2026

Introduction: Canine parvovirus type 2 (CPV-2) poses a serious viral threat to dogs. Despite the potential contribution of companion animals to antimicrobial resistance, data on CPV and associated bacterial coinfections remain limited. This study aimed to characterize the CPV-2 epizootic situation in Kostanay (Kazakhstan), assess bacterial coinfections and AMR profiles, including molecular markers, and evaluate their relevance to One Health. Methods: Epizootiological monitoring revealed a CPV-2 positivity rate of 19.4% (n = 549). For microbiological and PCR studies, two groups were established: CPV-2+ (n = 198) and clinically healthy (n = 200) dogs. E. coli, Klebsiella spp., and S. aureus were identified by culture/MALDI-TOF; AMR was assessed by disc diffusion (CLSI). Resistance genes were detected by PCR: for Enterobacteriaceae, blaTEM, OXA, tetA/tetB, StrA/StrB, aadB, aphA1, qnr/qepA, and sul1/sul3; for S. aureus, blaZ, ermB/ermC, tetK/tetM, and mecA. Results: A total of 131 isolates were obtained (CPV-2+: 72; healthy: 59), predominantly E. coli (n = 65) and S. aureus (n = 53). CPV-2+ dogs tended to carry more gram-negative bacteria. Enterobacteriaceae were highly resistant to tetracyclines (58.4%) and fluoroquinolones (51.2%), and sporadic carbapenem resistance was detected in Klebsiella (7%). β-Lactamase determinants (blaTEM/OXA) and aminoglycoside resistance genes were more frequently detected in CPV-2+ isolates, whereas blaZ predominated in S. aureus. Conclusion: CPV-2 infection is associated with a significant bacterial burden and pronounced AMR, supporting the need for improved surveillance and empirical therapy optimization. These results fill a geographical data gap in Central Asia and align with AMR trends reported in Europe and Asia, underscoring the cross-border circulation of CPV-2 and resistant bacteria and the need for a One Health approach.

Sowing represents one of the most critical technological processes in grain production, where seed distribution uniformity directly impacts crop yield by determining plant nutrition area efficiency. Conventional sowing methods with varying row spacings often fail to ensure optimal area utilization. This study enhances subsoil-broadcast sowing quality through a novel trough-profile seed guide that ensures uniform seed distribution across the sweep opener’s working width. The research employed a combined methodology of theoretical analysis, DEM simulation, and experimental studies. Theoretical analysis demonstrated that sowing parameters depend mainly on seeder forward speed and the rotational speed of the seed-metering device’s rollers. DEM simulations visually confirmed the mechanism of ordered seed flow formation within the guide. Experiments simulated drill seeder operation, evaluating forward speed (1.2–2.4 m/s) and fluted roller rotational speed (20–25 rpm) effects on distribution uniformity and sowing instability. The results at 20 rpm with 2.0–3.0 grains per cell showed a standard deviation reaching 0.2–0.5 pcs. (CV: 13.0–24.2%). At 25 rpm, the deviation increased to 0.5–1.0 pcs. (CV: 18.2–39.4%). For total sowing instability at 20 rpm with 10.0–15.0 grains per opener, the standard deviation measured 0.3–3.3 pcs. (CV: 2.8–22.4%), while at 25 rpm, with 15.0–19.0 grains, values reached 0.5–3.9 pcs. (CV: 3.5–19.8%). All parameters conform to agrotechnical requirements, confirming solution effectiveness and addressing the literature gap in uniform seed distribution across the sweep opener’s working width.

The article presents a comprehensive review and experimental analysis of the development of unmanned systems designed for electronic reconnaissance (REI) tasks. It combines a global assessment of technological trends, engineering solutions, and patent activity in the field of UAV-based radio intelligence platforms with the results of a practical implementation of a prototype SDR-based measurement system. The study outlines structural architectures, modular payload configurations, autonomous navigation strategies, and the integration of artificial intelligence in signal detection and direction-finding. Particular attention is given to approaches for enhancing situational awareness through adaptive signal processing and GNSS-independent navigation. The experimental part demonstrates the design, calibration, and field testing of a multi-antenna SDR system for real-time direction-of-arrival (DOA) estimation. Comparative analysis confirms the system’s accuracy and viability, highlighting the feasibility of compact, low-cost radio intelligence solutions. The paper concludes with recommendations for further R&D in autonomous REI systems, emphasizing AI integration, modular design, and resilience to electronic countermeasures.

Computerized adaptive testing (CAT) systems face major challenges at the beginning of test administration, when limited response data produces unstable ability estimates and poor item selection. This cold-start problem reduces measurement precision and testing efficiency, especially for students whose abilities diverge from population norms. This study introduces a hybrid ability-estimation model that dynamically integrates neural network predictions with classical item response theory (IRT) estimation throughout the adaptive testing process. The neural component uses auxiliary student information-including demographics, prior performance, and early response patterns-to generate accurate initial ability estimates, while the IRT component preserves psychometric validity as response data accumulate. A dynamic fusion mechanism gradually shifts estimation weight from the neural model to the IRT model as more items are administered. Experimental validation on 2847 students across four subject domains shows that the hybrid approach reduces RMSE in ability estimation by 34.2% during the first five items compared with traditional CAT methods, while maintaining equivalent precision in later stages. The system also decreases the number of items required to reach target precision (SE < 0.3) by 28.7% on average, with the largest gains observed for students at ability extremes.

This article, based on archival materials from the Orenburg Region State Archives, analyzes a little-known episode: the 1914 “denunciation campaign” against the editorial board of the Kazakh newspaper “Kazak” and its leaders, A. Baitursunov and M. Dulatov. Using source analysis and discourse analysis of administrative documents, the authors demonstrate that denunciation in late imperial Russia was not only a form of private political persecution but also part of an institutionalized mechanism of colonial surveillance. Letters from “trusted Kyrgyz from the Turgai and Ural regions” sent to the Ministry of Internal Affairs and governor's offices demonstrate a strategy by which some of the local elite positioned themselves as loyal intermediaries between the “authorities” and the “ignorant masses”. The bureaucratic trajectory of these appeals – from local officials to the police department – is traced, revealing the depth of the inclusion of peripheral regions in the imperial surveillance system. A comparison of the texts of denunciations and official responses allows us to reconstruct the logic of imperial administrative culture, in which suspicion and denunciation became the primary instruments of control over the national outskirts.

Brucellosis continues to pose a substantial zoonotic risk in Kazakhstan; however, evidence describing the knowledge, attitudes, and practices (KAP) of cattle farmers and veterinary personnel remains limited. A cross-sectional study was undertaken between May and October 2024 across twelve administrative locations nationwide. Structured questionnaires were administered to 506 cattle farmers and 33 veterinary professionals, and the data were evaluated using descriptive analyses and univariable logistic regression. Awareness of brucellosis in cattle was relatively high among farmers, yet understanding of its implications for human health was markedly lower. In contrast, animal health workers demonstrated consistently higher levels of knowledge (OR: 12.6; 95% CI: 9.88–16.34; p < 0.001). Several practices associated with zoonotic transmission were commonly reported by farmers, including handling aborted materials without protective gloves, consumption of unpasteurised milk, and leaving reproductive tissues in grazing areas. Nevertheless, most farmers expressed readiness to adopt preventive measures, particularly cattle vaccination and the use of basic protective practices. These findings reveal important gaps between awareness and behavior that may contribute to continued transmission of brucellosis. Strengthening farmer education through locally tailored, One Health-based interventions offers a practical pathway to improving brucellosis control and enhancing cattle productivity in Kazakhstan.

