One of the promising projects of the IV generation reactors is water-cooled power reactors with supercritical coolant pressure (VVER-SKD), which is capable of increasing the efficiency of VVER power units by increasing the pressure to 23.5-25 MPa and increasing the coolant temperature to 380-540 °C. One of the main problems that will have to be faced when developing the VVER-SKD project is the choice of cladding materials for a fuel element capable of operating at supercritical coolant parameters. To solve this problem, it is necessary to conduct in-reactor tests and post-reactor studies of candidate structural materials for fuel element cladding. For this purpose, it is necessary to develop an irradiation device that could ensure in-reactor tests of candidate structural materials for fuel element cladding under SCP coolant conditions. In the course of the work, thermal hydraulic calculations of the irradiation device design were carried out using the SolidWorks software package. The calculation results showed that this design of the irradiation device will allow for in-reactor testing of VVER-SKD fuel rod mockups at supercritical coolant parameters in the SM-3 research reactor facility.

The aim of this work is a comparative analysis of methods for improving spectral resolution in the detection of closely spaced spectral lines under conditions of their partial overlap. The main focus is on the second derivative method, which enhances the contrast between components by emphasizing high-frequency features of the signal. Within numerical modeling in the MATLAB environment, two approaches were investigated: direct detection of the total signal and analysis of its second derivative. The simulation was performed for two identical Gaussian signals with a variable interpeak distance d, supplemented by additive noise. The results showed that the second derivative method reduces the minimum visual resolution threshold from d_direct = 2.1 to d_mod = 1.6, providing a 31% gain in resolving power. However, noise fluctuations (SNR = 40 dB) significantly distort the derivative signals, masking the troughs between peaks. Smoothing the data with a moving average partially suppresses the noise but leads to peak broadening by 15%, demonstrating a compromise between accuracy and preservation of the signal shape.

This paper presents a method for analyzing data from cosmic-ray muon detectors, enabling the detection of subtle flux variations that are indistinguishable in the integral muon count rate. The method requires detectors capable of distinguishing muons by their azimuthal arrival angles and, for optimal performance, multiple independent detectors with similar characteristics. A key feature of the proposed approach is that it considers not only the amplitude of the signal (reflecting muon flux variations) but also its direction, which can be correlated with the spatial characteristics of variation sources, such as atmospheric phenomena. Each step of the method is illustrated using the example of a warm front approaching Moscow, as well as an atmospheric event accompanied by a cloud line. Additionally, the paper presents a data visualization for the new method that allows a large amount of data to be reduced to a single diagram that can be plotted on satellite images and the observed muon variations can be compared with atmospheric phenomena in situ

In this paper, one of generalized Vakhnenko-Parkes’ family equations is considered describing the propagation of short-wave disturbances in relaxing media, taking into account the dependence of the wave velocity on the amplitude. A general quadrature solution is obtained for the equation under consideration by reducing it to an ordinary differential equation using traveling wave variables. Some formal exact solutions of the initial equation are found. Periodic exact solutions are expressed in terms of Jacobi elliptic functions. An explicit solution is also presented, expressed in terms of a power function of spatial and temporal variables. The obtained exact solutions can be used as test functions when analyzing the results of numerical simulation of processes in relaxing medium described by Vakhnenko-Parkes type equations.

In the framework of mean-field approximation, the influence of social contacts on the spread of an epidemic in a population of constant size is discussed. This aspect, which seems to be not fully explored yet, is getting increasing attention in mathematical epidemiology. The key point of the proposed model is that it highlights two-infection transfer mechanisms depending on the physical nature of the contact between people. We separate the transfer mechanism related directly to the movement of people (the so-called transport processes) from the one occurring at zero relative speed of persons (the so-called social contacts). Under the framework of the proposed physical chemical analogy, this approach allows us uniformly to come to the description of the rate constants of infection transmission of different nature. The resulting transmission rate constants are used to modify the SEIS model to examine the influence of social activity on the formation of endemic equilibrium in the population under consideration. The frequency of social contacts is estimated with the Dunbar approach and direct statistical calculation based on the binomial distribution. Both methods provide close values, the ones are used to determine the permissible range of values ​for the infection transmission rate constant, employed to establish endemic equilibrium. The necessary conditions for the existence of this equilibrium, depending on both social and medical-biological factors, are also obtained.

