ABSTRACT
Compound Qinlan Oral Liquid (,CQOL) is derived from Yinqiao San (), which is composed of Jinyinhua (Lonicerae Japonicae Flos), Huangqin (Scutellariae Radix), Lianqiao (Forsythiae Fructus) and Banlangen (Isatidis Radix). It is a common clinical herbal medicine for clearing heat and detoxification, and has antiviral effects. By reviewing the active ingredients of CQOL and the research progress on its anti-influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) efficacy, with view to providing a basis for the clinical use of CQOL in treatment of respiratory diseases caused by SARS-CoV-2.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
ABSTRACT
In December 2019, a virus named SARS-CoV-2 broke out in Wuhan in China. The spread of the virus has brought great challenges to the global medical system. At present, over 6 million people died of the diseases caused by the virus. Under these situations, various corresponding vaccines such as Oxford, Pfizer, and Moderna vaccines have been developed and applied to the population. Nevertheless, due to the development of variants of the virus such as Delta and Omicron, there has been a decline in the effectiveness of current vaccines to some extent. Moreover, the proportion of people who have been inoculated with the COVID-19 vaccine in low-income countries is less than 20%. In this case, we designed a new vaccine to deal with these problems. Specifically, we utilized the antigens (RBD, HR1, and HR2) of the virus to cope with its potential variants of it, increasing the effectiveness of the vaccine. Moreover, we designed a new cell expression system to increase the efficiency of vaccine production by using CHO cells as host cells, Neo gene as a selective marker, CMV as a promoter, MBP as affinity tag, and β-globin as a terminator. Eventually, it was worth stating that our designed vaccine was hypothesized to be practicable and functional, it just started one step on the way to tackling the variants of this virus and increasing the productivity of the vaccine. The detailed experiments still needed to be implemented to verify the feasibility of our design. © 2023 SPIE.
ABSTRACT
Compound Qinlan Oral Liquid (,CQOL) is derived from Yinqiao San (), which is composed of Jinyinhua (Lonicerae Japonicae Flos), Huangqin (Scutellariae Radix), Lianqiao (Forsythiae Fructus) and Banlangen (Isatidis Radix). It is a common clinical herbal medicine for clearing heat and detoxification, and has antiviral effects. By reviewing the active ingredients of CQOL and the research progress on its anti-influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) efficacy, with view to providing a basis for the clinical use of CQOL in treatment of respiratory diseases caused by SARS-CoV-2.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
ABSTRACT
This study investigates how physical and psychological distance from one's surroundings may influence one's perception of connectedness with the servicescape and, ultimately, perception of value. It also examines the effect of consumers' techno-psychological differences and interaction modes on this distance–closeness relationship. The researchers develop and test a conceptual framework of how personal cognitive traits and technological intervention may alter consumers' perceived connectedness to the servicescape and influence their perceived value in different service settings. Via a quasi-experiment design in three service scenarios, this research shows a synthetical effect of contactless technology in the distancing setting that may work more effectively on high self-efficiency customers to change their perceived closeness to the servicescape and further change their evaluation of the service. The findings reveal the practical implications of social distancing for different types of consumers in service encounters during or after the COVID-19 pandemic. © The Author(s) 2023.
ABSTRACT
We analyze crude oil's dependence and the risk spillover effect on the Chinese stock market and the gold market. We compare both static and dynamic copula functions and calculate the average upward and downward spillover effect using the time-varying Copula model and the conditional value-at-risk approach. By utilizing daily data on crude oil prices, China's stock market, and the gold market, we observe an asymmetric spillover effect: the downside spillover effects from crude oil prices on the Chinese stock market and gold market are larger than the upside spillover effect. We then identify changes in the structure of the sample periods and calculate the dynamic conditional correlation between them. In addition, we explore the optimal weight and hedge ratios in diversified portfolios to mitigate potential risks. Our results suggest that investors and portfolio managers should frequently adjust their portfolio strategies, particularly during extreme events like COVID-19, when financial assets become more volatile. Furthermore, crude oil can help reduce the risk in the Chinese stock market and gold market to some extent during different sub-periods. © 2023 by the authors.
