Socio‐Emotional Context and Adolescents' Decision Making: The Experience of Regret and Relief After Social Comparison

Many studies indicate that adolescents are hypersensitive to rewards in salient socio‐emotional contexts. However, little is known about adolescents' sensitivity to complex negative emotions. To study the development of the ability to experience regret and relief, children, adolescents, and young adults performed a gambling task in a socio‐emotional context of competition, in which they were informed that their outcome would be compared with that of a competitor. The context of competition impacted the feelings of regret and relief in adolescents. When adolescents experienced an initial negative outcome, their feeling of relief was reinforced. However, they did not seem to experience regret in the social context of competition. These results provide a possible explanation for adolescents' enhanced risk seeking.     

Self-Exclusion Program: A Longitudinal Evaluation Study

Few self-exclusion programs have been evaluated and their long-term impact remains unknown. This study has two main goals: (1) to assess changes in gambling behaviour and gambling problems for self-excluded patrons, and (2) to follow self-excluded gamblers for a two-year period (during and after the self-exclusion period). Individuals who excluded themselves (N = 161 at the initial stage) participated in telephone interviews after signing the self-exclusion agreement and were followed at 6, 12, 18 and 24-months. Results show that according to the DSM-IV, 73.1% of the participants were pathological gamblers. The self-exclusion program has many positive effects. During the follow-ups, the urge to gamble was significantly reduced while the perception of control increased significantly for all participants. The intensity of negative consequences for gambling was significantly reduced for daily activities, social life, work, and mood. The DSM score was significantly reduced over time. This reduction also took place between the baseline and the 6-month follow-up. The clinical implications of the results are discussed in relation to the effectiveness of the program. Suggestions are provided in order to increase compliance of self-excluded patrons.     

Perceptron versus automaton in the finitely repeated prisoner’s dilemma

We study the finitely repeated prisoner’s dilemma in which the players are restricted to choosing strategies which are implementable by a machine with a bound on its complexity. One player has to use a finite automaton while the other player has to use a finite perceptron. Some examples illustrate that the sets of strategies which are induced by these two types of machines are different and not ordered by set inclusion. Repeated game payoffs are evaluated according to the limit of means. The main result establishes that a cooperation at almost all stages of the game is an equilibrium outcome if the complexity of the machines the players may use is limited enough and if the length T of the repeated game is sufficiently large. This result persists when more than T states are allowed in the player’s automaton. We further consider a variant of the model in which the two players are restricted to choosing strategies which are implementable by perceptrons and prove that the players can cooperate at most of the stages provided that the complexity of their perceptrons is sufficiently reduced.     

Statistical inference for oscillation processes

ABSTRACT

A new model for time series with a specific oscillation pattern is proposed. The model consists of a hidden phase process controlling the speed of polling and a nonparametric curve characterizing the pattern, leading together to a generalized state space model. Identifiability of the model is proved and a method for statistical inference based on a particle smoother and a nonparametric EM algorithm is developed. In particular, the oscillation pattern and the unobserved phase process are estimated. The proposed algorithms are computationally efficient and their performance is assessed through simulations and an application to human electrocardiogram recordings.     

Safe sets in graphs: Graph classes and structural parameters

A safe set of a graph \(G=(V,E)\) is a non-empty subset S of V such that for every component A of G[S] and every component B of \(G[V {\setminus } S]\), we have \(|A| \ge |B|\) whenever there exists an edge of G between A and B. In this paper, we show that a minimum safe set can be found in polynomial time for trees. We then further extend the result and present polynomial-time algorithms for graphs of bounded treewidth, and also for interval graphs. We also study the parameterized complexity. We show that the problem is fixed-parameter tractable when parameterized by the solution size. Furthermore, we show that this parameter lies between the tree-depth and the vertex cover number. We then conclude the paper by showing hardness for split graphs and planar graphs.     

Wavelet shrinkage for unequally spaced data

Wavelet shrinkage (WaveShrink) is a relatively new technique for nonparametric function estimation that has been shown to have asymptotic near-optimality properties over a wide class of functions. As originally formulated by Donoho and Johnstone, WaveShrink assumes equally spaced data. Because so many statistical applications (e.g., scatterplot smoothing) naturally involve unequally spaced data, we investigate in this paper how WaveShrink can be adapted to handle such data. Focusing on the Haar wavelet, we propose four approaches that extend the Haar wavelet transform to the unequally spaced case. Each approach is formulated in terms of continuous wavelet basis functions applied to a piecewise constant interpolation of the observed data, and each approach leads to wavelet coefficients that can be computed via a matrix transform of the original data. For each approach, we propose a practical way of adapting WaveShrink. We compare the four approaches in a Monte Carlo study and find them to be quite comparable in performance. The computationally simplest approach (isometric wavelets) has an appealing justification in terms of a weighted mean square error criterion and readily generalizes to wavelets of higher order than the Haar.     

A note on monotonicity in iterated choice functions

This short paper proves the following conjecture of D. Bouyssou: a preference aggregation function built by iteration of a strictly monotonic and symmetric social choice correspondence cannot be strictly monotonic. Received: 1 October 1998/Accepted: 23 December 1999     

Paired-domination in generalized claw-free graphs

In this paper, we continue the study of paired-domination in graphs introduced by Haynes and Slater (Networks 32 (1998) 199–206). A set S of vertices in a graph G is a paired-dominating set of G if every vertex of G is adjacent to some vertex in S and if the subgraph induced by S contains a perfect matching. The paired-domination number of G, denoted by , is the minimum cardinality of a paired-dominating set of G. If G does not contain a graph F as an induced subgraph, then G is said to be F-free. Haynes and Slater (Networks 32 (1998) 199–206) showed that if G is a connected graph of order , then and this bound is sharp for graphs of arbitrarily large order. Every graph is -free for some integer a ≥ 0. We show that for every integer a ≥ 0, if G is a connected -free graph of order n ≥ 2, then with infinitely many extremal graphs.