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Computer models help form new magnetic materials
Magnetic materials are extremely difficult to find. They're rare in nature, and creating one in the lab usually involves both a lot of experimentation and a little luck. Duke University, however, has found a way to take the mystery out of the process: its researchers have used computer modelling to help generate two new kinds of magnetic materials. The models whittled down the potential atomic structures from a whopping 236,115 combinations to just 14 candidates by subjecting the structures to increasingly tougher tests. How stable are they? Do they have a "magnetic moment" that determines the strength of their reaction to an outside magnetic field? After that, it was just a matter of synthesizing the few remaining materials to see how well they worked in real life.
MIT model reveals role of inhibitory neurons in the brain
Recent digital tech advancements have produced prototype artificial neurons and light-based neural networks, but we're still discovering ways our brain actually works. Researchers at MIT have built a computational model that could illustrate how inhibitory neurons work efficiently to block others from firing.
Scientists create first computer simulation of a complete organism
Everyone, meet Mycoplasma genitalium, the subject of many scientific papers, even more vists to the clinic and now the first organism to be entirely recreated in binary. Computer models are often used for simplicity, or when studying the real thing just ain't viable, but most look at an isolated process. Stanford researchers wanted to break with tradition and selected one of the simplest organisms around, M. genitalium, to be their test subject. They collated data from over 900 publications to account for everything going on inside the bacterial cell. But it wasn't just a case of running a model of each cellular process. They had to account for all the interactions that go on -- basically, a hell of a lot of math. The team managed to recreate cell division using the model, although a single pass took almost 10 hours with MATLAB software running on a 128-core Linux cluster. The representation was so accurate it predicted what M. genitalium looks like, just from the genetic data. And, despite the raft of research already conducted on the bacterium, the model revealed previously undiscovered inconsistencies in individual cell cycles. Such simulations could be used in the future to better understand the complicated biology of diseases like cancer and Alzheimer's. Looks like we're going to need more cores in that cluster. If you'd like to hear Stanford researcher Markus Covert's view on the work, we've embedded some footage beyond the fold.
Featureless avatars help scientists dominate the dancefloor
Scientists. If we didn't know better, we'd think they were messing with us all the time. But we know they're usually there to help, which is the only reason we've watched this video (after the break) 27 times this afternoon. Apparently Northumbria University researchers motion-captured a bunch of dudes dancing really hard, then mapped their movements to these fun models -- devoid of any popped collars, Ed Hardy vests, or Gucci bling to keep things scientifically pure -- then asked 35 women to rate the dancing on attractiveness. Turns out the left wrist, right knee, head, and trunk are most important parts to shake if you're a dude trying to catch the most feminine eyes in da club. Seems like those parts communicate a man's "reproductive quality" the most effectively. Now excuse us -- we've got a lot of work to do before Happy Hour rolls around.
