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1.
Electrochimica Acta ; 428, 2022.
Article in English | Scopus | ID: covidwho-1991021

ABSTRACT

Li–air batteries have received significant attention for their ultrahigh theoretical energy density. However, the byproducts induced by attacking air hinder the conversion of Li–O2 batteries to Li–air batteries. Humidity is one of the main obstacles, not only causing side reactions with the discharge products but also leading to rapid corrosion of the lithium anode. Here, we fabricated a novel composite hydrophobic catalyst by loading RuO2 and graphene on N-doped porous carbon. The catalyst was endowed with hydrophobicity and showed superior catalytic performance and low affinity to water in the air. A Li–air battery equipped with this novel composite catalyst exhibited eminent cycling performance in pure oxygen (over 470 h), humid oxygen [∼40% relative humidity (RH), over 310 h], and ambient air (∼42% RH, over 330 h) at a current density of 500 mA g−1, and the discharge specific capacity increased from 13122.1 to 19358.6 mAh g−1. © 2022

2.
2nd International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2021 ; : 600-605, 2021.
Article in English | Scopus | ID: covidwho-1788618

ABSTRACT

Big Traffic data [1] is cross-border multi-source data for multiple industries, but traffic roads have brought significant economic and social benefits, the number of traffic accidents and casualties is on the rise. Among them, traffic accidents are related to many factors, such as weather and population density. The data set used in this article is open source in Barcelona. The Random Forest algorithm is used to screen essential risk factors, establish a traffic risk prediction model, and compare traffic risks before and after COVID-19. It is concluded that the outbreak of the new crown virus -19-19 has a great impact on people's travel and transportation. Finally, the R square of the model established by Random Forest is 0.9. The K-means clustering algorithm is used to determine the location of the accident handling centre. Moreover, the scope of each accident risk management centre can cover more than 85 percent of traffic accident sites from 2016 to 2020. © 2021 IEEE.

3.
Dili Xuebao/Acta Geographica Sinica ; 77(2):426-442, 2022.
Article in Chinese | Scopus | ID: covidwho-1726805

ABSTRACT

The Chinese government has curbed the rapid transmission of COVID-19 through a population flow control rarely seen in history. What is the effect of population flow control on pandemic prevention and control? How does it affect China's population mobility and short-term population distribution? In this paper, an SEIR model of virus transmission dynamics is used to evaluate the effectiveness of the control measures, and mobile location data are employed to track the temporal and spatial changes of population mobility in China, in order to review the positive and negative effects of population flow control during the major outbreaks of COVID-19: (1) Population flow control has significantly stabilized the daily new infection, serving as an essential part of China's non-pharmacological intervention measures in response to major public emergencies of COVID-19. Population flow control postponed the arrival of the peak day of daily new infections in China by 1.9 times, and reduced the number of newly infected people on that day by 63.4%. In the selected 5 provinces, 5 cities in Hubei, and 6 cities outside Hubei, the peak days were postponed by 1.4-8 times, 5.6-16.7 times, and 2.3-7.2 times, respectively, and the number of newly infected people on that day was reduced by 56.9%-85.5%, 62.2%-89.2%, and 67.1%-86.2%, respectively. Therefore, population flow control bought valuable buffer time for the prevention and control of the pandemic, and greatly weakened the impact of concentrated transmissions on medical facilities. (2) Population flow control limited intercity population flow. From January to April 2020, the average daily population flow intensity in China decreased by 40.18% compared with the same period in 2019. In particular, the coming-back-to-work flow after the Spring Festival travel rush in 2020 (from January 25 to February 18) decreased by 66.4% on average. (3) Population flow control and people's fear of the pandemic greatly affected the Spring Festival travel rush in 2020, and the spatial and temporal and distribution of China's population was changed for a short period. This paper helps the understanding of the impact of the population flow control strategy introduced by the government on major public emergencies, as well as the influences of geographical characteristics upon on the population flow and distribution. © 2022, Science Press. All right reserved.

