1,516 research outputs found

    State of the Art in Face Recognition

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    Notwithstanding the tremendous effort to solve the face recognition problem, it is not possible yet to design a face recognition system with a potential close to human performance. New computer vision and pattern recognition approaches need to be investigated. Even new knowledge and perspectives from different fields like, psychology and neuroscience must be incorporated into the current field of face recognition to design a robust face recognition system. Indeed, many more efforts are required to end up with a human like face recognition system. This book tries to make an effort to reduce the gap between the previous face recognition research state and the future state

    In Vivo Bioengineering of Fluorescent Conductive Protein-Dye Microfibers

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    Engineering protein-based biomaterials is extremely challenging in bioelectronics, medicine, and materials science, as mechanical, electrical, and optical properties need to be merged to biocompatibility and resistance to biodegradation. An effective strategy is the engineering of physiological processes in situ, by addition of new properties to endogenous components. Here we show that a green fluorescent semiconducting thiophene dye, DTTO, promotes, in vivo, the biogenesis of fluorescent conductive protein microfibers via metabolic pathways. By challenging the simple freshwater polyp Hydra vulgaris with DTTO, we demonstrate the stable incorporation of the dye into supramolecular protein-dye co-assembled microfibers without signs of toxicity. An integrated multilevel analysis including morphological, optical, spectroscopical, and electrical characterization shows electrical conductivity of biofibers, opening the door to new opportunities for augmenting electronic functionalities within living tissue, which may be exploited for the regulation of cell and animal physiology, or in pathological contexts to enhance bioelectrical signaling

    Information extraction and transmission techniques for spaceborne synthetic aperture radar images

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    Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively

    Combining perceptual features with diffusion distance for face recognition

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    Modeling complex cellular systems: from differential equations to constraint-based models

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    In the beginning of the 20th century, scientists realized the necessity of purifying enzymes to unravel their mechanistic nature. A century and tremendous progresses in the natural sciences later, molecular and systems biology became fundamental pillars of modern biology. Moreover, natural scientists developed an increasing interest in theoretical models. In the first part of my thesis, I present my contribution to the field of studying the dynamics of biological phenomena. I present fundamental issues arising, when neglecting substrate inhibition in kinetic modeling. Furthermore, I describe a model that considers experimental data to simulate the transition of normal proliferating into cellular senescent cells. Since large-scaled models are more comprehensive, they commonly prohibit a mechanistic modeling approach. In order to analyze such models, nevertheless, constraint-based methods proved to be suitable tools. In the second part of my thesis, I contribute three studies to constraint-based modeling. I describe the established concept of elementary flux modes, which resemble non-decomposable and theoretically feasible pathways of metabolic networks. Subsequently, I present the analysis of the nitrogen metabolism network of Chlamydomonas reinhardtii with respect to circadian regulation, which gives rise to about three million elementary flux modes. In the last study, I present a comprehensive work on metabolic costs of amino acid and protein production in Escherichia coli. These costs were manually calculated as well as based on a flux balance analysis of an E. coli genome-scale metabolic model. Both approaches, either dynamic or constraint-based modeling, proved to be suitable strategies to describe biological processes at different levels. Whereas dynamic modeling allowed for a precise description of the temporal behavior of biological species, constraint-based modeling enabled studies, where the complexity of the investigated phenomena prohibits kinetic modeling

    Hepatitis C Virus Controls Interferon Production through PKR Activation

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    Hepatitis C virus is a poor inducer of interferon (IFN), although its structured viral RNA can bind the RNA helicase RIG-I, and activate the IFN-induction pathway. Low IFN induction has been attributed to HCV NS3/4A protease-mediated cleavage of the mitochondria-adapter MAVS. Here, we have investigated the early events of IFN induction upon HCV infection, using the cell-cultured HCV JFH1 strain and the new HCV-permissive hepatoma-derived Huh7.25.CD81 cell subclone. These cells depend on ectopic expression of the RIG-I ubiquitinating enzyme TRIM25 to induce IFN through the RIG-I/MAVS pathway. We observed induction of IFN during the first 12 hrs of HCV infection, after which a decline occurred which was more abrupt at the protein than at the RNA level, revealing a novel HCV-mediated control of IFN induction at the level of translation. The cellular protein kinase PKR is an important regulator of translation, through the phosphorylation of its substrate the eIF2α initiation factor. A comparison of the expression of luciferase placed under the control of an eIF2α-dependent (IRESEMCV) or independent (IRESHCV) RNA showed a specific HCV-mediated inhibition of eIF2α-dependent translation. We demonstrated that HCV infection triggers the phosphorylation of both PKR and eIF2α at 12 and 15 hrs post-infection. PKR silencing, as well as treatment with PKR pharmacological inhibitors, restored IFN induction in JFH1-infected cells, at least until 18 hrs post-infection, at which time a decrease in IFN expression could be attributed to NS3/4A-mediated MAVS cleavage. Importantly, both PKR silencing and PKR inhibitors led to inhibition of HCV yields in cells that express functional RIG-I/MAVS. In conclusion, here we provide the first evidence that HCV uses PKR to restrain its ability to induce IFN through the RIG-I/MAVS pathway. This opens up new possibilities to assay PKR chemical inhibitors for their potential to boost innate immunity in HCV infection

