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记得《疯城记》吗？Reece Shearsmith和Steve Pemberton再度携手归来，联合BBC推出这部暗黑喜剧《Inside NO.9》,关于片名，主创在一次采访中提到这完全是随机想到的一个名字，原本也不是9这个数字，后来觉得9更加顺口才采用了...该剧与《黑镜》的结构类似，一集一个故事，每集的故事都是独立的；看过《疯城记》的人应该都为二位的演技所折服，相信此次的6个新故事也不会令人失望...在青梅竹马小兰（忽那汐里 饰）的鼓动下，工藤新一（溝端淳平 饰）半推半就乘上飞往京都的飞机，去观摩正在那里拍摄时代剧的毛利小五郎（陈内孝则 饰）的表演。飞行途中，名叫大鹰和洋（波冈一喜 饰）的摄影师陈尸洗手间，引起乘务组的恐慌。工藤新一就在1万英尺的高空展开推理。好不容易来到京都摄影所，针对男主角樱庭（中村俊介 饰）的谋杀预告传来，不久更有一名女演员遇害。新一和对手服部平次（松坂桃李 饰）展开竞技般的推理……故事讲述了东北一所大学，五位同学之间的爆笑故事。这里有沙雕男友的欠揍日常、蠢到流泪的钢铁直男以及被气到“黑化”的班主任，每个故事都能让人笑出腹肌。　　故事来到1970年代，世界充满了希望、不确定性、压迫，还有难以想象的挑战。两位女性在社会变革带来的机遇中前进，始终矛盾地紧密相连。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.According to the proportion method, the monthly minimum wage standard in this area is calculated as follows: monthly minimum wage standard = 210 × 1.87 + a = 393 + a (yuan) (1)李敬武蹙眉想了好一会，写下先救离自己近的那个，然后就搁下笔。