Search Results (22,398)

The primary aim of this paper is to support the optimization of asset management in railway infrastructure through digitalization and criticality analysis. It addresses the current challenges in railway infrastructure management, where data-driven decision making and automation are key for effective resource allocation. The paper presents a methodology that emphasizes the development of a robust data model for criticality analysis, along with the advantages of integrating advanced digital tools. A master table is designed to rank assets and automatically calculate criticality through a novel asset attribute characterization (AAC) process. Digitalization facilitates dynamic, on-demand criticality assessments, which are essential in managing complex networks. The study also underscores the importance of combining digital technology adoption with organizational change management. The data process and structure proposed can be viewed as an ontological framework adaptable to various contexts, enabling more informed and efficient asset ranking decisions. This methodology is derived from its application to a metropolitan railway network, where thousands of assets were evaluated, providing a practical approach for conducting criticality assessments in a digitized environment. Full article

This review discusses the challenges of integrating emerging transportation technologies into existing urban environments, considering their impact on equity, sustainability, and urban design. The aim is to provide readers with strategic insights and policy recommendations for incorporating aerospace innovations into transportation systems. This narrative review draws on a wide range of publications, including books, journal articles, and industry reports, to examine the multifaceted aspects of urban aviation. The review explores the scales of aerospace transport, detailing the technologies enabling urban aviation, the necessary urban adaptations to support such a system, and the social and regulatory challenges of integrating urban air mobility into existing transportation networks. The research suggests that for urban air mobility to be successfully integrated into existing transportation systems, further research is needed on the social and regulatory implications, particularly regarding equitable access, sustainable practices, and community engagement. Full article

The increasing focus on environmental sustainability has prompted the healthcare sector, including dentistry, to reconsider waste management practices. Dental offices generate various waste streams from outdated technologies, including single-use plastics, hazardous materials, and digital waste. This scoping review explores how integrating circular economy principles with lean management practices can enhance sustainability and operational efficiency in dental clinics. Using the PRISMA methodology, the review identifies 30 articles that passed the Cochrane Risk of Bias Tool and the Critical Appraisal Skills Program (CASP) checklist from 2000. Circular economy principles focus on reducing waste and maximizing resource reuse, while lean management seeks to improve efficiency and minimize process waste. Together, these approaches can significantly reduce resource consumption and enhance recycling efforts in dental practices. Despite barriers such as high technology costs, regulatory constraints, and limited recycling infrastructure, case studies highlight successful implementation in healthcare settings, demonstrating improved environmental and operational outcomes. Collaboration between dental professionals, policymakers, and industry leaders is essential for promoting the adoption of these sustainable practices. Full article

Power cyber–physical systems such as multi-area power systems (MAPSs) have gained considerable attention due to their integration of power electronics with wireless communications technologies. Incorporating a communication setup enhances the sustainability, reliability, and efficiency of these systems. Amidst these exceptional benefits, such systems’ distributed nature invites various cyber-attacks. This work focuses on the equal power sharing of MAPSs in the event of false data injection (FDI) attacks. The proposed work uses a sliding mode control (SMC) mechanism to ensure timely detection of challenges such as FDI attacks and load change, making MAPSs reliable and secure. First, a SMC-based strategy is deployed to enable the detection and isolation of compromised participants in MAPS operations to achieve equal power sharing. Second, time-varying FDI attacks on MAPSs are formulated and demonstrate their impact on equal power sharing. Third, a robust adaptive sliding mode observer is used to accurately assess the state of the MAPS to handle state errors robustly and automatically adjust parameters for identifying FDI attacks and load changes. Lastly, simulation results are presented to explain the useful ability of the suggested method. Full article

