Search Results (22,615)

In recent years, China has vigorously promoted the EPC mode in the construction industry. However, under the weak trust environment of China’s construction industry, both owners and general contractors are involved in the design stage of EPC projects. Owing to conflicting interests in the design stage, there is a two-stage design interest paradox between the owners and general contractors of Chinese EPC projects, and this causes significant difficulties and challenges for project implementation. To resolve this paradox, this study proposes the “DART-PDCA” design management model by integrating value co-creation theory with the PDCA cycle. Applied to the Yuzhou High-speed Rail Station Square and Related Infrastructure PPP Project and the extended case, the model demonstrates how it resolves the paradox by (1) establishing structured dialogue platforms for aligning evolving design intentions, (2) enhancing information access and transparency through agreed protocols, and (3) facilitating dynamic risk assessment and allocation mechanisms. The results confirm that (1) the two-stage design interest paradox negatively impacts design management quality in China’s low-trust environment; and (2) the “DART-PDCA” design management model effectively resolves this paradox, leading to demonstrable improvements in design management quality, efficiency, and stakeholder alignment. This research forges novel interdisciplinary linkages among owner–general contractor relationships, design management, and EPC projects, providing critical insights into managing multi-organizational dynamics in complex EPC project environments. Full article

Rocks and soil excavated at construction sites can contain naturally occurring toxic substances. One low-cost means of managing the environmental burden posed by leaching of these substances is the attenuation layer method, which uses an adsorbent positioned between the fill and ground. Evaluation of adsorbent performance based on sorption tests is important for designing and optimizing attenuation layer methods; however, few studies have examined the effect of coexisting ions on sorption performance. Here, we examined the effects of these ions contained in soil extract solutions on the fluoride sorption performance of a commercial layered double-hydroxide (LDH)–based adsorbent used in the attenuation layer method. Batch and column sorption tests showed that the distribution coefficients in the presence of coexisting ions were 29%–72% lower than those in tests conducted without coexisting ions. Furthermore, the results of a solid-state analysis and various ion analyses suggest that competition for the sorption sites of LDH by sulfate ions in the soil extract solution was the cause of the reduced sorption performance. These findings imply that reliance only on deionized water-based sorption tests may overestimate the real-world sorption performance of LDH-based adsorbents. Full article

Cities are significant contributors to climate change, environmental degradation, and resource depletion. To address these challenges, sustainable strategies in building design, construction, and management are essential, and digitalisation through the integration of Building Information Modelling (BIM) and Life Cycle Assessment (LCA) can enable it. However, the environmental benefits of BIM–LCA integration remain underexplored, limiting broader practical adoption. This study systematically reviews 80 case studies (2015–2025) to assess how recent applications address known barriers and to identify enablers of successful BIM–LCA workflows. The analysis highlights a growing alignment between technological, regulatory, and methodological advancements and practical implementation needs, especially as technical barriers are increasingly overcome. Nevertheless, systemic challenges related to institutional, behavioural, and socio-economic factors persist. From a stakeholder perspective, four thematic drivers were identified: material circularity and resource efficiency; integration with complementary assessment tools; energy-performance strategies for comfort and efficiency; and alignment with international certification systems. The study offers a stakeholder-oriented framework that demonstrates the multi-level value of BIM–LCA integration not only for environmental impact assessment but to support informed decision-making and reduce resource consumption. These insights aim to bridge the gap between academic research and practical implementation, contributing to the advancement of sustainable practices in the built environment. Full article

