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The article examines the impact of non-market actions of participants in oligopolistic markets on the market structure. The following actions of one of the market participants aimed at increasing its market share are analyzed: 1) price manipulation; 2) blocking investments of stronger oligopolists; 3) destruction of produced products and capacities of competitors. Linear dynamic games with a quadratic criterion are used to model the strategies of oligopolists. The expediency of their use is due to the possibility of both an adequate description of the evolution of markets and the implementation of two mutually complementary approaches to determining the strategies of oligopolists: 1) based on the representation of models in the state space and the solution of generalized Riccati equations; 2) based on the application of operational calculus methods (in the frequency domain) which owns the visibility necessary for economic analysis.

The article shows the equivalence of approaches to solving the problem with maximin criteria of oligopolists in the state space and in the frequency domain. The results of calculations are considered in relation to a duopoly, with indicators close to one of the duopolies in the microelectronic industry of the world. The second duopolist is less effective from the standpoint of costs, though more mobile. Its goal is to increase its market share by implementing the non-market methods listed above.

Calculations carried out with help of the game model, made it possible to construct dependencies that characterize the relationship between the relative increase in production volumes over a 25-year period of weak and strong duopolists under price manipulation. Constructed dependencies show that an increase in the price for the accepted linear demand function leads to a very small increase in the production of a strong duopolist, but, simultaneously, to a significant increase in this indicator for a weak one.

Calculations carried out with use of the other variants of the model, show that blocking investments, as well as destroying the products of a strong duopolist, leads to more significant increase in the production of marketable products for a weak duopolist than to a decrease in this indicator for a strong one.

Mechanical properties of eukaryotic cells play an important role in life cycle conditions and in the development of pathological processes. In this paper we discuss the problem of parameters identification and verification of viscoelastic constitutive models based on force spectroscopy data of living cells. It is proposed to use one-dimensional continuous wavelet transform to calculate the relaxation function. Analytical calculations and the results of numerical simulation are given, which allow to obtain relaxation functions similar to each other on the basis of experimentally determined force curves and theoretical stress-strain relationships using wavelet differentiation algorithms. Test examples demonstrating correctness of software implementation of the proposed algorithms are analyzed. The cell models are considered, on the example of which the application of the proposed procedure of identification and verification of their parameters is demonstrated. Among them are a structural-mechanical model with parallel connected fractional elements, which is currently the most adequate in terms of compliance with atomic force microscopy data of a wide class of cells, and a new statistical-thermodynamic model, which is not inferior in descriptive capabilities to models with fractional derivatives, but has a clearer physical meaning. For the statistical-thermodynamic model, the procedure of its construction is described in detail, which includes the following. Introduction of a structural variable, the order parameter, to describe the orientation properties of the cell cytoskeleton. Setting and solving the statistical problem for the ensemble of actin filaments of a representative cell volume with respect to this variable. Establishment of the type of free energy depending on the order parameter, temperature and external load. It is also proposed to use an oriented-viscous-elastic body as a model of a representative element of the cell. Following the theory of linear thermodynamics, evolutionary equations describing the mechanical behavior of the representative volume of the cell are obtained, which satisfy the basic thermodynamic laws. The problem of optimizing the parameters of the statisticalthermodynamic model of the cell, which can be compared both with experimental data and with the results of simulations based on other mathematical models, is also posed and solved. The viscoelastic characteristics of cells are determined on the basis of comparison with literature data.

We propose a four-component model of a plankton community with discrete time. The model considers the competitive relationships of phytoplankton groups exhibited between each other and the trophic characteristics zooplankton displays: it considers the division of zooplankton into predatory and non-predatory components. The model explicitly represents the consumption of non-predatory zooplankton by predatory. Non-predatory zooplankton feeds on phytoplankton, which includes two competing components: toxic and non-toxic types, with the latter being suitable for zooplankton food. A model of two coupled Ricker equations, focused on describing the dynamics of a competitive community, describes the interaction of two phytoplanktons and allows implicitly taking into account the limitation of each of the competing components of biomass growth by the availability of external resources. The model describes the prey consumption by their predators using a Holling type II trophic function, considering predator saturation.

The analysis of scenarios for the transition from stationary dynamics to fluctuations in the population size of community members showed that the community loses the stability of the non-trivial equilibrium corresponding to the coexistence of the complete community both through a cascade of period-doubling bifurcations and through a Neimark – Sacker bifurcation leading to the emergence of quasi-periodic oscillations. Although quite simple, the model proposed in this work demonstrates dynamics of comunity similar to that natural systems and experiments observe: with a lag of predator oscillations relative to the prey by about a quarter of the period, long-period antiphase cycles of predator and prey, as well as hidden cycles in which the prey density remains almost constant, and the predator density fluctuates, demonstrating the influence fast evolution exhibits that masks the trophic interaction. At the same time, the variation of intra-population parameters of phytoplankton or zooplankton can lead to pronounced changes the community experiences in the dynamic mode: sharp transitions from regular to quasi-periodic dynamics and further to exact cycles with a small period or even stationary dynamics. Quasi-periodic dynamics can arise at sufficiently small phytoplankton growth rates corresponding to stable or regular community dynamics. The change of the dynamic mode in this area (the transition from stable dynamics to quasi-periodic and vice versa) can occur due to the variation of initial conditions or external influence that changes the current abundances of components and shifts the system to the basin of attraction of another dynamic mode.

