data[i+1]&63); j=2; }\n        else if(D < 240) { w=((D&15)<<12)+(data[i+1]&63)*64+(data[i+2]&63); j=3; }\n        else { w=(D&7)*262144+((data[i+1]&63)<<12)+(data[i+2]&63)*64+(data[i+3]&63); j=4; }\n        if(w < 65536) { mdb[k++] = w&255; mdb[k++] = w>>8; }\n        else {\n          w -= 65536; ww = 0xD800 + ((w>>10)&1023); w = 0xDC00 + (w&1023);\n          mdb[k++] = ww&255; mdb[k++] = ww>>>8; mdb[k++] = w&255; mdb[k++] = (w>>>8)&255;\n        }\n      }\n      mdb.length = k;\n      return mdb.toString('ucs2');\n    };\n    magic_encode[65001] = function utf8_e(data, ofmt) {\n      var len = data.length, w = 0, ww = 0, j = 0;\n      var direct = typeof data === \"string\";\n      if(4 * len > mdl) { mdl = 4 * len; mdb = new Buffer(mdl); }\n      for(var i = 0; i < len; ++i) {\n        w = direct ? data.charCodeAt(i) : data[i].charCodeAt(0);\n        if(w <= 0x007F) mdb[j++] = w;\n        else if(w <= 0x07FF) {\n          mdb[j++] = 192 + (w >> 6);\n          mdb[j++] = 128 + (w&63);\n        } else if(w >= 0xD800 && w <= 0xDFFF) {\n          w -= 0xD800; ++i;\n          ww = (direct ? data.charCodeAt(i) : data[i].charCodeAt(0)) - 0xDC00 + (w << 10);\n          mdb[j++] = 240 + ((ww>>>18) & 0x07);\n          mdb[j++] = 144 + ((ww>>>12) & 0x3F);\n          mdb[j++] = 128 + ((ww>>>6) & 0x3F);\n          mdb[j++] = 128 + (ww & 0x3F);\n        } else {\n          mdb[j++] = 224 + (w >> 12);\n          mdb[j++] = 128 + ((w >> 6)&63);\n          mdb[j++] = 128 + (w&63);\n        }\n      }\n      mdb.length = j;\n      if(ofmt === undefined || ofmt === 'buf') return mdb;\n      if(ofmt !== 'arr') return mdb.toString('binary');\n      return [].slice.call(mdb);\n    };\n  }\n\n  var encache = function encache() {\n    if(has_buf) {\n      if(cpdcache[sbcs_cache[0]]) return;\n      var i, s;\n      for(i = 0; i < sbcs_cache.length; ++i) {\n        s = sbcs_cache[i];\n        if(cpt[s]) {\n          cpdcache[s] = sbcs_decode(s);\n          cpecache[s] = sbcs_encode(s);\n        }\n      }\n      for(i = 0; i < dbcs_cache.length; ++i) {\n        s = dbcs_cache[i];\n        if(cpt[s]) {\n          cpdcache[s] = dbcs_decode(s);\n          cpecache[s] = dbcs_encode(s);\n        }\n      }\n      for(i = 0; i < magic_cache.length; ++i) {\n        s = magic_cache[i];\n        if(magic_decode[s]) cpdcache[s] = magic_decode[s];\n        if(magic_encode[s]) cpecache[s] = magic_encode[s];\n      }\n    }\n  };\n  var cp_decache = function cp_decache(cp) { cpdcache[cp] = cpecache[cp] = undefined; };\n  var decache = function decache() {\n    if(has_buf) {\n      if(!cpdcache[sbcs_cache[0]]) return;\n      sbcs_cache.forEach(cp_decache);\n      dbcs_cache.forEach(cp_decache);\n      magic_cache.forEach(cp_decache);\n    }\n    last_enc = last_cp = undefined;\n  };\n  var cache = {\n    encache: encache,\n    decache: decache,\n    sbcs: sbcs_cache,\n    dbcs: dbcs_cache\n  };\n\n  encache();\n\n  var BM = \"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/\";\n  var SetD = \"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789'(),-./:?\";\n  var last_enc, last_cp;\n  var encode = function encode(cp, data, ofmt) {\n    if(cp === last_cp) { return last_enc(data, ofmt); }\n    if(cpecache[cp] !== undefined) { last_enc = cpecache[last_cp=cp]; return last_enc(data, ofmt); }\n    if(has_buf && Buffer.isBuffer(data)) data = data.toString('utf8');\n    var len = data.length;\n    var out = has_buf ? new Buffer(4*len) : [], w, i, j = 0, c, tt, ww;\n    var C = cpt[cp], E, M;\n    if(C && (E=C.enc)) for(i = 0; i < len; ++i, ++j) {\n      w = E[data[i]];\n      out[j] = w&255;\n      if(w > 255) {\n        out[j] = w>>8;\n        out[++j] = w&255;\n      }\n    }\n    else if((M=magic[cp])) switch(M) {\n      case \"utf8\":\n        if(has_buf && typeof data === \"string\") { out = new Buffer(data, M); j = out.length; break; }\n        for(i = 0; i < len; ++i, ++j) {\n          w = data[i].charCodeAt(0);\n          if(w <= 0x007F) out[j] = w;\n          else if(w <= 0x07FF) {\n            out[j]   = 192 + (w >> 6);\n            out[++j] = 128 + (w&63);\n          } else if(w >= 0xD800 && w <= 0xDFFF) {\n            w -= 0xD800;\n            ww = data[++i].charCodeAt(0) - 0xDC00 + (w << 10);\n            out[j]   = 240 + ((ww>>>18) & 0x07);\n            out[++j] = 144 + ((ww>>>12) & 0x3F);\n            out[++j] = 128 + ((ww>>>6) & 0x3F);\n            out[++j] = 128 + (ww & 0x3F);\n          } else {\n            out[j]   = 224 + (w >> 12);\n            out[++j] = 128 + ((w >> 6)&63);\n            out[++j] = 128 + (w&63);\n          }\n        }\n        break;\n      case \"ascii\":\n        if(has_buf && typeof data === \"string\") { out = new Buffer(data, M); j = out.length; break; }\n        for(i = 0; i < len; ++i, ++j) {\n          w = data[i].charCodeAt(0);\n          if(w <= 0x007F) out[j] = w;\n          else throw new Error(\"bad ascii \" + w);\n        }\n        break;\n      case \"utf16le\":\n        if(has_buf && typeof data === \"string\") { out = new Buffer(data, M); j = out.length; break; }\n        for(i = 0; i < len; ++i) {\n          w = data[i].charCodeAt(0);\n          out[j++] = w&255;\n          out[j++] = w>>8;\n        }\n        break;\n      case \"utf16be\":\n        for(i = 0; i < len; ++i) {\n          w = data[i].charCodeAt(0);\n          out[j++] = w>>8;\n          out[j++] = w&255;\n        }\n        break;\n      case \"utf32le\":\n        for(i = 0; i < len; ++i) {\n          w = data[i].charCodeAt(0);\n          if(w >= 0xD800 && w <= 0xDFFF) w = 0x10000 + ((w - 0xD800) << 10) + (data[++i].charCodeAt(0) - 0xDC00);\n          out[j++] = w&255; w >>= 8;\n          out[j++] = w&255; w >>= 8;\n          out[j++] = w&255; w >>= 8;\n          out[j++] = w&255;\n        }\n        break;\n      case \"utf32be\":\n        for(i = 0; i < len; ++i) {\n          w = data[i].charCodeAt(0);\n          if(w >= 0xD800 && w <= 0xDFFF) w = 0x10000 + ((w - 0xD800) << 10) + (data[++i].charCodeAt(0) - 0xDC00);\n          out[j+3] = w&255; w >>= 8;\n          out[j+2] = w&255; w >>= 8;\n          out[j+1] = w&255; w >>= 8;\n          out[j] = w&255; w >>= 8;\n          j+=4;\n        }\n        break;\n      case \"utf7\":\n        for(i = 0; i < len; i++) {\n          c = data[i];\n          if(c === \"+\") { out[j++] = 0x2b; out[j++] = 0x2d; continue; }\n          if(SetD.indexOf(c) > -1) { out[j++] = c.charCodeAt(0); continue; }\n          tt = encode(1201, c);\n          out[j++] = 0x2b;\n          out[j++] = BM.charCodeAt(tt[0]>>2);\n          out[j++] = BM.charCodeAt(((tt[0]&0x03)<<4) + ((tt[1]||0)>>4));\n          out[j++] = BM.charCodeAt(((tt[1]&0x0F)<<2) + ((tt[2]||0)>>6));\n          out[j++] = 0x2d;\n        }\n        break;\n      default: throw new Error(\"Unsupported magic: \" + cp + \" \" + magic[cp]);\n    }\n    else throw new Error(\"Unrecognized CP: \" + cp);\n    out.length = j;\n    out = out.slice(0,j);\n    if(typeof Buffer === 'undefined') return (ofmt == 'str') ? out.map(sfcc).join(\"\") : out;\n    if(ofmt === undefined || ofmt === 'buf') return out;\n    if(ofmt !== 'arr') return out.toString('binary');\n    return [].slice.call(out);\n  };\n  var decode = function decode(cp, data) {\n    var F; if((F=cpdcache[cp])) return F(data);\n    var len = data.length, out = new Array(len), w, i, j = 1, k = 0, ww;\n    var C = cpt[cp], D, M;\n    if(C && (D=C.dec)) {\n      if(typeof data === \"string\") data = data.split(\"\").map(cca);\n      for(i = 0; i < len; i+=j) {\n        j = 2;\n        w = D[(data[i]<<8)+ data[i+1]];\n        if(!w) {\n          j = 1;\n          w = D[data[i]];\n        }\n        if(!w) throw new Error('Unrecognized code: ' + data[i] + ' ' + data[i+j-1] + ' ' + i + ' ' + j + ' ' + D[data[i]]);\n        out[k++] = w;\n      }\n    }\n    else if((M=magic[cp])) switch(M) {\n      case \"utf8\":\n        i = 0;\n        if(len >= 3 && data[0] == 0xEF) if(data[1] == 0xBB && data[2] == 0xBF) i = 3;\n        for(; i < len; i+=j) {\n          j = 1;\n          if(data[i] < 128) w = data[i];\n          else if(data[i] < 224) { w=(data[i]&31)*64+(data[i+1]&63); j=2; }\n          else if(data[i] < 240) { w=((data[i]&15)<<12)+(data[i+1]&63)*64+(data[i+2]&63); j=3; }\n          else { w=(data[i]&7)*262144+((data[i+1]&63)<<12)+(data[i+2]&63)*64+(data[i+3]&63); j=4; }\n          if(w < 65536) { out[k++] = String.fromCharCode(w); }\n          else {\n            w -= 65536; ww = 0xD800 + ((w>>10)&1023); w = 0xDC00 + (w&1023);\n            out[k++] = String.fromCharCode(ww); out[k++] = String.fromCharCode(w);\n          }\n        }\n        break;\n      case \"ascii\":\n        if(has_buf && Buffer.isBuffer(data)) return data.toString(M);\n        for(i = 0; i < len; i++) out[i] = String.fromCharCode(data[i]);\n        k = len; break;\n      case \"utf16le\":\n        i = 0;\n        if(len >= 2 && data[0] == 0xFF) if(data[1] == 0xFE) i = 2;\n        if(has_buf && Buffer.isBuffer(data)) return data.toString(M);\n        j = 2;\n        for(; i < len; i+=j) {\n          out[k++] = String.fromCharCode((data[i+1]<<8) + data[i]);\n        }\n        break;\n      case \"utf16be\":\n        i = 0;\n        if(len >= 2 && data[0] == 0xFE) if(data[1] == 0xFF) i = 2;\n        j = 2;\n        for(; i < len; i+=j) {\n          out[k++] = String.fromCharCode((data[i]<<8) + data[i+1]);\n        }\n        break;\n      case \"utf32le\":\n        i = 0;\n        if(len >= 4 && data[0] == 0xFF) if(data[1] == 0xFE && data[2] == 0 && data[3] == 0) i = 4;\n        j = 4;\n        for(; i < len; i+=j) {\n          w = (data[i+3]<<24) + (data[i+2]<<16) + (data[i+1]<<8) + (data[i]);\n          if(w > 0xFFFF) {\n            w -= 0x10000;\n            out[k++] = String.fromCharCode(0xD800 + ((w >> 10) & 0x3FF));\n            out[k++] = String.fromCharCode(0xDC00 + (w & 0x3FF));\n          }\n          else out[k++] = String.fromCharCode(w);\n        }\n        break;\n      case \"utf32be\":\n        i = 0;\n        if(len >= 4 && data[3] == 0xFF) if(data[2] == 0xFE && data[1] == 0 && data[0] == 0) i = 4;\n        j = 4;\n        for(; i < len; i+=j) {\n          w = (data[i]<<24) + (data[i+1]<<16) + (data[i+2]<<8) + (data[i+3]);\n          if(w > 0xFFFF) {\n            w -= 0x10000;\n            out[k++] = String.fromCharCode(0xD800 + ((w >> 10) & 0x3FF));\n            out[k++] = String.fromCharCode(0xDC00 + (w & 0x3FF));\n          }\n          else out[k++] = String.fromCharCode(w);\n        }\n        break;\n      case \"utf7\":\n        i = 0;\n        if(len >= 4 && data[0] == 0x2B && data[1] == 0x2F && data[2] == 0x76) {\n          if(len >= 5 && data[3] == 0x38 && data[4] == 0x2D) i = 5;\n          else if(data[3] == 0x38 || data[3] == 0x39 || data[3] == 0x2B || data[3] == 0x2F) i = 4;\n        }\n        for(; i < len; i+=j) {\n          if(data[i] !== 0x2b) { j=1; out[k++] = String.fromCharCode(data[i]); continue; }\n          j=1;\n          if(data[i+1] === 0x2d) { j = 2; out[k++] = \"+\"; continue; }\n          while(String.fromCharCode(data[i+j]).match(/[A-Za-z0-9+\\/]/)) j++;\n          var dash = 0;\n          if(data[i+j] === 0x2d) { ++j; dash=1; }\n          var tt = [];\n          var o64;\n          var c1, c2, c3;\n          var e1, e2, e3, e4;\n          for(var l = 1; l < j - dash;) {\n            e1 = BM.indexOf(String.fromCharCode(data[i+l++]));\n            e2 = BM.indexOf(String.fromCharCode(data[i+l++]));\n            c1 = e1 << 2 | e2 >> 4;\n            tt.push(c1);\n            e3 = BM.indexOf(String.fromCharCode(data[i+l++]));\n            if(e3 === -1) break;\n            c2 = (e2 & 15) << 4 | e3 >> 2;\n            tt.push(c2);\n            e4 = BM.indexOf(String.fromCharCode(data[i+l++]));\n            if(e4 === -1) break;\n            c3 = (e3 & 3) << 6 | e4;\n            if(e4 < 64) tt.push(c3);\n          }\n          if((tt.length & 1) === 1) tt.length--;\n          o64 = decode(1201, tt);\n          for(l = 0; l < o64.length; ++l) out[k++] = o64[l];\n        }\n        break;\n      default: throw new Error(\"Unsupported magic: \" + cp + \" \" + magic[cp]);\n    }\n    else throw new Error(\"Unrecognized CP: \" + cp);\n    out.length = k;\n    return out.join(\"\");\n  };\n  var hascp = function hascp(cp) { return cpt[cp] || magic[cp]; };\n  cpt.utils = { decode: decode, encode: encode, hascp: hascp, magic: magic, cache:cache };\n  return cpt;\n}));\n",
            "type": "application/javascript",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/dist/cpexcel.js",
            "module-type": "library"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/license": {
            "text": "Copyright (C) 2012-2015  SheetJS\n\n   Licensed under the Apache License, Version 2.0 (the \"License\");\n   you may not use this file except in compliance with the License.\n   You may obtain a copy of the License at\n\n       http://www.apache.org/licenses/LICENSE-2.0\n\n   Unless required by applicable law or agreed to in writing, software\n   distributed under the License is distributed on an \"AS IS\" BASIS,\n   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n   See the License for the specific language governing permissions and\n   limitations under the License.\n\nExcept where noted, this license applies to any and all software programs and associated documentation files created by the Original Author and distributed with the Software:\n\n'jszip.js' is a modified version of JSZip, Copyright (c) Stuart Knightley, David Duponchel, Franz Buchinger, Ant'onio Afonso.  JSZip is dual licensed and is used according to the terms of the MIT License.\n",
            "type": "text/plain",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/license"
        },
        "$:/language/Help/xlsx-import": {
            "title": "$:/language/Help/xlsx-import",
            "description": "Import tiddlers from an XLSX spreadsheet file",
            "text": "Imports tiddlers from an XLSX spreadsheet file\n\n```\n--xlsx-import <filename> <importSpec>\n```\n\n* ''filename'': filename of the `.xlsx` file\n* ''title'': title of the import specification tiddler to be used for the import"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/importer.js": {
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/xlsx-utils/importer.js\ntype: application/javascript\nmodule-type: library\n\nClass to import an Excel file\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nvar DEFAULT_IMPORT_SPEC_TITLE = \"$:/config/plugins/tiddlywiki/xlsx-utils/default-import-spec\";\n\nvar XLSX = require(\"$:/plugins/tiddlywiki/xlsx-utils/xlsx.js\"),\n\tJSZip = require(\"$:/plugins/tiddlywiki/jszip/jszip.js\");\n\nvar XLSXImporter = function(options) {\n\tthis.filename = options.filename;\n\tthis.text = options.text;\n\tthis.importSpec = options.importSpec || $tw.wiki.getTiddlerText(DEFAULT_IMPORT_SPEC_TITLE);\n\tthis.logger = new $tw.utils.Logger(\"xlsx-utils\");\n\tthis.results = [];\n\tif(JSZip) {\n\t\tthis.processWorkbook();\t\t\n\t}\n};\n\nXLSXImporter.prototype.getResults = function() {\n\treturn this.results;\n};\n\nXLSXImporter.prototype.processWorkbook = function() {\n\t// Read the workbook\n\tif(this.filename) {\n\t\tthis.workbook = XLSX.readFile(this.filename);\t\n\t} else if(this.text) {\n\t\tthis.workbook = XLSX.read(this.text,{type:\"base64\"});\n\t}\n\t// Read the root import specification\n\tthis.rootImportSpec = $tw.wiki.getTiddler(this.importSpec);\n\tif(this.rootImportSpec) {\n\t\t// Iterate through the sheets specified in the list field\n\t\t$tw.utils.each(this.rootImportSpec.fields.list || [],this.processSheet.bind(this));\n\t}\n};\n\nXLSXImporter.prototype.processSheet = function(sheetImportSpecTitle) {\n\t// Get the sheet import specifier\n\tthis.sheetImportSpec = $tw.wiki.getTiddler(sheetImportSpecTitle);\n\tif(this.sheetImportSpec) {\n\t\tthis.sheetName = this.sheetImportSpec.fields[\"import-sheet-name\"];\n\t\tthis.sheet = this.workbook.Sheets[this.sheetName];\n\t\tif(!this.sheet) {\n\t\t\tthis.logger.alert(\"Missing sheet '\" + this.sheetName + \"'\");\n\t\t} else {\n\t\t\t// Get the size of the sheet\n\t\t\tthis.sheetSize = this.measureSheet(this.sheet);\n\t\t\t// Read the column names from the first row\n\t\t\tthis.columnsByName = this.findColumns(this.sheet,this.sheetSize);\n\t\t\t// Iterate through the rows\n\t\t\tfor(this.row=this.sheetSize.startRow+1; this.row<=this.sheetSize.endRow; this.row++) {\n\t\t\t\t// Iterate through the row import specifiers\n\t\t\t\t$tw.utils.each(this.sheetImportSpec.fields.list || [],this.processRow.bind(this));\t\t\t\t\t\n\t\t\t}\n\t\t}\n\t}\n};\n\nXLSXImporter.prototype.processRow = function(rowImportSpecTitle) {\n\tthis.rowImportSpec = $tw.wiki.getTiddler(rowImportSpecTitle);\n\tif(this.rowImportSpec) {\n\t\tthis.tiddlerFields = {};\n\t\tthis.skipTiddler = false;\n\t\t// Determine the type of row\n\t\tthis.rowType = this.rowImportSpec.fields[\"import-row-type\"] || \"by-field\";\n\t\tswitch(this.rowType) {\n\t\t\tcase \"by-column\":\n\t\t\t\tthis.processRowByColumn();\n\t\t\t\tbreak;\n\t\t\tcase \"by-field\":\n\t\t\t\tthis.processRowByField();\n\t\t\t\tbreak;\n\t\t}\n\t\t// Save the tiddler if not skipped\n\t\tif(!this.skipTiddler) {\n\t\t\tif(!this.tiddlerFields.title) {\n\t\t\t\tthis.logger.alert(\"Missing title field for \" + JSON.stringify(this.tiddlerFields));\n\t\t\t}\n\t\t\tthis.results.push(this.tiddlerFields);\t\t\t\t\t\t\t\t\n\t\t}\n\t}\n};\n\nXLSXImporter.prototype.processRowByColumn = function() {\n\tvar self = this;\n\t// Iterate through the columns for the row\n\t$tw.utils.each(this.columnsByName,function(index,name) {\n\t\tvar cell = self.sheet[XLSX.utils.encode_cell({c: self.columnsByName[name], r: self.row})];\n\t\tname = name.toLowerCase();\n\t\tif(cell && cell.w && $tw.utils.isValidFieldName(name)) {\n\t\t\tself.tiddlerFields[name] = cell.w;\t\t\n\t\t}\n\t});\n\t// Skip the tiddler entirely if it doesn't have a title\n\tif(!this.tiddlerFields.title) {\n\t\tthis.skipTiddler = true;\n\t}\n};\n\nXLSXImporter.prototype.processRowByField = function() {\n\t// Iterate through the fields for the row\n\t$tw.utils.each(this.rowImportSpec.fields.list || [],this.processField.bind(this));\n};\n\nXLSXImporter.prototype.processField = function(fieldImportSpecTitle) {\n\tvar fieldImportSpec = $tw.wiki.getTiddler(fieldImportSpecTitle);\n\tif(fieldImportSpec) {\n\t\tvar fieldName = fieldImportSpec.fields[\"import-field-name\"],\n\t\t\tvalue;\n\t\tswitch(fieldImportSpec.fields[\"import-field-source\"]) {\n\t\t\tcase \"column\":\n\t\t\t\tvar columnName = fieldImportSpec.fields[\"import-field-column\"],\n\t\t\t\t\tcell = this.sheet[XLSX.utils.encode_cell({c: this.columnsByName[columnName], r: this.row})];\n\t\t\t\tif(cell) {\n\t\t\t\t\tswitch(fieldImportSpec.fields[\"import-field-type\"] || \"string\") {\n\t\t\t\t\t\tcase \"date\":\n\t\t\t\t\t\t\tif(cell.t === \"n\") {\n\t\t\t\t\t\t\t\tvalue = $tw.utils.stringifyDate(new Date((cell.v - (25567 + 2)) * 86400 * 1000));\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t\tbreak;\n\t\t\t\t\t\tcase \"string\":\n\t\t\t\t\t\t\t// Intentional fall-through\n\t\t\t\t\t\tdefault:\n\t\t\t\t\t\t\tvalue = cell.w;\n\t\t\t\t\t\t\tbreak;\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\tbreak;\n\t\t\tcase \"constant\":\n\t\t\t\tvalue = fieldImportSpec.fields[\"import-field-value\"]\n\t\t\t\tbreak;\n\t\t}\n\t\tvalue = (value || \"\").trim();\n\t\tif(value === \"\") {\n\t\t\tif((fieldImportSpec.fields[\"import-field-skip-tiddler-if-blank\"] || \"\").trim().toLowerCase() === \"yes\") {\n\t\t\t\tthis.skipTiddler = true;\n\t\t\t}\n\t\t\tif(fieldImportSpec.fields[\"import-field-replace-blank\"]) {\n\t\t\t\tvalue = fieldImportSpec.fields[\"import-field-replace-blank\"];\n\t\t\t}\n\t\t}\n\t\tif(fieldImportSpec.fields[\"import-field-prefix\"]) {\n\t\t\tvalue = fieldImportSpec.fields[\"import-field-prefix\"] + value;\n\t\t}\n\t\tif(fieldImportSpec.fields[\"import-field-suffix\"]) {\n\t\t\tvalue = value + fieldImportSpec.fields[\"import-field-suffix\"];\n\t\t}\n\t\tswitch(fieldImportSpec.fields[\"import-field-list-op\"] || \"none\") {\n\t\t\tcase \"none\":\n\t\t\t\tthis.tiddlerFields[fieldName] = value;\n\t\t\t\tbreak;\n\t\t\tcase \"append\":\n\t\t\t\tvar list = $tw.utils.parseStringArray(this.tiddlerFields[fieldName] || \"\");\n\t\t\t\t$tw.utils.pushTop(list,value)\n\t\t\t\tthis.tiddlerFields[fieldName] = list;\n\t\t\t\tbreak;\n\t\t}\n\t}\n}\n\nXLSXImporter.prototype.measureSheet = function(sheet) {\n\tvar sheetRange = XLSX.utils.decode_range(sheet[\"!ref\"]);\n\treturn {\n\t\tstartRow: Math.min(sheetRange.s.r,sheetRange.e.r),\n\t\tendRow: Math.max(sheetRange.s.r,sheetRange.e.r),\n\t\tstartCol: Math.min(sheetRange.s.c,sheetRange.e.c),\n\t\tendCol: Math.max(sheetRange.s.c,sheetRange.e.c)\n\t}\n};\n\nXLSXImporter.prototype.findColumns = function(sheet,sheetSize) {\n\tvar columnsByName = {};\n\tfor(var col=sheetSize.startCol; col<=sheetSize.endCol; col++) {\n\t\tvar cell = sheet[XLSX.utils.encode_cell({c: col, r: sheetSize.startRow})],\n\t\t\tcolumnName;\n\t\tif(cell) {\n\t\t\tcolumnName = cell.w;\n\t\t\tif(columnName) {\n\t\t\t\tcolumnsByName[columnName] = col;\t\t\t\t\t\t\t\n\t\t\t}\n\t\t}\n\t}\n\treturn columnsByName;\n};\n\nexports.XLSXImporter = XLSXImporter;\n\n})();\n",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/importer.js",
            "type": "application/javascript",
            "module-type": "library"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/readme": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/readme",
            "text": "This plugin provides a flexible way to import tiddlers from Excel files. It is based on the library [[js-xlsx|https://github.com/SheetJS/js-xlsx]].\n\nThe plugin uses //import specifications// to determine how incoming spreadsheets are processed. You can view, create and edit import specifications in the control panel \"XLSX Utilities\" tab, or directly in the [[plugin controls|$:/plugins/tiddlywiki/xlsx-utils]]. This is also where you select which import specification is selected for use during the next import operation.\n\nEach sheet is expected to consist of a single header row followed by multiple content rows, each consisting of an independent record. The plugin automatically detects the extent of each sheet by looking for the bottom right cell that contains a value. This can lead to unexpected results if a cell is accidentally created with an invisible, blank value.\n\nImport specifications describe how tiddlers are created from a particular row of a sheet; multiple tiddlers can be generated from a single row.\n\nEach field of each tiddler can be assigned a constant value, or a value taken from a named column of the sheet, optionally with a prefix and/or suffix added. There is special support for handling list fields (like the tags field), with the ability to append new items to the list.\n\nInternally, each import specifier is actually modelled as a hierarchy of connected tiddlers with the field ''import-spec-role'' indicating the following roles:\n\n* ''workbook'': describes the sheets to be imported from the workbook\n* ''sheet'': describes each sheet to be processed\n* ''row'': describes the tiddlers to be imported from each row of each sheet\n* ''field'': describes the fields to be assigned to each tiddler from each row of each sheet\n\nThe easiest way to understand the structure is to explore the example import specifications, and the corresponding spreadsheets they are designed to handle.\n\nNote that there are many possible different ways of importing a particular spreadsheet, depending on whether the structures are modelled with fields, tags, prefixes or other mechanisms. The plugin is designed to support a wide range of applications.\n\nThis plugin also requires the JSZip plugin ([[$:/plugins/tiddlywiki/jszip]]) to be installed.\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/startup.js": {
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/xlsx-utils/startup.js\ntype: application/javascript\nmodule-type: startup\n\nInitialisation\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\n// Export name and synchronous status\nexports.name = \"xlsx-startup\";\nexports.after = [\"load-modules\"];\nexports.synchronous = true;\n\nexports.startup = function() {\n\t// Check JSZip is installed\n\tif(!$tw.utils.hop($tw.modules.titles,\"$:/plugins/tiddlywiki/jszip/jszip.js\")) {\n\t\t// Make a logger\n\t\tvar logger = new $tw.utils.Logger(\"xlsx-utils\");\n\t\tlogger.alert(\"The plugin 'xlsx-utils' requires the 'jszip' plugin to be installed\");\n\t}\n};\n\n})();\n",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/startup.js",
            "type": "application/javascript",
            "module-type": "startup"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/styles": {
            "title": "$:/plugins/tiddlywiki/xlsx-utils/styles",
            "tags": "[[$:/tags/Stylesheet]]",
            "text": "\\define quick-colour-selector-background() #bac0f1\n\\define quick-colour-selector-border() #9196c1\n\n\\define quick-colour-editor-background() #bae3f1\n\\define quick-colour-editor-controls() #d2ffff\n\\define quick-colour-editor-border() #97b8c3\n\n\\define quick-colour-workbook-background() #baf1db\n\\define quick-colour-workbook-controls() #d3fff6\n\\define quick-colour-workbook-border() #98c3b2\n\n\\define quick-colour-sheet-background() #f1ebba\n\\define quick-colour-sheet-controls() #fffed3\n\\define quick-colour-sheet-border() #c4be98\n\n\\define quick-colour-row-background() #f1baba\n\\define quick-colour-row-controls() #fed1d2\n\\define quick-colour-row-border() #c39697\n\n\\define quick-colour-field-background() #e0d4fb\n\\define quick-colour-field-controls() #fcefff\n\\define quick-colour-field-border() #b6adcb\n\n\n\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\n.tc-import-spec-selector {\n\tborder: 1px solid <<quick-colour-selector-border>>;\n\tbackground-color: <<quick-colour-selector-background>>;\n\tpadding: 0.25em;\n}\n\n.tc-import-spec-editor-wrapper {\n\tborder: 1px solid <<quick-colour-editor-border>>;\n\tbackground-color: <<quick-colour-editor-background>>;\n\tpadding: 0.25em;\n}\n\n.tc-import-spec-editor {\n\tborder: 1px solid <<quick-colour-editor-border>>;\n\tbackground-color: <<colour background>>;\n\tmargin: 0.25em;\n}\n\n.tc-import-spec-editor-controls {\n\tdisplay: block;\n\tbackground-color: <<quick-colour-editor-controls>>;\n\tborder-bottom: 1px solid <<quick-colour-editor-background>>;\n\tpadding: 0;\n\tmargin: 0;\n\tlist-style: none;\n}\n\n.tc-import-spec-editor-controls li {\n\tpadding: 0.25em 0.5em;\n}\n\n.tc-import-spec-editor-controls li:not(:last-child) {\n\tborder-bottom: 1px solid <<quick-colour-editor-background>>;\n}\n\n.tc-import-spec-editor-list {\n}\n\n.tc-import-spec-workbook-wrapper {\n\tborder: 1px solid <<quick-colour-workbook-border>>;\n\tbackground-color: <<quick-colour-workbook-background>>;\n\tpadding: 0.25em;\n\tmargin: 0.5em;\n}\n\n.tc-import-spec-workbook {\n\tborder: 1px solid <<quick-colour-workbook-border>>;\n\tbackground-color: <<colour background>>;\n\tmargin: 0.25em;\n}\n\n.tc-import-spec-workbook-controls {\n\tdisplay: block;\n\tbackground-color: <<quick-colour-workbook-controls>>;\n\tborder-bottom: 1px solid <<quick-colour-workbook-background>>;\n\tpadding: 0;\n\tmargin: 0;\n\tlist-style: none;\n}\n\n.tc-import-spec-workbook-controls li {\n\tpadding: 0.25em 0.5em;\n}\n\n.tc-import-spec-workbook-controls li:not(:last-child) {\n\tborder-bottom: 1px solid <<quick-colour-workbook-background>>;\n}\n\n.tc-import-spec-workbook-list {\n}\n\n.tc-import-spec-sheet-wrapper {\n\tborder: 1px solid <<quick-colour-sheet-border>>;\n\tbackground-color: <<quick-colour-sheet-background>>;\n\tpadding: 0.25em;\n\tmargin: 0.5em;\n}\n\n.tc-import-spec-sheet {\n\tborder: 1px solid <<quick-colour-sheet-border>>;\n\tbackground-color: <<colour background>>;\n\tmargin: 0.25em;\n}\n\n.tc-import-spec-sheet-controls {\n\tdisplay: block;\n\tbackground-color: <<quick-colour-sheet-controls>>;\n\tborder-bottom: 1px solid <<quick-colour-sheet-background>>;\n\tpadding: 0;\n\tmargin: 0;\n\tlist-style: none;\n}\n\n.tc-import-spec-sheet-controls li {\n\tpadding: 0.25em 0.5em;\n}\n\n.tc-import-spec-sheet-controls li:not(:last-child) {\n\tborder-bottom: 1px solid <<quick-colour-sheet-background>>;\n}\n\n.tc-import-spec-sheet-list {\n}\n\n.tc-import-spec-row-wrapper {\n\tborder: 1px solid <<quick-colour-row-border>>;\n\tbackground-color: <<quick-colour-row-background>>;\n\tpadding: 0.25em;\n\tmargin: 0.5em;\n}\n\n.tc-import-spec-row {\n\tborder: 1px solid <<quick-colour-row-border>>;\n\tbackground-color: <<colour background>>;\n\tmargin: 0.25em;\n}\n\n.tc-import-spec-row-controls {\n\tdisplay: block;\n\tbackground-color: <<quick-colour-row-controls>>;\n\tborder-bottom: 1px solid <<quick-colour-row-background>>;\n\tpadding: 0;\n\tmargin: 0;\n\tlist-style: none;\n}\n\n.tc-import-spec-row-controls li {\n\tpadding: 0.25em 0.5em;\n}\n\n.tc-import-spec-row-controls li:not(:last-child) {\n\tborder-bottom: 1px solid <<quick-colour-row-background>>;\n}\n\n.tc-import-spec-row-list {\n\tlist-style: none;\n\tpadding: 0;\n\tmargin: 0;\n}\n\n.tc-import-spec-field-wrapper {\n\tfont-size: 0.9em;\n\tborder: 1px solid <<quick-colour-field-border>>;\n\tbackground-color: <<quick-colour-field-background>>;\n\tpadding: 0.25em;\n\tmargin: 0.5em;\n}\n"
        },
        "$:/plugins/tiddlywiki/xlsx-utils/xlsx-import-command.js": {
            "text": "/*\\\ntitle: $:/plugins/tiddlywiki/xlsx-utils/xlsx-import-command.js\ntype: application/javascript\nmodule-type: command\n\nCommand to import an xlsx file\n\n\\*/\n(function(){\n\n/*jslint node: true, browser: true */\n/*global $tw: false */\n\"use strict\";\n\nexports.info = {\n\tname: \"xlsx-import\",\n\tsynchronous: true\n};\n\nvar Command = function(params,commander,callback) {\n\tthis.params = params;\n\tthis.commander = commander;\n\tthis.callback = callback;\n};\n\nCommand.prototype.execute = function() {\n\tif(this.params.length < 1) {\n\t\treturn \"Missing parameters\";\n\t}\n\tvar self = this,\n\t\twiki = this.commander.wiki,\n\t\tfilename = this.params[0],\n\t\timportSpec = this.params[1],\n\t\tXLSXImporter = require(\"$:/plugins/tiddlywiki/xlsx-utils/importer.js\").XLSXImporter,\n\t\timporter = new XLSXImporter({\n\t\t\tfilename: filename,\n\t\t\timportSpec: importSpec\n\t\t});\n\t$tw.wiki.addTiddlers(importer.getResults());\n\treturn null;\n};\n\nexports.Command = Command;\n\n})();\n",
            "title": "$:/plugins/tiddlywiki/xlsx-utils/xlsx-import-command.js",
            "type": "application/javascript",
            "module-type": "command"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/tobibeer/appear/widget.js": {
            "text": "/*\\\r\ntitle: $:/plugins/tobibeer/appear/widget.js\r\ntype: application/javascript\r\nmodule-type: widget\r\n\r\nUse the appear widget for popups, sliders, accordion menus\r\n\r\n@preserve\r\n\\*/\n(function(){\"use strict\";var t=require(\"$:/core/modules/widgets/widget.js\").widget,e=function(t,e){this.initialise(t,e)},i={};e.prototype=new t;e.prototype.render=function(t,e){this.parentDomNode=t;this.nextSibling=e;this.computeAttributes();this.execute();var i,s,r,a,h,n,l=[];if(this.handle){this.getHandlerCache(this.handle,1);this.refreshHandler()}else{s={type:\"button\"};s.attributes=this.setAttributes(s,\"button\");i=s.attributes[\"class\"].value.trim();s.attributes[\"class\"].value=i+\" appear-show\"+(this.handler?\" tc-popup-absolute\":\"\");s.children=this.wiki.parseText(\"text/vnd.tiddlywiki\",this.show,{parseAsInline:true}).tree;h={type:\"reveal\",children:this.parseTreeNode.children};h.attributes=this.setAttributes(h,\"reveal\");h.isBlock=!(this.mode&&this.mode===\"inline\");if(h.attributes.type&&h.attributes.type.value===\"popup\"){s.attributes.popup=h.attributes.state;l.push(s);if(!this.handler){l.push(h)}else{s.attributes.handler=this.handler}}else{h.attributes.type={type:\"string\",value:\"match\"};h.attributes.text={type:\"string\",value:this.currentTiddler};s.attributes.set=h.attributes.state;s.attributes.setTo={type:\"string\",value:this.currentTiddler};a={type:\"reveal\",isBlock:this.block,children:[s],attributes:{type:{type:\"string\",value:\"nomatch\"},state:h.attributes.state,text:{type:\"string\",value:this.currentTiddler}}};if(!this.once){r=$tw.utils.deepCopy(s);r.attributes[\"class\"].value=i+\" appear-hide \"+(this.attr.button.selectedClass?this.attr.button.selectedClass:\"\");r.attributes.setTo={type:\"string\",value:\"\"};r.children=this.wiki.parseText(\"text/vnd.tiddlywiki\",this.hide,{parseAsInline:true}).tree}n=$tw.utils.deepCopy(a);n.children=[];if(!this.once){n.children.push(r)}if(!this.handler){n.children.push(h)}n.attributes.type.value=\"match\";l.push(a,n)}this.makeChildWidgets(l);this.renderChildren(this.parentDomNode,e);if(this.handler){this.addToHandlerCache(h)}}};e.prototype.execute=function(){var t=this;this.attr={map:{reveal:{\"class\":1,position:1,retain:1,state:1,style:1,tag:1,type:1},button:{\"button-class\":1,\"button-style\":1,\"button-tag\":1,tooltip:1,selectedClass:1}},rename:{\"button-class\":\"class\",\"button-style\":\"style\",\"button-tag\":\"tag\"},button:{},reveal:{}};$tw.utils.each(this.attributes,function(e,i){var s;$tw.utils.each(t.attr.map,function(r,a){$tw.utils.each(Object.keys(r),function(r){if(r==i){t.attr[a][i]=e;s=false;return false}});return s})});this.currentTiddler=this.getVariable(\"currentTiddler\");this.show=this.getValue(this.attributes.show,\"show\");this.hide=this.getValue(this.attributes.hide,\"hide\");if(!this.hide){this.hide=this.show}this.once=this.attributes.once&&this.attributes.once!==\"false\";this.$state=this.attributes.$state;this.mode=this.getValue(this.attributes.mode,\"mode\");this.handle=this.attributes.handle;this.handler=this.attributes.handler;this.handlerVariables=(this.attributes.variables||\"\")+\" currentTiddler\";this.keep=[\"yes\",\"true\"].indexOf((this.getValue(this.attributes.keep,\"keep\")||\"\").toLocaleLowerCase())>-1;if(!this.attr.reveal.state){this.attr.reveal.state=this.getValue(undefined,\"default-state\")+this.currentTiddler+this.getStateQualifier()+\"/\"+(this.attr.reveal.type?this.attr.reveal.type+\"/\":\"\")+(this.mode?this.mode+\"/\":\"\")+(this.once?\"once/\":\"\")+(this.$state?\"/\"+this.$state:\"\")}};e.prototype.refresh=function(t){var e=this.computeAttributes();if(Object.keys(e).length){this.refreshSelf();return true}if(this.handle){this.refreshHandler()}return this.refreshChildren(t)};e.prototype.getValue=function(t,e){var i,s,r={show:\"»\",\"default-state\":\"$:/temp/appear/\"};if(t===undefined){i=this.wiki.getTiddler(\"$:/plugins/tobibeer/appear/defaults/\"+e);if(i){s=i.getFieldString(\"undefined\");if(!s||s===\"false\"){t=i.getFieldString(\"text\")}}}if(t===undefined){t=r[e]}return t};e.prototype.setAttributes=function(t,e){var i=this,s={};$tw.utils.each(Object.keys(this.attr.map[e]),function(r){var a,h=i.attr.rename[r];if(!h){h=r}a=i.getValue(i.attr[e][r],r);if(h===\"class\"){a=[\"appear\",\"appear-\"+e,e===\"reveal\"&&i.keep?\"tc-popup-keep\":\"\",i.mode?\"appear-\"+i.mode:\"\",i.once?\"appear-once\":\"\",a||\"\"].join(\" \")}if(a!==undefined){if(h===\"tag\"){t.tag=a}else{s[h]={type:\"string\",value:a}}}});return s};e.prototype.getHandlerCache=function(t,e){var s=i[t];if(!s||e){i[t]={handled:{},handle:{}};s=i[t]}return s};e.prototype.refreshHandler=function(){var t=this,e=this.getHandlerCache(this.handle),s=e.handle;if(Object.keys(s).length){$tw.utils.each(s,function(e,i){t.removeChildNode(i);t.children.push(t.makeChildWidget(e));t.children[t.children.length-1].render(t.parentDomNode,t.nextSibling)});i[this.handle].handle={}}};e.prototype.removeChildNode=function(t){var e=this;$tw.utils.each(this.children,function(i,s){if(i.children[0].state===t){i.removeChildDomNodes();e.children.splice(s);return false}})};e.prototype.addToHandlerCache=function(t){var e=this,i=t.attributes.state.value,s=this.getHandlerCache(this.handler),r=s.handled[i],a={type:\"vars\",children:[t],attributes:{}};$tw.utils.each((this.handlerVariables||\"\").split(\" \"),function(t){t=t.trim();if(t){a.attributes[t]={type:\"string\",value:(e.getVariable(t)||\"\").toString()}}});if(a!==r){s.handle[i]=a;this.wiki.setText(\"$:/temp/appear-handler/\"+this.handler,\"text\",undefined,i)}};exports.appear=e})();",
            "title": "$:/plugins/tobibeer/appear/widget.js",
            "type": "application/javascript",
            "module-type": "widget"
        },
        "$:/plugins/tobibeer/appear/defaults/show": {
            "title": "$:/plugins/tobibeer/appear/defaults/show",
            "text": "»"
        },
        "$:/plugins/tobibeer/appear/defaults/mode": {
            "title": "$:/plugins/tobibeer/appear/defaults/mode",
            "text": "block"
        },
        "$:/plugins/tobibeer/appear/defaults/keep": {
            "title": "$:/plugins/tobibeer/appear/defaults/keep",
            "text": "yes"
        },
        "$:/plugins/tobibeer/appear/defaults/button-class": {
            "title": "$:/plugins/tobibeer/appear/defaults/button-class",
            "text": "tc-btn-invisible tc-tiddlylink"
        },
        "$:/plugins/tobibeer/appear/defaults/default-state": {
            "title": "$:/plugins/tobibeer/appear/defaults/default-state",
            "text": "$:/temp/appear/"
        },
        "$:/plugins/tobibeer/appear/popup.js": {
            "text": "/*\\\r\ntitle: $:/plugins/tobibeer/appear/popup.js\r\ntype: application/javascript\r\nmodule-type: utils\r\n\r\nAn enhanced version of the core Popup to support:\r\n* absolute popups\r\n* preview popups\r\n* popup z-index\r\n\r\n@preserve\r\n\\*/\n(function(){\"use strict\";var t=require(\"$:/core/modules/utils/dom/popup.js\").Popup,e=require(\"$:/core/modules/widgets/reveal.js\").reveal,s=e.prototype.refresh;t.prototype.show=function(t){var e,s=t.domNode,p=$tw.utils.hasClass(s,\"tc-popup-absolute\"),o=this.popupInfo(s),i=function(t){var e=t,s=0,p=0;do{s+=e.offsetLeft||0;p+=e.offsetTop||0;e=e.offsetParent}while(e);return{left:s,top:p}},l={left:s.offsetLeft,top:s.offsetTop};e=o.popupLevel;if(o.isHandle){e++}this.cancel(e);if(this.findPopup(t.title)===-1){this.popups.push({title:t.title,wiki:t.wiki,domNode:s})}l=p?i(s):l;t.wiki.setTextReference(t.title,\"(\"+l.left+\",\"+l.top+\",\"+s.offsetWidth+\",\"+s.offsetHeight+\")\");if(this.popups.length>0){this.rootElement.addEventListener(\"click\",this,true)}};t.prototype.popupInfo=function(t){var e,s=false,p=t;while(p&&e===undefined){if($tw.utils.hasClass(p,\"tc-popup-handle\")||$tw.utils.hasClass(p,\"tc-popup-keep\")){s=true}if($tw.utils.hasClass(p,\"tc-reveal\")&&($tw.utils.hasClass(p,\"tc-popup\")||$tw.utils.hasClass(p,\"tc-popup-handle\"))){e=parseInt(p.style.zIndex)-1e3}p=p.parentNode}var o={popupLevel:e||0,isHandle:s};return o};t.prototype.handleEvent=function(t){if(t.type===\"click\"){var e=this.popupInfo(t.target),s=e.popupLevel-1;if(e.isHandle){if(s<0){s=1}else{s++}}this.cancel(s)}};e.prototype.refresh=function(){var t,e,p=this.isOpen;e=s.apply(this,arguments);t=this.domNodes[0];if(this.isOpen&&(p!==this.isOpen||!t.style.zIndex)&&t&&(this.type===\"popup\"||$tw.utils.hasClass(t,\"tc-block-dropdown\")&&$tw.utils.hasClass(t,\"tc-reveal\"))){t.style.zIndex=1e3+$tw.popup.popups.length}return e}})();",
            "title": "$:/plugins/tobibeer/appear/popup.js",
            "type": "application/javascript",
            "module-type": "utils"
        },
        "$:/plugins/tobibeer/appear/readme": {
            "title": "$:/plugins/tobibeer/appear/readme",
            "text": "This plugin provides the ''$appear'' widget that can render popups and sliders (inline or block) as well as accordion menus.\n\n!! Attributes\r\n; type\r\n: set to `popup` to have the content appear as a popup\r\n; show\r\n: the button label\r\n; hide\r\n: the hide button label\r\n; mode\r\n: either `block` or `inline`, with respect to the inner content\r\n: any other mode is interpreted as block mode, without the default styles applying, e.g. drop-shadows\r\n; once\r\n: allows to click the button once, then hides it (unless the state is deleted)\r\n; $state\r\n: the widget calculates a state for you, use this to append a simple id\r\n; state\r\n: alternatively, specify a fully qualified state\r\n; keep\r\n: make popups sticky when `yes` or `true`\r\n; handle / handler / variables\r\n: allows to take the popup contents out of the flow and render them elsewhere on the page\r\n: required to properly create popups in table cells and other constained elements\r\n: specify variables to take along\n\n<br>\n\n; documentation / examples / demos...\r\n: http://tobibeer.github.io/tw5-plugins#appear\r\n"
        },
        "$:/plugins/tobibeer/appear/styles": {
            "title": "$:/plugins/tobibeer/appear/styles",
            "tags": "$:/tags/Stylesheet",
            "text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline html\n\n<pre>.tc-reveal.appear-block,\r\n.tc-popup.appear {\r\n\tborder-radius: 5px;\r\n\tpadding: 1px 1em;\r\n\t<<box-shadow \"2px 2px 4px rgba(0,0,0,0.3)\">>;\r\n}\r\n.tc-popup.appear {\r\n\tpadding: 0 1em;\r\n\tbackground: <<colour background>>;\r\n}\r\n.appear-reveal.appear-inline{\r\nmargin-left:5px;\r\n}\r\n.appear-reveal.appear-inline.appear-once{\r\nmargin-left:0;\r\n}</pre>"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/tobibeer/random/filter.js": {
            "title": "$:/plugins/tobibeer/random/filter.js",
            "text": "/*\\\ntitle: $:/plugins/tobibeer/random/filter.js\ntype: application/javascript\nmodule-type: filteroperator\n\na filter to...\n\n@preserve\n\\*/\n(function(){\"use strict\";exports.random=function(n,t,r){var e,o=[],a=[],i=parseInt(t.operand||\"1\");if(isNaN(i)){i=1}n(function(n,t){a.push(t)});while(i&&a.length){e=Math.floor(Math.random()*a.length);o.push(a[e]);a.splice(e,1);i--}return o}})();",
            "type": "application/javascript",
            "module-type": "filteroperator"
        },
        "$:/plugins/tobibeer/random/readme": {
            "title": "$:/plugins/tobibeer/random/readme",
            "text": "The plugin $:/plugins/tobibeer/random provides:\n\n; random[]\r\n: a filter retrieving one or more random titles from the input set\r\n: `[tag[Plugins]random[3]]` — returns three titles tagged [[Plugins]]\n\n<br>\n\n; documentation / examples / demos...\r\n: http://tobibeer.github.io/tw5-plugins#random"
        }
    }
}

{
    "tiddlers": {
        "$:/plugins/tobibeer/split/filter.js": {
            "title": "$:/plugins/tobibeer/split/filter.js",
            "text": "/*\\\r\ntitle: $:/plugins/tobibeer/split/filter.js\r\ntype: application/javascript\r\nmodule-type: filteroperator\r\n\r\nFilter operator that splits each item at a specified separator.\r\n\r\n@preserve\r\n\\*/\n(function(){\"use strict\";exports.split=function(s,t,e){var i,a,f=e.wiki,r=t.suffix||\"\",n=[],l=[],u=[],o=[],p={negate:t.prefix===\"!\",split:t.operand,prefix:\"\",suffix:\"\",num:1,$num:1},c=[[/^\\s+/,function(){}],[/^(num|pos|\\$num|\\$pos)=(n|-n|\\d+|-\\d+)(?:\\s|$)/i,function(s){p[s[1]]=s[2];if(s[1].charAt(0)===\"$\"){p.mode=\"$pos\"}if(s[1]===\"$num\"&&!p.$pos){p.$pos=1}if(s[1]===\"num\"&&!p.pos){p.pos=1}}],[/^(\\+|at|!at|first|!first|last|!last|list|keep|strict|\\$strict|trim|unique)(?:\\s|$)/i,function(s){var t=s[1];p[t]=1;switch(t){case\"+\":p.suffix=p.split;break;case\"!at\":p.nat=1;case\"at\":i=p.split.match(/(\\d+),(\\d+)/);if(i){p.at=parseInt(i[1]);p.to=parseInt(i[2])}else{p.at=parseInt(p.split)}if(isNaN(p.at)){throw\"suffix 'at' must be numeric: \"+p.at}else{p.at=p.at-1}break;case\"list\":p.list=\"list\";break;case\"first\":p.pos=1;break;case\"!first\":p.pos=2;p.num=\"n\";break;case\"last\":p.pos=\"n\";break;case\"!last\":p.pos=\"-2\";p.num=\"-n\";break}}],[/^(before|after|beforelast|afterlast)(?:\\s|$)/i,function(s){var t=s[1];p.before=(t.toLowerCase().indexOf(\"before\")===0?1:2)+(t.toLowerCase().indexOf(\"last\")===t.length-4?2:0)}],[/^list\\=\\s*([^\\s]+)(?:\\s|$)/i,function(s){p.list=s[1]}],[/^(\\!)?(\\$|\\$all|\\$first|\\$last)(?:\\s|$)/i,function(s){var t=s[2];p.mode=t;p.neg=s[1]?1:0;if(t===\"$first\"){if(p.neg){p.$pos=2;p.$num=\"n\"}else{p.$pos=1}}else if(t===\"$last\"){if(p.neg){p.$pos=\"-2\";p.$num=\"-n\"}else{p.$pos=\"n\"}}}],[/^(?:\\+\\\\([^\\\\]+)\\\\|\\\\([^\\\\]+)\\\\\\+)/,function(s){if(s[1]){p.prefix=s[1]}else{p.suffix=s[2]}}]];try{while(r){a=r;$tw.utils.each(c,function(s){var t=s[0].exec(r);if(t){s[1].call(this,t);r=r.substr(t[0].length);return false}});if(r===a){throw\"invalid suffix(es) '\"+r+\"'\"}}if(p.list&&p.split){o=$tw.utils.parseStringArray(p.split)}else{s(function(s,t){var e,a,r=[];l.push(t);if(p.before){i=1+(p.before<3?t.indexOf(p.split):t.lastIndexOf(p.split));if(i>0){r=[p.before%2===1?t.substr(0,i-1):t.substr(i+p.split.length-1)]}if(p.keep&&i===0){r[0]=t}}else if(p.at){if(p.to){r=p.nat?[t.substr(0,p.at)+t.substr(p.at+p.to)]:[t.substr(p.at,p.to)];if(p.keep&&r[0]===\"\"){r[0]=t}}else{r=[t.substr(0,p.at)];a=t.substr(p.at);if(a){r.push(a)}}}else if(p.list){r=f.getTiddlerList(t,p.list)}else{r=t.split(p.split)}e=r.length>1||p.list||r.length>0&&(p.before||p.to);if(p.pos){r=$tw.utils.getArrayItems(r,p.pos,p.num,p.strict)}if(r.length&&(e||p.keep)){n.push(t);$tw.utils.each(r,function(s){if(p.trim){s=s.trim()}if(s){if(!p.unique||p.unique&&o.indexOf(s)<0){o.push(p.prefix+s+p.suffix)}}})}else{u.push(t)}})}if(t.suffix){switch(p.mode){case\"$\":o=n;break;case\"$all\":if(o.length){if(p.negate){u=[]}else{o=l}}else if(p.negate){u=l}break;case\"$first\":case\"$last\":case\"$pos\":o=$tw.utils.getArrayItems(o,p.$pos,p.$num,p.$strict);break}}}catch($){return[\"split syntax error:\"+$]}return p.negate?u:o}})();",
            "type": "application/javascript",
            "module-type": "filteroperator"
        },
        "$:/plugins/tobibeer/split/readme": {
            "title": "$:/plugins/tobibeer/split/readme",
            "text": "Provides the filter `split[by]`, splitting input titles `by` a string defined in the operand, allowing you to slice and dice output elements as needed.\n\n; suffixes\r\n: `$` — return input titles that yield split items\r\n: `$all` — return all input titles if any yield split items\r\n: `+` — append operand to split titles\r\n: `+\\x\\` — append x to split titles\r\n: `\\x\\+` — prepend x to split titles\r\n: `unique` — prevents duplicate titles in the output\r\n: `trim` — no leading/trailing blanks in split titles\r\n: `first` — first title of the split => `!first` — all but first\r\n: `last` — last title of the split => `!last` — all but last\r\n: `at[<num>]` — split in two at number in the operand\r\n: `at[<num>,<len>]` — slice out ''len'' characters starting at character ''num''\r\n: `!at[<num>,<len>]` — cutting the above out of the input title\r\n: `before[x]` / `after[x]` — up until / after first match of `x`\r\n: `beforelast[x]` / `afterlast[x]`— up until / after last match of `x`\r\n: `pos=2` — 2nd split item of each input title in turn\r\n: `pos=1 num=3` — first three each\r\n: `pos=2 num=n` — 2nd to last each\r\n: `pos=-2 num=-n` — first to 2nd last each\r\n: `strict` — specified `num` is mandatory\r\n: `$pos`, `$num`, `$strict`, `$first`, `$!first`,`$last`, `$!last` — for final list\r\n: `keep` — return title even if not split\r\n: `list[]` — parse list field of input titles\r\n: `list=tags[]` — parse tags field of input titles\r\n: `list<foo>` — parse (soft) operand as list, e.g. variables or text-references\n\n<br>\n\n; documentation / examples / demos...\r\n: http://tobibeer.github.io/tw5-plugins#split"
        },
        "$:/plugins/tobibeer/split/utils.js": {
            "title": "$:/plugins/tobibeer/split/utils.js",
            "text": "/*\\\r\ntitle: $:/plugins/tobibeer/split/utils.js\r\ntype: application/javascript\r\nmodule-type: utils\r\n\r\n@preserve\r\n\\*/\n(function(){\"use strict\";exports.getArrayItems=function(e,t,n,s){var i,a=parseInt(n),f=parseInt(t),r=e.length;if(t===\"n\"){f=r}else if(t===\"-n\"){f=1}else if(!t){f=1}if(n===\"n\"){a=r}else if(n===\"-n\"){a=-(f<0?r+f+1:f)}else if(!n){a=1}f=Math.max(1,f<0?r+f+(a<0?a+2:1):a<0?f+a+1:f);a=Math.max(1,Math.abs(a));i=e.splice(f-1,a);if(i.length<a&&s){i=[]}return i}})();",
            "type": "application/javascript",
            "module-type": "utils"
        }
    }
}

Appears and tabs for each primary section

Writing in TiddlyWiki

Project Ideas

Linking

Appears and tabs for each primary section

Designing and Writing Interactive Texts

$:/themes/tiddlywiki/heavier

{
    "tiddlers": {
        "$:/themes/tiddlywiki/heavier/base": {
            "title": "$:/themes/tiddlywiki/heavier/base",
            "tags": "[[$:/tags/Stylesheet]]",
            "text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\nhtml body strong,\nhtml body button.tc-tiddlylink,\nhtml body a.tc-tiddlylink,\nhtml body a.tc-tiddlylink-shadow,\nhtml body .tc-menu-list-count {\n\tfont-weight: 700;\n}\n\nhtml body h1,\nhtml body h2,\nhtml body h3,\nhtml body h4,\nhtml body h5,\nhtml body h6,\nhtml body a.tc-tiddlylink-shadow.tc-tiddlylink-resolves,\nhtml body button.tc-tag-label,\nhtml body span.tc-tag-label,\nhtml body .tc-sidebar-header .tc-title a.tc-tiddlylink-resolves,\nhtml body .tc-site-title,\nhtml body .tc-titlebar,\nhtml body .tc-subtitle,\nhtml body .tc-tiddler-missing .tc-title,\nhtml body .tc-tab-buttons button,\nhtml body .tc-tiddler-frame .tc-tiddler-body {\n\tfont-weight: 500;\n}\n\nhtml body .tc-view-field-name {\n\tfont-weight: 400;\n}\n"
        }
    }
}

{
    "tiddlers": {
        "$:/themes/tiddlywiki/punch/base": {
            "title": "$:/themes/tiddlywiki/punch/base",
            "tags": "[[$:/tags/Stylesheet]]",
            "text": "\\rules only filteredtranscludeinline transcludeinline macrodef macrocallinline\n\n@media screen {\n\n@media (min-width: {{$:/themes/tiddlywiki/vanilla/metrics/sidebarbreakpoint}}) {\n\n\tbody.tc-body .tc-story-river {\n\t\tpadding: 0;\n\t}\n\n}\n\nbody.tc-body .tc-tiddler-frame {\n\tborder: 0;\n\tmargin-bottom: 0;\n\tmin-height: 1000px;\n}\n\nbody.tc-body .tc-tiddler-frame > a {\n\ttext-decoration: none;\n\tcolor: <<color foreground>>;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body {\n\ttext-align: center;\n\tmax-width: 850px;\n\tmargin-left: auto;\n\tmargin-right: auto;\n\tmargin-top: -70px;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body ul,\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body ol,\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body p {\n\tfont-size: 27px;\n\tline-height: 1.5;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body ul,\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body ol {\n\ttext-align: left;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body pre, body.tc-body .tc-tiddler-frame .tc-tiddler-body code {\n\tfont-size: 18px;\n\ttext-align: left;\n\tbackground: #121;\n\tcolor: #fff;\n}\n\nbody.tc-body .tc-tiddler-controls button svg {\n\twidth: 20px;\n\theight: 20px;\n}\n\nbody.tc-body .tc-tiddler-view-frame .tc-titlebar, body.tc-body .tc-tiddler-view-frame .tc-topbar {\n\t<<transition \"opacity 200ms ease-in-out\">>\n\topacity: 0;\n}\n\nbody.tc-body .tc-tiddler-view-frame .tc-titlebar:hover, body.tc-body .tc-tiddler-view-frame .tc-topbar:hover {\n\topacity: 1;\n}\n\nbody.tc-body .tc-tiddler-view-frame .tc-titlebar {\n\tfont-size: 20px;\n}\n\nbody.tc-body .tc-tiddler-view-frame .tc-titlebar h2 {\n\tfont-size: 10px;\n}\n\nbody.tc-body .tc-tiddler-view-frame .tc-subtitle, body.tc-body .tc-tiddler-view-frame .tc-tags-wrapper {\n\tdisplay: none;\n}\n\nbody.tc-body h1 {\n\tfont-weight: 700;\n\tfont-size: 60px;\n}\n\nbody.tc-body h2, body.tc-body h3, body.tc-body h4 {\n\tfont-weight: 400;\n}\n\nbody.tc-body h2 {\n\tfont-size: 35px;\n}\n\nbody.tc-body h3 {\n\tfont-size: 24px;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body .tc-diatribe {\n\tmax-height:85vh;\n\t-moz-columns:3;\n\t-webkit-columns:3;\n\tcolumns:3;\n\tfont-size: 10px;\n}\n\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body .tc-diatribe p {\n\tmargin: 0 0 0.5em 0;\n}\n\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body .tc-diatribe ul,\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body .tc-diatribe ol,\nbody.tc-body .tc-tiddler-frame .tc-tiddler-body .tc-diatribe p {\n\tfont-size: 10px;\n\ttext-align: left;\n}\n\n} /* @media screen */\n\n"
        }
    }
}

fluid-fixed

Exercise 5.03

Tabs for each primary section

classic

About

``Andrew is the first submission to the ``[[google form for sharing wikis|https://docs.google.com/forms/d/e/1FAIpQLSdoyt48nN7zQzzIl_UBJvViOiQ_jvgFGGCdUvYdS3LHhU50gA/viewform]]`` who used the new comment field! If you look at the response spreadsheet, you'll see his comment. Then edit this tiddler and you'll see the field ``comments`` that contains the text of his comment.  If you want to see the template for displaying the fields of this tiddler, click the ``^^[[Template|shared-exercises template]]^^`` link at the bottom of this tiddler.

So much!

Added in syllabus elements from spreadsheet. Wrote templates: [[class template]], [[exercise template]], [[exercise-group template]], [[presentation template]], [[workshop template]]

* Added better description of [[January-May 2018 Activities]], and integrated it into [[Hello There]] (note [[trick|January-May 2018 Activities]] of transcluding first line of tiddler using a ``{{!!fieldname}}`` so that on ``<$appear>`` transclusion it isn't visible...)
* Briefly explored https://github.com/Arlen22/TiddlyServer, and a tutorial for it at https://www.didaxy.com/introduction-to-tiddlyserver, and the really excellent site https://www.didaxy.com/.

* Finally, got [[PunchShow Macro]] working

In computer science, the concept of hypertext designates a way of making
direct connections among various pieces of information, textual or nontex-
tual, that may or may not be located in the same file (or on the same “page”
by means of embedded links. Using an interface based primarily on visual
and intuitive elements such as color and icons, hypertext users can identify
the places in a document where additional information is attached and ac-
cess them directly with a mouse click.

Selection, association, and contiguity. In addition to the above-men-
tioned modes of navigation, the blocks of information are here ac-
cessible sequentially, like the pages of a book. This model is suitable
for an essay or a scientific article and would be used, for example, for
adaptations of printed books. It corresponds to a simple transposi-
tion of codex format to electronic format. For example, in a hyper-
text adaptation of an essay such as Marvin Minsky’s Society of Mind,
readers can choose to select a title in the table of contents, search
for a word in the index, or move from section to section by scroll-
ing. The contiguity mode is useful only if a document is divided into
pages and sections that are supposed to be read in a specific order—
as is usually the case with a book.

Selection, association, contiguity, and stratification. In addition to being
accessible by the above-mentioned modes, the elements of informa-
tion can be distributed in two or three hierarchical levels accord-
ing to their degree of complexity. This makes it possible to meet the
needs of various categories of readers or to satisfy different informa-
tion needs for a single reader. This hypertext model best combines
the advantages of the codex with the possibilities opened up by the
computer by taking into account a new dimension of the text, that of
depth. By superimposing different layers of text on a single subject,
or to use another metaphor, by encircling a central nucleus with vari-
ous supplementary documents, the uses of which are well defined, a
stratified hypertext provides several books in one.

Users of such a hypertext could scroll through pages in a main
window, while at the same time being able to open one or more
secondary windows, providing more theoretical or more popular-
ized discourse. There are many fields in which this type of structure
with two or three layers, offering a basic discourse and additional
windows accessible on demand, is desirable. This is the case for self—
teaching textbooks and learning situations, for example, in which the
learner is confronted with a mass of interrelated concepts that may
not all be familiar. It is also the case for technical manuals in which
the user may at any time want to consult supplementary information
on a specific element.

These four modes of navigation may also be combined in the electronic edi-
tion of a work, opening up new perspectives for critical editions of works on
pap er. The main thread of reading would thus be the final version of the text,
dominating the layers of the previous versions, which the reader could also
choose to display in parallel windows. The different pages of the text would
be accessed by contiguity or by selection in a table of contents. Finally, com-
ments, notes, and illustrations would be accessible through connections or
associative links. Because of the richness and diversity of the links provided,
I will call this ideal type of hypertext a “stratified” or “tabular” hypertext.

The success of a tool of this kind obviously depends on the consistency
and interest of the base layer. While this is relatively easy to determine in
the case of a critical edition, the same is not true for other documents. In a
textbook aimed at a diverse readership, the various strata of information it
should contain would have to be established. The base layer would contain
the main thread of the text, consisting of the minimum information at a
medium level of difficulty. On every page where needed, hyperlinks would
open one or two supplementary windows, such as a “novice” window for
users whose knowledge is insufficient for them to grasp the main ideas and
an “expert” window for those who already possess the basic knowledge and
want to know more.

In creating an arrangement capable of working in depth and not only on
the surface of the thread of discourse, the author of a tabular hypertext must
take the utmost care in establishing the different layers and distributing the
information between the base level and the other layers. These choices will
vary with the type of text and target audience. The levels of information may
be distributed on the axis of concrete/ abstract or divided between narrative
and documents or between scholarly text, experimental data, and reference
works, or between didactic text, examples, and exercises, and so on.

Generally speaking, it does not seem desirable to create more than two
layers in addition to the base level. Increasing the number of layers will result
in a proliferation of cross—references, and reading would quickly become dif-
ficult. It is important to remember that in a reader-based textual economy,
reference markers should be provided that allow readers to predict the re—
sults of their actions when moving the mouse pointer over the surface of the
screen. The presence of a “novice” or an “expert” layer linked to a particular
word or page should thus always be indicated in the same way, by an icon
or the use of a color. Novice readers who click on an icon hoping to find an
explanation at their level would quickly become discouraged if, instead of
getting what they wanted, they encountered material intended for experts.
To be effective, reading must be based on stable conventions that enable
maximum concentration on the content.

Stratified hypertext will undoubtedly develop its own conventions just as
the print media did, and these will become part of readers’ culture. In spite
of the problems, this is where the most promising future for hypertext lies
if it is to move beyond the stage of utopian dreams of liberation to become
a productive working tool. However, these modes of organization of hyper—
text may lead to methods of navigation that are very different depending on
the degree of opacity or tabularity of the presentation of data. A literary or
game hypertext may opt for greater opacity in navigation and allow users to
produce events on the screen without knowing where they are or where they
are going. In this case, there are no obvious “movements,” since everything
occurs within the same visual framework. This form of opaque hypertext
may be suited to an experimental narrative such as Stuart Moulthrop’s He-
girascope3 or to an adventure game such as Myst, in which the players have
no idea of their position in relation to the puzzles to be solved. For an infor-
mational document, however, the most satisfying option for readers is one
that gives them a clear view of the distribution of information and enables
them to directly access all the blocks, with full control of their movement.
In this regard, it is significant that some games allow players to choose the
episode they want and allow them to display the percentage of the episode
completed at any time.

