ObjectiveRetinal vein occlusion (RVO) is the second most common retinal vascular disorder after diabetic retinopathy, which is the main cause of vision loss. Retinal vein occlusion might lead to macular edema, causing severe vision loss. Previous neuroimaging studies of patients with RVO demonstrated that RVO was accompanied by cerebral changes, and was related to stroke. The purpose of the study is to investigate synchronous neural activity changes in patients with RVO.MethodsA total of 50 patients with RVO and 48 healthy subjects (...) with matched sex, age, and education were enrolled in the study. The ReHo method was applied to investigate synchronous neural activity changes in patients with RVO.ResultsCompared with HC, patients with RVO showed increased ReHo values in the bilateral cerebellum_4_5. On the contrary, patients with RVO had decreased ReHo values in the bilateral middle occipital gyrus, right cerebelum_crus1, and right inferior temporal gyrus.ConclusionOur study demonstrated that patients with RVO were associated with abnormal synchronous neural activities in the cerebellum, middle occipital gyrus, and inferior temporal gyrus. These findings shed new insight into neural mechanisms of vision loss in patients with RVO. (shrink)

This study examined the relationship between ethical leadership as perceived by employees and the family satisfaction of the employees’ spouses. It also considered the mediating role of the employees’ ethical leadership in the family domain as perceived by their spouses, and the moderating role of the employees’ identification with leader. The results, which were based on a sample of 193 employee–spouse dyads in China, indicated that employees’ perceptions of ethical leadership in the workplace positively influenced their spouses’ family satisfaction. Moreover, (...) employees’ ethical leadership in the family domain mediated this relationship. Furthermore, whereas identification with leader strengthened the relationship between the employees’ perceptions of ethical leadership in the workplace and their ethical leadership demonstrations in the family domain, it weakened the relationship between their ethical leadership demonstrations in the family domain and their spouses’ family satisfaction. The theoretical and managerial implications of these findings are discussed. (shrink)

To demonstrate how green innovation effectively occurs, this study examines the effects of green intellectual capital on GI from the perspective of green supply chain integration. Based on a natural-resource-based view and knowledge-based view, the authors constructed an intermediary model of GIC-GSCI-GI, and analyzed the effects of green absorptive ability and relationship learning ability as moderators. An empirical survey of 328 Chinese manufacturing companies was conducted. Our results indicate that three dimensions of GIC positively impact GI. The mediating effects of (...) internal and external GSCI exist in the relationship between GIC and GI. The moderating effects of GAA and RLA in these effects were also verified. Our study provides further empirical evidence for the relationship between GIC and GI, highlights the effects of companies’ internal and external abilities on GI, and suggests new ways and implementation contexts for GI. (shrink)

Background:When the contagious COVID-19 spread worldwide, the frontline staff faced unprecedented excessive work pressure and expectations of all of the society.Objective:The aim was to explore healthcare workers’ stress and influencing factors when caring for COVID-19 patients from an altruistic perspective.Methods:A cross-sectional, descriptive study was conducted in a tertiary hospital during the outbreak of COVID-19 between February and March 2020 in Wuhan, the capital city of Hubei province in China. Data were collected from 1208 healthcare workers. Descriptive statistics and multiple linear (...) regression were used to analyze the data.Ethical considerations:Research ethics approval (with the code of TJ-IRB20200379) was obtained from Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology. Written informed consent was also received from participants.Results:Less than 60% of participants chose moderate or severe stress on all stressors, indicating a low stress level among healthcare workers. The main source of stress among frontline healthcare workers caring for COVID-19 patients came from the fear of being infected, the fear of family members being infected, and the discomfort caused by protective equipment. Frontline staff who were nurses, were married, and had worked more than 20 days suffered higher stress, whereas rescue staff showed lower stress.Conclusion:The healthcare workers caring for patients with COVID-19 had low stress level, although they still had the fear of being infected or uncomfortable feeling caused by personal protective equipment. A low stress level among healthcare workers indicated their professional devotion and altruism during COVID-19 epidemic. Medical institutions and the government should continue to strengthen infection prevention measures and provide more comprehensive care involving families of frontline healthcare workers, especially nurses and married staff. It will be a lesson to other countries that awaking healthcare workers’ inside motivation and providing necessary support from government and society were significant. (shrink)

