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China's metro system is developing rapidly. Walking is the most frequently adopted mode to connect to the metro, the attributes of the pedestrian-built environment around the stations directly influence people's willingness to use the metro. However, few studies have paid attention to the comprehensive assessments of the built environment in the metro catchment area. Thus, this paper attempts to construct a walkability evaluation model that combines subjective and objective perspectives. We collected field data of the built environment factors affecting on walkability in the 800 m buffer zone of eight case metro stations in Dalian city, China. We also collected on-site interviews from 867 passengers to evaluate the walkability. A machine learning-based approach was developed to calculate the weights of walkability variables, followed by constructing a Score-Effectiveness framework to identify the built environment factors in the metro catchment area that need to be improved. The study found that the shading facilities, obstacle barriers, and resting seats around pedestrian walkways are the most efficient and imbalanced variables recognized by the crowd. The convenience of overpasses and underpasses are additional efficient imbalance-type variables for leisure and commuting populations, respectively. This indicates that the current level of construction of the above five built environment factors is relatively low, but the construction has a significant impact on the degree of friendliness in supporting pedestrian walkability. In this paper, improvement measures are proposed in a targeted manner in order to achieve the effect of effectively improving the current level of metro catchment area's walkability. The results of the study can provide references to provide strategies for precise pedestrian planning in the metro catchment area, leading to a pedestrian environment with high walking quality.

E-bike, characterized as a low-carbon and health-beneficial active travel mode, is gradually becoming popular in China. Although built environment factors are considered to be key parameters that can facilitate or hinder active transportation, such as cycling or walking, few studies have explored the impact of built environment on e-bikes. To fill this gap, this study was the first to explore the relationship between e-bike usage and built environment factors based on population level travel survey in central Jinan, China. Both macro and micro levels of built environment were measured using multi-source data. We employed ordinary least squares (OLS) and geographically weighted regression (GWR) models to explore the aggregation patterns of e-bike trips. Besides, the local Moran's I was employed to classify the aggregation patterns of e-bike trips into four types. The results from OLS model showed that eye-level greenery, building floor area, road density and public service POI were positive significantly related to e-bike trips, while open sky index and NDVI had negative association with e-bike trips. The usage of GWR model provided more subtle results, which revealed significant spatial heterogeneity on the impacts of different built environment parameters. Road density and public service POI posed positive effects on e-bike travel while NDVI and open sky index were found mainly pose negative impacts on e-bike travel. Moreover, we found similar coefficient distribution patterns of eye-level greenery, building floor area and distance to bus stop. Therefore, tailored planning interventions and policies can be developed to facilitate e-bike travel and promote individual's health level.

In this study, a comprehensive evaluation of management for pathogenic microbiology laboratories is performed based on a combination of Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Rank Sum Ratio (RSR) methods; in addition, the basis for improving laboratory management is provided. Using the laboratory evaluation tool developed by World Health Organization and a combination of TOPSIS and RSR methods, a system of evaluation indicators for the management of Chinese pathogenic microbiology laboratories is established for comprehensively evaluating the pathogenic microbiology laboratories of seven provincial Centers for Disease Control and Prevention. The evaluation system includes 12 primary indicators and 37 secondary indicators. In terms of laboratory management, the seven laboratories were ranked as D, G, E, C, F, B, and A in descending order. None of these laboratories were evaluated as “good” or “poor.” One of the laboratories was marked as “relatively poor” (A), two as “medium” (B and F), and four as “relatively good” (C, E, G, and D). In this study, a method for evaluating laboratory management using the TOPSIS and RSR methods is proposed, and a basis for comprehensively evaluating laboratory management for pathogenic microbiology laboratories is provided to reflect management practices.

Bike share engages riders in physical activity, beneficial to health. In addition, it promotes green mobility and contributes to carbon neutrality. An understanding of the association between bike share usage and the built environment is essential for system operation/management and urban/transportation planning. Limited reviews of the existing literature exist now. Therefore, we review previous studies to decipher the complex relationship between bike share usage and the built environment. We focus on a few built environment dimensions (e.g., land use, transportation system, and urban design) and find that many attributes affect bike share usage differently across mobility cultures, between docked and dockless bike share, and between arrival and departure usage patterns. The effects of several attributes (e.g., proximity to a park or university and metro station density) on bike share usage also vary between weekdays and weekends and across trip purposes. The findings of this paper advance knowledge on the connection between bike share usage and the built environment.

Objectives: This study aimed to evaluate the level and factors affecting the perioperative exercise intention in China.Design: This study was a cross-sectional survey in Southwest China.Methods: Four hundred and ninety nine participants were randomly sampled in eight medical centers from November 23, 2020 to November 27, 2020. The survey included sociodemographic information and a 24-item modified questionnaire, which aimed to evaluate the attitude toward daily exercise, perception of perioperative exercise, social support and the perioperative exercise intention. A multivariable linear regression model was used to evaluate the effect of different items on the patients' intention for perioperative exercise.Results: A total of 523 responses (95.09%) were collected and 499 (95.41%) were analyzed. The level of exercise intention of the patients during the perioperative period was: 14.83% planned to exercise every day in the hospital, 21.04% planned to exercise every other day, and 35.87% planned to exercise every week. Intensity of daily exercise (P = 0.016), positive attitude of daily exercise (P < 0.001), positive attitude of perioperative exercise (P < 0.001) and social support (P < 0.001) were positively associated with the intention for perioperative exercise. Female (P = 0.012), non-tertiary center (P = 0.011), and preoperative anxiety (P = 0.023) was negatively associated with it.Conclusions: The intention for perioperative exercise was low in Southwest China. The authors aimed to relieve preoperative anxiety, promote the education of perioperative exercise, design perioperative exercise programs, and provide more social support from medical staff and family for inpatients undergoing elective surgery.