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Numerical modeling of turbulent flows requires finding the balance between accuracy and computational efficiency. For example, DNS and LES models allow to obtain more accurate results, comparing to RANS models, but are more computationally expensive. Because of this, modern applied simulations are mostly performed with RANS models. But even RANS models can be computationally expensive for complex geometries or series simulations due to the necessity of resolving the boundary layer. Some methods, such as wall functions and near-wall domain decomposition, allow to significantly improve the speed of RANS simulations. However, they inevitably lose precision due to using a simplified model in the near-wall domain. To obtain a model that is both accurate and computationally efficient, it is possible to construct a surrogate model based on previously made simulations using the precise model.

In this paper, an operator is constructed that allows reconstruction of the flow field obtained by an accurate model based on the flow field obtained by the simplified model. Spalart–Allmaras model with approximate nearwall domain decomposition and Spalart–Allmaras model resolving the near-wall region are taken as the simplified and the base models respectively. The operator is constructed using a local approach, i. e. to reconstruct a point in the flow field, only features (flow variables and their derivatives) at this point in the field are used. The operator is constructed using the Random Forest algorithm. The efficiency and accuracy of the obtained surrogate model are demonstrated on the supersonic flow over a compression corner with different values for angle $\alpha$ and Reynolds number. The investigation has been conducted into interpolation and extrapolation both by $Re$ and $\alpha$.

In Russian medicine two radiopharmaceuticals are currently used for radionuclide therapy of bone metastases: ⁸⁹Sr-chloride and ¹⁵³Sm-oxabifor. The first one has many side effects, so its use is limited. The second one is available only in clinics, its transportation to which does not take much time. Currently, the third radiopharmaceutical ¹⁸⁸Re-solerene is undergoing clinical trials. Due to the generator method of obtaining ¹⁸⁸Re, this radiopharmaceutical should become available for use in many regions of our country. Therefore, there is a need for a comparative analysis of the characteristics of these radiopharmaceuticals, including on the basis of mathematical modeling.

The article discusses the features of mathematical modeling the kinetics of osteotropic radiopharmaceutical drugs in the human body with bone metastases. Based on the four-compartment model, a complex of modeling and calculation of pharmacokinetic and dosimetric characteristics of radiopharmaceuticals for radionuclide therapy of bone metastases was developed and tested. Using clinical data, the transport constants of the model were identified and the individual characteristics of Russian radiopharmaceuticals labeled ⁸⁹Sr, 153Sm and ¹⁸⁸Re were calculated (effective half-lives, maximum activity in the compartments and the times of their achievement, absorbed doses to bone tissue and metastases, endosteal bone layer, red bone marrow, blood, kidneys and bladder). The time activity dependencies for all compartments of the model are obtained and analyzed. A comparative analysis of the pharmacokinetics and dosimetry of three radiopharmaceuticals (⁸⁹Sr-chloride, ¹⁵³Sm-oxabiphore, ¹⁸⁸Re-solerene) was carried out.

From a comparative analysis of the pharmacokinetic and dosimetric characteristics of these radiopharmaceutical drugs, it follows that the best of them for widespread use in many regions of our country should be ¹⁸⁸Re-solerene, taking into account the generator method of obtaining ¹⁸⁸Re in a hospital.

This work is devoted to the study of the problem of modeling and analyzing complex oscillatory modes, both regular and chaotic, in systems of interacting populations in the presence of random perturbations. As an initial conceptual deterministic model, a Volterra system of three differential equations is considered, which describes the dynamics of prey populations of two competing species and a predator. This model takes into account the following key biological factors: the natural increase in prey, their intraspecific and interspecific competition, the extinction of predators in the absence of prey, the rate of predation by predators, the growth of the predator population due to predation, and the intensity of intraspecific competition in the predator population. The growth rate of the second prey population is used as a bifurcation parameter. At a certain interval of variation of this parameter, the system demonstrates a wide variety of dynamic modes: equilibrium, oscillatory, and chaotic. An important feature of this model is multistability. In this paper, we focus on the study of the parametric zone of tristability, when a stable equilibrium and two limit cycles coexist in the system. Such birhythmicity in the presence of random perturbations generates new dynamic modes that have no analogues in the deterministic case. The aim of the paper is a detailed study of stochastic phenomena caused by random fluctuations in the growth rate of the second population of prey. As a mathematical model of such fluctuations, we consider white Gaussian noise. Using methods of direct numerical modeling of solutions of the corresponding system of stochastic differential equations, the following phenomena have been identified and described: unidirectional stochastic transitions from one cycle to another, trigger mode caused by transitions between cycles, noise-induced transitions from cycles to the equilibrium, corresponding to the extinction of the predator and the second prey population. The paper presents the results of the analysis of these phenomena using the Lyapunov exponents, and identifies the parametric conditions for transitions from order to chaos and from chaos to order. For the analytical study of such noise-induced multi-stage transitions, the technique of stochastic sensitivity functions and the method of confidence regions were applied. The paper shows how this mathematical apparatus allows predicting the intensity of noise, leading to qualitative transformations of the modes of stochastic population dynamics.

