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Large language models have abilities in creating high-volume human-like texts and can be used to generate persuasive misinformation. However, the risks remain under-explored. To address the gap, this work first examined characteristics of AI-generated misinformation (AI-misinfo) compared with human creations, and then evaluated the applicability of existing solutions. We compiled human-created COVID-19 misinformation and ed it into narrative prompts for a language model to output AI-misinfo. We found significant linguistic differences within human-AI pairs, and patterns of AI-misinfo in enhancing details, communicating uncertainties, drawing conclusions, and simulating personal tones. While existing models remained capable of classifying AI-misinfo, a significant performance drop compared to human-misinfo was observed. Results suggested that existing information assessment guidelines had questionable applicability, as AI-misinfo tended to meet criteria in evidence credibility, source transparency, and limitation acknowledgment. We discuss implications for practitioners, researchers, and journalists, as AI can create new challenges to the societal problem of misinformation. © 2023 Owner/Author.
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It is usually hard for unfamiliar partners to rapidly 'break the ice' in the early stage of relationship establishment, which hinders the development of relationship and even affects the team productivity. To solve this problem, we proposed a collaborative serious game for icebreaking by combining immersive virtual reality (VR) with brain-computer interface based on the team flow framework. We designed a multiplayer collaboration task with the theme of fighting COVID-19 and proposed an approach to improve empathy between team members by sharing their real-time mental state in VR;in addition, we propose an EEG-based method for dynamic evaluation and enhancement of group flow experience to achieve better team collaboration. Then, we developed a prototype system and performed a user study. Results show that our method has good ease of use and can significantly reduce the psychological distance among team members. Especially for unfamiliar partners, both functions of mental state sharing and group flow regulation enhancement can significantly reduce the psychological distance. © 2023 IEEE.
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The COVID-19 (corona virus disease 2019) has caused serious impacts worldwide. Many scholars have done a lot of research on the prevention and control of the epidemic. The diagnosis of COVID-19 by cough is non-contact, low-cost, and easy-access, however, such research is still relatively scarce in China. Mel frequency cepstral coefficients (MFCC) feature can only represent the static sound feature, while the first-order differential MFCC feature can also reflect the dynamic feature of sound. In order to better prevent and treat COVID-19, the paper proposes a dynamic-static dual input deep neural network algorithm for diagnosing COVID-19 by cough. Based on Coswara dataset, cough audio is clipped, MFCC and first-order differential MFCC features are extracted, and a dynamic and static feature dual-input neural network model is trained. The model adopts a statistic pooling layer so that different length of MFCC features can be input. The experiment results show the proposed algorithm can significantly improve the recognition accuracy, recall rate, specificity, and F1-score compared with the existing models. © 2023 Chinese Institute of Electronics. All rights reserved.
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Objective: To summarize and compare the main traditional Chinese medicineTCMsyndromes of Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2SARS-CoV-2 carriers to provide references for the syndrome evolution and syndrome differentiation of SARS-CoV-2 infection. Method(s):The TCM medical records of imported and local cases of infection with Delta and Omicron variants of SARS-CoV-2 in Changsha since September 23,2021 to March 27,2022 were collected,including 18 Delta variant cases and 36 Omicron variant cases. Their TCM diagnosis information and TCM pathogenesis were analyzed and compared. Result(s): The common manifestations in Delta variant cases were cough,fever,chest distress/shortness of breath,sore muscles,nausea,dry mouth,dry or sore throat,thick and greasy tongue coating,and rapid and slippery pulse. The predominant pathogenesis was dampness-heat in the upper-energizer and heat stagnation in the lesser Yang combined with dampness. The occurrence of chest distress/shortness of breath,greasy tongue coating,slippery pulse,and the proportion of dampness-heat in the upper-energizer syndrome were higher in Delta variant cases than in Omicron variant cases P<0.05. The common manifestations in Omicron variant cases were itchy and sore throat,nasal congestion,running nose,fever,mild aversion to cold,dry mouth,dizziness,slightly reddish tongue with thin white coating,and rapid or wiry pulse. The predominant pathogenesis was wind-dryness invading defensive exterior,and heat stagnation in the lesser Yang. The occurrence of white-coated tongue and the proportion of wind-dryness invading defensive exterior syndrome were higher in Omicron variant cases than in Delta variant casesP<0.05. Conclusion(s): There are certain differences in TCM syndromes and the corresponding pathogenesis between Delta variant and Omicron variant cases in Changsha,Hunan. The Delta variant of SARS-COV-2 tends to induce dampness-heat syndrome, whereas Omicron variant infection tends to elicit wind-dampness syndrome,which is expected to provide a reference for the pathogenesis evolution of SARS-COV-2 infection.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.
