1,747 research outputs found
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
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
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)
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