ELASTIC: Edge Workload Forecasting based on Collaborative Cloud-Edge Deep Learning

With the rapid development of edge computing in the post-COVID19 pandemic period, precise workload forecasting is considered the basis for making full use of the edge limited resources, and both edge service providers (ESPs) and edge service consumers (ESCs) can benefit significantly from it. Existing paradigms of workload forecasting (i.e., edge-only or cloud-only) are improper, due to failing to consider the inter-site correlations and might suffer from significant data transmission delays. With the increasing adoption of edge platforms by web services, it is critical to balance both accuracy and efficiency in workload forecasting. In this paper, we propose ELASTIC, which is the first study that leverages a cloud-edge collaborative paradigm for edge workload forecasting with multi-view graphs. Specifically, at the global stage, we design a learnable aggregation layer on each edge site to reduce the time consumption while capturing the inter-site correlation. Additionally, at the local stage, we design a disaggregation layer combining both the intra-site correlation and inter-site correlation to improve the prediction accuracy. Extensive experiments on realistic edge workload datasets collected from China's largest edge service provider show that ELASTIC outperforms state-of-the-art methods, decreases time consumption, and reduces communication cost. © 2023 ACM.

Related Return Patterns Adjustment Under the Impact of COVID-19 on Hedge Funds

The latest threat to global health is an ongoing outbreak of a respiratory disease known as COVID-19 and has become a global concern. The exponential spread of the COVID-19 pandemic shook up global markets and caused major adjustments to the world economy. In this paper, we investigate whether these changes affected hedge fund return patterns. We decompose hedge fund index returns into Fama-French factors using data from 2017 - 2019 and compare it to decompositions using data from 2020 and 2021 to date. Our empirical results suggest that the Fama-French factor exposures changed on the conventional hedge funds. This has reflected that COVID-19 has an impact on the return patterns of the hedge funds we selected. The findings have implications for investors and major players in the investment markets. Our research is useful for predicting how the performance of hedge funds changes in market disruption. © 2022 ACM.

Risk Factors of In-hospital Death in COVID-19 Patients：a Meta-analysis

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.

Risk Factors of In-hospital Death in COVID-19 Patients：a Meta-analysis

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.

[Management and short-term outcomes of neonates born to mothers infected with SARS-CoV-2 Omicron variant].

Objective: To summarize the management and short-term outcomes of neonates delivered by mothers infected with SARS-CoV-2 Omicron variant. Methods: A retrospective study was performed on 158 neonates born to mothers infected with SARS-CoV-2 Omicron variant admitted to the isolation ward of Children's Hospital of Fudan University from March 15th, 2022 to May 30th, 2022. The postnatal infection control measures for these neonates, and their clinical characteristics and short-term outcomes were analyzed. They were divided into maternal symptomatic group and maternal asymptomatic group according to whether their mothers had SARS-CoV-2 symptoms. The clinical outcomes were compared between the 2 groups using Rank sum test and Chi-square test. Results: All neonates were under strict infection control measures at birth and after birth. Of the 158 neonates, 75 (47.5%) were male. The gestational age was (38+3±1+3) weeks and the birth weight was (3 201±463)g. Of the neonates included, ten were preterm (6.3%) and the minimum gestational age was 30+1 weeks. Six neonates (3.8%) had respiratory difficulty and 4 of them were premature and required mechanical ventilation. All 158 neonates were tested negative for SARS-COV-2 nucleic acid by daily nasal swabs for the first 7 days. A total of 156 mothers (2 cases of twin pregnancy) infected with SARS-CoV-2 Omicron variant, the time from confirmed SARS-CoV-2 infection to delivery was 7 (3, 12) days. Among them, 88 cases (56.4%) showed clinical symptoms, but none needed intensive care treatment. The peripheral white blood cell count of the neonates in maternal symptomatic group was significantly higher than that in maternal symptomatic group (23.0 (18.7, 28.0) × 109 vs. 19.6 (15.4, 36.6) × 109/L, Z=2.44, P<0.05). Conclusions: Neonates of mothers infected with SARS-CoV-2 Omicron variant during third trimester have benign short-term outcomes, without intrauterine infection through vertical transmission. Strict infection control measures at birth and after birth can effectively protect these neonates from SARS-CoV-2 infection.

