414 research outputs found

    ā€˜Zhengmeiā€™: A new early-ripening table grape

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    Achieving a high-Q response in metamaterials by manipulating the toroidal excitations

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    The excitation of toroidal multipoles in metamaterials is investigated for a high- Q response at a subwavelength scale. In this paper, we explore the optimization of toroidal excitations in a planar metamaterial comprised of asymmetric split ring resonators (ASRRs). It is found that the scattering power of a toroidal dipole can be remarkably strengthened by adjusting the characteristic parameter of ASRRs: an asymmetric factor. Interestingly, the improvement in toroidal excitation accompanies an increment of the Q factor of the toroidal metamaterial; it is shown that both the scattering power of the toroidal dipole and the Q factor increase more than one order by changing the asymmetric factor of ASRRs. The optimization in the excitation of a toroidal multipole provides an opportunity to further increase the Q factor of the metamaterial and boost light-matter interactions at the subwavelength scale for potential applications in low-power nonlinear processing and sensitive photonic applications

    Automatic and Rapid Discrimination of Cotton Genotypes by Near Infrared Spectroscopy and Chemometrics

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    This paper reports the application of near infrared (NIR) spectroscopy and pattern recognition methods to rapid and automatic discrimination of the genotypes (parent, transgenic, and parent-transgenic hybrid) of cotton plants. Diffuse reflectance NIR spectra of representative cotton seeds (n = 120) and leaves (n = 123) were measured in the range of 4000ā€“12000ā€‰cmāˆ’1. A practical problem when developing classification models is the degradation and even breakdown of models caused by outliers. Considering the high-dimensional nature and uncertainty of potential spectral outliers, robust principal component analysis (rPCA) was applied to each separate sample group to detect and exclude outliers. The influence of different data preprocessing methods on model prediction performance was also investigated. The results demonstrate that rPCA can effectively detect outliers and maintain the efficiency of discriminant analysis. Moreover, the classification accuracy can be significantly improved by second-order derivative and standard normal variate (SNV). The best partial least squares discriminant analysis (PLSDA) models obtained total classification accuracy of 100% and 97.6% for seeds and leaves, respectively

    Integral equation method for the electromagnetic wave propagation in stratified anisotropic dielectric-magnetic materials

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    We investigate the propagation of electromagnetic waves in stratified anisotropic dielectric-magnetic materials using the integral equation method (IEM). Based on the superposition principle, we use Hertz vector formulations of radiated fields to study the interaction of wave with matter. We derive in a new way the dispersion relation, Snell's law and reflection/transmission coefficients by self-consistent analyses. Moreover, we find two new forms of the generalized extinction theorem. Applying the IEM, we investigate the wave propagation through a slab and disclose the underlying physics which are further verified by numerical simulations. The results lead to a unified framework of the IEM for the propagation of wave incident either from a medium or vacuum in stratified dielectric-magnetic materials.Comment: 14pages, 3figure

    Profiling alternatively spliced mRNA isoforms for prostate cancer classification

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    BACKGROUND: Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomarkers for early clinical diagnosis and treatment. Previously, we developed an exon-junction microarray-based assay and profiled 1532 mRNA splice isoforms from 364 potential prostate cancer related genes in 38 prostate tissues. Here, we investigate the advantage of using splice isoforms, which couple transcriptional and splicing regulation, for cancer classification. RESULTS: As many as 464 splice isoforms from more than 200 genes are differentially regulated in tumors at a false discovery rate (FDR) of 0.05. Remarkably, about 30% of genes have isoforms that are called significant but do not exhibit differential expression at the overall mRNA level. A support vector machine (SVM) classifier trained on 128 signature isoforms can correctly predict 92% of the cases, which outperforms the classifier using overall mRNA abundance by about 5%. It is also observed that the classification performance can be improved using multivariate variable selection methods, which take correlation among variables into account. CONCLUSION: These results demonstrate that profiling of splice isoforms is able to provide unique and important information which cannot be detected by conventional microarrays

    Direct phasing of one-wavelength anomalous-scattering data of the protein core streptavidin

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    The direct method [Fan, Hao, Gu, Qian, Zheng & Ke (1990). Acta Cryst. A46, 935-939] was used to break the phase ambiguity intrinsic to one-wavelength anomalous scattering data from a known protein of moderate size, core streptavidin, which was solved originally with three-wavelength anomalous diffraction data [Hendrickson, PƤhler, Smith, Satow, Merritt & Phizackerley (1989). Proc. Natl Acad. Sci. USA, 86, 2190-2194]. Unlike that in the previous test with a small protein, the Fourier map calculated with the direct-method phases could not clearly reveal the moderate-sized protein structure. However, the phases can be improved step by step using Wang's solvent-flattening method, non-crystallographic symmetry averaging and the skeletonization method. The final electron-density map clearly shows most Calpha positions and some side chains and it is traceable without prior knowledge of the structure. It is concluded that the direct method is capable of breaking the OAS phase ambiguity of a moderate-sized protein at moderate resolution such as 3 A, while the combination of direct methods with macromolecular techniques may produce phases good enough for unknown protein structure to be traced
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