Results 71 to 80 of about 18,341 (302)

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

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

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, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Evaluation of Digital Technologies for Home‐Based Assessment in People With Amyotrophic Lateral Sclerosis

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, Vanessa Vallejo, Mónica Povedano Panadés, Orla Hardiman, Véronique Danel‐Brunaud, Senda Ajroud‐Driss, Philippe Couratier, Jeremy Shefner, Anna Gokey, Mike DiCesare, Erin Lennox, Jens Praestgaard, Lucie Brujin, Peggy Allred, Ram Miller   +14 more
wiley   +1 more source

Physics-informed neural networks for solving forward and inverse problems in complex beam systems

, 2023
This paper proposes a new framework using physics-informed neural networks (PINNs) to simulate complex structural systems that consist of single and double beams based on Euler-Bernoulli and Timoshenko theory, where the double beams are connected with a ...
Dollevoet, R.P.B.J. (author), Kapoor, Taniya, Kapoor, T. (author), Wang, Hongrui, Nunez, Alfredo (author), Nunez, Alfredo, Dollevoet, Rolf, Wang, H. (author)   +7 more
core   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

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, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Physics-informed neural networks for inviscid transonic flows around an airfoil

Physics-informed neural networks (PINNs) have gained popularity as a deep-learning-based parametric partial differential equation solver. Especially for engineering applications, this approach is promising because a single neural network (NN) could ...
Wassing, Simon, Bekemeyer, Philipp, Langer, Stefan   +2 more
core   +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, Tianjia Zhu, Hao Huang, Shavonne L. Massey, Mark P. Fitzgerald, Darshana Parikh, Arastoo Vossough, Ingo Helbig, Nicholas S. Abend   +8 more
wiley   +1 more source

Latent representation learning in physics-informed neural networks for full waveform inversion

Full waveform inversion (FWI), a state-of-the-art seismic inversion algorithm, comprises an iterative data-fitting process to recover high-resolution Earth’s properties (e.g., velocity).
Alkhalifah, Tariq Ali, Taufik, Mohammad Hasyim, Huang, Xinquan   +2 more
core   +1 more source

Magnetostatics and micromagnetics with physics informed neural networks

, 2022
Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated with neural networks.
Breth, Leoni, Schrefl, Thomas, Fischbacher, Johann; orcid:, Gusenbauer, Markus; orcid:, Oezelt, Harald, Kornell, Alexander, Hovorka, Markus, Kovacs, Alexander, Exl, Lukas; orcid:, Praetorius, Dirk; orcid:, Süss, Dieter   +10 more
core   +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