    New algorithms for the analysis of live-cell images acquired in phase contrast microscopy

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    La détection et la caractérisation automatisée des cellules constituent un enjeu important dans de nombreux domaines de recherche tels que la cicatrisation, le développement de l'embryon et des cellules souches, l’immunologie, l’oncologie, l'ingénierie tissulaire et la découverte de nouveaux médicaments. Étudier le comportement cellulaire in vitro par imagerie des cellules vivantes et par le criblage à haut débit implique des milliers d'images et de vastes quantités de données. Des outils d'analyse automatisés reposant sur la vision numérique et les méthodes non-intrusives telles que la microscopie à contraste de phase (PCM) sont nécessaires. Comme les images PCM sont difficiles à analyser en raison du halo lumineux entourant les cellules et de la difficulté à distinguer les cellules individuelles, le but de ce projet était de développer des algorithmes de traitement d'image PCM dans Matlab® afin d’en tirer de l’information reliée à la morphologie cellulaire de manière automatisée. Pour développer ces algorithmes, des séries d’images de myoblastes acquises en PCM ont été générées, en faisant croître les cellules dans un milieu avec sérum bovin (SSM) ou dans un milieu sans sérum (SFM) sur plusieurs passages. La surface recouverte par les cellules a été estimée en utilisant un filtre de plage de valeurs, un seuil et une taille minimale de coupe afin d'examiner la cinétique de croissance cellulaire. Les résultats ont montré que les cellules avaient des taux de croissance similaires pour les deux milieux de culture, mais que celui-ci diminue de façon linéaire avec le nombre de passages. La méthode de transformée par ondelette continue combinée à l’analyse d'image multivariée (UWT-MIA) a été élaborée afin d’estimer la distribution de caractéristiques morphologiques des cellules (axe majeur, axe mineur, orientation et rondeur). Une analyse multivariée réalisée sur l’ensemble de la base de données (environ 1 million d’images PCM) a montré d'une manière quantitative que les myoblastes cultivés dans le milieu SFM étaient plus allongés et plus petits que ceux cultivés dans le milieu SSM. Les algorithmes développés grâce à ce projet pourraient être utilisés sur d'autres phénotypes cellulaires pour des applications de criblage à haut débit et de contrôle de cultures cellulaires.Automated cell detection and characterization is important in many research fields such as wound healing, embryo development, immune system studies, cancer research, parasite spreading, tissue engineering, stem cell research and drug research and testing. Studying in vitro cellular behavior via live-cell imaging and high-throughput screening involves thousands of images and vast amounts of data, and automated analysis tools relying on machine vision methods and non-intrusive methods such as phase contrast microscopy (PCM) are a necessity. However, there are still some challenges to overcome, since PCM images are difficult to analyze because of the bright halo surrounding the cells and blurry cell-cell boundaries when they are touching. The goal of this project was to develop image processing algorithms to analyze PCM images in an automated fashion, capable of processing large datasets of images to extract information related to cellular viability and morphology. To develop these algorithms, a large dataset of myoblasts images acquired in live-cell imaging (in PCM) was created, growing the cells in either a serum-supplemented (SSM) or a serum-free (SFM) medium over several passages. As a result, algorithms capable of computing the cell-covered surface and cellular morphological features were programmed in Matlab®. The cell-covered surface was estimated using a range filter, a threshold and a minimum cut size in order to look at the cellular growth kinetics. Results showed that the cells were growing at similar paces for both media, but their growth rate was decreasing linearly with passage number. The undecimated wavelet transform multivariate image analysis (UWT-MIA) method was developed, and was used to estimate cellular morphological features distributions (major axis, minor axis, orientation and roundness distributions) on a very large PCM image dataset using the Gabor continuous wavelet transform. Multivariate data analysis performed on the whole database (around 1 million PCM images) showed in a quantitative manner that myoblasts grown in SFM were more elongated and smaller than cells grown in SSM. The algorithms developed through this project could be used in the future on other cellular phenotypes for high-throughput screening and cell culture control applications

