News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences
ISSN (print): 1991-6639, ISSN (online): 2949-1940 Founder: Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences Editor-in-Chief: Ivanov Petr Matsovich, Doctor of Engineering Sciences, Professor Frequency / Access: 6 issues per year / Open Included in: Higher Attestation Commission List, RISC
Mixed boundary value problem for one discontinuously loaded parabolic equation
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.
Copyright (c) 2026 Karmokov M.M., Kerefov M.A., Gekkieva S.K. https://creativecommons.org/licenses/by/4.0
Nonlocal boundary value problem for the McKendrick - von Foerster loaded equation of fractional-order
The paper considers McKendrick–von Foerster loaded equation of fractional-order. Aim. The study aims to demonstrate the existence of a unique solution 'loaded equation' within Ω, contingent upon satisfaction of regularity conditions. Research methods. The convergence towards a solution was achieved via a reduction to a Volterra integral equation system, specifically of the second order. Employed the fractional calculus operator. Results. Given the McKendrick – von Foerster loaded equation of fractional-order, the existence and uniqueness of a solution to a nonlocal boundary value problem is proven. An explicit representation of the solution is derived, expressed as integral equations. Conclusion. The derived results facilitate mathematical modeling, specifically applied to population dynamics. Consider age-structured populations and incorporate diffusion phenomena exhibiting memory effects, formally representable via fractional-order derivatives. The derived theorems augment the axiomatic foundation for analyzing said differential equations, enabling further investigation in mathematical biology and the theory of integro-differential equations.
Copyright (c) 2026 Losanova F.M., Kenetova R.O. https://creativecommons.org/licenses/by/4.0
On inversion of Laplace transform of function, involving hyperbolic tangent
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.
Copyright (c) 2026 Khushtova F.G. https://creativecommons.org/licenses/by/4.0
On uniqueness of solution to functional-integral equation of fractional order with involution
The paper studies a functional integral equation with a fractional integration operator and an involution operator, which arise when solving boundary value problems for differential equations that contain a composition of left- and right-sided fractional derivatives. These equations underlie mathematical models of various physical and geophysical processes, such as describing dissipative oscillatory systems. Aim. The study aims to investigate a functional integral equation with an operator of fractional integration involving an involution operator in the critical case. Research methods. To solve the problem, weemploy methods of the theory of integral equations of the first kind, operator theory and properties of completely monotone functions. Results. It has been shown that the equation under study can be reduced to the problem of solving an integral equation of the first kind with a positive kernel, in a class of functions that change sign under the action of an operator, and for this class of functions, a theorem on the uniqueness of the solution has been proven.
Copyright (c) 2026 Eneeva L.M. https://creativecommons.org/licenses/by/4.0
Universal mobile platform for servicing computer numerical control machines
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%.
Copyright (c) 2026 Iskakov S.A., Munasypov R.A., Tselischev O.V. https://creativecommons.org/licenses/by/4.0
Design of a mobile robotic system for servicing oil storage facilities
In the oil industry, steel vertical tanks gradually become contaminated with sediments and deposits over time, leading to wall corrosion, loss of useful volume, and operational safety hazards. Various cleaning methods are employed, including manual, chemical, mechanical, hydrodynamic, and robotic approaches. However, non-robotic methods pose risks to maintenance personnel, require significant material and time resources, and may result in mechanical damage to tank walls. Existing robotic systems for oil tank cleaning ensure safe cleaning without personnel presence inside the tank but require constant monitoring and control by an operator. The development of a mobile autonomous robotic system will improve cleaning process efficiency, reduce technological equipment downtime, decrease operational costs, and minimize the human factor in the oil tank cleaning process. Аim. This study is to design and perform computer simulation of a mobile robotic system intended for automated oil tank cleaning. To achieve this goal, the following tasks are completed: development of kinematic and dynamic models of the mobile robotic system with tracked chassis and two-link manipulator, simulation of chassis motion with differential drive and manipulator in the Simulink simulation environment, and evaluation of the developed system'spositioning accuracy. Computer simulation results showed that when moving along a typical square trajectory with a side length of 1 meter, the final positioning error was no more than 0.102 meters. Error accumulation is due to the absence of a closed-loop position control system in the current version. The achieved accuracy is satisfactory for performing technological tasks of oil tank cleaning and confirms the prospects of applying autonomous robotic systems in this industry sector. Conclusions. The manufactured prototype confirms the practical feasibility of the proposed technical solutions and the possibility of their implementation in industrial operation at oil and gas industry enterprises.
