Results 21 to 30 of about 588 (114)

Numerical Investigation of a Diffusive SIR Model: Focus on Positivity Preservation

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In this paper, we consider a system of semilinear partial differential equations (PDEs) representing a spatially extended SIR epidemic model. A brief analytical investigation of the well‐posedness and positivity of the solutions is provided in the appendix, while the main focus is on the numerical treatment of the model.
Rahele Mosleh, Claudia Panico, Messoud Efendiyev   +2 more
wiley   +1 more source

Nordgren PINNs to VQE: Advancing Hydraulic Fracturing Simulations in Shale Reservoirs

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT This study advances hydraulic fracturing simulations in shale reservoirs using two computational paradigms, Physics‐Informed Neural Networks (PINNs) and the Variational Quantum Eigensolver (VQE). PINNs were employed to solve Nordgren's equation, which governs fracture width evolution, by embedding physical laws into the neural network ...
Dennis Delali Kwesi Wayo, Sonny Irawan, Mohd Zulkifli Bin Mohamad Noor, Mudasar Zafar, Shynar Juziyeva, Camila Martins Saporetti, Leonardo Goliatt, Randy Hazlett   +7 more
wiley   +1 more source

Responsive nitric oxide‐releasing antibacterial materials for biofilm‐associated infections: Mechanisms, design strategies, and applications

Responsive Materials, EarlyView.
This review summarizes the recent progress in responsive NO‐releasing materials and their applications in biofilm‐associated infectious diseases. The design principles and response mechanisms are given to provide inspiration toward the future development of multi‐responsive NO‐releasing materials.
Wenyue Sun, Meiqi Li, Di Nan, Jiaqi Zhao, Yu Chen, Yao Gao, Shichen Zhang, Kirsten L. Van Landuyt, Manlin Qi   +8 more
wiley   +1 more source

Micro‐Mechanism Informed Neural Networks for Process‐Property Prediction in Laser Powder Bed Fusion

Artificial Intelligence for Engineering, EarlyView.
Hard physics embedding, where neural networks learn residuals relative to analytical baselines, substantially outperforms soft loss‐function constraints for extrapolation in LPBF process–property prediction. Physics integration architecture determines generalization capability more than constraint quantity.
Yo‐Lun Yang
wiley   +1 more source

New biosensors and transgenic mice for multiplex cGMP imaging

British Journal of Pharmacology, EarlyView.
Background and Purpose Cyclic guanosine monophosphate (cGMP) is a versatile second messenger that is important for human (patho‐)physiology and pharmacotherapy. Live‐cell imaging of cGMP with biosensors allows to elucidate its spatiotemporal dynamics in real time under close‐to‐native conditions. However, to monitor two separate cGMP pools or cGMP/cAMP
Markus Wolters, Martin Thunemann, Barbara Birk, Susanne Feil, Viacheslav O. Nikolaev, Moritz Lehners, Robert Feil   +6 more
wiley   +1 more source

PDE4D and PDE3B orchestrate distinct cAMP microdomains in 3T3‐L1 adipocytes

British Journal of Pharmacology, EarlyView.
Basal conditions: •Ins/PDE3B lowers cytoplasmic cAMP (cyt‐cAMP) without affecting plasma membrane cAMP (pm‐cAMP). •Insulin decreases lipid droplet cAMP (LD‐cAMP) independent of PDE3B. •FGF1/PDE4D modestly reduces both cyt‐ and pm‐cAMP, while PDE4D alone can modulate LD‐cAMP. ISO stimulation: •Ins/PDE3B has minimal impact on cyt‐cAMP.
Johannes Krier, David Spähn, David Arturo Juarez Lopez, Judith L. Nono, Judith Seigner, Lisa Jacob, Siegfried Ussar, Robert Lukowski, Andreas L. Birkenfeld, Gencer Sancar   +9 more
wiley   +1 more source

Differential segment‐specific signalling pathways for guanylate cyclase C‐activated anion secretion in murine ileocolon

British Journal of Pharmacology, EarlyView.
Abstract Background and Purpose Guanylate cyclase‐C (GC‐C) is the receptor for endogenous (uro)guanylin peptides, bacterial toxins and pharmacological analogues. Receptor activation leads to intestinal fluid loss, but also activates an antiproliferative pathway and is a promising target in colorectal cancer therapy.
Renjie Xiu, Johannes Reiner, Franz Hofmann, Azam Salari, Ursula Seidler   +4 more
wiley   +1 more source

Computing Skinning Weights via Convex Duality

Computer Graphics Forum, EarlyView.
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

Measure‐valued processes for energy markets

Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero, Luca Di Persio, Francesco Guida, Sara Svaluto‐Ferro   +3 more
wiley   +1 more source