本文系轉(zhuǎn)載內(nèi)容。

試卷難度概括：

12月9日試卷考的是A05，依舊是隱藏了試卷原有的篇碼。這次A05四個(gè)單項(xiàng)的難度，以英語(yǔ)及科學(xué)較難，這次ACT可以說(shuō)是玩“陰”的，在做第一篇時(shí)會(huì)感覺簡(jiǎn)單，但難度的級(jí)別是層層遞增，愈做愈難。如果考生在時(shí)間控制上掌握不夠純熟，容易被前面簡(jiǎn)單的篇章掉以輕心，導(dǎo)致后面的時(shí)間較緊張。數(shù)學(xué)和閱讀相對(duì)簡(jiǎn)單，數(shù)學(xué)考的是基礎(chǔ)知識(shí)點(diǎn)，如果數(shù)學(xué)的知識(shí)點(diǎn)穩(wěn)固，拿35、36分不是問(wèn)題，閱讀的題型總題正常，小說(shuō)篇章簡(jiǎn)單，算是ACT終于在閱讀上放了大家一條生路。

英語(yǔ)篇章回顧：

英語(yǔ)更多的是句子功能題和簡(jiǎn)化。沒(méi)有什么難題。

Passage 1 The Guitar Man

1930年代，年輕的音樂(lè)家兼發(fā)明家Les Paul正苦心鉆研一種方式以克服當(dāng)時(shí)其它電吉他存在的音色問(wèn)題。Les Paul用松木創(chuàng)造出一種新的吉他，以克服之前電吉他的問(wèn)題，但是他的新吉他由于在外表上不traditional，所以觀眾不習(xí)慣。于是Les Paul大幅度地改裝了他自己的吉他：他將整個(gè)吉他琴體從中間鋸開，并將琴頸、琴橋與電路安裝到了一個(gè)長(zhǎng)方形的木塊上，并且將整個(gè)木塊放回鋸成兩半的吉他琴體中。這樣，他的吉他從外表上看來(lái)與一把原聲吉他別無(wú)二致，然而從內(nèi)部來(lái)看，卻是一把實(shí)心琴體的吉他。這樣，吉他就不能發(fā)出原聲吉他的聲音，且克服了其他吉他原有的問(wèn)題。目前他做出的original guitar在博物館展出，他的吉他給后來(lái)的音樂(lè)演奏留下了巨大財(cái)富。

有那么一道，....guitarist; named James/ guitarist, named James/ guitarist - named, James / guitarist named James。

Passage 2 A large scale environmental success story

文章主要講Mario J. Molina和Rowland研究CFCs，發(fā)現(xiàn)它們會(huì)破壞臭氧層，受到廣泛認(rèn)可，并于1995年獲得諾貝爾獎(jiǎng)。

以下摘自wikipedia：In 1974, as a postdoctoral researcher at University of California, Irvine, he and Rowland co-authored a paper in the journal Nature highlighting the threat of CFCs to the ozone layer in the stratosphere.At the time, CFCs were widely used as chemical propellants and refrigerants.

However, they discovered that chlorine atoms, produced by the decomposition of CFCs, catalytically destroy ozone.

Passage 3 The Rock’n’ Roll Camp for Girls

展開全文

文章主要講了女生搖滾夏令營(yíng)，這個(gè)活動(dòng)主要是為了help girls build self-esteem through music creation, performance, and workshops.活動(dòng)允許女生們自己選擇group的名字，活動(dòng)過(guò)程中instructors, band managers, band coaches, and other mentors come from all over to volunteer to help girls complete their project of creating and performing a song. 他們最終的演出不需要完美，目標(biāo)在于build girls’ self-esteem。

Passage 4 Cracking the Mayan Code

文章主要講Tatiana Proskouriakoff本來(lái)是去畫一個(gè)瑪雅遺跡的重建圖，在此過(guò)程中，他發(fā)現(xiàn)一個(gè)pattern，即瑪雅人記錄自己歷史的方式。

（摘自Nova：Tatiana Proskouriakoff was an architect. He took work drawing reconstructions of the ruins at Piedras Negras, a Classic Maya site on the border between Mexico and Guatemala (left). Later, while examining photographs of the Piedras Negras stelae, or commemorative stone slabs, Proskouriakoff noticed patterns in their dedication dates.