The paper is devoted to the study of relationships between discrete and continuous models financial processes and their probabilistic characteristics. First, a connection is established between the price processes of stocks, hedging portfolio and options in the models conditioned by binomial perturbations and their limit perturbations of the Brownian motion type. Secondly, analogues in the coefficients of stochastic equations with various random processes, continuous and jumpwise, and in the coefficients corresponding deterministic equations for their probabilistic characteristics. Statement of the results on the connections and finding analogies, obtained in this paper, led to the need for an adequate presentation of preliminary information and results from financial mathematics, as well as descriptions of related objects of stochastic analysis. In this paper, partially new and known results are presented in an accessible form for those who are not specialists in financial mathematics and stochastic analysis, and for whom these results are important from the point of view of applications. Specifically, the following sections are presented.

• In one- and n-period binomial models, it is proposed a unified approach to determining on the probability space a risk-neutral measure with which the discounted option price becomes a martingale. The resulting martingale formula for the option price is suitable for numerical simulation. In the following sections, the risk-neutral measures approach is applied to study financial processes in continuous-time models.

• In continuous time, models of the price of shares, hedging portfolios and options are considered in the form of stochastic equations with the Ito integral over Brownian motion and over a compensated Poisson process. The study of the properties of these processes in this section is based on one of the central objects of stochastic analysis — the Ito formula. Special attention is given to the methods of its application.

• The famous Black – Scholes formula is presented, which gives a solution to the partial differential equation for the function $v(t, x)$, which, when $x = S (t)$ is substituted, where $S(t)$ is the stock price at the moment time $t$, gives the price of the option in the model with continuous perturbation by Brownian motion.

• The analogue of the Black – Scholes formula for the case of the model with a jump-like perturbation by the Poisson process is suggested. The derivation of this formula is based on the technique of risk-neutral measures and the independence lemma.

Dynamic scenarios leading to multistability in the form of continuous families of stable solutions are studied for a system of autonomous differential equations. The approach is based on determining the cosymmetries of the problem, calculating stationary solutions, and numerically-analytically studying their stability. The analysis is carried out for equations of the Lotka –Volterra type, describing the interaction of two predators feeding on two related prey species. For a system of ordinary differential equations of the 4th order with 11 real parameters, a numerical-analytical study of possible interaction scenarios was carried out. Relationships are found analytically between the control parameters under which the cosymmetry linear in the variables of the problem is realized and families of stationary solutions (equilibria) arise. The case of multicosymmetry is established and explicit formulas for a two-parameter family of equilibria are presented. The analysis of the stability of these solutions made it possible to reveal the division of the family into regions of stable and unstable equilibria. In a computational experiment, the limit cycles branching off from unstable stationary solutions are determined and their multipliers corresponding to multistability are calculated. Examples of the coexistence of families of stable stationary and non-stationary solutions are presented. The analysis is carried out for the growth functions of logistic and “hyperbolic” types. Depending on the parameters, scenarios can be obtained when only stationary solutions (coexistence of prey without predators and mixed combinations), as well as families of limit cycles, are realized in the phase space. The multistability scenarios considered in the work allow one to analyze the situations that arise in the presence of several related species in the range. These results are the basis for subsequent analysis when the parameters deviate from cosymmetric relationships.

Technological development determines the emergence of highly detailed data in time and space, which expands the possibilities of analysis, allowing us to consider consumer decisions and the competitive behavior of enterprises in all their diversity, taking into account the context of the territory and the characteristics of time periods. Despite the promise of such studies, they are currently limited in the scientific literature. This is due to the range of problems, the solution of which is considered in this paper. The article draws attention to the complexity of the analysis of depersonalized high-frequency data and the possibility of modeling consumption changes in time and space based on them. The features of the new type of data are considered on the example of real depersonalized data received from the fiscal data operator “First OFD” (JSC “Energy Systems and Communications”). It is shown that along with the spectrum of problems inherent in high-frequency data, there are disadvantages associated with the process of generating data on the side of the sellers, which requires a wider use of data mining tools. A series of statistical tests were carried out on the data under consideration, including a Unit-Root Test, test for unobserved individual effects, test for serial correlation and for cross-sectional dependence in panels, etc. The presence of spatial autocorrelation of the data was tested using modified tests of Lagrange multipliers. The tests carried out showed the presence of a consistent correlation and spatial dependence of the data, which determine the expediency of applying the methods of panel and spatial analysis in relation to high-frequency data accumulated by fiscal operators. The constructed models made it possible to substantiate the spatial relationship of sales growth and its dependence on the day of the week. The limitation for increasing the predictive ability of the constructed models and their subsequent complication, due to the inclusion of explanatory factors, was the lack of open access statistics grouped in the required detail in time and space, which determines the relevance of the formation of high-frequency geographically structured data bases.

The approach for the analysis of some large-scale biological systems, on the base of quasiequilibrium stages is proposed. The approach allows us to reduce the detailed large-scaled models and obtain the simplified model with an analytical solution. This makes it possible to reproduce the experimental curves with a good accuracy. This approach has been applied to a detailed model of the primary processes of photosynthesis in the reaction center of photosystem II. The resulting simplified model of photosystem II describes the experimental fluorescence induction curves for higher and lower plants, obtained under different light intensities. Derived relationships between variables and parameters of detailed and simplified models, allow us to use parameters of simplified model to describe the dynamics of various states of photosystem II detailed model.

Volunteer computing resembles private desktop grids whereas desktop grids are not fully equivalent to volunteer computing. There are several attempts to distinguish and categorize them using informal and formal methods. However, most formal approaches model a particular middleware and do not focus on the general notion of volunteer or desktop grid computing. This work makes an attempt to formalize their characteristics and relationship. To this end formal modeling is applied that tries to grasp the semantic of their functionalities — as opposed to comparisons based on properties, features, etc. We apply this modeling method to formalize the Berkeley Open Infrastructure for Network Computing (BOINC) [Anderson D. P., 2004] volunteer computing system.