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  • Neuroinformatics
  • 2019-2023
  • Open Access
  • English

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Morel, Jean-Paul; Villedieu, Françoise;

    International audience

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    Other literature type . 2021
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    Authors: Belle Collaboration; Abdesselam, A.; Adachi, I.; Adamczyk, K.; +196 Authors

    We report the first measurement of the $D^{\ast -}$ meson polarization in the decay $B^0 \to D^{*-} \tau^+\nu_{\tau}$ using the full data sample of 772$\times 10^6$ $B\bar{B}$ pairs recorded with the Belle detector at the KEKB electron-positron collider. Our result, $F_L^{D^\ast} = 0.60 \pm 0.08 ({\rm stat}) \pm 0.04 ({\rm sys})$, where $F_L^{D^\ast}$ denotes the $D^{\ast-}$ meson longitudinal polarization fraction, agrees within about $1.7$ standard deviations of the standard model prediction. Comment: 16 pages, 4 figures, CKM 2018

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    Authors: Salimi, Fatemeh;

    While the reference framework for international portfolio choice emphasizes a mean-variance framework, uncovered parity conditions only involve mean stock or bond returns. We propose to augment the empirical specification by using the relative stock market uncertainty of two countries as an extra determinant of their bilateral exchange rate returns. A rise in the relative uncertainty of one stock market will lead capital to flow to the other stock market and generate an appreciation in the currency of the latter. By focusing on the JPY/USD exchange rate returns during the most recent decade (2009-2019) and relying on a nonlinear framework, we provide evidence that the Japanese-US differential stock market uncertainty affects the JPY/USD returns both contemporaneously and with weekly lags. This finding is robust when we control for the stock returns differential and the differential changes in Japanese and US unconventional monetary policy measures.

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    Authors: Permiakova, Olga;

