1,108 research outputs found

    Definitive chemical evidence for the constitutive ability of Candida albicans serotype A strains to synthesize β-1,2 linked oligomannosides containing up to 14 mannose residues

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    AbstractWe have previously reported the presence of phosphate bound β-1,2 linked oligomannosides with unusually high degrees of polymerization (DP>7) in the mannan of Candida albicans strain VW32. To confirm this observation, we have prepared these oligomannosides from the mannan of C. albicans strain NIH A 207. Gel filtration chromatography and TLC analysis revealed DP up to 14. For both strains, NMR analysis confirmed the exclusive presence of β-1,2 linkages in the pools of oligomannosides with a DP higher than 6 which presented an average DP of 10.6 (VW32) and 10.4 (NIH A 207). These results are important to consider in relation with the ability of these C. albicans derived oligomannosides to trigger TNFα synthesis according to their DP

    Automatic Matching and Expansion of Abbreviated Phrases without Context

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    International audienceIn many documents, like receipts or invoices, textual information is constrained by the space and organization of the document. The document information has no natural language context, and expressions are often abbreviated to respect the graphical layout, both at word level and phrase level. In order to analyze the semantic content of these types of document, we need to understand each phrase, and particularly each name of sold products. In this paper, we propose an approach to find the right expansion of abbreviations and acronyms, without context. First, we extract information about sold products from our receipts corpus and we analyze the different linguistic processes of abbreviation. Then, we retrieve a list of expanded names of products sold by the company that emitted receipts, and we propose an algorithm to pair extracted names of products with the corresponding expansions. We provide the research community with a unique document collection for abbreviation expansion

    Find it! Fraud Detection Contest Report

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    International audienceThis paper describes the ICPR2018 fraud detection contest, its data set, evaluation methodology, as well as the different methods submitted by the participants to tackle the predefined tasks. Forensics research is quite a sensitive topic. Data are either private or unlabeled and most of related works are evaluated on private datasets with a restricted access. This restriction has two major consequences: results cannot be reproduced and no benchmarking can be done between every approach. This contest was conceived in order to address these drawbacks. Two tasks were proposed: detecting documents containing at least one forgery in a flow of documents and spotting and localizing these forgeries within documents. An original dataset composed of images and texts of French receipts was provided to participants. The results they obtained are presented and discussed

    Colloidal stability of tannins: astringency, wine tasting and beyond

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    Tannin-tannin and tannin-protein interactions in water-ethanol solvent mixtures are studied in the context of red wine tasting. While tannin self-aggregation is relevant for visual aspect of wine tasting (limpidity and related colloidal phenomena), tannin affinities for salivary proline-rich proteins is fundamental for a wide spectrum of organoleptic properties related to astringency. Tannin-tannin interactions are analyzed in water-ethanol wine-like solvents and the precipitation map is constructed for a typical grape tannin. The interaction between tannins and human salivary proline-rich proteins (PRP) are investigated in the framework of the shell model for micellization, known for describing tannin-induced aggregation of beta-casein. Tannin-assisted micellization and compaction of proteins observed by SAXS are described quantitatively and discussed in the case of astringency

    Long-term chemical characterization of tropical and marine aerosols at the Cape Verde Atmospheric Observatory (CVAO) from 2007 to 2011