The two-dimensional coupled map lattice model has been extensively employed as the basis component for designing various schemes in the cryptography system due to its complicated chaotic dynamic behavior. In this study, we analyze the chaotic characteristics of the 2D CML model, such as the Lyapunov exponent, synchronization stability, bifurcation, and ergodicity. We then show that the chaotic sequences generated by the 2D CML model are random according to the NIST testing. Furthermore, we propose an image encryption scheme based on (...) the 2D CML model and Singular Value Decomposition. In our scheme, the SVD method is used to reduce the image storage, and the Red, Green, and Blue channels of a color image will be encrypted through confusion and diffusion. The simulation results, as well as the results of the comparison with other schemes, demonstrate that our scheme possesses outstanding statistics, excellent encryption performance, and high security. It has great potential for ensuring the security of digital images in real applications. (shrink)

ObjectiveCancer and its treatments affect patients’ fertility potential. This study examined the prevalence of reproductive concerns and their relationship with metacognitions among Chinese young adult female cancer survivors.MethodsA total of 318 YAFCS completed an online survey from March to December 2021. Participants reported sociodemographic characteristics, reproductive concerns and metacognitions. Reproductive concerns were measured using the Reproductive Concerns after Cancer scale, and metacognitions were measured by the Short Form of Metacognitions Questionnaire. We used Pearson correlation analysis to examine associations between metacognitions (...) and reproductive concerns across multiple domains and multivariable linear regression to determine the influencing factors of reproductive concerns.ResultsThe mean score of reproductive concern among YAFCS was 49.97 ± 12.52. A total of 57.9% of participants reported a high level of concern regarding at least one dimension of reproductive concerns, and they were most concerned about their child’s health and least concerned about partner disclosure of fertility status. We also found a moderate association between RCAC and MCQ-30 scores. In multivariate analyses, metacognitions, especially negative metacognitive beliefs had an impact on reproductive concerns among YAFCS.ConclusionHigher reproductive concerns were associated with higher metacognitions among YAFCS, especially with negative metacognitive beliefs. Oncology professionals should pay attention to assessing reproductive concerns in patients who want to have children or who have no children. Moreover, metacognitive beliefs may be an intervention target for alleviating reproductive concerns among YAFCS. (shrink)

We have refined entropy theory to explore the meaning of the increasing sequence data on nucleic acids and proteins more conveniently. The concept of selection constraint was not introduced, only the analyzed sequences themselves were considered. The refined theory serves as a basis for deriving a method to analyze non-coding regions (NCRs) as well as coding regions. Positions with maximal entropy might play the most important role in genome functions as opposed to positions with minimal entropy. This method was tested (...) in the well-characterized coding regions of 12 strains of Classical Swine Fever Virus (CSFV) and non-coding regions of 20 strains of CSFV. It is suitable to analyze nucleic acid sequences of a complete genome and to detect sensitive positions for mutagenesis. As such, the method serves to formulate the basis for elucidating the functional mechanism. (shrink)

Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function (...) was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.Trial Registration: Clinicaltrials.gov, NCT02880462. Registered August 26, 2016. (shrink)

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the (...) right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs. (shrink)

