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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.

In some cases, information warfare results in almost whole population accepting one of two contesting points of view and rejecting the other. In other cases, however, the “majority party” gets only a small advantage over the “minority party”. The relevant question is which network characteristics of a population contribute to the minority being able to maintain some significant numbers. Given that some societies are more connected than others, in the sense that they have a higher density of social ties, this question is specified as follows: how does the density of social ties affect the chances of a minority to maintain a significant number? Does a higher density contribute to a landslide victory of majority, or to resistance of minority? To address this issue, we consider information warfare between two parties, called the Left and the Right, in the population, which is represented as a network, the nodes of which are individuals, and the connections correspond to their acquaintance and describe mutual influence. At each of the discrete points in time, each individual decides which party to support based on their attitude, i. e. predisposition to the Left or Right party and taking into account the influence of his network ties. The influence means here that each tie sends a cue with a certain probability to the individual in question in favor of the party that themselves currently support. If the tie switches their party affiliation, they begin to agitate the individual in question for their “new” party. Such processes create dynamics, i. e. the process of changing the partisanship of individuals. The duration of the warfare is exogenously set, with the final time point roughly associated with the election day. The described model is numerically implemented on a scale-free network. Numerical experiments have been carried out for various values of network density. Because of the presence of stochastic elements in the model, 200 runs were conducted for each density value, for each of which the final number of supporters of each of the parties was calculated. It is found that with higher density, the chances increase that the winner will cover almost the entire population. Conversely, low network density contributes to the chances of a minority to maintain significant numbers.

Deposit benchmark interest rates are a policy implemented by banking regulators to calculate the interest rates offered to depositors, maintaining equitable and competitive rates within the financial industry. It functions as a benchmark for determining the pricing of different banking products, expenses, and financial choices. The benchmark rate will have a direct impact on the amount of money deposited, which in turn will determine the amount of money available for lending.We are motivated to analyze the influence of deposit benchmark interest rates on the dynamics of banking loans. This study examines the issue using a difference equation of banking loans. In this process, the decision on the loan amount in the next period is influenced by both the present loan volume and the information on its marginal profit. An analysis is made of the loan equilibrium point and its stability. We also analyze the bifurcations that arise in the model. To ensure a stable banking loan, it is necessary to set the benchmark rate higher than the flip value and lower than the transcritical bifurcation values. The confirmation of this result is supported by the bifurcation diagram and its associated Lyapunov exponent. Insufficient deposit benchmark interest rates might lead to chaotic dynamics in banking lending. Additionally, a bifurcation diagram with two parameters is also shown. We do numerical sensitivity analysis by examining contour plots of the stability requirements, which vary with the deposit benchmark interest rate and other parameters. In addition, we examine a nonstandard difference approach for the previous model, assess its stability, and make a comparison with the standard model. The outcome of our study can provide valuable insights to the banking regulator in making informed decisions regarding deposit benchmark interest rates, taking into account several other banking factors.

Modern mathematical models in the dynamics system “soil–plant” are considered. The components of this system are: agricultural plant, microorganisms of the rhizosphere (root zone of plants), the mineral nutrition elements of plants in their mobile and immobile forms. The model of submitted system based on the analysis of the adopted provisions was developed. The construction of system elements allows to display the coordinated dynamics of these elements among themselves. In particular, the dynamics of mineral nutrition elements in plants and the dynamics of their biomass are determined by the current contents in the rhizosphere of mineral fertilizers and organic origin substances (plant roots, leaves, etc.). The immobility of plants spatial distribution and the mobile spatial nature of microorganisms are assumed. This mechanism is determined by diffusion. Mutual relationships between weeds and pests are suggested. The dynamics of the mineral nutrition elements is determined by the peculiarity of sorption in the soil solution, environmental conditions, organic decomposition and fertilizer application. An analytical study for a system where each of the components is represented by only one species (fertilizer, the association of microorganisms and plants) was performed. An adaptation of the wave propagation model in the “resource–consumer” system (Kolmogorov–Petrovsky–Piskunov waves) has been developed for annual agricultural crops. The developed model has been adapted for the growth of Krasnoufimskaya-100 spring wheat in a vessel on peat lowland soil, where nitrogen, phosphorus, and potassium fertilizers were added variably. Sample distributions are plants biomass and the content of mineral nutrition elements in them. The parametric identification of the model and its adequacy was performed. An assessment of the model adequacy showed a good agreement between the model and experimental data.

Despite the widespread use of cancer chemotherapy drugs, the molecular mechanisms of action of many of them remain unclear. Some of these drugs, such as taxol, are known to affect the dynamics of microtubule assembly and stop the process of cell division in prophase-prometaphase. Recently, new spatial structures of microtubules and individual tubulin oligomers have emerged associated with various regulatory proteins and cancer chemotherapy drugs. However, knowledge of the spatial structure in itself does not provide information about the mechanism of action of drugs.

