Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients (...) with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. (shrink)

As the labeling costs in legal artificial intelligence tasks are expensive. Therefore, it becomes a challenge to utilize low cost to train a robust model. In this paper, we propose a LAIAugment approach, which aims to enhance the few-shot learning capability in legal artificial intelligence tasks. Specifically, we first use the self-training approach to label the amount of unlabelled data to enhance the feature learning capability of the model. Moreover, we also search for datasets that are similar to the training (...) set by improving the text similarity function. We conducted experimental analyses for three legal artificial intelligence tasks, including evidence extraction, legal element extraction, and case multi-label prediction, which composed of 3500 judgement documents. The experimental results show that the proposed LAIAugment method has an average F1-score of 72.3% on the three legal AI tasks, which is 1.93% higher than the baseline model. At the same time, it shows a huge improvement in few-shot learning. (shrink)

Previous studies have focused on the relationship between imaginary companions (ICs) and children’s social developments. As far as we know, few studies have focused on the relationship between ICs and children’s agency attributions. This study aimed to explore the potential differences in agency attributions between children with and without ICs, children with egalitarian IC relationships and hierarchical IC relationships. Children’s agency attributions were measured by two experiments. One was based on behavioral cues (Random animations/ToM animations) and the other was based (...) on appearance characteristics (ball/doll). The results revealed that children with ICs attributed more cognitive properties to Random and ToM animations than children without ICs. Compared with children without ICs, children with ICs attributed marginally more biological properties to a ball and more psychological properties to a ball and a doll. However, children with egalitarian and hierarchical IC relationships did not differ in their agency attributions. The results suggest that children with ICs are more likely to attribute agencies to non-human items with behavioral cues or appearance characteristics than children without ICs. Compared with child-IC relationship qualities, IC status may be more related to children’s agency attributions. However, only a correlation between IC status and children’s agency attributions was found in this study and it is interesting for future researchers to investigate the potential causal directions between children’s IC status and their agency attributions. If one of the causal directions or both the causal directions exist, future researchers can further explore the underlying mechanism. (shrink)

In the context of digital monetary market integration, the importance of cross-border digital currency research is receiving prominent attention. This study integrated Extended Unified Theory of Acceptance and Use of Technology and initial trust factors into an integrative framework, which synthetically complemented the objective measures and subjective insights of digital currencies. The results indicated the integrated framework, which verified its robustness predicting the acceptance and recommendation intention of digital currency. By analyzing the two different features of digital currencies, this research (...) puts forward a set of targeted solutions to ensure that users of Chinese and Korean digital currencies make a long-term policy for the sustainability, eventually benefitting the cross-border digital monetary transactions and economic cooperation in Asia, which leads the world to the sustainable development in the digital currencies field. (shrink)

Objective: To investigate the correlation between preoperative response to the L-dopa challenge test and efficacy of deep brain stimulation (DBS) on motor function in Parkinson’s disease (PD).Methods: We retrospectively reviewed the data of 38 patients with idiopathic PD who underwent DBS surgery with a median follow-up duration of 7 months. Twenty underwent bilateral globus pallidus interna (GPi) DBS, and 18 underwent bilateral subthalamic nucleus (STN) DBS. The Movement Disorder Society Unified Parkinson Disease Rating Scale-Motor Part (MDS UPDRS-III) was assessed before (...) surgery and at the last follow-up in different medication and stimulation conditions, respectively.Results: Pearson’s correlation analysis revealed a positive correlation between preoperative L-dopa challenge responsiveness and GPi-DBS responsiveness on the total score (R2 = 0.283, p = 0.016) but not on the non-tremor total score (R2 = 0.158, p = 0.083) of MDS UPDRS-III. Such correlation remained significant (R2′ = 0.332, p = 0.010) after controlling for age at the time of surgery as confounding factor by partial correlation analysis. The preoperative L-dopa challenge responsiveness was significantly correlated with the tremor-controlling outcome of GPi-DBS (R2 = 0.390, p = 0.003). In contrast, we found a positive correlation between preoperative L-dopa challenge responsiveness and STN-DBS responsiveness on the non-tremor total score (R2 = 0.290, p = 0.021), but not on the total score (R2 = 0.130, p = 0.141) of MDS UPDRS-III. The partial correlation analysis further demonstrated that the predictive value of preoperative L-dopa challenge responsiveness on the non-tremor motor outcome of STN-DBS was eliminated (R2′ = 0.120, p = 0.174) after controlling for age at the time of surgery as confounding factor.Interpretation: The short-term predictive value of preoperative response to the L-dopa challenge test for the motor outcome of GPi-DBS in PD was systematically described. Our findings suggest: (1) a solid therapeutic effect of GPi-DBS in treating L-dopa-responsive tremors; (2) a negative effect of age at the time of surgery on motor outcomes of STN-DBS, (3) a possible preference of STN- to GPi-DBS in L-dopa-resistant tremor control, and (4) a possible preference of GPi- to STN-DBS in elderly PD patients who have a satisfactory dopamine response. (shrink)

