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Accurate and reliable prediction of subway passenger flow is a particularly challenging application of spatiotemporal forecasting, due to the time-varying travel patterns and the complex spatial dependencies on subway networks. To address these challenges, this study proposes a novel spatiotemporal graph convolutional bidirectional long short-term memory neural network model combined with an attention mechanism (At-STGCN-BiLSTM) to better predict short-term passenger flow for all stations in a large-scale metro system. The STGCN-BiLSTM aims to capture the attributes of spatiotemporal characteristics of subway stations, and the attention mechanism helps account for the correlation between historical data and current moment inbound passenger flow. The performance of the short-time passenger flow forecast model is analyzed by different time intervals. Experimental results show that the proposed model outperforms baseline models on Wuhan, China, subway data. The value of root-mean square error (RMSE) and mean absolute error (MAE) decreased by 7.33% and 9.38%, respectively, compared with the baseline models at the 15-min interval. The attention mechanism in the proposed model can effectively improve the prediction capability of peak and nonperiodic passenger flow variations. The research not only is of great help to the passenger flow organization and emergency management of the subway, but also plays a vital role in the work of rail transit regulation, rail transit alarm release, and service efficiency improvement. [ABSTRACT FROM AUTHOR]

The quantification of the interplay between student behavior data and classroom teaching effectiveness using quantitative metrics has perennially posed a challenge in the evaluation of classroom instruction. Classroom activity serves as a reflection of student engagement, emotional ambiance, and other pertinent aspects during the pedagogical process. This article presents a methodology for quantifying student head posture during classroom instruction utilizing AI-driven video analysis technology, notably the Classroom Activity Index (CAI). A Classroom Activity Analysis System (CAAS) was designed and developed, integrating a multi-scale classification network based on ECA-ResNet50 and ECA-ResNet18. This network discerns and categorizes various head regions of students situated in both the frontal and real rows of a lecture-style classroom, irrespective of their dimensions. The classification network attains exceptional performance, boasting F1 score of 0.91 and 0.92 for student head-up and head-nodding. Drawing on the live classroom instruction at a higher vocational college in Wuhan, Hubei Province, China, a comparative experiment was executed. The findings revealed that three factors: teacher-student verbal interaction, teacher body language, and utilization of digital resource, all exert an influence on CAI. Simultaneously, the degree of classroom activity as gauged by FIAS and manual analysis fundamentally aligns with the CAI indicators quantified by CAAS, validating the efficacy of CAI in the quantification of classroom activity. Consequently, the incorporation of CAAS in teaching, research, and oversight scenarios can augment the precision and scientific rigor of classroom teaching assessment. [ABSTRACT FROM AUTHOR]

This study investigates the association between prenatal exposure to per- and polyfluoroalkyl substances (PFASs) and the incidence and frequency of respiratory tract infections (RTIs) in preschool children. We selected 527 mother–infant pairs from Wuhan Healthy Baby Cohort (WHBC), China. Ten PFASs were measured in umbilical cord serum, and we collected data on common RTIs in preschool children aged 4 years through a questionnaire. Associations of single PFASs with the incidence and frequency of RTIs were analyzed via Logistic regression and Poisson regression, while the collective effect was assessed by weighted quantile sum (WQS) regression. Furthermore, stratified and interaction analyses were performed to evaluate if there were sex-specific associations. We found a positive correlation between perfluorododecanoic acid (PFDoDA) and the incidence of tonsillitis, with several PFASs also showing positive associations with its frequency. Moreover, perfluorotridecanoic acid (PFTrDA) showed a positive link with the frequency of common cold. The results of WQS regression revealed that after adjusting for other covariates, PFASs mixture showed a positive association with the incidence of tonsillitis, the frequency of common cold, and episodes. In particular, perfluoroundecanoic acid (PFUnDA), PFDoDA, PFTrDA, perfluorodecanoic acid (PFDA) and 8:2 chlorinated polyfluorinated ether sulfonic acid (8:2 Cl-PFESA) had the most significant impact on this combined effect. The results suggest that both single and mixed exposures to PFASs may cause RTIs in preschool children. However, there was no statistically significant interaction between different PFASs and sex. [ABSTRACT FROM AUTHOR]

