So, I have a strange career. I know it because people come up to me, like colleagues, and say, "Chris, you have a strange career."
我的职业比较奇特 这么说是因为有人跑过来,比如我的同事 他说:“克里斯,你的职业很奇特啊”
(Laughter)
(笑声)
And I can see their point, because I started my career as a theoretical nuclear physicist. And I was thinking about quarks and gluons and heavy ion collisions, and I was only 14 years old -- No, no, I wasn't 14 years old. But after that, I actually had my own lab in the Computational Neuroscience department, and I wasn't doing any neuroscience. Later, I would work on evolutionary genetics, and I would work on systems biology.
我知道 这是因为我是从 理论核物理学家起家 成天想的都是夸克、胶子 还有重离子碰撞 那时只有14岁 不,不,我不是14岁 不过自那以后 我有了我自己的实验室 是在计算神经科学系 不过我没搞什么神经科学 后来我开始研究进化基因学 然后是组织生物学
But I'm going to tell you about something else today. I'm going to tell you about how I learned something about life. And I was actually a rocket scientist. I wasn't really a rocket scientist, but I was working at the Jet Propulsion Laboratory in sunny California, where it's warm; whereas now I am in the mid-West, and it's cold. But it was an exciting experience. One day, a NASA manager comes into my office, sits down and says, "Can you please tell us, how do we look for life outside Earth?" And that came as a surprise to me, because I was actually hired to work on quantum computation. Yet, I had a very good answer. I said, "I have no idea."
不过以上都不是今天要讲的 我要讲的是 我是如何研究生命的 我是个火箭科学家 我不是真的火箭科学家 不过我为喷气推进实验室(JPL) 喷气推进实验室(JPL)工作 它位于温暖的加利福尼亚 而我现在在中西部 天真冷 不过是有趣的经历 一天一名NASA主管来到我的办公室 坐下对我说 “你能不能告诉我们 怎么寻找外星生命?” 我当时很惊讶 因为我是被雇来 做量子计算的研究的 不过,我给了一个好答案 我说“我不知道”
(Laughter)
他说“生命指标
And he told me, "Biosignatures, we need to look for a biosignature." And I said, "What is that?" And he said, "It's any measurable phenomenon that allows us to indicate the presence of life." And I said, "Really? Because isn't that easy? I mean, we have life. Can't you apply a definition, for example, a Supreme Court-like definition of life?"
我们要找生命指标” 我说,“那是什么?” 他说“就是任何可被测量的现象 能帮助我们发现 生命的存在” 我说“当真?” 因为那不是太简单了? 我是说,我们有生命 但你能为生命给出一个 类似于最高法院的终极定义吗?
And then I thought about it a little bit, and I said, "Well, is it really that easy? Because, yes, if you see something like this, then all right, fine, I'm going to call it life -- no doubt about it. But here's something." And he goes, "Right, that's life too. I know that." Except, if you think that life is also defined by things that die, you're not in luck with this thing, because that's actually a very strange organism. It grows up into the adult stage like that and then goes through a Benjamin Button phase, and actually goes backwards and backwards until it's like a little embryo again, and then actually grows back up, and back down and back up -- sort of yo-yo -- and it never dies. So it's actually life, but it's actually not as we thought life would be. And then you see something like that. And he was like, "My God, what kind of a life form is that?" Anyone know? It's actually not life, it's a crystal.
我想了想说 “真就那么简单吗?” 因为你看到这个 毫无疑问,我会称之为生命- 没问题 但是这个 人们会说“没错,那也是生命,我知道” 但是,如果你觉得会死去的东西 是生命 那么这个怎么解释呢 因为这是个非常奇怪的有机体 进入成年期它呈这样 然后像本杰明·巴顿一样 越长越小 直到又变成一个胎儿 然后再长大,再长回去,再长大——像悠悠球一样—— 永生不死 这也是生命 但不象我们一般认为的 生命形态 你还能看到这样的东西 人们会说“天哪,这是什么生命形态啊?” 有人知道吗? 这不是生命,这是晶体
So once you start looking and looking at smaller and smaller things -- so this particular person wrote a whole article and said, "Hey, these are bacteria." Except, if you look a little bit closer, you see, in fact, that this thing is way too small to be anything like that. So he was convinced, but, in fact, most people aren't. And then, of course, NASA also had a big announcement, and President Clinton gave a press conference, about this amazing discovery of life in a Martian meteorite. Except that nowadays, it's heavily disputed. If you take the lesson of all these pictures, then you realize, well, actually, maybe it's not that easy. Maybe I do need a definition of life in order to make that kind of distinction.