Equivalent energy consumption minimization methods of energy management systems have been implemented as a rule-based strategy to enhance electric propulsion system efficiency. This study compares the efficiencies of different systems by applying variable- and constant-speed generators with battery hybrid systems, measuring fuel consumption. In the same scenario, the variable-speed operation showed a notable improvement of 10.36% compared to the conventional system. However, in the verification of hybrid system efficiency, onshore charged energy cannot be considered a reduction in fuel consumption. Instead, when converting onshore energy usage into equivalent fuel consumption for comparative analysis, both hybrid constant- and variable-speed operation modes achieved efficiency enhancements ranging from 5.5% to 9.79% compared to the conventional, nonequivalent constant-speed operation mode. Conversely, the nonequivalent variable-speed operation mode demonstrated an efficiency that was 5.41% higher than that of the hybrid constant-speed operation mode. In contrast, the battery-integrated variable-speed operation mode indicated a system efficiency approximately equal to that of the nonequivalent variable-speed operation mode. For vessels with load profiles characterized by prolonged periods of idling or low-load operations, a battery-integrated hybrid system could be a practical solution. This study demonstrates the necessity of analyzing load profiles, even when aiming for the optimal operational set points of the generator engine. Full article

Heartburn is a prevalent and frequently self-managed condition, with a myriad of over-the-counter (OTC) treatment options available for self-care. The potential for misinterpretation of drug labels and improper OTC medication selection may result in inadequate treatment, potential drug interactions, as well as medication overuse, misuse, or delay in seeking treatment for a more serious health condition. As highly accessible healthcare professionals, pharmacists play a crucial role in validating self-diagnoses, in guiding appropriate OTC medication selection and use, and in educating patients on both pharmacologic and non-pharmacologic management strategies for heartburn. It is essential for pharmacists to remain informed about the latest developments in disease management and treatment options. This narrative review provides an updated perspective on the epidemiology, risk factors, pathophysiology, and clinical manifestations associated with heartburn while underscoring the expanding role of pharmacists in patient care. This review includes a structured assessment framework and clinical management algorithm designed to enhance pharmacists’ ability to identify red flag symptoms, optimize OTC medication use, and facilitate timely referrals when necessary. By incorporating evidence-based guidance with patient-centered counseling, pharmacists can enhance treatment outcomes, optimize, medication use, promote adherence, and ensure safer self-care practices. As self-medication trends and the role of pharmacists evolves, this review offers a comprehensive resource to equip pharmacists with the latest knowledge and practical tools for optimizing heartburn management and promoting patient safety. Full article

Generative Artificial Intelligence (GenAI) is widely recognized for its profound impact on labor market demand, supply, and skill dynamics. However, due to its transformative nature, GenAI increasingly overlaps with traditional AI roles, blurring boundaries and intensifying the need to reassess workforce competencies. To address this challenge, this paper introduces KANVAS (Kolmogorov–Arnold Network Versatile Algorithmic Solution)—a framework based on Kolmogorov–Arnold Networks (KANs), which utilize B-spline-based, compact, and interpretable neural units—to distinguish between traditional AI roles and emerging GenAI-related positions. The aim of the study is to develop a reliable and interpretable labor market classification system that differentiates these roles using explainable machine learning. Unlike prior studies that emphasize predictive performance, our work is the first to employ KANs as an explanatory tool for labor classification, to reveal how GenAI-related and European Skills, Competences, Qualifications, and Occupations (ESCO)-aligned skills differentially contribute to distinguishing modern from traditional AI job roles. Using raw job vacancy data from two labor market platforms, KANVAS implements a hybrid pipeline combining a state-of-the-art Large Language Model (LLM) with Explainable AI (XAI) techniques, including Shapley Additive Explanations (SHAP), to enhance model transparency. The framework achieves approximately 80% classification consistency between traditional and GenAI-aligned roles, while also identifying the most influential skills contributing to each category. Our findings indicate that GenAI positions prioritize competencies such as prompt engineering and LLM integration, whereas traditional roles emphasize statistical modeling and legacy toolkits. By surfacing these distinctions, the framework offers actionable insights for curriculum design, targeted reskilling programs, and workforce policy development. Overall, KANVAS contributes a novel, interpretable approach to understanding how GenAI reshapes job roles and skill requirements in a rapidly evolving labor market. Finally, the open-source implementation of KANVAS is flexible and well-suited for HR managers and relevant stakeholders. Full article

