Relevance. The almost non-existent dynamics of the development of the innovative potential of science cities has a negative impact on the scientific and technological development of science cities. Aim. To identify the causes affecting the development of the innovative activities of science cities and their innovative potential in order to improve these activities. Materials and methods. Federal statistical data and scientometric methods of their analysis. Results. Based on the analysis of the innovative activities of science cities, the directions for adjusting the activities of the science and production complexes of science cities have been developed. Conclusion. Science cities are the focal points of Russia’s scientific and technological development, despite the challenges faced by individual science cities. The proposed areas for adjusting the activities of science cities can be used for their further development and improvement.

Introduction. The main barriers to increasing the level of robotics in Russia are personnel shortages, financial uncertainty, and the monopolization of competencies. A scientifically sound architecture for robotics competence centers (RCC) is lacking.

Aim. To justify the creation of a network of RCCs, propose a functional model, an AI-based architecture, and a three-level hierarchy to improve the efficiency of robot implementation in mechanical engineering.

Materials and methods. Methods of system analysis, functional modeling, comparative analysis, and content analysis were used. Materials included statistics from the International Federation of Robotics (IFR), company survey results, and practices from Rosatom, Russian Railways, and the Federal Center for Competence in Labor Productivity (FCC).

Results. Three groups of barriers were identified. A model of the CCR consisting of six modules was proposed, including an AI core (knowledge base, predictive analytics, road map generation, and KPI monitoring). A three-level hierarchy has been developed: federal, regional, and sectoral CCR.

Conclusion. The proposed architecture differs from its analogues in the central role of AI in end-to-end automation of audit, monitoring, and decision-making. The expected effects include a 15-25 % reduction in implementation costs, a 6-9 month reduction in project timelines, and a 1.5-2.5 p. p. increase in productivity. The CCR network with an AI core can become an element of government policy. Key measures to achieve this include the inclusion of CCR in national projects, the standardization of requirements for AI cores, and a unified methodological framework.

Introduction. The role of the Moscow metropolitan as the leading flagship of the entire transport infrastructure of the capital has increased. For the effective functioning of the metropolitan , it is important to comply with technical and regulatory indicators that determine the intensity of train traffic and affect the safety of the entire infrastructure. Aim. To analyze and evaluate the safety and reliability indicators of Moscow metropolitan facilities in order to improve the efficiency of its functioning. Materials and Methods. Statistical modeling methods, methods of queuing theory, reliability theory, systems analysis and a structural-functional approach. Results. Quantitative characteristics of metro passenger flow are calculated, and the features of the occurrence of failures are determined. It is shown that due to the increase in passenger flow during rush hours, most stations operate at the limit of their capacity. An integral coefficient of metro capacity is proposed. Conclusion. Active modernization of the Moscow metropolitan and the introduction of innovations contribute to increasing the reliability and comfort of passenger transportation. In order to improve the efficiency of the metro system, it is necessary to equip 100 % of all lines with innovative trains, and it is also important to begin the reconstruction of “problem” distances and implement a number of preventive measures. Innovative modernization of the metro will also increase the investment attractiveness of certain districts of Moscow.

Relevance. With the growing tax burden on small and medium-sized businesses, it is necessary to consider various tax accounting methods and inventory management systems to identify problem areas and subsequently optimize business processes.

Aim. A comprehensive study of the inventory management system and analysis of applicable tax regimes using a simulated small business entity as an example to identify key relationships and problem areas and develop practical recommendations for optimizing accounting, minimizing the tax burden, and increasing the overall financial stability of the business in a dynamic market environment and changing legislation.

Materials and Methods. The methodological framework utilized methods of systemic, comparative, financial management, ratio, SWOT, and average cost analyses.

Results. Аnalysis of the simulated sole proprietor’s operations revealed effective inventory management, as evidenced by a high turnover ratio. The chosen tax strategy is optimal. A SWOT analysis identified factors that threaten the simulated entity’s operations. The key threat is the planned increase in fixed insurance premiums starting in 2026.

Conclusion. The study showed that a system for accounting and analyzing inventory movements based on the average cost method enabled the company to achieve high inventory turnover, minimize storage costs, and reduce depreciation risks. The use of a simplified tax system for wholesale operations and a patent system for retail trade in the current environment ensures an acceptable tax burden and reduces administrative costs through simplified reporting.

To maintain and improve the efficiency of individual entrepreneurs, it is necessary not only to maintain current effective inventory management practices but also to actively implement analytical tools for demand forecasting, diversify suppliers, and regularly assess the suitability of the chosen tax system for changing economic conditions and their own operating performance.

Relevance. The study analyzes the topic of increasing energy consumption by AI systems, especially in training large models, which places pressure on energy infrastructures. The aim of this study is to analyze the limitations in the use of Author Keywords and IEEE terms presented in the corresponding fields of bibliometric records in the IEEE Xplore database on the topic of energy technologies. Materials and methods. The material under study consisted of 12,000 bibliometric records exported from the IEEE Xplore database from 2020 to 2025. Of these records, 6,000 were conference materials and 6,000 were journal articles. Results. The identified research highlights major trends in smart energy systems, emphasizing the integration of IoT, AI, and machine learning for enhanced operation and predictive maintenance. Key focus areas are smart microgrids, hydrogen energy storage, and electric transport/battery systems. A format is proposed for additional conclusions and recommendations on each issue under consideration, formulated in a semi-formal but clear descriptive style. Conclusion. The publications reflect a strong emphasis on cybersecurity, data privacy, and addressing economic and accessibility issues. Furthermore, research involves advanced topics like mathematical modeling, innovative components (e. g., varactor diodes), and thermal management to improve energy efficiency and ensure safe, modern energy infrastructure, particularly in applications like smart cities. Future research suggests utilizing the IEEE thesaurus to analyze publication trends based on term frequency in titles and abstracts.