Oil price shocks, economic policy uncertainty, and green finance: a case of China

This study investigates the long- and short-run effects of crude oil price (COP) and economic policy uncertainty (EPU) on China's green bond index (GBI) using the quantile autoregressive distributed lag model. The empirical results show that COP and EPU produce a significant positive and negative influence on GBI in the long-run across most quantiles, respectively, but their short-run counterparts are opposite direction and only significant in higher quantiles. Thus, major contributions are made accordingly and shown in the following aspects. The findings emphasise the importance of understanding how COP and EPU affect China's green bond market for the first time. In addition, both the long- and short-run effects are captured, but long-run shocks primarily drive the green bond market. Finally, time- and quantile-varying analyses are adopted to explain the nexus between COP and EPU to GBI, which considers not only different states of the bond market but also events that occur in different time periods. Some detailed policies, such as a unified and effective green bond market, an early warning mechanism of oil price fluctuation, and prudent economic policy adjustments, are beneficial for stabilising the green finance market.

Continuous Wavelet Transform of Time-Frequency Analysis Technique to Capture the Dynamic Hedging Ability of Precious Metals

Exploring the hedging ability of precious metals through a novel perspective is crucial for better investment. This investigation applies the wavelet technique to study the complicated correlation between global economic policy uncertainty (GEPU) and the prices of precious metals. The empirical outcomes suggest that GEPU exerts positive influences on the prices of precious metals, indicating that precious metals could hedge against global economic policy uncertainty, which is supported by the inter-temporal capital asset pricing model (ICAPM). Among them, gold is better for long-term investment than silver, which is more suitable for the short run in recent years, while platinum's hedging ability is virtually non-existent after the global trade wars. Conversely, the positive influences from gold price on GEPU underline that the gold market plays a prospective role in the situation of economic policies worldwide, which does not exist in the silver market. Besides, the effects of platinum price on GEPU change from positive to negative, suggesting that the underlying cause of its forward-looking effect on GEPU alters from the investment value to the industrial one. In the context of the increasing instability of global economic policies, the above conclusions could offer significant lessons to both investors and governments.

Identification and analyses of the proteins interacting with the nucleocapsid protein of the Porcine Deltacoronavirus

Preliminary screening and identification of the host proteins interacting with the nucleocapsid(N)protein of the porcine deltacoronavirus(DCoV). Co-immunoprecipitation and liquid chromatography- tandem mass spectrometry were used to screen out the host proteins interacting with the N protein of the porcine DCoV. Bioinformatics analysis was carried out, and then co-immunoprecipitation was used for identification. Sodium dodecyl sulfate - polyacrylamide gel electrophoresis of the immunoprecipitation products revealed different protein bands around 40 kDa and 100 kDa. Sixty-eight host proteins interacting with the N protein of the porcine DCoV were screened by mass spectrometry. Two candidate interacting proteins(ANXA2 and TUBB2 B)were selected by analyses using the Gene Ontology, Clusters of Orthologous Groups, and Kyoto Encyclopedia of Genes and Genomes databases. After co-immunoprecipitation verification, the N protein of the porcine DCoV was found to interact with TUBB2 B. Our study provides a new direction for further exploration of the role of the N protein of the porcine DCoV in infection.

Steroids Therapy in Patients With Severe COVID-19: Association With Decreasing of Pneumonia Fibrotic Tissue Volume

