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15 Research products

  • COVID-19
  • 2014-2023
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  • French National Research Agency (ANR)
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  • Hyper Article en Ligne - Sciences de l'Homme et de la Société

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Carastan dos Santos, Danilo; Rzadca, Krzysztof; Sousa, Leonel; Trystram, Denis;

    Conferencing is one of the main pillars of Computer Science research activity regarding career and networking, with conference publications playing a more pronounced role compared to other disciplines. The COVID-19 pandemic forced us to switch to virtual conferencing, and many works have shown the benefits of virtual conferencing in terms of inclusivity and reduction of Green House Gas emissions. We are moving toward the usual conferencing format as it appears that the pandemic is increasingly under control. However, the changes imposed during the period of the pandemic brought many essential lessons regarding conferencing social and environmental effects. A crucial task is to gather these community experiences to give directions on how to keep the learned lessons post-COVID-19. We used the Euro-Par conference to synthesize these lessons in the Computer Science case. We show practical results that reinforce the marginal emissions of virtual conferencing compared to in-person conference travel. We also open the debate that rethinking the conference utility according to our objectives (scientific and ecologic) and being aware of social/geographical biases are essential factors in participating and organizing post-COVID-19 conferences.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Coquidé, Célestin; Lages, José; Ermann, Leonardo; Shepelyansky, Dima;

    Using the United Nations Comtrade database, we perform the Google matrix analysis of the multiproduct World Trade Network (WTN) for the years 2018-2020 comprising the emergence of the COVID-19 as a global pandemic. The applied algorithms -- the PageRank, the CheiRank and the reduced Google matrix -- take into account the multiplicity of the WTN links providing new insights on the international trade comparing to the usual import-export analysis. These algorithms establish new rankings and trade balances of countries and products considering every countries on equal grounds, independently of their wealth, and every products on the basis of their relative exchanged volumes. In comparison with the pre-COVID-19 period, significant changes in these metrics occur for the year 2020 highlighting a major rewiring of the international trade flows induced by the COVID-19 pandemic crisis. We define a new PageRank-CheiRank product trade balance, either export or import oriented, which is significantly perturbed by the pandemic. Comment: 22 pages, 2 tables, 13 figures, 2 appendices

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Christakis, Theodore; Bannelier-Christakis, Karine; Castelluccia, Claude; Le Métayer, Daniel;

    Part 1 of our “MAPping the use of Facial Recognition in public spaces in Europe” (MAPFRE) project reports explained in detail what “facial recognition” means, addressed the issues surrounding definitions, presented the political landscape and set out the exact material and geographical scope of the study. Part 2 of our Reports presented, in the most accessible way possible, how facial recognition works and produced a “Classification Table” with illustrations, explanations and examples, detailing the uses of facial recognition/analysis in public spaces, in order to help avoid conflating the diverse ways in which facial recognition is used and to bring nuance and precision to the public debate. This 3rd Report focuses on what is, undoubtedly, the most widespread way in which Facial Recognition Technologies (FRT) are used in public (and private) spaces: Facial Recognitionfor authorisation purposes.Facial recognition is often used to authorise access to a space (e.g. access control) or to a service (e.g. to make a payment). Depending on the situation, both verification and identi fication functionalities (terms that are explained in our 2nd Report) can be used. Millions of people use FRT to unlock their phones every day. Private entities (such as banks) or public authorities (such as the French government in terms of the now abandoned ALICEM pro ject) increasingly envisage using FRT as a means of providing strong authentication in or der to control access to private or public online services, such as e-banking, or administra tive websites that concern income, health or other personal matters. FRT is increasingly being considered as a means of improving security when controlling and managing access to private areas (building entrances, goods warehouses, etc.). In public spaces, FRT is being used as an authentication tool for automated international border controls (for example at airports) or to manage access in places as diverse as airports, stadiums or schools. Pre Covid-19, there were a lot of projects to use in the future FRT in order to “accelerate people flows”, “improve the customer experience”, “speed up opera tions” and “reduce queuing time” for users of different services (e.g. passengers boarding a plane or shopping) but the advent of the Covid-19 pandemic has further boosted calls for investment in FRTs in order to provide contactless services and reduce the risk of contam ination. Supermarkets, such as Carrefour, which was involved in a pilot project in Romania, or transport utilities in “smart cities”, such as the EMT bus network in Madrid, which teamed with Mastercard to conduct a pilot project that enables users to pay on EMT buses using FRT, have implemented facial recognition payment systems that permit consumers to complete transactions by simply having their faces scanned. In Europe, similar pilot pro jects are currently being tested enabling the management of payments in restaurants, cafés and shops. Despite this widespread existing use or projected use of FRT for authorisation purposes we are not aware of any detailed study that is focusing on this specific issue. We hope that the present analytic study will help fill this gap by focusing on the specific issue of the use of FRT for authorisation purposes in public spaces in Europe. We have examined in detail seven “emblematic” cases of FRT being used for authorisation purposes in public spaces in Europe. We have reviewed the documents disseminated by data controllers concerning all of these cases (and several others). We have sought out the reactions of civil society and other actors. We have dived into EU and Member State laws. We have analysed a number of Data Protection Authority (DPA) opinions. We have iden tified Court decisions of relevance to this matter.

