1,721,039 research outputs found
Gene expression signatures of postnatal depression
No full text<p>This dataset consists of RNA sequencing gene expression data for 137 women with postnatal depression, which are also published in 2021 in the following publication: Mehta, D., Grewen, K., Pearson, B. <em>et al.</em> Genome-wide gene expression changes in postpartum depression point towards an altered immune landscape. <em>Transl Psychiatry</em> 11, 155 (2021). </p>
<p>This dataset was collected by the University of North Carolina, USA, through a University of Queensland grant, obtained by Dr Divya Mehta while employed at UQ. </p>
Gendered Science: Trends and analysis of contributions of Indian Women Scientists
No full textAll the major world organizations have recognized the vital role that a woman plays in educating the entire family & also in maintaining its health in a developing country. Indian women have excelled in almost all fields they are storming Information and Technology field , the number of women in computing and internet industries has registered a sharp rise. While presenting the hardcore figures about the women’s enrollment in higher education system in different faculties; relative presence of women as scientific and technical staff in various institutions; recognition by various reputed national agencies; motivation and constraints to opt for science are also focused in this study. As an output Indicator, Publication analysis of Women scientist has also been presented
MR medical image enhancement: an integration of residual approximation and contrast enhancement approach
No full textMagnetic Resonance Images are mainly corrupted by Gaussian and Rician noises during their acquisition, which degrades the calibre of post-processing diagnostics applied to MR data, such as segmentation, registration, morphometry etc. A pre-processing technique such as MR image enhancement is needed for precise diagnostic results. Recently, deep learning techniques are gaining much popularity in various biomedical applications due to their accuracy when trained with a huge volume of biomedical images. This article presents a deep learning-based pre-processing mechanism which integrates the residual approximation and contrast enhancement method. The denoised image is estimated using a denoising Convolutional Neural Network (CNN) and residual approximation. The contrast of the denoised image is enhanced using histogram equalization. To analyze the quality of enhanced image, metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Mean Squared Error (MSE) are considered. The experimental results on synthetic and clinical data show that the proposed method outperforms the existing methods in terms of PSNR, SSIM and MSE. The proposed method obtained a PSNR of 40dB, SSIM of 99%, and MSE of. 0052 for Gaussian noise addition and for Rician noise addition, attained a PSNR of 38 dB SSIM of 99% and MSE of. 0084 for σ = 9 %
Hybrid optimization algorithm-based generative adversarial network for change detection using pre-operative and post-operative MRI
No full textAutomatic detection of tumors is important to speed up treatment and to increase the survival rate of patients. In brain tumor detection, Magnetic Resonance Imaging (MRI) is considered an effective imaging model, which offers the internal structure of the brain. Change detection by pre-operative as well as post-operative multimodal images is an important research area in recent decades. Thus, this paper designs a hybrid optimization algorithm-based deep learning classifier to find the percentage of change detection in multimodal images. Initially, preprocessing is progressed to eradicate the noise from MRI images and then segmentation is performed using the modified DeepJoint model. After that, the pre-operative and the post-operative MRI images are engaged for the classification of a tumor. The classification of brain tumors is performed by Deep Convolutional Neural Network (Deep CNN) trained by a Tunicate Exponential Weighted Moving Average (TEWMA) algorithm, which is the integration of Tunicate Swarm Algorithm (TSA) and Exponential Weighted Moving Average (EWMA). After classification, the volume difference and the percentage of change detection are computed by GAN trained by PS-TEWMA, which is the integration of Particle Swarm Optimization (PSO) with TSA and EWMA. The proposed PS-TEWMA-based GAN obtained lower MSE and RMSE of 0.0881 and 0.2968 by measuring the volume detection. Also, it obtained minimal MSE and RMSE of 0.102 and 0.3194 concerning the percentage of change detection.<br/
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
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