Search Results (3,308)

In Seoul, neighborhood-scale commercial districts, known as Golmok commercial districts, are small-scale retail areas focused on local daily life but also play a significant role in the city’s economy. Existing classification strategies for supporting Seoul’s Golmok commercial districts primarily rely on static, administrative data, failing to sufficiently capture actual citizen usage patterns. This deficiency limits the effectiveness of revitalization efforts. This study employs a two-timescale analysis of de facto population data to build a more dynamic typology of Seoul’s Golmok commercial districts. An unsupervised machine learning approach, specifically time-series K-means clustering, was applied to both weekly (short-term) and multi-year (long-term) time series data. This enabled us to classify 1090 districts into 16 distinct types. This more granular typology reveals significant heterogeneity masked by the Seoul Metropolitan Government’s current system, which groups these districts into only four broad categories. Our results show that while a minority of districts maintain stable activity, many exhibit patterns of long-term decline or significant fluctuation, underscoring the diverse and dynamic nature of these areas. The short-term analysis also captures temporal variations in population activity. The proposed typology may offer a foundation for near real-time monitoring and more proactive policy interventions to support urban economic sustainability. Full article

As generative artificial intelligence (GenAI) tools undergo rapid iteration, the complexity and heterogeneity of teachers’ technology practices in authentic instructional contexts warrant closer empirical scrutiny. Focusing on a public middle school designated as an AI demonstration site in eastern China, this study drew on 17 months of fieldwork that combined critical incident interviews, participant observation, and artifact collection. Systematic thematic analysis yielded four distinct practice types: Implicit Empowerment, Ritualized Enhancement, Transformative Exploration, and Prudent Distancing. The differentiation among these types was traced to the interplay of four dimensions: professional agency, technological cognition, organizational governance, and field culture. Specifically, the professional agency dimension encompasses trade-offs in labor intensity, preservation of professional authority, and continuity of pedagogical habitus; the technological cognition dimension manifests as misalignment of technological empowerment, concerns over output hallucinations, and the narrowing of dialogic value; the organizational governance dimension includes evaluation system orientation, excessive resource consolidation, and a lack of tolerance for innovation failure; and the field culture dimension involves peer practice modeling, team cultural atmosphere, and stakeholder demands. Together, these factors help explain the diversity of teachers’ technology adoption behaviors and offer an empirically grounded framework for understanding the micro-level processes of AI integration into classroom teaching. Full article

What is the influence of different multilevel governance architectures on the provision of infrastructural powers? Multilevel governance corresponds [i] to the vertical distribution of decisions and responsibilities between territorial spheres of government, or [ii] polycentric relationships among different agents. In this work, the focus is on vertical [Type I], and polycentric models [Type II] are outside the scope of this study. Only the vertical subnational perspective will be considered, which can be associated with federalism, decentralization in administrative, fiscal and political dimensions or the scale of authority exercised by subnational governments. The result is the construction of a scale and typology of multilevel governance in the region, considering the influence on government “infrastructural powers” and, subsequently, indicators of and effective territorial penetration. Full article

Lightweight structures such as Schwedler domes offer high strength-to-weight ratios for large-span applications; however, their design typically involves time-consuming iterative processes. This study proposes an integrated parametric workflow combining geometry generation, structural analysis, and automated load application to improve both design efficiency and structural performance. The methodology is based on Python scripting within Grasshopper, enabling parametric control of dome geometry and direct interoperability with Autodesk Robot Structural Analysis Professional. Three open-apex Schwedler dome configurations were analyzed as a focused demonstration of the workflow, differing in cross-sectional typology and structural layout. The results show that the use of closed sections reduces structural mass by up to 31%, while hybrid configurations achieve significantly improved member utilization, reaching 0.87 for ribs and 0.63 for rings. Importantly, the parametric workflow enabled the rapid generation and evaluation of multiple design variants, significantly reducing modeling time and eliminating inconsistencies between geometric and analytical models. The study demonstrates that parametric modeling provides an effective framework for designing efficient dome structures, enabling both material optimization and accelerated design processes. The same parametric source is also suitable for extension into BIM and fabrication environments, as well as into life-cycle assessment, which are identified as planned continuations of this research. Full article