This paper investigates the association between board characteristics and the company’s corporate social responsibility assurance decision in China. By examining 2054 firm-years of Chinese listed companies with CSR reports from 2008 to 2012, we find that firms with a large board size, more female directors, and separation of CEO and chairman positions are more likely to engage in CSR assurance. Gender diversity also influences the CSR assurance provider choice. However, board independence and overseas background of the CEO do not affect (...) the CSR assurance decision. Inconsistent with our prediction, firms with foreign directors are less likely to engage in voluntary CSR assurance. In summary, this research provides in-depth insights into the determinants of Chinese firms’ voluntary CSR assurance. (shrink)

In response to the big data era trend, statistics has become an indispensable part of mathematics education in junior high school. In this study, a pre-test and a post-test were developed for the six attributes of the data distribution characteristic. This research then used the cognitive diagnosis model to learn about the poorly mastered attributes and to verify whether cognitive diagnosis can be used for targeted intervention to improve students' abilities effectively. One hundred two eighth graders participated in the experiment (...) and were divided into two groups. Among them, the intervention materials read by the experimental group students only contained attributes that they could not grasp well. In contrast, the reading materials of the control group were non-targeted. The results of the study showed the following: The variance and the weighted average were poorly mastered by students in the pre-test; compared with the control group, the average test score of the experimental group was significantly improved; in terms of attributes, the experimental group students' mastery of variance and the weighted average was significantly improved than the pre-test, while the control group's mastery was not. Based on this, some teaching suggestions were put forward. (shrink)

The California Verbal Learning Test-Second Edition, is a commonly used tool to assess episodic memory. This study analyzed learning and memory characteristics in a cognitively healthy Chinese population, as well as the effects of age, sex and education on CVLT-II factors. In total, 246 healthy people aged 20–80 years and 29 persons with multiple sclerosis were included in this study and completed the CVLT-II. Factors including total learning, learning strategy, serial position effects, short-delay free and cued recall, long-delay free and (...) cued recall, repetitions and intrusions during recall, hits and false positives of recognition, and total recognition discriminability were calculated. The effects of age, sex and education on these factors were analyzed using ANCOVA or independent two-sample t-tests and further confirmed by multiple regression analysis. The regression-based normative data were then computed by the equivalent scores method. Moreover, differences in learning and memory were compared between persons with MS and age-, sex- and education-matched healthy individuals. Most CVLT-II factors significantly differed between different age and education groups; in particular, better performance in total learning, recall, semantic clustering and recognition was observed in the younger and more educated groups than in the older and less educated groups. Male participants showed higher recency effect scores, more repetitions and fewer hits than female participants. Compared with healthy individuals, persons with MS showed extensive impairments in memory processes, such as learning, recall, learning strategy and recognition. These findings indicated that verbal learning and memory were highly dependent on age and educational level but not strongly affected by sex. The CVLT-II effectively assesses episodic memory impairment in the Chinese-speaking population. (shrink)

Evidences are important proofs to support judicial trials. Automatically extracting evidences from judgement documents can be used to assess the trial quality and support “Intelligent Court”. Current evidence extraction is primarily depended on sequence labelling models. Despite their success, they can only assign a label to a token, which is difficult to recognize nested evidence entities in judgment documents, where a token may belong to several evidences at the same time. In this paper, we present a novel evidence extraction architecture (...) called ATT-MRC, in which extracting evidence entities is formalized as a question answer problem, where all evidence spans are screened out as possible correct answers. Furthermore, to address the data imbalance problem in the judgement documents, we revised the loss function and combined it with a data enhancement technique. Experimental results demonstrate that our model has better performance than related works in evidence extraction. (shrink)

