Recombinant HEV Non-structural polyprotein (genotype 2)

By considering converter fundamental operating principles, the paper first derives a complete set of analytic expressions of the overall power losses of a conventional Dual Active Bridge (DAB) bidirectional DC-DC converter under Dual Phase Shift (DPS) control. Expressions for conduction and switching losses in the electronic devices acting as the converter switches, and copper and core losses in the isolation transformer, are derived and accounted for in the DC-DC converter model. DPS control involves many more converter operating conditions, in comparison to the more common single-phase-shift (SPS) control, which makes the analytic power loss characterization of a DPS-controlled converter an arduous task. Subsequently and by employing the derived analytic converter power loss model with exemplary parameter values, the paper analyzes the efficiency of a high-fidelity full hybrid electric vehicle (HEV) model that includes a DAB DC-DC converter, under a wide range of realistic driving conditions and converter operation, including low- to high-speed driving, and converter DPS operation. Two popular hybrid powertrain energy management schemes, the Thermostat and Power Follower control strategies, are used to simulate the vehicle model to reinforce the range of realistic vehicle operating conditions. The results show that in series HEV applications more accurate modeling of DC-DC converter models than conventional constant efficiency models is required to predict converter losses, and also the fidelity in the characterization of converter losses can have a significant impact on the vehicle fuel consumption prediction. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Simple Summary Domestic and wild pigs are the main Hepatitis E virus (HEV) zoonotic reservoirs. Identifying HEV-positive pig farms is important to implement surveillance programs for this emerging zoonotic agent. The aim of this study was to evaluate the use of serosanguineous fluids obtained as part of castration practice (processing fluids (PFs)) to detect anti-HEV antibodies. Ninety-five paired serum and PF samples were collected from newborn piglets of 29 different litters and tested with a commercial ELISA kit. A significant positive correlation (Spearman's rho: 0.600;p< 0.01) was found between the signal-to-cutoff (S/Co) ratio of anti-HEV antibodies in serum and PF samples. In 26 out of 29 litters (89.7%), there was at least one positive piglet in the serum. Sixteen litters out of 29 (55.2%) were also positive in PFs. The detection of anti-HEV maternal-derived antibodies in PFs confirms a past exposure of sows to the virus. PF may represent a rapid, noninvasive and economical tool to identify HEV-positive farms. Identifying Hepatitis E virus (HEV)-positive pig farms is important to implement surveillance programs for this emerging zoonotic agent. The aim of this study was to evaluate the use of serosanguineous fluids obtained as part of castration practice (processing fluids (PFs)) to detect anti-HEV antibodies in newborn piglets. Ninety-five paired serum and PF samples were collected from piglets of 29 different litters and tested with a commercial ELISA kit. A significant positive correlation (Spearman'srho: 0.600;p< 0.01) was found between anti-HEV antibodies in serum and PF samples. In 26 out of 29 litters (89.7%), there was at least one positive piglet in the serum. Sixteen litters out of 29 (55.2%) were also positive in PFs. To simulate the use of PF as pooled samples, the limit of detection of the ELISA was assessed mixing the PF sample with strong, medium, medium-weak and weak ELISA titres with 3, 4, 5 and 6 negative PF samples. Our results suggest that it is still possible to identify a positive PF pool when at least one individual PF sample with medium or strong antibody levels is mixed with 5 or 6 individual negative PF samples. The detection of anti-HEV maternal-derived antibodies in PF confirms a past exposure of sows to the virus. PF may represent a rapid, noninvasive and economical tool to identify HEV-positive farms.