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EN
In this study, abnormal vibrations of 1 pump fluid in a crude oil efflux station in the Changqing Oilfield was investigated. Kinetic simulation was applied to flow fields in the crude oil efflux pump using Ansys to determine trends of the impeller static pressure, speed, total pressure, wall pressure of the impeller, outlet pressure and pressure on the pump shell and to identify the reasons behind the abnormal vibrations. The results indicated that the axial vibration amplitude of the pump could be reduced from 1.3mm down to 0.68mm if the operation parameters of the external control oil pump were set as 2500-2550r/min and 325-335m3/h, respectively.
EN
The analysis of protein coding regions of DNA sequences is one of the most fundamental applications in bioinformatics. A number of model-independent approaches have been developed for differentiating between the protein-coding and non-protein-coding regions of DNA. However, these methods are often based on univariate analysis algorithms, which leads to the loss of joint information among four nucleotides of DNA. In this article, we introduce a method on basis of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) and the modified Gabor-wavelet transform (MGWT). The NA-MEMD algorithm, as a multivariate analysis tool, is utilized to reconstruct the numerical analyzed sequence since it enables a matched-scale decomposition across all variables and eliminates the mode mixing. By virtues of NA-MEMD, the MGWT method achieves a stable improvement on the general identification performance. We compare our method with other Digital Signal Processing (DSP) methods on two representative DNA sequences and three benchmark datasets. The results reveal that our method can enhance the spectra of the analyzed sequences, and improve the robustness of MGWT to different DNA sequences, thus obtaining higher identification accuracies of protein coding regions over other applied methods. In addition, another comparative experiment with the model-dependent method (AUGUSTUS) on the recently proposed benchmark dataset G3PO verifies the superiority of model-independent methods (especially NA-MEMD-MGWT) for identifying coding regions of the poor-quality DNA sequences.
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