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This chapter examines how L2 Chinese learners' ecologies of resources were reconfigured at universities in China and the US when face-to-face instruction was abruptly migrated to remote delivery in response to the COVID-19 pandemic. This chapter first conceptualizes four general categories of resources that support the L2 Chinese learners, that is, environment, technological tools, people, and knowledge and skills, then identifies the specific resources available to them during this global crisis and discusses how these resources interacted with the L2 Chinese learners to support their learning. Findings indicate that all four categories of resources were significantly restructured. While similarities can be found in how the ecologies of resources were reconfigured at universities in China and the US, some differences and reasons behind them were highlighted as well. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.
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Messenger RNA (mRNA) therapy is a novel anticancer treatment strategy based on in vitro transcription (IVT) mRNA, with promising potential for the treatment of malignant tumors. The outbreak of the COVID-19 pandemic in the early 21st century has greatly promoted the application of mRNA technologies in SARS-CoV-2 vaccines. Meanwhile, the research and development of the mRNA cancer vaccine has become a priority. A number of key technologies, including mRNA production strategies, delivery systems, anti-tumor immune strategies, etc., have made dramatic improvements and modifications. These technologies accelerated the research progress and clinical applications of mRNA therapy, thereby greatly overcoming the bottleneck problem, such as the instability, inefficient deliveries, and weak immunogenicity of the mRNA vaccines in the past. This review provides a detailed overview of the production, delivery systems, immunological mechanisms, and antitumor immune response strategies for mRNA cancer vaccines. We list some mRNA cancer vaccines that have been used as candidates for cancer treatment and the clinical trials in the field of tumor immunotherapy. In addition, we discuss about the immunological mechanism of the mRNA vaccines to destroy tumors, as well as the challenges and prospects for the future. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.
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By employing two systemic risk methods, the marginal expected shortfall (MES) and the component expected shortfall (CES), this paper measures the systemic risk level of all sectors in China's financial market from 2014 to 2022;thereby, it researches the total effect of sectoral systemic risk using a panel event study model during the three main emergency crisis events. Moreover, two nonparametric methods are utilized, the Wilcoxon signed rank sum test and the bootstrap Kolmogorov–Smirnov test, in order to investigate the changes in individual effects and the dominant ranks of sectoral systemic risk. The empirical results show that (1) the mean values and volatilities of CES and MES of all sectors have a higher level of magnitude in the extreme risk status than those in the normal risk status;(2) by comparing the total effects of three crisis events, we find that different from the continuous shock effect caused by two other events, sectoral systemic risk has a hysteresis effect on the entire market after the outbreak of COVID-19;(3) the long-term and short-term individual effects of sectoral systemic risk in all sectors are different from each other during three events;and (4) the dominance tests of MES are more sensitive and thus better demonstrate the changes in the rankings of sectoral systemic risk than the dominant tests of CES during the emergency crisis events. © 2023 by the authors.
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Writing about international student mobility (ISM) at such a juncture, there is a certain temptation to go with hyperbolic statements about how the ISM landscape has shifted dramatically in a world characterized by deglobalizing momentum (Irwin, 2020) or how the COVID pandemic was a "game-changer” (Yang & Lu, 2022, p. 133). Undoubtedly, the past several years have been volatile for international students and all those involved in various aspects of ISM. The unsynced trajectories of the pandemic in different regions/countries of the world, aggravated by the pandemic's multifarious global repercussions – social, economic, geo-political, etc. – have created a cacophony of experiences for international students, about which scholarship is rapidly emerging, both in this journal (to mention just a few: Sustarsic & Zhang, 2021;Thorson et al., 2021;Zabin, 2022) and elsewhere (e.g., Gomes, 2022;Xu & Tran, 2022;Yang, 2022b). © The Author(s) 2015. All Rights Reserved.
