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The dynamics of coupled elements’ ensembles are investigated in the context of description of spatio-temporal processes in the myocardium. Basic element is map-based model constructed by simplification and reduction of Luo-Rudy model. In particular, capabilities of the model in replication of different regimes of cardiac activity are shown, including excitable and oscillatory regimes. The dynamics of 1D and 2D lattices of coupled oscillatory elements with a random distribution of individual frequencies are considered. Effects of cluster synchronization and transition to global synchronization by increasing of coupling strength are discussed. Impulse propagation in the chain of excitable cells has been observed. Analysis of 2D lattice of excitable elements with target and spiral waves have been made. The characteristics of the spiral wave has been analyzed in depending on the individual parameters of the map and coupling strength between elements of the lattice. A study of mixed ensembles consisting of excitable and oscillatory elements with a gradient changing of the properties have been made, including the task for description of normal and pathological activity of the sinoatrial node.

We study the centrally symmetric mathematical model of electrodiffusion. This model describes in particular the transport of the Li⁺ ions in certain electrochemical current sources. We demonstrate that the steady state solution of the considered model exists and is unique if the boundary values of the ion concentration and electric potential are given. This solution also proves to be the stable attractor of the time-dependent solutions with different initial value distributions.

This paper presents a model mixture of probability distributions of signal and noise. Typically, when analyzing the data under conditions of uncertainty it is necessary to use nonparametric tests. However, such an analysis of nonstationary data in the presence of uncertainty on the mean of the distribution and its parameters may be ineffective. The model involves the implementation of a case of a priori non-parametric uncertainty in the processing of the signal at a time when the separation of signal and noise are related to different general population, is feasible.

This article is dedicated to numerical modeling of heat and mass transfer processes in microchannels. Microchannels are channels, that characteristic diameter is about 100 μm. Interest to the study of processes in them is growing every year, due to the rapid development of microfluid technique. The study was conducted using the software package σFlow. Isothermal and nonisothermal flows in microchannels of various configurations were considered. The obtained results were compared with available experimental and analytical data. In general for all problems a good agreement was obtained.

An application of the invariant imbedding method to describe the interaction of 3D electromagnetic field with 2D photonic crystal of finite thickness, formed by a dielectric circular cylinder or square bars, is considered in this paper. Matrix coefficients of transmission and reflection for waves at different angles of incidence were calculated taking into account different types of polarization and non-coplanar diffraction.

The paper presents an optimization approach to microstructure simulation. Porosity function was optimized by numerical method, grain-size model was optimized by complex method based on criteria of model quality. Methods have been validated on examples. Presented new regression model of model quality. Actual application of proposed method is 3D reconstruction of core sample microstructure. Presented results suggest to prolongation of investigations. 

The number of papers addressing the forecasting of the infectious disease morbidity is rapidly growing due to accumulation of available statistical data. This article surveys the major approaches for the shortterm and the long-term morbidity forecasting. Their limitations and the practical application possibilities are pointed out. The paper presents the conventional time series analysis methods — regression and autoregressive models; machine learning-based approaches — Bayesian networks and artificial neural networks; case-based reasoning; filtration-based techniques. The most known mathematical models of infectious diseases are mentioned: classical equation-based models (deterministic and stochastic), modern simulation models (network and agent-based).

On the basis of the MGD equations we consider 2D- and 3D- nonstationary problems about the evolution of perturbations in the lower atmosphere and the Earth’s ionosphere which are caused by the movement of large meteoroids along gently sloping paths of the entry with the simulation of their destruction by the momentary increase of the midship at the point of the pressure head maximum. According to the results of our numerical investigation we obtain and analyze the detailed spatial-temporal distributions of the main parameters of the plasma flows from which in particular a number of phenomena that are similar to those seen in the Chelyabinsk phenomenon follow.

Investigation of influence of non-equilibrium initial states and structural disorder on characteristics of anomalous slow non-equilibrium critical behavior of three-dimensional Ising model is carried out. The unique ageing properties and violations of the equilibrium fluctuation-dissipation theorem are observed for considered pure and disordered systems which were prepared in high-temperature initial state and then quenched in their critical points. The heat-bath algorithm description of ageing properties in non-equilibrium critical behavior of three-dimensional Ising model with spin concentrations p = 1.0, p = 0.8, and 0.6 is realized. On the base of analysis of such two-time quantities as autocorrelation function and dynamical susceptibility were demonstrated the ageing effects and were calculated asymptotic values of universal fluctuation-dissipation ratio in these systems. It was shown that the presence of defects leads to aging gain.

Problems of application of quasicellular networks for simulation of flows of visitors in different public spaces are considered. Quasicellular networks are basic discrete structures without signature. Proposed approach may be used to create simulations on micro and macro levels. It also may be used for creating geometrical models. There are also multi-flow systems for simulation of sports fans in a sports arena, propagation of fire and poison in public spaces. This approach satisfies the requirements of MOE of Russia № 7-3-113.