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The paper deals with a prey-predator model, which describes the spatiotemporal dynamics of plankton community and the nutrients. The system is described by reaction-diffusion-advection equations in a onedimensional vertical column of water in the surface layer. Advective term of the predator equation represents the vertical movements of zooplankton with velocity, which is assumed to be proportional to the gradient of phytoplankton density. This study aimed to determine the conditions under which these movements (taxis) lead to the spatially heterogeneous structures generated by the system. Assuming diffusion coefficients of all model components to be equal the instability of the system in the vicinity of stationary homogeneous state with respect to small inhomogeneous perturbations is analyzed.

Necessary conditions for the flow-induced instability were obtained through linear stability analysis. Depending on the local kinetics parameters, increasing the taxis rate leads to Turing or wave instability. This fact is in good agreement with conditions for the emergence of spatial and spatiotemporal patterns in a minimal phytoplankton–zooplankton model after flow-induced instabilities derived by other authors. This mechanism of generating patchiness is more general than the Turing mechanism, which depends on strong conditions on the diffusion coefficients.

While the taxis exceeding a certain critical value, the wave number corresponding to the fastest growing mode remains unchanged. This value determines the type of spatial structure. In support of obtained results, the paper presents the spatiotemporal dynamics of the model components demonstrating Turing-type pattern and standing wave pattern.

The article presents the numerical modeling and study of the kinetic model of propane pyrolysis. The study of the reaction kinetics is a necessary stage in modeling the dynamics of the gas flow in the reactor.

The kinetic model of propane pyrolysis is a nonlinear system of ordinary differential equations of the first order with parameters, the role of which is played by the reaction rate constants. Math modeling of processes is based on the use of the mass conservation law. To solve an initial (forward) problem, implicit methods for solving stiff ordinary differential equation systems are used. The model contains 60 input kinetic parameters and 17 output parameters corresponding to the reaction substances, of which only 9 are observable. In the process of solving the problem of estimating parameters (inverse problem), there is a question of non-uniqueness of the set of parameters that satisfy the experimental data. Therefore, before solving the inverse problem, the possibility of determining the parameters of the model is analyzed (analysis of identifiability).

To analyze identifiability, we use the orthogonal method, which has proven itself well for analyzing models with a large number of parameters. The algorithm is based on the analysis of the sensitivity matrix by the methods of differential and linear algebra, which shows the degree of dependence of the unknown parameters of the models on the given measurements. The analysis of sensitivity and identifiability showed that the parameters of the model are stably determined from a given set of experimental data. The article presents a list of model parameters from most to least identifiable. Taking into account the analysis of the identifiability of the mathematical model, restrictions were introduced on the search for less identifiable parameters when solving the inverse problem.

The inverse problem of estimating the parameters was solved using a genetic algorithm. The article presents the found optimal values of the kinetic parameters. A comparison of the experimental and calculated dependences of the concentrations of propane, main and by-products of the reaction on temperature for different flow rates of the mixture is presented. The conclusion about the adequacy of the constructed mathematical model is made on the basis of the correspondence of the results obtained to physicochemical laws and experimental data.

Modeling banking systems using a network approach has received growing attention in recent years. One of the notable models is that developed by Iori et al, who proposed a banking system model for analyzing systemic risks in interbank networks. The model is built based on the simple dynamics of several bank balance sheet variables such as deposit, equity, loan, liquid asset, and interbank lending (or borrowing) in the form of difference equations. Each bank faces random shocks in deposits and loans. The balance sheet is updated at the beginning or end of each period. In the model, banks are grouped into either potential lenders or borrowers. The potential borrowers are those that have lack of liquidity and the potential lenders are those which have excess liquids after dividend payment and channeling new investment. The borrowers and the lenders are connected through the interbank market. Those borrowers have some percentage of linkage to random potential lenders for borrowing funds to maintain their safety net of the liquidity. If the demand for borrowing funds can meet the supply of excess liquids, then the borrower bank survives. If not, they are deemed to be in default and will be removed from the banking system. However, in their paper, most part of the interbank borrowing-lending mechanism is described qualitatively rather than by detailed mathematical or computational analysis. Therefore, in this paper, we enhance the mathematical parts of borrowing-lending in the interbank market and present an algorithm for simulating the model. We also perform some simulations to analyze the effects of the model’s parameters on banking stability using the number of surviving banks as the measure. We apply this technique to analyze the effects of a macroprudential policy called loan-to-deposit ratio based reserve requirement for banking stability.

