Search Results (238)

At present, various advanced technologies for field development based on gas-enhanced oil recovery (EOR) methods are widely applied worldwide. These include high-pressure gas injection (hydrocarbon gases, nitrogen, flue gases), water-alternating-gas (WAG) injection, and carbon dioxide (CO₂) flooding. This study presents the results of filtration experiments investigating the application of gas EOR methods using core samples from a heavy oil reservoir. The primary objective of these experiments was to determine the oil displacement factor and analyze changes in interfacial tension upon injection of different gas agents. The following gases were utilized for modeling gas EOR processes: nitrogen (N₂), carbon dioxide (CO₂), and hydrocarbon gases (methane, propane). The core samples used in the study were obtained from the East Moldabek heavy oil field in Kazakhstan. Based on the results of the filtration experiments, carbon dioxide (CO₂) injection was identified as the most effective gas EOR method in terms of increasing the oil displacement factor, achieving an incremental displacement factor of 5.06%. Other gas injection methods demonstrated lower efficiency. Full article

The study presents a comprehensive assessment of the combustion efficiency of low-grade coal from the Karazhyra deposit in small- and medium-capacity boiler units of the energy workshops operated by Vostokenergo LLP (East Kazakhstan Region, Kazakhstan). It was found that the average annual thermal energy output amounts to 2,387,348.85 GJ with a coal consumption of 164,328.5 tons. Based on operational data from 2016 to 2017, the average thermal efficiency (boiler efficiency) was 66.03%, with a maximum value of 75% recorded at the Zhezkent energy workshop. The average lower heating value (LHV) of the coal was 19.41 MJ/kg, which is below the design value of 20.52 MJ/kg, indicating the use of coal with reduced energy characteristics and elevated ash content (21.4%). The unburned carbon content in the ash and slag waste (ASW) was determined to be between 14 and 35%, indicating incomplete combustion. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses revealed the presence of microspheres, porous granules, and coal residues, with silicon and aluminum oxides dominating the composition (up to 70.49%). Differences in the pollutant potential of ash from different boiler units were identified. Recommendations were substantiated regarding the adjustment of the air–fuel regime, modernization of combustion control systems, and utilization of ASW. The results may be used to develop measures aimed at improving the energy efficiency and environmental safety of coal-fired boiler plants. Full article

This study examines the development of the digital economy and society in the Republic of Kazakhstan by combining international benchmarking with a context-specific national framework. It highlights the limitations of existing global indices such as DESI, NRI, and EGDI in capturing the structural and institutional dimensions of digital transformation in emerging economies. To address this gap, the study introduces a novel composite metric, the Index of Digital Economy Development (IDED), which integrates five sub-indices: infrastructure, usage, human capital, economic digitization, and transformation effectiveness. The methodology involves comparative index analysis, the construction of the IDED, and statistical validation through a public opinion survey and regression modeling. Key findings indicate that cybersecurity is a critical yet under-represented component of digital development, showing strong empirical correlations with DESI scores in benchmark countries. The results also highlight Kazakhstan’s strengths in digital public services and internet access, contrasted with weaknesses in business digitization and innovation. The proposed IDED offers a more comprehensive and policy-relevant tool for assessing digital progress in transitional economies. This study contributes to the literature by proposing a replicable index structure and providing empirical evidence for the inclusion of cybersecurity in national digital economy assessments. The aim of the study is to assess Kazakhstan’s digital economy development by addressing limitations in global measurement frameworks. Methodologically, it combines comparative index analysis, the construction of a national composite index (IDED), and statistical validation using a regional survey and regression analysis. The findings reveal both strengths and gaps in Kazakhstan’s digital landscape, particularly in cybersecurity and SME digitalization. The IDED introduces an innovative, context-sensitive framework that enhances the measurement of digital transformation in transitional economies. Full article

