Sharp template estimation in a shifted curves model

This paper considers the problem of adaptive estimation of a template in a randomly shifted curve model. Using the Fourier transform of the data, we show that this problem can be transformed into a stochastic linear inverse problem. Our aim is to approach the estimator that has the smallest risk on the true template over a finite set of linear estimators defined in the Fourier domain. Based on the principle of unbiased empirical risk minimization, we derive a nonasymptotic oracle inequality in the case where the law of the random shifts is known. This inequality can then be used to obtain adaptive results on Sobolev spaces as the number of observed curves tend to infinity. Some numerical experiments are given to illustrate the performances of our approach

Intensity estimation of non-homogeneous Poisson processes from shifted trajectories

This paper considers the problem of adaptive estimation of a non-homogeneous intensity function from the observation of n independent Poisson processes having a common intensity that is randomly shifted for each observed trajectory. We show that estimating this intensity is a deconvolution problem for which the density of the random shifts plays the role of the convolution operator. In an asymptotic setting where the number n of observed trajectories tends to infinity, we derive upper and lower bounds for the minimax quadratic risk over Besov balls. Non-linear thresholding in a Meyer wavelet basis is used to derive an adaptive estimator of the intensity. The proposed estimator is shown to achieve a near-minimax rate of convergence. This rate depends both on the smoothness of the intensity function and the density of the random shifts, which makes a connection between the classical deconvolution problem in nonparametric statistics and the estimation of a mean intensity from the observations of independent Poisson processes

Intensity estimation of non-homogeneous Poisson processes from shifted trajectories

In this paper, we consider the problem of estimating nonparametrically a mean pattern intensity λ from the observation of n independent and non-homogeneous Poisson processes N1,…,Nn on the interval [0,1]. This problem arises when data (counts) are collected independently from n individuals according to similar Poisson processes. We show that estimating this intensity is a deconvolution problem for which the density of the random shifts plays the role of the convolution operator. In an asymptotic setting where the number n of observed trajectories tends to infinity, we derive upper and lower bounds for the minimax quadratic risk over Besov balls. Non-linear thresholding in a Meyer wavelet basis is used to derive an adaptive estimator of the intensity. The proposed estimator is shown to achieve a near-minimax rate of convergence. This rate depends both on the smoothness of the intensity function and the density of the random shifts, which makes a connection between the classical deconvolution problem in nonparametric statistics and the estimation of a mean intensity from the observations of independent Poisson processes

La fortification du Frankenbourg à Neubois (Bas-Rhin)

Rapport de la deuxième campagne de fouille sur la fortification du Frankenbourg (67

Heat Transport Through Plasmonic Interactions in Closely Spaced Metallic Nanoparticles Chains

We report a numerical investigation on the heat transfer through one dimensional arrays of metallic nanoparticles closely spaced in a host material. Our simulations show that the multipolar interactions play a crucial role in the heat transport via collective plasmons. Calculations of the plasmonic thermal conductance and of the thermal conductivity in ballistic and diffusive regime, respectively have been carried out. (a) Using the Landauer-Buttiker formalism we have found that, when the host material dielectric constant takes positive values, the multipolar interactions drastically enhance by several order of magnitude the ballistic thermal conductance of collective plasmons compared with that of a classical dipolar chain. On the contrary, when the host material dielectric constant takes negative values, we have demonstrated the existence of non-ballistic multipolar modes which annihilate the heat transfer through the chains. (b) Using the kinetic theory we have also examined the thermal behavior of chains in the diffusion approximation. We have shown that the plasmonic thermal conductivity of metallic nanoparticle chains can reach 1% of the bulk metal thermal conductivity . This result could explain the anomalously high thermal conductivity observed in many collo\"idal suspensions, the so called nanofluids.Comment: 10 pages, PR

Turning bacteria suspensions into a "superfluid"

The rheological response under simple shear of an active suspension of Escherichia coli is determined in a large range of shear rates and concentrations. The effective viscosity and the time scales characterizing the bacterial organization under shear are obtained. In the dilute regime, we bring evidences for a low shear Newtonian plateau characterized by a shear viscosity decreasing with concentration. In the semi-dilute regime, for particularly active bacteria, the suspension display a "super-fluid" like transition where the viscous resistance to shear vanishes, thus showing that macroscopically, the activity of pusher swimmers organized by shear, is able to fully overcome the dissipative effects due to viscous loss

Engineering Parallel Transmit/Receive Radio-Frequency Coil Arrays for Human Brain MRI at 7 Tesla

