X. Wang

Individuals often prefer information that matches their needs. In this study, we aimed to explore the relationship between regulatory focus and information preference. Specifically, we investigated the effects of promotion-focused information and prevention-focused information on explicit and implicit information preferences and choice behavior, and examined the mediating roles of information preference. In Experiment 1, we found that prevention-focused individuals were more likely to choose functional information, whereas promotion-focused people were more likely to choose hedonic information. However, there was no significant relationship between regulatory focus and explicit preference and no mediating effect of explicit information preference. In Experiment 2, we found that promotion-focused individuals had a greater implicit preference for hedonic information than did prevention-focused individuals. Implicit information preference mediated the influence of regulatory focus on information choice. The findings of this study may help us understand the psychological mechanism underlying information preference and have important implications for information dissemination.

ObjectiveProspective negative imagery is suggested to play an important role in the development and maintenance of anxiety and depression. The Prospective Imagery Task was developed to assess prospective imagery. Given the importance of prospective imagery for mental health in the Chinese cultural context, our objective was to examine the psychometric properties of the PIT in a Chinese sample.MethodsThe instrument was validated among a sample of 1,372 Chinese individuals who completed the PIT immediately following the Beck Depression Inventory-II and State-Trait Anxiety Inventory-Trait version.ResultsThe two-factor structure of the PIT was in line with the original study, with satisfactory reliability and positive correlations with the BDI-II and STAI-T scores. Latent profile analysis revealed a three-class pattern. The measurement invariance indicated that the instrument can be used among different age groups as well as among males and females.ConclusionThe Chinese version of the PIT is a reliable and valid tool to measure prospective imagery, and the positive subscale is meaningful for clinical psychology. Limitations and future research directions are discussed.

Due to the close relationship among intrinsic/extrinsic motivation, regulatory focus, and creativity revealed by previous literature, intrinsic/extrinsic motivation may play a mediating role between regulatory focus and creativity. Therefore, the present study aimed to investigate the relationship between regulatory focus and creativity by combining intrinsic/extrinsic motivation. In this study, senior high school students completed the Regulatory Focus Questionnaire, the Working Preference Inventory, the Williams Creativity Assessment Packet, and the Kirton Adaption–Innovation Inventory. The correlation analysis showed that both promotion and prevention focus positively correlated with intrinsic motivation; intrinsic motivation and promotion focus positively correlated with creativity personality and innovative-adaptive cognitive style; and extrinsic motivation and prevention focus negatively correlated with innovative–adaptive cognitive style. Furthermore, a path model showed that promotion focus positively predicted creativity through the mediation of intrinsic motivation. In general, our study suggests that intrinsic motivation plays a mediating role between promotion focus and creativity. Our results complement those of previous studies and serve as inspiration for the cultivation of creativity in classroom or enterprise settings.

This article evaluates learners’ thinking in the complex environment of teaching level and cognitive construct process and examines learners within the framework of cognitive factors, as well as the degree of consistency in the training process, in the social practice as the teaching of teachers and students to provide timely and dynamic feedback, first of all to “evidence centered” education evaluation of design patterns and cognitive framework theory as the theoretical basis. An evaluation model based on learners’ cognitive network analysis is designed and constructed by integrating cognitive visualization analysis techniques such as network analysis. Secondly, at the beginning of action research, the teaching framework structure sequence is established under the guidance of the implementation model of flipped classroom, and the investigation results of the current situation are designed under the guidance of operational steps and organizational strategies, and categories and autonomous learning theories are divided, so as to preliminarily construct strategies to improve the ability of autonomous learning. Then through three rounds of iterative action research to improve the flip classroom teaching middle school students’ autonomous learning ability of teaching strategy, the interview method is used; the questionnaire and autonomous learning process to improve the students’ autonomous learning ability training effect evaluation questionnaire is analyzed, and finally a complete set of reverse ascending of classroom teaching is formed to improve students’ autonomous learning ability of effective classroom strategies.

