Bimodality and Latent Heat of Gold Nuclei

Peripheral collisions give access to a set of events where hot quasi-projectile (QP) sources are produced exploring a large range of excitation energy. In this range evaporation and multifragmentation are both observed for a similar charge/size of the sources. In this work, this experimental fact will be described in terms of coexistence of two classes of events in the first order phase transition formalism. For this, a detailed study of the experimental correlation between the size/charge of the biggest cluster/fragment (Z1) and the excitation energy (E*) is made. Making the parallel with the same correlation derived from the canonical ensemble description, a first value of the latent heat and boundaries of spinodal and coexistence zone are extracted.Comment: 7 page

What Can be Learned Studying the Distribution of the Biggest Fragment ?

In the canonical formalism of statistical physics, a signature of a first order phase transition for finite systems is the bimodal distribution of an order parameter. Previous thermodynamical studies of nuclear sources produced in heavy-ion collisions provide information which support the existence of a phase transition in those finite nuclear systems. Some results suggest that the observable Z1 (charge of the biggest fragment) can be considered as a reliable order parameter of the transition. This talk will show how from peripheral collisions studied with the INDRA detector at GSI we can obtain this bimodal behaviour of Z1. Getting rid of the entrance channel effects and under the constraint of an equiprobable distribution of excitation energy (E*), we use the canonical description of a phase transition to link this bimodal behaviour with the residual convexity of the entropy. Theoretical (with and without phase transition) and experimental Z1-E* correlations are compared. This comparison allows us to rule out the case without transition. Moreover that quantitative comparison provides us with information about the coexistence region in the Z1-E* plane which is in good agreement with that obtained with the signal of abnormal uctuations of configurational energy (microcanonical negative heat capacity).Comment: 8 page

zt: A Sofware Tool for Simple and Partial Mantel Tests

Different methods of data analysis (e.g. clustering and ordination) are based on distance matrices. In some cases, researchers may wish to compare several distance matrices with one another in order to test a hypothesis concerning a possible relationship between these matrices. However, this is not always self-evident. Usually, values in distance matrices are, in some way, correlated and therefore the usual assumption of independence between objects is violated in the classical tests approach. Furthermore, often, spurious correlations can be observed when comparing two distances matrices. A classic example is the comparison between genetic and environmental distances. Colonies that are in close proximity of each other tend to have similar environments and therefore there will be a positive correlation between environmental and geographical distances. Such colonies will also be more likely to exchange migrants so that genetic distances will be positively correlated with spatial distances. The consequence is that an observed positive association between genetic and environmental distances may be simply due to spatial effects. The most widely used method to account for distance correlations is a procedure known as the Mantel test (Mantel,'67; Mantel and Valand,'70 following the pioneering work of Daniels,'44 ; Daniels and Kendall'47). The simple Mantel test considers two matrices while an extension known as the partial Mantel test considers three matrices. These tools are widely used in different fields of research such as population genetics, ecology, anthropology, psychometrics and sociology.

Investigation of collective radial expansion and stopping in heavy ion collisions at Fermi energies

We present an analysis of multifragmentation events observed in central Xe+Sn reactions at Fermi energies. Performing a comparison between the predictions of the Stochastic Mean Field (SMF) transport model and experimental data, we investigate the impact of the compression-expansion dynamics on the properties of the final reaction products. We show that the amount of radial collective expansion, which characterizes the dynamical stage of the reaction, influences directly the onset of multifragmentation and the kinematic properties of multifragmentation events. For the same set of events we also undertake a shape analysis in momentum space, looking at the degree of stopping reached in the collision, as proposed in recent experimental studies. We show that full stopping is achieved for the most central collisions at Fermi energies. However, considering the same central event selection as in the experimental data, we observe a similar behavior of the stopping power with the beam energy, which can be associated with a change of the fragmentation mechanism, from statistical to prompt fragment emission.Comment: 15 page

MOOC Avion : une diffusion massive de l’expertise ISAE-SUPAERO

Le numérique révolutionne la façon de travailler, de collaborer, de communiquer ; il devait nécessairement transformer en profondeur la manière d’enseigner. L’ISAE-SUPAERO, acteur majeur du domaine de la formation aéronautique et spatiale au niveau national et international, accorde une place importante à l’innovation pédagogique pour l’ensemble des formations proposées. Dans ce contexte, le numérique constitue une opportunité permettant de diversifier les méthodes d’apprentissage utilisées dans les différentes formations ainsi que de former les étudiants à un usage professionnel de ces outils. L’essor des MOOCs au sein de l'établissement redessine peu à peu l’accès à la connaissance aéronautique et spatiale, pour qu'au-delà de nos propres étudiants, les salariés, les futurs étudiants et tous les passionnés d’aéronautique et d’espace puissent bénéficier du savoir-faire et de l'expertise de l'ISAE-SUPAERO. Pour son premier MOOC, l’ISAE-SUPAERO a décidé de poser la question simple et universelle : « Comment vole un avion ? » et d’y répondre par le « MOOC-Avion : introduction à la mécanique du vol ». Cet article propose un retour d’expérience sur la réalisation et la mise en œuvre de ce projet

