Search Results (4,569)

Superhydrophobic magnetic nanomaterials (SHMNMs) are emerging as multifunctional platforms for efficient oil–water separation due to their combination of extreme water repellency, strong oil affinity, and external magnetic responsiveness. This review presents a comprehensive analysis of recent advances in the design, synthesis, and environmental application of SHMNMs. The theoretical foundations of superhydrophobicity and the physicochemical behavior of magnetic nanoparticles are first outlined, followed by discussion of their synergistic integration. Key fabrication techniques—such as sol–gel synthesis, electrospinning, dip-coating, laser-assisted processing, and the use of biomass-derived precursors—are critically assessed in terms of their ability to tailor surface morphology, chemical functionality, and long-term durability. The review further explores the mechanisms of oil adsorption, magnetic separation, and material reusability under realistic environmental conditions. Special attention is paid to the scalability, mechanical resilience, and environmental compatibility of SHMNMs in the context of water treatment technologies. Current limitations, including reduced efficiency in harsh media, potential environmental risks, and challenges in material regeneration, are discussed. This work provides a structured overview that could support the rational development of next-generation superhydrophobic materials tailored for sustainable and high-performance separation of oil and organic pollutants from water. Full article

This paper presents the results of a study on the development of a processing technology for pyrite–cobalt concentrates to obtain iron oxide pigments (Fe₂O₃ and Fe₃O₄) via high-temperature hydrolysis. It was found that, in a single operation, the concentrate can be effectively purified from lead, zinc, and copper, yielding an iron–nickel–cobalt product suitable for further processing by standard technologies, such as smelting into ferronickel. The scientific originality of research concludes in a mechanism of stepwise selective chloride volatilization, which was established as follows: stage I (500–650 °C)—removal of lead; stage II (700–750 °C)—chlorination of copper and iron; stage III (850–900 °C)—volatilization of nickel and cobalt. Microprobe analysis of the powders obtained from high-temperature hydrolysis of FeCl₂·4H₂O and FeCl₃·6H₂O revealed the resulting Fe₃O₄ and Fe₂O₃ powders with particle sizes 50 μm and 100 μm. A visual color palette was created, corresponding to different Fe₃O₄/Fe₂O₃ ratios in the pigment composition—ranging from black (magnetite) to red (hematite)—and potential application areas. For the first time, the new technological scheme was proposed of pigments Fe₂O₃ and Fe₃O₄ production from pyrite–cobalt concentrates via combination of oxidized roasting with subsequent chlorination and high-temperature hydrolysis of the products. Full article

The Working Set concept, originally introduced by P. Denning for memory management, defines a dynamic subset of system elements actively in use. Designed to reduce page faults and prevent thrashing, it has proven effective in optimizing memory performance. This study explores the interdisciplinary potential of the Working Set by applying it to two distinct domains: virtual memory systems and epidemiological modeling. We demonstrate that focusing on the active subset of a system enables optimization in both contexts—minimizing page faults and containing epidemics via dynamic isolation. The effectiveness of this approach is validated through memory access simulations and agent-based epidemic modeling. The advantages of using the Working Set as a general framework for describing the behavior of dynamic systems are discussed, along with its applicability across a wide range of scientific and engineering problems. Full article

Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research. Full article

Wireless sensor networks have become a vital technology that is extensively applied across multiple industries, including agriculture, industrial operations, and smart cities, as well as residential smart homes and environmental monitoring systems. Security threats emerge in these systems through hidden routing-level attacks such as Wormhole and Sinkhole attacks. The aim of this research was to develop a methodology for detecting security incidents in WSNs by conducting real-time analysis of Wormhole and Sinkhole attacks. Furthermore, the paper proposes a novel detection methodology combined with architectural enhancements to improve network robustness, measured by hop counts, delays, false data ratios, and route integrity. A real-time WSN infrastructure was developed using ZigBee and Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS) technologies. To realistically simulate Wormhole and Sinkhole attack scenarios and conduct evaluations, we developed a modular cyber–physical architecture that supports real-time monitoring, repeatability, and integration of ZigBee- and GSM/GPRS-based attacker nodes. During the experimentation, Wormhole attacks caused the hop count to decrease from 4 to 3, while the average delay increased by 40%, and false sensor readings were introduced in over 30% of cases. Additionally, Sinkhole attacks led to a 27% increase in traffic concentration at the malicious node, disrupting load balancing and route integrity. The proposed multi-stage methodology includes data collection, preprocessing, anomaly detection using the 3-sigma rule, and risk-based decision making. Simulation results demonstrated that the methodology successfully detected route shortening, packet loss, and data manipulation in real time. Thus, the integration of anomaly-based detection with ZigBee and GSM/GPRS enables a timely response to security threats in critical WSN deployments. Full article

