Search Results (235)

During the last decade, the blockchain landscape has rapidly evolved, fostering the development of decentralized applications (DApps) that utilize cross-chain interactions. Although existing technologies have enhanced transaction processing and introduced interoperability solutions, scalability challenges persist, undermining their effectiveness. In particular, traditional cross-chain DApp interaction protocols experience performance bottlenecks due to their dependence on on-chain validation mechanisms, resulting in increased latency and computational costs. To address these issues, this paper presents the ScaL2Chain protocol, which is designed to facilitate efficient and secure cross-chain transactions for DApps. ScaL2Chain leverages off-chain technologies, such as payment channels, to enable participants to conduct transactions with a minimal on-chain footprint. By implementing an innovative state verification mechanism, ScaL2Chain guarantees high performance, confidentiality, and transaction integrity. Our empirical evaluations indicate that ScaL2Chain significantly outperforms existing solutions in terms of transaction throughput. Specifically, compared to baseline systems, ScaL2Chain achieves a 7.9-times to 8.4-times improvement in permissionless environments and a 1.9-times to 35.8-times improvement in permissioned environments under workloads with 4-64 DApps and varying cross-chain transaction ratios (0–100%). Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

Infrastructure facility development and modernization highly contribute to national economic growth, but at the same time, such development also causes local negative impacts on the use of specific land plots, creating losses for their right holders. In Russia, some prerequisites have already been laid down on the issue of compensation for the losses associated with restrictions on the rights and prohibitions of economic activity within zones with special territory use conditions (ZSTUCs). However, the impacts of such facilities lead to environmental pollution and land use disadvantages, such as irregular parcels. The aim of this work is to substantiate a set of approaches to compensating for the cumulative negative impact of infrastructure facilities. The factors causing the negative impacts of infrastructure facilities are grouped into three areas: rights restrictions, territorial deficiencies and environmental pollution. This work uses the SWOT analysis method with the possibility of element-by-element analysis, as a result of which the approaches to the compensation for negative impacts under different external and internal conditions are determined. As a result of this study, a justification for a set of approaches to compensating for the negative impacts of infrastructure facilities on land use was executed, and a new algorithm to compensate the right holders of the land, industry sector or state for such negative impacts was developed. The following approaches to compensating for negative impacts were identified: loss assessment; the establishment of environmental payments; cadastral value adjustment; compensation for industry sector losses; and the use of state regulation tools. The first two approaches were identified as the main ones. The proposed algorithm can be realized only with the help of the abovementioned methodological approaches, which form a basis for further research. Full article

Engineering contract management is a critical component of project management systems, serving as a key mechanism for ensuring successful project implementation. This study systematically analyzes 349 s-instance judicial cases related to construction engineering contract disputes in the Yangtze River Delta Economic Zone from 2017 to 2021, based on data obtained from the China Judgments Online database. The research identifies contractual risk characteristics across dimensions such as regional distribution, dispute terminology, legal citation patterns, and appellate role transitions. The key findings include the following: (1) Primary risks involve payment disputes, quality assurance failures, contractual validity issues, and schedule compliance challenges. (2) Litigation patterns reveal complex interdependencies between contracting parties and stakeholders, posing significant risk management challenges. (3) High second-instance modification rates stem from procedural irregularities, new evidence, improper legal application, and factual errors in initial trials. The study proposes stratified risk mitigation strategies, including governmental regulatory improvements and enterprise-level management optimizations. These findings offer valuable insights into advancing risk governance in construction contract administration, particularly through an enhanced understanding of dispute complexity and systemic vulnerabilities. Full article