In the elicitation of decision makers' fuzzy and uncertain assessments, linguistic terms are natural and efficient as the preference modeling tools. Although the linguistic variables are available, they would not be operational without any detailed quantification. Motivated by the flexibility of information granularity, this paper develops information granules to represent linguistic terms in the form of intervals and interval type-2 fuzzy sets (IT2FSs) in best worst method (BWM). The development is aimed at minimizing inconsistency in the decision making (DM) process to ensure the rationality of the assessments provided by decision makers. Furthermore, the input and output based consistencies of BWM are considered. The granulation of entries of pairwise comparison vectors are the foundation of BWM to formulate an optimization problem where particle swarm optimization (PSO) algorithm serves as the optimization framework. Both individual and group decision making (GDM) scenarios are taken into consideration. For the GDM process, a performance index for measuring the group consensus is also proposed. Several examples and validity analysis are covered to illustrate the major ideas of this study. Finally, as a case study, a recommendation of the sequence of visiting tourist attractions in Wuhan and the corresponding comparative analysis are represented. • A granular computing-based method in BWM framework is proposed. • Construction of granular linguistic information to represent preference information of DMs is given. • A novel Euclidean distance function to measure the agreement among the group is proposed. • A case study of scenic spots recommendation in Wuhan with online reviews is exhibited. [ABSTRACT FROM AUTHOR]

Various measures have been taken to improve ship energy efficiency while decreasing CO2 emissions. In this work, the navigation environment between Wuhan and Shanghai in China has been classified based on an improved K-means algorithm in order to realize route division. A fuel consumption prediction model considering the navigation environment factors has been established. Consequently, speed optimization models with multiple different optimization objectives have been constructed and tested based on an actual case using an artificial fish swarm algorithm. Finally, sensitivity analysis has been carried out focusing on the navigation time, fuel price, charter rate, free carbon credits, and carbon tax rate. The results show that the total shipping cost and CO2 emissions could be reduced by 0.94% and 0.38%, respectively, after the optimization. Considering a carbon tax policy with a tax rate of roughly 1300 RMB/t, the optimization result (including the carbon tax cost) is close to the compromised solution of multi-objective optimization, and the corresponding carbon tax rate can provide a useful reference for policymakers. [ABSTRACT FROM AUTHOR]

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5 ± 38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42−, NO3− and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3−/SO42− was 0.86 ± 0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9 ± 1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively. [ABSTRACT FROM AUTHOR]

Proper and regular physical activity (PA) plays an important role in improving people's health. With the outbreak of the COVID-19 pandemic, which has posed a serious threat to individual health, residents' PA has aroused deep concern. Based on the theory of planned behavior, this study examines the impact of residents' PA intention and behavior in response to the COVID-19 pandemic. Data were collected from a sample of 961 residents in Wuhan in China using a questionnaire survey. The results show that residents' PA intention and behavior have been affected significantly by residents' PA attitude, subjective norms, and perceived behavioral control. The COVID-19 pandemic has a significant impact on both residents' PA intention and behavior. In addition, there were gender and region differences in this impact. The findings are of great significance in promoting residents' PA intention and PA behavior, which are of positive significance to the development of residents' physical and mental health in the period of global serious health crisis. [ABSTRACT FROM AUTHOR]

The increasing interest in fine-grained blocks requires a deeper understanding of the impact of block size on urban vitality. To date, limited empirical tests of the underlying relationships at the city level have been conducted using the ordinary linear-squares method, assuming a linear relationship. However, urban vitality is a complex system, thus making the use of linear regressions unfeasible because the assumption of homogeneity of variance would be violated. Therefore, the constraint line method was introduced to deepen the understanding of the relationship between block size and urban vitality. This paper employed a kernel density estimation of small catering businesses, point of interest density, social media check-in density, and comment density as proxies of urban vitality. Wuhan is the largest megacity in Central China and has been selected for this case study. When the block size increased to almost 0.08 km2, the maximum kernel density estimation value decreased sharply from above 2.70 to 1.60; when the block size exceeded 0.30 km2, vitality values tended to decrease very slowly. The maximum urban vitality measured by the other three indicators dropped an order of magnitude when the block size increased to 0.06 km2, then gradually slowed down, and tended toward a plateau when the block size increased beyond 0.20. Therefore, the dynamic process can be divided into three phrases with multiple critical thresholds of block size. These are approximately 0.06, 0.08, and 0.20 km2 ranked from the best to worst. The study indicates that block size has a nonlinear and threshold effect on urban vitality by constraining the maximum urban vitality. In general, the positive effect of small block size over urban vitality was confirmed, and additionally, urban planners should propose urban planning schemes with smaller residential blocks below 0.06 km2. [ABSTRACT FROM AUTHOR]

