This paper presents a new method for discovering the parameters of a fuzzy system; namely, the combination of input variables of the rules, the parameters of the membership functions of the variables, and a set of relevant rules; from numerical data using the newly proposed bacterial evolutionary algorithm (BEA). In early work, the authors proposed the pseudobacterial genetic algorithm (PBGA) that incorporates a modified mutation operator called bacterial mutation, based on a biological phenomenon of microbial evolution. The BEA has the same features of the PBGA, but introduces a new operation, called gene transfer operation, equally inspired by a microbial evolution phenomenon. While the bacterial mutation performs local optimization within the limits of a single chromosome, the gene transfer operation allows the chromosomes to directly transfer information to the other counterparts in the population. The gene transfer is inspired by the phenomenon of transfer of strands of genes in a population of bacteria. By means of this mechanism, one bacterium can rapidly spread its genetic information to other cells. Numerical experiments were performed to show the effectiveness of the BEA. The obtained results show the benefits that can be obtained with this method.

This study examined patterns of neural response to feedback received during simulated interpersonal interactions in adolescents with anxiety disorders and healthy peers. To this aim, behavioral and neural responses during the Prisoner's Dilemma (PD) game, an economic exchange task, were compared between adolescents with anxiety disorders (N=12) and healthy controls (n=17). Participants were deceived to believe that their co-player (a pre-programmed computer algorithm) was another study participant. Anxious participants and controls differed significantly in patterns of neural activation in the medial prefrontal cortex (mPFC), ACC, precuneus, insula, and temporoparietal junction (TPJ) when receiving feedback about co-player defection or cooperation. Groups also differed significantly in post-feedback behavior; specifically anxious adolescents were more likely than controls to cooperate following trials when the coplayer betrayed them. Our findings provide preliminary evidence that, in social situations, anxious adolescents may not only behave differently than healthy peers, but they may also engage neural resources in different ways. These findings constitute a first step toward elucidating mechanisms underlying social impairment in youth with internalizing disorders. Keywords fMRI; anxiety; depression; cooperation; betrayal; interpersonal interaction; Prisoner's Dilemma; medial prefrontal cortex; precuneus; temporoparietal junction Individuals with social fears show atypical cognitive and emotional responses to social signals, particularly when they interpret those signals as cues of negative or ambiguous interpersonal feedback. For example, they exhibit both a bias to over-attend to interpersonal threat cues such as angry faces and a hypersensitivity to criticism or rejection (Harb, Heimberg, Fresco, Schneier, & Liebowitz, 2002;Mogg, Bradley, Millar, & White, 1995;Mogg, Philippot, & Bradley, 2004). Such cognitive/emotional manifestations of anxiety, which increase risk for maladaptive behaviors including withdrawal, passivity, and avoidance (London, Downey, Bonica, & Paltin, 2007;Schneider, 2009), may relate to aberrant patterns of neural function (Cannistraro & Rauch, 2003 (Goldin, Manber, Hakimi, Canli, & Gross, 2009;Killgore & Yurgelun-Todd, 2005;McClure, Monk, et al., 2007;Monk, et al., 2008;Shin, et al., 2005;Stein, Goldin, Sareen, Zorrilla, & Brown, 2002;Stein, Simmons, Feinstein, & Paulus, 2007). Findings from at least two recent studies of anxiety-disordered adults and adolescents also document perturbations in these regions when negative social cues appear in more complex, self-relevant contexts (e.g., faces or words explicitly conveying critical or rejecting feedback to the participant) (Blair, et al., 2008;Guyer, et al., 2008).Notably, although the two studies that compared neural responses to self-relevant negative social cues between anxious individuals and controls focused primarily on the amygdala and prefrontal cortical regions (Blair, et al., 2008;Guyer, et al., 2008), both yielded evid...

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Background Past studies have associated gratitude interventions with a host of positive outcomes. However, there is a dearth of research regarding the impact such interventions have on the academic motivation of university students, thought to be a primary determinant of academic achievement and overall satisfaction with school activities. Here, we examined the effects of a 2-week online gratitude journal intervention on the academic motivation of university students. Methods Eighty-four students were randomly assigned to either an active manipulation group (gratitude group) or a neutral control group. In the first 6 days of each week, participants in the gratitude group were asked to log in to the online system once a day and list up to five things they had felt grateful for. They were also requested to evaluate various aspects of their daily lives. Participants in the control group were only requested to perform the daily self-evaluations. Academic motivation was assessed using the Academic Motivation Scale (AMS), which conceptualizes motivation in academic settings as being composed by three different components, i.e., intrinsic motivation, extrinsic motivation and amotivation, the latter being associated with the perceived lack of contingency between actions and outcomes. Responses were collected 5 times: before group assignment (baseline), 1 week after the start of the intervention, immediately after the intervention, and at two follow-ups, 1 and 3 months after the intervention. Results Analysis using a self-determination index derived from the AMS components showed that participants who regularly engaged with the gratitude journal task displayed significant enhancements in academic motivation. Additional analysis revealed that the enhancements were driven by decreases in the levels of amotivation. Furthermore, follow-up data showed that there were no signs that such enhancements had receded 3 months after the end of the intervention. Improvements in academic motivation were not observed among participants in the control group. Conclusions The current results provide evidence that gratitude interventions can positively impact the academic motivation of university students. More broadly, they show that the effects extend well beyond the realm of typically assessed measures of individual well-being, and can effectively regulate a fundamental component of goal-directed behavior such as motivation.