Liaoning Shihua University

The arithmetic optimization algorithm (AOA) is a recently proposed swarm intelligence optimizer with a simple structure and few control parameters. However, the original AOA relies on a single update mechanism, which often leads to premature convergence and limited adaptability in complex optimization problems. To address these limitations, this paper proposes a multi-strategy improved arithmetic optimization algorithm (IAOA). The proposed algorithm constructs a heterogeneous strategy pool composed of six search strategies, including arithmetic update, differential evolution operators, competitive elite learning, interpolation-based acceleration, and curriculum education learning. Furthermore, an adaptive strategy regulation mechanism based on fitness improvement contribution is introduced to dynamically adjust the selection probability of each strategy. Extensive experiments conducted on the CEC2017 and CEC2022 benchmark suites demonstrate that IAOA achieves a superior optimization accuracy, convergence speed, and stability compared with several classical algorithms, recent metaheuristics, and AOA variants. Statistical tests including the Wilcoxon rank-sum test and Friedman mean rank test confirm the significance of the performance improvements. In addition, the algorithm is successfully applied to a three-dimensional path planning problem for amphibious unmanned aerial vehicles, demonstrating its effectiveness in solving complex engineering optimization problems.

Influenza A virus continues to pose a significant global health threat, causing seasonal epidemics and occasional pandemics. Viral transcription and replication rely on the heterotrimeric polymerase complex where the PB2 subunit initiates RNA synthesis through binding to the host mRNA cap structure. In this study, we began with a structure-activity relationship analysis of the pioneering PB2 inhibitor VX-787. Through computer-aided drug design, combined with considerations of molecular docking scores, ADMET property predictions, and a prodrug esterification strategy, we ultimately designed eight novel compounds. Cytopathic effect assays demonstrated that all compounds exhibited superior inhibitory activity against both H1N1 and H3N2 strains compared to oseltamivir acid. In particular, compounds 11 and 15 displayed nanomolar-level activity against H1N1, while compound 18 showed activity against H3N2 superior to that of VX-787. These findings propose a rational design strategy that may offer new avenues for addressing the resistance and metabolic limitations associated with VX-787 and hold potential for advancing the development of next-generation PB2-targeted anti-influenza therapeutics.