A second-order linear differential operator A is defined on a tree of arbitrary topology. Any internal vertex P of the tree divides the tree into $m_p$ branches. The restrictions $A_i,i=1,\dots ,m_p$ of the operator A on each of these branches, where the vertex P is considered the root of the branch and the Dirichlet boundary condition is specified at the root. These restrictions must be, in a sense, asymmetric (not similar) to each other. Thus, the distinguished class of differential operators A turns out to have only simple eigenvalues. Moreover, the matching conditions at the internal vertices of the graph contain a set of parameters. These parameters are interpreted as stiffness coefficients. This paper proves that a finite set of eigenvalues allows one to uniquely restore the set of stiffness coefficients. The novelty of the work is the fact that it is sufficient to know a finite set of eigenvalues of intermediate Weinstein problems for uniquely restoring the required stiffness coefficients. We not only describe the results of selected studies but also compare them with each other and establish interconnections. Full article

This study investigates the modification of bitumen using mechanochemically devulcanized crumb rubber. The objective of this research is to enhance the performance characteristics of bituminous binders while addressing the inherent limitations associated with conventional crumb rubber (CCR), such as insufficient dispersion, elevated viscosity, and phase instability. Preliminary chemical activation of the crumb rubber was performed using a planetary ball mill, followed by thermomechanical devulcanization on a two-roll open mixing mill. Structural features of the devulcanized crumb rubber were analyzed using infrared spectroscopy, which confirmed the breakdown of S–S bonds. This study presents a comparative analysis of the performance characteristics of rubber–bitumen binders produced using both conventional rubber crumb (CRC) and devulcanized rubber crumb (DRC). The use of DCR, obtained mechanochemically from rubber waste, improved penetration, Fraass breaking point and the ring and ball softening point on average at high concentrations (20; 25% crumb rubber) compared to conventional crumb rubber by 33%, 66% and 2.4%, respectively. Optical microscopy revealed the formation of a uniform mesh-like rubber structure within the bitumen matrix, which contributes to enhanced performance characteristics of the modified binder and improved mechanical strength of the material. The key contribution of this work lies in the development and experimental validation of an efficient approach to deep devulcanization of crumb rubber via mechanochemical activation using readily available nitrogen-containing reagents. Furthermore, the study establishes a direct correlation between the degree of devulcanization, the dispersion quality of rubber particles within the bitumen matrix, and the resultant performance characteristics of the modified binder. Full article

This paper provides geospatial and correlation analysis of heavy metal distribution in the soil cover of the city of Temirtau and its industrial zones. Based on 25 soil samples taken in 2024, concentrations of nine heavy metals (As, Pb, Zn, Cu, Ni, Co, Mn, Cr, Ba) were determined using X-ray fluorescence analysis. Spatial data interpolation was performed using the Kriging method in the ArcGIS Pro environment. The results showed the presence of localized extreme pollution zones, primarily near the Qarmet JSC metallurgical plant. The most significant exceedances of maximum permissible concentrations (MPC), up to 348× MPC for Cr, 160× MPC for Zn, and 72× MPC for As, were recorded at individual locations. Correlation analysis revealed a moderate positive relationship between several elements, particularly Mn and Cu (r = 0.64). Comparison of the spatial distribution of pollution with population data allowed for the assessment of potential environmental risks. This research emphasizes the need to implement systematic monitoring, sustainable land management practices, ecological maps, and preventive measures to reduce the long-term impact of heavy metals on ecosystems and public health, and to promote environmental sustainability in industrial regions. Full article

This work aims to develop approaches to processing and interpreting spectral entropy outcomes in the context of seismic data, as well as to establish a methodological foundation for subsequent integration into practical monitoring solutions. The objective of this study is to evaluate the effectiveness of the Shannon spectral entropy method in detecting and assessing short-term seismic events through a seismogram analysis. This method has demonstrated sensitivity to variations in the spectral characteristics of the registered signals. A threshold value for the increase in spectral entropy information has been pinpointed for reliable P-wave detection. The results could be applied in real-time automated seismic monitoring systems. In addition to the conventional spectral analysis techniques, the proposed methodology may serve as the input to the neural network models used in seismological applications. Full article