Background: The pregnancy and psychological status of infertile couples has always been a concern, but there is no clear evidence for the efficacy of psychotherapy for infertile couples. This study aimed to summarize the current evidence of the effects of psychotherapy on psychological and pregnancy outcomes for infertile couples. Method: We searched Ovid MEDLINE, Ovid EMbase, The Cochrane Library, and Web of Science for articles published from 1946 to June 26, 2020. The pregnancy outcomes, psychological outcomes, and acceptability were involved (...) in the study. Results: Overall, 29 studies with a combined total of 3,522 adult participants were included in the meta-analysis. Compared with a placebo, psychotherapy was associated with the pregnancy rate [risk ratio = 1.43, 95% CI [1.07, 1.93]], total psychological scales associated with infertility [standardized mean difference = −0.33 95% CI [−0.63, −0.02]], subsymptoms of psychological scores using the 28-item version of GHQ, and the integrative body–mind–spirit ; total psychological scales associated with infertility using other treatments and more than a month; and anxiety using BMS had significant statistical significance. The funnel plots of all outcomes were approximately symmetrical, and no significant publication bias was found. Conclusions: The study showed that psychotherapy can lead to improvements in the pregnancy rate for infertile patients, especially for patients receiving assisted fertility. In addition, it may help improve total psychological scales associated with infertility and depression. CBT and BMS play an important role in improving rate of pregnancy, and BMS is associated with reducing anxiety. Although psychological interventions had limited effects on the pregnancy outcomes of infertility, our study still recommended that psychotherapies, in particular CBT and BMS, were applied to the therapeutic regimen for infertility, especially for patients receiving assisted fertility. (shrink)

With the rapid development of Internet of Things technology, RFID technology has been widely used in various fields. In order to optimize the RFID system hardware deployment strategy and improve the deployment efficiency, the prediction of the RFID system identification rate has become a new challenge. In this paper, a neighborhood rough set and random forest combination model is proposed to predict the identification rate of an RFID system. Firstly, the initial influencing factors of the RFID system identification rate are (...) reduced using neighborhood rough set theory combined with the principle of heuristic attribute reduction of neighborhood weighted dependency, thus obtaining a kernel factor subset. Secondly, a random forest prediction model is established based on the kernel factor subset, and a confusion matrix is established using out-of-bag data to evaluate the prediction results. The test is conducted under the constructed RFID experimental environment, whose results showed that the model can predict the identification rate of the RFID system in a fast and efficient way, and the classification accuracy can reach 90.5%. It can effectively guide the hardware deployment and communication parameter protocol setting of the system and improve the system performance. Compared with BP neural network and other prediction models, NRS-RF has shorter prediction time and faster calculation speed. Finally, the validity of the proposed model was verified by the RFID intelligent archives management platform. (shrink)

To investigate the relationships among child psychological abuse and neglect, children’s learning engagement, family socioeconomic status, and children’s academic achievement, 271 children and their parents participated in this study with a longitudinal design. Results revealed that learning engagement at T1 mediated the relationship between CPAN at T1 and academic achievement at T2 when gender, age, grade, and academic achievement at T1 were under control. Family SES at T1 moderated the relationship between children’s learning engagement at T1 and academic achievement at (...) T2. The association between learning engagement and academic achievement was stronger among children from lower family SES. Our findings highlighted the negative impact of CPAN and the critical role of learning engagement in children’s academic achievement, especially for those from low SES families. (shrink)

This paper proposes a new system whose potential function is with three types of asymmetric potential wells, driven by trichotomous noise. Firstly, the three types of asymmetric bistable system are described in detail, and the changes of asymmetric bistable system potential function under different asymmetric factors are analyzed. Secondly, the effect of potential function parameters, asymmetric factorα, noise intensity D, and the probability of particle transition q is discussed, using numerical simulation. The detection effects of traditional symmetric SR and three (...) types of asymmetric SR are observed and compared under the driving of trichotomous noise and periodic signals. The mean of signal-to-noise ratio gain is the indicator of the system's effectiveness on enhancing weak signal. The results indicate that it can make the detection effect of the asymmetric system better than that of the traditional bistable system by adjusting the parameters of the asymmetric stochastic resonance system and trichotomous noise. (shrink)