One area where the user’s route cannot be left to chance is learning. In-
structional programs and textbooks are based precisely on the principle that
the acquisition of knowledge cannot take place in random order guided only
by the learner’s associations. The first computer-assisted learning (CAL) pro-
grams took this principle of the sequential path to the limit, locking students
into programmed paths in which access to each exercise was conditional on
success in the previous one. Students were expected to move forward blindly,
without knowing how many steps they would have to go through or even,
sometimes, what they would actually learn from the program. Hypertext,
too, can be used in an opaque manner, to totally control users’ progress,
allowing them to follow only branchings accepted by the logic of the pro-
gram, thus reinforcing traditional practices of computer- assisted learning. I
believe, however, that hypertext should adopt some of the characteristics of
the age—old technology of the book to create a new product that will satisfy
the needs of demanding readers who use it as a tool for informational or
educational purposes.

As we can see, the production of a hypertext requires constant strategic
choices by the author. The distribution of elements of information also poses
the problem of identifying every primary textual unit with a title. If these
titles are meaningful to the users, it will be easier for them not only to find
the information they want, but also to keep track of which pages they have
read when they exit from the hypertext. In this way, readers will be able to
have real control over the text instead of being controlled by it or groping
their way through it.

Literary theory also uses the term hypertext, but in a very different sense.
For Gérard Genette, for example, hypertext is “any text derived from a previ—
ous text either through simple transformation . . . or through indirect trans-
formation.”1 In this sense, James Joyce’s Ulysses is a hypertext of Homer’s
Odyssey. The current concept of hypertext, as it comes to us from computer
science and the Web, is closer to that of intertext as first proposed by Julia
Kristeva and redefined by Michael Riffaterre: “the perception, by the reader,
of a relationship between a work and others that have either preceded or fol-
lowed it.” But the two concepts do not coincide completely, since the intertext,
in this meaning, results from the act of reading, while the hypertext we are
talking about is a computer construct of links and data corresponding to files
or parts of files that can be displayed in windows of various dimensions.

There are many hypertext software programs. Among the pioneers are
Hypercard, Hyperties, KMS, Intermedia, and Notecards. Since the advent
of the Web, hypertext has been based mainly on HTML (HyperText Markup
Language), XML (Extensible Markup Language), and XHTML.

Historically, the term hypertext was created in 1965 by Ted Nelson, who
used it to designate a new way of writing on the computer, in which the
units of text could be accessed nonsequentially. The text thus created would
reproduce the nonlinear structure of ideas as opposed to the “linear” format
of books, films, or speech. Nelson himself was indebted to a Visionary article
by Vannevar Bush, who in 1945 already envisaged a huge storage system for
human knowledge that anyone would be able to connect to and that would
allow them to annotate documents of interest. Even before the introduction
of the personal computer, Nelson had attempted to realize Bush’s dream us-
ing a computer system called Xanadu—the name of Mongol emperor Kublai
Khan’s palace, immortalized in a poem by Coleridge as a symbol of memory
and its accumulated treasures. Nelson’s Xanadu was supposed to lead to a
huge universal library system (docuverse), which could be consulted on
workstations by making “micropayments” for each information node ac-
cessed. Despite its commercial implications, Nelson’s model had a profound
influence on the evolution of hypertext, and the World Wide Web may be
seen as its culmination in an unrestricted form.

Hypertext can be used to manipulate data of all kinds, not only linguistic
data but also images, sound, video, and animation. It makes it possible to
regulate a reader’s interaction with a document by programming various
behavior into objects on the screen in relation to the reader’s movements
of the mouse: the author of a computer program can stipulate, for example,
that touching a certain word with the mouse pointer will change its form
or color or trigger a process that will lead to a new text. Through these fea-
tures, hypertext creates a radically new form of electronic dialogue in written
language. Even more numerous than the many forms of books, hypertext
products vary substantially in appearance and internal organization. Indeed,
computer technology can give digitized text any form imaginable.

In a text on paper, the paragraphs or blocks of information are arranged
in sequence, and the reader can access them essentially through contiguity,
relying on a number of tabular elements. In a hypertext, the various blocks
of information may be distinct and autonomous and may be located on a
single “page” or on separate “pages.” In accordance with the nature of the
document and the target readers, the author of a hypertext can provide ac—
cess by means of selection, association, contiguity, or stratification, and these
modes can exist alone or in different combinations.

Selection. In the simplest case, selection, readers select the block of
information they want to read from a list or enter a letter on the
keyboard. The various blocks of information are distinct units with
no essential links among them. Readers are guided by a specific need
for information, which exists only until it is satisfied. This model is
typical of the catalogue, the entire organization of which is based on
the principle of expansion, with each word of the index leading to
a detailed description. Dictionaries also work on this principle, but
each of their entries can also contain references to other entries such
as synonyms, antonyms, and so on. The user may also select from the
list of pages already consulted in the document during the work ses-
sion or may choose from a table of contents or from a tree diagram
in which the various branchings are accessible at different hierarchi-
cal levels. Finally, the most frequent mode of selection is by means of
hyperlinks indicated by a particular color, on which the user clicks in
order to explore the content behind them.

Applied to a text of a certain scope, the principle of selection is
also characteristic of hypertext fiction in which each screen page
includes several links to other pages, making Jorge Luis Borges’s
ideal of forking paths a reality. Similarly, in the case of a philosophi-
cal essay, every block of text could be followed by a number of icons,
each one corresponding to a possible continuation of the text accor—
ding to the anticipated reactions of the reader insofar as the author
could predict them. After reading a segment of text, the reader could
select the most relevant continuation. In so doing, he or she would
become actively involved in reading, making choices, and expressing
opinions at every step through each section read. But the number
of combinations can easily skyrocket. If a block of text gives rise to
three choices, and each of these gives rise to another three, there
would be nine possible continuations of the initial text at the third
level, twenty—seven at the fourth level, and eighty—one at the fifth. As
a result, 121 texts would have to be written for a sequence of five pa—
ragraphs to be accessible in perfectly “free” hypertext mode. Thus the
idea of providing choices at every level has to be abandoned, or their
proliferation would lead the reader into endless movement and force
the author to rigorously explore every logical alternative at each
point in the argument. Moreover, the freedom given the reader is pu-
rely artificial; it only reinforces the dominant position of the author,
who is the master of all possible outcomes.

Selection and association. In this mode, readers choose the element they
wish to consult but can also navigate among the blocks of informa-
tion, letting themselves be guided by the associations of ideas that
arise as they navigate and by the links offered them. This model is
typical of encyclopedias.

* Wrote some on design outlining the [[CoreTerms]]
* Developed a [[Demo of multi-reveal of annotations using appear plugin]]

* Worked on [[Spring 2018 Class Overview]]

# Added [[DWS ToDo]], a to-do List for DesignWriteStudio
# Added [[Bibtex plugin|$:/plugins/tiddlywiki/bibtex]]
# Started Journal to keep track of new devs
# Changed default storyview to classic {{$:/core/ui/Buttons/storyview}}
# Added edit tiddler to default view toolbar
# Expanded [[About]] and began documenting  [[DesignWriteStudio TiddlyWiki]]
# Explored bibtex outputs from Web of Science, Ebsco and ebrary. 
# Developed initial version of [[Annotation Using Ebrary]], the first of the <<tag Exercises>> for the <<tag Spring2018Courses>>
# Added a [[Contents]] tab and rearranged tabs in the Sidebar, and [[set default sidebar menu |$:/core/ui/ControlPanel/Settings]] to [[Contents]].
# Set  [[hide sidebar automatically|hide sidebar]] to no

* Designed structure to support <<tag CoreTerm>> and <<tag CoreSynonym>>

[[Presentation: Text, Interactivity, Writing and Designing]]

Last presentation: <$macrocall $name="youtube-embed" video="EjoWYSKhD5I"/>

{{Four words}}

* Played a bit with CollaborateUltra as possible video production platform. Not happy with outcome to date
* Discussed with Rick Shelton some ideas about video and the course. Agreed that I need
** IRB Notification (maybe exempt)
** Explanation about open source classroom
** Opportunity for pseudonymous participation via google groups
* Should not be a problem for external particiaption via blackboard and/or to watch collaborate ultra video 
* Added [[Display]] and [[menu config options|$:/_Menu/Home/Configuration/Options]] as [[DesignWriteStudio Customizations]]
* Imported .bib file from Web Of Science export and [[Testing Bibtex References from Web Of Science]]

* Worked on CollaborateUltra as possible video platform. Weak :(
* Added to list of [[DesignWriteStudio Exercises]], and refactored name of tag from [[Exercises]]

Unlike hieroglyphic writing, whose pictographic component gives it a visual,
spectacular aspect, alphabetic writing was conceived as a transcription of
speech and was from its inception associated with the linearity of orality. This
linearity is aptly symbolized in the arrangement used in early Greek writing, in
which the characters in the first line were aligned from left to right, and those
in the next line, from right to left, with the characters sometimes inverted,
imitating the path of a plow working a field, a metaphor that gave this type of
writing its name: houstrophedon.1 Readers were supposed to follow with their
eyes the uninterrupted movement the hand of the scribe had traced.

This incunabulum from Thomas Aquinas’s Summa Theologica, printed in 1477 in Venice,
follows the manuscript tradition. The decorated initials and paragraph marks are hand—
drawn. The first lines are in larger letters. There is no pagination. The layout of the text in
two columns and its organization in the form of questions and answers, however, make
it very readable. The illuminations are intensely symbolic. The first page (bottom left) is
illustrated with an image that depicts the teaching of Thomas Aquinas. At the base of the
column, an image depicts the reception of the work by angels (bottom right).

In the fifteenth century, the printing revolution was another time of in-
tense reflection on the organization of the book. Febvre and Martin8 note
that the title page made its appearance—finally!——around 1480. After the
infancy of the modern book, the period of incunahula—books that imitated
manuscripts as faithfully as possible—printers quickly saw the full potential
of the page as a discrete semiotic space.

Page numbering, which became common in the mid-sixteenth century,
enabled readers to better control the duration and pace of their reading and
facilitated the discussion of texts by making it possible for readers of the same
edition to refer to the same passage. Once this step was taken, the move-
ment toward tabularization intensified, and sophisticated techniques allowing
multiple points of entry into the text became widely used, such as paragraph
summaries in the margin and the running head. It was now possible for
readers to precisely locate the point they had reached in their reading and to
compare the relative size of different sections—in short, to control their read-
ing progress. They could also forget the details of what they had read earlier,
since they could quickly find them again by referring to a table of contents
or index. They could read only the parts of a book that interested them.
Especially if a book is long, readers often construct the meaning on the
basis of clues of various types. Typographical markers such as bold, capitals,
italics, or color allow them to quickly classify the elements they read and to
avoid ambiguity; for example, the italicization of foreign words prevents con-
fusion with homonyms. When justified by the material, an index of proper
names, a detailed index, or a bibliography permits readers to choose the way
of accessing the text that best suits their information needs of the moment.
These reading aids did not come into use all at once but were slowly refined,
in a process that culminated in the golden age of print in the nineteenth cen-
tury, when the progress of mechanization heralded the triumph of the printed
page. The table of contents, for example, appeared in the twelfth century. The
paragraph break, the concept of which had been expressed through the use
of the pilcrow in manuscripts of the eleventh century, was finally indicated
by a line break, as seen in an edition of Gargantua printed in Lyon in 1537.
Thus shaped by the ergonomics of the codex, the text was no longer a linear
thread that was unreeled, but a surface whose content could be perceived from
various perspectives. These reading aids, which allow readers to consider the
text the same way they look at a painting or tableau, are here called tabular.

With the introduction of printing, the art of publishing fluctuated between
the temptations of textual continuity and those of pictorial page layout. On
the one hand, an austere layout in which the text was rigidly aligned within
the frame of the page was best for emphasizing the mechanical perfection of
printing and the linear aspect of language and reading; on the other hand,
publishers could also be tempted by a complex layout in which the text was
presented in different visual blocks among which readers could pick and
choose as they wished, exploring their relationships in nonsequential order.
These fluctuations in the ideal of the book can be observed across different
periods. In this regard, it is informative to compare some of the printing
manuals studied by the typography expert Fernand Baudin. A manual pub-
lished by the printer Fertel in 1723, entitled La science pratique de l’imprimerie,
is a model of complex layout in which marginal glosses sometimes spill over
into the space of the main text. In contrast, a manual published forty years
later, written by Fournier, presents the text in a single, rather narrow column
and seems to have gone back to the linear order. As for the book by Baudin,
who was himself a typ ographer and wished to give an account of an art that
was the passion of his life, it is in large format, with a column of glosses and
cross-references systematically running down one side of the main column
and sometimes even framing it, as Fertel’s glosses do.

The challenge of printed text, in short, is to strike a balance between se-
mantic and visual demands, the ideal obviously being a combination of these
two modes of access to the text around a coherent focus. We can still ob—
serve the naive triumph of the visual over the semantic in even the titles of
sixteenth-century books, in which printers did not hesitate to cut out words
in order to create a symmetrical effect.

For Walter Ong, this segmentation shows that reading did not focus on
the visual aspect of the words grasped globally, but was still based on oral
practices; the presentation of the text was independent of its semantic aspect.
It is also likely that such practices involved a kind of playful allusion to a way
of reading that was already seen as outmoded.

Today, publishers make such effort to enable the reader to perceive com~
plete words that they sometimes hesitate to break a word at the end of a line,
and thus to use justified text, although that was the typographical ideal for
centuries, beginning in the time of the volumen. This concern with match
ing the semantic unit with the unit of visual perception is also evident in
magazines, which tend increasingly to make the text of articles fit into the
space of the page or double page.

It is now commonly acknowledged that the revolution of the codex was
not limited to ergonomics, but that it also had an impact on the nature of
content and the evolution of mentalities in general. Indeed, once a text is
perceived as a visual entity, and no longer as primarily oral, it lends itself
much more readily to criticism. The eye, given the richness of optic nerve
endings in the cortex, can mobilize the analytical faculties more easily and
more precisely than the ear. As historian Henri-Jean Martin notes on the
revolution of printing in the sixteenth century: “By the same token, any
reasoned argument was as if detached from the realms of God and men and
took on an objective existence. The written text became amoral because it
detached from the writing process and no longer demanded that the reader
take on responsibility for it by reading it aloud. This may have facilitated
heretical propositions.”

The process by which the text became an autonomous object crossed a new
threshold during the Enlightenment, when the last barriers to its generali-
zed objectification collapsed. That era coincided precisely with spectacular
growth in reading in Europe. We will come back to this question.

With the advent of newspapers and the mass-circulation press, which
underwent rapid expansion in the nineteenth century, the formatting of
text became even more tabular. In a radical departure from the original
linearity of speech, text was now presented in the form of visual blocks that
complemented and responded to each other on the eye-catching surface of
the page. McLuhan gave a name to the metaphor implicit in this arrange—
ment: the “mosaic” text. Indeed, newspapers provide a textual mosaic, in
which the reading of various types of information is subtly influenced by the
surrounding news, as has been pointed out by analysts of newspaper layout:
“For about a century, newspapers have been laid out in such a way that each
item of information, though flat on the page, stands out by virtue of the mere
fact of its coexistence with other items of information on the page, which
in turn acquire their value from this competition? ’1” The same authors note
that until the end of the nineteenth century, newspapers consisted simply
of vertically aligned columns, each of which theoretically constituted a page
that went on without interruption. “This type of layout naturally favored a
temporal sequence of discourse: there were no interruptions for turning
pages, no illustrations to create a break or suspension of reading, and no
lead or subheading introducing secondary material. This form corresponds
exactly to the temporal logic of discourse: It is the presentation of logos in
movement, and not the staging of an event.”11

Orality thus extended its influence over the medium of text. The scribe
lined up columns of text on sheets of papyrus—which had been in use since
3000 BCE—until he came to the end of the scroll. Despite the characteristics
that made the papyrus scroll the quintessential book for three millennia, the
fact that it was rolled up into a volumen placed serious limitations on the
expansion of writing and helped maintain the book’s dependence on oral
language. It was taken for granted that readers would read from the first line
to the last and that they had no choice but to immerse themselves in the text,
unrolling the volumen as a storyteller recounts a story in a strictly linear con—
tinuous order. In addition, readers needed both hands to unroll the papyrus,
which made it impossible to take notes or annotate the text. Worse still, as
Martial observed, readers would often have to use their chin when rerolling
the volumen, leaving marks on the edge that were rather off-putting to other
library users (“Sic noua nec mento sordida charta iuuat” [“How pleasant is
a new exemplar unsoiled by chins”] .2

The sudden appearance of banner headlines was the beginning of a new
kind of layout, one'no longer guided by the logic of discourse, but by a spa-
tial logic. “The number of columns, the use of rules, the weight of the type,
the font, the position of illustrations, and the use of color make it possible
to bring together or move apart, to select, and to separate the units that, in
the newspaper, are units of information. Layout then emerges as a rheto-
ric of space that destructures the order of discourse (its temporal logic) to
reconstitute an original discourse, which is precisely the discourse of the
newspaper.”12

Today, there is no doubt that tabularity meets the formatting requirements
of information texts in that it allows the reader to apprehend them most
effectively. This is especially apparent in magazines, where the dominant
model involves framing textual material by means of a hierarchy of titles:
section heading, main heading and subheadings. A more substantial article
will often be presented in the form of a feature story that, in addition to the
main text, includes one or more sidebars elaborating on points raised in the
main text. Such fragmented layouts are sometimes criticized. Their primary
function is clearly to hold on to readers whose attention span is unsteady or
short, unlike a linear format, which is intended for the “serious reader.” This
way of breaking up text into different elements is also very well suited for
communicating a variety of information that readers can select according
to their interests. On the other hand, popular magazines may diverge a bit
from this ideal and give predominance to glossy ads and photographs in or—
der to entice the reader to leaf through their pages and absorb the discourse
of advertising.

When tabularity is taken into account, then, printed text is not exclusively
linear and tends to incorporate characteristics of the visual realm. Readers
are thus able to free themselves from the thread of the text and go directly
to relevant elements. A book may thus be said to be tabular when it involves
the simultaneous spatial presentation and highlighting of various elements
that may help readers identify the connections and find information that
interests them as quickly as possible.

The concept of tabularity thus covers at least two distinct phenomena—4n
addition to designating an internal arrangement of data. On the one hand,
it refers to the various organizational means that facilitate access to the con—
tent of the text: This is functional tabularity, as shown in tables of contents,
indexes, and division into chapters and paragraphs. On the other hand,
tabularity also suggests that the page may be viewed in the same way as a
painting and may include data from various hierarchical levels: This is visual
tabularity, which enables readers to switch from reading the main text to
reading notes, glosses, figures, or illustrations, all of which are present within
the space of the double page. This visual tabularity, which is seen primarily
in newspapers and magazines, is also found in varying degrees in scholarly
books, which may present various types of text juxtaposed on a single page.
It is obviously highly developed in electronic publishing, as seen on the
Web pages of major newspapers, magazines, and encyclopedias. In addi-
tion, through a hybridization of publishing techniques, the layout of books
or magazines increasingly borrows from the methods of electronic publish—
ing, such as the use of color, underlining, and marking of text elements, with
cross-references to thumbnails or sidebars. In this type of tabularity, the text
is shaped like visual material, with blocks referring to each other on the page
surface and sometimes incorporating illustrations.

The spatial projection of the thread of the text obviously depends on the
format of the book. The smaller the book, the less manipulation of the visual
blocks is possible; readers are confined to a continuous movement through a
single column of text with no interruption. This format, which was adopted,
for example, by the famous French collection Bibliotheque de la Pléiade, tends
to reinforce the ideal of a linear typography with nothing to break its regular-
ity. It is especially well suited to novels, which are read for content. National
traditions prevent French publishers from placing the table of contents at
the front of the book as it is in the English-speaking world, a position better
suited to the tabular ideal and to readers’ needs.

It should be added, however, that the degree of tabularity of a book will
also depend on its content and intended use. Thus, children’s books often do
not have page numbers: young readers have no need for them, since these
books are designed to be read or looked at from cover to cover and there is
no expectation of a reflective reading with note taking or references. Schol-
arly books, which are intended for readers for whom time is valuable, have
many tabular guideposts: volumes, chapters, sections, paragraphs, headers,
notes, introductory summaries, detailed index, index of proper names, and
bibliography. But the linear thread may still be a justifiable choice for devel-
oping an argument, insofar as the author wishes to ensure that the reader
follows the entire proof. On the other hand, the novel, which is derived from
the ancient art of the storyteller, generally demands sustained reading and
does not require elaborate tabular clues. The large number of chapters and
the hierarchy of sections in Victor Hugo’s novels, which often have a very
linear narrative thread, may be explained by the fact that these novels were
initially published in serial form in newspapers. Today, some writers, anxious
to make their readers read continuously and to have their work seen as high
literature, as different as possible from the tabular format of the magazine,
dispense altogether with chapters, and even paragraphs and punctuation.

The advent of the codex was a radical break with this old order, and it
brought about a revolution in the reader’s relationship to the text. A codex
consists of pages folded and bound to form what we today call a book. These
pages were made of papyrus or parchmentmpaper having appeared in Eu-
rope only in the 11005. The codex emerged in classical Rome, several decades
before the Common Era, at the time of Horace, who used one himself as a
notebook. Smaller and easier to handle than a scroll, the codex was also more
economical, because it allowed scribes to write on both sides and even to
scrape off the surface and write on it again. But because of its antiquity, the
scroll was still considered to have greater dignity and was preferred by the
cultured elite, a status the codex did not acquire for several centuries. The
transition really took place only in the fourth century in the Roman Empire.
And it took even longer for the new medium to free itself from the model of
the volumenfljust as it took the automobile several decades to completely
rid itself of the model of the horse-drawn carriage. Such is the inertia of
dominant cultural representations.

Christians were the first to adopt the codex, which they used to spread the
Gospels. The new format, which was smaller, more compact, and easier to
hide and to handle than the scroll, also had the advantage of representing a
sharp break with the tradition of the Jewish Bible. Historians find more and
more evidence that the latter reason was in part responsible for the choice
of the codex format by the Christians, but the wide adoption of the codex
over the following centuries was essentially due to “the twin advantages of
comprehensiveness and convenience.”

The new element the codex introduced into the economy of the book was
the page. I will look at the problem of the integration of this important in-
novation into the digital order in the section “The End of the Page? [chapter
34]” It was the page that made it possible for text to break away from the
continuity and linearity of the scroll and allowed it to be much more easily
manipulated. Over the course of a slow but irreversible evolution, the page
made text part of the tabular order.

The codex is the quintessential book, without which the pursuit and dis-
semination of knowledge in our civilization could not have developed as fully
as they have. The codex gave rise to a new relationship between reader and
text. As one historian of the book writes, “This was a crucial development
in the history of the book, perhaps even more important than that brought
about by Gutenberg, because it modified the form of the book and required '
readers to completely change their physical position.”4 The codex left one
of the reader’s hands free, allowing him or her to take part in the cycle of
writing by making annotations, thus becoming more than a mere recipient
of the text. Readers could also now access the text directly at any point. A
bookmark let them take up reading where they left off, further altering their
relationship to the text. As another historian notes, it took “twenty centuries
for us to realize that the fundamental importance of the codex for our civili-
zation was to enable selective, noncontinuous reading, thus contributing to
the development of mental structures in which the text is dissociated from
speech and its rhythms.”5

When the potential of this union of form and content in the page became
apparent, various types of visual markers were gradually added to the organi-
zation of the book to help readers find their bearings more easily in the mass
of text and make reading easier and more efficient. Since the page constitutes
a visual unit of information related to the preceding and the following pages,
allowing it to be numbered and given a header, it has an autonomy that the
column of text in the volumen did not. Thanks to the page, it is possible to leaf
through a book and quickly know its contents, or at least the essentials.

The page can be displayed for all to see, inviting monks in scriptoria to
combine text and images. While the papyrus was rolled up again after read-
ing, the codex can remain open to a double page, as demonstrated by the big
psalters of the Middle Ages that were displayed on their lecterns in churches.
The page was thus the place where the text, which was previously seen as a
mere transcription of the voice, entered the visual order. From then on, it
would increasingly be handled like a painting and enriched with illumina-
tions, something that was profoundly foreign to the papyrus scroll. One can-
not see these illuminated manuscripts without being struck by their fusion of
letter and image. Reading becomes a polysemiotic experience in which the
perception of the image, which is far from a mere illustration, enables readers
to recreate in their own mental space the tensions and emotions experienced
by the artist. The readable gradually moves into the realm of the visible.6

The sight of the codex open on its lectern is emblematic of a religion whose
ideal was that all people should be able to read the sacred texts and share the
Revelation. Various other innovations gave rise to a change in the reader’s
relationship to the text and to reading. They include the insertion of spaces
between the words in Latin texts, which began about 700 CE in Irish scripto-
ria (Book of Kells) and led to decisive changes in the formatting of text.7 The
period from the eleventh to the thirteenth century saw the consolidation of
many features that allowed readers to escape the original linearity of speech,
such as the table of contents, the index, and the header. Paragraph breaks
indicated in the text by a pilcrow (9) made it easier for readers to deal with
units of meaning and helped them to follow the main divisions in the text.

* The [[official report|https://archive.org/details/911_final_report]]  of the commission that investigated the terrorist attacks of September 11, 2001 includes an amazing chapter, "[[WE HAVE SOME PLANES|https://govinfo.library.unt.edu/911/report/911Report_Ch1.htm]]." The chapter includes details a minute-by-minute timeline of the activities of the [[19 hijackers|https://en.wikipedia.org/wiki/Hijackers_in_the_September_11_attacks]]. 
* An interesting project can emerge by hypertextualizing the text of the chapter and  the tables in Wikipedia, allowing readers to navigate by various dimensions, including time, plane (the way the chapter is organized), terrorist, etc.

A consideration of how to implement the <$appear show="core features of hypertext »" hide="core features of hypertext «">(<$list filter="[tag[Core features of hypertext]]"><<currentTiddler>> </$list>)</$appear> within Google apps: 

* Transcluding: Paste Linked sheet cells in Docs and Slides
* Linking: Table  of Contents in  Docs; Hyperlinks in Sheets
* Tagging? Conditional formatting in Sheets?
* Listing?
* Templating: Style sheets in Docs. 

A consideration of how to implement the <$appear show="core features of hypertext »" hide="core features of hypertext «">(<$list filter="[tag[Core features of hypertext]]"><<currentTiddler>> </$list>)</$appear> within Office 365, with a focus on Sharepoint meta-data opportunities for tagging. 

A review and analysis of Roam, "a note-taking tool for networked thought," and one of the most interesting entrants into knowledge management -- the most hypertextual tool of the class?

* https://roamresearch.com/

http://sunypoly-steve-google-news.tiddlyspot.com/

The DesignWriteStudio is, first and foremost, a learning community, by which is meant a group of people (participants) sharing an interest in learning from and with each other. More formally: <$appear show=">>" hide="<<"><$transclude tiddler=LearningCommunities mode="block"/></$appear>

~McEneaney, J. E. (2002). A transactional theory of hypertext. 

[[Link|http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.89.9217&rep=rep1&type=pdf]]

<h2>A Web page</h2> a document in html format that is responsive to an http:// request
<h2> that anyone can write</h2>with modest technical skills
<h2>...but not that anyone can edit</h2>so not collaboratively written

* Tagged to the [[Core Features of Hypertext]]

I learned how to create a plugin today, using [[Tinka - the easy plugin packer|https://tinkaplugin.github.io/]]. The plugin is called  [[DesignWriteStudio - showNotes|$:/plugins/DesignWriteStudio/showNotes/read.me]]:
<hr>
{{$:/plugins/DesignWriteStudio/showNotes/read.me}}
<hr>
If the 
So you should be able to drag/drop from the plugins tab on the [[$:/ControlPanel]] to your wiki. Let me know if it works (or not) in the {{GoogleGroup}}.

* Modest barrier to entry
* DIY / ~MakerSpace / Code
* Multi-disciplinary (humanities, social sciences, mathematics, natural sciences)
* Useful at all [[points in the digital text cycle|Hillesund2005DigitalTextCycles]], as well as in full production mode

Welcome to ''Stroll'', a notetaking tool built with the ~TiddlyWiki platform, imitating a number of features of Roam: 

*bi-directional links, 
*autocomplete suggestions for linking, 
*renaming of links upon changing tiddler titles, 
*and side-by-side editing of multiple notes. 

Stroll is a new souped up replacement for our previous project, [[TiddlyBlink|https://giffmex.org/gifts/tiddlyblink.html]]. It is designed for use with a wide screen - probably not ideal for use on a phone or small tablet.

The best way to see what Stroll can do is play with it. This interactive tutorial will give you a hands-on overview.

Use the tabs to the left to take a tour of its features. You can download an empty version of Stroll [ext[here|https://giffmex.org/stroll/empty.html]].

* Build on ability in TiddlyWiki to easily and systematically vary presentation (such as in [[Designing & Writing Interactive Texts: Part II]]), and develop through google forms interaction (using partially completed forms, as in COM 302 project) some user data. 
* [[Justin Cushing]]: http://designwritestudio.com/sunypoly-cushinj-ny.html

The ''Designing and Writing Interactive Texts'' course explores hypertext theory and applies hypertextual techniques using TiddlyWiki as the primary teaching and learning platform.

The course is offered at both the graduate <$appear state="$:/575"><$transclude tiddler="SUNY Poly IDT 575 Spring 2018" mode="block"/></$appear> and undergraduate <$appear state="$:/375"><$transclude tiddler="SUNY Poly COM 375 Spring 2018" mode="block"/></$appear> level.  Degree-seeking students in the course are mostly matriculated in the graduate Information Design & Technology or undergraduate Interactive Media & Game Design or Communication & Inforamtion Design programs.

In addition, the course will be offered as an [[Open Course|Open Course Spring 2021]] (perhaps a SOOC - a //small// online open course) to anyone interested in participating. 

Finally, it is hoped that experienced TiddlyWiki enthusiasts will join the Studio as participants: reviewing and critiquing projects, providing support to participants, and possibly engaging in collaborative projects with participants.

Participants will study the historical and theoretical aspects of hypertext, and apply this understanding in the design and writing of interactive texts using TiddlyWiki. The primary teaching resources will include: 

# Links to as many TiddlyWiki tutorials as can be identified
# Twice-weekly 35-minute video/screen presentations on hypertext history and theory. These presentations will be recorded and made available in this wiki.
# Occasional video/screen presentations featuring guest commentators on hypertext and TiddlyWiki.
# Three weekly live-streamed workshops open to all participants
# Links to identified / annotated scholarly references examining hypertext
# A Google group for support and questions
# TiddlyWiki projects created and critiqued within the DesignWriteStudio community

More detail on the course is available in the [[Course Syllabus|Syllabus]]''. 

Hello. My name is [[Steve Schneider]], and I am a [[College Professor]] at the [[SUNY Polytechnic Institute]]. 

Before [[working]] as a college professor, my other [[Occupations]] were [[Adjunct Faculty Member]] at [[Wellesley College]] and [[Research Analyst]] at [[Kalba Bowen Associates]].

When I am [[driving]], I am frequently behind the wheel of a [[Red Honda Fit]]. Sometimes, I drive the [[Blue Dodge Dakota]]. These are just two of the many [[Cars I have owned]]. Before the Fit, I drove a [[Blue Subaru Forester]] and before that, a [[Grey Subaru Forester]].

There are a bunch of [[Digital activities in which I engage]], some while working and others while [[relaxing]].  When I am [[surfing the Web]], [[tweeting]], [[listening to podcasts]] or [[music|listening to music]], or [[texting]] with my family, 
I use an [[Apple iPhone SE]]. This phone replaced my [[Apple iPhone 5]]. Other [[Digital devices that I own]] include a [[Google Home]] (also for listening to podcasts or music) and an [[Apple MacBook Air]] (for [[working]] and [[watching videos]]. I

Over the years, I have had several <<tag "Occupations">>. There are many <<tag "Cars I have owned">>. There are several <<tag "Digital devices that I own">>. And, not surprisingly, there are different <<tag "Digital activities in which I engage">>.

I have some shape tiddlers:

* <$count filter="[tag[Circle]]"/> tagged <<tag Circle>>
* <$count filter="[tag[Square]]"/> tagged <<tag Square>>
* <$count filter="[tag[Large]]"/> tagged <<tag Large>>
* <$count filter="[tag[Red]]"/> tagged <<tag Red>>
* <$count filter="[tag[Blue]]"/> tagged <<tag Blue>>
* <$count filter="[tag[Large]]"/> tagged <<tag Large>>
* <$count filter="[tag[Medium]]"/> tagged <<tag Medium>>
* <$count filter="[tag[Small]]"/> tagged <<tag Small>>
<hr>

My shape tiddlers have some characteristics:

* <$count filter="[tag[Shape]]"/> <<tag Shape>>
* <$count filter="[tag[Color]]"/> <<tag Color>>
* <$count filter="[tag[Size]]"/> <<tag Size>>
<hr>

Here are my <<tag Blue>> tiddlers:

<$list filter="[tag[Blue]]">
{{!!title}}<br>
{{!!text}}<br>
</$list>

 

The ''Designing and Writing Interactive Texts'' course explores hypertext theory and applies hypertextual techniques using TiddlyWiki as the primary teaching and learning platform.

The course is offered at both the graduate <$appear state="$:/575"><$transclude tiddler="SUNY Poly IDT 575 Spring 2018" mode="block"/></$appear> and undergraduate <$appear state="$:/375"><$transclude tiddler="SUNY Poly COM 375 Spring 2018" mode="block"/></$appear> level.  Degree-seeking students in the course are mostly matriculated in the graduate Information Design & Technology or undergraduate Interactive Media & Game Design or Communication & Inforamtion Design programs.

In addition, the course will be offered as an [[Open Course|Open Course Spring 2018]] (perhaps a SOOC - a //small// online open course) to anyone interested in participating. 

Finally, it is hoped that experienced TiddlyWiki enthusiasts will join the Studio as participants: reviewing and critiquing projects, providing support to participants, and possibly engaging in collaborative projects with participants.

Participants will study the historical and theoretical aspects of hypertext, and apply this understanding in the design and writing of interactive texts using TiddlyWiki. The primary teaching resources will include: 

# Links to as many TiddlyWiki tutorials as can be identified
# Twice-weekly 35-minute video/screen presentations on hypertext history and theory. These presentations will be recorded and made available in this wiki.
# Occasional video/screen presentations featuring guest commentators on hypertext and TiddlyWiki.
# Three weekly live-streamed workshops open to all participants
# Links to identified / annotated scholarly references examining hypertext
# A Google group for support and questions
# TiddlyWiki projects created and critiqued within the DesignWriteStudio community

More detail on the course is available in the [[Course Syllabus|Syllabus]]''. 

The ~TiddlyCast is a Zoom-based conversation ((link will be here when available) for the  ~TiddlyWiki community, live streamed  at  Noon Wednesday EST <$appear show="(see other timezones)" hide="(hide other timezones)") state="$:/tiddlycast1"> 

{{Noon Wednesdays Utica Time}}
</$appear>

<$details summary="A TiddlyCast is a  different kind of podcast" open="yes" class="level3">
There will several ~TiddlyBites in each episode that will be tiddlers in the true sense of word:  "fundamental units of information" and "as small as possible so that they can be reused by weaving them together in different ways."<$appear 
show="»" hide="«">[[https://tiddlywiki.com/#Tiddlers]]</$appear>
</$details>


<$details summary="The Tiddlycast is designed to appeal to those interested in exploring writing and designing interactive texts" open="yes" class="level3">
We  are  especially interested in sharing with those currently engaged in learning how to use ~TiddlyWiki for the first time.

We will live-stream on eight consecutive Wednesdays beginning June 1, 2021 and continuing through July 20, 2021.

<$vars thisTiddler="TiddlyCast">
<$list filter="[tag<thisTiddler>]">
<$details summary=<<currentTiddler>>  field="caption" open="no" class="level3" >
<$transclude mode="block"/>
</$details>
</$list>
</$vars>

@@border:1px solid crimson;  BETA   @@

''Quick demo'' and background - note the //two buttons//:

StretchText is an <<stretch "old" "hypertext concept." "Ted Nelson coined the term around 1967 ([[ref|https://en.wikipedia.org/wiki/StretchText]]).">> It enables authoring ''text for different readers with'' <<stretch "''varying levels''" "of interest or knowledge." "For example, a text can immerse in detail and difficulty - or the opposite; it can add clarifications or examples.">>  It's an alternative to //links// and //pop-ups// but it lets the reading stay in the text.

In this implementation the aim is:

*simple syntax (see below)
*minimal distraction when reading the text

!!!!Installation
To your TW, shlepp over [[$:/_TWaddle/Stretch/Macro]] and [[$:/_TWaddle/Stretch/CSS]]

!!!!Syntax
:#.&nbsp;&nbsp;&nbsp;  `<<stretch "label" "rest" "content">>` ...or...
:#.&nbsp;  `<<stretch "label" "" "content">>` ...or...
:#.&nbsp; `<<stretch "label" "content">>`
<br>

*''label'' - the button text or symbol or dots "...".
**If you want to use multiple buttons with //identical labels//, title them;<br>hey''_1'', hey''_2'' etc. Anything after the ''_'' is hidden from display.
*''rest'' - refers to the remaining sentence-part after the button.
**This enables you to reveal the content without <<stretch "splitting" "the current sentence." "The remaining half sentence otherwise appears //after// the stretched content which is both confusing and distracting.">> 
**Note that the //rest// parameter can be; used, empty or completely omitted.

*''content''
**Type text directly - or transclude content like so;<br>`<<stretch "label" "{{...}}">>` - no transcludewidget needed. Take a stretchy peek at the <<stretch "stylesheet" "for example :-)" "{{$:/_TWaddle/Stretch/CSS}}">>

:...there are also the <<stretch "usual" "macro-call text-format quirks." """
⦁ &nbsp;if the argument, i.e the //label, rest// or //content// text, contains quotemarks (");
&nbsp;&nbsp;&nbsp; - surround the argument with triple quotemarks
&nbsp;&nbsp;&nbsp; - ...or with single quotemarks (like so: //'this "is" an argument'// ) 
⦁ &nbsp;some formatting doesn't work, e.g bullet lists (for this one, I'm using ⦁ )
""">>

!!!!Notes
*The buttons could, of course, be styled to appear like normal blue links instead. 
*I think [a better implementation of] StrechText would make for a very interesting <<stretch "//Storyview//" " in TW." """Instead of "click link + jump" to tiddlers, you'd use StrechText to immerse //into// the tiddler(s). The text really //evolves//. It's similar to the //Zoomin// storyview but keeps displaying the context around it. It might only make sense for as long as the link stays on the current tiddlers topic, or else the text remaining //after// the evolved content would become irrelevant.""">>
*Thanks to @JeremyRuston for enlightening me that [[StretchText|https://en.wikipedia.org/wiki/StretchText]] was an already established concept!


<br>//Mat von [[TWaddle|http://twaddle.tiddlyspot.com]]//

* Explore the genre of the adventure game <<wikipedia "Adventure_game">> and build one in TiddlyWiki.
* Consider finding the text and code of an existing adventure game, and adapt it or a portion of it to TiddlyWiki (perhaps [[Colossal Cave Aventure|https://en.wikipedia.org/wiki/Colossal_Cave_Adventure]])
* Write a new adventure, and develop some specific techniques that would facilitate adventure game development (such as having multiple tag (list) fields for each tiddler

* Word, Docs, Text editors, PDF
* PowerPoint, Slides
* Enhances Excel, Sheets
* Database (SQL) programs?
* Content Management Systems, Site Generators, Dreamweaver, etc.
* http://alternativeto.net/software/tiddlywiki/

Here, you have a text box into which you can type things:<br>

``
<$edit-text tiddler="MyTextTiddler" field="text" default=""/>
``

<$edit-text tiddler="MyTextTiddler" field="text" default=""/>

<hr>

<$vars MyTextTiddler="MyTextTiddler">

* What's happening is that the contents of that text box are written to the tiddler [[MyTextTiddler]] with each keystroke (the keystroke causes the wiki to regenerate itself)
* You can tell this by looking at the modified time of the tiddler [[MyTextTiddler]]:
<p> <h2>{{MyTextTiddler!!modified}}</h2></p>



*The ~EditTextWidget can not change properties of the tiddler it is embedded in or part of (see [[tiddlywiki.com|https://tiddlywiki.com/#EditTextWidget]]), so we use a second tiddler, in this case called [[MyTextTiddler]].
* We can transclude the contents of [[MyTextTiddler]] like this:
** ``{{MyTextTiddler}}`` : <h1>{{MyTextTiddler}}</h1>.
* You might find it helpful to create a field in your primary tiddler. Create a field ``mytextfield`` with value ``{{MyTextTiddler}}`` and you'll be able to transclude it like this::
** ``{{!!mytextfield}}``<h1>{{!!mytextfield}}</h1>

<svg width="12" height="12">
  <circle cx="6" cy="6" r="6" fill="black"/>
<text x="50%" y="50%" text-anchor="middle" stroke="#FFFFFF" stroke-width="1px" dy=".25em" fill="white">a</text>
</svg>

* Develop tool to facilitate annotating sources and generating an annotated bibliography (<<google "annotated bibliography">>)
* See [[demo|https://designwritestudio.updog.co/skunkworks/bibtex/bibliography3.html]] for overview of bibtex system, if one wanted to go in that direction. Could also consider building onto [[Zotero|zotero.org]] which can export bibtex file, 
* Build demo based on SUNY Poly library resources for an approach to a literature review (could be project for IDT 520)

These are my annotations so far<br>
<$list filter="[tag[Annotation]]">
<$link><<currentTiddler>></$link><br>
</$list>

# Use advanced search {{$:/core/ui/Buttons/advanced-search}}  to filter  all tiddlers associated with the Annotator.
# Paste  ``[tag[Annotator]]`` into the <$button class="tc-btn-invisible tc-tiddlylink"><$action-setfield $tiddler="$:/state/tab-1749438305" text=" $:/AdvancedSearch/Filter"/><$action-navigate $to="$:/AdvancedSearch"/>Advanced Search - filter </$button> tab
# Export as .tid file
# Import into your Annotator wiki. You should see these tiddlers imported into your wiki<br><$list filter="[tag[Annotator]]">
<$link><<currentTiddler>></$link><br>
</$list>

\define newtitlemacro() $(user)$-annotation $(static-title)$

\define annotate(from-tiddler)
<$set name=user value={{$:/status/UserName}}>
<$set name=static-title value=$from-tiddler$>
<$button class="tc-btn-invisible tc-tiddlylink">
<$action-setfield $tiddler=<<newtitlemacro>> tiddler-type="annotation" from-tiddler=<<static-title>>/>
<$action-sendmessage $message="tm-edit-tiddler" $param=<<newtitlemacro>>/>
{{Annotate-button}}</$button>
<<designwrite "[[Annotator Macros]]: annotate">>
\end

\define show-annotation(of-tiddler)
<$list filter="[title[Annotation Template]field:visible[yes]]">
<$set name=user value={{$:/status/UserName}}>
<$set name=static-title value=$of-tiddler$>

<$list filter='[<newtitlemacro>tags[]]'>
<<tag>>
</$list>


<div style="background-color:yellow">
<p><$transclude tiddler=<<newtitlemacro>> mode="block"/></p>
</div>
<<designwrite "[[Annotator Macros]]: show-annotation">>
\end

\define designwrite(text)
<$list filter="[title[Annotator Macros]field:visible-dox[yes]]">
^^$text$^^<br>
</$list>
\end

\define annotation-nav(essay paragraph)
<$set name=essay value=<<essay>>>
<$set name=paragraph value=<<paragraph>>>
<$button>
<$action-navigate $to=<<essay>>/>
<!--put the essay title as the label for the button-->
<$transclude tiddler=<<essay>>/>
</$button>
Paragraph <$count filter="[list<essay>allbefore:include<paragraph>]"/> of <$count filter="[list<essay>]"/> ||
<$list filter="[list<currentTiddler>first[]]">
<$link to=<<currentTiddler>>>First</$link> ||
</$list>
<$list filter="[list<essay>before<paragraph>]">
<$link to=<<currentTiddler>>>Previous</$link> ||
</$list>
<$list filter="[list<essay>after<paragraph>]">
<$link to=<<currentTiddler>>>Next</$link> ||
</$list>
<$list filter="[list<currentTiddler>last[]]">
<$link to=<<currentTiddler>>>Last</$link> 
</$list>
<<designwrite "[[Annotator Macros]] annotation-nav">>
\end

\define essay-nav-first(essay)
<$set name=essay value=<<essay>>>
<$list filter="[list<currentTiddler>first[]]">
<$link to=<<currentTiddler>>>Read in Paragraph Mode</$link><br>
</$list>
<<designwrite "[[Annotator Macros]] annotation-nav-first">>
\end



\define show-annotations()
<$checkbox tiddler="Annotation Template" field="visible" checked="yes" unchecked="no" default="no">{{Show Annotations-button}}</$checkbox>
<<designwrite "[[Annotator Macros]] show-annotations">>
\end

\define checkboxtag(tiddler parentTag)
<$link to="$parentTag$">$parentTag$</$link> <$list filter="[tag[$parentTag$]]"><$checkbox tiddler="$tiddler$" tag=<<currentTiddler>> ><<currentTiddler>></$checkbox>
</$list>
<<designwrite "[[Annotation Macros]]| checkboxtag">>
\end

\define show-dox()
<$checkbox tiddler="Annotator Macros" field="visible-dox" checked="yes" unchecked="no" default="no">{{Show Dox-button}}</$checkbox>
<<designwrite "[[Annotator Macros]] show-dox">>
\end

<span class="bigbold">We have focused our attention on <<howMany "" "Hypertextual Practices" "hypertextual practices">></span><$appear state="$:/practices"><<tabs "[tag[Hypertextual Practices]sort[title]]">></$appear><br>

<span class="bigbold">You have engaged these practices using specific techniques for [[hypertextual writing|Techniques for Hypertextual Writing in TiddlyWiki]] and [[creating tiddlers|Technique for Creating Tiddlers in TiddlyWiki]] </span><$appear state="$:/techniques"><<tabs "[tag[Techniques for Hypertextual Writing in TiddlyWiki]sort[title]] [tag[Technique for Creating Tiddlers in TiddlyWiki]]">></$appear><br>



<span class="bigbold">You will now turn your attention to [[creating and implementing self-designed exercises|Creating interactive texts based on self-designed exercises]] that engage these practices and use these techniques </span>
<$appear state="$:/designx"><<tabs "[tag[Creating interactive texts based on self-designed exercises]]">></$appear><br>

* Build on [[http://zuckerberg-testimony-annotated.tiddlyspot.com/]]
* Also for [[archived Web pages in Internet Archive|https://designwritestudio.updog.co/projects/dmss-2017/tiddlywiki-as-monadic-exploration-tool.html#Demo%202%3A%20Identifying%20and%20analyzing%20archived%20Web%20pages]]
* Develop exercises for DesignWriteStudio that detail these processes
* Develop templates for researchers and scholars to use as evidence in projects

Bush, V. (1945, July). As we may think. The Atlantic Monthly 176(1), 101-108. [[Online|https://www.theatlantic.com/magazine/archive/1945/07/as-we-may-think/303881/]].

[[As We May Think|http://en.wikipedia.org/w/index.php?title=As_We_May_Think]]

See [[Assignment 01: Introduction to Class, Hypertext, and TiddlyWiki]] for all details on <<tag "Assignment 01">>.

!Assignment Overview
This goals of this assignment are to:

* Introduce yourself to the class.
* Introduce the topic of [[Hypertextuality|Hypertext (Wikipedia)]].
* Introduce [[TiddlyWiki|https://tiddlywiki.com/]] as a learning platform for [[Hypertextuality|Hypertext (Wikipedia)]].

!!Part 1: Configure ~TiddlyWiki File
[[Configure|TiddlyWiki Configuration]] your ~TiddlyWiki file by following the steps for [[downloading|Download TiddlyWiki]] and [[saving|Saving in TiddlyWiki]].

!!Part 2: Development of <<tag Techniques>> Associated with Creating Hypertexts
An objective of this assignment is to develop basic techniques associated with creating hypertexts generally, and in ~TiddlyWiki specifically. You are asked to create a hypertextual version of the Information Design & Technology (IDT) program's course catalog. In ~TiddlyWiki, you will [[create a tiddler|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]] for each course that is part of the program, and then assign tags to each tiddler so that you can enable navigation of your emergent hypertext.

For each course, you'll need the course number, title, and description. Your first challenge is to find that text digitally somewhere on the Internet. Your second challenge is to ingest (translate? copy/paste?) that text into tiddlers, giving each tiddler an appropriate and useful title and set of tags. After / during your process of [[creating tiddlers|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]], you can explore different tagging strategies that make the hypertextual version of the catalog you are creating useful for you (and perhaps for others).

!!! Part 2: Source Text
Find a copy of the SUNY Poly catalog online, or a listing of courses for the IDT program. You might try to copy/paste the text into a more manageable form — perhaps a spreadsheet or google document, so that the text is easy for you to access in a predictable and stable way.

!!! Part 2: Creating Tiddlers: Title, Text, Tags
For each course in the program, [[create a new tiddler|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]]. The title should be the course number, followed by a consistent symbol (usually a colon or a dash) , and the course title.  

For the text, paste in the course description provided by the catalog.

For tags, enter the following:

* Course Discipline and number, without spaces: IDT575
* Descriptors of the relationship you have to the course, written either as multi-wird tags or as ~WikiWords. Here are some examples of possible tags to use:

```
"Completed Course" InterestedInTaking "Writing Intensive" ExcellentCourse
```
//To learn more details about [[tagging|Tagging]] in ~TiddlyWiki, please visit the [[online guide|https://tiddlywiki.com/#Tagging]].//

!!! Part 2: Creating / Editing Tiddlers Created By Tagging
* Edit the tiddlers that are created by each of the skills/knowledge tags that you reference in your course tiddlers:
** ''Text'': include a short sentence or phrase describing in more detail the skill/knowledge area (e.g., if you use the tag ~InDesign describe what ~InDesign is in the ~InDesign tiddler).
** ''Tags'': ``Skills``
* Edit the "Skills" tiddler to include an overall assessment of the skills and knowledge areas your courses have touched.

!! Part 3: Introduce Yourself
Write a short introduction / bio to introduce yourself to the class.  Your introduction / bio should minimally include:

* ''Introduction and Course Expectations'': Write 1 – 2 short paragraphs introducing yourself to the class (including at least one image of yourself), along with your expectations for this course.  If you have prior experience with ~TiddlyWiki and/or Hypertext, please feel free to note it within your introduction.
* ''Commentary'': Write 1 – 2 short paragraphs providing commentary on some aspect of your experience in ~TiddlyWiki and/or with hypertext so far; referencing ideas drawn from the readings for this assignment as well as any thoughts on the the usage of [[Linking]], [[Tagging]] and [[Transclusion]]. 

''Due Date:'' Sunday, June 6, 2021 by 11:59pm

{{Assignment 01: Due Date}}

{{Assignment 01: Objectives}}

{{Assignment 01: Required Readings}}

{{Assignment 01: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 01: Grading Details}}

!Objectives
# Introduce yourself to the class.
# Create and organize a set of tiddlers using [[Tagging]] and [[Transclusion]].
# Comment on the hypertextuality of the work produced.

!Required Readings
* [[The Machine is Us/ing Us]]
* [[Introduction to Computer Lib / Dream Machines (Nelson)]]
* [[As We May Think (Bush)]]
* [[As We May Think (Wikipedia)]]
* [[Hypertext (Wikipedia)]]
* [[Grok TiddlyWiki]]

See [[Assignment 02: Introduction to Hypertextualization]] for all details on <<tag "Assignment 02">>.

!Assignment Overview
We are ready to move on to the next step, which we will call "[[hypertextualization|Hypertext TiddlyWiki (from IDT507)]]."

In this assignment, the objective is to take existing texts and add value or knowledge to them with your own materials.  We will work with two sets of texts: the [[hypertextual version of the IDT course catalog|Assignment 01: Introduction to Class, Hypertext, and TiddlyWiki]] you built in [[assignment 01|Assignment 01]], and some of chapters in the <$appear show="Hypertext/Hypermedia Handbook [+]" hide="Hypertext/Hypermedia Handbook [-]">{{Hypertext/Hypermedia Handbook}}</$appear>.

!!Part 1: Using a Taxonomy to [[Tag|Tagging]] Tiddlers
For this part of the assignment, you should review each of the tiddlers you created for individuals classes in your [[hypertextual version of the IDT course catalog|Assignment 01: Introduction to Class, Hypertext, and TiddlyWiki]]. For example, you may created a tiddler for ``IDT 575``. Clicking on "tags" should reveal an opportunity to add tags that are associated with the [[IDEA Learning Objectives]].  For each of the courses you have entered in the catalog, you should go in and tag them to the <<strex "{{IDEA Learning Objectives}}" "IDEA Learning Objectives">> you believe should (or are) associated with the course. You can then review your work, and in the [[IDEA Learning Objectives]] tiddler.

Write a [[hypertextualized|Hypertext TiddlyWiki (from IDT507)]] summary (1 - 2 paragraphs) of the extent to which the IDT program touches the breadth and depth of these objectives.

!!Part 2: [[Hypertextualizing|Hypertext TiddlyWiki (from IDT507)]] an Existing Text
For this part of the assignment, we want you to actively engage the texts in the  [[Hypertext/Hypermedia Handbook]]. Select one of the first three texts in the <<tag "[[Hypertext/Hypermedia Handbook]]>> and add "value" to it with information and knowledge that you develop. This could be done with <<strex "{{Linking}}" "links">> to external resources such as citations or search queries; annotations inserted into the text of [[tiddlers you write|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]], [[transclusions|Transclusion]] of texts that you discover that are related, or other approaches.

Write a summary (1 - 2 paragraphs) proving details on newly developed hypertextual approaches, as well as commenting on this aspect of "hypertextualization" -- adding value to existing information through the use of [[tags|Tagging]], [[transclusion|Transclusion]], and [[links|Linking]].

''Due Date:'' Sunday, June 13, 2021 by 11:59pm

{{Assignment 02: Due Date}}

{{Assignment 02: Objectives}}

{{Assignment 02: Required Readings}}

{{Assignment 02: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 02: Grading Details}}

!Objectives
# Create a taxonomy of the [[IDEA Learning Objectives]] associated with courses in the [[SUNY Poly IDT program|https://sunypoly.edu/academics/majors-and-programs/ms-information-design-technology.html]] using the [[hypertextual technique|Techniques]] of [[Tagging]].
# Create an interactive text by using various <$appear show="hypertextual techniques [+]" hide="hypertextual techniques [-]">{{Techniques}}</$appear> such as [[Tagging]], [[Transclusion]], and [[Linking]].

!Required Readings
* [[Hypertext/Hypermedia Handbook]]
* <$appear show="Hypertext ~TiddlyWiki (from IDT507) [+]" hide="Hypertext ~TiddlyWiki (from IDT507) [-]">{{Hypertext TiddlyWiki (from IDT507)}}</$appear>
* [[Grok TiddlyWiki]]

! Submission Details

Submit your assignment by posting within the [[Assignment 02: Introduction to Hypertextualization|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326676_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Narrative as outlined in the [[Assignment 02: Assignment Overview]].
* A [[link|Linking]] to your ~TiddlyWIki file that you uploaded to the [[assignment 02 folder|https://drive.google.com/drive/folders/1nVfwx21J5VYfFMFmOzxESNSIGmfW-4v7?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your ~TiddlyWIki file will showcase your hypertext version of the IDT course catalog from the [[first assignment|Assignment 01: Introduction to Class, Hypertext, and TiddlyWiki]], as well as the hypertextualized details from <$appear show="assignment 02 [+]" hide="assignment 02 [-]">{{Assignment 02}}</$appear>.

See [[Assignment 03: Hypertextualization of Existing Text]] for all details on <<tag "Assignment 03">>.

! Assignment Overview
In this assignment, we will engage in the practice of hypertextualizing an existing text, in this case the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]] from volume 50 of the //Encyclopedia of Library and Information Science//. This book chapter was published in 1992 and a few things have happened that may be relevant to our understanding of hypertext in the 25 years since this chapter was published -- most importantly, the emergence of the Web as a medium used by billions of people every day -- that may inform our understanding of its topic. Our goal in this assignment is to both bring the text up to date so that it reflects our current understandings, and to add value to its presentation by enhancing it with hypertextual elements such as <<strex "{{Linking}}" "links">>, <<strex "{{Transclusion}}" "transclusions">> and <<strex "{{Tagging}}" "tags">>.

The full text of the chapter is [[available online|https://repository.arizona.edu/handle/10150/105403]] which can, with some work, be copy / pasted into tiddlers.

For this project, each student should focus on two tasks:

* ''Hypertextualization:'' Choose an approach to hypertextualizing the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]], following a consistent style or set of conventions. For example, you might chooce to use <<strex "The ~TextStretch macro is a great tool, for you as an author of hypertext, to keep the message short. Your readers can discover more details easily." "the ~TextStretch macro">> for definitions and <$appear show="Appear macro [+]" hide="Appear macro [-]">This plugin provides the ''$appear'' widget that can render popups and sliders (inline or block) as well as accordion menus.</$appear> for updated materials. Your readers should be able to follow the conventions to enhance and simplify their reading experience. In Part 3 of this assignment, you are asked to document and explain your conventions.

* ''Updated Research:'' For the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]], identify scholarly or professional trade publications, ideally published after 2004, that provide a more contemporary understanding of the issues being addressed. Aim for //at least 2 - 4 references// as you hypertextualize the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]]. Intersperse ([[transclude?|Transclusion]]) findings and/or discussion from the contemporary references into the hypertextualized version of the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]]. Consider using elements such as headings as organizing approachs providing [[links|Linking]] and [[transclusions|Transclusion]] to / from various sections ([[tiddlers?|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]]).

!Part 1: Import Source Material and Develop a Plan for Hypertexualization

For the <<strex "{{Hypertext / Hypermedia (McKnight, Dillon, Richardson)}}" "Hypertext / Hypermedia book chapter">>, import the text into tiddlers, and read / correct as necessary to make consistent with the [[online version|https://www.ischool.utexas.edu/~adillon/BookChapters/Encyc-text.htm]] of the chapter.  Do some [[basic formatting|https://tiddlywiki.com/#Formatting%20text%20in%20TiddlyWiki]] (headers, etc.) to make the texts more readable, and develop a strategy or plan for hypertextualization. 

Write a brief overview (1 - 2 short paragraphs) of your [[hypertextualization|Hypertext TiddlyWiki (from IDT507)]] plans for the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]].

!Part 2: Contemporary Research

Identify a //minimum// of 2 - 4 scholarly or professional references, ideally published in 2004 or later, that address themes or issues raised in the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]] you are working with. Create a reference tiddler for each scholarly or professional reference. //Note, you can use any formatted reference, including MLS, APA, or bibtex.  You can get formatted references from [[Google Scholar|https://scholar.google.com/]].//

[[Develop tiddlers|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]] tagged to your <<strex "{{Course Readings}}" "reference tiddlers">> with notes and concepts that add understanding to the issues raised in the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]]. Add value to the original [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]] by using  <<strex "{{Linking}}" "links">>, <<strex "{{Transclusion}}" "transclusions">> and <<strex "{{Tagging}}" "tags">> to include additional information and contemporary understanding of the topics.

!Part 3: Bringing It All Together

Submit your narrative and the link to your ~TiddlyWiki file in the [[Assignment 03: Hypertextualization of Existing Text|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326677_1&course_id=_26639_1&group_id=&mode=view]] assignment area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your narrative should minimally include: 

* Your brief overview (1 - 2 short paragraphs) of your [[hypertextualization|Hypertext TiddlyWiki (from IDT507)]] plans for the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]].
* A summary (1 - 2 paragraphs) proving details to explain your hypertexualization conventions.
* A [[link|Linking]] to your ~TiddlyWiki file that you uploaded to [[assignment 03 folder in Google Drive|https://drive.google.com/drive/folders/1cIgT76wxBIUPbBXIyUgJpF7riZjnp9p7?usp=sharing]].

Your ~TiddlyWIki file for this assignment should minimally include:

* A way to navigate to the hypertextualized version of the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]] that includes your additional information and references to add contemporary understanding of the topics.

''Due Date:'' Sunday, June 20, 2021 by 11:59pm

{{Assignment 03: Due Date}}

{{Assignment 03: Objectives}}

{{Assignment 03: Required Readings}}

{{Assignment 03: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 03: Grading Details}}

!Objectives
# Develop and execute a strategy for creating ([[writing|Writing]]) a [[hypertextualized|Hypertext TiddlyWiki (from IDT507)]] interactive text that includes considerations for how users will [[read|Reading]] via ~TiddlyWiki.
# Create an interactive text that adds value to an existing text by using various <$appear show="hypertextual techniques [+]" hide="hypertextual techniques [-]">{{Techniques}}</$appear> such as [[Tagging]], [[Transclusion]], and [[Linking]].

!Required Readings
* Review the [[Assignment 01: Required Readings]].
* Review the [[Assignment 02: Required Readings]].
* Read the [[Hypertext / Hypermedia book chapter|Hypertext / Hypermedia (McKnight, Dillon, Richardson)]].

! Submission Details

Submit your assignment by posting within the [[Assignment 03: Hypertextualization of Existing Text|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326677_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Narrative as outlined in the [[Assignment 03: Assignment Overview]].
* A [[link|Linking]] to your ~TiddlyWiki file that you uploaded to [[assignment 03 folder|https://drive.google.com/drive/folders/1cIgT76wxBIUPbBXIyUgJpF7riZjnp9p7?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your ~TiddlyWIki file will showcase your hypertext version of the IDT course catalog from the [[first|Assignment 01: Introduction to Class, Hypertext, and TiddlyWiki]] and [[second|Assignment 02: Introduction to Hypertextualization]] assignments, as well as the hypertextualized details from <$appear show="assignment 03 [+]" hide="assignment 03 [-]">{{Assignment 03}}</$appear>.

See [[Assignment 04: Organizing Your TiddlyWiki as a Class Portfolio]] for all details on <<tag "Assignment 04">>.

If preferred, you can navigate through the [[assignment 04 details|Assignment 04: Organizing Your TiddlyWiki as a Class Portfolio]] by using the tabs below.
<<tabs "[title[*]] [tag[Assignment 04]]">>

! Assignment Overview

The purpose of this assignment is to utilize the skills learned to date, such as [[Creating and Editing Tiddlers|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]], <<strex "{{Linking}}" "Linking">>, <<strex "{{Tagging}}" "Tagging">>, <<strex "{{Transclusion}}" "Transclusion">>, etc. to present hypertextual information in an easily consumable / <$appear show="readable [+]" hide="readable [-]">{{Reading}}</$appear> manner.

For this assignment, you should focus on updating your [[TiddlyWiki|https://tiddlywiki.com/]] file so your created content is available to the reader when your [[TiddlyWiki|https://tiddlywiki.com/]] file is initially loaded without the use of [[Permalinks|https://tiddlywiki.com/#PermaLinks]].  

//Expand <<strex "{{Your Created Content}}" "Your Created Content">> for the definition for this assignment.//

!! Helpful Hint(s)
Learn about using [[DefaultTiddlers|https://tiddlywiki.com/#DefaultTiddlers]] and [[how to add a new tab to the sidebar|https://tiddlywiki.com/#How%20to%20add%20a%20new%20tab%20to%20the%20sidebar]]may provide valuable information for completing this exercise.

!! Summary Narrative
Write a brief overview regarding your experiences trying to balance utilizing [[hypertextuality|Hypertext TiddlyWiki (from IDT507)]] with presenting information in an easily consumable / [[readable|Reading]] manner (i.e., web / [[information design|https://en.wikipedia.org/wiki/Information_design]]).

''Due Date:'' Sunday, June 27, 2021 by 11:59pm

! Objectives
# Create an organizational structure in your [[TiddlyWiki|https://tiddlywiki.com/]] file to display your created content using [[TiddlyWiki|https://tiddlywiki.com/]] functionality and [[affordances|https://sunypoly.open.suny.edu/bbcswebdav/courses/202106-IDT-575-3070/cohend-idt507-assign4.html#%5B%5BTiddlyWiki%20and%20Hypertext%5D%5D]].

{{Assignment 04: Due Date}}

{{Assignment 04: Objectives}}

{{Assignment 04: Required Readings}}

{{Assignment 04: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 04: Grading Details}}

!Required Readings
* Review the [[Assignment 01: Required Readings]].
* Review the [[Assignment 02: Required Readings]].
* Review the [[Assignment 03: Required Readings]].

! Submission Details

Submit your assignment by posting within the [[Assignment 04: Organizing Your TiddlyWiki as a Class Portfolio|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326678_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Summary narrative as outlined in the [[Assignment 04: Assignment Overview]].
* A [[link|Linking]] to your [[TiddlyWiki|https://tiddlywiki.com/]] file that you uploaded to [[assignment 04 folder|https://drive.google.com/drive/folders/1YV7xqQgYjQ6tLyv7Tq2IDQ1m6ImliFAY?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your [[TiddlyWiki|https://tiddlywiki.com/]] file will showcase <$appear show="your created content [+]" hide="your created content [-]">{{Your Created Content}}</$appear>, as well as any additional details from [[assignment 04|Assignment 04]].

See [[Assignment 05: Exploring Two-Dimensional and Multi-Dimensional Hypertext]] for all details on <<tag "Assignment 05">>.

If preferred, you can navigate through the [[assignment 05 details|Assignment 05: Exploring Two-Dimensional and Multi-Dimensional Hypertext]] by using the tabs below.
<<tabs "[title[*]] [tag[Assignment 05]]">>

! Assignment Overview
The purpose of this assignment is to use a combination of tools such as spreadsheets (i.e., [[Google Sheets|https://www.google.com/sheets/about/]], [[Microsoft Excel|https://products.office.com/en-us/excel]], etc.) and ~TiddlyWiki and hypertextual <$appear show="techniques [+]" hide="techniques [-]">{{Techniques}}</$appear> such as <<strex "{{Filtering}}" "Filtering">> and <<strex "{{Sorting}}" "Sorting">> to create two-dimensional and multi-dimensional interactive content.

For this assignment, you should focus on creating content within a spreadsheet and then importing that content into your [[TiddlyWiki|https://tiddlywiki.com/]] file by using the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin. 

//Note: In order to utilize the  plugin, the [[JSZip plugin|$:/plugins/tiddlywiki/jszip]] plugin must also be installed.//

!! Part 1: XLSX Spreadsheet Utilities Plugin
To install and use the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin, you must:

# Import the [[$:/plugins/tiddlywiki/xlsx-utils]] tiddler into your [[TiddlyWiki|https://tiddlywiki.com/]] file.
# Import the [[$:/plugins/tiddlywiki/jszip]] tiddler into your [[TiddlyWiki|https://tiddlywiki.com/]] file.
# Configure the XLSX Utilities within the [[$:/ControlPanel]].

!!! Reference Materials
* Video: [[XLSX Import Tool|https://youtu.be/r7XyGCbY4E4]] (52-minutes) created by [[Steven Schneider|https://sunypoly.edu/faculty-and-staff/steven-schneider.html]].

!! Part 2: Two-Dimensional and Multi-Dimensional Hypertext
An objective of this assignment is to expand your use of hypertectual [[techniques|Techniques]] (such as [[Filtering]] and [[Sorting]]) associated with creating hypertexts generally, and in ~TiddlyWiki specifically. You are asked to create two-dimensional and multi-dimensional interactive content within a spreadsheet (i.e., [[Google Sheets|https://www.google.com/sheets/about/]], [[Microsoft Excel|https://products.office.com/en-us/excel]], etc.) and import this content as individual tiddlers using the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin.

Students should create a spreadsheet that represents some digital objects //of their choice//. Think of the rows in the spreadsheet as the objects, and the columns in the spreadsheet as the characteristics of the objects. For example, the [[Our Cars Owned|https://drive.google.com/file/d/1otRpIE0ZdCt86c_cMIu4wxJp1McDTZ8F/view?usp=sharing]] spreadsheet contains a header row (Row 1), and 11 additional rows. Each row (after the header row) represents a car we have owned, and each column represents an attribute of the car (or data to be added into each tiddler).
* You should create a spreadsheet with ''at least seven'' objects of your choice, with each object having ''at least four'' characteristics. //As stated, the data and objects can be anything.// As you think of the spreadsheet, visualize how it might be presented as tiddlers with [[links|Linking]], [[tags|Tagging]], and as a [[Collection of Tiddlers]]. Feel free to use the [[Our Cars Owned|https://drive.google.com/file/d/1otRpIE0ZdCt86c_cMIu4wxJp1McDTZ8F/view?usp=sharing]] spreadsheet as a [[template|Templating]] by downloading a copy to your computer or your personal [[Google Drive|http://drive.google.com/]].

//Note: The Created and Modified columns are using the ``Now()`` function within Microsoft Excel to add a specific date and time. This data is important if you want the imported tiddlers to show up in the [[Recent|$:/core/ui/SideBar/Recent]] tab.//

!! Part 3: Summary Narrative
Write a brief overview regarding your experiences utilizing the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin, [[importing tiddlers|https://tiddlywiki.com/#Importing%20Tiddlers]], and conceptualizing digital objects in two-dimensional and multi-dimensional space. The summary narrative should be written 
[[hypertextuality|Hypertext TiddlyWiki (from IDT507)]].  Your [[TiddlyWiki|https://tiddlywiki.com/]] file should present all of [[your created content from the first three assignments|Your Created Content]], as well as any additional content from [[assignment 04|Assignment 04]] and this assignment ([[assignment 05|Assignment 05]]) in an easily consumable / [[readable|Reading]] manner (i.e., web / [[information design|https://en.wikipedia.org/wiki/Information_design]]).

