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The development of structured molecular systems based on a nucleic acid framework takes into account the ability of single-stranded DNA to form a stable double-stranded structure due to stacking interactions and hydrogen bonds of complementary pairs of nucleotides. To increase the stability of the DNA double helix and to expand the temperature range in the hybridization protocols, it was proposed to use more stable metal-mediated complexes of nucleotide pairs as an alternative to Watson-Crick hydrogen bonds. One of the most frequently considered options is the use of silver ions to stabilize a pair of cytosines from opposite DNA strands. Silver ions specifically bind to N3 cytosines along the helix axis to form, as is believed, a strong N3–Ag⁺–N3 bond, relative to which, two rotational isomers, the cis- and trans-configurations of C–Ag⁺–C can be formed. In present work, a theoretical study and a comparative analysis of the free energy profile of the dissociation of two С–Ag⁺–C isomers were carried out using the combined method of molecular mechanics and quantum chemistry (QM/MM). As a result, it was shown that the cis-configuration is more favorable in energy than the trans- for a single pair of cytosines, and the geometry of the global minimum at free energy profile for both isomers differs from the equilibrium geometries obtained previously by quantum chemistry methods. Apparently, the silver ion stabilization model of the DNA duplex should take into account not only the direct binding of silver ions to cytosines, but also the presence of related factors, such as stacking interaction in extended DNA, interplanar hydrogen bonds, and metallophilic interaction of neighboring silver ions.

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 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.

By numerical simulation methods the interaction processes of oscillating soliton (breather) with a 180-degree Neel domain wall in the framework of a (2 + 1)-dimensional supersymmetric O(3) nonlinear sigma model is studied. The purpose of this paper is to investigate nonlinear evolution and stability of a system of interacting localized dynamic and topological solutions. To construct the interaction models, were used a stationary breather and domain wall solutions, where obtained in the framework of the two-dimensional sine-Gordon equation by adding specially selected perturbations to the A3-field vector in the isotopic space of the Bloch sphere. In the absence of an external magnetic field, nonlinear sigma models have formal Lorentz invariance, which allows constructing, in particular, moving solutions and analyses the experimental data of the nonlinear dynamics of an interacting solitons system. In this paper, based on the obtained moving localized solutions, models for incident and head-on collisions of breathers with a domain wall are constructed, where, depending on the dynamic parameters of the system, are observed the collisions and reflections of solitons from each other, a long-range interactions and also the decay of an oscillating soliton into linear perturbation waves. In contrast to the breather solution that has the dynamics of the internal degree of freedom, the energy integral of a topologically stable soliton in the all experiments the preserved with high accuracy. For each type of interaction, the range of values of the velocity of the colliding dynamic and topological solitons is determined as a function of the rotation frequency of the A3-field vector in the isotopic space. Numerical models are constructed on the basis of methods of the theory of finite difference schemes, using the properties of stereographic projection, taking into account the group-theoretical features of constructions of the O(N) class of nonlinear sigma models of field theory. On the perimeter of the two-dimensional modeling area, specially developed boundary conditions are established that absorb linear perturbation waves radiated by interacting soliton fields. Thus, the simulation of the interaction processes of localized solutions in an infinite two-dimensional phase space is carried out. A software module has been developed that allows to carry out a complex analysis of the evolution of interacting solutions of nonlinear sigma models of field theory, taking into account it’s group properties in a two-dimensional pseudo-Euclidean space. The analysis of isospin dynamics, as well the energy density and energy integral of a system of interacting dynamic and topological solitons is carried out.

Analysis and practical aspects of implementing developed in the control theory robust control methods in studying economic systems is carried out. The main emphasis is placed on studying results obtained for dynamical systems with structured uncertainty. Practical aspects of implementing such results in control of economic systems on the basis of dynamical models with uncertain parameters and perturbations (stabilization of price on the oil market and inflation in macroeconomic systems) are discussed. With the help of specially constructed aggregate model of oil price dynamics studied the problem of finding control which provides minimal deviation of price from desired levels over middle range period. The second real problem considered in the article consists in determination of stabilizing control providing minimal deviation of inflation from desired levels (on the basis of constructed aggregate macroeconomic model of the USA over middle range period).