Background: Isolated terminal ileitis (ITI) is a phenomenon often observed during colonoscopy, but in most cases, the specific etiology of ITI is unclear. Helicobacter pylori (H. pylori) infection has been reported to be associated with a wide variety of diseases, especially gastrointestinal diseases. Here, we conducted a retrospective study to explore a potential correlation between H. pylori infection and unexplained ITI (UITI). Materials and Methods: The retrospective study was conducted at Sino-French New City Branch of Tongji Hospital, Wuhan, China, from April 2017 to October 2020. All subjects underwent total colonoscopy, with the endoscope being inserted more than 10cm into the terminal ileum. Subjects also received a 13C-urea breath test (13C-UBT). Data on the age, gender, endoscopic manifestations, and main clinical symptoms of subjects were collected. The presence of H. pylori infection was defined as a positive 13C-UBT result. Logistic regression models were used to analyze the potential correlation between H. pylori infection and UITI. Results: There were 247 subjects (25.1%) in the H. pylori (+) group and 739 subjects (74.9%) in the H. pylori (-) group. The prevalence of UITI in the H. pylori (+) group was significantly lower than that in the H. pylori (-) group (OR = 0.518; 95% CI 0.281– 0.956; P = 0.035), and there was no difference in other clinical features between groups. Stratification analysis results showed that there was an inverse association between H. pylori infection and UITI in subjects with age < 60 (P = 0.046). Conclusion: These data showed that H. pylori infection was negatively correlated with UITI. Additional studies are needed to validate these findings in a larger cohort as well as to explore the underlying mechanisms. [ABSTRACT FROM AUTHOR]

At the outbreak of coronavirus disease in Wuhan, China, 42,322 medical personnel from other provinces and municipalities in China volunteered to rush to Hubei to assist their colleagues. Their all-out efforts contributed to Hubei finally winning the fight to prevent and control the pandemic. The aim of this study is to explore the influence of perceived organizational support on the emotional labor of medical personnel in Hubei Province. A group of 170 medical personnel from (tertiary) hospitals who participated in the pandemic aid operation in Hubei completed self-administered questionnaires, including the perceived organizational support scale, emotional labor scale, and professional identity scale. This study used Pearson's correlation in SPSS to analyze the three variables of organizational support, emotional labor, and professional identity. Organizational support and emotional labor (r = 0.443, P < 0.01), organizational support and professional identity (r = 0.631, P < 0.01), and emotional labor and occupational identity (r = 0.511, P < 0.01) showed a significant positive correlation. The bootstrapping mediating effect test was used to determine the overall mediating effect of occupational identity. Occupational identity was a complete mediating effect between organizational support and emotional labor. The results show that a strong sense of organizational support can promote higher emotional labor among medical workers in Hubei Province. A strong sense of organizational support will also promote a stronger professional identity; further, a strong professional identity completely mediates the effect of perceived organizational support on emotional labor. These results infer that in emergency medical and health services, medical personnel can realize a high sense of organizational support, which could enhance their professional identity; this enables them to combine their professional goals with organizational goals more actively and to finally pay higher emotional labor to achieve organizational goals. [ABSTRACT FROM AUTHOR]

