Time and Frequency Spillovers between the Green Economy and Traditional Energy Markets

The green economy is aimed at decreasing the dependence of the global economy on traditional fossil energy, thereby resolving conflicts between economic development and environmental issues and achieving sustainable economic development. Thus, the relation between the green economy and traditional energy markets is of great importance for both policymakers and portfolio managers. In this study, we investigate the dynamic spillover effects between the green economy and traditional energy markets by applying time and frequency spillover measures based on the TVP-VAR model. The results reveal a strong spillover relationship between the green economy and traditional energy system, and the spillover direction is mainly from green economy markets to traditional energy markets. Our analysis further reveals the heterogeneity of these spillover effects, both within green economy markets and between these markets and traditional energy markets. The performance of the U.S. green economy market is similar to that of Europe, whereas the Asian green economy market is more complex. The frequency domain results demonstrate that the spillover effects are mainly dominated by short-term (1–5 days) components, whereas medium- and long-term components have less of an effect. In addition, we find a sharp increase in the level of spillover effects during the COVID-19 pandemic. © 2023 by the authors.

Strategy for covid-19 vaccination for patients with tuberculosis during the covid-19 pandemic.

The pandemic of COVID-19 is still rampaging all over the world, so it is urgent to popularize vaccination. Meanwhile, pulmonary tuberculosis is one of the chronic infectious diseases with a high incidence in China. Since these diseases all occur in lung tissue, patients with TB and COVID-19 co-infection show more serious conditions and poorer treatment effects. However, we have limited knowledge about the protective efficacy, immunogenicity and safety of COVID-19 vaccine in patients with TB at present, with a lack of corresponding evidence-based medicine as well. Therefore, this paper reviews the pathogenesis and epidemiology of TB, discusses the immune status of patients with TB and summarizes the existing proposals for vaccination of patients with TB at home and abroad. Furthermore, we analyze the existing clinical trials in TB patients and other special populations, and finally discuss the strategy of vaccination for patients with TB during the COVID-19 pandemic and the necessity of clinical research on COVID-19 vaccines with target population of TB patients.Copyright © 2022, Publication Centre of Anhui Medical University. All rights reserved.

Strategy for covid-19 vaccination for patients with tuberculosis during the covid-19 pandemic

The pandemic of COVID-19 is still rampaging all over the world, so it is urgent to popularize vaccination. Meanwhile, pulmonary tuberculosis is one of the chronic infectious diseases with a high incidence in China. Since these diseases all occur in lung tissue, patients with TB and COVID-19 co-infection show more serious conditions and poorer treatment effects. However, we have limited knowledge about the protective efficacy, immunogenicity and safety of COVID-19 vaccine in patients with TB at present, with a lack of corresponding evidence-based medicine as well. Therefore, this paper reviews the pathogenesis and epidemiology of TB, discusses the immune status of patients with TB and summarizes the existing proposals for vaccination of patients with TB at home and abroad. Furthermore, we analyze the existing clinical trials in TB patients and other special populations, and finally discuss the strategy of vaccination for patients with TB during the COVID-19 pandemic and the necessity of clinical research on COVID-19 vaccines with target population of TB patients.

Strategy for covid-19 vaccination for patients with tuberculosis during the covid-19 pandemic.

The pandemic of COVID-19 is still rampaging all over the world, so it is urgent to popularize vaccination. Meanwhile, pulmonary tuberculosis is one of the chronic infectious diseases with a high incidence in China. Since these diseases all occur in lung tissue, patients with TB and COVID-19 co-infection show more serious conditions and poorer treatment effects. However, we have limited knowledge about the protective efficacy, immunogenicity and safety of COVID-19 vaccine in patients with TB at present, with a lack of corresponding evidence-based medicine as well. Therefore, this paper reviews the pathogenesis and epidemiology of TB, discusses the immune status of patients with TB and summarizes the existing proposals for vaccination of patients with TB at home and abroad. Furthermore, we analyze the existing clinical trials in TB patients and other special populations, and finally discuss the strategy of vaccination for patients with TB during the COVID-19 pandemic and the necessity of clinical research on COVID-19 vaccines with target population of TB patients. Copyright © 2022, Publication Centre of Anhui Medical University. All rights reserved.

