Les gares TGV dans les zones périurbaines des villes moyennes sont-elles des vecteurs de métropolisation ?

19 p Article proposé aux les Cahiers scientifiques des transports Appel à contribution au dossier thématique (N° 63/2013) " TGV et villes petites et moyennes : les enseignements d'études de cas en Europe "International audienceCet article s'interroge sur la manière dont les nouvelles gares TGV installées en bordure d'agglomération de taille moyenne prennent place dans le processus de métropolisation qui structure la hiérarchie urbaine. Plus précisément, il cherche à préciser une méthodologie adaptée à cette question dans un contexte de villes moyennes pour servir de cadre à une proposition de recherche

Simultaneous Epicardial and Noncontact Endocardial Mapping of the Canine Right Atrium: Simulation and Experiment

Epicardial high-density electrical mapping is a well-established experimental instrument to monitor in vivo the activity of the atria in response to modulations of the autonomic nervous system in sinus rhythm. In regions that are not accessible by epicardial mapping, noncontact endocardial mapping performed through a balloon catheter may provide a more comprehensive description of atrial activity. We developed a computer model of the canine right atrium to compare epicardial and noncontact endocardial mapping. The model was derived from an experiment in which electroanatomical reconstruction, epicardial mapping (103 electrodes), noncontact endocardial mapping (2048 virtual electrodes computed from a 64-channel balloon catheter), and direct-contact endocardial catheter recordings were simultaneously performed in a dog. The recording system was simulated in the computer model. For simulations and experiments (after atrio-ventricular node suppression), activation maps were computed during sinus rhythm. Repolarization was assessed by measuring the area under the atrial T wave (ATa), a marker of repolarization gradients. Results showed an epicardial-endocardial correlation coefficients of 0.80 and 0.63 (two dog experiments) and 0.96 (simulation) between activation times, and a correlation coefficients of 0.57 and 0.46 (two dog experiments) and 0.92 (simulation) between ATa values. Despite distance (balloon-atrial wall) and dimension reduction (64 electrodes), some information about atrial repolarization remained present in noncontact signals

Les Écrins, un territoire d’altitude dans le contexte des Alpes occidentales de la Préhistoire récente à l’âge du Bronze (Hautes-Alpes, France)

Les premiers témoignages d’une présence humaine en altitude reconnus dans les Alpes méridionales françaises, dès la Préhistoire, s’inscrivent au sein de travaux pluridisciplinaires et diachroniques menés, depuis 1998, sur le peuplement et les activités humaines en moyenne et haute montagne. Développés plus particulièrement sur les hauts massifs de l’Argentiérois/Vallouise et du Champsaur dans le Parc National des Écrins (Hautes-Alpes), ces programmes corrèlent sur le terrain données archéologiques et paléoécologiques d’altitude. Dès la seconde moitié du iiie millénaire et au cours du iie millénaire BC (fin du Néolithique-âge du Bronze), se distinguent des structures bâties à vocation pastorale, entre 2 067 et 2 360 m d’altitude, en relation avec l’essor démographique observé dans les zones basses. L’occupation de la haute montagne durant cette période paraît continue et le milieu, exploité de manière durable.The earliest evidence for a prehistoric human presence identified in the Southern French Alps has been revealed by a multidisciplinary, diachronic research project that started in 1998. This research assesses the natural and social dynamics of occupation in the sub-alpine and alpine zones. This work is focussed on the high mountains of the Argentiérois/Vallouise and Champsaur areas in the Parc National des Écrins (Hautes-Alpes), and combines archaeological and palaeoenvironmental evidence. The second half of the IIIrd millennium BC and during the IInd millennium BC (the Late Neolithic and Bronze Age) is marked by the appearance of the built pastoral structures between 2067 and 2360m, related to the development and increase in populations at lower altitudes. This high altitude activity appears to be continuous and sustainable throughout these periods

FORECASTOR -- I. Finding Optics Requirements and Exposure times for the Cosmological Advanced Survey Telescope for Optical and UV Research mission

The Cosmological Advanced Survey Telescope for Optical and ultraviolet Research (CASTOR) is a proposed Canadian-led 1m-class space telescope that will carry out ultraviolet and blue-optical wide-field imaging, spectroscopy, and photometry. CASTOR will provide an essential bridge in the post-Hubble era, preventing a protracted UV-optical gap in space astronomy and enabling an enormous range of discovery opportunities from the solar system to the nature of the Cosmos, in conjunction with the other great wide-field observatories of the next decade (e.g., Euclid, Roman, Vera Rubin). FORECASTOR (Finding Optics Requirements and Exposure times for CASTOR) will supply a coordinated suite of mission-planning tools that will serve as the one-stop shop for proposal preparation, data reduction, and analysis for the CASTOR mission. We present the first of these tools: a pixel-based, user-friendly, extensible, multi-mission exposure time calculator (ETC) built in Python, including a modern browser-based graphical user interface that updates in real time. We then provide several illustrative examples of FORECASTOR's use that advance the design of planned legacy surveys for the CASTOR mission: a search for the most massive white dwarfs in the Magellanic Clouds; a study of the frequency of flaring activity in M stars, their distribution and impacts on habitability of exoplanets; mapping the proper motions of faint stars in the Milky Way; wide and deep galaxy surveys; and time-domain studies of active galactic nuclei.Comment: Updated references and acknowledgements to match published version. 24 pages, 16 figures, 3 tables, published in A