    L'analyse protéomique consiste à déterminer les identités et quantités des protéines contenues dans des échantillons biologiques. Une telle analyse est souvent nécessaire en recherche fondamentale ou clinique, pour trouver des protéines différentiellement exprimées entre plusieurs conditions, communément appelées « biomarqueurs ». La protéomique moderne s’appuie principalement sur des techniques de chimie analytique, et notamment, sur la spectrométrie de masse (MS) couplée à la chromatographie liquide haute pression (LC). Pour augmenter la profondeur et la couverture des analyses protéomiques, le multiplexage des acquisitions est de plus en plus utilisé, malgré les défis que cela soulève ensuite lors du traitement des données. Récemment, il a été montré que certains d’entre eux pouvaient être résolus à l'aide d’une « bibliothèque de chromatogrammes », c’est-à-dire une collection de profils chromatographiques élémentaires correspondant à différents fragments de protéines présents dans les échantillons. Les approches de l’état de l’art s’appuient sur des expériences complémentaires (et coûteuses) de spectrométrie de masse pour construire cette bibliothèque de chromatogrammes. L'objectif de ce travail a donc été de s’affranchir de ces expériences et d’appliquer des méthodes d’apprentissage automatique innovantes pour construire in silico cette bibliothèque. Deux méthodes ont été développées. La première, appelée CHICKN (Chromatogram Hierarchical Compressive K-means with Nyström approximation), propose de partitionner les profils d'élution observés (définis comme les colonnes de la matrice contenant les données LC-MS) en plusieurs groupes en fonction de leur forme, puis de construire la bibliothèque en utilisant un représentant de chaque groupe. Afin d’être calculatoirement efficace, l’étape de partitionnement s’appuie sur la théorie de l'apprentissage compressif, qui permet de traiter un sketch des données (un résumé de taille fixe) plutôt que les données complètes. Par ailleurs, l'algorithme ainsi obtenu est compatible avec l'astuce du noyau, qui est accélérée grâce à l'approximation de Nyström. Enfin, nous avons proposé deux nouveaux noyaux à partir de la distance Wasserstein-1. Nous avons établi sur des données protéomiques réelles que ces deux noyaux permettent de mieux appréhender les spécificités des données LC-MS. La deuxième méthode développée dans cette thèse est constituée d’un algorithme d'apprentissage de dictionnaire, baptisé SSDL (Sketched Stochastic Dictionary Learning); afin d'utiliser ensuite le dictionnaire ainsi appris comme bibliothèque de chromatogrammes. Cette méthode repose également sur la théorie de l'apprentissage compressif. De plus, son efficacité computationnelle est renforcée par une version stochastique de la méthode de descente de gradient accélérée de Nesterov. Les performances des deux méthodes ont été évaluées sur des données LC-MS réelles. Nous avons démontré que les deux méthodes conduisent effectivement à la construction de bibliothèques de chromatogrammes qui satisfont toutes les exigences de données LC-MS (dont, notamment, l’interprétabilité physique). En outre, elles ont un faible coût de calcul, ce qui leur permet de construire efficacement les très grandes bibliothèques de chromatogrammes qui sont nécessaires à l’analyse d’échantillons biologiques complexes. Proteomic analysis consists in determining which proteins are contained in biological samples and in which quantity. Such analysis is often required in fundamental or clinical research, to find proteins differentially expressed between several conditions, a.k.a. biomarkers. Modern proteomics largely relies on analytical chemistry techniques, and notably, on mass spectrometry (MS) coupled with high-pressure liquid chromatography (LC). To increase the depth and coverage of proteomics analyses, multiplexed LC-MS acquisitions are increasingly relied on, despite the subsequent challenges in data processing. Recently, it has been shown that some of these challenges could be addressed using chromatogram libraries, which consist of elementary chromatographic profile collections corresponding to different protein fragments present in the samples. The current state-of-the-art approaches propose to construct the chromatogram library by means of additional (and costly) mass spectrometry experiments. The aim of this work is to construct it numerically, through the direct analysis of the LC-MS data using innovative machine learning approaches. Two approaches have been developed. The first one, referred to as CHICKN (Chromatogram Hierarchical Compressive K-means with Nystrom approximation), proposes to cluster the observed elution profiles (defined as the columns of the matrix containing the LC-MS data) and to construct the library using the consensus chromatograms resulting from these clusters. This clustering method operates on a data sketch, as defined in the compressive learning theory. Furthermore, the algorithm is compatible with the kernel trick, which is accelerated thanks to Nyström kernel approximation. Finally, we have derived two new kernel functions, based on the Wasserstein-1 distance. We have established on real proteomics data that these kernel functions lead to better capturing the LC-MS data specificities. The second approach developed in this thesis is an online dictionary learning algorithm, referred to as SSDL (Sketched Stochastic Dictionary Learning), so as to use the trained dictionary as a chromatogram library. This method also relies on the compressive learning theory. In addition, its computational efficiency is strengthened by a stochastic version of Nesterov accelerated gradient descent method. The performance of both methods has been assessed on real LC-MS data. We demonstrated that both of them lead to the construction of meaningful chromatogram libraries, satisfying all LC-MS data requirements (notably physical interpretability). Moreover, they have small computational cost and are efficient to build extremely large chromatogram libraries, as required for complex biological samples.

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    Authors: Plot, Sylvie;

    Le code elsA de mécanique des fluide numérique développé à l'ONERA est à la fois un ensemble logiciel capitalisant les résultats innovants de la recherche dans le temps et un outil polyvalent pour l'aérodynamique numérique appliquée et la multi-physique. elsA est largement utilisé à l'ONERA, par les groupes Safran et Airbus, ainsi que par d'autres groupes industriels et des partenaires de recherche. Cet article présente les principales fonctionnalités d'elsA et les simulations numériques récentes utilisant elsA pour un large éventail d'applications dans les turbomachines difficiles. Les simulations portent sur des calculs aérodynamiques ainsi que des calculs aéroacoustiques et aéroélastiques. Chaque simulation permet de mettre en relief la modélisation et les méthodes numériques discriminantes mises en œuvre au sein d'elsA et montre que ce logiciel a atteint un très haut niveau de maturité et de fiabilité. The elsA CFD software developed at ONERA is both a software package capitalizing the innovative results of research over time and a multipurpose tool for applied CFD and for multi-physics. elsA is intensively used by the Safran and Airbus groups and ONERA, as well as other industrial groups and research partners. This paper presents the main capabilities of elsA and recent numerical simulations using elsA for a wide range of challenging turbomachinery applications. The simulations address aerodynamics computations as well as aero-structure and aeroacoustics ones. Each simulation enables to underline differentiating modelling and numerical methods implemented within elsA and shows that this software has reached a very high level of maturity and reliability.

