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Since traditional particle swarm optimization(PSO) is prone to premature phenomenon when solving complex functions in high-dimensional space, a particle swarm optimization algorithm with random variation and dynamic perception factors in terms of the movement laws and dispersion characteristics of particles in space is proposed. In order to encourage individual particles to explore their own neighborhoods and reduce the premature phenomenon of particles due to over-reliance on individual optimality and global optimality, a random mutation factor with a questioning strategy for neighborhoods is added to the basic algorithm to improve the speed update. At the same time, a perception factor is added to the particle position update, so that the particle can dynamically and adaptively control the spatial distance between itself and other particles in the same dimension, so as to avoid falling into local optimum. The algorithm has obvious superiority and robustness in solving complex functions in high-dimensional space through test function experiments, algorithm comparison analysis experiments, random parameter influence experiments and algorithm complexity experiments.

In order to balance the diversity and intensity of biogeography-based optimization (BBO) algorithm in the search process, the idea of symbiotic organisms search (SOS) is introduced, and the asymbiotic biogeography based optimization (SBBO) algorithm is proposed. Firstly, the initial population is optimized by symbiotic operation to reduce the randomness of the initial population. On this basis, in order to improve the ability to explore the diversity of solutions in the migration process and avoid premature convergence, dynamic selection migration operator and mutually beneficial migration operator are proposed, and the functions of the two migration operators in different iterations are balanced by cosine adaptive factor. Furthermore, a symbiotic mutation operator is proposed to improve the ability of the algorithm to maintain population diversity. Simulation results show that the proposed algorithm can coordinate local search and global search, and improve the accuracy and efficiency.

Aiming at the shortcomings of current air defense target threat assessment methods, a dynamic threat assessment method based on combination weighting and improved multi-attribute compromise solution decision (VIKOR) is proposed. Firstly, the AHP method is improved through grey correlation analysis and systematic clustering to obtain the subjective weight, the index correlation is introduced to improve the entropy weight method to determine the objective weight, and the final weight is obtained through subjective and objective combination. Then, an improved VIKOR threat assessment model based on regret theory is established. Finally, the optimization models of information entropy-time degree and coefficient of variation-time degree are constructed according to the time degree criterion, the time series weight is obtained through the idea of game theory, and the multi-time target information is integrated to obtain the final threat assessment result. The experimental simulation results show that the improved method obtains more scientific and reasonable index weights, and the threat assessment results can fully reflect the decision makers’ psychological preferences and dynamic changes of targets, which verifies the effectiveness of the method.

The military power represented by the US military continues to strengthen the development and application of air raid weapons, making it difficult for the ground air defense forces to deal with high-tech aviation formation penetration attack independently. The integration of information and firepower air defense operation can effectively broaden the confrontation dimension, improve the attack accuracy and increase the defense intensity. Based on the analysis of the penetration style and threat of aviation formation under the condition of informatization, this paper analyzes and studies the necessity of the integration of information and firepower against the penetration of aviation formation from the aspects of the mutual cooperation between information air defense and firepower air defense, information support and joint integration, and probes into the application of the integration of information and firepower against the penetration of aviation formation. Focusing on the actual combat, this paper puts forward some suggestions for the future development of the integration of information and firepower against the penetration of aviation formation.

Mosaic warfare is a new subversive military concept put forward by the US military, which is facing the future war, aiming at strategic opponents and relying on the cutting-edge technology. Once it forms actual combat capability, it will generate a series of nonlinear combat effects and form asymmetrical advantage over the major combat opponents. Based on the analysis of the background of mosaic warfare concept, the characteristic advantage of mosaic warfare are analyzed and condensed from the aspects of the improvement of force design efficiency, the optimization of command and control process, and the innovation of operation mode. The winning mechanism of mosaic warfare is analyzed in the aspects of multi-layer circular nesting of OODA, strong anti-attack ability, high reconstruction efficiency and intelligent fast destruction of the opponent’s OODA ring.

Yudong black goats (YDGs) are a local breed in southwest China that possess unique meat qualities and produce a high meat yield, making them ideal models for studying goat meat quality. Castration may decrease off-odors, significantly change metabolites and improve meat quality. Using multi-omics techniques, this study focused on Yudong black goat wethers (YDW, n = 4) and Yudong black bucks (YDB, n = 4). The findings revealed that 33 differentially expressed genes (DEGs) and 279 significantly changed metabolites (SCMs) influenced goat meat quality by affecting fat accumulation and lipolysis regulatory processes. Herein, several candidate genes (IGF1, TNNT2, PPP2R2C, MAPK10 and VNN1, etc.) were identified that play a role in regulating meat quality, non-castrated and castrated, alongside a series of metabolites that may serve as potential meat quality biomarkers. Lipids (triglycerides, oxidized lipids_5-iso PGF2VI, ceramide (t18:1/36:2(2OH)) and Carnitine C20:5, etc.) were significantly higher in the castrated goats. These results revealed that lipids and hydrophilic metabolites were affected by castration, which might be beneficial in terms of goat meat quality. This study aimed to investigate the differences in meat quality between uncastrated and castrated male goats and the possible molecular regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Image data play an important role in the network information, however, some images containing sensitive or confidential information are easy to attract the attention of malicious attackers. On the basis of deep learning and data hiding technology, in this article, a novel hiding–revealing network is designed to protect these secret images. The sender uses the hiding network to conceal the secret image into an ordinary cover image and the receiver uses the revealing network to recover the secret image. Symmetrical shortcut connection is designed to improve both the hiding and the revealing performances without adding any parameters. Consider that some secret images may have complex spatial features, a multilevel strong auxiliary module is designed to enhance feature representation and boost the restoration quality of the secret image. Then, a lifeline is proposed to transform the image hiding task into a residual identity mapping, which reduces the difficulty of network learning and obviously improves the hiding performance. In addition, a mixed loss function is designed to further improve the perceptual quality of both the hidden image and the revealed image, which further completely eliminates the secret content in the residual image and ensures the hiding security. Experimental results demonstrate that compared with the state-of-the-art methods, our proposed method achieves the best performance in both hidden image synthesis and secret image restoration. [ABSTRACT FROM AUTHOR]