Search Results (3,318)

This study investigates how Chinese learners of English express manners of motion, examining systematic features, cognitive motivations, and compensatory strategies. While Talmy’s motion events typology and Levin’s verb classification system provide important foundations, both have limitations in capturing the internal semantic granularity of manner verbs and the complexity of learner acquisition. To address this, we construct a 10-level verb typology establishing a “semantic granularity” continuum from concrete to abstract, physical to metaphorical, and lexical to grammatical. Using experimental data (N = 600) and corpus comparisons (COCA vs. learner corpus), we analyze Chinese learners’ manner expression patterns. Results reveal the following: (1) Chinese learners prioritize Path over Manner, overusing lower-level verbs (go, walk, run) while underusing higher-level and fine-grained manner verbs (stroll, scramble), which are preferred by native speakers. (2) Learners favor semi-tight or loose syntactic structures and show a preference for describing Manner precisely by adding other modifiers such as adverbials, prepositions, complements, or subordinate clauses. When it comes to precisely describing specific manners of motion, Chinese learners of English tend to use four strategies—analytic manner externalization, path salience, image-schematic transfer, and semantic simplification—whereas native English speakers typically rely on single verbs with high semantic density. These findings suggest learners’ expression of manner involves both L1 syntactic transfer and target language conceptual adaptation. The 10-level classification continuum advances the theoretical understanding of motion event lexicalization patterns, provides new perspectives for conceptual transfer research, and offer pedagogical implications for Chinese English learners’ accuracy of their expression of manner. Full article

Urban emptiness is a recurring spatial condition across contemporary cities, resulting from long-term planning decisions, functional transformations, and shifting socio-economic dynamics. Urban voids are often interpreted as signs of failure or neglect; however, they also represent flexible and open-ended spaces embedded within everyday urban environments. This study develops and tests the Adaptive Void Assessment Framework (AVAF), a five-dimensional typological instrument applied to n = 33 urban voids identified through a systematic grid-based field survey (100 × 100 m resolution) in the central urban zone of Nitra, Slovakia (March 2025–January 2026). The framework evaluates sites across nine indicators spanning openness, social appropriation, ecological succession, temporal persistence, and institutional flexibility, yielding composite Adaptivity Index scores and four dominant adaptive regimes. The findings demonstrate that 34% of identified voids function in a socially active regime while 14% exhibit ecological dominance, with a moderate positive correlation identified between temporal persistence and adaptive capacity (r = 0.46, p < 0.05). This challenges conventional deficit-based classifications and reframes urban voids as active components of the urban metabolism capable of enhancing ecological connectivity and spatial flexibility within post-industrial urban landscapes. This reframes urban voids from residual outcomes of urbanization to spaces with potential for green integration within sustainable contemporary cities. Full article

This study examined the critical sustainability challenge of regional demographic decline in South Korea by analyzing how young people’s mobility decisions are intricately influenced by structurally and socially constructed meaning systems. Countering strictly economic deterministic views, this research posited that youth out-migration is a complex socio-cognitive process mediated by social representations of place—collectively constructed and circulated meanings attached to regions. Applying a secondary analysis of Q-sort data from 24 undergraduate students at a regional national university, the study integrated Q methodology with Social Representation Theory to systematically identify youth typologies regarding regional identity, territorial stigma, and local extinction. Participants sorted 44 statements encompassing place attachment, local consumption, cultural experiences, and policy effectiveness. Rigorous factor analysis revealed four distinct perception typologies: identity-based strategic mobility, conditional leaving based on internalized success norms, re-anchoring toward alternative lifestyles, and skeptical leaving rooted in profound institutional distrust. The findings empirically demonstrated that identical structural constraints can produce highly divergent mobility trajectories—ranging from active retention to complete resignation—depending entirely on the region’s socio-cognitive representation. This study demonstrates that local extinction is not merely a demographic condition, but a socially constructed framework of meaning and an object of social representation that shapes youth perception typologies and mobility judgments. Accordingly, moving beyond conventional technical interventions, meaning governance, and strategic communication are needed to help reimagine regional futures. Full article