ABSTRACT
In recent years, the outbreak of COVID-19 has brought a new round of challenges to global health care, and daily large-scale testing has also increased the consumption of medical resources. However, studies have shown that the cough sounds of patients with COVID-19 are significantly different from other Characteristics of respiratory infectious diseases. Therefore, this paper considers the use of the patient's cough as a detection sample to give the preliminary screening results. The research was conducted on the COUGHVID dataset. The experiment is divided into two stages: (1) Preprocessing stage: use Pitch Shift and Time Stretch to perform data enhancement on audio data, and use spec Augment to perform data enhancement on mel spectrogram. (2) Model construction stage: use two layers of DSC and one layer of BILSTM to splicing to obtain a classification model. Finally, the method is compared with the baseline method using only two layers of LSTM. The results show that accuracy has increased by 1.9%, F1 has increased by 1.9%, and AUC has increased by 1.6%. © 2022 IEEE.
ABSTRACT
In our complex social environments, life situations are ever-changing. When dealing with these changes, there is no one-size-fits-all response or regulatory strategy suitable for all situations. Emotion regulation flexibility (ERF)—a framework for understanding individual differences in adaptive responding to ever-changing life contexts—emphasizes that individuals can flexibly deploy and adjust emotion regulation strategies according to specific characteristics of stressful situations in daily life. To achieve regulatory efficacy, it is important that one can utilize a balanced profile of ER strategies and select strategies that fit well with particular stressful situations. Specifically, using multiple ER strategies in daily life, rather than relying on only single-strategies, would indicate higher ERF. Additionally, based on leading models of strategy-situation fit, certain ER strategies are more appropriate for high versus low intensity stressful events. For instance, distraction involves with shielding oneself from negative stimuli and replacing them with irrelevant things, which may have a greater regulatory effect in high-intensity negative situations. Conversely, strategies such as reappraisal, which involves the processing of negative situations through deep cognitive change, may be more effective in lower-intensity negative situations and as a cornerstone of longer-term ER. We used the experience-sampling method (ESM) to quantify individual's ERF;more specifically we assess participants for 1) having more or less balanced ER strategy profiles and 2) showing greater strategy-situation fit, in regard to the use of distraction versus reappraisal in the regulation of high-intensity versus low-intensity negative life events. To test the adaptive value of ERF on negative emotions and mental health, we investigated the influence of ERF on depressive and anxiety symptoms in two samples. We hypothesized that individuals with a more balanced profile of ER strategy use and a great level of strategy-situation fit would have higher levels of mental health, indicated by low levels of anxiety and depressive feelings. In sample 1, two hundred eight college students finished the ESM procedure (2859 beeps). Intensity of negative situations was measured by self-reported negative feelings for the time points where participants reported an adverse event. Simultaneously, we assessed participants' use of two ER strategies (i.e., distraction and reappraisal). Considering the negative impact of COVID-19 on people's daily life, we collected another sample (sample 2, 3462 beeps) with one hundred people who lived in Hubei Province, where Wuhan was in lockdown during the severe phase of COVID-19 (March 7-13, 2020). We measured intensity of negative situations (by averaging individuals' negative feelings), as well as the use of two ER strategies at corresponding time points. After completing the ESM procedure, the participants were asked to fill out a series of emotional health questionnaires, including Beck Depression Inventory-II, Beck Anxiety Inventory and Spielberger State Anxiety Scale. Multilevel models were used to fit the covariation between the use of distraction versus reappraisal ER strategies and the intensity of negative events. Additionally, we used multiple level regression models to test whether high level of strategy-situation fit would result in lower negative feelings. To test whether a single-strategy preference would lead to higher levels of anxiety and depressive feelings compared to a multiple-strategy preference, latent profile analyses (LPA) was used. Results from the LPA indicated that individuals with preferences for rumination and express suppression reported higher levels depression and anxiety than individuals with a multi-strategy preference. In the multilevel models, results of the two independent samples both suggested individuals who were more inclined to use a higher level of distraction in response to high-intensity negative situations (e.g., adverse events or during COVID-19) and use hi her levels of reappraisal during low-intensity situations (i.e., high level of ERF) reported lower levels of anxiety and depressive feelings. On the converse, individuals who tended to use more distraction in low intensity situations and more reappraisal in high intensity situations, (i.e., those showing lower ERF) reported a higher level of negative feelings. Together, our findings revealed a negative relationship between ERF and mental health problems in two samples, suggesting that having balanced ER profiles and flexibly deploying strategies in specific life contexts may have adaptive value in facilitating positive mental health. This work deepens our understanding of the interaction between ER strategies and situational demands, paving the way for future intervention research to help alleviate negative emotions associated with affective disorders or the experience of major traumatic events (such as epidemics, earthquakes, etc.). © The Authors.
