Search Results (635)

Station-level ridership is an important indicator for understanding the relationship between land use and rail transit, which is crucial for building more sustainable urban mobility systems. However, the nonlinear effects of the built environment on metro ridership, particularly concerning temporal heterogeneity, have not been adequately explained. To address this gap, this study proposes a versatile methodology that employs the eXtreme gradient boosting (XGBoost) tree to analyze the effects of factors on station-level ridership variations and compares these results with those of a multiple regression model. In contrast to conventional feature interpretation methods, this study utilized Shapley additive explanations (SHAP) to detail the nonlinear effects of each factor on station-level ridership across temporal dimensions (weekdays and weekends). Using Shanghai as a case study, the findings confirmed the presence of complex nonlinear and threshold effects of land-use, transportation, and station-type factors on station-level ridership in the association. The factor “Commercial POI” represents the most significant influence on ridership changes in both the weekday and weekend models; “Public Facility Station” plays a role in increasing passenger flow in the weekend model, but it shows the opposite effect on the change in ridership in the weekday model. This study highlights the importance of explainable machine learning methods for comprehending the nonlinear influences of various factors on station-level ridership. Full article

Smart meters monitor hourly water consumption patterns while reducing the cost and inconvenience of traditional meters. This study comprehensively analyzes 1871 households that previously used traditional meters from the distribution point to the distribution area. All the households were equipped with smart meters and the data collected were used for analysis. On the basis of the total estimated water consumption, 227 households were classified as single households. These households were further classified into single-worker and -nonworker households. This study analyzed smart meter data to evaluate the timings and amounts of water consumption peaks. The results indicate that worker households peaked at 8:00, with 29 L/h of consumption on weekdays, and peaked again on evenings at 20:00–21:00, averaging 32 L/h. For nonworker households, the peak occurred at 9:00, with 20 L/h, with no major changes in the afternoon, and a second peak occurred at 19:00–20:00 in evening, with an average of 19 L/h. Moreover, worker households peaked at 8:00 and 20:00 on weekdays, and at 9:00 and 19:00 on weekends. It was revealed that worker households consume 10% more on weekends than on weekdays, and 262% more from 13:00 to 16:00. These findings may assist in water supply planning by supporting distribution schedules on the basis of peak household consumption, leading to more helpful resource management. Full article

This paper uses smart card data from Melbourne’s public transport network to model and evaluate the impacts of a flexible on-demand transport system. On-demand transport is an emerging mode of urban passenger transport that relies on meeting passenger demand for travel using dynamic and flexible scheduling using shared vehicles. Initially, a simulation model was developed to replicate existing fixed-schedule bus performance and was then extended to incorporate on-demand transport services within the same network. The simulation results were used to undertake a comparative analysis which included reliability, service quality, operational efficiency, network-wide effectiveness, and environmental impacts. The results showed that on-demand buses reduced average passenger trip time by 30%, increased vehicle occupancy rates from 8% to over 50%, and reduced emissions per passenger by over 70% on an average weekday compared to fixed-schedule buses. This study also offers insights for successful on-demand transport implementation, promoting urban sustainability. It also outlines future research directions, particularly the need for accurate short-term passenger demand prediction to improve service provision and passenger experience. Full article

The dynamic distribution of urban population density and the interaction with land use elements involve mutual constraints and guidance. However, in the existing research on the relationship between urban population density and land use, the discussion on the distribution patterns of urban population density typically spans long time periods and uses large spatial units, lacking analysis of the dynamic changes in population density within high granularity land parcels over a day. In studies related to the urban built environment, the complex relationships between different-dimensional land use elements and the dynamic distribution of population density also need further exploration. To address these bottlenecks, this study takes Shanghai’s central urban area as an example. Based on 24 h mobile signaling data on weekdays, weekends, and typical holidays, as well as urban land use data, clustering algorithms are used to summarize patterns of dynamic population density distribution. Pearson correlation analysis is then employed to study the correlation between dynamic population density distribution patterns and different land use elements. The results indicate that various urban land use factors such as locational centrality, functional diversity, transportation accessibility, compactness, and landscape quality have different impacts on the dynamic distribution of population density in spatial units, and the dynamic distribution patterns of population density in different land use types also vary. This research contributes to guiding the optimization of spatial quality and formulating planning and management measures that more effectively match construction intensity with population activity density. Full article

