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The rapid development of digital reading has made it a mainstream reading method for the public, and scholars have conducted research on its effectiveness.The purpose of this study is to systematically summarize and generalize the factors that affect the effectiveness of digital reading in current practical research.

Retrieved the search results from the Web of Science database and the China National Knowledge Infrastructure database, collected the relevant literature in both Chinese and English on the effectiveness of digital reading, qualitatively coded the relevant literature, and conducted a systematic literature review analysis on the factors affecting the effectiveness of digital reading.

There are 37 factors that influence the effectiveness of digital reading, forming five factor themes, namely, the reading subject, reading environment, organizational support, technical support and reading text. The five influencing factor themes are further divided into three types of functional mechanisms, namely, driving, supportive and assurance mechanisms. Based on this, a research framework is proposed, providing a comprehensive approach for the research positioning of digital reading effectiveness.

A research framework is proposed, providing a comprehensive approach for the research positioning of digital reading effectiveness.

Trajectory planning is a core aspect of manipulator operation, directly influencing its performance. This paper aims to introduce a chaotic improved sparrow search algorithm (CISSA) to optimize hybrid polynomial-interpolated trajectories, enhancing the efficiency and precision of manipulator trajectory planning.

The proposed approach leverages 3-5-3 polynomial interpolation to construct the motion trajectory of a 6R manipulator. To optimize the trajectory over time, the sparrow search algorithm is enhanced with chaotic mapping, a discoverer dispersion strategy, positional limiting mechanisms and Brownian motion. These enhancements collectively reduce the manipulator’s runtime while meeting operational requirements.

The proposed method was applied to the AUBO-i5 robot to evaluate its performance. Simulation results demonstrate that CISSA effectively avoids local optima and achieves more accurate solutions compared to similar algorithms. By integrating CISSA into trajectory planning, the robot’s movement time was reduced by 13.99% compared to the original SSA, and the number of algorithm iterations was significantly decreased, ensuring smoother and more efficient task execution in real production.

A CISSA is proposed and applied to the optimal time trajectory planning of the manipulator, verifying the effectiveness and superiority of the algorithm. Experimental results show that CISSA outperforms comparable algorithms by several orders of magnitude in solving manipulator inverse kinematics, significantly enhancing planning efficiency and reducing trajectory planning time.