ABSTRACT
The mega-scale online education conducted nationwide during the COVID-19 epidemic has enabled online learning to move from individualized participation to full participation, practicing and advancing the development of wisdom education to a large extent. In the post-epidemic era, a new educational order that integrates online and offline learning is gradually taking shape, and online learning has become a new norm from emergency. The popularization and promotion of online education has been the general trend. The "double reduction"policy has led to a trust dilemma, a communication dilemma, a cooperation dilemma and an organizational dilemma in the practice of home-school-society collaborative parenting, and an unprecedented challenge for school education and teachers teaching. This study proposes an intelligent operating system based on big data and adaptive learning traction model, rooted in rich pedagogical theories, to solve the above-mentioned challenges in online education by virtue of "wisdom". © 2023 IEEE.
ABSTRACT
During a public health crisis like the COVID-19 pandemic, a credible and easy-to-access information portal is highly desirable. It helps with disease prevention, public health planning, and misinformation mitigation. However, creating such an information portal is challenging because 1) domain expertise is required to identify and curate credible and intelligible content, 2) the information needs to be updated promptly in response to the fast-changing environment, and 3) the information should be easily accessible by the general public;which is particularly difficult when most people do not have the domain expertise about the crisis. In this paper, we presented an expert-sourcing framework and created Jennifer, an AI chatbot, which serves as a credible and easy-to-access information portal for individuals during the COVID-19 pandemic. Jennifer was created by a team of over 150 scientists and health professionals around the world, deployed in the real world and answered thousands of user questions about COVID-19. We evaluated Jennifer from two key stakeholders' perspectives, expert volunteers and information seekers. We first interviewed experts who contributed to the collaborative creation of Jennifer to learn about the challenges in the process and opportunities for future improvement. We then conducted an online experiment that examined Jennifer's effectiveness in supporting information seekers in locating COVID-19 information and gaining their trust. We share the key lessons learned and discuss design implications for building expert-sourced and AI-powered information portals, along with the risks and opportunities of misinformation mitigation and beyond. © 2023 Owner/Author.
ABSTRACT
Signal detection in a label-based immunoassay is performed normally when the antigen/antibody binding reaction reaches the equilibrium state during the incubation period of an assay process. Shortening the incubation period in an assay helps reduce the turnaround time and is particularly valuable for point-of-care testing, but the cost is the reduction of signal level and, possibly, measurement precision as well. This work demonstrates that the signal loss could be offset by the stronger emission of an electronically neutral ruthenium(II) complex label, Ru(2, 2′-bipyridine) (bathophenanthroline disulfonate)[4-(2, 2′-bipyridin-4-yl)butanoic acid], used in the electrochemiluminescence (ECL) immunoassay. Combined with the uniquely well-established flow-through washing process in the automated ECL analyzers and the precise control over liquid handling, the assays performed with a 5-minute incubation period showed the same signal level and measurement precision as those of conventional ECL assays. Additionally, the absence of biotin and streptavidin components in the reagent formulation avoids the biotin-streptavidin interaction during assay incubation and fundamentally eliminates the interference of biotin, especially when used in some high-dose therapies. The results obtained from the procalcitonin prototype kit and the supporting evidence from other preliminary reagents (for SARS-CoV-2 N protein and troponin T) are general. The nonequilibrium detection, along with the downsized instrument design, makes the enhanced ECL (EECL) technology a fast high-performance POCT platform that provides the same high-quality data as those generated from the widely deployed [Ru(bpy)3]2+ based laboratorial ECL systems. The anticipated regulatory approval and follow-up clinical implementation will be a significant stride in the decade-long pursuit of novel ECL labels. © 2023 The Author(s)
ABSTRACT
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to international public health. The SARS-COV-2 gene continues to mutate in COVID-19 outbreaks. Mutation mainly manifests in 3 forms: point mutation, gene recombination and epigenetic modification. Viral mutations are driven by multiple factors, with mutation rates modulated at 3 levels, the nature of virus, host-virus interactions and natural selection. Therefore, it is particularly important to strengthen the monitoring of the global novel coronavirus genome and the protection of immunosuppressed populations. In the early stage of virus evolution, the mutant strains exhibit greater transmissibility and less virulence than the wild-type strain, although 5 variants of concern (VOCs) showed different stability, transmission capacity, adaptability and pathogenicity. So physical interventions need to be further strengthened. As herd immunity is established, novel mutant strains tend to mutate against vaccines and antibodies. In that case, VOCs, especially the prevailing Omicron variant, bring challenges to the prevention and control of COVID-19 worldwide. The existing and potential prevention, diagnosis and treatment approaches for COVID-19 were summarized. In the vaccination part, the protective efficacy of COVID-19 vaccine against VOCs and the factors influencing the efficacy of COVID-19 vaccine were analyzed. In the detection part, the detection methods based on nucleic acid, antigen and antibody were summarized in order to satisfy the requirements for point-of-care testing and timely recognition of novel variants. And in the treatment part, the potential therapeutic drugs and targets of SARS-CoV-2 were summarized. Drug targets are generally divided into extracellular targets and intracellular targets. In general, this review proposes possible countermeasures by analyzing the impact of mutations on global epidemic prevention and control, hoping to provide theoretical basis for possible large-scale epidemic prevention and control in the future. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.
