Search Results (3,038)

Globally, technologically integrated housing solutions are increasingly relevant in addressing the challenges of aging populations and sustainable urban development. Drawing on the Technology Acceptance Model (TAM), this research investigates how perceptions of usefulness, ease of use, and attitudes influence relocation intention to smart retirement villages (SRVs), while also examining any significant differences between the socio-demographic variables and such intention. A total of 305 individuals aged 55 and above participated in an online survey, with data analyzed using IBM SPSS Statistics version 27 and AMOS-SEM version 25. The findings reveal that elderly individuals of Chinese ethnicity, those who are married, and those aged between 66 and 70 are more inclined to relocate to SRVs. Attitude and perceived usefulness significantly predict relocation intention, while perceived ease of use exerts an indirect effect through usefulness. These results highlight the importance of integrating user-centered technological design with socio-cultural and demographic considerations in the development of age-friendly built environments. The study offers insights for urban planners, policymakers, and developers seeking to create inclusive and sustainable smart housing solutions for aging populations. Full article

This study aims to clarify how different types of motivation influence employee retention by identifying the distinct roles of intrinsic and extrinsic factors in shaping job satisfaction, particularly under varying levels of urban stress and generational identity. Drawing on Herzberg’s Two-Factor Theory and Self-Determination Theory, we distinguish between intrinsic drivers (e.g., autonomy, achievement) and extrinsic hygiene factors (e.g., pay, stability). Using survey data from 356 Chinese employees and applying PLS-SEM with a moderated mediation design, we investigate how urbanization and Generation Z moderate these relationships. Results show that intrinsic motivation enhances satisfaction, especially in urban settings, while extrinsic factors negatively affect satisfaction when perceived as insufficient or unfair. Job satisfaction mediates the relationship between motivation and retention, although this effect is weaker among Generation Z employees. These findings refine motivational theories by demonstrating how environmental pressure and generational values jointly shape employee attitudes. The study contributes a context-sensitive framework for understanding retention by integrating individual motivation with macro-level moderators, offering practical implications for managing diverse and urbanizing labor markets. Full article

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

Promoting sustainable development requires a clear understanding of how short-term fluctuations in anthropogenic emissions affect urban environmental quality. This is especially relevant for cities experiencing rapid industrial changes or emergency policy interventions. Among key environmental concerns, variations in ambient pollutants like ozone (O₃) are closely tied to both public health and long-term sustainability goals. However, traditional chemical transport models often face challenges in accurately estimating emission changes and providing timely assessments. In contrast, statistical approaches such as the difference-in-differences (DID) model utilize observational data to improve evaluation accuracy and efficiency. This study leverages the synthetic difference-in-differences (SDID) approach, which integrates the strengths of both DID and the synthetic control method (SCM), to provide a more reliable and accurate analysis of the impacts of interventions on city-level air quality. Using Shanghai’s 2022 lockdown as a case study, we compare the deweathered ozone (O₃) concentration in Shanghai to a counterfactual constructed from a weighted average of cities in the Yangtze River Delta (YRD) that did not undergo lockdown. The quasi-natural experiment reveals an average increase of 4.4 μg/m³ (95% CI: 0.24–8.56) in Shanghai’s maximum daily 8 h O₃ concentration attributable to the lockdown. The SDID method reduces reliance on the parallel trends assumption and improves the estimate stability through unit- and time-specific weights. Multiple robustness checks confirm the reliability of these findings, underscoring the efficacy of the SDID approach in quantitatively evaluating the causal impact of emission perturbations on air quality. This study provides credible causal evidence of the environmental impact of short-term policy interventions, highlighting the utility of SDID in informing adaptive air quality management. The findings support the development of timely, evidence-based strategies for sustainable urban governance and environmental policy design. Full article

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article

Against the backdrop of China’s fast-growing digital economy and its financial inclusion agenda, there is still little city-level evidence on whether the e-CNY pilot accelerates financial deepening at the grassroots. Using a balanced panel of 271 prefecture-and-above cities for 2016–2022, this study employs a staggered difference-in-differences (SDID) design augmented by the synthetic control method (SCM) to rigorously identify the policy effect of the e-CNY pilot. The results show that the pilot program significantly improves urban financial inclusion, contributing to more equitable access to financial services and supporting inclusive socio-economic development. Mechanism analysis suggests that the effect operates mainly through two channels, a merchant-coverage channel and a transaction-scale channel, with the former contributing the majority of the overall effect. Incorporating a migration-based mobility index shows that most studies’ focus on the merchant-coverage effect is amplified in cities under tight mobility restrictions but wanes where commercial networks are already saturated, whereas the transaction-scale channel is largely insensitive to mobility shocks. Heterogeneity tests further indicate stronger gains in non-provincial capital cities and in the eastern and central regions. Overall, the study uncovers a “penetration-inclusion” network logic and provides policy insights for advancing sustainable financial inclusion through optimized terminal deployment, merchant incentives, and diversified scenario design. Full article