Copyright (c) 2026 Shereuzhev M.A., Ushakov A.E., Semyannikov I.V. https://creativecommons.org/licenses/by/4.0
Inverse problem on determining variable-order fractional derivative in mathematical model of anomalous variations in radon volumetric activity
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.
Copyright (c) 2026 Tverdyi D.A., Parovik R.I. https://creativecommons.org/licenses/by/4.0
Use of multimodal neural network techniques to assess quality of roadways
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.
Copyright (c) 2026 Gorodnichev M.G., Polyantseva K.A., Razumovsky I.D. https://creativecommons.org/licenses/by/4.0
Robust modification of PSO algorithm based on M-means for solving linear regression
Linear regression is a fundamental data analysis tool, but it can be greatly affected by outliers and noise, which can lead to distorted coefficients and a reduction in forecast quality. Classical heuristic PSO (Particle Swarm Optimization) and Jaya algorithms demonstrate good performance on smooth loss functions, but they are sensitive to outliers when applying the standard mean squared error (MSE). This creates a need for simple but effective modifications that would maintain global search capabilities without complicating the basic algorithm'sstructure. Aim. The study is to develop and subject to experimental evaluation modification of PSO algorithm (PSO-Robust) that ensures the robustness of linear regression to outliers without complicating the core algorithm or introducing additional hyperparameters. Methods. Algorithmic idea: to keep the standard PSO equations of motion; interfering only with the fitness function. Instead of the root mean squire loss, an M-means function based on the Huber function is used, with adaptive weights that reduce the contribution of outliers. Experiments have been conducted on synthetic data with 15 % and 25 % outliers, with the same hyperparameters for all compared algorithms and 30 independent runs. Evaluation by mean and median test errors, as well as by dispersion estimation (variance, interquartile range). Visual analysis – boxplot of error distributions and regression lines. Evaluation by mean and median test errors, as well as dispersion (variance, interquartile range). Visual analysis – boxplot of error distributions and regression lines. Results. PSO-Robust consistently outperforms classic PSO and Jaya in terms of mean and median test errors. The results show a smaller spread (variance). The visual analysis confirms reduced sensitivity to outliers (more compact box plots, more consistent regression lines). Conclusion. The PSO-Robust modification demonstrates consistent superiority over the original algorithms in accuracy and robustness, producing more compact boxplots andless distorted regression lines. The proposed approach combines simplicity of implementation and robustness, increasing the reliability of regression in the case with heterogeneous data. Future developments include extending the method to multivariate and nonlinear models, as well as exploring alternative robust loss functions.
Copyright (c) 2026 Kazakova E.M. https://creativecommons.org/licenses/by/4.0
Evolution of production functions from Cobb-Douglas to machine learning methods
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.
