The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

In the current study, a total of 102 common Todarodes pacificus squid caught in the East Sea were investigated for parasitological research. The results revealed that 33 (32.35%) out of 102 squid were infected by Nybelinia surmenicola, the mean intensity was 5.58 parasites per squid, and the maximum abundance was 11. Morphological analysis using a field emission scanning electron microscope showed the characteristic features of N. surmenicola. Molecular identification based on the 28S rRNA gene confirmed the isolated parasite as N. surmenicola, while phylogenetic analysis revealed that N. surmenicola isolated in this study was clustered with N. surmenicola isolated from Japan. This is the first report of phylogenetic characterization of N. surmenicola isolated from Korea.

Autophagy is an important self-eating process to eliminate damaged or unused organelles. We identified nine autophagy-related genes (Atg) including AaAtg-1, -3, -4b, -4d, -5, -6, -8, -12 and -13 from the Asian tiger mosquito, Aedes albopictus. Developmental expression patterns indicate that mRNA levels of AaAtg-1, -3, -4b, -4d, -5, -6, -12 and -13 were highly expressed in egg, whereas expression of AaAtg8 was high in 1stand3rdinstarlarvalstages. TissuespecificexpressionofthesegenesindicatesthatAaAtg1 was highly expressed in thorax and midgut in blood-fed adult female mosquitoes (BF), and head and thorax in sugar fed adult female mosquitoes (SF). Transcript level of AaAtg3 was high in thorax in BF, but head, thorax and Malpighian tubules in SF. AaAtg4b, -4d mRNA levels were significantly high in Malpighian tubules in BF, and head in SF, respectively. AaAtg-5 and -6 transcripts were highly expressed in head in BF, and expression of AaAtg-8 was high in Malpighian tubules in BF. Levels of AaAtg-12 and -13 mRNAs were significantly high in head and midgut in BF. Induction patterns of AaAtg genes against pathogens showed that AaAtg-1, -3, -4b, -8, -12 and -13 were strongly induced at 6 h-post injection of S. aureus, and mRNA levels of AaAtg-1, -3 and -13 were significantly induced by E. coli challenge after 3 h-post injection in SF abdominal carcass. In SF midgut, AaAtg-1, -3, -4b, -4d, -5, -6, -12 and -13 transcripts were drastically induced at 9 h-injection of E. coli and S. aureus, while expression of AaAtg-8 was highly induced by S. aureus and C. albicans at 9 h-post injection. Each AaAtg gene was slightly induced by E. coli, S. aureus or C. albicans at different time points in abdominal carcass in BF. Interestingly, AaAtg-8 was not induced by microbial challenge. While eight other Atg genes except AaAtg-8 were highly influenced by S. aureus at 6 and 9 h-post injection, E. coli at 3 h-post-treatment, and 3, 6, and 9 h-post inoculation. In the future, we will characterize the functional roles of autophagy during mosquito-microbes interaction.