4.
2021 International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2021 ; : 65-71, 2021.
Article in English | Scopus | ID: covidwho-1714061

ABSTRACT

In April 2020, with the development of the nationwide epidemic prevention and control work, the epidemic situation of New Coronavirus has entered a stable stage. However, the resumption of production and recovery is crucial to maintain the stable development of economy and society. Imminent. Therefore, how to co-ordinate the epidemic prevention and control and return to work has become another major challenge for governments at all levels. The joint prevention and control mechanism of the State Council issued a document requiring all localities to 'conduct accurate prevention and control in different regions and levels, and coordinate the prevention and control of epidemic situation and the restoration of economic and social order'. In this context, China Unicom gives full play to the unique advantages of multi-source, massive and integrated big data of operators, and helps enterprises to resume work and production from four aspects: real-time insight of regional return to work rate, grid risk index assessment, risk analysis of regional population inflow, and risk analysis of employees' travel mode, so as to provide support for enterprise decision makers and formulate scientific policies and means, gradually realize the full return to work. © 2021 IEEE.

5.
Frontiers in Optics and Photonics ; : 241-252, 2021.
Article in English | Scopus | ID: covidwho-1674037

ABSTRACT

Dr. Deborah Birx, the White House Coronavirus Task Force coordinator, told NBC News on "Meet the Press" that "[T]he U.S. needs a 'breakthrough' in coronavirus testing to help screen Americans and get a more accurate picture of the virus' spread." We have been involved with biopathogen detection since the 2001 anthrax attacks and were the first to detect anthrax in real-time. A variation on the laser spectroscopic techniques we developed for the rapid detection of anthrax can be applied to detect the Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-CoV-2 virus). In addition to detecting a single virus, this technique allows us to read its surface protein structure. In particular, we have been conducting research based on a variety of quantum optical approaches aimed at improving our ability to detect Corona Virus Disease-2019 (COVID-19) viral infection. Indeed, the detection of a small concentration of antibodies, after an infection has passed, is a challenging problem. Likewise, the early detection of disease, even before a detectible antibody population has been established, is very important. Our team is researching both aspects of this problem. The paper is written to stimulate the interest ofboth physical and biological scientists in this important problem. It is thus written as a combination of tutorial (review) and future work (preview). We join Prof. Federico Capasso and Editor Dennis Couwenberg in expressing our appreciation to all those working so heroically on all aspects of the COVTD-19 problem. And we thank Drs. Capasso and Couwenberg for their invitation to write this paper. © 2021 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.

6.
CHEST ; 161(1):A238-A238, 2022.
Article in English | Academic Search Complete | ID: covidwho-1625226
7.
Progress in Geography ; 40(7):1073-1085, 2021.
Article in Chinese | Scopus | ID: covidwho-1566882

ABSTRACT

The Chinese government has curbed the outbreak of COVID-19 through a population flow control rarely seen in history. The COVID-19 pandemic has greatly impacted the recreation industry. Using mobile location data, this study quantitatively analyzed the impact of the COVID-19 pandemic on population heat map in the leisure areas within the Third Ring Road of Beijing City on the Qingming Festival and Labor Day. The results showed that: 1) The COVID-19 pandemic significantly impacted population heat map in leisure areas in Beijing on holidays, and the population heat map values of the three types of leisure areas investigated in this study declined by 54.2% and 53.0% on the Qingming Festival and Labor Day in 2020 as compared to the 2019 values, respectively. To be specific, the population heat map values of famous scenery, shopping services, and hotel accommodation decreased by 53.6%, 57.5%, and 52.9% on the Qingming Festival, and by 48.5%, 52.0%, and 55.6% on Labor Day, respectively. 2) There were differences in the degree of the impact on population heat map in different types of areas in famous scenery. The impact on the three major segments of famous scenery can be ranked in ascending order as follows: temples and churches (41.7%, 50.3%), parks and squares (53.1%, 47.1%), and scenic spots (61.1%, 51.2%). Wilcoxon rank sum test showed that the hourly variation of population heat map in temples and churches was smaller, and the overall demand can be ranked in ascending order as follows: sightseeing, daily leisure, and religious activities. 3) The 2020 population heat map of the leisure areas within the Third Ring Road of Beijing City was significantly negatively and positively correlated with the population heat map before the pandemic and area of these leisure areas, respectively. This can be attributed to the risk perception of the leisure crowds and the spatial and environmental factors of the disease prevention and control measures. This study provides a scientific basis for assessing the impact of the COVID-19 pandemic on leisure forms in big cities of China. © 2021, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

8.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; : 4240-4244, 2021.
Article in English | Web of Science | ID: covidwho-1532675

