Y Jiang

Systems with human-centered artificial intelligence are always as good as their ability to consider their users’ context when making decisions. Research on identifying people’s everyday activities has evolved rapidly, but little attention has been paid to recognizing both the activities themselves and the motions they make during those tasks. Automated monitoring, human-to-computer interaction, and sports analysis all benefit from Web 4.0. Every sport has gotten its move, and every move is not known to everyone. In ice hockey, every move cannot be monitored by the referee. Here, Convolution Neural Network-based Real-Time Image Processing Framework (CNN-RTIPF) is introduced to classify every move in Ice Hockey. CNN-RTIPF can reduce the challenges in monitoring the player’s move individually. The image of every move is captured and compared with the trained data in CNN. These real-time captured images are processed using a human-centered artificial intelligence system. They compared images predicted by probability calculation of the trained set of images for effective classification. Simulation analysis shows that the proposed CNN-RTIPF can classify real-time images with improved classification ratio, sensitivity, and error rate. The proposed CNN-RTIPF has been validated based on the optimization parameter for reliability. To improve the algorithm for movement identification and train the system for many other everyday activities, human-centered artificial intelligence-based Web 4.0 will continue to develop.

Preservice mathematics teachers’ accurate understanding of mathematical problem solving and its teaching is key to the performance of their professional quality. This study aims to investigate preservice mathematics teachers’ understanding of problem solving and its teaching and compares it with the understanding of in-service mathematics teachers. After surveying 326 in-service mathematics teachers, this study constructs a reliable and valid tool for the cognition of mathematical problem solving and its teaching and conducts a questionnaire survey on 26 preservice mathematics teachers. Survey results reveal that preservice mathematics teachers have a good understanding of mathematical problem solving and its teaching and are more confident in the transfer value of problem solving ability. By contrast, in-service teachers are more optimistic that problem solving requires exploration, continuous thinking, and the participation of metacognition. This article concludes that preservice mathematics teachers should focus more on the initiative and creativity of students and put students at the center of education. In addition, teacher educators should provide more teaching practice opportunities for preservice teachers. The findings also show that in-service teachers’ understanding of problem solving and its teaching is inferior to that of preservice teachers on some indicators, implying the importance of post-service training for in-service teachers.

With the global pandemic of COVID-19, it has been striking psychological burdens on individuals. Under this background, more and more people get wellbeing by watching live broadcasts. However, the psychological mechanism behind this phenomenon is still a black box. This study finds that when people watch a live broadcast and interact with anchors and other people, an interaction ritual chain is formed, and emotional energy is generated, thus making people experience and understand the meaning of the live interaction ritual chains. Under the effect of the meaning transfer model, people will generate wellbeing. Specifically, the basic meaning of live interaction drives people’s generation of wellbeing. The meanings of self-participation, self-display, self-concept, and self-renewal play a role in mediation in enhancing people’s wellbeing with the basic meaning of live broadcast interaction.

With the development of network technology, enterprises face the explosive growth of data every day. Therefore, to fully mine the value of massive data, big data analysis technology has become the key to developing the core competitiveness of enterprises. However, few empirical studies have investigated the influencing mechanism of the BDA capability of an enterprise on its operational performance. To fill this gap, this study explores how BDA technology capability influences enterprise operation performance, based on dynamic capabilities theory and resource-based theory. It proposes the key variables, including the connectivity, compatibility, and modularization of big data analysis technical capability, enterprise's operational performance, and the fit between data and tools, to establish a model and study the correlation between the variables. The results highlight the mediating role of data-tool fit in the relationships between BDA capability and the enterprise's operational performance, which is a major finding that has not been underlined in the extant literature. This study provides valuable insight for operational managers to help them in mobilizing BDA capability for enterprises' operational management and improving operational performance.

As a sub-realm of Language Teacher Psychology, teachers’ professional agency has gained significant attention from educational practitioners and teachers. The aim is to better discern teachers’ professional development and teaching effectiveness with a view to ensuring the quality of language teaching. International literature concerning teachers’ professional agency has noted a shift from knowledge training to vocational development in relation to teachers’ experience in decision making. Yet, little research so far has scrutinized this specific issue in Chinese university settings, and the real picture of teacher agency needs further exploration. Besides, the multidimensional and complex nature of agency identifies the overwhelming research work in understanding its contents in detail based on the previous perspectives from individuals, society, and time. To this end, the ecological understanding of professional agency reframed the theoretical basis of this study, prone to explore how teachers’ experience could be examined in relation to individual capacity, resources, and structural and contextual variables. The study was conducted in Chinese university settings in response to the research gap related to understanding professional agency. Quantitative and qualitative data from questionnaires, interviews, and classroom observations with 116 university teachers in China demonstrated that the enactment of professional agency rested on the interplay between temporal contexts, teacher capacity, and beliefs, especially in the instructional community. The findings revealed that university teachers at different stages of career development manifested variability in exercising their professional agency in relation to adapting or adopting existing teaching concepts, methods, or approaches. Mounting evidence revealed some enablers and constraints in relation to formative assessment, time impact, classroom interaction, and school culture. Emphasizing the interaction between individuals’ ability and their engagement with the professional environment, the findings provide insights into theoretical implications associated with ecological theory and enhance the practical discussion about promoting professional development for novice, mid-career, and veteran English teachers at the university level.

