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Spread Pattern Formation of H5N1-Avian Influenza and its Implications for Control Strategies

R. Liu, V. R. S. K. Duvvuri, J. Wu (2008)

Mathematical Modelling of Natural Phenomena

Mechanisms contributing to the spread of avian influenza seem to be well identified, but how their interplay led to the current worldwide spread pattern of H5N1 influenza is still unknown due to the lack of effective global surveillance and relevant data. Here we develop some deterministic models based on the transmission cycle and modes of H5N1 and focusing on the interaction among poultry, wild birds and environment. Some of the model parameters are obtained from existing literatures, and others...

Stability Analysis of Cell Dynamics in Leukemia

H. Özbay, C. Bonnet, H. Benjelloun, J. Clairambault (2012)

Mathematical Modelling of Natural Phenomena

In order to better understand the dynamics of acute leukemia, and in particular to find theoretical conditions for the efficient delivery of drugs in acute myeloblastic leukemia, we investigate stability of a system modeling its cell dynamics. The overall system is a cascade connection of sub-systems consisting of distributed delays and static nonlinear feedbacks. Earlier results on local asymptotic stability are improved by the analysis of the linearized...

Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality

Yang Liu, Rongjiang Yang, Jianquan Lu, Bo Wu, Xiushan Cai (2013)

International Journal of Applied Mathematics and Computer Science

This paper is devoted to studying the globally exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays. In the process of impulsive effect, nonlinear and delayed factors are simultaneously considered. A new impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous...

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