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Objective To investigate the key genes associated with ferroptosis in peri-implantitis and explore the potential mechanisms regulating peri-implantitis. Methods Several datasets were obtained from the GEO database. Differential expressed genes were screened, and GO and KEGG analyses were performed. A PPI network was constructed using the STRING website. Key genes were validated using a test set, and the diagnostic value of key genes was determined. The content and proportion of 22 immune cells in peri-implantitis tissues were obtained through immune infiltration analysis. Key genes were validated by qRT-PCR and Western Blot(WB). Results There were 1 138 differential genes between peri-implantitis tissues and normal gingival tissues, of which 29 were related to ferroptosis. The gene expression in peri-implantitis tissues mainly involved processes such as immune response activation. Five key genes in the ferroptosis-related differential genes, namely SOX2, GJA1, IL1B, GPX2 and CHAC1, were differentially expressed in peri-implantitis tissues and had high diagnostic value. Immune infiltration analysis showed significant changes in immune cells such as memory B cells and plasma cells in peri-implantitis tissues. qRT-PCR and WB confirmed significant differential expression of mRNA and the protein transcribed by key genes. Conclusion Differential genes between peri-implantitis and ferroptosis are screened using bioinformatics analysis and biological validation, providing new insights into the study on peri-implantitis.

Based on the problem that considerable ballistic error and inaccurate target coverage of terminal-sensitive projectiles while fighting without weather conditions causing the reduction of combat effectiveness and/or even can’t complete combat tasks, this work elaborated two commonly used solutions and methods. According to the real working experience of the test range, a new proposal of using the meteorological forecast data to calculate the ballistic elements of the terminal-sensitive projectile was studied. Furthermore, the deviation between the ballistic landing point and the test landing point under various environmental factors such as standard meteorological conditions, meteorological forecast data and actual meteorological data was analyzed using numerous testing data and ballistic simulation results, which indicates the accuracy and reliability of meteorological forecast data in the terminal sensitive projectiles range and side deflection prediction. In summary, this study proves a theoretical reference for improving the combat effectiveness of terminal-sensitive projectiles under real combat environments, and also provides convenience for the development of terminal-sensitive projectile tests.

Aiming at the aerodynamic and trajectory design problem of gliding guided projectiles, this paper stu-died a comprehensive optimization method of aerodynamic and trajectory so as to improve the gliding performance of projectile. This optimization method used engineering algorithms for aerodynamic analysis and adaptive Radau pseudo-spectral method for trajectory analysis, and the static parameter optimization of aerodynamic shape and the dynamic optimization of angle of attack control law during the gliding process can be considered comprehensively. The mapping relationship between shape parameters and performance indicators (such as range and flight time) was established by using Kriging model, which realized the tight coupling of shape optimization and trajectory optimization. At the same time, the Kriging model was constantly updated by using the combined infill sampling criterion until convergence to obtain the optimal shape and optimal trajectory. This paper took the maximum range and shortest flight time/minimum consumption of control energy as the objective functions to comprehensively optimize the shape parameters of canard and tail of the gliding guided projectile. The simulation results show that the comprehensive optimization scheme has better trajectory performance when compared with the reference scheme. The Opt-1 scheme increases the range by 37.8%, the Opt-2 scheme can effectively reduce the flight time and reduce control energy consumption by 46% when attacking fixed targets, which verifies the feasibility and effectiveness of this comprehensive optimization method of aero-dynamic and trajectory.

With the emergence of vehicular edge computing (VEC) and electric vehicles (EVs), integrating computation and charging tasks presents challenges due to limited resources and dynamic vehicular networks. This research focuses on the joint optimization of computation offloading and charging scheduling in VEC networks. Specifically, we optimize the offloading factor, charging association variable, and charging rates to minimize the system delay and energy consumption by leveraging the multi-attributes of EVs in both information and energy networks. Considering the dynamic environment, we model the problem as a Markov Decision Process, and use the Multi-Agent Reinforcement Learning (MARL) algorithm MADDPG, with its centralized training and distributed execution mechanisms. Simulation results demonstrate that this approach significantly improves utility while reducing energy consumption and latency. [ABSTRACT FROM AUTHOR]