Background Acute kidney injury (AKI) is an important complication of coronavirus disease 2019 (COVID-19), which could be caused by both systematic responses from multi-organ dysfunction and direct virus infection. While advanced evidence is needed regarding its clinical features and mechanisms. We aimed to describe two phenotypes of AKI as well as their risk factors and the association with mortality. Methods Consecutive hospitalized patients with COVID-19 in tertiary hospitals in Wuhan, China from 1 January 2020 to 23 March 2020 were included. Patients with AKI were classified as AKI-early and AKI-late according to the sequence of organ dysfunction (kidney as the first dysfunctional organ or not). Demographic and clinical features were compared between two AKI groups. Their risk factors and the associations with in-hospital mortality were analyzed. Results A total of 4020 cases with laboratory-confirmed COVID-19 were included and 285 (7.09%) of them were identified as AKI. Compared with patients with AKI-early, patients with AKI-late had significantly higher levels of systemic inflammatory markers. Both AKIs were associated with an increased risk of in-hospital mortality, with similar fully adjusted hazard ratios of 2.46 [95% confidence interval (CI) 1.35–4.49] for AKI-early and 3.09 (95% CI 2.17–4.40) for AKI-late. Only hypertension was independently associated with the risk of AKI-early. While age, history of chronic kidney disease and the levels of inflammatory biomarkers were associated with the risk of AKI-late. Conclusions AKI among patients with COVID-19 has two clinical phenotypes, which could be due to different mechanisms. Considering the increased risk for mortality for both phenotypes, monitoring for AKI should be emphasized during COVID-19. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the prognostic value of baseline clinical and high resolution CT (HRCT) findings in patients with severe COVID-19. In this retrospective, two-center study, we included two groups of inpatients with severe COVID-19 who had been discharged or died in Jin Yin-tan hospital and Wuhan union hospital between January 5, 2020, and February 22, 2020. Cases were confirmed by real-time polymerase chain reaction. Demographic, clinical, and laboratory data, and HRCT imaging were collected and compared between discharged and deceased patients. Univariable and multivariable logistic regression models were used to assess predictors of mortality risk in these patients. 101 patients were included in this study, of whom 66 were discharged and 35 died in the hospital. The mean age was 56.6 ± 15.1 years and 67 (66.3%) were men. Of the 101 patients, hypertension (38, 37.6%), cardiovascular disease (21,20.8%), diabetes (18,17.8%), and chronic pulmonary disease (16,15.8%) were the most common coexisting conditions. The multivariable regression analysis showed older age (OR: 1.142, 95% CI 1.059–1.231, p < 0.001), acute respiratory distress syndrome (ARDS) (OR: 10.142, 95% CI 1.611–63.853, p = 0.014), reduced lymphocyte count (OR: 0.004, 95% CI 0.001–0.306, p = 0.013), and elevated HRCT score (OR: 1.276, 95% CI 1.002–1.625, p = 0.049) to be independent predictors of mortality risk on admission in severe COVID-19 patients. These findings may have important clinical implications for decision-making based on risk stratification of severe COVID-19 patients. [ABSTRACT FROM AUTHOR]

Wuhan, China was the epicenter of the 2019 coronavirus outbreak. As a designated hospital for COVID-19, Wuhan Pulmonary Hospital has received over 700 COVID-19 patients. With the COVID-19 becoming a pandemic all over the world, we aim to share our epidemiological and clinical findings with the global community. We studied 340 confirmed COVID-19 patients with clear clinical outcomes from Wuhan Pulmonary Hospital, including 310 discharged cases and 30 death cases. We analyzed their demographic, epidemiological, clinical and laboratory data and implemented our findings into an interactive, free access web application to evaluate COVID-19 patient's severity level. Our results show that baseline T cell subsets results differed significantly between the discharged cases and the death cases in Mann Whitney U test: Total T cells (p < 0.001), Helper T cells (p <0.001), Suppressor T cells (p <0.001), and TH/TSC (Helper/Suppressor ratio, p<0.001). Multivariate logistic regression model with death or discharge as the outcome resulted in the following significant predictors: age (OR 1.05, 95% CI, 1.00 to 1.10), underlying disease status (OR 3.42, 95% CI, 1.30 to 9.95), Helper T cells on the log scale (OR 0.22, 95% CI, 0.12 to 0.40), and TH/TSC on the log scale (OR 4.80, 95% CI, 2.12 to 11.86). The AUC for the logistic regression model is 0.90 (95% CI, 0.84 to 0.95), suggesting the model has a very good predictive power. Our findings suggest that while age and underlying diseases are known risk factors for poor prognosis, patients with a less damaged immune system at the time of hospitalization had higher chance of recovery. Close monitoring of the T cell subsets might provide valuable information of the patient's condition change during the treatment process. Our web visualization application can be used as a supplementary tool for the evaluation. [ABSTRACT FROM AUTHOR]

