Search Results (439)

Background: Multidrug-resistant tuberculosis (MDR-TB) prevention presents significant challenges in Peruvian healthcare settings, with substantial gaps in knowledge implementation and preventive practices. However, little is known about how patients’ sociodemographic factors influence the translation of knowledge into preventive practices. Methods: This cross-sectional study examined the associations between knowledge, preventive practices, and potential mediating roles of occupation, educational level, and sex among MDR-TB patients. We surveyed 280 patients from twelve health centers in the Piura-Castilla Network, Peru, recruited from urban (38.55%), marginal urban (32.06%), and rural (29.39%) areas through nonprobability convenience sampling. Participants represented diverse occupational backgrounds, including housewives (19.85%), workers (20.99%), and unemployed individuals (23.28%). Results: Measurement instruments were validated through confirmatory factor analysis, demonstrating adequate reliability (McDonald’s ω > 0.80) and discriminant validity (HTMT < 0.85). Path analysis using structural equation modeling assessed direct and indirect relationships. Knowledge showed a significant direct association with preventive practices (β = 0.194, p < 0.001). Among the three mediating variables examined, only educational level demonstrated a significant indirect effect (β = 0.073, p < 0.001), while occupation (β = −0.010, p = 0.490) and sex (β = −0.035, p = 0.150) showed no significant indirect associations. The model explained 29.7% of the variance in preventive practices. Conclusions: Educational level appears to facilitate the translation of knowledge into preventive practices among MDR-TB patients, though the cross-sectional design precludes causal or directional inferences. Healthcare institutions should develop tailored educational interventions according to patients’ educational backgrounds, including literacy-sensitive materials, simplified visual aids, and personalized counseling sessions to enhance MDR-TB prevention effectiveness in clinical settings. Full article

A well-performing road network is essential for modern society. But any road is nothing without its users—cyclists, drivers, pedestrians. Road network cannot be managed without knowing who the roads serve. The gaps in this knowledge lead to decisions that hinder efficiency, equality, and sustainability. This is why monitoring traffic is imperative for road management. However, traditional short-term traffic counting methods fail to provide full coverage at a reasonable cost. This study assessed the economic feasibility of drone-enabled traffic monitoring systems across Estonian urban environments through comparative spatial and economic analysis. Hexagonal tessellation was applied to 255 urban locations, identifying 47,530 monitoring points across 4077 grid cells. Economic modeling compared traditional counting costs with drone-based systems utilizing ultralight drones and nomadic 5G infrastructure. Monte Carlo simulation evaluated robustness under varying operational intensities from 30 to 180 days annually. Analysis identified an 8-point density threshold for economic viability, substantially lower than previously reported requirements. Operational intensity emerged as the critical determinant: minimal operations (30 days) proved viable for 9.0% of locations, while semi-continuous deployment (180 days) expanded viability to 81.6%. The findings demonstrate that drone-based monitoring achieves 60–80% cost reductions compared to traditional methods while maintaining equivalent accuracy (95–100% detection rates for vehicles, cyclists, and pedestrians), presenting an economically superior alternative for 67% of Estonian urban areas, with viability extending to lower-density locations through increased operational utilization. Full article

With the intensification of global urbanization and climate change challenges, urban green spaces and urban forests are playing an increasingly critical role in supporting sustainable urban development. Based on the Web of Science Core Collection, this study employed bibliometric analysis and visualization methods (VOSviewer 1.6.19 and Bibliometrix v5.0.1 (R package)) to systematically map the global knowledge landscape of urban green space and urban forest research from 2000 to 2025, identifying key thematic clusters and research fronts. The results show a shift in research focus from traditional green infrastructure and ecosystem service assessment to an integrated approach emphasizing multifunctionality, climate adaptation, public health, and governance innovation. Furthermore, research efforts are concentrated in rapidly urbanizing regions, and global spatial distribution remains a significant issue. Based on this, this paper proposes a strategic research agenda to promote the development of this field, including four key directions: (1) embedding social equity and people-oriented values into green space planning and management; (2) leveraging digital technologies and artificial intelligence to strengthen urban ecological governance; (3) promoting the transition of green infrastructure from fragmented to systematic ecological networks; and (4) deepening the role of urban green space in climate adaptation and sustainable urban transformation. By systematically combing through the knowledge system and governance logic of urban forests and greening, this article aims to reveal the key role of urban ecosystems in addressing climate change and promoting social well-being, and provide operational scientific basis and policy inspiration for the sustainable transformation of global cities. Full article

