Currently, increasing the effectiveness of the training process, reducing the risk of injuries, and personalizing training and education are key challenges in the fields of sports and physical education. In this context, research focused on the automated analysis and evaluation of physical exercises using artificial intelligence (AI) and computer vision technologies is rapidly developing. These technologies enable real-time tracking of human movement and accurate determination of biomechanical parameters.

This paper presents the development of an intelligent computer vision – based fitness assistant designed to recognize physical activity, analyze exercise execution techniques, and provide users with real-time feedback. The proposed system is implemented using deep learning methods based on the Ultralytics YOLO architecture and the OpenCV library. The system detects key body landmarks and joints, analyzes their spatial positions, evaluates the correctness of exercise execution, counts repetitions, and determines performance metrics.

During the study, a dataset of video recordings containing various exercise movements was collected, preprocessed, and annotated. Deep neural network models were trained, and their accuracy and performance were evaluated. In addition, biomechanical modeling was applied to calculate loads on individual body segments and to generate corrective recommendations aimed at improving movement quality.

Experimental results demonstrate that the proposed system achieves high accuracy in exercise recognition and operates efficiently in real time. The developed software solution can be used by individuals training at home, athletes, coaches, and physical education professionals as an additional tool for monitoring and optimizing the training process. The research findings confirm the promising potential for widespread application of artificial intelligence and computer vision technologies in the fields of fitness and sports.

This article presents and experimentally validates a formalized development flow for a specialized cryptographic controller designed for hardware implementation of digital signature algorithms. The flow covers the complete design cycle, encompassing architectural synthesis, RTL implementation, FPGA-based hardware verification, and physical implementation within an MPW flow. The controller architecture follows a modular design principle, in which the system is decomposed into functionally independent hardware blocks that are developed and verified individually. For each block, RTL implementation, software interface generation, and hardware verification are carried out during FPGA prototyping, enabling early detection of functional and interface errors. Critical components undergo additional physical verification through an RTLto-GDS flow, including DRC and LVS checks. Upon completion of modular verification, the blocks are integrated, a memory map is generated, and system-level hardware verification is performed. The approach was experimentally validated on a demonstration computing module based on the TinyQV (RISC-V) core, using the GOWIN Tang Primer 20K and TinyTapeout (PDK SkyWater SKY130) platforms. The results confirm the reproducibility of the proposed flow and its practical applicability for developing specialized cryptographic controllers and secure embedded systems.

This paper presents a comprehensive performance analysis of a dual-band multiple-input multipleoutput (MIMO) antenna system for unmanned aerial vehicles (UAVs). Ensuring high-data-rate and reliable transmission between UAVs and ground control stations is one of the key challenges in modern wireless communications. Accordingly, the proposed antenna array is designed to operate stably in two frequency bands (dual-band mode). Numerical simulation results indicate that the array provides high isolation (23 dB and 19 dB) and wide impedance bandwidths (2.14-3.25 GHz and 5.4-7.4 GHz). These results suggest high data throughput, reduced mutual coupling between the elements, and efficient utilization of spectral resources. In addition, the radiation-pattern analysis yields favorable values of the envelope correlation coefficient and diversity gain, highlighting the importance of MIMO technology in improving spatial diversity and link reliability. The conclusions are based on numerical simulations; although the proposed design is promising for UAV communication systems, further prototype fabrication and experimental validation are required.

Pipelines are widely used for the transportation of water, oil, gas, and other liquid and gaseous media. The occurrence of leaks in pipeline systems leads to significant losses of natural resources and may pose a threat to the environment and public safety. In this regard, the problem of timely leak detection and localization remains one of the most important challenges in the oil and gas industry. This paper addresses the problem of determining the leak location in a pipeline based on pressure measurement data using artificial intelligence methods. An approach to leak localization is proposed based on approximating the relationship between pressure drop, leak flow rate, and the distance to the leak location using a radial basis function neural network implemented in the MATLAB environment. Experimental data were obtained during testing of a leak detection system under simulated leak conditions with different operating modes. The simulation results demonstrate that the developed model provides an effective approximation of the studied relationship and allows the leak location to be determined with a root-mean-square error of approximately 1.9 km for medium and large leaks, confirming the potential of neural network-based methods for pipeline monitoring applications.

The study presents the development and experimental verification of an automated control system for the two-stage hydrolysis of wheat straw, implemented through the integration of a dynamic kinetic model into a model predictive control framework. The control object is characterized by nonlinear dynamics, the presence of technological constraints, and sensitivity to variations in feedstock composition, including cellulose, hemicellulose, and lignin content, which justifies the application of predictive control methods.

The structure of the control system is based on a hierarchical architecture: local PID controllers ensure stabilization of temperature and pH conditions, while model predictive control optimizes control actions according to the criterion of maximizing sugar yield under constraints on temperature, pressure, and processing time. The mathematical model includes the kinetics of acid hydrolysis (hemicellulose-xylosefurfural) and the enzymatic stage based on a modified Michaelis-Menten equation accounting for enzyme inhibition and deactivation.

Control is implemented using a discrete state-space model with a time step of 1 minute, taking into account transient processes. The system is implemented on a programmable logic controller platform with SCADA integration for data acquisition and visualization. Experimental validation demonstrated an increase in sugar yield up to 76-85%, a reduction in the coefficient of variation to 4%, a decrease in inhibitor concentration, reduced stabilization time and energy consumption, as well as robustness to disturbances and variations in feedstock composition.

This paper presents a comprehensive mathematical modeling study of the effect of an antireflection coating on the optical characteristics and performance of a silicon solar cell. The analysis is based on the Fresnel equations and the thin-film interference model, which are used to evaluate the spectral dependence of the reflection and absorption coefficients of solar radiation in the wavelength range of 400- 1100 nm. Particular attention is given to the interaction of incident light with the silicon surface and the role of optical losses in limiting device efficiency.

The results demonstrate that the application of an anti-reflection coating based on silicon nitride (Si₃N₄) leads to a significant reduction in surface reflectance and a corresponding increase in the absorption of incident solar radiation. A detailed modeling study of the dependence of the reflection coefficient on the coating thickness was carried out, allowing the determination of the optimal thickness of the anti-reflection layer under standard illumination conditions. The obtained results are consistent with theoretical predictions and reported experimental data.

In addition, the influence of optical losses on the overall photovoltaic performance was evaluated by considering the spectral distribution of solar irradiance and its contribution to photocurrent generation. It was shown that reducing reflection losses directly contributes to an increase in photocurrent and an improvement in the efficiency of photovoltaic energy conversion. The proposed modeling approach provides a useful framework for the design and optimization of thin-film coatings in modern high-efficiency silicon solar cells and can be extended to other photovoltaic materials and multilayer coating systems.

Cardiovascular diseases remain the leading cause of mortality, which determines the relevance of developing robust methods for cardiac image analysis and patient monitoring. This paper presents and validates a prototype pipeline for automated preprocessing and segmentation of biomedical images, developed within the framework of a scientific project (IRN: AP05132044). The experimental protocol is implemented on the Heart Database dataset (18 patients, 3D+t MRI (three-dimensional with time dimension)), using expert endocardial masks and 36 slices (diastole/systole, 2 slices per patient). Performance evaluation was conducted using PSNR, SSIM, Dice, and IoU metrics. A comparative analysis was performed across five preprocessing modes: none, Gaussian, wavelet, NLM, and hybrid (wavelet + NLM + CLAHE). The results show that the NLM method achieves the best denoising performance (PSNR = 26.07±0.33 dB vs. 22.85±0.21 dB for the baseline, p = 1.46×10⁻¹¹, Wilcoxon test), while the highest segmentation accuracy is obtained with hybrid preprocessing (Dice = 0.681±0.176 vs. 0.636±0.153 without preprocessing, p = 0.018). An analysis of challenging cases revealed that segmentation performance is strongly influenced by endocardial contrast and geometric complexity across different phases of the cardiac cycle. The obtained results demonstrate a statistically significant impact of the preprocessing stage on downstream segmentation quality and confirm the feasibility of the integrated “preprocessing-segmentation-evaluation” pipeline as an engineering foundation for clinical frameworks. The proposed approach is designed for reproducible performance under real-world data heterogeneity and can serve as a basis for further integration into clinical information systems.

The article investigates the control problem for a class of nonlinear strict-feedback systems with uncertain parameters and external disturbances. The main objective of the study is to develop an adaptive control algorithm that ensures system robustness and guarantees semi-global uniform boundedness of all signals.

To compensate for unknown dynamic functions, the recursive synthesis method, namely backstepping, is combined with adaptive approximation laws. The semi-global stability of the closed-loop system is analytically proven using the Lyapunov function method, and it is shown that the tracking error converges to a bounded neighborhood of zero.

As a result of the study, the control problem is formulated for second-order nonlinear strict-feedback systems with uncertain parameters and bounded external disturbances, and it is constructively demonstrated that this problem can be solved by means of adaptive robust control. In particular, the existence of a control law ensuring tracking of a given reference trajectory is established on the basis of the backstepping method, and a step-by-step synthesis procedure for its construction is proposed: first, a virtual control is designed, and then adaptive control laws are defined. Using the Lyapunov function method, the stability of the closed-loop system, the uniform boundedness of all signals, and the convergence of the tracking error to a bounded neighborhood of zero are proven. Thus, the work proposes not only a specific control algorithm, but also a theoretical and constructive approach that substantiates the solvability of the control problem for a class of uncertain nonlinear systems.

To verify the proposed method in practice, numerical simulation was carried out for the dynamics of a single-link robotic manipulator. The results showed that the proposed adaptive backstepping algorithm preserves the bounded motion mode of the system under sudden changes in the load parameter and in the presence of external disturbances. A numerical comparison was performed using the MSE, maximum error, and settling time criteria, and it was found that the control performance depends on the choice of algorithm parameters. The proposed method can be applied to the control of mechatronic and robotic systems with parametric uncertainty; however, additional tuning of the control gains is required before practical implementation.

A comparative evaluation of machine learning models for predicting liver cancer risk was performed using an open structured clinical dataset. A Kaggle dataset was used in the study (N=5000): target variable Liver_cancer, 13 features (9 numerical, 4 categorical), with class imbalance (0: 78.22%, 1: 21.78%). Data preprocessing, model training and evaluation were carried out within a unified experimental protocol. Numerical variables were normalized via standardization; categorical variables were encoded in binary format.

The comparative analysis included Logistic Regression, Support Vector Machine with an RBF kernel, k-Nearest Neighbors, Random Forest, and Gradient Boosting. All models were evaluated using accuracy, precision, recall (sensitivity), specificity, F1-score, and the area under the ROC curve (ROC-AUC).

Gradient Boosting achieved the highest overall performance: ROC-AUC=0.999498, Accuracy=0.9754, Precision=0.998967, Sensitivity=0.887971, Specificity=0.999744, F1=0.940204. Although SVM (RBF) and Random Forest demonstrated stable discrimination, they underperformed compared to Gradient Boosting in terms of sensitivity and F1. The results indicate that selecting a model based on structured clinical features requires a comprehensive multi-metric assessment; key limitations include class imbalance and the absence of external validation.

