Search Results (345)

This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It applies a multi-nominal logit (MNL) model to examine factors influencing travel mode choices and utilizes structural equation modeling (SEM) to assess travel satisfaction—a composite metric derived from residents’ subjective evaluations of convenience, cost, time, and comfort. Findings indicate that private cars and public transportation are the primary travel modes. The MNL model reveals that age and destination accessibility significantly influence travel choices. SEM path analysis further shows that annual household income has a direct positive effect on satisfaction, while age exerts an indirect negative influence through mediating variables. Female satisfaction levels were significantly lower than those of males. Both road density and perceived infrastructure quality significantly enhanced satisfaction, while destination accessibility may exert a slight negative indirect effect by increasing travel expectations. The study theoretically enriches research on rural travel patterns and provides practical insights into rural transportation planning and infrastructure development. Full article

The present study investigated how visual characteristics of a fire influence extinguisher use. Safety guidance indicates that occupants should consider situational aspects when deciding whether to use an extinguisher, such as fire characteristics. The visual fire cues of intensity, growth rate, and smoke thickness were systematically manipulated to examine the impact on judgments to intervene with an extinguisher. Participants (N = 135) viewed simulated fire scenes as part of an experiment and judged whether they could safely attempt to use an extinguisher. The results indicated that the participants were significantly less likely to attempt extinguisher use with greater fire intensity and thicker smoke. In contrast, variations in fire growth rate did not significantly affect participant decisions. These findings indicate that perceived fire intensity and smoke density are strong factors in extinguisher use decisions, while growth rate may not meaningfully influence occupant behavior. Understanding these perceptual factors can inform fire safety education and improve guidance on when extinguisher use is appropriate, potentially enhancing residential fire response outcomes. Full article

Against the backdrop of global population aging, the impact of urban built environments on the physical and mental health of older adults is receiving increasing attention. As the world’s largest developing nation, China, is simultaneously undergoing rapid urbanization and significant demographic aging. This dual trend makes it particularly imperative to investigate the relationship between the built environment and senior health. This study employs a meta-analysis methodology to quantitatively evaluate the relationship between urban built environment characteristics and physical and mental rehabilitation among older adults. Empirical studies were systematically screened from the CNKI and Web of Science databases using weighted Z-scores. Methodological quality, sample size, and heterogeneity were assessed to ensure the robustness of the analysis. Thirteen environmental indicators were categorized into objective built environment attributes and perceived environmental attributes. Results indicate that land use diversity and green coverage significantly correlate positively with better physical health outcomes, while safety, road quality, and environmental aesthetics significantly correlate positively with mental health. In contrast, some indicators, such as intersection density and NDVI, did not show significant correlations. This study explores the synergistic and complex effects of objective and perceived environmental characteristics in Chinese cities on the physical and mental rehabilitation of older adults within the context of dual-trend superposition. The findings not only provide scientific evidence for future urban planning and renewal in China but also offer valuable references for addressing the tension between urbanization and the health of older adults in Asia and other developing regions. Full article

Inshore ship detection in synthetic aperture radar (SAR) imagery poses significant challenges due to the high density and diversity of ships. However, low inter-object backscatter contrast and blurred boundaries of docked ships often result in performance degradation for traditional object detection methods, especially under complex backgrounds and low signal-to-noise ratio (SNR) conditions. To address these issues, this paper proposes a novel detection framework, the Dynamic Weighted Joint Time–Frequency Feature Fusion DEtection TRansformer (DETR) Model (DWTF-DETR), specifically designed for SAR-based ship detection in inshore areas. The proposed model integrates a Dual-Domain Feature Fusion Module (DDFM) to extract and fuse features from both SAR images and their frequency-domain representations, enhancing sensitivity to both high- and low-frequency target features. Subsequently, a Dual-Path Attention Fusion Module (DPAFM) is introduced to dynamically weight and fuse shallow detail features with deep semantic representations. By leveraging an attention mechanism, the module adaptively adjusts the importance of different feature paths, thereby enhancing the model’s ability to perceive targets with ambiguous structural characteristics. Experiments conducted on a self-constructed inshore SAR ship detection dataset and the public HRSID dataset demonstrate that DWTF-DETR achieves superior performance compared to the baseline RT-DETR. Specifically, the proposed method improves mAP@50 by 1.60% and 0.72%, and F1-score by 0.58% and 1.40%, respectively. Moreover, comparative experiments show that the proposed approach outperforms several state-of-the-art SAR ship detection methods. The results confirm that DWTF-DETR is capable of achieving accurate and robust detection in diverse and complex maritime environments. Full article

