995 resultados para Breast volume


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Computational modelling of dynamic fluid–structure interaction (DFSI) is a considerable challenge. Our approach to this class of problems involves the use of a single software framework for all the phenomena involved, employing finite volume methods on unstructured meshes in three dimensions. This method enables time and space accurate calculations in a consistent manner. One key application of DFSI simulation is the analysis of the onset of flutter in aircraft wings, where the work of Yates et al. [Measured and Calculated Subsonic and Transonic Flutter Characteristics of a 45° degree Sweptback Wing Planform in Air and Freon-12 in the Langley Transonic Dynamic Tunnel. NASA Technical Note D-1616, 1963] on the AGARD 445.6 wing planform still provides the most comprehensive benchmark data available. This paper presents the results of a significant effort to model the onset of flutter for the AGARD 445.6 wing planform geometry. A series of key issues needs to be addressed for this computational approach. • The advantage of using a single mesh, in order to eliminate numerical problems when applying boundary conditions at the fluid-structure interface, is counteracted by the challenge of generating a suitably high quality mesh in both the fluid and structural domains. • The computational effort for this DFSI procedure, in terms of run time and memory requirements, is very significant. Practical simulations require even finer meshes and shorter time steps, requiring parallel implementation for operation on large, high performance parallel systems. • The consistency and completeness of the AGARD data in the public domain is inadequate for use in the validation of DFSI codes when predicting the onset of flutter.

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CFD modelling of 'real-life' processes often requires solutions in complex three dimensional geometries, which can often result in meshes where aspects of it are badly distorted. Cell-centred finite volume methods, typical of most commercial CFD tools, are computationally efficient, but can lead to convergence problems on meshes which feature cells with high non-orthogonal shapes. The vertex-based finite volume method handles distorted meshes with relative ease, but is computationally expensive. A combined vertex-based - cell-centred (VB-CC) technique, detailed in this paper, allows solutions on distorted meshes that defeat purely cell-centred physical models to be employed in the solution of other transported quantities. The VB-CC method is validated with benchmark solutions for thermally driven flow and turbulent flow. An early application of this hybrid technique is to three-dimensional flow over an aircraft wing, although it is planned to use it in a wide variety of processing applications in the future.

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An unstructured cell-centred finite volume method for modelling viscoelastic flow is presented. The method is applied to the flow through a planar channel and the 4:1 planar contraction for creeping flow of an Oldroyd-B fluid. The results are presented for a range of Weissenberg numbers. In the case of the planar channel results are compared with analytical solutions. For the 4:1 planar contraction benchmark problem the convection terms in the constitutive equations are approximated using both first and second order differencing schemes to compare the techniques and the effect of mesh refinement on the solution is investigated. This is the first time that a fully unstructured, cell-centredfinitevolume technique has been used to model the Oldroyd-B fluid for the test cases presented in this paper.

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Johnson's SB and the logit-logistic are four-parameter distribution models that may be obtained from the standard normal and logistic distributions by a four-parameter transformation. For relatively small data sets, such as diameter at breast height measurements obtained from typical sample plots, distribution models with four or less parameters have been found to be empirically adequate. However, in situations in which the distributions are complex, for example in mixed stands or when the stand has been thinned or when working with aggregated data, then distribution models with more shape parameters may prove to be necessary. By replacing the symmetric standard logistic distribution of the logit-logistic with a one-parameter “standard Richards” distribution and transforming by a five-parameter Richards function, we obtain a new six-parameter distribution model, the “Richit-Richards”. The Richit-Richards includes the “logit-Richards”, the “Richit-logistic”, and the logit-logistic as submodels. Maximum likelihood estimation is used to fit the model, and some problems in the maximum likelihood estimation of bounding parameters are discussed. An empirical case study of the Richit-Richards and its submodels is conducted on pooled diameter at breast height data from 107 sample plots of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.). It is found that the new models provide significantly better fits than the four-parameter logit-logistic for large data sets.

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This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.

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Pulse design is investigated for time-reversal (TR) imaging as applied to ultrawideband (UWB) breast cancer detection. Earlier it has been shown that a suitably-designed UWB pulse may help to improve imaging performance for a single-tumor breast phantom with predetermined lesion properties. The current work considers the following more general and practical situations: presence of multiple malignancies with unknown tumor size and dielectric properties. Four pulse selection criteria are proposed with each focusing on one of the following aspects: eliminating signal clutter generated by tissue inhomogeneities, canceling mutual interference among tumors, improving image resolution, and suppressing artifacts created by sidelobe of the target response. By applying the proposed criteria, the shape parameters of UWB waveforms with desirable characteristics are identified through search of all the possible pulses. Simulation example using a numerical breast phantom, comprised of two tumors and structured clutter distribution, demonstrates the effectiveness of the proposed approach. Specifically, a tradeoff between the image resolution and signal-to-clutter contrast (SCC) is observed in terms of selection of the excitation waveforms.

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In this paper, a runback water and ice prediction model is extended to anti-icing and thermal de-icing situations. The resulting coupled equations that govern thin-film flow, ice accretion, and heat conduction in the multilayered system substrate-ice-water are solved using an explicit finite volume approach. The procedure is implemented in the three-dimensional icing code ICECREMO2, and both structured and unstructured grids can be considered. Numerical results are presented to compare the present code simulations to some data provided by other ice prediction codes and to show the capabilities of the present numerical tool.

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AIM: To examine the concentrations of zinc and omega-6 polyunsaturated fatty acids (omega-6 PUFAs) in breast milk, the impact of zinc on omega-6 PUFA metabolism, and the growth rate of infants. METHODS: Forty-one mother-term infant pairs from a rural area of northern Beijing, China, who were 1 month (n = 18, group I) and 3 months (n = 23, group II) old and exclusively breastfed, were studied. The dietary records and the concentrations of zinc and omega-6 PUFAs in the milk of lactating women and the increase in weight and length of their infants during 1 and 3 postnatal months were analysed. RESULTS: The dietary intakes of mothers in the two groups were the same, i.e. high in carbohydrate and low in fat, protein and energy. The maternal zinc intake was 7.5mg/d and thus reached only 34.6% of the current Recommended Nutrient Intake (RNI). The levels of zinc and arachidonic acid (AA, C20:4 omega-6) in the milk of group I were significantly higher than those in group II. Furthermore, significant positive correlations were found between the concentrations of zinc and AA in the breast milk and between the level of milk AA and weight gain. CONCLUSION: Zinc may be a co-factor and essential for essential fatty acids (EFA) metabolism. Thus suboptimal zinc intake may cause EFA imbalance. Further studies of Chinese rural mother-infant pairs are necessary to determine whether zinc supplementation should be recommended when lactation exceeds 3 months.