ABSTRACT
The COVID-19 pandemic influenced higher degree by research (HDR) students' academic experiences profoundly as it forced HDR students to adjust their intensive and demanding research work and studies according to unforeseeable challenges. This was particularly challenging for international HDR students as they had rather limited resources in their host countries to cope with uncertainties, and the university emergency responses gave them limited attention and support. This resulted in many international HDR students feeling disempowered. However, recent research on international HDR students' experience in their host countries during the pandemic remains sparse. From an insiders' account, this autoethnography study aims to bridge this gap, investigating two Australia-based Chinese HDR students' struggles in their research studies and their academic identity self-formation. This study presents that the international HDR students managed to empower themselves by holding on to their support systems and exercising their agency in the middle of uncertainty. The findings presented in the study add to the understanding of the importance of providing a more inclusive and supportive environment for international HDR students' development. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
ABSTRACT
This chapter firstly provides a brief overview of the overall structure of the Chinese program and the Chinese language teaching at the University of Queensland (UQ) in Australia. Then it reports the findings of a one-on-one interviews with 35 students enrolled to a Chinese second year spoken course delivered in remote/online mode. The chapter ends with reflections on the points that were considered important in managing virtual classroom in online teaching. The conclusion is that it is possible to maintain high levels of student satisfaction by ensuring an interactive and engaging teaching style in a fully online delivery mode. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.
ABSTRACT
The spread of COVID-19 in the world has changed the way of life, economy, society, learning, and work around the world. Under the background of normalization of epidemic prevention and control, how to carry out overseas Chinese education and how to affect overseas Chinese education is an important issue with scholars in China and abroad and overseas Chinese. How to effectively deal with the international situation after the outbreak of the epidemic and how to determine the future developmental direction of overseas Chinese education is an important goal and direction that researchers need to study in depth. Based on the perspective of teaching effect evaluation of blended learning mode under the background of artificial intelligence, this article takes ASEAN Phuket Thai Chinese Schools as an example, collects relevant research data through a grounded survey method, adopts a quantitative analysis method, comprehensively judges the impact of overseas Chinese education after the outbreak of the epidemic, and puts forward systematic, comprehensive, and scientific suggestions. It is hoped that the decision-making mechanism and method innovation of overseas Chinese education in response to COVID-19 will be effectively promoted, and the effective development of overseas Chinese education will be actively promoted.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.
ABSTRACT
Objective To analyze the potential factors influencing the viral shedding time (duration of nucleic acid positivity) in elderly patients with mild and asymptomatic infection. Methods The clinical data of 1141 elderly (>=60 years) patients with mild and asymptomatic Omicron infection who were admitted to National Exhibition and Convention Center (Shanghai) Cabin Hospital from April 14, 2022 to May 1, 2022 were retrospectively collected, viral shedding time of patients were compared between different groups (age, gender, number of vaccination, hypertension, diabetes). Pearson analysis was adopted to analyze the relationship between age and viral shedding time. Kaplan-Meier curve and Log-rank test were used to evaluate the viral shedding time in elderly patients with different clinical characteristics. Multivariate Cox proportional-hazards regression model was adopted to analyze the factors influencing viral shedding time in elderly patients with Omicron. Results Among 1441 patients, 791(54.9%) males and 650(45.1%) females. There were 513(35.6%) patients receiving 0 dose of vaccine, 29(2.0%) patients received 1 dose of vaccine, 405(28.1%) patients received 2 doses of vaccine, 494(34.3%) patients received 3 doses of vaccine. Compared with patients aged 60 to 70 years, patients aged 70 to 80 years had longer viral shedding time (P<0.001). The viral shedding time in patients with hypertension and diabetes was longer than that in patients without hypertension and diabetes (P<0.05). In terms of vaccination, the viral shedding time of patients receiving 2 or 3 doses of vaccine was significantly shorter than that of patients receiving 1 dose of vaccine or none (P<0.05). There was a positive correlation between patient age and viral shedding time, with an R2=0.029 (P<0.001). Kaplan-Meier curve showed that there existed significant difference in viral shedding time between the patients with different vaccination doses (P<0.001), and patients with age >=70, hypertension and diabetes were all associated with prolonged viral shedding time (P<0.05). Cox regression analysis showed that the age >=70 years was a risk factor for prolonged viral shedding time, and 2 or 3 doses of vaccine was a protective factor for prolonged viral shedding time (P<0.05). Conclusions Among the elderly population, the viral shedding time would gradually increase with age. Patients who received >=2 doses of vaccine would have reduced viral shedding time compared with those who received <2 doses of vaccine.Copyright © 2022 Authors. All rights reserved.
