32 research outputs found

    Subgraph spotting in graph representations of comic book images

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record Graph-based representations are the most powerful data structures for extracting, representing and preserving the structural information of underlying data. Subgraph spotting is an interesting research problem, especially for studying and investigating the structural information based content-based image retrieval (CBIR) and query by example (QBE) in image databases. In this paper we address the problem of lack of freely available ground-truthed datasets for subgraph spotting and present a new dataset for subgraph spotting in graph representations of comic book images (SSGCI) with its ground-truth and evaluation protocol. Experimental results of two state-of-the-art methods of subgraph spotting are presented on the new SSGCI dataset.University of La Rochelle (France

    Surface Plasmon Resonance Sensing Detection of Mercury and Lead Ions Based on Conducting Polymer Composite

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    A new sensing area for a sensor based on surface plasmon resonance (SPR) was fabricated to detect trace amounts of mercury and lead ions. The gold surface used for SPR measurements were modified with polypyrrole-chitosan (PPy-CHI) conducting polymer composite. The polymer layer was deposited on the gold surface by electrodeposition. This optical sensor was used for monitoring toxic metal ions with and without sensitivity enhancement by chitosan in water samples. The higher amounts of resonance angle unit (ΔRU) were obtained for PPy-CHI film due to a specific binding of chitosan with Pb2+ and Hg2+ ions. The Pb2+ ion bind to the polymer films most strongly, and the sensor was more sensitive to Pb2+ compared to Hg2+. The concentrations of ions in the parts per million range produced the changes in the SPR angle minimum in the region of 0.03 to 0.07. Data analysis was done by Matlab software using Fresnel formula for multilayer system

    Gene Expression Signature of DMBA-Induced Hamster Buccal Pouch Carcinomas: Modulation by Chlorophyllin and Ellagic Acid

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    Chlorophyllin (CHL), a water-soluble, semi-synthetic derivative of chlorophyll and ellagic acid (EA), a naturally occurring polyphenolic compound in berries, grapes, and nuts have been reported to exert anticancer effects in various human cancer cell lines and in animal tumour models. The present study was undertaken to examine the mechanism underlying chemoprevention and changes in gene expression pattern induced by dietary supplementation of chlorophyllin and ellagic acid in the 7,12-dimethylbenz[a]anthracene (DMBA)-induced hamster buccal pouch (HBP) carcinogenesis model by whole genome profiling using pangenomic microarrays. In hamsters painted with DMBA, the expression of 1,700 genes was found to be altered significantly relative to control. Dietary supplementation of chlorophyllin and ellagic acid modulated the expression profiles of 104 and 37 genes respectively. Microarray analysis also revealed changes in the expression of TGFβ receptors, NF-κB, cyclin D1, and matrix metalloproteinases (MMPs) that may play a crucial role in the transformation of the normal buccal pouch to a malignant phenotype. This gene expression signature was altered on treatment with chlorophyllin and ellagic acid. Our study has also revealed patterns of gene expression signature specific for chlorophyllin and ellagic acid exposure. Thus dietary chlorophyllin and ellagic acid that can reverse gene expression signature associated with carcinogenesis are novel candidates for cancer prevention and therapy
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