Urban commemorative landscapes serve as vital components of a city’s cultural expression. Employing a two-dimensional “physical-perceptual” accessibility evaluation framework, this study conducted a systematic analysis of the spatial distribution characteristics and accessibility of 124 commemorative landscapes in Nanjing, and investigated the factors influencing their accessibility. The analysis revealed four key findings: (1) A pronounced “core-periphery” pattern was identified, characterized by high-density, evenly distributed clusters in central districts that contrast with sparse, scattered layouts in outer suburbs. (2) Weighting analysis via the entropy method indicated that perceived accessibility (53.96%) exerted a slightly greater influence on composite accessibility than spatial accessibility (46.04%). (3) Modern commemorative landscapes in the main urban areas exhibited strong correlations with road network density and high public perception, and their comprehensive accessibility is significantly better than that of the remote suburban areas. Significant disparities in accessibility were observed among different types of modern commemorative landscapes. The comprehensive accessibility of memorial facilities was found to be the highest, attributable to their balanced spatial distribution and the fact that most of them are distributed in the densely populated main urban areas. (4) Key factors influencing accessibility were identified as attraction carrying capacity, regional population density, and elevation. This study aims to provide a reference for the comprehensive quantitative evaluation of urban commemorative landscapes, thereby promoting the coordinated development of historical space preservation and cultural resource utilization. Full article

Background: Nicotinamide mononucleotide (NMN) has gained attention as an anti-aging compound due to its ability to replenish NAD⁺ levels, which typically decline with age and stress. While improvements in skin conditions have been reported, clinical studies on human hair remain lacking. In this study, we evaluated the effects of NMN supplementation on hair conditions in middle-aged women and explored its association with quality-of-life (QOL) factors such as fatigue. Methods: Torula yeast-fermented NMN was evaluated in this clinical trial. A single-arm, pre-post intervention study was conducted involving 15 healthy Japanese women aged between 40 and 50 years who orally consumed NMN for 12 weeks. Hair growth cycles and hair shaft diameters were assessed using TrichoScan (TrichoGrabV3B) analysis and scanning electron microscopy (SEM). Hair metabolites and hormone levels were also measured. Subjective indices, including fatigue and hair texture, were evaluated using a visual analog scale (VAS) questionnaire. Results: Following NMN supplementation, anagen hair elongation density (hairs/cm²) significantly increased from 55.9 to 87.7 (p = 0.03). Hair diameter (µm) also significantly increased from 75.3 to 78.8 (p < 0.01), with improvements in hair cuticle condition. Metabolomic analyses revealed significant changes in amino acids and energy metabolism-related compounds. No marked changes were observed in hair hormone concentrations. The VAS questionnaire indicated improvements in subjective hair characteristics such as elasticity, gloss, and volume, as well as reductions in fatigue and perceived hair loss, suggesting enhanced QOL. Conclusions: Oral supplementation with NMN may be a beneficial strategy for promoting hair growth and improvement in hair cuticle condition in middle-aged women, thus potentially enhancing overall hair care and quality of life. Full article