Instructional interactions, which includes student–student interaction, student–teacher interaction, and student–content interaction, are crucial factors affecting the learning outcomes in online education. The current study aims to explore the effects of instructional interactions on individuals’ learning outcomes based on the Interactive Equivalence Theory by conducting two empirical studies. In Study 1, we explored the direct relationships between instructional interactions and learning outcomes. A quasi-experimental design was used to manipulate the two groups of subjects, and the results show that not all of (...) the three types of interaction can significantly positively predict learning satisfaction, among which ST cannot significantly predict learning satisfaction. When the total amount of instructional interactions is constant, adjusting the relative level of the three types of instructional interactions can effectively improve the learning outcomes to some extent. We further probed into the mediating effects of task value and self-regulated learning on the relationships between instructional interactions and learning outcomes in Study 2. We conducted an online survey and collected 374 valid data. The results showed that task values mediated the relationship between SS and learning satisfaction. In addition, SC can not only directly affect learning satisfaction, but also affect it through task value and self-regulated learning respectively, or via chain mediations of both task value and self-regulated learning. Our findings enrich the previous instructional interactions research and provide reference for online education curriculum design. (shrink)

Individuals' knowledge hiding behavior may lead to massive economic losses to organizations, and exploring the antecedents of it has crucial relevance for mitigating its negative influences. This research aims to investigate the impact of perceived overqualification on knowledge hiding by testing the mediating effect of psychological capital and the moderating effect of person-organization fit. Empirical analyses were conducted on 249 employee dataset using versions SPSS 26 and AMOS 26. Results illustrate an inverse correlation between perceived overqualification and knowledge hiding behavior (...) which is partly mediated by psychological capital and moderated by person-organization fit, implying that good organizational atmosphere that builds up individual psychological capital with better person-organization fit will allow employees to work positively to reduce knowledge hiding behavior when perceived overqualified. This study complements a small quantity of discussions on the positive impact of perceived overqualification on knowledge management and fills omissions in previous studies on the negative effect of perceived overqualification on knowledge hiding behavior in changing surroundings. (shrink)

This study aims to explore the current situation and strategy formulation of sports psychology teaching in colleges and universities following adaptive learning and deep learning under information education. The informatization in physical education, teaching methods, and teaching processes make psychological education more scientific and efficient. First, the relevant theories of adaptive learning and deep learning are introduced, and an adaptive learning analysis model is implemented. Second, based on the deep learning automatic encoder, college students’ sports psychology is investigated and the (...) test results are predicted. Finally, the current situation and development strategy of physical education in colleges and universities are analyzed. The results show that when the learning rate is 1, 0.1, and 0.01, there is no significant change in the analysis factors of recall, ndcg, item_coverage, and sps. When the learning rate is 1, their analysis factors change obviously, and it is calculated that the optimal learning rate of the model is 1. And the difficulty of the recommended test questions by using the sports psychology teaching method based on adaptive learning and deep learning is relatively stable. The test questions include various language points of sports psychology. Compared with others methods, adaptive learning and deep learning can provide comprehensive test questions for sports psychology teaching. This study provides technical support for the reform of sports psychology teaching in colleges and universities and contributes to optimizing the information-based teaching mode. (shrink)

Based on a 12-year bibliographic record collected from the Web of Science database, the present study aims to provide a macroscopic overview of the knowledge domain in financial decision making. A scientometric and bibliometric analysis was conducted on the literature published in the field from 2010 to 2021, using the CiteSpace software. The analysis focuses on the co-occurring categories, the geographic distributions, the vital references, the distribution of topics, as well as the research fronts and emerging trends of financial related (...) decision making. The steady increase of papers published year by year demonstrated the increasing interest on this topic at the international level. The scientometric analysis of the literature showed that financial decision, investment decision, and financing decision stood out of the crowd of the research on FDM, suggesting their important role in FDM and its research. The results of citation burst analysis predicted the focus of topics, i.e., the impact of individual differences such as financial literacy, gender and age on FDM in the coming years. Different from the traditional approach of literature review, this bibliometric analysis offers a scientometric approach to reveal the status quo and the development trend of FDM by macro and quantitative means. In addition, future research directions for the field are recommended. (shrink)