This paper addresses the stability problem of switched nonlinear systems with time delay. The dynamics of the considered system are governed by a switching signal that describes transitions between multiple subsystems, while the effect of time delay is explicitly taken into account. Ensuring system stability under arbitrary switching signals is a challenging and important problem in control theory. In this study, a method based on the Lyapunov-Krasovskii functional is employed to derive sufficient stability conditions for switched nonlinear systems with time delay. The proposed approach allows simultaneous consideration of nonlinear system properties, time-delay effects, and switching behavior, thereby providing a generalization of classical results. In addition, finite-time stabilization conditions are investigated, and a corresponding nonlinear state-feedback control law is proposed. This control law guarantees that the system states converge to the equilibrium within a finite time and achieves faster stabilization compared to asymptotic stability.The obtained theoretical results are validated through numerical simulations. The simulation results demonstrate that the system state variables converge to the equilibrium despite the presence of switching and time delay. Moreover, multiple switchings do not deteriorate system stability. The results confirm the effectiveness of the proposed method and show its applicability to the control of switched nonlinear systems with time delay.

This article presents the development of an information system for digital passports of laboratory equipment, intended to automate the accounting, identification and recording of the operational history of physical resources in laboratories of higher education institutions. The relevance of the study is determined by the need to move from paper-based journals and spreadsheets to more reliable digital solutions that ensure transparency, accessibility and structured storage of equipment data.

The aim of the study is to develop and test a prototype system that provides rapid identification of laboratory equipment using QR codes and access to up-to-date information through a web interface. The system was developed using the Python programming language, the Flask microframework, the embedded SQLite database and the qrcode library for QR code generation. The digital passport of equipment includes a unique identifier, name, inventory number, location, user information, as well as the date and time of the beginning and completion of equipment use.

As part of the study, a minimum viable version of the system was implemented and tested in the laboratory of the Department of Automation and Information Technologies at Shakarim University. The testing results confirmed the correct operation of the main modules, including QR code generation, registration of the beginning and completion of equipment use, saving records in the database and displaying the operational history. The proposed solution reduces the number of manual operations, lowers the risk of data loss and increases the transparency of laboratory equipment accounting.

The practical significance of the work lies in the possibility of adapting the system for other laboratories and educational organisations. The article also discusses the limitations of the current version and prospects for further development, including functionality expansion, repair accounting, report export and integration with the university’s information systems.

The article is devoted to the research of personalized medicine methods using Bayesian analysis. In modern medicine, one of the most important ways is to make effective decisions taking into account the genetic, clinical and lifestyle characteristics of each patient. In this regard, probabilistic approaches to data analysis in conditions of uncertainty have a special application. The research examines the possibilities of assessing the likelihood of developing diseases and optimizing treatment strategies by combining various sources of medical data. The Bayesian method combines preliminary knowledge and new clinical information. Thus, it allows you to increase the accuracy of diagnosis and assess risks. The study analyzes effective ways to support the medical decision-making process using probabilistic models. At the same time, the practical significance of a personalized approach in medicine is revealed. In particular, the issues of early diagnosis and individualization of treatment are considered. The presented method allows you to improve the quality of medical data processing. Aimed at developing the rules of personalized medicine.

This article examines the design and practical implementation of an intelligent multi-agent system for monitoring educational achievements in the context of the digitalization of secondary education. The relevance of the study is обусловлена the need to shift from retrospective knowledge assessment to preventive management of individual learning trajectories based on the analysis of a student’s “digital footprint.” The authors propose a system architecture that includes three types of specialized agents: a Diagnostic Agent, a Methodological Agent, and a Predictive Agent. The mathematical framework of the system is based on hierarchical models for classifying learning risks according to four key criteria: academic performance, attendance, activity, and learning pace. The developed software, implemented in Python, follows the concept of Explainable Artificial Intelligence (XAI), ensuring transparency and interpretability of diagnostic outcomes for educators. During the system’s testing on a student sample, significant positive results were obtained: automation of the monitoring process reduced the time required for preparing class analytical reports by 70- 80%, while simultaneously improving the accuracy of final grade predictions. The system automatically generates personalized intervention scenarios tailored to the specific type of identified learning barrier.

The discussion section outlines unresolved issues, including the dynamic adjustment of weighting coefficients in the utility function and the need to integrate the developed solution with national educational information systems for academic performance tracking.

Automatic morphological analysis remains a challenging task for agglutinative languages because of their rich inflectional systems, productive derivation, and complex morphophonological rules. Recent neural models, especially transformer-based architectures, have demonstrated impressive empirical performance. However, they frequently exhibit a deficiency in linguistic transparency and encounter challenges in systematic generalization inside low-resource environments. This research offers a comparative and integrative examination of formal (rule-based and finite-state) and neural (KazBERT-based) methodologies for morphological analysis, utilizing the Kazakh language as a case study of low-resource agglutinative morphology. Initially present a formal morphological model that distinctly represents root-affix structure, vowel harmony, and morphotactic restrictions. We next test many neural architectures for morphological disambiguation and tagging, such as KazBERT coupled with CRF-based decoding. In addition to typical accuracy measurements, we do a comprehensive error taxonomy and linguistic analysis, investigating how various model classes manage ambiguity, infrequent forms, and extended affix chains. The findings indicate that whereas neural models excel in surface-level accuracy compared to exclusively rule-based systems, they demonstrate consistent deficiencies in morphologically intricate and infrequent constructs. On the other hand, formal models show better generalization based on language limitations. Based on these results, we suggest a hybrid morphology-aware framework that adds symbolic restrictions to neural inference. This framework consistently improves results in a variety of assessment contexts. The study demonstrates that effective morphological analysis of agglutinative languages requires the integration of neural representation learning with explicit linguistic structure. The results are not tied to any one language and have wider implications for morphology-sensitive NLP in low-resource settings.

A new method is presented for synthesising a control algorithm for second-order nonlinear dynamic systems based on the concept of fixed-time stabilisation with output feedback. The study focuses on a broad class of planar nonlinear systems for which full access to state variables is not possible. The proposed methodology is based on a combination of the theory of bi-limit homogeneity and the principles of classical Lyapunov stability analysis. This approach has enabled the development of a continuous observer with a fixed convergence time, which reliably estimates the unmeasurable state of the system regardless of initial conditions and initial estimation errors. Based on this estimation, a continuous controller is constructed that ensures system stabilisation within a predetermined time.

The method has a number of advantages: stability and convergence do not depend on the magnitude and sign of the initial conditions; control remains continuous, which eliminates oscillation of the actuators; high robustness to limited external disturbances and measurement noise is achieved. The algorithm can be implemented on microcontrollers without the need for high-frequency sampling, making it attractive for practical use. As an example, the dynamics of a microelectromechanical system (MEMS) mirror are considered, which is a striking example of a highly non-linear electromechanical object. Numerical simulations were carried out, the results of which confirm the effectiveness of the proposed control scheme. Compared to existing finite-time controllers, the transient response time is reduced by more than a factor of four, whilst the system error and energy consumption are reduced by almost half. The results obtained confirm the applicability of the developed method to high-precision control of micro- and macro-mechanical actuators, as well as in intelligent robotic and vibro-optical systems.

The article examines the methodological foundations of applying artificial intelligence technologies in the teaching of specialized disciplines, with a focus on identifying both their pedagogical potential and associated risks. The relevance of the study is determined by the ongoing digital transformation of education and the growing demand for innovative tools that enhance the effectiveness and adaptability of the learning process. The paper analyzes key directions of AI integration into educational practice, including adaptive learning systems, intelligent tutoring, automated assessment, and personalized learning pathways. Particular attention is given to the methodological principles that ensure the effective implementation of these technologies, such as alignment with learning objectives, didactic appropriateness, and the role of the instructor in a technology-enhanced environment.

At the same time, the study highlights a range of challenges and risks related to the use of artificial intelligence, including potential bias in algorithmic decision-making, issues of academic integrity, reduced critical thinking, and increased dependence on digital tools. The importance of maintaining a balance between technological innovation and pedagogical control is emphasized. The results of the study contribute to the development of a structured approach to integrating artificial intelligence into higher education, aimed at improving the quality of teaching specialized disciplines while minimizing potential negative impacts.

This paper presents a hardware and software platform for modeling and analyzing interference in wireless data transmission systems aimed at studying the reliability and stability of modern wireless communication networks. The relevance of the research is driven by the rapid growth of Internet of Things devices, the active deployment of Wi-Fi and 5G technologies, and the increasing requirements for communication quality and reliability under external electromagnetic interference conditions. The main objective of the study is to develop a universal tool for generating, simulating, and analyzing different types of interference in wireless communication channels with real-time visualization capabilities.

The hardware architecture includes a transmitter, receiver, and interference generator implemented on ESP32 microcontrollers. Software for controlling device parameters and simulation scenarios was developed in the C++ programming language using the Arduino IDE environment. Data exchange between system modules is organized through the WebSocket protocol within a unified Wi-Fi network, enabling synchronous real-time transmission and processing of signals. The paper describes the electrical schematics of the developed devices, the interaction architecture of the modules, and the operating algorithms of the system components.

The proposed platform makes it possible to simulate electromagnetic, noise, and adjacent-channel interference, analyze the influence of amplitude modulation on data transmission quality, and evaluate the stability of wireless communication channels. Experimental testing confirmed the effectiveness of the developed model and the operational reliability of the system. Due to its flexible architecture, the platform can be adapted for research on Wi-Fi, Bluetooth, and ZigBee technologies and can be effectively used in scientific and educational laboratories for developing and testing new interference mitigation methods in wireless networks.

This study focuses on the development of a forecasting model for the distribution of school graduates across educational pathways based on demographic and socio-economic factors in the Republic of Kazakhstan. The relevance of the research is driven by the need for a scientific understanding of how graduates are allocated among different forms of further education under conditions of demographic change and transformation of the education system. The study is based on official statistical data for the period 1992– 2025, including indicators of birth rates, living standards, and the distribution of graduates across educational pathways (higher education, vocational education, studying abroad, and alternative forms of activity). To identify relationships between demographic and socio-economic variables and the choice of educational pathway, correlation analysis and analysis of variance (ANOVA) were applied.

The results reveal statistically significant relationships between birth rates, population income levels, and the distribution of graduates across different educational directions. It is established that demographic fluctuations determine the volume of graduates, while socio-economic factors shape the structure of their educational choices. The proposed forecasting model enables the assessment of future demand for the education system and supports the development of evidence-based policy decisions in the field of education.

This study aims to explore and develop advanced methods for the effective detection of breast pathologies using state-of-the-art machine learning techniques, specifically YOLOv8 and Faster R-CNN. Traditional approaches to breast disease diagnosis are critically reviewed, and their effectiveness is evaluated in comparison to modern automated methods. The proposed models are applied to mammographic images to identify and categorize pathological patterns into six distinct levels, considering variations in severity and disease characteristics. This multi-level classification allows for a more precise assessment of disease progression and provides critical information for personalized treatment planning.

Experimental results demonstrate that the proposed approach achieves high accuracy and fast image processing, enabling reliable and rapid detection of potential breast abnormalities. These findings suggest that machine learning algorithms can significantly enhance the diagnostic process, providing clinicians with more accurate and timely information. Furthermore, the study highlights the potential of automated detection systems to improve early diagnosis, optimize treatment strategies, and ultimately enhance patient outcomes. The results emphasize the growing role of artificial intelligence in medical imaging and its transformative impact on the future of breast disease management.

In recent decades, the use of virtual reality (VR) and augmented reality (AR) in the field of education has been growing significantly. Virtual reality (VR) and augmented reality (AR) are becoming one of the key directions in the digital transformation of education in Kazakhstan. Their immersive and interactive nature offers teachers and students unique opportunities to collaboratively explore complex concepts and environments. These technologies open new possibilities for improving the quality of the learning process, expanding access to modern educational resources, and developing practical skills that are in demand in a rapidly changing economy.

