ABSTRACT
Interest in online learning is increasing due to its advantages and pedagogical potential. However, few studies have investigated the effects of task-driven instruction on learning outcomes. This study examines the effectiveness of the application of task-driven instruction as a means of verifying that the use of task-driven instruction in online learning is effective by comparing changes in students' grades, intrinsic motivation, perceived social presence, and perceived cognitive load before and after the application of the method. Eighty high school students (33 males) were recruited for this experiment. Prior to the experiment, the purpose and steps of the study were explained frankly and candidly, problems and risks that might arise from participation in the study were pointed out, the benefits that would result from participation in the study were explained, and the possibility of voluntarily withdrawing from the study at any time was clearly communicated and approved by the study subjects or guardians. They were divided into experimental group I and control group II, with 40 students in each group. The results of the study showed that after the implementation of the instruction, the experimental group I performed significantly better than the control group II. In addition, the experimental group II outperformed the control group II in terms of perceived intrinsic motivation, social presence, and cognitive load. © 2023 ACM.
ABSTRACT
There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015–2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 μg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16–11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 −13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution. © 2022 The Authors
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Public facilities are important transmission places for respiratory infectious diseases (e.g., COVID-19), due to the frequent crowd interactions inside. Usually, changes of obstacle factors can affect the movements of human crowds and result in different epidemic transmissions among individuals. However, most related studies only focus on the specific scenarios, but the common rules are usually ignored for the impacts of obstacles' spatial elements on epidemic transmission. To tackle these problems, this study aims to evaluate the impacts of three spatial factors of obstacles (i.e., size, quantity, and placement) on infection spreading trends in two-dimension, which can provide scientific and concise spatial design guidelines for indoor public places. Firstly, we used the obstacle area proportion as the indicator of the size factor, gave the mathematical expression of the quantity factor, and proposed the walkable-space distribution indicator to represent the placement factor by introducing the Space Syntax. Secondly, two spreading epidemic indicators (i.e., daily new cases and people's average exposure risk) were estimated based on the fundamental model named exposure risk with the virion-laden particles, which accurately forecasted the disease spreading between individuals. Thirdly, 120 indoor scenarios were built and simulated, based on which the value of independent and dependent variables can be measured. Besides, structural equation modeling was employed to examine the effects of obstacle factors on epidemic transmissions. Finally, three obstacle-related guidelines were provided for policymakers to mitigate the disease spreading: minimizing the size of obstacles, dividing the obstacle into more sub-ones, and placing obstacles evenly distributed in space. © 2022 Elsevier Ltd
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When public health emergencies occur, a large amount of low-credibility information is widely disseminated by social bots, and public sentiment is easily manipulated by social bots, which may pose a potential threat to the public opinion ecology of social media. Therefore, exploring how social bots affect the mechanism of information diffusion in social networks is a key strategy for network governance. This study combines machine learning methods and causal regression methods to explore how social bots influence information diffusion in social networks with theoretical support. Specifically, combining stakeholder perspective and emotional contagion theory, we proposed several questions and hypotheses to investigate the influence of social bots. Then, the study obtained 144,314 pieces of public opinion data related to COVID-19 in J city from March 1, 2022, to April 18, 2022, on Weibo, and selected 185,782 pieces of data related to the outbreak of COVID-19 in X city from December 9, 2021, to January 10, 2022, as supplement and