Tadeo Ramirez-Parada studied the timing of plant flowering for his PhD — but he didn’t touch a single petal. Instead, he ...

Artificial intelligence is changing how we predict river flow—but a new study led by researchers at the University of British ...

Earth system box models are essential tools for reconstructing long-term climatic and environmental evolution and uncovering ...

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient ...

Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

Objective To examine whether a multicomponent commercial fitness app with very small (‘micro’) financial incentives (FI) ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

What if artificial intelligence could turn centuries of scientific literature—and just a few lab experiments—into a smarter, ...

Abstract: One-shot devices, such as automotive airbags, fire extinguishers and ammunitions, pose significant challenges in their reliability analysis due to their inherently unobservable lifespans.

Abstract: This paper proposes a data-driven bidding algorithm for virtual power plants (VPPs) based on photovoltaic (PV) and wind energy sources to maximize revenue in the Korean electricity market, ...