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1.
Zhonghua Er Ke Za Zhi ; 60(11): 1168-1171, 2022 Nov 02.
Article in Chinese | MEDLINE | ID: covidwho-2099942

ABSTRACT

Objective: To summarize the application experience and the therapeutic effect of Nirmatrelvir-Ritonavir (trade name: Paxlovid) for COVID-19 in children. Methods: A retrospective analysis was performed on the clinical data, including collecting the clinical manifestations and clinical outcomes, dynamically monitoring the blood routine, hepatic and renal function and SARS-CoV-2 nucleic acid results, and observing the related side effects during the treatment, etc, of 3 cases with COVID-19 treated with Paxlovid admitted to Shanghai Children's Hospital (designated referral hospital for SARS-CoV-2 infection in Shanghai) from May 1st to June 1st, 2022. Results: The 3 cases were 12, 14, 17 years of age, among which 2 cases were males, 1 case was female. All 3 cases were mild cases with underlying diseases and risk of developing into severe COVID-19, with symptoms of high fever, sore throat and dry cough. The treatment of Paxlovid at 3rd day of symptom onset contributed to the symptom-free after 1-2 days and negative results of SARS-CoV-2 nucleic acid after 2-4 days. All patients had no adverse manifestations of gastrointestinal tract and nervous system but a case had little skin rashes, which recovered after the withdrawal of Paxlovid. Three cases had normal hepatic and renal function during the Paxlovid treatment. At 3 months after discharge, no clinical manifestations of post-COVID syndrome were found in all 3 cases. Conclusion: Paxlovid was effective and relatively safe in the treatment of 3 children with COVID-19.


Subject(s)
COVID-19 , Nucleic Acids , Child , Male , Humans , Female , SARS-CoV-2 , Ritonavir/therapeutic use , Retrospective Studies , China
2.
Chinese Journal of Disease Control and Prevention ; 26(7):803-807, 856, 2022.
Article in Chinese | Scopus | ID: covidwho-2030399

ABSTRACT

Objective To realize the current situation and influencing factors of turnover intention among public health workers fighting against COVID-19 in Guangdong Province, explore the moderating effect of social support, and provide evidence for improving the stability of epidemic prevention team. Methods A self-constructed online questionnaire was used to investigate the personnel of Centres for Disease Control and Prevention and primary health care institutes in Guangdong Province. Hierarchical regression analysis was conducted to examine the associated factors of turnover intention and the moderating role of social support. Results A total of 2 168 participants were collected, of which 632(29.15%) had turnover intention. Anti-epidemic public health workers with senior title, working in CDC, having a fixed establishment, sleeping ≥ 6 h, showing more job satisfaction and reporting higher leadership/colleague/relative support had lower turnover intention, while those working overnight and working overtime on rest days were more likely to report turnover intention. The interaction term "job satisfaction × family support" had a negative moderating effect on the relationship between job satisfaction and turnover intention. Conclusions A relatively high turnover intention is reported among public health workers during the fight against COVID-19 in Guangdong Province. Improving the incentive mechanism, increasing job satisfaction and providing more support to primary health workers may reduce their turnover intention. © 2022, Publication Centre of Anhui Medical University. All rights reserved.

3.
Frontiers in Physics ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2022847

ABSTRACT

At the end of 2019, the outbreak of the Corona Virus Disease 2019 (COVID-19) became a grave global public health emergency. At that time, there was a lack of information about this virus. Nowadays, social media has become the main source for the public to obtain information, especially during the COVID-19 pandemic. Therefore, in order to know about the public of information demand after the outbreak, the research collects the data of hot search on Sina-microblog from 1 January 2020 to 30 December 2020, and then conducts data mining by combining text processing with topic models. Then we show the topics mined in the knowledge map. The results show that with the outbreak of the COVID-19, people's attention to the topics related to the epidemic reaches the maximum in a short time, and then decreases with fluctuation, but does not disappear immediately. Some topics fluctuate violently due to the emergence of special events. The results conformed to the four-stage crisis model in the emergency management. We analyze the role of social media in four stages for this. The findings of this study could help the government and emergency agencies to better understand the main aspects, which the public's concern about COVID-19, and accelerate public opinion guidance and emotional reassurance.

4.
2nd International Conference on Digital Signal and Computer Communications, DSCC 2022 ; 12306, 2022.
Article in English | Scopus | ID: covidwho-2019667

ABSTRACT

Accurate identification of parameters is critical to the epidemiological utility of the results obtained from the COVID-19 transmission model. In order to optimize the model parameters, we propose an adaptive Cauchy quantum particle swarm optimization (QPSO) algorithm. We introduce a piecewise Cauchy mutation operator and the mutation probability is adjusted adaptively according to the fitness to enhance the global search ability of QPSO. The experimental results show that the improved QPSO algorithm has higher accuracy than original QPSO and PSO algorithms. © 2022 SPIE.

