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This work is devoted to the analysis of conformational changes in tubulin dimers and tetramers, in particular, the assessment of the bending of microtubule protofilaments. Three recently exploited approaches for estimating the bend of tubulin protofilaments are reviewed: (1) measurement of the angle between the vector passing through the H7 helices in $\alpha$ and $\beta$ tubulin monomers in the straight structure and the same vector in the curved structure of tubulin; (2) measurement of the angle between the vector, connecting the centers of mass of the subunit and the associated GTP nucleotide, and the vector, connecting the centers of mass of the same nucleotide and the adjacent tubulin subunit; (3) measurement of the three rotation angles of the bent tubulin subunit relative to the straight subunit. Quantitative estimates of the angles calculated at the intra- and inter-dimer interfaces of tubulin in published crystal structures, calculated in accordance with the three metrics, are presented. Intra-dimer angles of tubulin in one structure, measured by the method (3), as well as measurements by this method of the intra-dimer angles in different structures, were more similar, which indicates a lower sensitivity of the method to local changes in tubulin conformation and characterizes the method as more robust. Measuring the angle of curvature between H7-helices (method 1) produces somewhat underestimated values of the curvature per dimer. Method (2), while at first glance generating the bending angle values, consistent the with estimates of curved protofilaments from cryoelectron microscopy, significantly overestimates the angles in the straight structures. For the structures of tubulin tetramers in complex with the stathmin protein, the bending angles calculated with all three metrics varied quite significantly for the first and second dimers (up to 20% or more), which indicates the sensitivity of all metrics to slight variations in the conformation of tubulin dimers within these complexes. A detailed description of the procedures for measuring the bending of tubulin protofilaments, as well as identifying the advantages and disadvantages of various metrics, will increase the reproducibility and clarity of the analysis of tubulin structures in the future, as well as it will hopefully make it easier to compare the results obtained by various scientific groups.

In this work, we analyze the system of contracts made by Russian defense enterprises in the process of state defense order execution. We conclude that methods of statistical mechanics can be applied to the description of the given system. Following the original grand-canonical ensemble approach, we can create the statistical ensemble under investigation as a set of instant snapshots of indistinguishable contracts having individual values. We show that due to government regulations of contract prices the contract system can be described in terms of nonextensive Tsallis statistics. We have found that probability distributions of contract prices correspond to deformed Bose – Einstein distributions obtained using nonextensive Tsallis entropy. This conclusion is true both in the case of the whole set of contracts and in the case of the contracts made by an individual defense company as a seller.

In order to analyze how deformed Bose – Einstein distributions fit the empirical contract price distributions we compare the corresponding cumulative distribution functions. We conclude that annual distributions of individual sales which correspond to each company’s contract (order) can be used as relevant data for contract price distributions analysis. The empirical cumulative distribution functions for the individual sales ranking of Concern CSRI Elektropribor, one of the leading Russian defense companies, are analyzed for the period 2007–2021. The theoretical cumulative distribution functions, obtained using deformed Bose – Einstein distributions in the case of «rare contract gas» limit, fit well to the empirical cumulative distribution functions. The fitted values for the entropic index show that the degree of nonextensivity of the system under investigations is rather high. It is shown that the characteristic prices of distributions can be estimated by weighing the values of annual individual sales with the escort probabilities. Given that the fitted values of chemical potential are equal to zero, we suggest that «gas of contracts» can be compared to photon gas in which the number of particles is not conserved.

This paper is devoted to some variants of improving the convergence rate guarantees of the gradient-type algorithms for relatively smooth and relatively Lipschitz-continuous problems in the case of additional information about some analogues of the strong convexity of the objective function. We consider two classes of problems, namely, convex problems with a relative functional growth condition, and problems (generally, non-convex) with an analogue of the Polyak – Lojasiewicz gradient dominance condition with respect to Bregman divergence. For the first type of problems, we propose two restart schemes for the gradient type methods and justify theoretical estimates of the convergence of two algorithms with adaptively chosen parameters corresponding to the relative smoothness or Lipschitz property of the objective function. The first of these algorithms is simpler in terms of the stopping criterion from the iteration, but for this algorithm, the near-optimal computational guarantees are justified only on the class of relatively Lipschitz-continuous problems. The restart procedure of another algorithm, in its turn, allowed us to obtain more universal theoretical results. We proved a near-optimal estimate of the complexity on the class of convex relatively Lipschitz continuous problems with a functional growth condition. We also obtained linear convergence rate guarantees on the class of relatively smooth problems with a functional growth condition. For a class of problems with an analogue of the gradient dominance condition with respect to the Bregman divergence, estimates of the quality of the output solution were obtained using adaptively selected parameters. We also present the results of some computational experiments illustrating the performance of the methods for the second approach at the conclusion of the paper. As examples, we considered a linear inverse Poisson problem (minimizing the Kullback – Leibler divergence), its regularized version which allows guaranteeing a relative strong convexity of the objective function, as well as an example of a relatively smooth and relatively strongly convex problem. In particular, calculations show that a relatively strongly convex function may not satisfy the relative variant of the gradient dominance condition.

