Loop Residual Attention Network for Automatic Segmentation of COVID-19 Chest X-ray Images

As COVID-19 continues to put pressure on the global healthcare industry, using artificial intelligence to analyze chest X-rays (CXR) has become an effective way to diagnose the virus and treat patients. Despite that many studies have made significant progress in COVID-19 detection, accurately segmenting infected regions with variable locations and scales from COVID-19 CXR remains challenging. Therefore, this paper proposes a novel framework for COVID-19 CXR image segmentation. Specifically, we design a loop residual module to cyclically extract feature information in the process of encoding and decoding splicing, avoiding the loss of complex semantic information in network computing. At the same time, an absolute position information coding block is proposed to strengthen the position information of feature pixels. Moreover, a hybrid attention module is designed to establish semantic associations between channels and multi-scale spaces. Better feature representation is formed by the fusion of location and scale information to alleviate the impact of variable infection regions on segmentation performance. Extensive experiments are conducted on the public COVID-19 CXR dataset COVID-Qu-Ex, and the results show that our network is leading and robust compared to other networks in COVID-19 segmentation. Author

Trend Prediction of Stock Index Based on Convolutional Neural Network

The emergence of the COVID-19 has a huge impact on the Chinese and American economies, including the fluctuations of stock price in the financial market. It's significantly valuable to search out the rules of index variability under this post-epidemic era. In this paper, we create an improved Convolutional Neural Network to search out the future trend of Shanghai Composite Index and Nasdaq composite index by using the daily data from January 1, 2011 to April 23, 2021, and find out the characteristics through nonlinear test and random lasso algorithm. The empirical results show that the prediction correction determination coefficients of Shanghai Composite Index and Nasdaq composite index reach 0.87 and 0.97 respectively, which shows that it is feasible and effective to use convolutional neural network to predict the stock index. © 2022 IEEE.

[Considerations on vaccines and immunization against COVID-19 for epidemic control in China].

The Delta variant of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a new global wave of the Coronavirus Disease 2019 (COVID-19) pandemic. COVID-19 vaccines currently available in China show high effectiveness against severe illness and death. However, transmission of the virus is not fully stopped by vaccination alone, therefore, integrated vaccination and non-pharmacological interventions is necessary to prevent and control the epidemic in the near future. Further expanded vaccine coverage of primary doses as well as booster shots in China's domestic population are needed to reduce severe illness and death. In order to provide evidence necessary for adjusting and optimizing immunization strategies and pandemic control measures, it is essential to conduct research on vaccine effectiveness against emerging variants, persistence of vaccine-induced protection, surveillance of adverse event following immunization with large-scale vaccine use, and modelling studies on strategic combinations of vaccination and non-pharmacological interventions.

Eltrombopag plus rhtpo versus eltrombopag for itp during the covid-19 pandemic (elaborate-19)