We analyze and study the tracking of nonrigid complex targets of sports video based on mean shift fusion color histogram algorithm. A simple and controllable 3D template generation method based on monocular video sequences is constructed, which is used as a preprocessing stage of dynamic target 3D reconstruction algorithm to achieve the construction of templates for a variety of complex objects, such as human faces and human hands, broadening the use of the reconstruction method. This stage requires video sequences of rigid moving target objects or sets of target images taken from different angles as input. First, the standard rigid body method of Visuals is used to obtain the external camera parameters of the sequence frames as well as the sparse feature point reconstruction data, and the algorithm has high accuracy and robustness. Then, a dense depth map is computed for each input image frame by the Multi-View Stereo algorithm. The depth reconstruction with a too high resolution not only increases the processing time significantly but also generates more noise, so the resolution of the depth map is controlled by parameters. The multiple hypothesis target tracking algorithms are used to track multiple targets, while the chunking feature is used to solve the problem of mutual occlusion and adhesion between targets. After finishing the matching, the target and background models are updated online separately to ensure the validity of the target and background models. Our results of nonrigid complex target tracking by mean shift fusion color histogram algorithm for sports video improve the accuracy by about 8% compared to other studies. The proposed tracking method based on the mean shift algorithm and color histogram algorithm can not only estimate the position of the target effectively but also depict the shape of the target well, which solves the problem that the nonrigid targets in sports video have complicated shapes and are not easy to track. An example is given to demonstrate the effectiveness and adaptiveness of the applied method.

Background: With the outbreak of the coronavirus disease 2019 epidemic in China, the general public but also medical staff were confronted with psychological challenges, suffering from the highly infectious and unknown characteristics of COVID-19. In this study, we surveyed psychological symptoms including anxiety, depression, and sleep disorders in medical staff.Method: A questionnaire star/WeChat link-based survey assessing the Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire-9 depression, the Insomnia Severity Index, Social Support scales in addition to lifestyle, and income level was conducted and included 8,288 medical staff from 24 provinces in China. Pearson Chi-square and Mann-Whitney U-tests were used to evaluate single risk factors and significant differences in psychological symptoms before and during the outbreak of COVID-19. Binary logistic regression analyses were conducted for the risk factors of anxiety, depression, and sleep disorder symptoms.Results: Medical staff had a high incidence of psychological symptoms, which was more prominent during the COVID-19 epidemic. Comparatively, females, nurses, first-line department, never exercised, and low income were risk factors for psychological symptoms. Social support including objective support, subjective support, support utility, and regular sports over 3 times per week were protective and manageable elements that could protect from and manage the psychological symptoms of medical staff.Conclusion: The susceptibility of psychological symptoms among medical staff should be of concern to policymakers and the public in the long-term, and the aggravation of mental health problems of medical staff could be eased by providing adequate social support during and after the COVID-19 outbreak.

In this study, we focus on the problem of information expiration when using the traditional collaborative filtering algorithm and propose a new collaborative filtering algorithm by integrating the time factor. This algorithm considers information influence attenuation over time, introduces an information retention period based on the information half-value period, and proposes a time-weighted function, which is applied to the nearest neighbor selection and score prediction to assign different time weights to the scores. In addition, to further improve the quality of the nearest neighbor selection and alleviate the problem of data sparsity, a method of calculating users’ sentiment tendency by analysis of user review features is proposed to mine users’ attitudes about the reviewed items, which expands the score matrix. The time factor and sentiment tendency are then integrated into the K-means clustering algorithm to select the nearest neighbor. A hybrid collaborative filtering model based on the improved K-means clustering algorithm is then proposed, by combining item-based and user-based collaborative filtering. Finally, the experimental results show that the proposed algorithm can address the time effect and sentiment analysis in recommendations and improve the predictive performance of the model.

