The primary data of micro- and macroplastics in the aquatic environment of Lake Markakol, located in the mountainous area of East Kazakhstan, are presented. The determination of micro- and macroplastics in water is based on sieving, drying, liquid oxidation, density separation and visual sorting using a microscope with a magnification of 40×. The detected plastic fragments in the aquatic environment include fishing line nets, Styrofoam balls, plastic bags, plastic bottles, wrappers, food labels and packages and other types of plastic waste. The sizes of the plastic fragments were ˃25 mm, 1.0–5.0 mm and 0.315–1.0 mm. The concentration of plastic in Lake Markakol was 837.5 µg/m3 in the tributaries and 482.1 µg/m3 in the lake water. The detected plastic mainly corresponded to sieve mesh sizes of 1.0–5.0 mm and 0.315–1.0 mm. The main sources of plastic pollution are fishing, tourism and the lack of adequate infrastructure for household waste management. These data emphasize the importance of measures to regulate plastic waste management in order to preserve the Lake Markakol ecosystem and maintain human health. © 2024 by the authors.

Due to its persistence and potential negative effects on ecosystems and human health, microplastic pollution in aquatic environments has become a major worldwide concern. Photocatalytic degradation is a sustainable manner to degrade microplastics to non-toxic by-products. In this review, comprehensive discussion focuses on the synergistic effects of various photocatalytic materials including TiO2, ZnO, WO3, graphene oxide, and metal–organic frameworks for producing heterojunctions and involving multidimensional nanostructures. Such mechanisms can include the generation of reactive oxygen species and polymer chain scission, which can lead to microplastic breakdown and mineralization. The advancements of material modifications in the (nano)structure of photocatalysts, doping, and heterojunction formation methods to promote UV and visible light-driven photocatalytic activity is discussed in this paper. Reactor designs, operational parameters, and scalability for practical applications are also reviewed. Photocatalytic systems have shown a lot of development but are hampered by shortcomings which include a lack of complete mineralization and production of intermediary secondary products; variability in performance due to the fluctuation in the intensity of solar light, limited UV light, and environmental conditions such as weather and the diurnal cycle. Future research involving multifunctional, environmentally benign photocatalytic techniques—e.g., doped composites or composite-based catalysts that involve adsorption, photocatalysis, and magnetic retrieval—are proposed to focus on the mechanism of utilizing light effectively and the environmental safety, which are necessary for successful operational and industrial-scale remediation. © 2025 by the authors.

The object of the research is in-pipe defect detection and classification. The primary problem to be solved is the inefficiency, high cost, and inaccuracy of traditional manual inspection methods, which are often time-consuming and prone to human error. The results obtained include the creation of a multi-modal platform that integrates Red-Green-Blue (RGB) imaging and depth data with advanced artificial intelligence algorithms, Canny edge detection, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering, achieving a 93 % mean Average Precision (mAP) in detecting and classifying various defects such as cracks, corrosion, and debris. A brief interpretation of the findings reveals that the high performance is due to the synergy between multi-modal sensing, artificial intelligence pattern recognition, and robust robotic navigation. This integrated approach ensures that the system not only detects defects accurately but does so in real time. Features and characteristics of the obtained results that directly address the identified problem include real-time high-precision defect identification, and reduced inspection downtime. As a result, inspection time is shortened, costs are lowered, and the safety of the pipeline system is increased, leading to accurate measurement of indicators (93 % mAP) and a reduction in occupational safety risks. The developed system is designed for use in traditional industrial environments, especially in large pipeline networks and in conditions where traditional methods are ineffective

