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aprilsnail一只蜗牛 11/11/2009 zz Global Darwin: Revolutionary roadOpinionNature 462, 162-163 (12 November 2009) | doi:10.1038/462162a; Published online 11 November 2009 Global Darwin: Revolutionary roadJames Pusey1 Top of page AbstractIn China, under the threat of Western imperialism, interpretations of Darwin's ideas paved the way for Marx, Lenin and Mao, argues James Pusey in the third in our series on reactions to evolutionary theory. Charles Darwin's banner was first unfurled in China during the Reform Movement of 1895–98, in response to China's defeat in the Sino–Japanese War. This had been the most crushing moment in what the Chinese call their century of humiliation, during which the Manchu Qing Dynasty barely survived five great rebellions, and lost four wars against foreign imperialists: Britain, Britain and France, France, and — most galling of all — Japan. This last defeat was the most frightening, not because the Chinese feared 'puny Japan', as they often called it, but because they feared that the European powers, emboldened by this demonstration of weakness, would "carve up the Chinese melon" into colonies. The watchword of the reform movement was 'bianfa', meaning 'change our institutions'. But the very word 'change' was anathema to the conservative officialdom of China. So reformers turned to Darwin as a foreign authority on change, presenting him not first and foremost as a natural scientist who had discovered an amazing fact of life, but as a political scientist who had discovered a cosmic imperative for change. Meanwhile, the Europeans waved Darwin's banner to justify imperialism. Dubbing themselves 'the fit', they declared their right to rule the 'unfit'. And some Chinese accepted this argument. Liang Qichao, one of the leading reformers, said in 1898: "If a country can strengthen itself and make itself one of the fittest, then, even if it annihilates the unfit and the weak, it can still not be said to be immoral. Why? Because it is a law of evolution." The reformers had to find hope in On the Origin of Species. And they did, but their most optimistic interpretations were based on a handful of mistranslations, themselves based on a series of misunderstandings. (Westerners leapt to these misunderstandings as well — without the benefit of mistranslations.) Chinese readings of Darwin inspired two groups — reformers and revolutionaries — to attempt to change their society through different means. Ultimately, after the failure of both groups and an erosion of traditional philosophies, Chinese Darwinian thinking prepared the nation for the rhetoric of Karl Marx, Vladimir Ilyich Lenin, and Mao Zedong.
The man who introduced Darwinian evolution to the reformers of 1895 was Yan Fu. Yan had graduated from the naval academy at Fuzhou, and was sent to England in 1877 for further study of the naval arts, which patriots hoped would one day help drive European imperialists out of the China Sea. But in England, Yan discovered political philosophy, which he came to think of as the true secret of Britain's 'fitness'. He returned to China in 1879 with a bundle of books, by Adam Smith, John Stuart Mill, Darwin and others, that he thought could rescue China from extinction. He meant to translate them, but did not publish anything for about 15 years, when goaded into action by the insult and injury of the war with Japan. In 1895 Yan published his first essay, Whence Strength?, soon followed by a brilliant, periphrastic translation of Thomas Huxley's Evolution and Ethics, which Yan wrote in such elegant classical Chinese that even conservatives respected the text. The Origin itself was too long and too difficult for Yan to tackle. But Yan's translations were enough to introduce to China the basic ideas of evolution and, more importantly, the handful of Darwinian slogans that were taken up by social Darwinists around the world.  G. LAM Subtle errors of translation, however, went with them: "natural selection" came out as "natural elimination"; the "survival of the fittest" became the "superior survive and the inferior are defeated"; and, causing the most confusion of all, "evolution" became jinhua lun, "the theory of progressive change". Strictly speaking, Darwin did not prove that evolution led to progress; to this day, that mistranslation makes it hard to discuss evolution in Chinese. As Confucius said: "If terms are not correct, discourse is difficult." Just before Darwin's ideas reached China, the scholar and bureaucrat Kang Youwei argued that Confucius had delineated three stages of world progress: chaos, ascending peace and great peace. A mixture of these ideas soon spawned a plethora of 'stage theories' of history, all of which claimed to outline the natural and inevitable development of all 'fit races'. This seemingly benign idea — that cosmic forces or natural laws were perfecting mankind and human society — eventually led to racist or class philosophies that killed people. Natural lawAt the start of the reform movement, the promise of Darwinian progress (which was not really Darwinian) seemed to hold the key to China's salvation. China was in the monarchy stage and should hence move on to the constitutional monarchy stage. The fittest nation on Earth, Great Britain, had shown the way. Yan wanted democracy for China — even anarchic democracy, without presidential rule. In Whence Strength? his call for reform was revolutionary: "Establish a parliament at the capital and let each province and county elect its own officials." But 'Darwin' held him back from real revolution. Yan believed that step-by-step progress was a fixed natural law, so stages had to be taken in order. America had skipped constitutional monarchy and gone straight to democracy, but a resulting class war, he felt, would be their undoing. "Should we, then, now throw away all loyalty to our ruler?" he asked in his essay. "We most certainly should not! Because the time has not arrived. ... Our people are not yet ready to rule themselves." (An argument that Chinese governments have used ever since to postpone democracy.) Sun Yat-sen, later dubiously dubbed the father or George Washington of his country, was also a professed Darwinian, and an advocate of democracy. But Sun was as convinced that Darwinism was for revolution as Yan, Kang and Liang were convinced that it was for reform. One of Sun's followers, Zou Rong, put it most succinctly: "Revolution is a law of Evolution." Taking advantage of the war against Japan, Sun and his would-be revolutionaries put their philosophy into action in 1895, hiring an 'army' from a secret society in Hong Kong in an attempt to capture the city of Guangzhou and trigger a revolution. It was an almost farcical failure. They arrived in Guangzhou by ferry, but their weapons were on the wrong boat, leaving them unarmed for their grand revolution. The police easily quashed them, although Sun managed to escape, eventually to Japan. A few years later, the reformers had only a little more luck. They won the ear of the young Guangxu Emperor and established a constitutional monarchy — on paper — in the summer of 1898. But the Emperor's aunt, the Empress Dowager, crushed the reform movement, beheaded the six leaders she could catch and put the Emperor under lifelong house arrest. Yan was somehow left alone. Others, led by Kang and Liang, took refuge in Japan. The two self-professed Darwinian camps had much in common. Both believed in stage theories of history. Both were for democracy — but not yet. Confucian philosophy led them to believe that the fit were those who made themselves fit, and Daoist thinking made it easy to believe in a natural path that the fit could follow to survive. Both believed, at once, in determinism and 'determinationism' — a potent if illogical mix that at once met impatient patriots' demand for action and promised victory. Sadly, both camps also accepted the pervasive Western view that Darwin had proven races unequal — that one race was 'fitter' and therefore better than another. The reformers had originally done so to disassociate themselves from those who had fallen prey to the imperialists, such as the Africans and Indians. But in their exile in Japan, reformers and revolutionaries alike turned angrily on the Manchus as scapegoats, labelling them evolutionary low life, whose 'unnatural' conquest of the Han Chinese was responsible for China's peril. There were also crucial differences between the camps. The reformers, despite everything, remained loyal to the Guangxu Emperor. They were convinced that the stage of constitutional monarchy could not be skipped, and they were against civil war. The revolutionaries believed that the Qing dynasty needed to be overthrown, that China could 'lie deng' (leap over stages) to catch up to the West and that civil war was an indispensable precondition of China's evolution or progress. For a decade the two groups debated the reform or revolution question in Chinese journals smuggled back to China from Japan — with both sides wildly waving Darwin's banner. Enter the MarxistsIn the end, the debate between reformers and revolutionaries was settled by a nearly accidental success. On a truly dark and stormy night in October 1911, Sun's followers pulled off an uprising in Wuchang. The dynasty soon fell, with Yuan Shikai, the leading 'loyalist' general, bought off with a gift of the presidency. But Yuan killed the Republic by trying to crown himself Emperor. Yuan's generals baulked. Yuan died. China fell to pieces, ruled by warlords. The debate over reform and revolution revived. Eventually the New Culture Movement arose, with Darwinian reruns, as reformers gave up on politics, embracing instead cultural reform — until 1919, when the Western powers betrayed China when they signed the Treaty of Versailles at the end of the First World War, granting Germany's 'possessions' in China to Japan. In all of this, "politics", as Mao would later say, were "in command". Few Chinese seemed shocked by the fact of evolution, or indeed overly interested in it. Unlike Europeans, few perceived, at first, any threat to their traditional philosophies or religions. But in the decade that followed the failure of the Reform Movement, Chinese philosophies — Confucianism, Daoism and Buddhism — did come under attack, as pacifistic doctrines that were unfit because they had rendered China unfit to survive. And so, both philosophically and politically, reformers and revolutionaries together created a naturally abhorrent vacuum. Many tried to fill it: Sun, Jiang Jieshi (Chiang Kaishek) and, finally, the small group of intellectuals who, in indignation at the betrayal at Versailles, found in Marxism what seemed to them the fittest faith on Earth to help China to survive. This was not, of course, all Darwin's doing, but Darwin was involved in it all. To believe in Marxism, one had to believe in inexorable forces pushing mankind, or at least the elect, to inevitable progress, through set stages (which could, however, be skipped). One had to believe that history was a violent, hereditary class struggle (almost a 'racial' struggle); that the individual must be severely subordinated to the group; that an enlightened group must lead the people for their own good; that the people must not be humane to their enemies; that the forces of history assured victory to those who were right and who struggled. Who taught Chinese these things? Marx? Mao? No. Darwin. FURTHER READING Schwartz, B. I. In Search of Wealth and Power — Yen Fu and the West (Harvard Univ. Press, 1964). For more on Darwin see http://www.nature.com/darwin
10/28/2009 zz Stitching science togetherOpinionNature 461, 881 (15 October 2009) | doi:10.1038/461881a; Published online 14 October 2009 Stitching science togetherCameron Neylon1 Top of page
AbstractGoogle Wave is the kind of open-source online collaboration tool that should drive scientists to wire their research and publications into an interactive data web, says Cameron Neylon. 