This paper examines how place-sensitive, transdisciplinary entrepreneurship education can catalyze inclusive innovation in peripheral regions. Drawing on the Pathways to Innovation and Entrepreneurship initiative—implemented in Southern Italy through a collaboration between the University of Naples Federico II and Cornell Tech with the support of the US Diplomatic Mission to Italy—this study explores the role of universities as active agents in regional innovation ecosystems. Adopting an action research methodology across inner and peri-urban territories, the initiative combined transdisciplinary learning, international knowledge exchange, and applied innovation to support regional planning. Findings highlight three interdependent causal pathways: (1) experiental learning and the development of transversal competencies, (2) network formation across scales, and (3) context-sensitive innovation practices. The results show how a locally embedded yet globally networked approach contributes to innovation capacity building of peripheral regions, aligning global knowledge flows with territorial strengths. The paper concludes with implications for embedding EE into regional innovation strategies, fostering diverse network management, and promoting sustainable, place-based development in left-behind places. Full article

Drive-through establishments are becoming increasingly prominent in urban transport systems; however, their impacts on traffic generation, spatial form, and sustainability remain insufficiently understood. Conventional trip generation manuals often rely on static predictors, such as gross floor area, which can misrepresent demand in high-turnover, convenience-driven contexts and fail to capture operational, behavioral, and environmental effects. This knowledge gap underscores the need for an integrated framework that supports both effective planning and congestion mitigation, particularly in cities experiencing rapid motorization and shifting mobility behaviors. This study investigated the evolving dynamics in trip generation associated with drive-through services and their influence on urban development patterns. A mixed-methods approach was employed, combining a systematic literature review, meta-analysis of queue data, cross-comparison of trip generation rates from international and Asian datasets, and case-based scenario modeling. The results revealed that drive-throughs intensify high-frequency, impulse-driven vehicle trips, thereby causing congestion, reducing pedestrian accessibility, and reinforcing auto-centric land use configurations, while also enhancing consumer convenience and commercial efficiency. This study contributes to the literature by synthesizing inconsistencies in regional datasets; introducing a systems-based framework that integrates structural, behavioral, and environmental determinants with road network topology; and outlining policy applications that align trip generation with zoning, design standards, and sustainable infrastructure planning. Full article

This study presents a comprehensive latitudinal analysis of air particulate matter (PM) across an 1400 km pollution corridor spanning Chile’s central-southern zone. We systematically analyzed PM_2.5 and PM₁₀ concentrations across eight major urban centers (2014–2015), providing crucial pre-Paris Agreement baseline data for South America’s most extensive air quality monitoring network. Our analysis reveals significant pollution gradients, with Coyhaique ranking one of the world’s most severely polluted cities (95th percentile globally, WHO database) and demonstrating an extreme 86% fine particulate matter ratio that far exceeds international urban standards. Residential wood combustion (RWC) demonstrates systematic correlations with fine PM concentrations (R² > 0.96), suggesting RWC is the dominant pollution driver across multiple climate zones. The documented pollution patterns represent a concerning continental-scale environmental pattern, with 4900–6500 annual premature deaths directly attributable to PM_2.5 exposure-one of the highest per-capita pollution mortality rates in South America. This work provides a methodological framework applicable to mountain-valley pollution systems globally while addressing critical knowledge gaps in regional air quality science. The evidence indicates the need for urgent implementation of comprehensive wood combustion control strategies and positions this research as essential baseline documentation for both national air quality policy and international climate change assessment frameworks. Full article

The built environment plays a crucial role in shaping residents’ quality of life and emotional well-being. In the context of growing efforts to promote livable and walkable cities, a key question emerges: how can emerging technologies—particularly virtual reality (VR)—be leveraged to evaluate and enhance urban environments through the lens of pedestrian emotional perception? This study systematically reviewed the literature published between 2015 and 2024 in the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) databases, ultimately identifying 37 Chinese-language and 113 English-language journal articles. Using bibliometric analysis and CiteSpace, the research mapped publication trends, research hotspots, and disciplinary networks across linguistic contexts. Results reveal that Chinese-language studies often emphasize embodied cognition and electroencephalogram (EEG) monitoring, while English-language studies focus more on VR application in stress recovery and health assessment. Based on this synthesis, this study proposes a “sensory–cognitive–affective” framework and a set of spatial intervention strategies, offering a novel perspective for emotion-driven urban design. The findings highlight a paradigm shift from engineering-oriented planning to human-centered approaches, with VR technologies serving as a critical enabling tool. This review contributes both conceptual and methodological foundations for future research at the intersection of immersive technologies, built environment studies, and urban emotional well-being. Full article