ABSTRACT
To investigate the effect of COVID-19 control measures on aerosol chemistry, the chemical compositions, mixing states, and formation mechanisms of carbonaceous particles in the urban atmosphere of Liaocheng in the North China Plain (NCP) were compared before and during the pandemic using a single particle aerosol mass spectrometry (SPAMS). The results showed that the concentrations of five air pollutants including PM2.5, PM10, SO2, NO2, and CO decreased by 41.2%-71.5% during the pandemic compared to those before the pandemic, whereas O3 increased by 1.3 times during the pandemic because of the depressed titration of O3 and more favorable meteorological conditions. The count and percentage contribution of carbonaceous particles in the total detected particles were lower during the pandemic than those before the pandemic. The carbonaceous particles were dominated by elemental and organic carbon (ECOC, 35.9%), followed by elemental carbon-aged (EC-aged, 19.6%) and organic carbon-fresh (OCfresh, 13.5%) before the pandemic, while EC-aged (25.3%), ECOC (17.9%), and secondary ions-rich (SEC, 17.8%) became the predominant species during the pandemic. The carbonaceous particle sizes during the pandemic showed a broader distribution than that before the pandemic, due to the condensation and coagulation of carbonaceous particles in the aging processes. The relative aerosol acidity (Rra) was smaller before the pandemic than that during the pandemic, indicating the more acidic particle aerosol during the pandemic closely related to the secondary species and relative humidity (RH). More than 95.0% and 86.0% of carbonaceous particles in the whole period were internally mixed with nitrate and sulfate, implying that most of the carbonaceous particles were associated with secondary oxidation during their formation processes. The diurnal variations of oxalate particles and correlation analyses suggested that oxalate particles before the pandemic were derived from aqueous oxidation driven by RH and liquid water content (LWC), while oxalate particles during the pandemic were originated from O3dominated photochemical oxidation.(c) 2022 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
ABSTRACT
There are growing concerns about the role of identity narratives in spreading misinformation on social media, which threatens informed citizenship. Drawing on the social identity model of deindividualization effects (SIDE) and social identity theory, we investigate how the use of national identity language is associated with the diffusion and discourse of COVID-19 conspiracy theories on Weibo, a popular social media platform in China. Our results reveal a pattern of identity communication contagion in public conversations about conspiracies: national identity language usage in original posts is associated with more frequent use of such language in all subsequent conversations. Users who engaged in discussions about COVID-19 conspiracies used more national identity expressions in everyday social media conversations. By extending the SIDE model and social identity theory to misinformation studies, our article offers theoretical and empirical insight into how identity-contagious communication might exacerbate public engagement with misinformation on social media in non-Western contexts. Lay Summary This article examined the use and consequences of national identity language in public discourse related to COVID-19 conspiracy theories on Weibo, one of the largest social media platforms in China. We investigated how social media users discussed conspiracy theories about the origins of COVID-19 to understand how national identity expressions on Weibo affected public engagement with these conspiracy theories. Our findings reveal a contagion of national identity language between the original posts and all subsequent replies. We also discovered that users who employed national identity language during discussions about COVID-19 conspiracy theories subsequently used more of this language, even in everyday posts that were unrelated to COVID-19. Our findings uncover how social media platforms are used as public spheres for identity-contagious communication that challenges misinformation correction and public understanding of other social groups.
