C Zhou

We study an application of gaggle theory to unary negative modal operators. First we treat negation as impossibility and get a minimal logic system Ki that has a perp semantics. Dunn 's kite of different negations can be dealt with in the extensions of this basic logic Ki. Next we treat negation as “unnecessity” and use a characteristic semantics for different negations in a kite which is dual to Dunn 's original one. Ku is the minimal logic that has a characteristic semantics. We also show that Shramko's falsification logic FL can be incorporated into some extension of this basic logic Ku. Finally, we unite the two basic logics Ki and Ku together to get a negative modal logic K-, which is dual to the positive modal logic K+ in [7]. Shramko has suggested an extension of Dunn 's kite and also a dual version in [12]. He also suggested combining them into a “united” kite. We give a united semantics for this united kite of negations.

Probability logics have been an active topic of investigation of beliefs in type spaces in game theoretical economics. Beliefs are expressed as subjective probability measures. Savage’s postulates in decision theory imply that subjective probability measures are not necessarily countably additive but finitely additive. In this paper, we formulate a probability logic Σ + that is strongly complete with respect to this class of type spaces with finitely additive probability measures, i.e. a set of formulas is consistent in Σ + iff it is satisfied in a finitely additive type space. Although we can characterize Σ + -theories satisfiable in the class as maximally consistent sets of formulas, we prove that any canonical model of maximally consistent sets is not universal in the class of type spaces with finitely additive measures, and, moreover, it is not a type space. At the end of this paper, we show that even a minimal use of probability indices causes the failure of compactness in probability logics.

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

Mining time series data is of great significance in various areas. To efficiently find representative patterns in these data, this article focuses on the definition of a valid dissimilarity measure and the acceleration of partitioning clustering, a common group of techniques used to discover typical shapes of time series. Dissimilarity measure is a crucial component in clustering. It is required, by some particular applications, to be invariant to specific transformations. The rationale for using the angle between two time series to define a dissimilarity is analyzed. Moreover, our proposed measure satisfies the triangle inequality with specific restrictions. This property can be employed to accelerate clustering. An integrated algorithm is proposed. The experiments show that angle-based dissimilarity captures the essence of time series patterns that are invariant to amplitude scaling. In addition, the accelerated algorithm outperforms the standard one as redundancies are pruned. Our approach has been applied to discover typical patterns of information diffusion in an online social network. Analyses revealed the formation mechanisms of different patterns.

The ability to recover from official match-play across a single and multiple matches is often considered a key factor in subsequent performance for modern professional basketball. The aims of this study were to: explore the differences in match performances between different match congestion cycles ; and identify the key performance indicators discriminating between winning and losing during different match congestion cycles. The current study indicated that scoring close to or very far away was significantly greater for winning matches separated by 1- and 2-days of rest compared to consecutive matches. Additionally, shooting efficiency, and attaining Defensive Rebounds and Steals, were significant offensive and defensive KPIs that differentiated winning and losing teams. Similarly, opponent quality and match pace were important situational variables that affected match outcome during different match congestion cycles. While match location had an impact on winning following 1- and 2-days of rest, it had no impact for back-to-back matches. The current results will support coaches' offensive, defensive and recovery strategies during various match congestion cycles for a greater probability of winning NBA matches.

In the paper, several data reduction techniques for machine learning from big datasets are discussed and evaluated. The discussed approach focuses on combining several techniques including stacking, rotation, and data reduction aimed at improving the performance of the machine classification. Stacking is seen as the technique allowing to take advantage of the multiple classification models. The rotation-based techniques are used to increase the heterogeneity of the stacking ensembles. Data reduction makes it possible to classify instances belonging to big datasets. We propose to use an agent-based population learning algorithm for data reduction in the feature and instance dimensions. For diversification of the classifier ensembles within the rotation also, alternatively, principal component analysis and independent component analysis are used. The research question addressed in the paper is formulated as follows: does the performance of a classifier using the reduced dataset be improved by integrating the data reduction mechanism with the rotation-based technique and the stacking?

