Monday, June 30, 2008

Reprint: PhD Candidates Can Take Job Search to a Level Beyond Academia

PhD Candidates Can Take Job Search to a Level Beyond Academia

By Amy Joyce
Washington Post Staff Writer
Monday, January 29, 2001 ; Page E07

Working on your PhD? Getting sick of people asking what you're going to do with it?

Okay, seriously now . . . what are you going to do with it?

The experts say only about 50 percent of doctoral students get a decent tenure-track teaching job after they graduate. And many of those students are going to win that job in a small school somewhere in the middle of nowhere. Are you sure that's what you want to do? If not, why not think about the many possibilities -- hold onto your tassels here, folks -- outside the world of academia?

Tech companies, foundations, nonprofits, lobbying firms and others are finding that they can benefit from PhD students. And the students are finding that they really dig the variety of occupations in what they commonly refer to as "the real world."

Take, for instance, Susan Basalla and Maggie Debelius. Both have their doctorates in English from Princeton. Basalla is the online editor at Motley Fool Inc. of Alexandria and Debelius is the editor in chief at LifeMinders Inc. of Herndon. Together they wrote the book, "So What Are You Going to Do With That?: A Guide to Career-Changing for MAs and PhDs."

They have some advice.

A Different Context

In the midst of earning her degree -- she is a Victorianist -- Debelius had a few epiphanies. She knew she loved to teach, which would make her a great candidate for professorship. But she also knew what the job market for would-be professors was like, and that she probably wouldn't end up living where she wanted. Yes, she loved teaching, but she "wasn't ready to move to some place that seemed atrocious to me to do it."

Basalla, on the other hand, wasn't convinced she wanted to follow the academic track at all. "I wasn't entirely convinced I wanted to be a professor," she said. "[It] didn't warm my heart" the way it would for someone with a real vocation for teaching. She and Debelius spent many nights talking about what else was out there.

Basalla got a list of alumni and their jobs from the chairman of her department. She started making cold calls, asking people how they got into their line of work, what they liked and disliked about it. "I literally didn't know what was out there," she said.

As Basalla and Debelius found their way around a world outside academia, they started writing their book and interviewing others. Among some of the PhDs with outside-world jobs: A midwife who had written her thesis on images of mothering in medieval French literature, one of the hosts of the "Car Talk" radio show, a writer for Hallmark Cards and the former chief executive of Maidenform.

So how do you figure out what you want to do if you've been in that academic bubble for so long?

Explore and get some experience. Remember that although many of the skills you have from grad school can transfer over to the workplace, it's always good to have real work experience to pique a potential employer's interest -- and trust.

"I really find that I think the best thing a grad student can do to explore careers and get hired is test the waters," Debelius said. "Do temp work, volunteer. I think when [potential employers] see a résumé with only grad work, they are understandably skeptical. But if they see PhD plus work experience, that can be a feather in someone's cap."

Basalla did temporary work for three summers. Then, the day after she defended her dissertation, she called the temp agency and said that she needed a real job. "Put me somewhere where I have a future," she told them. "They were glad to help me and I went to work right away at the Robert Wood Johnson Foundation as a researcher. That basically started my career."

Basalla is a big advocate of taking time off. She said that some students will turn in a chapter of their thesis and not hear from their adviser until a year later. Use that time to do something part time, she suggests, or spend a summer doing something completely different from academic work.

"See yourself in a different context," she said. "We interviewed a PhD in chemistry who went to work for a law firm without a great passion for law, but she discovered she loved to write. . . . You just have to test-drive some experience."

Research a Career

The skills students obtain in graduate school can very easily transfer over into "real-world" work.

"They should realize that they've acquired knowledge in their PhD studies and skills that can be valuable outside," said David Drew, chairman of the school of education at Claremont Graduate University in California. For example, he said, they have developed analytical reasoning skills, they question assumptions and they constantly work on communication skills.

And they obviously have great research skills, which Drew suggests they use in the job search. "All these students have learned how to do research and . . . how to do detailed study," he said. "They need to do the same for finding a job."

Wendy Martin, a professor of American literature at Claremont who often speaks on this topic, said she always tells her students to really pay attention to what they enjoy. "What would you like to do even if you weren't getting paid to do it? Which aspects do you like the best? Where else can I use this skill?"

Those students who like to teach and explain things, as professors are wont to do, can look to corporations and organizations that need that sort of skill. And many do.

"Those are highly prized skills," Martin said. "People in the humanities can think quite clearly and their communications skills are outstanding. It's not a gift everyone has, and many don't realize how unusual their ability to articulate really is."

She added that if she knew then what she knows now . . . well, let's just say she may not have been a professor for the last two decades. "I never even thought of anything beyond teaching and writing when I was a new PhD," she said. "The real world was like a huge frightening place that I had no knowledge of. . . . It wasn't even in anyone's mind to explain there are other options."

