Search Results (1,211)

This study focuses on cultural and urban development policies under China’s 14th Five-Year Plan, exploring the content and semantic structure of discussions on the “East Asian Cultural Capital” project on the Weibo platform. It analyzes how national cultural development policies are reflected in the discourse system related to the “East Asian Cultural Capital” on social media and emphasizes the guiding role of policies in the dissemination of online culture. When China announced the 14th Five-Year Plan in 2021, the strategic direction and policy framework for cultural development over the five-year period from 2021 to 2025 were clearly outlined. This study employs text mining and semantic network analysis methods to analyze user-generated content on Weibo from 2023 to 2024, aiming to understand public perception and discourse trends. Word frequency and TF-IDF analyses identify key terms and issues, while centrality and CONCOR clustering analyses reveal the semantic structure and discourse communities. MR-QAP regression is employed to compare network changes across the two years. Findings highlight that urban cultural development, heritage preservation, and regional exchange are central themes, with digital media, cultural branding, trilateral cooperation, and cultural–economic integration emerging as key factors in regional collaboration. Full article

Existing research fails to effectively address the problem of increased GNSS positioning errors caused by non-line-of-sight (NLOS) and line-of-sight (LOS) signal attenuation due to obstructions such as buildings and trees in complex urban environments. To address this issue, we dig into the environmental perception perspective to propose a semantic segmentation-based GNSS signal occlusion detection and optimization method. The approach distinguishes between building and tree occlusions and adjusts signal weights accordingly to enhance positioning accuracy. First, a fisheye camera captures environmental imagery above the vehicle, which is then processed using deep learning to segment sky, tree, and building regions. Subsequently, satellite projections are mapped onto the segmented sky image to classify signal occlusions. Then, based on the type of obstruction, a dynamic weight optimization model is constructed to adjust the contribution of each satellite in the positioning solution, thereby enhancing the positioning accuracy of vehicle-navigation in urban environments. Finally, we construct a vehicle-mounted navigation system for experimentation. The experimental results demonstrate that the proposed method enhances accuracy by 16% and 10% compared to the existing GNSS/INS/Canny and GNSS/INS/Flood Fill methods, respectively, confirming its effectiveness in complex urban environments. Full article

Object detection in remote sensing imagery is critical in environmental monitoring, urban planning, and land resource management. However, the task remains challenging due to significant scale variations, arbitrary object orientations, and complex background clutter. To address these issues, we propose a novel orientation module (SOAM Block) that jointly models object scale and directional features while exploiting geometric symmetry inherent in many remote sensing targets. The SOAM Block is constructed upon a lightweight and efficient Adaptive Multi-Scale (AMS) Module, which utilizes a symmetric arrangement of parallel depth-wise convolutional branches with varied kernel sizes to extract fine-grained multi-scale features without dilation, thereby preserving local context and enhancing scale adaptability. In addition, a Strip-based Context Attention (SCA) mechanism is introduced to model long-range spatial dependencies, leveraging horizontal and vertical 1D strip convolutions in a directionally symmetric fashion. This design captures spatial correlations between distant regions and reinforces semantic consistency in cluttered scenes. Importantly, this work is the first to explicitly analyze the coupling between object scale and orientation in remote sensing imagery. The proposed method addresses the limitations of fixed receptive fields in capturing symmetric directional cues of large-scale objects. Extensive experiments are conducted on two widely used benchmarks—DOTA and HRSC2016—both of which exhibit significant scale variations and orientation diversity. Results demonstrate that our approach achieves superior detection accuracy with fewer parameters and lower computational overhead compared to state-of-the-art methods. The proposed SOAM Block thus offers a robust, scalable, and symmetry-aware solution for high-precision object detection in complex aerial scenes. Full article

Accurately predicting the next location of urban individuals is a central issue in human mobility research. Human mobility exhibits diverse patterns, requiring the integration of spatiotemporal contexts for location prediction. In this context, multi-view learning has become a prominent method in location prediction. Despite notable advances, current methods still face challenges in effectively capturing non-spatial proximity of regional preferences, complex temporal periodicity, and the ambiguity of location semantics. To address these challenges, we propose a representation-enhanced multi-view learning network (ReMVL-Net) for location prediction. Specifically, we propose a community-enhanced spatial representation that transcends geographic proximity to capture latent mobility patterns. In addition, we introduce a multi-granular enhanced temporal representation to model the multi-level periodicity of human mobility and design a rule-based semantic recognition method to enrich location semantics. We evaluate the proposed model using mobile phone data from Fuzhou. Experimental results show a 2.94% improvement in prediction accuracy over the best-performing baseline. Further analysis reveals that community space plays a key role in narrowing the candidate location set. Moreover, we observe that prediction difficulty is strongly influenced by individual travel behaviors, with more regular activity patterns being easier to predict. Full article