ABSTRACT

The existing face recognition datasets usually lack occlusion samples, which hinders the development of face recognition. Especially during the COVID-19 coronavirus epidemic, wearing a mask has become an effective means of preventing the virus spread. Traditional CNN-based face recognition models trained on existing datasets are almost ineffective for heavy occlusion. To this end, we pioneer a simulated occlusion face recognition dataset. In particular, we first collect a variety of glasses and masks as occlusion, and randomly combine the occlusion attributes (occlusion objects, textures,and colors) to achieve a large number of more realistic occlusion types. We then cover them in the proper position of the face image with the normal occlusion habit. Furthermore, we reasonably combine original normal face images and occluded face images to form our final dataset, termed as Webface-OCC. It covers 804,704 face images of 10,575 subjects, with diverse occlusion types to ensure its diversity and stability. Extensive experiments on public datasets show that the ArcFace retrained by our dataset significantly outperforms the state-of-the-arts. Webface-OCC is available at https://github.com/Baojin-Huang/Webface-OCC.

9.
Journal of Communications and Networks ; 23(5):314-325, 2021.
Article in English | Web of Science | ID: covidwho-1524836

ABSTRACT

The coronavirus pandemic has been declared a world health emergency by the World Health Organization, which has raised the importance of an accurate epidemiological model to predict the evolution of COVID-19. In this paper, we propose mean field evolutionary dynamics (MFEDs), inspired by optimal transport theory and mean field games on graphs, to model the evolution of COVID-19. In the MFEDs, we derive the payoff functions for different individual states from the commonly used replicator dynamics (RDs) and employ them to govern the evolution of epidemics. We also compare epidemic modeling based on MFEDs with that based on RDs through numerical experiments. Moreover, we show the efficiency of the proposed MFED-based model by fitting it to the COVID-19 statistics of Wuhan, China. Finally, we analyze the effects of one-time social distancing as well as the seasonality of COVID19 through the post-pandemic period.

10.
IEEE International Symposium on Circuits and Systems (IEEE ISCAS) ; 2021.
Article in English | Web of Science | ID: covidwho-1511237

ABSTRACT

Custom-made, point-of-care PCR platforms are a necessary tool for rapid, point-of-care diagnostics in situations such as the current Covid-19 pandemic. However, a common issue faced by them is noisy fluorescence signals, which consist of a drifting baseline or noisy sigmoidal curve. This makes automated detection difficult and requires human verification. In this paper, we have tried to use nonlinear fitting for automated classification of PCR waveforms to identify whether amplification has taken place or not. We have presented several novel signal reconstruction techniques based on nonlinear fitting which will enable better pre-processing and automated differentiation of a valid or invalid PCR amplification curve. We have also tried to perform this classification at lower PCR cycles to reduce decision times in diagnostic tests.

11.
Journal of Geovisualization and Spatial Analysis ; 5(2):17, 2021.
Article in English | Web of Science | ID: covidwho-1504042

ABSTRACT

Public health emergencies always lead to serious consequences which affect a lot on human health and socioeconomic progress. It is essential that governments and regional health commissions guide the public toward self-protection and better arranged social production during epidemic outbreaks and spreads. According to the need of risk communication and information disclosure, existing studies for COVID-19 maps and visualization applications are conducive to predicting the future trend of the pandemic, mitigating the harmful effect on public wellbeing by leading to effective intervention and policy measures. However, unsettled tasks remain on comprehensive organization of risk information, effective expression of data for public requirement, and systematic theoretical framework as a standard of map design for public health emergencies. To close the research gaps, this paper proposes a conceptual framework with a three-dimensional spatiotemporal-logic structure as a theoretical foundation for map thematic content selection, which is also a good basis for determining the effective visualization approaches of map design. It enhances the validity and legibility of the map expression by leading maps' thematic content couple with features and processes of an epidemic. Then, using the COVID-19 outbreak in Shenzhen, China, as an example, this paper illustrates how to apply the conceptual framework for selecting the thematic content of COVID-19 maps, and explains the specific ways to transform epidemic data into objects for cartographic representation with proper principles and modes. To our knowledge, this paper is the very first study to bring the thematic content of maps for public health emergencies to the fore, and it is thus believed to shed fresh lights into thematic map design.

