This paper presents an automated method for the classification of hemodynamically significant arrhythmias (HSA) based solely on electrocardiographic (ECG) features, without the use of additional imaging diagnostic techniques. The proposed approach relies on key ECG parameters, including QRS complex duration, RR intervals, and heart rate (HR). The study is based on data from the open-access MIT-BIH Arrhythmia Database, which contains multiple types of cardiac rhythm disturbances. A comparative analysis of arrhythmia classes was conducted, leading to the identification of diagnostically significant predictors associated with hemodynamic instability. Logical decision rules and a decision tree model were developed to enable automatic recognition of HSA and clinical risk stratification. The proposed algorithm demonstrates high interpretability and practical applicability for real-time monitoring systems. The results confirm that ECG-based features alone can be effectively used for preliminary detection of dangerous arrhythmias. The developed approach is especially valuable for telemedicine systems and healthcare facilities with limited access to expensive diagnostic equipment.

The article discusses a three-circuit cascade system for automatic control of the water level in a steam boiler using adaptive adjustment of the coefficients of the PID controller. A feature of the proposed system is the use of fuzzy logic for adaptive correction of regulator parameters, which ensures stable and reliable operation of thermal power equipment under various external and internal disturbances. The developed control structure includes three interconnected circuits: water level control through feed water flow, steam flow control, and steam flow control through fuel supply. The use of second-order models, taking into account thermophysical characteristics, makes it possible to increase control accuracy and reduce energy losses. The adaptive adjustment system provides automatic adjustment of the coefficients of the PID controller depending on the current state of the control object. It is shown that the adaptive system effectively compensates for unsteady fluctuations in the water level caused by the characteristics of a two-phase medium and transient conditions, increasing the reliability and stability of the thermal engineering process. The results of numerical modeling and analysis confirm the effectiveness of the proposed approach in conditions of changing object characteristics, noise, delays, and limited information about environmental parameters, which is especially important for complex multiconnected systems.

This article presents a comparative analysis of neural network architectures LSTM, BiLSTM, and RuBERT applied to the automatic classification of student feedback. Particular attention is paid to data preprocessing, manual annotation with consideration of sentiment and thematic aspects, as well as corpus reliability assessment using Cohen’s kappa coefficient (0.82). The experimental results show that RuBERT achieves the highest Accuracy (0.87) and F1-score (0.85), which is statistically confirmed by t-test results. At the same time, BiLSTM demonstrates higher efficiency compared to LSTM due to its ability to capture bidirectional context. Error analysis revealed that recurrent models most often confuse neutral and negative feedback, while the transformer-based architecture performs better in handling ambiguous expressions and subtle emotional nuances. The practical significance of the study lies in the possibility of integrating the proposed approach into LMS and digital educational platforms to automate the analysis of student feedback. Future research directions include expanding the corpus with Kazakh-language texts and applying advanced Transformer-based models (RoBERTa, DeBERTa, ChatGLM).

This article presents a comparative analysis of two primary routing protocols – OSPF (Open Shortest Path First) and BGP (Border Gateway Protocol) – within multi-level network architectures. The study involved testing the actual performance of both protocols using Cisco Packet Tracer. Key aspects such as connection establishment time, convergence speed, resource load, and routing policy flexibility were examined.
The test results showed that OSPF is characterized by fast connection establishment and quick convergence, making it the preferred choice for use within an autonomous system where high availability and minimal response time are critical. On the other hand, while BGP has a slower connection setup and convergence, it offers significantly greater scalability and flexibility in routing policy configuration, making it an optimal choice for inter-network communication and global networks.
The study also addressed the protocols' resistance to routing loops, as well as their processor and memory load, highlighting that BGP requires fewer resources. This makes it more efficient in scalable and high-load network environments.
The presented results may serve as a valuable reference for network engineers and administrators when choosing an appropriate routing protocol depending on the specific network requirements and architecture.

With the rapid growth of disinformation, cognitive manipulation and coordinated information campaigns in digital media, there is a need to develop intelligent methods for identifying and analyzing information operations. This paper proposes a conceptual model that integrates a multilingual annotated corpus, an ontological knowledge base and a semantic knowledge graph for the systematic study of mechanisms of information impact.
The methodology of the research includes the construction of a specialized framework formed out of messages collected from Telegram channels, news portals and social networks. The data goes through a multi-level annotation using the Label Studio platform, where experts manually mark key entities, including military terms, target audiences, sources, actors, and emotional evaluations. The annotated corpus is semantically corresponded with the ontology of the subject field, formalized in OWL and enriched with the military thesaurus MIL_term, which provides consistency of terminology and support for multilingual analytics.
The ontological model is transformed into an RDF-graph of knowledge, reflecting the relationships between entities, events, tactics and narratives. SWRL-rules are used to identify hidden patterns, and the developed SPARQL-queries allow to extract complex analytical patterns, including chains of "actor – tactic – narrative – audience". The proposed approach forms the basis for complex analysis of information flows, early detection of threats and construction of analytical scenarios, which makes it applicable for research and monitoring of information operations in multilingual digital environments.

Coronary artery disease remains one of the leading causes of death and disability worldwide. Timely diagnosis can reduce the incidence of complications and ease the burden on healthcare systems. However, traditional methods are often costly, invasive, and limited in accessibility. Recent studies confirm the potential of machine learning for clinical applications. This raises the question: is it possible to reliably predict the presence of disease using only clinical and demographic data, without imaging methods?
The aim of this study was to evaluate the accuracy and practical value of such models. Using the UCI Heart Disease dataset (n = 920) under a unified protocol, the LightGBM algorithm was trained and achieved the following results: accuracy = 0.8696, precision = 0.8679, recall = 0.9020, F1-score = 0.8846. These findings complement previous research based on imaging approaches.
The study compared multiple algorithms under identical preprocessing and validation conditions, assessed probability calibration, and applied SHAP for interpretability. The analysis revealed that the main predictors (e.g., ST-segment depression) aligned with established clinical knowledge. This confirms that the model can be used for initial screening and referral to additional diagnostics. Overall, calibrated and interpretable algorithms based on open clinical data can serve as a valuable tool for patient routing in resourcelimited settings.

The article is dedicated to assessing the impact of digitalization on educational practices and the professional activities of teachers. The aim of the study was to analyze primary data collected from the teaching community to identify the current level of digital competencies, the nature of the use of digital tools and artificial intelligence (AI) technologies, as well as their influence on the educational process and student outcomes. The research methodology included a quantitative and qualitative survey of 832 teachers from various educational institutions, conducted through an online questionnaire. The data collection covered demographic characteristics of the respondents, the frequency of use of digital tools (MS Office, Kahoot) and AI (ChatGPT, Gemini), the use of digital technologies in the classroom (interactive testing, AR), subjective assessment of their impact on student motivation and performance, as well as the need for professional development. 
The results of the study revealed active integration of digital tools, with MS Office being the most commonly used and growing popularity of AI tools. Teachers noted a significant increase in student engagement (84.6%) and improvement in content comprehension due to digitalization. However, despite the overall positive trend, 4.4% of respondents indicated negative aspects, such as decreased comprehension or increased time costs. A high level of interest in mastering interactive tasks, AR technologies, and AI was
identified among educators, confirming the demand for continued  professional development. The obtained data provide an empirical basis for the development of targeted training programs and the optimization of
strategies for integrating digital technologies into the educational environment.

I

In the modern era, where rapidly changing educational landscapes require adaptive learning mechanisms, integrating artificial intelligence into education is no longer a futuristic dream but a necessity. This paper presents a sophisticated intelligent system for real-time monitoring, detailed analyzing, and adaptive optimizing of competency acquisition throughout the learning process. Based on a neural network architecture augmented with ontological modeling and set-theoretic principles, this system provides a structured yet flexible framework for continuous learning improvement. Using the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) methodology, the proposed model systematically improves educational trajectories through data-driven analysis and iterative improvements, ensuring precise alignment with industry and institutional requirements. In addition, the system incorporates predictive analytics and personalized feedback mechanisms that adapt instructional strategies to individual learner needs, thus bridging the gap between standardized curricula and personal learning paths. It further enhances decision-making for educators by providing actionable insights, real-time performance dashboards, and evidence-based recommendations. By combining advanced computational intelligence with proven educational methodologies, this research contributes to the creation of resilient, scalable, and future-ready learning environments that foster innovation, efficiency, and lifelong skill development.

This article presents a comparative analysis of approaches to auditing Information Security Management Systems (ISMS) used in the Republic of Kazakhstan and other countries. The study examines key audit methodologies, including international regulatory frameworks such as ISO/IEC 27001 (International Organization for Standardization / International Electrotechnical Commission), NIST (National Institute of Standards and Technology), and the GDPR (General Data Protection Regulation), with a particular focus on their adaptation across different legal jurisdictions. Special attention is given to the strengths and limitations of various auditing practices, as well as the maturity levels of ISMS executions across different nations. The paper analyzes the current state of information security in Kazakhstan, taking into account the national regulatory landscape and the practical application of audit mechanisms in both public and private sectors. It also identifies critical challenges faced by organizations, such as the shortage of qualified personnel, difficulties in implementing contemporary standards and technologies, and weak interdepartmental coordination. Prospective directions for enhancing ISMS audit methods are outlined based on an evaluation of global best practices. Additionally, the paper discusses potential directions for enhancing ISMS auditing practices by drawing on global experience and offers practical recommendations for improving audit effectiveness and strengthening national cybersecurity frameworks.
The findings of this study are of practical relevance to information security professionals, auditors, researchers, and organizations involved in risk management and data protection within the context of ongoing digital transformation.

This study investigates the impact of educational level on students’ academic performance across bachelor’s, master’s, and doctoral programs. Analysis of Variance (ANOVA) and Tukey’s post hoc test were applied to identify statistically significant differences among the groups. The results demonstrate that master’s students, particularly those enrolled in specialized tracks, and doctoral students achieve higher average grades compared to undergraduates. Such differences can be explained by advanced research orientation, greater learning autonomy, and more developed self-regulation skills. At the same time, the complexity of academic disciplines was found to be an important determinant of performance outcomes. Technical courses such as Machine Learning and Microcontroller Programming showed lower average grades, while courses related to databases and Internet technologies were characterized by higher achievement levels. These findings provide valuable insights for universities to reconsider curriculum design, adapt teaching methods, and develop personalized learning strategies to enhance educational quality and competitiveness in higher education.

Deep learning from medical images is typically hindered by limited access to images and severe imbalance of classes that reduces the effectiveness of typical machine learning algorithms. Generative adversarial networks can be employed to address such issues by creating natural-appearing synthetic images to complement training sets. In this study, we compare two advanced GAN architectures, StyleGAN2 and StyleGAN3, using two publicly available breast imaging datasets: BUSI (ultrasound, 210 malignant cases) and CBIS-DDSM (mammography, 509 malignant cases). Evaluation was based on Fréchet Inception Distance and Kernel Inception Distance. On BUSI, StyleGAN3 achieved FID = 140.7 and KID = 0.06 at 1000 epochs, whereas StyleGAN2 achieved FID = 259.7 and KID = 0.25. On CBIS-DDSM, StyleGAN3 achieved FID = 90.6 and KID = 0.06, and StyleGAN2 achieved FID = 124.8 and KID = 0.10. These results demonstrate that StyleGAN3 has a tendency to synthesize images that are more natural and diversified under limited dataset conditions, at the cost of increased training times, whereas StyleGAN2 provides similar quality at less expensive computational costs. The results indicate the potential of generating medical images and the tradeoff between image quality and efficiency in data augmentation for breast cancer image improvement.

