4 resultados para Classes of Degeneracy

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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[EN]A comprehensive evaluation of the fatty acid composition of subcutaneous adipose tissue from beef cattle produced in western Canada was undertaken to determine if the current Canadian grading system is able to distinguish classes of animals with value added potential due to their fatty acid composition. Grades included youthful Canadian Yield Grade 1 A/AA beef, under (YUTM) and over (YOTM) 30 mo of age and the four mature grades (D1, D2, D2 and D4). Subcutaneous fat between the 12th and 13th ribs over the longissimus muscle was obtained from 18_21 animals per grade. Fatty acids were analyzed using a combination of silver-ion HPLC and GC with a highly polar 100 m column. There were no differences in total trans-18:1 content amongst grades, but adipose tissue from grade D1, D2 and D4 had more 11t-18:1 than YUTM (PB0.05), whereas adipose tissue from YUTM carcasses had more 10t-18:1 than all other grades (PB0.05). Adipose tissue from YUTM carcasses also had less total CLA (PB0.05) than the D grades, mainly due to a lower level of 9c,11t-CLA, but they had slightly more 7t,9c-CLA and 10t,12c-CLA (PB0.05). Adipose tissue from YOTM and D grades contained more n-3 fatty acids relative to YUTM (0.56% vs. 0.29%; PB0.05) and lower n-6:n-3 ratios (PB0.05). Overall, older animals (YOTM and D grades) had adipose tissue compositions with higher levels of fatty acids with reported health benefits. Taken together, these higher levels may provide opportunities for value added marketing if regulatory authorities allow claims for their enrichment based on demonstrated health benefits. Higher concentrations of beneficial fatty acids, however, need to be considered within the context of the complete fatty acid profile and it would be important to demonstrate their advantages in the presence of relatively high levels of saturated fatty acids.

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In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

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On several classes of n-person NTU games that have at least one Shapley NTU value, Aumann characterized this solution by six axioms: Non-emptiness, efficiency, unanimity, scale covariance, conditional additivity, and independence of irrelevant alternatives (IIA). Each of the first five axioms is logically independent of the remaining axioms, and the logical independence of IIA is an open problem. We show that for n = 2 the first five axioms already characterize the Shapley NTU value, provided that the class of games is not further restricted. Moreover, we present an example of a solution that satisfies the first five axioms and violates IIA for two-person NTU games (N, V) with uniformly p-smooth V(N).

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Grain boundaries and defect lines in graphene are intensively studied for their novel electronic and magnetic properties. However, there is not a complete comprehension of the appearance of localized states along these defects. Graphene grain boundaries are herein seen as the outcome of matching two semi-infinite graphene sheets with different edges. We classify the energy spectra of grain boundaries into three different types, directly related to the combination of the four basic classes of spectra of graphene edges. From the specific geometry of the grains, we are able to obtain the band structure and the number of localized states close to the Fermi energy. This provides a new understanding of states localized at grain boundaries, showing that they are derived from the edge states of graphene. Such knowledge is crucial for the ultimate tailoring of electronic and optoelectronic applications.