5 resultados para systems of quantities

em Duke University


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Mechanisms for the evolution of convergent behavioral traits are largely unknown. Vocal learning is one such trait that evolved multiple times and is necessary in humans for the acquisition of spoken language. Among birds, vocal learning is evolved in songbirds, parrots, and hummingbirds. Each time similar forebrain song nuclei specialized for vocal learning and production have evolved. This finding led to the hypothesis that the behavioral and neuroanatomical convergences for vocal learning could be associated with molecular convergence. We previously found that the neural activity-induced gene dual specificity phosphatase 1 (dusp1) was up-regulated in non-vocal circuits, specifically in sensory-input neurons of the thalamus and telencephalon; however, dusp1 was not up-regulated in higher order sensory neurons or motor circuits. Here we show that song motor nuclei are an exception to this pattern. The song nuclei of species from all known vocal learning avian lineages showed motor-driven up-regulation of dusp1 expression induced by singing. There was no detectable motor-driven dusp1 expression throughout the rest of the forebrain after non-vocal motor performance. This pattern contrasts with expression of the commonly studied activity-induced gene egr1, which shows motor-driven expression in song nuclei induced by singing, but also motor-driven expression in adjacent brain regions after non-vocal motor behaviors. In the vocal non-learning avian species, we found no detectable vocalizing-driven dusp1 expression in the forebrain. These findings suggest that independent evolutions of neural systems for vocal learning were accompanied by selection for specialized motor-driven expression of the dusp1 gene in those circuits. This specialized expression of dusp1 could potentially lead to differential regulation of dusp1-modulated molecular cascades in vocal learning circuits.

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We report a comprehensive study of the binary systems of the platinum-group metals with the transition metals, using high-throughput first-principles calculations. These computations predict stability of new compounds in 28 binary systems where no compounds have been reported in the literature experimentally and a few dozen of as-yet unreported compounds in additional systems. Our calculations also identify stable structures at compound compositions that have been previously reported without detailed structural data and indicate that some experimentally reported compounds may actually be unstable at low temperatures. With these results, we construct enhanced structure maps for the binary alloys of platinum-group metals. These maps are much more complete, systematic, and predictive than those based on empirical results alone.

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Vocal learning is a critical behavioral substrate for spoken human language. It is a rare trait found in three distantly related groups of birds-songbirds, hummingbirds, and parrots. These avian groups have remarkably similar systems of cerebral vocal nuclei for the control of learned vocalizations that are not found in their more closely related vocal non-learning relatives. These findings led to the hypothesis that brain pathways for vocal learning in different groups evolved independently from a common ancestor but under pre-existing constraints. Here, we suggest one constraint, a pre-existing system for movement control. Using behavioral molecular mapping, we discovered that in songbirds, parrots, and hummingbirds, all cerebral vocal learning nuclei are adjacent to discrete brain areas active during limb and body movements. Similar to the relationships between vocal nuclei activation and singing, activation in the adjacent areas correlated with the amount of movement performed and was independent of auditory and visual input. These same movement-associated brain areas were also present in female songbirds that do not learn vocalizations and have atrophied cerebral vocal nuclei, and in ring doves that are vocal non-learners and do not have cerebral vocal nuclei. A compilation of previous neural tracing experiments in songbirds suggests that the movement-associated areas are connected in a network that is in parallel with the adjacent vocal learning system. This study is the first global mapping that we are aware for movement-associated areas of the avian cerebrum and it indicates that brain systems that control vocal learning in distantly related birds are directly adjacent to brain systems involved in movement control. Based upon these findings, we propose a motor theory for the origin of vocal learning, this being that the brain areas specialized for vocal learning in vocal learners evolved as a specialization of a pre-existing motor pathway that controls movement.

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The ability to imitate complex sounds is rare, and among birds has been found only in parrots, songbirds, and hummingbirds. Parrots exhibit the most advanced vocal mimicry among non-human animals. A few studies have noted differences in connectivity, brain position and shape in the vocal learning systems of parrots relative to songbirds and hummingbirds. However, only one parrot species, the budgerigar, has been examined and no differences in the presence of song system structures were found with other avian vocal learners. Motivated by questions of whether there are important differences in the vocal systems of parrots relative to other vocal learners, we used specialized constitutive gene expression, singing-driven gene expression, and neural connectivity tracing experiments to further characterize the song system of budgerigars and/or other parrots. We found that the parrot brain uniquely contains a song system within a song system. The parrot "core" song system is similar to the song systems of songbirds and hummingbirds, whereas the "shell" song system is unique to parrots. The core with only rudimentary shell regions were found in the New Zealand kea, representing one of the only living species at a basal divergence with all other parrots, implying that parrots evolved vocal learning systems at least 29 million years ago. Relative size differences in the core and shell regions occur among species, which we suggest could be related to species differences in vocal and cognitive abilities.

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In the United States, poverty has been historically higher and disproportionately concentrated in the American South. Despite this fact, much of the conventional poverty literature in the United States has focused on urban poverty in cities, particularly in the Northeast and Midwest. Relatively less American poverty research has focused on the enduring economic distress in the South, which Wimberley (2008:899) calls “a neglected regional crisis of historic and contemporary urgency.” Accordingly, this dissertation contributes to the inequality literature by focusing much needed attention on poverty in the South.

Each empirical chapter focuses on a different aspect of poverty in the South. Chapter 2 examines why poverty is higher in the South relative to the Non-South. Chapter 3 focuses on poverty predictors within the South and whether there are differences in the sub-regions of the Deep South and Peripheral South. These two chapters compare the roles of family demography, economic structure, racial/ethnic composition and heterogeneity, and power resources in shaping poverty. Chapter 4 examines whether poverty in the South has been shaped by historical racial regimes.

The Luxembourg Income Study (LIS) United States datasets (2000, 2004, 2007, 2010, and 2013) (derived from the U.S. Census Current Population Survey (CPS) Annual Social and Economic Supplement) provide all the individual-level data for this study. The LIS sample of 745,135 individuals is nested in rich economic, political, and racial state-level data compiled from multiple sources (e.g. U.S. Census Bureau, U.S. Department of Agriculture, University of Kentucky Center for Poverty Research, etc.). Analyses involve a combination of techniques including linear probability regression models to predict poverty and binary decomposition of poverty differences.

Chapter 2 results suggest that power resources, followed by economic structure, are most important in explaining the higher poverty in the South. This underscores the salience of political and economic contexts in shaping poverty across place. Chapter 3 results indicate that individual-level economic factors are the largest predictors of poverty within the South, and even more so in the Deep South. Moreover, divergent results between the South, Deep South, and Peripheral South illustrate how the impact of poverty predictors can vary in different contexts. Chapter 4 results show significant bivariate associations between historical race regimes and poverty among Southern states, although regression models fail to yield significant effects. Conversely, historical race regimes do have a small, but significant effect in explaining the Black-White poverty gap. Results also suggest that employment and education are key to understanding poverty among Blacks and the Black-White poverty gap. Collectively, these chapters underscore why place is so important for understanding poverty and inequality. They also illustrate the salience of micro and macro characteristics of place for helping create, maintain, and reproduce systems of inequality across place.