In high-density built environments, perceived density (PD)—shaped by physical, socio-cultural, and perceptual factors—often induces sensations of crowding, stress, and spatial oppression. Although green spaces are recognised for their stress-reducing effects, the influence of built-environment characteristics on public sentiment under stringent mobility restrictions remains inadequately explored. This study takes Chongqing, a representative mountainous metropolis in China, as a case to examine how natural and built environmental elements modulate emotional valence across varying PD levels. Using housing data (n = 4865) and geotagged Weibo posts (n = 120,319) collected during the 2022 lockdown, we constructed a PD-sensitive sentiment dictionary and applied Python’s Jieba package and natural language processing (NLP) techniques to analyse emotional scores related to PD. Spatial and bivariate autocorrelation analyses revealed clustered patterns of sentiment distribution and their association with physical density. Using entropy weighting, building density and floor area ratio were integrated to classify residential built environments (RBEs) into five tiers based on natural breaks. Key factors influencing positive sentiment across PD groups were identified through Pearson correlation heatmaps and OLS regression. Three main findings emerged: (1) Although higher-PD areas yielded a greater volume of positive sentiment expressions, they exhibited lower diversity and intensity compared to low-PD areas, suggesting inferior emotional quality; (2) Environmental and socio-cultural factors showed limited effects on sentiment in low-PD areas, whereas medium- and high-PD areas benefited from a significantly enhanced cumulative effect through the integration of socio-cultural amenities and transportation facilities—however, this positive correlation reversed at the highest level (RBE 5); (3) The model explained 20.3% of the variance in positive sentiment, with spatial autocorrelation effectively controlled. These findings offer nuanced insights into the nonlinear mechanisms linking urban form and emotional well-being in high-density mountainous settings, providing theoretical and practical guidance for emotion-sensitive urban planning. Full article

This work studies yellow pea flour (YPF) fermentation with kefir (1:1.5 mass ratio, incubated 30 h at 25 °C) for gluten-free breadmaking. Three samples were evaluated: untreated YPF, YPF mixed with kefir (UF), and fermented YPF (FF). Structural changes were minimal, but fermentation improved the flour functionality. Bulk density (g/mL) decreased from 0.54 ± 0.02 in YPF and 0.47 ± 0.01 in UF to 0.43 ± 0.01 in FF, while the water absorption capacity (g/g) increased from 1.20 ± 0.01 in YPF and 1.50 ± 0.05 in UF to 1.92 ± 0.02 in FF. YPF showed the lowest oil absorption capacity (0.90 ± 0.02 g/g), while higher values were obtained for FF and UF (averaging 1.54 g/g). The yellowness index showed a clear tendency: higher in UF (34.9 ± 0.2), intermediate in FF (32.869 ± 0.008), and lower in YPF (22.4 ± 0.1). In gluten-free bread, baking loss did not show significant differences between FF-B and UF-B (averaging 15.65%) but they were significantly lower than that of YPF-B (18.5 ± 0.5%). The highest specific volume (mL/g) was observed in FF-B (1.96 ± 0.02), followed by UF-B (1.33 ± 0.02) and YPF-B (1.08 ± 0.02). Significantly reduced “pea” sensory attributes were perceived in FF-B, while acidity perception increased. Hardness was similar among breads, although chewiness was higher in FF-B. These results suggest that kefir fermentation enhances YPF functionality in gluten-free breadmaking. Full article

Amid the global challenges of rapid urbanization, understanding how micro-scale spatial features shape human perception is critical for advancing livable cities. This study pro-poses a data-driven framework that integrates street view imagery, deep learning-based semantic segmentation, and machine learning interpretation models including SHAP analysis to explore the relationship between urban spatial characteristics and subjective perceptions. A total of 12,604 street-level images from Xi’an, China, were analyzed to ex-tract seven spatial indicators. These indicators were then linked with perceptual data across six emotional dimensions derived from the Place Pulse 2.0 dataset. The analysis revealed that natural elements significantly enhance perceived comfort and aesthetics, while high-density built environments can suppress perceived safety and liveliness. Spatial clustering further identified three urban typologies—traditional, transitional, and modern—with distinct perceptual signatures. These findings offer scalable and transferable insights for perception-informed urban design and renewal, particularly in dense urban settings worldwide. Full article

