ABSTRACT
In recent years, machine learning and deep neural networks have achieved remarkable results and have been widely used in different domains. Affected by COVID-19, the potential of gait feature recognition in biometric authentication has gradually emerged. However, machine learning algorithms are generally demanded in terms of computing power, sometimes need the support of cloud service providers, and require raw data, which is often sensitive, most privacy-preserving approaches only encrypted the trained model, and the data collected from users are unprotected. We propose a scheme for running deep neural networks on encrypted data using homomorphic encryption to address these issues. © 2022 IEEE.
ABSTRACT
Safe social distance is an important parameter for the prevention and treatment of a virus transmitted through droplets. However, the distance selected is not suitable for all air environments, and the calculation method of fluid research is time-consuming. Therefore, rapid and accurate prediction of safe social distance is the key to epidemic prevention and control. However, it is difficult for the existing fluid research to obtain the safe social distance rapidly. In this study, we set up a simple and effective numerical model and develop codes that combine the effects of evaporation, drag force, and gravity. We further conducted numerical simulations to investigate the motion of droplets in various air conditions. We completed a single case simulation with only one core and within several minutes, and determined that the resistance time and velocity evolution directly impact the transmission distance. We also observed two-stage regularity of motions in both the vertical and horizontal directions, and competition between evaporation and vertical falling. In addition, we derived a set of analytical solutions to describe the evaporation time and vertical and horizontal distances. The results demonstrated the good accuracy of the predicted data. Herein, we obtained an approximate rather than an accurate solution and, together with empirical coefficients, fitted it based on our numerical simulation. The proposed method can provide a rapid and accurate estimation of safe social distances for various environmental conditions. Common clinical cases were also analyzed, and prevention and control recommendations were provided based on the outcomes of the study. © 2023 Elsevier Ltd
ABSTRACT
To analyze the safety risks of blood products during the COVID-19 pandemic, and to study the emergency countermeasures of the World Health Organization (WHO), the US FDA (FDA) and the Plasma Protein Therapeutics Association (PPTA) to ensure the safety of blood products during the COVID-19 pandemic, in order to suggest improvements for blood product regulation in China in response to public health emergencies. This article uses literature review, comparative research and descriptive research methods to analyze the existing problems of blood product regulation in response to public health emergencies during the COVID-19 pandemic. When responding to sudden epidemic situations or infectious public health emergencies, Chinese government regulatory agencies should strengthen communication and cooperation with blood product manufacturers, industry associations, and professional consulting teams, providing timely scientific industry guidelines to give a full play as the role of industry associations so as to ensure the safety of blood products on the market.
ABSTRACT
Traditional Chinese medicine has been used for the treatment of many diseases including acute infections often associated with public health emergencies for thousands of years. However, clinical evidence supporting the use of these treatments is insufficient, and the mechanism for using Chinese medicine therapy in the public health setting has not been fully established. In this report, the Evidence-based Traditional and Integrative Chinese medicine Responding to Public Health Emergencies Working Group proposed five recommendations to facilitate the inclusion of Chinese medicine as part of our responses to public health emergencies. It is expected that the Working Group’s proposals may promote the investigation and practice of Chinese Medicine in public health settings.
ABSTRACT
This paper analyzes the spread of the COVID-19 epidemic in China, establishes a SEIR+CAQ epidemiologic model that classifies the diagnosed population into asymptomatic, mild, and severe, and considers the condition of an isolated population. First of all, we theoretically analyzed the key problems of the disease-free equilibrium, stability, and basic reproduction number of the model. Then, combined with the actual data, the development trend of the epidemic situation is simulated and compared, and the influence of some important parameters is discussed in the model evaluation part. Finally, based on the theoretical analysis and numerical simulation results, we forecast the future development of the COVID-19 epidemic and put forward some reasonable scientific suggestions for the government to formulate a future epidemic prevention policy. © World Scientific Publishing Company.
ABSTRACT
The duplicate US1 genes of duck enteritis virus (DEV) encode a protein with a conserved Herpes_IE68 domain, which was found to be closely related to the herpes virus immediate early regulatory protein family and is highly conserved among counterparts encoded by Herpes_IE68 genes. Previous studies found the homologous proteins HSV-1 ICP22 and VZV ORF63/ORF70 to be critical for virus transcription and replication. However, little is known about the DEV ICP22 protein. In this paper, we describe the characteristics of this protein based on pharmacological experiments, real-time quantitative Polymerase Chain Reaction, Western blot, and immunofluorescence assays. We also investigate the role of the protein in DEV replication via mutation of US1. As a result, we found that the DEV ICP22 protein is a non-essential immediate early protein predominantly located in the nucleus of infected DEF cells and that DEV replication is impaired by US1 deletion. We also found that ICP22 contains a classical nuclear localization signal (NLS) at 305-312AA, and ICP22 cannot enter the nucleus by itself after mutating residue 309. © Copyright © 2020 Li, Wu, Wang, Ma, Jia, Chen, Zhu, Liu, Yang, Zhao, Zhang, Huang, Ou, Mao, Zhang, Liu, Yu, Pan, Tian, Rehman, Chen and Cheng.
ABSTRACT
Coronavirus disease 2019 (COVID-19), a newly identified acute respiratory disease caused by a strain of novel coronavirus (SARS-CoV-2), has become a worldwide pandemic. From December 2019 to present, millions of cases have been reported, bringing unprecedented pressure on both health and epidemic prevention services in every country. As frontline healthcare workers, ophthalmologists face an increased threat of viral infection, not only because of close contact with patients during examinations or operations, but also due to evidence showing that ocular fluids such as tears or conjunctival secretions may carry the virus. The risk that healthcare workers face is emphasized by the loss of our colleagues who have sacrificed themselves in combating the virus. As a result, it is necessary to have a comprehensive understanding of the threats that we face. In the first part of this review, we start by explaining the structure of SARS-CoV-2 and examining its transmission and means of infection. Next, we summarize the latest scientific advancements of epidemiology, clinical presentations, and current treatments of COVID-19. In the second half of the review, we emphasize the ocular transmission, symptomatic manifestations, and the essential knowledge in an ophthalmology clinic setting. As the pandemic of COVID-19 continues to pose a threat to global health, we hope that this review makes a contribution to combating COVID-19.