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Objective This article analyzes the epidemic situation and characteristics of Corona virus disease 2019 (COVID-19) in Russian Federation (referred to as Russia), summarizes the effective measures and problems exposed by Russia to deal with COVID-19, so as to provide reference for our country's epidemic prevention and control, and seek the direction of cooperation under the background oi Sino Russia scientific and technological innovation in view of public health emergency. Methods The epidemic characteristics and prevention and control measures were analyzed based on the data released by official authoritative news media such as Sputnik News Agency & Radio and Stopcoronavirus Website. Results Russia's first confirmed case was on January 31, 2020 and its first peak of epidemic outbreak was on May 10, 2020. Thanks to a series of prevention and control measures and isolation and detection systems established by the Russia government according with national conditions, such as establishment of COVID-19 medical treatment centers, restrictions on alcohol sales, and the accelerating development of the vaccine and test kit the epidemic was basically controlled at the end of August in 2020. In September, Russia saw the second peak of the outbreak of COVID-19. Conclusions The fatality rate of COVID-19 in Russia has been at a low level. Therefore, its prevention and control measures, experience and even its deficiencies are worth of learning by China. And we should also strengthen cooperation with Russia in the field of vaccine research and development and its clinical trials.Copyright © 2021 Chinese Medical Association. All rights reserved.
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Objective This article analyzes the epidemic situation and characteristics of Corona virus disease 2019 (COVID-19) in Russian Federation (referred to as Russia), summarizes the effective measures and problems exposed by Russia to deal with COVID-19, so as to provide reference for our country's epidemic prevention and control, and seek the direction of cooperation under the background oi Sino Russia scientific and technological innovation in view of public health emergency. Methods The epidemic characteristics and prevention and control measures were analyzed based on the data released by official authoritative news media such as Sputnik News Agency & Radio and Stopcoronavirus Website. Results Russia's first confirmed case was on January 31, 2020 and its first peak of epidemic outbreak was on May 10, 2020. Thanks to a series of prevention and control measures and isolation and detection systems established by the Russia government according with national conditions, such as establishment of COVID-19 medical treatment centers, restrictions on alcohol sales, and the accelerating development of the vaccine and test kit the epidemic was basically controlled at the end of August in 2020. In September, Russia saw the second peak of the outbreak of COVID-19. Conclusions The fatality rate of COVID-19 in Russia has been at a low level. Therefore, its prevention and control measures, experience and even its deficiencies are worth of learning by China. And we should also strengthen cooperation with Russia in the field of vaccine research and development and its clinical trials.Copyright © 2021 Chinese Medical Association. All rights reserved.
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Background: Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID-19 pandemic. However, online learning has seen students lose interest and become anxious, which affects learning performance and leads to dropout. Thus, measuring students' engagement in online learning has become imperative. It is challenging to recognize online learning engagement due to the lack of effective recognition methods and publicly accessible datasets. Methods: This study gathered a large number of online learning videos of students at a normal university. Engagement cues were used to annotate the dataset, which was constructed with three levels of engagement: low engagement, engagement, and high engagement. Then, we introduced a bi-directional long-term recurrent convolutional network (BiLRCN) for online learning engagement recognition in video. Result: An online learning engagement dataset has been constructed. We evaluated six methods using precision and recall, where BiLRCN obtained the best performance. Conclusions: Both category balance and category similarity of the data affect the performance of the results;it is more appropriate to consider learning engagement as a process-based evaluation;learning engagement can provide intervention strategies for teachers from a variety of perspectives and is associated with learning performance. Dataset construction and deep learning methods need to be improved, and learning data management also deserves attention. © 2022 by the authors.
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Messenger RNA (mRNA) therapy is a novel anticancer treatment strategy based on in vitro transcription (IVT) mRNA, with promising potential for the treatment of malignant tumors. The outbreak of the COVID-19 pandemic in the early 21st century has greatly promoted the application of mRNA technologies in SARS-CoV-2 vaccines. Meanwhile, the research and development of the mRNA cancer vaccine has become a priority. A nwnber of key technologies, including mRNA production strategies, delivery systems, anti-tumor immune strategies, etc., have made dramatic improvements and modifications. These technologies accelerated the research progress and clinical applications of mRNA therapy, thereby greatly overcoming the bottleneck problem, such as the instability, inefficient deliveries, and weak immunogenicity of the mRNA vaccines in the past. This review provides a detailed overview of the production, delivery systems, immunological mechanisms, and antitumor immune response strategies for mRNA cancer vaccines. We list some mRNA cancer vaccines that have been used as candidates for cancer treatment and the clinical trials in the field of tumor immunotherapy. In addition, we discuss about the immunological mechanism of the mRNA vaccines to destroy tumors, as well as the challenges and prospects for the future.
