87 research outputs found

    Online Forum Thread Retrieval using Pseudo Cluster Selection and Voting Techniques

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    Online forums facilitate knowledge seeking and sharing on the Web. However, the shared knowledge is not fully utilized due to information overload. Thread retrieval is one method to overcome information overload. In this paper, we propose a model that combines two existing approaches: the Pseudo Cluster Selection and the Voting Techniques. In both, a retrieval system first scores a list of messages and then ranks threads by aggregating their scored messages. They differ on what and how to aggregate. The pseudo cluster selection focuses on input, while voting techniques focus on the aggregation method. Our combined models focus on the input and the aggregation methods. The result shows that some combined models are statistically superior to baseline methods.Comment: The original publication is available at http://www.springerlink.com/. arXiv admin note: substantial text overlap with arXiv:1212.533

    Sliding and Rocking of Unanchored Components and Structures: Chapter 7.6 ASCE 4 Revision 2

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    GeoTextMESS: result fusion with fuzzy Borda ranking in geographical information retrieval

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    In this paper we discuss the integration of different GIR systems by means of a fuzzy Borda method for result fusion. Two of the systems, the one by the Universidad Politécnica de Valencia and the one of the Universidad of Jaén participated to the GeoCLEF task under the name TextMess. The proposed result fusion method takes as input the document lists returned by the different systems and returns a document list where the documents are ranked according to the fuzzy Borda voting scheme. The obtained results show that the fusion method allows to improve the results of the component systems, although the fusion is not optimal, because it is effective only if the components return a similar set of relevant documents.Peer ReviewedPostprint (author’s final draft

    Synthesis and bio-molecular study of (+)-N-Acetyl-α-amino acid dehydroabietylamine derivative for the selective therapy of hepatocellular carcinoma

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    Background: The purpose of present work is to synthesize novel (+)-Dehydroabietylamine derivatives (DAAD) using N-acetyl-α-amino acid conjugates and determine its cytotoxic effects on hepatocellular carcinoma cells. Methods: An analytical study was conducted to explore cytotoxic activity of DAAD on hepatocellular carcinoma cell lines. The cytotoxicity effect was recorded using sulforhodamine B technique. Cell cycle analysis was performed using Propidium Iodide (PI) staining. Based on cell morphology, anti growth activity and microarray findings of DAAD2 treatment, Comet assay, Annexin V/PI staining, Immunoperoxidase assay and western blots were performed accoringly. Results: Hep3B cells were found to be the most sensitive with IC50 of 2.00 ± 0.4 μM against (+)-N-(N-Acetyl-L-Cysteine)-dehydroabietylamine as DAAD2. In compliance to time dependent morphological changes of low cellular confluence, detachment and rounding of DAAD2 treated cells; noticeable changes in G2/M phase were recorded may be leading to cell cycle cessation. Up-regulation (5folds) of TUBA1A gene in Hep3B cells was determined in microarray experiments. Apoptotic mode of cell death was evaluated using standardized staining procedures including comet assay and annexin V/PI staining, Immuno-peroxidase assay. Using western blotting technique, caspase dependant apoptotic mode of cell death was recorded against Hep3B cell line. Conclusion: It is concluded that a novel DAAD2 with IC50 values less than 8 μM can induce massive cell attenuation following caspase dependent apoptotic cell death in Hep3B cells. Moreover, the corelation study indicated that DAAD2 may have vital influence on cell prolifration properties. © 2016 The Author(s)

    Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error.

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    Corneal curvature, a highly heritable trait, is a key clinical endophenotype for myopia - a major cause of visual impairment and blindness in the world. Here we present a trans-ethnic meta-analysis of corneal curvature GWAS in 44,042 individuals of Caucasian and Asian with replication in 88,218 UK Biobank data. We identified 47 loci (of which 26 are novel), with population-specific signals as well as shared signals across ethnicities. Some identified variants showed precise scaling in corneal curvature and eye elongation (i.e. axial length) to maintain eyes in emmetropia (i.e. HDAC11/FBLN2 rs2630445, RBP3 rs11204213); others exhibited association with myopia with little pleiotropic effects on eye elongation. Implicated genes are involved in extracellular matrix organization, developmental process for body and eye, connective tissue cartilage and glycosylation protein activities. Our study provides insights into population-specific novel genes for corneal curvature, and their pleiotropic effect in regulating eye size or conferring susceptibility to myopia

    High Resolution Sharp Computational Methods for Elliptic and Parabolic Problems in Complex Geometries

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    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    A case for automatic system evaluation

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    Ranking a set retrieval systems according to their retrieval effectiveness without relying on relevance judgments was first explored by Soboroff et al. [13]. Over the years, a number of alternative approaches have been proposed, all of which have been evaluated on early TREC test collections. In this work, we perform a wider analysis of system ranking estimation methods on sixteen TREC data sets which cover more tasks and corpora than previously. Our analysis reveals that the performance of system ranking estimation approaches varies across topics. This observation motivates the hypothesis that the performance of such methods can be improved by selecting the “right” subset of topics from a topic set. We show that using topic subsets improves the performance of automatic system ranking methods by 26% on average, with a maximum of 60%. We also observe that the commonly experienced problem of underestimating the performance of the best systems is data set dependent and not inherent to system ranking estimation. These findings support the case for automatic system evaluation and motivate further rese

    Predicting Query Performance via Classification

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    Abstract. We investigate using topic prediction data, as a summary of document content, to compute measures of search result quality. Unlike existing quality measures such as query clarity that require the entire content of the top-ranked results, class-based statistics can be computed efficiently online, because class information is compact enough to precompute and store in the index. In an empirical study we compare the performance of class-based statistics to their language-model counterparts for two performance-related tasks: predicting query difficulty and expansion risk. Our findings suggest that using class predictions can offer comparable performance to full language models while reducing computation overhead.
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