Machine-learning analysis of X-ray data picks out key catalytic properties

Scientists seeking to design new catalysts to convert carbon dioxide (CO2) to methane have used a novel artificial intelligence (AI) approach to identify key catalytic properties. By using this method to track the size, structure, and chemistry of catalytic particles under real reaction conditions, the scientists can identify which properties correspond to the best catalytic performance, and then use that information to guide the design of more efficient catalysts.

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Pushy robots learn the fundamentals of object manipulation

Researchers have compiled a dataset that captures the detailed behavior of a robotic system physically pushing hundreds of different objects. Using the dataset — the largest and most diverse of its kind — researchers can train robots to 'learn' pushing dynamics that are fundamental to many complex object-manipulation tasks, including reorienting and inspecting objects, and uncluttering scenes.

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Browser tool aims to help researchers ID malicious websites, code

Researchers have developed an open-source tool that allows users to track and record the behavior of JavaScript programs without alerting the websites that run those programs. The tool, called VisibleV8, runs in the Chrome browser and is designed to detect malicious programs that are capable of evading existing malware detection systems.

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Listening in to how proteins talk and learning their language

A research team has created a third approach to engineering proteins that uses deep learning to distill the fundamental features of proteins directly from their amino acid sequence without the need for additional information.

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Model system for distribution of more accurate time signals

Physicists have demonstrated the first next-generation 'time scale' — a system that incorporates data from multiple atomic clocks to produce a single highly accurate timekeeping signal for distribution. The new time scale outperforms the best existing hubs for disseminating official time worldwide and offers the possibility of providing more accurate time to millions of customers such as financial markets and computer and phone networks.

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Land management practices to reduce nitrogen load may be affected by climate changes

Nitrogen from agricultural production is a major cause of pollution in the Mississippi River Basin and contributes to large dead zones in the Gulf of Mexico. Illinois and other Midwestern states have set goals to reduce nitrogen load through strategies that include different land management practices. A new study uses computer modeling to estimate how those practices may be affected by potential changes in the climate, such as increased rainfall.

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