4 resultados para preference representation

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Experimental analyses of hermit crabs and their preferences for shells are essential to understand the intrinsic relationship of the crabs` dependence on shells, and may be useful to explain their shell use pattern in nature. The aim of this study was to evaluate the effect of crab species and site on the pattern of shell use, selection, and preference in the south-western Atlantic hermit crabs Pagurus brevidactylus and Pagurus criniticornis, comparing sympatric and allopatric populations. Differently from the traditional approach to evaluate shell preference by simply determining the shell selection pattern (i.e., the number of shells of each type selected), preference was defined (according to [Liszka, D., Underwood, AJ., 1990. An experimental design to determine preferences for gastropod shells by a hermit-crab. J. Exp. Mar. Biol. Ecol., 137(1), 47-62]) by the comparison of the number of crabs changing for a particular shell type when three options were given (Cerithium atratum, Morula nodulosa, and Tegula viridula) with the number of crabs changing for this same type when only this type was offered. The effect of crab species was tested at Cabelo Gordo Beach, where P. brevidacrylus was found occupying shells of C. atratum, M. nodulosa, and T viridula in similar frequencies, whereas P. criniticornis occupied predominantly shells of C atratum. In laboratory experiments the selection patterns of the two hermit-crab species for these three gastropods were different, with P criniticornis selecting mainly shells of C atratum, and R brevidactylus selecting more shells of M. nodulosa. The shell preference was also dependent on crab species, with P. criniticornis showing a clear preference for shells of C atratum, whereas P. brevidactylus did not show a preference for any of the tested shells. The effect of site was tested for the two species comparing data from Cabelo Gordo to Preta (P brevidactylus) and Araca beaches (P. criniticornis). The pattern of shell use, selection, and preference was demonstrated to be dependent on site only for P. brevidactylus. The results also showed that the shell use pattern of P criniticornis can be explained by its preference at both sites, whereas for P. brevidactylus it occurred only at Cabelo Gordo, where the absence of preference was correlated with the similar use of the three gastropod species studied. Finally, the results showed that the shell selection pattern cannot be considered as a measure of shell preference, since it overestimates crab selectivity. (C) 2009 Elsevier B.V. All rights reserved.

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We examine Weddell Sea deep water mass distributions with respect to the results from three different model runs using the oceanic component of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM). One run is inter-annually forced by corrected NCAR/NCEP fluxes, while the other two are forced with the annual cycle obtained from the same climatology. One of the latter runs includes an interactive sea-ice model. Optimum Multiparameter analysis is applied to separate the deep water masses in the Greenwich Meridian section (into the Weddell Sea only) to measure the degree of realism obtained in the simulations. First, we describe the distribution of the simulated deep water masses using observed water type indices. Since the observed indices do not provide an acceptable representation of the Weddell Sea deep water masses as expected, they are specifically adjusted for each simulation. Differences among the water masses` representations in the three simulations are quantified through their root-mean-square differences. Results point out the need for better representation (and inclusion) of ice-related processes in order to improve the oceanic characteristics and variability of dense Southern Ocean water masses in the outputs of the NCAR-CCSM model, and probably in other ocean and climate models.

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ACID-BASE REACTIONS: CONCEPT, REPRESENTATION AND GENERALIZATION FROM THE ENERGY INVOLVED IN TRANSFORMATIONS. Undergraduate students on the first year of Chemistry Courses are unfamiliar with the representation of acid-base reactions using the ionic equation H+ + OH- -> H2O. A chemistry class was proposed about acid-base reactions using theory and experimental evaluation of neutralization heat to discuss the energy involved when water is formed from H+ and OH- ions. The experiment is suggested using different strong acids and strong base pairs. The presentation of the theme within a chemistry class for high school teachers increased the number of individuals that saw the acid-base reaction from this perspective.

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Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.