''Due Date:'' Sunday, July 11, 2021 by 11:59pm

{{Assignment 05: Due Date}}

{{Assignment 05: Objectives}}

{{Assignment 05: Required Readings}}

{{Assignment 05: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 05: Grading Details}}

! Objectives
# Develop an understanding of theoretical concepts and the [[Sorting]] and [[Filtering]] hypertextual [[techniques|Techniques]].
#* Visualize digital objects in two-dimensional and multi-dimensional space.
#  Design and develop [[techniques|Techniques]] to represent digital objects in two-dimensional and multi-dimensional space and implement ([[write|Writing]]) using spreadsheets (i.e., [[Google Sheets|https://www.google.com/sheets/about/]], [[Microsoft Excel|https://products.office.com/en-us/excel]], etc.) and ~TiddlyWiki.
#  Demonstrate the ability to [[read|Reading]] hypertextually with [[filtering|Filtering]] within the spreadsheet software.
# Demonstrate the ability to gather information from two-dimensional and multi-dimensional hypertexts.

! Required Readings
* Review the previous required readings from  [[assignment 01|Assignment 01: Required Readings]], [[assignment 02|Assignment 02: Required Readings]], [[assignment 03|Assignment 03: Required Readings]], and [[assignment 04|Assignment 04: Required Readings]].
* Read three or four results returned by [[Google Scholar|http://goo.gl/22C2Sh]] or [[Google|http://goo.gl/6VpNzJ]] from the ``"multidimensional hypertext"`` query.

! Submission Details

Submit your assignment by posting within the [[Assignment 05: Exploring Two-Dimensional and Multi-Dimensional Hypertext|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326679_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Summary narrative as outlined in the [[Assignment 05: Assignment Overview]].
* A [[link|Linking]] to your [[TiddlyWiki|https://tiddlywiki.com/]] file that you uploaded to [[assignment 05 folder|https://drive.google.com/drive/folders/1TDKAWOILOAKPUPAQLidn6oQ4U1FaGiLi?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your [[TiddlyWiki|https://tiddlywiki.com/]] file will showcase [[your created content from the first three assignments|Your Created Content]], as well as any additional content from [[assignment 04|Assignment 04]] and this assignment ([[assignment 05|Assignment 05]]) in an easily consumable / [[readable|Reading]] manner (i.e., web / [[information design|https://en.wikipedia.org/wiki/Information_design]]).

See [[Assignment 06: Filtering and Sorting as a Display Mechanism]] for all details on <<tag "Assignment 06">>.

If preferred, you can navigate through the [[assignment 06 details|Assignment 06: Filtering and Sorting as a Display Mechanism]] by using the tabs below.
<<tabs "[title[*]] [tag[Assignment 06]]">>

! Assignment Overview
The purpose of this assignment is to use ~TiddlyWiki and the hypertextual <$appear show="techniques [+]" hide="techniques [-]">{{Techniques}}</$appear> of <<strex "{{Transclusion}}" "Transclusion">>, <<strex "{{Filtering}}" "Filtering">> and <<strex "{{Sorting}}" "Sorting">> to create interactive content.

For this assignment, you should focus on updating your [[TiddlyWiki|https://tiddlywiki.com/]] file to include the use of [[Transclusion]], [[Sorting]], and [[Filtering]] to display a subset of your already created content.  This will provide the reader with another option to interact with the content you've created to date.

!! Part 1: Filtering Data
The IDT Course Catalog that was [[already created|Your Created Content]] provides existing content that can be enhanced by the use of the [[Filtering]] hypertextual [[technique|Techniques]]. Specifically, the use of [[Filtering]] may allow for the creation of various list(s) of IDT courses without having to create link(s) to each tiddler.  An example of how this might be accomplished is to use the ''[[list-links macro|https://tiddlywiki.com/#list-links%20Macro]]'' with the ''prefix'' [[Filter Operator|https://tiddlywiki.com/#Filter%20Operators]] as shown below.

`<<list-links "[prefix[IDT]]">>`

For this part of the assignment, you need to demonstrate the use of [[Filtering]].  In order to do so, you should [[create a new tiddler|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]] or a series of new tiddlers that display components of the IDT course catalog.  Some examples have been added to the [[example TiddlyWiki file|https://sunypoly.open.suny.edu/bbcswebdav/courses/201906-IDT-575-3123/IDT575-Examples.html]] for your review.

//Note, the [[Tag Macro]] that has been throughout this course is another example of using [[Filtering]].//

!! Part 2: Sorting Data
Your <$appear show="already created content [+]" hide="already created content [-]">{{Your Created Content}}</$appear> to date provides existing content that can be enhanced by the use of the [[Sorting]] hypertextual [[technique|Techniques]]. Specifically, the use of [[Sorting]] allows for the creation of various list(s) and/or array(s) that display in ascending or descending order. In addition, the [[Assignment 06: Required Readings]] provides access to the various kinds of sorts available within ~TiddlyWiki.

For this part of the assignment, you need to demonstrate the use of [[Sorting]].  In order to do so, you should [[create a new tiddler|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]] or a series of new tiddlers that display portions of your [[already created content|Your Created Content]] sorted in ascending and descending order. You may want to experiment with the different sort options to see how as some ignore case-sensitivity while others do not. Some examples have been added to the [[TiddlyWiki Examples]] for your review.

!! Part 3: Summary Narrative
Write a brief overview regarding your experiences utilizing [[Sorting]] and [[Filtering]] within ~TiddlyWiki. The summary narrative should be written 
[[hypertextuality|Hypertext TiddlyWiki (from IDT507)]].

''Due Date:'' Sunday, July 18, 2021 by 11:59pm

{{Assignment 06: Due Date}}

{{Assignment 06: Objectives}}

{{Assignment 06: Required Readings}}

{{Assignment 06: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 06: Grading Details}}

! Objectives
# Develop an understanding of theoretical concepts and the [[Sorting]] and [[Filtering]] hypertextual [[techniques|Techniques]].
#  Design and develop [[techniques|Techniques]] to represent digital arrays in various ways using the [[Sorting]] and [[Filtering]]  functionality of ~TiddlyWiki.
#  Demonstrate the ability to [[read|Reading]] and [[write|Writing]] hypertextually with [[Sorting]] and [[Filtering]] within ~TiddlyWiki.

! Required Readings
* Review the previous required readings from  [[assignment 01|Assignment 01: Required Readings]], [[assignment 02|Assignment 02: Required Readings]], [[assignment 03|Assignment 03: Required Readings]], [[assignment 04|Assignment 04: Required Readings]], and [[assignment 05|Assignment 05: Required Readings]].
* Read the [[sort Operator|https://tiddlywiki.com/#sort%20Operator]], [[sortcs Operator|https://tiddlywiki.com/#sortcs%20Operator]], [[sortby Operator|https://tiddlywiki.com/#sortby%20Operator]], [[sortan Operator|https://tiddlywiki.com/#sortan%20Operator]], [[nsortcs Operator|https://tiddlywiki.com/#nsortcs%20Operator]], and [[nsort Operator|https://tiddlywiki.com/#nsort%20Operator]] documentation.
* Read the [[Filters|https://tiddlywiki.com/#Filters]] documentation //(including the [[Introduction to filter notation|https://tiddlywiki.com/#Introduction%20to%20filter%20notation]], [[Filter Syntax|https://tiddlywiki.com/#Filter%20Syntax]], and [[Filter Operators|https://tiddlywiki.com/#Filter%20Operators]] tiddlers in the ''Find Out More'' section)//.
* Read the [[Searching in TiddlyWiki|https://tiddlywiki.com/#Searching%20in%20TiddlyWiki]] documentation to learn how to take full advantage of the Advanced Search capabilities.

! Submission Details

Submit your assignment by posting within the [[Assignment 06: Filtering and Sorting as a Display Mechanism|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326680_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Summary narrative as outlined in the [[Assignment 06: Assignment Overview]].
* A [[link|Linking]] to your [[TiddlyWiki|https://tiddlywiki.com/]] file that you uploaded to [[assignment 06 folder|https://drive.google.com/drive/folders/1Ijaq3Um5hMNRjx3uJFAF8hqWQMVxPDYs?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your [[TiddlyWiki|https://tiddlywiki.com/]] file will showcase [[your created content from the first three assignments|Your Created Content]], as well as any additional content from [[assignment 04|Assignment 04]], [[assignment 05|Assignment 05]], and this assignment ([[assignment 06|Assignment 06]]) in an easily consumable / [[readable|Reading]] manner (i.e., web / [[information design|https://en.wikipedia.org/wiki/Information_design]]).

See [[Assignment 07]] for all details on <<tag "Assignment 07">>.

If preferred, you can navigate through the [[assignment 07 details|Assignment 07]] by using the tabs below.
<<tabs "[title[*]] [tag[Assignment 07]]">>

! Assignment Overview


The purpose of this assignment is to demonstrate the [[hypertextual|Hypertext TiddlyWiki (from IDT507)]] skills and approaches used throughout this course to create an interactive text that adds value to an [[existing text|Universal Principles of Design]] provided by the instructor.

For this assignment, you will use a combination of tools such as spreadsheets (i.e., [[Google Sheets|https://www.google.com/sheets/about/]], [[Microsoft Excel|https://products.office.com/en-us/excel]], etc.) and ~TiddlyWiki as well as hypertextual <$appear show="techniques [+]" hide="techniques [-]">{{Techniques}}</$appear> such as <<strex "{{Linking}}" "Linking">>, <<strex "{{Tagging}}" "Tagging">>, <<strex "{{Transclusion}}" "Transclusion">>, <<strex "{{Filtering}}" "Filtering">> and <<strex "{{Sorting}}" "Sorting">> to create multi-dimensional interactive content.

!! Part 1: Import Spreadsheet Data
Import the [[Universal Principles of Design spreadsheet data|https://drive.google.com/file/d/1yaXwrjnDUD_XxcM4Hquu5E5uZ9GJPgF2/view?usp=sharing]] provided by the instructor using the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin.

!!! Reference Materials
* Review the [[Assignment 05: Assignment Overview]] for reference materials on using the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin. 
* Review the [[TiddlyWiki Examples]] to see an example of the [[XLSX Spreadsheet Utilities|$:/plugins/tiddlywiki/xlsx-utils]] plugin mapping, as well as an example displaying the imported [[Universal Principles of Design]] data after import.

//Note: Be sure to map both sheets within the [[Universal Principles of Design spreadsheet|https://drive.google.com/file/d/1yaXwrjnDUD_XxcM4Hquu5E5uZ9GJPgF2/view?usp=sharing]]. If done correctly, the import will create [[multi-dimensional interactive content|Universal Principles of Design]] as demonstrated in the [[TiddlyWiki Examples]].//

!! Part 2: [[Hypertextualizing|Hypertext TiddlyWiki (from IDT507)]] an Existing Text
Actively engage in the [[Universal Principles of Design]] text after import and add "value" to it with information and knowledge you have learned throughout the [[IDT program|https://sunypoly.edu/academics/majors-and-programs/ms-information-design-technology.html]] and/or this course.

For this part of the assignment, you need to demonstrate the use of all [[hypertextual techniques|Techniques]]. Specifically, the [[hypertextualized|Hypertext TiddlyWiki (from IDT507)]] version of the [[Universal Principles of Design]] book should demonstrate effective uses of [[Linking]], [[Tagging]], [[Transclusion]], [[Sorting]], and [[Filtering]].  //Note, the [[Templating]] technique is also being used by importing the [[Universal Principles of Design spreadsheet|https://drive.google.com/file/d/1yaXwrjnDUD_XxcM4Hquu5E5uZ9GJPgF2/view?usp=sharing]].//

!! Part 3: Summary Narrative
Write a brief overview regarding your experiences utilizing all <<strex "{{Techniques}}" "hypertextual techniques">> within ~TiddlyWiki to create one interactive text. The summary narrative should be written 
[[hypertextuality|Hypertext TiddlyWiki (from IDT507)]].

{{Assignment 07: Due Date}}

{{Assignment 07: Objectives}}

{{Assignment 07: Required Readings}}

{{Assignment 07: Assignment Overview}}

{{Assignment Submission Details}}

{{Assignment 07: Grading Details}}

''Due Date:'' Sunday, July 25, 2021 by 11:59pm

! Objectives

# Demonstrate the ability to create ([[writing|Writing]]) a [[hypertextualized|Hypertext TiddlyWiki (from IDT507)]] interactive text that includes considerations for how users will [[read|Reading]] via ~TiddlyWiki.
# Demonstrate the ability to create an interactive text that adds value to an existing text by using various <$appear show="hypertextual techniques [+]" hide="hypertextual techniques [-]">{{Techniques}}</$appear> such as [[Tagging]], [[Transclusion]], [[Linking]], [[Filtering]], and [[Sorting]].
#  Demonstrate [[techniques|Techniques]] to use digital objects in two-dimensional form to create a multi-dimensional space and implement ([[write|Writing]]) using spreadsheets (i.e., [[Google Sheets|https://www.google.com/sheets/about/]], [[Microsoft Excel|https://products.office.com/en-us/excel]], etc.) and ~TiddlyWiki.
# Demonstrate the ability to utilize [[TiddlyWiki|https://tiddlywiki.com/]] functionality and [[affordances|https://sunypoly.open.suny.edu/bbcswebdav/courses/202106-IDT-575-3070/cohend-idt507-assign4.html#%5B%5BTiddlyWiki%20and%20Hypertext%5D%5D]].

! Required Readings
Review the previous required readings from all prior [[assignments|Assignments]].
<<list-links "[suffix[Required Readings]]">>

Review the [[Universal Principles of Design]] book provided within the [[Assignment 07 folder|https://drive.google.com/drive/folders/1J4__L2XEkzXApL2pnCZpwp-0HpN2HqqN?usp=sharing]] within [[Google Drive|https://drive.google.com]].

! Submission Details

Submit your assignment by posting within the [[Assignment 07: Culminating Activity|https://sunypoly.open.suny.edu/webapps/assignment/uploadAssignment?content_id=_1326681_1&course_id=_26639_1&group_id=&mode=view]] area within our [[Blackboard course|https://sunypoly.open.suny.edu/webapps/blackboard/execute/courseMain?course_id=_26639_1]]. Your assignment submission should include:

* Summary narrative as outlined in the [[Assignment 07: Assignment Overview]].
* A [[link|Linking]] to your [[TiddlyWiki|https://tiddlywiki.com/]] file that you uploaded to [[assignment 07 folder|https://drive.google.com/drive/folders/1J4__L2XEkzXApL2pnCZpwp-0HpN2HqqN?usp=sharing]] in the class [[Google Drive folder|https://drive.google.com/drive/folders/1UtRSrCXIRAjunZgZfJszaeTqQjb9SFF7?usp=sharing]].
** Your [[TiddlyWiki|https://tiddlywiki.com/]] file will showcase your created content from all prior [[assignments|Assignments]], as well as this assignment ([[assignment 07|Assignment 07]]) in an easily consumable / [[readable|Reading]] manner (i.e., web / [[information design|https://en.wikipedia.org/wiki/Information_design]]).

! Submission Details

Submit your exercises to the open course using the [[Google form|https://forms.gle/tU9VwBn8oCkY3Snp7]]. The google form requests the following optional information:

* Name of contributor
* Project Self-critique: What did you discover or learn doing this project? What works? What doesn't?
* Thoughts on hypertext, tiddlywiki or ~DesignWriteStudio

The course <<tag Assignments>> work through the [[reading|Reading]] and ([[writing|Writing]]) [[hypertextual techniques|Techniques]] including <<strex "{{Linking}}" "linking">>, <<strex "{{Transclusion}}" "transclusion">>, <<strex "{{Tagging}}" "tagging">>, <<strex "{{Filtering}}" "filtering">>, and <<strex "{{Sorting}}" "sorting">>, as well as [[techniques|Techniques]] to use digital objects in two-dimensional form to create a multi-dimensional space and implement ([[write|Writing]]) using spreadsheets.

<<list-links "[tag[Assignments]]">>

* Navigate collection of audio or video clips using tags

! Circles

Large Circle

<svg width="100" height="100">
  <circle cx="50" cy="50" r="50" fill="red" />
</svg>

Medium Circle

<svg width="100" height="100">
  <circle cx="50" cy="50" r="25" fill="red" />
</svg>

Small Circle

<svg width="100" height="100">
  <circle cx="50" cy="50" r="10" fill="red" />
</svg>




!! Squares

Large Square

<svg width="100" height="100">
<rect width="100" height="100" fill="orange"/>
</svg>

Medium Square

<svg width="100" height="100">
<rect width="50" height="50" fill="orange"/>
</svg>

Small Square

<svg width="100" height="100">
<rect width="25" height="25" fill="orange"/>
</svg>

!! Rectangles

Large Rectangle

<svg width="100" height="100">
<rect width="100" height="50" fill="green"/>
</svg>

Medium Rectangle

<svg width="100" height="100">
<rect width="100" height="25" fill="green"/>
</svg>

Small Rectangle

<svg width="100" height="100">
<rect width="100" height="10" fill="green"/>
</svg>

!! Triangles
Large Triangle

<svg height="100" width="100">
<polygon fill="black" points="0,0 50,100 100,0"/>
 </svg>

Medium Triangle

<svg height="100" width="100">
<polygon fill="black" points="0,0 25,50 50,0"/>
 </svg>

Small Triangle

<svg height="100" width="100">
<polygon fill="black" points="0,0 12.5,25 25,0"/>
 </svg>

!! Ellipse

<svg height="120" width="120">
  <ellipse cx="40" cy="40" rx="40" ry="40"
  style="fill:yellow;stroke:yellow;stroke-width:2" />
</svg>

!! Line

<svg height="120" width="120">
  <line x1="40" y1="10" x2="20" y2="20" style="stroke:rgb(255,0,0);stroke-width:2" />
</svg>

Tutorials:

http://unicorn-ui.com/blog/svg-for-beginners.html

rcardell@sunyrockland.edu

* Working on TiddlyFilm
* Extension of Master's Thesis
* May be interested in developing a TiddlySyllabusCreator, and other instructional tools

<<list-links filter:"[tag[Bookmarks]]">>

<h1>Quick video: Building a [[Rhizome]]</h1>
<<youtube-embed "NKQoZ2piQWI">>

"As We May Think" is often described as the first conceptualization of hypertext. The original article was published in 1945 -- and thus obviously referred to an analog rather than a digital system. The article is worth reading today for its scope of vision and the concepts introduced that remain key to us today.

* [[Original article in Atlantic Monthly|http://www.theatlantic.com/magazine/archive/1945/07/as-we-may-think/3881/]]
* [[Wikipedia|https://en.wikipedia.org/wiki/As_We_May_Think]]

<h1>Buttons</h1>
These buttons are generated using the macro fpnl-show-by-tag which is in tiddler [[Navigating Through A Set of Tiddlers]]
<$macrocall $name="fpnl-show-by-tag" myTiddler=<<currentTiddler>> myTag="Exercises" mySortField="title"/>
<h1>Show the indicated contents of the selected tiddler:</h1>
<$list filter="[title{$:/thisObject}]">
The buttons above write a value to the $:/thisObject tiddler. We can show the ``{{!!exercise-number}}`` field of tiddler {{$:/thisObject}}:
<h2>{{!!exercise-number}}</h2>
</$list>

* Independent Study with Brianna Moyer

* Generate a ~Tiddlywikified version of [[Universal Principles of Design]]
* Integrate syllabus and assignments from [[COM 106 Course Design Project]]
* Assignments and classes will be engaged around the principles of design, and clusters of students who are either assigned or opt-in to groups of principles will be teamed.
* Gamify by having students rate other's on basis of principles, and assign points or characters.

''Professor'': Steven M. Schneider 

* steve@sunyit.edu
* http://people.sunyit.edu/~steve
* Office Hours Tue, Thu 9-10 (Donovan 1228), Wed 11-1 (Donovan 2143B), Monday 7-815pm (Zoom)

Explores the contemporary practice of writing in digital environments, with an emphasis on hypertext and hypertextuality. Reviews the history of writing, and the notion of interactivity. Techniques for writing digital texts with navigational and semantic elements are presented and practiced. Students design and write wikis featuring words, images, video and audio, and use a variant of Markdown to structure elements and render documents and texts consistent with contemporary standards of design and presentation.

\define checkboxtag(tiddler parentTag)
<$link to="$parentTag$">$parentTag$</$link> ||
 <$list filter="[tag[$parentTag$]]"><$checkbox tiddler="$tiddler$" tag=<<currentTiddler>> ><$link to=<<currentTiddler>>><<currentTiddler>></$link></$checkbox> || 
</$list>
<br>
<<designwrite "[[Macro|Checkbox tag macro]]">>
\end

```
<$macrocall $name="checkboxtag" tiddler=<<currentTiddler>> parentTag="Characteristics"/>
```

<$macrocall $name="checkboxtag" tiddler="03-01" parentTag="Exercises"/>

* Tuesdays 10-11

* Recorded and available to students by Tuesday 6pm

\define presentation() Presentation: $(presentation-topic)$
\define workshop() Workshop: $(workshop-topic)$
\define exercise() Exercise $(exercise-number)$

<$list filter="[tag[Classes]sort[date]]">
<$vars presentation-topic={{!!presentation-topic}} workshop-topic={{!!workshop-topic}} exercise-number={{!!exercise-number}} >
<$link><<currentTiddler>></$link><$appear>
Presentation: <$link to=<<presentation>>>{{!!presentation-topic}}</$link><br>
Workshop: <$link to=<<workshop>>>{{!!workshop-topic}}</$link><br>
Exercise Assigned: <$link to=<<exercise>>>Exercise {{!!exercise-number}}: {{!!exercise}}</$link> (Due: <$list filter="[title<exercise>]"><$view field="due-date" format="date" template="ddd 0DD mmm"/></$list>)
</$appear><br>
</$vars>
</$list>

Class participants are welcome to attend classroom-based workshops on the SUNY Polytechnic campus. Classroom Workshops are generally held on Tuesdays from 11:00-11:50 am in Donovan Hall 1229. 

Students registered for  [[COM 375|SUNY Poly COM 375 Spring 2018]] are expected to attend. Attendance is optional but welcome for students registered [[IDT 575|SUNY Poly IDT 575 Spring 2018]].

All classroom workshops will be recorded for later review by students.

* Am exploring using Collaborate Ultra rather than Zoom as main video production platform
* Worked for [[first video|https://us-lti.bbcollab.com/recording/0162dc0d54e24fceb209355d6281975c]] -- though no audio -- and here it is in an iframe <$appear>
<iframe src="https://us-lti.bbcollab.com/recording/0162dc0d54e24fceb209355d6281975c" width="100%"/></$appear>
* But fundamentally, it doesn't seem to work very reliably. Haven't been able to launch session again. Here are two more attempts [[zoom_0.mp4 1]] and [[zoom_0.mp4 2]]

* Watched a tutorial and figured out how to record in the "course room" (by clicking on the "Get Secure Link" button)/Join classroom
** Then:
**# share audio
**# share video
**# Open Colaborate Panel/share content (screen)/select screen
**# start recording
**# do lesson
**# stop recording / leave session

Here is my first CollaborateUltra tutorial:

https://us-lti.bbcollab.com/recording/c8fbca942f774d32b21bd7929fcd7512

Here it is in an iframe:

<iframe src="https://us-lti.bbcollab.com/recording/c8fbca942f774d32b21bd7929fcd7512" width="100%" height="400">

this is interesting feature. how do comments work on xememesx/

I don't even know where this commenting capability came from! Or what it does!

<div class="tc-table-of-contents">
<<toc-selective-expandable  "Summer 2021 @DesignWriteStudio" >>
</div>

* During the course of the semester, I hope to host and post "Chats with Scholars." I will engage in a discussion with invited scholars, record the conversation, and post it for students to review.
* Ideally, video can flip between "talking head" mode and screen-sharing mode. Any of the participants should be able to share their screen.
* We may have up to 3 guests at a time, for a total of 4 video views.
* Video should be posted to a reliable location and viewed publicly. 

<$vars thisTiddler="Core features of hypertext">
<$list filter="[tag<thisTiddler>]">
<$details summary=<<currentTiddler>>  field="caption" open="yes" class="level2">
<$transclude mode="block"/>
</$details>
</$list>
</$vars>

Core components of the DesignWriteStudio Tiddlywiki to be built out / developed:

<div class="tc-table-of-contents">
<<toc-expandable "CoreComponents">>
</div>

<<list-links filter:[tag[CoreSynonym]]>>
See [[synonym template]]

<<list-links filter:[tag[CoreTerm]]>>
See [[term template]]

<ul>
<$list filter="[tag[Course Resources]]">
<li><$link><<currentTiddler>></$link></li>
</$list>

{{Syllabus}}

<hr>
{{Spring 2018 Class Overview}}

!! Components
<$list filter="[tag[CourseComponents]]">
<$link><<currentTiddler>></$link>
<$appear><$transclude/></$appear><br>
</$list>

!! Resources
<$list filter="[tag[CourseResources]]">
<$link><<currentTiddler>></$link>
<$appear><$transclude/></$appear><br>
</$list>

this is the new tiddler on Wed June 30, which is either <<now>> or not.

# General ideas
## Design exercises matching things you are interested in constructing <$appear state="$:/design"> 

* You might wikify an existing text (as we did in {{Exercise 3.02!!caption}}) or system (as we did in {{Exercise 3.01!!caption}})
* You might geneate a set of tiddlers to work with (as we did {{Exercise 3.03!!caption}})
* You might do anyting else (see [[Ideas for self-designed exercises]] or generate your own idea.
</$appear><br>
## The <$count filter="[tag[Self-designed Exercises]]"/> exercises you create can be independent (new projects for each one) or can build sequentially on each other (you can do keep working on a project for a 2nd, 3rd or even 4th exercise).
# Process

## Create a new tiddler as the entry point for your project, either in an existing wiki or a new wiki, using a one word or CamelCase title. Use this tiddler to provide a guide and navigation to your project.
## Create tagged tiddlers that address <$appear show="these topics about your project (show)" hide="these topics about your project: (hide)" state="$:/topics"> 

# Description of the project. Perhaps begin with a single sentence description and then provide a fuller description in 3-4 sentences.
# Design statement describing the ways in which the reader will interact with the wiki. Begin with a single sentence design statement. Expand to 4-6 sentences to consider and discuss the objectives of the reader, and what kind of device they might use to interact with the wiki. Will they be writing? Or only reading?
# Kinds of source materials needed; possible examples. Identify possible examples of source material, if you are planning to build a wiki that relies on existing content. Be aware of the license of the content. 
# Relationship to previous self-designed exercises (new project, continuation, branch, etc.). For [[Exercise 5.01]], this will be a "new project." If you decide to continue developing this project for a future exercise, it becomes a continuation. In this way, you can also return to a previous project in a future exercise. 
</$appear><br>

## Post new thread to {{GoogleGroup}} with <$appear show="these components (show)" hide="these components: (hide)" state="$:/components"> 

<<show "This builds on someone's way of using the show and hide fields of the ``<$appear>`` macro. ">>

# Permalink to entry point for your project. 
# Basic statement describing the contents of the wiki to be built.
# Design statement describing the ways in which the reader will interact with the wiki.
# Kinds of source materials needed; possible examples
# Relationship to previous self-designed exercises (new project, continuation, branch, etc.)
</$appear><br>

<<tabs "[tag[Creating interactive texts based on self-designed exercises]]">>

Materials included in this wiki other than the core of ~TiddlyWiki and any included plugins are licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>
<br>
<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br />

<<wikipedia "Dungeons_%26_Dragons_campaign_settings">>




[[Google|https://www.google.com/search?q=tiddlywiki+dungeons+dragons&oq=tiddlywiki+dungeons+dragons&aqs=chrome..69i57.5715j0j7&sourceid=chrome&ie=UTF-8]]

<b><<strex "<b>Designing" "<b>Design">><<strex "<b>and Writing</b>" "<b>Wr</b>">><<strex "<b>Interactive</b>" "<b>i</b>">><<strex "<b>Texts</b>" "<b>Te</b>">>Studio</b>

.bigbold {
    font-weight: bold;
    font-size: 175%;
}

.orange-hilite {
    background-color: orange;
}

.yellow-hilite {
    background-color: yellow;
}

.fpnl-days {
    background-color: cornsilk;
}
.component-description {
    background-color: cornsilk;
}

.paragraph {
    color: green;
}

.class-event {
    font-weight: bold;
}

.class-topic {
    font-weight: bold;
}

.calendar-event {
    font-style: italic;
}

.project-link {
    font-weight: normal;
}

.project-title {
    font-weight: bold;
}

.project-title-overview {
    font-weight: bold;
    font-size: 125%;
}

.days-overview {
    font-weight: bold;
    font-size: 125%;
}

.project-component-title {
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<<list-links "[tag[DWS ToDo]]">>

Individuals writing reports from databases produce formatted results of specified fields associated with specified records. 

Dattolo, Antonina, and Flaminia L. Luccio. "A formal description of zz-structures." 1st Workshop on New Forms of Xanalogical Storage and Function. CEUR. Vol. 508. 2009.

Dattolo, Antonina, and Flaminia L. Luccio. "A state of art survey on zz-structures." 1st Workshop on New Forms of Xanalogical Storage and Function. CEUR. Vol. 508. 2009.

Dave Gifford has been using ~TiddlyWiki and contributing to its open source community since 2007. In addition to Stroll, Dave (@giffmex) is the author of the [[TiddlyWiki Toolmap|https://tiddlywiki.com/static/%2522TiddlyWiki%2520Toolmap%2522%2520by%2520David%2520Gifford.html]], a categorized and indexed listing of plugins and resources useful to Tiddlywiki authors produced in Dynalist, and [[Documenting TW|https://giffmex.org/gifts/documenting.tw.html]], a compendium of his solutions to various ~TiddlyWiki challenges.

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

<h1>Politics</h1>

>Politics is the process of making decisions applying to all members of each group. 
>More narrowly, it refers to achieving and exercising positions of governance — organized control over a human community, particularly a state. 
>Furthermore, politics is the study or practice of the distribution of power and resources within a given community as well as the interrelationship(s) between communities.

[[Wikipedia|https://en.wikipedia.org/wiki/Politics]]

>A "Xanalogical literary structure is a unique symmetrical connective system for text (and other separable media elements), with two complementary forms of connection that achieve these functions -- survivable deep linkage (content links) and recognizable, visible re-use (transclusion)." ^^<$link to={{!!source}}>{{!!source}}</$link>^^

>Zz-structures are particular data structures capable of representing both hypertextual information and contextual interconnections among different information. ^^<$link to={{!!source}}>{{!!source}}</$link>^^

<span class="yellow-hilite">''Goals of design/presentation''</span> <$appear> Overlay my annotations / comments on existing text. I want readers to read the entire quoted text first, and then read my comments on sub-sections of the quoted text, in context to the sub-sections. I want readers to tap one-button to reveal all comments, and to hide all comments. The Show Comments/Hide Comments button should be after the original text (and the annotations)</$appear>
<hr>
The [[Google Dictionary|https://www.google.com/search?ei=thw4WtvdDYjcjwT2xLHYAg&q=define%3Adesign]] suggests three parts to the definition of design, each of which is a component worth thinking about:

# a plan or drawing produced to show the look and function or workings of a building, garment, or other object before it is built or made<$appear show="" state="$:/temp/dictionary"  class="yellow-hilite">
I like the words like "look and function" (similar to but not exactly the same as "[[look and feel|https://en.wikipedia.org/wiki/Look_and_feel]]" in the digital world).
</$appear>
# purpose, planning, or intention that exists or is thought to exist behind an action, fact, or material object <$appear show="" state="$:/temp/dictionary" class="yellow-hilite"> the word "behind" is key -- design exists behind things such as actions, facts or material objects.  When designing hypertexts, the text is the material object whose look and function is shaped by design</$appear>
# decide upon the look and functioning of (a building, garment, or other object), typically by making a detailed drawing of it <$appear show="" state="$:/temp/dictionary" class="yellow-hilite">the notion of design as a verb -- to decide upon --  highlights the activity of design - the fact that it is something that is done with intention and agency by a designer</$appear><br><$appear show="+Show Comments" hide="-Hide Comments" state="$:/temp/dictionary"  ></$appear>

* Provide demonstrations in narrated screen-overs of -- <$list filter="[tag[Key things to demonstrate]]"> <$link to=<<currentTiddler>>/> ||</$list> -- all aligned to [[Explicate]] the [[Core features of hypertext]]

Demonstrations of alternatives to ~TiddlyWiki will feature a platform that is designed to facilitate hypertextual writing and thinking, or will explore how to introduce hypertextuality to platforms not designed for this purpose. Some possible ideas:
<$vars thisTiddler="Demonstrations: Alternatives To TiddlyWiki">
<$list filter="[tag<thisTiddler>]">
<$details summary={{!!caption}}  field="caption" open="no" class="level2">
<$transclude mode="block"/>
</$details>
</$list>
</$vars>

//The ~TiddlyWiki Demo// providing a guided tour of a ~TiddlyWiki implementation that highlights a distinct use of the platform that allows authors to write hypertextually. Some  possible ideas:
<$vars thisTiddler="Demonstrations: TiddlyWiki as a  Tool for Hypertextual Thinking and Writing">
<$list filter="[tag<thisTiddler>]">
<$details summary={{!!caption}} field="caption" open="no" class="level3">
<$transclude mode="block"/>
</$details>
</$list>
</$vars>

1a. the working place of a content creator or remixer who is making interactive texts. b: a place for the study of the art of interactive texts (such as writing, visualizing, and interpreting) 2a: a place where interactive texts are made. b: a company that produces interactive texts.<br><br>
^^http://designwritestudio.com > dictionary > studio^^<br>
<$link>Studio | Definition of DesignWriteStudio by DesignWriteStudio</$link>

<<tabs "[title[*]] [tag[DesignWrite: The Screencast, Summer 2021]]" "*">>

<$details summary="What is DesignWriteStudio?"  field="caption" open="yes"
 class="level1" >
<$transclude tiddler="DesignWriteStudio Definition" mode="block"/>
The ~DesignWriteStudio engages in these activities through teaching, training, consulting and sponsored research.
</$details>
<$details summary="TiddlyCast: The DesignWriteStudio Podcast" open="no" class="level1">
{{TiddlyCastNavigator}}
</$details>
<$details summary="Contact"  field="caption" open="no"
 class="level1" >
<$transclude tiddler="DesignWriteStudio Contact" mode="block"/>
</$details>
<$details summary="Open Source License"  open="no" field="caption" class="level1">
<$transclude tiddler="DesignWriteStudio is Open Source" mode="block" open="yes"/>
</$details>

<$vars thisTiddler={{!!title}}>
<<tabs "[title[*]] [tag<thisTiddler>]" "*">>
</$vars>

* Steve Schneider
* @stevesunypoly
* steve@sunypoly.edu

This identifies plugins and other customizations that have been added to the default TiddlyWiki <<list-links [tag[DWS]]>>

Macros:
<<list-links [tag[$:/tags/Macro]tag[DWS]]>>

//Welcome to <b>The Studio for Designing and Writing Interactive Texts</b>//<br>

In this space, we teach, support, collaborate and discover ways of creating interactive texts, or hypertexts, primarily using ~TiddlyWiki.

https://github.com/DesignWriteStudio/designwritestudio.github.io

* TiddlyAPI: Learn how to [[Process API results into a TW]] on request
* "Book" proposal: [[DesignWriteStudio: The Resource]]
* [[Hypertext(ual) Bibliography]]
* [[Multi-dimensional Slide Show]]

* Updates in [[Journal]]
* [[DesignWriteStudio Customizations]]
* [[GitHub Repo|Write in-depth read.me and explanation of DesignWrite Github Repository]]

* {{Creative Commons Attribution-ShareAlike 4.0 International License}}

DesignWrite Studio: The Resource^^1^^

A resource for students, teachers and scholars seeking to study, design and make interactive texts.

^^1^^ //To be distinguished from DesignWrite Studio: The Place, where we formally engage student, teachers and scholars in courses, workshops, and exhibits.//

//Below is an outdated outline//<br>


<$list filter="[tag[Purposes]]">

<$link/>

<$transclude mode="block"/>
</$list>

! Director

Steven M. Schneider || steve@sunypoly.edu || @stevesunypoly

! Participants

! Things

* This Thing: [[DWS 1.0]]
* Origins: http://designwritestudio.com/

* Dictionary <$appear state="$:/dictionary" >

The [[Google Dictionary|https://www.google.com/search?ei=thw4WtvdDYjcjwT2xLHYAg&q=define%3Adesign&oq=define%3Adesign&gs_l=psy-ab.3..0i71k1l4.0.0.0.967524.0.0.0.0.0.0.0.0..0.0....0...1c..64.psy-ab..0.0.0....0.sMCetYk-HDE]] suggests three parts to the definition of design, each of which is a component worth thinking about:

# a plan or drawing produced to show the look and function or workings of a building, garment, or other object before it is built or made
# purpose, planning, or intention that exists or is thought to exist behind an action, fact, or material object.
# decide upon the look and functioning of (a building, garment, or other object), typically by making a detailed drawing of it.

All three are part of what I think of with the term design:

* I like the words like "look and function" (similar to but not exactly the same as "[[look and feel|https://en.wikipedia.org/wiki/Look_and_feel]]" in the digital world).
* In the second point, I think the word "behind" is key -- design exists behind things -- actions, facts, material objects are mentioned. When designing hypertexts, the text is the material object whose look and function is shaped by design.
* Finally, the notion of design as a verb highlights the activity of design - the fact that it is something that is done with intention and agency, by a designer.
</$appear>
* Wikipedia <$appear state="$:/wikipedia">

* [[Wikipedia|https://en.wikipedia.org/wiki/Design]] suggests that design includes both the material abstraction of a thing to be created, and a verb signifying the process of creating. 
* I think the [[six stages of the design process|https://en.wikipedia.org/wiki/Design#Six_stages_of_the_Design_Process]] are helpful to identify and think about.
* When designing interactive texts, I think we should give consideration to both the [[action-centric|https://en.wikipedia.org/wiki/Design#The_action-centric_model]] and the [[rational|https://en.wikipedia.org/wiki/Design#The_rational_model]] of design. Which should guide us?
</$appear>

There are three ways to view this information:<br>
<$list filter="[tag[Designing & Writing Interactive Texts: Part II]]">
<$link><<currentTiddler>></$link><br>
</$list>

<span class="yellow-hilite">Transclusion</span><$appear state="$:/transclusion">
Designing<$appear state="$:/designing">{{Designing}}</$appear>
and 
Writing<$appear state="$:/writing">{{Writing}}</$appear>
Interactive<$appear state="$:/interactive">{{Interactive}}</$appear>
Texts<$appear state="$:/texts">{{Texts}}</$appear>
</$appear>
<br><br>
<span class="yellow-hilite">Links</span><br>
[[Designing]] and [[Writing]] [[Interactive]] [[Texts]]

If to interact with is to change, then a change in the material form of an object is a form of interactivity. So digitizing a printed text is a way of interacting with a printed text, just like <span class="yellow-hilite">hilighting</span> and annotating. 

If we say that one can interact with a book by hilighting, we should also say that one can interact with a book by digitizing.

<$list filter="[is[current]tag[Dimensions]]">
<$list filter="[tag{!!title}]">
''<<currentTiddler>>''
<$appear show=">>" hide="<<">
<$transclude tiddler=<<currentTiddler>> mode="block"/>
</$appear>
<br>
</$list>
</$list>

* Develop tools and techniques to create a navigable discography on multiple dimensions -- album, song, year, musicians, etc
* Tristan - Tool
* See  [[Bley demo|http://designwritestudio.com/projects/paul-bley-wikified/demo2.html]]

{{$:/_Menu/Home/Configuration/Options}}
Templates:
<<list-links filter:"[tag[$:/tags/ViewTemplate]]">>

This wiki -- visible on the [[web|http://designwritestudio.com]] and [[github|DesignWriteStudio GitHub Repository]] -- includes several self-documenting features, including a <<tag Journal>>, some <<tag Workflow>> tiddlers, and tags to customizations <<tag DWS>>

I have had many dogs in my life.

Growing up as a kid, we had a little mutt dog -- part Beagle -- named Scampy. I think we got him when I was five or six. I remember him disappearing after he bit me and one of our neighbors' kids: my parents told me he went to live on a farm in the country.

Later, we got a Standard Poodle. He was brown, and named KoKo. He was a pretty good dog, but would run away whenever he could. He got hit by a car at a busy intersection about five miles from our house.

When my wife and I moved into our house, we got a six-week old puppy that was half Newfoundland and half Labrador Retriever. He was a great dog from the moment we had him. We named him Buckaroo at first, but it didn't fit; after a few weeks his name became Barney, which fit him well (that was before I had heard of the purple dinosaur with the same name). He was a very big dog -- entirely black -- and looked more like a bear to some people than a dog. He was the biggest dog most people had ever seen. He lived for about 12 years, and was there for the first 6-10 years of the kids' lives.

When one of our twin daughters -- who was dog-obsessed from birth was about four, she decided she wanted a Husky. And, lo and behold, a young Husky showed up at our house one day! We had seen him at the neighbor's house for the past few days, but when we told him his dog was at our house, he said, "Nope. He just showed up last week, I think someone dropped him. Tag, you're it!" So, we kept him. His name was, somewhat unimaginatively, Husky. He was a great dog, though true to his breed. We gave up trying to keep him close to the house, and let him roam, thinking if someone shot him for chasing deer or hit him with a car, that would just be the price of his freedom. Friends reported seeing him over a range of about five miles from our house, and he had a regular routine of visiting various neighbors. He lived with us for about 14 years, and died recently as an old dog.

When the same dog-obsessed kid turned seven, we got her a young puppy that was a Rat Terrier / Cocker Spaniel mix. She named him Chester. He is still around 13 years later.

After Barney died, we got a Great Pyrenees from a rescue -- by this time, petfinder.com had emerged and it was easy to find dogs. We named her Clover. Although we got her at four months, it was clear that her early days had caused some permanent damage. She was a rather strange dog -- very friendly and very stand-offish at the same time. True to her breed, she was nocturnal and protective and spent every night patrolling the perimeter of the house, barking at whatever moved or blew in the wind. She lived entirely outside, rarely venturing into the house, and never moving from under the kitchen table when she did. Her bed was under the porch, and when people came to visit, she barked ferociously from her perch. We used to call her our porch troll. She died a natural death out in the field: we found her one day after we noticed she hadn't come home.

More recently, we got a Rat Terrier from a rescue. We hoped he'd help with the rat problem in the barn, but he's not that into it. He came with the name Nipper, which we didn't think was appropriate, and changed it to Kipper, or Kip for short. He's a nasty little dog, and will probably live forever.

Now that my kids are older, they are beginning to get their own dogs.  One of my daughters lives in Brooklyn, and has two dogs: a tiny little Yorkshire Terrier named Pippen, and a yellow Lab named Zen. 

Another daughter (I have three, two with dogs, one without) also has two dogs. She trains working dogs for police and rescue work, and has two Labs. Birdy is trained for live search: she finds living people buried in rubble or hiding in building. Charge is a multi-purpose police dog, trained for scent detection and apprehension.

I have had many dogs in my life.

Growing up as a kid, we had a little mutt dog -- part Beagle -- named [[Scampy]]. I think we got him when I was five or six. I remember him disappearing after he bit me and one of our neighbors' kids: my parents told me he went to live on a farm in the country.

Later, we got a Standard Poodle. He was brown, and named [[KoKo]]. He was a pretty good dog, but would run away whenever he could. He got hit by a car at a busy intersection about five miles from our house.

When my wife and I moved into our house, we got a six-week old puppy that was half Newfoundland and half Labrador Retriever. He was a great dog from the moment we had him. We named him Buckaroo at first, but it didn't fit; after a few weeks his name became [[Barney]], which fit him well (that was before I had heard of the purple dinosaur with the same name). He was a very big dog -- entirely black -- and looked more like a bear to some people than a dog. He was the biggest dog most people had ever seen. He lived for about 12 years, and was there for the first 6-10 years of the kids' lives.

When one of our twin daughters -- who was dog-obsessed from birth was about four, she decided she wanted a Husky. And, lo and behold, a young Husky showed up at our house one day! We had seen him at the neighbor's house for the past few days, but when we told him his dog was at our house, he said, "Nope. He just showed up last week, I think someone dropped him. Tag, you're it!" So, we kept him. His name was, somewhat unimaginatively, [[Husky]]. He was a great dog, though true to his breed. We gave up trying to keep him close to the house, and let him roam, thinking if someone shot him for chasing deer or hit him with a car, that would just be the price of his freedom. Friends reported seeing him over a range of about five miles from our house, and he had a regular routine of visiting various neighbors. He lived with us for about 14 years, and died recently as an old dog.

When the same dog-obsessed kid turned seven, we got her a young puppy that was a Rat Terrier / Cocker Spaniel mix. She named him [[Chester]]. He is still around 13 years later.

After Barney died, we got a Great Pyrenees from a rescue -- by this time, petfinder.com had emerged and it was easy to find dogs. We named her [[Clover]]. Although we got her at four months, it was clear that her early days had caused some permanent damage. She was a rather strange dog -- very friendly and very stand-offish at the same time. True to her breed, she was nocturnal and protective and spent every night patrolling the perimeter of the house, barking at whatever moved or blew in the wind. She lived entirely outside, rarely venturing into the house, and never moving from under the kitchen table when she did. Her bed was under the porch, and when people came to visit, she barked ferociously from her perch. We used to call her our porch troll. She died a natural death out in the field: we found her one day after we noticed she hadn't come home.

More recently, we got a Rat Terrier from a rescue. We hoped he'd help with the rat problem in the barn, but he's not that into it. He came with the name Nipper, which we didn't think was appropriate, and changed it to Kipper, or [[Kip]] for short. He's a nasty little dog, and will probably live forever.

Two summers ago, for some reason, we thought we needed a new puppy. We got another Great Pyrenees, and named her [[Kira]]. She's nothing like Clover: she actually comes in the house, and sleeps at night. After a difficult first year of puppy-dom, during which she ate most of our furniture, she has settled into a very nice (and very large) dog that more-or-less gets along with the goats and other dogs.

Now that my kids are older, they are beginning to get their own dogs.  One of my daughters (I have three, two with dogs, one without) trains working dogs for police and rescue work. She currently has two Labs. Birdy is trained for live search: she finds living people buried in rubble or hiding in buildings. Charge is a multi-purpose police dog, trained for scent detection and apprehension.

Another daughter lives in Brooklyn, and also has two dogs: a tiny little Yorkshire Terrier named [[Pippen]], and a yellow Lab named [[Zen]]. Zen flunked out of police dog school, but he's a good if rather energetic dog who would rather sleep and eat than work.

# Navigate to the [[GettingStarted|https://tiddlywiki.com/#GettingStarted]] tiddler to download an empty copy of ~TiddlyWiki.
# Once your ~TiddlyWiki has been downloaded, navigate to this file on your computer.
#* It will be named //empty.html// by default.
# It is suggested that you rename this file to something more relevant.
#* For example, the filename for the [[IDT575 Course TiddlyWiki|https://sunypoly.open.suny.edu/bbcswebdav/courses/202006-IDT-575-3099/SU20_IDT575.html]] is //SU20_IDT575.html//.
# ''Be sure to save the new ~TiddlyWiki file in a location that you will remember.''

<$list filter="[tag[DesignWriteStudio: Summer 2021]]">
<$link><<currentTiddler>></$link><$appear><$transclude mode="block"/></$appear><br></$list>

<<list-links-draggable tiddler:"Days of the Week">>

\define query() <a href="https://www.google.com/search?q=$(theQuery)$" target="_blank">$(theQuery)$</a>
\define google(theQueryText)
<$set name="theQuery" value="""$theQueryText$""">
<<query>>
</$set>
\end


!! Expanding on the techniques you developed in work done in [[Exercise 4.03]] (such as creating [[Annotations|Annotator]] and developing references) create a TiddlyWiki that addresses one of these questions:

# How can we use [[hypertextual practices|Hypertextual Practices]] when we create texts designe to engage and inform readers?
# How can we use [[hypertextual practices|Hypertextual Practices]] to facilitate our own writing processes?
# How can those who are <<google "writing to think">> use [[hypertextual practices|Hypertextual Practices]]?
# How can we use [[hypertextual practices|Hypertextual Practices]] to... (insert your own question here)


!! Project Specifications

* Your wiki should encompass references to at least five external sources
* Your wiki should be designed to engage your audience for about 15 minutes. 
** Assume that individuals in our target audience read about [[300 words per minute|http://www.readingsoft.com/]]
** Assume that readers of your wiki will spend about two-thirds of their time with your wiki reading, and about one-third navigating
** That suggests  10 minutes reading @ 300 words per minute = about 3000 words of text.
** Some portion of these words should be your own original writing (including tiddler titles, etc), and some portion of these words can be text that you encounter or discover.

<$list filter="[is[current]tag[Illustrations]]">

Navigation among Illustrations:
<$list filter="[tag[Illustrations]first[]]">
<$button>
<$action<$link>First {{!!title}}</$link></$list> ||
<$list filter="[tag[Illustrations]before<currentTiddler>]"><$link>Previous {{!!title}}</$link></$list> ||
<$list filter="[tag[Illustrations]after<currentTiddler>]"><$link>Next {{!!title}}</$link></$list> ||
<$list filter="[tag[Illustrations]last[]]">
<$link>Last {{!!title}}</$link></$list> ||
<hr>

Derek [[wrote in the group|https://groups.google.com/forum/#!topic/designwrite/s7PnZCjj6EU] // I'm trying to find a way to navigate between tiddlers using buttons. I would like to navigate among all tiddlers of one tag, based on a numerical data in one of the fields, I've tried making a template myself but to no avail, if anyone has any idea id appreciate the help//

So, let's say I want to navigate among the <$count filter="[tag[Exercises]]"/> tiddlers tagged <<tag Exercises>>. They (conveniently) have a field called "exericse-number:" (look at the code to see how to put these results in an html table)

<table>
<tr><td>Exercise</td><td>exercise-number</td></tr>
<$list filter="[tag[Exercises]sort[exercise-number]]">
<tr><td><$link>{{!!title}}</$link></td><td>{{!!exercise-number}}</td></tr>
</$list>
</table>

For this example, I modified [[exercise template]] to include a "first, previous, next, last" navigation bar along the bottom, using this code:

\define annotate($from-tiddler$)
<$action-sendmessage $message="tm-new-tiddler" tags="Annotation $from-tiddler$"/>
\end


\define annotation-nav(essay paragraph)
<$set name=essay value=<<essay>>>
<$set name=paragraph value=<<paragraph>>>
<$button>
<<essay>>
<$action-navigate $to=<<essay>>/>
</$button>
Paragraph <$count filter="[list<essay>allbefore:include<paragraph>]"/> of <$count filter="[list<essay>]"/> ||
<$list filter="[list<currentTiddler>first[]]">
<$link to=<<currentTiddler>>>First</$link> ||
</$list>
<$list filter="[list<essay>before<paragraph>]">
<$link to=<<currentTiddler>>>Previous</$link> ||
</$list>
<$list filter="[list<essay>after<paragraph>]">
<$link to=<<currentTiddler>>>Next</$link> ||
</$list>
<$list filter="[list<currentTiddler>last[]]">
<$link to=<<currentTiddler>>>Last</$link> 
</$list>
</$set>
</$set>
\end



<$list filter="[is[current]field:toc-type[paragraph]]">
<!--show the annotator-nav bar-->
<$set name="paragraph" value=<<currentTiddler>> >
<!--fetch the name of the essay to which this paragraph belongs-->
<$list filter="[<currentTiddler>listed[]field:toc-type[heading]]">
<$set name="essay" value=<<currentTiddler>> >
<$macrocall $name="annotation-nav" essay=<<essay>> paragraph=<<paragraph>>/>
<br>
<$button>
<$macrocall $name="annotate" from-tiddler=<<paragraph>>/>
New Annotation of <<paragraph>>
</$button>
<ul>
<$list filter="[tag<paragraph>]">
<li>Annotation: <$link><<currentTiddler>></$link></li>
</$list>
</ul>
</$set>
</$list>
</$set>
</$list>

<$macrocall $name="youtube-embed" video={{!!youtube}}/>
<$macrocall $name="punchshow" slidetag="What is Hypertext?"/>
<<tag "What is Hypertext?">>

There are <$count filter="[!field:bibtex-author[]]"/> bibliographic references.

Here are all of the titles, with author, sorted by author, with the URL provided:
<$list filter="[!field:bibtex-author[]sort[bibtex-author]]">

<hr>Tiddler: <$link><<currentTiddler>></$link><br>
<p>
<$link to={!!bibtex-title}>></$link>{{!!bibtex-title}}<br>{{!!bibtex-author}}<br>{{!!bibtex-url}}</p>
</$list>

we build this little information structure in class this morning. we 

#  fill in [[form|https://goo.gl/forms/nHXtpUkcTpVrLlPJ3]]
# gather [[responses|https://docs.google.com/spreadsheets/d/19HDeeUt_dY8SwaC4qyIxWJUgVpl_VCSuCO1wyZZbs9Y/edit?usp=sharing]]
# ingest using xlsx plugin
# write story





tiddly ideas<$appear state="$:/ideas">
<$list filter="[tag[games]each[what game]]">
 about ''{{!!what game}}'' game<$appear>
<ul>
<$list filter="[tag[games]what game{!!what game}]">
<li>{{!!tiddly ideas}}</li>
</$list>
</ul>
</$appear><br>
</$list>
</$appear><br>

links to rules <$appear state="$:/links">
<$list filter="[tag[games]each[what game]]">
 about ''{{!!what game}}'' game<$appear>
<ul>
<$list filter="[tag[games]what game{!!what game}]">
<li><a href={{!!link to rules}} target="_blank">rules</a></li>
</$list>
</ul>
</$appear><br>
</$list>
</$appear><br>

\define comments-tiddler() $:/Comments on $(thisTiddler)$

<$list filter="[is[current]tag[shared-exercises]]">
<$vars thisTiddler=<<currentTiddler>>>
<a href={{!!url}} target="_blank">{{!!exercise}}</a><br>
Submission Comments: {{!!comments}}<br>
<$list filter="[title<comments-tiddler>]">
Quick Crit: {{!!text}}<br>
</$list>
<hr>
Live critique maker<br>
<$edit-text tiddler=<<comments-tiddler>> field="text" default=""/>
<hr>
<$checkbox tag="ReviewInClass"> Review in class?</$checkbox>
<hr>

^^[[Template|shared-exercises template]]^^

Each student is responsible for designing and completing <$count filter="[tag[Self-designed Exercises]]"/> self-designed exercises, due as follows:
<table>
<tr><td>Exercise</td><td>Concept Due</td><td>Exercise Due</td>
</tr>
<$list filter="[tag[Self-designed Exercises]]">
<tr>
<td><$link>{{!!title}}</$link></td>
<td><$view field="concept" format="date" template="ddd 0DD mmm"/></td>
<td><$view field="date" format="date" template="ddd 0DD mmm"/></td>
</tr>
</$list>
</table>