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    Authors: Borau, Sylvie; Couprie, Hélène; Hopfensitz, Astrid;

    Single people are more likely to die from COVID-19. Here, we study whether this higher death rate could be partly explained by differences in compliance with protective health measures against COVID-19 between single and married people, and the drivers of this marital compliance gap. Data collected from 46,450 respondents in 67 countries reveal that married people are more likely to comply with protective measures than single people. This marital gap in compliance is higher for men (approximately 5%) than for women (approximately 2%). These results are robust across a large range of countries and independent of country level differences with respect to culture, values or infection rates. Prosocial characteristics linked to morality and social belonging explain more than 38% of the marital gap, while individual risk perceptions play a minor role. These findings help explain single people's and particularly single men's greater vulnerability to COVID-19, which in turn can be leveraged to improve the effectiveness of international public policy campaigns aimed at promoting protective health measures.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Roquencourt, Camille;

    L'analyse des composés organiques volatils (COVs) dans l'air expiré est une méthode non invasive prometteuse en médecine pour le diagnostic précoce, le phénotypage, le suivi de la maladie et du traitement et le dépistage à grande échelle. La spectrométrie de masse à temps de vol par réaction de transfert de protons (PTR-TOF-MS) présente un intérêt majeur pour l'analyse en temps réel des COVs et la découverte de nouveaux biomarqueurs. Le manque de méthodes et d'outils logiciels pour le traitement des données PTR-TOF-MS provenant de cohortes représente actuellement un verrou pour le développement de ces approches.Nous avons ainsi développé une suite d'algorithmes permettant le traitement des données brutes jusqu’au tableau des intensités des molécules détectées, grâce à la détection des expirations et des pics dans les spectres de masse, la quantification dans la dimension temporelle, l'alignement entre les échantillons et l'imputation des valeurs manquantes. Nous avons notamment mis au point un modèle innovant de déconvolution des pics en 2 dimensions reposant sur une régression du signal par splines pénalisées, ainsi qu'une méthode permettant de sélectionner spécifiquement les COVs dans l'air expiré. L'ensemble du processus est implémenté dans le paquet R/Bioconductor ptairMS, disponible en ligne. Nous avons validé notre approche à la fois sur des données expérimentales (mélange de COVs à des concentrations standardisées) et par simulation. Les résultats montrent que l'identification des COVs provenant de l’air expiré à partir du modèle proposé atteint une sensibilité de 99 `%. Une interface graphique a également été développée pour faciliter l'analyse des données et l'interprétation des résultats par les expérimentateurs (les cliniciens notamment). Nous avons appliqué notre méthodologie à la caractérisation de l'air expiré d'adultes sous ventilation mécanique atteints de l’infection COVID-19. Les analyses de l'air expiré de 40 patients atteints d’un syndrome de détresse respiratoire aiguë (SDRA) ont été effectuées quotidiennement, de l'entrée à la sortie de l'hôpital. Nous avons d'abord réalisé un modèle de classification pour prédire le statut de l'infection, en utilisant l'acquisition disponible la plus proche de l’admission à l'hôpital.Ce modèle permet de prédire le statut de l'infection avec une précision de 93%. Ensuite, nous avons utilisé toutes les données disponibles pour une analyse longitudinale de l'évolution des COVs en fonction de la durée de l'hospitalisation, en utilisant un modèle à effets mixtes. Après sélection de variables, quatre biomarqueurs de l'infection par le COVID-19 ont pu être identifiés. Ces résultats soulignent la valeur des données PTR-TOF-MS et du logiciel ptairMS pour la découverte de biomarqueurs dans l'air expiré. The analysis of Volatile Organic Compounds (VOCs) in exhaled breath is a promising non-invasive approach in medicine for early diagnosis, phenotyping, disease and treatment monitoring and large-scale screening. Proton Transfer Reaction Time-Of-Flight Mass Spectrometry (PTR-TOF-MS) is of major interest for the real time analysis of VOCs and the discovery of new biomarkers in the clinics. However, there is currently a lack of methods and software tools for the processing of PTR-TOF-MS data from cohorts.We therefore developed a suite of algorithms that process raw data from the patient acquisitions, and build the table of feature intensities, through expiration and peak detection, quantification, alignment between samples, and missing value imputation. Notably, we developed an innovative 2D peak deconvolution model based on penalized splines signal regression, and a method to specifically select the VOCs from exhaled breath. The full workflow is implemented in the freely available ptairMS R/Bioconductor package. Our approach was validated both on experimental data (mixture of VOCs at standardized concentrations) and simulations, which showed that the sensitivity for the identification of VOCs from exhaled breath reached 99 %. A graphical interface was also developed to facilitate data analysis and result interpretation by experimenters (e.g., clinicians).We applied our methodology to the characterization of exhaled breath from mechanically ventilated adults with COVID-19 infection. Analysis of exhaled breath from 28 patients with an acute respiratory distress syndrome (ARDS) and COVID-19 infection, and 12 patients with non-COVID-19 ARDS were performed daily from the hospital admission to the discharge. First, classification models were built to predict the status of the infection, using the closest available acquisition to the entry into hospital, and achieved high prediction accuracies (93 %). Then, all the available data acquired during the hospital stay were used for the longitudinal analysis of the VOCs evolution as a function of the hospitalization time by mixed-effects modeling. Following feature ranking and selection, four biomarkers of COVID-19 infection were identified. Altogether, these results highlight the value of the PTR-TOF-MS data and the ptairMS software for biomarker discovery in exhaled breath.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Milhaud, Xavier; Pommeret, Denys; Salhi, Yahia; Vandekerkhove, Pierre;

