News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences

The relevance of this study stems from the need to apply advanced proactive methods, such as Cash Flow at Risk (CFaR), to manage liquidity and inform management decisions. This article addresses the problem of quantitatively assessing the cash flow risks of Russian commodity corporations in the face of macroeconomic volatility. Aim . The study is to develop and test a practical algorithm for assessing CFaR, adapted to the factor structure of risk for Russian corporations. The methodology involves constructing a regression model linking cash flow to key macroeconomic variables, followed by probabilistic modeling. The study results indicate that the projected EBITDA value for the planning period is approximately 1,600 billion rubles. Calculations based on the model's random error distribution demonstrate that, with a 5% probability, EBITDA could be less than the expected value by up to 80 billion rubles, which quantifies the CFaR indicator. The scientific novelty lies in the development of a structural algorithm integrating regression analysis and the CFaR methodology for Russian corporations. Conclusions . The practical significance of this approach is confirmed by the fact that it provides financial managers with a tool for building liquidity reserves and developing hedging strategies.

Forecasting electricity consumption is an important tool for energy companies to ensure the stability and economic efficiency of the national energy system. For large industrial enterprises, accurate forecasting allows them to optimize production costs and avoid financial losses due to imbalances and high electricity tariffs. Aim. The study is to construct a detailed step-by-step algorithm for hourly forecasting of electricity consumption at an enterprise, using the method of statistical analysis of dynamic series in various programming languages. Materials and methods. The modeling and forecasting algorithm is based on the classical ordinary least squares (OLS) method for small data samples, as well as the moving matrix method. The mathematical apparatus of the data processing method was implemented using the engineering software Mathcad Express. The implementation of the data processing method using modern programming languages is demonstrated: Python, R, C#, C++, Go, and Java. Results. The authors implemented an algorithm for calculating daily electricity consumption forecasts using the classical sliding matrix method in Python, R, C#, C++, Go, and Java for subsequent code comparison. The authors present the results of a comparison of the forecasting algorithm implementations based on the following criteria: number of lines of code and execution time, use of external resources, parallelism support, and code size (in characters). Specific examples demonstrate that the choice of programming language depends on the problem being solved by researchers and developers. The adequacy of the developed regression model is statistically proven, and the equation quality is verified. Confidence intervals for the error corridor of the forecast model have been calculated. Conclusions. The study demonstrates that the task of system data analysis and electricity consumption forecasting is effectively solved using the Python programming language. The code for implementing the classical sliding matrix method is available in an open repository on GitHub at the following link: https://github.com/CollaborativeProgrammingTeam/Method-of-Classical-sliding-matrix.

The relevance of this study is related to the development of agricultural robotics and autonomous systems for biotechnology, where precise control of environmental parameters is critical. Creating an optimal climate is essential for the efficient operation of a greenhouse complex during the winter and the production of a good harvest, even under ideal sealed conditions. Aim. The study is to develop an autonomous robotic microclimate control system with stage-by-stage adaptive control, diagnostics, and remote interaction functions based on an affordable microcontroller platform. The research methods include hardware testing on a physical prototype (ESP8266 controller, SCD40 sensor, actuators), software data monitoring via REST API at 6-second intervals, and a test protocol for humidity, CO₂ (relay control), and temperature (PID controller) circuits. Data processing was performed in JavaScript with the ability to visualize in MATLAB, Python, or Excel. Results. An autonomous microclimate control system based on the ESP8266 microcontroller, implementing stage-by-stage adaptive control and remote monitoring, has been developed and tested. The effectiveness of the key algorithms has been experimentally confirmed: relay control ensures reliable reduction of excess humidity and CO₂ concentration, while the implementation of a PID controller enables smooth and precise temperature control without overshoot. The obtained data identified areas for optimization, such as accounting for thermal inertia to improve algorithms and refining the design to increase energy efficiency, confirming the practical value of the system as a ready-made, cost-effective, and scalable solution for precision agriculture and biotechnology.

