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1.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(7): 1044-1048, 2022 Jul 10.
Article in Chinese | MEDLINE | ID: covidwho-1954150

ABSTRACT

Objective: To investigate the local epidemic of COVID-19 caused by 2019-nCoV Delta variant in Zhenhai district of Ningbo, identify the transmission chain and provide reference for the prevention and control of COVID-19 epidemic. Methods: The incidence data of COVID-19 in Zhenhai from 6 to 18 December, 2021 were collected in field investigation. Field epidemiological investigation was conducted to understand the epidemiological characteristics of COVID-19 cases and analyze the transmission chains. Results: The first case might be infected with 2019-nCoV through direct or indirect exposure when passing through a medium-risk area, then a family cluster was caused, and the epidemic spread through close contacts of family members with others such as work, daily life, and moxibustion. The epidemic lasted for 14 days, and 74 confirmed COVID-19 cases were reported. The median incubation period was 4.0(3.0,5.8)d. All the cases were in a chain of transmission for more than 6 generations, and the intergenerational interval was 3.5(2.0,5.3)d. The gene sequencing result indicated that the pathogen was Delta AY.4 variant of 2019-nCoV. Both the epidemiological investigation and the gene sequencing results supported that the local COVID-19 epidemic in Zhenhai was associated with the COVID-19 epidemic in Shanghai. Conclusions: The transmission chain of this epidemic was clear. Delta AY.4 variant has obvious characteristic to cause case clusters in families, places with poor ventilation, and residential communities. It is suggested to strengthen the health management in key areas and key populations, and increase the frequency of nucleic acid testing.


Subject(s)
COVID-19 , Epidemics , China/epidemiology , Humans , SARS-CoV-2
2.
Corrosion Management ; - (165):31-33, 2022.
Article in English | Scopus | ID: covidwho-1929340
3.
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering ; 42(12):4623-4632, 2022.
Article in Chinese | Scopus | ID: covidwho-1912216

ABSTRACT

Coronavirus Disease 2019 is an acute respiratory infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2, which has posed a major threat to world economic development and people's health and security. In view of the emergence of virus variants, the difficulty of prevention and control is constantly escalating, and rapid, simple and large-scale detection methods play a key role in epidemic control. Based on Fourier transform infrared spectroscopy detection technology, pattern recognition and plasma disinfection technology, this paper developed a new integrated system for the detection and disinfection of pathogens, and preliminarily tested the effectiveness of the system. In terms of 'detection', the data scale was expanded from 115 to 857 cases. Recognition algorithms including partial least squares classification and convolutional neural network were used to establish classification models for the positive, health control and interference samples, and the prediction accuracy could reach 91.97% and 98.29% respectively. In terms of 'disinfection',to reduce the safety risk of the operation safety, a sample drying and disinfection module and a flexible disinfection film were developed based on the plasma disinfection technology, which was used to protect the key positions of the instruments. The disinfection rate of E. coli in both modules could be higher than 99.9%, in line with the relevant provisions. In summary, the two parts of the spectroscopy detection process of Coronavirus Disease 2019 samples have been innovated. For the first time, the combination of 'detection' and 'disinfection' has been realized, which is conducive to the application and promotion of spectroscopy detection methods. © 2022 Chin. Soc. for Elec. Eng.