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YmKiJ/GAytakwXtjYB8+fPj48ePW1hbtjM1WN3AfP348Ojp6XYmWgB13RxK5WYjKvnMXs1aASizwBz+QZ5QXPUH4aB2jwHAgrsigbkzdUYgz8a2KF0NgeEDuhclmHIWlpaUXL15wL3eK0cAukEW+q4TOOyXw+fNnhIAEgrpR5s5h6tHgCHZep4dKgK8YweJnkQAqJ1uLN90rn5mZ4Qe7U63AZDkGSOjdu3fv6Ob29jYDRN+NjzrFaNKVhqUyuAiHrhkYWFhYMNGLkpmcnKzwTq6DSkJL/vOf/zD9UTlNXIUo07iM61v+IIJSTHDagK5aMuCGs+yRN8VcDmNjYxgEGsxoeoK5RrO1teaLQV9GlvUCMZrKwvB8GZJx/jITv6vAMdBSN6xs5VlwiSkrKyvcVFtaWUc6Z0stGcag08fff/+dPnJfGkN3zBWB9vbWhDId/vzzT0YBiSFqJjvvyzGqMFdaEfXF6B0/wiSlg2bakDRQEUWUz5ATgNhN9kAbblMDxQIc/M7Q0BCG6OXLl9xd9ajEa3sOOytR5r///S8rFN1EpL/88gvdtMHfFe9tEOwNLBI3wjyiV4ZILVtTkQwNszImQ8agM2RMPSxhMGO0NhrV1kWzUVSP4pU+GlvlF/gKg4L+YB61z3wYM9WFdB0RLUbOzDIu6D5CsAEmlWnLmOrrMqbchWWX7s/PzyMlM760zuX4PKJm/ULmOooSRFTm8I2DAlgxbqVv7ILIkOGZ4GYz9UxWxH97y5UpFZJGomCu2qhlxbbLRQjP5IaHgui7THo1DVthNpFQNmmU/FnJ5xE/xR2ZibSBUaBVfJ6v84OS7WrtRbeyeOkpInJhZTqge8jNhHZ6I9qfm33CmOBqnUbeNDMyKXUI+SICrCS87IQtZchcZegRvfO+dIcRZNyvG0F6Td9RP91jCYvmpAnSPH28jYf86BL6cuqhyVRogMc5gnuEwankcemcjpngkOlGH3UwNH0+PiOfkjveOkkRDpJBqgjHVSCeHfSuTX523UJQeYZ1giNzXS/kwDDJI9T1kivT5cJ8iUSiy0iiTCKRSCQSiUQikUgkfgiUO9EGaaSMfPjw4c8mVldX9/f3Ly4uDFJOTk5aYMIj5pWK6W5WujFn8vw4xMabcfTcABtYXFy0XklUE+j0Llvr0UbDQubOodduvtNlGmkNKYNM9NpgYYTDK8fH7bs7kh6c9YwjcuC/Y2NjkZPffy0sLBi8/MH3GdU6t6rdOjcEJe+BD0QtoSjJEYpXGc1QPxMaxbltd3X51vj4uEUo1EneZxSmp6ctaRGj0IUhqJyQNgbgGXrDAGBjY8OwmQF4SxKoh+XUa9XDCKJEKRYLIvDFsgwHbz5//nxmZsYyE2VFj3ZJINpmwRqmALOM8f3jjz+wLWtra4w7/3IXfmpqqpxolSGO8TU7ve13/pr8KWwL4768vIxh4ddCRNf1KIKyWrytrS0rfbQSZRqXWW081+u/IjlK5Qx9KypEGZrHfVFIhsAYVS1maytFxpovCNAIlkQZWW70q9GsqoD2GqFhoFsHt6LARnFkUXgUHriUIGRnsakyVGzubg4G7tIFW+psdZWky06c+fn5KD/Uq6Ex8O9YYEakF5Rtu40pNjTrifbff/+dDvInvxxlaCrTwdGMfDOxAlbSQV13OxkY6AaeABeG4iQr9OE6ZcUQ1ynEYjkM5q/E33YNosxdj/KjYy5/3MWwZUUVpUZhVFk3MV9MQJMJyW2y3sp1DltMN+eay6U5UegmH0MNjEPLdXNwrRPX0bVSUUsbNXGLJherbmPaclNFXU4Z4+LlXC5lJb1AygJTI1gLOooIGZOulass0GXAPnzjKPRphg/TPxib1wDyMZ3tcDi77JZIaEA4joK2nVfzuOjWhm2XnRAecuMy7t6qaUE21aRr1S0rGSl5AGPNQFQK8VQ8RpPc6Mth/3XzauoGt1ZSi/R1MqfRN14ZC/pu/qorH8euezCJOe7Th9LjK1bzjCwjfGBubq7Tc1w+pSaOJUZtx/JfN4JWIzLTVeghYkFhaLD8D/lzpRJe6WCUj2lOw8i8yJt80SpOZr9TP31SK0u1drQuFQMh7dikktoWx6h1lYmyXLJkEAvetaaJIZa/q6qU3ldw9a6cofEAFc+q3ppfYLwQlNUz/RfaYk2orhXmSyQSXUYSZRKJRCKRSCQSiUQiMfiIo2MiTo6+e/fuzz//5NXkz4ayLHEyOzvrvpgMj0pqeg9eG0qMjeytrS033Yyf+QH+jDJGhrQ7EaevdLbyTuS3+Pz5s5muTeduiNcdxqhef10UpFFsv0a0yb5bGN53JAa5Tx21hJaXl1vLTPxQ+4xmGXGTV4rM+/fvuWYIjAegaablB8bCHYLWBB5BEEHIhs8RMuPLECB51S8KIoR+vmjCQHt3GEutUR8PDX++hHrIO7zPB6zRgxIiAUSBtniA+MrNboWgph0fHzN5LeRETw02hIoiooMm6L7lisqTxA9XwtZ88rJkMCxGGZlx3F0G3tjYmMV0nGi0pBL7aRQJXQySWb+J3pl2KBK9yKHhemVlBYlFAobrDkk7bSNsKbPtSqIMb1oSyNCdn1HfIsfM7YkywFoVrSW0+nm9qPSojNB8+PDBOn0GfRkFU1mwXmhC1d7hJq6L1riCONBGqlASi+KZ0iMWDjXcOY4OM9yqcafL+WnqQ9Okp/TDIFbYRUgPXY1F9pZtK1exKGZxJVEG2WIwnzURgxgkAJOxffdekUoKC9Dn06GyxCNe1DiGvu33CjPeaCYyudK8mOHm3SVYOKyWxb9cNzWqTArpMpVF01+L8Hk4bGYQdDhiTQkDK7W0o2tlBLMjkm1BkMhf0l5px7DG2tHKxeFf1sOS4sn6hZTMw4FgTdXmGi37makX9q3k/+n6WvDFAmf8QqT/KakkkfItEtt01DO80j2WDhgJPMwlg5LwL7ka6JUdlzQWHnJkMal4Jq6VUXrJKk6IEQkEeciKQtz69evXeMj8ciW1T0U9tDbfXX/rsqo2ikJXCJxJHc8m8pOww+obyoZ6lI9jrWLXJgd3PwrCukY7x+MDmjXneJlqse1zvLRvGhnXKZeM1lSLkSvlUxNRmJVv0WuVEEOnEsryuc5DdrJHFSrp6dLHo/uhpXrI8aSGa9rKFu3EKqNwNEdYkhtWGUneluVCMvKHJKDzebRC7qlPT+UMDbJyZYbqDEvS0u+SmxVi0VTqevEB/C6LD3a0MF8ikeghkiiTSCQSiUQikUgkEokfArFTZn0WI9l//PHH+/fv19fXj4+Pnz59OjExMT8//7yJxcXFmZmZiNZXiDIRcjAS4Pk/9+akPlxcXOzu7poTIs7sur3benK0o/jy5YuFfgx70HH+PDg4ML5ofouFhYXlJriIXhttujIM4OZmlL1fXV3lK6Ojo/v7+8jEnDp+wILxIQQ+1g9p9rsMA+1mLzDLCFqH3JCMMnGTF5VD8RgCo1AOgYGoVqKMQyCRwh1kvmI6H2kiwHiDG8EW2GJo+Knb1+tpF4IlgwbS/Sg4xZt0xGxGKN7S0hIS4NWIlHGRUMJKGMDJpRBMlYQmr62tWeTI/yIW4wQenI2o9pXFDtoy1+iUtsXCJdoWQz7WwyrNC0NWxtuidw6fx3+3trZWm6AvdFPqD39GtirjClZwuMGw8PvoEiKlGXxYDsR1RBlROb3Nn1HW5GZtr2SUYSgNYFesaC3gQDh5zT3GBX+qTowd8rSyAzOX8WVkI2YfVtSwU2scy0GUqMHgbjSBqpjiwvE1TiZRJs5bW3Wro7Y0dEArJGmvEnbq1VLufJHO5fHxSha07/4CH5YhajEUhtI6aBLXWudOoJwOUdzhu9bPXEoWvAg+R99OB8XruIvvFly7n2rJxjO9ljequBw6bCwcrJv//ve/y+xcrhqW2FtZWcGoluyNUrbBSwvqBrMMK80vmDXEcDKWNqLaLpT8DrOso2NUivoemnzLW4SoTbdAN0vvLm5kqN7yfKxfeCmSv61miOpi4iJgLLUliJ4hZyEnyVwaiFqFlyzCQFhgLtjkfF470+XqkEFfdsm2Cpu2F5NLk3TD9JCx7Xbc5czkfMq2VdOM/WPV9ZBNysUvY8BVMASLYnOjSHOiVeeXK7qhegTaqxs9hNlEkLyV1CwwhDSYoXRQugMr6VIT8WBiNrUrH0zkI/pQJv/GgwFMdquqIWSGQM8w5nhIuHOzO9bQWF9ac5S60Otj/P777xY7oyPqodJACFi5UELJuKZiavWQNWWmipGshhLyI4jFwmeuSryvh2ziOh9d+R0+2WmuTEU4N6h3pEK0WC3DalomWh51tdST8L4UzpU0dGdo5BXDKPFrTE+1K1wsLIOPD/tNBLPccqK5o5JIDB6SKJNIJBKJRCKRSCQSiUFGHD10p+zs7MzN2T/++OP3339///79zs7O+fn5+Pj47OxshLG58Nyeaa6vjEe6LesupLuWhoQ3NjZ2d3fN28yPW0QjohSxIdiFvnt+UVYQ/Y3Ix5cvX0xhQoNNn7PYRBAU7LXx+yt/1r1+A/kmUUB6BvI9mOjGq0H9OOvvcHRhB7bnKlfyHug4QkDsHz58CK0zAQ/6IGvBMhwOgYpnKv4ro7aNSy6F9QIcAg9TxplRC/RwixiR09PT8qRmyZXpxAHuSp4VC2cgAZQQCZhM3lIOZuCg8cEzAJ5q9cjsddriBFQIzDiPHSMKz4KrgRabOG0iDtA7QGVup7Z0v2RUmDFofX2dd+gCo+z4Guew2oKloIyXXzm+nnZ1fqkkkcWEf62trXkWP+hrfOaGacv7KBUSRiYjIyOW0riSKBNRljh5bMw44qwRGb3O7JREGQaRzr548QIh8N3+j/BVioWpQtar+s9//qMJRevoixQ3DBpdcwqjw7wyZGqvw3GdrOKAuzl+mBGeF+dHzCFkeEaWTISyJHsJ7suIdGgWB0vGmji8unj1A72j5BZINbN5tyfK8HkGjimJkvN1LlB16/i0zkeNrbDMlnUiooDazbeTFMWP82FsnUbA+mt9uBSW1A0abCqRtnNlDJEyCpbbA/4ZhAA+oIV39v23CRYOZgr/lRPDfJG+ALiI4PGVI2KAXKeFT042wYXpQ1wjpKYZz5aIw0WsFB0SdTnLvGi7qP1ZOmJ1EgQbIeQw5ogayQTLk1ezWyFSpCRLRmnrKEoQlCxypYvo+qWo+TCvrF+6x/xXx1veKm2zsJHVzbqm6mY0kZ2AbefVKpC6BzJZwz1buAQdCQ/5SsVQb2VlIQFXBD2TsOqmNTKXmJ5JpJiK8i4ljUB6U/9Y4HtDfgbCsQqYOaKCe0q/0DfErkOLtKU+lI9jt3wwMbkI30Lyek2WImUIfB7RhitPbtqJOR4cNUdQw9JKB4mpxwPCv//9b17lUfFJbaO9WLqEs08H47pnhEaTfBPllmYvgR8eSmj9L/60xlB5qKPRrKLrk28n8qZcafpCOLEKO5VoYVCIWAt8hvUpRslompyePjtEarErhaPrFbWc9LHVE/401ZMPsBLxnaTy+ZRGuXZnDaZEYjCQRJlEIpFIJBKJRCKRSAwsfirg1tjh4eHa2tq7d+9+//13Xnd3d//55x+TAbx8+fLFixfLy8uGpd1ruyEG9ujRI+NkBsz4sHttvH769Onx48cR6l5fXzfoYjCgDORUkoc/sLOVd2TJfPz4kc7+97//pb8bGxsmkqF35s6hv/IS3FP+bq8bl1FGj+Mb5TJkhfQsAGR+bEMOvEYy7chRwS1aUywMktaVm+Bm9Hn//r2hPi5MNWSY1vPZQYZwCKy7dPMt3HznY3zYbCUMaFTCQuU+f/68ublpeMDDyu7nxljwlYgNtHErvFUPaQBqoARQRRTSWAUtjzw6cWgYCUTu9JujQU5AwYcjZctOEx4SRQ/d+PbEtoEoB0haSeSHuGv3W6vzSGiwggNQ/2UCYVtevXpl0ZwocHZDbKYcX+s+OL7AzPN0zQw9QX6y8cjzuigav8aP0BJ+k6mKHfDocCtRht+0L3SBW6BU8tuM9qmfYSKuFFooG68W7LDxHUrk08aZW/4pwQtFQnU1oQaPEY4UN3ldxmYiHoygrF733XQvRoUd4uDcIGGmg7PYZF2GV43iRxKayEDAfUuuTNvN6U//i75d3+/UNk0H07DRTC7FIDLQMiRi+pTCNJymYbFCk7lMUICy6tl1wtfqysIpS+zJDqmF+9Teob8yl0CZswcYIt3b24syQMwFhM/nsSTY0nL2RZ6eGyYdtwsHDAQHguH48OGDCT8YaCPorqrxg7EYdSgm2tFZFtF6yWQlzTFup28scSEY5IgCqVq0MUStxMzc810XMXxjCcFMGb7IgFo5C4FLHdCHdDpIl2m7KbvSPQ7S/H/+8x9eXVVd7MxlEu5xcH0kKNxs28Mz0eeXaYT0uJ31gExoZMqQqJIZJp1PmrIiKNf9bITvKvmSOP7XX3+ZoQ2xSBy3jJpTWzpIcNq+K/brHkz4NWW+3oQ0CNPjmQTUeVEpXtl2XkgYkAqTntGnPQih1EOWexMaSRw3i0wUdoy6SzffVB9SbhwapWx3m1APowKv6etcpOw4r3yYG4XMu2b6YiFoXFLZzIdqJdN4hjWLjM/smqapJnx2uFlVStdL74tfQ85WWYoHKM2UCWZKtxBBIRx0sqLkSZdJJGqNJMokEolEIpFIJBKJRGJgEbtvhn7Pzs42NjbMDcCrLJnZ2dmXL1/+3MTz588Nn0fihNvcwrCxRBl369zr58eten54eLi+vm4c1PTOHhruaN/Nbx+5c+ivR3gNEK6srLx+/dou02ZaFWkDbh+645N0yswKCwsLZto3o4Y/SK/N9mFUzMCY+/59HiN8uNa54/zt2zdGwdOQlhziT/47NzfHELx584ZRYAjisKxDcHvdMImC2REYAjQcZXMIIlvJwcHBxcUF76MMtiqS+TNMnY67RNZ0lBAJ0AZa0mgeBpWdhgRevXplPgDjFiYwuH3D7CbSY+pFcQ10z2pEhuUsw1QWMuD3next6SYDbeRPdo7Ho+kFk4ve/frrr7/88ovmxXExYf5tumbUTaKM8QCpbEjSyWVwyMiQJSEqP+L2vUQZPonumZWk3Nav1JXjl+mI+STMKMPoOFiOVARpvhsbMEYblKa6nL5FPgjBeJ4Ut7/++os/MaEIGRmG6sqtdFgNud3JiioiizRJHbNoHSPLEBjF5zcl6DB3LDpmtEZTUw5H4gaE4lkAUYPDUHqSPhiElRnBt4zVMRAmWwoCAfMaBSgDZo3rqWP+ZuT2iNX2x4yuBVcmUGb+02FjAmLl3r17Z3yUdxgvzCDr5tu3b5E/9lB3S4t6J4fNJILSPnyHmzLLMHeSmyXKRJKb+k6xSA1VprIIUUceDsmsOCqoukwCHUWUHEdRsy/TyAX6Nrc2GQ+vQQ6z2iA/jrRNuGLVyOA5uZR32i0xh4ek+SCRW8mFZtBZHwr0TFw37fUt1UzwLbuvt6OHzI1wz3wKkE27ubmpzjeKXFlW6hmMKksl6KbccYSPpuEs4a3xJmJHRExqZI7wndrhDd5J7OWDCeaCBVratMUKEb6ZVHiHj8UBhruu2g95OiiXCX2tKNZJU61GypRh9qGESAPXkY6YZvKuj2nWTeNbPiOgb0w60/nwjvbNIq3cOvQt8gIitO48qVXoMp5siRxXEqpop0X3dMB8bG91wO46Q+U9m14O4Vi0K2aodbvQWH1XSTMu5Xwm3apEYmCQRJlEIpFIJBKJRCKRSAwyDI1fXFy4P/jp06e//vqLVzdnp6enX7169a9//euXX355+fLl3Nxca5j5uzBrghuRZbEYA5lyZdwfj6whJpjp0P6jdVsODw8j8mG5EHN40IAXL164w0jfFxYWylODd4UhLtkGnrw3FhKxq8+fP3tK7+PHj1Egw0Pk9xB1LVDW+ULlDMYAOSKmGEHyqNybN2/QOnfAr8snf6chaDSPYMausUdm19fXGQLeZxQMvUhcsA6OpK5OyMEc+7u7u55Td6eblvAvD1gjBKlCKKRtvne6EaOAbltzU88iI1XPFrvfjQR4jUIGvralDhrmhR+na8wyC5AxEeiLoY63b98aa/Sk+F2l7Xzhi+W5anUMwZpXf3Nz05PT5oe/Tk88PvtdNWPg+E3uIt+Ia74iO8Q4Fhc3Zzy60ijVaArT2tPT06jK4VFmC5Fg3DzHzPxVdRcXFw04PdBoSHjyT3TYNAauFL7SAOyJXBmDWJEfAm2/tw3/AREZm9Dq704HRM38cnWzkh3yj5WU2W1mmgGeDp1bJcssMnGBcGTySVNj7dDQMQuYFEy63377Td4hBvYepIpI+GH+PDlqQYFifuGwuWxJazaafifuZh9KuxR1OMaNJqMaxabX+sb4afSd97X2Ll56KfdzWTVrso6kL0S8mcUFUcuVMRWEufT0DzsnjeBC0V9tO9cYfG7NXMaeS4JkyUYCyOEh4XAdDHSMDsoNMiOIngl3NE8Stt0Z4YfNcqG31s852O63tloEDYHjNSETPTS94uCOy3K+913CKzaVkdqFtD01YcoWnXPrzwIE3h2iTIypBDUWFx7Q/vjjDwwd17wZieUQiEQZdFKWz8Mf0xA+fbesmNNN+WNs5co0LjMCRtGoqAXWUZZzyZIxnVikovSMAXaJ9x0vVUXh+AB177Ernx0UTpS+VTgmmuJ9GiNLJuqQllWiEolE3ZFEmUQikUgkEolEIpFIDCAqR2bN4W86Gc+lXVxcTE5Ovnjx4v+akCVzXfT3us3BSuDE0Hjs9JmM4awJw65muXAL2I3LTmyCc1NZMgaZzKjx5csXa0zQ019++cVcMgsLC5XT8LfpdeOqPPa+OT4+bpAjckhwTTMODg52dnZMdh3odDikVyoXtQzMYhLp5Y+Ojp49e4aGIPy3b9++efNmeXnZ9OY3/OwtdS+gzD2XHCVdLMOEVnhS3JQGUnNQ+4gWP3wfvEzD4OnM1dXVv5qgDbLTpqam6DhCQA89sU0brsvscnN7rqsxxBQLQkwcwF1bW6NJzEH+FUpoDO8hEVBP5JvcBSEz10zhY/IDOvj69WtDHdcN9JV9bG2SwSRGNtLjc80dPXqLskXy/DspTCv4WSPEoUsG8KJI0F1ZMo26FVmTVWY2iwpLRpZhxPM0oTfI9q5WNHR4dnY2gqyRK4gmWSAGZXYiR0KOrp38HhhzfftPSrlD7SMqVk6HB979hyXNlCtmWW5Dc8or2v7+/XuWTgmmmFBXDSC38rrI8S1toPkSjJ1b/gbIZ8WGm4nBuCyvcisHwzkJgcsINKmJvjHmRQY59g3HGEfF9B7XkUVuL2pJopYhs34cr9wOY8srop5oIqhLHRKF+dIiAI+FxyVAApb0skiiDMibPZN72HYETge16sba+XEucNFROTxkk1sohHDGWnNc1RrmkWI2WQxIfTCdzKsmrGd3w1y7q9gRKSOru6viBUkLnw1N4NbYFsmmnV5Do5aWKetwyD3MgI/BHKRJiAL3WFFELhnadt3o31UadDAe06I4molVaIB0EEsQ6j9HVqROE7ZKo+RTcxAlfYZl7Gh5PMOa3RDhWKesjcKJFGKeNEAOLArS39HVqNkk50/yekcL8yUSie4giTKJRCKRSCQSiUQikRg0lEFZN92Oj4+NuxgJuLi4mJqaev78+a+//ipLZnZ29h7R3yvhXp6h6y9NeHry5OTEbVlLHckUadfmY3TZQ6tbW1sfP370fLDVBEZHR2mVNQt4XVlZQQKdSBztqdySKEPbjASYocG4LxLgv8FRqHuJ93KHVI4Uw20enffv36+ursqS8UC8hXiWl5eNv97ws/cTCDKfnp42zifjIQr90CprMJlMJSoyRDSoXQMR2XToPnqIBPiT9y1ZQvfRw59//hmdVBPaPiLmp4kqJ/SUrtEeJuPm5maQDzzj7ty/H5mDD1sTB/U24QR/StbBwhjqsF7Sw4fYSNvS0lJkBqIXzHfrdgWp5eHSi+I+0TxtqXV/BnW9ECY5MN+ARfpMxcScYs5KrLTikrVI7i1wz23fvJQwoOgq46ut0JyaIIoWRoIuL4K0UXdz2m+IuRAcNeeC0yFz+dxb/yvT0Pgxi5SvrJ5YbEwrs2Bubo5V47fffmMBderdlSVzw0rBMqTFY9kylB6ZujDj8/PzphVx9tWL83edxbMX9JRu4p3imCFt1i8Z5Cxb//rXvzB0EpLalfzPup9KWBI5t8O66rLKSYrkH1IWHi7tio2NWpCyZCzpRcMYYhnMJpIxTUUnPBMLx2CxdUL0xGSDWWgG3UYUemWSXxt1ZslU6D5R6QY3hiFeWFiQmIvAmYYPzHB5HbiRGX2+FfD8AG4bF7zipOkuRvaU9s5xnxGiFrCPhGZblCVDk5ADxu1tExLUzD/a9tH3MS2IMj4gADMvMkGCyAV0ns3d1VHXQhF50oNZyaSQKKldQjjWq/Wkh88OnchLSk/dEDC3k341Q2aBKinUEmiUjKzZXNATibojiTKJRCKRSCQSiUQikRhARJJ5s3wfHh4eHR2tr69vbW3x58jIyPPnz9++fRssmSs3xL+7G1jZAhaPHz+2GPzp6Sk3PT4+Pjk58RCtteFpg2eUPdjX3o57GtvzsoALmvHs2bP5+fmff/5ZisbKyoqbwjd06jYdb1x/gjNit43LKKMpVej+6OioERG674HFQTop6yb4ly9fzs7OED69NpMKH0DmCJ8hQPEYgkg+1IkhQPLusEc+lcZlDRGTG7kPbkaE2PNtlyjkjrihLFtrZ2fH86DOO0sRLS0toQnXccUeKAR+VhKMgSgT/gMkwHxkaGjM1NSUXIeHpE+PLPH7+/vYGcTLm/ymyfOXl5cNsrZ28+YOXmlbGk0WFOYliDL0AqvCmwb2bj6HfcuJZjYgOmWUzhJyBpl403/dr9JQ/4eW6aNRW4M0ZfCYOcv8/de//vXmzRtUF+W5X7KB289iI4iR/ciAjePIFMacrq2t0Qa0yzIKWt3BMKedxu2nQ6OZYaicDgKD5nS4dzQ9mUwl90gLyVyzEhDmFIcN48Z/pVcaP3bVuNLQ3c9hc5YtLi4ymkdNGKa1YiYTjYWMd5zvNU3a9E+BMDgu0/QRE4e5s/YKiyYSxtDhG79+/foGBvn91i/rZ8kj1zdmBlkXdbsJ7s47qEHbRe1KrV59+PAB884FbcCuska/evVK3yyKuXTIM2k0I/GR7k6rTmflyqBveE24x3wG5wQpuf4OTA0m05PQNS6YyBhVLli8mF8+E1037g8UO3Lm99Euzy0w7lJVZLQjdhTDNbRDci45dhIBMTXooZW/XEecer/99hs+huWWOv2YFhVI4ytSx5iJuhby7H2a62gG0NBwSfYeM/BkC0qC3UA48eyAX43P09EZaq/tsrxYLmgYasNDhE8WppyR7pZ+VyJRdyRRJpFIJBKJRCKRSCQSg4Yyh7PEEa6NB5ycnDx+/Nht8V9++eU6lsxdU0pU9siePHkyNTW1uLh43AQN+PLly+HhoUlltre3FxYW5ufnadvQ0FAb99essL63t7e6uvrp0yfjTBaEMo3HlSyZh4Tryu+WHTH1hanOv379aiZt+utpxbW1NYZgcnLS45sDcCI/VI4LD0TSX0aBnjIcjItFWwz1MQQzMzMPUbkbvliOAtqFnP2MBXp4lTvlPrhkkbGxMYagjfUOnHRbW1ufm/DkLrdD7V+/fu15UKkG7SpBcp0emtnFtFLqIW1jDlqbjH+Z3snULPcLkPjjTG3DfgZ+ECk/7jRvZVTcvqdX7uYzrFYMkSjDfXkTBWOa37xff8tE9EEFKAOrkVFGtGXU+g2e82aZsOZLpONiNINY+ebNG64Z00oE64FyaP16jIikN22LK5opGTAsZr5xFss7vCG0lriTyS2TtN08HdplyX9kh62skmkwkmmIoY5yGxYiYdVgLlRC6XcVeCuHwyA65po5xZTn1kFxxm+UKMO1a0R9A6Jl9SWJjzIG8FJYDelyUEYszdnKknm4qBk7zCl3QZ47TSBeMy8aHeeVf6EGMkja2H1Vi55i2D98+IDlZFhpGxolCdJ6LrStUiSxE56JOU6ig+oVDbMeEK4jUorUO42C+j8Ak12/hVfkXNayMWdJ58TOXeQeofMS4GQ6Msd9KMMIyBrv6NRjWK3tyE15TGP2OfWs1KkSLi8vox4PNHTffUbwMU0ljGWOZwQ8dukgZrMDUYizE5Jp9cE87IFwaAOywqXx2cF8qD47dOIBqmwM11LSKw7AfhMqLR+Q4GX5qlzKE4laI4kyiUQikUgkEolEIpEYNMSm5N9//y035evXr0dHR1w/evRoamrKBM6vXr1aWFiopG6+33ZbazzAPdnl5WVTTViQRQKBG228f3Z2FiSb+2WYr4S3DTZsbW0Z+bDYTeRCsOKSCbc7IfZWwtDo6Oj8/LyHsy1BJVfJFprMw0ON0Z16RRnL7e9S5c7Pz40/MdD0aGJiQpWLo5BdayFjLVPk4uIi6h3IWGIsHAVD7JER5x4DUY47fY8qY/y+e+4McbDTZMlE1a1Og07FSWL10KQFkgxmZ2f5r4drIyh4p+4bcfSXndHSbkxXw1hjYcqA370tTMW8NJoUCn4/bjo2NibxLkP199DbxmUkFa342ESkH/Oc96+//nodS6YLOmzMxuowTmTjbYeHhzRYooz5CSLAnJqQqMUC2rikcpqayxSA1hezCsarJkyx0N7gcUlHYwaxSHGX7e1t7u4U03/b29szy4jzq+4WT76dNCBkjqHTV2TBevnyJQu0jmK76olURI0AkaRE0s3NTe6OkBlr/ATGnZbILDdnQ7ssvDk8TBVmSa9wjzHp1nMxl0wnCpJeB5ZshOAscArgNTEi+Garq6uMEe8jHMsdlilJaodynjKFzakjy1DP07pmnW6GyWyQOdMc3TN3FBI2qYzeYNur+VRYMui59c4Ya5UfCWjl3r59+/r1a5NmdS15lY9pwZKhhZYZkq3CVMX3MNmPDkajHQXRWuXDT4VwLErlswNGgCGLsmg+O3RNby2G1bhMKqPrhemIwnwMnMk7GcRSh9P1SiRqhyTKJBKJRCKRSCQSiURiMBGnk7kYHh7m+vz83JIoL168WFlZmZ+fHxsba9cRxkZLMNsk84eHh1tbW5ubm7TEYg2m9/fU7MXFRbtOzRrU2dnZ2djY4Hb7+/v8OP1dWlp6/fq1R4Rbgx/t3c6rSMDUGgsLC1+/fjXTOF0+PT31XK/1pywaUtOKBleqHCP+999/e0qVP+md+7wOwdTUVCXS1tEhaDRjA+ih5BjLHBhfR1vQEw9EMkwmG39gFDAmHX230plhANlpSABVNN5ZUfs2CqGVtfb06VMagPDpOEqIBproSDYPeogSyha6R6jG0II5k7jgF/gdT+K29xhupV8mw+cuITpPnGcG+HuL13pha2trnz9/NsUCdgn1ePnypURDVKg1ZUuHIiKViWzJLfU2eIdWS0GNabM6jD5YcC0HNFELVELIOmxmcOF9Zh+T7tWrV8vLy60Vlx4+9cpZxrxmEuEf4rHI6HXFlL1h9aU25l3riahdI4JUTV+sRqSjgkv8sgmEcO8saLcRtSsXfhE3wjmhAWZPkcAa+Xv4WLuWM36fn8Xhwbavrq5iM63nYrIibDsPBVcWSeyoZ2LZr0h+GSxewALEOwyQ5GYTWgzMlK8QzlpHuUOdRdQMOhMZw4L64abGQ5kucXl6oe1WLtxjy6Fyd81dsLUkgmCFuvmMwDUyQfmtJ6jRCzqIHrLzlDkbZPr2GiUdaY2S9p/7RsIn86EiHGZra8WlTs9QDzZYxBm7xCLloRe5MrQT4fj40HbhJBKJbiKJMolEIpFIJBKJRCKRGByUx7kib/nx8fHw8PDjx4+Nly8vLz9//nx+ft7aQJ1rjGeUY5Nxe3vbCL3p7k9OTr5+/XpxcdGWRN9Ged25W19f39nZ4S5PnjzhvisrK69fv7biUhlA7U58lzsi8yBP8GrCfwk9NMlE920/xNlNlavUMtjd3TWduzW/TOxvLplWlkwXhqBxyZVBQ8xqbjyARhpin5yclC7jifmH3LqVrcU7DO7CwkLUzqiwZLqgh9xudHQUCTg6e3t7JnbilUbOXoLP3KP7Rhc0NUxn7oupefbs2VATzO721o+IrXzR+uN5kvV+UjVahuquNyHR0IIsL5ow4X9HiYbXjXUsKLQHM+LkdQWJOmJMXkyN7MO2a10i0aHV05oyWFEnoHk10G3esbDFchOtqT7aPvVkb7AQcC8mlJkITW9jSSCWD5pUXxZaLBlKmA7K8jTVIl3D1iFqXrnuaEFMmoFPgqWaawLPMPLwRcJFRd0WCnUQgyLLnfxdzSluCeadXstZ6bKHLFfGijOWnaKRJvwznQYflrhg/pUB4MLerzpku4BIsSQTTXBhwh5ELQdCObeRuF8+kzrvJNBzC8ydbC2LLvGYxpMpi3jJUeucEpZtozEoYRD9gYRy/sT0mfZJgrsZQNuogdr/RrNgq1Q274514u4mdHnThFzJzrFkrpuh1mDCPqAqts2ycVFHmCXDZ9gyPWoikagdkiiTSCQSiUQikUgkEokBQVk1xui1TBTD5KbNmJ+fNxIwPj5eboa2a7utsv84NDTETS3CQgNM9G2ub88rf/v2zao3D7yvMQbTeLjVSBvo49LS0qtXr1ZWVjws252BqOwzmu0cydOY3d1dOu5WLK3d2triTf7rabxGu3N6d0frIm2+oQ5j2ID/eiD+zZs3L1++nJ2d7cIO+JV62GjmV0cHorqBCY1CZ2SKWFPmIQMhIwoNXFtbkxn25MkThIAGmhXAse6aEMpIADPRcg9W1rBS0t7eHkpoKv6SJxQlKq4c8fJ9h/68CYkyfMBSAo+bSMvcz+tFaT9VBrSXC3QDRWVSPG8CDekyS+ZKYEDQYQl5Ec2y5TTbZBhOMYtwZSGARJ/DHCcyfa1hp0U1no224zkYiSxjkJ3QZ2y12SZcDU1pEOUyXTQxFNctBLWweErb5A2Sk3Q+gyGEDbEWYSdEXcnfEzxyZG6KF6tBYc2QvEUh77eAVvJEBgkSI8nqb84/fpz+YttxTuQGlTTZrnkm4Z5JakcCFmDiAsMuv1+iT1niMxNX3FvaKDzqHTn/0EOJzpFJBfmH1t3gB95DD6P4KdqoskXKOtxjVLHyjNBNyJVhMuKlMwElq3EhuVyujA8I1hhqiw0M6h6vnvSwiijXOmC0x2JwUog6vQRc9wDl0zRWwnSwSMYTODJ7eNhBMvKukiiTSNQXSZRJJBKJRCKRSCQSicTgIDa2Ion0169fG81tL8tSzM/PLy4uut/XuWbEzqx7snJlPHPmVikNiwTObdnv8zTe9va2J6Ejyhvpc2hDN3MMlPuMvJpXxooGnsy2yglNtSC9Ob1rqnJ204iaZwpNoW+Oh5WVlcjq3+W2tTJF0AT0RLGbbR4wKFtbWwyHp/bvPRDcjo7HCVTDUdbeQgmXlpZmZma6HAYoJfDkyRPDgVgA83Dwenx8vNsEf9q8u3ZfWp4Itc8qSDVCRFJRA/SWVwwUYzc5OYmqoLpXLhldi5G3VvRDUZlNpl4I8qUsH5YATU2ltkUi0berZxQD4hVNRm9ZQ804grmWMNFRhy1gUhnzq+GwmenEgn2S0nTYamrYS6IM/ZITgK1AvHRZlkzXRG0RHOQsiZxmBHlXCmC7Ei5GSZedJqwzRR+1orrHrQX1uukhNy5pCmatkGmtyjEjTA+mKNS9uvsV182gri2pPpdhYdA6LhCyhXVQjMjc06FnUh8TMHHcnRFH8VDCly9fWhi3klmz0wKpKKEecnBlmDIKhAZ7qsHqS20sJ9ooSi+dXcKZaCE8hMPTk8LpPoWoUi3OwYpslDTVlH5ylAGmDI1Ktz+RqCkyD2cikUgkEolEIpFIJAYQkeZBYorbzRMTE7OzszMzM6014DsH7mui78nJyZGRkUePHkUZ+DKh+kPgJq+MB8/L0n13PBcXFz0i3OUwQKsQPK1Iezw0iRCOjo7i5OLZ2Rm9qKOmuc8bSctlXZhOxlPCCwsL1vnqedx6aGgITTC1jxkyaBLNZggsSGTQ/d4DYVkxfg0lNDM5v28Ejtsx77rM1gpTUEog2mP36e/BwYF9tzLavedjpShSR09+/3M90vjfFYbnrQ0X5eFQFSOpy8vLGK4Kk6+3ctaw2DY0mbbRHkue0X6U2RPPqQyJWiygpiUwoYhGuPTWdJy60xgD2Ewo7o7HwjVtY4k0vUdUZqm1tMPi2aPwFV2jH8KUvWtLJJFPNsEQI3z5UsdNcFHm77k3zBaGhyNRhutGM4OO6WT0BHqVxqOUhtnCsOryMpkCttwMFkpjMIgy1zkwXbu7xTFHmrC4lflHgXkBO9TlmHeMKQNKM8pawOhkRT7d95BRQpoU/GBsIMKJpDJMHwkibbf/zlOzjcoPs1wsbdAu9bw4L4MVfhfggibRTlNVycBz8co1PZGoKZIok0gkEolEIpFIJBKJgYJBl3Kf0V1Rd+TN7FLJG9HRHcknT56MjIyMN+F9JcpERhnLtdy1j7G9GBEm6Q688rOefvOUGxeVij/dD6h7eliOgqcSaTxCsAyQZ7XruMNYDgRij7OGjKkFpzwQT38rOcO7uQke96Kdo6OjtMdKQw4E7yN8s/swFpKWbtm8svvGAIIqVAqBQZ+ZmSmPqveK1SFhyxoTNGxoaIhGeoTdvtOFMg56m3PPkT2eqZ2JZOoI8yuYkSVYbgaPl5aWUJVK0aXu621lspQnvy1dh2Jb9Sy4PljXJMok6gJ0VVozr9bKtCiPZ/S7tnqaaoI7jjUhe8OUJFErs7JA1NHayyPX+aSDuMTXFV3qqKjNG6Rv7CjrzZ42IWvhgaKWeWM6GQ0jdpIboVe4QBhPSZAlf7dXHAXJYbRHf0lqpm6VqTGVRpZeevgCakGroSa0LRZ961BGmXhSM3WNZTrDyqGHMun7oWoP1sAjDRK2LOOITMoZ1OokP0Qb4+tIxhwt/Dg39TlF76tkyXT52aG8kUlurAZo8i1PGiATTxrIf1I4OU8TidohiTKJRCKRSCQSiUQikRhARHaHZ8+emdBleno66h91M7fHo0ePPLxozmr3vs/Ozswow4XnRO/9++6kS9GwjBG/ZnmOubk5D8v2Q1UjOQqMghl9kMnFxcXp6aknCCXK1DGyWx6IpxfHx8d0xH3e2E6txPl62FqPRTIEcmUsKBPZfdzqreyD3xJxHhQlNE6P5hv46YecRjEZy4oenp5n4OTKeG77rueJ+c0nl+DXLCNiRCSKMSX6Gdb7kOBlOpkgGkqowpz2W2E4ZpPF7Iz1oslomnQfe3EPTU4keuiwaTYbl/HI2SakbnQz3Fhmm4giI8bRg9k8ANJ2YaKzMphN3tO1dDKlqBGy0magWUx1jxX1w31CnUys4vb2dpnqz+yG/UNQiKcVI/FSxIzEIxDzYt6DUp+4zmeTK2NZq8ZlXSQTCnYiZVRJ75AihhJGvbMKE7e3MPGkzg9mwYqxpoo0A2iHTjW4BDQuGWNmvmxN5tfbGYpwmJXOUPPcmHEHj8s6mJlUJpGo8dKQIkgkEolEIpFIJBKJxODBTcnYkTSXDK9jY2NdDtjHwVmaYdxFUkWZVOYh1V6sdxPlY/hB7kg3Z2dnW48I9xCGZCYmJhwIo1+GqI+Ojk5OTupeK8Qj2h4V9VBm5Azvqyg7+h/74DQPnUTssQ+OCsWZyNvD4FawtRhTpBE38nh0n4SjSoMgh8lD50dNIIf7EWXoLCrNBVodmpCRrVpMW4mGEsUkGlqAQDZVhejWJzCpTARsDCaZ0smATRJlEjX12TCkwWzu/sIR9ny4Ce4eJj2s+gBI2yxoldWQ/nazNiJtCFEz6Fxwd0Vtbo+HL6CyYM22aDIM7KRZ5SQodJkb9F2BIAqVP4qOKZOHFIVMXDnNA3qwgc4ZNytnxaRjiIOx3fPCrJUntSDPydZiHune41r4sNYhQclllwQMEI717/pKOFLtFQ7vWHU3nn34M6dqIlHLdSFFkEgkEolEIpFIJBKJAUN5es+MMkGU4bokynQhh7PBAIMuhtIbzfQbZUL1e7eBL8o1cZPu6OiIX/NAngeyueghUabslwGwsbExmmSm/Uoyj9tX/Ok3lNW+7Ga5z+uhw57PiLhG/6P8kIfILYMl14rXe5yJ9Ny2v+CRU9MaRfGp/okEuNONBNRDd+GlStybKGMGAvoYZ+JNP2DKqMqmeSZj7/lsLVPiW7cuVJch41+YKaYwemsGsoik9qRe2JWzmCZFSNV2YvatI2ZKJ6NZlV7n6Cf6fG6q2FjmK/P/dWL2VWp5BHsjKrOURJlaJ/aIbmoN6KZ1plwN9Y27SZRpNAl/ZREcV0+LcF0p6puNWMW26x5LgoxykCbMmGmiy2VYbx4UEblGKgzjXlWrHFQ707omhmw7ZGTMLxhEQFkyoYRRnqkno1zeN/KmyNYyKan56sybUhYYeqBb+0+BRpFrx3yc1l3qOVGmMiJlxh1TAUXtzuQoJxK1RhJlEolEIpFIJBKJRCIxgHBf0hi2QZdIJ9PlSICxH0MvgIvKqdmHHBUt6y6ZTobbeeKtNcrbcygEaQrBWKLNJycnp6ennTuk2AVli4EuU3PPzs6icv1zVDQUMmJFkTDDEPvBwcH9koeb1ojv8gsWnzLjhWwDbtHl8hk3d9/IHBpICw3E2n708MuXL3ftu5EPw43ygRBmpKip8BUSfQUzIVkyTHKJkVQJKB7o77f5W5rTCqWgkqOrvtTDxA/lqkWUNMoeYZk1p/JUutwkk8pYmcUkYbRQn+2iifpOq0hrESyZsSasfNR9XzEKF5ailijz8Do4ZgvTsbGmZLjHkUGn32rq6Z4FkUKigM8sP6wx/6lNiB983ET5fvmBThicIMpEvhYfEPrtGS1mJXY4HHifYqQUM48sUdquUrkVlkykHTWjWF/l2gnlkcoWZwBoeWlnkiiTSNQUSZRJJBKJRCKRSCQSicSgoZLmemxsbLKJXkU9DUsI92cbzRitQZeHRAKiaowJsfk1bjE6OjrRhKdR+yqRgOGZ4eFhxuLZs2e07fz8/EsTNSXKxD4vI2uNLfd5jV73ZyQm9qOZFOPj4wwEXXCr103wu5bBkmgiNYTf4btmD/L3+41tUFZDs212/34ZnuKIMJ3lFWGixohxt4mDgwN+tnUI0kr3w8w1kipRxggH75v5X4JX94mVd4L50tQ9Q0oRzeL1genKEoluLqCaZWypRBlgqcpeEWX01rimAeGt1b2gXukYI94gJCnqnngjIW1J5Jrl8I0fkm0xzDvLMa+MXRQA1S3pw5p6jWZSGcvqWX2pD33IbqpHh6a/GYyc4M7xVj5Ne+ddZJSJwkZyUPpWCaWDRL462i+bPAjl7TKDYf/Dn4n8r30oHItDSWULFpE5NYNFlESZRKKOSKJMIpFIJBKJRCKRSCQGEB5F/emnn+JgXHfS+LfCSIBHGMvQS7ThTqm2K9u4cWTWqjF02U12WTKtkYCeB3giqYxEmUaz9IkEhQpRpi61Qso4n/u84+PjciYqdb4afXMm2HBRlMHyyLIhdnSpkt3nyvhBpcABny+JMvzLXBeAu/TkqHqr2EP4RuYkbBkgtEZDEGXupIeVfXO6TGf5nb29vY2Njc3Nzf39fX48bXIfwhJ4Uf1N1Y34UF9lQqpYG1GewDbkZhUAeT9O5PLzydBK9NvqGZpZppMBPWRv6LCZUcaVq13sjT6xHlK3y8w98gbu55Teb8TLcY+MMhWizEOaYWYaTHrkiivdY92e0j3un7J6NhKTLlFGukAklak4M4mHPJd1Z0GMISszyljVqA8zpsSTWuRNQQmxD6YvlXPGnGotKvpAoxT5OD3WIlGyUvWyH9ReZryZ/ExM5UkDLIwnDXyISKcrkagdnqQIEolEIpFIJBKJRCIxYGgteW7cpVfpAUquTBxhjF3ah+yjxZFZC200mgcly+BHK7+ht0MTR8ZN9U/j6QIt54LXOp7DiyPaDq7BJ4N8/ZbOp1SDsvICbT46OnIf/PT0NEhLt2S38EmJMm6gW3fJAltR06G1AT3pdaseOkzonkE1q6Hdvu+Nyww99HR6etp0+iZg53V9fd0T4Xxgfn6+DMtVJJBxr+6j1FsjqdZdYlIE0a3Pj/IbW4rQLwuctlTGm8SvPk+Kk0hvLQKlIBJ9Sd3oyUqht1Zhb0ROCC9qLe1wAPTEkDlWoie2LnxjRc2FmSr+vsS9V0bL6unSmCRP/q7usSTy/jSMUm9pZJn5RhLnwHsLN8/36HgpgXscM0DHokpOdzJZllbOwY1sjv35jBB0kMjGikehvySZ3ue1h7N8wpyWzoz0+v6kEGk8Y4ZK6LEwX1m/VTOb63siUSMkUSaRSCQSiUQikUgkEoMJt+DNMN/buMuVSWUi3fdDflmWyWkT5+fn7rC71QhaCQo9B90fv4R7rxHP+PbtW60TVseBeFkyXPfnPm/ZWqOSHtxHfxiCsyYci1umPS+PbvPKgEqUUQkZ6D7cL3aPO3bk7XIQZW7f9xAmMpycnFxYWFhcXDw4ODBP0traGlPSw/H8cuRpv9JEhDDTdHcHZkJSb02+0rgsZiTRsFfB47taVElp5kgwmmUxuzCq/WyIEglhoq9nl9BT6pXrGC0xqUxJ3RgMaesADDXRQ0MXpZcUtcXjQtoPse2SyDGDEmX4M3K/tWaX7LcnlygNKdXY6TDYcfebe6d3Gq/C9E4lfe1mZlXcgi/u7Ox8/vx5a2vr6OgI30xl6Ggay1B1ybjhePctmd58dfLdTe6C3JhKEuI95NAuT6xxSZQpdb5vCb5mD3WGeiLFwsdhbZIok0jUEfmklEgkEolEIpFIJBKJwUGZyT+S+VtjxQNq3d+6cnvUHVIhY+Yee7KVDDQSFCwZ48nIRjNuakGZPmTJiDgy7mFKumBM1xOKle1FrvucOlApvXTdEe2e9yJqLvinHLJorQGqCLGbYeW6rd7WbCihh+6e88vuIyuHPhw1D5fbfVobnInW0ku3MTWNJsFiYmJifn7+xYsXsi7W19f39vaishhvrqysLC0tTU9PZ4aPPpm5jk4cArZUn0mhWkM1/WmISqKMKcSCtRbH5TNmk+jn1TMW0JKeYiqXK01uF1aHqM2n32gpjbqzGEPa+samVQsyUK9cEVuio27qlEZLtcR7QJ8ksoXxpwn/JMpYz6hvR0rSwMglVMKYDj8amzbqZwmJrVEoU7oMr7JnouruDUseHzg+PsY9220CPUEfohhTG9fKslpQSZSRT9+rZ9Lb28BgawWZ3upLFhhqC1EmjJI5bKSe9GHCp4oTVWbk4oKmIpzIKKPfFe33i0mCTyT6HEmUSSQSiUQikUgkEonEQMH9rCiF87QJT2R2rSZ9BZFR5iEsmSt76u6wFAeZDXGU9uTkZGJiog9PzdKwCN/yGu13v7teMd0yzhc5WiK61s98iLL4grWBDCZFdp/bn4mMQYx0LI6jG8fHx8d9yJWR1hNhFbtg++34XX+QsUaSs7Oz0oyUxvb29v7+fqSr8Y5gcnKytSxajEurjqVV79DkjbpvUW/LKWz8uM+nsCgTWRmwibxQ0t1a2YeJRB+uR0aRddh66K3ZmJJHQmNqnevuyg7qAChtcxz2UNTluOset8u2B/EX866djDRy/ZwtLHIauRhJIVIyJfdiYLTxyhE02aTkg4ODg8PDw4MmcCmPmpCR7OCWz0HfJcrIkQ2XVYpGEGXa7mY0/jdzUjDIu0xQu4droQ20wVwrZPOmyFJq1zNUozhpEBSiPve7yhnKn6pTZvJLJOqLnLGJRCKRSCQSiUQikRhAxL6kW/BR8KhXjWnFw3/WreSL/8Xp6ene3t7a2tqzZ88ODg7Krboebq+X/aV5nz9/3t3dPT4+Pjs7sxcl46R2KIkyccSw/4u2lA32dHUQZYwflGcib4BEE9VPIghfPzo62t7e/vTpEx+YnJwMQfU2RVDoIb3b2tra2NhgjjBlaDD/eqAeMtfGxsYWFhYUhcQLhGANJu6Iwh8eHvLOzMyMhXLKkMl325yMmbZPW4YpWHqNIrdBbyu/3FWlDdgYTGXCRoanIK7lWCf6H/1DlIlp1Q8t6VDvwtbZx96K+vEl2pXS40oSeWQJMurf5yTIeH65LsHSYOhh5Z0ohijhwBQyOE4HBXCiJMrIuXeNq4x148ZaTpFUyQMMOMAmEexo6aWwb2V1uX42LCVfMLI9IaggGLW3Dl3UM4oHqP4XTlSvMyVn6U8OTJG+ROLHQRJlEolEIpFIJBKJRCIxUIjTaWVGmah51MMzyu1lyTQuiTJBUzA4ur+/T3+/ffu2s7MzNjbWJ9V/yi6fnJzs7e3tNMG1hW/qq2xlLYPIHN7POdUDZXp/k75EnaDIRXGbKRPJgSSIuE3M4DIHj4+PV1dXEUiIq0+IMrTw8PBwd3eXdjJl6LKUsodMT8s5TU1NydJDsen4x48fNzY2kMP6+vrR0RG3m5ubm2mCT8aFdXO++/vJlWnv5A3LWSHK1ChAXilYw5+RHimIMqk2iT5fQ8uMCxFF7mGrXAgeXaLnHlTb3ZVg1/XcVykd43aZ3LDtZYqRCGz3nBt0S/cseGNBqhjIjDIB3DC9su3tbZ4RDg4OTBsDpMVImjHHTCQ1cXyDqB3r3c1EmZIUG65XJ4gyrRllZGvVgihTWomoRHl+ibZkAK2k5CxrjfWzrlZyPpmSU9crhJOLeyJRLyRRJpFIJBKJRCKRSCQSA4Jy+7isdtRzlkylbe0qhPF3AbeJLY5+dna2tbXlqdk+3IeNyiCnp6e0eXx8vNEM99b0vGxlnzcOX/Znd0rdk8wRDeb9Kyso3YYoU8LQlAlU1tbW+nPL23Z+vQR9HBkZuV+grozKWIDJGIxVHiz0sLq6utcEMtnc3ETnp6en5+bmFhcXl5aW5ufnzTFjap8bNMe7JO+hXXMhciAZ1YjYZG8zkN1pFpc1a2KZqwSJU2ESfe62fbf0Uk90ePAmTki7rC3VD8kb2stRiLKewZyIBC2iH7TrBqseM+LpJRgjG1m+1hplZxksHl5wkHhywVn69OnTxsbG7u7u4eGhhWzMX3JeQLKLfAWdcP3P20imklGmZMJ1QrBBBOQ6BlQ97P+kKWVOI89dxPNme4kyUQ3WR9c+zChTIWAF16pM5lemd83FPZGoF5Iok0gkEolEIpFIJBKJAUQrUabn6QHaXl3I/cogKJyfn3/58sVUGf2cRcCYtLuK7r26CV73rf/YVu45K+tOcyRmR6PYAY9N8NtodXw+8nN45Nd3+rPv5e48r8PDw6Ojo5G0/x6qGAEDJOlxYX8zsLq6urOzwwxFMrxaTWB/f393d3d2dnZ6enpiYsJcRAYvnz59asCgNblCv0X4aopQ1yDKxHQwG1mNzE5J8Ym5fPvAYSLRPz6boeue09T+KTB40g5R9wkjsL2irpTVC6KMAfhapAoLfzJ4FYMReq9Ink59/foVd2hvb29zc3Ntbe1DE+vr65Zn5QORDSjy66i3rXk6b0m3Qh/UDUnhYW06OtkjQ1XYt1rkq6s8RDf+lyhzy/Ksd7X/tXiAKoUTBOX2sogSiUQ3kUSZRCKRSCQSiUQikUgMIPoto0zbEQSFODXrhYEBc5L3bZTUoAWvQ0NDVvkZDKLMowK1iMREmyNVSQTXbxkzKIvXhEKqhOYNcsu4PyVQbsq3N/0GIh0fH9f+oOQTExPz8/MbGxt7e3uHh4dfvnzhXl7s7OyMjo6OjIz4Ojw8PNYEX7Eq0+TkJD/V54no6wizCqmlcqTK1Cy1mMKNIvFAVF+Kxg92pD8xeD5bJypUJm65+g8SsHiWn2OF5dXSS0E6qQVXJrL+hGGPypUDY88ZF2stbW5urq+vr62t8fr582c8Jfwi08n4mIBHhGuEU4QvhKfEten3Sl7d7Qko3Fdqzm4TaIgJezr9GFI7ExfMlWDJhIdfVrnqxDNUjYgywTX0vEoIhz/rwrdOJBKNJMokEolEIpFIJBKJRGKQUGaJqOTWrmllnxt6Wub/cMvSYIA7d32bVMaAtOyEKPEeab0HQP0aNcnzcWUjy+3722xVl4lk3B1uXBbSMn7fnxSoSIYvZKiYu+Xee/St50f5zZmZGdR7dnZ2ZWVlp4nt7W1eZcycnp7u7u7yjjPXkNjY2Njk5CRfWVhYWFxcnJ+fPzs7Gx8f59cGzIh1GUYZ40+VtiTKRHaWupxpbvxv4oGyREJW6UrUdPVMdFPmgyp2TLp1FYMoE1HtSEbSn25JxbCHVadHdV9/K64jLtDGxsbHJiy3hGu0v79/fHxMZ+21HhF+1GwTXEiXAT44xJgGn8PBbVXsaABLPzf6/Pnzhw8f+JM7muEyOOJpGUJiFeZKWQCr8ozZFpejRpXFSqKh+lYRThJlEol6IYkyiUQikUgkEolEIpEYQMSJPbexBvLUbCtBwVrpw8PDZaLsPmx2RClo5OTk5NLS0vT0tM2u73C4w15mZKlFm8v6LPc47Wpmo8giIwtK3kmc3u7PiFQEpXhl4szNzS0sLExMTDx79uzeDS6Jel4MNzEzM8OPHx8fS4vZ2tra2NjglT8PDw9PTk7Ozs5OT0+/fPnCVw6a2G9ib2+Pj5laZnx83HPV1mZyCz7LMD3EEFVCPiVRpkbrRVn0LfIlRPwmBzpRrzU00yClqNvi2ERtHX3OSI9RC8NYNrhGGc5uOToMytHR0ebm5ocPH/7888937959+vQJ1wgXiMFiFcPnwcnB1cGZxCsLlgwwxx6+kM87kdKjwoK6gSjDir++vs6fOF24WLyWk6Jrk6528y6eFzr0mBPPULUTTvn0V69nwEQiEUiiTCKRSCQSiUQikUgkBhaDncnf/biI8j5+/Hh0dHRqampubo7XiYmJoaGh+HD/7NkFmcA2j4yMzMzMLC8v0+anT5+m0tYLbgdHWiPeMbxhVIMxHRsbi1OVfbVxXDYGxRsfH5+fn19aWqLBDyRsVegyjYIxY2Ul5iaS4Xb7+/sHBwcnTXj23cAekuT909PT7e1tJrU5ZvhKnKuenp7mncpx1SuDQ4mbVbcMbNR0vSirqFQqqQ12tCZpQIlE4gb32LwO8neDO1gX816mrKg7UaZsPE4Ons/GxsaHDx/evXv3119/ccGfx8fH1qzENeIppkwew4X8GC5whyIFYFS9uRP4or8mn9t0MjllbvMEXeGy/MhyazUmFX8ylSqRqBeSKJNIJBKJRCKRSCQSiR8Cg7dpVW7Pcf306dOhoaGFhYXXr1+/ePFiaWlpfHy8D7tfEmWi2WNjY7TWZB65vVhHPXTUHj16xCBOTU0tLy+jhysrK3Nzc7zTh3OwbIzNHhkZ8aTy48ePO9TU0dFRfnx4eHh6evq0iS9NcCFd5vDw8ODggNejoyP/9DQ8bZucnESYCBapPn/+nPfNf5Ma+EDtbY0D1fGod91Pq+eankgkOmrYa2c06lXN8+bnFHFxcYFXs7a29u7duz///PP9+/fr6+s7Ozt4QU+ePMEB48nl1atXL1++5GJmZoZ3cH6GmrA2pakK+fBDmEPB9siZcssVtrXKUuPH5qreULs2KbyJRB2RRJlEIpFIJBKJRCKRSAwsBjtq+Oh/8eTJE6PpS0tLb968ef369fT0dCmK/uzFIGX9qV1HrjwTeaf5ou55rtcSMLyOjo7Ozs6+ePHi7du3z58/Hx4e7nMlbBRpOdo1fFHaqXIX4z3MU0M1ZuL5+vXrycnJ0dHR/v6+tZl85U/e/PLly/Hx8eHh4d7enkloePP09HRhYYE5zqyPFDjJM7uT/YxCS55Kj+BZvUJolaxOJlEAOcSJROKHNe+WoosipGWCmbpUxqxdNc+bQUfwW3Z3dz9//vznn3/+8ccfq6urODbn5+c4jRMTE4uLi69evfr55595XV5enpmZ4X0GseKpPtBDQ5L4VN++fYt8nF2Tbe2eESpPBB19Xhsw4SRdJpGoF5Iok0gkEolEIpFIJBKJRP0gKcEwgDDiyzvDw8Pj4+PT09N1zDZR64OzddwkrbBkKq+3+fqTAhJluDBBiwnz6ziabdHDyo9EjKdVN5ywJycnvE5NTfE6Ozs7Nze3u7srM8bcM8fHx9++fTs6Otrb2+NfL1++XFlZWVhYKMuWJVfmlohIagRTg7pUI6JJtPm8iZ4E/7rf5R8td04ikbire2wVSGvraNXjVbvRz05ayaMNfk+tB4Uu4MPgz2xubn769Onjx4+fP3/e2dmhX2NjYzMzMzgzr5rgYnFxEf+H99votsVwh1S7vIJU9K3/nxFaF9lgk7eRU37dY1S9hFOpgJlEmUSidkiiTCKRSCQSiUQikUgkEvV8pG9GeU1QEYHei4uLb01wkSLqJmoavm1t6p22d2UbPLsE1+je33//rRKen5+nYtwSjx8/Hh8fl+g2OTm5uLh4fHx8dHRkIpmdnZ2tra3NzU3+3NjYkCizv79/cnKCkBmyqampMq9MIwvTXKXqFYGH6lrHAb2tcE1qEa3R5p+dnX39+tXGl5GbwQvY2OXW/BAZl0okEo1L/i6+MYsp5h1Tr2EM37j/eZASZc4LBLmnRoaubKocX9yY1SZ0ZhiLsbExvJ2ff/757du3r1+/fv78Oc4MvtDo6GiXXYLElUpYUoflgkQKyXJ820Uur1HCp9IJabQkKTSRVSKRqAuSKJNIJBKJRCKRSCQSiUT9EJk8IiMCb56fn3/58uXk5OS4iZGRkXp1agCOzAbq2OBKMa/b/IJbw2jgs2fPPLrNIJ6dnYUe8tqFgEct9PC7xAsLMyHGiYkJt+C/fft2enoah7DHxsZ4lSiDYL9+/cqUl6vEd/lW5JVJfBcSZbSfXDsdIipZR6KMiJbHyeb2rjv90OXItTAAiRYSiUTb3eMw7y6OWImSBKnd6POMMuYJqxG55+bu4K7gyeC9rK2t4c8cHR3xJs7h4uLimzdvfvvtt19//fXFixczMzOxIg/YU8Pf/4v+b7ntVA/VwMcF2u5d1E44kclPp6tClEnmbiJRLyRRJpFIJBKJRCKRSCQSiVrCYIDxALeVz8/Pv379+qUJg+iRZCKjiZ0bBfdDy3A1kq/FkeVK/iEpF+L2UXZ3h1VCrk0ngwZaLQhpBFEmlfA6CYScndTx/sjIyOTk5NTU1MTEBGLkz+HhYUS9urp6fHy8ubnJ540qqYd8LKZ84pb2U711CkfYoy4MjAgAh+UxANz2gE0Yup6nNCgDVFraNCyJRKLVLbnOtve/0agwILmodd4s+oJDuLu7u9EEF3RqaGhoZmbm559//vXXX//v//7v5cuX8/PzrQ5MJ0aqy5lLJHdWqBXg9nygXi21QS9zqXVCRaHVhydNCX0OanhdHqAicWak8Qt+XlShTTucSNQI+fCcSCQSiUQikUgkEolEPVA5AhtJsEWjuRltAY7WrcasxtIJROTYfXDEftoEQ9Cfpa9K/QlGCzAMYyUak5rIlbnlb8bWuRllJGyFHobext1TD++E4eHhmZkZ5vjIyIh0GQZIrsz29raVg2KDfnx8PKV9S70NoanqhoWMSkZYqP9ncfAjTSfTaCbLMclTcCgHwMyGMkf0rlzmBrLIVCKRuJ/FEEETLHknVocsl0VduP6xco2Co6ArxYXOVaMPqIr36A59wV3Z3d3d2tra2dk5OTnhzcnJyRcvXrx9+/aXX355+fIlTk53aL5SZMr8JZ2TZwxWeBfBfOJPlum+HcqSg6sG0gVd/cjD1y4OrreL5xGPefRbzqeKH1KZnrxTZrFKokwiUTskUSaRSCQSiUQikUgkEom6ojzb99NPPxkJcJ8x0oQkOooyowxiL4kyfZ7bX1qVDUZbeAdFGmoi6ijdPqNMJJVpJcr0LeGgf/BdVTGRzHgTY2NjDtCnT58ODw83NjYQL++MNvGsidyjv6X9DEJJo0gKFRU6LNvRz12Qn2d4iQtjfjLeVJJ2BWwiuNjNg/hXNiMCVI6UljaVOZFIlLZdz0Q3poz6RwaIfm6/i9HXS3DtIlXHld26S0dHR7tNHBwcIH9cmvn5+ZcvX/78888vXryYnZ3F87zyu51ojwldIsPQwzOjfPeOFeZT//vGpniRJWODFZRker2mh2tj+QBVOWnQzw9QqlAIh6FsNAnK4XdlZsdEonbISZtIJBKJRCKRSCQSiURdITvBXUs5CgZNgyjT51yNwUDrPm8lk0p/wgZHiN0DkfIG3AS/fUYZN4hNRcO3PDjrz6qHSZT5Lr5blUlKnNSHCPMgXvRtc3NzdHR0enp6ampqeHhY/lxO/O/qrcYTiam3rRm5+t9+lpXODC8F++dOdLebjZtxvotL9LBwSRlurBBlUuETiUT4JJrBIAtKZS7zVfSzMxCszfCjwh+rl6GTosTydHh4uL+/f3BwQI/owtjY2Nzc3NLS0uLi4pUsmc4NUFT5icKjHc0o0yiIMiXvpM+VUNciivkGmX64CR852yKfyLijtuvJSD3pZ+HEY45+l1VQg0KUjzyJRO3wKEWQSCQSiUQikUgkEolEXVCe5jcYYKB3ZGTk2bNnEmXkakSCgRRa51DmwA/eicI3UfmVn+x5UxtFfP3k5ERmj6WXIqPMDUyLSkoJI1J8CyVEFfmTH49fjrTkqS1tAaKemZlZWVl5/fq11QoePXp0dHS0ubm5tra2tbVlICoF/l14NjqqWaHwFfvZOoX7sBfn5+c09fj4GB1grnlCfegSDwzYlDW8JGZdWbik04ar/DOypgXDz8RplXJjiUTiR3bMdGY071zI38VCYirxTPq2OGa4Z6UzCcx9Uhfie6VIjXReViicE17NjjM5OTk3Nzc7O8sFw3SDh9l277dCQgpSe9tlW3G5I0tQLF59y5WJjCl68mog3WEqMaHGxsZ09ds4Ouo892KGeru+kkyrHxLHDDQmSMMn8SBed06fE4lER54KUwSJRCKRSCQSiUQikUjUFJbYiJIrP/30U4X9kNWXOo0yc7jxgGAp9fOZSHelaaqq4ia4fBcTw9y+YotfHB4elnDAdRAO3GGvEA4SDwQzXa7MixcvFhcXx8bGEO/R0dHOzs7W1tbe3h6Sz4n/XZh5BY1FgNpP3lRvj4+P5Xj1ud6WMUjaTIN5x8lIvyLT2MPjfx6I9/x9hGx70uVIJxPH3DOjTCKRqPgkpr7QtsuDxIJpKgGmo5+XyArrOjKcRe9qNBaRmESH0EWKEZmamsKNmZyclMZUrjVdEG9rCaRGZ+js8YORVMYHtGCf9O3ASSwrm8owSZSRfNbejDImfPJ2Pr32rfel3xUsIpsqUQbJtBJlEolEPZ4KUwSJRCKRSCQSiUQikUjUFJa8GWkiTs0G+6H/M8wPACr7vBXh922zo7Ue3/z27Ru9QJeGh4eDKHN7CcTpbb4emTlqseXd//jnEvEO03x0dHR2dnZxcXF+fn5ychKZM4KHh4d7e3sHBwdJlLmH3gbRkBnhwfc+D6Y2CqLMcRNMtEaTR3XdyeZ7KF5cRLWvMmTb/f5GeayyslsMaGp1IpHQN9a2j42NBX8XuyFRBptpKZn+tOpyFCpEmfp68kFMsSMsSYwIfsv09DSj49B0eREJokzlKamjNZi8tWmNUELc477NthgFsyIDUySrC3+pjRllGgVRxunZz8c8YobGuQiEE3U8zeSX3kgiUTskUSaRSCQSiUQikUgkEonaPtVfVg+JVNgXFxdfvnwxGBBn3eLzuXnXdkiU8bSo7JAQfuuB0T6RP011kzeCRu7zRhkalCri661EjXg/rj1MOdbE0NAQ73z79k1RmJwjk8q0FwwQop6cnJyampqYmEDmDAdyPmzCFEF9qHj9NnPL8hxyvJAberu/v7+3txfUk36zNvGn+cMsaWHUjWlLR8bHx10RyonceMBh/TgNH0SZnoT3SpaMMc6oA5WllxKJRNjJkigTbgl2g/VRHmSl+lJvi2NWavSEJxk85jJvVs/reN517ZBhaUIyrl2k8FtwYBgaKardkW3jMsNN1M2pZJTpxCJSDpkPaHKaee1bMq5k9yANM1l0O8NZuhOZ/jYuTTy6ckckU2ER9ZXaRxG3Sia/0pN8uNOVSCS6jCTKJBKJRCKRSCQSiUQiUVeYBcSa8VYPiVOz7ja2hswTbR8Cd2+jmBHCl69goL3f9kkjC0UZMeL9oaGh8SbukYjCoJR6aJmDi4sLbnHQhFvJSZRpL6K0hDJnvCQnGVrLWX9LvbVQURlMRW/39vZ2d3dR3T7XW6M1WhuGnklHd+hIEGX4896xJS3boya4QA6RUYaL7ovFY9xmWZCG6KHzmlYkSSQSHXXMStvOEom1Z4nE4dnf3+9n39hMHuFDSuipb7j97ybKhSPcRRNhtisxye3FW5a1MqNM50ovlYsp0DFGA3EweGUh63MlpJFMGTm4UXfpga5FRTI+a/gApT/jU0N/zlCPGUQ7g6CMcHwM775KJxKJtiCJMolEIpFIJBKJRCKRSNQVBgNGRkaC4vDo0aOzs7OjoyOLsLiLl4LqAgwGuIVqRor+PDDqUVGpVG6C86fJ8NUimS53+s3IKMPXJWwhDfrOLZSDSWtSSdoIhkyujFvzUXYta67dSYYV+4lFRW/7ef4GZI145tumMsXkTToNHxKwMXz1+BJRNiLind3XLg2XTMTI15VWJZFIXOeWVBIumjAsmIV9yGNuNPOEhQ8pjxkrV68sMqXRNoOLSVzMEaLrwtCw+Ha5SE0U7/tyibKsVUdbEnzTIMowviphf3oXkVpPogzTJ45kmDSlXUSZ1pMGwbDvwxnqow0GJKhO5uNELBMTE7qRSZRJJGr5SJgiSCQSiUQikUgkEolEoqYwo4xFWMD4+PjTp0/Pz88PDw93mjApQrnVWNMN91rAkID7ywh/d3fXLeZ+0JO49kjr3t7e9vY2jTw+PjYRBcozPT2NFo2Ojt6DKGNCmqmpKX7BBCcSDrgLcuAupRxSCe+BSsAgok3A8bIQTytRJqvSVMQYpcQiI9fExIRFrJgIiNEoSMQp+yT/f6U8h5nD9prQzvMBph4TkI5Y0qLS6zvdK7QriixIBLTgUXeqllQMlwEqE0JUiDKp3olE2vbS0EUODHmQUaBQinCUd7nO4HTNqlcMuwxjfDN8p3Dga1dxqbTbeiZRKc+hCQpmNztFY6w6etJEpCXrdPE+iadmlInxNWudlUl762BU7ivlmrbtNoGbwaiFhx9k+rKd96OzhMxl4sr9NecTXo00lJ4/QLXWu+RxhuHb2tpCOAiKNxEIkuEBCtfrHicNEolEPyCJMolEIpFIJBKJRCKRSNQVhjNHRkYM9E5OTg4PDxsMiI28Ckeht61txcAMBDCcbKB9e3t7c3PTM6N9lfbg7OxMHhXqQfOu3Oe964HIkrDlTnpJ2OJG+/v7ZrxIPWxjLyyLY8CpcZnTSHCdGWVuA5MhofYoP6o7OjraaFZfkusmV6YPz3xbQ0S6m0b+4uKCORgdYRYzBx+4svCDQ034UxJlolxFlxVMDmJUxdKeDNg6kkgk2ojI9CAD2OpL8iDDjPRVzjDD8LQN7xHbTlP13qVZ1M7QmVFGn0SWTKwad+Vutku8UR21TEvW6YwysU6ZN0UyfShhXyVcRBQlVYt2styjfrj3U01YpPJOtVlvlkx56yhNxa377cEhhEOrtprgAo3CO9Lv8gGqjcJJJBLdRM7bRCKRSCQSiUQikUgkaoxI5mEigdHRUZN5RAz18PCwklSmJ7huD3pgwpyRgAFRHx8fb21tbWxsMAQnJyd9FYkJogxtQ0nKTfB77/NWCFv+yN9//+3JS3fbkcP5+XnPlfAGPXzgz/aEdvOoQKMIPvUkClVHmHXAdEozMzNcoMnMEUM1Vybl6gcwlY6OjmSh8crkooXS3eiFjMmHRGuc0U+fPo2URbzjge8gynQ5fBURbu1JSZRJNU4kEld6ZSbZkkeOKcMZC8spxbDnbknAMHzQi3kN712iTK3Hwqwh0VM5NF12VKKslVVHkW3XygiW+VrMm+Jaxihz3T9KaNGlSDmJBvJOcEEknPFnh7TRVHmMzubmJg9QNOD09LR/vK9SOICBQ39wILsjnEQi0dnnwRRBIpFIJBKJRCKRSCQS9cVPP/309OnT0dHRIDo8e/asTOZxZVKE3MhrF9zodxRGRkasW4S0EfvGxsbm5ub+/n651dtlLkXlXuZUp20oRmWfd2ZmxmQw6M89mmdmDnOze+r00aNHbnm7p9zKlRkMJeyTXkSCmTh63t6GDXDqDmYu6or+z83NYUJRYyYF9pM5sr6+zmvP41gVyZszbHd3d6MJLphohrLmmjCjzAOPNfN1fnO4CUxEEGWYxdzdihWdmwithstT+BoT2UuNyxIeuZwlEokr3RIsIVZ9fn4eC4+dx1ZgSfCNsZzY9rAk11mebjoPtCT89orLVNP1V7dEzqUl/KTL/N1El1kylj2KuqjBkeqCYKP0kjeKlgQdhMb0Ax1E16LCU6HNTJzZ2dlwLe6acvKW/obq4dMrU2BtbY1mcF0+vXb/AarUHytSme2GxygG0WMGppOJtFVpeBOJOiKJMolEIpFIJBKJRCKRSNQM/1zCP6N6yMzMzOzsLBfB1Sj3YXtYgCl2G8u94DL7Rd3HQqKMNBFeTeqzu7trgm4rHPW8m6Z4sVWGYVASm43auM87MjJi9oh76GEQtvw1q9iYVEbOkDvLvc2jfuUo1DH/im2+aEKRYgcMRzGCrSSJB3awMtaDBGRlLpb5+fm5uTnt59evX5kp6+vra2trUsr6p+9y3ZhQ8niYYhHKWlhYcAm4B92t0kEDnENDQwiH9YVrA0VHTZycnHQt0Y7RO9PJ0HEjZ5pcmqe9GmD9TCQS97bt2C4cGww75h0jj2HEE5bHjG2XB9kPxUmxaQcHB7THokuy280lg4ljca9pPRdaHiX8uKAX+i3WY+paQhclbB6XSBRHY2iSDJ62uEnXrapRm9Ul1dUZZ5iBXl1dRQ9plVVQ+0EJ0UCaxAThmjGiwVLNdC1kzbbLeY6v+xjLU4Npn3g8oQF6OGa16fnTk4lanaE+UzeaVWsRTjzyhN+VDkkiUTs8SREkEolEIpFIJBKJRCJRawRLY2ZmZn5+fnt7+/Dw8OjoiFd3PD1KOzw8zMe63zYv/vnnn2/fvn39+vXs7Oz8/Jw/YwOdVtW3prunY7mgL54sfPLkiRkXTk5OPBbJ+4Y66GwP2yl3x9i/8SHLtcivouWmk7n3WFjFJoJSOzs73FHCFjflTYk4ZWmnMht/F5Sw0dzvpknoIdp4cXFhiRn18PYMoUbLWXCPRyuE8sBr53qn4jGVvjXBtWEYiTKZZuNO6oECTExMMAtMPIDGHhwc7O/vo7fW7GBqmFtFqUYspPut9bw1Rp62bWxs0FT0mYYF0ceADTrwcLEEUcbZYazIleX4+JhreXWd7jLqzU33mgiWjJFXr6PuWCpzIpFo9Y3Nh4FtxPPBMbM4pp5PkMu7vGJWbofTWNImcFGkDkiRkWZRR/mbmUxzrauPoWYVw3Trg3XUboeQreljwp7I4EKTlKqrWKdbwl1Mz2ZNQ5qEj8GI8ybPCNIsbEkXHMgrlTDy3MQzAm/KwZUow1Rq71NkPEApE0sXoR4MFsPk06tF05ikXZ4ClQcH7AYzdK0Jn25oT5nG74H1LhOJRG+RRJlEIpFIJBKJRCKRSCTq/3j/5MnY2Njc3NzS0tJuE9bI2Nra+vz5s2lO+MDIyEjs/XWBo1CpnXFwcLC3t2c+eSka09PTboOWzIlGrUKeMiSMtUuUGRoaOj4+9pgy/f306ZMnVnmdnZ2Nrd4uy1/Cyurq6ocPH2gSioGG0CR0Y6EJBuLh8XX67g9yL6MRHt4tCQdIqfuErYCRACYIA+SRYhlmUZfhHnpo1IfXiAl1R/FQMLpzenpKR7i7RBlhaK1d94paCcEHGiSUwVS5JqZpwUxtbm6ONSFRhtmN1Sq/2GWa18XFBXpLqz43wYXpZIzWLC4uSke7X/W01vsa2MMsIAF+s9EsDiJnhUnEBe93gpJV6XLkwXJdQ7fDUvEns8DgaxcOcJcp0P4pkKS0RKJvfWMThhnPxmbikFjHbWNjw2wQ2E/LzHXZtgewq+Ge8Xp4eGiSMAxdpGApU2fVSP6W1JEGoScsu1fXBcepCykGkZgsGVaQ7e1t2aWOuGxjPdJOCDZ+M5xD5CCjAiGgh/jGjCwDjY/Bf9vORLnlOtu4rPwlSybYWjQMj2K+CTm47WWrlCcN+HH8cLqv94WDQTMQiMs9raUl3XyAbZ2htOfjx48KB7UxfSYP3TzySJRJe5tI1NhbSBEkEolEIpFIJBKJRCJRdzx+/HhkZGR2dtYAwM7ODhe7u7sHBwdra2uTk5MTTfCZ8fHx+FbXthq5y+Hh4cbGxufPn3nl+tGjR9PT0ysrK/JLjMLWDmXc1OO/IWpjyWdnZ+vr65GbwYQrpfwbndmdr+yAX1xcqAkfPnz466+/jMQwBDRmcXFxeXnZfd4yp/r9WkU3UbD5+XlT3HMX9PD09BSFZOgVjkSZYJN0kxolWwg50Jjt7e0vX77QDPrO3UebuEfA23QXJrqQr0YfO7FjXkl3T+PlYwEkfH5+zuyOSExJX7i3bE2N49etlWCZp8HgypT8hpi8qO7S0pKVL1AVXpm/MkXUWL7Sq3AIDWbEsZ+fPn0ynoqFYThoG81+/vw5c1kqz70LSUSdCP9EnVwyUGmDVRJlpK3ILbPaV+d6Hce4XThooewclJxrzBoy6QJRppxNQRpzOpjMqfuraiKRuMGOxRKmk4m9Yq3HcGE0WKxZQHFLsKLYTHP+cdEd215xM8Itwap//PgRc8dSq1esMfnSROTNqhdXxlw4EmVMpmK+kMhMRvdL+mknLDa3Y9C3m2DRjGw9wHqCytlClm2UbTlYQTydaoI/fVKjYVI/TejIh/FDupCnrdU3NpfMahMIipU3MqYwceTglvkgG+0o6Bn0a/qOWPBhUAZrkJnVD2/HhHYSwZkXXVhqW2eovDoaw7ODxwxoFSYFd5EHKBwwhq/7o5ZIJNqInMCJRCKRSCQSiUQikUgMAp49eyZHwTLq+/v7x8fHwVEw2Gki9ygg0ugMTaG1Ko3Bzo8fP757947G0LChoaGvX7+OjY1JU6iv2GMf3AOjVjIyXw7vMBAMhzkPELsx7Aoho+27va3yNwsF8n///v2nT58Yi7OzM0NHy8vLz58/R22MFT3w1nbTpDL88u7uLt1noA3wjzdhBGh2dra8XRf00JxG6+vrfzXB0CAEj6hOT08zRncdd+M91sFhlnGNVtMv/oUc5H51KIU+t2Zqc2umOa9cX1xcWNvLWFS7Tv1GpEeiDOjC+e+ewFPdRj4YTaRqUi4GN1huVrYqxdu5Egmts9jaHMxfZjFzmQnFtELN0F6jNUy69p5Hd7GQ+ecve86bZmBPUHVmuskY2mXKKr1mVsrw8xg3t6ZJjBGGlI6bjSDqd3R0HYmJID9GDGSCpURiwBBuyeLiovRx7RjOiTk8LCEXuU86Z9tbmbiaONySDx8+YNhXV1ctaWeqxcZlDjxW3orDWReU1S0ZBUv4sZbRKUvp4TjxTntr1lRYxT4HIWSWLUuOSn7llUXEsrDh4biadCJJGH10ZFmp1TTpzrTNzG1WPjW/XVnksdNKaD1HPIqPTaCEDA2D4hNlmTGl7cWPIqNMZEVF7WXDMCgMHEP2uAm5VvoknXtwuFI4VuGUx8ZFEHbN4YpVybpLicQgPAamCBKJRCKRSCQSiUQikRgAuAk7PT29uLi4vb1tPECOwvr6+tDQkAknHj9+PDc3VznB2dFD8FaA+vjx459//vnu3buNjY1v375ZdOnvv/+ue9GKiFtIj0DCEpLGxsZkCMljMBGFcQKuR0dHOyT/VnkGS+avv/768OED17Tq2bNnppNZWVlZWlpiLNqyz2sVm9hB3mlCIezv76+urnKXOB46NTVVoeZ0Tg6yZNbW1t6/f//HH3/wSntogwnw7xEXubi4oF97e3tMrk+fPvEq8ev58+eNJsMADW9jnolK8758+SIfrjwhbe56gITbFc+Ik9ZI6ezsLEgJA2lCPdOM3nrSHXjwnf5G5QgZM8zxLrdNyg6ahgllIn/+/Jlxl5BnOhnApLNUR7tuaqIyOot9QDL8uIXzaAkKPzs7yx2lrbRFz1vnrJUgDCFzU9406w9Nom0MDWPEZySsdIG2EkQZJoIhVekybQ8fJhKJNkLHDIfnsAmcAXmQ2LEoCSSwMB1KkdXqY2BPrC+DVf/9998xdPjtUt5pKqbVID3txKoHRbV2pZdcN1k+WClMzIZLjAPjc4o8gzLFYBs9pUaTb4EMI48gboz+OfpgmVSz2lhAMwx7e7ODRIU+9ZAlTCeNWyMHn9EYd+tmSgfp3DNCBegVDXCdxTfGu+AZjQGS9q1rIQe3E4k/4wFKBgx3walgdEykxIgwQXhwUHRKhlZVMj+1SzjXsWRowLsmUCHGy4RPFl0CNFi6cFZgTCRqjSTKJBKJRCKRSCQSiUQiUVeUGeYbRVKE5eXl/8fenbcl0mxp20cFRBTnearatXf39/86ffQ91GA5z7NMvlfn9bjevBO1LAUEPH9/cCAqZEZGRAYZK1f4Zs1qteqJge3tbV9k9DTq/Px8d5LMX15eHh4e/vjxw1EyOzs7esUzE75u7q1q3aP+Kv/INxDhSpVKxUulqPCPj4+Pjo5UCL4j07noY2Kg7ZuUvlzrmebv37+r8PWo5zc3Nw5SWVxcXFtbczqZdFqI3GtXbIl66EgCva3roRcGuru7c3IOT0p5tRTV1S7MMTcaDd8S+u3bN5WDo4Vqtdrk5KRv5HUA00tSykfZNpvN29vbk5MTz3L9/PlTuzk+Pn59fe3jq0cVcif2zlEy2gXtkRqXGpR20EvkaI/06N159ftry4cTPkz6Ue+vw6cd1EfrSdzdnuvzhWYyKw1pf53jSnvqlAPaX9+DrqNcTDjMS/+ocu7aDcTqRhxr+Ndff3m2xjkGPKu0urqqhpyZbmxLX+pMDKpUaqezs7N64qUiZH9/3y96vZJ2xcqEzD3uKn8dC22AI5n0xBEq6kxiRZIOFb5Xb3FziLgxnVjVENwc1JM4/JEBCdCbvLqN+iv17epOnVTGcZDqW+JMJ+pV1Kd1dDm56J8dwOEoGQ3P1Luq39NGemymXk4bqa6mdWm5Hj/nZkahXnIoxicaNXmJWKcl0ylML6bLvI1pQnQ0PfbTCE3fPnTcdaz1cfpcnev1QSpwByE5FNgRM87Pl867+ZaNuU/RW3kBVo2QVSyqjXE/g07rXl3IY1HnLOn0kdKOawP8HcGjCy/Mqm3Q+V1Di42NDT2quHSK70R6m3TF1l67cJzo8S7hNZhySaybM+74C2wXluv1FwcdF317dQvVVxjVExWFKm2EEKVXpCLDHNC/CJQBAAAAAGBw+IbFhYUFJ0W4vb2t1+t6cnR0FJMBueRynm/La11DJPzykt/zU4O1Wi2dS0Y8v6ttcMYRbWS7Epn0AmcaUKHl8/mJiQkXrKfbPe/u+ZhYv8M3lUZAQ9vLv1qt6kPjPlFfAT8/P9fbTk5OLi0tbWxsrK2txXXeNhZFrHSwvLzs3Vc9VA30DdwOwvDcg+jP0vditrccPP8RuWT+/PNPlYO2QZs0NjamHdfu60C4BH5rqjvyrHjKx4udeTkY76D3Ln17+u/u2qPbow918NN2wmEc+kvtjkrSEVpvb1MOCzBPJnmNAHcp2obW7Wzdl1ccynenI6gCVOtQDXHVvbu7Ozk50cH9+fOnw7xcIJ7ei0CNRw/WS/b3l72oe2+vW+cbvvWjtkpHWVXXUTLaYB16L/fWxtLwbdzlctkJwMT1LULE9HrMEqX7kMzKF7+7767kaqdqs5E+xwtSeCUIR6SpXb8kuK0tHZrnL1ubg2qIZ85ed6CZVwO6PDZ2oIzPZV4dMt0SnSbKQYdv6dt/OSxxIKAGxv/7v/+rjl3PNXjw2ccRzOpVjo+PPX7o30RuEReu3nsqocGSem9nMdH+6iTidT91Kskk4XvLSCn3kEtG416dRxwerReddFPVQCdQx6nE6D3SybR9fUmP+f22Lg1XMJ3HXRWdXCeGXrkkVFQnXJXMqweQv6yEztfifJN//PGHKqGeOFOd66G+I6yvr7d9Scenisgb7LhbfZyXXhJVGDUEn4W95aLC6dwXKBeODo1zyahw1E414FG91SeqCjmESI3UIUSklAMGAIEyAAAAAAAMDmc0mZub8/3uvs7oJ75M3Gw2nd5DL+rPnkl68fxtlM/P7+r9fcNorBWiJ8fHx/qVE+B7JsAXGQcjUCZ9W6Qv9apgHa2iwt/d3b28vPzx44dKRi/6iDgfw1N3Rj5/W+3z5e/M9rHi0vfv3/Xk6Oio0WiUy+WFhYXNzc3Pnz/rKGRWTmmXQqHgcBzXNBWCJ6U8LZFLJn5qtZp+u7y8rG2YmJh4pqa9uh5eXV15pkQl75w6eq4XtXmq+aqBDjLQpuoo/FagjBcUiIQ0+tG3p2u/HCVTS+jN9UFPlfBTu/bUlqjxOkpGrUkHdHt7W23KSz6pAB3K4DQ5b2lT+nTn/x8dHXXCJ68zpWOnwvQ6Ba9+5x6f7XP/qWJ0Bh3f0+xJTTUfb7z6TwfAqR05MunV+/t8lXPqoP39fVVat2JVY/2oTfKyCOvr62rFGxsbXq2gEx2pV19SpYqFlpyiTLu/t7eXzsakP/itm7yf2ncvR6I3V4P9+++/teOq5Kr5quEqcHUXevQHeZIsnWihQ1QIseqWnjublJqDjo4ePZ2ZzuHUetzJNwO8L8/BO37XIW5e28V9u3p1tdkYG3s9SvXtT7XcVw9L3L950Ub153/++aejZPS56k41NlZ/ruGZNiCXRFpHpoq+DqrzelI+iai0vWqeOna97rySjkR8xZqGTxW1B5w6dap4//jjD+f8m06oAqic9XFev9Lx682UDn1BSI+vPGbTZ6kovDyrSkNDO/+ZY0R8slONfSr956sroT83/R3BUTIqMf0qIunF4/Mu3M8QGXe8AqbagqOEncHO415nN3Q6N+e5eWahtFcXjuN0VTgOr9cgxF8cHJirA6fC2UzoG4S/O9C7AgOAQBkAAAAAAPpeOtW5rzP6lrjrhJ44CcHh4WG9Xo/oDT3xnXmvuB8uk1w9TR90fHy8vb3948eP74m9vb3IZbK8vPwpsbq6mrkC29druMRMhq+Dl8tlp1hwRvdGo+FCiEAZWVtbU/k/M8H8TIE8U/6+BfPnz58u/62trf39/dPTU2c+mJ+f39zc/PLly+fPn3UsKpVKG5e+iq1yjpO5uTntuLMveAEmJzra2dnRxjhaSI96rn95Klbm1ZvklPKqh155SgWiVqBP19FRmavwVQk9I6VqmZ7nfsknppdyOEt4qkM7qA/SYfWBdiZ/lcNvRSM9enD1ope88cSGHn1ndiwloCOrRx3QSFD/anpPz2BFNdZh0j4eJfREn9iFdQG61nj9xGXuBZhUmL6/3I+eWNK+6288t+obwVdWVtyttX2rnIRJdcnxMW7FqmCqZjo0OtAbGxv//ve///Wvf2kb1OGn+5C3t+J0gRQKBRWIPnFhYcE13EFgJycnTrISOaL0N2+/71wF61wyf/75p+q59lqfpVqt3VxfX3d4pVe1i6xUHa0ezoigtjCeiKg4R4Jq83T0nc/pmfJ/prsG0J2+3Wdtx5G7E1Pfrq5VfZrzeThZVAyPnfGujdsTK91oWOKFINXROZeMTqkaivwroY5OvYq2IdZ0yyy91C8lH52eQ0PUdceysF5vaHd3t/DAZxMdoLd/ur+DeMnXv/76S090+vayPouLi15v1NHM6cFSF0o4vQCT9lQfHVknnV1GgzpvvwrHydu0kb87gHz+pBNZCVX48R0tnW9S5aOxsb4g6DuaPlrbGcPjzpWPY5X06Dqgkon4bJWDo+r9BdYZOlU+aib6m2duNnhd4ejMriapoVfcY6C6pI/TJvk2Dw29VD76dNWi9J0e5IcD+hqBMgAAAAAADBRnNJmennZSBK++NDQ0dHZ2pld86+r19XVM5OsPPLkei63EW71wbs/L0JizIOzt7X1LOAWCJzU92RkzAfPz8+Pj40OJwSj5+xQVo6dUHZnkzPnO3b29ve0wER8FPfqe0UKhkF4e63XlryPu+2j//vvvr1+/bm1tHRwc6COazabXanEWis3NzeXlZS97lH6fNpaGl6DyJsW0k3bQGSl837a5Hs7OzvqKvCthXH1+efVw/nxRmV9eXh4fH/tidyQ0UrFrfx1k4FAhVciZmZlXRJY49Yi2zTEx4huRnWTCDcF3vuqJHp255xVNzDvlPfLtv15/xxMbvv13bm7Oqwk4e0066OcVHOnliRy1UL9hzOLoc11i+mj9wTNrt2Xaxe8ezXfkqqsijWal7Vez9fSSisIpVZwnST96Gaaot5nkIi+vvVGB4274rwm3YvWiqsBqxekoGYcbdiIpVHBXpqqlAtFJxLN3ak3On+S24ObjJUt8Knl5+/UMWT0RCZNUydWD6Tyi4tWJQ52Vc+f4rKEXI0omZmQ7dyrRAVUJ6xBrS1znHR6nTdUx0vZ4l2MJhuc3o++aAzAwHLERfbuDINW36+ymLtfT8ObTup68pW935+bPcmYyB5E7XZbz/DlKRpukLk7DEvdyGqg4c1u/55JJn0S87JF6zlj6youx6rdOS6Y91cnUa8L+7iDQCYEc6hS5ZFzI+ji9v85NS0tLGvJ5pKTidYawdO7GTn8fidQ1DiXXp2t7VBSO3HI8rk4r6aX93jiAzHxHcOLDuJPBowt9R9OLKm3nWVQ9TH9Hi+8IHa2H3kJ/hMef2mVtjEdZKhkNPp0Y1YEyEc2m33odq0ydeXnhxBjba1H5NgN/gXLWRv3KY0Lnkvn06dPa2poKR68MRj5UADkCZQAAAAAAGDxDQ0NOd+FbZj3zvb29fXBwcHl56fl7Pd7c3Jyfn0eSef3LxMTE2NhYqVR6+cXiuMPPN/k57YRvVdzZ2Tk8PNSLIyMjXtb9S2Jzc9MXGQdymjDuGfWl1YWFBR0FvzI8PKyS8X20vmB9enq6vLzsNbAmJyf1987h8fLLr3EPtMvfyeR9Efznz596fnFx4YTh2pJPnz79+9//doBIJkqmQ/XQn+t1DbyCibbt5OREWxVxJNpybbYKQZXEqUocn/HyzdObuz6rBHyHrtesUQno41TajpLxqjqOkokgg6fS2v9y19zKms2m3tmX+P2i9k6tQNvj/PlqYvp0FYJXmNKu+RC/pPLHKj+eYNOOOPRHB1etTO+vt1JTWk3oiSPe3t6sVGG0hdrUyYTKzRVMRer1mDzj4lbslDPP7IILZ/hBX7R6333uW5wdAqXNVuHraKrkPXmjg+vj4jWYfGQdXfTC45uuvY6ZcyuOmKRoxaoD+ku9s5qJM0KpIa+trTm8rNNFqpboe6l9m7vzQrluu1vzLng5KnUs7sde0n69jJH22vFzPneozW5tbTlKJpJgqe9y8idPIaejElsbZnt33xnCVALeNUeJaWfVHCIuTZXc+Zyebw4OCfJEabQIRixA9/v2WGfHPYYXU4ucf+ridCp/S9+ursmnCXebojdUF6eO/fv37+rY9aP6Db2nAwHVpauXUzfr7HrdyZjVNeo2VewqT69r45hLxyc5WkUdowrKq1XGSOmFg0BnH/G5SW+ontk5e1TUekVdtEZf6+vrXi5HB9SjvoircDn7dN/pAo9AGUfG64TuSHq/6PxGqiQOIo8BpE6CMYB8xXc0n2RVPip2lY9HF/6a4O9ojpLRMFIDY40uVA8dSf/86azt35vi25OHHP7uoMLx6VJDAhWONtiF4/qjA+ovUPHF4bfGwB6lx8DGlcfDbBWRftTR8eqTToaq8tGjNkybx7kbGCQEygAAAAAAMAhab1L3jbO+5uhEHb4W7GuvnqE8OTmZn5+fS3j1lunpaQfN/DIvhacBPK2r9zk+Pj56cHBwoEfnHtDn+j7Ff/3rX//5z388E+BcMq0bPxgHIn0sJiYmlpeXvX5HsVjUsXAuEN8feXZ2tre3p8JfWFhQ4TucQuWv8nlJXhBf/nb5q8B1CFTyemeXv9cD0p95slklr/L/8uXL+vp6Jl15G8s/k3Jf+6uj78vc+YRf943UvllTu6BtViF48SDXQ0+WvGQ+wKFangM4TrgSuhxOT08jFYc+wqk4RIWgD0pHybykEFpbmcvWzx0xoCc6HL759e7uziE7OrKq9vMJH+Jfpn5R+Xjq7iChN1FV8aNLL1IEbW5uRmaR1+WBz+yXHlU9VAlVT1RKXrLK4UexbZ5QdI19ajYlMlppq1QT9J7uiDwF6Mde60LjyPoO+CgQh/g4VsY1NpYwUAm43roXFUccvqQJu/47UkTFGxX4MKEn/jhtm7MOONbNN3zr49IdaecKMxbOcIfvlADufPSj6qQTR2n7VQ+XlpZcyScnJ38ZROV38+yUSnIvoRLwKnUqQ1WwuIc7wtqeipJpb2WIgnU6BLXZ6YSeaJsd3qeScaicJ9d1gJ5qDk495dBV9xVuERE6xsINQHf6drVQ9+3meDWnHnHf7hRu6pTcq6tR/27f7mGJz+Duz923e6isvs6Z5/RuGhtrVKax2efPn9V5OoFNLhUo09drkqZ7UX2tUElqH7Xv7kJVSuoVHTDkbJT6rUdKLvBfhh56NOIgJBWyB0geKTn7iJfadHi0TiU6oUQmy/SyVhE41enTSvrNVeucpyT3kJjNuescRaTnLhztTnoA6XPQS0LJ/Q4qZ59kPZL00MJfGURF5O9oOsNqXOFIen1niXCi7n97cly1G6kHtHG89Cvn83NolL9AOZ+iK4y/OLykhfoLrL84eKwV4y4XlJd80jlam+FEOyqcSMb5u6u1AuhxBMoAAAAAAB6XzhnumU7f9NbLl4Rim+sPemeb09s2NDQUG9bR2c1KpeI0HpHefHR01CEsXvfHKcpnZmYWFhaWlpaWl5cj9cWjiwF5gyNP9dXVlXMqxBzn4eFhhCb4ynjciucrsPoUb1W6ZPq0gaSPqRO/N1PiKKgEHCVTeuCE3iq6m5sbPZmampqfn19cXNTh8FRrXAd3RvrW8heVv+fXPc0c0wP60XmD9F863Hqfubm59fX1//znPw4Q0Y/ptVo6Uf7pCRJtw+zsrKNkXJ1UFHpR9cST656a8v2jrofn5+dxk6ijizKpF6LkvYhVpDLS7u/u7urRc+163YdAb6U39ExArG7wW3flPkV75Jmt2EIfa+2XDoE2yYEyKgEd2dXVVbUFPfFN6joK6eT/udQyNNovFYvnfrYTblw63HrdUTIqK+2IF9LSe6oA25giKGIj9M7aBQe9udPQtt098CoVquFefcb/69ABHxenzdfWeuWadMPv2XbdOp8aYV4qYVUwBxqqWHQ4dFy0a9GFil6M46u/d5BcLjVNG7XX8UZxK7Pn+cTzWO5FvciXOlKHeakVO0rGUSNdu6fZ+QDc52v3ddC1F2pl3n4/niS8+lhUcpWhyi2d6MU13JElvnteZagarjORziNqyD536H9VmL6H2w3WcWCNf3KQihM4xRm/vdVM76a98FH2DK7XMXSOJTcE3/3vR0cIxaFxTKr5TKFaoWP3wmjI7g9vBu+D3r5tHRqwZT4ll+TG6HJRv3tpZ75rdLS+ReBja98u6b5dHVqmb9e5O9O3x0k/HXLhdGuirlI9pDpzva3TK7pXd3/lHB56T0fJqKNznj9HMEfoxsDMwTtk30nRVLY+u+WSmGn1mc5rouJSma8kVDL6sziJeJiUjm6J/t/DPy+EJyptf8dxeLSOncZI//Vf/6XziEtYb+V+OP11JpckF4mTSHoY0KHvDnFi1T7GskEuJe2Capq2JAaQqoQxgIwsR9o7n2j8j+kBhnfKIzR/R1PBunBU1Courw2qv9H7uB56bBxJd9KZk7pZCb3xqvle8dCtLNqpflRpePFWt1Yddz1ZeuAvDk99gc09ZPTxsCGdA9XfnlQ4ek9/gdL/6lTuKBkVi8rHIUREyQADiUAZAAAAAMDjfLnKc6LOC+Ip0lhHvGc3OJZ0KZVKPbLBMf/tbRsaGvI1yk5vm46aE0R74RsVyOTk5Pb29v7+/tHRke/Mi/tcnc8gVsDRH0dkw6OBMp7Ljylez/LqTVTy+huHyMzPzy8tLa2trW0kPJ3f+5Plr2ggXnzE19nTgTK5h1gZX+d1uIyK9+fPn76a78uycdtxpFj3NeK4TJwpf8+yO5OK/9dT7E7+4dAEHUfP7K6srKyvr3/+/Hl1dVXHV4emmwXlVaimpqaiNLymjy9MO2DIK9poRzzXrhedkUKb+nygjLPKR1ojZ15xQImn2/UmTtjjQnDylfYWgle2ip3V1urw7ezsaI+0Sb55+jThnDfaQscAOUv8U4EyTjgUF/E9vaFfOf5MTUn7Egtp+fbfNk7teLmZ2dlZV1Hxgjsu2Ah00CZpdzyVFasYRKCMbxn3Ld3qB0YTfdTGM/Opjm9QjXJH59U00gkDXHXj+Hqq5plAGfceLlUf60iD5EgU5/x3VgMdZXWhnz59UgXOJEPKdX62xkWh/dJx1DZ7Hku1121NGx/Li7hMtBf6Y7ffZwJlfAJyfJvfSsUS4ZWq4are2mV1YtHE3Lu6jUTwltdc8xDFs8vtnebUEfTCbdp9H3oH+TnOz6d1J5DQvnh5puivnG7HE5PaKlchvZWK5eW37GfqjN7NS1D5dNPelGDpsYo+KAZ+ffpBb982a/tgMs7mcUxVJfSkE8c080GqnN0Zgv5uxfbwuAvj9qf6dp1q3cA9stURcYCLByfu29VBOWXFU4EyrjZeCtOBgB7qeGzmeBH1ADEB71BXRydELzdI6y6ly9x9u2NTHCCi8lHZ+tuE05VFmrE4iTwVKON4cScFcRYZ/aNruJO1eKVCFbJDHOLbR0S6u+L564x7aXdBHQ1CjTWGcg+R3JHcyCd9h7x76OXS8Jqeqk5OuOgBhk80rYEysV8+yXpsrJOsQ1F1PnLKFoenq2Q8tNA3NdfD30212PYOIVJAqbGopfhwOM2h9l0VxgfaAfHx7VV1wEllPCL9ZaBM5ON0zXFL1+u5JFWkvz2pcNYTKhwn2vmt8FYA/YKGDQAAAADAQMkkmc8lazDNz897/n52dnZmZsZrz3sJ9ru7uwg4OD091YsxxRsXGTN3Fvo6cnqy8yLh+xT1x3qHhYWFtbU1X2FcWVlZXFycm5sbjFwyr+A1mDwfUy6XHcLy8+dPL6PjqWWv5bG7u+soJd9E2xqolEtNFbv8Y4LB09U6Op6NWFpaSl/h1SHwrENrbelCPXTMSi7J0uF5YnFOBRWC7zD29WvfWKxfxSx768XudDofzwd4FRiXg2/GVVGrvjk+xlXRWf3bUgiPtrIIR9NHaB+3trb0ozbS0QO+wff8/Fz761wy3rvnMwY5M7yTl+jfHb+iHfHtv7EEj15MzwC95ah5Yzxho+4i4uGcAMkTDNoe58k4PDxUdXXWkHSgjLc/7srVEy+7kEut7pR7WF2iB7vQ9JHVYfIEm7OAqEzUcp3j5+DgQMXiTCHuQnWw1IVqZ2OexrNfuX8GyrTGPTjQxAFJDrzzVM3q6upawqsaqV/VxnQnSqZ1QS4vNBbzyp6li2kn7buzKeiJyifdftO7H9kjHA3m3s+zd/pEnzs8b+eoIP3orqN189LRsea5/070YI4TUkfq+VRtrVcf04+5h7Qxbg6OMU1P6Hr+NZdMv6n+qFNy75Suab3ZFj64zmWVQA/27V5ET927hmFq0e6K3Vk5blV9e5y7I0Ah989AGXEsaQRB+vTtsFFHJ6gndzY4PaqLU6fq0+gznXBffx+JIlKJ6byg/XWGS/eTPoP464NL219GHC+eHl2kA2ViGOxydsS5E9X4sHq5HBeyCjwd4uD38TbEWpA+lXTn5op0oIyLRbUil6xV6q9pPxOqb5kBpEpJldMDjAhCfXSAEbsTORe9opNqst5T7+DTmU6ym5ubGmCouCKZaE9VIcfKeESqbVbh6FBq+/WKvil40OWVzvR91l8cXDitX2Bz/wyy9+nblcdDL4cQRQI/ja7dQl1/NA4hlwwwqAiUAQAAAAA8zssNOPeD84RHgoeuLffwW3zDmbawUqn4ljhnYHbAwbtvm/NIe9uGhoa8tk56vZL2yswHeAkblYY+3bP4+nQVkYrLKSK0hTc3NzrQx8fHce9m7omJIl8fTKcu95VHp0vxXKCzd8Q0gPZXvxqkKBmvsOPkBzMzM9odR2BkFtMJekW/9XVwh4n4gq8T/Jyfn+so6NHrEOWenaKL8s89BM14psFBCZ6CdZTMp0+fdAh8BVx1ILM0T5cPgW+c9f2yjtZyK1DFODo60o77EraXTMoEx/yyHnpuw49OxqM3d9oVUVEsLy97GiDmsN9eCJlW5uPrHdSnO2eM6ICqcXmyrV6vn5ycpC/ft+5a7Jfngdy+3LIc9KY9+s9//uMUQT6ybYmSyXBd1QY4UEaPvhveIU3OTq8Dl7mhOWaA/Khtc3CS05D0S+t+dD7VuaBU4Gq2Or56riPuqutVJJxcxGXyfBeaqb3Rih3l5gXanL7Fubgc5uXm0/1WnL733St8iU9eXtpP2+wZStWWs7MzlUN6juqpGh7dlwpNj67e6SgZdVzqJFXImXu4Hamjv9chcI+XyWnUiYUznMlJrc+Zw5z5Q5+oHdfHef2pg4OD1vv73Yr16EXo9ETbrHf4rYwRHkJ4BShVP73itczSQTlt4QRgeluPVfTcGebS09WdGBQ5BVp80PtGqMS2ubQd3BmZLdpY1DHM1qeoXjn5XGQrafsHeXectKnTQ9Dfqm/xXcMplzo6bn+mb59OuGN33+5Ttv5FzVwNXKfyTOt+amQSHbtjKL1Eo4cl7uK+fPmiLk69uhfRy3RxgzcHH8XuQohAfL3u/lydpwrZxeWTSGtf+tR4Kda0dS+tInUIiCOJnZAsc96MAbyOvg66YzT99bY7hZ/5FKf/zIwxtHkxPHb8kL6gqXDSJ9bnx8a5VGC9FBMqCr1/pNtRbfRyTq2N7r3qYeZztWEe6HotpFhcSd+eTk9PnYbKC32+ZPQVb55e9M0naC9Wq4/Q0Nqrmqr+aATrYQa5ZIABRvMGAAAAADzCaZl9tej+/n5ubm5oaMgXHyuVSm9eLdJWTUxMLC4uVqvV8fFxP3qViphCexe+euspwOvra22kXvFyMCrMzgUepW/l9AH1RcAIZ/Ele+eZd1YDcx5yz9DHvZVxmTvuxfQUqd7Nb+vJ3VhxaTWxtLTkKJmoM4MxAeAr+07trmPq3ABeHsXZeh6d41G5+Tq14ydUVr4mrn90CnEdCB+CWEYkVhJJl5vnD9Ll7/uh/c6e7/FiQ+bJ5qeqR0dl7if2Ciaufq6HnqjwukLea2drcMKG9FJWUQhRD10OXgLG7+ZkSDHZoN7A9VBP9KM+K5Obpy07mL4t2HlE4tGb4cV0dHAdSOFDHPcuZ1bZ8H75XudoXA7Acll5mm1zc1O9sZfg6dCEoqcwtQtqws5x4sUpvFqWV2LSUfNSBRGdECtZOJRBj54Ja00L1ONaUyL5KLiC+eZmtVwvGKSicKChl+BJd6HpqptO2JNuxU7QEk0jegYvi6Am7BuaVR+634QzfC6Lo6lNUu+nenhycuJyiGwrrt4ugcy+u3p7r90JeA5M76P9dRIdV2+VRus2OOjTEWN6rk/0ch6ef+3Q+TR2Vp2JeyRPfnsRQ+2vQ8cyCQnidn/9rzbSeadcAi7Dlw8hvBTa+vq6XtFnqWRiFbl2RZa4ycf99PpQHUrtoz7UJ5FHY0DfMijyQVQdUNHpg1TVM/mx3mXA5tArbYl23EtcpStYuzoxJzLxMFt1RiWsV5w1qjWgs40fpAqsfky7ow9yAME7dsseEmjf1eT1XKdItRRtoU9tHR0bt/bt5igx1Uw1bYftemQSfbtjDmJYkq45bu/OleIxgE/cjpp1RJTe2auRejGglySSibCbCMHp6/Gz237sl6NCY0FDxyT5m0gkCUsvx5M5icSBc/SqR79eMUflrNJOD/wyHZ3+8tOnT9oAD+B9xnmvb7g+KaS/T3kYoJLx8DjGGOmvaY+u0hVjY39HcPo3R/tF8iS1ski1qF/1wujiGTFMCk7v5/OvG2Yscdi6DG5UnvQXB1cef29yETmC0FnfPAhxDj8SyQADj0AZAAAAAMD/yVz6cfaLxcXFQqEwOzt7c3PjV7xkzOjoaC8sE5C5Qu17zvS8Uql4ARrfKqrtHx8f79ptgo+Wp7dkfX1dZahtc6IF373qyYCubZtvavcctj59bW3tNOG83F7r3SvXPJqHPD2L70uNnrx3chSnCfGTubk5p6rW4UjPdvTvAhOP1rdms6lDeXl5mUsSinhlK8/zZWJE0nxDZ0wRLS8vu+SPjo5OEnoSCfwjnCKXilLyfLDfwXfkTyXSh8AVzFkonq+fXeaFqNwutPGqKt59OT8/dwnoiUvA9TDmA+IdIlTLMwEuBNfD2P1I2+Pb9DtXMdKH2Fn0Pa2uz1UvqqN5/ED7qL3LPaxf5nmg9CSQG5criTMZeP7Gu+M98jxi6xpSbaznsUfqoPShrvAODdnZ2dlPOGLGGezdS3gGwkfEByW6AqfbyeTy6buVTXR0vFSH9k47pZbrzlPVNd2Lqlh8cNPBIlF7owv1ug96VB/iso1mq+M+9U+ZG+K73/ulD5ZqhWpgLFKgcjg8PFQ916Nj/pzjyt2Xa3h6371mRDRb7fV8wvGjs4mnVpiKKF79qE/XKcwLmrimRYxFGyPhcqnZWXcjPmru8L0Il3tsN+doDtFXe6oydla7FtkLXnjGcVmtrKzoiYpIH6G3dZ1xpopXn1gz5zUHgPqD9Oh1TLTZXjnRk6lv/6DcQ+SQB0UbGxs+iE425sjaLp+k0icXD9hyyVJZKgRtm8dLHv2+ZcCW/kc3fB1NVRJVJKfQcIiG4yfa8kERZaWzhp446tGpoXxaeeMHvXHzHG22tLSkzXDFjm3z6ipd27Do2+MmAfXkXvfQJ2738JGcozUOMk5/fuL6nB4PR2ceXdzv9up9PUnfmufSYwaH7Ovc4aGvh8Eq7RgDu1+NYNwIj3asg+qPh74+d6ioVcld5k5D8mgBupq5o/MNIQ68cMhI91tEuhP2ADLyD6lAXA9dA/0kRo+ZQKI4yTpnT3xHcxHJZMLDDI8te/bul0cbqTbejdTLy8Z3h/gCq+GHl4DMfHuKL7CuNq5CjtCNkolG6srjsnr3lLQAuoBAGQAAAADAIzwh5DzwzmmRSy5RecrnfWfsnuLgA88H+KJqesr2fTPK+Irn6Ojo/Px8o9HIPeT9jvTj3dwez3t5ku/q6uri4sIzAZ7m9EVqrwEUN3RmAmV8hdH3O/qS4kLCl6dVZ/S6k0m03t8/MBllnDZGu+n6lj6mPqzpXW4NCPBlepWh89A4OYfKf/+B72Z2lgLPteceAmXi3krPr/t6t6cH9Oi05F4n4tHW2iOHwFvoeUHtvnbWoSSHCWeY14u+iTYy60Q9dJyBbwb1BW69j46F6qEnpSJxvSdUOrovrYfYcSEOlHET0wHVYT04OPDe6UUdXK/sELFo6f3ywfWNv87M5P3SwfVCMx09suk98rnA6WRiIsGbEfmoIlAm1vhwiI+2fHV11bfOa6cyGX16vzdoPbIOc/Tp5vb2VlVXJeBJGk/yOYGQF6tKJ1ZJz2N5qsaxUBEl42QS7kVde32U7d1bcWusjLbZk4uOBtOO7+3tOYLKFcO3d8cQIpdaQkj/6CA57bL+XTVEOx4xba0dVyaOwX+mf/EaRl54MU6pbQ/ASqfDcXOIfFE+5WlftPuRFstnhFjGyInWtJvq6jc2NryUQybx2DMHNOJXnBfENSo9vGljohcnkdJ7ar984GLg566pXR8UgyLVgfSArfUE2v0Bm4tUB1rb5gqWHv22MdFLnASd68UDA7f6NmaU8WS5C3xtbc2Vx2eZ9n7Q6wrBQWOu2G5okSWuo2Pj1r5dH+fKH327O3aftWNYEvnD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

