Search Results (19,705)

Hydrogen storage technologies are improving over time, such as in the case of hydrogen adsorption in systems, which has been investigated in various experimental ways, as well as with theoretical methods. The design of systems that meet the needs of their experimental application is one of the challenges of these days. There are different strategies to generate adsorption of more hydrogen molecules, and several research groups have chosen to use alkali metal atoms to cause better interactions between surfaces and hydrogen molecules. Carbon, silicon, boron, phosphorus, and other systems have been reported, with carbon nanostructures being the most widely used. This review describes theoretical studies based on the addition of lithium atoms to various materials to increase the adsorption properties of hydrogen molecules. Full article

This study investigates the integration of 3D laser scanning technology in the retrofitting of Ballast Water Treatment Systems (BWTS) on existing commercial vessels, addressing the global challenge of invasive aquatic species. The methodology combines a bibliometric analysis of keywords—indicating recent trends and knowledge gaps, a feasibility study, and detailed engineering design with on-site supervision. A case study is presented on a crude oil tanker, employing a multi-station 3D scanning strategy across the engine and pump rooms—performed using 63 and 45 scan positions, respectively. These data were processed with removal filters and integrated into specialized CAD software for detailed piping design. The implementation of high-fidelity point clouds served as the digital foundation for modeling the vessel’s existing piping infrastructure and retrofitting with the installation of an electrolysis-based BWTS. Results confirm that 3D scanning enables precise spatial analysis, minimizes retrofitting errors, reduces installation time, and ensures regulatory compliance with the IMO Ballast Water Management Convention. By digitally capturing complex onboard environments, the approach enhances accuracy, safety, and cost-effectiveness in maritime engineering projects. This work underscores the transition toward point cloud-based digital twins as a standard for sustainable and efficient ship conversions in the global shipping industry. Full article

About 16% of typhoons making landfall in China strike Hainan Island, where near-surface extreme winds in dense urban areas exhibit a strong spatiotemporal heterogeneity that is difficult to capture with current observations and mesoscale models. Focusing on Haikou during Super Typhoon Yagi (2024)—the strongest autumn typhoon to hit China since 1949—we developed a multiscale ERA5–WRF–PALM framework to conduct 30 m resolution large-eddy simulations. PALM results are in reasonable agreement with most of the five automatic weather stations, while performance is weaker at the most sheltered park site. Mean near-surface wind speeds increased by 20–50% relative to normal conditions, showing a coastal–urban gradient: maps of weighted cumulative exposure to strong winds (≥Beaufort force 8) show much longer and more intense events along open coasts than within built-up urban cores. Urban morphology exerted nonlinear effects: wind speeds followed a U-shaped relation with both the open-space ratio and mean building height, with suppression zones at ~0.5–0.7 openness and ~20–40 m height, while clusters of super-tall buildings induced Venturi-like acceleration of 2–3 m s⁻¹. Spatiotemporal analysis revealed banded swaths of high winds, with open areas and islands sustaining longer, broader extremes, and dense street grids experiencing shorter, localized events. Methodologically, this study provides a rare, systematically evaluated application of a multiscale ERA5–WRF–PALM framework to a real typhoon case at 30 m resolution in a tropical coastal city. These findings clarify typhoon–city interactions, quantify morphological regulation of extreme winds, and support risk assessment, urban planning, and wind-resilient design in coastal megacities. Full article

This article examines how the same heritage or revival site can produce both welcoming and hostile atmospheres depending on the cohort, yielding selectively permeable environments that enable some groups while constraining others. Climatic volatility further shapes these encounters, as extreme weather has been shown to increase negative valence by making movement and access more difficult, especially for marginalized populations. Drawing on built-form analyses and political history—supplemented with interview data on everyday navigation and affective experiences in cities—the paper examines three cases: Cairo’s Tahrir Square, revivalist university campuses and Buenos Aires women’s marches. To explain why these locales produce varying atmospheres for different groups, the article draws on affordance theory—an empirically grounded account of valenced action possibilities that exist independently of any one observer yet remain harder for vulnerable populations to negotiate. These challenges often intensify around heritage and revival aesthetics, which can alienate outsiders, and are amplified by Crime Prevention Through Environmental Design (CPTED) elements, such as elevation changes, ornamental walls and other territorial cues. The study contributes to urban political ecology, especially scholarship on how aestheticized urban forms serve as instruments through which powerbrokers materialize dominance and produce uneven access to public venues. Full article

