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In the course of the COVID-19 pandemic, borders have become relevant (again) in political action and in people's everyday lives within a very short time. This was especially true for the inhabitants of border regions, whose cross-border life worlds were suddenly irritated by closed borders and police controls. However, the COVID-19 pandemic also led to an increased evidence of social, cultural, eco-nomic, health and mobility boundaries beyond national borders. The authors of this new issue of “UniGR-CBS Borders in Perspective” shed light on these dynamics from the perspective of territorial borders, social boundaries and (dis)continuities in border regions through a variety of thematic and spatial approaches. Their critical observations and scientific comments were made during the lockdown in April and May 2020 and provide insights into the events during the global pandemic. Im Zuge der COVID-19-Pandemie sind Grenzen binnen kürzester Zeit im politischen Handeln und im Alltag der Menschen (wieder) relevant geworden. Dies betraf in besonderem Maße die Bewohner*innen von Grenzregionen, deren grenzüberschreitende Lebenswelten plötzlich von geschlossenen Grenzen und polizeilichen Kontrollen irritiert wurden. Doch auch jenseits von Staatsgrenzen führte die COVID-19-Pandemie zu einer verstärkten Wahrnehmung von sozialen, kulturellen, wirtschaftlichen, gesundheitlichen und mobilitätsbezogenen Grenzen. Die Autor*innen der neuen Ausgabe von “UniGR-CBS Borders in Perspective” beleuchten diese Dynamiken aus dem Blickwinkel von territorialen Grenzen, sozialen Grenzziehungen und (Dis)Kontinuitäten in Grenzregionen über vielfältige thematische und räumliche Zugänge. Ihre kritischen Beobachtungen und wissenschaftlichen Kommentare sind während des Lockdown im April und Mai 2020 entstanden und geben Einblicke in das Zeitgeschehen während der globalen Pandemie. Au cours de la pandémie COVID-19, les frontières ont (re)pris de l'importance dans l'action politique et dans la vie quotidienne en très peu de temps. C'était particulièrement vrai pour les habitants des régions frontalières, dont le quotidien transfrontalier était soudainement irrité par la fermeture des frontières et les contrôles de police. Toutefois, la pandémie de COVID-19 a également entraîné une perception accrue des frontières sociales, culturelles, économiques, sanitaires et de mobilité au-delà des frontières nationales. Les auteurs de la nouvelle édition de l’« UniGR-CBS Borders in Perspective » éclairent ces dynamiques sous l'angle des frontières territoriales, des démarcations sociales et des (dis)continuités dans les régions frontalières par le biais de diverses approches thématiques et spatiales. Leurs observations critiques et commentaires scientifiques ont été faits pendant le confinement en avril et mai 2020 et donnent un aperçu des événements pendant la pandémie mondiale.

Background: High vaccination coverage rates are necessary to reduce infections and transmissions of the SARS-CoV-2 virus causing COVID-19 and to allow successful mitigation of the current pandemic. To date, we are still lacking information to explain the hesitancy in Luxembourg towards uptake of the available COVID-19 vaccines. The present study explored motivations for and against vaccination in a population-representative sample of residents across Luxembourg to identify hesitant groups and develop strategies to increase population immunity against SARS-CoV-2. Methods: In the framework of the nationwide, representative longitudinal CON-VINCE study, a sample of 1589 respondents (49.6% women, 84.3% Luxembourg nationality) ranging from 18-84 years, participated in the survey in spring 2021. The protocol of the CON-VINCE study has been described in detail elsewhere (Snoeck et al. 2020). Results: 52% of the respondents had at least partial vaccination at time of assessment between April to June 2021. The most common reasons for vaccination of those willing to be vaccinated (81.2%) were altruistic motivations. Prevalent reasons against vaccination for those undecided (8.7%) or reluctant (10.2%) to be vaccinated were that the vaccine had not been tested sufficiently and the fear of long-term vaccine side effects. Only very few of the vaccination-hesitant or -reluctant respondents reported that they did not believe in vaccination in general. Conclusion: The present study identified motivations for and against COVID-19 vaccination and determined demographic and socio-economic factors associated with vaccination willingness. To increase vaccination rates, public health communication needs to target those unsure or unwilling to be vaccinated. We will continue to study the vaccination uptake in the Luxembourg population, as CON-VINCE is now part of the H2020-funded international ORCHESTRA project (https://orchestra-cohort.eu), research into comparing these results on a Pan-European level.