The siphon effect between airports has amplified the polarization in passenger throughput, undermining the balanced development and sustainability of airport clusters. The airport siphon effect occurs when one airport attracts a disproportionate share of passengers, concentrating traffic at the expense of others, which affects the overall resilience of the entire airport cluster. To address this issue, this study proposes a siphon index, expands the range of ground transportation options for passengers, and establishes a zero-siphon model to assess the impact of siphoning on the resiliency of airport clusters. Using this framework, four major airport clusters in China were selected as research subjects, with regional aviation accessibility serving as a measure of resilience. The results showed that among the four airport clusters, the siphon effect is most pronounced in the Guangzhou region. To explore the implications of this effect further, three airport disruption scenarios were simulated to assess the resilience of the Pearl River Delta airport cluster. The results indicated that the intensity and timing of disruptive events significantly affect airport cluster resilience, with hub airports being particularly sensitive. This study analyzes the risks associated with excessive route concentration, providing policymakers with critical insights to enhance the sustainability, equity, and resilience of airport clusters. The proposed strategies facilitate coordinated infrastructure development, optimized air–ground intermodal connectivity, and risk mitigation. These measures contribute to building more sustainable and adaptive aviation networks in rapidly urbanizing regions. Full article

The Latin American and Caribbean (LAC) region faces persistent challenges of inequality, climate change vulnerability, and deteriorating air quality. The Aburrá Valley, where Medellín is located, is a narrow tropical valley with complex topography, strong thermal inversions, and unstable atmospheric conditions, all of which exacerbate the accumulation of pollutants. In Medellín, ${\mathrm{NO}}_2$ concentrations have remained nearly unchanged over the past eight years, consistently approaching critical thresholds, despite the implementation of air quality control strategies. These persistent high concentrations are closely linked to the variability of the atmospheric boundary layer (ABL) and are often intensified by prolonged dry periods. This study focuses on a representative street canyon in Medellín that has undergone recent urban interventions, including the construction of new public spaces and pedestrian areas, without explicitly considering their impact on ${\mathrm{NO}}_x$ dispersion. Using Computational Fluid Dynamics (CFD) simulations, this work evaluates the influence of urban morphology on ${\mathrm{NO}}_x$ accumulation. The results reveal that areas with high Aspect Ratios (AR > 0.65) and dense vegetation exhibit reduced wind speeds at the pedestrian level—up to 40% lower compared to open zones—and higher ${\mathrm{NO}}_2$ concentrations, with maximum simulated values exceeding 50 μg/m³. This study demonstrates that the design of pedestrian corridors in complex urban environments like Medellín can unintentionally create pollutant accumulation zones, underscoring the importance of integrating air quality considerations into urban planning. The findings provide actionable insights for policymakers, emphasizing the need for comprehensive modeling and field validation to ensure healthier urban spaces in cities affected by persistent air quality issues. Full article

The development of urban underground space is a necessary way to realize the sustainable development of the city, and it is also an essential means to solve urban environmental problems such as traffic congestion and resource shortage. Scientific suitability evaluation is the prerequisite for the rational planning and development of underground space. Previous studies have encountered problems such as an imperfect index system, a single weighting method, and loss of membership degrees in fuzzy evaluation, which have led to unreasonable evaluation results. Taking the northern coastal cities of Weifang as the research area, the evaluation index system is established, and the index weights are calculated by the improved structural CRITIC. An improved fuzzy mathematical evaluation model based on the weighted summation method is proposed to carry out the suitability evaluation of underground space development in the research area. The results show that: (1) The proposed method of combination weight and improved fuzzy mathematics evaluation takes into account the scientific weight and avoids the subjective bias, and also corrects the issue of membership degree loss in the membership matrix of comprehensive evaluation. (2) When the area of the grid unit is 0.02% of the area of the research area, the size of the evaluation unit is more reasonable. (3) The area that is very suitable for underground space development accounts for 8.69%, and the more suitable area accounts for 25.55%, mainly located in the northwest and central–southern regions of the research area. It can provide a reference for the suitability evaluation of underground space development. Full article

Projections indicate that the global urban population is anticipated to reach 67.2% by 2050, accompanied by a threefold increase in urban built-up areas worldwide. Urbanization has profoundly transformed Earth’s natural environment, notably characterized by the drastic reduction and fragmentation of wildlife habitats. These changes contribute to local species extinction, leading to biodiversity loss and profoundly impacting ecological processes and regional sustainable development. However, within urban settings, certain ‘generalist’ species demonstrate survival capabilities contingent upon phenotypic plasticity. The co-evolution of gut microbiota with their hosts emerges as a key driver of this phenotypic plasticity. The presence of diverse gut microbiota constitutes a crucial adaptive mechanism essential for enabling hosts to adjust to rapid environmental shifts. This review comprehensively explores amniote gut microbial changes in the context of urbanization, examining potential drivers of these changes (including diet and environmental pollutants) and their potential consequences for host health (such as physiology, metabolism, immune function, and susceptibility to infectious and non-infectious diseases). Ultimately, the implications of the gut microbiome are highlighted for elucidating key issues in ecology and evolution. This understanding is expected to enhance our comprehension of species adaptation in the Anthropocene. Full article

