A weighted polynomial regression method for local fitting of spatial data

Typically, parametric approaches to spatial problems require restrictive assumptions. On the other hand, in a wide variety of practical situations nonparametric bivariate smoothing techniques has been shown to be successfully employable for estimating small or large scale regularity factors, or even the signal content of spatial data taken as a whole.We propose a weighted local polynomial regression smoother suitable for fitting of spatial data. To account for spatial variability, we both insert a spatial contiguity index in the standard formulation, and construct a spatial-adaptive bandwidth selection rule. Our bandwidth selector depends on the Gearys local indicator of spatial association. As illustrative example, we provide a brief Monte Carlo study case on equally spaced data, the performances of our smoother and the standard polynomial regression procedure are compared.This note, though it is the result of a close collaboration, was specifically elaborated as follows: paragraphs 1 and 2 by T. Sclocco and the remainder by M. Di Marzio. The authors are grateful to the referees for constructive comments and suggestions.     

Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy): spatial special issue

To improve the quality of prediction of radioactive contamination, geostatistical methods, and in particular multivariate geostatistical models, are increasingly being used. These methods, however, are optimal only in the case in which the data may be assumed Gaussian and do not properly cope with data measurements that are discrete, nonnegative or show some degree of skewness. To deal with these situations, here we consider a hierarchical model in which non-Gaussian variables of different kind are handled simultaneously. We show that when observations are assumed to be conditionally distributed as Poisson and Gamma, variograms and cross-variograms have convenient simple forms, and estimation of the parameters of the model can be carried out by Monte Carlo EM. This work was inspired by radioactive contamination data from the Maddalena Archipelago (Sardinia, Italy).     

Behavioural Addictions in Adolescents and Young Adults: Results from a Prevalence Study

Our study aims to assess the prevalence of behavioural addictions in an adolescent population, evaluating the effects of gender and age, and to assess the correlations among different behavioural addictions. 2853 high school students were assessed in order to evaluate the prevalence of behavioural addictions such as Pathological Gambling (PG), Compulsive Buying (CB), Exercise Addiction (EA), Internet Addiction (IA), and Work Addiction (WA), in a population of Italian adolescents. The South Oaks Gambling Screen-Revised Adolescent (SOGS-RA), the Compulsive Buying Scale (CBS), the Exercise Addiction Inventory (EAI), the Internet Addiction Test (IAT), and the Work Addiction Risk Test (WART), were compiled anonymously by the students. Overall prevalence was 7.0% for PG, 11.3% for CB, 1.2% for IA, 7.6% for WA, 8.5% for EA. PG and EA were more common among boys, while gender had no effect on the other conditions. CB was more common among younger (<18 years old) students. The scores of all of these scales were significantly correlated. The strong correlation among different addictive behaviours is in line with the hypothesis of a common psychopathological dimension underlying these phenomena. Further studies are needed to assess personality traits and other clinical disorders associated with these problems behaviours.     

Identifying Dispersion Effects in Robust Design Experiments—Issues and Improvements

The two experimental methods most commonly used for reducing the effect of noise factors on a response of interest Y aim either to estimate a model of the variability (V(Y), or an associated function), that is transmitted by the noise factors, or to estimate a model of the ratio between the response (Y) and all the control and noise factors involved therein. Both methods aim to determine which control factor conditions minimise the noise factors' effect on the response of interest, and a series of analytical guidelines are established to reach this end. Product array designs allow robustness problems to be solved in both ways, but require a large number of experiments. Thus, practitioners tend to choose more economical designs that only allow them to model the surface response for Y. The general assumption is that both methods would lead to similar conclusions. In this article we present a case that utilises a design based on a product design and for which the conclusions yielded by the two analytical methods are quite different. This example casts doubt on the guidelines that experimental practice follows when using either of the two methods. Based on this example, we show the causes behind these discrepancies and we propose a number of guidelines to help researchers in the design and interpretation of robustness problems when using either of the two methods.     

The minimal overlap rule revisited

This paper provides an analysis of the Minimal Overlap Rule, a solution for bankruptcy problems introduced by O’Neill (1982). We point out that this rule can be understood as a composition of Ibn Ezra’s proposal and the recommendation given by the Constrained Equal Loss Rule. Following an interpretation of bankruptcy problems in terms of TU games, we show that the Minimal Overlap Value is the unique solution for bankruptcy games which satisfies Anonymity and Core Transition Responsiveness.     

Weber on anomie

InGesammelte Aufsätze zur Religionssoziologie, Max Weber discussed the anomic potential of some non-Western religious doctrines. This paper provides an analysis of Weber's writings on anomie and attempts to show the relevance of Weber's work to contemporary anomie research. First, I locate Weber's treatment of anomie within his discussion of great world religions, highlighting its significance in a cross-cultural context. Second, I compare Weber's notion of anomie with current evaluations of anomie and discuss a typology of usages of the term. Finally, I explore the suggested usefulness of Weber's work on anomie for contemporary purposes.     

Knowledge Transfer between For‐Profit Corporations and Their Corporate Foundations

This article investigates the impact of knowledge transfer (Goh 2002) from founder firms to the corporate foundations (CFs) on the CFs’ effectiveness. Starting from a typology of CFs’ effectiveness (Ostrower 2006a), we conducted a survey addressed to a sample of Italian CFs to address the impact of different knowledge transfer methods (KTMs) on three dimensions of CFs’ orientation to effectiveness: proactive orientation, social advocacy, and capacity building. The research identified four different KTMs and, using a linear regression, pointed out that the methods adopted by founder firms have a significant influence on proactivity, competences, and on social advocacy of CFs.     

The policies of unemployment protection in Europe

The abundant literature on welfare state policies, regimes or ‘worlds’ has been only limitedly interested in unemployment protection, and even less in youth unemployment protection. What is clearly lacking in the literature is an updated analysis of the most recent policies developed in European countries targeting youth. This mini‐symposium aims to fill in this gap by presenting findings from an EU‐funded research project entitled ‘Youth, Unemployment and Exclusion in Europe: A Multidimensional Approach to Understanding the Conditions and Prospects for Social and Political Integration of Young Unemployed’ (YOUNEX). The main aim of the research endeavour was to develop theory and contribute to empirical knowledge concerning the social and political exclusion of unemployed youth in Europe.