185 resultados para NEURAL-TUBE DEFECTS


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Composite structures exhibit many different failure mechanisms, but attempts to model composite failure frequently make a priori assumptions about the mechanism by which failure will occur. Wang et al. [1] conducted compressive tests on four configurations of composite specimen manufactured with out-of-plane waviness created by ply-drop defects. There were significantly different failures for each case. Detailed finite element models of these experiments were developed which include competing failure mechanisms. The model predictions correlate well with experimental results-both qualitatively (location of failure and shape of failed specimen) and quantitatively (failure load). The models are used to identify the progression of failure during the compressive tests, determine the critical failure mechanism for each configuration, and investigate the effect of cohesive parameters upon specimen strength. This modelling approach which includes multiple competing failure mechanisms can be applied to predict failure in situations where the failure mechanism is not known in advance. © 2013 Elsevier Ltd. All rights reserved.

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There is increasing evidence for the involvement of lipid membranes in both the functional and pathological properties of α-synuclein (α-Syn). Despite many investigations to characterize the binding of α-Syn to membranes, there is still a lack of understanding of the binding mode linking the properties of lipid membranes to α-Syn insertion into these dynamic structures. Using a combination of an optical biosensing technique and in situ atomic force microscopy, we show that the binding strength of α-Syn is related to the specificity of the lipid environment (the lipid chemistry and steric properties within a bilayer structure) and to the ability of the membranes to accommodate and remodel upon the interaction of α-Syn with lipid membranes. We show that this interaction results in the insertion of α-Syn into the region of the headgroups, inducing a lateral expansion of lipid molecules that can progress to further bilayer remodeling, such as membrane thinning and expansion of lipids out of the membrane plane. We provide new insights into the affinity of α-Syn for lipid packing defects found in vesicles of high curvature and in planar membranes with cone-shaped lipids and suggest a comprehensive model of the interaction between α-Syn and lipid bilayers. The ability of α-Syn to sense lipid packing defects and to remodel membrane structure supports its proposed role in vesicle trafficking.

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We investigate how to tailor the structural, crystallographic and optical properties of GaAs nanowires. Nanowires were grown by Au nanoparticle-catalyzed metalorganic chemical vapor deposition. A high arsine flow rate, that is, a high ratio of group V to group III precursors, imparts significant advantages. It dramatically reduces planar crystallographic defects and reduces intrinsic carbon dopant incorporation. Increasing V/III ratio further, however, instigates nanowire kinking and increases nanowire tapering. By choosing an intermediate V/III ratio we achieve uniform, vertically aligned GaAs nanowires, free of planar crystallographic defects, with excellent optical properties and high purity. These findings will greatly assist the development of future GaAs nanowire-based electronic and optoelectronic devices, and are expected to be more broadly relevant to the rational synthesis of other III-V nanowires. © 2008 WILEY-VCH Verlag GmbH & Co. KGaA.

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One-color transient reflectivity measurements are carried out on two different samples of vertically aligned single-wall carbon nanotube bundles and compared with the response recently published on unaligned bundles. The negative sign of the optical response for both samples indicates that the free electron character revealed on unaligned bundles is only due to the intertube interactions favored by the tube bending. Neither the presence of bundles nor the existence of structural defects in aligned bundles is able to induce a free-electron like behavior of the photoexcited carriers. This result is also confirmed by the presence of non-linear excitonic effects in the transient response of the aligned bundles. © 2013 Elsevier B.V.

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This paper presents ongoing work on data collection and collation from a large number of laboratory cement-stabilization projects worldwide. The aim is to employ Artificial Neural Networks (ANN) to establish relationships between variables, which define the properties of cement-stabilized soils, and the two parameters determined by the Unconfined Compression Test, the Unconfined Compressive Strength (UCS), and stiffness, using E50 calculated from UCS results. Bayesian predictive neural network models are developed to predict the UCS values of cement-stabilized inorganic clays/silts, as well as sands as a function of selected soil mix variables, such as grain size distribution, water content, cement content and curing time. A model which can predict the stiffness values of cement-stabilized clays/silts is also developed and compared to the UCS model. The UCS model results emulate known trends better and provide more accurate estimates than the results from the E50 stiffness model. © 2013 American Society of Civil Engineers.

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In natural languages multiple word sequences can represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage, for example, when using n-gram language models (LM). To handle this issue, paraphrastic LMs were proposed in previous research and successfully applied to a US English conversational telephone speech transcription task. In order to exploit the complementary characteristics of paraphrastic LMs and neural network LMs (NNLM), the combination between the two is investigated in this paper. To investigate paraphrastic LMs' generalization ability to other languages, experiments are conducted on a Mandarin Chinese broadcast speech transcription task. Using a paraphrastic multi-level LM modelling both word and phrase sequences, significant error rate reductions of 0.9% absolute (9% relative) and 0.5% absolute (5% relative) were obtained over the baseline n-gram and NNLM systems respectively, after a combination with word and phrase level NNLMs. © 2013 IEEE.

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The advent of nanotechnology has revolutionised our ability to engineer electrode interfaces. These are particularly attractive to measure biopotentials, and to study the nervous system. In this work, we demonstrate enhanced in vitro recording of neuronal activity using electrodes decorated with carbon nanosheets (CNSs). This material comprises of vertically aligned, free standing conductive sheets of only a few graphene layers with a high surfacearea- to-volume ratio, which makes them an interesting material for biomedical electrodes. Further, compared to carbon nanotubes, CNSs can be synthesised without the need for metallic catalysts like Ni, Co or Fe, thereby reducing potential cytotoxicity risks. Electrochemical measurements show a five times higher charge storage capacity, and an almost ten times higher double layer capacitance as compared to TiN. In vitro experiments were performed by culturing primary hippocampal neurons from mice on micropatterned electrodes. Neurophysiological recordings exhibited high signal-to-noise ratios of 6.4, which is a twofold improvement over standard TiN electrodes under the same conditions. © 2013 Elsevier Ltd. All rights reserved.