The purpose of this article is to examine how documentaries produced by Kazakh television channels contribute to audience discussions and social discourse on YouTube, with particular attention to issues of culture, history, and politics. In the context of the rapid digitalization of Kazakhstan’s media landscape, television documentaries now circulate widely on YouTube and trigger new forms of social conversation, making the study of their impact on public opinion increasingly relevant. The research is based on a quantitative content analysis of official YouTube channels of Qazaqstan TV and Jibek Joly TV between June 2023 and June 2024. Using VidIQ analytics and official statistical sources, the study measured views, likes, comments, approval, and engagement rates, and classified user comments into thematic categories. The findings show that historical and cultural documentaries generate the highest levels of interaction and often stimulate expressions of national pride, while political documentaries attract significantly fewer responses but remain present due to state policy priorities. Audience behavior differs by age, with older viewers engaging more actively than younger ones, and reciprocity between viewers and content creators was found to be limited. The study concludes that YouTube offers Kazakh television channels an effective platform for extending the impact of documentaries beyond broadcast, fostering civic dialogue, and shaping cultural identity. However, to strengthen engagement, broadcasters need to adapt television content to platform-specific formats, incorporate interactive elements, and develop integrated multimedia strategies that reflect the expectations of diverse audiences.

Nitrogen (N) fertilizer deep placement has been widely adopted to improve nutrient use efficiency and maize yield in the semiarid regions of northwest China. However, previous studies on optimal fertilization depth have yielded inconsistent results across climate conditions, limiting its practical application. This study aims to determine the site-specific optimal N fertilization depth for spring maize by evaluating photosynthetic growth dynamics, yield formation, and N utilization in two contrasting semiarid regions. A two-year (2021–2022) field experiment was conducted in Dingxi (semiarid drought-prone region) and Jingning (typical semiarid region), with five fertilization depths: 0 cm (D0), 5 cm (D5), 15 cm (D15), 25 cm (D25), and 35 cm (D35). A 15N-labeled urea micro-plot experiment was additionally conducted to trace N fate. The results demonstrated that, compared with the conventional N placement treatment (D15), D25 increased soil total N storage, net photosynthetic rate, root bleeding rate, and the concentrations of NO3−-N and NH4+-N in the bleeding sap. PLS-PM analysis revealed that fertilization depths that are excessively deep (D35) or shallow (D0, D5, D15) adversely affect the photosynthetic parameters and root activity of maize, thereby inhibiting dry matter accumulation and grain N uptake, which ultimately reduces both yield and nitrogen use efficiency (NUE). Compared with D15, D25 increased grain yield, and NUE by 8.79% and 33.19% at Dingxi, and by 7.11% and 11.25% at Jingning. 15N isotope tracing revealed that D25 improved maize N uptake while reducing residual soil N and N losses. Regression analysis indicates regional differences in the optimal N application depth. To achieve the lowest N residual loss and the highest yield and NUE, Dingxi (23.49 cm) requires a deeper fertilization depth compared to Jingning (21.64 cm). In conclusion, N fertilizer deep placement is a viable strategy for enhancing agricultural productivity and efficiency in semiarid regions, but the appropriate depth should be selected based on local conditions.

Background and Objective: Chlamydial abortion is one of the leading causes of reproductive loss in sheep, yet diagnostic accuracy remains limited due to suboptimal assay conditions. To address this gap, the present study aimed to optimize the conditions of an Enzyme-Linked Immunosorbent Assay (ELISA) for the detection of chlamydial abortion in sheep, using TT and MM strains of Chlamydia previously isolated from affected animals. Materials and Methods: Yolk sac suspensions from 6-7-day-old chicken embryos infected with the causative agent of sheep enzootic abortion were used as starting material for antigen preparation. The MM strain was employed to develop an optimal method for the purification and concentration of antigens. Hyperimmunization schemes were designed using purified proteins in combination with biostimulants to obtain positive serum. Conjugates were prepared from isolated immunoglobulins, achieving an activity of 1:800. Immunoglobulins were purified by triple precipitation with saturated ammonium sulfate solution, followed by gel chromatography on Sephadex G-200 and identification by immunoelectrophoresis. Statistical analyses were performed using Student’s t-test (p≤0.05) for continuous data and a one-sided Fisher’s exact test (α<0.05) for comparing group efficacy. Results: The study established optimal contact parameters for antigen antibody interactions in the ELISA system. Results showed that effective binding occurred within 3 hrs at 37±1 °C or 18 hrs at 4±2 °C, while specific conjugate-antigen interaction was optimal for 1 hr at 37±1 °C. These optimized parameters significantly enhanced assay sensitivity and reliability, providing reproducible detection of antibodies against the chlamydial abortion pathogen. Conclusion: This study developed an optimized ELISA protocol for the diagnosis of sheep enzootic abortion by refining antigen preparation, immunoglobulin purification and incubation conditions. The findings contribute to improving diagnostic accuracy and may serve as a foundation for developing more rapid and cost-effective diagnostic kits for field application. Future research should validate these optimized conditions across broader sheep populations and different chlamydial strains.

The aim of this study is to assess the geoheritage of the Uly-Zhilanshik River Basin in the Turgai Depression (Western Central Kazakhstan) and to evaluate its potential for conservation and sustainable geotourism deve lopment. The basin is a geoheritage area of national and international significance, preserving well-exposed Cenozoic stratigraphic sections that document paleoenvironmental evolution and hosting numerous fossil flora and fauna localities that inform regio nal paleoclimatic and paleoecological reconstructions. These geological and paleontological features constitute a natural archive of Earth history and provide a scientific basis for territorial planning and conservation policy. The research combined field surveys of geological and geomorphological sites with an assessment of geotouristic attractiveness of natural complexes, comparative-geographical and socio-cultural analyses, and a review of environmental protection regulations. A SWOT analysis was additionally applied to identify strengths, constraints, development opportunities, and potential risks associated with tourism growth. The study demonstrates the high scientific, educational, and touristic value of the Cenozoic sections, paleontological localities, and associated landscapes, and identifies prospects for integrating geotourism into nature conservation initiatives and regional management strategies. Key directions for sustainable development are outlined, highlighting geotourism as a practical conservation instrument and a viable alternative to resource-extractive economic models. The results support the need for targeted protection measures, responsible access planning, and the incorporation of the Uly-Zhilanshik Basin into broader geoheritage and geopark frameworks within the Turgai Depression.

