Indexing of mid-resolution satellite images with structural attributes.

Satellite image classification has been a major research field for many years with its varied applications in the field of Geography, Geology, Archaeology, Environmental Sciences and Military purposes. Many different techniques have been proposed to classify satellite images with color, shape and texture features. Complex indices like Vegetation index (NDVI), Brightness index (BI) or Urban index (ISU) are used for multi-spectral or hyper-spectral satellite images. In this paper we will show the efficiency of structural features describing man-made objects in mid-resolution satellite images to describe image content. We will then show the state-of-the-art to classify large satellite images with structural features computed from road networks and urban regions extracted on small image patches cut in the large image. Fisher Linear Discriminant (FLD) analysis is used for feature selection and a one-vsrest probabilistic Gaussian kernel Support Vector Machines (SVM) classification method is used to classify the images. The classification probabilities associated with each subimage of the large image provide an estimate of the geographical class coverage

Indexing of mid-resolution satellite images with structural attributes

Satellite image classification has been a major research field for many years with its varied applications in the field of Geography, Geology, Archaeology, Environmental Sciences and Military purposes. Many different techniques have been proposed to classify satellite images with color, shape and texture features. Complex indices like Vegetation index (NDVI), Brightness index (BI) or Urban index (ISU) are used for multi-spectral or hyper-spectral satellite images. In this paper we will show the efficiency of structural features describing man-made objects in mid-resolution satellite images to describe image content. We will then show the state-of-the-art to classify large satellite images with structural features computed from road networks and urban regions extracted on small image patches cut in the large image. Fisher Linear Discriminant (FLD) analysis is used for feature selection and a one-vsrest probabilistic Gaussian kernel Support Vector Machines (SVM) classification method is used to classify the images. The classification probabilities associated with each subimage of the large image provide an estimate of the geographical class coverage

An explicit hybridizable discontinuous Galerkin method for the 3D time-domain Maxwell equations

International audienceWe present an explicit hybridizable discontinuous Galerkin (HDG) method for numerically solving the system of three-dimensional (3D) time-domain Maxwell equations. The method is fully explicit similarly to classical so-called DGTD (Dis-continuous Galerkin Time-Domain) methods, is also high-order accurate in both space and time and can be seen as a generalization of the classical DGTD scheme based on upwind fluxes. We provide numerical results aiming at assessing its numerical convergence properties by considering a model problem and we present preliminary results of the superconvergence property on the H curl norm

DNA methylation during human adipogenesis and the impact of fructose

Background: Increased adipogenesis and altered adipocyte function contribute to the development of obesity and associated comorbidities. Fructose modified adipocyte metabolism compared to glucose, but the regulatory mechanisms and consequences for obesity are unknown. Genome-wide methylation and global transcriptomics in SGBS pre-adipocytes exposed to 0, 2.5, 5, and 10 mM fructose, added to a 5-mM glucose-containing medium, were analyzed at 0, 24, 48, 96, 192, and 384 h following the induction of adipogenesis. Results: Time-dependent changes in DNA methylation compared to baseline (0 h) occurred during the final maturation of adipocytes, between 192 and 384 h. Larger percentages (0.1% at 192 h, 3.2% at 384 h) of differentially methylated regions (DMRs) were found in adipocytes differentiated in the glucose-containing control media compared to adipocytes differentiated in fructose-supplemented media (0.0006% for 10 mM, 0.001% for 5 mM, and 0.005% for 2.5 mM at 384 h). A total of 1437 DMRs were identified in 5237 differentially expressed genes at 384 h post-induction in glucose-containing (5 mM) control media. The majority of them inversely correlated with the gene expression, but 666 regions were positively correlated to the gene expression. Conclusions: Our studies demonstrate that DNA methylation regulates or marks the transformation of morphologically differentiating adipocytes (seen at 192 h), to the more mature and metabolically robust adipocytes (as seen at 384 h) in a genome-wide manner. Lower (2.5 mM) concentrations of fructose have the most robust effects on methylation compared to higher concentrations (5 and 10 mM), suggesting that fructose may be playing a signaling/regulatory role at lower concentrations of fructose and as a substrate at higher concentrations

A Q-Ising model application for linear-time image segmentation

A computational method is presented which efficiently segments digital grayscale images by directly applying the Q-state Ising (or Potts) model. Since the Potts model was first proposed in 1952, physicists have studied lattice models to gain deep insights into magnetism and other disordered systems. For some time, researchers have realized that digital images may be modeled in much the same way as these physical systems (i.e., as a square lattice of numerical values). A major drawback in using Potts model methods for image segmentation is that, with conventional methods, it processes in exponential time. Advances have been made via certain approximations to reduce the segmentation process to power-law time. However, in many applications (such as for sonar imagery), real-time processing requires much greater efficiency. This article contains a description of an energy minimization technique that applies four Potts (Q-Ising) models directly to the image and processes in linear time. The result is analogous to partitioning the system into regions of four classes of magnetism. This direct Potts segmentation technique is demonstrated on photographic, medical, and acoustic images.Comment: 7 pages, 8 figures, revtex, uses subfigure.sty. Central European Journal of Physics, in press (2010

