There are presented results of the accumulation of polychlorinated biphenyls (PCBs) – the most toxic compounds among persistent organic pollutants (POPS) in the snow cover (SC) study (2018 and 2020) in the Almaty agglomeration (AA). Protection of the natural environment and the population from the efects of POPs, including PCBs, is one of the most acute problems for Kazakhstan. Тhe territory of AA is experiencing a serious technogenic load, the concentration of a number of pollutants in its natural objects exceeds the permissible standards. Snow cover among natural objects, is one of the informative indicators of pollution of the natural environment, including the air basin, and reflects the main trends in the spread of pollutants in the region.

The article presents a study on overburden deposit rock in Southeastern Kazakhstan, focusing on the lithological composition and water-physical properties of cover sediments in infiltration basins for artificial groundwater replenishment. Analysis at pit No. 5 revealed sediment layers affecting dynamic infiltration: the uppermost layer (0–0.5 m) consists of fine-grained, micaceous sand; sandy loams (0.5–1.4 m) exhibit good permeability; dark brown impermeable clays (1.4–1.7 m) act as a barrier; a second sandy loam (1.7–2.4 m) and medium-grained sands (2.4–2.8 m) provide high permeability; and mixed-grain sands (2.8 m and below) show minimal capillarity and emerging water-bearing properties at 3.5 m. These findings confirm that surface infiltration basins can effectively enhance groundwater reserves with minimal surface runoff. The study's practical significance lies in its scientific basis for designing and optimizing groundwater replenishment systems, allowing precise site selection and contributing to predictive models for assessing infiltration rates. Overall, the results strengthen water management practices in arid and semi-arid regions, demonstrating the suitability of these basins for artificial groundwater replenishment in Southeastern Kazakhstan.

It has been recognized that Blockchain technology contributes to environmentally sustainable development goals (SDGs). It has emerged as a disruptive innovation capable of transforming various economic and social sectors significantly. This conceptual paper is driven by the need to explore how blockchain, specifically a consortium-based Ethereum architecture, can be integrated into higher education institutions to ensure data sovereignty, integrity, and verifiability while adhering to legal and ethical standards such as GDPR. We propose a multi-layered blockchain-based model for Kazakhstan’s Unified Platform of Higher Education (UPHE). This model employs hybrid on-chain/off-chain data storage, smart contract automation, and a Proof-of-Authority consensus mechanism to address system limitations, including data centralization and inadequate verification of academic credentials. Empirical simulations using Blockscout and Ethereum-compatible tools demonstrate the model’s feasibility and performance. This paper contributes to the growing discussion on educational blockchain applications by presenting a scalable, secure, and transparent architecture that aligns with institutional governance and Environmental, Social, and Governance (ESG) principles. It also supports the objectives of UN SDG 4 (i.e., Quality education) by fostering trust, transparency, and equitable access to verifiable educational credentials.

The study presents a comparative assessment of eight machine learning (ML) algorithms - Random Forest (RF), Lasso Regression (LASSO), AdaBoost (ADB), Gradient Boosting Regressor (GBR), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LGBM), and K-Nearest Neighbors (KNN) - for modeling daily river discharge at ten hydrological stations within the Zhaiyk - Caspian water management basin. Model performance was evaluated using mean absolute error (MAE), mean squared error (MSE), and symmetric mean absolute percentage error (SMAPE). The highest predictive accuracy (MAE ≈ 0.3) was achieved by ensemble tree-based methods (Random Forest, CatBoost, Gradient Boosting, LightGBM, XGBoost), while LASSO and AdaBoost exhibited the weakest performance (MAE ≈ 22). Identifying the most significant predictors enhanced both model interpretability and forecasting quality. The findings highlight the importance of tailoring ML approaches to the specific characteristics of river basins and suggest promising prospects for their integration with physically based hydrological models to improve river discharge forecasting and strengthen water resources management under climate change conditions.

