With the expansion of urbanization, the interaction between different hazards has become increasing evident. In order to promote sustainable development of urban areas, it is particularly important to systematically analyze and evaluate urban safety and security under the coupling effect of multi-hazard risks. In response to the practical needs of urban safety and security assessment practice, this paper constructs an application-oriented urban safety and security quantitative assessment methodology. First, following the comprehensive risk management perspective, the logical relationship between urban safety and security elements is analyzed. It proposes “comprehensive screening, key analysis, and comprehensive evaluation” as a new assessment concept. Second, a system of urban safety and security assessment methods consisting of a weighting method and a function model is constructed. The function model includes two sub-models: a quantitative risk assessment model that considers triggering effects and a quantitative assessment model of emergency capacity that considers the evolution of emergencies. Finally, the method was applied to a coastal urban area in south China. The case study proved that the proposed method system can not only effectively evaluate various disaster risks and emergency capacity but also provide evidence for the formulation and implementation of urban safety and security management measures.
Depression is common worldwide, and stigmatizing attitudes toward depression have proved to be one of the major barriers to seeking professional help. The purpose of this study was to evaluate the level of personal depression stigma and identify its predictive factors among medical students in Hainan, China, as well as explore the gender difference. A total of 2,186 medical students were recruited using stratified random cluster sampling and interviewed by structured anonymous questionnaires. Personal stigma was measured by the standardized Depression Stigma Scale (DSS). Multivariate linear regression models were used to identify predictors of stigma, and the interactions between gender and each predictor were included to test its gender difference. The mean score on DSS Scale was 13.71 ± 5.35, with males significantly higher than females (14.85 vs 12.99, P < 0.0001). Compared to females, males were more likely to agree with ‘I would not vote for a class cadre if I knew they had been depressed’ and ‘I would not make friends with him if I knew he had been depressed’. Multivariate linear regression analysis revealed that males’ personal stigma was predicted by being only child ( ß = 1.01, P = 0.0083), moderate-to-severe depression ( ß = 1.12, P = 0.0302), and lower self-rated academic core competitiveness (Competitive: ß = 1.29, P = 0.0088, Not at all/Somewhat competitive: ß = 1.04, P = 0.0381), while females’ personal stigma was only associated with moderate-to-severe depression ( ß = 1.75, P < 0.0001). Significant interactions were found between gender and self-rated academic core competitiveness. Stigmatizing attitudes toward depression were prevalent among Chinese medical students, especially male students. Gender differences were found in the predictors of stigma. Effective measures must be taken to reduce the stigma of mental health among Chinese medical students.
Information overload is a prevalent challenge in many high-value domains. A prominent case in point is the explosion of the biomedical literature on COVID-19, which swelled to hundreds of thousands of papers in a matter of months. In general, biomedical literature expands by two papers every minute, totalling over a million new papers every year. Search in the biomedical realm, and many other vertical domains is challenging due to the scarcity of direct supervision from click logs. Self-supervised learning has emerged as a promising direction to overcome the annotation bottleneck. We propose a general approach for vertical search based on domainspecific pretraining and present a case study for the biomedical domain. Despite being substantially simpler and not using any relevance labels for training or development, our method performs comparably or better than the best systems in the official TREC-COVID evaluation, a COVID-related biomedical search competition. Using distributed computing in modern cloud infrastructure, our system can scale to tens of millions of articles on PubMed and has been deployed as Microsoft Biomedical Search, a new search experience for biomedical literature: https://aka.ms/biomedsearch.
Pulmonary infection is common in patients with heart failure, yet the risk factors remain unclear. We aimed to evaluate the clinical characteristics and risk factors of pulmonary infection in elderly patients with heart failure, to provide reference to the prevention of pulmonary infection.This study was a retrospective study design. We included elderly heart failure patient admitted to our hospital from April 1, 2018 to August 31, 2020. The characteristics and clinical data of pulmonary infection and no infection patients were assessed. Logistic regression analyses were conducted to identify the risk factors of pulmonary infections in patients with heart failure.A total of 201 patients were included. The incidence of pulmonary infection in patients with heart failure was 23.88%. There were significant differences in the age, diabetes, New York Heart Association (NYHA) grade, left ventricular ejection fraction (LVEF), C-reactive protein (CRP) between infection and no infection group (all P < .05), and there were not differences in the sex, body mass index, alcohol drinking, smoking, hypertension, hyperlipidemia, length of hospital stay between 2 groups (all P > .05). Logistic regression analyses indicated that age ≥70 years, diabetes, NYHA grade III, LVEF 55%, and CRP ≥10 mg/L were the independent risk factors of pulmonary infections in patients with heart failure (all P < .05). Pseudomonas aeruginosa (34.48%), Staphylococcus aureus (19.57%), and Klebsiella pneumoniae (15.22%) were the most common 3 pathogens in patients with pulmonary infection.Heart failure patients with age ≥70 years, diabetes, NYHA grade III, LVEF 55%, and CRP ≥10 mg/L have higher risks of pulmonary infections, preventive measures targeted on those risk factors are needed to reduce pulmonary infections.
Background Early mobilization (EM) may be an effective intervention for the promotion of rehabilitation in noninvasive positive pressure ventilation (NIPPV) patients. The aim of this study was to investigate the effects of EM in patients with NIPPV in Intensive Care Unit (ICU). Methods Participants were randomly allocated to the intervention group involving active and passive activities combined with routine treatments and the control group with routine treatments in this single-center, parallel-designed randomized controlled trial. Participants accepted initiative and passive activities following brought by medical and nursing team who were standardized training The primary outcomes were the incidence of ICU-AW, length of ICU stay, duration of ventilation and mortality. Results There were no adverse event in participants during EM. Compared with the control group, there was a significantly lower length of ICU stay (m = 6.0 vs 7.8 days, respectively, P = 0.038), incidence of ICU-acquired weakness (n = 17.4% vs 50%, respectively, P = 0.026), duration of ventilation (m = 2.1 vs 4.0 days, respectively, P = 0.019) in the intervention group. Conclusions EM is feasible and safe in noninvasive ventilator patients, it can decrease the incidence of ICU-acquired weakness, length of stay and duration of noninvasive ventilation in ICU, and promoted the recovery of grip strength.
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