This article describes Ulytau National Park, its natural features, and unique attractions. The goal of this study is to create a favorable environment for using innovative technologies to discover historical sites and improve the tourism experience. It is necessary to focus on creating more sustainable and innovative solutions by considering the changing demands and expectations of tourists. This helps to improve the quality of services, develop more efficient tourist routes, meet the needs of eco-friendly tourism, and promote sustainable development in this sphere. In this case, GIS methodology provides a useful and systematic approach to work with geodata for decision-making, analysis, and visualization of spatial information. Using GIS maps in ecotourism contributes to creating more optimal and exciting routes, improving infrastructure, and providing more informative services for tourists. The integration of GIS technologies in tourism management not only enhances visitor experiences but also supports effective resource planning and environmental conservation within the national park. The study analysis provides recommendations for public and private organizations and travel agencies on using GIS technologies to achieve sustainable development in ecotourism. Constructed GIS maps give information about the park’s territory, the location of main objects and routes, which improves the awareness and orientation of tourists. The study highlights the importance of integrating GIS technologies with strategic planning, infrastructure development, and continuous monitoring to enhance the effectiveness of tourist routes and promote sustainable regional tourism. By applying cluster analysis, the study identified optimal routes and facilitated more efficient management of tourist flows. Additionally, GIS maps created during the study contribute to improved accessibility, providing tourists with up-to-date information on attractions, routes, and services. The findings demonstrate that GIS-based solutions can optimize the overall tourism experience, leading to more sustainable tourism practices and better resource management. The research showed that integrating data from multiple sources, including GPS devices and satellite images, allows for accurate mapping and route planning. This experience reveals new perspectives in tourist navigation, discovery, and obtaining information about historical sites and main tourist attractions. © 2025 Editura Universitatii din Oradea. All rights reserved.

In recent years, the escalating challenges of noise pollution in urban environments have necessitated the development of more sophisticated sound detection and classification systems. This research introduces a novel approach employing a Convolutional Long Short-Term Memory (ConvLSTM) network tailored for real-time impulsive sound detection in metropolitan landscapes. Impulsive sounds, characterized by sudden onsets and short durations—such as honking, abrupt shouts, or breaking glass—are inherently sporadic but can significantly impact urban soundscapes and the well-being of city dwellers. Traditional sound detection mechanisms often falter in identifying these ephemeral noises amidst the cacophony of urban life. The ConvLSTM network proposed in this study amalgamates the spatial feature learning capabilities of Convolutional Neural Networks (CNN) with the temporal sequence retention attributes of LSTM, culminating in an architecture that excels in both sound detection and classification tasks. The model was trained and evaluated on a comprehensive dataset sourced from various urban settings and demonstrated commendable proficiency in discerning impulsive sounds with minimal false positives. Furthermore, the system's real-time processing capabilities ensure timely interventions, paving the way for smarter noise management in cities. This research not only propels the frontier of impulsive sound detection but also underscores the potential of ConvLSTM in addressing multifaceted urban challenges. © (2023), (Science and Information Organization). All Rights Reserved.

Co3O4 nanoparticles synthesized by solution combustion synthesis present a versatile platform for the development of porous nanostructures with tunable morphology and physicochemical properties. Synthesis conditions and parameters such as fuel type; fuel-to-oxidizer ratio and temperature control lead yielding; and Co3O4 NPs with fine particle size, surface area, and porosity result in enhancing their electrochemical and catalytic capabilities. This review evaluates present studies about SCS Co3O4 NPs to study how synthesis parameter modifications affect both surface morphology and material structure characteristics including porosity features, which make their improved performance ideal for lithium-ion batteries and supercapacitors. Moreover, the integration of dopants with carbon-based hybrid composites enhances material conductivity and stability by addressing both capacity fading and low electronic conductivity concerns. This review mainly aims to explore the significant relation between fundamental material design principles together with practical uses and provides predictions about future research advancements that aim to enhance the performance of Co3O4 NPs in next-generation energy and environmental technology applications. © 2025 by the authors.