verification. A comparative analysis of different data sets revealed the following findings. Firstly, through the STM topic model, it is found that some topics posted by social bots are significantly different from those posted by humans, and social bots play an important role in certain topics. Secondly, based on regression analysis, the study found that social bots tend to transmit information with negative sentiments more than positive sentiments. Thirdly, the study verifies the specific distribution of social bots in sentimental transmission through network analysis and finds that social bots are weaker than human users in the ability to spread negative sentiments. Finally, the Granger causality test is used to confirm that the sentiments of humans and bots can predict each other in time series. The results provide practical suggestions for emergency management under sudden public opinion and provide a useful reference for the identification and analysis of social bots, which is conducive to the maintenance of network security and the stability of social order. © 2022
ABSTRACT
Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis，and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library，ScienceDirect，PubMed，Medline，Wanfang Data，CNKI and CQVIP from inception to October 1，2021. Literature screening，data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors（86.37%），and 55 234 deaths（13.63%）〕，that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49，95%CI（1.41，1.57），P<0.001），older age〔WMD=10.44，95%CI（9.79，11.09），P<0.001〕，dyspnoea〔OR=2.09，95%CI（1.80，2.43），P<0.001〕，fatigue〔OR=1.49，95%CI（1.31，1.69），P<0.001〕，obesity〔OR=1.46，95%CI（1.43，1.50），P<0.001〕，smoking〔OR=1.18，95%CI （1.14，1.23），P<0.001〕，stroke〔OR=2.26，95%CI（1.41，3.62），P<0.001〕，kidney disease〔OR=3.62，95%CI （3.26，4.03），P<0.001〕，cardiovascular disease〔OR=2.34，95%CI（2.21，2.47），P<0.001〕，hypertension〔OR=2.23，95%CI（2.10，2.37），P<0.001〕，diabetes〔OR=1.84，95%CI（1.74，1.94），P<0.001〕，cancer〔OR=1.86，95%CI （1.69，2.05），P<0.001〕，pulmonary disease〔OR=2.38，95%CI（2.19，2.58），P<0.001〕，liver disease〔OR=1.65，95%CI（1.36，2.01），P<0.001〕，elevated levels of white blood cell count〔WMD=2.03，95%CI（1.74，2.32），P<0.001〕，neutrophil count〔WMD=1.77，95%CI（1.49，2.05），P<0.001〕，total bilirubin〔WMD=3.19，95%CI（1.96，4.42），P<0.001〕，aspartate transaminase〔WMD=13.02，95%CI（11.70，14.34），P<0.001〕，alanine transaminase 〔WMD=2.76，95%CI（1.68，3.85），P<0.001〕，lactate dehydrogenase〔WMD=166.91，95%CI（150.17，183.64），P<0.001〕，blood urea nitrogen〔WMD=3.11，95%CI（2.61，3.60），P<0.001〕，serum creatinine〔WMD=22.06，95%CI （19.41，24.72），P<0.001〕，C-reactive protein〔WMD=76.45，95%CI （71.33，81.56），P<0.001〕，interleukin-6 〔WMD=28.21，95%CI（14.98，41.44），P<0.001〕，and erythrocyte sedimentation rate〔WMD=8.48，95%CI（5.79，11.17），P<0.001〕were associated with increased risk of in-hospital death for patients with COVID-19，while myalgia〔OR=0.73，95%CI（0.62，0.85），P<0.001〕，cough〔OR=0.87，95%CI（0.78，0.97），P=0.013〕，vomiting〔OR=0.73，95%CI （0.54，0.98），P=0.030〕，diarrhoea〔OR=0.79，95%CI（0.69，0.92），P=0.001〕，headache〔OR=0.55，95%CI（0.45，0.68），P<0.001〕，asthma〔OR=0.73，95%CI（0.69，0.78），P<0.001〕，low body mass index〔WMD=-0.58，95%CI （-1.10，-0.06），P=0.029〕，decreased lymphocyte count〔WMD=-0.36，95%CI（-0.39，-0.32），P<0.001〕，decreased platelet count 〔WMD=-38.26，95%CI（-44.37，-32.15），P<0.001〕，increased D-dimer〔WMD=0.79，95%CI（0.63，0.95），P<0.001〕，longer prothrombin time〔WMD=0.78，95%CI（0.61，0.94），P<0.001〕，lower albumin〔WMD =-1.88，95%CI（-2.35，-1.40），P<0.001〕，increased procalcitonin〔WMD=0.27，95%CI（0.24，0.31），P<0.001〕，and increased cardiac troponin〔WMD=0.04，95%CI（0.03，0.04），P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result，the heterogeneity in gender，renal disease，cardiovascular diseases，asthma，white blood cell count，neutrophil count，platelet count，hemoglobin，and urea nitrogen differed siangificnatly by country（P<0.05）. Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors（including being male，older age，dyspnoea，fatigue，obesity，smoking，stroke，kidney disease，cardiovascular disease，hypertension，diabetes，cancer，pulmonary disease，liver disease，elevated levels of white blood cells，neutrophil count，total bilirubin，aspartate transaminase，alanine transaminase，lactate dehydrogenase，blood urea nitrogen，serum creatinine，C-reactive protein，interleukin-6，and erythrocyte sedimentation rate），and may be decreased by 13 factors（including myalgia，cough，vomiting，diarrhoea，headache，asthma，low body mass index，decreased lymphocyte count and platelet count，increased D-dimer，longer prothrombin time，lower albumin，increased procalcitonin and cardiac troponin）. The conclusion drawn from this study needs to be further confirmed by high-quality，multicenter，large-sample，real-world studies. © 2023 Chinese General Practice. All rights reserved.