This article examines the role of computer science in enhancing laser processing techniques, emphasizing the transformative potential of their integration into manufacturing. It discusses key areas where computational methods enhance the precision, adaptability, and performance of laser operations. Through advanced modeling and simulation techniques, a deeper understanding of material behavior under laser irradiation was achieved, enabling the optimization of processing parameters and a reduction in defects. The role of intelligent control systems, driven by machine learning and artificial intelligence, was examined, showcasing how a real-time data analysis and adjustments lead to improved process reliability and quality. The utilization of computer-generated diffractive optical elements (DOEs) was emphasized as a means to precisely control laser beam characteristics, thus broadening the application opportunities across various industries. Additionally, the significance of predictive modeling and data analyses in enhancing manufacturing effectiveness and sustainability is discussed. While challenges such as the need for specialized expertise and investment in new technologies persist, this article underscores the considerable advantages of integrating computer science with laser processing. Future research should aim to address these challenges, further improving the quality, adaptability, and sustainability of manufacturing processes. Full article

Nanotechnology and machine learning (ML) are rapidly emerging fields with numerous real-world applications in medicine, materials science, computer engineering, and data processing. ML enhances nanotechnology by facilitating the processing of dataset in nanomaterial synthesis, characterization, and optimization of nanoscale properties. Conversely, nanotechnology improves the speed and efficiency of computing power, which is crucial for ML algorithms. Although the capabilities of nanotechnology and ML are still in their infancy, a review of the research literature provides insights into the exciting frontiers of these fields and suggests that their integration can be transformative. Future research directions include developing tools for manipulating nanomaterials and ensuring ethical and unbiased data collection for ML models. This review emphasizes the importance of the coevolution of these technologies and their mutual reinforcement to advance scientific and societal goals. Full article

The global cumulative installed PV capacity is anticipated to surpass 2 TWp by the end of 2024, which is an increase in three orders of magnitude from the 1 GWp at the end of 2004. Depending on the energy transition scenarios, up to 8 kWp per capita have to be operational by 2050 globally. In Europe, this capacity could even be 50% higher, and this will have consequences on the decisions regarding where to install this capacity; thus, these decisions will be significantly impacted. This paper gives an overview of the technology options for installing PV systems in areas already used for other human activities as well as integrating them into ships and vehicles without the acquisition of extra land. The focus of this paper is on the situations within the European Union, such as land competition, and presents innovative solutions. Full article

Background: In northern countries, spring requires the removal of large volumes of abrasive materials used in winter road maintenance. This sweeping process, crucial for safety and environmental protection, has traditionally relied on conventional mechanical brooms. Recent technological innovations, however, have introduced more efficient and environmentally friendly sweeping solutions; Methods: This study provides a comprehensive comparative analysis of the environmental and operational performance of these innovative sweeping systems versus conventional methods. Using simulation models based on real-world data and integrating fuel consumption models, the analysis replicates sweeping behaviors to assess both operational and environmental performance. A sensitivity analysis was conducted using these models, focusing on key parameters such as the collection rate, the number of trucks, the payload capacity, and the truck unloading duration; Results: The results show that the innovative sweeping system achieves an average 45% reduction in GHG emissions per kilometer compared to the conventional system, consistently demonstrating superior environmental efficiency across all resources configurations; Conclusions: These insights offer valuable guidance for service providers by identifying effective resource configurations that align with both environmental and operational objectives. The approach adopted in this study demonstrates the potential to develop decision-making support tools that balance operational and environmental pillars of sustainability, encouraging policy decision-makers to adopt greener procurement policies. Future research should explore the integration of advanced technologies such as IoT, AI-driven analytics, and digital twin systems, along with life cycle assessments, to further support sustainable logistics in road maintenance. Full article

This study aims to develop a Secured Fiscal Credits Model to address the challenges of managing Italy’s “Superbonus 110%” tax credit. Using a decentralised governance approach, our research objective is to provide a feasible system to track and control the entire tax credit process, from generation to redemption. The method integrates Artificial Intelligence and blockchain technology within a Decentralised Autonomous Organisation architecture, combined with a Multi-agent System to establish a tokenomics model. The system is structured to prevent accidental errors, such as double spending or overspending, and detect fraudulent behaviours, like false claims of completed work. Our main findings indicate that deploying two Decentralised Autonomous Organisations on the Algorand blockchain significantly enhances trust and security, supporting effective oversight of the Superbonus process and facilitating transparent value exchange among stakeholders. This decentralised governance model introduces substantial automation, reduces biases, and offers a viable solution to strengthen tax credit management. This work proposes an innovative, technology-driven framework that can be generalised to similar fiscal and governance contexts, enhancing transparency and control. Full article