The present article is devoted to the development and analysis of the cascade model of formation of digital competencies (DC) of teachers, which responds to the current challenges caused by the global digital transformation and the national strategy of education development in the Republic of Kazakhstan. The model is conceptually structured into three interrelated stages: the first is a systematized process of formation of DSC, including motivational-target, methodological, content-technological and regulatory-result blocks; the second is the direct application of formed DSC in everyday pedagogical activities; and the third is the assessment of the impact of these competencies on the academic results of students.
The paper provides an in-depth analysis of each stage of the model, describing the principles, the digital eco-environment, teaching methods and tools, and the assessment system. Particular attention is paid to the context of digitalization in Kazakhstan, highlighting the critical importance of teachers acquiring relevant digital skills in light of government programs and regulations. To confirm the practical significance of the model, the results of the first stage of a large-scale empirical survey covering 1,352 teachers are presented. This survey convincingly demonstrated the high interest of the teaching community in mastering interactive lesson formats and implementing augmented reality (AR) and generative artificial intelligence (GenAI) technologies. The article also compares the proposed model with relevant foreign and domestic scientific research in the field of digital pedagogy, identifying common trends and specific challenges. The results of the first stage of the survey and their implication for further adaptation and improvement of the model are discussed. Prospects for further research are outlined, including the second stage of the survey, which will be conducted after the training module aimed at the development of interactive forms of learning and work with AR-technologies. Thus, the article is a contribution to the development of theoretical and methodological foundations for the formation of teachers' CK and their practical realization in the conditions of digital educational environment.

Digital transformation in higher education represents a comprehensive strategic process that transcends technological modernization and embraces institutional, managerial, and pedagogical innovations. This paper explores the evolution of digital transformation in Kazakhstan – from informatization and digitalization to a fully integrated transformation – based on a systematic analysis of 44 academic
publications. The study proposes a structural model of university digital transformation, integrating three key dimensions: strategic management and institutional processes, technological ecosystems and pedagogical innovations, and the development of human capital. The findings demonstrate that digital transformation serves as a crucial framework for bridging the digital divide, enhancing institutional efficiency, and ensuring the sustainable development of higher education. Moreover, the proposed model contributes to the alignment of national digital policies with university strategies, reinforcing competitiveness and adaptability in the global digital environment. The study provides theoretical and practical insights for universities navigating digital transition toward sustainable growth.

Pipeline integrity and safety are critical for transporting water, oil and gas, but traditional inspection methods are resource-intensive and error-prone, delaying defect detection. The objective of this work is to create an autonomous robotic system capable of detecting, localizing and classifying problems inside a pipe using sophisticated imaging techniques and artificial intelligence algorithms. To achieve this goal, multimodal precision-enhancing sensors (high-resolution RGB cameras, ultrasonic and infrared sensors) with data processing methods such as the Canny edge detector and the DBSCAN clustering algorithm were used. The research approaches include the creation of a modular robotic platform for autonomous navigation, the creation of synthetic data for training deep neural networks, and experimental validation on pipelines of different materials and dimensions. The experimental results show that the system outperforms existing approaches, making it a valuable tool for predictive maintenance, regulatory compliance and improving pipeline safety.

This study focuses on the application of machine learning methods and statistical time series modeling to historical data on natural gas production in Kazakhstan (2000-2024) in order to build a reliable predictive model. The study considers and compares ARIMA, Holt-Winters, linear regression with lag variables, Random Forest, and gradient boosting models. The accuracy of these models was evaluated using standard metrics: MAE, RMSE, and the coefficient of determination R². The comparison results showed that the Holt–Winters exponential smoothing method provides the highest forecast accuracy among all the approaches tested. This model was chosen to generate the forecast of natural gas production volumes for 2025-2027. According to the forecast, a further gradual increase in natural gas production is expected in 2025-2027 while maintaining the identified trend and seasonal patterns. The results obtained demonstrate the effectiveness of integrating modern machine learning algorithms with classical time series analysis methods when working with historical statistical data. The practical significance of this work lies in the fact that the developed forecasting model can contribute to more substantiated strategic planning in the gas industry and improved efficiency of resource management.

As part of the research work (IRN AP23489791), an online voting system based on blockchain technology was developed and implemented. This article is devoted to the methodology and practical application of the Power BI business intelligence tool for analyzing and visualizing data generated by this system. Using business intelligence tools such as Power BI to analyze data from blockchain voting systems is an important step to validate their performance, security, and transparency. The blockchain is a decentralized digital registry consisting of a chronologically ordered chain of blocks. In the context of electronic voting, these blocks contain transactions that can represent various operations: registration of voters and candidates, submission of votes, and counting of results.
The key characteristics of the data in the blockchain that make them suitable for voting systems and subsequent analysis include: Immutability, transparency, decentralization, Traceability. Each transaction has a unique identifier and a timestamp, which allows you to track all transactions in the system.
The work demonstrates how Power BI enables the transformation of complex and distributed blockchain data into visual and easily interpretable graphs and dashboards, which is critical for evaluating the performance, security and transparency of the voting system. Key metrics and visualizations are presented, and the process of integrating blockchain data with an analytical tool is described. The results confirm that using Power BI is an effective approach for validating and demonstrating the benefits of decentralized systems.

This article provides an extensive analytical overview of the scientific, methodological and technological foundations for developing an automated mobile system designed for high-precision soil composition mapping using GPS navigation and artificial intelligence. The relevance of this research is particularly significant for Kazakhstan, where soil conditions vary widely across regions – from chernozems to chestnut soils, saline soils and degraded landscapes. Such diversity requires advanced digital tools capable of performing rapid and accurate soil assessment.
The literature review reveals the strong potential of VIS-NIR spectroscopy, mathematical modelling techniques, machine learning algorithms and geoinformation systems for improving soil diagnostics. Emphasis is placed on evaluating model performance indicators such as the coefficient of determination (R²) and root mean square error (RMSE), as well as the role of RTK-GPS in achieving centimeter-level geospatial accuracy. The integration of AI-enabled spectral analysis with GPS-based georeferencing ensures the generation of high-resolution soil maps (3-7 m), allowing precise identification of nitrogen, phosphorus, potassium, organic carbon and other vital soil attributes.
Furthermore, automated mobile platforms significantly reduce time and labor costs, increase analytical efficiency and provide valuable decision-making tools for sustainable agriculture. They support targeted fertilizer application, soil fertility management, monitoring of erosion and salinization processes and assessment of agroecological risks. The findings confirm that implementing AI- and GPS-integrated mobile systems in Kazakhstan can substantially enhance soil monitoring infrastructure, optimize agricultural resource management and strengthen long-term environmental sustainability.

Kazakhstan is struggling with the problem of desertification and land degradation, especially in the southern regions and the Aral Sea region, where the annual release of about 150 million tons of salt is causing an ecological imbalance. One of the main plants that plays an important role in soil stabilization is saxaul, which covers an area of more than 6 million hectares. However, traditional methods of collecting its seeds are not effective enough, which slows down the process of restoring forests.
The purpose of this study is to analyze scientific works aimed at developing an automated mechanism for collecting saxaul seeds using modern technologies, such as artificial intelligence (AI), remote sensing and robotics. The analysis considered the potential of satellite information (KazEOSat, Sentinel), deep learning methods (CNN, Random Forest), unmanned aerial vehicles (UAV), Internet of Things (IoT) systems and innovative solutions.
The results of the study show that the introduction of modern technologies allows to increase the productivity of forest restoration measures and enhance the viability of plants. Moreover, these approaches can make a significant contribution to sustainable greening of the Aral Sea region. However, further research is needed to ensure their adaptation to the natural and climatic conditions of Kazakhstan.

Railways remain an essential part of modern transportation, yet their safe functioning is often determined by the actual condition of the tracks. The study looks at various ways to detect faults in the rail infrastructure and splits them broadly into two categories: static and dynamic techniques. Different countries rely on different tools to monitor tracks, and this paper compares those tools based on practical factors like how precise they are, how much ground they cover, and how difficult or costly they are to operate. Rather than simply listing pros and cons, we try to show where each method works best. To make sense of the data, visuals like charts and summaries were added, making it easier to see where each approach fits. One part of the analysis pays special attention to how certain features of the railway - such as how wide the rails are or how much the outer rail is elevated - can influence the choice of inspection methods. Lately, there's been a shift toward smarter diagnostics. Technologies like AI, digital simulations of tracks (known as digital twins), and systems using many sensors at once are gaining ground. These tools are changing how track inspections are done and offer new opportunities for early problem detection. This paper doesn't just list methods - it gives a clear structure for understanding which approach fits what context. The outcomes can help transportation teams fine-tune how they take care of tracks and make the system more dependable in the long term.

The article presents a systematic review of modern requirements for the development of e-learning applications for children, covering aspects of content, UX/UI design and digital security. With the rapid growth of the EdTech sector and an increasing number of preschool and primary school age users, the need for highquality, inclusive and secure digital content is increasing. The study is based on an analysis of scientific and regulatory literature, international standards (ISO, COPPA, GDPR-K), as well as practices in countries with a high level of digitalization of education (USA, Finland, South Korea, Australia).
The key technical and design criteria that children's educational applications must meet are highlighted: adaptation to the age and cognitive characteristics of children, accessibility and simplicity of the interface, minimization of visual and cognitive noise, as well as compliance with the principles of digital ethics and privacy. Special attention is paid to the issues of UX testing with the participation of the target audience – children, as well as the requirements for the licensed examination of applications.
Examples of applications aimed at developing graphomotor skills are analyzed, indicating their functions, platforms, and language adaptation. The article highlights the need for an interdisciplinary approach in the development of digital products for children, taking into account both pedagogical tasks and technical limitations.
It is concluded that there is a need for further development of national and international standards, especially in the light of the integration of artificial intelligence technologies into children's applications. The presented work can serve as a methodological basis for researchers, educators and developers working in the field of digital education.

The depletion of high-grade molybdenum ores and the need to process complex sulfide concentrates pose significant challenges for the hydrometallurgical industry. Traditional approaches to processing experimental data based on manual calculations are characterized by high labor intensity, risk of computational errors, and information fragmentation. This paper describes the development of a specialized information system for modeling and analyzing the hydrometallurgical processing of molybdenite concentrates. The software is implemented using the Django web framework and includes modules for experimental data input, automated calculation of material balances for leaching and sorption processes, and visualization of results through interactive analytical dashboards. The system has been validated using data from 6 leaching experiments and 9 molybdenum sorption experiments. The modular three-tier architecture ensures solution scalability and enables its adaptation for modeling other hydrometallurgical processes. The developed calculators allow predicting molybdenum recovery rates at various stages of the technological cycle without conducting additional physical experiments. The practical significance of this work lies in creating a digital twin of the technological process that establishes a unified information space for researchers, ensures transparency and reproducibility of experiments, and lays the foundation for industrial scaling of molybdenite concentrate processing technology.

