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Alexander S. Szalay is a well-regarded astronomer, but he hasn't peered through a telescope in nearly a decade. Instead, the professor of physics and astronomy at the Johns Hopkins University learned how to write software code, build computer servers, and stitch millions of digital telescope images into a sweeping panorama of the universe.

Today, data sharing in astronomy isn't just among professors. Amateurs are invited into the data sets through friendly Web interfaces, and a schoolteacher in Holland recently made a major discovery, of an unusual gas cloud that might help explain the life cycle of quasars—bright centers of distant galaxies—after spending part of her summer vacation gazing at the objects on her computer screen. Crowd Science, as it might be called, is taking hold in several other disciplines, such as biology, and is rising rapidly in oceanography and a range of environmental sciences. "Crowdsourcing is a natural solution to many of the problems that scientists are dealing with that involve massive amounts of data," says Haym Hirsh, director of the Division of Information and Intelligent Systems at the National Science Foundation.

Mr. Szalay's unusual career began with a stint as a rock star. While in graduate school in Hungary, he played lead guitar in the band Panta Rhei, which released two albums and several singles in the 1970s.

The National Science Foundation announces plans to expand its support of research coordination networks designed to foster communication and promote new collaboration among scientists and engineers with diverse expertise and who share a common interest in a new or developing area of science or engineering. By encouraging the formation of new groups and networks, the RCN program will advance fields and create novel directions and opportunities for research and science education. It is anticipated that this program will contribute to further progress in all areas of science, however RCNs are intended to foster networking activities and thus will not directly support costs related to research.

The conceptual framework and value chain analysis methodology developed for this study are being refined in light of the lessons learned by the research team, and applied to further studies in other sectors, not all of which are as buoyant as bagged salad! Co-innovation is a concept in which we firmly believe and in which Houston's Farm is now firmly engaged. However, there remains much to learn about how to do it and how to research it. The value chain innovation research initiative at the University of Tasmania will, we hope, provide more valuable insights for academics and practitioners in the future.

IIAM one of the largest recovery and placement networks in the world that provides a link between humanity and medical discovery - honoring the wishes of donors and their families wanting to contribute to medical research and education. IIAM provides researchers with the human tissues needed to find cures for disease, improve treatments and techniques, and develop drugs.

Founded in 1967, NDRI is a non-profit research and educational organization dedicated to advancing scientific knowledge in the areas of drug and alcohol abuse, treatment and recovery; HIV, AIDS and HCV; therapeutic communities; youth at risk; and related areas of public health, mental health, criminal justice, urban problems, prevention and epidemiology.

The systematic review of published research studies is a major method used for evaluating particular treatments. The Cochrane Collaboration is one of the best-known, respected examples of systematic reviews. Like other collections of systematic reviews, it requires authors to provide a detailed and repeatable plan of their literature search and evaluations of the evidence. Once all the best evidence is assessed, treatment is categoried as "likely to be beneficial", "likely to be harmful", or "evidence did not support either benefit or harm".

Evidence-based medicine categorizes different types of clinical evidence and ranks them according to the strength of their freedom from the various biases that beset medical research. For example, the strongest evidence for therapeutic interventions is provided by systematic review of randomized, double-blind, placebo-controlled trials involving a homogeneous patient population and medical condition. In contrast, patient testimonials, case reports, and even expert opinion have little value as proof because of the placebo effect, the biases inherent in observation and reporting of cases, difficulties in ascertaining who is an expert, and more.