ABSTRACT
The unexpected increased cases of COVID-19 pressured the healthcare system to be exposed to unprecedented challenges, where healthcare management is a complex but essential process to manage and coordinate all information and resources. Critical problems are emerging in this new routine and demanding a higher efficiency of medical data sharing. It is becoming necessary to improve the performances of city systems and create an open data city for reliable information and data sharing (e.g., medical and testing) for better public awareness and healthcare services. This research aims to critically review past efforts in open data city for healthcare from the perspective of data management strategy and development. China was selected as a representative due to its fast development in healthcare infrastructure and medical big data, and 79 out of 4,611 articles were selected, reviewed, and analyzed. A mixed-method approach was implemented to review and assess the existing efforts of open data city for healthcare through latitudinal and longitudinal analyses from five aspects based on sociotechnical systems: technology, people, infrastructure, processes, and culture. The gaps, missions, and challenges of developing an open data city for healthcare are also summarized, and an open data city healthcare reinforcement framework is proposed accordingly. This research contributes a new multidimensional way to rethink the development of open data city in healthcare and helps establish the state of the art of open data city. © 2022 American Society of Civil Engineers.
ABSTRACT
In our complex social environments, life situations are ever-changing. When dealing with these changes, there is no one-size-fits-all response or regulatory strategy suitable for all situations. Emotion regulation flexibility (ERF)—a framework for understanding individual differences in adaptive responding to ever-changing life contexts—emphasizes that individuals can flexibly deploy and adjust emotion regulation strategies according to specific characteristics of stressful situations in daily life. To achieve regulatory efficacy, it is important that one can utilize a balanced profile of ER strategies and select strategies that fit well with particular stressful situations. Specifically, using multiple ER strategies in daily life, rather than relying on only single-strategies, would indicate higher ERF. Additionally, based on leading models of strategy-situation fit, certain ER strategies are more appropriate for high versus low intensity stressful events. For instance, distraction involves with shielding oneself from negative stimuli and replacing them with irrelevant things, which may have a greater regulatory effect in high-intensity negative situations. Conversely, strategies such as reappraisal, which involves the processing of negative situations through deep cognitive change, may be more effective in lower-intensity negative situations and as a cornerstone of longer-term ER. We used the experience-sampling method (ESM) to quantify individual’s ERF;more specifically we assess participants for 1) having more or less balanced ER strategy profiles and 2) showing greater strategy-situation fit, in regard to the use of distraction versus reappraisal in the regulation of high-intensity versus low-intensity negative life events. To test the adaptive value of ERF on negative emotions and mental health, we investigated the influence of ERF on depressive and anxiety symptoms in two samples. We hypothesized that individuals with a more balanced profile of ER strategy use and a great level of strategy-situation fit would have higher levels of mental health, indicated by low levels of anxiety and depressive feelings. In sample 1, two hundred eight college students finished the ESM procedure (2859 beeps). Intensity of negative situations was measured by self-reported negative feelings for the time points where participants reported an adverse event. Simultaneously, we assessed participants’ use of two ER strategies (i.e., distraction and reappraisal). Considering the negative impact of COVID-19 on people’s daily life, we collected another sample (sample 2, 3462 beeps) with one hundred people who lived in Hubei Province, where Wuhan was in lockdown during the severe phase of COVID-19 (March 7-13, 2020). We measured intensity of negative situations (by averaging individuals’ negative feelings), as well as the use of two ER strategies at corresponding time points. After completing the ESM procedure, the participants were asked to fill out a series of emotional health questionnaires, including Beck Depression Inventory-II, Beck Anxiety Inventory and Spielberger State Anxiety Scale. Multilevel models were used to fit the covariation between the use of distraction versus reappraisal ER strategies and the intensity of negative events. Additionally, we used multiple level regression models to test whether high level of strategy-situation fit would result in lower negative feelings. To test whether a single-strategy preference would lead to higher levels of anxiety and depressive feelings compared to a multiple-strategy preference, latent profile analyses (LPA) was used. Results from the LPA indicated that individuals with preferences for rumination and express suppression reported higher levels depression and anxiety than individuals with a multi-strategy preference. In the multilevel models, results of the two independent samples both suggested individuals who were more inclined to use a higher level of distraction in response to high-intensity negative situations (e.g., adverse events or during COVID-19) and use hi her levels of reappraisal during low-intensity situations (i.e., high level of ERF) reported lower levels of anxiety and depressive feelings. On the converse, individuals who tended to use more distraction in low intensity situations and more reappraisal in high intensity situations, (i.e., those showing lower ERF) reported a higher level of negative feelings. Together, our findings revealed a negative relationship between ERF and mental health problems in two samples, suggesting that having balanced ER profiles and flexibly deploying strategies in specific life contexts may have adaptive value in facilitating positive mental health. This work deepens our understanding of the interaction between ER strategies and situational demands, paving the way for future intervention research to help alleviate negative emotions associated with affective disorders or the experience of major traumatic events (such as epidemics, earthquakes, etc.). © The Authors.