The article discusses modern approaches to modeling and predicting student academic performance dynamics in educational systems using machine learning methods. The study includes a detailed analysis of existing methodological approaches, ready-made solutions, and commercial platforms; a review of literature sources describing the application of data analysis algorithms in the educational field; and the development of a custom model that covers data collection, processing, model and algorithm selection, and prediction of student performance.
Various popular ready-made solutions and commercial platforms that use machine learning methods to analyze, predict, and optimize educational processes have been examined, including: Blackboard Predict, Civitas Learning, Knewton Adaptive Learning Platform, DreamBox Learning, IBM Watson Education, and SAS Campus Analytics. The study analyzed the weights of general attributes that affect prediction, and examined how specific features influence outcomes.
The presented article demonstrates that the use of neural networks can significantly improve prediction accuracy, making them a valuable tool for managing educational institutions and making timely administrative decisions. However, one drawback of this algorithm is its long training time on computers with lower computational capabilities. Therefore, other algorithms were also considered during the development of the custom model.
The research results showed that ensemble methods significantly reduced prediction errors compared to linear regression, while also requiring much less time for training and forecasting.

The article presents a case study on the implementation and evaluation of the effectiveness of an adaptive business process management system (BPM) for small and medium-sized businesses (SMEs), integrating machine learning (ML), serverless architecture and cybersecurity measures. The research is based on the previous works of the author [1, 2], where the methods of designing automated information systems (AIS) were analyzed and a conceptual model of the system was developed. The relevance of the topic is due to the growing need for automation in SMEs in developing economies such as Kazakhstan and Russia, where traditional ERP/CRM systems are often ineffective due to high costs and low adaptability. The goal is to evaluate the ROI of the system through implementation in two fictional but realistic cases (retail and services) using data modeling for privacy.
The methodology includes the collection of metrics before and after implementation (process processing time, costs, security level), A/B testing, and log analysis. Python with TensorFlow for predictive analysis ML models, AWS Lambda for serverless components, and OWASP threat assessment tools were used. The results show a 25-30% reduction in costs, a 35-40% improvement in adaptability due to ML, and an increase in cybersecurity through vulnerability detection. Ethical aspects include data anonymization and compliance with GDPR-like standards. The findings confirm the benefits of the system for SMEs, with recommendations for scaling and discussion of limitations such as reliance on cloud services.

This article examines the importance of digitizing data visualization processes in media art and its impact on creative practice. With the increasing volume and complexity of information, new methods of working with visual data are required. In this context, key visualization tools such as raster, vector, three-dimensional (3D), and fractal graphics are analyzed, and their role in media art is defined. Special attention is given to IT technologies – animation, interactive infographics, virtual and augmented reality (VR/AR), and cloud systems – and their significance for the development of artistic projects.
Based on informational and comparative analysis, the article explores digital practices in media art and art therapy. It reviews the experience of exhibitions, online platforms, and social networks in Europe, the USA, and Asian countries, outlining their advantages. The role of online art therapy in providing psychological support and developing creative abilities is emphasized. In addition, the initial steps in Kazakhstan are examined and compared with international practices.
The research findings indicate that the main challenges of introducing digitalization into media art are linked to insufficient technical infrastructure, lack of qualified personnel, and methodological limitations. At the same time, broad integration opportunities are identified: applying international experience, adapting modern technologies, and training professional specialists. The conclusion presents practical recommendations for the development of digital formats in media art and art therapy.

This study presents a new intelligent system based on deep learning methods for the automatic detection of hate speech in the Kazakh language. Particular attention is paid to the specific nature of Kazakh as a resource-poor language, where the limited linguistic data poses significant challenges in building reliable models. A multilingual data corpus covering a wide range of speech contexts was generated and preprocessed using various online sources-social media, forums, and news portals. To improve efficiency and generalization performance, a hybrid architecture was proposed, including convolutional neural networks (CNNs), bidirectional long short-term memories (BiLSTMs), and Transformer attention mechanisms. An evaluation using precision, recall, F1-criterion, and accuracy metrics demonstrated the superiority of the proposed model over traditional machine learning algorithms. The results of the study make a significant contribution to the development of automatic content moderation systems and promote the creation of a safer, inclusive, and linguistically sensitive digital space for Kazakh-speaking users.

The paper presents the development and optimization of a hybrid hardware-software implementation of the post-quantum cryptographic algorithm Saber on an embedded CPU-FPGA platform. The main objective of the research is to enhance the performance, energy efficiency, and security of post-quantum key exchange schemes under limited computational resources while maintaining resistance to side-channel attacks.
The proposed architecture integrates the computational capabilities of the ARM processor and the FPGA core, enabling efficient distribution of workloads between the processor and the hardware accelerator.
The hardware part implements pipelined polynomial multiplication and SHA-3 hashing, while the software component manages data flow, synchronization, and integrity control. A fixed-latency communication interface between the CPU and FPGA ensures constant-time execution and stability against timing variations.
Three implementations of the algorithm were compared: software, hardware, and hybrid. Experimental results demonstrated a 35-50% reduction in execution time without compromising cryptographic strength or increasing power consumption. A TVLA (Test Vector Leakage Assessment) analysis confirmed the absence of any statistical correlation between the energy profile and secret data, validating the system’s side-channel resistance.
The proposed solution can be effectively applied to mobile robotic platforms, unmanned marine vehicles, industrial telemetry networks, and IoT systems requiring high-performance and quantum-resistant data protection.

Cardiovascular diseases remain the leading cause of mortality worldwide; therefore, early-stage noninvasive risk assessment is crucial both for prevention and for the efficient allocation of healthcare resources. Heart rate variability (HRV) is a reliable indicator of autonomic balance, yet in clinical practice it still relies mainly on long-term ECG recordings, which limits large-scale application. Although photoplethysmography (PPG) is widely available, the effectiveness of PPG-derived HRV metrics for detecting ischemic heart disease (IHD) has not been fully established.
In this study, PPG signals obtained from a low-cost Zhurek device, combined with machine learning classifiers, enabled IHD detection with an accuracy of 90.82%. Comparison with three-channel Holter ECG showed satisfactory agreement. SHAP and mutual information analyses highlighted the dominant role of frequency-domain features (HF, LF). Data balancing using CTGAN improved training stability.
Overall, the results demonstrate that PPG-based HRV analysis offers a feasible, accessible, and interpretable approach for IHD screening. Future steps include multicenter validation, expansion of feature sets, and integration of the method into wearable devices.

This article examines the problem of optimizing security policies in software-defined networks (SDN). The authors propose solving this problem using NSGA-II, an efficient algorithm for evolutionary optimization of multiple objectives. The proposed approach aims to achieve a balance between the need to strictly enforce network security and the availability of limited computing resources. Particular attention is paid to factors such as data transmission latency and TCAM table size, which significantly affect the effectiveness of traffic filtering. Based on the model developed in the article, which includes threat probability assessments, objective function normalization methods, and the use of penalty coefficients for rule conflicts, optimization was performed across three key parameters: attack risk, network latency, and TCAM load. The simulation covered three network operation scenarios-normal, mixed, and attack-using Mininet and Ryu packets. A comparison of the proposed method with differential evolution (DE) and a greedy algorithm (Greedy) showed that NSGA-II achieves optimal solution distribution along the Pareto frontier, converges faster, and maintains filtering accuracy. The paper also presents visualization of generational transitions, tradeoff graphs, and load profiles. The conclusion discusses the potential for integrating the proposed model with ONOS and OpenDaylight controllers, and discusses the feasibility of using hybrid solutions based on Deep Reinforcement Learning, Federated Learning, and Explainable AI.

Currently, many types of centrifugal equipment are used in various industries. Among them:continuously operating filter screw centrifuges, pulsating, inertial, vibrationally discharged sludge and settling screw centrifuges. It is the most efficient equipment used in the food and meat industry and provides high-quality separation of liquid heterogeneous systems [1].
Screw devices used in the food industry are divided into augers: conveying and pressing.
The pressing screws are designed to create increased pressure in the product in order to change its physical properties, shape and ratio between the solid and liquid phases.
The special feature of the pressing screws is high pressure: up to 6-20 MPa and low rotation speed: 5-30 rpm.
Transporting screws are provided to move the product. They can additionally perform the functions of dosing and mixing.
They have higher rotational speeds: from 50 to 400 rpm and should not create excessive pressure on the product, as well as not over–pump the transported material.
As a working body, the auger has the following advantages: simplicity of design, versatility, compactness, and low cost.
In research papers, geometric dimensions are considered generically and are taken based on the patterns of the average value. This cannot fully provide an accurate description of the ongoing process. These facts indicate that the separation of liquid heterogeneous systems in centrifugal equipment still requires a large amount of research.

CAES technology combines mechanical and thermodynamic forms of energy storage. It can be scaled from local modular units to industrial-scale solutions. Its main advantages include high energy storage capacity, long operation time without recharging, integration potential with solar and wind power plants, and potentially low cost with mass deployment. As the share of renewable energy sources (RES) grows and the need to ensure the resilience of power systems increases, energy storage technologies are becoming strategically important. This paper presents a comprehensive analysis of compressed air energy storage (CAES) technology, including comparative evaluation with other storage systems, design features, advantages, and implementation challenges. Special attention is given to the potential of CAES application in the Republic of Kazakhstan, considering its climatic, geological, and economic conditions. The study explores innovative approaches, including thermomechanical CAES, as a promising direction for Kazakhstan. The work also presents research analysis results, identifies key barriers, and proposes measures to overcome them. The article is based on national and international sources, modeling, and expert assessments, and may serve as a foundation for shaping a national strategy for energy storage technology development.

In this study, an investigation was carried out to reduce the mass of a cantilever beam made of Al9 aluminum alloy using topology optimization (TO) based on the SIMP method. The optimization was performed with the APM FEM software package, which made it possible to implement numerical modeling at a modern level, taking into account the material features. The beam was subjected to a combined action of a concentrated vertical force of 4000 N and a longitudinal tensile force of 3000 N, which allowed simulating an actual operating load close to the working conditions of structures in mechanical engineering and construction. During the calculations, it was possible to reduce the mass of the structure by 52% while maintaining the main strength characteristics. At the same time, an increase in maximum stresses compared to the initial model was observed, which is associated with the redistribution of material and stress concentration in certain zones. However, the stress level remained within values close to those permissible for the chosen material considering the safety factor. Modal analysis confirmed sufficient separation of natural frequencies from critical values. The obtained results demonstrate the potential of applying TO for the design of lightweight, energyefficient, and technologically promising structures.