As a response to the global outbreak of the SARS-COVID-19 pandemic, authorities have enforced a number of measures including social distancing, travel restrictions that lead to the “temporary” closure of activities stemming from public services, schools, industry to local businesses. In this poster we draw the attention to the impact of such measures on urban environments and activities. For this, we use crowdsensed information available from datasets like Google Popular Times and Apple Maps to shed light on the changes undergone during the outbreak and the recovery

When the COVID-19 pandemic hit in early 2020, a lot of research efforts were quickly redirected towards studies on SARS-CoV2 and COVID-19 disease, from the sequencing and assembly of viral genomes to the elaboration of robust testing methodologies and the development of treatment and vaccination strategies. At the same time, a flurry of scientific publications around SARS-CoV-2 and COVID-19 began to appear, making it increasingly difficult for researchers to stay up-to-date with latest trends and developments in this rapidly evolving field. The BioKB platform is a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles. The content of the articles is analysed and concepts from a range of contexts, including proteins, species, chemicals, diseases and biological processes are tagged based on existing dictionaries of controlled terms. Co-occurring concepts are classified based on their asserted relationship and the resulting subject-relation-object triples are stored in a publicly accessible human- and machine-readable knowledge base. All concepts in the BioKB dictionaries are linked to stable, persistent identifiers, either a resource accession such as an Ensembl, Uniprot or PubChem ID for genes, proteins and chemicals, or an ontology term ID for diseases, phenotypes and other ontology terms. In order to improve COVID-19 related text mining, we extended the underlying dictionaries to include many additional viral species (via NCBI Taxonomy identifiers), phenotypes from the Human Phenotype Ontology (HPO), COVID-related concepts including clinical and laboratory tests from the COVID-19 ontology, as well as additional diseases (DO) and biological processes (GO). We also added all viral proteins found in UniProt and gene entries from EntrezGene to increase the sensitivity of the text mining pipeline to viral data. To date, BioKB has indexed over 270’000 sentences from 21’935 publications relating to coronavirus infections, with publications dating from 1963 to 2021, 3’863 of which were published this year. We are currently working to further refine the text mining pipeline by training it on the extraction of increasingly complex relations such as protein-phenotype relationships. We are also regularly adding new terms to our dictionaries for areas where coverage is currently low, such as clinical and laboratory tests and procedures and novel drug treatments.

Our working hypothesis is that key factors in COVID-19 imaging are the available imaging data and their label noise and confounders, rather than network architectures per se. Thus, we applied existing state-of-the-art convolution neural network frameworks based on the U-Net architecture, namely nnU-Net [3], and focused on leveraging the available training data. We did not apply any pre-training nor modi ed the network architecture. First, we enriched training information by generating two additional labels for lung and body area. Lung labels were created with a public available lung segmentation network and weak body labels were generated by thresholding. Subsequently, we trained three di erent multi-class networks: 2-label (original background and lesion labels), 3-label (additional lung label) and 4-label (additional lung and body label). The 3-label obtained the best single network performance in internal cross-validation (Dice-Score 0.756) and on the leaderboard (Dice- Score 0.755, Haussdor 95-Score 57.5). To improve robustness, we created a weighted ensemble of all three models, with calibrated weights to optimise the ranking in Dice-Score. This ensemble achieved a slight performance gain in internal cross-validation (Dice-Score 0.760). On the validation set leaderboard, it improved our Dice-Score to 0.768 and Haussdor 95- Score to 54.8. It ranked 3rd in phase I according to mean Dice-Score. Adding unlabelled data from the public TCIA dataset in a student-teacher manner signi cantly improved our internal validation score (Dice-Score of 0.770). However, we noticed partial overlap between our additional training data (although not human-labelled) and nal test data and therefore submitted the ensemble without additional data, to yield realistic assessments.

The lifestyle of children and adolescents during the COVID-19 pandemic has been affected dramatically by restrictions, causing a substantial decrease in physical activity (PA) and extensive increase in sedentary activity time (Xiang et al. 2020). The purpose of this study was to investigate PA and lifestyle habits of adolescent students in a sample of European countries involved in the SUGAPAS project (Supporting Gamified Physical Activities in & out of Schools), an Erasmus+ funded project aiming to design and implement mobile games which should trigger students’ health-related habitual behavior.