33 resultados para visual contrast


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Graphene oxide-CoFe2O4 nanoparticle composites were synthesized using a two step synthesis method in which graphene oxide was initially synthesized followed by precipitation of CoFe2O4 nanoparticles in a reaction mixture containing graphene oxide. Samples were extracted from the reaction mixture at different times at 80 degrees C. All the extracted samples contained CoFe2O4 nanoparticles formed over the graphene oxide. It was observed that the increase in the reflux time significantly increased the saturation magnetization value for the superparamagnetic nanoparticles in the composite. It was also noticed that the size of the nanoparticles increased with increase in the reflux time. Transverse relaxivity of the water protons increased monotonically with increase in the reflux time. Whereas, the longitudinal relaxivity value initially increased and then decreased with the reflux time. Graphene oxide-CoFe2O4 nanoparticle composites also exhibit biocompatibility towards the MCF-7 cell line.

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Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.

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We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes.