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1.
Chinese Science Bulletin-Chinese ; JOUR(28-29):3439-3451, 67.
Article in Chinese | Web of Science | ID: covidwho-2089307

ABSTRACT

Persistent air pollution in the Beijing-Tianjin-Hebei region (BTH) has become an extremely complex challenge due to the combined effects of industrial structure, regional characteristics, weather and climate, and development. Although China's air pollution levels have reduced significantly since the Airborne Pollution Prevention and Control Action Plan and the Blue Sky Protection Campaign were implemented, the BTH remains a sensitive and vulnerable area. Such large decrease in primary pollution was mainly attributed to the substantial reductions in economic activities and associated emissions during the 2019 novel coronavirus (COVID-19) lockdown, i.e., around the Chinese New Year of 2020. Yet two consecutive severely polluting weather processes occurred in the BTH around the Chinese New Year of 2020, which have seeded doubt among the Chinese public and policymakers regarding the current scientific understanding of the mechanisms of haze pollution. The causes of formation and maintenance of pollution processes can differ significantly. The formation and maintenance of heavy pollution weather is caused by various factors, which is a complex process. Thus, it is crucial to distinguish the contribution of emissions and meteorological conditions on polluting weather, as well as distinguish the contribution of various meteorological factors on the formation and maintenance of polluting weather, for conducting effective attribution diagnostic analysis in actually environmental and meteorological impact assessment operation systems, especially in areas that are sensitive or vulnerable to air pollution. Identifying the specific meteorological conditions formed by polluting weather and establishing a comprehensive model for discriminating atmospheric dynamics and thermodynamics can provide a scientific basis for improving numerical models for air pollution potential forecasting in the future. Therefore, in this study, we focused on two consecutive severely polluting weather processes in BTH around the 2020 Chinese New Year (January to February 2020), as an ideal and unique field experiment for the prevention and control of current severe air pollution. We explored the reasons for the formation and maintenance of continuous severely polluting weather in the context of "continuous emissions reduction" and "relatively low social activity levels" from the perspective of the abnormal structure of the high-low atmospheric circulation system. Based on comprehensive diagnostic analyses, we quantified the relative contribution of each key meteorological factor to the continuous severely polluting weather in BTH by using the standardized multiple linear regression method. The results indicated that stable maintenance of low-level coastal high-pressure systems led to higher relative humidity at ground level compared with normal years and blocking systems, which are two key meteorological factors that induced persistent polluting weather in BTH. The abnormally stable blocking situation provided a special circulation background for the occurrence and maintenance of persistent heavy air pollution in BTH. The continuous and stable easterly and southerly water vapor transportation structure provided the BTH with more moisture than normal years, and it was conducive to increased moisture absorption by aerosols, especially under blocking. The "subsidence warming" effect of the high-level blocking high-pressure system facilitated the production of a "warm cover" structure in the middle of the troposphere. The presence of the anomalous warm cover structure in the troposphere facilitated the establishment of stable and high humidity weather, which was conducive to the accumulation of pollutants and continued air pollution. Dynamic systems (blocking systems) and water vapor transportation factors directly explained 46.8% of the meteorological causes of persistent heavy air polluting weather events around the 2020 Chinese New Year in BTH.

2.
HKIE Transactions Hong Kong Institution of Engineers ; 28(4):213-220, 2021.
Article in English | Scopus | ID: covidwho-2081532

ABSTRACT

To efficiently fight against the COVID-19 pandemic, a sterilisation module using 265 nm UVC LED packages was developed. In this paper, the performance of the sterilisation module in terms of irradiance uniformity, junction temperature increase and sterilisation efficiency were characterised. The irradiance uniformity fluctuation across the four corners and the centre point in a 130 mm × 130 mm area was below 10%, exhibiting good uniformity. Uniform irradiance was important to achieve consistent sterilisation, which was the primary difference between the UVC LED package developed and commercial UVC LED packages. Key to achieving uniform irradiance was the structure, consisting of a stacked silicon reflector and a secondary optical lens designed by ray tracing simulation. The junction temperature increase of the 265 nm UVC LED package driving at 200 mA was only 28°C, sufficiently low to exhibit better reliability and performance. A 99.99% sterilisation efficiency on E. coli bacteria was achieved within one minute with UV dosage of 2.7 mJ/cm2 at 200 mA driving current. From the results, the novel 265 nm UVC LED package was a time-efficient solution for disinfection purposes. © 2021 The Hong Kong Institution of Engineers.

3.
Annals of Agricultural and Environmental Medicine ; 29(3):375-382, 2022.
Article in English | EMBASE | ID: covidwho-2067567

ABSTRACT

Introduction and Objective. From March 2022, China has been in the rapid progressing stage of the Omicron outbreak. However, the mental status of clinical nurses against infection by the Omicron variant of COVID-19 has been not explored. Therefore, a nationwide online investigation with a larger sample size was conducted to explore the mental status of Chinese frontline clinical nurses, and its influencing factors using sound validated and reliable measurements. Materials and method. A cross-sectional study was conducted, and 1,204 clinical nurses fighting the Omicron outbreak were recruited across various provinces of China. Results. The mean age of the nurses was 30.43 (SD=6.59) years. The majority were female. The rates of these nurses with depression, anxiety, stress, and insomnia symptoms were 29.2%, 37.2%, 19.1%, and 48.8%, respectively. The variables of department, insomnia, fear with COVID-19, turnover intention, job burnout, work coping style, and public recognition of nursing, were significant factors influencing the mental status of clinical nurses. Conclusions. The Chinese clinical nurses fighting the Omicron variant of COVID-19 had a similar level of depression and anxiety, a higher level of insomnia, and a lower level of stress, in comparison with nurses globally who experienced the initial period of the pandemic. Targeted investigation and interventions are urgently needed for Chinese frontline clinical nurses with high levels of anxiety, depression and insomnia, who fought against infection by Omicron. Much more professional advocacy is strongly recommended during control of the pandemic and recovery to consolidate the role and influence of nurses. The contribution and visibility of nursing should be recognized not only by the medical professionals, but by the public in general. Copyright © 2022, Institute of Agricultural Medicine. All rights reserved.

4.
Infocommunications Journal ; 14(2):73-84, 2022.
Article in English | Web of Science | ID: covidwho-2026672

ABSTRACT

The turn of the decade introduced a new era of global pandemics to the world through the appearance of COVID-19, which is still an active crisis at the time of this paper. As a countermeasure, the phenomena of home office and online education became not only widely available, but also mandatory in many countries. However, the performance, reliability and general usability of such real-time activities may be severely affected by unfavorable network conditions. In both contexts, content sharing is now a common practice, and the success of the related use cases may fundamentally depend on it. In this paper, we present our surveys and subjective studies on the Quality of Experience of content sharing in online education and online meetings. A total of 6 surveys and 5 experiments are detailed, addressing topics of student experience, user interface settings, sharing options of lecturers and employees of the private sector, the perceivable effects of network impairments and the related long-term adaptation, the rubber band effect of slide sharing, the overall perceived quality and the separate quality aspects of media loading times, and the preference between visual quality, average frame rate and frame rale uniformity. The findings of the subjective studies do not characterize the use cases of the investigated topics on a general, widely-applicable level, as only a single online platform is involved throughout the experiments. However, their experimental configurations are reinforced by comprehensive surveys and many results indicate statistically significant differences between the selected lest conditions.

5.
7th International Conference on Distance Education and Learning, ICDEL 2022 ; : 133-138, 2022.
Article in English | Scopus | ID: covidwho-2020435

ABSTRACT

During the period of COVID-19, the national universities support the policy of "continuing teaching and learning while stopping the class", and fully apply the teaching advantage of "Internet +"to conduct the online teaching activity. "Technical Fundamentals of Web Front-end", as the main course of the major of financial science and technology, plays a significant role in cultivating professionals and improving the core competitiveness of students. During the epidemic period, the online teaching mode based on SPOC and WeChat, which coordinates the pre-class guidance, in-class research, after-class supervision and development, has been applied to complete the online teaching of 2019 and 2020 students. This paper not only shares the online teaching experience of the course, but also summarizes and discusses the advantages and disadvantages of online education, in order to provide reference for improving the quality of online teaching of financial technology courses. © 2022 ACM.

6.
Innovation in Aging ; 5:731-731, 2021.
Article in English | Web of Science | ID: covidwho-2012934
7.
IEEE Transactions on Computational Social Systems ; : 1-13, 2022.
Article in English | Scopus | ID: covidwho-1992675

ABSTRACT

Since the outbreak of the coronavirus disease 2019 (COVID-19), the issue of how to maintain economic development while containing the epidemic has become a significant concern for decision-makers. Though lockdown measures are verified to be very effective in containing the epidemic, its economic costs and other influences have not been fully explored. As a result, decision-makers in many countries are still hesitant to include the lockdown measure in an intervention strategy in response to COVID-19. To address this issue, we propose a universal computational experiment approach for policy evaluation and adjustment based on the Artificial societies, Computational experiments, Parallel execution (ACP) concept. First, we innovatively construct a model via observable CO<inline-formula> <tex-math notation="LaTeX">$_2$</tex-math> </inline-formula> emissions, which is able to estimate the economic costs affected by nonpharmaceutical interventions. Furthermore, based on the population movement data, a risk source model is proposed to estimate the local transmission risk for any prefectures outside the epicenter. Finally, we integrate the data models in a high-resolution agent-based artificial society and carry out large-scale computational experiments supported by the Tianhe supercomputer. Policy adjustments and evaluations are carried out in four cities: Wenzhou, Guangzhou, Beijing, and Wuhan. Our research findings show important implications for policy-making: 1) the local transmission of a city can be almost contained if lockdowns are adopted immediately when the risk index is larger than 1.645, 1.960, or 2.576 at the 90%, 95%, or 99% confidence interval, respectively;2) if lockdowns are required, in-advance lockdown measures facilitate mitigation efficacy and reduce economic loss;and 3) lockdowns lasting for 7–14 days in a prefecture would be effective in controlling the spread of the epidemic. The duration of the measure should be prolonged with the increment of the initial transmission risk. IEEE

8.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-335650

ABSTRACT

BACKGROUND Debate about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) infection continues. The amount of evidence is increasing and study designs have changed over time. We updated a living systematic review to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) What is the infectiousness of asymptomatic and presymptomatic, compared with symptomatic, SARS-CoV-2 infection? (3) What proportion of SARS-CoV-2 transmission in a population is accounted for by people who are asymptomatic or presymptomatic? METHODS AND FINDINGS The protocol was first published on 1 April 2020 and last updated on 18 June 2021. We searched PubMed, Embase, bioRxiv and medRxiv, aggregated in a database of SARS-CoV-2 literature, most recently on 6 July 2021. Studies of people with PCR-diagnosed SARS-CoV-2, which documented symptom status at the beginning and end of follow-up, or mathematical modelling studies were included. Studies restricted to people already diagnosed, of single individuals or families, or without sufficient follow-up were excluded. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with a bespoke checklist and modelling studies with a published checklist. All data syntheses were done using random effects models. Review question (1): We included 130 studies. Heterogeneity was high so we did not estimate a mean proportion of asymptomatic infections overall (interquartile range 14-50%, prediction interval 2-90%), or in 84 studies based on screening of defined populations (interquartile range 20-65%, prediction interval 4-94%). In 46 studies based on contact or outbreak investigations, the summary proportion asymptomatic was 19% (95% CI 15-25%, prediction interval 2-70%). (2) The secondary attack rate in contacts of people with asymptomatic infection compared with symptomatic infection was 0.32 (95% CI 0.16-0.64, prediction interval 0.11-0-95, 8 studies). (3) In 13 modelling studies fit to data, the proportion of all SARS-CoV-2 transmission from presymptomatic individuals was higher than from asymptomatic individuals. Limitations of the evidence include high heterogeneity and high risks of selection and information bias in studies that were not designed to measure persistently asymptomatic infection, and limited information about variants of concern or in people who have been vaccinated. CONCLUSIONS Based on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic and asymptomatic infections were less infectious than symptomatic infections. Summary estimates from meta-analysis may be misleading when variability between studies is extreme and prediction intervals should be presented. Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection. Without prospective longitudinal studies with methods that minimise selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2.

9.
Journal of Applied Science and Engineering ; 25(6):1015-1024, 2022.
Article in English | Web of Science | ID: covidwho-1771695

ABSTRACT

In this paper, we propose a novel U-Net model based on atrous spatial pyramid pooling for medical image segmentation. In the encoder, a pre-trained ImageNet Efficientnet-B0 network is used to extract features for effective information. Atrous spatial pyramid pooling (ASPP) is used to extract the above multi-scale information between encoding and decoding. Finally, the captured information is cascaded with the information of the encoding layer, and the segmentation accuracy is improved by combining the attention mechanism. Experimental results on public data sets show that the accuracy, recall rate and Dice coefficient of the proposed algorithm are 85.35

10.
Journal of Research in Medical and Dental Science ; 9(11):14-20, 2021.
Article in English | Web of Science | ID: covidwho-1576500

ABSTRACT

The term corona virus (Latin: Corona, crown) is coined due to presence of spikes glycoproteins on the surface that gives it a crown-like appearance. Coronaviruses came from the family Coronaviridae and the order Nidovirales. Novel Corona Virus Disease outbreak happened in January 2020 subsequently dispersed around the world and reason for death of several million people worldwide. Currently, no effective treatment for severe COVID-19 patients is present. Now days, patients are only treated symptomatically. Scientific community working to develop novel antiviral drugs, vaccines, immunomodulatory medications. In the recent scenario of COVID-19 pandemic, we lack any better therapeutic option for treatment of severe COVID-19 patients. MSCs may be a better option for providing emergency therapy. Vast number of studies and clinical trials are warranted regarding the safety and efficacy stem cell therapy in COVID-19 and other respiratory disorders.