This paper presents the results of an experimental study on the effect of electrolyte-plasma hardening (EPH) on the microstructure, microhardness, and abrasive wear resistance of widely used structural steels – grades 45 and 65G. The treatment was carried out in an aqueous solution of sodium carbonate under a voltage of 300-320 V for a duration of 2-3 seconds. The EPH method provided ultra-high heating and cooling rates due to direct contact with the electrolyte, which contributed to the formation of a thin hardened layer with a martensitic structure and carbide inclusions.
Microstructural analysis revealed the presence of three characteristic zones: a hardened surface layer, a heat-affected zone, and an unchanged core matrix. The surface microhardness after EPH increased by 1.6-1.8 times compared to the initial state, while abrasive wear resistance improved by 1.3-1.6 times. It was also noted that extending the treatment duration positively influenced the surface layer’s plasticity, with only a slight reduction in hardness.
The obtained results confirm the high efficiency of EPH as a resource- and energy-saving method of local surface hardening, capable of significantly extending the service life of components operating under frictional and abrasive conditions. The method is recommended for integration into the technological processes of the mechanical engineering, transportation, and agricultural industries.

This article discusses modern methods of producing yogurts with the addition of plant-based biologically active additives. The article describes the main components used to enrich yogurts with plant extracts, their impact on the organoleptic and physicochemical properties of the product, as well as the role of such additives in improving the functional properties of yogurts. The article also considers methods that help preserve the beneficial properties of plant additives during production and storage of yogurt. An important aspect is the use of natural plant components to enhance flavor and increase the nutritional value of the product, which helps meet the needs of consumers interested in healthy eating. The article also discusses the prospects of developing this technology and its influence on market trends in dairy product production. The scientific significance of the work is in expanding knowledge about the possibilities of using plant additives in the dairy industry, while the practical value is in the implementation of new technologies for producing functional products with improved health benefits. A method for obtaining a thick extract for the production of functional bio-yogurt has been developed. To develop the technology for obtaining a thick extract, the following modes have been experimentally established: extraction temperature of 50-55 ºС, duration of 5 hours, with a ratio of raw materials and extractant of 1:20, 95% ethyl alcohol has been selected as the extractant.

This study investigates the impact of incorporating powdered juniper berries into the formulation of wheat-based bakery products on their microbiological stability during storage. Juniper berries are rich in natural antimicrobial and antioxidant compounds, which makes them promising as a functional ingredient in food production. The aim of the research was to evaluate the effectiveness of adding 3% powdered juniper berries to wheat bread. A comparative analysis was conducted between a control sample (without additives) and an experimental sample containing the juniper berry powder. Microbiological indicators were assessed under room temperature conditions and at elevated temperature (37 °C) over a defined storage period. No signs of "potato disease" caused by Bacillus subtilis and Bacillus mesentericus were observed in the experimental samples. Furthermore, compared to the control, the juniper-enriched bread showed a significant reduction in the total count of mesophilic aerobic and facultative anaerobic microorganisms (TAMC), mold fungi, and coliform bacteria. The results confirm that the use of powdered juniper berries contributes to enhanced microbiological safety and prolonged shelf life of bread products without the need for synthetic preservatives. The obtained results open up prospects for the development of functional bakery products with enhanced hygienic, technological, and consumer characteristics, aligned with the principles of healthy nutrition in the baking industry.

Milk is one of the most important and nutritious food products; however, its quality largely depends on environmental conditions. Environmental pollution leads to the accumulation of heavy metals in food products, posing a threat to public health. Among them, lead (Pb), cadmium (Cd), arsenic (As), and other elements are considered the most hazardous. The aim of this study was to determine the content of lead, cadmium, and arsenic in raw cow’s milk samples and to evaluate the efficiency of adsorption purification using natural sorbents. Samples collected from three settlements were analyzed by the method of inversion voltammetry. It was found that the cadmium content in milk from the village of Sarzhal exceeded the maximum permissible concentration (0.067 mg/kg at a standard of 0.03 mg/kg), whereas lead and arsenic levels remained within permissible limits. For milk purification, an improved experimental installation with three sorption columns filled with shungite, zeolite, and coconut-based activated carbon was used. The highest efficiency was achieved with the 1+3 column combination (shungite + coconut activated carbon), which reduced lead concentration by 91%, cadmium by 75%, and arsenic by 84%. The obtained results confirm the feasibility of using natural sorbents for milk purification and demonstrate the potential of the developed installation for application in laboratory and small-scale production conditions.

In the context of global protein deficiency and the growing interest in functional food products, special attention is paid to leguminous crops with a high content of essential amino acids. This study aimed to evaluate the dynamics of the essential amino acid profile in seeds of Vigna radiata L. “Zhasyl dän” during fermentation. The work is based on the author’s experimental data obtained by germinating the seeds for 72 hours, followed by amino acid analysis.
The results showed that the total content of essential amino acids (EAA) in the control samples was 8032 мг/100 г dry matter. At 24 hours, this value increased to 9398 мг/100 г, reaching a maximum of 10,674 мг/100 г at 48 hours (an increase of about 33%), and slightly decreased to 10,390 мг/100 г at 72 hours. The most pronounced changes were observed for leucine+isoleucine (from 2895 to 3493 мг/100 г) and lysine (from 1394 to 1674 мг/100 г). Threonine increased from 605 to 714 мг/100 г, and valine – from 1178 to 1430 мг/100 г.
The obtained results confirm that fermentation of mung bean seeds activates endogenous enzymatic systems, promoting the accumulation of amino acids and enhancing their bioavailability. These findings are of practical importance for the development of functional food products with high protein value. The presented work is the first author’s study carried out for the “Zhasyl dän” variety and expands scientific understanding of the biochemical changes in Vigna radiata protein during fermentation.

The scientific article discusses the technology of developing fermented milk drinks based on camel milk using probiotic starter cultures and the results of a study of their organoleptic, physico-chemical and microbiological properties. Based on the characteristics of probiotic lactobacilli listed in the technical documentation, 4 starter cultures were formulated under aseptic conditions. To produce fermented milk drinks, the prepared compositions were injected directly into camel milk, which had undergone preliminary heat treatment (30 minutes at 63°C) and cooled to the required temperature (37°C).
In the course of the research, a traditional product, shubat, was chosen as a control sample. The organoleptic characteristics of the developed fermented milk products met the requirements of regulatory documentation and received high scores (4.8-4.9). In order to determine the physico-chemical parameters and shelf life for 21 days, a change in the titrated acidity of drinks and shubat was observed. Compared with shubat, the new products showed normal acidity (up to 120°C) during the study period. The energy value of fermented milk drinks (59.2-61.2 kCal) was also calculated.
Based on the results of microbiological studies, the number of beneficial lactobacilli in the composition of drinks was determined, which met the requirements of regulatory and technical documentation (3,6*10⁶-5*10⁶ CFU/g). This is an important indicator justifying the probiotic properties of fermented milk drinks. Thus, as a result of the conducted research, the technology of preparation and storage conditions of the produced fermented milk drinks (21 days at 2-4 °C) were approved.

This article presents a comprehensive evaluation of protein isolates derived from pea, soy, wheat, and corn, including their yield, chemical composition, physicochemical and colorimetric characteristics (CIE Lab*), and amino acid profiles. Proteins were obtained via alkaline extraction (0.1 M NaOH, pH 9, 30°C, 60 min). Extraction efficiency was high across all samples (83.25-85.21%); the highest yields were recorded for soy (31.1%) and pea (21.23%). The protein mass fraction in the isolates ranged from 69.37% to 79.36%; fat content was lowest in soy (0.12%), whereas the carbohydrate fraction was elevated in the wheat isolate (19.2%). Bulk and tapped densities for the wheat isolate (0.52 g/mL and 0.73 g/mL, respectively) indicate a favorable potential for forming a fibrous, meat-like texture. Color analysis confirmed high lightness across all isolates (L* = 80.15-85.47). Based on amino acid profiles, pea and soy isolates exhibited more balanced compositions (higher lysine and arginine), whereas lysine was limiting in corn (zein) and wheat. These findings substantiate the use of soy and pea proteins as base components for plant-based meat analogues, with wheat (gluten) and corn serving as functional structure-forming additives.

With the increase in the proportion of elderly people in Kazakhstan and worldwide, there is a growing need to develop specialized functional food products that meet their physiological needs. This study examines the possibility of producing sugar cookies of gerodietetic purpose using soy isolate and rye bran. The prepared samples were analyzed for organoleptic and physicochemical characteristics, and the influence of the introduced components on the taste and texture properties of the final product was studied. The following samples were used in the study: Sample No. 1: 90% wheat flour of the first grade + 5% rye bran + 5% soy isolate; Sample No. 2: 85% wheat flour of the first grade + 10% rye bran + 5% soy isolate; Sample No. 3: 85% wheat flour of the first grade + 5% rye bran + 10% soy isolate; and as a control, wheat flour of the first grade was applied. According to the research results, the optimal ratio was found to be the addition of 10% rye bran and 5% soy isolate, which ensures a balanced composition and improved consumer properties. The inclusion of these ingredients contributes to an increase in protein and dietary fiber content, making the cookies beneficial for elderly people. The development of gerodietetic flour-based products opens up opportunities for creating affordable and functional foods aimed at maintaining the health and quality of life of the elderly population.

Meat maturation is a complex process that includes biochemical, microbiological, and physicochemical transformations that determine the flavor profile of the final product. This review summarizes current scientific data on the influence of various methods of postmortem maturation (wet, dry, modified forms) and related technological parameters – temperature, humidity, air flow velocity, storage duration – on the formation of organoleptic characteristics of meat. Special attention is paid to the dynamics of flavor-forming compounds (amino acids, peptides, sugars, nucleotides, lipids), the microbial community (Lactic acid bacteria, Pseudomonas, Debaryomyces, etc.), as well as the interaction of biotic and abiotic factors that determine the intensity of metabolic reactions. Innovative approaches aimed at purposefully changing the taste profile are considered, including the use of ultrasound, sous vide technologies, regulated air parameters and controlled fungal fermentation. The data from metabolic and microbiological profiling are presented, confirming the importance of integrated monitoring in the process of optimizing sensory properties. The review emphasizes that the strategic management of the conditions and duration of maturation, as well as the integration of new technological solutions, allow not only to adapt the taste to the needs of consumers, but also to increase the market value of even the lowest category of products. The findings form the basis for the development of scientifically based programs to improve the quality of meat products.