Retour d’expérience sur le MOOC. Introduction à la mécanique du vol

Le premier MOOC de l’ISAE-SUPAERO “introduction à la mécanique du vol”, s’est déroulé du 26 janvier au 26 avril 2015. Quels enseignements peut-on en tirer ? Après en avoir rappelé les objectifs et le public initialement visé, nous présenterons les méthodes pédagogiques retenues et les choix techniques de production de contenu. En nous appuyant sur les données recueillies pendant la navigation et sur les échanges des forums, nous chercherons à comprendre qui étaient les apprenants, quels ont été leur comportement d’internaute et leur démarche d’apprentissage. Nous essaierons enfin de tirer les principaux enseignements de cette expérience et quelques facteurs clefs de succès d’un MOOC. The first ISAE-SUPAERO MOOC “introduction to flight mechanics”, has been de-livered from January 26th to April 26th 2015. What lessons can we draw from this experience ? After a word on the objectives and the audience targeted, we will introduce the pedagogical methodology chosen as well as the technical means used to actually produce contents. Relying on the data gathered from students navigation events as well as forum discussions, we will determine who were actually our students, what kind of behaviour they adopted when browsing the contents available, and what was their learning path. Eventually, we will extract the main lessons learned from this experiment and try to determine some success factors for a MOOC

Using convolutional neural networks for the classification of breast cancer images

In this study I compare different architectures of convolutional neural networks and different hardware acceleration devices for the detection of breast cancer from microscopic images of sentinel lymph nodes tissue. Convolutional models with increasing depth are trained and tested on a public data set of more than 300,000 images of lymph node tissue, on four different hardware acceleration cards, using an off-the-shelf deep learning framework. The impact of transfer learning, data augmentation and hyperparameters fine-tuning are also tested. Hardware acceleration device performance can improve training time by a factor of five to twelve, depending on the model used. On the other hand, increasing convolutional depth will augment the training time by a factor of four to six times, depending on the acceleration device used. Increasing the depth of the model, as could be expected, clearly improves performance, while data augmentation and transfer learning do not. Fine-tuning the hyperparameters of the model notably improves the results, with the best model showing a performance comparable to state-of-the-art models.Comment: 9 pages, 2 figures, 4 tables; corrected typos; added one more (recent) GPU car

Genetic studies in French Guiana populations: Synthesis

International audienceTwelve blood group and protein systems from a total of 819 individuals from six tribal groups (Apalaí-Wayana, Emerillon, Kaliña, Palikur Wayampi, and Wayana) living in French Guiana and Brazil were compared with each other and integrated with previous results from 17 other South Amerindian populations studied for the same genetic markers. Using correspondence analysis, map methodologies, and maximum linkage cluster analysis developed with the UPGMA method, we attempted to establish the genetic position of these tribes among South American Indians. Peripheral positions for the Emerillon and the Palikur were observed. Ethnohistorical data in French Guiana suggest that a strong founder effect for the former and endogamy for the latter could have generated the genetic differentiation of these two ethnic groups. However, when considered in a wider context, all French Guiana Natives cluster together in an intermediate position as compared with 17 other Amerindian groups studied for the comparison

New and emerging agents in the management of lipodystrophy in HIV-infected patients

Lipodystrophy remains a major long-term complication in human immunodeficiency virus-infected patients under antiretroviral (ARV) therapy. Patients may present with lipoatrophy or lipohypertrophy or both. The choice of treatments to improve fat redistribution depends on the form of lipodystrophy and its duration. Measures known to improve lipoatrophy are switches in ARV therapy (stavudine or zidovudine to abacavir or tenofovir) and filling interventions. Pioglitazone may be added to these measures, although any benefits appear small. Uridine and leptin were found to be disappointing so far. Regarding lipohypertrophy, diet and exercise, recombinant human growth hormone, and metformin may reduce visceral fat, but may worsen subcutaneous lipoatrophy. Surgical therapy may be required. Attractive pharmacologic treatments include growth hormone-releasing factor and leptin. Adiponectin and adiponectin receptors are promising therapeutic targets to explore