One of the main problems with graphite anodes in LIBs is the limited charge/discharge rate, especially for the lithization process. In recent years, in order to solve the above-mentioned problems, more and more attention has been paid to the practical use of silicon oxide-based anode materials in LIBs, due to its large amount in the earth's crust, low discharge potential, and high initial irreversible and reversible capacity of 1961 mA*h*g-1. The study explores a novel approach to producing high-purity SiO2 from rice husk (RH) and enhancing its electrochemical performance by incorporating a carbon coating, aiming to develop an advanced anode material for lithium-ion batteries (LIBs). The methodology involved a multi-step process: initially, RH was subjected to hydrochloric acid pre-treatment to remove impurities, followed by calcination to yield SiO2. Pure SiO2 was further processed with sodium hydroxide and hydrochloric acid to achieve high purity. To improve the electrochemical properties, SiO2 was coated with carbon derived from sucrose.

The concluding chapter provides a guiding map for successful R&D&I in the creative industries. After reiterating the book’s vision and the multiple approaches deployed for analysing R&D&I in the creative industries, the chapter draws the most important conclusions for each book chapter. In doing so it stresses the importance of understanding the historical context in which the concept of R&D&I developed in the creative industries, the relevance of an extended definition of R&D that aligns with real mechanisms of the sector, the need for developing novel R&D-based typologies of innovation and support mechanisms (e.g. funding) that meet the needs of R&D implementers and the context within which they operate. The chapter then uses these reflections to draw overall conclusions about the frameworks, models and pathways resulting from the research. It finally closes by stressing: (1) the need for expanding this research (geographically and content-wise), (2) the real social, economic and cultural value that R&D brings to creative economies and (3) the importance of innovative funding and support ecosystems that are aligned to the realities of the creative sector.

This paper presents the results of studies on intra-annual runoff changes in the Ile River basin based on data from gauging stations up to 2021. Changes in climatic characteristics that determine runoff formation in the mountainous and foothill areas of the river catchment have led to alterations in the water regime of the watercourses. The analysis of the temporal and spatial patterns of river flow formation in the basin, as well as its distribution by seasons and months, is essential for solving applied water management problems and assessing the risks of hazardous hydrological phenomena, such as high floods and low water levels. The statistical analysis of annual and monthly river runoff fluctuations enabled the identification of relatively homogeneous estimation periods during stationary observations under varying climatic conditions. The obtained characteristics of annual and intra-annual river runoff in the Ile River basin for the modern period provide insights into changes in average monthly water discharge and, more broadly, runoff volume during different phases of the water regime. In the future, these characteristics are expected to guide the design of hydraulic structures and the rational use of surface runoff in this intensively developing region of Kazakhstan.

This research investigates the biodiversity and ecological status of the Fraxinus sogdiana Bunge forests within Charyn Canyon, Kazakhstan, a unique ecosystem known for its high biodiversity and geological significance. Charyn Canyon, stretching for 154 km, contains over 1,500 plant species, 17 of which are listed in the Red Book of Kazakhstan. The relict grove of F. sogdiana occupies over 800 hectares of the 5,000-hectare floodplain area. The study assessed the photosynthetic parameters of Fraxinus L. and Populus L., measuring key indicators such as minimum fluorescence (Fo), variable fluorescence (Fv), maximum fluorescence (Fm), and chlorophyll content (mg m-²). Results show that F. sogdiana exhibited an Fv/Fm ratio of 0.735–0.828, indicating that some individuals are under stress. In contrast, Populus species showed higher photosynthetic efficiency with a maximum Fv/Fm value of 0.834. Floristic analysis revealed a complex plant community with significant species diversity, including xerophytes, mesophytes, and halophytes, indicative of the region's varied ecological zones. Vegetation indices derived from UAV mapping, including NDVI, GNDVI, and OSAVI, further supported these findings, showing higher photosynthetic activity and chlorophyll content in Populus than in Fraxinus. Correlation analysis between physiological parameters and vegetation indices highlighted significant relationships, particularly between NDVI and photosynthetic efficiency, providing insights into the health of the forest canopy. The study underscores the significant anthropogenic threats to the region, such as deforestation and uncontrolled grazing, accelerating habitat degradation, and reducing genetic diversity. The critical findings of this research underscore the urgent need for conservation efforts and provide a wealth of information that can guide these efforts, enlightening us about the state of these unique ecosystems and the measures needed to preserve them. © The Author(s) Publisher: University of Guilan.