Upper levels of parameters uncertainty and control laws guaranteeing stabilizability of the real considered economic systems have been found using the robust method of control with structured uncertainty. At the same time we have come to the conclusion that received estimates of parameters uncertainty upper levels are conservative. Monte-Carlo experiments carried out for the article made it possible to analyze dynamics of oil price and inflation under received limit levels of models parameters uncertainty and under implementing found robust control laws for the worst and the best scenarios. Results of these experiments show that received robust control laws may be successfully used under less stringent uncertainty constraints than it is guaranteed by sufficient conditions of stabilization.

The repressilator is the first genetic regulatory network in synthetic biology, which was artificially constructed in 2000. It is a closed network of three genetic elements $lacI$, $\lambda cI$ and $tetR$, which have a natural origin, but are not found in nature in such a combination. The promoter of each of the three genes controls the next cistron via the negative feedback, suppressing the expression of the neighboring gene. In our previous paper [Bratsun et al., 2018], we proposed a mathematical model of a delayed repressillator and studied its properties within the framework of a deterministic description. We assume that delay can be both natural, i.e. arises during the transcription / translation of genes due to the multistage nature of these processes, and artificial, i.e. specially to be introduced into the work of the regulatory network using gene engineering technologies. In this work, we apply the stochastic description of dynamic processes in a delayed repressilator, which is an important addition to deterministic analysis due to the small number of molecules involved in gene regulation. The stochastic study is carried out numerically using the Gillespie algorithm, which is modified for time delay systems. We present the description of the algorithm, its software implementation, and the results of benchmark simulations for a onegene delayed autorepressor. When studying the behavior of a repressilator, we show that a stochastic description in a number of cases gives new information about the behavior of a system, which does not reduce to deterministic dynamics even when averaged over a large number of realizations. We show that in the subcritical range of parameters, where deterministic analysis predicts the absolute stability of the system, quasi-regular oscillations may be excited due to the nonlinear interaction of noise and delay. Earlier, we have discovered within the framework of the deterministic description, that there exists a long-lived transient regime, which is represented in the phase space by a slow manifold. This mode reflects the process of long-term synchronization of protein pulsations in the work of the repressilator genes. In this work, we show that the transition to the cooperative mode of gene operation occurs a two order of magnitude faster, when the effect of the intrinsic noise is taken into account. We have obtained the probability distribution of moment when the phase trajectory leaves the slow manifold and have determined the most probable time for such a transition. The influence of the intrinsic noise of chemical reactions on the dynamic properties of the repressilator is discussed.

The paper presents an analysis of the nonlinear equation of spin wave transport by the method of characteristics. The conclusion of a new mathematical model of spin wave propagation is presented for the solution of which the characteristic is applied. The behavior analysis of the behavior of the real and imaginary parts of the wave and its amplitude is performed. The phase portraits demonstrate the dependence of the desired function on the nonlinearity coefficient. It is established that the real and imaginary parts of the wave oscillate by studying the nature of the evolution of the initial wave profile by the phase plane method. The transition of trajectories from an unstable focus to a limiting cycle, which corresponds to the oscillation of the real and imaginary parts, is shown. For the amplitude of the wave, such a transition is characterized by its amplification or attenuation (depending on the nonlinearity coefficient and the chosen initial conditions) up to a certain threshold value. It is shown that the time of the transition process from amplification (attenuation) to stabilization of the amplitude also depends on the nonlinearity parameter. It was found out that at the interval of amplification of the amplitude of the spin wave, the time of the transition process decreases, and lower amplitude values correspond to higher parameters of nonlinearity.

