Search

This trial was conducted to investigate the effect of mannose oligosaccharides (MOS) on the growth performance, antioxidation, immunity and disease resistance of Vibro Parahemolyticus in juvenile abalone Haliotis discus hannai Ino. Four formulated diets were produced to contain 0.00 g/kg, 0.40 g/kg, 0.80 g/kg and 1.60 g/kg Actigen®, with functional ingredients of MOS, respectively. Accordingly, the experimental diets were named as A0, A4, A8 and A16. After 120-days feeding trial, the best growth performance was observed in A8 group (P 0.05) and there was no significant difference in A0, A4 and A16 groups. With the increase of dietary MOS, the activity of the total antioxidant capacity in hepatopancreas is increasingly elevated (P 0.05) while no significant difference was observed on activity of glutathione S-transferase (P 0.05). The activities of superoxide dismutase and glutathione peroxidase were firstly increased and then decreased, with the highest values in A8 group (P 0.05). Immune-related parameters were significantly affected by dietary MOS inclusion. Specifically, the activities of alkaline phosphatase and acid phosphatase in hepatopancreas and serum of abalone fed diets containing MOS were significantly higher than those of control A0 group (P 0.05). Moreover, the highest values of both enzymes were observed in hepatopancreas of A8 group but in serum of A16 group, respectively. The lysozyme activities in hepatopancreas and serum of A4 group were significantly higher than those of other groups (P 0.05) and there was no significant difference in A0, A8 and A16 groups (P 0.05). The activities of cytophagy and respiratory burst in serum of abalone were not significantly affected by dietary MOS content (P 0.05). The mRNA levels of focal adhesion kinase and integrin-linked kinase were gradually elevated with the increase of dietary MOS, with the highest value recorded in A16 group (P 0.05). The gene expression of caspse-3 in A8 group was dramatically higher than those of other groups (P 0.05) and there was no significant difference in A0, A4 and A16 groups (P 0.05). The mRNA level of nuclear factor-κB was not significantly affected by dietary MOS (P 0.05). During 56 h of V. Parahemolyticus challenge period, the accumulated mortality rate of abalone fed diets containing MOS were significantly lower than that of control A0 group in each time point (P 0.05). Overall, the lowest rate was happened in A8 group (P 0.05). In conclusion, MOS inclusion in diet has obviously positive effect on growth, immunity and disease resistance capability of abalone, with the optimal level of Actigen® at 0.80 g/kg in diet.

In the present study, a sialic acid-binding lectin was identified and characterized from Manila clam Ruditapes philippinarum (designed as RpSABL-1). Multiple alignments strongly suggested that RpSABL-1 was a new member of the sialic acid-binding lectin family. In non-stimulated clams, RpSABL-1 transcripts were constitutively expressed in all five tested tissues, especially in hepatopancreas. After Vibrio anguillarum challenge, the expression of RpSABL-1 mRNA was significantly up-regulated at 6 h (P

Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power prediction interval model, combining rough set (RS) theory and particle swarm optimization (PSO), is proposed to further improve wind power prediction performance. First, in the designed prediction interval model, the input variables are identified based on attribute significance using rough set theory. Next, the Naive Bayesian Classifier (NBC) is established to obtain the prediction power class. Finally, the upper and lower output weights of NBC are optimized segmentally by PSO, and are used to calculate the upper and lower bounds of the optimal prediction intervals. The superiority of the proposed approach is demonstrated by comparison with a Naive Bayesian model with fixed output weight, and a rough set-Naive Bayesian model with fixed output weight. It is shown that the proposed rough set-Naive Bayesian-particle swarm optimization method has higher coverage of the probabilistic prediction intervals and a narrower average bandwidth under different confidence levels.

An on-line fuzzy neural network control (FNNC) with decoupling unit is applied for ball mill system of blast furnace. The structure of FNNC is composed of premise and consequence part. Premise parameters reduce fuzzy rules to solve the combination explosion of multi-inputs. Consequence parameters achieve a good transient response. An adaptive step size equation created by a Lyapunov function guarantees convergence of algorithm. Neural network decoupler based on timedomain response curve is used to counter the interaction among channels. Simulation results prove effectiveness of proposed control system.