1. In the border breakthrough mode, the player who takes the lead in killing the BOSS annihilation eye that appeared in the final stage or persists until the end will win the final victory.
# Exposure Compensation #
某朝某代，盛世繁华，国泰民安，世人皆赞小皇帝 英明睿智。但事实上，小皇帝尚未亲政，大权把握在太后和皇叔手中。对朝政不感兴趣的小皇帝一心想出宫游历，并对听戏十分痴迷。一日，小皇帝发现一条宫中密道，悄摸溜出，不料 密道尽头竟是一家关张多年的瓦舍（古代剧院兼会所）。小皇帝偶遇盘下瓦舍的戏班班主白小青，从此隐瞒身份，开启了瓦舍小厮与真命天子的双面人生，与一群奇葩艺人为伍，历经波折，纷争不断，难舍难分。
"Well, all right, go to the store and choose for yourself."
见大家都瞪她，忙道，送回去大姐就活不成了。
武当大殿上，玄冥二老、明教高手、武当弟子、赵敏、朝廷大军……所有人都亲眼所见《太极拳》。
There is still a gap with China.
作为实现愿望的代价，在无人知晓的情况下不断战斗的魔法少女们。
61. X.X.12
漆黑的夜里，史密斯（克里夫•欧文 Clive Owen 饰）无意中被卷入了一场黑帮的追杀，穿越激烈的枪林弹雨，他解救了一个在襁褓中的婴儿。婴儿的啼哭，让这个功夫了得的铁汉遭遇了难言的尴尬。除了在超市购置婴儿用品之外，他还得解决婴儿的喂奶问题。这时，他想到了在妓院工作的朋友DQ（莫妮卡•贝鲁奇 Monica Bellucci 饰），并强行赶走了嫖客，把婴儿托付给她。DQ其实对史密斯怀有深情，却一直没有机会表白。在蜂拥而至的黑帮暴徒来临之际，两人终于坦诚相见，并肩作战，照顾婴儿。经过史密斯的调查，他们发现想要加害婴儿的黑帮其实跟军火商有关系，而且他们还雇佣了很多代孕妈妈。史密斯隐隐觉得这背后隐藏着一个不可告人的秘密，于是他决定铤而走险，一场正邪较量由此展开……
来应付可能突然出现的的意外状况，明枪易躲暗箭难防。
1853年10月20日，因争夺对巴尔干半岛控制权，土耳其、英法等国先后向俄宣战，战争持续至1856年，以俄国失败告终。战争的失败引发了俄国国内的一系列变革，其中也包括了废除农奴制。
经过九九八十一难，唐僧师徒四人终于到达灵山，求取真经并修得正果。师徒一行驾云回到都城长安，觐见唐王李世民，并向其讲述了取经的经过。话说这一路真可谓艰难险阻，困难重重。通天河有灵感大王阻断行程，伤害性命；狮驼岭又有来自灵山的三神兽为妖作怪；期间更有师徒心生嫌隙，导致六耳猕猴趁虚而入，上演真假美猴王的好戏；更有金平府犀牛怪假冒佛祖，欺世盗名，引来天兵天将除妖。这万里艰辛，一言难尽。
《唐突的女子》讲述了本来是小姑子和嫂子关系的两个女人，变成儿媳和婆婆关系而发生的一系列故事。
前SAS特工，声名显赫的安保专家丹尼·斯特拉顿（奥兰多·布鲁姆 Orlando Bloom 饰）遭遇了人生中最大的劫难：藏品被盗，女友离去，身败名裂。沉寂已久的他决定东山再起，一次看似简单的任务背后，却藏着更为惊人的阴谋。面对警方的误会，队友的背叛，爱人的失踪，反派的追 杀，他该何去何从……
The Publish-Subscribe Model in Real Life;
Taibai Flying Sword: Drink a bottle of wine, Taibai Flying Sword [Skill Damage] +20%. (Do you need to consume? Ask for advice.)
Is to create a factory class to create instances of some classes that implement the same interface. First, look at the following diagram:
When you need to add a new state to the light object, you only need to add a new state class and slightly change some existing code. Assuming that the light object now has an extra state of super light, add the SuperStrongLightState class first:
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.