ABSTRACT
In order to improve risk prevention and control capabilities for international sports events under the background of COVID-19, case data of 23 international sports since the pandemic outbreak were collected, and an evolutionary network model with COVID-19 as risk source was established. Then, risk analysis on the model was carried out based on in-and-out degree, number of sub-net nodes, the shortest path and average path of complex network theory, key risk event nodes were identified, and preventive measures were put forward. Finally, critical chains were obtained by analyzing causal mechanism and types of risk chains, and countermeasures and suggestions for chain disconnection and disaster mitigation were put forward. The results show that severe epidemic situation and rising risk of virus transmission in host cities are the key nodes in evolutionary network, and cycle chain of political relations and public opinion is the most destructive one. Therefore, it is necessary to promote the development of a public opinion monitoring system and strengthen positive publicity of sports events. © 2020 China Safety Science Journal. All rights reserved.
ABSTRACT
The spread of fake news related to COVID-19 is an infodemic that leads to a public health crisis. Therefore, detecting fake news is crucial for an effective management of the COVID-19 pandemic response. Studies have shown that machine learning models can detect COVID-19 fake news based on the content of news articles. However, the use of biomedical information, which is often featured in COVID-19 news, has not been explored in the development of these models. We present a novel approach for predicting COVID-19 fake news by leveraging biomedical information extraction (BioIE) in combination with machine learning models. We analyzed 1164 COVID-19 news articles and used advanced BioIE algorithms to extract 158 novel features. These features were then used to train 15 machine learning classifiers to predict COVID-19 fake news. Among the 15 classifiers, the random forest model achieved the best performance with an area under the ROC curve (AUC) of 0.882, which is 12.36% to 31.05% higher compared to models trained on traditional features. Furthermore, incorporating BioIE-based features improved the performance of a state-of-the-art multi-modality model (AUC 0.914 vs. 0.887). Our study suggests that incorporating biomedical information into fake news detection models improves their performance, and thus could be a valuable tool in the fight against the COVID-19 infodemic. © 2023 by the authors.
ABSTRACT
In order to improve risk prevention and control capabilities for international sports events under the background of COVID-19, case data of 23 international sports since the pandemic outbreak were collected, and an evolutionary network model with COVID-19 as risk source was established. Then, risk analysis on the model was carried out based on in-and-out degree, number of sub-net nodes, the shortest path and average path of complex network theory, key risk event nodes were identified, and preventive measures were put forward. Finally, critical chains were obtained by analyzing causal mechanism and types of risk chains, and countermeasures and suggestions for chain disconnection and disaster mitigation were put forward. The results show that severe epidemic situation and rising risk of virus transmission in host cities are the key nodes in evolutionary network, and cycle chain of political relations and public opinion is the most destructive one. Therefore, it is necessary to promote the development of a public opinion monitoring system and strengthen positive publicity of sports events. © 2020 China Safety Science Journal. All rights reserved.
