Previous studies have demonstrated positive correlations between children’s interpersonal trust and social adjustment. However, the psychological mechanism underlying this effect is still unclear. The current study tested the indirect roles of teacher–student relationships from both students’ and teachers’ perspectives in a Chinese context. In total, 709 pupils from grade three to grade five, and their 17 head teachers from a Chinese public primary school participated in this study. The Children’s Generalized Trust Beliefs Scale, Social Adjustment Scale for Children and Adolescents, (...) and Teacher–Student Relationship Questionnaire were used in this study. All these variables were correlated with each other. Structural equation models showed that the interpersonal trust indirectly influenced social adjustment through the teacher–student relationship from students’ perspectives, while the teacher–student relationship from teachers’ perspectives did not play an indirect role. These findings suggest that the teacher–student relationship perceived by students is more important for children’s social adjustment than that perceived by teachers. Both parents and teachers should pay more attention to developing children’s interpersonal trust, build better teacher–student relationships, and focus more on how children feel about the relationship. (shrink)

In a congested large-scale subway network, the distribution of passenger flow in space-time dimension is very complex. Accurate estimation of passenger path choice is very important to understand the passenger flow distribution and even improve the operation service level. The availability of automated fare collection data, timetable, and network topology data opens up a new opportunity to study this topic based on multisource data. A probability model is proposed in this study to calculate the individual passenger’s path choice with multisource (...) data, in which the impact of the network time-varying state on passenger path choice is fully considered. First, according to the number and characteristics of OD candidate paths, the AFC data among special kinds of OD are selected to estimate the distribution of passengers’ walking time and waiting time of each platform. Then, based on the composition of path travel time, its real-time probability distribution is formulated with the distribution of walking time, waiting time, and in-vehicle time as parameters. Finally, a membership function is introduced to evaluate the dependence between passenger’s travel time and the real-time travel time distribution of each candidate path and take the path with the largest membership degree as passenger’s choice. Finally, a case study with Beijing Subway data is applied to verify the effectiveness of the model presented in this study. We have compared and analysed the path calculation results in which the time-varying characteristics of network state are considered or not. The results indicate that a passenger’s path choice behavior is affected by the network time-varying state, and our model can quantify the time-varying state and its impact on passenger path choice. (shrink)

Previous studies have shown that the motion intention recognition for lower limb prosthesis mainly focused on the identification of performed gait. However, the bionic prosthesis needs to know the next movement at the beginning of a new gait, especially in complex operation environments. In this paper, an upcoming locomotion prediction scheme via multilevel classifier fusion was proposed for the complex operation. At first, two motion states, including steady state and transient state, were defined. Steady-state recognition was backtracking of a completed (...) gait, which would be used as prior knowledge of motion prediction. In steady-state recognition, surface electromyographic and inertial sensors were fused to improve recognition accuracy; five typical locomotion modes were recognized by random forest classifier with over 97.8% accuracy. The transient state was defined as an observation period at the initial stage of upcoming movement, in which only the sEMG signal was recorded due to the limitation of sliding window length. LightGBM classifier was validated to outperform other methods in the accuracy and prediction time of transient-state recognition. Finally, a simplified HMM model based on prior knowledge and observation result was constructed to predict upcoming locomotion. The results indicated that the locomotion prediction was over 91% accuracy. The proposed scheme implements the locomotion prediction at the initial stage of each gait and provides critical information for the gait control of lower limb prosthesis. (shrink)

Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and (...) gradation. At the same time, the differences, advantages, and disadvantages of K-NN, DT, and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises. (shrink)

书名原文:Transport processes in plasmas.vol.1,Classisal transport.

This study inspected the effect of Massive Open Online Course and flipped instruction on EFL learners’ foreign language speaking anxiety, foreign language learning motivation, and attitude toward English learning. To fulfill this objective, the Oxford Quick Placement Test was given to 160 Iranian EFL learners, of whom 120 upper-intermediate participants were chosen and divided into two experimental groups—MOOC and flipped —and one control group. After that, all selected participants were administered a speaking anxiety questionnaire and a motivation questionnaire as the (...) pre-test of the research. Then, one of the experimental groups received an online-based instruction via Skype: one conversation was instructed to this group online every session. The other experimental group received the treatment via flipped-based instruction. The audio files and the texts of the conversations were sent to this group via the WhatsApp application because they all had easy access to it. On the other hand, the control group did not receive any Internet-delivered treatment yet was trained through a face-to-face method. This process continued until the last session, and after the treatment period, the post-tests of speaking anxiety and motivation were given to all three groups to determine the effectiveness of the treatment. Moreover, two attitude questionnaires were administered to the experimental groups to examine their attitudes toward the MOOC and the flipped models of instructions. The findings of the One-way ANOVA test, Post-hoc Scheffe test, and paired samples t-test showed that there were significant differences between the post-test of the experimental groups and the control group. The results indicated that the experimental groups significantly outflanked the control group after the treatment. Lastly, the outcomes showed that participants in both experimental groups had positive attitudes toward technological-based instructional environments. (shrink)

Resumen: La esencia del desarrollo del ecoturismo moderno reside en la coexistencia armónica y armoniosa de la relación entre el hombre y la naturaleza, que es la práctica ecológica del turismo bajo el trasfondo del desarrollo sostenible moderno. El desarrollo del turismo tradicional se centra en los intereses económicos y descuida la protección sostenible de la ecología turística, y el ecoturismo se ha convertido gradualmente en la dirección de desarrollo y reforma del turismo contemporáneo. El taoísmo hace hincapié en seguir (...) a la naturaleza, lo que tiene evidentes tendencias naturalistas, proporciona diferentes perspectivas filosóficas clásicas tradicionales para comprender la relación entre la naturaleza y el desarrollo humano, y tiene un importante significado esclarecedor para promover el desarrollo común del hombre y la naturaleza. El taoísmo aboga por respetar e imitar las leyes del desarrollo natural, persiguiendo la armonía general entre el hombre y la naturaleza, y es coherente con la naturaleza intrínseca del ecoturismo moderno. Por lo tanto, basándose en el pensamiento ecológico taoísta, la investigación explora la vía de desarrollo de la cultura ecoturística sostenible contemporánea y proporciona orientación teórica para el desarrollo armonioso y la unidad del hombre y la naturaleza. (shrink)

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)

Circular economy is a critical approach to realize the coordinated development of society, economy, and ecological environment. Given the fact that urban is a complex system in which human beings integrate material, energy, information, and natural environment and interact and influence each other, reviewing the urban circular economy research and development could benefit for having a better and comprehensive understanding on urban complexity. Mainly based on the Chinese literature studies from 1999 to 2020, this study aims to present an in-depth (...) analysis of the research themes, policy systems, and index system of Chinaʼs urban-scale circular economy, discuss the changes and evolution trends of themes, levels, and perspectives in time series, sort out the policy systems at both the national and local levels, and analyze the design principles and application fields of indicators. Finally, we propose that future development of an urban circular economy should be built based on modern techniques, technologies, and models. The construction of development mechanism on the circular economy should be framed as “government-led, market-driven, legal norms, policy support, technological support, and public participation” and inject concepts such as “Internet +,” “sharing economy,” “Internet of Things,” and “artificial intelligence.”. (shrink)

Objective wealth plays an important role in social interaction and economic decision making. Previous studies indicate that objective wealth of others may influence the way we participate in resources allocation. However, the effect of objective wealth on responses to fairness-related resource distribution is far from clear, as are the underlying neural processes. To address this issue, we dynamically manipulated proposers’ objective wealth and analyzed participants’ behavior as responders in a modified Ultimatum Game, during which event-related potentials were recorded. Behavioral results (...) showed that participants were prone to reject unfair proposals although that rejection would reduce their own benefit. Importantly, participants were more likely to accept unfair offers from proposers with low objective wealth than from proposers with high objective wealth, with a drastic increase in acceptance rates of unfair offers from 32.79 to 50.59%. Further electrophysiological results showed that there was significantly enhanced feedback-related negativity amplitude toward proposers with high objective wealth for unfair offers. Furthermore, the late frontal negativity amplitude was larger for all the conditions which are not high-fair, which might be the only option that did not elicit any ambiguity. These findings suggest a strong role of proposers’ objective wealth in modulating responders’ behavioral and neural responses to fairness. (shrink)

With a focus in the financial market, stock market dynamics forecasting has received much attention. Predicting stock market fluctuations is usually challenging due to the nonlinear and nonstationary time series of stock prices. The Elman recurrent network is renowned for its capability of dealing with dynamic information, which has made it a successful application to predicting. We developed a hybrid approach which combined Elman recurrent network with factorization machine technique, i.e., the FM-Elman neural network, to predict stock market volatility. In (...) this paper, the Standard & Poor’s 500 Composite Stock Price index, the Dow Jones industrial average index, the Shanghai Stock Exchange Composite index, and the Shenzhen Securities Component Index were used to demonstrate the validity of our proposed FM-Elman model in time-series prediction. The results were compared with predictions obtained from the other two models which are basic BP neural network and the Elman neural network. Some experiments showed that the FM-Elman model outperforms others through different accuracy measures. Furthermore, the effects of volatility degree on prediction performance from different stock indexes were investigated. An interesting phenomenon had been found through some numerical experiments on the effects of different user-specified dimensions on the proposed FM-Elman neural network. (shrink)