Background/Objectives: Rural public health is significantly impacted by social drivers of health (SDOH), a set of community-level factors, with rural areas facing challenges such as a higher rate of aging population, fewer jobs, lower income, higher mortality, and poor healthcare access. While much research exists on rurality and SDOH, methodological issues remain, including a narrow definition of SDOH that often overlooks the critical location aspect of healthcare. Methods: This study utilized county-level data from the 2020 Agency of Healthcare Research and Quality SDOH database to investigate geospatial variations in healthcare across the spectrum of rurality. This study employed a set of novel spatial–statistical methods: gradient boosting machines (GBM), Shapley additive explanations (SHAP), and multiscale geographically weighted regression (MGWR). Results: The analysis of 262 variables across 1976 counties identified 20 key variables related to rural healthcare. These variables were grouped into three categories: health insurance status, access to care, and the volume of standardized Medicare payments. The MGWR model further revealed both global and local effects of specific healthcare characteristics on rurality, demonstrating that geographically varying relationships were strongly associated with socio-geographical factors. Conclusions: To improve the SDOH in vulnerable rural communities, particularly in Southern states without Medicaid expansion, policymakers must develop and implement equitable and innovative care models to address social determinants of health and access-to-care issues, especially given the potential cuts to public health programs. Full article

The transmission of vibrations generated by high-powered machines to the hands can lead to serious health problems and various work-related difficulties for the operators. These issues result in a loss of workforce and increased operational costs due to compensation payments made to affected workers. Exposure to hand–arm vibration can be controlled through the use of vibration damping gloves. In this study, the hand–arm vibration exposure of operators using a jackhammer in three different mines was measured with and without gloves, and the vibration damping ratio of each glove was calculated. One-way analysis of variance was performed to determine the difference between the vibration damping ratios (%) obtained from three separate field measurements of 12 different gloves, and significant differences were detected. In addition, vibration exposure was measured with and without gloves for operators using a vibrating sieve set with standard vibration in a laboratory environment. From both the field and laboratory measurements, the gloves made of chloroprene rubber provide the most effective protection. Full article

Vehicle electrification should not be limited to specific geographical areas like wealthy or privileged regions. Recognizing this, China initiated the “NEVs going to rural areas” (NEVgoRural) initiative, highlighting the need for systematic metrics to quantify equity progress. This study develops a comprehensive analysis framework, including equality degree calculation, prevalence analysis, and correlation analysis, to assess and track China’s vehicle electrification process from 2020 to 2023. The equality degree calculation roughly evaluated the spatial inequality degree across China at the macro level. The results indicated that equality issues exist in China (Gini > 0.4, World Bank warning), and this inequality has been gradually improving year by year. The prevalence analysis, based on an Information Entropy Weighting-based model, identified specific geographical areas lagging behind. Furthermore, a correlation analysis was conducted to explore potential associations underlying this geographical inequity. The results revealed that variables, such as a high-level education ratio, NEV manufacturing company number, etc., were significantly correlated with the inequity situation. Drawing on these insights, this study proposed targeted strategies to enhance electrification equity across regions, such as extending NEV tax exemptions in lagging provinces, implementing rural-specific zero-down-payment and interest-free plans, establishing a robust rural sales and after-sales network, and improving mobile payment skills in rural areas. Full article

Demand response (DR) has high regulation potential, which can reduce the power supply–demand imbalance caused by extreme disasters. However, its actual effectiveness still needs to be improved because of low user willingness and incomplete compensation mechanisms. To address this issue, a symmetrical incentive mechanism for DR is proposed. Building upon this mechanism, a bi-level load restoration optimization model under extreme events is proposed. The upper-level model minimizes grid-side costs during load restoration, determining load restoration ratios and incentive coefficients transmitted to the lower level. The lower-level model maximizes user profits while considering comfort-level losses from DR participation, solving for actual response quantities that are fed back to the upper level. To efficiently solve the proposed load restoration model, an iterative mixed-integer load restoration solver is proposed. Case studies demonstrate that the proposed symmetrical mechanism achieved an 89.6% participation rate, showing a 2.46% improvement over fixed incentive schemes. Grid payment costs were reduced by CNY 365,400, achieving incentive compatibility that facilitates rapid load restoration post extreme disasters. Full article

