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

Michael O. Lawanson, a Nigerian data scientist at the University of Arkansas, United States, is at the forefront of global ...

Objective To characterise the age-related impact of organ damage patterns on health-related quality of life (HRQoL) in ...

This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models (LMM). It ...

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Background The likelihood of HIV acquisition is increased following forced vaginal sex. This relates in part to ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

Abstract: Multiple inertial measurement unit (multi-IMU) fusion plays a crucial role in various applications requiring accurate motion estimation. This work presents a likelihood-based approach for ...

Abstract: We present a novel data-driven Parametric Linear Blend Skinning (PLBS) model meticulously crafted for generalized 3D garment dressing and animation. Previous data-driven methods are impeded ...

That tension becomes especially clear with heart rate zone training, a popular five-tier system that endurance athletes use ...

A research team has developed a low-cost, high-throughput phenotyping platform that continuously measures plant transpiration, enabling real-time monitoring of drought response.