The main aim, formulated in the first part of article, is to carry out detailed numerical studies of the chemical, ionization, optical, and temperature characteristics of the lower ionosphere perturbed by powerful radio emission. The brief review of the main experimental and theoretical researches of physical phenomena occurring in the ionosphere when it is heated by high-power high-frequency radio waves from heating facilities is given. The decisive role of the $D$-region of the ionosphere in the absorption of radio beam energy is shown. A detailed analysis of kinetic processes in the disturbed $D$-region, which is the most complex in kinetic terms, has been performed. It is shown that for a complete description of the ionization-chemical and optical characteristics of the disturbed region, it is necessary to take into account more than 70 components, which, according to their main physical content, can be conveniently divided into five groups. A kinetic model is presented to describe changes in the concentrations of components interacting (the total number of reactions is 259). The system of kinetic equations was solved using a semi-implicit numerical method specially adapted to such problems. Based on the proposed structure, a software package was developed in which the algorithm scheme allowed changing both the content of individual program blocks and their number, which made it possible to conduct detailed numerical studies of individual processes in the behavior of the parameters of the perturbed region. The complete numerical algorithm is based on the two-temperature approximation, in which the main attention was paid to the calculation of the electron temperature, since its behavior is determined by inelastic kinetic processes involving electrons. The formulation of the problem is of a rather general nature and makes it possible to calculate the parameters of the disturbed ionosphere in a wide range of powers and frequencies of radio emission. Based on the developed numerical technique, it is possible to study a wide range of phenomena both in the natural and disturbed ionosphere.

The article deals with the nonlinear boundary-value problem of hydrogen permeability corresponding to the following experiment. A membrane made of the target structural material heated to a sufficiently high temperature serves as the partition in the vacuum chamber. Degassing is performed in advance. A constant pressure of gaseous (molecular) hydrogen is built up at the inlet side. The penetrating flux is determined by mass-spectrometry in the vacuum maintained at the outlet side.

A linear model of dependence on concentration is adopted for the coefficient of dissolved atomic hydrogen diffusion in the bulk. The temperature dependence conforms to the Arrhenius law. The surface processes of dissolution and sorptiondesorption are taken into account in the form of nonlinear dynamic boundary conditions (differential equations for the dynamics of surface concentrations of atomic hydrogen). The characteristic mathematical feature of the boundary-value problem is that concentration time derivatives are included both in the diffusion equation and in the boundary conditions with quadratic nonlinearity. In terms of the general theory of functional differential equations, this leads to the so-called neutral type equations and requires a more complex mathematical apparatus. An iterative computational algorithm of second-(higher- )order accuracy is suggested for solving the corresponding nonlinear boundary-value problem based on explicit-implicit difference schemes. To avoid solving the nonlinear system of equations at every time step, we apply the explicit component of difference scheme to slower sub-processes.

The results of numerical modeling are presented to confirm the fitness of the model to experimental data. The degrees of impact of variations in hydrogen permeability parameters (“derivatives”) on the penetrating flux and the concentration distribution of H atoms through the sample thickness are determined. This knowledge is important, in particular, when designing protective structures against hydrogen embrittlement or membrane technologies for producing high-purity hydrogen. The computational algorithm enables using the model in the analysis of extreme regimes for structural materials (pressure drops, high temperatures, unsteady heating), identifying the limiting factors under specific operating conditions, and saving on costly experiments (especially in deuterium-tritium investigations).

This paper presents new research results that have been conducted at the Institute of Economics of the Russian Academy of Sciences since 2011 under the leadership of Academician of the Russian Academy of Sciences V. I.Mayevsky. These works are aimed at developing the theory of switching mode of reproduction and corresponding mathematical models, the peculiarity of which is that they explicitly model the interaction of the financial and real sectors of the economy, and the country’s economy itself is not disaggregated according to the sectoral principle (engineering, agriculture, services, etc.), but by production subsystems that differ from each other by the age of the fixed capital. One of the mathematical difficulties of working with such models, called models of switching mode of reproduction (SMR), is the difficulty of modeling competitive relationships between subsystems of different “ages”. Therefore, until now, the interaction of a finite number of production subsystems has been considered in the SMR models, the models themselves were of a discrete-continuous nature, calculations were done exclusively on computers, and obtaining analytical dependencies was difficult. This paper shows that for the special case of balanced economic growth and a continuum of production subsystems, it is possible to obtain analytical expressions that allow a better understanding of the impact of monetary policy on economic dynamics. In addition to purely scientific interest, this is of great practical importance, since it allows us to assess the possible reaction of the real sector of the economy to changes in the monetary sphere without conducting complex simulation calculations.

Aberrant alternative splicing of the CD44 gene drives colorectal cancer progression and facilitates the emergence of cancer stem cells. Although biomedical research recognizes this transmembrane glycoprotein as a major catalyst of malignancy, deciphering its multi-isoform regulatory networks remains a complex analytical challenge. To address this knowledge gap, this study presents a machine learning framework designed to decode these biological mechanisms. The author constructed a neural network regressor based on beta regression to model bounded isoform proportions. This computational architecture jointly estimates both the mean and the precision parameters of the underlying probability distribution. Furthermore, the system employs elastic net regularization to perform quantitative feature selection from highdimensional molecular expression data.