In the current study, an attempt was made to synthesize coffee husk (CH) activated carbon by chemical modification approach (sulphuric acid-activated CH (SACH) activated carbon) and was used as a valuable and economical sorbent for plausible remediation of Methylene blue (MB) dye. Batch mode trials were carried out by carefully varying the batch experimental variables: SACH activated carbon (SACH AC) dosage, pH, initial dye concentration, temperature, and contact time. The optimum equilibrium time for adsorption by SACH activated carbon was obtained as 60 min, and the maximum adsorption took place at 30 °C. Morphological and elemental composition, crystallinity behaviour, functional groups, and thermal stability were examined using SEM with EDX, XRD, FTIR, BET, TGA, and DTA and these tests showed successful production of activated carbon. The outcomes showed that chemical activation enhanced the number of pores and roughness which possibly maximized the adsorptive potential of coffee husk. The Box-Benken design (BBD) was used to optimize the MB dye adsorption studies and 99.48% MB dye removed at SACH AC dosage of 4.83 g/L at 30 °C for 60 min and pH 8.12, and the maximum adsorption was yielded for sulphuric acid-activated coffee husk carbon carbon with 88.1 mg/g maximum MB adsorption capacity. Langmuir- Freundlich model deliberately provided a better fit to the equilibrium data. The SACH AC-MB dye system kinetics showed a high goodness-of-fit with pseudo second order model, compared to other studied models. Change in Gibbs's free energy (ΔGo) of the system indicated spontaneity whereas low entropy value (ΔSo) suggested that the removal of MB dye on the SACH activated carbon was an enthalpy-driven process. The exothermic nature of the sorption cycle was affirmed by the negative enthalpy value (ΔHo). The adsorptive-desorptive studies reveal that SACH AC could be restored with the maximum adsorption efficiency being conserved after the fifth cycles. Overall, the outcomes revealed that sulphuric acid-activated coffee husk activated carbon (SACH AC) can be used as prompt alternative for low-cost sorbent for treating dye-laden synthetic wastewaters. © Elsevier Inc.

Objectives: To quantify quercetin, gallic acid, rutin, naringin, and caffeic acid in the rhizome of Zingiber officinale different extracts in seven different solvents (methanol, ethanol, ethyl acetate, water, dichloromethane, chloroform, and n-hexane), for the first time, using HPLC/UV. Also, to study the anticancer activity of Zingiber officinale different extracts by evaluating its in vitro toxicity on HT-29 colorectal cancer cell line. Methods: The fresh and dried rhizomes were extracted using Soxhlet (SOX) and maceration (MAC) methods. Separation of compounds was conducted using HPLC. The cell line used for MTT cell proliferation assay antiproliferative; is HT-29 (HTB-38) colorectal adenocarcinoma. Results: The MTT test indicated that powder ginger extracted by MAC or SOX showed high cytotoxicity activity (IC50<50) against HT-29 cells, except water using SOX, which showed mild cytotoxicity activity. The fresh ginger extracted by MAC using dichloromethane and those extracted by SOX using ethyl acetate showed strong cytotoxicity activity (IC50 <50). Conclusion: The phenolic and flavonoid contents of ginger can vary depending on the different extracts from ginger plant. Also, HPLC results revealed that quercetin was the highest in all extracts.

Introduction: This study investigates the integration of Sufism into medieval Turkic nomadic culture, analyzing how Sufi rituals, saintly authority, and scholarly networks reshaped social structures and collective identity on the Eurasian steppe. Methods: We assembled a multidisciplinary corpus, including Divan‑i Ḥikmet verses, 12th-14th‑century hagiographies, waqf endowments, archaeological surveys, and secondary literature, and applied hermeneutic coding in NVivo to identify ritual motifs and symbolic continuities. Ragin’s comparative method organized data across four dimensions: ritual form, institutional patterns, symbolic vocabulary, and succession mechanisms, with intercoder reliability ensured through author reviews. Results: We found that communal dhikr ceremonies and whirling dances generated Durkheimian collective effervescence that amplified indigenous circle‑based traditions and accelerated Sufi adoption; that charismatic saints such as Khoja Aḥmad Yasawi transcended tribal loyalties through reputed miracles and moral prestige, founding khanqahs and neutral mazars to facilitate peaceful Islamization; and that Qurʾānic literacy, mastery of Sufi poetry, and formal ijāzas functioned as new forms of cultural capital enabling social mobility. Comparative analysis of South Asian, Anatolian, and North African cases confirms Sufism’s role as a cultural mediator adapting to local cosmologies. Discussion: Our findings show how Sufism simultaneously preserved pre‑Islamic values and transformed Turkic society, revealing the explanatory limits of Durkheim, Weber, and Bourdieu when applied in isolation and highlighting the value of a complementary theoretical approach. Copyright © 2025 Kurmanbek, Osserbayev, Shagyrbay, Azhimov and Kossalbayev.