Background We use longitudinal chest CT images to explore the effect of steroids therapy in COVID-19 pneumonia which caused pulmonary lesion progression. Materials and Methods We retrospectively enrolled 78 patients with severe to critical COVID-19 pneumonia, among which 25 patients (32.1%) who received steroid therapy. Patients were further divided into two groups with severe and significant-severe illness based on clinical symptoms. Serial longitudinal chest CT scans were performed for each patient. Lung tissue was segmented into the five lung lobes and mapped into the five pulmonary tissue type categories based on Hounsfield unit value. The volume changes of normal tissue and pneumonia fibrotic tissue in the entire lung and each five lung lobes were the primary outcomes. In addition, this study calculated the changing percentage of tissue volume relative to baseline value to directly demonstrate the disease progress. Results Steroid therapy was associated with the decrease of pneumonia fibrotic tissue (PFT) volume proportion. For example, after four CT cycles of treatment, the volume reduction percentage of PFT in the entire lung was −59.79[±12.4]% for the steroid-treated patients with severe illness, and its p-value was 0.000 compared to that (−27.54[±85.81]%) in non-steroid-treated ones. However, for the patient with a significant-severe illness, PFT reduction in steroid-treated patients was −41.92[±52.26]%, showing a 0.275 p-value compared to −37.18[±76.49]% in non-steroid-treated ones. The PFT evolution analysis in different lung lobes indicated consistent findings as well. Conclusion Steroid therapy showed a positive effect on the COVID-19 recovery, and its effect was related to the disease severity.

Establishing a blockchain online travel agency with a human–computer interaction perspective

Purpose>This study aims to incorporate innovative technology (i.e. blockchain) into the design of an online travel agency (B-OTA). The authors accelerated the design of the prototype system through expert interviews to understand the convenience of the blockchain travel and accommodation platform for users. The authors further validated the prototype system design and improved reference capability through usability testing.Design/methodology/approach>Rapid prototyping of B-OTA was carried out through the Delphi method and literature compilation. Design validation of usability testing was conducted using modified systematic evaluation methodology. Prototype system suggestions and improvements were collected through feedback from test subjects.Findings>This study will be helpful for the development of B-OTAs and related technologies. Through usability testing, the authors verified that creating a familiar operating environment for users can reduce users’ fear of unfamiliar technology. The results of this research provide future B-OTA researchers and practitioners with design guidelines.Originality/value>Beyond the blockchain-related technologies used, few studies have reported experiences and interface design of B-OTAs. This study states that, as many human–computer interaction-related papers have pointed out, the basic prerequisite for successful interface design is a clearer definition of users’ needs during operation. User experience and user interface design should provide a good user experience.

Immunogenicity and safety of the CoronaVac inactivated SARS-CoV-2 vaccine in people with underlying medical conditions in China: a retrospective study (preprint)

People living with chronic disease, particularly seniors older than 60 years old, are lagging behind in the national COVID-19 vaccination campaign in China due to the uncertainty of vaccine safety and effectiveness. However, this special population made up of most severe symptom and death cases among SARS-CoV-2 infected patients and should be prioritized in vaccination program. Thus, safety and immunogenicity data of COVID-19 vaccines in people with underlying medical conditions are needed to address the vaccine hesitancy in this special population. Here, we report a retrospective cohort study evaluating the immunogenicity and safety of the inactivated COVID-19 vaccine, CoronaVac, in people with at least one of the six common diseases, focusing on seniors (N = 969). We found that CoronaVac is as safe in people with chronic diseases as that in healthy control, without serious adverse event reported in this study. By day 14-28 post vaccination, we observed no significant difference for the antibody responses between disease groups and healthy control, except for the coronary artery disease (p=0.03) and chronic respiratory disease group (p=0.04) showing moderate reduction. Such difference diminished by day 90 and 180, as neutralizing antibodies significantly reduced in all participants. Most people showed detectable SARS-CoV-2-specific T cell response at day 90 and day 180 without significant difference between disease groups and healthy control. Overall, our results highlight the comparable safety, immunogenicity and cellular immunity memory of CoronaVac in seniors and people living with chronic diseases, addressing vaccine hesitancy for this special population.