4.
ENGINEERING ; 10:155-166, 2022.
Article in English | Web of Science | ID: covidwho-1906991

ABSTRACT

The coronavirus disease 2019 (COVID-19) and concerns about several other pandemics in the 21st century have attracted extensive global attention. These emerging infectious diseases threaten global public health and raise urgent studies on unraveling the underlying mechanisms of their transmission from animals to humans. Although numerous works have intensively discussed the cross-species and endemic barriers to the occurrence and spread of emerging infectious diseases, both types of barriers play synergistic roles in wildlife habitats. Thus far, there is still a lack of a complete understanding of viral diffusion, migration, and transmission in ecosystems from a macro perspective. In this review, we conceptualize the ecological barrier that represents the combined effects of cross-species and endemic barriers for either the natural or intermediate hosts of viruses. We comprehensively discuss the key influential factors affecting the ecological barrier against viral transmission from virus hosts in their natural habitats into human society, including transmission routes, contact probability, contact frequency, and viral characteristics. Considering the significant impacts of human activities and global industrialization on the strength of the ecological barrier, ecological barrier deterioration driven by human activities is critically analyzed for potential mechanisms. Global climate change can trigger and expand the range of emerging infectious diseases, and human disturbances promote higher contact frequency and greater transmission possibility. In addition, globalization drives more transmission routes and produces new high-risk regions in city areas. This review aims to provide a new concept for and comprehensive evidence of the ecological barrier blocking the transmission and spread of emerging infectious diseases. It also offers new insights into potential strategies to protect the ecological barrier and reduce the wide-ranging risks of emerging infectious diseases to public health. (c) 2020 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

5.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(6): 841-845, 2022 Jun 10.
Article in Chinese | MEDLINE | ID: covidwho-1903514

ABSTRACT

Objective: To investigate the infection rate in close contacts of COVID-19 patients before and after the last negative nucleic acid test, evaluate the effect of dynamic nucleic acid test in determining the infectivity of COVID-19 patients. Methods: Dynamic nucleic acid test results of COVID-19 cases were collected in a retrospective cohort study. COVID-19 cases with negative nucleic acid test results before their first positive nucleic acid tests were selected as study subjects. Close contacts of the index cases and the secondary close contacts were kept isolation for medical observation to assess their risk of infection. Results: This study included 89 confirmed cases from two local COVID-19 epidemics in Ningbo. A total of 5 609 close contacts were surveyed, the overall infection rate was 0.20%. No close contacts of the COVID-19 cases before the last negative nucleic acid test were infected, and the infection rate in the close contacts of the COVID-19 cases after the last negative nucleic acid test was 1.33%, all of these close contacts lived together with the index cases. No secondary close contacts were infected. Conclusion: COVID-19 patient becomes infectious after the last nucleic acid is negative, and has no infectivity before the last nucleic acid negative.


Subject(s)
COVID-19 , Epidemics , Nucleic Acids , COVID-19/epidemiology , Humans , Retrospective Studies , SARS-CoV-2
6.
Chinese General Practice ; 25(11):1383-1386 and 1392, 2022.
Article in Chinese | Scopus | ID: covidwho-1835846

ABSTRACT

Background: For a period of time, the outbreak of the COVID-19 outbreak in many urban villages in our country had caused concern. The dense and complex population structure of urban villages, with their inter-regional mobility, posed a challenge to the prevention and control of the epidemic. Objective: Urban village areasare more prone to regional outbreaks of infectious diseases because of their spatial environment, demographic characteristics, cross-regional mobility and the characteristics of residents' medical treatment behavior. The purpose of this study was tounderstand the characteristics of the COVID-19 epidemic situation in urban villages and the current situation and difficulties of primary care institutions in carrying out COVID-19 epidemic prevention and control measures, in order to provide references for primary care institutions to deal with normalized prevention and control, social dynamic clearing work and future infectious disease prevention and control. Methods: By using public opinion analysis, literature retrieval, online interviews with epidemic prevention and control personnel and experts in urban village, the epidemic situation, prevention and control status of urban village were summarized, and the existing weak links and important loopholes were analyzed. Results: Based on the relevant information, a total of six points of concern were extracted: (1) The number of mapping and screening objects was large, which was the focus and difficulty of epidemic prevention and control work in urban villages.(2) There was not strict closed-loop management lead to virus carriers who were not timely controlled, which caused a risk of spreading the epidemic.(3) The prevention and control of nosocomial infection in primary care institutions was not in place.(4)There were loopholes in the inspection of close contacts in the principle of territorial management;close contacts who did not live and work in the same administrative area but only screened in their living places, which may lead to the spread of the epidemic in workplaces where secondary close contacts may be at risk of infection were not screened in a timely manner.(5) Overload had become the norm, highlighting the large gap in primary health care manpower.(6) During the normalization of epidemic prevention and control, residents were paralyzed and careless, and the phenomenon of not wearing masks in public places and crowd gathering was common. Health education still needs to be strengthened and emphasized that residents were the first responsible for their own health. Conclusion: Primary care providers played an important role in the prevention and control of COVID-19 in urban village by undertaking community management, outpatient treatment, public health services, health education, vaccination, quarantine hotel stationing, joint prevention and control, etc. It was recommended that additional fever sentinel clinics be set up for early detection and isolation to avoid further spread of the epidemic, rental houses be requisitioned to meet the demand for isolated medical observation, primary care institutions be strengthened for hospitalization and prevention, green relief channels be opened to protect special groups from medical treatment, volunteers be organized to reinforce primary care institutions, and health education emphasized that residents were the first to be responsible for maintaining their own health and raised personal awareness of the risk of COVID-19 prevention and control. Copyright © 2022 by the Chinese General Practice.

7.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816891

ABSTRACT

Background: Serology tests for detecting the antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can identify previous infection and help to confirm the presence of current infection. Objective: The aim of this study was to evaluate the performances of a newly developed high throughput immunoassay for anti-SARS-CoV-2 IgG antibody detection. Results: Clinical agreement studies were performed in 77 COVID-19 patient serum samples and 226 negative donor serum/plasma samples. Positive percent agreement (PPA) was 46.15% (95% CI: 19.22% ∼74.87%), 61.54% (95% CI: 31.58% ∼86.14%), and 97.53% (95% CI: 91.36% ∼99.70%) for samples collected on 0-7 days, 8-14 days, and ≥15 days from symptom onset, respectively. Negative Percent Agreement (NPA) was 98.23% (95% CI: 95.53% ∼99.52%). No cross-reactivity was observed to patient samples positive for IgG antibodies against the following pathogens: HIV, HAV, HBV, RSV, CMV, EBV, Rubella, Influenza A, and Influenza B. Hemoglobin (200 mg/dL), bilirubin (2 mg/dL) and EDTA (10 mM) showed no significant interfering effect on this assay. Conclusion: An anti-SARS-CoV-2 IgG antibody assay with high sensitivity and specificity has been developed. With the high throughput, this assay will speed up the anti-SARS-CoV-2 IgG testing.

8.
Journal of East Asian Studies ; 2022.
Article in English | Scopus | ID: covidwho-1805488

ABSTRACT

How can authoritarian regimes effectively control information to maintain regime legitimacy in times of crisis? We argue that media framing constitutes a subtle and sophisticated information control strategy in authoritarian regimes and plays a critical role in steering public opinion and cultivating an image of competent government during a tremendous crisis. Using structural topic models (STM), we conduct a textual analysis of more than 4,600 news reports produced by seven Chinese media outlets during the COVID-19 pandemic. We find that Chinese media, instructed by the propaganda authorities, used a heroism frame to feature frontline medics' sacrifices when saving others in need and resorted to a contrast frame to highlight the poor performance of the United States in the fight against COVID-19. We also show that both state and commercial media outlets used these two frames, though the tone of commercial media coverage was generally more moderate than the state media version. © 2022 Cambridge University Press. All rights reserved.

9.
5th Asian Conference on Artificial Intelligence Technology, ACAIT 2021 ; : 254-258, 2021.
Article in English | Scopus | ID: covidwho-1788611