In this research work, a user-friendly decision support framework is developed to analyze the behavior of Pakistani students in academics. The purpose of this article is to analyze the performance of the Pakistani students using an intelligent decision support system (DSS) based on the three-level machine learning (ML) technique. The neural network used a three-level classifier approach for the prediction of Pakistani student achievement. A self-recorded dataset of 1,011 respondents of graduate students of English and Physics courses are used. The (...) ten interviews along with ten questions were conducted to determine the perception of the individual student. The chi-squared ( χ ) \left(\chi ) test was applied to test statistical significancy of the questionnaire. The statistical calculations and computation of data were performed by using the statistical package of IBMM SPSS version 21.0. The seven different algorithms were tested to improve the data classification. The Java-based environment was used for the development of numerous prediction classifiers. C4.5 algorithm shows the finest accuracy, whereas Naïve Bayes (NB) algorithm shows the least. The results depict that the classifier’s efficiency was improved by using a three-level proposed scheme from 83.2% to 88.8%. This prediction has shown remarkable results when compared with the individual level classifier technique of ML. This improvement in the accuracy of DSSs is used to identify more efficiently the gray areas in the education stratum of Pakistan. This will pave a path for making policies in the higher education system of Pakistan. The presented framework can be deployed on different platforms under numerous operating systems. (shrink)

The purpose of this study was to develop a Physician's Spiritual Well-Being Scale (PSpWBS). The significance of a physician's spiritual well-being was explored through in-depth interviews with and qualitative data collection from focus groups. Based on the results of qualitative analysis and related literature, the PSpWBS consisting of 25 questions was established. Reliability and validity tests were performed on 177 subjects. Four domains of the PSpWBS were devised: physician's characteristics; medical practice challenges; response to changes; and overall well-being. The explainable (...) total variance was 65.65%. Cronbach α was 0.864 when the internal consistency of the whole scale was calculated. Factor analysis showed that the internal consistency Cronbach α value for each factor was between 0.625 and 0.794 and the split-half reliability was 0.865. The scale has satisfactory reliability and validity and could serve as the basis for assessment of the spiritual well-being of a physician. (shrink)

Antibiotic resistance in bacteria has become a great threat to global public health. Tigecycline is a next‐generation tetracycline that is the final line of defense against severe infections by pan‐drug‐resistant bacterial pathogens. Unfortunately, this last‐resort antibiotic has been challenged by the recent emergence of the mobile Tet(X) orthologs that can confer high‐level tigecycline resistance. As it is reviewed here, these novel tetracycline destructases represent a growing threat to the next‐generation tetracyclines, and a basic framework for understanding the molecular epidemiology and (...) resistance mechanisms of them is presented. However, further large‐scale epidemiological and functional studies are urgently needed to better understand the prevalence and dissemination of these newly discovered Tet(X) orthologs among Gram‐negative bacteria in both human and veterinary medicine. (shrink)

COVID-19 has created significant concern surrounding the impact of pandemic lockdown on mental health. While the pandemic lockdown can be distressing, times of crisis can also provide people with the opportunity to think divergently and explore different activities. Novelty seeking, where individuals explore novel and unfamiliarly stimuli and environments, may enhance the creativity of individuals to solve problems in a way that allows them to adjust their emotional responses to stressful situations. This study employs a longitudinal design to investigate changes (...) in novelty seeking and mental health outcomes before, during, and after COVID-19 pandemic lockdown, among a group of students from a university in southeast China. Participants were surveyed at three points: November, 2019 ; between February and March, 2020 ; and between May and June, 2020. Cross-sectionally, correlation analysis indicated that greater novelty seeking was associated with lower levels of stress, anxiety, and depression at all three time points. Univariate latent curve modeling indicated a growth trajectory in which novelty seeking increased over time and then remained high during the post-lockdown period. Stress, anxiety, and depression all showed V-shaped growth trajectories in which these variables decreased during lockdown, before increasing in the post-lockdown period. Multivariate LCM indicated the growth trajectory for novelty seeking was associated with the growth trajectories for stress, anxiety, and depression. This suggests that the observed decreases in stress, anxiety, and depression during the lockdown period may be attributable to the sample’s observed increase in novelty seeking. These findings are valuable in that they challenge the notion that lockdown measures are inherently detrimental to mental health. The findings indicate the important role of novelty seeking in responding to crises. It may be possible for future public health measures to incorporate the promotion of novelty seeking to help individuals’ respond to stressful situations and maintain good mental health in the face of crises. (shrink)