The use of quantum technologies in the modern world poses significant challenges to the security of critical information infrastructure, which underpins key sectors such as healthcare, energy, transportation, and communications. Cryptographic algorithms like RSA and ECC, long considered reliable, have lost their resilience in the face of quantum computing capabilities, making the search for modern solutions to ensure data protection a top priority. The main risks posed by quantum computers include the potential compromise of encryption algorithms, disruption of data integrity, and destabilization of critical system operations. The methodological foundation of this study is based on the analysis of 318 sources from international databases such as Scopus, Web of Science, and others. From this body of literature, 24 publications most relevant to the topic were selected. A comparative method was employed to analyze classical and quantum threats. The aim of the study is to examine the impact of quantum attacks on the security of critical information infrastructure (CII) at the current level and propose pathways for transitioning to quantum-resilient solutions. The results emphasize the necessity of implementing innovative cryptographic approaches, such as lattice-based and code-based algorithms, as well as combined (hybrid) technologies. Successful protection of the infrastructure requires a systematic approach, including a comprehensive audit of existing systems, training of specialists, and the removal of technical and regulatory barriers. The developed step-by-step plan minimizes risks and establishes a foundation for the secure implementation of new standards.

In the context of expanding Earth remote sensing capabilities, increasing availability of diverse satellite data, and the need for efficient geospatial analysis, effective transformation and integration of synthetic aperture radar (SAR) and optical (RGB) imagery has become highly relevant. We propose a reversible diffusion model based on the Schrodinger bridge for bidirectional transformation of unpaired SAR and RGB images. A multi-step stochastic process progressively perturbs the data with noise, while a U-Net-based neural network denoises each step. A bidirectional scheme ensures reversibility: the forward generator converts optical images into radar, and the backward generator does the opposite. Both components are trained iteratively under an entropy-regularized stochastic control framework, aligning intermediate distributions and preserving key scene structures. The model was tested on the SEN1-2 and SN6-SAROPT datasets. According to PSNR, SSIM, and FID metrics, it surpasses traditional GAN-based approaches (e.g., CycleGAN) and one-way diffusion models. Moreover, for the complete RGB→SAR→RGB cycle, the discrepancy from the original image remains under 5–10% (SSIM). The approach can be applied to generate missing imagery, support multisensor data analysis, and mitigate cloud coverage in optical domains.

The work studied terahertz (THz) transmission spectra of hexogen (RDX, cyclotrimethylenetrinitramine) film experimentally and theoretically in the frequency region of the intense characteristic absorption band of RDX ~0.8 THz at different incidence angles (0˚ – 60˚) and polarization of the probing THz radiation. Registration of experimental THz transmission spectra of the RDX sample was carried out using a THz radio vision setup with spectral resolution. For mathematical modeling of the spectra, the method of characteristic matrices of the medium (transfer matrices) was used. It is shown that both in the experimental and in the theoretical THz transmission spectra of the RDX film for all studied incidence angles and polarizations of the probing THz radiation, the manifestation of the hexogen absorption band in the form of a local minimum in the frequency region of ~0.8 THz is clearly observed. The results of the work can be used in the development of terahertz systems designed for the spectral identification of substances in a condensed state.

The pair correlation function of inhomogeneities in samples is actively studied using small-angle scattering methods. Recently, it has become possible to determine this function from atom probe tomography (APT) data. This work examines the influence of the finite size and shape of a sample on the pair correlation function of inhomogeneities derived from APT data.

In a large cubic sample whose dimensions in all directions significantly exceed the characteristic correlation radius, the number of impurities near the sample boundaries can be considered much smaller than in the bulk. If this assumption is not fulfilled, a geometric factor arises, for which a general expression has been derived. The geometric meaning of this factor is the probability of a specific interpoint distance presence within the sample. For the case in which the sample is an elongated rectangular parallelepiped, an analytical expression for the geometric factor in terms of elementary functions is obtained.

The following model systems were considered: a completely uncorrelated distribution of centers, a simple cubic lattice, and a densely packed system of polydisperse hard spheres. These systems were chosen due to their differing degrees of spatial order. It is shown that accounting for the geometric factor yields the correct pair correlation function for the selected model systems of inhomogeneities.