47 research outputs found

    The association of two single nucleotide polymorphisms (SNPs) in growth hormone (GH) gene with litter size and superovulation response in goat-breeds

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    Two active mutations (A 781 G and A 1575 G) in growth hormone (GH) gene, and their associations with litter size (LS), were investigated in both a high prolificacy (Matou, n = 182) and a low prolificacy breed (Boer, n = 352) by using the PCR-RFLP method. Superovulation experiments were designed in 57 dams, in order to evaluate the effect of different genotypes of the GH gene on superovulation response. Two genotypes (AA and AB, CC and CD) in each mutation were detected in these two goat breeds. Neither BB nor DD homozygous genotypes were observed. The genotypic frequencies of AB and CC were significantly higher than those of AA and CD. In the third parity, Matou dams with AB or CC genotypes had significantly larger litter sizes than those with AA and CD (p < 0.05). On combining the two loci, both Matou and Boer dams with ABCD genotype had the largest litter sizes when compared to the other genotypes (p < 0.05). When undergoing like superovulation treatments, a significantly higher number of corpora lutea and ova, with a lower incidence of ovarian cysts, were harvested in the AB and CC genotypes than in AA and CD. These results show that the two loci of GH gene are highly associated with abundant prolificacy and superovulation response in goat breeds

    Biology and Clinical Implications of the 19q13 Aggressive Prostate Cancer Susceptibility Locus

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    Genome-wide association studies (GWAS) have identified rs11672691 at 19q13 associated with aggressive prostate cancer (PCa). Here, we independently confirmed the finding in a cohort of 2,738 PCa patients and discovered the biological mechanism underlying this association. We found an association of the aggressive PCa-associated allele G of rs11672691 with elevated transcript levels of two biologically plausible candidate genes, PCAT19 and CEACAM21, implicated in PCa cell growth and tumor progression. Mechanistically, rs11672691 resides in an enhancer element and alters the binding site of HOXA2, a novel oncogenic transcription factor with prognostic potential in PCa. Remarkably, CRISPR/Cas9-mediated single-nucleotide editing showed the direct effect of rs11672691 on PCAT19 and CEACAM21 expression and PCa cellular aggressive phenotype. Clinical data demonstrated synergistic effects of rs11672691 genotype and PCAT19/CEACAM21 gene expression on PCa prognosis. These results provide a plausible mechanism for rs11672691 associated with aggressive PCa and thus lay the ground work for translating this finding to the clinic

    Radon Transform Based on Waveform for AVO-Preserving Data Construction

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    The traditional hyperbolic Radon transform suffers from the major problem of how to both obtain a high resolution and preserve the amplitude variation with offset (AVO). In the Radon domain, high resolution (sparseness) is a valid criterion. However, if a sparse model is obtained in the Radon domain due to averaging along the offset direction, then it is not possible to preserve the AVO in the inversion data. In addition, hyperbolic Radon transform has a time-variant kernel based on a traditional iterative algorithm, the conjugate gradient (CG), which requires significant computation time. To solve these problems, we propose a Radon transform based on waveform that contains both cycle and amplitude characteristics of seismic waves. The new transform entails creating an upper envelope for the seismic data and computing a preliminary forward Radon transform in the time domain. The forward Radon transform incorporates a priori information by measuring the energy of each slowness (p) trace to obtain the high-resolution result of the Radon domain. For AVO preserving, the proposed method uses polynomials to describe the AVO characteristics in the inverse Radon transform based on the least-squares inversion. Besides amplitude preserving and high resolution, the proposed method avoids using CG and greatly reduces the cost of computing hyperbolic Radon transform in the time domain. In applications to both synthetic and field data, waveform Radon transform (WRT) has a better performance than the conjugate gradient Radon transform (CGRT)

    Improving Remote Sensing Image Super-Resolution Mapping Based on the Spatial Attraction Model by Utilizing the Pansharpening Technique

