Search Results (5,581)

The increasing deployment of wind energy has brought renewed attention to aeroacoustic noise generated by wind turbine blades, where broadband noise is primarily associated with vortex shedding at the trailing edge (TE) and leading edge (LE) of airfoils. Owls, particularly Tyto alba, exhibit wing morphologies such as serrations, velvet-like surfaces, and fringes that enable silent flight through aerodynamic noise suppression. This study presents a scoping review of the scientific literature on owl-inspired serration strategies applied to aerodynamic airfoils and wind turbine blades. The literature search was conducted across major academic databases, including Scopus, ScienceDirect, SpringerLink, and MDPI, covering publications from 1970 to 2025. A total of 69 experimental and numerical studies focusing on LE and TE serrations was analyzed. The review integrates aeroacoustic analysis with bio-inspired design perspectives. The analyzed studies consistently show that serrated geometries modify vortex dynamics and turbulence structures, leading to measurable acoustic benefits. Experimentally, the largest reductions reported for aerodynamic airfoils reached about 7 dB for both LE and TE serrations, mainly as broadband noise attenuation, in specific frequency ranges. Numerically, the highest reported reduction reached up to 21 dB for a serrated TE configuration, corresponding to spectral SPL reduction mainly below 1.6 kHz. The reviewed studies also indicate that the associated aerodynamic response is strongly configuration-dependent, ranging from limited penalties to measurable changes in lift, drag, power output, or structural loading. Numerical simulations further support experimental findings and highlight the importance of geometric parameters such as serration amplitude, wavelength, and spacing. Overall, bio-inspired serrations represent a promising passive strategy for aeroacoustic noise mitigation in wind turbines, drones, and rotating aerodynamic systems. Future research should focus on the multi-objective optimization of serration geometry, large-scale experimental validation, and the integration of bio-inspired concepts into industrial blade designs. Full article

Cognition in older adults may be influenced by environmental factors; however, the pathways linking environmental exposures and cognition remain unclear. The aim of this narrative review is to synthesize evidence on the association between the environment and cognition in older adults, integrating biological, environmental, and behavioral elements. Systematic reviews and original studies addressing this topic were identified in Web of Science, PubMed, and Scopus. The primary neural processes associated with maintaining cognition during aging are neuronal plasticity and compensatory scaffolding. Participation in intellectually stimulating activities, physical exercise, and a healthy diet; mitigation of chronic stress; reduction in the severity of depressive symptoms; and buffering against the adverse effects of air pollution are proposed as plausible pathways that may mediate the relationship between neural processes and the environment. In this context, environmental factors that affect cognition can be classified at three levels: (i) micro-level (family and home): social interaction with family members and indoor pollution; (ii) meso-level (community and services): social interaction, land-use diversity, transportation systems, environmental design, and urban green spaces; and (iii) macro-level (society in general and public policies): social representations of old age and aging (positive aging vs. ageism) and public policies aimed at improving pathways related to cognitive maintenance. Overall, the environment may influence cognition in older adults; however, the available studies show methodological and conceptual heterogeneity, inconsistent findings, and important gaps in knowledge. Full article

Imbalanced class distributions hinder time series classifiers by underrepresenting rare yet important events. We introduce Path Signature Synthetic Time-series Oversampling (PSSTO), a structure-preserving oversampling method that operates in path signature space to synthesize informative minority samples while pruning low-quality ones. Across 12 public datasets, PSSTO with a random forest improves classification over conventional resampling approaches on average. Pairwise Wilcoxon signed-rank tests against these approaches indicate statistically significant gains. Compared with time series-specific oversamplers, PSSTO with random forest attains the best averages on F1, G-mean, and AUC compared to the strongest alternative. These results show that structure-preserving oversampling in signature space is an effective and broadly applicable remedy for imbalanced time-series classification. Full article