ILLUSTRATION BY M. HODSON Science communication today remains firmly wedded to its print origins. We cling to the notion that 'the real version' exists on the page. Beyond ease of delivery, we take very little advantage of the potential of the World Wide Web to transform the way we store and transfer knowledge. We rarely take the opportunity to update material with new data, or to provide a record of how a document or data set has changed. Gene names and protein structures should be routinely linked to database entries through hyperlinks. The outputs of computational processes should be connected to their inputs, so analyses can be redone. If we can make these records accessible to humans and readable by machines, then whole new types of analysis will become possible, indeed standard. Many of these things are possible today. But they are hard to achieve. Much effort has gone into solving parts of the problem, by big players such as Microsoft and Amazon as well as by smaller organizations. Electronic lab notebooks can help to capture the details of science, and databases can make it available to the user. Reference-management tools such as Delicious, semantic data stores and Wikipedia can help to wire up and monitor knowledge. But the tools are often difficult to use and don't 'talk' to each other. There is no single framework that makes it easy to link all the steps of science. Scientists do their analysis and writing using different software, and prepare graphs and record data using different tools. Very few companies worldwide have both the expertise and resources to take on the task of stitching this together. So it is with great interest that I have watched Google develop its product, Google Wave. The company describes Google Wave as "what e-mail would look like if it were invented today". It blends elements of e-mail with instant messaging and online collaborative authoring. The big change is that the 'document' or 'wave' is shared between all the participants and updates flow in real time. You no longer need to worry about which version of a document you have e-mailed around. This is helpful for scientists, but not revolutionary. Where Wave offers a big step for science is in two other functionalities. Two steps forwardFirst, Wave introduces the idea of robots: automated agents that can be invited into a document. Robots could look through your paper checking for Protein Data Bank codes or gene names, for example, and putting in links to the databases. A robot might represent a lab instrument, adding data automatically to your laboratory record when they become available. You can easily add maps, video or three-dimensional graphics to your work using 'gadgets' or 'applications', familiar from services such as iGoogle and Facebook. Robots can interact with this information, making it possible to have a dashboard in your inbox to monitor and control instruments in the lab. The second step forward is using versions. Each wave maintains a record of every change. It could be possible to check each step from data collection to drawing a graph and its publication. This would allow a reader to step through an analysis to see where conclusions have come from, and would make detecting fraud — or honest mistakes — much easier. Google has done a good thing in making the protocol and programming tools open source, enabling people to test and build. Perhaps 50 people, myself included, from experimental scientists to journal publishers, have been testing the prototype system for science applications since June, building robots that link chemical information, visualize data and format references. Since 30 September, a much bigger group has been testing. But real benefits will come only if the system is widely adopted. Perhaps a new generation of scientists will be required to exploit the power that working with these dynamic documents and tools offers. Solving the current problems in science communication requires the intervention of strong companies such as Google. But it will take more than technical advances to provoke scientists into taking full advantage of the web. We need pressure, and perhaps compulsion, from journals and funders to raise publishing standards to the new level made possible by such tools. Google Wave may not be, indeed is probably not, the whole answer. But it points the way to tools that build records and reproducibility into every step. And that has to be good for science.
10/16/2009 zz China's unofficial democracyBooks and ArtsNature 461, 731 (8 October 2009) | doi:10.1038/461731a; Published online 7 October 2009 China's unofficial democracyLi Gong1 BOOK REVIEWED-The Power of the Internet in China: Citizen Activism Onlineby Guobin Yang Columbia University Press: 2009. 320 pp. $29.50, £20.50  JIANAN YU/REUTERS/CORBIS China's online community has found its own voice. In July this year, a 20-year-old university student in the southern Chinese city of Hangzhou was sentenced to three years in prison for driving recklessly and killing a pedestrian. This would have been a sad but unremarkable case, except that it was only brought following a huge national outcry. Reports that local police initially protected the student, whose family was well connected, were spread over the Internet and eventually forced the police to respond. Similar examples of online citizen activism occur every day. The Power of the Internet in China analyses how the Internet's rapid development in China has given its citizens a mechanism to air and share individual opinions that may differ from official positions, to connect and organize often against the will of the authorities, and to improve their own lives directly and visibly. The Internet allows Chinese citizens to practise, as cultural critic Raymond Williams termed it, "unofficial democracy". In researching the book, Guobin Yang, a professor at Columbia University who grew up in China, read Chinese material first-hand, observed and participated in online forums and interacted with Chinese citizens online. The book's 70 case studies range from patients with diabetes or hepatitis B fighting against governmental employment discrimination, to Internet-organized worldwide demonstrations in response to the 1998 Indonesian atrocities towards the local ethnic Chinese population, to massive online and offline protests over news reporting by Western media in the run-up to the 2008 Beijing Olympics. Yang's recounting of notable events along the historical path to China's online activism brought back old memories of my own. The first electronic gathering place targeted at people interested in China — the USENET newsgroup soc.culture.china — was started soon after I left Beijing for Cambridge, UK, in late 1987. I quickly became an active participant, devoting entire mornings to reading and replying to postings. As a student, I helped edit China News Digest, the first China-themed English-language electronic newsletter, which was published free by e-mail. The milestone event for the citizens' Internet inside China was the founding in 1995 of the Tsinghua Bulletin Board System (BBS), which was started by students at the computer-science department of Tsinghua University, where I was an undergraduate. Even today, with the prevalence of text messaging, blogs, YouTube and Twitter, the BBS continues to be a widely used online platform in China, and its underlying technology has progressed from dial-up connections to broadband networks. Although filled with vivid anecdotes, this book is an academic publication. Its storytelling is punctuated by jargon and scholarly narratives, including numerous academic references. Nonetheless, it is a valuable information resource. Yang's analysis covers a broad canvas and includes many statistics. The investigation into the business side of online activism will particularly fascinate many readers. Online viewings surely translate into money, and manufactured online contention generates lots of viewings. Some businesses, including art dealers, present items as 'banned in China' to promote their wares. Also a reality are competitive tactics, such as the '50 cents party' — people who are paid 50 cents an item for posting prescribed messages at online forums. Governmental control of content is the elephant in the room. The mechanisms for restricting content flow into China and for controlling domestic Internet content — down to a single book entry on Amazon, for example — have become sophisticated in recent years. This is aided by the fact that only a few state-owned access points connect the domestic Internet to the outside world. Chinese 'netizens' counter these constraints with ingenuity, such as using Internet proxies to bypass state firewalls, or posting opinions in unrelated forums to postpone detection. The Chinese habit of reposting — in which a user copies an article in its entirety to a new forum, rather than linking to the original posting — makes the job of eradicating an erratic blog much harder. Sixteen years ago this month, media magnate Rupert Murdoch declared that "advances in the technology of telecommunications have proved an unambiguous threat to totalitarian regimes everywhere". Last year, China overtook the United States as the country with the largest online population. In the time between, Yang's book documents how China's netizens have stumbled on online activism as a response to, among other things, a flawed justice system. Time will tell whether the revolution in communication technologies will lead to a new cultural or social revolution.
