Letteratura scientifica selezionata sul tema "Multi-scale architecture"

Mammalian nuclear function depends on the complex interaction of genetic and epi-genetic elements coordinated in space and time. Structure and function overlap to such a degree that they are usually considered as being inextricably linked. In this work I combine an experimental approach with a computational one in order to answer two main questions in the field of mammalian chromosome organization. In the first section of this thesis, I attempted to answer the question, to what extent does chromatin from different chromosome territories share the same space inside the nucleus? This is a relatively open question in the field of chromosome territories. It is well-known and accepted that interphase chromosomes are spatially constrained inside the nucleus and that they occupy their own territory, however, the degree of spatial interaction between neighbouring chromosomes is still under debate. Using labelling methods that directly incorporate halogenated DNA precursors into newly replicated DNA without the need for immuno-detection or in situ hybridization, we show that neighbouring chromosome territories colocalise at very low levels. We also found that the native structure of DNA foci is partially responsible for constraining the interaction of chromosome territories as disruption of the innate architecture of DNA foci by treatment with TSA resulted in increased colocalisation signal between adjacent chromosomes territories. The second major question I attempted to answer concerned the correlation between nuclear function and the banding pattern observed in human mitotic chromosomes. Human mitotic chromosomes display characteristic patterns of light and dark bands when visualized under the light microscope using specific chemical dyes such as Giemsa. Despite the long standing use of the Giemsa banding pattern in human genetics for identifying chromosome abnormalities and mapping genes, little is known about the molecular mechanisms that generate the Giemsa banding pattern or its biological relevance. The recent availability of many genetic and epigenetic features mapped to the human genome permit a high-resolution investigation of the molecular correlates of Giemsa banding. Here I investigate the relationship of more than 50 genomic and epigenomic features with light (R) and dark (G) bands. My results confirm many classical results, such as the low gene density of the most darkly staining G bands and their late replication time, using genome-wide data. Surprisingly, I found that for virtually all features investigated, R bands show intermediate properties between the lightest and darkest G bands, suggesting that many R bands contain G-like sequences within them. To identify R bands that show properties of G bands, I employed an unsupervised learning approach to classify R bands on their genomic and epigenomic properties and show that the smallest R bands show a tendency to have characteristics typical of G bands. I revisit the evidence supporting the boundaries of G and R bands in the current cytogenomic map and conclude that inaccurate placement of weakly supported band boundaries can explain the intermediate pattern of R bands. Finally, I propose an approach based on aggregating data from multiple genomic and epigenomic features to improve the positioning of band boundaries in the human cytogenomic map. My results suggest that contiguous domains showing a high degree of uniformity in the ratio of heterochromatin and euchromatin sub-domains define the Giemsa banding pattern in human chromosomes.

This thesis describes a methodology to deal with the interaction between MPC controllers in a distributed MPC architecture. This approach combines ideas from Distributed Artificial Intelligence (DAI) and Reinforcement Learning (RL) in order to provide a controller interaction based on cooperative agents and learning techniques. The aim of this methodology is to provide a general structure to perform optimal control in networked distributed environments, where multiple dependencies between subsystems are found. Those dependencies or connections often correspond to control variables. In that case, the distributed control has to be consistent in both subsystems. One of the main new concepts of this architecture is the negotiator agent. Negotiator agents interact with MPC agents to determine the optimal value of the shared control variables in a cooperative way using learning techniques (RL). The optimal value of those shared control variables has to accomplish a common goal, probably different from the specific goal of each agent sharing the variable. Two cases of study, in which the proposed architecture is applied and tested are considered, a small water distribution network and the Barcelona water network. The results suggest this approach is a promising strategy when centralized control is not a reasonable choice.<br>Esta tesis describe una metodología para hacer frente a la interacción entre controladores MPC en una arquitectura MPC distribuida. Este enfoque combina las ideas de Inteligencia Artificial Distribuida (DIA) y aprendizaje por refuerzo (RL) con el fin de proporcionar una interacción entre controladores basado en agentes de cooperativos y técnicas de aprendizaje. El objetivo de esta metodología es proporcionar una estructura general para llevar a cabo un control óptimo en entornos de redes distribuidas, donde se encuentran varias dependencias entre subsistemas. Esas dependencias o conexiones corresponden a menudo a variables de control. En ese caso, el control distribuido tiene que ser coherente en ambos subsistemas. Uno de los principales conceptos novedosos de esta arquitectura es el agente negociador. Los agentes negociadores actúan junto con agentes MPC para determinar el valor óptimo de las variables de control compartidas de forma cooperativa utilizando técnicas de aprendizaje (RL). El valor óptimo de esas variables compartidas debe lograr un objetivo común, probablemente diferente de los objetivos específicos de cada agente que está compartiendo la variable. Se consideran dos casos de estudio, en el que la arquitectura propuesta se ha aplicado y probado, una pequeña red de distribución de agua y la red de agua de Barcelona. Los resultados sugieren que este enfoque es una estrategia prometedora cuando el control centralizado no es una opción razonable.

