Thermal power plants are the most flexible concerning power level regulation. Furthermore, nuclear power plants are preferentially used for base load. Presently, electrical power systems require continuous adjustment of the nuclear energy produced. Consequently, it becomes imperative to adapt nuclear power plants to new specific operating conditions in load following operation. To solve this problem, advanced algorithms are proposed for the improvement of power control at nuclear power plants. Therefore, a special algorithm has been developed in which temperature regulation is introduced to reduce the amplitude impact of existing regulators, such as control rods and dissolved boric acid. The effect of temperature regulation on load following modes for VVER-1000 and VVER-1200 reactors, on the axial offset, and on the volume of water exchange required to control the reactor power is analyzed in this work. It has been found that the use of temperature regulation to operate nuclear power plants in load following modes makes it possible to keep the current axial offset in the recommended area and to reduce water exchange by more than 40 %.

   In nonlinear optics, great attention is currently paid to the analysis of nonlinear differential equations describing the propagation of solitary waves in optical media. In this work, the system of partial differential equations of the sixth order is studied to describe the propagation of two waves in a Bragg grating. This system includes nonlinearities of the third, fifth, and seventh degrees. To solve the problem, we apply the simplest equation method variance for finding solitary wave solutions. At the first step, the system is transformed to a system of ordinary differential equations by using the traveling wave variables. The resulting system is an overdetermined system consisting of four equations corresponding to the real and imaginary parts of the initial equations. From the equations corresponding to the imaginary parts, some restrictions for the parameters of initial partial differential equations are obtained. The pole order of the general solutions for the differential equations corresponding to the real parts is determined. This pole order allows us to use the simplest equations method to construct solutions in the form of solitary waves. Thus, the analytical solutions are constructed and graphs with different values of the mathematical model parameters are analyzed.

   The principle of determining the sizes during inspection of irradiated fuel assemblies by the ultrasonic echo-pulse method is considered. The factors caused by the presence of residual heat release in the fuel assemblies that affect the propagation path of ultrasound in the medium are presented. In the geometric acoustics approximation, a mathematical model of the acoustic path is developed. The medium in which ultrasound propagates is considered in the approximation of a plane–parallel layered fluid medium with a monotonic variation of the temperature and density of water from layer to layer. It is assumed that the water temperature between the sensors and the surface of the fuel assembly is determined by convective heat transfer between the fuel assembly and the water in the pool of a nuclear power plant. The model takes into account the instability of the speed of sound and the refraction of ultrasonic waves during the oblique incidence of waves on the surface. The proposed model allows the study of the acoustic tract with the ultrasonic echo-pulse method. This model can be used to develop forming control systems for a VVER-1000 fuel assembly.

   The 3D-TCAD simulation of a noise pulse generation in CMOS combinational elements as a part of a majority element when collecting charge from tracks of single ionizing particles has been reported. The duration of noise pulses and its reducing in the logical elements by the 65-nm CMOS bulk technology with shallow trench isolation of transistor groups have been estimated. The simulation of the charge collection has been performed for a linear energy transfer of 60 MeV cm²/mg to a track. When the charge is collected from the particle track by the closed transistors of the NAND (NOR) elements, they transit to an open state (in particular, to the inverse offset mode). As a result, a noise pulse appears at the NAND (NOR) node, which closes the transistor of the output inverter of the AND (OR) element. The closed transistor of the inverter, collecting a charge from the same track, can compensate a part of the pulse duration when transmitting the pulse to the output of the AND (OR) element. Duplicating the inverter with the location of the main and additional transistors of the inverter on the boundary sides of the topological groups of NAND (NOR) transistors promotes reducing the duration of noise pulses when collecting a charge from the track of a single particle. Taking into account the correction, the duration of interferences occurring in the majority element is in the range of 50–300 ps.

   The efficiency of multitask deep learning methods for combined neural network models is comprehensively studied in application to a selected set of tasks: generating headers, defining lemmas, and keywords. The multitask model is built using Multi-head Attention layers and is used to develop models for generating headers and a model based on LSTM layers for lemmatization. Open corpuses RIA Novosti, containing news texts and headings for them, and a corpus with morphological, syntactic markup and lemmas for word forms SynTagRus from the universal dependencies project are used. For the task of highlighting keywords, we have assembled a new corpus consisting of news texts using the crowdsourcing platform. The results of the work show an increase in the accuracy by 1 % in the F1 score for the lemmatization problem when using features from the multitask model compared to using only morphological features, state-of- art accuracy (0.42 ROUGE F1 score) is achieved for the title generation task. An algorithm for highlighting keywords without additional network training is proposed on the basis of the model for generating headings obtained in this work.

