Science & Mathematics

Although hydrogen bonding is one of the most important motifs in chemistry and biology, H-atom parameters are especially problematic to refine against X-ray diffraction data. New developments in quantum crystallography offer a remedy. This article reports how hydrogen bonds are treated in three different quantum-crystallographic methods: Hirshfeld atom refinement (HAR), HAR coupled to extremely localized molecular orbitals and X-ray wavefunction refinement. Three different compound classes that form strong intra-or intermolecular hydrogen bonds are used as test cases: hydrogen maleates, the tripeptide l-alanyl-glycyl-l-alanine co-crystallized with water, and xylitol. The differences in the quantum-mechanical electron densities underlying all the used methods are analysed, as well as how these differences impact on the refinement results.

Statement of objectives Soft, waterborne polyurethane dispersions are indispensable components in many state-of-the-art materials, with applications ranging from binders for coatings and adhesives to matrixes for flexible devices. While the static bulk nanostructure of such systems is widely studied, the influence that environmental conditions such as relative humidity and airflow have on their film formation and phase segregation behavior in supported films is unknown. Experiments Here, we elucidate the nanostructure evolution occurring during drying of an industrially relevant, soft polyurethane, utilizing real-time, non-destructive grazing incidence X-ray scattering analysis. Using an environmental-controlled casting cell, we highlight the differences between the drying mechanism under different conditions generated by tuning the airflow and the relative humidity. Findings Our results show how the environment’s relative humidity strongly influences chain aggregation and chain interdiffusion due to extended plasticization of the hard segment at high humidities, while accelerated air flows are responsible for the occurrence of (partial) skinning. Interestingly, despite changes in the chain aggregation behavior and occurrence of skinning and skin breakup during drying resulting in higher roughness at the film surface, minor influence is registered on the bulk tensile properties of the films, revealing the resilient nature towards environmental conditions of these soft weakly phase segregating polyurethane systems.

L'objectif de ce travail est de développer des matériaux composites à fibres courtes aux propriétés mécaniques spécifiques élevées à partir de mélange (résine + renforts) ayant une faible viscosité pour un moulage de structures complexes. Dans le but de réduire la viscosité des mélanges élaborés, le vide et les ultrasons ont été utilisés pour homogénéiser les suspensions. A également été mis en évidence que l'ajout d'un faible taux de microbilles (

Despite general agreement that laughter is crucial in social interactions and cognitive development, there is surprisingly little work looking at its use through childhood. Here we investigate laughter in middle childhood, using a corpus of online calls between child and parent and between the (same parent) and another adult. We focus on laughter mimicry, i.e., laughter shortly following laughter from the partner, and we compare mimicking and non-mimicking laughter in terms of distribution and acoustic properties using spectrotemporal modulation measures. Our results show, despite similar frequencies in laughter production, different laughter mimicry patterns between Parent-Child and Parent-Adult interactions. Overall, in comparison with previous work in infants and toddlers, our results show laughter mimicry is more balanced between parents and school-age children. At the acoustic level, we observe differences between mimicking and non-mimicking laughter in children, but not in adults. Moreover, we observe significant differences in laughter acoustics in parents depending on whether they interact with children or adults, which highlights a strong interlocutor effect on laughter mimicry.

24x36 mm, gélatine plan-film.

Septic shock is associated with not only an excessive and an inappropriate immune response against infection, but also with increased sympathetic nerve activity, elevated circulating catecholamines and autonomic dysfunction. Beta 1-adrenergic blockade has shown to provide cardiovascular protection and survival improvement during septic shock in experimental and clinical studies, which seems due to its anti-inflammatory effects. However, the effects of heart rate reduction (HRR) of a beta 1-adrenoreceptor blocker on cardiovascular function and inflammatory pathways remain unclear. By using a pure heart rate-lowering drug, Ivabradine, in a polymicrobial septic shock model induced by CLP, we found isolated heart rate reduction 1) was not associated with any improvement in cardiac or vascular functions; 2) has no impact on circulating levels of TNF-a, IL-6 or IL-10; 3) had no influence in cardiovascular iNOS and NF-κB expression, P-akt/akt and P-eNOS/eNOS ratio and IκBα degradations in this acute setting. By using a beta 1-adrenergic blocker, Esmolol, in a polymicrobial septic shock model induced by CLP, we found that a low dose of Esmolol, which didn’t induce HRR, also 1) improved cardiac function evaluated by echocardiography and vasoreactivity tested by myograph; 2) beneficial effects were associated with the modulation of inflammatory pathways at both the systemic and the tissue levels. These results open up new perspectives in clinical treatment of septic shock with beta 1 adrenergic blockers