12.
Molecular and Cellular Biology ; 41(9):16, 2021.
Article in English | Web of Science | ID: covidwho-1501542

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the COVID-19 pandemic, responsible for millions of deaths globally. Even with effective vaccines, SARS-CoV-2 will likely maintain a hold in the human population through gaps in efficacy, percent vaccinated, and arising new strains. Therefore, understanding how SARS-CoV-2 causes widespread tissue damage and the development of targeted pharmacological treatments will be critical in fighting this virus and preparing for future outbreaks. Herein, we summarize the progress made thus far by using in vitro or in vivo models to investigate individual SARS-CoV-2 proteins and their pathogenic mechanisms. We have grouped the SARS-CoV-2 proteins into three categories: host entry, self-acting, and host interacting. This review focuses on the self-acting and host-interacting SARS-CoV-2 proteins and summarizes current knowledge on how these proteins promote virus replication and disrupt host systems, as well as drugs that target the virus and virus interacting host proteins. Encouragingly, many of these drugs are currently in clinical trials for the treatment of COVID-19. Future coronavirus outbreaks will most likely be caused by new virus strains that evade vaccine protection through mutations in entry proteins. Therefore, study of individual self-acting and host-interacting SARS-CoV-2 proteins for targeted therapeutic interventions is not only essential for fighting COVID-19 but also valuable against future coronavirus outbreaks.

13.
IEEE Global Communications Conference (GLOBECOM) on Advanced Technology for 5G Plus ; 2020.
Article in English | Web of Science | ID: covidwho-1476049

ABSTRACT

The coronavirus disease 2019 (COVID-19) has recently attracted extensive attention due to its serious impact on public health worldwide. In this paper, we study and verify that the popularity of virus-related content has a negative correlation with the epidemic spread by means of statistical analysis. Inspired by this result, a practical solution of recommender system is proposed for pushing virus-related content, aiming to gain insight about the newly discovered virus for people and thus reduce the epidemic spread to the utmost extent. First, we formulate the optimization of recommendation policy subject to quality of experience (QoE) loss constraints as a finite-horizon Constrained Markov Decision Problem (CMDP). To solve this problem, then, we present both enumeration and heuristic methods, from perspectives of achieving optimal recommendation policy and reducing computational complexity, respectively. Finally, our simulations validate the benefit of our solution by showing that to recommend virus-related content following our strategy does help slow down the spread of the epidemic.

14.
Canadian Journal of Respiratory, Critical Care, and Sleep Medicine ; 2021.
Article in English | EMBASE | ID: covidwho-1434331

ABSTRACT

Rationale: Severe acute respiratory syndrome caused by coronavirus 2 (SARS-CoV-2) was declared a pandemic on March 11, 2020. Countries entered lockdown, restricting medical activities to essential services. Pulmonary function tests (PFT) are crucial for management of lung diseases. With limited data regarding aerosol generation and the risk of disease transmission during PFTs, many laboratories closed. Our objective is to quantify aerosol generation during different PFT modalities. Methods: We measured aerosol particles in the 0.3-10.0 µm range with an Optical Particle Sizer (Model 3330;TSI Incorporated) and collected bioaerosols to detect respiratory pathogens during clinically indicated PFTs at a hospital-based laboratory during 2 time points in 2020. Results: We monitored 81 and 41 individual multi-modality PFT sessions in June/July and December, respectively. Slow vital capacity, forced vital capacity and diffusion capacity generated higher aerosol counts compared to pre- and post-test room levels although all modalities were lower than during talking or coughing. The aerosol sizes generated were primarily 2.5-10 µm. Oscillometry generated higher overall concentrations than room sampling, also primarily in the 2.5-10 µm aerosols. The bioaerosol filters revealed no respiratory viruses or bacteria. Conclusions: While PFT can generate aerosols, it is less than normal speech with the exception of PFT-induced coughing. Our findings suggest the risk of SARS-CoV-2 transmission is not increased and support the re-opening of PFT laboratories that adhere to universal masking, use of personal protective equipment and stringent infection control protocols. We strongly endorse adherence to public health guidelines in the operation of PFT laboratories.

15.
Frontiers of Philosophy in China ; 15(4):547-566, 2020.
Article in English | Web of Science | ID: covidwho-1372089

ABSTRACT

The COVID-19 pandemic will inevitably change the evolutionary process of human civilization. It not only affects everyone's understanding of globalization, but also makes people reflect on many cultural values and on the institutional arrangements of society. The underlying problems are ultimately men's survival and life's meaning. The outbreak, which was so sudden, has forced people to reconsider the possible forms of a reasonable lifestyle, the relationship between individual and collective rights, the boundaries of men's right to freedom, the relationship between man and nature, the relationship between man and other creatures, and so on.