所以当你观察的东西 越来越小- 这个人 他写了一篇文章说“这些是细菌” 如果你凑近了看 可以看到这个东西太小了不可能长成那样 他是被说服了 不过大部分人却没有 当然 NASA做了一个重大宣布 克林顿总统开了新闻发布会 宣布在火星陨石上 发现了生命 不过近来这个观点备受质疑 如果你研究这些图片 你会意识到,也许这并不那么容易 也许我需要 一个生命的定义 来做区别
So can life be defined? Well how would you go about it? Well of course, you'd go to Encyclopedia Britannica and open at L. No, of course you don't do that; you put it somewhere in Google. And then you might get something.
那生命能被定义吗? 你怎么说? 当然 你会翻开大英百科全书的L部 不,你不会这么做,你会在Google搜索 或许会得到些什么
(Laughter)
可能会得到——
And what you might get -- and anything that actually refers to things that we are used to, you throw away. And then you might come up with something like this. And it says something complicated with lots and lots of concepts. Who on Earth would write something as convoluted and complex and inane? Oh, it's actually a really, really, important set of concepts. So I'm highlighting just a few words and saying definitions like that rely on things that are not based on amino acids or leaves or anything that we are used to, but in fact on processes only. And if you take a look at that, this was actually in a book that I wrote that deals with artificial life. And that explains why that NASA manager was actually in my office to begin with. Because the idea was that, with concepts like that, maybe we can actually manufacture a form of life.
一切称我们习以为常的东西生命的 扔到一边去 然后你可能会得到这个 带着许多许多概念的 复杂表述 到底谁写出 这么晦涩复杂 疯狂的东西? 但这确实是一堆很重要的概念 我标出了几个词 这样的定义 不是基于氨基酸 或者叶子 或者我们知道的任何东西 而是只基于过程 如果你仔细看下 这是我写的一本关于人工生命的书 它解释了 那位NASA主管来到我办公室的原因 因为这样的想法,这样的概念 我们可能创造出 一个生命形式
And so if you go and ask yourself, "What on Earth is artificial life?", let me give you a whirlwind tour of how all this stuff came about. And it started out quite a while ago, when someone wrote one of the first successful computer viruses. And for those of you who aren't old enough, you have no idea how this infection was working -- namely, through these floppy disks. But the interesting thing about these computer virus infections was that, if you look at the rate at which the infection worked, they show this spiky behavior that you're used to from a flu virus. And it is in fact due to this arms race between hackers and operating system designers that things go back and forth. And the result is kind of a tree of life of these viruses, a phylogeny that looks very much like the type of life that we're used to, at least on the viral level.
如果你反问自己 “到底什么是人工生命” 让我带你快速了解一下 这是怎么弄出来的 很久以前 有人写出了 最早的计算机病毒 对年纪还比较轻的人来说 你可能不知道它是怎么感染的- 就是这个软盘 但感染电脑病毒有趣的是 如果你看看 感染的速率 它们表现出这种上下波动 是在流感病毒上常见的 事实上正是由于 黑客和操作系统设计者间的军备竞赛 表现出这样结果 这个结果是这些病毒的 生命树形图 一个看上去十分像我们熟悉的 生命的发展史,至少对病毒的层面来说
So is that life? Not as far as I'm concerned. Why? Because these things don't evolve by themselves. In fact, they have hackers writing them. But the idea was taken very quickly a little bit further, when a scientist working at the Santa Fe Institute decided, "Why don't we try to package these little viruses in artificial worlds inside of the computer and let them evolve?" And this was Steen Rasmussen. And he designed this system, but it really didn't work, because his viruses were constantly destroying each other. But there was another scientist who had been watching this, an ecologist. And he went home and says, "I know how to fix this." And he wrote the Tierra system, and, in my book, is in fact one of the first truly artificial living systems -- except for the fact that these programs didn't really grow in complexity.