This study analyzed changes in ultra-processed food consumption patterns during weekends in patients in the post-metabolic and bariatric surgery periods. It is a cross-sectional study, which recruited and collected data via social media from adults who underwent metabolic and bariatric surgery. The Brazil Food and Nutritional Surveillance System markers of dietary consumption and the NOVA Ultra-Processed Food Screening tools were applied to evaluate dietary patterns and ultra-processed food consumption from the previous day. A total of 1525 participants were included, with a mean age of 38 ± 8 years and a mean body mass index of 29.9 ± 5.8 kg/m². From these, 766 (50.3%) individuals answered the questionnaire referring to a weekend day. After adjusting for confounders, ultra-processed food consumption was higher on weekends compared to weekdays (NOVA Score 3.07 vs. 2.42; p < 0.01). The consumption of fruits and vegetables was lower on weekends, whereas the consumption of hamburgers/sausages, sugar-sweetened beverages, boxed/canned juice, and frozen pizza increased on weekends. Instant noodles and sandwich cookies did not show differences between weekdays and weekend days. This pattern suggests the need to monitor eating habits on weekends in individuals after metabolic and bariatric surgery. Full article

Wind speed differences between weekdays and holidays at urban sites in Japan were investigated in search of the influence of urban anthropogenic heat on surface wind speed using data from the Automated Meteorological Data Acquisition System (AMeDAS) of the Japan Meteorological Agency (JMA) for 44 years. The wind speed was found to be lower on holidays than on weekdays, not only in large cities but also in areas with medium degrees of urbanization, which is interpreted to be due to the stronger stability of the surface boundary layer under lower temperatures with smaller amounts of anthropogenic heat. The rate of decrease is about −3% in central Tokyo, and about −0.5% for the average over stations with population densities between 1000 and 3000 km⁻². Additionally, an analysis using the spatially dense data on the Air Pollution Monitoring System of Tokyo Metropolis for 28 years showed that negative anomalies in wind speed on holidays were detected at many stations in the Tokyo Wards Area, although negative temperature anomalies were limited to a few stations in the central area or near big roads, suggesting different spatial scales in the response of temperature and wind speed to anthropogenic heat. Full article

This study aims to create a reliable water-demand forecasting system using Long Short-Term Memory networks. The model integrates hourly water demands from 10 District Metered Areas of a Water Distribution Network in northeast Italy and weather data, handling missing values with LSTM-based data imputation. It considers temporal aspects like time, weekdays, holidays, and weekend patterns, employing sine and cosine transformations to capture daily cycles. To ensure the model’s robustness, the testing was conducted during the last week of the dataset, specifically week 81, with iterative adjustments to the LSTM’s hyperparameters to optimize prediction accuracy. These tuning efforts focused on learning rate, number of layers, and batch size, tailored to maximize the system’s performance. This method is essential for smart decision-making in water utility management and demonstrates significant potential for improving operational efficiencies. Full article

Background: Inconsistent sleep schedules, frequent awakening after sleep onset (WASO), and decreased sleep efficiency (SE) are common issues among adolescent team sports athletes. Moreover, research indicates that sleep problems are enhanced across schooldays. The aim of the present study was to assess sleep patterns of adolescent athletes and compare sleep parameters between schooldays and holidays. Methods: The chronotype and sleep quality of twelve adolescent basketball players (mean age: 15.58 ± 0.67 years) were assessed. Objective sleep parameters were then analyzed using actigraphy over a 12-day period, which included six days during the school period and six days during holidays. Results: Data showed that total sleep time (TST), SE, and WASO (382.48 min, 81.81%, and 66.70 min, respectively) did not meet international recommendations for sleep quantity and quality. During school weekdays, time in bed (TIB), TST, and SE significantly decreased compared to weekends (p < 0.001, d = −1.49; p < 0.001, d = −1.64; and p = 0.01, d = −0.89, respectively). On weekdays, TIB, TST, and WASO were significantly lower on schooldays compared to holidays (p < 0.001, d = −1.83; p < 0.01, d = −1.01; and p = 0.02, d = −0.77, respectively). While no significant difference was observed in social jetlag, the mid-point of sleep was significantly later on holiday weekdays compared to school weekdays (p < 0.05, d = 0.65). Conclusions: Adolescent athletes experience insufficient sleep, especially on school weekdays, which is partially improved during weekends and holidays. Although sleep duration was longer during holidays, our results suggest that adolescent athletes’ sleep was more fragmented. Consequently, it remains crucial to implement strategies to enhance their sleep health (e.g., napping). Full article