5.
2022 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2022 ; : 724-729, 2022.
Article in English | Scopus | ID: covidwho-2018779

ABSTRACT

With the development of modern technology and the rise of artificial intelligence, the application scenarios of identity authentication technology are becoming more and more complex, especially in the current situation of the spread of the new coronavirus, traditional identity authentication technology can no longer meet people's practical needs, and society urgently needs a security and convenient authentication technology. Voiceprint recognition is a kind of biometric technology, and it is one of the products of comprehensive research on computer technology, acoustics and life sciences. This paper introduces a voiceprint recognition check-in system based on deep learning algorithm. In this design, the audio is converted into Mel frequency cepstral coefficients, and then the convolution network is provided to extract features. Finally, the similarity is calculated to obtain the classification result for voiceprint feature extraction, which is compared with the voice database data to realize voiceprint recognition. The voiceprint recognition check-in system introduced in this paper has a check-in system with an interactive interface. The average recognition rate of the system measured by experiments is higher than 93.3%, which can meet the requirements of practical applications. © 2022 IEEE.

6.
Tourism Review ; 2022.
Article in English | Scopus | ID: covidwho-1992565

ABSTRACT

Purpose: The purpose of this study is to examine the mediating and moderating processes that link crisis management to tourist attitude changes and hygiene/safety perceptions through destination image. Design/methodology/approach: Data from 524 tourists and structural equation models were used to examine the tourists’ perceptions of attitudes, safety perceptions and destination images in Taiwan. Findings: The effectiveness of crisis management may positively influence destination image through attitude changes and hygiene/safety perceptions. This study also confirms that information sharing may not only speed up the process of positive destination-image development but also strengthen relationships among the critical attributes of crisis management. Originality/value: As the impact of the COVID-19 crisis continues, it is critical to understand the role of crisis management in destination image and identify how attitudes or behavior intentions can be affected in the fast-spreading network of information sharing in an increasingly competitive tourism and hospitality market. © 2022, Emerald Publishing Limited.

7.
Ieee Transactions on Emerging Topics in Computational Intelligence ; : 10, 2022.
Article in English | Web of Science | ID: covidwho-1978407

ABSTRACT

The upheaval brought by the arrival of the COVID-19 pandemic has continued to bring fresh challenges over the past two years. During this COVID-19 pandemic, there has been a need for rapid identification of infected patients and specific delineation of infection areas in computed tomography (CT) images. Although deep supervised learning methods have been established quickly, the scarcity of both image-level and pixel-level labels as well as the lack of explainable transparency still hinder the applicability of AI. Can we identify infected patients and delineate the infections with extreme minimal supervision? Semi-supervised learning has demonstrated promising performance under limited labelled data and sufficient unlabelled data. Inspired by semi-supervised learning, we propose a model-agnostic calibrated pseudo-labelling strategy and apply it under a consistency regularization framework to generate explainable identification and delineation results. We demonstrate the effectiveness of our model with the combination of limited labelled data and sufficient unlabelled data or weakly-labelled data. Extensive experiments have shown that our model can efficiently utilize limited labelled data and provide explainable classification and segmentation results for decision-making in clinical routine.

8.
2nd International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2021 ; : 373-376, 2021.
Article in English | Scopus | ID: covidwho-1948771

ABSTRACT

Because of COVID-19, wearing a face mask has become the most efficient and convenient way to spread this virus. Face mask detection can fulfill the function of warning those people who do not wear a face mask. Using the Convolutional neural network, the Feedforward Neural Network and the MobileNet V2, a high recognition rate for the face mask detecting system can be achieved. This study compares the accuracy, the loss and the training time for these models and concludes that CNN is the best model based on its high accuracy of 100%. The result that comes out from our study can improve the efficiency of the face mask detecting system. In general, the identification model in our study can be changed easily to apply in other areas, such as medical image classification and geographic image classification. © 2021 IEEE.

9.
Chinese Journal of General Practitioners ; 21(6):567-572, 2022.
Article in Chinese | Scopus | ID: covidwho-1934280

ABSTRACT

Artificial Intelligence (AI) is an interdisciplinary subject developed on the basis of computer technology, cybernetics, mathematics, philosophy and brain science. The purpose of AI is to study new ways to extend the intelligence of human brain in various fields. In recent years, the rapid development of AI technology has brought innovation to medical science and health care. During the pandemic of coronavirus disease 2019 (COVID‑19) AI has been widely used in epidemiological investigation and outbreak prediction, clinical diagnosis and treatment, hospital management, research and development of new drugs and vaccines. The application of AI has reduced the clinical workload and the consumption of medical resources, greatly assisted the battle against COVID‑19. This article introduces the progresses on the applications of AI technology to provide information for its further application in the fighting against COVID‑19. © 2022 Chinese Medical Journals Publishing House Co.Ltd.

