Search Results (289)

This paper presents the design and implementation of a high-precision vehicle detection and classification system for toll stations on national highways in Colombia, leveraging LiDAR-based 3D point cloud processing and supervised machine learning. The system integrates a multi-sensor architecture, including a LiDAR scanner, high-resolution cameras, and Doppler radars, with an embedded computing platform for real-time processing and on-site inference. The methodology covers data preprocessing, feature extraction, descriptor encoding, and classification using Support Vector Machines. The system supports eight vehicular categories established by national regulations, which present significant challenges due to the need to differentiate categories by axle count, the presence of lifted axles, and vehicle usage. These distinctions affect toll fees and require a classification strategy beyond geometric profiling. The system achieves $89.9\%$ overall classification accuracy, including $96.2\%$ for light vehicles and $99.0\%$ for vehicles with three or more axles. It also incorporates license plate recognition for complete vehicle traceability. The system was deployed at an operational toll station and has run continuously under real traffic and environmental conditions for over eighteen months. This framework represents a robust, scalable, and strategic technological component within Intelligent Transportation Systems and contributes to data-driven decision-making for road management and toll operations. Full article

Public–private partnership (PPP) logistics infrastructure projects have become increasingly prevalent globally. Consequently, the effective management of these projects as their concession periods expire presents a crucial challenge for governments, vital for the sustainable management of PPP logistics infrastructure. This study addresses this challenge by focusing on the pivotal post-concession decision: whether the government should self-operate the mature logistics infrastructure or re-delegate its management to a private entity. Our theoretical model, built on a principal–agent framework, first establishes a social welfare baseline under government self-operation and then analyzes delegated operation under symmetric information, identifying efficiency frontiers. Under symmetric information, we find that government self-operation is more advantageous when its own operational efficiency is sufficiently high, irrespective of the private enterprise’s efficiency; conversely, delegating to an efficient private enterprise is optimal only when government operational efficiency is low. We also demonstrate that if the government can directly specify the demand quantity and service level and delegates operation via a fixed fee, the enterprise can be incentivized to align with the social optimum. However, under asymmetric information, potential welfare gains from delegation are inevitably offset by informational rent and output distortion. We further uncover non-monotonic impacts of parameters like the proportion of low-cost firms on social welfare loss and demonstrate how information asymmetry can indirectly compromise the long-term resilience of the infrastructure. Ultimately, our work asserts that delegation is only superior if its potential efficiency gains sufficiently offset the inherent losses stemming from information asymmetry. Full article

The global coffee supply chain is a complex multi-stakeholder ecosystem plagued by fragmented records, unverifiable origin claims, and limited real-time visibility. These limitations pose risks to ethical sourcing, product quality, and consumer trust. To address these issues, this paper proposes a blockchain and IoT-enabled framework for secure and transparent coffee supply chain management. The system integrates simulated IoT sensor data such as Radio-Frequency Identification (RFID) identity tags, Global Positioning System (GPS) logs, weight measurements, environmental readings, and mobile validations with Ethereum smart contracts to establish traceability and automate supply chain logic. A Solidity-based Ethereum smart contract is developed and deployed on the Sepolia testnet to register users and log batches and to handle ownership transfers. The Internet of Things (IoT) data stream is simulated using structured datasets to mimic real-world device behavior, ensuring that the system is tested under realistic conditions. Our performance evaluation on 1000 transactions shows that the model incurs low transaction costs and demonstrates predictable efficiency behavior of the smart contract in decentralized conditions. Over 95% of the 1000 simulated transactions incurred a gas fee of less than ETH 0.001. The proposed architecture is also scalable and modular, providing a foundation for future deployment with live IoT integrations and off-chain data storage. Overall, the results highlight the system’s ability to improve transparency and auditability, automate enforcement, and enhance consumer confidence in the origin and handling of coffee products. Full article