Evaluating the price policy of raw milk is of great significance to the sustainable development of an industry supply chain. In this context, our study used the multi-period difference-in-difference method to systematically examine the impact of the policy implementation on product price and profit distribution in the supply chain. The results showed the following: the price of raw milk in the implementation area of the price support policy is 13.54% higher than that of the unimplemented area; the effect of price increase in the western region is higher than that in the eastern region, and the central region ; furthermore, the purchase price guidance policy of raw milk drives price increase or price suppression in the links of the supply chain to promote a balanced distribution of profits among the participants in the chain. These conclusions all have good stability and have reference significance for further improving and adjusting the price support policy of raw milk to realize the sustainable development of the Chinese dairy industry. This will enhance the production confidence of Chinese raw milk producers and improve Chinese consumers’ expectations and consumer psychology regarding domestic dairy products.

Amid the COVID-19 pandemic, fear has run rampant across the globe. To curb the spread of the virus, several governments have taken measures to drastically transition businesses, work, and schooling to virtual settings. While such transitions are warranted and well-intended, these measures may come with unforeseen consequences. Namely, one’s fear of COVID-19 may more readily manifest as aggressive behaviors in an otherwise incognito virtual social ecology. In the current research, a moderated mediation model examined the mechanisms underlying the relation between fear of COVID-19 and overt and relational aggressive online behavior among Chinese college students. Utilizing a large sample of Chinese college students, results indicated that moral disengagement mediated the effect of fear of COVID-19 on college students’ overt and relational online aggressive behavior. A positive family cohesion buffered the effect of moral disengagement on relational aggressive behavior, but only for females. The findings, theoretical contributions, and practical implications of the present paper are also discussed.

The One-Child Policy dramatically changed the Chinese family structure, and the literature indicates that only children may have an advantage in terms of family resource dilution. Moreover, as Chinese families traditionally prioritize investing in sons, only daughters are found to have been empowered by the policy because they did not need to compete with their brothers for parental investment. However, the literature is limited to only teenage children when they were still living in their parents' homes. It is unclear whether—when the generation of only children grew up and married—their family structure differed from that of children with siblings and whether married only daughters retained more family resources from their parents. Based on the data analysis of a 2016 survey, “Study of Youths in 12 Cities of Mainland China,” including a sample of 1,007 fathers and 2,168 mothers born between 1975 and 1985, this study explores the empowerment of married only daughters, employing the theory of family resource dilution in expanded Chinese families. Using educational investment in children as an example, and with random intercept models, this study presents empirical evidence that the dilution of family resources in Chinese expanded families still benefits males and patrilineal practices. Thus, this study demonstrates that Chinese families still tend to sacrifice the interests of married daughters to ensure support for their adult sons. However, it also illustrates that married only daughters could still connect to their parents' resources, giving them a relatively dominant position for decision-making regarding the family's educational expenditure on her own children. Thus, this study extends our understanding of the family resource dilution theory to Chinese expanded families, underscoring the need for further research on Chinese only children after they marry and form families of their own.

Background: Trait self-esteem reflects stable self-evaluation, and it affects social interaction patterns. However, whether and how trait self-esteem can be expressed through behaviors are controversial. Considering that facial expressions can effectively convey information related to personal traits, the present study investigated the three-dimensional facial movements related to self-esteem level and the sex differences therein. Methods: The sample comprised 238 participants. Their levels of trait self-esteem were evaluated by employing the Rosenberg Self-Esteem Scale. During self-introductions, their facial movements in 3D space were recorded by Microsoft Kinect. Two-way ANOVA was performed to analyze the effect of self-esteem and gender on 3D facial movements. Additionally, Logistic regression models were established to describe the relationship between 3D facial movements and self-esteem levels in both genders. Results: The results of two-way ANOVA revealed a main effect of trait self-esteem level for cheeks and lips’ movements. Meanwhile, there was a significant interaction between trait self-esteem and gender on the variability of lips’ movements. In addition, the combination of facial movements can effectively identify trait self-esteem in men and women, with 75.5 and 68% accuracy, respectively. Conclusion: The present results suggest that the 3D facial expressions of individuals with different trait self-esteem levels were different, and such difference is affected by gender. Our study explores a possible way in which trait self-esteem plays a role in social interaction and also provides the basis for automatic self-esteem recognition.