Now she shares her learned wisdom with her own students. "Take a chance" is her most popular mantra. "What kept me back as much as anything else is not being sufficiently adventurous," she said. She suggests students just go talk to the personnel office at a company they are interested in and see what opportunities there are.

Why a PhD?

There's even a foundation set up, at least partially, to help students find work outside of academia.

The Woodrow Wilson National Fellowship Foundation in Princeton, N.J., helps students, especially those in liberal arts, connect with the outside world so they can discover that having a PhD with a concentration in 18th-century female poets can translate into many things other than professorship.

Robert Weisbuch, president of the foundation and former English Department chairman at the University of Michigan, said he was "sick of seeing my great students get lousy jobs."

For the last several decades, "we've not been creative enough about thinking about what these grads can do," he said. "I now say to grad students when I talk to them that four months from now you could end up with one offer of a part-time temporary instructor position at a mediocre college, or you could have an offer from AT&T, A.T. Kearney, the Wall Street Journal."

So how do students learn how to take the plunge into that other world? Talk to as many people as you can. Network. Check out the Wilson Web site (www.woodrow.org). "Only three or four universities in the country have figured out they need to put their career offices together at the graduate level. So even if a student says, 'I figured out that I want to look more broadly out there,' you can't expect faculty to understand that."

But, he adds, students should take advantage of the "incredible network" of people who have done something with the PhD beyond academia.

So why PhD it at all? Because you want to, and that can be enough.

"We asked almost everyone if you had to do it all over again, would you go to grad school," Debelius said. "I think all of them said yes. It's a wonderful thing to be able to spend five, seven years spending time with something you're passionate about. It sharpens your mind. You don't need a PhD to be an online editor, but it's who I am. I feel like I'm a better manager because I have so much teaching experience. I feel like a lot of that came from spending so much time in classroom."

Join Amy Joyce tomorrow for Career Track Live at washingtonpost.com. Share your stories, questions and your own advice from 11 to 12.

© 2001 The Washington Post

Sunday, June 29, 2008

She

Wednesday, June 25, 2008

两情若是久长时,又岂在朝朝暮暮?

Sunday, June 22, 2008

以色列数学家破解路线着色谜题 全球数学界震惊

最近,全球数学界兴奋无比――困扰科学界近40年的一道谜题,最近终于被以色列巴尔伊兰大学数学家艾夫拉汉・特雷特曼破解。他成功解决了所谓的路线着色问题。

  路线着色问题是图论中最著名的猜想之一。
这个猜想认为,可以绘制一张"万能地图",指导人们到达某一目的地,不管他们原来在什么位置。而这一似乎违反逻辑的命题可以运用于制图、计算机科学、电网络分析等诸多领域。

   路线着色问题是犹太裔美国数学家和计算机专家本杰明・韦斯和他在IBM工作的同事罗伊・艾德勒于1970年首先提出来的。他们认为,如果路线的数量有 限,人们应该能画出一张地图,标上不同的颜色,把人引导到某一目的地。路线着色问题可以通俗解释为,"一个人来到他从未造访过的小镇上,驾着车到处寻找他 朋友的家,即使连路名都没有。朋友说,别担心,他会指示他如何到达,先向左,再向右,接着向左……"

   38年来,许多杰出的数学家都致力于解决这一路线着色问题,而解决这一难题要涉及到图论、群论、矩阵论、概率论、代数学、拓扑学、数值分析等多个数学分 支。然而,数学奇才特雷特曼只花了一年时间就解决了这道难题。以色列著名数学家斯图尔特・马戈利斯对美联社说,"在数学界,我们都在谈论这一美好的结果, 多么美好啊,而且是那么出乎意料。用外行话来说,这是完全反直觉的,但它确实管用。"

   为了与同行交流,特雷特曼于去年底在网上的一个数学文献库里贴出他的解题方法。在对特雷特曼的方法深入研究后,数学界为之震惊了,并公认他已经掌握了破 解路线着色谜题的要领和诀窍。今年2月,他进一步完善了自己的解题方法。最近,世界上众多著名学术刊物编辑部得知此事后,纷纷向他约稿,但他最终决定把论 文发表在即将出版的《以色列数学杂志》上。

  今年63岁的特雷特曼出生在 俄罗斯叶卡捷琳堡,1972年在乌拉尔州立大学获得数学博士学位,之后在乌拉尔科技大学任教。但是犹太人身份使他在工作中受到歧视和排挤。尽管特雷特曼在 1992年移居以色列之前就是一位颇有造诣的数学家,但他刚到以色列时身无分文,为养家糊口他经常去教会领救济品,后来在好心人的介绍下,他成了一名值夜 班的保安员,但生活仍然十分艰苦。1995年,特雷特曼被聘为巴尔伊兰大学的教员。当年把他招进巴尔伊兰大学的马戈利斯回忆说,"我第一次见到他时,他穿 着守夜人的制服,不修边幅,衣服很脏。"