ABSTRACT
The k-vertex cut (k-VC) problem belongs to the family of the critical node detection problems, which aims to find a minimum subset of vertices whose removal decomposes a graph into at least k connected components. It is an important NP-hard problem with various real-world applications, e.g., vulnerability assessment, carbon emissions tracking, epidemic control, drug design, emergency response, network security, and social network analysis. In this article, we propose a fast local search (FLS) approach to solve it. It integrates a two-stage vertex exchange strategy based on neighborhood decomposition and cut vertex, and iteratively executes operations of addition and removal during the search. Extensive experiments on both intersection graphs of linear systems and coloring/DIMACS graphs are conducted to evaluate its performance. Empirical results show that it significantly outperforms the state-of-the-art (SOTA) algorithms in terms of both solution quality and computation time in most of the instances. To evaluate its generalization ability, we simply extend it to solve the weighted version of the k-VC problem. FLS also demonstrates its excellent performance. IEEE
ABSTRACT
Flows are usually represented as vector lines from origins to destinations and can reflect the movements of individuals or groups in space and time. Revealing and analyzing the spatiotemporal flow patterns are conducive to understanding information underlying movements. This paper proposes a new method called the OD–EOF (Origin–Destination–Empirical Orthogonal Function) to discover important spatiotemporal flow patterns on the premise of maintaining the pairwise connections between origins and destinations. We first construct a spatiotemporal flow matrix that contains connection information between origins and destinations and temporal flow information by adding a temporal dimension to the OD map. Then, we decompose the spatiotemporal flow matrix into spatial modes and corresponding time coefficients by EOF decomposition. The decomposition results depict the prominent spatial distribution of and temporal variation in flows, with most of the spatiotemporal characteristics highly concentrated into the first few spatial modes. The method is evaluated by five synthetic datasets and a user study and subsequently applied to analyze the impact of the COVID-19 pandemic on the spatiotemporal patterns of human mobility in China during the Spring Festival travel rush in 2020 and 2021. The results show the prominent spatiotemporal patterns of human mobility during these periods under the influence of the COVID-19 pandemic outbreak and the normalization of pandemic prevention and control. © 2023 Cartography and Geographic Information Society.
ABSTRACT
Water clarity is a key parameter for assessing changes of aquatic environment. Coastal waters are complex and variable, remote sensing of water clarity for it is often limited by low spatial resolution. The Sentinel-2 Multi-Spectral Instrument (MSI) imagery with a resolution of up to 10 m are employed to solve the problem from 2017 to 2021. Distribution and characteristics of Secchi disk depth (SDD) in Jiaozhou Bay (JZB) are analyzed. Subtle changes in localized small areas are discovered, and main factors affecting the changes are explored. Among natural factors, precipitation and wind play dominant roles in variation in SDD. Human activities have a significant influence on transparency, among which fishery farming has the greatest impact. This is clearly evidenced by the significant improvement of SDD in JZB due to the sharp decrease in human activities caused by coronavirus disease 2019 (COVID-19).Copyright © 2022 The Authors
ABSTRACT
There is a lack of research on the effects of acute exposure to ambient sulfur dioxide (SO2) on mortality caused by asthma, especially nationwide research in China. To explore the acute effect of exposure to ambient SO2 on asthma mortality using nationwide dataset in China from 2015 to 2020 and further evaluate the associations in subgroups with different geographical and demographic characteristics. We used data from China's Disease Surveillance Points system with 29,553 asthma deaths in China during 2015–2020. The exposure variable was the daily mean concentrations of SO2 from the ChinaHighSO2 10 km × 10 km daily grid dataset. Bilinear interpolation was used to estimate each individual's exposure to air pollutants and meteorological variables. We used a time-stratified case crossover design at the individual level to analyze the exposure response relationship between short-term exposure to SO2 and asthma mortality. Stratified analyses were carried out by sex, age group, marital status, warm season and cold season, urbanicity and region. Significant associations between short-term exposure to ambient SO2 and increased asthma mortality were found in this nationwide study. The excess risk (ER) for each 10 μg/m3 increase in SO2 concentrations at lag07 was 7.78 % (95 % CI, 4.16–11.52 %). Season appeared to significantly modify the association. The associations were stronger in cold season (ER 9.78 %, 95 % CI:5.82 −13.89 %). The association remained consistent using different lag periods, adjusting for other pollutants, and in the analysis during pre-Corona Virus Disease 2019 (COVID-19) period. Our study indicates increased risk of asthma mortality with acute exposures to SO2 in Chinese population. The current study lends support for greater awareness of the harmful effect of SO2 in China and other countries with high SO2 pollution. © 2022 The Authors
ABSTRACT
Severe acute respiratory syndrome coronavirus-2 infection is usually self-limited, with a short duration for viral shedding within several weeks. However, prolonged viral shedding has been observed in severe or immune-compromised coronavirus disease 2019 (COVID-19) cases. Here, we reported that three young adult cases of COVID-19 patients, who were either immunosuppressed nor severe, showed prolonged viral RNA shedding from the upper respiratory tract for 58, 81, and 137 days since initial diagnosis. To our knowledge, this is the longest duration of viral shedding reported to date in young adult patients. Further studies on factors relevant to prolonged viral positivity, as well as the correlation between viral positivity and transmission risk are needed for the optimal management of COVID-19 patients with prolonged nucleic acid positive. © Copyright 2022 The Chinese Medical Association, published by Wolters Kluwer Health, Inc.
