206 research outputs found

    A new feature extraction method based on clustering for face recognition

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    Part 13: Feature Extraction - MinimizationInternational audienceWhen solving a pattern classification problem, it is common to apply a feature extraction method as a pre-processing step, not only to reduce the computation complexity but also to obtain better classification performance by reducing the amount of irrelevant and redundant information in the data. In this study, we investigate a novel schema for linear feature extraction in classification problems. The method we have proposed is based on clustering technique to realize feature extraction. It focuses in identifying and transforming redundant information in the data. A new similarity measure-based trend analysis is devised to identify those features. The simulation results on face recognition show that the proposed method gives better or competitive results when compared to conventional unsupervised methods like PCA and ICA

    ACCIO: How to Make Location Privacy Experimentation Open and Easy

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    The advent of mobile applications collecting and exploiting the location of users opens a number of privacy threats. To mitigate these privacy issues, several protection mechanisms have been proposed this last decade to protect users' location privacy. However, these protection mechanisms are usually implemented and evaluated in monolithic way, with heterogeneous tools and languages. Moreover, they are evaluated using different methodologies, metrics and datasets. This lack of standard makes the task of evaluating and comparing protection mechanisms particularly hard. In this paper, we present ACCIO, a unified framework to ease the design and evaluation of protection mechanisms. Thanks to its Domain Specific Language, ACCIO allows researchers and practitioners to define and deploy experiments in an intuitive way, as well as to easily collect and analyse the results. ACCIO already comes with several state-of-the-art protection mechanisms and a toolbox to manipulate mobility data. Finally, ACCIO is open and easily extensible with new evaluation metrics and protection mechanisms. This openness, combined with a description of experiments through a user-friendly DSL, makes ACCIO an appealing tool to reproduce and disseminate research results easier. In this paper, we present ACCIO's motivation and architecture, and demonstrate its capabilities through several use cases involving multiples metrics, state-of-the-art protection mechanisms, and two real-life mobility datasets collected in Beijing and in the San Francisco area

    The Constitutive Lack of α7 Nicotinic Receptor Leads to Metabolic Disorders in Mouse.

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    Type 2 diabetes (T2D) occurs by deterioration in pancreatic β-cell function and/or progressive loss of pancreatic β-cell mass under the context of insulin resistance. α7 nicotinic acetylcholine receptor (nAChR) may contribute to insulin sensitivity but its role in the pathogenesis of T2D remains undefined. We investigated whether the systemic lack of α7 nAChR was sufficient to impair glucose homeostasis. We used an α7 nAChR knock-out (α7 <sup>-/-</sup> ) mouse model fed a standard chow diet. The effects of the lack of α7 nAChR on islet mass, insulin secretion, glucose and insulin tolerance, body composition, and food behaviour were assessed in vivo and ex vivo experiments. Young α7 <sup>-/-</sup> mice display a chronic mild high glycemia combined with an impaired glucose tolerance and a marked deficit in β-cell mass. In addition to these metabolic disorders, old mice developed adipose tissue inflammation, elevated plasma free fatty acid concentrations and presented glycolytic muscle insulin resistance in old mice. Finally, α7 <sup>-/-</sup> mice, fed a chow diet, exhibited a late-onset excessive gain in body weight through increased fat mass associated with higher food intake. Our work highlights the important role of α7 nAChR in glucose homeostasis. The constitutive lack of α7 nAChR suggests a novel pathway influencing the pathogenesis of T2D

    Genetics and beyond - the transcriptome of human monocytes and disease susceptibility

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    BACKGROUND: Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes. METHODOLOGY/PRINCIPAL FINDINGS: To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78x10(-12)), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9x10(-7)), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment

    SIGNATURE: A workbench for gene expression signature analysis

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    <p>Abstract</p> <p>Background</p> <p>The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise.</p> <p>Results</p> <p>We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access.</p> <p>Conclusions</p> <p>SIGNATURE is available for public use at <url>http://genepattern.genome.duke.edu/signature/</url>.</p

    Immunohistochemical detection and regulation of α5 nicotinic acetylcholine receptor (nAChR) subunits by FoxA2 during mouse lung organogenesis

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    <p>Abstract</p> <p>Background</p> <p>α<sub>5 </sub>nicotinic acetylcholine receptor (nAChR) subunits structurally stabilize functional nAChRs in many non-neuronal tissue types. The expression of α<sub>5 </sub>nAChR subunits and cell-specific markers were assessed during lung morphogenesis by co-localizing immunohistochemistry from embryonic day (E) 13.5 to post natal day (PN) 20. Transcriptional control of α<sub>5 </sub>nAChR expression by FoxA2 and GATA-6 was determined by reporter gene assays.</p> <p>Results</p> <p>Steady expression of α<sub>5 </sub>nAChR subunits was observed in distal lung epithelial cells during development while proximal lung expression significantly alternates between abundant prenatal expression, absence at PN4 and PN10, and a return to intense expression at PN20. α<sub>5 </sub>expression was most abundant on luminal edges of alveolar type (AT) I and ATII cells, non-ciliated Clara cells, and ciliated cells in the proximal lung at various periods of lung formation. Expression of α<sub>5 </sub>nAChR subunits correlated with cell differentiation and reporter gene assays suggest expression of α<sub>5 </sub>is regulated in part by FoxA2, with possible cooperation by GATA-6.</p> <p>Conclusions</p> <p>Our data reveal a highly regulated temporal-spatial pattern of α<sub>5 </sub>nAChR subunit expression during important periods of lung morphogenesis. Due to specific regulation by FoxA2 and distinct identification of α<sub>5 </sub>in alveolar epithelium and Clara cells, future studies may identify possible mechanisms of cell differentiation and lung homeostasis mediated at least in part by α<sub>5</sub>-containing nAChRs.</p

    The FEBEX benchmark test: case definition and comparison of modelling approaches

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    The FEBEX (Full-scale Engineered Barriers Experiment in Crystalline Host Rock) ‘‘in situ’’ test was installed at the Grimsel Test Site underground laboratory (Switzerland) and is a near-to-real scale simulation of the Spanish reference concept of deep geological storage in crystalline host rock. A modelling exercise, aimed at predicting field behaviour, was divided in three parts. In Part A, predictions for both the total water inflow to the tunnel as well as the water pressure changes induced by the boring of the tunnel were required. In Part B, predictions for local field variables, such as temperature, relative humidity, stresses and displacements at selected points in the bentonite barrier, and global variables, such as the total input power to the heaters were required. In Part C, predictions for temperature, stresses, water pressures and displacements in selected points of the host rock were required. Ten Modelling Teams from Europe, North America and Japan were involved in the analysis of the test. Differences among approaches may be found in the constitutive models used, in the simplifications made to the balance equations and in the geometric symmetries considered. Several aspects are addressed in the paper: the basic THM physical phenomena which dominate the test response are discussed, a comparison of different modelling results with actual measurements is presented and a discussion is given to explain the performance of the various predictions.Peer Reviewe
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