Nonverbal signals color the meanings of interpersonal relationships. Humans rely on facial, head, postural, and vocal signals to express relational messages along continua. Three of relevance are dominance-submission, composure-nervousness and trust-distrust. Machine learning and new automated analysis tools are making possible a deeper understanding of the dynamics of relational communication. These are explored in the context of group interactions during a game entailing deception. The “messiness” of studying communication under naturalistic conditions creates many measurement and design obstacles that are discussed here. Possibilities for their mitigation are considered.

As of the end of October 2020, the cumulative number of confirmed cases of COVID-19 has exceeded 45 million and the cumulative number of deaths has exceeded 1.1 million all over the world. Faced with the fatal pandemic, countries around the world have taken various prevention and control measures. One of the important issues in epidemic prevention and control is the assessment of the prevention and control effectiveness. Changes in the time series of daily new confirmed cases can reflect the impact of policies in certain regions. In this paper, a smooth transition autoregressive model is applied to investigate the intrinsic changes during the epidemic in certain countries and regions. In order to quantitatively evaluate the influence of the epidemic control measures, the sequence is fitted to the STAR model; then, comparisons between the dates of transition points and those of releasing certain policies are applied. Our model well fits the data. Moreover, the nonlinear smooth function within the STAR model reveals that the implementation of prevention and control policies is effective in some regions with different speeds. However, the ineffectiveness is also revealed and the threat of a second wave had already emerged.

The COVID-19 epidemic is associated with negative mood, which has the potential to be a powerful driver of creativity. However, the influence of negative mood on cognitive creativity and emotional creativity remains elusive. Previous research has indicated that self-focused attention is likely to be related to both negative mood and creativity. The current study introduced two self-focused attention variables to explore how negative mood might contribute to cognitive creativity and emotional creativity. Based on a sample of 351 participants, our study found that negative mood during the outbreak of COVID-19 was associated with cognitive creativity and emotional creativity. Meanwhile, there were significant serial mediation effects of rumination and reflection in the relationship between negative mood and creativity and the psychological impact after exposure to the COVID-19 epidemic was positively correlated with emotional creativity but not with cognitive creativity. These results suggested that individuals, in real life and work, could achieve better creative performance through moderate self-focus. Moreover, individuals with different mood states can be induced to enhance their creativity in times of crisis through intervention training to promote reflection.

The performance of the grinding wheel demonstrably affects the machining efficiency and the quality of the workpiece. Therefore, it is essential to evaluate the wear of the wheel and then operate the dressing or replacement in time. The wear procession of the wheel was monitored and evaluated systematically in this paper. A surface grinding experiment was performed by using an alumina wheel to grind the workpiece made of Cr12. The grinding force and the grinding temperature were monitored and measured while the wheel grinds the workpiece. The surface topography of the wheel was also being observed. The distribution of the gray value of pixels in the image of the wheel surface was analyzed by the method of the histogram. Processing of the binary image of the wheel was performed after determining the gray threshold of the gray value. Then, the blockading and the wearing area on the grinding wheel were calculated. Moreover, the relation of the projection area of a single abrasive derived from theory and derived by image recognition was studied. The results of the grinding experiment show that wheel performance degradation occurs when the material removal volume reaches 210 mm3/mm. At this time, the ratio of blockage area on the grinding wheel reaches 13.4%. The percentage of the wearing area is 9.5%. The method of image recognition combined with grinding temperature is workable to realize monitoring and evaluating the wear of wheels on site without unloading them.

