The pinewood nematode (PWN) Bursaphelenchus xylophilus, vectored primarily by the sawyer beetle, Monochamus alternatus, is an important invasive pest and causal agent of pine wilt disease of Chinese Masson pine, Pinus massoniana. Previous work demonstrated that the ratios and concentrations of α-pinene∶β-pinene differed between healthy trees and those trees containing blue-stain fungus (and M. alternatus pupae). However, the potential influence of the altered monoterpene ratios and concentrations on PWN and associated fungi remained unknown. Our current results show that low concentrations of the monoterpenes within petri dishes reduced PWN propagation, whereas the highest concentration of the monoterpenes increased PWN propagation. The propagation rate of PWN treated with the monoterpene ratio representative of blue-stain infected pine (α-pinene∶β-pinene = 1∶0.8, 137.6 mg/ml) was significantly higher than that (α-pinene∶β-pinene = 1∶0.1, 137.6 mg/ml) representative of healthy pines or those damaged by M. alternatus feeding, but without blue stain. Furthermore, inhibition of mycelial growth of associated fungi increased with the concentration of the monoterpenes α-pinene and β-pinene. Additionally, higher levels of β-pinene (α-pinene∶β-pinene = 1∶0.8) resulted in greater inhibition of the growth of the associated fungi Sporothrix sp.2 and Ophiostoma ips strains, but had no significant effects on the growth of Sporothrix sp.1, which is the best food resource for PWN. These results suggest that host monoterpenes generally reduce the reproduction of PWN. However, PWN utilizes high monoterpene concentrations and native blue-stain fungus Sporothrix sp.1 to improve its own propagation and overcome host resistance, which may provide clues to understanding the ecological mechanisms of PWN's successful invasion.

Nowadays, social network-based collaborative filtering (CF) methods are widely applied to recommend suitable products to consumers by combining trust relationships and similarities in the preference ratings among past users. However, these types of methods are rarely used for recommending manufacturing services. Hence, this study has developed a hybrid social network-based CF method for recommending personalized manufacturing services. The trustworthy enterprises and three types of similar enterprises with different features were considered as the four influential components for calculating predicted ratings of candidate services. The stochastic approach for link structure analysis (SALSA) was adopted to select top K trustworthy enterprises while also considering their reputation propagation on enterprise social network. The predicted ratings of candidate services were computed by using an extended user-based CF method where the particle swarm optimization (PSO) algorithm was leveraged to optimize the weights of the four components, thus making service recommendation more objective. Finally, an evaluation experiment illustrated that the proposed method is more accurate than the traditional user-based CF method.

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Plants would release herbivore-induced plant volatiles (HIPVs) to repel herbivores and attract natural enemies after being damaged by herbivores. In this study, after cotton plants were damaged by different densities of Apolygus lucorum, the behavioral responses of A. lucorum and Peristenus spretus to cotton plants volatiles were evaluated, and the quality and quantity of volatiles from cotton plants were analyzed. Only when cotton plants were damaged by four bugs did both A. lucorum and P. spretus show an obvious response to damaged cotton plants, which indicates that cotton defense is correlated with pest density. The collection and analysis of volatiles reveals that the increase in pest density results in the emission of new compounds and an increase in the total number of volatiles with an alteration in proportions among the compounds in the blend. These changes in volatile profiles might provide wasps and mirids with specific information on host habitat quality and thus could explain the behavioral responses of parasitoids and pests.