High-throughput Chromosome Conformation Capture (3C) techniques have provided a comprehensive overview of the genome architecture. Hi-C, a derivative of 3C, has become a reference technique to study the 3D chromatin structure and its relationship with the functional state of the cell. However, several aspects of the analysis and interpretation of Hi-C data remain a challenge and may hide a potential yet to be unveiled. In this thesis, we explore the structural landscape of multiple chromatin features. We developed an integrative approach combining in situ Hi-C data with nine additional omic layers and revealed a new dynamic and transitional genomic compartment enriched in poised and polycomb-repressed chromatin. This novel intermediate compartment plays an important role in the modulation of the genome during B cells differentiation and upon neoplastic transformation, specifically in chronic lymphocytic leukemia (CLL) or mantle cell lymphoma (MCL) patients. We also developed TADpole, a computational tool designed to characterize the hierarchy of topologically-associated domains (TADs) using Hi-C interaction matrices. We demonstrated its technical and biological robustness, and its capacity to reveal topological differences in high-resolution capture Hi-C experiments.<br>El desarrollo de métodos experimentales basados en la captura de la conformación cromosómica (3C) ha permitido tener una visión más detallada de la arquitectura genómica. El Hi-C, derivado del 3C, se ha convertido en una técnica de referencia para analizar la estructura tridimensional de la cromatina, así como su relación con el estado funcional celular. Sin embargo, varios aspectos del análisis y la interpretación de los datos de Hi-C siguen siendo un desafío, y pueden ocultar un potencial aún por descubrir. En esta tesis se exploran múltiples niveles de organización estructural de la cromatina. Hemos realizado un estudio integrativo combinando datos de in situ Hi-C con nueve capas epigenéticas y hemos revelado un nuevo compartimento genómico caracterizado por su dinámica y capacidad de transición, enriquecido en cromatina reprimida por polycomb. Este nuevo compartimento intermedio juega un papel importante en la modulación del genoma durante la diferenciación de células B y durante su transformación neoplásica, específicamente en pacientes con leucemia linfocítica crónica (CLL) o con linfoma de células del manto (MCL). Además, hemos desarrollado TADpole, un nuevo método computacional destinado a la detección de la jerarquía de dominios asociados topológicamente (TADs) empleando mapas de interacciones de Hi-C. Hemos demostrado su robustez ante una evaluación técnica y biológica, así como su capacidad de detectar diferencias topológicas en experimentos de capture Hi-C de alta resolución.

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 67-70).<br>This thesis sets the stage for Fabrication Information Modeling (FIM); a design approach for enabling seamless design-to-production workflows that can derive complex designs fusing advanced digital design technologies associated with analysis, engineering and manufacturing. Present day digital fabrication platforms enable the design and construction of high-resolution and complex material distribution structures. However, virtual-to-physical workflows and their associated software environments are yet to incorporate such capabilities. As preliminary methods towards FIM I have developed four computational strategies for the design and digital construction of custom systems. These methods are presented in this thesis in the context of specific design challenges and include a biologically driven fiber construction algorithm; an anatomically driven shell-to-wearable translation protocol; an environmentally-driven swarm printing system; and a manufacturing-driven hierarchical fabrication platform. I discuss and analyze these four challenges in terms of their capabilities to integrate design across media, disciplines and scales through the concepts of multidimensionality, media-informed computation and trans-disciplinary data in advanced digital design workflows. With FIM I aim to contribute to the field of digital design and fabrication by enabling feedback workflows where materials are designed rather than selected; where the question of how information is passed across spatiotemporal scales is central to design generation itself; where modeling at each level of resolution and representation is based on various methods and carried out by various media or agents within a single environment; and finally, where virtual and physical considerations coexist as equals.<br>by Jorge Duro Royo.<br>S.M.