The aim of this study was to analyze the nutritional value of feed mixtures and premixes produced by selected feed manufacturers in southeastern Kazakhstan for dairy farms. The feed mixtures produced in the analyzed feed mills differed significantly (p≤0.01 and p≤0.05) in terms of their basic nutrient content. The amino acid, mineral, and vitamin composition of the feed mixtures was neither monitored nor balanced, except in the Good-Zhem feed mill, as the facilities did not produce mineral-vitamin premixes. For research purposes, the Kormovik and Vet Effect feed mills developed premixes for lactating cows, dry cows, and young cattle aged 6-12 months. The premixes contained high levels of minerals, including Ca, P, Mg, Na, Cl, Cu, Zn, Mn, Co, Se, and I, as well as vitamins A, D, and E. For high-yielding cows from the OST group and for cows in the first dry period (period I), an antioxidant was added at levels of 177 mg kg-1 and 95 mg kg-1, respectively. Additionally, for low-yielding cows and cows in the second dry period (period II), supplementary vitamins were included: K, B1, B2, B4, B5, B6, B9, B12, and PP. The experimental premixes used in cattle feeding on the JSC AIC Adal farm allowed the maintenance of milk yield in cows, kept there at the level of 8 000 kg of milk. The research shows that including a premix in cattle feed rations helps to balance ratios in terms of their nutritional value and content of minerals and vitamins, which ultimately enables better use of the animals’ genetic potential.

This study investigated the prevalence of Brucella abortus and Vibrio melitensis pathogens among farm animals in the Kostanay region of Kazakhstan in 2024. A total of 200 animals (120 cattle and 80 sheep/goats) were sampled from various farms. Blood and tissue samples were analyzed using bacterial culture, serological agglutination tests, and PCR for the detection of pathogens. Results showed that 45% of cattle, 40% of sheep, and 40% of goats were infected, with the highest infection rates observed in animals aged two to five years. Younger animals had a significantly lower infection rate. Serological tests indicated 46% seropositivity for Brucella abortus in cattle and 38% for Vibrio melitensis in sheep/goats. PCR confirmed pathogen presence in 43.3% of cattle and 38.75% of small ruminants. These findings underscore the importance of regular monitoring, vaccination, and enhanced animal welfare to reduce infection rates and mitigate economic losses in the region.

Garlic is a widely cultivated vegetable valued for its health-promoting compounds. This study investigated the effects of humic acid (HA) and potassium (K) on garlic productivity, bioactive compounds, and nutrient uptake. A field trial was conducted to evaluate treatments combining potassium sulfate (120 and 150 kg K₂O ha⁻¹) and humic acid (10 and 20 kg ha⁻¹). Potassium and humic acid significantly enhanced garlic performance, with combined treatments producing the most potent effects. Applying humic and K significantly increased productivity. Photosynthetic pigments increased up to 22% for chlorophylls and 45.7% for carotenoids, improving photosynthesis and photoprotection. HA raised TSS by 20% and vitamin C by 32%. Potassium enhanced TSS by 24%, carbohydrates by 3%, and vitamin C by 28%. Combined treatments maximized TSS (+32%) and vitamin C (+38%), with polyphenols restored to 40%. Bioactive compounds, metabolites, and antioxidants were enhanced, with proline up to 45%, H₂O₂ up to 55.7%, APX up to 25%, SOD up to 42%, and CAT up to 25–79%, indicating improved osmotic and oxidative management. Nutrient uptake (N, P, Ca, Mg, S, and K) improved markedly, highlighting balanced nutrient allocation from leaves to cloves. Moderate combinations (K120+HA10) maximized yield, improved photosynthetic pigments, increased vitamin C and total soluble solids, and balanced nutrient allocation between cloves and leaves. These results demonstrate that integrating HA and K provides a practical strategy to support sustainable production under nutrient-efficient management. © 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.

Context: Nitrogen management is pivotal for attaining sustainable agricultural development in the future. Among the array of mitigation strategies, deep fertilization emerges as a promising approach to address the multifaceted challenges associated with agricultural productivity, environmental sustainability, economic efficiency, and social demands. Objective: This study seeks to comprehensively assess the effects of deep nitrogen fertilization on potato productivity, environmental footprint, ecological and social costs and benefits. The findings are Intended to provide furnish an actionable guidance for advancing sustainable potato production in Northwest China. Methods: Field experiments were conducted over three consecutive years (2021–2023) at four representative sites spanning two typical climatic zones in Northwest China: the arid region (Ganzhou and Yongchang—Site 1 and Site 2) and the semi-arid region (Anding and Jingning—Site 3 and Site 4). All trials were integrated into local mainstream potato cultivation practices, with drip irrigation applied at Sites 1, 2, and 3, whereas Site 4 was cultivated under rain-fed cultivations. Four nitrogen fertilization depths were investigated: D5 (5 cm), D15 (15 cm), D25 (25 cm), and D35 (35 cm), to assess the effects of nitrogen placement depth on multiple performance indicators. Results: In arid region, the lowest nitrogen footprint (NF) and carbon footprint (CF), as well as the highest yield, N-derived potato tuber yield (YN), N-Partial factor productivity (PFPN), private profitability (BP), ecological benefits (BE) and social benefits (BS) were observed when the fertilization depth was 15 cm, while the best performance was observed at 25 cm in semi-arid region. In addition, when the fertilization depth is 35 cm, the ecological cost (Ecost) and social cost (Scost) in arid and semi-arid regions are the lowest. Compared with the conventional fertilization depth (D5) in the northwest region, the NF, CF, Ecost and Scost were significantly reduced by 14.8–34.2 %, 7.1–20.6 %, 15.0–19.7 % and 20.1–25.1 % when the optimal treatment depth was adjusted, and the yield, YN, PFPN, BP, BE and BS were significantly increased by 4.7–22.2 %, 10.2–42.8 %, 4.7–22.2 %, 10.4–86.7 %, 10.9–88.4 % and 11.8–92.5 %. The regression analysis revealed a clear spatial pattern: the optimal fertilization depth for maximizing productivity, minimizing environmental footprint, optimizing cost and benefit was generally shallower in arid areas compared to the semi-arid area, and shallower in the drip irrigation area than in the rain-fed area (with the exception of cost). Conclusions: Based on the comprehensive evaluation of productivity, environmental impacts, and economic and social outcomes, we recommend adjusting the fertilization depths to approximately 18.0 cm for Site 1, 13.3 cm for Site 2, 20.2 cm for Site 3, and 22.9 cm for Site 4. These adjustments are expected to enhance potato productivity and overall benefits.