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With the COVID-19 pandemic, people's real-life interactions diminished, and the game-based metaverse platforms such as Minecraft and Roblox are on the rise. The main users of these platforms are teenagers, they generate content in a virtual environment, which can significantly increase the activity of the platform. However, the experience of User-Generated Content in the metaverse is not very good. So what kind of support do users need to improve the efficiency of generating content in the metaverse? To investigate teenage users' preferences and expectations of it, this paper interviewed 72 teenagers aged 12-22 who are familiar with the metaverse game, and distilled 4 suggestions that can help promote metaverse users to generate content. © 2023 IEEE.
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The outbreak of the COVID-19 pandemic forced students to move from face-to-face learning to online learning. Online learning has high demands on students' Self-regulated Learning (SRL) skills. In this study, a questionnaire that used five-point Likert scale was administrated between international African undergraduates and Chinese undergraduate students to investigate their online learning behaviors. The questionnaire was composed of six categories: environment structuring, goal setting, time management, help-seeking, task strategies, and self-evaluation. 441 valid responses were received, 89 from international African students and 352 from Chinese undergraduates. The collected data were analyzed with SPSS Version 24.0. The results showed that there was no significant difference between Chinese student' and international African students' SRL skills in the six sub-scales. This may be due to the small sample size of African students and the similar learning environment. Larger samples are needed in future research to further verify the conclusion. The research results can be used as a reference for the future online learning design to strengthen learners' SRL skills. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The outbreak of the COVID-19 pandemic in early 2020 has brought tremendous challenges to higher education teaching and learning. Much attention has been put on online course construction and delivery to ensure the effectiveness of online learning. However, higher education assessment deserves more attention as it is also significantly impacted by the sudden switch from face-to-face to online. To examine how higher education institutions responded to the challenges in higher education assessment during the pandemic, this chapter conducted a case study of postgraduate programs at Lingnan University (LU) in Hong Kong to explore an appropriate assessment framework for online learning in a liberal arts education context. Through a quantitative approach, this study surveyed taught postgraduate students to explore the effectiveness, efficiency, and fairness of the assessment approaches applied by LU faculty members in the online and hybrid-mode classes. This case study aims to provide insights for improving higher education assessment under the pandemic crisis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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In spite of the sudden onset of the COVID-19 pandemic, many instructors who used team-based pedagogies shifted them online rather than suspending them entirely, but with limited time and resources. To examine the difference in team dynamics and outcomes for courses in Spring 2019 and Spring 2020 of over 1500 first-year engineering students per semester, Wilcoxon signed-rank tests and random forests method were used. Results show that students reported less improvement in team-member effectiveness, lower psychological safety, and less satisfaction in the semester with the emergency transition. However, students also reported lower conflict. The most important factor predicting project grades shifted from 'Interacting with teammates' to 'Having relevant knowledge, skills, and abilities' amid the emergency shift, accompanied by a reduction in team interdependence. In spite of the collection of data during an emergency transition, the foundation of face-to-face interaction before moving to virtual cooperation represents a useful contribution to research that has focused exclusively on virtual learning circumstances.
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Objective To analyze the disinfection quality and influencing factors of nurseries in Nanjing during 2019-2021 so as to provide a scientific basis for optimizing preventive disinfection strategies and measures in nurseries. Methods Environmental samples from 389 nurseries in Nanjing from January 2019 to December 2021 were tested and the change of disinfection quality qualification rate was compared. Results The overall disinfection qualification rate of nurseries of year 2019-2021 were 96.32% 95.85% and 94.60% respectively showing a downward trend χ2trend = 8.67 P<0.05 . Specifically disinfection qualification rate of object surfaces staff hands and tableware showed a downward trend while the disinfection qualification rate of dynamic air showed an upward trend and the differences were statistically significant χ2trend = 23.17 12.32 5.37 21.48 P<0.05 . The total qualification rate of disinfection in Jiangning and Liuhe districts increased during 2019-2021 χ2trend = 21.46 24.05 P<0.05 . Conclusion Disinfection quality of nurseries in Nanjing has declined by year during 2019-2021 especially the object surfaces and staff hands. It is urgent to optimize and refine the strategies and measures for preventive disinfection in nurseries strengthen the training of personnel on disinfection knowledge and ensure the quality of disinfection in nurseries. © 2023 Chinese Journal of General Surgery. All rights reserved.