Copyright (c) 2026 Kanametova D.A. https://creativecommons.org/licenses/by/4.0
Logical and mathematical interpretation of decisions of intelligent agents
Modern cybersecurity systems are faced with increasingly complex network architectures and a growing diversity of attack vectors. In this context, the ability of intelligent systems not only to effectively detect threats but also to rationalize their decisions is becoming increasingly important. Аim. The work is to develop and experimentally verify a model of an RL agent capable of making decisions in a network environment, interpreted in terms of temporal and epistemic logic. Results. This paper presents a formal approach to developing explainable reinforcement learning (XRL) for cybersecurity problems. This approach includes developing a mathematical model of an intelligent agent capable of detecting anomalies in network traffic and making decisions under uncertainty. A method for interpreting agent strategies is proposed, based on the use of linear temporal logic (LTL) and epistemic logic (EL), which ensures transparency, formal verifiability, and explainability of system behavior. It is demonstrated that the logical and mathematical interpretation of learned policies enables a transition from empirical dependencies to formalizable properties of security, liveness, and causality, thereby increasing the trust and reliability of cybersecurity systems. A computational experiment confirms the effectiveness of the proposed approach: anomaly detection accuracy reaches 94–96%, and the average response latency is less than 0.3 seconds. Conclusion. The obtained results demonstrate the model'shigh applicability for constructing explainable, verifiable, and resilient cybersecurity systems, and also demonstrate that logical interpretation of strategies contributes to increased decision transparency and strengthens trust in intelligent information security systems. The experiment demonstrate that the agent is capable of achieving high threat detection accuracy with short response times, and the resulting logical formulas successfully pass specification feasibility checks. This confirms that logical interpretation of strategies increases the transparency and trust in the decisions of intelligent systems.
Copyright (c) 2026 Lyutikova L.A., Kochkarova M.S. https://creativecommons.org/licenses/by/4.0
Development of a software architecture for agent-based modeling of intelligent agricultural systems
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.
Copyright (c) 2026 Anchekov M.I. https://creativecommons.org/licenses/by/4.0
Investigation of properties of processes characterized by logistic curves, using probabilistic cellular automata
One of the most successful processes studied is the development of systems that are either limited in area (populations), have limited development potential (technologies), or are associated with a small market size (product producers). These processes have a similar mathematical description, which involves constructing the corresponding logistic curves. Despite the obvious external differences between the listed processes, their underlying similarities are revealed through the cybernetic approach. The processes of development of biological, technical, and economic systems, which are described using C-shaped curves with the resources limited, testify to the cybernetic nature of the interaction mechanism within these systems. Aim. The paper aims to identify system-wide patterns and mechanisms of development under limited resources. Research methods. A one-dimensional probabilistic cellular automaton has been used to study developmental processes under resource constraints. The automata, which possess a scalar degree of development, compete for shared resources. Result. The use of one-dimensional cellular automata allowes usto easily obtain interpretable results and analyze the impact of different dominance conditions on the internal diversity of the system. Conclusions. The analysis of the structures allows to identify the dependence of the internal diversity of the system on the choice of dominant representatives during the competition for resources. In addition, the study predicts regarding the nature of changes in the system'sstructure under conditions not only of internal constraints, but also of the presence of another system that implements the "predator-prey" relationship.
Copyright (c) 2026 Dimitrichenko D.P. https://creativecommons.org/licenses/by/4.0
Issues of functioning of information systems for increasing productivity of technological cycles in various industries
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.
Copyright (c) 2026 Zvyagin L.S. https://creativecommons.org/licenses/by/4.0
"What does the brain do?", or Solving a priori undefined problems based on an autonomous agent behavior in real environment
The relevance of the work is determined by the need to develop theoretical foundations for the creation of universal artificial intelligence systems. Aim. This work is to create a conceptual model of the systemic essence of the brain. Research methods. Of fundamental importance is that both ontology meta-matching technique and problem-solving algorithms synthesize points and segments along an agent'smovement in a behavioral space. This means that ontologization, identification, and solution of all problems encountered by the agent in the real environment during its existence are accomplished through the synthesis and implementation of the agent'sbehavior in that environment. Results. A hypothesis about the systematic target function of the brain has been formulated, and a computational model of the basic processes underlying its operation has been developed, based on the analogy of designing a neurocognitive system to control the behavior of an autonomous agent in a real-world environment. A concept of an agent'sexistence as a trajectory in its behavioral space was proposed, which is a mathematical abstraction of the state space of the "agent – environment – observer" system. A concept for adapting agents to real-world conditions has been proposed, based on brain-implemented meta-algorithms for ontologization and algorithms for identifying and solving a priori undefined problems, grounded on a metaphor for designing an autonomous synthesis of the agent'strajectory in behavioral space. Conclusion. The developed concepts support the idea of ontologization, identification, and problem-solving by an agent in a real-world environment as processes of autonomous behavior synthesis, which provides a theoretical foundation for the development of universal artificial intelligence systems.
