Associations of habitual glucosamine use with SARS-CoV-2 infection and hospital admission and death with COVID-19: Evidence from a large population based cohort study.

The coronavirus disease 2019 (COVID-19) pandemic has led to a fundamental number of morbidity and mortality worldwide. Glucosamine was indicated to help prevent and control RNA virus infection preclinically, while its potential therapeutic effects on COVID-19-related outcomes are largely unknown. To assess the association of habitual glucosamine use with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, hospital admission, and mortality with COVID-19 in a large population based cohort. Participants from UK Biobank were reinvited between June and September 2021 to have SARS-CoV-2 antibody testing. The associations between glucosamine use and the risk of SARS-CoV-2 infection were estimated by logistic regression. Hazard ratios (HRs) and 95% confidence intervals (CIs) for COVID-19-related outcomes were calculated using COX proportional hazards model. Furthermore, we carried out propensity-score matching (PSM) and stratified analyses. At baseline, 42 673 (20.7%) of the 205 704 participants reported as habitual glucosamine users. During median follow-up of 1.67 years, there were 15 299 cases of SARS-CoV-2 infection, 4214 cases of COVID-19 hospital admission, and 1141 cases of COVID-19 mortality. The fully adjusted odds ratio of SARS-CoV-2 infection with glucosamine use was 0.96 (95% CI: 0.92-1.01). The fully adjusted HR were 0.80 (95% CI: 0.74-0.87) for hospital admission, and 0.81 (95% CI: 0.69-0.95) for mortality. The logistic regression and Cox proportional hazard analyses after PSM yielded consistent results. Our study demonstrated that habitual glucosamine use is associated with reduced risks of hospital admission and death with COVID-19, but not the incidence of SARS-CoV-2 infection.

A technology-enhanced scaffolding instructional design for fully online courses

The COVID-19 pandemic has forced teachers to implement fully online teaching. This study reviewed the popular technologies that are used in online learning, as well as the advantages and difficulties of applying fully online courses for formal education. Based on this research background, this study proposed a nested scaffolding design of an online course for 215 college students in China with the help of six technological tools, which effectively replaced face-to-face interactions and significantly improved the usage of the supporting learning platform. The inner-outer learning cycles supported by the technological tools improved the quality of the scaffolding conversations, reduced the scaffolding time cost that teachers had to expend and enhanced the effectiveness of the individualised scaffolding instructions.

Supply Chain Resilience of Mineral Resources Industry in China

Improving the supply chain resilience of the mineral resources industry is crucial for ensuring national economic security in China. Based on the supply and demand data of China's mineral resources industry from 2002 to 2018, this study adopts system dynamics model to simulate the supply chain resilience of the mineral resources industry, the mining industry, and the smelting and processing industry under the scenario of steady economic development and the scenario of supply chain crisis. From the simulation results, the reserves of the mineral resources industry and the smelting and processing industry under the two scenarios are nearly the same, indicating that they are weakly affected by the foreign market, and both have strong resilience. The mining industry has a high dependence on imports and a lack of supply chain resilience. Under the condition of steady economic development, the output of the mining industry needs to develop at a low speed to reduce production capacity. More attention should be paid to the high level of import dependence and insufficient supply chain resilience of the mining industry. In the stable international trade situation, reserves of important minerals should be increased to alleviate the resource shortage during the supply chain crisis.

Emerging trends and hot spots in subacute thyroiditis research from 2001 to 2022: A bibliometric analysis.