Background: Immune thrombocytopenia (ITP) is an acquired thrombocytopenia caused by immune-mediated platelet destruction and impaired platelet production. Recombinant human thrombopoietin (rhTPO) and Eltrombopag, a small molecule agonist of thrombopoietin receptor (TPO-RA), are both recommended as the subsequent treatment for ITP patients, which also already showed robust efficacy. They increase the number of platelets through different mechanisms, and previous studies demonstrated that they might exert synergic effect. During the COVID- 19 pandemic, the classical subsequent treatment regimen for ITP of immunosuppressants and/or steroids might increase patients' susceptibility of virus infections. The investigators hypothesized that the combination of these two agents could be a promising option for ITP treatment during the COVID-19 pandemic. To minimize ITP patients' risk during the COVID-19 global crisis and to improve treatment efficacy, this treatment regimen of Eltrombopag plus rhTPO should be investigated. This trial is registered with ClinicalTrials.gov, number NCT01667263. Aims: This study aimed to evaluate the sustained responses at 6 months and safety of Eltrombopag plus rhTPO as treatment for corticosteroid- resistant or relapsed ITP patients during the COVID-19 pandemic. Methods: In this open-label, randomized, phase 2 trial, we enrolled confirmed corticosteroid-resistant or relapsed adult ITP patients from 5 different tertiary medical centers in China. They were randomly assigned 1:1 with an interactive web-based response system to receive either Eltrombopag 25-75 mg oral daily according to platelet response plus rh-TPO 300U/kg subcutaneous injection once daily for 7 consecutive days, followed by a tapering dose in maintenance therapy or Eltrombopag monotherapy for 12 weeks (Figure 1). The primary endpoint was 6-month sustained response (SR) defined as platelet counts maintained > 30×109/L and at least a doubling of baseline platelet count. Key secondary endpoints were initial response by day 14, duration of response (DOR), TTR, bleeding scores, and adverse events (AEs). Results: Between August 2020, and March 2021, 60 patients were randomly allocated into either rh-TPO plus Eltrombopag (n=30) or Eltrombopag monotherapy (n=30). At the 6-month follow-up, the proportion of patients with SR was significantly higher in the rh-TPO plus Eltrombopag group than in the Eltrombopag monotherapy group (66.7% vs 36.7%, p= 0.020). The combination of rh-TPO and Eltrombopag resulted in a higher incidence of initial response by day 14 compared with Eltrombopag monotherapy (76.7% vs 60%, p= 0.165). Throughout the follow-up period, overall DOR was greater in the combination group, estimated by the Kaplan-Meier analysis. Bleeding was more effectively controlled in the rh-TPO plus Eltrombopag arm, with fewer bleeding events and lower bleeding scores. There was no difference between the 2 groups in terms of rescue treatments. All subjects tolerated the treatment well, and no grade 4 adverse events or treatment- related death were reported. No statistically significant differences were observed in the incidence of treatment-related AEs between the two groups. Summary/Conclusion: Rh-TPO plus Eltrombopag is an effective and safe treatment for corticosteroid-resistant or relapsed ITP patients during the COVID-19 pandemic. (NCT04516837).

Intelligent Mobile Body Temperature Monitoring Management System for Nursing Home

Public health security is a common challenge facing all mankind and requires efforts from worldwide countries. Since the beginning of 2020, the sudden outbreak of the COVID-19 has affected everyone around the world. Thermometers have played a crucial role in the fight against the pandemic. For example, public places like airports and stations are all equipped with necessary temperature-measuring devices such as medical thermometers, infrared ear thermometers, and thermal imagers. Traditional mercury thermometers not only easily break, but also take a long time to measure body temperature and are difficult to read. As staffers need to be assigned to measure people's temperature, infrared ear thermometers and thermal imagers increase the chances of cross infection and are unable to provide real-time and continuous data, making temperature monitoring and management during the pandemic much more difficult. This paper will introduce an intelligent mobile body temperature monitoring and management system (IMBTMMS) particularly designed for nursing homes. Besides monitoring body temperature on a real-time and continuous basis, the system also provides heart rate and blood oxygen data and intelligently recommends relaxing music solutions. The sensor pad is connected to the mobile app via Bluetooth, with the server on the cloud integrated with an advanced artificial intelligence (AI) algorithm. By regularly processing body temperature, heart rate, and blood oxygen data, the system offers real-time and continuous monitoring, forecasting, warning, and management services. Targeting at use in nursing home, the system enables large-scale monitoring and management, which greatly eases the shortage of manpower during the pandemic and reduces the risk of cross infection. Finally, the system is highly extendable as it can be connected with offline and online medical services, which can be customized as per different demands. © 2021 IEEE.

EuroBonds: Three lessons from China’s “debt centralization/decentralization” experience

Eurobonds, dubbed as Coronabonds in the context of the current coronavirus crisis, are being hotly debated among the euro area member states amid the COVID-19 pandemic. The debate is in many ways a retread of the euro area sovereign debt crisis of 2011–2012. As China’s “debt centralization/decentralization” experience is comparable with the introduction of Eurobonds in the European Union (EU) in terms of institutional mechanism design, we review our previous series of studies of China’s “debt centralization/decentralization” experience to shed some light on the Eurobonds debate. We obtain three key lessons. First, the introduction of Eurobonds in EU is likely to soften the budget constraint of the governments of the euro area member states. Second, it is also likely to strengthen the moral hazard incentives of the governments of the euro area member states to intentionally overstate their budget problems. Finally, the magnitudes of the moral hazard effects generated by the introduction of Eurobonds in EU are likely larger than their respective counterparts in China. © 2021 De Gruyter. All rights reserved.

