Results 101 to 110 of about 223,632 (263)
Precision therapies for genetic epilepsies in 2025: Promises and pitfalls
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 +3 more
wiley +1 more source
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 +3 more
wiley +1 more source
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 +3 more
wiley +1 more source
Intraoperative Molecular Imaging Can Detect Large Nerve Perineural Invasion: A Case Report
ABSTRACT Background Perineural invasion (PNI) in head and neck squamous cell carcinoma (SCC) results in worse overall survival. Diagnosis requires resection and microscopic evaluation. Methods A 63‐year‐old male with persistent cT4aN0 p16‐positive SCC of the left base of tongue following chemoradiotherapy underwent salvage total glossectomy ...
Carleigh R. Burns +9 more
wiley +1 more source
This paper is a contribution to the Floquet ideas applied for multitime overdetermined linear first order PDE dynamical systems with multi- periodic coefficients.
Constantin Udrişte
doaj +1 more source
Geometry of PDEs. I: Integral bordism groups in PDEs
Global solutions of formally integrable and completely integrable systems of partial differential equations are characterized by means of integral bordism groups. Unfortunately, a thorough acquintance with the author's articles, namely with \textit{A. Prástaro} [Acta Appl. Math. 51, 243--302 (1998; Zbl 0924.58103) and Acta Appl. Math.
openaire +3 more sources
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
PDE-DKL: PDE-constrained deep kernel learning in high dimensionality
Many physics-informed machine learning methods for PDE-based problems rely on Gaussian processes (GPs) or neural networks (NNs). However, both face limitations when data are scarce and the dimensionality is high. Although GPs are known for their robust uncertainty quantification in low-dimensional settings, their computational complexity becomes ...
Yan, Weihao +2 more
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In this review, agents such baicalein, troxerutin, epigallocatechin gallate, quercetin, melatonin, valproic acid, lithium, neurosteroid progesterone, as well as minocycline have been implicated as neuroprotective agents for irradiation‐induced neurological deficits. Also, agents such as glucocorticoids, methylphenidate, vitamin E, bisdemethoxycurcumin,
Seidu A. Richard +2 more
wiley +1 more source
MU-LSM: latent spectral model based on multi-scale fusion and UNet
For partial differential equations (PDE), neural operators can learn the mapping of input and output functions in infinite dimensional Spaces by introducing kernel functions into linear transformations.
Jingjian Chen +4 more
doaj +1 more source

