JMIR Publications released a feature News and Perspectives story on AI fitness advice in its News and Perspectives section.

A Dartmouth study shows that where people look as they take in new environments could be as unique as a fingerprint and be used to identify them by the objects that have personal meaning. The researchers developed an AI model that correctly predicted where people would look first in unfamiliar settings based on how objects are thematically linked. The findings reveal how much we subjectively evaluate what's around us, while also suggesting that in a world of constant surveillance, we may be giving away more personal information than we realize.

Geological faults do not only move during earthquakes. Sometimes they slip silently, without generating noticeable shaking, releasing stress over hours or days. A research team led by Dr Zahra Zali (GFZ Helmholtz Centre for Geosciences), together with Prof. Patricia Martínez-Garzón (GFZ), Dr David Mencin (EarthScope), and Prof. Gregory C. Beroza (Stanford University), has uncovered a previously hidden population of so-called slow slip events beneath the Parkfield section of California’s San Andreas Fault. Using artificial intelligence and highly sensitive strainmeter observations, the researchers identified dozens of short-duration slow slip events and showed that these silent fault movements are systematically followed by increased low-frequency earthquake activity. The study has been published in Nature Communications.

Researchers at the U.S. Department of Energy’s Oak Ridge National Laboratory’s National (ORNL) Transportation Research Center have developed a novel electric motor drive design that meets the performance demands of aircraft, marine vessels and heavy-duty trucks while reducing excess heat and premature wear.