16.
AHFE Conference on Human Factors in Training, Education, and Learning Sciences, 2021 ; 269:337-342, 2021.
Article in English | Scopus | ID: covidwho-1366312

ABSTRACT

Online education has been promoted and applicated since the covid-19 pandemic spread world widely, meanwhile, big data and the vigorous development of online education brought the explosion of education data, unlike traditional offline education, online education has higher flexibility and universality, but at the same time, the way that teachers and learners how to deal with massive amounts of data of learning and visual interactive display needs to be analyzed and solved in the field of learning problems. Through the investigation and analysis of learners and teachers of the higher education platform, this paper finds out the pain points of the low interaction efficiency and incomplete information understanding of the existing online education APPs and puts forward some optimization strategies for the information visualization of online education APPs. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

17.
27th International Conference on Information Processing in Medical Imaging, IPMI 2021 ; 12729 LNCS:611-623, 2021.
Article in English | Scopus | ID: covidwho-1345080

ABSTRACT

With the COVID-19 pandemic bringing about a severe global crisis, our health systems are under tremendous pressure. Automated screening plays a critical role in the fight against this pandemic, and much of the previous work has been very successful in designing effective screening models. However, they would lose effectiveness under the semi-supervised learning environment with only positive and unlabeled (PU) data, which is easy to collect clinically. In this paper, we report our attempt towards achieving semi-supervised screening of COVID-19 from PU data. We propose a new PU learning method called Constraint Non-Negative Positive Unlabeled Learning (cnPU). It suggests the constraint non-negative risk estimator, which is more robust against overfitting than previous PU learning methods when giving limited positive data. It also embodies a new and efficient optimization algorithm that can make the model learn well on positive data and avoid overfitting on unlabeled data. To the best of our knowledge, this is the first work that realizes PU learning of COVID-19. A series of empirical studies show that our algorithm remarkably outperforms state of the art in real datasets of two medical imaging modalities, including X-ray and computed tomography. These advantages endow our algorithm as a robust and useful computer-assisted tool in the semi-supervised screening of COVID-19. © 2021, Springer Nature Switzerland AG.

18.
Proceedings of 2020 Ieee International Conference on Teaching, Assessment, and Learning for Engineering ; : 742-747, 2020.
Article in English | Web of Science | ID: covidwho-1313971

ABSTRACT

Affected by the epidemic, the utilization rate of online education platforms has risen sharply. The change of teaching mode not only provides more opportunities for online education, but also brings more challenges to users of the platforms. The method to solve the difference in experience brought by the transition from offline education to online education, to help students improve their sense of learning, and to reduce the confusion and discomfort caused by online learning are the problems facing online education platforms at this moment. Hence, this study aims to explore the potential user requirements of online scene experience by the use of a questionnaire survey associated with text and images. Taking a class of industrial design students as the sample for investigation on four scenes, such as a scene of offline social communication environment, a scene of effective interaction, a scene of learning environment, and a scene of supporting physical movement, which the online platform can bring users with pleasure and comfort as offline.

19.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies ; 5(2), 2021.
Article in English | Scopus | ID: covidwho-1295246

ABSTRACT

A rapid-spreading epidemic of COVID-19 hit China at the end of 2019, resulting in unignorable social and economic damage in the epicenter, Wuhan. POIs capture the microscopic behavior of citizens, providing valuable information to understand city reactions toward the epidemic. Leveraging large-scale check-in records, we analyze the POI visit trends over the epidemic period and normal times. We demonstrate that COVID-19 greatly influences the society, where most POIs demonstrate more than 60% of visit drops during the city lockdown period. Among them, Tourist Attractions received greatest impact with a 78.8% drop. Entertainment, Food, Medical and Shopping are sensible to the disease before lockdown, and we identify these "early birds"to investigate the public reaction in the early stage of the epidemic. We further analyze the revival trends, generating four different revival patterns that correlated with the necessity of POI functions. Finally, we analyze the perseverance during the COVID-19, finding no large-scale closures compared with the tremendous visit drop. The strong resilience in Wuhan supports the rapid recovery of society. These findings are important for researchers, industries, and governments to understand the city respondence under severe epidemic, proposing better regulations to respond, control, and prevent public emergencies. © 2021 ACM.

20.
Proc. IEEE Int. Conf. Teach., Assess., Learn. Eng., TALE ; : 742-747, 2020.
Article in English | Scopus | ID: covidwho-1155849
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