260 research outputs found
An Improved Observation Model for Super-Resolution under Affine Motion
Super-resolution (SR) techniques make use of subpixel shifts between frames
in an image sequence to yield higher-resolution images. We propose an original
observation model devoted to the case of non isometric inter-frame motion as
required, for instance, in the context of airborne imaging sensors. First, we
describe how the main observation models used in the SR literature deal with
motion, and we explain why they are not suited for non isometric motion. Then,
we propose an extension of the observation model by Elad and Feuer adapted to
affine motion. This model is based on a decomposition of affine transforms into
successive shear transforms, each one efficiently implemented by row-by-row or
column-by-column 1-D affine transforms.
We demonstrate on synthetic and real sequences that our observation model
incorporated in a SR reconstruction technique leads to better results in the
case of variable scale motions and it provides equivalent results in the case
of isometric motions
Polymorphic evolution sequence and evolutionary branching
We are interested in the study of models describing the evolution of a
polymorphic population with mutation and selection in the specific scales of
the biological framework of adaptive dynamics. The population size is assumed
to be large and the mutation rate small. We prove that under a good combination
of these two scales, the population process is approximated in the long time
scale of mutations by a Markov pure jump process describing the successive
trait equilibria of the population. This process, which generalizes the
so-called trait substitution sequence, is called polymorphic evolution
sequence. Then we introduce a scaling of the size of mutations and we study the
polymorphic evolution sequence in the limit of small mutations. From this study
in the neighborhood of evolutionary singularities, we obtain a full
mathematical justification of a heuristic criterion for the phenomenon of
evolutionary branching. To this end we finely analyze the asymptotic behavior
of 3-dimensional competitive Lotka-Volterra systems
Croissance du patudo (Thunnus obesus) de l'Océan Atlantique intertropical oriental
The growth of big eye tuna (Thunnus obesus) in the Eastern Tropical Atlantic Ocean was studied using Petersen's method, by the analysis of the length frequency data of the F.I.S. (French-Ivorian-Senegalese) surface tuna fleet from 1969 to 1977. The results are in agreement with a previous study by Champagnat and Pianet (1973) and with observations made in the Pacific Ocean
The monomer-dimer problem and moment Lyapunov exponents of homogeneous Gaussian random fields
We consider an "elastic" version of the statistical mechanical monomer-dimer
problem on the n-dimensional integer lattice. Our setting includes the
classical "rigid" formulation as a special case and extends it by allowing each
dimer to consist of particles at arbitrarily distant sites of the lattice, with
the energy of interaction between the particles in a dimer depending on their
relative position. We reduce the free energy of the elastic dimer-monomer (EDM)
system per lattice site in the thermodynamic limit to the moment Lyapunov
exponent (MLE) of a homogeneous Gaussian random field (GRF) whose mean value
and covariance function are the Boltzmann factors associated with the monomer
energy and dimer potential. In particular, the classical monomer-dimer problem
becomes related to the MLE of a moving average GRF. We outline an approach to
recursive computation of the partition function for "Manhattan" EDM systems
where the dimer potential is a weighted l1-distance and the auxiliary GRF is a
Markov random field of Pickard type which behaves in space like autoregressive
processes do in time. For one-dimensional Manhattan EDM systems, we compute the
MLE of the resulting Gaussian Markov chain as the largest eigenvalue of a
compact transfer operator on a Hilbert space which is related to the
annihilation and creation operators of the quantum harmonic oscillator and also
recast it as the eigenvalue problem for a pantograph functional-differential
equation.Comment: 24 pages, 4 figures, submitted on 14 October 2011 to a special issue
of DCDS-
Distinct roles of Hoxa2 and Krox20 in the development of rhythmic neural networks controlling inspiratory depth, respiratory frequency, and jaw opening
<p>Abstract</p> <p>Background</p> <p>Little is known about the involvement of molecular determinants of segmental patterning of rhombomeres (r) in the development of rhythmic neural networks in the mouse hindbrain. Here, we compare the phenotypes of mice carrying targeted inactivations of <it>Hoxa2</it>, the only <it>Hox </it>gene expressed up to r2, and of <it>Krox20</it>, expressed in r3 and r5. We investigated the impact of such mutations on the neural circuits controlling jaw opening and breathing in newborn mice, compatible with Hoxa2-dependent trigeminal defects and direct regulation of <it>Hoxa2 </it>by Krox20 in r3.</p> <p>Results</p> <p>We found that <it>Hoxa2 </it>mutants displayed an impaired oro-buccal reflex, similarly to <it>Krox20 </it>mutants. In contrast, while <it>Krox20 </it>is required for the development of the rhythm-promoting parafacial respiratory group (pFRG) modulating respiratory frequency,<it> Hoxa2 </it>inactivation did not affect neonatal breathing frequency. Instead, we found that <it>Hoxa2</it><sup>-/- </sup>but not <it>Krox20</it><sup>-/- </sup>mutation leads to the elimination of a transient control of the inspiratory amplitude normally occurring during the first hours following birth. Tracing of r2-specific progenies of <it>Hoxa2 </it>expressing cells indicated that the control of inspiratory activity resides in rostral pontine areas and required an intact r2-derived territory.</p> <p>Conclusion</p> <p>Thus, inspiratory shaping and respiratory frequency are under the control of distinct <it>Hox</it>-dependent segmental cues in the mammalian brain. Moreover, these data point to the importance of rhombomere-specific genetic control in the development of modular neural networks in the mammalian hindbrain.</p
