IPHONE APPS AND MORE.

www.youthsprouts.blogspot.com

The iPhone is a popular platform for hackers who have developed software that takes advantage of the gadget's features. Here a person who downloaded the pocket guitar software, developed by Shinya Kasatani, plays music by pressing and strumming the phone's touch screen. __

Atomic Magnetometers

www.youthsprouts.blogspot.com By Katherine Bourzac

Physicist John Kitching explains what his sensitive magnetic detectors do and how they work. __

Better Graphene Transistors. IBM ALWAYS GREAT

www.youthsprouts.blogspot.com Double-decker: IBM researchers have found that they can significantly reduce noise in graphene devices by stacking two layers together. Here, the noise produced from a single layer of graphene (left) is compared with that from two layers (right).

Credit: IBM

IBM researchers have discovered a way to massively improve the performance of transistors made out of sheets of the two-dimensional carbon material grapheme: they stack them up. By placing two layers of graphene on top of each other, they found that they can reduce the electrical noise of the device by a factor of 10.

The findings could help realize graphene-based chips that run faster, are more compact, and consume less power than today's silicon chips, says Yu-Ming Lin, a scientist at the IBM T. J. Watson Research Center, in Yorktown Heights, NY. IBM researchers are also investigating other promising successors to silicon, such as graphene-like carbon nanotubes. Graphene, which is made entirely out of carbon atoms arranged in a one-atom-thick honeycomb structure, has a number of properties that make it attractive for electronics, particularly for transistors that produce radio-frequency signals. But transistors created from the material have been plagued by noise, making the signals they produce less than ideal for communications. The researchers' discovery could help make graphene transistors practical.

__

Probabilistic Chips- COMPUTER SCIENTISTS ARE GREAT

www.youthsprouts.blogspot.com By Erika Jonietz

Computer scientist Krishna Palem explains how permitting a small amount of error in computation could result in computer chips that consume much less power than today's designs, without compromising user experience.

Krishna Palem Credit: Brent Humphreys

Krishna Palem is a heretic. In the world of microchips, precision and perfection have always been imperative. Every step of the fabrication process involves testing and retesting and is aimed at ensuring that every chip calculates the exact answer every time. But Palem, a professor of computing at Rice ­University, believes that a little error can be a good thing.

Palem has developed a way for chips to use significantly less power in exchange for a small loss of precision. His concept carrie­s the daunting moniker "probabilistic complementary metal-oxide semi­conductor technology"--PCMOS for short. Palem's premise is that for many applications--in particular those like audio or video processing, where the final result isn't a number--maximum precision is ­unnecessary. Instead, chips could be designed to produce the correct answer sometimes, but only come close the rest of the time. Because the errors would be small, so would their effects: in essence, Palem believes that in computing, close enough is often good enough.

__

Clothes That Clean Themselves

www.youthsprouts.blogspot.com Australian researchers are developing a process that could lead to self-cleaning wool sweaters and silk ties. Wine be gone: Wool fibers have to be chemically modified to receive a stable coating of titanium dioxide nanocrystals, which break down organic matter in sunlight. Red-wine stains do not leave uncoated fibers even after 20 hours (top right); unmodified nanocrystal-coated fibers show some stains (middle right). The stain is almost gone in chemically modified fibers because of the firmly attached nanocrystals (bottom right). Credit: American Chemical Society

Researchers at Monash University, in Victoria, Australia, have found a way to coat fibers with titanium dioxide nanocrystals, which break down food and dirt in sunlight. The researchers, led by organic chemist and nanomaterials researcher Walid Daoud, have made natural fibers such as wool, silk, and hemp that will automatically remove food, grime, and even red-wine stains when exposed to sunlight.

Daoud and his colleagues coat the fibers with a thin, invisible layer of titanium dioxide nanoparticles. Titanium dioxide, which is used in sunscreens, toothpaste, and paint, is a strong photocatalyst: in the presence of ultraviolet light and water vapor, it forms hydroxyl radicals, which oxidize, or decompose, organic matter. However, says Daoud, "these nanocrystals cannot decompose wool and are harmless to skin." Moreover, the coating does not change the look and feel of the fabric.

To make self-cleaning wool, Daoud and his colleagues use nanocrystals of titanium dioxide that are four to five nanometers in size. In the past, the researchers have made self-cleaning cotton by coating it with these nanocrystals. But coating wool, silk, and hemp has proved more difficult. These fibers are made of a protein called keratin, which does not have any reactive chemical groups on its surface to bind with titanium dioxide. __

www.youthsprouts.blogspot.com

TR10: Modeling Surprise

M. Mitchell Waldrop

Eric Horvitz, head of the Adaptive Systems and Interaction group at Microsoft Research, talks about surprise modeling.

Combining massive quantities of data, insights into human psychology, and machine learning can help manage surprising events, says Eric Horvitz.

Much of modern life depends on forecasts: where the next hurricane will make landfall, how the stock market will react to falling home prices, who will win the next primary. While existing computer models predict many things fairly accurately, surprises still crop up, and we probably can't eliminate them. But Eric Horvitz, head of the Adaptive Systems and Interaction group at Microsoft Research, thinks we can at least minimize them, using a technique he calls "surprise modeling."

Credit: Photo: Bettman/Corbis; Graphics: John Hersey

Multimedia • Eric Horvitz talks about surprise modeling.

Who: Eric Horvitz, Microsoft Research Definition: Surprise modeling combines data mining and machine learning to help people do a better job of anticipating and coping with unusual events. Impact: Although research in the field is preliminary, surprise modeling could aid decision makers in a wide range of domains, such as traffic management, preventive medicine, military planning, politics, business, and finance. Context: A prototype that alerts users to surprises in Seattle traffic patterns has proved effective in field tests involving thousands of Microsoft employees. Studies investigating broader applications are now under way.

Horvitz stresses that surprise modeling is not about building a technological crystal ball to predict what the stock market will do tomorrow, or what al-Qaeda might do next month. But, he says, "We think we can apply these methodologies to look at the kinds of things that have surprised us in the past and then model the kinds of things that may surprise us in the future." The result could be enormously useful for decision makers in fields that range from health care to military strategy, politics to financial markets.

__