The present study investigated the configuration effect of human capital, social capital, and psychological capital on job performance. The human capital questionnaire, social capital scale, psychological capital scale, and job performance scale were used to survey 458 employees. Results revealed that four antecedent configurations could achieve high task performance, and three antecedent configurations can achieve high contextual performance. The high job performance driving path was characterized by “all roads lead to Rome.” Human capital, social capital, and psychological capital affected job (...) performance in the form of configuration, which reflected the asymmetric causal relationship. (shrink)

本书立足于儒家大师的经典文本, 通过学术性的分析论证, 集中探讨了孔孟荀、董仲舒、宋明儒学以及当代儒学的核心观念, 运用学术批判方法指出了儒家伦理陷入的深度悖论. 本书在批判儒家伦理、正当与善的关系、平等等问题上的一些见解和论证, 为作者在国内外学术界首次明确提出, 具有鲜明的原创性.

The development and application of artificial intelligence (AI) technology has raised many concerns about privacy violations in the public. Thus, privacy-preserving computation technologies (PPCTs) have been developed, and it is expected that these new privacy protection technologies can solve the current privacy problems. By not directly using raw data provided by users, PPCTs claim to protect privacy in a better way than their predecessors. They still have technical limitations, and considerable research has treated PPCTs as a privacy-protecting tool and focused (...) on possible technical improvements. In this article, we argue that PPCTs cannot effectively protect privacy in the narrow sense due to their technical limitations. Moreover, although these shortcomings could be remedied, they still fall into a paradox because their aim is to protect privacy, but they could reveal private information from users. This paradox of privacy protection not only aggravates the social impact arising from AI privacy issues but may also make the current privacy protection lose its meaning, resulting in a situation in which privacy protection is useless. (shrink)

Major events such as the COVID-19 pandemic, Olympic Games, and G20 Summit bring about supplier disruption risks and challenges to supply chain management. To help deal with these risks, a virtual dual-sourcing production-inventory system can be deployed. In this paper, we study such a system which consists of a raw material supplier, a manufacturer, and a virtual dual-sourcing contingency supplier. The manufacturer needs to determine the production, procurement, and inventory plan of raw materials. When its supplier is interrupted, the manufacturer (...) may need to adjust the production and inventory plan and work with the contingency supplier. We develop a system dynamics method to simulate the operations in this production-inventory system to identify the approximately optimal order-up-to-level inventory policies. We find that the virtual dual production-inventory strategy can be the optimal contingency policy to deal with supplier dynamic disruption risks. Furthermore, for disruption risk with low frequency and long duration, the manufacturer should increase the safety inventory level before the disruption. Otherwise, it should increase the safety inventory level in every cycle. (shrink)

In recent years, somatosensory interaction technology, represented by Microsoft’s Kinect hardware platform, has been widely used in various fields, such as entertainment, education, and medicine. Kinect technology can easily capture and record behavioral data, which provides new opportunities for behavioral and psychological correlation analysis research. In this paper, an automatic decision-style recognition method is proposed. Experiments involving 240 subjects were conducted to obtain face data and individual decision-making style score. The face data was obtained using the Kinect camera, and the (...) decision-style score were obtained via a questionnaire. To realize automatic recognition of an individual decision-making style, machine learning was employed to establish the mapping relationship between the face data and a scaled evaluation of the decision-making style score. This study adopts a variety of classical machine learning algorithms, including Linear regression, Support vector machine regression, Ridge regression, and Bayesian ridge regression. The experimental results show that the linear regression model returns the best results. The correlation coefficient between the linear regression model evaluation results and the scale evaluation results was 0.6, which represents a medium and higher correlation. The results verify the feasibility of automatic decision-making style recognition method based on facial analysis. (shrink)

