Results 61 to 70 of about 11,005 (190)

Are physiological oscillations physiological?

The Journal of Physiology, EarlyView., 2023
Abstract figure legend Mechanisms and functions of physiological oscillations. Abstract Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function.
Lingyun (Ivy) Xiong, Alan Garfinkel
wiley   +1 more source

Lie Symmetry Methods for Multidimensional Linear, Parabolic PDES and Diffusions [PDF]

In this paper we introduce methods based upon Lie symmetry analysis for the construction of explicit fundamental solutions of multidimensional parabolic PDEs.
Kelly A. Lennox, Mark Craddock
core  

Advection‐Pressure Splitting Schemes Applied to a Non‐Conservative 1D Blood Flow Model With Transport for Arteries and Veins

International Journal for Numerical Methods in Fluids, EarlyView.
We introduce new efficient and accurate first order finite volume‐type numerical schemes, for the non‐conservative one‐dimensional blood flow equations with transport, taking into account different velocity profiles. The framework is the flux‐vector splitting approach of Toro and Vázquez‐Cendón (2012), that splits the system in two subsystems of PDEs ...
Alessandra Spilimbergo, Eleuterio F. Toro, Annunziato Siviglia, Lucas O. Müller   +3 more
wiley   +1 more source

Impact of Uncertain Parameters on Navier–Stokes Equations With Heat Transfer via Polynomial Chaos Expansion

International Journal for Numerical Methods in Fluids, EarlyView.
This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element‐Volume method.
N. Nouaime, B. Després, M. A. Puscas, C. Fiorini   +3 more
wiley   +1 more source

Direct Numerical Simulation of Magnetohydrodynamic Slip‐Flow Past a Stretching Surface Using Physics‐Informed Neural Network

Heat Transfer, EarlyView.
ABSTRACT Traditional numerical methods, such as finite difference methods (FDM), finite element methods (FEM), and spectral methods, often face meshing challenges and high computational cost for solving nonlinear coupled differential equations. Machine learning techniques, specifically Physics‐informed machine learning, address these obstacles by ...
Ahmad, Feroz Soomro, Husna Zafar
wiley   +1 more source

Artificial intelligence strategies for predicting kinase inhibitor resistance: A comprehensive review of methods, challenges, and future perspectives

Journal of Intelligent Medicine, EarlyView.
Abstract Kinase inhibitors are essential in targeted cancer therapy, yet resistance often emerges through secondary mutations, activation of compensatory signaling pathways, or drug‐efflux mechanisms. Artificial intelligence (AI) provides a workflow‐based strategy rather than a list of unrelated tools for predicting and addressing kinase‐inhibitor ...
Faris Hassan, Mohanad Ali Deifallah, Alaa Zaghloul, Rania Elgohary   +3 more
wiley   +1 more source

Coping Practices of Small‐ and Medium‐Sized Enterprises Facing Power Asymmetry in Digital Platform Business

Strategic Change, EarlyView.
ABSTRACT Digital platform (DP) enterprises have risen to the top of the global economy by inverting traditional business models. They earn money through matchmaking, transaction facilitation, and efficient orchestration of other stakeholders' resources.
Lukas R. G. Fitz, Jochen Scheeg
wiley   +1 more source

Using physics‐informed neural networks to quantify submarine groundwater discharge under high‐frequency tidal dynamics using heat as a tracer

Limnology and Oceanography: Methods, EarlyView.
Abstract Estimating exchange rates of submarine groundwater discharge (SGD) at high temporal resolution over extended periods remains challenging, particularly when using heat as a tracer in highly dynamic environments such as tidal systems. Currently available heat transport models struggle to accurately quantify SGD exchange rates in these settings ...
S. Frei, M. U. Munir, A. M. Seiverth, B. S. Gilfedder   +3 more
wiley   +1 more source

Unveiling New Perspectives on the Hirota–Maccari System With Multiplicative White Noise

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In this study, we delve into the stochastic Hirota–Maccari system, which is subjected to multiplicative noise according to the Itô sense. The stochastic Hirota–Maccari system is significant for its ability to accurately model how stochastic affects nonlinear wave propagation, providing valuable insights into complex systems like fluid dynamics
Mohamed E. M. Alngar, Khaled A. Gepreel, Reham M. A. Shohib, Yakup Yildirim   +3 more
wiley   +1 more source

On the Mean‐Field Limit of Consensus‐Based Methods

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT Consensus‐based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivative free sampling method referred to as consensus‐based sampling (CBS). In this paper, we investigate the “mean‐field limit” of a class of consensus methods, including
Marvin Koß, Simon Weissmann, Jakob Zech
wiley   +1 more source