Search Results (2,524)

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

The structural design of rail vehicle bodies significantly influences rail vehicle performance, passenger comfort, and operational efficiency. This study presents a comparative analysis of three key concepts of a rail vehicle body, namely a differential, an integral, and a hybrid structure, with a focus on their structural principles, material utilization, and implications for manufacturability and maintenance. Three rail vehicle body variants were developed, each incorporating a low-floor configuration to enhance accessibility and interior layout flexibility. The research explores the suitable placement of technical components such as a power unit and an air-conditioning system, and it evaluates interior layouts aimed at maximizing both passenger capacity and their travelling comfort. Key features, including door and window technologies, thermal comfort solutions, and seating arrangements, are also analyzed. The study emphasizes the importance of compromises between structural stiffness, reparability, production complexity, and passenger-oriented design considerations. A part of the research includes a proposal of three variants of a rail vehicle body frame, together with their strength analysis by means of the finite element method. These analyses identified that the maximal permissible stresses for the individual versions of the frame were not exceeded. Findings contribute to the development of more efficient, accessible, and sustainable regional passenger rail vehicles. Full article

Automated vehicles controlled by artificial intelligence are becoming capable of making moral decisions independently. This study investigates the differences in participants’ perceptions of the moral decision-maker’s permissibility when viewing scenarios (pre-test) and after witnessing the outcomes of moral decisions (post-test). It also investigates how permissibility, ten typical moral emotions, and perceived moral agency fluctuate when AI and the human driver make deontological or utilitarian decisions in a pedestrian-sacrificing dilemma (Experiment 1, N = 254) and a driver-sacrificing dilemma (Experiment 2, N = 269) from a third-person perspective. Moreover, by conducting binary logistic regression, this study examined whether these factors could predict the non-decrease in permissibility ratings. In both experiments, participants preferred to delegate decisions to human drivers rather than to AI, and they generally preferred utilitarianism over deontology. The results of perceived moral emotions and moral agency provide evidence. Moreover, Experiment 2 elicited greater variations in permissibility, moral emotions, and perceived moral agency compared to Experiment 1. Moreover, deontology and gratitude could positively predict the non-decrease in permissibility ratings in Experiment 1, while contempt had a negative influence. In Experiment 2, the human driver and disgust were significant negative predictor factors, while perceived moral agency had a positive influence. These findings deepen the comprehension of the dynamic processes of autonomous driving’s moral decision-making and facilitate understanding of people’s attitudes toward moral machines and their underlying reasons, providing a reference for developing more sophisticated moral machines. Full article

Smart contracts and cryptocurrency wallets are foundational components of decentralized applications (dApps) on blockchain platforms such as Ethereum. While these technologies enable secure, transparent, and automated transactions, their integration also introduces complex security challenges. This study presents a security-oriented analysis of smart contract and wallet integration, focusing on BlockScribe—a decentralized Ethereum-based application for digital record certification. We systematically identify and categorize security risks arising from the interaction between wallet interfaces and smart contract logic. In particular, we analyze how user authorization flows, transaction design, and contract modularity affect the security posture of the entire dApp. To support our findings, we conduct an empirical evaluation using static analysis tools and formal verification methods, examining both contract-level vulnerabilities and integration-level flaws. Our results highlight several overlooked attack surfaces in wallet–contract communication patterns, including reentrancy amplification, permission mismanagement, and transaction ordering issues. We further discuss implications for secure dApp development and propose mitigation strategies that improve the robustness of wallet–contract ecosystems. This case study contributes to a deeper understanding of integration-layer vulnerabilities in blockchain-based systems and offers practical guidance for developers and auditors aiming to strengthen smart contract security. Full article