Numerical simulation of hull flow, marine propellers and other basic problems of ship hydrodynamics using Cartesian adaptive locally-refined grids is advantageous with respect to numerical setup and makes an express analysis very convenient. However, when more accurate viscous phenomena are needed, they condition some problems including a sharp increase of cell number due to high levels of main grid adaptation needed to resolve boundary layers and time step decrease in simulations with a free surface due to decrease of transit time in adapted cells. To avoid those disadvantages, additional boundary layer grids are suggested for resolution of boundary layers. The boundary layer grids are one-dimensional adaptations of main grid layers nearest to a wall, which are built along a normal direction. The boundary layer grids are additional (or chimerical), their volumes are not subtracted from main grid volumes. Governing equations of flow are integrated in both grids simultaneously, and the solutions are merged according to a special algorithm. In simulations of ship hull flow boundary layer grids are able to provide sufficient conditions for low-Reynolds turbulence models and significantly improve flow structure in continues boundary layers along smooth surfaces. When there are flow separations or other complex phenomena on a hull surface, it can be subdivided into regions, and the boundary layer grids should be applied to the regions with simple flow only. This still provides a drastic decrease of computational efforts. In simulations of marine propellers, the boundary layer grids are able to provide refuse of wall functions on blade surfaces, what leads to significantly more accurate hydrodynamic forces. Altering number and configuration of boundary grid layers, it is possible to vary a boundary layer resolution without change of a main grid. This makes the boundary layer grids a suitable tool to investigate scale effects in both problems considered.

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.

This work deals with numerical modeling of motion of the multibody systems consisting of rigid bodies with arbitrary masses and inertial properties. We consider both planar and spatial systems which may contain kinematic loops.

The numerical modeling is fully automatic and its computational algorithm contains three principal steps. On step one a graph of the considered mechanical system is formed from the userinput data. This graph represents the hierarchical structure of the mechanical system. On step two the differential-algebraic equations of motion of the system are derived using the so-called Joint Coordinate Method. This method allows to minimize the redundancy and lower the number of the equations of motion and thus optimize the calculations. On step three the equations of motion are integrated numerically and the resulting laws of motion are presented via user interface or files.

The aforementioned algorithm is implemented in the software complex that contains a computer algebra system, a graph library, a mechanical solver, a library of numerical methods and a user interface.

A Large Language Model (LLM) is an advanced artificial intelligence algorithm that utilizes deep learning methodologies and extensive datasets to process, understand, and generate humanlike text. These models are capable of performing various tasks, such as summarization, content creation, translation, and predictive text generation, making them highly versatile in applications involving natural language understanding. Generative AI, often associated with LLMs, specifically focuses on creating new content, particularly text, by leveraging the capabilities of these models. Developers can harness LLMs to automate complex processes, such as extracting relevant information from system requirement documents and translating them into a structured database schema. This capability has the potential to streamline the database design phase, saving significant time and effort while ensuring that the resulting schema aligns closely with the given requirements. By integrating LLM technology with Natural Language Processing (NLP) techniques, the efficiency and accuracy of generating database schemas based on textual requirement specifications can be significantly enhanced. The proposed tool will utilize these capabilities to read system requirement specifications, which may be provided as text descriptions or as Entity-Relationship Diagrams (ERDs). It will then analyze the input and automatically generate a relational database schema in the form of SQL commands. This innovation eliminates much of the manual effort involved in database design, reduces human errors, and accelerates development timelines. The aim of this work is to provide a tool can be invaluable for software developers, database architects, and organizations aiming to optimize their workflow and align technical deliverables with business requirements seamlessly.

Numerous contemporary studies confirm that neurons, astrocytes and blood vessels function as a unified dynamic system. Consequently, the concept of the integrated neurogliovascular unit (NGVU), encompassing these components, has emerged and gained significant traction in recent years. According to this framework, normal brain function relies on a broad complex of interactions between NGVU elements, while the disruption of these links may underlie various neuropathologies. Understanding the processes within a single NGVU, as well as the organization of connections between multiple units, is a prerequisite for successful diagnosis and therapy of neurological disorders.

In this work, we developed an NGVU model that, for the first time, integrates a detailed description of synaptically coupled excitatory and inhibitory neuronal networks (accounting for the E/I balance), extracellular environment dynamics (potassium, glutamate, GABA), and norepinephrine-modulated astrocytic activity, with subsequent regulation of local blood flow.

A key conceptual feature of the model is the integration of multiscale processes — ranging from ion dynamics at the level of individual Hodgkin – Huxley neurons to substance diffusion across a network of 100 NGVUs — into a single system of coupled nonlinear differential equations. This approach enabled the investigation of the ensemble’s collective dynamics and the identification of novel functional regimes.