Vertiports, as the foundational ground infrastructure for Urban Air Mobility (UAM), have garnered increasing scholarly attention in recent years. To examine how the existing literature has reviewed and summarized vertiport-related knowledge, this study conducts a bibliometric analysis of publications (2000–2024) from four major databases, including Web of Science and Scopus, using VOSviewer and CiteSpace. By analyzing co-citation and keyword co-occurrence patterns, the results suggest that vertiport research frontiers are shifting toward facility location, network planning, airspace and scheduling management, scalable infrastructure, and integration with ground transport systems. Scholars and institutions in the United States, China, Europe, and South Korea have taken leading roles in advancing this field, though collaboration among research organizations still requires strengthening. Overall, the findings reveal future research pathways and provide support for the planning and integration of vertiport infrastructure in UAM operations. Full article

The increasing complexity of urban traffic networks has highlighted the potential of Multi-Agent Reinforcement Learning (MARL) for Traffic Signal Control (TSC). However, most existing MARL methods assume homogeneous observation and action spaces among agents, ignoring the inherent heterogeneity of real-world intersections in topology and signal phasing, which limits their practical applicability. To address this gap, we propose HAPS-PPO (Heterogeneity-Aware Policy Sharing Proximal Policy Optimization), a novel MARL framework for coordinated signal control in heterogeneous road networks. HAPS-PPO integrates two key mechanisms: an Observation Padding Wrapper (OPW) that standardizes varying observation dimensions, and a Dynamic Multi-Strategy Grouping Learning (DMSGL) mechanism that trains dedicated policy heads for agent groups with distinct action spaces, enabling adequate knowledge sharing while maintaining structural correctness. Comprehensive experiments in a high-fidelity simulation environment based on a real-world road network demonstrate that HAPS-PPO significantly outperforms Fixed-time control and mainstream MARL baselines (e.g., MADQN, FMA2C), reducing average delay time by up to 44.74% and average waiting time by 59.60%. This work provides a scalable and plug-and-play solution for deploying MARL in realistic, heterogeneous traffic networks. Full article

Real estate plays a pivotal role in fostering national economic growth and ensuring social stability. In China, housing constitutes the largest fixed asset for the majority of households. Given the extensive network of upstream and downstream industries associated with real estate, the government places significant emphasis on its regulation and development, employing a variety of policy instruments to maintain market stability. This study adopts a quantitative approach to conduct a text analysis of China’s real estate policies through the lens of knowledge mapping and LDA topic modeling, while also comparing policy content across 21 different cities. The findings indicate that real estate policy in China transcends mere market regulation. It also encompasses governance within the construction industry as well as provisions for housing security. Furthermore, due to the diverse roles that real estate plays in economic development and urban construction, there is notable regional heterogeneity in policy priorities. By text analysis of real estate policies, this study provides a systematic overview of policy content, thereby laying a foundation for more nuanced and regionally differentiated research within the realm of real estate policy. Full article

This study examines the global mobility of researchers in the smart city domain from 2000 to 2020, using inter-country and intercity affiliation data from the Web of Science. Employing network analysis and spatial econometric models, the paper maps the structural reconfiguration of scientific labor circulation. The results show that the international mobility network is dense yet asymmetric, dominated by a small set of high-frequency corridors such as China–United States, which intensified markedly over the two decades. While early networks were fragmented and polycentric, the later period reveals a multipolar configuration with significant growth in South–South and intra-European exchanges. At the city level, Beijing, Shanghai, Wuhan, and Nanjing emerged as central nodes, reflecting the consolidation of East Asian hubs within the global knowledge system. Mesoscale community detection highlights the coexistence of territorially embedded ecosystems and transregional corridors sustained by thematic and reputational affinities. Growth decomposition indicates that high-income countries benefit from both talent retention and international inflows, while upper-middle-income countries rely heavily on inbound mobility. Spatial regression and quantile models confirm that economic growth and baseline scientific visibility remain robust drivers of urban smart city performance. In contrast, mobility effects are context-dependent and heterogeneous across city positions. Together, these findings demonstrate that researcher mobility is not only a vector of knowledge exchange but also a mechanism that reinforces spatial hierarchies and reshapes the geography of global smart city innovation. Full article

Given that urban mobility arises from the interaction between social and environmental conditions, this study constructs a Bayesian network to represent these relationships in David, Panama, using 500 georeferenced household surveys that recorded variables related to demographics, travel behavior, infrastructure, mobility patterns and perceptions of risk, safety, and vulnerability. The Bayesian network was built and validated through a consensus-driven hybrid procedure combining structural learning and expert knowledge, resulting in a directed acyclic graph (DAG) with 127 nodes and 189 arcs; and conditional probability tables (CPTs) were learned from data. The topology of the network was analyzed with Louvain community detection, revealing eleven subsystems that group household economy and mode choice, hydrometeorological mobility barriers, congestion, public-transport quality, and safety in school travel. The inferences show gender-based differences in the risk of harassment on public transport, higher perceived vulnerability on longer trips, and elevated stress among middle-aged drivers. The model highlights potential priority interventions such as reinforcing public-transport safety, promoting self-contained trips, and encouraging short-distance active mobility, based on population perceptions. The resulting DAG functions as both an analytical and communication tool for urban management, is visually understandable to all stakeholders, and provides unprecedented evidence for Panama in a little-studied context. Full article