9/15/2009 zz China Fights Against Statistical Corruption
LettersChina Fights Against Statistical CorruptionParticularly in the current financial crisis, many countries rely on statistics released by the Chinese government for production and trade of bulk commodities, exchange rates, and economic stimulus. However, the credibility of China's statistics has long been questioned. On 1 May, a new regulation, Rules on Punishment for Violation of Laws in Statistics, was put in effect by the Ministry of Supervision, Ministry of Human Resources and Social Security, and the National Bureau of Statistics (1).Statistical corruption has been found in China for years, largely for two reasons. First, economic growth is a key factor determining the promotion of government officials. Statistical data and numbers are regarded as a reflection of economic growth, which is used to evaluate the performance of the officials. This is the so-called "numbers make leaders" phenomenon ("shu zi chu guan" in Chinese). Second, the statistical organizations are not independent entities in China. They are a part of the government and hence are vulnerable to government interference. Without specific laws and regulations to punish statistical corruption, government leaders can intervene in statistical reporting with low political risks. They may tailor statistics for different purposes, such as inflating statistical numbers that indicate economic achievements and decreasing statistical numbers for environmental pollution and damage (2). This is the so-called "leaders make numbers" phenomenon ("guan chu shu zi" in Chinese). The previous Statistics Law in China has been in effect since 1983, but it was too vague to enforce. Although it stated the penalty for illegal acts, the law did not clearly specify the types of the illegal acts and the extent to which penalties should be imposed. In contrast, the new regulation lists four types of statistics cheating: revising statistics without permission, or making up statistics; forcing or ordering statistics departments or individuals to revise or make up statistics or refuse to report statistics; retaliation against individuals who refuse to issue false statistics; and retaliation against individuals who report statistics violations (3). The degree of punishment depends on consequences of the violations, and the punishments include a warning, recording a demerit, or even removing officials from their positions. The new regulation is an important step in the fight against statistical corruption in China. Nevertheless, to eradicate illegal acts in statistical work, further actions are needed, such as reform of the evaluation system for officials and the establishment of independent statistical organizations. Without progress in these areas, the goal of an 8% GDP growth rate for 2009 announced by the Chinese government could be merely another number created by leaders. Junguo Liu1,* and Hong Yang2 * To whom correspondence should be addressed. E-mail: water21water@yahoo.com
1 School of Nature Conservation, Beijing Forestry University, Beijing, 100083, China.
References
9/3/2009 zz Internet addiction center opens in USInternet addiction center opens in US AP – This photo taken Sept. 1, 2009 shows reSTART Internet Addiction Recovery Program client Ben Alexander … By NICHOLAS K. GERANIOS, Associated Press Writer Nicholas K. Geranios, Associated Press Writer – 22 mins ago
FALL CITY, Wash. – Ben Alexander spent nearly every waking minute playing the video game "World of Warcraft." As a result, he flunked out of the University of Iowa. Alexander, 19, needed help to break an addiction he calls as destructive as alcohol or drugs. He found it in this suburb of high-tech Seattle, where what claims to be the first residential treatment center for Internet addiction in the United States just opened its doors. The center, called ReSTART, is somewhat ironically located near Redmond, headquarters of Microsoft and a world center of the computer industry. It opened in July and for $14,000 offers a 45-day program intended to help people wean themselves from pathological computer use, which can include obsessive use of video games, texting, Facebook, eBay, Twitter and any other time-killers brought courtesy of technology. "We've been doing this for years on an outpatient basis," said Hilarie Cash, a therapist and executive director of the center. "Up until now, we had no place to send them." Internet addiction is not recognized as a separate disorder by the American Psychiatric Association, and treatment is not generally covered by insurance. But there are many such treatment centers in China, South Korea and Taiwan — where Internet addiction is taken very seriously — and many psychiatric experts say it is clear that Internet addiction is real and harmful. The five-acre center in Fall City, about 30 miles east of Seattle, can handle up to six patients at a time. Alexander is so far the only patient of the program, which uses a cold turkey approach. He spends his days in counseling and psychotherapy sessions, doing household chores, working on the grounds, going on outings, exercising and baking a mean batch of ginger cookies. Whether such programs work in the long run remains to be seen. For one thing, the Internet is so pervasive that it can be nearly impossible to resist, akin to placing an alcoholic in a bar, Cash said. The effects of addiction are no joke. They range from loss of a job or marriage to car accidents for those who can't stop texting while driving. Some people have died after playing video games for days without a break, generally stemming from a blood clot associated with being sedentary. Psychotherapist Cosette Dawna Rae has owned the bucolic retreat center since 1994, and was searching for a new use for it when she hooked up with Cash. They decided to avoid treating people addicted to Internet sex, in part because she lives in the center with her family. According to Dr. Kimberly Young of the Center for Internet Addiction Recovery in Bradford, Pa., addiction warning signs are being preoccupied with thoughts of the Internet; using it longer than intended, and for increasing amounts of time; repeatedly making unsuccessful efforts to control use; jeopardizing relationships, school or work to spend time online; lying to cover the extent of Internet use; using the Internet to escape problems or feelings of depression; physical changes to weight, headaches or carpal tunnel syndrome. Exactly how to respond is being debated. For instance, Internet addiction can be a symptom of other mental illness, such as depression, or conditions like autism, experts say. "From what we know, many so-called `Internet addicts' are folks who have severe depression, anxiety disorders, or social phobic symptoms that make it hard for them to live a full, balanced life and deal face-to-face with other people," said Dr. Ronald Pies, professor of psychiatry at SUNY Upstate Medical University in Syracuse, N.Y. "It may be that unless we treat their underlying problems, some new form of `addiction' will pop up down the line," Pies said. There is debate about whether to include Internet addiction as a separate illness in the next edition of the "Diagnostic and Statistical Manual of Mental Disorders," due in 2012, which determines which mental illnesses get covered by insurance. Pies and Dr. Jerald Block, of Oregon Health Sciences University in Portland, said there is not enough research yet to justify that. "Among psychiatrists there is general recognition that many patients have difficulty controlling their impulses to chat online, or play computer games or watch porn," Block said. "The debate is how to classify that." Cash, co-author of the book "Video Games & Your Kids," first started dealing with Internet addiction in 1994, with a patient who was so consumed by video games that he had lost his marriage and two jobs. Internet addicts miss out on real conversations and real human development, often see their hygiene, their home and relationships deteriorate, don't eat or sleep properly and don't get enough exercise, Rae said. Alexander is a tall, quiet young man who always got good grades and hopes to become a biologist. He started playing "World of Warcraft," a hugely popular online multiplayer role playing game, about a year ago, and got sucked right in. "At first it was a couple of hours a day," he said. "By midway through the first semester, I was playing 16 or 17 hours a day. "School wasn't interesting," he said. "It was an easy way to socialize and meet people." It was also an easy way to flunk out. Alexander dropped out in the second semester and went to a traditional substance abuse program, which was not a good fit. He graduated from a 10-week outdoors-based program in southern Utah, but felt he still had little control over his gaming. So he sought out a specialized program and arrived in Fall City in July. He thinks it was a good choice. "I don't think I'll go back to `World of Warcraft' anytime soon," Alexander said. 9/1/2009 zz Strategic Reading, Ontologies, and the Future of Scientific Publishing -- for BiaoGe again
ReviewStrategic Reading, Ontologies, and the Future of Scientific PublishingAllen H. Renear* and Carole L. Palmer
The revolution in scientific publishing that has been promised since the 1980s is about to take place. Scientists have always read strategically, working with many articles simultaneously to search, filter, scan, link, annotate, and analyze fragments of content. An observed recent increase in strategic reading in the online environment will soon be further intensified by two current trends: (i) the widespread use of digital indexing, retrieval, and navigation resources and (ii) the emergence within many scientific disciplines of interoperable ontologies. Accelerated and enhanced by reading tools that take advantage of ontologies, reading practices will become even more rapid and indirect, transforming the ways in which scientists engage the literature and shaping the evolution of scientific publishing.
Center for Informatics Research in Science and Scholarship, Graduate
School of Library and Information Science, University of Illinois at
Urbana-Champaign, Champaign, IL 61820, USA.