  特雷特曼在数学上的这一成果极为令人瞩目,英国《独立报》为此事专门发表了一篇题为"身无分文的移民成了数学超级明星"的文章,给予了高度的评价。

  以色列人也为特雷特曼取得的成就感到无比的骄傲。特拉维夫电视台中断了正常的节目播放,以第一时间发布了这一重大消息,连中东其他国家的主流媒体也作了大篇幅的。

  得知特雷特曼解决这一难题的消息后,多年从事路线着色问题研究的加拿大数学家乔尔・弗里德曼说,"路线着色问题的解决令数学共同体非常兴奋。"读过特雷特曼论文的中国数学家和语言学家周海中教授认为,特雷特曼的数学知识非常渊博,解题方法十分巧妙,这一谜题得到破解,无疑是数学史上的一个华彩乐章。

电视剧 change

所以请大家只批评我一个人可以吗?因为美山小姐和大家一样都是拿薪水的普通工作人员,而我是大家选出来的,以后也请只批评我一个人就可以了,因为责任在于我。
---
看日剧可以得到很多的启发,无论从工作上还是生活上。
今天的查经班上讲的是罗马书第五章。的确是如此,从困难到忍耐,从忍耐到老练,从老练到盼望,而这盼望又不至于羞耻。
每一个人都在这短短的百年里经历着。有些人可能达到老练,但不是所有的人都可以有盼望。

而很多时候我们做错的时候,我们自己是不知道的。就像耶稣基督的祷告中所说的:父啊,求人不要惩罚这些人,因为他们所做的他们不知道。

人啊,,,经历了这些后,慢慢的心也会变得宽容吧。毕竟每个人都不一样,就算在亲昵的夫妻,父子,母女,也有本质的观点差异,而不顾忌对方与自己的不同的话,那就不能够相处下去了。所以,吵架,争执等矛盾多源于此。

大熊

Saturday, June 21, 2008

上海满分高考作文: 他们


在城市尽头,没有繁华的街市,闪亮的霓虹;在城市的尽头,只有破旧的棚户区,有饱经生活风霜的生命;在城市的尽头,有他们这样一群人。

让我怎样称呼他们?外来务工人员子女?农民子弟?亦或是农民工二代?不,我不想用这些冰冷的名字称呼他们,我多想叫着他们带着泥土气的乳名,拉着他们的小手,走近他们的生活……

他 们从小生长在故乡的青山绿水中,纯洁的灵魂在田野里抽穗拔节。在山野的风中,他们奔跑着,憧憬着。风从田野中吹过,吹进了城市,为了生计,为了未来,他们 跟从父母来到了城市,在城市的尽头扎下了根。于是习惯了青山绿水的双眸第一次触碰到了高楼大厦、车水马龙。他们不知道怎样穿过六车道的马路,小小的手指怎 么也数不清写字楼的层数。繁华的现代文明不曾给他们带来任何快乐,这一次,却在心上烙下了深深的痕迹。

他们背起书包,小心翼翼地融入城市的生活。可是却在"城市人"异样的眼光中,第一次明白了户口与暂住证的区别。他们都是父母心头的宝啊!却过早地承担了不属于这个年龄的负担。

放学回家,他们做好简单的晚饭,父母还在工地或菜场上劳作;午夜醒来,泪眼中城里的星空没有家乡的明亮;悄悄许愿,希望明天他们的打工子弟小学不会因交不出电费而被查封……

然而,在他们日益长高的身体上,我看到了他们的成长。记得一位记者问一个打工子弟学校的孩子,学成后是否会回到家乡时,小姑娘毫不犹豫地说:当然,一定回去!那一刻,我差点落下泪来,为他们的成长。

记得那年春晚他们稚气的宣言:"我们的学校很小,但我们的成绩不差""我们不和城里的孩子比爸爸""北京的2008,也是我们的2008!"他们逐渐成熟,告别昨天的羞怯,开始迎接新的一天。

虽然,他们还在为不多的学费而苦恼;虽然,学校还是交不上水电费;虽然,还有好多体制还不够完善……虽然有好多个"虽然",但是,只有一个"但是"就足够了,已经有好多视线转向他们,他们正在茁壮地成长。

太阳从地平线上升起,照亮了城市的尽头,照亮了他们的生活。

他们,终将会成为我们。

有感

今天早上起床打开ppstream看了一下法证先锋2。那个Dr.Koo现在是法医。不过过去的时候也做过小混混,认真做人,做了法医。虽然我也有自己的不同人生。不过倒是想起我小时候成绩也非常差,每次开学摸底考试都是不及格。要是分数能到80分,那就开心的不得了了。 变化真的很大,重来没有想到人的改变这么大。不过,童年虽然读书一般,但也是尽了当时的力的,但童年真的是好开心,虽然没有学钢琴等,却常常去海边江边玩。

scott说上海 so incredible.

