graph neural networks

Beyond direct AI exposure: Measuring network-mediated labor risk through multilayer occupational networks

Data‐Driven Spectral Prediction for Accelerating Large‐Scale Electronic Structure Calculations

ABSTRACT Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architecture...

Optimization of Resource Allocation in 5G Networks Using Game Theory-Based Algorithms

Experimental results on a realistic 5G QoS dataset demonstrate significant improvements over baseline methods, including higher throughput, lower latency, improved fairness, reduced packet loss, and enhanced energy efficiency, confirming the framework's scalability and QoS awareness.

An Edge-Deployable Lightweight Dynamic Spatio-Temporal Graph Neural Network for Joint Distribution-Network Line-Loss Prediction and Operating-State Recognition

A lightweight dynamic spatio-temporal graph neural network, EdgeLite-DSTGNN, is proposed to address the intensified spatio-temporal coupling of line-loss rates, complex state correlations, and limited edge-terminal resources in distribution networks with high renewable-energy penetration. The method treats branches as...

Revealing environmental associations underlying seasonal distribution of Pacific yellowfin tuna species with geospatial neural networks

Yellowfin tuna ( Thunnus albacares ) is a highly migratory and economically important species in the Pacific Ocean, and its spatial distribution is closely associated with marine environmental conditions. To investigate the environmental associations underlying the spatial patterns of yellowfin tuna nominal catch per u...

Mechanism-aware and safety-validated AI for drug repurposing: a critical review and translational pharmacology framework

Background Artificial intelligence (AI)-assisted drug repurposing seeks to identify new therapeutic applications for existing drugs. Nevertheless, most of the existing studies are centered on prediction scores and candidate ranking, and there is still relatively little attention paid to the pharmacological mechanisms,...

A novel FedLLM intrusion detection framework for privacy-preserving security in IoT enabled smart city network

Editorial: Exploring neuropsychiatric disorders through multimodal MRI: network analysis, biomarker discovery, and clinical insights

The research included in this Research Topic span a broad range of conditions, including neurodevelopmental disorders, psychiatric disorders, neurodegenerative diseases, infection-related brain injury, pain-related disorders, disorders of consciousness, and spinal disorders affecting the nervous system. Despite the div...

Harmonizing Predictive Accuracy and Cooperative Outcomes in Game-Theoretic Systems

This paper examines the intricate relationship between predictive accuracy and collective welfare in scenarios where forecasts actively influence individual behaviors. We propose a novel framework in which predictions lead to Nash equilibria that can either prioritize precise outcomes or foster broader social benefits...

Big Data-Driven Production Scheduling Risk Identification Using a Lightweight Adaptive Graph Attention Network.

The advancement of Industry 4.0 and smart manufacturing has led to the generation of high-volume, multisource data that evolve in real-time within production scheduling systems. This poses significant challenges to traditional risk identification methods. Models that ignore topological relationships lack robustness whe...

A Physics-First Hamiltonian Latent Model for Twelve Universality Classes of Fluid Behaviour

FEM-ANN-GNN modeling of MHD Darcy–Forchheimer Boger nanofluid flow with coupled heat–mass transfer in a Y-shaped hourglass cavity

Purpose This study aims to numerically investigate steady two-dimensional MHD Darcy–Forchheimer mixed convection flow of a Boger nanofluid (Cu/H2O) with coupled heat and mass transfer inside a Y-shaped hourglass cavity containing a cylindrical obstacle, incorporating thermal radiation, Cattaneo–Christov heat flux, Sore...