Context and problem: As potato is one of the four major food crops, enhancing yield is crucial, particularly when considering the mitigation of environmental impacts. Deep fertilization represents a potential strategy for efficient nutrient utilization; however, its specific on potato yield, quality and greenhouse gas emissions require further elucidation. Methods: We conducted a four-year field experiment (2020–2023) using potatoes as the test crop. We investigated the impacts of four fertilization depths (D5, 5 cm, control with locally conventional fertilization depth; D15, 15 cm; D25, 25 cm; D35, 35 cm) on soil C, N, and P content and ratios, enzyme activity, greenhouse gas emissions, potato growth, yield, and quality. Results: Deep fertilization significantly increased the soil SOC:TN, SOC:TP, MBC:MBN, and SIC:SIN ratios, while decreasing the MBC:MBP, MBN:MBP, and POC:PON ratios. In addition to soil catalase, the activities of invertase, urease and phosphatase were closely related to the soil C:N:P ratio. Specifically, deep fertilization increased soil invertase and phosphatase activities but decreased catalase and urease activities. Correlation analysis showed that N2O and CO2 emissions were positively correlated with soil urease activity, whereas CH4 uptake and CO2 emissions were negatively correlated with soil phosphatase and sucrase activities, respectively. Furthermore, increase of soil phosphatase activity enhanced the leaf area index, net photosynthetic rate, and dry matter accumulation of potato while reducing stem lodging, ultimately improving yield and quality. Among these treatments, D25 achieved the highest improvements in large potato rate (16.4 %) and yield (11.5 %), while simultaneously resulting in high tuber quality in starch (42.5 %), reducing sugar (52.7 %), protein (33.4 %), and vitamin C (31.9 %) content. In addition, its greenhouse gas emission intensity was also at the lowest level (decreased by 32.7 %). Conclusions: Deep fertilization affects enzyme activity by altering soil C:N:P ratios, thereby promoting potato production and reducing greenhouse gas emissions. In this region, fertilization depths of 15–25 cm exhibited distinct advantage in terms of yield enhancement, whereas depths exceeding 35 cm were more effective in reducing emissions.

Postharvest loss of tropical fruits remains a significant challenge for food security and sustainability, as their delicate texture and high metabolic activity make them highly susceptible to rapid deterioration through handling and distribution. This study investigates the application of an edible coating technique to reduce loss, deterioration, and spoilage, and to increase the shelf-life of guava fruit. The fruits were immersed in chitosan and edible oils (moringa, lemongrass, marjoram, and rosemary). Chitosan (2%) and 1–2% moringa oil extended the shelf life of fruits by up to 24 days. Moringa oil at 1–2% mitigated the loss in fruit weight compared to 1% chitosan after the 24th day of storage, and the fruits had superior quality attributes (TSS, vitamin C, sugar content). The findings show that 2% chitosan and 1–2% moringa oil were the most effective treatments, reducing weight loss to about 10–25% compared to nearly 50% in untreated fruits and maintaining overall fruit quality. These treatments boosted peroxidase (POD) activity, reaching a peak of 76.47 U/g and keeping hydrogen peroxide (H2O2) levels low at 24.25 µmol g-1 FW, signalling strong protection against oxidative stress. On the chemical side, they maintained higher total soluble solids (13.17 °Brix), total sugars (11.36%), and vitamin C (32.49mg/100mL), while keeping acidity lower (0.82%). By comparison, lemongrass and marjoram oil treatments were far less effective, showing faster weight loss and oxidative damage levels similar to those of the control group. Chitosan and oil coatings substantially reduce bacteria and yeasts/ moulds on guava fruits, and moringa oil treatment improved physio-biochemical characteristics and reduced postharvest disease spoilage. The results highlight that natural coatings, particularly chitosan and moringa oil, not only preserved the physio-biochemical quality of guava but also offered a sustainable, biodegradable solution that can help reduce food loss, limit reliance on synthetic chemicals, and support environmentally responsible postharvest management practices.

While long-term film mulching has consistently increased crop yields, it has also contributed to land degradation, prompting adjustments in straw returning rates. However, the responses of soil organic carbon (SOC) and structure to optimal straw returning rates are in need of a deeper understanding. Here, we examined the effects of soil structure, SOC dynamics, and maize productivity under long-term film mulching with varying straw return rates (0, 6000, 12,000, and 18,000 kg ha−1) in semi-arid farmland. The SOC and particulate organic carbon (POC) content both reduced after long-term film mulching. The varying changes of soil aggregation processes caused by different straw returning rates, which in turn affect the distribution of soil aggregates, particularly the proportion of > 0.25 mm aggregates. The effects of different straw return rates on crop yield were mainly driven by changes in organic carbon pools (microbial biomass and dissolved organic carbon), resulting from nutrient inputs that stimulated microbial growth. Higher straw return rates have promoted the stratification of SOC and modified the proportional distribution of organic carbon fractions. These changes have directly and indirectly increased maize yield by 21% and economic benefits by 15%. Based on the total application of straw in dryland farming systems, increasing the straw application rate to 18,000 kg ha−1 resulted in a synergistic improvement in SOC content, soil structure and economic benefits.

The study examines how food security operates at the national level in the Republic of Kazakhstan, using the grain sector as a focal case. The analysis responds to a gap in empirical research that connects agricultural investment, grain production trends, and food price behavior within one food security framework. The study relies on national statistical data from Kazakhstan for the period 2015–2023. The analysis applies descriptive statistics, trend analysis, and correlation assessment to gross grain and legume harvests, per capita consumption of staple foods, fixed capital investment in agriculture, forestry, and fisheries, agricultural lending volumes, and food price inflation. A SWOT analysis complements the quantitative results and places them within existing institutional and market conditions. The findings show a general rise in grain and legume output over the study period, alongside marked year-to-year volatility. Consumption data confirm the central role of grain-based foods in household diets. Correlation results show a strong statistical association between fixed capital investment in agriculture-related sectors and food price inflation (R2 = 0.9238). The relationship reflects structural co-movement rather than direct causation. The SWOT analysis highlights key strengths of Kazakhstan's grain sector, including high production capacity, export potential, developed infrastructure, and state support. At the same time, it reveals ongoing weaknesses linked to climate exposure, narrow production structure, and transport and logistics limits. The study offers an integrated empirical view of food security in Kazakhstan that links production, investment, and price dynamics within a single system-based approach. The results inform policy discussions on grain sector resilience and national food security. Stable investment conditions, technological renewal, and effective risk management emerge as central priorities. The analysis also creates a basis for future research using advanced econometric methods and cross-country comparison. 

The Great Bustard and the Little Bustard are emblematic species of Kazakh steppes. Populations of these birds were numerous in the middle of the last century but in the early 1970’s they fare on the brink of extinction. This paper is based on a long-term observation in Naurzum Reserve and adjacent territories in 1977-2014 and on territory of Kostanai Region in 1998-2014, as well as literature data. The paper provides information on the population dynamics of the Great Bustard and the Little Bustard in Kostanai region, the factors influenced on decline in their numbers, and the current state of their populations. Population dynamics of Little Bustard during the end of 1990th and until 2010 characterized by decreasing of its density, that was most visible in feather-grass steppe. In 2006-2012 the number of Little Bustard varied from year to year, but dynamics from habitat to habitat had sometimes different trend. Since 2012, experienced rapid population growth, which was probably due to the appearance of the gregarious locust forms. The situation with the Great Bustard is absolutely different. The number of this specie in the past 40 years is maintained at an extremely low level, without visible changes.

Our study investigates the effects of precision farming and varying nitrogen (N) and phosphorus (P) fertilizer doses on spring wheat yield in Kostanay, Kazakhstan. By using agrochemical analysis and productivity zones, this research aims to optimize fertilizer use for better crop yields and offers practical recommendations for sustainable farming in similar climates. The study was conducted in 2023 at Lugovoye Farm on 215ha, and N and P fertilizers were tested on spring wheat. The best results were achieved with a 75 kg/ha ammophos application, resulting in a 3.0kg/ha increase in yield. Higher doses in productive zones and lower doses in less productive areas also yielded positive results. The findings highlight the potential of precision agriculture to increase productivity, sustainability, and food security, particularly in developing regions, to support economic growth and poverty reduction.