12.
BJOG: An International Journal of Obstetrics and Gynaecology ; 128(SUPPL 2):196-197, 2021.
Article in English | EMBASE | ID: covidwho-1276492

ABSTRACT

Background Since the first report of COVID-19 in December 2019, there have been significant concerns regarding the effects of the disease on pregnant and recently pregnant women. Quantifying prevalence, and identifying risk factors for severe COVID-19 in this population is key to planning and providing effective clinical maternal care. Objectives To identify rates of COVID-19 amongst pregnant and recently pregnant women and to identify maternal risk factors for severe COVID-19 and worsening clinical outcomes. Design To address the objectives using the developing evidence base we are using a 'Living systematic review' study design. Methods A systematic search of various databases and sources was conducted, including: Medline, Embase, Cochrane database, WHO COVID-19 database, CNKI, Wanfang databases, preprint servers, social media, reference lists of guidelines and included studies until the 6th of October 2020. Quality assessment of prevalence studies was done using the risk of bias tool by Hoy et al. and comparative cohorts using the Newcastle Ottawa Scale. Data extraction was completed with a pre-piloted form by two independent reviewers. The analysis is undertaken monthly and findings are regularly updated. Results are disseminated through our website: https://www.birmingham.ac.uk/research/who-collabora ting-centre/pregcov/index.aspx. The living systematic review process and collated database has given rise to distinct review questions, and the authors of this focused on prevalence and maternal risk factors. Random effects meta-analysis was used to determine prevalence of COVID-19 and the maternal risk factors associated with severe COVID-19. Results 192 studies were included. Overall, 10% (95% confidence interval 7% to 12%;73 studies, 67 271 women) of pregnant and recently pregnant women attending or admitted to hospital for any reason were diagnosed as having suspected or confirmed COVID-19. Increased maternal age (1.82, 1.27 to 2.63;I2 = 30.1%;7 studies;3561 women), high body mass index (2.37, 1.83 to 3.07;I2 = 0%;6 studies;3380 women), pre-existing maternal comorbidity (1.81, 1.49 to 2.20;I2 = 0%;3 studies;2634 women), chronic hypertension (2.0, 1.14 to 3.48;I2 = 0%;2 studies;858 women), pre-existing diabetes (2.12, 1.62 to 2.78;I2 = 0%;3 studies;3333 women), and pre-eclampsia (4.21, 1.26 to 14.0;I2 = 0%;4 studies;274 women) were associated with severe COVID-19 in pregnancy. Conclusions 1 in 10 pregnant or recently pregnant women attending or admitted to hospital are estimated to have COVID-19. Pre-existing co-morbidities, chronic hypertension, pre-eclampsia, pre-existing diabetes, high maternal age, and high BMI are risk factors for severe COVID-19.

16.
Journal of Research in Medical and Dental Science ; 9(4):433-437, 2021.
Article in English | Web of Science | ID: covidwho-1250128

ABSTRACT

Introduction: In recent days, trend of taking online lectures is booming in medical education all around the globe. Online lectures show its greatest importance during COVID-19 outbreak and lockdown period, where it is the only possible way to teach the international students from home. However, there are several issues including lack of support from management, ignorance & resistance of other faculty members, changes in syllabus of medical education putting extra pressure on overloaded teaching faculty, low level of satisfaction in students, poor internet connection, poor software qualities, poor language skills in students,lack of communication between teacher and students. Material and method: We ran an online survey, under which we send the set of Questions (given in the Table 1) to 54 volunteer Fourth Year Medical students, who were taking online lectures during COVID-19 Pandemic. Results: In our online survey we found that 92 % students agree with idea of saving energy and time through online lectures. 46 % students face poor internet problems, 20 % students face problems to understand online lectures because of their poor language skills,22% students reported lack of concentration during online classes, 38% students reported technical issues,42% students are satisfied, 42% partially satisfied, 10 % students not satisfied. 94% students believe that these online lectures are not enough to make students more confident and independent about medical knowledge. Additionally, 37% students (maximum number of students) reported that they like to take online lectures one zoom app. Conclusion: Online teaching in medical colleges is still a new concept;however, with improved technology, it can be a fruitful deal for the coming generations. During COVID -19, these online lectures became a crucial candlelight in the dark era of lockdown worldwide. Last but not the least, online lectures are not the substitute of face-to-face classroom lectures. Contrarily, if we solve the connectivity issues, electronic device issues, software problems, language issues etc., then only online lectures can reach up to the level of face-to-face classroom lectures.

