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Habituation - a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld - is universally observed in living systems from animals to unicellular…

Adaptation and Self-Organizing Systems · Physics 2024-07-26 Matthew Smart , Stanislav Y. Shvartsman , Martin Mönnigmann

We study a material modeled as a network of nodes connected by edges. Using a discrete approach, we build a nonlinear algebraic system that connects applied forces to internal forces and node positions. The model can describe elasticity,…

Optimization and Control · Mathematics 2025-10-14 Ioannis Dassios

Despite the importance of non-equilibrium statistical mechanics in modern physics and related fields, the topic is often omitted from undergraduate and core-graduate curricula. Key aspects of non-equilibrium physics, however, can be…

Statistical Mechanics · Physics 2021-11-03 Daniel M. Zuckerman , John D. Russo

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

A brief review of modeling and simulation methods for a study of polymers at interfaces is provided. When studying truly multiscale problems as provided by realistic polymer systems, coarse graining is practically unavoidable. In this…

Soft Condensed Matter · Physics 2009-10-19 Fathollah Varnik , Kurt Binder

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

Materials Science · Physics 2007-05-23 Thorsten Poeschel , Volkhard Buchholtz

Physical experiments can characterize the elastic response of granular materials in terms of macroscopic state-variables, namely volume (packing) fraction and stress, while the microstructure is not accessible and thus neglected. Here, by…

Soft Condensed Matter · Physics 2015-06-16 Nishant Kumar , Stefan Luding , Vanessa Magnanimo

Piecewise smooth hybrid systems, involving continuous and discrete variables, are suitable models for describing the multiscale regulatory machinery of the biological cells. In hybrid models, the discrete variables can switch on and off…

Computational Engineering, Finance, and Science · Computer Science 2012-08-21 Vincent Noel , Dima Grigoriev , Sergei Vakulenko , Ovidiu Radulescu

The purpose of this review is to analyze the physics at play in particle resuspension in order to bring insights into the rich complexity of this common but challenging concern. Following the more-is-different vision, this is performed by…

Fluid Dynamics · Physics 2023-04-05 Christophe Henry , Jean-Pierre Minier , Sara Brambilla

The macroscopic properties of materials that we observe and exploit in engineering application result from complex interactions between physics at multiple length and time scales: electronic, atomistic, defects, domains etc. Multiscale…

Biochars have been attracting renewed attention as economical and environmentally friendly carbon sequestration materials with a diverse range of applications. However, experimental developments may be limited by the lack of molecular-level…

Materials Science · Physics 2024-06-11 Rosie Wood , Ondrej Masek , Valentina Erastova

Mathematical models are increasingly used in both academia and the pharmaceutical industry to understand how phenotypes emerge from systems of molecular interactions. However, their current construction as monolithic sets of equations…

Molecular Networks · Quantitative Biology 2007-10-19 Aneil Mallavarapu , Matthew Thomson , Benjamin Ullian , Jeremy Gunawardena

Recent advances in deep learning frameworks have established valuable tools for analyzing the long-timescale behavior of complex systems such as proteins. Especially the inclusion of physical constraints, e.g. time-reversibility, was a…

Quantitative Methods · Quantitative Biology 2021-12-22 Andreas Mardt , Frank Noé

The main subject of this thesis rests on the study ---at different levels of description--- of instabilities in systems which are driven, i.e., maintained far from equilibrium by an external forcing. We focus here on two main classes,…

Statistical Mechanics · Physics 2011-06-08 Manuel Diez-Minguito

In this paper homogenization of a mathematical model for plant tissue biomechanics is presented. The microscopic model constitutes a strongly coupled system of reaction-diffusion-convection equations for chemical processes in plant cells,…

Analysis of PDEs · Mathematics 2017-08-24 Andrey Piatnitski , Mariya Ptashnyk

These are notes for a set of 7 two-hour lectures given at the 2010 Summer School on Quantitative Evolutionary and Comparative Genomics at OIST, Okinawa, Japan. The emphasis is on understanding how biological systems process information. We…

Molecular Networks · Quantitative Biology 2010-06-23 Gašper Tkačik

A microscopic model is proposed for the interactions between sickle hemoglobin molecules based on information from the protein data bank. A Monte Carlo simulation of a simplified two patch model is carried out, with the goal of…

Soft Condensed Matter · Physics 2009-11-11 Andrey Shiryayev , Xiaofei Li , James D. Gunton

Mathematical models are increasingly being used to understand complex biochemical systems, to analyze experimental data and make predictions about unobserved quantities. However, we rarely know how robust our conclusions are with respect to…

Molecular Networks · Quantitative Biology 2015-11-06 Elisenda Feliu , Carsten Wiuf

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen

Learning dynamical systems from sparse observations is critical in numerous fields, including biology, finance, and physics. Even if tackling such problems is standard in general information fusion, it remains challenging for contemporary…

Machine Learning · Computer Science 2024-06-04 Ella Tamir , Arno Solin