Outbreak Of Coronavirus Pneumonia Research Articles

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe acute respiratory syndrome (SARS-Cov) and SARS-COV-2. Many peptides in the host defense system have antiviral activity. How to establish a set of efficient models to identify anti-coronavirus peptides is a meaningful study. Given this, a new prediction model EACVP is proposed. This model uses the evolutionary scale language model (ESM-2 LM) to characterize peptide sequence information. The ESM model is a natural language processing model trained by machine learning technology. It is trained on a highly diverse and dense dataset (UR50/D 2021_04) and uses the pre-trained language model to obtain peptide sequence features with 320 dimensions. Compared with traditional feature extraction methods, the information represented by ESM-2 LM is more comprehensive and stable. Then, the features are input into the convolutional neural network (CNN), and the convolutional block attention module (CBAM) lightweight attention module is used to perform attention operations on CNN in space dimension and channel dimension. To verify the rationality of the model structure, we performed ablation experiments on the benchmark and independent test datasets. We compared the EACVP with existing methods on the independent test dataset. Experimental results show that ACC, F1-score, and MCC are 3.95%, 35.65% and 0.0725 higher than the most advanced methods, respectively. At the same time, we tested EACVP on ENNAVIA-C and ENNAVIA-D data sets, and the results showed that EACVP has good migration and is a powerful tool for predicting anti-coronavirus peptides. The results prove that this model EACVP could fully characterize the peptide information and achieve high prediction accuracy. It can be generalized to different data sets. The data and code of the article have been uploaded to https://github.- com/JYY625/EACVP.git.

Ultrasound COVID-19 Classification Based on the Novel Module-Based Dual-Path Network

With a large-scale novel coronavirus pneumonia (COVID-19) outbreak, more and more researchers have acquired convenient and efficient COVID-19 infection status through medical imaging. Here, due to the excellent features of zero-radiation and rapid clinical examination, ultrasound images have been used to assist doctors in COVID-19 diagnosis. To effectively identify the pathological differences between common pneumonia and novel coronavirus pneumonia, an ultrasound COVID-19 classification based on the novel module-based dual-path network (MD-DPNet) is proposed. Specifically, this paper effectively improves the generalization ability by adding the progressive heatmaps intuitively representing the lesion density with the original ultrasound images. Meanwhile, the proposed algorithm creates regular modular sets to reduce the calculating loads and the coupling between each module, which takes advantage of the fact that most pathological features are concentrated in relatively small regions. Furthermore, the proposed MD-DPNet model divides the complete task into multiple sub-tasks to alleviate interclass disequilibrium and the lesion artifact localization is obtained by an unsupervised method. In this paper, experiments show the effectiveness of the proposed innovation, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Dice reach 0.99, 0.99, 0.99, 0.98, and 0.99, respectively. Experiments on the proposed mixed dataset demonstrate satisfactory results on all the considered tasks, which can provide a new idea for effectively assisting doctors in COVID-19 diagnosis and follow-up treatment.

Analysis of Fiscal Policy and Monetary Policy during Covid-19 Crisis---an Australian perspective

The outbreak of new coronavirus pneumonia in 2020 has emerged as a significant global epidemic, representing a profound disaster. All nations encounter a shift towards crisis management frameworks, exhibiting variable levels of success in limiting the spread of the virus and mitigating economic repercussions. This is by far the most far-reaching public health event of the 21st century on a global scale, with immeasurable research significance from immunological, economic, and sociological perspectives. For the continent of Australia, which is alone in the ocean, the Australian community could not carry the blow once the epidemic exploded across the country. So, as early as the 20th of March, Australia quickly declared a "border closure", banning all non-Australian citizens and non-permanent residents from entering the country. Moreover, with regard to the movement of persons, production activities and control of cases and close contacts in the region, each oblast has adopted restrictive measures of varying degrees, depending on the severity and development of the outbreak. The special geographical conditions and the policy of a completely closed borderline allow us to value the effectiveness of the Australian government's and banks' response to the stimulus provided by the COVID-19 policy directly by removing most of the external conditions from the equation.

