1,720,981 research outputs found
Fully automatic saliency-based subjects extraction in digital images
No full textIn this paper we present a novel saliency-based technique for the automatic extraction of relevant subjects in digital images. We use enhanced saliency maps to determine the most relevant parts of the images and an image cropping technique on the map itself to extract one or more relevant subjects. The contribution of the paper is two-fold as we propose a technique to enhance the standard GBVS saliency map and a technique to extract the most salient parts of the image. The GBVS saliency map is enhanced by applying three filters particularly designed to optimize the performance for the task of relevant subjects extraction. The extraction of relevant subjects is demonstrated on a manually annotated dataset and results are encouraging. A variation of the same technique has also been used to extract the most significant region of an image. This region can then be used to obtain a thumbnail keeping most of the relevant information of the original image and discarding nonsignificant background. Experimental results are reported also in this case
Curcumin as scaffold for drug discovery against neurodegenerative diseases
Full text linkNeurodegenerative diseases (NDs) are one of major public health problems and their impact is continuously growing. Curcumin has been proposed for the treatment of several of these pathologies, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) due to the ability of this molecule to reduce inflammation and aggregation of involved proteins. Nevertheless, the poor metabolic stability and bioavailability of curcumin reduce the possibilities of its practical use. For these reasons, many curcumin derivatives were synthetized in order to overcome some limitations. In this review will be highlighted recent results on modification of curcumin scaffold in the search of new effective therapeutic agents against NDs, with particular emphasis on AD
Narcotrend (NT) monitoring depth of anesthesia in gynaecologic surgery: a comparison with Bispectral Index (BIS)
No full textHeat shock protein 60 (Hsp60) modulation by the Histon Deacetylase Inhibitor (HDAC-i) SAHA in mucoepidermoid tumor H292 cells
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
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