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    Authors: Nazim Mamache, Hamed; Mazué, Gabin; Rashid, Osama; Bu, Gewu; +1 Authors

    International audience; Les registres distribués sont des technologies attractives ayant des applications variées allant du monde financier au monde des télécommunications. Dans le paysage des blockchains IOTA est le seul registre partagé dédié à l'internet des objets. Afin d'assurer des propriétés fortes de cohérence la version initiale d'IOTA proposait l'utilisation d'un contrôleur permettant d'assurer un ordre total sur les transactions insérées dans le système. Plus récemment, IOTA a proposé de remplacer le contrôleur par un algorithme de consensus. Pour cela, deux algorithmes de consensus ont été proposés par la fondation IOTA, décrits dans le framework Coordicide : Fast Probabilistic Consensus et Cellular Consensus. Au moment de leur publication, ces algorithmes étaient publicités comme étant la nouvelle brique de consensus de IOTA. Nous avons évalué les performances de ces algorithmes en utilisant des hypothèses d'implémentation réalistes. De plus, nous avons évalué la convergence des ces algorithmes en variant les topologies du réseau sous-jacent. Nos simulations montrent des taux de convergence faible, même sous des adversaires de faible puissance. De plus, nous avons observé de mauvaises performances de passage à l'échelle sauf lors des tests avec des topologies Watts Strogatz. Nos résultats indiquent que la conception de registres distribués dédiés aux IoT reste un problème ouvert et proposent des directions de recherche potentielle. Depuis l'apparition de nos résultats, la fondation IOTA a annoncé la publication imminente d'une nouvelle version de sa brique de consensus.

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    Authors: Lu, Xin;