Credit risk is one of the most important issues in the rapidly growing and developing finance sector. This study utilized a dataset containing real information about the bill payments of individuals who made transactions with a payment institution operating in Turkey. First, the transactions in the dataset were analyzed based on the bill type and the individual and features reflecting the payment habits were extracted. For the target class, real credit scores generated by the Credit Registry Office for the individuals whose payment habits were extracted were used. The dataset is a multi-class, unbalanced, and alternative dataset. Therefore, the dataset was prepared for the analysis by using data cleaning, feature selection, and sampling techniques. Then, the dataset was classified using various classification and evaluation methods. The best results were obtained with a model consisting of ANOVA F-Test, SMOTE, and Extra Tree algorithms. With this model, 80.49% accuracy, 79.89% precision, and 97.04% UAC rate were obtained. These results are quite efficient for an alternative dataset with 10 classes. This model was transformed into an explainable and interpretable form using LIME and SHAP, which are XAI techniques. This study presents a new hybrid model for credit risk assessment based on a multi-class and imbalanced alternative dataset and machine learning. Full article

This study investigates the factors that affect the adoption of mobile payment systems in Oman, focusing specifically on small and medium-sized enterprises (SMEs) within the expanding FinTech landscape. By utilizing secondary sources of data from the Central Bank of Oman and global FinTech reports, this research identifies essential enablers, such as security features and ease of use, which are propelled by developments in FinTech solutions. It also addresses the obstacles, such as high transaction fees and issues with authentication, that impede SMEs from embracing these technologies. Through an examination of worldwide FinTech adoption patterns, this research offers perspectives on Oman’s progress toward becoming a cashless society. This study employs sophisticated statistical techniques, including histograms and correlation analysis, to reveal significant trends in the rates of mobile payment adoption. The results emphasize the necessity for cooperative efforts among regulators, financial entities, and FinTech developers to minimize costs, strengthen digital infrastructure, and enhance user experiences. These findings are consistent with Oman’s Vision 2040, which aims to foster financial inclusion and propel the country’s shift toward a robust, digitally oriented economy powered by FinTech innovation. Full article

Bike-sharing initiatives play a crucial role in sustainable urban transportation, addressing vehicular congestion, air quality issues, and sedentary lifestyles. However, the connection between bike-sharing facilities and the advantages perceived by users remains insufficiently explored particular in post-industrial regions, such as Silesia, Poland. This study develops a multidimensional framework linking infrastructure elements—such as station density, bicycle accessibility, maintenance standards, and technological integration—to perceived benefits. Using a mixed-methods approach, a survey conducted in key Silesian cities combines quantitative analysis (descriptive statistics, factor analysis, and regression modelling) with qualitative insights from user feedback. The results indicate that the most valuable benefits are health improvements (e.g., improved physical fitness and mobility) and environmental sustainability. However, infrastructural deficiencies—disjointed bike path systems, uneven station placements, and irregular maintenance—substantially hinder system efficiency and accessibility. Inadequate bike maintenance adversely affects efficiency, safety, and sustainability, highlighting the necessity for predictive upkeep and optimised services. This research underscores innovation as a crucial factor for enhancing systems, promoting seamless integration across multiple modes, diversification of fleets (including e-bikes and cargo bikes), and the use of sophisticated digital solutions like real-time tracking, contactless payment systems, and IoT-based monitoring. Furthermore, the transformation of post-industrial areas into cycling-supportive environments presents strategic opportunities for sustainable regional revitalisation. These findings extend beyond the context of Silesia, offering actionable insights for policymakers, urban mobility planners, and Smart City stakeholders worldwide, aiming to foster inclusive, efficient, and technology-enabled bike-sharing systems. Full article