The Maya would set up a series of stelae in front of a single temple, one every five years. The first stela in each series always showed a seated figure. Thompson had thought these were gods, but Proskouriakoff convincingly proved that they were kings and that the different markings on the stelae depicted their lives from birth until death. When a ruler died, the Maya at Piedras Negras would begin erecting stelae at another temple, detailing the life story of another ruler. For the first time, as Thompson and others came to agree, the glyphs were found to tell the stories of the Maya.）

Passage 5 When a Highway Ran Celebrity

本文主要講的是Lincoln Highway的建造背景，建成時(shí)的受歡迎程度，以及實(shí)際上不夠完善的實(shí)施情況。

(背景摘自wikipedia：The Lincoln Highway was one of the earliest transcontinental highways for automobiles across the United States of America. Conceived in 1912 by Indiana entrepreneur Carl G. Fisher, and formally dedicated October 31, 1913, the Lincoln Highway ran coast-to-coast from Times Square in New York City west to Lincoln Park in San Francisco.)

數(shù)學(xué)試卷分析：

1. 考試難度

本次ACT考試數(shù)學(xué)部分簡(jiǎn)單，較難/更高級(jí)知識(shí)點(diǎn)沒(méi)有出現(xiàn)，考生只要掌握好在上課所涵蓋的知識(shí)點(diǎn)范圍，基本不會(huì)出現(xiàn)卡題情況。但比起以往的數(shù)學(xué)試題ACT增加了較多的干擾點(diǎn)，不是所有數(shù)字都會(huì)使用到，考時(shí)注意一些小的細(xì)節(jié)點(diǎn), 避免粗心大意的問(wèn)題, 數(shù)學(xué)部分考取一個(gè)理想的分?jǐn)?shù)應(yīng)該不成問(wèn)題。

2. 閱讀理解層面

本次考試題目上的閱讀理解難度適中, 雖然題目的篇幅增長(zhǎng)，增加了較多的干擾點(diǎn)，但整體沒(méi)有較難或者較為生僻的數(shù)學(xué)學(xué)科詞匯干擾大家做題。甚至是概率題中害怕考生無(wú)法理解題目，甚至給了例子，如1-6-P，助考生理解。

3. 數(shù)學(xué)知識(shí)層面

本次考試在數(shù)學(xué)知識(shí)方面難度相對(duì)簡(jiǎn)單，考的知識(shí)點(diǎn)大致可以概括為：

(1)Probability

(2)Algebra

(3)Coordinate Geometry

(4)Trigonometry

(5)Amplitude and Period

(6)Parabola

(7)Circle

整套試題沒(méi)有出現(xiàn)序列題、橢圓題、矩陣題、邏輯題等易錯(cuò)的題型都沒(méi)有在本次考試中出現(xiàn)，就連需要考生背誦的三角函數(shù)都給出了公式formula。

閱讀篇章回顧：

1. 閱讀第一篇

本篇閱讀是來(lái)自 Teju Cole 的一本書 “Open City”的一段節(jié)選。講述作者與這個(gè)以前的同學(xué)的偶然相遇，作者沒(méi)認(rèn)出來(lái)，但他的同學(xué)認(rèn)出來(lái)了。接著作者回憶了關(guān)于那個(gè)同學(xué)哥哥的事。閱讀小說(shuō)是一個(gè)尼日利亞的人遇見了以前在軍校的好友的姐姐，對(duì)此作出的感慨。原文如下：

2. 閱讀第二篇

本篇閱讀是 Jonathans 的一本書 “The Future of the Wild: Radical Conservation for a Crowded World” 的一段節(jié)選，文章大意是講述生物學(xué)家 Jonathan S.其背后的主要策略是利用最新的保護(hù)科學(xué)和當(dāng)?shù)厣鐓^(qū)的需求來(lái)保護(hù)人們的生活和工作場(chǎng)所。

文章的節(jié)選是書的前部分，由當(dāng)時(shí)人們建立Earth Day 去解決pollution，但事實(shí)上還有更嚴(yán)重的問(wèn)題來(lái)引入。通過(guò)這種方式，每一次小小的成功都使保護(hù)主義者更加接近創(chuàng)造出足夠大的保護(hù)景觀來(lái)支持野牛和狼等動(dòng)物。只有在這些土地之間漫游的自由，使用荒野走廊，這樣的大動(dòng)物才能蓬勃發(fā)展。