Background: A cluster of patients with coronavirus disease 2019 (COVID-19) pneumonia caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were successively reported in Wuhan, China. We aimed to describe the CT findings across different timepoints throughout the disease course.Methods: Patients with COVID-19 pneumonia (confirmed by next-generation sequencing or RT-PCR) who were admitted to one of two hospitals in Wuhan and who underwent serial chest CT scans were retrospectively enrolled. Patients were grouped on the basis of the interval between symptom onset and the first CT scan: group 1 (subclinical patients; scans done before symptom onset), group 2 (scans done ≤1 week after symptom onset), group 3 (>1 week to 2 weeks), and group 4 (>2 weeks to 3 weeks). Imaging features and their distribution were analysed and compared across the four groups.Findings: 81 patients admitted to hospital between Dec 20, 2019, and Jan 23, 2020, were retrospectively enrolled. The cohort included 42 (52%) men and 39 (48%) women, and the mean age was 49·5 years (SD 11·0). The mean number of involved lung segments was 10·5 (SD 6·4) overall, 2·8 (3·3) in group 1, 11·1 (5·4) in group 2, 13·0 (5·7) in group 3, and 12·1 (5·9) in group 4. The predominant pattern of abnormality observed was bilateral (64 [79%] patients), peripheral (44 [54%]), ill-defined (66 [81%]), and ground-glass opacification (53 [65%]), mainly involving the right lower lobes (225 [27%] of 849 affected segments). In group 1 (n=15), the predominant pattern was unilateral (nine [60%]) and multifocal (eight [53%]) ground-glass opacities (14 [93%]). Lesions quickly evolved to bilateral (19 [90%]), diffuse (11 [52%]) ground-glass opacity predominance (17 [81%]) in group 2 (n=21). Thereafter, the prevalence of ground-glass opacities continued to decrease (17 [57%] of 30 patients in group 3, and five [33%] of 15 in group 4), and consolidation and mixed patterns became more frequent (12 [40%] in group 3, eight [53%] in group 4).Interpretation: COVID-19 pneumonia manifests with chest CT imaging abnormalities, even in asymptomatic patients, with rapid evolution from focal unilateral to diffuse bilateral ground-glass opacities that progressed to or co-existed with consolidations within 1-3 weeks. Combining assessment of imaging features with clinical and laboratory findings could facilitate early diagnosis of COVID-19 pneumonia.Funding: None. [ABSTRACT FROM AUTHOR]

• Mitigating urban heat island from the perspective of cold island connectivity. • A method for constructing the combined cooling pattern is proposed;. • The key cooling sources are identified based on the morphospatial pattern analysis;. • Cooling network and key nodes are identified based on circuit theory;. • Proposals for climate adaptation planning at three levels: "surface-line-point". Many studies have proposed strategies to mitigate the urban heat island effect from the perspective of landscape patches, yet few studies have mitigated the urban heat island effect from the perspective of cold island connectivity and network. This study proposes a new method (Combined cooling pattern) to connect cold islands: surface (Cooling sources) - line (Networks)- point (Cooling spaces, heating spaces). Initially, the cooling sources are identified by the morphological spatial pattern analysis method and connectivity analysis. Then, to enhance the connectivity of the cooling sources, we applied circuit theory to construct the cooling network and identify the critical nodes. Finally, three levels of cooling strategies are developed. Taking Wuhan as an example, the results show that 27 cooling sources, 58 cooling corridors, 69 cooling spaces and 26 heating spaces are identified. A regional cooling network should be constructed to mitigate the urban heat island effect, and effective cooling measures should be implemented in key node areas. The method adopted can provide new ideas for sustainable urban development and urban climate adaptation planning. [ABSTRACT FROM AUTHOR]

The eruption of COVID-19 at the beginning of 2020 has sounded the alarm, making experts pay more attention to public health emergency events. A suitable emergency response plan plays a vital role in handling emergency events. Therefore, this paper focuses on the evaluation of emergency response plans among a set of group in the comprehensive prospect, and an emergency decision making method integrated with the interval type-2 fuzzy information based on the third generation prospect theory (PT 3) and the extended MULTIMOORA method is proposed. Individuals express their preferences using some given linguistic terms set. Furthermore, considering the conflicts may occur in the group, a convergent iterative algorithm is designed for group consensus reaching. Then, the stochastic multi-criteria acceptability analysis (SMAA) method and the Borda Count (BC) method are generated to combine the results instead of the dominance theory in MULTIMOORA system. Finally, based on the background of the COVID-19 pandemic from Wuhan, a case study about the selection of emergency response plan and the corresponding sensitivity and comparative analysis are exhibited to explain the effectiveness of the proposed method. • A new fuzzy MCDA method to evaluate emergency response plans is proposed. • An integrated model based on PT3 and extended MULTIMOORA with IT2FSs is developed. • The proposed method considers CRP with an effectiveness iterative algorithm. • A case study of emergency response plans assessment on COVID-19 in Wuhan is presented. [ABSTRACT FROM AUTHOR]