Using VR, it is possible to create fully immersive learning environments in which students can safely simulate real-life scenarios-from conducting laboratory experiments to mastering complex technical processes. Such learning helps develop critical thinking, increases motivation, and enhances understanding of the material due to the strong sense of presence.

AR technologies, in turn, make the learning process more visual and interactive by overlaying digital information onto the surrounding physical world. In schools and universities across Kazakhstan, the use of AR is already showing high effectiveness: students can visualize anatomical structures, geological layers, historical artifacts, and other objects that are difficult to understand. This makes abstract concepts easier to comprehend and allows students to maintain their individual learning pace.

In recent years, Kazakhstan has been actively implementing state and private initiatives aimed at integrating VR/AR technologies into the educational process. Specialized laboratories, digital classrooms, and pilot projects in engineering, medical, and humanities programs are being launched. The development of these technologies helps build an innovative educational ecosystem, enhance digital literacy, and develop the competencies required for the future among young people.

To achieve this goal, the article analyzes these initiatives and explores how digital tools contribute not only to subject-specific knowledge but also to the development of transversal competencies. Among the selected examples, this article highlights the pedagogical value of virtual and augmented reality technologies, their advantages, and their practical application in the university environment. The findings demonstrate that immersive technologies make the learning process engaging, flexible, and student–centered. Thus, VR and AR are becoming powerful tools for modernizing Kazakhstan’s education system. Their integration helps create a flexible, accessible, and practice-oriented learning model that aligns with the requirements of the digital economy and the country's strategic development priorities.

In the context of water scarcity and tightening environmental requirements, improving the energy efficiency of biological wastewater treatment processes has become particularly important. The aeration tank is one of the most energy-intensive and dynamically complex components units, strongly affected by the variability in influent flow and composition. Conventional PID control, do not provide predictive disturbance compensation and often result in excessive aeration and increased energy consumption. The study proposes an intelligent control approach based on a digital twin, neural network-based influent flow forecasting, and model predictive control (MPC). The digital twin represents a dynamic model of the biological process incorporating key state variables, including substrate, activated sludge, and dissolved oxygen concentrations. A neural network model is used to predict the diurnal variability coefficient of influent flow based on long-term statistical observations. The predicted values are incorporated into the MPC algorithm as measured disturbances, enabling anticipatory aeration system. Simulation results show stabilisation of dissolved oxygen under variable inflow conditions and reduces energy consumption by preventing over-aeration. The proposed architecture is suitable for implementation within existing industrial PLC-SCADA systems in advisory MPC mode and improves energy efficiency, robustness, and environmental performance.

At present, self-adjusting systems are widely used in robotics, autonomous transport, and the aerospace industry. D. Wayns examines the key principles, engineering approaches, and application areas of self-adaptation in software-intensive systems, emphasizing its growing importance in addressing the challenges of emerging technologies.

Bollinger provides an overview of automated drives and control systems used both in industry and in research facilities. It is noted that multi-coordinate robotic systems are complex technical objects for which control processes may be accompanied by fundamental theoretical limitations.

The expansion of self-adaptation capabilities can be achieved through the implementation of adaptive mechanical drives capable of independently responding to changes in external load without the need to regulate energy parameters. In this case, control is largely reduced to coordinating the operation of individual drive elements.

This study considers a compact self-regulating adaptive drive consisting of a motor and an adaptive mechanical converter operating without a control system.

The paper examines the theoretical principles for developing a compact continuously variable drive with an adaptive mechanical converter that provides regulation over a wide range without the use of a control system.

This paper presents the results of a comparative analysis of the architecture of IoT monitoring systems in the mining industry. It examines the implementation of Internet of Things technologies to improve the efficiency of monitoring and control in an industrial environment. The focus is on ensuring safe working conditions, increasing productivity and environmental sustainability, as well as compliance with regulatory requirements. Furthermore, this article examines the current state of information technology in the mining industry, with a focus on the risks and consequences caused by outdated equipment, unreliable software, and the degree of digitalisation. This study discusses the integration of IoT technologies into existing information systems in the mining industry, enhancing their levels of security, efficiency and sustainability. The scientific novelty of the research lies in the creation of a phenomenological model of an IoT system architecture suitable for a wide range of operations in the mining industry. The study provides a detailed analysis of process optimisation and the operation of distributed sensor systems that collect, process and analyse critical data in real time. Based on the information obtained, well-founded decisions are made regarding the implementation of intelligent monitoring and control systems designed to ensure sustainable operations.

This paper presents a tutorial on programming the ESP32 microcontroller using MicroPython firmware and the Thonny development environment on the KEIT (Knowledge ESP32 Integration Trainer) training rig. The designed and manufactured rig, its operating principles, and a schematic diagram and printed circuit board (PCB) are provided. The MicroPython programming curriculum includes 12 lab sessions, ranging from basic GPIO control (LEDs, buttons, and buzzer) to integration with cloud services via the MQTT protocol. Sequentially completing the tasks allows students to master the fundamentals of working with digital and analog interfaces, learn to interact with sensors, displays, and actuators, and become familiar with the networking capabilities of the ESP32. Particular attention is paid to practical aspects, such as button debounce, working with interrupts, generating PWM signals, and measuring time intervals. The authors also present the specialized control software «KEIT Master Control», which complements the entire hardware and software system and reinforces the theoretical foundations of microcontroller programming in MicroPython. The final lessons focus on creating a simple web server on the ESP32 and exchanging data via an MQTT broker, providing students with a basic understanding of the principles of the Internet of Things. The course concludes with mini-projects («smart room», «parking assistant», and «Wi-Fi weather station») that integrate the technologies covered and demonstrate the potential of the ESP32 for automation and smart home systems. The curriculum can be used in universities and colleges for students majoring in Information Technology, Automation, Mechatronics and Radioelectronics.

The conducted research is aimed at studying the chemical composition and physical properties of nontraditional crops, such as naked oats, triticale, naked barley and green buckwheat. Despite the limited use of the studied crops in the food industry, their grain has significant potential due to the high content of proteins, flavonoids, vitamins, dietary fiber, antioxidants and phenolic acids, which have beneficial properties. As a result of the conducted research, it was found that the highest amount of protein is contained in naked oat grain (16.17%), while the lowest fat content was found in green buckwheat grain (1.54%). Carbohydrate analysis showed that the highest carbohydrate content is in green buckwheat. The mineral content, estimated through ash content, varies from 0.16% in buckwheat to 1.22% in barley. The highest content of crude fiber is observed in green buckwheat (3.52%). An analysis of the amino acid composition of the grain was also conducted, where oats stand out for their high content of phenylalanine, and barley for its high content of valine. The results of the study highlight the importance of these non-traditional grain crops for the food industry, as they can be used as valuable sources of proteins, amino acids and dietary fiber, as well as for the creation of functional products with improved nutritional properties.

The paper presents the results of a study on the production of food oleogels based on beeswax, monoglyceride and their binary mixture (50:50) used as structure-forming agents. The choice of the optimal structurizer is justified based on the assessment of the structural-mechanical (hardness, elasticity) and functional-technological (oil-binding ability) properties of oleogels for use in the technology of fat-and-oil products. It was found that all the studied samples form self-sustaining oleogels with a homogeneous structure. It is shown that the samples obtained using binary mixtures of structure-forming agents are characterized by higher values of hardness, elasticity, and oil-binding ability compared with single-component samples. This indicates a more efficient formation of the spatial gel network and an increased ability to retain oil. Beeswax promotes the formation of a strong crystalline structure, while monoglycerides provide plasticity and improved oil retention. Their combined use leads to the formation of a structured gel system with an optimal combination of structural-mechanical and functional-technological characteristics and may also indicate the presence of synergistic interaction of structure-forming agents. The results obtained confirm the expediency of using binary systems of structure-forming agents and their prospects in the development of spreads and other fat-and-oil products.

Enzymatic reactions play a fundamental role in the transformation of muscle tissue into meat and in the formation of quality attributes in meat products. Postmortem glycolysis, proteolysis, and lipolysis mediated by endogenous enzymes – calpains, cathepsins, aminopeptidases, and lipases – determine texture, color, and flavor. Additional modification of the protein–lipid matrix is ensured by microbial enzymes of starter cultures and by exogenous plant-derived proteases used to regulate structural and sensory properties. Their activity promotes the accumulation of free amino acids, peptides, and volatile compounds responsible for characteristic flavor development. However, the natural rate of enzymatic reactions and the complexity of their control, influenced by pH, temperature, salt content, and water activity, require the application of controlled intensification strategies.

This review summarizes current advances in innovative technologies aimed at accelerating and optimizing enzymatic processes in the meat industry. The effects of ultrasound (US), pulsed electric fields (PEF), moderate electric fields (MEF), high hydrostatic pressure (HHP), and supercritical CO₂ (SC-CO₂) are discussed in relation to protease activation, increased tissue permeability, and enzyme activity modulation. The review emphasizes that integrating non-enzymatic intensification methods with conventional fermentation and ripening technologies offers prospects for shortening production cycles, improving quality stability, and expanding the range of functional meat products. The findings provide a theoretical basis for the development of scientifically grounded modernization strategies in meat fermentation and ripening processes.

This scientific study, taking into account the biochemical and technological advantages of camel milk, developed a technology for producing national kurt with the addition of dried apricot (kuraga). The research analyzed the physicochemical properties of camel milk, its natural parameters suitable for fermentation, and its efficiency in the production of fermented milk products.

The nutritional and functional properties of kuraga, including natural sugars, potassium, β-carotene, and pectins, were used to improve the quality characteristics of kurt.

The study included determining the chemical composition, organoleptic characteristics, moisture content, acidity, and energy value of the final product. Samples with 3%, 5%, 7% kuraga were comparatively studied, and the 5% kuraga variant was found to be the most effective in terms of taste, structure, and vitamin content. The content of B vitamins in the selected sample showed the following results: B1 – 0.057±0.011, B2 – 0.208±0.085, B3 – 4.22±0.818, B5 – 0.330±0.064, B6 – 0.125±0.023.

As a result, a scientifically justified technological scheme for producing kurt from camel milk with the addition of kuraga was proposed, which increases the nutritional value and functional properties of the product. This technology promotes the modernization of national products and expands their market demand.

This article focuses on the development of a polycomponent fat emulsion and the investigation of its physicochemical properties. The emulsion exhibited a moderately acidic pH of 5.64 ± 0.12, indicating suitability for food applications and consistent structural stability. The structured lipid matrix, formed by rice bran wax and stabilized with chickpea flour, maintained emulsion integrity during storage at 4 °C. Water activity (aw) was measured at 0.947, reflecting a relatively high level of free moisture typical of oil-in-water food emulsions, emphasizing the need for proper storage conditions to ensure microbiological stability. Rheological analysis revealed shear-thinning behavior, with apparent viscosity decreasing from 83.43 to 29.60 mPa·s as rotational speed increased, demonstrating progressive disruption of internal interactions under stress. Color and oil binding capacity measurements confirmed a visually uniform and stable system. Overall, the emulsion combines improved lipid composition with desirable technological properties and has potential as a structured fat system or partial animal fat replacer in various food products. Further studies will investigate the possibility of using this emulsion as a partial animal fat replacer in cooked sausage products.

