Results 11 to 20 of about 3,001 (111)

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

Advanced Science, EarlyView.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Thermal Conductance and Mass Transport of Brinkman‐Type Nanofluids Across Porous Plates: A Prabhakar‐Fractional Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The paper establishes an advanced computing algorithm to investigate the thermosolutal dynamics of an electrically conductive Brinkman‐type nanofluid that moves in a porous channel, and the fluid is acted on by an inclined magnetic field exerted externally.
Urwa Shehbaz, Umair Khan, MD. Shamshuddin, Nermeen Abdullah, Samia Elattar   +4 more
wiley   +1 more source

Transition to turbulence in wall-bounded flows: Where do we stand?

, 2016
In this essay, we recall the specificities of the transition to turbulence in wall-bounded flows and present recent achievements in the understanding of this problem.
Manneville, Paul
core   +1 more source

Addressing Small Data Challenges in Biopharmaceutical Development and Manufacturing: A Mini Review of Multi‐Fidelity Techniques

Biotechnology and Bioengineering, EarlyView.
ABSTRACT The growing demand for biopharmaceutical products reflects their effectiveness in medical treatments. However, developing new biopharmaceuticals remains a major bottleneck, often taking up to a decade before market approval. Machine learning (ML) models have the potential to accelerate this process, but their success depends on access to large
Mohammad Golzarijalal, Uwe Aickelin, Ellen Otte   +2 more
wiley   +1 more source

Max-Min characterization of the mountain pass energy level for a class of variational problems

, 2009
We provide a max-min characterization of the mountain pass energy level for a family of variational problems. As a consequence we deduce the mountain pass structure of solutions to suitable PDEs, whose existence follows from classical minimization ...
Bellazzini, Jacopo, Visciglia, Nicola
core   +1 more source

Precision therapies for genetic epilepsies in 2025: Promises and pitfalls

Epilepsia Open, EarlyView.
Abstract By targeting the underlying etiology, precision therapies offer an exciting paradigm shift to improve the stagnant outcomes of drug‐resistant epilepsies, including developmental and epileptic encephalopathies. Unlike conventional antiseizure medications (ASMs) which only treat the symptoms (seizures) but have no effect on the underlying ...
Shuyu Wang, Emilio Perucca, Samuel F. Berkovic, Piero Perucca   +3 more
wiley   +1 more source

Roughening of the (1+1) interfaces in two-component surface growth with an admixture of random deposition

, 2004
We simulate competitive two-component growth on a one dimensional substrate of $L$ sites. One component is a Poisson-type deposition that generates Kardar-Parisi-Zhang (KPZ) correlations. The other is random deposition (RD).
A. Kolakowska, A.-L. Barabasi, B. D. Lubachevsky, B. J. Overeiner, D. A. Jefferson, D. O’Connor, G. Korniss, G. Korniss, H. N. Yang, J. S. Steinman, K. M. Chandy, M. A. Novotny, M. A. Novotny, M. den Nijs, M. Kardar, M. Kotrla, M. Kotrla, P. M. Dickens, P. S. Verma, R. M. Fujimoto   +19 more
core   +1 more source

Fast Calculation for the Flow and Heat Transfer of Tempered Fractional Maxwell Viscoelastic Fluid

International Journal for Numerical Methods in Fluids, EarlyView.
This study develops a tempered fractional Maxwell model to simulate unsteady thermal flow in viscoelastic fluids, capturing key rheological behaviors. A fast SOE‐based algorithm is proposed to improve the computational efficiency of the numerical scheme. Results reveal how key parameters influence fluid motion and heat transfer, demonstrating the model'
Yi Liu, Mochen Jiang, Libo Feng
wiley   +1 more source

The Pearcey Process

, 2004
The extended Airy kernel describes the space-time correlation functions for the Airy process, which is the limiting process for a polynuclear growth model.
Tracy, Craig A., Widom, Harold
core   +1 more source