[pt] Determinar a proveniência dos dados, isto é, o processo que levou a esses dados, é vital em muitas áreas, especialmente quando é essencial que os resultados ou ações sejam confiáveis. Com o crescente número de aplicações baseadas em inteligência artificial, criou-se a necessidade de torná-las capazes de explicar seu comportamento e responder às suas decisões. Isso é um desafio, especialmente se as aplicações forem distribuídas e compostas de vários agentes autônomos, formando um Sistema Multiagente (SMA). Uma maneira fundamental de tornar tais sistemas explicáveis é rastrear o comportamento do agente, isto é, registrar a origem de suas ações e raciocínios, como em uma depuração onisciente. Embora a ideia de proveniência já tenha sido explorada em alguns contextos, ela não foi extensivamente explorada no contexto de SMA, deixando muitas questões para serem compreendidas e abordadas. Nosso objetivo neste trabalho é justificar a importância da proveniência dos dados para SMA, discutindo quais perguntas podem ser respondidas em relação ao comportamento do SMA, utilizando a proveniência e ilustrando, através de cenários de aplicação, os benefícios que a proveniência proporciona para responder a essas questões. Este estudo envolve a criação de um framework de software, chamado FProvW3C, que suporta a coleta e armazenamento da proveniência dos dados produzidos pelo SMA, que foi integrado a plataforma BDI4JADE (41), formando o que denominamos de Prov-BDI4JADE. Por meio desta plataforma, utilizando exemplos de sistemas autônomos, demostramos com rigor que, o uso da proveniência de dados em SMA é uma solução sólida, para tornar transparente o processo de raciocínio e ação do agente. / [en] Determining the data provenance, that is, the process that led to those data, is vital in many areas, especially when it is essential that the results or actions be reliable. With the increasing number of applications based on artificial intelligence, the need has been created to make them capable of explaining their behavior and be responsive to their decisions. This is a challenge especially if the applications are distributed, and composed of multiple autonomous agents, forming a Multiagent System (MAS). A key way of making such systems explicable is to track the agent s behavior, that is, to record the source of their actions and reasoning, as in an omniscient debugging. Although the idea of provenance has already been explored in some contexts, it has not been extensively explored in the context of MAS, leaving many questions to be understood and addressed. Our objective in this work is to justify the importance of the data provenance to MAS, discussing which questions can be answered regarding the behavior of MAS using the provenance and illustrating, through application scenarios, to demonstrate the benefits that provenance provides to reply to these questions. This study involves the creation of a software framework, called FProvW3C, which supports the collects and stores the provenance of the data produced by the MAS, which was integrated with the platform BDI4JADE (41), forming what we call Prov-BDI4JADE. Through this platform, using examples of autonomous systems, we have rigorously demonstrated that the use of data provenance in MAS is a solid solution to make the agent’s reasoning and action process transparent.

Spinal Muscular Atrophy with Progressive Myoclonic Epilepsy (SMA-PME), Farber Lipogranulomatosis (FL), and a rare variant form of Neonatal Progeroid Syndrome (NPS) are three monogenetic rare disorders caused by pathogenic variation in genes encoding lipid modifying proteins. FL and SMA-PME are caused by loss of function mutations in ASAH1, encoding the acid ceramidase (aCDase) enzyme. It is not, however, known how aCDase deficiency can produce either the isolated neurological symptoms of SMA-PME or the predominantly systemic symptoms of FL. Further, a recently identified variant form of NPS has been attributed to variants in ANO6, encoding a dual function calcium-activated chloride channel and glycerophosphoserine (GPS) scramblase. Here, it is not known how ANO6 mutation causes the premature aging phenotype that defines NPS. To address these questions, I sought to elucidate pathogenic changes in lipid metabolism that associate clinical phenotype. I show here that the different patient mutations in ANO6 cause a non-physiological gain of channel function and either a loss or gain of scramblase function depending on the variant expressed. Both variants, however, alter GPS metabolic homeostasis suggesting a common mechanism of action. To provide in vivo insight, I characterized a novel mouse model based on our NPS patient genetics, showing extremely low penetrance of disease symptoms in terms of live births yet confirming that affected animals show impaired GPS metabolism in affected organs. Next, I characterized the clinical presentation of six new patients with SMA-PME and identified distinct sphingolipid metabolic fingerprints in FL and SMA-PME cells. I show that FL is defined by a hypometabolic sphingolipid phenotype with cellular and molecular features of a classic lysosomal storage disorder. By contrast, SMA-PME has a hypermetabolic sphingolipid phenotype with features of non-classic lysosomal trafficking disorders. To provide clinical insight, I assessed the potential of enzyme replacement therapy, demonstrating a rescue of sphingolipid metabolism in SMA-PME patient cells. Together, this thesis identified changes in the cellular and tissue lipid profiles of patients with ANO6-NPS, SMA-PME, or FL, elucidating some of the lipid-centric pathomechanisms of these diseases.