那这是生命吗?至少我不这么认为 为什么?因为它们不能自己演化 事实上,是黑客写出了它们 但是这个想法立刻被推进一步 一个在新墨西哥州圣菲市的科学家决定 “干嘛不把这些病毒 放到电脑的虚拟世界里 让它们自己演化呢?” 这个科学家就是Steen Rasmussen 他设计了这个系统,但是不奏效 因为他的病毒不断互相摧毁 但是当时还有一个科学家在关注此事,一个生态学家 他回了家说,“我知道怎么解决” 他写了Tierra系统 在我的书里,是最早出现的 真正的虚拟生命系统之一—— 只是这些程序不会拥有复杂体
So having seen this work, worked a little bit on this, this is where I came in. And I decided to create a system that has all the properties that are necessary to see, in fact, the evolution of complexity, more and more complex problems constantly evolving. And of course, since I really don't know how to write code, I had help in this. I had two undergraduate students at California Institute of Technology that worked with me. That's Charles Ofria on the left, Titus Brown on the right. They are now, actually, respectable professors at Michigan State University, but I can assure you, back in the day, we were not a respectable team. And I'm really happy that no photo survives of the three of us anywhere close together.
看了这些研究,自己也多少涉猎一些 我开始了我的研究 我决定创造一个系统 其属性必须支持 复杂体的进化 越来越多的复杂问题不断进化 当然,因为我不知道怎么写代码,所以需要帮助 这是加州理工学院的 两个和我公事过的本科生 左边是Charles Offria,右边是Titus Brown 他们现在都是密歇根州立大学里 受人尊敬的教授 不过那时候 我们还不没有受尊敬的份儿 我很高兴那些我们三个人老粘在一起的照片 都没有保留下来
But what is this system like? Well I can't really go into the details, but what you see here is some of the entrails. But what I wanted to focus on is this type of population structure. There's about 10,000 programs sitting here. And all different strains are colored in different colors. And as you see here, there are groups that are growing on top of each other, because they are spreading. Any time there is a program that's better at surviving in this world, due to whatever mutation it has acquired, it is going to spread over the others and drive the others to extinction.
这个系统什么样子 我没法深入讲解 但你这儿你可以看到一些细部 我着重要讲的 是群体构造特征 这儿有大概一万个程序 每一个变种都用不同的颜色标记 你可以看到群体会互相覆盖 因为它们在扩散 任何时刻一个程序 因为获得某个突变 从而在这个世界里更好的生存 那它讲不断扩散把其他程度逼入绝境
So I'm going to show you a movie where you're going to see that kind of dynamic. And these kinds of experiments are started with programs that we wrote ourselves. We write our own stuff, replicate it, and are very proud of ourselves. And we put them in, and what you see immediately is that there are waves and waves of innovation. By the way, this is highly accelerated, so it's like a 1000 generations a second. But immediately, the system goes like, "What kind of dumb piece of code was this? This can be improved upon in so many ways, so quickly." So you see waves of new types taking over the other types. And this type of activity goes on for quite a while, until the main easy things have been acquired by these programs. And then, you see sort of like a stasis coming on where the system essentially waits for a new type of innovation, like this one, which is going to spread over all the other innovations that were before and is erasing the genes that it had before, until a new type of higher level of complexity has been achieved. And this process goes on and on and on.
下面播放的这个短片你就可以看到这种变化 这个实验是从 我们自己写的程序开始的 我们写了程序,复制了它们 我们为此很骄傲 然后放到系统里,你马上可以看见的 不断变化的波形 顺便提一下,这个是加速播放 大概是一秒是一千代 但是很快系统有了反应 “这是什么愚蠢的代码? 这可以以很多种方式 很快地改善” 你可以看到新的类型 取代其他的 这种类型的活动持续一段时间 直到这些程序都获得了主要的简单的东西 然后有一段停滞期 系统在等待 一种新的变化,像这个 它将扩散 覆盖之前所有的变化 并消除之前的所有基因 直到获得一种新的高层次的复杂体 这个过程会一致持续
So what we see here is a system that lives in very much the way we're used to how life goes. But what the NASA people had asked me really was, "Do these guys have a biosignature? Can we measure this type of life? Because if we can, maybe we have a chance of actually discovering life somewhere else without being biased by things like amino acids." So I said, "Well, perhaps we should construct a biosignature based on life as a universal process. In fact, it should perhaps make use of the concepts that I developed just in order to sort of capture what a simple living system might be."
