In the present study, we use a training design in two experiments to examine whether bilingual language switching facilitates two components of cognitive control, namely monitoring and inhibitory control. The results of Experiment 1 showed that training in language switching reduced mixing costs and the anti-saccade effect among bilinguals. In Experiment 2, the findings revealed a greater decrease of mixing costs and a smaller decrease of the anti-saccade effect from pre- to post-training for the language switching training group compared to (...) the L2 training group. Overall, the results suggest that extensive exercise in monitoring and inhibitory control among languages in an experimental setting may enhance the corresponding components of cognitive control. We discuss these findings in the context of the relationship between bilingual language control and executive control. (shrink)

Purpose: This study aimed to explore the relationship between mathematic achievement and programming self-efficacy, and adopt a mediation model to verify the mediating role of creativity on the relationship between mathematic achievement and programming self-efficacy.Methods: A total of 950 upper-secondary school students were surveyed using their math test scores, the Kirton Adaption-Innovation and the Programmed Self-Efficacy Scale. SPSS-26 was used for descriptive statistical analysis and correlation analysis of related variables. The PROCESS plugin was used to test the mediating effect of (...) creativity.Results: Mathematic achievement has a positive effect on programming self-efficacy, mathematic achievement is positively related to creativity, and creativity also has a positive influence on programming self-efficacy. Creativity has a mediating effect on the relationship between mathematic achievement and programming self-efficacy.Conclusion: The results revealed that mathematic achievement affected programming self-efficacy directly and also indirectly through creativity. This provided certain ideas for the development of programming education for teenagers. Since students’ mathematics learning and creativity are related to programming learning, it is necessary to pay attention to the integration of the disciplines of programming education and mathematics. Further, the cultivation of innovative thinking is also critical to facilitate programming learning. (shrink)

This work is developed to improve the current quality of e-commerce logistics services. From the perspective of multiple consumer psychology, based on e-commerce, consumer psychology, and other related theories, vegetable e-commerce B is selected as the research object. The commodity quality, accuracy, and timeliness of commodity distribution and other factors of e-commerce B are discussed through questionnaire survey. Then, according to customers’ opinions about “e-commerce B’s distribution and professional aspects that need to be improved,” the research is conducted. Finally, the (...) direction of follow-up optimization is proposed from four different perspectives of multiple consumption psychology. The research results show that more than 89% of the surveyed customers believe that e-commerce B does a good job in terms of commodity quality, accuracy, and timeliness of commodity distribution, and has a high level of logistics service. However, 26.34% of customers hope that e-commerce B can strengthen the protection of personal privacy, 24.97% hope that the platform can add “delay insurance” for goods, and 39.54% hope that the logistics information of purchased goods can be updated in real time. Therefore, e-commerce B needs to be optimized and improved continuously in the future development. Therefore, research on the optimization of logistics service quality of e-commerce is performed under multiple consumption psychology, which provides certain help for the rapid development of subsequent e-commerce. (shrink)

The coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. In this study, an assembly optimization method for the multistage rotor of an aeroengine is proposed based on the (...) genetic algorithm. Firstly, a spatial location propagation model is developed to accurately predict the spatial position of each rotor after assembly. The alignment process of the assembly screw holes of the adjacent rotors is considered for the first time. Secondly, a new assembly optimization strategy is proposed to select different assembly data for the specific values of the coaxiality and unbalance, respectively. Finally, a double-objective fitness function is constructed based on the coaxiality and unbalance. The simulation and experimental results show that the assembly optimization method proposed in this study can be utilized to achieve synchronous optimization of the coaxiality and unbalance of an aeroengine during preassembly. (shrink)

The purpose is to solve the problem that the current research on the impact of the microstructure of mental elasticity and its constituent factors on the development of the mental elasticity of children is not comprehensive, and the traditional artificial analysis method of mental problems has strong subjectivity and low accuracy. First, the structural equation model is used to study the microstructure of poor children's mental elasticity, and to explore the structural relationship and functional path between the mental elasticity of (...) children and the self-efficacy of their mental health, psychological anxiety, and attachment. Second, a prediction model of mental problems of children in plight based on the backpropagation neural network is constructed. Finally, middle schools in the representative areas of Northwest China are selected as the research unit. The relevant research data are collected by issuing questionnaires, and the data set is constructed to verify the performance of the model. The experimental results show that the average prediction errors of the BPNN model and the support vector regression model are 1.87 and 5.4, respectively. The error of BPNN is 65.4% lower than that of SVR, so BPNN has a better performance. The prediction results of the test set show that the actual error and the relative error of the BPNN model are controlled in the range of 0.01, and the prediction accuracy is high. The structural equation model has a high fitting degree. The results of the questionnaire analysis show that attachment, self-efficacy, and psychological anxiety exert a significant direct impact on mental elasticity. This exploration aims to conduct a micro investigation on the relationship among the three core variables in the resilience research of children in plight, and analyze their resilience, to provide a theoretical basis for the resilience intervention design of vulnerable groups. (shrink)

Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning (...) effects in the serial reaction time task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning. (shrink)