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    The first long-term aerosol sampling and chemical characterization results from measurements at the Cape Verde Atmospheric Observatory (CVAO) on the island of São Vicente are presented and are discussed with respect to air mass origin and seasonal trends. In total 671 samples were collected using a high-volume PM10 sampler on quartz fiber filters from January 2007 to December 2011. The samples were analyzed for their aerosol chemical composition, including their ionic and organic constituents. Back trajectory analyses showed that the aerosol at CVAO was strongly influenced by emissions from Europe and Africa, with the latter often responsible for high mineral dust loading. Sea salt and mineral dust dominated the aerosol mass and made up in total about 80% of the aerosol mass. The 5-year PM10 mean was 47.1 ± 55.5 μg m−2, while the mineral dust and sea salt means were 27.9 ± 48.7 and 11.1 ± 5.5 μg m−2, respectively. Non-sea-salt (nss) sulfate made up 62% of the total sulfate and originated from both long-range transport from Africa or Europe and marine sources. Strong seasonal variation was observed for the aerosol components. While nitrate showed no clear seasonal variation with an annual mean of 1.1 ± 0.6 μg m−3, the aerosol mass, OC (organic carbon) and EC (elemental carbon), showed strong winter maxima due to strong influence of African air mass inflow. Additionally during summer, elevated concentrations of OM were observed originating from marine emissions. A summer maximum was observed for non-sea-salt sulfate and was connected to periods when air mass inflow was predominantly of marine origin, indicating that marine biogenic emissions were a significant source. Ammonium showed a distinct maximum in spring and coincided with ocean surface water chlorophyll a concentrations. Good correlations were also observed between nss-sulfate and oxalate during the summer and winter seasons, indicating a likely photochemical in-cloud processing of the marine and anthropogenic precursors of these species. High temporal variability was observed in both chloride and bromide depletion, differing significantly within the seasons, air mass history and Saharan dust concentration. Chloride (bromide) depletion varied from 8.8 ± 8.5% (62 ± 42%) in Saharan-dust-dominated air mass to 30 \textpm 12% (87 ± 11%) in polluted Europe air masses. During summer, bromide depletion often reached 100% in marine as well as in polluted continental samples. In addition to the influence of the aerosol acidic components, photochemistry was one of the main drivers of halogenide depletion during the summer; while during dust events, displacement reaction with nitric acid was found to be the dominant mechanism. Positive matrix factorization (PMF) analysis identified three major aerosol sources: sea salt, aged sea salt and long-range transport. The ionic budget was dominated by the first two of these factors, while the long-range transport factor could only account for about 14% of the total observed ionic mass

    Variational assimilation of Lagrangian trajectories in the Mediterranean ocean Forecasting System

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    Abstract. A novel method for three-dimensional variational assimilation of Lagrangian data with a primitive-equation ocean model is proposed. The assimilation scheme was implemented in the Mediterranean ocean Forecasting System and evaluated for a 4-month period. Four experiments were designed to assess the impact of trajectory assimilation on the model output, i.e. the sea-surface height, velocity, temperature and salinity fields. It was found from the drifter and Argo trajectory assimilation experiment that the forecast skill of surface-drifter trajectories improved by 15 %, that of intermediate-depth float trajectories by 20 %, and moreover, that the forecasted sea-surface height fields improved locally by 5 % compared to satellite data, while the quality of the temperature and salinity fields remained at previous levels. In conclusion, the addition of Lagrangian trajectory assimilation proved to reduce the uncertainties in the model fields, thus yielding a higher accuracy of the ocean forecasts

    CHIC: Corporate Document for Visual question Answering

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    The massive use of digital documents due to the substantial trend of paperless initiatives confronted some companies to find ways to process thousands of documents per day automatically. To achieve this, they use automatic information retrieval (IR) allowing them to extract useful information from large datasets quickly. In order to have effective IR methods, it is first necessary to have an adequate dataset. Although companies have enough data to take into account their needs, there is also a need for a public database to compare contributions between state-of-the-art methods. Public data on the document exists as DocVQA[2] and XFUND [10], but these do not fully satisfy the needs of companies. XFUND contains only form documents while the company uses several types of documents (i.e. structured documents like forms but also semi-structured as invoices, and unstructured as emails). Compared to XFUND, DocVQA has several types of documents but only 4.5% of them are corporate documents (i.e. invoice, purchase order, etc). All of this 4.5% of documents do not meet the diversity of documents required by the company. We propose CHIC a visual question-answering public dataset. This dataset contains different types of corporate documents and the information extracted from these documents meet the right expectations of companies
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