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The repressor 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 this paper, the nonlinear dynamics of a modified repressilator, which has time delays in all parts of the regulatory network, has been studied for the first time. 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 synthetic biology technologies. It is assumed that the regulation is carried out by proteins being in a dimeric form. The considered repressilator has two more important modifications: the location on the same plasmid of the gene $gfp$, which codes for the fluorescent protein, and also the presence in the system of a DNA sponge. In the paper, the nonlinear dynamics has been considered within the framework of the deterministic description. By applying the method of decomposition into fast and slow motions, the set of nonlinear differential equations with delay on a slow manifold has been obtained. It is shown that there exists a single equilibrium state which loses its stability in an oscillatory manner at certain values of the control parameters. For a symmetric repressilator, in which all three genes are identical, an analytical solution for the neutral Andronov–Hopf bifurcation curve has been obtained. For the general case of an asymmetric repressilator, neutral curves are found numerically. It is shown that the asymmetric repressor generally is more stable, since the system is oriented to the behavior of the most stable element in the network. Nonlinear dynamic regimes arising in a repressilator with increase of the parameters are studied in detail. It was found that there exists a limit cycle corresponding to relaxation oscillations of protein concentrations. In addition to the limit cycle, we found the slow manifold not associated with above cycle. This is the long-lived transitional regime, which reflects the process of long-term synchronization of pulsations in the work of individual genes. The obtained results are compared with the experimental data known from the literature. The place of the model proposed in the present work among other theoretical models of the repressilator is discussed.

The article is devoted to the effect of thermal feedback, which occurs during the operation of integrated circuits and electronic systems with their use. Thermal feedback is due to the fact that the power consumed by the functioning of the microchip heats it and, due to the significant dependence of its electrical parameters on temperature, interactive interaction arises between its electrical and thermal processes. The effect of thermal feedback leads to a change in both electrical parameters and temperature levels in microcircuits. Positive thermal feedback is an undesirable phenomenon, because it causes the output of the electrical parameters of the microcircuits beyond the permissible values, the reduction in reliability and, in some cases, burn out. Negative thermal feedback is manifested in stabilizing the electrical and thermal regimes at lower temperature levels. Therefore, when designing microcircuits and electronic systems with their application, it is necessary to achieve the implementation of negative feedback. In this paper, we propose a method for modeling of thermal modes in electronic systems, taking into account the effect of thermal feedback. The method is based on introducing into the thermal model of the electronic system new model circuit elements that are nonlinearly dependent on temperature, the number of which is equal to the number of microcircuits in the electronic system. This approach makes it possible to apply matrix-topological equations of thermal processes to the thermal model with new circuit elements introduced into it and incorporate them into existing thermal design software packages. An example of modeling a thermal process in a real electronic system is presented, taking into account the effect of thermal feedback on the example of a microcircuit installed on a printed circuit board. It is shown that in order to adequately model the electrical and thermal processes of microcircuits and electronic systems, it is necessary to take into account the effects of thermal feedback in order to avoid design errors and create competitive electronic systems.

The paper presents a mathematical model that describes the process of obtaining biogas from livestock waste. This model describes the processes occurring in a biogas plant for mesophilic and thermophilic media, as well as for continuous and periodic modes of substrate inflow. The values of the coefficients of this model found earlier for the periodic mode, obtained by solving the problem of model identification from experimental data using a genetic algorithm, are given.

For the model of methanogenesis, an optimal control problem is formulated in the form of a Lagrange problem, whose criterial functionality is the output of biogas over a certain period of time. The controlling parameter of the task is the rate of substrate entry into the biogas plant. An algorithm for solving this problem is proposed, based on the numerical implementation of the Pontryagin maximum principle. In this case, a hybrid genetic algorithm with an additional search in the vicinity of the best solution using the method of conjugate gradients was used as an optimization method. This numerical method for solving an optimal control problem is universal and applicable to a wide class of mathematical models.