ABSTRACT
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a serious threat to international public health. The SARS-COV-2 gene continues to mutate in COVID-19 outbreaks. Mutation mainly manifests in 3 forms: point mutation, gene recombination and epigenetic modification. Viral mutations are driven by multiple factors, with mutation rates modulated at 3 levels, the nature of virus, host-virus interactions and natural selection. Therefore, it is particularly important to strengthen the monitoring of the global novel coronavirus genome and the protection of immunosuppressed populations. In the early stage of virus evolution, the mutant strains exhibit greater transmissibility and less virulence than the wild-type strain, although 5 variants of concern (VOCs) showed different stability, transmission capacity, adaptability and pathogenicity. So physical interventions need to be further strengthened. As herd immunity is established, novel mutant strains tend to mutate against vaccines and antibodies. In that case, VOCs, especially the prevailing Omicron variant, bring challenges to the prevention and control of COVID-19 worldwide. The existing and potential prevention, diagnosis and treatment approaches for COVID-19 were summarized. In the vaccination part, the protective efficacy of COVID-19 vaccine against VOCs and the factors influencing the efficacy of COVID-19 vaccine were analyzed. In the detection part, the detection methods based on nucleic acid, antigen and antibody were summarized in order to satisfy the requirements for point-of-care testing and timely recognition of novel variants. And in the treatment part, the potential therapeutic drugs and targets of SARS-CoV-2 were summarized. Drug targets are generally divided into extracellular targets and intracellular targets. In general, this review proposes possible countermeasures by analyzing the impact of mutations on global epidemic prevention and control, hoping to provide theoretical basis for possible large-scale epidemic prevention and control in the future.
ABSTRACT
Background: Telehealth utilization, including the use of telephone appointments (TAV) and video appointment visits (VAV), are a valuable alternative to in-person visits and were a crucial form of health delivery during the COVID-19 national emergency. Among chronic kidney disease (CKD) patients within an integrated healthcare system, we evaluated the rate of successfully completed telehealth visits and assess differences in adoption using an equity lens. Method(s): A retrospective cohort study was conducted among individuals (age>=18yrs) with CKD stage 3 and 4 receiving care at Kaiser Permanente Southern California (KPSC). We limited our sample to patients with at least one in-person visit within 12 months prior to Mar 1, 2020 and followed them for 1 year. A successfully completed telehealth visit was defined as a >=20 min completed appointment via TAV/VAV. Poisson regression with robust variance error was conducted to estimate the rate ratio for a successful telehealth visit. Result(s): Of 161,088 patients, 74% (N=118,456) had >= 1 successfully completed telehealth visit, 34% of which were VAVs. Younger age, female gender, white race, and English as spoken language were associated with the successful completion of a telehealth visit. Senior persons (85+) were less likely to have a successfully TAV/VAV compared to young adults (18-34 yrs) (RR:0.82;95% CI:0.79-0.86) (Figure). Those having a KPSC online account were more likely to have successful TAV/VAV (RR:1.11;95% CI:1.10-1.12). Medicaid patients had more successful telehealth visits while patients living in neighborhoods with less internet access were marginally less likely to have successful TAV/VAV (p=0.05). Conclusion(s): We observed disparities in adoption of telehealth care among CKD patients within an integrated health system. Our findings suggest that further studies and management strategies are needed to facilitate and improve equitable patient-centered care.
