A Hybrid Model of Deep Learning Features and Clinical Features for Severe Cases Predication of COVID-19

COVID-19 has spread around the world since 2019. Approximately 6.5% of COVID-19 a risk of developing severe disease with high mortality rate. To reduce the mortality rate and provide appropriate treatment, this research established an integrated models with to predict the clinical outcome of COVID-19 patients with clinical, deep learning and radiomics features. To obtain the optimal feature combination for prediction, 9 clinical features combination was selected from all available clinical factors after using LASSO, 18 deep learning features from U-Net architecture, and 9 radiomics features from segmentation result. A total of 213 COVID-19 patients and 335 non-COVID-19 patients from 5 hospitals were enrolled and used as training and test sample in this research. The proposed model obtained an accuracy, precision, recall, specificity, F1-score and ROC curve of 0.971, 0.943, 0.937, 0.974, 0.941 and 0.979, respectively, which exceeds the related work using only clinical, deep learning or radiomics factors. © 2023 SPIE.

Inflammatory biomarkers: Breast cancer survival and possible role in COVID-19 associated comorbidity

It is known that inflammatory cytokines exacerbate the persistence and severity of various disease states. Breast cancer is the most frequently detected cancer among women worldwide and our recent studies suggest that the inflammatory state of breast (BrCa) cancer, a byproduct of elevated cytokine expression, induces epigenetic modifications leading to increased recurrence. Ongoing NCI clinical trial data (ClinicalTrials.gov, CCC19, NCT04354701) indicates that among patients with cancer and COVID-19, the mortality is high, and the most prevalent malignancies are of breast [21%] and prostate [16%] origin. Due to the risk of cytokine storm during SARS-CoV-2 infection, it is crucial to identify potential mechanisms of hyperinflammation in BrCa patients. In this study, we have evaluated the level of copy number alteration (CNA) of different inflammatory cytokines including IL-8, IL-1b, IL6, IL-8, GM-CSF, TNF-alpha and many others using cBioportal platform which includes over sixty-nine thousand tumor samples (n>69,000 from 213 different studies) from over 33 different cancers. We found that IL-8 has the highest level of amplification in different breast cancers subtypes. Besides, we also analyzed serum samples from BrCa patients, both recurrent and non-recurrent, by different proteomics methods to identify serum cytokines involved in prognosis and recurrence. Comparative data analysis between non-recurrent BrCa against recurrent BrCa patients identified several proteins with very high significance, mostly proteins associated with epigenetic pathways including HDAC9 (P = 0.0035), HDAC5 (P = 0.013), and HDAC7 (P = 0.020). Besides, we identified differential expression of several pro-inflammatory cytokines and immune regulators (IL-8, IL-4, IL-18, IL-12p70) that were present only in recurrent BrCa patient serum. Our data indicate that inflammatory processes contribute to epigenetic modifications that ultimately play a critical role in breast cancer recurrence. In terms of COVID-19 associated co-morbidity, the already dysregulated inflammatory state of BrCa patients may increase their susceptibility to cytokine-storm, leading to increased severity of COVID-related complications and increased mortality rate. Specifically, we hypothesize that the identified elevated level of IL-8 in BrCa patients may lead to a higher basal level of inflammation and contribute to the risk of attaining cytokine-storm during SARS-CoV-2 infection, making it a valuable target for future studies.

User Consumption Behavior Recognition Based on SMOTE and Improved AdaBoost

The sudden outbreak of COVID-19 has dealt a huge blow to traditional education and training companies. Institutions use the WeChat platform to attract users, but how to identify high-quality users has always been a difficult point for enterprises. In this paper, researchers proposed a classification algorithm based on SMOTE and the improved AdaBoost, which fuses feature information weights and sample weights to effectively solve the problems of overfitting and sample imbalance. To justify the study, it was compared with other traditional machine-learning algorithms. The accuracy and recall of the model increased by 19% and 36%, respectively, and the AUC value reached 0.98, indicating that the model could effectively identify the user's purchase intention. The proposed algorithm also ensures that it works well in spam identification and fraud detection. This research is of great significance for educational institutions to identify high-quality users of the WeChat platform and increase purchase conversion rate.