    In this paper, we consider two-component mixture distributions having one known component. This type of model is of particular interest when a known random phenomenon is contaminated by an unknown random effect. We propose in this setup to compare the unknown random sources involved in two separate samples. For this purpose, we introduce the so-called IBM (Inversion-Best Matching) approach resulting in a relaxed semiparametric Cramér-von Mises type two-sample test requiring very minimal assumptions (shape constraint free) about the unknown distributions. The accomplishment of our work lies in the fact that we establish a functional central limit theorem on the proportion parameters along with the unknown cumulative distribution functions of the model when Patra and Sen [22] prove that the √ n-rate cannot be achieved on these quantities in the basic one-sample case. An intensive numerical study is carried out from a large range of simulation setups to illustrate the asymptotic properties of our test. Finally, our testing procedure is applied to a real-life application through pairwise post-covid mortality effect testing across a panel of European countries. Nous considérons dans cet article des mélanges à deux composantes dont une composante est connue. Ces modèles sont d'un intérêt particulier lorsqu'un phénomène bien connu est affecté par une perturbation inconnue. Nous proposons de comparer les sources de cet impact inconnu entre deux échantillons distincts. Pour ce faire nous introduisons une nouvelle approche, appelée IBM (Inversion-Best Matching), qui permet d'effectuer le test à la manière d'un test de type Cramer-Von Mises sous très peu d'hypothèses concernant les aléas perturbateurs inconnus. Nous établissons un théorème central limite (TCL) fonctionnel sur les estimateurs que sont les proportions de chacun des modèles de contamination, ainsi que la fonction de répartition inconnue, là où Patra et Sen [22] n'obtenait pas de résultat asymptotique de type TCL. Des simulations permettent de valider la performance de la procédure de test et d'en valider ses propriétés asymptotiques. Enfin, nous appliquons notre stratégie de test à un problème concret de comparaison de déformation de la mortalité suite à la pandémie de Covid-19 à travers plusieurs pays européens.

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    Authors: Gallic, Ewen; Lubrano, Michel; Michel, Pierre;

    Uprising in China, the global COVID-19 epidemic soon started to spread out in Europe. As no medical treatment was available, it became urgent to design optimal non-pharmaceutical policies. With the help of a SIR model, we contrast two policies, one based on herd immunity (adopted by Sweden and the Netherlands), the other based on ICU capacity shortage. Both policies led to the danger of a second wave. Policy efficiency corresponds to the absence or limitation of a second wave. The aim of the paper is to measure the efficiency of these policies using statistical models and data. As a measure of efficiency, we propose the ratio of the size of two observed waves using a double sigmoid model coming from the biological growth literature. The Oxford data set provides a policy severity index together with observed number of cases and deaths. This severity index is used to illustrate the key features of national policies for ten European countries and to help for statistical inference. We estimate basic reproduction numbers, identify key moments of the epidemic and provide an instrument for comparing the two reported waves between January and October 2020. We reached the following conclusions. With a soft but long lasting policy, Sweden managed to master the first wave for cases thanks to a low R 0 , but at the cost of a large number of deaths compared to other Nordic countries and Denmark is taken as an example. We predict the failure of herd immunity policy for the Netherlands. We could not identify a clear sanitary policy for large European countries. What we observed was a lack of control for observed cases, but not for deaths.