Simulation of Evaporative Flow and Coupled Transport Behaviors of Aerosol Particles

Intense scientific interest in the mechanisms of aerosol transport has been aroused due to the global COVID-19 pandemic. In this study, a new droplet evaporation model considering solid components such as salt, has proposed to simulate the diffusion and evaporative flow behaviors of saliva-forming aerosols droplets, caused by human breathing, coughing and sneezing. The model considers the evaporation process on the surface of aerosols and couples the droplet kinetic equations, including the incorporation of influencing factors such as flow resistance, gravity, droplet-like size and initial velocity. Different ambient temperatures, relative humidity and wind speed have been simulated and the mechanisms of aerosols migration behaviors have been analyzed. For individual droplet, the results not only show that the larger the droplet size, the longer it remains suspended in airborne, but also the lower the humidity and the higher the temperature, the faster the evaporation rate. © 2022, Science Press. All right reserved.

The Impact of COVID 19 on the Meat Supply Chain in the USA: A Review.

The COVID 19 pandemic resulted in a considerable influence on the world economy. Being a big sector of the economy, the food supply chain struggled. The meat supply chain was most notably affected as every part of the supply chain from farm to shelf was closely inter-related. With the closure of businesses and restaurants the demand for at home food from grocery stores increased. Meat production facilities were impacted when the virus spread to the workers causing facilities to close or line speeds to slow. The combination of these two issues, in turn, led to there being less meat on the shelves. With less meat animals being harvested, there was less demand for livestock leading to farmers having an excess in slaughter ready animals. The decreased demand for livestock led to economic issues as money was lost in multiple sections of the supply chain. Aside from the economy and supply chain issues, other issues include concerns over the safety of meat products due to decreased safety protocols to increase line speed. Additionally, concerns of animal welfare with the excess of animals being culled were raised due to decreased capacity in processing facilities. While this review paper mainly focuses on characterizing the impact of COVID 19 on the meat supply chain in the USA, the compiled information should be able to provide practical insights to the meat/food industry across the globe to develop potential mitigating strategies against the COVID 19 and/or any similar pandemic incidences in the future.

Psychological experience of infected individuals during the pandemic: A qualitative meta-synthesis

The purpose of this review is to integrate the psychological experience of infected individuals during the pandemic. The spread of the pandemic has led to psychological and emotional impacts on patients. A qualitative synthesis is needed to identify, appraise, and integrate the available qualitative findings to provide an evidence for the development of interventions. A meta-aggregation approach was used to analyze studies published in English from January 2020 to August 2021. The JBI Qualitative Assessment and Review Instrument was used to assess the methodological quality of included studies. The ConQual system was used to establish the dependability and credibility in the synthesized findings. Six phenomenological studies and one narrative inquiry with an overall quality score of 70%-100% were included. The research findings from 87 participants in eligible studies were aggregated into three categories based on similarity of meaning. Two synthesized findings were generated and rated as moderate based on the ConQual score. The synthesized findings suggested that participants had psychological distress such as fear, anxiety, loneliness, and uncertainty, but they accepted the fact of being infected and tried to adjust themselves using some self-coping strategies, such as diverting attention from disease, seeking help from professional counselors, relying on religious beliefs, and participating in religious activities. They would like to learn more about infections and diseases and needed more informational support from health-care professionals. They were looking forward to recovery from the disease. © 2022 Journal of Integrative Nursing Published by Wolters Kluwer - Medknow.

[SWOT analysis of influenza vaccination promotion of primary care staff based on the perspective of the supplier, customer, and management].