ABSTRACT

Coronavirus Disease 2019 (COVID-19) has become an unprecedented public health crisis since December of 2019. Compared with real-time reverse transcription polymerase chain reaction (rRT-PCR), the computer-aided diagnosis machine learning algorithm based on medical images can vastly ease the burden on clinicians. Even so, despite existing hundreds of millions of confirmed cases worldwide, there has not been a mature, large scale, high quality, single standard shared image data set yet, which can lead to some problems. For instance, 1) Because the sources of medical images and the collection standards are not guaranteed, features extracted by the neural network may not be very ideal. 2) Due to the small number of samples, some outliers (e.g., blurry medical images, inconspicuous symptoms) may significantly descend the performance of the model. To address these problems, we propose an adaptive self-paced transfer learning (ASPTL) algorithm in this paper. Specifically, inspired by the process of human learning from easy to difficult, we also evaluated the learning difficulty of the samples. Samples with no obvious disease features or wrong labels are relatively difficult to diagnose, and the samples that are easy to diagnose are selected adaptively in the iterative process. In addition, we adopt transfer learning to select easy to learn samples on the pre-trained network by self-paced learning, and gradually fine-tune the pre-trained model in an iterative way. We designed two experiments to validate the ASPTL algorithm's performance on COVID-19. The reult prove the effectiveness on solving mentioned problems. © 2021 IEEE.

10.
IEEE Internet of Things Journal ; 2022.
Article in English | Scopus | ID: covidwho-1779143

ABSTRACT

Mobile sensing systems have been widely used as a practical approach to collect behavioral and health-related information from individuals and to provide timely intervention to promote health and well-being, such as mental health and chronic care. As the objectives of mobile sensing could be either personalized medicine for individuals or public health for populations, in this work we review the design of these mobile sensing systems, and propose to categorize the design of these systems in two paradigms –(i) Personal Sensing and (ii) Crowd Sensing paradigms. While both sensing paradigms might incorporate common ubiquitous sensing technologies, such as wearable sensors, mobility monitoring, mobile data offloading, and cloud-based data analytics to collect and process sensing data from individuals, we present two novel taxonomy systems based on the (a) Sensing Objectives (e.g., goals of mHealth sensing systems and how technologies achieve the goals), and (b) the Sensing Systems Design and Implementation (D&I) (e.g., designs of mHealth sensing systems and how technologies are implemented). With respect to the two paradigms and two taxonomy systems, this work systematically reviews this field. Specifically, we first present technical reviews on the mHealth sensing systems in eight common/popular healthcare issues, ranging from depression and anxiety to COVID-19. Through summarizing the mHealth sensing systems, we comprehensively survey the research works using the two taxonomy systems, where we systematically review the Sensing Objectives and Sensing Systems D&I while mapping the related research works onto the life-cycles of mHealth Sensing, i.e., (1) Sensing Task Creation &Participation, (2) Health Surveillance &Data Collection, and (3) Data Analysis &Knowledge Discovery. In addition to summarization, the proposed taxonomy systems also help the potential directions of mobile sensing for health from both personalized medicine and population health perspectives. Finally, we attempt to test and discuss the validity of our scientific approaches to the survey. IEEE

11.
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice ; 42(1):24-36, 2022.
Article in Chinese | Scopus | ID: covidwho-1771786

ABSTRACT

With the continuous improvement of trade freedom and the cooperation level of financial institutions among the countries along the Belt and Road, the financial markets among these countries are also gradually integration. Research on identification, contagion and measurement of financial market risk among countries along the Belt and Road is of great practical significance to ensure the healthy development of regional finance. In this paper, the extreme risk spoillover network of stock markets along the Belt and Road is constructed by using TENET method, and the risk characteristics, risk sources, risk transmission paths and risk evolution laws of stock markets under extreme tail risk situation are explored. The research results show that the systemic risk index of the stock markets along the Belt and Road countries has time-varying characteristics, and presents an upward trend during periods of economic pressure. From a regional point of view, the European region was at high risk in 2008 due to the financial crisis, and the Asian region was at high risk during the 2020 COVID-19 pandemic. From the perspective of specific countries, Greece and Cyprus, which are more affected by the European debt crisis, are at higher risk. China mainly receives external financial risks in the Belt and Road financial risk network, which mainly come from Israel, Greece, Singapore and other countries. This research can provide theoretical guidance for macro policy makers and transnational financial investment institutions of countries along the Belt and Road to monitor financial risks and manage foreign imported risks. © 2022, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.

