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Photon-Counting Computed Tomography (PCCT) is a novel imaging modality that simultaneously acquires volumetric data at multiple X-ray energy levels, generating separate volumes that capture energy-dependent attenuation properties.…

Human-Computer Interaction · Computer Science 2025-08-21 Mohit Sharma , Emma Nilsson , Martin Falk , Talha Bin Masood , Lee Jollans , Anders Persson , Tino Ebbers , Ingrid Hotz

Life-transformative applications such as immersive extended reality are revolutionizing wireless communications and computer vision (CV). This paper presents a novel framework for importance-aware adaptive data transmissions, designed…

Signal Processing · Electrical Eng. & Systems 2025-08-26 Chunmei Xu , Yi Ma , Rahim Tafazolli , Jiangzhou Wang

A methodology is developed to quantify the transfer and transport of kinetic energy of specific scales associated with coherent structures. Coherent motions are characterized by the triple decomposition of a multi-scale flow and used to…

Fluid Dynamics · Physics 2021-12-17 Daniel Foti

Porous and heterogeneous materials are found in many applications from composites, membranes, chemical reactors, and other engineered materials to biological matter and natural subsurface structures. In this work we propose an integrated…

Computational Physics · Physics 2019-09-15 Gianluca Boccardo , Eleonora Crevacore , Alberto Passalacqua , Matteo Icardi

Irregularly sampled multivariate time series (ISMTS) are prevalent in reality. Due to their non-uniform intervals between successive observations and varying sampling rates among series, the channel-independent (CI) strategy, which has been…

Machine Learning · Computer Science 2024-12-18 Jiexi Liu , Meng Cao , Songcan Chen

This article presents a priori error estimates of the miscible displacement of one compressible fluid by another in a porous medium. The study utilizes the $H(\rm div)$ conforming virtual element method (VEM) for the approximation of the…

Numerical Analysis · Mathematics 2024-05-13 Sarvesh Kumar , Devika Shylaja

This note presents a simulation method for investigating the relationship between porosity and particle size distribution in porous media characterization. The method simulates particle packing based on particle size distributions,…

Soft Condensed Matter · Physics 2024-09-25 Yuhe Wang

Cryopreservation via vitrification requires loading cryoprotective cocktails. Insufficient loading may lead to freezing, precluding successful recovery; overloading is toxic. Yet, existing in situ measurements of cryoprotectant permeation…

We develop a mathematical model for adsorption based on averaging the flow around, and diffusion inside, adsorbent particles in a column. The model involves three coupled partial differential equations for the contaminant concentration both…

Other Condensed Matter · Physics 2023-11-20 Lucy C. Auton , Maria Aguareles , Abel Valverde , Timothy G. Myers , Marc Calvo-Schwarzwalder

Numerical modeling of the migration of three-phase immiscible fluid flow in variably saturated zones is challenging due to the different behavior of the system between unsaturated and saturated zones. This behavior results in the use of…

Fluid Dynamics · Physics 2022-04-27 Alessandra Feo , Fulvio Celico

We present a general mechanistic model of mass diffusion for a composite sphere placed in a large ambient medium. The multi-layer problem is described by a system of diffusion equations coupled via interlayer boundary conditions such as…

Medical Physics · Physics 2018-01-17 Elliot J. Carr , Giuseppe Pontrelli

The predictions of the mode-coupling theory of the glass transition (MCT) for the tagged-particle density-correlation functions and the mean-squared displacement curves are compared quantitatively and in detail to results from Newtonian-…

Statistical Mechanics · Physics 2009-11-10 Th. Voigtmann , A. M. Puertas , M. Fuchs

The established macroscopic equations of motion for two phase immiscible displacement in porous media are known to be physically incomplete because they do not contain the surface tension and surface areas governing capillary phenomena.…

Materials Science · Physics 2009-10-31 R. Hilfer

Score-based diffusion models have significantly advanced generative deep learning for image processing. Measurement conditioned models have also been applied to inverse problems such as CT reconstruction. However, the conventional approach,…

Medical Physics · Physics 2025-02-24 Matthew Tivnan , Dufan Wu , Quanzheng Li

The dispersion of solute in porous media shows a non-linear increase in the transition from diffusion to advection dominated dispersion as the flow velocity is raised. In the past, the behavior in this intermediate regime has been explained…

Fluid Dynamics · Physics 2014-09-23 B. Ph. van Milligen , P. D. Bons

Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms,…

Methodology · Statistics 2017-08-21 Luca Faes , Daniele Marinazzo , Sebastiano Stramaglia

We propose a novel deep learning framework for predicting permeability of porous media from their digital images. Unlike convolutional neural networks, instead of feeding the whole image volume as inputs to the network, we model the…

Image and Video Processing · Electrical Eng. & Systems 2021-10-13 Ali Kashefi , Tapan Mukerji

Fluid antenna systems (FAS) enable unprecedented spatial diversity within a compact form factor by flexibly switching among high-density antenna ports. To activate this capability, channel state information (CSI) over the ports is required,…

Information Theory · Computer Science 2026-04-21 Zhentian Zhang , Hao Jiang , Kai-Kit Wong , Hyundong Shin , Ross Murch

The current conceptual model of mineral dissolution in porous media is comprised of three dissolution patterns (wormhole, compact, and uniform) - or regimes - that develop depending on the relative dominance of flow, diffusion, and reaction…

Fluid Dynamics · Physics 2023-03-20 Hannah P. Menke , Julien Maes , Sebastian Geiger

We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by…

Disordered Systems and Neural Networks · Physics 2019-10-23 X. L. Zhao , L. B. Fu
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