Compare with other professions, teachers are reported to have a higher risk of poor mental health. This study examined the relationships between emotional intelligence, perceived organizational justice, and mental health among Chinese high school teachers. Three hundred and eighty-one high school teachers, with their age range between 21 and 50 years, were administered the Emotional Intelligence Scale, Perceived Organizational Justice Scale, and Mental Health Scale. The result found that emotional intelligence and perceived organizational justice directly influence the mental health of (...) high school teachers. In addition, perceived organizational justice mediated the association between emotional intelligence and mental health. Moreover, the present study analyzes the different role of subtypes of perceived organizational justice on the relationships between emotional intelligence and mental health, and the results showed that the mediating effects of perceived distributive justice and interactive justice on emotional intelligence and mental health are not significant, only the perceived procedural justice mediated the relationships between emotional intelligence and teachers’ mental health. The results are discussed in a conceptual context. (shrink)

Compared with the large number of studies on reading of children with hearing loss in alphabetic languages, there are only a very limited number of studies on reading of Chinese-speaking children with HL. It remains unclear how phonological, orthographic, and semantic skills contribute to reading fluency of Chinese school-age children with HL. The present study explored this issue by examining the performances of children with HL on reading fluency and three linguistic skills compared with matched controls with normal hearing. Specifically, (...) twenty-eight children with HL and 28 chronological-age-matched children with NH were tested on word/sentence reading fluency, phonological awareness which was composed of onset/vowel/lexical tone awareness, orthographic knowledge, and semantic competence which comprised animal word identification, pseudo-homophone detection, and word segmentation. Results showed that children with HL lagged behind their peers with NH in WRF/SRF and most of the phonological, orthographic, and semantic subskills except onset awareness and pseudo-homophone detection. Furthermore, the significant contributors to WRF differed between the two groups with PA being the significant contributor in the children with NH while OK being the significant contributor in the children with HL. However, the significant contributor to SRF did not differ between the two groups with SC being the only significant contributor. These results revealed not only between-group differences but also similarities in the relative contributions of PA, OK, and SC to reading fluency at both word and sentence levels, which has practical implications for developing better training programs to improve reading for children with HL. (shrink)

Ben shu nei rong bao kuo:zhong hua min zu dao de sheng huo zong lun,Yuan gu zhi zhan guo dao de sheng huo de ji ben zhuang kuang,Dao de guan xi ji wu zhong ji ben lun chang de que li,Li yi gui fan he li wen hua de xing qi yu hong yang,De hua tian xia yu dao de jiao yu zhi kai zhan deng.

This study aimed to explore the mediating role of emotional regulation strategies in the relationship between emotional intelligence and subjective well-being among Chinese university teachers, and evaluate whether effort-reward imbalance moderated the mediating effect of emotional regulation strategies. A total of 308 Chinese university teachers were recruited for this study. The results showed that emotional regulation strategies played a partial mediating role in the relationship between EI and SWB. Moreover, an effort-reward imbalance moderated the relationship between emotional regulation strategies and (...) SWB. For individuals with more balanced perceptions, EI had a significant effect on SWB via cognitive reappraisal, while for individuals with more imbalanced perceptions, EI did not have a significant effect on SWB via cognitive reappraisal. These findings provide a better understanding of the effects of EI and emotional regulation strategies on SWB, which could provide interventions for promoting SWB among teachers. (shrink)

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through (...) TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

The whale optimization algorithm is a powerful swarm intelligence method which has been widely used in various fields such as parameter identification of solar cells and PV modules. In order to better balance the exploration and exploitation of WOA, we propose a novel modified WOA in which both the mutation strategy based on Levy flight and a local search mechanism of pattern search are introduced. On the one hand, Levy flight can make the algorithm get rid of the local optimum (...) and avoid stagnation; thus, it is able to prevent the algorithm from losing diversity and to increase the global search capability. On the other hand, pattern search, a direct search method, has not only high convergence rate but also good stability, which can boost the local optimization ability of the WOA. Therefore, the combination of these two mechanisms can greatly improve the capability of WOA to obtain the best solution. In addition, MWOA may be employed to estimate parameters in single diode model, double diode model, and PV modules and to identify unknown parameters of two different types of PV modules under diverse light irradiance and temperature conditions. The analytical results demonstrate the validity and the practicality of MWOA for estimating parameters of solar cells and PV modules. (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)