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  • Authors: Etilé, Fabrice; Geoffard, Pierre-Yves;

    The COVID-19 outbreak has generated significant uncertainty about the future, especially for young adults. Health and economic threats, as well as more diffuse concerns about the consequences of COVID-19, can trigger feelings of anxiety, leading individuals to adopt uncertainty-reducing behaviours. We tested whether anxiety was associated with an increase in willingness to be exposed to the risk of COVID-19 infection (WiRE) using an online survey administered to 3,110 French individuals aged between 18 and 35 years old during the lockdown period (April 2020). Overall, 56.5% of the sample declared a positive WiRE. Unemployment was associated with a higher WiRE (+8.2 percentage points (pp); 95% CI +0.9-15.4 pp). One standard deviation increases in income (+1160€) and psychological state anxiety raised the WiRE by +2.7 pp (95% CI: +1.1-4.4 pp) and +3.9 pp (95% CI: +1.6-6.2 pp), respectively. A one standard deviation increase in perceived hospitalisation risk was associated with a -4.1 pp (95% CI: -6.2-2.1 pp) decrease in the WiRE. Overall, our results suggest that both the prospect of economic losses and psychological anxiety can undermine young adults’adherence to physical distancing recommendations. Public policies targeting young adults must consider both their economic situation and their mental health, and they must use uncertaintyreducingcommunication strategies.

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  • Authors: Boyer, Pierre, C; Gerschel, Elie; Raj, Anasuya;

    Summary:The European economic union is incomplete, which makes it vulnerable to macroeconomic shocks. The opportunity to move forward in the integration process was highly debated even before the Covid-19 crisis.Yet the diverging views among countries and political groups are often considered as an obstacle on the path to required agreements for completing the Economic and Monetary Union (EMU). We present the results of a survey conducted in 2018 among members of national parliaments (MPs) in France, Germany and Italy on European integration in policy fields related to risk-sharing and budgetary institutions, asking for their opinion on proposals such as the creation of a European Unemployment Insurance (EUI), Eurobonds, or an EU tax. We find that nationality and political groups are key determinants of support for such proposals, the latter being the strongest. We describe how opinions are divided and try to identify policy proposals which could gather enough political support. The agreement reached on July 21st, 2020 at the last European summit includes financial transfers between States and the creation of Eurobonds, thus representing an important institutional move and an application of some of the reforms suggested by our survey. Yet what has been decided upon is only temporary and leaves open the question of the future of European integration.Key points: At first glance, the answers show diverging opinions on most questions between countries with Italy supporting more integration, and Germany opposing it for most proposals. France has an intermediate position, leaning towards Italy. A breakdown of the results by party affiliation shows a more nuanced picture. For cross-country comparisons, we build a party indicator using the affiliation of national parties to European political groups. National MPs associated with the group of Socialists and Democrats (S&D) at the European level show strong support for the creation of new fiscal institutions and a new EU tax, and for risk sharing institutions (European Unemployment Insurance, Eurobonds). On the contrary, MPs associated with the European People’s Party (EPP) are mildly positive or against risk-sharing and fiscal institutions. National MPs affiliated to Renew Europe hold similar views to S&D MPs, but are less supportive of risk-sharing mechanisms. There is a substantial diversity of positions between the German AfD, the Italian Lega and the 5-star movement: the three parties have diverging views on the future of integration. Our econometric analysis shows that party affiliations have more explanatory power than nationality for all questions. This clearly shows that outcomes of national parliamentary elections could change the overall support for any issue.; Summary:The European economic union is incomplete, which makes it vulnerable to macroeconomic shocks. The opportunity to move forward in the integration process was highly debated even before the Covid-19 crisis.Yet the diverging views among countries and political groups are often considered as an obstacle on the path to required agreements for completing the Economic and Monetary Union (EMU). We present the results of a survey conducted in 2018 among members of national parliaments (MPs) in France, Germany and Italy on European integration in policy fields related to risk-sharing and budgetary institutions, asking for their opinion on proposals such as the creation of a European Unemployment Insurance (EUI), Eurobonds, or an EU tax. We find that nationality and political groups are key determinants of support for such proposals, the latter being the strongest. We describe how opinions are divided and try to identify policy proposals which could gather enough political support. The agreement reached on July 21st, 2020 at the last European summit includes financial transfers between States and the creation of Eurobonds, thus representing an important institutional move and an application of some of the reforms suggested by our survey. Yet what has been decided upon is only temporary and leaves open the question of the future of European integration.Key points: At first glance, the answers show diverging opinions on most questions between countries with Italy supporting more integration, and Germany opposing it for most proposals. France has an intermediate position, leaning towards Italy. A breakdown of the results by party affiliation shows a more nuanced picture. For cross-country comparisons, we build a party indicator using the affiliation of national parties to European political groups. National MPs associated with the group of Socialists and Democrats (S&D) at the European level show strong support for the creation of new fiscal institutions and a new EU tax, and for risk sharing institutions (European Unemployment Insurance, Eurobonds). On the contrary, MPs associated with the European People’s Party (EPP) are mildly positive or against risk-sharing and fiscal institutions. National MPs affiliated to Renew Europe hold similar views to S&D MPs, but are less supportive of risk-sharing mechanisms. There is a substantial diversity of positions between the German AfD, the Italian Lega and the 5-star movement: the three parties have diverging views on the future of integration. Our econometric analysis shows that party affiliations have more explanatory power than nationality for all questions. This clearly shows that outcomes of national parliamentary elections could change the overall support for any issue.