Magnetic resonance imaging is widely used in medical diagnosis to obtain anatomical details of the human body in a non-invasive way. Clinical MR scanners typically operate at a static magnetic field strength (B0) of 1.5T or 3T. However, going to higher field is of great interest since the signal-to-noise ratio is proportional to B0. Therefore, higher image resolution and better contrast between the human tissues could be achieved. Nevertheless, new challenges arise when increasing B0. The wavelength associated with the radio-frequency field B1+ has smaller dimensions - approx. 12 cm for human brain tissues - than the human brain itself (20 cm in length), the organ of interest in this thesis. The main consequence is that the transmit field distribution pattern (B1+) is altered and the final MR images present bright and dark signal spots. These effects prevent the ultra-high field MR scanners (>= 7T) to be used for routine clinical diagnosis. Parallel-transmit is one approach to address these new challenges. Instead of using an RF coil connected to a single power input as it is commonly done at lower magnetic fields, multiple RF coils are used with independent power inputs. The subsequent distinct RF signals can be manipulated separately, which provides an additional degree of freedom to generate homogeneous B1+-field distributions over large or specific regions in the human body. A transmit/receive RF coil array optimized for whole-brain MR imaging was developed and is described in this thesis. Dipoles antennas were used since they could provide a large longitudinal (vertical axis-head to neck) coverage and high transmit field efficiency. Results demonstrated a complete coverage of the human brain, and particularly high homogeneity over the cerebellum. However, since the receive sensitivity over large field-of-views is related to the number of channels available to detect the NMR signal, the next work was to add a 32-channel receive loop coil array to the transmit coil array. The complete coverage of the human brain was assessed with a substantial increase in signal-to-noise compared to the transmit/receive dipole coil array alone. Moreover, acquisition time was shortened since higher acceleration factors could be used. To optimize the individual RF fields and generate an homogeneous B1+-field, a method was developed making use of the particle-swarm algorithm. A user-friendly graphical interface was implemented. Good homogeneity could be achieved over the whole-brain after optimization with the coil array built in this study. Moreover, the optimization was shown to be robust across multiple subjects. The last project was focused on the single transmit system. Local volume coils (single transmit) present pronounced transmit field inhomogeneities in specific regions of the human brain such as the temporal lobes. A widely used approach to address locally these challenges is to add dielectric pads inside the volume coils to enhance the local transmit field efficiency. It was shown in this thesis that constructing dedicated surface coils is a valuable alternative to the dielectric pads in terms of transmit field efficiency and MR spectroscopy results. Two RF coil setups were developed for the temporal and frontal lobes of the human brain, respectively. This thesis provides extensive insight on MR engineering of RF coils at ultra-high field and the potential of parallel-transmit to address the future needs in clinical applications

Impacts de le récupération des eaux pluviales sur le régime hydrologique de petits bassins versants partiellement urbanisés

International audienceRainwater harvesting is a relevant and sustainable solution to reduce the pressure on conventional water resources. Rainwater harvesting techniques can as well provide stormwater management benefits through the reduction of runoff volumes. The impact of a wide implementation of these practices on the hydrological regimes of already disturbed catchments however remains unclear. The capture of significant fraction of runoff volume in urbanized areas to satisfy various uses, could in particular result in an over-extraction of water, exacerbating low streamflow issues. In this study, a method associating geodata processing and allotment-scale hydrological modeling is introduced to investigate the impact of rainwater harvesting on the hydrology of two semi-urban catchments, addressing both stormwater management benefits and low-flow effects. Results indicate that rainwater harvesting alone is unlikely to meet usual runoff-control objectives, but as well suggest that a systematic implementation of these practices on upstream catchments that already face low water flow issues might be detrimental to stream health.La récupération des eaux de pluie suscite aujourd'hui un intérêt croissant du fait des incertitudes sur la disponibilité future des ressources en eau. Celle-ci est par ailleurs fréquemment envisagée comme un moyen de limiter à la source les volumes de ruissellement générés niveau des surfaces revêtues, participant ainsi à la gestion des eaux pluviales urbaines. La perspective d'une mise en oeuvre de politiques incitatives de récupération des eaux pluviales impose cependant de s'interroger sur l'incidence de cette pratique sur le régime hydrologique de certains bassins versants. Dans les secteurs urbanisés, pour lesquels le potentiel de développement de la récupération des eaux pluviales est important, l'interception d'une fraction significative du ruissellement pour satisfaire divers usages pourrait en effet conduire à un déséquilibre hydrologique se traduisant par une aggravation des étiages. Une méthode associant modélisation hydrologique et exploitation de données géographiques est ici introduite pour construire différents scénarios de récupération des eaux pluviales et évaluer leur incidence de sur le régime hydrologique deux bassins-versants semi-urbains. L'analyse suggère ici que cette pratique n'est à elle seule pas suffisante pour satisfaire les objectifs usuels de gestion des eaux pluviales mais indique que sa systématisation sur des têtes de bassins versant présentant de faibles débits pourrait en revanche donner lieu à une aggravation des étiage