Moisture dynamics in the critical zone have significant implications for a variety of hydrologic processes, from water availability to plants, to infiltration and groundwater recharge rates. These processes are perturbed by events such as wildfires, which may have long-lasting impacts. In September 2011, the most destructive wildfire in Texas history occurred in and around Bastrop State Park, which was significantly affected; thus this is a rare opportunity to study soil moisture under such burned conditions. A 165 m long transect, bridging burned and unburned areas, was established within the “Lost Pines” of the park. Soil moisture was monitored using a variety of methods, including 2D electrical resistivity imaging (using dipole-dipole and Schlumberger configurations), handheld measurements using a ThetaProbe, and readings at depth using PR2 profile probes. Field measurements were collected at approximately one-month intervals to study temporal and seasonal effects on soil moisture. Greater soil moisture was found near the ground surface at the heavily burned end of the transect, where the majority of trees were killed by the fire and grasses now dominate, and lower near-surface soil moisture and higher resistivity at the opposite end of the transect, which is still populated by pine trees. These variations can likely be attributed to the vegetative variations between the two ends of the transect, with trees consuming more water at one end and the ground cover of grasses and mosses consuming less water and helping reduce evaporation at the burned end. Soil texture differences could also be a factor in greater soil moisture retention at the burned end of the transect. Given the higher moisture throughout the soil profile at the burned end of the transect, this could be an indication of greater infiltration, and could increase recharge, at least in the short term. / text

Robots exhibit flexible behavior largely in proportion to their degree of semantic knowledge about the world. Such knowledge is often meticulously hand-coded for a narrow class of tasks, limiting the scope of possible robot competencies. Thus, the primary limiting factor of robot capabilities is often not the physical attributes of the robot, but the limited time and skill of expert programmers. One way to deal with the vast number of situations and environments that robots face outside the laboratory is to provide users with simple methods for programming robots that do not require the skill of an expert. For this reason, learning from demonstration (LfD) has become a popular alternative to traditional robot programming methods, aiming to provide a natural mechanism for quickly teaching robots. By simply showing a robot how to perform a task, users can easily demonstrate new tasks as needed, without any special knowledge about the robot. Unfortunately, LfD often yields little semantic knowledge about the world, and thus lacks robust generalization capabilities, especially for complex, multi-step tasks. To address this shortcoming of LfD, we present a series of algorithms that draw from recent advances in Bayesian nonparametric statistics and control theory to automatically detect and leverage repeated structure at multiple levels of abstraction in demonstration data. The discovery of repeated structure provides critical insights into task invariants, features of importance, high-level task structure, and appropriate skills for the task. This culminates in the discovery of semantically meaningful skills that are flexible and reusable, providing robust generalization and transfer in complex, multi-step robotic tasks. These algorithms are tested and evaluated using a PR2 mobile manipulator, showing success on several complex real-world tasks, such as furniture assembly.

De par les centaines de milliers de données qui les caractérisent, les bases de données épigénétiques représentent actuellement un défi majeur. L’objectif principal de cette thèse est d’évaluer la performance d’outils statistiques développés pour les données de grande dimension, en explorant l’association entre facteurs alimentaires reliés au cancer du sein (CS) et méthylation de l’ADN dans la cohorte EPIC.Afin d’étudier les caractéristiques des données de méthylation, l’identification des sources systématiques de variabilité des mesures de méthylation a été effectuée par la méthode de la PC-PR2. Ainsi la performance de trois techniques de normalisation, très répandues pour corriger la part de variabilité non désirée, a été évaluée en quantifiant l’entendu de variabilité attribuée aux facteurs de laboratoire avant et après chaque méthode de correction.Une fois la méthode de normalisation la plus appropriée identifiée, la relation entre le folate, l’alcool et la méthylation de l’ADN a été analysée par le biais de trois approches : une analyse individuelle des sites CpG, une analyse de DMR et la régression fused lasso. Les deux dernières méthodes visent à identifier des régions spécifiques de l’épigénome grâce aux corrélations possibles entre les sites proches. La méthylation globale a aussi été utilisée pour étudier la relation entre méthylation et risque de CS.Grâce à une évaluation exhaustive d’outils statistiques révélant la complexité des données de méthylation de l’ADN, cette thèse offre un aperçu instructif de connaissances pour les études épigénétiques, avec une possibilité d’application de méthodologie similaire aux analyses d’autres types de données -omiques / Epigenetics data are challenging sets characterized by hundreds of thousands of features. The main objective of this thesis was to evaluate the performance of some of the existing statistical methods to handle sets of large dimension data, exploring the association between dietary factors related to breast cancer (BC) and DNA methylation within the EPIC study.In order to investigate the characteristics of epigenetics data, the identification of random and systematic sources of variability of methylation measurements was attempted, via the principal component partial R-square (PC-PR2) method. Using this technique, the performance of three popular normalization techniques to correct for unwanted sources of variability was evaluated by quantifying epigenetics variability attributed to laboratory factors before and after the application of each correction method.Once a suitable normalization procedure was identified, the association between alcohol intake, dietary folate and methylation levels was examined by means of three approaches: an analysis of individual CpG sites, of differentially methylated regions (DMRs) and using fused lasso regression. The last two methods aim at the identification of specific regions of the epigenome using the potential correlation between neighboring CpG sites. Global methylation levels were used to investigate the relationship between methylation and BC risk.By performing an exhaustive evaluation of the statistical tools used to disclose complexity of DNA methylation data, this thesis provides informative insights for studies focusing on epigenetics, with promising potentials to apply similar methodology to the analysis of other -omics data

Nous présentons la dépendance en température de la réponse infrarouge-visible des plans ab de Pr2-xCexCuO4. Dans l'état normal, en variant le dopage de couches minces de x=0.11 (non-supraconductrice) à x=0.17 (supraconductrice surdopée), on observe l'ouverture d'un gap partiel jusqu'au dopage optimal x=0.15. Un modèle d'onde de densité de spin reproduit qualitativement des données. En extrapolant l'amplitude de ce gap, celui-ci s'annule pour x=0.17 indiquant la présence d'un point critique quantique ainsi que la coexistence de magnétisme et de supraconductivité. En dessous de Tc, pour x=0.15 et x=0.17, la modification des spectres optiques à des énergies inférieures à 2Delta=4.7kBTc est interprétée comme la signature de l'ouverture du gap supraconducteur. La réponse optique de La2/3Ca1/3MnO3 mesurée est analysée par un modèle de milieu effectif. L'absorption supplémentaire proche de la transition isolant/métal est interprétée comme la signature d'une percolation dans le système.

The aim of the thesis is to design, create and evaluate a user interface for control of service robot. I will focus on controlling of robotic arm, to be able to accomplish pick and place tasks. Specifically I will work with robotic platform PR2. The thesis describes different devices for sensing and perception of a user and usage of information from these devices to control robotic arm. Moreover, different methods for controlling of robotic arm are described there. Application design and implementation is presented further in this thesis together with description of the experiments used for evaluation of application.

Tato práce se zaměřuje na použitelnost brýlí Microsoft HoloLens pro rozšířenou realitu v prototypu pracoviště pro spolupráci člověka s robotem - "ARTable". Použití brýlí je demonstrováno vytvořeným uživatelským rozhraním, které pomáhá uživatelům lépe a rychleji porozumět systému ARTable. Umožňuje prostorově vizualizovat naučené programy, aniž by bylo nutné spouštět samotného robota. Uživatel je veden 3D animací jednotlivých programů a hlasem zařízení, což mu pomůže získat jasnou představu o tom, co by se stalo, pokud by program spustil přímo na robotovi. Implementované řešení také umožňuje interaktivně provést uživatele celým procesem programování robota. Použití brýlí umožňuje mimo jiné zobrazit cenné prostorové informace, například vidění robota, tedy zvýraznit ty objekty, které jsou robotem detekovány.