Visualization Design Practices in a Crisis: Behind the Scenes With COVID-19 Dashboard Creators.

During the COVID-19 pandemic, a number of data visualizations were created to inform the public about the rapidly evolving crisis. Data dashboards, a form of information dissemination used during the pandemic, have facilitated this process by visualizing statistics regarding the number of COVID-19 cases over time. Prior work on COVID-19 visualizations has primarily focused on the design and evaluation of specific visualization systems from technology-centered perspectives. However, little is known about what occurs behind the scenes during the visualization creation processes, given the complex sociotechnical contexts in which they are embedded. Yet, such ecological knowledge is necessary to help characterize the nuances and trajectories of visualization design practices in the wild, as well as generate insights into how creators come to understand and approach visualization design on their own terms and for their own situated purposes. In this research, we conducted a qualitative interview study among dashboard creators from federal agencies, state health departments, mainstream news media outlets, and other organizations that created (often widely-used) COVID-19 dashboards to answer the following questions: how did visualization creators engage in COVID-19 dashboard design, and what tensions, conflicts, and challenges arose during this process? Our findings detail the trajectory of design practices-from creation to expansion, maintenance, and termination-that are shaped by the complex interplay between design goals, tools and technologies, labor, emerging crisis contexts, and public engagement. We particularly examined the tensions between designers and the general public involved in these processes. These conflicts, which often materialized due to a divergence between public demands and standing policies, centered around the type and amount of information to be visualized, how public perceptions shape and are shaped by visualization design, and the strategies utilized to deal with (potential) misinterpretations and misuse of visualizations. Our findings and lessons learned shed light on new ways of thinking in visualization design, focusing on the bundled activities that are invariably involved in human and nonhuman participation throughout the entire trajectory of design practice.

Decrease of atmospheric black carbon and CO2 concentrations due to COVID-19 lockdown at the Mt. Waliguan WMO/GAW baseline station in China.

The Coronavirus Disease 2019 (COVID-19) lockdown policy reduced anthropogenic emissions and impacted the atmospheric chemical characteristics in Chinese urban cities. However, rare studies were conducted at the high mountain site. In this work, in-situ measurements of light absorption by carbonaceous aerosols and carbon dioxide (CO2) concentrations were conducted at Waliguan (WLG) over the northeastern Tibetan Plateau of China from January 3 to March 30, 2020. The data was employed to explore the influence of the COVID-19 lockdown on atmospheric chemistry in the background-free troposphere. During the sampling period, the light absorption near-infrared (>470 nm) was mainly contributed by BC (>72%), however, BC and brown carbon (BrC) contributed equally to light absorption in the short wavelength (∼350 nm). The average BC concentrations in the pre-, during and post-lockdown were 0.28 ±â€¯0.25, 0.18 ±â€¯0.16, and 0.28 ±â€¯0.20 µg m-3, respectively, which decreased by approximately 35% during the lockdown period. Meanwhile, CO2 also showed slight decreases during the lockdown period. The declined BC was profoundly attributed to the reduced emissions (∼86%), especially for the combustion of fossil fuels. Moreover, the declined light absorption of BC, primary and secondary BrC decreased the solar energy absorbance by 35, 15, and 14%, respectively. The concentration weighted trajectories (CWT) analysis suggested that the decreased BC and CO2 at WLG were exclusively associated with the emission reduction in the eastern region of WLG. Our results highlighted that the reduced anthropogenic emissions attributed to the lockdown in the urban cities did impact the atmospheric chemistry in the free troposphere of the Tibetan Plateau.

Preparation of a Single-Chain Antibody against Nucleocapsid Protein of Porcine Deltacoronavirus by Phage Display Technology.