In the context of global e-commerce platform supply chains dominated by Alibaba and Amazon, power reconfiguration among tripartite stakeholders (platforms, manufacturers, and retailers) remains a critical yet underexplored issue in supply chain contract design. To analyze the strategic interactions between platforms, manufacturers, and retailers, as well as how platforms select the contract format within a tripartite supply chain, this study proposes a Stackelberg game-theoretic framework incorporating participation constraints to compare fixed-fee and revenue-sharing contracts. The results demonstrate that revenue-sharing contracts significantly enhance supply chain efficiency by aligning incentives across members, leading to improved pricing and sales outcomes. However, this coordination benefit comes with reduced platform dominance, as revenue-sharing inherently redistributes power toward upstream and downstream partners. The analysis reveals a nuanced contract selection framework: given the revenue sharing rate, as the additional value increases, the optimal contract shifts from the mode RR to the mode RF, and ultimately to the mode FF. Notably, manufacturers and retailers exhibit a consistent preference for revenue-sharing contracts due to their favorable profit alignment properties, regardless of the platform’s value proposition. These findings may contribute to platform operations theory by (1) proposing a dynamic participation framework for contract analysis, (2) exploring value-based thresholds for contract transitions, and (3) examining the power-balancing effects of alternative contract formats. This study offers actionable insights for platform operators seeking to balance control and cooperation in their supply chain relationships, while providing manufacturers and retailers with strategic guidance for contract negotiations in platform-mediated markets. These findings are especially relevant for large e-commerce platforms and their partners managing the complexities of contemporary digital supply chains. Full article

The public–private partnerships (PPP) mode is very popular in public infrastructure projects. The PPP model for sponge city construction (SCC) provides an effective way to curb and manage the increasingly serious ecological water problems in China. The quantitative evaluation of value for money (VFM) is an evaluation method that obtains quantitative values through a certain calculation process. However, the current studies lack a dynamic quantitative evaluation of VFM for the entire life cycle of SCC PPP projects, and cannot observe the impact of key factors on the VFM value. By constructing a system dynamics (SD) model for the VFM quantitative evaluation of SCC PPP projects from the perspective of the whole life cycle, this study can intuitively and transparently observe the impact of key factors (such as discount rate and profit margin) on the evaluation results and feasibility of adopting a PPP model in the project, offering policymakers a tool to mitigate the risks of “Pseudo-PPP” projects. After collecting cases in Anhui province from the China PPP Center, this study constructed a life cycle VFM quantitative evaluation system dynamics model suitable for SCC PPP projects that consist of the public sector comparison (PSC) value and PPP value. The results indicate that the system dynamics model can be effectively applied to the dynamic quantitative evaluation of SCC PPP projects and clarify the influence degree on and sensitivity of various factors to the VFM value. Specifically, when the discount rate increases, the decrease in the PPP value is greater than that in the PSC value, leading to an increase in the VFM value. Moreover, a reasonable profit margin is more sensitive to the VFM value and decreases as the reasonable profit margin increases. In addition, choosing different availability service fee calculation methods will result in varying the adjustment range to a reasonable profit margin that drives the adoption of VFM quantitative evaluation. These research findings have provided a viable dynamic research methodology for the quantitative VFM evaluation of SCC PPP projects. This methodology enables the dynamic visualization and easy determination of the acceptable ranges for relevant factors, offers rational policy recommendations for the quantitative evaluation of key factor values, and thereby effectively prevents PPP project violations, promoting fair and reasonable cooperation between governments and private enterprises. Full article

Protected areas are essential for biodiversity conservation, ecosystem services, and protecting different cultural heritage. They are legally designated and managed to safeguard habitats, species, and ecological processes. The EU aims to protect 30% of its land by 2030, while in Serbia 9.74% of land is under protection. One of the important categories of protected areas represents national parks, which cover 17.3% of all protected areas in Serbia. In order to understand the mechanisms of financing national parks in Serbia, the period from 2008 to 2022 was analyzed. The 15-year period was selected due to the availability of data and the necessity for long-term analysis. All revenues are divided in four groups: business, fee, grant and other business revenues. The results of regression analysis show that the growth rate of business revenue is the most significant contributor among the revenue sources, with a very strong positive impact on the growth rate of total revenue in all four national parks. The growth rate of grant revenue also contributes positively to the growth rate of total revenue. However, its impact is much smaller than the growth rate of business revenue and fee revenue but still highly significant. A strong negative correlation (−0.82) is present between the growth rate of business and fee revenue in National Park Kopaonik. This suggests that with an increase in fee revenues, business revenues decrease. The results of this research show that business revenues are the most important, followed by fee and grant revenue. Full article