12.
Journal of Geo-Information Science ; 24(3):533-545, 2022.
Article in Chinese | Scopus | ID: covidwho-1761235

ABSTRACT

Aiming at the problem of insufficient quantity and spatial refinement in the extraction of industrial heat source from annual scale thermal anomaly data, a neural network industrial heat source extraction method based on temperature feature template is proposed by using VIIRS active fire data. This study took Beijing-Tianjin-Hebei and its surrounding areas as the study area, Firstly, according to the spatial aggregation characteristics of industrial heat sources, the heat source objects were divided by the OPTICS algorithm. Secondly, according to the thermal radiation characteristics of the heat sources, the temperature characteristic template of industrial heat sources and non-industrial heat sources were constructed. Finally, the BP neural network was used to extract industrial heat source objects using the temperature feature template and heat source statistical characteristics as parameters. The results show that: (1) the extraction precision of industrial heat source of the neural network algorithm of temperature feature template proposed in this paper reached 96.31%. Compared with time filtering and logistic regression methods, the extraction precision of industrial heat sources was improved by 8.45% and 7.53%, respectively;(2) From 2015 to 2020, the number of industrial heat sources in the six provinces and cities in Beijing-Tianjin-Hebei and its surrounding areas decreased by 27.46%. The number of industrial heat source objects and heat anomalies in Hebei Province decreased by 8.06% and 7.44% annually, respectively, which was the largest decrease compared with other provinces and cities. The concentration of industrial heat sources in Shandong and Tianjin increased by 25.72% and 86.64%, respectively, indicating that the industrial transformation and upgrade policies in the two places have achieved remarkable results;(3) Tangshan, Handan, Lvliang, and Changzhi accounted for 31.37% of the total industrial heat sources in the study area, which are the main cities in Beijing-Tianjin-Hebei and its surrounding areas. The degree of industrial heat source accumulation and energy consumption in seven cities such as Linfen and Taiyuan was higher than those in other cities;The degree of industrial heat source accumulation and energy consumption in 11 cities such as Beijing and Zhoukou was lower than those in other cities;(4) From January to May 2020, the number of industrial heat anomalies in Beijing-Tianjin-Hebei and its surrounding areas remained unchanged or increased compared with the same period in 2019 and 2021. The COVID-19 had no significant impact on the industrial heat source in the study area. The number of industrial heat anomalies in Wuhan in January and February 2020 decreased by more than 66.67% compared with that in the same period in 2019 and 2021, the number of industrial heat anomalies from March to May 2020 was lower than that in the same period of 2019. The COVID-19 has had a significant impact on industrial heat sources in Wuhan from January to May 2020. This study reflects the current situation and trend of industrial heat source development in Beijing-Tianjin-Hebei and its surrounding areas, which provides a valuable reference for the formulation and adjustment of relevant policies such as reducing energy consumption and improving secondary industry concentration. © 2022, Science Press. All right reserved.

13.
9th International Conference On Secure Knowledge Management In Artificial Intelligence Era, SKM 2021 ; 1549 CCIS:186-199, 2022.
Article in English | Scopus | ID: covidwho-1750601

ABSTRACT

Social media fuels fake news’ spread across the world. English news has dominated existing fake news research, and how fake news in different languages compares remains severely under studied. To address this scarcity of literature, this research examines the content and linguistic behaviors of fake news in relation to COVID-19. The comparisons reveal both differences and similarities between English and Spanish fake news. The findings have implications for global collaboration in combating fake news. © 2022, Springer Nature Switzerland AG.

