Results 61 to 70 of about 1,653,373 (168)

PLOD1 Catalytic Activity Stabilizes ENO1 by Limiting FBXW7‐dependent Degradation to Promote Glycolysis and TMZ Resistance in Glioblastoma

open access: yesAdvanced Science, EarlyView.
PLOD1 interacts with ENO1 and limits its FBXW7‐dependent ubiquitination and proteasomal degradation through a mechanism requiring PLOD1 catalytic activity. ENO1 stabilization sustains glycolysis, promoting glioblastoma cell proliferation, migration, and temozolomide resistance.
Fen Xue   +4 more
wiley   +1 more source

Density and current of a dissipative Schrödinger operator [PDF]

open access: yes, 2002
A net current flow through an open 1-dimensional Schrödinger-Poisson system is modeled by replacing self-adjoint boundary conditions by dissipative ones.
Joachim Rehberg   +5 more
core   +1 more source

Energy-dependent noncommutative quantum mechanics

open access: yesEuropean Physical Journal C: Particles and Fields, 2019
We propose a model of dynamical noncommutative quantum mechanics in which the noncommutative strengths, describing the properties of the commutation relations of the coordinate and momenta, respectively, are arbitrary energy-dependent functions.
Tiberiu Harko, Shi-Dong Liang
doaj   +1 more source

Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections

open access: yesAdvanced Electronic Materials, EarlyView.
The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

Spurious Four-Wave Mixing Processes in Generalized Nonlinear Schrödinger Equations

open access: yes, 2023
Numerical solutions of a nonlinear Schrödinger equation may suffer from the spurious four-wave mixing processes. We study how these nonphysical resonances appear in solutions of a much more stiff generalized nonlinear Schrödinger equation with an ...
Bandelow, Uwe   +5 more
core   +1 more source

An estimate for solutions to the Schrodinger equation

open access: yesElectronic Journal of Differential Equations, 2004
In this note, we find a priori estimates in the $L_2$-norm for solutions to the Schrodinger equation with a parameter. It is shown that a constant occuring in the inequality does not depend on the value of the parameter.
Alexander Makin, Bevan Thompson
doaj  

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

open access: yesAdvanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz   +4 more
wiley   +1 more source

A random cloud model for the Schrödinger equation [PDF]

open access: yes, 2013
The paper is concerned with the construction of a stochastic model for the spatially discretized time-dependent Schrödinger equation. The model is based on a particle system with a Markov jump evolution. The particles are characterized by a sign (plus or
Wagner, Wolfgang
core   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath   +4 more
wiley   +1 more source

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