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Nucleic acid vaccine based on messenger RNA (mRNA) is a kind of mRNA technology emerging in recent years. mRNA vaccines have many advantages over traditional vaccines, which can be manufactured in a cell-free manner, enabling rapid, economical and efficient production. In addition, single mRNA vaccines can encode multiple antigens, enhance the immune response against certain pathogens, improve the efficiency of treatment process of diseases, and can target multiple microbial or viral variants in a single formulation. mRNA is seen as a revolutionary vaccine technology in COVID-19 prevention and control, which has been developed and successfully applied in record time. The mRNA vaccine is with poor stability, so the development and applications of novel delivery systems are essential. With the intensive study of pharmacology of mRNA vaccines, the clinical applications of mRNA vaccines enter into a new stage. Recently, mRNA technologies were used in the prevention and therapies of diseases, and some results were published. Here, the output of mRNA vaccines used in prevention and therapies of diseases was summarized, and the development of mRNA vaccines was also discussed. © 2022, China Biotechnology Press. All rights reserved.
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Since the beginning of the Covid-19 Pandemic, Contact Tracing Apps have been implemented in many countries as a way to detect if someone has been in contact with a patient within a minimum amount of time. However, most existing solutions only consider users in pairs. Since many people meet at the same time in real-life scenarios, those applications aren't able to accurately reflect the situation. Moreover, extending current schemes to a multi-party setting could cause scaling problems and place a heavier load on the device. In this paper, we propose a new Contact Tracing protocol that works in a multi-party setting. We evaluate our scheme to show its efficiency. © 2022 Information Processing Society of Japan.
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Objective: To identify the potential biological mechanisms by which Rhodiola crenulata (RC) treats cytokine storm (CS) using network pharmacology, molecular docking, and experimental verification. Method(s): The ingredients and targets of RC were collected from the Organchem database. CS-related genes were collected using the GeneCards and OMIM databases. Cytoscape 3.7.2 software was used to construct the RC-CS network diagram. These data were inputted into the STRING database to construct a protein-protein interaction network. we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis using DAVID and R software. Molecular docking of the active ingredient and pathway-related targets was carried out using AutoDock Vina and PyMOL, and then a CS model was established in rats induced by lipopolysaccharide for in vivo experimental verification. Result(s): The network pharmacology results showed that kaempferol was the most important active component of RC in the treatment of CS, and IL6 and STAT3 were identified as key targets. Molecular docking results showed that RC active components kaempferol had a good binding ability to IL6/STAT3. At the same time, compared with the model group, different doses of kaempferol could down-regulate the expression of inflammatory factors (P <.05), and protect against systemic inflammatory response multiple organ damage. Conclusion(s): This study preliminarily revealed that RC can prevent and treat CS by regulating the expression of inflammatory factors, inhibiting the systemic inflammatory response induced by lipopolysaccharide, and providing a theoretical basis for the study of its pharmacodynamic material basis and mechanism of action. Copyright © The Author(s) 2022.
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Background. Down syndrome (DS) is associated with an increased risk of infections attributed to immune defects. Whether individuals with DS are at an increased risk of severe COVID-19 remains unclear. Methods. In a matched cohort study, we evaluated the risk of COVID-19 infection and severe COVID-19 disease in individuals with DS and their matched counterparts in a pre-COVID-19 vaccination period at Kaiser Permanente Southern California. Multivariable Cox proportion hazard regression was used to investigate associations between DS and risk of COVID-19 infection and severe COVID-19 disease. Results. Our cohort included 2,541 individuals with DS and 10,164 without DS matched on age, sex, and race/ethnicity (51.6% female, 53.3% Hispanic, median age 25 years [interquartile range 14 - 38]), with pulmonary disease as the most common comorbidity (13.1%) followed by diabetes (5.4%). While the rate of COVID-19 infection in individuals with DS was 32% lower than their matched counterparts (adjusted hazard ratio [aHR] 0.68, 95% CI: 0.56-0.83), the rate of severe COVID-19 disease was 6-fold higher (aHR 6.14, 95% CI: 1.87-20.16) (Table 1). The Kaplan-Meier plot demonstrated similar cumulative incidence for those with and without DS at the beginning of the pandemic, followed by a rate increase in July 2020 (at 4 months of follow-up), and in November 2020 (at 8 months of follow-up) (Figure 1), after which the cumulative incidence for those with DS was consistently higher. Figure 2 demonstrated consistently higher cumulative incidence estimates of COVID-19 hospitalization for those with DS than those without. (Table Presented) Conclusion. Although the risk of COVID-19 infection is lower, the risk of severe disease is higher in individuals with DS compared to their matched counterparts. Better infection monitoring, early treatment, and promotion of vaccine for COVID-19 are warranted for DS populations.
