The hypoxic environment imposes severe selective pressure on species living at high altitude. To understand the genetic bases of adaptation to high altitude in dogs, we performed whole-genome sequencing of 60 dogs including five breeds living at continuous altitudes along the Tibetan Plateau from 800 to 5100 m as well as one European breed. More than 1503 sequencing coverage for each breed provides us with a comprehensive assessment of the genetic polymorphisms of the dogs, including Tibetan Mastiffs. Comparison of the breeds from different altitudes reveals strong signals of population differentiation at the locus of hypoxia-related genes including endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1) and beta hemoglobin cluster. Notably, four novel nonsynonymous mutations specific to high-altitude dogs are identified at EPAS1, one of which occurred at a quite conserved site in the PAS domain. The association testing between EPAS1 genotypes and blood-related phenotypes on additional high-altitude dogs reveals that the homozygous mutation is associated with decreased blood flow resistance, which may help to improve hemorheologic fitness. Interestingly, EPAS1 was also identified as a selective target in Tibetan highlanders, though no amino acid changes were found. Thus, our results not only indicate parallel evolution of humans and dogs in adaptation to high-altitude hypoxia, but also provide a new opportunity to study the role of EPAS1 in the adaptive processes.
This study proposes a method to detect and quantify broken rotor bar fault using zero-sequence voltage in a wye-connected squirrel-cage induction motor. The zero-sequence voltage is analysed and two fault severity factors are defined. The factors are almost independent of motor speed and load torque. Furthermore, it is proved that closed-loop control has little influence on the diagnosis results. Consequently, the method can detect broken rotor bar fault for induction motors in both open-and closed-loop drives. Moreover, the method can discriminate the broken bar fault from a low-frequency load oscillation, even when these two phenomena occur simultaneously. In addition, the influence of unbalanced voltage supply on the diagnosis results is negligible. The effectiveness and robustness of the proposed method have been validated by experimental results.
Abstract. In this paper, we investigate the constrained minimization problem e(a) := infwhere the energy functionalwith m ∈ R, a > 0, is defined on a Sobolev space H. We show that there exists a threshold a * > 0 so that e(a) is achieved if 0 < a < a * , and has no minimizers if a ≥ a * . We also investigate the asymptotic behavior of nonnegative minimizers of e(a) as a → a * .
Performance degradation forecast technology for quantitatively assessing degradation states of aeroengine using exhaust gas temperature is an important technology in the aeroengine health management. In this paper, a GM (1, 1) Markov chain-based approach is introduced to forecast exhaust gas temperature by taking the advantages of GM (1, 1) model in time series and the advantages of Markov chain model in dealing with highly nonlinear and stochastic data caused by uncertain factors. In this approach, firstly, the GM (1, 1) model is used to forecast the trend by using limited data samples. Then, Markov chain model is integrated into GM (1, 1) model in order to enhance the forecast performance, which can solve the influence of random fluctuation data on forecasting accuracy and achieving an accurate estimate of the nonlinear forecast. As an example, the historical monitoring data of exhaust gas temperature from CFM56 aeroengine of China Southern is used to verify the forecast performance of the GM (1, 1) Markov chain model. The results show that the GM (1, 1) Markov chain model is able to forecast exhaust gas temperature accurately, which can effectively reflect the random fluctuation characteristics of exhaust gas temperature changes over time.
Background. Spatial characteristics of sEMG signals are obtained by high-density matrix sEMG electrodes for further complex upper arm movement classification. Multiple electrode channels of the high-density sEMG acquisition device aggravate the burden of the microprocessor and deteriorate control system’s real-time performance at the same time. A shoulder motion recognition optimization method based on the maximizing mutual information from multiclass CSP selected spatial feature channels and wavelet packet features extraction is proposed in this study. Results. The relationship between the number of channels and recognition rate is obtained by the recognition optimization method. The original 64 electrodes channels are reduced to only 4-5 active signal channels with the accuracy over 92%. Conclusion. The shoulder motion recognition optimization method is combined with the spatial-domain and time-frequency-domain features. In addition, the spatial feature channel selection is independent of feature extraction and classification algorithm. Therefore, it is more convenient to use less channels to achieve the desired classification accuracy.
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