Rural areas are currently facing a deepening “social-ecological divide,” where the fragmentation of natural, economic, and cultural data—often trapped in “data silos”—hinders effective systemic governance. To bridge this gap, in this study, the Rural Landscape Information Model (RLIM), an integrative framework designed to reconfigure rural connections through data fusion, process coordination, and performance feedback, is proposed. We validate the framework’s effectiveness through a comparative analysis of two distinct rural archetypes in China: the innovation-driven Yu Village and the heritage-conservation-oriented Hani Terraces. Our results reveal that digital technologies drive distinct empowerment pathways moderated by regional contexts: (1) In the data domain, heterogeneous resources were successfully integrated into the framework in both cases (achieving a Monitoring Coverage > 80%), yet served divergent strategic ends—comprehensive territorial management in Yu Village versus precision heritage monitoring in the Hani Terraces. (2) In the process domain, digital platforms restructured social interactions differently. Yu Village achieved high individual participation (Participation Rate ≈ 0.85) via mobile governance apps, whereas the Hani Terraces relied on cooperative-mediated engagement to bridge the digital divide for elderly farmers. (3) In the performance domain, the interventions yielded contrasting but positive economic-ecological outcomes. Yu Village realized a 25% growth in tourism revenue through “industrial transformation” (Ecology+), while the Hani Terraces achieved a 12% value enhancement by stabilizing traditional agricultural ecosystems (Culture+). This study contributes a verifiable theoretical model and a set of operational tools, demonstrating that digital technologies are not merely instrumental add-ons but catalysts for fostering resilient, collaborative, and context-specific rural socio-ecological systems, ultimately offering scalable governance strategies for sustainable rural revitalization in the digital era. Full article

Clearance in joints caused by assemblage, manufacturing errors, and wear is inevitable, which will affect the dynamic performance of the dual-manipulator system on spacecraft. The motion of the dual-manipulator system with clearances in imperfect joints is the motion of dual-manipulator system with ideal joints. In this paper, the dynamic responses and motion accuracy ofdual-manipulator system on spacecraft considering clearance effects are investigated numerically. The imperfect joint with clearance is considered as contact force constraint and the mathematical model of revolute joint with clearance is established, where the normal contact force is established using nonlinear continuous contact force model and the friction effect is considered using modified Coulomb friction model. Then, a dual-manipulator system on spacecraft with clearance joints is used as the numerical example to implement the investigation. The effects of clearances on dynamic responses and motion accuracy of the dual-manipulator system are presented and discussed via different case studies. Numerical simulation results indicate that clearances present significant effects on the dynamic performances of dual-manipulator system due to contact and impact in clearance joints. The motion accuracy and stability of the dual-manipulator system are obviously reduced. The investigation in this work clearly shows the effects of clearances on dynamic performance of the dual-manipulator system on spacecraft, which is the basis for robust control system design of dual-manipulator system. Full article

Recent advances in image-based 3D reconstruction have seen a shift from traditional photogrammetric techniques to learning-based methods, with Neural Radiance Fields (NeRFs) emerging as a powerful alternative. This study evaluates NeRF (via Nerfstudio) for accurate 3D reconstruction, comparing its performance to the widely used SfM-MVS pipeline implemented in Agisoft Metashape Professional (v. 2.2.1). This work considers a diverse set of datasets with varying object scales, capture methods (including drone imagery), and lighting conditions. Several assessment analyses were conducted, including evaluation of accuracy, completeness, planarity, and density of the reconstructed point clouds. Special attention was given to the influence of shadows and surface flatness on the fidelity of reconstruction. Results show that, despite not being initially designed for metric accuracy, NeRF demonstrates promising spatial consistency, producing reconstructions in some cases comparable to those of conventional methods when provided with precise camera poses. These findings suggest that NeRF may serve as a viable tool for 3D modelling in controlled settings. The applicability of the approach to more diverse and challenging scenarios remains to be explored, with particular attention to optimizing the reconstruction pipeline in terms of pose estimation, point cloud density, and robustness to varying lighting conditions. Full article