This thesis is interested in unsupervised statistical learning methods and their applications to health monitoring of aircraft engines at an industrial scale. Our first objective is to make health monitoring methodologies scale to massive datasets and allow engineering team to flexibly deploy various use cases. Besides the engineering aspects, we also try to address two fundamental theoretical challenges in unsupervised learning. First, the links between cluster structure and representation.And second, the very definition of structure, arising from the problem of model selection in clustering.Modern aircraft engines generate growing amounts of data during manufacturing,tests and flights, that can be leveraged for health monitoring and predictive maintenance, in order to improve safety, availability and reduce costs. In this work, we use sensor measurements collected on board of civil short and mid-range aircraft.These data sets are temporal and highly multidimensional due to the large number of sensors and sampling frequencies. Hence, applications need to scale to the large volumes of data, driven by the growing number of daily operating engines.Among all unsupervised learning approaches, clustering and self-organizing maps (SOM) provide useful insights on the distribution of complex and high-dimensional unlabeled data sets. To describe the internal state of an engine, expert indicators or features need to be extracted from raw data, before applying clustering algorithms.Our first contribution is to scale these methodologies using Big Data tools and distributed computing, in order to process entire fleets. We propose a generic and scalable pipeline enabling engineers to analyze flight data on a cluster. In addition,we present an new application to monitoring of vibration signatures.Another option is to automatically extract relevant features with deep neural networks, known as deep learning, which had a great impact in many areas of machine learning. Recently, its ability to improve clustering has been investigated. A second contribution of this thesis is a Deep Embedded SOM, a neural network-based model performing joint representation learning with an autoencoder and self-organization of the cluster prototypes. The third contribution of this thesis concerns model selection, which is perhaps the most difficult problem in clustering. We adopt the framework of cluster stability analysis, and propose a novel concept of within-cluster stability, leading to a criterion called Stadion (stability difference criterion) able to effectively select the number of clusters in a data set. We also apply Stadion to time series clustering validation by leveraging invariant transformations of the data.

Dans cette thèse, nous nous intéressons à l'approximation numérique de problèmes de convection-diffusion, potentiellement anisotropes, par des schémas d'ordre élevé sur maillages généraux. Notre objectif est de proposer des méthodes fiables, précises et efficaces : les solutions numériques doivent préserver les propriétés physiques des solutions continues (conservation de la masse, positivité des densités, comportement en temps long) tout en autorisant une large gamme de paramètres de discrétisation (pas de temps grands, maillages spatiaux généraux) et en optimisant la précision de calcul à coût donné. Les problèmes considérés sont des équations d'advection-diffusion ainsi que des systèmes couplés de dérive-diffusion qui modélisent les composants semi-conducteurs.On se concentre d'abord sur une équation d'advection-diffusion seule, pour laquelle nous proposons et analysons trois méthodes d'ordre bas de type volumes finis hybrides (HFV). Cette comparaison met en avant la nécessité d'utiliser un schéma non-linéaire afin de préserver la positivité des solutions, tant d'un point de vue théorique que numérique. On s'intéresse alors à l'approximation d'un système de dérive-diffusion, constitué de deux équations d'advection-diffusion couplées avec une équation de Poisson. Pour ce problème, on introduit un schéma non-linéaire basé sur la méthode précédente, qui préserve les bornes des densités calculées (et en particulier leur positivité) et le comportement en temps long de la solution. Ce schéma HFV pour la dérive-diffusion est ensuite comparé numériquement avec un schéma présentant des propriétés similaires basé sur la méthode volumes finis en dualité discrète (DDFV).Nous nous intéressons alors à des schémas d'ordre élevé (en espace). Ces schémas sont basés sur des méthodes de type hybride d'ordre élevé (HHO) qui peuvent être interprétées comme des extensions à l'ordre arbitraire des méthodes HFV. Nous introduisons deux méthodes pour les équations d'advection-diffusion linéaires. La première est linéaire, tandis que la seconde est non-linéaire, et permet de préserver la positivité. Pour ces deux schémas, nous prouvons l'existence de solutions discrètes et établissons des résultats de comportement en temps long. Nous confirmons également ces résultats numériquement, et mettons en avant la nécessité d'utiliser une méthode non-linéaire pour préserver la positivité. Par ailleurs, on observe que la méthode non-linéaire converge à l'ordre attendu. De plus, la montée en ordre permet un gain d'efficacité (précision de l'approximation pour un coût de calcul donné) conséquent par rapport aux méthodes d'ordre bas des premiers chapitres.Ces travaux sont complétés par l'étude de problèmes de convection-diffusion avec convection très irrégulière, effectuée en collaboration avec des physiciens durant la thèse. Les recherches menées visent à comprendre comment concevoir des diodes électroluminescentes efficaces émettant dans l'ultraviolet profond, et soulèvent divers enjeux relatifs à la modélisation, l'analyse numérique et la simulation de ces problèmes.