The scope of actual pro-environmental initiatives, programs, interventions, and campaigns is limited. Therefore, spillover effects from these activities to other domains of economy, the private sphere, and society are crucial to achieve a transformation of society towards sustainability. Starting from the known literature and using Google Scholar as a platform for searching additional studies, this explorative, traditional narrative review analyses behavioural spillover effects, where either one behaviour influences the likelihood of another behaviour, or an intervention shows an impact on an environmentally significant behaviour, which it did not primarily address. In the scientific literature, spillover is classified by direction (environmentally positive versus negative), involved behaviours (similar or cross-behavioural), timing (short or long term), context (e.g., work to private life), and social scope (personal, interpersonal, intra- and inter-organisational, intergroup, or international). Positive spillover can result from cognitive dissonance reduction, consistent self-perception, pro-environmental values, norms, self-identity, action-based learning, and habit formation. Negative spillover emerges through rebound effects, moral licensing, and psychological reactance. Stronger spillover is observed between similar behaviours, while cross-domain spillover is generally weaker. According to previous research, a facilitated participatory approach with strong pro-environmental orientation appears recommendable for practitioners to foster the value change required for effective and sustained positive spillover. Full article

The detection and monitoring of asbestos–cement roofing remain a critical public health and environmental challenge, especially in urban and suburban areas where asbestos-containing materials are still widespread due to their extensive use in the 20th century. Although hyperspectral and high-resolution multispectral remote sensing have proven effective for mapping asbestos–cement roofs, many existing approaches rely on proprietary software, limiting transparency, reproducibility, and large-scale adoption. This study presents a fully reproducible, cost-free Python-based workflow for the detection and temporal monitoring of asbestos–cement roofing using high-resolution multispectral WorldView-3 imagery. The workflow integrates atmospheric correction (using the Py6S radiative transfer model), spatial preprocessing, supervised pixel-based classification, postprocessing, and building-level aggregation within an open framework. A Maximum Likelihood Classifier is applied to VNIR and SWIR data using empirically defined roof typologies to enhance class separability. Pixel-level results are aggregated to the building scale through adaptive thresholding enabling the translation of spectral classifications into meaningful building-level information. Tested over the city of Mantua (Italy), the approach achieved reliable classification performance and enabled multi-temporal comparison to identify changes potentially due to roof remediation. Evaluation metrics (precision, recall, and F1-score) highlight the importance of carefully choosing the building-level threshold. By relying exclusively on open-source tools, the workflow enhances transparency, reproducibility, and scalability for long-term monitoring. Full article

Small settlements in Serbia are confronted with long-term processes of depopulation, ageing, and migration, characterised by pronounced spatial and structural heterogeneity. This raises questions about the effectiveness of uniform development policies and underscores the need for a differentiated, place-based approach. The aim of this paper is to identify the demographic heterogeneity of small settlements (with fewer than 100 inhabitants) and to analyse its implications for decentralised territorial development. The research is based on the analysis of 1302 settlements in Serbia, using 26 demographic, socio-economic, and geographical indicators. The methodological framework is based on principal component analysis and cluster analysis, complemented by nonparametric tests and logistic regression. The results indicate pronounced population ageing, low labour potential, and a clear spatial polarisation between accessible and peripheral settlements. Four clearly differentiated types of small settlements are identified. It is concluded that demographic heterogeneity represents a key determinant of development capacity, indicating the need for territorially sensitive and differentiated development policies. In this context, decentralisation and tailored development models may contribute to the revitalisation and long-term sustainability of rural areas. Full article

Rail-trail corridors in the agricultural Midwest exhibit layered ecological conditions influenced by the material legacy of railroad infrastructure and contemporary land use pressures. This study uses a mixed-methods approach integrating GIS analysis, field documentation, and open-response surveys with trail managers to characterize the structural and ecological heterogeneity of two rail-trails within the Corn Belt. Spatial methods quantify variation in right of way width, land cover context, connectivity, and patterns of fragmentation, revealing that corridors shift in response to agricultural edges, successional woodlands, riparian zones, and urban conditions. Field visits and on-site sketching provide fine-grained insight into vegetative structure, topography, and edge dynamics, while the thematic analysis of survey responses highlights how management regimes, resource limitations, invasive species, and adjacent land uses shape ecological patterns along the trail. Together, these methods support the development of a typology of rail-trails based on their vegetative, hydrological, and disturbance patterns. We argue that design and management should work with the nuance of the corridors, noting the potential for landscape experimentation. Novel design approaches can support the performance of rail-trails as ecological infrastructure while enabling meaningful human–environment interactions within the right of way. Full article

