From the Newton equation to the wave equation : the case of shock waves

We study the macroscopic limit of a chain of atoms governed by the Newton equation. It is known from the work of Blanc, Le Bris, Lions, that this limit is the solution of a nonlinear wave equation, as long as this solution remains smooth. We show, numerically and mathematically that, if the distances between particles remain bounded, it is not the case any more when there are shocks -at least for a convex nearest-neighbour interaction potential with convex derivative

New bounds for the inhomogenous Burgers and the Kuramoto-Sivashinsky equations

We give a substantially simplified proof of near-optimal estimate on the Kuramoto-Sivashinsky equation from [F. Otto, "Optimal bounds on the Kuramoto-Sivashinsky equation", JFA 2009], at the same time slightly improving the result. The result in the above cited paper relied on two ingredients: a regularity estimate for capillary Burgers and an a novel priori estimate for the inhomogeneous inviscid Burgers equation, which works out that in many ways the conservative transport nonlinearity acts as a coercive term. It is the proof of the second ingredient that we substantially simplify by proving a modified K\'arm\'an-Howarth-Monin identity for solutions of the inhomogeneous inviscid Burgers equation. This gives a new interpretation of the results obtained in [F. Golse, B. Perthame "Optimal regularizing effect for scalar conservation laws", Rev. Mat. Iber., 2013]

Isointense infant brain MRI segmentation with a dilated convolutional neural network

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation of white matter, gray matter and cerebrospinal fluid in infant brain MR images, as provided by the MICCAI grand challenge on 6-month infant brain MRI segmentation.Comment: MICCAI grand challenge on 6-month infant brain MRI segmentatio

Typologie des différents phénomènes dynamiques et méthodologie d'action

National audienceDans nos chantiers miniers, l'évolution vers le nouvel état d'équilibre est par nature discontinue du fait de la facturation (qui nous oblige à utiliser du soutènement) ; mais fort heureusement elle se fait généralement sous forme d'un grand nombre de petits sauts qui, intégrés à l'échelle de l'ouvrage, nous paraissent une évolution continue

Exploring the similarity of medical imaging classification problems

Supervised learning is ubiquitous in medical image analysis. In this paper we consider the problem of meta-learning -- predicting which methods will perform well in an unseen classification problem, given previous experience with other classification problems. We investigate the first step of such an approach: how to quantify the similarity of different classification problems. We characterize datasets sampled from six classification problems by performance ranks of simple classifiers, and define the similarity by the inverse of Euclidean distance in this meta-feature space. We visualize the similarities in a 2D space, where meaningful clusters start to emerge, and show that the proposed representation can be used to classify datasets according to their origin with 89.3\% accuracy. These findings, together with the observations of recent trends in machine learning, suggest that meta-learning could be a valuable tool for the medical imaging community

Experimental approaches towards therapeutic interventions for fragile X syndrome

Fragile X syndrome (FXS) is one of the most common inherited forms of intellectual disability. It affects on average 1/4000 males and 1/7000 females. FXS was described for the first time in 1943 by Martin and Bell. They reported a family with an inherited form of mental retardation that was linked to a sex chromosome, hence mainly males were affected. In 1969, the syndrome was linked to the X chromosome. Karyotyping of cells from patients revealed a fragile site at the end of the long arm of the X chromosome at position q27.3. Finally, the gene involved in FXS was discovered in 1991. It was called fragile X mental retardation 1 (FMR1) gene (Verkerk et al., 1991)

Antecedents of entrepreneurial orientation: A contingency approach

This research was created in order to offer a better understanding of the entrepreneurial orientation construct. Based on the literature review several antecedents of the entrepreneurial orientation construct were identified: risk, achievement, innovation, locus of control, self-esteem, opportunity, autonomy, proactiveness, and competitive aggressiveness. Relying on the contingency theory developed by Burns and Stalker (1961), it was decided to use the Carland\u27s trichotomy of entrepreneurs as a moderator variable between the antecedents and the entrepreneurial orientation construct. As a result, three main areas of research were identified. The first area deals with determining which dimensions are underpinning the entrepreneurial orientation construct, while the second is centered on the number of dimensions composing that construct. The third axis of research was to determine if there is a relationship between entrepreneurial orientation and performance. All things considered, 13 sets of hypothesis were created and tested for the research. The survey was sent through e-mail to entrepreneurs based in Louisiana, it was received by 1003 entrepreneurs. 103 surveys were returned for analysis resulting in a 10.2% response rate. After analyzing the results, it became clear that several different types of entrepreneurs exist and that these types are heterogeneous. The three types of entrepreneurs tested did not have the same number of antecedents or even the same kind of antecedents. Finally, only one type of entrepreneurs showed a significant, albeit negative, relationship between entrepreneurial orientation and performance