3 resultados para University of Michigan. College of Literature, Science and the Arts

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Corn grits that were supplemented with isovaleraldehyde, ethyl butyrate, butyric acid and flavour enhancers were extruded under different processing conditions. Volatile compounds retained in the extrudates were isolated by dynamic headspace and analysed using gas chromatographymass spectrometry. The expansion ratio, density and cut force to break down the extrudates were evaluated and aroma intensity was assessed using a multisample difference test. Butyric acid showed the greatest retention (96.4%), regardless of the extrusion conditions. All compounds were better retained when samples were extruded at 20% feed moisture and 90 degrees C processing temperature (2.981.0%), conditions that also resulted in greater aromatic intensity (moderate to moderate-strong intensity). The addition of volatile compounds reduced the expansion ratio and cut force, whereas the addition of flavour enhancers increased the expansion ratio but reduced ethyl butyrate and butyric acid retention.

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Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.