* To whom correspondence should be addressed. E-mail: renear@illinois.edu The 1980s abounded in descriptions of a coming new world of scholarly communication, predicting functionality that we knew was possible and would soon be technologically feasible. This imagined world, which was never fully realized, predicted advanced navigation; discipline-specific intelligent tools for searching, browsing, and analysis; reader-initiated hypertext linking; "live" data-driven diagrams; computationally available information objects; searchable indexed annotations; thorough-going interoperability; and so on. Substantial improvements in hardware and software and an infrastructure of networked communications now make this anticipated functionality possible. Lying at the heart of the changes taking place is an escalation of strategic reading practices. Scientists have always read strategically, working with many articles simultaneously to search, filter, compare, arrange, link, annotate, and analyze fragments of content. Now, however, two important trends are interacting to support and intensify the effectiveness of these practices. The first is the wide-scale use by scientists of digital indexing, retrieval, and navigation resources (such as PubMed, Web of Science, the ACM Digital Library, NASA’s Astrophysics Data System, CiteSeer, Scopus, and Google Scholar) to exploit large quantities of relevant information without reading individual articles. The second is the emergence within many scientific disciplines of ontologies for representing and linking scientific data. This convergence of digital resources and data-linking ontologies will result in even more rapid and indirect use of the literature, supported not only by text mining (1) and literature-based discovery applications (2), but by "ontology-aware" strategic reading tools as well.
Why Will the Revolution Happen Now?
When it was launched in 1992, the Online Journal of Current Clinical Trials, jointly designed by the American Association for the Advancement of Science and the OCLC Online Computer Library Center, was seen by some as the beginning of the long-awaited world of advanced digital publishing. However, the journal failed to flourish, and the new world did not materialize. In retrospect, we can see that in the early 1990s, none of the basic conditions required for an advanced scientific publishing system existed. Not only was the basic technology and infrastructure inadequate, but the entire publishing system also would have required extensive coordinated changes. Although there was no revolution, an important transformation did take place in the 1990s. In 1993, very few scientific, technical, and medical (STM) journals had an electronic version, and yet by 2003, virtually all of them did. For the daily work routines of most scientists, that new format had already become more important than print. The system of digital publishing that emerged from 1993 to 2003 was impressive in some respects, but was still largely another case of new technology compromised by imitation of the old. The reasons a more radical change failed to occur are understandable in retrospect, and they also suggest why we are now on the cusp of a larger change. None of the developments during this period required costly or uncertain changes in workflow and production processes, software tools, user behavior, or business models. STM publishers were already creating Adobe PostScript files for print production. These could be automatically converted to the Adobe page description language format (PDF), which was suitable for distribution over the existing Internet and could be browsed with existing free software applications. Users, in turn, were presented with a printlike experience that was at once familiar and yet had additional advantages, including Internet delivery, digital storage, full-text searching, and local printing, all of which was easily realized with existing technologies. Hence, as its value became apparent, PDF-based digital STM publishing emerged relatively quickly, with few changes in production or existing infrastructure. Since 1992, processor speeds, memory, storage, and bandwidth to the desktop have undergone enormous improvements, as have connectivity and costs. Standard protocols for network communication have been adopted, new software tools and software engineering strategies have emerged, and there is now a supporting infrastructure of information professions and institutions. The pervasive use of the World Wide Web via intuitive Web browsers is an especially visible change, and the widespread use of Extensible Markup Language (XML), with its associated standards and technologies, provides a foundational framework for storing, processing, and presenting information on the Web. In addition, an important recent development is the convergence within the STM publishing community on a single XML schema for the representation of scientific articles: the National Library of Medicine (NLM)’s Journal Archiving and Interchange Tag Suite (3). The driving force for change remains the same: the growing quantity and complexity of information in combination with limited time for reading. But in some disciplines, we seem to be past the point where any further specialization of research focus or elaboration of collaborative relationships are effective (4, 5) (Fig. 1). Just as the increased quantity of information and general intensity of scientific activity is reaching the point where it cannot be sustained with current practices, technology and user behavior are making new practices feasible, and research scenarios that a decade ago were utopian are now widely anticipated by practicing scientists. P. Bourne, a Public Library of Science journal editor, offers this vision of the near future the scientific literature will seamlessly provide annotation of records in the biological databases. Imagine reading a description of an active site of a biological molecule in a paper, being able to access immediately the atomic coordinates specifically for that active site, and then using a tool to explore the intricate set of hydrogen-bonding interactions described in the paper.... Alternatively, if you are starting with the data ... viewing the chromosome location of a human single-nucleotide polymorphism associated with a neurological disorder, ... immediately access a variety of papers ranked in order of relevance to your profile ... pinpointing the reference to the single-nucleotide polymorphism in the full-text article (6), p. 179.
This sort of information gathering goes well beyond conventional digital publishing and reveals why the current state of affairs has failed to meet some expectations. As chemists P. Murray-Rust and H. S. Rzepa remarked in 2004, "The current transition to [PDF-based] e-journals seems to be welcomed by many—but not us ... a cultural change in our approach to information is needed" (7).
How Are Scientists Working with the Literature?
Scientists have always strived to avoid unnecessary reading. Like all researchers, they use indexing and citations as indicators of relevance, abstracts and literature reviews as surrogates for full papers, and social networks of colleagues and graduate students as personal alerting services. The aim is to move rapidly through the literature to assess and exploit content with as little actual reading as possible. As indexing, recommending, and navigation has become more sophisticated in the online environment, these strategic reading practices have intensified. Now, as scientists search and browse, they are making queries and selecting information in much tighter iterations and with many different kinds of objectives in mind, almost as if they were playing a fast-paced video game. They sweep through resources, changing search strings, chaining references backward and citations forward, dodging integrator and publisher sites to find open-access copies, continually working to reduce the number of clicks required for access. By note-taking or cutting and pasting, scientists often extract and accumulate bits of specific information, such as findings, equations, protocols, and data. In this process, rapid judgments are made—such as assessments of relevance, impact, and quality—while search queries are being formulated and refined. (Fig. 3). The goal often seems to be undifferentiated assimilation of information about a domain or a problem at hand, and the online experience may be highly valuable, even though no clear aim is met and no articles to read are located. In a compelling analogy, Nicholas et al. (8) describe a "slightly irritated" father watching his young daughter flick from channel to channel while watching television [the] father asks ... why she cannot make up her mind and she answers that she is not attempting to make up her mind but is watching all the channels. ... gathering information horizontally, not vertically (8), p. 40. And they conclude Now we see what the migration from traditional to electronic sources has meant in information seeking terms. We are all bouncers and flickers, and the success of Google is a testament to that, with its marvelous ability to enhance and amplify this flicking and bouncing (like a really good remote).... In the past, information seeking was seen to be the first step to creating knowledge. Now ... it is a continuous process (8), pp. 41–42.
Just as the aim of channel surfing is not to find a program to watch, the goal of literature surfing, is not to find an article to read, but rather to find, assess, and exploit a range of information by scanning portions of many articles. This behavior is common among scientists (9). Longitudinal studies of e-journal use confirm that scientists are indeed "reading" more papers at a faster pace (10). That is, the total time spent reading journal articles has risen only a little, whereas the number of journal articles read per year has gone up much faster and appears to be growing still. The number of articles read (as distinguished from those merely browsed) by scientists was ~50% higher in 2005 than in the mid-1990s. Furthermore, though the average reading time per article did not change much from 1977 to the mid-1990s (48 versus 47 min), it started falling in the mid-1990s and is now just over 30 min per article (Fig. 2). At the same time, identifying papers by searching online increased more than fourfold between 1977 and 2005. These changes in journal use are far greater in STM disciplines than the averages over all disciplines, suggesting that as work with the literature has moved online, scientists are scanning more and reading less. Early digital library research also showed how scientists scan individual printed journal articles to identify key components—such as tables of contents, references, figures, formatted lists, equations, and scientific names—for quick review and absorption of information (11, 12). More recent studies of the research process have emphasized the varied ways in which scientists work with information (13, 14). The literature is scanned not only to position new findings in cognate fields and learn about collaborators’ domains, but also to monitor the progress of peers and competitors. Information is collated to compare measurement and instrumentation details; it is also used to compile personal collections in evolving areas of interest and to extract the facts and evidence needed to build databases. These are all aspects of strategic reading, a robust, well-entrenched behavior that is vastly more efficient in the digital realm and is thus a promising target for digital support.
How Is Scientific Information Being Represented?
