Results 231 to 240 of about 111,822 (311)
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary +1 more
wiley +1 more source
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley +1 more source
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley +1 more source
Soft robotic arms are promising for gentle grasping but often rely on bulky actuation systems. This work presents a computational design framework that optimizes tendon number and routing to achieve target grasps with fewer actuators. Validated on an octopus‐inspired underwater arm, the approach enables efficient, underactuated soft manipulators for ...
Michele Martini +6 more
wiley +1 more source
Context‐Aware Semiautonomous Control for Upper‐Limb Prostheses
A semiautonomous prosthetic control strategy integrates electromyographic‐based intention with computer vision‐driven grasp adaptation and wrist orientation. Comparative experiments with functional tasks evaluate performance, usability, and cognitive workload.
Gianmarco Cirelli +7 more
wiley +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
Terrestrial Cyborg Insects for Real‐Life Applications
This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le +10 more
wiley +1 more source
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source
Quantification of Temperature Dependence of Hydrogen Embrittlement in Pipeline Steel. [PDF]
Xing X +5 more
europepmc +1 more source
The 9th International RASopathies Symposium
ABSTRACT The RASopathies are a group of congenital disorders with overlapping clinical manifestations that are caused by pathogenic germline or early somatic variants that result in the hyperactivation of the RAS/mitogen‐activated protein kinase (MAPK) signaling pathway.
Pau Castel +41 more
wiley +1 more source

