Search Results (4,045)

Port resilience performance (PRP) is a critical factor in advancing the sustainable development of the 21st Century Maritime Silk Road (MSR). The Environmental, Social, and Governance (ESG) framework, widely recognized as a cornerstone of global sustainability efforts, offers a robust foundation for enhancing PRP. This study employs a system dynamics (SD) approach to explore the impact of ESG on PRP along the MSR. By developing an ESG evaluation index system and a resilience assessment framework, the research examines the mechanisms and evolutionary patterns through which ESG influences port resilience. Simulations are conducted for four strategic ports: Chattogram Port, Singapore Port, Gwadar Port, and Djibouti Port. The findings reveal that ESG initiatives significantly enhance PRP, with Singapore Port exhibiting the most stable and rapid resilience improvement. In contrast, the other ports demonstrate varying levels of adaptation and enhancement. Among the intervention strategies, prioritizing social dimension (S) improvements proves most effective for achieving rapid short-term resilience gains. This study offers both theoretical insights and practical strategies for strengthening port resilience and fostering sustainable development along the MSR. Full article

This study focuses on exploring the differences in driving abilities in emergency traffic situations between older drivers (aged 60–70) and young drivers (aged 20–35) in a simple traffic environment. Two typical emergency scenarios were designed in the experiment: Scenario A (intrusion of electric bicycles) and Scenario B (pedestrians crossing the road). The experiment employed a driving simulation system to synchronously collect data on eye movement characteristics, driving behavior, and physiological metrics from 30 drivers. Two-factor covariance analysis, correlation analysis, and regression analysis were conducted on the experimental data. The comprehensive study results indicated that the older group exhibited better driving performance in emergency scenarios compared to the younger group. Specifically, in Scenario A, the older group had a faster first fixation time on the AOI compared to the younger group, a faster braking reaction time, a higher maximum brake pedal depth, and a higher skin conductance level. In Scenario B, the older group’s driving performance was similar to that in Scenario A, with better performance than the younger group. The study reveals that in some simple driving tasks, young-old drivers (60–70 years) can compensate for their physiological decline through self-regulation and self-restraint, thereby exhibiting safer driving behaviors. Full article

This study investigates the perception of postural discomfort experienced by passengers seated in the middle rear seat of a vehicle—an area often overlooked in ergonomic research. A total of 20 participants (12 males and 8 females) were involved in a pilot test using two car models: a City Car (Fiat Panda) and a C-SUV (Renault Arkana). Each participant completed a short on-road ride (~24 min, 11.7 km) in both vehicles. Discomfort was assessed using a 5-point Likert scale, considering both overall and localized body discomfort, as well as other elements/factors, such as those involved in the human–car interaction (e.g., the central tunnel, the headrest, AC vents, and other passengers). The results showed that overall discomfort was significantly higher in the City Car (mean: 3.75 ± 0.72) compared to the SUV (mean: 3.00 ± 1.16). The most affected body regions in the City Car were the arms (mean: 3.95), knees (3.90), and legs/feet (3.55). In the SUV, discomfort was lower across all regions, with the arms (3.15) and knees (3.05) still being notably impacted. Strong correlations were observed between discomfort and several vehicle features: backrest width, headrests, interference with adjacent passengers, and rear air conditioning vents. This study highlights specific ergonomic issues in the middle rear seat and suggests design improvements, including wider backrests and headrests, repositioned air vents, and the inclusion of lateral supports. These findings offer actionable insights for automotive manufacturers to enhance passenger comfort in multi-passenger configurations. Full article