The bearing capacity of the road pavement is one of the most important indices that reflect the road condition. To collect such data, various deflectometers were developed in the past three decades. Note that the newly developed Traffic-Speed Deflectometer (TSD) declares to perform a nondestructive measuring at traffic speeds. However, TSD is limited as it needs more than 4 h to calibrate the system before a measuring task. This paper introduces a Laser Dynamic Deflectometer (LDD) developed at the Transportation Research Center of Wuhan University. LDD applies four laser Doppler sensors mounted on a measuring beam to capture the deflection velocity of the pavement surface. Unlike TSD using a servo to keep the beam static, LDD utilizes a gyroscope to measure and compensate the vibration of the beam. Moreover, in the procedure of calibration, LDD applies an efficient relative-motion method to calculate the relative angles between each two Doppler lasers, which reduces the time of system calibration to about 2 h. [ABSTRACT FROM PUBLISHER]

(1) To find some predictive markers for identifying those who will develop into psychosis. (2) Compared with normal controls, CHR performed poorer in all tests of cognitive function. (3) These who converted to psychosis showed worse performance in almost all cognitive tests, except the trail making test A(TMT-A) and continuous performance test-identical pairs (CPT-IP) than the CHR who do not convert. (4) The degree of impairment in visual learning, working memory may be as predictive markers for individuals at CHR who developed psychosis later. The purpose of our study was to explore the value of measuring cognitive functions for predicting the conversion to psychosis in Chinese college students with a clinical high risk (CHR). A total of 115 CHR students and 99 healthy controls were enrolled. All included participants were recruited from colleges in Wuhan, China. The MATRICS Consensus Cognitive Battery was used to evaluate cognitive function. CHR individuals were followed for 2 years, and the cognitive function of CHR individuals who later converted to psychosis (CHR-C) was compared to CHR individuals who did not convert (CHR-NC). Of the 107 CHR individuals that completed the 2- year follow-up, 29 (27.1%) developed a psychotic disorder. CHR individuals demonstrated poorer performance on all cognitive function tests compared to controls. CHR-C participants exhibited poorer performance on all cognitive tests except the Trail Making Test A and Continuous Performance Test-Identical Pairs compared to CHR-NC participants. The most significant differences displayed between CHR-C and CHR-NC groups were in visual learning, working memory, and reasoning and problem solving. The degree of cognitive impairment in visual learning and working memory may be a predictive marker for individuals who are at risk of developing psychosis. [ABSTRACT FROM AUTHOR]

Following advancement in urbanization, outdoor thermal comfort is receiving increasing attention, with radiation being an influencing factor. To determine the shading preference, instead of a subjective questionnaire survey, an objective foot vote approach was proposed using remote sensing images. Subsequently, the meteorological data of cities were obtained from the Bureau of Meteorology. From the results, the foot vote was approximately consistent with the PMV, and pedestrians tended to move to the shaded area if it was hot and to the non-shaded area if it was cold. However, people do not move if the foot vote value ranges from 1 to 2, and the thermal acceptance range of PET is 19.2–29 °C in Beijing when using the definitions of foot vote. The outdoor thermal acceptance differs significantly with the types of outdoor sites and climates, and pedestrians in Beijing are significantly more sensitive than those in Wuhan if the outdoor thermal environment changes. Compared to transportation hubs and shopping malls, pedestrians in public buildings are less sensitive, whereas those in scenic spots are more sensitive. Results from this study will be beneficial to policymakers in urban designing to renovate and improve thermally comfortable urban environments at the pedestrian level. [Display omitted] • An objective foot vote approach from remote sensing images is proposed. • The foot vote approach is tested and consistent with PMV approach. • Air temperature and global radiation are important factors affecting foot votes. • Thermal acceptance range of PET is 19.2–29 °C in Beijing under foot vote approach. • Outdoor thermal sensitivity differs with the types of outdoor sites and climates. [ABSTRACT FROM AUTHOR]

