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The significance of interactive pedagogy in English education cannot be overstated, as it fosters student engagement, collaboration, and active learning, thereby enhancing both academic performance and comprehensive capabilities. This article presents a structured three-step strategy designed to integrate curriculum thinking into the teaching of English at higher vocational levels through a blended online and offline approach. Central to this methodology is the development of a robust “online + offline” teaching quality evaluation index system, innovatively constructed using a combination of rough set theory and a backpropagation (BP) neural network algorithm. Furthermore, the effectiveness of this pedagogical approach is quantitatively analyzed using a Markov chain model, which evaluates the progression of students’ English proficiency. The analysis reveals that sustained application of the proposed teaching methodology is likely to elevate students’ English performance to an estimated score of 84.273, marking a substantial improvement of 5.443 points over traditional methods. Empirical validation of the model’s effectiveness was achieved through student evaluations across three critical areas: Civic Integration Effectiveness, Pre-Class Preview, and Follow-Up Testing. The results of the post-test assessments yielded mean scores of 3.565, 3.564, and 3.695, respectively, indicating a significant enhancement in learning outcomes, as evidenced by p-values of less than 0.05. This statistical analysis confirms the significant impact of the innovative pedagogical strategy on student learning outcomes.

This paper firstly explores the power mechanism of agricultural insurance to help rural revitalization from three aspects of agriculture, farmers and rural three farmers, respectively, and constructs the rural revitalization development index system by combining the entropy power method. Then, the three-stage DEA model and the three-stage Malmquist index model are used to measure the efficiency of agricultural insurance boosting rural revitalization by combining the selected agricultural insurance boosting indicators. Finally, taking province A as an example, after descriptive statistical analysis, the method of this paper is combined with empirical analysis, and the practical path of agricultural insurance to help farmers is proposed from the three aspects of the insurance system, publicity as well and supply. The results show that after the optimization of agricultural insurance, the value of technical efficiency is distributed in [0.600, 0.738], the value of pure technical efficiency is distributed in [0.716, 0.826], and the value of scale efficiency is distributed in [0.738, 0.833] from 2010 to 2019. The mean value of the agricultural technical efficiency index in each city is 1.091, the mean value of the progress index is 1.033, and the mean value of total factor productivity is 1.029, which is an upward trending technology, and all of them have a growth rate of more than 5%. Based on this study, agricultural insurance can help improve the efficiency of rural revitalization.

Objective: In order to solve the problem of inaccurate defect extraction caused by complex and variable color and irregular texture changes of tomato surface defects, the defect segmentation method based on image local variance with brightness correction was proposed. Methods: On the basis of using histogram threshold segmentation method to segment calyx and stem scar and the method of domain pixel weighted sum to replace the original pixel to complete the brightness correction, the gray image of tomato surface was divided into several image blocks, and the color of each block was characterized by image pixel variance, and then the defect and healthy area were separated. SVM model was used to detect the proportion of tomato surface defect area in the original tomato area. Results: Considering the brightness correction, the accuracy of tomato defect area extraction could be improved by 27.74%. On this basis, compared with the global threshold, dynamic threshold and regional growth algorithm, the defect extraction method based on image local variance could accurately achieve the quasi-deterministic and complete extraction of tomato surface defects, and the accuracy of the Gauss-SVM model with the defect area ratio as the input for tomato surface defect detection reached 96%. Conclusion: Considering brightness correction, the SVM defect extraction method based on image local variance is suitable for tomato surface defect detection.

ObjectiveTo clarify the effectiveness and safety of psycho-behavioral intervention combined with a non-benzodiazepine to improve perioperative sleep quality in patients undergoing knee arthroplasty, and also to explore the optimal dosage of non-benzodiazepine (oral zolpidem tartrate) to form a standardized sleep quality management process to promote accelerated recovery of patients.Methods240 patients undergoing initial unilateral total knee arthroplasty between January and December 2016 were prospectively included and randomly divided into blank control group (group A), psycho-behavioral intervention group (group B), zolpidem tartrate 10 mg group (group C), and psycho-behavioral intervention + zolpidem tartrate 5 mg group (group D). Sleep, pain, psychological, and knee function scores were compared.ResultsThere were significant differences between the four groups with respect to Pittsburgh sleep quality index scores, sleep efficiency, Epworth Sleepiness Scale scores, inflammatory indices, pain, and enhanced recovery after surgery indices during hospitalization (P

Money donation and time donation, as charitable donations from individuals to organizations, are two forms of prosocial behavior that have been increasingly studied in recent years. Despite the vast amount of research about money and/or time donation, however, only limited work has been done on reviewing the research on these two forms of charitable donations as comparable or parallel entities. In this paper, we seek to help fill this gap by reviewing the existing research. We applied the backwards and forwards snowballing technique to arrive at a review sample of 39 experimental papers published in 2000–2020 that have compared money and time donation, or at least analyzed them as two parallel entities. We examine the issues that are predominantly considered in these experimental papers and summarize the general directions of their findings. We also point out certain gaps in the existing literature and posit some potentially fruitful directions for future experimental research regarding money and time donation.

The major objective of this research is to test if two types of information overload are different: Information overload from searching for the information someone needs to search, and information overload from following all the information someone needs to follow. These two types of information overload may be labelled information search overload and information follow overload, corresponding to the concepts of information search and information follow. Using the data of a survey from a sample of about 1600 respondents across 50 states in the United States, the research identified 2 items corresponding to information search overload and information follow overload, and ran analyses including correlation and logistic regression with the 2 items separately as the dependent variables, and with some other items about consumers’ activities involving information as independent variables. Results of the various analyses suggest that information search overload and information follow overload are different, especially in terms of how they associate with different variables of consumer activities involving information, therefore indicate as a preliminary research that we may separate the two types of information overload in our future research.