Results 101 to 110 of about 120,010 (245)

A spatial–temporal normalization framework for Fourier-enhanced physics-informed deep learning in large-scale wave propagation

Discover Computing
Physics-informed neural networks (PINNs) have emerged as promising artificial intelligence-driven approaches for solving wave propagation equations in scientific and engineering applications such as seismic simulation, fluid dynamics, and ...
Jichao Ma, Dandan Liu, Xi’an Li, Yayong Li, Jinran Wu   +4 more
doaj   +1 more source

A Graph-Structured, Physics-Informed DeepONet Neural Network for Complex Structural Analysis

Machine Learning and Knowledge Extraction
This study introduces the Graph-Structured Physics-Informed DeepONet (GS-PI-DeepONet), a novel neural network framework designed to address the challenges of solving parametric Partial Differential Equations (PDEs) in structural analysis, particularly ...
Guangya Zhang, Tie Xu, Jinli Xu, Hu Wang
doaj   +1 more source

Blood RNA Biomarker Signatures for Early Diagnosis and Prognosis in Ischemic and Hemorrhagic Stroke: The IBIS‐CT1 Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau, Marie Bruguet, Irina Viakhireva‐Dovganyuk, François‐Mathias Merrien, Denis Marechal, Aurore Jourdain, Philippe Goas, Jordan Coris, Julien Asselineau, Maëlys Consigny, Gérald Le Gac, Serge Timsit   +11 more
wiley   +1 more source

A Scattering-Parameter Diagnostic Framework for Monitoring Convergence in Neural Experience Engines

 Neural learning is often described as iterative parameter adaptation; however, such descriptions rarely capture the structural stabilization of knowledge. Building upon previous work[1]demonstrating convergence toward stable automorphisms in probability distribution spaces, this study introduces a diagnostic framework based on Scattering Parameters (S-
openaire   +2 more sources

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

LKG-RiskNet: legal knowledge-guided graph neural networks for data security risk prediction in cyber-physical power systems

Journal of Engineering and Applied Science
Data generated by cyber-physical infrastructures—such as smart grids, renewable-energy plants, electric-vehicle (EV) platforms, and industrial IoT—has become a core operational asset.
A. Rong, Shikai Wang
doaj   +1 more source

RosenPy: An open source Python framework for complex-valued neural networks

SoftwareX
Deep learning is an essential artificial intelligence tool broadly used in engineering, physics, data science, biology, healthcare, agribusiness, finance, and many other areas.
Ariadne A. Cruz, Kayol S. Mayer, Dalton S. Arantes   +2 more
doaj   +1 more source

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias, Federica Avantaggiato, Gianni Pezzoli, Andrea Canessa   +3 more
wiley   +1 more source

Temporal Interference Stimulation of Centromedian‐Parafascicular Complex in Disorders of Consciousness: A Pilot Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu, Changgeng Song, Dianwei Wu, Xiaoqian Niu, Jianmin Hao, Lijuan Liu, Xiaogang Kang, Wen Jiang   +7 more
wiley   +1 more source

Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad, Pouya Metanat, Michael Thomas, Luke W. Bonham, Tyson Lam, Mehmet Kurt, Hong Nguyen, Tara Ellingson, Mauro Zucchelli, Stefano Casagranda, Quin Lu, Andreas M. Rauschecker, Leo Sugrue, Luis E. Savastano, Christopher P. Hess, Kamalini Ranasinghe, S. Andrew Josephson, Bruce L. Miller, Jennifer S. Yokoyama, Gil D. Rabinovici, Peter A. Ljubenkov, Lawren VandeVrede, Kambiz Nael   +22 more
wiley   +1 more source