Many hospitals still lack digital traceability in hygiene and cleaning management, leading to operational inefficiencies and inconsistent quality control. This study aims to establish cleaning and hygiene processes in healthcare services that are planned in accordance with standards, as well as to enhance the traceability and sustainability of these processes through digitalization. This study proposes a Hyperledger Fabric-based blockchain architecture to establish a reliable and transparent quality assurance system in process management. The proposed Quality Assurance Model utilizes digital technologies and IoT-based RFID devices to ensure the transparent and reliable monitoring of cleaning processes. Operational data related to cleaning processes are automatically recorded and secured using a decentralized blockchain infrastructure. The permissioned nature of Hyperledger Fabric provides a more secure solution compared to traditional data management systems in the healthcare sector while preserving data privacy. Additionally, the execute–order–validate mechanism supports effective data sharing among stakeholders, and consensus algorithms along with chaincode rules enhance the reliability of processes. A working prototype was implemented and validated using Hyperledger Caliper under resource-constrained cloud environments, confirming the system’s feasibility through over 100 TPS throughput and zero transaction failures. Through the proposed system, cleaning/hygiene processes in patient rooms are conducted securely, contributing to the improvement of quality standards in healthcare services. Full article

The presence of lead (Pb) and cadmium (Cd) can have considerable effects on the environment and on humans. The present study examines their levels in two lakes with different trophic levels located in northwestern Poland; their concentrations were determined in water and the bottom sediments, in common reed and in the organs of pike, bream and roach. The work also evaluates Pb and Cd bioavailability in bottom sediments, their potential for biomagnification, their bioaccumulation in the food chain and risk to human consumers. Metal concentrations were determined by graphite furnace atomic absorption spectrometry (GFAAS). The geochemical fractions of the metals were isolated by sequential extraction. Both Pb and Cd demonstrated low bioavailability, with the carbonate fraction playing a key role in their bioconversion. The concentrations of Pb and Cd in some organs and tissue types of fish and reeds correlated with their levels in water and sediments. No biomagnification was observed between the studied fish species. Calculations based on BMDL, TWI and THQ concentrations found Pb and Cd levels in the edible parts of fish to be within permissible limits and not to pose any threat to consumer health. Full article

Zoning policies play a critical role in shaping the geography of urban and suburban development in the United States. Using data from the National Zoning and Land-Use Database and tract-level census data from 42 Metropolitan Statistical Areas, we classify metros into four zoning regime types based on the relative restrictiveness of urban and suburban land-use policies and compare trends in population growth and neighborhood change across these regimes. Our findings show that suburban areas have outpaced urban cores in population growth across all zoning configurations, with the most pronounced growth occurring in metros where restrictive urban zoning coexists with permissive suburban regulation. This growth is disproportionately concentrated in affluent suburban neighborhoods, suggesting a spatial sorting of access to resources and amenities. We also find that urban–suburban gentrification gaps are the smallest in these asymmetrical zoning regimes, suggesting that permissive suburban land use may facilitate spillover effects from constrained cores. These findings suggest that zoning asymmetries shape not only the geography of growth but also the spatial dynamics of gentrification. We argue for a metropolitan perspective on land-use governance to better understand the interconnected nature of suburbanization and the spatial expansion of gentrification. Full article

This study aimed to assess the use of selected raw materials, such as whole-grain oat flakes, pumpkin seeds, sunflower seeds, and flaxseeds, to obtain bars using baking and drying methods. Modifying the bars’ composition involved selecting the fibre preparation, replacing water with NFC juice, and using fresh apple juice and apple pomace. The Psyllium fibre preparation, also in the form of a mixture with apple fibre, was the most useful in dough cohesion and the quality of the bars. Baked bars were characterised by higher sensory quality than those obtained by drying. Microwave–convection drying was a good alternative to baking, primarily due to the lower temperature resulting in a lower acrylamide content and comparable product quality. The basic grain ingredients and fibre preparations mainly shaped the nutritional and energy value and the sensory and microbiological quality. Modifying the recipe using NFC or fresh juice and apple pomace allowed the bars to develop new properties and quality characteristics. The use of NFC juices resulted in a reduction in the pH of the bars, which is associated with a higher microbiological quality of the bars. All bars had low acrylamide content, significantly lower than the permissible level. Using fresh pomace or fibre preparations made from by-products is a possibility to increase the fibre content in the bars and a method of managing by-products. Full article