This article deals with the effect of Kr¹⁵⁺ ion irradiation on the structure and properties of partially stabilized zirconium dioxide (ZrO₂ + 3 mol. % Y₂O₃) ceramics. Ion irradiation is used to simulate radiation damage typical of operating conditions in nuclear reactors and space technology. It is shown that with an increase in the irradiation fluence, point defects are formed, dislocations accumulate, and the crystal lattice parameters change. At high fluences (>10¹³ ions/cm²), a phase transition of the monoclinic (m-ZrO₂) phase to the tetragonal (t-ZrO₂) and cubic (c-ZrO₂) modifications is observed, which is accompanied by a decrease in the crystallite size and an increase in internal stresses. Changes in the mechanical properties of the material were also observed: at moderate irradiation fluences, strengthening is observed due to the formation of dislocation structures, whereas at high fluences (>10¹⁴ ions/cm²), a decrease in strength and a potential amorphization of the structure begins. The change in the phase composition was confirmed by X-ray phase analysis and Raman spectroscopy. The results obtained allow a deeper understanding of the mechanisms of radiation-induced phase transformations in stabilized ZrO₂ and can be used in the development of ceramic materials with increased radiation resistance. Full article

Accurate river discharge forecasting remains a critical challenge in hydrology, particularly in data-scarce mountainous regions where in situ observations are limited. This study investigated the potential of long short-term memory (LSTM) networks to improve discharge prediction by leveraging spatially distributed reanalysis data. Using the ERA5-Land dataset, we developed an LSTM model that integrates grid-based meteorological inputs and assesses their relative importance. We conducted experiments on two snow-dominated basins with contrasting physiographic characteristics, the Uba River basin in Kazakhstan and the Flathead River basin in the USA, to answer three research questions: (1) whether full-grid input outperforms reduced configurations and models trained on Caravan, (2) the impact of spatial resolution on accuracy and efficiency, and (3) the effect of partial spatial coverage on prediction reliability. Specifically, we compared the full-grid LSTM with a single-cell LSTM, a basin-average LSTM, a Caravan-trained LSTM, and coarser cell aggregations. The results demonstrate that the full-grid LSTM consistently yields the highest forecasting performance, achieving a median Nash–Sutcliffe efficiency of 0.905 for Uba and 0.93 for Middle Fork Flathead, while using coarser grids and random subsets reduces performance. Our findings highlight the critical importance of spatial input richness and provide a reproducible framework for grid selection in flood-prone basins lacking dense observation networks. Full article

This study investigates the effects of ultrasonic nanocrystalline surface modification (UNSM) on the formation of nitride layers in Ti-6Al-4V alloy during ion-plasma nitriding (IPN). Various UNSM parameters, including vibration amplitude, static load, and processing temperature, were systematically varied to evaluate their influence on microstructure, hardness, elastic modulus, and tribological behavior. The results reveal that pre-treatment with optimized UNSM conditions significantly enhances nitrogen diffusion, leading to the formation of dense and uniform TiN/Ti₂N layers. Samples pre-treated under high-load and elevated-temperature UNSM exhibited the greatest improvements in surface hardness (up to 25%), elastic modulus (up to 18%), and wear resistance, with a reduced and stabilized friction coefficient (~0.55). Scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses confirmed microstructural densification, grain refinement, and increased nitride phase intensity. These findings demonstrate not only the scientific relevance but also the practical potential of UNSM as an effective surface activation technique. The hybrid UNSM + IPN approach may serve as a promising method for extending the service life of load-bearing biomedical implants and engineering components subjected to intensive wear. Full article

This study proposes an interpretable hybrid deep learning framework for classifying attention deficit hyperactivity disorder (ADHD) using EEG signals recorded during cognitively demanding tasks. The core architecture integrates convolutional neural networks (CNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) layers to jointly capture spatial and temporal dynamics. In addition to the final hybrid architecture, the CNN–GRU–LSTM model alone demonstrates excellent accuracy (99.63%) with minimal variance, making it a strong baseline for clinical applications. To evaluate the role of global attention mechanisms, transformer encoder models with two and three attention blocks, along with a spatiotemporal transformer employing 2D positional encoding, are benchmarked. A hybrid CNN–RNN–transformer model is introduced, combining convolutional, recurrent, and transformer-based modules into a unified architecture. To enhance interpretability, SHapley Additive exPlanations (SHAP) are employed to identify key EEG channels contributing to classification outcomes. Experimental evaluation using stratified five-fold cross-validation demonstrates that the proposed hybrid model achieves superior performance, with average accuracy exceeding 99.98%, F1-scores above 0.9999, and near-perfect AUC and Matthews correlation coefficients. In contrast, transformer-only models, despite high training accuracy, exhibit reduced generalization. SHAP-based analysis confirms the hybrid model’s clinical relevance. This work advances the development of transparent and reliable EEG-based tools for pediatric ADHD screening. Full article

