Simulation and Implementation of the Modeling of Forklift with Tricycle in Warehouse Systems for ROS. [PDF]
Tu KY, Hung CP, Lin HY, Lin KY.
europepmc +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
Use of SEM-PLS analysis to predict sports injuries in professional football players through warehouse technology data. [PDF]
Cheng F, Al-Hashimy HNH, Yao J.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Practice and challenges of humanitarian logistics management within the Ethiopian public pharmaceutical supply chain. [PDF]
Tufa BB, Tebeka SM.
europepmc +1 more source
Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar +5 more
wiley +1 more source
Evolving Inguinal Hernia Repair Practice at the Veterans Health Administration.
Bradley EM +3 more
europepmc +1 more source
The development and use of data warehousing in clinical settings: a scoping review. [PDF]
Lyu S, Craig S, O'Reilly G, Taniar D.
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source