The article introduces a class Pn(ϕλ) of functions ϕ(z) of the form ϕ(z) = 1 + cnzn +cn+1 zn+1 + · · ·, n ≥ 1, subordinating to the function ϕλ (z) = 1 + (1−λ)2 z, 0 ≤ λ < 1, analytic in the open unit disk E = {z : |z| < 1}, and studies its properties. In particular, precise estimates are obtained for ϕ(z), |ϕ(z) − 1| and |zϕ′(z)/ϕ(z)|, which are used to study the extremal properties of a number of classes of analytic in E normalized functions f (z) with expansion of the form f (z) = z + an+1zn+1 + an+2zn+2 + · · ·, n ≥ 1. Theorems of growth, covering, rotation, and convexity radii for one class of starlike functions constructed on the basis of the function ϕλ(z) are obtained. Also the radii of starlikeness for a number of classes of close-to-starlike and doubly close-to-starlike functions related to ϕλ(z) are found. All results are sharp. Both new original results and generalizations of previously known results are presented.

Against the backdrop of intensifying climate-related threats and the growing recurrence of natural disasters, media discourse has emerged as a key site where public perceptions of risk, patterns of social mobilization, and models of collective response are actively constructed. Within this communicative space, metaphor functions not merely as a stylistic device but as a fundamental cognitive and discursive mechanism, through which meaning is organized, interpretation is guided, and culturally embedded patterns of understanding are activated. The study of metaphorical framing thus offers a productive analytical lens for examining the dynamics of crisis communication, environmental rhetoric, and processes of collective sense-making. The present study is devoted to the identification and systematic analysis of metaphorical frames in English-language media discourse devoted to natural disasters. The empirical basis of the research is a balanced corpus of texts published by English-speaking media between 2023 and 2024, focusing on two recurrent types of natural hazards – wildfires and floods, which makes it possible to conduct a symmetrical comparison of British and American media environments. The theoretical framework of the study draws on an integrative approach that combines Conceptual Metaphor Theory, Frame Semantics, Critical Discourse Analysis, and the principles of Critical Metaphor Analysis. Methodologically, the research relies on corpus-based techniques, including frequency analysis, collocational profiling, and contextual examination implemented through the AntConc software, in conjunction with the MIPVU protocol for systematic metaphor identification. The reliability of the analytical procedure is ensured by corpus symmetry and inter-annotator validation. As a methodological contribution, the study introduces the notion of a frame index, understood as a quantitative indicator of metaphorical intensity, thereby extending the analytical toolkit of cognitive-discursive research. The study aims to determine the dominant patterns of metaphorical framing employed in media representations of natural disasters, to explicate their cognitive and discursive functions, and to trace their variation across different media platforms and types of catastrophic events. The findings advance current approaches in cognitive linguistics and media discourse analysis and have practical implications for the development of environmental communication strategies, media literacy, and editorial practices in the coverage of climate-related risks.

Purpose. To investigate the regularities of reactive species formation during the plasma treatment of multicomponent wastewater from the mining and petroleum industries, as well as to assess their role in contaminant transformation and removal efficiency. Methods. Laboratory experiments were carried out using a specially designed plasma-liquid reactor operating under high-frequency electrical discharge conditions (10-25 kV, 10-30 kHz, interelectrode gap 3-7 mm). The study included determination of the initial physicochemical characteristics of wastewater, including pH, electrical conductivity, total dissolved solids, and concentrations of heavy metals (Cu, Zn, Cd). During plasma treatment, the formation of reactive species (•OH, O3, H2O2) was analyzed, and a kinetic model was applied to describe contaminant removal dynamics and treatment efficiency. Findings. It was established that plasma treatment leads to the formation of hydroxyl radicals at a rate of (1-5)·10-6 mol·L-1·s-1, ozone in the concentration range of 10-6-10-4 mol·L-1, and hydrogen peroxide accumulation within 10-80 mg/L, thereby creating a pronounced oxidative environment. Copper concentration decreased from 20 to 0.5 mg/L (97.5%), zinc from 15 to 0.4 mg/L (97.3%), and cadmium from 0.5 to 0.02 mg/L (96.0%). The degree of organic contaminant degradation reached 70-90%. It was shown that the intensity of reactive species formation strongly depends on discharge parameters, while the proposed kinetic model adequately describes the experimentally observed treatment dynamics. Originality. The study provides a comprehensive experimental and model-based analysis of reactive species formation during the plasma treatment of highly mineralized multicomponent wastewater from the mining and petroleum industries. Quantitative relationships were established among discharge parameters, reactive species generation, and contaminant removal efficiency. Practical implications. The obtained results confirm the potential of plasma technologies for the advanced treatment of industrial wastewater with complex composition and high salinity. Practical implementation of the proposed approach may contribute to improved environmental safety, reduced reagent consumption, lower sludge generation, and expanded opportunities for water reuse in mining and petroleum production processes.

Soil phosphorus deficiency is a growing constraint on crop productivity in the agricultural lands of the Kostanay Region, Republic of Kazakhstan, yet systematic data on the spatial dynamics of mobile phosphorus and potassium across soil types remain limited. This study assessed the availability of mobile forms of phosphorus and potassium, alongside key physicochemical properties, including soil pH and cation exchange capacity, in Chernozem and chestnut soils of agricultural enterprises across the Kostanay Region. Soil samples were collected from arable fields and analyzed using standard agrochemical methods. Results revealed a widespread deficiency of available phosphorus in arable soils across most surveyed enterprises, with concentrations ranging from 25 to 80 mg/kg, in contrast to consistently high mobile potassium levels of 200-450 mg/kg. In flat, poorly drained areas of steppe plains and low-relief zones, Chernozem and chestnut soils were frequently subject to salinization and alkalinization, exhibiting elevated soil pH values that further constrain nutrient availability and overall fertility. These conditions underscore the need for targeted phosphorus fertilization, optimized crop rotation planning, and soil amelioration measures in affected areas. Continued monitoring of soil degradation and desertification processes on agricultural lands is recommended to support sustainable land management in the Kostanay Region.