With cardiovascular diseases (CVD) remaining a leading cause of mortality, wearable devices for monitoring cardiac activity have gained significant, renewed interest among the medical community. This paper introduces an innovative ECG monitoring system based on a single-lead ECG machine, enhanced using machine learning methods. The system only processes and analyzes ECG data, but it can also be used to predict potential heart disease at an early stage. The wearable device was built on the ADS1298 and a microcontroller STM32L151xD. A server module based on the architecture style of the REST API was designed to facilitate interaction with the web-based segment of the system. The module is responsible for receiving data in real time from the microcontroller and delivering this data to the web-based segment of the module. Algorithms for analyzing ECG signals have been developed, including band filter artifact removal, K-means clustering for signal segmentation, and PQRST analysis. Machine learning methods, such as isolation forests, have been employed for ECG anomaly detection. Moreover, a comparative analysis with various machine learning methods, including logistic regression, random forest, SVM, XGBoost, decision forest, and CNNs, was conducted to predict the incidence of cardiovascular diseases. Convoluted neural networks (CNN) showed an accuracy of 0.926, proving their high effectiveness for ECG data processing. © 2024 by the authors.

Investigation of the physical characteristics of mineral artifacts was undertaken with purpose of development of dating by the electron paramagnetic resonance (EPR) method in a new direction, by means of analysis of spectra of the carbonate probes from the surface of archaeological artifacts. The artifacts – samples of layers from the surface of ceramics and stone tools, containing impurities of quartz and alumosilicates, have been tested. For obtaining the physical characteristics and dating the complex of the methods and equipment has been used which allowed us to reveal specialties of mineral content and structure of the surface. There were chosen optimal conditions for registration, distinguishing and identification of the EPR signals from the paramagnetic centers. Applying of radiation of the ILU-10 accelerator with converter and consequent EPR-studying allowed to estimate the age of artifacts. © 2024 Academy of Sciences of Tatarstan, A.Kh. Khalikov Archaeology Institute. All rights reserved.

Sustainable development cannot be achieved by leaving behind vulnerable and marginalized groups like older persons who experience multidimensional inequalities and social exclusion. This study investigates the root causes, manifestations, and impacts of social exclusion faced by the elderly population in Kazakhstan through an interdisciplinary socio-anthropological lens. Utilizing qualitative and quantitative methods, including surveys, interviews, and empirical analysis, the research examines subjective experiences of loneliness, isolation, low social engagement, and barriers to accessing essential services among older adults. It highlights how factors like health status, income insecurity, ageism, lack of social support systems, and physical/digital accessibility issues intersect to produce and perpetuate social exclusion. In the course of the work carried out, it was revealed that the process of reducing the phenomenon of social exclusion provides an opportunity to increase the effectiveness of social policy, one of the key tasks of which is to ensure a high standard of living for the elderly. Among the results obtained, factors such as subjective feeling of loneliness, diagnosis of social isolation, low level of social activity, and so on, should be noted. Through a conceptual analysis, the main group of risks was considered, which includes a large list of various areas of public activity. Policy proposals include strengthening social protection, facilitating intergenerational solidarity, inclusive urban planning, digital inclusion and enhancing accessibility to public services tailored to older persons’ needs.

Sustainable potable groundwater supply is crucial for human development and the preservation of natural habitats. The largest endorheic inland lake in Kazakhstan, Balkhash Lake, is the main water resource for the arid southeastern part of the country. Several ore enrichment plants that are located along its shore have heavy metal pollution potential. The study area is located around a plant that has an evident anthropogenic impact on the Balkhash Lake aquatic ecological system, with ten known heavy metal toxic hotspots endangering fragile habitats, including some indigenous human communities. This study assessed the risk of heavy metal contamination from tailing dump operations, storage ponds, and related facilities and suggested management practices for preventing this risk. The coastal zone risk assessment analysis used an innovative integrated groundwater numerical flow and transport model that predicted the spread of groundwater contamination from tailing dump operations under several mitigation strategies. Heavy metal pollution prevention models included a no-action scenario, a filtration barrier construction scenario, and two scenarios involving the drilling of drainage wells between the pollution sources and the lake. The scenario assessment indicates that drilling ten drainage wells down to the bedrock between the existing drainage channel and the lake is the optimal engineering solution for confining pollution. Under these conditions, pollution from tailings will not reach Lake Balkhash during the forecast period. The methods and tools used in this study to enable mining activity without environmental implications for the region can be applied to sites with similar anthropogenic influences worldwide. © 2024 by the authors.