Urban livability and sustainability are increasingly studied at the neighborhood scale, where built, social, and governance conditions shape residents’ everyday experiences. Yet existing assessment frameworks often fail to integrate subjective perceptions with multi-dimensional environmental indicators in replicable and scalable ways. To address this gap, this study develops an Environmental, Social, and Governance (ESG)-informed framework for evaluating perceived environmental quality in urban communities. Using Baidu Street View imagery—selected due to its comprehensive coverage of Chinese urban areas—and Point of Interest (POI) data, we analyze seven communities in Shenyang, China, selected for their diversity in built form and demographic context. Kernel Density Analysis and Exploratory Factor Analysis (EFA) are applied to derive latent ESG-related spatial dimensions. These are then correlated with Place Pulse 2.0 perception scores using Spearman analysis to assess subjective livability. Results show that environmental and social factors—particularly greenery visibility—are strongly associated with favorable perceptions, while governance-related indicators display weaker or context-specific relationships. The findings highlight the differentiated influence of ESG components, with environmental openness and walkability emerging as key predictors of perceived livability. By integrating pixel-level spatial features with perception metrics, the proposed framework offers a scalable and transferable tool for human-centered neighborhood evaluation, with implications for planning strategies that align with how residents experience urban environments. Full article

This paper investigates the associations between urban form, neighbourhood characteristics, socioeconomic factors and commuting mode choice and neighbourhood-level active travel (walking and cycling) in Windhoek, Namibia. Despite growing interest in sustainable mobility, limited research has examined these relationships in medium-sized African cities, particularly in distinguishing between commuting and neighbourhood travel behaviour. To address this gap, the study explores three interrelated research questions: (1) In what ways are urban form, accessibility, and socioeconomic factors associated with residents’ choices between motorised and non-motorised commuting modes? (2) What factors determine the propensity of cycling within neighbourhoods? (3) How are similar factors associated with walking propensity at the neighbourhood level? Using survey data from 1000 residents across nine constituencies and spatial analysis through GIS, the study applies binary logistic and multiple linear regression models to analyse commuting and local travel patterns. The findings show that commuting mode choice is significantly associated with socioeconomic status, car ownership, commuting time, and urban sprawl around homes, all of which reduce the likelihood of walking or cycling. Neighbourhood walking, in contrast, is largely driven by necessity in underserved, high-density areas and is positively associated with population density, perceived safety, and community belonging but constrained by inadequate infrastructure and car access. Cycling, though less frequent, is associated with perceived security, access to local amenities, and cycling competence, while negatively constrained by inexperience and cultural norms. The study concludes that fragmented urban form and socioeconomic disparities reinforce mobility exclusion and calls for equity-oriented transport planning that integrates infrastructure and behavioural change. Full article

This study examined how different lighting characteristics of conventional and eco-friendly lighting and environmental conditions, particularly snow cover, influenced the luminous environment and, in relation to that, pedestrian perception of faces on footpaths. The analysis was based on a dataset comprising both subjective evaluations and objective measurements. The spatial and directional light field above a footpath was measured for the two types of road lighting, of which the “eco-centric” luminaire had a lumen output of 4820 lm and reduced blue-light component (correlated color temperature (CCT) of 2200 K) compared to the conventional luminaire with 14,000 lm and 4000 K. The luminaires were analyzed under snowy and non-snowy conditions. Snow cover significantly increased light diffuseness and density (directionally averaged illuminance at a point), resulting in more uniform light and higher subjective ratings. Also, face visibility ratings were generally higher and more uniform, while non-snowy conditions led to more pronounced differences between positions and luminaire types. Regression analysis revealed that vertical illuminance at eye height was the strongest predictor of perceived facial friendliness and well-lighted-ness and contributed to more favorable ratings for the environment lighting too. The eco-centric luminaire was found to positively influence face lighting ratings but received lower ratings for environmental visibility. Increased horizontal illuminance did not consistently result in enhanced subjective evaluations, which points to limitations of traditional illuminance-based lighting standards, often considering horizontal illuminance at ground level as one of the main metrics. The “social light field” concept emphasizes a holistic approach to urban lighting design that integrates social perception and environmental sustainability by considering the distribution of the actual, resulting light throughout the urban space, especially vertical illuminance at the face and its effects on visual appearance, as well as contributing interactions with the environment and materials in it. Full article