• The heat stress-social vulnerability-human exposure assessment framework was built. • Risk in main urban area was 1.6 times that beyond metropolitan development area. • Most blocks had negative relationships between heat stress and social vulnerability. • Risk zoning is an important basis to bridge risk assessment and risk governance. Assessing heatwave-induced human health risk is of critical importance in order to mitigate hazards caused by extreme environmental events. Air temperature or land surface temperature in previous studies was often used to characterize the severity of heatwaves, and human perception of the thermal environment was neglected as a key component in the heatwave-induced risk assessment. In order to redress this issue, in this study we applied the Universal Thermal Climate Index (UTCI) to represent human thermal comfort perception and embedded the measure within an assessment framework of heat stress-social vulnerability-human exposure. The heatwave-induced human health risk was then evaluated in Wuhan City, China across 177 blocks covering the entire city area and local risk governance measures were also explored based on risk zoning. The results showed that spatial patterns of heatwave-induced human health risk followed a decreasing trend from the city center towards the surrounding areas, with the average risk of the main urban area being 1.6 times that beyond the metropolitan development area. Through the heatwave-induced human health risk zoning, about 73.45% of the 177 blocks in Wuhan City demonstrated a positive relationship between heat stress and human exposure, and both were opposite with social vulnerability. Multiple linear regression between UTCI and the proportion of greenspace, water body and construction land indicated that, more blue or green infrastructure should be integrated within the urban fabric to help mitigate heat stress particularly in the main urban area, while in the metropolitan development area construction land dominating heat stress should be strictly regulated. Furthermore, protecting vulnerable groups such as left-behind children and elderly people should be a priority in rural areas that were generally associated with higher levels of social vulnerability. This study proposed a new heatwave-induced human health risk framework with a local evidence in Wuhan City, and further emphasized that risk zoning could be used as a basic yet important approach to facilitating more effective urban planning guidelines for risk governance. [ABSTRACT FROM AUTHOR]

Aims: To investigate the clinical characteristics, laboratory findings and high- resolution CT (HRCT) features and to explore the risk factors for in-hospital death and complications of coronavirus disease 2019 (COVID-19) patients with diabetes.Methods: From Dec 31, 2019, to Apr 5, 2020, a total of 132 laboratory-confirmed COVID-19 patients with diabetes from two hospitals were retrospectively included in our study. Clinical, laboratory and chest CT data were analyzed and compared between the two groups with an admission glucose level of ≤11 mmol/L (group 1) and >11 mmol/L (group 2). Logistic regression analyses were used to identify the risk factors associated with in-hospital death and complications.Results: Of 132 patients, 15 died in hospital and 113 were discharged. Patients in group 2 were more likely to require intensive care unit care (21.4% vs. 9.2%), to develop acute respiratory distress syndrome (ARDS) (23.2% vs. 9.2%) and acute cardiac injury (12.5% vs. 1.3%), and had a higher death rate (19.6% vs. 5.3%) than group 1. In the multivariable analysis, patients with admission glucose of >11 mmol/l had an increased risk of death (OR: 7.629, 95%CI: 1.391-37.984) and in-hospital complications (OR: 3.232, 95%CI: 1.393-7.498). Admission d-dimer of ≥1.5 μg/mL (OR: 6.645, 95%CI: 1.212-36.444) and HRCT score of ≥10 (OR: 7.792, 95%CI: 2.195-28.958) were associated with increased odds of in-hospital death and complications, respectively.Conclusions: In COVID-19 patients with diabetes, poorly-controlled blood glucose (>11 mmol/L) may be associated with poor outcomes. Admission hyperglycemia, elevated d-dimer and high HRCT score are potential risk factors for adverse outcomes and death. [ABSTRACT FROM AUTHOR]