Copyright (c) 2026 Nagoev Z.V., Nagoeva O.V. https://creativecommons.org/licenses/by/4.0
Neuropsychological architecture of a general-purpose artificial intelligence agent
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.
Copyright (c) 2026 Nagoev Z.V. https://creativecommons.org/licenses/by/4.0
Collaborative dialogue system for plant simulation based on neuropsychological agents of universal artificial intelligence
The relevance of this work stems from the need to enhance the productivity, manageability, and efficiency of plant breeding and cultivation processes by creating predictive models. A general architecture for plant simulation systems based on universal artificial intelligence agents is developed. The feasibility of using a design metaphor for decentralized collaborative dialog systems based on universal artificial intelligence agents for developing such systems is substantiated. Generalized multi-agent training algorithms are developed for controlling neurocognitive architectures of artificial intelligence agents in plant simulation models; these algorithms are based on knowledge extracted from texts and natural language utterances, as well as the implementation of exploratory behavior by autonomous mobile robots in a real environment. Aim. The study is to develop a methodology for creating simulation models of plants based on dialogue agents of universal artificial intelligence. Research methods. The possibility of using a design metaphor for decentralized collaborative dialogue systems based on universal artificial intelligence agents to develop such systems is substantiated. Results. Fundamental principles for constructing open-source plant simulation models with high expressiveness and predictive power have been developed based on neuropsychological agents from universal artificial intelligence. Conclusion. A general architecture for plant simulation systems has been developed created on universal artificial intelligence agents and autonomous mobile robots.
Copyright (c) 2026 Pshenokova I.A., Anchekov M.I., Bzhikhatlov K.C., Nagoev Z.V., Nagoeva O.V., Khamov A.A. https://creativecommons.org/licenses/by/4.0
Evaluation of ecological plasticity and stability of mid-season corn hybrids
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.
Copyright (c) 2026 Appaev S.P., Azubekov L.K., Karaev V.Y., Shomakhov B.R. https://creativecommons.org/licenses/by/4.0
Productivity and economic efficiency of herbicide application in sugar beet cultivation
The cultivation of sugar beet remains highly significant for the economy of the Russian Federation. The use of herbicides during sugar beet cultivation enhances weed control efficiency, minimizes competitive pressure from weeds on the growth and development of crops, improves yield quality, and increases productivity. Aim. The study is to determine the best method for using herbicide when cultivating the highly productive sugar beet hybrid "Bartavella" on leached chernozem soils of the enterprise JSC "Rassvet", located in the Ust-Labinsk district of the Krasnodar Territory. Research methods. Experimental research was conducted between 2023 and 2024 following B.A. Dospekhov'smethodology for field experiments. Results. Studies have established optimal variants of applying Frontier Optima and Caribu herbicides, ensuring root yields averaging 39.8 t/haand 38.7 t/harespectively over 2023-2024, with corresponding sugar extraction rates of 6.8 t/haand 6.6 t/ha. In terms of economic efficiency, using Frontier Optima provided conditional net income of 82,748 rubles per hectare, while the variant with Caribu yielded 78,527 rubles per hectare. Conclusion. Analysis of herbicide effectiveness in the agronomic technology of producing sugar beet roots «Bartavella» demonstrated that, on average over 2023-2024, this variety responded positively to all tested herbicides, providing high profitability ranging from 75.8% to 87.4%, compared to only 45.1% in the control variant without herbicides but with double inter-row cultivation.
Copyright (c) 2026 Mamsirov N.I., Bashkov V.I. https://creativecommons.org/licenses/by/4.0
Yield and quality of soybean grain when cultivated using intensive and organic technologies in Altai region
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.
