Searching for thermal signatures of persistent currents in normal metal rings

We introduce a calorimetric approach to probe persistent currents in normal metal rings. The heat capacity of a large ensemble of silver rings is measured by nanocalorimetry under a varying magnetic field at different temperatures (60 mK, 100 mK and 150 mK). Periodic oscillations versus magnetic field are detected in the phase signal of the temperature oscillations, though not in the amplitude (both of them directly linked to the heat capacity). The period of these oscillations ($\Phi_0/2$, with $\Phi_0 = h/e$ the magnetic flux quantum) and their evolution with temperature are in agreement with theoretical predictions. In contrast, the amplitude of the corresponding heat capacity oscillations (several $k_{\mathrm{B}}$) is two orders of magnitude larger than predicted by theory

Estimation de la vitesse d'une cible en mouvement par une méthode large bande et haute résolution

National audience– La connaissance de la réponse impulsionnelle d'un canal de propagation est nécessaire pour un grand nombre d'applications dans le domaine de l'acoustique sous-marine comme la communication, la localisation et détection sonar, la surveillance des mammifères marins... Cette réponse impulsionnelle nous informe sur les distorsions dues au canal, que subit un signal, et sur les déformations (décalage doppler non maîtrisé) engendrées par le mouvement relatif entre source et récepteur. Dans ce contexte, la connaissance du signal transmis permet d'estimer la vitesse apparente de chaque trajet de propagation à l'aide du plan d'ambiguïté large bande [1][2][3]. On sait qu'un filtrage basé sur les opérateurs de déformation temporelle et de plan d'ambiguïté large bande permet de séparer chaque trajet de façon précise afin de supprimer les interférences et d'estimer correctement la réponse impulsionnelle-avec le retard et le facteur de compression [4]. Dans cette étude, il est proposé une approche complémentaire pour estimer conjointement la vitesse et la distance d'une cible à faible vitesse (faible doppler) avec de bonnes résolutions. Les formes d'ondes émises sont des signaux codés tels que les signaux de Costas, les Binary Phase Shift Keying (BPSK) et les trains d'impulsions modulés linéairement en fréquence (Pulse Train Frequency Modulation, PTFM), dans un contexte haute résolution. Ces formes d'ondes étant larges bandes et ayant un fort produit BT, permettent ainsi d'utiliser un modèle d'écho prenant en compte la compression temporelle du signal dû à l'effet Doppler. Abstract – The knowledge of the impulse response of the propagation channel is required for many underwater applications such communication , sonar localization and detection, and marine mammals monitoring. This impulse response affects the signal and informs about the canal distortions, but also modifications (uncontrolled Doppler effects) caused by the relative motion between source and receiver. Knowing the emitted signal, the radial speed of each acoustic path can be estimated with the wideband ambiguity plan [1][2][3]. With warping operators based-filter and wideband ambiguity plan [4], acoustic paths can be accurately separated in order to remove interferences and estimate properly the impulse response-with the delay and the Doppler compression coefficient. This paper presents a complementary approach to jointly estimate the target distance and speed at low speed (low Doppler) with reasonable resolution. The emitted waveforms are 22-Welch-Costas signal, Binary Phase Shift Keying (BPSK) signal, and Pulse Train Frequency Modulation (PTFM) signal. Context is high resolution because signals have a large time-bandwidth product (high TB). For this reason, an echo model that accounts for a signal temporal compression (Doppler effect) can be used

Seismo-volcano source localization with triaxial broad-band seismic array

International audienceSeismo-volcano source localization is essential to improve our understanding of eruptive dynamics and of magmatic systems. The lack of clear seismic wave phases prohibits the use of classical location methods. Seismic antennas composed of one-component (1C) seismometers provide a good estimate of the backazimuth of the wavefield. The depth estimation, on the other hand, is difficult or impossible to determine. As in classical seismology, the use of three-component (3C) seismometers is now common in volcano studies. To determine the source location parameters (backazimuth and depth), we extend the 1C seismic antenna approach to 3Cs. This paper discusses a high-resolution location method using a 3C array survey (3CMUSIC algorithm) with data from two seismic antennas installed on an andesitic volcano in Peru (Ubinas volcano). One of the main scientific questions related to the eruptive process of Ubinas volcano is the relationship between the magmatic explosions and long-period (LP) swarms. After introducing the 3C array theory, we evaluate the robustness of the location method on a full wavefield 3-D synthetic data set generated using a digital elevation model of Ubinas volcano and an homogeneous velocity model. Results show that the backazimuth determined using the 3C array has a smaller error than a 1C array. Only the 3C method allows the recovery of the source depths. Finally, we applied the 3C approach to two seismic events recorded in 2009. Crossing the estimated backazimuth and incidence angles, we find sources located 1000 ± 660 m and 3000 ± 730 m below the bottom of the active crater for the explosion and the LP event, respectively. Therefore, extending 1C arrays to 3C arrays in volcano monitoring allows a more accurate determination of the source epicentre and now an estimate for the depth

An Open Resource for Non-human Primate Imaging.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

