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Researchers have developed a machine learning algorithm that could help reduce charging times and prolong battery life in electric vehicles by predicting how different driving patterns affect battery performance, improving safety and reliability.

The researchers, from the University of Cambridge, say their algorithm could help drivers, manufacturers and businesses get the most out of the batteries that power by suggesting routes and driving patterns that minimize battery degradation and charging times.

The team developed a non-invasive way to probe batteries and get a holistic view of battery health. These results were then fed into a machine learning algorithm that can predict how different driving patterns will affect the future health of the battery.

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Summary: A new language-switching experiment revealed traditional categorization of brain areas may not be sufficient. Researchers set their sights on the caudal inferior parietal cortex to better understand functional categorization in the brain.

Source: Leiden University.

Based on the results of a language-switching experiment, Ph.D. candidate Fatemeh (Simeen) Tabassi Mofrad MA and Professor Niels Schiller have discovered that the traditional categorization of brain areas is not sufficient.

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A team of researchers at the Max Planck Institute for Intelligent Systems, working with a pair of colleagues from the Harbin Institute of Technology, has developed a tiny actuated gearbox that can be used to give very tiny robots more power. In their paper published in the journal Science Robotics, the group describes how their gearbox works and the power improvements observed in several types of tiny robots.

Over the past several years, scientists have been working toward the development of tiny robots that can be injected into the to carry out medical procedures. The hope is that such robots can be sent to find and destroy , for example. Such tiny robots are too small to carry their own power plant; thus, they must be manipulated using an . Unfortunately, as the robots grow ever tinier, their power diminishes as they have too little mass. In this new effort, the researchers have found a way to increase the power of the tiny robots using a tiny gearbox that helps them become stronger.

The gearbox comes with a magnet on its end to harness the power in a magnetic field via the gears in the box. And the gearbox is able to magnify the power of a using clever features including elastic components and mechanical linkages.

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A team of researchers at Google’s Deep Mind London project, has taught animated players how to play a realistic version of soccer on a computer screen. In their paper published in the journal Science Robotics, the group describes teaching the animated players to play as solo players and also in teams.

For several years, engineers have been working diligently to create robots capable of playing . Such work has resulted in competition between various groups to see who can devise the best robot players. And that has led to the creation of RoboCup, which has several leagues, both in the real world and simulated. In this new effort, the researchers applied a new degree of artificial intelligence programming and learning networks to teach simulated robots how to play soccer without ever giving them the rules.

The idea behind the new approach is to get simulated soccer players to learn to play the game the same way humans do—by watching how others do it. It also involved starting from pretty much ground zero. The simulated players first had to learn how to walk, then to run and kick a ball around. At each new level, the AI systems were shown video of real-world , which allowed them to learn not just the basics of soccer playing, but to mimic the way move as they engage in high level sporting events.

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Researchers from North Carolina State University used computational analysis to predict how optical properties of semiconductor material zinc selenide (ZnSe) change when doped with halogen elements, and found the predictions were confirmed by experimental results. Their method could speed the process of identifying and creating materials useful in quantum applications.

Creating semiconductors with desirable properties means taking advantage of point defects—sites within a material where an atom may be missing, or where there are impurities. By manipulating these sites in the material, often by adding different elements (a process referred to as “doping”), designers can elicit different properties.

“Defects are unavoidable, even in ‘pure’ ,” says Doug Irving, University Faculty Scholar and professor of materials science and engineering at NC State. “We want to interface with those spaces via doping to change certain properties of a material. But figuring out which elements to use in doping is time and labor intensive. If we could use a to predict these outcomes it would allow material engineers to focus on elements with the best potential.”

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The trial was only on 8 people, but it appears to have worked well across the board.

Published in GeroScience, a groundbreaking study from the renowned Conboy lab has confirmed that plasma dilution leads to systemic rejuvenation against multiple proteomic aspects of aging in human beings.

This paper takes the view that much of aging is driven by systemic molecular excess. Signaling molecules, antibodies, and toxins, which gradually accumulate out of control, cause cells to exhibit the gene expression that characterizes older cells.

While the bloodstreams of old and young mice have been joined in previous experiments with substantial effects [1], this heterochronic parabiosis approach is neither feasible nor necessary for human beings. Instead, this paper focuses on therapeutic plasma exchange (TPE), a procedure that simply replaces blood plasma with saline solution and albumin. This procedure has already been used to dilute pathogenic, toxic compounds [2], the systemic problems associated with autoimmune and neurological disorders, including Alzheimer’s [3], and even the lingering aftereffects of viral infection [4].

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