Background/Objectives: Degenerative lumbar spine disease (DLSD) is increasingly managed with minimally invasive surgery (MIS) and evolving anesthesia methods. While general anesthesia (GA) remains standard, spinal anesthesia (SA) may offer faster recovery and fewer side effects. This study compares the clinical and economic outcomes of GA versus SA in transforaminal lumbar interbody fusion (TLIF). Methods: A retrospective review of 18 TLIF patients (2018–2022) was performed, with 9 patients in each cohort. Patients were matched by demographics and procedure type. Data collected included operative time, blood loss, complications, postoperative opioid utilization, and 30-day readmissions. Costs were analyzed in categories: anesthesia, implants, inpatient care, operating room (OR) supplies, OR time, and PACU fees, using Wilcoxon Rank T-tests and Pearson Chi-Squared tests. Results: Clinical outcomes such as blood loss, and operative time were similar between groups. However, SA patients had significantly shorter LOS compared to GA (SA: 12 h vs. GA: 84 h, % difference: −150%, p = 0.04). Additionally, SA patients had lower total direct costs ($27,881.85 vs. $35,669.01; p = 0.027). Significant cost reductions with SA were noted in OR supplies/medications ($7367.93 vs. $10,879.46; p = 0.039) and inpatient costs ($621.65 vs. $3092.66; p = 0.027). Within these categories, reductions were observed for intravenous solutions, sedatives/anesthetics, pressure management, labs, imaging, evaluations, hospital care, and medications. Although costs for implants, anesthesia care, OR time, and PACU fees were lower with SA, these differences did not reach statistical significance. Conclusions: In TLIF for DLSD, SA provides significant economic advantages over GA while yielding comparable clinical outcomes. These results support SA as a cost-effective alternative, warranting further prospective studies to confirm these findings. Full article

Urban sprawl and excessive reliance on motorization have led to many urban problems. The balance of supply and demand in the real estate market, as well as price fluctuations, also face many challenges. Urban rail transit not only alleviates traffic congestion and air pollution, but also significantly reduces residents’ commuting time, broadens urban accessibility, and reshapes the decision-making basis for residents when choosing residential locations. This study takes the 1st, 2nd, 3rd, 4th, 8th, 11th, and 13th metro lines that have been opened in Qingdao City as examples. It selects 12,924 residential samples within a 2 km radius along the rail transit lines. By using GIS spatial analysis tools and the multi-scale geographically weighted regression (MGWR) model, it analyzes the spatial differentiation characteristics of housing prices along the rail transit lines and the reasons and mechanisms behind them. The empirical results show that housing prices decrease to varying degrees with the increase in the distance from the rail transit. For every additional 1 km from the rail transit station, the housing price increases by 0.246%. Through model comparison, it was found that MGWR has a better fitting degree than the traditional ordinary least squares method (OLS) and the previous geographically weighted regression model (GWR), and reveals the spatial heterogeneity of the influence of urban rail transit on housing prices. Different indicator elements have different effects on housing prices along these lines. The urban rail transit factor in the location characteristics has a positive impact on housing prices, and has a significant negative correlation in some areas. The significant influence range of the distance to the nearest metro station on housing prices is concentrated within a radius of 373 m, and the effect decays beyond this range. The total floors, building area, green coverage rate, property management fee, and the distance to hospitals and parks in the neighborhood and structural characteristics have spatial heterogeneity. Analyzing the areas affected by the urban rail transit factor, it was found that the double location superposition effect, the networked transportation system, and the agglomeration of urban functional axes are important reasons for the significant phenomena in some local areas. This research provides a scientific basis for optimizing the sustainable development of rail transit in Qingdao and formulating differentiated housing policies. Meanwhile, it expands the application of the MGWR model in sustainable urban spatial governance and has practical significance for other cities to achieve sustainable urban development. Full article

The rapid expansion of 5G networks and edge computing has amplified security challenges in Internet of Things (IoT) environments, including unauthorized access, data tampering, and DDoS attacks. This paper introduces EdgeChainGuard, a hybrid blockchain-based authentication framework designed to secure 5G-enabled IoT systems through decentralized identity management, smart contract-based access control, and AI-driven anomaly detection. By combining permissioned and permissionless blockchain layers with Layer-2 scaling solutions and adaptive consensus mechanisms, the framework enhances both security and scalability while maintaining computational efficiency. Using synthetic datasets that simulate real-world adversarial behaviour, our evaluation shows an average authentication latency of 172.50 s and a 50% reduction in gas fees compared to traditional Ethereum-based implementations. The results demonstrate that EdgeChainGuard effectively enforces tamper-resistant authentication, reduces unauthorized access, and adapts to dynamic network conditions. Future research will focus on integrating zero-knowledge proofs (ZKPs) for privacy preservation, federated learning for decentralized AI retraining, and lightweight anomaly detection models to enable secure, low-latency authentication in resource-constrained IoT deployments. Full article