10.
2nd International Conference on Internet of Things and Smart City, IoTSC 2022 ; 12249, 2022.
Article in English | Scopus | ID: covidwho-1923087

ABSTRACT

The new corona pneumonia (COVID-19) epidemic is still spreading globally. The critical role of ports in the global economy and logistics system are highlighted. More and more attention is paid to port development trend. Therefore, it is very important to establish a model to forecast the development trend of the port container throughput. This paper quantified the factors affecting container throughput such as economy and foreign trade, and predicted the container throughput of ports in China. In this paper, a multi-factor dynamic model is constructed, which considers macroeconomic growth, foreign trade import and export volume, containerization rate, single container weight, empty and heavy container ratio and other factors. With the data of 2020 as the benchmark, it is comprehensively predicted that by 2025. China's port container throughput will reach 320 million TEU. The container throughput growth will continue to decline. The average annual growth will be 4.0% in the 14th Five-Year Plan period. Further, this model can be used to predict the development trend of port container in 2050. At the same time, the development peak of port container throughput in China can also be analyzed. This conclusion can provide a basis for government departments and enterprises to make decisions. © 2022 SPIE

11.
12.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research ; 25(7):S498-S498, 2022.
Article in English | EuropePMC | ID: covidwho-1904974
13.
Frontiers in Political Science ; 4, 2022.
Article in English | Scopus | ID: covidwho-1875427

ABSTRACT

Open science provides a bright light for global engineering and technology cooperation and promoting global sustainable development. The International Knowledge Centre for Engineering Sciences and Technology (IKCEST), a category II center under the auspices of UNESCO based in Beijing, aims at providing knowledge-based services at a global scale for policy-makers and engineering science and technology professionals in the world, with particular reference to the developing countries. IKCEST has established a platform with data resources and knowledge services at the core, which includes one general platform and several sub-platforms in its prioritized areas such as the disaster risk reduction (DRR), the intelligent city (ICITY), the engineering education (ENGEDU) and the silk road sciences and technology (SRST). Since the platform was put into operation, it has launched 38 knowledge applications (APPs), serving 3.26 million users from 220 countries and regions worldwide, and offered training for more than 18,000 persons from developing countries. In face of the pandemic, IKCEST set up a COVID-19 column which received positive feedback from users across the globe, the introductory video of which was publicized on the UNESCO official website. As a knowledge hub supporting global sustainable development goals (SDGs) and an open platform for global engineering initiatives, IKCEST will spare no efforts to make greater contributions to providing more tailored and valuable knowledge-based services for global users. Copyright © 2022 Chen, Liu, Ma, Zhang and Fang.

14.
Modern Pathology ; 35(SUPPL 2):969-970, 2022.
Article in English | EMBASE | ID: covidwho-1857373

ABSTRACT

Background: Since the first case of COVID19 infection in 2019, this RNA virus has led an unprecedented pandemic that infected more than 232 million people. Although the disease is studied extensively, much remains poorly understood. Here, we performed the first correlation study on the peripheral blood morphology and immunophenotype of the white blood cells (WBCs) from COVID19 patients. Design: A total of 52 samples from COVID19 patients and 15 blood samples as control group were analyzed. COVID19 patients were divided into two groups based on clinical severity, severe (respiratory failure) or non-severe (hospitalized but stable). The controls were the patients with negative COVID19 results by PCR and antibody tests. The WBC morphology was examined either by blood smear review or via CellaVision DM analyzer captured images. Navios flow cytometer and Beckman Kaluza C software were used for immunophenotype analysis. Two-tailed T-test was performed on the COVID19 groups and the control group Results: Almost all COVID19 patients showed marked neutrophilia and lymphopenia on the CBC tests. Morphologically, the neutrophils showed irregularities like hypogranulation, toxic granules and pseudo Pelger-Huet anomaly (Fig 1A). In severe COIVD19 group, there was an increase in neutrophils with immatures phenotypes, showing CD33 positivity while CD10, CD13 and CD16 negative (Fig 1B). Conversely, the CD10(+) mature neutrophils aberrantly expressed CD56 (Fig 1B). The percentage of CD56(+) neutrophils was significantly higher in both COVID19 groups, suggesting a stronger cellular adhesion and interaction. The monocytes from the COVID19 patients had increased cytoplasm with cytoplasmic protrusion and vacuolization (Fig 2A). Phenotypically they were positive for CD13, CD33, CD38 and HLA-DR. The lymphocytes were also atypical, including increased cytoplasm with large granules and vacuoles. Phenotypically, they are activated, expressing CD38, HLA-DR, and mainly α/β subtype. Giant platelets with cytoplasmic vacuoles and projections were easily seen. Platelet aggregations were observed (Fig 2B). These platelets were CD45(-) and expressed CD61 at lower-than-normal intensity, while expressing increased CD42b intensity when compared to the control group on a log scale. Conclusions: Despite being a small study, we were able to correlate the morphologic and phenotypic alterations of the WBCs in COVID19 patients. As such, this helped to explain some of the clinical hematologic manifestation of the disease. (Figure Presented).

