Coastal and nearshore zones face growing pressure from storms, flooding, erosion, and sea-level rise, which threaten civil infrastructure such as ports, ...

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

Government agencies face increasingly sophisticated security challenges in a world driven by digital transformation.

Machine learning helped identify new superconductors and a process that could speed the discovery of thousands more ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Researchers have discovered two new superconductors using a machine learning-based screening method, demonstrating a ...

Two newly discovered superconductors highlight the potential of machine learning to accelerate materials discovery.