An Integrated Cognitive Theory of Comprehension

This article proposes an integrated cognitive theory of reading and listening that draws on a maximalist account of comprehension and emphasizes the role of bottom-up and top-down processing. The theoretical framework draws on the findings of previous research and integrates them into a coherent and plausible narrative to explain and predict the comprehension of written and auditory inputs. The theory is accompanied by a model that schematically represents the fundamental components of the theory and the comprehension mechanisms described. The theory further highlights the role of perception and word recognition (underresearched in reading research), situation models (missing in listening research), mental imagery (missing in both streams), and inferencing. The robustness of the theory is discussed in light of the principles of scientific theories adopted from Popper (1959).     

A new generalization of the Weibull-geometric distribution with bathtub failure rate

In this paper, the researchers attempt to introduce a new generalization of the Weibull-geometric distribution. The failure rate function of the new model is found to be increasing, decreasing, upside-down bathtub, and bathtub-shaped. The researchers obtained the new model by compounding Weibull distribution and discrete generalized exponential distribution of a second type, which is a generalization of the geometric distribution. The new introduced model contains some previously known lifetime distributions as well as a new one. Some basic distributional properties and moments of the new model are discussed. Estimation of the parameters is illustrated and the model with two known real data sets is examined.     

Truncated-exponential skew-symmetric distributions

The family of skew distributions introduced by Azzalini and extended by others has received widespread attention. However, it suffers from complicated inference procedures. In this paper, a new family of skew distributions that overcomes the difficulties is introduced. This new family belongs to the exponential family. Many properties of this family are studied, inference procedures developed and simulation studies performed to assess the procedures. Some particular cases of this family, evidence of its flexibility and a real data application are presented. At least 10 advantages of the new family over Azzalini's distributions are established.     

The dark side of leadership: A systematic review of creativity and innovation

It is believed that workplace creativity and innovation are fostered by positive leader behaviors and positive workplace relationships and hindered by the opposite. However, some challenge this view and argue that creativity and innovation can also be fostered when employees experience what is increasingly referred to as “the dark side of leadership”. Research in this area is sparse, contradictory, and overly confusing. We provide a comprehensive systematic review of 106 empirical studies on this topic. We review research on a broad range of constructs, including abusive supervision, authoritarian leadership, narcissistic leadership, and close monitoring. As might be expected, a larger number of the articles reviewed found a negative relationship, but there are important discrepancies and details. Our review reports the main effects, summarizes the results of the mediating and moderating variables, and highlights methodological shortcomings of the previous literature. On this basis, several recommendations are made to advance this field of research.     

Attachment and joint attention in infants: The role of expectation

Previous research highlighted the correlation between parent–infant's attachment quality and joint attention skills. However, the underlying mechanisms of this relationship are still unclear. The aim of this study was to assess whether it is by mediating the expectation component in Internal Working Models that the quality of attachment style can affect joint attention. At first, 12- to 20-month-old infants were classified into secure and insecure groups using the Strange Situation Procedure. On a following day, using a violation-of-expectation paradigm, infants were habituated to two joint attention videos. Finally, the mean looking time duration of secure and insecure infants were compared with each other between two “divergent attention” and “joint attention” videos. Infants looked longer for divergent attention videos suggesting they did have expectation regarding the appropriate response in triadic interactions. In line with our main hypothesis, secure infants, but not insecure ones, looked longer in the divergent attention situation when an attachment-related context was present, revealing the possible mediating role of “expectations” in the correlation between attachment and joint attention.     

Solving Noisy ICA Using Multivariate Wavelet Denoising with an Application to Noisy Latent Variables Regression

A novel approach to solve the independent component analysis (ICA) model in the presence of noise is proposed. We use wavelets as natural denoising tools to solve the noisy ICA model. To do this, we use a multivariate wavelet denoising algorithm allowing spatial and temporal dependency. We propose also using a statistical approach, named nested design of experiments, to select the parameters such as wavelet family and thresholding type. This technique helps us to select more convenient combination of the parameters. This approach could be extended to many other problems in which one needs to choose parameters between many choices. The performance of the proposed method is illustrated on the simulated data and promising results are obtained. Also, the suggested method applied in latent variables regression in the presence of noise on real data. The good results confirm the ability of multivariate wavelet denoising to solving noisy ICA.     

Bivariate discrete generalized exponential distribution

In this paper, we develop a bivariate discrete generalized exponential distribution, whose marginals are discrete generalized exponential distribution as proposed by Nekoukhou, Alamatsaz and Bidram [Discrete generalized exponential distribution of a second type. Statistics. 2013;47:876–887]. It is observed that the proposed bivariate distribution is a very flexible distribution and the bivariate geometric distribution can be obtained as a special case of this distribution. The proposed distribution can be seen as a natural discrete analogue of the bivariate generalized exponential distribution proposed by Kundu and Gupta [Bivariate generalized exponential distribution. J Multivariate Anal. 2009;100:581–593]. We study different properties of this distribution and explore its dependence structures. We propose a new EM algorithm to compute the maximum-likelihood estimators of the unknown parameters which can be implemented very efficiently, and discuss some inferential issues also. The analysis of one data set has been performed to show the effectiveness of the proposed model. Finally, we propose some open problems and conclude the paper.