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Xenon Gas Can Erase Traumatic Memories

Xenon gas is commonly used for diagnostic inhalation because of its anesthetic properties but more...

Bronze Age Wine Cellar Found In Israel

A Middle Bronze Age Canaanite palace at the Tel Kabri excavation in Israel has revealed an ancient...

Brain Networks Hyper-Connected In Depressed Young Adults

Functional magnetic resonance imaging (fMRI) has led University of Illinois at Chicago scholars...

Wealthy, Liberal, Elites: Vaccine Refusal Linked To Expression Of Privilege

Not all students returning to school this month will be up to date on their vaccinations and a...

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A new study by Yan Zhang at Rice University's Jones Graduate School of Management seeks to determine why CEOs leave the job after a short period. Of the 204 company leaders Zhang studied from 1993 to 1998, 55 (27 percent) left their jobs within three years.

Is it an alarming statistic? Not really. According to the 2005 Hudson report (1), 36 percent of employees expect to leave within three years, though most of them are likely unhappy with pay and benefits, something CEOs don't share.

Zhang doesn't factor in competition from other companies and the specific nature of Sarbanes-Oxley that make competition for risk-takers more prevalent, namely that signing a company document in today's business climate can send you to jail.

Getting an accurate picture of information and people is difficult. If you start counting people in China today, by the time you finish there are a lot more. Ditto with information. So you may get only a snapshot accurate to milliseconds.

But researchers at the University of California, San Diego, have announced a new study to quantify the amounts and kinds of information being produced worldwide by businesses and consumers alike.

The “How Much Information?” study will be completed by a multi-disciplinary, multi-university faculty team supported by corporate and foundation sponsorship. The program will be undertaken at the Global Information Industry Center (GIIC) at the School of International Relations and Pacific Studies (IR/PS), with support from the Jacobs School of Engineering and the San Diego Supercomputer Center.

Disinfectants are routinely used on hard surfaces in hospitals to kill bacteria, with antimicrobial containing wipes increasingly being employed for this purpose.

A study by the University's Welsh School of Pharmacy looked into the ability of antimicrobial-surface wipes to remove, kill and prevent the spread of such infections as MRSA. They found that current protocols utilized by hospital staff have the potential to spread pathogens, particularly due to the ineffectiveness of wipes to actually kill bacteria.

The team, led by microbiologist Dr Jean-Yves Maillard is now calling for a 'one wipe – one application – per surface' approach to infection control in healthcare environments.

Mind readers have long been the domain of folklore and science fiction. But some new findings demonstrate the power of computational modeling to improve our understanding of how the brain processes information and thoughts and it brings scientists closer to knowing how specific thoughts activate our brains.

In their most recent work a computer scientist, Tom Mitchell, and a cognitive neuroscientist, Marcel Just, both of Carnegie Mellon University, used fMRI data to develop a sophisticated computational model that can predict the brain activation patterns associated with concrete nouns, or things that we experience through our senses, even if the computer did not already have the fMRI data for that specific noun.

The researchers first built a model that took the fMRI activation patterns for 60 concrete nouns broken down into 12 categories including animals, body parts, buildings, clothing, insects, vehicles and vegetables. The model also analyzed a text corpus, or a set of texts that contained more than a trillion words, noting how each noun was used in relation to a set of 25 verbs associated with sensory or motor functions. Combining the brain scan information with the analysis of the text corpus, the computer then predicted the brain activity pattern of thousands of other concrete nouns.

In cases where the actual activation patterns were known, the researchers found that the accuracy of the computer model's predictions was significantly better than chance. The computer can effectively predict what each participant's brain activation patterns would look like when each thought about these words, even without having seen the patterns associated with those words in advance.


It used to be you went to see a doctor, he gave expert advice and you did what you were told.

In today's world, patients have the opportunity to become more knowledgeable, sometimes increasing problems (diagnosing themselves) and sometimes causing impatience with hurried doctors who don't want to argue but most often a better understanding of the issues is good for everyone.

Due to that, there is growing interest in shared decision-making (SDM) in which the clinician and patient go through all phases of the decision-making process together, share treatment preferences, and reach an agreement on treatment choice.

Brown dwarfs, "failed stars", are a class of objects that represent the missing link between the lowest-mass stars and the gas-giant planets, such as Jupiter and Saturn. Brown dwarfs are the faintest and coolest objects that can be directly observed outside the solar system, emitting as little as 1/300,000th of the energy of the sun and having surface temperatures around 800° F - that's the temperature of a pizza oven and more than 9,000° F cooler than the surface of the sun.

Astronomers have used ultrasharp images obtained with the Keck Telescope and Hubble Space Telescope to determine for the first time the masses of the coldest class brown dwarfs. With masses as light as 3 percent the mass of the sun, these are the lowest mass free-floating objects ever weighed outside the solar system. The observations are a major step in testing the theoretical predictions of objects that cannot generate their own internal energy, both brown dwarfs and gas-giant planets. The new findings, which are being presented in a press conference today at the American Astronomical Society meeting in St. Louis, show that the predictions may have some problems.