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  • Authors: Guibon, Gaël; Sagot, Benoît;

    Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at http://www.lrec-conf.org/proceedings/lrec2020/index.htmlThe version 2 of the paper is an updated version with regard to the originally published version (minor corrections).; International audience; In this paper we describe our work on the development and enrichment of OFrLex, a freely available, large-coverage morphological and syntactic Old French lexicon. We rely on several heterogeneous language resources to extract structured and exploitable information. The extraction follows a semi-automatic procedure with substantial manual steps to respond to difficulties encountered while aligning lexical entries from distinct language resources. OFrLex aims at improving natural language processing tasks on Old French such as part-of-speech tagging and dependency parsing. We provide quantitative information on OFrLex and discuss its reliability. We also describe and evaluate a semi-automatic, word-embedding-based lexical enrichment process aimed at increasing the accuracy of the resource. Results of this extension technique will be manually validated in the near future, a step that will take advantage of OFrLex's viewing, searching and editing interface, which is already accessible online.

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    Authors: Carastan dos Santos, Danilo; Rzadca, Krzysztof; Sousa, Leonel; Trystram, Denis;

    Conferencing is one of the main pillars of Computer Science research activity regarding career and networking, with conference publications playing a more pronounced role compared to other disciplines. The COVID-19 pandemic forced us to switch to virtual conferencing, and many works have shown the benefits of virtual conferencing in terms of inclusivity and reduction of Green House Gas emissions. We are moving toward the usual conferencing format as it appears that the pandemic is increasingly under control. However, the changes imposed during the period of the pandemic brought many essential lessons regarding conferencing social and environmental effects. A crucial task is to gather these community experiences to give directions on how to keep the learned lessons post-COVID-19. We used the Euro-Par conference to synthesize these lessons in the Computer Science case. We show practical results that reinforce the marginal emissions of virtual conferencing compared to in-person conference travel. We also open the debate that rethinking the conference utility according to our objectives (scientific and ecologic) and being aware of social/geographical biases are essential factors in participating and organizing post-COVID-19 conferences.

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    Authors: Coquidé, Célestin; Lages, José; Ermann, Leonardo; Shepelyansky, Dima;

    Using the United Nations Comtrade database, we perform the Google matrix analysis of the multiproduct World Trade Network (WTN) for the years 2018-2020 comprising the emergence of the COVID-19 as a global pandemic. The applied algorithms -- the PageRank, the CheiRank and the reduced Google matrix -- take into account the multiplicity of the WTN links providing new insights on the international trade comparing to the usual import-export analysis. These algorithms establish new rankings and trade balances of countries and products considering every countries on equal grounds, independently of their wealth, and every products on the basis of their relative exchanged volumes. In comparison with the pre-COVID-19 period, significant changes in these metrics occur for the year 2020 highlighting a major rewiring of the international trade flows induced by the COVID-19 pandemic crisis. We define a new PageRank-CheiRank product trade balance, either export or import oriented, which is significantly perturbed by the pandemic. Comment: 22 pages, 2 tables, 13 figures, 2 appendices