Automatic detection and tracking of convective cells using radar data is a crucial task for the nowcasting of severe weather events. Traditional algorithms, such as threshold-based and object-oriented methods, are widely employed but suffer from limitations in accuracy. Aim. To investigate and compare the performance of various machine learning models in detecting and tracking convective cells in radar imagery. Results. A theoretical review of state-of-the-art approaches was conducted, covering classical algorithms (TITAN, SCIT), computer vision methods (threshold segmentation, clustering), and machine learning techniques, including fuzzy logic, decision trees, and neural networks (including deep convolutional networks). The performance characteristics of established machine learning models were evaluated based on quality metrics. The results demonstrate that such models can increase the probability of detection and reduce false alarms compared to threshold-based methods. Conclusions. AI-based algorithms outperform traditional approaches across several metrics, enabling more reliable identification of dangerous convective cells and forecasting of their evolution. The practical application of these methods will improve the accuracy of thunderstorm and hail nowcasting; however, their implementation requires large, properly prepared training datasets that account for specific local conditions.

The paper provides a comparative analysis of socket performance implemented with the TCP, UDP, SCTP and QUIC transport protocols under conditions similar to those of cloud services. Bandwidth, network delays, and CPU load are selected as the main metrics for comparison. At the next stage, a practical experiment is conducted. The experiment involves the implementation of a reproducible stand configuration: virtual machines and a master – slave model. Identical sets of data are transmitted, for which a fixed time for repeated measurements is determined. At the final stage, the results are analyzed. Aim. The study is to analyze the transport protocols and architectural features of TCP, UDP, SCTP and QUIC sockets and to develop an experimental bench for evaluating key quality parameters. Research methods include comparative analysis of transport sockets architecture and the estimates obtained as a result of the experiment, followed by data processing and interpretation of the results. Results. Within the scope of this project, we analyzed the features of TCP, UDP, SCTP, and QUIC transport protocols in order to evaluate their performance. An experimental setup has been developed and implemented to measure performance parameters such as bandwidth, latency, and processor load. Test graphs with metric’s values for four transport sockets have been obtained. A comparative analysis has been conducted, based on which the patterns of influence of architecture and protocol mechanisms on socket efficiency have been identified. The paper reveals the relevance of this research, sets goals and objectives. The work of the experimental stand was demonstrated and data was collected, on the basis of which conclusions were drawn. Each task was completed successfully.

Given the widespread use of volcanic tuff in construction in the Kabardino-Balkarian Republic and the potential negative impact of radiation on health, it is becoming increasingly important to determine the presence of natural radiation in these materials. This is necessary to ensure radiation background control and minimize unavoidable radiation exposure during the operation of buildings constructed using volcanic tuff. Aim. The study is to determine the presence of natural radiation activity in a sample of volcanic tuff under low-background conditions, which can form the basis for developing a method for sorting tuff minerals according to the degree of contamination with primordial radionuclides. Materials and methods. A sample of pink volcanic breccia was collected on the bank of the Baksan River near the village of Elbrus in the Kabardino-Balkarian Republic. The specific activities of primordial radionuclides 40K and the daughter products of 238U and 232Th were measured using a high-resolution MKGB-01 "RADEK" scintillation γ-spectrometer under reduced cosmogenic background conditions. The scintillation spectrometer uses a 150x150 mm NaI (Tl) crystal. The energy range of the detected gamma radiation is from 40 to 10,000 keV. The detector crystal has a well, allowing for highly efficient measurements in a 4π geometry. Results. A study of the γ-activity of natural radionuclides in a sample of tuff breccia with complex mineral composition collected in the Elbrus volcanic recreation zone was conducted. Activity measurements were carried out using the peaks of total absorption of γ-lines 212Pb (232Th), 214Bi (226Ra), and 40K. Based on the research, a method for determining the content of primordial radionuclides in tuff minerals is proposed to minimize unavoidable dose loads during their use in the construction of social facilities. The essence of the method consists of measuring the specific activity of 40K radionuclides, daughter products of 238U and 232Th decay, using a high-resolution scintillation γ-spectrometer under low-background conditions. Conclusions. A gamma-spectrum analysis of a tuff breccia sample with complex mineral composition collected in the Elbrus volcanic recreation zone reveals that the mineral raw materials used in construction contain naturally occurring radioactive substances. These are primarily 40K and daughter products of 238U and 232Th. The total activity of natural radionuclides in the pink volcanic tuff sample was 829 Bq/kg.

