186,440 research outputs found

    The Senet Group’s responsible gambling campaign tagline.

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    In the original campaign imagery (a) the font size for the word “FUN” was larger and the second “STOP” was smaller than the version currently in use. On the 1st of June 2015, the Senet Group announced that “Senet has slightly altered the relative size of the words ‘Fun’ and ‘Stop’ in its yellow advertising strip, ‘When the Fun Stops, Stop’, to bring the two symbols into better balance” (b) (Source: Senet Group press release titled Senet Group runs new burst of #BadBetty advertising and strengthens regulation) [73].</p

    A. Senet, Histoire de la médecine vétérinaire

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    Théodoridès Jean. A. Senet, Histoire de la médecine vétérinaire. In: Revue d'histoire des sciences et de leurs applications, tome 7, n°2, 1954. p. 195

    MgO/Ag(100): confined vibrational modes in the limit of ultrathin films

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    The vibrational modes of clean MgO films are investigated vs film thickness by means of high-resolution electron energy-loss spectroscopy. For thin films (20-30 monolayers) we observe, in accord with the literature, the Fuchs-Khewer phonon at 677 cm(-1) and the Wallis mode at 524 cm(-1). For ultrathin films standing wave optical phonons confined in the overlayer are present, whose frequencies depend strongly on film thickness. Comparison with theoretical calculations for MgO slabs on a perfect conductor shows that the experimental frequencies are lower than expected, indicating the presence of compressive stress. At and below one-monolayer thickness an intense loss peak at 427 cm(-1) is observed

    An investigation of shortest paths algorithms

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    In this work, we classify the shortest path problems, review all source algorithms and analyse the different implementations of single source algorithms using various list structures and labelling techniques. Furthermore, we study the Sensitivity Analysis of one-to-all problems and present an algorithm, Senet, for their Post Optimality Analysis. Senet determines all the critical values for the weight of an arc (which could be optimal, non-optimal or non-existant) at which the optimal solution changes. Senet also provides the updated optimal solution for every range formed by two successive critical values

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Withdrawn by Author

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    &lt;p&gt;Withdrawn by Author&nbsp;&lt;/p&gt
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