Road noise is one of the key issues in maintaining high environmental standards. At speeds between 50 and 120 km/h, tires are the main source of noise generated by a moving vehicle. It is well known that either the interaction between the tire tread and the road surface or some internal dynamic effects are responsible for tire noise and vibration. This paper discusses the application of a new method for modelling the generation and propagation of sound during tire motion, based on the application of the so-called acoustic-vortex decomposition. Currently, the application of the Lighthill equation and the aeroacoustics analogy are the main approaches used to model tire noise. The aeroacoustics analogy, in solving the problem of separating acoustic and vortex (pseudo-sound) modes of vibration, is not a mathematically rigorous formulation for deriving the source (righthand side) of the acoustic wave equation. In the development of the acoustic-vortex decomposition method, a mathematically rigorous transformation of the equations of motion of a compressible medium is performed to obtain an inhomogeneous wave equation with respect to static enthalpy pulsations with a source term that de-pends on the velocity field of the vortex mode. In this case, the near-field pressure fluctuations are the sum of acoustic fluctuations and pseudo-sound. Thus, the acoustic-vortex decomposition method allows to adequately modeling the acoustic field and the dynamic loads that generate tire vibration, providing a complete solution to the problem of modelling tire noise, which is the result of its turbulent flow with the generation of vortex sound, as well as the dynamic loads and noise emission due to tire vibration. The method is first implemented and test-ed in the FlowVision software package. The results obtained with FlowVision are compared with those obtained with the LMS Virtual.Lab Acoustics package and a number of differences in the acoustic field are highlighted.

The numerical methods developed by the author recently for calculating the molecular system based on the direct solution of the Schrodinger equation by the Monte Carlo method have shown a huge uncertainty in the choice of solutions. On the one hand, it turned out to be possible to build many new solutions; on the other hand, the problem of their connection with reality has become sharply aggravated. In ab initio quantum mechanical calculations, the problem of choosing solutions is not so acute after the transition to the classical format of describing a molecular system in terms of potential energy, the method of molecular dynamics, etc. In this paper, we investigate the problem of choosing solutions in the classical format of describing a molecular system without taking into account quantum mechanical prerequisites. As it turned out, the problem of choosing solutions in the classical format of describing a molecular system is reduced to a specific marking of the configuration space in the form of a set of stationary points and reconstruction of the corresponding potential energy function. In this formulation, the solution of the choice problem is reduced to two possible physical and mathematical problems: to find all its stationary points for a given potential energy function (the direct problem of the choice problem), to reconstruct the potential energy function for a given set of stationary points (the inverse problem of the choice problem). In this paper, using a computational experiment, the direct problem of the choice problem is discussed using the example of a description of a monoatomic cluster. The number and shape of the locally equilibrium (saddle) configurations of the binary potential are numerically estimated. An appropriate measure is introduced to distinguish configurations in space. The format of constructing the entire chain of multiparticle contributions to the potential energy function is proposed: binary, threeparticle, etc., multiparticle potential of maximum partiality. An infinite number of locally equilibrium (saddle) configurations for the maximum multiparticle potential is discussed and illustrated. A method of variation of the number of stationary points by combining multiparticle contributions to the potential energy function is proposed. The results of the work listed above are aimed at reducing the huge arbitrariness of the choice of the form of potential that is currently taking place. Reducing the arbitrariness of choice is expressed in the fact that the available knowledge about the set of a very specific set of stationary points is consistent with the corresponding form of the potential energy function.

We consider an approach based on linear algebra methods to analyze the rate of electron transport through the cytochrome $b_6 f$ complex. In the proposed approach, the dependence of the quasi-stationary electron flux through the complex on the degree of reduction of pools of mobile electron carriers is considered a response function characterizing this process. We have developed software in the Python programming language that allows us to construct the master equation for the complex according to the scheme of elementary reactions and calculate quasi-stationary electron transport rates through the complex and the dynamics of their changes during the transition process. The calculations are performed in multithreaded mode, which makes it possible to efficiently use the resources of modern computing systems and to obtain data on the functioning of the complex in a wide range of parameters in a relatively short time. The proposed approach can be easily adapted for the analysis of electron transport in other components of the photosynthetic and respiratory electron-transport chain, as well as other processes in multienzyme complexes containing several reaction centers. Cryo-electron microscopy and redox titration data were used to parameterize the model of cytochrome $b_6 f$ complex. We obtained dependences of the quasi-stationary rate of plastocyanin reduction and plastoquinone oxidation on the degree of reduction of pools of mobile electron carriers and analyzed the dynamics of rate changes in response to changes in the redox state of the plastoquinone pool. The modeling results are in good agreement with the available experimental data.

