238 resultados para Mechanical harvest


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Bone plays a key role in the paleontological and archeological records and can provide insight into the biology, ecology and the environment of ancient vertebrates. Examination of bone at the tissue level reveals a definitive relationship between nanomechanical properties and the local organic content, mineral content, and microstructural organization. However, it is unclear as to how these properties change following fossilization, or diagenesis, where the organic phase is rapidly removed and the remaining mineral phase is reinforced by the deposition of apatites, calcites, and other minerals. While the process of diagenesis is poorly understood, its outcome clearly results in the potential for dramatic alteration of the mechanical response of biological tissues. In this study, fossilized specimens of mammalian long bones, collected from Colorado and Wyoming, were studied for mechanical variations. Nanoindentation performed in both longitudinal and transverse directions revealed preservation of bone's natural anisotropy as transverse modulus values were consistently smaller than longitudinal values. Additionally, modulus values of fossilized bone from 35.0 to 89.1 GPa increased linearly with logarithm of the sample's age. Future studies will aim to clarify what mechanical and material elements of bone are retained during diagenesis as bone becomes part of the geologic milieu. © 2007 Materials Research Society.

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A biomimetic reactor has been developed to synthesize hydroxyapatite- gelatin (HAP-GEL) nanocomposites that mimic ultra-structures of natural bone. We hypothesize that in the reactor, gelatin concentration controls morphology and packing structures of HAP crystals. To test the hypothesis, three types of mechanical tests were conducted, including nanoindentation, compression, and fracture tests. Nanoindentation tests in conjunction with computer modeling were used to assess effects on gelatin-induced microstructures of HAP. The results showed that increasing gelatin content increased both the plane strain modulus and the fracture toughness. The gelatin appeared to shorten the HAP crystal distance, which consolidated the internal structure of the composite and made the material more rigid. The fracture toughness KIC increased partially due to the effect of fiber bridging between gelatin molecules. The highest fracture toughness (1.12 MPa·1/2) was equivalent to that of pure hydroxyapatite. The compressive strength of the HAP-GEL (107.7±26.8 MPa) was, however, less sensitive to microstructural changes and was within the range of natural cortical bone (human 170 MPa, pig: 100 MPa). The compression strength was dominated by void inclusions while the nanoindentation response reflected ultra-structural arrangement of the crystals. The gelatin concentration is likely to modify crystal arrangement as demonstrated in TEM experiments but not void distribution at macroscopic levels. © 2006 Materials Research Society.

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Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

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