Copyright (c) 2026 Cherepanova O.V., Chernyshkov V.N., Pugach D.A., Bodnya T.S. https://creativecommons.org/licenses/by/4.0
Effectiveness of insecticides against the cotton bollworm on corn in steppe zone of Kabardino-Balkarian Republic
The relevance of the research lies in identifying and studying dominant pests, such as the cotton bollworm (Helicoverpa armigera Hb.) and the corn stem borer (Ostrinia nubilalis Hb.), between which an inverse relationship in the dynamics of harmfulness has been revealed. Aim. The research is to determine the species composition and population dynamics of phytophages in agrocenoses of Karat SV hybrid corn and to evaluate the effectiveness of protective measures. Materials and methods. For the first time, research was conducted in the steppe zone of the Kabardino-Balkarian Republic between 2022 and 2024 to determine the species composition and population dynamics of phytophages in agrocenoses of Karat SV hybrid corn as well as to evaluate the effectiveness of protective measures. Field experiments were carried out on experimental plots of the Institute of Agriculture of the Kabardino-Balkarian Scientific Center, RAS. To classify phytophages, the "Identifier of Agricultural Pests for Damage to Cultivated Plants" compiled by M.B. Akhremovichetal. is used. The soil of the experimental plots is southern chernozem, which has a low humus content in the topsoil (3.5–5.0%) and a gradual distribution decrease in humus content down through the soil profile. Decade-long phytosanitary monitoring was realized using optical instruments (a Primo Star microscope (Zeiss), a Biolam binocular microscope, a portable net, magnifying glasses of various magnifications, and electronic scales). Results. Weather conditions significantly impacted the development of phytophages: hot and dry weather favored outbreaks of aphids and spider mites, while heavy precipitation resulted in extended development of cotton bollworm and active flight of the cotton bollworm. The most effective chemical and biological insecticides for controlling the cotton bollworm were identified. The use of these insecticides also led to increased yields: 1.5 t/haand 0.6 t/ha, respectively. Conclusions. The chemical insecticide Proclaim (VRG) has proven to be the most effective control agent for cotton bollworm, with demonstration of high biological (94.3 %) and economic efficacy (yield increase of 1.5 t/ha). Among biological products, Lepidocide (SK) is promising, with a biological efficacy of 85.0 %. Based on the data collected, werecommend a strategy that involves alternating between chemical and biological insecticides for corn protection in order to effectively control pests and reduce the risk of insecticide resistance.
Copyright (c) 2026 Shabatukov A.K., Shipsheva Z.L. https://creativecommons.org/licenses/by/4.0
Smart economy as a driver of regional innovation system transformation: comprehensive assessment, models, and development mechanisms
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.
Copyright (c) 2026 Makhosheva S.A. https://creativecommons.org/licenses/by/4.0
Socio-demographic indicators for national security
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.
Copyright (c) 2026 Berova F.Z., Tabaksoev I.A. https://creativecommons.org/licenses/by/4.0
Integration of artificial intelligence technologies into regional governance systems: principles, models, and development directions
Artificial intelligence is becoming an increasingly significant factor in the economic and social development of countries worldwide. The use of artificial intelligence in regional economic governance has a number of specific aspects that have not yet been fully understood and incorporated into the traditional regional governance system. Aim. The paper is to identify various aspects of artificial intelligence'sinvolvement in regional economic governance. Materials and methods. The study combines theoretical and empirical methods, including a systematic review on the use of artificial intelligence (AI) in economics, a classification of AI technologies, an analysis of their impact on key regional indicators, and a comparison of AI implementation practices using statistical data and case studies. Results. The proposed framework for integrating AI into regional economic management systems can be used as a methodological basis for designing similar institutions in the constituent entities of the Russian Federation. The developed classifications of AI types and the identified paths for adapting them to the design of regional management systems are of practical value. Conclusions. Based on the conducted study, it can be concluded that artificial intelligence is becoming a key tool for improving the effectiveness of regional economic management, providing a qualitatively new level of analysis, forecasting, and decision-making. The implementation of AI contributes to the optimization of resource allocation, improved coordination between industries, and increased transparency and the validity of management actions. The proposed model of a regional AI center and approaches to integrating industry-specific intelligent systems demonstrate the potential for developing a comprehensive digital governance infrastructure. However, AI development requires addressing a number of technological, institutional, and ethical challenges, including data standardization, security, personnel training, and the development of a regulatory framework. Thus, artificial intelligence has the potential to become a systemic factor in sustainable regional development, provided a comprehensive approach to its implementation is adopted.