14.
Chinese Science Bulletin-Chinese ; 67(6):473-480, 2022.
Article in Chinese | Web of Science | ID: covidwho-1745366

ABSTRACT

Selenium (Se) is an essential trace element for animal and human health. Se deficiency and Se excessive intake can lead to severe symptoms and are related to diseases. Se is mainly combined with protein in the form of selenocysteine (Sec) and selenomethionine (Se-Met) in the human body. Generally, proteins formed by incorporating Sec into them are called selenoproteins, while proteins bound in other forms are called Se-containing proteins. Selenoprotein is the main form of Se to exert its biological functions in the human body, and Se deficiency could reduce the content and activity of selenoproteins and disturb the normal physiological function. Researches on the relationship between selenoproteins and human health have received increasing attention, and a comprehensive understanding of the function of selenoproteins is helpful to explain the effects of Se on human health. Although the functions of selenoproteins are not yet fully understood, the critical role of many selenoproteins in human health has been revealed increasingly. So far, 25 kinds of selenoproteins have been found in the human body, and this review focuses on the structure and biological function of glutathione peroxidase (GPX), thioredoxin reductase (TrxR) and iodothyronine deiodinase (ID) families and their relationship with diseases. It shows that selenoproteins such as GPX, TrxR and ID families have biological functions of regulating cell oxidative stress, endoplasmic reticulum stress, antioxidant defense, immune response and inflammatory response. The single nucleotide polymorphism (SNP) and DNA methylation in the promoter region of selenoprotein are related to the risk of diseases. Selenoproteins play a vital role in the pathogenesis and prevention of diseases such as tumors, cardiovascular diseases, osteoarthritis (OA), Keshan disease (KSD), Kashin-Beck disease (KBD), and corona virus disease 2019 (COVID-19) through their genetic and epigenetic forms. This research will provide clues and basis for further revealing the role of Se and selenoprotein in human health and screening to prevent disease targets. However, due to the complexity and unknown biological functions of selenoproteins, the mechanism of selenoproteins in resisting diseases and promoting human health is still worthy of further exploration and research.

15.
IEEE Transactions on Industrial Informatics ; 2022.
Article in English | Scopus | ID: covidwho-1731041

ABSTRACT

Obstructive sleep apnea-hypopnea syndrome (OSAHS) has been gradually valued due to its high prevalence, high risk, and high mortality. This article is to find an alternative to the polysomnography (PSG) OSAHS diagnosis method and assesses the subject's degree of illness considering the supply chain and Industry 5.0 requirement, efficiently, accurately and easily. The blood oxygen saturation (SpO2) signal is used to count the number of apnea or hypoventilation events. It extracts 35-dimensional features based on the time domain to enhance the process resilience, including approximate entropy, Centralized Trend Measurement (CTM), and LZ complexity for the diagnosis process in supply chains. This article summarizes the Oxygen Desaturation Index (ODI) characteristics. The feature selection process is reduced from 35 to 7 dimensions and benefits the implementation in the practical supply chains in industry 5.0. A 92% accuracy rate is reached in assessing the prevalence of OSAHS, satisfying the industrial deployment. IEEE

16.
Forest Chemicals Review ; 2021(July-August):1365-1384, 2021.
Article in English | Scopus | ID: covidwho-1717199

ABSTRACT

Between COVID-19 and the ongoing trade friction between China and the United States, the domestic and international economic situations have become much more complicated. In this context, what is of vital importance is studying the impact of exchange rate fluctuations on trade balance from two perspectives, namely China's international balance of payments and maintaining the smooth operation of the domestic economy. Economists at home and abroad have done considerable research into the relationship between exchange rate fluctuations and trade balance. However, few studies to date have examined the relationship from the perspective of exchange rate pass-through. This paper reviews relevant theories about exchange rate pass-through (EPT in short) and its impact on trade balance, both at home and abroad. A literature review on empirical studies of the relationship between exchange rate pass-through (EPT) and trade balance is also conducted. After that, a brief conclusion of the literature is made. As a result, the findings of this research can provide a reference platform for future scholars who choose to study the relationship between exchange rate fluctuation and its influence on trade balance, from the exchange rate pass-through (EPT) perspective. © 2021 Kriedt Enterprises Ltd. All right reserved.