Friday, June 20, 2008

Without You

No, I can't forget this evening
我无法忘记今晚
Oh, your face as you were leaving
当你离去时的脸庞
But I guess that's just the way the story goes
但我想那就是故事的结局
You always smile
你一直保持著笑容
But in your eyes your sorrow show
但眼里却流露著哀伤
Yes, it shows
没错,那是哀伤

No, I can't forget tomorrow
我无法忘记明日
When I think of all my sorrow
当我想到自己的哀愁
When I had you there, but then I let you go
我拥有了你,却又让你溜走
And now it's only fair that I should let you know
现在我只想让你知道
What you should know
一些你该知道的事

I can't live, if living is without you
我活不下去,如果生命中失去了你
I can't live, I can't give anymore
我活不下去,我再也无法付出
I can't live, if living is without you
我活不下去,如果生命中没有你
I can't live, I can't give anymore
我活不下去,我再也无法付出

耐心等候

又是工作到凌晨3点多。
在这夜深人静的思考,也是经历了一次失恋后(曾经以为自己全部的付出,对方也会不弃不离,但毕竟感情的事情都是主观的,知道对方的观点不同,我也就可以设身处地的为对方考虑了),思绪比较多。
听着 游湖民的 下沙。 越是爱得深,越是伤得深。。。。很好的歌词。

30年来,我经历了3次恋爱。虽然一再的出局,但让我慢慢的明白,那命中注定的人是要我们真心的认真的去等待的。想起圣经上的神的话语来:
Pro 20:22 你不要说、我要以恶报恶.要等候耶和华、他必拯救你。
Isa 40:31 但那等候耶和华的、必从新得力、他们必如鹰展翅上腾、他们奔跑却不困倦、行走却不疲乏。
也想通过祷告来告诉我的主,我必耐心等候你的恩赐。

该睡觉了。明天还有接下来的科研。
加油,大熊

Thursday, June 19, 2008

人生就像一盒巧克力---for me

"Life is like a box of chocolates. You never know what you're gonna get." ---from "Forrest Gump"

人生就像一盒巧克力,你永远也不知道下一个吃到的是什么味道。

Optimization Methode

From Wiki:

In mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function by systematically choosing the values of real or integer variables from within an allowed set.

An optimization problem can be represented in the following way

Given: a function f : A \to R from some set A to the real numbers
Sought: an element x0 in A such that f(x0) ? f(x) for all x in A ("minimization") or such that f(x0) ? f(x) for all x in A ("maximization").

Such a formulation is called an optimization problem or a mathematical programming problem (a term not directly related to computer programming, but still in use for example in linear programming - see History below). Many real-world and theoretical problems may be modeled in this general framework. Problems formulated using this technique in the fields of physics and computer vision may refer to the technique as energy minimization, speaking of the value of the function f as representing the energy of the system being modeled.

Typically, A is some subset of the Euclidean space Rn, often specified by a set of constraints, equalities or inequalities that the members of A have to satisfy. The domain A of f is called the search space, while the elements of A are called candidate solutions or feasible solutions.

The function f is called an objective function, or cost function. A feasible solution that minimizes (or maximizes, if that is the goal) the objective function is called an optimal solution.

Generally, when the feasible region or the objective function of the problem does not present convexity, there may be several local minima and maxima, where a local minimum x* is defined as a point for which there exists some ? > 0 so that for all x such that

\|\mathbf{x}-\mathbf{x}^*\|\leq\delta;\,

the expression

f(\mathbf{x}^*)\leq f(\mathbf{x})

holds; that is to say, on some region around x* all of the function values are greater than or equal to the value at that point. Local maxima are defined similarly.

A large number of algorithms proposed for solving non-convex problems - including the majority of commercially available solvers - are not capable of making a distinction between local optimal solutions and rigorous optimal solutions, and will treat the former as actual solutions to the original problem. The branch of applied mathematics and numerical analysis that is concerned with the development of deterministic algorithms that are capable of guaranteeing convergence in finite time to the actual optimal solution of a non-convex problem is called global optimization.

History

The first optimization technique, which is known as steepest descent, goes back to Gauss. Historically, the first term to be introduced was linear programming, which was invented by George Dantzig in the 1940s. The term programming in this context does not refer to computer programming (although computers are nowadays used extensively to solve mathematical problems). Instead, the term comes from the use of program by the United States military to refer to proposed training and logistics schedules, which were the problems that Dantzig was studying at the time. (Additionally, later on, the use of the term "programming" was apparently important for receiving government funding, as it was associated with high-technology research areas that were considered important.)