Copyright (c) 2026 Zhangorazova Z.S., Bakkuev E.S., Gazaeva M.S., Kilov A.O. https://creativecommons.org/licenses/by/4.0
Development of theoretical foundations, models and methods for managing processes of formation of motivation system for regional economic actors to participate in the creation and development of new high-tech industries
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.
Copyright (c) 2026 Zagazezheva O.Z., Mambetov I.A. https://creativecommons.org/licenses/by/4.0
Research on development and forecast of domestic and global markets for artificial intelligence systems and intelligent robotic complexes
The article is devoted to a comprehensive study of the current state and long-term prospects for the development of the global and domestic markets for artificial intelligence systems and intelligent robotic complexes. A comparative analysis of the technological development strategies of leading countries has been conducted, and key trends, growth drivers, and systemic constraints have been identified. Based on statistical data and government programs, scenario forecasts for industry development over 5-, 10-, and 15–20-year horizons are presented. Special attention is paid to the positioning of Russian companies on the global stage and their competitive advantages in light of import substitution and geopolitical changes. Aim. The study provides a comprehensive analysis of the long-term prospects for the development of domestic and global markets for artificial intelligence systems and intelligent robotic complexes, as well as the identification of strategic competitive advantages within an emerging multipolar technological ecosystem. Research methods. The study employs comparative analysis, statistical data analysis, expert assessments, content analysis of government programs and technological development strategies, as well as scenario forecasting. Data from international organizations (IFR, Stanford HAI), analytical agencies (McKinsey, Gartner, BCG), and official statistical reports have been used. Results. Technological development strategies of leading countries were systematized, revealing a significant gap in Russia’slevel of robotization (5–7 robots per 10,000 employees compared to 150–1000 among global leaders). Three scenarios for the development of the Russian AI market (optimistic, baseline, pessimistic) were formulated, projecting market volume between USD 4.1 and 7.1 billion by 2027. The study highlights the successful specialization of Russian companies in niche segments (cybersecurity, infrastructure inspection, service robotics) and their growing presence in Asian, Middle Eastern, and African markets. Conclusions. The dominance of Western countries in the technological sphere is gradually weakening, giving rise to an era of technological polycentrism. Russia, by focusing on technological sovereignty, is demonstrating significant progress in specialized segments of AI and robotics. Key success factors include overcoming systemic constraints (low private investment, weak business innovation activity), developing educational infrastructure, and deepening international cooperation with friendly countries. The long-term competitiveness of Russian solutions will depend on their reliability, adaptability, and independence from Western technological chains.
Copyright (c) 2026 Zagazezheva O.Z., Makoshev A.A., Krai K.F., Shalova S.K., Khadzhieva M.I. https://creativecommons.org/licenses/by/4.0
Inclusive employment as a concept of socio-economic well-being of regions
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.