Effective municipal solid waste (MSW) management is crucial for urban sustainability, especially in fast-growing cities, like Hangzhou, China. This study examines residents’ willingness to pay (WTP) for the following five key MSW measures: differentiated waste charging, smart recycling points, on-site organic waste recovery, volunteer-based waste sorting supervision, and a community self-governance fund. Based on a survey of 521 residents across 13 districts, we use logistic and interval regression models to identify factors influencing WTP and payment amounts. Key findings include the following: Higher-income and more educated residents prefer cost-efficient, technology-driven solutions, like smart recycling and differentiated charging. Newcomers (≤5 years of residence) show higher WTP and greater sensitivity to environmental information, highlighting the need for targeted outreach. Providing explicit environmental benefits (e.g., waste reduction, increased recycling) significantly boosts WTP rates and payment levels. Community characteristics matter—residents in high-density areas favor waste charging, while those in older neighborhoods support volunteer programs and self-governance funds. Policy implications center on targeted outreach, transparent fee structures, and incentive programs to foster public trust and enhance participation. Although MSW management in Hangzhou remains predominantly government-led, select collaboration with private enterprises (e.g., in specialized recycling services) may offer additional efficiency gains. By aligning these measures with localized preferences and demographic patterns, Hangzhou—and other quickly urbanizing regions—can develop robust and inclusive MSW systems that contribute to broader sustainable development objectives. Full article

Our research analyzes the design of an auction model for railway transportation on the South-East Railway of Peru, managed by Ferrocarril Transandino S.A. (Fetransa) and operated by PeruRail. Initially, the regulatory framework aimed to promote competition in railway transportation through timetable auctions and infrastructure access. However, the concession has resulted in a vertically integrated structure that favors PeruRail, which faces minimal direct competition, controls high-demand time slots, and hinders the entry of other operators due to strategic and structural access barriers. To address these distortions, we propose reforming the auction mechanism to neutralize these advantages and enhance competition. In this revised framework, the track usage fee will serve as the competitive factor, with the highest bid above a minimum base rate securing the allocation. Additionally, we propose the implementation of asymmetric tariffs to compensate for the higher costs faced by operators with fewer economies of scale, technological optimizations to facilitate equitable access to time slots, and stricter oversight mechanisms to ensure transparency in timetable allocation. These measures aim to balance the market and safeguard competition through a more equitable and efficient auction design. Full article

Background/Objectives: Dysphagia, a prevalent condition among older adults, poses significant health risks if not accurately assessed and managed. Instrumental assessments (IAs) like videofluoroscopic swallowing study (VFSS) and fiberoptic endoscopic evaluation of swallowing (FEES) allow detailed examinations of swallowing physiology but are underutilized in long-term care settings due to logistical challenges. This study aims to explore the current practice patterns, stakeholder perspectives, and barriers to and facilitators of IA implementation in these settings. Methods: A scoping review was conducted following the PRISMA-ScR guidelines, analyzing the literature from databases including CINAHL Complete, EMBASE, MEDLINE, and SCOPUS. A total of 1339 articles were identified. After the removal of 332 duplications, 1007 articles were screened, with four meeting the inclusion criteria for describing IA implementation or stakeholder perspectives in community-based long-term care settings for older adults. Results: This review identified significant underutilization of IA in long-term care settings, primarily due to logistical barriers and transportation issues. Stakeholders, particularly speech–language pathologists (SLPs), acknowledged the benefits of IA in improving dysphagia management but encountered challenges in accessing these assessments. Mobile FEES (mFEES) emerged as a promising solution, offering on-site assessments that could enhance the accuracy and timeliness of dysphagia care. Conclusions: While IA is crucial for effective dysphagia management in older adults, its implementation in long-term care settings is hindered by various barriers. mFEES presents a viable solution to improve IA accessibility and representativeness. Further research is warranted to develop context-specific implementation strategies and to explore the perspectives of all stakeholders involved in dysphagia care. Full article