The article is devoted to the comprehensive study of agrotechnical methods of resource-saving technologies for cultivating amaranth samples. Aim. The study aims to identify the most productive varieties of fodder and vegetable amaranth for further introduction into commercial production. Development and scientific justification of a resource-saving technology for cultivating the Krepysh and Iriston varieties of amaranth, adapted to the soil and climatic conditions of the Republic of Ingushetia. Materials and methods of research. In 2022, the Krepysh and Iriston varieties of amaranth were obtained from Z.S. Vinogradov, a breeder at the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR). The field studies were conducted on the land plot of the Ingush Agricultural Research Institute, located in the forest-steppe zone of Ingushetia. The soils of the experimental plot were leached medium-thick chernozems. Results. The study determined that the protein level depends on the degree of nitrogen nutrition. The fat content in the seeds showed an inverse relationship with the level of nitrogen nutrition, and the maximum squalene content was recorded in variants with moderate nitrogen nutrition. The yield of green mass sown from May 1 to 5 with a seeding rate of 1.0 kg/ha and the use of fertilizers at doses of N P K 45 60 60 was achieved by the Iriston variety – 23.4 t/ha. The grain yield of the Iriston variety was lower – 11.3 c/ha. The productivity of green mass sown at early dates (April 20–25) with a seeding rate of 0.5 kg/ha and a fertilizer dose of N P K 45 60 60 for the Krepysh variety was 19.7 t/ha. The Krepysh variety has a plant height of 150 cm, grain yield per plant – 130 g, green mass – 2.00 kg. The Iriston variety is 160 cm tall, grain yield per plant – 120 g, green mass – 3.0 kg. The maturity of the Krepysh and Iriston amaranth varieties occurs in the early second decade of September. Conclusions. The practical significance of the study lies in the formation of a scientific basis for the introduction of a new highly profitable crop into the agro-industrial complex of the republic, which contributes to strengthening the feed base, developing the processing industry, and increasing the sustainability of the regional agro-industrial complex in the context of climate change.

In the context of the transition from Industry 4.0 to Industry 5.0, the importance of digitalizing business models based on trusted access to data and the integration of digital ecosystem participants is growing. The relevance of this study stems from the lack of effective tools for development companies to consolidate and analyze marketing information in a single digital space. The scientific novelty of this work lies in the development of a model of a development company's digital ecosystem, considered as a business model for trusted access to data, as well as in the formation of a system of metrics and sources of marketing information to support management decisions. Aim. This study is to describe a digital ecosystem model for development firms. Research methods. The methodological basis of the study are ITSM, MBSE, and enterprise information management (EIM) approaches, which enable the integration of structured and unstructured relevant data sets, including Big Data, AI, and IoT technologies. Results. The article proposes a classification of relevant data sets and conducts an expert assessment of their significance and frequency of application. Using the example of a development company's business process for determining the cost per square meter, the need to use integrated data sets for decision-making by the commercial director is substantiated. The results of the study demonstrate the feasibility of systematically consolidating marketing information and building a unified data model for a developer's digital ecosystem. Conclusions. The paper concludes that the proposed model is of practical importance for improving management efficiency, and identifies areas for further research related to the development of scenario-based game and simulation models of interaction between ecosystem participants.

In the context of digital transformation of business models, innovation ecosystems and platform-driven behavior increasingly determine firms’ innovation demand. Aim. The article is to provide a theoretical and analytical justification for the mechanisms of influence of the platform economy and platform models of demand on the innovative behavior of firms, as well as to develop methodological approaches to their assessment. The scientific novelty of the study lies in conceptualizing platform demand as an endogenous institutional and algorithmic mechanism that shapes innovation trajectories through informational, network, algorithmic, and institutional channels. The methodological basis of the work was the theory of multi-sided markets, the concept of innovation ecosystems, methods of structural-functional analysis, formalization of economic dependencies, as well as analysis of empirical data from Rosstat, the HSE Institute for Statistical Studies and Economics of Knowledge, and the OECD for 2024–2025. The article demonstrates that the inclusion of firms in platform ecosystems helps reduce the uncertainty of innovation activities, accelerate innovation cycles, and increase the diffusion of product and service innovations. The study concludes that the impact of the platform economy on innovation activity is systemic in nature, requiring explicit consideration of platform mechanisms in the development of innovation and digital development policies.

Digital ecosystems as an emerging concept are a critical component of the modern digital economy and have attracted the attention of many scholars and practitioners. Aim. The study is to conduct a bibliometric analysis of scientific publications in the field of digital ecosystems based on 250 articles indexed in the international scientific citation database Scopus for the period from 2014 to 2025. Research methods. Bibliometric analysis has been conducted using the Bibliometrix-Biblioshiny package in the R programming language. Results. The analysis reveals a significant increase in the number of published scientific articles in the field of digital ecosystems research since 2018, demonstrating growing scientific interest in this topic. Geographic distribution exposes that Germany, the United Kingdom, and Spain lead in the number of scientific publications in the field of digital ecosystems. The leading journal in this field is Sustainability Journal. The study's results identified the most significant scholars who have published papers on digital ecosystems with the highest citation rates. The study also identified the most frequently used keywords and the logical relationships between them. An analysis of keyword co-occurrence patterns discovered seven main thematic clusters in the field. Conclusions. The growing number of publications in the field of digital ecosystems indicates that digital ecosystems are a relevant and important topic for science, attracting the interest of a large number of researchers.

Migration has a significant impact on the state of a country's sustainable development. Research at both the federal and regional levels, is a crucial tool for monitoring and analyzing ongoing migration and demographic processes. This is particularly important for mitigating negative depopulation trends, as migration significantly impacts the social structure, economy, and culture of the population. Aim. The study is to identify the influence of socio-economic factors on population mobility in Kabardino-Balkaria: population migration trends. Research methods. To achieve this goal, a sociological survey was used. The analysis of the research is based on the factor-dynamic method of social change and key sociological approaches, both qualitative and quantitative. The study uses the principles of triangulation to ensure the comparative analysis is objective and factually accurate. Results. This article analyzes migration processes and factors influencing population mobility in modern Kabardino-Balkaria. Conclusions. Based on the analysis, it is concluded that economic factors are the main driver of migration processes. It is also concluded that labor migration is accompanied by difficulties in finding employment in the labor market.

The article examines the problem of structural efficiency of regional innovation systems (RIS) as a key condition for sustainable socio-economic development of territories in the knowledge-based economy. The relevance of this study stems from the fact that, in the context of increased interregional competition and technological transformation, traditional approaches to assessing innovation development, based primarily on quantitative indicators, fail to identify internal constraints in the RIS functioning. Aim. The research is to substantiate the theoretical, methodological and institutional-legal foundations for analyzing the structural efficiency of regional innovation systems and to develop approaches to its assessment. Scientific novelty lies in interpreting structural efficiency as an integral characteristic of the RIS architecture, reflecting the coherence of innovation cycle elements, network connectivity of actors, institutional sustainability and functional completeness of the system. The research employs methods of systemic and structural-functional analysis, institutional and network approaches, comparative analysis, as well as interpretation of Rosstat statistics and analytical materials of the Higher School of Economics. Results. Key criteria of RIS structural efficiency are substantiated, the role of the institutional and legal environment in shaping innovation linkages is revealed, and methodological approaches for diagnosing the coherence of regional innovation system elements are proposed. Conclusions. Increasing regional innovation performance requires not only resource accumulation but also optimization of the interaction structure between science, business and government. The findings can be used in designing and adjusting regional innovation policy.

The significance of this study stems from the lack of a comprehensive analysis of the use of metaphorical epithets in the poetry of Rasul Gamzatov and the need to explore the methods of their creation and application, considering the morphological, structural, and semantic features of figurative and allegorical descriptions. The scientific novelty of this article lies in its attempt to describe and analyze metaphorical epithets used in Rasul Gamzatov's poetry for the first time, revealing their role and importance in the poetic landscape of the late 20th century. Aim. The study aims to identify and analyze metaphorical epithets, which are a dominant artistic device and a distinctive stylistic feature of his poetics in the 1980s. Research materials and methods. We use a variety of methods for systematic scientific description, including systematization, comparison, interpretation of analytical results, continuous sampling, and contextual analysis. The study's material consists of adjective metaphorical epithets (adjectives, participles) found in the poetic texts of Rasul Gamzatov from the 1980s. Results. This article examines the use of metaphorical epithets to create vivid and expressive artistic images, portray heroes, phenomena, and the realities of the time, as well as to express the author's attitude towards current socio-political events in the country. The distinctive themes and topics vividly symbolize the socio-political and economic reforms that intensified in the country at the end of the 20th century. Conclusions. The author's metaphorical statements during this period were primarily motivated by bitter reflections on the spiritual, political, and economic decline of the country. Using this technique, Rasul Gamzatov conveys his negative feelings about the outcome of Perestroika through figurative language, showing how it has led to the destruction, impoverishment, and rise of cruelty, commercialism, and apathy in society.