Parking management and operation represent a major challenge for both users and administrators, who seek to ensure efficient utilization, accommodate as many demands as possible, and reduce maintenance costs. This paper presents a theoretical model for an integrated IT system designed for parking management and administration. The modeling process involved designing a parking facility using the AutoCAD Vehicle Tracking v25.00.2775 software package, in accordance with current design standards. To simulate system operation, a dedicated Python v2025.12.0 program was developed to assign parking spaces to arriving vehicles based on specific allocation criteria. Three allocation strategies were applied: random allocation, allocation aimed at minimizing the driving distance within the parking lot, and allocation aimed at reducing the walking distance from the assigned space to the destination. The simulation results show that, in the absence of allocation criteria, parking spaces are utilized in a quasi-uniform manner. The calculated values of variance and standard deviation are significantly lower in this case, increasing as allocation restrictions are introduced, but then returning to reduced values as the occupancy rate grows, since under intensive use the potential for controlled allocation decreases. The relationship between the number of allocations of each parking space and the applied allocation strategies was examined using Pearson and Spearman correlation coefficients. The results reveal a direct linear dependence under moderate demand and an inverse dependence under high demand—patterns consistent with situations observed in practice. The proposed software application provides a practical tool for effective parking management, contributing to the rational use of parking spaces, reduced travel distances within the facility, lower fuel consumption, and consequently, reduced pollution. Full article

In the face of the challenge of urban water resource degradation, green infrastructure construction has become a core strategy in modern urban water resource management. Urban aquatic horticulture (UAH), as an important component of this strategy, possesses the dual value of ecological purification and landscape aesthetics. However, its practical implementation is often constrained by public awareness and acceptance. This study aims to address the mismatch between the dual values of urban aquatic horticulture and public perception, and to develop an optimised plant selection strategy that integrates purification functions with public perception. Based on literature reviews, 18 images of aquatic plant landscapes showcasing different ornamental forms, species richness, and life types were created. A questionnaire survey was conducted on 320 participants to assess their perceptions of landscape aesthetic appeal and visual preferences, and a quantitative relationship model was established using multiple stepwise linear regression analysis. The public’s aesthetic perception of aquatic plant landscapes with different ornamental forms and species richness varies significantly, with flowering plant landscapes more likely to evoke aesthetic perception than non-flowering landscapes. The public’s visual preferences for landscape attributes significantly influence their aesthetic perception of aquatic plant landscapes. A multiple stepwise linear regression equation was established to model the relationship between the aesthetic perception of aquatic plant community landscapes and the public’s visual preferences for landscape attributes. There is no significant association between species richness and perceived landscape aesthetic appeal. The study developed an optimised selection strategy for aquatic plants that integrates purification functions with public perception, providing theoretical basis and practical guidance for the scientific configuration of aquatic horticultural systems in urban green infrastructure. In landscape design, flowering plants with ornamental value should be prioritised, with emphasis on landscape layers, colour, and spatial shaping to enhance public acceptance and promote the sustainable development of urban water resource management. Full article

Air Traffic Flow Management (ATFM) delay refers to the difference between a flight’s Target Take-Off Time (TTOT) and its Calculated Take-Off Time (CTOT), reflecting congestion levels in the air traffic network. ATFM delays are assigned to balance demand and capacity at key points in the network. The traditional First-Come, First-Served (FCFS) approach allocates delays strictly in the order flights are ready to depart, which is simple but inflexible. This study proposes a dynamic priority-based aircraft sequencing method at critical waypoints under multi-resource scenarios, aiming to reduce ATFM delays. An improved Constrained Position Shifting (CPS) constraint is introduced into the optimization model to enhance the influence of flight priority during decision-making. Additionally, three different priority strategies are designed to compare their respective impacts on ATFM delay. Finally, a dynamic priority-based ATFM delay optimization model is developed to address the identified challenges. Experimental results demonstrate that, compared with the FCFS scheme, the three priority strategies achieve maximum ATFM delay reductions of 30.5%, 44.1%, and 19.9%, respectively. The proposed model effectively allocates shorter delays to critical flights, optimizing resource utilization and improving the operational efficiency of the air route network. The research provides a reference framework for air traffic managers in allocating spatiotemporal resources across multiple congestion hotspots. By aligning priorities with network-wide efficiency goals, it overcomes traditional model limitations, avoids local optima, and supports globally optimal ATFM policy and practice. Full article