The article presents the results of a study on the technological parameters of the fermentation process of a combined dairy mixture using buttermilk concentrate. The relevance of the research is determined by the growing interest in the utilization of secondary dairy resources with high nutritional and biological value, as well as by the need to develop scientifically grounded technologies to produce functional fermented dairy products. The aim of the study was to evaluate the effectiveness of various starter cultures under different fermentation temperature regimes of a combined dairy mixture. The object of the study was a dairy mixture consisting of skimmed cow’s milk, goat’s milk, and buttermilk. The influence of starter culture composition and fermentation temperature on physicochemical parameters, acidification dynamics, and curd structure formation was investigated. It was established that the combination of mesophilic and thermophilic lactic acid microorganisms significantly affects fermentation intensity, titratable acidity, and structural stability of the product. The results demonstrated that an optimal fermentation temperature promotes the formation of a homogeneous curd with improved physicochemical and sensory characteristics, whereas deviations from optimal conditions lead to structural defects and deterioration of product quality. The results obtained confirm the feasibility of a comprehensive selection of starter cultures and fermentation temperature regimes in the production of fermented dairy products based on combined dairy mixtures using buttermilk concentrate.

The article examines approaches to improving the salting technology of horse meat in order to enhance its nutritional and biological value. In the course of the study, a plant-based salting composition was applied in combination with the shock freezing method. The salting mixture included sodium chloride, laminaria, dried spinach, and garlic, which made it possible to enrich the product with biologically active substances and mineral components. The prepared horse meat samples were subjected to shock freezing at a temperature of -45°C for 3 hours, contributing to the preservation of muscle tissue structure and reduction of nutrient losses.

To assess the effect of the plant-based additive, different concentrations of the salting mixture – 5%, 10%, and 15% – were used. The resulting samples were analyzed based on organoleptic, structural-mechanical, and quality indicators. The research results showed that horse meat treated with a 10% salting mixture exhibited the most balanced characteristics in terms of taste, aroma, and texture. The use of laminaria and spinach contributed to an increase in mineral content, particularly iodine, thereby enhancing the functional value of the product, especially for regions with iodine deficiency. The conducted studies confirm the effectiveness of using a plant-based salting composition combined with shock freezing as a promising approach in horse meat processing technology, ensuring quality preservation and extended shelf life.

The article presents the results of comprehensive studies on the development of formulations for meatplant pâtés using plant ingredients – flax and hemp flour (зығыр және қарасора ұны). The object of the study was pâtés made from turkey and duck meat with the addition of plant components in the amount of 4-10% in a 1:1 ratio. Standard physicochemical, functional-technological, and organoleptic methods were applied to comprehensively assess the quality of the final product. It was found that the inclusion of plant ingredients significantly affects the chemical composition of pâtés: protein content increased up to 19.8%, the share of minerals and carbohydrates increased, while moisture content decreased. The addition of flax and hemp flour positively influenced the functional-technological properties of the product: water-holding capacity increased up to 82%, structural-mechanical characteristics of the mince improved, and reduced water activity contributed to enhanced microbiological stability and prolonged shelf life. Organoleptic evaluation results indicated that the optimal dosage of plant ingredients is 6% (flax flour – 3%, hemp flour – 3%), ensuring the best combination of taste, aroma, color, and consistency. Increasing the dosage to 8-10% led to a deterioration of organoleptic properties, in particular the appearance of bitterness and changes in product texture. The scientific novelty of the study lies in the rationale for the rational combination of meat and plant ingredients, considering their complex influence on pâté quality indicators. The practical significance of the study is the possibility of applying the developed formulation in the production of functional meat products with enhanced nutritional and biological value, meeting modern healthy nutrition requirements.

The nutritional and biological value of animal fats directly depends on their anatomical location, physicochemical properties, and fatty acid composition. Currently, in the development of functional food products, the effective use of natural lipid raw materials with high biological activity is one of the important scientific directions. In this context, horse fat attracts scientific interest not only as a traditional food resource but also as a promising functional ingredient.

In this study, the physicochemical and fatty acid properties of horse internal fat, visceral fat (kazy), and subcutaneous fat (zhaya) were comparatively investigated. During the research, the acid value, peroxide value, and iodine value, the mass fraction of moisture and volatile substances, as well as the composition of the main fatty acids were determined. The experimental results revealed significant differences among the fat samples in terms of oxidative stability, the proportion of unsaturated fatty acids, and quality indicators. In particular, it was established that the subcutaneous fat contains a higher level of unsaturated fatty acids, which confirms its high nutritional and biological value.

The obtained data substantiate the possibility of the targeted use of different anatomical types of horse fat in food products. In addition, the research findings establish scientific prerequisites for the effective application of horse fat in the development of formulations for functional, traditional, and composite food products and provide a basis for expanding the range of high-quality fat-based products in the domestic food industry.

This study presents a comparative analysis of organic compounds in extracts obtained from cherry  v(Prunus cerasus), stevia (Stevia rebaudiana), and soybean (Glycine max). The chemical composition of the extracts was characterized using gas chromatography-mass spectrometry (GC-MS), allowing identification of the main constituents and determination of their relative abundances. In the cherry extract, furan derivatives were found to be predominant, with 5-hydroxymethylfurfural being the major component. The soybean extract contained significant amounts of sugar derivatives and phenolic compounds, which are known for their antioxidant activity. Analysis of the stevia extract revealed the presence of polyols and phenolic compounds, including hydroquinone. The detected furan derivatives, phenolic compounds, and polyols may contribute to the antioxidant and anti-inflammatory properties of the extracts. Overall, the findings suggest that these plant materials are promising sources of naturally occurring bioactive compounds, which could be further utilized in the development of functional foods, dietary supplements, or nutraceutical applications.

The article presents the results of a study on the effect of soluble plant dietary fiber on the viability of lactic acid bacteria and the microbiological stability of functional yogurt. The relevance of the study is determined by the need to increase the functional value of fermented dairy products and to ensure a stable level of probiotic microflora throughout the storage period.

The object of the study was yogurt produced from pasteurized milk with a fat content of 1.0% using a starter culture containing Streptococcus thermophiles and Lactobacillus delbrueckii subsp. bulgaricus. Soluble plant dietary fiber was added at concentrations of 0.3%, 0.5%, and 1.0%.

The viability of lactic acid bacteria was determined by the plate count method on MRS agar followed by colony-forming unit enumeration, and the results were expressed as log CFU/g. The analyses were performed on days 1, 7, and 14 of storage at 4 ± 2 °C.

The results showed that the addition of plant dietary fiber did not exert an inhibitory effect on the development of lactic acid microflora. On the contrary, samples containing fiber demonstrated higher bacterial survival compared with the control sample. On the 14th day of storage, the number of viable cells in the control sample decreased to 7.6 log CFU/g, whereas at a concentration of 0.5% it remained at the level of 8.1 log CFU/g.

The obtained data indicate the potential prebiotic effect of plant dietary fiber and its positive influence on the microbiological stability of the product. The concentration of 0.5% was found to be optimal, providing the best balance between microbial stability and technological characteristics. The developed product meets regulatory requirements and can be recommended for the production of functional fermented dairy products.

The modern food industry offers consumers bread baked using sourdough starters enriched with various biologically active components of plant origin. The use of sourdough with directed cultivation of microorganisms allows for the production of high-quality, competitive bread. The aim of this research was to develop a formulation for spontaneous fermentation wheat sourdough using rose hip concentrate and to study its qualitative characteristics. As a result of the studies, a formulation for spontaneous (natural) fermentation sourdough based on rose hip fruit concentrate was developed. The cultivation of the wheat sourdough takes 7 days; a temperature between 21°C and 28°C is maintained for optimal fermentation. The finished sourdough should be strong and bubbly, with a pleasant acidic-fruity aroma. It was established that with an increase in rose hip concentrate dosages from 2.5% to 17.5%, the initial acidity increased by 5.2-31.6%, and the final acidity by 2.3-45.45%. The lifting power (leavening ability) of sourdough samples containing 2.5, 5.0, 7.5, and 10.0% rose hip concentrate was not inferior to the control sample, while a further increase led to a deterioration of the lifting power. Thus, a rational dosage of rose hip concentrate in the amount of up to 10.0% in the sourdough was established, ensuring good physicochemical quality indicators of the starter.

Camels (Camelus dromedarius), which are highly resilient to extreme climatic conditions, play a vital role in ensuring food security and the sustainability of pastoral farming in Kazakhstan. Enzymatic coagulation is a key stage in cheese production, determining the structure, yield and quality characteristics of the product. The efficiency of coagulation and the intensity of proteolysis depend on the nature of the coagulant and its rennet and proteolytic activity, which is particularly important when processing camel milk, given its specific protein composition.

This study aimed to conduct a comparative analysis of camel’s milk cheeses produced using microbial and animal-derived coagulants. The study assessed dry matter content, yield, and textural characteristics, and evaluated the effect of coagulant type on the formation of the cheese’s peptide profile. The results obtained show that, under various temperature conditions, the Kalase coagulant exhibited a longer coagulation time, ranging from 224,8 s at 34 °C to 95,6 s at 40 °C, compared with the Chy-Max coagulant, which ranged from 180 s at 34 °C to 88 s at 40 °C. In contrast, at higher temperatures (38-40 °C), the difference narrowed to 7,6- 9 s. Syneresis showed that when using the Chy-Max coagulant, the curd released an average of 55,6% whey, whilst cheese samples using the Kalase coagulant showed a lower syneresis level of 45,6%. The cheese yield using the Chy-Max coagulant was 20,9%, whilst that using the coagulant Kalase was 18,7%. The total solid content in the cheese samples using the coagulant Chy-Max and Kalase was 48,4%±0,05 and 47,3%±0,5, respectively. The textural parameters of the cheeses indicated a denser texture when the microbial coagulant was used. Biologically active peptides were also identified in both cheese samples, which possess antihypertensive, antioxidant, antimicrobial, and immunomodulatory properties.

The article proposes and tests an integrated technical scheme for the early detection, digital passportization, and preparation of Halyomorpha halys Stål samples for molecular-genetic verification under the conditions of southern Kazakhstan. The aim of the study was to develop a reproducible system combining field monitoring, GPS referencing of foci, standardized recording of samples, and the formation of a collection suitable for subsequent analysis using the COI and ITS1 markers. Field testing of the system was carried out in the Botanical Garden of Almaty using pheromone traps and trap belts on apple and pear trees. During the observations, 215 individuals at different developmental stages were recorded. The highest abundance was detected in the central part of the surveyed territory; the maximum values were recorded at points D1 and D2 (30 and 33 individuals, respectively). It was established that pheromone traps provide more complete detection of adult imagoes, whereas trap belts increase the detectability of nymphal stages. A unified digital passport of the sample was proposed, ensuring the traceability of data from the moment of collection to the stage of laboratory processing and spatial analysis. The developed system can serve as the first stage of dissertation research on the molecular structure of invasive populations of H. halys and as a basis for regional phytosanitary monitoring programs.

The effectiveness of phytohormone application is largely limited by their rapid degradation, uneven distribution on the seed surface, and the lack of control over their release during germination. In this study, a multilayer polymer coating based on methylcellulose was developed and investigated for the controlled delivery of the phytohormone fusicoccin (FC) to soybean seeds using a mineral filler (talc) and a polysaccharide filler (potato starch). The physicochemical properties of the coatings, application uniformity, degradation kinetics, and release of the active compound under different temperature and humidity conditions were evaluated. The methylcellulose-talc compositions exhibited higher mechanical stability, lower swelling tendency, and longer degradation time compared with starch-based systems. The release of FC followed first-order kinetics, with a rate constant of 0.025 h⁻¹ and a half-life of 27.8 h. The obtained results confirm the potential of the developed methylcellulose-talc coatings for the prolonged and controlled delivery of phytohormones in seed pre-sowing treatment technologies. In the future, these findings may be used in further studies of polymer coatings under seed germination conditions.

