https://elib.bsu.by:443/handle/123456789/292313 NPCS Vol.24, no.4 (2021), pp. 311-414 Mon, 20 Apr 2026 07:02:11 GMT 2026-04-20T07:02:11Z https://elib.bsu.by:443/handle/123456789/292550 Заглавие документа: Stochastic Generalization of the Epidemiological SIR Model Авторы: Obolonkin, V.; Zherelo, A. Аннотация: In this paper we propose stochastic modification of well-known in epidemiology SIR model. This modification allows us to simulate various scenarios of infection and can be used for the risk management. Fri, 01 Jan 2021 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/292550 2021-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/292549 Заглавие документа: Structure of the plane waves for a spin 3/2 particle, massive and massless cases, gauge symmetry Авторы: Ivashkevich, A. V. Аннотация: The structure of the plane waves solutions for a relativistic spin 3/2 particle described by 16-component vector-bispinor is studied. In massless case, two representations are used: Rarita – Schwinger basis, and a special second basis in which the wave equation contains the Levi-Civita tensor. In the second representation it becomes evident the existence of gauge solutions in the form of 4-gradient of an arbitrary bispinor. General solution of the massless equation consists of six independent components, it is proved in an explicit form that four of them may be identified with the gauge solutions, and therefore may be removed. This procedure is performed in the Rarita – Schwinger basis as well. For the massive case, in Rarita – Schwinger basis four independent solutions are constructed explicitly. Fri, 01 Jan 2021 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/292549 2021-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/292548 Заглавие документа: Comparison Between Different Growth Functions of the Jatropha Curcas Plant with Random Attack Pattern of Whitefly Авторы: Roshmi Das; Ashis Kumar Sarkar Аннотация: We have proposed here two deterministic models of Jatropha Curcas plant and Whitefly that simulate the dynamics of interaction between them where the distribution of Whitefly on plant follows Poisson distribution.In the first model growth rate of the plant is assumed to be in logistic form whereas in the second model it is taken as exponential form. The attack pattern and the growth of the whitefly are assumed as Holling type II function.The first model results a globally stable state and in the second one we find a globally attracting steady state for some parameter values,and a stable limit cycle for some other parameter values. It is also shown that there exist Hopf bifurcation with respect to some parameter values. The paper also discusses the question about persistence and permanence of the model. It is found that the specific growth rate of both the population and attack pattern of the whitefly governs the dynamics of both the models. Fri, 01 Jan 2021 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/292548 2021-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/292547 Заглавие документа: Inter-event Times Statistic in Stationary Processes: Nonlinear ARMA Modeling of Wind Speed Time Series Авторы: Cammarota, C. Аннотация: The random sequence of inter-event times of a level-crossing is a statistical tool that can be used to investigate time series from complex phenomena. Typical features of observed series as the skewed distribution and long range correlations are modeled using non linear transformations applied to Gaussian ARMA processes. We investigate the distribution of the inter-event times of the level-crossing events in ARMA processes in function of the probability corresponding to the level. For Gaussian ARMA processes we establish a representation of this indicator, prove its symmetry and that it is invariant with respect to the application of a non linear monotonic transformation. Using simulated series we provide evidence that the symmetry disappears if a non monotonic transformation is applied to an ARMA process. We estimate this indicator in wind speed time series obtained from three different databases. Data analysis provides evidence that the indicator is non symmetric, suggesting that only highly non linear transformations of ARMA processes can be used in modeling. We discuss the possible use of the inter-event times in the prediction task. Fri, 01 Jan 2021 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/292547 2021-01-01T00:00:00Z