Abnormal behaviour detection algorithm needs to conduct behaviour analysis on the basis of continuous video inclination tracking, and the robustness of the algorithm is reduced for the occlusion of moving targets, the occlusion of the environment, and the movement of targets with the same colour. For this reason, the optical flow information between RGB images and video frames is used as the input of the network in view of group behaviour. Then, the direction, velocity, acceleration, and energy of the crowd (...) were weighted and fused into a global optical flow descriptor. At the same time, the crowd trajectory map is extracted from the original image of a single frame. Following, in order to realize the detection of large displacement moving target and solve the problem that the traditional optical flow algorithm is only suitable for the detection of displacement moving target, a video abnormal behaviour detection algorithm based on the double-flow convolutional neural network is proposed. The network uses two network branches to learn spatial dimension information and temporal dimension information, respectively, and uses short- and long-time neural network to model the dependency relationship between long-time video frames, so as to obtain the final behaviour classification results. Simulation test results show that the proposed method can achieve good recognition effect on multiple datasets, and the performance of abnormal behaviour detection can be significantly improved by using interframe motion information. (shrink)

With the development of artificial intelligence technologies, it is possible to use computer to read digital medical images. Because Alzheimer’s disease has the characteristics of high incidence and high disability, it has attracted the attention of many scholars, and its diagnosis and treatment have gradually become a hot topic. In this paper, a multimodal diagnosis method for AD based on three-dimensional shufflenet and principal component analysis network is proposed. First, the data on structural magnetic resonance imaging and functional magnetic resonance (...) imaging are preprocessed to remove the influence resulting from the differences in image size and shape of different individuals, head movement, noise, and so on. Then, the original two-dimensional ShuffleNet is developed three-dimensional, which is more suitable for 3D sMRI data to extract the features. In addition, the PCANet network is applied to the brain function connection analysis, and the features on fMRI data are obtained. Next, kernel canonical correlation analysis is used to fuse the features coming from sMRI and fMRI, respectively. Finally, a good classification effect is obtained through the support vector machines method classifier, which proves the feasibility and effectiveness of the proposed method. (shrink)

This paper addresses the robust output feedback model predictive control schemes for networked control systems with input quantization. The logarithmic quantizer is considered in this paper, and the sector bound approach is applied, which appropriately treats the quantization error as a sector-bounded uncertainty. The presented method involves an offline designed state observer using linear matrix inequality and online robust output feedback MPC algorithms which optimize one free control move followed by the output feedback using the estimated state. Moreover, due to (...) the uncertainty of estimation error, a technique of refreshing the bound of estimation error which involves the quantization error is provided so as to guarantee the recursive feasibility of the optimization problem. The proposed MPC schemes inherit the characteristics of the synthesis approach of MPC, guaranteeing the recursive feasibility of the optimization problem and the stability of a closed-loop system, and explicitly account for quantization error. Two simulation examples are given to illustrate the effectiveness of the proposed methods. (shrink)

Information-sharing behavior is affected by identity recognition perception. The current study aims to delve into the impact of familiarity and anonymity on information-sharing behavior, and the mediating role of intrinsic motivations on WeChat Moments. We hypothesized a mediator role of intrinsic motivations in the relationship between an individual’s perceptions and information sharing. Based on the self-determination theory, a model was created and tested using a sample of 531 frequent users. In this study, these users were asked to use WeChat Moments, (...) the most popular mobile private social networking site in China. The results demonstrate the significance of familiarity and identifiability in an interpersonal relationship, when using social networking sites. Moreover, the influence of perceived anonymity on information-sharing behavior, which is entirely mediated by intrinsic motivation has been validated from an empirical perspective. Our findings extend previous studies by showing the totally mediated effect of perceived anonymity on information-sharing behavior on WeChat Moments and the influential mechanism of intrinsic motivation. The results will inform researchers about the importance of incorporating the interpersonal structural features and intrinsic motivation of social networking sites into future studies on online information-sharing behavior. Important ways to promote attention and share information involve building a familiar relationship with communities and equipping oneself with off-line relations. Final indications for future developments are provided, with a special emphasis on the development of these findings in various social networking sites contexts. (shrink)