Varying the types of skills you work on in practice sessions engages a different part of the brain than the one you use when focusing on a single task, researchers say. The finding explains why variable practice improves the brain's memory of most skills better than working on just one type of task, according to the research team from the University of Southern California and the University of California, Los Angeles.In their study, published online recently in Nature Neuroscience, the investigators divided 59 volunteers into different groups. Some were asked to practice a challenging arm movement, while others did the arm movement and related tasks in a variable practice structure.The participants in the variable practice group learned the arm movement better than those who practiced only the arm movement, the study authors found.Among those in the variable practice group, the process of consolidating memory of the skill engaged a part of the brain called the prefrontal cortex, which is associated with higher level planning. Among those who practiced only the arm movement, the engaged part of the brain was the primary motor cortex, which is associated with simple motor learning, the authors explained."In the variable practice structure condition, you're basically solving the motor problem anew each time. If I'm just repeating the same thing over and over again as in the constant practice condition, I don't have to process it very deeply," study senior author Carolee Winstein, a professor of biokinesiology and physical therapy at the University of Southern California, said in a university news release.

Primary care practices typically measure productivity according to the number of visits, which also drives payment.

Several studies have estimated the amount of time that primary care physicians devote to nonvisit work.1,2 To provide a more detailed description, my colleagues and I used our electronic health record to count units of primary care work during the course of a year.

Greenhouse Internists is a community-based internal medicine practice employing five physicians in Philadelphia. In 2008, we had an active caseload of 8440 patients between 15 and 99 years of age.

etadata is the “data about the data”: all the habitat data, SOPs and abiotic data that is in dire need of the standardization Kyrpides writes about.

Metadata is the “data about the data”: all the habitat data, SOPs and abiotic data that is in dire need of the standardization Kyrpides writes about.

In 2005 the Genomics Standards Consortium was formed to address this problem. Renzo Kottman from the Max-Planck Institute for Marine Microbiology in Bremen, Germany  talked about software development within the GSC, and specifically about his own project: the Genomic Contextual Data Markup Language, or GCDML. GCDML is an XML-based standard for describing everything associated with a genomic or a metagenomic sample: where it was taken from , under what conditions, which protocols were used to extract, sequence, assemble, finish and analyze the metagenome.

Today, the iBridgeSM Network provides the centralized online source for research and innovations. While traditional search engines provide a means for looking for information, the iBridgeSM Network provides a public, centralized source for unbiased information about early stage technologies and inventions. Our objective is to drive transparency and access to university developed innovations that are available today as well as to field experts, ideas and information. Through the iBridgeSM Network, researchers and those seeking innovations can easily search for and obtain the resources they need.

The Pentagon is looking to better train its troops — by scanning their minds as they play video games. Adaptive, mind-reading computer systems have been a work-in-progress among military agencies for at least a decade. In 2000, far-out research agency Darpa launched “Augmented Cognition,” a program that sought to develop computers that used EEG scans to adjust how they displayed information — visually, orally, or otherwise — to avoid overtaxing one realm of a troop’s cognition. The Air Force also took up the idea, by trying to use EEGs to “assess the operator’s actual cognitive state”  and “avoid cognitive bottlenecks before they occur.”

Now, the Office of the Secretary of Defense (OSD) is soliciting small business proposals for an even more immersive trainer, one that includes voice-recognition technology, and picks up on vocal tone and facial gestures. The game would then react and adapt to a war-fighter’s every action. For example, if a player’s gesture “insults the local tribal leader,” the trainee would “find that future interactions with the population are more difficult and more hostile.” And, most importantly, the new programs would react to the warrior’s own physiological and neurological cues. They’d be monitored using an EEG, eye tracking, heart and respiration rate, and other physiological markers. Based on the metrics, the game would adapt in difficulty and “keep trainees in an optimal state of learning.”

The OSD isn’t ready to use neuro-based systems in the war zone, but the agency does want to capitalize on advances in neuroscience that have assigned meaningful value to intuitive decision-making. As the OSD solicitation points out, troops often need to make fast-paced decisions in high-stress environments, with limited information and context. Well-reasoned, analytic decisions are rarely possible

The Directorate for Engineering’s Division of Industrial Innovation and Partnerships’ Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs invites all active SBIR/STTR Phase I grantees to participate in the Phase IB supplemental funding opportunity. Phase IB supplements to Phase I grantees are intended to foster partnerships between strategic partners and investors and the SBIR/STTR companies.