Copyright (c) 2026 Kazova Z.M., Tsikanova L.M. https://creativecommons.org/licenses/by/4.0
Role of agrotourism in the development of rural areas in the Republic of North Ossetia - Alania
This article examines the challenges of establishing and developing agritourism in rural areas under conditions of limited land use. This paper explores various possible options and models for a hitherto virtually undeveloped sector – agritourism – and attempts to provide a scientifically substantiated organizational and economic mechanism, structure, and the need to develop this important sector of the agro-industrial complex in the unique natural and climatic conditions of the region under study. Furthermore, various options for developing these small businesses are proposed. Aim. The study is to provide a scientifically based organizational and economic mechanism for the development of agricultural tourism in the Republic of North Ossetia-Alania based on a study of various possible options and models of agricultural tourism. Research methods. The research has been conducted using abstract-logical, analytical, computational-constructive, and expert assessment methods. Research result. It has been revealed that there is a trend towards de-urbanization, in particular, more and more former city dwellers are returning to villages and creating sustainable farms. In this regard, the development of agricultural tourism in small-scale farming is justified, and measures to stimulate this trend in the Republic of North Ossetia-Alania are proposed. Conclusion. The analysis shows that the development of agricultural tourism in the Republic of North Ossetia-Alania would not only accelerate the socio-economic development of rural areas but also create a sustainable distribution channel for agricultural products and food, strengthening the region'sfood security and improving the quality of life for the rural population.
Copyright (c) 2026 Mazloev V.Z. https://creativecommons.org/licenses/by/4.0
Regional aspects of demographic processes in modern world
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.
Copyright (c) 2026 Tabaksoev I.A., Berova F.Z. https://creativecommons.org/licenses/by/4.0
Management of digital transformation of an IT company
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.
Copyright (c) 2026 Banduryan A.S., Nazarenko A.V. https://creativecommons.org/licenses/by/4.0
Analysis of the development of the creative industry in Russia
The article is devoted to the current problem of developing the creative sector as a driver of economic growth and social change. Aim. The study is to conduct a detailed analysis of the current challenges and barriers facing creative industries in Russia and compare them with successful strategies implemented in leading countries. The study focuses on issues such as sector fragmentation, lack of institutional support, difficulties monetizing ideas, and brain drain. Based on this analysis, potential solutions are identified, including the development of cluster initiatives, the creation of specialized funds, the modernization of educational programs, and the adaptation of best international practices to Russian conditions. Results. We systematized data on global creative industry centers, developed a methodology for assessing the contribution of creative industries to economic performance, and identified factors for the successful development of creative clusters in regions. Conclusions. Based on the results of the study, conclusions are drawn regarding the need to support creative industries in the Russian Federation, based on the identified advantages of implementing the described technologies, the importance of timely infrastructure development, and the integration of new technological solutions. Of particular importance is the impact of tourism, cooperation, and investment attractiveness on urban development.
Copyright (c) 2026 Savka K.V., Nazarenko A.V. https://creativecommons.org/licenses/by/4.0
Strategic decision-making in context of differentiation in telecommunications industry
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.
Copyright (c) 2026 Fedorov A.A., Nazarenko A.V. https://creativecommons.org/licenses/by/4.0
Historical documents on Imperial Land Grant along Zolka and Etoka rivers (1841-1842)
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.
Copyright (c) 2026 Glasheva Z.Z. https://creativecommons.org/licenses/by/4.0
Burial mounds museifying experiences and prospects for creating burial mound museum in Kabardino-Balkarian Republic
This article examines the prospects for converting burial mounds in Kabardino-Balkaria into open-air archaeological museums. The importance of this topic stems from the need to protect and preserve archaeological sites in the region, which are rapidly being destroyed by natural and human-made factors. Aim. The study is to examine the prospects for transforming one of the Bronze Age burial mounds in the rural settlement of Aushiger (Chereksky district of the Kabardino-Balkarian Republic) into an object of historical and ethnographic tourism, taking into account European and domestic experience. Materials and methods. The author used a comparative analytical method. The research draws on publications in the scientific and periodical press and data obtained during fieldwork in the Cherek District of Kabardino-Balkaria. Results. Factors determining the attractiveness of burial mound museums for the tourism industry were identified. Conclusions. The in-situ museumification of individual archaeological sites in historical sites such as the Cherek Gorge appears to be the most promising direction for the development of historical and ethnographic tourism in Kabardino-Balkaria.
