6 resultados para Occupancy

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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We report time evolution studies of low coverage CO adsorption (surface hydrogen site blocking < 40%) and oxidative stripping on stepped Pt(776) and Pt(554) surfaces. It was observed that there is no preferential site occupancy for CO adsorption on step or terrace. It is proposed that CO adsorption onto these surfaces is a random process, and after CO adsorption there is no appreciable shift from CO-(111) to CO-(110) sites. This implies that after adsorption, CO molecules either have a very long residence time, or that the diffusion coefficient is much lower than previously thought. After CO electrooxidation the sites released included both terrace (111) and step (110) orientations. For surface hydrogen site blocking > 40%, the lateral interactions might play a role in the preferential CO site occupancy. (C) 2011 Elsevier B.V. All rights reserved.

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Extinction risk has not been evaluated for 96% of all described plant species. Given that the Global Strategy for Plant Conservation proposes preliminary conservation assessments of all described plant species by 2010, herbarium specimens (i.e., primary occurrence data) are increasingly being used to infer threat components from estimates of geographic range size. Nevertheless, estimates of range size based on herbarium data may be inaccurate due to collection bias associated with interspecific variation in detectability. We used data on 377 species of Bignonieae to test the hypothesis that there is a positive relationship between detectability and estimates of geographic range size derived from herbarium specimens. This relationship is expected if the proportion of the true geographic range size of a species that is documented by herbarium specimens is given by the product of the true geographic range size and the detectability of the species, assuming no relationship between true geographic range size and detectability. We developed 4 measures of detectability that can be estimated from herbarium data and examined the relationship between detectability and 2 types of estimates of geographic range size: area of occupancy and extent of occurrence. Our results from regressing estimates of extent of occurrence and area of occupancy on detectability across genera provided no support for this hypothesis. The same was true for regressions of estimated extent of occurrence on detectability across species within genera. Nevertheless, regressions of estimated area of occupancy on detectability across species within genera provided partial support for our hypothesis. We considered 3 possible explanations for this mixed outcome: violation of the assumption of no relationship between true geographic range size and detectability; the relationships between estimated geographic range size and detectability may be an artifact of a negative relationship between estimated area of occupancy and the sampling variance of detectability; detectability may have had 2 opposite effects on estimated species range sizes: one determines the proportion of the true range of a species documented by herbarium specimens and the other determines the distribution of true range size for the species actually observed with herbarium data. Our findings should help improve understanding of the potential biases incurred with the use of herbarium data.

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Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.

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Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.

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Bendadaite, ideally Fe(2+)Fe(2)(3+)(AsO(4))(2)(OH)(2 center dot).4H(2)O, is a new member of the arthurite group It was found as a weathering product of arsenopyrite on a single hand specimen from the phosphate pegmatite Bendada. central Portugal (type locality) Co-type locality is the granite pegmatite of La via do Almerindo (Almerindo mine), Linopolis, Divmo das Laranjeiras county, Minas Gerais, Brazil Further localities are the Vein Negra mine, Copiapo province, Chile, mid-East, Bou Azzer district, Morocco, and Para Inferida yard, Fenugu Sibirt mine, Gonnosfanadiga, Medio Campidano Province, Sardinia. Italy Type bendadaite occurs as blackish green to dark brownish tufts (<0 1 mm long) and flattened radiating aggregates. in intimate association with an intermediate member of the scorodite-mansfieldite series It is monoclinic. space group P2(l/c). with a = 10 239(3) angstrom. b = 9 713(2) angstrom, c = 5 552(2) angstrom. beta = 94 11(2)degrees. = 550 7(2) angstrom(3). Z = 2 Electron-microprobe analysis yielded (wt %). CaO 0 04, MnO 0 03. CuO 006, ZnO 004. Fe(2)O(3) (total) 43 92, Al(2)O(3) 115. SnO(2) 0 10, As(2)O(5) 43 27. P(2)O(5) 1 86, SO(3) 0.03 The empirical formula is (Fe(0 52)(2+)Fe(0 32)(3+)rectangle(0 16))(Sigma 1 00)(Fe(1 89)(3+)Al(0 11))(Sigma 2 00)(As(1 87)P(0 13))(Sigma 2 00)O(8)(OH)(2 00) 4H(2)O based. CM 2(As,P) and assuming ideal 80, 2(OH), 4H2O and complete occupancy of the ferric on site by Fe(3+) and Al Optically, bendadaite is biaxial, positive, 2V(est) = 85+/-4 degrees, 2V(eale) = 88 degrees, with alpha 1 734(3). 13 1 759(3), 7 1 787(4) Pleochrosim is medium strong X pale reddish brown. Y yellowish brown, Z dark yellowish brown. absorption Z > V > X, optical dispersion weak, r > v. Optical axis plane Is parallel to (010), with X approximately parallel to a and Z nearly parallel to c Bendadaite has vitreous to sub-adamantine luster, is translucent and non-fluorescent It is brittle, shows irregular fracture and a good cleavage parallel to 1010} 3 15 0 10 g/cm(3), 3 193 g/cm3 (for the empirical formula) The five strongest powder diffraction lines [d in angstrom (I)(hkl] are 10 22 (10)(100), 7 036 (8)(110), 4 250 (5)(11 I), 2 865 (4)(311), 4 833 (3)(020,011) The d spacings are very similar to those of its Zn analogue, ojelaite The crystal structure of bendadaite was solved and refined using a crystal from the co-type locality with the composition (Fe(0 95)(2+)rectangle(0 05))(Sigma 1 00)(Fe(1 80)(3+)Al(0 20))Sigma(2 00)(As(1 48)P(0 52))(Sigma 2 00)O(8)) (OH)(2) 4H(2)O (R = 16%) and confirms an arthurite-type atomic arrangement