ABSTRACT
Objectives: Ganoderic acid Me [GA-Me], a major bioactive triterpene extracted from Ganoderma lucidum, is often used to treat immune system diseases caused by viral infections. Although triterpenes have been widely employed in traditional medicine, the comprehensive mechanisms by which GA-Me acts against viral infections have not been reported. Sendai virus [SeV]-infected host cells have been widely employed as an RNA viral model to elucidate the mechanisms of viral infection. Method(s): In this study, SeV-and mock-infected [Control] cells were treated with or without 54.3 muM GA-Me. RNA-Seq was performed to identify differentially expressed mRNAs, followed by qRT-PCR validation for selected genes. GO and KEGG analyses were applied to investigate potential mechanisms and critical pathways associated with these genes. Result(s): GA-Me altered the levels of certain genes' mRNA, these genes revealed are associated pathways related to immune processes, including antigen processing and presentation in SeV-infected cells. Multiple signaling pathways, such as the mTOR pathway, chemokine signaling pathway, and the p53 pathways, significantly correlate with GA-Me activity against the SeV infection process. qRT-PCR results were consistent with the trend of RNA-Seq findings. Moreover, PPI network analysis identified 20 crucial target proteins, including MTOR, CDKN2A, MDM2, RPL4, RPS6, CREBBP, UBC, UBB, and NEDD8. GA-Me significantly changed transcriptome-wide mRNA profiles of RNA polymerase II/III, protein posttranslational and immune signaling pathways. Conclusion(s): These results should be further assessed to determine the innate immune response against SeV infection, which might help in elucidating the functions of these genes affected by GA-Me treatment in virus-infected cells, including cells infected with SARS-CoV-2. Copyright © 2022 Bentham Science Publishers.
ABSTRACT
Background: Novel Coronavirus pneumonia 2019 (COVID-19) is a systemic infectious disease with prominent involvement of the respiratory tract, due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)[1]. Systemic lupus erythematosus is charcterized by an aberrant immune response with the presence of circulating autoantibodies, lymphopenia, and proinfammatory[2]. They are immune-compromised and vulnerable to infections with immune-suppressants treatment. However, data regarding the impact of COVID-19 pandemic in patients with SLE and drug use were relatively scarce. Objectives: The prevalence of COVID-19 in SLE patients was estimated by means of meta-analysis, and the effect of the use of anti-rheumatic drugs on the clinical outcome of SLE patients with COVID-19 was investigated. Methods: Cross-sectional investigations and case series on SLE and COVID-19 published by CBM, CNKI, China Science and Technology Journal Database, Wan Fang Data, PubMed, Embase, Web of Science, Cochrane Library and Medline from its establishment to November 10, 2021 were searched. Random effects model was used to pool data. Heterogeneity and risk of bias was examined with I-squared index (I2) statistic. Inconsistency was evaluated by using the I2. Egger tests were used for the evaluation of potential publication bias (STATA v.12.0). Results: A total of 14 studies comprising 5365 patients were identifed (Table 1). Overall prevalence of COVID-19 in SLE patients was 1.5% (95%CI: 1.2%-1.8%). Eight of the studies included patients who used hydroxychloroquine as part of their treatment regimen, with 29.8% (95%CI: 25.8%-33.8%) hospitalization rates and 14.6% (95%CI: 11.5%-17.8%) adverse outcome rates. Among patients treated with hydroxychloroquine throughout the course of disease, the prevalence was 0.7% (95%CI: 0.4%-1.0%, Figure 1). Conclusion: Patients with SLE had a higher risk of COVID-19. Hydroxychloro-quine might beneft to reduce the overall hospitalization rate and prevalence rate of COVID-19, and alleviate infammatory damage in the chronic stage of viral infection by inhibiting over activation of the immune system.
