Search Results (294)

Against the global imperative to address climate change and accelerate energy transitions, the rapid growth of the electric vehicle (EV) industry has turned public charging infrastructure into a key foundation of urban operations, driven by carbon peaking and carbon neutrality goals. However, effective supply depends not only on scale but on deep association with urban functional spaces. This study compares Gusu District (a historic preservation district) and Industrial Park District (a new development district) in Suzhou. The goal is to reveal how public electric vehicle charging stations (EVCSes) associate with functional spaces under different urban development models. The study employs Standard Deviational Ellipse (SDE), Kernel Density Estimation (KDE), Bivariate Spatial Autocorrelation, and Coupling Coordination Degree (CCD) models to compare layout patterns, clustering features and functional association. The research findings are as follows: (1) The EVCS layout in Gusu District shows strong dependence on roads and administrative boundaries, while EVCSes in Industrial Park District show clear planning intervention, less constrained by its administrative boundary. (2) KDE analysis confirms that Gusu District has continuous clustering centered on the ancient city, but Industrial Park District shows a multi-center layout. (3) Bivariate Spatial Autocorrelation reveals different priorities in facility allocation. In Gusu District, spatial association is mainly driven by high-mobility nodes, while in Industrial Park District, EVCSes are more deeply embedded in social services and daily life scenarios. (4) CCD analysis reveals that the coordination in Gusu District forms a monocentric, spatially continuous gradient centered on the ancient city, whereas in Industrial Park District it displays a polycentric but fragmented pattern, with high coordination areas confined to planned cores. This comparative study reveals the EVCS spatial layout, which is shaped by both administrative boundaries and policy constraints, and the heterogeneity in spatial association between two districts. It provides scientific evidence and decision support for different spatial governance and facility optimization in various types of urban areas. Full article

Using the Suzhou East Station integrated transportation hub as a case study, this paper investigates the train-induced vibration responses and their distribution patterns under various operating conditions of high-speed railway lines, intercity lines, and subway lines. The results show that train speed is the dominant factor: the high-speed railway passage controls floor vibrations in most stories, while line distance also plays a role for some floors. No significant amplification is observed under multi-train convergence; the vibration level is similar to that of the most unfavorable single-train condition. Therefore, only the most unfavorable single-train condition needs to be considered. As vibrations propagate upward through the floors, high-frequency vibrations gradually attenuate while low-frequency vibrations are amplified, leading to an overall amplification of vibrations at the top floors of some buildings. The floor vibration response level decreases as the vertical stiffness of the structural member increases. Cantilevered slabs and mid-span areas are vibration-sensitive zones. For station–city integrated transportation hubs with high-speed railways running underneath, track vibration mitigation measures should be prioritized, such as thickening the track slab. Thin side-wall vibration mitigation pads have a poor vibration reduction effect. When diaphragm walls are rigidly connected to the station and buildings, they amplify the building’s vibration response. Full article

With increasing urban solid waste generation and the advancement of Zero Waste City initiatives, sanitation-facility siting has become central to urban waste governance but continues to trigger Not-In-My-Backyard (NIMBY) conflicts related to perceived environmental risk, spatial equity, and asset-value concerns. Existing studies often explain NIMBY effects through objective exposure or facility distance, while less attention has been paid to the mismatch between objective risk and residents’ subjective fear and its cost implications. Taking Suzhou, China, as a case study, we develop an integrated framework to assess NIMBY effects associated with current and planned sanitation facilities. An objective risk index is constructed based on facility hazard, exposure, and vulnerability. Resident questionnaires are used to measure subjective fear, and the bias between objective risk and subjective fear is quantified. Probit, hedonic price, and welfare models are then combined to evaluate the effects of this bias on facility support, housing prices, and marginal social welfare losses. The results show that (1) sanitation facilities in Suzhou present clear type differentiation and spatial clustering, with terminal treatment facilities mainly located on the urban periphery, and transfer, sorting, and recovery facilities more embedded in daily living spaces; (2) stronger subjective fear, particularly risk perception, significantly reduces residents’ support for facility expansion, especially under the planned scenario; (3) perception bias is negatively associated with housing prices and generates substantial marginal social welfare losses, especially when the planned expansion of facilities is considered at the system level. This study extends the explanatory framework of environmental NIMBY effects and provides evidence for integrating risk communication, spatial equity compensation, and marginal social welfare loss reduction into Zero Waste City governance. Full article