Color harmony is the focus of many researchers in the field of art and design, and its research results have been widely used in artistic creation and design activities. With the development of signal processing and artificial intelligence technology, new ideas and methods are provided for color harmony theory and color harmony calculation. In this article, psychological experimental methods and information technology are combined to design and quantify the 16-dimensional physical features of multiple colors, including multi-color statistical features and multi-color contrast features. Eighty-four subjects are invited to give a 5-level score on the degree of color harmony for 164 multi-color materials selected from the screenshots of film and television scenes. Based on the multi-color physical features and the subjective evaluation experiment, the correlation analysis is firstly carried out, which shows that the overall lightness, difference of the color tones, number of multiple colors, lightness contrast, color tone contrast, and cool/warm contrast are significantly correlated with color harmony. On the other hand, the regression prediction model and classification prediction model of color harmony are constructed based on machine learning algorithms. In terms of regression prediction model, the prediction accuracy of linear models is higher than that of nonlinear models, with 63.9% as the highest, indicating that the multi-color physical features can explain color harmony well. In terms of classification prediction model, the Random Forest has the best prediction performance, with an accuracy of 80.2%.

Behavioral studies have demonstrated differences in the effect of constrained retrieval of semantic vs. non-semantic information on the encoding of foils. However, the impact of recognition on foils between semantic and non-semantic trials remains unclear. This study thus examines the roles of recognition—familiarity and recollection—in constrained retrieval for foils. We applied the event-related brain potentials data of new/old effects to elucidate the neural mechanisms underlying the “foil effect.” Participants encoded semantic and non-semantic tasks, were tested in a blocked memory task with new words presented as foils, and performed a surprise recognition task involving foils and completely new words. Behavioral results showed better recognition performance regarding reaction times and accuracy by hit and correct reject for semantic vs. non-semantic trials in Phase 2. Conversely, inferior recognition performance in reaction times and accuracy by hit and correct reject was noted for semantic vs. non-semantic foils in Phase 3. ERP results showed more positive Frontal N400 for hit in non-semantic trials, more positive late positive component for correct rejects in semantic trials in Phase 2, and more positive LPC for hits in both semantic and non-semantic trials only in Phase 3. Through dual-processing theory, we prove that different task types in constrained retrieval depend on different retrieval processes. Particularly, familiarity may be applied more often in non-semantic trials, and recollection in semantic trials. The difference in processes between semantic and non-semantic trials during constrained retrieval affects incidental encoding of foils.

BackgroundThe cognitive outcomes induced by subthalamic nucleus deep brain stimulation (STN-DBS) remain unclear, especially in PD patients with mild cognitive impairment (MCI). This study explored the cognitive effects of STN-DBS in PD patients with MCI.MethodsThis was a retrospective cohort study that included 126 PD patients who underwent STN-DBS; all patients completed cognitive and motor assessments before and at least 6 months after surgery. Cognitive changes were mainly evaluated by the Montreal cognitive assessment (MoCA) scale and the seven specific MoCA domains, including visuospatial/executive function, naming, attention, language, abstract, delayed recall, and orientation. Motor improvement was evaluated by the UPDRS-III. Cognitive changes and motor improvements were compared between PD-MCI and normal cognitive (NC) patients. Logistic regression analyses were performed to explore predictors of post-operative cognitive change.ResultsAt the time of surgery, 61.90% of the included PD patients had MCI. Compared with the PD-MCI group, the PD-NC group had a significantly higher proportion of cases with post-operative cognitive decline during follow-up of up to 36 months (mean 17.34 ± 10.61 months), mainly including in global cognitive function, visuospatial/executive function and attention. Covariate-adjusted binary logistic regression analyses showed that pre-operative global cognitive status was an independent variable for post-operative cognitive decline. We also found that pre-operative cognitive specific function could predict its own decline after STN-DBS, except for the naming and orientation domains.ConclusionPD-MCI patients are at a lower risk of cognitive decline after STN-DBS compared with PD-NC patients.