15.
Emerging Markets Finance and Trade ; : 12, 2022.
Article in English | Web of Science | ID: covidwho-1852672

ABSTRACT

We employ the state-dependent local projection method to identify the dynamic risk aggravation effects on Treasury market volatilities and risk spillovers under both local and global COVID-19 pandemic shocks. We find that emerging markets suffer more instability as risk receivers during the pandemic. Local pandemic shock sharpens the risk spillover mainly in the short run, especially when global risk is high, while global pandemic shock aggravates spillover in the medium run led by economic depression expectations. The results are not only helpful to encourage governments to deepen cooperation in combating the pandemic but also alert authorities to pay more attention to imported financial risk.

16.
13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022 ; : 605-610, 2022.
Article in English | Scopus | ID: covidwho-1840637

ABSTRACT

Supply management plays an important role in the business. In our research, we make the introduction with research background in COVID-19, in the APPLE Inc. and large amount of data is constructed. Several methods are used during the task, for example, literature review, data analysis, quantitative analysis and comparative analysis. The research shows the current problems faced by electronic technology companies, which are instability of the supply chains, material shortage and regional policies, after which the research reasons for deep causes and provides feasible improvements of the company, which are production concentration, purchase limit strategy, online commodity physical models, price reduction, and comprehensive capital. © 2022 ACM.

17.
IEEE International Conference on Robotics and Automation (ICRA) ; : 14018-14024, 2021.
Article in English | Web of Science | ID: covidwho-1799297

ABSTRACT

Human activities are hugely restricted by COVID-19, recently. Robots that can conduct inter-floor navigation attract much public attention since they can substitute human workers to conduct the service work. However, current robots either depend on human assistance or elevator retrofitting, and fully autonomous inter-floor navigation is still not available. As the very first step of inter-floor navigation, elevator button segmentation and recognition hold an important position. Therefore, we release the first large-scale publicly available elevator panel dataset in this work, containing 3,718 panel images with 35,100 button labels, to facilitate more powerful algorithms on autonomous elevator operation. Together with the dataset, a number of deep learning based implementations for button segmentation and recognition are also released to benchmark future methods in the community. The dataset is available at https://github.com/zhudelong/elevator_button_recognition

18.
Modern Pathology ; 35(SUPPL 2):969-970, 2022.
Article in English | Web of Science | ID: covidwho-1782022
19.
Springer Protocol. Handb. ; : 219-234, 2022.
Article in English | EMBASE | ID: covidwho-1718506

ABSTRACT

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the biggest challenge in public health worldwide. Similarities among viral receptors predict that there are several animal species that could function as reservoirs for the virus. Recent studies have reported that felid animals, including wild and domestic cats, are highly susceptible to SARS-CoV-2 infection. These findings cause great concerns on the potential for human-to-animal and animal-to-human transmission, along with the virus mutations that appear as the virus goes back and forth between species. It is urgently needed to develop novel reagents for control of viral infection and preventing interspecies transmission. In this chapter, we described protocols for generation of a mouse-feline chimeric neutralizing antibody against SARS-CoV-2. This chimeric antibody has potential to be developed as a diagnostic tool and therapeutic agent against SARS-CoV-2 infections in cats.

20.
IEEE/CVF International Conference on Computer Vision (ICCVW) ; : 1708-1717, 2021.
Article in English | Web of Science | ID: covidwho-1704201

ABSTRACT

The Blind or Visually Impaired (BVI) individuals use haptics much more frequently than the healthy-sighted in their everyday lives to locate objects and acquire object details. This consequently puts them at higher risk of contracting the virus through close contact during a pandemic crisis (e.g. COVID-19). Traditional canes only give the BVIs limited perceptive range. Our project develops a wearable solution named Virtual Touch to augment the BVI's perceptive power so they can perceive objects near and far in their surrounding environment in a touch free manner and consequently carry out activities of daily living during pandemics more intuitively, safely, and independently. The Virtual Touch feature contains a camera with a novel point-based neural network TouchNet tailored for real-time blind-centered object detection, and a headphone telling the BVI the semantic labels. Through finger pointing, the BVI end user indicates where he or she is paying attention to relative to their egocentric coordinate system, based on which we build attention-driven spatial intelligence.

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