3. 閱讀第三篇

Avast, Me Critics! Ye Kill the Fun: Critics and the Masses Disagree About Film Choices，本篇閱讀是來(lái)自 A.O. Scott ，是2006年7月的一篇文章，刊登在 NewYork Times，內(nèi)容是關(guān)于電影批評(píng)家，作者的觀點(diǎn)是支持并且為這些批評(píng)家們辯護(hù)。原文如下 ：

Let’s start with a few numbers. At Rottentomatoes.com, a Web site that quantifies movie reviews on a 100-point scale, the aggregate score for “Pirates of the Caribbean: Dead Man’s Chest” stands at a sodden 54. Metacritic.com, a similar site, crunches the critical prose of the nation’s reviewers and comes up with a numerical grade of 52 out of 100. Even in an era of rampant grade inflation, that’s a solid F.

Meanwhile, over at boxofficemojo.com, where the daily grosses are tabulated, the second installment in the “Pirates” series, which opened on July 7, plunders onward, trailing broken records in its wake. Its $136 million first-weekend take was the highest three-day tally in history, building on a best-ever $55 million on that Friday, and it is cruising into blockbuster territory at a furious clip. As of this writing, a mere 10 days into its run, the movie has brought in $258.2 million, a hit by any measure.

All of which makes “Dead Man’s Chest” a fascinating sequel — not to “Curse of the Black Pearl,” which inaugurated the franchise three years ago, but to “The Da Vinci Code.” Way back in the early days of the Hollywood summer — the third week in May, to be precise — America’s finest critics trooped into screening rooms in Cannes, Los Angeles, New York and points between, saw Ron Howard’s adaptation of Dan Brown’s best seller, and emerged in a fit of collective grouchiness. The movie promptly pocketed some of the biggest opening-weekend grosses in the history of its studio, Sony.

For the second time this summer, then, my colleagues and I must face a frequently — and not always politely — asked question: What is wrong with you people? I will, for now, suppress the impulse to turn the question on the moviegoing public, which persists in paying good money to see bad movies that I see free. I don’t for a minute believe that financial success contradicts negative critical judgment; $500 million from now, “Dead Man’s Chest” will still be, in my estimation, occasionally amusing, frequently tedious and entirely too long. But the discrepancy between what critics think and how the public behaves is of perennial interest because it throws into relief some basic questions about taste, economics and the nature of popular entertainment, as well as the more vexing issue of what, exactly, critics are for.

Are we out of touch with the audience? Why do we go sniffing after art where everyone else is looking for fun, and spoiling everybody’s fun when it doesn’t live up to our notion or art? What gives us the right to yell “bomb” outside a crowded theater? Variations on these questions arrive regularly in our e-mail in-boxes, and also constitute a major theme in the comments sections of film blogs and Web sites. Online, everyone is a critic, which is as it should be: professional prerogatives aside, a critic is really just anyone who thinks out loud about something he or she cares about, and gets into arguments with fellow enthusiasts. But it would be silly to pretend that those professional prerogatives don’t exist, and that they don’t foster a degree of resentment. Entitled elites, self-regarding experts, bearers of intellectual or institutional authority, misfits who get to see a movie before anybody else and then take it upon themselves to give away the ending: such people are easy targets of populist anger. Just who do we think we are?

There is no easy answer to this question. Film criticism — at least as practiced in the general-interest daily and weekly press — has never been a specialist pursuit. Movies, more than any other art form, are understood to be common cultural property, something everyone can enjoy, which makes any claim of expertise suspect. Therefore, a certain estrangement between us and them — or me and you, to put it plainly — has been built into the enterprise from the start.

The current schism is in some ways nothing new: go back and read reviews in The New York Times of “Top Gun,” “Crocodile Dundee” and “The Karate Kid Part II” to see how some of my predecessors dealt with three of the top-earning movies 20 years ago. (The Australian with the big knife was treated more kindly than the flyboy or the high-kicker, by the way.) And the divide between critic and public may also be temporary. Last year, during the Great Box-Office Slump of 2005, we all seemed happy to shrug together at the mediocrity of the big studio offerings.

