The seasonal migration of wild aquatic birds plays a critical role in the maintenance, transmission, and incursion of the avian influenza virus (AIV). AIV surveillance was performed during 2020–2021 in two national nature reserves with abundant wild bird resources in Yunnan, China. Four H5N8 AIVs isolates from the common crane were identified by next-generation sequencing. Phylogenetic analysis demonstrated that all eight gene segments of these H5N8 AIVs belonged to clade 2.3.4.4b high-pathogenic AIV (HPAIV) and shared high nucleotide sequence similarity with the strains isolated in Hubei, China, and Siberia, Russia, in 2020–2021. The H5N8 HPAIVs from common cranes were characterized by both human and avian dual-receptor specificity in the hemagglutinin (HA) protein. Moreover, possessing the substitutions contributes to overcoming transmission barriers of mammalian hosts in polymerase basic 2 (PB2), polymerase basic protein 1 (PB1), and polymerase acid (PA), and exhibiting the long stalk in the neck region of the neuraminidase (NA) protein contributes to adaptation in wild birds. Monitoring AIVs in migratory birds, at stopover sites and in their primary habitats, i.e., breeding or wintering grounds, could provide insight into potential zoonosis caused by AIVs.
With the continuous advancement of smart grid and the rapid development of computer and information technology, massive amounts of redundant and noisy information are connected to the power grid. Therefore, this paper proposes a key stable feature selection method based on improved ant colony algorithm. First, use the artificial intelligence model to solve the optimal number of key features. Then use Filter based on the minimum redundancy-maximal relevance (mRMR) algorithm and Wrapper based on the improved ant colony algorithm to select the optimal key feature subset in two stages. Finally, example analysis with IEEE39 nodes system is used to verify the availability and effectiveness of the selection method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.