Analysis of Models in Mathematical Biology and of Sign Pattern Matrices

我的研究计划集中在应用数学的两个领域：I。数学生物学，2。矩阵分析。在数学生物学中，我的建议主要解决传染病传播模型的数学分析。 每种疾病的模型制定取决于疾病的生物学特征、要解决的问题和现有数据。我的重点是稳定性分析，包括解决方案的分歧，灵敏度和疾病控制。一个目的是确定阈值数量，帮助推荐疾病控制策略（例如，流感疫苗和抗病毒药物）。 基本繁殖数是标准的方法，找到这个阈值，但其他数量，即类型和目标繁殖numbers已制定。我建议调查这些可以适应离散时间生态模型。 最近，我开发了网络上的疾病模型，我将把这些模型扩展到更真实的动态网络。 受海地霍乱数据的启发，社区网络模型最近得出了一个域基本生殖数。当水的流动速度快于病原体的衰变速度时，这个数字是通过劳伦级数计算的。 我建议从理论上研究大量的疾病传播性聚集在一起的地区促进疾病侵袭的数值观察。符号模式矩阵的研究是组合矩阵理论的一个分支，其中只知道矩阵元素的符号。我提出的研究主要涉及一个给定的符号模式的矩阵实现允许的特征值。 特别感兴趣的是允许（要求）所有特征值具有负真实的部分的情况，对应于潜在的（符号）稳定性。对于稳定性重要的特征值的位置由经典的3-d惯性向量给出。 我介绍了精细惯性的概念，一个4维向量与零特征值区别于其他纯虚的，我建议进一步研究这个概念。特别是3个精细惯性在检测潜在动力系统中由Hopf分叉引起的周期行为方面是重要的。因此，这项研究在许多领域的线性化系统的应用中具有相关性，例如， 生物化学、人口生物学、经济学和流行病学。该项目还涉及潜在的稳定性，其目标是描述潜在稳定的符号模式（一个长期存在的开放问题），至少对于具有一些有向图结构的模式的子集。 在矩阵的稳定性，主要的未成年人发挥了重要作用，最近的兴趣集中在确定一个对称矩阵是否有一个非零的主要未成年人的每一个订单。 这导致了一个主秩特征序列，并且是主秩分配问题的一个变体，我打算对模式进行研究。

My research proposal is focussed on two areas of applied mathematics: I. Mathematical biology, II. Matrix analysis.I. In mathematical biology, my proposal mainly addresses mathematical analysis of infectious disease transmission models. Model formulation for each disease is governed by the biological features of the disease, the question being addressed and available data. My focus is on stability analysis, including bifurcation of solutions, sensitivity and disease control.One aim is to determine threshold quantities that help recommend disease control strategies (e.g., vaccination and antivirals for influenza). The basic reproduction number is the standard method for finding this threshold, but other quantities, namely type and target reproduction numbers have been formulated.I propose to investigate how these can be adapted to discrete time ecological models. Recently I have developed disease models on networks, and I will extend these models to more realistic dynamic networks. Motivated by data on cholera in Haiti, a community network model recently led to a domain basic reproduction number. When water movement is fast compared with pathogen decay, this number is computed through a Laurent series. I propose to investigate theoretically the numerical observation that regions of large disease transmissibility clustered together facilitate disease invasion.II. The study of sign pattern matrices is a branch of combinatorial matrix theory, in which only the sign of matrix entries is known. My proposed research is mainly related to eigenvalues allowed by matrix realizations of a given sign pattern. Of special interest are the cases in which all eigenvalues are allowed (required) to have negative real parts, corresponding to potential (sign) stability. The location of eigenvalues important for stability is given by the classical 3-d inertia vector. I introduced the concept of refined inertia, a 4-d vector with zero eigenvalues distinguished from other pure imaginary ones, and I propose to further investigate this concept. In particular 3 refined inertias are important in detecting periodic behavior arising from Hopf bifurcation in underlying dynamical systems.Thus this research has relevance in applications to linearized systems in many areas, e.g., biochemistry, population biology, economics, and epidemiology. This project also relates to potential stability, and an objective is to characterize potentially stable sign patterns (a long standing open problem), at least for a subset of patterns having some digraph structure. In matrix stability, principal minors play an important role, and a recent interest focusses on determining for a symmetric matrix whether or not there is a nonzero principal minor of each order. This leads to a principal rank characteristic sequence, and is a variant on the principal rank assignment problem, which I intend to pursue for patterns.