Blockchain technology has emerged as a transformative solution for secure, immutable, and decentralized data management across diverse domains, including economics, healthcare, and supply chain management. Given its soaring adoption, it is crucial to assess the suitability of various blockchain platforms for specific applications. This study evaluates the performance of Hyperledger Fabric (HF) and private Ethereum (Geth) to analyze their scalability (node count), throughput (transactions per second (TPS)), and latency (measured in milliseconds). A benchmarking tool was developed in-house to assess the execution of key smart contract functions—QueryUser, CreateUser, TransferMoney, and IssueMoney—under varying transaction loads (10–1000 transactions) and network sizes (2–16 node count). The results indicate that HF performs significantly better than private Ethereum in terms of invoke functions, achieving up to 5× throughput and up to 26× lower latency. However, private Ethereum excels in query operations because of its account-based ledger model. While Hyperledger Fabric scales efficiently within moderate transaction volumes, it experiences concurrency limitations beyond 1000 transactions, whereas private Ethereum processes up to 10,000 transactions, albeit with performance fluctuations due to gas fees. The findings offer valuable insights into the strengths and tradeoffs of both platforms, informing optimal blockchain selection for enterprise applications that require high transaction efficiency. Full article

New energy vehicles are an important tool for the transition to clean energy and sustainable development. The Nudge Theory is introduced to construct a management model for energy conservation and carbon reduction in new energy vehicles. The model takes into account the strategy of reducing or exempting charging fees for new energy vehicles. Through dynamic simulation, we analyze the impact of considering the Nudge Theory and not considering the Nudge Theory on the energy-saving and carbon reduction effect of new energy vehicles. Through the analysis, it is found that (1) the energy-saving and carbon reduction management model is constructed by introducing the consumer reference effect to optimize the effect of the strategy of charging fee reduction for new energy vehicles, which further enhances the effect of energy saving and carbon reduction. (2) The consideration of the boosting strategy can increase the consumers’ willingness to purchase new energy vehicles, and the growth of new energy vehicles is more significant under the combined strategy compared with the baseline scenario. In the combined strategy, from the beginning of the simulation of Scenario 6 to the end of the simulation, new energy vehicles increased by 131.74%. (3) In terms of energy-saving and carbon reduction effects, Scenario 3 in the single strategy has the best effect, and Scenario 9 in the combined strategy has the best effect. Compared with the baseline scenario, the number of new energy vehicles increased by 253.03%, and carbon dioxide emissions decreased by 38.85%. Scenario 9 of the combined strategy can reach the peak of carbon emissions by 2030, and carbon dioxide emissions will decrease year by year. Full article

Background/Objectives: Oral intake and secretions need to be assessed separately, especially in patients with tracheal tubes, as they are vital for dysphagia treatment and may require different management strategies. This study aims to validate the Italian version of the Munich Swallowing Score (IT-MUCSS) by examining its content and construct validity in relation to the fiberoptic endoscopic evaluation of swallowing (FEES) and oral intake in adults with neurogenic dysphagia, as well as assessing intra- and inter-rater reliability. This tool is clinically and scientifically useful as it includes two subscales: IT-MUCSS-Saliva, which assesses saliva/secretion management and the presence of a tracheal tube, and IT-MUCSS-Alimentazione, which evaluates feeding methods. Methods: In this prospective cross-sectional study, a total of 50 dysphagic patients with a neurological diagnosis were recruited from a neuro-rehabilitation hospital and underwent both clinical and instrumental assessments. The main outcome measures included evaluating food and liquid intake using the Italian versions of the Functional Oral Intake Scale (FOIS-It) and the IT-MUCSS. Pharyngeal residues were assessed using the Yale Pharyngeal Residue Severity Rating Scale (IT-YPRSRS), and airway penetration/aspiration were evaluated using the Penetration–Aspiration Scale (PAS) during FEES. Results: The IT-MUCSS demonstrated excellent reproducibility (K = 0.91) and internal consistency (Cronbach’s alpha = 0.72). Strong correlations were found between IT-MUCSS and the FOIS-It scale, indicating the effective assessment of dysphagia. Test–retest reliability was high (ICC = 0.96 for total score). Construct validity was confirmed through significant correlations with instrumental measures during FEES. Conclusions: The IT-MUCSS is a valid tool for assessing functional oral intake and the management of saliva/secretions, specifically in relation to the level of saliva/secretions management compared to FEES measures of swallowing safety and efficiency in patients with neurogenic dysphagia. Full article