Numerical experiments established that extracellular potassium dynamics and positive feedback play a decisive role in the formation of stable spatial excitation structures. It is shown that under local stimulation, activity remains confined due to potassium diffusion outflow; however, supercritical excitation initiates self-sustaining autowave regimes. The stabilization of these regimes leads to the formation of spatial patterns morphologically similar to Turing structures. These patterns, characterized by alternating zones of high and low activity, are independent of specific initial conditions but sensitive to parameter variations. This suggests that the system operates in a dynamic instability (chaos) regime, which is consistent with the concept of self-organized criticality of the brain under physiological conditions. The model successfully reproduces experimentally observed phenomena, including bursting and sensitivity to extracellular potassium. The results provide new perspectives for analyzing the pathophysiological mechanisms of brain function.

Numerical simulation of moving sportsman external flow is presented. The unique method is developed for obtaining integral aerodynamic characteristics, which were the function of the flow regime (i.e. angle of attack, flow speed) and body position. Individual anthropometric characteristics and moving boundaries of sportsman (or sports equipment) during the race are taken into consideration.

Numerical simulation is realized using FlowVision CFD. The software is based on the finite volume method, high-performance numerical methods and reliable mathematical models of physical processes. A Cartesian computational grid is used by FlowVision, the grid generation is a completely automated process. Local grid adaptation is used for solving high-pressure gradient and object complex shape. Flow simulation process performed by solutions systems of equations describing movement of fluid and/or gas in the computational domain, including: mass, moment and energy conservation equations; state equations; turbulence model equations. FlowVision permits flow simulation near moving bodies by means of computational domain transformation according to the athlete shape changes in the motion. Ski jumper aerodynamic characteristics are studied during all phases: take-off performance in motion, in-run and flight. Projected investigation defined simulation method, which includes: inverted statement of sportsman external flow development (velocity of the motion is equal to air flow velocity, object is immobile); changes boundary of the body technology defining; multiple calculations with the national team member data projecting. The research results are identification of the main factors affected to jumping performance: aerodynamic forces, rotating moments etc. Developed method was tested with active sportsmen. Ski jumpers used this method during preparations for Sochi Olympic Games 2014. A comparison of the predicted characteristics and experimental data shows a good agreement. Method versatility is underlined by performing swimmer and skater flow simulation. Designed technology is applicable for sorts of natural and technical objects.

Radiopharmaceuticals with iodine radioisotopes are now widely used in imaging and non-imaging methods of nuclear medicine. When evaluating the results of radionuclide studies of the structural and functional state of organs and tissues, parallel modeling of the kinetics of radiopharmaceuticals in the body plays an important role. The complexity of such modeling lies in two opposite aspects. On the one hand, excessive simplification of the anatomical and physiological characteristics of the organism when splitting it to the compartments that may result in the loss or distortion of important clinical diagnosis information, on the other – excessive, taking into account all possible interdependencies of the functioning of the organs and systems that, on the contrary, will lead to excess amount of absolutely useless for clinical interpretation of the data or the mathematical model becomes even more intractable. Our work develops a unified approach to the construction of mathematical models of the kinetics of radiopharmaceuticals with iodine isotopes in the human body during diagnostic and therapeutic procedures of nuclear medicine. Based on this approach, three- and four-compartment pharmacokinetic models were developed and corresponding calculation programs were created in the C⁺⁺ programming language for processing and evaluating the results of radionuclide diagnostics and therapy. Various methods for identifying model parameters based on quantitative data from radionuclide studies of the functional state of vital organs are proposed. The results of pharmacokinetic modeling for radionuclide diagnostics of the liver, kidney, and thyroid using iodine-containing radiopharmaceuticals are presented and analyzed. Using clinical and diagnostic data, individual pharmacokinetic parameters of transport of different radiopharmaceuticals in the body (transport constants, half-life periods, maximum activity in the organ and the time of its achievement) were determined. It is shown that the pharmacokinetic characteristics for each patient are strictly individual and cannot be described by averaged kinetic parameters. Within the framework of three pharmacokinetic models, “Activity–time” relationships were obtained and analyzed for different organs and tissues, including for tissues in which the activity of a radiopharmaceutical is impossible or difficult to measure by clinical methods. Also discussed are the features and the results of simulation and dosimetric planning of radioiodine therapy of the thyroid gland. It is shown that the values of absorbed radiation doses are very sensitive to the kinetic parameters of the compartment model. Therefore, special attention should be paid to obtaining accurate quantitative data from ultrasound and thyroid radiometry and identifying simulation parameters based on them. The work is based on the principles and methods of pharmacokinetics. For the numerical solution of systems of differential equations of the pharmacokinetic models we used Runge–Kutta methods and Rosenbrock method. The Hooke–Jeeves method was used to find the minimum of a function of several variables when identifying modeling parameters.