Background: Subacute thyroiditis (SAT) is the most prevalent self-limiting thyroid disease that causes pain, accounting for about 5% of all clinical thyroid disorders. Numerous clinically noteworthy results have been published in this area over the last 20 years. However, no article has comprehensively assessed the relevant literature yet. We conducted a bibliometric analysis of SAT to provide light on the dynamic nature of scientific advancement and aid researchers in gaining a global perspective while examining research core themes and hotspots. Methods: SAT-related articles and reviews from 2001 to 2022 were retrieved from the Science Citation Index-Expanded of Web of Science Core Collection (WoSCC). We analyzed current research trends and hotspots in this area using CiteSpace and Vosviewer. Results: A total of 568 studies associated with SAT research were published in 282 academic journals by 2,473 authors in 900 institutions from 61 countries/regions. The United States was a crucial link in inter-country/region collaboration and was the most frequently involved country in international cooperation. The University of Missouri System was the top organization, and Braley-Mullen H. was the most productive researcher. Thyroid published the most papers, with 36 publications. The most co-cited article was "Clinical features and outcome of subacute thyroiditis in an incidence cohort: Olmsted County, Minnesota, study" (by Fatourechi V., 2003). The clustered network and timeline view of keywords showed that the prevalence, diagnosis, and treatment of SAT were the research core themes during the past 20 years. Analysis of keyword bursts indicated that the clinical characteristic and the influence of COVID-19 on SAT appeared to be the current research hotspots. Conclusion: This bibliometric analysis conducted a thorough review of the SAT research. The clinical characteristics and the genetic background of SAT under the influence of COVID-19 are current research hotspots. However, there is still a need for further study and global collaboration. Our findings can aid researchers in understanding the current status of SAT research and immediately pinpoint new directions for further investigation.

How to achieve carbon neutrality while maintaining economic vitality: An exploration from the perspective of technological innovation and trade openness.

The significant drop in global carbon emissions in 2020 was credited to the enormous loss of economic activity from the impact of COVID-19. The challenge is now to reduce carbon emissions without causing massive disruption and damage to economic production. To achieve carbon neutrality while maintaining economic vitality, the impact of technological innovation and trade openness must be considered. This paper sets technological innovation and trade openness as core variables and establishes two extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) models. The first model focuses on carbon emissions and the second focuses on economic growth. Comparisons were made between the BRICS (i.e., Brazil, Russia, India, China, and South Africa) and G7 (i.e., Canada, France, Germany, Italy, Japan, the UK, and the USA) countries. The fully modified ordinary least squares (FMOLS) regression analysis was used to explore the impact of technological innovation and trade openness on low-carbon economic development. A Panel Granger Causality Test explores the causal relationship between the core, control and dependent variables. The results illustrate that: (1) technological innovation is the primary factor that inhibits carbon emissions and promotes economic growth in both international organizations, (2) trade openness promotes the growth of carbon emissions in BRICS countries, but restrains G7 growth, confirming the "Pollution Haven Hypothesis", (3) per capita GDP is the largest contributor to carbon emissions growth in both the G7 and BRICS countries, which illustrates that per capita GDP is the largest contributor to carbon emissions. It is proportional to G7 and BRICS carbon emissions. This paper provides several policy recommendations: breaking through basic research, adjusting the science and technology evaluation system, optimizing the export trade structure, and increasing the proportion of renewable energy.

Flexible Scheduling Model of Bus Services between Venues of the Beijing Winter Olympic Games

Traditional buses travel on fixed routes and areas, which cannot satisfy the flexible demands of athletes in the context of COVID-19 and the closed-loop traffic management policy during the 2022 Beijing Winter Olympic Games (BWOG). This study predicts the travel demands based on the characteristics of athletes' daily travel demands and then presents a flexible bus service scheduling model for cross-region scheduling among Beijing, Yanqing, and Zhangjiakou to provide high-level service. The flexible bus service is point-to-point and avoids unnecessary contact, which reduces the risk of spreading COVID-19 and ensures athletes' safety. In this study, the flexible bus scheduling model is established to optimize scheduling schemes, whose object is to minimize the cost of the system based on some realistic constraints. These constraints consider not only the preferred time windows of athletes' demand but also the vehicle's capacity, depot, minimum load factor, total demands, etc. In addition, a genetic-simulated annealing hybrid algorithm (GSAHA) is designed to solve the model based on the characteristics of the genetic algorithm (GA) and simulated annealing. To assess the feasibility and efficiency of the model and algorithm, a case study is conducted in the Beijing-Yanqing area. Furthermore, the travel time of the flexible bus is compared to that of the traditional bus, according to the results of the case study. Moreover, the sensitivity of the model and algorithm are analyzed. The experimental results show that the proposed model and algorithm can dispatch buses with superior flexibility and high-level services during the BWOG. [ FROM AUTHOR]

Cardiac involvement in patients recovering from Delta Variant of COVID-19: a prospective multi-parametric MRI study.

