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主人公佟承勋是一位出身名门，八旗后裔。父亲身居高官，又救过慈喜的命，对太后忠心耿耿。对承勋的改良变法抵制，为此，父子经常闹的不开心。在承勋的一再支持策划下，维新变法开始了。很快得罪慈喜、李连英、贺世龙等保守派的利益。关键时刻，袁世凯的叛敌，宫廷政变彻底失败。六君子血染午门，承勋也入狱待毙。为保儿子，老父向慈喜求情，将罪名揽在自己身上，上吊自尽。承勋被放，见家中哀声一片，才知缘由，跪在灵前叩头坠地，血泪纵横，凄惨之极。因平日与贺世龙结怨，贺借机落井下石，耸恿太后，说承勋是幕后的执使，想致太后死地。慈喜勃然大怒，接受了贺的毒计，佟家满门被抄，老父尸抛荒野，鞭挞二百，十八岁以下的男丁被阉入宫，余下人等世代为奴，永不翻身。 　　马素心（蓝洁英）是七品县令的二小姐，一晚在回家途中，被人贩子摞去，准备运出京城时，被承勋救下，成为知音。佟家遭难，素心向父求助，并与哥哥离家出走，重男轻女的老父无奈，花银十万两，买通狱吏，成为马家的奴隶。素心得知，欢喜不已，而承勋憔悴不堪，已几夜不眠。在素心哥哥的帮助下，//Since the single pattern is instantiated only once, the following instances are equal九朔满大（菊池风磨饰）是楼龄88年的5层杂居楼“巴别九朔”的新晋管理员。27岁的他梦想成为一名编剧，有一天，从地下一层的杂物间误入实现所有愿望的虚假世界“巴别”。在那里满大看到的是现实世界中放弃成为导演梦想的好友后藤健和古怪的大楼的租户们。为了从说出某一句话就回不去现实世界的“巴别”中救出同伴，满大在神秘少女的引导下揭开了大楼的秘密。板栗看见三人，忙问道：六弟，怎么不进去？大苞谷笑道：大哥先进去，我跟黛丝和珊瑚说几句话该剧描述主人公Piper（Taylor Schilling）在大学里结识了一名毒贩，从此与她保持了长达10年的关系。警方破获了这起贩毒案，Piper遭到逮捕，被判入狱服刑一年。Piper的社会经验很少，面对糟糕的新环境有些不知所措。在联邦女子监狱内，她将第一次领略什么是「监狱文化」——这里有敌意，有包容，有眼泪，有欢笑，也有爱。她虽然得到了一群性格坦率的女囚犯的认可，但她的牢狱生活绝不会一帆风顺。从新兵登记开始，这几个欢喜冤家就彻底结下了梁子，随即搞出了无数令人啼笑皆非的荒唐事。在经历了温指导员、江参谋、康班长、姚排、牛副队长等人的点拨和打磨后，他们逐渐磨去了浮躁，精进了技艺，完善了人格，最终成长为武警战士。For codes of the same length, theoretically, the further the coding distance between any two categories, the stronger the error correction capability. Therefore, when the code length is small, the theoretical optimal code can be calculated according to this principle. However, it is difficult to effectively determine the optimal code when the code length is slightly larger. In fact, this is an NP-hard problem. However, we usually do not need to obtain theoretical optimal codes, because non-optimal codes can often produce good enough classifiers in practice. On the other hand, it is not that the better the theoretical properties of coding, the better the classification performance, because the machine learning problem involves many factors, such as dismantling multiple classes into two "class subsets", and the difficulty of distinguishing the two class subsets formed by different dismantling methods is often different, that is, the difficulty of the two classification problems caused by them is different. Therefore, one theory has a good quality of error correction, but it leads to a difficult coding for the two-classification problem, which is worse than the other theory, but it leads to a simpler coding for the two-classification problem, and it is hard to say which is better or weaker in the final performance of the model.