All issues

We consider a mathematical model describing the competition for a heterogeneous resource of two populations on a one-dimensional area. Distribution of populations is governed by diffusion and directed migration, species growth obeys to the logistic law. We study the corresponding problem of nonlinear parabolic equations with variable coefficients (function of a resource, parameters of growth, diffusion and migration). Approach on the theory the cosymmetric dynamic systems of V. Yudovich is applied to the analysis of population patterns. Conditions on parameters for which the problem under investigation has nontrivial cosymmetry are analytically derived. Numerical experiment is used to find an emergence of continuous family of steady states when cosymmetry takes place. The numerical scheme is based on the finite-difference discretization in space using the balance method and integration on time by Runge-Kutta method. Impact of diffusive and migration parameters on scenarios of distribution of populations is studied. In the vicinity of the line, corresponding to cosymmetry, neutral curves for diffusive parameters are calculated. We present the mappings with areas of diffusive parameters which correspond to scenarios of coexistence and extinction of species. For a number of migration parameters and resource functions with one and two maxima the analysis of possible scenarios is carried out. Particularly, we found the areas of parameters for which the survival of each specie is determined by initial conditions. It should be noted that dynamics may be nontrivial: after starting decrease in densities of both species the growth of only one population takes place whenever another specie decreases. The analysis has shown that areas of the diffusive parameters corresponding to various scenarios of population patterns are grouped near the cosymmetry lines. The derived mappings allow to explain, in particular, effect of a survival of population due to increasing of diffusive mobility in case of starvation.

We analyze variants of considering the inhomogeneity of the environment in computer modeling of the dynamics of a predator and prey based on a system of reaction-diffusion–advection equations. The local interaction of species (reaction terms) is described by the logistic law for the prey and the Beddington –DeAngelis functional response, special cases of which are the Holling type II functional response and the Arditi – Ginzburg model. We consider a one-dimensional problem in space for a heterogeneous resource (carrying capacity) and three types of taxis (the prey to resource and from the predator, the predator to the prey). An analytical approach is used to study the stability of stationary solutions in the case of local interaction (diffusionless approach). We employ the method of lines to study diffusion and advective processes. A comparison of the critical values of the mortality parameter of predators is given. Analysis showed that at constant coefficients in the Beddington –DeAngelis model, critical values are variable along the spatial coordinate, while we do not observe this effect for the Arditi –Ginzburg model. We propose a modification of the reaction terms, which makes it possible to take into account the heterogeneity of the resource. Numerical results on the dynamics of species for large and small migration coefficients are presented, demonstrating a decrease in the influence of the species of local members on the emerging spatio-temporal distributions of populations. Bifurcation transitions are analyzed when changing the parameters of diffusion–advection and reaction terms.

Safe carrying out of emergency recovery operations at emergency offshore gas condensate wells is possible when taking into account the hazardous factors that prevent anti-fontanning measures. One of such factors is the gassiness of the operation zone due to the release from the water column of a large amount of light, as compared to air, natural gas, as well as vapours of heavier components of gas condensate. To estimate the distribution of explosive concentration of petroleum product vapours in the near surface layer of the atmosphere, it is necessary to determine the characteristics of the source of the contamination. Based on the analysis of theoretical works concerning to the formation of the velocity field in the upper layer of the sea as a result of large amounts of gas coming to the surface, an analytical model is proposed to calculate the size of the area in which a significant amount of gas condensate coming to the surface is vaporised during accidents at shallow-water wells. The stationary regime of reservoir fluid flow during fountaining of offshore gas and oil wells with an underwater location of their mouths is considered. A low-parametric model of oil product evaporation from films of different thickness is constructed. It is shown that the size of the zone of intensive evaporation at shallow-water wells is determined by the volume flow of liquid fraction, its fractional composition and selected threshold for estimation of oil product vapour flow into the atmosphere. In the context of this work shallow water wells are wells with gas flow rate from 1 to 20 million cubic meters at sea depths of about 50–200 metres. In this case, the formation fluid jet from the wellhead on the seabed is transformed into a bubble plume, the stratification of the water column, typical for the summer-autumn period, does not limit the plume’s exit to the sea surface, and the velocity of bubble rise allows the gas dissolution process to be disregardded. The analysis was limited to almost calm hydrometeorological conditions. Such conditions are favourable for offshore operations, but unfavourable from the point of view of dispersion of high concentrations of oil product vapours in the near surface layer of the atmosphere. As a result of this work, an analytical dependence for an approximate assessment of the zone of intensive evaporation of gas condensate is proposed.