Copyright (c) 2026 Gukemukh I.K. https://creativecommons.org/licenses/by/4.0
On functions of Nalchik district police department in last third of 19th and early 20th centuries
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.
Copyright (c) 2026 Dabagova I.M. https://creativecommons.org/licenses/by/4.0
The article discusses the discovery and inclusion into scientific discourse of rock carvings found on Mount Buksha in the Republic of Adygea. These petroglyphs, located in the upper section of the mountain, consist of various geometric forms carved into the rocks. Although they resemble previous petroglyph discoveries to some extent, the carvings on Buksha are unique. The discovery and analysis of these petroglyphs represent a new chapter in the historiography of ancient rock art research. Their discovery significantly expands the geographic distribution of petroglyph sites in the North Caucasus, making it an important contribution to the field. Given their proximity to an important historical area with concentrations of dolmens and artifacts from the Meshoko culture, the study of these petroglyphs assumes additional significance. Determining their chronology and context is essential for a comprehensive understanding of this region'sancient history. Undoubtedly, a more in-depth study of the semantic meaning of the rock carvings on Mount Buksha would expressively contribute to and enrich our understanding of the ancient culture of the area. This aspect of the research requires further detailed investigation in the future. Aim. The paper aims to introduce to the research community the recently discovered petroglyphs on Mount Buksha, which represent valuable material for the study of ancient rock art in the North Caucasus region.
Copyright (c) 2026 Kagazezhev Z.V. https://creativecommons.org/licenses/by/4.0
Artistic originality of M.S. Guliev's work (Review analysis)
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.
Copyright (c) 2026 Atabieva A.D. https://creativecommons.org/licenses/by/4.0
Tragic understanding of loss of one's homeland in Karachay-Balkar folk songs of resettlement
This work examines the historical truth about the deportation of the Balkar and Karachai people to Central Asia through the lens of oral poetry that emerged during their exile. The significance of this study lies in the need to thoroughly examine the songs that deal with the topic of resettlement, which has not been adequately explored in a scholarly context. The scientific novelty of this article lies in its first attempt to provide a literary analysis of the oral poetry of the Balkar and Karachai people, which reflects the tragic events of their deportation and loss of homeland. Aim. The research is to identify and analyze how the emotional state of the people in exile, their hopes, and their faith in returning to their historical homeland are reflected in folk songs. It is this aspect that makes the article a valuable resource for understanding the past. The methodological basis of the study includes theoretical works and scientific publications by domestic scholars, including M.Z. Ulakov, F.A. Urusbieva, B.A. Berberov, Kh.-M.A. Sabanchiev, and others. The materials for the research are historical songs about the theme of migration, which have been collected and published in various publications. An important aspect of the study is the introduction of oral poetic works from the archive of the Institute of Humanitarian Research of the Kabardino-Balkarian Scientific Center of RAS into scientific circulation. Within the framework of solving this task, weuse a cultural-historical approach and the method of historical comparison. Based on the results of the study on songwriting about the forced displacement of the Karachay and Balkar people, two main stages have been identified: 1. In the early stages, compositions predominate that convey the suddenness and traumatic nature of the expulsion. 2. After thirteen years of exile, the people were tormented by humiliation, hunger, cold, and the grief of loss. Songs began to express gratitude for those who had paved the way for their return to their historical homeland. This period also saw the clearing of false accusations against them. The findings from this research provide a new perspective for future scientific investigation into national folklore.
Copyright (c) 2026 Ulakov M.Z., Gergokova L.S. https://creativecommons.org/licenses/by/4.0
National and cultural features of phraseological dialecticisms in Karachay-Balkar language
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.
Copyright (c) 2026 Ulakov M.Z., Musukov B.A., Makhieva L.K., Kuchmezova L.B. https://creativecommons.org/licenses/by/4.0
Vasily Georgievich Zakshevsky is 60 years old
Copyright (c) 2026 Team E. https://creativecommons.org/licenses/by/4.0