This article examines the role of melissopalynological analysis in food safety assurance and honey authenticity control in the Republic of Kazakhstan. The relevance of the study is associated with increasing quality requirements for food products, the need to verify the botanical origin of honey, and the risks of adulteration related to mislabeling and alteration of the natural composition of the product. The aim of the work is to substantiate the significance of melissopalynological analysis as an effective tool for identifying the origin of honey and detecting signs of adulteration. The study is based on an analytical review of international regulatory documents and modern domestic and foreign publications on melissopalynology, honey authentication, and methods for verifying botanical composition. It is shown that the pollen spectrum is an important natural marker of honey origin and that melissopalynological analysis makes it possible to confirm botanical origin, identify discrepancies in labeling, and form an evidence base in quality assessment. Based on the literature analysis, an integrated model of honey control for Kazakhstan is proposed, combining melissopalynological, physicochemical, and molecular levels of verification. The results may be used in laboratory practice, veterinary and sanitary expertise, and state quality control systems.

This article examines the role of microorganisms in breadmaking, as key participants in fermentation processes. Special attention is given to yeasts and lactic acid bacteria, their interaction, and their influence on the formation of bread structure, taste, aroma, and nutritional value. Modern scientific data on the metabolic activity of microorganisms in dough are analyzed, as well as factors affecting their growth and development, including temperature, medium composition, and technological parameters. Contemporary approaches to the use of probiotic cultures in bread production are also considered, aimed at enhancing the functional value of the final product.

Particular attention is paid to methods of controlling microbiological contamination of raw materials and finished products, which is essential for ensuring the safety and consistent quality of bakery products. It is shown that the use of controlled microbiological processes not only improves technological characteristics but also enhances the biological value of the product.

Thus, the development of breadmaking is closely linked to a deeper understanding of the role of microorganisms. Advances in microbiology and biotechnology create opportunities for improving technologies, enhancing product quality, and ensuring safety, which is especially important in the context of increasing demands for food products.

Plant remains are an important component of the ecosystem and a source of organic matter for soils, playing a key role in the carbon cycle and the formation of humus. In the conditions of the Turkestan region, characterized by an arid climate, the study of the microbial diversity of plant residues is especially important for assessing the decomposition processes of cellulose and polysaccharides.

The aim of the study was to study the composition of cellulolytic microorganisms in plant residues and to assess their functional potential for biotechnological applications. The main areas of work included the isolation of bacteria and fungi, their morphological and quantitative characteristics, identification by the MALDI-TOF method, as well as analysis of their role in the decomposition of cellulose and the formation of soil humus.

The scientific significance of the study lies in clarifying the structure of the microbial community of the plant remains of the arid region and identifying species with high enzymatic activity, which expands knowledge about cellulolytic bacteria and fungi. The practical significance of the work lies in using the data obtained to develop biotechnological approaches for processing plant residues and increasing soil fertility.

The methodology used was the isolation of microorganisms on standard nutrient media, morphological assessment of colonies, quantitative determination in CFU/g, as well as species identification of bacteria and fungi by the MALDI-TOF method, which ensured high accuracy in the determination of microorganisms.

The bacteria Bacillus cereus, Bacillus megaterium, and Acinetobacter lwoffii were isolated during the study. Bacillus spp. they provide the primary destruction of fiber and polysaccharides, fungi participate in the decomposition of more structured cellulose and lignin, and Acinetobacter lwoffii processes decomposition byproducts and supports the functional diversity of the microbial community.

The study has contributed to the understanding of the functional diversity of cellulolytic microorganisms in arid ecosystems and highlighted their role in biotechnology. The practical significance of the work lies in the possibility of creating enzyme preparations, bioconversion of agricultural waste and the development of biofertilizers that contribute to the sustainable development of the agroecological systems of the region.

The article presents the results of applying the QFD (Quality Function Deployment) methodology for the systematic analysis and improvement of the quality of dry-cured smoked chicken breast. The relevance of the study is обусловлена increasing competition in the meat products market, as well as the growing consumer demands for product safety, naturalness, and stability of organoleptic characteristics. In the course of the research, a marketing study was conducted using a questionnaire survey method, which made it possible to identify and quantitatively assess the key consumer requirements. Based on the obtained data, a House of Quality matrix was constructed, reflecting the relationships between consumer requirements and the technical characteristics of the product. The conducted QFD analysis enabled a systematic evaluation of the impact of the technical characteristics of dry-cured smoked chicken breast on consumer satisfaction. Using the weighted coefficient method, the relative priorities of technological parameters were calculated. The results showed that the indicators having the greatest influence on consumer satisfaction are moisture content (26.65%), formulation composition (25.48%), and storage parameters (18.26%). Technological interdependencies between moisture content, protein content, and storage conditions that affect product safety and organoleptic properties were identified. The practical significance of the study lies in the possibility of applying the obtained results to optimize formulations, improve technological regimes, and enhance the competitiveness of meat processing enterprises.

This study investigates the effect of the husking stage of safflower seeds on the quality, physicochemical parameters, organoleptic properties, and biochemical composition of the oil. A comparative analysis of oil obtained from uncrushed seeds and crushed kernels was performed, with an assessment of the acid number, peroxide number, mass fraction of moisture, dynamics of oxidative stability, fatty acid composition, and content of minor components (tocopherols, phytomelan, chlorophylls).

The results showed that removing the shell significantly improves the organoleptic properties of the oil (taste, smell, color, transparency), reduces the acid and peroxide values, decreases the moisture content, and increases resistance to oxidation. Biochemical analysis confirmed an increase in the proportion of linoleic and oleic acids, an increase in the concentration of tocopherols, and the absence of antinutrients such as phytomelan.

Thus, seed hulling technology provides a comprehensive improvement in the quality and nutritional value of the oil, making it a premium product ready for consumption without additional intensive refining. The results of the study can be used to optimize the technological processes of producing high-quality vegetable oils. The data obtained during the study demonstrated that optimizing the dehulling process can enhance the efficiency of comprehensive raw material processing. The proposed technological approaches are environmentally friendly, economically efficient, and well adapted for industrial application. These results can serve as a basis for implementing innovative solutions in the field of vegetable oil production and for increasing the competitiveness of domestic products.

The article presents the results of a comparative assessment of the physicochemical and rheological properties of first-grade bread wheat flour produced by different manufacturers in the southern region of Kazakhstan. The relevance of the study is обусловлена the significant role of the flour-milling and baking industries in the agro-industrial complex of the Republic of Kazakhstan, as well as the need to ensure stable flour quality and improve the efficiency of bread production. Flour samples of the “Pioner,” “Ordabasy-Nan,” “Tsesna,” and “Kemel” brands, widely represented in the regional market, were selected as research objects. The study was carried out using standard methods for determining moisture content, falling number, quantity and quality of wet gluten, and gluten deformation index. The rheological properties of dough were evaluated using the alveograph method with determination of flour strength, dough elasticity, extensibility, and water absorption capacity. The results showed that the “Ordabasy-Nan” flour sample demonstrated the best technological characteristics, including high wet gluten content (36%), maximum flour strength (W = 492 J/10⁻⁴), balanced elasticity and extensibility parameters, and high water absorption capacity. The obtained results indicate the high technological suitability of the studied flour sample for the production of pan bread and medium-thickness flatbread products. The practical significance of the study lies in the possibility of using the obtained data to select flour with optimal baking properties and improve the stability of finished product quality.

This study presents the development of a functional yogurt technology enriched with plant-based dietary fiber - psyllium (Plantago ovata husk). The effect of psyllium addition at concentrations of 0.3-1.0% on the physicochemical, rheological, and sensory properties of the product was investigated. The results demonstrated that psyllium incorporation does not inhibit the growth of lactic acid bacteria and does not interfere with the fermentation process. The addition of plant fiber promoted the formation of a stable protein-polysaccharide matrix, increased viscosity up to 1120 mPa·s, and reduced syneresis to 1.9% compared to the control sample.

The optimal concentration was determined to be 0.5%, providing a balanced combination of texture and sensory characteristics while preserving the traditional taste and aroma of yogurt. The use of psyllium allows for the replacement of synthetic stabilizers and aligns with the “clean label” concept.

The developed product is characterized by enhanced nutritional value due to its content of soluble dietary fiber, exhibits prebiotic properties, and can be recommended for functional, preventive, and dietary nutrition. The novelty of the technology is confirmed by a filed patent application in the Republic of Kazakhstan.

The aim of this review is to analyse the mechanisms of plant extract action on milk coagulation and to evaluate their applicability in mixtures of cow and camel milk. The review includes publications devoted to the milk-clotting activity of plant proteases, the influence of polyphenolic compounds on casein micelle aggregation, and the role of technological parameters in the coagulation process.

The analysis shows that plant extracts can act through two main mechanisms. The first mechanism is associated with proteolytic hydrolysis of κ-casein and the initiation of micelle aggregation. The second mechanism is related to interactions of polyphenols and pectic substances with proteins, which modifies interparticle interactions and the water-holding capacity of the gel. The efficiency of extracts depends on their composition, concentration, pH of the medium, temperature, and calcium content.

However, plant proteases often have lower selectivity compared to chymosin. This may lead to excessive proteolysis and weakening of the curd structure. In mixtures of cow and camel milk, additional factors are related to differences in protein composition and colloidal stability of the milk systems.

The review confirms the potential of plant-based modifiers of milk coagulation. At the same time, it highlights the need for careful optimization of technological conditions and a mechanistic approach to their application. For practical implementation, further studies are required to evaluate gel microstructure, protein retention, and the balance between milk-clotting and proteolytic activities.

An analysis was conducted of the organoleptic, physicochemical, and microbiological parameters of the finished product to determine the effect of rosehip leaf extract on the quality parameters of whole-grain bread and its shelf life.

Rosehip leaf extract was used as a plant raw material. The effective amount of rosehip leaf extract has been established. Rosehip leaf extract contains biologically active substances belonging to different classes of compounds: flavonoids, tannins, glycosides, alkaloids, organic acids, which increase the microbiological safety of grain and products. Whole grain bread was stored at room temperature (t= 20 ÷ 25 0C) at a high humidity of 40-50%.

The number of mesophilic aerobic and facultatively anaerobic microorganisms was not detected after 96 hours in the bread sample containing 4% rosehip leaf extract. In the control sample, an increase in the number of mesophilic aerobic and facultatively anaerobic microorganisms was observed after 24 hours of storage. On the second day, mold growth appeared in the control sample, whereas no mold was detected in the bread sample supplemented with 4% rosehip leaf extract. The results of the study demonstrated that rosehip leaf extract improves the microbiological safety and stability of the product by inhibiting the growth of microorganisms and mold. The results obtained indicate that rosehip leaf extract increases the nutritional value of the finished product and extends its shelf life. Thus, bakery products with rosehip leaf extract can be stored for 72 to 96 hours.

Genome stability is fundamental to cell viability, the evolutionary stability of organisms, and the preservation of their functional integrity. Endogenous damage, particularly the oxidative modification of nitrogenous bases resulting from cellular metabolism, is one of the main factors disrupting DNA structure. To prevent the accumulation of mutations, cells utilize a base excision repair (BER) system in which DNA glycosylases play a pivotal role. These enzymes recognize and remove damaged or mismatched bases, thereby initiating a cascade of repair reactions.

