The neural network analysis of physical education and sports in the regions of Russia is carried out with the help of multidimensional statistical data of the Ministry of Sports of the Russian Federation. The research tool for data clustering was neural networks implemented in the analytical package Deductor-Kohonen self-organizing maps (SOM). The distribution of Russian regions by five clusters is obtained. It is shown that there is an uneven development of sports infrastructure. The regions with the highest development rates are identified. The results obtained are of practical importance for the strategic planning of the development of physical education and sports essential for improving the quality of human capital and ensuring the economic security of the country.

With the use of neural network modeling, the authors analyzed the current state of youth sports in rural areas of Russian regions, which characterizes human capital. The simulation uses neural networks implemented in the Deductor package – self-organizing Kohonen maps. As a result of the analysis, the authors obtained a distribution of regions in five clusters. The composition and characteristics of each cluster are presented. The regions with the highest indicators of sports development in rural areas have been identified. This paper shows the influence of the indicators considered on human capital, which is one of the dominant internal factors of socio-economic potential of territories. The results of the research are of practical significance for a comparative analysis of the development of children’s and youth sports in the regions of Russia and can be taken into account in the strategic planning of the development of the sports industry in the context of increasing the quality of human capital.

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The article presents a study of the dynamics of students' psychological and emotional state in the implementation of the author's program of dance movement training. The effectiveness of the training was monitored by evaluating the types of the participants' psychological problems and their emotional and functional state. The study involved 96 students of Nizhny Novgorod universities aged from 18 to 25. We used: the author's questionnaire for subjective evaluation of the training participants' psychological problems; Cattell's questionnaire; the method of computer campimetry to assess the functional state of the body by the function of color differentiation. The technology used for measuring differential thresholds based on the coordinates of color models in a computer environment was the HandTracker (Polevaya) campimetry test for virtual environment. The system of dance movement training included methods of body-oriented psychotherapy, vegetotherapy, dance movement therapy, including contact improvisation. The structure of the class included: warm-up (aerobic and anaerobic exercise, muscle stretching exercises);

Under conditions of evolving digital economy, in view of speedy progress of science and technology, the need to take investment decisions and analyze vast data flows, it is very important to introduce new effective approaches to risk management. The authors integrate the scientists’ modern views in the risk management area. The article discusses specific features of risk management in the process of attracting investment in digitalization projects. This study contributes to understanding investment risks and helps determine directions of future strategies aimed at developing investment activities within the framework of digital economy. The work results can be used in developing a risk management system and forming a digital investment portfolio. The analysis of risk management approaches and techniques conducted helped provide a practical and expedient scientific basis for further development of digital ecosystems.