Machine learning techniques have been used to quantify the relationship between local structural features and variations in local dynamical activity in disordered glass-forming materials. To date these methods have been applied to an array of standard (Arrhenius and super-Arrhenius) glass formers, where work on "soft spots" indicates a connection between the linear vibrational response of a configuration and the energy barriers to non-linear deformations. Here we study the Voronoi model, which takes its inspiration from dense epithelial monolayers and which displays anomalous, sub-Arrhenius scaling of its dynamical relaxation time with decreasing temperature. Despite these differences, we find that the likelihood of rearrangements can vary by several orders of magnitude within the model tissue and extract a local structural quantity, "softness" that accurately predicts the temperature-dependence of the relaxation time. We use an information-theoretic measure to quantify the extent to which softness determines impending topological rearrangements; we find that softness captures nearly all of the information about rearrangements that is obtainable from structure, and that this information is large in the solid phase of the model and decreases rapidly as state variables are varied into the fluid phase.
Cell divisions suppress dynamical correlations in solid tissues
Max Planck Institute for the Physics of Complex Systems（马克斯·普朗克复杂系统物理研究所）；Center for Systems Biology Dresden（德累斯顿系统生物学中心）；Ruđer Bošković Institute（鲁杰尔·博什科维奇研究所）
Exotic rheology of materials with active rearrangements
University of Bristol（布里斯托大学）；Max Planck Institute for Dynamics and Self-Organization（马克斯·普朗克动力学与自组织研究所）；University of Exeter（埃克塞特大学）；Isaac Newton Institute for Mathematical Sciences（牛顿数学科学研究所）；Leiden University（莱顿大学）
Elasticity and plasticity of epithelial gap closure
Max Planck Institute for the Physics of Complex Systems（马克斯·普朗克复杂系统物理研究所）；Max Planck Institute of Molecular Cell Biology and Genetics（马克斯·普朗克分子细胞生物学与遗传学研究所）；Center for Systems Biology Dresden（德累斯顿系统生物学中心）
Noninvasive rheological inference from stable flows in confined tissues
Aix Marseille Univ, Université de Toulon, CNRS, CPT (UMR 7332), Turing Centre for Living Systems（艾克斯马赛大学，土伦大学，法国国家科学研究中心，CPT（UMR 7332），图灵生命系统中心）；Université Paris Cité, CNRS, Institut Jacques Monod（巴黎西岱大学，法国国家科学研究中心，雅克·莫诺研究所）；Friedrich-Alexander Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希·亚历山大大学）；Max-Planck-Zentrum für Physik und Medizin（马克斯·普朗克物理与医学中心）；Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices, School of Physics, Sun Yat-sen University（广东磁电物理与器件重点实验室，中山大学物理学院）；Centre for Physical Mechanics and Biophysics, School of Physics, Sun Yat-sen University（物理力学与生物物理中心，中山大学物理学院）；Aix Marseille Univ, IBDM (UMR 7288), Turing Centre for Living Systems（艾克斯马赛大学，IBDM（UMR 7288），图灵生命系统中心）；Aix Marseille Univ, Université de Toulon, CNRS, LAI (UMR 7333), Turing Centre for Living Systems（艾克斯马赛大学，土伦大学，法国国家科学研究中心，LAI（UMR 7333），图灵生命系统中心）