Progress in Research of COVID-19 Based on Proteomics Techniques

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is highly contagious and spreads rapidly, posing a serious threat to the health and safety of people around the world. Proteomics technology has the characteristics of high throughput and high sensitivity, and plays an important role in biomarker discovery, molecular mechanism research, and therapeutic target research. Proteomics technology has been widely used in the research of COVID-19. Herein, this study provides a comprehensive review of the research progress of COVID-19 based on proteomics techniques. In section 1, the genome structure of SARS-CoV-2 and the process of SARS-CoV-2 infecting host cells were summarized. In section 2, the currently commonly used mass spectrometry (MS)-based proteomics techniques including liquid chromatography (LC)-MS and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS were reviewed. In section 3, the application progress in the research of precise diagnosis, molecular mechanism and drug therapy targets of COVID-19 based proteomics technology was highlighted. Proteomics have been employed in biomedical research to uncover biomarkers associated with COVID-19, it also provides a comprehensive snapshot of virus-induced changes to the host following infection, invasion, persistence, and pathogenesis and can prime the identification of novel therapeutic targets for preventing or lessening disease severity. In section 4, the future development direction of proteomics was prospected. It's hoped that this review can help to promote the development of proteomics technology in the precise diagnosis and treatment of diseases. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

Risk Factors of In-hospital Death in COVID-19 Patients：a Meta-analysis

Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis，and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library，ScienceDirect，PubMed，Medline，Wanfang Data，CNKI and CQVIP from inception to October 1，2021. Literature screening，data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors（86.37%），and 55 234 deaths（13.63%）〕，that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49，95%CI（1.41，1.57），P<0.001），older age〔WMD=10.44，95%CI（9.79，11.09），P<0.001〕，dyspnoea〔OR=2.09，95%CI（1.80，2.43），P<0.001〕，fatigue〔OR=1.49，95%CI（1.31，1.69），P<0.001〕，obesity〔OR=1.46，95%CI（1.43，1.50），P<0.001〕，smoking〔OR=1.18，95%CI （1.14，1.23），P<0.001〕，stroke〔OR=2.26，95%CI（1.41，3.62），P<0.001〕，kidney disease〔OR=3.62，95%CI （3.26，4.03），P<0.001〕，cardiovascular disease〔OR=2.34，95%CI（2.21，2.47），P<0.001〕，hypertension〔OR=2.23，95%CI（2.10，2.37），P<0.001〕，diabetes〔OR=1.84，95%CI（1.74，1.94），P<0.001〕，cancer〔OR=1.86，95%CI （1.69，2.05），P<0.001〕，pulmonary