Adenine DNA glycosylases belonging to the MutY/MUTYH family are unique in that they do not directly remove damaged bases, but rather correct replication errors arising from oxidative damage to guanine. In bacteria, this function is performed by the MutY enzyme, whereas in eukaryotes it is performed by its homologue, MUTYH. These enzymes prevent G:C → T:A transition mutations from becoming fixed, thereby significantly reducing the level of spontaneous mutagenesis.

This review discusses the role of DNA glycosylases in maintaining genomic stability, focusing on the molecular mechanisms of adenine DNA glycosylase function, their place in the BER system, evolutionary conservation, and their significance in biotechnology, molecular genetics, and applied research.

The study aimed to evaluate the microbiological safety, quality, and organoleptic properties of broiler chicken meat when grape seed meal was included in the diet. The research was conducted on two groups of broilers: a control group fed a standard balanced diet, and an experimental group whose diet was supplemented with grape seed meal as a source of natural polyphenolic compounds and antioxidants. Microbiological analysis of whole carcasses and livers, collected on the day of slaughter after cooling, showed lower microbial counts in the experimental group. The total count of mesophilic aerobic and facultative anaerobic microorganisms in whole carcasses was less than 4×10¹ CFU/g compared to 1.1×10² CFU/g in the control, while in livers, TAMC was 1.1×10³ CFU/g versus 2.1×10⁴ CFU/g, well below established limits. Listeria monocytogenes and pathogenic microorganisms, including Salmonella spp., were not detected in either group. Analysis of toxic elements (lead, arsenic, cadmium, and mercury) revealed values below detection limits, confirming the toxicological safety of the meat. Shelf-life evaluation demonstrated that meat from the experimental group remained acceptable 2 days longer than control meat, with delayed changes in odor and spoilage. Organoleptic assessment of boiled breast and thigh fillets showed slightly higher scores in the experimental group, particularly for aroma, juiciness, tenderness, and overall quality (breast fillets: 9.1 vs. 8.9, thigh fillets: 9.4 vs. 9.2). The results indicate that the inclusion of grape seed meal in broiler diets improves microbiological safety, extends shelf life, and enhances sensory quality without negatively affecting organoleptic characteristics. These findings support the use of grape seed meal as a functional feed additive in poultry production, including products intended for children.

The rational use of mixed dairy raw materials is a promising direction in soft cheese technology, as it allows to increase the cheese suitability and improve the quality of the finished product. The study investigated the effect of the ratio of cow's, goat's and camel's milk on the coagulation processes and the quality of soft cheese. The temperature regimes of coagulation, duration of coagulation, organoleptic, physic-chemical and textural parameters of the product were studied.

It has been established that optimal coagulation conditions for combined dairy raw materials are achieved at a temperature of 40 ° C and a duration of 40 minutes. The best results were shown by a sample with a ratio of 60% cow's milk, 20% goat's milk and 20% camel's milk, which provided an increase in the yield of cheese mass by 3.3% compared with the control, stable coagulation and formation of a homogeneous structure of the product and a decrease in titrated acidity to 106 °T versus 116°T in the control sample from cow's milk.

The increased cheese yield and coagulation stability in 1-sample are due to the balanced ratio of proteins and fats in the combined dairy raw materials.

The results obtained confirm the prospects of using combined dairy raw materials in soft cheese technology and can be used in the development of products with improved organoleptic and structural-mechanical properties.

The article presents the results of a study on the physicochemical parameters, antioxidant activity, and rheological properties of plant-based raw materials and the dessert product “kiyoma” developed on their basis. Saffron, turmeric, and ginger were used as the objects of the study, as well as kiyoma samples formulated using various recipe solutions.

The aim of this study is to substantiate the feasibility of using plant ingredients with high antioxidant activity in the development of a functional fruit-vegetable-berry dessert “kiyoma”, as well as to assess their influence on the structural and mechanical characteristics of the finished product. The expansion of the range of natural desserts based on fruits, vegetables, and spice-aromatic raw materials contributes to the formation of rational nutrition by replacing traditional sugar-containing confectionery products with foods of increased nutritional and biological value.

During the experimental studies, moisture content, ash content, pH value, content of biologically active compounds, and antioxidant activity of the plant raw materials were determined. It was established that saffron is characterized by the highest antioxidant activity due to its high content of crocin and flavonoids, while turmeric and ginger complement the composition through the presence of curcumin.

The rheological properties of kiyoma were evaluated by viscosity, torque, flowability, stickiness, and adhesion parameters. It was shown that the studied samples belong to viscoplastic systems with a pseudoplastic flow behavior, and that formulation differences significantly affect the formation of their structural and mechanical properties. The obtained results confirm the prospects of the developed «kiyoma» dessert as a functional food product.

The article addresses a topical issue in food biotechnology, namely the improvement of freeze-dried mare’s milk production technology and the development of a fermented milk beverage with an extended shelf life based on this product. The relevance of the study is determined by the high nutritional and biological value of mare’s milk, which contains highly digestible protein fractions, biologically active compounds, and polyunsaturated fatty acids. At the same time, the elevated content of unsaturated lipids makes milk fat susceptible to oxidative processes during storage, thereby necessitating the application of technological approaches aimed at product stabilization.

The study specifies the technological stages of freeze-dried mare’s milk production, including preliminary pasteurization, cooling, deep freezing, primary drying under vacuum, and final drying until a residual moisture content of no more than 5% is achieved. A comparative analysis of safety parameters, chemical composition, and nutritional value of native and freeze-dried mare’s milk was performed. To enhance the oxidative stability of the lipid fraction, the incorporation of natural antioxidants – dihydroquercetin, αtocopherol, and γ-tocopherol – was investigated at technologically justified concentrations relative to the mass of the milk fat fraction. The results indicate that the use of dihydroquercetin and γ-tocopherol slows the accumulation of lipid peroxidation products during storage of dried mare’s milk. The most pronounced stabilizing effect was observed when these antioxidants were applied at a concentration of 2.0% of the fat fraction mass, as evidenced by lower peroxide values compared with the control sample. Based on native and reconstituted freeze-dried mare’s milk, a fermented milk beverage enriched with vitamins A and E and dihydroquercetin was developed. The use of the antioxidant complex makes it possible to extend the beverage shelf life to 25 days while preserving its organoleptic properties and nutritional value. The findings are of practical significance for the development of specialized dairy products based on traditional domestic raw materials and may be used in the creation of functional food products with enhanced resistance to oxidative deterioration.

In this review article, modern approaches to improving the performance characteristics of coatings produced by electric arc spraying are analyzed. Particular attention is given to studies in the field of directed energy deposition using an electric arc (DED-Arc), including the selection of spraying parameters, substrate surface preparation, and the application of new types of wires and composite materials. Advances in feedstock design for corrosion-resistant, heat-resistant, and wear-resistant protection are reviewed, including Zn, Al-Mg, and Zn-Al-Mg systems, Al-Cu cored wires for antifouling applications, stainless steel and NiCrMoAl alloys, cermets, and WC-reinforced high-entropy alloys. The review also summarizes recent results on adhesion enhancement through laser surface texturing and on adapting electric arc spraying technology for non-conductive substrates. Particular attention is given to the relationships between processing parameters, coating microstructure, and functional properties. The analysis highlights key factors controlling coating performance and identifies current research challenges in arc-sprayed coating systems. The summarized results demonstrate that electric arc spraying is a flexible and cost-effective technology for producing functional coatings with tailored properties for a wide range of industrial applications.

The article discusses the development and application of induction heating systems in various industries, including agricultural machinery manufacturing, the automotive industry, and metal processing. A comparative analysis of induction installations and conventional heating methods is presented, highlighting their advantages such as high heating rates and efficiency, improved process control, and reduced energy consumption. The mathematical model of the frequency converter for induction heating systems is based on a system of discrete equations describing the dynamics of multidimensional variables. Unlike existing approaches, the proposed model takes into account the optimal operating frequency range, reduces the number of power transistors, and considers the installed power, thereby maintaining high energy efficiency. Within the scope of the study, a prototype frequency converter operating in the 2-20 kHz range with single-phase and three-phase power supply, as well as a 6 kW inductor, were designed and manufactured. Experimental studies confirmed the adequacy of the proposed model and its applicability under real technological conditions. The practical significance of the work lies in the possibility of using the developed model and prototype to select optimal induction heating technologies for mechanical engineering and agricultural machinery, ensuring increased reliability, reduced energy consumption, and lower operational costs. The results demonstrated the sufficiency of the proposed model and confirmed its practical applicability. onic components, which may affect both the converter operation and the power supply network. It was shown that variations in converter parameters have a significant impact on the selection of optimal induction heating modes, which is of practical importance for both educational purposes and industrial implementation.

Thermal stability, tribological and electrochemical properties of TiSiCN coatings obtained by reactive plasma sputtering of mechanically activated powder mixtures of TiCN-SiC-Si system are investigated. The effect of arc current strength (400-600 A) on the test results and characteristics of the formed layer is shown. X-ray phase analysis and cross-section analysis by scanning electron microscopy confirm the formation of the coating of the Ti-Si-C-N system and make it possible to assess its thickness and microstructural features. Thermogravimetric analysis conducted in an N ₂ atmosphere was used to compare the thermal stability of coatings when heated to 950 °C. According to the data of tribological tests, the dependence of the friction coefficient on the spraying mode was established and a tendency to its stabilization was noted at increased current values. Electrochemical studies in a 3.5% NaCl solution showed improved corrosion characteristics of the coatings compared to the substrate. The results obtained characterize TiSiCN coatings as promising protective layers for use in friction, heating and corrosive environments.

In this study, bioactive hydroxyapatite coatings were deposited on commercially pure Grade 2 titanium substrates by detonation spraying at different O₂/C₂H₂ ratios in the range of 2.6-3.7. X-ray diffraction analysis confirmed the predominance of the hydroxyapatite phase with partial formation of α-tricalcium phosphate, which is attributed to high temperatures and intense dynamic processes in the detonation jet. The formed coatings exhibit pronounced hydrophobicity, high structural heterogeneity, and a well-developed surface microrelief, promoting improved interaction with bone tissue and accelerated osseointegration. Tribological tests conducted under dry conditions and in Ringer’s solution demonstrated a significant increase in wear resistance compared to uncoated Grade 2 titanium. The best friction characteristics and the lowest wear volume were observed for coatings deposited at O₂/C₂H₂ ratios of 3.0 and 3.3, which is associated with an optimal combination of crystallinity, phase composition, and adhesion strength. Coatings formed under these conditions provide stable tribological behavior in physiological environments. The obtained results confirm the prospects of detonation-sprayed hydroxyapatite for improving the durability, biocompatibility, and operational reliability of titanium implants.

This study examines the thermophysical properties of corn grain and corn cobs at various moisture content levels. The aim of the research was to determine the specific heat capacity, thermal conductivity, and thermal diffusivity for the analysis of thermal treatment and drying processes of corn. In addition, thermophysical characteristics, including the density of corn grain and cobs, were determined, and the dependence of these parameters on moisture content was established. The obtained relationships allow for a more accurate description of heat and moisture transfer processes during the drying and storage of corn. To determine the thermophysical properties of corn cobs, the ITP MG4-100 device was used, which provides measurement of the main thermophysical parameters with the required accuracy. A spherical bicalorimeter was also employed to determine the thermophysical properties of corn grain and to calculate the main thermal characteristics of the material. Measurement of temperature parameters on the surface of corn cobs was carried out using a Fluke infrared thermometer, which enabled temperature monitoring during the experiment. Drying of the samples was performed in the «ShS-40 SPU» drying unit within specified temperature and humidity ranges. During the study, the thermophysical properties of corn grain and cobs at different moisture contents were determined. Moisture transfer processes were also investigated; as a result of drying, the moisture content of the product decreased from 72% to 60%. Analysis of the experimental data and the obtained relationships contributes to the development of thermal treatment and drying methods aimed at improving the efficiency of corn drying.

