9 resultados para Corn - Fibers

em Queensland University of Technology - ePrints Archive


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The mechanical strength and failure behavior of conventional and microstructured silica optical fibers was investigated using a tensile test and fracture mechanics and numerical analyses. The effect of polymer coating on failure behavior was also studied. The results indicate that all these fibers fail in a brittle manner and failure normally starts from fiber surfaces. The failure loads observed in coated fibers are higher than those in bare fibers. The introduction of air holes reduces fiber strength and their geometrical arrangements have a remarkable effect on stress distribution in the longitudinal direction. These results are potentially useful for the design, fabrication and evaluation of optical fibers for a wide range of applications.

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Nitrous oxide (N2O) is a major greenhouse gas (GHG) product of intensive agriculture. Fertilizer nitrogen (N) rate is the best single predictor of N2O emissions in row-crop agriculture in the US Midwest. We use this relationship to propose a transparent, scientifically robust protocol that can be utilized by developers of agricultural offset projects for generating fungible GHG emission reduction credits for the emerging US carbon cap and trade market. By coupling predicted N2O flux with the recently developed maximum return to N (MRTN) approach for determining economically profitable N input rates for optimized crop yield, we provide the basis for incentivizing N2O reductions without affecting yields. The protocol, if widely adopted, could reduce N2O from fertilized row-crop agriculture by more than 50%. Although other management and environmental factors can influence N2O emissions, fertilizer N rate can be viewed as a single unambiguous proxy—a transparent, tangible, and readily manageable commodity. Our protocol addresses baseline establishment, additionality, permanence, variability, and leakage, and provides for producers and other stakeholders the economic and environmental incentives necessary for adoption of agricultural N2O reduction offset projects.

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Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.

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Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry. © 2009 Elsevier Inc. All rights reserved.

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To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

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An intrinsic exposed core optical fiber sensor (IECOFS) made from fused silica was used to monitor the crystallization of calcium carbonate (CaCO3) and CaCO3/calcium sulfate (CaSO4) composite at 100 and 120 °C in the absence and presence of low-molar-mass (Mn ≤ 2000) poly(acrylic acid) (PAA) with different end groups. The IECOFS responded only to deposition and growth processes on the fiber surface rather than changes occurring in the bulk of the solution. Hexyl isobutyrate-terminated PAA (Mn = 1400) and hexadecyl isobutyrate-terminated PAA (Mn = 1700) were the most effective species in preventing CaCO3 deposition. Phase transformation from vaterite to aragonite/calcite decreased with increasing hydrophobicity of the PAA end group. Low-molar-mass PAA at 10 ppm showed very significant inhibition of CaCO3/CaSO4 composite formation for all end groups investigated.