This study aims to investigate mental health among Chinese people living in areas with differing levels of infection severity during the COVID-19 outbreak. It also assesses the association between reciprocal and authoritarian filial piety and mental health in times of crises. A sample of 1,201 Chinese participants was surveyed between April and June 2020. Wuhan city, Hubei province outside Wuhan, and elsewhere in China were categorized into high, moderate, and low infection severity areas, respectively. The Depression, Anxiety, and Stress Scale’s (...) severity cut-points were used to categorize participants. In the overall sample, 20.9, 34.2, and 29.0% of the participants showed elevated levels of stress, anxiety, and depression. Those in the highest infection severity group were significantly more likely to be categorized as having elevated levels of stress, anxiety, and depression. General linear modeling was performed on a composite mental distress variable. This model indicated that, even after adjusting for group differences in age, gender, education, and filial piety, the high infection severity group displayed more mental distress than the low infection severity groups. The model also found reciprocal filial piety to have a negative association with mental distress. Conversely, authoritarian filial piety was found to be unrelated to mental distress when controlling for the other variables in the model. No evidence was found for an interaction between either authoritarian or reciprocal filial piety and infection severity, which suggests that the negative association observed between reciprocal filial piety and mental distress was relatively consistent across the three infection severity groups. The findings suggest that future public health programs may integrate the promotion of filial piety as a strategy to help Chinese people maintain good mental health in the face of pandemic crises. (shrink)

This study aimed to examine the relationship between parents' intelligence mindset and children's math anxiety and the mediating role of parents' failure mindset and evaluations of their child's math performance. A total of 419 Chinese students and their parents were recruited to complete a series of questionnaires on topics such as math anxiety, parent's failure mindset, parent's intelligence mindset, and parents' evaluations of their child's mathematical performance. The results revealed that parents' intelligence mindset was not correlated with children's math anxiety. (...) However, parents' intelligence mindset indirectly predicted children's math anxiety through the chain-mediated role of parents' failure beliefs and parents' evaluations of their child's math performance. Further, sex differences were found through a multigroup analysis, which showed a chain-mediated effect between parents' intelligence mindset and girls' math anxiety. (shrink)

Global warming and other climate issues seriously threaten global sustainable development. As citizen environmental behavior can have a positive impact on the environment, it is of great theoretical significance and practical reference value to study the impact of psychological distance theory on citizen environmental behavior. This study obtained 2,633 related studies from 1980 to 2020 from the Web of Science as research objects, and used CiteSpace, VOSviewer, Netdraw, and other software programs to perform a bibliometric analysis, which can show the (...) complex relationship implied in the citation, intuitively grasp the development context and hot frontier in this field, and help scholars better study citizen environmental behavior. The results and conclusions are as follows. The related research covered three periods: infancy, growth, and outbreak. Chronologically, the relevant research evolved from building models to analyze the impact of environmental enrichment on human environmental behavior, to studying the motivation behind citizen environmental behavior, and finally to paying attention to sustainable development. A cluster analysis of high-frequency keywords identified three research hotspots: “drivers of psychological distance of environmental change perception on citizen environmental behavior,” “impact of social distance on adolescents’ behavior,” and “construal level theory and citizen green behavior.” Based on these findings, possible future research directions were identified, including changing from a single theory to a combination of multiple theories to comprehensively study citizen environmental protection behavior; analyzing the motivation of citizen environmental behavior and summarizing the general motivation of environmental behavior according to its internal relationship; and determining how to narrow the global psychological distance, strengthen the awareness of the community of human destiny, and explore the establishment of an efficient global climate cooperation mechanism. (shrink)

As an efficient approach, the trust policy is implemented to defend against insider attacks in complex networks. However, the imperfection of trust relationships directly hinders the effort to quantitatively calculate trust value, especially in choosing a cooperative partner. Fortunately, the game theory is gradually concerned with addressing the above issue to further enhance security. In this paper, the game theory and the trust policy are reviewed briefly. Then, the research roadmap on game-based trust in complex networks is discussed and analysed (...) deeply. Furthermore, some research directions in the near future are given. It is worth mentioning that our contributions not only describe the evolution of the game-based trust clearly but also suggest the trust mechanism based on the bounded rational game more suitable to uncertain information. (shrink)