To address the negative sample selection bias and limited interpretability of traditional debris-flow event susceptibility models, this study proposes a framework that enhances generalization by integrating negative sample screening via a stacking ensemble model with an interpretable random forest. Using Wenchuan County, Sichuan Province, as the study area, 19 influencing factors were selected, encompassing topographic, geological, environmental, and anthropogenic variables. First, a stacking ensemble—comprising logistic regression (LR), decision tree (DT), gradient boosting decision tree (GBDT), and random forest (RF)—was employed as a preliminary classifier to identify very low-susceptibility areas as reliable negative samples, achieving a balanced 1:1 ratio of positive to negative instances. Subsequently, a stacking–random forest model (Stacking-RF) was trained for susceptibility zonation, and SHAP (Shapley additive explanations) was applied to quantify each factor’s contribution. The results show that: (1) the stacking ensemble achieved a test-set AUC (area under the receiver operating characteristic curve) of 0.9044, confirming its effectiveness in screening dependable negative samples; (2) the random forest model attained a test-set AUC of 0.9931, with very high-susceptibility zones—covering 15.86% of the study area—encompassing 92.3% of historical debris-flow events; (3) SHAP analysis identified the distance to a road and point-of-interest (POI) kernel density as the primary drivers of debris-flow susceptibility. The method quantified nonlinear impact thresholds, revealing significant susceptibility increases when road distance was less than 500 m or POI kernel density ranged between 50 and 200 units/km²; and (4) cross-regional validation in Qingchuan County demonstrated that the proposed model improved the capture rate for high/very high susceptibility areas by 48.86%, improving it from 4.55% to 53.41%, with a site density of 0.0469 events/km² in very high-susceptibility zones. Overall, this framework offers a high-precision and interpretable debris-flow risk management tool, highlights the substantial influence of anthropogenic factors such as roads and land development, and introduces a “negative-sample screening with cross-regional generalization” strategy to support land-use planning and disaster prevention in mountainous regions. Full article

Accurate prediction of geological hazard susceptibility forms the foundation of effective risk management, yet small-sample constraints often limit model generalization. In order to address this issue, this study applied an ensemble method based on predictive symmetry quantification, using Mount Tai, China, as a test case. Thirteen influencing factors were integrated using six machine learning algorithms—Logistic Regression (LR), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGB), and Support Vector Machine (SVM)—trained on 34 hazard sites. Symmetry breaking in model outputs was quantified, and XGB and MLP, which showed the lowest correlation (0.59), were selected for dynamic weighted integration. Symmetry-adjusted weighting counteracts bias from individual models. For hyperparameter tuning, grid search was employed, while SHapley Additive exPlanations (SHAP) was used to quantify factor contributions. The performance of each model was evaluated using AUC and AP metrics. The key results show that all base models performed robustly (AUC > 0.8), with XGB showing high consistency (AUC = 0.927), and the performance of the symmetry-optimized ensemble (MLP + XGB) exceeded that of all the individual models (AUC = 0.964). The dominant drivers of Geohazards included elevation, slope, the topographic wetness index, and road adjacency, with high-susceptibility zones clustered in southeastern high-altitude terrain, central mountains, and road-intensive north-central sectors. The approach presented here provides an ensemble method based on predictive symmetry quantification that is effective under the constraints of small sample sizes. Full article

Trees play a vital role in supporting biodiversity, particularly in regions where human demand for resources is increasing and many species are experiencing population decline. Native orchids, especially those that are endemic, are particularly vulnerable to population decreases in biodiversity hotspot areas, with anthropogenic factors playing an increasingly significant role in this trend. A substantial portion of the northern district of Kerala, situated in southern India, falls within the biodiversity hotspot of the Western Ghats. The road network traversing the Western Ghats provides refuge for native orchids on various tree species. The present study examined a 60 km perimeter area encompassing 15 different sites located near small towns and built-up areas, regions where trees have already been lost due to settlement and infrastructure development. These roadside areas are lined with a mixture of native and exotic trees, including both naturally recruited fruit trees and exotic species. Approximately 600 trees, representing 72 different tree taxa, were recorded from the sampled areas in Wayanad. Nearly 10,000 orchids encompassing 13 species were observed, with 6 of these species, constituting 46%, being endemic to the region. This study revealed variations between sites, with some locations exhibiting high diversity and abundance of both trees and orchids. The diversity and abundance of native orchids, risks, and prospects of development mitigation are discussed in detail. Full article