In the course of the study, various modes of submission of the substrate to the digesters, temperature environments and types of raw materials were analyzed. It is shown that the rate of biogas production in the continuous feed mode is 1.4–1.9 times higher in the mesophilic medium (1.9–3.2 in the thermophilic medium) than in the periodic mode over the period of complete fermentation, which is associated with a higher feed rate of the substrate and a greater concentration of nutrients in the substrate. However, the yield of biogas during the period of complete fermentation with a periodic mode is twice as high as the output over the period of a complete change of the substrate in the methane tank at a continuous mode, which means incomplete processing of the substrate in the second case. The rate of biogas formation for a thermophilic medium in continuous mode and the optimal rate of supply of raw materials is three times higher than for a mesophilic medium. Comparison of biogas output for various types of raw materials shows that the highest biogas output is observed for waste poultry farms, the least — for cattle farms waste, which is associated with the nutrient content in a unit of substrate of each type.

The article describes the basic approaches of the calculation procedure of payload swim-out (objects of different function with own propulsor) from the underwater carrier a method of a self-exit using modern CFD technologies. It contains the description of swim-out by a self-exit method, its advantages and disadvantages. Also it contains results of research of convergence on a grid of a final-volume model with accuracy-time criterion, and results of comparison of calculation with experiment (validation of models). Validation of models was carried out using the available data of experimental definition of traction characteristics of water-jet propulsor of the natural sample in the development pool. Calculations of traction characteristics of water-jet propulsor were carried out via software package FlowVision ver. 3.10. On the basis of comparison of results of calculations for conditions of carrying out of experiments the error of water-jet propulsor calculated model which has made no more than 5% in a range of advance coefficient water-jet propulsor, realised in the process of swim-out by a selfexit method has been defined. The received value of an error of calculation of traction characteristics is used for definition of limiting settlement values of speed of branch of object from the carrier (the minimum and maximum values). The considered problem is significant from the scientific point of view thanks to features of the approach to modelling hydrojet moving system together with movement of separated object, and also from the practical point of view, thanks to possibility of reception with high degree of reliability of parametres swim-out of objects from sea bed vehicles a method of the self-exit which working conditions are assumed by movement in the closed volumes, already on a design stage.

The article deals with the problem of a distributed system operation reliability. The system core is an open integration platform that provides interaction of varied software for modeling gas transportation. Some of them provide an access through thin clients on the cloud technology “software as a service”. Mathematical models of operation, transmission and computing are to ensure the operation of an automated dispatching system for oil and gas transportation. The paper presents a system solution based on the theory of Markov random processes and considers the stable operation stage. The stationary operation mode of the Markov chain with continuous time and discrete states is described by a system of Chapman–Kolmogorov equations with respect to the average numbers (mathematical expectations) of the objects in certain states. The objects of research are both system elements that are present in a large number – thin clients and computing modules, and individual ones – a server, a network manager (message broker). Together, they are interacting Markov random processes. The interaction is determined by the fact that the transition probabilities in one group of elements depend on the average numbers of other elements groups.

The authors propose a multi-criteria dispersion model of risk assessment for such systems (both in the broad and narrow sense, in accordance with the IEC standard). The risk is the standard deviation of estimated object parameter from its average value. The dispersion risk model makes possible to define optimality criteria and whole system functioning risks. In particular, for a thin client, the following is calculated: the loss profit risk, the total risk of losses due to non-productive element states, and the total risk of all system states losses.

Finally the paper proposes compromise schemes for solving the multi-criteria problem of choosing the optimal operation strategy based on the selected set of compromise criteria.

Automated urban traffic monitoring systems are widely used to solve various tasks in intelligent transport systems of different regions. They include video enforcement, video surveillance, traffic management system, etc. Effective traffic management and rapid response to traffic incidents require continuous monitoring and analysis of information from these complexes, as well as time series forecasting for further anomaly detection in traffic flow. To increase the forecasting quality, data fusion from different sources is needed. It will reduce the forecasting error, related to possible incorrect values and data gaps. We implemented the approach for short-term and middle-term forecasting of traffic flow (5, 10, 15 min) based on data fusion from video enforcement and video surveillance systems. We made forecasting using different recurrent neural network architectures: LSTM, GRU, and bidirectional LSTM with one and two layers. We investigated the forecasting quality of bidirectional LSTM with 64 and 128 neurons in hidden layers. The input window size (1, 4, 12, 24, 48) was investigated. The RMSE value was used as a forecasting error. We got minimum RMSE = 0.032405 for basic LSTM with 64 neurons in the hidden layer and window size = 24.

