"Then you mean, in the subsequent battle with the" killer bee ", you still rely on the guns in your hands? If so, what effective means do you have to persist in fighting?" I asked.
有时清醒的时刻拼命的想找些麻醉自己的处方，被麻醉了，却拼命有了清醒的理由，真实生活，我们经历多少明明是清醒的自我麻醉呢?
Teerakitkankul家族和Wirayawanit家族的竞争从爷爷这辈开始，延续到了孙辈，看起来竞争的DNA直接遗传到了两家巨头家族集团的继承人Anawin Teerakitkankul（Alek 饰）和 Milin Wirayawanit（Nychaa 饰）的身上。
一部都市喜剧，讲述了在“能人”冯天贵的帮助下，一群农民工的媳妇在城里艰苦创业，几经周折，最终让城里人另眼相看的奋斗历程。一个偶然的机会，冯天贵结识了农民工谭有德的老婆沈秀枝，这让他与妻子之间本来就不和谐的婚姻产生了更大的缝隙。但是，经过一系列曲折之后，两人之间的误会终归化解。并且在冯天贵的穿针引线下，农民工的媳妇们用她们的勤劳和真诚，渐渐成了城市社区服务的一道亮丽风景线。
小公爷还有军务在身。
女孩Nayika是清迈一所著名大学的泰语系老师。她为人很保守，从来都不打扮自己，也没过有男朋友。有一天，她想要改变自己的形象，在弟媳的帮助下，Nayika焕然一新，她开始注重自己的打扮，终于她变成了一个很美丽的老师，就连同班的男老师也开始喜欢上了她。而她自己也幻想着，有一天会有个像小说里男主角一样的人来爱着他，保护他。 Nidanuch把自己舅舅（Na Kin）的故事写成的小说出版了。现实中的Na Kin住在清迈，是橘子园的主人。他曾经是一个性情很好的人，但是一场事故使他失去了自己的妻子和两个孩子，从此他变成了一个沉默寡言的男人。 Nayika在看Nidanuch所写小说的时候，不知不觉的就喜欢上了小说的男主角，后来知道了这竟是一个真实的故事，从而开始迷上了他。Nidanuch想当红娘让他们两个相见。但之后事情却与Nayika的想象完全不一样，Nakin已经封闭了自己的心，活在自己的世界里，完全没有理会过她。他们的爱情会有怎样的结果呢？
"I think the battle with these" killer bees "will not end so simply, will it? So did more bitter fighting take place later on at position 149?"
小娃儿正学说话的时候，回来这几天，整日被亲戚们围着，满耳都是乡音，因此也跟着满嘴乡音了。
板栗、葫芦和黄瓜大了，没有参与，只黄豆领着弟弟们嬉闹。
“女王”凯特·布兰切特演而优则导，不但导演电影，还涉足电视剧，首部参与执导的新剧定名为《Stateless》，根据2004年澳大利亚移民局的一则真实丑闻改编。 当时，一名幼年起就生活在澳洲的德裔妇女，被当成精神不健全的非法移民无故关押一年，该丑闻一经爆光，引发澳洲妇女组织的震怒和抗议，以至于澳洲国会不得不介入此案进行调查。 这部名为《Stateless》的剧集将由Matchbox Pictures公司制作出品，澳大利亚联邦资助机构宣布将为该剧提供发展资金。目前还未确定布兰切特是否参与主演。
If (state.getValue (). Equals ("state1")) {
这时，吕馨已经拿回手机，对着上面说道：听到没有，那个就是我男朋友，高大威猛，英俊潇洒。
青年放下手里的书，认真的看了陈启一眼，发觉陈启不像在骗人，便掏出一个小本子。
If the time goes back, will you still remember the promise you made to her when registering the marriage:
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.
In general, The proportion of the wounded on the attacking side is relatively large, And the losing side, As its wounded were unable to evacuate in time, Or eventually became a prisoner, or died due to lack of effective medical treatment, so the retreating party died in its losses. The proportion of captured personnel was generally large, especially the encircled troops. For example, the 280,000 German troops encircled in Stalingrad were either dead or captured except for more than 30,000 wounded who were airlifted out of the encirclement. Japan's encounter in the Pacific battlefield is similar to this. One island after another has become the death trap of the Japanese army that has lost its power to control the sea, and death has become the destination of the vast majority of the Japanese army guarding the islands.
Focal length, also known as MF. It refers to manual focusing. When taking photos, you need to click on the screen to determine the focus.
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EXAMPLE 5