ABSTRACT
Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis，and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library，ScienceDirect，PubMed，Medline，Wanfang Data，CNKI and CQVIP from inception to October 1，2021. Literature screening，data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors（86.37%），and 55 234 deaths（13.63%）〕，that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49，95%CI（1.41，1.57），P<0.001），older age〔WMD=10.44，95%CI（9.79，11.09），P<0.001〕，dyspnoea〔OR=2.09，95%CI（1.80，2.43），P<0.001〕，fatigue〔OR=1.49，95%CI（1.31，1.69），P<0.001〕，obesity〔OR=1.46，95%CI（1.43，1.50），P<0.001〕，smoking〔OR=1.18，95%CI （1.14，1.23），P<0.001〕，stroke〔OR=2.26，95%CI（1.41，3.62），P<0.001〕，kidney disease〔OR=3.62，95%CI （3.26，4.03），P<0.001〕，cardiovascular disease〔OR=2.34，95%CI（2.21，2.47），P<0.001〕，hypertension〔OR=2.23，95%CI（2.10，2.37），P<0.001〕，diabetes〔OR=1.84，95%CI（1.74，1.94），P<0.001〕，cancer〔OR=1.86，95%CI （1.69，2.05），P<0.001〕，pulmonary disease〔OR=2.38，95%CI（2.19，2.58），P<0.001〕，liver disease〔OR=1.65，95%CI（1.36，2.01），P<0.001〕，elevated levels of white blood cell count〔WMD=2.03，95%CI（1.74，2.32），P<0.001〕，neutrophil count〔WMD=1.77，95%CI（1.49，2.05），P<0.001〕，total bilirubin〔WMD=3.19，95%CI（1.96，4.42），P<0.001〕，aspartate transaminase〔WMD=13.02，95%CI（11.70，14.34），P<0.001〕，alanine transaminase 〔WMD=2.76，95%CI（1.68，3.85），P<0.001〕，lactate dehydrogenase〔WMD=166.91，95%CI（150.17，183.64），P<0.001〕，blood urea nitrogen〔WMD=3.11，95%CI（2.61，3.60），P<0.001〕，serum creatinine〔WMD=22.06，95%CI （19.41，24.72），P<0.001〕，C-reactive protein〔WMD=76.45，95%CI （71.33，81.56），P<0.001〕，interleukin-6 〔WMD=28.21，95%CI（14.98，41.44），P<0.001〕，and erythrocyte sedimentation rate〔WMD=8.48，95%CI（5.79，11.17），P<0.001〕were associated with increased risk of in-hospital death for patients with COVID-19，while myalgia〔OR=0.73，95%CI（0.62，0.85），P<0.001〕，cough〔OR=0.87，95%CI（0.78，0.97），P=0.013〕，vomiting〔OR=0.73，95%CI （0.54，0.98），P=0.030〕，diarrhoea〔OR=0.79，95%CI（0.69，0.92），P=0.001〕，headache〔OR=0.55，95%CI（0.45，0.68），P<0.001〕，asthma〔OR=0.73，95%CI（0.69，0.78），P<0.001〕，low body mass index〔WMD=-0.58，95%CI （-1.10，-0.06），P=0.029〕，decreased lymphocyte count〔WMD=-0.36，95%CI（-0.39，-0.32），P<0.001〕，decreased platelet count 〔WMD=-38.26，95%CI（-44.37，-32.15），P<0.001〕，increased D-dimer〔WMD=0.79，95%CI（0.63，0.95），P<0.001〕，longer prothrombin time〔WMD=0.78，95%CI（0.61，0.94），P<0.001〕，lower albumin〔WMD =-1.88，95%CI（-2.35，-1.40），P<0.001〕，increased procalcitonin〔WMD=0.27，95%CI（0.24，0.31），P<0.001〕，and increased cardiac troponin〔WMD=0.04，95%CI（0.03，0.04），P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result，the heterogeneity in gender，renal disease，cardiovascular diseases，asthma，white blood cell count，neutrophil count，platelet count，hemoglobin，and urea nitrogen differed siangificnatly by country（P<0.05）. Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors（including being male，older age，dyspnoea，fatigue，obesity，smoking，stroke，kidney disease，cardiovascular disease，hypertension，diabetes，cancer，pulmonary disease，liver disease，elevated levels of white blood cells，neutrophil count，total bilirubin，aspartate transaminase，alanine transaminase，lactate dehydrogenase，blood urea nitrogen，serum creatinine，C-reactive protein，interleukin-6，and erythrocyte sedimentation rate），and may be decreased by 13 factors（including myalgia，cough，vomiting，diarrhoea，headache，asthma，low body mass index，decreased lymphocyte count and platelet count，increased D-dimer，longer prothrombin time，lower albumin，increased procalcitonin and cardiac troponin）. The conclusion drawn from this study needs to be further confirmed by high-quality，multicenter，large-sample，real-world studies. © 2023 Chinese General Practice. All rights reserved.