No description available.

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The development of micro and nano-electromechanical systems (MEMS and NEMS) with entirely new or improved functionalities is typically based on novel or improved designs, materials and fabrication methods. However, today’s micro- and nano-fabrication is restrained by manufacturing paradigms that have been established by the integrated circuit (IC) industry over the past few decades. The exclusive use of IC manufacturing technologies leads to limited material choices, limited design flexibility and consequently to sub-optimal MEMS and NEMS devices. The work presented in this thesis breaks new ground with a multitude of novel approaches for the integration of non-standard materials that enable the fabrication of 3D micro and nanoelectromechanical systems. The objective of this thesis is to highlight methods that make use of non-standard materials with superior characteristics or methods that use standard materials and fabrication techniques in a novel context. The overall goal is to propose suitable and cost-efficient fabrication and integration methods, which can easily be made available to the industry. The first part of the thesis deals with the integration of bulk wire materials. A novel approach for the integration of at least partly ferromagnetic bulk wire materials has been implemented for the fabrication of high aspect ratio through silicon vias. Standard wire bonding technology, a very mature back-end technology, has been adapted for yet another through silicon via fabrication method and applications including liquid and vacuum packaging as well as microactuators based on shape memory alloy wires. As this thesis reveals, wire bonding, as a versatile and highly efficient technology, can be utilized for applications far beyond traditional interconnections in electronics packaging. The second part presents two approaches for the 3D heterogeneous integration based on layer transfer. Highly efficient monocrystalline silicon/ germanium is integrated on wafer-level for the fabrication of uncooled thermal image sensors and monolayer-graphene is integrated on chip-level for the use in diaphragm-based pressure sensors. The last part introduces a novel additive fabrication method for layer-bylayer printing of 3D silicon micro- and nano-structures. This method combines existing technologies, including focused ion beam implantation and chemical vapor deposition of silicon, in order to establish a high-resolution fabrication process that is related to popular 3D printing techniques. / <p>QC 20121207</p>

Spinal muscular atrophy (SMA) and Charcot-Marie-Tooth disease type 2D (CMT2D)/distal SMA type V (dSMAV) are two incurable neuromuscular disorders that predominantly manifest during childhood and adolescence. Both conditions are caused by mutations in widely and constitutively expressed genes that encode proteins with essential housekeeping functions, yet display specific lower motor neuron pathology. SMA results from recessive inactivating mutations in the survival motor neuron 1 (SMN1) gene, while CMT2D/dSMAV manifests due to dominant point mutations in the glycyl-tRNA synthetase (GlyRS) gene, GARS. Using a number of different model systems, ranging from Caenorhabditis elegans to the mouse, this thesis aimed to identify potential novel therapeutic compounds for SMA, and to increase our understanding of the mechanisms underlying both diseases. I characterised a novel C. elegans allele, which possesses a point mutation in the worm SMN1 orthologue, smn-1, and showed its potential for large-scale screening by highlighting 4-aminopyridine in a screen for compounds able to improve the mutant motility defect. Previously, the gene encoding three isoforms of chondrolectin (Chodl) was shown to be alternatively spliced in the spinal cord of SMA mice before disease onset. I performed functional analyses of the three isoforms in neuronal cells with experimentally reduced Smn levels, and determined that the dysregulation of Chodl likely reflects a combination of compensatory mechanism and contributor to pathology, rather than mis-splicing. Finally, working with two Gars mutant mice and a new Drosophila model, I have implicated semaphorin-plexin pathways and axonal guidance in the GlyRS toxic gain-of-function disease mechanism of CMT2D/dSMAV.