disease〔OR=2.38，95%CI（2.19，2.58），P<0.001〕，liver disease〔OR=1.65，95%CI（1.36，2.01），P<0.001〕，elevated levels of white blood cell count〔WMD=2.03，95%CI（1.74，2.32），P<0.001〕，neutrophil count〔WMD=1.77，95%CI（1.49，2.05），P<0.001〕，total bilirubin〔WMD=3.19，95%CI（1.96，4.42），P<0.001〕，aspartate transaminase〔WMD=13.02，95%CI（11.70，14.34），P<0.001〕，alanine transaminase 〔WMD=2.76，95%CI（1.68，3.85），P<0.001〕，lactate dehydrogenase〔WMD=166.91，95%CI（150.17，183.64），P<0.001〕，blood urea nitrogen〔WMD=3.11，95%CI（2.61，3.60），P<0.001〕，serum creatinine〔WMD=22.06，95%CI （19.41，24.72），P<0.001〕，C-reactive protein〔WMD=76.45，95%CI （71.33，81.56），P<0.001〕，interleukin-6 〔WMD=28.21，95%CI（14.98，41.44），P<0.001〕，and erythrocyte sedimentation rate〔WMD=8.48，95%CI（5.79，11.17），P<0.001〕were associated with increased risk of in-hospital death for patients with COVID-19，while myalgia〔OR=0.73，95%CI（0.62，0.85），P<0.001〕，cough〔OR=0.87，95%CI（0.78，0.97），P=0.013〕，vomiting〔OR=0.73，95%CI （0.54，0.98），P=0.030〕，diarrhoea〔OR=0.79，95%CI（0.69，0.92），P=0.001〕，headache〔OR=0.55，95%CI（0.45，0.68），P<0.001〕，asthma〔OR=0.73，95%CI（0.69，0.78），P<0.001〕，low body mass index〔WMD=-0.58，95%CI （-1.10，-0.06），P=0.029〕，decreased lymphocyte count〔WMD=-0.36，95%CI（-0.39，-0.32），P<0.001〕，decreased platelet count 〔WMD=-38.26，95%CI（-44.37，-32.15），P<0.001〕，increased D-dimer〔WMD=0.79，95%CI（0.63，0.95），P<0.001〕，longer prothrombin time〔WMD=0.78，95%CI（0.61，0.94），P<0.001〕，lower albumin〔WMD =-1.88，95%CI（-2.35，-1.40），P<0.001〕，increased procalcitonin〔WMD=0.27，95%CI（0.24，0.31），P<0.001〕，and increased cardiac troponin〔WMD=0.04，95%CI（0.03，0.04），P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result，the heterogeneity in gender，renal disease，cardiovascular diseases，asthma，white blood cell count，neutrophil count，platelet count，hemoglobin，and urea nitrogen differed siangificnatly by country（P<0.05）. Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors（including being male，older age，dyspnoea，fatigue，obesity，smoking，stroke，kidney disease，cardiovascular disease，hypertension，diabetes，cancer，pulmonary disease，liver disease，elevated levels of white blood cells，neutrophil count，total bilirubin，aspartate transaminase，alanine transaminase，lactate dehydrogenase，blood urea nitrogen，serum creatinine，C-reactive protein，interleukin-6，and erythrocyte sedimentation rate），and may be decreased by 13 factors（including myalgia，cough，vomiting，diarrhoea，headache，asthma，low body mass index，decreased lymphocyte count and platelet count，increased D-dimer，longer prothrombin time，lower albumin，increased procalcitonin and cardiac troponin）. The conclusion drawn from this study needs to be further confirmed by high-quality，multicenter，large-sample，real-world studies. © 2023 Chinese General Practice. All rights reserved.

