11 research outputs found

    Polynomial-Chaos-based Kriging

    Full text link
    Computer simulation has become the standard tool in many engineering fields for designing and optimizing systems, as well as for assessing their reliability. To cope with demanding analysis such as optimization and reliability, surrogate models (a.k.a meta-models) have been increasingly investigated in the last decade. Polynomial Chaos Expansions (PCE) and Kriging are two popular non-intrusive meta-modelling techniques. PCE surrogates the computational model with a series of orthonormal polynomials in the input variables where polynomials are chosen in coherency with the probability distributions of those input variables. On the other hand, Kriging assumes that the computer model behaves as a realization of a Gaussian random process whose parameters are estimated from the available computer runs, i.e. input vectors and response values. These two techniques have been developed more or less in parallel so far with little interaction between the researchers in the two fields. In this paper, PC-Kriging is derived as a new non-intrusive meta-modeling approach combining PCE and Kriging. A sparse set of orthonormal polynomials (PCE) approximates the global behavior of the computational model whereas Kriging manages the local variability of the model output. An adaptive algorithm similar to the least angle regression algorithm determines the optimal sparse set of polynomials. PC-Kriging is validated on various benchmark analytical functions which are easy to sample for reference results. From the numerical investigations it is concluded that PC-Kriging performs better than or at least as good as the two distinct meta-modeling techniques. A larger gain in accuracy is obtained when the experimental design has a limited size, which is an asset when dealing with demanding computational models

    Striatal responsiveness to reward under threat-of-shock and working memory load: A preliminary study.

    Get PDF
    Reward and stress are important determinants of motivated behaviors. Striatal regions play a crucial role in both motivation and hedonic processes. So far, little is known on how cognitive effort interacts with stress to modulate reward processes. This study examines how cognitive effort (load) interacts with an unpredictable acute stressor (threat-of-shock) to modulate motivational and hedonic processes in healthy adults. A reward task, involving stress with unpredictable mild electric shocks, was conducted in 23 healthy adults aged 20-37 (mean age: 24.7 ± 0.9; 14 females) during functional magnetic resonance imaging (fMRI). Manipulation included the use of (a) monetary reward for reinforcement, (b) threat-of-shock as the stressor, and (c) a spatial working memory task with two levels of difficulty (low and high load) for cognitive load. Reward-related activation was investigated in a priori three regions of interest, the nucleus accumbens (NAcc), caudate nucleus, and putamen. During anticipation, threat-of-shock or cognitive load did not affect striatal responsiveness to reward. Anticipated reward increased activation in the ventral and dorsal striatum. During feedback delivery, both threat-of-shock and cognitive effort modulated striatal activation. Higher working memory load blunted NAcc responsiveness to reward delivery, while stress strengthened caudate nucleus reactivity regardless reinforcement or load. These findings provide initial evidence that both stress and cognitive load modulate striatal responsiveness during feedback delivery but not during anticipation in healthy adults. Of clinical importance, sustained stress exposure might go along with dysregulated arousal, increasing therefore the risk for the development of maladaptive incentive-triggered motivation. This study brings new insight that might help to build a framework to understand common stress-related disorders, given that these psychiatric disorders involve disturbances of the reward system, cognitive deficits, and abnormal stress reactivity

    Trajectories of perceived superiority across the transition to marriage

    No full text
    Perceived superiority, the tendency to regard one\u2019s own relationship as better than other people\u2019s relationships, is a key relationship maintenance mechanism. Little is known about whether and how it changes during the transition to marriage, a pivotal moment in most couples\u2019 life cycle. In a longitudinal study following 97 couples for three waves across the transition, men presented stable perceived superiority, whereas women presented a curvilinear change in superiority perceptions, with a substantial increase in perceived superiority between T1 and T2 and a significantly reduced change between T2 and T3. In addition, trajectories differed according to partners\u2019 commitment level. More committed and less committed partners both showed a curvilinear change in perceived superiority, though following different patterns. Results point to the functional value of perceived superiority, which emerges as a strategy aimed at sustaining partners through the challenges deriving from the transition to marriage
    corecore