La stéréophotométrie est une technique de reconstruction 3D de la surface d'un objet. De plus en plus de recherches s'intéressent à ce problème qui se veut prometteur dans le monde industriel. En effet, la stéréophotométrie peut être utilisée pour détecter les défauts d'usinage de pièces mécaniques ou pour de la reconnaissance faciale par exemple. Cette thèse explore les méthodes d'apprentissage profond pour la stéréophotométrie, notamment les différents aspects liés aux bases de données d'entraînement et aux architectures considérées.De manière générale, la sur-paramétrisation d'un réseau de neurones est souvent suffisante pour supporter la diversité des problèmes rencontrés. La base de données d'entraînement est alors considérée comme le point clé permettant de conditionner le réseau au problème traité. Par conséquent, pour répondre à ce besoin, nous proposons une nouvelle base de données d'entraînement synthétique. Cette base de données considère une très grande variété de géométries, de textures, de directions ou conditions lumineuses mais également d'environnements, permettant donc de générer un nombre de situation quasiment infini.Le second point décisif d'une bonne reconstruction concerne le choix de l'architecture. L'architecture d'un réseau doit assurer une bonne capacité de généralisation sur de nouvelles données pour générer de très bons résultats sur des données inédites. Et ce, quelle que soit l'application. En particulier, pour la stéréophotométrie, l'enjeu est d'être capable de reconstruire des images très haute résolution afin de ne pas perdre de détails. Nous proposons alors une architecture multi-échelles de type encodeur-décodeur afin de répondre à ce problème.Dans un premier temps, nous proposons une architecture fondée sur les réseaux convolutionnels pour répondre au problème de stéréophotométrie calibrée, i.e. quand la direction lumineuse est connue. Dans un second temps, nous proposons une version fondé sur les Transformers afin de répondre au problème de stéréophotométrie universelle. C'est-à-dire que nous sommes en capacité de gérer n'importe quel environnement, direction lumineuse, etc., sans aucune information préalable. Finalement, pour améliorer les reconstructions sur des matériaux difficiles (translucides ou brillants par exemple), nous proposons une nouvelle approche que nous appelons ``faiblement calibrée'' pour la stéréophotométrie. Dans ce contexte, nous n'avons qu'une connaissance approximative de la direction d'éclairage.L'ensemble des pistes que nous avons explorées ont conduit à des résultats convaincants, à la fois quantitatifs et visuels sur l'ensemble des bases de données de l'état-de-l'art. En effet, nous avons pu observer une amélioration notable de la précision de reconstruction des cartes de normales, contribuant ainsi à avancer l'état de l'art dans ce domaine<br>Photometric stereo is a technique for 3D surface reconstruction of objects. This field has seen a surge in research interest due to its potential applications in industry. Specifically, photometric stereo can be employed for tasks such as detecting machining defects in mechanical components or facial recognition. This thesis delves into deep learning methods for photometry stero, with a particular focus on training data and network architectures.While neural network over-parameterization is often adequate, the training dataset plays a pivotal role in task adaptation. To generate a highly diverse and extensible training set, we propose a new synthetic dataset. This dataset incorporates a broad spectrum of geometric, textural, lighting, and environmental variations, allowing for the creation of nearly infinite training instances.The second decisive point of a good reconstruction concerns the choice of architecture. The architecture of a network must ensure a good generalization capacity on new data to generate very good results on unseen data. And this, regardless of the application. In particular, for the photometric stereo problem, the challenge is to be able to reconstruct very high-resolution images in order not to lose any details. We therefore propose a multi-scale encoder-decoder architecture to address this problem.We first introduce a convolutional neural network architecture for calibrated photometric stereo, where the lighting direction is known. To handle unconstrained environments, we propose a Transformers-based approach for universal photometric stereo. Lastly, for challenging materials shiny like translucent or shiny surfaces, we introduce a ``weakly calibrated'' approach that assumes only approximate knowledge of the lighting direction.The approaches we have investigated have consistently demonstrated strong performance on standard benchmarks, as evidenced by both quantitative metrics and visual assessments. Our results, particularly the improved accuracy of reconstructed normal maps, represent a significant advancement in photometric stereo

Buildings are directly responsible for 40% of the final energy use in most developed economies and for much more if indirect requirements are considered. This results in huge impacts which affect the environmental balance of our planet.<p>However, most current building energy assessments focus solely on operational energy overlooking other energy uses such as embodied and transport energy. Embodied energy comprises the energy requirements for building materials production, construction and replacement. Transport energy represents the amount of energy required for the mobility of building users.<p>Decisions based on partial assessments might result in an increased energy demand during other life cycle stages or at different scales of the built environment. Recent studies have shown that embodied and transport energy demands often account for more than half of the total lifecycle energy demand of residential buildings. Current assessment tools and policies therefore overlook more than 50% of the life cycle energy use.<p>This thesis presents a comprehensive life cycle energy analysis framework for residential buildings. This framework takes into account energy requirements at the building scale, i.e. the embodied and operational energy demands, and at the city scale, i.e. the embodied energy of nearby infrastructures and the transport energy of its users. This framework is implemented through the development, verification and validation of an advanced software tool which allows the rapid analysis of the life cycle energy demand of residential buildings and districts. Two case studies, located in Brussels, Belgium and Melbourne, Australia, are used to investigate the potential of the developed framework.<p>Results show that each of the embodied, operational and transport energy requirements represent a significant share of the total energy requirements and associated greenhouse gas emissions of a residential building, over its useful life. The use of the developed tool will allow building designers, town planners and policy makers to reduce the energy demand and greenhouse gas emissions of residential buildings by selecting measures that result in overall savings. This will ultimately contribute to reducing the environmental impact of the built environment.<br>Doctorat en Sciences de l'ingénieur<br>info:eu-repo/semantics/nonPublished