Objective: To analyze the situation of influenza vaccination among primary healthcare workers, find out the problems, and explore the strategies and measures to promote influenza vaccination among grass-roots medical staff. Methods: From April to May 2021, key insider interviews and literature research were carried out based on the perspectives of influenza vaccine suppliers (influenza vaccine manufacturers), consumers (primary medical institutions and primary healthcare workers), and managers (governments at all levels, health administrative departments and disease prevention and control departments). The SWOT (strengths, weaknesses, opportunities, and threats) analysis technique was used to comprehensively evaluate the current situation of influenza vaccination among grass-roots healthcare workers, and a SWOT analysis matrix was established. Results: Influenza vaccination of grass-roots healthcare workers have advantages and opportunities, including primary medical and health institutions' vital influenza vaccination accessibility, influenza vaccine safety is higher, COVID-19 outbreak improves the public awareness of respiratory infectious diseases and vaccine production enthusiasm, coronavirus vaccination has strengthened the capacity of the vaccine distribution system. There are also disadvantages and threats such as the high price of influenza vaccine, insufficient supply, low awareness of influenza vaccine vaccination among grass-roots healthcare workers, lack of demand assessment mechanism on influenza vaccine, poor vaccine deployment, structural imbalance in vaccine supply in different areas, and severe vaccine waste. SWOT analysis matrix of the influenza vaccination status of grass-roots healthcare workers was established, forming dominant opportunity (SO) strategy, dominant threat (ST) strategy, inferior opportunity (WO) strategy, and inferior threat (WT) strategy. Conclusion: Measures should be taken by the supplier, the demand-side, and the management side to improve the influenza vaccine coverage rate of primary healthcare workers, but the emphasis should be on the coordination and management of the management side.

A COVID-19 medical image Segmentation method based on U-NET

COVID-19 covers many countries around the world, Chest X-ray is the mainstream method for identifying COVID-19 infection. Traditional Chest X-ray detection requires professional medical personnel, which is time-consuming and laborious. Accurate medical segmentation can be used as an auxiliary means to detect COVID-19, which not only greatly reduces the cost and time, but also greatly improves the applicability. With the rapid development of deep learning, a network model based on U-NET has been proposed and widely used in medical image segmentation in recent years. However, in U-NET network, multiple convolutional pooling operations cause the loss of image spatial information features, and each channel of output features is treated equally, thus lacking flexibility in processing different information. Therefore, in this paper, we add gray bars to the samples to avoid the distortion and feature reduction caused by clipping and resize. the U-NET model architecture is taken as the main body to improve the weight of each channel in the U-NET encoding layer to increase the semantic information of the feature map and improve the segmentation accuracy of the network. In the decoding channel, feature information is restored by up-sampling. Finally, convolution and Softmax function are used to obtain the predictive segmentation image with the same size as the original image. The results show that the improved model has better performance than the traditional U-NET network.

CT Image Classification and Detection of COVID-19 Based on Convolutional Neural Network

As Corona Virus Disease (COVID-19) emerged at the end of 2019, traditional detection is mainly carried out using four methods: coronavirus screening detection strips, COVID-19 antibody detection kits, COVID-19 nucleic acid detection and CT detection, and the problem of low efficiency exists. In order to solve the problem of using neural network to detection a large number of data, slow speed, low efficiency, high cost, complex algorithm structure and low accuracy of detection of large data sets at present. In this paper, by collecting known public COVID-19 CT image data sets, a convolutional neural network algorithm based on residual network is proposed to reduce parameter complexity, modify weights and biases associated with neurons, and simplify the overall network structure. This algorithm is used to improve the accuracy of COVID-19 case classification detection and the convergence speed of the model. Through model verification, the accuracy of the proposed algorithm model is 0.985, the precision is 0.805, the area under the curve (AUC) of the ROC curve is found to be 0.852, and the recall rate is 0.897. The results show that the classification detection algorithm model proposed in this paper has higher accuracy than the general image classification model, is more concise in the network model, reduces the complexity, and can be more effectively applied to the detection of COVID-19. The combination of traditional medical imaging diagnosis and deep learning technology helps medical personnel to make more rapid, accurate and effective diagnosis.

Optimize Path Planning for UAV COVID-19 Test Kits Delivery System by Hybrid Reinforcement Learning

This paper aims to solve an optimization problem in the UAV-enabled COVID-19 test kits delivery system. The UAV intends to find the optimal path to deliver the COVID-19 test kits to people with a high probability of COVID-19 infection in the shortest time. The traditional Deep Reinforcement Learning doesn't perform well in solving the optimization problem because of the slow converging speed and difficult parameters-tuning. In order to solve this problem efficiently, a low-complexity Hybrid Reinforcement Learning is proposed. The algorithm consists of a heuristic algorithm and a Q Learning algorithm. At first, a heuristic algorithm is utilized to calculate the optimal path between any two users. Next, Q learning is applied to determine the sequence of the users to deliver the COVID-19 test kits. As a result, both the delivery sequence and the specific path from one user to another can be generated. The simulation results prove the superiority of the proposed Hybrid Reinforcement Learning in solving the proposed optimization problem compared with the state-of-arts. © 2022 IEEE.