Successful Post-Pandemic Cities

The novel coronavirus pneumonia outbreak was a significant test of global urban governance capacity and a major rethink for cities to recognize their developmental deficiencies and plan for the future. After successfully combating the pandemic, cities are entering the post-outbreak era, which is both an opportunity and a challenge for development. In the face of increasing urban population and unpredictable disasters, planning and building resilient cities has become an inevitable choice. Therefore, this paper analyses the impact of the pandemic on the city, focuses on how to build a resilient city, puts forward suggestions from four aspects: land use, community building, environmental design, and transport development, and discusses and analyses other challenges facing the city.

Artificial Intelligence-Based Intelligent Internet Of Things Services

The global Internet market is maturing, with strong potential for growth and vitality, and progressively taking on a larger role in fostering economic problems and development. In the future, with the help of artificial intelligence technology, big data technology, 5G and other new technologies, and with the expansion of Internet usage, the focus of Internet connection will move from people-oriented connection to Internet of things connection. The new coronavirus pneumonia outbreak that began in 2020 has expanded around the world and presented significant challenges to both society and the global economy. The maintenance of social operations, economic recovery, and the restart of employment and industry have all benefited greatly from the Internet. The use of the Internet of things has helped to advance economic development and mitigated some of the epidemic's negative impacts.

Research on the Impact of Live Broadcasting on the Development of Rural Industries

With the innovation of information technology and e-commerce model, live e-commerce meets the diversified needs of consumers and has become a new driving force for the growth of online consumption. In the 2020 novel coronavirus pneumonia outbreak and the decisive struggle against poverty, the direct broadcast of electric business has opened a convenient door for the sale of agricultural products. Direct broadcasting economy has promoted the development of rural economy, but there are also some problems. This paper analyzes the current situation of live broadcast sales of agricultural products and gives countermeasures to the problems. At present, with the continuous development of internet live broadcasting, various industries are trying to use live broadcasting for sales. For example, in the agricultural field, live broadcasting of agricultural products has become the main means of agricultural product marketing. During the live broadcast and delivery period, the diversity of live broadcast types ensures the delivery effect and increases the sales of agricultural products. However, the live broadcast of goods has also brought many problems, such as false publicity, data fraud, hidden gray industrial chain, difficulty in returning and exchanging goods, and other phenomena have also occurred many times, which has attracted the attention of all walks of life. Therefore, it is suggested that in the process of live broadcast sales of agricultural products, the anchor with goods should be encouraged to continuously enhance their live broadcast ability, and try to adopt diversified live broadcast modes for live broadcast with goods. In addition, it is also necessary to do a good job in the supervision and management of webcast. It is suggested that the relevant departments should establish a perfect supervision and management system for live broadcasting of commodities, and investigate and deal with all kinds of bad and illegal behaviors according to the law.

The Legal Dilemma of China's Tax Law Regulatory System in the Context of the Epidemic and Its Resolution

In early 2020, a new outbreak of coronavirus pneumonia broke out and quickly swept the world. In mid-2020, after the epidemic had been brought under control, China tried to gradually resume production to innovate and boost its economy. However, the epidemic soon returned. As it rebounded, China had to resume its embargo policy and its already fragile economy was hit hard again. As the epidemic continues, China is realizing that the epidemic will continue and that the economy will need new policies to support the normalization of the epidemic. New tax policy adjustments will naturally need attention. The Chinese government has already provided tax incentives to taxpayers affected by the epidemic, and these policies have effectively contributed to the socio-economic recovery. It should be noted, however, that China has not made timely adjustments to its tax system in the face of health emergencies and that even the current tax incentives, which have been marginally effective, are temporary rather than permanent measures. This paper sets out to analyze the strengths and weaknesses of China's current taxation system in the face of public emergencies, such as health emergencies. Using a normative analysis, it is concluded that the reason why taxation schemes are difficult to implement in the current legislative context is that the description of taxation in both higher law and local regulations is rarely relevant to public events and needs to be supplemented. At the same time, a study of actual cases suggests that the reasons for the difficulty in implementing tax measures are also related to the legislation. Finally, after taking into account the existing effective measures both at home and abroad, the author believes that the tax law should be improved, starting with the improvement of the relevant constitutional provisions and the establishment of a complete response system for similar public security incidents.