    Characterization of Bacterial Metabolites Involved in Host Pathogen Resistance

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    The intestinal microbiome can mediate host resistance to enteric pathogens by modulating host immunity or by directly inhibiting pathogen growth and virulence. Although the abundance and diversity of bacterial metabolites in the intestine is appreciated, the majority of intestinal bacteria and bacterial products have not been characterized in the context of microbiota-mediated pathogen resistance. In this thesis, we describe two projects aimed at developing new methodologies to study how intestinal bacteria, and the metabolites they generate, inhibit bacterial pathogenesis. In Chapters 2 and 3, we use a chemical reporter strategy to analyze fatty acid protein modifications in bacteria. Dietary and bacterially-produced fatty acids can modulate the virulence of various pathogens, such as Salmonella typhimurium, possibly through covalent protein modification. We demonstrate that alkynyl-functionalized fatty acids can be metabolized and covalently attached to known fatty-acylated proteins in E. coli. Proteomic analysis of modified proteins revealed an unconventional fatty-acid modification on the metabolic enzyme YjgF, highlighting the utility of this method for the discovery of novel sites of fatty-acylation. Using these reporters, we also explored the effects of fatty acids on S. typhimurium virulence. Our results in S. typhimurium underscored the extensive fatty acid metabolism of this pathogen as compared to E. coli, and revealed a potential fatty acid modification on the virulence factor HilA. In addition, we demonstrated that alkynyl-functionalized short chain fatty acids, like natural fatty acids, can inhibit the secretion of Salmonella virulence factors in vitro. Overall, our results suggest that alkynyl-functionalized fatty acids may be useful for analyzing Salmonella metabolism and virulence. In Chapter 4, we describe a C. elegans model system that we used to investigate the effects of Enterococcus faecium on bacterial pathogenesis. Probiotic strains of E. faecium can inhibit the virulence of several intestinal pathogens, including Salmonella typhimurium, but it is unknown if E. faecium directly targets pathogens or modulates host immunity. Through a combination of genetic, biochemical, and proteomic approaches, we identified a secreted peptidoglycan hydrolase (SagA) from E. faecium that confers protection against Salmonella pathogenesis. Our results indicate that SagA does not directly inhibit pathogen growth, but instead remodels peptidoglycan in vivo to enhance host resistance to pathogenesis. We define specific peptidoglycan fragments that are sufficient for mediating host protection, and show that this protection requires the host gene tol-1. Notably, introduction of SagA into a non-protective intestinal bacteria, E. faecalis, is sufficient to mediate host protection in C. elegans as well as germ-free mice, suggesting that SagA acts through evolutionarily conserved host pathways. We hypothesize that SagA-generated peptidoglycan fragments may strengthen intestinal barrier integrity through local innate immune activation to confine pathogens to the intestinal lumen. Our results suggest that commensal bacteria can restrict intestinal pathogens by directly modifying microbial-associated molecular patterns in the intestine. Overall, the projects described in this thesis underscore the role of bacterial metabolites, such as fatty acids and peptidoglycan fragments, in restricting intestinal pathogens

    Global Audience Participation in the Production and Consumption of Gangnam Style

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    This thesis examines the cultural consumption of the Korean music video Gangnam Style in the broader context of the increasing popularity of Korean popular content, often called the Korean Wave, and of complex conditions of transnational consumption. Specifically, it investigates why the music video Gangnam Style gained popularity not only in East Asia but also over the world, how it is circulated, and what conditions contribute to its success. It focuses on the role of the networked audiences and the interactions between the networked audiences and mainstream media through a chronological analysis on the distribution and reproduction process of Gangnam Style on YouTube. Through the case study of Gangman Style, this thesis attempts to rethink the established globalization theories and to suggest new perspective of cultural circulation in the globalized and digitalized media environment

    A framework for the design, prototyping and evaluation of mobile interfaces for domestic environments

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    The idea of the smart home has been discussed for over three decades, but it has yet to achieve mass-market adoption. This thesis asks the question Why is my home not smart? It highlights four main areas that are barriers to adoption, and concentrates on a single one of these issues: usability. It presents an investigation that focuses on design, prototyping and evaluation of mobile interfaces for domestic environments resulting in the development of a novel framework. A smart home is the physical realisation of a ubiquitous computing system for domestic living. The research area offers numerous benefits to end-users such as convenience, assistive living, energy saving and improved security and safety. However, these benefits have yet to become accessible due to a lack of usable smart home control interfaces. This issue is considered a key reason for lack of adoption and is the focus for this thesis. Within this thesis, a framework is introduced as a novel approach for the design, prototyping and evaluation of mobile interfaces for domestic environments. Included within this framework are three components. Firstly, the Reconfigurable Multimedia Environment (RME), a physical evaluation and observation space for conducting user centred research. Secondly, Simulated Interactive Devices (SID), a video-based development and control tool for simulating interactive devices commonly found within a smart home. Thirdly, iProto, a tool that facilitates the production and rapid deployment of high fidelity prototypes for mobile touch screen devices. This framework is evaluated as a round-tripping toolchain for prototyping smart home control and found to be an efficient process for facilitating the design and evaluation of such interfaces
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