Preventing illegal, unreported, and unregulated (IUU) fishing—which depletes fishery resources—is a critical task in international fisheries governance. Many countries operate vessel monitoring systems (VMS) and electronic reporting systems (ERS) to track their fishing vessels, while regional fisheries management organizations (RFMOs) are actively considering the adoption of electronic monitoring systems (EMS). Although ERS and EMS share the same operational goals, differences in their concepts and functions lead to technical and institutional limitations when implemented separately. This study presents a conceptual design of an intelligent electronic monitoring and reporting (I-EMR) system model, which integrates the strengths of both systems to address these limitations and provides a framework for efficient operation. The necessity for the prompt and proactive adoption of such systems is reinforced by recent analyses of global IUU fishing trends, which indicate that IUU activities are not decreasing despite existing monitoring efforts. While empirical validation is beyond the scope of this study, the conceptual framework aims to support transparent management of fishery resources, facilitate real-time monitoring of fishing activities, and serve as a foundation for future pilot testing and operational deployment. Full article

Monkeypox (Mpox), a re-emerging zoonotic disease, has garnered global attention due to its evolving epidemiology, diverse clinical manifestations, and significant public health impact. The rapid international spread of the Mpox prompted the World Health Organization to designate the outbreak as a Public Health Emergency of International Concern. Accurate and timely diagnosis is hindered by its critical resemblance to other orthopoxviruses and viral exanthems, underscoring the need for improved diagnostic tools. Point-of-care diagnostic innovations, including CRISPR-based and smartphone-integrated technologies, have revolutionized outbreak management, offering rapid and accurate detection critical for containment and treatment. The effective control of Mpox outbreak underscores the necessity of strengthened global surveillance, equitable healthcare access, rapid diagnostics, the prompt isolation of infected individuals, and the implantation of ring vaccination strategies. The integration of a “One Health” framework that links human, animal, and environmental health is vital for sustained preparedness. Advances in vaccine development, including novel bionic self-adjuvating vaccines and platforms utilizing DNA, mRNA, and viral vectors, highlight promising prevention efforts. However, issues such as vaccine hesitancy, limited immunization coverage and accessibility in resource-constrained regions remain significant barriers. Therapeutic interventions like tecovirimat and the JYNNEOS vaccine demonstrate efficacy but face challenges in scalability and deployment. To address these multifaceted challenges, this review delves into the molecular insights, clinical features, epidemiological trends, and diagnostic challenges posed by Mpox. This review further highlights the critical need for robust scientific evidence and sustained research to inform effective, evidence-based responses, and long-term management strategies for Mpox outbreaks. Full article

With the rapid evolution of 5G wireless communications, millimeter-wave (mmWave) technology has become a crucial enabler for high-speed, low-latency, and large-scale connectivity. As the critical interface for signal transmission, mmWave antennas directly affect system performance, reliability, and application scope. This paper reviews the current state of mmWave antenna technologies in 5G systems, focusing on antenna types, design considerations, and integration strategies. We discuss how the multiple-input multiple-output (MIMO) architectures and advanced beamforming techniques enhance system capacity and link robustness. State-of-the-art integration methods, such as antenna-in-package (AiP) and chip-level integration, are examined for their importance in achieving compact and high-performance mmWave systems. Material selection and fabrication technologies—including low-loss substrates like polytetrafluoroethylene (PTFE), hydrocarbon-based materials, liquid crystal polymer (LCP), and microwave dielectric ceramics, as well as emerging processes such as low-temperature co-fired ceramics (LTCC), 3D printing, and micro-electro-mechanical systems (MEMS)—are also analyzed. Key challenges include propagation path limitations, power consumption and thermal management in highly integrated systems, cost–performance trade-offs for mass production, and interoperability standardization across vendors. Finally, we outline future research directions, including intelligent beam management, reconfigurable antennas, AI-driven designs, and hybrid mmWave–sub-6 GHz systems, highlighting the vital role of mmWave antennas in shaping next-generation wireless networks. Full article