ABSTRACT
Community is directly responsible for implementing the policy measures against public emergencies such as extreme weather, earthquake, flash flood and pandemic diseases. Summarizing the experience at the urban community level can help promote the global emergency management. This paper, from the perspective of COVID-19 prevention and control, selects three communities with different features to explore an effective response system for public emergency management at the urban community level. It demonstrates that based on a centralized leadership, the multi-level governance (MLG) network combined with information technology has mobilized their participation in combating COVID-19 and ensured the effective and timely response to the public emergencies, which blocked the spread of epidemic to the greatest extent, proving worthy of being promoted as one of the Chinese approaches and Chinese wisdom. © Chinese Journal of Urban and Environmental Studies. All rights reserved.
ABSTRACT
Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. "Contact tracing " is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COVID-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules-1) case maps;2) exposure detection;3) screening;and 4) health indicators that take multiple inputs like users' self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users' risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the Web-based information on confirmed COVID-19 cases and screening tools, which potentially increases the adoption rate of the system.
ABSTRACT
Objective To analyze the potential factors influencing the viral shedding time (duration of nucleic acid positivity) in elderly patients with mild and asymptomatic infection. Methods The clinical data of 1141 elderly (>=60 years) patients with mild and asymptomatic Omicron infection who were admitted to National Exhibition and Convention Center (Shanghai) Cabin Hospital from April 14, 2022 to May 1, 2022 were retrospectively collected, viral shedding time of patients were compared between different groups (age, gender, number of vaccination, hypertension, diabetes). Pearson analysis was adopted to analyze the relationship between age and viral shedding time. Kaplan-Meier curve and Log-rank test were used to evaluate the viral shedding time in elderly patients with different clinical characteristics. Multivariate Cox proportional-hazards regression model was adopted to analyze the factors influencing viral shedding time in elderly patients with Omicron. Results Among 1441 patients, 791(54.9%) males and 650(45.1%) females. There were 513(35.6%) patients receiving 0 dose of vaccine, 29(2.0%) patients received 1 dose of vaccine, 405(28.1%) patients received 2 doses of vaccine, 494(34.3%) patients received 3 doses of vaccine. Compared with patients aged 60 to 70 years, patients aged 70 to 80 years had longer viral shedding time (P<0.001). The viral shedding time in patients with hypertension and diabetes was longer than that in patients without hypertension and diabetes (P<0.05). In terms of vaccination, the viral shedding time of patients receiving 2 or 3 doses of vaccine was significantly shorter than that of patients receiving 1 dose of vaccine or none (P<0.05). There was a positive correlation between patient age and viral shedding time, with an R2=0.029 (P<0.001). Kaplan-Meier curve showed that there existed significant difference in viral shedding time between the patients with different vaccination doses (P<0.001), and patients with age >=70, hypertension and diabetes were all associated with prolonged viral shedding time (P<0.05). Cox regression analysis showed that the age >=70 years was a risk factor for prolonged viral shedding time, and 2 or 3 doses of vaccine was a protective factor for prolonged viral shedding time (P<0.05). Conclusions Among the elderly population, the viral shedding time would gradually increase with age. Patients who received >=2 doses of vaccine would have reduced viral shedding time compared with those who received <2 doses of vaccine. Copyright © 2022 Authors. All rights reserved.
