Results 81 to 90 of about 51,978 (203)
Quasi‐invariance of Gaussian measures for the 3d$3d$ energy critical nonlinear Schrödinger equation
Communications on Pure and Applied Mathematics, Volume 78, Issue 12, Page 2305-2353, December 2025.Abstract We consider the 3d$3d$ energy critical nonlinear Schrödinger equation with data distributed according to the Gaussian measure with covariance operator (1−Δ)−s$(1-\Delta)^{-s}$, where Δ$\Delta$ is the Laplace operator and s$s$ is sufficiently large. We prove that the flow sends full measure sets to full measure sets. We also discuss some simple
Chenmin Sun, Nikolay Tzvetkov
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Slags as Thermal Energy Storage Media for Concentrated Solar Power and Renewable Energy Integration
Energy Storage, Volume 7, Issue 8, December 2025.ABSTRACT The growing demand for low‐cost, high‐performance thermal energy storage (TES) materials has prompted interest in repurposing metallurgical slags in concentrated solar power (CSP) systems. This review critically evaluates the potential of various steel, copper, and aluminum slags as high‐temperature TES media in packed‐bed configurations ...
Michael Enemuo +3 more
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Understanding the development of bacterial colony: Physiology, new technology, and modeling
Quantitative Biology, Volume 13, Issue 4, December 2025.Abstract Bacterial colonies, as dynamic ecosystems, display intricate behaviors and organizational structures that profoundly influence their survival and functionality. These communities engage in physiological and social interactions, resulting in remarkable spatial heterogeneity.
Jingwen Zhu, Pan Chu, Xiongfei Fu
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Journal of Sustainable Agriculture and Environment, Volume 4, Issue 4, December 2025.ABSTRACT Shifting from conventional to sustainable agriculture demands well‐designed experiments and robust analytical models to evaluate agroecological system performance and resilience. We modelled aphid population dynamics in broccoli monocultures and broccoli‐basil intercrops using spatio‐temporal approaches, informed by laboratory experiments on ...
Rayana M. R. Carvalho +3 more
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Seismic Denoising by Deep Learning From Natural Repeating Earthquakes
Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.Abstract Effective seismic waveform denoising is crucial for advancing our understanding of Earth's subsurface structures and dynamics. Recently, deep learning‐based denoising methods have emerged and shown remarkable performance in improving the signal‐to‐noise ratio (SNR) of seismic waveforms.
Feiyi Wang, Yi Yang, Jianwei Ma
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Transactions of the London Mathematical Society, Volume 12, Issue 1, December 2025.Abstract We study convergence problems for the intermediate long wave (ILW) equation, with the depth parameter δ>0$\delta > 0$, in the deep‐water limit (δ→∞$\delta \rightarrow \infty$) and the shallow‐water limit (δ→0$\delta \rightarrow 0$) from a statistical point of view.
Guopeng Li, Tadahiro Oh, Guangqu Zheng
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On Bergman–Toeplitz operators in periodic planar domains
Transactions of the London Mathematical Society, Volume 12, Issue 1, December 2025.Abstract We study spectra of Toeplitz operators Ta$T_a$ with periodic symbols in Bergman spaces A2(Π)$A^2(\Pi)$ on unbounded singly periodic planar domains Π$\Pi$, which are defined as the union of infinitely many copies of the translated, bounded periodic cell ϖ$\varpi$.
Jari Taskinen
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Transactions of the London Mathematical Society, Volume 12, Issue 1, December 2025.Abstract In subwavelength physics, a challenging problem is to characterise the spectral properties of finite systems of subwavelength resonators. In particular, it is important to identify localised modes as well as bandgaps and associated mobility edges.
Habib Ammari +2 more
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Multi GPU Sparse Matrix by Sparse Matrix Multiplication
Concurrency and Computation: Practice and Experience, Volume 37, Issue 25-26, 30 November 2025.ABSTRACT The paper focuses on the improvement of the existing nsparse Nagasaka et al. algorithm and its extension to the multi‐GPU setting for the application of real engineering problems. In this work, we propose a distributed multi‐GPU framework for SpGEMM that is designed specifically for the nsparse like algorithms.
Artem Mavliutov +4 more
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A Physics‐Informed Learning Framework to Solve the Infinite‐Horizon Optimal Control Problem
International Journal of Robust and Nonlinear Control, Volume 35, Issue 16, Page 6932-6944, 10 November 2025.ABSTRACT We propose a physics‐informed neural networks (PINNs) framework to solve the infinite‐horizon optimal control problem of nonlinear systems. In particular, since PINNs are generally able to solve a class of partial differential equations (PDEs), they can be employed to learn the value function of the infinite‐horizon optimal control problem via
Filippos Fotiadis +1 more
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