Research on capturing human mobility patterns for efficient and sustainable urban planning has been widely conducted. However, studies that unveil spatial context beyond macro-level mobility patterns are relatively scarce. This study aims to analyze the spatiotemporal human meta-mobility patterns with rich context using POI data in Seoul from comprehensive perspectives. As a result, the floating population of Seoul exhibits regular and irregular cyclical mobility patterns on weekdays and weekends, respectively, stemming from the periodicity of the dominant POIs. Additionally, graph construction based on mobility similarity and their regional clustering show clusters vary by POIs but are generally divided into peripheral and central regions of Seoul. This indicates that socioeconomic factors cannot be ignored when understanding human mobility patterns. This helps to provide scientific evidence to support policy recommendations towards greenways and sustainable urban mobility systems, such as quantitative disparity of greenways, qualitative issues of greenways in the central areas, and inequality in cultural consumption. Addressing key considerations through targeted policies could significantly improve the overall quality of life for urban residents. We expect this study to lay the groundwork for future research that aims to understand realistic human mobility patterns with a rich context. Full article

The spatial distribution of Leisure Urban Spaces (LUSs) is closely linked to urban sustainability and residents’ quality of life. This study uses the Central Urban Area of Nanjing as the study area. Using POI and AOI data, the locations of LUS were precisely identified and categorized, including parks, squares, waterfront spaces, and leisure blocks. GIS spatial analysis methods, the nearest neighbor index, standard deviation ellipse, and kernel density estimation were used to analyze these spaces’ form, directivity, and density. Population activity intensity (PAI) data at various time points, collected by Baidu heat map, are correlated with LUS distribution through multiple linear regression analysis. (1) Parks and squares exhibit significant clustering tendencies, whereas waterfront spaces show weaker clustering, and leisure blocks are randomly distributed; (2) The central points of all types of LUS are located in the city center, extending from southeast to northwest, with parks and squares offering a broader range of services; (3) The overall LUS layout shows a ‘core and multiple points’ structure, with varying density patterns across different spaces, indicating concentrated and dispersed leisure areas; (4) The correlation between LUS distribution and PAI strengthens throughout the day and is greater on weekends than weekdays. Leisure blocks significantly enhance activity intensity, while parks have a limited effect, and waterfront spaces often show a negative correlation due to their remote locations. These results provide insights for future urban planning in Nanjing and underscore patterns in residents’ leisure activities. Full article

The fuel consumption and greenhouse gas (GHG) emission patterns of taxis are in accordance with the urban structure and daily travel footprints of residents. With taxi trajectory data from the intelligent transportation system in Xi’an, China, this study excludes trajectories from electric taxis to accurately estimate GHG emissions of taxis. A gradient boosting decision tree (GBDT) model is employed to examine the nonlinear influence of the built environment (BE) on the GHG emissions of taxis on weekdays and weekends in various urban areas. The research findings indicate that the GHG emissions of taxis within the research area exhibit peak levels during the time intervals of 7:00–9:00, 12:00–14:00, and 23:00–0:00, with notably higher emission factors on weekends than on weekdays. Moreover, a clear nonlinear association exists between BE elements and GHG emissions, with a distinct impact threshold. In the different urban areas, the factors that influence emissions exhibit spatial and temporal heterogeneity. Metro/bus/taxi stops density, residential density, and road network density are the most influential BE elements impacting GHG emissions. Road network density has both positive and negative influences on the GHG emissions in various urban areas. Increasing the road network density in subcentral urban areas and increasing the mixed degree of urban functions in newly developed urban centers to 1.85 or higher can help reduce GHG emissions. These findings provide valuable insights for reducing emissions in urban transportation and promoting sustainable urban development by adjusting urban functional areas. Full article

Passenger density is a major factor influencing indoor climate conditions and the corresponding energy consumption in the transfer halls of metro transportation hubs. In this study, passenger flow in a subway transfer hall in Beijing was measured across three typical seasons. A differential equation model was established to account for the characteristics of passenger density. Based on this, a passenger density prediction model was developed and utilized for analysis. The results show that passenger density is primarily affected by operation time and the surrounding population composition, with a relatively weak correlation to outdoor weather conditions. Additionally, passenger density differs significantly between weekdays and weekends, with the weekday peak being 2.5 times higher than that on weekends. During the four peak hours on weekdays, both in the morning and evening, passenger density exceeds the design capacity, resulting in insufficient fresh air supply. However, for most of the weekday hours and for all hours on weekends, passenger density remains below the design capacity. This indicates a substantial potential for energy savings by adjusting the fresh air supply according to actual passenger density. Full article