Structured terminologies for representing scientific data, along with standard XML-based techniques for defining and using these terminologies, are forming the basis for new types of scientific publishing. Although computer-processible scientific terminologies range from simple standardized vocabularies to sophisticated formal systems with logical axioms, we have called all of them ontologies. Ontologies are particularly prominent in the biological sciences (15, 16). One example of rapid adoption is the Gene Ontology (GO) (17), which started in 1998 to support the annotation of genes and gene products and is now very widely used, containing more than 25,000 terms and 3.3 million annotations. Although many biological ontologies were originally developed independently, the need for interoperability has driven collaboration, a good example being the Open Biomedical Ontologies (OBO), which currently has 54 participating projects (18), including Microarray Gene Expression Data (MGED), BioPAX, for biological pathways data, and Foundational Model of Anatomy (FMA). Although the size, complexity, and logical design of scientific ontologies may vary, a partial description of GO, drawing on examples from the GO introductory material, will illustrate some of their general features (19, 20). GO consists of three separate ontologies: (i) molecular function, (ii) biological process, and (iii) cellular component. Within each of these, terms are uniquely identified, defined, and related in a network of "is a" relationships (e.g., a nuclear chromosome is a chromosome). GO also contains the relationship "part of" (e.g., periplasmic flagellum is part of periplasmic space), and recently, the relationship "regulates" and subtype relationships "positively regulates" and "negatively regulates" were added. These relationships have logical features; for instance, "is a" and "part of" are transitive (e.g., if X is part of Y and Y is part of Z, then X is part of Z). It is easy to see not only how the controlled vocabulary of a shared ontology can facilitate the integration of data from multiple sources, but also how relationships such as "is a", "part of", and "regulates" can support other information management tasks as well, including information retrieval and text mining, error checking, and automated inferencing. Neither controlled vocabularies nor even logic-based ontologies are entirely new, although the enormous increase in the amount and complexity of biological data makes such organizational strategies increasingly urgent. Now, however, we can make ontologies and their applications computationally available and interoperable through well-supported standards associated with the Internet and World Wide Web. In 1998, as work began on GO, the World Wide Web Consortium (W3C) released XML (21), a metalanguage for defining markup languages (22) for representing information on the World Wide Web. Originally designed for document-oriented languages, XML was soon used for other kinds of information as well. XML languages are defined by a computer-readable schema, which specifies, among other things, the terms of the markup language and the ways those terms can be arranged in valid documents. XML organizes information as a hierarchical structure (an "ordered tree") of labeled nodes and attribute/value pairs and represents that structure in a linear format readable by both humans and computers. Software can read data in this format and construct the correct tree structure, even without the schema that defines the language (this is a virtue of XML). If a schema is available, additional processing is possible, such as verifying that the data are complete and correctly organized; a schema can also configure editing tools so that human coders are only offered legal coding options, making coding easier and syntax errors impossible. In just 10 years, XML and related supporting software and standards have come to dominate information representation in networked environments—all popular Web browsers support XML, and most major database systems import and export XML-formatted data. Although using XML to declare and apply a terminological vocabulary improves interoperability and access to software applications, it does have some limitations. XML schemas specify syntax, not semantics (23). An XML schema does not itself indicate how to interpret portions of a particular XML tree structure in terms of scientific assertions, nor is it, alone, suitable for defining logical relationships among terms. That information must be recorded in the natural language documentation for the schema, but then it is unavailable for computer processing. To address this problem, the semantic Web languages Resource Description Framework (RDF), Resource Description Framework Schema (RDFS), Web Ontology Language (OWL), and Semantic Web Rule Language (SWRL) were developed (24). These are computer-processible knowledge representation languages that provide a standard technique for defining ontologies and expressing assertions that use terms from those ontologies. Although technically independent of any particular computer-encoding format, RDFS and OWL each have a standard XML syntax that is now well-supported by software applications and widely used for ontology representation. Today, an emerging infrastructure of education, research, conferences, organizations, and software tools is sustaining the development and adoption of scientific ontologies and providing opportunities for coordination to improve interoperability and share best practices. Particularly important for biology are the National Center for Biomedical Ontology, OBO, and the International Society for Biocuration, as well as more broadly defined organizations such as the National Center for Biotechnology Information and the European Bioinformatics Institute. One notable software application for ontology development is the widely used and well-supported Protégé ontology editor.
How Can Ontologies Help Scientific Publishing?
Originally motivated by the need for data integration, scientific ontologies are now being explored for STM publishing to support information retrieval and text mining, with applications for hypothesis generation and knowledge discovery well underway. Nevertheless, reading-like engagement with scientific articles is not likely to disappear entirely: The natural language prose of scientific articles provides too much valuable nuance and context to be treated only as data (25). Scientists may have moved well beyond traditional reading, but they still remain engaged with the narrative of scientific articles and need tools to help them read, and not only mine, that narrative. The integration of ontologies into the scientific literature has been recommended by leading scientists (26–28), and the current generation of ontology-based text mining and retrieval tools in the biomedical sciences is already taking advantage of natural language processing and databases of annotations (5, 29, 30). One example is Textpresso, an ontology-based mining and retrieval system that works with prepared collections of articles, split into sentences and annotated with terms from 33 ontology categories, three of which correspond to the GO ontologies (31). Results screens present a ranked list of sentences within a ranked list of articles, with term highlighting, and links to articles and external databases (Fig. 4, top). Reading the sentences of an article in relevance order rather than narrative order is an example of strategic reading within an article. An example of strategic reading across a collection is provided by Information Hyperlinked over Proteins (iHOP), which uses genes and proteins to create a network of sentences and abstracts for searching and navigating MEDLINE abstracts (32). The iHOP database processes abstract sentences using National Center for Biotechnology Information taxonomy identifiers and the Medical Subject Headings (MeSH) thesaurus and supplies pages of configurable results, in ranked lists of sentences retrieved from many abstracts (Fig. 4, bottom).
Unlike similar explorations in the 1980s and 1990s, these are not computer science experiments or pilot projects requiring substantial investment and large upfront changes in infrastructure and practices to scale them up for general use. These are projects that are already producing practical and widely used tools.
How Do We Support and Shape These Changes?
The infrastructures and services to support strategic reading practices will no doubt be promoted by open access and alternative publishing models, which are already being widely discussed in the academic community. However, research on information behavior and the use of ontologies is also needed. Traditional approaches to evaluating information systems, such as precision, recall, and satisfaction measures, offer limited guidance for further development of strategic reading technologies. Finer-grained methods that analyze what scientists actually do and value are required if we want to understand the nearly subconscious tactics that govern second-by-second interactions with the literature and the nuances of intention and use. We know, for instance, that scientists often have trouble locating very problem-specific information (on methods and protocols, for instance) and that the occasional exploration of results from another discipline can have considerable impact on progress or the direction of research. These are the kinds of information behaviors that we need to understand more fully to design tools that go beyond search and retrieval to support creative strategic reading. For ontology-aware reading tools to function well, terminological annotations must be included in, or mapped to, the XML encoding of articles during the publishing production process, to connect names and phrases in narrative text with appropriate standard terminology. The emergence of the NLM schema as a standard XML encoding for scientific articles provides a promising shared context for terminological annotation; however, we also need specific strategies that are economically sustainable within the current context of STM publishing workflows, as well as remedies for "legacy data," the articles already published and stored in repositories. To exploit terminological annotations across the Internet, reading tools will have to operate in real time to take advantage of the ontologies that define and relate terms and connect terms with relevant databases with the use of "service-oriented architectures" (33). Finally, the development of ontology languages with additional expressive power is needed, as well as continued support for evolving, coordinating, and harmonizing ontologies.
How Will Scientists Work with the Literature in 2019?
Scientists will still read narrative prose, even as text mining and automated processing become common; however, these reading practices will become increasingly strategic, supported by enhanced literature and ontology-aware tools. As part of the publishing workflow, scientific terminology will be indexed routinely against rich ontologies. More importantly, formalized assertions, perhaps maintained in specialized "structured abstracts" (27), will provide indexing and browsing tools with computational access to causal and ontological relationships. Hypertext linking will be extensive, generated both automatically and by readers providing commentary on blogs and through shared annotation databases. At the same time, more tools for enhanced searching, scanning, and analyzing will appear and exploit the increasingly rich layer of indexing, linking, and annotation information. There are no technical obstacles to this trajectory, and it is already under way. The changes, as always, will be incremental: Scientists, who today already make extensive use of existing indexing and retrieval services, will encounter a steady stream of new enhancements and adopt those that allow rapid and productive engagement with the literature. The new functionality will sometimes be provided as part of the application interface (new features in PubMed, for instance) or as shared external tools that users can add to their Web browsers. These developments chart a middle course between the already obsolete activity of finding an article to read on the one hand, and the narrower objectives of text mining on the other, responding directly to the entrenched necessity and value of strategic reading in the daily work of today’s scientists.