The main statements and inferences of the Dynamic Theory Information (DTI) are considered. It is shown that DTI provides the possibility two reveal two essentially important types of information: objective (unconventional) and subjective (conventional) informtion. There are two ways of obtaining information: reception (perception of an already existing one) and generation (production of new) information. It is shown that the processes of generation and perception of information should proceed in two different subsystems of the same cognitive system. The main points of the Natural-Constructivist Approach to modeling the cognitive process are discussed. It is shown that any neuromorphic approach faces the problem of Explanatory Gap between the “Brain” and the “Mind”, i. e. the gap between objectively measurable information about the ensemble of neurons (“Brain”) and subjective information about the human consciousness (“Mind”). The Natural-Constructive Cognitive Architecture developed within the framework of this approach is discussed. It is a complex block-hierarchical combination of several neuroprocessors. The main constructive feature of this architecture is splitting the whole system into two linked subsystems, by analogy with the hemispheres of the human brain. One of the subsystems is processing the new information, learning, and creativity, i.e. for the generation of information. Another subsystem is responsible for processing already existing information, i.e. reception of information. It is shown that the lowest (zero) level of the hierarchy is represented by processors that should record images of real objects (distributed memory) as a response to sensory signals, which is objective information (and refers to the “Brain”). The next hierarchy levels are represented by processors containing symbols of the recorded images. It is shown that symbols represent subjective (conventional) information created by the system itself and providing its individuality. The highest hierarchy levels containing the symbols of abstract concepts provide the possibility to interpret the concepts of “consciousness”, “sub-consciousness”, “intuition”, referring to the field of “Mind”, in terms of the ensemble of neurons. Thus, DTI provides an opportunity to build a model that allows us to trace how the “Mind” could emerge basing on the “Brain”.

The efficiency of mobile robotic systems (MRS) that monitor the traffic situation, urban infrastructure, consequences of emergency situations, etc., directly depends on the quality of vision systems, which are the most important part of MRS. In turn, the accuracy of image processing in vision systems depends to a great extent on the accuracy of spatial orientation of the video camera placed on the MRS. However, when video cameras are placed on the MRS, the level of errors of their spatial orientation increases sharply, caused by wind and seismic vibrations, movement of the MRS over rough terrain, etc. In this connection, the paper considers a general solution to the problem of stochastic estimation of spatial orientation parameters of video cameras in conditions of both random mast vibrations and arbitrary character of MRS movement. Since the methods of solving this problem on the basis of satellite measurements at high intensity of natural and artificial radio interference (the methods of formation of which are constantly being improved) are not able to provide the required accuracy of the solution, the proposed approach is based on the use of autonomous means of measurement — inertial and non-inertial. But when using them, the problem of building and stochastic estimation of the general model of video camera motion arises, the complexity of which is determined by arbitrary motion of the video camera, random mast oscillations, measurement disturbances, etc. The problem of stochastic estimation of the general model of video camera motion arises. Due to the unsolved nature of this problem, the paper considers the synthesis of both the video camera motion model in the most general case and the stochastic estimation of its state parameters. The developed algorithm for joint estimation of the spatial orientation parameters of the video camera placed on the mast of the MRS is invariant to the nature of motion of the mast, the video camera, and the MRS itself, providing stability and the required accuracy of estimation under the most general assumptions about the nature of interference of the sensitive elements of the autonomous measuring complex used. The results of the numerical experiment allow us to conclude that the proposed approach can be practically applied to solve the problem of the current spatial orientation of MRS and video cameras placed on them using inexpensive autonomous measuring devices.