No more. Whatever the slump might have portended for the movie industry, it appears to be over for the moment, and the critics have resumed their customary role of scapegoat. The modern blockbuster — the movie that millions of people line up to see more or less simultaneously, on the first convenient showing on the opening weekend — can be seen as the fulfillment of the democratic ideal the movies were born to fulfill. To stand outside that happy communal experience and, worse, to regard it with skepticism or with scorn, is to be a crank, a malcontent, a snob.

So we’re damned if we don’t. And sometimes, also, if we do. When our breathless praise garlands advertisements for movies the public greets with a shrug, we look like suckers or shills. But these accusations would stick only if the job of the critic were to reflect, predict or influence the public taste.

That, however, is the job of the Hollywood studios, in particular of their marketing and publicity departments, and it is the professional duty of critics to be out of touch with — to be independent of — their concerns. These companies spend tens of millions of dollars to persuade you that the opening of a movie is a public event, a cultural experience you will want to be part of. The campaign of persuasion starts weeks or months — or, in the case of multisequel cash cows, years — before the tickets go on sale, with the goal of making their purchase a foregone conclusion by the time the first reviews appear. Sometimes it works and sometimes it doesn’t, but the judgment of critics almost never makes the difference between failure and success, at least for mass-release, big-budget movies like “Dead Man’s Chest” or “The Da Vinci Code.”

So why review them? Why not let the market do its work, let the audience have its fun and occupy ourselves with the arcana — the art — we critics ostensibly prefer? The obvious answer is that art, or at least the kind of pleasure, wonder and surprise we associate with art, often pops out of commerce, and we want to be around to celebrate when it does and to complain when it doesn’t. But the deeper answer is that our love of movies is sometimes expressed as a mistrust of the people who make and sell them, and even of the people who see them. We take entertainment very seriously, which is to say that we don’t go to the movies for fun. Or for money. We do it for you.

http://www.nytimes.com/2006/07/18/movies/18crit.html

4. 閱讀第四篇

這次雙篇閱讀放在最后的自然科學(xué)，大致是第一篇說(shuō)螞蟻怎么排隊(duì)回洞，第二篇說(shuō)蜜蜂的尋找別的家，主要講的就是螞蟻與蜜蜂團(tuán)體決策機(jī)智。

第一篇閱讀A是來(lái)自 CARL ZIMMERNO，是2007年的一篇文章，刊登在 NewYork Times，標(biāo)題為 “From Ants to People, an Instinct to Swarm”，原文如下 ：(紅字是閱讀的內(nèi)容）

If you have ever observed ants marching in and out of a nest, you might have been reminded of a highway buzzing with traffic. To Iain D. Couzin, such a comparison is a cruel insult — to the ants.

Americans spend a 3.7 billion hours a year in congested traffic. But you will never see ants stuck in gridlock.

Army ants, which Dr. Couzin has spent much time observing in Panama, are particularly good at moving in swarms. If they have to travel over a depression in the ground, they erect bridges so that they can proceed as quickly as possible.

“They build the bridges with their living bodies,” said Dr. Couzin, a mathematical biologist at Princeton University and the University of Oxford. “They build them up if they’re required, and they dissolve if they’re not being used.”

The reason may be that the ants have had a lot more time to adapt to living in big groups. “We haven’t evolved in the societies we currently live in,” Dr. Couzin said.

By studying army ants — as well as birds, fish, locusts and other swarming animals — Dr. Couzin and his colleagues are starting to discover simple rules that allow swarms to work so well. Those rules allow thousands of relatively simple animals to form a collective brain able to make decisions and move like a single organism.

Deciphering those rules is a big challenge, however, because the behavior of swarms emerges unpredictably from the actions of thousands or millions of individuals.

“No matter how much you look at an individual army ant,” Dr. Couzin said, “you will never get a sense that when you put 1.5 million of them together, they form these bridges and columns. You just cannot know that.”

To get a sense of swarms, Dr. Couzin builds computer models of virtual swarms. Each model contains thousands of individual agents, which he can program to follow a few simple rules. To decide what those rules ought to be, he and his colleagues head out to jungles, deserts or oceans to observe animals in action.

Daniel Grunbaum, a mathematical biologist at the University of Washington, said his field was suddenly making leaps forward, as math and observation of nature were joined in the work of Dr. Couzin and others. “In the next 10 years there’s going to be a lot of progress.”

