Results 71 to 80 of about 8,084,029 (292)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
IEEE Open Access Journal of Power and EnergyAccurate estimation of dynamic parameters of generators is crucial for constructing high-fidelity models for dynamic studies and ensuring the reliable operation of power systems.
Koji Yamashita, Nanpeng Yu
doaj +1 more source
Physics-informed neural network reconciles Australian displacements and tectonic stresses
Scientific Reports, 2023 Stress orientation information is invaluable to evaluate active tectonic forces within the Earth’s crust. The global dataset provided by the World Stress Map offers a rich resource of stress indicators, facilitating the calibration of mechanical models ...
Thomas Poulet, Pouria Behnoudfar
doaj +1 more source
Bayesian reasoning for physics-informed neural networks
Physical Review E21 pages, 12 figures, re-edit the description of the Bayesian framework, some of the content moved to Appendix.
Krzysztof M. Graczyk, Kornel Witkowski
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source
Physics-informed neural network modeling of soliton pulses in optical communication systems [PDF]
, 2022 The nonlinear Schrodinger equation which models the pulse propagation in an optical fiber is solved using a physics-informed neural network for the case of soliton propagation.
Leeson, Mark S. +3 more
core +1 more source
A Short Note on Physics-Guided GAN to Learn Physical Models without Gradients
AlgorithmsThis study briefly describes the concept of guided training of deep neural networks (DNNs) to learn physically reasonable solutions. The proposed method does not need the gradients of the physical equations, although the conventional physics-informed ...
Kazuo Yonekura
doaj +1 more source
PND: Physics-informed neural-network software for molecular dynamics applications
SoftwareX, 2021 We have developed PND, a differential equation solver software based on a physics-informed neural network (PINN) for molecular dynamics simulators. Based on automatic differentiation technique provided by PyTorch, our software allows users to flexibly ...
Taufeq Mohammed Razakh +6 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe +7 more
wiley +1 more source
White Matter Microstructural Abnormalities in Neonatal Onset Genetic Epilepsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Recent evidence indicates that epilepsy is associated with abnormal white matter. If seizures alter white matter, then the impact upon network function, epileptogenesis, and cognition could be pronounced in neonates undergoing rapid developmental myelination. Neonates with epilepsy due to nonstructural genetic causes provide a unique
Amanda G. Sandoval Karamian +8 more
wiley +1 more source