We examine a phenomenological algorithm for generating morphology of astrocytes, a major class of glial brain cells, based on morphometric data of rat brain protoplasmic astrocytes and observations of general cell development trends in vivo, based on current literature. We adapted the Space Colonization Algorithm (SCA) for procedural generation of astrocytic morphology from scratch. Attractor points used in generation were spatially distributed in the model volume according to the synapse distribution density in the rat hippocampus tissue during the first week of postnatal brain development. We analyzed and compared astrocytic morphology reconstructions at different brain development stages using morphometry estimation techniques such as Sholl analysis, number of bifurcations, number of terminals, total tree length, and maximum branching order. Using morphometric data from protoplasmic astrocytes of rats at different ages, we selected the necessary generation parameters to obtain the most realistic three-dimensional cell morphology models. We demonstrate that our proposed algorithm allows not only to obtain individual cell geometry but also recreate the phenomenon of tiling domain organization in the cell populations. In our algorithm tiling emerges due to the cell competition for territory and the assignment of unique attractor points to their processes, which then become unavailable to other cells and their processes. We further extend the original algorithm by splitting morphology generation in two phases, thereby simulating astrocyte tree structure development during the first and third-fourth weeks of rat postnatal brain development: rapid space exploration at the first stage and extensive branching at the second stage. To this end, we introduce two attractor types to separate two different growth strategies in time. We hypothesize that the extended algorithm with dynamic attractor generation can explain the formation process of fine astrocyte cell structures and maturation of astrocytic arborizations.

This paper is devoted to the analysis of the effect of additive and parametric noise on the processes occurring in the nerve cell. This study is carried out on the example of the well-known Morris – Lecar model described by the two-dimensional system of ordinary differential equations. One of the main properties of the neuron is the excitability, i.e., the ability to respond to external stimuli with an abrupt change of the electric potential on the cell membrane. This article considers a set of parameters, wherein the model exhibits the class 2 excitability. The dynamics of the system is studied under variation of the external current parameter. We consider two parametric zones: the monostability zone, where a stable equilibrium is the only attractor of the deterministic system, and the bistability zone, characterized by the coexistence of a stable equilibrium and a limit cycle. We show that in both cases random disturbances result in the phenomenon of the stochastic generation of mixed-mode oscillations (i. e., alternating oscillations of small and large amplitudes). In the monostability zone this phenomenon is associated with a high excitability of the system, while in the bistability zone, it occurs due to noise-induced transitions between attractors. This phenomenon is confirmed by changes of probability density functions for distribution of random trajectories, power spectral densities and interspike intervals statistics. The action of additive and parametric noise is compared. We show that under the parametric noise, the stochastic generation of mixed-mode oscillations is observed at lower intensities than under the additive noise. For the quantitative analysis of these stochastic phenomena we propose and apply an approach based on the stochastic sensitivity function technique and the method of confidence domains. In the case of a stable equilibrium, this confidence domain is an ellipse. For the stable limit cycle, this domain is a confidence band. The study of the mutual location of confidence bands and the boundary separating the basins of attraction for different noise intensities allows us to predict the emergence of noise-induced transitions. The effectiveness of this analytical approach is confirmed by the good agreement of theoretical estimations with results of direct numerical simulations.

In this work, we develop a model of the immune response to respiratory viral infections taking into account some particular properties of the SARS-CoV-2 infection. The model represents a system of ordinary differential equations for the concentrations of epithelial cells, immune cells, virus and inflammatory cytokines. Conventional analysis of the existence and stability of stationary points is completed by numerical simulations in order to study dynamics of solutions. Behavior of solutions is characterized by large peaks of virus concentration specific for acute respiratory viral infections.

At the first stage, we study the innate immune response based on the protective properties of interferon secreted by virus-infected cells. On the other hand, viral infection down-regulates interferon production. Their competition can lead to the bistability of the system with different regimes of infection progression with high or low intensity. In the case of infection outbreak, the incubation period and the maximal viral load depend on the initial viral load and the parameters of the immune response. In particular, increase of the initial viral load leads to shorter incubation period and higher maximal viral load.

In order to study the emergence and dynamics of cytokine storm, we consider proinflammatory cytokines produced by cells of the innate immune response. Depending on parameters of the model, the system can remain in the normal inflammatory state specific for viral infections or, due to positive feedback between inflammation and immune cells, pass to cytokine storm characterized by excessive production of proinflammatory cytokines. Furthermore, inflammatory cell death can stimulate transition to cytokine storm. However, it cannot sustain it by itself without the innate immune response. Assumptions of the model and obtained results are in qualitative agreement with the experimental and clinical data.

