Almaty Technological University

Studies of the soils of the city of Semey were carried out in the winter and summer periods during 2024. Gross forms defined in soil are As, Co, Pb, Cu, Zn, Ni, Mn, V, Sr, Sn, Mo, Ba, Ti, Cr, Ag, Li, Nb, Be, Ga, Bi, P, Sc, Y; mobile forms: Pb, Ni, Zn, Cu, Co; and petroleum product content. The content of contaminants was determined by flame atomic absorption spectrometry. All pollutants were assessed for compliance with their regulatory indicators in the soil. The assessment of the state and degree of soil pollution is based on the values of the maximum permissible concentrations (MPC) of pollutants in soils. Calculations of indicators of total soil pollution with heavy metals were performed and risks were assessed. It was established that the degree of pollution of the soil cover of Semey is acceptable, the risk levels are from low to moderately local.

This study explores the development of smart electronic textiles (E-textiles) crafted from knitted fabrics, designed for everyday wear and specifically engineered to meet the needs of individuals with chronic conditions. We propose the design of a vest and knee braces equipped with heating elements and specialised sensors for monitoring human body temperature. The ergonomic structure of these garments ensures their suitability for both athletes during training sessions and for everyday wear. The products are made from wool yarn using various knitting techniques, including double jersey, press stitch, and 2x2 ribbing. During the development of the knee braces, samples of varying densities were examined, employing the double jersey technique. The edges of the braces were finished with ribbing to ensure secure fixation due to its superior dimensional stability. For the main section of the vest, a press stitch was selected, providing excellent shape retention, a three-dimensional texture, and enhanced thermal insulation—qualities that make it ideal for warm clothing. The lower part of the vest incorporates double jersey knitting to ensure structural integrity and facilitate the integration of electronic components. The heating elements and temperature sensors are integrated through specially designed openings formed during the knitting process using double jersey construction.

The article examines the process of developing innovative hospital patient clothing aimed at improving comfort, hygiene, safety, and functionality in inpatient conditions. A systematic analysis of existing patient clothing samples was conducted, identifying their main drawbacks, including limited mobility, difficulty of care, insufficient ventilation, low adaptability to various clinical and climatic conditions, as well as inconvenience for both patients and medical staff. Based on the research, a new model of patient clothing is proposed, featuring a modular access system, magnetic clips, and an adaptive ventilation panel that ensure ease of dressing, personalized microclimate adjustment, ergonomics, and enhanced overall comfort. A comprehensive survey was also conducted, and the results demonstrated the preferences of patients and medical staff regarding materials, color, ease of use, functionality, and hypoallergenic fabrics. The developed prototype is equipped with a digital identification system using a QR-code, providing simplified access to patient information and monitoring their condition, which increases the efficiency of medical staff. The novelty of this research lies in its comprehensive approach to designing hospital patient clothing, integrating medical, ergonomic, and technological solutions that contribute to improving the quality of patient care.

The article discusses the introduction of drought-resistant local feed sorghum as a substitute for widely used feed corn in compound feed for young fattening cattle. In the context of diversifying agricultural production and ensuring food security in Kazakhstan Republic, there is great potential for the development of feed grain crops. The feed sorghum market in Kazakhstan is developing rapidly, which is characterized by growing interest from the agricultural sector. Given the climate and the increase in arable land, feed corn is becoming an attractive alternative to traditional grain crops. Based on a study of grain and sugar varieties selected in Kazakhstan and abroad, an assessment of their main economic characteristics was carried out. The feed sorghum varieties “Volzhskoe 51” and “Sazhen” are distinguished by high productivity, maximum sugar content in the stem juice, as well as high dry matter and grain yields. These varieties are used by scientific institutions (breeding centers) as the main objects for creating new varieties in breeding and are offered to agricultural structures and farms in the North Kazakhstan region. Literature data indicate that sorghum is drought- resistant, has high nutritional value, and can replace other types of feed, contributing to the development of animal husbandry. The results of studies indicate broad prospects for the use of high-yielding sorghum varieties in various regions. The results of calculating the recipe for replacing corn with sorghum by 25%, 50%, 75%, and 100% in experimental compound feed for young animals for fattening showed that the feed unit index per 100 kg of feed in the experimental samples decreased compared to the control group but corresponded to the norm, and the amount of crude protein increased in the experimental groups compared to the control group.

