The TAL-Family of Rules for Bankruptcy Problems

This paper analyzes a family of rules for bankruptcy problems that generalizes the Talmud rule (T) and encompasses both the constrained equal-awards rule (A) and the constrained equal-losses rule (L). The family is defined by means of a parameter that can be interpreted as a measure of the distributive power of the rule. We provide a systematic study of the structural properties of the rules within the family and its connections with the existing literature.     

Health-related determinants of perceived quality of life: a comparison between first-year university students and their working peers

This study compares aspects of the health-related behaviors and working life of first-year university students with those of their working counterparts and assesses the roles of these aspects as predictors of each groups' perceived quality of life (QoL). Subjects were taken from two cross-sectional data sets (a student survey and a population survey) from the Swedish central-western region of Osterg?tland. Male and female respondents aged 20-35 years were extracted and comparison were made considering in turn socio-demographic characteristics, health-related behaviors, exposure to abusive events at work and perceived QoL. University students smoked and used oral snuff in smaller proportions, they were not as frequent drinkers as their working counterparts, but they tended to drink more when they did drink. Threats and violence were less prevalent among students, but sexual harassment, were almost as common. The strongest predictors of perceived QoL for both groups are expected and former perceived QoL, followed by current self-rated health.     

Fitting insurance and economic data with outliers: a flexible approach based on finite mixtures of contaminated gamma distributions

Insurance and economic data are frequently characterized by positivity, skewness, leptokurtosis, and multi-modality; although many parametric models have been used in the literature, often these peculiarities call for more flexible approaches. Here, we propose a finite mixture of contaminated gamma distributions that provides a better characterization of data. It is placed in between parametric and non-parametric density estimation and strikes a balance between these alternatives, as a large class of densities can be implemented. We adopt a maximum likelihood approach to estimate the model parameters, providing the likelihood and the expected-maximization algorithm implemented to estimate all unknown parameters. We apply our approach to an artificial dataset and to two well-known datasets as the workers compensation data and the healthcare expenditure data taken from the medical expenditure panel survey. The Value-at-Risk is evaluated and comparisons with other benchmark models are provided.     

A Multi-Exchange Neighborhood for Minimum Makespan Parallel Machine Scheduling Problems

We propose new local search algorithms for minimum makespan parallel machine scheduling problems, which perform multiple exchanges of jobs among machines. Inspired by the work of Thompson and Orlin (1989) on cyclic transfer neighborhood structures, we model multiple exchanges of jobs as special disjoint cycles and paths in a suitably defined improvement graph, by extending definitions and properties introduced in the context of vehicle routing problems (Thompson and Psaraftis, 1993) and of the capacitated minimum spanning tree problem (Ahuja et al., 2001). Several algorithms for searching the neighborhood are suggested.We report the results of a wide computational experimentation, on different families of benchmark instances, performed for the case of identical machines. This problem has been selected as a case study to perform a comparison among the alternative algorithms, and to discover families of instances for which the proposed neighborhood may be promising in practice. Based on the results of the experiments, we can suggest which among the many possible variants of the proposed approaches may be more promising for developing local search algorithms based on multi-exchange moves for related problems. Also, on some families of instances, which are very hard to solve exactly, the most promising multi-exchange algorithms were observed to dominate, in solution quality and in computational time, competitive benchmark heuristics.     

The Management of Redundancies in Europe: The Case of Spain

The paper presents the findings of a comparative and interdisciplinary legal and economic study on managing labour redundancies in seven EU member countries. It is structured for comparability between the systems examined. The introductory section contains an account of the evolution of the Spanish labour market, with special reference to redundancy trends, of the features of the programmes for managing redundancies, of the roles of forms and the ‘external environment’ in handling workforce adjustments. The second section presents a map of policies that work to prevent labour redundancies (preventive measures) such as flexibility, training etc. Next, the instruments for handling temporary labour redundancies (retentive measures) are examined (e.g. short-time working, temporary layoffs etc.) The following section is devoted to instruments and programmes involved in the management of permanent labour redundancies (expulsive measures), e.g. collective dismissals, severance pay etc. The final section provides and overall assessment of the Spanish system for managing labour redundancies, and briefly discusses the national debate on the prospects for reform, in light of the principles and policies of convergence set forth by the European Union.     

Asymptotic hypothesis test to compare likelihood ratios of multiple diagnostic tests in unpaired designs

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity. Other measures of the performance of a diagnostic test are the positive and negative likelihood ratios, which quantify the increase in knowledge about the presence of the disease through the application of a diagnostic test, and which depend on the sensitivity and specificity of the diagnostic test. In this article, we construct an asymptotic hypothesis test to simultaneously compare the positive and negative likelihood ratios of two or more diagnostic tests in unpaired designs. The hypothesis test is based on the logarithmic transformation of the likelihood ratios and on the chi-square distribution. Simulation experiments have been carried out to study the type I error and the power of the constructed hypothesis test when comparing two and three binary diagnostic tests. The method has been extended to the case of multiple multi-level diagnostic tests.     

Expedient and Monotone Learning Rules

This paper considers learning rules for environments in which little prior and feedback information is available to the decision maker. Two properties of such learning rules are studied: absolute expediency and monotonicity. Both require that some aspect of the decision maker's performance improves from the current period to the next. The paper provides some necessary, and some sufficient conditions for these properties. It turns out that there is a large variety of learning rules that have the properties. However, all learning rules that have these properties are related to the replicator dynamics of evolutionary game theory. For the case in which there are only two actions, it is shown that one of the absolutely expedient learning rules dominates all others.     

Topiramate Combined with Cognitive Restructuring for the Treatment of Gambling Disorder: A Two-Center,Randomized, Double-Blind Clinical Trial

Gambling disorder (GD) is a prevalent condition for which no pharmacological treatment has yet been approved, although there is evidence that topiramate can reduce impulsivity in GD and craving in various addictive behaviors. The goal of this study was to investigate the effectiveness of topiramate combined with cognitive restructuring for GD in a two-center, randomized, double-blind clinical trial. Participants were individuals seeking outpatient treatment for GD (n = 30), treated with either topiramate or placebo combined with a brief cognitive intervention, over a 12-week period, the dose of topiramate being tapered up during the first 8 weeks. The main outcome measures were gambling craving, behavior, and cognitive distortions; impulsivity; depression and social adjustment. Topiramate proved superior to placebo in reducing gambling craving (P = 0.017); time and money spent gambling (P = 0.007 and P = 0.047, respectively); cognitive distortions related to gambling (P = 0.003); and social adjustment (P = 0.040). We found no significant effects on impulsivity or depression. These findings are in contrast with data from a previous clinical trial with topiramate for GD. In the current study, we found that topiramate affects features specifically related to gambling addiction and had no significant effect on associated phenomena such as impulsiveness and depression. We believe that this response could be due to synergistic interaction between topiramate and the cognitive intervention.