This study addresses the significant challenge of hole cleaning in drilling operations, which is essential for preventing stuck pipe incidents-a major cause of non-productive time and additional costs in drilling. This research aims to develop and validate machine learning models that enhance the prediction and optimization of cuttings removal during drilling. Utilizing a dataset derived from historical drilling operations, we employed regression analysis and neural network models to forecast the presence and height of slurry beds. The models were trained on variables such as borehole dimensions, drilling fluid characteristics, and operational parameters. Our results demonstrate that these models effectively predict conditions that could lead to stuck pipes, allowing for preemptive adjustments to drilling operations. This capability could significantly reduce unplanned downtime and associated costs. The primary contribution of this study lies in its innovative use of machine learning to transform predictive maintenance in drilling operations, offering substantial improvements in efficiency and safety. These advancements represent a crucial step forward in drilling technology, with the potential to mitigate risks and enhance operational decision-making across the industry.

Optimization techniques play a pivotal role in modern research and development across various engineering and technology sectors. It allows these methods to integrate cutting-edge concepts and sophisticated computational capabilities to provide robust solutions for intricate problems. Optimization has emerged as a rapidly evolving multidisciplinary field, serving as a conduit between industry and academia, with the primary goal of streamlining processes, minimizing resource wastage, and accelerating the time-to-market for new products and technologies. Optimization Tools and Techniques for Enhanced Computational Efficiency sheds light on the widespread application and importance of optimization techniques. By showcasing how researchers employ these tools to efficiently design and enhance products, systems, and processes across diverse industries, it highlights the interdisciplinary nature of optimization research fosters innovation in various fields beyond traditional boundaries. Covering topics such as biomedical engineering, smart cities, and student performance, this book is an excellent resource for engineers, scientists, technologists, policymakers, industry practitioners, educators, professionals, researchers, scholars, academics, and more. © 2025 by IGI Global Scientific Publishing. All rights reserved.

Using the optical interaction potential between an electron and a helium atom, we have calculated the momentum-transfer cross-section, collision frequency, and energy transfer rate during elastic electron–helium scattering, focusing on energies up to the ionization threshold of helium (24.6 eV). The interaction potential includes static, polarization, and exchange contributions, accurately representing the scattering process in this range. The optical potential method is well-suited for this analysis, as it effectively reduces the complexity of multiparticle interactions while maintaining the essential physics of elastic scattering. The calculated collision frequency as a function of energy exhibits a distinct maximum near 5 eV, consistent with experimental observations, which has not been captured in earlier theoretical studies. The energy transfer rate, derived using the effective collision frequency, demonstrates efficient energy exchange at low electron energies, with a gradual decline as the energy approaches the ionization threshold. These findings offer critical insights into plasma processes in the diverter region of tokamaks, where helium atoms play a significant role, and contribute to modeling energy transport properties such as electron mobility and temperature equilibrium. The results can serve as a valuable reference for plasma simulations and fusion research applications.

Background: Diabetic retinopathy (DR) is the most common complication of diabetes, leading to blindness. The asymptomatic onset and the existing difficulties in diagnosing warrant the search for biomarkers that can facilitate the early diagnosis of DR. The aim of this study was to evaluate the potential of plasma microRNAs (miRNAs), which have previously been shown to be involved in the pathogenesis of DR and differentially expressed in plasma/serum of patients, as biomarkers for DR in the Kazakhstani population. Materials and Methods: Using quantitative RT-PCR, we compared the levels of ten candidate miRNAs in plasma among three groups: type 2 diabetes mellitus (T2DM) patients with DR (DR patients, N = 100), T2DM patients without DR (noDR patients, N = 98), and healthy controls (N = 30). Results: Level of miR-423-3p was significantly reduced in DR patients compared to noDR patients (pFDR = 5.4 × 10−3). Levels of miR-423-3p and miR-221-3p were significantly reduced in DR patients compared to controls (pFDR = 5.4 × 10−3 and 0.024, respectively), level of miR-23a-3p was significantly reduced in noDR patients compared to controls (pFDR = 0.047), levels of miR-221-3p and miR-23a-3p were significantly reduced in T2DM patients (combined group) compared to controls (pFDR = 0.047, and 0.049, respectively). Also, there were several significant differences between groups formed based on clinical-pathological characteristics, but none of these results remained significant after adjustment for multiple comparisons. Correlation analysis revealed weak associations between the levels of miR-423 and miR-221-3p and DR staging (pFDR = 1.3 × 10−3 and 0.026, respectively), and fair associations between the levels of miR-29b-3p and miR-328-3p and diabetes duration in noDR patients (pFDR = 8.8 × 10−3 and 0.016, respectively). According to receiver operating characteristic (ROC) analysis, only miR-23a-3p can be considered a potential biomarker with moderate informativeness for diagnosing proliferative DR (PDR); however, a larger sample size is needed to verify this finding. Furthermore, the small magnitude of observed changes in miRNA levels between groups significantly complicates classification. Conclusions: Due to the low specificity and small magnitude of deviations from the norm, the studied miRNAs have low potential in the diagnosis of DR. Copyright 2025 Magazova et al.

