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Unidirectional wave propagation has emerged as a key concept in the dynamics of non-reciprocal mechanical and acoustic metamaterials. This work investigates two fundamentally distinct strategies for achieving directional wave propagation in…

Applied Physics · Physics 2026-05-29 João H. S. Brandão , Danilo Braghini , José R. F. Arruda

We propose a general multiscale approach for the mechanical behavior of three-dimensional networks of macromolecules undergoing strain-induced unfolding. Starting from a (statistically based) energetic analysis of the macromolecule…

Soft Condensed Matter · Physics 2015-06-22 Domenico De Tommasi , Giuseppe Puglisi , Giuseppe Saccomandi

Recent theoretical and experimental work in neuroscience has focused on the representational and dynamical character of neural manifolds --subspaces in neural activity space wherein many neurons coactivate. Importantly, neural populations…

Neurons and Cognition · Quantitative Biology 2024-10-21 Jacob Tanner , Sina Mansour L. , Ludovico Coletta , Alessandro Gozzi , Richard F. Betzel

We present a hybrid vertex/cell-centred model for mechanically simulating planar cellular monolayers undergoing cell reorganisation. Cell centres are represented by a triangular nodal network, while the cell boundaries are formed by an…

Cell Behavior · Quantitative Biology 2017-05-17 Payman Mosaffa , Antonio Rodríguez-Ferran , José J. Muñoz

Reinforced elastic sheets surround us in daily life, from concrete shell buildings to biological structures such as the arthropod exoskeleton or the venation network of dicotyledonous plant leaves. Natural structures are often highly…

Biological Physics · Physics 2021-01-27 Henrik Ronellenfitsch

Self-regulation of living tissue as an example of self-organization phenomena in active fractal systems of biological, ecological, and social nature is under consideration. The characteristic feature of these systems is the absence of any…

Tissues and Organs · Quantitative Biology 2008-12-02 Wassily Lubashevsky , Ihor Lubashevsky , Reinhard Mahnke

Nonlocal neural networks have been proposed and shown to be effective in several computer vision tasks, where the nonlocal operations can directly capture long-range dependencies in the feature space. In this paper, we study the nature of…

Machine Learning · Computer Science 2019-01-28 Yunzhe Tao , Qi Sun , Qiang Du , Wei Liu

We suggest a 3D phase field model to describe 3D cell spreading on a flat substrate. The model is a simplified version of a minimal model that was developed in [1]. Our model couples the order parameter $u$ with 3D polarization…

Biological Physics · Physics 2021-06-25 Mohammad Abu Hamed , Alexander A. Nepomnyashchy

A cellular model introduced for the evolution of the fluvial landscape is revisited using extensive numerical and scaling analyses. The basic network shapes and their recurrence especially in the aggregation structure are then addressed.…

Statistical Mechanics · Physics 2009-10-31 G. Caldarelli

Discrete-time modeling of acoustic, mechanical and electrical systems is a prominent topic in the musical signal processing literature. Such models are mostly derived by discretizing a mathematical model, given in terms of ordinary or…

We investigate the stability of self-propelled particle flocks in the Taylor-Green vortex, a steady vortical flow. We consider a model where particles align themselves to a combination of the orientation and the acceleration of particles…

Biological Physics · Physics 2016-07-13 Andrew W. Baggaley

We review continuum elastic models for the transmission of both external forces and internal active cellular forces in biopolymer gels, and relate them to recent experiments. Rather than being exhaustive, we focus on continuum elastic…

Soft Condensed Matter · Physics 2022-03-23 Haiqin Wang , Xinpeng Xu

We propose a continuum theory of the liquid-liquid phase separation in an elastic network where phase-separated microscopic droplets rich in one fluid component can form as an interplay of fluids mixing, droplet nucleation, network…

Soft Condensed Matter · Physics 2021-01-04 Xuefeng Wei , Jiajia Zhou , Yanting Wang , Fanlong Meng

Suppressing vibrations in mechanical systems, usually described by second-order dynamical models, is a challenging task in mechanical engineering in terms of computational resources even nowadays. One remedy is structure-preserving model…

Optimization and Control · Mathematics 2023-09-25 Rebekka S. Beddig , Peter Benner , Ines Dorschky , Timo Reis , Paul Schwerdtner , Matthias Voigt , Steffen W. R. Werner

We construct a homogeneous, nonlinear elastic constitutive law, that models aspects of the mechanical behavior of inhomogeneous fibrin networks. Fibers in such networks buckle when in compression. We model this as a loss of stiffness in…

Biological Physics · Physics 2015-12-18 Phoebus Rosakis , Jacob Notbohm , Guruswami Ravichandran

This study presents a fractional-order continuum mechanics approach that allows combining selected characteristics of nonlocal elasticity, typical of classical integral and gradient formulations, under a single frame-invariant framework.…

Numerical Analysis · Mathematics 2020-05-21 Sansit Patnaik , Sai Sidhardh , Fabio Semperlotti

We extend a recently introduced class of exactly solvable models for recurrent neural networks with competition between 1D nearest neighbour and infinite range information processing. We increase the potential for further frustration and…

Disordered Systems and Neural Networks · Physics 2009-10-31 N. S. Skantzos , A. C. C. Coolen

We use an elastic model to explore faceting of solid-wall vesicles with elastic heterogeneities. We show that faceting occurs in regions where the vesicle wall is softer, such as areas of reduced wall thicknesses or concentrated in…

Soft Condensed Matter · Physics 2012-05-30 Rastko Sknepnek , Monica Olvera de la Cruz

Animal cells use traction forces to sense the mechanics and geometry of their environment. Measuring these traction forces requires a workflow combining cell experiments, image processing and force reconstruction based on elasticity theory.…

Quantitative Methods · Quantitative Biology 2016-08-24 Jerome R. Soine , Nils Hersch , Georg Dreissen , Nico Hampe , Bernd Hoffmann , Rudolf Merkel , Ulrich S. Schwarz

Understanding the geometric properties of gradient descent dynamics is a key ingredient in deciphering the recent success of very large machine learning models. A striking observation is that trained over-parameterized models retain some…

Machine Learning · Computer Science 2024-07-11 Sibylle Marcotte , Rémi Gribonval , Gabriel Peyré