* Example: https://sunypoly-cramerj4.updog.co/dynamicphotoalbum.html

* See http://designwritestudio.updog.co/skunkworks/startingoverutica/startingover-photowiki.html

* Goto https://nyenr.elections.ny.gov/ and scrape county-level results for three House district primary elections 20180626
** CD 11
** CD 14
** CD 19
** Scrape full district by county results into a worksheet; should be able to do one well-executed copy/paste. There is a structure in there of cells that you can grab onto to select.
* For each, we need results by county.
** One possible method: treat the sheet as a county-level object, and move the county-level results into a new sheet, named for the county, with an identical structure in each sheet
** It's a lot of copy paste, but if you get a clipboard buffer, you can copy each county from a single sheet, and then paste each county into a new sheet by navigating your clipboard buffer. Mine has copies of my last 99 copies, and they are in order. 
* You could also treat the entire worksheet as a set of tiddlers. Add a column that has county name, and for each row, copy/paste the column. You should be able to copy a county's-worth of formulas to get the county name at a time (so build formulas to get county name from some other cell, and do so for each row of results. Really, the only thing we need for each row is election,district, county, candidate, votes-received; you can discard empty rows on import)
* Then, you import and build structure that reports the total votes for each county by candidate, and each candidate by county. 
* And, using Justin's county-level map project, integrate so that on roll-over, it displays vote totals for each county.

Elise Springer is a Philosophy professor at Wesleyan University (USA) and a long-time builder of teaching environments using ~TiddlyWiki.

```
Think about the technique of linking while writing in Word, or GMail. Copy the destination link, highlight the word to be linked, click ``Insert Hyperlink`` and paste the destination link. Or, more commonly, copy / paste the link as raw text, and hope for the best.
```

```
In ~WikiText, enclose a word or phrase in double brackets and [[it becomes a link]].
```
Enclose a word or phrase in double brackets and [[it becomes a link]].

<$list filter="[is[current]field:toc-type[heading]]">
<$macrocall $name="essay-nav-first" essay=<<currentTiddler>>/><br>

<$list filter="[list<currentTiddler>]">
<$set name="paragraph" value=<<currentTiddler>> >
<!--generate an annotate button-->
<$macrocall $name="newhere-annotate" from-tiddler=<<paragraph>>/>
<$link><<currentTiddler>></$link>
<$transclude/>
<!--show the annotation-->
<$macrocall $name="show-annotation" of-tiddler=<<paragraph>>/>
<hr>

Individuals writing essays produce text organized in patterns. 

> For the writer, a well organized outline of information serves as a blue print for action. It provides focus and direction as the writer composes the document, which helps to ensure that the stated purpose is fulfilled. 

> For the reader, clear organization greatly enhances the ease with which one can understand and remember the information being presented

There are a variety of [[patterns of organization|http://faculty.washington.edu/ezent/impo.htm]]. 

* Chronological Patterns
* Sequential Patterns
* Spatial Patterns
* Compare-Contrast Patterns
* Advantages- Disadvantages Patterns
* Cause-Effect Patterns
* Problem-Solution Patterns
* Topical Patterns

Individuals writing essays produce text organized in patterns. 

> For the writer, a well organized outline of information serves as a blue print for action. It provides focus and direction as the writer composes the document, which helps to ensure that the stated purpose is fulfilled. 

> For the reader, clear organization greatly enhances the ease with which one can understand and remember the information being presented

There are a variety of [[patterns of organization|http://faculty.washington.edu/ezent/impo.htm]]. 

* Chronological Patterns
* Sequential Patterns
* Spatial Patterns
* Compare-Contrast Patterns
* Advantages- Disadvantages Patterns
* Cause-Effect Patterns
* Problem-Solution Patterns
* Topical Patterns

This is an outline for an "essay" on Applied Hypertext.

# What is Hypertext?
# Practices and techniques of hypertext
## [[Hypertextual Practices]]
## [[Techniques for Hypertextual Writing in TiddlyWiki]]
# Examples of hypertext in the wild
## Google News
## Wikipedia
## Google Scholar
##* (Tag each example to one of the [[Hypertextual Practices]] and one of the [[Techniques for Hypertextual Writing in TiddlyWiki]])
# Identify and annotate examples of applied hypertext in exercises using ``comments`` or ShowNotesMacro
<hr>
//Aside:// ``wouldn't it be nice if there were a macro that took an outline as above and excised it into separate tiddlers? try copy/paste the outline above into a new tiddler at `` [[text slicer edition|https://tiddlywiki.com/editions/text-slicer/]] `` and then click the slice button. This is significant text processing that we can apply to virtually any document ``

{{$:/core/images/excise}}

//Excise// is a technique used while writing in TiddlyWiki. This technique, enacted while editing a tiddler, cuts the selected text from the tiddler being edited, and pastes it into the text field of a new tiddler. The process of using this technique includes establishing the title of the tiddler to hold the selected text, and modifying the tiddler being edited to reference the new tiddler.

By default, the text field of the new tiddler is transcluded into the tiddler being edited.

The new tiddler can also be referenced withhin a macro for other effects.

The //excise// button is likely on the Editor Toolbar, visible while editing a tiddler. The toolbar can be modified on the  <$button>
<$action-setfield $tiddler="$:/state/tab-1749438307" 
text="$:/core/ui/ControlPanel/Toolbars/ViewToolbar"
/>
<$action-navigate $to="$:/core/ui/ControlPanel/Toolbars/EditorToolbar"/>
editor toolbar panel</$button>, which is accessible on the [[Control Panel|$:/ControlPanel]] {{$:/core/ui/Buttons/control-panel}} Appearance / Toolbars / Editor Toolbar tab

* Complete the steps outlined in [[Workshop: Saving, Serving, New Tiddlers]] (watch the video)
* Respond to the welcome message in the [[Google Group|https://groups.google.com/forum/#!topic/designwrite/PzoHJwkHVh4]] by introducing yourself
* Share your wiki on the submission form
** <a href={{!!form}} target="_blank">Visit form in another tab</a>
** <$appear show="View embedded form >>" hide="<< Hide Form">{{!!form-embed}}</$appear><br>
* We will <a href={{!!responses}} target="_blank">Review responses</a> Thursday morning

* Complete the steps outlined in [[Workshop: Saving, Serving, New Tiddlers]] (watch the video)
* Respond to the welcome message in the [[Google Group|https://groups.google.com/forum/#!topic/designwrite/PzoHJwkHVh4]] by introducing yourself
* Share your wiki on the submission form
** <a href={{!!form}} target="_blank">Visit form in another tab</a>
** <$appear show="View embedded form >>" hide="<< Hide Form">{{!!form-embed}}</$appear><br>
* We will <a href={{!!responses}} target="_blank">Review responses</a> Thursday morning

In-class review of submissions: <$macrocall $name="youtube-embed" video={{!!youtube}}/><br>

Core concepts: with links to relevant [[TiddlyWiki.com|http://tiddlywiki.com]] pages

* [[Creating and editing tiddlers|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]]
* [[Tagging|https://tiddlywiki.com/#Tagging:Tagging%20TagTiddlers%20%5B%5BOrder%20of%20Tagged%20Tiddlers%5D%5D]]
* [[Linking|https://tiddlywiki.com/#Using%20links%20to%20navigate%20between%20tiddlers]]
* [[list-links Macro|https://tiddlywiki.com/#list-links%20Macro]]

Assignment:

!!! Create a new TiddlyWiki5 wiki
* Easiest method: [[TiddlyWiki5 on TiddlySpot|http://tiddlywiki5.tiddlyspot.com/]] ([[Demo|Workshop: Saving, Serving, New Tiddlers]])
* Alternative <$appear> 
*  [[Mac OS X Chrome Workflow: Saving using saveTiddlers]]
* [[Mac OS X Chrome Workflow: Saving using TiddlyDrive]]
*  [[Mac OS X Workflow: Serving via ftp.sunyit.edu]]
</$appear><br>

!!! Set the default tiddler to`` [[About Me]]``

!!! Edit the [[About Me]] me tiddler and write a story about yourself

* Start with your own words, or copy my story from [[About Me]] and change some words to reflect your life.
* The story should discuss a few different aspects of your life. Think about different ''dimensions'' of your life, and ''characteristics'' of the ''elements'' in those dimensions. 
* Write your story as a narrative in a tiddler. As you are writing your story, enclose words that represent either dimensions or characteristics in double square brackets, like this: ``[[Words in double square brackets]]``. Be sure to consider both nouns and verbs as dimensions and objects. 
* For example, in my [[About Me]] story, I mentioned these <<stretch "dimensions" "(and characteristics)">>: <<stretch "Occupations" "(College Professor, Adjunct Faculty Member, Research Analyst)">>, <<stretch "Cars I have owned" "(Red Honda Fit, Blue Dodge Dakota, Blue Subaru Forester, Grey Subaru Forester)">>, <<stretch "Digital activities in which I engage" "(surfing the Web, tweeting, listening to podcasts, listening to music, texting)">> and <<stretch "Digital devices that I own" "Apple iPhone SE, Google Home, Apple MacBook Air)">>. In addition, I also referenced working, driving and relaxing.
!! Flesh out your story in other tiddlers
* Click on the links that you've created in your tiddler. Tag tiddlers as appropriate. Tag characteristics with dimensions. For example, in my story, I would tag the //College Professor// tiddler with //Occupations//.  Make up other tags.
* Write brief descriptions of each dimension and characteristic.
!! Do the [[About Me in Tags]] approach
* Create another tiddler, [[About Me in Tags]], and tell it using tags (don't worry about the grammar being awkward...).
* On each of the the //tag tiddlers//, use the ``<<list-links>>`` macro to generate a list of links matching the tag.
!! Share your wiki
{{Google form to share links}}

//Note change in due date//

Core concepts: with links to relevant [[TiddlyWiki.com|http://tiddlywiki.com]] pages

# [[Introduction to Lists|https://tiddlywiki.com/#Introduction%20to%20Lists:%5B%5BIntroduction%20to%20Lists%5D%5D]]
# [[Dragging and dropping across wikis and within wikis|https://tiddlywiki.com/#Drag%20and%20Drop:%5B%5BDrag%20and%20Drop%5D%5D]]
# [[Transclusion|https://tiddlywiki.com/#Transclusion:Transclusion%20%5B%5BTransclusion%20Basic%20Usage%5D%5D]]

# [[Using SVG|https://tiddlywiki.com/#Using%20SVG]]
# See also [[Basic Shapes]] 

Assignment:

# Create a new TiddlyWiki5 wiki ``-shapes``
#* Easiest method: [[TiddlyWiki5 on TiddlySpot|http://tiddlywiki5.tiddlyspot.com/]] ([[Demo|Workshop: Saving, Serving, New Tiddlers]])
#* Alternative <$appear> 
*  [[Mac OS X Chrome Workflow: Saving using saveTiddlers]]
* [[Mac OS X Chrome Workflow: Saving using TiddlyDrive]]
*  [[Mac OS X Workflow: Serving via ftp.sunyit.edu]]
</$appear><br>
# Drag these tiddlers to your new wiki
#* [[Medium Blue Circle]]
#* [[Medium Blue Square]]
# In your wiki, clone [[Medium Blue Square]] 4 times naming the clones as follows:
#* [[Large Red Square]]
#* [[Large Green Square]]
#* [[Small Red Square]]
#* [[Small Green Square]]
# In your wiki, clone [[Medium Blue Circe]] 4 times naming the clones as follows:
#* [[Large Red Circle]]
#* [[Large Green Circle]]
#* [[Small Red Circle]]
#* [[Small Green Circle]]
# In each of the eight cloned tiddlers
## Modify the code in the text field adjust the size and fill (color) to match the title.
##* For large squares, set ``width="100"`` and ``height="100"``
##* For small squares, set ``width="20"`` and ``height="20"``
##* For large circles, set ``r="50"``
##* For small circles, set ``r="10"``
## Tag tiddlers with appropriate tags:
##* <<tag Red>> or <<tag Green>>
##* <<tag Small>> or <<tag Large>>
##* <<tag Square>> or <<tag Circle>>
# For each of your six tag tiddlers ( <<tag Red>><<tag Green>><<tag Small>><<tag Large>><<tag Square>><<tag Circle>>)
## Tag as appropriate as ``Shape``, ``Color`` or ``Size``
## Paste the following code in the text field, adjusting as appropriate:<br>``<$list filter="[tag[Red]]">``<br>``{{!!text}}``<br>``</$list>``
# Drag the [[About My Shapes]] tiddler
## Review the narrative to be sure it reflects what you've done.
## Add to the narrative using ``<<tag>>`` macro, including referencing ``<<tag Size>>`` and ``<<tag Color>>``
## Transclude several tiddlers using this code: ``{{Circle}} {{Square}}``
# Optional: Add a third color, a third size, and/or a third shape to your wiki. See [[Basic Shapes]] for more information. Adjust as needed.
# Share your wiki {{Share}}

Review in Class:<br><<list-links "[tag[ReviewInClass]]">>

! Objectives
* Present a narrative story in multiple sequences selectable by readers.
* Develop skills creating tiddlers with fields, and using a template tiddler.
* Expand skills using the ``<$list>`` widget, importing tiddlers and using macros.
! Resources
! Directions

# Get a story
##  Conceptualize, copy or identify a narrative story that references a set of objects easily described in multiple dimensions. The story should be about 500-1000 words.
## See my example --  [[Dogs in My Life -- Narrative]]. Your could be about your pets, your family member, games you play, places you've lived, courses you've taken, people you've known, etc. You can write one yourself, find one that someone else has written (a magazine article, for example), or use one that you wrote for another class.
# Put your story in a TiddlyWiki and identify object tiddlers
##  Create a new [[TiddlyWiki5 on TiddlySpot|http://tiddlywiki5.tiddlyspot.com/]] Append ``-objects`` to the your standard name.
## Copy your narrative into a tiddler. 
## Clone your narrative into a new tiddler, and use ``[[ ]]`` to identify objects in your narrative (See my [[Dogs in My Life -- Objects]]. You should have at least five objects in your narrative.
# Create Your First Object Tiddler
## Create a tiddler with the name of the first object you've identified in your narrative.
## <<y "Tag your new tiddler with the type of object you are creating. In my case, it was "Dog". In your case, it is likely something else">> 
## Copy the sentences from your narrative that describe your object into the tiddler.
## Create fields
### Identify at least three characteristics that can be used to describe each of your object. In my example, I'd describe each dog with its breed, its owner, and its size. Create tiddlers with these tags (in my case, ``Breed``, ``Owner``, ``Size``. I might expand to include each dog's ``Longevity`` (how many years it lived), and my ``Feelings`` (how much I liked (or didn't like) each dog). 
### Create a field for each of these characteristics, and describe your object in terms of these fields. You should have at least three fields to describe objects. In my case, I'd create fields called ``Breed``, ``Owner``, ``Size``, ``Longevity`` and ``Feelings``. Put appropriate values for each field in the tiddler.
# Clone object tiddler (repeat this step for each object)
## Rename it with the name of the next object.
## <<y "Tag the tiddler with  the type of object you are creating (i.e. 'Dog' 'Trip' etc)">>
## Copy sentences from your narrative into the text field.
## Put appropriate values in each of the other fields.
# Write a template
## Copy [[Exercise 2.02 Template]] to your tiddlywiki.
## Adjust the first filter to match your objects.
## Adjust subsequent lines to capture fields you created to describe your objects.
# Write two or more generated stories
## Copy these tiddlers to your tiddlywiki:<ul><$list filter="[prefix[Exercise 2.02 Generated]]"><li><$link><<currentTiddler>></$link></li></$list></ul>
## Modify at least two of them, or create your own, to generate a story based on your objects
# Create a tiddler called [[Exercise 2.02 - Reflection]]. Write some notes about your process. What are some of the advantages of generating stories with fields? What are some of the disadvantages? 
# Share {{Share}} your tiddlywiki.

I have had <$count filter="[tag[Dog]]"/> dogs in my life. Some I liked. Others, I didn't.

<$list filter="[tag[Dog]sort[feelings]]">
I {{!!feelings}} {{!!title}}.<br>
</$list>

I have had many dogs in my life.

<$list filter="[tag[Dog]nsort[longevity]]">
<$link>{{!!title}}</$link> {{!!status}}
 {{!!longevity}} years old. 
 {{!!text}}<br><br>
</$list>

I have had many dogs in my life. They have been owned by different people

<$list filter="[tag[Dog]each[owner]]">
<h2>''{{!!owner}}'' owned <$count filter="[tag[Dog]owner{!!owner}]"/> of the dogs in my life</h2>
<$list filter="[tag[Dog]owner{!!owner}nsort[longevity]]">
<$link>{{!!title}}</$link> ({{!!longevity}} years):
 {{!!text}}<br><br>
</$list>
</$list>

<$list filter="[is[current]tag[Dog]]">
<hr>
Fields: {{!!title}} was a {{!!size}} {{!!breed}} owned by {{!!owner}}. {{!!title}} lived for {{!!longevity}} years. I {{!!feelings}} {{!!title}}.<hr>
^^[[Exercise 2.02 Template]]^^
</$list>

<span class="bigbold">Objectives</span>
<$appear show="Show" hide="Hide" state="objectives">

* Engage in the practices of 
** tagging, by associating objects with other objects
** transcluding, by displaying parts of objects
** templating, by displaying objects in structured patterns
** listing, by generating sets of objects
** linking, by affording navigation among associated objects
</$appear>

<span class="bigbold">Preliminary reviews of Student Work</span> 
<$appear show="Show" hide="Hide" state="reviews">
<$macrocall $name="youtube-embed" video="uRBkNUkVBn8"/>
<$macrocall $name="youtube-embed" video="xVqy4N4X9U0"/>
</$appear>

# Create a new wiki, or build onto an existing wiki.
# Select a panel (tiddler?) from [[today's google news frontpage|https://news.google.com/news/?ned=us&gl=US&hl=en]]. Make sure the panel is on expanded mode (there should be a button in the lower right that says "Collaps Story"). 
# Make a screenshot using your favorite screenshot software -- it has to allow you to draw on your screenshots. (I like [[Jing|https://www.techsmith.com/jing-tool.html]]).
# For each and every link from the Google News expanded story panel, including links to news stories, full coverage, collapse story, tags (?) and photos -- create a new tiddler
#* Title these tiddlers with a name representing its content or its function. 
#* Tag these tiddlers with its type (i.e. "news story" "google news navigation" 
#* For tiddlers that are news stories
#** copy the first 5 or 6 paragraphs into the text field of the tiddler
#** copy the first sentences into the ``lede`` field 
#** Add three or four additional fields to these tiddlers to characterize them properly -- such as news-source, time-of-story, date-of-story, story-teaser ("Highly Cited!"), etc.
# For each of the "more about" tags, add two additional associated tiddlers, with fields as described above for news stories (be sure to represent the "more about" as either a tag or a field).
# Illustrate your screenshot by drawing boxes around different blocks of text that could be engineered as links to these tiddlers. Use color to differentiate links to different types of tiddlers.
# Import your screenshot into your assignment wiki.
# Build a tiddler that resembles the Google News expanded story panel. Use each of the [[techniques|Techniques for Hypertextual Writing in TiddlyWiki]] to accomplish a goal:
#* [[Writing Links]]: to afford navigation to news stories.
#* [[Creating Transclusions]]: to render the lede and source of each story.
#* [[Generating Lists]] and [[Tagging Objects]] to determine which stories should be listed.
#* [[Using templates]] to create a standard view of each story.
# Describe your work in a journal tiddler.
# Share {{Share}} your wiki.

<span class="bigbold">New Concepts</span>
<$appear show="Show" hide="Hide" state="concepts">
<p>
[[New Here]]{{$:/core/images/new-here-button}}<$appear state="$:/newhere">{{New Here}}</$appear></p>
<p>
[[Excise]] {{$:/core/images/excise}}<$appear state="$:/excise">{{Excise}}</$appear>
</p>
<p>
[[Table of contents|https://tiddlywiki.com/#Table-of-Contents%20Macros]]
</p>
<p>
[[Journal|https://tiddlywiki.com/#Creating%20journal%20tiddlers]] {{$:/core/images/new-journal-button}}
</p>

</$appear>




<span class="bigbold">Directions</span>
<$appear show="Show" hide="Hide" state="directions">

# Select a Wikipedia article that is interesting to you.
# Create a new tiddlywiki file (or add to your existing tiddlywiki file). Using the [[journal|https://tiddlywiki.com/#Creating%20journal%20tiddlers]] feature, begin to document and organize your work on this exercise.
# Describe ways in which each of the hypertextual practices (<$list filter="[tag[Practices]]" template="$:/core/ui/LinkTemplate"/>) are used in the Wikipedia article (including noting if the practice is not present).
# Ingest the text of the article into your TiddlyWiki, and use the excise tool {{$:/core/images/excise}} 
## to slice the text of the article into separate tiddlers, and 
## to transclude the new tiddlers into the main article tiddler.
# Use tagging to structure a [[table of contents|https://tiddlywiki.com/#Table-of-Contents%20Macros]] to guide navigation in your article.
# Use the new here {{$:/core/ui/Buttons/new-here}} feature to annotate and extend several paragraphs of the Wikipedia article.
# Create a journal entry describing
## the ways in which you used the different <<tag "Techniques for Hypertextual Writing in TiddlyWiki">> 
## the ways in which your use of these techniques is associated with one of the practices of hypertextuality: (<$list filter="[tag[Practices]]" template="$:/core/ui/LinkTemplate"/>) 
</$appear>

<$appear show="Show Links to Videos" hide="Hide Links to Videos">
<h1>Doing the Exercise</h1>
Tuesday Morning<br>
<<youtube-embed "Sie9oxlDDvI">>
Reviewing Wikipedia Table Imports</h1><<youtube-embed "0nxQdUcfnFU">>
{{Building a Rhizome}}
</$appear>
<hr>

# Use google sheets to ingest (import) a table from wikipedia, using the [[=importhtml() command|https://support.google.com/docs/answer/3093339?hl=en]]
# I suggest you insert a row above the wikipedia table and use it to create short, easy-to-understand fieldnames for each column
# Download your spreadsheet as an [[xlsx|http://www.solveyourtech.com/how-to-download-a-google-sheet-as-an-excel-file/]]
# Create a new tiddlywiki (or build on to an existing tiddlywiki file)
# Navigate to the <$button class="tc-btn-invisible tc-tiddlylink"><$action-setfield $tiddler="$:/state/tab-1749438307" text="$:/core/ui/ControlPanel/Plugins"/><$action-navigate $to="$:/ControlPanel"/>Control Panel Plugins</$button> tab, select ''Get More Plugins'' and search for/install two plugins:
## xlsx utilities
## jszip
# Save and refresh your wiki
# Click on the <$button class="tc-btn-invisible tc-tiddlylink"><$action-setfield $tiddler="$:/state/tab-1749438307" text="$:/core/ui/ControlPanel/XLSX Utilities"/><$action-navigate $to="$:/ControlPanel"/>XLSX Utilities </$button> tab.
## Create a new workbook (any name is fine)
## Create a new sheet (most likely, your sheet name will be ``Sheet1``) 
## Create a new row.
## Add a new field for ''each'' column in the spreadsheet. It is easiest to name your fields with the same names as the spreadsheet columns. Be sure to exactly replicate the column name in the appropriate space in the form
## Add a new field called ``title`` and set it to equal the contents of a column that has unique values (such as ''Mountain'' in <<wikipedia "List_of_highest_mountains_on_Earth">>)
## Add a new field called ``tags`` and set it to a ''constant'' value that describes your objects (i.e. mountains, cars, etc).
## Save your wiki, and reload
# Select your new workbook as the ''Current Import Specification'' in the <$button class="tc-btn-invisible tc-tiddlylink"><$action-setfield $tiddler="$:/state/tab-1749438307" text="$:/core/ui/ControlPanel/XLSX Utilities"/><$action-navigate $to="$:/ControlPanel"/>XLSX Utilities </$button> tab
# Use the import tool {{$:/core/ui/Buttons/import}} and import your downloaded xlsx file.
# Hope for the best!
# If it works
## Create a template to display contents of your tagged tiddlers (i.e. "mountains") with at least two fields.

(these directions were generated in the [[Workshop: Annotating Sources]])<br>

# Create new wiki/tiddler
# Identify and download text of two articles that looks interesting: one focused on hypertext and one focused on annotation
# Ingest each article into their own tiddlers
# Use excise tool to split articles into paragraphs or sections
# Use some of these techniques (or others that you develop) to annotate the articles:
## Add tags to paragraph/section tiddlers
## `[[bracket keywords]]` to make new tiddlers
## Use ``new here`` to create annotations

<h1>Objective</h1>

# Enhance use of Table of Contents to organize content and associate ideas with readings about hypertext and annotation.

<h1>Task</h1>

# Follow directions in [[Annotator]] to export / import tiddlers into your own wiki.
# Use the technique developed in the [[Paragraph Template]] to actively read two essays from [[Vandendorpe From Papyrus to Hypertext]] (<<tag "Vandendorpe Essays">>)
## Add annotations to paragraphs in the essays.
## Tag your annotations with one or more of the <<tag Hypertextual Practices">>. 
## Write short explanations in your annotation tiddlers associating the ideas in the paragraph with the tag you've selected.
# Create a tiddler that presents your annotations as an exploration of hypertextual practices, and a presentation of your knowledge of [[Hypertextual Practices]].
# Share a submission {{Share}} by Tuesday 9am for critique during that morning's workshop

! Objectives

# Create framework for an essay including references, annotations and a structure

! Directions

# Build a set of tiddlers to manage References, Annotations and Examples based on a framework provided by [[[[Hypertextual Practices]] and [[Techniques for Hypertextual Writing in TiddlyWiki]].
# Build tiddlers to support annotation of several sources, including the <<tag "Vandendorpe Essays">> and other readings tagged as <<tag References>>.
# Annotate these sources, and use your annotations in the construction of an "essays" about hypertext (you may consider this [[outline|Essays: Applied Hypertext]] or create one of your own.
# Share {{Share}}

! Some thoughts and further guidance

!! Reference Tiddlers
# One tiddler per reference
# Text field: Use citation generated from Google Scholar or Library database
# Link field: Consider building different kinds of links to external sources, depending on objective
# Tag: [[References]]

!! Bibliograpy / Reference List Tiddlers
# List references
# External inks
# Reveal additional tagging if available

!! Annotations
# Associate with References
# Associate with concepts or framework

\define query() <a href="https://www.google.com/search?q=$(theQuery)$" target="_blank">$(theQuery)$</a>
\define google(theQueryText)
<$set name="theQuery" value="""$theQueryText$""">
<<query>>
</$set>
\end


!! Expanding on the techniques you developed in work done in [[Exercise 4.03]] (such as creating [[Annotations|Annotator]] and developing references) create a TiddlyWiki that addresses one of these questions:

# How can we use [[hypertextual practices|Hypertextual Practices]] when we create texts designe to engage and inform readers?
# How can we use [[hypertextual practices|Hypertextual Practices]] to facilitate our own writing processes?
# How can those who are <<google "writing to think">> use [[hypertextual practices|Hypertextual Practices]]?
# How can we use [[hypertextual practices|Hypertextual Practices]] to... (insert your own question here)


!! Project Specifications

* Your wiki should encompass references to at least five external sources
* Your wiki should be designed to engage your audience for about 15 minutes. 
** Assume that individuals in our target audience read about [[300 words per minute|http://www.readingsoft.com/]]
** Assume that readers of your wiki will spend about two-thirds of their time with your wiki reading, and about one-third navigating
** That suggests  10 minutes reading @ 300 words per minute = about 3000 words of text.
** Some portion of these words should be your own original writing (including tiddler titles, etc), and some portion of these words can be text that you encounter or discover.

<$list filter="[list[]]">
<$link><<currentTiddler>></$link><$appear>
<$list filter="[exercise-group<currentTiddler>]">
<$link><<currentTiddler>></$link><br>
</$list>
</$appear><br>
</$list>

\define exercise() Exercise: $(presentation-topic)$
\define workshop() Workshop: $(workshop-topic)$
\define exercise() Exercise $(exercise-number)$

<$list filter="[tag[Exercises]]">
<$link><<currentTiddler>></$link>: {{!!exercise-title}}, Due: <$view field="date" format="date" template="ddd 0DD mmm"/><br>

</$list>

Introduce the core features of hypertext in the context of  practices and techniques.

Comment on the possible wisdom of naming a thing both a practice and a technique. 

From Nelson and others, derive the [[Core features of hypertext]] as <$list filter="[tag[Core features of hypertext]]"><<currentTiddler>>, </$list>) in a series of essays:

<table>
<tr>
<td><$button class="tc-btn-invisible tc-tiddlylink">Practices</$button> || <$button class="tc-btn-invisible tc-tiddlylink">Techniques</$button></td>
</tr>
<$list filter="[tag[Core features of hypertext]]">
<tr>
<td><$button class="tc-btn-invisible tc-tiddlylink"><<currentTiddler>>: Practice and Technique</$button></td>
</tr>
</$list>
</table>

Explain the notions of practices and techniques, and the possible wisdom of naming both a practice and a technique with the same name. From Nelson and others, derive the [[Core features of hypertext]] as <$list filter="[tag[Core features of hypertext]]"><<currentTiddler>>, </$list>) in a series of essays:

<table>
<tr>
<td><$button class="tc-btn-invisible tc-tiddlylink">Practices</$button> || <$button class="tc-btn-invisible tc-tiddlylink">Techniques</$button></td>
</tr>
<$list filter="[tag[Core features of hypertext]]">
<tr>
<td><$button class="tc-btn-invisible tc-tiddlylink"><<currentTiddler>>: Practice and Technique</$button></td>
</tr>
</$list>
</table>

* Create new wiki
* New tiddlers
* Save wiki
* Share wiki

This is my first exploration ever with the use of storylist in a filter.

```
[list[$:/StoryList]]
```

There are currently <$count filter="[list[$:/StoryList]]"/> tiddlers in the story list.

<$list filter="[list[$:/StoryList]first[]]"/>|| the first tiddler in the story list.

<$list filter="[list[$:/StoryList]last[]]"/> || the last tiddler in the story list.

<$list filter="[list[$:/StoryList]before<currentTiddler>]"/> || the tiddler before this tiddler, {{!!title}}.

<$list filter="[list[$:/StoryList]after<currentTiddler>]"/> ||  the tiddler after this tiddler ( <$link to={{!!title}}>{{!!title}}</$link> )

Here are all the tiddlers in the story list: <$list filter="[list[$:/StoryList]]" history="$:/HistoryList" storyview="pop">
<$link><<currentTiddler>></$link>, 
</$list>

<$list filter="[tag[Practices]]">
<$link><<currentTiddler>></$link><br>
</$list>

! Four words
* Text
* Hyper
* Wiki
* Tiddly
!! Obviously:
* <<o "Hyper">><<y "Text">>
* <<o "Tiddly">><<y "Wiki">>
!! This presentation: explores the four words as separate concepts

* Develop tools and techniques to gather data necessary to complete IDT thesis/project.
** [[Alicia demo|https://designwritestudio.updog.co/demos/alicia/demo.html]]

<<punchshow "generic">>

Slide 1

Slide 2

Slide 3

Slide 4

Slide 5

Slide 6

Slide 7

* Read [[A Gentle Guide to TiddlyWiki|https://tiddlywiki.com/#A%20Gentle%20Guide%20to%20TiddlyWiki]]
* Read the tiddlers that are open when you click [[here|https://tiddlywiki.com/#Using%20links%20to%20navigate%20between%20tiddlers:%5B%5BUsing%20links%20to%20navigate%20between%20tiddlers%5D%5D%20%5B%5BNavigating%20between%20open%20tiddlers%5D%5D%20%5B%5BCreating%20and%20editing%20tiddlers%5D%5D%20%5B%5BCreating%20journal%20tiddlers%5D%5D]] (but don't worry about remembering things; that will come later...)

* Complete the steps outlined in the [[Instructions|http://people.sunyit.edu/~steve/dwit/tiddlywiki/workflow.html#Workshop%3A%20Saving%2C%20Serving%2C%20New%20Tiddlers%20Text]]
* You may find it helpful to watch the video from last fall class explaining how to do this exercise //Start at about 15:00 if you want to skip the intro stuff// <$macrocall $name="youtube-embed" video={{!!youtube}}/>
* Subscribe to the [[Google Group|https://groups.google.com/forum/#!topic/designwrite/PzoHJwkHVh4]], and once enrolled, respond to the "Welcome Summer 2018 Participants" thread by introducing yourself
* Share your wiki on the submission form
** <a href={{!!form}} target="_blank">Visit form in another tab</a>
** <$appear show="View embedded form >>" hide="<< Hide Form">{{!!form-embed}}</$appear><br>

Core concepts: with links to relevant [[TiddlyWiki.com|http://tiddlywiki.com]] pages

* [[Creating and editing tiddlers|https://tiddlywiki.com/#Creating%20and%20editing%20tiddlers]]
* [[Tagging|https://tiddlywiki.com/#Tagging:Tagging%20TagTiddlers%20%5B%5BOrder%20of%20Tagged%20Tiddlers%5D%5D]]
* [[Linking|https://tiddlywiki.com/#Using%20links%20to%20navigate%20between%20tiddlers]]
* [[list-links Macro|https://tiddlywiki.com/#list-links%20Macro]]

Assignment:

!!! Create a new tiddler in the wiki you created in [[Getting Started]] titled ``About Me``
!!! Set the default tiddler to`` [[About Me]]``
!!! Edit the [[About Me]] me tiddler and write a story about yourself

* Start with your own words, or copy my story from [[About Me]] and change some words to reflect your life.
* The story should discuss a few different aspects of your life. Think about different ''dimensions'' of your life, and ''characteristics'' of the ''elements'' in those dimensions. 
* Write your story as a narrative in a tiddler. As you are writing your story, enclose words that represent either dimensions or characteristics in double square brackets, like this: ``[[Words in double square brackets]]``. Be sure to consider both nouns and verbs as dimensions and objects. 
* For example, in my [[About Me]] story, I mentioned these <<stretch "dimensions" "(and characteristics)">>: <<stretch "Occupations" "(College Professor, Adjunct Faculty Member, Research Analyst)">>, <<stretch "Cars I have owned" "(Red Honda Fit, Blue Dodge Dakota, Blue Subaru Forester, Grey Subaru Forester)">>, <<stretch "Digital activities in which I engage" "(surfing the Web, tweeting, listening to podcasts, listening to music, texting)">> and <<stretch "Digital devices that I own" "Apple iPhone SE, Google Home, Apple MacBook Air)">>. In addition, I also referenced working, driving and relaxing.
!! Flesh out your story in other tiddlers
* Click on the links that you've created in your tiddler. Tag tiddlers as appropriate. Tag characteristics with dimensions. For example, in my story, I would tag the //College Professor// tiddler with //Occupations//.  Make up other tags.
* Write brief descriptions of each dimension and characteristic.
!! Do the [[About Me in Tags]] approach
* Create another tiddler, [[About Me in Tags]], and tell it using tags (don't worry about the grammar being awkward...).
* On each of the the //tag tiddlers//, use the ``<<list-links>>`` macro to generate a list of links matching the tag.
!! Share your wiki
{{Google form to share links}}

IDT 553: http://designwritestudio.com/sunypoly-natarag-blockchain<br>
IDT 575 <$appear><$list filter="[search[(Gladson]tag[shared-exercises]]"><$link><<currentTiddler>></$link><br></$list></$appear>

# Students will become familiar with the history of writing and the introduction of interactivity into various forms of text creation.
# Students will have an appreciation of the meaning and structure of hypertext, and be able to differentiate hypertexts from other types of texts.
# Students will be able to apply design concepts when creating interactive texts.
# Students will understand the distinction between techniques and practices.
# Students will become familiar with the open source software movement, and understand the contours of an open source software community.

\define google-scholar-query() https://scholar.google.com/scholar?q=$(query)$

\define google-query() https://google.com/search?q=$(query)$


\define gs(query)
<$vars query="""$query$""">
<a href=<<google-scholar-query>> target="_blank">Google Scholar</a>
\end

\define google(query)
<$vars query="""$query$""">
<a href=<<google-query>> target="_blank">Google</a>
\end



```
<<gs "Dattolo Luccio 2009 State of art survey on zz-structures">>

<<google "911 Commission Report text file">>
```

<<gs "Dattolo Luccio 2009 State of art survey on zz-structures">>


<<google "911 Commission Report text file">>

<<show "These macros use the ``\define`` construct (first two lines) to transclude a future value into a string">>

* [[Every Page is Page One: Transclusion will never catch on|https://everypageispageone.com/2014/09/15/transclusion-will-never-catch-on/]]

* <a href={{!!form}} target="_blank">Visit form in another tab</a>
* <$appear show="View embedded form >>" hide="<< Hide Form">{{!!form-embed}}</$appear><br>

*<a href={{!!form}} target="_blank">Visit share-wiki form in another tab</a>
*<$appear show="View embedded share-wiki form >>" hide="<< Hide embedded form">{{!!form-embed}}</$appear><br>
* View <a href={{!!responses}} target="_blank">responses to share-wiki form</a>
<hr>

[[GoogleGroup|https://groups.google.com/forum/#!forum/designwrite]]

* Adapt the text from Dr. Seuss book as a TiddlyWiki.
* [[Google|https://www.google.com/search?ei=Rs6eWr6lM5y6jwSOu5eICg&q=tiddlywiki+green+eggs+ham&oq=tiddlywiki+green+eggs+ham&gs_l=psy-ab.3..35i39k1.5160.8175.0.8442.15.11.0.0.0.0.358.1417.0j1j4j1.6.0....0...1c.1.64.psy-ab..12.1.155....0.GcIg6vhA74A]]

Bjornstad, Soren (2021, March). Grok ~TiddlyWiki. [[Online|https://groktiddlywiki.com]]

^^//click on grey boxes with blue text//^^<br>

!! Welcome to the <<strex "Designing" "Design">><<strex "and Writing" "Wr">><<strex "Interactive" "i">><<strex "Texts" "Te">>Studio 
{{DesignWriteStudio}}

* Download empty
* New Tiddler - Hello World
* Save
* Serve

* [[Plugin for bookmarks in tiddlywiki]]

I'd like to get some feedback (anonymous or otherwise) from everyone in this class. Please complete [[this form|https://goo.gl/forms/LoGMkPouQoYSJb6q2]] when you have a chance. I'll share the results next week. 