People are ingesting various information from different sense organs all the time to complete different cognitive tasks. The brain integrates and regulates this information. The two significant sensory channels for receiving external information are sight and hearing that have received extensive attention. This paper mainly studies the effect of music and visual-auditory stimulation on electroencephalogram of happy emotion recognition based on a complex system. In the experiment, the presentation was used to prepare the experimental stimulation program, and the cognitive neuroscience (...) experimental paradigm of EEG evoked by happy emotion pictures was established. Using 93 videos as natural stimuli, fMRI data were collected. Finally, the collected EEG signals were removed with the eye artifact and baseline drift, and the t-test was used to analyze the significant differences of different lead EEG data. Experimental data shows that, by adjusting the parameters of the convolutional neural network, the highest accuracy of the two-classification algorithm can reach 98.8%, and the average accuracy can reach 83.45%. The results show that the brain source under the combined visual and auditory stimulus is not a simple superposition of the brain source of the single visual and auditory stimulation, but a new interactive source is generated. (shrink)

The cultural element is the minimum unit of a cultural system. The systematic categorizing, organizing, and retrieval of the traditional Chinese cultural elements are essential prerequisites for the realization of effective extracting and rational utilization, as well as the prerequisite for exploiting the contemporary value of the traditional Chinese culture. To build an objective, integrated, and reliable classification method and a system of traditional Chinese cultural elements, this study takes the text of Taiping Imperial Encyclopedia in Northern Song Dynasty as (...) the primary data source. The unsupervised word segmentation methods are used to detect Out-of-Vocabulary, and then the segmentation results by the THULAC tool with and without custom dictionary are compared. The TF-IDF algorithm is applied to extract the keywords of cultural elements and the Ochiia coefficient is introduced to create complex networks of traditional Chinese cultural elements. After analyzing the topological characteristics of the network, the community detection algorithm is used to identify the topics of cultural elements. Finally, a “Means-Ends” two-dimensional orthogonal classification system is established to categorize the topics. The results showed that the degree distribution in the complex network of Chinese traditional cultural elements is a scale-free network with γ = 2.28. The network shows a structure of community and hierarchy features. The top 12 communities have taken up to 91.77% of the scale of the networks. Those 12 topics of the traditional Chinese cultural elements are circularly distributed in the orthogonal system of cultural elements’ categorization. (shrink)

The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking over most of the research conducted in this field, especially in the biomedical domain. Unlike other languages, Arabic suffers from lack of resources. This work presents a BERT-based (...) model to identify biomedical named entities in the Arabic text data that investigates the effectiveness of pretraining a monolingual BERT model with a small-scale biomedical dataset on enhancing the model understanding of Arabic biomedical text. The model performance was compared with two state-of-the-art models, and it outperformed both models with 85% F1-score. (shrink)

Early in Aristotle's terminology, and ever since, "essence" has been conceived as having two meanings, namely "universality" and "individuality". According to the tradition of thought that has dominated throughout the history of Western philosophy, "essence" unequivocally refers to "universality". As a matter of fact, however, "universality" cannot cover Aristotle's definition and formulation of "essence": Essence is what makes a thing "happen to be this thing." "Individuality" should be the deep meaning of "essence". By means of an analysis of some relevant (...) Western thoughts and a review of cultural realities, it can be concluded that the difference between the attitudes toward things of the natural sciences and the humane sciences mainly lies in the fact that the former focus on the pursuit of universal regularity, whereas the latter go after the value and significance of human life. The movement from natural things to cultural things is a process in which essence shifts from universality to individuality. It is the author's contention that what should be stressed in the fields of human culture and society is the construction of an ideal society that is "harmonious yet not identical", on the basis of respecting and developing individual peculiarity and otherness. /// "本质" 最早在亚里士多德的用语中包含有两重含义: 是指 "普遍的东 西" ("共相")，一是指 "个体的东西" ("这个")。在西方哲学史上民期占统治 地位的思想片面地认为: "本质" 就是指 "普遍的东西"。但实际上"普遍的东 西" 并不能涵盖亚里士多德对 "本质" 的界定和表述t 本质是使一事物 "恰恰地是 这个事物"的东西。"本质" 的深层含义应是 "个体性"。通过对西方一些相关思 想观点的分析和文化现实的考察，可以得出结论z 自然科学与人文科学对待事物的 态度的区别在于z 前者重普遍性规律的追求，后者重个体性的人生价值意义的追求。 从自然物到文化物是一个由以普遍性为本质到以个体性为本质的转化过程。在人文 社会领域应该强调的是z 在尊重和发扬个人的独特性和差异性的基础上，建立 "和而 不同"的理想社会。. (shrink)