As a key engine driving China’s green financial transformation, the Green Financial Reform and Innovation Pilot Zones have demonstrated significant achievements in enhancing the capacity of financial services to support green real economies, preventing and mitigating green financial risks, and bolstering national and urban economic resilience. On this basis, a spatial Markov chain model is applied to further analyze the economic toughness of prefecture-level cities. This study treats the establishment of these pilot zones as a quasi-natural experiment, using panel data from 269 prefecture-level cities in China from 2013 to 2023 and employing a multi-period difference-in-differences (DID) model to empirically examine the impact of green financial reform on urban economic resilience and its underlying mechanisms. The results reveal that the establishment of these pilot zones significantly enhances urban economic resilience. Specifically, green financial reforms primarily improve urban economic resilience by increasing credit accessibility and capital allocation efficiency in the pilot cities. Furthermore, the policy effects are more pronounced in large cities and resource-dependent cities compared to small and medium-sized cities and non-resource-dependent cities, with stronger impacts observed in southern and coastal regions than in northern inland areas. Additionally, the policy effects are significantly greater in environmentally prioritized cities than in non-prioritized cities. By integrating green financial reforms and urban economic resilience into a unified analytical framework, this study provides valuable insights for policymakers to refine green financial strategies and design resilience-enhancing policies. Full article

The growing popularity of Personal Light Electric Vehicles (PLEVs), such as e-scooters, has revolutionized urban mobility by offering compact, cost-effective, and environmentally friendly transportation solutions. However, safety concerns, including inadequate infrastructure, poor protective measures, and high accident rates, remain critical challenges. This paper presents the design and development of an innovative self-balancing microvehicle under the H2020 LEONARDO project, which aims to address these challenges through advanced engineering and user-centric design. The vehicle combines features of monowheels and e-scooters, integrating cutting-edge technologies to enhance safety, stability, and usability. The design adheres to European regulations, including Germany’s eKFV standards, and incorporates user preferences identified through representative online surveys of 1500 PLEV users. These preferences include improved handling on uneven surfaces, enhanced signaling capabilities, and reduced instability during maneuvers. The prototype features a lightweight composite structure reinforced with carbon fibers, a high-torque motorized front wheel, and multiple speed modes tailored to different conditions, such as travel in pedestrian areas, use by novice riders, and advanced users. Braking tests demonstrate deceleration values of up to 3.5 m/s², comparable to PLEV market standards and exceeding regulatory minimums, while smooth acceleration ramps ensure rider stability and safety. Additional features, such as identification plates and weight-dependent motor control, enhance compliance with local traffic rules and prevent misuse. The vehicle’s design also addresses common safety concerns, such as curb navigation and signaling, by incorporating large-diameter wheels, increased ground clearance, and electrically operated direction indicators. Future upgrades include the addition of a second rear wheel for enhanced stability, skateboard-like rear axle modifications for improved maneuverability, and hybrid supercapacitors to minimize fire risks and extend battery life. With its focus on safety, regulatory compliance, and rider-friendly innovations, this microvehicle represents a significant advancement in promoting safe and sustainable urban mobility. Full article

