A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...
Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...
What was the rationale behind applying machine learning (ML) models to improve identification probability in the absence of ...
Built on a new architecture KumoRFM-2 achieves state-of-the-art results across 41 predictive tasks and four major benchmarks, ...
Researchers have developed a multi-fidelity framework for lithium-ion battery lifespan prediction that combines coupled ...
Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...
Web3 is looking at a similar trajectory. The industry is pivoting from theoretical musings to measurable utility in 2026, ...
A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...
Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
Researchers developed an AI model that stabilizes molecular simulations under extreme conditions, enabling long, accurate ...
The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, necessitates innovative approaches to resource management. Biomass, a versatile ...
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