This study aims to describe and assess the impact of critical infrastructure (CI) cybersecurity issues on the sustainable development of smart cities. This study highlights the integration of PayTech systems into the broader CI landscape, highlighting their impact on maintaining economic stability and ensuring the smooth operation of city services. Key companies within smart regions, particularly those operating in the payment industries, are essential to maintaining the functionality of critical services. These companies facilitate the processing of services provided to citizens, enabling access to vital municipal services. As key players in the PayTech and online e-commerce sectors, they form a crucial part of modern critical infrastructure, operating within an ever-evolving digital environment. This study examines the recovery processes employed after cyberattacks, focusing on the differing perspectives of internal and external professionals. It identifies significant differences in the perceptions of recovery strategies among internal stakeholders, such as investor relations (IR) teams, reputation management (RM) experts, and Chief Information Security Officers (CISOs), who represent critical infrastructure companies. Additionally, it explores the roles of external auditors, who provide impartial emergency support and perform specialized recovery tasks. Importantly, this study underscores the current attitudes toward future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company’s internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors. Full article

Shandong and Henan provinces face significant pest and disease issues, creating a strong demand for green pest control technologies. This paper analyzes the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies, based on 419 survey responses collected through stratified sampling in Shandong and Henan provinces in 2024, using the Heckman two-stage model. The results show the following: (1) Government subsidies and quality certification significantly promote farmers’ adoption of green pest control technologies, with regression coefficients of 0.260 and 0.493, respectively. (2) An interaction effect exists between government subsidies and quality certification on farmers’ adoption of green pest control technologies, with a coefficient of 0.454. For a given government subsidy, higher quality certification levels increase the likelihood of farmers adopting green pest control technologies. (3) From the perspective of human capital quantity, there is obvious heterogeneity in the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies. (4) From the perspective of generational differences, quality certification has obvious heterogeneity on farmers’ adoption of green pest control technologies, while there is no obvious generational difference in government subsidies. Therefore, it is necessary to establish a stable and multi-channel government transfer payment system, improve the construction of the agricultural product quality traceability system, take a two-pronged approach, and complement each other’s strengths to build a targeted incentive mechanism based on different groups of farmers. Full article

The widespread reliance on paper-based currency poses significant drawbacks, such as counterfeiting, lack of transparency, and environmental impacts. While Central Bank Digital Currencies (CBDCs) address many of these issues, their dependence on continuous internet connectivity limits their usability in scenarios with poor or no network access. To overcome such limitations, this paper introduces ElasticPay, a novel Peer-to-Peer (P2P) Offline Digital Payment System that leverages advanced hardware security measures realised through Trusted Platform Modules (TPMs), Trusted Execution Environments (TEEs), and Secure Elements (SEs). ElasticPay ensures transaction privacy, unforgeability, and immediate settlement while preventing double spending. Our approach integrates robust recovery mechanisms and provides a scalable solution for diverse environments. Extensive experimentation validates the system’s reliability and practicality, highlighting its potential to advance secure and inclusive CBDC ecosystems. We demonstrate the proposed solution implementation on the iPhone mobilephone because it has an inbuilt Secure Enclave, which is an integrated implementation of the necessary TPM, TEE, and SE functionalities. Full article

Since the Fourth Industrial Revolution was announced in 2015, relevant key technologies have recently merged and have extensively affected our society. To provide empirical insights into the future and address expected issues in the context of transportation, this study seeks to investigate how future road infrastructure technology will shift. Going over the mainstream future road infrastructure inspired by the strategy implemented in the Korean New Deal 2.0, we extract central keywords explaining what specific technologies and political directions will prevail globally. In particular, a specific morphological analyzer, Mecab-Ko, which is suitable for Korean is selected after comparing a variety of packages. Then, a specific text mining approach is employed to collect textual online sources (news articles, research articles, and reports) written in Korean while most studies gather information written in English. Using the term frequency-inverse document frequency (TF-IDF), 11 keywords were extracted from unstructured textual online sources. Topic modelling with latent Dirichlet allocation (LDA) is subsequently performed to classify them into four groups: an unmanned payment system, intelligent road infrastructure, connected automated driving road, and eco-friendly road. Based on these findings, we can take a glimpse into how the future road infrastructure in Korea will be reshaped. Evidently, a digitalized road without a human component is around the corner. Fully automated systems will soon become available, and the keyword sustainability will continue to receive critical attention in the transportation sector. Full article