He said Dr. Couzin has been important in fusing the different kinds of science required to understand animal group behavior. “He’s been a real leader in bringing a lot of ideas together,” Dr. Grunbaum said. “He has a larger vision. If it works, that’ll be a big advance.”

In the case of army ants, Dr. Couzin was intrigued by their highways. Army ants returning to their nest with food travel in a dense column. This incoming lane is flanked by two lanes of outgoing traffic. A three-lane highway of army ants can stretch for as far as 150 yards from the ant nest, comprising hundreds of thousands of insects.

What Dr. Couzin wanted to know was why army ants do not move to and from their colony in a mad, disorganized scramble. To find out, he built a computer model based on some basic ant biology. Each simulated ant laid down a chemical marker that attracted other ants while the marker was still fresh. Each ant could also sweep the air with its antennas; if it made contact with another ant, it turned away and slowed down to avoid a collision.

Dr. Couzin analyzed how the ants behaved when he tweaked their behavior. If the ants turned away too quickly from oncoming insects, they lost the scent of their trail. If they did not turn fast enough, they ground to a halt and forced ants behind them to slow down. Dr. Couzin found that a narrow range of behavior allowed ants to move as a group as quickly as possible.

It turned out that these optimal ants also spontaneously formed highways. If the ants going in one direction happened to become dense, their chemical trails attracted more ants headed the same way. This feedback caused the ants to form a single packed column. The ants going the other direction turned away from the oncoming traffic and formed flanking lanes.

To test this model, Dr. Couzin and Nigel Franks, an ant expert at the University of Bristol in England, filmed a trail of army ants in Panama. Back in England, they went through the film frame by frame, analyzing the movements of 226 ants. “Everything in the ant world is happening at such a high tempo it was very difficult to see,” Dr. Couzin said.

Eventually they found that the real ants were moving in the way that Dr. Couzin had predicted would allow the entire swarm to go as fast as possible. They also found that the ants behaved differently if they were leaving the nest or heading back. When two ants encountered each other, the outgoing ant turned away further than the incoming one. As a result, the ants headed to the nest end up clustered in a central lane, while the outgoing ants form two outer lanes. Dr. Couzin has been extending his model for ants to other animals that move in giant crowds, like fish and birds. And instead of tracking individual animals himself, he has developed programs to let computers do the work.

The more Dr. Couzin studies swarm behavior, the more patterns he finds common to many different species. He is reminded of the laws of physics that govern liquids. “You look at liquid metal and at water, and you can see they’re both liquids,” he said. “They have fundamental characteristics in common. That’s what I was finding with the animal groups — there were fundamental states they could exist in.”

Just as liquid water can suddenly begin to boil, animal swarms can also change abruptly thanks to some simple rules.

Dr. Couzin has discovered some of those rules in the ways that locusts begin to form their devastating swarms. The insects typically crawl around on their own, but sometimes young locusts come together in huge bands that march across the land, devouring everything in their path. After developing wings, they rise into the air as giant clouds made of millions of insects.

“Locusts are known to be around all the time,” Dr. Couzin said. “Why does the situation suddenly get out of control, and these locusts swarm together and devastate crops?”

Dr. Couzin traveled to remote areas of Mauritania in Africa to study the behavior of locust swarms. Back at Oxford, he and his colleagues built a circular track on which locusts could walk. “We could track the motion of all these individuals five times a second for eight hours a day,” he said.

The scientists found that when the density of locusts rose beyond a threshold, the insects suddenly began to move together. Each locust always tried to align its own movements with any neighbor. When the locusts were widely spaced, however, this rule did not have much effect on them. Only when they had enough neighbors did they spontaneously form huge bands.

“We showed that you don’t need to know lots of information about individuals to predict how the group will behave,” Dr. Couzin said of the locust findings, which were published June 2006 in Science.

Understanding how animals swarm and why they do are two separate questions, however.

In some species, animals may swarm so that the entire group enjoys an evolutionary benefit. All the army ants in a colony, for example, belong to the same family. So if individuals cooperate, their shared genes associated with swarming will become more common.

But in the deserts of Utah, Dr. Couzin and his colleagues discovered that giant swarms may actually be made up of a lot of selfish individuals.

