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首页> 外文期刊>International journal of non-linear mechanics >Autocatalator as the source of instability in the complex non-linear neuroendocrine model
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Autocatalator as the source of instability in the complex non-linear neuroendocrine model

机译:自动催化剂是复杂非线性神经内分泌模型中不稳定的来源

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摘要

The mathematical analogy between properties of simple and complex models of non-linear reactions was used to determine reaction steps in the complex model, necessary to generate instability region and appropriate type of bifurcations on the border between stable and unstable non-equilibrium stationary state. The autocatalator was recognized as the simple prototype two-variable non-linear model practical for examination of the complex four-variable non-linear neuroendocrine system known as the Hypothalamic-Pituitary-Adrenal (HPA) axis. In both cases, we derived the instability criteria by stoichiometric network analysis (SNA), determine conditions under which dynamic transitions, i.e. bifurcations occur, and identify the type of bifurcation. The supercritical Andronov-Hopf bifurcation was found in both cases whereas saddle-node bifurcation was detected only in the model for HPA axis.
机译:在非线性模型的简单模型和复杂模型之间,用数学上的类比来确定复杂模型中的反应步骤,这对于在稳定和不稳定的非平衡稳态之间的边界上产生不稳定性区域和适当的分叉类型是必不可少的。自动催化剂被认为是简单的原型二变量非线性模型,可用于检查复杂的四变量非线性神经内分泌系统,称为下丘脑-垂体-肾上腺(HPA)轴。在这两种情况下,我们都通过化学计量网络分析(SNA)得出了不稳定性标准,确定了发生动态过渡(即分叉)的条件,并确定了分叉的类型。在这两种情况下均发现了超临界安德罗诺夫-霍普夫分叉,而仅在HPA轴模型中检测到了鞍节点分叉。

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