Invisible gold research is essential for understanding gold mineralization, overcoming analytical limitations, and addressing the technological bottlenecks in the economic extraction of refractory gold, thereby unlocking the potential of these deposits and their tailings. To assess research trends and demand, this study analyzed 1300 records from the Web of Science database (1985–2024) using the cross-disciplinary publication index (CDPI), the co-authorship model, and the technology-economic linkage model (TELM), with visualizations generated via VOSviewer and Microsoft Excel. The analysis reveals a 65% increase in publications between 2015 and 2021, with a peak of 98 papers in 2021. Articles constitute the majority (84.6%), followed by conference proceedings (9.8%) and reviews (3.9%). Interdisciplinary contributions surged by 40% after 2015, particularly in “materials science”, as indicated by a high CDPI of 0.81; while a discipline-pair co-occurrence score between “materials science and nanotechnology” reached a CDPI of 0.75. Notably, the CDPI model reveals that 68% of advancements in extraction technologies between 2015 and 2024 originated from nanoscale-oriented invisible gold research published in geoscience-focused journals employing advanced nanotechnologies. Furthermore, the TELM framework identifies that between 2021 and 2024, high gold prices—ranging from $1,798/oz to $1,940/oz—were well correlated (R2 = 0.89) with publication counts, which remained consistently high at 94 to 98 papers annually. Two key methodological trends identified in this study for invisible gold research are: (1) the development of environmentally friendly extraction techniques, including biooxidation or thiosulfate leaching, and advanced pre-treatment processes; and (2) the adoption of high-precision analytical tools such as LA-ICP-MS, SIMS, and TIMA-X, which have significantly enhanced nanoscale gold detection and characterization. This methodological progress is further supported by the increase in annual research funding—from approximately $2–5 million when gold prices averaged $370/oz (1985–2000), to $10–30 million at around $700/oz (2001–2015), and up to $50–120 million as prices exceeded $1,500/oz (2016–2024)—demonstrating a strong positive association between rising gold prices and investment in invisible gold research. The findings reveal key trends in invisible gold research, demonstrating that Web of Science data, VOSviewer visualizations, and the CDPI and TELM frameworks provide a more reliable basis for identifying interdisciplinary patterns and economic drivers. They highlight not only scientific progress in mineral exploration, extraction technologies, and metallurgical methods, but also persistent challenges in the economic recovery of invisible gold. These insights offer a roadmap for future research, industrial application, and international collaboration. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

The accelerated development of industrialization has resulted in the extensive discharge of dyes into aquatic habitats, creating significant health hazards due to their poisonous and cancer-causing characteristics. This work introduces a new adsorbent called CUR-CPTMS-NZC, constructed of curcumin-functionalized natural zeolite clinoptilolite encapsulated in alginate beads. This adsorbent aims to improve the removal of methylene blue (MB) dye from wastewater. The functionalized adsorbent underwent characterization utilizing FT-IR, TGA, N2 gas adsorption-desorption, SEM, and zeta potential studies. The adsorption assessments examined the impact of contact time, adsorbent dosage, initial dye concentration, and pH on the efficacy of removing MB. Response Surface Methodology (RSM) with Central Composite Design (CCD) was employed to optimize the adsorption conditions, improving efficiency in removing dyes. Under optimized conditions: pH 7.8, adsorbent dosage of 0.5 g/L, and MB concentration of 13 mg/L, CUR-CPTMS-NZC beads achieved 100 % removal efficiency. The maximum adsorption capacity was found to be 69.81 mg/g, demonstrating the high efficiency of the adsorbent. Regeneration studies have verified the capacity to reuse the adsorbent for six cycles with less than 25 % reduction in the removal efficiency. This study offers an enduring remedy for the issue of dye contamination in wastewater, hence encouraging environmental sustainability and promoting breakthroughs in wastewater treatment technologies. © 2025 Elsevier B.V.