    L'équation de Dirac et ses variantes sont omniprésentes dans la description à basse énergie des matériaux topologiques incluant les isolants topologiques et les semi-métaux topologiques mais aussi leurs états de surface protégés. Leurs propriétés spectroscopiques pourraient être étudiées théoriquement en se basant sur le Hamiltonien de Dirac correspondant. D'une part, grâce à la symétrie de Lorentz sous-jacente des Hamiltonians de Dirac, la renormalisation relativiste se manifeste sous la forme de la renormalisation de gap qui offre une signature expérimentale claire et directe dans la spectroscopie magnéto-optique. En particulier, la renormalisation de gap est observée expérimentalement dans les mesures magnéto-optiques du semi-métal de lignes nodales de Dirac, diarséniure de niobium, par nos collaborateurs du LNCMI à Grenoble. Non seulement plusieurs Hamiltonians de Dirac sont systématiquement discutés afin de dévoiler leurs propriétés relativistes, mais aussi leurs interprétations dans le langage de la physique des solides. D'autre part, la théorie de la réponse linéaire appliquée au Hamiltonien de Dirac correspondant prédit une signature magnéto-optique des états de surface massifs au-delà des états de surface chiraux et topologiquement protégés. Ces états de surface massifs, qui sont aussi appelés états de Volkov-Pankratov, émergent génériquement aux surfaces douces des matériaux topologiques. L'origine de leur apparition peut être considérée de façon équivalente comme une conséquence soit d'un pseudo-champs magnétique soit d'un effet du confinement quantique. En comparant APRES qui ne peut pas établir sans ambiguïté la présence des états de Volkov-Pankratov, leurs signatures magnéto-optiques associées offrent des preuves claires pour leur présence grâce aux règles de sélection exceptionnelles. En plus, la présence des états de Volkov-Pankratov donne lieu aux plasmons de surface non-réciproques qui fournissent les possibilités dans la plasmonique de surface des matériaux topologiques. The Dirac equation and its variants are ubiquitous in the low-energy description of topological materials ranging from topological insulators to semimetals as well as their topologically protected surface states. Their spectroscopic properties can be studied theoretically with the help of the corresponding Dirac Hamiltonian. On the one hand, thanks to the underlying Lorentz symmetry of the Dirac Hamiltonians, the relativistic renormalization manifests itself as the renormalization of the band gap resulting in a clear-cut experimental signature in magneto-optics. Most saliently, the renormalization of the band gap is experimentally observed in the magneto-optical measurements of the nodal-line Dirac semimetal niobium diarsenide by our collaborators in LNCMI, Grenoble. Not only are several typical Dirac-type Hamiltonians systematically discussed in order to unveil their relativistic properties, but their interpretation in the language of condensed matter physics is also provided. On the other hand, the magneto-optical signature of additional massive surface states of topological materials is also predicted using linear response theory and the corresponding Dirac Hamiltonians. These massive states called Volkov-Pankratov states arise generically on a smooth surface of topological materials. Their emergence can be equivalently seen as a consequence of a pseudo-magnetic field and/or of a quantum confinement effect. While ARPES cannot unambiguously substantiate the presence of Volkov-Pankratov states, their magneto-optical signature offers a smoking gun thanks to unusual selection rules. Furthermore, the presence of the additional Volkov-Pankratov states gives birth to non-reciprocal surface plasmon modes which provide possibilities in surface plasmonics of topological materials.

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      Hal-Diderot
      Doctoral thesis . 2021
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    Authors: de Vignemont, Frédérique;

    International audience; The body is a material entity located in space and time in the same way as a rock, a tree or a bird. But do we perceive and experience our body like those other objects? Most philosophical interest for bodily awareness has come from its peculiarities. It is precisely because we assume that we are aware of our body differently from other objects that it raises many questions. But what makes it unique? The most intuitive answer is that it bears a special relation to the self, and to self-awareness. Yet, although introspectively familiar, it is hard to exactly pinpoint the nature of this specific relationship. Thanks to their privileged relation to our body, bodily experiences seem to afford awareness of our body as being our own, what has been called the sense of bodily ownership, for want of a better name. 1 In my book, Mind the body (2018), I explored what it takes to be aware of one's body as one's own but I had to face a number of issues, many of which are still unresolved, and since then, new ones have raised. The aim of this chapter is to offer a very brief outline of the main questions and puzzles that await those interested in bodily ownership. I have picked ten of them, to echo Michael Tye's famous Ten problems of consciousness, but there are many more, I am afraid, and each problem raises major issues that deserve much more than the space allocated here.

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    Authors: Grazioplene, Rachael; Tseng, Wan-Ling; Cimino, Kimberly; Kalvin, Carla; +3 Authors

    Childhood aggression has been linked to white matter abnormalities, but research has been inconsistent with regard to both regions of alterations and directionality of the associations. We examined white matter microstructure correlates of aggression using a novel diffusion imaging analysis technique, fixel-based analysis, which leverages connectivity and crossing-fiber information to assess fiber bundle density.The sample included 70 children with aggressive behavior and 25 healthy control children without aggressive behavior. Aggression was measured by the parent-rated Aggressive Behavior scale of the Child Behavior Checklist. Fixel-based analysis was conducted at the whole-brain and region-of-interest levels, including the uncinate fasciculus, inferior longitudinal fasciculus, fornix, cingulum bundle, and genu, body, isthmus, and splenium of the corpus callosum.Whole-brain analysis of covariance revealed that children with aggressive behavior, relative to control children, had lower fiber density in a cluster of limbic and cortical pathways, including the inferior fronto-occipital fasciculus, fornix, middle cerebellar peduncle, and superior thalamic radiations (familywise error-corrected p .01), and had higher fiber density in the corpus callosum (body and splenium) (familywise error-corrected p .05). Region-of-interest analyses showed decreased fiber density in cingulum bundles associated with aggression. These effects were independent of age, sex, IQ, symptoms of attention-deficit/hyperactivity disorder, medications, and head motion. In children with aggressive behavior, co-occurring callous-unemotional traits and anxiety did not moderate the association between aggression and white matter density.Diminished white matter density in pathways connecting limbic and cortical regions is associated with childhood aggression. Abnormal interhemispheric connectivity via corpus callosum may also reflect a potential neural mechanism involved in aggression.