Other important mathematicians in the optimization field include:

* John von Neumann
* Leonid Vitalyevich Kantorovich
* Naum Z. Shor
* Leonid Khachian
* Boris Polyak
* Yurii Nesterov
* Arkadii Nemirovskii
* Michael J. Todd
* Richard Bellman
* Hoang Tuy

Notation

Optimization problems are often expressed with special notation. Here are some examples:

\min_{x\in\mathbb R}\; x^2 + 1.\,

This asks for the minimum value for the objective function x2 + 1, where x ranges over the real numbers R. The minimum value in this case is 1, occurring at x = 0.

\max_{x\in\mathbb R}\; 2x.

This asks for the maximum value for the objective function 2x, where x ranges over the reals. In this case, there is no such maximum as the objective function is unbounded, so the answer is "infinity" or "undefined".

\operatorname{argmin}_{x\in(-\infty,-1]}\; x^2 + 1.\,

This asks for the value (or values) of x in the interval (??, ?1] that minimizes (or minimize) the objective function x2 + 1 (the actual minimum value of that function does not matter). In this case, the answer is x = ?1.

\operatorname{argmax}_{x\in[-5,5],\;y\in\mathbb R}\; x\cdot\cos(y).\,

This asks for the (x, y) pair (or pairs) that maximizes (or maximize) the value of the objective function x·cos(y), with the added constraint that x lies in the interval [?5, 5] (again, the actual maximum value of the expression does not matter). In this case, the solutions are the pairs of the form (5, 2?k) and (?5, (2k + 1)?), where k ranges over all integers.

[edit] Major subfields

* Linear programming studies the case in which the objective function f is linear and the set A is specified using only linear equalities and inequalities. Such a set is called a polyhedron or a polytope if it is bounded.
* Integer programming studies linear programs in which some or all variables are constrained to take on integer values.
* Quadratic programming allows the objective function to have quadratic terms, while the set A must be specified with linear equalities and inequalities.
* Nonlinear programming studies the general case in which the objective function or the constraints or both contain nonlinear parts.
* Convex programming studies the case when the objective function is convex and the constraints, if any, form a convex set. This can be viewed as a particular case of nonlinear programming or as generalization of linear or convex quadratic programming.
o Second order cone programming (SOCP).
* Semidefinite programming (SDP) is a subfield of convex optimization where the underlying variables are semidefinite matrices. It is generalization of linear and convex quadratic programming.

* Stochastic programming studies the case in which some of the constraints or parameters depend on random variables.
* Robust programming is, as stochastic programming, an attempt to capture uncertainty in the data underlying the optimization problem. This is not done through the use of random variables, but instead, the problem is solved taking into account inaccuracies in the input data.
* Combinatorial optimization is concerned with problems where the set of feasible solutions is discrete or can be reduced to a discrete one.
* Infinite-dimensional optimization studies the case when the set of feasible solutions is a subset of an infinite-dimensional space, such as a space of functions.
* Heuristic algorithms
o Metaheuristics
* Constraint satisfaction studies the case in which the objective function f is constant (this is used in artificial intelligence, particularly in automated reasoning).
o Constraint programming.
* Disjunctive programming used where at least one constraint must be satisfied but not all. Of particular use in scheduling.
* Trajectory optimization is the speciality of optimizing trajectories for air and space vehicles.

In a number of subfields, the techniques are designed primarily for optimization in dynamic contexts (that is, decision making over time):

* Calculus of variations seeks to optimize an objective defined over many points in time, by considering how the objective function changes if there is a small change in the choice path.
* Optimal control theory is a generalization of the calculus of variations.
* Dynamic programming studies the case in which the optimization strategy is based on splitting the problem into smaller subproblems. The equation that relates these subproblems is called the Bellman equation.

[edit] Techniques

For twice-differentiable functions, unconstrained problems can be solved by finding the points where the gradient of the objective function is zero (that is, the stationary points) and using the Hessian matrix to classify the type of each point. If the Hessian is positive definite, the point is a local minimum, if negative definite, a local maximum, and if indefinite it is some kind of saddle point.

However, existence of derivatives is not always assumed and many methods were devised for specific situations. The basic classes of methods, based on smoothness of the objective function, are:

* Combinatorial methods
* Derivative-free methods
* First order methods
* Second-order methods

Actual methods falling somewhere among the categories above include:

* Gradient descent aka steepest descent or steepest ascent
* Nelder-Mead method aka the Amoeba method
* Subgradient method - similar to gradient method in case there are no gradients
* Simplex method
* Ellipsoid method
* Bundle methods
* Newton's method
* Quasi-Newton methods
* Interior point methods
* Conjugate gradient method
* Line search - a technique for one dimensional optimization, usually used as a subroutine for other, more general techniques.