! Hyper
* The //hyper// in //hypertext// means multi-dimensional.
* [[Nelson meant "hypertext" to be compared to "hyperspace":
** to invoke the sense of multiple dimensions, unseen, unseeable but mathematically postulated so therefore likely to exist.
* In science fiction, hyperspace refers to "a space or more than three dimensions"
* Hypertext, then, is text constructed in, and experienced in, more than the usual number of dimensions. 

"hypermedia content (i.e., multimedia content connected across the network with hypertext links)" ([[Hoffman & Novak, 1996|https://journals.sagepub.com/doi/full/10.1177/002224299606000304]]). 

//this is evidence that in Web 1.0, links were either all of hypertext, or perhaps a reading of that quote is that hypertext links were a minimum; hypertext transclusion and hypertext tags etc. were on their way?//

[[Hypertext|http://en.wikipedia.org/w/index.php?title=Hypertext]]

~McKnight, C., Dillon, A. and Richardson, J. (1992) Hypermedia. In A. Kent (Ed.) //Encyclopedia of Library and Information Science//, Vol. 50, New York: Marcel Dekker, 226-255. [[Online.|https://repository.arizona.edu/handle/10150/105403]]

Braisier, H. (2010). Hypertext Teaching - by Adrian Miles. [Blog Post].

*[[Online|http://raws.adc.rmit.edu.au/~s3239835/blog2/?p=214]].

Miles, Adrian. (2009). Hypertext Teaching. In M. Bernstein and D. Greco (Eds.), //Reading Hypertext// (223-238). Watertown: Eastgate.  

* [[Online|https://sunypoly.open.suny.edu/bbcswebdav/courses/202106-IDT-575-3070/Course%20Readings/Hypertext_Teaching.pdf]]

Cripps, M. J. (2003).  Hypertext Theory and ~WebDev in the Composition Classroom.  

* [[Online|http://cconlinejournal.org/cripps/index.html]] (Jan 2012).

Cohen, D. (2012, December). Hypertext. [[Online|https://sunypoly.open.suny.edu/bbcswebdav/courses/202106-IDT-575-3070/cohend-idt507-assign4.html]].

The [[Hypertext TiddlyWiki|https://sunypoly.open.suny.edu/bbcswebdav/courses/202006-IDT-575-3099/cohend-idt507-assign4.html]] was built using [[TiddlyWiki Classic|https://classic.tiddlywiki.com/]] and explains what hypertext is and how it's used from its origins through Web 2.0.

* Create a hypertextual bibliogphy of scholarly literature about hypertext, from origins including Bush and as described in [[Secret History|https://www.theatlantic.com/technology/archive/2014/05/in-search-of-the-proto-memex/371385/]] thru 60s ([[Nelson File Structure for the Complex, the Changing and the Indeterminate]] and [[zzstructure|References on zzstructure]], and Englebart, through 90s explosion, through 21st century evolution, to today.
* Build on TW efforts such as [[TW-Refnotes|https://kookma.github.io/TW-Refnotes/]] and [[Zotero-tiddly|https://opensourcelibs.com/lib/zotero-tiddly]] ([[very old thread|https://forums.zotero.org/discussion/2628/tiddlywiki-as-a-zotero-database-presentation-layer]])
* Consider bibtex solution
** Use [[$:/plugins/tiddlywiki/bibtex]]: See [[Google Group discussion on bibtex|https://groups.google.com/g/tiddlywiki/search?q=bibtex]], and this [[thread|https://groups.google.com/g/tiddlywiki/c/OR48TT_loB8/m/2J5b_o_3BAAJ]] in particular.
** A small bit of work: [[Testing Bibtex References from Web Of Science]] 

Building on [[What is Hypertext?]] ....
<hr>
<$transclude tiddler="What is Hypertext?" mode="block"/>

Emily Berk and Joseph Devlin (Ed.s), ~McGraw-Hill, New York, NY.

This book was published in 1991. 

<div class="tc-table-of-contents">
<<toc-expandable 'Hypertext/Hypermedia Handbook' sort[title]>>
</div>

We have iidentified  <$count filter="[tag[Hypertextual Practices]]"/> practices in which hypertextual writers and readers engage:
<<tabs "[title[*]][tag[Hypertextual Practices]]">>
This is a matter of some debate, and the meaning of "listing" in particular (and the place of filtering and sorting), is to be discussed.

! ~LiveStreamed Thursdays

Exploring core readings about hypertext and  key examples of hypertextuality

* 30 minutes presentation/discussion
* 15 minutes question/answer 
* May include guests

Streaming info forthcoming

First session: [[Thursday, January 25, 2018 at 16:00:00 GMT|https://www.timeanddate.com/worldclock/meetingdetails.html?year=2018&month=1&day=25&hour=16&min=0&sec=0&p1=4710&p2=136&p3=16&p4=224&p5=64]]
<hr>

* NY: 11am EST
* London 4pm GMT
* San Francisco 8am PST
* Amsterdam 5pm CET

[[Projects|http://idt553-summer2018.tiddlyspot.com/]]