ABSTRACT
Using AIS data to mine the dynamic characteristics of fishery resource exploitation helps to carry out scientific management of fishery and realize the sustainable development of marine resources. We proposed a framework that integrates multiple AIS data processing and analysis modules, which can efficiently divide fishing voyages, determine the fishing activities and identify fishing types, and provide near real-time analysis results on the number of fishing vessels, fishing duration, voyages and so on. The framework was applied to 1.68 billion AIS trajectory data points of approximately 588,000 fishing vessels. We selected China's sea areas overall and six fishing grounds as the research area, explored the characteristics of fishing vessel activities in winter and spring of 2019, and analyzed the impact of COVID-19 on winter-spring fishing in China in 2020. In 2019, our results showed that the number of fishing vessels in China's sea areas gradually increased over time, with the Chinese New Year holiday affecting fishing activities at the corresponding time but having little impact on the entire month. We found that the changing laws of the fishing duration and voyages in the inshore fishing grounds were similar to those of the number of fishing vessels, which increased to varying degrees over time. Gillnetters were the most numerous fishing vessel type operating in the inshore fishing grounds with increased in spring, while seiners had an absolute advantage in the Xisha-Zhongsha fishing ground. In 2020, during the occurrence period of COVID-19, the fishing activities in China's sea areas was almost unaffected. During the outbreak period, the number, distribution range, activity intensity, and fishing duration of fishing vessels all experienced a relatively large decline. After the epidemic was effectively controlled, they were rapidly increased. In addition, we found that compared with the Government Response Stringency Index, the number of fishing vessels and the number of new confirmed cases showed a more obvious negative correlation. By processing, mining and analyzing AIS data with high spatial-temporal granularity, this study can provide data support for the reasonable development of fishery resources, and help fishery practitioners make wise decisions when responding to unexpected emergencies (e.g. pandemics).
ABSTRACT
Developing and using the rich data implied by dynamic digital twins and blockchain is relevant to manage both patients and medical resources (e.g., doctors/nurses, ventilators etc.) at the COVID-19 and post COVID period. This paper aims at exploring the blockchain solutions for preparing healthcare systems ready for both efficient operation daily and in pandemic through (1) information integration of patient and medical resource flow from healthcare and medical records;(2) optimizing the deployment of such resources based on hospitals, regions and local pandemic levels switching from normal to the outbreak. The main idea is to develop the concepts of the novel framework for creating an inter-hospital resilient network for pandemic response based on blockchain and dynamic digital twin, which will set up innovative ways to best care for patients, protect NHS staff, and support government scientific decisions to beat COVID-19 now and manage the crisis in the future. © 2021 IEEE.
ABSTRACT
This article discussed air quality changes in the Beijing-Tianjin-Tangshan (BTT) region. The air quality index (AQI) values, and the concentrations of PM2.5, PM10, SO2, CO, NO2, and O-3 in the BTT region during the COVID-19 outbreak in 2020 were, respectively, 79.4, 47.2 mu g m(-3), 73.4 mu g m(-3), 10.3 mu g m(-3), 0.87 mg m(-3), 33.6 mu g m(-3), and 90.7 mu g m(-3). However, they were, respectively, 102.7, 61.4 mu g m(-3), 121.0 mu g m(-3), 9.0 mu g m(-3), 0.88 mg m(-3), 40.1 mu g m(-3), and 84.0 mu g m(-3) during the same period in 2021, which is an increase of 29.2%, 30.1%, 64.8%, -12.9%, 1.94 %, 19.5%, and -7.4% compared with the values in 2020. The combined proportions of grade I and grade II during the COVID-19 outbreak in 2020 were 16.7% higher than those in the same period in 2021, so the air quality has deteriorated rapidly from 2020 to the post-COVID era in 2021. The possible reasons for poorer air quality are that the frequency of dusty weather and air pollutant discharge has increased, and meteorological conditions have been relatively unfavorable. The average AQI values, and concentrations of PM2.5, PM10, SO2, CO, NO2, and O-3 during the post-COVID period in 2021 respectively decreased by 14.8%, 29.0%, 14.6%, 22.5%, 37.4%, 14.8%, and 8.7%, compared with those in 2020. It is also worth noting that all the changes in air pollution during the post-COVID era have been consistent. The combined proportions of grade I and grade II during post-COVID period in 2021 were 18.4% higher than those during the same period of 2020, which indicates that the air quality during post-COVID 2021 has obviously improved compared with those in the same period of 2020. The possible reasons are a series of clean air policies and clean air actions, as well as favorable atmospheric diffusion conditions. These results indicate that clean air policies play a very important role in improving air quality.