Should the objective function be convex over the region of interest, then any local minimum will also be a global minimum. There exist robust, fast numerical techniques for optimizing twice differentiable convex functions.

Constrained problems can often be transformed into unconstrained problems with the help of Lagrange multipliers.

Here are a few other popular methods:

* Hill climbing
* Simulated annealing
* Quantum annealing
* Tabu search
* Beam search
* Genetic algorithms
* Ant colony optimization
* Evolution strategy
* Stochastic tunneling
* Differential evolution
* Particle swarm optimization
* Harmony search
* Bees algorithm

[edit] Uses

Problems in rigid body dynamics (in particular articulated rigid body dynamics) often require mathematical programming techniques, since you can view rigid body dynamics as attempting to solve an ordinary differential equation on a constraint manifold; the constraints are various nonlinear geometric constraints such as "these two points must always coincide", "this surface must not penetrate any other", or "this point must always lie somewhere on this curve". Also, the problem of computing contact forces can be done by solving a linear complementarity problem, which can also be viewed as a QP (quadratic programming problem).

Many design problems can also be expressed as optimization programs. This application is called design optimization. One recent and growing subset of this field is multidisciplinary design optimization, which, while useful in many problems, has in particular been applied to aerospace engineering problems.

Mainstream economics also relies heavily on mathematical programming. An often studied problem in microeconomics, the utility maximization problem, and its dual problem the Expenditure minimization problem, are economic optimization problems. Consumers and firms are assumed to maximize their utility/profit. Also, agents are most frequently assumed to be risk-averse thereby wishing to minimize whatever risk they might be exposed to. Asset prices are also explained using optimization though the underlying theory is more complicated than simple utility or profit optimization. Trade theory also uses optimization to explain trade patterns between nations.

Another field that uses optimization techniques extensively is operations research.

Tuesday, June 17, 2008

Larynx

研究的仿生医学--声带的3维运动(在说话的时候)

心中的烙印

刚刚在做数值优化,沉浸在 nelder mead algorithms,simulated annealing, generic algorithms里。突然心里想起曾经的心中的那位公主。
最近科研蛮忙的。带我的人成了教授了。很为michael高兴。

也是刚才去网站上看了看公主的歌贴。恩,还是那么美。很为她感到高兴:-)

为你祝福着。相信我们会在天堂里见面的。盼望着。

大熊

Friday, June 6, 2008

【KIMI★乔任梁】比坦然接受更深情的爱,是尊重

卫宣利有一篇文章叫做《玫瑰丝巾》,大意讲的是一个27岁女子,优雅,干练,颈间总是一条飘逸的玫瑰丝巾,在朋友的生日派对上他遇到的她,他的目光越过人群追随着她,那一抹灵动飘逸的玫瑰红,引燃了一颗激情四溢的心。  再后来便开始有许多"巧合":她常去的咖啡店,总能碰到他;她不小心丢掉的钥匙,会碰巧让他捡了去;她去看电影,散了场还兀自抹眼泪,也是他,递过来一方洁白手帕……便这样慢慢熟悉起来,她盈盈的笑,如花一样。  很奇怪,她那样风情万种的女子,却不喜欢耳环项链手镯之类的饰品。唯独丝巾,却是无论春秋冬夏,从不离身。真丝的,羊绒的,薄的,厚的,长的,方的,或打个漂亮的蝴蝶结,或随意绕在颈间,每一种姿态,都让他心醉神迷。   是在无意间,发现了她丝巾背后的秘密。  那日两人一起去郊游,晴朗朗的天,突然就变了,席地而起的狂风,如一双强硬的手,毫不留情地揭去她颈间的玫瑰丝巾。她慌忙跟过去追,那一抹浅红,早已随风飘远。他握着她的手,嗔怪她,不过一条丝巾而已,回头买条新的给你。眼睛望向她裸露的脖颈,却惊异地发现:她颀长的脖颈上,竟布满了紫红色的疤痕。道道疤痕交织扭曲,像一条条蜿蜒的蚯蚓,在她的颈间恣意爬行。   他怔住了。她尴尬地笑,说,小时候,冬天烤火,不小心从凳子上跌下来,碰翻了火炉……    他也只是一怔,很快便坦然笑道,瑕不掩瑜,以后,不要再系丝巾了,我更喜欢真实的你。   他果然再不准她系丝巾,坦然牵她的手出入各种场合。他不止一次对她说,爱一个人,就是坦然接受她的一切,包括缺点和瑕疵。   她从此就收了那些千娇百媚的丝巾,裸露着颈上的疤痕。那些疤痕引来各种各样的目光,很多人惊问,呀,你的脖子,怎么回事?问一次,她都要把原因重复一遍。她的骄傲和自尊,就这样一点点被蚕食。当爱恋的欢喜终于被一次次的尴尬淹没时,她提出了分手。   她重新系上玫瑰丝巾,依然是笑眸流转,风情万种。心却愈加成熟淡定。   半年后,朋友介绍新的男朋友,是个干净儒雅的男人,目光在她飞扬的玫瑰丝巾间辗转停留,亦有疑问:怎么你老是系着丝巾呢?   她便大方地解了丝巾给他看,面对着那些蜿蜒的伤痕,他微微叹息。然后,轻轻帮她系上玫瑰丝巾,在颈间斜着打一个优雅的结。那个结系得翩然舒展,如一只展翅欲飞的蝶,栖息在她的肩头。   那以后,他给她买了各种各样的丝巾,亲手给她系上。他说,最美的花,总是开在伤口之上的。   她的心,被柔柔地濡湿了。   原来,比坦然接受更深情的爱,是尊重。   [转自天涯]