ABSTRACT
Due to the excessive use of disposable face masks during the COVID-19 pandemic, their accumulation has posed a great threat to the environment. In this study, we explored the fate of masks after being disposed in landfill. We simulated the possible process that masks would experience, including the exposure to sunlight before being covered and the contact with landfill leachate. After exposure to UV radiation, all three mask layers exhibited abrasions and fractures on the surface and became unstable with the increased UV radiation duration showed aging process. The alterations in chemical groups of masks as well as the lower mechanical strength of masks after UV weathering were detected to prove the happened aging process. Then it was found that the aging of masks in landfill leachate was further accelerated compared to these processes occurring in deionized water. Furthermore, the carbonyl index and isotacticity of the mask samples after aging for 30 days in leachate were higher than those of pristine materials, especially for those endured longer UV radiation. Similarly, the weight and tensile strength of the aged masks were also found lower than the original samples. Masks were likely to release more microparticles and high concentration of metal elements into leachate than deionized water after UV radiation and aging. After being exposed to UV radiation for 48 h, the concentration of released particles in leachate was 39.45 muL/L after 1 day and then grew to 309.45 muL/L after 30 days of aging. Seven elements (Al, Cr, Cu, Zn, Cd, Sb and Pb) were detected in leachate and the concentration of this metal elements increased with the longer aging time. The findings of this study can advance our understanding of the fate of disposable masks in the landfill and develop the strategy to address this challenge in waste management. Copyright © 2023 Elsevier B.V.
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Travel is an essential part of life for most people. Tourism is a very important part of the industry in most countries, and the prosperity of tourism is of great significance to promote the economic development of a country. After the outbreak of the Covid-19 pandemic, the development of tourism has entered a through. To explore public travel decision-making considering risk perception under the pandemic, we developed an agent-based model. In the model, we assumed that agents make decisions based on their willingness to travel and risk perception. We also combined the model with a model of opinion dynamics to explore the effect of government risk information on the number of trips. Our results show that individual travel probability decrease when considering risk perception on the pandemic. In the case of medium government credibility, the risk information released by the government has less impact on the number of people traveling. © 2022 The Authors. Published by Elsevier B.V.
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All living cells are affected deadly by their environmental temperature, a rela-tively higher temperature results in a higher metabolic rate, but when it reaches a threshold, its death acceleration occurs. The same principle is also valid for the Covid-19 virus. This paper suggests a sample way to its prevention by a hot cup of water under the noise. The vapor with a high temperature can make the virus greatly inactive. An optimal height from a boiling water surface is recommended. © 2022. Society of Thermal Engineers of Serbia.