Background: Previous systematic review indicated the prevalence of prenatal anxiety as 14–54%. Pregnant women are a high-risk population for COVID-19. However, the prevalence of anxiety symptoms and related factors is unknown in Chinese pregnant women during COVID-19 outbreak.Objective: To investigate the prevalence of anxiety symptoms and the related factors in Chinese pregnant women who were attending crisis intervention during the COVID-19 pandemic.Methods: The data of this cross-sectional study were collected in about 2 months. Data analysis was performed from April to May 2020. Participants completed a set of questionnaires via the Wechat Mini-program before starting the online self-help crisis intervention for COVID-19 epidemic. A total of 2,120 Chinese pregnant women who were attending a self-help crisis intervention participated in this study. A survey was developed to address possible stress-related factors in pregnant women during the COVID-19 outbreak, including demographic, socioeconomic, and pregnancy-related factors, as well as COVID-19 related factors. Generalized Anxiety Disorder-7 scale and the 10-item perceived stress scale were, respectively, employed to measure anxiety and stress-related factors.Results: A total of 21.7% of pregnant women reported at least mild anxiety, and only 82 women reported moderate to severe anxiety. Factors associated with at least mild anxiety included living in Hubei province, nobody providing everyday life support, pelvic pain or vaginal bleeding, and higher perceived stress. Having relatives or neighbors with a diagnosis of COVID-19 was not associated with anxiety.Conclusions and Relevance: Our findings indicate that evaluation and intervention for maternal and infant health are necessary in pregnant women with anxiety during COVID-19 epidemic, especially those with higher perceived stress, less everyday life support, or vaginal bleeding. Interactions among these related medical, social and psychological factors need to be investigated in future studies.

BackgroundMore than 15% of Chinese respondents reported somatic symptoms in the last week of January 2020. Promoting resilience is a possible target in crisis intervention that can alleviate somatization.ObjectivesThis study aims to investigate the relationship between resilience and somatization, as well as the underlying possible mediating and moderating mechanism, in a large sample of Chinese participants receiving a crisis intervention during the coronavirus disease 2019 epidemic.MethodsParticipants were invited online to complete demographic information and questionnaires. The Symptom Checklist-90 somatization subscale, 10-item Connor–Davidson resilience scale, and 10-item Perceived Stress Scale were measured.ResultsA total of 2,557 participants were included. Spearman correlation analysis revealed that lower resilience was associated with more somatic symptoms. The conditional process model was proved. The interaction effects between perceived stress and sex predicted somatization.ConclusionResilience is a key predictor of somatization. The mediating effects of perceived stress between resilience and somatization work in the context of sex difference. Sex-specific intervention by enhancing resilience is of implication for alleviating somatization during the coronavirus disease 2019 epidemic.

PurposePlaying styles play a key role in winning soccer matches, but the technical and physical styles of play between home and away match considering team quality in the Chinese Soccer Super League remain unclear. The aim of this study was to explore the technical and physical styles of play between home and away matches integrating with team quality in the CSL.Materials and methodsThe study sample consists of 480 performance records from 240 matches during the 2019 competitive season in the CSL. These match events were collected using a semi-automatic computerized video tracking system, Amisco Pro®. A k-means cluster analysis was used to evaluate team quality and then using principal component analysis to identify the playing styles between home and away matches according to team quality. Differences between home and away matches in terms of playing styles were analyzed using a linear mixed model.ResultsOur study found that PC1 presented a positive correlation with physical-related variables such as HIRD, HIRE, HSRD, and HSRE while PC2 was positively associated with the passing-related variables such as Pass, FPass, PassAcc, and FPAcc. Therefore, PC1 typically represents intense-play styles while PC2 represents possession-play styles at home and away matches, respectively. In addition, strong teams preferred to utilize intensity play whereas medium and weak teams utilized possession play whenever playing at home or away matches. Furthermore, the first five teams in the final overall ranking in the CSL presented a compensated technical-physical playing style whereas the last five teams showed inferior performance in terms of intensity and possession play.ConclusionIntensity or possession play was associated with the final overall ranking in the CSL, and playing styles that combine these two factors could be more liable to win the competition. Our study provides a detailed explanation for the impact of playing styles on match performances whereby coaches can adjust and combine different playing styles for ultimate success.