In the article, a quasi-periodic two-component dynamical model with possibility of defining the cardio-cycle morphology, that provides the model with an ability of generating a temporal and a spectral cardiosignal characteristics, including heart rate variability is described. A technique for determining the cardio-cycle morphology to provide realistic cardio-signal form is defined. A method for defining cardio-signal dynamical system by the way of determining a three-dimensional state space and equations which describe a trajectory of point’s motion in this space is presented. A technique for solving equations of motion in the three-dimensional state space of dynamical cardio-signal system using the fourth-order Runge–Kutta method is presented. Based on this model, algorithm and software package are developed. Using software package, a cardio-signal synthesis experiment is conducted and the relationship of cardio-signal diagnostic features is analyzed.

In this paper the method of concentrations is applied to the human genome. The dynamical characteristics of three different genes (ADRB2, NOS1, IL-5) with the established effect on bronchial asthma.

Now days the main research activity in the field of nanotechnology is aimed at the creation, study and application of new materials and new structures. Recently, much attention has been attracted by the possibility of controlling magnetic properties using a superconducting current, as well as the influence of magnetic dynamics on the current–voltage characteristics of hybrid superconductor/ferromagnet (S/F) nanostructures. In particular, such structures include the S/F/S Josephson junction or molecular nanomagnets coupled to the Josephson junctions. Theoretical studies of the dynamics of such structures need processes of a large number of coupled nonlinear equations. Numerical modeling of hybrid superconductor/magnet nanostructures implies the calculation of both magnetic dynamics and the dynamics of the superconducting phase, which strongly increases their complexity and scale, so it is advisable to use heterogeneous computing systems.

In the course of studying the physical properties of these objects, it becomes necessary to numerically solve complex systems of nonlinear differential equations, which requires significant time and computational resources.

The currently existing micromagnetic algorithms and frameworks are based on the finite difference or finite element method and are extremely useful for modeling the dynamics of magnetization on a wide time scale. However, the functionality of existing packages does not allow to fully implement the desired computation scheme.

The aim of the research is to develop a unified environment for modeling hybrid superconductor/magnet nanostructures, providing access to solvers and developed algorithms, and based on a heterogeneous computing paradigm that allows research of superconducting elements in nanoscale structures with magnets and hybrid quantum materials. In this paper, we investigate resonant phenomena in the nanomagnet system associated with the Josephson junction. Such a system has rich resonant physics. To study the possibility of magnetic reversal depending on the model parameters, it is necessary to solve numerically the Cauchy problem for a system of nonlinear equations. For numerical simulation of hybrid superconductor/magnet nanostructures, a computing environment based on the heterogeneous HybriLIT computing platform is implemented. During the calculations, all the calculation times obtained were averaged over three launches. The results obtained here are of great practical importance and provide the necessary information for evaluating the physical parameters in superconductor/magnet hybrid nanostructures.

The paper investigates the dynamics of a finite-dimensional model describing the interaction of three populations: prey $x(t)$, its consuming predator $y(t)$, and a superpredator $z(t)$ that feeds on both species. Mathematically, the problem is formulated as a system of nonlinear first-order differential equations with the following right-hand side: $[x(1-x)-(y+z)g;\,\eta_1^{}yg-d_1^{}f-\mu_1^{}y;\,\eta_2^{}zg+d_2^{}f-\mu_2^{}z]$, where $\eta_j^{}$, $d_j^{}$, $\mu_j^{}$ ($j=1,\,2$) are positive coefficients. The considered model belongs to the class of cosymmetric dynamical systems under the Lotka\,--\,Volterra functional response $g=x$, $f=yz$, and two parameter constraints: $\mu_2^{}=d_2^{}\left(1+\frac{\mu_1^{}}{d_1^{}}\right)$, $\eta_2^{}=d_2^{}\left(1+\frac{\eta_1^{}}{d_1^{}}\right)$. In this case, a family of equilibria is being of a straight line in phase space. We have analyzed the stability of the equilibria from the family and isolated equilibria. Maps of stationary solutions and limit cycles have been constructed. The breakdown of the family is studied by violating the cosymmetry conditions and using the Holling model $g(x)=\frac x{1+b_1^{}x}$ and the Beddington–DeAngelis model $f(y,\,z)=\frac{yz}{1+b_2^{}y+b_3^{}z}$. To achieve this, the apparatus of Yudovich's theory of cosymmetry is applied, including the computation of cosymmetric defects and selective functions. Through numerical experimentation, invasive scenarios have been analyzed, encompassing the introduction of a superpredator into the predator-prey system, the elimination of the predator, or the superpredator.