Building inclusive, high-density cities requires understanding vulnerable groups’ public space usage. While green exposure significantly impacts urban health, existing research frequently overlooks females’ specific needs regarding streetscape visual quality, green space structures, and daily travel experiences. To address this, the study investigates spatial disparities in Suzhou’s historic district. Utilizing multi-source data and mixed modeling strategies, including Partial Least Squares and Ordinary Least Squares (PLS-OLS) and eXtreme Gradient Boosting (XGBoost), the research analyzes how streetscape perceptions and green space characteristics affect female life satisfaction and expressed sentiment. Results indicate three main findings. (1) Streetscape visual features fundamentally drive subjective evaluations. Safe significantly enhances well-being, whereas boring and lively negatively impact life satisfaction, reflecting females’ acute sensitivity to environmental oppressiveness during daily travel. (2) Park diversity elevates expressed sentiment, while patch density positively influences life satisfaction, demonstrating the vital value of fragmented greenery for daily public space usage. (3) Boring precipitously diminishes life satisfaction after surpassing a specific threshold, while park diversity elevates expressed sentiment only after crossing a critical interval. The study establishes an integrated analytical framework linking visual perception, green space structure, emotional response, and satisfaction. These findings provide targeted strategies for enhancing inclusive urban design and optimizing green space allocation to improve streetscape safety and alleviate visual oppressiveness, thereby advancing gender social justice for vulnerable groups in historic districts. Full article

Objective: Rapid vertical manoeuvres and intermittent vibration in autonomous electric vertical take-off and landing (eVTOL) aircraft can provoke pronounced psychological anxiety in passengers. To address this, we propose a closed-loop adaptive system that integrates an in-ear wearable sensor with dynamic regulation of the cabin microenvironment, enabling real-time monitoring of each passenger’s autonomic state and delivering individualised mitigation through a continuous sense–analyse–intervene–feedback loop. Methods: The system is built around a pair of custom in-ear modules that integrate dual-wavelength photoplethysmography (PPG; 525 nm green and 940 nm infrared), galvanic skin response (GSR), and a six-axis inertial measurement unit (IMU) sampled at 200 Hz. To suppress the 20–80 Hz vibration generated by the distributed electric propulsion system, a compliant silicone damping sleeve attenuates high-frequency components at the hardware level, while a Kalman filter fuses the IMU and PPG streams and an adaptive notch filter removes residual rotor harmonics. The pipeline raises the heart-rate-variability (HRV) signal-to-noise ratio (SNR) to 24.1 dB, with a Pearson correlation of 0.96 against a medical-grade chest strap. A hybrid CNN–LSTM network—two convolutional layers (32 filters each) followed by two LSTM layers (128 hidden units)—predicts impending anxiety from HRV time-domain features (RMSSD, pNN50) and frequency-domain features (LF/HF ratio), triggering intervention 8.2 s in advance on average. According to the predicted anxiety level (mild/moderate/severe), a fuzzy controller modulates transcutaneous auricular vagus nerve stimulation (1–5 mA), the binaural-beat frequency (4–8 Hz, theta band), and the cabin lighting colour temperature (2700–6500 K) in real time. The intervention parameters are continuously refined by SPSA-based stochastic optimisation of the HRV recovery rate (step size 0.01; updated every 30 s). Results: In a randomised controlled experiment conducted in a simulated flight environment (N = 50; aged 22–45 years; 1:1 sex ratio), the active group reached physiological recovery in 52.3 s on average, compared with 98.6 s for the sham-controlled group—a 47% reduction (Cohen’s d = 1.24, p < 0.001). User acceptance reached 94%. Conclusions: The proposed in-ear platform enables closed-loop adaptive regulation of anxiety in the eVTOL cabin and overcomes the limitations of conventional passive mitigation strategies. By combining vibration-tolerant physiological sensing with multimodal environmental control, the work offers a practical pathway for improving passenger experience in urban air mobility and provides a useful reference for human-factors standards governing autonomous aircraft. Full article