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    Authors: Christakis, Theodore; Bannelier-Christakis, Karine; Castelluccia, Claude; Le Métayer, Daniel;

    Part 1 of our “MAPping the use of Facial Recognition in public spaces in Europe” (MAPFRE) project reports explained in detail what “facial recognition” means, addressed the issues surrounding definitions, presented the political landscape and set out the exact material and geographical scope of the study. Part 2 of our Reports presented, in the most accessible way possible, how facial recognition works and produced a “Classification Table” with illustrations, explanations and examples, detailing the uses of facial recognition/analysis in public spaces, in order to help avoid conflating the diverse ways in which facial recognition is used and to bring nuance and precision to the public debate. This 3rd Report focuses on what is, undoubtedly, the most widespread way in which Facial Recognition Technologies (FRT) are used in public (and private) spaces: Facial Recognitionfor authorisation purposes.Facial recognition is often used to authorise access to a space (e.g. access control) or to a service (e.g. to make a payment). Depending on the situation, both verification and identi fication functionalities (terms that are explained in our 2nd Report) can be used. Millions of people use FRT to unlock their phones every day. Private entities (such as banks) or public authorities (such as the French government in terms of the now abandoned ALICEM pro ject) increasingly envisage using FRT as a means of providing strong authentication in or der to control access to private or public online services, such as e-banking, or administra tive websites that concern income, health or other personal matters. FRT is increasingly being considered as a means of improving security when controlling and managing access to private areas (building entrances, goods warehouses, etc.). In public spaces, FRT is being used as an authentication tool for automated international border controls (for example at airports) or to manage access in places as diverse as airports, stadiums or schools. Pre Covid-19, there were a lot of projects to use in the future FRT in order to “accelerate people flows”, “improve the customer experience”, “speed up opera tions” and “reduce queuing time” for users of different services (e.g. passengers boarding a plane or shopping) but the advent of the Covid-19 pandemic has further boosted calls for investment in FRTs in order to provide contactless services and reduce the risk of contam ination. Supermarkets, such as Carrefour, which was involved in a pilot project in Romania, or transport utilities in “smart cities”, such as the EMT bus network in Madrid, which teamed with Mastercard to conduct a pilot project that enables users to pay on EMT buses using FRT, have implemented facial recognition payment systems that permit consumers to complete transactions by simply having their faces scanned. In Europe, similar pilot pro jects are currently being tested enabling the management of payments in restaurants, cafés and shops. Despite this widespread existing use or projected use of FRT for authorisation purposes we are not aware of any detailed study that is focusing on this specific issue. We hope that the present analytic study will help fill this gap by focusing on the specific issue of the use of FRT for authorisation purposes in public spaces in Europe. We have examined in detail seven “emblematic” cases of FRT being used for authorisation purposes in public spaces in Europe. We have reviewed the documents disseminated by data controllers concerning all of these cases (and several others). We have sought out the reactions of civil society and other actors. We have dived into EU and Member State laws. We have analysed a number of Data Protection Authority (DPA) opinions. We have iden tified Court decisions of relevance to this matter.

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    Authors: Borau, Sylvie; Couprie, Hélène; Hopfensitz, Astrid;

    Single people are more likely to die from COVID-19. Here, we study whether this higher death rate could be partly explained by differences in compliance with protective health measures against COVID-19 between single and married people, and the drivers of this marital compliance gap. Data collected from 46,450 respondents in 67 countries reveal that married people are more likely to comply with protective measures than single people. This marital gap in compliance is higher for men (approximately 5%) than for women (approximately 2%). These results are robust across a large range of countries and independent of country level differences with respect to culture, values or infection rates. Prosocial characteristics linked to morality and social belonging explain more than 38% of the marital gap, while individual risk perceptions play a minor role. These findings help explain single people's and particularly single men's greater vulnerability to COVID-19, which in turn can be leveraged to improve the effectiveness of international public policy campaigns aimed at promoting protective health measures.