While many publications have reported brain hemodynamic responses to decision-making under various conditions of risk, no inventory management scenarios, such as the newsvendor problem, have been investigated in conjunction with neuroimaging. In this study, we hypothesized that NP stimulates the dorsolateral prefrontal cortex and the orbitofrontal cortex joined with frontal polar area significantly in the human brain, and that local brain network properties are increased when a person transits from rest to the NP decision-making phase. A 77-channel functional near infrared spectroscopy system with wide field-of-view was employed to measure frontal cerebral hemodynamics in response to NP in 27 healthy human subjects. NP-induced changes in oxy-hemoglobin concentration, Δ[HbO], were investigated using a general linear model and graph theory analysis. Significant activation induced by NP was shown in both DLPFC and OFC+FPA across all subjects. Specifically, higher risk NP with low-profit margins activated left-DLPFC but deactivated right-DLPFC in 14 subjects, while lower risk NP with high-profit margins stimulated both DLPFC and OFC+FPA in 13 subjects. The local efficiency, clustering coefficient, and path length of the network metrics were significantly enhanced under NP decision making. In summary, multi-channel fNIRS enabled us to identify DLPFC and OFC+FPA as key cortical regions of brain activations when subjects were making inventory-management risk decisions. We demonstrated that challenging NP resulted in the deactivation within right-DLPFC due to higher levels of stress. Also, local brain network properties were increased when a person transitioned from the rest phase to the NP decision-making phase.

Wheels are the key components of a train, and the shape of the wheel flange should be maintained to ensure the security of train operations. As a method to maintain the shape at the cost of the diameter size, reprofiling has significant impacts on the lifecycle of a train. A wheel model is built in this paper based on the analysis of the wheel wear features and datasets from Taiyuan locomotives. With the decision variables T i, T i ′, which describe the reprofiling strategy, we formulate a multiobjective optimization problem simultaneously minimizing the reprofiling numbers and maximizing the serving years. To find the solutions of the multiobjective model, the NSGA-II is extended with an alteration of the crowding distance calculation and genetic operators. The improved NSGA-II performs better than other approaches. Meanwhile, outstanding solutions with longer servicing years and less reprofiling are listed in this paper. Our study reveals the relationship between the diameter, flange thickness, and their individual attrition rates and proposes a wear model, multiobjective model, and improved NSGA-II. Compared with existing reprofiling strategies, the strategy recommended in our work can significantly increase the lifecycle of the wheel coupled with a low repair frequency.

The aim of cognitive diagnosis is to classify respondents' mastery status of latent attributes from their responses on multiple items. Since respondents may answer some but not all items, item-level missing data often occur. Even if the primary interest is to provide diagnostic classification of respondents, misspecification of missing data mechanism may lead to biased conclusions. This paper proposes a joint cognitive diagnosis modeling of item responses and item-level missing data mechanism. A Bayesian Markov chain Monte Carlo method is developed for model parameter estimation. Our simulation studies examine the parameter recovery under different missing data mechanisms. The parameters could be recovered well with correct use of missing data mechanism for model fit, and missing that is not at random is less sensitive to incorrect use. The Program for International Student Assessment 2015 computer-based mathematics data are applied to demonstrate the practical value of the proposed method.

At present, the Chinese government is trying to resolve various social contradictions, such as people’s ever-growing need for a better life and unbalanced and inadequate development. To do so, urban governance practices including holistic governance, decentralized and interconnected governance, multiple participatory governance, and smart governance have been developed in China. Urban smart governance supported by mobile Internet, the Internet of Things, quantum computing, big data, artificial intelligence, and other information technologies has also entered the field of vision of academics and administrators. However, the research and practice on the integration of organizational structure and smart governance technology for urban governance in China are still insufficient. Hence, this paper proposes the design of the organizational structure of an urban smart governance platform and presents the “1 + N” integrated smart information platform and the “power-sharing linkage, one-center and dual-track” platform construction command system. In this system, the functional module of the information platform for smart urban governance is elaborated. This paper contributes to promoting the modernization of China’s urban governance capacity, which can enhance social equity and social order, promote social democracy and rule of law, and enhance the efficiency of urban governance.

A long-standing problem in biology, economics, and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. This paper investigates how to promote the evolution of cooperation in the Prisoner’s Dilemma game. Differing from previous approaches, we not only propose a tag-based control mechanism but also look at how the evolution of cooperation by TBC can be successfully promoted. The effect of TBC on the evolutionary process of cooperation shows that it can both reduce the payoff of defectors and inhibit defection; although when the cooperation rate is high, TBC will also reduce the payoff of cooperators unless the identified rate of the TBC is large enough. An optimal timing control of switched replicator dynamics is designed to consider the control costs, the cooperation rate at terminal time, and the cooperator’s payoff. The results show that the switching control between an optimal identified rate control of the TBC and no TBC can properly not only maintain a high cooperation rate but also greatly enhance the payoff of the cooperators. Our results provide valuable insights for some clusters, for example, logistics parks and government, to regard the decision to promote cooperation.

To improve the accuracy of the multiple channel integration quality evaluation, this paper proposes a comprehensive evaluation method using the nonlinear autoregressive exogenous model and constructs an index system. First, the entropy method is used to determine the objective weight of each indicator. The indicators used in this paper are process consistency, information consistency, emotional value, procedural value, service structure transparency, online result value, business relevance, and online purchase intention. Second, an improved gray relational analysis algorithm is used to obtain the comprehensive gray relational degree between the above eight indicators’ standard samples and the tested samples. Then, this study uses the dataset preprocessed with the GRA algorithm for training the NARX model. Then, this study uses the trained model to evaluate the quality of multiple channel integration comprehensively. Next, this study uses standardized methods to quantify the evaluation results to provide new ideas and theoretical guidance for teaching traditional retailers to use the advantages of multiple channels to expand their online business. This paper uses 50,000 consecutive samples of a product for 3 months as a dataset in the experimental part. Through the GRA method and the NARX model, the comprehensive gray relational degree between the test sample and the ideal sample is obtained, and the results are quantified. Experiments show that, compared with the GRA method, this paper’s method has a higher degree of fit between the output value and the target value.

The long-term success of organizations is mainly attributable to employees’ psychological health. Organizations focusing on promoting and managing the flow (an optimal experience and optimal functioning state) may enhance employees’ well-being and performance to an optimum level. Surprisingly, the literature representing the role of HRM practices for their effect on work-related flow (i.e., intrinsic motivation, absorption, and work enjoyment) is very sparse. Accordingly, by drawing primarily on the job demands-resources model and HRM specific attribution theory, this paper develops a theoretical framework that unravels the effectiveness of specific organizational level High Involvement HRM (HIHRM) practices (i.e., recognition, empowerment, information sharing, fair rewards, and competence development) in activating the individual level work-related flow with beneficial effect and mediating role of affective commitment. In addition to highlighting the underlying mechanisms that may cause HIHRM practices to be regarded as resources and sometimes as demands, this paper especially proposes that these practices implemented with a focus to promote employee well-being are perceived as job resources and may positively influence affective commitment and flow, whereas these practices used as a demand to increase performance are perceived as job demands and may hinder affective commitment and flow. It is further significant to understand the possible moderating effects of emotional intelligence on the relationships among HIHRM practices, affective commitment, and flow. The paper augments the knowledge and understanding of the impact process of HIHRM practices, in particular how the HIHRM effect is sensed by the workers and thus, influences their succeeding job attitude and work experience. Finally, this work, as the first paper to link HIHRM practices with work-related flow, promotes the concept of positive psychology in the workplace.

