When Hyperpropositions Meet ...

With each proposition P we associate a set of proposition (a hyperproposition) which determines the order in which one may retreat from accepting P, if one cannot fully hold on to P. We first describe the structure of hyperpropositions. Then we describe two operations on propositions, subtraction and merge, which can be modelled in terms of hyperpropositions. Subtraction is an operation that takes away part of the content of a proposition. Merge is an operation that determines the maximal consistent content of two propositions considered jointly. The merge operation gives rise to an inference relation which is, in a certain sense, optimally paraconsistent.     

Contagion in the Representational Field of Water Recycling: Informing New Environment Practice Through Social Representation Theory

Water shortages in Australia have highlighted an urgent need for alternative water sources, and technologically, water recycling is argued to offer the most cost‐effective, environmentally sustainable solution to these shortages. Yet public support for its implementation is low even in the drought‐stricken areas of Australia. Drawing from the theory of social representations, this study addressed community perceptions of water recycling. Three interrelated methodologies were employed in a self‐report questionnaire. Individual difference scaling/multidimensional scaling analyses of three word association tasks revealed that the emergent social representation of water recycling was contradictory in affect. Normative responses indicated an awareness of the need to use recycled water whereas the functional responses were associated with a fear of contamination. An analysis of differential use scales further revealed that the perception of contagion was specific to when recycled water had contact with the body. The discursive analysis of respondents' comments expanded on both these findings. The study identified the themata of purity/impurity as underpinning the social understanding of water recycling. Copyright © 2011 John Wiley & Sons, Ltd.     

Stressors Experienced During Deployment Among Canadian Armed Forces Personnel: Factor Structure of Two Combat Exposure Scales

Combat exposure is linked to increased mental health problems among military personnel. Reliable, precise, and efficient measurement of combat experiences can facilitate understanding of the effects of combat on mental health. This study examined the psychometric properties of 2 scales used to assess deployment experiences in Canadian Armed Forces (CAF) personnel in 2 different settings: during a Third Location Decompression (TLD) program after deployment, and during routine postdeployment screening. Principal components analyses yielded similar results for the 2 measures. The components containing items relevant to Exposure to the Dead and Injured, Dangerous Environment, and Active Combat were common across both surveys. The TLD results revealed a fourth component, Personal Suffering, while the postdeployment screening data revealed a fourth component, Perceived Responsibility. This study found categories of deployment stressors that can be used for further analysis, and underscores the importance of assessing a broad range of exposures in the combat environment.     

Improved Insight into and Prediction of Network Dynamics by Combining VAR and Dimension Reduction

To understand within-person psychological processes, one may fit VAR(1) models (or continuous-time variants thereof) to multivariate time series and display the VAR(1) coefficients as a network. This approach has two major problems. First, the contemporaneous correlations between the variables will frequently be substantial, yielding multicollinearity issues. In addition, the shared effects of the variables are not included in the network. Consequently, VAR(1) networks can be hard to interpret. Second, crossvalidation results show that the highly parametrized VAR(1) model is prone to overfitting. In this article, we compare the pros and cons of two potential solutions to both problems. The first is to impose a lasso penalty on the VAR(1) coefficients, setting some of them to zero. The second, which has not yet been pursued in psychological network analysis, uses principal component VAR(1) (termed PC-VAR(1)). In this approach, the variables are first reduced to a few principal components, which are rotated toward simple structure; then VAR(1) analysis (or a continuous-time analog) is applied to the rotated components. Reanalyzing the data of a single participant of the COGITO study, we show that PC-VAR(1) has the better predictive performance and that networks based on PC-VAR(1) clearly represent both the lagged and the contemporaneous variable relations.     

Interactions of persistent slip bands with a grain boundary on the common primary slip plane in a copper bicrystal

In this letter, the dislocation patterns on the common primary slip plane in a fatigued \[1-34]-\[182-7] copper bicrystal with a Sigma=19b grain boundary (GB) have been investigated using the electron channelling contrast technique in a scanning electron microscope. The results show that the two-phase dislocation structure, such as veins and persistent slip band (PSB) walls, embedded within veins, can be clearly seen on the common primary slip plane. In particular, the interactions of PSBs with the GB are clearly revealed. It is found that there are three kinds of interaction mode between the GB and the dislocations during cyclic deformation, and those are discussed. It is suggested that the dislocations carried by PSBs cannot transfer through the GB continuously even though the bicrystal has a common primary slip plane and its surface slip bands are continuous across the GB.     

The personality of meaning in life: Associations between dimensions of life meaning and the Big Five

The goal of the current study was to identify aspects of personality that are associated with different ways in which people find meaning in life. This was achieved using constrained principal component analysis (CPCA) on data from 322 university students, who completed the Sources of Meaning and Meaning in Life questionnaire and the Big Five Aspects Scale. CPCA demonstrated that personality traits and life meaning are associated, but not redundant, with one another. Specifically, respondents with high scores on lower-level aspects of Openness to Experience tended to derive meaning from questioning, learning and challenging tradition, whereas those with high scores on aspects of Conscientiousness and Extraversion tended to derive meaning from success at work, health, and family. Results suggest that personality traits are associated with variations in the domains used to derive meaning in life, and demonstrate the utility of CPCA as an innovative statistical technique for the study of individual differences.     

Imagining an ‘ideal school’: an approach for reflecting on principals’ educational creed

In this paper, we describe an approach to the study and development of school principals’ school creed. The approach and its underlying method are grounded in the phenomenological tradition, predominantly in the philosophy of Merleau-Ponty. School principals are asked to imagine an ideal school and present it both visually and verbally. We illustrate the potential of this process using one ideal school proposal developed by a high school principal in Israel. The paper concludes with a discussion of the implications of the approach for research, theory and practice.     

骨折治疗方法与原则的最优化历程

多年来骨折治疗,新旧技术、新旧理论相互融合,相互碰撞,产生了新的理论和方法,使得临床疗效显著提高,现阶段理智的临床医生应该融汇各家之长,多方互补,对每一位骨折患者的治疗都应该按照最优化的原则进行.但是在医疗过程中总存在着如方法选择不当或者错误,过度治疗,医患信任危机,医疗伦理道德的丧失等情况,我们应该用矛盾分析的方法来思考这些问题.     

抗抑郁药应用选择的思考

目前市场上可供选择的抗抑郁药越来越多.从系统方法论、医学模式转变和矛盾重点论的角度来阐述临床上应该如何选择用药,才能使治疗效果和医疗费用更符合个体的情况,达到比较和谐的状态.     

Component Models for Fuzzy Data

The fuzzy perspective in statistical analysis is first illustrated with reference to the “Informational Paradigm” allowing us to deal with different types of uncertainties related to the various informational ingredients (data, model, assumptions). The fuzzy empirical data are then introduced, referring to J LR fuzzy variables as observed on I observation units. Each observation is characterized by its center and its left and right spreads (LR₁ fuzzy number) or by its left and right “centers” and its left and right spreads (LR₂ fuzzy number). Two types of component models for LR₁ and LR₂ fuzzy data are proposed. The estimation of the parameters of these models is based on a Least Squares approach, exploiting an appropriately introduced distance measure for fuzzy data. A simulation study is carried out in order to assess the efficacy of the suggested models as compared with traditional Principal Component Analysis on the centers and with existing methods for fuzzy and interval valued data. An application to real fuzzy data is finally performed. We would like to express our gratitude to the Editor, the Associate Editor, and the Referees whose comments and suggestions improved significantly the quality of the paper.