A synthetic methodology of the CuAAC “click” approach was exploited for the construction of 1,2-azolyltriazole quinine derivatives by the reaction of O-propargylquinine with azidomethyl-1,2-azoles in methanol. Quinine–piperidine and quinine–anabasine conjugates were obtained using a chloroacetate linker by reacting quinine chloroacetate with piperidine or anabasine in a diethyl ether medium. Cinchophene ester was obtained by the acylation of quinine with cinchophen acid chloride in methylene chloride. The antibacterial, fungicidal, analgesic and cytotoxic properties of the obtained compounds were examined. Full article

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

This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance of leaching solution. A reactive transport model incorporating uranium dissolution kinetics and acid–rock interactions were utilized to assess the accuracy of both traditional and proposed methods. The results reveal a significant spatial imbalance in sulfuric acid distribution, with up to 239.1 tons of acid migrating beyond the block boundaries. To reduce computational demands while maintaining predictive accuracy, two alternative methods, a streamline-based and a trajectory-based approach were proposed and verified. The streamline method showed close agreement with reactive transport modeling and was able to effectively identify the presence of intra-block reagent imbalance. The trajectory-based method provided detailed insight into flow dynamics but tended to overestimate acid overflow outside the block. Both alternative methods outperformed the conventional approach in terms of accuracy by accounting for geological heterogeneity and well spacing. The proposed methods have significantly lower computational costs, as they do not require solving complex systems of partial differential equations involved in reactive transport simulations. The proposed approaches can be used to analyze the efficiency of mineral In Situ Recovery at both the design and operational stages, as well as to determine optimal production regimes for reducing economic expenditures in a timely manner. Full article

Grapevine (Vitis vinifera L.) cultivation is an important agricultural sector worldwide. Its expansion into new areas, like Kazakhstan, brings significant phytosanitary risks. Viroids, such as grapevine yellow speckle viroid 1 (GYSVd-1) and hop stunt viroid (HSVd), are RNA pathogens that threaten vineyard productivity. They can cause a progressive decline through latent infections. Traditional diagnostic methods are usually targeted and therefore not suitable for thorough surveillance. In contrast, modern high-throughput sequencing (HTS) methods often face challenges due to their high costs and complicated sample preparation, such as ribosomal RNA (rRNA) depletion. This study introduces a simplified diagnostic workflow that overcomes these barriers. We utilized the latest Oxford Nanopore V14 cDNA chemistry, which is designed to prevent internal priming, by substituting a targeted oligo(dT)VN priming strategy to facilitate the sequencing of non-polyadenylated viroids from total RNA extracts, completely bypassing the rRNA depletion step and use of random oligonucleotides for c DNA synthesis. This method effectively detects and identifies both GYSVd-1 and HSVd. This workflow significantly reduces the time, cost, and complexity of HTS-based diagnostics. It provides a powerful and scalable tool for establishing strong genomic surveillance and phytosanitary certification programs, which are essential for supporting the growing viticulture industry in Kazakhstan. Full article

In the process of producing ferroalloys, a large amount of secondary raw materials is formed, including slag, aspiration dusts and sludge. The recycling of secondary raw materials can create resources and bring environmental and economic benefits. Wet secondary raw materials (WSRMs) are characterized by a high chromium oxide content (averaging 24%), but due to their high moisture levels, they cannot be directly used in arc furnaces. As a strategic approach, mixing WSRMs with drier, more chromium-rich dusts (up to 45% Cr₂O₃) has been proposed. This not only reduces the overall moisture content of the mixture but also enhances the metallurgical value of the charge material. This paper presents the results of laboratory studies on the agglomeration of secondary wet raw materials using briquetting, extrusion and pelletizing methods. The main factors influencing the quality of the resulting product were analyzed, including the method of agglomeration, the composition of the mixture, as well as the type and dosage of the binder component. The strength characteristics of the finished agglomerated samples were evaluated in terms of resistance to splitting, impact loads and falling. Notably, the selected binders are organic and polymer substances capable of complete combustion under metallurgical smelting conditions. Full article