Permafrost degradation poses a growing threat to infrastructure stability and ecosystem resilience in the rapidly warming Arctic. We investigated the spatiotemporal dynamics of active layer thickness ...

Dry farming systems in drylands are sensitive to climate extremes, resulting in large yield variability and posing challenges to food security. Reliable crop modeling approaches are therefore ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

OpenX, The Intelligent SSP, today announced the launch of OpenX IQ, a suite of proprietary AI and machine learning capabilities to give buyers greater quality, control, and performance across every ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has been sharped using a machine learning technique called PRIMO. PRIMO is short ...

As artificial intelligence continues to reshape biomedical research, data-driven methods are opening new possibilities for understanding complex inflammatory ...