Lepidopteran insects are a major threat to global agriculture, causing significant crop losses and economic damage. Traditional pest control methods are becoming less effective due to the rapid evolution of insecticide resistance. This study explores the current status and genomic characteristics of 1315 Lepidopteran records, alongside an overview of relevant research, utilizing advanced functional genomics techniques, including RNA-seq and CRISPR/Cas9 gene-editing technologies to uncover the molecular mechanisms underlying insecticide resistance. Our genomic analysis revealed significant variability in genome size, assembly quality, and chromosome number, which may influence species’ biology and resistance mechanisms. We identified key resistance-associated genes and pathways, including detoxification and metabolic pathways, which help these insects evade chemical control. By employing CRISPR/Cas9 gene-editing techniques, we directly manipulated resistance-associated genes to confirm their roles in resistance, demonstrating their potential for targeted interventions in pest management. These findings emphasize the value of integrating genomic data into the development of effective and sustainable pest control strategies, reducing reliance on chemical insecticides and promoting environmentally friendly integrated pest management (IPM) approaches. Our study highlights the critical role of functional genomics in IPM and its potential to provide long-term solutions to the growing challenge of Lepidopteran resistance. Full article

This paper presents a comprehensive review of state-of-health (SoH) estimation methods for lithium-ion batteries, with a particular focus on the specific challenges encountered in hybrid electric vehicle (HEV) applications. As the demand for electric transportation grows, accurately assessing battery health has become crucial to ensuring vehicle range, safety, and battery lifespan, underscoring the relevance of high-precision SoH estimation methods in HEV applications. The paper begins with outlining current SoH estimation methods, including capacity-based, impedance-based, voltage and temperature-based, and model-based approaches, analyzing their advantages, limitations, and applicability. The paper then examines the impact of unique operating conditions in HEVs, such as frequent charge–discharge cycles and fluctuating power demands, which necessitate tailored SoH estimation techniques. Moreover, this review summarizes the latest research advances, identifies gaps in existing methods, and proposes scientifically innovative improvements, such as refining estimation models, developing techniques specific to HEV operational profiles, and integrating multiple parameters (e.g., voltage, temperature, and impedance) to enhance estimation accuracy. These approaches offer new pathways to achieve higher predictive accuracy, better meeting practical application needs. The paper also underscores the importance of validating these estimation methods in real-world scenarios to ensure their practical feasibility. Through systematic evaluation and innovative recommendations, this review contributes to a deeper understanding of SoH estimation for lithium-ion batteries, especially in HEV contexts, and provides a theoretical basis to advance battery management system optimization technologies. Full article

Background and Objectives: This article investigates the transformative impact of 3D and bio 3D printing technologies in assisted reproductive technology (ART), offering a comprehensive review of their applications in improving reproductive outcomes. Materials and Methods: Following PRISMA guidelines, we conducted a thorough literature search focusing on the intersection of ART and additive manufacturing, resulting in the inclusion of 48 research papers. Results: The study highlights bio 3D printing’s potential in revolutionizing female infertility treatments, especially in follicle complex culture and ovary printing. We explore the use of decellularized extracellular matrix (dECM) as bioink, demonstrating its efficacy in replicating the ovarian microenvironment for in vitro maturation of primordial oocytes. Furthermore, advancements in endometrial cavity interventions are discussed, including the application of sustained-release systems for growth factors and stem cell integration for endometrial regeneration, showing promise in addressing conditions like Asherman’s syndrome and thin endometrium. We also examine the role of conventional 3D printing in reproductive medicine, including its use in educational simulators, personalized IVF instruments, and microfluidic platforms, enhancing training and precision in reproductive procedures. Conclusions: Our review underscores both 3D printing technologies’ contribution to the dynamic landscape of reproductive medicine. They offer innovative solutions for individualized patient care, augmenting success rates in fertility treatments. This research not only presents current achievements but also anticipates future advancements in these domains, promising to expand the horizons for individuals and families seeking assistance in their reproductive journeys. Full article