所以我们看到的就是 一个如同我们所知的 生命形式一样生存的系统 但是是NASA的官员问我 “那这些人 有生命指标吗? 我们能测量到这样的生命吗? 因为如果我们能的话 也许有机会发现其他形式的生命 而不需要 依赖氨基酸” 我说,“也许我们应该构造 一个基于 作为通用过程的生命的生命指标 事实上,这得利用 我开发的概念 以了解 简单的生命体是什么样的
And the thing I came up with -- I have to first give you an introduction about the idea, and maybe that would be a meaning detector, rather than a life detector. And the way we would do that -- I would like to find out how I can distinguish text that was written by a million monkeys, as opposed to text that is in our books. And I would like to do it in such a way that I don't actually have to be able to read the language, because I'm sure I won't be able to. As long as I know that there's some sort of alphabet. So here would be a frequency plot of how often you find each of the 26 letters of the alphabet in a text written by random monkeys. And obviously, each of these letters comes off about roughly equally frequent.
我得出的—— 首先我得介绍一下这个想法 也许是个存在探测器 而不是生命探测器 操纵的方式是—— 我怎么区分一段文字 是一百万个猴子写的 还是我们的书 我会这么做 我并不去阅读它 因为我知道我无法做到 只要我知道存在某种字母表 这是一个猴子写的 一段文字的 26个字母频度的 示意图 显然这些字母 出现的频率基本相等
But if you now look at the same distribution in English texts, it looks like that. And I'm telling you, this is very robust across English texts. And if I look at French texts, it looks a little bit different, or Italian or German. They all have their own type of frequency distribution, but it's robust. It doesn't matter whether it writes about politics or about science. It doesn't matter whether it's a poem or whether it's a mathematical text. It's a robust signature, and it's very stable. As long as our books are written in English -- because people are rewriting them and recopying them -- it's going to be there.
但是如果你看看一段英文段落的字母分布的话 是这样的 而且英语文字的这种现象非常明显 如果是法语的,会有些不一样 或者是意大利语,德语 它们都有自己的频度分布 但也都非常明显 不论内容是关于政治还是科学 不管是一首诗 还是数学内容 都有明显的标识 并且很稳定 只要我们的书是英语写的- 因为人们不断地写和再印- 这个标识就存在
So that inspired me to think about, well, what if I try to use this idea in order, not to detect random texts from texts with meaning, but rather detect the fact that there is meaning in the biomolecules that make up life. But first I have to ask: what are these building blocks, like the alphabet, elements that I showed you? Well it turns out, we have many different alternatives for such a set of building blocks. We could use amino acids, we could use nucleic acids, carboxylic acids, fatty acids. In fact, chemistry's extremely rich, and our body uses a lot of them.
这促使我想到 如果我用这个法子 不是去探测随意的 是否有意义的文字 而是探测可标志生命的 生物分子的存在 首先我问道: 组成的基本单位是什么,就像我展示给你的字母表,要素一样? 我们有很多不同选择 作为这种构造基础 可以是氨基酸 核酸,羧酸或者不饱和脂肪酸 事实上,化学物质十分丰富,我们的身体有很多 为了试验这个想法
So that we actually, to test this idea, first took a look at amino acids and some other carboxylic acids. And here's the result. Here is, in fact, what you get if you, for example, look at the distribution of amino acids on a comet or in interstellar space or, in fact, in a laboratory, where you made very sure that in your primordial soup, there is no living stuff in there. What you find is mostly glycine and then alanine and there's some trace elements of the other ones. That is also very robust -- what you find in systems like Earth where there are amino acids, but there is no life.
我们首先研究了氨基酸和其他一些羧酸 这是结果 这个结果 如果你观察一个彗星或者星际空间的 或者一个实验室的 氨基酸分布 实验室的话得保证原始汤里 没有任何生命 你能找到的大部分是甘氨酸和丙氨酸 还有其他一些 这结果也非常明显—— 你可以在地球系统中 找到氨基酸
But suppose you take some dirt and dig through it
但是没有生命
and then put it into these spectrometers, because there's bacteria all over the place; or you take water anywhere on Earth, because it's teaming with life, and you make the same analysis; the spectrum looks completely different. Of course, there is still glycine and alanine, but in fact, there are these heavy elements, these heavy amino acids, that are being produced because they are valuable to the organism. And some other ones that are not used in the set of 20, they will not appear at all in any type of concentration. So this also turns out to be extremely robust. It doesn't matter what kind of sediment you're using to grind up, whether it's bacteria or any other plants or animals. Anywhere there's life, you're going to have this distribution, as opposed to that distribution. And it is detectable not just in amino acids.