来自网络:有一种爱叫做放手

http://www.helloread.com/  2007-09-02

*  核心提示:原来,七十分跟一百分的区别在这里。如果一个女人真心爱你,即使你是多么不完美,你在她心目中都是一百分;但若是她不爱你,无论你有多优秀,对她有多好,你充其量也只能拿个七十分!


有一种爱叫做放手
他跟她一起已经四年了。四年来,都是他在照顾她、呵护她、紧张她,而她一直在享受这种关心爱护,但她对他总是不冷不热,周末依然跟朋友同事玩乐,从来对他不会太挂心。他心里明白其实自己对她的爱比起她对自己的爱要重很多很多,这份感情之所以能够维系下去完全于在他对她的迁就、忍让以及骨子里面渗透出来的那份爱
!她也知道,他会对她深情相伴,不离不弃,所以她尽情的去挥霍他的爱、榨干他的爱,一次次的出卖、一次次回归、一次次言归于好... ...但他却一次次的奢望自己的真情终有一天能够感动她!因为他知道他对她的爱是没有其他人可以相比的,最终能够留在她身边的人只有她!可是,他一直生活在恐慌当中,不知道哪一天,她又会离开他投入到另外一个男人的怀抱里。
这一天终于来临,她开始夜不归家,手机整天呈关机状态。他发疯地到处找她,希望跟以前每一次一样用自己的双手把她牵回家。可是他居然连她新换了工作的地址都不知道,人海茫茫,这座城市这么大,到哪里能把心爱的她找回来?!这一次她一消失就一个多星期,再次相见却已形同陌路。她回到他们的小家,默默的收拾行李并告诉她她爱上了一个刚认识了两个月的男人,她希望他能成全她... ...他绝望地看着她,衷伤地对她说:"你考虑清楚了吗?现在给你两条路:要么跟他走,要么留下来跟我一起。你衡量一下,一边是你相恋了四年的深受着你的男友,一边却是你才认识了两个月的男人!"他以为她这一次又会像之前那样子扑到他怀里。谁知她这一次的回答远远的超出他的预料之外。"我选他!既然我可以找到一个一百分的男人我什么要勉强自己跟一个七十分的男人在一起!"原来,他在她心目中只值七十分!原来他以为自己是她这辈子的依靠事实证明这一切不过是他自己在痴人说梦;原来自己只不过是她生命中一个过客;原来当一个女人无情起来的时候可以如此的狠心!可是,他爱她!他没有办法去恨一个已经融入自己生命的女人。

他只是恨自己为什么只值七十分而不是一百分!她走了,他的世界已经垮下来,天空是灰的,从此没有色彩。分手后的那段时间,他打她的手机,谁知道她居然狠心到把他的电话设为拒接号码。是自己太犯贱了吗?他反省自己,可是,思念却像枯叶上的树藤把自己缠得无法呼吸。他打听到她跟新男友就住在二横路附近,于是他就到附近的文化宫报了一个学习班,每天下班后他都要去那里上课,为的就是希望有一天能够遇到她,能看看她过得好不好。也许是他们的缘份已尽吧!分后一年多了,他从未把她忘怀,但却就是从来没有遇到过她。
眨眼两年已经过去了,他从没有感觉到她的离开,他的房子里面还保留着她走之前的模样。他总是想终有一天她会回来,这个世界上最合适她的人是自己,最爱她的人也是自己。哪一天,她倦了,累了,她就会回来... ...