Strategy for covid-19 vaccination for patients with tuberculosis during the covid-19 pandemic

The pandemic of COVID-19 is still rampaging all over the world, so it is urgent to popularize vaccination. Meanwhile, pulmonary tuberculosis is one of the chronic infectious diseases with a high incidence in China. Since these diseases all occur in lung tissue, patients with TB and COVID-19 co-infection show more serious conditions and poorer treatment effects. However, we have limited knowledge about the protective efficacy, immunogenicity and safety of COVID-19 vaccine in patients with TB at present, with a lack of corresponding evidence-based medicine as well. Therefore, this paper reviews the pathogenesis and epidemiology of TB, discusses the immune status of patients with TB and summarizes the existing proposals for vaccination of patients with TB at home and abroad. Furthermore, we analyze the existing clinical trials in TB patients and other special populations, and finally discuss the strategy of vaccination for patients with TB during the COVID-19 pandemic and the necessity of clinical research on COVID-19 vaccines with target population of TB patients. Copyright © 2022, Publication Centre of Anhui Medical University. All rights reserved.

Parallel Emergency Management of Incidents by Integrating OODA and PREA Loops: The C2 Mechanism and Modes

Given the differences of command and control (C2) activities between the field command center and the emergency operations center (EOC), this article combined the edge C2 theory with the parallel C2 theory, and proposed a parallel incident C2 mode based on the observe–orient–decide–act (OODA) loop and planning–readiness–execution–assessment (PREA) loop. The aim is to build up a PREA loop-based parallel incident C2 mode and its related operating mechanism of edge empowerment and energy release in parallel incident C2 mode. The parallel incident C2 mode based on the PREA loop and OODA loop supports the co-existence and connection of the two roles of the incident C2 agent at the emergency scene. The two roles are the executive role of emergency response and operation and the command and organization role of the edge emergency system. This article initiates a deep integration of two different C2 process mechanisms in the emergency response and operation process, taking into account the local emergency scene and the global emergency system. Taken together, a key issue has been well addressed regarding the contradiction that the traditional emergency response cannot be reconciled in terms of rapidity and thoroughness. Author

Trifluoroacetic Anhydride as Acylating Agent and Dehydrant in One-pot Synthesis of Nirmatrelvir

Nirmatrelvir is an effective ingredient in the anti COVID-19 drug Paxlovid. There were two key steps in the original synthetic route, which involved trifluoroacetylation and dehydration. A facile and efficient synthesis of nirmatrelvir is described in this work. Intermediate 7 was converted to nirmatrelvir in one-pot synthesis with trifluoroacetic anhydride. In addition, the condensation and deprotection conditions were optimized. The yield of nirmatrelvir produced from 1raised from 51.6% to 72.5%. © 2023,Cleveland Clinic Journal of Medicine.All Rights Reserved.

[Kinetics of SARS-CoV-2-specific antibodies among inactivated COVID-19 vaccine recipients, SARS-CoV-2 natural infection cases, and breakthrough cases].

Between August and September, 2021, this study included 605 SARS-CoV-2 natural infection cases and 589 SARS-CoV-2 breakthrough cases from Nanjing and Yangzhou, as well as 690 inactivated COVID-19 vaccine recipients from Changzhou, China. In SARS-CoV-2 natural infection cases, the age range was 19-91 years (median age: 66 year), and the medians(Q1,Q3) of IgG titers were 0.19 (0.06-1.31), 3.70 (0.76-69.48), 15.31 (2.59-82.16), 4.41 (0.99-31.74), 2.31 (0.75-13.83), 2.28 (0.68-9.94) and 2.80 (1.00-9.53) at one to seven weeks after SARS-CoV-2 infection, respectively. In SARS-CoV-2 breakthrough cases, the age range was 18-76 years (median age: 45 year), and the medians(Q1,Q3)of IgG titers were 1.93 (0.34-26.67), 38.87 (7.90-121.0), 75.09 (11.85-123.70), 21.97 (5.20-95.58), 13.97 (3.47-46.82), 9.56 (2.48-33.38) and 4.38 (1.87-11.00) at one to seven weeks after SARS-CoV-2 infection, respectively. In inactivated COVID-19 vaccine recipients, the age range was 18-87 years (median age: 47 years), and the medians(Q1,Q3)of IgG titers were 16.22 (15.84-33.42), 5.35 (2.96-13.23), 3.30 (2.18-6.18), 3.14 (1.16-5.70), 2.77 (1.50-4.52), 2.72 (1.76-4.36), 2.01 (1.27-3.51) and 1.94 (1.35-3.09) at one to eight months after SARS-CoV-2 infection, respectively. The results suggested that IgG antibodies increased gradually within two weeks after SARS-CoV-2 infection, then declined gradually at three to seven weeks in SARS-CoV-2 natural infection cases. In SARS-CoV-2 breakthrough cases, IgG antibodies increased rapidly within two weeks, then declined gradually at three to seven weeks after SARS-CoV-2 infection. Additionally, IgG antibodies decreased rapidly within three months, then decreased gradually and remained at a low level within three months after immunization.