Risk Factors of In-hospital Death in COVID-19 Patients：a Meta-analysis

Background The worldwide COVID-19 pandemic has turned into a global catastrophic public health crisis，and the conclusion about the risk factors of hospital death in COVID-19 patients is not uniform. Objective To explore risk factors of in-hospital death in patients with COVID-19 by a meta-analysis. Methods Case-control studies about risk factors of in-hospital death in COVID-19 patients were searched from databases of the Cochrane Library，ScienceDirect，PubMed，Medline，Wanfang Data，CNKI and CQVIP from inception to October 1，2021. Literature screening，data extraction and methodological quality assessment were conducted. Meta-analysis was performed using Stata 15.1. Meta-regression was used to explore the potential sources of heterogeneity. Results Eighty studies were included which involving 405 157 cases〔349 923 were survivors（86.37%），and 55 234 deaths（13.63%）〕，that were rated as being of high quality by the Newcastle-Ottawa Scale. Meta-analysis showed that being male〔OR=1.49，95%CI（1.41，1.57），P<0.001），older age〔WMD=10.44，95%CI（9.79，11.09），P<0.001〕，dyspnoea〔OR=2.09，95%CI（1.80，2.43），P<0.001〕，fatigue〔OR=1.49，95%CI（1.31，1.69），P<0.001〕，obesity〔OR=1.46，95%CI（1.43，1.50），P<0.001〕，smoking〔OR=1.18，95%CI （1.14，1.23），P<0.001〕，stroke〔OR=2.26，95%CI（1.41，3.62），P<0.001〕，kidney disease〔OR=3.62，95%CI （3.26，4.03），P<0.001〕，cardiovascular disease〔OR=2.34，95%CI（2.21，2.47），P<0.001〕，hypertension〔OR=2.23，95%CI（2.10，2.37），P<0.001〕，diabetes〔OR=1.84，95%CI（1.74，1.94），P<0.001〕，cancer〔OR=1.86，95%CI （1.69，2.05），P<0.001〕，pulmonary disease〔OR=2.38，95%CI（2.19，2.58），P<0.001〕，liver disease〔OR=1.65，95%CI（1.36，2.01），P<0.001〕，elevated levels of white blood cell count〔WMD=2.03，95%CI（1.74，2.32），P<0.001〕，neutrophil count〔WMD=1.77，95%CI（1.49，2.05），P<0.001〕，total bilirubin〔WMD=3.19，95%CI（1.96，4.42），P<0.001〕，aspartate transaminase〔WMD=13.02，95%CI（11.70，14.34），P<0.001〕，alanine transaminase 〔WMD=2.76，95%CI（1.68，3.85），P<0.001〕，lactate dehydrogenase〔WMD=166.91，95%CI（150.17，183.64），P<0.001〕，blood urea nitrogen〔WMD=3.11，95%CI（2.61，3.60），P<0.001〕，serum creatinine〔WMD=22.06，95%CI （19.41，24.72），P<0.001〕，C-reactive protein〔WMD=76.45，95%CI （71.33，81.56），P<0.001〕，interleukin-6 〔WMD=28.21，95%CI（14.98，41.44），P<0.001〕，and erythrocyte sedimentation rate〔WMD=8.48，95%CI（5.79，11.17），P<0.001〕were associated with increased risk of in-hospital death for patients with COVID-19，while myalgia〔OR=0.73，95%CI（0.62，0.85），P<0.001〕，cough〔OR=0.87，95%CI（0.78，0.97），P=0.013〕，vomiting〔OR=0.73，95%CI （0.54，0.98），P=0.030〕，diarrhoea〔OR=0.79，95%CI（0.69，0.92），P=0.001〕，headache〔OR=0.55，95%CI（0.45，0.68），P<0.001〕，asthma〔OR=0.73，95%CI（0.69，0.78），P<0.001〕，low body mass index〔WMD=-0.58，95%CI （-1.10，-0.06），P=0.029〕，decreased lymphocyte count〔WMD=-0.36，95%CI（-0.39，-0.32），P<0.001〕，decreased platelet count 〔WMD=-38.26，95%CI（-44.37，-32.15），P<0.001〕，increased D-dimer〔WMD=0.79，95%CI（0.63，0.95），P<0.001〕，longer prothrombin time〔WMD=0.78，95%CI（0.61，0.94），P<0.001〕，lower albumin〔WMD =-1.88，95%CI（-2.35，-1.40），P<0.001〕，increased procalcitonin〔WMD=0.27，95%CI（0.24，0.31），P<0.001〕，and increased cardiac troponin〔WMD=0.04，95%CI（0.03，0.04），P<0.001〕were associated with decreased risk of in-hospital death due to COVID-19. According to the meta-regression result，the heterogeneity in gender，renal disease，cardiovascular diseases，asthma，white blood cell count，neutrophil count，platelet count，hemoglobin，and urea nitrogen differed siangificnatly by country（P<0.05）. Conclusion The risk of in-hospital death due to COVID-19 may be increased by 25 factors（including being male，older age，dyspnoea，fatigue，obesity，smoking，stroke，kidney disease，cardiovascular disease，hypertension，diabetes，cancer，pulmonary disease，liver disease，elevated levels of white blood cells，neutrophil count，total bilirubin，aspartate transaminase，alanine transaminase，lactate dehydrogenase，blood urea nitrogen，serum creatinine，C-reactive protein，interleukin-6，and erythrocyte sedimentation rate），and may be decreased by 13 factors（including myalgia，cough，vomiting，diarrhoea，headache，asthma，low body mass index，decreased lymphocyte count and platelet count，increased D-dimer，longer prothrombin time，lower albumin，increased procalcitonin and cardiac troponin）. The conclusion drawn from this study needs to be further confirmed by high-quality，multicenter，large-sample，real-world studies. © 2023 Chinese General Practice. All rights reserved.