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Background. While a 3-dose mRNA-1273 primary series is recommended for moderately or severely immunocompromised (IC) individuals in the U.S., some IC individuals do not complete the 3-dose series. We conducted a matched cohort study to evaluate the relative vaccine effectiveness (rVE) of the 3-dose mRNA-1273 primary series vs. 2 doses of mRNA-1273 in preventing SARS-CoV-2 infection and severe COVID-19 disease in IC individuals. Methods. IC individuals aged >=18 years with >=12 months of Kaiser Permanente Southern California membership who received 3 doses of mRNA-1273 >=24 days apart were 1:1 matched with randomly selected IC 2-dose recipients on age, sex, race/ethnicity, and 2nd dose date. Third doses were accrued from 08/12/2021 to 12/31/2021, with follow-up through 1/31/2022, spanning the delta and omicron periods. Outcomes were SARS-CoV-2 infection (positive molecular test or diagnosis code), COVID-19 hospitalization, and COVID-19 hospital death. Adjusted hazard ratios (aHR) with confidence intervals (CI) were estimated by Cox proportional hazards models. Adjusted rVE (%) was calculated as (1-aHR) x 100. Results. Our study included 21,942 3-dose and 21,942 2-dose mRNA-1273 IC recipients. Adjusted rVE of 3 doses compared to 2 doses of mRNA-1273 against SARS-CoV-2 infection, COVID-19 hospitalization, and COVID-19 hospital death were 55.0% (95% CI: 50.8-58.9%), 83.0% (75.4-88.3%), and 87.1% (30.6-97.6%), respectively (Table 1). Adjusted rVE against SARS-CoV-2 infection ranged from 43.0% to 59.1% across subgroups of age, sex, race/ethnicity, history of SARS-CoV-2 infection, pregnancy, and comorbidities (Table 2). Point estimates of the 3-dose rVE were higher against COVID-19 infection and hospitalization in the first 3 months, compared to 3-6 months after the 3rd dose (Table 3). Conclusion. Three doses of mRNA-1273 provide additional protection against SARS-CoV-2 infection and severe outcomes for IC individuals, compared to 2 doses, highlighting the importance of completing 3-doses for IC populations. However, possible waning of protection against SARS-CoV-2 infection and severe outcomes after 3 months supports the ACIP recommendation of a booster dose at least 3 months after the 3rd primary series dose for adequate protection of IC individuals. (Table Presented).
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We examined the relationship between COVID-19 stressors and individuals' career insecurity and the moderating effect of family support and openness to experience on that relationship. Participants were 207 young Chinese employees (female = 52.2%;mean age = 25.5 years, SD = 4.673 years). They completed the COVID-related stressors, Family Support, Career Insecurity, and Openness Questionnaires. Regression analysis results showed that COVID-related stressors were associated with higher career insecurity. Openness to experience buffered such a link between the COVID-related stressors and career insecurity so that when openness was high, career insecurity from COVID-related stressors was lower. Family support did not moderate the relationship between COVID-related stressors and career insecurity. These findings suggest the importance of personality traits in the relationship between COVID-19 pandemic stressors and work participation for resilient careers.
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COVID-19, the disease caused by SARS-CoV-2, emerged in December 2019 in Wuhan, China, when Chinese authorities confirmed several patients with fever, difficulty breathing, and invasive lesions on the lungs. The virus then spread quickly across the globe, and by May 17, there were a total of 18,151,717 cases worldwide. While some countries still have an exponentially increasing rate of new cases, China has stabilized the spread of the virus. In the review of COVID-19 in this paper, we used sources from Google Scholar, PubMed, Research Gate, etc. In addition, when investigating public policy data and the number of infections, we also used the statements and relevant data from the official websites of the governments of Dalian and Beijing. Our investigation is based on the summary and analysis of the above data to reach our conclusion. We investigated the basic characteristics of COVID-19, the corresponding Sinovac vaccine and mRNA vaccine, the first round of outbreaks in Wuhan, Beijing, and Dalian, and the warning role of COVID-19 in the future. We demonstrated that keeping social distance and isolating infected patients in time can effectively block the transmission of the virus. This paper exposes the necessary public health measures during the pandemic, providing experiences and lessons for a potential future pandemic. © The Authors, published by EDP Sciences.
