1,720,982 research outputs found

    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

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    RNA-Seq analysis of bovine oocyte transcriptome reveals that differences between heifers and repeat breeders are limited to a few key transcripts

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    Maternal transcripts are accumulated during oocyte growth and drive early embryonic development; therefore, their characterisation is a relevant factor for predicting fertility. DNA microarrays have been the method of choice for transcriptional profiling, but this method has some limitations when applied to domestic species because it relies upon existing knowledge about genome sequence and offers a limited quantitative evaluation. These limits are overcome by next-generation sequencing technology. The aim of the work was to define a reference standard for bovine fertility determining the list and the level of transcripts stored in fully grown oocytes collected from heifers (H) and to compare this pattern with that of adult repeat breeders (RB). Oocytes were collected by ovum pick-up (OPU) from 5 Italian Dappled Red heifers of 11 to 15 months of age that became pregnant at the following oestrus and from 4 adult cows of the same breed with an age of 4 to 7 years, classified as repeat breeders after they failed to become pregnant for a minimum of 3 consecutive AI. In both groups, oocytes were aspirated from follicles of 4 to 6mm in diameter. Each oocyte was carefully denuded and immediately snap frozen in liquid nitrogen. Oocytes from each animal were pooled together (range 4 to 11) and analysed as a single sample. Total RNA extraction was performed by RNeasy Micro Kit (Qiagen, Valencia, CA, USA). Amplified cDNA, from both mRNA and non-polyadenylated transcripts, was prepared starting from total RNA using the Ovation RNA-Seq System V2 (NuGEN Inc., San Carlos, CA, USA). Purified cDNA was ligated directly into an Illumina sequencing library using TruSeq DNA Sample Prep kit (Illumina Inc., San Diego, CA, USA). Sequencing was performed on Illumina HiSEqn 2000 in the 50-bp long single-read set-up, at a 4-plex of multiplexing level, producing 30 to 40 million reads per sample. Data were annotated using the cDNA ENSEMBL UMD 3.1.67 database. On average, the number of transcripts present in each sample was 15438±766 in H and 15624±768 in RB oocytes. Nineteen thousand one hundred sixty-one transcripts were detected at least in one sample, and 12174 were detected in all samples. The comparison between H and RB showed that 598 transcripts out of 19161 (3.12%) and 437 out of 12174 (3.59%) are expressed at a significantly different level (P<0.05) in the 2 groups. Taking into consideration only the transcripts detected in all the samples, with an expression rate of at least 10-fold different and a P<0.05 we identified 39 genes. Seventeen transcripts were more abundant in RB oocytes, whereas 22 were downregulated. This is the first analysis of the oocyte transcriptome performed with deep sequencing technology. The method enabled us to compile a full list of transcripts that are found in highly competent oocytes. A direct comparison with low-quality oocytes indicated that quantitative differences of transcripts level are limited to a small subpopulation of key transcripts

    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

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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