Predicting pharmacist intention to contributing to COVID-19 management: A cross-sectional survey study

Background: Pharmacists have a key role to play in responding to public health emergencies such as the COVID-19 pandemic. However, few studies have sought to evaluate their intention to contributing to the outbreak management. Purpose(s): This study used the theory of planned behaviour (TPB) to investigate pharmacists' intention to practice the FIP COVID-19 recommendations and to explore possible enablers that support such practice. Method(s): A cross-sectional, self-administered survey was distributed to pharmacists in Macau in May 2020. Cronbach's alpha was used to test the reliability for the four TPB constructs (attitude, subjective norm (SN), perceived behavioral control (PBC), and intention). Multiple linear regressions were conducted to predict intention using the other three TPB constructs Results: Pharmacists (n=110) had a positive intention to contributing to COVID-19 management (mean=4.21+/-0.60). Attitude (beta=0.547, p=0.000), SN (beta=0.177, p=0.050) and PBC (beta=0.158, p=0.027) were significant predictors of intention, accounting for 60.2% of the variance in their intention to practice. Scale reliability ranged from 0.838 to 0.948 for the four constructs. The difference between past behaviours and intentions was statistically significant (p=0.000). Important enablers to support the practice included training (mean= 4.26+/-0.57), better communication with stakeholders (mean=4.17+/-0.61) and improved pharmacy management (mean=4.18+/-0.60). Conclusion(s): Pharmacists showed favourable attitude, SN, PBC and intention to contributing to COVID19 management. Actions to enhance training, stakeholder communication and pharmacy management are important to increasing their willingness to take part in public health emergency alike in the future.

Progress in Research of COVID-19 Based on Proteomics Techniques

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is highly contagious and spreads rapidly, posing a serious threat to the health and safety of people around the world. Proteomics technology has the characteristics of high throughput and high sensitivity, and plays an important role in biomarker discovery, molecular mechanism research, and therapeutic target research. Proteomics technology has been widely used in the research of COVID-19. Herein, this study provides a comprehensive review of the research progress of COVID-19 based on proteomics techniques. In section 1, the genome structure of SARS-CoV-2 and the process of SARS-CoV-2 infecting host cells were summarized. In section 2, the currently commonly used mass spectrometry (MS) -based proteomics techniques including liquid chromatography (LC)-MS and matrix-assisted laser desorption/ionization time-of-flight (MALDITOF) MS were reviewed. In section 3, the application progress in the research of precise diagnosis, molecular mechanism and drug therapy targets of COVID-19 based proteomics technology was highlighted. Proteomics have been employed in biomedical research to uncover biomarkers associated with COVID-19, it also provides a comprehensive snapshot of virus-induced changes to the host following infection, invasion, persistence, and pathogenesis and can prime the identification of novel therapeutic targets for preventing or lessening disease severity. In section 4, the future development direction of proteomics was prospected. It's hoped that this review can help to promote the development of proteomics technology in the precise diagnosis and treatment of diseases.