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    Authors: Roquencourt, Camille;

    L'analyse des composés organiques volatils (COVs) dans l'air expiré est une méthode non invasive prometteuse en médecine pour le diagnostic précoce, le phénotypage, le suivi de la maladie et du traitement et le dépistage à grande échelle. La spectrométrie de masse à temps de vol par réaction de transfert de protons (PTR-TOF-MS) présente un intérêt majeur pour l'analyse en temps réel des COVs et la découverte de nouveaux biomarqueurs. Le manque de méthodes et d'outils logiciels pour le traitement des données PTR-TOF-MS provenant de cohortes représente actuellement un verrou pour le développement de ces approches.Nous avons ainsi développé une suite d'algorithmes permettant le traitement des données brutes jusqu’au tableau des intensités des molécules détectées, grâce à la détection des expirations et des pics dans les spectres de masse, la quantification dans la dimension temporelle, l'alignement entre les échantillons et l'imputation des valeurs manquantes. Nous avons notamment mis au point un modèle innovant de déconvolution des pics en 2 dimensions reposant sur une régression du signal par splines pénalisées, ainsi qu'une méthode permettant de sélectionner spécifiquement les COVs dans l'air expiré. L'ensemble du processus est implémenté dans le paquet R/Bioconductor ptairMS, disponible en ligne. Nous avons validé notre approche à la fois sur des données expérimentales (mélange de COVs à des concentrations standardisées) et par simulation. Les résultats montrent que l'identification des COVs provenant de l’air expiré à partir du modèle proposé atteint une sensibilité de 99 `%. Une interface graphique a également été développée pour faciliter l'analyse des données et l'interprétation des résultats par les expérimentateurs (les cliniciens notamment). Nous avons appliqué notre méthodologie à la caractérisation de l'air expiré d'adultes sous ventilation mécanique atteints de l’infection COVID-19. Les analyses de l'air expiré de 40 patients atteints d’un syndrome de détresse respiratoire aiguë (SDRA) ont été effectuées quotidiennement, de l'entrée à la sortie de l'hôpital. Nous avons d'abord réalisé un modèle de classification pour prédire le statut de l'infection, en utilisant l'acquisition disponible la plus proche de l’admission à l'hôpital.Ce modèle permet de prédire le statut de l'infection avec une précision de 93%. Ensuite, nous avons utilisé toutes les données disponibles pour une analyse longitudinale de l'évolution des COVs en fonction de la durée de l'hospitalisation, en utilisant un modèle à effets mixtes. Après sélection de variables, quatre biomarqueurs de l'infection par le COVID-19 ont pu être identifiés. Ces résultats soulignent la valeur des données PTR-TOF-MS et du logiciel ptairMS pour la découverte de biomarqueurs dans l'air expiré. The analysis of Volatile Organic Compounds (VOCs) in exhaled breath is a promising non-invasive approach in medicine for early diagnosis, phenotyping, disease and treatment monitoring and large-scale screening. Proton Transfer Reaction Time-Of-Flight Mass Spectrometry (PTR-TOF-MS) is of major interest for the real time analysis of VOCs and the discovery of new biomarkers in the clinics. However, there is currently a lack of methods and software tools for the processing of PTR-TOF-MS data from cohorts.We therefore developed a suite of algorithms that process raw data from the patient acquisitions, and build the table of feature intensities, through expiration and peak detection, quantification, alignment between samples, and missing value imputation. Notably, we developed an innovative 2D peak deconvolution model based on penalized splines signal regression, and a method to specifically select the VOCs from exhaled breath. The full workflow is implemented in the freely available ptairMS R/Bioconductor package. Our approach was validated both on experimental data (mixture of VOCs at standardized concentrations) and simulations, which showed that the sensitivity for the identification of VOCs from exhaled breath reached 99 %. A graphical interface was also developed to facilitate data analysis and result interpretation by experimenters (e.g., clinicians).We applied our methodology to the characterization of exhaled breath from mechanically ventilated adults with COVID-19 infection. Analysis of exhaled breath from 28 patients with an acute respiratory distress syndrome (ARDS) and COVID-19 infection, and 12 patients with non-COVID-19 ARDS were performed daily from the hospital admission to the discharge. First, classification models were built to predict the status of the infection, using the closest available acquisition to the entry into hospital, and achieved high prediction accuracies (93 %). Then, all the available data acquired during the hospital stay were used for the longitudinal analysis of the VOCs evolution as a function of the hospitalization time by mixed-effects modeling. Following feature ranking and selection, four biomarkers of COVID-19 infection were identified. Altogether, these results highlight the value of the PTR-TOF-MS data and the ptairMS software for biomarker discovery in exhaled breath.