Trans-Neptunian objects (TNOs) are the witnesses of the formation of the planets during the dynamical and collisional period of our solar system. The population characteristics of sub-kilometer TNOs may carry some important clues for the origin of the planets. However, the knowledge of them is far from enough, particularly for those sub-kilometer ones, due to very fex directions. now adays only TNOs larger than about 25 km can be directly observed. For the TNOs not able to be directly observed, searching for serendipitous stellar occultation events is a possible method. Several serendipitous searches were proceeded, but so far there are only two possible detections from archival data of Hubble Space Telescope by Schlichting et al. in 2009 and 2012. My thesis work is going to search for more sub-kilometer sized TNOs by applying the serendipitous occultation method. The search is divided into two major parts : in X-rays and in optical bands. The X-rays observations are all from the RXTE satellie, and the optical observations are from COROT satellite ans MIOSOTYS instrument mounted on two ground-based telescopes in France and Spain. From 334-ks, no definite TNO occultation events were found. The only suspicious non-instrumental flux-drop event was not considered to be resulted from the small TNO occultation after analyzing it with the fittings of the diffraction patterns. Then we investigate the detection efficiency dependence on the TNO size to better define the sensible size range of our approach, and suggested upper limits to the TNO size distribution in the size range from 30 to 300 m. A list of X-ray sources suitable for future larger facilities to observe is proposed. The total observation time employed in our COROT work is about 144408.34 star-hours with SNR larger than 1000 computed on 30-second intervals. 13 Possible Occultation Events (POEs) were found from the deviation method. The MIOSOTYS instrument has been mounted as a visitor instrument on the 1.93 m telescope at Observatoire de Haute-Provence (OHP) in France since february 2010, and on the 1.23 m telescope at Calar Alto Observatory (CAHA) in Spain since november 2012. By july 2014, MIOSOTYS project has successfukky carried out 19 observational runs. The total exposure time before screening is about 3.5 × 10⁷ sec, which is about 9840 star hours, from 85 nights. For MIOSOTYS, we have developed an optimized observing strategy to search for TNOs. We have also developed in this project a new search algorithm of events by the method of fluctuations.

A combination of Landsat 8 and Sentinel-2 offers a high frequency of observations (3–5 days) at moderate spatial resolution (10–30 m), which is essential for crop yield studies. Existing methods traditionally apply vegetation indices (VIs) that incorporate surface reflectances (SRs) in two or more spectral bands into a single variable, and rarely address the incorporation of SRs into empirical regression models of crop yield. In this work, we address these issues by normalizing satellite data (both VIs and SRs) derived from NASA’s Harmonized Landsat Sentinel-2 (HLS) product, through a phenological fitting. We apply a quadratic function to fit VIs or SRs against accumulated growing degree days (AGDDs), which affects the rate of crop development. The derived phenological metrics for VIs and SRs, namely peak, area under curve (AUC), and fitting coefficients from a quadratic function, were used to build empirical regression winter wheat models at a regional scale in Ukraine for three years, 2016–2018. The best results were achieved for the model with near infrared (NIR) and red spectral bands and derived AUC, constant, linear, and quadratic coefficients of the quadratic model. The best model yielded a root mean square error (RMSE) of 0.201 t/ha (5.4%) and coefficient of determination R2 = 0.73 on cross-validation.

L’humour traverse toutes les cultures. Si ses modalités sont liées aux ressources linguistiques disponibles, sa thématique découle des conditions historiques. Le rire est révélateur de la société dont il émane, sa compréhension requiert d’une communauté l’existence de connaissances partagées. La spécificité du discours humoristique doit être recherchée dans la relation singulière qui se noue entre producteur et récepteur.

By the end of their first year of life, infants have become experts in discriminating the sounds of their native language, while they have lost the ability to discriminate non-native contrasts. This type of phonetic learning is referred to as perceptual attunement. In the present study, we investigated the emergence of a contextdependent form of perceptual attunement in infancy. Indeed, some native contrasts are not discriminated in certain phonological contexts by adults, due to the presence of a language-specific process that neutralizes the contrasts in those contexts. We used a mismatch design and recorded high-density Electroencephalography (EEG) in French-learning 14-month-olds. Our results show that similarly to French adults, infants fail to discriminate a native voicing contrast (e.g., [f] vs. [v]) when it occurs in a specific phonological context (e.g. [ofbe] vs. [ovbe], no mismatch response), while they successfully detected it in other phonological contexts (e.g., [ofne] vs. [ovne], mismatch response). The present results demonstrate for the first time that by the age of 14 months, infants' phonetic learning does not only rely on the processing of individual sounds, but also takes into account in a language-specific manner the phonological contexts in which these sounds occur.