2 resultados para Models for effects separation

em Universidade do Minho


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This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

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BACKGROUND: General anesthetics (GA) are well known for the ability to induce a state of reversible loss of consciousness and unresponsiveness to painful stimuli. However, evidence from animal models and clinical studies show that GA exposure may induce behavioral changes beyond acute effects. Most research and concerns are focused on changes in cognition and memory. METHODS: We will look at effects of GA on behavior that is mediated by the dopaminergic system. RESULTS: Pharmacological resemblance of GA with drugs of abuse, and the complexity and importance of dopaminergic systems in both reward seeking and addictive illnesses make us believe that it deserves an overview about what is already known and what matters to us as healthcare workers and specifically as anesthesiologists. CONCLUSION: A review of available evidence strongly suggests that there may be a link between the effects of GA on the brain and substance abuse, partly explained by their influence on the dopaminergic system.