Genomic structure and evolution of the Pi2/9 locus in wild rice species.

Rice blast, caused by the fungal pathogen Magnaporthe oryzae, is a devastating disease of rice worldwide. Among the 85 mapped resistance (R) genes against blast, 13 have been cloned and characterized. However, how these genes originated and how they evolved in the Oryza genus remains unclear. We previously cloned the rice blast R-genes Pi2, Pi9, and Piz-t, and analyzed their genomic structure and evolution in cultivated rice. In this study, we determined the genomic sequences of the Pi2/9 locus in four wild Oryza species representing three genomes (AA, BB and CC). The number of Pi2/9 family members in the four wild species ranges from two copies to 12 copies. Although these genes are conserved in structure and categorized into the same subfamily, sequence duplications and subsequent inversions or uneven crossing overs were observed, suggesting that the locus in different wild species has undergone dynamic changes. Positive selection was found in the leucine-rich repeat region of most members, especially in the largest clade where Pi9 is included. We also provide evidence that the Pi9 gene is more related to its homologues in the recurrent line and other rice cultivars than to those in its alleged donor species O. minuta, indicating a possible origin of the Pi9 gene from O. sativa. Comparative sequence analysis between the four wild Oryza species and the previously established reference sequences in cultivated rice species at the Pi2/9 locus has provided extensive and unique information on the genomic structure and evolution of a complex R-gene cluster in the Oryza genus.

Signal extraction using ensemble empirical mode decomposition and sparsity in pipeline magnetic flux leakage nondestructive evaluation.

The commonly used and cost effective corrosion inspection tools for the evaluation of pipelines utilize the magnetic flux leakage (MFL) technique. The MFL signal is usually contaminated by various noise sources. In this paper, we propose that the pipeline flaw MFL signal is extracted using the ensemble empirical mode decomposition (EEMD) and the sparsity. At first, we introduce the EEMD method. The EEMD defines the true intrinsic mode function (IMF) components as the mean of an ensemble of trials, each consisting of the signal plus a white noise of finite amplitude. Moreover, sparsity selection restriction was defined. Then, The MFL signal is decomposed into several IMFs used for signal reconstruction. Some modes are selected to reconstruct a new signal considering their sparsity. Finally, the comparison is made with the empirical mode decomposition. At the same time, the comparison of the selection restriction between the sparsity and the energy is described. The results show that the EEMD and the sparsity is an efficient technology with the pipeline flaw extraction.