Porcine deltacoronavirus (PDCoV) mainly causes severe diarrhea and intestinal pathological damage in piglets and poses a serious threat to pig farms. Currently, no effective reagents or vaccines are available to control PDCoV infection. Single-chain fragment variable (scFv) antibodies can effectively inhibit virus infection and may be a potential therapeutic reagent for PDCoV treatment. In this study, a porcine phage display antibody library from the peripheral blood lymphocytes of piglets infected with PDCoV was constructed and used to select PDCoV-specific scFv. The library was screened with four rounds of biopanning using the PDCoV N protein, and the colony with the highest affinity to the PDCoV N protein was obtained (namely, N53). Then, the N53-scFv gene fragment was cloned into plasmid pFUSE-hIgG-Fc2 and expressed in HEK-293T cells. The scFv-Fc antibody N53 (namely, scFv N53) was purified using Protein A-sepharose. The reactive activity of the purified antibody with the PDCoV N protein was confirmed by indirect enzyme-linked immunosorbent assay (ELISA), western blot and indirect immunofluorescence assay (IFA). Finally, the antigenic epitopes that the scFv N53 recognized were identified by a series of truncated PDCoV N proteins. The amino acid residues 82GELPPNDTPATTRVT96 of the PDCoV N protein were verified as the minimal epitope that can be recognized by the scFv-Fc antibody N53. In addition, the interaction between the scFv-Fc antibody N53 and the PDCoV N protein was further analyzed by molecule docking. In conclusion, our research provides some references for the treatment and prevention of PDCoV.

Optimization of extreme learning machine model with biological heuristic algorithms to estimate daily reference crop evapotranspiration in different climatic regions of China

• Hybrid ELM models (PSO-ELM, GA-ELM and ABC-ELM) were proposed for estimating ET 0 in different climate zones of China. • PSO-ELM model had the highest accuracy, followed by GA-ELM and ABC-ELM. • Hybrid ELM models outperformed standalone ELM and empirical models in different climate zones. • PSO-ELM model with T max , T min and RH obtained accurate ET 0 estimates in TCZ, SMZ and TMZ. • PSO-ELM model with only T max and T min was better performance on ET 0 estimates in MPZ. Accurate prediction of reference crop evapotranspiration (ET 0) is important for regional water resources management and optimal design of agricultural irrigation system. In this study, three hybrid models (PSO-ELM, GA-ELM and ABC-ELM) integrating the extreme learning machine model (ELM) with three biological heuristic algorithms, i.e., PSO, GA and ABC, were proposed for predicting daily ET 0 based on daily meteorological data from 2000 to 2019 at twelve representative stations in different climatic zones of China. The performances of the three hybrid ELM models were further compared with the standalone ELM model and three empirical models (Hargreaves, Priestley-Talor and Makkink models). The results showed that the hybrid ELM models (R 2 = 0.973–0.999) all performed better than the standalone ELM model (R 2 = 0.955–0.989) in four climatic regions in China. The estimation accuracy of the empirical models was relatively lower, with R2 of 0.822–0.887 and RMSE of 0.381–1.951 mm/d. The R 2 values of PSO-ELM, GA-ELM and ABC-ELM models were 0.993, 0.986 and 0.981 and the RMSE values were 0.266 mm/d, 0.306 mm/d and 0.404 mm/d, respectively, indicating that the PSO-ELM model had the best performance. When setting T max , T min and RH as the model inputs, the PSO-ELM model presented better performance in the temperate continental zone (TCZ), subtropical monsoon region (SMZ) and temperate monsoon zone (TMZ) climate zones, with R 2 of 0.892, 0866 and 0.870 and RMSE of 0.773 mm/d, 0.597 mm/d and 0.832 mm/d, respectively. The PSO-ELM model also performed in the mountain plateau region (MPZ) when only T max and T min data were available, with R2 of 0.808 and RMSE of 0.651 mm/d. All the three biological heuristic algorithms effectively improved the performance of the ELM model. Particularly, the PSO-ELM was recommended as a promising model realizing the high-precision estimation of daily ET 0 with fewer meteorological parameters in different climatic zones of China. [ FROM AUTHOR] Copyright of Journal of Hydrology is the property of Elsevier B.V. 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 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 . (Copyright applies to all s.)

Public Attitudes and Factors of COVID-19 Testing Hesitancy in the United Kingdom and China: Comparative Infodemiology Study.