Urban railway corridors—including abandoned, redesigned, and in-use lines—can support biodiversity and ecological connectivity in fragmented cities, yet their ecological dynamics and roles in Nature-based Solutions (NbS) remain poorly understood. Addressing this requires a context-sensitive approach that differentiates corridor types and compares their ecological functions. This study compares vegetation dynamics along railway corridors in two cities with contrasting socio-ecological contexts—Perth (Western Australia) and Beijing (China)—using a typology-based comparative approach. The results show that: (1) vegetation dynamics differ fundamentally between the two cities, with Perth characterized by vertically structured vegetation dominated by native tree layers and non-native disturbance-tolerant annual groundcover, while Beijing supports more continuous vegetation with widespread natural regeneration of native species; and (2) these differences correspond to distinct suggested NbS strategies. For Perth, NbS should combine phenology-aware management (wet versus dry seasons) with disturbance-based zoning and staged native planting strategies. In contrast, Beijing corridors are characterized by more uniform disturbance patterns but differentiated corridor typologies, indicating NbS structured around corridor-type management with a stronger emphasis on the support of native groundcover establishment and allowing for self-sustaining regeneration. These findings highlight how different contexts shape vegetation dynamics and provide comparative ecological insights for developing context-specific NbS for urban railway corridors. Full article

This article examines how the discourse of “for your own good” functions as a moral framework through which parental violence is reinterpreted as care in Sinophone family cinema. Focusing on family-centered films as a key site of representation, we analyze how reconciliation is constructed not merely as a narrative resolution but as an ethical expectation. Drawing on theoretical perspectives from Michel Foucault and Louis Althusser, we develop the concept of “moralized parental violence” to describe how authority, discipline, and emotional control are legitimized through moral discourse. Through a typological analysis, identify three recurring models of reconciliation: deathbed reconciliation, retrospective understanding, and silent reconciliation. The study further explores works that resist reconciliation, arguing that such narratives suspend ethical closure and challenge normative expectations of forgiveness. By examining narrative structure, visual emphasis, and affective strategies, we demonstrate how cultural texts guide audience responses and shape moral interpretation. Rather than rejecting family values, this study reconsiders how ethics, power, and care are intertwined in cultural narratives and how the refusal of reconciliation opens a critical space for rethinking the limits of moral obligation. Full article

Vanilla (Vanilla planifolia Jacks. ex Andrews) is a tropical orchid of high economic value, with an annual production of 8000 to 10,000 t and a market exceeding 800 million USD in over 40 countries. In vitro propagation has strengthened the innovation, production, and conservation of this species. Bibliometrics, as a quantitative approach, systematically examines the patterns, dynamics, and evolutionary trends of scientific production. A systematic search was conducted in Scopus and Web of Science until December 2025, using the terms “vanilla” and “micropropagation”. A total of 53 documents were identified in Scopus (1997–2025) and 39 in Web of Science (2000–2025). The evaluated indicators included: year of publication, country of origin, language, areas, main categories, document typology, authorship, and keyword distribution. VOSviewer was used for keyword analysis to identify author collaboration networks and emerging trends. The years with the most information were 2024 and 2025, with Mexico and India standing out prominently. The main thematic areas were Agricultural and Biological Sciences, and the role of researcher Ramírez-Mosqueda was highlighted. The keywords with the highest correlation and impact were bioreactors, vanillin, and cryopreservation. This bibliometric study provides a comprehensive perspective on scientific production related to vanilla micropropagation. The results highlight the multidisciplinary nature of biotechnology applied to this crop, integrating contributions from various areas of knowledge for the benefit of the main actors in the value chain. Full article

This study presents a comprehensive and systematic integrative review of Neighborhood-Level Energy Hubs (NLEHs) as pivotal enablers of sustainable and resilient urban energy systems. In response to accelerating climate pressures, rapid urbanization, and the decentralization of energy production, NLEHs are conceptualized as multi-carrier platforms that enable coordinated energy generation, storage, conversion, and exchange at the neighborhood scale. Utilizing a PRISMA-informed methodology to synthesize 125 core studies, the review systematically evaluates recent advances across five interconnected dimensions: conceptual foundations, system typologies, energy flow architectures, urban integration, and optimization paradigms. Unlike conventional reviews, this study explicitly bridges the critical gap between techno-economic optimization and socio-environmental priorities. A key novelty is the proposed mathematical integration of energy justice and Social Life Cycle Assessment (S-LCA) directly into optimization algorithms (e.g., MILP and MPC) as dynamic constraints and penalty terms. Particular emphasis is placed on participatory governance models, lifecycle sustainability metrics, and digitalization tools such as AI-driven energy management systems and urban digital twins. The analysis further reveals critical research gaps, highlighting a stark geographic dichotomy between high-tech, market-driven NLEHs in the Global North and resilience-oriented hybrid microgrids in the Global South, alongside the lack of adaptive regulatory frameworks. By proposing a unified Cyber–Physical–Social perspective, this study provides actionable insights for planners, policymakers, and researchers to support the development of scalable, inclusive, and context-sensitive NLEH implementations. Ultimately, the paper contributes to redefining neighborhood-scale energy systems as not only efficient and low-carbon infrastructures, but also as socially equitable, globally scalable, and institutionally adaptive components of future smart cities. Full article