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Objective: To describe the spectrum of acute neurological disorders among hospitalized patients who recently received COVID-19 mRNA vaccination. Background: The unprecedented pace of COVID-19 vaccine development, use of novel mRNA technology and large-scale vaccination programs have engendered concerns of adverse events following immunization. Design/Methods: We performed a multi-centre prospective observational study in 7 public acute hospitals. Hospitalized patients who were referred for neurological complaints and had COVID-19 mRNA vaccines, BNT162b2 and mRNA-1273, in the last 6 weeks were classified into central nervous system(CNS) syndromes, cerebrovascular disorders, peripheral nervous system(PNS) disorders, autonomic nervous system(ANS) disorders and immunization stressrelated responses(ISRR). To contextualize our findings, data from National Immunization Registry was probed for the total number and demographic of individuals vaccinated in the corresponding period. Results: From 30 December 2020 to 20 April 2021, 1,398,074 persons (median age 59 years, 54.5% males) received COVID-19 mRNA vaccine (86.7% BNT162b2, 13.3% mRNA-1273);915,344 (65.5%) completed 2 doses. Four hundred and fifty-seven (0.03%) patients were referred for neurological complaints [median age 67 years, 61.5% males;95.8% received BNT162b2 and 4.2% mRNA-1273];classified into 73 (16.0%) CNS syndromes, 286 (62.6%) cerebrovascular disorders, 59 (12.9%) PNS disorders, 0 ANS disorders and 39 (8.5%) ISRRs. Twenty-seven had cranial mononeuropathy, 11 of whom had Bell's palsy. Of 33 patients with seizures, only 4 were unprovoked and occurred within 2 weeks of vaccination. All strokes occurred among individuals with pre-existing cardiovascular risk factors. We recorded 2 cases of cerebral venous thrombosis;none associated with thrombocytopenia. Five had mild flares of immune-mediated diseases. Conclusions: Our observational study does not establish causality of the described disorders to vaccines and is limited by lack of baseline incidence data of several conditions. Nevertheless, we did not observe any obvious signal of serious neurological morbidity associated with mRNA vaccination. The benefits of COVID-19 vaccination outweigh concerns over neurological adverse events.
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With the introduction of the Educational Informationization 2.0 Action Plan, major colleges and universities have also launched online learning along with this educational wave. In order to analyze the interaction and satisfaction of college students' online learning, and to understand the current situation of college online learning, this paper uses a questionnaire survey research method. Based on the existing research results, this paper sorts out the factors that affect the interaction and satisfaction of college students' online learning. These include the basic characteristics of the survey object, teacher-student interaction, student-student interaction, interactive platform, learning resources, learning efficiency, learning literacy, learning platform, and satisfaction. This study found that the students of China West Normal University are quite satisfied with the online learning method, and also proposed strategies to improve the interaction and satisfaction of college students' online learning, such as setting teaching goals, guiding learners to learn, improving students' quality, and enhancing learners' information literacy. At the same time, the result has a certain reference effect for some international universities in online learning interaction and satisfaction. © 2022 ACM.
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Coronavirus disease 2019 (COVID-19) has spread throughout China. However, information about COVID-19 in cities and regions outside Wuhan is limited and the indicators that predict the length of hospital stay for patients with COVID-19 are unclear. Therefore, we collected clinical data from 47 patients with COVID-19 in Quanzhou City. The median age was 38 years [interquartile range (IQR): 31-50 years], and 24 (51%) were male. There were 8 mild, 36 moderate, and 3 severe/critical cases. The median interval from exposure to disease onset was 13 days (IQR: 8-18 days). The incidence of severe/critical cases was 33% (3/10) in patients with hypertension. Common symptoms included fever (83%), cough (77%), fatigue (40%), a sore, dry throat (28%), and diarrhea (21%). One patient (2%) developed respiratory distress syndrome on day 13 of inpatient treatment. Six patients had leukopenia, 17 had elevated C-reactive protein (CRP), and 8 had lymphocytopenia and elevated lactate dehydrogenase (LDH). The median length of hospitalization was 22 days (IQR: 16-30 days). Dynamic monitoring of LDH, CRP, and neutrophil-lymphocyte ratio predicted whether length of hospitalization would exceed 21 days. Most patients presented with mild and moderate disease. Patients with hypertension were more likely to become severe or critical. Dynamic monitoring of LDH, CRP, and neutrophil-lymphocyte ratio levels can help predict delayed discharge from the hospital. © 2022 Lippincott Williams and Wilkins. All rights reserved.
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The emergence of novel coronavirus-infected pneumonia has put tremendous pressure on the operation and organization of urban rail transit. This paper analyzes the calculation method of urban rail transit transport capacity and calculates the safe transport capacity of Shenzhen Metro under the major infectious disease-caused epidemic. This paper then uses Mass Motion passenger flow simulation software to simulate passenger flow to simulate the operation of the station and verify the carrying capacity of Shenzhen Metro stations under the conditions of epidemic prevention. Finally, targeted measures for managing passenger flow of subway under major infectious disease epidemics are proposed to provide ideas and experience for improving the level of subway safety operation and management under major infectious disease epidemics. © 2022 SPIE. All rights reserved.