This article presents the results of a comparative analysis of the amino acid and fatty acid composition of oat grains from three varieties: «Duman», «Nikola», and «Ishimsky2. Oats are an important source of biologically active compounds, including essential amino acids and polyunsaturated fatty acids, which play a crucial role in maintaining human health, supporting the immune system, and regulating metabolic processes.
The comparative study was conducted at the Japanese Center of the Kazakh National Agrarian Research University using high-performance liquid chromatography (HPLC) and gas chromatography (GC) methods. The oat grain samples were provided by the A.I. Baraev Scientific and Production Center of Grain Farming.
According to the results, the «Ishimsky» variety showed the highest concentrations of amino acids: cystine – 1109.11 µg/ml, valine – 784.01 µg/ml, tyrosine – 769.81 µg/ml, arginine – 314.79 µg/ml, histidine – 265.96 µg/ml, and alanine – 242.93 µg/ml.
The «Duman» variety also demonstrated high levels of valine (535.35 µg/ml), tyrosine (606.90 µg/ml), cystine (460.91 µg/ml), arginine (216.61 µg/ml), and histidine (178.47 µg/ml), as well as the presence of unique omega-3 fatty acids not found in other varieties: alpha-linolenic (1.71 %), docosahexaenoic (0.218 %), and nervonic acid (0.367 %).
These characteristics make the «Duman» variety a promising candidate for use in functional food products, oat-based beverages, and the development of biologically active supplements. The data obtained are of scientific and practical interest to breeders, food technologists, and specialists in the field of nutraceuticals.

This article investigates the influence of biodegradable packaging on the shelf life and suitability of food products. A bun was chosen as the research object, and its preservation efficiency in various types of biodegradable packaging was evaluated. As packaging materials, environmentally safe natural and semisynthetic polymers were used: gelatin, agar, starch, chitosan, sodium carboxymethylcellulose (NaCMC), and polyvinyl alcohol (PVA). During the study, the physicochemical stability of these materials, their ability to interact with food products, and their resistance to temperature and humidity were analysed.
The research was conducted in accordance with the United Nations Sustainable Development Goal (SDG) 12 – «Responsible Consumption and Production», which focuses on reducing waste and promoting efficient use of resources through environmentally safe solutions. This study substantiates the scientific and practical importance of introducing biodegradable packaging into the food industry.
The results demonstrated that the storage efficiency of biodegradable materials is not uniform. Some samples maintained product quality for a longer period, while others showed insufficient structural stability. Furthermore, it was confirmed that the decisive factors affecting packaging performance are the type of polymer, its thickness, and moisture permeability.

This article presents the scientific rationale for the analysis and selection of ingredients aimed at improving the quality of dry-cured poultry products and intensifying biotechnological processes. At present, an urgent task in the food industry is the production of new types of products with high nutritional and biological value, as well as favorable organoleptic characteristics. The study examined the possibility of controlling biotechnological, biochemical, and microbiological processes through the use of probiotic cultures and hydroalcoholic extracts based on herbal raw materials.
When selecting phytoextracts, not only their physiological value was taken into account, but also their organoleptic compatibility with poultry meat and their suitability for use with probiotic cultures. Experimental studies established that rosehip extract at a concentration of 0.4% had different effects on the growth of probiotic strains: a decrease in the growth of L. plantarum was observed, while L. casei showed stable growth potential. In addition, it was demonstrated that the use of lactic acid bacteria and bifidobacteria in a 1:2 ratio ensures their mutual quantitative balance and contributes to the optimization of proteolytic activity.
The conducted research has shown that the combined use of probiotic cultures and phytopreparations in the production technology of dry-cured poultry products makes it possible to improve product quality, accelerate maturation stages, and ensure the stability of technological processes.

Scientific research is devoted to the processes of cultivation of garden Spinach (Spinacia oleracea) and further stages of preparation of evacuated powder (dietary supplements) and eco-soap from the grown plant. The main object of research is Garden spinach, which is currently one of the generally recognized leaders of vegetable greens in the diet of modern humans. This fact is due to the presence of a wide range of biologically important chemical components in this plant. In this regard, within the framework of this study, the task was set to create a modern product with a long shelf life, convenient for daily use, preserving a fullfledged biochemical composition, affordable from an economic point of view. An important aspect of the experiment was the control of cultivation conditions, which does not allow the use of chemical fertilizers, since spinach has the property of accumulating these substances in biomass in large quantities. The process of green biomass cultivation was accompanied by monitoring of temperature, humidity, lighting, and watering frequency, which allowed for a comparative analysis of growth dynamics over time by the end of cultivation.
Research aimed at creating experimental biotechnological products – evacuated powder from dried spinach leaves, allowed us to obtain a biologically active food additive for long-term storage (for one year). The proposed additive, which is an alternative to fresh spinach, has the advantage of off-season products that fully preserve biological activity in a vacuum state. The range of spinach powder applications is also important, both in the traditional formulation, as well as in cocktails and smoothies, and as a natural colorant in confectionery technology. In order to compare the preservation of biological activity in the evacuated powder and in freshly harvested spinach leaves, a chromatographic analysis was performed. The indicator of biological activity was chlorophylls a and b contained in fresh and dried spinach leaves.
At the final stage of the research, a technology was developed for using freshly squeezed young spinach juice, the so-called «baby spinach», to make eco-soap. The «baby spinach» crop was harvested in the second week of cultivation under the specified conditions, then it was harvested and crushed by liquid extraction. The stage of introduction of liquid plant biomass (spinach extract) was included in the traditional technological process of cooking soap mass.

This article presents the development of experimental low-productivity equipment for the condensation and pasteurization of liquid food products, aimed on the needs of small and medium-sized food industry enterprises. The relevance of creating compact and energy-efficient equipment for the processing of dairy raw materials and other liquid products is substantiated. The design of the equipment includes a capacitive evaporator with a heat exchange jacket, a vacuum system, a coolant preparation and circulation unit, an automated control unit and a condensation module. The use of a vacuum allows the process to be carried out at reduced pressure, which ensures a lower boiling point, minimizes nutrient loss and prevents thermal damage to the product. The basic principles of the device operation and the sequence of the technological process are presented. Automation of process control simplifies operation, reduces energy costs and increases the stability of the obtained results. The equipment provides efficient condensation by evaporating moisture at low pressure, which reduces energy costs, preserves the nutritional value of products, and improves ease of use. The development can be used in farms, craft workshops and small enterprises in the production of condensed milk, juices, extracts and other types of liquid food products.

Structural and functional properties of soy and pea protein isolates have been comparatively studied. The composition and structure of protein fractions, colloidal-physical properties (ζ-potential, electrophoretic mobility, particle size, conductivity), thermal stability (DSC analysis), and protein profiles (SDS-PAGE) of SPI and PPI were examined. The results demonstrate that SPI exhibits higher thermal stability and can form denser gel-like structures, whereas PPI is characterized by smaller particle size and higher dispersion, leading to superior emulsifying properties. The findings suggest the need for differentiated application of SPI and PPI in the food industry and indicate that combining these isolates could achieve optimal functional performance in food products.

The production of high-quality products and their balance in the human diet are of great importance. Pasta products are in constant demand in the market. Therefore, the creation of products using non-traditional raw materials in order to increase the nutritional value is relevant. The work proposes a technology for the production of tubular pasta with the addition of non-traditional raw materials – pumpkin puree with purpose to increase their nutritional and biological value. A pasta dough recipe developed, containing pumpkin puree in varying proportions, enriches product by β-carotene, dietary fiber, vitamins, and microelements. Research has determined the optimal component ratio (20% by weight of pumpkin puree), ensuring the preservation of the product's technological properties, such as shape, density, and cooking stability, while improving its nutrient composition. Changes in the organoleptic and physicochemical characteristics of pasta products containing pumpkin puree were assessed, enabling identification of the best parameters for industrial production. A promising technology is proposed that can be used in the industrial production of functional pasta products using plant-based raw materials.

In the context of a rapidly growing elderly population, one of the key priorities is the development of specialized food products that support health maintenance, prevent age-related diseases, and provide nutritionally adequate diets. The aim of this study was to develop a gerodietetic meat semi-finished product technology using plant-based ingredients – bulgur flour and zucchini – known for their high nutritional and biological value. Three formulation variants were developed, differing in the percentage ratio of animal and plant-based raw materials. The samples were evaluated by sensory analysis using a scoring system (appearance, color, smell, taste, texture) and by determining their chemical composition. The results showed that the inclusion of plant ingredients improves the sensory qualities of the product, reduces fat content, and increases the levels of dietary fiber, vitamins, and minerals. The best performance was observed in sample No. 2, containing approximately 20% plant ingredients. The proposed formulation offers an optimal balance of sensory and nutritional properties, making it suitable for implementation in the production of gerodietetic meat products. Given its balanced composition and high consumer appeal, it is also appropriate for use in institutional catering systems and in the production of functional foods targeted at elderly nutrition.

This article discusses the importance of the application of plant proteins in meat products, with a particular focus on meat pâté production. The nutritional value of plant proteins and their role in the composition of meat products are analyzed. The organoleptic characteristics of pâtés enriched with plant proteins, including taste and texture, as well as aspects related to their shelf life, are examined. The article identifies the opportunities for enhancing the nutritional value of pâtés through the incorporation of plant proteins and describes the technological stages of the production process. The effects of different types of plant proteins on the quality of pâté products are considered, and current scientific research in this field is systematized. Methods aimed at ensuring ecological safety and improving the beneficial properties of products are proposed. Furthermore, conclusions are drawn regarding the market prospects of plant-protein-enriched pâtés and their contribution to the Sustainable Development Goals. These technologies not only increase environmental safety but also promote the efficient development of the food industry in the future. Pâtés enriched with plant proteins enhance the nutritional value of products while simultaneously improving the economic efficiency of production. The functional properties of such products exert a positive effect on consumer health and reinforce their competitiveness in the market.

The article presents the results of comprehensive studies aimed at improving the efficiency of citric acid recovery from a fermentation broth obtained using the Aspergillus niger R5/4 strain. Particular attention was paid to evaluating the impact of different ozonation regimes, applied at the equipment sterilization stage, on the microbiological purity and stability of the fermentation process. Optimization was carried out for the key stages of the technological process, including neutralization, clarification, evaporation, and crystallization. It was established that ozonation at a concentration of 200 ppm, with a feed rate of 10 g/min and a residual content of 1 ppm, ensured the maximum yield of citric acid, whereas sterilization without ozonation resulted in decreased efficiency. The optimal parameters of subsequent processing stages were identified: neutralization with calcium carbonate (CaCO₃) at a concentration of 75 g/L and 50 °C, as well as clarification at 20 °C with 1.5 h of stirring. The combination of these factors enabled achieving a citric acid yield of 91.6%. The obtained results scientifically substantiate the effectiveness of combining ozonation with subsequent processing stages, providing a practical basis for improving citric acid production at the industrial level. This, in turn, paves the way for the development of new solutions aimed at enhancing the stability and economic efficiency of biotechnological production.

This article examines the main factors of the food legislation of the Republic of Kazakhstan. The main regulatory legal acts and processes of certification and standardization of food products regulating the safety and quality of food products in the country are also considered. The production processes and packaging are described, as well as the requirements for them. Special attention is paid to control mechanisms at all stages – from production to sale of food, as well as consumer protection issues.
In addition, the features of the implementation of international standards such as ISO 22000 and the HACCP system as a quality and safety assurance tool are analyzed. The role of state policy in the formation of an effective food industry control system, including educational work among producers and consumers, is emphasized. The problems of food traceability and the need to integrate modern digital solutions into quality monitoring are also considered.
The article highlights the importance of interaction between all participants in the food chain and the need for interagency cooperation. In conclusion, it is concluded that it is necessary to constantly update the legislative framework, taking into account international requirements and practices, in order to increase the competitiveness of domestic products in the domestic and foreign markets. The issues of food traceability and the need to integrate modern digital solutions into quality monitoring and risk management at all stages of production and storage are also considered. The article highlights the importance of interaction between all participants in the food chain and the need for interagency cooperation, as well as the training of qualified specialists in the field of food safety.
In conclusion, it is concluded that it is necessary to constantly update the legislative framework, taking into account international requirements and practices, in order to increase the competitiveness of domestic products in the domestic and foreign markets.