A História da Alimentação: balizas historiográficas

Os M. pretenderam traçar um quadro da História da Alimentação, não como um novo ramo epistemológico da disciplina, mas como um campo em desenvolvimento de práticas e atividades especializadas, incluindo pesquisa, formação, publicações, associações, encontros acadêmicos, etc. Um breve relato das condições em que tal campo se assentou faz-se preceder de um panorama dos estudos de alimentação e temas correia tos, em geral, segundo cinco abardagens Ia biológica, a econômica, a social, a cultural e a filosófica!, assim como da identificação das contribuições mais relevantes da Antropologia, Arqueologia, Sociologia e Geografia. A fim de comentar a multiforme e volumosa bibliografia histórica, foi ela organizada segundo critérios morfológicos. A seguir, alguns tópicos importantes mereceram tratamento à parte: a fome, o alimento e o domínio religioso, as descobertas européias e a difusão mundial de alimentos, gosto e gastronomia. O artigo se encerra com um rápido balanço crítico da historiografia brasileira sobre o tema

Approximation of modal wavenumbers and group speeds in an oceanic waveguide using a neural network

International audienceUnderwater acoustic propagation is influenced not only by the property of the water column, but also by the seabed property. Modeling this propagation using normal mode simulation can be computationally intensive, especially for wideband signals. To address this challenge, a Deep Neural Network is used to predict modal horizontal wavenumbers and group velocities. Predicted wavenumbers are then used to compute modal depth functions and transmission losses, reducing computational cost without significant loss in accuracy. This is illustrated on a simulated Shallow Water 2006 inversion scenario

Sparse Deconvolution for Moving-Source Localization

International audienceIn this paper, we propose a method for moving-source localization based on beamforming output and on sparse representation of the source positions. The goal of this method is to achieve spatial deconvolution of the beamforming, to provide accurate source localization for pass-by experiments. To perform this deconvolution, we use a smooth approximation of L1/L2 [1], which is well suited for the recovery of sparse signals. We validate this method on simulated data, and compare it to the DAMAS-MS method [2], one of the classical methods used in beamforming deconvolution

Comparaison des capacités prédictives de réseaux de neurones, application à la masse sèche de cellules

International audienceDepuis une dizaine d'années, de nombreuses architectures de réseaux de neurones ont été proposées pour résoudre des problèmes complexes, jusqu'alors insolubles. Bien que chaque architecture tente d'augmenter les performances de ses prédécesseurs, nous constatons aujourd'hui un manque d'évaluation comparée de leurs performances.Nous présentons dans ce papier une étude comparative de différentes architectures des réseaux de neurones pour la prédiction de séries temporelles. En particulier, celle de masse sèche de cellules.Quatre types d'architectures (Perceptrons Multicouches, CNN-1D, LSTM et réseaux à connexions résiduelles) sont comparées selon leurs capacités prédictives, leur nombre de paramètres, leur temps d'entraînement et leur temps d'inférence.Les expériences réalisées mettent en avant une prédominance des perceptrons multicouches à extraire une représentation utile pour la prédiction de la masse sèche de cellule par un réseau totalement connecté, et ce, sur toutes les métriques étudiées

Comparaison des capacités prédictives de réseaux de neurones, application à la masse sèche de cellules

International audienceDepuis une dizaine d'années, de nombreuses architectures de réseaux de neurones ont été proposées pour résoudre des problèmes complexes, jusqu'alors insolubles. Bien que chaque architecture tente d'augmenter les performances de ses prédécesseurs, nous constatons aujourd'hui un manque d'évaluation comparée de leurs performances.Nous présentons dans ce papier une étude comparative de différentes architectures des réseaux de neurones pour la prédiction de séries temporelles. En particulier, celle de masse sèche de cellules.Quatre types d'architectures (Perceptrons Multicouches, CNN-1D, LSTM et réseaux à connexions résiduelles) sont comparées selon leurs capacités prédictives, leur nombre de paramètres, leur temps d'entraînement et leur temps d'inférence.Les expériences réalisées mettent en avant une prédominance des perceptrons multicouches à extraire une représentation utile pour la prédiction de la masse sèche de cellule par un réseau totalement connecté, et ce, sur toutes les métriques étudiées

Modal depth function estimation using time-frequency analysis

WOSInternational audienceAcoustic propagation in shallow water is characterized by a set of depth-dependent modes, the modal depth functions, which propagate in range according to their horizontal wavenumbers. For inversion purposes, modal depth function estimation in shallow water is an issue when the environment is not known. Classical methods that provide blind mode estimation rely on the singular value decomposition of the received field at different frequencies over a vertical array of transducers. These methods require that the vertical array spans the full water column. This is obviously a strong limitation for the application of such methods in an operational context. To overcome these shortcomings, this study proposes to replace the spatial diversity constraint by a frequency diversity condition, and thus considers the case of a field emanating from an impulsive source. Indeed, because of the discrete nature of the wavenumber spectrum and due to their dispersive behavior, the modes are separated in the time-frequency domain. This phenomenon enables the design of a modal filtering scheme for signals received on a single receiver. In the case of a vertical receiver array, the modal contributions can be isolated for each receiver even when using a partial water column spanning array. This method thus eliminates the receiving constraints of classical methods of modal depth function estimation, although it imposes the use of an impulsive source. The developed algorithm is benchmarked on numerical simulations and validated on laboratory experimental data recorded in an ultrasonic waveguide. Practical applications are also discussed