Ben shu wei wo she chong dian tu shu hua xia wen ku ru xue shu xi zhong di yi ben. Gai shu yi jian ming de wen zi gou le le Gu Yanwu, Wang Fuzhi, Huang Zongxi san wei Ming mo da ru sheng huo de shi dai bei jing, hong ru de sheng ping jing li, ta men de xue shu zao yi (zhu yao zhi ta men zai ru xue fang mian de cheng jiu), cheng (...) yu jiao you yi ji san wei zai li shi shang de di wei he gong xian, ta men ren sheng de kan ke du lai ling ren bu sheng xi. (shrink)

Patients with Wilson’s disease suffer from prospective memory impairment, and some of patients develop cognitive impairment. However, very little is known about how brain structure and function changes effect PM in WD. Here, we employed multimodal neuroimaging data acquired from 22 WD patients and 26 healthy controls who underwent three-dimensional T1-weighted, diffusion tensor imaging, and resting state functional magnetic resonance imaging. We investigated gray matter volumes with voxel-based morphometry, DTI metrics using the fiber tractography method, and RS-fMRI using the seed-based (...) functional connectivity method. Compared with HC, WD patients showed GM volume reductions in the basal ganglia and occipital fusiform gyrus, as well as volume increase in the visual association cortex. Moreover, whiter matter tracks of WD were widely impaired in association and limbic fibers. WM tracks in association fibers are significant related to PM in WD patients. Relative to HC, WD patients showed that the visual association cortex functionally connects to the thalamus and hippocampus, which is associated with global cognitive function in patients with WD. Together, these findings suggested that PM impairment in WD may be modulated by aberrant WM in association fibers, and that GM volume changes in the association cortex has no direct effect on cognitive status, but indirectly affect global cognitive function by its aberrant functional connectivity in patients with WD. Our findings may provide a new window to further study how WD develops into cognitive impairment, and deepen our understanding of the cognitive status and neuropathology of WD. (shrink)

According to the reports in the past decade, some Asian subcontractors, mainly Taiwan, Hong Kong and Korea transnational corporations, tend to be labor abusive in their overseas investment destinations like China or Southeast Asia. Taking Vietnam as an example, this paper raises questions as to why Taiwanese transnational companies can control workplace unions in a trade-union-supportive regime. Given the government s constraint of political rights, and the individualized workplace unions, the function of trade unions in Vietnam is destined to (...) be limited. The trade unions turn out be an arm of management, rather than representing workers interests in these transnational companies. This article also explores the influence of the newly developed codes of conducts from Western buyers. In the survey of three companies which are required to follow the codes of conduct by buyers, trade unions had no more freedom than those in companies without codes of conduct. The paper discusses the implications of this research, offering strategies for labor rights improvements. (shrink)

The category \(\mathbb {DRDL}{'}\), whose objects are c-differential residuated distributive lattices satisfying the condition \(\textbf{CK}\), is the image of the category \(\mathbb {RDL}\), whose objects are residuated distributive lattices, under the categorical equivalence \(\textbf{K}\) that is constructed in Castiglioni et al. (Stud Log 90:93–124, 2008). In this paper, we introduce weak monadic residuated lattices and study some of their subvarieties. In particular, we use the functor \(\textbf{K}\) to relate the category \(\mathbb {WMRDL}\), whose objects are weak monadic residuated distributive lattices, (...) and the category \(\mathbb {WMDRDL}{'}\), whose objects are pairs formed by an object of \(\mathbb {DRDL}{'}\) and a center weak universal quantifier. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

Two kinds of probability expressions, verbal and numerical, have been used to characterize the uncertainty that people face. However, the question of whether verbal and numerical probabilities are cognitively processed in a similar manner remains unresolved. From a levels-of-processing perspective, verbal and numerical probabilities may be processed differently during early sensory processing but similarly in later semantic-associated operations. This event-related potential (ERP) study investigated the neural processing of verbal and numerical probabilities in risky choices. The results showed that verbal probability (...) and numerical probability elicited different N1 amplitudes but that verbal and numerical probabilities elicited similar N2 and P3 waveforms in response to different levels of probability (high to low). These results were consistent with a level-of-processing framework and suggest some internal consistency between the cognitive processing of verbal and numerical probabilities in risky choices. Our findings shed light on possible mechanism underlying probability expression and may provide the neural evidence to support the translation of verbal to numerical probabilities (or vice versa). (shrink)

