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Search: MSC category 92 ( Biology and other natural sciences )

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1. CMB 2017 (vol 61 pp. 423)

Zhang, Guo-Bao; Tian, Ge
 Stability of Traveling Wavefronts for a Two-Component Lattice Dynamical System Arising in Competition Models In this paper, we study a two-component Lotka-Volterra competition system on an one-dimensional spatial lattice. By the method of the comparison principle together with the weighted energy, we prove that the traveling wavefronts with large speed are exponentially asymptotically stable, when the initial perturbation around the traveling wavefronts decays exponentially as $j+ct \rightarrow -\infty$, where $j\in\mathbb{Z}$, $t\gt 0$, but the initial perturbation can be arbitrarily large on other locations. This partially answers an open problem by J.-S. Guo and C.-H. Wu. Keywords:lattice dynamical system, competition model, traveling wavefront, stabilityCategories:34A33, 34K20, 92D25

2. CMB 2017 (vol 60 pp. 436)

Weng, Peixuan; Liu, Li
 Globally Asymptotic Stability of a Delayed Integro-Differential Equation with Nonlocal Diffusion We study a population model with nonlocal diffusion, which is a delayed integro-differential equation with double nonlinearity and two integrable kernels. By comparison method and analytical technique, we obtain globally asymptotic stability of the zero solution and the positive equilibrium. The results obtained reveal that the globally asymptotic stability only depends on the property of nonlinearity. As application, an example for a population model with age structure is discussed at the end of the article. Keywords:integro-differential equation, nonlocal diffusion, equilibrium, globally asymptotic stability, population model with age structureCategories:45J05, 35K57, 92D25

3. CMB 2012 (vol 56 pp. 621)

Shang, Yilun
 Optimal Control Strategies for Virus Spreading in Inhomogeneous Epidemic Dynamics In this paper, we study the spread of virus/worm in computer networks with a view to addressing cyber security problems. Epidemic models have been applied extensively to model the propagation of computer viruses, which characterize the fact that infected machines may spread malware to other hosts connected to the network. In our framework, the dynamics of hosts evolves according to a modified inhomogeneous Susceptible-Infectious-Susceptible (SIS) epidemic model with time-varying transmission rate and recovery rate. The infection of computers is subject to direct attack as well as propagation among hosts. Based on optimal control theory, optimal attack strategies are provided by minimizing the cost (equivalently maximizing the profit) of the attacker. We present a threshold function of the fraction of infectious hosts, which captures the dynamically evolving strategies of the attacker and reflects the persistence of virus spreading. Moreover, our results indicate that if the infectivity of a computer worm is low and the computers are installed with antivirus software with high reliability, the intensity of attacks incurred will likely be low. This agrees with our intuition. Keywords:network securitypidemic dynamics, optimal controlCategories:49J15, 92D30
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