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Optimization of fluid transport in the slime mold Physarum polycephalum has been the subject of several modeling efforts in recent literature. Existing models assume that the tube adaptation mechanism in P. polycephalum's tubular network is…

Tissues and Organs · Quantitative Biology 2019-07-01 Vincenzo Bonifaci

Complex distribution networks are pervasive in biology. Examples include nutrient transport in the slime mold \emph{Physarum polycephalum} as well as mammalian and plant venation. Adaptive rules are believed to guide development of these…

Adaptation and Self-Organizing Systems · Physics 2019-12-16 Henrik Ronellenfitsch , Eleni Katifori

Wounding is a severe impairment of function, especially for an exposed organism like the network-forming true slime mould Physarum polycephalum. The tubular network making up the organism's body plan is entirely interconnected and shares a…

Quantitative Methods · Quantitative Biology 2017-10-25 Felix Bäuerle , Mirna Kramar , Karen Alim

Plasmodium of true slime mold, Physarum polycephalum, is an amoeboid organism, which spreads with developing tubular network structure and crawls on two-dimensional plane with oscillating the cell thickness. The plasmodium transforms its…

Adaptation and Self-Organizing Systems · Physics 2009-04-10 Yuki Kagawa , Atsuko Takamatsu

A fundamental question regarding biological transport networks is the interplay between the network development or reorganization and the flows it carries. We use Physarum polycephalum, a true slime mould with a transport network which…

Biological Physics · Physics 2022-12-27 Raphaël Saiseau , Valentin Busson , Laura Xénard , Marc Durand

Life evolved organisms to adapt dynamically to their environment and autonomously exhibit behaviours. While complex behaviours in organisms are typically associated with the capability of neurons to process information, the unicellular…

Biological Physics · Physics 2023-06-16 Mathieu Le Verge-Serandour , Karen Alim

Diffusion of a solute along a channel is enhanced by hydrodynamic flow, a phenomenon known as Taylor dispersion. In microfluidic applications, the compliance of the channel boundaries modifies the hydrodynamic flow and thus solutal…

Soft Condensed Matter · Physics 2026-04-08 Aditya Jha , Masoodah Gunny , Joshua D Mcgraw , Yacine Amarouchene , Thomas Salez

Tracer dispersion is studied experimentally in periodic or disordered arrays of beads in a capillary tube. Dispersion is measured from light absorption variations near the outlet following a steplike injection of dye at the inlet.…

Network pruning reduces the computation costs of an over-parameterized network without performance damage. Prevailing pruning algorithms pre-define the width and depth of the pruned networks, and then transfer parameters from the unpruned…

Computer Vision and Pattern Recognition · Computer Science 2019-10-17 Xuanyi Dong , Yi Yang

Particles transported in fluid flows, such as cells, polymers, or nanorods, are rarely spherical. In this study, we numerically and theoretically investigate the dispersion of an initially localized patch of passive elongated Brownian…

Fluid Dynamics · Physics 2021-09-15 Ajay Harishankar Kumar , Stuart J. Thomson , Thomas R. Powers , Daniel M. Harris

The true slime mould Physarum polycephalum is a recent well studied example of how complex transport networks emerge from simple auto-catalytic and self- organising local interactions, adapting structure and function against changing…

Emerging Technologies · Computer Science 2015-03-29 Jeff Jones

In the realm of biological flow networks, the ability to dynamically adjust to varying demands is paramount. Drawing inspiration from the remarkable adaptability of Physarum polycephalum, we present a novel physical mechanism tailored to…

Soft Condensed Matter · Physics 2023-10-05 Vidyesh Rao Anisetti , Ananth Kandala , J. M. Schwarz

The phenomenon of Taylor or shear-induced dispersion of a non-passive scalar field in a pulsatile pipe flow is investigated, accounting for the scalar field's influence on fluid density and transport coefficients. By employing multiple…

Fluid Dynamics · Physics 2026-03-13 Prabakaran Rajamanickam , Adam D. Weiss

We study diffusion of information packets on several classes of structured networks. Packets diffuse from a randomly chosen node to a specified destination in the network. As local transport rules we consider random diffusion and an…

Statistical Mechanics · Physics 2015-06-24 Bosiljka Tadic , Stefan Thurner

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

Channels are fundamental building blocks from biophysics to soft robotics, often used to transport or separate solutes. As solute particles inevitably transverse between streamlines along the channel by molecular diffusion, the effective…

Soft Condensed Matter · Physics 2020-02-10 Sophie Marbach , Karen Alim

The miscible displacement of a shear-thinning fluid by another of same rheological properties is studied experimentally in a transparent fracture by an optical technique imaging relative concentration distributions. The fracture walls have…

Physarum polycephalum is a single-celled, multi-nucleated slime mold whose body constitutes a network of veins. As it explores its environment, it adapts and optimizes its network to external stimuli. It has been shown to exhibit complex…

Fluid Dynamics · Physics 2023-09-20 Ana Filipa Valente

A number of important transport networks, such as the airline and trade networks of the world, exhibit a characteristic core-periphery structure, wherein a few nodes are highly interconnected and the rest of the network frays into a tree.…

Physics and Society · Physics 2016-02-17 T. Verma , F. Russmann , N. A. M. Araújo , J. Nagler , H. J. Herrmann

Inspired by the prevalence of recurrent circuits in biological brains, we investigate the degree to which directionality is a helpful inductive bias for artificial neural networks. Taking directionality as topologically-ordered information…

Machine Learning · Computer Science 2025-07-22 Yiding Song
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