Leadership humor is widely used in management practice and has aroused extensive discussion in academia. On account of the two-sided influence of leader humor on employees, its double-edged sword effect on employee behavior has been put more emphasis. As a benign violation of organizational norms and a kind of pro-organizational violation, respectively, both Leadership humor and employee bootleg innovation have the characteristics of violating organizational norms, but few studies have examined the relationship between them. Based on benign violation theory and social cognition theory, this study conducted a two-stage questionnaire survey and statistical-econometric analysis of 324 employees in 23 IT and manufacturing technology companies in Guangdong, Jiangsu, Zhejiang, Hubei, Beijing, and Shanghai, China. It not only examined the relationship between leadership humor and employee bootleg innovation but also tested a moderated mediation model. Results show that leadership humor is positively correlated with psychological empowerment and employee bootleg innovation, namely, leadership humor indirectly and positively affects employee bootleg innovation through psychological empowerment. Moreover, the indirect effect is positively regulated by leadership emotional trust. The higher the emotional trust of employees to leadership, the stronger the mediating role of psychological empowerment between leader humor and bootleg innovation behavior. The study enriches the existing path of research on the double-edged impact of leader humor on employee behavior, expands the boundary conditions of the relationship between empowered cognitive mediation and employee bootleg innovation and provides enlightenments for Chinese leaders to effectively apply the tool of leader humor.

BackgroundMethamphetamine addicts can experience severe emotional processing disorders, with abnormal responses to emotional and drug-related stimuli. These aberrant behaviors are one of the key factors leading to relapse. Nevertheless, the characteristics of addicts’ responses to drug-related stimuli and their responses to emotional stimuli remain controversial.Methods52 methamphetamine addicts from China passively viewed three different categories of images: Drug-related; positive emotional; and negative emotional. In the first task, participants completed a 9-point Self-Assessment Manikin (SAM) scale, rating the valence of each image. In the second, they performed a cued-action task while electroencephalography (EEG) data were recorded.ResultDrug-related images were rated negatively, with an average rating of 3.57. However, reaction times to drug-related stimuli were significantly faster than for negative stimuli (p = 0.030), and were indistinguishable from positive stimuli (p > 0.99). Similarly, EPN amplitudes evoked by drug-related images were significantly larger than those evoked by negative stimuli (p 0.99). LPP amplitudes evoked by drug-related stimuli were significantly smaller than those evoked by negative (p < 0.001) and positive stimuli (p = 0.004).ConclusionDespite negative self-assessments of drug-related imagery, MA-addicts reaction times were no slower than positive reactions. Similarly, drug-related and positive imagery EPN amplitudes were indistinguishable. Together, these results suggest increased attentional resources were allocated to the processing of drug-related stimuli and the pathways responsible partially overlap with the those recruited in processing positive emotional imagery in addicts. Moreover, in the late stage of visual processing, MA-addicts showed reduced brain activity in response to drug-related stimuli, suggesting reverse inhibition in response preparation and emotional appraisal. These findings may provide a reference for clinicians treating drug-taking behavior and for the development of new models of rehabilitation therapy.

Based on social learning theory and the trickle-down effects, in which behavioral patterns cascade from one management level to the next, we attempt to answer whether upper-level managers’ temporal leadership can be transferred to lower-level managers to form their temporal leadership, and what the mediating mechanisms and boundary conditions for this occurrence are. By analyzing the data from 234 middle-level managers and 686 junior managers/employees, we found that top managers’ temporal leadership was positively associated with middle-level managers’ temporal leadership through the mediating role of middle-level managers’ temporal leadership perspective and that the relationship was moderated by middle-level managers’ identification with the top manager. Identification with the top manager, in particular, strengthens both the top manager’s positive effect on middle-level managers’ temporal leadership and the top manager’s temporal leadership’s mediating role in this relationship through their temporal leadership perspective. The theoretical and managerial implications of these findings are investigated.