Mormon crickets will sometimes gather by the millions and crawl in bands stretching more than five miles long. Dr. Couzin and his colleagues ran experiments to find out what caused them to form bands. They found that the forces behind cricket swarms are very different from the ones that bring locusts together. When Mormon crickets cannot find enough salt and protein, they become cannibals.

“Each cricket itself is a perfectly balanced source of nutrition,” Dr. Couzin said. “So the crickets, every 17 seconds or so, try to attack other individuals. If you don’t move, you’re likely to be eaten.”

This collective movement causes the crickets to form vast swarms. “All these crickets are on a forced march,” Dr. Couzin said. “They’re trying to attack the crickets who are ahead, and they’re trying to avoid being eaten from behind.”

Swarms, regardless of the forces that bring them together, have a remarkable ability to act like a collective mind. A swarm navigates as a unit, making decisions about where to go and how to escape predators together.

“There’s a swarm intelligence,” Dr. Couzin said. “You can see how people thought there was some sort of telekinesis involved.”

What makes this collective decision-making all the more puzzling is that each individual can behave only based on its own experience. If a shark lunges into a school of fish, only some of them will see it coming. If a flock of birds is migrating, only a few experienced individuals may know the route.

Dr. Couzin and his colleagues have built a model of the flow of information through swarms. Each individual has to balance two instincts: to stay with the group and to move in a desired direction. The scientists found that just a few leaders can guide a swarm effectively. They do not even need to send any special signals to the animals around them. They create a bias in the swarm’s movement that steers it in a particular direction.

“It doesn’t necessarily mean you have the right information, though,” Dr. Couzin pointed out.

Two leaders may try to pull a swarm in opposite directions, and yet the swarm holds together. In Dr. Couzin’s model, the swarm was able to decide which leaders to follow.

“As we increased the difference of opinion between the informed individuals, the group would spontaneously come to a consensus and move in the direction chosen by the majority,” Dr. Couzin said. “They can make these decisions without mathematics, without even recognizing each other or knowing that a decision has been made.”

Dr. Couzin and his colleagues have been finding support for this model in real groups of animals. They have even found support in studies on mediocre swarmers — humans.

To study humans, Dr. Couzin teamed up with researchers at the University of Leeds. They recruited eight people at a time to play a game. Players stood in the middle of a circle, and along the edge of the circle were 16 cards, each labeled with a number. The scientists handed each person a slip of paper and instructed the players to follow the instructions printed on it while not saying anything to the others. Those rules correspond to the ones in Dr. Couzin’s models. And just as in his models, each person had no idea what the others had been instructed to do.

In one version of the experiment, each person was instructed simply to stay with the group. As Dr. Couzin’s model predicted, they tended to circle around in a doughnut-shaped flock. In another version, one person was instructed to head for a particular card at the edge of the circle without leaving the group. The players quickly formed little swarms with their leader at the head, moving together to the target.

The scientists then sowed discord by telling two or more people to move to opposite sides of the circle. The other people had to try to stay with the group even as leaders tried to pull it apart.

As Dr. Couzin’s model predicted, the human swarm made a quick, unconscious decision about which way to go. People tended to follow the largest group of leaders, even if it contained only one additional person.

Dr. Couzin and his colleagues describe the results of these experiments in a paper to be published in the journal Animal Behavior.

Dr. Couzin is carrying the lessons he has learned from animals to other kinds of swarms. He is helping Dr. Naomi Leonard, a Princeton engineer, to program swarming into robots.

“These things are beginning to move around and interact in ways we see in nature,” he said. Ultimately, flocks of robots might do a better job of collecting information in dangerous places. “If you knock out some individual, the algorithm still works. The group still moves normally.” The rules of the swarm may also apply to the cells inside our bodies. Dr. Couzin is working with cancer biologists to discover the rules by which cancer cells work together to build tumors or migrate through tissues. Even brain cells may follow the same rules for collective behavior seen in locusts or fish.

“One of the really fun things that we’re doing now is understanding how the type of feedbacks in these groups is like the ones in the brain that allows humans to make decisions,” Dr. Couzin said. Those decisions are not just about what to order for lunch, but about basic perception — making sense, for example, of the flood of signals coming from the eyes. “How does your brain take this information and come to a collective decision about what you’re seeing?” Dr. Couzin said. The answer, he suspects, may lie in our inner swarm.