Regional Logistics Demand Prediction: A Long Short-Term Memory Network Method

With the growth of e-commerce and the recurrence of the novel coronavirus pneumonia outbreak, the global logistics industry has been deeply affected. People are forced to shop online, which leads to a surge in logistics needs. Conversely, the novel coronavirus can also be transmitted through goods, so there are some security risks. Thus, in the post-epidemic era, the analysis of regional logistics needs can serve as a foundation for logistics planning and policy formation in the region, and it is critical to find a logistics needs forecasting index system and a effective method to effectively exploit the logistics demand information in recent years. In this paper, we use the freight volume to assess the logistics needs, and the Long short-term memory (LSTM) network to predict the regional logistics needs based on time series and impact factors. For the first time, the Changsha logistics needs prediction index system is built in terms of e-commerce and the post-epidemic era and compared with some well-known methods such as Grey Model (1,1), linear regression model, and Back Propagation neural network. The findings show that the LSTM network has the smallest prediction errors, and the logistics needs are not affected by the epidemic. Therefore, the authors suggest that the government and businesses pay more attention to regional logistics needs forecasting, choosing scientific prediction methods.

Bibliometric analysis of the top-50 cited articles on COVID-19 and physical activity.

BackgroundSince the 2019 novel coronavirus (COVID-19) pneumonia outbreak in late 2019, an endless stream of research has emerged surrounding physical activity. This study analyzes the 50 most influential articles on COVID-19 and physical activity over the past 2 years to describe the research landscape and hotspots from bibliometric citation analysis.MethodsThe top-50 cited articles were extracted from the Web of Science Core Collection database, and bibliometric citation analysis was performed by Excel 2019 and VOSviewer software.ResultsThe top-50 articles were cited 160.48 ± 106.90 (range: 70–587). Most of the articles were from the United States (14), followed by Italy (11) and England (9). The International Journal of Environmental Research and Public Health (n = 10) is the journal with the top-50 cited articles. The collaboration between authors was mainly among three teams, including Smith L, Musumeci G, and Napoli C. The hotspot of research around COVID-19 and physical activity focused on lifestyle change (sedentary behavior, sitting time), mental health (depressive, anxiety, loneliness), the credibility of physical activity assessment tools (reliability, validity), and physical activity of different populations (gender, youth, children).ConclusionsBased on a bibliometric analysis of high-impact articles on COVID-19 and physical activity highlights physical activity as an essential lifestyle change and developments and hotspots in this field. These data will provide insights for future researchers regarding the direction of physical activity research in the COVID-19 pandemic.

Research on the Host Country's Regulatory Power in the Situation of the Novel Coronavirus Pneumonia Outbreak

<p>In the process of combating the Newcastle pneumonia epidemic, shutdown measures taken by countries may harm the legitimate interests of foreign investors, and when foreign investors use the international investment dispute settlement (ISDS) mechanism to arbitrate with the host country, the purpose of international investment agreements (IIAs), which tends to protect the interests of investors, tends to be constantly expanded and used to the neglect of the host country's regulatory power. This is due both to the lack of clarity of certain provisions and to the inherent flaws of the ISDS mechanism. China should actively study the new changes in international investment rules, so that China can more favorably balance the interests of investors and host countries in the process of negotiating international investment agreements, and effectively safeguard the right of national regulation.</p>

A Review of SARS-CoV-2 Disease (COVID-19): Pandemic in Our Time.

Development and deployment of biosensors for the rapid detection of the 2019 novel severe acute respiratory syndrome—coronavirus 2 (SARS-CoV-2) are of utmost importance and urgency during this recent outbreak of coronavirus pneumonia (COVID-19) caused by SARS-CoV-2 infection, which spread rapidly around the world. Cases now confirmed in February 2022 indicate that more than 170 countries worldwide are affected. Recent evidence indicates over 430 million confirmed cases with over 5.92 million deaths scattered across the globe, with the United States having more than 78 million confirmed cases and over 920,000 deaths. The US now has many more cases than in China where coronavirus cases were first reported in late December 2019. During the initial outbreak in China, many leaders did not anticipate it could reach the whole world, spreading to many countries and posing severe threats to global health. The objective of this review is to summarize the origin of COVID-19, its biological nature, comparison with other coronaviruses, symptoms, prevention, treatment, potential, available methods for SARS-CoV-2 detection, and post-COVID-19 symptoms.

Mental stress in health care professionals during COVID-19 outbreak.

BackgroundIn December 2019, an outbreak of novel corona virus pneumonia occurred in Wuhan City, China, and spread throughout the whole of country in a short period. Figures from China’s National Health Commission show that more than 3300 health care workers have been infected as of early March. In Italy, 20% of responding health care professionals was infected, and some have died. Health care professionals are exposed to different types of stress both physical and psychological in response to this serious infectious public health event.Research aimsThe aim of this study is to measure the degree of mental stress among front line health care workers dealing with COVID-19 patients.MethodsWe conducted the study through online survey questionnaire after obtaining the ethics approval from the Research Ethics Committee of Galway University Hospital in Ireland (Ref: C.A. 2355). All personal information of the medical staff involved in the survey has been kept confidential.ResultsThree hundred nine health care members (209 male and 97 female) have agreed to participate in our survey from different hospitals and different specialties all over the world. Overall PSS Score: mean 19.42 (Standard Deviation ± 5.876, range 1–33). Frontline health care workers working in University Hospitals and tertiary referral centres had lower levels of stress compared to those working in peripheral hospitals (P = 0.007, Kruskal Wallis).ConclusionThe COVID-19 pandemic is one of the most stressful events that a health care worker may face during his life time. Most of the participants in the survey developed a moderate degree of stress.

Mental Health and Related Factors of Adolescent Students During Coronavirus Disease 2019 (COVID-19) Pandemic.

Objective Adolescents are at a special stage of physical and mental development, which is a susceptible period for mental disorders. Since the outbreak of coronavirus pneumonia in December 2019, long term stress may have negative effects on the mental health of the adolescents. In the context of the coronavirus disease 2019 (COVID-19), the study was designed to investigate the mental and psychological health of adolescents in China and its possible related factors. Methods A cross-sectional study design was adopted using a structured questionnaire which were distributed through the Internet to measure depression, anxiety, life events and stress related factors. Descriptive statistics and multiple regression analyses were conducted to process the data. Results The final sample comprised 795 adolescents. The total detection rate of depression was 76.48% and the total detection rate of anxiety was 33.08%. ANOVA showed that there were significant differences in depression scores in terms of gender, anxiety scores, history of mental disorders, COVID-19 knowledge reserve, family and social contradictions (p<0.05). And there were significant differences in anxiety scores in terms of gender, depression scores, mental health knowledge reserves, family and social contradictions (p<0.05). Multiple regression analysis showed that anxiety score, health status and COVID-19 knowledge reserve were positively associated with depression score (p<0.01), and history of psychosocial disorders was negatively associated with depression score (p<0.05); depression score, family and social contradictions were significantly positively correlated with anxiety score (p<0.01), and history of mental disorders was significantly negatively correlated with SDS score (p<0.01). Conclusion During the outbreak of COVID-19, adolescent students with better understanding of the pandemic, more complete knowledge of mental health, and better family and social relationship had less impact on their mental health. Therefore, to ensure a sound social support system, elaborate health instruction, and family communication and mutual understanding are conducive to alleviating the psychological stress caused by the epidemic, and it is positive for adolescent students to maintain a good mental health.

Finger Vein Image ROI Extraction Based on Active Contour Method

Under the background of the novel coronavirus pneumonia outbreak in the world, unrestricted and contactless finger vein collection devices have significantly improved public health safety. However, due to the unfixed position of the finger and the open or semi-open characteristics of the acquisition device, it is inevitable to introduce plenty of factors that affect the recognition performance, such as low contrast, uneven illumination and edge disappearance. In view of these practical problems, we propose a method for ROI extraction of finger vein images that combines active contour method and morphological post-processing operations. This method starts from the local segmentation, and finally completes the acquisition of finger masks at the global level, and then combines some morphological operations to achieve precise extraction of finger masks. We designed and conducted plenty of comparison experiments on the proposed algorithm and the current mainstream finger vein image ROI extraction methods on three public available finger vein datasets. Experimental results show that our method accurately extracts the complete finger region mask and achieves the best matching accuracy on all datasets.