Under the dual pressures of heritage conservation and tourism growth, improving inclusive access to cultural tourism opportunities in historic urban areas has become an urgent planning issue under Sustainable Development Goal 11 and the Historic Urban Landscape approach. Taking the central urban area of Suzhou, China, as a case study, this study evaluates time-budgeted walkable accessibility, spatial equity, local mismatch, and accessibility-generating conditions from a 15 min city perspective. An integrated analytical framework was developed by combining kernel density analysis, GIS-based network accessibility modelling, Lorenz–Gini equity assessment, bivariate Local Indicators of Spatial Association (LISA), and XGBoost–SHAP interpretation. The results show that cultural tourism opportunities exhibit a clear core polarisation–peripheral attenuation pattern. Within the 15 min threshold, Gusu District records SACR and AAR values of 80.18% and 95.23%, respectively, indicating a pronounced historic-core accessibility advantage. Accommodation-tier differences do not form a simple monotonic relationship with accessibility, but are shaped by the spatial embedding of different accommodation-market segments within the cultural tourism opportunity field. HL units, namely high-tier accommodation near low accessibility, emerge as priority diagnostic areas of local mismatch, while delayed accessibility beyond 30 min becomes particularly evident among elderly visitors. The SHAP interpretation further indicates that leisure-strolling attractions show a more balanced supply–accommodation structure, whereas commercial–cultural mixed and heritage-core attractions are more strongly supply-led. By linking accessibility measurement, equity assessment, local mismatch diagnosis, and mechanism-based explanation, this study provides an operational basis for zonal and typology-oriented optimisation of cultural tourism accessibility in historic urban areas. Full article

Generative AI (GenAI) is increasingly embedded in higher education, yet evidence on its implications for students’ academic engagement and psychological experiences remains mixed. One possible reason is that prior research has often focused on how much students use AI and their general confidence in task completion, while paying less attention to how they use AI and how they attribute AI-supported achievement. To address this gap, this study distinguishes reflective from thoughtless AI use, examines academic impostor syndrome as a self-evaluative mechanism linking AI use styles to academic engagement, and tests perceived AI policy clarity as a contextual moderator. A two-wave survey of 478 Chinese university students showed that reflective AI use was negatively associated with academic impostor syndrome, whereas thoughtless AI use showed the opposite pattern. Academic impostor syndrome, in turn, was negatively associated with engagement and mediated both pathways. Perceived AI policy clarity amplified these patterns. These findings suggest that GenAI integration should be understood not only as a question of adoption or efficiency, but also of interaction quality and competence attribution. The study highlights the importance of cultivating reflective AI literacy and developing institutional policies that are clear yet psychologically attuned to students’ self-evaluative concerns. Full article

