Can Psychosocial Intervention Improve Peer and Sibling Relations Among War‐affected Children? Impact and Mediating Analyses in a Randomized Controlled Trial

Social resources are considered important protectors in traumatic conditions, but few studies have analyzed their role in psychosocial interventions among war‐affected children. We examined (1) whether a psychosocial intervention (teaching recovery techniques, TRT) is effective in improving peer and sibling relations, and (2) whether these potentially improved relations mediate the intervention's impacts on children's mental health. Participants were 428 Palestinian children [10–13 (mean = 11.29, standard deviation SD = .68)‐year‐old girls (49.4 percent) and boys (50.6 percent)], who were cluster‐randomized into the TRT and wait‐list control groups. They reported the quality of peer (friendship and loneliness) and sibling (intimacy, warmth, conflict, and rivalry) relations, and posttraumatic stress, depressive and psychological distress symptoms, as well as psychosocial well‐being at baseline (T1), postintervention (T2), and six month follow‐up (T3). Results showed gender‐specific TRT intervention effects: Loneliness in peer relations reduced among boys and sibling rivalry reduced among girls. The TRT prevented the increase in sibling conflict that happened in the control group. The mediating hypothesis was partially substantiated for improved peer relations, and beneficial changes in sibling relations were generally associated with improved mental health.     

Que faut‐il voir dans les écarts de rémunération entre les travailleurs immigrés des pays du Golfe: l'effet d'a priori patronaux ou la simple conséquence de coûts d'opportunité différents?

Les auteurs s'intéressent aux disparités salariales entre les différents groupes de migrants qualifiés qui travaillent en grand nombre pour le secteur privé dans les États du Conseil de coopération du Golfe. Ils se demandent notamment si la prime salariale des Occidentaux (par rapport aux travailleurs venus d'Asie ou d'autres États arabes) découle d'éventuels a priori des employeurs. L'analyse, qui repose sur des données de 2012–2014 et sur deux méthodes de décomposition classiques, infirme l'hypothèse: les caractéristiques observables relatives à la productivité expliquent entre un tiers et trois quarts des écarts; le coût d'opportunité de la migration, supérieur pour les Occidentaux, explique la portion restante.     

Kirkuk conflict in its ethnic/political media: the Turkmen newspaper Alqal'a as a model

This article explores the Kirkuk conflict through the Turkmens’ newspaper Alqal'a. Using agenda-setting and framing/priming for theoretical background and qualitative content analysis as a method, two macro-themes, related to the conflict, are found to be fundamental therein. These two main themes are: (1) exclusion and (2) self-confirmation. The two macro-themes overarch several micro- or sub-themes and are closely related to each other. They are set to inform the readers about what to think and how to think about the conflict. While ‘exclusion’ constitutes the cause, ‘self-confirmation’ is the latter's effect.     

Bayes Inference in Constant Partially Accelerated Life Tests for the Generalized Exponential Distribution with Progressive Censoring

In this paper, the problem of constant partially accelerated life tests when the lifetime follows the generalized exponential distribution is considered. Based on progressive type-II censoring scheme, the maximum likelihood and Bayes methods of estimation are used for estimating the distribution parameters and acceleration factor. A Monte Carlo simulation study is carried out to examine the performance of the obtained estimates.     

Psychology in the Arab World: Past, Present, and Future

In this article, we present a broad-based view of psychology in the Arab countries. We begin by casting light on the relevant contributions by ancient Arab scholars in the Middle Ages. Given that systematic scientific investigation of this legacy has been minuscule, we argue that in the future, scholars seeking to provide a more balanced and comprehensive history of Arab psychology should reanalyze these works. We point out that in the early decades of the modern twentieth century, Western psychology was introduced in the Arab countries, especially in Egypt—the gateway through which such psychology was introduced and practiced. By the early 1960s, a number of universities had been established in some Arab countries, and Egyptian academicians, including psychologists, were invited to perform teaching, research, and administration tasks. Their legacy was a discipline bearing most of the strengths and weaknesses of Egyptian psychology, although in spite of such commonalties, there exist also some interesting differences characterizing psychology in the various Arab countries. The final section of the article summarizes some key aspects endemic to psychology in the Arab countries.     

Bayesian estimation for the Pareto income distribution

The Bayes estimators of the Gini index, the mean income and the proportion of the population living below a prescribed income level are obtained in this paper on the basis of censored income data from a pareto income distribution. The said estimators are obtained under the assumptions of a two-parameter exponential prior distribution and the usual squared error loss function. This work is also extended to the case when the income data are grouped and the exact incomes for the individuals in the population are not available. The method for the assessment of the hyperparameters is also outlined. Finally, the results are generalized for the doubly truncated gamma prior distribution. Now deceased.     

Bayesian classification with multivariate autoregressive sources that might have different orders

The main objective of this paper is to develop an exact Bayesian technique that can be used to assign a multivariate time series realization to one of several autoregressive sources, with unknown coefficients and precision, that might have different orders. The foundation of the proposed technique is to develop the posterior mass function of a classification vector, in an easy form, using the conditional likelihood function. A multivariate time series realization is assigned to the multivariate autoregressive source with the largest posterior probability. A simulation study, with uniform prior mass function, is carried out to demonstrate the performance of the proposed technique and to test its adequacy in handling the multivariate classification problems. The analysis of the numerical results supports the adequacy of the proposed technique in solving the classification problems with multivariate autoregressive sources.     

Bayesian inferences and forecasts with moving averages processes

This paper will develop Bayesian inferential and forecasting techniques which can be used with any moving average process. By employing the conditional likelihood function, at-approximation to the predictive distribution and the marginal posterior distribution of the moving average parameters is developed. Several examples demonstrate posterior and predictive inferences.     

Facility Location with Dynamic Distance Functions

Facility location problems have always been studied with theassumption that the edge lengths in the network are static anddo not change over time. The underlying network could be used to model a city street networkfor emergency facility location/hospitals, or an electronic network for locating information centers. In any case, it is clear that due to trafficcongestion the traversal time on links changes with time. Very often, we have estimates as to how the edge lengths change over time, and our objective is to choose a set of locations (vertices) ascenters, such that at every time instant each vertex has a center close to it (clearly, the center close to a vertex may change over time). We also provide approximation algorithms as well as hardness results forthe K-center problem under this model. This is the first comprehensive study regarding approximation algorithmsfor facility location for good time-invariant solutions.     

Response to the COVID-19: Understanding implications of government lockdown policies

The rising number of COVID-19 cases and economic implications of lockdown measures indicate the tricky balancing act policy makers face as they implement the subsequent phases of 'unlock'. We develop a model to examine how lockdown and social distancing measures have influenced the behavioral conduct of people. The current situation highlights that policy makers need to focus on bringing awareness and social restraint among people rather than going for stringent lockdown measures. We believe this work will help the policy makers gain insights into the troubled COVID-19 times ahead, and based on the estimates, they can frame policies to navigate these wild waves in the best possible way.