Background/Objectives: A growing body of literature has demonstrated that living with food insecurity (FI) increases risk for mental health concerns in addition to nutritional deficits (e.g., suboptimal micronutrient consumption, excessive macronutrient consumption, malnutrition). Yet, research is needed to improve our understanding of subpopulations potentially at increased risk for mental health concerns when living in the context of FI. The current study examined psychosocial health across women of different developmental life stages all living with FI. Methods: Female clients of a large, urban food bank (N = 680) living with FI completed measures of mental health and health-related quality of life (HRQOL) in a cross-sectional design conducted on site at the food bank. Results: Consistent with past research, FI severity was correlated with poorer psychosocial health across all variables. A multivariate analysis of covariance compared women living with FI across 4 developmental life stages (young adult, early midlife, late midlife, and older adult; age range = 18–94 years), controlling for FI severity and race/ethnicity, on outcomes related to mental health and HRQOL. Women in early and late midlife reported higher anxiety, eating disorder symptoms, and eating-related psychosocial impairment than younger and older women. Conclusions: The mental health toll of living with FI is profound; midlife may comprise a developmental period of increased vulnerability to experience this mental health burden of living with FI for women. Thus, efforts are needed to develop innovative pathways for interventions to support the mental health of midlife women living with FI, likely involving multi-level and/or multicomponent approaches to resource access. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

Ensuring a sustainable and healthy human environment in university dormitories is essential for students’ learning, living, and overall health and well-being. To address this need, we carried out a series of systematic field measurements of the noise levels at 30 dormitories in three representative major urban universities in a major provincial capital city in China and designed and implemented a comprehensive questionnaire and surveyed 1005 students about their perceptions of their acoustic environment. We proposed and applied a sustainability–health-oriented, multidimensional assessment framework to assess the acoustic environment of the dormitories and student responses to natural sound, technological sounds, and human-made sounds. Using the Structural Equation Modeling (SEM) approach combined with the field measurements and student surveys, we identified three categories and six factors on student health and well-being for assessing the acoustic environment of university dormitories. The field data indicated that noise levels at most of the measurement points exceeded the recommended or regulatory thresholds. Higher noise impacts were observed in early mornings and evenings, primarily due to traffic noise and indoor activities. Natural sounds (e.g., wind, birdsong, water flow) were highly valued by students for their positive effect on the students’ pleasantness and satisfaction. Conversely, human and technological sounds (traffic noise, construction noise, and indoor noise from student activities) were deemed highly disturbing. Gender differences were evident in the assessment of the acoustic environment, with male students generally reporting higher levels of the pleasantness and preference for natural sounds compared to female students. Educational backgrounds showed no significant influence on sound perceptions. The findings highlight the need for providing actionable guidelines for dormitory ecological design, such as integrating vertical greening in dormitory design, water features, and biodiversity planting to introduce natural soundscapes, in parallel with developing campus activity standards and lifestyle during noise-sensitive periods. The multidimensional assessment framework will drive a sustainable human–ecology–sound symbiosis in university dormitories, and the category and factor scales to be employed and actions to improve the level of student health and well-being, thus, providing a reference for both research and practice for sustainable cities and communities. Full article

Circular deep excavations, characterized by their symmetrical geometry, are commonly employed in constructing foundations for large-span suspension bridges and as launching shafts for shield tunneling. However, the mechanical behavior of such excavations under asymmetric surface surcharge remains inadequately understood due to a paucity of relevant investigations. This study addresses this knowledge gap by establishing a three-dimensional finite element model (3D-FEA) based on the anchor deep excavation project of a specific bridge. The model is utilized to investigate the influence of asymmetric surcharge on the forces and deformations within the supporting structure. The results show that both the internal force and displacement cloud diagrams of the support structure exhibit asymmetric characteristics. The distribution of displacement and internal forces has spatial effects, and the maximum values all occur in the areas where asymmetric loads are applied. The maximum values of the displacement, axial force, and shear force of underground continuous walls increase with the increase in the excavation depth. The total displacement curves all show the feature of a “bulging belly”. The maximum displacement is 13.3 mm. The axial force is mainly compression, with a maximum value of −9514 kN/m. The maximum positive and negative values of the shear force are 333 kN/m and −705 kN/m, respectively. The bending moment diagram of different monitoring points shows the characteristics of “bow knot”. The maximum values of the positive bending moment and negative bending moment are 1509.4 kN·m/m and −2394.3 kN·m/m, respectively. The axial force of the ring beam is mainly compression, with a maximum value of −5360 kN, which occurs in ring beams 3, 4, and 5. The displacement cloud diagram of the support structure under symmetrical loads shows symmetrical characteristics. Under different load conditions, the displacement curve of the diaphragm wall shows the characteristics of “bulge belly”. The forms of loads with displacements from largest to smallest at the same position are as follows: asymmetric loads, symmetrical loads, and no loads. These findings provide valuable insights for optimizing the structural design of similar deep excavation projects and contribute to promoting sustainable urban underground development. Full article