Clarifying the coordination and impediments of social, economic, and spatial connection in rural areas is essential for advancing rural revitalization, urban-rural integration, and regional coordinated development. Utilizing the 24 counties and districts in western Hunan as case studies, we developed an evaluation index system for sustainable rural development across three dimensions: social, economic, and spatial. We employed the coupling model, coordination model, and obstacle factor model to investigate the comprehensive development level, coupling and coordination status, and obstacle factors of the villages in the study area at three temporal points: 2002, 2012, and 2022. The findings indicate the following: (1) The degree of rural development in western Hunan has escalated swiftly throughout the study period, transitioning from relative homogeneity to a heterogeneous developmental landscape, accompanied by issues such as inadequate development and regional polarization. (2) The overall rural social, economic, and spatial indices are low, and the degree of coupling has increased variably across different study periods; the average coordination degree has gradually improved over time, yet the level of coordination remains low, and spatial development is unbalanced. (3) The criterion-level impediments hindering the sustainable development of rural society, economy, and space are, in descending order, social factors, spatial factors, and economic factors. The urbanization rate, total fixed investment rate, and arable land change rate are the primary impediments in most counties and cities. The study’s findings will inform the planning of rural development in ethnic regions, promote sustainable social and spatial advancement in the countryside, and serve as a reference for rural revitalization efforts. Full article

Salinity intrusion is a growing threat to freshwater resources, particularly in low-lying coastal and estuarine regions, necessitating the development of effective early warning systems (EWS) to support timely mitigation. Although various water quality monitoring technologies exist, many face challenges related to long-term sustainability, ongoing maintenance, and accessibility for local users. This study introduces a novel hybrid real-time salinity intrusion early warning system that uniquely integrates fixed and portable monitoring technologies with strong community participation—an approach not yet widely applied in comparable urban-adjacent delta regions. Unlike traditional systems, this model emphasizes local ownership, flexible data collection, and system scalability in resource-constrained environments. This study presents a real-time salinity intrusion early warning system for Bang Kachao, Thailand, combining eight fixed monitoring stations and 20 portable salinity measurement devices. The system was developed in response to community needs, with local input guiding both station placement and the design of mobile measurement tools. By integrating fixed stations for continuous, high-resolution data collection with portable devices for flexible, on-demand monitoring, the system achieves comprehensive spatial coverage and adaptability. A core innovation lies in its emphasis on community participation, enabling villagers to actively engage in monitoring and decision-making. The use of IoT-based sensors, Remote Telemetry Units (RTUs), and cloud-based data platforms further enhances system reliability, efficiency, and accessibility. Automated alerts are issued when salinity thresholds are exceeded, supporting timely interventions. Field deployment and testing over a seven-month period confirmed the system’s effectiveness, with fixed stations achieving 90.5% accuracy and portable devices 88.7% accuracy in detecting salinity intrusions. These results underscore the feasibility and value of a hybrid, community-driven monitoring approach for protecting freshwater resources and building local resilience in vulnerable regions. Full article

In the stage of high-quality development, the functional coordination between transportation systems and territorial space is a key issue for improving urban spatial efficiency. This paper breaks through the traditional volume-to-capacity ratio analysis paradigm and innovatively integrates the “production-living-ecological space” theory. By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. Empirical research indicates that the improved accessibility indicators can precisely identify the transportation location value of regional functional cores, while the composite coordination indicators can deconstruct the spatiotemporal matching characteristics of “transportation facilities—spatial functions,” providing a dual decision-making basis for the redevelopment of existing space. This measurement system innovatively realizes the integration of planning transmission mechanisms with multi-scale application scenarios, guiding both overall spatial planning and urban renewal area re-optimization. The methodology, applied to the urban villages of Guangzhou, can significantly increase land utilization intensity and value. The research results offer a technical tool for cross-scale collaboration in land space planning reforms and provide theoretical innovations and practical guidance for the value reconstruction of existing spaces under the context of new urbanization. Full article

