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Statistical and mathematical modeling are crucial to describe, interpret, compare and predict the behavior of complex biological systems including the organization of hematopoietic stem and progenitor cells in the bone marrow environment.…

Quantitative Methods · Quantitative Biology 2018-09-07 Walter de Back , Thomas Zerjatke , Ingo Roeder

Limited throughput is a key challenge in in-vivo deep-tissue imaging using nonlinear optical microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow especially compared to the wide-field imaging modalities used…

Image and Video Processing · Electrical Eng. & Systems 2022-12-26 Navodini Wijethilake , Mithunjha Anandakumar , Cheng Zheng , Peter T. C. So , Murat Yildirim , Dushan N. Wadduwage

We studied the step dynamics during crystal sublimation and growth in the limit of fast surface diffusion and slow kinetics of atom attachment-detachment at the steps. For this limit we formulate a model free of the quasi-static…

Chemical Physics · Physics 2009-11-13 Bogdan Ranguelov , Stoyan Stoyanov

When analyzing thermodynamic and kinetic properties of crystals whose anisotropy is not large and the considered effects do not relate to the existence of singled-out directions in crystals, one may use a more simple model of an isotropic…

Statistical Mechanics · Physics 2020-04-15 Yu. M. Poluektov

Streamline classification is essential to identify anatomically meaningful white matter tracts from diffusion MRI (dMRI) tractography. However, current streamline classification methods rely primarily on the geometric features of the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Haotian Yan , Bocheng Guo , Jianzhong He , Nir A. Sochen , Ofer Pasternak , Lauren J O'Donnell , Fan Zhang

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

The performance of flow matching and diffusion models can be greatly improved at inference time using reward alignment algorithms, yet efficiency remains a major limitation. While several algorithms were proposed, we demonstrate that a…

Machine Learning · Computer Science 2026-02-12 Peter Holderrieth , Uriel Singer , Tommi Jaakkola , Ricky T. Q. Chen , Yaron Lipman , Brian Karrer

The analysis of the size distribution of droplets condensing on a substrate (breath figures) is a test ground for scaling theories. Here, we show that a faithful description of these distributions must explicitly deal with the growth…

Statistical Mechanics · Physics 2012-09-04 Johannes Blaschke , Tobias Lapp , Björn Hof , Jürgen Vollmer

It is often stated that if one is presented with a snapshot of the positions of the molecules of a glass and one of a liquid, one is unable to tell the difference. Here we argue instead that given several such snapshots taken over a…

Disordered Systems and Neural Networks · Physics 2024-02-08 Ittai Fraenkel , Jorge Kurchan , Dov Levine

Solidification is an important process in many alloy processing routes. The solidified microstructure of alloys is usually made up of dendrites, eutectics or a combination of both. The evolving morphologies are largely determined by the…

Materials Science · Physics 2024-12-17 Marco Seiz , Michael Kellner , Britta Nestler

Aligning diffusion models to downstream tasks often requires finetuning new models or gradient-based guidance at inference time to enable sampling from the reward-tilted posterior. In this work, we explore a simple inference-time…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Anuj Singh , Sayak Mukherjee , Ahmad Beirami , Hadi Jamali-Rad

This paper is devoted to the micro-mechanical origins of the high compressibility of brittle tubular particle assemblies. The material is extremely porous due to the presence of a large hole within the tube-shaped particle. The release of…

Materials Science · Physics 2021-10-26 M. Stasiak , G. Combe , V. Richefeu , G. Armand , J. Zghondi

This study aims to relate the time-frequency patterns of acoustic emission (AE) and other multi-modal sensor data collected in a hybrid directed energy deposition (DED) process to the pore formations at high spatial (0.5 mm) and time (<…

We derive mathematical models of the elementary process of dissolution/growth of bubbles in a liquid under pressure control. The modeling starts with a fully compressible version, both for the liquid and the gas phase so that the entropy…

Fluid Dynamics · Physics 2014-03-04 Dieter Bothe , Kohei Soga

Cell deformability is an essential determinant for tissue-scale mechanical nature, such as fluidity and rigidity, and is thus crucial for understanding tissue homeostasis and stable developmental processes. However, numerical simulations…

Tissues and Organs · Quantitative Biology 2023-03-08 Nen Saito , Shuji Ishihara

We analytically and numerically study a fourth order PDE modeling rough crystal surface diffusion on the macroscopic level. We discuss existence of solutions globally in time and long time dynamics for the PDE model. The PDE, originally…

Analysis of PDEs · Mathematics 2022-11-09 Yuan Gao , Anya E. Katsevich , Jian-Guo Liu , Jianfeng Lu , Jeremy L. Marzuola

Purpose: Electron density is the most important tissue property influencing photon and ion dose distributions in radiotherapy patients. Dual-energy computed tomography (DECT) enables the determination of electron density by combining the…

Medical Physics · Physics 2017-06-29 Christian Möhler , Patrick Wohlfahrt , Christian Richter , Steffen Greilich

Double Exponential Smoothing (DES) has broad application in various fields primarily as a forecasting tool. The values of the two smoothing parameters and , involved in DES, are traditionally chosen by the users which yield minimum MSE. In…

Signal Processing · Electrical Eng. & Systems 2020-02-25 Moloy Mukherjee , Dipta Chaudhuri , Mofazzal H. Khondekar , Koushik Ghosh

We analyse how the sampling dynamics of distributions evolve in score-based diffusion models using cross-fluctuations, a centered-moment statistic from statistical physics. Specifically, we show that starting from an unbiased isotropic…

Machine Learning · Computer Science 2026-05-04 Sai Niranjan Ramachandran , Manish Krishan Lal , Suvrit Sra

A standard model for the study of scalar dispersion through advection and molecular diffusion is a two-dimensional periodic flow with closed streamlines inside periodic cells. Over long time scales, the dispersion of a scalar in this flow…

Fluid Dynamics · Physics 2015-06-18 P. H. Haynes , J. Vanneste
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