Results 51 to 60 of about 13,405 (259)

Artificial Intelligence for Studying Interactions of Solitons and Peakons

Mathematics
In this paper, Artificial Intelligence (AI) is developed for studying the Boussinesq Paradigm equation and so called b-equation based on Physics-Informed Cellular Neural Networks (PICNNs). The models studied here come from fluid dynamics.
Angela Slavova, Ventsislav Ignatov
doaj   +1 more source

Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks

IEEE Access, 2023
Physics-informed neural networks (PINNs) have emerged as a promising deep learning method, capable of solving forward and inverse problems governed by differential equations.
Franz M. Rohrhofer, Stefan Posch, Clemens Gobnitzer, Bernhard C. Geiger   +3 more
doaj   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source

Physics-Informed Neural Networks for Quantum Control

Physical Review Letters
Quantum control is a ubiquitous research field that has enabled physicists to delve into the dynamics and features of quantum systems, delivering powerful applications for various atomic, optical, mechanical, and solid-state systems. In recent years, traditional control techniques based on optimization processes have been translated into efficient ...
Ariel Norambuena, Marios Mattheakis, Francisco J. González, Raúl Coto   +3 more
openaire   +3 more sources

ALS With and Without Upper Motor Neuron Signs: A Comparative Study Supporting the Gold Coast Criteria

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The Gold Coast criteria permit diagnosis of amyotrophic lateral sclerosis (ALS) even without upper motor neuron (UMN) signs. However, whether ALS patients with UMN signs (ALSwUMN) and those without (ALSwoUMN) share similar characteristics and prognoses remains unclear.
Hee‐Jae Jung, E‐nae Cheong, Jungmin So, Heung‐Won Kang, Yangsean Choi, Eun‐Jae Lee, Hyunjin Kim, Young‐Min Lim   +7 more
wiley   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano, Giacomo Boffa, Maria Petracca, Marta Ponzano, Nicole Graziano, Claire Wigley, Claire Riley, Jonathan Howard, Pietro Bontempi, Sylvia Klineova, Fred Lublin, Matilde Inglese   +11 more
wiley   +1 more source

Towards Stable Training of Complex-Valued Physics-Informed Neural Networks: A Holomorphic Initialization Approach

Mathematics
This work introduces a new initialization scheme for complex-valued layers in physics-informed neural networks that use holomorphic activation functions.
Andrei-Ionuț Mohuț, Călin-Adrian Popa
doaj   +1 more source

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati, Sami I. Nassar, Shaun A. Nguyen, Patricia L. Gerend, Michael C. Schubert, Michael T. Teixido, Frederick A. Godley, Joel A. Goebel, Cynthia A. Ryan, Habib G. Rizk, Amir Kheradmand   +10 more
wiley   +1 more source

MODELING OF KOVAZHNY FLOW AND TAYLOR – GREEN VORTEX ON PHYSICS-INFORMED RADIAL BASIS FUNCTION NETWORKS

Модели, системы, сети в экономике, технике, природе и обществе
Background. An analysis of physics-informed neural networks for solving partial differential equations has been conducted, and the advantages of physics-informed radial basis function networks have been demonstrated.
Dmitry A. Stenkin
doaj   +1 more source