Transport processes in stars: diffusion, rotation, magnetic fields and internal waves

In this paper, I explore various transport processes that have a large impact of the distribution of elements inside stars and thus, on stellar evolution. A heuristic description of the physics behind equations is provided, and key references are given. Finally, for each process, I will briefly review (some) important results as well as discuss directions for future work.Comment: 50 pages, proceedings of the Aussois school "Stellar Nucleosynthesis: 50 years after B2FH

The Unexpected Kinematics of Multiple Populations in NGC 6362: Do Binaries Play a Role?

We present a detailed analysis of the kinematic properties of the multiple populations (MPs) in the low-mass Galactic globular cluster (GC) NGC 6362 based on a sample of about 500 member stars for which radial velocities (RVs), and Fe and Na abundances have been homogeneously derived. At distances from the cluster center larger than about 0.5r h , we find that first-generation (FG–Na-poor) and second-generation (SG–Na-rich) stars show hints of different line-of-sight velocity dispersion profiles, with FG stars being dynamically hotter. This is the first time that differences in the velocity dispersion of MPs are detected using only RVs. While kinematic differences between MPs in GCs are usually described in terms of anisotropy differences driven by the different radial distributions, this explanation hardly seems viable for NGC 6362, where SG and FG stars are spatially mixed. We demonstrate that the observed difference in the velocity dispersion profiles can be accounted for by the effect of binary stars. In fact, thanks to our multi-epoch RV measurements, we find that the binary fraction is significantly larger in the FG sample (f ~ 14%) than in the SG population (f < 1%), and we show that such a difference can inflate the velocity dispersion of FG with respect to SG by the observed amount in the relevant radial range. Our results nicely match the predictions of state-of-the art N-body simulations of the co-evolution of MPs in GCs that include the effects of binaries

Geometric and algebraic classification of quadratic differential systems with invariant hyperbolas

Let QSH be the whole class of non-degenerate planar quadratic differential systems possessing at least one invariant hyperbola. We classify this family of systems, modulo the action of the group of real affine transformations and time rescaling, according to their geometric properties encoded in the configurations of invariant hyperbolas and invariant straight lines which these systems possess. The classification is given both in terms of algebraic geometric invariants and also in terms of affine invariant polynomials and it yields a total of 205 distinct such configurations. We have 162 configurations for the subclass QSH(η>0) of systems which possess three distinct real singularities at infinity, and 43 configurations for the subclass QSH(η=0) of systems which possess either exactly two distinct real singularities at infinity or the line at infinity filled up with singularities. The algebraic classification, based on the invariant polynomials, is also an algorithm which makes it possible to verify for any given real quadratic differential system if it has invariant hyperbolas or not and to specify its configuration of invariant hyperbolas and straight lines

Genetic diversity in Mediterranean Brassica vegetables: seed phenotyping could be useful for sustainable crop production

The European BrasExplor project aims to explore the genetic diversity present in two economically important Brassica crop species, Brassica oleracea and B. rapa, for sustainable crop production. This diversity is present in wild populations but also in cultivated landraces and has been shaped by contrasting environments. An international consortium of 11 partners has begun to collect and multiply wild populations extending from the French North Atlantic coast to the southern Algerian desert as well as local cultivars from 6 contributing countries in order to characterize the genetic diversity available over a wide soil-climate gradient. A total of 100 populations has been obtained for each species. Identifying the genetic variation and understanding the basis for it will allow the development of breeding strategies for a better adaptation of turnip (Brassica rapa) and cabbage (Brassica oleracea var. capitata) to climate change. One third of the collection has been already phenotyped for its germination traits of native seeds harvested in 2020 for wild populations or of local landraces provided by farmers and seed banks. In favourable conditions, a high diversity in germination capacity and germination rate was observed independently of seed age. The two species have a different germination profile: some turnip seeds can stand higher temperature and lower water potential than most cabbage seeds. Variation in flowering time has also been documented in these plants.We are grateful to Benjamin Foltran for his contribution to the project during his internship, Anne-Sophie Grenier for her input in communication and project website. We also thank Hakima Arrar, Fariza Boussad, Thouraya Rhim, Ilahy Riadh who are involved in field phenotyping. BrasExplor project is funded by the PRIMA programme supported under Horizon ? ? ? ? the European Union’s framework programme for research and innovation.Peer reviewe

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches