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

This article is devoted to current issues in the theory of partial differential equations related to the study of boundary value problems for loaded parabolic equations with a fractional integro-differen- tiation operator, which are of interest not only for the advancement of this specific theory, but also for their numerous applications.

Aim. The study is to prove the unique solvability of a mixed boundary value problem for a discontinuously loaded parabolic equation with the Riemann–Liouville fractional derivative.

Research methods. The study employs the Green's function method, simple layer potential theory, and fractional calculus theory.

Results. This paper demonstrates the unique solvability of a mixed boundary value problem for a loaded fractional-order parabolic equation.

Conclusion. The results obtained are significant for the development of the theory of boundary value problems for partial differential equations of fractional order, including loaded parabolic equations; they are also relevant for mathematical modeling of various processes and systems with distributed parameters and fractal structures.

The paper examines the inverse of the Laplace transform with a hyperbolic tangen function. This function arises when solving a boundary value problem in a bounded domain governed by the heat equation, subject to boundary conditions of the second and third kind.

Aim. To determine the inverse Laplace transform of a function that emerges from solving a boundary value problem, specifically a second or third type condition, associated with the heat equation.

Results. Using the residue theorem and the theory of a complex variable functions, wederive the inverse transform, suitable for large and small time values. In the first case, the inverse transform is expressed as a series of exponential functions with constant coefficients; in the second case, as a series of Laplace convolutions of special functions.

Conclusion and deduction. The derived results constitute a basis for constructing a solution to the boundary value problem for the heat equation in a bounded domain with a second-order condition on one of the boundaries and a third-order condition on the other, in a form suitable for small time values. In the context of mathematical physics, a solution to a similar problem is derived via separation of variables suitable for characterizing heat transfer processes for large time values. However, this proves inconvenient given sufficiently small temporal values, due to poor convergence properties pertaining to the Fourier series expansion involving eigenfunctions of the problem.

In the context of the development of Industry 4.0 and digital manufacturing, minimizing downtime of process equipment is a key factor in increasing efficiency. The development of a universal mobile platform (UMP) is driven by the growing need for robotic automation of CNC machine tool interoperability, which still relies heavily on manual labor, resulting in lost time and reduced overall productivity. Existing stationary and mobile solutionsdo not provide the necessary combination of precision, adaptability, and rapid deployment in a dynamic production environment.

Aim. The study is to develop a universal mobile platform for servicing numerically controlled (CNC) machines with improved adaptability, accuracy, and reliability.

Research materials and methods. The research methodology includes systems analysis, mathematical modeling, and strength calculations, which confirm the structural reliability (safety factor of 36.4–52.3%). Results. This paper presents a mobile robotic platform designed for the rapid maintenance of CNC machine tools in a dynamic production environment. The scientific novelty lies in the synthesis of three innovative elements: a modular architecture, an adaptive air suspension, and a high-speed stabilization system, which provides improved off-road capability by adapting to surface irregularities, unlike existing solutions.

Conclusions. The results demonstrate the feasibility of integrating the platform into the production cycle based on predictive notifications from equipment, ensuring positioning accuracy of ±1.5 mmand autonomous operation. An important practical result is the proven reliability of the selected air springs, ensuring safe operation even in emergency situations. The work offers potential in the development of artificial intelligence (AI) algorithms for automatic control systems (ACS), enabling more complex predictive planning and adaptation to unforeseen situations without operator intervention. The practical significance of the work is confirmed by the estimated reduction in equipment downtime by 15–20%.

The seismicity issue in the Kamchatka region highlights the importance of fundamental research to understand the processes occurring in the Earth'scrust. Anomalous changes in the concentration of radioactive radon gas (222Rn) have been observed to be precursor to earthquakes. Monitoring involves collecting data on the volume activity of 222Rn in the recording chamber over time and detecting any unusual patterns or anomalies. However, the mechanisms behind these irregularities are still not well understood. Therefore, the authors have previously proposed new mathematical hereditary VAR models to describe the unusual migration capacity of 222Rn, taking into account the time-dependent transport process in a heterogeneous fractal geoenvironment. The key parameter of the models is the variable order of the Gerasimov-Caputo fractional derivative, related to the intensity of the 222Rn transport process with changes in the permeability of the geoenvironment.

Аim. The study is to solve the coefficient inverse problem of identifying values ​​in the mathematical hereditary model of anomalous variations of the OAR.

Research methods. Methods of mathematical modeling of processes occurring in the geological environment are used, as well as solving coefficient inverse problems for these models using an algorithm based on the Levenberg-Marquardt method (IP-LM).

Results. A series of results are obtained for solving the inverse problem with various parameters controlling the IP-LM motion. The results are divided into two types: implausible – due to going beyond the range of acceptable values ​​and the initial approximation of identified values ​​close to the reference point, similar to manually selected values; plausible – due to the initial approximation close to 0, good agreement between the results and the OAR data, where the increase in values ​​from 0 to 1 is maintained despite the loss of the reference point'sapparent periodicity.

Conclusions. The results suggest that it is possible to solve the formulated two-parameter inverse problem based on the experimental data of the OAR. The obtained results are plausible; however, the outcome of the inverse problem solution depends on the initial approximation of the identified values.

The article discusses the problem of automatic detection of pavement defects using multimodal neural network methods.

Aim. To develop and experimentally evaluate a multimodal neural network method for automatically detecting pavement defects using combined analysis of visual and three-dimensional data.

Methods. The Faster R-CNN model is used for detecting damage areas, the Swin Transformer Small model for classifying visual fragments, and the PointNet model for analyzing surface geometry based on lidar data. The predictions from each modality are combined by weighted summation (weights 0.1, 0.6, and 0.4, respectively). The training and testing are conducted on the RSRD multimodal dataset, which includes RGB images and point clouds obtained in various road and weather conditions.

Results. Experimental studies have shown that the multimodal approach provides an increase in classification accuracy ofup to 95.57%, as well as a significant improvement in defect detection metrics. For the pothole class, completeness increased by 27% and F1-score by 20% compared to using individual models.

Conclusions. The developed architecture demonstrates high stability and accuracy in the tasks of analyzing the roadway. The results obtained confirm the effectiveness of the integration of visual and spatial data and the expediency of using multimodal methods to build intelligent monitoring systems for road infrastructure.

The paper presents a comparative analysis of the classical Cobb-Douglas production function, its transcendental-logarithmic specification, and modern machine learning techniques used to model production processes.

Aim. The paper aims to show how increasing the complexity of the real-world production function leads to the superiority of machine learning methods for forecasting quality compared to the traditional Cobb–Douglas function, while still allowing for economic interpretation through the use of explainable artificial intelligence techniques.

Research materials and methods. A computational experiment was conducted with data including technological heterogeneity and nonlinear interactions between factors, ensuring an objective assessment of the accuracy of various approaches.

Results. It has been shown that the strict form of the Cobb–Douglas production function leads to systematic errors when applied to complex production structures, while the Translog model partially compensates for these limitations by incorporating interactions between quadratic terms. Machine learning methods, such as gradient boosting and multilayer neural networks, demonstrate the best forecast quality due to their ability to approximate complex, nonlinear relationships and account for hidden factors. The paper also discusses the potential of using SHAP techniques to interpret machine learning models, which helps to recover economically significant relationships and increase confidence in the results.

Conclusion. The outputs confirm the possibility of integrating machine learning algorithms into modern economic models of production functions.

This article presents the architecture of an agent-based modeling software package for intelligent agricultural systems, focused on modeling the interactions between robots, plants, and infrastructure in an apple orchard. The system integrates physical, sensor, effector, energy, and computational models into a single discrete 3D environment and supports decentralized federated learning without a centralized server. Particular attention is paid to agent autonomy, asynchronous simulation execution, and the ability to integrate with real sensors and robots.

Aim. The study aims to develop the architecture of an agent-based modeling software package designed for simulating intelligent integrated information and control systems in a real, physically correct, dynamic, and partially observable environment.

Research methods. The primary research method is agent-based (multi-agent) modeling, which allows simulating the interaction of autonomous agents in an uncertain and dynamic environment. Object-oriented design using UML notation is used to structure the architecture and decompose tasks.

Results. A software architecture is proposed that takes into account entities such as a simulated World, Agent, Entity, Billboard, and Computer.

Conclusions. The proposed platform ensures the reproducibility of experiments, scalability, and serves as a basis for testing collective behavior algorithms in heterogeneous and resource-limited agricultural environments.

The article presents a comprehensive analysis of the application of modern information and measuring systems (IMS) as a tool for improving the efficiency and reliability of technological processes in the context of "Industry 4.0". The architecture, components and principles of IMS operation are considered, including their integration with the Industrial Internet of Things (IIoT), big data and artificial intelligence. Based on the analysis of specific examples from leading Russian industries, such as oil and gas, mechanical engineering, energy, chemical and metallurgical, the significant impact of IMS on resource optimization, increased productivity and security is demonstrated. The article proposes a new integrated multi-level adaptive scheme for using IMS, which combines the physical, control, production and corporate levels into a single system with an analytical core based on artificial intelligence. The developed scheme ensures proactive decision-making and the creation of self-regulating production cycles. Conclusions. The results of the study confirm that the implementation of the IIS helps to move to predictive maintenance and improve product quality. The article summarizes the existing experience and identifies promising areas for the development of the IIS for building sustainable and competitive industrial enterprises.

The object of the study is the neuropsychological architecture of the brain.

Aim. The study is to develop theoretical foundations for the creation of a universal artificial intelligence agent.

Research methods. An approach to the ontogenetic formation of universal control systems is used. The essence of these systems lies in the simulation modeling of the growth and development of natural autonomous intelligent agents, equipped with a basic cognitive architecture possessing structural and functional similarities to the cognitive architecture of the brain, in a real social environment. Specifically, a key hypothesis is advanced that such similarities are possessed by so-called neurocognitive architectures, which represent a metaphor for designing an intelligent system for controlling the behavior of an autonomous agent immersed in a real environment using sensors and effectors. This architecture is based on concepts regarding the composition and interaction modes of functional units–the so-called invariants of the organization of the cognitive architecture of decision-making.

Results. A structural and functional diagram of neuropsychological architecture has been developed, motivated by its systemic purpose, enabling neurocognitive transformations of the problem-defining space through the coordinated work of neurocognitive components implementing cascades of n-functions for dynamic transitions between the behavioral space, local problem-defining spaces, and the mental space.

Conclusion. A concept for the neuropsychological architecture of an autonomous behavioral control system for a universally intelligent agent has been developed. It is shown that the universal nature of the range of problems that such agents are capable of handling is ensured by a methodological and algorithmic framework for ontologization, identification, and problem solving based on the synthesis of the agent'sbehavior within the agent-environment system by the neuropsychological architecture.

One of the most important stages in the study of new hybrids is their comprehensive comparative testing under various environmental conditions and an assessment of their ecological plasticity and stability, which allows for the specification of regions for their use.

Aim. The research is to conduct an analysis of the environmental stability and yield stability of 20 new promising corn hybrids.

Research materials and methods. The study was conducted using regression analysis according to the Eberhart and Russell method in two different ecological locations: the Institute of Agriculture of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences (Kabardino-Balkarian Republic, Tersky District, Opytnoye village) and the VSC RAS ​​(Republic of North Ossetia-Alania, Prigorodny District) in 2023–2024.

Results. Promising high-yielding hybrids were identified: RSO-9, RSO-27, and RSO-43, demonstrating stable yields regardless of cultivation conditions. Hybrids RSO-1, RSO-15, RSO-39, and RSO-40 are characterized by increased adaptability and stability, effectively responding to changes in growing conditions. Hybrid combinations RSO-4, RSO-6, RSO-22, RSO-23, RSO-29, RSO-33, RSO-38, RSO-45, and RSO-42 demonstrated high ecological flexibility with moderate stability, indicating their responsiveness to improved agricultural practices while maintaining the ability to produce high yields in less favorable conditions. In addition, a comparative analysis of two approaches to assessing ecological plasticity – by the regression coefficient and the standard deviation and the parameters αjand λj – showed that although the first method is more informative, the second method can be successfully applied when working with large arrays of hybrid material.

Conclusions. A comprehensive assessment of the ecological flexibility and stability of new promising hybrid combinations under various agroclimatic conditions identified hybrids with both high stability and pronounced responsiveness to growing conditions. These hybrids respond effectively to changing growing conditions and ensure stable yields across a variety of ecological zones.

The use of microbial-based biopreparations and their producers in organic crop cultivation technologies, where the use of mineral fertilizers and pesticides is completely avoided, can improve the nutritional conditions for plants and provide protection against harmful organisms. This is especially important when soil fertility levels are declining.

Aim. To conduct a comparative assessment of the yield and quality of the obtained grain when cultivating soybeans using organic and intensive technologies in the Altai Territory.

Materials and methods. The research area is the moderately arid and piercing steppe of the Altai Territory, the Pripyat variety, the predecessor is spring wheat, the seeding rate is 735 thousand pcs./ha, taking into account the yield – from accounting sites 0.25 m2, in 4-fold repetition. Statistical processing was performed by analysis of variance.

Results. Organic and intensive cultivation technologies contributed to better conservation of plants for harvesting. The average plant height and lower bean attachment are the highest with intensive technology reaching 104.7 cmand 15.9 cm. The largest number of beans on the plant is recorded on the organic technology option – 15.4 pcs., Which is 33.9% higher than on the intensive technology option. The indicator "the number of seeds in the bean" varied slightly (2.4–2.6 pcs.). Yield on organic technology is 14% higher than control and 4.5% higher than intensive technology.

Conclusions. Organic technology ensures the ecological purity of products, improves the nutritional value of soybean grains, increasing the content of protein and mineral elements. Intensive technology increases oiliness, but is inferior in yield and protein content in grain. The control option is characterized by the lowest indicators, which confirms the need to use modern agricultural technologies based on the use of biologics and microbiological agents in the production of organic plant materials.

This article examines the theoretical and methodological foundations for developing a smart economy within regional innovation systems, using the Kabardino-Balkarian Republic (KBR) as a case study. The relevance of the study stems from the need for Russian regions to adapt to digital transformation, as well as the growing importance of intelligent technologies and platform solutions for sustainable territorial development. The scientific novelty of the work lies in the development of an integrated smart economy index based on three standardized components: digital infrastructure, human capital, and innovation and technological activity, as well as the integration of PCA, AHP, and DEA methods for a comprehensive assessment of a region'sdigital maturity.

Aim. The study is to develop a scientific and applied model for the implementation of a smart economy in the context of a regional innovation system in a mountainous region, based on an empirical analysis of the socio-economic, digital, scientific and environmental parameters of KBR.

The research methodology includes Rosstat statistical analysis, indicators standardization, construction of index models, heat maps and clustering.

Results. The results obtained show that KBR is demonstrating significant positive progress in digitalization and human capital development, while innovation is progressing more slowly and continues to be a key challenge for the transition to a smart economy. The integrated index confirms the region'stransition to the medium-high digital maturity level in 2020-2024.

Conclusion. The main areas of regional policy have been identified: strengthening the research sector, developing human resource competencies, creating innovative clusters, and incorporating intelligent technologies into mountain development management.

The demographic crisis and depopulation that have been ongoing for decades, have made research on the demographic security of Russia and its regions particularly important. Therefore, research into rising mortality rates and, conversely, declining fertility rates, depopulation, unregulated migration processes, and identifying ways to prevent them is crucial for Russian regions. When studying demographic security, the key indicators are solely based on the characteristics of natural population movement, ignoring the role of external migration and determining both its positive and negative potential consequences. Accordingly, monitoring demographic security requires the creation of a database and the development of a system of indicators. When determining indicators of demographic security, it is important to move away from general indicators of population growth and focus on more specific indicators that reflect the rate of change in population growth and the quality of the population.

Aim. The study is to identify the main indicators of demographic security and their target benchmarks.

Research methods. To achieve this goal, statistical and sociological analysis methods are used.

Research results. This paper proposes demographic security indicators and their target benchmarks. The particular significance of our proposed demographic security indicators lies in their ability to reflect not only quantitative but also qualitative aspects of population growth.

Conclusion. This study is of great importance for assessing the demographic situation in Russia and its regions, as well as for developing a more targeted demographic policy.

The article is devoted to the study of the theoretical foundations and practical mechanisms for managing the motivation of actors in the regional economy to create and develop new high-tech industries. Using the example of specific robotics projects developed at the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences (such as an agro-protection robot, a greenhouse harvesting robot, and an anthropomimetic manipulator), the potential and market prospects for their commercialization are discussed. The paper proposes the application of multi-agent neurocognitive architectures for modeling complex, weakly-structured processes. Investments in the production of highly intellectual products, coupled with the motivation of all actors in the regional economic system and cooperation in this area, will lead to rapid and stable economic growth and an improvement in the quality of human life.

Aim. Research objective is to study the theoretical foundations, models, and management methods necessary for forming an effective system of motivation for actors in the regional economy. The ultimate goal of this motivation system is to stimulate the creation and development of new high-tech industries in the region.

Methods. Statistical and system analysis, induction, data processing and interpretation, identification of patterns, and simulation modeling.

Results. Elements of an effective regional innovation system are proposed, including a scientific-educational foundation, a technological base, and global integration, necessary for achieving technological sovereignty and the sustainable development of production systems. The paper presents an intelligent system for data analysis and decision-making, applicable in various spheres of human activity. Models of organizing innovation activity (administrative-command, market society, triple helix, Novum Trivium) are analyzed, as well as key factors limiting technological development in Russia.

Conclusions. The study confirms that the development of competitive high-tech sectors necessitates systematic management of key regional economic actors' motivation. The triple helix model integrating government, business, and science proves most effective. Developments in agricultural robotics and AI show significant import substitution potential. Realizing this requires overcoming systemic constraints, creating an integrated innovation environment, and implementing flexible support mechanisms to ensure technological sovereignty and sustainable regional development.

The relevance of the research topic is conditioned by the determinant influence of the regional policy of employment of people with disabilities on overcoming labor stigmatization and the level of socio-economic development of society. Decisions of regional authorities in the field of inclusive employment act as an indicator of labor integration and involvement in public life of people with disabilities. The article explores trends in the implementation of an inclusive approach to employment as a conceptual basis for building a just society, oriented towards the prevalence of ethical norms and equal rights of all population groups.

Aim. The study is to identify the mechanisms and potential for developing inclusive employment as a concept for regional development.

Research methods include a comparative analysis to compare regional inclusive employment practices, sociological methods to collect information on barriers to employment for people with disabilities, a retrospective analysis of the dynamics of inclusion processes in the labor market, and statistical analysis tools to identify the relationship between the employment rate of people with disabilities and indicators of regional socio-economic development.

The results presented in the study consist of identifying the specifics of the socio-economic and labor integration of people with disabilities as a catalyst for regional development, as well as identifying barriers to the formation of an inclusive labor market environment and opportunities for overcoming them.

Conclusions. The scientific significance of the research lies in the definition of the imperatives of inclusive employment in the context of the impact on the socio-development of society. The practical significance of the research is to identify the tools for ensuring an inclusive labor market and the potential for its implementation in the context of a shortage of personnel in the domestic economy. The value of the research and scientific novelty consists in the dissemination of knowledge about the relevance of the issue of inclusive employment in the context of the formation of socio-cultural and economic basis of regional development.

Demography is one of the key factors in the preservation and sustainable development of any country in all aspects. Research dedicated to assessing the demographic situation, at both the federal and regional levels, is a crucial tool for monitoring and analyzing ongoing demographic processes. This is particularly important for mitigating negative trends of depopulation.

Aim. The paper aims to analyze and identify the main demographic trends in the natural population movement in the Russian Federation and compare them with general trends in the North Caucasus Federal District.

Research methods. To achieve this goal, statistical and sociological analysis methods have been used.

Results. This article analyzes the current demographic situation in both the Russian Federation and the North Caucasus Federal District. Using official Rosstat statistics for 2010–2025, a comparative analysis of natural population indicators and their trends is provided.

Conclusions. Based on the analysis, wecan conclude that the demographic situation in the Russian Federation is worsening and urgent measures need to be taken to improve the current situation. An analysis of data for the North Caucasus Federal District reveals that the demographic situation shows steady positive trends.

The article is devoted to the study of challenges facing IT companies during the digital transformation. In the current conditions of global turbulence of industries, the issue of organizing digital transformation in companies remains especially acute. The scientific novelty of the study is the development of a phased digital transformation model in IT companies with an emphasis on technological and management solutions and a three-level "map" for assessing the company'sdigital maturity.

Aim. The study is to develop a practice-oriented digital transformation model that allows IT companies to make a phased transition towards modern technologies and assess the current level of digital maturity of the company. Research methods.

Research methodology is characterized by the application of systematic and comparative analysis, as well as specific methods represented by multivariate modeling.

Results. The current state of digital transformation was assessed and the main factors contributing to the effective operation of the IT company were identified.

Conclusion. The practical significance of the work lies in the adaptability of developments for different segments of companies and their flexibility to modernize to changing market conditions. Based on the results of the analysis, conclusions are drawn about the need for an integrated, consistent approach to organizing the digital transformation process, taking into account the critical importance of a successful personnel policy, special attention to cybersecurity and continuity of development.

The relevance of the study is due to the need to adapt and timely transform domestic telecommunications companies to the conditions of digitalization and sanctions challenges, where priority should be given to diversification as a key tool for ensuring sustainability. The novelty of the work lies in the formation of a new integrated approach to choosing a diversification strategy for a specific company, taking into account the integrating analysis of the resource state, the availability of core competencies, the possibility of synergies, a high level of managerial skills and other factors.

Aim. The study is to develop theoretical, methodological and practical tools for launching and conducting an effective diversification process through the formation of internal strategies in telecommunications companies. The research methodology is based on system analysis, synthesis of theoretical works of Russian and foreign authors.

Results. It was revealed that an effective diversification process is associated with a balance of internal opportunities and a favorable external environment. We have developed our own list of activities that contribute to the effective diversification process, wehave also proposed a logical scheme for deciding on the feasibility of diversifying production, and a matrix for understanding the dependence of the choice of possible corporate strategies on the existing factors of an undiversified company.

The materials presented in this study are significant because they will enable usto uncover previously unknown aspects of historical events related to the lands along the Zolka and Etoka rivers.

Aim. This study aims to introduce new archival documents to academic research: interdepartmental correspondence from 1841–1842, from the collections of the Russian State Military Historical Archive. Analysis of these documents provides a fresh perspective on the circumstances surrounding the allocation of land to the Kabardian people in the Zolka and Etoka river valleys, in addition it traces how understanding of this issue has developed within historical scholarship and outlines avenues for future research.

Research materials and methods. The article'smethodology is based on the principles and methods of historical research. Two principles were applied throughout the study: a scientific approach and an emphasis on historicism. The article was prepared based on a collection of documents, literature, and interdepartmental communication between middle-level managers.

Results. The study presents materials that reveal previously unknown aspects of historical events related to the lands along the Zolka and Etok rivers. This approach allowsus to examine the governance mechanisms used in the Caucasus to implement pro-Russian policies aimed at integrating the region into the Russian state.

This article examines the main activities of the Nalchik District Police Department in the last third of the 19th and early 20th centuries. The novelty of this research lies in its focus on the formulation of specific tasks: until now, the functionality of this institution for maintaining public order has not been a subject of special attention.

Aim. The study is to identify the functions and determine the scope of the Nalchik District Police Department in the last third of the 19th – early 20th centuries.

Research materials and methods. We used problem-chronological and comparative-historical research methods, dividing the research object into a series of narrow problems that are examined in chronological order, and comparing various authorial approaches to identify their common and specific characteristics; wealso conducted prospective analysis to identify possible vectors for future research on the topic.

Results. Based on a review of the records, a detailed analysis was conducted of the main activities of the Nalchik District Police Department, including: interaction with other agencies, maintaining public order among the local population, compiling service records of Nalchik District police officers and family lists of the region'ssettlements, deporting criminals to correctional facilities, and arresting local residents sentenced to imprisonment in guardhouses.

Conclusions. It has been concluded that during the relevant period, the police department was responsible for recording and investigating crimes, monitoring the activities of the 1st Hundred of the Terek Permanent Militia, resolving land disputes, carrying out tax control, and other related matters.

This article provides a comprehensive analysis of the creative legacy of Balkar writer Majid Samatovich Guliyev, which until recently had not been the subject of literary criticism. The work is generally introductory in nature, as the writer'sentire artistic output is difficult to encompass within the limited scope of a single scholarly publication.

Aim. This study is to provide a comprehensive understanding of the author'sexperience in creating poetry and prose texts, the specifics of his artistic thinking, poetic, stylistic, and genre preferences, figurative and expressive tropes, and the dominant themes of his works.

Results. In accordance with the set objectives, the study aims to analyze the key creative concepts and systematically examine the structural, stylistic, figurative, and thematic features of M.S. Guliyev'spoems, verses, fables, short stories, novellas, and plays. The article also includes brief biographical information highlighting important stages in the writer'slife and public activities. The author'spublished books and collections are listed chronologically, and significant works are examined by genre.

Conclusion. The results of this study allow usto reveal the vibrant creative individuality of M.S. Guliyev and to understand the specific intentionality evident in his works. The writer'sactive artistic practice, focusing on finding effective methods for reflecting and interpreting reality, has contributed to the expansion of potential genre forms and thematic directions in national literature.

In the article, based on lexical and semantic analysis, dialectal phraseological units of the Karachay-Balkar language are systematized and established for the first time within the framework of its national and cultural specificity.

Aim. The study is to identify the socio-cultural potential of dialectal phraseological units that convey the ethnic characteristics of the linguistic worldview of speakers of the tsok dialect.

Materials and methods research. The theoretical and methodological basis of this study was provided by the works of Russian scholars and linguists engaged in the study of dialectal phraseology in the Karachay-Balkar language. The following lexicographic sources have been used: “Explanatory Dictionary of the Karachay-Balkar Language” (in three volumes); “Brief Dictionary of the Malkar Central/West Dialect”; “Karachay-Balkar Phraseological Dictionary”, as well as materials from the fiction of D. Taumurzaev and I. Gadiev. The study primarily uses methods of structural-semantic, contextual analysis, and the descriptive method.

Results. Based on the collected factual material, the distinctive national and cultural characteristics and nuanced meanings of dialectical phraseological units have been analyzed and identified. From a functional and semantic perspective, the object of the study is dialectal phraseological units characteristic of the tsok dialect in all their diversity and richness.

Conclusion. The practical significance of this work lies in the fact that the results and conclusions of the study can be applied in lectures and seminars on the modern Karachay-Balkar language and in the compilation of translated dictionaries of Turkic languages.