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The article contains review of various estimation methods of combined extrusion process for the representative part, also analytical calculations and numerical simulation of this process using program DEFORM 3D. The comparative analysis of the results obtained by different methods was made. The assumptions of the main factors having a significant effect on the reliability of the results were formulated.

It is known that in the native state the DNA molecule always contains some amount of locally unwound regions, often called the open states of DNA. It is believed that these states play an important role in DNA-protein recognition and that the study of the open states dynamics may shed further light on the mechanisms of regulation of transcription and replication. In this paper we consider the effect of the thermostat on the movement of the open states in the artificial sequence consisting of four homogeneous regions. We construct the energetic profile of the sequence and investigate the trajectories of the movement of the open states under the action of a random force.

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.

This article solves the problem of developing a technology for collecting initial data for building models for assessing the functional state of a person. This condition is assessed by the pupil response of a person to a change in illumination based on the pupillometry method. This method involves the collection and analysis of initial data (pupillograms), presented in the form of time series characterizing the dynamics of changes in the human pupils to a light impulse effect. The drawbacks of the traditional approach to the collection of initial data using the methods of computer vision and smoothing of time series are analyzed. Attention is focused on the importance of the quality of the initial data for the construction of adequate mathematical models. The need for manual marking of the iris and pupil circles is updated to improve the accuracy and quality of the initial data. The stages of the proposed technology for collecting initial data are described. An example of the obtained pupillogram is given, which has a smooth shape and does not contain outliers, noise, anomalies and missing values. Based on the presented technology, a software and hardware complex has been developed, which is a collection of special software with two main modules, and hardware implemented on the basis of a Raspberry Pi 4 Model B microcomputer, with peripheral equipment that implements the specified functionality. To evaluate the effectiveness of the developed technology, models of a single-layer perspetron and a collective of neural networks are used, for the construction of which the initial data on the functional state of intoxication of a person were used. The studies have shown that the use of manual marking of the initial data (in comparison with automatic methods of computer vision) leads to a decrease in the number of errors of the 1st and 2nd years of the kind and, accordingly, to an increase in the accuracy of assessing the functional state of a person. Thus, the presented technology for collecting initial data can be effectively used to build adequate models for assessing the functional state of a person by pupillary response to changes in illumination. The use of such models is relevant in solving individual problems of ensuring transport security, in particular, monitoring the functional state of drivers.

The aim of the work is to study a monotone finite-difference scheme of the second order of accuracy, created on the basis of a generalization of the one-dimensional Z-scheme. The study was carried out for model equations of the transfer of an incompressible medium. The paper describes a two-dimensional generalization of the Z-scheme with nonlinear correction, using instead of streams oblique differences containing values from different time layers. The monotonicity of the obtained nonlinear scheme is verified numerically for the limit functions of two types, both for smooth solutions and for nonsmooth solutions, and numerical estimates of the order of accuracy of the constructed scheme are obtained.

The constructed scheme is absolutely stable, but it loses the property of monotony when the Courant step is exceeded. A distinctive feature of the proposed finite-difference scheme is the minimality of its template. The constructed numerical scheme is intended for models of plasma instabilities of various scales in the low-latitude ionospheric plasma of the Earth. One of the real problems in the solution of which such equations arise is the numerical simulation of highly nonstationary medium-scale processes in the earth’s ionosphere under conditions of the appearance of the Rayleigh – Taylor instability and plasma structures with smaller scales, the generation mechanisms of which are instabilities of other types, which leads to the phenomenon F-scattering. Due to the fact that the transfer processes in the ionospheric plasma are controlled by the magnetic field, it is assumed that the plasma incompressibility condition is fulfilled in the direction transverse to the magnetic field.

A previously developed model that describes the dynamics of social tension in a society divided into two groups: the elite and the people was considered. This model took into account the impact of economic situation changes and the elite–people interaction. The model has been modified by including in the equation describing the tension of the people, a term that takes into account the adaptation of the people to the current situation.

The model coefficients estimation is an important task, the solution of which allows obtaining information about the nature of the interaction between elite and people. We believe that the solution of the system of model equations with optimal coefficients is closest to the values of the indicator characterizing social tension. We used the normalized level of homicide rate as an indicator of social tension.

The model contains seven coefficients. Two coefficients characterizing the influence of economic situation changes on elite and people are taken equal to each other and the same for all countries. We obtained their estimations using a simplified model that takes into account only the change in the economic situation and allows an analytical solution.

The Bayesian approach was used to estimate the remaining five coefficients of model for post-Soviet countries. The prior probability densities of the four coefficients for all countries under consideration were taken to be the same. The prior probability density of fifth coefficient was considered to depend on the regime of government (authoritarian or «transitional»). We assumed that the calculated tension matches with the corresponding indicator of tension in cases where the difference between them does not exceed 5%.