What do U.S. consumers care about regarding beef and its supply chain?

Stated levels of concerns regarding different aspects of beef and its supply chain in the U.S. were studied for a representative sample of 1275 U.S. residents. In addition to top concerns, frequency of general beef consumption and different beef subprimal cuts were collected. Sixty-two percent of respondents indicated eating beef at least twice per week; ground beef was the most frequently purchased beef item. We find that price and food safety prevailed as the most prominent considerations for U.S. residents regarding beef and it's supply chain, though employee welfare, supply chain issues and beef availability have gained prominence in light of the severe disruptions to the industry induced by COVID-19. Concerns regarding cattle emissions, cattle welfare, beef availability and food safety were more prevalent amongst younger consumers. Marketing campaigns highlighting the industry's efforts on improving such matters may be particularly meaningful to younger age groups.

Investigation on cognitive level of covid-19 of medical staffs in Anhui province

Objective During the COVID-19 epidemic period, we investigated the cognitive level of COVID-19 knowledge of medical staffs in Anhui Province and analyzed the influencing factors of cognitive level of COVID-19 knowledge. Methods From February 12, 2020 to March 4, 2020, a self-made questionnaire was used to evaluate the knowledge of COVID-19 among medical staff in Anhui Province. A total of 15 342 valid questionnaires were obtained. By SPSS 17.0 statistical software, and descriptive analysis, t-test, ANOVA analysis, and multiple linear regression were used to analyze the cognitive level of COVID-19 knowledge of medical staffs and the influencing factors. Results The total score of COVID-19 knowledge of medical staffs in Anhui Province was (6.95±2.67) points, the average score of diagnosis knowledge was (2.58±1.74) points, the average score of treatment knowledge was (1.53±1.03) points, and the score of nosocomial infections knowledge was (2.84±1.01) points. There were significant differences in COVID-19 diagnosis knowledge, nosocomial infections knowledge and total score between doctors and nurses (all P < 0.05). Multivariate linear regression analysis showed that the scores in senior and intermediate professional title groups were higher than those in primary professional title group;the scores in master′s degree group and above and undergraduate education group were higher than those in junior college education group;the knowledge scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospital group;the scores in patients aged 30~ years and ≥40 years were lower than those in group < 30 years. The scores in senior and intermediate professional title groups were higher than those in junior professional title group;the scores in municipal, county-level hospitals, primary medical institutions and private medical institutions were lower than those in provincial hospitals;the scores of 30~ years old and ≥40 years old were lower than those of < 30 years old group, and the scores of nurses with bachelor′s degree were higher than junior college degree or below (all P < 0.05). Conclusions The score of COVID-19 knowledge of medical staffs in Anhui Province is low, so we should train them COVID-19 knowledge systematically. We should pay attention to the influencing factors like occupation, title, education background, age and hospital rank when selecting and training anti-epidemic medical staffs. © 2021, Publication Centre of Anhui Medical University. All rights reserved.

Research on Impact of COVID-19 on the Student Management of Vocational and Technical Colleges in China Based on Emerging Network Technologies

The pandemic spread of the COVID-19 epidemic disrupted the normal teaching order of China's vocational and technical colleges. A series of measures to respond to the epidemic, such as postponing the start of school and online education based on emerging network technologies, have caused the students management in vocational and technical colleges to face multiple challenges. In the post-epidemic era, how to promote the validity and efficiency of the student management of vocational and technical colleges based on emerging network technologies becomes an important research question. After sufficient data mining and analysis, this research puts forward some advices to optimize the student management and education system of vocational and technical colleges. The vocational and technical colleges can adopt a unified college student management information system to break through information barriers and realize resource sharing;make full use of emerging network technologies to target the interests of college students and guide their value orientation and public opinion orientation;create multiple organizations Alliance-style management, in-depth exploration of students' learning and living conditions, realizing precise assistance and other coping strategies for student problems, and further improving the efficiency and quality of student management. © 2021 IEEE.