但是如果 采集一些土壤 放到光谱仪里 因为细菌的存在 或者采集地球上任何一处的水 因为水里富含生命 然后你做同样的分析 光谱结果完全不一样 当然仍然还有甘氨酸和丙氨酸 但是更重要的因素是大量的氨基酸 它们对有机体非常重要 因而大量产生 而其他一些 没有在20个集合被使用 因为不在任何一个聚集里 出现 这个结果特征也非常明显 不管你是研磨是哪种泥沙 不管是细菌,植物或者动物 到处都有生命存在 就会得出这样的分布 而不是那样的 不光是氨基酸可被探测
Now you could ask: Well, what about these Avidians? The Avidians being the denizens of this computer world where they are perfectly happy replicating and growing in complexity. So this is the distribution that you get if, in fact, there is no life. They have about 28 of these instructions. And if you have a system where they're being replaced one by the other, it's like the monkeys writing on a typewriter. Each of these instructions appears with roughly the equal frequency. But if you now take a set of replicating guys like in the video that you saw, it looks like this. So there are some instructions that are extremely valuable to these organisms, and their frequency is going to be high. And there's actually some instructions that you only use once, if ever. So they are either poisonous or really should be used at less of a level than random. In this case, the frequency is lower. And so now we can see, is that really a robust signature? I can tell you indeed it is, because this type of spectrum, just like what you've seen in books, and just like what you've seen in amino acids, it doesn't really matter how you change the environment, it's very robust, it's going to reflect the environment.
现在你会问: 那么Avidian呢?(一台叫Avida计算机里的数字生物物种) Avidian是计算机世界的居民 它们在那里快乐得繁殖成长 这是它们的分布 不是生命 它们有28个这样的结构 如果有一个供他们相互取代的系统 就像是猴子用打字机写作 每一个结构 出现的频率基本一样 但是如果是像刚刚视频里 那些复制的家伙 则是这样 这里有些结构 是机体里非常脆弱的部分 他们的频度很高 而有些 你只能用一次,如果要用的话 它们不是有毒 就是应该以低于随机的水平使用 这种情况下,频度较低 那我们看到,这是个明显的生命指标吗? 是的 因为这种分布,就如刚刚的书 和氨基酸一样 不管你怎么改变环境,特征十分明显 会反映环境
So I'm going to show you now a little experiment that we did. And I have to explain to you, the top of this graph shows you that frequency distribution that I talked about. Here, that's the lifeless environment where each instruction occurs at an equal frequency. And below there, I show, in fact, the mutation rate in the environment. And I'm starting this at a mutation rate that is so high that even if you would drop a replicating program that would otherwise happily grow up to fill the entire world, if you drop it in, it gets mutated to death immediately. So there is no life possible at that type of mutation rate. But then I'm going to slowly turn down the heat, so to speak, and then there's this viability threshold where now it would be possible for a replicator to actually live. And indeed, we're going to be dropping these guys into that soup all the time.
现在给你们看一个我们做的实验 得解释一下 图表的上部 是我提到的频度分布 这是无生命的环境 每一个结构的 频度相等 下面的 是环境里的突变率 我将开始的突变率设得很高 高到就算你放入 一个复制程序 能快乐的成长 并布满整个空间 如果你放进去,立刻突变至死亡 所以那样的突变率 任何生命无法存活 但是我降低了温度 到这个可行阈值 这样有一个复制体 能够存活 我们把这些家伙放进 (原始)汤里
So let's see what that looks like. So first, nothing, nothing, nothing. Too hot, too hot. Now the viability threshold is reached, and the frequency distribution has dramatically changed and, in fact, stabilizes. And now what I did there is, I was being nasty, I just turned up the heat again and again. And of course, it reaches the viability threshold. And I'm just showing this to you again because it's so nice. You hit the viability threshold. The distribution changes to "alive!" And then, once you hit the threshold where the mutation rate is so high that you cannot self-reproduce, you cannot copy the information forward to your offspring without making so many mistakes that your ability to replicate vanishes. And then, that signature is lost.