Immunogenicity and safety of the CoronaVac inactivated SARS-CoV-2 vaccine in people with underlying medical conditions: a retrospective study (preprint)

Background: People living with chronic disease, particularly seniors older than 60 years old, are lagging behind in the national vaccination campaign in China due to uncertainty of safety and effectiveness. However, this special population made up of most severe symptom and death cases among infected patients and should be prioritized in vaccination program. In this retrospective study, we assessed the safety and immunogenicity of the CoronaVac inactivated vaccines in people with underlying medical conditions to address the vaccine hesitation in this special population. Methods: In this cohort study, volunteers aged 40 years and older, had received two doses of CoronaVac inactivated vaccines (3-5 weeks interval), been healthy or with at least one of the six diseases: coronary heart disease (CAD), hypertension, diabetes mellitus (DM), chronic respiratory disease (CRD), obesity and cancer, were recruited from 4 study sites in China. The primary safety outcome was the incidence of adverse events within 14 days after each dose of vaccination. The primary immunogenic outcome was geometric mean titer (GMT) of neutralizing antibodies to living SARS-CoV-2 virus at 14-28 days, 3 months, and 6 months after full two-dose vaccination. This study is registered with ChiCTR.org.cn (ChiCTR2200058281) and is active but no longer recruiting. Findings: Among 1,302 volunteers screened between Jul 5 and Dec 30, 2021, 969 were eligible and enrolled in our cohort, including 740 living with underlying medical conditions and 229 as healthy control. All of them formed the safety cohort. The overall incidence of adverse reactions was 150 (20.27%) of 740 in the comorbidities group versus 32 (13.97%) of 229 in the healthy group, with significant difference (P=0.0334). The difference was mainly contributed by fatigue and injection-site pain in some groups. Most adverse reactions were mild (Grade 1). We did not observe any serious adverse events related to vaccination. By day 14-28 post vaccination, the seroconversion rates and GMT of neutralizing antibody showed no significant difference between disease group and healthy group, except CAD group (P=0.03) and CRD group (P=0.04) showed slight reduction. By day 90, the neutralizing antibody GMTs were significantly reduced in each group, with no significant difference between diseases and healthy group. By day 180, the neutralizing antibody continued to decrease in each group, but with slower declination. Interpretation: For people living with chronic disease especially seniors older than 60 years, the CoronaVac vaccines are as safe as in healthy people. Although the immunogenicity is slightly different in subgroup of some diseases compared with that of the healthy population, the overall trend was consistent. Our findings highlight the evidence to address vaccine hesitancy for seniors and people living with chronic diseases. Funding: Yunnan Provincial Science and Technology Department (202102AA100051 and 202003AC100010, China), Sinovac Biotech Ltd (PRO-nCOV-4004).

Occurrence of relative bradycardia and relative tachycardia in individuals diagnosed with COVID-19 (preprint)

Background: The COVID-19 disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) has become one of the worst global pandemics of the century causing tremendous human and economic suffering worldwide. While considered a respiratory disease, COVID-19 is known to cause cardiac complications. Wearable devices are well equipped to measure heart rate continuously and their popularity makes them valuable devices in the field of digital health. In this article, we use Fitbit devices to examine resting heart rate from individuals diagnosed with COVID-19. Methods: The Fitbit COVID-19 survey was conducted from May 2020 - June 2021. We collected resting heart rate data from 7,200 individuals (6,606 symptomatic, 594 asymptomatic) diagnosed with COVID- 19 between March 2020 - December 2020, as well as from 463 individuals diagnosed with influenza between January 2020 - December 2020. Data from healthy individuals served as a control, in order to model the seasonal variation. We also computed heart rate variability and respiratory rate data for symptomatic COVID-19. Findings: Resting Heart Rate is elevated during COVID-19 symptom onset, with average peak increases relative to the baseline of 1.8%+/-0.1% (3.4%+/-0.2%) for females (males), where the quoted numbers are mean and standard error of the mean. After the initial peak, the resting heart rate decreased and reached a minimum on average ~ 13 days after symptom onset. The minimum value relative to the baseline is more negative for females (-1.75% +/- 0.1%) compared to males (0.08% +/- 0.2%). The resting heart rate then increased, reaching a second peak on average ~ 28 days from symptom onset, before falling back to the baseline ~ 112 days from symptom onset. All estimates vary with disease severity. Interpretation: The resting heart rate is modified for several months following a COVID-19 diagnosis. Interestingly, this effect is seen with seasonal influenza also, although the bradycardia minimum and the second tachycardia peak are often more pronounced in the case of symptomatic COVID-19. By computing resting heart rate daily, wearable devices can contribute to monitoring wellness during recovery from COVID-19, and seasonal influenza. Funding: A.N., H.-W.S., and C.H. are supported by Fitbit Research, Google LLC.