Cows of the Reflection Sovereign line had a longer productive life and a higher lifetime milk yield than Vis Beck Ideal cows. Seasonal conditions influenced milk density and composition. Milk density varied slightly across seasons, and it was highest in winter in both genetic lines. Milk acidity changed minimally and was somewhat higher in winter, probably due to inflammatory conditions such as mastitis. Seasonal changes in milk fat and protein content revealed notable differences between genetic lines. Milk fat content was highest (3.65%) in summer in Reflection Sovereign cows, and it was 0.04% higher than in Vis Beck Ideal cows. Milk protein content was highest (3.28–3.29%) in autumn, with no significant differences between the lines. Autumn milk from Reflection Sovereign cows had the most desirable composition (3.65% fat, 3.27% protein, 4.61% lactose). Seasonal variations in milk lactose content were less pronounced than those observed in fat and protein content. The dry matter content of milk was highest in autumn (12.57%) and lowest in spring (12.21%). Dry skim milk solids ranged from 8.28% to 9.02%, and the highest value was noted in winter in Reflection Sovereign cows. Milk from Vis Beck Ideal cows had higher somatic cell counts (SCC), peaking in summer. Reflection Sovereign cows had better reproductive performance, with a shorter inter-calving interval and a higher coefficient of reproductive capacity. Inseminating heifers at 15–16 months of age supports the development of highly productive cows with favorable reproductive traits. Seasonal conditions affected individual milk components differently in Holstein cows. Reflection Sovereign cows are recommended for breeding to maximize genetic potential for longevity and milk production. Breeding this line is economically advantageous because it produces more fat and protein per lactation. Revenue, profit, and profitability were higher in Reflection Sovereign cows than in Vis Beck Ideal cows. Overall, Reflection Sovereign cows are better suited for intensive industrial dairy production.

The study aims to analyse the features of state regulation in the information sphere of Kazakhstan and to assess its impact on the development and functioning of regional media. The study identifies key stages in the evolution of national information policy and the mechanisms through which it influences regional media outlets. A sociological survey involving 100 representatives from regional authorities across six regions of Kazakhstan – Akmola, Aktobe, Almaty, Atyrau, Karaganda and Kostanay – helps establish the geographical and structural features of the impact of state policy. In-depth interviews highlight three primary functions of regional media: political communication, cooperation with government bodies and educational outreach. The evaluation results show that the public oversight function received the highest rating (7.9), while educational activity scored the lowest (5.2). The survey further indicates perceptual differences regarding the role of mass media between senior officials and mid-level civil servants, indicating internal differentiation in approaches to information policy. The findings suggest that in the digital age, the information policy of Kazakhstan must strike a balance between information security and freedom of expression. The practical value lies in the potential application of these results for refining information policy amidst ongoing digital transformations.

Background and Aim: Brucellosis is a chronic infectious disease of cattle that may influence not only animal health but also the nutritional and sanitary quality of meat. While veterinary-sanitary implications of infected carcasses are well documented, limited information is available on the biochemical composition of meat derived from chronically infected animals. This study aimed to evaluate the veterinary-sanitary status, organoleptic characteristics, and biochemical composition of beef obtained from cattle with chronic brucellosis compared with clinically healthy animals. Materials and Methods: An observational comparative cross-sectional study was conducted using post-slaughter samples collected within official veterinary surveillance programs. A total of 250 meat samples were subjected to veterinary-sanitary and organoleptic assessment, including animals diagnosed with brucellosis, leukemia, tuberculosis, and leptospirosis. Biochemical analysis was restricted to chronic brucellosis and matched controls (n = 100 per group). Standardized methods were used to determine proximate composition, mineral content, vitamin levels, fatty acid profile, and amino acid composition. Statistical analysis was performed using independent Student's t-test, with significance set at p ≤ 0.05, and false discovery rate correction applied for multiple comparisons. Results: Veterinary-sanitary assessment revealed a higher proportion of carcass alterations and conditional suitability in infected animals compared with controls. Organoleptic evaluation indicated mild but consistent changes in color, texture, and overall quality of meat from infected cattle. Biochemical analysis demonstrated significant alterations in nutrient composition in the infected group, including reduced protein content and modifications in lipid fractions. Changes in fatty acid composition were observed, with variations in saturated and unsaturated fatty acids and altered polyunsaturated to saturated fatty acids and n-6 to n-3 ratios. Mineral and vitamin profiles also exhibited measurable differences between groups. Effect size analysis confirmed moderate to large differences for several key nutritional parameters, indicating biologically relevant impacts of chronic infection on meat quality. Conclusion: Chronic brucellosis is associated with measurable alterations in the biochemical composition and veterinary-sanitary quality of beef. Although meat from infected animals may remain conditionally suitable for consumption following regulatory assessment, its nutritional value can be compromised. These findings highlight the importance of integrating veterinary disease status into meat quality evaluation frameworks and support the need for continued surveillance and risk-based assessment in meat inspection systems. Copyright: Ansabayeva, et al. This article is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)

This study investigates the spatiotemporal variability of minimum river discharge in Northern Kazakhstan and its sensitivity to climatic factors under continental and semi-arid conditions. Long-term meteorological and hydrological data from key regional rivers, including Tobyl, Toguzak, Torgay, Karatorgay, and Ayat, were analyzed to detect structural shifts, trends, and stationarity. Structural changes were identified using Pettitt’s test and supported by difference-integral and cumulative-integral curves, while linear trend analysis with 10-year moving averages highlighted long-term tendencies. Correlation analysis assessed the influence of temperature and precipitation, distinguishing low-and high-flow years. Stationarity and homogeneity were evaluated with ADF, KPSS, and complementary parametric and non-parametric tests to ensure robust statistical interpretation. Results reveal significant structural shifts during 1980–1990, with rising winter air temperatures and marked heterogeneity of minimum discharge, especially in cold seasons. Winter flows are predominantly controlled by temperature and groundwater recharge, while summer flows are strongly linked to precipitation dynamics and evapotranspiration processes. Differences between low-and high-flow years confirm the dynamic non-stationarity of the system. These findings enhance understanding of regional hydro-climatic interactions and provide a scientific basis for adaptive water resource management, reservoir regulation, and long-term strategies of climate change adaptation in the steppe and semi-arid regions of Central Asia.

This article presents an approach to developing digital educational systems for analyzing and predicting the academic performance of university students using machine learning methods. Learning analytics enables the consideration of individual student characteristics and supports decision-making in educational planning. The study was conducted using a dataset containing academic records of 2,423 students collected over five semesters. Several types of models were evaluated, including linear, tree-based, ensemble, and neural network algorithms. A hybrid neural architecture is proposed that combines embedding-based representations of categorical features, a conditional attention mechanism, and LSTM-based sequential modeling to process students' academic history. The experimental results demonstrate performance differences among the tested models. Baseline approaches, including linear, tree-based, kernel-based, and neural network methods, achieved accuracy in the range of approximately 0.71 to 0.86. The proposed Attention-LSTM model achieved an accuracy of 0.89, with F1-macro and F1-weighted scores of 0.88 and 0.89, respectively. The results indicate that hybrid neural architectures can effectively capture patterns in students' academic data. The proposed approach can be applied in digital educational systems to monitor and analyze student learning dynamics.

Diffuser-augmented wind turbines (DAWTs) are a promising wind-energy concept designed to enhance airflow through the rotor and improve energy capture, especially in low-wind and urban environments. This study evaluates the development prospects of DAWTs through an integrated bibliometric and patent analysis. Bibliographic records were retrieved from Scopus, and patent records were obtained from Google Patents for the period 2013–2023. After screening and eligibility assessment, 334 scientific publications and 401 patent families were included in the final analysis. The results show a sustained increase in research output, with China, the United States, and Japan emerging as leading contributors. Keyword co-occurrence analysis identified four dominant research clusters: aerodynamics and optimization, design and materials, urban and distributed systems, and noise and control. Patent activity peaked around 2020 and was concentrated in China, the United States, and Europe, indicating growing commercial interest. Although DAWTs can achieve rotor-area-normalized performance values above the classical Betz limit, such results should be interpreted within the specific fluid-dynamic framework of ducted systems. Overall, DAWTs demonstrate strong technical potential, but large-scale deployment remains constrained by structural complexity, cost, and limited field validation. Future progress depends on scalable design, field testing, and techno-economic assessment.