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    Europe PubMed Central
    Other literature type . 2020
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      Europe PubMed Central
      Other literature type . 2020
      Data sources: PubMed Central
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    Authors: COMBARNOUS, François; BERROU, Jean-Philippe; CLEMENT, Matthieu; DARBON, Dominique; +1 Authors

    Abstract. This article aims to identify and characterise the Turkish middle class. Our objective is to improve its description by implementing a clustering method combining an economic and a sociological approach. Using the Income and Living Conditions Survey (2014), we first identify the middle-class on the basis of an income interval. We then use information about employment and education to characterise the heterogeneity of this middle-income class. The distinctive behaviors and aspirations of four middle class groups are explored in depth by using the results of original qualitative field research carried out among middle class households from two contrasting regions.Keywords. Social stratification, Income distribution, Middle class, Turkey, Clustering methods.JEL. O15, D13, E25.

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    KSP Journals
    Article . 2019
    License: CC BY NC
    Data sources: KSP Journals
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    Oskar Bordeaux
    Article . 2019
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    Authors: Morel, Jean-Paul; Villedieu, Françoise;

    International audience

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    Hyper Article en Ligne
    Other literature type . 2021
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    Authors: Belle Collaboration; Abdesselam, A.; Adachi, I.; Adamczyk, K.; +196 Authors

    We report the first measurement of the $D^{\ast -}$ meson polarization in the decay $B^0 \to D^{*-} \tau^+\nu_{\tau}$ using the full data sample of 772$\times 10^6$ $B\bar{B}$ pairs recorded with the Belle detector at the KEKB electron-positron collider. Our result, $F_L^{D^\ast} = 0.60 \pm 0.08 ({\rm stat}) \pm 0.04 ({\rm sys})$, where $F_L^{D^\ast}$ denotes the $D^{\ast-}$ meson longitudinal polarization fraction, agrees within about $1.7$ standard deviations of the standard model prediction. Comment: 16 pages, 4 figures, CKM 2018

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    Authors: Salimi, Fatemeh;

    While the reference framework for international portfolio choice emphasizes a mean-variance framework, uncovered parity conditions only involve mean stock or bond returns. We propose to augment the empirical specification by using the relative stock market uncertainty of two countries as an extra determinant of their bilateral exchange rate returns. A rise in the relative uncertainty of one stock market will lead capital to flow to the other stock market and generate an appreciation in the currency of the latter. By focusing on the JPY/USD exchange rate returns during the most recent decade (2009-2019) and relying on a nonlinear framework, we provide evidence that the Japanese-US differential stock market uncertainty affects the JPY/USD returns both contemporaneously and with weekly lags. This finding is robust when we control for the stock returns differential and the differential changes in Japanese and US unconventional monetary policy measures.

