796 resultados para Recruitment message


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Synaptic recruitment of AMPA receptors (AMPARs) represents a key postsynaptic mechanism driving functional development and maturation of glutamatergic synapses. At immature hippocampal synapses, PKA-driven synaptic insertion of GluA4 is the predominant mechanism for synaptic reinforcement. However, the physiological significance and molecular determinants of this developmentally restricted form of plasticity are not known. Here we show that PKA activation leads to insertion of GluA4 to synaptic sites with initially weak or silent AMPAR-mediated transmission. This effect depends on a novel mechanism involving the extreme C-terminal end of GluA4, which interacts with the membrane proximal region of the C-terminal domain to control GluA4 trafficking. In the absence of GluA4, strengthening of AMPAR-mediated transmission during postnatal development was significantly delayed. These data suggest that the GluA4-mediated activation of silent synapses is a critical mechanism facilitating the functional maturation of glutamatergic circuitry during the critical period of experience-dependent fine-tuning.

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

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As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

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Despite the confimied health benefits of exercise during the postpartum period, many new mothers are not sufficiently active. The present research aimed to examine the effectiveness of 2 types of messages on intention to exercise after giving birth on 2 groups of pregnant women (low and high self-monitors) using the Theory of Planned Behavior as a theoretical basis. Participants were 2 1 8 pregnant women 1 8 years of age and older (Mean age = 27.9 years, SD = 5.47), and in their second or third trimester. Women completed a demographics questionnaire, a self-monitoring (SM) scale and the Godin Leisure Time Exercise Questionnaire for current and pre-pregnancy exercise levels. They then read one of two brochures, describing either the health or appearance benefits of exercise for postpartum women. Women's attitudes, social norms, perceived behavioral control, and intentions to exercise postpartum were then assessed to determine whether one type of message (health or appearance) was more effective for each group. A MANOVA found no significant effect (p>0.05) for message type, SM, or their interaction. Possible reasons include the fact that the two messages may have been too similar, reading any message about exercise may result in intentions to exercise, or lack of attention given to the brochure. Given the lack of research in this area, more studies are necessary to confirm the present results. Two additional exploratory analyses were conducted. Pearson correlations found higher levels of pre-pregnancy exercise and current exercise to be associated with more positive attitudes, more positive subjective norms, higher perceived behavioral control, and higher intention to exercise postpartum. A hierarchical regression was conducted to determine the predictive utility of attitudes, subjective norms, and perceived behavioral control on intention for each self-monitoring group. Results of the analysis demonstrated the three independent variables significantly predicted intention (p < .001) in both groups, accounting for 58-62% of the variance in intention. For low self-monitors, attitude was the strongest predictor of intention, followed by perceived behavioral control and subjective norm. For high self-monitors, perceived behavioral control was the strongest predictors, followed by attitudes and subjective norm. The present study has practical and real world implications by contributing to our understanding of what types of messages, in a brochure format, are most effective in changing pregnant women's attitudes, subjective norm, perceived behavioral control and intention to exercise postpartum and provides ftirther support for the use of the Theory of Planned Behavior with this population.