论文标题

用自动杂质分析和模拟新型跑步模型

Analysis and Simulation of a Novel Run-and-Tumble Model with Autochemotaxis

论文作者

Russell, Nicholas J., Rossi, Louis F.

论文摘要

我们使用自动杂质进行建模,分析和模拟一种新型的跑步模型,并受到浮游植物异源Akashiwo的生物学启发。通过光疗法和趋化性对浮游生物运动和相互作用进行基本理解对于理解为什么有害藻类开花(HAB)开始形成以及如何预防它们至关重要。我们开发了一个一维数学和计算模型,反映了浮游生物的生态学运动,并结合了奔跑的运动和自动降解。我们提出了一系列复杂且具有生物学上有意义的模型,并结合了一系列实验室和计算实验,这些模型为模型所基于的思想提供了信息。通过分析与实验观测相似的动力学和模式形成,我们在没有散装流体流动的情况下确定了在浮游生物模式形成中显着的参数。我们发现,化学沉积和浮游物质对小化学梯度的敏感性的精确形式是在浮游物密度中驱动非线性图案形成的关键参数。

We model, analyze, and simulate a novel run-and-tumble model with autochemotaxis, biologically inspired by the phytoplankton Heterosigma akashiwo. Developing a fundamental understanding of planktonic movements and interactions through phototaxis and chemotaxis is vital to comprehending why harmful algal blooms (HABs) start to form and how they can be prevented. We develop a one- and two-dimensional mathematical and computational model reflecting the movement of an ecology of plankton, incorporating both run-and-tumble motion and autochemotaxis. We present a succession of complex and biologically meaningful models combined with a sequence of laboratory and computational experiments that inform the ideas underlying the model. By analyzing the dynamics and pattern formation which are similar to experimental observations, we identify parameters that are significant in plankton's pattern formation in the absence of bulk fluid flow. We find that the precise form of chemical deposition and plankton sensitivity to small chemical gradients are crucial parameters that drive nonlinear pattern formation in the plankton density.

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