Super-resolution in map-making based on a physical instrument model and regularized inversion. Application to SPIRE/Herschel
We investigate super-resolution methods for image reconstruction from data
provided by a family of scanning instruments like the Herschel observatory. To
do this, we constructed a model of the instrument that faithfully reflects the
physical reality, accurately taking the acquisition process into account to
explain the data in a reliable manner. The inversion, ie the image
reconstruction process, is based on a linear approach resulting from a
quadratic regularized criterion and numerical optimization tools. The
application concerns the reconstruction of maps for the SPIRE instrument of the
Herschel observatory. The numerical evaluation uses simulated and real data to
compare the standard tool (coaddition) and the proposed method. The inversion
approach is capable to restore spatial frequencies over a bandwidth four times
that possible with coaddition and thus to correctly show details invisible on
standard maps. The approach is also applied to real data with significant
improvement in spatial resolution.Comment: Astronomy & Astrophysic
Stochasticity in the adaptive dynamics of evolution: The bare bones
First a population model with one single type of individuals is considered. Individuals reproduce asexually by splitting into two, with a population-size-dependent probability. Population extinction, growth and persistence are studied. Subsequently the results are extended to such a population with two competing morphs and are applied to a simple model, where morphs arise through mutation. The movement in the trait space of a monomorphic population and its possible branching into polymorphism are discussed. This is a first report. It purports to display the basic conceptual structure of a simple exact probabilistic formulation of adaptive dynamics
3D Fluid Flow Estimation with Integrated Particle Reconstruction
The standard approach to densely reconstruct the motion in a volume of fluid
is to inject high-contrast tracer particles and record their motion with
multiple high-speed cameras. Almost all existing work processes the acquired
multi-view video in two separate steps, utilizing either a pure Eulerian or
pure Lagrangian approach. Eulerian methods perform a voxel-based reconstruction
of particles per time step, followed by 3D motion estimation, with some form of
dense matching between the precomputed voxel grids from different time steps.
In this sequential procedure, the first step cannot use temporal consistency
considerations to support the reconstruction, while the second step has no
access to the original, high-resolution image data. Alternatively, Lagrangian
methods reconstruct an explicit, sparse set of particles and track the
individual particles over time. Physical constraints can only be incorporated
in a post-processing step when interpolating the particle tracks to a dense
motion field. We show, for the first time, how to jointly reconstruct both the
individual tracer particles and a dense 3D fluid motion field from the image
data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian
model reconstructs individual particles, and at the same time recovers a dense
3D motion field in the entire domain. Making particles explicit greatly reduces
the memory consumption and allows one to use the high-res input images for
matching. Whereas the dense motion field makes it possible to include physical
a-priori constraints and account for the incompressibility and viscosity of the
fluid. The method exhibits greatly (~70%) improved results over our recently
published baseline with two separate steps for 3D reconstruction and motion
estimation. Our results with only two time steps are comparable to those of
sota tracking-based methods that require much longer sequences.Comment: To appear in International Journal of Computer Vision (IJCV
Patient/family views on data sharing in rare diseases: study in the European LeukoTreat project.: Survey assessing data sharing in leukodystrophies
International audienceThe purpose of this study was to explore patient and family views on the sharing of their medical data in the context of compiling a European leukodystrophies database. A survey questionnaire was delivered with help from referral centers and the European Leukodystrophies Association, and the questionnaires returned were both quantitatively and qualitatively analyzed. This study found that patients/families were strongly in favor of participating. Patients/families hold great hope and trust in the development of this type of research. They have a strong need for information and transparency on database governance, the conditions framing access to data, all research conducted, partnerships with the pharmaceutical industry, and they also need access to results. Our findings bring ethics-driven arguments for a process combining initial broad consent with ongoing information. On both, we propose key item-deliverables to database participants
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