Building integrated photovoltaics (BIPVs) consist of PV panels that are integrated into a building as part of its construction. This technology has advantages such as the production of electricity without necessitating additional land area. This paper provides a literature review on recent developments in urban building energy modelling, including tools and methods as well as how they can be used to predict the effect of PV systems on building outdoor and indoor environments. It is also intended to provide a critical analysis on how PV systems affect the urban environment, both from an energy and a comfort point of view. The microclimate, namely the urban heat island concept, is introduced and related to the existence of PV systems. It is concluded that urban building energy models (UBEMs) can be effective in studying the performance of PV systems in the urban environment. It allows one to simultaneously predict building energy performance and microclimate effects. However, there is a need to develop new methodologies to overcome the challenges associated with UBEMs, especially those concerning non-geometric data, which lead to a major source of errors, and to find an effective method to predict the effect of PV systems in the urban environment. Full article

This study investigated the accuracy and precision of a commercially available PNT solution that uses DGNSS-SBAS technology. Time and position data were sampled at a frequency of 20Hz during both a short and long trajectory of a simulated controlled dry-land slalom, as well as during a real-world on-water slalom exercise. The primary objective was to assess the positional accuracy, availability, integrity, and service continuity of the PNT solution while evaluating its ability to differentiate between trajectories. Additionally, the simulated results were compared with an on-water real-world slalom test to validate the findings. The results of the controlled dry-land slalom test indicate that the PNT solution provided accurate measurements with an overall mean ± SD Hrms of 0.20 ± 0.02 m. The integrity measures, HDOD and PDOP, were found to be ideal to excellent, with values of 0.68 ± 0.03 and 1.36 ± 0.07, respectively. The PNT solution utilised an average of 20 ± 1 satellites from the constellation, resulting in an accuracy of <1.5% when measuring the known trajectory of 50 simulated slalom runs. The data from the real-world on-water slalom test supported these findings, providing similar or improved results. Based on these findings, a PNT solution using DGNSS-SBAS can be considered an effective means of tracking athlete trajectory in the sport of canoe slalom. Future research should be conducted to quantify its efficacy more precisely. Full article

The integration of blockchain technology into supply chain management (SCM) has emerged as a revolutionary force transforming traditional business operations. This study uses bibliometric analysis on 1069 articles from the Scopus database, using text mining and Python to uncover predominant themes and research trends at the intersection of blockchain and SCM. The key findings revealed three main thematic groups: ‘blockchain to improve transparency and traceability in SCM’ (supported by 323 articles), ‘impact of blockchain on supply chain efficiency and cost reduction’ (295 articles), and ‘blockchain-enabled supply chain resilience’ (191 articles). Furthermore, text mining highlighted prominent themes such as ‘decentralized supply chain networks’ (204 articles), ‘smart contracts for automated processes in SCM’ (234 articles), and ‘blockchain for sustainable supply chain practices’ (227 articles). The inclusion of sustainability themes reflects the growing importance of environmentally conscious strategies within supply chains, driven by the capacity of blockchain to reduce waste, and promote resource efficiency. The study identifies critical literature gaps, advocating for further exploration of the socio-economic impacts of blockchain on SCM. The topic extraction suggests new directions for SCM theory, while the role of blockchain in fostering sustainable and ethical supply chains is underscored. Practically, blockchain and IoT emerge as pivotal in the advancement of SCM, with text mining offering industry foresight and emphasizing blockchain-driven resilient strategies. Limitations include reliance on a single database and the recommendation that future studies incorporate diverse sources and qualitative insights. The findings provide a roadmap for academics and practitioners, highlighting potential avenues in SCM, especially in the context of sustainable and ethical practices. Full article