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State and local transportation agencies have established bicycle and pedestrian traffic monitoring programs to generate traffic data needed to plan, design, construct, and maintain non-motorized infrastructure. These agencies typically have not cited the need to assess changes in traffic associated with a deadly global pandemic as a rationale for monitoring, but data from these monitoring networks can provide insights into trends and changes associated with exogenous shocks to transportation systems such as the COVID-19 pandemic. Researchers have reported surges in bicycling and walking during the pandemic, but few have described these changes in the context of longer-term trends.
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The spread of COVID-19 throughout the world has led to cataclysmic consequences on the global community, which poses an urgent need to accurately understand and predict the trajectories of the pandemic. Existing research has relied on graph-structured human mobility data for the task of pandemic forecasting. To perform pandemic forecasting of COVID-19 in the United States, we curate Large-MG, a large-scale mobility dataset that contains 66 dynamic mobility graphs, with each graph having over 3k nodes and an average of 540k edges. One drawback with existing Graph Neural Networks (GNNs) for pandemic forecasting is that they generally perform information propagation in a flat way and thus ignore the inherent community structure in a mobility graph. To bridge this gap, we propose a Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to perform pandemic forecasting, which learns both spatial and temporal information from a sequence of dynamic mobility graphs. HiSTGNN consists of two network architectures. One is a hierarchical graph neural network (HiGNN) that constructs a two-level neural architecture: county-level and region-level, and performs information propagation in a hierarchical way. The other network architecture is a Transformer-based model that captures the temporal dynamics among the sequence of learned node representations from HiGNN. Additionally, we introduce a joint learning objective to further optimize HiSTGNN. Extensive experiments have demonstrated HiSTGNN's superior predictive power of COVID-19 new case/death counts compared with state-of-the-art baselines. © 2022 Owner/Author.
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High-quality sustainable development is the common goal pursued by all countries in the world. China's high-quality development (HQD) includes five concepts of "innovation, coordination, green, opening-up, and sharing ". In this context, we established an evaluation system that included these five fundamental characteristics, used the comprehensive entropy method and BP neural network to evaluate and predict the high-quality development of Hubei Province in China, and conducted a spatiotemporal deductive analysis. The study found that: 1) Economic growth still has an important impact on HQD, for all the five main indicators, "opening-up " and "innovation " have the highest impact weights, which are 0.379 and 0.278, respectively, while the proportions of coordination and sharing are both less than 0.1. 2) There are huge differences in the level of high-quality development between regions in Hubei Province. From 2010 to 2020, the average comprehensive index of Wuhan City was greater than 0.5, which is 7 times that of the second Xiangyang City, and 46 times that of the last Shennongjia district. 3) In the past few years, the overall high-quality development of Hubei Province has shown a fluctuating upward trend. However, due to the impact of COVID-19, during the following years, its comprehensive development index will decline by an average of 5% annually, but starting from 2022, it will gradually increase. As a result, tailored and coordinated sustainable environmental policies of integrating institutional and open-market measures should be provided.
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During the coronavirus disease 2019 (COVID-19) epidemics, universities take responsibility for the health of their students and epidemic control. Our urgent recommendation focuses on four key questions of emergency management in universities following rigorous evidence-based approaches and provides timely suggestions to university managers, academic faculties and student affairs managers. We recommend universities during the COVID-19 epidemics should: 1) suspend offline lectures;2) provide proper health education on the disease;3) encourage face masks, however oppose using N95 masks on the campus;4) encourage hand hygiene and provide sanitizing products on the campus. Copyright © 2020 West China University of Medical Science. All rights reserved.
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The prediction of pedestrian volume in public area is of great significance to maintain personnel safety and improve the level of public management. Especially under the situation of COVID-19 prevention and control, the prediction of pedestrian volume within closed public spaces has a higher demand. While long short-term memory (LSTM), is often used to establish the prediction model of time series, for this purpose, taking the pedestrian flow prediction as the application background, the influence of the activation function on the time performance of LSTM model is studied, and an optimized scheme of the activation function, which can significantly improve the time performance while ensuring the prediction accuracy is proposed in this paper. The experimental results based on pedestrian flow prediction show that the time performance of the optimized LSTM model is improved by about 12.8% compared with the traditional model, and the prediction accuracy is even slightly increased. © 2022 IEEE.