Thermo-Mechanical Adjustment after Impacts during Planetary Growth

The thermal evolution of planets during their growth is strongly influenced by impact heating. The temperature increase after a collision is mostly located next to the shock. For Moon to Mars size planets where impact melting is limited, the long term thermo-mechanical readjustment is driven by spreading and cooling of the heated zone. To determine the time and length scales of the adjustment, we developed a numerical model in axisymmetric cylindrical geometry with variable viscosity. We show that if the impactor is larger than a critical size, the spherical heated zone isothermally flattens until its thickness reaches a value for which motionless thermal diffusion becomes more effective. The thickness at the end of advection depends only on the physical properties of the impacted body. The obtained timescales for the adjustment are comparable to the duration of planetary accretion and depend mostly on the physical properties of the impacted body

Using morphological description for generic sound retrieval

Systems for sound retrieval are usually “source-centred”. This means that retrieval is based on using the proper keywords that define or specify a sound source. Although this type of description is of great interest, it is very difficult to implement it into realistic automatic labelling systems because of the necessity of dealing with thousands of categories, hence with thousands of different sound models. Moreover, digitally synthesised or transformed sounds, which are frequently used in most of the contemporary popular music, have no identifiable sources. We propose a description framework, based on Schaeffer’s research on a generalised solfeggio which could be applied to any type of sounds. He defined some morphological description criteria, based on intrinsic perceptual qualities of sound, which doesn’t refer to the cause or the meaning of a sound. We describe more specifically experiments on automatic extraction of morphological descriptors

Cross-validation of ELISA and a portable surface plasmon resonance instrument for IgG antibody serology with SARS-CoV-2 positive individuals.

We report on the development of surface plasmon resonance (SPR) sensors and matching ELISAs for the detection of nucleocapsid and spike antibodies specific to the novel coronavirus 2019 (SARS-CoV-2) in human serum, plasma and dried blood spots (DBS)

ClimateBench v1.0: A benchmark for data-driven climate projections

Many different emission pathways exist that are compatible with the Paris climate agreement, and many more are possible that miss that target. While some of the most complex Earth System Models have simulated a small selection of Shared Socioeconomic Pathways, it is impractical to use these expensive models to fully explore the space of possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate response to a given scenario. Here we present ClimateBench - a benchmarking framework based on a suite of CMIP, AerChemMIP and DAMIP simulations performed by a full complexity Earth System Model, and a set of baseline machine learning models that emulate its response to a variety of forcers. These emulators can predict annual mean global distributions of temperature, diurnal temperature range and precipitation (including extreme precipitation) given a wide range of emissions and concentrations of carbon dioxide, methane and aerosols, allowing them to efficiently probe previously unexplored scenarios. We discuss the accuracy and interpretability of these emulators and consider their robustness to physical constraints such as total energy conservation. Future opportunities incorporating such physical constraints directly in the machine learning models and using the emulators for detection and attribution studies are also discussed. This opens a wide range of opportunities to improve prediction, consistency and mathematical tractability. We hope that by laying out the principles of climate model emulation with clear examples and metrics we encourage others to tackle this important and demanding challenge

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

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P &lt; 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Indexation et recherche d'objets 3D à partir de requêtes 2D et 3D

The increasing use of Computer-Aided Design (CAD) tools last decades has lead to huge 3D-model databases that still have to be correctly indexed. The context of this work is the content-based retrieval of images or models. We are interested in both 2D images and 3D-models indexing. We aim at extracting shape descriptors from images or models that allow to compute a similarity measure between them. We present two approaches. On the one hand retrieving a 3D-model from a 2D image-based query (called 2D/3D) and on the other hand, retrieving a 3D-modelfrom another one (called 3D/3D).The first part is dedicated to the 2D/3D approach. First, we generalize the 2D shape descriptor ART (Angular Radial Transform) by making it robust to rotationand viewpoint-based deformations. In a second time, we propose a view-based approach that describes a 3D-model with a set of 2D views. More precisely, we compute for each model a set of views that are indexed by a 2D shape descriptor. This 2D/3D method is dynamic and adaptive to the complexity of both the 3D-model and the request. For a dynamic comparison we need a fast process for view extraction as it will be repeated a number of times. That is why we introduce a new spectral representation that characterizes all views from a given 3D-model.In the second part of this work, we proposed a new fast 3D shape descriptor to index huge databases. The great number of 3D-models from the database imposes the use of a very compact shape descriptor. This one should contain maximum information in a minimum size to guarantee fast answer. We propose a 3D extension from ART called 3D Angular Radial Transform (3D ART). The latter has a strong descriptions capacity while keeping the 2D-ART robustness to deformations.Depuis l'émergence de la Conception Assisté par Ordinateurs (CAO), l'archivage, la structuration et la recherche dans des bases de modèles 3D constituent des domaines de recherche privilégiés. Cette thèse s'inscrit dans ce cadre, et plus généralement, dans la recherche d'information par le contenu. Dans ce contexte, nous nous intéressons plus particulièrement à l'indexation d'objets tridimensionnels, qui a pour objectif de caractériser la forme des objets, pour permettre de calculer des distances de similarité entre modèles. Pour cela, deux types d'approches ont été étudiées : les approches 3D/3D, comparant les objets entre eux et les approches 2D/3D, comparant les objets 3D à une image. La première partie de la thèse est consacrée à l'étude des descripteurs de forme 2D et 2D/3D. D'une part, nous avons généralisé le descripteur de forme 2D : Angular Radial Transform (ART), pour le rendre applicable sur les images couleurs et robuste aux déformation perspective. Dans un deuxième temps, nous avons étudié les approches 2D/3D, qui permettent de rechercher un objet 3D à partir d'une image 2D. La méthode d'indexation 2D/3D que nous proposons est une méthode dynamique qui compare directement l'image requête à l'objet 3D et s'adapte aux complexités de l'objet 3D et de la requête. Notre système se base sur un système de représentation spectral des vues de l'objet, permettant d'extraire rapidement les vues et de mettre en place une recherche dynamique de la vue requête. La deuxième partie de la thèse porte sur l'indexation d'objets 3D. Pour indexer des grandes bases, nous avons réalisé une extension de la transformation ART en 3D, appelé : 3D Angular Radial Transform (3D ART). Ce descripteur possède un fort pouvoir de description, en gardant les propriétés de robustesse d'ART 2D. Pour permettre d'appréhender des grandes bases d'objets 3D, nous proposons également un système de navigation permettant de structurer les bases

Tutor: Dr. Xavier Serra

Towards computational morphological description of sound b