14 research outputs found
Survey of correlation properties of polyatomic molecules vibrational energy levels using FT analysis
International audienceIn the last few years molecular spectroscopists have begun to study the highly excited vibrational levels of polyatomic molecules. In this high energy regime vibrational quantum numbers can no longer be intrinsically assigned (in contrast to vibrational levels at low energy). One can only characterize these levels by their correlation properties. The authors consider: short range correlations which are characterized by the next neighbor distribution, (NND). These correlations range from a Poisson (random or uncorrelated spectra) to a Wigner distribution (which shows 'level repulsion'); (ii) long range correlations are characterized by the(L) and(L) function. They describe the behavior which ranges from an uncorrelated spectra (Poisson statistic) to a spectra with 'spectral rigidity'
Learning redundant dictionaries with translation invariance property: the MoTIF algorithm
International audienceSparse approximation using redundant dictionaries is an efficient tool for many applications in the field of signal processing. The performances largely depend on the adaptation of the dictionary to the signal to decompose. As the statistical dependencies are most of the time not obvious in natural high- dimensional data, learning fundamental patterns is an alternative to analytical design of bases and has become a field of acute research. Most of the time, the underlying patterns of a class of signals can be found at any time, and in the design of a dictionary, this translation invariance property should be present. We present a new algorithm for learning short generating functions, each of them building a set of atoms corresponding to all its translations. The resulting dictionary is highly redundant and translation invariant
Fourier transform: A tool to measure statistical level properties in very complex spectra
International audienceWe show that the Fourier transform of very complex spectra gives a sound measurement of long-range statistical properties of levels even in cases of badly resolved, poorly correlated spectra. Examples of nuclear energy levels, highly excited acetylene vibrational levels, and singlet-triplet anticrossing spectra in methylglyoxal are displayed
Carfilzomib, lenalidomide and dexamethasone followed by a second ASCT is an effective strategy in first relapse multiple myeloma: a study on behalf of the Chronic malignancies working party of the EBMT
In the setting of a first relapse of multiple myeloma (MM), a second autologous stem cell transplant (ASCT) following carfilzomib-lenalidomide-dexamethasone (KRd) is an option, although there is scarce data concerning this approach. We performed a retrospective study involving 22 EBMT-affiliated centers. Eligible MM patients had received a second-line treatment with KRd induction followed by a second ASCT between 2016 and 2018. Primary objective was to estimate progression-free survival (PFS) and overall survival (OS). Secondary objectives were to assess the response rate and identify significant variables affecting PFS and OS. Fifty-one patients were identified, with a median age of 62 years. Median PFS after ASCT was 29.5 months while 24- and 36-months OS rates were 92.1% and 84.5%, respectively. Variables affecting PFS were an interval over four years between transplants and the achievement of a very good partial response (VGPR) or better before the relapse ASCT. Our study suggests that a relapse treatment with ASCT after KRd induction is an effective strategy for patients with a lenalidomide-sensitive first relapse. Patients with at least four years of remission after a frontline ASCT and who achieved at least a VGPR after KRd induction appear to benefit the most from this approach
Conférence nationalesur l'enseignement des mathématiques à l'école primaire et au collège: Recueil des interventions suscitées
Etats des lieux et analyses de l'enseignement des mathématiques en France, aujourd'hui
Plus d'autonomie protéique dans les élevages caprins grâce à la prairie multi-espèces : expérience du REDCap en Poitou-Charentes et Pays de la Loire
Depuis une quinzaine d’années, les élevages caprins de l’Ouest de la France s’intensifient, entraînant desachats croissants en intrants. Deux dispositifs de Recherche et Développement complémentaires visent à favoriser la recherche d’autonomie alimentaire et protéique : Patuchev (Inra-UE FERLus) et le Réseaud’Expérimentation et de Développement Caprin-REDCap (BRILAC) (BONNES et al., 2012). Pour répondre à cetenjeu, l’utilisation de la prairie multi-espèces a été identifiée comme une priorité par les éleveurs et lestechniciens. Cependant, il manque encore actuellement des références régionales sur les prairies multiespècesvalorisées par les caprins. L’objectif est donc de proposer un (ou des) mélange(s) prairial(aux)adapté(s) aux chèvres, aux conditions pédoclimatiques régionales et aux différents systèmes fourragers
MoTIF : an Efficient Algorithm for Learning Translation Invariant Dictionaries
International audienceThe performances of approximation using redundant expansions rely on having dictionaries adapted to the signals. In natural high-dimensional data, the statistical dependencies are, most of the time, not obvious. Learning fundamental patterns is an alternative to analytical design of bases and is nowadays a popular problem in the field of approximation theory. In many situations, the basis elements are shift invariant, thus the learning should try to find the best matching filters. We present a new algorithm for learning iteratively generating functions that can be translated at all positions in the signal to generate a highly redundant dictionary