The article presents the results of an investigation of the corn drying process using an experimental drying unit based on an air-type solar collector. Thermotechnical experiments were conducted, including measurements of air flow velocity and monitoring of changes in corn moisture content during the drying process. In addition, the structural and operational characteristics of the solar heliocollector were analyzed, and solar radiation indicators in the experimental area were studied, which made it possible to assess the level of available solar energy and its influence on air heating efficiency. The study allowed the thermal power of the air collector to be determined, the temperature distribution along its length to be evaluated, and optimal operating parameters of the system to be established. It was found that the use of solar heating provides a significant reduction in energy consumption for corn drying, increases the energy efficiency of the process, and promotes the sustainable use of renewable energy sources. Furthermore, experimental results were compared with theoretical calculations, enabling refinement of heat and moisture transfer kinetics within the corn layer. The obtained results can be applied in the design and improvement of solar drying systems for agricultural products and in substantiating rational drying regimes under conditions of variable solar radiation and natural ventilation.

The article presents a methodological approach to the development of a digital quality management loop at a nuclear industry enterprise based on KPI standardization, management of corrective and preventive actions (CAPA), and the use of artificial intelligence analytical tools. The study is based on data for 2020-2024, including occupational health and industrial safety indicators, LTIFR, dose monitoring of Group A personnel, environmental indicators, as well as a scenario-based economic assessment of the implementation of the digital quality loop.

It is shown that safety, radiation and environmental monitoring indicators can be considered practical metrics of the stability of the quality management system. During the analyzed period, the number of accidents decreased from 1-2 cases in 2020-2021 to zero values in 2022-2024, while the LTIFR indicator decreased from 0.28 to 0.00. Radiation indicators remained below the control level of 10 mSv/year; however, maximum doses of up to 5.2 mSv confirm the need to manage local episodes rather than relying only on average values. Environmental KPIs demonstrate year-to-year volatility, which justifies the need for threshold control and analysis of the causes of deviations.

The paper proposes the logic of the digital loop «KPI – thresholds – deviation – CAPA – effectiveness verification – audit», in which artificial intelligence is used as an additional tool for anomaly detection, prioritization of reviews, and classification of causes. The economic assessment shows that with CAPEX of 30 million tenge and OPEX of 6 million tenge per year, the estimated payback period is approximately 1.67 years, and about 2.5 years in the conservative scenario. The obtained results confirm the feasibility of a phased implementation of the digital quality loop: from data and CAPA standardization to analytics and predictive models.

This article presents a clinical decision support system for diagnosing acid–base balance disorders based on arterial blood gas (ABG) analysis using the Henderson–Hasselbalch equation. Considering the increasing requirements for accuracy and rapid clinical diagnostics, algorithm-based interpretation of ABG parameters has become highly relevant. The study aims to systematize the key blood gas indicators (рН, 𝑃𝑎𝐶𝑂2 , 𝐻𝐶𝑂3 − , BE) and analyze their physiological relationships, as well as to develop a logical and mathematical model for automated classification of acid–base disorders. The proposed algorithm enables the identification of metabolic, respiratory, and mixed disturbances, taking compensatory mechanisms into account. The results demonstrate that the implementation of a computerized decision support model enhances diagnostic objectivity, reduces interpretation errors, and improves the quality of clinical decision-making.

This study examines how electrolytic plasma treatment can improve the wear resistance of 30CrMnSi bucket teeth used in loaders operating under severe abrasive conditions. Samples were subjected to various processing methods, including electrolytic plasma hardening, nitriding, carburizing, nitrocarburizing hardening, and quenching. Multiple analytical techniques, including scanning electron microscopy energy dispersive spectroscopy, X-ray diffraction, and microhardness testing, were used to comprehensively characterize the structure, phases, and mechanical properties of the samples. The tribological properties of the materials were evaluated using a TRB3 tribometer, and abrasive wear testing was conducted according to GOST 23.208–79. The results show that electrolytic plasma treatment results in the formation of diffusion layers with a thickness of 15 to 25 μm. This process is accompanied by the formation of carbide, nitride, and carbonitride phases (Fe₄C, Fe₇C₃, Fe₄N, Fe₂N, and Fe₃(CN)). This process significantly increases surface hardness (up to 810 HV) and improves wear resistance. The study also showed that electrolytic plasma nitriding provides an optimal balance between hardness and toughness, resulting in low friction and increased resistance to abrasive wear. The development of this technology can extend the service life of earthmoving and mining equipment components, reducing maintenance costs and downtime.

This study analyzes the effect of HVOF-sprayed Cr₃C₂-NiCr coatings on the thermophysical characteristics of superheater tubes of the BKZ-320-140 boiler unit. The influence of the protective coating on heat transfer processes, including convective and radiative heat exchange, as well as on the temperature state of the tube material under high-temperature flue gas conditions, is investigated. The temperature field was calculated using the finite element method in the ELCUT 6.6 software under transient heat transfer conditions. The model incorporates real operating parameters, including steam pressure and temperature, flow velocities, and thermophysical properties of materials. The results show that the presence of the coating leads to a slight increase in the total thermal resistance of the “tube wall–coating” system. However, its effect on the temperature regime and heat flux density is negligible. It is demonstrated that Cr₃C₂-NiCr coatings improve the corrosion and erosion resistance of heating surfaces without significantly reducing the thermal efficiency of the boiler unit under real operating conditions. The obtained results can be applied in design, modernization and optimization of power equipment in industrial energy systems of Kazakhstan.

This study investigates the effect of plasma hardening under different processing conditions on the microstructure and tribological properties of bearing steel ShKh15. It is shown that plasma treatment, based on localized high-speed heating followed by self-quenching, enables the formation of a hardened surface layer without the use of liquid cooling media. Experimental studies were carried out by varying the plasma arc current (120-140 A) and the flow rate of the plasma-forming gas (0.2-0.25 L/min).The results demonstrate that plasma hardening leads to the formation of a gradient microstructure consisting of martensite, retained austenite, and pearlite, with a smooth transition to the initial pearlitic structure. The maximum microhardness of the hardened layer reaches up to 700 HV with a depth of up to 250 μm. Tribological tests using a ball-on-disk configuration showed that after plasma treatment, the coefficient of friction increases, while the wear rate decreases by 3-3.5 times compared to the initial state. The obtained results indicate a significant improvement in the wear resistance of ShKh15 steel and confirm the effectiveness of plasma hardening as a surface strengthening method.

Waterborne paint and coating composites are finding increasingly broad application in construction, industry, and everyday use. This shift is largely motivated by environmental goals – lowering organic solvent emissions – and by cost advantages, since water is both less expensive and more widely available than organic solvents.At the same time, the key task remains to increase the barrier and mechanical characteristics of water-based coatings while maintaining the processability of application and rapid curing.Two main approaches are employed to modify water-dispersible systems: chemical modification of polymer binders and polymer blending. It has been shown that targeted tailoring of the polyurethane soft/hard segment structure, as well as the incorporation of an acrylate component and functional additives (plasticizers, nanofillers), enables control over the degree of crosslinking and phase distribution, thereby improving coating adhesion, abrasion resistance, and barrier properties. Among modified waterborne systems, polyurethane and acrylic-polyurethane coatings are of particular interest, as discussed in this article, owing to their unique combination of properties. These systems provide high coating durability and a wide range of applications, including protective and decorative coatings for various substrates. Special attention is given to methods for their modification. The promise of polyurethane and acrylic-polyurethane waterborne coatings for anticorrosion protection is highlighted, along with the need to tailor formulations to specific service conditions.

The article presents the results of a study focused on the isolation and structural identification of the triterpenoid compound friedelan-3-one from the wild-growing plant Rumex rechingerianus Losinsk.

The object of the study was the aboveground part of the plant, collected during the growing season in the foothills of the Trans-Ili Alatau (Almaty region, Kazakhstan) in October 2022. The botanical identification was carried out jointly with a specialist from the RSE "Institute of Botany and Phytointroduction" of the National Research University of the Ministry of Education and Science of the Republic of Kazakhstan. The relevance of the work is due to the insufficient knowledge of the chemical composition of this endemic species and the need to expand information on triterpenoid compounds of natural origin, which are of interest to phytochemistry and pharmacognosy.

Extraction of biologically active substances was carried out by maceration using 70% ethanol. The obtained extract was concentrated under reduced pressure and subjected to fractionation by vacuum liquid chromatography using a gradient system of dichloromethane-methanol.

Further separation of the target fractions was performed by column chromatography on silica gel, while the purity of the isolated compounds was monitored by thin-layer chromatography.

Structural identification of the isolated compound was carried out using NMR spectroscopy (¹H, ¹³C, DEPT) and gas chromatography-mass spectrometry. Analysis of the combined spectral data confirmed that the isolated compound belongs to the triterpenoid class and allowed its unambiguous identification as friedelan-3-one. The obtained results supplement existing data on the chemical composition of Rumex rechingerianus Losinsk and provide a basis for further phytochemical and pharmacological studies of this species.

The problem of utilization and storage of phosphogypsum generated during the production of wetprocess phosphoric acid (WPA) is extremely relevant due to environmental issues associated with the pollution of water bodies, land, and the atmosphere. The large-scale accumulation of phosphogypsum requires the development of effective methods for its processing. A key requirement for the chemical processing of phosphogypsum is its particle-size distribution, primarily the size and shape of crystals. This study investigates the influence of the WPA production mode and the liquid-to-solid ratio (L:S) on the chemical composition, crystal size and habit, and filtration properties of phosphogypsum. Phosphogypsum was produced by dihydrate and hemihydrate methods at L:S ratios of 2.5:1 and 3:1 under laboratory conditions and under industrial process conditions at the Taraz branch «Mineral Fertilizers» of Kazphosphate. The composition and morphology of the samples were examined using X-ray fluorescence and X-ray diffraction methods, as well as electron microscopy. X-ray diffraction analysis identified the presence of finely dispersed anhydrite, which reduces the filterability of phosphogypsum precipitate obtained under industrial conditions at temperatures of 90-95°C. It was established that extraction in the dihydrate mode at L:S ratio of 3:1 promotes to formation of larger, uniform-size, isometric crystals of gypsum and ensures the maximum filtration productivity. The research results can be used to optimize WPA production.