COVID-19 Classification from Chest X-rays Based on Attention and Knowledge Distillation

The Coronavirus Disease 2019 (COVID-19) is the pandemic that has had the greatest impact on world economic development in recent years. Early detection is critical to identify patients with COVID-19, chest x-ray is used for early detection is a rapid, extensive and cost-effective method. The existing technology use deep learning methods, and have achieved very good results. However, the training time of deep learning method is long, and the model size makes it difficult to deploy on hardware system. In this work, we have proposed an attention-based ResNet50v2 network, and taken the network as the teacher network to transfer the knowledge to the student network by knowledge distillation. Thus, the student network has higher accuracy and sensitivity to the positive samples of COVID-19 under the condition of low model parameters, high training speed. The experimental results show that our network of teacher and student have achieved 100% accuracy and sensitivity in both COVID-19 and Normal binary classification. In addition, the accuracy rate of teacher network is 98.20%, the sensitivity is 99.58%, the accuracy rate of student network is 97.68%, the sensitivity is 99.17% in the COVID-19, Viral pneumonia and Normal multiple classification, and the parameters of the student network are only 0.269M. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

[Advances in clinical research of virus vector-based COVID-19 vaccines].

The COVID-19 outbreak at the end of 2019 has accelerated the development and research for COVID-19 vaccines worldwide. Among the COVID-19 vaccines in clinical trials developed via different platforms, recombinant virus vector-based vaccines have shown excellent immunogenicity and efficacy. However, at the same time, there are serious issues such as vaccine safety and pre-existing antibodies against vectors. This article summarizes the design concept and development history of recombinant virus vector-based vaccines, and focuses on the progress in the clinical studies of vector-based COVID-19 vaccines as well as the challenges, in order to provide reference for the research of recombinant vector-based vaccines.

Automated Detection of COVID-19 with Chest CT Scans using 3D Deep Learning model

COVID-19 is breaking out and spreading globally, posing a severe threat to public health and economies worldwide due to its highly transmissible and pathogenic nature. Early, accurate and rapid diagnosis of COVID-19 can effectively stop the spread of the COVID-19 virus. Automatic diagnostic models based on deep learning can detect COVID-19 quickly and accurately. This paper uses a three-dimensional Convolutional Neural Network (3D CNN) to build a COVID-19 diagnostic prediction model for COVID-19 detection. All 192 sets of chest Computed Tomography(CT) data collected are used for this study, including 96 sets of confirmed COVID-19 patients and 96 sets of CT scans of normal human lungs. 5-fold cross-validation is used to train and validate the model. 154 data sets are used to train the model, and 38 sets are used for testing. All experimental data are segmented using a pre-trained SP-V-Net to obtain 3D lung masks fed into 3D CNN for training and validation of the prediction model. In addition, to verify the accuracy of the model predictions and provide interpretability for medical diagnosis, we visualize the experimental results using Class Activation Maps(CAM) to localize the predicted disease regions. The results from several experiments show that the accuracy of our prediction model is 0.911, the Area Under Curve (AUC) 0.976, for no-COVID-19(Precision, 0.902, Recall 0.911, F1-Score 0.900), COVID-19 (Precision, 0.932, Recall 0.911, F1-Score 0.902). The experimental results show that our established diagnostic model can help physicians make a rapid and accurate diagnosis of COVID-19 in response to the spread of COVID-19. © 2021 IEEE.