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Background & Aim: The long-term effects of human mesenchymal stem cell (MSC) treatment on COVID-19 patients have not been fully characterized. The aim of this study was to evaluate the safety and efficacy of a MSC treatment administered to severe COVID-19 patients enrolled in a randomized, double-blind, placebo-controlled clinical trial (NCT 04288102). Methods, Results & Conclusion(s): A total of 100 patients experiencing severe COVID-19 received either MSC treatment (n = 65, 4x107 cells per infusion) or a placebo (n = 35) combined with standard of care on days 0, 3, and 6. Patients were subsequently evaluated 18 and 24 months after treatment to evaluate the long-term safety and efficacy of the MSC treatment. The outcomes measured included: 6-minute walking distance (6-MWD), lung imaging, quality of life according to the Short Form 36 questionnaire, COVID-19-related symptoms, titers of SARS-CoV-2 neutralizing antibodies, MSC-related adverse events (AEs), and tumor markers. Two years after treatment, a marginally smaller proportion of patients had a 6-MWD below the lower limit of the normal range in the MSC group than in the placebo group (OR = 0.19, 95% CI: 0.04-0.80, Fisher's exact test, p = 0.015). On the SF-36 questionnaire, a marginally higher general health score was received by the MSC group at month 18 compared with the placebo group (50.00 vs. 35.00;95% CI: 0.00-20.00, Wilcoxon rank sum test, p = 0.016). In contrast, there were no differences in the total severity score of lung imaging or the titer of neutralizing antibodies between the two groups. Meanwhile, there were no MSC-related AEs reported at the 18- or 24-month follow-ups. The serum levels of most of the tumor markers examined remained within normal ranges and were similar between the MSC and placebo groups. Long-term safety was observed for the COVID-19 patients who received MSC treatment. Yet few sustained efficacy of MSC treatment was observed at the end of the 2-year follow-up period. Funding(s): The National Key Research and Development Program of China (2022YFA1105604, 2020YFC0860900), the specific research fund of The Innovation Platform for Academicians of Hainan Province (YSPTZX202216) and the Fund of National Clinical Center for Infectious Diseases, PLA General Hospital (NCRCID202105,413FZT6). [Figure presented]Copyright © 2023 International Society for Cell & Gene Therapy
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The COVID-19 pandemic has had a significant impact on human behaviors and how it influenced peoples' interests in cultural products is an unsolved problem. While prior studies mostly adopt subjective surveys to find an answer, these methods are always suffering from high cost, limited size, and subjective bias. Inspired by the rich user-oriented data over the Internet, this work explores the possibility to leverage users' search logs to reflect humans' underlying cultural product interests. To further examine how the COVID-19 mobility policy might influence cultural interest changes, we propose a new regression discontinuity design that has the additional potential to predict the recovery phase of peoples' cultural product interests. By analyzing the 1592 search interest time series in 6 countries, we found different patterns of change in interest in movies, music, and art during the COVID-19 pandemic, but a clear overall incremental increase. Across the six countries we studied, we found that changes in interest in cultural products were found to be strongly correlated with mobility and that as mobility declined, interest in movies, music, and art increased by an average of 35, 27 and 20, respectively, with these changes lasting at least eight weeks. © 2023 ACM.
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The rapidly spreading COVID-19 disease had already infected more than 190 countries. As a result of this scenario, nations everywhere monitored confirmed cases of infection, cures, and fatalities and made predictions about what the future would hold. In the event of a pandemic, governments had set limit rules for the spread of the virus and save lives. Multiple computer methods existed for forecasting epidemic time series. Deep learning was one of the most promising methods for time-series prediction. In this research, we propose a model for predicting the spread of COVID-19 in Egypt based on deep learning sequence-to-sequence regression, which makes use of data on the population mobility reports. The presented model utilized a new combined dataset from two different sources. The first source is Google population mobility reports, and the second source is the number of infected cases reported daily "world in data” website. The suggested model could predict new cases of COVID-19 infection within 3–7 days with the least amount of prediction error. The proposed model achieved 96.69% accuracy for 3 days of prediction. This study is noteworthy since it is one of the first trials to estimate the daily influx of new COVID-19 infections using population mobility data instead of daily infection rates. © 2023, The Author(s).