Introduction: Rare diseases disperse expertise across institutions and borders, making structured second-opinion systems a pragmatic way to concentrate subspecialty knowledge and reduce diagnostic delays. This scoping review mapped the design, governance, adoption, and impacts of such services across implementation scales. Objectives: To describe how second-opinion services for rare diseases are organized and governed, to characterize technological and workflow models, to summarize benefits and barriers, and to identify priority evidence gaps for implementation. Methods: Using a population–concept–context approach, we included peer-reviewed studies describing implemented second-opinion systems for rare diseases and excluded isolated case reports, purely conceptual proposals, and work outside this focus. Searches in August 2025 covered PubMed/MEDLINE, Scopus, Web of Science Core Collection, Cochrane Library, IEEE Xplore, ACM Digital Library, and LILACS without date limits and were restricted to English, Portuguese, or Spanish. Two reviewers screened independently, and the data were charted with a standardized, piloted form. No formal critical appraisal was undertaken, and the synthesis was descriptive. Results: Initiatives were clustered by scale (European networks, national programs, regional systems, international collaborations) and favored hybrid models over asynchronous and synchronous ones. Across settings, services shared reproducible workflows and provided faster access to expertise, quicker decision-making, and more frequent clarification of care plans. These improvements were enabled by transparent governance and dedicated support but were constrained by platform complexity, the effort required to assemble panels, uneven incentives, interoperability gaps, and medico-legal uncertainty. Conclusions: Systematized second-opinion services for rare diseases are feasible and clinically relevant. Progress hinges on usability, aligned incentives, and pragmatic interoperability, advancing from registries toward bidirectional electronic health record connections, alongside prospective evaluations of outcomes, equity, experience, effectiveness, and costs. Full article

This article explores the integration of food ethics as a proposed fifth and emerging pillar of food security, complementing the four dimensions established by the FAO 1996 framework (availability, accessibility, utilization, and stability). Using Romania as a case study, the research combines descriptive statistical analysis, legislative review, and conceptual interpretation to examine how moral responsibility, social equity, and food citizenship shape sustainable food systems. Quantitative data from Eurostat (2020–2022) reveal that Romania generates over 3.4 million tons of food waste annually, with households accounting for more than half of the total. This wasted abundance coexists with persistent food insecurity, affecting 14.7% of the population who cannot afford a protein-based meal even once every second day. Given the short time series (n = 3), including the entire data that was reported to date and the exclusive use of secondary data, the statistical results are interpreted descriptively and, where applicable, exploratorily. In this context, the findings demonstrate that food waste is not merely an issue of economic inefficiency, but rather a profound ethical and social imbalance. This research argues for the conceptual recognition of an ethical pillar within the food security framework linking moral awareness, responsible consumption, and equitable access to food. By advancing food ethics as a normative and societal foundation of sustainable food systems, this article offers a framework relevant for policy design, civic engagement, and collective responsibility, reframing food security beyond a purely technical objective. Full article