La raréfaction des sources de production conventionnelles et leurs émissions nocives ont favorisé l’essor notable de la production renouvelable, plus durable et mieux répartie géographiquement. Toutefois, son intégration au système électrique est problématique. En effet, la production renouvelable est peu prédictible et issue de sources majoritairement incontrôlables, ce qui compromet la stabilité du réseau, la viabilité économique des producteurs et rend nécessaire la définition de solutions adaptées pour leur participation au marché de l’électricité. Dans ce contexte, le projet scientifique Winpower propose de relier par un réseau à courant continu les ressources de plusieurs acteurs possédant respectivement des fermes éoliennes offshore (acteurs EnR) et des centrales de stockage de masse (acteurs CSM). Cette configuration impose aux acteurs d’assurer conjointement la gestion du réseau électrique.Nous supposons que les acteurs participent au marché comme une entité unique : cette hypothèse permet aux acteurs EnR de tirer profit de la flexibilité des ressources contrôlables pour minimiser le risque de pénalités sur le marché de l’électricité, aux acteurs CSM de valoriser leurs ressources auprès des acteurs EnR et/ou auprès du marché et à la coalition de faciliter la gestion des déséquilibres sur le réseau électrique, en agrégeant les ressources disponibles. Dans ce cadre, notre travail s’attaque à la problématique de la participation au marché EPEX SPOT Day-Ahead de la coalition comme une centrale électrique virtuelle ou CVPP (Cooperative Virtual Power Plant). Nous proposons une architecture de pilotage multi-acteurs basée sur les systèmes multi-agents (SMA) : elle permet d’allier les objectifs et contraintes locaux des acteurs et les objectifs globaux de la coalition.Nous formalisons alors l’agrégation et la planification de l’utilisation des ressources comme un processus décisionnel de Markov (MDP), un modèle formel adapté à la décision séquentielle en environnement incertain, pour déterminer la séquence d’actions sur les ressources contrôlables qui maximise l’espérance des revenus effectifs de la coalition. Toutefois, au moment de la planification des ressources de la coalition, l’état de la production renouvelable n’est pas connue et le MDP n’est pas résoluble en l’état : on parle de MDP partiellement observable (POMDP). Nous décomposons le POMDP en un MDP classique et un état d’information (la distribution de probabilités des erreurs de prévision de la production renouvelable) ; en extrayant cet état d’information de l’expression du POMDP, nous obtenons un MDP à état d’information (IS-MDP), pour la résolution duquel nous proposons une adaptation d’un algorithme de résolution classique des MDP, le Backwards Induction.Nous décrivons alors un cadre de simulation commun pour comparer dans les mêmes conditions nos propositions et quelques autres stratégies de participation au marché dont l’état de l’art dans la gestion des ressources renouvelables et contrôlables. Les résultats obtenus confortent l’hypothèse de la minimisation du risque associé à la production renouvelable, grâce à l’agrégation des ressources et confirment l’intérêt de la coopération des acteurs EnR et CSM dans leur participation au marché de l’électricité. Enfin, l’architecture proposée offre la possibilité de distribuer le processus de décision optimale entre les différents acteurs de la coalition : nous proposons quelques pistes de solution dans cette direction. / Renewable Energy Sources (RES) has grown remarkably in last few decades. Compared to conventional energy sources, renewable generation is more available, sustainable and environment-friendly - for example, there is no greenhouse gases emission during the energy generation. However, while electrical network stability requires production and consumption equality and the electricity market constrains producers to contract future production a priori and respect their furniture commitments or pay substantial penalties, RES are mainly uncontrollable and their behavior is difficult to forecast accurately. De facto, they jeopardize the stability of the physical network and renewable producers competitiveness in the market. The Winpower project aims to design realistic, robust and stable control strategies for offshore networks connecting to the main electricity system renewable sources and controllable storage devices owned by different autonomous actors. Each actor must embed its own local physical device control strategy but a global network management mechanism, jointly decided between connected actors, should be designed as well.We assume a market participation of the actors as an unique entity (the coalition of actors connected by the Winpower network) allowing the coalition to facilitate the network management through resources aggregation, renewable producers to take advantage of controllable sources flexibility to handle market penalties risks, as well as storage devices owners to leverage their resources on the market and/or with the management of renewable imbalances. This work tackles the market participation of the coalition as a Cooperative Virtual Power Plant. For this purpose, we describe a multi-agent architecture trough the definition of intelligent agents managing and operating actors resources and the description of these agents interactions; it allows the alliance of local constraints and objectives and the global network management objective.We formalize the aggregation and planning of resources utilization as a Markov Decision Process (MDP), a formal model suited for sequential decision making in uncertain environments. Its aim is to define the sequence of actions which maximize expected actual incomes of the market participation, while decisions over controllable resources have uncertain outcomes. However, market participation decision is prior to the actual operation when renewable generation still is uncertain. Thus, the Markov Decision Process is intractable as its state in each decision time-slot is not fully observable. To solve such a Partially Observable MDP (POMDP), we decompose it into a classical MDP and an information state (a probability distribution over renewable generation errors). The Information State MDP (IS-MDP) obtained is solved with an adaptation of the Backwards Induction, a classical MDP resolution algorithm.Then, we describe a common simulation framework to compare our proposed methodology to some other strategies, including the state of the art in renewable generation market participation. Simulations results validate the resources aggregation strategy and confirm that cooperation is beneficial to renewable producers and storage devices owners when they participate in electricity market. The proposed architecture is designed to allow the distribution of the decision making between the coalition’s actors, through the implementation of a suitable coordination mechanism. We propose some distribution methodologies, to this end.