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

Although many genetic variants are known for obesity, their function remains largely unknown. Here, in a weight-loss intervention cohort, the authors identify protein quantitative trait loci associated with BMI at baseline and after weight loss and find FAM46A to be a regulator of leptin in adipocytes

C/EBPβ-Thr217 Phosphorylation Signaling Contributes to the Development of Lung Injury and Fibrosis in Mice

mice are refractory to Bleomycin-induced lung fibrosis the molecular mechanisms remain unknown. Here we show that blocking the ribosomal S-6 kinase (RSK) phosphorylation of the CCAAT/Enhancer Binding Protein (C/EBP)-β on Thr217 (a RSK phosphoacceptor) with either a single point mutation (Ala217), dominant negative transgene or a blocking peptide containing the mutated phosphoacceptor ameliorates the progression of lung injury and fibrosis induced by Bleomycin in mice. mice with a cell permeant, C/EBPβ peptide that inhibits phosphorylation of C/EBPβ on Thr217 (40 µg instilled intracheally on day-2 and day-6 after the single Bleomycin dose) also blocked the progression of lung injury and fibrosis induced by Bleomycin. Phosphorylation of human C/EBPβ on Thr266 (human homologue phosphoacceptor) was induced in collagen-activated human lung fibroblasts in culture as well as in activated lung fibroblasts in situ in lungs of patients with severe lung fibrosis but not in control lungs, suggesting that this signaling pathway may be also relevant in human lung injury and fibrosis.These data suggest that the RSK-C/EBPβ phosphorylation pathway may contribute to the development of lung injury and fibrosis

One-carbon metabolism, cognitive impairment and CSF measures of Alzheimer pathology: homocysteine and beyond.

Hyperhomocysteinemia is a risk factor for cognitive decline and dementia, including Alzheimer disease (AD). Homocysteine (Hcy) is a sulfur-containing amino acid and metabolite of the methionine pathway. The interrelated methionine, purine, and thymidylate cycles constitute the one-carbon metabolism that plays a critical role in the synthesis of DNA, neurotransmitters, phospholipids, and myelin. In this study, we tested the hypothesis that one-carbon metabolites beyond Hcy are relevant to cognitive function and cerebrospinal fluid (CSF) measures of AD pathology in older adults. Cross-sectional analysis was performed on matched CSF and plasma collected from 120 older community-dwelling adults with (n = 72) or without (n = 48) cognitive impairment. Liquid chromatography-mass spectrometry was performed to quantify one-carbon metabolites and their cofactors. Least absolute shrinkage and selection operator (LASSO) regression was initially applied to clinical and biomarker measures that generate the highest diagnostic accuracy of a priori-defined cognitive impairment (Clinical Dementia Rating-based) and AD pathology (i.e., CSF tau phosphorylated at threonine 181 [p-tau181]/β-Amyloid 1-42 peptide chain [Aβ1-42] >0.0779) to establish a reference benchmark. Two other LASSO-determined models were generated that included the one-carbon metabolites in CSF and then plasma. Correlations of CSF and plasma one-carbon metabolites with CSF amyloid and tau were explored. LASSO-determined models were stratified by apolipoprotein E (APOE) ε4 carrier status. The diagnostic accuracy of cognitive impairment for the reference model was 80.8% and included age, years of education, Aβ1-42, tau, and p-tau181. A model including CSF cystathionine, methionine, S-adenosyl-L-homocysteine (SAH), S-adenosylmethionine (SAM), serine, cysteine, and 5-methyltetrahydrofolate (5-MTHF) improved the diagnostic accuracy to 87.4%. A second model derived from plasma included cystathionine, glycine, methionine, SAH, SAM, serine, cysteine, and Hcy and reached a diagnostic accuracy of 87.5%. CSF SAH and 5-MTHF were associated with CSF tau and p-tau181. Plasma one-carbon metabolites were able to diagnose subjects with a positive CSF profile of AD pathology in APOE ε4 carriers. We observed significant improvements in the prediction of cognitive impairment by adding one-carbon metabolites. This is partially explained by associations with CSF tau and p-tau181, suggesting a role for one-carbon metabolism in the aggregation of tau and neuronal injury. These metabolites may be particularly critical in APOE ε4 carriers