UVA exposure elicits immediate and persistent pigment darkening of the skin, which is thought to result from the oxidation and polymerization of existing melanin and/or precursors. Melanocytes produce eumelanin and pheomelanin. Eumelanin consists of 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA), while pheomelanin consists of benzothiazine and benzothiazole units. Melanins can be analyzed by quantifying specific degradation products using HPLC. Specifically, eumelanin can be analyzed as pyrrole-2,3,5-tricarboxylic acid (PTCA) and pyrrole-2,3-dicarboxylic acid (PDCA), specific degradation products of DHICA and DHI, respectively. Benzothiazole pheomelanin can be analyzed as thiazole-2,4,5-tricarboxylic acid (TTCA), whereas benzothiazine pheomelanin is analyzed as 4-amino-3-hydroxyphenylalanine (4-AHP) and 3-amino-4-hydroxyphenylalanine (3-AHP). Upon UVA exposure, melanins undergo structural modifications. Eumelanin undergoes oxidative cleavage to free pyrrole-2,3,5-tricarboxylic acid (Free PTCA) and undergoes cross-linking to form pyrrole-2,3,4,5-tetracarboxylic acid (PTeCA). UVA exposure of pheomelanin induces oxidative conversion from the benzothiazine to the benzothiazole. Nevertheless, these structural modifications have never been previously characterized in human skin. In this study, we exposed ex vivo skin to increasing UVA1 doses (60, 90 and 120 J/cm²; n = 6 in triplicate) and characterized the induced pigment darkening before, immediately, and 2 h after exposure through colorimetry, HPLC and spectrophotometry. The results showed changes in the CIELAB colorimetric parameters, namely a decrease in Luminance L*, the yellow-blue component b* and the Individual Typology Angle (ITA) in UVA1-exposed samples, indicative of skin darkening. In parallel, UVA1 exposure induced significant modifications of the levels of absorbance at 500 nm (A500) and melanin markers PTCA, PTeCA, PDCA, TTCA, and 4-AHP, as well as in the ratios of various markers, such as PTeCA/PTCA, Free/Total PTCA, and TTCA/4-AHP, indicative of photooxidation/degradation of melanins. Our study provides the first evidence of UVA1-induced modifications of melanins associated with pigment darkening occurring in human skin. Full article

Shared pilot-scale bases enhance organizational efficiency and improve the success rate of transformation by leveraging spatial proximity among innovation actors, serving as a critical bridge between laboratory R&D and industrialization in biomedicine. Unlike the dominant models in mature markets such as Europe and the United States, which rely on in-house R&D by leading firms or marketized outsourcing, China has developed a government-guided, regionally adapted model of shared pilot-scale bases. This study refines the classification of innovation actors within innovation ecosystem theory and aims to reveal the spatial agglomeration patterns of these actors within shared pilot-based ecosystems and identify the dominant forces within them. Our analysis reveals that: (1) Shared pilot-scale bases anchor themselves in regions of high innovation concentration, representing government-guided agglomerations of diverse innovation actors. (2) Influenced by variations in local economic foundations, innovation resources, and policies, the innovation networks of shared pilot bases in different cities exhibit both functional and morphological similarities and differences. (3) Strategic placement around leading enterprises can rapidly steer regional innovation gradients and foster industrial aggregation through pilot-scale activities. This study can provide a theoretical basis for spatial policymaking in China’s biomedical industry and offer a typological reference for the layout of pilot-scale platforms within heterogeneous innovation ecosystems globally. Full article

[Problem] Converting viral tourism popularity into long-term destination sustainability is a central governance challenge in the digital era. [Aim] This study aims to explicitly measure how emotional value mediates the transition from ephemeral online traffic to durable offline place attachment. [Methodology] Adopting a descriptive mixed-methods approach, data were collected through semi-structured interviews with 16 purposively selected participants (including tourists and locals) recruited via on-site intercepts and online snowball sampling. The inclusion criterion required active engagement with Harbin’s digital tourism discourse. Qualitative transcripts were coded using the NVivo 12 software and subsequently converted into panel data. Grey Panel Relational Clustering was then utilized to geometrically track tourist emotional trajectories. [Results] The analysis identified three structural tourist typologies—the Full-Link Empathy Type, Pragmatic Verification Type, and Traffic-Driven Co-conspirator Type—and revealed three corresponding synergistic paths driving online–offline integration: Virtual–Real Isomorphism, Complementarity, and Symbiosis. [Conclusions] The findings demonstrate that sustainable destination resilience depends fundamentally on the qualitative composition of emotional engagement across different tourist types, rather than sheer visitor volume. [Implications] This study contributes an empirically grounded, emotional value-driven framework to sustainable tourism theory, offering differentiated governance strategies for destinations navigating the volatility of platform-driven attention economies. Full article

In rapidly growing Saudi cities like Mecca and Jeddah, population diversity and expansion have increased the need to improve residents’ quality of life. As part of Saudi Vision 2030, both cities have launched major redevelopment initiatives that replace old neighbourhoods and relocate residents to newly developed housing. This study evaluates residents’ perceptions of indoor environmental quality across different housing environments, reflecting changes in residential context, building typology, and interior conditions. The study adopted a quantitative approach to gather data from 80 participants who were impacted by demolition projects and moved to newer urban neighbourhoods; the analysis used descriptive statistics and one-way ANOVA to analyse the obtained results. The results revealed that for most of the environmental factors, the ANOVA test showed no significant differences between premodern and modern houses, yet the descriptive statistics showed that modern houses were perceived slightly more positively than older houses. Furthermore, the results showed that, in both premodern and modern houses, thermal comfort was identified as one of the most important parameters, followed by indoor air quality and lighting, while acoustics ranked as the least important. Full article