Phthalates are endocrine disrupting chemicals (EDCs) that pose a serious hazard to the human health. Many epidemiological studies revealed a relationship between phthalates exposure and blood pressure in general population, while the relationship in pregnant women remains unknown. Aimed to elucidate whether phthalate exposure is associated with blood pressure among pregnant women. This study included 636 participants from Wuhan, China. Urine samples were conducted repeatedly in three trimesters, and 9 phthalates were measured in these samples. After each urine was sampled, all the participants completed blood pressure measurements. Associations between repeated measurements of phthalate concentration and blood pressure were evaluated by using generalized estimating equations. Stratified analysis by fetus gender was conducted. Among the pregnant women with male fetuses, mono-i-butyl phthalate (MiBP) exposed in the 1st trimester was associated with the increased diastolic blood pressure (DBP) measured in the 2nd trimester, while the environmental risk score (ERS) measured in the 1st and 2nd trimester was positively associated with systolic blood pressure (SBP) and DBP in the 2nd trimester. No significant relationships were observed among all the population or pregnant women with female fetuses. Exposure to higher levels of MiBP may be related to increased blood pressure during pregnancy in pregnant women with male fetuses. • Repeated measures of urinary metabolites and blood pressure in three trimesters were carried out to cover the whole pregnancy. • Exposure to phthalates was significantly related to the increment of blood pressure in pregnant women with male fetus. • The effects of multi-phthalate risk score were more prominent than single phthalate, which may indicate greater harm to human health. [ABSTRACT FROM AUTHOR]

• A zonal multi-objective runoff control optimization framework was proposed. • A natural endowment and urban development adaptive spatial heterogeneity analysis. • Hydrological features were quantified and partitioned to identify runoff control cost-efficiency. • Pressure adaptive weights for optimization objectives were quantitively assigned. • Environment, economic, and ecological objectives were weighted optimized for green-gray infrastructure. Cost-effective runoff control scheme drafting involves localization, multi-sector coordination, and configuration of multifunctional infrastructures. Numerous independent variables, parameters, weights, and objectives make runoff control optimization quantitatively arduous. This study innovatively proposed a multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development. The quantitative methods of multi-objective evaluation, hydrological feature partition, and pressure-adapted multi-objective weight assignment were proposed. Remote sensing inversion of water quality, hydrological model simulation (using SWAT and SWMM software), landscape pattern index calculation, life cycle cost (LCC), life cycle assessment (LCA) on ecological impact, and NSGA-II optimization algorithm were applied. Wuhan, the most water-sensitive city in China, was studied as a case. Runoff control function (RCF), capital investment (CI), and ecological return on investment (EROI) served as optimized objectives. High, medium, and low built-up regions in Wuhan urban development planning district were extracted by topographic factors and landscape patterns, which comprised 28, 34, and 38% of the case area, respectively. Three corresponding hydrological models were then built to illustrate distinct runoff control cost-efficiency in each region. Pressure distributions on runoff control, economic constraints, and ecological resource scarcity were quantitatively evaluated. And four pressure zones were clustered, which occupied 36, 29, 16, and 19% of the case area, respectively. Then the zonal weighted optimization decision-making matrix (with 3 hydrological models and 5 wt) was established by overlaying the pressure zone and built-up zone. In high, medium, and low built-up regions, optimized solutions reduced annual runoff volume by 86, 82%, and 77%The average runoff investments per square meter of impervious underlying surface in high, medium, and low built-up regions were 34.2, 18.7, and 7.9 RMB yuan, respectively. Medium and low built-up regions may only need 55 and 23% of the high built-up region for the unitary impervious underlying surface to balance runoff control and ecological benefits. Runoff control and financial utilization efficiency enhance with hydrological differentiation zones. Thus, the optimization solutions are zonal adaptive, refined, comparable, replicable, and implementable. [Display omitted] [ABSTRACT FROM AUTHOR]

• The failure mode of double-layer lining structure with defect is revealed. • Bearing Performance of double-layer lining structure with defect is revealed. • A thickness control standard of secondary lining defects is proposed. Difficulties such as large burial depth, large cross-section, and high water pressures exist in the construction of underwater shield tunnels. Thus, the double-layer lining structure begins to be one means of reinforcement of tunnels. To figure out how the depth of the insufficient thickness in the vault of the segment's secondary lining influences the entire structure, the Rail-cum-Road Yangtze River Cross Tunnel in Wuhan is taken as an example, where the deformation distribution, internal force characteristics and failure process of the double-layer lining structure caused by the thickness insufficiency are revealed through a model test method. [ABSTRACT FROM AUTHOR]