Near-field imaging of locally perturbed periodic surfaces

This paper concerns the inverse scattering problem to reconstruct a locally perturbed periodic surface. Different from scattering problems with quasi-periodic incident fields and periodic surfaces, the scattered fields are no longer quasi-periodic. Thus the classical method for quasi-periodic scattering problems no longer works. In this paper, we apply a Floquet-Bloch transform based numerical method to reconstruct both the unknown periodic part and the unknown local perturbation from the near-field data. By transforming the original scattering problem into one defined in an infinite rectangle, the information of the surface is included in the coefficients. The numerical scheme contains two steps. The first step is to obtain an initial guess, i.e., the locations of both the periodic surfaces and the local perturbations, from a sampling method. The second step is to reconstruct the surface. As is proved in this paper, for some incident fields, the corresponding scattered fields carry little information of the perturbation. In this case, we use this scattered field to reconstruct the periodic surface. Then we could apply the data that carries more information of the perturbation to reconstruct the local perturbation. The Newton-CG method is applied to solve the associated optimization problems. Numerical examples are given at the end of this paper to show the efficiency of the numerical method

Recursive integral method for transmission eigenvalues

Recently, a new eigenvalue problem, called the transmission eigenvalue problem, has attracted many researchers. The problem arose in inverse scattering theory for inhomogeneous media and has important applications in a variety of inverse problems for target identification and nondestructive testing. The problem is numerically challenging because it is non-selfadjoint and nonlinear. In this paper, we propose a recursive integral method for computing transmission eigenvalues from a finite element discretization of the continuous problem. The method, which overcomes some difficulties of existing methods, is based on eigenprojectors of compact operators. It is self-correcting, can separate nearby eigenvalues, and does not require an initial approximation based on some a priori spectral information. These features make the method well suited for the transmission eigenvalue problem whose spectrum is complicated. Numerical examples show that the method is effective and robust.Comment: 18 pages, 8 figure

Defining social exclusion in Western Sydney: exploring the role of housing tenure

Over the past decade social exclusion has increasingly been positioned at the forefront of political, academic and lay discourse as the cause of disadvantage. While the definition, measurement and solutions to social exclusion remain open to debate, housing has progressively been positioned as a central variable creating neighbourhoods of exclusion. Much of this debate has positioned areas of public housing as the most disadvantaged and socially excluded neighbourhoods. However, the multiplicity of social exclusion questions the simple identification of areas of public housing as the most excluded. By exploring six dimensions of exclusion (neighbourhood, social and civic engagement, access, crime and security, community identify and economic disadvantage) we argue that there is relatively little difference between areas dominated by public housing and those characterised by private rental for each of these individual dimensions of exclusion (with a number of exceptions). Rather, it is the experience of multiple dimensions of exclusion which marks areas of public housing as unique

A genetic study of resistance to kernel infection by Aspergillus flavus in maize (Zea mays L.)

Maize (Zea mays L.) kernel infection by Aspergillus flavus is a chronic problem in the southern USA. Genetic resistance to A. flavus is needed to solve this problem. To ascertain and understand the inheritance of resistance to field kernel infection by A. flavus, a five-parent diallel analysis and a half-sib family analysis of 35 maize crosses were conducted during 2003 and 2004 for percent kernel infection (PKI) rates. All parents contained the leafy gene (Lfy). From the combining ability analysis of the five maize parents and their 20 F1s, highly significant general combining ability (GCA), specific combining ability (SCA), and reciprocal effects were found. The analysis of genetic effects showed that the parents 914 and A619 had desirable GCA effects to enhance the average performance of A. flavus resistance in hybrid progeny. The crosses 914 �� A632, 914 �� WF9, and HY �� WF9 had consistently negative SCA effects across the two years. These results suggested that resistance to kernel infection by A. flavus existed among the parents and some of their crosses. Their potential performance with desired GCAs and SCAs could be exploited to develop resistant lines in breeding programs and to produce resistant hybrids. The reciprocal effects in the crosses across years reflected the presence of maternal effects in the maize kernel. These effects were partly responsible for resistance to A. flavus and should be considered in making crosses. The cross A632 �� HY had the highest negative significant reciprocal effect, indicating that it should promote resistance to A. flavus. Analyses of the 35 half-sib crosses derived from seven maize breeding lines indicated that both the genotype and genotype-by-year effects were highly significant. Broad-sense heritability for PKI estimated from variance components was 73.8%. A North Carolina Design-II analysis of 12 crosses was used to estimate additive and dominance genetic variances. Narrow-sense heritability and the average degree of dominance for PKI were 37.6% and 1.67, respectively. A comparison of a laboratory-based infection resistance screening (LIRS) with field-based PKI demonstrated that LIRS was effective and could be used to improve maize germplasm screening and to expedite A. flavus resistance breeding