In the realm of urban vehicular ad hoc networks (VANETs), cross-domain data has constituted a multifaceted amalgamation of information sources, which significantly enhances the accuracy and response speed of traffic prediction. However, the interplay between spatial and temporal heterogeneity will complicate the complexity of geographical locations or physical connections in the data normalization. Besides, the traffic pattern differences incurred by dynamic external factors also bring cumulative and sensitive impacts during the construction of the prediction model. In this work, we propose the spatio-temporal heterogeneity-oriented graph convolutional network (SHGCN) to tackle the above challenges. First, the SHGCN analytically employs spatial heterogeneity between urban streets rather than simple adjacency relationships to reveal the spatio-temporal correlations of traffic stream movement. Then, the air quality data is taken as external factors to identify the traffic forecasting trend at the street level. The hybrid model of the graph convolutional network (GCN) and gated recurrent unit (GRU) is designed to investigate cross-correlation characteristics. Finally, with the real-world urban datasets, experimental results demonstrate that the SHGCN achieves improvements, with the RMSE and MAE reductions ranging from 2.91% to 41.26% compared to baseline models. Ablation studies confirm that integrating air quality factors with traffic patterns enhances prediction performance at varying degrees, validating the method’s effectiveness in capturing the complex correlations among air pollutants, traffic flow dynamics, and road network topology. Full article

The impact of cycling-related traffic crashes on public health has increased significantly in recent decades, with cyclists being among the most vulnerable road users. The risk of severe injury in traffic crashes is notably high for cyclists, especially when distracted. Research indicates that distraction while cycling significantly increases the crash risk. This study investigates cycling distraction through a field operational test involving 100 participants. Riders followed a predetermined course while being exposed to external visual and auditory stimuli, including alarms, advertising signs, and car horns. Distraction levels were measured using eye-tracking technology. Data were analyzed by means of descriptive statistics, cluster, and correlation analyses. Our findings showed that auditory stimuli distract a higher percentage of cyclists, while audiovisual stimuli from road-related factors cause longer-lasting distractions. Additionally, five distraction clusters were identified based on stimulus duration. Lastly, it was found that males were more likely to belong to high-distraction clusters, whereas females and daily cyclists were more likely to fall into the lowest-distraction group. Full article

Identification of causal factors in traffic crashes has always been a significant challenge in road safety studies. Traditional crash prediction models are limited in elucidating the underlying causal mechanisms in road crashes. This research explores the application of three graphic models, namely, the Gaussian graphical model (GGM), causal Bayesian network (CBN) and graphic extreme gradient boosting (XGBoost), through a case study using highway–railroad-grade crossing (HRGC) inventory and collision data from Canada. The three modelling approaches have generally yielded consistent findings on various risk factors such as crossing control type, track angle, and exposure, showing their potential for identifying causal relationships through the interpretation of causal graphs. With the ability to make better causal inferences from crash data, the effectiveness of safety countermeasures could be more accurately and reliably estimated. Full article