[Analysis on prevention and control of some infectious diseases in the elderly aged 60 years and above in China and countermeasure recommendation].

As the progress of population aging in China, the proportion of elderly population is increasing. Both chronic diseases and infectious diseases can threaten the health of the elderly. There are many kinds of infectious diseases, including vaccine preventable infectious diseases affecting the health of adults, such as influenza, pneumococcal diseases and herpes zoster. In addition, the newly emerged COVID-19 has caused a pandemic in the world, resulting the highest proportion of deaths occurred in the elderly and posing a serious threat to the health of the elderly. This paper mainly summarizes the prevention and control of vaccine preventable diseases and COVID-19 to which the elderly are susceptible, analyzes the infectious disease problems affecting the health of elderly population, and recommends countermeasures for the prevention and control of these diseases in elderly population.

Student-centred webcast + home-based learning model and investigation during the covid-19 epidemic

With the rapid development of Internet technology, traditional online learning can no longer meet the adaptive learning needs of students. Through big data and learning analysis technology, artificial intelligence technology based on learning has gradually become a new research hotspot. How to further use these big data resources for adaptive learning and push to improve the quality of student training has become an important issue in the current research field. To support students' learning during the COVID-19 epidemic, schools have shifted completely from offline to online teaching. Students study online at home, so the family plays a vital role as a special classroom. Based on the analysis of factors affecting home-based learning, this paper compares live broadcast platforms and constructs a student-centered webcast + home-based learning model under the epidemic situation. Through the implementation effect investigation, the evaluation effect is good. It is hoped that this model can provide reference for teachers and students under the new situation and solve some problems of current online teaching. © IBERAMIA and the authors.

Factors Associated with Increased Risk of SARS-CoV-2 Infections in Diabetics

Novel coronavirus 2019 (COVID-19)is spreading worldwide in 2020. Previous studies showed that elderly diabetic patients are more susceptible to COVID-19 and have higher rates of severity and mortality, though the reasons for this are unclear yet. This research retrieved, the relevant articles in recent years and found that it may be related to the changes of lung structure and function, cellular and humoral immunity deficiency, angiotensin converting enzyme 2, obesity and inflammatory factors, hypercoagulability, oxidative stress, glycosylation, age and other factors in diabetic patients, but whether diabetes increases the susceptibility to COVID-19 needs to be confirmed by further research. Copyright © 2020 by the Chinese General Practice.

[Progress in research of specific antibody dynamic characteristics in patients with COVID-19].

COVID-19 is an emerging infectious disease caused by SARS-CoV-2. After the infection of the virus, the host immune system is stimulated to produce multifarious specific antibodies to decrease or eliminate effects of the pathogen. Study of the specific antibodies dynamic characteristics in patients with COVID-19 is very important for the understanding and diagnosis of the disease, research and development of vaccine, and planning of prevention and control strategy. This paper reviews and summarizes the domestic and oversea research on dynamic characteristics of specific antibodies of COVID-19 patients, including the antibody producing, duration and level, and its possible influencing factors in order to improve the understanding of the immunological characteristics of COVID-19.

[Early containment strategies and core measures for prevention and control of novel coronavirus pneumonia in China].

In December 2019, novel coronavirus pneumonia epidemic occurred in Wuhan, Hubei Province, and spread rapidly across the country. In the early stages of the epidemic, China adopted the containment strategy and implemented a series of core measures around this strategic point, including social mobilization, strengthening case isolation and close contacts tracking management, blocking epidemic areas and traffic control to reduce personnel movements and increase social distance, environmental measures and personal protection, with a view to controlling the epidemic as soon as possible in limited areas such as Wuhan. This article summarizes the background, key points and core measures in the country and provinces. It sent prospects for future prevention and control strategies.