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    Authors: Permiakova, Olga;

    L'analyse protéomique consiste à déterminer les identités et quantités des protéines contenues dans des échantillons biologiques. Une telle analyse est souvent nécessaire en recherche fondamentale ou clinique, pour trouver des protéines différentiellement exprimées entre plusieurs conditions, communément appelées « biomarqueurs ». La protéomique moderne s’appuie principalement sur des techniques de chimie analytique, et notamment, sur la spectrométrie de masse (MS) couplée à la chromatographie liquide haute pression (LC). Pour augmenter la profondeur et la couverture des analyses protéomiques, le multiplexage des acquisitions est de plus en plus utilisé, malgré les défis que cela soulève ensuite lors du traitement des données. Récemment, il a été montré que certains d’entre eux pouvaient être résolus à l'aide d’une « bibliothèque de chromatogrammes », c’est-à-dire une collection de profils chromatographiques élémentaires correspondant à différents fragments de protéines présents dans les échantillons. Les approches de l’état de l’art s’appuient sur des expériences complémentaires (et coûteuses) de spectrométrie de masse pour construire cette bibliothèque de chromatogrammes. L'objectif de ce travail a donc été de s’affranchir de ces expériences et d’appliquer des méthodes d’apprentissage automatique innovantes pour construire in silico cette bibliothèque. Deux méthodes ont été développées. La première, appelée CHICKN (Chromatogram Hierarchical Compressive K-means with Nyström approximation), propose de partitionner les profils d'élution observés (définis comme les colonnes de la matrice contenant les données LC-MS) en plusieurs groupes en fonction de leur forme, puis de construire la bibliothèque en utilisant un représentant de chaque groupe. Afin d’être calculatoirement efficace, l’étape de partitionnement s’appuie sur la théorie de l'apprentissage compressif, qui permet de traiter un sketch des données (un résumé de taille fixe) plutôt que les données complètes. Par ailleurs, l'algorithme ainsi obtenu est compatible avec l'astuce du noyau, qui est accélérée grâce à l'approximation de Nyström. Enfin, nous avons proposé deux nouveaux noyaux à partir de la distance Wasserstein-1. Nous avons établi sur des données protéomiques réelles que ces deux noyaux permettent de mieux appréhender les spécificités des données LC-MS. La deuxième méthode développée dans cette thèse est constituée d’un algorithme d'apprentissage de dictionnaire, baptisé SSDL (Sketched Stochastic Dictionary Learning); afin d'utiliser ensuite le dictionnaire ainsi appris comme bibliothèque de chromatogrammes. Cette méthode repose également sur la théorie de l'apprentissage compressif. De plus, son efficacité computationnelle est renforcée par une version stochastique de la méthode de descente de gradient accélérée de Nesterov. Les performances des deux méthodes ont été évaluées sur des données LC-MS réelles. Nous avons démontré que les deux méthodes conduisent effectivement à la construction de bibliothèques de chromatogrammes qui satisfont toutes les exigences de données LC-MS (dont, notamment, l’interprétabilité physique). En outre, elles ont un faible coût de calcul, ce qui leur permet de construire efficacement les très grandes bibliothèques de chromatogrammes qui sont nécessaires à l’analyse d’échantillons biologiques complexes. Proteomic analysis consists in determining which proteins are contained in biological samples and in which quantity. Such analysis is often required in fundamental or clinical research, to find proteins differentially expressed between several conditions, a.k.a. biomarkers. Modern proteomics largely relies on analytical chemistry techniques, and notably, on mass spectrometry (MS) coupled with high-pressure liquid chromatography (LC). To increase the depth and coverage of proteomics analyses, multiplexed LC-MS acquisitions are increasingly relied on, despite the subsequent challenges in data processing. Recently, it has been shown that some of these challenges could be addressed using chromatogram libraries, which consist of elementary chromatographic profile collections corresponding to different protein fragments present in the samples. The current state-of-the-art approaches propose to construct the chromatogram library by means of additional (and costly) mass spectrometry experiments. The aim of this work is to construct it numerically, through the direct analysis of the LC-MS data using innovative machine learning approaches. Two approaches have been developed. The first one, referred to as CHICKN (Chromatogram Hierarchical Compressive K-means with Nystrom approximation), proposes to cluster the observed elution profiles (defined as the columns of the matrix containing the LC-MS data) and to construct the library using the consensus chromatograms resulting from these clusters. This clustering method operates on a data sketch, as defined in the compressive learning theory. Furthermore, the algorithm is compatible with the kernel trick, which is accelerated thanks to Nyström kernel approximation. Finally, we have derived two new kernel functions, based on the Wasserstein-1 distance. We have established on real proteomics data that these kernel functions lead to better capturing the LC-MS data specificities. The second approach developed in this thesis is an online dictionary learning algorithm, referred to as SSDL (Sketched Stochastic Dictionary Learning), so as to use the trained dictionary as a chromatogram library. This method also relies on the compressive learning theory. In addition, its computational efficiency is strengthened by a stochastic version of Nesterov accelerated gradient descent method. The performance of both methods has been assessed on real LC-MS data. We demonstrated that both of them lead to the construction of meaningful chromatogram libraries, satisfying all LC-MS data requirements (notably physical interpretability). Moreover, they have small computational cost and are efficient to build extremely large chromatogram libraries, as required for complex biological samples.