This study aims to increase the energy efficiency and product uniformity of centrifugal impact crushers for feed grain processing through targeted optimisation of technological parameters. A direct-impact mechanism was implemented by profiling the stationary impact lining with an involute tooth geometry that ensures grain collisions at a 90° angle, minimising kinetic energy losses. Experimental tests were conducted on pea grain (moisture 11.6%) using a prototype crusher developed at Kostanay Regional University. Rotor speed was set at 2000 rpm, throughput maintained at 400 kg/h. The optimised crusher achieved a specific energy consumption of 2.89 kWh/t, which is 22% lower than a conventional impact crusher of similar capacity. The crushed product had an arithmetic mean particle size of 1.31 mm with 85% of particles within the 0.5-1.5 mm range, meeting zootechnical standards. Theoretically, this work refines comminution models by quantifying the effect of impact angle on breakage efficiency and provides a design criterion (involute profile with 47°-56° contact angles) for normal-impact crushers. Practically, the prototype offers a low-energy, high-uniformity solution suitable for feed mills and can be retrofitted into existing machines. The main contribution is the experimental validation that deliberate alignment of impact geometry reduces specific energy by over one-fifth without sacrificing throughput or quality, opening a new direction for energy-efficient grinder design.

The widespread use of antibacterial agents in livestock production is associated with antibiotic residues in animal products and feed, posing a potential threat to food safety and contributing to antimicrobial resistance. The aim of this study was to assess contamination levels of beef, pork, and feed with antibiotic residues in the Kostanay region. The results demonstrated the presence of antibiotic residues in beef, pork, and feed, while all detected concentrations remained below established maximum residue limits. Despite compliance with regulatory standards, residues were detected frequently, and their levels differed significantly depending on feed type (p < 0.001). Microbiological analysis confirmed the presence of Escherichia coli and Staphylococcus aureus in meat samples, with isolates exhibiting moderate to high antimicrobial resistance, particularly in pork. The highest resistance was observed to tetracycline, streptomycin, and thiamphenicol. The obtained data indicate that even trace antibiotic concentrations entering the “feed–animal–product” chain may be associated with selective pressure on microbiota and the circulation of resistant microorganisms. The results highlight the need for comprehensive monitoring of feed and animal products to assess and mitigate antimicrobial resistance spread within the food chain

Digital soil mapping (DSM), based on multimodal satellite data, is a crucial tool for the transition to precision agriculture. However, systematic studies using this method and machine and deep learning techniques are lacking for the arid and semi-arid regions of Central Asia, where multimodal satellite data can provide valuable insights into soil conditions. This work provides, for the first time, benchmark metrics for the predictive ability of six soil agrochemical properties (pH, Soil Organic Carbon, NO3, P2O5, K2O, and S) in the dry steppe zone of Central Asia, with a quantitative assessment of the difference between “standard” and “fair” validation strategies. This has methodological significance for the entire field of DSM research. A comprehensive comparison of 11 machine learning (ML) models and four deep learning (DL) architectures was conducted to predict soil agrochemical properties using a set of 530 features extracted from various satellite datasets. These features were extracted from Sentinel-2, Landsat-8, Sentinel-1 SAR, SRTM DEM, and ERA 5-Land using Google Earth Engine (GEE) automated pipeline. All models were evaluated using three spatial validation strategies with increasing stringency: Leave-One-Field-Out CV (LOFO-CV), Leave-One-Farm-Out CV (Farm-LOFO), and an optimized spatial split. We propose a three-level hierarchical validation scheme that allows for the quantitative separation of spatial leakage and feature selection leakage, a methodology that can be applied to any spatial ML problem. Local models have been shown to outperform the global SoilGrids v2.0 product in terms of accuracy, demonstrating the need for high-resolution regional models for precision agriculture. Local models outperformed SoilGrids v2.0 by 3.6× in Spearman ρ for pH (0.750 vs. 0.208), quantitatively confirming the necessity of regional calibration over global soil products. Multi-season ConvNeXt with SE-blocks on 54-channel composites improved R2 for NO3 by 36% (0.422 → 0.575), confirming the value of temporal dynamics for mobile elements; however, it underperformed RF on tabular features for most properties at the available sample size (n = 1085).

The aim of the study was to analyse how cognitive processes create cultural archetypes in linguofolkloristics of different cultures, particularly Kazakh. In the course of the work, a content analysis of 16 folklore texts was conducted: 9 in Kazakh (metaphorical strategies are used in most cases, logical structure of the narrative – to a lesser extent), and 7 in English (metaphorical strategies and logical structure – to varying degrees). The results of the study confirm that cognitive strategies have a significant impact on the formation and interpretation of linguofolklore texts. In particular, metaphorical strategies play a key role in conveying cultural values and social experience, which is especially noticeable in Kazakh folklore texts. The analysis has shown that Kazakh folklore texts use metaphors more often than foreign ones, which emphasizes the uniqueness of cultural identity and the specificity of Kazakh folklore. The logical structure of the narrative in Kazakh texts also differs, highlighting emotionality and cultural aspects, while foreign texts more often follow a clear logic of plot development. The adaptation of traditional images to modern conditions has been identified as a significant aspect demonstrating how folklore can respond to new social challenges and changes. This result opens up new possibilities for further study of folklore as a dynamic element of culture that can retain its relevance and significance in a changing world. The study also revealed that new media create new formats and ways of disseminating folklore, which allows it to adapt to contemporary audience interests and expand its audience. The findings can be used to develop educational programmes aimed at preserving and developing cultural identity and understanding of folklore traditions

In recent years, Kazakhstan has faced serious challenges, both in terms of water shortages and the operation of existing hydraulic structures. Droughts have systematically reduced accumulated freshwater reserves, while the 2024 flood has led to the inundation of several settlements. To understand the true state of existing hydraulic structures and the water reserves in these reservoirs, as well as to forecast potential risks, the government has initiated a series of studies. In light of the increased urgency of understanding the condition of hydraulic structures, the authors address the issue of assessing the accuracy of computer modeling of the region’s reservoirs (using the Karatomar and Verkhne-Tobol reservoirs as examples). In this study, the bathymetry of the Karatomar reservoir was obtained using an Apache 3 drone. Kriging methods were used to study the relationship between modeling accuracy and line frequency. Reservoir models were built in QGIS and Surfe. Sentinel-2 satellite imagery and data from the Kazvodkhoz Agency (Kazvodkhoz) were used for shoreline analysis. The study resulted in an algorithm for determining the density (pitch) of hydrodrone lines for modern bottom geomorphology. The research showed that the accuracy of surveys of even lowland hydraulic structures in Kazakhstan significantly depends on the field survey parameters, and the hydraulic structures themselves have undergone significant changes over the course of their operation.