Global urban development has fully entered the stage of stock renewal, and the synergy between public health and historic heritage conservation has become a core issue of urban sustainable development in the post-pandemic era. As special spatial units carrying urban cultural memories, historic districts generally face problems such as chaotic traffic functions, a lack of slow traffic spaces, and insufficient public health support. Existing studies lack a public health-oriented special evaluation system and a sustainable renewal path adapted to their characteristics. This paper systematically sorts out eight core impact paths of street built environment elements on public health and constructs a healthy street evaluation system for historic districts, including six dimensions (transportation facilities, green squares, ancillary facilities, street-front commerce, urban furniture, and street network) and 30 core elements combined with the spatial and cultural characteristics of historic districts. Taking five typical streets in the Liuhe Area of Hankou Historic District as an empirical case, a comprehensive evaluation is carried out using a combination of quantitative surveys, questionnaire surveys, and spatial analyses. The results show that the overall health performance of street space in the study area is low, with extremely unbalanced development across dimensions. The core shortcomings are concentrated in incomplete slow traffic systems, lack of public spaces, prominent parking chaos, and fragmented historic styles, and the health problems of streets with different functional types show significant typological differentiation characteristics. Based on this, this paper proposes five systematic renewal strategies, transportation system optimization, public space improvement, landscape system perfection, historic style activation, and long-term mechanism construction, for achieving the synergistic goals of historic culture conservation, public health promotion, and urban sustainable development. This study not only enriches the theoretical system of research on healthy spaces in historic districts but also provides a referable evaluation framework and practical approach for modern historic districts in China and other similar historic districts with comparable spatial textures and functional characteristics. Full article

Multilingual learning is key in natural language processing, but is challenged by the transfer–interference trade-off, where positive transfer benefits certain languages, while negative interference affects others. Prior methods, including linguistic-based and embedding-based language clustering, have attempted to address this; yet, they remain constrained by their static design and lack of task-specific feedback. In this study, we propose a novel computational strategy inspired by molecular design that constructs molecules with targeted properties. Languages are modeled as nodes in an undirected graph, with edges representing the transfer strength. This language molecule is optimized via Reinforcement Learning to adjust edge connections and weights to enhance positive transfer and minimize interference, where graph clustering is applied, and clusters are then evaluated on the Named Entity Recognition and POS tagging tasks using 25 languages from the WikiANN dataset and 12 typologically diverse languages from the UDPOS dataset. Compared to linguistic and embedding-based language clustering baselines, our method yields substantial improvements, especially for low-resource languages, with some showing over 35% increase in F1 score, while high-resource languages benefit moderately, confirming reduced transfer–interference trade-off. Our atom–language model offers a novel path for multilingual learning, inspired by molecular principles from physical sciences. Full article

Socio-environmental conflicts in mining regions are often examined through political, economic, or social lenses, while the role of land-system transformation remains less integrated into quantitative analysis. This study examines the co-evolution of socio-environmental conflict and territorial change in Las Bambas (Apurímac, Peru) as a socio-territorial process. Annual conflict records from the Peruvian Ombudsman’s Office (2007–2024) were combined with annual land-cover data from MapBiomas. Yearly conflict influence zones were reconstructed from reported affected communities and geographic features using buffered spatial entities and concave hull polygons. Clustering methods (K-medoids, DBSCAN, and agglomerative hierarchical clustering) and FP-Growth association rule mining were applied to 23 unique conflicts consolidated from the original records and encoded with 10 root causes. The most intense conflict phases were accompanied by measurable landscape transformations, including the emergence of mining-related land cover from 2012 onward, sustained loss of high-Andean natural vegetation, expansion of agricultural mosaics, urban growth along the Apurímac–Cusco corridor, and hydrological alterations in wetlands and headwaters. Three conflict typologies were identified, with unfulfilled company commitments emerging as the most recurrent co-occurring grievance. The dynamic polygon approach offers a replicable framework for linking conflict records with land-system change in extractive regions. Full article