China has rocketed back into the top ranks of scientific research by being free from the social and legal hindrances common in the West and due to its investment of billions of dollars. Nearly every Chinese ministry boasts a program to gain a technological lead of some sort, and in May a Chinese supercomputer was named the second fastest machine in the world at an international conference in Germany. China also is only second to the United States in the number of research articles published in scientific and technical journals worldwide. Many top Chinese scientific institutes appear to be insulating themselves from bureaucratic interference, which has raised ethical concerns about the research they are conducting. Among the challenges China faces is a weak innovation framework and unrealistic bureaucrat-driven mandates to produce discoveries. Another troubling fact is China’s status as the leading source of “junk” patents, while plagiarism and doctored results abound. China’s growing competitiveness is causing U.S. experts to question the practice of opening research institutions to Chinese students. U.S. Federal Bureau of Investigation officials also claim that China is running a large U.S.-based espionage operation to steal the country’s industrial, military, technological, and scientific secrets.
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New modeling software called Qlucore is being used by researchers at King’s College to study how genes react to toxins. The gene-modeling software can sort through thousands of entries in a spreadsheet very quickly and produce results in hours rather than days or weeks, as was the standard with earlier techniques. One gene test can generate 100,000 or more data points, but Qlucore has significantly reduced the time it takes to analyze that data. “We moved within one year from getting one gene a week to getting information on thousands of genes in a matter of hours. That put a lot of challenges to us,” says King’s College’s Thoas Fioretos, Qlucore’s developer. “If you do not have this type of software, it’s like sitting in front of an Excel spreadsheet with 6,000 pages. You cannot find patterns in that, you cannot ask if this gene is expressed with another.” Despite the success of the modeling technique, researchers say their understanding of how genes work together, or even individually, is not yet complete, says King’s College’s Stephen Sturzenbaum.

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ACM and its partners have launched the first-ever Computer Science Education Week (CSEdWeek) to bring greater attention to the need to improve computer science (CS) education at the K-12 level. “The conversation about computer science education speaks directly to the issues of innovation, competitiveness, and a healthy future,” says ACM CEO John White. Computers are becoming more ingrained in everyday life, but the percentage of high schools offering rigorous computing courses fell from 40 percent to 27 percent from 2005 to 2009. Created by a U.S. House of Representatives resolution, CSEdWeek views CS education as a critical element of the national science, technology, engineering, and math (STEM) movement, and not as an add-on or an optional course. Best practices for CS education are highlighted on the Web site www.csedweek.org, which serves as the central hub for CSEdWeek. The site offers computer science curriculum guides, data, research, posters, and brochures, and provides a platform for sharing ideas on improving CS education. CSEdWeek is the second week in December, and was chosen in honor of computer science pioneer Grace Murray Hopper, who was born on Dec. 9, 1906. ACM is leading the joint effort of the Computer Science Teachers Association, the Computing Research Association, the National Center for Women & Information Technology, the Anita Borg Institute, the National Science Foundation, Google, Intel, and Microsoft.

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TraSer, developed by researchers in Hungary, Romania, the Netherlands and Finland, is a track-and-trace open source program that enables small companies to share commercially sensitive information and monitor the movement of materials and products from suppliers to customers. TraSer also allows companies along the supply chain to share data, instead of having the information owned or controlled by a central authority. The program creates a unique product identifier by combining a product identification code with a company Web address, which does not depend on registration with a centralized authority. “TraSer is designed as an entry-level solution platform,” says Elisabeth Ilie-Zudor, coordinator of the TraSer project and a researcher at the Computer and Automation Research Institute of the Hungarian Academy of Sciences. “We strove to keep it as simple as possible in operation. Still, it remains vital to understand what is actually done in a track-and-trace network to make it work.” By eliminating the need for a centralized service, the network is less vulnerable to malfunction or abuse. A TraSer network has a core of connected company servers, surrounded by an ‘envelope’ of clients. Those clients can access information from bar codes, radio frequency identification tags, or other carriers of a product’s unique identifier. TraSer also can adapt to a wide range of input types because the interface between client and server is uniform. Ilie-Zudor says that “companies need to view shared data as an investment where the creation of a better picture for everyone leads to a payback in cost reductions, better working methods, and greater coordination.”

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A Massachusetts Institute of Technology (MIT) research group beat out about 4,300 other teams on Saturday in a Defense Advanced Research Project Agency (DARPA) contest to test human social networking. DARPA released 10 eight-foot weather balloons across the continental United States on Saturday and challenged competitors to correctly identify the longitude and latitude coordinates for each balloon as quickly as possible. The first team to correctly identify the location of all 10 balloons won $40,000. The MIT group set up a Web site asking people to join their team and offered to share the prize money with people who offered correct information. “This was a once-in-a-lifetime opportunity to perform an experiment at a massive scale,” says MIT’s Riley Crane, part of a group of researchers that study human interactions involving computer networks. Crane describes the MIT strategy as a “recursive incentive structure.” The MIT researchers received contributions from 4,665 participants. They said their techniques could be used for finding criminals and missing children, as well as possibly stopping impending terrorist attacks. “They got a huge amount of participation from shockingly little money,” says DARPA’s Peter Lee.

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