The digital economy (DE) is increasingly associated with higher carbon productivity (CP) and is widely regarded as an important factor in efforts to achieve the dual-carbon goals. However, the formulation of differentiated policies is constrained by a limited understanding of the multi-factor collaborative mechanisms and their asymmetric configurational pathways. This study combines the GMDH algorithm with the fsQCA approach to explore the multiple sufficient paths for high carbon productivity. Through feature selection and nonlinear modeling, the GMDH algorithm identifies five key variables associated with CP: the industrial robot permeability, software business development, digital innovation input, the usage depth of digital finance, and mobile communication facilities. The fsQCA method reveals that three configurational pathways consistent with higher levels of CP: the “innovation and finance-driven model” represented by Sichuan and Hunan, the “innovation-assisted digital industrialization model” represented by Henan and Hebei, and the “industry digitalization first developing model” represented by Jiangxi, Guangdong, Zhejiang, and Shanghai. Considering the uneven regional development across China, this study further categorizes provinces into four regional development types: innovation and finance-driven, digital industry empowerment, industrial digitalization leadership, and potential cultivation. Correspondingly, tailored policy recommendations are proposed for each region, providing practical insights consistent with the observed configurational patterns for improving CP in the context of DE development. Full article

In mechanical material evaluation and biomechanical studies, Young’s modulus is commonly used to describe the elastic response of materials. Existing measurement approaches are mainly based on contact loading or large-scale experimental instruments, which may limit excitation controllability and system integration in practical applications. In this work, a Young’s modulus measurement system based on electromagnetic excitation and capacitive sensing is designed and experimentally implemented. The system is composed of an electromagnetic driving unit and a capacitive sensing unit. In the driving unit, a coaxial copper wire coil is arranged with a ring-shaped neodymium–iron–boron permanent magnet assembly. When a square-wave electrical signal is applied, the coil generates a Lorentz force, which produces transient mechanical excitation on the tested sample. The resulting micro-scale deformation of the material surface is monitored using a coaxial passive capacitive sensor. The sensor records the relative capacitance variation (ΔC/C₀) induced by deformation during excitation. Based on the measured capacitance response, a force–capacitance coupling model is established to relate the electrical signal to the mechanical behavior of the material, enabling the inverse calculation of Young’s modulus. Commercial standard hardness blocks were used for system calibration and performance verification. The experimentally obtained Young’s modulus values are consistent with reference data within an acceptable deviation range, indicating that the proposed system can be used for quantitative evaluation of elastic properties. Due to its compact configuration and controllable excitation, the system is suitable for non-invasive surface mechanical characterization of soft materials, including biological tissues. Full article

Transformers are key devices in the new electricity system, and the entire life cycle is associated with a considerable resource consumption and carbon footprint (CF). Understanding CF is essential for accelerating the low-carbon transition of the industry. Therefore, a systematic CF model for transformers is constructed in this study based on life cycle assessment (LCA). The results indicate that the operation stage is the overwhelmingly dominant phase for CF of transformer, with electricity acting as the main carbon source. The CF at the raw-material stage mainly originates from steel and copper. Through analysis, eight key impact factors were identified, leading to the formulation of three-dimensional carbon reduction pathways. It was observed that a 10% reduction in total losses of a transformer results in an approximate 10% decline in CF. At the same time, the transition of the electricity grid to clean energy helps reduce CF during operation. In addition, the effectiveness of a multi-factor carbon reduction pathway was examined. The results showed that, under this integrated pathway, the CF across all transformer rated voltages could be reduced by 9.75%. Based on this, a system pathway centered on enhancing operational energy efficiency is proposed, supported by green materials and processes, and coordinated through smart operation and maintenance, and circular recycling. This provides quantitative evidence and decision support for the green transition of transformers, contributing to the broader goals of sustainability development in electricity system. Full article