The prevailing challenges of fading characteristics and identity crises in historical and cultural districts of small and medium-sized cities have been identified. Traditional analytical methods have been found to be deficient in systematically capturing the unique forms and urban memory of these districts. The present study thus adopts the Shangcheng Historical and Cultural District of Huangling County as a case study, proposing a comprehensive analytical framework that integrates urban memory and multi-dimensional methods such as space syntax, grounded-theory-inspired coding, and urban image analysis. The district is subject to a systematic assessment of its spatial form, structural design, and the mechanisms by which urban memory is conveyed. The proposal sets out targeted renewal strategies for four aspects: paths, edges, nodes and landmarks, and districts. The research findings are as follows: (1) Paths with high integration and connection degrees simultaneously serve as both sacrificial axes and carriers of folk narratives. (2) Edges are composed of the city wall ruins, Loess Plateau landform, and street spaces. The fishbone-like street structure leads to significant differences in the connection degrees of main and secondary roads. (3) Nodes such as Guanyv Temple-Confucian Temple, the South Gate, and the North City Wall Ruins Square have high visual control, while the visual integration and visual control of the Qiaoshan Middle School and Gongsun Road historical nodes are relatively low, and their spatial accessibility is insufficient. (4) Based on the “memory–space” coupling relationship, the district is divided into the Academy Life Area, the Historical and Cultural Core Experience Area, and the Comprehensive Service Area, providing an effective path to alleviate the problem of functional homogenization. The present study proffers a novel perspective on the revitalization mechanisms of historical districts in small and medium-sized cities, encompassing both theoretical integration and practical strategy levels. It further contributes methodological inspirations and localized planning experiences for addressing the cultural disconnection and spatial inactivity problems of historical urban areas on a global scale. Full article

Existing experience-based methods cannot effectively assist commercial building operators in allocating workforce resources according to contracts and balance multiple workforce management objectives under resource constraints, leading to misaligned allocation strategies. To address this issue, this study develops a workforce resource allocation optimization model based on BERT and the NSGA-II. First, a natural language processing (NLP) model is trained to extract operational tasks from contracts and match required workforce types, thereby establishing the framework for workforce allocation schemes. Second, a mathematical optimization model for workforce allocation strategies is constructed with the objectives of minimizing workforce wage costs (B1), maximizing average service levels (B2), and maximizing average digital technology acceptance (B3). An algorithm based on NSGA-II is then designed to solve the model and obtain the optimal Pareto solution set of allocation schemes. Third, the CRITIC–VIKOR method evaluates the Pareto set and determines the final recommended schemes. A case study was conducted on a university campus in Shandong, China, to validate the model’s effectiveness. The results show that the NLP model successfully identified 14 operational tasks and 13 required workforce types from the contract. Compared with the operator’s expected values (B1 = 46,0000 CNY, B2 = 65 points, B3 = 50 points), the optimal allocation scheme calculated using NSGA-II and the CRITIC–VIKOR method reduces B1 by 10.79%, increases B2 by 18.02%, and improves the B3 by 16.79%. This study formulates the workforce allocation problem in the operation stage as a mathematical optimization model and, for the first time, incorporates the workforce’s digital technology acceptance as an optimization objective, thereby filling a theoretical gap in workforce management for commercial building operations. The proposed model provides operators with a semi-automated decision-support tool to enhance workforce management, thereby promoting the sustainable operation of commercial buildings. Full article

The contribution that the inclusion of CS in the curriculum can make to address SDG 4—Quality Education—which fosters convergence between Science Education and Education for Sustainable Development, essential for addressing the sustainability challenges currently facing humanity, has been widely recognized. This recognition is driving the inclusion of CS in formal education. However, to ensure that the use of CS in formal education contributes to this objective, a systematic and rigorous evaluation of its benefits in terms of participants’ learning outcomes (LO) is necessary. This study presents a systematic review of the published literature on CS projects implemented in compulsory education to examine whether students’ LO from participation in CS projects are evaluated, and if so, how this evaluation is performed. The results indicate a lack of systematic evaluation of LO from participating in CS projects. Moreover, although in 79% of cases, where some LO is evaluated, the evaluation reported positive results, in most of them, the results may have been influenced by the voluntary or mandatory nature of participation in the projects and the design of the evaluation itself. This may bias the results, leading to an over-optimistic view of the contribution of CS to SDG 4. In order to obtain solid evidence of the benefits, or lack thereof, for learners of participation in CS activities, which can guide the designers and educators in improving the CS projects to maximize their educational and sustainability impacts, some recommendations for future studies are presented. Full article