This thesis presents methods for the wafer-level integration of shape memory alloy (SMA) and electrostatic actuators to functionalize MEMS devices. The integration methods are based on heterogeneous integration, which is the integration of different materials and technologies. Background information about the actuators and the integration method is provided. SMA microactuators offer the highest work density of all MEMS actuators, however, they are not yet a standard MEMS material, partially due to the lack of proper wafer-level integration methods. This thesis presents methods for the wafer-level heterogeneous integration of bulk SMA sheets and wires with silicon microstructures. First concepts and experiments are presented for integrating SMA actuators with knife gate microvalves, which are introduced in this thesis. These microvalves feature a gate moving out-of-plane to regulate a gas flow and first measurements indicate outstanding pneumatic performance in relation to the consumed silicon footprint area. This part of the work also includes a novel technique for the footprint and thickness independent selective release of Au-Si eutectically bonded microstructures based on localized electrochemical etching. Electrostatic actuators are presented to functionalize MEMS crossbar switches, which are intended for the automated reconfiguration of copper-wire telecommunication networks and must allow to interconnect a number of input lines to a number of output lines in any combination desired. Following the concepts of heterogeneous integration, the device is divided into two parts which are fabricated separately and then assembled. One part contains an array of double-pole single-throw S-shaped actuator MEMS switches. The other part contains a signal line routing network which is interconnected by the switches after assembly of the two parts. The assembly is based on patterned adhesive wafer bonding and results in wafer-level encapsulation of the switch array. During operation, the switches in these arrays must be individually addressable. Instead of controlling each element with individual control lines, this thesis investigates a row/column addressing scheme to individually pull in or pull out single electrostatic actuators in the array with maximum operational reliability, determined by the statistical parameters of the pull-in and pull-out characteristics of the actuators. / QC20100729

Made available in DSpace on 2016-08-17T14:52:45Z (GMT). No. of bitstreams: 1 Yonara Magalhaes.pdf: 3488130 bytes, checksum: e183eccb37268ce608c84048d98d467a (MD5) Previous issue date: 2003-01-31 / Cooperative process of teach-learning at a distance of the society of intelligent agents of environment MATHNET. It is presented architecture of the society of agents of the MATHNET that to provide the process with teach-learning. It is in exchange for distinguished the Tutor Agent and the model of communication, based messages and that it uses the FIPA-ACL Agent Communication Language, between the Tutor Agent and excessively the participant agents of this society. The main characteristics and the paper (responsibilities) of the Tutor Agent describe. Its conceptual model is constructed. Its main Cases Use, interactions with several agents of this architecture and the protocols of communication of the Tutor Agent with the other agents are shaped. The Tutor Agent creates itself using a tool of construction of agents. One implements the Tutor Agent and its Cases Use to inside demonstrate to its relevance and importance of the system and the model of communication. / Processo de ensino-aprendizagem cooperativo à distância da sociedade de agentes inteligentes do ambiente MATHNET. Apresenta-se a arquitetura da sociedade de agentes do MATHNET que provê o processo de ensino-aprendizagem. Destaca-se o Agente Tutor e o modelo de comunicação, baseado em troca de mensagens e que utiliza a Linguagem de Comunicação FIPA-ACL, entre o Agente Tutor e os demais agentes participantes dessa sociedade. Descrevem-se as principais características e o papel (responsabilidades) do Agente Tutor. Constrói-se o seu modelo conceitual. Modelam-se os seus principais Casos de Uso, as interações com os demais agentes dessa arquitetura e os protocolos de comunicação do Agente Tutor com os outros agentes. Cria-se o Agente Tutor utilizando para isto uma ferramenta de construção de agentes. Implementa-se o Agente Tutor e seus Casos de Uso para demonstrar sua relevância e importância dentro do sistema e o modelo de comunicação aqui proposto.