A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. Description: The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data (...) relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term ‘adverse event’ denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. (shrink)

The car-sharing system is a popular rental model for cars in shared use. It has become particularly attractive due to its flexibility; that is, the car can be rented and returned anywhere within one of the authorized parking slots. The main objective of this research work is to predict the car usage in parking stations and to investigate the factors that help to improve the prediction. Thus, new strategies can be designed to make more cars on the road and fewer (...) in the parking stations. To achieve that, various machine learning models, namely vector autoregression, support vector regression, eXtreme gradient boosting, k-nearest neighbors, and deep learning models specifically long short-time memory, gated recurrent unit, convolutional neural network, CNN-LSTM, and multilayer perceptron, were performed on different kinds of features. These features include the past usage levels, Chongqing’s environmental conditions, and temporal information. After comparing the obtained results using different metrics, we found that CNN-LSTM outperformed other methods to predict the future car usage. Meanwhile, the model using all the different feature categories results in the most precise prediction than any of the models using one feature category at a time. (shrink)

BackgroundThe evaluation of the surgical readiness of patients plays an important role in clinical care. Preoperative readiness assessment is needed to identify the inadequacy among surgical patients, which provides guide for interventions to improve patients’ preoperative readiness. However, there is a paucity of high-level, quality tool that evaluate surgical readiness of patients in China. The purpose of this study is to translate the Preoperative Assessment of Readiness Tool into Chinese and determine the reliability and validity of the Chinese version in (...) the population of surgical patients.MethodsUsing a standard translation-backward method, the original English version of PART was translated into Chinese. A convenient sampling of 210 surgical patients was recruited from 6 hospitals in Zhejiang Province to test the psychometric properties of this scale including internal consistency, split-half reliability, content validity, structure validity, and floor/ceiling effect.ResultsA total of 194 patients completed questionnaires. The Chinese version of PART achieved Cronbach’s alphas 0.948 and McDonald’s omega coefficient 0.947, respectively, for the full scale. The estimated odd-even split-half reliability was 0.959. The scale-level content validity index was 0.867, and the items content validity index ranged from 0.83 to 1.0.The output of confirmatory factor analysis revealed a two-factor model with no floor/ceiling effect.ConclusionThe Chinese version of PART demonstrated acceptable reliability and validity among surgical patients. It can be used to evaluate patients’ preoperative preparation and help health professionals provide proper preoperative support. (shrink)

Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election predictions. Objective. Identify, categorize, and present a comprehensive overview of the approaches, techniques, and tools used in election predictions on Twitter. Method. Conducted a systematic mapping study on election predictions on Twitter and provided empirical evidence for the work published between January 2010 and (...) January 2021. Results. This research identified 787 studies related to election predictions on Twitter. 98 primary studies were selected after defining and implementing several inclusion/exclusion criteria. The results show that most of the studies implemented sentiment analysis followed by volume-based and social network analysis approaches. The majority of the studies employed supervised learning techniques, subsequently, lexicon-based approach SA, volume-based, and unsupervised learning. Besides this, 18 types of dictionaries were identified. Elections of 28 countries were analyzed, mainly USA and Indian elections. Furthermore, the results revealed that 50% of the primary studies used English tweets. The demographic data showed that academic organizations and conference venues are the most active. Conclusion. The evolution of the work published in the past 11 years shows that most of the studies employed SA. The implementation of SNA techniques is lower as compared to SA. Appropriate political labelled datasets are not available, especially in languages other than English. Deep learning needs to be employed in this domain to get better predictions. (shrink)