Due to the valuable properties of oil extracted from seeds, its use in the food industry is constantly expanding. This, in turn, stimulates active study of by-products of oil production - oilcakes and meal obtained from oilseed crops such as safflower and flax. These residues are a source of bioactive compounds (protein, dietary fiber, antioxidants) with beneficial health properties that can be used in the production of meat products. Utilization of these wastes allows solving ecological and economic problems. Safflower and flax cakes, rich in healthy substances, are considered as promising sources of vegetable protein, dietary fiber and antioxidants. Studies show that these by-products can be successfully utilized in the production of food products with improved nutritional and functional characteristics. This approach promotes sustainable development, the creation of innovative functional products and the realization of zero-waste principles. This work is devoted to analyzing the composition of flax and safflower cakes and studying the possibility of their use in the production of cooked sausage.
To achieve this goal, the possibility of using safflower and flaxseed meal in the production of cooked sausages was investigated, which would be a solution for reducing food waste. Organoleptic evaluation is given, physico-chemical and bacteriological parameters are determined, which testify to the conformity of the obtained products to the established requirements in the current normative documents.
During the study, 2%, 4%, and 6% safflower and flaxseed meal were added to the cooked sausage recipe.
The results of the organoleptic analysis showed that the samples with 4% meal added had the most harmonious taste and aroma.
According to the physical and chemical analysis, the sausage with 4% safflower meal contained 71.35±1.2% moisture, 10.58±0.1% fat, and 15.76±0.2% protein, while sausage with 4% flaxseed meal contained 70.69±1.4% moisture, 11.18±0.2% fat, and 16.65±0.1% protein.
Microbiological studies showed the absence of Escherichia coli, Salmonella, and sulfite-reducing Clostridia.
These results confirmed that the use of 4% safflower and flaxseed meal improves the quality of the finished product and its nutritional value.

The article presents the results of a study aimed at a comparative analysis of postbiotic isolation methods and determining the yield and antioxidant activity of preparations obtained from Lacticaseibacillus sp., Leuconostoc sp., and Saccharomyces sp. strains isolated from traditional fermented products (shubat, sauerkraut, and kumiss). Based on an analysis of literary sources, three methods were selected for experimental studies: thermal cell inactivation, ethanol precipitation, and ultrafiltration, characterized by technological simplicity, cost-effectiveness, and the ability to preserve biologically active components. The yield of postbiotics was determined gravimetrically, antioxidant activity by DPPH and ABTS tests, and microbiological safety by the absence of viable cell growth. It was found that the thermal method provides the highest dry matter yield (90-92%), high antioxidant activity (86-89%), and complete microbiological safety compared to other methods. A gentle inactivation regime (70°C for 30 min) preserved functional metabolites without destroying low-molecular-weight antioxidants and exopolysaccharides involved in redox processes. The highest activity values were obtained for the Leuconostoc sp. strain, which is due to the presence of an exopolysaccharide matrix stabilizing the active compounds. The obtained results confirm the feasibility of thermal inactivation as an effective and affordable method for isolating postbiotics for the development of functional dairy products and the expansion of biotechnological approaches in the food industry.

The work is devoted to the study of inhibitory factors limiting the yield of biohydrogen during the processing of lignocellulosic biomass (LCB). In this context, dark fermentation is considered one of the most promising biological methods for producing hydrogen, since it does not require an external energy source, is compatible with modern reactor technologies and allows the use of a wide range of substrates. The main barrier to its industrial application remains the accumulation of toxic compounds formed during the pretreatment of LCB and during fermentation. The work summarizes information on the composition and action of the main inhibitors. The results of the analysis showed that the yield of H₂ during TF reaches 2-4 mol/mol sugar (maximum ~3.8 mol/mol hexose), but drops significantly in the presence of: (i) furans (furfural 0.03-8.23 g/l; 5-HMF 0.09-1.59 g/l), (ii) phenolic compounds of lignin (vanillin, syringaldehyde), (iii) organic acids (formic, acetic, levulinic), (iv) inorganic ions and heavy metals (Zn, Cu, Cr, Ni, etc.), (v) ammonia and sulfates. Dosedependent effects and changes in microbial community composition are also discussed, such as the effect of pH, the reduction in Clostridium abundance due to furfural, or the increase in Clostridium and Ruminococcaceae abundance with the addition of 5-HMP. Thus, understanding the mechanisms of action of inhibitors and finding ways to reduce their impact are key areas for improving the efficiency of dark fermentation and its implementation as a sustainable technology for converting lignocellulosic biomass into biohydrogen.

In modern research on functional foods, special attention is paid to the development of composite ingredients capable of enriching the diet with protein, vitamins, minerals and biologically active compounds. In this work, a comprehensive analysis of composite flour obtained from flax and hemp meal in a 1:1 ratio was carried out in order to evaluate its physico-chemical characteristics, vitamin and mineral composition, amino acid profile and antioxidant activity, as well as to determine the potential for use in functional and fortified foods.
The results of the study demonstrated that composite flour has a significantly higher fiber content – 11.03 ± 0.13%, compared with premium wheat flour (0.1-0.15 ± 0.02%). The analysis of the vitamin composition showed the presence of significant amounts of vitamin E (92.02 ± 0.96 mg / 100 g) and B vitamins (B1, B2, B3, B5, B6, folic acid), the content of which is many times higher than wheat flour. The mineral profile is characterized by an increased content of iron (11.70 ± 0.14 mg/100 g), magnesium (256.7 ± 3.1 mg/100 g), calcium (200.17 ± 2.41 mg/100 g), phosphorus (582.10 ± 6.98 mg/100 g) and zinc (3.56 ± 0.04 mg/100 g), and the presence of iodine (0.0069 ± 0.0001 mg/100 g) expands the range of trace elements.
Amino acid analysis showed a high content of essential and conditionally essential amino acids, including arginine, lysine, leucine, isoleucine, valine and methionine, which confirms the high biological value of the protein. Composite flour also has a pronounced antioxidant activity, providing protection of lipid and protein structures from oxidative processes.
The results obtained indicate the expediency of using composite flour from flax and hemp meal in formulations of functional, fortified and preventive food products, including meat products, in order to increase nutritional value, improve technological properties and prolong shelf life.

Currently, a significant portion of non-wood plant materials, particularly agricultural waste, is not effectively utilized and is primarily left in fields or disposed of through incineration, resulting in significant negative environmental impacts. The problem of agricultural waste recycling is particularly acute in regions (Kazakhstan, China, India, and the CIS countries) where the production of cereals and grains is the primary industry upon which their livelihoods are built. The main advantage of non-wood raw materials is their annual reproducibility and low cost. At the same time, annual plants are a source of a number of valuable natural products, including cellulose. This article presents the results of a study of the morphological structure and chemical composition of wheat straw. The analysis results demonstrate the high potential of this type of lignocellulosic raw material for the direct production of cellulose without the need for preliminary extraction of the wood component. The mineral composition of wheat straw was also studied, revealing the presence of vital macro- and microelements, such as potassium, magnesium, calcium, phosphorus, aluminum, and silicon. The established ratio of these elements indicates the potential of this type of raw material for producing cellulose suitable for further chemical modification.

This article discusses the potential use of milk thistle and milk thistle seed extract to improve the quality characteristics of low-calorie meat products.
Milk thistle (Silybum marianum) is a plant rich in biologically active substances, especially the silymarin complex, known for its hepatoprotective properties. In the course of the study, its effect on the chemical composition, nutritional value, and functional properties of the final product was comprehensively examined by adding sunflower extract and seeds.
During the experimental work, a comparative analysis of the samples was conducted, and the content of proteins, fats, carbohydrates, and energy value were determined. In the samples with milk thistle additives, an increase in the concentration of biologically active substances and an improvement in the functional properties of the product were observed. In addition, positive results were recorded for organoleptic indicators, demonstrating a favorable effect on consumer perception.
The study proved that sunflower and milk thistle seed extracts are effective ingredients that in-crease the nutritional and biological value of low-calorie meat products. The use of such additives allows the product to be classified as a functional food, provides scientific justification for its inclusion in the daily diet, and enables the choice between milk thistle seed suspension or extract.

The article presents the results of a study aimed at enhancing the safety and quality of a popular foodservice product – Philadelphia sushi. The relevance of this study is driven by the expanding production and consumption of Japanese cuisine products, as well as the associated microbiological hazards arising from the use of perishable ingredients. The main objective of the work was to develop and substantiate a structure for managing the safety of food products based on HACCP principles, with a focus on the critical control points (CCPs) of the production process.
The study employed methods of hazard analysis, CCP identification using a «decision tree», as well as the establishment of critical limits and corrective actions. A thorough analysis of the technological cycle, which included 16 stages and 54 operations, initially identified 11 CCPs.
For practical implementation, the system was optimized to four of the most important control points: acceptance of raw materials, storage of rice and fish semi-finished products, the manufacturing process, and storage of the finished product. For each CCP, strict critical limits for temperature, storage duration, and microbiological indicators were defined, and monitoring procedures were developed.
The scientific and practical significance of the study lies in the development of an adapted and effective HACCP plan, the implementation of which substantially reduces microbiological risks, ensures consistent quality and safety of the finished dish, and proves to be economically viable for foodservice enterprises.

This study presents the results of isolation and comprehensive characterization of lactic acid bacteria and yeasts obtained from traditional Kazakh fermented beverages – kumis and shubat. Cultural, morphological, and biochemical properties of the isolates were examined, and their species identification and potential for carbohydrate fermentation were evaluated. Lactic acid bacteria were cultivated on MRS medium, and yeasts on Sabouraud agar supplemented. Identification was performed using Gram staining, colony morphology, microscopy, and biochemical tests. The ability of strains to ferment glucose, lactose, sucrose, maltose, and mannitol was assessed. The isolates were preliminarily identified as Lactobacillus plantarum, L. sakei, Candida kefir, and Kazachstania unispora. The most active strains showed the ability to ferment multiple carbohydrates with gas and sediment formation, indicating their potential for inclusion in starter cultures. The results confirm the biotechnological value of the native microflora and its promise for developing authentic starter cultures for dairy production.