As multi-view datasets expand across diverse practical fields, feature selection (FS) has become an indispensable preparatory stage for machine learning models. Nevertheless, real-world multi-view data is often unlabeled and distributed among isolated clients, posing significant challenges to traditional centralized methods due to privacy concerns and communication constraints. Furthermore, existing centralized and federated approaches frequently suffer from entrapment in local optima and lack robust convergence guarantees. To address these issues, we propose Fed-MUFSHT, a federated framework for multi-view unsupervised FS (MUFS) that integrates tensor learning with a novel metaheuristic optimizer, Hierarchical-Cognitive Tianji’s Horse Racing Optimization (HC-THRO). Within the federated learning paradigm, Fed-MUFSHT follows a dual-stage local optimization process. Stage 1 applies HC-THRO, which integrates Hierarchical Competitive Learning and Adaptive Cognitive Mapping to simulate multi-level strategic competition and cognitive adaptation among individuals. This design enhances global exploration, adaptive learning, and fine-grained feature selection in high-dimensional spaces. Stage 2 employs a TL module based on canonical polyadic (CP) decomposition to perform missing-view imputation and refine latent representation learning. At the global level, a privacy-preserving aggregation strategy based on Normalized Mutual Information (NMI) and feature weights enables efficient model coordination without exposing raw data. Comparative experiments on several public benchmark datasets reveal that Fed-MUFSHT maintains clear advantages over strong competing methods, showing better optimization results together with more dependable convergence characteristics. The overall evidence suggests that the proposed approach is both robust and effective for distributed optimization tasks involving privacy protection. Full article

Revisit intention is increasingly recognized as a key indicator of sustainable heritage tourism, as it reflects long-term visitor engagement rather than one-time consumption. However, limited attention has been paid to how tourism preferences shape perceived heritage quality and subsequently influence revisit intention, particularly in industrial heritage contexts undergoing urban regeneration. This study develops a structural model linking tourism preferences, perceived quality, and revisit intention, using Shanghai’s waterfront industrial heritage as an empirical case. Based on 335 valid questionnaires, structural equation modeling (SEM) is employed to examine the relationships among environmental preference, cultural and social sustainability preferences, situational perception, and behavioral intention. The results indicate that preference for a sustainable public space environment significantly enhances both physical and atmospheric perception, which in turn positively affects revisit intention. In contrast, social sustainability shows limited influence, suggesting that visitors’ behavioral responses are more strongly driven by environmental quality and experiential engagement in regenerated industrial heritage settings. This study contributes to sustainable heritage tourism research by integrating preference-based perception mechanisms into revisit intention analysis. It also provides practical implications for enhancing long-term attractiveness through experience-oriented adaptive reuse strategies. Full article

Against the backdrop of rapid population aging, rural public spaces face growing challenges in meeting the everyday needs of older adults. Drawing on a place-based care perspective, this study develops age-friendly design strategies attuned to the spatial and cultural characteristics of rural environments. Using a mixed-methods approach that includes field observations, structured interviews, and questionnaire surveys, we identify the needs of older adults in rural public spaces. These needs are first clustered using the K-means algorithm and then analyzed using the FKANO model to extract core priorities. Their relative importance is quantified by an integrated procedure that combines ordinal relation diagrams and entropy weighting. Building on these results, we propose an age-friendly design framework and validate it with spatial simulation to assess scale, accessibility, and connectivity. The findings highlight five critical features prioritized by older adults in rural areas: non-slip surfaces, barrier-free access, safety railings, lighting systems, and public restrooms. The study provides a targeted and actionable pathway for the age-adaptive transformation of rural public spaces, offering both a theoretical foundation and a practical design paradigm for aging-friendly rural environments worldwide. Full article

