5 resultados para Precious stones.

em Bucknell University Digital Commons - Pensilvania - USA


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Capuchin monkeys are notable among New World monkeys for their widespread use of tools. They use both hammer tools and insertion tools in the wild to acquire food that would be unobtainable otherwise. Evidence indicates that capuchins transport stones to anvil sites and use the most functionally efficient stones to crack nuts. We investigated capuchins’ assessment of functionality by testing their ability to select a tool that was appropriate for two different tool-use tasks: A stone for a hammer task and a stick for an insertion task. To select the appropriate tools, the monkeys investigated a baited tool-use apparatus (insertion or hammer), traveled to a location in their enclosure where they could no longer see the apparatus, made a selection between two tools (stick or stone), and then could transport the tool back to the apparatus to obtain a walnut. Four capuchins were first trained to select and use the appropriate tool for each apparatus. After training, they were then tested by allowing them to view a baited apparatus and then travel to a location 8 m distant where they could select a tool while out of view of the apparatus. All four monkeys chose the correct tool significantly more than expected and transported the tools back to the apparatus. Results confirm capuchins’ propensity for transporting tools, demonstrate their capacity to select the functionally appropriate tool for two different tool-use tasks, and indicate that they can retain the memory of the correct choice during a travel time of several seconds.

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Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

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Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

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This thesis assesses relationships between vegetation and topography and the impact of human tree-cutting on the vegetation of Union County during the early historical era (1755-1855). I use early warrant maps and forestry maps from the Pennsylvania historical archives and a warrantee map from the Union County courthouse depicting the distribution of witness trees and non-tree surveyed markers (posts and stones) in early European settlement land surveys to reconstruct the vegetation and compare vegetation by broad scale (mountains and valleys) and local scale (topographic classes with mountains and valleys) topography. I calculated marker density based on 2 km x 2 km grid cells to assess tree-cutting impacts. Valleys were mostly forests dominated by white oak (Quercus alba) with abundant hickory (Carya spp.), pine (Pinus spp.), and black oak (Quercus velutina), while pine dominated what were mostly pine-oak forests in the mountains. Within the valleys, pine was strongly associated with hilltops, eastern hemlock (Tsuga canadensis) was abundant on north slopes, hickory was associated with south slopes, and riparian zones had high frequencies of ash (Fraxinus spp.) and hickory. In the mountains, white oak was infrequent on south slopes, chestnut (Castanea dentata) was more abundant on south slopes and ridgetops than north slopes and mountain coves, and white oak and maple (Acer spp.) were common in riparian zones. Marker density analysis suggests that trees were still common over most of the landscape by 1855. The findings suggest there were large differences in vegetation between valleys and mountains due in part to differences in elevation, and vegetation differed more by topographic classes in the valleys than in the mountains. Possible areas of tree-cutting were evenly distributed by topographic classes, suggesting Europeans settlers were clearing land and harvesting timber in most areas of Union County.

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Content Addressable Memory (CAM) is a special type of Complementary Metal-Oxide-Semiconductor (CMOS) storage element that allows for a parallel search operation on a memory stack in addition to the read and write operations yielded by a conventional SRAM storage array. In practice, it is often desirable to be able to store a “don’t care” state for faster searching operation. However, commercially available CAM chips are forced to accomplish this functionality by having to include two binary memory storage elements per CAM cell,which is a waste of precious area and power resources. This research presents a novel CAM circuit that achieves the “don’t care” functionality with a single ternary memory storage element. Using the recent development of multiple-voltage-threshold (MVT) CMOS transistors, the functionality of the proposed circuit is validated and characteristics for performance, power consumption, noise immunity, and silicon area are presented. This workpresents the following contributions to the field of CAM and ternary-valued logic:• We present a novel Simple Ternary Inverter (STI) transistor geometry scheme for achieving ternary-valued functionality in existing SOI-CMOS 0.18µm processes.• We present a novel Ternary Content Addressable Memory based on Three-Valued Logic (3CAM) as a single-storage-element CAM cell with “don’t care” functionality.• We explore the application of macro partitioning schemes to our proposed 3CAM array to observe the benefits and tradeoffs of architecture design in the context of power, delay, and area.