891 resultados para Minimization


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For minimizing cannibalism of African catfish (Clarias gariepinus) larvae two trials for a period of 14 and 15 days respectively in four aquaria of size 120x49x32 cm³ were conducted. Seven days old African catfish larvae with an initial total length and weight of 7.84 (±0.40) mm and 4.40 (±1.18) mg respectively in the first trial and similarly 7.52(±0.61) mm and 3.98 (±0.56) mg in the second trial at the rate of same stocking densities of 2500 larvae in each aquarium were stocked in both trials. Cannibalistic larvae were separated by using grader frame from each treatment at 7 days and 5 days interval during first and second trial respectively. Two mesh sizes i.e., 5 mm and 7 mm were used in the grader frame in both trials. Survival rate was significantly higher in T1 than that of T2 in each trial. Grading of larvae with 5 days interval resulted higher survival rate than that of 7 days interval.

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A new combined Non Fertile and Uranium (CONFU) fuel assembly is proposed to limit the actinides that need long-term high-level waste storage from the pressurized water reactor (PWR) fuel cycle. In the CONFU assembly concept, ∼20% of the UO2 fuel pins are replaced with fertile free fuel hosting the transuranic elements (TRUs) generated in the previous cycle. This leads to a fuel cycle sustainable with respect to net TRU generation, and the amount and radiotoxicity of the nuclear waste can be significantly reduced in comparison with the conventional once-through UO2 fuel cycle. It is shown that under the constraints of acceptable power peaking limits, the CONFU assembly exhibits negative reactivity feedback coefficients comparable in values to those of the reference UO2 fuel. Feasibility of the PWR core operation and control with complete TRU recycle has been shown based on full-core three-dimensional neutronic simulation. However, gradual buildup of small amounts of Cm and Cf challenges fuel reprocessing and fabrication due to the high spontaneous fission rates of these nuclides and heat generation by some Pu, Am, and Cm isotopes. Feasibility of the processing steps becomes more attainable if the time between discharge and reprocessing is 20 yr or longer.

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How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.

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The problem of minimizing a multivariate function is recurrent in many disciplines as Physics, Mathematics, Engeneering and, of course, Computer Science. In this paper we describe a simple nondeterministic algorithm which is based on the idea of adaptive noise, and that proved to be particularly effective in the minimization of a class of multivariate, continuous valued, smooth functions, associated with some recent extension of regularization theory by Poggio and Girosi (1990). Results obtained by using this method and a more traditional gradient descent technique are also compared.

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This paper compares the Random Regret Minimization and the Random Utility Maximization models for determining recreational choice. The Random Regret approach is based on the idea that, when choosing, individuals aim to minimize their regret – regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. The Random Regret paradigm, recently developed in transport economics, presents a tractable, regret-based alternative to the dominant choice paradigm based on Random Utility. Using data from a travel cost study exploring factors that influence kayakers’ site-choice decisions in the Republic of Ireland, we estimate both the traditional Random Utility multinomial logit model (RU-MNL) and the Random Regret multinomial logit model (RR-MNL) to gain more insights into site choice decisions. We further explore whether choices are driven by a utility maximization or a regret minimization paradigm by running a binary logit model to examine the likelihood of the two decision choice paradigms using site visits and respondents characteristics as explanatory variables. In addition to being one of the first studies to apply the RR-MNL to an environmental good, this paper also represents the first application of the RR-MNL to compute the Logsum to test and strengthen conclusions on welfare impacts of potential alternative policy scenarios.

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This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.

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A new model to explain animal spacing, based on a trade-off between foraging efficiency and predation risk, is derived from biological principles. The model is able to explain not only the general tendency for animal groups to form, but some of the attributes of real groups. These include the independence of mean animal spacing from group population, the observed variation of animal spacing with resource availability and also with the probability of predation, and the decline in group stability with group size. The appearance of "neutral zones" within which animals are not motivated to adjust their relative positions is also explained. The model assumes that animals try to minimize a cost potential combining the loss of intake rate due to foraging interference and the risk from exposure to predators. The cost potential describes a hypothetical field giving rise to apparent attractive and repulsive forces between animals. Biologically based functions are given for the decline in interference cost and increase in the cost of predation risk with increasing animal separation. Predation risk is calculated from the probabilities of predator attack and predator detection as they vary with distance. Using example functions for these probabilities and foraging interference, we calculate the minimum cost potential for regular lattice arrangements of animals before generalizing to finite-sized groups and random arrangements of animals, showing optimal geometries in each case and describing how potentials vary with animal spacing. (C) 1999 Academic Press.</p>