Innovative Practice of Key Technologies in Nucleic Acid Detection Laboratory of Gas Membrane Building Structure

The novel corona-virus pneumonia outbreak that broke out at the end of 2019, and it has spread to many countries around the world, so the world's public health security is facing great challenges. As a key medical resource, nucleic acid testing laboratories directly affect the management and control capabilities of countries in response to the epidemic; there are disadvantages in the traditional laboratories for nucleic acid testing, such as high implementation costs, long construction periods, difficult installations, and difficult overall storage and transportation. In view of the rapid spread of the virus, it is particularly important to solve the problems that how to quickly provide laboratories for nucleic acid testing, which must be with fast mass production, low cost, easy installation, and convenient storage and transportation. This article introduces the importance of viral nucleic acid testing laboratories, and discusses the domestic nucleic acid testing capabilities during the epidemic and the innovative solutions of testing laboratories. An innovative design plan was proposed, the air-film structure nucleic acid testing laboratory adopted fresh air systems to achieve positive and negative pressure conversion, it equipped with intelligent technical equipment and combined with air film structure, which is rapid installation and high airtightness. The air-film structure nucleic acid testing laboratories have been successfully used in 9 countries and 26 cities in the world. The local nucleic acid testing capabilities have significantly improved, it was up to 1,000,000 single tubes a day. The newly designed laboratories have contributed to global epidemic prevention and control.

Characteristic of herd immunity among the population of Stavropol region amid the COVID-19 epidemic

Introduction. The first pandemic in the 21st century, caused by the pathogenic representative of the coronavirus SARS-CoV-2, began in the Chinese city of Wuhan, where the first outbreak of coronavirus pneumonia was recorded in December 2019. The disease spread so quickly around the world that already on February 11, 2020, WHO was forced to declare a pandemic of the “coronavirus disease 2019” COVID-19. The first case of COVID-19 in the Stavropol Territory was registered on March 20, 2020, and three weeks later, starting from the 15th week of the year, a steady increase in the incidence began, which lasted until the 52nd week. During the study period, the incidence increased from 21.1 to 28.3 per hundred thousand of the population. Growth 1.3 times.Purpose: to determine the dynamics of population immunity among the population of the Stavropol Territory in 2020-2021. during the period of an epidemic increase in the incidence of COVID-19. Materials and methods. The SARS-CoV-2 study was carried out according to a unified methodology within the framework of the program for assessing the population immunity of the population of the Russian Federation, developed by Rospotrebnadzor with the participation of the St. Pasteur. In total, 2688 people were examined, divided into 7 age groups. In the examined individuals, the level of specific IgG to the SARS-CoV-2 nucleocapsid was determined by the enzyme immunoassay.Results. The level of seroprevalence among residents of the Stavropol Territory was 9.8%. The largest proportion of seropositive individuals was found in the age groups 1-6 and 7-13 years old (19.2% and 19.7%, respectively). Seroprevalence had no gender differences and ranged from 9.3% to 10.8%. When assessing the distribution of the proportion of seropositive persons in different geographic territories of the region, it was found that the maximum proportion was found in the Kochubeevsky district (23.1%), the minimum in Kislovodsk (7.7%). Among convalescents, the content of specific antibodies to SARS-CoV-2 was noted in 73.3%, which is 7.8 times higher than the average population level. When conducting seromonitoring in the 2nd half of 2020, a 10-fold increase in seroprevalence was recorded, accompanied by a decrease in incidence from the 5th week of 2021. Among asymptomatic volunteers in whom SARS-CoV-2 RNA was detected by the polymerase chain reaction, antibody titers to viruses were found in 78.6%, which corresponds to the seroprevalence of convalescents. The proportion of seropositive persons among those who have come into contact with COVID-19 patients was 16.4%, (1.8 times higher than the average for the population). Out of 262 seroprevalent volunteers, the asymptomatic form of SARS-CoV-2 was detected in 92% of the examined, which indicates a significant role of the number of asymptomatic forms of infection in the epidemic process of COVID-19.Conclusion. The results of assessing the population immunity of the population of the Stavropol Territory indicate that it has not yet reached the threshold level at which a decrease in the intensity of the COVID-19 epidemic process can be expected.