ABSTRACT
Background The transmission speed and concealment of the Omicron variant of SARS-CoV-2 have been enhanced. The awareness level and skills of correctly donning and doffing personal protective equipment （PPE） in SARS-CoV-2 containment workers from the mobile cabin hospital are associated with their own health status, and the overall quality of COVID-19 pandemic control. Objective To understand the awareness and skills of correctly donning and doffing PPE in SARS-CoV-2 containment workers from a mobile cabin hospital. Methods By use of cluster sampling, 460 SARS-CoV-2 containment workers were selected from the Fourth Branch of Shanghai Mobile Cabin Hospital located in the National Exhibition and Convention Center （Shanghai）, from April 10 to May 10, 2022. Their awareness and skills of correctly donning and doffing PPE were assessed using an online survey with a self-developed questionnaire named Awareness of Correctly Donning and Doffing Personal Protective Equipment, and using an onsite performance assessment with a self-developed questionnaire named Skills of Correctly Donning and Doffing Personal Protective Equipment, respectively. Results The survey obtained a response rate of 83.5% （384/460）. According to the survey, both doctors and nurses had significantly higher average scores with regards to the operations at the first donning area, second donning area, front doffing area and first doffing area, second doffing area, and hand hygiene disinfection than public security officers and fire fighters（P<0.05）. All of the 460 cases completed the onsite performance assessment. Both doctors and nurses obtained lower average scores in terms of completing the operations at the first donning area, and donning steps in clean area into contaminated area than public security officers and fire fighters （P<0.05）. Doctors had much lower average score for completing the operations at the first donning area than nurses （P<0.05）. Conclusion There were significant differences in the levels of awareness and skills of correctly donning and doffing PPE in SARS-CoV-2 containment workers by occupation. Targeted and focused trainings and supervisions should be carried out to improve the mismatching between the levels of awareness and skills. © 2022 Chinese General Practice. All rights reserved.
ABSTRACT
Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. ’Contact tracing’is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COIVD-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules -Case Maps, Exposure Detection, Screening, and Health Indicators that takes multiple inputs like users’self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users’risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the web-based information on confirmed Covid-19 cases and screening tools, which potentially increases the adoption rate of the system. IEEE
ABSTRACT
Purpose: The purpose of this paper is to contribute to the literature of blended learning by practically implementing best practices in employee training. Design/methodology/approach: In response to the Covid-19 pandemic, an organization had modified its training procedures over the course of three years to improve employee and organizational outcomes. Employee candidates who were onboarded into sales positions during the years 2019–2021 were given the opportunity to learn the content in an online format and subsequently evaluated prior to their in-person training and final evaluation to provide them with a self-paced blended learning experience. Both evaluation scores, along with the length it took to complete the trainings, were used to determine the trainings effectiveness and efficiency respectively. Findings: The findings for the study showed that the organization was successfully able to improve upon the efficiency of the training by reducing training length and the effectiveness by improving employee outcomes. Research limitations/implications: The study’s design was limited to the probation process, which resulted in issues drawing conclusions for employee outcomes that were relevant to their long-term organizational success. This emphasizes the importance of comprehensive investigations for future practical studies. Practical implications: The findings allow for the improvement of blended learning models within real-world organizational contexts that provide organizations with the opportunity to improve employee outcomes while reducing time costs. Originality/value: This study provides data from applied blended learning procedures that were validated using empirical findings, which contributes to the practicality of blended learning in workplace training. © 2022, Emerald Publishing Limited.
ABSTRACT
In recent years, Corona Virus Disease 2019 (COVID-19), as a highly contagious disease worldwide, poses a serious threat to public health. It is necessary to scientifically predict the development of the epidemic and to study and judge the situation of the epidemic. Based on the Susceptible-Exposed-Infectious-Recovered (SEIR) model, this paper divides the population according to infectivity and considers the impact of double groups on the spread of the new coronavirus COVID-19. In the propagation model, important factors such as the incubation period, average healing days, and recovery rate are introduced, and its stability is analyzed and simulated. In the end, the experimental results prove that the model is stable and can achieve the desired expected effect. The research results provide a theoretical basis for the accurate simulation of the spread of the epidemic in the population, and have important research value and practical significance for improving the prevention and control strategy of the epidemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Background: The challenges that viral pneumonia poses to the global public health system remain daunting. In this study, an analysis of publications on viral pneumonia over the past two decades was conducted. Through this work, we hope to provide inspiration for future research on viral pneumonia. Methods: We extracted all of the English publications relevant to viral pneumonia published during 1999-2019 from Web of Science. GraphPad Prism, CiteSpace, and VOSviewer were used to collect and analyze the publication trends in related fields. Results: We identified 2,006 publications with 62,155 citations as of February 16, 2021. The United States accounted for the largest number of publications (34.2%), with the highest number of citations (27,616) and the highest h-index (78). China ranked second in the number of publications. Ctr Dis Control & Prevent proved to be the center of research cooperation. Clinical Infectious Diseases included the most papers published relating to the topic of viral pneumonia. Chan KH published the most papers in this field (25), while an article from Fouchier RAM presented the highest citation frequency (1,275). Conclusions: According to the bibliometric analysis database and related software results, the United States dominates the field of viral pneumonia research. The key term extracted by VOS-viewer has shifted to "Diagnosis and management", indicating a new trend for viral pneumonia research.