Gulf cities have embarked on ambitious public transport infrastructure initiatives in recent decades to foster more livable and sustainable cities. This investigation explores the interpretations and implementation of Transit-Oriented Development (TOD) principles in two prototypical urban districts: Doha’s West Bay, Qatar, and Riyadh’s King Abdullah Financial District (KAFD), Saudi Arabia. By following a comparative case study approach, the study explores how retrofitted (West Bay) and purpose-built (KAFD) TOD configurations fare regarding land use mix, density, connectivity, transit access, and environmental responsiveness. The comparative methodology was selected to specifically capture the spatial, climatic, and socio-economic complexities of TOD implementation in hyper-arid urban environments. Based on qualitative evidence from stakeholder interviews, spatial assessments, and geospatial indicators—such as metro access buffers, building shape compactness, and TOD proximity classification—the investigation reflects both common challenges and localized adaptations in hot-desert Urbanism. It emerges that, while benefiting from integrated planning and multimodal connectivity, KAFD’s pedestrian realm is delimited by climatic constraints and inactive active transport networks. West Bay, on the other hand, features fragmented public spaces and low TOD cohesion because of automotive planning heritages. However, it holds potential for retrofit through infill development and tactical Urbanism. The results provide transferable insights that can inform TOD strategies in other Gulf and international contexts facing similar sustainability and mobility challenges. By finalizing strategic recommendations for urban livability improvement through context-adaptive TOD approaches in Gulf cities, the study contributes to the wider discussion of sustainable Urbanism in rapidly changing environments and supplies a reproducible assessment frame for future TOD planning. This study contributes new knowledge by advancing a context-adaptive TOD framework tailored to the unique conditions of hyper-arid Gulf cities. Full article

In the context of global climate change and rapid urbanization, the urban heat island (UHI) effect has emerged as a critical issue impacting urban sustainability. This study analyzes 945 publications retrieved from the Web of Science Core Collection (2000–2025) and employs VOSviewer and Scimago Graphica to construct and visualize a knowledge map. The findings indicate that, since 2013, there has been a significant increase in research interest in utilizing green infrastructure (GI) to mitigate UHI, with China, the United States, and Europe leading international collaboration efforts. Keyword analysis reveals that early studies primarily focused on thermodynamic manifestations. Recent research has shifted toward more diverse topics, including artificial neural networks (ANNs), environmental justice, and public participation. By constructing a knowledge framework, this study clarifies how GI mitigates UHI while simultaneously promoting carbon reduction, enhancing health benefits, and supporting resilient governance. This research provides a comprehensive overview of the role of GI in mitigating UHI, offering theoretical insights and practical solutions for achieving integrated governance that combines climate resilience, biodiversity conservation, and social equity. These findings have significant theoretical and practical implications for advancing both UHI mitigation and sustainable development. Full article

Rapid urban growth in Middle Eastern cities has intensified congestion-related challenges, yet traffic data-based decision making remains limited. This study leverages crowd-sourced travel time data from the Google Maps API to evaluate temporal and spatial patterns of congestion across multiple strategic routes in Jeddah, Saudi Arabia, a coastal metropolis with a complex road network characterized by narrow, high-traffic corridors and limited public transit. A real-time Congestion Index quantifies traffic flow, incorporating free-flow speed benchmarking, dynamic profiling, and temporal classification to pinpoint congestion hotspots. The analysis identifies consistent peak congestion windows and route-specific delays that are critical for travel behavior modeling. In addition to congestion monitoring, the framework contributes to urban sustainability by supporting reductions in traffic-related emissions, enhancing mobility equity, and improving economic efficiency through data-driven transport management. To our knowledge, this is the first study to systematically use the validated, real-time Google Maps API to quantify route-specific congestion in a Middle Eastern urban context. The approach provides a scalable and replicable framework for evaluating urban mobility in other data-sparse cities, especially in contexts where traditional traffic sensors or GPS tracking are unavailable. The findings support evidence-based transport policy and demonstrate the utility of publicly accessible traffic data for smart city integration, real-time traffic monitoring, and assisting transport authorities in enhancing urban mobility. Full article