Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.
Carbonaceous materials are considered to be effective materials for selective catalytic reduction (SCR) of NO, especially at room temperature. Carbonaceous materials can not only be used for adsorption applications due to their porosity properties but also can act as supports or reactants, which are globally available. This paper reviews the current state removal of NO by carbonaceous materials. Moreover, the characteristics of carbonaceous materials, mechanisms and kinetics of removal of NO by carbonaceous materials are also discussed. It is observed that carbonaceous material supported metal oxides can remove NO effectively at low temperature. Currently, removal of NO by carbonaceous materials at room temperature has been developed in the lab, but it is still in the research and development stage. In the future, three aspects of the work should be further studied, which is to extend the catalyst life, enhance the catalytic properties and reduce the cost of catalyst preparation. All the tasks are necessary for the practical application of NO removal technology at room temperature.
This paper presents a triangulation-based hierarchical image matching method for wide-baseline images. The method includes the following three steps: (a) image orientation by incorporating the SIFT algorithm with the RANSAC approach, (b) feature matching based on the self-adaptive triangle constraint, which includes point-to-point matching and subsequent point-to-area matching, and (c) triangulation constrained dense matching based on the previous matched results. Two new constraints, the triangulation-based disparity constraint and triangulation-based gradient orientation constraint, are developed to alleviate the matching ambiguity for wide-baseline images. A triangulation based affine-adaptive cross-correlation is developed to help find correct matches even in the image regions with large perspective distortions. Experiments using Mars ground wide-baseline images and terrestrial wide-baseline images revealed that the proposed method is capable of generating reliable and dense matching results for terrain mapping and surface reconstruction from the wide-baseline images.
Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculation cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.
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