The second part presents numerical studies of the parameters of the lower ionosphere at altitudes of 40–90 km when heated by powerful high-frequency radio waves of various frequencies and powers. The problem statement is considered in the first part of the article. The main attention is paid to the interrelation between the energy and kinetic parameters of the disturbed $D$-region of the ionosphere in the processes that determine the absorption and transformation of the radio beam energy flux in space and time. The possibility of a significant difference in the behavior of the parameters of the disturbed region in the daytime and at nighttime, both in magnitude and in space-time distribution, is shown. In the absence of sufficiently reliable values of the rate constants for a number of important kinetic processes, numerical studies were carried out in stages with the gradual addition of individual processes and kinetic blocks corresponding at the same time to a certain physical content. It is shown that the energy thresholds for inelastic collisions of electrons with air molecules are the main ones. This approach made it possible to detect the effect of the emergence of a self-oscillating mode of changing parameters if the main channel for energy losses in inelastic processes is the most energy-intensive process — ionization. This effect may play a role in plasma studies using high-frequency inductive and capacitive discharges. The results of calculations of the ionization and optical parameters of the disturbed $D$-region for daytime conditions are presented. The electron temperature, density, emission coefficients in the visible and infrared ranges of the spectrum are obtained for various values of the power of the radio beam and its frequency in the lower ionosphere. The height-time distribution of the absorbed radiation power is calculated, which is necessary in studies of higher layers of the ionosphere. The influence on the electron temperature and on the general behavior of the parameters of energy losses by electrons on the excitation of vibrational and metastable states of molecules has been studied in detail. It is shown that under nighttime conditions, when the electron concentration begins at altitudes of about 80 km, and the concentration of heavy particles decreases by two orders of magnitude compared to the average $D$-region, large-scale gas-dynamic motion can develop with sufficient radio emission power The algorithm was developed based on the McCormack method and two-dimensional gas-dynamic calculations of the behavior of the parameters of the perturbed region were performed with some simplifications of the kinetics.

The paper constructs and studies a generalized model describing two-component systems of reaction – diffusion type with power nonlinearity, considering the influence of external noise. A methodology has been developed for analyzing the generalized model, which includes linear stability analysis, nonlinear stability analysis, and numerical simulation of the system’s evolution. The linear analysis technique uses basic approaches, in which the characteristic equation is obtained using a linearization matrix. Nonlinear stability analysis realized up to third-order moments inclusively. For this, the functions describing the dynamics of the components are expanded in Taylor series up to third-order terms. Then, using the Novikov theorem, the averaging procedure is carried out. As a result, the obtained equations form an infinite hierarchically subordinate structure, which must be truncated at some point. To achieve this, contributions from terms higher than the third order are neglected in both the equations themselves and during the construction of the moment equations. The resulting equations form a set of linear equations, from which the stability matrix is constructed. This matrix has a rather complex structure, making it solvable only numerically. For the numerical study of the system’s evolution, the method of variable directions was chosen. Due to the presence of a stochastic component in the analyzed system, the method was modified such that random fields with a specified distribution and correlation function, responsible for the noise contribution to the overall nonlinearity, are generated across entire layers. The developed methodology was tested on the reaction – diffusion model proposed by Barrio et al., according to the results of the study, they showed the similarity of the obtained structures with the pigmentation of fish. This paper focuses on the system behavior analysis in the neighborhood of a non-zero stationary point. The dependence of the real part of the eigenvalues on the wavenumber has been examined. In the linear analysis, a range of wavenumber values is identified in which Turing instability occurs. Nonlinear analysis and numerical simulation of the system’s evolution are conducted for model parameters that, in contrast, lie outside the Turing instability region. Nonlinear analysis found noise intensities of additive noise for which, despite the absence of conditions for the emergence of diffusion instability, the system transitions to an unstable state. The results of the numerical simulation of the evolution of the tested model demonstrate the process of forming spatial structures of Turing type under the influence of additive noise.