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Falling coffee filters are a common object of study in introductory physics laboratory classes. They are usually used to demonstrate the terminal velocity, and determine how the drag force depends on this velocity. However they can also be…

Fluid Dynamics · Physics 2022-07-01 Chandra Boyle , James Pantaleone

We study the initial evolution of the coffee ring that is formed by the evaporation of a thin, axisymmetric, surface tension-dominated droplet containing a dilute solute. When the solutal P\'{e}clet number is large, we show that diffusion…

Fluid Dynamics · Physics 2021-06-21 Matthew R. Moore , Dominic Vella , James M. Oliver

Stretching of a protein by a fluid flow is compared to that in a force-clamp apparatus. The comparison is made within a simple topology-based dynamical model of a protein in which the effects of the flow are implemented using Langevin…

Biomolecules · Quantitative Biology 2009-11-13 P. Szymczak , Marek Cieplak

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative sampling caused by the highly curved generative paths they learn. An important cause of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Nazir Nayal , Christopher Wewer , Jan Eric Lenssen

Diffusion models have demonstrated impressive image synthesis performance, yet many UNet-based models are trained at certain fixed resolutions. Their quality tends to degrade when generating images at out-of-training resolutions. We trace…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Jiaxuan Ren , Junhan Zhu , Huan Wang

A wide range of techniques exist for extracting the dominant flow dynamics and features about steady, or periodic base flows. However, there have been limited efforts in extracting the dominant dynamics about unsteady, aperiodic base flow.…

Fluid Dynamics · Physics 2025-06-05 Alec J. Linot , Barbara Lopez-Doriga , Yonghong Zhong , Kunihiko Taira

We consider the motion by curvature of a network of smooth curves with multiple junctions in the plane, that is, the geometric gradient flow associated to the length functional. Such a flow represents the evolution of a two--dimensional…

Analysis of PDEs · Mathematics 2007-05-23 Carlo Mantegazza , Matteo Novaga , Vincenzo Maria Tortorelli

High speed machining has been improved thanks to considerable advancement on the tools (optimum geometry, harder materials), on machined materials (increased workability and machining capacity for harder workpieces) and finally on the…

Classical Physics · Physics 2009-09-29 Olivier Cahuc , Alain Gérard

The possible transport of fibers by fluid flow in fractures is investigated experimentally in transparent models using flexible polyester thread (mean diameter $280 \mu\mathrm{m}$) and Newtonian and shear thinning fluids. In the case of…

In the preparation of Caf\'e Latte, spectacular layer formation can occur between the expresso shot in a glass of milk and the milk itself. Xue et al. (Nat. Commun., vol. 8, 2017, pp. 1-6) showed that the injection velocity of expresso…

Fluid Dynamics · Physics 2023-07-19 K. L. Chong , R. Yang , Q. Wang , R. Verzicco , D. Lohse

We present a study of the dynamics of a cup of coffee while walking with it in terms of a lumped model. The model considered is a planar (nonlinear) pendulum with parametric and direct excitation. The position of the pivot is changed with…

Classical Physics · Physics 2021-06-23 Nicolás Guarín-Zapata

Network pruning is a widely-used compression technique that is able to significantly scale down overparameterized models with minimal loss of accuracy. This paper shows that pruning may create or exacerbate disparate impacts. The paper…

Machine Learning · Computer Science 2022-10-14 Cuong Tran , Ferdinando Fioretto , Jung-Eun Kim , Rakshit Naidu

Grain segregation occurs under various conditions, such as vibration, shear and mixing. In the gravity-driven shear flow, size segregation is triggered by the percolation of small particles through the opened voids (kinetic sieving), and…

Adaptation and Self-Organizing Systems · Physics 2016-05-26 Lu Jing , C. Y. Kwok , Y. F. Leung

Deep neural networks have achieved exceptional results across a range of applications. As the demand for efficient and sparse deep learning models escalates, the significance of model compression, particularly pruning, is increasingly…

Machine Learning · Computer Science 2025-04-01 Yucong Dai , Gen Li , Feng Luo , Xiaolong Ma , Yongkai Wu

Top-down induction of decision trees has been observed to suffer from the inadequate functioning of the pruning phase. In particular, it is known that the size of the resulting tree grows linearly with the sample size, even though the…

Artificial Intelligence · Computer Science 2011-06-06 T. Elomaa , M. Kaariainen

Sampling a target probability distribution with an unknown normalization constant is a fundamental challenge in computational science and engineering. Recent work shows that algorithms derived by considering gradient flows in the space of…

Machine Learning · Statistics 2024-03-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M Stuart

Filters whose porosity decreases with depth are often more efficient at removing solute from a fluid than filters with a uniform porosity. We investigate this phenomenon via an extension of homogenization theory that accounts for a…

Fluid Dynamics · Physics 2016-02-11 Mohit P. Dalwadi , Ian M. Griffiths , Maria Bruna

Rectified flow (Liu et al., 2022; Liu, 2022; Wu et al., 2023) is a method for defining a transport map between two distributions, and enjoys popularity in machine learning, although theoretical results supporting the validity of these…

Statistics Theory · Mathematics 2025-12-11 Gonzalo Mena , Arun Kumar Kuchibhotla , Larry Wasserman

Recent advances in diffusion generative models have yielded remarkable progress. While the quality of generated content continues to improve, these models have grown considerably in size and complexity. This increasing computational burden…

Machine Learning · Computer Science 2025-03-13 Reza Shirkavand , Peiran Yu , Shangqian Gao , Gowthami Somepalli , Tom Goldstein , Heng Huang