Pixel-based Active Fire Spot (AFS) statistics alone are insufficient for characterizing forest fire activity in fragmented mountainous agroforestry regions because cross-sensor differences, geometric distortion, and discontinuous satellite overpasses can fragment physically continuous fires into multiple detections. To address this problem, we developed a reconstruction framework that combines optical–thermal cross-validation with multi-level spatio-temporal clustering to identify physically independent fires in Yunnan Province, China. Starting from 497,834 raw AFSs detected during 2012–2024, the framework removed unusable detections, aggregated the retained AFSs, and identified 41,215 validated Forest Fire Events (FFEs). The reconstructed database revealed clear temporal, spatial, and topographic heterogeneity. Fire activity was strongly concentrated in the late dry season, with 32.8% of all FFEs occurring during the main spring fire window. Daytime FFEs accounted for 82.8% of all FFEs, but nocturnal activity increased substantially in some years, reaching 20.7% in 2023. Persistence showed a long-tailed structure under both observation frameworks, although the operational thresholds differed between 2012–2017 (105 min) and 2018–2024 (75 min). Regionally, Southeast and Southwest Yunnan concentrated most reconstructed FFEs, whereas Northwest and Central Yunnan showed much higher CFRP per event. Topographically, fire energy was concentrated mainly on gentle-to-moderate slopes, and nighttime fires were centered 215.03 m higher than daytime fires. The typology analysis further showed that event frequency and physical fire impact were not distributed proportionally across fire types. Random Forest validation indicated high reproducibility of the rule-based typology system (Macro-F1 = 0.9935; Weighted-F1 = 0.9964), whereas the first two principal components explained 42.65% of the total variance. These results show that event-level reconstruction provides a stronger basis than AFS counts alone for understanding fire heterogeneity and supporting zone-specific fire management in Yunnan. Full article

Background/Objectives: As artificial intelligence systems become increasingly embedded in everyday cognitive tasks, human–AI interaction is no longer limited to tool use but evolves into a dynamic process of mutual adaptation. While extensive research has examined algorithmic learning, far less attention has been given to how users progressively adapt to AI systems. This paper introduces the concept of algorithmic habituation, defined as the gradual accommodation of users to the regularities and predictive patterns of AI systems. The objective is to provide a neurocognitive and systems-based framework that explains this phenomenon. Methods: The study develops a conceptual and integrative framework grounded in classical theories of habituation, neuroplasticity, predictive processing, and systems theory. Building on these foundations, we propose a mechanistic model of human–AI co-adaptation, conceptualized as a recursive feedback loop involving repeated interaction, pattern recognition, expectation stabilization, and cognitive economy. In addition, a typology of algorithmic habituation is advanced, alongside proposed empirical pathways for future validation, including scale development, experimental paradigms, and longitudinal designs. Results: The proposed framework suggests that repeated interaction with AI systems leads to stabilization of cognitive expectations, reduced cognitive effort, and increased behavioral standardization. This process extends beyond perceptual habituation into higher-order domains, including decision-making, creativity, and moral judgment. The typology identifies four primary forms of algorithmic habituation: cognitive, decisional, creative, and moral. The model predicts both adaptive outcomes (efficiency, reduced cognitive load) and maladaptive consequences (reduced reflexivity, automation bias, and potential erosion of critical thinking). Conclusions: Algorithmic habituation represents a novel construct at the intersection of neuroscience, cognitive psychology, and human–AI interaction. By framing user adaptation as a form of neurocognitively grounded habituation within recursive systems, this paper contributes a new perspective to understanding AI integration in human cognition. The framework has implications for digital wellbeing, education, and AI ethics, and opens multiple avenues for empirical research. Full article

Urban canyons, integral components of the built environment, significantly influence microclimatic conditions and thermal comfort. This review investigates their combined effects with green infrastructure on thermal comfort, offering a comprehensive framework for supporting urban design and greening strategies. The review is based on a structured literature analysis of peer-reviewed studies retrieved from major scientific databases (Scopus and Web of Science), following defined selection and screening criteria. Urban canyon orientation determines solar exposure and its interaction with prevailing wind patterns, affecting ventilation and heat dissipation. The urban canyon aspect ratio influences shading and airflow regulation, while their sky view factor moderates radiative cooling and daylight availability. Urban greening—encompassing street trees, green roofs, and vertical green walls—complements urban geometry by reducing air temperatures, enhancing evapotranspiration, and modifying local wind dynamics. Tree shading can reduce the physiological equivalent temperature in urban canyons, mitigating extreme heat stress. Key vegetative parameters, such as leaf area index and canopy density, are critical for quantifying cooling contributions. Key findings underscore the role of higher aspect ratios in enhancing shading and ventilation while they emphasize the critical influence of street orientation and sky view factor on microclimatic regulation. Vegetation emerges as a vital component, with tree shading contributing substantially to cooling effects and reducing physiological equivalent temperature. The beneficial synergistic interaction between urban geometry and vegetation optimizes thermal comfort. Tailored strategies based on urban canyon typologies balance urban development with environmental sustainability. The proposed framework provides actionable strategies for designing resilient and thermally optimized urban spaces, promoting climate-adaptive urban planning by addressing the dual challenges of the urban heat island and thermal discomfort in cities. Full article

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