The calculations showed that for the post-Soviet countries, a good coincidence was obtained between the calculated values of the people tension and the normalized level of homicide rate. The coincidence is satisfactory only on average.

The following main results was obtained at the work: under the influence of some «significant» events in 40% of post-Soviet countries, there was a rapid change in the nature of interaction between the elite and the people; regional feature have some influence on the elite–people interaction; the type of government does not significantly affect the elite–people interaction; the method for assessing the stability of the country by the value of the model coefficients is proposed.

Examining the spectral response of plants from data collected using remote sensing has a lot of potential for solving real-world problems in different fields of research. In this study, we have used the spectral property to identify the invasive plant Heracleum sosnowskyi Manden from satellite imagery. H. sosnowskyi is an invasive plant that causes many harms to humans, animals and the ecosystem at large. We have used data collected from the years 2018 to 2020 containing sample geolocation data from the Moscow Region where this plant exists and we have used Sentinel-2 imagery for the spectral analysis towards the aim of detecting it from the satellite imagery. We deployed a Random Forest (RF) machine learning model within the framework of Google Earth Engine (GEE). The algorithm learns from the collected data, which is made up of 12 bands of Sentinel-2, and also includes the digital elevation together with some spectral indices, which are used as features in the algorithm. The approach used is to learn the biophysical parameters of H. sosnowskyi from its reflectances by fitting the RF model directly from the data. Our results demonstrate how the combination of remote sensing and machine learning can assist in locating H. sosnowskyi, which aids in controlling its invasive expansion. Our approach provides a high detection accuracy of the plant, which is 96.93%.

In single-photon emission computed tomography (SPECT), patients with bone disorders receive a radiopharmaceutical (RP) that accumulates selectively in pathological lesions. Accurate quantification of RP uptake plays a critical role in disease staging, prognosis, and the development of personalized treatment strategies. Traditionally, the accuracy of quantitative assessment is evaluated through in vitro clinical trials using the standardized physical NEMA IEC phantom, which contains six spheres simulating lesions of various sizes. However, such experiments are limited by high costs and radiation exposure to researchers. This study proposes an alternative in silico approach based on numerical simulation using a digital twin of the NEMA IEC phantom. The computational framework allows for extensive testing under varying conditions without physical constraints. Analogous to clinical protocols, we calculated the recovery coefficient (RC_max), defined as the ratio of the maximum activity in a lesion to its known true value. The simulation settings were tailored to clinical SPECT/CT protocols involving ^99mTc for patients with bone-related diseases. For the first time, we systematically analyzed the impact of lesion-to-background ratios and post-reconstruction filtering on RC_max values. Numerical experiments revealed the presence of edge artifacts in reconstructed lesion images, consistent with those observed in both real NEMA IEC phantom studies and patient scans. These artifacts introduce instability into the iterative reconstruction process and lead to errors in activity quantification. Our results demonstrate that post-filtering helps suppress edge artifacts and stabilizes the solution. However, it also significantly underestimates activity in small lesions. To address this issue, we introduce post-reconstruction correction factors derived from our simulations to improve the accuracy of quantification in lesions smaller than 20 mm in diameter.

We propose an approach for the reconstruction and quantitative phenotyping of plant morphological traits at early ontogenetic stages based on digital image analysis. The proposed algorithm combines deep learning and graph-based representations while incorporating biological principles of morphogenesis. This integration enables the transition from binary segmentation to the reconstruction of a topologically consistent plant structure with accurate separation of intersecting root systems in images containing multiple plants. At the first stage, binary masks of seeds, shoots, and root systems are generated using a U-Net convolutional neural network architecture. The resulting image is transformed into a graph model in which edges correspond to root and shoot segments, while vertices represent key morphological points, including branching and intersection nodes. A directed traversal algorithm initialized from the seed point, combined with watershed-based graph partitioning and a composite scoring function for primary axis selection, identifies individual plants as isolated subgraphs and accurately distinguishes the primary root, lateral roots, and shoot. The validity of the algorithm was confirmed through a multi-level validation procedure, including comparison of graph reconstruction results on segmented images and end-to-end evaluation of the complete computational pipeline on original images against existing software solutions and expert manual annotations. The proposed approach is robust to variability in root system morphology and image noise and provides high accuracy in morphological trait extraction. The results of this study can be applied in plant breeding programs.

The article contains results of modeling of bi-modal microstructure evolution of VT6 alloy during isothermal forging. The model of recrystallization based on dislocation approach to nucleation and growth of nuclear was made to calculate recrystallization processes of the secondary alpha phase. The globularization process of lamellar alpha phase was calculated with assumption of diffusion-control migration of beta-phase boundary due to grain boundary diffusion of vanadium atom. The theoretical results were compared with experimental one.