References and Notes
8/29/2009 回国 最近好久没在这里码过中国字了，主要是因为太懒，转载比自己写容易多了，更别提是想要正经地写点什么了。耗到现在，回国一趟要是还不再冒个泡简直就是说不过去了，所以试着冒冒，然而已经是不习惯了。 从90度的北京回到70度的Toledo，身上清凉不少，脑子里也清爽多了：北京人太多了，天天出门都是乌泱乌泱的人在眼前晃，坐什么车都是人挤人，就算是打车也不过是稍微拉开人与人的间距，从紧贴着变成隔着个铁皮，照样还是在暴晒的街面上挤着动不了。唉，为什么我两年才回去一次，就先从牢骚开始呢。 回国的主要目的是看老爸老妈，主要的行动内容则是吃，然后就是说，总之一张嘴忙了20天，还是觉得没忙够，要是能再多吃点再多说点也还不会有啥怨言。从吃这个事儿就看出来咱国家是进步了，消费水平就算是合成美元也已经直追美国农村水平，我这穷学生平时肯定是不敢这么个吃法。老百姓就是琢磨点衣食住行，咱也都到了聚会话题总是固定在房子车子孩子的年龄，一个一个饭局上聊起这家长里短的琐事，让我觉得中国人民杠杠的消费热情真是红火，赶英超美四个字不过是小菜一碟罢了。 回国赶上了60年大庆前夕，那套红旗飘飘的国庆纪念明信片是个送人的好东西，据说还能盖个天安门的邮戳，估计过几天就能收到给自己的那份了。在家上网实在是不方便，google reader天天报错，从来也连不上，photo更是直接一屏的叉叉。我还非常倒霉地赶上台风刮断了中美电缆，弄得msn也上不去。当年我申请学校的时候就赶上台湾海底地震，中美email中断，这次又来了，我看下次我回国之前得先去找个庙烧注香才好。自己爬墙的技术已经荒废掉，也怕老爸在家莫名其妙爬过了墙再摔着，索性就这么与世隔绝了20天，有点到火星旅游的意思了。 另外一件回国的大事是拷电影，再次郑重感谢图有其表和我没有昵称，关于齐欣同志赞助的辎重，另有别人致谢，我就不管了。高清的就是好，别看一个片子要占4G空间，还是物有所值，昨天先拿watchman开刀，确实不错，效果不错片子也不错。 8/27/2009 zz Reshuffling Graduate Training
News FocusScience Education:Reshuffling Graduate TrainingJeffrey Mervis
Nobelist Roald Hoffmann believes that taking graduate students off grants and giving them fellowships would be good for U.S. science. But others say such a radical change isn't in the cards.
"I think science should be fun," Hoffmann said in May to the National Science Board, the oversight body for the National Science Foundation (NSF), when it awarded him its prestigious Public Service Medal. But after flashing pictures of himself at Carnival and on stage at the Cornelia Street Café in Greenwich Village, Hoffmann got down to business: "Now I want to shift gears and talk about something serious." What Hoffmann wanted to discuss is a proposal for changing how the U.S. government supports the training of graduate students in the sciences. Federal research agencies now funnel most of their money for graduate students through grants to faculty members. That's the case for nearly 90% of the 39,000 graduate students whom NSF supports each year and for about two-thirds of those getting money from the National Institutes of Health (NIH). The remaining students are funded via fellowships, awarded directly to them, or through traineeships, in which universities compete for a grant to support a certain number of students in a particular area for a fixed period of time. The commingling of education and research has created a system that is the envy of the world in terms of research productivity. It's also not a bad deal for the student, who typically doesn't pay a penny to earn her Ph.D. The university picks up the tuition for her required courses, and her research is funded through a federal grant awarded to her adviser, who then hires her to work in his lab. In return, she'll probably teach some undergraduate classes during her first few semesters, after which her adviser will receive several years of skilled labor at below-market rates. But that wildly successful system comes at a high cost to both students and the profession, says Hoffmann, who also made his case in an 8 May editorial in The Chronicle of Higher Education. And it's not sustainable, he argues, especially during tough economic times like these. A better approach, says Hoffmann, would be for the government to stop supporting graduate students on research grants—roughly 30% of a typical NSF chemistry grant pays for graduate students, for example—and use the money for competitive fellowships that students could use at the university of their choice. That seemingly minor shift could have huge consequences for universities and for the entire U.S. research enterprise. Although they admit Hoffmann's proposal faces long odds, some community leaders say that such a change is long overdue and that his suggestion offers a promising road map. "The real power of an individual fellowship is that it empowers a young scientist to act in a more independent manner, on something creative and for which they have a passion," says Thomas Cech, a Nobelist who recently returned to academia after a decade as head of the Howard Hughes Medical Institute (HHMI) in Chevy Chase, Maryland. "And that's what science is really about." Under the current system, he says, "a graduate student is told, ‘Do experiment 2a because it's in our grant.’ That turns the student into a pair of hands. So I think a shift to fellowships would be an excellent idea." Shirley Tilghman, president of Princeton University and chair of a 1998 National Academies panel that offered advice on career paths in the life sciences, says a move away from supporting graduate students on research grants would also address two other major flaws. Although the current system has succeeded in maximizing the amount of research performed, she says, it has also degraded the quality of graduate training and led to an overproduction of Ph.D.s in some areas. Unhitching training from research grants would be a much-needed form of professional "birth control," says Tilghman, who favors more federally funded traineeships. (Traineeships are grants awarded to institutions, which in turn promise to provide students with professional and career counseling as well as a chance to develop their scientific skills in specific areas.) Reducing the overall number of graduate students in the life sciences "is a price that I'd be willing to pay," she says, in return for a better training environment and improved job prospects. Fellowships already have a strong following. Building on a 2007 proposal from economist Richard Freeman of Harvard University, President Barack Obama has promised to triple by 2013 the annual number of NSF's prestigious Graduate Research Fellowships, which run for 3 years and cover all fields that NSF funds. And another newcomer to Washington, HHMI President Robert Tjian, hopes to revive a graduate fellowship program that the institute terminated in 2003 when money became tight. Tjian sees the program, which would be open to the most talented students from around the world who are studying in the United States, as an important investment in the next generation of academic researchers. However, other academic leaders worry that Hoffmann's proposal risks killing the goose that laid the golden egg. "Any radical shift away from what we do now is risky because it would jeopardize a strong innovation system," says Debra Stewart, president of the Council of Graduate Schools in Washington, D.C. Robert Berdahl, president of the Association of American Universities, also thinks that a wholesale shift to fellowships would be unwise because it would take the selection of graduate students out of the hands of investigators. "In effect, by making awards to individual researchers, we are asking faculty members to find the best students," says Berdahl, a former chancellor of the University of California, Berkeley. "Presumably, there is a correlation between the quality of an individual [scientist] and the quality of the students in his or her lab."
A system out of balance
Hoffmann, a professor at Cornell University, says he began to think about the need for changing the current system during a series of recent departmental meetings on coping with the economic downturn. Most of the suggestions from faculty members, he concluded, would erode undergraduate instruction, about which he is passionate. Although Cornell officials say they are still working on a long-term plan, Hoffmann fears that a one-time, 5% cut in the chemistry department's operating budget starting this fall will be extended for 3 years and that the result will be larger classes, fewer instructors, and limits on enrollment in some courses. "We're firing some of our best teachers," he says. In contrast, he adds, research programs are likely to be unaffected because they are funded by federal dollars that are beyond the university's control. G. Peter Lepage, a physicist and dean of the College of Arts and Sciences at Cornell, says every university is struggling to educate undergraduates and maintain a strong research program in the face of shrinking endowments, reduced state subsidies, and pressure to hold down tuition increases. Lepage says he doesn't see how Hoffmann's suggestions would help undergraduates, and he worries that they could harm research. "I have to make sure I have enough money to cover our teaching responsibilities [to undergraduates]," he says. "And we'll figure out a way to do that. At the same time, our faculty need graduate students to do their research, and we need to admit enough of them to do the research as well as to teach the courses."
Hoffmann readily admits that a shift to fellowships, which are now limited to U.S. citizens, would have one major unfortunate consequence: It would drain the graduate pool of most students from China, India, and other nations. Foreign students f ill a majority of the slots in many U.S. graduate programs in the natural sciences and engineering, but few could afford to come on their own dime. Hoffmann says he would regret losing those students but points to a silver lining. Having universities award fewer science Ph.D.s should force employers to pay higher salaries, he predicts, and attract more of the best U.S. students into science. Tjian's plan would extend a helping hand to foreign students as well. (As a private philanthropy, Hughes doesn't have to answer to the political argument that U.S. tax dollars should be spent on Americans.) But the Hughes program will serve only a tiny fraction of the foreign graduate students now in the country. Freeman, a labor economist who studies the dynamics of the scientific work force, sides with Cech and Hoffmann when it comes to the value of fellowships. However, Freeman thinks that Hoffmann's all-or-nothing plan ignores both economic and political realities. "We produce two things at our universities: education and science," says Freeman. "That's what society wants from us. And students will still want to work in a lab." Freeman says Hoffmann's suggestions would result in "more expensive science, and that means fewer people doing it. That's not consistent with where most policymakers think we should be headed as a country. ... I hate to reject something because it's radically different, but I think he needs to do a better job of modeling [the consequences]."