是什么样子呢 开始的时候什么都没有 太热了太热了 达到可行阈值之后 频度分布 开始剧烈变化然后稳定下来 然后我就 很邪恶地调高了温度 当然到达了可行阈值 我再给你们看一遍因为这个太棒了 降到可行阈值 分布就变成“有生命的” 升高到可行阈值 突变率太高了 就无法自我繁殖 不能将信息 没有错误地 复制给后代 复制的能力就消失了 然后生命指标消失了
What do we learn from that? Well, I think we learn a number of things from that. One of them is, if we are able to think about life in abstract terms -- and we're not talking about things like plants, and we're not talking about amino acids, and we're not talking about bacteria, but we think in terms of processes -- then we could start to think about life not as something that is so special to Earth, but that, in fact, could exist anywhere. Because it really only has to do with these concepts of information, of storing information within physical substrates -- anything: bits, nucleic acids, anything that's an alphabet -- and make sure that there's some process so that this information can be stored for much longer than you would expect -- the time scales for the deterioration of information. And if you can do that, then you have life.
就此我们学到什么? 我觉得我们学到几点 第一是 如果我们可以 从抽象意义上认知生命- 我们不是在讨论植物 也不是氨基酸 或者细菌 而是一种过程—— 那么我们可以认为生命 不是地球特有的 可能存在任何一个地方 因为它只是 与信息的概念有关 与储存信息有关 通过物质性基板—— 任何东西:数位,核酸 任何类似字母表的东西—— 并确保存在某种程序 从而信息可以被长久保存 比你预期的信息损坏的 时间尺度还要长很多 如果是这样 那么就是生命
So the first thing that we learn is that it is possible to define life in terms of processes alone, without referring at all to the type of things that we hold dear, as far as the type of life on Earth is. And that, in a sense, removes us again, like all of our scientific discoveries, or many of them -- it's this continuous dethroning of man -- of how we think we're special because we're alive. Well, we can make life; we can make life in the computer. Granted, it's limited, but we have learned what it takes in order to actually construct it. And once we have that, then it is not such a difficult task anymore to say, if we understand the fundamental processes that do not refer to any particular substrate, then we can go out and try other worlds, figure out what kind of chemical alphabets might there be, figure enough about the normal chemistry, the geochemistry of the planet, so that we know what this distribution would look like in the absence of life, and then look for large deviations from this -- this thing sticking out, which says, "This chemical really shouldn't be there." Now we don't know that there's life then, but we could say, "Well at least I'm going to have to take a look very precisely at this chemical and see where it comes from." And that might be our chance of actually discovering life when we cannot visibly see it.
所以头一件我们学到的 就是生命可以被定义为 一种过程本身 而不需要借助 其他我们珍视的东西 比如地球上的生命形式 这个结论再一次 就像其他所有科学发现,或者很多科学发现- 告诉人们- 我们的存在并不是什么独特的事 我们可以创造生命,可以在电脑里创造生命 当然这个有限 但是我们据此可以知道 构建生命的要素 一旦我们有这些要素 那么创造生命不是什么难事 如果我们掌握了最基本的 不借助于任何特殊基板的过程的话 我们就能走出去 探寻其他世界 了解那里有什么样的化学字母表 了解一般的化学物质 和那个星球的地理化学 那样我们就知道没有生命的 分布是什么样子 从而以此寻找更大的偏差- 这个突起意味着 “这个化学物质不应该在这儿” 现在我们还不知道那里有没有生命 但是我们可以说 “至少我会精确地研究一下这个化学物质 看看哪里来的” 这也许就是 当我们无法看到生命 但真正发现生命的机会
And so that's really the only take-home message that I have for you. Life can be less mysterious than we make it out to be when we try to think about how it would be on other planets. And if we remove the mystery of life, then I think it is a little bit easier for us to think about how we live, and how perhaps we're not as special as we always think we are. And I'm going to leave you with that.
这是我唯一的可以让你 带回家的信息 生命并不一定像 我们以为的那样神秘 如果我们知道其他星球上也存在的话 如果我们去掉生命的神秘感 我像对于我们 思考如何生活 和我们并不特殊来说会更容易 这就是我要讲的
And thank you very much.
非常感谢
(Applause)
(掌声)