186,223 research outputs found
Gene expression reliability estimation through cluster-based analysis
No full textGene expression is the fundamental control of the structure and functions of the cellular versatility and adaptability of any organisms. The measurement of gene expressions is performed on images generated by optical inspection of microarray devices which allow the simultaneous analysis of thousands of genes. The images produced by these devices are used to calculate the expression levels of mRNA in order to draw diagnostic information related to human disease. The quality measures are mandatory in genes classification and in the decision-making diagnostic. However, microarrays are characterized by imperfections due to sample contaminations, scratches, precipitation or imperfect gridding and spot detection. The automatic and efficient quality measurement of microarray is needed in order to discriminate faulty gene expression levels. In this paper we present a new method for estimate the quality degree and the data's reliability of a microarray analysis. The efficiency of the proposed approach in terms of genes expression classification has been demonstrated through a clustering supervised analysis performed on a set of three different histological samples related to the Lymphoma's cancer diseas
Reliability Evaluation of Embedded GPGPUs for Safety Critical Applications
No full textThanks to the capability of efficiently executing massive computations in parallel, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for several parallel applications in different domains. Two are the most relevant fields in which, recently, GPGPUs have begun to be employed: High Performance Computing (HPC), and embedded systems. The reliability requirements are different in these two applications domain. In order to be employed in safety-critical applications, GPGPUs for embedded systems must be qualified as reliable. In this paper, we analyze through neutron irradiation typical parallel algorithms for embedded GPGPUs and we evaluate their reliability. We analyze how caches and threads distributions affect the GPGPU reliability. The data have been acquired through neutron test experiments, performed at the VESUVIO neutron facility at ISIS. The obtained experimental results show that, if the L1 cache of the considered GPGPU is disabled, the algorithm execution is most reliable. Moreover, it is demonstrated that during a FFT execution most errors appear in the stages in which the GPGPU is completely loaded as the number of instantiated parallel tasks is higher
Differential gene expression graphs: A data structure for classification in DNA microarrays
No full textThis paper proposes an innovative data structure to be used as a backbone in designing microarray phenotype sample classifiers. The data structure is based on graphs and it is built from a differential analysis of the expression levels of healthy and diseased tissue samples in a microarray dataset. The proposed data structure is built in such a way that, by construction, it shows a number of properties that are perfectly suited to address several problems like feature extraction, clustering, and classificatio
Facial expressivity during the clinical interview as a predictor functional disability in schizophrenia. a pilot study
No full textDespite the central role of nonverbal behavior in regulating social interactions, its relationship to functional disability in schizophrenia has received little empirical attention. This study aimed at assessing the relationship of patients' spontaneous facial expressivity during the clinical interview to clinician-rated and self-reported measures of functional disability. The nonverbal behavior of 28 stabilized patients with schizophrenia was analyzed by using the Ethological Coding System for Interviews (ECSI). Functional disability was assessed using the Global Assessment of Functioning (GAF) scale and the Sheehan Disability Scale (DISS). Partial correlation analysis controlling for the confounding effects of neuroleptic treatment showed that facial expressivity was correlated with the GAF score (r=0.42, P=0.03) and the scores on the subscales of the DISS measuring work (r=-0.52, P=0.005) and social (r=-0.50, P=0.007) disability. In a multiple regression model, nonverbal behavior explained variation in patients' work and social disability better than negative symptoms. The results of this pilot study suggest that deficits in encoding affiliative signals may play a role in determining or aggravating functional disability in schizophrenia. One clinical implication of this finding is that remediation training programs designed to improve nonverbal communication could also serve as a useful adjunct for improving work and social functioning in patients with schizophrenia
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
On the evaluation of soft-errors detection techniques for GPGPUs
No full textRecently, General Purpose Graphic Processing Units (GPGPUs) have begun to be preferred to CPUs for several computationally intensive applications, not necessarily related to computer graphics. However, due to their complexity GPGPUs also show a relatively high sensitivity to soft errors. Hence, there is some interest in devising and applying software techniques able to exploit their computational power by just acting on the executed code. In this paper we report some preliminary results obtained by applying two different software redundancy techniques aimed at soft-error detection; these techniques are completely algorithm independent, and have been applied on a sample application running on a Commercial-Off-The-Shelf GPGPU. The results have been gathered resorting to a neutron testing campaign. Some experimental results, explaining the capabilities of the methods, are presented and commente
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe 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
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