The popularization of intelligent machines such as service robot and industrial robot will make human–machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human–machine interaction that how influences the employee’s learning is still rarely. This paper was to reveal the relationship between human–machine interaction and employee’s learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence (...) companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human–machine interaction has a U-shaped curvilinear relationship with employee learning, and employee’s vitality mediates the curvilinear relationship. In addition, job characteristics moderate the U-shaped curvilinear relationship between human–machine interaction and employee’s vitality, especially the results of moderating effects varying with employee’s competence perception. Exploring the mechanism of the effect of human–machine interaction on employee’s learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human–machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human–machine interaction on individual’s behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human–machine interaction literature by underscoring the important of individual’s behavior among individuals with different skills. (shrink)

ObjectivePrevious studies have demonstrated altered brain activity in strabismic amblyopia. In this study, low-frequency repetitive transcranial magnetic stimulation was applied in children with strabismic amblyopia after they had undergone strabismus surgery. The effect of rTMS was investigated by measuring the changes of brain features using the amplitude of low-frequency fluctuation.Materials and MethodsIn this study, 21 SA patients were recruited based on their age, weight, and sex. They all had SA in their left eyes and they received rTMS treatment one month (...) after strabismus surgery. Their vision before and after surgery were categorized as pre-rTMS and post-rTMS. All participants received rTMS treatment, underwent magnetic resonance imaging, and their data were analyzed using the repeated measures t-test. The team used correlation analysis to explore the relationship between logMAR visual acuity and ALFF.ResultsPre- versus post-rTMS values of ALFF were significantly different within individuals. In the POT group, ALFF values were significantly decreased in the Angular_R, Parietal_Inf_L, and Cingulum_Mid_R while ALFF values were significantly increased in the Fusiform_R and Frontal_Inf_Orb_L compared to the PRT stage.ConclusionOur data showed that ALFF recorded from some brain regions was changed significantly after rTMS in strabismic amblyopes. The results may infer the pathological basis of SA and demonstrate that visual function may be improved using rTMS in strabismic amblyopic patients. (shrink)

BackgroundBoosting the individual learning passion of medical students is a novel approach to improve their academic performance. It facilitates the medical education reform, motivating both policymakers and educators to focus on the function of positive psychology in the career development of medical students. Therefore, this study aimed to assess the status of two types of learning passion; to clarify the relationship between self-esteem and two types of learning passion among Chinese medical students; to examine the mediating role of psychological capital (...) in the relationship between self-esteem and two types of learning passion, respectively; and to identify the moderating role of professional identity in the relationship between PsyCap and two types of learning passion, respectively.MethodsA cross-sectional online survey was conducted from April to June 2016 in China. A total of 1,218 valid questionnaires were collected from four medical schools.ResultsSelf-esteem significantly and positively influenced medical students’ PsyCap.ConclusionTwo types of learning passion of medical students are positively influenced by self-esteem and PsyCap. Medical students with high-level self-esteem should possess strong PsyCap, which augments their harmonious as well as obsessive learning passion. Moreover, the positive effect of medical students’ PsyCap on harmonious learning passion is more notable among those with a lower professional identity. Finally, this study argues that strengths-based interventions of self-esteem and PsyCap are a beneficial approach for future enhancing learning passion in the domain of medical education. (shrink)

Due to the development of information technology, music piracy has become an escalating problem. This study attempts to employ the theory of planned behavior (TPB) and the social identity theory to investigate the antecedents of downloading pop music illegally from the Internet, the relationship between the intention to illegally download music and the intention to buy music, and the moderating effects of idolatry. Data were collected from 350 teenagers in Northern Taiwan through questionnaire interviews conducted in city centers where teenagers (...) gather. The results of partial least squares (PLS) analyses reconfirm the explanatory power of the TPB model with regard to the pop music illegal downloading behavior. However, it is interesting to note that the intention to illegally download music does not have a significant influence on the intention to buy music. This finding contradicts our common intuitions. Further analyses also reveal that idolatry moderates the relationship between the intention to illegally download music and the intention to buy music. For teenagers with high idolatry, a higher music downloading intention results in a lower buying intention. One possible explanation is the price of music CDs. Several interviews were also held to verify our results. Implications and a discussion are then provided. (shrink)

The main purpose of this note is to characterize consistency of logic theories in propositional logic by means of topological concept. Based on the concepts of truth degree of formulas and similarity degree between formulas the concept of logic metric space has been proposed by the first author. It is proved in this note that a closed logic theory Γ is consistent if and only if it contains no interior point in the logic metric space. Moreover the relationship between logic (...) closedness and topological closedness of a logic theory Γ is discussed. Finally, the concept of full divergency is also characterized by means of the topological concept of density. (shrink)

A semiotic study seeks to find sign significance in its relation with others. This paper is a search for the semiotic manifestation of certain signs in the contemporary campaign against corruption in mainland China. It uses Greimas’s semiotic square as a theoretical base upon which an examination of official discourse pertaining to anti-corruption is conducted. Power, agency, and sexual relation are the three parameters of analysis. The study comes to the tentative conclusion that the marked combinatory presence of women in (...) anti-corruption discourse implicates women as the primary benefactors in the male-dominated corruption practice, thus directing the public attention to a gender issue of minor importance. (shrink)

The COVID-19 pandemic has caused tremendous loss starting from early this year. This article aims to investigate the change of anxiety severity and prevalence among non-graduating undergraduate students in the new semester of online learning during COVID-19 in China and also to evaluate a machine learning model based on the XGBoost model. A total of 1172 non-graduating undergraduate students aged between 18 and 22 from 34 provincial-level administrative units and 260 cities in China were enrolled onto this study and asked (...) to fill in a sociodemographic questionnaire and the Self-Rating Anxiety Scale twice, respectively, during February 15 to 17, 2020, before the new semester started, and March 15 to 17, 2020, 1 month after the new semester based on online learning had started. SPSS 22.0 was used to conduct t-test and single factor analysis. XGBoost models were implemented to predict the anxiety level of students 1 month after the start of the new semester. There were 184 and 221 students who met the cut-off of 50 and were screened as positive for anxiety, respectively, in the two investigations. The mean SAS scores in the second test was significantly higher than those in the first test. Significant differences were also found among all males, females, and students majoring in arts and sciences between the two studies. The results also showed students from Hubei province, where most cases of COVID-19 were confirmed, had a higher percentage of participants meeting the cut-off of being anxious. This article applied machine learning to establish XGBoost models to successfully predict the anxiety level and changes of anxiety levels 4 weeks later based on the SAS scores of the students in the first test. It was concluded that, during COVID-19, Chinese non-graduating undergraduate students showed higher anxiety in the new semester based on online learning than before the new semester started. More students from Hubei province had a different level of anxiety than other provinces. Families, universities, and society as a whole should pay attention to the psychological health of non-graduating undergraduate students and take measures accordingly. It also confirmed that the XGBoost model had better prediction accuracy compared to the traditional multiple stepwise regression model on the anxiety status of university students. (shrink)

In the presence of heterogeneity between the randomized controlled trial (RCT) participants and the target population, evaluating the treatment effect solely based on the RCT often leads to biased quantification of the real-world treatment effect. To address the problem of lack of generalizability for the treatment effect estimated by the RCT sample, we leverage observational studies with large samples that are representative of the target population. This article concerns evaluating treatment effects on survival outcomes for a target population and considers (...) a broad class of estimands that are functionals of treatment-specific survival functions, including differences in survival probability and restricted mean survival times. Motivated by two intuitive but distinct approaches, i.e., imputation based on survival outcome regression and weighting based on inverse probability of sampling, censoring, and treatment assignment, we propose a semiparametric estimator through the guidance of the efficient influence function. The proposed estimator is doubly robust in the sense that it is consistent for the target population estimands if either the survival model or the weighting model is correctly specified and is locally efficient when both are correct. In addition, as an alternative to parametric estimation, we employ the nonparametric method of sieves for flexible and robust estimation of the nuisance functions and show that the resulting estimator retains the root- n n consistency and efficiency, the so-called rate-double robustness. Simulation studies confirm the theoretical properties of the proposed estimator and show that it outperforms competitors. We apply the proposed method to estimate the effect of adjuvant chemotherapy on survival in patients with early-stage resected non-small cell lung cancer. (shrink)