Results 181 to 190 of about 977,116 (306)
Robust detection framework for adversarial threats in Autonomous Vehicle Platooning. [PDF]
Ness S.
europepmc +1 more source
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak +14 more
wiley +1 more source
A cost-effective image-based machine learning framework for automating active iron estimation in Peach (Prunus persica (L.) Batsch) Leaves. [PDF]
Imani A, Sepehr E, Rengel Z, Hajizade N.
europepmc +1 more source
An epi‐intraneural interface is developed through in silico optimization and a novel tridimensional microfabrication pipeline. The device integrates penetrating and epineural contacts on a flexible substrate. Mechanical, electrochemical, and in vivo testing in rat and pig reveal robust implantation, low‐threshold activation, and site‐dependent ...
Federico Ciotti +14 more
wiley +1 more source
Detection and classification of venous thromboembolism through image test reports analysis using active learning and deep learning. [PDF]
Jeong E, Woo Y, Lee HJ, Kim JY.
europepmc +1 more source
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken +6 more
wiley +1 more source
Validation and interpretation of machine-learning models for rapid identification of active tuberculosis infection using routine laboratory indicators. [PDF]
Liu ZZ +8 more
europepmc +1 more source
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy +3 more
wiley +1 more source
Identification of risk factors for latent tuberculosis infection in Xinjiang using machine learning. [PDF]
Wang Y +6 more
europepmc +1 more source
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley +1 more source