This study examines diurnal surface temperature dynamics across major Moroccan cities during the growing season and explores the interaction between urban and vegetated surfaces. We also introduce the Urban Thermal Impact Ratio (UTIR), a novel metric designed to quantify urban thermal comfort as a function of the surface urban heat island (SUHI) intensity. The analysis is based on outputs from a land surface model (LSM) for the year 2010, integrating high-resolution Landsat and MODIS data to characterize land cover and biophysical parameters across twelve land cover types. Our findings reveal moderate urban–vegetation temperature differences in coastal cities like Tangier (1.8 °C) and Rabat (1.0 °C), where winter vegetation remains active. In inland areas, urban morphology plays a more dominant role: Fes, with a 20% impervious surface area (ISA), exhibits a smaller SUHI than Meknes (5% ISA), due to higher urban heating in the latter. The Atlantic desert city of Dakhla shows a distinct pattern, with a nighttime SUHI of 2.1 °C and a daytime urban cooling of −0.7 °C, driven by irrigated parks and lawns enhancing evapotranspiration and shading. At the regional scale, summer UTIR values remain below one in Tangier-Tetouan-Al Hoceima, Rabat-Sale-Kenitra, and Casablanca-Settat, suggesting that urban conditions generally stay within thermal comfort thresholds. In contrast, higher UTIR values in Marrakech-Safi, Beni Mellal-Khénifra, and Guelmim-Oued Noun indicate elevated heat discomfort. At the city scale, the UTIR in Tangier, Rabat, and Casablanca demonstrates a clear diurnal pattern: it emerges around 11:00 a.m., peaks at 1:00 p.m., and fades by 3:00 p.m. This study highlights the critical role of vegetation in regulating urban surface temperatures and modulating urban–rural thermal contrasts. The UTIR provides a practical, scalable indicator of urban heat stress, particularly valuable in data-scarce settings. These findings carry significant implications for climate-resilient urban planning, optimized energy use, and the design of public health early warning systems in the context of climate change. Full article

High-resolution remote sensing imagery plays an essential role in urban management and environmental monitoring, providing detailed insights for applications ranging from land cover mapping to disaster response. Semantic segmentation methods are among the most effective techniques for comprehensive land cover mapping, and they commonly employ ImageNet-based pre-training semantics. However, traditional fine-tuning processes exhibit poor transferability across different downstream tasks and require large amounts of labeled data. To address these challenges, we introduce Denoising Diffusion Probabilistic Models (DDPMs) as a generative pre-training approach for semantic features extraction in remote sensing imagery. We pre-trained a DDPM on extensive unlabeled imagery, obtaining features at multiple noise levels and resolutions. In order to integrate and optimize these features efficiently, we designed a multi-layer perceptron module with residual connections. It performs channel-wise optimization to suppress feature redundancy and refine representations. Additionally, we froze the feature extractor during fine-tuning. This strategy significantly reduces computational consumption and facilitates fast transfer and deployment across various interpretation tasks on homogeneous imagery. Our comprehensive evaluation on the sparsely labeled dataset MiniFrance-S and the fully labeled Gaofen Image Dataset achieved mean intersection over union scores of 42.7% and 66.5%, respectively, outperforming previous works. This demonstrates that our approach effectively reduces reliance on labeled imagery and increases transferability to downstream remote sensing tasks. Full article

The tandem tilt-wing UAV features an advanced aerodynamic layout design and is regarded as a solution for small-scale urban air mobility. However, the tandem wing configuration exhibits complex aerodynamic interactions between the front and rear wings during cruise flight and the wing tilt transition process. The objective of this paper is to investigate the aerodynamic coupling characteristics between the front and rear wings of the tandem tilt-wing UAV under level flight and tilt transition conditions while also assessing the influence of the propellers on the aircraft’s aerodynamic performance. Through CFD numerical analysis, the aerodynamic characteristics of various aircraft components are examined at different angles of attack and wing tilt angles, and the underlying reasons for the observed differences and variations are explored. The results indicate that, during level flight, the aerodynamic interference between the wings is primarily dominated by the detrimental influence of the front wing on the rear wing. During the tilt transition process, mutual interactions between the front and rear wings occur as wing tilt angle changes, leading to more drastic variations in lift coefficients and increased control difficulty. However, the propeller’s effect contributes to smoother changes in lift and drag, thereby enhancing aircraft stability. Full article