Ongoing urbanization continuously reshapes water quality, habitat structure, and biological communities in river ecosystems; however, its impacts on host-associated microbial communities remain poorly documented. The fish gut microbiota, a critical interface between the aquatic environment and host physiology, is widely recognized as an integrative indicator of both environmental change and host ecological traits. This study established a continuous urbanization gradient along Shanghai’s Suzhou River, spanning from suburban areas through the outer and inner ring roads to the city center. Five common wild fish species (Coilia nasus, Hemiculter bleekeri, Culter alburnus, Acheilognathus macropterus, and Pseudorasbora parva) were collected, and their gut microbiota were characterized via high-throughput 16S rRNA gene sequencing. Significant variation in OTU richness, alpha diversity, and community structure was observed across urbanization gradients and among fish species. Principal coordinate analysis revealed that samples from suburban areas were structurally distinct from those collected in other zones, whereas inner-ring and urban-core areas exhibited substantial compositional overlap. Taxonomic analysis revealed that Firmicutes and Pseudomonadota dominated all samples; however, their relative abundances and genus-level composition varied considerably among fish species and across the urbanization gradient. PICRUSt-based functional prediction indicated that metabolic pathways predominated, particularly those involved in global and overview maps, carbohydrate metabolism, amino acid metabolism, energy metabolism, and metabolism of cofactors and vitamins. Collectively, these findings demonstrate that fish gut microbial communities exhibit spatial structuring along the urbanization gradient, with species-specific responses linked to ecological traits. This study provides valuable data on host-associated microbial communities in urban rivers and offers a reference for incorporating microbial indicators into urban water ecological assessments. Full article

Rapid urbanization has intensified urban surface thermal stress, yet how blue–green spaces (BGs) are associated with land surface temperature (LST) under different urban morphological contexts remains insufficiently understood. Using Suzhou, China, as a case study, this study integrates Landsat imagery from five representative years (2000, 2005, 2010, 2016, and 2022) with a 100 m local climate zone (LCZ) dataset to examine BGs–LST relationships over time. Two BGs indicators are considered: BGs proportion and the within-grid local dispersion of BGs, represented by BGs_std. The results show that LST in Suzhou’s built-up area exhibits a “rise–decline–rise” pattern during the study period, whereas BGs proportions evolve differently across LCZ types. Regression slope analysis shows that higher BGs proportion is generally associated with lower LST across most LCZ types and study years. Relatively stable negative associations are observed in LCZ 2, LCZ 3, LCZ 6, LCZ 9, and LCZ 10. Pearson correlation analysis further shows that BGs_std is generally positively associated with LST and that this relationship tends to strengthen over time. Relatively stronger associations are observed in LCZ 1, LCZ 3, LCZ 5, and LCZ 6 in some years. These findings suggest that BGs–LST relationships should be interpreted not only in terms of BGs proportion, but also in relation to urban form and within-unit BGs organization. This study provides an LCZ-based empirical perspective on BGs–LST associations in the context of a rapidly urbanizing city. Full article

Rapid urbanization increasingly threatens urban cultural heritage. While buffer zones are crucial for mitigating external pressures, conventional delineation relies on value-based or geometric rules, overlooking parcel-scale heterogeneous externalities. This study addresses this gap by proposing a parcel-based, risk–value coupling framework that delineates heritage buffer zones and supports differentiated land-use regulations. In this study, “negative-impact risk” is operationalized as a composite proxy of cumulative urban development pressures that may increase the likelihood and potential severity of adverse externalities on heritage settings, rather than a full hazard–exposure–vulnerability risk model. And we construct a multi-source indicator system with 12 parcel-level indicators to characterize negative impact risk and heritage value, and adopt a hybrid weighting strategy integrating an AHP, entropy weighting, and game-theoretic combination to reconcile expert judgement and data-driven heterogeneity. To address uncertainty in multi-criteria evaluation, a cloud model maps indicator sets into discrete management levels. The framework is applied to the Pingjiang Historic District in Suzhou, China, using 121 land parcels as decision units. Results show that the approach identifies spatial risk–value patterns and delineates an operational buffer prioritizing parcels with elevated coupled scores. Compared with a fixed-distance buffer, it achieves greater coverage of high-risk parcels while maintaining a smaller regulatory scope. The parcel classification is then translated into tiered planning controls, including development intensity limits, land-use rules, and monitoring priorities. The framework integrates risk management and heritage conservation to support uncertainty-aware, proactive, and transferable zoning decisions. Full article