ABSTRACT
COVID-19, which has lasted for a year, has caused great damage to the global economy. In order to control COVID-19 effectively, rapid detection of COVID-19 (SARS-CoV-2) is an urgent problem. Spike protein is the detection point of Raman spectroscopy to detect SARS-CoV-2. The construction of spike protein Raman characteristic peaks plays an important role in the rapid detection of SARS-CoV-2 using Raman technology. In this paper, we used Deep Neural Networks to construct the amide I and III characteristic peak model of spike proteins based on simplified exciton model, and combined with the experimental structures of seven coronaviruses (HCoV-229E, HCoV-HKUl, HCoV-NL63, HCoV-OC43, MERS-CoV, SARS-CoV, SARS-CoV-2) spike proteins, analyzed the differences of amide I and III characteristic peaks of seven coronaviruses. The results showed that seven coronaviruses could be divided into four groups according to the amide I and III characteristic peaks of spike proteins: SARS-CoV-2, SARS-CoV, MERS-CoV form a group;HCoV-HKUl, HCoV-NL63 form a group;HCoV-229E and HCoV-OC43 form a group independently. The frequency of amide I and III in the same group is relatively close,and it is difficult to distinguish spike proteins by the frequency of amide I and III ;the characteristic peaks of amide I and III in different groups are quite different, and spike proteins can be distinguished by Raman spectroscopy. The results provide a theoretical basis for the development of Raman spectroscopy for rapid detection of SARS-CoV-2. © 2022 Science Press. All rights reserved.
ABSTRACT
In response to the outbreak of the new coronavirus pneumonia- "COVID-19" in 2019, the health code is widely used in China as an effective means of epidemic prevention and testing. The information security issues among the health code have important research significance. This paper proposes a set of security protocols based on the existing cryptographic theory system, the information security issues of health codes will also be discussed in depth on this basis. In the study, some problems with the use of health code was explained and solutions were proposed. © VDE VERLAG GMBH - Berlin - Offenbach.
ABSTRACT
Since the first report of COVID-19 in Wuhan, China, the disease has rapidly spread to many countries worldwide. The initial reports showed that the incidence rate in adults was higher, while children and adolescents had fewer cases of infection. However, the number of COVID-19 cases has gradually increased in children and adolescents. Therefore, this study aimed to assess the percentage of children and/or adolescents of the total patients diagnosed with COVID-19. PubMed, Embase, Web of Science and the Cochrane Library were searched to find relevant studies. All statistical analyses were conducted using StataMP 14 software. A total of 12 studies met the inclusion criteria. The final results showed that the percentage of children and/or adolescents of all COVID-19 cases was 0.06 [95% confidence interval (CI), 0.04-0.07], which meant an average of 6 cases in children per 10,000 COVID-19 cases. The percentage of children and/or adolescents with COVID-19 was 0.03 (95% CI, 0.01-0.05), 0.09 (95% CI, 0.08-0.09), 0.09 (95% CI, 0.03-0.16) and 0.04 (95% CI, 0.00-0.10) in Asia, South America, North America and Europe, respectively. The present study showed a low percentage of COVID-19 cases of children and/or adolescents, but not without infection risk. Therefore, we should pay attention to the cases of children and/or adolescents during the COVID-19 period and raise our vigilance. © 2022, Medcom Limited. All rights reserved.
ABSTRACT
The outbreak of COVID-19 pandemic in 2020 has caused incalculable losses to all walks of life around the world, which inevitably brought negative effects to the development of TCSL with the halt of export of teachers and the normal teaching of TCSL classes abroad. In this critical period, online teaching mode began to play an essential role and Massive Open Online Course, the product of 'Internet+Education' MOOC has become the very first choice of TCSL online classes. Admitting the dominant position of it, progress still needs to be made in precision of online TCSL classes. In view of the present situation and the condition that SPOC, as a small private online course mode, which has achieved gratifying results in many other subjects while there is still potential for practicing in the field of TCSL, applying the method of data investigation and flow design, combining with the characteristics of Internet Education in Digital Age, feasibility of practicing SPOC teaching mode in HSK online classes under the COVID-19 global pandemic and reflection of putting SPOC into practice will be discussed in this article, which is to provide a reference for the application of SPOC teaching mode in TCSL and provide more feasible examples for the combination of digitization and humanity education. © 2021 IEEE.