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Metabolomics Pathway Prediction Using Enhanced-Graph Convolutional Networks with Graph Attention Networks

Metabolomics, the comprehensive study of small molecules in biological systems, has a central role to play in the diagnosis of diseases, biomarker detection, and the design of new drugs. Although there have been major breakthroughs in analytical toolsets
Natarajan, Jayapandian, Moozhippurath, Bineesh +1 more
core

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu +8 more
wiley +1 more source

KnvResGAT: SARS-CoV-2 sequence classification using k-mer natural vector and graph attention networks. [PDF]

BMC Res Notes
Yu W, Deng Y, Li Z, Dong W.
europepmc +1 more source

Demystifying Oversmoothing in Attention-Based Graph Neural Networks

Oversmoothing in Graph Neural Networks (GNNs) refers to the phenomenon where increasing network depth leads to homogeneous node representations. While previous work has established that Graph Convolutional Networks (GCNs) exponentially lose expressive ...
Wu, Zihui +3 more
core

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang +8 more
wiley +1 more source

Clustered Federated Spatio-Temporal Graph Attention Networks for Skeleton-Based Action Recognition. [PDF]

Sensors (Basel)
Yu T, Pinto S, Gomes T, Tavares A, Xu H.
europepmc +1 more source

Next‐Generation Water Treatment With Molybdenum Disulfide: Dual‐Functionality in Pollutant Adsorption and Photocatalysis

Advanced Materials Technologies, EarlyView.
ABSTRACT Molybdenum disulfide (MoS2) has attracted attention as a promising material due to the growing demand for environmentally friendly, cost‐effective, and efficient water treatment techniques. With its physicochemical characteristics, this stratified bidimensional material allows it to be highly effective in adsorption and catalytic performance ...
Pariksha Bishnoi +4 more
wiley +1 more source

Graph attention networks-based prediction of MicroRNA-disease causality in head and neck neoplasms. [PDF]

Sci Rep
Yadalam PK, Ayyachamy S, Natarajan PM, Ardila CM. +3 more
europepmc +1 more source

Highly Anisotropic Quasi‐Direct Organic Metal Halide Hybrids: A Platform for Polarization‐Sensitive Optoelectronics

Advanced Materials Technologies, EarlyView.
One‐dimensional C4N2H14PbBr4 is shown to have a quasi‐direct electronic band structure and strongly anisotropic transport with polarized broadband emission. A GW/Bethe–Salpeter excited‐state force formalism, supported by polarized Raman and temperature‐dependent photoluminescence, identifies low–frequency Pb–Br phonons that drive ultrafast exciton self‐
Rijan Karkee +7 more
wiley +1 more source

Cross-language hotel review sentiment analysis via multi-agent federated learning with heterogeneous graph attention networks. [PDF]

Sci Rep
Han X.
europepmc +1 more source

graph neural networks
attention mechanism
graph neural network

deep learning
graph attention network