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Theories of stellar convective core overshoot can be examined through analysis of pulsating stars. Better accuracy can be achieved by obtaining external constraints such as those provided by observing pulsating stars in eclipsing binary…

Solar and Stellar Astrophysics · Physics 2022-02-16 Padraic Odesse , Catherine Lovekin

We study the effect of spatially-varying potential and diffusivity on the dispersion of a tracer particle in single-file diffusion. Non-interacting particles in such a system exhibit normal diffusion at late times, which is characterised by…

Statistical Mechanics · Physics 2025-09-15 Benjamin Sorkin , David S. Dean

Methods for global measurement of transcript abundance such as microarrays and RNA-Seq generate datasets in which the number of measured features far exceeds the number of observations. Extracting biologically meaningful and experimentally…

Methodology · Statistics 2022-06-22 Lei Ding , Gabriel E. Zentner , Daniel J. McDonald

On the basis of input-output time-domain data collected from a complex simulator, this paper proposes a constructive methodology to infer a reduced-order linear, bilinear or quadratic time invariant dynamical model reproducing the…

Dynamical Systems · Mathematics 2020-12-15 Charles Poussot-Vassal , Tiphaine Sabatier , Claire Sarrat , Pierre Vuillemin

This paper develops new identification results for multidimensional continuous measurement-error models where all observed measurements are contaminated by potentially correlated errors and none provides an injective mapping of the latent…

Econometrics · Economics 2025-12-30 Yingyao Hu

Diffusion, a fundamental internal mechanism emerging in many physical processes, describes the interaction among different objects. In many learning tasks with limited training samples, the diffusion connects the labeled and unlabeled data…

Machine Learning · Computer Science 2023-05-02 Tangjun Wang , Zehao Dou , Chenglong Bao , Zuoqiang Shi

Exploring the vast composition space of multi-component alloys presents a challenging task for both \textit{ab initio} (first principles) and experimental methods due to the time-consuming procedures involved. This ultimately impedes the…

We investigate the obstructed motion of tracer (test) particles in crowded environments by carrying simulations of two-dimensional Gaussian random walk in model fibrinogen monolayers of different orientational ordering. The fibrinogen…

Chemical Physics · Physics 2014-03-14 Michał Cieśla , Ewa Gudowska-Nowak , Francesc Sagués , Igor M. Sokolov

In this article, a Probability Mass Function (PMF) estimation method which tames the curse of dimensionality is proposed. This method, called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D, has for principle to partially…

Signal Processing · Electrical Eng. & Systems 2025-09-08 Philippe Flores , Konstantin Usevich , David Brie

Tracer diffusion in crowded environments is central to many biological and soft matter systems, but quantitative frameworks for linking tracer motion to environmental structure remain limited. Here, we study the transport of rigid tracers…

Soft Condensed Matter · Physics 2026-05-07 Jinseok Lee , Tong Lin , Mengyang Gu , Yimin Luo

Mass transport of impurities immersed in a confined quasi-two-dimensional moderately dense granular gas of inelastic hard spheres is studied. The effect of the confinement on granular particles is modeled through a collisional model (the…

Soft Condensed Matter · Physics 2024-12-31 Rubén Gómez González , Vicente Garzó , Ricardo Brito , Rodrigo Soto

Most chemistry and cloud formation models for planetary atmospheres adopt a one-dimensional (1D) diffusion approach to approximate the global-mean vertical tracer transport. The physical underpinning of the key parameter in this framework,…

Earth and Planetary Astrophysics · Physics 2018-10-17 Xi Zhang , Adam P. Showman

In this paper, uniqueness properties of a coupled tensor model are studied. This new coupled tensor model is used in a new method called Partial Coupled Tensor Factorization of 3D marginals or PCTF3D. This method performs estimation of…

Signal Processing · Electrical Eng. & Systems 2025-09-08 Philippe Flores , Konstantin Usevich , David Brie

We consider inference of the parameters of the diffusion term for Cox-Ingersoll-Ross and similar processes with a power type dependence of the diffusion coefficient from the underlying process. We suggest some original pathwise estimates…

Probability · Mathematics 2017-04-12 Nikolai Dokuchaev

The standard setup for single-file diffusion is diffusing particles in one dimension which cannot overtake each other, where the dynamics of a tracer (tagged) particle is of main interest. In this article we generalise this system and…

Statistical Mechanics · Physics 2015-06-18 Robin Forsling , Lloyd Sanders , Tobias Ambjörnsson , Ludvig Lizana

Structure and dynamics at soft-matter interfaces play an important role in nature and technical applications. Optical single-molecule investigations are non-invasive and capable to reveal heterogeneities at the nanoscale. In this work we…

Crack Segmentation in industrial concrete surfaces is a challenging task because cracks usually exhibit intricate morphology with slender appearances. Traditional segmentation methods often struggle to accurately locate such cracks, leading…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Xianglong Shi , Yunhan Jiang , Xiaoheng Jiang , Mingling Xu , Yang Liu

Despite the huge advancement in knowledge discovery and data mining techniques, the X-ray diffraction (XRD) analysis process has mostly remained untouched and still involves manual investigation, comparison, and verification. Due to the…

Experiments on particles' motion in living cells show that it is often subdiffusive. This subdiffusion may be due to trapping, percolation-like structures, or viscoelatic behavior of the medium. While the models based on trapping (leading…

Disordered Systems and Neural Networks · Physics 2015-06-11 Yasmine Meroz , Igor M. Sokolov , Joseph Klafter

Accurate aerodynamic prediction often relies on high-fidelity simulations; however, their prohibitive computational costs severely limit their applicability in data-driven modeling. This limitation motivates the development of…

Machine Learning · Computer Science 2025-12-16 Javier Nieto-Centenero , Esther Andrés , Rodrigo Castellanos
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