第二篇閱讀B是來(lái)自 Peter MillerO，也是2007年的一篇文章，刊登在National Geographic，標(biāo)題為 “The Genius of Swarms”，原文如下 ：

“Thomas Seeley, a biologist at Cornell University, has been looking into the uncanny ability of honeybees to make good decisions. With as many as 50,000 workers in a single hive, honeybees have evolved ways to work through individual differences of opinion to do what’s best for the colony. If only people could be as effective in boardrooms, church committees, and town meetings, Seeley says, we could avoid problems making decisions in our own lives.

“During the past decade, Seeley, Kirk Visscher of the University of California, Riverside, and others have been studying colonies of honeybees (Apis mellifera) to see how they choose a new home. In late spring, when a hive gets too crowded, a colony normally splits, and the queen, some drones, and about half the workers fly a short distance to cluster on a tree branch. There the bees bivouac while a small percentage of them go searching for new real estate. Ideally, the site will be a cavity in a tree, well off the ground, with a small entrance hole facing south, and lots of room inside for brood and honey. Once a colony selects a site, it usually won’t move again, so it has to make the right choice.

“To find out how, Seeley’s team applied paint dots and tiny plastic tags to identify all 4,000 bees in each of several small swarms that they ferried to Appledore Island, home of the Shoals Marine Laboratory. There, in a series of experiments, they released each swarm to locate nest boxes they’d placed on one side of the half-mile-long (one kilometer) island, which has plenty of shrubs but almost no trees or other places for nests.

“In one test they put out five nest boxes, four that weren’t quite big enough and one that was just about perfect. Scout bees soon appeared at all five. When they returned to the swarm, each performed a waggle dance urging other scouts to go have a look. (These dances include a code giving directions to a box’s location.) The strength of each dance reflected the scout’s enthusiasm for the site. After a while, dozens of scouts were dancing their little feet off, some for one site, some for another, and a small cloud of bees was buzzing around each box.

“The decisive moment didn’t take place in the main cluster of bees, but out at the boxes, where scouts were building up. As soon as the number of scouts visible near the entrance to a box reached about 15—a threshold confirmed by other experiments—the bees at that box sensed that a quorum had been reached, and they returned to the swarm with the news.

“‘It was a race,’ Seeley says. ‘Which site was going to build up 15 bees first?’

“Scouts from the chosen box then spread through the swarm, signaling that it was time to move. Once all the bees had warmed up, they lifted off for their new home, which, to no one’s surprise, turned out to be the best of the five boxes.

“The bees’ rules for decision-making—seek a diversity of options, encourage a free competition among ideas, and use an effective mechanism to narrow choices—so impressed Seeley that he now uses them at Cornell as chairman of his department.”

科學(xué)試卷分析：

科學(xué)這次是六篇。

科學(xué)第一篇是Coral跟氣體、溫度與水壓的一個(gè)綜合圖表；第二篇是oil 的 viscosity ；第三篇是 Antigen 的 exposure; 第四篇是CV題，講的是海王星的一個(gè)衛(wèi)星，三個(gè)天體物理學(xué)講述這個(gè)衛(wèi)星怎么變成海王星的衛(wèi)星。常識(shí)題在這篇出現(xiàn)了一題，是第一個(gè)天體物理學(xué)家提到了星環(huán)，然后有一個(gè)問(wèn)題就問(wèn)道這個(gè)有星環(huán)的行星可能是太陽(yáng)系里的哪個(gè)，分別是venus, earth, mars, Saturn，所以是saturn。

第五篇是最難的，是關(guān)于生物細(xì)菌繁殖的。但是是多實(shí)驗(yàn)，每個(gè)實(shí)驗(yàn)有五個(gè)patch。變量很多，不容易找到對(duì)的答案。另一個(gè)常識(shí)題出現(xiàn)在第五篇，問(wèn)的就是它是紅細(xì)胞還是白細(xì)胞，所以答案是白細(xì)胞，因?yàn)榘准?xì)胞是有吞噬細(xì)菌的用處。第六篇是斜坡頂上有彈簧，一個(gè)cart被彈下去了，主要講的是動(dòng)量。