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Objective: To analyze the epidemiological characteristics of a local outbreak of COVID-19 caused by SARS-CoV-2 B.1.617.2(Delta) variant in Liwan district, Guangzhou, and provide evidence for the further prevention and control of the Delta variant of COVID-19. Methods: From May 21 to June 18, 2021, the incidence data of COVID-19 caused by Delta variant were obtained from National Notifiable Disease Report System of Chinese Disease Prevention and Control Information System and Liwan District Center for Disease Control and Prevention of Guangzhou.Frequency analysis (proportions), histograms, and percentage stacked area plots were used to describe the epidemiological characteristics of the outbreaks. The incubation period and time-varying reproduction numbers (Rt) estimations were used for the further analysis. Results: By June 18, 2021, a total of 127 COVID-19 cases caused by Delta variant was reported in Liwan district. The youngest case was aged 2 years and the oldest was aged 85 years. There were 18.9% (24/127) aged <18 years, 43.3% (55/127) aged 18-59 years, and 37.8% (48/127) aged ≥60 years, the male to female ratio of the cases was 1â¶1.35 (54â¶73). The cases were mainly retired people (32.3%, 41/127), the jobless or unemployed (18.1%, 23/127), and students (16.5%, 21/127). The infections mainly occurred in Baihedong (70.1%, 89/127) and Zhongnan street (23.6%, 30/127) communities in the southern area of Liwan district. The median incubation period of the Delta variant infection was 6 days (range: 1-15 days). The clinical classification were mainly common type (64.6%, 82/127). The basic reproduction number (R0) was 5.1, Rt which once increased to 7.3. The transmissions mainly occurred in confined spaces, such as home (26.8%), restaurant (29.1%), neighborhood (3.9%), and market (3.1%), the household clustering was predominant. Close contacts tracing (66.1%) and community screening (33.1%) were the main ways to find the infections. Conclusion: The COVID-19 outbreak caused by Delta variant in Liwan district of Guangzhou was highly contagious, with the obvious characteristics of household clustering and high proportions of cases in adults aged 18-59 years and elderly people aged ≥60 years.
Subject(s)
COVID-19 , SARS-CoV-2 , Adolescent , Adult , Age Distribution , Aged , Basic Reproduction Number , COVID-19/epidemiology , COVID-19/virology , China/epidemiology , Disease Outbreaks , Female , Humans , Male , Middle Aged , Sex Ratio , Young AdultABSTRACT
Coronavirus Disease 2019 (COVID-19) has rapidly spread in 2020, emerging a mass of studies for lung infection segmentation from CT images. Though many methods have been proposed for this issue, it is a challenging task because of infections of various size appearing in different lobe zones. To tackle these issues, we propose a Graph-based Pyramid Global Context Reasoning (Graph-PGCR) module, which is capable of modeling long-range dependencies among disjoint infections as well as adapt size variation. We first incorporate graph convolution to exploit long-term contextual information from multiple lobe zones. Different from previous average pooling or maximum object probability, we propose a saliency-aware projection mechanism to pick up infection-related pixels as a set of graph nodes. After graph reasoning, the relation-aware features are reversed back to the original coordinate space for the down-stream tasks. We further construct multiple graphs with different sampling rates to handle the size variation problem. To this end, distinct multi-scale long-range contextual patterns can be captured. Our Graph-PGCR module is plug-and-play, which can be integrated into any architecture to improve its performance. Experiments demonstrated that the proposed method consistently boost the performance of state-of-the-art backbone architectures on both of public and our private COVID-19 datasets.
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With over 127 million cases globally, the COVID-19 pandemic marks a sentinel event in global health. However, true case estimations have been elusive due to lack of testing and diagnostic capacity, asymptomatic cases, and individuals who do not get tested or seek care. Concomitantly, new digital surveillance tools to detect, characterize, and report COVID-19 cases are emerging, including using structured and unstructured data from users self-reporting COVID-19-related experiences on the Internet and social media platforms. In this study, we develop and evaluate a hybrid unsupervised and supervised machine learning approach to detect self-reported COVID-19-related symptoms on Twitter during the early stages of the pandemic. Tweets were collected from the public API stream from March 3rd-31st 2020, filtered for COVID-19-related terms. We used the biterm topic model to cluster tweets into theme-associated groups for the first 18 days of tweets, which were then extracted and manually annotated to identify users self-reporting suspected COVID-19 symptoms or status. Using this manually annotated data as a training set, we used an XLNet deep learning model for classifying symptom-related tweets from a larger corpus and also evaluated model performance. From 4, 492, 954 tweets collected, the unsupervised learning process yielded 3, 465 (<1%) symptom tweets used to form our ground-truth COVID-19 symptoms dataset (n = 11, 550). The XLNet text classifier achieved the highest accuracy (.91) and f1 (.62) compared to baseline models evaluated for classification. After re-training with adjusted loss function, we boosted the classifier's precision to 0.81 while maintaining a high f1 (0.66), resulting in identification of an additional 2, 622 symptom-related tweets when applied to an additional 11 days of tweets collected. Our study used a hybrid machine learning approach to enable high precision identification of Twitter user-generated COVID-19 symptom discussions. The model is a digital epidemiology tool that can identify social media users who self-report symptoms during the early periods of an outbreak. © 2021 IEEE.