Criminals targeting and exploiting older adults in online environments are of great concern. This study systematically retrieved and analyzed articles on the psychological characteristics of older adult victims of online fraud. First, we found that there was no evidence that older adults were more prevalent than other individuals of other ages among online fraud victims, and current researchers have focused more on why older adults are easy targets for fraud. Second, research on psychological factors of older adults' susceptibility to online fraud has mainly focused on cognitive function, trust traits, and other personality traits, such as social loneliness, the Big Five personality traits, and self-control. Among them, most researchers claim that the cyber-cheating of older adults may be due to a decline in their cognitive function. However, there has not been a consensus on how cognitive function and physical and mental conditions affect older people who are cheated. Third, techniques and experience may be related to the susceptibility of older adults to fraud, and these studies have also not yet generated a consensus supported by reliable data. Based on the above research uncertainties, we propose that fraud prevention and control strategies for older adults should be applied with caution.

Orphans and vulnerable children fall under the category of children who are at risk of exposure to more stressful circumstances and receive less social assistance compared to other children. This study aims to investigate the impact of group counseling based on social intervention and psychological therapy on social support and the perceived stress growth of orphans and vulnerable children. In one special educational needs school in Nanning, China, the SSGPC was developed and implemented. Using the social support and post-stress growth scales, the researchers investigated the effects of SSGPC on orphans and vulnerable children. Twenty-seven orphans and vulnerable children between the ages of nine and 12 were arbitrarily assigned to the experimental and control groups. A pre-test post-test method of quasi-experimental design was applied, with 13 participants in the experimental group and 14 in the control group. The results revealed that the intervention group had significantly higher scores for social support and post-stress growth than the control group. The SSGPC had significantly improved the levels of social support for orphans. The findings indicated that the SSGPC provided an effective way to improve social support and post-stress growth of orphans and vulnerable children.

The present study investigated the effects of L1-L2 congruency, collocation type, and restriction on L2 collocational processing. Advanced Chinese learners of English and native English-speaking controls performed an online acceptability judgment task to investigate how advanced L2 learners processed congruent (sharing the same meaning and structure in L1 language) collocations and English-only (not equivalent in L1 construction) collocations with the same node (right) word and a different collocate (left). The experimental materials included verb-noun (VN), adjective-noun (AN) collocations, free (less fixed), and restricted (more fixed) collocations chosen from BNC. The results revealed that (i) The non-native speakers were sensitive to L1-L2 congruency, but the native speakers were not. (ii) The native speakers were sensitive to collocation restriction, whereas the non-native speakers were not. These results lend initial support to the mapping hypothesis and open choice principle of L2 collocational processing for Chinese English learners.

BackgroundExercise is one of the effective ways to improve cognition. Different forms of exercises, such as aerobic exercise, resistance exercise, and coordination exercise, have different effects on the improvement of cognitive impairment. In recent years, exergames based on Non-Immersive Virtual Reality have been widely used in entertainment and have gradually been applied to clinical rehabilitation. However, the mechanism of NIVR-Exergames on improving motor cognition has not been clarified. Therefore, the aim of this study is to find whether NIVR-Exergames result in a better neural response mechanism to improve the area of the cerebral cortex related to motor cognition under functional near-infrared spectroscopy dynamic monitoring in comparison with resistance exercise.MethodsA cross-over study design was adopted in this study, and 15 healthy young subjects were randomly divided into group A and group B according to a computerized digital table method. Task 1 was an NIVR-Exergame task, and Task 2 was resistance band stretching. Group A first performed Task 1, rested for 30 min, and then performed Task 2. Group B had the reverse order. The fNIRS test was synchronized in real time during exercise tasks, and heart rate measurements, blood pressure measurements, and 2-back task synchronization fNIRS tests were performed at baseline, Post-task 1, and Post-task 2. The primary outcomes were beta values from the general linear model in different regions of interest, and the secondary outcomes were heart rate, blood pressure, reaction time of 2-back, and accuracy rate of 2-back.ResultsThe activation differences of Task 1 and Task 2 in the right premotor cortex and the left PMC were statistically significant. There were statistically significant differences in the activation of the right supplementary motor area, left dorsolateral prefrontal cortex, left and right PMC between baseline and Post-task 1. The differences in systolic pressure between the two groups at three time points among women were statistically significant.ConclusionIn this study, we found that NIVR-Exergames combined with motor and challenging cognitive tasks can promote the activation of SMA, PMC and DLPFC in healthy young people compared with resistance exercise alone, providing compelling preliminary evidence of the power for the rehabilitation of motor and cognitive function in patients with central nervous system diseases.