The integration of composite materials into commercial aviation has transformed the industry by providing superior performance benefits, including enhanced fuel efficiency, reduced emissions, and improved structural integrity. With a significant shift towards aircraft featuring high contents of composite materials, the focus has also turned to the challenges associated with the end-of-life management of these materials. Unlike metals, composites are notoriously difficult to recycle due to the strong bonding between fibres and resin, creating significant environmental and economic challenges. The methodology employed—consisting of an extensive literature review that prioritises a holistic approach—aims to provide an overview of the status of composite recyclability in aviation. With this, the report investigates the durability of composites under operational conditions, the associated environmental factors, and their impact on the recycling potential. The dismantling processes for decommissioned aircraft are analysed to identify strategies that preserve material integrity for effective recycling. Established recycling methods are critically evaluated alongside innovative approaches. The study highlights the limitations of current techniques in terms of costs, energy consumption, and material degradation while exploring emerging technologies that aim to overcome these barriers. It is concluded that currently available techniques do not possess the industrial maturity required to handle the amount of composite materials being employed in aviation. Moreover, there is a clear discontinuity between the developments in the usage of composites and their end-of-life recycling, which can cause serious environmental and economic challenges in future years. By combining information regarding composite usage and aircraft retirements, assessing the environmental and economic implications of composite recycling as well as available techniques, and proposing pathways for improvement, this research underscores the importance of adopting sustainable practices in aviation. The findings aim to contribute to the development of a circular economy within the aerospace sector, ensuring the long-term viability and environmental responsibility of future composite-intensive aircraft designs. This is performed by calling for a multi-stakeholder strategy to drive recycling readiness and facilitate the evolution towards a circular economy in aviation, leading to more sustainable design, production, and dismantlement of aircraft in the future. Full article

Urban growth and rising vehicle usage have intensified congestion, accidents, and environmental impact, exposing the limitations of traditional traffic management systems. This study introduces a dual-incident simulation framework to investigate the potential of Vehicle-to-Everything (V2X) technologies in enhancing urban mobility. Using the Eclipse MOSAIC platform integrated with SUMO, a realistic network in Iași, Romania, was modeled under single- and dual-incident scenarios with three V2X penetration levels: 0%, 50%, and 100%. Unlike prior works that focus on single-incident cases or assume full penetration, our approach evaluates cascading disruptions under partial adoption, providing a more realistic transition path for mid-sized European cities. Key performance indicators, i.e., average speed, vehicle density, time loss, and waiting time, were calculated using mathematically defined formulas and validated across multiple simulation runs. Results demonstrate that full V2X deployment reduces average time loss by 18% and peak density by more than 70% compared to baseline conditions, while partial adoption delivers measurable yet limited benefits. The dual-incident scenario shows that V2X-enabled rerouting significantly mitigates cascading congestion effects. These contributions advance the state of the art by bridging microscopic vehicle dynamics with network-level communication modeling, offering quantitative insights for phased V2X implementation and the design of resilient, sustainable intelligent transportation systems. Full article

Loss functions play a significant role in shaping model behavior in machine learning, yet their design implications remain underexplored in natural language processing tasks such as Named Entity Recognition (NER). This study investigates the performance and optimization behavior of five loss functions—L1, L2, Cross-Entropy (CE), KL Divergence (KL), and the proposed DLITE (Discounted Least Information Theory of Entropy) Loss—within transformer-based NER models. DLITE introduces a bounded, entropy-discounting approach to penalization, prioritizing recall and training stability, especially under noisy or imbalanced data conditions. We conducted empirical evaluations across three benchmark NER datasets: Basic NER, CoNLL-2003, and the Broad Twitter Corpus. While CE and KL achieved the highest weighted F1-scores in clean datasets, DLITE Loss demonstrated distinct advantages in macro recall, precision–recall balance, and convergence stability—particularly in noisy environments. Our findings suggest that the choice of loss function should align with application-specific priorities, such as minimizing false negatives or managing uncertainty. DLITE adds a new dimension to model design by enabling more measured predictions, making it a valuable alternative in high-stakes or real-world NLP deployments. Full article