EuReCa ONE—27 Nations, ONE Europe, ONE Registry A prospective one month analysis of out-of-hospital cardiac arrest outcomes in 27 countries in Europe

AbstractIntroductionThe aim of the EuReCa ONE study was to determine the incidence, process, and outcome for out of hospital cardiac arrest (OHCA) throughout Europe.MethodsThis was an international, prospective, multi-centre one-month study. Patients who suffered an OHCA during October 2014 who were attended and/or treated by an Emergency Medical Service (EMS) were eligible for inclusion in the study. Data were extracted from national, regional or local registries.ResultsData on 10,682 confirmed OHCAs from 248 regions in 27 countries, covering an estimated population of 174 million. In 7146 (66%) cases, CPR was started by a bystander or by the EMS. The incidence of CPR attempts ranged from 19.0 to 104.0 per 100,000 population per year. 1735 had ROSC on arrival at hospital (25.2%), Overall, 662/6414 (10.3%) in all cases with CPR attempted survived for at least 30 days or to hospital discharge.ConclusionThe results of EuReCa ONE highlight that OHCA is still a major public health problem accounting for a substantial number of deaths in Europe.EuReCa ONE very clearly demonstrates marked differences in the processes for data collection and reported outcomes following OHCA all over Europe. Using these data and analyses, different countries, regions, systems, and concepts can benchmark themselves and may learn from each other to further improve survival following one of our major health care events

Visual Contagions: extraire et tracer la circulation d'images dans des imprimés illustrés

International audienceLe projet Visual Contagions vise à pister la circulation internationale des images, à partir notamment d'un corpus mondial d'imprimés illustrés numérisés. Cet article présente la chaîne de pré-traitement des sources du projet, par laquelle sont récupérés des lots d'images proches visuellement-reproductions exactes, images similaires. C'est à partir des résultats de cette chaîne, croisés avec des métadonnées de dates et lieux de publication, qu'une étude sur le temps long et d'échelle mondiale devient possible. La première partie de l'article détaille quels choix algorithmiques ont été faits pour regrouper des illustrations par similarité ; la seconde partie décrit les outils mis en place pour récupérer des données (au format IIIF), extraire les images et les traiter automatiquement, et enfin permettre un post-traitement humain des résultats du classement algorithmique

New Algorithmic Approaches to Point Constellation Recogniti

Point constellation recognition is a common problem with many pattern matching applications. Whilst useful in many contexts, this work is mainly motivated by fingerprint matching. Fingerprints are traditionally modelled as constellations of oriented points called minutiae. The fingerprint verifier's task consists in comparing two point constellations. The compared constellations may differ by rotation and translation or by much more involved transforms such as distortion or occlusion. This paper presents three new constellation matching algorithms. The first two methods generalize an algorithm by Bringer and Despiegel. Our third proposal creates a very interesting analogy between mechanical system simulation and the constellation recognition problem

Spatially-consistent Feature Matching and Learning for Heritage Image Analysis

International audienceProgress in the digitization of cultural assets leads to online databases that become too large for a human to analyze. Moreover, some analyses might be challenging, even for experts. In this paper, we explore two applications of computer vision to analyze historical data: watermark recognition and one-shot repeated pattern detection in artwork collections. Both problems present computer vision challenges which we believe to be representative of the ones encountered in cultural heritage applications: limited supervision is available, the tasks are fine-grained recognition, and the data comes in several different modalities. Both applications are also highly practical, as recognizing watermarks makes it possible to date and locate documents, while detecting repeated patterns allows exploring visual links between artworks. We demonstrate on both tasks the benefits of relying on deep mid-level features. More precisely, we define an image similarity score based on geometric verification of mid-level features and show how spatial consistency can be used to fine-tune out-of-the-box features for the target dataset with weak or no supervision. This paper relates and extends our previous works. Our code and data are available at \url{http://imagine.enpc.fr/~shenx/HisImgAnalysis/}

La péninsule arabique aujourd’hui. Tome II

Voici le second tome de la péninsule Arabique d’aujourd’hui, ouvrage collectif s’adressant au public non spécialiste mais désireux de prendre une connaissance attentive de cette région du monde arabe, placée chaque jour au cœur de l’actualité économique, financière, stratégique, diplomatique et religieuse. Le tome I a tenté une présentation systématique de la péninsule prise dans son ensemble. Le tome II, Études par pays, offre, comme son nom l’indique, vingt-deux études sur les divers États de la péninsule Arabique. Elles sont regroupées en quatre ensembles : l’Arabie du Sud, le sultanat d’Oman, les États du Golfe et l’Arabie Saoudite. La présentation de chaque pays est accompagnée d’une carte et d’une chronologie, pour permettre au lecteur de le situer d’une orientation bibliographique. Nous espérons que ces études suggèreront la diversité géographique, historique, religieuse, économique et culturelle de cette région, une des plus mal connues du monde arabe