Previous researchers have found that head-down bed rest will affect the emotional state of individuals, and negative emotions such as anxiety are closely related to attention bias. The present study adopted the dot-probe task to evaluate the effects of 15-days of −6° HDBR on the attention bias of threatening stimulus in 17 young men, which was completed before, during, after the bed rest. In addition, self-report inventories were conducted to record emotional changes. The results showed that the participants’ negative affect scores on HDBR-8 were significantly lower than the HDBR-1 in PANAS while there was no significant difference on positive affect scores and anxiety scores in SAI. And the results showed that at the Pre-HDBR, HDBT-1, HDBR-15, Post-HDBR, the response speed to threatening stimulus was faster than neutral stimulus, but no statistical significance. However, reaction time of threatening stimulus is significantly longer than neutral stimulus in the HDBR-8, indicating that HDBR may have an effect on the participants’ attention bias, and this effect is manifested as attention avoidance.

Several functional magnetic resonance imaging studies have demonstrated abnormalities in static intra- and interhemispheric functional connectivity among diverse brain regions in patients with major depressive disorder. However, the dynamic changes in intra- and interhemispheric functional connectivity patterns in patients with MDD remain unclear. Fifty-eight first-episode, drug-naive patients with MDD and 48 age-, sex-, and education level-matched healthy controls underwent resting-state fMRI. Whole-brain functional connectivity, analyzed using the functional connectivity density approach, was decomposed into ipsilateral and contralateral functional connectivity. We computed the intra- and interhemispheric dynamic FCD using a sliding window analysis to capture the dynamic patterns of functional connectivity. The temporal variability in functional connectivity was quantified as the variance of the dFCD over time. In addition, intra- and interhemispheric static FCD patterns were calculated. Associations between the dFCD variance and sFCD in abnormal brain regions and the severity of depressive symptoms were analyzed. Compared to HCs, patients with MDD showed lower interhemispheric dFCD variability in the inferior/middle frontal gyrus and decreased sFCD in the medial prefrontal cortex/anterior cingulate cortex and posterior cingulate cortex/precuneus in both intra- and interhemispheric comparisons. No significant correlations were found between any abnormal dFCD variance or sFCD at the intra- and interhemispheric levels and the severity of depressive symptoms. Our results suggest intra- and interhemispheric functional connectivity alterations in the dorsolateral prefrontal cortex and default mode network regions involved in cognition, execution and emotion. Furthermore, our study emphasizes the essential role of altered interhemispheric communication dynamics in the DLPFC in patients with MDD. These findings contribute to our understanding of the pathophysiology of MDD.

Compared to a charging scheduling and management problem characterized by predetermined trip assignment, this study takes bus and driver scheduling into account, and mealtime windows must be guaranteed as one of the major labor regulations. A discretized mixed-integer linear programming model is developed based on a single electric bus route. We aim to obtain fast and high-quality global solutions for this problem, and the model can be easily executed by bus operators by directly invoking an available optimization solver such as IBM ILOG CPLEX. We test our model on a real round-trip bus route. Numerical experiments show that CPLEX takes approximately 6 sec to obtain an optimal solution. The model can not only reasonably arrange daily trips for each electric bus and driver but also effectively determine the optimal charging schedule and management for an electric bus line. Besides, we analyze the sensitivity of the key parameters in the model. With the increase in the drivers’ maximum workload, the drivers’ average idle time decreases by approximately 11.25%. The objective value decreases by approximately 38.71% and 40.04% with increases in the battery capacity and fleet size, respectively, and the objective value increases by approximately 30.06% with the decrease in the initial battery driving range. In addition, we compare the effectiveness of our time discretization modeling method in solving the same case study to that from other similar studies, and the validity of our method can be verified by the calculation time. We also compare the computational efficiency of CPLEX in solving the same case study problem with and without implementing valid inequalities, and the computational efficiency of the valid inequality method is greatly improved. Finally, through the testing of a multiline network, the potential application of the model to a large-scale traffic network is verified.

In this paper, a three-dimensional chaotic system with a line equilibrium is studied, in which a single nonbifurcation parameter is used to control the amplitude and frequency. A variety of chaotic signals can be modified using the amplitude-frequency control switch. The realization of circuit simulation based on multisim further verifies the theoretical analysis. Finally, the method for encrypting color images is tested, and the process performance is valued. It shows that the novel chaotic oscillation has a promising application prospect in image encryption.