Construction and Analysis of Surrounding Travel Demanding Graph Based on Dual Contrastive Learning Text Classification and Graph Neural Network

Understanding the main information about the current situation of the tourism market has become an urgent need and new trends in the development of the tourism market. In this paper, we use natural language processing technology to analyze the development of tourism around Maoming City, Guangdong Province during the COVID-19 epidemic by means of data mining methods to build a local tourism graph, refine and design models and methods such as RoBERTa-BiGRU-Attention fusion model, dual contrastive learning, BERT-BiLSTM-CRF named entity identification technique, improved Apriori algorithm, GNNLP model based on conventional models and proved the rationality and efficiency of the improved model by comparative test, provide oriented suggestions to help government departments promote tourism and tourism enterprises product supply, optimize resource allocation and explore the market constantly during the epidemic period after scientific analysis and summary. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Traditional Chinese medicine for promoting mental health of patients with COVID-19: a scoping review

This study aimed to systematically review and depict the current studies of traditional Chinese medicine for the mental health of patients with coronavirus disease 2019 (COVID-19).Methods:: A scoping review was conducted by searching PubMed, Web of Science, CNKI, Wanfang database, VIP database, and SinoMed, with the retrieval time being from the establishment of the database to April 18, 2022. The basic information of the included studies, objective, design, types of patients, interventions, outcomes, etc., was reviewed and summarized narratively. Methodological quality was assessed using the Cochrane Risk of Bias assessment tool, the methodological index for non-randomized studies or the Newcastle–Ottawa scale. Results:: We identified 30 traditional Chinese medicine (TCM) studies from six databases. Among them, finished randomized controlled trials (n = 16) accounted for most of the studies, followed by single-arm studies (n = 9). In terms of study theme, 20 studies defined the mental health of patients with COVID-19 as the research theme. Psychological assessment was included in the inclusion criteria (performed before participation) of nine studies, whereas the other studies only mentioned the mental outcomes. TCM interventions included TCM exercises (Yijinjing, Baduanjin, Liuzijue, Taichi), acupoint stimulation (auricular and body points), moxibustion, decoction, or granules based on TCM syndrome differentiation, decoction, or granules with fixed formulae (Baidu Jieduan granules, Xuanfei Baidu decoction, and Qingfei Paidu decoction), Chinese patent medicine (Jinhua Qinggan granules), TCM psychological therapy (TCM ideological therapy, TCM five-tone therapy, and TCM psychological sand table), and TCM nursing (dialectical care, dialectical diet, and psychological counseling). Anxiety and depression were the main outcomes evaluated in regard to mental health in patients with COVID-19. The limitations of methodological quality were predominantly from follow-up, blinding, and registration. Positive results were reported by 27 studies (90%, n = 30). Conclusion:: We summarized the existing literature about the impact of TCM on mental health in patients with COVID-19. The number of studies evaluating the impact of TCM on mental health is encouraging, but overall methodological quality was low. Several TCM interventions warrant further evaluation, particularly among populations outside of China, for the purpose of establishing supporting evidence. More importantly, research with stronger methodological quality needs to be developed. Graphical :: http://links.lww.com/AHM/A36.

BYOZ: Protecting BYOD Through Zero Trust Network Security

As the COVID-19 pandemic scattered businesses and their workforces into new scales of remote work, vital security concerns arose surrounding remote access. Bring Your Own Device (BYOD) also plays a growing role in the ability of companies to support remote workforces. As more enterprises embrace concepts of zero trust in their network security posture, access control policy management problems become a more significant concern as it relates to BYOD security enforcement. This BYOD security policy must enable work from home, but enterprises have a vested interest in maintaining the security of their assets. Therefore, the BYOD security policy must strike a balance between access, security, and privacy, given the personal device use. This paper explores the challenges and opportunities of enabling zero trust in BYOD use cases. We present a BYOD policy specification to enable the zero trust access control known as BYOZ. Accompanying this policy specification, we have designed a network architecture to support enterprise zero trust BYOD use cases through the novel incorporation of continuous authentication & authorization enforcement. We evaluate our architecture through a demo implementation of BYOZ and demonstrate how it can meet the needs of existing enterprise networks using BYOD. © 2022 IEEE.