The paper investigates the process of degumming substandard soybean oil using an enzyme complex of phospholipases to prepare it as a feedstock for biodiesel production. Dehumidification is an important refining step aimed at reducing the phosphorus content, which exceeds the permissible limits according to ASTM, EN, and ISO standards, by re-moving phospholipids. The enzyme complex of phospholipases includes phospholipase C, which specifically targets phosphatidylinositol, and phospholipase A2, which catalyzes the hydrolysis of phospholipids into water-soluble phosphates and lysophospholipids. This process contributes to the efficient removal of phospholipids, increased neutral oil yield, and reduced residual oil in the humic phase. The use of an enzyme complex of phospholipases provides an innovative, cost-effective, and environmentally friendly method of oil purification. The results of the study demonstrate the high efficiency of using the phospholipase enzyme complex in the processing of substandard soybean oil, which allows reducing the content of total phosphorus to 0.001% by weight, turning it into a high-quality raw material for biodiesel production. The proposed approach contributes to increasing the profitability of agricultural raw materials and the introduction of environmentally friendly technologies in the field of renewable energy. Full article

The optimal design of electromagnetic interference (EMI) filters relies on accurate characterization of noise source impedance. The conventional insertion loss method involves integrating two distinct passive two-port networks between the linear impedance stabilization network (LISN) and the equipment under test (EUT). The utilization of the insertion loss to formulate a system of binary quadratic equations concerning the real and imaginary components of the impedance of the noise source enables the precise extraction of the magnitude and phase of the noise source impedance in theory. However, inherent inaccuracies in the insertion loss method during extraction can compromise impedance accuracy or even cause extraction failure. This work employs a series inductance method to overcome these limitations. Exact analytical expressions are derived for the magnitude and phase of the noise source impedance. Subsequently, the application scope of the series insertion loss method is analyzed, and the impact of insertion loss measurement error on noise source impedance extraction accuracy is quantified. Requirements for improving extraction accuracy are discussed, and method optimization strategies are proposed. The permissible range of insertion loss error ensuring a solution exists is deduced. Finally, simulation and experimental results validate the proposed approach in a buck converter. Full article

In the deep integration process between digital infrastructure and new economic forms, structural imbalance between the evolution rate of cloud storage technology and the growth rate of data-sharing demands has caused systemic security vulnerabilities such as blurred data sovereignty boundaries and nonlinear surges in privacy leakage risks. Existing academic research indicates current proxy re-encryption schemes remain insufficient for cloud access control scenarios characterized by diversified user requirements and personalized permission management, thus failing to fulfill the security needs of emerging computing paradigms. To resolve these issues, a revocable attribute-based proxy re-encryption scheme supporting policy-hiding is proposed. Data owners encrypt data and upload it to the blockchain while concealing attribute values within attribute-based encryption access policies, effectively preventing sensitive information leaks and achieving fine-grained secure data sharing. Simultaneously, proxy re-encryption technology enables verifiable outsourcing of complex computations. Furthermore, the SM3 (SM3 Cryptographic Hash Algorithm) hash function is embedded in user private key generation, and key updates are executed using fresh random factors to revoke malicious users. Ultimately, the scheme proves indistinguishability under chosen-plaintext attacks for specific access structures in the standard model. Experimental simulations confirm that compared with existing schemes, this solution delivers higher execution efficiency in both encryption/decryption and revocation phases. Full article

A particularly important activity carried out by railway infrastructure managers to maintain railway devices in full working order is the diagnostic process. It increases the level of railway safety. The diagnostic process involves collecting information about the equipment through inspections, tests, functional trials, parameter measurements, and analysis of the working environment, followed by comparing the obtained information with the required parameters or permissible conditions. This activity also enables the formulation of a technical diagnosis regarding the current ability of the devices to perform its intended functions, taking into account the impact of its technical condition on railway traffic safety. This is especially important in the case of railway traffic control devices, as these devices are largely responsible for ensuring railway traffic safety. The collection of data on the condition of railway traffic control devices in the form of Big Data sets and diagnostic inference is an effective factor in making operational decisions for such devices. It enables the acquisition of complete information about the actual course of the exploitation process and allows for obtaining reliable information necessary to manage this process, particularly in the areas of diagnostics forecasting of devices conditions, renewal, and organization of maintenance and repair facilities. To support this, a service data acquisition and analysis system for railway traffic control devices (SADEK) was developed. This system can serve as a software platform for maintenance needs in the railway sector. Full article