This paper explores the accumulation of Indian astronomical knowledge within Chinese Buddhist scriptures and its dissemination across Chinese society through a comparative study of the Modengjia jing (Ch1 of the ZKA) and the Xiuyao jing (XYJ). The period from the Ch1 of ZKA to the XYJ was a time when Buddhism was in the midst of developing and maturing within China. The Ch1 of the ZKA is regarded as the first Buddhist scripture including a complete account of Indian nakṣatra astrology and translated from Sanskrit parallel text, rather than a native work codified by Buddhists in Ancient China. The XYJ is not a translation but rather an authoritative handbook of Indian astrological knowledge taught by Amoghavajra. A detailed comparison of the contents of the two texts shows that the knowledge contained within Ch1 of the ZKA belongs to the Vedic era and that the XYJ belongs to the post-Vedic era. Beginning with the Ch1 of the ZKA and ending with the XYJ, Buddhist astronomical knowledge steadily grew. Yang Jingfeng’s revision and explanation of the first fascicle of the Sutra reflects Ancient Chinese intellectuals’ acceptance, digestion, and recreation of Buddhist astronomical knowledge. His abandonment of the “Calculation of weekdays” reflects the influence of the Chinese mathematical and astronomical tradition and the calendar tradition upon his perspective; perhaps this is one of the reasons why China has accepted the weekday within daily life up to the modern era. Every civilization, in learning to assimilate other cultures, has a choice between foreignization and domestication, within which a tension is reflected. Learning from foreign cultures is about keeping up with the most advanced civilizations in the world and advancing with the times, while maintaining one’s own cultural identity and cultural characteristics is necessary for one’s own civilization; these two notions are complementary and should not be neglected. Full article

Due to its high short-term global warming potential (GWP) compared to carbon dioxide, methane (CH₄) is a considerable agent of climate change. This research is aimed at analyzing data on methane gathered at the GAW (Global Atmosphere Watch) station of Lamezia Terme (Calabria, Southern Italy) spanning seven years of continuous measurements (2016–2022) and integrating the results with key meteorological data. Compared to previous studies on detected methane mole fractions at the same station, daily-to-yearly patterns have become more prominent thanks to the analysis of a much larger dataset. Overall, the yearly increase of methane at the Lamezia Terme station is in general agreement with global measurements by NOAA, though local peaks are present, and an increase linked to COVID-19 is identified. Seasonal changes and trends have proved to be fully cyclic, with the daily cycles being largely driven by local wind circulation patterns and synoptic features. Outbreak events have been statistically evaluated depending on their weekday of occurrence to test possible correlations with anthropogenic activities. A cross analysis between methane peaks and specific wind directions has also proved that local sources may be deemed responsible for the highest mole fractions. Full article

Purpose: This study aimed to investigate the association between social jetlag (SJL) and obesity-related outcomes among adolescents from Valle de Ricote (Region of Murcia, Spain). We explored the relationship between SJL and body mass index (BMI) z-score, waist circumference, and body fat percentage, as well as the odds of having excess weight, obesity, and abdominal obesity in a sample of Spanish adolescents. Methods: A cross-sectional study was conducted using data from the Eating Healthy and Daily Life Activities (EHDLA) project, which included 847 Spanish adolescents aged 12–17 years. SJL was assessed based on the differences in sleep patterns between weekdays and weekends. Obesity-related indicators such as BMI z-score, waist circumference, body fat percentage, excess weight, obesity, and abdominal obesity were measured. Generalized linear models with a Gaussian or binomial distribution were used to analyze the associations between SJL and obesity-related outcomes, adjusting for potential confounders. Results: The analysis revealed significant associations between SJL and BMI z-score (unstandardized beta coefficient [B] = 0.15, 95% CI: 0.05 to 0.25, p = 0.003), waist circumference (B = 1.03, 95% CI: 0.39 to 1.67, p = 0.002), and body fat percentage (B = 0.83, 95% CI: 0.31 to 1.43, p = 0.008). Additionally, the odds ratios (ORs) for excess weight (OR = 1.35, 95% CI: 1.16 to 1.57; p < 0.001), obesity (OR = 1.59, 95% CI: 1.26 to 2.00; p < 0.001), and abdominal obesity (OR = 1.46, 95% CI: 1.23 to 1.72; p < 0.001) increased significantly with each 60 min increment in SJL. Conclusions: This study pointed out that the misalignment of sleeping times during weekdays and weekends (SJL) is significantly associated with higher BMI z-scores, waist circumference, body fat percentage, and higher odds of excess weight, obesity, and abdominal obesity among adolescents, being more significant in boys than in girls. These findings highlight the importance of addressing circadian misalignment in the prevention and management of obesity and its related metabolic disorders in this population. Full article