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As a reflection of shifting and fluid experiences in time and space, live streaming can reduce losses in the tourism industry associated with travel restrictions during the COVID-19 pandemic. Compared with the use of live streaming activities in entertainment, shopping, sport, e-sport, religious, educational, and academic settings, the tourism context has yet to be explored. This study takes China as a case to examine tourism practices related to live streaming. Specifically, 48,114 social media posts were subjected to systematic content analysis. The dataset contained live streaming content related to 147 countries and 34 Chinese provincial administrative regions between 2010 and 2021. Findings revealed the following: (1) the development of tourism live streaming in China can be classified into germination, exploration, and opportunity stages and (4) live streaming tools and attractions constituted the core of the identified semantic network and had the strongest regulation capabilities in tourism live streaming activities. Findings shed light on latent cultural meanings in social media communications, where tourism live streaming features high-frequency linguistic signs. (3) users’ perceptions of tourism live streaming content involved institutions, live streaming tools, live streaming attractions, the live streaming economy, people, facilities and information, time, and regions (2) live content mainly evoked positive emotions, whereas negative sentiment resulted from illegal or boring content

The prevention and control of COVID-19 in megacities is under large pressure because of tens of millions and high-density populations. The majority of epidemic prevention and control policies implemented focused on travel restrictions, which severely affected urban mobility during the epidemic. Considering the impacts of epidemic and associated control policies, this study analyzes the relationship between COVID-19, travel of residents, Point of Interest (POI), and social activities from the perspective of taxi travel. First, changes in the characteristics of taxi trips at different periods were analyzed. Next, the relationship between POIs and taxi travels was established by the Geographic Information System (GIS) method, and the spatial lag model (SLM) was introduced to explore the changes in taxi travel driving force. Then, a social activities recovery level evaluation model was proposed based on the taxi travel datasets to evaluate the recovery of social activities. The results demonstrated that the number of taxi trips dropped sharply, and the travel speed, travel time, and spatial distribution of taxi trips had been significantly influenced during the epidemic period. The spatial correlation between taxi trips was gradually weakened after the outbreak of the epidemic, and the consumption travel demand of people significantly decreased while the travel demand for community life increased dramatically. The evaluation score of social activity is increased from 8.12 to 74.43 during the post-epidemic period, which may take 3&ndash 6 months to be fully recovered as a normal period. Results and models proposed in this study may provide references for the optimization of epidemic control policies and recovery of public transport in megacities during the post-epidemic period.

After steep drops and then rebounds in transportation-related CO$_2$ emissions over the first half of 2020, a second wave of COVID-19 this fall has caused further -- but less substantial -- emissions reductions. Here, we use near-real-time estimates of daily emissions to explore differences in human behavior and restriction policies over the course of 2020.

Silvicultural herbicides are used in Integrated Vegetation Management (IVM) to suppress vegetation that competes with trees for growing space, light, nutrients, water, and other resources in managed forests. While the toxicity and environmental impacts of silvicultural herbicides have been widely studied, far less is known about their effects on culturally significant plants important to Indigenous Peoples in the Canadian Boreal Forest Region. The main objective of this thesis is to assess the silvicultural use of herbicides on ethnobotanical species in the Canadian boreal. I identified 914 ethnobotanical plants in the Canadian boreal, including plants used as food, medicines, tools, art and culture, and for spiritual purposes. Most of these plants are not considered threatened globally or in Canada but are vulnerable to decline or elimination following herbicide spraying in managed forests. The results of my thesis support restricting herbicide spraying as an IVM practice in areas important to Indigenous Peoples. Professor Robin Roth for providing funding for my thesis, through the Conservation through Reconciliation Partnership (CRP), Graduate Coordinators in the Department of Geography, Geomatics and Environment - Drs. Noella Gray and Aaron Berg for funding support that I received from the department and additional financial support from the University of Guelph’s College of Social and Applied Human Sciences (CSAHS) COVID-19 Delay Assistance Program

Background Understanding the molecular basis of susceptibility factors to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health imperative. It is well-established that males are more likely to acquire SARS-CoV-2 infection and exhibit more severe outcomes. Similarly, exposure to air pollutants and pre-existing respiratory chronic conditions, such as asthma and chronic obstructive respiratory disease (COPD) confer an increased risk to coronavirus disease 2019 (COVID-19). Methods We investigated molecular patterns associated with risk factors in 398 candidate genes relevant to COVID-19 biology. To accomplish this, we downloaded DNA methylation and gene expression data sets from publicly available repositories (GEO and GTEx Portal) and utilized data from an empirical controlled human exposure study conducted by our team. Results First, we observed sex-biased DNA methylation patterns in autosomal immune genes, such as NLRP2, TLE1, GPX1, and ARRB2 (FDR < 0.05, magnitude of DNA methylation difference ���� > 0.05). Second, our analysis on the X-linked genes identified sex associated DNA methylation profiles in genes, such as ACE2, CA5B, and HS6ST2 (FDR < 0.05, ���� > 0.05). These associations were observed across multiple respiratory tissues (lung, nasal epithelia, airway epithelia, and bronchoalveolar lavage) and in whole blood. Some of these genes, such as NLRP2 and CA5B, also exhibited sex-biased gene expression patterns. In addition, we found differential DNA methylation patterns by COVID-19 status for genes, such as NLRP2 and ACE2 in an exploratory analysis of an empirical data set reporting on human COVID-9 infections. Third, we identified modest DNA methylation changes in CpGs associated with PRIM2 and TATDN1 (FDR < 0.1, ���� > 0.05) in response to particle-depleted diesel exhaust in bronchoalveolar lavage. Finally, we captured a DNA methylation signature associated with COPD diagnosis in a gene involved in nicotine dependence (COMT) (FDR < 0.1, ���� > 0.05). Conclusion Our findings on sex differences might be of clinical relevance given that they revealed molecular associations of sex-biased differences in COVID-19. Specifically, our results hinted at a potentially exaggerated immune response in males linked to autosomal genes, such as NLRP2. In contrast, our findings at X-linked loci such as ACE2 suggested a potentially distinct DNA methylation pattern in females that may interact with its mRNA expression and inactivation status. We also found tissue-specific DNA methylation differences in response to particulate exposure potentially capturing a nitrogen dioxide (NO2) effect���a contributor to COVID-19 susceptibility. While we identified a molecular signature associated with COPD, all COPD-affected individuals were smokers, which may either reflect an association with the disease, smoking, or may highlight a compounded effect of these two risk factors in COVID-19. Overall, our findings point towards a molecular basis of variation in susceptibility factors that may partly explain disparities in the risk for SARS-CoV-2 infection.