This paper uses the 5-five-minute high-frequency data of energy-listed companies in China's A-share market to extract the jump of energy stock prices and build a dynamic stock price jump complex network. Then, we analyze the clustering effect of the complex network. The research shows that the energy stock price jump is an important part of stock price volatility, and the complex network of energy stock jump risk has obvious time-varying characteristics. However, the infection problem of stock price jump risks needs specific analysis. China's coal industry has an important influence on the development of China's energy industry. According to the clustering analysis results of the network community, the clustering effect of the network community has time-varying characteristics. After October 2017, the clustering effect of the jumping risk of the coal industry and the new energy industry is obvious. The risk contagion within the new energy industry community is a key point for the development of the new energy industry.

In China, online sales continue to grow against the generally adverse effects of the COVID-19 pandemic on economic development. Although advertisers favor online targeted advertising for its precision, consumers may find it intrusive and avoid it. This study constructed a conceptual model based on Stimulus-Organism-Response theory, Approach-Avoidance Theory, and Brand Avoidance Theory to investigate the influence mechanism of consumers’ perceived risk on the avoidance behavior of online targeted advertising via an online survey. Collected 436 validated data was analyzed through structural equation method in AMOS statistical software. Results showed that the positively influenced advertising avoidance, and negative emotions mediated the relationship between perceived performance risk, time-loss risk, freedom risk, and advertising avoidance, but perceived privacy risk did not influence advertising avoidance through negative emotions. Perceived COVID-19 risk moderates the effect of negative emotions on advertising avoidance. The findings provide important insights for helping governments, advertisers and online platforms into which risk perceptions influence advertising avoidance, and suggests ways to mitigate consumers risk perceptions for the mutual benefit of brands and users.

Intern physicians are generally more burdened by stress than the general population. This cross-sectional study aimed to evaluate the current situation regarding burnout and explore its association with the self-evaluation of competence among Chinese dental interns. A self-administered anonymous survey was conducted on 91 dental interns in the Peking University School of Stomatology, from August 2019 to June 2020. It consisted of a psychological stress questionnaire, including burnout and self-evaluation of clinical competence. The Wilcoxon signed rank test was used to determine the differences between self-evaluation scores of clinical competence. Results showed average scores for emotional exhaustion, depersonalization, and personal accomplishment of 22.22 ± 9.04, 8.16 ± 5.21, and 36.08 ± 7.76, respectively. Dental clinical technology was considered more useful than other clinical competencies, and there was a correlation between its importance and the stress caused by its deficiency. Significant associations were found between stress due to a lack of dental clinical technology and high emotional exhaustion. Burnout was common among the dental interns, which may be a valuable finding. Among the six different aspects of clinical competence, “dental clinical technology” represented the most stressful item. Strengthening pre-clinical training and promptly conducting targeted training in the early clinical process may be considered as decompression measures.

This study examines the impact of top management team media exposure on corporate social responsibility and the moderating effect of TMT characteristics based on the upper echelons theory and stakeholder theory. Based on the observations of 5,352 firms between 2010 and 2019, multiple regression analysis is conducted to empirically test whether TMT media exposure can promote CSR. TMT media exposure is further divided into paper media and online media to reveal the impact of different types of TMT media exposure on CSR. Some robustness tests are also conducted to strengthen the regression results. The results found that a high level of TMT media exposure promotes social responsibility. In addition, the TMT power and political connections negatively moderate the relationship between TMT media exposure and CSR. The main contribution of this study is to develop a TMT media exposure model to assess the impact of TMT media exposure on CSR, providing a theoretical contribution to the existing literature and enriching the research in the CSR context from the perspective of the TMT characteristic moderating role.

This study adopted a positive psychology perspective to investigate positive emotion and foreign language enjoyment among Chinese as a second language learners in an emergency remote teaching context amid the COVID-19 pandemic. A set of 90 preparatory Chinese language students was assessed for their level of foreign language enjoyment using the Foreign Language Enjoyment Scale. Participles' scores on self-perceived language achievement and actual test scores were adopted as the measurement of their Chinese language proficiency. The results revealed that: CSL learners experienced high level of FL enjoyment in an online learning context, no significant correlation was found between FLE and leaners' actual language achievement nor between FLE and their self-perceived achievement, female learners showed higher FLE than male learners and gender was found to have a significant effect on FLE-Private, participants' geological location, i.e., whether in China or at home countries, significantly influenced their FLE, participants' regional group was not a significant predictor of FLE, and teacher-related variables and learner self-perceptions of achievement were strong predictors of FLE among CSL learners. The findings highlight the importance of teacher's role in an online learning environment and suggest that FLE may not boost performance in the short term for language beginners but is still conducive in the long run. Implications for both teachers and learners, and suggestions for future researches are provided.

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.