Analysis of COVID-19 Impact on Public Transport Usage based on Smart Card Data-A Regional Case Study in Australia

The outbreak of COVID-19 has made a profound impact on mobility, especially for public transport users. Extensive research has been conducted on the change of travel patterns in major cities where public transport systems have been well developed and heavily used. However, in small cities, the public transport network is relatively sparse, especially in suburban areas, which makes the corresponding travel patterns differ from those in major cities. Therefore, proper investigation of the public transport usage in such small cities is still needed, especially under the COVID-19 impact. This paper aims to reveal the change of public transport users' travel patterns based on a comparative study of public transport usage Pre-COVID and during the COVID-19 period. The Illawarra, a coastal region close to Sydney in Australia is used as a case study. Smart card data is used to reveal relevant changes in both intraregion (in the Illawarra) and inter-region (between the Illawarra and Sydney) travels in consideration of heterogeneous user groups. The results show a significant decrease (around 47%) in public transport ridership by both train and bus. However, compared to intra-region ridership, the inter-region trips by train drop much more (around 62%). Moreover, heterogeneous age group passengers show different changes after the COVID-19 outbreak. The research findings are expected to provide valuable suggestions for policy making and public transport service adjustment when a similar crisis occurs again. © 2022 IEEE.

School librarians leading from the center in online learning contexts: Informal communities of practice creating space for connection and collaboration

This study used qualitative methodology based on focus group interviews to explore school librarians ' involvement during the move to online teaching and learning contexts. Findings indicate these educators felt underutilized because of stakeholder misperceptions of their roles. However, most school librarians in the study reported creating informal communities of practice to support teachers and students through innovative responses to online learning demands caused by the COVID-19 pandemic. © 2022, American Library Association. All rights reserved.

Strategies for China's Historic Districts Regeneration in Responding to Public Health Emergencies

Most of China's historic districts are located in urban centers with excessive building density and possess rich historical, cultural, scientific and aesthetic value. However, historic districts lack infrastructure and specific plans for emergency response compared to modern residential areas in cities, creating a social inequity trap for the residents in both. In addition, as valuable material cultural heritage, the usual conservation of local culture and the ecological environment conflict with anti-epidemic requirements. This study proposes a system of strategies for responding to public health emergencies that can address the above issues. Through the methods of policy refinement and the application of the concept of normal and disaster time conversion, the strategic system was constructed, including five major aspects: emergency preparedness programs at the planning level, installation of modulized variable devices, environmentally friendly health protection, disaster prevention preparation at the spatial level, and plant configuration. It is beneficial to improve the disaster prevention system for special urban communities and provide a reference for emergency planning in the future regeneration process of historic districts.

Prediction of Post-COVID-19 economic and environmental policy and recovery based on recurrent neural network and long short-term memory network

COVID-19 has brought significant impacts on the global economy and environment. The Global Economic-and-environmental Policy Uncertainty (GEPU) index is a critical indicator to measure the uncertainty of global economic policies. Its prediction provides evidence for the good prospect of global economic and environmental policy and recovery. This is the first study using the monthly data of GEPU from January 1997 to January 2022 to predict the GEPU index after the COVID-19 pandemic. Both Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models have been adopted to predict the GEPU. In general, the RNN outperforms the LSTM networks, and most results suggest that the GEPU index will remain stable or decline in the coming year. A few results point to the possibility of a short-term increase in GEPU, but still far from its two peaks during the first year of the COVID-19 pandemic. This forecast confirms that the impact of the epidemic on global economic and environmental policy will continue to wane. Lower economic and environmental policy uncertainty facilitates global economic and environmental recovery. Economic recovery brings more opportunities and a stable macroeconomic environment, which is a positive sign for both investors and businesses. Meanwhile, for the ecological environment, the declining GEPU index marks a gradual reduction in the direct impact of policy uncertainty on sustainable development, but the indirect environmental impact of uncertainty may remain in the long run. Our prediction also provides a reference for subsequent policy formulation and related research.