Detection of COVID-19 severity using blood gas analysis parameters and Harris hawks optimized extreme learning machine

Coronavirus disease-2019 (COVID-19) has made the world more cautious about widespread viruses, and a tragic pandemic that was caused by a novel coronavirus has harmed human beings in recent years. The new coronavirus pneumonia outbreak is spreading rapidly worldwide. We collect arterial blood samples from 51 patients with a COVID-19 diagnosis. Blood gas analysis is performed using a Siemens RAPID Point 500 blood gas analyzer. To accurately determine the factors that play a decisive role in the early recognition and discrimination of COVID-19 severity, a prediction framework that is based on an improved binary Harris hawk optimization (HHO) algorithm in combination with a kernel extreme learning machine is proposed in this paper. This method uses specular reflection learning to improve the original HHO algorithm and is referred to as HHOSRL. The experimental results show that the selected indicators, such as age, partial pressure of oxygen, oxygen saturation, sodium ion concentration, and lactic acid, are essential for the early accurate assessment of COVID-19 severity by the proposed feature selection method. The simulation results show that the established methodlogy can achieve promising performance. We believe that our proposed model provides an effective strategy for accurate early assessment of COVID-19 and distinguishing disease severity. The codes of HHO will be updated in https://aliasgharheidari.com/HHO.html.

Research on the Application of “Full Online” Model in Chorus Teaching under the Background of Epidemic Situation

After novel coronavirus pneumonia outbreak, online teaching has become a trend. Various educational institutions actively promote online teaching mode and build online teaching courses, which has played an important role in promoting the development of teaching informatization, also solved the teaching problems during the epidemic period, and has kept classes suspended. In terms of chorus teaching, this is a collective performance training activity. Under the background of the epidemic situation, this collective singing training cannot be carried out offline. Therefore, the construction of online chorus teaching mode is one of the important directions of chorus teaching in the new era. This paper analyzes the advantages of the “full online” chorus teaching mode under the background of the epidemic situation, analyzes the difficulties faced in promoting the “full online” chorus teaching mode, and analyzes the development countermeasures of the “full online” chorus teaching mode under the epidemic situation.

Optimization of medical waste recycling network considering disposal capacity bottlenecks under a novel coronavirus pneumonia outbreak.

The sudden outbreak and prolonged impact of the global novel coronavirus disease (COVID-19) epidemic has caused an increase in demand for medical products, such as masks and protective clothing, leading to an exponential increase in the generation of medical waste. As medical waste under the epidemic is highly infectious, it poses a great danger to human health. Therefore, with the proliferation of medical waste, it has become crucial to construct a reverse logistics recycling network that can handle medical waste quickly and efficiently. In this study, we construct a multi-period medical waste emergency reverse logistics network siting model with the objectives of minimum cost, minimum safety risk, and minimum time for the safe and quick disposal of medical waste. The model considers disposal capacity bottlenecks of existing facilities. Based on an empirical analysis using the COVID-19 epidemic in New York City, USA, as a case study, we find that the use of a suitable number of synergistic facilities and the establishment of temporary medical waste disposal centers are viable options for handling the dramatic increase in medical waste during the peak of the COVID-19 epidemic.

Application of Network Imparting Platform in Higher Mathematics Imparting

This year, online imparting has become a popular topic. Due to the novel coronavirus pneumonia outbreak, schools in China have to stop the students’ return to school and the behavior of imparting under the school’s line. It is because of the emergence of network imparting platform jointly produced by many schools that students can hear the imparter’s lecture in their own home as usual. Higher mathematics has always been a science subject for college students [1]. We know that the learning of offline higher mathematics is very difficult. In this paper, based on the application of network imparting platform, the imparting of higher mathematics course is explored, and the conclusion is drawn.