ABSTRACT
SARS-CoV-2 caused atypical pneumonia (COVID-19) is an ongoing pandemic that seriously threat the global public health. Many people die from this disease with severe symptoms. The most prevalent m6A RNA modification may be involved in by assisting the virus escaping from the host cell immune system attack. We provided here the first computational prediction study of RNA methylation sites in SARS-CoV-2. Based on virus sequence information, we predict the potential virus m6A sites and hope to make anyhow contributions to this unprecedented situation. As a result, we found 27 most frequent m6A sequences (41 bp) in SARS-CoV-2, and two of them are quite near to the spike protein stop codon position. © 2021 ACM.
ABSTRACT
The outbreak of the novel coronavirus and its disease COVID-19 present an unprecedented challenge for humanity. Artificial Intelligence (AI) and robotics may help fighting COVID-19. Potential applications of AI in this accelerating pandemic include, but are not limited to, early detection and diagnosis, massive agent modeling and simulation, data analytics, assistive robots, disinfection robots, public awareness and patrolling, contactless delivery services, virtual healthcare assistants, drug repurposing and vaccination discovery. This chapter sheds light on the roles AI and robotics can play in fighting this disastrous pandemic, and possible future ones, and highlights several potential applications to transform this challenge into opportunities. This chapter also discusses the ethical implications of AI and robotics during the pandemic and in the post-pandemic world. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The coronavirus pandemic is challenging the existing global economic order and the risk of infection is reordering the way people interact. Communication technologies have provided new ways of managing social activities and maintaining social order. The digital health code is a technology developed to digitize health and mobility via mobile devices;its objective is to restore the flow and control of the physical body in a post-pandemic society. This paper examines the digital health code in post-pandemic China. Through analysis of its technical structure, government policies and the use of the digital health code, the paper explores how this social biotechnology reconstructs the notion of health, how it restores mobility and in doing so how it strikes a balance between biosecurity and capital accumulation in post-pandemic societies. © AMIC/WKWSCI-NTU 2021.
ABSTRACT
Liaocheng represents one of the most serious polluted cities in Northern China. To investigate the impact of residential heating activities on atmospheric particles, the chemical composition, size distribution, and evolution process of single particles collected during the wintertime of 2019 were investigated using a single-particle aerosol mass spectrometer (SPAMS). The results showed that the concentrations of four air pollutants including PM2.5, SO2, NO2, and CO during the heating period were 1.1-1.2 times higher than those before the heating period largely due to the increase of pollutant emissions from coal combustion, while O-3 concentration during the heating period decreased by 40.2%. The mass spectra and unscaled size distributions of single particles suggested that the particles had undergone a significant aging process during the whole observation period. The acidity of single particles was calculated by the relative acidity ratio (R-ra), which increased from 36.1 +/- 13.9 before the heating period to 64.8 +/- 43.9 during the heating period, implying that the single particles were more acidic and less aged during the heating period, mainly due to the enhanced formation of sulfate and nitrate and the decreased O-3 concentration during the heating period. Moreover, R-ra decreased from clean days to polluted days before and during the heating period, suggesting that the atmospheric particles in polluted days were less acidic and more aged. The percentage of elemental carbon (EC) particles increased by 13.6% and 11.5% from clean days to polluted days before and during the heating period, respectively, suggesting the significant contribution of EC particles to the polluted days. Source identification results showed that single particles before the heating period were mostly derived from secondary inorganic source (26.5%) and vehicle exhaust (21.4%), whereas those during the heating period were largely from coal combustion (24.0%) and secondary inorganic source (21.4%).