BACKGROUND: Massive community-wide testing has become the cornerstone of management strategies for the COVID-19 pandemic. OBJECTIVE: This study was a comparative analysis between the United Kingdom and China, which aimed to assess public attitudes and uptake regarding COVID-19 testing, with a focus on factors of COVID-19 testing hesitancy, including effectiveness, access, risk perception, and communication. METHODS: We collected and manually coded 3856 UK tweets and 9299 Chinese Sina Weibo posts mentioning COVID-19 testing from June 1 to July 15, 2020. Adapted from the World Health Organization's 3C Model of Vaccine Hesitancy, we employed social listening analysis examining key factors of COVID-19 testing hesitancy (confidence, complacency, convenience, and communication). Descriptive analysis, time trends, geographical mapping, and chi-squared tests were performed to assess the temporal, spatial, and sociodemographic characteristics that determine the difference in attitudes or uptake of COVID-19 tests. RESULTS: The UK tweets demonstrated a higher percentage of support toward COVID-19 testing than the posts from China. There were much wider reports of public uptake of COVID-19 tests in mainland China than in the United Kingdom; however, uncomfortable experiences and logistical barriers to testing were more expressed in China. The driving forces for undergoing COVID-19 testing were personal health needs, community-wide testing, and mandatory testing policies for travel, with major differences in the ranking order between the two countries. Rumors and information inquiries about COVID-19 testing were also identified. CONCLUSIONS: Public attitudes and acceptance toward COVID-19 testing constantly evolve with local epidemic situations. Policies and information campaigns that emphasize the importance of timely testing and rapid communication responses to inquiries and rumors, and provide a supportive environment for accessing tests are key to tackling COVID-19 testing hesitancy and increasing uptake.

Therapeutic application of estrogen for COVID-19: Attenuation of SARS-CoV-2 spike protein and IL-6 stimulated, ACE2-dependent NOX2 activation, ROS production and MCP-1 upregulation in endothelial cells.

The outbreak of COVID-19 has remained uncontained with urgent need for robust therapeutics. We have previously reported sex difference of COVID-19 for the first time indicating male predisposition. Males are more susceptible than females, and more often to develop into severe cases with higher mortality. This predisposition is potentially linked to higher prevalence of cigarette smoking. Nonetheless, we found for the first time that cigarette smoking extract (CSE) had no effect on angiotensin converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) expression in endothelial cells. The otherwise observed worse outcomes in smokers is likely linked to baseline respiratory diseases associated with chronic smoking. Instead, we hypothesized that estrogen mediated protection might underlie lower morbidity, severity and mortality of COVID-19 in females. Of note, endothelial inflammation and barrier dysfunction are major mediators of disease progression, and development of acute respiratory distress syndrome (ARDS) and multi-organ failure in patients with COVID-19. Therefore, we investigated potential protective effects of estrogen on endothelial cells against oxidative stress induced by interleukin-6 (IL-6) and SARS-CoV-2 spike protein (S protein). Indeed, 17ß-estradiol completely reversed S protein-induced selective activation of NADPH oxidase isoform 2 (NOX2) and reactive oxygen species (ROS) production that are ACE2-dependent, as well as ACE2 upregulation and induction of pro-inflammatory gene monocyte chemoattractant protein-1 (MCP-1) in endothelial cells to effectively attenuate endothelial dysfunction. Effects of IL-6 on activating NOX2-dependent ROS production and upregulation of MCP-1 were also completely attenuated by 17ß-estradiol. Of note, co-treatment with CSE had no additional effects on S protein stimulated endothelial oxidative stress, confirming that current smoking status is likely unrelated to more severe disease in chronic smokers. These data indicate that estrogen can serve as a novel therapy for patients with COVID-19 via inhibition of initial viral responses and attenuation of cytokine storm induced endothelial dysfunction, to substantially alleviate morbidity, severity and mortality of the disease, especially in men and post-menopause women. Short-term administration of estrogen can therefore be readily applied to the clinical management of COVID-19 as a robust therapeutic option.