Getting the work done
What would fewer graduate students mean for research? Tilghman says that many scientists reacted in horror to the suggestion in her 1998 report that a typical 10-member lab might shed one graduate student as a way to reduce the overproduction of Ph.D.s and improve the quality of their training. "The PIs [principal investigators] told us that the lab's productivity would go way down if they left," she recalls. Tilghman is dubious. "I think that's highly debatable, and in any case, it's never been rigorously tested," she says. "Every scientist knows that graduate students often go through long periods in which they are totally unproductive."
At NIH, the bulk of the training programs are run by the National Institute of General Medical Sciences. Its director, Jeremy Berg, says he shares Hoffmann's concern about maintaining high-quality undergraduate and graduate programs in the face of mounting pressure from faculty members to maintain their research programs. "The biggest driver for the production of Ph.D.s is not the perception that there is an undersupply but rather that there's work that needs to be done," says Berg. "However, even if they are cheap, I'd argue that students are also smart, committed, and hard-working labor." Hoffmann says he assumes that a system of competitive fellowships would widen the already large gap between the elite universities and the rest of the nation's system of higher education, pointing to the fact that the top-20 research universities historically have attracted a disproportionate share of NSF's graduate research fellowships. Increasing that imbalance would bother him, he admits, but not enough to torpedo the idea.
A fellowships-only system, Gerbi says, would also lead to "wild swings in enrollment from one year to the next." On the other hand, say Gerbi and Tilghman, a shift to traineeships would reward universities that articulate a well-crafted approach to build up the talent pool in a particular area and also provide program stability.
Is that difference large enough to make fellowships unattractive to most universities? "I'd like to know" what administrators think about that, says Berg. Cech thinks the different overhead rates do influence how universities view support for graduate students. But he says those reimbursement rates aren't carved in stone. "There's no law that you can only give 10% in indirect costs for a fellowship," he argues. "You could make it 40%, on the grounds that they provide us with research results as well as training. Of course, that would cost more, so the money for training wouldn't go as far." Senior NSF officials actually considered a variation of Hoffmann's proposal several years ago, notes Esin Gulari, dean of science and engineering at Clemson University in South Carolina and a former head of engineering at NSF. The plan would have allowed researchers to request money for a certain number of traineeships as part of their grant application; at the same time, support for graduate students would be excluded from their grant. "But it never went further than that," says Gulari, now a member of the science board and part of Hoffmann's target audience. "We were so focused on increasing the size of the stipends" for existing fellowships, she says, that the question of shifting the balance between various modes of support was never addressed. Even those who agree with Hoffmann that changes are needed are not optimistic they will occur. Tilghman says the topic "is not high on the agenda" of most of her fellow university presidents. Instead, she's pinning her hopes on the heads of the various federal research agencies. But bringing about the changes Hoffmann has suggested, she adds, will require them to put the common good above the self-interest of their constituents, namely, individual scientists. "We need to care most about the health of the overall scientific enterprise," she says. "If your only perspective is attracting the labor to run your lab, then the status quo works very well."7/17/2009 zz Toward a Smarter Web
PerspectivesComputer Science:Toward a Smarter WebGregory S. Hornby1 and Tolga Kurtoglu2
1 University of California at Santa Cruz, University Affiliated Research Center, Mail Stop 269-3, Moffett Field, CA 94035, USA. E-mail: gregory.s.hornby@nasa.gov; tolga.kurtoglu@nasa.gov Since its creation in the early 1990s, the World Wide Web has evolved from its initial, static Web sites to the dynamic, interactive Web sites of today. But whereas existing Web sites merely respond directly to user input, there is growing interest in making them adaptive through the use of computational intelligence. A promising approach for this involves a family of optimization techniques called evolutionary algorithms. A typical evolutionary algorithm (1) starts with an initial population of randomly generated, digital solutions to a problem ("individuals"). These individuals are evaluated with a user-supplied fitness function; on the basis of their fitness scores, better individuals are stochastically selected to act as "parents." Either one parent is copied while making a small change to it (mutation), or parts of two parents are combined to make a new individual (recombination). This breeding process is repeated for a fixed number of evaluations or until the problem has been solved.
Since the 1990s, evolutionary algorithms have been applied to architectural problems from arch dams and suspension bridges to building plans. In industrial and engineering design, they have found use in color design for knitwear, shape design for scissors, and car body styling, as well as for creating complex devices such as gyroscopes and wind turbines. Examples are the nose cone of Hitachi's Series N700 Bullet Train (2) and the communications antennas for the spacecraft in NASA's ST-5 mission, a test mission to validate new space technologies and study the magnetosphere (3). Traditional evolutionary algorithms optimize against explicit fitness functions, but problems involving taste or aesthetics cannot be easily reduced to a mathematical function of goodness. Instead, a human user can perform evaluation manually, as first proposed by Dawkins (4). Running on a standard PC, the first interactive evolutionary algorithm showed the user computer-generated images, of which the user would select one as the parent for the next generation. By iteratively selecting images on the basis of aesthetics, the algorithm produces more and more visually appealing images over time. This has become the standard interface for interactive evolutionary algorithms (see the figure). Since then, interactive evolutionary algorithms have been used in various human-computer interactive design systems. Most applications are visual, such as the evolution of images (5), three-dimensional shapes (6), and architectural forms (7), but they have also been used for musical tasks, including sound synthesis and composition. For example, GenJam is an interactive evolutionary algorithm for real-time jazz improvisation (8). Along with its creator, Al Biles, it forms a virtual jazz quintet that has performed at more than 100 private receptions. The first Web browser that supported images (Mosaic) was released in April 1993. Soon afterward, the first online interactive evolutionary algorithms appeared. The International Interactive Genetic Art 1 (IIGA1) (9) and its successor, IIGA2, had more than 100,000 visitors who collectively created thousands of images over a period of 4 years. In an early commercial application, Affinnova (www.affinnova.com) has used an interactive evolutionary algorithm–based system to design product packaging since 2000. Nymbler (www.nymbler.com) allows users to evolve baby names instead of images. A key challenge for interactive evolutionary algorithms is user fatigue (10). For typical noninteractive evolutionary algorithms, tens of thousands of evaluations are needed to achieve interesting results—orders of magnitude more than can be expected from a single user. On the Web, many users are available, but even this multiplier effect may not overcome user fatigue: Because the interactions are distributed in time, no single user is likely to experience evolution at a sufficiently fast pace for it to be interesting. Given that user fatigue limits the number of interactions, one must make the most of what little data the user provides. The main approach to this is to automate most design evaluations and only selectively query the user. For parameterized design spaces (11), function approximation techniques can be used to assign a goodness score, based on similar designs evaluated by the user. But creating an adequate approximation is difficult, and this approach does not generalize to more open-ended, generative representations (11) for encoding designs. Another approach—using mathematical heuristics of aesthetics—has found some success in the interactive evolution of jewelry (12). The most promising long-term approach is to continuously learn and refine a model of user preferences (13) while simultaneously using this model to perform most evaluations. The interactive systems described above explicitly present the user with choices to select from. Interactive evolutionary algorithms on the Web can also be invisible to the user. For example, the company SnapAds (www.snapads.com) uses an implicit interactive evolutionary algorithm to evolve banner ads. Variations of an ad are placed on Web pages. On the basis of click-through rates, the ad layout evolves and is optimized over the course of a few days. With this approach, the company has improved click-through rates by as much as 1900% (14). The challenge in extending such implicit algorithms to other Web applications will be to convert user interactions into a fitness assignment. As interactive evolutionary algorithms improve and are adopted by Web site developers, we expect them to become increasingly useful for adding intelligence to interactive Web sites. Web sites with explicit interactive evolutionary algorithms could allow users to custom-design products by interactively browsing through virtual catalogs that evolve as users surf through them. Implicit algorithms could enable search engines to adaptively improve their responses to search queries over time and produce user-customized responses. This intelligent Web of the future will not just be powered by better algorithms, but will emerge from the interactions of millions of online users.