事实证明,他错了!她再也不会回来了!就在那天,他上完在文化宫最后一节课,拖着疲倦的身子去附件的超市买点饮料。突然之间,他看到她!她跟两年前一样还是留着长长的直直的头发,清秀的面容,纤细的身子,一点都没有改变。但是,她好像又完全变了,因为她的眼神不像以前那样飘忽迷离,她眼睛里有一种亮亮的东西。哦,是温柔!顺着她的目光,他看到了她的男友,个子高高的,条件并不见得特别优秀。刹那间,有种撕心裂肺的感觉扑面而来。他闭上了眼睛,任由心底的那颗眼泪从眼角滴下来。她何时曾用过这种温柔专注的眼神看过自己??原来,七十分跟一百分的区别在这里。如果一个女人真心爱你,即使你是多么不完美,你在她心目中都是一百分;但若是她不爱你,无论你有多优秀,对她有多好,你充其量也只能拿个七十分!
他终于明白了,有一种爱叫做放手!当彼此感情已不再,那么就放手吧!让你去找属于你的幸福,让我对你的那份爱深深埋藏,让所有的记忆尘封。他转过身,擦干眼泪大步的往车站方向走去... ...

Wednesday, June 4, 2008

心有独钟

这种感觉从来不曾有
左右每天思绪
每一次呼吸心被占据
却苦无厌
是你让我着了迷
给了甜蜜又保持距离
而你潇洒来去玩爱情游戏
我一天天失去勇气
偏偏难又难忘记
等等为你心有独钟
因为爱过才知情多浓
浓得发痛在心中痛全是感动
我是真的真的与众不同
真正为你心有独钟
因为有你世界变不同
笑我太傻太蒙懂或爱得太重
只为相信我自己
能永远对你心有独钟

Tuesday, June 3, 2008

原谅别人善待自己

http://blog.ci123.com/shenyiling/entry/365164

今晨起来,照例拉开窗帘,一树黄叶,遍地秋风。某些对于秋的记忆,像季节一般重临了,而且比往日更深沉。

不再是情人了,难道就该是仇人,甚至路人了么?我不相信如此,也认为绝对不应该如此。

在爱情的道路上,由于各种各样的原因,包括人力无法企及的在内,分手和离异往往成为难于避免的结果。

对于自己过去曾经深深爱过的人,无论是情人还是夫妻,即使对方有负于我,或者犯下某种过错,作为伤心人的你,与其记恨,不如宽恕,并且遗忘最好。何况,有的时候,我们本身亦有错失。

一个怀着怨恨的人只能活在过去,而过去是不能挽救,也无法予以更正的。我们只是徒然遭受苦恼的鞭策。对于负心的情人,出轨的丈夫或妻子,在宽恕了他们的同时,自己亦安全地通过了艰难的情感关渡,可以期待一个重新的开始。

许多人往往在口头上原谅了对方,可是对一切并不忘怀,这并不是真正的宽恕。怀着一颗冰冷的心,口头上的原谅只不过是证明自己道德的优越性,这只是在令对方痛苦,并折磨着自己。

真正的宽恕非但原谅对方的过错,并且遗忘自已所做出的原谅。过分地强调自己的襟怀大度,会使对方负咎,并非彻底的原谅。只有心口如一的真正宽恕,才会为你带来安静平和的心境。对别人仁慈,亦即是善待自己。

谁都明白一个怀有仇恨情结的人,自己的内心亦饱受骚扰,并不平安。因此宽恕别人亦即拯救自己。至少是为了不防碍自己的快乐,我们选择宽恕。这些道理既平凡又乏味,但是我们仍然要强调一句话――宽恕了别人,便是宽恕了自己。

由于宽恕,有的时候,破镜亦能重圆。这是爱的神奇力量。尤其是在夫妻的一方发生外遇的时刻,宽恕,能令双方回心转意,两颗心再重新做出坚定的结合。

在许多情况之下,由于意气,原本值得挽救的婚姻和爱情却毁弃了。

对自己曾经深深受过的人,即使不能做夫妻、不能做爱人,至少也应该作为朋友,而绝非仇人或路人。

对过去的恋人口出恶言,这只能表示一切尚未过去,并且承认错爱及否定自己,眼光大有问题之外,同时亦是一个量窄的人。能够将过去的亲密关系转变为朋友的情谊,这非但是对过去爱恋的价值肯定,同时也是一种成熟的人格表现。

人生的许多造化不能强求。修正不了命运,至少可以修正自己。一个怀抱仇恨的人,往往会自筑感情的高墙,非但自绝于人,也自绝于已。

所谓感情的韧度,也就是恢复感情刺伤的能力,使自己未来的幸福不致受到妨碍。何况真正爱一个人,只要对方幸福,也不一定以自己为依归。

我深深感到通过了爱情的友谊,特别容易沟通且温馨感人。让分手的恋人,今后仍然成为互相关怀的友人,并为对方祝福。

这一声祝福虽然说与对方,却会回到自身。这是现代人际关系中新的一课,然而却是必修的一课。