The subjective perception of safety in public space is a crucial indicator of urban participation, shaping how people experience and navigate their surroundings. Urban fear spaces highlight how physical, social, and emotional factors unequally structure access to and use of public environments, linking spatial perception to social justice. This paper addresses the question: What opportunities and limitations does a mixed-methods approach—combining immersive Virtual Reality (VR), electrodermal activity (EDA) measurement, and semi-structured interviews—offer for examining subjective perceptions of urban fear? It offers a methodological reflection on an exploratory study of potential fear spaces on the campus of Ruhr University Bochum, hypothesizing that mixed-methods integration reveals non-conscious arousal patterns inaccessible via verbal data alone. We discuss methodological potentials and limitations in integrating physiological data within qualitative frameworks. The study design comprised VR simulation, physiological signal acquisition, and qualitative interpretation and triangulation. Findings show that combining immersive VR with EDA detects non-conscious physiological arousal patterns that would remain inaccessible through verbal data alone, while simultaneously revealing substantial interpretative challenges that necessitate qualitative contextualization. Integrating interviews proved vital for linking physiological patterns to subjective meaning. The reflection concludes with implications for applying such multimodal approaches in participatory urban planning and spatial research. Full article

Sub-Saharan African health systems face critical funding challenges due to declining foreign aid, mounting debt and increasing disease burdens. Traditional financing mechanisms have proven inadequate, necessitating the exploration of innovative domestic revenue mobilization (DRM) strategies. This paper contributes to the health economics literature by examining the use of innovative tax models as DRM strategies for sustainable health financing in Sub-Saharan Africa, using the fiscal space for health framework. This narrative review synthesizes peer-reviewed articles, policy documents, and grey literature published between 2010 and 2025. The review identifies four promising innovative models: health taxes (tobacco, alcohol, sugar-sweetened beverages), environmental levies (pollution, carbon, plastic), digital taxation (digital services taxes, mobile money taxes, Value Added Tax (VAT) on digital services) and resource extraction taxes. The evidence demonstrates significant revenue generation potential while achieving public health and environmental co-benefits. However, critical implementation challenges persist: weak administrative capacity, poor governance quality, equity concerns and extensive informality and economic diversity. The paper recommends strengthening tax administration through digital infrastructure investment and capacity building, implementing progressive tax design with targeted exemptions, enhancing transparency and linking tax revenue to health service delivery, and tailoring reforms to country-specific contexts while learning from regional experience. Full article

This article draws on public opinion surveys conducted as part of the AV-PL-ROAD project, “Polish Road to Automation of Road Transport”. Although selected findings from this survey material were published in 2023, the earlier study was limited to descriptive statistical analysis. The present paper re-examines the same empirical dataset through a different analytical framework focused on latent-structure reconstruction, using a different analytical framework focused on latent-structure reconstruction, providing a more structured and informative interpretation of perceptions of autonomous vehicles in Poland. The study combines within-respondent standardization, Principal Component Analysis (PCA), and k-means clustering to identify the dominant dimensions of perception and recurring perception profiles, complemented by qualitative insights from focus group interviews (FGI) used to support interpretation. The results indicate that perceptions of autonomous vehicles are not one-dimensional, but are organized around three main axes: systemic benefits versus implementation barriers, technological trust and information security, and regulatory-ethical readiness linked to deployment conditions. The analysis also reveals four recurring perception profiles that do not map directly onto simple demographic divisions and are better understood in relation to operational and institutional context. In addition, statistically significant differences between clusters were confirmed using nonparametric tests (Kruskal–Wallis with Dunn–Šidák post hoc analysis). The main contribution of the paper is methodological: it illustrates that previously analyzed survey data can yield structurally informative insights, including the identification of latent dimensions, perception profiles, and statistically significant differences between clusters when reinterpreted through a latent-space approach rather than conventional descriptive methods. The findings provide additional evidence on the social and institutional conditions of transport automation in Poland and provide a more robust analytical basis for future mobility policy and implementation strategies. Full article