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    Hal-Diderot
    Doctoral thesis . 2021
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      Hal-Diderot
      Doctoral thesis . 2021
      Data sources: Hal-Diderot
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    Authors: Plot, Sylvie;

    Le code elsA de mécanique des fluide numérique développé à l'ONERA est à la fois un ensemble logiciel capitalisant les résultats innovants de la recherche dans le temps et un outil polyvalent pour l'aérodynamique numérique appliquée et la multi-physique. elsA est largement utilisé à l'ONERA, par les groupes Safran et Airbus, ainsi que par d'autres groupes industriels et des partenaires de recherche. Cet article présente les principales fonctionnalités d'elsA et les simulations numériques récentes utilisant elsA pour un large éventail d'applications dans les turbomachines difficiles. Les simulations portent sur des calculs aérodynamiques ainsi que des calculs aéroacoustiques et aéroélastiques. Chaque simulation permet de mettre en relief la modélisation et les méthodes numériques discriminantes mises en œuvre au sein d'elsA et montre que ce logiciel a atteint un très haut niveau de maturité et de fiabilité. The elsA CFD software developed at ONERA is both a software package capitalizing the innovative results of research over time and a multipurpose tool for applied CFD and for multi-physics. elsA is intensively used by the Safran and Airbus groups and ONERA, as well as other industrial groups and research partners. This paper presents the main capabilities of elsA and recent numerical simulations using elsA for a wide range of challenging turbomachinery applications. The simulations address aerodynamics computations as well as aero-structure and aeroacoustics ones. Each simulation enables to underline differentiating modelling and numerical methods implemented within elsA and shows that this software has reached a very high level of maturity and reliability.

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    Authors: Nazim Mamache, Hamed; Mazué, Gabin; Rashid, Osama; Bu, Gewu; +1 Authors

    International audience; Les registres distribués sont des technologies attractives ayant des applications variées allant du monde financier au monde des télécommunications. Dans le paysage des blockchains IOTA est le seul registre partagé dédié à l'internet des objets. Afin d'assurer des propriétés fortes de cohérence la version initiale d'IOTA proposait l'utilisation d'un contrôleur permettant d'assurer un ordre total sur les transactions insérées dans le système. Plus récemment, IOTA a proposé de remplacer le contrôleur par un algorithme de consensus. Pour cela, deux algorithmes de consensus ont été proposés par la fondation IOTA, décrits dans le framework Coordicide : Fast Probabilistic Consensus et Cellular Consensus. Au moment de leur publication, ces algorithmes étaient publicités comme étant la nouvelle brique de consensus de IOTA. Nous avons évalué les performances de ces algorithmes en utilisant des hypothèses d'implémentation réalistes. De plus, nous avons évalué la convergence des ces algorithmes en variant les topologies du réseau sous-jacent. Nos simulations montrent des taux de convergence faible, même sous des adversaires de faible puissance. De plus, nous avons observé de mauvaises performances de passage à l'échelle sauf lors des tests avec des topologies Watts Strogatz. Nos résultats indiquent que la conception de registres distribués dédiés aux IoT reste un problème ouvert et proposent des directions de recherche potentielle. Depuis l'apparition de nos résultats, la fondation IOTA a annoncé la publication imminente d'une nouvelle version de sa brique de consensus.