Identifiability as an “Antidote”: Exploring Emotional Contagion and the Role of Anonymity in Twitter Discussions on Misinformation

Misinformation carries both distorted facts and sophisticated emotional signals. Comparing to facts that could be labeled as true or false, we are more concerned about contaminative negative emotions transferring digitally among users. In this study, we explored an emotional contagion effect among misinformation discussion participants on Twitter. We analyzed the sentiment of 573 tweets in 192 discussion threads. Our result revealed that highly emotional tweets do not have a universal effect on the online discussions, but it affects those individuals with limited social and personal identity cues (i.e., being anonymous). We found that anonymous members of the online discussion are more susceptible to emotional contagions than those are not. We also suggest coping strategies that protect social media users’ emotional well-being during the era COVID-19. © 2021, Springer Nature Switzerland AG.

Herding Effect in China's A Share Stock Market under COVID-19 Pandemic

Affected by the COVID-19 pandemic, China's stock market has been experiencing fluctuation in 2020. Deterioration of investors' sentiment prompted more anomalies in the financial market, especially for large-scale unilateral transactions caused by investors' fear and panic. This paper examines the existence of herding effect in Chinese A share main board market using both market-level and industry-level data by testing the non-linear relationship between cross-sectional absolute deviation of returns and market returns. Our findings indicate that herd formation existed in Chinese A share market during non-pandemic period and its effect got more pronounced during the COVID-19 pandemic period. We also observe that the herding effect turned out to be more obvious in the down phase of the stock market than that in the up phase. Sub-sample test classified by industry shows that industries such as transportation, leasing and business services, culture products, etc. have suffered from severely intensified herding effect during pandemic period, while the herding levels of manufacturing and real estate industries did not change significantly. The results shed light on understandings of the decision-making behavior for both individual investors and other market participants, and thus provide important policy implications. © 2021 ACM.

Beneficial effect of Arbidol in the management of COVID-19 infection

This study analyzed the effect of Arbidol, a broad-spectrum antiviral compound, on the outcomes of COVID-19 patients. Records of 252 COVID-19 patients were retrospectively analyzed from February 13 to February 29, 2020 in 4 inpatient wards in the Cancer Center, Union Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China. The rate of clinical improvement was significantly greater among patients treated with Arbidol than among those who did not receive Arbidol (86.8% vs. 54.2%). In moderately and severely ill patients, the clinical improvement rates in the Arbidol group were 95.6% and 81.7%, respectively, which was significantly higher than in the no-Arbidol group (66.6% and 53.8%). Among critically ill patients, however, there was no significant difference. The levels of hypersensitive C-reactive protein, lactate dehydrogenase, D-dimer, IL-6, and IL-10 were increased in non-improved patients but declined during treatment in the improved patients. This suggests these mediators are associated with the disease severity and could potentially serve as prognostic markers. Moreover, our data demonstrate that Arbidol is effective in the treatment of COVID-19 patients and may serve as a cost-effective antiviral treatment strategy for patients with moderate to severe COVID-19 symptoms.

[Impact of cardiovascular metabolic diseases on COVID-19: review of recent progress].

The high comorbidity between cardiovascular and metabolic diseases (CVMD) and coronavirus disease 2019 (COVID-19) and the consequent high mortality and the potential risk of cardiovascular damage have brought great challenges to the clinical diagnosis and treatment of the condition. The latest studies found that advanced age, immune function defects, inflammatory factor storms and oxidative stress damage all potentially contribute to the high comorbidity of the two. Direct virus invasion, myocardial oxygen supply and demand imbalance and vascular endothelial and coagulation dysfunction may be important mechanisms for cardiovascular injury in COVID-19 patients. In addition, the expression level of ACE2 (the cell membrane receptor of SARS-CoV-2) in various organs and the peripheral blood not only mediates the direct invasion and damage of the organs, but also participates in regulation of the balance of systematic inflammation and oxidative stress, thus affecting the susceptibility and outcomes of the patients. Herein we review the recent research progress in the comorbidity between COVID-19 and CVMD and explore the mechanisms of cardiovascular damage caused by SARS-CoV-2, thus to provide a theoretical basis for the clinical diagnosis and treatment of COVID-19 with underlying CVMD.