This paper presents the results of a comprehensive study of the structure, phase composition, thermal corrosion, and tribological properties of multilayer gradient coatings based on YSZ/NiCrAlY obtained using detonation spraying. X-ray phase analysis showed that the coatings consist entirely of metastable tetragonal zirconium dioxide (t’-ZrO₂) phase stabilized by high temperature and rapid cooling during spraying. SEM analysis confirmed the multilayer gradient phase distribution and high density of the structure. Wear resistance, optical profilometry, wear quantification, and coefficient of friction measurements were used to evaluate the operational stability. The results confirm that the structural parameters of the coating, such as porosity and phase gradient, play a key role in improving its resistance to thermal corrosion and CMAS melt, which makes such coatings promising for use in high-temperature applications. It is shown that a dense and thick coating effectively prevents the penetration of aggressive media, providing a high barrier effect and minimal structural damage. Tribological tests in the temperature range from 21 °C to 650 °C revealed that the best characteristics are observed at 550 °C: minimum coefficient of friction (0.63) and high stability in the stage of stable wear. At room temperature and at 650 °C, there is an increase in wear due to the absence or destabilization of the protective layer. Full article

Hydroxyapatite (HA) has become a widely used material for bone grafting and surface modification of titanium-based orthopedic implants due to its excellent biocompatibility. Among various coating techniques, microplasma spraying (MPS) has gained significant industrial relevance. However, the clinical success of HA coatings also depends on their adhesion to the implant substrate. Achieving durable fixation and reliable biological integration of orthopedic implants remains a major challenge due to insufficient coating adhesion and limited osseointegration. This study addresses challenges in dental and orthopedic implantology by evaluating the microstructure, mechanical properties, and biological behavior of bilayer coatings composed of a zirconium (Zr) sublayer and an HA top layer, applied via MPS onto titanium alloy. Surface roughness, porosity, and adhesion were characterized, and pull-off and shear tests were used to assess mechanical performance. In vitro biocompatibility was tested using rat mesenchymal stem cells (MSCs) to model osteointegration. The results showed that the MPS-fabricated Zr–HA bilayer coatings achieved a pull-off strength of 28.0 ± 4.2 MPa and a shear strength of 32.3 ± 3.2 MPa, exceeding standard requirements. Biologically, the HA top layer promoted a 45% increase in MSC proliferation over three days compared to the uncoated titanium substrate. Antibacterial testing also revealed suppression of E. coli growth after 14 h. These findings support the potential of MPS-applied Zr-HA coatings to enhance both the mechanical integrity and biological performance of titanium-based orthopedic implants. Full article

Multilayer thin films composed of cobalt (Co), carbon (C), and chromium (Cr) possess promising electromagnetic properties, yet the combined Co–C–Cr system remains underexplored, particularly regarding its performance as a microwave absorber. Existing research has primarily focused on binary Co–C or Co–Cr compositions, leaving a critical knowledge gap in understanding how ternary multilayer architectures influence electromagnetic behavior. This study addresses this gap by investigating the structure, phase composition, and microwave absorption performance of Co–C–Cr multilayer coatings fabricated via magnetron sputtering onto porous silicon substrates. This study compares four-layer and eight-layer configurations to assess how multilayer architecture affects impedance matching, reflection coefficients, and absorption characteristics within the 8.2–12.4 GHz frequency range. Structural analyses using X-ray diffraction and transmission electron microscopy confirm the coexistence of amorphous and nanocrystalline phases, which enhance absorption through dielectric and magnetic loss mechanisms. Both experimental and simulated results show that increasing the number of layers improves impedance gradients and broadens the operational bandwidth. The eight-layer coatings demonstrate a more uniform absorption response, while four-layer structures exhibit sharper resonant minima. These findings advance the understanding of ternary multilayer systems and contribute to the development of frequency-selective surfaces and broadband microwave shielding materials. Full article