17.
IEEE Transactions on Systems, Man, and Cybernetics: Systems ; 2022.
Article in English | Scopus | ID: covidwho-1704312

ABSTRACT

Recently, contactless bimodal palmprint recognition technology has attracted increased attention due to the COVID-19 pandemic. Many dual-camera-based sensors have been proposed to capture palm vein and palmprint images synchronously. However, translations between captured palmprint and palm vein images differ depending on the distance between the hand and the sensors. To address this issue, we designed a low-cost method to align the bimodal palm regions for current dual-camera systems. In this study, we first implemented a contactless palm image acquisition device with a dual-camera module and a single-point time of flight (TOF) ranging sensor. Using this device, we collected a dataset named DCPD under different distances and light source intensities from 271 different palms. Then, a bimodal palm image alignment method is proposed based on the imaging and ranging models. After the system model is calibrated, the translation between the visible light and infrared light palm regions can be estimated quickly based on the palm distance. Finally, we designed a convolutional neural network (CNN) to effectively extract the fine- and coarse-grained palm features. Compared to widely used existing methods, the proposed networks achieved the lowest equal error rate (EER) on the Tongji, IITD, and DCPD datasets, and the average time cost of the system to perform one-time identification is approximately 0.15 s. The experimental results indicate that the proposed methods achieved high efficiency and comparable accuracy. In addition, the system's EER and rank-1 on the DCPD dataset were 0.304%and 98.66%, respectively. IEEE

18.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326858

ABSTRACT

The outbreak of the COVID-19 pandemic has led to intensive studies of both the structure and replication mechanism of SARS-CoV-2. In spite of some secondary structure experiments being carried out, the 3D structure of the key function regions of the viral RNA has not yet been well understood. At the beginning of COVID-19 breakout, RNA-Puzzles community attempted to envisage the three-dimensional structure of 5'- and 3'-Un-Translated Regions (UTRs) of the SARS-CoV-2 genome. Here, we report the results of this prediction challenge, presenting the methodologies developed by six participating groups and discussing 100 RNA 3D models (60 models of 5'-UTR and 40 of 3'-UTR) predicted through applying both human experts and automated server approaches. We describe the original protocol for the reference-free comparative analysis of RNA 3D structures designed especially for this challenge. We elaborate on the deduced consensus structure and the reliability of the predicted structural motifs. All the computationally simulated models, as well as the development and the testing of computational tools dedicated to 3D structure analysis, are available for further study.

19.
Journal of Engineering-Joe ; : 6, 2022.
Article in English | Web of Science | ID: covidwho-1655689

ABSTRACT

During the COVID-19 outbreak, service robots have provided good service for teachers and students in universities. In order to improve the safety and convenience of pharmaceutical undergraduate laboratory, a service robot for pharmaceutical undergraduate teaching laboratory was designed from the aspects of path planning, positioning and navigation, human-computer interaction etc., which can solve practical problems such as epidemic prevention and control, laboratory safety etc.

20.
Qinghua Daxue Xuebao/Journal of Tsinghua University ; 61(12):1438-1451, 2021.
Article in Chinese | Scopus | ID: covidwho-1600027

ABSTRACT

SARS, MERS, SARS-CoV-2 and other pathogens have caused many pandemics in the world. These pathogens are often spread as aerosols in the air. Thus, fast, efficient air disinfection is essential for effectively limiting the spread of the pathogens. A low temperature plasma disinfection method that deactivates many kinds of bacteria, fungi, viruses, spores and other microorganisms has attracted much attention due to its efficiency and environmental friendliness. Disinfection methods can be divided into physical disinfection, chemical disinfection and comprehensive disinfection based on their key factors. This paper reviews the disinfection mechanisms, application scenarios, development progress and other characteristics of various disinfection methods. The review then focuses on the application of these technologies to the disinfection of pathogens such as SARS-CoV-2 with emphasis on plasma disinfection including the key methods and prospects of plasma disinfection in central air conditioning systems. Finally, the Gong Zi Ting performance center of Tsinghua University is used as an example to show the practicality of this surface discharge plasma disinfection method as an example for further applications. This method can significantly improve epidemic prevention and control, as well as the construction of national biosafety systems. © 2021, Tsinghua University Press. All right reserved.

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