Property crime is a pressing issue in maintaining social order and urban sustainability, particularly in regions marked by pronounced socioeconomic disparity. While the link between socioeconomic stress and crime is well established, regional variations in Thailand have not been fully examined. Therefore, the purpose of this research was to examine spatial patterns of property crime and identify the potential associations between property crime and socioeconomic environment across Thailand. Using nationally compiled property-crime data from official sources across all provinces of Thailand, we employed geographic information system (GIS) tools to conduct a spatial cluster analysis at the sub-national level across 76 provinces. Both global and local statistical techniques were applied to identify spatial associations between property-crime rates and neighborhood-level socioeconomic conditions. The results revealed that property-crime clusters are primarily concentrated in the south, while low-crime areas dominate parts of the north and northeast regions. To analyze the spatial dynamics of property crime, we used geospatial statistical models to investigate the influence of socioeconomic variables across provinces. We found that property-crime rates were significantly associated with monthly income, areas experiencing high levels of household debt, migrant populations, working-age populations, an uneducated labor force, and population density. Identifying associated factors and mapping geographic regions with significant spatial clusters is an effective approach for determining where issues concentrate and for deepening understanding of the underlying patterns and drivers of property crime. This study offers actionable insights for enhancing safety, resilience, and urban sustainability in Thailand’s diverse regional contexts by highlighting geographies of vulnerability. Full article

With the accelerated development of urban underground spaces, prefabricated tunnel linings have become a research focus due to their advantages in construction efficiency and cost effectiveness. However, issues such as stress concentration at joints and insufficient overall stability hinder their broader application. This study investigates a cut-and-cover prefabricated tunnel project in the Chongqing High-Tech Zone through scale model tests and numerical simulations to systematically compare the mechanical behaviors of cast-in situ linings and three-segment prefabricated linings under surrounding rock loads. The experimental results show that the ultimate bearing capacity of the prefabricated lining is 15.3% lower than that of the cast-in situ lining, with asymmetric failure modes and cracks concentrated near joint regions. Numerical simulations further reveal the influence of joint stiffness on structural performance: when the joint stiffness is 30 MN·m/rad, the bending moment of the segmented lining decreases by 37.7% compared to the cast-in situ lining, while displacement increments remain controllable. By optimising joint pre-tightening forces and stiffness parameters, prefabricated linings can achieve stability comparable to cast-in situ structures while retaining construction efficiency. This research provides theoretical and technical references for the design and construction of open-cut prefabricated tunnel linings. Full article

Superficial fungal infections (SFIs) remain a common dermatological issue in the pediatric population, with varying prevalence across regions and age groups. This study aimed to assess the epidemiology of SFIs among children and adolescents in northern Poland in the years 2019 to 2024. A retrospective analysis was conducted on 1237 patients under 18 years of age who underwent direct mycological examination and culture, due to suspicion of SFIs. Data were evaluated based on age, gender, infection site, fungal species identified, and place of residence. The prevalence of SFIs in the studied population was 21.4%. The most frequently isolated fungi were Microsporum canis and Trichophyton rubrum complex. Infection patterns varied by age: tinea capitis and tinea cutis glabrae predominated in younger children, while adolescents were more affected by tinea pedis and onychomycosis. A higher proportion of positive results was observed in rural patients, although more urban dwellers were tested. Species distribution also varied with gender and place of residence. No significant change in SFI prevalence or pathogen profile was observed over the study period. This study provides updated insights into the epidemiology of SFIs in Polish children, highlighting the influence of demographic and environmental factors. The findings underscore the importance of accurate diagnosis and suggest a need for further research into behavioral and socio-economic contributors to infection patterns. Full article

As shared micromobility grows quickly in metropolitan settings, e-scooter safety issues have become more urgent. This paper uses a Bayesian hierarchical model applied to census block groups in several Texas metropolitan areas to construct a spatial risk assessment methodology for e-scooter crashes. Based on crash statistics from 2018 to 2024, we develop a severity-weighted crash risk index and combine it with variables related to land use, transportation, demographics, economics, and other factors. The model comprises a geographically structured random effect based on a Conditional Autoregressive (CAR) model, which accounts for residual spatial clustering after capture. It also includes fixed effects for covariates such as car ownership and nightlife density, as well as regional random intercepts to account for city-level heterogeneity. Markov Chain Monte Carlo is used for model fitting; evaluation reveals robust spatial calibration and predictive ability. The following key predictors are statistically significant: a higher share of working-age residents shows a positive association with crash frequency (incidence rate ratio (IRR): ≈1.55 per +10% population aged 18–64), as does a greater proportion of car-free households (IRR ≈ 1.20). In the built environment, entertainment-related employment density is strongly linked to elevated risk (IRR ≈ 1.37), and high intersection density similarly increases crash risk (IRR ≈ 1.32). In contrast, higher residential housing density has a protective effect (IRR ≈ 0.78), correlating with fewer crashes. Additionally, a sensitivity study reveals that the risk index is responsive to policy scenarios, including reducing car ownership or increasing employment density, and is sensitive to varying crash intensity weights. Results show notable collision hotspots near entertainment venues and central areas, as well as increased baseline risk in car-oriented urban environments. The results provide practical information for targeted initiatives to lower e-scooter collision risk and safety planning. Full article