Measurement of Respiratory Rate using Wearable Devices and Applications to COVID-19 Detection (preprint)

We show that heart rate enabled wearable devices can be used to measure respiratory rate. Respiration modulates the heart rate creating excess power in the heart rate variability at a frequency equal to the respiratory rate, a phenomenon known as respiratory sinus arrhythmia. We isolate this component from the power spectral density of the heart beat interval time series, and show that the respiratory rate thus estimated is in good agreement with a validation dataset acquired from sleep studies (root mean squared error = 0.648 per minute, mean absolute percentage error = 3%). Using the same respiratory rate algorithm, we investigate population level characteristics by computing the respiratory rate from 10,000 individuals over a 14 day period, with equal number of males and females ranging in age from 20 - 69 years. 90% of respiratory rate values for healthy adults fall within the range 11.8 per minute to 19.2 per minute with a mean value of 15.4 per minute. Respiratory rate is shown to increase with nocturnal heart rate. It also varies with BMI, reaching a minimum at 25 kg/m^2, and increasing for lower and higher BMI. The respiratory rate decreases slightly with age and is higher in females compared to males for age < 50 years, with no difference between females and males thereafter. The 90% range for the coecient of variation in a 14 day period for females (males) varies from 2.3% - 9.2% (2.3% - 9.5%) for ages 20 - 24 yr, to 2.5% - 16.8% (2.7% - 21.7%) for ages 65 - 69 yr. We show that respiratory rate is often elevated in subjects diagnosed with COVID-19. In a 7 day window centered on the date when symptoms present (or the test date for asymptomatic cases), we find that 33% (18%) of symptomatic (asymptomatic) individuals had at least one measurement of respiratory rate 3 per minute higher than the regular rate.

Assessment of physiological signs associated with COVID-19 measured using wearable devices (preprint)

Respiration rate, heart rate, and heart rate variability are some health metrics that are easily measured by consumer devices and which can potentially provide early signs of illness. Furthermore, mobile applications which accompany wearable devices can be used to collect relevant self-reported symptoms and demographic data. This makes consumer devices a valuable tool in the fight against the COVID-19 pandemic. We considered two approaches to assessing COVID-19 - a symptom-based approach, and a physiological signs based technique. Firstly, we trained a Logistic Regression classifier to predict the need for hospitalization of COVID-19 patients given the symptoms experienced, age, sex, and BMI. Secondly, we trained a neural network classifier to predict whether a person is sick on any specific day given respiration rate, heart rate, and heart rate variability data for that day and and for the four preceding days. Data on 1,181 subjects diagnosed with COVID-19 (active infection, PCR test) were collected from May 21 - July 14, 2020. 11.0% of COVID-19 subjects were asymptomatic, 47.2% of subjects recovered at home by themselves, 33.2% recovered at home with the help of someone else, 8.16% of subjects required hospitalization without ventilation support, and 0.448% required ventilation. Fever was present in 54.8% of subjects. Based on self-reported symptoms alone, we obtained an AUC of 0.77 +/- 0.05 for the prediction of the need for hospitalization. Based on physiological signs, we obtained an AUC of 0.77 +/- 0.03 for the prediction of illness on a specific day with 4 previous days of history. Respiration rate and heart rate are typically elevated by illness, while heart rate variability is decreased. Measuring these metrics can help in early diagnosis, and in monitoring the progress of the disease.