Urban public space is a crucial constituent of livable city construction. A pleasant and comfortable public space is not simply spacious, bright, and accessible but also subjectively preferred by citizens who use it. Efforts to understand how citizens experience and perceive therein thus matters and would significantly aid urban design and well-being improvement. This research constructs a perception lexicon for 129 sites of public street space, a significant type of public space, in Shanghai and identifies how citizens comment on these sites through sentiment analysis based on social platform texts. A Chinese natural language processing (NLP) tool is applied to sort out the extent of citizens’ feelings on the urban street environment through a 0–1 scoring system. Six types of built environment elements and five categories of urban public spaces are identified. Pleasantly perceived sites primarily locate in the urban center and sporadically distribute in the outskirts and are normally “high-density” and “multi-function” in nature. Among the five categories of urban public spaces, sites that are commercially dynamic with culture, arts, and historical elements or that have gourmet food and good walkability generally receive the higher sentiment scores, but scores of ancient town commercial streets (many are antique streets), once popular and contributing much to tourism economy, are not satisfactory. The NLP-based text analysis also quantifies the intensity of emotional perceptions toward the six types of built environment elements and their associations with the general perception. This study not only offers insights for designers and policy makers in public space optimization but also showcases a scalable, data-driven approach for integrating public emotional and experiential dimensions into urban livability assessments. Full article

China’s rapid urbanization has presented challenges for sustainably revitalizing the historic and cultural heritage within its urban villages. Often, these efforts overlook the crucial roles of community ties and cultural values. This study focuses on 15 representative urban villages in Guangzhou (2019–2024). It tests the core idea that the physical layout of these spaces reflects underlying community structures and cultural values shaped by specific policies. Integrating this understanding into landscape planning can significantly improve revitalization outcomes. We used a mixed-methods approach: (1) Extended fieldwork to understand community networks and cultural practices; (2) Spatial analysis to measure how building density relates to land uses; (3) Sentiment analysis to reveal how people perceive cultural symbols; (4) A coordination model to link population influx with landscape suitability. Key findings reveal different patterns: Villages with strong clan networks maintained high cultural integrity and public acceptance through bodies like ancestral hall councils. Economically driven villages showed a split—open for business but culturally closed, with very low tenant participation. Successful revitalization requires balancing three elements: protecting physical landmarks in their original locations; modernizing cultural events; and reconstructing community narratives. Practically, we propose a planning framework with four approaches tailored to different village types. For instance, decaying villages should prioritize repairing key landmarks that hold community memory. Theoretically, we build a model linking social and spatial change, extending the cultural value concepts of Amos Rapoport to the context of fast-growing cities. This provides a new methodological perspective for managing urban–rural heritage in East Asia. Full article

Social media platforms like Instagram significantly shape destination images and influence tourist behavior. Understanding how different cities are represented and perceived on these platforms is crucial for effective tourism marketing. This study provides a comparative analysis of Instagram content and engagement patterns in Seoul and Tokyo, two major Asian metropolises, to derive actionable marketing insights. We collected and analyzed 59,944 public Instagram posts geotagged or location-tagged within Seoul (n = 29,985) and Tokyo (n = 29,959). We employed a mixed-methods approach involving content categorization using a fine-tuned convolutional neural network (CNN) model, engagement metric analysis (likes, comments), Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis and thematic classification of comments, geospatial analysis (Kernel Density Estimation [KDE], Moran’s I), and predictive modeling (Gradient Boosting with SHapley Additive exPlanations [SHAP] value analysis). A validation analysis using balanced samples (n = 2000 each) was conducted to address Tokyo’s lower geotagged data proportion. While both cities showed ‘Person’ as the dominant content category, notable differences emerged. Tokyo exhibited higher like-based engagement across categories, particularly for ‘Animal’ and ‘Food’ content, while Seoul generated slightly more comments, often expressing stronger sentiment. Qualitative comment analysis revealed Seoul comments focused more on emotional reactions, whereas Tokyo comments were often shorter, appreciative remarks. Geospatial analysis identified distinct hotspots. The validation analysis confirmed these spatial patterns despite Tokyo’s data limitations. Predictive modeling highlighted hashtag counts as the key engagement driver in Seoul and the presence of people in Tokyo. Seoul and Tokyo project distinct visual narratives and elicit different engagement patterns on Instagram. These findings offer practical implications for destination marketers, suggesting tailored content strategies and location-based campaigns targeting identified hotspots and specific content themes. This study underscores the value of integrating quantitative and qualitative analyses of social media data for nuanced destination marketing insights. Full article