BackgroundNurses working in the intensive care unit clung tenaciously to their job during the COVID-19 pandemic in spite of enduring stressed psychological and physical effects as a result of providing nursing care for the infected patients, which indicates that they possessed a high degree of professionalism and career calling. The aim of this study was to explain the associations between resilience, thriving at work, and ethical leadership influencing the calling of ICU nurses.MethodsFrom December 2020 to January 2021 during the COVID-19 (...) pandemic, a cross-sectional survey of 15 provinces in China was conducted using an online questionnaire. A total of 340 ICU nurses completed sufficient responses to be used in the study. Sociodemographic factors, job demographic factors, resilience, calling, thriving at work, and ethical leadership were assessed using the questionnaire. General linear modeling, hierarchical linear regression analysis, and generalized additive model were performed to examine all the considered research hypotheses.ResultsResilience was positively and significantly associated with calling. Moreover, thriving at work partially mediated the relationship between resilience and calling. The indirect effect of resilience on calling was 0.204, and the direct effect of resilience on calling through thriving at work was 0.215. The total effect of resilience on calling was 0.419. In addition, ethical leadership played a moderating role in the relationship between resilience and calling.ConclusionGreater resilience can positively predict increased calling among Chinese ICU nurses during the COVID-19 pandemic. Moreover, thriving at work is a mechanism that partly transmits the positive effects of resilience on calling. Overall, nurses possessing greater resilience tend to maintain thriving at work in the face of such adversity, further resulting in subsequently increased calling. Besides, findings suggest that there is stronger influence of resilience on calling among nurses working in an organization managed by an ethical leader. The current findings may offer two insights for nursing practitioners and policymakers in the postpandemic world. First, resilience training and intervention are necessary to foster nurses' sense of thriving at work in the nursing industry, further promoting career calling. Second, better training and effort on the development of ethical leadership for leaders in nursing practice are essential to encourage followers to engage in social learning of ethical behaviors and abiding by normatively appropriate conduct, further enacting prosocial values and expressing moral emotions. (shrink)

Previous research has shown that virtuous leader behavior in the form of benevolent leadership has considerable impact on employee creativity. However, little is known as to how and under what conditions these constructs are linked. In the current research, we proposed and tested a moderated mediation model positing leader–member exchange as a mediator, and employee power-distance orientation as a moderator of this relationship. Two studies were conducted to test our hypothesized model. In Study 1, repeated measured data collected from 284 (...) Chinese employees in an information technology company demonstrated that benevolent leadership had a lagged effect on LMX. In Study 2, analyses of multisource and lagged data from 391 Chinese employees in 42 research and development teams, and their direct supervisors indicated that benevolent leadership was positively related to supervisor-rated employee creativity via LMX. In addition, the relationship between benevolent leadership and LMX was stronger for employees high in power-distance orientation. Theoretical implications of benevolent leadership’s research and practical contributions concerning promoting creativity in organizations where benevolent leaders prevail are also discussed. (shrink)

Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium (...) traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole. (shrink)

The choice of coping style of recruits under psychological stress in the process of military task execution has been an important topic in the promotion of military operations and cohesion of military forces. Taking a positive coping style under psychological stress can help recruits overcome the negative effects of stress and improve military morale and group combat effectiveness. Although soldiers' psychological stress in the process of military mission execution having an impact on coping style has been studied by a large (...) body of literature, very little literature has focused on the mechanism of self-efficacy and social support between recruits' psychological stress and coping style from the person-environment fit perspective. Therefore, this study was conducted to analyze the impact of recruits' psychological stress on coping style through a chain mediation model and to discuss the role of self-efficacy and social support in this relationship. Two waves of survey data were utilized to test the research hypotheses on a sample of 1028 Chinese recruits performing military tasks. The results indicated that recruits' psychological stress negatively impacted positive coping styles and positively correlated with negative ones. In addition, self-efficacy and social support mediated the relationship between psychological stress and positive coping style, and self-efficacy mediated the relationship between psychological stress and negative coping style. More importantly, self-efficacy and social support play the chain mediating effect between psychological stress and positive coping style. (shrink)

Discovering high-utility itemsets (HUIs) consists of finding sets of items that yield a high profit in customer transaction databases. An important limitation of traditional high-utility itemset mining (HUIM) is that only the utility measure is used for assessing the interestingness of patterns. This leads to finding several itemsets that have a high profit but contain items that are weakly correlated. To address this issue, this paper proposes to integrate the concept of correlation in HUIM to find profitable itemsets that are (...) highly correlated, using the all-confidence and bond measures. An efficient algorithm named FCHM (fast correlated high-utility itemset miner) is proposed to efficiently discover correlated high-utility itemsets (CHIs). Two versions of the algorithm are proposed: FCHM|$_{all\text{-}confidence}$| and FCHM|$_{bond}$|⁠, which are based on the all-confidence and bond measures, respectively. An experimental evaluation was done using four real-life benchmark datasets from the HUIM literature: mushroom, retail, kosarak and foodmart. Results show that FCHM is efficient and can prune a huge amount of weakly CHIs. (shrink)