<<tabs "[title[*]] [tag[IDT 553 Module]sort[order]]">>

{{Project Ideas}}

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

iVBORw0KGgoAAAANSUhEUgAAAocAAAGjCAYAAABewb9fAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAP+lSURBVHhe7L0LeitJ0lypfzZWrU2MljPScrSKaq1MA7vF021l7R6PfAAgL873WWWGu4eHxyNBkMRl/df/+//+v//3v3348OHDhw8fPnz48OD/+bp++PDhw4cPHz58+PB5c/jhw4cPHz58+PDh3/zHr5X/9//+3193Hz58+PDhw4cPH34y/+N//I+vu3/z+cnhhw8fPnz48OHDh3/xeXP44cOHDx8+fPjw4V983hx++PDhw4cPH340//Vf//V19zxeMeZVLH/m8H/+z//53/7xj3/8t3/+85//autethmK9asjW2V/BavzcY70AebuOdTWveR+iTa2UUzmqGz0YVzJ7z0e1PY+OS726l5kG7C73+993Hch66T94Xvxv/7X//p1/f/+v//v13UF76NzqfP5Tqi+nfl8V2bzPLI39CG32v/n//yfv42T4+Y42SfbVd05blL5uefq4+zk6VDMH3/88bf47EeMj+t9hOxZm/cBcmeOzuZzSXKchHGrulbmm+NmrPsSj8ncosvBuGfJr1XVZw6X3xx+53fAHz58+PDhw4cPH/7bf/u///fvf9768D9I+bwx/PDhw4cPd+E/PbmSnbz5BTPbHStxXkc1jttWxxU5P7V3+ndUNV6B57mi1m5/V/LujN2NAzP/u7Hynu72zxzOFm1ngzx21u+7bRbsrMfd7KzhnXUr924tXs9qbWfPajfmdz2LH9YZnbfZuXk1qq+qEZvOb8b4fZ5v+WZn/s5nwmsT2V5hp0/1hTbn578eXP1hy8oaVb+69PxH1jn7qP2KHxDt1p7nbraHozll31znrG30kaIj52+V3TWCpZr0a2VXxSOs1KOwf90D95WdNv0g7zNvF0+M/B6DbeTPGOmPP/74173HrShzXanV3LO4P//8s7S7lGNnPF+zkTznrE+O73vhPre7FOM+v19V1oBW5yt5ji6faxbj/p06PnofjfZYPvza39l5OKLq3IjRuF5XJfd1caP+gro8zl+vBPejXCmf76zOtO2Mk6rG1dVz+pw9Br/fS91cqjbyPqvKPt243ZhX6EjuO+tBGuPMOM+ocUWqw8n3gdKpN4fPkKgWVHibmLTvyMchD9ejWjkMK/MbaTV2pZZdjXJ6XX6f67wyf2LSTjtzYM/7jz46q9GZX9UVOe7QrC6eJUif0H3mOTJf70NerulPXyX3+72rs89U1Tq6l3bWxPvCqM19pSO1ppRjFrOrlfU4Ou6RPlfrHWpwOfk+UHr7N4fvqKvWZJRn5NvVKNfI1+lIH8n7+X31YsU1Bd52/1H7qroX1kqdnxzuX3lhnGmUw8f66JxynX1tuYcq5qiqc+P3K2doFuN+z502qHyVsvaVWivRX8oc7vP7HYmsNe9HGsW5T8zWupPHKke2ud8RdO1U+kbjeqzfp1Zqz5jVPqNxpfRne1dV/8r2KiX5PlD6/J1D43GIvu5+rd7XXc3MP4JxRp956Hyr43pc5sLn862Q/8g8vU/Xv5sf9pkfVuMqZvOfMRuj8/P5FfmPrG9H9fkj5+x8P/xFrrPv88r9UWb7u0t19nyMqubRPEa+q2rfXccjr2HUemTPdtaHcfL18srXhNVnXrVRn/pk+ww5746VM3L0HM1qcD/zd2ZrwL75/nU2v45YiTnK0p7ku8WKR9hvodFnOqSZv7Ih0fndPso76y/S5prVj2Z5Knlc9scH2ImZqYrNz8UckefVPTndXo3DHKTMwf2uuvmQ80zujz6qlGc3z1h35nRWPb6LG4kc3ta1sqV9Jo+9s5/HZK0+n5VcSBDvOat2pS5GcL+Sx7VTP6rG2J1P59+tJ/N4/yNzUx/pCsi1W8dufCrJ94HSZf8g5Seoms9o/tJsDVbWSDE5jrerHCt5Jc8zEzkh/avKvl5r+rJdaSWmW49RX/Vx/+qadvJcZ1TlOVvbO6ma33fRmdrP9L1T4G33z1Q930fOK31RlSNjsr0iqHyp1TiX9+nupZ01yr6z9hF1Oaiz81damdsophtLfTqf8JzC/ZVWYtCzqMZOrcZ1SvJ9oPT5tfIE/fj1sXZfrTVm8Y8D/OtKnH5UvvRj3gN4/YwL2Qb1yXq6OXkOYrKv/yqgmmdXh7MSUzGaf/6K4sr/w0m3Xp3dqdZo9uuUlbzvQjW/78KZ2r/LvHfr5GzqDNJ3dl4rclzP2+F9PG7Wx/t1ry0+n1G+JOdRkfl28ntdwts7r5M+pt8rh7fZh5U1g27/Pe+I0RqOfKMzU9lyHTtW676ClbFGa3AVp98cPnPR7kJzyHl4u9qI0bw9fvQiuZp35UVSuL96eLMWtb1P+j2HaiW2q+PsgVXeaozM676Ve6j2wnP7/SxXha+RU+3Fas5Vzq79T4f1nn1Rm9Gdi6v381WcWZ+7zuDdZ9tfF7p99Bp8jWb77v26eWSOKmeXR7V0ecVoP7PfKE+y8420z2dnjF1GuVXDbOzKr37VftzNleMefaZPvzlkQXMy3FeFdZO+ajFW8dryYKi98mCtvLAI91VvUoC8WY+QjTyjHEmVizyVz/G6q9pmdYzWRHiu7n5EF9fZR/XkfnvsbB4V9PE1oi5dj+QccfRF4HeAdd95bir8XHX3V/DMvVTtV63PDkfO/2idO99onPR5ji4fa6S+xOR+rezfbK2vyLG6nz7XlT7dm8NqrWfr2FHNf2c+3d6soHmMzs2zuKKGas26Pfkb+XvmikdYKX3Q87Hwv+5Bf7hUECM/MZVNV/KIjF0VHzolN/ncBvSRTVdBDL5Kld8/7DrqX+Wn7etYyX1V3Kiva5YHCe5nuX3+ldS/ivG83Rr6vf9BXNnd53Zvk1d25sR1RZ6vGu9K5RrN1vWjn60j5+0dzsxq3Ved99l4R/J6nyP7kH2O5Jjpjpyddtawqsttul+pXTGMq3tet7OWI/vbidoY751QTVXNR5Xk+0Dpsn+tDL6R7yhqEyy48JjUyH9m00Z5R76jylqvOHBX5Hi2WNt3r506P/qo0srzfPSMHz17R/sdVY539pkW5BC6ns35XcR8O838d+lZ434HqrqPKMn3gdKl/1qZWK5XKR/WsyLPLO/oRaHr8yxd9YL16nl81OuzN++h3Ifu2fM4v1+V9+nuXWnPtjSqVeS9+73ttpXXnpXXTq4zeZzfV223C+7T32kn9oyeNc5Rzeq76uvPO+k7sLPuorJLSb4PlC7/BymP4td+n32Aq/Jmnipvzis5U4vW6Cyrn72YsTOP2Zr8jlyxlx1XnfcP13L22TvyHNHH+678z/5Vq/fx86rzRZuzVp1nt2XtXXt1jYgfjdExqvXos+P9ZnWM/FVtP4mrvv50rJ6BK9BePXO8M1z5FzVmnHpzqAPiD5MK58XoysX+xz/+8et6RU4dhO7B/eOPP77u/nqR+Oc///nV+gv37+JjrjxYXY1u13rQ1tXv/Vox8jmjNV/NMePMuoqjdVTjVrncpj7e5oxUMdgYx2MSj5HUvvIZ6mDcDz1HXpBHffTa4meBe38t5TVPyE4+j8nXJ4d47W9VC3l4LaKGKqfb1C/bjo/rdG3ifb7C1wfcxrOh/m7PPMLn73VUz5dyVeNAton9888/f12FYrRGxCpG43puanIbV6DWtK/geZOVfLmvIvuNxnBWYlbJc3RF7urMvDM6V6N5s0bVHm6RP0qseIQtyWP9/qweC/Gv+7N5z/a/U16b36fwcZV8jSoRy1WiD2DH5tfKxjXvU1lbtr2v37u8Vm+7LduzcascXDtbl8Njsj3rI6oY4TZvZ/xM3tfvd/N8tCZf41V5H98XyJifpG6+tKv76uy6v7rPq5R5aAP37ge3ESeIyT60uedKDPfe9hhU2VyQ40o5zoqA9ixH5/ccI9uqjszF9d2p5rSiJN8HSpf/EezHZn3dXYd/5yfuGOMudmt97NPX3b/vPYf7RRWf1w5+anDmO4zZ/GY1iGp/s9+s1iNnwn+CS17PX42lPl6b53Cqvt7P7zO2WzOP68bt6Oa1m+fD2lmr9n9G10d2fB5z5MxfTXdWd8lnUToyP1+fCl5rRnHU4jF+Lz/tnD/2fK6y7fm61wVQLPYj693VCp57d5wuzl/Tu5jcX7VH48rXnQn5qr6zfN+dW18D8t1ixSOs1cx/VJ73sQCl/W75uGg0Pj6uM3slYiD9+LiK9FdajUt5P79HrBG+XDNRreOujuS4YlxJVPYrVdX6jHE/Oq4z+3PV2TyjUf0jn9c+ius06jPyndHZvGf7S1UOt+WZyHUerXvVFu7jqjzcuz3vvQ3YqQVb1o59dF/l4F5UdaYNu3Dbin4Cue6rSvJ9oHTpr5VX9Efxd4ncVo1X9XGtLBA5PFbQXs3hcdlnJUelKiekHx/3+GZrJK3EfHRMo73/rPtH76jRmb1Tq+O+y3Nz1WvrznorlpxVP/8asKuslb8hq3HI62Mq3n0ubOSkzZV78gns2acaH7AhtVHa0p82jfuTqOY7U5LvA6WnvDn0HD4R7GnLyVZtQVtgE8SknzaqbN9VP2kule6Y309fs3eQqOwfvaeufiZG+z/yHdWs/pX5/W6vCyvzhco306yf+/1+RUf2Sn1+GtU8R0ryfaB0+WcOV3nU83X3F9mu8Bj/zIbwz4EI/4xHxkJ+DuQqVubyDN6ljhmPh/Xr7v2h1u+ytlezu1fds/ehZnSuqrXv4kd5zp7dnTPA/ld9/Gys1jSL89d0xea4+D1PF3MVZ9cbdtZ9h9X5+n5lLaPaZq8B7h/FVus4q73qk59x/wlcdcacW98cqmA/NNUEZPMNrl4w8M8OmSDm7gd+RFXnHZvnVPNTHTvj3vXis0tVh+Z39RqunIluTVbX9q59P7NXo5re5Qz8roxe47pnHNg77S/23M9Z28fwc9KdGdl93C5uRv4Dhi7PaH0SxXbPuOdZeR3oWJnvTs3OaG/OsrtPOYeshfYob85nl911VC1H1/7Dg/xRYsUj7JQ8R3fvehyi0v7O6uaCoPKd0SznzO8arfsoj/tme+exV+pZZ6YaB9KOjz4i/R99f505e88+E6rVx/T7lPv8vpvvSozkcZVm/lcIKp+U61pp5n8XnTnPd+jKdfvpaI6r++fk+0DpKb9W9nfvoz+gCld+hzTjsZBfd3vQ7w/7g5PYPKf7q/l6bNaSbcfzJo+9PvSHMNmbatxuHCEf97O9u/pH+t0aYV9ZQ+Fxoz7V/HJtvL/mm318XMHa7TKqU8z8Imv5STxrbrMzP9qH7nnw2v18VLlW9hn0jPt55V45Mk8VJ7r5djGjvNXZZ02657Pq4/4cr4O46pxkDtXka1Xhe1nV6POGLpfbu5iKWeyKv9pf2XfquJJq3WCnptVY9nokfx+TqP+urkJzXPmj3ktfc/LdYsUj7KV6TLi03yWfs9+v1uF9Ku3MZ5YL7a7RKO/I5+OM4lxH98/zz8aV3+1+jzJHl9PvV3Wkz0e/h46cDc4mpH+mI30qdXnc7s9RyuP8fmRb1WjcSj6W3+/mWYn3/H4/UpXX++7WOZLnPaIra3mWVqj6jZRUMSu6ktXz6eT7QOnp/yDlUfjX3R6P+r/u7kffGYDfd99RVTyzXpG1VXW5zed1lFkO1qBaN1+fvJ+dkWpcjdHtW4X8+R3bbNzRnlbjjeJ/Fz5r8O+zsbMWPDOzc9wx63dkX+gzek4y76wO/LNn7wq8Fr+vXp+crM3ju3Xsfhq0u+7d+nke3Z/Jm/Nb2YvZmq3wjD2HlfXp1npE9tndh7cm3y1WPMJu0Z25HwfvP2yz8ao+q/Lcfu824W33d5rFzfyunVjJ18P7+n2q65NyX677mX3YkdeQqnxu435UKzGp2fzEXWsgKvtHf6la95+2ZqD7lbOYtuzj7SoejXxdHaM+KY/1+x2N+o18UuV3m9+7Ovuqsn+2dyRW9/NZ8hpm51XyeLfNyD7Zr/JLTuVf0ZWsrpGT7wOll/0pG3HknbrzWISvu/+k+0zAqE/13dBj3Za+w9FcFCv0XSN9+DyL/D5f7j13NU4VJzzvCGoS+izCylzAP7vAOBq3GpNxZp8prdYo1330XWlXv9u7+2T0WY+qdq8ZVKuvcfppe4yD3/t5XbJXMSufk6qYnZffGa1fdfa6c8J6ay9W1t7J/aPd5XF7d5Y6Ml5ngHOg53U0ZnVeRs8ra+XzI7/nyvl2z3zXp6qZseXzOjzW76t1ZLwqP/jcoIv3+qu17CCfrtxX48rm51NtH6ery/M66lvtp9bK472Wbgzozms1Hwd/rpuPl7nl8/VQezaO8D6Q88o1gNG+Kn5FHXo+VVtV3+3ku8WKR9hQKzHfWaP5PTa2tK9KjHIIriL9ncgJ6Xd1/tncvJ/fjzSL6/xeCzFc0+8+rneqG8Pt3T3K+mdr/9FHq6rO292qntdKwH36K3mc3+/I+6lWb6c/VT2bmaO7T0HlS62uaSf6ZK3VfJ6h2XxmdVV9UoL5jqj6dWSsx498u1S5VuYiqr6uJN8HSpf85HDnO6IjPBbk665nJeYoo/l13/FCVZfbVtdOcbPvUB57/NX6d11dP49NRr6Eucxqg1EcED+rYyWXYsjjdWRu2mn3Ph1dHW7v7iHP0excrTJbww+/L+9yNrrnp2P2LK3g/fSsZR5v52uAP5usYeboftKTa64+9Ju91oxeE1b20uvze0d5Vl7zroD5aMyqHvdXdHNwVmLuZGVfKrq6R2cALvspY75brHiEfbShas3c9nj4/uZLud/7vVLUMavdRZ9K7sv50hbYz6jLU60zpP276rvX/9E98nPh93cK0ubtM/Jcfn9WO695aKXPKGZWv/uh8u1KVK+Lz9Id42k+KyhWzOIzP/3EyLdD9s/2DI+vlOT7QOnpnzlc+f3/XTw2Xavy1fo3le0MetevsRy9m2ec7t0/fdzffQeR+Vc40sdRf9WWebyt/aVd1Y5P68F9fk6Rdjf3XVbyqB7VnrHV34zy+fq9oJ126OwVO7Edoz1wrn4GPlzP6LWzO3fdGbrq2dpBz1iOO6vD6/f5V/PyXP7TE4/N+5VzP/oJVlWHyNf4au+6rwOCuSg/Y3gOn6vuaSvG596tmed1lMfnW9VxFNUyyiG/z+sKdmpmf339VvAxcjy1lQ9pftz71z1HPiDfzjy6vNvku8WKR9hlekyytI+00mcUM5vDzF9ptw9UvpXaIf2dPKf38/uRLTWLcb/fp9zn96vyPn7fzfcuMUbuHXau0kptxED6P/rojHbP1G58Suf5bI5OV+Ud5Rn58pmfaZRrpjN9V7U7H9cz6js7BmfxLFVuyan8I1W432sf9Uk8R6Uk3wdKt/3k8DHe193f70ffLXWoj+eAylYx+27Evztysu3sfoej+N0+zqxv1urffXjfnRo8p/rlenft0Rg7tXh+almtf/VsHIU6uvMsf1WD19/5V+f44cMqu2fK40evg6Pn7Mg5Xnlur3o+yDOaX8Xu1zCvd/d1aXWuu3mvoqtvd02v5FVrcYRq/br6ZX/m3C5/c1h9Ee8O0Gyi7p89JEfedFYH2Mfczbm6cRp3NI7XpXlXa5pkjtl6OYqtaq9yjmrbGbOjW8NqL7rxOrvX7qzu2wo+9mw93L971j58OEt37tM+OpvdGc8+3bOXzJ6ZVXae6Z3XlrN43tGazOpPv+fdmbvw+Wff3Vxw1euZxl9dMyH/HXvnP2xxVtdHcV1s1ntl/Uf3T5x6c7j6wHfMFmFlkXLyO4tx1QG+GtW1M48zBwBWD2Su2WwNu9rc7udIdXh7dW5Zx8p8qvO7Uu8u73rOPuzDOThyHo6eodV+K6/H+azBaIyVvDPOPANH1q2b29m5ZC1HaoMzazJ6fXNfN9+VuhVDrjPzPEPOc7Zmd73WVnmrNUmb2m7r1rE7r2cZnZMZp94csmA+mSs2xz9EO0ITz3f0ZxZDtXu+7sO8onroZmPTR+PMYt1framPvzPn7sViBv1W9sbH6L7jcjQ/78N8Na+duc3IdfR/+MIZVr1eC/eKcfuH3xPO4+651HPTvbbM8LGqMyib2/312O26z2dN98R7P91nG/7888+vu7/s1Vxkm9XkNvA+5GXd3CdW1lAxvn7+D8yUL3M6Ix/4np7N5eyer47qa4fo8ru9u/e57M5rlepsHOFsfdrfaq38GUg0purvYuSr5sfXIz9Tych3OfkhxIpH2FBdTGd/Fz02sbSjmT/l8/X7mUbjdHmqPh6bfvfdobvzP1M7c9k5I+TdPVfPlNcmZuco2x8d12wttRezmKOCvJdm5xV/9sk299i5utyW4+LjmjmFt7l3uR3yPv2j2iHnmyKHx+T8VnNIGQeV7911d72s6y5VLukqMm+1/147thU8R6Uk3wdKT/9TNlfzmNfX3Roe331XdZTuO60Zo+8GlOdxQL5a/66/qn005qye3XVMlP9sjl1WxjtS087e7Zwh8nZ9nr1+FV6b6s1ac2121urDmNlaai/uWm/l9dx+Pzvj7u/OcJWDMXb6CK+t60uMXjuveK5m42StOW71Gp825ZitidiZz0ps9fUl2RlzF9/Pd6Gr6c51gLNjXPXTxUveHPpC+kGrFtj9FVqYWYyzerDIOYv3jeGBH23WTq2O51ydg1iN7V5YO3Zq6Lgixw4r43nMkb3q+nRnArv7ySGbpLb7/T7pfEfP3Yf3ZnQWnsXR51j9dp9J4e1R/+qLXhfv67hSk1M9W6s5cv9oz75gE+f9/XWjY+d1QHmqcZzVeWZtao/qFLNad+ZyJ91ezeZ3FbvnNbnqzeFb/h9SHofkb9fUH3/8MbWp7f2rPjsSZ3NI3ZzO6khtuUaplZx3zeduqW7mJ3TNNnF+Twx2tT0euY1YcJurshH/Ks3OQFXzR8/RbG+uVJ7D2b7v1pbP1RF536wXdXVB2slZXf1eeb2/bIKYan7Vvdu6WhXjcRLgdzv3VVv6888//9aHe+Aev/AYXdXmnjb3lSq/5jvrt6LMQW0rdONrjWaor2vWJ/dXfUD37kOcsxFdX5ePJfJ9oPTW//s8qHwrOtP3qFY25g6Nxt1dh934HZGbq7S6Zt5nJEibX6Uclza47wpB5fvo99MrzsIVr09X5FjRmXFesbavVjXnXMMqJlW9DnKtYmhzv6rMkfdV7WnLdiVqm1H1lVbJfrNxZ/Hpr2IqVtYkyfeB0lt/5vDsj1fP9j/C7q9zxWMzv+7+zmPPvu5q3F995sXxWO4V4/bs4+2uliqmGsvJcYDYyi/b6n4qLmNpuz3XjHbV/wruyvvhe3LlWZg9c3Dk9Sm57NdWE87U6ms7Wo+r6F7TVriqvuo85RqunLnqdfDq9axy+Gt85Z/Vnn2uXFfOfK7HqKbR+a365XOl+rUmuqJnPXvi9JvDqzbA8QdttPjfjW6t8hD5/Onjfat7+tBWTo/zdTyypvTx2irkn401emg+HKfaGz8DHz6scObMvNt5y9ejuzjzmvaM+kbk68bsNV71Ml9qV3tnHl0OqHLtni3PsVNbhc8vr1DVV427U8sz3wz+B/mjxIpH2FCPw1Tan6nu8xno6OcZvA9j7OTxuujneZD7/TMgYmXcahxvd30F955jVaPclRiv6oOtquNIbd9FzJu1+ehnyJ+NPL+j81w9G66Z3+XjjM4XOTO3qMar4kH3GnfU7xnSWDvr/mxVtTxrfe4e5478Z3OOqOJXpbqcKkbqzl72P8vKGU/yfaD01p85fLZGh8/Xwe9nWs3pbQ6L+34H/cQ5z+bU+fPcjM7RR7+n8nVidkaI5boij+3uK9sd53WUEyrfXdoZb6X23TUTld11dh9Wxnh3+Rp0ePyuKqq4SldT5U8bdiffB0rf/u8cjnjM+evu73R2J2N2fhQ843FYf109p4+3+yP6n8I7zpm9uotuzv4rFpHtZOVMv5p3rXG3rrvPxCqzM5Fw1naes1Hs6DVStbn/GWu2Mq+VOlZr7carztPKXhGj/rtnsiPHXcnr8985K2Kn7mc9Rytrz5ofUYXss/l1fa9kd//+Rr5brHiEndLRHF2/x6Iv2Vzu38m7qi7nSEf67GpnjDPzP6O7xn3VfFw76//T9a5r8a51vVKjNcnnKmOzLVXPInT+TlD5djXLM/NfJR/H71Mj31V6xhiv1KvQGb+bar6VknwfKF32k8NH/q+7/2Tl3euo/wrVdweec+c7tyMceYd+5l3946B93dXgn41xdN27frO6KnLdj+SY4fV293dw6ju3Dap5jNbx7nl/J561RzNevSeMn3XkOTryOln10bqz9ukfrYX3m63Z6jNQ5ZGtOhuec5ZjhOfxcfy+q+sOyFvNeRfN7a46k2eNc5a7/3HJFfvmHH5zmA/dkcKUgzzVwnU5V1+cuv5XL+IZmH+uZ5J+/ifdoP/J9yxH8kf8j+tX1pUxWMNZXclKjVUdWWuC3/P7/2Rf58t93O88sKPaRz6vvYsb9V+hOtOj/XzFM6AxeSGf7edPYnXPZ3uS58jPPLm6saB6ToDx9Uz4c+HPUdXP/XB2f6llNrd8fnNcnoFuvj7npNsPf668To/POmbrof4eQ71Zg+r0MTNvNc/qzVPGqV3Nt8pX2SoyX7Umq7k6su7ZOv9Uqr07Tf4oseIR9tFEZ9fpbP/HQzLNoZjKPtMobzduZZtpp0/OZXduO2Oh3T7Ed7XiH6mLWZ1v17/T7jruKuvJ9kf78jX0+7vVjYWdayU/Z8RxXdEsdua/W6PnqKotbdmeaTfelbVWtVf5V22VxMq4nURlX83xk6jmN1OS7wOlH/0PUp7B4zD+uq68c3/swdfddZBT381WNeyMyVyE+q3MrRv3CGfyjH5KVnF0LNbE13VnjbtYX3uRe5Ew39nYV+3NlVCzrqpvNoefiPb3qnn7Hj9zv7uxsI9q8fPbxecz4XhstY74RznE2T3o+q8+n5Bzz/YRzs7N2alnddx8zd59Da+4IseHv/jxbw6vfEAqdg7j6AFz3+wFTRCz89DOavVfrShvFc+4K+vaxazMr+LoXno/v886ZnPzte7WfVbjSg7B2o9ixMy/yzNeXFWz1lpXrRft343R3nXrMTtfZ/Fxd8Y6WtdoDVbPoufIdfMcVY3e98gcZv2r+Y3mvMLqOCM8B2uEbbZm2HxMX/eVWs6ugfevavxdqD4OcRn5o8SKR9jb6nEoS/uK/jj4B1F9zCrHjr+S/gh22sQob7ZX10Vwv7Ieo7ydj7yrNWUcNc76C4/hXldR3VfxV+nqfJ0YZ2X/3kG55uK71P7OGq3hkbPofYT7RurGkv1IHVdJYz/rnK2Moxhfj1yb1RyjdqdqH6o9Xo2r6jgyn5GUb2WckTL2O1Otx6qSfB8o/TafOdw5QJVevQ6z8TU/j1mdr/dZsadWxhnF+Djc51wqVTlnfc7Ic/v9FfJ8fl9p5v8O8jlwz34C/o8+enf9tPO68pouPWve1TiV7ai+K9VcVpXk+0Dpt/m18hW/Lns8NF93/wnjXIlyklc/Rq/G6OZXzbeqf/Tj/dF8d1j90Te1qPbZrx08p6/Rs1lZoyqm2sukiunOwXfC96mazyv28cMxtHdXvU6s8k7nX7X4eX1Wbe+0BneS63uE2fm89VezN/GM18i3eHN49YuLPzg7iziqQ3lGb7i6F4gzc8vaZ3PZmWvFTq3MsXvT7WuQD5+Ps1Oz53RWcxzZC99fxvf7jpnfUb6dcWT/SWg+nKOfNrd3YuVM7j4jvncdPu7Oc9ExOiOz+kd+1Taqr/J5Le7XOLtz7WrLPGrf+Zz4fnZzUK3PeFa7MTp7tYaz8znzvxvPWPdf5I8SKx5hL9cz6rjiMxFcq3rxV+Pgk1bq8Hgp+3hbZHyllZhZbSP/KP9o/it1SR4nyCOwu3wc9Z3N7TuqW1fsso3W9xlr4uN39z9N1V64jqz7LGelHCdzkEfX7jnyz0gLxXoewb1LdPkFPvxdrMe5vI8kPEflF6pddnCf7rs1cjI3+bzN/cjmdsbNvF0/qfN5LSNbpdF4V6mrxdceXVnPu1PN/4iSfB8oveTNIVS+1Gpcp7P9dzQbq/JXtkqzOD0gHuP3Z+W58kHceTA9Twq87f4V7fZ5xovcKwTcY3+n+a7U4rXfqTvGuSPnEc3WWX6vdXQvaI8kfFzhfrcLb3c+qcvp9znf7EMb8KUcb2ccPq7gbd1rXO69j7eF29ynq9eOj7wC2+w+a8m8tF34XqHZ2O6vat+Vr+m7UNV5Rkm+D5Re8mtl/Vh09UejR36E+pjr1906R/oks1pX5/I4nF93/2bWN380Poufzdf9nuvIj+CZz6gm+dw/q9+h1p0+4rv9OmEVX0tfk3ear9dyxbN3ht1zs8IdOY8w23P5vVbuqz3p5lS9Xq3S5ZS981VQb86Xds4n88/82a4ghrhZfJLxua7MRXFVvXfAOHflX2E2tvtn532FK3JcyavW/i0/c3jmxUb4YnYLe9XDdWWtR/B5rM5VrIw7mhs5Vx6kux+2s2u4S7WeH47z7P37MGdnT6rnG9uVz4qP4/XpflYvMd1rUdd/lleMYlb6d4xeN8k7ihH6vLfvAff0X92fKofbqq8Vq7nfkTP7diWv/Mcyl785PPJmaXbARXXQzhy+qza/qv2ZD0U3D9+H0Vy7B3yWd7Z+d6zBM9Y1x2C+Z8Y+8kz8Tvja6v4Z+/w7sruuR18jvZ/uae/u7U96bvR1ItdllVls+r09G3eWW+Q+eJ9qPztb5jmyv888E5rnyvrchcZeeW90F5e9OWTT/vnPf/66wh/F/whbsdUmY/MF4aBVmyTbzosNjMYWld/p+o9qFaNxdeW+mr/7O0b+zue15kGk7X1XD2u3BitUZ0bkd8FO9vGaqz65Hl0855nv4HIctb0v9zlmjjejGkfs5vkO+FnR/Su/W353tP9Hz8CZZ/KKPdH41KDznDnP1HeWM+t6Fo3ra3FlHf46wvr6a3iOpXZ+DSee1zRd2b/cQ8+XvvzakX5Rzd1fS//xj3983f07Vn7uda1yHEW5VKePexdad43lz8lLyQ8hVjzCnqJqrMpW6bGJpR2lP/OK3RwrOtLHJSo7mvnv1l3zW7XTrvYXm3BfZ8MuuM+8agu3edvvP1rX2XP00T06ep6P9vvJWl2T1birNRt35kercdUz733z9Rvwcw+6z9dn7rnm/VFdTTXGnUryfaB0+2cOH5v1dferoq+7murd8l3voDOv2rOfiq3+1MznWfXxNalwP3V2a3fX+qyi+Xlts7k9m1lt+Kv1rdZW863ODnT70e3fUd5tnc9SPSdXr9l34ZnzvuscVT8VmvGT9rta19XX6tW4q5mNu1KX9nAU53u8+vUUlJdzxTi5zpmTWlZrX0X50FGuyHEnT/0HKXcsAhs6O2i7B/EMs3nOvhB2te4c3qPMxuBhzLiV2ogZfUFSjPy+hqPcxFUvCthG+4HPrx5/1bkZ1fDh73vMvdZstPc/lbvOSrWWq+d7dx9WXsMyZ867ep1Qn91aRlyZy1lZ15zf6HXxTq4cd3Z2d8726PUbW7XOOzVcsf/KlxL+DZJstD1mhbvO6Izb3hxy4PLzCyOOHNLV71DzM1zVWBkza89YmQ8x3WFx/5HvxmFlvsBh/PPPP39d1df7c5/2DsUoJ/X7majmpAfe8/ra5DrNxvf8/kKy83C+IzvP1YiV/XsG3Wd6zpz5d+GqNfY83O/kHp35Lg99vG/3uqEc/oXMc9LH8/jeVjlnb7DUp/rCWc3FbX7v9XQxSTd/Meonn/uZn+Ygu8835yU/43ZjVGvhtXb9Zuv8TEZnVFS1qg/9NN9unhU+nucYsZJfuVSr10YbunGUnzF09T6OfLNaT5G/Z654hN2mu/PfrVfV/zgY/7of1eA+9ck299jB/ZA22uB+V/a5Q9W4H30/gbfd/9Fx+Vr6/bM1Gtt9u8+09x1pNW5XK3lXYlxVvNuqNXJ/JfWZxVyhnTF2Ykd6xteBq2o9K8F8YRSTdiffB0o//n+fd7Tfu2t2KFD6vA3pF9y7TxodtLR/9NFZ/ZRzNXtu0l/FXynGXdHdtaxIzOoQlX0mz7uaYxa3sp+Z48g6Z47O5lqp7QrN6ljVVXnQXfN9tXbWKcn3gdLtbw53NuLIWEf6PENn6mLNMoe3uQfs7sv7FKTN2x999Cp997Po9T/7C5KPfYc8/zPm5uNV7U5nalsdQ8zGWakjY2btznZWd+SUVuYj0uaa+X+K7p5nku8Dpbf4yeEfxf9QHN11UCtRx1Xq5pPjeJxQG8lGvCCO/9m9YsSR2qs+XstP09X7e6dWa/Vz8hP1znNj7d/9XD17DY+Ml2tIjiqXbCP/irzfbP9mfuUiRoxqk02kvbKlGEM5qtyubuzq3iVW5lvdj2yumR9lHerH171Oisn8vm5u72wrmq3RikY5jtYlrdSm/E6+D5Te4s3hykI8q47RONRZxXS2KufqOCOtxPyu8rX1+6tU5axsqNqrjM+Yz/6+r9gb9vCzVz9LK/vJ3o9UxUDaR9qNd63M5ar5Vqr6VbaRnMovdT5x9fMpKnuqGne17xHt5E7yfaD0bT5zeFRV/ZA2v1bKzfZYv5/p6sMq3ZHzHcU6j+ZLzBX6Xdb1o7nyXNHmerXuyvvR83XkdeRZfZ51zrK2K19bqzlA2me6sq53VZLvA6Wn/p3Du3nM8etu/s/Nu38eDuTynIDNc+i+iq24408HnM25WrtzpM8ZNB5rPprvbG93uGKvZmfxLl417k9H6+pn/xl/bufZz9q74+vxDmvjz1pVz7P+JBOvVztr0r1eKkeVJ21VzMprT762Zp8qx0rejtU1ueI1P1kd+63Id4sVj7Bb5b8jf2z+33zZRiJ9oPv8nIHHAu30r9g/+rdesXarn6uo7s9oNu6ZcfJMSneu4Ufz/XQ/+yMb99LKHilmFLdynr+Lds/slWe8Wscr869I46mObtxRPVfVekUez3FkLtKROugzeyZExqhvNeaROqSu39HnVflE5at0dJyZknwfKL3Vv1autDP+Tux319l1vVKvWPeVMd9hjaiTa8rtfl9p5B/5fpqY6xX72+VgjKqtPrS5PkOz+b7DeT8iX0O/93V+d33Xta9UzSX34TvP9yftVaWV+SX5PlB6+q+VH4X/uj7q+XWdceWvCH8Ssx99s85nWM1xdI9Wz0DFyq9p7vj1wFHuPsfPfE7O7NsV3DHXnFOO0bWfue6z8/xO530HX0O/13zuXF/f89mZnvnfce2PPqc+F3LkPjxjvld8DavI+eU4Z8Y9uuZXctXePOXNYbVgz3xR/Q5cfaiuOCBHcuw8WKMzMFuPZ7w4XcHsnLt/J/aVvEsdV56BnFOev9F59DN/xXN89WvBd4a1uGNNunNcvYbtnPmq1jNvOFaoxjxb8x1rfpZuHc/Umq8jZ15X3uW1Ec6sy+1vDq9c+BnvtjE7fOfa7+DK9dAD8o4vdB/OceUX3DwfR85fdcaOnLvPa8G/YS1218TXXfdX7c0KVa13ft0Td5wZ5SRvt4Z3Uq1Zt45H5+/9rp7f3d8QrHDmXGy9Ofzj4P/k+UyB78rKxncxO+t45wHz3DvjZKy3d14E6Tdajy5mZQ2J0fn7TmdwZy9GMH9fQ8/Nfb4oXjX+3dz1BXc2/3/+859fd3+HM+Znk48/5Nr/BN55PrPn3Wv3/RL/+Mc//vZMKPauud65hju5fb1yPcTKa+idczlCV081P3H1/GavT10db0N+CLHiEfbRAe2s3U7sd9BPm88R+Rr4faXHC8+/7omF9LvwV/f0Edh/kro12VGVY7Ze2adrk4crEiu1C2+v9HmFXlFXrs1ZeT7NZ9bmHrl/Jo/1+3fUK+vbOVdH6zza77sryfeB0o/6O4d38Vi7r7s5jwP9dTf/TsSZxe7UcBcrNTD/nbnfySvWrVqDI2eh69PNqRtvZ+zfldE52T1Do58Y7OTKfbvrJ6VneUVdV59pz6f5ZP70J1fVo/PBGfGvJdh2z+IqVV7Zrl7nHXbO1dE6nz2/u/bvFvLdYsUj7Ntp5buOlZgrBJXvjEY5d+c2yrWjK9a0yvGsvbparCvXTu7nnutHY12xTlfkQDqrXT4YxXw019Vrd3W+1Lu8fnXzrOxu8/ujWl2DK8b6TnrFfJN8Hyg97SeHj4Pxdfef+O/eR3E7VN91ZO7V70x2aqpi9d3Jld+hMMYo58rcfN3P1OdzZtydNUuqz3TtfBd5N9Xc3Ma9rtWf3Kk+a+Jx3K/8uZ5VzuzHO6N5XfFsjXLsrp3OKntH3z///PNf9/g05kru3fHFkT7fiSv23FnJpzV9fB09tLbd61eVC5teJ7jXNduO9wH6gNqaZ9oS92u+CX2qtZCNPt5X97yu08f7Vn3kz/xdbcTm3OjveTLG24nnuIurz/Jl5LvFikfYpboj553aqfdxkEo72sklrcbPxr1Cq7VUOtP3Dh2tx9fZc/h9ZfP7Ss/Yv5+o2bqe1e6+dPUoD9DWlfZH7yffG9A9e4nvnVTVhY2rn2lsXN0P6ff7FHDvvjzzXR0CP/dcq9oqv8eQR+DzmKqOWdtr+45K8n2gdPlPDh+L9nXX87bvlBt26q2+Q3ys/dfd/txH8Z43x13ZB8dzdZzZt1ftuc9La6K2VNXDmo3Wwtd5Nif3z2K7nyx8GHP3udrdl1E98rk/z+aH98FfI9gn2vrJ72ifVxi9xpyhqgsb1+pM78yniuX8ylf5Nd/Rs1T1UTx2ruToxpHf98v7V/HC66piyJd71uUDvt6I7Cve/Zm/5M2hJs7kRweg46e/MHaHqDowV7GzD6pjdtBfze4ZYW01r9WzeeTsws76XXneqzN057n6cIzR2bpzv/KsaSwfL8f2+N/lHI3WAHi+c+2OrtG7vN6O6pAP/6ze6nx3fVbHPIL2LvuPnj3Fjl6PM1dX2yiH8HF2zsws763kjxIrHmG36o+b/ufS76oj830cktL+HTWbv/uZd84/Y0Y5ve/R8zxb/5l/V8xHkPvqMaTZXnx0TtozSesssGXcFfvgYyBviz///PPXvWrwNn4/dwLfd1W3rsxfpB2Br5nHCmyKgYyTrtjfn6Jqfe4Q4zxj7asxZKvmmmfE63S7IK/AjhRb5VlRku8DpVveHHZ9OvuzdPX4V+aDyvfTxCHO+YLb0M7Bv0NdXWfV5a3m28V+9L6C3E9vC/dlu1PmEO5PCfqA+/xeVD6pOpudvC+4/2qpNh+jqtWp7HlfyX0VO2v00UdHJCr7ipJ8Hyhd9pnDR/6vu/5Hr+Lx0HzdvQav8yzVPI/OT7lG6/Yd6dY6f8zPmv3ENVglz83Or2k+vDfat9xP2tUzsrLP3k/31bOTMULjVvHc+7MI+a/mq7PZkWN4+w5WPw+Ytfia5LNYtenrayzIoTrS97szW1e4et26cb47nMG7uOzN4Uqhitl5YbkKDhsP7k/nVS9Ku+OyFytn4lnnppvD6Nxkn+rFyGMq/+783u0F71VnbsRVazSb25lxjr4eqR9npsqRNSuGuNGY+UaQPO+4vxVev2qunqucv++f+pBjtE7gMdx/l7W6i27+uRfdax7ruPtc/e7rfjVP+zuHFXduph+slYf8Kna/yN/Bznyv3INnrvMRVl5sZnMgx5l18zNydM3e4Zw577j3R9Yoz4jazG1lzzNmZV26mNUzprgqdpSXeM0v+2Y/rePKPO5m5fllzzWnnZo91n/6mGujtp8r/Lyh9Pija5ZjfjdedVa6cd/ttfK78NI3h/ld6oiVF4bVmJW4d2R3DTL+jz/2/uf/ik92+t/xIsH4K3OhfuJmLxKer8tNDp9bzrP6I96ztchaRfVFoqurs6/gfas9X+VMDTPO1DWiWvcOXq92+hxFfzTbz4zG0ri6+ri6Vxyx+LMvKIfH6zx7rOfR+VP7GfOdobGr56rD5wRd/fnHmdVm/kJrhC/XR+hcKMafV84KcazhClXt7wRrscvqGpB/9np9hKO1/5bkhxArHmGlHgtd2u/WHeOO5vkqeU3dPWJNgPuMcdur9u8u+dxWdbbP7hrSl2uqs38H3Vn7VWfVn5NRG3mbmGzn9WoB99iz9ivlOXNNfro0X6A98iPo2js62u8d9IzanzFG6hVj3vXsJfk+UDr1k8M73tk/6vy6O8djUb/u1njld2uqVfNm7lXtqg9/VSt7IR9+j1Nf369svwLmcxXVuvgY1XhVn12unMcV9Tyb3WftCHed1Z287A3zpb3zG5AjaBzG8vPhz/xd8Dpx9bO6ymzc3bpWzir72e2v2r4nIs9EVddOrZ5b/Xbn+Uq89jOM9qoao1ujKs+RNb1qXju88mv0S3+tXKENmD3AKwt2dFFnB6by7x6yCj94dxwI8uf1u7LyIp+M5tztYTVO7tXOWv6U9Xc4r0fW90qOnAmg9uqNgFip/yftqc9F65rtZzFb0901X31tJa/23c9Etp2qFmy5hjuo39G+35ndr4PdGlV5dtf0mWf+XTj15nDncxSw0mf3UPjGndlE1aYDcyQHXzx2P1ch+MxLvujk4d05zO9Et56j+ajP6Avy7Iwwpo+Re+N1KQ6/21fPYjfHCq9jp9+74vMZ7Rlz1bV6TkZrUcUnK3uVz9pK3qQb52z9r0B1ed269/bsGb2C7szcsWbkHJ1TzZl10DnJzyRW+49NeSX1Y+3UjxyC3Dvsxr8j1X5W87pzrkdzr34d+FHk75krHmFvp6zrsel/a1fyPn6PyOE+v6/aM3un3fh3VjeXzr6iBFvGuUb+kW9Hfs5Etrkf2WZ9Ou3Evkpi5VmsYiDtd6gbp6udeK5uX5nvuyhrhc6fIpbrWZHnWWt4ZByn8kvKm37H2x7jetYa/FSN1vZOvWrcM0ryfaD0dr9WvoPH3L/u/hP3+XcH2PM75+476co+GrfLc4bReK9gNsfZ+mR/tdWn6zcaT77Hi+9Xq6fK7TY/I6PxoIrZzQGz2JX53cVoX0T6u1/NPYuVda/mM9vPuxit7YzRums+PqfRXJQn53+mLkG+Z6yh8HF2as91muHPovrNnk3V8qw1+Kns7M9ZtJ+cn2eO+0y+1ZtDbYY/0KsPd7V5sw29YsOvyLE6R7E73uqbiVkNO+N6rq5fvrBK2OizWrvTvfiemZ/nHMU9g1d9cVndi9X12Tnzu1DryhijendqvHM+K/g8rjijWsNXn/WENd55XbhqDozt+fi1MjZ/U16dhzO1vPp8PZt3mK9/bOCVHPk6uMpL3xz6xFYm6Q+YNsbbK18Yq81ctb0K1ZKfC1ph5fM6szUjh6/H7HMjszpX1lb7qhcAz+W1yv+Pf/yjHWt1rar5XbH3uUZdPd/9RZ15aS983dRO/FntUIzyXLEHM3bG0Dy9fu3vTv+z89E5UQ4/V6qpehbvJOfBuuh691kezVc+avPPB0pXMNo/9kavT4wp8frE65jq0lpxxityf2coxv8eptor/b47o/14BlrjV9cAt/5AIH/PXPEIu0WQ9sfi/61dxXxXdXPp7K4qprLtapRj5LtL7D+kX1IMVP6zuivvT1TuF2ScK5/xd1FV12gu+LjO7FfprryVfE0Yl+vo/iqt5MyYbF8toM3rUca43+2C9hGB30PG/kR183zV68qrxj2qJN8HSi//tXL1DjzfDb/Lu/QVHofk666mm8vROc76Pfb9665nlEO+lRzJmT7sP3VVuW79junB0f34sPZTwrv3r2P0fOqc7dTFuVTO7rxceY689lecT813NG71nDozf8fKXD3G6zwy5uw1XCh/1uXtPBNXfk1jTsqxUutPpFu/V72uvGrcO3n6m8NXv8DdzRWHpHvgfb1WXxR21nhl3LvgBU/XPCPS6nydlT5HvnioD4Ijed6No3PwM/+Ms/LOaA2PnFXY2YMz43Ss5FQM+6x6/ZuB0f7fdTZ8zbw2sfKNSqLzvLMPGdv1lV3ytetiR6g/OXJ+R+b7nbjjzF/Bu9Z1ivxRYsUjbKiVGPRYxNL+au3M4R30qnW8elxBTsgYqRsXvD3yn1VXq4PtdxPkvfu9/QqNzu9ufZA2jSHcji9t76BZXX7m04cNOv+zNNrfmbxWv99V1beq60ytUpJ2j/3oXn239U7yfaC09ZPD7gPBO98RXvGTtZ0PYj8ewK+7MTtz2OHsh8a7+lnHx77e8l3LbFxYmV8Vo7oloe92NR7fEVdjV+eGPuqvD2YL+pMDv9uOov584J1aReallu+A743mQbtbr9F+sx7E0AZvj/Lcif8x4hm+HqJaD80Ju67MMecuKtur0fxG+6I58ewRRwzz1VXPWObx9biDUa2O7Fy5r6DWnbo9H/mrvlmX4nQW6SNhH0Esr52CtZddrz3ezjX6Hck1UNvX7yjshbR6Xr4V+W6x4hH20UOPQ1Da30F31NblPHsmlLeDGL/vBHm/qp01W8mdVDHvKK+VNQHsMxErfH8zDu2s/ZUajZv1Zts18r1qbkd0Ra0rOTLmyjUa7QXyGL9PjXxXS2uwMx7xDusI2fb+v6NyDcBtv6OSfB8ofau/c/hqqu9KOx7r/XX3HFTbbMzHC8fX3RrdfM9+l6TvbB3lIydzUHs0H83F68j+Yne+HcrpY60y2493JPdmdQ2PrM8rGD3DV80h1/CdqX6itUN3xmd5rlyjK8/es8+xj7e7Zuqbr/vefvZc3o183ab9u6/LKp83hzfxrAPoLwyM6TZn9IXxCrpxQf4qhhdF6vd2xpPDXyiJUbz3mc13ZT12v1gyB8j635FqnWH1i7j3v/ucnWV1T3IvE89zxT5fkeMsO8+E6tUaVX1GeXKed8+bOqv7u8fuyHHV7tasqtPnALLla+mz2H2dvButi69Btu+i2qsKxbzbmiVv+ebwp35O4srDwBpVBx7baLw7DmZVi8ahVt5o6KpYSff6g7E8ULL5H7gmp8+XPP4Q+uf8FOPj6n7lge2ghhmMm/Hf5Tyrdq2tr9XKZ/Q0P5+7rjOqP5T9LFb3cwRnGPye8zlCa6Z1Yq2667uhuvQmRmdktI5+5umjqz/naktaL8XLd+Y57aBOjeV/nFrjSiufEaZWcfZ5Zs68GaQWwRiCNQE9i5oLayef24jxXLu1qo+rQz6vjbnM+nWozxXrCqyHUF5v34XG971ImB9x/s2AbF7/W5C/Z654hL2VHotY2p+pZ63L2XHO9D/TFzlu8xi3i8qXe652RcaM2jNlvpGq2Mr2bK3WQFyuq6+Z4N7VrTO4D+3uxXdXtUagNuAH2u+g1Xo8jvucbwp/5btaPo7wvRHcV5r5zyhzJ2n3WMRcOj+q/ODrUcnBNutzt7yWHYln1V6NA2m/W0m+D5Se/qdsPrpW1dpXthXp8Hrfow+N53A8ZkXZp2rDSq0784HKl1qNm+mqPGh1vsC9+46cAfpA+p+lI7Wv6MyadO1cp5n/nUWtXLkXGdNp5t+R5/J1ha79LEHa/Fr5KrvmJ7DlOcKWMQ52yLao8r5KorKjd6rV9cq6knwfKH3+tfINetc1WzmMUPl25Dl2HwLvm0qf4/ZOV8dJo1jxqhcBxhXY/F5SjNuy1pXauz7gvmcJ/F5k3F2Czpe2XMOMyfaztTo+cbP5rJyrK7R6NoG229O2otX5OW7zGBfQ9vlgQ6Kqw22O+yHbgriPXqez+5Dk+0DpbT5z+DiAX3fnP9OxgsbzMa9k5/MNV9VQrVnOceXzY3xe5XFetvfB+2gNGJ/PG3ktI6r1I6/qYxzlU6ykuck+G2Nlb5SDdVjBc+b48vlnS54J++1zqebvNtZRcJ2R86OtcXfWcYavLfduq+qVP+ece3QVysvZ1LyrtRa5JlU9GaNcnHnmyTOxy2j+ntPjVmpWXVWc29WWOJvysWZJNcZRfFzqYX9k9zbrLMmmK/j9iJVnXuMwru+vryF1iPwbhhLjUDt25ig/NqQ1IEboc5iekzY25UGMU6HYGYzxTKqz5cz8V+PzZz1212S0DyO2xsl3ixWPsFvU5X5MoLRfLY0Dlf+ZurKGK3KJlX24KmYmzwHud7tI345W+q/EIM5Z5au0E3tW1d48c/xO1EUtrKGT65r3ItueB99ZVWvYqRq3sq0KKl+lUa0Cv0h/ymOgsnNf+YT73VfZXbMY93NfzZ8z4e306wpVjpmyD3jb/ZL3ESvjCm+rT9ogY0QXg82vaX9XVWvwbOX44LZnKsn3gdJLf3LYvftd+a5rl8cB+br7NxqH75A6Huv2dXcvR78TqLgil3KM9oF1Ucwz1shrYc80ro+NXTrDSv9RTJ41ztkqXewd65x7TO2MVT03V5H7x31ez+A5fF25v3N+R9mdN3Op+lVnURBb+Ufj49M115B2tc5i1Mfr6MbPWj13RVdHMno+VUuuST4zR9FP4oSvC/i4jD0bt8ojsJHLfwLobbcJz4VN18z3LnS15P7mOboTasq1VNttb0m+W6x4hH30RD0Ob2l/lr7bnh+t9xnr7LX5/bvJa/P7s7ojF1T3HiuyrT2H7PMKnRmfudDOe1GdccE9frfNtPLcZG3eBnypzue1CveB247Ic3Cfc+nUxQhygPvynuvOuJC2mV+wrtmvihVp81h8abtTO+MJn++dynFW9/MZSvJ9oPT5I9gbPDb36+5nU31H8zg/v3QlV+U7+h2YfyeuWlb2d/cMZG1Xr+FVUKfmp/tX700FuXSV2IvZGMzF42Z9nsVOHdXZq/p3e8cZp4/a/HSqgz7cr5KfT/Of3ug6qrvyCZ7Xrj825dmp1dfVc3BffdYu8/u6Op4HaGcf3XveHNfrBGyKI5Yxpc4PsnEGsGtc4TbhOUS2BfHe726yhgqfi7/u34mPw9grtb4Lb/HmsPtAqA529UCscKZvBx+iviM3KO+zDm/CPjA/nyeHWocc2wjvmzCOcirG938l99VoTNUyW3fFre6NYnMuvOhCFbPCkT6rML+s9ZVovtVrhGr1F9tZzb5u1dpfta7VON1r3A6ab1ej7P7H47UWvh6ys1a6l+THzrMoObLzukd/zgjxmpv3032OzZUv0vTxfuR33J991M4vuvLp3tuO9+c+X9eVl7VR/vyD7bKTn9dDcoD+8Yjs5NEVqS34hyGge6+dq/A4RzkyTm1d6eNt1UsfauGPgKtNLtZVYM+cTp6BXI9XorqYA3V7rR0rMato3NWvHW9D/iix4hH2LeU8NrqMOSKxY58JKt8z5WuUpJ12qsrhfvdx/4y9eaZW5+Ok78o1eUfN5pfnSG3hMasC3Xse8LiqLuA+/WnPe6eK2RH9uI7uJeYraLsfO/f4BfbsU60RgrTP+lR2yX1Q+bp2NR/aomqrD/eptGcbm48LGVcJdD9aM1TF0F9iLuAxDnb30V6po6KKe6aO1sCaVb7voln9Sb4PlH6LzxxC5dtR9ZCsPDgjXVHXWUG2RRUn3O7K9RCrLy7cn13Td5LI+VTzk0107Y/+ff4q30ig+1zXvK/2Brj3awryvtpf7rED9lV5n+q+u0rUAdj9vloTV5fD1eUAz+E+7lNiVhcSu23R2TQu95XwORmTgsq3o1wTp7KJWSz3I3lc0sXdpbNjVP0h7e+oleciyfeB0rd/cwhp5wEW6btSZ/J3fasXn2zfoWQUU9n9XlS+lPv8fqaVB+BdlLV2tYPuqzPwuwhmPq55P1KuK/eAXxDjsSJtvp8wu6cPjMZNZQxtrwN72rJW983slTzW710i68AOtN1X9UGiuk9V8/d46NpS1cevLrf5fSen8rtGMelzKrvb3C7StyLW2XG/GO3nsyUqm8g6hbePKs/RHVrNn+T7QOnb/4MUfZZASvz3+4+5X/r5Acc/e6FxZqgOfT5D+OcfkNBnXDQn5ZP446dXz4E6hOfm8xkV/IFU4LMm2NTWPfXLx2ehqvo9l+6ruKqf6Owzjvab0eXNz5rkZ8d0L/m6KcbX8FX4GVlhp9YuVuvgZ0Fr4M+MJLQ+DmeRvFV+1jVJWxXD/ghyq83nq9xWjZ05NS+hvHyurRoXfA0c2v45L40ve9bGWdTY1VgaY1SDwxjqo3xZl2CcfAbUR/GINuhetas/6yQ0po8rvJ+juFwT4fGqbdQWqh2bcvheUY/EGug+11E2R20+6ydyzAqvAYH7WHPm4vE5P9lyL46gNfJxec33/csz8Ep8nn6OpKzz6Jr4uks6i+RSO6lsuxyttSTfLVY8wko9JlPanyGofMh5Za0zdYxiK9+uKqq4FXV9ha+9cL+Ue6N2xnX7B5Wv0k7sFVodz+ME8wV876jR3sxs3vb7StD5/Cr5GmIbiTiued8p90ptIIZ7GN3fJfJzParc7539H8mp2qwr8d24lbyf36/YctxK1EJc1ubtxON+iipYR1H1+SmCPAP4sg1uv1tJvg+UvuWvlXcOGeRGCW/v6ExflDk6POYKec6rH9YuT/WQSBnvbb+v5DlFN0YKKt8rRC3sBXbmA6vzW5Go7JW6cXdy7Gg1r5itia9h+kbyeMj7SlDdV/spvC/30mxudyhrOKMj9UPeI8+ZPhd4m3vWXVR+j0l/XlNup1bwGDiyRqms9RWqxq/ImJ8oJ+2536/cuyTfB0rf8s2hU/lXdbb/UXEowH3iiheNlOd1Mu5Zciq/VPmwHV0j+t+pndqAe7dXMVfpbD6ofEd1db5K/uxV/pTHQ+4vbcgxhMfQh3vQfcZfJVHZz6rLO6q/64PgyBpkn2yDt0d90g+0K+Hnmj5I37uqqjXXDEHl+8nSelTzHtm6NXyGknwfKD3lM4ePRfi6uwZ9noHPNsx4zPuXKvyzcDs1HpmPj6HPNHj9qg9f9ZmHsyg3n0VgLTT2pZ9P2ERj+xpUa1rVJ5ti9fkNXdGImf8qGGdn/1gHPqPEWeCeGEF+XfmczFGqtU2q58Y/n1PhtememkW2E83ZY7jv+mgc1kvib8t1Etob1ly4r4Jn1eEzZ8Bn44THahzP7eupHNUaEs/5Zn5iVOeMlf12urHSnnnll7Ru3Ce5ng7xiqk+LzhCMb43WjtyyKc26662pHF4XrH586tYn4vi/euGUF6dRWzqo3auje//aA2O4PVcDWdR6OrzYFzZdNW8ct7A68JPRGck5631wMY6sUYi1xX8/i6Wzl++W6x4hL2FkiomBZUvtRp3VE7lv1NQ+T56vR4vCL+ukPfyA32OKnN4m3Hc/0zl2OA2t+/COmcurqP5Q5dD7Nzryj05Ie9pV/dXq8vd2a/S3fk7VfvpyjNR7ZXnwJaCyvfuStI2W8OfLFHZXR4DuWbC23cqyfeB0o//3+fpnXv3nUyiuMc6/dIdeC13jgOeX+Ne/d3qKl4H83bb4yEp7b8jnA+tiZ8V/2nGWchbUX0HLNgb1XUnObbao3p30TOQZ8zzr65zlWNUJ+uWMZ6He8VkvHw8v1Wfq/Bz52ic0fzO1tGNewSvZeW8zvY8nwniZcuau3XyOq7es2fAnJizn09p9bn5ibA2jvbY95wYzoevmWzduXkl3+rNoS/ebCFZcGlExrBxR6lejLIGvcifHWcVH/uVDzB1aM7+RU7KF1/A/06sfLE5gu+NrxHrcucXl+4csv6M18W9Al+jI/i8QDlzf6sXeJ5fkTnErK6qTz6bnoN4xXBf1fouVPMbofijr005ltrsTcXRNVPeal7Y2JvR2M/gzjPhc9N8Xz3XdyfPtPbG10xtzgz27pxdzcrefYs3hyxiLmTii+oxo8UmH/nPUr3IUQtjHH0hHJEvCsylW6s7YZ5eg9dRPTQi47hXnpzfO8E8z+Jr5rAOvjZ3k3Uw9h1nt4P1qNZEqJazazNab5Hzlc/fuFXjel2iiuneQM76Of4m1enWa4b6dfs7qkXP5qzWEVf1Vf3ZdkbzG+GvT6J6LVpdA8WsxB3lzPw+XEd1DtkbtbF5HGfozvOxw6k3h1d8wFQLgmiP0KJ2MXqx9HwsdPdC7BBL7m6MZLQGnoN6VMtVH8xVTsbQh1tZG13V1njPwmvxNVct1XxZ79neEMOHwF9N9eJ71Tr7eujqZ50P2q+s2Q7aG86MCzTW0fmt7pfPU3Dv446eGeJYG8Q/RpjBnDWu769srI+jGK/Z/5hxQm3+DyVAOYRq9TGwC+zE6Kqcumd+Xgt9Pd8qvt7OaO29DujyXIXG9PnR1tpkm/1U+0hd6pf/iEXz1VXkXnRQ2zugev3MVK9piWLRh78YrYV8PDecEf7BHM+w1l1t8qzsw1X4a0xLfgix4hF2qx6L8zXStWNB5btKqn3URlD5jshzCcYFfM8UVPa0pZzKL0Hl+0nyOfr9Hbrr2ZN2cvpz4/38/qyEz7fCY0X3PLuEX9OeNlHde0z1PHP1e9A9cyOmUrfOP0Ur+3VEvlbVGlbj4uNeuP9OVWN1uN/jR3bmW/l+B62eM6eyu21HZ/pKSb4PlF7ya+VHLX+T3jHrnbTkZNwuVc4Zu+Pku31ve91Haqmo1oK8sl81zgoa7/GQfLX6Oeo7paw58X4eq3vGISbH/Wn4WlTreQd3jEPOlb3y5+auOStvvtbwXbzIcbO9wso5l3JN+MlSnn1BHVWM8DqzZh+nyi0y392sjveqZ7wa19dVZ4g55HqDclS+Z611jt2N63FdH7dj43mt5vg74K9XHb5+rJNs1bruMup72XOT7xYrHmGXy6n8UlLFvLMg7Y/N+w/bijyXcgBtfHdJnKkd0kbODnzZj/ZH76+j+wWVPW1Xivzd1YUNKnv13Aju8xmo7hUD9NuR9+M+6wK3HVE135GqOqo1mSnzzNooqWI6rcRD5btbI+Tv1sRFbCflgMr/OyjxdQWPP6or8iT5PlB66k8OHzX86/fuvJuu3gHzOR++q9eV75qvRuPsMuqj+Wmekqg+a8R3npJyuVijRD6tAX30GRfWRu38Tmb0OaGjaLzRZ2tURzcutQrmoLbsfJ5QbYnP+BAvn2z0k0/QfmdUX64JZyRrl026AsbV9d3XKPF6tdfstyObz0/yZ0/itaZSB37Onq7eFrmfqqXKSd3qy+fUPA6/bP7TKB/Tc/PsUUv3rIGPJRhPcE9OxWp8XlewZY5VVn6y0qExNcdck9xvoSv7rXv1wc98QDZeaxLNmfX2depgDKmLr8apbHehsaqvJY7WSPOe1eVzrGI5Nytr953hnCWyaR05Q4KvWayx2mfQGNLT1jjfLSaPkKcreSxIGSeJyv5sJVVMqmM0X+RUfjTzzwSVr5Jqn8UTA1WM2/2eduL+31U7EJ85niU/4yt15JnpUCxXxuggd8p9K+fZJXxuKeHXTu7nfmXNsIPbJF8TbK+U1+H3tAXt3AvaYmSTYMXm7ZTwfeiUtToed6c6qB98Pg62tAv3/SSJ2f6Kyv6dlOT7QOkt3xxKTuVPrTywdwqO1KE+jvuyjbxP5XetxFyl0VxQcmTNKqq4dxccWQOpA98sLqGOCtmP1imRQ/I8bq/UcaaWkQT3GoM2V5Rt5H06zWqnP7gt7yvhz1oYF/K+as9qvUI5BqRt1O5sq/K+kG2BbaSMc9yOL21nNKKKd1Vgz9gj2smzcu6SKmamfEZ+ByX5PlB6mzeHSRXzjuJgicp/RLNcTuXv9IwXeeSMfEnGduqoYl+t6guft4/Izx3g8/sUvrNk3rPKNfJ2hcdeLfJzTTv3wv2I2iH9yH05f1TFAPaRnyv3HqOr2txX7e7+TkE3X8Df2VZVrcHM7+2UM7K5vWsf0YgqHnVUsbvqSN8sXuzm7M4EVL6friTfB0rTzxw++n3djXlsQPm7+BXUj9/Xg8aVPCdjYHNfMvs8zi6jsYTXPoqVzz8LJfgsDfP1zyYQz3pIQjG7nz3Y/RyQ17iCauMzLqqNNWFe4GuVMEcf2/ti7z6/wfq8A9TNZ09o6/M5Z+r09dA6IxitL3HsD9ddfJ+OMOqnvKpJMcSpTb0+1wr1OVObr4fXwLiZN9vVc1Z99otx1J/z7Ln8XvPxc1OtAeP6GnmcxuMzedhZUyG72j5/r9FzzdBrGrWuojHYe0nzpSaNzeukkI25MA42x19rPdbh83LEgMfj93bS5U8Uw1jKo7p1r1qZ61GUp2OUd1S356TuHUa506d2F6+1Ya28BuwSz5HPVXblpB9ngj55RqQPD/LdYsUj7DZVVHEpp/I/S4+D9FXFX1QxCPxeKEcXlzbh9ncTrNpErmGux6qg8r1K1OO4fVdQ+XY1An/uTUfmXlHXL6lipO6cOJ0v7Z0YI/tA5UPAvV9dohsHCfYCW86/W49OwscVuzk6Za0rAtpZC7jf29i8vaIqD6y2ySFmfoEdsi2w7SjHgSrWNWPUp/Ihh70Zkf3PqCPXiLqyb9p+kpJ8HyidenPIIle+VYHbqs16ZzkrtefhdIjxe9rCbTs603ckoJ1z8zjuaQu3zbQSD5XvSkHlcwnOBBw936KydxqNU1HFuVap+s6Ute7UXvnThh3S7m2X7x1X2YS3ie8kuAq3i8rnMbr6OCJrSz/3MzmV/4h2c2W86ObrNm9LGbOizFONI7o2tvSDbMrZkf1oH1E3ThXrGlHFrqxzsuq7SxWVz/v8VCX5PlC65E/ZPHJ/3e2jH//mj7urX8u8M17/Su0ZwxpIrGWuiahsqxzp+3gB+Lrr0Y/lBXXn3GRXnhxf7d2aVuOPzHWVlTVxVAtrdKau1XH9WWQv8vnMtupaqW21/t01qhg9R9Tb1d3VOeqTawLUkX26MTo4A0J9tUbVmCt56afaqhyyzfLQj71S/Eof+nEvkcNt+bowQjHV2MyPHH6eJV9Tj+MqKpsju+dJ8FNfl2dnvon6SCt7cISVnCsxzE2xo+dTeCxy3J6+u6jGYe0dns3Kl8z835p8t1jxCLtUSRWTWo37neRU/jvlYzqPB6u0YzsqzzvSFWONpDqcKiZFH91Dxsy0On+J/LkX3NMWO3nRKlXfTlUduzmOajZO+r3t9yNxBkA2cL/3IYb7Lof7ue+U44DHzJR1MK5DLNCu5H6YtUUVw7WLTV/a0i/S1q1zh3y5ZpA5zqoap4qrVFHFzQSVb6aj/VZ0lCrXd1eS7wOl7Z8cPg6fMv9S9SHrGfpQ8ZHvGjzu6n9sciertWpdEX10P0LfrSLtxyh+lqtiVLv2Qzl1BthH1aEPBMsuYav+AcZuPf5ThFFfPye75Hw1jmxZu9C8GKvyg3KodsWzJlqPHVbXyutXTfnd/Wg/d2BfpRGzvXL4xwfAWu2gPq6KKmY2TufX/LQGWtccL9vVT1qUl9x6bnTv/XTva6wc9KEfV1GNUUFO5ecfYziy+975ufGadKUvzwA2vS5gq2DNJMVzT3/d+2sLbfwSOaiH/dCVsVlXUDxx2MnTjUMfIXv1/HodFdXejOKPciZn9s225ih15LrP8DNA3qr+0Zjedwb7KWmcTsnOGD+KfLdY8Qi7VE7l/2lyKt/j4P1HHGT8SI7bPGZH1DWSU9mE24g5ImeltpWYlPB7x+M8prIj4fub/qOq5uY2MWpjE25zjXyuEVV8pWo+RzQasyL93u5ErcTnOvs11dkRcJ/+VVV9hdcu3Ker/Nxjzz45X6hsAnslqHJ2MUJXagWPFfR3ezeOM5uf+4nx2pKMddx3hSqquE7C17Xyi7R7H8gYCTvXI3Iq/1Uiv8g9/+5K8n2gtPXmcHRojsip/Hfrzg0HHwM8Dnu2hdtW5aSNe+wzjdbH8zj0cTKP8PaOnMrvWomplFQxElQ+V54B983UxVd7U62z8PbI73buq3FSiqmoYq/USm13ijlmHd4mJjWrHX/XH1X+mQ06X3XfSeRcHLenINtCbeUFj6li3UY77cJt3HfjOG7v9m5EF+P9r1Ayq7XySdD50uZrKNIvdfYdQWUTbkfdGqwIKt93VpLvA6WX/ykbaeVg3SEft/KfkdP5aJ99sEQ+AOC2Mw9JCsjpVHECG/P1uJk83skYQXs2zpXrkcpxs70iJ305N5E22qLrA9mH9isFne+VtVbjYlNdaXumRmPmmmWt3r5TOQ51CWzgbbeLjO3yug26ttciujhX9km8rsTznFFHF5d2VK3Zipxsi4zfEVQ24XZ8fnWxF5UvBdnH9/O7ysn3gdLtbw7/+OOP/2hrYV0Zc6c0nmDsKuaIyPvnn3/+zdaNQ7yuzB+b8H7KWYFf8nWlDdiJoc9ZKZfPV6r2UnHUQTtjOhGbeSFzCW9LiqnGZD0EMRnHuO7PmBUxRuWrtLJX8gvafk7oSwxtQTxt0flnop+rOgOv0GwNR74dkSevvpa+JmJljbr6sGcOtYXbjkj5xWz8o1L/fJ3MNuMjIR+kT+g+c5CXWG8D/dwmsPNceZt7pDZyaFfzE7rHhv+owHPRdlVUPrU9/0wO+fDpfvY8poinj66+FymRY2QMefFXIraiikPuqzSL8VywkveIknwfKD3tJ4dQ+e5agJmg8q1qt3bwdvoc2f2wQNW/E1y5zuBt91cihuuKYFY7fpE+NPK5nMp/VFD5Uuy5t92PINvC+9AW2CRswu0jeSy4f1eim18KKt+OkirmqJjL1XnfQSL3audcwUrbc4gcB2h3dsi2ULsax+NoV31TUPWp4hz3HxFUth28/46yr6O2r8mOnNleyJ/gS3W+KkdH1R9RKxyd/x1K8n2g9PRfK/vCV/67dNe4UPlSCXY/NBWjvmjl4LEGlW9XkLV7TCWn8qP0Zzvl+yuwZRy+VwgqX2q2V7nuApuTMQKb5Ovm9pmSKmZHXnv6sEPll0a+V+pd69oVpL06q9DFVOcORm23C3weI9JW3dMGbF6byDggvlOF+6txzgiy7Xh8FZP+VTnZBs03+42UZ8ZtM7zPWVWsxO3OtxI5RPrOKMn3gdL2P0jxAVLiigW5SxVV3JXiMLvNcbv7ve1rCkfX2an8O6qo4lJO5Ueg+5X5Am3WXmSct99R1Xy97vRDZasgxtdIeP+RnMq/K+YD2KFaDwSV73dXdU68vSOo7NmGKsbBxjns/BXV3ITbXOkDz+NgozbIcStVZEzmhYxbFfi9k/FVXBUz04yqz0yi25cRnuMqVZzZO+JWztGKnMpfKcn3gdLWm0N+V69JMbGcYH5OYPb7/WdIUBN1ZXtHK/3wa/4z/PMo3h+Rw/25zisi1vNmzEyMS5vP33hufJ343AjQn3vPib1aIxdzoY/7yJExqSPrsSrGqHyVuljsqlV4Xl2xqZ3rnHgekG1FztXrdmXOhLXppHFZR+E+7G57hqjZ10S2ai5pp49sItdVbUGfagxihOcmxu+hG5c2z3j2A9lQQj/6EqOrxqnayP0Cm+N9HGxVDupZkcd7HrGby5W5kll8+lHn68aTnXn4/Uzkow+vX56DGMf9d6gaE7qxK7vbqj46V2lz0d/HRVX8SEm+D5Se/mvlVyo5sqirAh+jwvscEeRcqrnJJtK+Iqh8R3SEKg+CtHm7WhOPqfxXyseaaRTrPidt7HdCXMaL9HUiVly9bl1OkTaXU/l3dEWOO7VSn8f4vWvF7ngM8nPmtozp2klnr84EElwTj3HSTtvnI7pasXkft+0qGc23U5K1d7FudzluzzUSnd/tM0Hlk3LcKuasunV3Mqbr04kcFVX8iqDypZJ8Hyhd8uZwJeZVqmpz0nelHG9n3Fk5K/Zd0V/sPgQj7VLlQJ0fdH9l7UcElS81qxW/U9k6PJf3SfsrBDNb+qCK6aQ1g8r/jlqp1WP83s+V211pz3aezfTvCKqcids91pV0No/PNUnSN6rV7Ufk5DgrUh/HfZBt4XEup7OLtFOH9/GYVXtlu0NJFYM6uthsw2iNVpVUMZWSfB8obb059PvvpiMP2hVyKv/VAp8vXLEGorKfEQ+JI3tF9vE4fCl41RlAcLQO0H3mOELV321ndTQfeLtaM86AkzF3ivEg/Wjk29VKLo/pzhpUPgSeQ2RMdRa93dnBbS6gvbLfHlP1oVYn21DlFNgd8nofbx8RVL5OXa0Zo6uTMSONqOJTGZftziZdsa6pIzlznR2PA7et6EifHSX5PlA69JNDFjM/G5Zxlbrfq2f/1XzvrtnnCO6S703lH8n7kAOeMR/Vzj14Dbrn8yiO5yDG20JXj3uG+IxS5es0ek4E965VFJt5Ie1HRO0ix6rGTjGXyudiXVH684ysjJ3qcr+j8pzpPs9Rzqc6Z/KzXsRmP9rpp51ye8bpvqozn9/cT+brZB6HPEJXVOUlNuOrHIyV7atEXp/baBziReW/4rlIyDEam/1ym7dz7yTPl30l9el8iPmSJ/3UVSljUx6bVPNJCfqSR3audynJ94HSpZ85hMrnSqoYJFi8yv/ReVVrKzigScZeLfbbkX2FzAW697wZ9w4a1eUvFiL3hpgdyJd5RvI6Khv4fQXxnVZiZkoqezWfs+rWw23sldvPKsd1H6rm67HUJdxGHOBzfyePh66NLdsifRXuq+JzjURXP1R9Ms7b76KuLs3Hme1fpRlHcqacyi85lV9K0r5S6858HLez7m67Q4zBtVKS7wOlt/gHKasLTy1XHLyP/lO5rhzmCo+7Q9UYicdVD57PR9AGfO+kUV0rvhWyr/erfDONzomjWK4zVXGQ9h11tVaxnfxcjeSs9jkiMWrP7K6MEaPnxtvgflf6qrag7XtFO2Od7COq2hPPSw7isDnYMuYOncnf9e3WqFPGz6hySN06HxVUPimpYlKrcStyKv+VclbWNcn3gdL0zWGV+B30zrV9d+XadnjM1cr8tIEHQGTMShvc32k17iodHW/2Iq4YrimofJ2In7H7RQDcxtzcJiXpT+Ua7dYmJVUM6vyd/ZUSvh7g9wK/y6n8uc5VO/tm2+3OzAe6Zxzo+rp9p7YrlWt0pZzZOLlmHVXflLMyP1HZJTHKASvzq+wIKt9IrFvlu1JHxkjyfaD0Fm8OVw7JR8+X70vicc+Qjwl+Xz2I2MRKWwLaM/tdmo3le+M270cMVH3cX/mOyNdVdON2ArdVOXIcyLgdZc4qZqZuvkkV8yz5+ND5aScrPvyzdq6Z20T6oLKB7OznqG9ndzz2Oynn7zbItU9lfEfVF+F3MibV1eVUfsmp/KjzJ1lL4j4XVL67NNtPKcn3gdLLf62sifDBTd17+910VV3+AdjKf4eqsagj29h0FVzB+1wt5VYd4HZUoQ8dV3V5H+4RfST89KHte04s7Uoz/6pYg1G+rMdrxV/dpxy3Z38px6ikuBGjWiSofK4cR/s58lfjVmvmWpkvoo/fI6CdfXfGuVIa12vK50j32I5Cfgeb5GPhU1u1ifQL3VO74/V7DHH48Lsdn3Kk7TuLeaCK0Tw7PGc+ey5i0ubtmR1xJkQVm/5ZPhfxK/04I9DVpXuY5UTE6Yoy5qySfB8ovcVnDr+DoPK9u6ibQ0b7KOS9QxUjOz7uXflQOfjB21182t2GPW1nBXe8QKAdVupYoeqHoPLtyPdXuC9x30jJyOd4nGtEFX+lcgzh+wvY7oCx8lyJrMX9Uu6v6GLclqQvazki4e3VnNnvDuW6Oh7XxYidNRKVPVXtVYoYccSPoPJJI5+Utfq4wmOlJP1HpXEr+4qcfB8ofd4cLsqp/N9Ru1Q57lJF+v2+ekiqFwonbVV899AD7bvlVP4z2mH2YlQx65OCzlfZd5VUMSln5HMyzgW6Z41G7K7jjkS2Rbavhtw+N/A29y6n8lfSOOA2Xd12VGdy5P7eud8uZ+YX6fN2pZUYCSofgsonQeVDnIHK90r52RRVjORU/hUl+T5Q+rw5XNB3WYPdOvMwVhDr988WpM3bnZxVm5M+f8EG2s8QXPWFY+UMOCvjVjmruFSy699R0vnc3inne2ZvVqn6HlXmA9o+nzsgN/m9PRJU9rRhh7R7+6jO5Fnt61T+Ixqd1yTtHtsJKp8LKp8ElU9yKj+a+XmeK99dciq/5FT+HSX5PlD6fx6BL+OxCX+7vht//vmnVvHXva5q7/LHH3/8bX53zvW//uu/fl01BlLdLuzif/2v//XrCuqP/uf//J//yif8/tmoln/+859frb+QbYbm6fPR/snG3JSTNZHtH//4x1fPf6P98xwS6yeb+qiNwO+vhFpUu8bwPT2ias5nyXMl8gwm+Wzlfgv2oEN75eOo7WhcbKyj5q8rZJ+uXkc5OBtSNf8Rys9rDTmq+Ts+T8T5rurFnn7ON9DGplhqoZ/qk7+qFdvsXKkPeQR1eZszoXvNj72hnXsnu3Cb+rA+1CU/sbp6/BmO5PGa8+yBYpDi0FX4edUYnEUpkU0xufaO/LvQZzav2XMhzq6NxhjNzeeXbcEadfsp0s+zIJFTIpfkMTAa4zT5brHiEXaZHpP8yvoXVcyzlLXQrmKF/JVvJqfyX6Edqv7SaP7fUc5Rm5+RUbzb0+btZ2iFlXiPIY5nwMnnwtcM3I9GVPEz5bhel+N9RupiR+NcpRwj/YJxR3R+z1UJunbaRWev8DjvV9m8DV0bW+erdMf+XSGofFcqz1pF1a9SFQtpd0HlQ6LbK5jt5UrMynnINatiUvSpfGjmv0pJvg+UXv5rZbGyGZVEZxfcpz/tcMWhmWllnB11VLE/XY7aPIzAujtdX8djfO8E967O/iqN6sk1qmJSSbWuTvZHFV2cr/tROdi8dmydkirGBbo/Uj99uXY6A/0zpytr9za4H7ItaONzAe3RuLQ93m3gvln7TmXtI1HXTp8zyjVLPDbbaFQrVD4kzuSAlRxXjCMq/7M1mguqYpJ8Hyjd+uaQvlzvELlzAdSu8BiHPu7PmJWNWJWo7J0yfobHXi3wtvtnynjWNe0rqvpAtkUVJzobV/eP2iu68hydlVP5Ozk5H7Wd2XxFZXdVOXKc9Feq8jgzv1iJWSFzHNUVVHlHcnw9oIrrYlYkcpzch0S2bq+8XcVcJah8Kah8dyrRegj82U7NfFD5kRjtA1Q+CVZydDFQ+d5F1D6qk/2CKibJ94HS7T85/OOPv/5+F5OicG8TsyP6V7b0qY2AtscR622oYp8lH1v3jtrSkTU8K43759fft6IOtXX1ONWGH5+u4GcEO3ErUixjuI1asOsKuve6gHuuyiGIow82/CAbY1FLivleKR8XZUw1LqR9JOV2qhiJuFFNV4i8Ob/VMYmTPIfaeYY64ScWjXB/9dzsSH2pfTRuntdk5Wz6M6G2+tDGRg2dzWvNNjHuJ8bb7gfs+Hw+2T4ixusEs/3MfqPYTkf6pJQDMh91EePtbh3lSxtUPkl2oTWr/BKMfKLyI+jqmCn70R7Nq7JfqXwmpNwbj8GW5PtA6am/VhYqEKqYXYFPvPJXPsk54j+irtZKPm7icfgzLmPuEGQbKjs2t1c2cJ/EOUq7k7bRw9H1Tfsoh+P9R9qJnSlr82v68Qm3rcqp/O8uGPlErtkRHaHKM6tldDY9bsRsjCpGZFuMbMpRtYXbuK/kpJ37WY4V7VD1dzmV/1lKKn+2hdtWBaO9GPmh8klO5UeweyZEZXeNqOJfrSTfB0ov+QcpuiYZd1RdLo3b+VYkRoe3sp8VZFtkLczPcf8R7awZUFdSxQq1s/YqTmCv/J1vZMtxve39ELjN1wjctqLV2Fmcxq3aVT/HbR7Tyan830VV/bMzsKLcB5RgyzjJ9w4yBq1ALPOb9SPeBbO2wNbF+RoB7S5m1ic188+0Q/ZlnZOM25HP/4hGVPGSU/lXBKP6ofJJMx+sjDFbR/au8iFioIq5Q7PaOznZFvk+UHrKZw5n2lnomf8qVfjGCI+/Q+D3TsY53SESlX0kqHwuqGwCW7XfCbHpo517IWh39iRt5BT0SUHaqja4r9OZOLf5/ei8wiimk1P5v7P8bFb+d1cHvuq56SBuRU5l684ZrJxVvxfe50r5Geio+qWcrlZR2dHMv6JVZn3c7rEzwWi/oPJJMx9UfgRHz41zxdkjh0jfVUo6e74PlJ7yk0Pwtl9Tld1tV2zMiiqquLvk41Ws+HblVL7Z2ld+2Rzs4H0S7JVP4PMxuj7ZFhlb3Vfa8c/WDHmfI8pxwG1uF/SBlVqhsycZ944C7tP/3cQckvRXMQlxnaozIxtg83vaIm3ZFtkWVQzj4jsqZyenU/klWHnWzuouqrFGgsonwa5Pcio/gp11dyp/py6+s18tqHxSku8DpVv+CPZj8f8m/8ONauuPOeoqHnX9xx9y9D/yCLKRr4IcxGTOFdSH/hJ/dFJX5HjsnWT+rCVrrNZvhT/jDxHnuMqbfzA1qf4AsGxek/ZcyCbpj46yjtQv+Rzlczs+5ZKPP6orqY3d42XTFZv6yEYsfYXuRXeOlGOG18b9CMafxQGxxLOOQlfm2SFf7tfsjxfrjKifz19rpPlVdOu08nwyl44jz3hHrtVsbOfKOq6Cdc/91/75GVmpnbPrEtznGZKNP5Ls+889/ThHtCVvq1a1FUfbUV1+7nSf811Ba6D8jsZF+fpFvItaNL7PS1Qx8vvzegWM42NdDfOD1TFYv26+5Kz89F0Za3SeGUNX1knkfjoaGzn0oaY8Q4qvask8M6ocWWNFVXM1vyH5brHiEXZKzqO4MmaklT5Q+Y5K4zrp7/CYI/NNZR1Cdq5XqKKKS63Mz2PA/StiDSofpL3q42QbPP6IEuYPGetttLKulbp8yOnsAruvoci6Ojym0tH5ua7IUQkq33fWnVTjpZy0eZv7zj/D+4/kVH60QsbPziZUvl1dgefjmYduLqKydyJv5ZOczpd294nVda+o4lOrce8orz3J94HSU/73ebyL5Z3so5a/aYa+c5vFVu+Ud3kcrF9XxuE7RpTjy6bvQnJcrzW/qz5C5mA8H3e0NjOqvjmnDmobjc/+CdZMbWysewVx7EWF7JUv+2gcj1Xeqi917UCdVV++Y2Usj6M9YuZ3ci4O6zyKgapGXf0sel3k1HUl/wpeg7NqE9i5js7aO9DN4wq0L5zFq1HdK7Xn+fC2+ruPfO6fMZofNaIEm38dyDjVks+zpD7Eq+3PSUKMdJasr6Iah/GrOnjdRN1c6LdSg9PFj/aOsarnF98KVazGTXtX485Y78Z27fluseIRdovgseH/YRMe+9F8bRxf05kqqriZxGhc8Lau6sM9be4lcNvIjq+yCdo5LjHeXtEI+XMcx23cV7bRul4lH+9u+Xy6cUH31fyrHFxTnd1FjJMxlZ6xN1fqGeSYu2skcn9XIV5X5dihGm9Uu9A1YxjXbRI2kbWNxkmtUvWttBt7tHZn5s+clc19UPldXnvl/x2U5PtA6dRPDqvfh++gd7KSvjN5bNgvG+/ieZcrO74rIa/r3fHvrLrPMyA+z9LNy+2KV+5ce5itDX76Pc5aOTbj4Cde+49dEvITJ58+w+T5NH9qVhyfpSJGuclBHuVQPHaPQ9kWupKDdcdPHkdjADmoU2LegryqjXuhq9eSn086++xVeF1H8Ro7NE9/5jVurqt/vixz+jrpXlRrnjEifYyrGNbb10Ft5Hi7+8lKBbmu2r+sawXND10Bz5WTnw9cWSPWRlJtfFaX/VM7x6kgXtcuHruu1C8xvu5Zo1HtvoZev3Af+80YsDoO+HpUaI3I5+Mn1On5dPXaQLVnzY63q/6MJVQT8dV4XnOOI2SrxvB+mVf1M0fhaySYX5X31cxeJzq/zyf3b5l8t1jxCCv1GLC0361XjfsTBZXvjJzcL7Ud90nYIP2dL6nsHu91ZKzHcJ/tDo+HWZu8CTbiEaR9pJzLHRKjcaDyIaEcDm38ulY2cD9kn4yhrSvtvN9R9sv2OyjXaJfM0eXF3ol1R0ll36mdvuTJXG53X9pRQi1VnK6769Gpo4qdqaKKQ1D5EMxsbofOt2Kv/EK2PFvEpe13UpLvA6VTPznc+Y75Sl417k/Ev4MSj3PydXcOz5nk/j0e3q+7f6M6vDbFyEZ9+LxejxfkdbvHqw58XV7FeB+HnEnWJDy/vvv1tuC75MzZjb0DOXIuR3JXe+Wo/mp/c765nzCqKdcm8dq6PFlbtoX6+ljVuJ6/WxPvN1u3V6NaUdXu0DpUZzd/6jPaV+H74LFeQ66h+szqUx3E6JrnzvMLfGkH7yuIy1qoVTbFUwfaRTmqM+Tzu4rurGbtrIXXRgzrnDbHz4jnFWrnGRJu69bEoYYkx3tnujkI1hldSr5brHiE/Yeg8r2TvkONP1lQ+SQH2+PAf1n+wmO5d0HlS43iNK63R7GuDvw+n+wzawN2lDlF1u8Sfk119hRjjOKzNtr4uQfs7vc+wucGactxaAtsxGaM27l29z6u27nPOjLmCnk+cP+OoPKlRsz8kDldjq+zgy33dwdyVHkqObn/LpFt4bZVrVD1m8nn61SxnZzKn+rinPRV+1LV3vUR7vuJGp3FkZJ8Hygd/smh3sHrsxriUaBGm76LvwKNwe/ZV8Zb+Q5Becj7jDlczTvVrM8a6SxwHrT+/tmhrJXvECX8fCaE7xJl1950eym7zqL6SuSpPo/hOdhvSeRPkbrxHOpyed0Sn5XyORLH+DxL6ScXNYJq9ZxdHCiffMRXcbLnmgi/Z42UT1Rxvo6VXzXonvqF2hoftGaJ56Kf9wHFSeRgPKH50Re87WN4Dl9j9kpgp5/WhfMrZFcM51P3uhIPtNMOsvveKD+fs9X4jDeDHA7zSnu2hcbRXNSHflDtBfiaKI51ANUlG3ORdI4UQ16fp+zklF1tavI4kXZdFY+UJ/sAMd5f8d4fCfnd1uXtYG2Ys1AOoXVXLhd4DY6fGfKSD3xvVqlqENSQ56zL3+UR2n/ZvV7Vmvg4vC56TtXSob5Z6yj+3fDX2svJd4sVj7C3lUM7Y3bkVP531eNwf1X9F1XMswVduxNUNnBfJ6h8V8vRXlR2j0/RBzyH291W+ZyMSb/IGOE291X2To633e92zi+2WVvXUYz7hdu4l/BxdT824J4YQSxKG3ht4DGVPf1Zm9ch8I1Uzc/l/lXNqOLSVo0Lacs2pM3jjtg7OdhUP2Ss+93XaTVOcka+juxzVEfOjcup/C6PYVy3zZRUMT9dSb4PlA7/5PCR72/vtl8F3yHwXQLXo3g+5qe5vhuqzeviuyz0DmQdtPPc5FyIkw175urO3izPXXh9/p2u7LS9jqyH7wDJk9/de46EPloTr8PXCLv7RRXTjVHZhezuyzoqcn5JNV/Pib0bR/5cU881I2N9HOV1f7WGQjFqS6P9lJ8c3l/gdxjb68iYCsWyJlVegT9hHOHzFaOx8XEmkNqe05Fd0hplbm/Tn5wia3M8TozGSYitxiSHwObz8z4r7NRC7Tnu7phn0FjduZlBrcxhpV6PyWdxBHG+ZivjfQdma8A6b5HvFiseYaVGvh09DnRpf2ddNfcrJL7TGorOLiqbzy+p4oXb3Zf2kTTubh+nsq/sFTECm1P5qzWi3fkzj9pArMtzIKDtOYXnFPiyL1e3Azk8rhsHm4/rNt0j4ddZTuG27IMNuM+8eY8fu19doHvvU7UR8ZJioPJX7VQ3jtQxi0m7x6cg63DcnnLc5jGupLJ7LQ62K+Ss+ny/E4/bFXS+7owIriL9H10n1pdr+px8Hyhd+mtlMXrh6OQHuPKjmT8Fle8qrdZ+t/JFoIr5LqrqB9o5Xz93CfYdJVXMSI7X5r60eRsbVPPLtq+J7NUaiewnaFf2maq8XAW1g8dwP6pNuD+v3Hc5MibbAht+bH4VxHA/a0PeMw72HDf92Lh3e967PI+UceC2TuBtXXMMfE5nQ8xNuD0FlU1kLVVtKWfFTq1uk5L0zwSdr7OLzl6xsiaVnJG/8knJ0TrO6FXjPlOj+QmuTr4PlC793+fpR7RHfrysPvpRLz+a7xj9CPixIF93/8Z/bJwfMlV8pwrZyUGMrl672o91/nUl5lmoDuYrUYvXc8UHba/IQT1dXfrgddauObHGEvP1c4NPuD1zdfABf8UK9fcPa9OfGF3zH+BIgj7gPv5BA20gj6S8Pj/6CNlVF2MSh0/38gnsgnvvxwe8aWc+1QHy5XwZR/iY5KHtyOdXx/MlmUe1ew7fK+XxdSaOPt72deHKHHwM1kc+/MQwrvvJJ5/WzfupNl0Zi3EYw+uUjfngl3x+2GlL6kMe3XscNo2NTe3q+ZaNvj4O9xoD8Kk25QblFqxBVQeQo4IaHPJJOV+vzWFsyftjo6asVVJO2TKPbPRhb2aon8by9QHWndxOjuk2yfNQk6T4la/RysEVqS/juV2o1vQxL0ltr2G1jqNQQ+rucd8B5qf5Jpr/MvluseIRtiTxKKj0vauE3zse10nzHfEu6+FUflcy8u/Or6OKlSDt1biJx1R0e+c5u747ZB20xcoY8metVR+PoU/mz35V3uwjKhvkfMjp8d4/Y7zt4Mt4rj6uoI0tc3ofj6n6VO2qj0S7IvsI+nDvdq6Zs4rzOgRXgT3HybYE+N3nIqZqg/td6RvhcTsCt1XzTREDlT9tTvok7yMyR0Xld9uOqr6VrdJsviJ9uYa0PW4kYrmuqqq1E+z0+cly8n2gdPm/Vj6y8M/arNlcONBOFddpRBV/pa5cwxEZc2TcJHMIb8+0gseO+uFD1Zk4Cjn93m0jqpjsyzrCyn32yb1g/tlO5APu6ZP3Yjevx+fVY7gXVU5iuj7uczKGaxcvqj6Ce++bNq/d40TGuk+4LecrurbbhNtH8jHSBj6filGOmWDV7oLK1wlGPmfFJ+Ua+fzB4yvlmmVO96U6f2XPvCJjXq2KKu53VJLvA6Wn/Ckbp/LnQ+C+Z4oDTxs8JsmH0WPS5te7tJvfqeaSMVDFrarC/f7C4/aKmR88bhS/ErNLNR+g7TEd2VekzdvsJ4zuq3Zld7q2Xz2muicmawX3084r97mG1ZpWazJqi2yTA1Xj4ANivB9+v08qH7aci9cFfi/S73VB3ncC7v2afm8n+DOumw9yvwsqW9fHJSobpE9iHUXldyqfrlVtzmi+nR0qv9T5nM4u3JfCDytrf1ZJFXOnXjHmESX5PlC67DOHj43/peozK3wWQarwzwB0MXdArapb8PmUx1r9EtDmcxWIWvFL+dkiPjfC7/q53sVu/pyLatU8HGJcZ6g+j+Nj6jxoDNZQPl3Vxk69rDtr7H7/vJFitDeKg6xDfcgFjNNRfaYpbWpTk3KrDmpVW8rPwXgf8Hlix6a25uNt5eBefRhXbcUR43lpSyC7kM3XjBySt4X6kEM5BbUI1SIUI/voM1rkSZhf5afmDtWhGO/v83QUA5nX5wRqk1fxamt+jCd4XSDWXzckoatySNjJISknOaTcO/rjlxSPX7hdV3KCxwJ+1UI96ivIhc3rpU0s9/LxbErkFcxHcZwR4jq8v6+z1J0ZxpGIQbKRUyInPvr4uPiIU+3UgC+/Nug1gHhETsn3Vz6Qj3hfR41FX+J11bjgfV301bXLKQnZ/Qr4M1bSHK6ANWRdVJ/XznjSXZBbV4179VjM7enku8WKR9gpVTkq27P12MRhHR1VLOpyOun7CQLNv/JXStLusW4Xnd1Z9RPjbZeTtpxv2hxseUbErE9CvJO2qg3YM0fVRrDaB3zciuwvsg/tKhZbNb8Ee9dnVKvnHOVXDl0Rdq4SMU62Hfo5o1orGNchb+YG97tgZINsQxWTcZ0d3L8icNvKOnr/3Dt8HrNicwnyVoLOLtIndTkdjxHpx+cxkD5Ujeuk76hm44iM6dbkd1KS7wOlS94cOp2/sj9TswMhFCPSXuExu6IW8rzzYXXS7m1UreFIUNnAfe7v7JDrWlH53Tbbm4yXZuPiF5VfNtZRdHkqexcrfFyh+7RlW6iNvO14mxzYfC4VmWvEKNZ9XRy1ZG1qj3KL7FNBTOZiTSD92QbZkaP2bF2dzEHbbY77qN1t2RZpyza4PdX5kyrmiCDbFVU/oXaeoxXluqZyf90HXQ7R2WHFLjEGpN99ovJfoZXcTuWXfM26uM7+Kl1dT5LvA6XTbw6dyr+rq/J0Ws0/o+ojzR74d9asdqEY4TaPcbuofCuqcD91gPuSro9T9acPNo9JwawNnR3S53UkmYt2N98qT9q6GM/pMbpH3uZ+l67PKKfbVvpLzKeLB/fP1rXaK2/rPtexyik7crINlZ1a8Hl7FO9UbbflGNx7jHB71iFVMc6sdlHlrQQzu9+736n8WUdVe1erM/KJlfk6I3/nq+wa11mpw2OE+1aUfWbt1Mz/OynJ94HSf+k/j+B/8b//9//+uvs3fF5Anz3Q5x7y81GOPgPwf/7P//lq/cXjUPxHn0c9/8r7bqjeEaP5/xS0BvqcjPZbMGftL5/9EfKz3+xz7neu58760VdjMq4+SyIYS/BZE0gf18oOmoufb68bW55v1sP7KEfaBG09Rz4X2RXj9Xgt+PDL5jmEfGq7jbbnFWpXY3KvKzE5TpWT+WIjhs/fMJcRjAne1jVzqja9hjj0IYY+DjESOYiXzZG9GqPK28E4/trJWF6D43Vwr2uusyBHzjdjaGcOrsohWFvuBf1TCXUIjeF7Xo3LOImvB/FeUzW2qGJFN45QDLWJjJVfNnIJjwe1sakOxeh1gnolr8vH8dxQ1exxo/5Zr3Bb1u+1impsyLwix2P+GoM9EYxzFJ5VJ78ewWgO/hquus/W9R3J15z/8T/+x9edke8WKx5hh/VY/NL+CiVVjDTyndWduZ+hbj9hZpPOnImKzp/jOGrLPyL70caWbZG2bItsC2rt2I0Hxupicw0yb7VGmS9j3Ees2yqqOnahdlTVhY2Yjso36+NkXFVLxc64q3buV2JnEE+fbEPac29Svj6VX8xySLnOTsZC2ndqBfcLYtzufrEyn6skVmxSVVcV25FxM0Hlc2WMoFbhdkHb7br6/LC9u66uM8n3gdKl/4cU8Vj4r7v3Q991uB5r8svOFfK7kyu5M/cz0HdkWi+XYE19/7F5nOC7Orc5ozNETv+OtKqDmPSBbJ6jQjGqhXxVLmr1GLc5HuNtQS1uc7wO4fEjvOZqvvkddhWTY5DP8Zjcv2yvMppb+mhXtTk+v1mss5pfrKxzron6aAzPrza2HFd25XC753A791zJ2+WoIF6QP9uiigO/d6q+gtok2Uc/DRKKy/pZE/J6zh0ynpye22NUK3bh60yf2XyO4DXoXuMKr0V2yW0Cu9aMeyA27Q7zGkF/10q/CvVhDXVPPtrAGoCv+5FxX8FL6sx3ixWPsMt1V953FfPl+lP0ePB+zUm4PdudbaQuHntHxu7i/Zmf26q2oD3rU62ZU9lgN97xcZ2qr+fs8rst/elDHarN/blGMxST88v2Sh5Rxc36uj9j1aYW3Vf+tOV6OFW8WLF1eclZrVnaROagf9qBcZHndLsEVR9vu2AW0/mhs4v0uXbzjgSjuaQqZv4OH5e2M8qLzWOwrcxHVHZJZA7ajvs/qpXk+0DpsjeHq3G/uwQPW+X/Dupqh8rnGsWkz+nsDr4qtnohmdHlwMZ91xb5gub+bMOo1ipecK6gand9K7vamcPJPlVbjMYFYhzaumYdXSys9OmY5RajGB/X7bpfzZW1i2qNBHlX1iht5Oxi056sxHkMcT4uNsd9+NNWzXcUU/mh83V2qPydiOda2UHtXKMVZZ9cI+F+CSpbRRVzpFZJ+HUkj+nw+J+go+u6IiffB0pb/yCl4lH8191f3PGj8u8M66N10X2uT2V7F/iwL7+aweYf5nVW5qE+1QeAcx3IzbplH6/NoU2/yu85qxyaK+PLrzjhOZHgSv2K4f7x3P3qnzmAtsc7yk0M4wjPKeRT2z+crXutWfb1nIrxPgn9vL/DuNSidsZSF+va5ZLf508uKevM2KTK5ddVVvqprmr+fl/hcbmGwH11BlgTbOr/3//7f/8VJ8ibNr/KTw7iPWcFOUV3htKme/UT1Vy68XguhJ55chBPLoc+siveX6+YHyjWX0s8LzBu5Ruh8aiPOrxWXxPhtVZQpzOqJZ8Pnj+vhfrA98HvOxjfa1tZH8au6Hyaj8bw2h3ZWFP3qbbRur47o7U6Sp6Nl/yDlI/memz+v9YZ8v6ZYkzVlT4ElT1tLsF8RedPOxKVrWIWl+N0dTmjPpD96NNBvCsZ5ej6wMhf1Z+McouVHCuMxskxZjVdxWhuua7ZXkV9qnFG+ao+Gdv1H9mTVVsHY3V93E9MtsHtks8/fYiYyicB9+kf2XfkVP5OHVWsCyq71sRjnIyXujV0yHmXwGtPn5jt90d/Kcn3gdKpN4d3H4hXiTl/p/nxUMCZ2pMqBkHnq+5T0Pl0reaDz9sdOzEem7ZdOZUNmJ8Yxc18HfLlGdlhlFvM/GfJ2p9Rz+4Yu2Mqvuvj58EZ9QFiVvp3MRXZF6pzRf2zXJ2ctFf3yGtJX/pFFSNB5btTCbaMQ9XaV3EjfK+yT2fv+typHHeE93uGcj2qGqo1q+KeJSffB0qH/7XyI9/lP+p8F/Tjd0dzld4Z7YXqpnb9SuBozeRRDl+Lah18TPkeD8Cve4HdbRUrOTS/HB+fUB/yIIe8nV94bqGYtAnqqHyJcvDrGeKr8X2/dPVaHc+RjNZZ/c4+r9WYzsz/TFino6zMlTF4TnbHVHz2UR7GTh9nZDYOMR5HXp0Rt2cuP4dAX8+JTeJ8C2zC44X3wed+wMa6driPXPTJfpU/YwRxnf9qGI97kfVxZe9cOR9iKzJuFCvc72OKK77283qVuVfZmcvd5HpU9VRr9qq6V9Z6+zOH2tArDsaz6T538M7zGdXGfHjAMi4/A3LVPD2v4DMeQvnTrxcvSeT41MQcQPk8h6hswvt388NPHVz57I3wGjwu66MPNp+/IN5rUZucjtuUp5qf1yq/9xndezvp+s1QbFenmI17htx/vSbtfjFZRbm7PRM+z7wexfufyaW+XlN1bhzfT4/xe/n9jIOPw3n3dfMc6l/lAM+hfaWvP0f+Gq5xqrp8vkhU+YDnldqVg89UvgLV0UGdXIXPk/lX8xSeO2PwKQevcV2eo/j4Yic/fX3ujq+D5z0z5jtw1z6wVuL0Zw4fCf/W/k6qqOJeLah8O2KvROXfFSjvzC+qGNTlQMB95we3ZayrAvssFvtofhUzP1wVs4Ny+Tn5Tly5Djv4uFftx1X7sFNPF+vPJnSx2Kvauz4z6DfqnzFdnKhiXSLr9zV4F1GXoC0yjtphZS5Q+VYFle9KdfPxsSs89hnKMb3t96s60mekJN8HSr/VP0jJuXR4zLMFbjvzYgW6P5MHJVWMBJVPwpdkTIIvXwQrcr5qO53fbZKTvlTHbkzW6sz8P5Gc72gdnwH7tMpd+0Ud0pVr5HmTzuf22flF4Lb0gXK6jzGyj7dT5JjFfSdVVHGS6Pamiq8kMofvzV2ajeNU/iO6Mpd0db6jSvJ9oHT5/yHlncnf76td6bFWXxHPhxqcMz9S9nz6MfLu3IjnSj4kO3Lwd+DLOM+FT+JH4DlW9neYL/FaR4/v/Al9pMeL05f1L7y/UIz/uB4yRkrIJY32nFxVjg/Pw/e0o9trcXb/6M+Z4dyNxlyFnD5H8uoZcJ/G7WpxvC5ydKz4quc1x83nlefK+81qeSdUZ4p1dRHLFYnqtYU+FawhOYj18UavV1ehcXJ/c26C+iD9O2Sus1yd705O/53D74J/Ro+DnJ+Pe8YBvxrm45/H6fD5HpkrLxLqq4ctH1TZPYZ7PsOySu6LxvGxGH+F7Cto8/kcqMZxfG4gG308r382SnifP//881eM8HXyscWsLWRjPXw+xHZ9QPG+Bu9K7tU7o1qrvy0ouN9d92ofPYf81f6fQTm6PGnPtmqRBGfcz3rup4/FlXUEXhf8WSJvRY4pcs2A8btczyJrZQ0d5qRrvlYyP58bMDf1UV6P8XWSj6+VolqTs19LjsLXnW7M/LqgWObz4d9ob33/P3/n8IfKqfyVnMqPkipGSqqYK3SElRyjmM4u3Ff5ky728bAOc+AfoRhn1mc03ofjXL2mo326Yw+7nNjznAF+5KQPjfDzm/2wC297bdjwp/BxfbaqdaziUh7HGnVaWQ9iOj8aUcXfoWq+zmw9pJWYn64k3wdKt/9a+bERX3cf7kI/2UUwW3fF8p3D42z8uoK3Pbcknws8RnjMlWcgx1kh66C/f+fk9QqPSZ+T9sybeLxigXEEYzvu78hx6VPlE/J9ns9r0TpX+zQ6ExWKZ9+Ur8rJnla+I3i+zOm+6pxlX/rLjg8yRozWh/46q1Vf2orTT5R8TB9bMeQQGeM574A6kaBWtILH+U/QlDPXiHWlj/elBtaswnOBYlNX4Huja/fa5LX4/QiPG521d0S1r87zUvLdYsUj7C30TrX8dDmVHzmVX3o85F8R9+8fY3DlvgI/8jrB/asc6ZNjq72bY0Y1vw97aD9+wjp258rPHarmO/K7z7XCrB/tjOlUzce1k+uoxKyOIxqBP/vMRB9IfyWofCPluVlZI0gb9+R0/0f/qSTfB0rf6h+kXPUdyg6Pdfu6q3kcxl8xxKk9w/tk/myvkjlX6hjh3xFmXl2BOMnjBNf8bv5qsh6/ui+h1qpO7+8x7oNsz+I7PFbf3ZJnJ8eMq/L8jvjefFdU++wMcHY5fzlfP5vur86pxyXEu5zqtYar7Cuvcf6TNZF9csw70BhZxy7Ml7VkXdjPlOCasAbkcLxv1194LbPYCh+b/itrlGdR+NiVP1k5Nx8e66p3iF/3v3iXf5CiDTz7QAkOQvUioQ+q+odq88O9QvaqFvJWH3Ylvup3J9QE/qDo/swHc5lL9QFo5a1g7urj/0DjHT8gvLNXiq1ehDqb5ptrVMUCvozp7DvQl/N5JtfvxBVr/wr0fObz6u0RPlfd085n3p9nnSnRnfmdZ4wzCl77Ti5Bvt+N6hnXvoz+yDev1++4ZsyH9yT6x31+JpDXzXx4I+s5sO3iX9OEr5WPI7Bnn1Xu2AfWAL7NP0h5FF7an6lq3qoryZhU1cep+tyh0VgjX8qp/OwduO3VSo7W5ezsr+P29K0wG7eiq+HDz4E93d3XnX6ruT1nivNb+SSn8qOZ/ydp5fWqAnvGVhIre7NSyx3y173K71T+j/4tJ98HSp9/rXyx/PCuUOV4pZwjL0ZVjAS6n734HNHsRWNX5OnWACpbkjmSka/Dc+6QfXzdPvxecBbyTIxQXHdmMp/LmflFFfOdBZWd++61ppJT+V8pp/NX9hX52XO74/ZOq3E/VUm+D5S+7ZvDqq4K7PnFVFcOWhWzq44up6jsrxZUPsnXrNLOGo7yrAoqX2o1rhJU9srW4TEZi09inWd4n1WO9PnwM8jnc5Wqj9tSSfrzfKefGF0rvyBH+vCLnO8rVNUBbpsp10xUcTPt9FuN7ahiz8jXINtJ9gX6YM+9WVWXA64a5w4l+T5QevpnDo/+3v0VPDbz6+7v+O/qd+EzEZ7DP7PzSkafo+jY2c+VfDPYk1wz1aHPnvj6+hqLK9a5WiMfR/eMQ63+WSnI2kZt3Wc7GfXvIEZ7Qq0r/T68J9q7bv+wV2cRqr6ec/Ts+rOtez0D3Tgdfg4FObDnc1XVI5/PQ31Gn697JbyWqObR2jq+PkLrozlCtWa+D9U4vHbiow3eh/Ezr9qz19bMq3v1Wz1j8Hgv8+tavS/x9fH5zM7N7wZrCN/6j2CP6hCPjf91FbKN2sL7ozvQuLP8HvMucio/WllXhJ/rrqCyv8saVox874RqzP388DpWzg0xs7gVVnL4eMTPzkz2kbxP5V+xg/u7Wjzmu4n6v9PcRrVyPSrIduJ9vqtYx8p3Rkm+D5Ru/cnhY8xf3xHonbruyeP3u3R5Hot46jsC5VpFY67OwfMenfMroG6v2W0+f+7ddgdVTa8ia6nmToxwn9s/fEhWz4qfvVX4Kc2RviOUT7m8dsd9o7gReo3nJ0yCry2Oz+fIGO/G0bVKWJedXCtjE3P26+8Ooz0ezdN9o7jfAV9DUf3k8Na/c8jCU4iuOkRnNsT7+v2Rg6laVFMulKMxUthX8BczxloZ9xmojg6fq8N83Le7JqNxvxPMl330/RXyewz68KGiOi/JSozDG0Gk10n6H8VfAxBt6vHadPXXQeKJIW4GtaPZa/4or4/tejdYqxVG9bNmO6zEE3PFG8Mrvi6szPOnfP25m5f/nUMdaH32YPZ5BUebq8PIJnMwsVfk5x38xUp4++xB98Pnn81gDNn4rIXQ9YqH66ejdWXNds/MVXgNPBd+Dn3vhWKJdyrbKvQ9k+PD+6BzxLnZ3VOP57WmOocwyi+f+ku699iqHzbGzRhe01RLvuYBtY5e/5gL4wjlIZf35Q1S1jZaE+H5nFFdgtr5XNsO/lk46puN946s1p2f/cu9WZ27Ytmr0bPjZ4C9IRbefb131mUHX0NR/eTwpW8O9SDf+cbTqb6r0uJcvfC56CtcXYfmesfc3gnfz2ecodF41dkSihv5oIuZsVrHh5/L6IxdDWPluTtC1nxFTuGvv57zqrrFXV+wP/zFyl5xfqo491257z8J1gie/mvlGSubxiTyuoris4/Gle54wJWT/CvzE7tvJldQTuZe6bvja3t2Tt437zN3tVez/a76eN5R3xFZ35EcH7437P2d+PlcPWN6AwV+TtGdeL2qg/F09brESi3kQMLbbv9wntUzJnI/sz3K9Tvv2coav+zN4erGMIm8ruBj6Au0+mb/Kw+I59rNe2UdzLOab2V7B47MP+eiHK58oXA8ztt5n/g3FMR5fNZDm1olf7NIX9WKX1RvKEdkDvJ8+L3ZPUcVnFHkpA8xru4dP993nNX8hr9rU6ffVxL5DX+2gfhn47XeDWPx2nrluJ4zlfi6g+Kq19adHL8L1XokL3lzqMLu3BgOAw+vlC8SxOT9Durjb0CYk+zcew2oe8GmDs+5ivrQX3J87HeF2rL2Fbq5aZ19TVy75BhVjiq32tRB27+4gNcqOzE7eI4Pvxc6K9p/zhU6AzmU1+GMzc6Z/F6LJHTV+fY8qAK7+3W/+jrpYwvyYE//CPVNPZscc6f+GcrtX0tEfo2T+Ho6GtfrJC/3lfx1knHQDPqNWIn5XVhZ06d/5pADkm/WzpAvElfmdvIftQi109ahwy/pA7JSwoswfuaRH1xOZPcP3YpcE3HXusw48mHtZJSjW5dqvwT7sELmZSy/VrnSRmwyqsN93Zn5XWAtfB13nr3vjuavueoM6F7Sfc4fH/I+Dm359Uei+eKsduas8HzK769P1Tknb9ZBPDkScop8HZy9Jgj6Aq8Jbve8ghpnX/dYM5RjPQvq7lBdvo5nUS7fL9qzc+MxK7X463c1B62/cvofOVcf2SDPm/Da353RGT9DvlF+iz+CfSTf41CU9pHUp6KKXZFDO2Nmos8OmaOTz1dtrq/QHWPPzkBSxZzVldyd/ydRrZXrJ9Kd97N0r4sj6FPVI0HlqyRmOSWvlXbG7KrLkVQxI11R27vqjrmxxn5lHCB2pIxbxfv8jkryfaD0Ld4cvot0eGdUD5Lwa8bM8lY530mCq+O+s2KNKl+lCs8hsj3Cc7tme7fKVXl+Ir7eTmf/cBydw1zPylbhMXmeydGpo4q9Q0kX09lF5XsHeW0OttneSFD5XqmsaYWV+f50Jfk+UHrqZw4fNZQ/5hXyPRuNWQkeh+g/7HwGovuVQ/XjcmJ1JY/n7dYE5Kdfh2oVs7grYAzq597XppozUOsOWldyrpA1CNaZerKd8UIxahPDmRA5rzPMzsDvBuvO2iOB3VH7s4b/ia9jyqlsoByzs66+iiEPz6u3fR9ToFiuO/tJHn8+k86+CrXdAfXvKl+PKqlu7gVngnb1NSth7vR5BsyNMXWtvnbMaspnQHjed+XV9T31M4earD5DsPI7dB0CHVoOw+wA7/xuntzeB5uTn1+okJ+YWY05J6ezJ6MxvL/Wmc9r6OGY1SZW1zDHmf2P7ZVXcSs1gK9V9mP8Kl/6vFbhOdN3Fb72QufD9yL9H/5OdV6rs1mdq3d/wb8LvUazHh1aVz+LIxQrcS9Wnxnvm+w+f10e2TWP1ddezgVfy3xs5WFNrvpa92xYU2e0vr5HmjufO9X8//zzz19t+rM+9JE4R+yj2no+qcOfV/LMzh45dlBu1VPtm78WMFcxOyu/A6wbPO0zh1UfSPsV2sHjuSfPY8H+dY8g7VfLxwDuqUsQc1RX5Diro/Nx0qacwuNTK1T9XFfg50xcmfu7w1qwn+Brlmvl9vR9GJNr51ol90by5/EM9Pfcnbo4qHxSnrUq5p21S7Vf7yRR2Sv53mHb5d3X4w4l+T5QespnDqHyrYjNczLmd9AV874ix6s1moP7eOFwv2uHqr+LmA/HyfV0qtcAZ9T3w1/4Gj17rXL/nvkFWVR2l1P5rxL5KzL2ozWB7nnNryDWzyI5XNi5pv2Zuus5SfJ9oPTS/0NK8qjx1/WxIL+utIXu9aNjVOHx3wnmKzQHb4tsn6Fbu+9Gt9c+P/36QG3F+rrSd3SWEnJ08jz8msP1YYz/ikPreQT297PmNXlmj65z4r/WY+1TehY1nrdFV0NV35HXwa4P+XMc1XYn5GcdXM/C1yTXONvvxEptvOZ3ayobZ69bc+zp7+LvhFqvZmUut3/mUJ890GcJ9AJydqIc6u6zCX7o9dkGxcGRzzM8G9WvNao+O+RfPK9Yy+8Ga8N97q/aozVzPI9DvPer8o7QszL77Nduzt8BXmO0J9W+cea7LxC57jxHfkY+1GhtqzUfkfGeYzfXiPzak89sov33z0Dr83M6A90zL6j3zNe5EdWY1FOheM6v5qN72fgahl9UZ977ELfCLH433ypn86p/tYeyi9F5lE/rypqd4er1qfJpf694H+NrJl7ydw4fRZzOsUPV/x3ltbJGFZWffr+TEq1JFeci5iiew4VPjPauInN12s37nWHOI2Z7mTloj/r8NKqzWtk6ObRHMR2K2xn3LgmvQ/h9gu+naAXFzfZqZS8VQz5BHyAGm7cROUTlF8TQdp/wMRzivpPurDvJ94HS7W8Oz/ZHM6o+V8sPXvqukvCHpKPq+5M1Qv58IdmR5xhBjPdd0cp+el7h978Ds7nm+lSkb6XPT8Lnyn2uwcpZrHLQHkE8fYiv2hWyu9zGPVcp58a92zymk6jsz9ZsPjOJzCE8RsqYlTUa6WwOUdmlkS9VxSaynZ3vT5GT7wOlt3hzmFQx76IZVZ+UU/k/+k9B5VvVkRfFD/ezstbVXmEDvxe53x++L+yj76dfU9DZk4y7SqCzmKTN295X0M6rI5uf+bu0AnOp+t8lUc0/13lE9v2pSvJ9oHTrZw4fY/76vfYdn1P4jjwO6a/10Ocbus+FqC0fn5Xyz0T4ZwR+xzXV2nTsrMcsD+dW+Jp/uAdeX7TuHdoHnhfwPadv7hv9hPr+LvuZ81R7Z+7Eeh/ueT2qqMao9o029xnTwV6K7vNXfhY8PlmNA+o8ArX6vCt8LfyzcG73q3/mUKx8fu7M59YYF7wO/zxk1iVUm69BNz/hOUWOU6EY5cu/u6vPncpenU1sK2fAa7sTxhF3jaUxfD2e/pnDrm8Hvox/V1W1Pha9tI+kPpV9RBX/O+jDz2Jlb1f2Xv58jngWRWX7qWieec354/M1E1xnVHGrfY+g3NRKu1Lu+cp+Z4530UrtKygX16vke3GGKucZZU4p1/GKcb67knwfKN32p2we433d/QXtx8b8uuqnBSlidE1hP4L6Me6VqOZE7/Qr+4juuwNfm4T5HF2T7wpr4euiq74LSl8nYvjOCZt/J/XhOVx9fpWvyvk7PSfM1a+IM45PbXyC6wr+TPEMpc3VId/s2aN2XRWvq14Ds17yMB6vxyipbA7jdDA+tdD2a6cZWXslzbeyuwTXlXFXUG3K5fmPSHhNfu9rWomYBB/k2eIcdfrwRb5bTB4hhwSVb6bHhpf2M6IWrlfrbN6q/4g71uioHNUlsGfsFRIr8ydGeDsFee9+b5/RUbz2n8TK2sjHuaqgv8dgkyDbH16D782Vcio/gsr3ClXI3r1evbsgbdX91Zqt2RGqPN9dSb4PlKY/OXz0+7pbhz58Z7BL95O0M1DL0Zpm+HdBrlWquq6u9fHgfN1di68t3+3SvovZd38SMcLbKch7iTWjfVYdWquR/JlI34e/8J8QaK3ZO9aI9f+s2Wvx52Gko69Xvr9V3neD5zjrzterxH2d/PULrvg6oBw5FoK0Vfduq2pNVmof9fe1XpHwfKPcV6D8d4+xyvQfpOiA3vFmDbTZd+Z3tOj+BUScHZsP3irPXXPhQ7iqnwP7jnCotcasc1Xv6EPFK/g4I0YfnBd8QLpD+0mObiz5JfdjA/XPOjKf/LM+PxE/H1pv1kVr4R8s15nx9QHF88xVL6rk4/lUDv+Qe+7DT0fzr9ZRaC3kO3rudtaSPdMeOMqBaCf5Gjs6N1Dt9dHXUuW643X+CGdfS+9AzyHnbGedVr+WznycH2Kqvc+2wzOwU/vV3H3Gck2e+g9S6Pco4j/a3Dtq/yQxJ+bvqmwjsWbObo67lVQxV8nB5uuBfQX6rEhU6y78vtqvDzW+jp08LunsCXGp332vVl9HBNeza6Y8Pq6o6ujG8Ziks1d4HpePSztjrhZjja7UIfz6aolur0TVZ0WjnFD1g8qXmlH1+Sly8n2gdPvfOfxJesaLxEzvuh9O5b9SDm33cT2yX4Lrh+eg9eYLge+F74PvJVS2DuJSjPuhp1o3dIQqz448R1LZEvq+mzjP1Ahu+27awZ/ns4LKd0Z35HyFknwfKN32r5Xflcc6/O06Q3FIP4b1tvQ40F+Rf0FbPuDebUd5x18r+7xGP66/Cq0Bog1u04/lc+39WgnfWbwO1gRbtrl++Pe+cF8xWy9fV9Txyl8dfRfYE+Sveb7GM0HmW7UhcuVrL/iYz3g9clQfV5fXSkzCWWR+zIH7XRgnr926CWrVdSX+Sqqvr51gVFuuWfb3PKsc2YfvyiV/BFsbtPoi658rgHf63ITPhbp25ncXOsh6eNCr63kH2Bddj35Wyr94+P0qGtfPiK5HUO35GTufj+6PzO87oNcXzVdrCbJpLXNP/LXIXzdY93wucj+q5+bIF4nvAGvHuezOp+LQGeivK8+j5/Qx8rnhvHuN1bOlK+S+cY6q58THrT6TOMJzUivnbpWuLsHcmG+SayToM0PxylvBfrA21dd56upqzxyg+N01Ej6nbtzR3OUT8lMTtciW6+jQ9woY6whn+q7i6yOe/kewv5PumKd4bMKvK+2MuVJ35/8uYh12yH67/T8cR2ud613ZHHzEVZr5pd+dK9cjc61K8Do5QjHeBzzXLI/HnlHir/MStbptV91c5ON6p6DyjQSVr5LjNr+inXUF+rgNPP53k5PvA6Xf7tfKzmNN/iXxOES/rleh78T0HYCuGqP6zmwVr1XyWrFx/7tyZh2y325/R9+Rsde65n1+l/27w1qzTmL2LFb7oz5u93yOYtDvjq+FxNntJLgmmasScX5VPl4nR+KnKfSr8Dx34nVJjAtq+zxnEnnmmW9CfOYYyePza0cHc6NfJ8GzR9vXYgbjeB/dKyc28up8cs94rlzDxMeSqhyvYlb7lSzNM98tVjzCPlrUY4NL+4pmaz3ynxn3pyvBrjU7Ajk9Bzkr4ffrh7+T68V5riAu9w976sM5Zq8tR5+jCuXj2o3rpN37VFQ5qZ8+szb9joj+grwV2U+idvx34WOmVqn6vkLgNtbxLuV4q/JzdreSfB8oHf7M4WMi7Xc274TqFM+q1T+P8ljzX9/paGyvo/rMimJBn7WQsmZyiO+w9s67nhdfUz7jwn6N1t/JnwSSR3bkZFuw56D+1edifirMnzX39fd19z3J58g/S1St8U+iOlcraI31mbvuLF917sjDsyT8XmQbsPsV/HVS88enONZktC7V17KEc1XV1qF13Vk3n9MRcl1mVPHY/LmBI/X5emk98mvcUXbn6nBeurMiNHfV6yiW+Rwd+whn5roDawCfzxy+uZIq5ndXrku2rxBUNsDmMZU+HKNay06/K8z97Dpknk7w+MJS+it1ZFzmFLIJj3E8PtVRxb5CFbN1FWnzNVoh+9Dm/p2UdYnZfD0eQeVbEaTN21es4bP3wcn3gdL0M4cr32l9uAbWWu/of9K6Pw79r+vjDP66niHX5cw6UZdQbQj8XuO4sAniPAfq8ByuD3+hvRmt4coa/3SYO+uQZ2n1PGWeFM8J+fT6VMUJrjOqvo7G0k9QfA7+kw7IPKhidT2gypsibhfVkhKe21+fBDGOr5HnSuFXXtaRcUb72eHPZ+oq8idoqn823wqfL3ituc5JlTvbV/y074ocq6zs0y3/b+UP56heBJPq4XxXOPTdw3sF+YD7euQ6IX9RrKjq7dZ9lEPj6OrCRz/yfvgLfwZYZ9eH/+SudZo9J4CfWI8fPQOSj4G6L9pV/zsgt4+RYzHHrN3twueCLeGND6rWBAm/otGaca3kPvaK/BWKuYLRGHfAeMxZ7W6df3d+63+t/I74oZ3Bwyxd9bA+i9n8dh/SfMCF37NGrG91zTX0fGi2zsrjUh+ReRC+77Z/H34uOrdXk8+n3sT4OP7MIIdnpaPq44x8q5CDsVIJNfs17135xi7z+2uE4v0Kuc4pwTi0hde/8s2815Vawevh/iqRE7qfyM1qzpx3072xv4OVfbrkj2C/Gi3qM38kezXVP1BZoZo3tjxosh0dRyifvzhxJqqcOfbKh5O9T75RUts/NOxzZr4V1QfLlQvNPkRejVt9eNtRnwofV/2lKpa989q6nB8+zNA5qv4BSp5FZ/W8cVarHIIxkNDrBrXQn+eqeo2Q3+vRveLF6hdt71Mxe6adUZ6z+Br4frF+SLB2TlUbc6vinczPFbKtcyV5nxzfxzu7bsqlHKwRbcbgntdN2j4u50X1Yqe/4z7vfxd3jtPllt339PMPUj46rceh+nXlXKgN2Cvo38mp/J1GrMZwnWkV1qTKIbGG0ocPr4CzxzlE/jyfJXMjUY3TxULlRyOq+FWtoDh/pl34If2dnMrvImYG8fn6w31qlyrHs8T4zI02VwRuG9l/spx8Hyh9fq1sPA6WVuyr9RpeOb7mP4PvQqqfJs9qPzo39aOvX7t8qs3ro10J/ygfVH3B7Voj/OR16Ts27kE2+n/4cJTVM8TZ4xz6eSTHai4/ux6fuZFieEZQ9UysvB6B53GyvYvX2I2hmrN+alc8V4kYqfp6g8/x+IocI4WPPFkr9y6ReSoRd2adGZP1YPzd/Rf59Ykr0GYMkD1jn4XP+VksjZfvFiseYR8NdHaNHg/BrxygdhV3h5IqJuVcUWvOv0JxkP07OWqvjnNER7kix4cPybPPE+P5eXZ1z14Vi5LOPsLzPUOMyXyx5etkhftdM4jJfquiNkj/3WJMX7Oqzb1fiXE8ppIzsj1Tzx43yfeB0rf4zGF+HiXbZ3kcsPL38u8K9frVP2txFOUR+i5QUj7lxeZXyM946F4iB3mkVRiDnB0+RoVqo37wnPLx+RWnyye75sFnuKr6FMOaeG2eEz+478OHZ1Kd1avxvDwz1bMnn5Ata8mvQeSg9orZ1y3l0Jg7X0/oA57Dn2nBXD3eyT6698+HskaO59N9vpYA+5lyvL68zqjm62NkXcrp6+y1M67w+2SnvhGqQ2ML1Uu+x3ukX23VJLnPa/8JaK7O5zOHN+vMWlVUca+Q83g4f12xZ/udUG1n62INEPOt8Bhdr2Q07ocPV8D5XYX4WZ9ZjOfp4mTffQYy7zO1UiuvE5UqRn73XSVgLtgy7pWq1hDSnoLRPtwpPyOV/245+T5Q+q0/c/hYk6+7Pbp++Z3q0fxwtv9VaF6I7wypLdsi14F22u+CcVTbyhp6vO5djwf4Vw7EfMH7wMq42aeCGGk0rvTh9+DOveaM+7lCFcTrGSGGeD+vHpNKFOt0cTOO9BHUugK16uoS+okTtUs8rw6vE/Rxqvo91nNL+DzmLORmLtiUP18XUx0z/y7VTxGpe0YXc2V9I/yMPJuVOf7Wbw7zC+4qq5t5ZNM5LOgV8AD7Acr2iIyjvdJ/d86sk79Zmo1DHMKmh9VrlY6ckVEfxiR/hddVxXmtozwffh7aa84G1xGcJZS2Cj9XaNSHNzmC+HwGiEG8AfN8sjuZo3ojcAX5ZjBrpa6sj9p9XXTNvt6P2KpP1pFxsJpXeKzHn0H5/Y1NJcbKK/6jsEbk402q0DXbaUtUy+yskkN0eb4bK3sw/cyhFuquh3IFbcorxx+xUhufzZjFcfiS3blnHu+/s5bEdnXxQOmzG5Lakn9eA4HH8JkPkTWC7HoYdZD//PPPv/UB8udYHR6vfKplBPPr2BlTdPFpr/r4fnR5Pnx/RmfB4WyungWPO3OWqvhZju454tnX853PouKrv9EoRuPtvvng82Qax1+LnG6t1EYjNBfmx9p3Y43o1mJUx+441efrfNxuHNB4q1/3kpwfa8W955Vd6+q1pp8+7C/IDrJrPmfetO5S1f5s/I3u5zOHNwoqX+pxMP6j3eFxnZzK32k07lkYQ+R8sfv9Ct5/t+8KXZ27sK5n6ztbx4fvz91nIM/8EY48Nyuxq7mc1VqOxFQi7ghVrZ6r84+0Q9X/jMi5guKOzI8+oPYKmSfljGwr2o1/hZJ8HyhNf638zHfTzqPer7treByir7t70DqtrpV/1yK678JG+TQf1oixV8cX6qs6vG9q9N1hQh/uE43ncpvDuORzef+q7xmUXxzN73XSPlvfkTo+/Cz8DHC2rkTPWo6xO47nAPK4Vsn4nb752irIJ/GaNqtXEJOxDrFV/xmsW0KOnMvK1zCvASW8vq7Mr6OqhbF8bLc5Gi/Pzcr8WBNyz76GoRlVzE5/ZxS/u853sTSnfLdY8Qj79nocvNL+DqK2M2vtORxsHtvpCEf6ruwF+P3VqI6jUGe37h8+7MKZGp2nlZizXJHfn3HBfaqiipNWnteq3xXqqGIrVevRzYe4Z4uxqcttnWB1v130OQL9qlq5Iq9tJFiN/85K8n2gNH1zWCW+U68Y80o962DxUIA/JGd0FeTK/GiX2breiY9xZKzcq7u4ex0+PAft4+zMcCaP7Pkrz8lK3TN/hefttBqXyteelefZ43eVVDHPFnA/ez2uJPx6RIwLV+8FpP3IfN9dTr4PlN7iH6RUH4Cd8disX9eV2h5z3/7R8BWoxlF9qqtCH1SVdtZ9dQ2pqaotfXy4F/iVjKM69aFxoX4VyuF5wPN1NUHWQk7lQE5V6wz6UAPzOZPrSF9H/ascfkbO1PnhPcn97fY27StngJjZ2dFrJn6xkjuhj+ai55Vnq/oHKLxGa0zF6ZlXvxkag7wz/HVE/ao5aUx/Lc01mPXJNfX4UZ2j13DlzLquYCVvvvYK9UkbsHe5HjlO5tW9YoAxWDNqxZZtkB1/1rICZ5N9q3If5Wz/q1Adfi7f9h+kPAot7dLR8Uc5Ox3pc1ZH57eis6yuxw5VP40j3OcxlR3hX4FxrkLjdmu0y05tR8dIrsjx4Tlor1bOyJE95TyNxliN6fDn5ErIeVbkEtX8Mj6VVDGSkz7WqCJjXyFn5Zx0GlHFdxJdHStUOV1Q+b67knwfKL3FP0gZvZM+M/5jzl93a7ziHT3zo9bdmuHxkPy6qj8Syo+q73gdj5VG65HjrJL9GEfXis7udDVovsxlJc8KnpNxfU5oh9XafB67Y1RckePDc9Be+dnrOLKn6oO6Z7GKqeKwu0/3d7y2zl7PdqBeamUO2H3+vNY6Hi8pxvtAFQOskcdIInN5P7+/E68p1wh5nV1d2cfxvv41rUJ9uzo60U8wTofHneFs/ztgbiOmbw6vmFiX4+5FW1mAK1mdT75w0I9r9eJTkf2F5uwSxOSL6e6bp2q8o6yOmXgNXkc1F9k89oovJp6T9i5ep7RSG3E+9i4aQ3k+fF/Ye+1jnhnO0xl47Rnl8jPoMdjdn6SdcSrNWHnDmTV1r61el8eLqi6PSYl801KNSwz9uto8j2AM+nmO1LPxWrNeza+qLfugxPvuCsg7GschxnPsoH5n+t/FSj3TN4dHvvglvgH6/T/MNuYIOoDSygvHUUYP8RH0uQmtM1+8V2rXOiqWfkIbLrEGiLwpjSs/ffRZC3J4Lu6Vh89iIOXYRTkqqNfldUiM6zloe70J/aQOj9H66MrewJH5ek4p50X+HIcapJyTx85QrHKJam0+fC84OwnPL/vN2Uncxj1XniOJs5lnXjaJOJ4R5GNz7vR6pVggp8aQVDvPBdcOzztDcUj9BHUj5gneR6h2xQDz9Titm66y+3xQztdFrnzdly+vPiYSlZ1aEHP1eXN1JXzNdh9rgnKNQDbVIvwNc9Ym5TisGf3pO5Lvg4ucTmXrUM4j0O9o/7vQmkzJ3zMnj5C302NTS/tZ3ZX3DjmVf0WQ7avx/Ny7rSLjtDcdxAD32N2XeEwlxtX9lfgYDrZuvumnLSV+no+gfqN1//D+cAagOhPZdvCl3+3pEz5O5R/5OjLnFeqoYisRWz0nGQdud0HlczmMW8WtakbVJzWiiz9TO/1y3Y/kVJ/KfkRQ+d5NTr4PlJ76D1KuzPXdlVQxnWbxR/1XUD2cle0o9PVcnfKFA6pY1910Y4zGx+f+ygadfZWz/T+c5849IHf1jOSY+cUzSb/ktqvw/HdohapfJafypS0l2JvKn3Iq/67I05HxKfYf0l9pZ77fUdVz8iol+T5Qeuo/SLnzR6uP+f3SO0ONWefSj3gNX0fyPQ7el+XffsbJ8bp9OLM/6ivxqwNBbcyPtiA+7zsyPtH8yY9yXdXOvtTj/e6COXRj5PjESz4/Ua0pKF6kfZWz/T9cA+vPflyJnxvOmO+7t3XWRvH4HX5FmnZBvx2O9BH+uiiq1wlifF6Mp6u/jni/EZ5DeB3Y3Zb5FMNrKb7RmIxHPMr5r6I8XFPCx0DYBfvvfXLtaYN/7fiJsCbfhdv/zqE+R6DPDty96Rrn6r8BlWgMfaaB9dDh9rXJNsjuLzDC27P1Vf8Kr0Mo507ehL0ih+YqQebOuuRXf/XxWMh6uvUS6VPbc2ocPpMiGJe6qKWKEVV9V6MxqjpENz52avU47jVH/hYXME639oI6Or9Q/6z1XVmZz09hZX+T7ONtIBdX+f11VM+S98l4wTPHveC1xPE+yud1dKiPvw505OuFg48anc7u+JooNtcQPJf8OX9nNqeqZsYd9eXrIP35miXIx3wyBv8of4fXKbRvvt/C19HJvpD16L7LAT6XGTku4zlZw0/B35SLp/+dwzN9VwWVb0dX5OgEle+oKqq4qzWiivVr2nf0eED/wzZiJ1Z4zGqfHWY5R358M/9ZrsjxTHQmfjfY65298j6smds6dvq4r/IfoXrmz2hGFV/126lLcBXpd83ysg8VVbx0ZA0ZR/fiSA40o+qzIvrm9S6xBuBr9F3l5PtA6dZ/kCLOHKwVQeV7RzmVv1OS/qvXOcfoyHF5aCo8DonV2kcw7k6fjHV1jHwdKzln61b5Z3mdlTFWc70Lo/n8dGb7WcEe+z4rR2V30ufx0kqOHTzXipyZf5XVPFXcSE6uG36ulT/VnYEqFq3k7eTQzphOPu4I77Oritl8WcPKN9MI/MSeWferleT7QOkt/g8pR+R1+f27qaOKHSn7cNASjzmqGR7LgzXC4yVIe6eK0QM9wuOqhzXJmB3o063RkbzE7vYZxe/keifYm9+Vo/PnPEh+NrFVeB/H7ek7QubrJPLZdJ/QfbdGHu9r0OHxUoX7u9pc1dqnn/suphKxYqUOSVT2mRxvMy54n5k65Fudj9QxW/er5GuAze9fLSffB0rTf5DyHbjy84yPdfq6O0+XKz+LsYLmSD7PK7vrDI/DPJ0/tStO6ubiNWXeUa3EkT/7cdVnQGh7rMcLxkLu98+ReF+PF/i8b4X3877VGsm/mlcoBzl11Zqu4HV0rIwPR87unezU/k6M1pE9m6EcR+avPvTLZ0DnSuNnDfSR8FcxR/HzvQKxXhdQm2zMr6rV+9FHqvbG432NvI/nY1zvhw94DZNEvk763hCzArG6KkeOW7GT31E/5G1fd3zMD/lrmNdInxR4DlRR9RW+v1Uu6Qp8DSBreRUrc7z8H6Ro0GcsAJM7MpYOZTenka8j+6idLzDe3s2fHzImP3ujdvUh49EHd0fsPBwaV0qobxfm4+R6ya8PHfNBa9GNNbKrf1d7hey5zlyhqm0F5c0+1ME4XV0dejbUT4zmtJJXMarDz0Zl24WxV2pIzvR9NVlztjlDq3NT3Mq5y3OmfpxfP7s+rvuF/MqDXa811XM0QvGeYwfVoX75Gic785OfeoXX6vMXucbUBuR0vI+vofA6AL/XxDrCLIfj8xm9zud8fQyo1lEoVvdVH+FzyZhqnR3FK8bnz5rqmnsCXS2CNVv9utfNbbamPwHN3df40D9IeYQsidjHoP/hu1oaAyr/TxNUPnTVuq/S9evsDvtHTLYrJTlfPxNX8sxxrsRrls5S5VjNPZrbmdqOrNld+3cU5t/VtbrGoopzW+bKtsCWduE+1xGqPJ26+Iq0a11n8fi6GPA4l/Bx0sdVpB9VVHHSCM5R1Q85lf+ZOgr987lZmT97NYs7o93cu/FnleT7QOmyzxyuxl2h7kF8B/nBczJupC6HyNgrNWMU39mTWV9XBb7RGl0B46C7uCv/O9XdxZ2tUWfgCGfGvItZTfKvzJc1JV/1nHhMijEqG7hvB++3K6eyV3E7eM4uT/q9vatR/wrZ2UvX7pmoBNyn/y6t1O6oj5P5pOr8flTLyfeB0qmfHPphBfdfLfJzfSd1VA90JZFtWM2xq5WHc9bHfR2zmOocOd4/Y2hXvl2qdV5Zowr6d8z8RyGv5z4zVtVvN1+3hmfqEmf25pVo/Kydszdip27FEs+996fNuN4Gt0tpW8X7nFGuWRXjOspoTUT6wW3Y01ZpFpdUMZLIWpOqX2pEFb+jGRnr7dTM/1GvJN8HSqc+c8hnBp75GUPVM/tcweMBWfrswRWfLeCzFfz+XuNKMKpDdYpqfeWTfRQzIudGnu6zHG5nLPqI7Edbc+ezJbLR9vjsK7BVPq3Zf//v/70cn6uvDVS5wPtxloTboVor3SMn5y9Uf66BoJ12Ua2bUNtttBkDZGNNiPd19ByrqA91AeP4Go7Qa0P+wW6QbzVPhWphXn4/gjU5M+4VsK5Z82geql3Kfe6ocue4tAV5uTqyAa/7iY8n/+i1NV+faPv4oxzUR120c345F5+v47X7vfB2tTaJx/hcctycH19LqjFkc/ArPveiixU5TySyX5I1Ocwlx/L8zuqYd6N6X13DK9C8fV9u+SPYUPmuFlS+K/RYsNL+bCVVDJr5pRnErMRWHO23A3PZGcv7eD/u06/9T9zf4TFVLHnT3sULzqJTxY1yVLYVRv12cnZ1iWp+Yie/79eoX9axM8bddLVUZ9HJOTmVPeO9zb2Ua1rJqfw7OpNjVGtF5XObX93e4XHUQh/3dco9rmIQVD5XojGqOFfGZF134OP5uJW9i79L1PHscZ+pJN8HSqf/38ryX/2Tw0etX3d/8disr7ue7HOEo99BMLauV9TBmiLypoh1sO9AnyN9xdF+K7AGQuPsjKVzQx/J17Nat+o7XO9fkXlEF+v2bk7UKNKeeX3sype2FbQGXT/lzGfRa3Cwd7lG43TkWKPn1WM1zpG1eAaqS7VWZ69bW6F+2osuJu3MP+3sA35fU7eD2sqBzuI5cqwRilWt1EGt5MDu+UWeX/oQ57loew6/J06iFlj5muX1S54vWYkRinFGzwisxFxNNw+3s4Y5p7thPXxc1UKtWfN3ZGlN891ixSPsb8L2WLD/8N0txr5KR/N1VLFH1VHFruyFYl6Fxt8ha1+BuIwnR7VGZ/GcSWXvYsVO/Mxe+SryTIz6pS/H6e4rurPY9WOdndF4O7E7nOk7QnmrmlfGG/XNdc7zyj1t97+DnKytq9UZzaei8s/WzKl8uh/l6KQ+o9ikihnN/05V4zKfo2S+d9E719YpyfeB0qHPHD5ylfaj5OdP4HGYfo3hn8WYQZ+KkW8F9ffv8PO7/atyZ14Y5a8+szNah4Q+VQ2ep/v8WOL9q8/bCMVI/rkZ6hCeI1F89vH46t77iCq/25S3m6/iXKB7jaE+2Bl3tsZ6rkDx1ecFdd/VpbaPO0PfPZKHvF4DKC7rzrl4jMd1aEzfC8F3s1UNjOk+H0t93eft7JvzGcFegvqwzjt5KqjL1y3X1XMzbgX9k7SRo4rV2Hod0Zzxyya0duzP3Wj+1MJ8c52E6vTPuRFDzYIc3m8EMRmbOfPzdYnG9PPt/YXXSR4/a1U8803INaon870To7pHaE7sxYc9tOZ+xi/9O4cj31UC7tM/05E+V+uxCaV9JPVJZjGjcURld0Hlk1ap+nltSWef0fUZ5RvVIUY+IEfS9Z3ZR37nyBqqT4fHV32hG8/xNdF1lA+ozWNn/dLv80vfTjt9TrWGO+OuspJnxaa227LWLgd2xXdxAt8dcir7qLYqXri98ju7Ma5cZ2pNvM9ISRWzqqSK+ej3k5PvA6XpZw4f/b7u/s6zvouE2XiPh/Hr7t9cXaPG0Hq4Zux+x6acvKNX/UjkuO7XOO739aC/Qw4gT0XGVnT9ZfPasCG3z/B+ud/YRZXPfd14O7UAe1X17erJn0pU/XL/OEerY2CvkI/4rGVGFc/+QvUsOqPaOnbqzPxHxtvBa9M67K6p0Jp5nayn24jJOLdlP+2N+7ocosrhcQLfFSgXElmT2yWtq9ty3Ud5XORDgN/XyP2CmCTXmdo8j0R/KZ8Tb3sf4f0qOrvwXNIozxnuyPkTYF1Y93dYp6Ua8t1ixSPsZRKPh6b0PUMdVWxKrNROjEhfMvI5HueCytdpxGh+Cfacr9oz6FvR2cWo3y7Ks1Krr0mCvfMns9jKvhPfxQn5cr5VvMeM8gExunLPmkGOm34xGnennb4k/VnbzL9DVYtsbs+2UDvXA1sVLzqb26u+tPHtCGY2t4tV2y7k6PK4H7HOuudayRn5ue98K3Y08qWcyo/8DH10nfwcvUJOvg+Upj85dB6T+bo7xqOGr7s5O7F3Uc2X775WUBw/8XGUV/NjjsSQN/36LpRxseMDj5E8h8fin6E+Pn/6+HfrslXzG40pu8+3iiPW28wHmK9wuzPzr0INyuPz79D8FOvjZi3p9/mAt30vHM8hchxHY6S9yws534xnPF2z/oqMoZ6VdU2yz5EcR9A4Po9qDVfWokN9R3Op1iz3VW2Jsyiqte/2Q3ZJbc2PtqANOX/6OJlX/moshB1k8zqIF27bJceTRusqtKY+FrUBbfJJVR58oBji3Iddyj5J1aeDXNIo3s+QGOUccbTfTyXP0TNZ2YtTfwT7TnjYnj024/IC4S8U3QeCQX1VL9cjMH7idfg944F86V8lx67m6x/wFoqRhGzepjbP423dKyY/eO5tkXmF/BmTVDZnJaf8so1y4WO+GUuOhDi/cq8+u3/Amvo9B+P6GEIvSl1uXrDSL7v/QxjP0fURamPLPrxI4fcr9yLbwm2eS2R8+p2RTyiP9jbzc632Kq+KkWjPyL0U2ITso3FFxuSzlX3k9/3FrhzYBG3Oe/oZR3bPrViQj9cAof6qU3ic+gnZFMM4zM3HFVVe2RxqcrzORHPJ10Gnq617javweYLX3uXwGMG4kPs9mid4DQn9PK/XNsoLrMmIlZgRZ/vfQa6r9oo1e3a9Gs+fg1v+CPYdehT+6/qKsXflVP4djchYrZHDml0hkfdc3e5gz7qw4XetotjMC5lTWmUUu5KLmFlcwno4Pj/5uvlWUEP2YQz8kG2nqo14t3dttwF1VX0ga5+1hdty3FnbkW/kF1WMtzt/xlxBlVeq1sjxmMwBMzs+b6eExkmbt7MOyRnZ0i6w5xpkbNZV9RH0y1iJHI77wW3YK39H1lrVLvy6Kqfyd0qqmB05lf8uOZV/V9XeXC2ofEfk5PtA6SlvDndz7MZfJX/ovV2JmF11/UaM4tyHX9cjhzX7qE2+FFT2tKXIK7JdUcVkrZU68M/GHbEyTkf2oZYjObs+bndfxiWVv8qxEgess/ur/XRmbSEbOT230L33ST8Qk76qPbOtxlRU83OqvNmnGqfq575q/sS4TWDr1pX71RhsorIpx0ocuK/yd1R9Zrb0AfZq/qn0eZ/E43bka9jpaH5nZRwksp24nxi/Xqmd2mfy+q7Mi67KmeT7QOnwn7LZ1U6undgz0kJ3VPG7SqoYF+QBqEg/c3H7qqp+lQ2lD9zWCdw22gfhMfRJsLsyL+t6Fh9jh6qP50rfjOzr86WtK1TzzzVKv0ib2itxAlv2ydj0ZV3ZFuQ8ImBN3CZo+7gZI7p+zkrMDPWp9spz+VxQNT9vVz7AV43r5BjcVzYY1eU2Udnd5nYx8o3IPt52Vb4k58caep9qXV1J2jK+U0UVh7z2FTm0M6ZSNU5Hxvh1Jsbp4kfzhd01eXcl+T5Qmr45fOaiCF015u64f/zxR2lPkVtwj1ZzuDLHn3/++a/7Kr6T55Ag7QhoVzkrEZt9OjuSXermN+rnfYjjviNjhd87xM1U9d1B/dEKxOlcJeTpatOaVXb6cVbJoav3IQaqtmKBtnI4GaccsiUeA4ojVn6P8fscQ/ddHeTUvauyY3NRPzG+Jg5+zq6gn0Ne0H3WLnLtvY+j/Ph09fFy7anN+whsyGOIw6acVQwSjEtb6F7xDjbPk23kOaUqBhvkfGm7DYFi5HM/0E4/Nu59XJfH5Xw8v+Tr7D7PpXHc5308NjXykcNFPpE+V+YdjZPy2rn6fkmsGX24x4/d/dV8Uit5VmwzkV9aqWsm1oNarspbSbmdfB8ovcVnDlkM6RnjHVUuqKjiOkHlQ5U/Sf+qfJ07eX6fr8dIzlGfSL9rhapfpRVYH8fbozw5Dm1pdG4qZn3wc5+kfdYW2Yaqb1LVmmSOSuBt98+U8dRV+dCodvn9KvweMkeVUzbvm+3EcyiOWL8HbJ3d7xm3kvC6sGctozbQF2i7fdQe2aCy5fwS9ydVvyrW41zQ2cVVvqOqcuV+dn7afj9SFYdN5F6lZv4rVJHjCm93gsr3bkryfaD0tF8rj+SbIe46FKKyo25cJ33qg52rK0l/JXImVexMV/dLOn9nF7nOVXsF79PJmeWt/JmjohoLW9Wf+VZ0dl8jb1ek/WhbVwQ7azSyn1GC3ddoVSvrSCzkGmS7y5eM4qp1dpv6VuN6Ttou+njb/e7ztlO1PR7S7u2sA6UNKptw+8jnpD39rAnkGqVEtrMP8wX3ObQr/6yOlKjsqKKKQ1D5niVfx8r/zmL/qH13P6+Wk+8Dpbf5yaGPc8eief5K0Pkqu1TV6hyZS1LFpLo60lbJ4/zebdDNB9LvuN2lPrtUeVJO2ip/VQf9Rn2TlTVI6FNBH/dXtsxR5azaXUz6dF+tUdp25yLcXqmCcav4VY1qFT4G5HzFzH+ErCvzyu9iLogYvxIjdK36OB6LvI9T2QR9nIyl7Xa/h4yBzi7cRx1p83b6Hbe7oPKlYGXtO3/lS5vk617ZRNaxIqh8R5X5su12p4p5d1Uc2YejSvJ9oPTyv3P4qOtff2esGuuxYEvjK07wt5wQeA5i9TeG+Nta4o8//vrbXKonoT5BrhzTUYz8/N0pYlfmojr87x+Jqp98xKzkTTSO1yY8D/4K+qhOzZF+1A4rdbHuI/ibUFpn5RzVpr0S6lP97bRE+eTPPRR+FshRxQH1OX/++ee/1qgaR2236T7XlX5S2oB7ruSA9Osqv8eoD+tMW/7sK3SvWjQ/xQF2nhn5/DlzunlpTM8p5JePuCvw158K6sg5Ca7APLgnXlTzmUE+pBwSKJ/arIc/e9i0N/ydQ0Ed8mNz8Gs8wbhZu+w8G77/sis3tXgeH1NtfBXkyL/Zp1rol/mE/BI+1ZC1yc74jOPzy/l6W310T13KpRzcUwe5IedC3YJaBPWB+0T6VQvzBeqQ5PNaRZXzKF6LIO8oP/X5Oiaed1QfccTkOieKZ81YB/a3qtMhXvi6Jl7TyjxyHMFY1CpG67CLxmQu4tDfOXyE3CLP/Sj0XzaBfUVJFdPJqfzUlW1wH1IMuJ02110lVcyuulo7OZ0v10x4W8p1rPB4kXlTPhfhvmy7ZqzGZ1ylpLLTxud+t1XzdVsVk34pyRinalc5sH8Hab7cg987uzFO7sUOypl5q7YLW7WfXEV1rytyaK+eo84nW66Hx9Mnc1Qxwm2Z132Qtlle8JhU+r0Ot4+U5Pydrh99hMd0trtUket8RsA6VzFn5KidtSfu61RRxT1LTr4PlF72a2XQ/ZFDk1QxIyWjmMqHOJyi81e2Lr5SUvnctqLVPkn3kLgNe9qwz/AxRHXvctxerb3LyTZkH/bOwef3rlmfxPtCromT9ipu5heyUeuoP5BnR07lf7aqdfX73Dt82WcG40Dmdbq8XS3gc8FXxYiMyXhstEHtrINxK8iRtXk7STttbNmGtOtajQvYnM4G+FOeV7gP3NapYhRX+d5NSRWTAu7Tj8Db7r9K1blxOZU/JUZn5m4l+T5QeulPDoXuWaSMeaWSLiZtmkvaiOO6K6hswu0z7cQnVYzPV1Tzxya4jvC+qLI71bgjeZ8K4qq8jvxOxma86Oyi6jeKF+mrYlfyZQwQL62us+PrnHHPVDU++4cfaFf7yzX7zOjGSGTPcUXG+7qC2i5iJOF9Rn6P4R6yLYir4kXnzzZUdq8tBZVPcp+TMSLXQHib+0pO50t7J9XhVDHfSUB7tJ9Szh+q2LOa5a1qqeIkp/LvaLZGZ+Tk+0Dp5f8gZSf/TuyVmo0LM9sVgjw0K4doJSbpYlZsnSrcv/Igegw28LiUMxoHujWrqOIkR+1q3BxHeLvqk5DDob/wMRxs2Kv7SvhHtWWfdxO1697xdvqgs1frUY2j+1HujGX/nIwT2Nzn98LtoHuv02M8TmBLu5At14Daq37ZBu8DtFeVOaqcWZvItqDdzSXb4Hb3V/ZURxX73ZRUMZ2Ir/ZiplmfIzk7JVUM0rgd8nO9Sk6+D5T+n0fQEP/Q4hH0AdER+Y8/Hgv0S496f4m2qP6hyAj6JZ5zhuJm48pPjOZLn916R1AzeflwKnb/sKrafoX8QCu1urTfjKEPw6ZfyKd77Q/7K9sI4iUfgw/dkh+/o7bXqhhBf7VlJydUZ48+wsfRveqgRpCtwvuKbCfya2zVWfXlQ8fVGtAn+zn4vHbl9PViDNrq4+vFGoLu84yor6R74bnIh0b1vhs5d2/r3ufCveauGNZ1Bc/LOlbrxNmVT2Kd6e81kAOb2qA8ipdN0nkmn676xyS6EiO/x8vHGSBO81V/xqaP/JLseq1xW7VG+BlLbWyCXPg8FkHaEc+ARF5gPCE/aD70EYxNLcLnL1EbNrVHNcvHugpd2XPhceSRQOPchdfRkTFq+3pQfwV+1qhap8yFGFd9RH7dW6k9vw4m8vuYYiVvBfNDwvMK2jqrrImvDf24XoWfp5J8t5g8Qm7XY2FK+0fnlPuX65x+F6zaRwLaqqPCYyFzCM+BPwVuq8bN+ArP4XIqP+rmKzwOKht71yGfj5P9BbaZnByXe4/l/rsKdJ9rCH6f5P5mW4xiclxgzKoOXd0ulGNk6/qO7JXP7x3sV2lnzbIvSl+2d+VkWxCXtWOnj7fRynyQU/mvELlVV/pmGs2lY2Ucp/LfravHdSr/XUryfaD08l8rfzexHsCBFh73auWD5vVBxqw+0OnrBD5OhY/rZB/aUuZ0X6dk5oeM29EM4liDru9sjTJebV+jkRK3e9xPUs6ta/u+7FDFuy33s4vH7n63uV1gq3wCm/u5lzgzgH10n1RxOwK/F6PawG26+jpX7TPyHCv7KYinj7dd4LYqfpTjiHJMiTEqH5rVUfVVn4ou/p10xbr7/Ct/pZ3YkZJ8Hyg95SeHM65Y6JlWxpjFrFL1fZUg28Lj8FW2JGMqQWWrHooZGedt7lPsZwV+7lGycm5GGpFx2XYqm8h42pV83SsUw9VV2d5VXmu1d34m0ifcL1gzj+lwfxVb5YVsg49b9XG/gz1jaAv8kPHEZZ+89xzgcYJ2Jx8Dqlr8XqQ/+7hPZFt43Ip8DMj6sw61HfdJlc3tXNOegso3kvdxPMZ9aff5pQ8RU/m+s549J6h8O3LyfaB06o9g6/fw+kOQj03/1+/pidW90O/RiXFmv/e/Cq9pla7PYw2/7v79+3rNj8/xJPqMAPNOv7d97XzsI7VXUIPq5LM/yssfZ4ZqLPqKWS2K1RisB/E+jmw6N4pxv9oO66MY8ioHfTh7IxiHXOrPHwTO/cjPcyiGWmfjjPD1ExrX14ZavB7uPY65OPiSakzw3JzPLo+Y+Uec6buC7w1j+ZiVDSqbnm/OCM+61qi6r9Ca+loTL5v2zs8i6+/52A/PIWQH4hWjWv1sel+uzN+RT5KPNaQv/cD7c8+z6Hm6MQTjqI+gD2hOrI/wcbCpj/qrjd+vK3iN9Mm6Z7kUz7p7DdSWsAY+F8F8qj8OT9483z4GdXbPgENslXdE5hGeK3Gf6lS9mqef3xnUWOV3lJe1Fd7HfdQEiun2SpAn+83Qmiqn96tsCTXvjgfsJTWPanef7n39Dv0RbPEI+5uwzch+r9RjMUr7qrr5KK/7aEO2vS8a2cWZ2qGynV0T5HhOwAZVjJPxgvgdOWor74js/yrt1tJRxd4tH9fvX6mdOrqzCn4Pea68TXxlE5lP7WoM2apxiB31c9FHws8Vv7fzXtB2e9qwQ9qyDjHrI7BJnmNkq+SkfXeN0k9bZFt43EiMI9IHacc3ale2bFdyjvhdwue3yur+HhHkunM9I3Fn7asSfg/5PlB6i3+QcrdW5tHFdPZOTuVHTvryEAH37nO5z+/dBuk7KmfH5jBf0cWnOjtyKlvFXQ/vVXkF98qZpM373iUfB9x/VLlm1RrO1hV/VVNlczt4DuH3oBjH2+SdxQDxFVmL8Piqr/fJWMDuflCbHO6jjR/cjsQoh9PF7MTtSHhtUtUGbLASI7ItiJsJsi5wW+eDUQw2b6ecyj9SB37WsGpz/QmC3M9nKsn3gdLWTw7BB/no31pZG6h8MyVVTCeofK6VGOn/b+9csCPHcXY5d2W9jFnOXc+sorb2Z/RUVH+FASnqkQ+7FOegRQIgCIKUnLZV7iT19QbvdPZBXYe2FJndWEmn68jxV0ml85nJjFrTbK/K2TFS27O9uUKcZyTat/LQb6ST2q/keYbq242v/YzR+Uun1z/Xm6ROH+DqvKlTpNq69Vb/1HW2nDf7MNKN5kVqf6TrpJtbah/wr7rOr+pq3ziddPYuz9RJjun6NS5kf0XqvDVmSgf62ZjvKK5becf6zaFSPwciu/7OIe8O7Hl/4E+j1uax+X/Lo/a/2tQTP9p7sf4I700YO+Mn6hDfw5j58P6Ca6h+CfMZz3c3jEE/Y+Druyf2AR91+bfWjKtNwSfnhbQj2PUhFrmoA/JIzMu58ON6Fa6HPJxD2cJ1pBBP4d0RrkC8bK/iGGEsZ0CyT9uc7AMx9DHe0fdnksyj4jwzHzAP97/iWsD1eF8l2c8xSY1Fjl2t1JH7KFbn7zXPBeDjuc3cc6x2dN4DtNFRI/y0Z02NkfsO3vPCvel4YyHguIyFeO/hR7/zAfrq7OvnvM7N1fzV0ddnhPeS8ziWPm3moa+O9aPPXBxHG2F9rkMd9ux39wk+QFz309jgWGOnzhzxVdwrxxtX0KOzDVlDyDOBLmM5d65Fu776ZI7Qrf8ZrJyBJP3PSIV1p919SP9sr2Cuq1h79mKT+mmx4+H2x4h0tr1yVZyZjOh8H4fof/oJOq97RKrOds6Tdqn9EY4d+Y/sqzrRNpNVv1dK3d8tyTVI1086373zrkh3VrM/0iGZW9fvRB/JNnQ+SeevQOYKI7tUe9qEMaBfxqi6VRn5C23nldpPH8fXuLUvZ3SQ+ioje5ebdH0kWdWJ+upT+6MawYo+bVWfUuf5DpJsrS/3t4Ld65boN+KZdU46eydJ/RyI3B8OQ96xVrjy0MhKTOj0e0Tse6NVn9oX+jmmQ303XlxvZTSm6rLvmO8olarLfh2Tfduvktl5rvnU/kg6v3p+xXb6JOkLjldf86998AppUzK3vELqanuvyEyfjOrRjVGfY6qvVJ1+M6l17STp7EhSdZ2f8ybVJ9GWUvW530ol11vp9KmzPdN10vmt1P0V0rHl9+zcwWtS/a4S6WxKpX4ORDZ/reyPIf8EurU+6va3XMnjMP6KyZxX/nideAg/Nt7K2/WeWZ+/KoBcE9BH7EOdq45J0Knn2sVLnxrbGqjPX2ukr/1cyyrs5SeT66+5stbUdWuvY+jvrdFecm9W2MpnFK+OW5k3fRhvDPQZb+8aZLQW4vmccK66F5xfGcVhTM2t9hmLjPTOi0jtz86Na8k+5Hio89SYHcQ1XuZPO/tA3KqTbl77OUadz5oc180pnZ5xOcYapc7Y4ryQcwP6WsPUVdR1dXYOyFhSv4at7NVVkIcirjnXqZ1r2mvuWzB+z/rMwfmk5nwVzjGLn3mM2Pxw+MpN/hTcfKRu6BmsZT4YId/pAOc+w2rerrEyyyH1vheD8KDKG61+2Mpx2LTXGIr+1cb+cGUsevugD1LfjQJvGH3U0d77kGBuxpjfO3BuxPcypa4zr+6LNbKf71cR0/Hak2esOfMX5vGMdHRjZuhPPAWsD6jzvSDGWIPUgX3GdDEYl3rIMcA+EI++tU/UmYN28+JqjcyLdn221GcP1L4YlzjOB75zh+BT+6xVXZ6dXF++p5h9/bki6PSrNRuBr7FyPEI9bOs7A3s+F3KsedD3PnKN5tqRNTE/xNzMO2uSa3G8em3Mnfevtqw7At2+An2faYnj1JsroKPPNccxh/PMyJgZg/4M/IgPrpV9qLkaU73XIxjHM2FsRd0MxiM1161xsuLrHEhXR+s2pf4osePh9sfKn7j+uubaT3kc0lafgk+SY2pfXUW9PjUmdOO7fvplf2UtnyKun7bUukLtw5ZP9mvMrl1lbx0zVrZnOmQ0z8hfSXu3Pkm7fUCXZD/HA33jZD9FvdDOvJTUQZ232m2fkWSmr2RuUMfVdtqzn7quJiNxzKh/lUjtz8jxKdLpoNOJtnomOn/1aUvdqkinr7qZVDofxfV1NiXp7MqW/btLUj8HIvevlTfI9T9q+LdcydXxjmAOrs81P27E3/qZq22/g0pbgp7v6IRYOabGrnGwI+kLGRP0yfGdD+iX8SB/QvCJ5NqSug796vohawD62K92yX61JdhW6sjZqnRx0dX1ydbZkz32Lq+ky6WuN+u+Nbcwb9a+qyE64+HLPFwR9Tnfytwr680zgmSuYD91kDpzSZ/qD6s6mK2vjhnFOAtxEWszQ98R2jJW+qeuinBG7OPf7U3miZ79zTml9ivGrWPRbZ2rDs9zh3PkvdWR89ZYdT2jua7CXGp9PoGlfOqnxY6H2x8vZ+owGjvSV3kcslZ/lUjOI7Vt33bXT0nUMU/2R1R7ts0Vqh9Unf2R7tOlnoHMX2o/awSj/a39JO1dG6lx0zaSmpvt9FFG+pFs+ae95k4/6fKsum4M6MO1xqiiXqpdEdrdPF5XpNL5KGK70+/Vpa3TW+cUGfWPSN2/SjdmJCO6teg/0kOng9Sn1Hmk9qXzrTG63DufJG1nJelyqQKd/k8R6WxKpX4ORO6fHC5ypg6jsVsxH3v297X7KcJVOAf4kwl1mR/tTo9utI7016fG6Hw6f6hjwfbjofH3FVKXsaQbMyNzuIKVefHJefM7ZvT50xxwTTkmf9KUVF2NUeuFPWuWdmxnz+doXhnpr9i/UY06zKP76cUoR+ji19yNaZzR2rp53B/3ZrYefLA7JpmNS99cv3pjQqfL86pO8O/Wm+cqYyO1v4rzp3T7meCzivlkTrP8tNU50JOXOULmmfqk3os1Pv3MJ2Noc17xHqm6hH7GTl+o41eoZ4LYdV4wtvHNYYUc5/XdZE5HyD04E+f+BykfjJu89WLuXvwCwcvLPAiYh2u+zIwwL37YGMM1c1GXGJurcaqOl7XtM96XucF5sWkHxtA2nujny73akfogMS7g1z1otAtj8JVcP1CzvcxeVodcD21qRZ+2+VlDsEbmYp0yN9ebY4xP2xigLu0d1UbskW/COHKZxbbOnpNad3D/sM9YyQlYb/WlzsTHZu1AXYcx8DdmrpV2dwZyb9JXPL/m4j0B9mteXd0Yo495GIczQ4wUYQx95wGu6BFikIe6mlvqMi6YR+pdr/FAu/0RjkOYX6mYzxYZIyXnqZCjeXbPmgQ/czUWY9BbV2pEOyVrlDnYx24e6nzOG6PuuTb7zE0f/QjzAPx8XrkexudzXpwjqTridXPrp73zAe8B/bPGjqPvmrUrr4Z8zMW92Yvryn1M0G9Sf5TY8XC7ZSCPorf6Zwvz7t2bhL4xoPPNNtBeXW8yG9PZ7Yt6yb7trp9xYTX3kUDVnY2JZFwhbpI22trrOBjpMqY+W/lX+8w/4+7VjebpfBV8OnvV1X7VSbYl55BOZyx1eUVyPdDlLrZTbztFfTLyWZWOkZ9t15Y2qH1Ine0qMurPZAvrDt24Lk6nG6HvGUlGdttd7bOvDrZ0W/qqGwnUvJBO1wl0+qMinW1FpLOdlZW4M5/Vmlap1M+ByOaHwy7wLf/I0c05K3v3Rqour7XN2iR1to9Ixsp2ZwP7dV5zo+01RV2S/fTdkhX/FZ9OclxSbbnearMPtQ8zn66u2a+iHVJf+zO9Oq+djOZRRvpOqm/Xh2xL1l3UgfqMVcds+SA1ZjevvrZnPkrVMSb7SPpkHjIaA9mf2TNu+tjupJu3ky3Sr46rfRj1t3RJ2o9KUvWjflfnlE5f65yk/qw4z9m4Z8efEVk9m53M6Py3RDrbTJL6ORDZ/LXyY9zP1g1Qj6xJ/rrg2bVybmTpx8IP9Ad+zAzq7Ht9HPjffJwjdWfJWDkvVFs3L2372NMG2rEZF+xn3FVW/PfGBPOELtck97tbM+iTduOrq3nWX3fNfv1FjCvPe81tRq1Hjq3jt+Ixdm/u+Gftah0FPfug3Wu9X/UxjxxTc1NvDXKcjMZWmGc0Vuir49qdCX2I5X0Fxq797tw43n5ldhaBeUdjnT/rji7PkfOLY7LOUMdANw5oIznmKJk789W81NGnjVCzak9GueErjocuxl6M7X6ab42LLvOATpf5dXRjRqz6CXMj3kd7x4MxOjnC1ljzzFxX8t78cJgHtOLv8v8k2ARrkoebNvqVmuytG7GNj5CDN5o51Fycw4OTuanr8BDhzzsiXJ3fee0jRyAPYhnDd5gUbWAfzMu+toxlH3xHR7vvvOj7LniPhLWYJ7mQZ8017eJNne/0JNknXpL9nF9mNTHHxPHupxinG4MO39k9QG6cM66O9500yVzrOuqclcwr8zBmjs99AGyeV/X41H3I/MAx4DjzYKz7mXNrs42P6KcPY7HneKi1yfXUHMHnCuDX+SQ1lmM8E+ZX33MzZ8djX4ExCOPrWsF7Hoht3RGoffMV80m7e6POfchx1l4/z2/67IVcmT/XaXwEPT5AO9diH8xDm89woe9YxL1zbtZGjCTjbWEeea+h86wRh/iuV9Cbxx72jNkbW5wDsWbP5ug85pnnKNtD6o8SKw+XWwYCjw1r9VV3VGaxqk2qLvspmbuM7Ernk7raH8mKDyI1V/uibUsS+9Xn2VLXAtZN6vqSOhboZwx9rhKpbSTX0/W3JGPZdy3qRjGl6rg6xn5K6jpSX31qbtW3s1dJH6hjbEvVcXV96rK/IkfGHBXXB+pqG+x3skL6dmOrrmuPdLW/opO0zyR9Z3uTpH5lzOqeQ6dH3M/OtldkNa+z8qp5niHJyN7pO0nq50Dk/rXyCfg0nt9pw+Pg/a0/AzGoO+J3JnUf6jz21TlmlEvG0y99tXNN6eJV3WhOydydR7Kfbb8TNwf7tLfmS9K31vBVeGZyffU7OddXMV9yrxj3yJq6uSorcWdxsGnPaxfXtVS6+LOaSDcOVs+APvUqsxijuSHXz7X6ZlzOiP76eUU3qtmII2OOkvNkztkG+5WRnnGOTYztmdAnz0iOm8WQGhNGOqGNpF06nfEQa5Y5iHFBf2BM5w+O8RyN/MT4HbPc9pDjMyZS67M112oueRa/Gls/8WPPrN+MlVrdf+fwYvLgrR7WDm9kyXaNO+rXvasPMHOtfpB2oJ9+zlHXu3Lj1biJ/VwDUtfEWupYwVexnxiTPKqt9p/FbB5y675wJD4kXEtHF+PI+hjjHMYczTnCeR2XD7k9OTk+x9j2XHW51fxHkFcd3+WObpT3yj2whXNIN9cV87yCWj/Ic5T2WnsY1Tlr5NjcX/r1WZPnboUuZo2BbovRXnVrI17OSzv9sp1zZy26uGJ8mPmtciZG5g8Zq9as+u7lirW+G2ri/o3Ws7K3K7U8/XcOt+xX8+r5jsCmuDFH3hHwPZK6VvoID6d8dyYPg33t6pDZFxPsHcTKg2QsdfZTVznzngQQmzXTdy5rVNE3a+Q43/UzBmTO5Fkf/M+Ceetc5g2+1ySsJeuBPXMH8k+frkZ1DOA7WvfW3llHsO289L0PZmROed/UnHKutOX49Ekyt/Qx14ynvc5vbl1dRZ8uv5w370X05sU4+9oYj14dc6DTnz7tCrrVd/meCbmSR64lQdedM/ytpziWq18oc+2zvQH8t6i51JjOmfPOnq0jMn+kq4F7y3r1swb2iYEOyTpvgU/Or6zi+BoDansENmMI68h+xqpYM+OMSHtX53fi+tw7ZIXZerEho7hLc9TfM3c83G55gXS1rrquDyu67Kds0Y15tTwO865ctnyTzn6VrMZPvyR9toQadfqZdHXNfo2ZttqXru8126I+dTWvUR5ekepjv/NJnZKMdHkVfdM+kmqX1K0I5Hqh2iX1nyLkLp0d6aj27L9DjubQjet06mGkk85e74lOqg/k9VniGehsKTOfmvtsvbJSk3eLdDZE9qwFsp3Uz4HI/WvlD+GxP7/Vmj6oo7/lA50Oal/0n+HcyOMw/tIl9tNXmYGdmCv+ozUcxe/At+ad2VZYGW8uwDrrd89bMIc/vdiar9pzHvYi+5lXZbUunpkZnY95OM/KfKs5Ab4rua2Q89aYs5xY4559FsbkT6tGMWb7904y964+o5ql/kjdKrO9WYEcjsTocmevulj6dmtHR7vmoW51/7vY0OVzFSvPq635u5qNxriuUZ0/Cfdv9HzSvoe9/vc/SPkQ6sZlnwOSh4E9QVKHj3uVfjNqXG6a7Gdb8sYyj+x3pF8VWH2ArWLcGazLX+vIaFytwR6sYa63I79YVrbWgz1z3Mr3zHpWMefVXGbrhy271PlmtetyWz2Ldaz91GcN8iE/y2lmO8Jq3d4BdVGSUQ30xb6nTtU3+3XuI1wRA9yrbm3M4bNXuzrp8kDnmC4uMG/6eVbRqX8GOQ/kPSLmMKK7X2f+GW9Wk0+BvZnlePT+ntVI7p8cvgE3e+Vg4pMHwDG5L+i4SerB39q7fBjhm/1kK85VZP6VPTfBLE6Hvlzr2s+S8fbklOwZt5V/tefDtdq6vv4j36NrzC8MqzHqBy7OSM2rQ58VX3PJa/dFLGN1X7BWOVq/ZGVdn0rNnXpYk/phYhX8M27td7yrhq6X+es5q18HkNEzOzEmdHFFH86v8UH9s3CePc94YUzmZ+5bOObZa7uCvTm6d7UO2V+p0el/kHIEYqZ8Z3j5ta53djA7X65sJlcOf+oQdPwDhfTTBxmh3TzyZWbE3EFdFeZWjmDuxLqa2dql1oB81K2M38J4xqe98kI0D72t+c3R2MStdcwY1c5Z8R++1Lnsb+3ryr4zh351HkDHS//kI+Y1I7+YED/XV+fJ2EnO262FOOhzvH65pvQhJjpyMQ/vT3R1j54B+bxinivp9oiaWTfraj+fT+IzrIJ/6mu/cnXtvOeZczYvYHd+apJj0Cvssev1LDpPh+OyjpWMjVQfx+39xxPS+Zt7x1b8ave50Z2lCuv86rAPldw/z496mdX8F/UlxI6H27I8Etk95ruKVB01Sp16qfr0T6of2O/mQJKq25oHRnFHknT2Z8ueeVfq/CnS7UOnG+UvW31jSu1Xf9r42NZW/aqPfbCfY/I60o1sQjvngfTTnrp6tQ22cwxk7orzVv3VIp3tkyX3hb5XBWqd0waj/idInglJexWYjZHazzGdQKefSe7NGTJOjVvnPCvS2b6qwNb+djIak9TPgchl/4cUqYkcWcxXE7A9OvBJp09dF6OSdRX7SFf3qtvKdWsO6Ob5FHF9nW1LHFepfp8iXW6jvUmy39mNIdnXP+20a91rG9IH7EM3pl6h+inq6hXJeUA7VN/se+3akO26NtB/S/b4diKd7ZMlmdmzT52rz6z/DpnlMLMh1S5VN+vvldXx9T5aZRQj9VdI0tk/WaSzXSWV+jkQueQfpOjDjy3rewNH3iP4KuS6xR/XqnvcAL/5qUfXjZf0JUaCnrrOYnR1r7pZrqA/uswn5/3k/WV9tS4ruF4wRl171uAddGdiBrnmGNdU41Q8Z1L7yVYOot+Kv3N166267DMuf3UyynlE9We+1M3i5T3BuJV1Jntzreyd7xPInLs6ax/1oa6b/tb5fjbm1OWR57ODsaxvZc3p45j0W8V4W3DG8dW/Xju21jviyFrMbZbPp2LeR/dwhZW6bH447DbUg+77DV91Ezq2HiZpd83quGYt3Fh12BHeE/BDB9ccD9x4+hLDd7aUjIE4X8V4iXER4mZeOY8x0WfbvvJuzKkj3z/Zc5Plung/R6iLNcKHK3HNQZm993MV+QFkhD7kRL70rQM6yD0H9a6xo/p6FeapPpBt90bqemrdK5lnB7nXOVh7xoW6V9VO/DqXPuitUW2P8gLjeU2IwVju7zy3nW/HbN6jUKPV+Y9AbNbL2q0h62Ze+s5tbbCh48ykvYO9Svuz1yKeK+eq5xs6XcU1EwfJvnXQj7Y1Uxyn3zNgnnrtZLTerTPr+I6VdbkXXwnW1a27e8dwhe4MbD4r6o8SKw+XW37Ko7i/9aHqOqlUffa5ElO0aZfUnxHpbCkrPleL0F6pc5VRHa+UnKPS+SMdnd9I9vrPZO/57frWIMco4ByQ+uojafeac3itudc8bEv6SJ23jq3zQh0jtrHT3hLo9EpCfzXus0Q621HJeNnu+rl+SfuWpH+2P03E9UK12a9ncSby7nOkZO7Q+ShS9Z+ylmdJXZ81S92qSO1D/RyI3H/ncAf5nQ916b4bmtXL7wQeG/xrfPaB6+g7LP2RK2DerXjkY66vIusBs5rMcIy5E/dqal7Ws6uXtdz8jq3BmlgX251oX2Glrq6F66iGo/XuxThdjbo5ZnQxqq6uf3ZGRvMf2U/YWs/e9T6bZ+RDTM4Jdbct1HV0ho7kkmNsHzmjK5yJa26eq6wL7exzflfX4tij5/XZHLn3WD/rPlPvT6Y+n3K/wa8LK7j/sDLm/juHO7GotS4jvQ+9uinZz4cA4k2iz7OoB6/DnF6JN0DKUXLssx6KW3nWh17WfTSOc5GyJ3f883oF5ph5qBudo1E9EnKsfl3ezruyNm0rNfP+hIyJbjTH7L5h3Mp9JbN1APFmuciWfS+jeNbqWbhWxOeAudDPvNL3KMSo9+dVnM2L82uMrAPYz68Vo7XUPBxb9a9mz30Co/W59q/Os87hUd7ydw4/jZU14uP7HB3qfadF8QbwRuaG9z0YdPR970sdduOh2wIf5SxXxDhCnXdlPXtz9R20GntvnC3qGXC/2WP3lWueJX19aJsrY6qoz/HVJ+PX2Aj9I3hWc+4Z+PqOXs33DMTKdwpZT53Hfkfn060p719hf60zEIOxR2razdlhHTMPYd7VOKscXc8ejG/u2We9vitmLvn8rb7dma79EXs/pKzgfbIH1yvklWsjJlfFWmhHXEvnZ986IumHvBpzg7yfoctpz17lumqcTyT3TuqZqDAma5icXnP9PXPHw+2WRXlsyLSfVF36rUhS57lKoNM/S1bnO7reJPvV74xIZ+sEuvWA7bSDfeh8lKQb8y6puYht7FL9IXVKHZNX6NpcFciY4BU6n3cIdPpnyLPnyvhif6vOnf3de3NGtnLP2ki1Q+q29J3uHTWUvbYq3+1MKDKyjfSVkb1+DkQu/bXyY46fra/J4xAdXoPjZt/Z6MN3g9YVXfZXIVdh7J7vqPawN68VMvfK6ny5Xmo4i5kYn6tj1BHHPRpRz8ho3pV15Hyux/7e9cDWGXjWGdnLVo1XqDHos76VuicZJ8/BiL3xn80VtZzx7PUS3zXUudhPbLnGbGufsXofJUfGVLby6vD+HI31p4gItcragfXTR6re9Tk+15u+r2SUO2DTLnvy+5Tn3hmsAXvV1ce6pc0x3U+wl+pXPy12PNymsuLzFeRR+FZ/RGS1v1fOjH2HJFfXeUW3IlJ1e+25PrBdJbGvbVQj6WydJParz6sFXB94harjOvIjhm2wD6MxQjt9bGfM1IP90d7c8jzJ+mfbPlTdrP/JIjMb0J+dV0h92rZ0M/2zpN6/M5GVe/E73q8w0kNnS6nUz4HI5k8OV+DT6XfgyHcYj4P3s/UPj1r/+tQu2WdMta9AXKX7buBTyRqx5lpn13SErKFxqm6V7ie49o2Tda9z2c711XhQzww+Vec8NX98u5iJY2rd8/pqzMkrNerWNsJ66DMbW+OM4q7OP5pzRN3LFY6MEfJaze2rwh5Yo25/kazBVh8+tWaupzsT2oD8fdbQdj3VJ9eJnnup81eXdUbOnM0RmVNH5tFhbmDeX40zdXXtlazJaeqnxcpjAcxyy4IcrRXjFPjx48evdtqULoaifcvvFUIOSecDK+uqkv60rVnV2Uf++uuv3/p7xNjGqHPZ3tKB7fRRb1tbF2ePnB1/hZCDa7KN3mvVAXUG7XUv0env1TFpq345F1LPRM6bduN07Rqjky2fen5XxfVAZ/9Uma11ZFM/G7tV584+i3dUVs7EXqkxyTvvC/u5HtoI2K56x1Sb/YyV/bOS83U28gLas7m1I6O6z8a/S8x1K/e9Qizr1tkRfaR+DkTuf5CyIbn+WbG3xDhebXdo3yNudmd7hyRd3aTqjwjkHKJOtL9DJPvZ/pRcpbMdFc9mgj6vkG3HVHsV9XmF1KU+445EOlsV6Wx7ZCWvTo6M+QTxvI9ktq6ZbSRHxnyaSOry3kq9dDpIfcaAujeQfWRr/66Qmhd0fimO6WxfQa7MXWY2qZ8DkfvvHE541OzX1XaC7nEYf/b+F+0Zx6tt8NeZyl6Ixa8XPmWvcm1Qf41MTY6uteJc+esVIHbO+wm1MQdyzDaQa+beoT3pdEfJWLSR2fneC+vKtY3WmZhT/jpfam5bua7Mt5e6pqPU87tS9yv35tXUZ0KFmo7Wt6fexnjG3l+F99oW3Vmjjt3a9M24OT7nNIY2f+0s6hOfV+n3CrbmHNXjq3Bl7sbq7qOVeTY/HNaNePVheAejA+gDLe35/kYV7Qmboo42YtyjrGz0q1j5gtV9oQdrthfXz/hai073aqhJ5tCdiaM8e22jvdpDfWDTrudkZZ6t89HdRzmG9uoXj6N13cpxxrP38qtx9rkIV8Q4wspz8EpGZ6fTp47zmrli817ENjvP+CI1xivYyu3mv3T7Dyu12/xweOUXsk/Fg/3Xzz846Zr5o7O0vQl+/Pjx202ATV/bVRiXbdj6AsUc77jhzmDO/lFh19uts9MxXv3Kut2rjGXbKz7dXFdwdG+oEftvvaiTemvWxc76yNEcOphfPK8If5gWm+I9oCTqqg9S8ZykLXNIXLe1EuqYOs+EeP/K6lkY7YHUeZLVOUbk+FkO341a0yvXXmPRT91sP4/iPT5bh/Oy5yvnhvtK8n7M+4aY9Ovc9pFcL/dH/QDt16fVvPDhXhvN0YHPFpkHedb7H6yD83bs3d8uzkq+MMvjCvauBer+QlfL/6H+nrnj4fYtRKrO9mNT/+7LyO8qkS0deWX/06Tmu1dyfaNYV9Ug47+irpDnCp399AH7qbddx1wtYk2Aa50317IHx1eRjIu+6+e4qoPZGHV75MiYK0U6W8rMp6vbLf/IrHZnZLXu0tm2JMdlO3X1HpDql/0rzox0tqtkxsi36jtJOnsnSerS59MkqZ8Dkc0Ph13Qryjdgc/1Jeock7qrpMZMOp9sf5JQoy63TrclszFXPLCuiLEieW7AtvZs26+5Qdc+KrMYSWdPqfs9I8fYriKdDZFRDKhXoJ1j1D1LVuOv+iHS2W553f2cUvej9kfyjlyRbl50NW+p/RFdjHfJjM43c5fOT6pNmdH5v1NqTpX6ORD5I35yWNfQ9eFdN7DYH9282f8UeUXNVta+ksezcs38bAvtup+1DfYVc5VqX5Fc7yiGuQk6ryuSvnJlnYHrVkzItairfs+Ulfmks3UinW1vnUdxvpLUNdT+K6TOWftXyZX3USdSdXVeyXZHjnmX5DNA6no6H0ifLckY1Zak3jGpe6XUuZP6ORDZ/c7hV+CxCT9b/8X3JtTTp+37Gr7P0P1uHj8EP3/fX+ML+vpOgONzTPqgZ25zQnh/w5wB/+zjU2PUeVfYGoPdnJAKulqz+g7MGZw31w7mop35fIdtRre/Z8n8PEvUzTMFvLfn/uLj/0Bff8egA/TkSh9bXf8qrjdzdA6p/7N7WJ0vY5EzkG/Wuc63CuOMuYfM/WjdjsLaV9e7er8SE47WMcl6XBHvVXgWuLIGruZ/1R7vqYf3r9Scki1dZ09c9zMg71o/+87JlfV6Dh1jn6s6fHPclnT3QNpZu7IKz57MMe8fBNInBXJu20i+Ry2uvaI+n/Nc/bpunIz1CqwFLNW0flqsPFy+jMiq7rE5v+nSR52kLn2IIamXnONqkc42E8l+Xqt+VZLOfrXkPM+s80ycV2xrh+rTnZn0yX6Ktr0yGlfpfGYitb1XunGVaq+ij9d3ydb80u3vSKTq98T4agK5viT9Pk0yv2xXga390y7V/knS5Xc1Nf4RGcUZMbLV8exVpfogSd1/Y6TuWVKpnwOR3X/K5mqujF+/AyB26ujnfHwHkTrGiDrH62csoO+n8aoHdPlTlDMYMzG3PWRuYJ9rjbUntnHyuyl0SNb1DM4BNWZ+V/QKXJtnCFx3zaXzqaTPiNHYOq726zjs6YN9FLuSdXfcyv46n3OnODftjtU5YHUdz2Ir1yP5OebdZ/6VuGbPBP18tnwq5EfO7JXt7lxjW/3agK+xPpVureadksz2s9Nfsf49cfHFxrVKhb3c8oG0s/6c2xifwtv+CDZFsfAd2s+QsTMW+jovfb9A66tP7YO6esDR00/dWXzQnMUvLsbK/t74rh+y7QOv042oX/QkY0DmmHW35q8gc2XOWlNyyRp0PuQ+Qp+tmkm39toX8pjV9Cxbsbq5V+dfqcfoHH0XZufmO1KfJav3xLvhTLtXnu+jZ7PeM5+M9zM5j9arT6Ku01euqgdxlEp+beE68gNts/3VRxHXnLot9vhWdo+tP0rseLi9VB6FbvXS2WYiW3qxTx6iLv2g6ke5V4FOB1WX/T1Sx271V6Sur6uRpI/tKwQyJqRdeca8XoH2aA6hbY1SD+lf4zwj90Rd9duSo3l1pD1rVP21a9sSx9T2Edmat4u/MuZIHWHW/64iVTeyfSeRzvbVRUb6vEf2kvGqEHeVbvxRqff8kWfAiiSdHanUz4HI5ofDKxcwi4VtZP/rr79+s9FP+0xynO2qQ3Kt6n7E/9Qcoa8t9chIV3M1bvq7vi6GMrNVwberUepgTx2VzIN21sg+qAPnwQ7aRjLKy/Fc8eHa+V0lrsd2SvVNqbllDMiaKekPI9secS8q2rN9VshR6Www86FmQLtSfbcEnGM251VCnZ8ZfyTvmvcdUveRa95HaUvd6FnyiTLL9exarI11SnlmjYif104yl/QjL/t5VSqpS//Rc7BiXEXsm1ftV3HszAfRT7b8O+lqlDKKWeeunwORL/GnbI4UrZO6FgtU+5B+cjYP6PRbsmdc55u6bFeZra+Ok6rLGJBtoH2kju5N9tP+DMn5bK/MW2tg7pK+Vbbsq1JBV2v4DIG6XkmfHFOlUm3ZH8nIb2X/9kql83mWSGf7ZHEf9uYutf1dJdc3Orsdnd9MjoxZFan6q+7FLrb6PeSYWaxOJzmmSjKzd7Yqq34zSernQOSydw4f8X+2roOYyFXvmnRrSV19TwRcF7qzeazWUlz/aJy5weNG+/va+arDZ5bDaH2ZAzGyJmCeUu01t5U6ZjzI90CqbYu9/sCYnG9P7pXZmMzNNldrthfGZsyK63gm9d24Oif9o+vbwyvmgLreV80Lr9jPZ7Kav2c6/W3PzvtXpVvv6DmiD1fPYtaE9laNcp69ENsz71z0c95ur448S42bdLFh75oYn7FSMpY6UJ9fn0a4N/hlDOnmHrE1V0fGm8X+Rf202PFw2y1Hxylnx29JxpfHwRv6zPSSurNS49V+zfVZ0s2bOvuQfikzmzLzgVetV4GuvSXpK1kjSP8UbV73SrcX2X52DaVbr9cVSTpb1XUC7zgz0tmfJdLZtuTVNdojdU2ZqzZRf8s/knWRkf2ojHCvkneetRnVPhrT6dV1Upn5VF3290pX56T2oX4ORJ72R7CPfLKVv/76/Y8+X8mjcH9fic889P3Uz3cy9JXuDwQDvulHnxi0z5Ix7YN9eOzl0h99lsxrT441DyT/QDd91m396FNToU+utY7pI7m+hPHE97tMYnZ0MY/CHLnGUW6VOs66uH77HT9+/Pjb5rgZ+HTkPFD9Ruf5LNae/BH2yra50E5m++XYOma07g7Gdj+ZOHJOVudlrciee/MKWCvzHlnbkZ/ePANy517PWnNe0Ql97ayZtmunnWOz/adijWxbp7xf6Vv3Wc3wSRHjAlcEnXulTnEuIA/nR/L8dvnQP3LGgZxSzAeYu/ZTp7/5ZBwxXwV4DhgD6XLP2MzJNeOO0J+vG86X89rGh3lrzsy5Sf202PFw+/YyWudIvyqPTWr1SI291d8rdfwsl5nUOOqg6hXpbJ8qtT6r+Ve/Lg6kLqXS+czEMcxr277trv+VxLVBZ98je2Ps9V+Rr7wXz5RRrVM/aiNZV/hKdX5lrtDpoOr3SsZI8h6Gut6Efvqn35Wyhxxjburq2qCuL0U620hkZoPZvEqlfg5E3vZ3Dj+FR13+vnbrxPbM9Rv7sZn/M9fZuYl5Re41D3OFLn6updodJ9nPNjFWqPHOkj9FcQ1HyO/KiEN/FMs1aJ/N2a13lmfN45lk/Ny/Ou/ZPI7uSXIkxrPrd/MP1LrWmz3rzhX69M17GNvST0hOcOW5eOVPcbt7AF2t8xEytjEl2+xN1i9t6KmHOvq11vRnzxpwXMpRcvzomY5OgdF8dV0jv9Qbt/PXhqycI/y2ePv/IeUZrOSMDwdrVqSVAs5gjpWNypsAtvLaC3ms5pJ0eXhTqN/zIKljRjGe/UAfsWctMqrRHhjfxals2Ss1j737v8LWvVZz3rsGqffIK2Hed839pzGrs+dXn3yOjM4h94DPv2fQ5fusuV4Fdb56DdSp7p/k/mDTPtNB55exRqQPY+pzkr5zOgfUftI9n6qufn0ZxUrwqetBtzI2qTG2agRPe+fw1fC7dxZcv8jmhtBW8PGwXonxoW6g+i325FVjOj8xbNfDNBpT6fKo761Vn3wnUeq7JPlOlvMyxjzq+BHVz/F7cZxr4Ryt5pB0caCrI+Dr/bX1ntrKuzbsjXkTW3Kes9Q8jNvFN4eV3N9N1usV5HtBW7w6t1fAmhCf2QlnmPPEM30EPt07iJ41Y1Nnz2ad51kceXZ8GqPnxVU1JD77x1UhtvE9A+yhZ0Sdfohfb+wb0zHGRhLjeEaIYfw8V6Be9E2fFfg64JyZn/FGzGwVYirCPeF6JdczpP6euePh9rEij4W39lcKdPpXSF3/aj1emXOdK/vZPrKXZ/Y/5872llTf7EvaU2a2VRH7WYPUZ/usjOZYlTqm9t8l78hjz5x7fL+SSHf/StWnSPbTfua58GnyndYyk7qH6qDWALJfRWa6pPpl/4x0sZJqq3apPmfORFI/ByJf+p3Dx5r+vpLj6Kcz+jwT5kA+uVbwOEg/W/+F/ijnZ9TNuZi31ivb9buaZ+9h5jWqR6Xmn33rPIu1Os8WV8VZZXSfzajnLnl1/iOuymPPWWXOVf9PqdMVsOZ6JrqfZLjmWY2qT63pkfN6Buae5XuzTXdfoEPqfrr/I7BztnJfHKPO2OpkK/YW9YxnbHDe0TydrcY8er5rLh1f8p1DClQ3teMVuZPLVh5XU9dFPw9J7XfMavOKuo3qxdxpq/2OXO+e3Fe+QK3Q5bh6HvbkW6l1ksznTPyryLNoXrX274Y6XVGr1X2XPf6fVrM9jGo7OsOVzmY9iIGkzxV7eQRzeQZHPwh8Ra6sIXUznuci46cO2Xt2Rv5+KAXi1g+pq5gXctUZINYWmx8OP5WtxeWmfDdyTazT/mzN2PIDFD7dQdPWxbiK0QHPtUDtr5D+W19MM489c1XfOu7oh8yzjOq6t4YzjnxA6caMcn0X1KjWiX3+JD6tZnuoXyih9qHWPPdl6+zhh49jPm3/tqjrm/W/2to+gXqOPCdAPa1pntUVjFHx64Cx69ebPXNczcrcX+IfpLCZKaOHZPrkxkvar+KVD+zM27Zr5KXTbr1eseFD2z2t/1CAF8Dfsd/mlWvJ/hYjv9k/8sibY89cW77E5YXmpNZZ8M0174E8hHY+iI7EzHgzrOmemnmPZM33rvcVZH5w9F44srZPrMcVUFPOCmeAetr3H4p47vKe0Sfp9oKY+KVv/mOCjC+1fxWj/dszX31e0c9apH313rv5HepGHampdUXHWfF8gmdnz/5VOJ8Z2//RgX3kXSzNXV9CrDxchvIoXKu/SmRlni2fzi5V/9VkdQ2zGmWMbD9bIPOq/SMCnV5Je7ZXZKuG0NmqrPqtSMbK9tk6fkdZuQe83jKX1Tqln7gPUu3Q7RVUXdVLZyNm9l8hR+fL9R+Nccsxkc52RpLO/iqp1M+ByKl3Dp/xUzPmU2RlnpFPjQWpq9+Bdf6fTl0DPB4sP1v/hTV1NXK9XYxn47zmZd1rfw9bazkSUxg7O2fQnae8Xg1xj+7d1TltxUt7PZ+vYrR/72a1Hs86R0fJfEa5cT611bNq3/WnffTTjW6eHEcbyTltd8+WLt6VZG5HuSLGzTp5hur5oH/0+WVceNczEFbO08f8a+W6CRbx6PwU3njE6B4KNTa2M3N+Erle11WpD+TuAf1Mcp5a+1HOV2Bc1rs6x0o+nX00Rj1xz2KM+rDZ+iB0dQ5b9bmaut4VGDNa76vz/yrUOls/66W91i/rnB/08NvqS90rbaM9TD2+mXvmnXPQHsW7kr1zfOo3Mn8S9awA/bo3R55F79zflbM4/XBYi7LF3gLhj/iumxuxNe/s/RzisXD/GKaxmANbzkMc/bnWd8XexRXvHxGDdY3qyXpBG/36zgvo90zqu47MmXmt5OBedmuVGnd1v/HN/Do6u3mPxmc+W3tuLKg3dq55tv4kc1sdM2NvjO6svQIeyLNc2YeRPffgalbrccVezfC5IayZmvmMBM5ytvM9P64IcbAxDulizPqs05qkHrDhz3MDsCm1Pr5fhn5WO2w5xzPo5s/cb74G7FV9XnMP1HM6g/O79cx/O/X3zMljoTwlvq1Ap/8OMtu7T1o3ZK7QtbdkxXc0z0yO3gMZP9sj6XLzOrND1e+Ro+v7BFnNfasuaf/K9bhKxL41kdrGLnWMvrWfbcg2VDuoU5y36rJ/yy2vkkq117P5zrNaqZ8DkelPDv1u7jvCumbfScJj8362vhasbfYj6611vwrPVuZqbiv7k3BWYXResyZ7Ys/qOCPXYW5gfqM8wbGjHNOe84z8PwHym635CKt7s1WXtOde/ankmUqyTukz2gfH41vrWp+t9PHLuOqk5rM1b9Lpbm6O0n028Px6ZjufPIdHv7a8io955/AVuDFct9aFz6dvXsfK2j4B98Jc7UP9orBF7lU3LmPvpbvBtxiNyb3JPEf5dfoza+l41RlnvXv2dJW99dh6YN8fDv9L7hVnxBqhzzbk/aqtO1c5zjrTzn6HsSH3SlLnvOrcb2McuZ+36HK6+d54T4z2nvNW74E8m1/hzGx+OHzGzfRqWEM+wPJhM2LF5xP5CnnnO6aQe0N7z7uAjh29v4HdufDJuWYYu/sit4XvSjEeZjHSxzmBq3nyIMHOdfRFdGtNGTd5xnsvXcyct+YwY8s3a7Sylu7dvqydezWa9+g6YK//u6Eu1pVzZ/6+xwfotdW9cDw27+ns2wZi2GdcxgV09b4C9Ai69DWe902S46+A+W6+3vk+i2dvFe8Jz6f/DuJj61Z/z9zxcPuyIp3tltfI4/D/akPtZxvsp77qiNHpz4h5XRFXsm97tn7bmQuo72TLPpIcl+2ZZO6fIqu5pxwZU+WKGF9BuvtCtEu12c82dH3RVuNmH/SbSZ5Xx0jV284xSO3fMhbpbGflWXHfLfLKc1apnwORU38E+5PFB0lnu+U9Itnv2impX2mnvPOhLrRHeQjt9FFX251IZ1td/2j8lXJ0jqPjzsjeOffUGTrbp0nmOTu/2YbOhtTzDdnWLtUXqm6l7tLZlBqn9rfGf0dJOvtIOjq/K0U621eSpLNV3Rmp1M+ByOavlR/jfra+DuZ8/7j/c6h7Qn9rf9Ln8cD+bSw/lq84xxHOjK2QK3Trq/Ns1WCFrFEy+3X2UeocqxxdZx13dp/2jl9Z72qdr9jrZ5NnN2uV7c7Htdn317o5TrIOtr2fMw7zpG/di+4ZUGF8xkjMzV89Z67ZZ3y1/0lsrTvtXb33jF+FMY5zTvor9+unkrXL9YHrS92z+Vb/ICWL94wvjDdj8tDWA5xfTKA+9GHvOXN/mcuxGQP9njOwd/6jOE+tUX6hS59ZXjVGrrfaruLoffWsfJKrvjC86ix8Iuyve2Ud8l7rqPc3fvWcZFzwwyPkuI66H9kfjVlhFJdcq+2TOVODEXX9szm6WqFLmaF9z/3rmMyr031FrJnrEfor3xBdxeaHw69CvuxZi/rprLxI/6mQe37Ycx+SfNiuPADqFxv6xODKjY++zpuM9K8kc/dF+vogyxy96fEH1tc9CLAjnpmcR501mrE1z9Vs5WPuW4xqAvmBRF1l9R87ScaULtfRfJUztV6t0Rk8D66HK7o8Z9SEM0YbPTXV3/Xxsj02+vhmXCTvCfr5D1YY51jj1nno1xhQa7RaM+JVUkfb/mrMV2GNrcEZMoZrrnU+O89ovM/4VcjNtZsbubpP35HuefQ06u+ZKw+XW25ZkpXzkj7ZHok+jxv/V9u+7ZT0GcmKz9Uym7Ozba2v1mPU3pLRPMqW/YjsyW+PbOW6Z949vt9Jct3ZTp11Bq71LGqD7I/akDGBtnGh+tc+pM52l9teMbfs15jVB0nSLt2YM/KMmCnJ2Xmg058R6Wy3/C6V+jkQ+TY/Obx5Po8z9LP1exvor3zHps/IfzZH+vsd1Myn8nigLed5BTW3jhUfydxZf65j1D5Lfqe6J9cZz6r/s76rvmrdn4xr5Ccx4j5x30g9Z1mbbGecCuOMabzqT6zZ2bOf+aTOdn1O+AxI6Kdu5FPpdCO6uqZuT6zk6LgjZK3J/czcxMpzdQXEnJ27m53UT4uVh8st30S29vNxs7Z6ZDZ2ZutkNo8i9nNM6vfI0XFn5ZPzg6UAAALnSURBVEhduzHpO4qZPrecl1rn71xfYL3Q2VbaQNs4kH19u7pC9jMGbPlDxoVq72w1V+2w1Qd1nVTSVmtyRLo6Zv9ZUuc9I6/K+ZZ/pFI/ByKbHw6vPATfTZ5Vm7/++uvS2MTaitfZyaPqUmZxZ/NpG41P/ai9V86MfYbM8lnJs9ubOm5r/1bEGJ9SuzN5fMoaPknyjFAf+lyV9LWPD6RNwQeMK9mucZVqs80V+fHjx2+26o9UXR1DX3v60VbyzNc+VHvq0o9r1UHqJXX6Z7vrI8zr+NrHl77tmWz5bNmdZ2WuTo6OW5Hcm1v+K5X6ORD59n8E+9lSD/UzD/mr5aq1ZBzPU0U70vkfkU/eizPrQlxbxqnrPbv+jD2SFZ8r5Yr5rojxHeRIHXJMtqvUezjPK3RnU+zjU/u2kSR9JP1sd/0ubvarvfbV5bguDySpuoxb+0jtw6gvVX9GVuNAXUvaV6Wu95brpFI/ByL/j/88nH/xn//852frd/J9g5ubm5ubm5ubm6/J4zPhz9a//vXvf//7Z+sf7n+QcnNzc3Nzc3Nz84vlD4d8yuRvV3G9Uv7/z38ZVtt7xdxGMaqda67HfrXbv0KuiEWMUZwrc/0u8oqavLruZ+fL8bSfnX+9j2jnvbclq/ldfb+O5FXzXCHmujffmb97V+N286irY7q8bI98vNru8qhjRvNWHX116aMu/Wt/pZ15advKLcfon/YVH/rpr08XA10ndY567aTGpJ26Olb7rM+15tL1HaPoU/UI+m6M/l3cGquLnXFH9trPPL1WXY05G5OiPftbLP9a+ebm5ubm5ubm5ntx/1r55ubm5ubm5uZmyv3h8Obm5ubm5ubm5hf/82vlm5ubm5ubm5ubP5f7J4c3Nzc3Nzc3Nze/uD8c3tzc3Nzc3Nzc/OL+cHhzc3Nzc3Nzc/OL+8Phzc3Nzc3Nzc3NL+4Phzc3Nzc3Nzc3N7+4Pxze3Nzc3Nzc3Nz85F//+j9KRQH1WFBYRgAAAABJRU5ErkJggg==

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