Multiple goals balancing is an important but not yet fully validated dimension of complex problem solving (CPS). The present study used process data to explore how solvers clarify goals, set priorities, and balance conflicting goals. We extracted behavioral indicators of goal pursuit from the log data of 3,201 students on the third subtask of the “Ticket” task in the PISA 2012 CPS test. Cluster analysis was used to identify 10 groups that varied in goal pursuit behavior. Logistics and least-squares regression (...) analysis were used to explore how goal pursuit affected task scores and CPS proficiency. The results showed that competent solvers clarified goals and weighed priorities more effectively. They also made trade-offs between conflicting goals. The importance of theoretically-driven log data analysis and coping strategies in the face of multiple goals conflict scenarios was discussed. (shrink)

Objective: The COVID-19 epidemic has generated great stress throughout healthcare workers. The situation of HCWs should be fully and timely understood. The aim of this meta-analysis is to determine the psychological impact of COVID-19 pandemic on health care workers.Method: We searched the original literatures published from 1 Nov 2019 to 20 Sep 2020 in electronic databases of PUBMED, EMBASE and WEB OF SCIENCE. Forty-seven studies were included in the meta-analysis with a combined total of 81,277 participants.Results: The pooled prevalence of (...) anxiety is 37% from 44 studies. Depression is estimated in 39 studies, and the pooled prevalence of depression is 36%. There are 10 studies reported the prevalence of insomnia, and the overall prevalence of insomnia is 32%. The subgroup analysis showed a higher incidence of anxiety and depression among women and the frontline HCWs compared to men and non-frontline HCWs respectively.Conclusions: The COVID-19 pandemic has caused heavy psychological impact among healthcare professionals especially women and frontline workers. Timely psychological counseling and intervention ought to be implemented for HCWs in order to alleviate their anxiety and improve their general mental health. (shrink)

Pain has not only sensory, but also emotional and cognitive, components. Some studies have explored the effect of pain on time perception, but the results remain controversial. Whether individual pain-related emotional and cognitive factors play roles in this process should also be explored. In this study, we investigated the effect of electrical stimulation–induced pain on interval timing using a temporal bisection task. During each task session, subjects received one of five types of stimulation randomly: no stimulus and 100 and 300 (...) ms of non-painful and painful stimulation. Pain-related emotional and cognitive factors were measured using a series of questionnaires. The proportion of “long” judgments of a 1,200-ms visual stimulus duration was significantly smaller with 300 ms painful stimulation than with no stimulus and 100 ms and 300 ms non-painful stimulation. The point of subjective equality did not differ among sessions, but the average Weber fraction was higher for painful sessions than for no-stimulus session. The pain fear score correlated positively with the PSE under 100 ms non-painful and painful and 300 ms painful stimulation. Pain catastrophizing and pain anxiety scores correlated significantly with the WF under no stimulus and 100 ms non-painful stimulation, respectively. These results suggest that electrical stimulation–induced pain affects temporal sensitivity, and that pain-related emotional and cognitive factors are associated with the processing of time perception. (shrink)

ObjectivesAbnormal brain function in ASD patients changes dynamically across developmental stages. However, no one has studied the brain function of prepubertal children with ASD. Prepuberty is an important stage for children’s socialization. This study aimed to investigate alterations in local spontaneous brain activity in prepubertal boys with ASD.Materials and MethodsMeasures of the amplitude of low-frequency fluctuations and regional homogeneity acquired from resting-state functional magnetic resonance imaging database, including 34 boys with ASD and 49 typically developing boys aged 7 to 10 (...) years, were used to detect regional brain activity. Pearson correlation analyses were conducted on the relationship between abnormal ALFF and ReHo values and Autism Diagnostic Observation Schedule and Autism Diagnostic Interview-Revised scores.ResultsIn the ASD group, we found decreased ALFF in the left inferior parietal lobule and decreased ReHo in the left lingual gyrus, left superior temporal gyrus, left middle occipital gyrus, and right cuneus. There were negative correlations between ReHo values in the left LG and left STG and the ADOS social affect score and a negative correlation between ReHo values in the left STG and the calibrated severity total ADOS score.ConclusionBrain regions with functional abnormalities, including the left IPL, left LG, left STG, left MOG, and right cuneus may be crucial in the neuropathology of prepubertal boys with ASD. Furthermore, ReHo abnormalities in the left LG and left STG were correlated with sociality. These results will supplement the study of neural mechanisms in ASD at different developmental stages, and be helpful in exploring the neural mechanisms of prepubertal boys with ASD. (shrink)

For understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy method. Compared to the benchmark methods in the six different empirical networks, the IIE method has been found with a better performance on Kendall’s Tau and imprecision function under (...) the Susceptible Infected Recovered model. Especially in the Facebook network, Kendall’s Tau can grow by 120% as compared with the original IE method. And, there is also an equally good performance in the comparative analysis of imprecise functions. The imprecise functions’ value of the IIE method is smaller than the benchmark methods in six networks. (shrink)

The vigorous development of online education has produced massive amounts of education data. How to mine and analyze education big data has become an urgent problem in the field of education and big data knowledge engineering. As for the dynamic learning data, knowledge tracing aims to track learners’ knowledge status over time by analyzing the learners’ exercise data, so as to predict their performance in the next time step. Deep learning knowledge tracking performs well, but they mainly model the knowledge (...) components while ignoring the personalized information of questions and learners, and provide limited interpretability in the interaction between learners’ knowledge status and questions. A context-aware attentive knowledge query network model is proposed in this paper, which combines flexible neural network models with interpretable model components inspired by psychometric theory. We use the Rasch model to regularize the embedding of questions and learners’ interaction tuples, and obtain personalized representations from them. In addition, the long-term short-term memory network and monotonic attention mechanism are used to mine the contextual information of learner interaction sequences and question sequences. It can not only retain the ability to model sequences, but also use the monotonic attention mechanism with exponential decay term to extract the hidden forgetting behavior and other characteristics of learners in the learning process. Finally, the vector dot product is used to simulate the interaction between the learners’ knowledge state and questions to improve the interpretability. A series of experimental results on 4 real-world online learning datasets show that CAKQN has the best performance, and its AUC value is improved by an average of 2.945% compared with the existing optimal model. Furthermore, the CAKQN proposed in this paper can not only track learners’ knowledge status like other models but also model learners’ forgetting behavior. In the future, our research will have high application value in the realization of personalized learning strategies, teaching interventions, and resource recommendations for intelligent online education platforms. (shrink)

The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation or data augmentation. Here, we proposed a DA method for the motor imagery EEG signal called brain-area-recombination. For the BAR, each sample was first separated into two ones by left/right brain channels, and the artificial samples were generated by (...) recombining the half-samples. We then designed two schemas corresponding to the single- and multi-subject scenarios. Extensive experiments using the classifier of EEGnet were conducted on two public datasets under various training set sizes. In both schemas, the BAR method can make the EEGnet have a better performance of classification. To make a comparative investigation, we selected two common DA methods, and the BAR method beat them. Further, using the proposed BAR for augmentation, EEGnet achieved up to 8.3% improvement than a typical decoding algorithm CSP-SVM, note that both the models were trained on the augmented dataset. This study shows that BAR usage can significantly improve the classification ability of deep learning to MI-EEG signals. To a certain extent, it may promote the development of deep learning technology in the field of BCI. (shrink)

Background: Previous studies have found that alexithymia plays an important role in the pathogenesis of Internet addiction. However, the effect of alexithymia on both metacognition and Internet addiction has yet to be examined.Methods: The Toronto Alexithymia Scale, Metacognition Questionnaire, and Internet Addiction Test were used to assess a sample of 356 college students. A parallel mediator effect analysis was applied to test the hypothesis that metacognition mediates the relationship between alexithymia and Internet addiction.Results: The parallel multiple mediator models showed that (...) alexithymia predicted the five dimensions of metacognition and Internet addiction, and that three dimensions—cognitive confidence, positive beliefs about worry, and the need to control thoughts—partially mediated this relationship.Conclusion: Alexithymia could directly and indirectly predict Internet addiction via metacognition. (shrink)