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BackgroundThe risk of incident gout in the United Kingdom (UK) appears to have declined since 2013.[1] However, whether this is temporary or likely to continue is unclear.ObjectivesTo examine the influence of age, calendar year, and year of birth on recent gout incidence in the UK.MethodsUsing data from IQVIA Medical Research Database in the UK, we identified incident gout by READ codes from 1999 to 2019. We grouped age, calendar year, and year of birth into 3-year categories. We assessed the effect of age, calendar year, and birth cohort categories on the incidence rate of gout using the age-period-cohort model among all participants and in men and women separately.ResultsOver the 21 years, there were 164,588 incident gout cases. The incidence rate of gout increased with age until age 80, then leveled off (P for trend <0.001) (Figure 1A). The gout incidence increased from 1999 to 2013, then declined (Figure 1B). The incidence rate of gout was higher in the late birth cohorts than in the early birth cohorts from the Year 1999 to the Year 2013 (Figure 1C);however, such a trend was reversed after the Year 2013, with the incidence rate of gout being higher in the early birth cohorts than that in the late birth cohorts (Figure 1D). Similar patterns were observed in men and women.ConclusionUsing the age-period-cohort model, we found that the risk of gout in the UK increased from 1999 to 2013 and then declined afterward. These findings suggest that some environmental factors occurring after 2013 may play role. Such a downward trend of the risk of gout may continue if these environmental factors are still present.Reference[1]Abhishek A, Tata LJ, Mamas M, et al. Has the gout epidemic peaked in the UK? A nationwide cohort study using data from the Clinical Practice Research Datalink, from 1997 to across the COVID-19 pandemic in 2021. Ann Rheum Dis 2022 Jan 27.Figure 1.(A) Age rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each age category compared with the reference age category (57-59) was adjusted for the calendar year and birth cohort. (B) Calendar year rate ratios and 95% confidence intervals of gout incidence. The relative risk of each calendar year compared with the reference calendar year (2008-2010) was adjusted for age and birth cohort. (C) Cohort rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each birth cohort (1911-1982) compared with the reference birth cohort (1950-1952) was adjusted for age and calendar year. (D) Cohort rate ratios and the corresponding 95% confidence intervals of gout incidence. The relative risk of each birth cohort (1923-1988) compared with the reference birth cohort (1950-1952) was adjusted for age and calendar year.[Figure omitted. See PDF]AcknowledgementsThis work was supported by the National Natural Science Foundation of China (81930071, 82072502, U21A20352), Project Program of National Clinical Research Center for Geriatric Disorders (2021LNJJ06, 2022LNJJ07), the Natural Science Foundation of Hunan Province (2022JJ20100), and the Science and Technology Innovation Program of Hunan Province (2022RC3075, 2022RC1009).Disclosure of InterestsNone Declared.
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Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the "limmar" and "Venn" packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression;And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
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Nucleic acids, as a next generation of biotechnology drugs, not only can fundamentally treat diseases, but also own significant platform characteristics in view of technology and production. Therefore, nucleic acid-based drugs have broad clinical applications in biomedical fields. However, nucleic acids are degradable and unstable, and have very low intracellular delivery efficiency in vitro and in vivo, which greatly limits their applications. In recent years, ionizable lipid-based lipid nanoparticles have shown promising application potentials and have been successfully applied to COVID-19 (Coronavirus Disease 2019) vaccines in clinic. Lipid nanoparticles demonstrate high in vivo delivery efficiency and good safety profile due to their unique structural and physicochemical properties, which provides many possibilities for their clinical applications for nucleic acid delivery in the future. This review focused on the characteristics of nucleic acid drugs and their delivery barriers, and discussed the approved nucleic acid drugs to illustrate the key aspects of the success of their delivery carrier system. In addition, problems to be solved in the field were highlighted.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.