ABSTRACT
Objective To screen the potential biomarkers for the diagnosis and differential diagnosis of immune-mediated demyelinating diseases by tandem mass tags (TMT) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology. Methods Twenty patients with demyelinating diseases (demyelinating group) and 10 patients with noninflammatory neurological diseases (NND group) from Beijing Tiantan Hospital affiliated to Capital Medical University from January 2020 to January 2021 were enrolled in this study. The demyelinating group included 10 patients with Guillain-Barre syndrome (GBS subgroup) and 10 patients with multiple sclerosis (MS subgroup). TMT proteomics was used to screen out the different protein expression patterns between the demyelinating group and the NND group and between the GBS subgroup and the MS subgroup (difference>2 or<0.5 and with statistical significance), and String database was used to perform gene ontology (GO) analysis and Kyoto encyclopedia of gene and genomes (KEGG) analysis on the pathways involved in the differently expressed proteins between the groups. In addition, 80 demyelinating patients (demyelinating diseases validation group) and 40 healthy subjects (healthy control group) were selected for retrospective analysis of general lipid indexes. The demyelinating diseases validation group included 40 GBS patients (GBS validation group) and 40 MS patients (MS validation group). Receiver operating characteristic (ROC) curve was obtained to evaluate the value of general lipid indexes for the diagnosis of demyelinating diseases and the differential diagnosis between GBS and MS groups. Results A total of 362 proteins were detected by TMT proteomics. There were 101 differentially expressed proteins between the demyelinating group and the NND group, and 45 differentially expressed proteins between the GBS group and the MS group. Compared with the NND group, GO enrichment analysis showed that the top five enrichment pathways in the demyelinating group were macrophage colony stimulating factor and receptor complex, negative regulation of cholesterol input, negative regulation of very low density lipoprotein particle clearance, triglyceride-rich lipoprotein particle remodeling, and cholesterol reverse transport. Compared with MS group, the top five enriched pathways in GBS group were high-density lipoprotein particle receptor binding, negative regulation of very low density lipoprotein particle remodeling, negative regulation of cholesterol input, negative regulation of very low density lipoprotein particle clearance, and medium density lipoprotein particle. KEGG enrichment analysis results showed that differentially expressed proteins in the demyelinating group and the NND group were enriched in 8 pathways, including phosphatidylinositide 3-kinases-protein kinase B signaling pathway, complement and coagulation cascade reaction, extracellular matrix and its receptor interaction, Staphylococcus aureus infection, cholesterol metabolism, RAS signaling pathway, phagosome, and mitogen-activated protein kinase signaling pathway. Differentially expressed proteins in GBS group and MS group were enriched in 9 pathways: cholesterol metabolism, complement and coagulation cascade, platelet activation, peroxisome proliferators-activated receptors signaling pathway, vitamin digestion and absorption, novel coronavirus infection, fat digestion and absorption, axon guidance, and neutrophil extracellular trap formation pathway. The levels of triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apoB) were significantly higher, while high density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (apoA1) levels were significantly lower in the demyelinating disease validation group than in the healthy control group (all P<0.05 or 0.01). Area under the curve (AUC) of TG, TC, HDL-C, LDL-C, apoA1 and apoB alone or in combination for the diagnosis of immune-mediated demyelinating diseases was 0.746, 0.643, 0.798, 0.703, 0.806, 0.708 and 0.868, respectively. The AUC of HDL-C, apoA1, LDL-C and apoB for differential diagnosis between GBS and MS was 0.692, 0.653, 0.632, 0.695 and 0.718, respectively. Conclusions There are differences in cerebrospinal fluid proteomics between patients with immune-mediated demyelinating disease and patients with NND, GBS and MS, and the differentially expressed protein patterns mainly exist in the pathways related to lipid metabolism. Lipid related indicators may be used as biomarkers for the diagnosis and differential diagnosis of immune-mediated demyelinating disease. © 2022 Chinese Medical Journals Publishing House Co.Ltd. All rights reserved.