Through this supplemental program, small businesses will be able to effectively leverage funding and investment from interested outside parties on the technology funded in Phase I that could lead to successful commercial products and processes and at the same time provide some of the gap funding required to carry the grantees' effort from Phase I to Phase II.

The objective of the Phase IB option is to extend the R&D efforts beyond the current grant to meet the product/process/software requirements of a third party investor to accelerate the Phase I project to the commercialization stage and enhance the overall strength of the commercial potential of the subsequent Phase II project. The Phase IB option extends the Phase I grant for six months, and the combined Phase I and IB project will typically not exceed one year in duration for the SBIR grant and one and one half years for the STTR grant.

This ethnographic study investigates how a project group deals with the contradiction between distributed knowledge in boundary-spanning collaborative processes and the expectation that software systems will provide unified, codified knowledge. Group and individual activities were observed over a period of 18 months, to examine the ways knowledge was presented, recognized, shared, or otherwise managed during joint design of business process and IT systems change. The study explores how knowledge and expertise were translated across organizational boundaries, and identifies four stages in the development of group understanding of how to manage sensemaking and expertise across knowledge boundaries: focus on defining shared goals; acknowledging and sharing tacit knowledge about organizational practice; identifying external influences; and explicit knowledge generation.

A new study published on August 26 in the journal Science explains the old adage that two heads are better than one is not always true. Professors Chris Frith of the Wellcome Trust Centre for Neuroimaging at the University College London (UCL) and Niels Bohr at the University of Aarhus in Denmark and colleagues discovered that two heads work best when they are equals and can speak freely with one another.Bahador Bahrami, MD, researcher at UCL's Institute of Cognitive Neuroscience and lead author of the study, explained, "When we are trying to solve problems, we usually put our heads together in teams, calling on each other's opinions. "For our study, we wanted to see if two people could combine information from each other in a difficult judgement task and how much this would improve their performance."Frith noted, "When two people working together can discuss their disagreements, two heads can be better than one. But, when one person is working with flawed information - or perhaps is less able at their job - then this can have a very negative effect on the outcome.

Lawrence Aldrich President and Chief Executive Officer (CEO) Larry Aldrich is an attorney with over 25 years of proven leadership abilities in diverse business positions. As President and CEO he is responsible for various corporate departments at UPH, including Legal/Risk, Information Systems, Electronic Medical Records, Marketing/Business Development/Contracts Administration and Facilities. Prior to joining UPH, Larry was the founding Chief Operating Officer at The Critical Path Institute (C-Path), a non-profit medical research organization focused on improving the safety and efficacy of the drug development process through the U.S. Food and Drug Administration. He also served as the president and CEO of Tucson Newspapers. Larry received his law degree from Tulane Law School and his civil engineering degree from Georgia Institute of Technology.

Transforming Technology Transfer from a Cost Center into a Profit Center Are your intellectual assets working hard enough? It’s a troubling question. Every year, universities, businesses, and government agencies lose millions of dollars in uncollected license fees, avoidable legal expenses, and missed opportunities. Even the most heroic efforts from Technology Transfer Offices aren’t enough. Constantly growing caseloads, paperwork, and reporting requirements keep them swamped. So researchers can’t access critical information. Invention disclosures and legal filings are missed. And valuable marketing opportunities fall between the cracks. KSS TechTracS® changes all this.

Technology has given us access to endless amounts of information from every corner of the world. But the real challenge is to make sense of all this seemingly disconnected data. To cut through the clutter, make relevant associations, and transform raw information into true knowledge. Atigeo™ is solving this complex challenge with xPatterns,™ a new breed of compassionate technology that allows users to derive insight and wisdom from data. Based upon an advanced platform of artificial intelligence and machine learning, it effectively interprets unstructured data to arrive at new and unexpected connections. Connections that can personalize individual interactions, enhance consumer privacy, improve business intelligence, advance research development, and foster a greater understanding of the world around us.