8 resultados para Relevance feature


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In real life strategic interactions, decision-makers are likely to entertain doubts about the degree of optimality of their play. To capture this feature of real choice-making, we present here a model based on the doubts felt by an agent about how well is playing a game. The doubts are coupled with (and mutually reinforced by) imperfect discrimination capacity, which we model here by means of similarity relations. We assume that each agent builds procedural preferences de ned on the space of expected payoffs-strategy frequencies attached to his current strategy. These preferences, together with an adaptive learning process lead to doubt-based selection dynamic systems. We introduce the concepts of Mixed Strategy Doubt Equilibria, Mixed Strategy Doubt-Full Equilibria and Mixed Strategy Doubtless Equilibria and show the theoretical and the empirical relevance of these concepts.

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Background: Maladaptive behavior has been reported as a phenotypical feature in Prader–Willi syndrome (PWS). It severely limits social adaptation and the quality of life of children and adults with the syndrome. Different factors have been linked with the intensity and form of these behavioral disturbances but there is no consensus about the cause. Consequently, there is still controversy regarding management strategies and there is a need for new data. Methods: The behavior of 100 adults with PWS attending a dedicated center was assessed using the Developmental Behavior Checklist for Adults (DBC-A) and the PWS-specific Hyperphagia Questionnaire. The DBC-A was completed separately by trained caregivers at the center and relatives or caregivers in a natural setting. Genotype, gender, age, degree of obesity and cognitive impairment were analyzed as variables with a hypothetical influence on behavioral features. Results: Patients showed a relatively high rate of behavioral disturbances other than hyperphagia. Disruptive and social relating were the highest scoring DBC-A subscales whereas anxiety/antisocial and self-absorbed were the lowest. When hospital caregiver and natural caregiver scores were compared, scores for the latter were higher for all subscales except for disruptive and anxiety/antisocial. These effects of institutional management were underlined. In the DBC-A, 22 items have descriptive indications of PWS behavior and were used for further comparisons and correlation analysis. In contrast to previous reports, rates of disturbed behavior were lower in patients with a deletion genotype. However, the behavioral profile was similar for both genotypes. No differences were found in any measurement when comparing type I and type II deletions. The other analyzed variables showed little relevance. Conclusions: Significant rates of behavioral disorders were highlighted and their typology described in a large cohort of adults with PWS. The deletion genotype was related to a lower severity of symptoms. Some major behavioral problems, such as hyperphagia, may be well controlled if living circumstances are adapted to the specific requirements of individuals with PWS.

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Rating enables the information asymmetry existing in the issuer-investor relationship to be reduced, particularly for issues with a high degree of complexity, as is the case of securitizations. However, there may be a serious conflict of interest between the issuer’s choice and remuneration of the agency and the credit rating awarded, resulting in lower quality and information power of the published rating. In this paper, we propose an explicative model of the number of ratings requested, by analyzing the relevance of the number of ratings to measure the reliability, where multirating is shown to be associated to the quality, size, liquidity and the degree of information asymmetry relating to the issue. Thus, we consider that the regulatory changes that foster the widespread publication of simultaneous ratings could help to alleviate the problem of rating model arbitrage and the crisis of confidence in credit ratings in general and in the securitization issues, in particular.

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Overexpression of the mammalian homolog of the unc-18 gene (munc18-1) has been described in the brain of subjects with schizophrenia. Munc18-1 protein is involved in membrane fusion processes, exocytosis and neurotransmitter release. A transgenic mouse strain that overexpresses the protein isoform munc18-1a in the brain was characterized. This animal displays several schizophrenia-related behaviors, supersensitivity to hallucinogenic drugs and deficits in prepulse inhibition that reverse after antipsychotic treatment. Relevant brain areas (that is, cortex and striatum) exhibit reduced expression of dopamine D-1 receptors and dopamine transporters together with enhanced amphetamine-induced in vivo dopamine release. Magnetic resonance imaging demonstrates decreased gray matter volume in the transgenic animal. In conclusion, the mouse overexpressing brain munc18-1a represents a new valid animal model that resembles functional and structural abnormalities in patients with schizophrenia.

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This paper investigates the effect of focal points and initial relative position in the outcome of a bargaining process. We conduct two on-line experiments. In the first experiment we attempt to replicate Güth, Huck and Müller's (2001) results about the relevance of equal splits. In our second experiment, we recover the choices of participants in forty mini-ultimatum games. This design allows us to test whether the equal split or any other distribution or set of distributions are salient. Our data provide no support for a focal-point explanation but we find support for an explanation based on relative position. Our results confirm that there is a norm against hyper-fair offers. Proposers are expected to behave selfishly when the unselfish distribution leads to a change in the initial relative position.

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Presentation for the 5th International Conference on Corpus Linguistics (CILC 2013), V Congreso Internacional de Lingüistica de Corpus.

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Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.