In this study, an adaptive event-driven coordination paradigm is proposed for achieving consensus in nonlinear multi-agent systems (MASs) over directed networks. First, a newly dynamic event-triggered mechanism with single-point historical information is introduced to minimize unnecessary network communication. And a more general form of an event triggering mechanism with moving window historical information is designed for further saving network resources. Considering that the use of historical information over a long period of time may cause deviations, an event-triggered mechanism that can adjust the maximum memory length is proposed in this work to minimize unnecessary network communication. Secondly, the unknown nonlinearities in the MAS model are addressed using the universal approximation capability of neural networks. Then, a methodology for distributed adaptive control under event-triggered mechanisms is introduced leveraging the memory-based command-filtered backstepping methodology, and the proposed scheme resolves the complexity explosion problem. Finally, a case study is conducted to validate the feasibility of the proposed method. Full article

Large Language Models (LLMs) promise to enhance clinical decision-making, yet empirical studies reveal a paradox: physician performance with LLM assistance shows minimal improvement or even deterioration. This failure stems from an “acquiescence problem”: current LLMs passively confirm rather than challenge clinicians’ hypotheses, reinforcing cognitive biases such as anchoring and premature closure. To address these limitations, we propose a Dialogic Reasoning Framework that operationalizes Dialogical AI principles through a prototype implementation named “Diagnostic Dialogue” (DiDi). This framework operationalizes LLMs into three user-controlled roles: the Framework Coach (guiding structured reasoning), the Socratic Guide (asking probing questions), and the Red Team Partner (presenting evidence-based alternatives). Built upon Retrieval-Augmented Generation (RAG) architecture for factual grounding and traceability, this framework transforms LLMs from passive information providers into active reasoning partners that systematically mitigate cognitive bias. We evaluate the feasibility and qualitative impact of this framework through a pilot study (DiDi) deployed at Centro Chirurgico Toscano (CCT). Through purposive sampling of complex clinical scenarios, we present comparative case studies illustrating how the dialogic approach generates necessary cognitive friction to overcome acquiescence observed in standard LLM interactions. While rigorous clinical validation through randomized controlled trials remains necessary, this work establishes a methodological foundation for designing LLM-based clinical decision support systems that genuinely augment human clinical reasoning. Full article

Background: Periodontitis is a multifactorial, chronic inflammatory disease that leads to progressive destruction of the periodontal apparatus. Despite the effectiveness of scaling and root planing (SRP), residual inflammation and limited regenerative potential justify the search for adjunctive biologic therapies. Platelet-derived concentrates, including platelet-rich plasma (PRP), platelet-rich fibrin (PRF), concentrated growth factors (CGF), and platelet-poor plasma (PPP), have gained attention as autologous sources of growth factors enhancing periodontal regeneration. Aim: This narrative review provides a comparative analysis of the biological mechanisms, preparation protocols, and clinical outcomes associated with the adjunctive use of platelet-derived concentrates in non-surgical periodontal therapy. Methods: A narrative literature review was conducted using English-language publications retrieved from PubMed and Google Scholar, covering studies published from 2012 onward. The search strategy was based on combinations of keywords related to platelet-derived concentrates and non-surgical periodontal therapy. In vitro, in vivo, and clinical studies, as well as relevant narrative, systematic, and umbrella reviews evaluating the adjunctive use of platelet-derived concentrates (PRP, PRF, CGF, and PPP) were considered. Studies focusing on biological mechanisms, preparation protocols, and clinical periodontal outcomes were included, whereas case reports, studies unrelated to periodontal therapy, and publications lacking relevant clinical or biological outcome data were excluded. Results: Most clinical studies reported improvements in probing depth reduction, clinical attachment level gain, and bleeding indices following adjunctive use of platelet-derived concentrates with SRP. PRF tended to demonstrate more consistent clinical outcomes compared to PRP, potentially related to its simplified preparation and sustained release of bioactive molecules. CGF showed promising osteogenic and angiogenic properties in preclinical and early clinical studies. PPP, although less extensively investigated, exhibited regenerative and antimicrobial potential in preliminary reports. Conclusions: Platelet-derived concentrates may serve as valuable adjuncts in non-surgical periodontal therapy; however, the current evidence is characterized by methodological heterogeneity and variable study quality. While PRF appears to yield more consistent clinical results, definitive conclusions regarding superiority among different platelet concentrates cannot be drawn. Further well-designed randomized controlled trials are required, particularly for CGF and PPP. Full article