Aiming to realize rapid and efficient three-dimensional identification of substation equipment, this article proposes a new method in which the 3D identification of substation equipment is based on K-nearest neighbor classification of subspace feature vector. First of all, the article uses octree encoding to reduce and denoise the point cloud data obtained by a 3D laser scanner. Secondly, position calibration and size standardization are used for the point cloud after pretreatment. Then, the normalized point cloud is divided into a number (...) of cubes with same size. The cosine of the angle between the positive direction of z axis and a vector from the global centroid of the point cloud to the centroid of each subspace is regarded as the feature of the subspace. All cosines of subspaces constitute the feature of the point cloud. Finally, we classify the subspace feature vector by using the KNN algorithm and improve classification accuracy by using the particle swarm optimization algorithm. The simulation results show that the identification accuracy of the proposed method for unknown substation equipment is about 90% and the proposed method is applicable to low-degree losses. Apparently, this method can accurately identify 3D substation equipment. At the same time, increasing the number of subspaces will improve the accuracy; however, it will increase the recognition time. (shrink)

Urban inclusive green growth (UIGG) refers to the synergetic enhancement of the economy, the environment, and the society in a city. Achieving such enhancement requires addressing a series of problems in the development of urbanization, such as unemployment, lack of access to education, insufficient medical resources, inequity, and environmental pollution. As firms are critical to city development and urbanization, whether they practice corporate social responsibility (CSR) plays a crucial part in UIGG. In this study, we focus on Chinese cities as (...) examples of UIGG and Chinese listed companies as CSR engagers, employing matched data on Chinese listed companies and cities to investigate how CSR affects UIGG. Specifically, the empirical results of a high-dimensional fixed effect model indicate that CSR significantly promotes UIGG. This finding remains valid after a set of robustness checks, including instrumental variable (IV) regression. CSR can promote UIGG by positively influencing enterprises’ economic performance, innovation, and employment. To promote firms’ substantive CSR actions, the government of Jiangsu Province, China, launched a pilot policy for CSR promotion by issuing an official guidance document, which can be considered a quasi-natural experiment to test the causality between CSR and UIGG. We find that the CSR pilot significantly promoted UIGG. The heterogeneity test results indicate that the influence of CSR on UIGG varies based on the audit company, the nature of the enterprise, and the structure of corporate leadership. (shrink)

Culture is the most basic cause of a person’s wants and behavior. Country, like China, who has such a long history, has rich culture background. So it is very critical for international cooperates who want to do business in China to know about Chinese culture and how it works to buyers’ behavior. Starting from Chinese culture in Marketing context, this paper discusses how culture influence buyers’ behavior in Chinese Market.

In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we (...) can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system. (shrink)

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. (shrink)

Public health emergencies can trigger individual death anxiety. Most previous studies focus on the negative effects of death anxiety via the Western materialistic view, neglecting both the positive aspects of death anxiety within the Chinese cultural background and the positive effects of death anxiety upon environmental consumption. By implementing the unique Chinese cultural background for the concepts of justice and interests, this study explores the positive influence of individual death anxiety on altruistic environmental consumption during the COVID-19 crisis by analyzing (...) personal life reviews and other sources. The results show that under the guidance of the correct concept of justice and benefit, individuals with high death anxiety during the epidemic period not only enhance their self-esteem through positive self-perception and social evaluation, but they are more inclined to benefit from other environmental consumption behaviors and attain a symbolic self-survival; and during the epidemic period, mental resilience, as a transformation mechanism of external defense and the internal growth of death psychology, can directly affect altruistic environmental consumption by consumers without relying on external standards. In the context of the Chinese culture’s concept of justice and interests, this study enriches the knowledge of fear management theory and the positive impact of death anxiety on environmental consumption. The introduction of mental resilience as a boundary condition has important theoretical and practical significance within the study of consumer behavior in public health emergencies and post-epidemic economic recovery. (shrink)

