1,720,958 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
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
Quantifying Data Quality and Its Impact on Functional Brain Imaging Experiments
Get PDFFunctional Magnetic Resonance Imaging (fMRI) is a widely-used tool in neuroscience research. While there is general agreement on what imaging sequences and methods work best overall, there is much less agreement and consistency on how particular parameter choices are made. These parameter choices can have an effect on data quality, which can negatively affect analysis of this data. It is therefore important to characterise this effect. The thesis investigates the impact of image acceleration techniques on fMRI data quality, quantified using temporal Signal-to-Noise Ratio (tSNR), and explores how these effects vary across different brain regions. The thesis then investigates the impact of higher levels of Gaussian noise and head motion on an important and widely adopted analysis method: population Receptive Field (pRF) analysis. Assessment of the effects of applying image denoising to fMRI data are also investigated throughout.
Chapter 3 presents development and use of the fMRI ROI Analysis Tool (fRAT), software designed to provide a comprehensive Region-of-Interest (ROI) analysis toolset for fMRI data. fRAT addresses the lack of existing fMRI tools making it easy to analyse multiple ROIs with data quality metrics. This tool enables researchers to easily study spatial variations in the relationship between scanning parameters and data quality. The software's features, including statistical analysis and data visualisation capabilities are detailed, and current and potential future applications are highlighted.
Chapter 4 uses fRAT to characterise the effect of hardware (3T Philips Achieva and 3T Philips Ingenia), image acceleration (in-plane SENSE factor and through-plane Multiband factor) and a post-hoc denoising technique (using NOise reduction with DIstribution Corrected [NORDIC] PCA) on data quality across a selection of regions of interest: the Frontal Pole, the posterior Inferior Temporal Gyrus and the Occipital Pole. The relationship between these variables was found to vary between these regions, supporting the idea that region-wise data quality (tSNR) reporting provides important information.
Chapter 5 evaluates the robustness of pRF analysis in the visual domain to decreased levels of tSNR and increased levels of participant motion through adding simulated thermal noise and head motion to a pre-existing pRF dataset collected in stroke patients [@behLinkingMultiModalMRI2021]. Work in this chapter also makes use of fRAT to first quantify noise levels and then provide a convenient way to manipulate the data before pRF analysis. It is shown that in general, pRF analysis is more robust to the addition of head motion than to noise, with the polar angle of the pRF estimates being the property most consistently affected by these factors.
Overall, this thesis provides a detailed analysis of the spatially dependent effects of image acceleration on fMRI data quality and underscores the practical consequences of changes in the level of data quality and motion in pRF analysis. The findings aim to inform best practices when conducting fMRI research, and importantly, the software developed within this thesis has been made open-source with usage tutorials to enable it to be used across a wide range of applications in future research
Quantifying Data Quality and Its Impact on Functional Brain Imaging Experiments
Get PDFFunctional Magnetic Resonance Imaging (fMRI) is a widely-used tool in neuroscience research. While there is general agreement on what imaging sequences and methods work best overall, there is much less agreement and consistency on how particular parameter choices are made. These parameter choices can have an effect on data quality, which can negatively affect analysis of this data. It is therefore important to characterise this effect. The thesis investigates the impact of image acceleration techniques on fMRI data quality, quantified using temporal Signal-to-Noise Ratio (tSNR), and explores how these effects vary across different brain regions. The thesis then investigates the impact of higher levels of Gaussian noise and head motion on an important and widely adopted analysis method: population Receptive Field (pRF) analysis. Assessment of the effects of applying image denoising to fMRI data are also investigated throughout.
Chapter 3 presents development and use of the fMRI ROI Analysis Tool (fRAT), software designed to provide a comprehensive Region-of-Interest (ROI) analysis toolset for fMRI data. fRAT addresses the lack of existing fMRI tools making it easy to analyse multiple ROIs with data quality metrics. This tool enables researchers to easily study spatial variations in the relationship between scanning parameters and data quality. The software's features, including statistical analysis and data visualisation capabilities are detailed, and current and potential future applications are highlighted.
Chapter 4 uses fRAT to characterise the effect of hardware (3T Philips Achieva and 3T Philips Ingenia), image acceleration (in-plane SENSE factor and through-plane Multiband factor) and a post-hoc denoising technique (using NOise reduction with DIstribution Corrected [NORDIC] PCA) on data quality across a selection of regions of interest: the Frontal Pole, the posterior Inferior Temporal Gyrus and the Occipital Pole. The relationship between these variables was found to vary between these regions, supporting the idea that region-wise data quality (tSNR) reporting provides important information.
Chapter 5 evaluates the robustness of pRF analysis in the visual domain to decreased levels of tSNR and increased levels of participant motion through adding simulated thermal noise and head motion to a pre-existing pRF dataset collected in stroke patients [@behLinkingMultiModalMRI2021]. Work in this chapter also makes use of fRAT to first quantify noise levels and then provide a convenient way to manipulate the data before pRF analysis. It is shown that in general, pRF analysis is more robust to the addition of head motion than to noise, with the polar angle of the pRF estimates being the property most consistently affected by these factors.
Overall, this thesis provides a detailed analysis of the spatially dependent effects of image acceleration on fMRI data quality and underscores the practical consequences of changes in the level of data quality and motion in pRF analysis. The findings aim to inform best practices when conducting fMRI research, and importantly, the software developed within this thesis has been made open-source with usage tutorials to enable it to be used across a wide range of applications in future research
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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