News

If you wear a smart watch or fitness tracker, you're likely capturing an important but currently underused vital sign – resting heart rate – that soon may serve as a valuable window into your health, according to new study by the Scripps Research Translational Institute.

Researchers have made a breakthrough in the control of terahertz quantum cascade lasers, which could lead to the transmission of data at the rate of 100 gigabits per second - around one thousand times quicker than a fast Ethernet operating at 100 megabits a second.

Texas A&M researchers, along with computer scientists at Intel Labs, have designed a tool to identify the source of errors caused by software updates.

A team of researchers has developed a new set of machine learning algorithms and a software tool called PrintFixer to improve 3-D printing accuracy by 50 percent or more, making the process vastly more economical and sustainable.

When scientists and others use their specialized jargon terms while communicating with the general public, the effects are much worse than just making what they’re saying hard to understand.

A new study demonstrates that digital simulations of guitar amplifiers can sound just like the real thing. The implications are that as the software models continue to improve, they can replace traditional analogue guitar amplifiers, which are bulky, fragile and expensive.

Electrical engineers at Northwestern University and the University of Messina in Italy have developed a new magnetic memory device that could potentially support the surge of data-centric computing, which requires ever-increasing power, storage and speed.

A team has identified a neural signature that can predict whether individuals with depression are likely to benefit from the antidepressant sertraline.

Scientists from EMBL present a tool for large-scale analysis of genomic data with cloud computing. Main advantages of the new tool, called Butler, are continuous system monitoring and its ability to self-heal in case of failure, allowing for 43% more efficient data processing than previous approaches. The tool was developed for the Pan-Cancer project.

Researchers have designed an artificial intelligence (AI) model that is better able to predict how much students are learning in educational games. The improved model makes use of an AI training concept called multi-task learning, and could be used to improve both instruction and learning outcomes.