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Benjamin M. Alessio

Publications and source records attributed to Benjamin M. Alessio.

3 recordsLinked to original sources

Dense granular rheology from fluctuations

A unifying framework to describe dense flows of dry, deformable grains is proposed. Perturbative analysis of a granular temperature equation describing flows with contact stresses, supported by the recovery of the nonlocal granular fluidity equation, is used to derive an expression for a recently postulated critical exponent. Direct numerical simulation justifies models for the unclosed terms that provide a material-dependent estimate. Non-universality of the velocity and strain rate distributions, arising from competition between production and diffusion, rationalizes model shortcomings.

cond-mat.soft

A Reaction-Diffusion-Chemotaxis Model for Human Population Dynamics over Fractal Terrains

Advection of entities induced by gradients in attractant concentration fields is observed via diffusiophoresis in colloids and via chemotaxis in microorganisms. Mathematically, both diffusiophoresis and chemotaxis follow similar mathematical descriptions and display a variety of interesting behaviors that are not observed through other transport mechanisms. However, the application of such a mathematical framework has largely been restricted to soft matter research. In this article, we argue that this framework is more general and can be expanded to study human population dynamics. We assert that human populations also migrate chemotactically, but by sensing concentrations gradients in attractants such as resource availability, social connections, and safety indices. Therefore, we extend the Fisher-KPP reaction-diffusion model, foundational to human population dynamics, to incorporate chemotactic advection. Furthermore, we introduce a fractal terrain to better mimic the human dispersal phenomena. Simulations demonstrate that, by including chemotaxis of a population toward attractants which are dispersed heterogenously over fractal terrains, population hotspots can appear from from initially uniformly dispersed states whereas Fisher-KPP without chemotaxis predicts a persistent tendency toward population uniformity. Varying the chemotactic migration yields fine control over inter- or intra-population segregation and thus the population growth rates may be substantially altered by considering the population-attractant coupling. This framework may be useful for characterizing historical population separations, and furthermore is particularly pertinent for predicting emergence of new population hotspots as climate change is expected to cause large-scale human displacement, which may be dictated by chemotactic movement of humans due to evolving concentration gradients in safety indices.

q-bio.PE

Diffusiophoresis-Enhanced Turing Patterns

Turing patterns are fundamental in biophysics, emerging from short-range activation and long-range inhibition processes. However, their paradigm is based on diffusive transport processes, which yields Turing patters that are less sharp than the ones observed in nature. A complete physical description of why the Turing patterns observed in nature are significantly sharper than state-of-the-art models remains unknown. Here, we propose a novel solution to this phenomenon by investigating the role of diffusiophoresis in Turing patterns. The inclusion of diffusiophoresis enables one to generate patterns of colloidal particles with significantly finer length scales than the accompanying chemical patterns. Further, diffusiophoresis enables a robust degree of control that closely mimics natural patterns observed in species like the Ornate Boxfish and the Jewel Moray Eel. We present a scaling analysis indicating that chromatophores, ubiquitous in biological pattern formation, are likely diffusiophoretic, and that colloidal Péclet number controls the pattern enhancement. This discovery suggests important features of biological pattern formation can be explained with a universal mechanism that is quantified straightforwardly from the fundamental physics of colloids and inspires future exploration of adaptive materials, lab-on-a-chip devices, and tumorigenesis.

cond-mat.soft