Results 211 to 220 of about 18,341 (302)

Dynamics and forecasting of an age-structured stochastic SIR model with Lévy perturbations via physics-informed neural networks. [PDF]

Infect Dis Model
Zhang G, Wang Z, Li Z, Chen S, Chen Q.
europepmc   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

Physics-Informed Neural Networks for Thermo-Responsive Hydrogel Swelling: Integrating Constitutive Models with Sparse Experimental Data. [PDF]

Materials (Basel)
Takmili SA, Choi E, Ostadrahimi A, Baghani M.   +3 more
europepmc   +1 more source

Upcycling Compact Discs Into Ultra‐Stable, Flexible, and Stretchable Nanoporous Gold Electrodes for Enhanced Biosensing Performance

Advanced Materials Technologies, EarlyView.
This article highlights the development of robust and high‐performance flexible and stretchable biosensors that maintain long‐term functionality and optimal electrical conductivity under mechanical deformation, utilizing sustainable and cost‐effective manufacturing principles.
Mousa H. Aldosari, Ahyeon Koh
wiley   +1 more source

Physics-informed neural networks for physiological signal processing and modeling: a narrative review. [PDF]

Physiol Meas
Zhao A, Fattahi D, Hu X.
europepmc   +1 more source

At Home Detection of Ovarian Health Biomarker in Menstruation Blood

Advanced Materials Technologies, EarlyView.
A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon, Thomas Rduch, Salma Sherif Azer, Inge K. Herrmann   +3 more
wiley   +1 more source

Thermodynamically consistent modeling of granular soils using physics-informed neural networks. [PDF]

Sci Rep
Irani N, Salimi M, Wichtmann T.
europepmc   +1 more source

Non‐Volatile Silicon Mach‐Zehnder Switches with 0.7 π Phase Shift Based on Graphene Heaters and Sb2Se3 Phase Change Material

Advanced Optical Materials, EarlyView.
ABSTRACT Photonic integrated circuits (PICs) can deliver unparalleled performance for future neuromorphic computing applications. Such neuromorphic PICs require a large number of tunable switches, which are typically realized with current‐controlled heaters, resulting in considerable energy consumption.
Jens Samland, Felix Hoff, Timo Veslin, Holger Lerch, Bartos Chmielak, Martin Otto, Caroline Porschatis, Bárbara Canto, Stephan Suckow, Matthias Wuttig, Max C. Lemme   +10 more
wiley   +1 more source

Time-Varying Autoregressive Models: A Novel Approach Using Physics-Informed Neural Networks. [PDF]

Entropy (Basel)
Jia Z, Zhang C.
europepmc   +1 more source

Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning

Advanced Optical Materials, EarlyView.
Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam, Chan Y. Park, Min Seok Jang   +2 more
wiley   +1 more source