This article focuses on the possibility of using local wild fruits and berries, namely wild cherry, spiky irga and red mountain ash, in the production of milk dessert – ice cream. The indicated raw materials of plant origin are characterized by a high content of pectin substances with gelling, astringent and foaming properties, which are important for the formation of the necessary rheological properties of desserts. In addition, pectin substances are capable of forming complexes with harmful substances (heavy and radioactive metal ions) entering the body from the outside and removing them, preventing them from being absorbed into the blood and without disturbing the balance of the internal environment; antibacterial properties that prevent the development of infectious diseases, suppressing the development of harmful microorganisms; a large number of vitamins that have a restorative effect. on the human body.
The results of the conducted studies on the effect of the proposed composition of vegetable origin on such important qualitative indicators of milk dessert – ice cream as the degree of whipping and the melting rate of the product are presented. Since it is these indicators that form a stable consistency of your favorite delicacy, on which the taste perception and tenderness of the frozen product depend without causing hypothermia of the oral cavity. Based on the data obtained, the optimal amount of the additive was determined from dried powdered irga berries and fruits of wild cherry and red mountain ash. The rheological parameters studied were also studied in the finished milk dessert. The results obtained indicate that the ice cream meets the requirements set out in the current regulatory and technical documentation.
The prospects of creating milk processing products enriched with natural ingredients that can replace artificial additives and some expensive dairy raw materials without reducing the quality characteristics of finished products are presented.

It is known that classic cottage cheese has a more or less sour taste, which does not always satisfy the consumer's request. Therefore, cottage cheese with a more delicate taste and low acidity is in high demand. Today, a modern approach to science in the field of biotechnology makes it possible to regulate the taste of cottage cheese using starter cultures that improve the nutritional value of the final product.
The article discusses the improvement of technology for the production of viscoplastic fermented milk products using the example of cottage cheese from goat's milk. The technology development is based on minimizing thermal effects and the use of low-acid-producing probiotic strains of domestic origin (Lacticaseibacillus paracasei, Lactococcus lactis, Bifidobacterium spp.) adapted to the fermentation of goat's milk. The key stages of the technological process have been optimized, including the preparation of raw materials, normalization, pasteurization, selection and use of starter cultures, as well as fermentation modes. The result is a soft curd product with a delicate texture, moderate acidity (about 68°C), pleasant organoleptic characteristics and high biological value. It was found that a consortium of L.paracasei Gch 5.2.1 and L. lactis 7-8 M strains ensures stable quality, probiotic activity and preserves the nutritional properties of raw materials. The developed technology is adapted to the conditions of small-scale production and is recommended for the production of functional and dietary products, including for children and people with gastrointestinal diseases.

The study presents an assessment of the quality of feeds (silage and haylage) and biochemical parameters of blood in dairy cows under experimental farm conditions. Four feed samples (two alfalfa haylage samples, a grain haylage, and corn silage) and 12 blood samples from lactating cows were analyzed. All examined feeds met regulatory requirements for fermentation and nutritional characteristics: optimal moisture content, predominance of lactic acid over acetic acid, low butyric acid content (<0,1%), reduced ammonia nitrogen levels, and absence of spoilage signs. The biochemical profile of serum samples was within physiological norms: total protein 75-79 g/L, glucose 2.4-2.8 mmol/L, urea 3.2-3.9 mmol/L, and liver enzyme activity (ALT, AST) slightly exceeded reference values. The obtained data indicate stable metabolic processes and a normal physiological state of cows when fed high-quality silage and haylage. It was concluded that the nutritional value of the prepared feeds fully meets the cows’ requirements without causing metabolic disorders: the rations are balanced, as evidenced by normal blood biochemical constants and high milk productivity.

This paper examines an individual pulverizing system with a hammer mill and direct injection, serving a hot water boiler of the KVT–116.3–150 type. The relevance of the study lies in the crucial role of fuel pulverization in ensuring stable, efficient, and environmentally safe operation of coal-fired boiler plants.
A functional diagram of the pulverizing system is presented, covering drying, grinding, classification, and conveying of the air-fuel mixture to the boiler burner. The schematic provides a clear representation of the equipment interconnections, identifies key technological nodes, determines the paths of heat carrier, air, and fuel movement, and highlights zones most sensitive to operational parameters. This lays the foundation for further analysis of thermal efficiency and potential optimization reserves.
During the operation of the system, key parameters were recorded: the temperature of the air-fuel mixture at the mill outlet did not exceed 85 °C, the coal dust fineness was R₉₀ = 45 ÷ 55%, and the fuel moisture and consumption values corresponded to the operating charts. The data analysis confirmed the stability and efficiency of the system under boiler load variations in the range from 60% to 100% of the nominal capacity.
Special attention is given to the design and technological features of the equipment: the hammer mill with an integrated separator, a recuperative air heater, a downward drying unit, the air supply system, and control elements. Advantages of the individual system include enhanced automation, reduced heat loss, flexible operation control, and adaptability to variable loads or unstable fuel characteristics.
Recommendations are made for optimizing the drying process and implementing a monitoring system for the mill and separator condition. The study concludes that the system is technologically complete, efficient, and promising for retrofitting existing solid fuel-fired boiler units.

The article provides an overview of a number of studies on the use of alloys and intermetallic compounds for hydrogen storage. Among them, a particularly important place is occupied by the inter-metallic compound LaNi₅ eye. The latest achievements in the development of intermetallic compounds of the AB₅-type are analyzed. These compounds, in particular LaNi₅ and its alloyed counterparts, are widely used due to the ability to regulate their properties by replacing elements. The article also provides an overview of the methods of synthesis and modification of AB5 alloys aimed at improving their efficiency in hydrogen technologies. Both traditional production methods and modern technological approaches, including Spark plasma sintering and mechanical activation, are considered. A review of the scientific literature has shown that mechanical activation is an effective way to modify the LaNi₅ intermetallic compound to improve its hydrogen absorption properties. According to a number of studies, the effect of high-energy ball milling leads to significant changes in the microstructure of the material. It is shown that to increase the effectiveness of practical applications of LaNi5 in hydrogen energy, additional comprehensive studies are needed to establish the relationship between mechanical processing parameters, structural characteristics, and functional properties of the material.The aim of this work is to use mechanical activation to modify the microstructure of a material, reduce the size of crystallites, increase the density of defects, and promote the formation of amorphous or nanostructured states, which together can significantly affect the structure and interactions with hydrogen.

Enhancing the efficiency of heat transfer processes remains one of the key challenges in modern energy and thermal engineering. Conventional working fluids, such as water and ethylene glycol, are limited in terms of thermal conductivity and heat capacity, which reduces their potential under high heat flux conditions. One of the promising approaches is the use of nanofluids – suspensions of nanoparticles in a base liquid that can modify its thermophysical properties and improve heat transfer performance.
This study presents a numerical investigation of the flow of water and TiO2-CuO nanofluid in a Ushaped tube channel under a constant heat flux. Computational fluid dynamics (CFD) was applied to analyze the distribution of turbulent kinetic energy (TKE), pressure variations along the channel, as well as integral heat transfer parameters: the heat transfer coefficient and heat absorption.
The results showed that water exhibits higher turbulent activity, with maximum TKE values reaching 1.9·10-3 m2/s2, while the overall pressure drop is about 230 Pa. Its relatively low thermal conductivity (0.6 W/m·K) leads to a temperature rise of 5-7 °C at the outlet. For the TiO2-CuO nanofluid, turbulence intensity decreases on straight sections (10-6-10-5 m2/s2) and the pressure drop increases up to 270 Pa due to higher viscosity. However, improved thermophysical properties – thermal conductivity (0.702 W/m·K) and density – ensure more effective heat removal, with outlet overheating reduced to 4-5 °C.
Comparative analysis of heat absorption and the heat transfer coefficient revealed the advantage of the nanofluid: h=68.3 W/(m2·K), Q=143 W compared with water (h=67.6 W/(m2·K), Q=141.8 W). These results indicate that TiO2-CuO nanofluid provides higher heat transfer efficiency with an acceptable increase in hydraulic losses, making it a promising coolant for compact and high-load thermal systems.

This paper presents a comparative study on the grinding efficiency of non-design Karazhyra coal using two main types of milling equipment: ball mills and hammer mills. The research was conducted to assess the suitability of local fuel for combustion in boiler units not originally designed for this type of coal. Laboratory sieve analysis was performed to determine the particle size distribution of the pulverized fuel. For the first time, polydispersity coefficients for Karazhyra coal dust, processed in both types of mills, were obtained and analyzed. Sieve residue measurements showed that in the product of the hammer mill only 0.2% of particles remained on the 400 µm sieve, whereas in the product of the ball drum mill this value was 2.5%. This indicates an almost complete elimination of coarse fractions during grinding in the hammer mill. It was found that with both grinding methods about 88% of coal dust particles are smaller than 200 µm. At the same time, the residue on the 90 µm sieve was 32% for the ball drum mill and 53% for the hammer mill. Thus, the hammer mill product is characterized by an increased proportion of medium-sized particles (90-200 µm) in the absence of an excessive amount of ultrafine fractions. The absence of coarse and ultrafine fractions during grinding in the hammer mill contributes to the formation of a higher polydispersity index of coal dust, which was 1.51, whereas for the ball drum mill it was only 0.78. The findings suggest that both mills are suitable for fuel preparation, but the hammer mill ensures better combustion quality and thermal efficiency. Therefore, it is recommended as the more effective solution for the preparation of non-design coal in thermal. The conducted studies serve as a basis for further study of the characteristics and behavior of nondesign coal in various operating modes.

This article presents an assessment of the performance of a vapor-compression refrigeration system under shock thermal load. The study was carried out on a modernized experimental stand «Kholodilnik-2» equipped with a digital monitoring system, including 24 DS18B20 sensors and an STM32 microcontroller. The main objective was to compare the system behavior when introducing an object with temperatures of 40, 60, and 80°C after reaching a quasi-steady-state mode. Temperature curves, transient process duration, and stabilization times were analyzed. Additionally, features of temperature distribution inside the freezer compartment and the influence of thermal load on the main elements of the cycle were examined.
The scientific novelty of the study lies in the comprehensive analysis of transient processes occurring under sudden thermal impacts, with a focus on their duration and system stability. The practical significance of the work is related to the possibility of applying the obtained results to optimize the operating modes of refrigeration systems and to diagnose faults under conditions close to real operation. The optimal regime was found at 60°C, which ensures a balance between transient process duration and uniformity of temperature distribution.

Chronic wounds pose a serious challenge to modern medicine. There is now a trend towards an increase in the number of patients with diabetic foot wounds. Therefore, the development of dressing materials with ideal characteristics is one of the key tasks in modern medicine. Cellulose is a promising material for the development of wound dressings due to its biocompatibility, availability and environmental friendliness. The aim of this article is to review the studies on hydrogels and films based on cellulose derivatives and its compositions for wound covering published in the scientific literature over the past decades. Particular attention is paid to materials containing bentonite and its influence on the mechanical, sorption and biomedical properties of dressings. An analysis of domestic and foreign studies devoted to composite materials based on carboxymethyl cellulose (CMC) and bentonite was conducted. Analysis of the research available to date shows that the introduction of bentonite into polymer matrices helps to increase the mechanical strength, moisture absorption capacity and structural stability of the coatings. The inclusion of clay particles allows for the regulation of the release of medicinal substances, thus increasing the effectiveness of the therapeutic effect. Studies conducted by Kazakhstan scientists confirm the potential of using local bentonite clays in the development of dressings. The development of composite hydrogels and films based on cellulose and bentonite derivatives opens new possibilities for creating effective biocompatible wound dressings. Further research should be aimed at optimizing their composition and structure to improve functional characteristics and therapeutic effectiveness.