The process dissociation procedure (PDP) of implicit sequence learning states that the correct inclusion-task response contains the incorrect exclusion-task response. However, there has been no research to test the hypothesis. The current study used a single variable (Stimulus Onset Asynchrony SOA: 850 ms vs. 1350 ms) between-subjects design, with pre-task resting-state fMRI, to test and improve the classical PDP to the mutually exclusive theory (MET). (1) Behavioral data and neuroimaging data demonstrated that the classical PDP has not been validated. In the SOA = 850 ms group, the correct inclusion-task response was at chance, but the incorrect exclusion-task response occurred greater than chance. In the SOA = 850 ms group, the two responses were not correlated, but in the SOA = 1,350 ms group and putting the two groups together, the two responses were in contrast to each other. In each group, brain areas whose amplitude of low frequency fluctuations (ALFFs) in the resting-state related to the two responses were either completely different or opposite to one another. However, the results were perfectly consistent with the MET proposed by the present study which suggests that the correct inclusion-task response is equal to the correct exclusion-task response is equal toC+A1, and the incorrect exclusion-task response is equal toA2.Cdenotes the controlled response andA1andA2denote two different automatic responses. (2) The improved PDP was proposed to categorize the 12 kinds of triplets as delineating four knowledge types, namely non-acquisition of knowledge, uncontrollable knowledge, half-controllable knowledge, and controllable knowledge with the MET. ALFFs in the resting-state could predict the four knowledge types of the improved PDP among two groups. The participants’ control of the four knowledge types (degree of consciousness) gradually improved. Correspondingly, the brain areas in the resting-state positively related to the four knowledge types, gradually changed from the sensory and motor network to the somatic sensorimotor network, and then to the implicit learning network, and then to the consciousness network. The brain areas in the resting-state negatively related to the four knowledge types gradually changed from the consciousness network to the sensory and motor network. As SOA increased, the brain areas associated with almost all the four knowledge types changed. (3) The inhomogeneous hypothesis of the MET is best suited to interpret behavioral and neuroimaging data; it states that the same components among the four knowledge types are not homogeneous, and the same knowledge types are not homogeneous between the two SOA groups.

According to resource limitation, a more realistic pest management is that the impulsive control actions should be adjusted according to the densities of both pest and natural enemy in the field, which result in nonlinear impulsive control. Therefore, we have proposed a Beddington–DeAngelis interference predator-prey model concerning integrated pest management with both density-dependent pest and natural enemy population. We find that the pest-eradication periodic solution is globally stable if the impulsive period is less than the critical value by Floquet theorem. The condition of permanent is established, and a stable positive periodic solution appears via a supercritical bifurcation by bifurcation theorem. Finally, in order to investigate the effects of those nonlinear control strategies on the successful pest control, the bifurcation diagrams showed that the model exists with very complex dynamics. Consequently, the resource limitation may result in pest outbreak in complex ways, which means that the pest control strategies should be carefully designed.

In the evaluation of teaching quality, aiming at the shortcomings of slow convergence of BP neural network and easy to fall into local optimum, an online teaching quality evaluation model based on analytic hierarchy process and particle swarm optimization BP neural network is proposed. Firstly, an online teaching quality evaluation system was established by using the analytic hierarchy process to determine the weight of each subsystem and each index in the online teaching quality evaluation system and then combined with actual experience, the risk value of each index was constructed according to safety regulations. The regression model is established through BP neural network, and the weight and threshold of the model are optimized by the particle swarm algorithm. Based on the online teaching quality evaluation model of BP neural network, the parameters of the model are constantly adjusted, the appropriate function is selected, and the particle swarm algorithm which is used in the training and learning process of the neural network is optimized. The scientificity of the questionnaire was verified by reliability and validity test. According to the scoring results and combined with the weight coefficient of each indicator in the online course quality evaluation index system, the key factors affecting the quality of online courses were obtained. Based on the survey data, descriptive statistics, analysis of variance, and Pearson’s correlation coefficient method are used to verify the research hypothesis and obtain valuable empirical results. By comparing the model with the standard BP model, the results show that the accuracy of the PSO-BP model is higher than that of the standard BP model and PSO-BP effectively overcomes the shortcomings of the BP neural network.