The uneven green after being dyed blue is exactly what we want.
纯真的云想想从小母亲宠爱，生活幸福，个性善良，没想到家庭生活突然发生了一系列的变故。在继父云逸茗种种算计之下，云想想险些遭遇不测，母亲叶卿也危在旦夕。为了保护母亲，云想想从逆境中奋起，在傅司寒的帮助下，与云逸茗斗智斗勇，数次挫败云逸茗的阴谋，云想想自己也在磨难中成长起来，从一个不谙世事的少女变成敢做敢当的新女性，并与傅司寒收获了甜蜜的爱情。
Comparison:
Condition 5, Critical Strike Changed to 80% 4823.9268
苏颜（黄姵嘉 饰）是一个看似活泼开朗，但其实内心有些自卑的女生，因不愿敞开心扉，曾经和家人、朋友发生了很多误会与矛盾，在男友陆瑾瑜（陈玺安 饰）的关爱和照顾下，在结婚前夕她决定以邮件的方式向亲朋好友吐露心声，揭开所有隐藏的真相，这封密码信也开启了他们对曾经那段青春往事的回忆，然而一场车祸却在此时不期而至……
原来，第一道关是让参选的人亲笔书写家乡、姓氏、年纪、兴趣专长以及家庭成员等，包括有几个小妾和通房。
Not expected:
'w. P% n' E3 x
你记住了，坏事咱们坚决不能干，害人的事更不能干。
PS: If necessary, I can make a video on the skills of Blood River. Please comment or put forward different opinions below. Please indicate Bilibili Xilin Gyoro for reprinting. Explanation of Supporting Victims and No Resurrection
Don't laugh at the smoke-pulling plane that passed over Tiananmen Square during the National Day parade. The pilot was not a super pilot. He said that the war was all about letting the recruits consume the enemy's troops first and then the veterans were on board.
那霸王的意思是将韩信摘出来？尹旭点头道：既然如此，就先不牵连韩信和彭越的。
Power Up -- Red Velvet
该剧讲述了不正之风不良女检察官由于记忆丧失,稀里糊涂地变成与自己长的非常相似的端正的财阀媳妇,人生发生大逆转,开始走上充满危险跌宕起伏的寻找记忆的故事。
The function of + = means to accept the input of other operation instructions while the macro-defined moves are issued. After observation, it is found that U, D, F and B are the letters of the English words above, below, before and after.
背景设定在20世纪康涅狄格州的三河，Dominick的兄弟Thomas患有妄想型精神分裂症，通过药物治疗，他能正常在咖啡店工作，但病情时不时会发作。Thomas认为他能做出反抗牺牲来阻止中东战争，在一所公立图书馆割断了自己的右手。Dominick看透过了他并没有将手接回去的打算，代表他将他从一所压抑的、治疗危险精神病患者的医院释放。
民国初年，北方桐城县，阔别家乡四年的展家长子展云飞在归途中，与萧家大女雨凤结识，从此两人魂牵梦萦，两情缱绻。展家次子展云翔向来与兄不睦，加之其妻天虹少女时期就对云飞充满仰慕且一直将真情掩藏，更使云翔嫉恨云飞。为泄心头之恨，云翔在向萧家索债不成时，竟一把火将萧家的“寄傲山庄”化为灰烬，致使萧父葬身火海，萧家五姐弟流落街头。
普通大学生林海更新微信后，被拉入天庭交易群，这是什么奇怪的微信群？里面有孙悟空猪八戒，还有嫦娥和玉皇大帝？不会都是骗子吧？但是林海想不到的是，他们居然可以交易各种神丹妙药，让原本平凡低调的林海，摇身一变成为了实力高强的救世主！从此他的人生变得多姿多彩，正义善良的他也为城市的安宁献出自己的力量！
From the defender's point of view, this type of attack has proved (so far) to be very problematic, because we do not have effective methods to defend against this type of attack. Fundamentally speaking, we do not have an effective way for DNN to produce good output for all inputs. It is very difficult for them to do so, because DNN performs nonlinear/nonconvex optimization in a very large space, and we have not taught them to learn generalized high-level representations. You can read Ian and Nicolas's in-depth articles (http://www.cleverhans.io/security/privacy/ml/2017/02/15/why-attaching-machine-learning-is-easier-than-defending-it.html) to learn more about this.
