Glyceraldehyde-3-phosphate dehydrogenase (GAP-DH), derived from the outer-membrane protein (OMP) fraction, has been used as a potential candidate for vaccine development. The gene-encoding 37 kDa GAPDH outer membrane protein (OMP) from Edwardsiella ictaluri was amplified using polymerase chain reaction (PCR) and was cloned and expressed in Escherichia coli BL21 (DE3). Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), Western blotting, and nucleotide and amino acid sequencing were used to analyze the expressed antigenic protein and gene encoding this protein. Comparative DNA and protein sequence analysis of GAPDH from E. ictaluri GAPDHs from several Gram-negative bacterial species within the Enterobacteriaceae family revealed that the GAPDHs within this group are highly conserved and share a sequence similarity of 75 100% with E. ictaluri GDPDH. Rabbit antiserum raised against the E. ictaluri recombinant GAPDH (rGAPDH) protein recognized purified GADPH, indicating that it has a strong immunogenicity. Tilapia fish were intraperitoneally immunized with formalin-killed E. ictaluri whole cells, and rGAPDH (30 µg fish 1 ) from E. ictaluri, both of which were emulsified in ISA 763A adjuvant. At 3 months after immunization, fish were challenged with the E. tarda strain to assess vaccine efficacy; the relative percent survival (RPS) values were found to exceed 71.4%. The specific mean antibody titer log 2 level of groups vaccinated with rGAPDH at 3 months was significantly higher than that of non-vaccinated fish (control group). Therefore, this recombinant protein can be considered a multi-purpose candidate vaccine against several pathogenic bacteria.Key words: channel catfish; Edwardsiella ictaluri; enteric septicemia of catfish; glyceraldehyde-3-phosphate dehydrogenase (GAPDH) IntroductionEnteric septicemia of catfish (ESC), caused by the bacterial pathogen Edwardsiella ictaluri, was first identified in channel catfish (Ictalurus punctatus) by Hawke (1979). E. ictaluri has become the most lethal infectious disease of channel catfish and other ictalurids in the USA (Plumb, 1999). More than 50% of American catfish fry/fingerling losses are due to ESC (Williams and Lawrence, 2010). E. ictaluri was also isolated from cultured fish species in Indonesia, Vietnam, Japan, Turkey (Crumlish et al., 2002;Keskün et al., 2004;Nagai et al., 2008; Yuas et al., 2003) and China (Ye et al., 2009). ESC is currently controlled using antibiotics; however, extensive use of antimicrobial com pounds reduces their effectiveness by increasing the number of antibiotic-resistant bacterial strains, resulting in the need for higher dosages for effective treatment as well as higher residual amounts of drugs in the harvested fish Thompson and Adams, 2004). Vaccines that protect fish against bacterial diseases are an important alternative to antibiotics and are a safer strategy for disease prevention. Most vaccines for controlling ESC have been tested using Full Paper Vaccine efficacy of glyceraldehyde-3-phosphate dehydrogenase (G...

In this study, the optimal tracking control problem for the quadrotor which is a highly coupling system with completely unknown dynamics is addressed based on data by introducing the reinforcement learning (RL) technique. The proposed Off-policy RL algorithm does not need any knowledge of quadrotor model. By collecting data, which is the states of quadrotor system then using an actor-critic networks (NNs) to solve the optimal tracking trajectory problem. Finally, simulation results are provided to illustrate the effectiveness of proposed method.

Precise control is critical for robots, but it is difficult to obtain an accurate dynamic model of the robot due to the presence of modeling errors and uncertainties in the complex working environment, resulting in decreased control performances. The article proposes a method for designing a digital controller for output tracking of disturbed repetitive robot manipulators that does not require a mathematical model of the controlled robots, with the goal of improving tracking accuracy. This controller consists of two separate intelligent parts. The first part aims to stabilize the original robot manipulators via a model-free state feedback linearization technique. The suggested model-free state feedback linearization technique does not make use of the original Euler-Lagrange model of the robot. The second part will then employ the concept of iterative learning control to asymptotically drive the obtained stable linear system to desired references. Both of these parts use only the robot’s measured data from the past for carrying out their tasks instead of robot models. Moreover, the proposed controller is structurally simple and computationally efficient. Finally, to validate the theoretical results, a simulation verification on a 2-degree-of-freedom (DOF) uncertain planar robot is performed, and the results show that excellent tracking performance is feasible.

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