Globalization and informatization are reshaping human life and social behaviors. The purpose is to explore the worldwide strategies to cultivate international talents with a global vision. As a global language with the largest population, English, and especially its learning effect, have always been the major concerns of scholars and educators. This work innovatively studies the combination of immersion-based English teaching with virtual reality technology. Then, based on the experimental design mode, 106 students from a Chinese school were selected for a (...) quasi-experimental study for 16 weeks. The collected data were analyzed by computer statistical software, and hypotheses are verified. The results showed that there is a significantly positive correlation between VR and immersion-based language teaching. There is a significantly positive correlation between immersion-based language teaching and academic achievement, and VR is positively correlated with learning outcome. Compared with other state-of-art research methods, this work modifies the students’ oral test through the analysis and comparison with the system database, and the students’ learning effect is greatly improved. Finally, some suggestions are put forward according to the research results to provide an experimental reference for English teachers and future linguistics teaching. (shrink)

Dragon boat sport is a traditional activity in China. In recent years, dragon boat sport has become more and more popular around the world. In order to face more challenges, it is urgent for athletes to enhance their own strength. Scientific training methods are particularly important for athletes, and accurate training data are the basis to support scientific training. Traditional mathematical statistic methods neither can sample signals accurately nor can they do real-time analysis and feedback the characteristics to each athlete. (...) In this paper, we use the wearable device with a triaxial accelerometer and heart rate sensor builtin to sample the speed signals and heart rate signals of athletes in various stages of men’s 1000m straight race. Based on the complex network theory, we regard the 23 dragon boat athletes in the dragon boat race as 23 nodes so as to establish a network with 23 nodes and reflect the importance of nodes by measuring the impact of node deletion on the results of the race. The neural network multilayer perceptron model is used for training to obtain the optimal combined value with speed and heart rate for each race stage. The optimal value will be used in the simulated race as the target value to verify if it can help to improve the training efficiency. Experimental results show that the optimal value obtained by this method has a positive effect on the results of the dragon boat race which is beneficial to sports training and tactics planning. (shrink)

GraphicalPatients with early- to middle-stage PD were enrolled for C-Gait assessment and traditional walking ability assessments. The correlation of C-Gait assessment and traditional walking tests were studied. Two models were established based on C-Gait assessment and traditional walking tests to explore the value of C-Gait assessment in predicting freezing of gait.ObjectiveEfficient methods for assessing walking adaptability in individuals with Parkinson’s disease are urgently needed. Therefore, this study aimed to assess C-Gait for detecting freezing of gait in patients with early- to (...) middle-stage PD.MethodPeople with PD diagnosis were recruited from April 2019 to November 2019 in Beijing Rehabilitation Hospital. The participants performed six items of walking adaptability on an instrumented treadmill augmented with visual targets and obstacles. The patient’s walking adaptability was evaluated by C-Gait assessment and traditional walking tests, and FOG-related indexes were collected as outcome measures. Two discriminant models were established by stepwise discriminant analysis; area under the receiver operating characteristic curve was used to validate the models.ResultIn total, 53 patients were included in this study. Most C-Gait assessment items had no or low correlations with traditional walking tests. The obstacle avoidance and speed of adaptation items could lead to FOG with high sensitivity. In addition, the C-Gait assessment model had slightly better discrimination of freezers from non-freezers compared with traditional walking test models ; specifically, obstacle avoidance and speed of adaptation have uniquely discriminant potential.ConclusionC-gait assessment could provide additional value to the traditional walking tests for PD. Gait adaptability assessment, as measured by C-Gait, may be able to help identify freezers in a PD population. (shrink)

It is important for energy enterprises to research on the investment potential of the energy markets in countries along the “Belt and Road,” which can help them optimize the regional investment structure, reduce investment risks, and conform to the development trend of “going global.” Therefore, we construct an investment potential assessment system of 29 indexes including five dimensions: politics, economy, society, energy, and cooperation and assess energy investment potential of 48 sample countries along the “Belt and Road” using principal component (...) analysis to provide reference meanings for energy enterprises. The results show that the assessment results of investment potential are affected by a combination of multiple indexes. In addition, compared with Central Asia and South Asia, which have weak economic foundations and greater political and legal risks, the investment potential of Central and Eastern Europe and some emerging economies in Southeast Asia is higher. (shrink)