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The analysis of the IR carbonyl band of the N-methoxy-N-methyl-2-[(4`-substituted)phenylthio]propanamides Y-PhSCH(Me)C(O)N(OMe)Me (Y=OMe 1, Me 2, H 3, Cl 4, NO(2) 5), supported by B3LYP/cc-pVDZ calculations of 3, indicated the existence of two gauche conformers (g(1) and g(2)), the g(1) conformer being the more stable and the less polar one (in gas phase and in solution). Both conformers are present in solution of the polar solvents (CH(2)Cl(2) and CH(3)CN) for 1-5 and in solution of the less polar solvent (CHCl(3)) for 1-4, while only the g(1) conformer is present in solution of non polar solvents (n-C(6)H(14) and CCl(4)) and in solution of CHCl(3) for 5. NBO analysis shows that both the sigma(C-S) -> pi*(C=O) (hyperconjugative) and the pi(C=O) -> sigma*(C-S) orbital interactions contribute almost to the same extent for the stabilization of g(1) and g(2) conformers. The pi*(C=O) -> sigma*(C-S), n(S) -> pi*(C=O) and the n(S) -> pi*(C=O) orbital interactions stabilize more the g(1) conformer than the g(2) one. Moreover, the suitable geometry of the g(1) conformer leads to its stabilization through the LP(O2) -> sigma*(C8-H11) orbital interaction (hydrogen bond) along with the strong O([CO])(delta-) center dot center dot center dot H([O-Ph])(delta+) electrostatic interaction. On the other hand, the appropriate geometry of the g(2) conformer leads to its stabilization by the LP(O22) -> sigma*(C9-H13) orbital interaction (hydrogen bond) along with the weak O([OMe])(delta-) center dot center dot center dot H([o`-Ph])(delta+) electrostatic static interaction. As for the 4`-nitro derivative 5 the ortho-phenyl hydrogen atom becomes more acidic, leading to a stronger O([CO])(delta-) center dot center dot center dot H([o-Ph])(delta+) interaction and, thus, into a larger stabilization of the g(1) conformer in the whole series. This trend is responsible for the unique IR carbonyl band in CHCl(3) solution of 5. The larger occupancy of the pi*(C=O) orbital of the g(1) conformer relative to that of the g(2) conformer, along with the O([CO])(delta-) center dot center dot center dot H([o-Ph])(delta+) electrostatic interaction (hydrogen bond) justifies the lower carbonyl frequency of the g(1) conformer with respect to the g(2) one, in gas phase and in solution. (C) 2008 Elsevier B.V. All rights reserved.