The paper considers the process of flow formation in an outflow of a binary gas mixture through a thin slit into vacuum. An approach to modeling the flows of rarefied gas mixtures in the transient regime is proposed based on the direct solution of the Boltzmann kinetic equation, in which the conservative projection method is used to calculate the collision integrals. Calculation formulas are provided; the calculation procedure is described in detail in relation to the flow of a binary gas mixture. The Lennard–Jones potential is used as an interaction potential of molecules. A software modeling environment has been developed that makes it possible to study the flows of gas mixtures in a transitional regime on systems of cluster architecture. Due to the use of code parallelization technologies, an acceleration of calculations by 50–100 times was obtained. Numerical simulation of a two-dimensional outflow of a binary argon-neon gas mixture from a vessel into vacuum through a thin slit is carried out for various values of the Knudsen number. The graphs of the dependence of gas mixture components output flow on time in the process of establishing the flow are obtained. Non-stationary regions of strong separation of gas mixture components, in which the molecular densities ratio reaches 10 or more, were discovered. The discovered effect can have applications in the problem of gas mixtures separation.

The study of the Volterra model describing the competition of three types is carried out. The corresponding system of first-order differential equations with a quadratic right-hand side, after a change of variables, reduces to a system with eight parameters. Two of them characterize the growth rates of populations; for the first species, this parameter is taken equal to one. The remaining six coefficients define the species interaction matrix. Previously, in the analytical study of the so-called symmetric model [May, Leonard, 1975] and the asymmetric model [Chi, Wu, Hsu, 1998] with growth factors equal to unity, relations were established for the interaction coefficients, under which the system has a one-parameter family of limit cycles. In this paper, we carried out a numerical-analytical study of the complete system based on a cosymmetric approach, which made it possible to determine the ratios for the parameters that correspond to families of equilibria. Various variants of oneparameter families are obtained and it is shown that they can consist of both stable and unstable equilibria. In the case of an interaction matrix with unit coefficients, a multicosymmetry of the system and a two-parameter family of equilibria are found that exist for any growth coefficients. For various interaction coefficients, the values of growth parameters are found at which periodic regimes are realized. Their belonging to the family of limit cycles is confirmed by the calculation of multipliers. In a wide range of values that violate the relationships under which the existence of cycles is ensured, a slow oscillatory establishment, typical of the destruction of cosymmetry, is obtained. Examples are given where a fixed value of one growth parameter corresponds to two values of another parameter, so that there are different families of periodic regimes. Thus, the variability of scenarios for the development of a three-species system has been established.

The COVID-19 pandemic has caused increased interest in mathematical models of the epidemic process, since only statistical analysis of morbidity does not allow medium-term forecasting in a rapidly changing situation.

Among the specific features of COVID-19 that need to be taken into account in mathematical models are the heterogeneity of the pathogen, repeated changes in the dominant variant of SARS-CoV-2, and the relative short duration of post-infectious immunity.

In this regard, solutions to a system of differential equations for a SIR class model with a heterogeneous duration of post-infectious immunity were analytically studied, and numerical calculations were carried out for the dynamics of the system with an average duration of post-infectious immunity of the order of a year.

For a SIR class model with a heterogeneous duration of post-infectious immunity, it was proven that any solution can be continued indefinitely in time in a positive direction without leaving the domain of definition of the system.

For the contact number $R_0 \leqslant 1$, all solutions tend to a single trivial stationary solution with a zero share of infected people, and for $R_0 > 1$, in addition to the trivial solution, there is also a non-trivial stationary solution with non-zero shares of infected and susceptible people. The existence and uniqueness of a non-trivial stationary solution for $R_0 > 1$ was proven, and it was also proven that it is a global attractor.

Also, for several variants of heterogeneity, the eigenvalues of the rate of exponential convergence of small deviations from a nontrivial stationary solution were calculated.

It was found that for contact number values corresponding to COVID-19, the phase trajectory has the form of a twisting spiral with a period length of the order of a year.

This corresponds to the real dynamics of the incidence of COVID-19, in which, after several months of increasing incidence, a period of falling begins. At the same time, a second wave of incidence of a smaller amplitude, as predicted by the model, was not observed, since during 2020–2023, approximately every six months, a new variant of SARS-CoV-2 appeared, which was more infectious than the previous one, as a result of which the new variant replaced the previous one and became dominant.

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.