ObjectiveDespite its prevalence, insomnia disorder remains poorly understood. In this study, we used machine learning to analyze the functional connectivity disturbances underlying ID, and identify potential predictors of treatment response through recurrent transcranial magnetic stimulation and pharmacotherapy.Materials and methods51 adult patients with chronic insomnia and 42 healthy age and education matched controls underwent baseline anatomical T1 magnetic resonance imaging, resting-stage functional MRI, and diffusion weighted imaging. Imaging was repeated for 24 ID patients following four weeks of treatment with pharmacotherapy, with (...) or without rTMS. A recently developed machine learning technique, Hollow Tree Super was used to classify subjects into ID and control groups based on their FC, and derive network and parcel-based FC features contributing to each model. The number of FC anomalies within each network was also compared between responders and non-responders using median absolute deviation at baseline and follow-up.ResultsSubjects were classified into ID and control with an area under the receiver operating characteristic curve of 0.828. Baseline FC anomaly counts were higher in responders than non-responders. Response as measured by the Insomnia Severity Index was associated with a decrease in anomaly counts across all networks, while all networks showed an increase in anomaly counts when response was measured using the Pittsburgh Sleep Quality Index. Overall, responders also showed greater change in all networks, with the Default Mode Network demonstrating the greatest change.ConclusionMachine learning analysis into the functional connectome in ID may provide useful insight into diagnostic and therapeutic targets. (shrink)

To grasp the truth in traditional Chinese classics, we need to uncover the long obscured "xiang" 象 (image) thinking, which has long been overshadowed by Occidentalism, "xiang thinking" is the most fundamental thought of human beings. The logic of linguistics all comes from "xiang thinking". Through conceptual thinking, people can understand Western classics on metaphysics, yet they may not completely understand the various schools of Chinese classics. The difference between Chinese and Western ways of thinking originated in the difference of (...) the basic views developed in the "Axial period". Since Aristotle, Western metaphysical ideas have all been manifested in substantiality, objectivity, and being ready-made, whereas Chinese Taiji, Dao, Xin-xing, and Zen were manifested in the non-substantiality, non-objectivity, and non-ready-made-ness of a dynamic whole. To grasp substance, rational and logical thinking such as definition, judgment, and reasoning is necessary. On the other hand, to grasp Taiji, Dao, etc., which is a dynamic whole or non-substances, "xiang thinking", which is related to perception and rich in poetic association, is essential. History has taught us a lesson, i.e., when we opened the window to logical thought, we closed that of "xiang thinking". We should remember the words of Xu Guangqi, i.e., "To mingle harmoniously and understand thoroughly so as to excel". /// 重新打开被西方中心论长期遮蔽的 "象思维" 是把握中国传统经典本真的 需要。"象思维" 是人类最本原的思维。语言逻辑部经过 "象思维" 孕育而产生。 用概念思维可以透彻解读西方形上学经典，却未必能透彻解读中国诸家经典。中西 两种思维的不同，源于在 "轴心时期" 产生的基本理念的不同。西方形上学理念从 亚里士多德以降均为不同实体，显示为实体性、对象性、现成性。而中国的太极、 道、心性、禅则显示为动态整体的非实体性、非对象性、非现成性。把握实体，需 要用理性的、逻辑的概念思维，如定义、判断、推理等。而把握动态整体或非实体 的太极、道等，则需要用悟性的、诗意联想的 "象思维"。历史的经验教训是:在我 们打开逻辑概念思维这扇窗户时，却错误地关闭了 "象思维" 这扇窗户。我们应记 住徐光启的箴言 "会通以超胜"。. (shrink)

The complex bursting oscillation and bifurcation mechanisms in coupling systems of different scales have been a hot spot domestically and overseas. In this paper, we analyze the bursting oscillation of a generalized Duffing–Van der Pol system with periodic excitation. Regarding this periodic excitation as a slow-varying parameter, the system can possess two time scales and the equilibrium curves and bifurcation analysis of the fast subsystem with slow-varying parameters are given. Through numerical simulations, we obtain four kinds of typical bursting oscillations, (...) namely, symmetric fold/fold bursting, symmetric fold/supHopf bursting, symmetric subHopf/fold cycle bursting, and symmetric subHopf/subHopf bursting. It is found that these four kinds of bursting oscillations are symmetric. Combining the transformed phase portrait with bifurcation analysis, we can observe bursting oscillations obviously and further reveal bifurcation mechanisms of these four kinds of bursting oscillations. (shrink)