17.
16th Dahe Fortune China Forum and Chinese High-Educational Management Annual Academic Conference, DFHMC 2020 ; : 254-257, 2020.
Article in English | Scopus | ID: covidwho-1234207

ABSTRACT

Affected by the Coronavirus disease (COVID-19), the safety of cold chain logistics has received unprecedented attention. Under the situation that major economies are under impact, how the cold chain industry can further develop has attracted widespread attention in the academic community. In order to make up for the imperfect deficiencies in the index system of cold chain logistics influencing factors in the existing literature, while considering that existing studies rarely pay attention to the impact of the epidemic on the cold chain industry. Based on the ISM model, this article compares and analyzes factors such as the lack of construction of a cold chain logistics standardization system. Research shows that product quality and safety and information system construction are factors at level one, so they are the most critical factors affecting the development of cold chain logistics. Finally, this article enriches the research of cold chain logistics related fields, provides suggestions for the development of the industry, and has theoretical and practical guiding significance. © 2020 IEEE.

19.
IEEE Transactions on Evolutionary Computation ; 2021.
Article in English | Scopus | ID: covidwho-1138056

ABSTRACT

Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with non-pharmaceutical interventions (NPIs) such as social distancing restrictions and school and business closures. This paper demonstrates how evolutionary AI can be used to facilitate the next step, i.e. determining most effective intervention strategies automatically. Through evolutionary surrogate-assisted prescription (ESP), it is possible to generate a large number of candidate strategies and evaluate them with predictive models. In principle, strategies can be customized for different countries and locales, and balance the need to contain the pandemic and the need to minimize their economic impact. Early experiments suggest that workplace and school restrictions are the most important and need to be designed carefully. They also demonstrate that results of lifting restrictions can be unreliable, and suggest creative ways in which restrictions can be implemented softly, e.g. by alternating them over time. As more data becomes available, the approach can be increasingly useful in dealing with COVID-19 as well as possible future pandemics. IEEE

20.
Public Health ; 186: 1-5, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-642460

ABSTRACT

OBJECTIVES: Nucleic acid testing is the gold standard method for the diagnosis of coronavirus disease 2019 (COVID-19); however, large numbers of false-negative results have been reported. In this study, nucleic acid detection and antibody detection (IgG and IgM) were combined to improve the testing accuracy of patients with suspected COVID-19. STUDY DESIGN: The positive rate of nucleic acid detection and antibody detection (IgG and IgM) were compared in suspected COVID-19 patients. METHODS: A total of 71 patients with suspected COVID-19 were selected to participate in this study, which included a retrospective analysis of clinical features, imaging examination, laboratory biochemical examination and nucleic acid detection and specific antibody (IgM and IgG) detection. RESULTS: The majority of participants with suspected COVID-19 presented with fever (67.61%) and cough (54.93%), and the imaging results showed multiple small patches and ground-glass opacity in both lungs, with less common infiltration and consolidation opacity (23.94%). Routine blood tests were mostly normal (69.01%), although only a few patients had lymphopenia (4.23%) or leucopenia (12.68%). There was no statistical difference in the double-positive rate between nucleic acid detection (46.48%) and specific antibody (IgG and IgM) detection (42.25%) (P = 0.612), both of which were also poorly consistent with each other (kappa = 0.231). The positive rate of combined nucleic acid detection and antibody detection (63.38%) was significantly increased, compared with that of nucleic acid detection (46.48%) and that of specific antibody (IgG and IgM) detection (42.25%), and the differences were statistically significant (P = 0.043 and P = 0.012, respectively). CONCLUSIONS: Nucleic acid detection and specific antibody (IgG and IgM) detection had similar positive rates, and their combination could improve the positive rate of COVID-19 detection, which is of great significance for diagnosis and epidemic control.


Subject(s)
Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adolescent , Adult , Aged , Antibodies, Viral/isolation & purification , Betacoronavirus/genetics , Betacoronavirus/immunology , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Coronavirus Infections/epidemiology , Female , Humans , Immunoglobulin G/isolation & purification , Immunoglobulin M/isolation & purification , Male , Middle Aged , Nucleic Acids/isolation & purification , Pandemics , Pneumonia, Viral/epidemiology , Reproducibility of Results , Retrospective Studies , SARS-CoV-2 , Young Adult
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