AIMS: The cardiac injury and sequelae of Delta Variant of coronavirus disease 2019 (COVID-19) remain unknown. This study aimed to evaluate the presence of cardiac involvement in patients recovering from Delta Variant of COVID-19 based on multi-parametric cardiac magnetic resonance imaging (MRI). METHODS AND RESULTS: We prospectively assessed patients recovering from Delta Variant of COVID-19 using multi-parametric cardiac magnetic resonance imaging (MRI) between June 2021 and July 2021. Comparison was made with 25 healthy controls. Forty-four patients (median age 51 years, 28 women) recovering from Delta Variant were recruited and had a median time of 35 days between diagnosis and cardiac MRI. There were no patients with chest pain (0/44, 0%) and high sensitivity cardiac troponin T troponin elevation (median levels 2.20 pg/mL, IQR levels 0.85-4.40 pg/mL). Regarding the cardiac imaging findings, a total of 14 (32%) patients presented cardiac tissue feature abnormalities, and a total of 9 (20%) patients had a myocarditis-like injury based on cardiac MRI 2018 Lake Louise criteria. When we further assessed the T1 and T2 mapping values for of patients' individual, abnormal raised global native T1, T2, and extracellular volume were seen in 6 (14%), 6 (14%), and 4 (9%) patients, respectively. Comparing with controls, the patients had lower LV global longitudinal strain and (-22.2 ± 2.8% vs. -24.6 ± 2.0%, P < 0.001) and global circumferential strain (-20.7 ± 6.8% vs. -24.3 ± 2.9%, P = 0.014), but higher global native T1 (1318.8 ± 55.5 ms vs. 1282.9 ± 38.1 ms, P = 0.006). Four (9%) patients presented myocardial late gadolinium enhancement with subepicardial pattern mostly common seen, and two (5%) patients presented pericardial enhancement. CONCLUSIONS: The cardiac MRI could detect subclinical functional and myocardial tissue characteristic abnormalities in individuals who were recovering from Delta Variant without cardiac-related clinical findings. The native T1 mapping and strain imaging may be a sensitive tool for the noninvasive detection of a subset of patients who are at risk for cardiac sequelae and more prone to myocardial damage in survivors with Delta Variant.

Investor's herding behavior in Asian equity markets during COVID-19 period

In this paper we investigate herding behavior triggered by the COVID-19 outbreak in 2020 by considering six typical Asian stock markets. Cross-sectional Standard Deviation (CSSD) and Cross-sectional Absolute Deviation (CSAD) have been employed as the key indicators, which are aligned with the Markov-switching regression and HS model to identify the presence and magnitude of herding. We then elaborate our study by examining herding in specific time slots and markets with different idiosyncratic volatility. Our empirical results show a clear presence of herding in the “Feb 2020-Jan 2021” time window and we have captured a sharp rise of the magnitude of herding during the market crash in March 2020, and found herding emerged in these markets with shocks and fierce fluctuations.

Health Communication in Games at the Early Stage of COVID-19 Epidemic: A Grounded Theory Study Based on Plague, Inc.

Objectives: An empirical study is carried out based on Plague, Inc. to explore whether the game has raised awareness of public health and urged players to make a better choice about health. Materials and Methods: Twenty-six college students from 24 cities in 11 provinces of China were investigated for a week-long survey. According to grounded theory principles, we coded original records from 69 diary reports using qualitative analysis tools. Results: We constructed nine core categories from participants' journals and drew the mechanism chart of the game as a means of health communication. The results showed that participants had experienced (1) an iterative learning process based on the authenticity and multiperspective features of the game and obtained specific learning outcomes; (2) deep thinking through the association between the game and the real world. And we extracted variables that are highly predictive of behavior change, including cognition of seriousness, cognition of susceptibility, action clue, and self-efficacy. Furthermore, noncore categories (including emotions and gameplay) directly and indirectly impacted players' learning and behavior change. Conclusion: The study shows Plague, Inc. has played a positive role in health communication (mainly reflected in the improvement of players' cognitive level, the establishment of health belief, and behavior changes). Moreover, it is concluded that reflection plays an important role in health communication interventions. However, careful consideration should be given to the use of this game as a means of health intervention due to its limitations and certain deficiencies.

Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover. [ABSTRACT FROM AUTHOR] Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mental health status and its influencing factors of college students in Anhui Province during the coronavirus disease 2019 pandemic

[Background] As a public health emergency, the coronavirus disease 2019 (COVID-19) pandemic has brought a certain impact on the public. [Objective] This study explores the mental health status of college students in Anhui Province during the COVID-19 pandemic and analyzes possible influencing factors. [Methods] On February 2020, 493 college students from two universities in Anhui Province completed the Self-Esteem Scale (SES), the Perceived Social Support Scale (PSSS), and the Symptom Checklist 90 (SCL-90). Independent samples t test and one-way analysis of variance were used to analyze the differences of college students' mental health scores by different sociodemographic characteristics. Independent samples t test was also used to analyze the differences in mental health status between the participants and the norms. Pearson correlation analysis was used to explore the relationships between mental health, self-esteem, and perceived social support. With the total score of SCL-90 as dependent variable and the scores of SES and PSSS as independent variables, a multiple linear stepwise regression analysis was established to explore the potential influencing factors of college students' mental health during the pandemic. [Results] Finally 472 (95.74%) valid questionnaires were returned. Of them 90 (19.07%) respondents were positive at the SCL-90 scale;the highest three dimensional positive rates were anxiety (34.75%), interpersonal sensitivity (24.36%), and obsessive-compulsive (23.73%), and the lowest rate was psychiatric disorders (13.77%). The overall SCL-90 score was 139.13±31.59, and the score of the college students who were the only child was lower than that of the college students who were not the only child (t=-2.098, P < 0.05). Compared with the norms, the total score of SCL-90 and the dimensional scores of interpersonal sensitivity, depression, anxiety, phobic anxiety, and psychiatric disorders of the participants were higher (P < 0.05). The students' self-esteem score was 25.35±4.92 and perceived social support score was 60.28±12.98. The total SCL-90 score was negatively correlated with the self-esteem score (r=-0.506, P < 0.01) and the perceived social support score (r=-0.482, P < 0.01). The multiple linear stepwise regression analysis results showed that self-esteem (b=-2.590, P < 0.001) and perceived social support (b=-0.903, P < 0.001) jointly explained 38.3% of the changes in total SCL-90 score. [Conclusion] During the COVID-19 pandemic, the overall mental health status of the college students is not good. Reasonable levels of self-esteem and perceived social support are helpful to improve their mental health.

Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2.

BACKGROUND: The pneumonia caused by the 2019 novel coronavirus (SARS-CoV-2, also called 2019-nCoV) recently break out in Wuhan, China, and was named as COVID-19. With the spread of the disease, similar cases have also been confirmed in other regions of China. We aimed to report the imaging and clinical characteristics of these patients infected with SARS-CoV-2 in Guangzhou, China. METHODS: All patients with laboratory-identified SARS-CoV-2 infection by real-time polymerase chain reaction (PCR) were collected between January 23, 2020, and February 4, 2020, in a designated hospital (Guangzhou Eighth People's Hospital). This analysis included 90 patients (39 men and 51 women; median age, 50 years (age range, 18-86 years). All the included SARS-CoV-2-infected patients underwent non-contrast enhanced chest computed tomography (CT). We analyzed the clinical characteristics of the patients, as well as the distribution characteristics, pattern, morphology, and accompanying manifestations of lung lesions. In addition, after 1-6 days (mean 3.5 days), follow-up chest CT images were evaluated to assess radiological evolution. FINDINGS: The majority of infected patients had a history of exposure in Wuhan or to infected patients and mostly presented with fever and cough. More than half of the patients presented bilateral, multifocal lung lesions, with peripheral distribution, and 53 (59%) patients had more than two lobes involved. Of all included patients, COVID-19 pneumonia presented with ground glass opacities in 65 (72%), consolidation in 12 (13%), crazy paving pattern in 11 (12%), interlobular thickening in 33 (37%), adjacent pleura thickening in 50 (56%), and linear opacities combined in 55 (61%). Pleural effusion, pericardial effusion, and lymphadenopathy were uncommon findings. In addition, baseline chest CT did not show any abnormalities in 21 patients (23%), but 3 patients presented bilateral ground glass opacities on the second CT after 3-4 days. CONCLUSION: SARS-CoV-2 infection can be confirmed based on the patient's history, clinical manifestations, imaging characteristics, and laboratory tests. Chest CT examination plays an important role in the initial diagnosis of the novel coronavirus pneumonia. Multiple patchy ground glass opacities in bilateral multiple lobular with periphery distribution are typical chest CT imaging features of the COVID-19 pneumonia.