As one of the important 21st-century skills, collaborative problem solving (CPS) has caught much attention in the assessment area. Two initiative approaches have been created: the human-to-human and human-to-agent modes. Between the two modes, the human-to-human interaction is much closer to the real-world situation and its process stream data can reveal more detailed information about the cognitive processes. In order to measure CPS ability effectively by this mode, how to extract indicators from the data and model it is crucial, while (...) the existing methods all have some disadvantages. In the present study, we proposed a new paradigm for extracting indicators and modeling the dyad data in the human-to-human mode. Specifically, both individual and group indicators were extracted from the data stream, which served as evidence for demonstrating CPS skills. In addition, a within-item multidimensional Rasch model was used to fit the dyad data. To test the validity of the paradigm, we developed five tasks following the asymmetric mechanism and integrated them into an online testing platform. Four hundred thirty-four students from China participated in the assessment and the online platform recorded their crucial actions with time stamps. The new paradigm was used to deal with the generated process stream data. Results showed that the model fitted well. The item parameter estimates and fitting indexes were acceptable, and students were well differentiated. In general, the new paradigm of extracting indicators and modeling the dyad data is feasible for improving the human-to-human assessment of CPS. Finally, the limitations of the current study and further research directions are discussed. (shrink)

People have three cognitive representations of the self, namely, the individual, relational, and collective selves, which are indispensable components of selfhood but not necessarily given equal preference. Previous studies found that people displayed varied self-hierarchy in miscellaneous tasks involving different research materials that had pre-existing learned associations established over long periods of time. Therefore, this study tries to explore a purer self-hierarchy without the influence of research materials, using perceptual matching tasks. The behavioral and event-related potentials’ findings showed that people (...) recognized information association with their individual self faster compared with their relational and CS. Smaller N2, stronger P3 and late positive complex amplitudes were evoked during IS compared with RS and CS. However, the three selves evoked equal P2 amplitudes at the early processing stage. Moreover, CS showed a weaker advantage than RS, demonstrating a longer reaction time, lower d prime, and weaker P3 and LPC amplitudes in the parietal region. Overall, self-hierarchy during simple perceptual processing manifested as IS > RS > CS at the late processing stage but manifested as IS = RS = CS at the early processing stage. Self-hierarchy varies according to the processing stage, even without meaningful information and during the simple perception processing. This result provides direct evidence that all selves can be tagged with neutral actions, which would fit the idea of an organism attuned to self-survival at multiple processing levels. (shrink)

During the COVID-19 pandemic, online education has become an important approach to learning in the information era and an important research topic in the field of educational technology as well as that of education in general. Teacher–student interaction in online education is an important factor affecting students’ learning performance. This study employed a questionnaire survey to explore the influence of teacher–student interaction on learning effects in online education as well as the mediating role of psychological atmosphere and learning engagement. The (...) study involved 398 college students studying at Chinese universities as the research object. Participants filled out a self-report questionnaire. The study found that the level of teacher–student interaction positively affected students’ learning effects. The psychological atmosphere mediated the positive effect of the level of teacher–student interaction on learning effects with mediating effect value of 0.1248. Learning engagement mediated the positive effect of teacher–student interaction on learning effects with a mediating effect value of 0.1539. The psychological atmosphere and learning engagement play a chain-mediating role in the mechanism of teacher–student interaction affecting students’ learning effects; that is, teacher–student interaction promotes students’ learning engagement by creating a good psychological atmosphere, which, in turn, influences learning effects. The mediating effect value was 0.0403. The results indicate that teacher–student interaction not only directly affects students’ learning effects but also influences students’ learning effects through the mediating effect of the psychological atmosphere and learning engagement. (shrink)