Against the backdrop of rapid industrial growth, water pollution has become a pressing global environmental issue. This review provides a systematic analysis of the efficiency of functionalized nanocellulose- based adsorbents for the removal of organic (synthetic dyes, phenols, antibiotics, pesticides) and inorganic (Pb²⁺, Cd²⁺, Hg²⁺, Cr(VI), Cu²⁺, As) pollutants from water. Key findings: the highest sorption capacities are achieved by TEMPO- oxidized nanocellulose and amine-functionalized composites – up to 2500 mg/g for methylene blue and up to 2270 mg/g for lead ions. Nanocellulose- based molecularly imprinted polymers (MIPs) selectively adsorb phenols with efficiencies of up to 97% even in the presence of structurally similar competitors. Most adsorbents reviewed retain 80+90% of their capacity after 20 regeneration cycles. The paper examines three main types of nanocellulose (CNC, NFC, BNC), their preparation methods (acid hydrolysis, TEMPO-oxidation, mechanical and enzymatic treatment), and surface functionalization strategies (isocyanate-based, amine- and thiol-functionalization). The alignment of nanocellulose production from agricultural waste (rice husks, soybean hulls) with sustainable development principles is emphasized. Key unresolved challenges – scale-up, stability in real wastewater matrices, and cost-effectiveness – and future research directions are also identified.

Currently, the recycling of ash-slag waste generated by thermal power plants and the efficient recovery of valuable metals such as aluminum from these materials represent one of the most important environmental and economic challenges. Traditional aluminum extraction methods, including acid and alkaline leaching, high-temperature thermal treatment, pyrometallurgical processes, and organic extraction techniques, are characterized by high energy consumption, significant environmental impact, and low economic efficiency.

This review provides a comprehensive analysis of modern methods for extracting aluminum from industrial ash-slag waste, comparing their efficiency, energy consumption, and technological limitations. Special attention is given to microwave-assisted leaching technology using amorphous graphite, and its advantages over conventional methods are systematically evaluated.

The results of the literature review indicate that microwave-assisted leaching is a promising approach due to its energy efficiency, accelerated reaction kinetics, increased aluminum dissolution rate, and reduced environmental burden. Furthermore, this review highlights the scientific advantages of the proposed technology and identifies key areas for further development, including optimization of microwave penetration depth, power input, and temperature regimes.

Thus, this review systematizes the scientific basis for the application of microwave technologies in the processing of ash–slag waste and contributes to the development of new, environmentally friendly methods for the efficient recovery of aluminum from waste materials.

The investigation of the influence of UV irradiation on polymers represents an important and relevant area of science and technology, as it enables the development of new approaches for designing more durable and efficient materials. This work examines the changes occurring in polymers based on unsaturated polyesters under prolonged exposure to ultraviolet radiation. The objective of the study was to evaluate the effect of long-term UV irradiation on the thermal stability of polymeric materials based on polyethylene glycol maleate and polypropylene glycol maleate copolymerized with acrylic acid at a component ratio of approximately 70:30 wt.%. The samples were examined using microscopy to identify microcracks formed as a result of UV exposure. In addition, visual assessment of color variation and the appearance of turbidity in the studied materials was performed. Additionally, the carbonyl index was determined to quantitatively evaluate the degree of photooxidative degradation of the polymers. This parameter characterizes the accumulation of carbonyl groups formed as a result of polymer chain scission under UV irradiation and allows estimation of the extent of photodegradation processes in the materials. The obtained results demonstrate that the polymer synthesized on the basis of polyethylene glycol maleate exhibited a more pronounced decrease in the onset temperature of thermal deformation after UV exposure compared with the copolymer based on polypropylene glycol maleate, indicating higher resistance of the latter to UV-induced degradation. The thermal stability of the copolymers was evaluated by thermogravimetric analysis through determination of the onset temperature of thermal deformation before and after 21 days of UV irradiation.

The results of the conversion of n-butane on supported palladium catalysts in a stationary mode in the temperature range of 400-600 °C, at atmospheric pressure and a volumetric feed rate of n-butane of 250 h– ¹ are presented. The catalysts were obtained by the method of incipient wetness impregnation using γ-Al₂O₃ and SiO₂ (silica gel) as supports, the palladium loading was 1 and 3%. It was found that, along with the dehydrogenation of n-butane, cracking processes occur in parallel, leading to the formation of both olefins (ethylene, propylene) and alkanes (methane, ethane, propane), isomerization of n-butane to isobutane, and other reactions. Hydrogen contained in contact gases is equivalent to the amount of dehydrogenation and degradation products. In trace amounts, non-condensed liquid products such as pentane and aromatics are present in the gas phase. The catalysts were studied by SEM-EDS to determine the morphology of catalysts and the elemental composition of individual sections of their surface, and the specific surface area of the catalysts was also determined.

The study considers technogenic waste from the mining and metallurgical complex of the Republic of Kazakhstan as a promising secondary source of non-ferrous and rare metals. The object of investigation was copper ore tailings from the Balkhash Concentration Plant, characterized by a silicate matrix (Si ≈ 36%) and the presence of residual amounts of Cu (≈0.32%) and Zn (≈0.77%). A comprehensive analysis of their chemical, granulometric, and physicochemical composition was carried out using the ICP-OES method. The processes of raw material preparation, including crushing, grinding, and classification, were studied, and the grinding conditions were optimized. It was shown that reducing the particle size to < 40 µm is a critical factor for enhancing leaching efficiency. An integrated processing technology combining microfluidic separation and bioleaching is proposed. It was established that microfluidic separation provides selective concentration of copper up to 0.52-0.58% in the target fraction with a recovery of 70-75%. Bioleaching under optimal conditions (pH 1.8-1.9; T ≈ 31-32 °C) ensures copper recovery up to 60-63% and zinc recovery up to 55-58%. The obtained results confirm the potential of bioleaching for the integrated processing of technogenic waste and the reduction of its environmental impact.

The study examines modern approaches to oil regeneration, including physical, chemical, and sorption methods, and substantiates the choice of adsorption purification as an environmentally safe and technologically simple alternative. An effective method for the purification and utilization of used motor oils using natural and modified bentonite sorbents has been developed. The research objects included used KIXX 10W-40 motor oil, P1T1A and «13 Horizon» bentonites, as well as their modified forms obtained through acid and peroxide activation methods. Experimental studies were carried out using a vacuum oil purification unit and sorption filtration techniques. The purification efficiency was evaluated using FTIR spectroscopy, thermogravimetric analysis (TGA), and ICP-MS methods. The results demonstrated a significant reduction in water content, oxidation products, sulfur-containing compounds, and metal impurities. The highest efficiency was achieved with modified P1T1A bentonite, ensuring maximum contaminant removal. It was established that modification increases specific surface area and sorption capacity, enhancing adsorption processes. The proposed method is simple, cost-effective, scalable, and does not generate secondary toxic waste, making it suitable for industrial application while reducing environmental impact.

Spent coffee grounds (SCGs), an abundant lignocellulosic agro-industrial residue, were valorized into porous carbonaceous adsorbents through hydrothermal carbonization (HTC) followed by alkaline activation, aiming at the efficient removal of methylene blue (MB) from aqueous solutions. HTC was conducted under subcritical water conditions at temperatures of 180-220 °C and residence times of 2-6 h, producing hydrochars with tunable physicochemical properties. The obtained hydrochars were subsequently activated using potassium hydroxide in a microwave reactor to enhance surface functionality and porosity. The structural, textural, and chemical characteristics of the materials were comprehensively analyzed by N₂ physisorption (BET surface area and pore size distribution), FTIR spectroscopy, SEM, XRD/Raman spectroscopy, and elemental analysis (XRF/EDX).

Batch adsorption experiments were performed to evaluate the adsorption kinetics, equilibrium isotherms, and thermodynamic behavior toward methylene blue. The activated coffee-ground-derived carbons exhibited rapid adsorption kinetics and significantly enhanced adsorption capacities compared to non-activated hydrochars. The improved performance was attributed to the synergistic effects of developed micro- and mesoporous structures and abundant oxygen-containing surface functional groups. Mechanistic analysis indicated that methylene blue uptake was governed by a combination of pore filling, electrostatic attraction, π– π electron donor–acceptor interactions between the aromatic carbon surface and dye molecules, hydrogen bonding, and intraparticle diffusion.

The results demonstrate that hydrothermal carbonization coupled with mild alkaline activation provides an effective and sustainable route for converting spent coffee grounds into high-performance adsorbents. This study elucidates the relationships between synthesis conditions, surface chemistry, textural properties, and adsorption performance, highlighting the potential of SCG-derived activated carbon for practical wastewater treatment applications.

Heavy metal contamination of water resources has become one of the most pressing problems of our time, and therefore it is necessary to invent new and effective materials for the removal of heavy metals from water. Although scientists consider two-dimensional transition metal carbides and nitrides (MXenes) as good adsorbents, natural structural defects are often found in the initial samples of these materials. The main obstacles to unlocking the full potential of the material are the close stacking of nanosheets and the lack of active centers on the surface. In this article, we will explain the role and mechanism of vacancy engineering in the removal of heavy metals by metal (VM), carbon/nitrogen (VX), and surface terminal vacancies (VTx). By specifically modifying the bonding and electronic structure of atoms, we can make vacancy defects not only reduce the adhesion of layers, but also act as active thermodynamic traps. Artificial atomic defects lead to the redistribution of electrons in a single location, and this phenomenon significantly reduces the Gibbs energy of binding to heavy metals. Such artificial defects activate the material, increasing its adsorption capacity several times (e.g., >400 mg/g for Pb²⁺) and lead to the spontaneous reduction of heavy metals such as Cr⁶⁺ in water. In this article, we discuss in detail new synthesis technologies that precisely introduce structural defects. Finally, we propose a strategic direction for the development of a new generation of MXene materials for pure water filters, while addressing the issues of industrial large-scale production and long-term storage.

The buildup of plastic microparticles in water is a serious problem that requires new, faster ways to break them down. Polystyrene is one of the toughest pollutants to destroy. Because of its large phenyl groups, microbes can hardly break it down, making the material very stable. In this study, we looked at how to decompose polystyrene particles in water using the Fenton process (FeSO4 * 7H2O/H2O2). We ran the experiments at a stable temperature of 35-40°C and a pH level of 2-3. Keeping the pH in this narrow range is vital; it keeps the iron active and stops it from settling out as a solid. Under these conditions, the system starts producing hydroxyl radicals (•OH). These radicals are powerful oxidizers that pull hydrogen atoms from the polymer frame, which breaks the carbon-carbon bonds and cuts the size of the molecules. To see how the surface changed before and after the reaction, we used optical and scanning electron microscopy (SEM). The images clearly show the plastic wearing away, with deep cracks, chips, and small pits (cavities) appearing. We also checked the particle sizes using dynamic light scattering (DLS). The data confirmed that the particles became significantly smaller after the treatment.Our results prove that the Fenton reaction effectively starts the breakdown of strong aromatic polymers. Therefore, this method is a promising step for industrial wastewater treatment systems.

This research paper presents a comprehensive study of the magnesiothermic reduction (MTR) process of amorphous silica derived from rice husks of the Kyzylorda region, aimed at synthesizing high-purity nanoporous silicon. Silica was extracted via alkaline leaching followed by precipitation, yielding a precursor with a highly developed specific surface area. During the experimental study conducted at temperatures of 650–700 °C in an inert argon atmosphere, the thermodynamic patterns of the process were analyzed. Special attention was paid to the role of sodium chloride (NaCl) as a heat-absorbing agent, which prevents structural sintering by controlling the exothermic reaction effect. For the efficient removal of by-products such as magnesium oxide (MgO) and residual SiO2, a multi-stage hydrometallurgical purification in the HCl–H₂O–EtOH system was utilized. The phase composition and morphological features of the synthesized samples were characterized in detail using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results confirmed the formation of polycrystalline silicon with a unique hierarchical porous morphology, entirely inherited from the biogenic precursor structure. The proposed methodology demonstrates high efficiency and environmental significance in utilizing renewable agro-industrial waste for the production of advanced nanomaterials.