Secret sharing schemes distribute a secret among participants so that only authorised subsets can reconstruct it. In this paper, we focus on space-efficient secret sharing and show that matrix normal forms can significantly reduce share sizes while achieving computational security properties. Our scheme is implemented within an online secret sharing architecture, where authenticated public data P is maintained and shares of private data Q are issued over a secure channel. We study an existing probabilistic matrix-based approach to share size reduction and prove that the expected number of iterations of the underlying cyclic vector algorithm is small, yielding an expected polynomial runtime. We then design a novel deterministic method based on the Frobenius canonical normal form, avoiding reliance on cyclic vector techniques, and derive its runtime complexity. This yields a space-efficient secret sharing scheme that is computationally secure under a suitably defined adversary model. We have implemented our algorithm in the computer algebra system Maple as an Open Source project and provide an evaluation of its performance. Our results demonstrate that matrix normal forms can provide a suitable mathematical framework for secure and practical secret sharing. Full article

As essential components of the natural environment, urban green and blue spaces (UGBSs) hold significant potential to enhance public health and wellbeing. However, existing research is limited in understanding the spatiotemporal heterogeneity and nonlinear relationships characterizing how built environment (BE) features of UGBSs influence public happiness. This study takes Nanjing, China as a case study. It integrates multisource data (e.g., social media text, remote-sensing imagery, POI data, land use, etc.) and employs machine learning techniques (including sentiment analysis and random forest), to investigate the nonlinear effects and spatiotemporal dynamics of UGBSs’ BE on public happiness. The results show that nonlinear relationships (e.g., S-shaped and inverted U-shaped) commonly exist between UGBSs’ BE indicators and happiness. The influence of UGBSs’ BE on happiness demonstrates significant spatiotemporal dynamics. Diversity and destination accessibility were dominant factors from 2021 to 2023, whereas the importance of the design and density dimensions increased substantially after 2023. The influence varied across UGBS types; except for the diversity dimension, the BE’s density, design, and destination accessibility were significantly associated with happiness across all UGBS types. The study offers empirical evidence to inform planning and management of UGBS infrastructure, with the aim to maximize public health benefits and foster healthy cities. Full article

Urban fires are highly destructive with high casualty rates, often causing significant casualties and property losses. The obstruction of the Community Emergency Corridor System is a critical factor exacerbating fire casualties, directly related to residents’ life safety and public security governance effectiveness. Currently, community emergency corridors face severe systemic bottlenecks in the coordinated development of triadic space (physical, social, and information spaces), and the lag of information space has become a fatal shortcoming restricting emergency response efficiency, highlighting the urgent need for a comprehensive evaluation framework. However, existing studies mostly focus on a single spatial dimension, lacking a systematic framework for the coordinated patency of triadic space. Based on this, this study adopts the triadic space perspective, takes 77 typical communities in China as research objects, and uses the Entropy Weighted TOPSIS method to construct an evaluation index system for the accessibility of the Community Emergency Corridor System and systematically measure its level. The results show that the patency of triadic space is unbalanced overall; social space outperforms physical and information spaces (with the latter being the lowest), reflecting deficiencies in emergency information release and acquisition. Regionally, accessibility in Northeast China is significantly higher than in other regions (Northeast > West > Central > East), and eastern China has the lowest scores in physical and information spaces due to high urbanization, dense buildings, and land scarcity. Corresponding countermeasures are proposed to address regional disparities. The triadic space evaluation framework and methodological path provide a replicable analytical tool for urban fire-oriented community emergency management and references for fire resilience governance in other countries or high-density communities. Full article