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    The spatial distribution information of remote sensing images can be derived by the super-resolution mapping (SRM) technique. Super-resolution mapping, based on the spatial attraction model (SRMSAM), has been an important SRM method, due to its simplicity and explicit physical meanings. However, the resolution of the original remote sensing image is coarse, and the existing SRMSAM cannot take full advantage of the spatial&ndash;spectral information from the original image. To utilize more spatial&ndash;spectral information, improving remote sensing image super-resolution mapping based on the spatial attraction model by utilizing the pansharpening technique (SRMSAM-PAN) is proposed. In SRMSAM-PAN, a novel processing path, named the pansharpening path, is added to the existing SRMSAM. The original coarse remote sensing image is first fused with the high-resolution panchromatic image from the same area by the pansharpening technique in the novel pansharpening path, and the improved image is unmixed to obtain the novel fine-fraction images. The novel fine-fraction images from the pansharpening path and the existing fine-fraction images from the existing path are then integrated to produce finer-fraction images with more spatial&ndash;spectral information. Finally, the values predicted from the finer-fraction images are utilized to allocate class labels to all subpixels, to achieve the final mapping result. Experimental results show that the proposed SRMSAM-PAN can obtain a higher mapping accuracy than the existing SRMSAM methods

    Subpixel Mapping Based on Hopfield Neural Network With More Prior Information

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    Multisource Seismic Full Waveform Inversion of Metal Ore Bodies

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    The seismic exploration method could explore deep metal ore bodies (depth > 1000 m). However, it is difficult to describe the geometry of the complex metal ore body accurately. Seismic full waveform inversion is a relatively new method to achieve accurate imaging of subsurface structures, but its success requires better initial models and low-frequency data. The seismic data acquired in the metal mine area is usually difficult to meet the requirements of full waveform inversion. The passive seismic data usually contains good low frequency information. In this paper, we use both passive and active seismic datasets to improve the full waveform inversion results in the metal mining area. The results show that the multisource seismic full waveform inversion could obtain a suitable result for high-resolution seismic imaging of metal ore bodies

    Multisource Seismic Full Waveform Inversion of Metal Ore Bodies

    No full text
    The seismic exploration method could explore deep metal ore bodies (depth &gt; 1000 m). However, it is difficult to describe the geometry of the complex metal ore body accurately. Seismic full waveform inversion is a relatively new method to achieve accurate imaging of subsurface structures, but its success requires better initial models and low-frequency data. The seismic data acquired in the metal mine area is usually difficult to meet the requirements of full waveform inversion. The passive seismic data usually contains good low frequency information. In this paper, we use both passive and active seismic datasets to improve the full waveform inversion results in the metal mining area. The results show that the multisource seismic full waveform inversion could obtain a suitable result for high-resolution seismic imaging of metal ore bodies

    A Low RCS and Array-Insensitive FSS Wideband Radome

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    In order to further expand the RCS reduction model of the miniature broadband antenna, a four-notch shaped FSS radome insensitive to the number of array elements is designed based on the multi-layered medium Green’s function and the transflective coefficient of the finite radome is derived. The calculated results are in good agreement with the infinite array, showing broadband transmission performance in both C-band and X-band. The electric field distribution and far-field distribution of a finite FSS array are given and the effects of a 5 × 5 array in a V-shaped structure on the surface of a miniature broadband antenna on its gain coefficient and RCS reduction characteristics are calculated numerically. The results show that the designed radome exhibits good array element insensitivity and far-field scattering reduction characteristics and achieves significant in-band and out-of-band RCS accurate reduction under the premise of constant antenna radiation performance. At normal incidence, the single-station RCS in the passband and stopband are as low as −35 dB and −32.66 dB, respectively. The maximum reduction in the transmission band reaches 20.96 dB under oblique incidence and the projection size of the radome decreases with the increase in the bottom angle of the radome but the RSC reduction performance is basically unaffected and can be adjusted flexibly according to actual needs. The above results provide a theoretical basis and technical support for the application of FSS radome in RCS reduction in micro wideband antennas
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