This article examines the effect of propolis addition on the amino acid profile of soft cheese made from goat's milk. Ethanol propolis extract was added to the cheese in concentrations of 0.5%, 1% and 2%. Methods included high performance liquid chromatography for quantification of amino acids, microbiological testing for pathogen inhibition, physico-chemical analysis of product stability, and organoleptic assessment of consumer acceptability. The results show that propolis minimally changes the total amino acid content, but significantly increases the content of free amino acids (for example, proline by 8-15%, lysine by 4-8% and branched chain amino acids by 3-6%) due to improved microbiological stability and controlled proteolysis. Cheese retains a high level of essential amino acids, the ratio of total amino acids is 42-43%, which makes it suitable for dietary use in people with weakened immune systems or in need of high-protein nutrition. Propolis also prolongs the shelf life by reducing the growth of pathogenic microorganisms by 80-95%.

The aim of this study was to develop a diagnostic algorithm for assessing the technical condition of the lubrication system in KAMAZ diesel engines based on the analysis of used oil parameters. Experimental measurements were conducted to determine discrepancies between the actual and permissible (according to technical documentation) oil levels, as well as statistical calculations to evaluate the diagnostic value of specific parameters. The findings revealed that the maximum permissible oil volume in the KAMAZ-740 engine exceeds the nominal level by 30%, and in the KAMAZ-EURO engine by 24%. Statistical analysis identified the most informative diagnostic parameters as oil volume, viscosity, total base number, and flash point. Using the permissible values of the identified indicators, schematic plots were developed, each reflecting the current oil condition and enabling the identification of complex and combined faults. The results led to the development of a diagnostic algorithm for diesel engine lubrication system evaluation and a finite state machine method to predict critical oil levels and prevent typical problems and critical engine breakdowns. The projected annual economic benefit from implementing the developed diagnostic system amounted to USD 144,000 for a fleet of 2000 vehicles, based on an average annual mileage of 60,000 km.

Diabetes mellitus is a metabolic disease characterized by persistently elevated blood glucose levels and is a significant global public health problem. Wet cupping therapy is a complementary therapy that supports glycemic control, although community-based evidence is still very limited. This study was conducted to examine the short-term impact of wet cupping therapy on blood glucose levels in adults. This study used a pre-experimental, single-group pre-test-post-test design and was conducted in Wirobrajan Village, Yogyakarta, Indonesia, in April 2025. Thirty adults aged 26-45 years who were not receiving glucose-lowering medication were recruited using quota sampling. Blood glucose levels were measured before and immediately after one wet cupping therapy session. A paired-sample t-test with a significance level of p < 0.05 was used to look at the data. The mean blood glucose level dropped from 131 mg/dL before the intervention to 117 mg/dL after, a difference of 14.2 mg/dL. This drop was statistically significant (p = 0.0001). These findings indicate that wet cupping therapy significantly reduces short-term blood glucose levels in adults. Wet cupping therapy can be considered a complementary intervention for glycemic control. However, further randomized controlled trials are needed to confirm these findings.

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.

Kazakhstan’s growing potato industry underscores the need to develop and apply digital solutions that boost grading efficiency. A comparison between two traditional deep neural network architectures used to classify color images of potatoes from Kazakhstan is discussed in the paper. Ten representative varieties of Kazakhstani potatoes were selected as objects of study: Alians, Alians mini, Astana, Astana mini, Edem, Edem mini, Nerli, Nerli mini, Zhanaisan, and Zhanaisan mini. Two convolutional neural network (CNN) models, SqueezeNet and GoogLeNet, were refined via transfer learning employing three optimization approaches. Then, they were used to classify the potato images. A comparison of the two neural networks’ classification performance was conducted using common evaluation criteria—accuracy, precision, F1 score, and recall—alongside a confusion matrix to highlight misclassified samples. The comparative analysis demonstrated that both CNN architectures—SqueezeNet and GoogLeNet—achieve high classification accuracy for Kazakhstani potato varieties, with the best performance on Astana and Zhanaisan (>97%). The study confirms the applicability of lightweight CNNs for digital varietal identification and automated quality assessment of seed potatoes under controlled imaging conditions. The developed approach is the first comparative CNN-based varietal identification of Kazakhstani potato tubers using transfer learning and contributes to the digitalization of potato breeding, and provides a baseline for future real-time sorting systems using deep learning.