References and Notes
7/16/2009 zz Open Access Series
LettersOpen Access: Increased Citations Not GuaranteedIn their Brevia "Open access and global participation in science" (20 February, p. 1025), J. A. Evans and J. Reimer report a small but significant citation effect (about 8%) that they attribute to free access to the scientific literature. However, Evans and Reimer only measure the effect of open access where publishing is concerned, such as when a journal makes articles freely available after a period of delay (1). They ignore other sources of open-access articles, such as when authors pay to make their articles freely available in subscription-access journals (2) or use self-archiving. In a randomized controlled trial of open-access publishing, we were unable to detect a citation advantage that could be attributed to access status, although we did observe that open-access articles received more article downloads from more visitors (3).Philip M. Davis E-mail: pmd8@cornell.edu Department of Communication, Cornell University, Ithaca, NY 14853, USA.
References
LettersOpen Access: The Self-Selection EffectIn the Brevia "Open access and global participation in science" (20 February, p. 1025), J. A. Evans and J. Reimer claim that open access—i.e., free and unrestricted online access to scientific publications—has little influence on research attention, as measured by article citation frequency. Their claim is questionable, however, because it assumes that open access is a randomly assigned journal attribute, whereas it is actually assigned by publishers according to their objectives and the characteristics of the journal.Large, established, widely distributed journals naturally attract important papers and are, consequently, highly cited. Converting such journals to open access will likely cause a fall in revenue unmatched by a comparable rise in impact, making conversion an unappealing option. Publishers of new stand-alone journals face a different situation. Unless they have a captive market, such as a learned society, they will likely have difficulty selling subscriptions. In such cases, open access appears to offer the best hope for gaining both visibility and a stream of contributions. Although the Evans and Reimer study indicates little about the influence of open access on the impact of otherwise similar journals, it does establish that, with open access, new journals can be as effective as the old in gaining readership for the work that they publish. This means that established journals have no inherent monopoly over the literature and that the creation of effective new options for distributing research findings remains possible. Alfred N. Burdett E-mail: alfredburdett@heronpublishing.com Heron Publishing, 202-3994 Shelbourne Street, Victoria, BC V8N 3E2, Canada.
LettersOpen Access: The Sooner the BetterIn the Brevia "Open access and global participation in science" (20 February, p. 1025), J. A. Evans and J. Reimer argue that a research article published online is only modestly (8%) more likely to be cited if it is freely available. This result would seem to cast doubt on one important argument in favor of free access—that it will increase the visibility of a paper to colleagues.However, the 8% statistic that Evans and Reimer highlight is misleading. The authors' supporting online material (figure S1C) clearly shows that the impact of free access on citations is heavily dependent on the age of the article at the time free access was provided. In particular, when articles were made freely available within 2 years of publication, their citations increased by almost 20%. This far more dramatic effect is the one scientists and journals should consider when deciding when to provide free access. If this decision is to be made purely on the basis of citation impact, the upward trend of the curve in figure S1C argues strongly in favor of minimal delays. Unfortunately, it is hard to tell exactly how short a delay the data support, because the underlying citation information is not provided. That the raw data for such a provocative paper is unavailable is an astonishing violation of the norms of science, and the explicitly stated publication policies of Science. Michael Eisen1,* and Steven Salzberg2 * To whom correspondence should be addressed. E-mail: mbeisen@berkeley.edu
1 Howard Hughes Medical Institute, Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA.
LettersOpen Access: The Sooner the BetterEditor's Note: It is Science policy, as stated in our online information to contributors, that "After publication, all data necessary to understand, assess, and extend the conclusions of the manuscript must be available to any reader of Science." However, we do not preclude our authors from obtaining data from commercial sources when those are the only sources of the data and when those data are available to the scientific community.
Bruce Alberts, Editor-in-Chief
LettersResponse—Open AccessDavis accurately observes that our analysis of open access only accounts for scientific literature provided by publishers. We chose to analyze when journal volumes come online through publisher Web sites because publishers do not select specific articles for availability; instead, they select a batch of articles (one or more years'worth) based on duration since publication. The difficulty with analyzing the open-access effect for articles that authors have paid or taken pains to post freely is that authors likely select the best articles. Moreover, in author-pays and self-archiving analyses, articles cannot be compared with themselves over time—they must be compared with other articles that were not selected. As a result, they report large open-access effects—from 100% (1) to 286% (2). A reanalysis of one of these studies using instrumental variables to predict whether authors paid the open-access fee suggests that much of the purported open-access effect comes from author selection (3).Davis recommends his recent open-access experiment with 11 physiology journals that finds no open-access effect (4). Truly randomized, article-level experiments would offer an improvement over current studies. The problem with Davis's experiment, however, is that it introduces another level of selection suggested by Burdett's letter: Established private journals like Nature or Cell would never consider opening their content for an open-access experiment. Journals that do are often sponsored by scientific societies and post a much smaller sticker price. Consider that the average price per article in Davis' sample of journals is $3.39 relative to $14.55 for all 66 physiology titles indexed by Thomson's Web of Science and includes the eight least expensive journals (the average price in our open access sample was $10.28). It should not be surprising that the cheapest journals post an indiscernible open-access effect. This illustration validates Burdett's criticism of our analysis: The modest open-access effect we report derives from the subset of journal volumes that are at some but not all points in the public domain by 2004. The effect would likely be larger if the most expensive journals from private publishers had made their holdings available freely. Eisen argues that the 8% open-access effect we report is misleading because he interprets our figure S1C to suggest that the effect is larger in recent years. A methodological challenge described in our supporting online material cautions against this interpretation. Our analysis relies on estimates of what citations would have been in the absence of online access. Article citations typically trace a log-normal distribution, with a steep rise in citations followed by a gradual fall (5). Whether one models this path explicitly, as we do, or simply uses the prior year's citations, as we show in our supporting material, the estimates become less accurate as you approach the present. For very recent years, these calculations underestimate expected citations because this is when the citation trend rises most steeply. This produces an inflated estimate of the influence of free and commercial online availability, exacerbated because journals that become open access do so disproportionately in the last years of our study. Burdett suggests that new journals can gain quick access to the market for ideas through an open-access model. Our published analysis could not directly support this claim—our estimation excluded journals online at publication—but additional models available from the author provide strong support for it. The only reasonable explanation is that, following Eisen, the culture of modern science and scholarship values the open-access ideal (6). The irony is not lost on us that we published a paper about open access whose data is not open access. It was collected and is owned by private companies. It is, however, widely available and licensed to thousands of research institutions internationally for those who would reassemble it and improve upon our analyses. James A. Evans E-mail: jevans@uchicago.edu Department of Sociology, University of Chicago, Chicago, IL 60637, USA.
References
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来了就留个印吧，不用跟我客气。
杰 徐wrote:
其实他的片子除了第一部在画功上有些差以外其他都很不错的
当然啦，云之彼端是我们开始熟悉了解他的第一部片子
May 5
欣 李wrote:
北京这边大风四起；沙尘风暴……都随之而来。三天两头刮风！！
电影院上映《国家宝藏2》了——Nicolas Cage 
Mar. 23
欣 李wrote:
 提前拜个早年，祝胡爽姐：春节快乐；身体健康；万事如意！
Feb. 3
欣 李wrote:
冯小刚又一部力作，贺岁电影——《集结号》。不是喜剧而是一部战争片，讲兄弟之情的！很是感人，尤其是男人……在电影院里有那么一段让当时的观影气氛鸦雀无声；而且确实也有几位男同志在不知不觉中流泪了～～～ 
Dec. 20
欣 李wrote:
 这边12月13日陈可辛的作品——《投名状》上映。场面宏大；拒说李连杰的片酬高达一个亿！比刘德华还要多。
Dec. 3
欣 李wrote:
这边最近的动态就是，股票开始回落－跌了！
Nov. 29
欣 李wrote:
从15日开始十七大召开了，马路上多了交通警进行交通管制；每天路边上都有带红袖标的站岗。地铁五号线也开通了，车箱像香港那边的从头通到尾，有屏蔽门。这边的天气开始逐渐转凉了，我们穿了有两层衣服以上！ 
Oct. 17
杰 徐wrote:
应该算是新片
在威尼斯电影节上大获好评
姜文导演
姜文、黄秋生、陈冲、房祖名主演
Oct. 1
杰 徐wrote:
抢个板凳坐坐也还不错
Sept. 9
aprilsnail
wrote:
抢第一，貌似有趣的样子，弄一个来玩玩。
July 24
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Chinese readings of Darwin inspired two groups — reformers and revolutionaries.
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