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    Authors: Milhaud, Xavier; Pommeret, Denys; Salhi, Yahia; Vandekerkhove, Pierre;

    In this paper, we consider two-component mixture distributions having one known component. This type of model is of particular interest when a known random phenomenon is contaminated by an unknown random effect. We propose in this setup to compare the unknown random sources involved in two separate samples. For this purpose, we introduce the so-called IBM (Inversion-Best Matching) approach resulting in a relaxed semiparametric Cramér-von Mises type two-sample test requiring very minimal assumptions (shape constraint free) about the unknown distributions. The accomplishment of our work lies in the fact that we establish a functional central limit theorem on the proportion parameters along with the unknown cumulative distribution functions of the model when Patra and Sen [22] prove that the √ n-rate cannot be achieved on these quantities in the basic one-sample case. An intensive numerical study is carried out from a large range of simulation setups to illustrate the asymptotic properties of our test. Finally, our testing procedure is applied to a real-life application through pairwise post-covid mortality effect testing across a panel of European countries. Nous considérons dans cet article des mélanges à deux composantes dont une composante est connue. Ces modèles sont d'un intérêt particulier lorsqu'un phénomène bien connu est affecté par une perturbation inconnue. Nous proposons de comparer les sources de cet impact inconnu entre deux échantillons distincts. Pour ce faire nous introduisons une nouvelle approche, appelée IBM (Inversion-Best Matching), qui permet d'effectuer le test à la manière d'un test de type Cramer-Von Mises sous très peu d'hypothèses concernant les aléas perturbateurs inconnus. Nous établissons un théorème central limite (TCL) fonctionnel sur les estimateurs que sont les proportions de chacun des modèles de contamination, ainsi que la fonction de répartition inconnue, là où Patra et Sen [22] n'obtenait pas de résultat asymptotique de type TCL. Des simulations permettent de valider la performance de la procédure de test et d'en valider ses propriétés asymptotiques. Enfin, nous appliquons notre stratégie de test à un problème concret de comparaison de déformation de la mortalité suite à la pandémie de Covid-19 à travers plusieurs pays européens.

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    Authors: Gallic, Ewen; Lubrano, Michel; Michel, Pierre;

    Uprising in China, the global COVID-19 epidemic soon started to spread out in Europe. As no medical treatment was available, it became urgent to design optimal non-pharmaceutical policies. With the help of a SIR model, we contrast two policies, one based on herd immunity (adopted by Sweden and the Netherlands), the other based on ICU capacity shortage. Both policies led to the danger of a second wave. Policy efficiency corresponds to the absence or limitation of a second wave. The aim of the paper is to measure the efficiency of these policies using statistical models and data. As a measure of efficiency, we propose the ratio of the size of two observed waves using a double sigmoid model coming from the biological growth literature. The Oxford data set provides a policy severity index together with observed number of cases and deaths. This severity index is used to illustrate the key features of national policies for ten European countries and to help for statistical inference. We estimate basic reproduction numbers, identify key moments of the epidemic and provide an instrument for comparing the two reported waves between January and October 2020. We reached the following conclusions. With a soft but long lasting policy, Sweden managed to master the first wave for cases thanks to a low R 0 , but at the cost of a large number of deaths compared to other Nordic countries and Denmark is taken as an example. We predict the failure of herd immunity policy for the Netherlands. We could not identify a clear sanitary policy for large European countries. What we observed was a lack of control for observed cases, but not for deaths.

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  • Authors: Etilé, Fabrice; Geoffard, Pierre-Yves;

    The COVID-19 outbreak has generated significant uncertainty about the future, especially for young adults. Health and economic threats, as well as more diffuse concerns about the consequences of COVID-19, can trigger feelings of anxiety, leading individuals to adopt uncertainty-reducing behaviours. We tested whether anxiety was associated with an increase in willingness to be exposed to the risk of COVID-19 infection (WiRE) using an online survey administered to 3,110 French individuals aged between 18 and 35 years old during the lockdown period (April 2020). Overall, 56.5% of the sample declared a positive WiRE. Unemployment was associated with a higher WiRE (+8.2 percentage points (pp); 95% CI +0.9-15.4 pp). One standard deviation increases in income (+1160€) and psychological state anxiety raised the WiRE by +2.7 pp (95% CI: +1.1-4.4 pp) and +3.9 pp (95% CI: +1.6-6.2 pp), respectively. A one standard deviation increase in perceived hospitalisation risk was associated with a -4.1 pp (95% CI: -6.2-2.1 pp) decrease in the WiRE. Overall, our results suggest that both the prospect of economic losses and psychological anxiety can undermine young adults’adherence to physical distancing recommendations. Public policies targeting young adults must consider both their economic situation and their mental health, and they must use uncertaintyreducingcommunication strategies.

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