Analysis of Epidemic Prevention and Economic Operation Monitoring Based on Electric Power Big Data

Restoring economic development while strictly preventing and controlling the epidemic is the new challenge for the Chinese government under the normal state of COVID-19 epidemic prevention and control. This paper constructs an epidemic situation-population flow-consumption climate index model based on K-means clustering analysis algorithm. The model extracts the real-time and historical power consumption of residents, merchants and enterprises as the basic data, selects the epidemic information and user attributes as the classification parameters, applies k-means algorithm for cluster analysis, and finally obtains the relationship between consumption climate index and population flow index which reflects the government's monitoring strength. A case of delta COVID-19 in Hubei from August 1, 2021, to August 16, 2021, was analyzed. The analysis results show that the epidemic prevention and control effect is obvious, and population mobility is significantly reduced. © 2022 IEEE.

Composition decipherment of Ficus pumila var. awkeotsang and its potential on COVID-19 symptom amelioration and in silico prediction of SARS-CoV-2 interference

The jelly from achenes of Ficus pumila var. awkeotsang (FPAA) is a famous beverage ingredient in Taiwan. In this work, ficumarin (1), a new compound was obtained from its twigs (FPAT) and elucidated with comprehensive spectroscopic data. The biosynthetic origin was proposed from the p-coumaroyl-CoA pathway. Alloxanthoxyletin, betulinic acid, and catechin were identified as the major and active constituents responsible for relieving neutrophilic inflammation by FPAT. Among them, the most potent alloxanthoxyletin was found to interact with PRO350 and GLU377 of human INOSOX. Further, Nrf2 activating capacity of the FPAT fraction and its coumarins was confirmed. With the analysis of LC-MS/MS data and feature-based molecular networking, coumarins were found as the dominant and responsible components. Notably, alloxanthoxyletin increased Nrf2 expression by up to 816.8 +/- 58% due to the interacting with the VAL561, THR560 and VAL420 residues of 5FNQ protein. COVID-19 Docking Server simulation indicated that pyranocoumarins would promisingly interfere with the life cycle of SARS-CoV-2. FPAT was proven to exert. Copyright © 2022 Taiwan Food and Drug Administration.

Correction to: Isolation and Propagation of Porcine Deltacoronavirus in Cell Culture and Embryonated Chicken Eggs (Animal Coronaviruses)

Correction to: Chapter 6 in: LeyiWang (ed.), Animal Coronaviruses, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-2091-5_6 In the original version of this book, the title of Chapter 6 was published incorrectly. This has been rectified in the updated version of this book. Copyright © 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Analysis on parents'willingness and factors to inoculate COVID-19 vaccine

Objective To understand the willingness and factors of children's parents for COVID- 19 inoculation,and to provide the basis for the formulation of COVID- 19 inoculation strategy. Methods Easy sampling was used to conduct questionnaire survey on parents of 215 children from a Grade AAA hospital in Wuhan between December 2020 and January 2021. Results One hundred and fifteen valid questionnaires were collected, and 96.74% of parents had heard of COVID- 19 before this survey. WeChat accounts 43.72%(94/215) and Tiktok accounts 28.37%(61/215) were main sources of COVID- 19 and vaccine- related knowledge. 90.23%(194/215) of the parents of children were willing to be inoculated against COVID- 19, and 9.77%(21/215) of children’s parents weren’ t willing to be inoculated against COVID -19 vaccine, mainly because they believed that the interval between the development and use of the vaccine was short,the necessity of time spending in considering(38.10%, 8/21),concerns about adverse effects and safety(47.62%,10/21). Parents of children with a bachelor's degree(OR=0.034,95% CTJO.002-0.582) and a monthly income of 5 000 to 7 999 Yuan(OR=11.459,95%CI-1.708-76.870) were more likely to inoculate COVID- 19 vaccine. Conclusion Parents of children have high willingness to inoculate COVID- 19 vaccines, while they show concerns about adverse reactions and safety of vaccines. The authorities concerned are recommended to strengthen the publicity of inoculation knowledge of COVID- 19 to thereby ease public doubts and ensure safe and effective promotion of vaccines. © 2022, Editorial Department of Medical Pest Control. All rights reserved.