Activity reductions in early 2020 due to the Coronavirus Disease 2019 pandemic led to unprecedented decreases in carbon dioxide (CO2) emissions. Despite their record size, the resulting atmospheric signals are smaller than and obscured by climate variability in atmospheric transport and biospheric fluxes, notably that related to the 2019-2020 Indian Ocean Dipole. Monitoring CO2 anomalies and distinguishing human and climatic causes thus remains a new frontier in Earth system science. We show, for the first time, that the impact of short-term, regional changes in fossil fuel emissions on CO2 concentrations was observable from space. Starting in February and continuing through May, column CO2 over many of the World's largest emitting regions was 0.14 to 0.62 parts per million less than expected in a pandemic-free scenario, consistent with reductions of 3 to 13 percent in annual, global emissions. Current spaceborne technologies are therefore approaching levels of accuracy and precision needed to support climate mitigation strategies with future missions expected to meet those needs.

Objective: To determine the relative risk of drug-induced Long QT Syndrome (LQTS) associated with SARS-CoV-2 (COVID-19) proposed repurposed drugs compared to well-known torsadogenic compounds. Setting: Computer calculations and simulations were performed using primary pharmacokinetic and pharmacodynamic data for each proposed drug. Seven different LQTS indices were calculated and compared. The U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database was queried with specific key words relating to arrhythmogenic events. Interventions: A thorough literature search was performed to gather information on the pharmacological properties of six drugs (azithromycin, chloroquine, favipiravir, hydroxychloroquine, lopinavir/ritonavir, and remdesivir) repurposed to treat COVID-19. Researchers emphasized the affinity of these drugs to block the rapid component of the delayed rectifier cardiac potassium current (IKr) encoded by the human ether-a-go-go gene (hERG), their propensity to prolong cardiac repolarization (QT interval), and cause torsade de pointes (TdP). The risk of drug-induced LQTS for these drugs was quantified by comparing six indices that assess such risk. Primary and secondary outcome measures: Level of risk estimated for the six COVID-19 drugs being proposed compared to 23 torsadogenic drugs. Number of proarrhythmic adverse events identified for these drugs in the FAERS. Results: Estimators of LQTS risk levels indicated a very high or high risk for all COVID-19 repurposed drugs with the exception for azithromycin, although cases of TdP have been reported with this drug. There was excellent agreement among the various indices used to assess risk of drug-induced LQTS for the six repurposed drugs and 23 torsadogenic compounds. Conclusion: The risk-benefit assessment for the use of repurposed drugs to treat COVID-19 is complicated since benefits are currently anticipated, not proven. Mandatory monitoring of the QT interval shall be performed, as such monitoring is possible for hospitalized patients or with the use of biodevices for outpatients prescribed these drugs.

We constructed a near-real-time daily CO2 emission dataset, namely the Carbon Monitor, to monitor the variations of CO2 emissions from fossil fuel combustion and cement production since January 1st 2019 at national level with near-global coverage on a daily basis, with the potential to be frequently updated. Daily CO2 emissions are estimated from a diverse range of activity data, including: hourly to daily electrical power generation data of 29 countries, monthly production data and production indices of industry processes of 62 countries/regions, daily mobility data and mobility indices of road transportation of 416 cities worldwide. Individual flight location data and monthly data were utilised for aviation and maritime transportation sectors estimates. In addition, monthly fuel consumption data that corrected for daily air temperature of 206 countries were used for estimating the emissions from commercial and residential buildings. This Carbon Monitor dataset manifests the dynamic nature of CO2 emissions through daily, weekly and seasonal variations as influenced by workdays and holidays, as well as the unfolding impacts of the COVID-19 pandemic. The Carbon Monitor near-real-time CO2 emission dataset shows a 7.8% decline of CO2 emission globally from Jan 1st to Apr 30th in 2020 when compared with the same period in 2019, and detects a re-growth of CO2 emissions by late April which are mainly attributed to the recovery of economy activities in China and partial easing of lockdowns in other countries. Further, this daily updated CO2 emission dataset could offer a range of opportunities for related scientific research and policy making.