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In early 2020, under the influence of the global spread of novel coronavirus, colleges and universities across China have been carrying out online teaching. Taking the short film production course in digital media art major in the Academy of Art and Design of Beijing City University as an example, this thesis expounds the overall design of online teaching in digital image creation courses, including the research background, establishment of teaching ideas, teaching operations and the process of solving several key problems in teaching. In addition, this thesis elaborates the advantages and disadvantages of online teaching and puts forward suggestions for improvement, based on the post-class questionnaire survey and this teaching experience. The article provides a reference for the development of online teaching in digital image creation courses. © 2021, Springer Nature Switzerland AG.
ABSTRACT
Biosafety has seriously threatened the survival and development of human beings. Under the situation of the coronavirus disease 2019 (COVID-19) epidemic and the normalization of anti-epidemic, biosafety prevention and control is becoming more and more important, which is directly related to the development of society, economy and politics. At the beginning of COVID-19 epidemic, there was a serious lack of personal protective equipment, due to the shortage of medical emergency supplies and the lack of ability to public health emergencies. In the face of the severe challenge of the epidemic, interdisciplinary and multidisciplinary cooperation is the key to scientific epidemic prevention. The characteristics of the material, such as optical, electrical acoustic magnetic thermal are helpfulforth designandpr parationofmulti-functional new materials which can met the requirements of biosafety prevention indetection prevention and treatment. We should give fulplay to the advantages of biosafety and materials science. Using new biosafety materials to overcome the short coming soft raditional materials can improve or provide new detection methods. Not only can we use biosafety materials to develope a variety of highly effective, low toxicity drugs and vaccines but also to produce multifunctional masks and protective clothing. What we have done has contributed to the preparation of medical emergence supplies and to the fight against the COVID-19 pandemic. At the same time the toxicit of new biosafety materials can not be ignored. Only be accelerating industrialization based on basic research and practical problems can we better cope with other emerging outbreaks of infectious diseases in the future. © 2021, Science in China Press. All rights reserved.
ABSTRACT
Aims An outbreak of coronavirus disease 19 (COVID-19) has altered the dynamic of endoscopic practices. Many guidelines, questionnaires have been published addressing service resumption during the pandemic. Curious about the situation indifferent endoscopic units across the globe, the study was designed to evaluate different aspects of practice resumptionworldwide and their adherence to guidelines. Methods An online questionnaire was created and distributed by national/regional representatives and societies. Redcapplatform was used as the interface;afterwards, Microsoft Excel 2016 and Prism 5 were utilized for data analysis. Results From a total of 307 responses from 47 countries/regions was collected, 290 valid answers were analyzed. Almosthalf (47 %) were in post-peak period by August, 2020. Many units were not designated to be COVID-oriented facility. About15.5 % of centers remained unrecovered, mainly in North and South America;those were recovered, training was still withheld significantly. Nevertheless, opened centers kept safety measurements strictly. Patient load was decreased by 37 %,but waiting list was increased 0-25 %. Among many surveillance methods, body temperature, PCR and chest CT were themost common. 74.8 % increased post-procedural disinfection time and 68.2 % increase in per-case inspection were noted.PPE usage was implemented highly and shortage of these posed as one of the resumption barriers. Post-procedural patientsurveillance was not reinforced. Conclusions The study represented real-time global endoscopic service's adaptation to COVID-19 pandemic. Previouslypublished barriers upon practice resumption remained. Despite Delphi consensus' emphasis on post-procedural surveillance, application was not widely reinforced, raising concerns in disease control.