The investigation evaluates the proposed framework using gene expression profiles from colorectal cancer patients. The primary objective involves identifying specific ribonucleic acid-binding proteins acting as regulatory splicing factors. The experimental design contrasts two distinct mathematical modeling strategies. The first configuration incorporates an independent ”one-vs-all” approach that treats each transcript variant as an isolated regression target. The second formulation utilizes a structured ”isoform tree” method that directly mirrors hierarchical exon inclusion relationships. Validation experiments on synthetically generated datasets confirmed the mathematical integrity of the network. The model recovered true distribution parameters with precision and exhibited no systematic bias. Comprehensive empirical comparisons subsequently demonstrated that the independent ”one-vs-all” layout consistently outperforms the hierarchical tree configuration in predictive stability and accuracy.

The computational analysis maps the regulatory landscape of the CD44 gene. The framework validates several established splicing factors while uncovering new candidate proteins, including ACO1, NUDT21, and AGO2. Based on these statistical associations, the paper introduces a biological hypothesis. This concept functionally connects intracellular iron metabolism via the ACO1 protein with the shifting balance of CD44 variants. These discoveries provide deeper insights into oncogenic splicing regulation. Ultimately, they highlight molecular targets for future therapeutic interventions aimed at suppressing the cancer stem cell phenotype.

Kinetics of complex formation between components of the photosynthetic electron transport chain — flavodoxin and membrane complex photosystem I has been studied using computer model based on methods of multiparticle simulation and Brownian dynamics. We simulated Brownian motion of several hundreds of flavodoxin molecules, taking into account electrostatic interactions and complex shape of the molecules. Our model could describe experimental nonmonotonic dependence of the association rate constant for flavodoxin and photosystem I. This lets us conclude that electrostatic interactions are sufficient to form such kind of nonmonotonic dependence.

It is known that the internal mobility of DNA molecules plays an important role in the functioning of these molecules. This explains the great interest of researchers in studying the internal dynamics of DNA. Complexity, laboriousness and high cost of research in this field stimulate the search and creation of simpler physical analogues, convenient for simulating the various dynamic regimes possible in DNA. One of the directions of such a search is connected with the use of a mechanical analogue of DNA — a chain of coupled pendulums. In this model, pendulums imitate nitrous bases, horizontal thread on which pendulums are suspended, simulates a sugarphosphate chain, and gravitational field simulates a field induced by a second strand of DNA. Simplicity and visibility are the main advantages of the mechanical analogue. However, the model becomes too cumbersome in cases where it is necessary to simulate long (more than a thousand base pairs) DNA sequences. Another direction is associated with the use of an electronic analogue of the DNA molecule, which has no shortcomings of the mechanical model. In this paper, we investigate the possibility of using the Josephson line as an electronic analogue. We calculated the coefficients of the direct and indirect transformations for the simple case of a homogeneous, synthetic DNA, the sequence of which contains only adenines. The internal mobility of the DNA molecule was modeled by the sine-Gordon equation for angular vibrations of nitrous bases belonging to one of the two polynucleotide chains of DNA. The second polynucleotide chain was modeled as a certain average field in which these oscillations occur. We obtained the transformation, allowing the transition from DNA to an electronic analog in two ways. The first includes two stages: (1) the transition from DNA to the mechanical analogue (a chain of coupled pendulums) and (2) the transition from the mechanical analogue to the electronic one (the Josephson line). The second way is direct. It includes only one stage — a direct transition from DNA to the electronic analogue.

In this paper, we address the mathematical modeling of robots based on tensegrity structures. The pivotal property of such structures is the forming elements working only for compression or tension, which allows the use of materials and structural solutions that minimize the weight of the structure while maintaining its strength.

Tensegrity structures hold several properties important for collaborative robotics, exploration and motion tasks in non-deterministic environments: natural compliance, compactness for transportation, low weight with significant impact resistance and rigidity. The control of such structures remains an open research problem, which is associated with the complexity of describing the dynamics of such structures.

We formulate an approach for describing the dynamics of such structures, based on second-order dynamics of the Cartesian coordinates of structure elements (rods), first-order dynamics for angular velocities of rods, and first-order dynamics for quaternions that are used to describe the orientation of rods. We propose a numerical method for solving these dynamic equations. The proposed methods are implemented in the form of a freely distributed mathematical package with open source code.

Further, we show how the provided software package can be used for modeling the dynamics and determining the operating modes of tensegrity structures. We present an example of a tensegrity structure moving in zero gravity with three rigid rods and nine elastic elements working in tension (cables), showing the features of the dynamics of the structure in reaching the equilibrium position. The range of initial conditions for which the structure operates in the normal mode is determined. The results can be directly used to analyze the nature of passive dynamic movements of the robots based on a three-link tensegrity structure, considered in the paper; the proposed modeling methods and the developed software are suitable for modeling a significant variety of tensegrity robots.