The blockchain technology is transforming the mining industry by enabling mineral reserve tokenization, improving security, transparency, and traceability. However, controlling access to sensitive mining data remains a challenge. Existing access control models, such as role-based access control, are too rigid because they assign permissions based on predefined roles rather than real-world conditions like mining licenses, regulatory approvals, or investment status. To address this, this paper explores an attribute-based access control model for blockchain-based mineral tokenization systems. ABAC allows access permissions to be granted dynamically based on multiple attributes rather than fixed roles, making it more adaptable to the mining industry. This paper presents a high-level system design that integrates ABAC with the blockchain using smart contracts to manage access policies and ensure compliance. The proposed model is designed for permissioned blockchain platforms, where access control decisions can be automated and securely recorded. A comparative analysis between ABAC and RBAC highlights how ABAC provides greater flexibility, security, and privacy for mining operations. By introducing ABAC in blockchain-based mineral reserve tokenization, this paper contributes to a more efficient and secure way of managing data access in the mining industry, ensuring that only authorized stakeholders can interact with tokenized mineral assets. Full article

Blockchain provides the opportunity for organizations to execute trustable collaborations through smart contract automations. However, linkability problems exist in blockchain-based collaboration platforms due to privacy leakages, which, when exploited, will result in tracing transaction patterns to users and exposing collaborating organizations and parties. Some privacy-preserving mechanisms have been adopted to reduce linkability problems through the integration of access control systems to smart contracts, off-chain data storage, usage of permissioned blockchain, etc. Still, linkability problems persist in applications deployed in both private and public blockchain networks. Zero-knowledge proof (ZKP) systems provide mechanisms for verifying the correctness of transactions and actions executed on the blockchain without revealing complete information about the transaction. Hence, ZKP systems provide a potential solution to eliminating linkability problems in blockchain-based collaboration systems. The objective of this paper is to identify various linkability problems that exist in blockchain-enabled collaboration systems and understand how ZKP algorithms and smart contract frameworks can be used in addressing the linkability problems. Furthermore, a proof of concept (PoC) is implemented and simulated to demonstrate a ZKP system for a privacy-preserving feedback mechanism that mitigates linkability problems in collaboration systems. The scenario-based results from the PoC evaluation show that a feedback system that includes project participants’ verification through membership proofs, verification of on-time submission of feedback through range proofs, and encrypted calculation of feedback scores through homomorphic arithmetic provides a privacy-aware system for executing collaborations on the blockchain without linking project participants. Full article

This study evaluates leadership uniformity—the degree to which the proposer role is evenly distributed among validator nodes over time—in Quorum-based Byzantine Fault Tolerance (QBFT), a Byzantine Fault-Tolerant (BFT) consensus algorithm used in permissioned blockchain networks. By introducing simulated follower timeouts derived from uniform, normal, lognormal, and Weibull distributions, it models a range of network conditions and latency patterns across nodes. This approach integrates Raft-inspired timeout mechanisms into the QBFT framework, enabling a more detailed analysis of leader selection under different network conditions. Three leader selection strategies are tested: Direct selection of the node with the shortest timeout, and two quorum-based approaches selecting from the top 20% and 30% of nodes with the shortest timeouts. Simulations were conducted over 200 rounds in a 10-node network. Results show that leader selection was most equitable under the Weibull distribution with shape $k=0.5$, which captures delay behavior observed in real-world networks. In contrast, the uniform distribution did not consistently yield the most balanced outcomes. The findings also highlight the effectiveness of quorum-based selection: While choosing the node with the lowest timeout ensures responsiveness in each round, it does not guarantee uniform leadership over time. In low-variability distributions, certain nodes may be repeatedly selected by chance, as similar timeout values increase the likelihood of the same nodes appearing among the fastest. Incorporating controlled randomness through quorum-based voting improves rotation consistency and promotes fairer leader distribution, especially under heavy-tailed latency conditions. However, expanding the candidate pool beyond 30% (e.g., to 40% or 50%) introduced vote fragmentation, which complicated quorum formation in small networks and led to consensus failure. Overall, the study demonstrates the potential of timeout-aware, quorum-based leader selection as a more adaptive and equitable alternative to round-robin approaches, and provides a foundation for developing more sophisticated QBFT variants tailored to latency-sensitive networks. Full article