   In this paper we suggest to break down natural numbers, P, in two coefficients, i and j, reported to their subscript N which is defined by the equation P = 6N ± 1; i and j are defined by an other equation, N = 6 * |i| * |j| ± (i ± j). N is a natural whole number but i and j are not necessarily natural whole numbers. They could be irrational. By using such unusual approach of number theory, we would propose a simple relation between two square numbers as a necessary condition for any prime number. We would like to suggest that such relationship could be looked as a corollary of the last Fermat’s theorem.

   The structure of the optimal decision support system for the decommissioning of nuclear facilities is examined. The proposed structure provides the analysis of various options for decommissioning the facility under consideration for atomic energy use and the selection of the best option for decommissioning it. The system takes into account uncertainties in the source data, including uncertainties that are described using fuzzy values. The decommissioning options are evaluated by several particular indicators, reducing them to two or three aggregated indicators.

   The blood flow quality in placenta of pregnant women suffering from chronic kidney disease has been experimentally studied. The patients are divided into five groups (classes). Four groups represent patients with varying disease severity degrees and the fifth, control group consists of patients without kidney disease. Cross sections in 50 slices of the placental villi, which supply the fetus with blood, have been measured and summarized in a database. This database has been analyzed by non-parametric statistic methods. In each group, distributions of the capillaries over cross-sectional areas along villus, over cross-sectional areas in villi slices, over cross-sectional areas for all capillaries of group, over the summary cross-sectional areas of the capillaries, etc. have been studied. Data processing has involved the two-sample Smirnov criterion. Explicit relations have been established between the disease severity and the degree of villi vascularization. It has been shown that an increase in the severity of chronic kidney disease is accompanied by a decrease in the number of capillaries in the villus, in the cross-sectional area of capillaries, and in the total area of capillaries in villi. The results of experimental data processing are compared to our results obtained in 2017 by the logical symptoms method based on the analysis of verbal doctor conclusions. New results are consistent with previous ones.

   Modern distributed monitoring systems include observation and detection devices of different types. Heterogeneity of corresponding data creates problems associated with such data unification, with inconsistency, deficiency, and inaccuracy of data, as well as with necessity of big information volume processing. Algorithms providing heterogeneous data fusion for convenient representation of last ones, for getting reliable conclusions, and for decision making are considered in this work. The proposed approach to heterogeneous data fusion based on associate index vector application and data fusion realization on unified formal base. Start attempts of such base creation are quite justified. In this field, the approach based on transfer from original indices to generalized ones is developed. The aims of the generalized index processing methods are as follows: (i) reduction of the vector dimension, (ii) rational index nominalization, (iii) object classification without teaching, (iv) statistical analysis of classification efficiency. For the representation of indices, nominal (binary), ordinal (integer), and relative (real) variables normalized in range (0, 1) are used. It is demonstrated that the advantage of Euclidian and Manhattan metrics is the possibility of forming the diversity threshold based on the Neyman–Pearson criterion. Examples of indices of different types and their application are also presented.

   A tool for complex thematic, tonal, aspect-sentiment, and emotive analysis of natural-language texts is reported. For thematic analysis, a method based on probabilistic-entropy characteristics is employed, which allows us to identify automatically the number of topics in a text collection. Aspect-based sentiment analysis is performed within the neural network model with the topology of an interactive attention network, which demonstrates an accuracy of 0.58 by F1-macro score on the corpus from the SentiRuEval-2015 competition, thus outperforming the best results of the competition. For conducting emotive analysis, a method is developed on the basis of context-dependent vector representations of words, with the subsequent processing by an ensemble classifier trained on a corpus of texts prepared specially for five basic emotions: joy, sadness, anger, fear, and surprise (this classifier achieving an accuracy of 0.76 by F1-macro). An example of using the method is also demonstrated. Texts of the LiveJournal social network and news from the SCTM-ru project are selected for analysis. Presented visualization of text analysis results in the form of graphs, which shows the efficiency of the developed method.