Atmospheric pollution constitutes one of the key environmental challenges hindering Atmospheric pollution is a key environmental challenge constraining the sustainable development of Gansu Province’s land-based Belt and Road corridor and its regional ecological barrier function. The spatiotemporal heterogeneity of aerosol optical depth (AOD) profoundly impacts regional environmental quality. Based on MODIS AOD, NCEP reanalysis, and emission data, this study employed trend analysis (Mann–Kendall test) and attribution analysis (multiple linear regression combined with LMG and Spearman correlation) to investigate the spatiotemporal evolution of AOD over Gansu Province during 2009–2019 and its meteorological and emission drivers. Key findings include the following: (1) AOD exhibited significant spatial heterogeneity, with high values concentrated in the Hexi Corridor and central regions; monthly variation showed a unimodal pattern (peak value of 0.293 in April); and AOD generally declined slowly province-wide during 2009–2019 (52.8% of the area showed significant decreases). (2) Following the implementation of the Air Pollution Prevention and Control Action Plan in 2013 (2014–2019), AOD trends stabilized or declined in 99.8% of the area, indicating significant improvement. (3) Meteorological influences displayed distinct regional-seasonal specificity—the Hexi Corridor (arid zone) was characterized by strong negative correlations with relative humidity (RH2) and wind speed (WS) year-round, and positive correlations with temperature (T2) in spring but negative in summer in the north; the Hedong region (industrial zone) featured strong positive correlations with planetary boundary layer height (PBLH) in summer (r > 0.6) and with T2 in spring/summer; and the Gannan Plateau (alpine zone) showed positive WS correlations in spring and weak positive RH2 correlations in spring/autumn, highlighting the decisive regulatory role of underlying surface properties. (4) Emission factors (PM_2.5, ${\mathrm{SO}}_4^{2-}$, ${\mathrm{NO}}_3^{-}$, ${\mathrm{NH}}_4^{+}$, OM, and BC) dominated (>50% relative contribution) in 80% of seasonal scenarios, prevailing in most regions (Hexi: 71–95% year-round; Hedong: 68–80% year-round; and Gannan: 69–72% in spring/summer). Key components included BC (contributing > 30% in 11 seasons, e.g., 52.5% in Hedong summer), ${\mathrm{NO}}_3^{-}$ + ${\mathrm{NH}}_4^{+}$ (>57% in Hexi summer/autumn), and OM (20.3% in Gannan summer, 19.0% province-wide spring). Meteorological factors were the primary driver exclusively in Gannan winter (82%, T2-dominated) and province-wide summer (67%, RH2 + WS-dominated). In conclusion, Gansu’s AOD evolution is co-driven by emission factors (dominant province-wide) and meteorological factors (regionally and seasonally specific). Post-2013 environmental policies effectively promoted regional air quality improvement, providing a scientific basis for differentiated aerosol pollution control in arid, industrial, and alpine zones. Full article

This research examines road users’ willingness to pay for enhanced active mobility infrastructure at King Mongkut’s Institute of Technology Ladkrabang (KMITL), a suburban university campus in Bangkok, Thailand. The study addresses the need for sustainable transportation solutions in middle-income urban environments by analyzing factors that influence walking and cycling adoption among university community members. The research employed a comprehensive mixed-methods framework combining qualitative SWOT analysis, a stated preference survey of 400 participants, and regularized logistic regression modeling with cross-validation. The analysis revealed that specific infrastructure improvements significantly increase the likelihood of active mobility adoption. Rest areas demonstrated the strongest positive association (OR = 2.15, 95% CI: 1.08–4.27, p = 0.029), followed by CCTV security systems (OR = 1.89, 95% CI: 0.98–3.65, p = 0.047), and improved public transport connectivity (OR = 2.84, 95% CI: 1.42–5.68, p = 0.003). Demographic analysis uncovered notable resistance patterns, with male participants (OR = 0.48, 95% CI: 0.26–0.89, p = 0.020) and higher-income individuals showing reduced willingness to transition from motorized transportation. Using the Contingent Valuation Method with proper bias mitigation strategies, the study quantified potential behavioral changes, projecting a 12–18 min daily increase in active mobility engagement. This enhancement would generate measurable health benefits valued at 2840–4260 THB per person annually using WHO-HEAT methodology. The research contributes valuable insights to the limited body of active mobility literature from Southeast Asian suburban contexts, providing a replicable framework for similar investigations. Full article

The shear strength parameters of landslide zones are the necessary data basis for landslide stability evaluation and landslide surge disaster chain research. It is important to determine the physical and mechanical parameters of landslide zones scientifically and reasonably. In this study, four small residual landslide deposits near the Hei Duo Village road in Diebu County, Gansu Province, were investigated. The research involved detailed field investigations, the construction of landslide engineering geological models, and the use of the transfer coefficient method for simultaneous/inverse inversion and sensitivity analysis of the strength parameters of the four landslides. Based on the inversion results, an analysis of the landslide formation mechanism was conducted. The inversion results yielded the shear strength parameters of the sliding surface soil as c = 30.12 kPa and φ = 21.08°. It was found that the excavation at the base of the slope is the direct triggering factor for the landslides, with the 3# landslide being the most affected by the base excavation. In terms of the type of movement, all four landslides belong to the retrogressive landslide, with the maximum shear strain increment mainly concentrated at the slope angle after excavation. The slope body experiences shear failure, which is in good agreement with the field conditions. The study provides reference for stability prediction and disaster prevention and control of reservoir bank slope. Full article