Physarum polycephalum, a unicellular and multiheaded slime mould, can form highly efficient networks connecting separated food sources during the process of foraging. These adaptive networks exhibit a unique characteristic in that they are optimized without the control of a central consciousness. Inspired by this phenomenon, we present an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to overcome the limited abilities of the individual robots. The task faced by the robots consists in the (...) exploration of an unknown environment in order to find a path between two distant target areas. For the proposed algorithm, we experimentally present robustness tests and obstacle tests conducted to analyse the performance of our algorithm and compare the proposed algorithm with other swarm robot foraging algorithms that also focus on the path formation task. This work has certain significance for the research of swarm robots and Physarum polycephalum. For the research of swarm robotics, our algorithm not only can lead multirobot as a whole to overcome the limitations of very simple individual agents but also can offer better performance in terms of search efficiency and success rate. For the research of Physarum polycephalum, this work is the first one combining swarm robots and Physarum polycephalum. It also reveals the potential of the Physarum polycephalum foraging principle in multirobot systems. (shrink)

GIS is important equipment in the substation system in a complex microgrid network. Due to the long-term service in harsh operation environments, the electrical performance of GIS equipment will be seriously affected. Therefore, the regular maintenance of GIS equipment in the substation system is a routine task so as to ensure the normal operation of the microgrid networks. The traditional method relies on manual labor, where not only with the low operation efficiency but also regarding some maintenance, labors cannot reach (...) the inside of the GIS equipment, which seriously restricted the completion of GIS equipment maintenance operation. Based on the above analysis, a basic configuration of a GIS equipment maintenance robot with smart structure, convenient control, and stable motion characteristic has been proposed in this paper. Through the optimization design of the chassis adsorption system, the GIS inspection robot can achieve hanging and vertical adsorption inside the GIS equipment and some special motion status. In this way, the entire GIS equipment can be inspected without blind spots. Through establishing the mechanical model of the GIS inspection robot under the hanging and vertical motion state, the robustness and stability of the GIS inspection robot in the special status have been analyzed, and the corresponding GIS inspection robot robust stability motion control method has also been proposed. Finally, through the integrated design of mechanical system and hardware and software control system, the GIS inspection robot physical prototype system has been developed and the maintenance operation experiment has been carried out in Hunan Electric Power Company Maintenance Company through simulating the internal GIS equipment. The physical prototype can realize the basic movement and special movement in internal GIS equipment without any blind spots and complete the inspection task of GIS equipment operation; the movement of GIS robot is dexterous and stable in the whole operation process, which has strong robust stability. The research of GIS inspection robot in the complex microgrid networks has important theoretical significance and practical application value for the intelligent operation and maintenance management of substation system in complex microgrid networks. (shrink)

Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent “complexity loss” in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory (...) steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments. (shrink)

本書從思想史脈絡的溯源，立足在孟學發展史上之歷史關鍵點，以宋／清孟學發展轉折切入，以朱熹／戴震做為研究對象，探究二家思想的關聯性，並從西方詮釋學的新視野研究兩家詮釋殊異之因；透過朱熹與戴震二位理學大家 ，釐清由宋至清的孟學系譜，勾勒出孟學何以能從宋明理學「向內體證理路」轉而趨向清代義理「向外道德實踐」的不同蘊趣。【秀威資訊科技股份有限公司製作】.

本書系統總結了2016年順義區社會建設成果，在區級層面出版社會建設藍皮書，是一個創新。本書的出版，將有助於系統梳理順義區社會建設的經驗，進一步推進全區社會治理體系建設，促進全區社會治理能力現代化，更好 地服務於北京市城市戰略定位、優化提升首都核心功能，助力構建首都有效的超大城市治理體系，加快建設國際一流的和諧宜居之都進程。.