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    Other literature type . 2022
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    Authors: Lu, Xin;

    L'équation de Dirac et ses variantes sont omniprésentes dans la description à basse énergie des matériaux topologiques incluant les isolants topologiques et les semi-métaux topologiques mais aussi leurs états de surface protégés. Leurs propriétés spectroscopiques pourraient être étudiées théoriquement en se basant sur le Hamiltonien de Dirac correspondant. D'une part, grâce à la symétrie de Lorentz sous-jacente des Hamiltonians de Dirac, la renormalisation relativiste se manifeste sous la forme de la renormalisation de gap qui offre une signature expérimentale claire et directe dans la spectroscopie magnéto-optique. En particulier, la renormalisation de gap est observée expérimentalement dans les mesures magnéto-optiques du semi-métal de lignes nodales de Dirac, diarséniure de niobium, par nos collaborateurs du LNCMI à Grenoble. Non seulement plusieurs Hamiltonians de Dirac sont systématiquement discutés afin de dévoiler leurs propriétés relativistes, mais aussi leurs interprétations dans le langage de la physique des solides. D'autre part, la théorie de la réponse linéaire appliquée au Hamiltonien de Dirac correspondant prédit une signature magnéto-optique des états de surface massifs au-delà des états de surface chiraux et topologiquement protégés. Ces états de surface massifs, qui sont aussi appelés états de Volkov-Pankratov, émergent génériquement aux surfaces douces des matériaux topologiques. L'origine de leur apparition peut être considérée de façon équivalente comme une conséquence soit d'un pseudo-champs magnétique soit d'un effet du confinement quantique. En comparant APRES qui ne peut pas établir sans ambiguïté la présence des états de Volkov-Pankratov, leurs signatures magnéto-optiques associées offrent des preuves claires pour leur présence grâce aux règles de sélection exceptionnelles. En plus, la présence des états de Volkov-Pankratov donne lieu aux plasmons de surface non-réciproques qui fournissent les possibilités dans la plasmonique de surface des matériaux topologiques. The Dirac equation and its variants are ubiquitous in the low-energy description of topological materials ranging from topological insulators to semimetals as well as their topologically protected surface states. Their spectroscopic properties can be studied theoretically with the help of the corresponding Dirac Hamiltonian. On the one hand, thanks to the underlying Lorentz symmetry of the Dirac Hamiltonians, the relativistic renormalization manifests itself as the renormalization of the band gap resulting in a clear-cut experimental signature in magneto-optics. Most saliently, the renormalization of the band gap is experimentally observed in the magneto-optical measurements of the nodal-line Dirac semimetal niobium diarsenide by our collaborators in LNCMI, Grenoble. Not only are several typical Dirac-type Hamiltonians systematically discussed in order to unveil their relativistic properties, but their interpretation in the language of condensed matter physics is also provided. On the other hand, the magneto-optical signature of additional massive surface states of topological materials is also predicted using linear response theory and the corresponding Dirac Hamiltonians. These massive states called Volkov-Pankratov states arise generically on a smooth surface of topological materials. Their emergence can be equivalently seen as a consequence of a pseudo-magnetic field and/or of a quantum confinement effect. While ARPES cannot unambiguously substantiate the presence of Volkov-Pankratov states, their magneto-optical signature offers a smoking gun thanks to unusual selection rules. Furthermore, the presence of the additional Volkov-Pankratov states gives birth to non-reciprocal surface plasmon modes which provide possibilities in surface plasmonics of topological materials.

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    Other literature type . 2021
    Hal-Diderot
    Doctoral thesis . 2021
    Data sources: Hal-Diderot
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Hyper Article en Ligne
      Other literature type . 2021
      Hal-Diderot
      Doctoral thesis . 2021
      Data sources: Hal-Diderot
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/