Flood hazards have increasingly threatened the East Kazakhstan region in recent decades due to climate change and growing anthropogenic pressures, leading to more frequent and severe flooding events. This article considers an approach to modeling and forecasting river runoff using the example of the small Kurchum River in the East Kazakhstan region. The main objective of this study was to evaluate the numerical performance of the flood hazard model by comparing simulated flood extents with observed flood data. Two types of data were used as initial data: topographic data (digital elevation models and topographic maps) and hydrological data, including streamflow time series from stream gauges (hourly time steps) and lateral inflows along the river course. Spatially distributed rainfall forcing was not applied. To build the model, we used the software packages of HEC-RAS version 5.0.5 and MIKE version 11. Using retrospective data for 3 years (2019–2021), modeling was performed, the calculated boundaries of possible flooding were obtained, and the highest risk zones were identified. A dynamic map of depth changes in the river system is presented, showing the process of flood wave propagation, the dynamics of depth changes, and the expansion of the flood zone. Temporal flood inundation mapping and performance metrics were evaluated for each individual flood event (2019, 2020, and 2021). The simulation outcomes closely correlate with actual flood events. The assessment showed that the model data coincide with the real ones by 91.89% (2019), 89.09% (2020), and 95.91% (2021). The obtained results allow for a clarification of potential flood zones and can be used in planning measures to reduce flood risks. This study demonstrates the importance of an integrated approach to modeling, combining various software packages and data sources. Full article

In this study, the process of electrolytic–plasma nitrocarburizing (EPNC) of 20-grade steel was investigated using various electrolytes and temperature regimes. At the first stage, optical spectral analysis of plasma emission during EPNC was carried out with spectral registration in the range of 275–850 nm, which allowed the identification of active components (Hα, CN, Fe I, O I lines, etc.) and the calculation of electron density. Additionally, the EPNC process was recorded using a high-speed camera (1500 frames per second), which made it possible to visually evaluate the dynamics of arc and glow discharges under varying electrolyte compositions. At the next stage, the influence of temperature regimes (650 °C, 750 °C, and 850 °C) on the formation of the hardened layer was studied. Using SEM and EDS methods, the morphology, phase zones, and the distribution of chemical elements were determined. Microhardness measurements along the depth and friction tests were carried out. It was found that a temperature of 750 °C provides the best balance between the uniformity of chemical composition, high microhardness (~800 HV), and a minimal coefficient of friction (~0.48). The obtained results confirm the potential of the selected EPNC regime for improving the performance characteristics of 20-grade steel. Full article

The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm³), Cd (up to 0.8 mg/dm³), and Cu (up to 0.051 mg/dm³). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R² = 0.903), Glubochanka (R² = 0.602), and Tikhaya (R² = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R² = 0.130), Ulba (R² = 0.100), and Krasnoyarka (R² = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article

The Kalba–Narym metallogenic belt is located in East Kazakhstan, which displays rare metal mineralization. The Kvartsevoye rare metal Li–Ta–Nb deposit is located in the north-western ore district. This study presents the results of geological, mineralogical, geochemical, and geochronological analyses of rare metal granite pegmatites. Rare metal mineralization belongs to a field of variably differentiated pegmatites, including barren, quartz–albite–muscovite, muscovite, and muscovite–quartz–albite microcline mineral associations. This study established that the rare metal mineralization is localized in the quartz–albite–muscovite zone. The main concentrator minerals of rare metals are spodumene for Li and tantalite–columbite for Ta and Nb. Ar/Ar dating of the muscovite allowed us to establish the age of mineralization during the period of 288–285 Ma. The present study enabled the linkage of rare metal mineralization with the differentiation processes of the granites of the Kalba complex. Full article

Additive manufacturing reshapes concrete construction, yet routine strength verification of printed elements still depends on destructive core sampling. This study evaluates whether standard 70 mm cubes—corrected by a single factor—can provide an equally reliable measure of in situ compressive strength. Five Portland-cement mixes, with and without ash-slag techno-mineral filler, were extruded into wall blocks on a laboratory 3D printer. For each mix, the compressive strengths of the cubes and ∅ 28 mm drilled cores were measured at 7, 14 and 28 days. The core strengths were consistently lower than the cube strengths, but their ratios remained remarkably stable: the transition coefficient clustered between 0.82 and 0.85 (mean 0.83). Ordinary least-squares regression of the pooled data produced the linear relation ${\widehat{R}}_{core}$ [MPa] = 0.97 ${\widehat{R}}_{cube}$ − 4.9, limiting the prediction error to less than 2 MPa (under 3% across the 40–300 MPa range) and outperforming more complex machine-learning models. Mixtures containing up to 30% ash-slag filler maintained structural-grade strength while reducing clinker demand, underscoring their sustainability potential. The results deliver a simple, evidence-based protocol for non-destructive strength assessment of 3D-printed concrete and provide quantitative groundwork for future standardisation of quality-control practices in additive construction. Full article