2 resultados para Visió artificial
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The effects of estradiol benzoate (EB) and estradiol cypionate (EC) on induction of ovulation after a synchronized LH surge and on fertility of Bos indicus females submitted to timed AI (TAI) were evaluated. In Experiment 1, ovariectomized Nelore heifers were used to evaluate the effect of EB (n = 5) and EC (n = 5) on the circulating LH profile. The LH surge timing (19.6 and 50.5 h; P = 0.001), magnitude (20.5 and 9.4 ng/mL; P = 0.005), duration (8.6 and 16.5 h; P = 0.001), and area under the LH curve (158.6 and 339.4 ng/mL; P = 0.01) differed between the EB and EC treatments, respectively. In Experiment 2 (follicular responses; n = 60) and 3 (pregnancy per AI; P/AI; n = 953) suckled Bos indicus beef cows submitted to an estradiol/progesterone-based synchronization protocol were assigned to receive one of two treatments to induce synchronized ovulation: 1 mg of EB im 24 h after progesterone (P4) device removal or 1 mg of EC im at P4 device removal. There was no difference (P > 0.05) between EB and EC treatments on follicular responses (maximum diameter of the ovulatory follicle, 13.1 vs. 13.9 mm; interval from progesterone device removal to ovulation, 70.2 vs. 68.5 h; and ovulation rate, 77.8 vs. 82.8%, respectively). In addition, P/AI was similar (P < 0.22) between the cows treated with EB (57.5%; 277/482) and EC (61.8%; 291/471). In conclusion, despite pharmacologic differences, both esters of estradiol administered either at P4 device removal (EC) or 24 h later (EB) were effective in inducing an LH surge which resulted in synchronized ovulations and similar P/AI in suckled Bos indicus beef cows submitted to TAI. (C) 2012 Elsevier Inc. All rights reserved.
Resumo:
Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.