Ore deposits, taken in the traditional interpretation of the concept as “natural or man-made accumulations of metallic minerals in the Earth’s crust or on the Earth’s surface, development of which is economical”, are formed during the time length commensurate with the geological time of formation of complexes of minerals and rocks. In the practice of subsoil use, ore deposits are developed 5–10 thousand times faster than they can be recreated in the subsoil, so the world civilization faces the main task of solving the problems of providing mankind with metal resources for their safe, economically efficient and technologically feasible extraction on the historical time scale. This problem is complicated by the need to simultaneously address the environmental consequences of human impact on nature. The complications of implementing practical measures depend on two objective factors: —the impending complete depletion of metal reserves in the continental earth’s crust to a depth of anthropogenic-and-technological capability HATC = 5 km within 30–1500 years depending on the type of metal; —the demand for metals which continuously increase in geometric progression in relation to the growth of the population. The authors propose new trends of development of material basis to meet the necessaries by creation of reproduction of reserves using deposits of new type to be mined with application of new geotechnologies and mineralogical sciences, and with a full closed cycle of multiple use of metals.

The aim of the work is to justify the possibility of using organic polymers as a binding material for a positive temperature technology designed for long-term equipment of operational wells of various purposes with systems for mechanical purification of liquid and gaseous mineral resources in productive horizons located at depths greater than 200 m, represented by medium-grained, fine-grained, silty, and dusty sands. The work utilizes methods of analysis of innovative technologies and materials, synthesis and research of materials, as well as the development of systems for mechanical purification of liquid mineral resources, along with the generalization of scientific and technical information. The selection of the binding material for the polymer-gravel composite of the inverse gravel filter of the block type has been justified, as well as the technology for its use in systems for the mechanical purification of liquid and gaseous mineral resources, intended for the equipment of productive horizons. For the first time, the use of water-based binding materials containing organic polymers for solidification of loose gravel material into a block structure of a gravel filter for mechanical purification systems of operational wells has been justified, according to the proposed technology. For the first time, the dependence of the physical-mechanical properties of the polymer-gravel composite on the mass concentration of the binding material has been established. It lies in the development of a program and conducting studies on the physical-mechanical properties of the polymer-gravel composite filter, and based on this, the development of well-founded recommendations for determining the parameters of technologies for manufacturing systems for mechanical purification of mineral resources and equipping hydrogeological wells with them. © 2025 Latvia University of Life Sciences and Technologies. All rights reserved.

This article examines the qualitative and quantitative indicators of the reverse supply chain strategy. These indicators are crucial for evaluating the effectiveness and sustainability of the reverse supply chain. The study explores the reverse supply chain for producing new construction materials from mining and metallurgical industry waste in the Republic of Kazakhstan. Utilizing industrial tailings for further processing and the production of new products will address strategic, environmental, and economic challenges. Based on the example of the Ridder Metallurgical Complex of KazZinc LLP, qualitative and quantitative indicators are proposed for achieving the strategic goals of sustainable development in the reverse supply chain. The list of indicators requires expansion and refinement for further research.