1,720,960 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe 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
Get PDFWe 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
Studies on Molecular Targets and Pathways Regulated by Rice RFL for Flowering Transition and Panicle Development
Get PDFLFY of Arabidopsis is a member of a unique plant specific transcription factor family. It is involved in giving meristem a determinate floral fate by the activation of floral organ identity genes and preventing inflorescence meristem identity. RFL is a homolog of FLO/LFY in rice. Studies from our lab on rice RFL, based on the effects of knockdown or overexpression, showed its major functions are in timing the conversion of SAM to IM and to prevent the premature conversion of branch meristem to spikelets. Additionally roles in vegetative axillary meristem specification have been also been identified in laboratory. Here, we attempt to delineate molecular pathways directly regulated by RFL as a transcription factor controlling inflorescence and floral development in rice.
Part I: Identification of global target genes bound by RFL in developing rice inflorescences
We carried out ChIP sequencing of the DNA bound by RFL in panicles (01.-0.3cm stage) using anti-RFL antibody. DNA sequences in one library pool were analyses by the MACS algorithm (FDR<0.01), to find 8000 binding sites while the SPP algorithm identified 5000 enriched peaks. These mapped to 2500 or 2800 gene-associated loci respectively, 617 of which were common loci to both pipelines. Several RFL bound gene loci were homologs of Arabidopsis thaliana LFY gene targets. Such gene targets underscore conserved downstream targets for LFY-proteins in evolutionarily very distinct species. AtLFY is known to bind variants of CCANT/G cis element classified as primary, inflorescence or seedling type. We scanned for these three types of cis elements at 123 RFL bound genes with likely functions in flowering. For a few of these 123 rice loci we find one of these cis motifs (p-value<0.001) in RFL bound ChIP-seq data. To validate these targets of RFL, we adopted in vitro DNA-protein binding assays with bacterially purified RFL protein. We confirm RFL target interactions with some genes implicated in flowering time, others in photoperiod triggered flowering, circadian rhythm, gibberellin hormone pathway, inflorescence development and branching. The in vitro experiments hint different RFL-DNA binding properties as compared to Arabidopsis LFY. We report binding to sequences at rice gene loci that are unique targets.
Part II: Pathways regulated by RFL for reproductive transition and panicle development
To co-relate DNA binding of RFL to target loci with changes in their gene expression, expression studies were taken up for selected set of genes implicated in rice flowering transition and panicle architecture. To study in planta and tissue specific gene regulation by RFL we raised RFL dsRNAi transgenics. Comparative transcript analysis in these RFL partial knockdown lines and matched wild type tissues reveal that RFL is an activator for some genes and repressor for other gene targets. We also examined if the gene expression effects of RFL knockdown can be reversed by induced complementation with an RFL-GR protein. We raised transgenics plants with a T-DNA ubi:RFL-GR, 35S CaMV:amiR RFL for these experiments. In planta target gene transcript levels were assessed in various conditions conditions. These studies validate rice RFL as an activator of some panicle architecture genes.
Part III: Analysis of endogenous RFL protein in WT rice tissues
Studies in Arabidopsis and in petunia with LFY and AFL, respectively, implicate these some abnormal mobility as compared to their predicted molecular weight when overexpressed. We studied endogenous RFL protein abundance in planta, adopting western analysis with anti-RFL antibody. We consistently identify two prominent cross reacting bands in different tissues which can be also be pulled-down from whole nuclear extracts of panicle and axillary meristem tissues. We speculate on likely modifications and possible functions for the same
Describe The Process Of Improving Software Fault Prediction Through The Use Of Hybrid Machine Learning Algorithms
Get PDFIn contemporary software development, it is imperative to guarantee the dependability and quality of software. The identification of potential defects in software systems prior to deployment is a critical function of Software Fault Prediction (SFP), which in turn reduces maintenance costs, improves reliability, and improves the overall quality of software. Although conventional defect prediction models are somewhat effective, they frequently encounter issues such as data imbalance, poor generalization, and the inability to manage high-dimensional software metrics. This research suggests a hybrid machine learning framework that incorporates feature selection techniques, deep learning, and ensemble learning to improve the prediction of software faults in order to overcome these challenges. The hybrid model that has been proposed combines Deep Neural Networks (DNN) and Gradient Boosting Decision Trees (GBDT) to capitalize on their respective strengths in the learning of complex data patterns and the generation of reliable predictions. In order to enhance the efficacy of the model by reducing dimensionality and eliminating redundant features, feature selection methods such as Recursive Feature Elimination (RFE) and Mutual Information (MI) are implemented. The model is trained and evaluated using publicly available NASA MDP and PROMISE repository datasets, which include core software metrics such as lines of code (LOC), cyclomatic complexity, coupling, and cohesiveness. The hybrid model outperforms conventional machine learning classifiers, such as Support Vector Machines (SVM), Random Forest, and Gradient Boosting, across a variety of performance metrics, as evidenced by experimental results. The hybrid model considerably improves the reliability of software fault detection by achieving a 92% accuracy, 91% generalization score, and a low false positive rate of 7%. Additionally, it maintains a high F1-score (90.5%) and AUC-ROC (93%), which guarantees enhanced precision and recall in the identification of failed software components. The hybrid machine learning framework that has been proposed improves scalability, reduces misclassification errors, and enhances defect prediction accuracy by incorporating adaptive learning, feature selection, and ensemble techniques. The results of this study indicate that hybrid models are a valuable instrument for software quality assurance and defect management in real-world applications, as they can effectively address critical challenges in software fault prediction
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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