Effect of a Modern Palaeolithic Diet in Combination with a Sprint Interval Training on Metabolic and Performance-Related Parameters in Male Athletes: A Pilot Trial. [PDF]
Zdzieblik D +4 more
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Sprint interval training in the postpartum period maintains the enhanced cardiac output of pregnancy: A case study. [PDF]
Richard N, Claydon V, Koehle M, Coté A.
europepmc +1 more source
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
Distinct lipidomic profiles but similar improvements in aerobic capacity following sprint interval training versus moderate-intensity continuous training in male adolescents. [PDF]
Su W +8 more
europepmc +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Sprint Interval Training Improves Brain-Derived Neurotropic Factor-Induced Benefits in Brain Health-A Possible Molecular Signaling Intervention. [PDF]
Zhu X, Chen W, Thirupathi A.
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience
An automated robotic system is described for rapid scientific experimentation with multicellular organisms. By enhancing a robotic liquid handler with a custom developed deep learning algorithm and camera module, samples and data are prepared with minimal human intervention.
Mark A. DeAngelis +2 more
wiley +1 more source
This study presents a compact, three IMU wearable system that enables accurate motion capture and robust gait‐feature extraction, thereby supporting reliable machine learning‐based balance evaluation. Accurate assessment of balance is critical for fall prevention and targeted rehabilitation, particularly in older adults and individuals with ...
Seok‐Hoon Choi +8 more
wiley +1 more source