Empirical Investigation of the Academic Emotions of Gaokao Applicants during the COVID-19 Pandemic

This global lockdown of educational institutions by COVID-19 has caused overwhelming disruption in students’ learning and assessment, which has substantial effects on their academic emotions. This study applied a mixed methods approach to investigate how COVID-19 influences Gaokao applicants’ academic emotions in the Chinese context. The study found that Gaokao applicants during the COVID-19 pandemic had strong positive activating emotions, positive deactivating emotions, and negative activating emotions. The results showed that there were significant gender differences in academic emotions, and students’ physical exercise was also related. This study found that there was no correlation between the Gaokao applicants’ academic emotions and their parents’ occupations, parents’ academic qualifications, or types of exams. As COVID-19 continues to be a worldwide public challenge, this study has implications on how to alleviate negative academic emotions of students who will take high-risk tests under the pressure of the pandemic. © The Author(s) 2022.

High-Throughput virtual screening of small molecule inhibitors for sars-cov-2 protein targets with deep fusion models

Structure-based Deep Fusion modelswere recently shown to outperform several physicsand machine learning-based protein-ligand binding affinity prediction methods. As part of a multi-institutional COVID-19 pandemic response, over 500 million small molecules were computationally screened against four protein structures from the novel coronavirus (SARS-CoV-2), which causes COVID-19. Three enhancements to Deep Fusion were made in order to evaluate more than 5 billion docked poses on SARS-CoV-2 protein targets. First, the Deep Fusion concept was refined by formulating the architecture as one, coherently backpropagated model (Coherent Fusion) to improve bindingaffinity prediction accuracy. Secondly, the model was trained using a distributed, genetic hyper-parameter optimization. Finally, a scalable, high-Throughput screening capability was developed to maximize the number of ligands evaluated and expedite the path to experimental evaluation. In this work, we present both the methods developed for machine learning-based high-Throughput screening and results from using our computational pipeline to find SARS-CoV-2 inhibitors. © 2021 IEEE Computer Society. All rights reserved.

Gender Inequality in Research Productivity During the COVID-19 Pandemic

Problem definition: We study the disproportionate impact of the lockdown as a result of the COVID-19 outbreak on female and male academic research productivity in social science. Academic/practical relevance: The lockdown has caused substantial disruptions to academic activities, requiring people to work from home. How this disruption affects productivity and the related gender equity is an important operations and societal question. Methodology: We collect data from the largest open-access preprint repository for social science on 41,858 research preprints in 18 disciplines produced by 76,832 authors across 25 countries over a span of two years. We use a difference-in-differences approach leveraging the exogenous pandemic shock. Results: Our results indicate that, in the 10 weeks after the lockdown in the United States, although total research productivity increased by 35%, female academics' productivity dropped by 13.2% relative to that of male academics. We also show that this intensified productivity gap is more pronounced for assistant professors and for academics in top-ranked universities and is found in six other countries. Managerial implications: Our work points out the fairness issue in productivity caused by the lockdown, a finding that universities will find helpful when evaluating faculty productivity. It also helps organizations realize the potential unintended consequences that can arise from telecommuting.

Immunogenicity and safety of a SARS-CoV-2 inactivated vaccine in healthy adults: randomized, double-blind, and placebo-controlled phase 1 and phase 2 clinical trials

