Search

Porcine viral diarrhea diseases affect the swine industry, resulting in significant economic losses. Porcine epidemic diarrhea virus (PEDV) genotypes G1 and G2, and groups A and C of the porcine rotavirus, are major etiological agents of severe gastroenteritis and profuse diarrhea, particularly among piglets, with mortality rates of up to 100%. Based on the high prevalence rate and frequent co-infection of PEDV, RVA, and RVC, close monitoring is necessary to avoid greater economic losses. We have developed a multiplex TaqMan probe-based real-time PCR for the rapid simultaneous detection and differentiation of PEDV subtypes G1 and G2, RVA, and RVC. This test is highly sensitive, as the detection limits were 20 and 100 copies/μL for the G1 and G2 subtypes of PEDV, respectively, and 50 copies/μL for RVA and RVC, respectively. Eighty-eight swine clinical samples were used to evaluate this new test. The results were 100% in concordance with the standard methods. Since reassortment between porcine and human rotaviruses has been reported, this multiplex test not only provides a basis for the management of swine diarrheal viruses, but also has the potential to impact public health as well.

The characterization of material anisotropic properties at high strain rates remains a challenging work due to the limitations of the conventional dynamic testing methods. In this study, a novel inverse identification strategy is proposed based on the dynamic virtual fields method (VFM) to enable a simultaneous identification of the anisotropic constitutive parameters from a single high speed impact test of a non-uniform specimen. This is implemented by taking advantage of the heterogeneous full-field strain and inertial acceleration data, in which the restrictions of one-dimensional stress wave propagation and homogeneous deformation states for the conventional methods are released. Specifically, the dynamic VFM-based identification algorithm is developed first. Then, several virtual impact tests with different specimen configurations are designed to provide distinct stress/strain distributions. Next, the simulated full-field strain and acceleration data are utilized to extract the input target orthotropic stiffness components. The results show that the identification accuracy of the anisotropic parameters is highly dependent on the heterogeneity of the stress/strain distributions. Also, the identification results are unstable for different time steps but can be significantly improved using a minimization algorithm on multiple time steps. Finally, the influences of noise, impact speed and loading mode are analyzed in the sensitivity study.