This paper analyzed the current development status of the economy, transportation, and ecology in Xi’an and constructed a coupling coordination evaluation index system. Employing the entropy weight method to determine indicator weights, it adopted the coupling coordination degree model and the obstacle degree model to examine the coupling coordination development level of the three subsystems and identified key obstacle factors at the criterion layer and the indicator layer. The results showed the following: (1) From a temporal perspective, the coordination degree among the three subsystems in Xi’an increased significantly from 0.217 in 2013 to 0.712 in 2023. Its coupling coordination development level showed a steady evolutionary trend, evolving from “Moderately Imbalanced” to “Moderately Coordinated;” (2) The comprehensive ranking of the obstacle degrees of the three system layers was as follows: from 2013 to 2017, economy > transportation > ecology; in 2018, ecology > economy > transportation; in 2019, ecology > transportation > economy; from 2020 to 2023, transportation > ecology > economy; (3) The top five in the ranking of obstacle degree calculation results at the indicator layer were as follows in sequence: investment in environmental pollution control, built forestry areas, road passenger turnover, highway density, and length of highways; (4) The key obstacle factors at the indicator layer exhibited an evolutionary trend of “economic dominance → transportation dominance → interweaving of ecology and transportation.” Ultimately, it proposed corresponding implementation paths, aiming to promote the collaborative development of economic growth model innovation, green transformation of transportation, and ecological protection. Full article

With the increasing requirements for speed and travel distance in tracked vehicles on various terrains and the increasing mass ratio of powertrains, the vibration problem of high-power powertrains becomes a critical challenge. In this paper, in order to reflect on the vibration transmission relationship between the powertrain and the complex carrier, the magnetorheological damping system of a powertrain is studied in a whole vehicle model. The transfer matrix and equations of each component, including the magnetorheological mount, are derived by the Rui Method. Then, the electromechanical coupling multibody dynamic model of the vehicle–powertrain magnetorheological damping system is established. Consequently, the fast solution of vehicle–powertrain vibration characteristics under various road excitations is realized. The dynamic and static coupling characteristics of the powertrain system and the factors affecting its performance are analyzed in a moving vehicle. The simulation results indicate that the vibration reduction performance is the worst in the X-direction, whereas the vibration reduction performance is the best in the Y-direction. Under the E-class road condition at 10 m/s, the RMS acceleration reduction in the powertrain is 41.63% in the Y-direction relative to the chassis. Both the resonant frequency of the powertrain and chassis are 86.93 Hz in the Y-direction. Finally, the accuracy of the results is verified by simulation and driving experiments. The research results can provide theoretical guidance for the design and optimization of the powertrain mount of a tracked vehicle. Moreover, it provides a new technical means of studying the vibration characteristics of a complex multibody system. The simulation results demonstrate notable directional variations in the vibration attenuation performance of the powertrain damping system. Specifically, the X-direction shows the poorest vibration attenuation, whereas the Y-direction exhibits the best damping characteristics. Full article

This paper presents an assessment of the impact of maintenance of a road lighting luminaire with a high-pressure sodium lamp and an LED luminaire on the lighting parameters on the road and the energy efficiency of the entire road lighting installation. Improper maintenance of road lighting installations, especially of luminaires, can significantly worsen road traffic safety. In addition, after performing maintenance activities, e.g., after replacing a lamp in the luminaire, the energy consumption of the road lighting installation can increase. Both active and reactive energy can increase. Using the examples of a road luminaire with a high-pressure sodium lamp and an LED luminaire, it was shown that such a phenomenon can occur. An assessment of maintenance in terms of energy performance indicators was performed for the luminaire using the indicators described in the lightning standard and those proposed by the authors of this paper. This approach allows for a comprehensive assessment of maintenance on energy performance indicators—energy efficiency. Full article