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In order to reduce the movement energy consumption of the hydraulic excavator and realize the reasonable and effective operation of each joint, a joint interpolation method based on a T-type velocity curve is proposed to realize the optimal energy consumption trajectory planning of the hydraulic excavator. In this method, the speed of each joint is set as uniform acceleration, constant velocity, and uniform deceleration to ensure the stability of the hydraulic excavator in the operation process. Under the constraint conditions of the joint angle, angular velocity, and angular acceleration, the improved adaptive genetic algorithm is used to optimize the uniform acceleration (deceleration) and constant velocity motion time of each joint, obtain the optimal motion curve of each joint, and realize the optimal energy consumption trajectory planning of the hydraulic excavator. The interpolation programming method based on the T-type velocity curve is simulated and compared with the interpolation results of the quartic polynomial under the same conditions. The experimental results show that the trajectory planned by this method has low energy consumption, avoids unnecessary movement of each joint, effectively reduces friction loss, and makes the excavator complete the operation smoothly and with low energy consumption.

Background: In research to improve the quality of transgenic crops, it is often necessary to introduce multiple functionally related genes into recipient plants simultaneously to improve crop genetic traits effectively. Compared with unidirectional promoters, bidirectional promoters simultaneously regulate the expression of multiple genes and improve the efficiency of biotechnology. Therefore, in this study, bidirectional gene pairs were systematically analyzed in Gossypium hirsutum TM-1, and the structure, function and evolutionary relationships of the bidirectional genes were analyzed. The endogenous bidirectional promoters of cotton were mined, and their specific regulatory elements and biological functions were explored to provide useful promoter resources and a theoretical basis for cultivating new cotton germplasms with excellent fiber quality. Results: Using an improved search model, a total of 1,383 bidirectional transcript pairs were identified in the Gossypium hirsutum TM-1 genome, and their gene structure and functional annotations were systematically analyzed. Thirty bidirectional intergenic sequences were randomly screened for promoter activity analysis via a transient expression system, and 25 intergenic sequences were found to have bidirectional promoter activity. Comparative analysis of the bidirectional gene profiles of the four cotton subspecies revealed that these subspecies presented abundant bidirectional gene pairs with high homology and that the bidirectional genes in the cotton subspecies were more similar in terms of their molecular functions, cellular components and biological processes. In addition, parallel analysis of bidirectional genes in dicotyledons and monocotyledons revealed that abundant bidirectional gene pairs exist in different species. Although the total number of orthologous bidirectional genes was similar, there was a significant difference in the number of orthologous bidirectional gene pairs between dicotyledons and monocotyledons. This evolutionary analysis of the function and structure of homologous bidirectional gene pairs in different varieties and different subspecies of the same species revealed potential pathways by which these gene pairs originated, which may be necessary for the evolution of a new species. Conclusion: In this study, many bidirectional gene pairs in Gossypium hirsutum TM-1 were identified using computer programming, and systematic analysis was conducted to explore their functions and evolutionary relationships. In addition, the promoter activity of the bidirectional intergenic sequences was verified. The combination of computer programming screening, experimental validation and other methods is expected to provide preferred bidirectional promoters for transgenic breeding work via multigene cotransformation methods, and this information is valuable for genetic engineering research and applications. [ABSTRACT FROM AUTHOR]