A method is proposed for analyzing the tremor of the earth’s surface, measured by means of space geodesy, in order to highlight the prognostic effects of seismicity activation. The method is illustrated by the example of a joint analysis of a set of synchronous time series of daily vertical displacements of the earth’s surface on the Japanese Islands for the time interval 2009–2023. The analysis is based on dividing the source data (1047 time series) into blocks (clusters of stations) and sequentially applying the principal component method. The station network is divided into clusters using the K-means method from the maximum pseudo-F-statistics criterion, and for Japan the optimal number of clusters was chosen to be 15. The Huang decomposition method into a sequence of independent empirical oscillation modes (EMD — Empirical Mode Decomposition) is applied to the time series of principal components from station blocks. To provide the stability of estimates of the waveforms of the EMD decomposition, averaging of 1000 independent additive realizations of white noise of limited amplitude was performed. Using the Cholesky decomposition of the covariance matrix of the waveforms of the first three EMD components in a sliding time window, indicators of abnormal tremor behavior were determined. By calculating the correlation function between the average indicators of anomalous behavior and the released seismic energy in the vicinity of the Japanese Islands, it was established that bursts in the measure of anomalous tremor behavior precede emissions of seismic energy. The purpose of the article is to clarify common hypotheses that movements of the earth’s crust recorded by space geodesy may contain predictive information. That displacements recorded by geodetic methods respond to the effects of earthquakes is widely known and has been demonstrated many times. But isolating geodetic effects that predict seismic events is much more challenging. In our paper, we propose one method for detecting predictive effects in space geodesy data.

Base long-term modern scenarios of hydrochemical and temperature regimes of the Sea of Azov were considered. New schemes of modeling mechanisms of algal adaptation to changes in the hydrochemical regime and temperature were proposed. In comparison to the traditional ecological-evolutionary schemes, these models have a relatively small dimension, high speed and allow carrying out various calculations on long-term perspective (evolutionally significant times). Based on the ecology-evolutionary model of the lower trophic levels the impact of these environmental factors on the dynamics and microevolution of algae in the Sea of Azov was estimated. In each scenario, the calculations were made for 100 years, with the final values of the variables and parameters not depending on the choice of the initial values. In the process of such asymptotic computer analysis, it was found that as a result of climate warming and temperature adaptation of organisms, the average annual biomass of thermophilic algae (Pyrrophyta and Cyanophyta) naturally increases. However, for a number of diatom algae (Bacillariophyta), even with their temperature adaptation, the average annual biomass may unexpectedly decrease. Probably, this phenomenon is associated with a toughening of competition between species with close temperature parameters of existence. The influence of the variation in the chemical composition of the Don River’s flow on the dynamics of nutrients and algae of the Sea of Azov was also investigated. It turned out that the ratio of organic forms of nitrogen and phosphorus in sea waters varies little. This stabilization phenomenon will take place for all high-productive reservoirs with low flow, due to autochthonous origin of larger part of organic matter in water bodies of this type.

In the conditions of the development of modern economy, human capital is one of the main factors of economic growth. The formation of human capital begins with the birth of a person and continues throughout life, so the value of human capital is inseparable from its carriers, which in turn makes it difficult to account for this factor. This has led to the fact that currently there are no generally accepted methods of calculating the value of human capital. There are only a few approaches to the measurement of human capital: the cost approach (by income or investment) and the index approach, of which the most well-known approach developed under the auspices of the UN.

This paper presents the assigned task in conjunction with the task of demographic dynamics solved in the time-age plane, which allows to more fully take into account the temporary changes in the demographic structure on the dynamics of human capital.

The task of demographic dynamics is posed within the framework of the Mac-Kendrick – von Foerster model on the basis of the equation of age structure dynamics. The form of distribution functions for births, deaths and migration of the population is determined on the basis of the available statistical information. The numerical solution of the problem is given. The analysis and forecast of demographic indicators are presented. The economic and mathematical model of human capital dynamics is formulated on the basis of the demographic dynamics problem. The problem of modeling the human capital dynamics considers three components of capital: educational, health and cultural (spiritual). Description of the evolution of human capital components uses an equation of the transfer equation type. Investments in human capital components are determined on the basis of budget expenditures and private expenditures, taking into account the characteristic time life cycle of demographic elements. A one-dimensional kinetic equation is used to predict the dynamics of the total human capital. The method of calculating the dynamics of this factor is given as a time function. The calculated data on the human capital dynamics are presented for the Russian Federation. As studies have shown, the value of human capital increased rapidly until 2008, in the future there was a period of stabilization, but after 2014 there is a negative dynamics of this value.