Meat maturation is a set of biochemical and biophysical processes that affect the muscle structure, surface color, and taste of a product. The purpose of this study was to compare the qualitative characteristics of horse meat that has undergone dry and wet maturation. The work used Longissimus Dorsi muscle samples obtained from a lumbosacral cut with maturation duration of 14 and 21 days. The analysis of losses during stripping, cutting force, chemical composition and microbiological parameters was carried out. It was found that losses during dry maturation are higher, especially at 21 days. However, as the duration increases, the energy value of the product increases. The difference in cutting force between the methods is insignificant, but the overall decrease in effort on day 21 indicates an increase in the tenderness of the meat. The chemical composition varies depending on the method, and the products of dry maturation are characterized by a higher energy value and digestibility of proteins. Microbiological parameters comply with regulatory requirements, which indicates the safety of the finished product.

Ephedrine and its derivatives have long been recognized for their therapeutic potential in the treatment of hypotension, asthma, and obesity. However, their use is limited by significant side effects, including cardiovascular risks and toxicity. This study presents a comprehensive computational evaluation of 13 ephedrine derivatives using integrated ADMET analysis, PASS prediction, and quantum-chemical approaches. Pharmacological profiles, toxicity risks, and electronic properties were systematically analyzed to establish structure–activity relationships. Key physicochemical parameters, pharmacokinetic properties, and toxicity risks were analyzed to identify compounds with optimal drug-like characteristics. The results highlight compound 5 as the most promising candidate, demonstrating high drug-likeness (Quantitative Estimate of Drug-likeness, QED = 0.85) and favorable pharmacokinetic properties. Conversely, compounds 3, 11–13 exhibit high toxicity and require structural optimization. PASS predictions indicate diverse biological activities, including spasmolytic and analeptic effects, with compounds 5–7 showing significant potential for further development and compound 13 exhibiting antioxidant activity. DFT analysis of ephedrine, cephedrine and key derivatives (compounds 5, 7, 13) revealed an optimal HOMO-LUMO range (ΔE = 4.7–5.0 eV) for compounds with high activity and low toxicity, where derivative 5 exhibits the best balance. This study underscores the importance of rational drug design in optimizing therapeutic efficacy while minimizing adverse effects and environmental risks.

Purpose of the study. The aim of the study is to develop scientifically substantiated recommendations for improving the design and operating parameters of a belt conveyor intended for transporting bulk materials in technological systems of mining enterprises and agricultural production complexes. An additional objective is to determine the optimal combination of belt speed, belt filling coefficient and roller support parameters ensuring reduced energy consumption and improved stability of material transportation. Materials and methods. The research employed experimental methods and analysis of operational characteristics of belt conveyors. The experiments were carried out on a laboratory–industrial test bench using an LT-800 belt conveyor equipped with an asynchronous electric drive with a power of 11 kW and a frequency converter. During the experiments the belt speed varied within 0.8–2.5 m/s, the belt filling coefficient ranged from 0.3 to 0.8, and the conveyor capacity ranged from 20 to 120 t/h. Crushed stone and wheat grain were used as transported materials. Power consumption of the electric drive, loads on roller supports and belt tension were measured. Results. It was established that an increase in belt speed leads to higher power consumption and specific energy costs of transportation. When the belt speed increased from 0.8 to 2.5 m/s, the power consumption increased from 4.1 to 10.8 kW. It was shown that an increase in the belt filling coefficient from 0.3 to 0.8 resulted in an increase in roller load from 280–320 to 620–680 N. Optimal operating modes of the conveyor ensuring minimum energy consumption and stable transportation of materials were determined. Discussion. The obtained experimental dependences showed that the most efficient operating modes of the belt conveyor are achieved at belt speeds of 1.2–1.6 m/s and a belt filling coefficient of 0.5–0.6. Under these conditions the specific energy consumption is 0.21–0.24 kWh/t, while dynamic loads on conveyor components decrease by 12–18%. The results demonstrate that optimized operating conditions significantly improve the efficiency of bulk material transportation both in mining and agricultural industries. Conclusion. The conducted research confirmed the possibility of improving the performance of belt conveyors by optimizing their design and operating parameters. The proposed recommendations allow reducing energy consumption and increasing the service life of conveyor components. Conclusions. Recommendations for selecting rational operating parameters of belt conveyors based on experimental analysis of belt speed and belt filling degree were developed. It was shown that optimization of operating modes reduces specific energy consumption by 12–15%. Practical application and future research. The obtained results can be applied in the design and modernization of transport systems at mining enterprises as well as in agricultural production facilities for transporting grain and other bulk materials. Further research will focus on the development of intelligent control systems and digital models of conveyor transport systems.

This article examines the colonial character of the Russian Empire within the framework of contemporary comparative imperial and postcolonial studies. It addresses ongoing historiographical debates concerning the nature of Russia’s imperial expansion and critically engages with interpretations that deny or relativize its colonial dimension, particularly the concept of Russia’s “self-colonization”. Drawing on a broad corpus of historiographical works, imperial-era scholarly and reference publications, and post-Soviet research, the study employs comparative-historical and discourse-analytical methods to reassess the structural features of Russian imperial rule. The analysis demonstrates that the continental form of Russia’s expansion does not negate its colonial character but rather represents a specific spatial modality of colonialism. The article argues that key characteristics of classical colonial empires – such as institutional and legal asymmetry between the center and the periphery, extractive economic relations, and cultural hierarchization – were also intrinsic to the Russian imperial model. Particular attention is paid to the territory of present-day Kazakhstan, which is interpreted as part of the colonial space of the Russian Empire. The incorporation of Kazakh lands involved military conquest, the establishment of special administrative regimes, restrictions on political representation, and the reorientation of the regional economy toward the needs of the metropolitan center. The study concludes that integrating the Russian imperial experience, including Kazakhstan, into the global history of colonialism allows for a more nuanced and analytically grounded understanding of imperial governance, beyond national-centered or ideologically driven narratives.

This work presents a hybrid deep learning approach for identifying students who are likely to experience academic difficulties in virtual learning environments. The proposed framework is evaluated on the Open University Learning Analytics Dataset (OULAD) and combines two complementary types of information: temporal patterns of learner activity captured using Bidirectional Long Short-Term Memory (Bi-LSTM) networks and relatively stable student attributes modeled through a Multi-Layer Perceptron (MLP). To account for the fact that student engagement does not contribute equally across different phases of a course, a temporal attention mechanism is incorporated to emphasize the most informative periods over the 32-week learning timeline. The experimental results indicate that the hybrid model achieves stronger predictive performance than baseline approaches, with a ROC-AUC of 0.95 and a weighted F1-score of 0.90. Analysis of the attention weights suggests that both early engagement and activity toward the end of the course (Weeks 25–32) play an important role in predicting final outcomes. To address the imbalance between successful and at-risk learners, a cost-sensitive training strategy is adopted, resulting in a recall of 0.79 for the at-risk group. Overall, these findings suggest that integrating temporal behavioral signals with static student characteristics leads to more reliable risk prediction and provides a useful basis for data-informed academic support in online learning contexts.