Modeling the Subsurface Structure of Sunspots

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local helioseismology is the only means by which we can investigate subphotospheric structure. However, as current linear inversion techniques do not yet allow helioseismology to probe the internal structure with sufficient confidence to distinguish between the monolith and cluster models, the development of physically realistic sunspot models are a priority for helioseismologists. This is because they are not only important indicators of the variety of physical effects that may influence helioseismic inferences in active regions, but they also enable detailed assessments of the validity of helioseismic interpretations through numerical forward modeling. In this paper, we provide a critical review of the existing sunspot models and an overview of numerical methods employed to model wave propagation through model sunspots. We then carry out an helioseismic analysis of the sunspot in Active Region 9787 and address the serious inconsistencies uncovered by \citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find that this sunspot is most probably associated with a shallow, positive wave-speed perturbation (unlike the traditional two-layer model) and that travel-time measurements are consistent with a horizontal outflow in the surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic

The COVID-19 pandemic and its global effects on dental practice. An international survey

Objectives: A multicentre survey was designed to evaluate the impact of COVID-19 outbreak on dental practice worldwide, estimate the COVID-19 related symptoms/signs, work attitudes and behaviour and the routine use of protective measures and Personal Protective Equipment (PPE). Methods: A global survey using a standardized questionnaire with research groups from 36 countries was designed. The questionnaire was developed and pretested during April 2020 and contained three domains: 1) Personal data; 2) COVID-19 positive rate and symptoms/signs presumably related to the coronavirus; 3) Working conditions and PPE adopted after the outbreak. Countries’ data were grouped by the Country Positive Rate (CPR) during the survey period and by Gross-National-Income per capita. An ordinal multinomial logistic regression model was carried out with COVID-19 self-reported rate referred by dental professionals as dependent variable to assess the association with questionnaire items. Results: A total of 52,491 questionnaires were returned with a male/female ratio of 0.63. Out of the total respondents, 7,859 dental professionals (15%) reported symptoms/signs compatible with COVID-19. More than half of the sample (n = 27,818; 53%) stated to use FFP2/N95 masks, while 21,558 (41.07%) used eye protection. In the bivariate analysis, CPR and N95/FFP2 were significantly associated (OR = 1.80 95%CI = 1.60/2.82 and OR = 5.20 95%CI = 1.44/18.80, respectively), while Gross-National-Income was not statistically associated with CPR (OR = 1.09 95%CI = 0.97/1.60). The same significant associations were observed in the multivariate analysis. Conclusions: Oral health service provision has not been significantly affected by COVID-19, although access to routine dental care was reduced due to country-specific temporary lockdown periods. While the dental profession has been identified at high-risk, the reported rates of COVID-19 for dental professionals were not significantly different to those reported for the general population in each country. These findings may help to better plan oral health care for future pandemic events

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press