The production of low-carbon ferrochrome is inevitably accompanied by the formation of significant volumes of slags, the key feature of which is their ability to spontaneously disintegrate upon cooling and exposure to atmospheric factors. This phenomenon is caused by polymorphic transformations of β-dicalcium silicate (C2S) into the γ-modification, accompanied by an increase in volume. This unique characteristic, on the one hand, creates challenges in waste management, on the other hand, it opens up wide opportunities for their efficient and cost-effective disposal without the need for expensive crushing. This review article is a systematic analysis and generalization of modern high-performance world-class technologies for the use of self-decaying slags produced by low-carbon ferrochrome. Special attention is paid to their use in the production of building materials (cements, concretes, binders), sorbents for water treatment, ameliorants for agriculture, as well as in road construction. This paper provides a literary review of fifty-seven sources published over the past ten years describing the most effective technologies for the use of self-decaying slags for the production of low-carbon ferrochrome.
The purpose of the article is to demonstrate the potential of these slags as valuable secondary raw materials that contribute to reducing the environmental burden, increasing the resource efficiency of ferroalloy production and developing the principles of circular economy.

A study has been conducted on the quality of drinking water in villages located in the zones of extreme (Dolon, Bridge, Cheryomushka, Sarzhal) and maximum (Karaul, Kainar) radiation risks in the territory of the Abai region adjacent to the former Semipalatinsk test site. The aim of the work was to evaluate water by indicators of total mineralization (TDS) and the content of basic cations (sodium, potassium, calcium, magnesium). The analysis of samples taken from the central water supply systems showed that in three settlements (Sarzhal, Kainar, Dolon) the total mineralization exceeds the WHO recommended limit of 1000 mg/l, reaching 1500 mg/l in the village of Dolon. In all the villages studied, except Cheryomushka, an increased sodium content was recorded, while in the villages of Kainar and Dolon its concentration exceeds the established maximum permissible concentration of 200 mg/l. The total hardness of the water in most samples meets the standards, with the exception of the water sample from the village of Dolon, where the water is classified as hard. The water in the village of Cheryomushka, which does not have a central water supply, is characterized by a physiologically insufficient calcium content. The results indicate an unsatisfactory quality of drinking water in most of the studied settlements of the radiation risk zone.

In the present work, a study was conducted on the spectral characteristics of the electric discharge during the electrolytic plasma nitriding process, as well as the structural and phase changes occurring in austenitic stainless steel. The treatment was carried out in an electrolyte containing 10% soda ash (Na₂CO₃), 20% carbamide (CO(NH₂)₂), and 3% ammonium chloride (NH₄Cl) at a temperature of 550 °C for 10 minutes. Emis-sion spectroscopy revealed the presence of active nitrogen species (N₂⁺, N I), hydrogen (Hα), and oxygen (O I) in the plasma composition. The calculation of electron density based on the broadening of the Hα line from the Balmer series yielded a value of ap-proximately 8.5 × 10¹⁸ cm⁻³. X-ray phase analysis revealed the formation of nitride phases CrN and Fe₃N, as well as a solid solution of nitrogen in γ-Fe. Microstructural investigations using SEM revealed a three-layer structure of the nitrided layer: a ni-tride zone, a transition region, and the original austenitic matrix. Energy-dispersive X-ray analysis confirmed the presence of a nitrogen concentration gradient with depth.

In the context of the increasing accumulation of agricultural and food bio-waste (grain husks, straw, corn stalks, etc.), the development of efficient and environmentally safe processing technologies is a highly relevant task. The study analyzes modern methods of biomass utilization, including composting, anaerobic digestion, biopolymer production, and the manufacture of construction materials. Pyrolysis has been selected as the primary processing technology, as it enables the production of a wide range of products – biochar, liquid and gaseous fuels – that can be potentially applied in agriculture, energy, and industry. The chemical composition of the initial bio-waste (cellulose, lignin, ash-forming elements) is characterized, and the methods of their preparation (drying, grinding, pretreatment) are discussed. The results of laboratory studies are presented, confirming the effectiveness of pyrolysis in producing valuable products. A comparative assessment with existing analogues has been carried out, along with an analysis of the environmental benefits (reduction of CO₂ and CH₄ emissions, decrease in landfilled waste volumes) and an economic evaluation of the prospects for industrial implementation. It is shown that bio-waste processing by pyrolysis has high practical significance for addressing resource conservation and environmental protection challenges. The study demonstrates the potential applications of the obtained products as organic fertilizers, energy sources, sorbents, and components of construction materials. Promising directions for further research are identified, including combined processing technologies and the expansion of the spectrum of target products.

This article presents a study of the problem of polyethylene re-utilization (its secondary processing – recycling) by rotational molding. In scientific literature, recycling of rotational grades of polyethylene (RPE) is very poorly studied, and the data presented are often contradictory. However, for the production of containers by rotational molding, using secondary polyethylene in industry, it is necessary to take into account its degradation (occurring under recycling conditions), for the assessment of which the authors used the following methods: IR spectroscopy, atomic force microscopy, study of the hydrophobicity of the RPE surface (by measuring the contact angle (CAA)) and mechanical tests. In view of the widespread use of these containers (for storing mineral fertilizer, grade KAS28), the CAA of RPE with distilled water (after exposure to KAS28) was studied under various technological modes of their processing (PIAT indicator). It is shown that recycling of RPE leads to the formation of carboxyl groups on the surface of polyethylene and a significant increase in its hydrophilicity (the contact angle decreased to 36%). Keeping KAS28 also increases the hydrophilicity of products made of secondary and primary RPE (reduction in the contact angle from 8% to 28%) regardless of the processing parameters considered. It is shown that the most influential factor (of those studied) on the hydrophilicity of RPE is recycling. It was found that at a dosage of up to 15-25% of secondary polyethylene in composites, only minor changes in the strength characteristics (tensile strength and deformation) are observed, which allows us to recommend partial substitution of primary raw materials without critical losses in performance properties (with secondary polyethylene). This opens prospects for the economically feasible use of secondary PE in the production of rotational composites. This study can be used to assess the degradation of RPE during its recycling and improve the performance properties of finished products.

The scientific study is devoted to the assessment of phytotoxic effects of petroleum products, in particular hydrocarbon rocket fuel (HCF), on plants. Under laboratory conditions, radish (Raphanus sativus L. var. sativus) was used as a test subject. The reason for the work was the necessity of ecological assessment of soils contaminated in the areas where rocket carrier parts fall.
The main task was to determine the relationship between the degree of soil contamination by HCM and changes in morphophysiological parameters in the indicator plant. Five soil variants were used in the study: three experimental ones with HCV content in concentrations of 100, 500 and 1000 mg/kg, as well as two control samples – a standard artificial soil reference (ASR) and soil from a real contaminated area (CA). Biotesting was carried out for six weeks. During the experiment, germination, stem and root lengths of seedlings were recorded and toxicity indices were calculated.
The results demonstrated the depressing effect of UHG on plant development and seed germination. At minimum concentrations of 100 mg/kg, only a slight reduction in shoot and root length was observed. However, when the concentration was increased to 500 and 1000 mg/kg, the negative effect became more pronounced: seed germination decreased to 40% and 25%, respectively, and the length of stems and roots decreased 2-4 times compared to control samples.
The observed changes clearly indicate the dose-dependent nature of UHG toxicity. The obtained data are of practical value for the development of pollution assessment standards, environmental monitoring and planning of measures for the restoration of the affected territories.

The study evaluated the performance of natural zeolite and its modified forms for removing the stable iodine isotope (^127I) from aqueous solutions. The natural zeolite was modified with silver (Ag⁺) and copper (Cu²⁺) ions via an ion-exchange method. The structure and chemical composition of the modified samples were characterized by X-ray fluorescence (XRF), X-ray diffraction (XRD), and scanning electron microscopy coupled with energy-dispersive X-ray analysis (SEM-EDX).
Kinetic experiments showed that the Cu-modified zeolite reached sorption equilibrium faster than its Ag-modified counterpart. The time to equilibrium was approximately 30.5 h for the Cu-modified zeolite and about 36.0 h for the Ag-modified sample. In both cases, iodine removal from aqueous solutions was high: 99.4% for the Cu-modified zeolite and 99.1% for the Ag-modified zeolite.
Analysis of the adsorption isotherms indicated that the data were best described by the Langmuir model, with a coefficient of determination R² > 0.98. The calculated maximum sorption capacity of the modified zeolites exceeded that of the natural zeolite.
These results confirm that metal-modified zeolites are highly effective and environmentally safe sorbents for the removal of iodine-containing contaminants from water. Of particular practical interest is the Cu modification, which exhibits improved sorption kinetics and is therefore promising for water treatment technologies.

The paper discusses current trends in the development of geopolymer composites as an environmentally sustainable alternative to Portland cement. An analysis of raw material sources for geopolymerization is presented, including natural aluminosilicate materials and industrial by-products such as fly ash, blast furnace and ferroalloy slags, red mud, and other residues from energy and metallurgical industries. The main stages and mechanisms of geopolymerization are described, as well as the influence of alkaline activators and synthesis parameters on the formation of the structure and properties of the materials. It is shown that geopolymer composites exhibit high strength, thermal stability, and chemical resistance with a significantly lower carbon footprint, making them promising for use in construction and industrial waste recycling.
It is noted that the Republic of Kazakhstan possesses substantial reserves of both natural aluminosilicate rocks and secondary technogenic resources, which creates favorable conditions for the widespread implementation of geopolymer technologies aimed at reducing environmental impact and improving the efficiency of mineral resource utilization.

In this study, we investigated the selective sorption of neodymium ions from a mixture of solutions using interpolymer systems consisting of two industrial sorbents – Amberlite IR120(Н+) and AB-17-8(ОН-) ion exchange resins – in various molar ratios. Based on the obtained results, we found that maximum polymer activation occurs at an Amberlite IR120:AB-17-8 ratio of 5:1. These ratios yield the highest neodymium ion sorption. The sorption process was carried out in static mode. After 48 hours of remote polymer interaction, the maximum neodymium ion sorption was 56.2%, and the degree of polymer chain binding was 3.96%. The calculated values of the unactivated polymers demonstrated that the sorption activity of the interpolymer systems in the Amberlite IR120:AB-17-8 (5:1) and Amberlite IR120:AB-17-8 (3:3) ratios is significantly higher than that of the original unactivated polymers Amberlite IR120 (6:0) and AB-17-8 (0:6). The results demonstrate that the electrochemical and sorption properties of the original polymers are altered in the interpolymer systems, increasing the reactivity of the functional groups. This allows them to be used in the development of an effective sorption technology for the separation of neodymium ions. Thus, it is demonstrated that the interpolymer systems can be used in industry by varying the sorption conditions for the efficient extraction of neodymium from industrial solutions.