Subject(s)
Coronavirus Infections/therapy , Coronavirus Infections/transmission , Coronavirus/isolation & purification , Oxygen/therapeutic use , Pneumonia, Viral/therapy , Betacoronavirus , COVID-19 , Coronavirus Infections/diagnosis , Humans , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , SARS-CoV-2ABSTRACT
The outbreak of the global COVID-19 pandemic emphasizes the importance of collaborative drug discovery for high effectiveness;however, due to the stringent data regulation, data privacy becomes an imminent issue needing to be addressed to enable collaborative drug discovery. In addition to the data privacy issue, the efficiency of drug discovery is another key objective since infectious diseases spread exponentially and effectively conducting drug discovery could save lives. Advanced Artificial Intelligence (AI) techniques are promising to solve these problems: (1) Federated Learning (FL) is born to keep data privacy while learning data from distributed clients;(2) graph neural network (GNN) can extract structural properties of molecules whose underlying architecture is the connected atoms;and (3) generative adversarial network (GAN) can generate novel molecules while retaining the properties learned from the training data. In this work, we make the first attempt to build a holistic collaborative and privacy-preserving FL framework, namely FL-DISCO, which integrates GAN and GNN to generate molecular graphs. Experimental results demonstrate the effectiveness of FL-DISCO on: (1) IID data for ESOL and QM9, where FL-DISCO can generate highly novel compounds with high drug-likeliness, uniqueness and LogP scores compared to the baseline;(2) non-IID data for ESOL and QM9, where FL-DISCO generates 100% novel compounds with high validity and LogP scores compared to the baseline. We also demonstrate how different fractions of clients, generator and discriminator architectures affect our evaluation scores.
ABSTRACT
This paper studies static and dynamic connectedness among carbon, traditional (oil and coal)/new energy and material (iron, aluminum, cement, and plastic) markets based on the Diebold Yilmaz (2012) method and the Barunik and Krehlik (2018) method. First, total connectedness is larger in the short term and enhanced after the COVID-19 outbreak. Second, material markets exhibit higher explanatory power;plastic prices, for example, have played a leading role during the pandemic crisis according to the networks. Third, the spillover of China's carbon markets post-outbreak is about twice as large as pre-outbreak, showing positive net connectedness in the medium and long term. Carbon markets' spillover is relatively small and mainly contributes to new energy. Finally, time-varying analysis demonstrate that the positive and negative values of time-varying connectedness peak due to economic shocks or global emergencies. High connectedness with longer duration may be caused by a sudden emergency rather than anticipated events. These findings can offer significant benefits to policymakers, high-carbon businesses and investors in crafting appropriate strategies with heterogeneous frequency horizons. © 2022 Elsevier Ltd
ABSTRACT
China has made remarkable progress in reducing tuberculosis cases and deaths during the past three decades;however, it is still far from achieving the targets set out in the WHO End TB Strategy Since the 2000s, China has tried to transform its vertical tuberculosis control programme led by the Chinese Center for Disease Control and Prevention (CDC) into an integrated system under the collaboration of CDC, tuberculosis-designated hospitals, and primary health centres. Such a transition has faced many challenges. Profit-driven practices in hospitals designated to tuberculosis and an absence of adequate tuberculosis-related training for health professionals are partially jeopardising the quality of tuberculosis care. In addition, primary health-care providers are not incentivised to make referrals and manage cases effectively. The CDC does not have the administrative power to influence hospital practices or deploy resources to support community-based tuberculosis control activities. Furthermore, an absence of policy coherence and effective coordination causes challenges for quality tuberculosis care that is affordable and accessible. Improving policy dialogues and multi-level coordination within the government is fundamental to successfully ending tuberculosis in China and other countries facing similar challenges.