In this work, we applied the molecular dynamics method to study the behavior of taxol-bound tubulin oligomers and used our previously developed method for analyzing the conformation of tubulin protofilaments, based on the calculation of modified Euler angles. Recent structures of microtubule fragments have demonstrated that tubulin protofilaments bend not in the radial direction, as many researchers assume, but at an angle of approximately 45◦ from the radial direction. However, in the presence of taxol, the bending direction shifts closer to the radial direction. There was no significant difference between the mean bending and torsion angles of the studied tubulin structures when bound to the various natural regulatory ligands, guanosine triphosphate and guanosine diphosphate. The intra-dimer bending angle was found to be greater than the interdimer bending angle in all analyzed trajectories. This indicates that the bulk of the deformation energy is stored within the dimeric tubulin subunits and not between them. Analysis of the structures of the latest generation of tubulins indicated that the presence of taxol in the tubulin beta subunit pocket allosterically reduces the torsional rigidity of the tubulin oligomer, which could explain the underlying mechanism of taxol’s effect on microtubule dynamics. Indeed, a decrease in torsional rigidity makes it possible to maintain lateral connections between protofilaments, and therefore should lead to the stabilization of microtubules, which is what is observed in experiments. The results of the work shed light on the phenomenon of dynamic instability of microtubules and allow to come closer to understanding the molecular mechanisms of cell division.

The work focuses on mathematical modeling of light influence mechanisms on macromolecular composition of microalgae batch culture. It is shown that even with a single limiting factor, the growth of microalgae is associated with a significant change in the biochemical composition of the biomass in any part of the batch curve. The well-known qualitative models of microalgae are based on concepts of enzymatic kinetics and do not take into account the possible change of the limiting factor during batch culture growth. Such models do not allow describing the dynamics of the relative content of biochemical components of cells. We proposed an alternative approach which is based on generally accepted two-stage photoautotrophic growth of microalgae. Microalgae biomass can be considered as the sum of two macromolecular components — structural and reserve. At the first stage, during photosynthesis a reserve part of biomass is formed, from which the biosynthesis of cell structures occurs at the second stage. Model also assumes the proportionality of all biomass structural components which greatly simplifies mathematical calculations and experimental data fitting. The proposed mathematical model is represented by a system of two differential equations describing the synthesis of reserve biomass compounds at the expense of light and biosynthesis of structural components from reserve ones. The model takes into account that a part of the reserve compounds is spent on replenishing the pool of macroergs. The rates of synthesis of structural and reserve forms of biomass are given by linear splines. Such approach allows us to mathematically describe the change in the limiting factor with an increase in the biomass of the enrichment culture of microalgae. It is shown that under light limitation conditions the batch curve must be divided into several areas: unlimited growth, low cell concentration and optically dense culture. The analytical solutions of the basic system of equations describing the dynamics of macromolecular biomass content made it possible to determine species-specific coefficients for various light conditions. The model was verified on the experimental data of biomass growth and dynamics of chlorophyll $a$ content of the red marine microalgae Pоrphуridium purpurеum batch culture.

Muscle contraction is controlled by Ca2+ ions via regulatory proteins, troponin and tropomyosin, associated with thin actin filaments in sarcomeres. Depending on the Ca2+ concentration, the thin filament rearranges so that tropomyosin moves along its surface, opening or closing access to actin for the motor domains of myosin molecules, and causing contraction or relaxation, respectively. Numerous point amino acid substitutions in tropomyosin are known, leading to genetic pathologies — myo- and cardiomyopathies caused by changes in the structural and functional properties of the thin filament. The results of molecular dynamics modeling of a fragment of a thin filament of cardiac muscle sarcomeres formed by fibrillar actin and wildtype tropomyosin or with amino acid substitutions: the double stabilizing substitution D137L/G126R and the cardiomyopathic substitution S215L are presented. For numerical calculations, we used a new model of a thin filament fragment containing 26 actin monomers and 4 tropomyosin dimers, with a refined structure of the region of overlap of neighboring tropomyosin molecules in each of the two tropomyosin strands. The simulation results showed that tropomyosin significantly increases the bending stiffness of the thin filament, as previously found experimentally. The double stabilizing replacement D137L/G126R leads to a further increase in this rigidity, and the replacement S215L, on the contrary, leads to its decrease, which also corresponds to experimental data. At the same time, these substitutions have different effects on the angular mobility of the actin helix and only slightly modulate the angular mobility of tropomyosin cables relative to the actin helix and the population of hydrogen bonds between negatively charged tropomyosin residues and positively charged actin residues. The results of the verification of the new model demonstrate that its quality is sufficient for the numerical study of the effect of single amino acid substitutions on the structure and dynamics of thin filaments and study the effects leading to dysregulation of muscle contraction. This model can be used as a useful tool for elucidating the molecular mechanisms of some genetic diseases and assessing the pathogenicity of newly discovered genetic variants.

Virtual machines are usually associated with an ability to create them on demand by calling web services, then these machines are used to deliver resident services to their clients; however, providing clients with an ability to run an arbitrary programme on the newly created machines is beyond their power. Such kind of usage is useful in a high performance computing environment where most of the resources are consumed by batch programmes and not by daemons or services. In this case a cluster of virtual machines is created on demand to run a distributed or parallel programme and to save its output to a network attached storage. Upon completion this cluster is destroyed and resources are released. With certain modifications this approach can be extended to interactively deliver computational resources to the user thus providing virtual desktop as a service. Experiments show that the process of creating virtual clusters on demand can be made efficient in both cases.

A new approach to the identification of hardly perceptible diagnostically significant changes in electrocardiograms is suggested. The approach is based on the analysis of topological transformations in wavelet spectra associated with electrocardiograms. Possible practical application of the approach developed is discussed.

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.