Scientists have created a drug for type 2 diabetes that is switched on by blue light, which they hope will improve treatment of the disease. The drug would be inactive under normal conditions, but a patient could in theory switch it on using blue LEDs stuck to the skin. Only a small amount of light would need to penetrate the skin to change the drug’s shape and turn it on. This change is reversible, so the drug switches off again when the light goes off.
Source: www3.imperial.ac.uk
Despite recent advances in gestural interfaces, we’re nowhere near the Minority Report-style future we were promised. Sure, technologies like Kinect and Leap Motion make for some impressive, sci-fi-seeming projects, but when was the last time you saw somebody waving their hands in front of a computer orsmartphone in the wild?
That day may come sooner than you think.
SideSwipe is a clever new approach to 3-D gesture control from researchers at the University of Washington. It uses the device’s own wireless signal transmissions to detect nearby hand gestures, effectively turning the 3-D space around your phone into an interface. It even works when your phone is in your pocket.
“Today’s smartphones already include multiple antennas for spatial diversity and to support multiple wireless standards,” says Matt Reynolds, a UW computer science and engineering professor who helped lead the research. “We expect that the simple broadbandreceivers that we have developed could be integrated with existing antennas, and the detection of reflected power could be built-in to the phone’s chipset by the chipset manufacturer.”
Since SideSwipe doesn’t rely on processor-hogging resources like the phone’s camera or internal sensors, it lets the device effectively “listen” for its owner’s gestural commands at all times without sapping the battery. In doing so, SideSwipe removes the biggest obstacle phone manufacturers face when it comes to including persistent gestural control in mobile devices: preserving battery life. For most people, gee-whiz functionality like this just isn’t important enough to justify the power it would normally consume.
Source: www.washington.edu
UC Berkeley scientists have taken proteins from nerve cells and used them to create a “smart” material that is extremely sensitive to its environment. This marriage of materials science and biology could give birth to a flexible, sensitive coating that is easy and cheap to manufacture in large quantities.
Source: newscenter.berkeley.edu
Stanford University scientists have developed a ‘smart’ lithium-ion battery that gives ample warning before it overheats and bursts into flames. The new technology is designed for conventional lithium-ion batteries now used in billions of cellphones, laptops and other electronic devices, as well as a growing number of cars and airplanes.
The early-warning technology can also be used in zinc, aluminum and other metal batteries. “It will work in any battery that would require you to detect a short before it explodes,” Cui said.
Source: energy.stanford.edu
No-power Wi-Fi connectivity could fuel Internet of Things realityResearchers at the University of Washington have devised a way for battery-free devices to skim a connective link from errant WiFi signals, potentially increasing the reach of the Internet of Things to include just about any thing. The new tool, called a backscatter, looks like a thin plate of metal that works by “looking” for WiFi signals moving between the router and a laptop or smartphone.
They encode data by either reflecting or not reflecting the Wi-Fi router’s signals, slightly changing the wireless signal. Wi-Fi-enabled devices like laptops and smartphones would detect these minute changes and receive data from the tag. In this way, your [battery-free] smart watch could download emails or offload your workout data onto a Google spreadsheet.
Source: www.washington.edu
University of Washington bioengineers have designed a peptide structure that can stop the harmful changes of the body’s normal proteins into a state that’s linked to widespread diseases such as Alzheimer’s, Parkinson’s, heart disease, Type 2 diabetes and Lou Gehrig’s disease. The synthetic molecule blocks these proteins as they shift from their normal state into an abnormally folded form by targeting a toxic intermediate phase.
The discovery of a protein blocker could lead to ways to diagnose and even treat a large swath of diseases that are hard to pin down and rarely have a cure. The researchers hope their designed compounds could be used as diagnostics for amyloid diseases and as drugs to treat the diseases or at least slow progression.
“For example, patients could have a broad first-pass test done to see if they have an amyloid disease and then drill down further to determine which proteins are present to identify the specific disease,” Daggett said.
The research was funded by the National Institutes of Health (General Medicine Sciences), the National Science Foundation, the Wallace H. Coulter Foundation and Coins for Alzheimer’s Research Trust.
Source: www.washington.edu
Technology could lead to e-readers, smartphones, and displays that let users dispense with glasses.
Researchers from the Massachusetts Institute of Technology and the University of California at Berkeley have joined forces to produce a system which “predistorts” digital content for the individual observer in order to produce a correctly-perceived image without corrective eye wear. Drawing from UC Berkeley’s School of Optometry and Computer Science Division and MIT’s Media Lab and Camera Culture Group, the team has developed technology which can account for, but also potentially diagnose, a user’s vision correction.
As lead author Fu-Chung Huang explains, the project’s significance is that, “instead of relying on optics to correct your vision, we use computation. This is a very different class of correction, and it is non-intrusive.” Project leader Brian Barsky has further suggested that a potential impact of the technology may even be removing the need for invasive eye treatments and the effects of lowered visual function.
Source: newsoffice.mit.edu
Algorithm recovers speech from the vibrations of a potato-chip bag filmed through soundproof glass.
Researchers at MIT, Microsoft, and Adobe have developed an algorithm that can reconstruct an audio signal by analyzing minute vibrations of objects depicted in video. In one set of experiments, they were able to recover intelligible speech from the vibrations of a potato-chip bag photographed from 15 feet away through soundproof glass.
In other experiments, they extracted useful audio signals from videos of aluminum foil, the surface of a glass of water, and even the leaves of a potted plant.
Source: newsoffice.mit.edu
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If you’ve ever wanted to chop data up into separate little piles, here’s your chance. Using a proof-of-concept called Kinetica, Ph.D. students at CMU’s Human-Computer Interaction Institute have created a system that lets you slide certain subsets of data out of a chart, order data along arbitrary lines, and even create charts and graphs with a quick swipe.
The app, which runs on the iPad, allows you to import a data set and then slide across it to separate out, say, outliers or specific values. You can automatically sort things along hand-drawn curves and even create multiple chart styles out of the same data.
Data points appear as magnetic dots that change color depending on another value. For example, you can separate the dots out by a certain statistic (allowing you to sort a list of cars by color or a list of foods by sugar content) and order them within those categories.
See on www.cmu.edu
See on Scoop.it – :: Science Innovation :: Research News ::
The ability to stick objects to a wide range of surfaces such as drywall, wood, metal and glass with a single adhesive has been the elusive goal of many research teams across the world, but now a team of University of Massachusetts Amherst inventors describe a new, more versatile version of their invention, Geckskin, that can adhere strongly to a wider range of surfaces, yet releases easily, like a gecko’s feet.
See on www.umass.edu
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