In 2010, new Chinese strains of porcine epidemic diarrhea virus (PEDV), clinically more severe than the classical strains, emerged. These strains were spread to United States in 2013 through an intercontinental transmission from China with further spreading across the world, evidencing the emergent nature of these strains. In the present study, an analysis of PEDV field sequences from Ecuador was conducted by comparing all the PEDV S gene sequences available in the GenBank database. Phylogenetic comparisons and Bayesian phylogeographic inference based on complete S gene sequences were also conducted to track the origin and putative route of PEDV. The sequence from the PED-outbreak in Ecuador was grouped into the clade II of PEDV genogroup 2a together with other sequences of isolates from Mexico, Canada, and United States. The phylogeographic study revealed the emergence of the Chinese PEDV strains, followed by spreading to US in 2013, from US to Korea, and later the introduction of PEDV to Canada, Mexico, and Ecuador directly from the US. The sources of imports of live swine in Ecuador in 2014 were mainly from Chile and US. Thus, this movement of pigs is suggested as the main way for introducing PEDV to Ecuador.

Abstract:The importance of early fault detection in electric motors has attracted the attention of research groups, as the detection of incipient faults can prevent damage spreading and increase the lifetime of the motor. At present, studies have focused their attention on optimization procedures used for fault detection in induction machines to achieve a quick and easy-to-interpret assessment at an industrial level. This paper proposes an alternative approach based on the Continuous Wavelet Transform (CWT) for broken bar diagnosis in squirrel cage induction motors. This work uses the Motor Current Signature Analysis (MCSA) method to acquire the current signal of the induction motor. The novelty of this study lies in broken bar detection in electric machines operating at non-load by analyzing variations in the spectrum of the motor's current signal. This way, the faults are presented as oscillations in the current signal spectrum. Additionally, a quantification of broken bars for the same type of motors operating at full-load is performed in this study. An experimental validation and the comparison with the Fast Fourier Transform (FFT) technique are provided to validate the proposed technique.