BACKGROUND: The significant morbidity and mortality resulted from the infection of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for urgent development of effective and safe vaccines. We report the immunogenicity and safety of an inactivated SARS-CoV-2 vaccine, KCONVAC, in healthy adults. METHODS: Phase 1 and phase 2 randomized, double-blind, and placebo-controlled trials of KCONVAC were conducted in healthy Chinese adults aged 18-59 years. The participants in the phase 1 trial were randomized to receive two doses, one each on Days 0 and 14, of either KCONVAC (5 mug/dose or 10 mug/dose) or placebo. The participants in the phase 2 trial were randomized to receive either KCONVAC (at 5 or 10 mug/dose) or placebo on Days 0 and 14 (0/14 regimen) or Days 0 and 28 (0/28 regimen). In the phase 1 trial, the primary safety endpoint was the proportion of participants experiencing adverse reactions/events within 28 days following the administration of each dose. In the phase 2 trial, the primary immunogenicity endpoints were neutralization antibody seroconversion and titer and anti-receptor-binding domain immunoglobulin G seroconversion at 28 days after the second dose. RESULTS: In the phase 1 trial, 60 participants were enrolled and received at least one dose of 5-mug vaccine (n = 24), 10-mug vaccine (n = 24), or placebo (n = 12). In the phase 2 trial, 500 participants were enrolled and received at least one dose of 5-mug vaccine (n = 100 for 0/14 or 0/28 regimens), 10-mug vaccine (n = 100 for each regimen), or placebo (n = 50 for each regimen). In the phase 1 trial, 13 (54%), 11 (46%), and 7 (58%) participants reported at least one adverse event (AE) after receiving 5-mug vaccine, 10-mug vaccine, or placebo, respectively. In the phase 2 trial, 16 (16%), 19 (19%), and 9 (18%) 0/14-regimen participants reported at least one AE after receiving 5-mug vaccine, 10-mug vaccine, or placebo, respectively. Similar AE incidences were observed in the three 0/28-regimen treatment groups. No AEs with an intensity of grade 3+ were reported, expect for one vaccine-unrelated serious AE (foot fracture) reported in the phase 1 trial. KCONVAC induced significant antibody responses;0/28 regimen showed a higher immune responses than that did 0/14 regimen after receiving two vaccine doses. CONCLUSIONS: Both doses of KCONVAC are well tolerated and able to induce robust immune responses in healthy adults. These results support testing 5-mug vaccine in the 0/28 regimen in an upcoming phase 3 efficacy trial. TRIAL REGISTRATION: http://www.chictr.org.cn/index.aspx (No. ChiCTR2000038804, http://www.chictr.org.cn/showproj.aspx?proj=62350;No. ChiCTR2000039462, http://www.chictr.org.cn/showproj.aspx?proj=63353).

[Exploration and application of a novel attempt to recruit participants in clinical trials of vaccines under the emergency].

Objective: To evaluate and share the novel method for recruiting participants in clinical trials of vaccines in emergency situations. Methods: To publish recruitment notice in local areas of Wuhan through websites and medium, and guide interested persons to log in to the"Clinical Trials of SARS-CoV-2 Vaccine Reservation and Health Declaration System"to appoint and register their health information. The "Health Declaration System" provides each volunteer evaluation and risk levels to preliminarily exclude those who do not meet the inclusion criteria. Researchers review the qualified volunteers by telephone, organize them to go to the vaccination site, and finally conduct a strict medical screening to determine the final subjects. Results: A total of 4 819 people and 5 132 people registered in the Phase Ⅰ and Phase Ⅱ recruitment system respectively, with men 2 912 (60.43%) and 2 887 (56.25%) more than women 1 907 (39.57%) and 2 245 (43.75%), mostly in the 20-39 age group, with 3 211 (66.63%) and 3 966 (77.28%). All 13 districts in Wuhan have interested residents to participate clinical research.The initial qualified rate of the Phase Ⅱ recruitment system was higher than that of Phase Ⅰ, with men 2 047 (70.28%) and 2 135(73.95%), higher than women 1 083 (56.80%) and 1 472 (65.57%); 440 and 689 people were reviewed by telephone in Phase Ⅰ and Phase Ⅱ respectively, and the number of verified volunteers was about 440 (35.00%) and 689 (67.20%); Of the 201 603 people who arrived at the vaccination site, 12 and 26 of them were positive for the SARS-CoV-2 antibody with an antibody positive rate of 6.00% and 4.31% respectively. Conclusion: The novel method for recruiting subjects in this clinical study is efficient and reliable, and the recruitment situation of Phase Ⅰ had set a good example for Phase Ⅱ but the medium-and long-term compliance of subjects and the separation of willingness and behaviors still need to be further studied.

Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China.

BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown. PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010). CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.