Raphiel Eristavi’s [Kakheti, 1824–Telavi, 1901] archival legacy constitutes a unique, underexplored corpus for examining the sociopolitical and cultural processes shaping 19th-century Georgia’s national identity. These archival documents contain his writings as a publicist, his ethnographic and geographical notes, literary texts, and private correspondence, shedding light on the intellectual and cultural dynamics of the period, particularly about reintegrating Muslim Georgian communities into the national space. Eristavi’s contributions to periodicals reflect his publicist activities, illustrating the press’s formative role in shaping public opinion, consolidating cultural identity, and fostering national awareness. His writings articulate his conviction that language, culture, tradition, and shared historical memory function as the primary instruments for reconnecting estranged territories with Georgia’s historical continuum. This entry analyzes Eristavi’s role as an intellectual and cultural mediator in integrating Muslim Georgian populations (i.e., Tao-Klarjeti and Samtskhe) into broader national frameworks, particularly in his writings on the Crimean War and Russo-Turkish War of 1877–1878, as well as how he engaged with questions about ethnic identity, territorial cohesion, and cultural memory. By situating Eristavi’s archive within the wider efforts of the Georgian intelligentsia, this study seeks to highlight his contribution to preserving language, promoting education, and reaffirming historical unity as essential components of national and state consciousness. Full article

As university campuses increasingly open to the public and become integrated into urban tourism systems, campus spaces are evolving into institutionalized multifunctional environments shared by students and visitors. However, existing tourism conflict research has mainly focused on traditional resident–tourist relations, with limited attention to institutionalized educational spaces. Taking Hunan University in the Yuelu Mountain Scenic Area, Changsha, as a case study, this study develops a perceived conflict–place attachment–overall impact evaluation framework and tests it using data from 438 student questionnaires and structural equation modeling. The results show that perceived conflict significantly weakens place attachment and reduces students’ positive evaluations of campus tourism impacts, with place attachment serving as a significant mediator. More importantly, the effects are not uniform: only economic and social conflict significantly reduce place attachment, campus belonging amplifies rather than buffers the negative effect of perceived conflict, and study duration does not significantly moderate this relationship. In addition, students whose daily study or living spaces are closer to tourism core areas report stronger perceived conflict and greater vulnerability to its consequences. By showing that tourism conflict in campus spaces is selective and context-dependent, this study extends tourism conflict theory beyond conventional community settings and offers practical implications for conflict-sensitive, spatially differentiated, and student-oriented campus tourism governance. Full article

China’s rural public open spaces (POS) are largely governed as common-pool resources through self-organized collective arrangements, often regarded as a viable pathway to sustainable commons management. Yet, in practice, these systems remain prone to overuse and under-maintenance, reflecting collective action failures associated with the tragedy of the commons. The governance of rural POS therefore constitutes a complex social–ecological problem shaped by the interplay of institutional rules, biophysical conditions, and user–stakeholder interactions. Taking Taigu District in Shanxi Province—characterized by heterogeneous social–ecological contexts and collective action dilemmas—as the empirical case, this study develops a meso-level baseline model to identify the key conditions (design principles) for sustainable rural POS governance. Adopting an expert-based epistemological approach, 24 specialists in rural governance (scholars, planners, and local administrators) were engaged. Grounded in commons and collective action theories within the Social–Ecological Systems (SES) framework and informed by Transaction Cost Economics (TCE), the study operationalizes a Delphic Hierarchy Process (DHP), combining three rounds of Delphi to establish consensus on governance conditions with the Analytic Hierarchy Process (AHP) to derive their relative weights. The model specifies 14 governance conditions across four interrelated dimensions: ecological (e.g., clearly defined resource boundaries and congruence between resource characteristics and user needs), institutional (e.g., simple and enforceable rules, accessible conflict-resolution mechanisms, accountable monitoring, and calibrated external support), social (e.g., social capital, leadership capacity, clearly defined user boundaries, and group interdependence), and interactional (e.g., resource dependence, equity in benefit distribution, and supply–demand alignment). It further clarifies their relative importance and systemic interdependencies. By operationalizing commons design principles within a meso-level analytical framework, the study advances their empirical application in rural planning and offers five targeted managerial implications to strengthen institutional robustness and the long-term sustainability of self-governed rural POS. Full article