22 resultados para Gibbs Sampler
Resumo:
The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 +/- 0.00, 0.42 +/- 0.02, 0.49 +/- 0.01, 0.11 +/- 0.01 and 0.19 +/- 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.
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Abundance and composition of marine benthic communities have been relatively well studied in the SE Brazilian coast, but little is known on patterns controlling the distribution of their planktonic larval stages. A survey of larval abundance in the continental margin, using a Multi-Plankton Sampler, was conducted in a cross-shelf transect off Cabo Frio (23 degrees S and 42 degrees W) during a costal upwelling event. Hydrographic conditions were monitored through discrete CDT casts. Chlorophyll-a in the top 100 m of the water column was determined and changes in surface chlorophyll-a was estimated using SeaWiFS images. Based on the larval abundances and the meso-scale hydrodynamics scenario, our results suggest two different processes affecting larval distributions. High larval densities were found nearshore due to the upwelling event associated with high chlorophyll a and strong along shore current. On the continental slope, high larval abundance was associated with a clockwise rotating meander, which may have entrapped larvae from a region located further north (Cabo de Sao Tome, 22 degrees S and 41 degrees W). In mid-shelf areas, our data suggests that vertical migration may likely occur as a response to avoid offshore transport by upwelling plumes and/or cyclonic meanders. The hydrodynamic scenario observed in the study area has two distinct yet extremely important consequences: larval retention on food-rich upwelling areas and the broadening of the tropical domain to southernmost subtropical areas. (C) 2009 Elsevier B.V. All rights reserved.
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The genus Lamprosoma Kirby, 1818 includes 128 neotropical species and 54 of them are recorded from Brazil (Monros, 1960). The first species with a described larva was L. seraphinum Lacordaire. After that, larvae and pupae of three species were described: L. bicolor Kirby, 1818, L. chorisiae Monros, 1948 and L. azureum Germar, 1824. Fiebrig (1910) described the larva of L. seraphinum Lacordaire, collected on Teminalia hassleriana Chod. (Combretaceae) of Paraguay. Moreira (1913) described L. bicolor collected on Terminalia catappa L., in Rio de Janeiro. According to him, this tree was introduced from Molucas Islands, in Oceania. He also considered it probable that L. bicolor lived on one native species of Terminalia or on another species of Combretaceae and adaptated itself to live on Terminalia catappa. Monros (1949) described L. chorisiae collected on Chorisia speciosa and Ch. insignis [ Ceiba speciosa (A. St.-Hil., A. Juss. & Cambess.) Ravenna and Ceiba insignis (Kunth) P. E. Gibbs & J. Semir] (Bombacaceae) ("" palos borrachos"") in Tucuman. Caxambu and Almeida (1999) described L. azureum collected on Psidium cattleianum Sabine (Myrtaceae)(""araca""), in Parana state. Herein, the larva and pupa of L. amethystinum collected on Terminalia catappa amendoeira-da-praia"", "" chapeu-de-sol"") in Campinas, Sao Paulo state, are described and illustrated.
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We compare experimental and predicted differential scanning calorimetry (DSC) curves for palm oil (PO), peanut oil (PeO) and grapeseed oil (GO). The predicted curves are computed from the solid-liquid equilibrium modelling and direct minimization of the Gibbs free energy. For PO, the lower the scan rate, the better the agreement. The temperature transitions of PeO and GO were predicted with an average deviation of -0.72 degrees C and -1.29 degrees C respectively, in relation to experimental data from literature. However, the predicted curves showed other peaks not reported experimentally, as computed DSC curves correspond to equilibrium hypothesis which is reached experimentally for an infinitely small scan rate. The results revealed that predicted transitions temperatures using equilibrium hypotheses can be useful in pre-experimental evaluation of vegetable oils formulations seeking for desired melting profiles. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Strain ST211CH, identified as a strain of Enterococcus faecium, isolated from Lombo produced a bacteriocin that inhibited the growth of Enterococcus spp., Listeria spp., Klebsiella spp., Lactobacillus spp., Pseudomonas spp., Staphylococcus spp. and Streptococcus spp. The mode of action of the bacteriocin named as bacteriocin ST211Ch was bactericidal against Enterococcus faecalis ATCC19443. As determined by Tricine-SDS-PAGE, the approximate molecular mass of the bacteriocin was 8.0 kDa. Loss in antimicrobial activity was recorded after treatment with proteolytic enzymes. Maximum activity of bacteriocin ST211Ch was measured in broth cultures of E. faecium strain ST211Ch after 24 h; thereafter, the activity was reduced. Bacteriocin ST211Ch remained active after exposure to various temperatures and pHs, as well as to Triton X-100, Tween-80, Tween-20, sodium dodecyl sulfate, NaCl, urea and EDTA. Effect of media components on production of bacteriocin ST211Ch was also studied. On the basis of PCR reactions targeting different bacteriocin genes, i.e. enterocins, curvacins and sakacins, no evidences for the presence of these genes in the total DNA of E. faecium strain ST211Ch was obtained. The bacterium most probably produced a bacteriocin different from those mentioned above. Based on the antimicrobial spectrum, stability and mode of action of bacteriocin ST211CH, E. faecium strain ST211Ch might be considered as a potential candidate with beneficial properties for use in biopreservation to control food spoilage bacteria.
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In this study, particulate matter (PM) were characterized from a place impacted by heavy-duty vehicles (Bus Station) fuelled with diesel/biodiesel fuel blend (B3) in the city of Londrina, Brazil. Sixteen priority polycyclic aromatic hydrocarbons (PAH) concentrations were analyzed in the samples by their association with atmospheric PM, mass size distributions and major ions (fluorite, chloride, bromide, nitrate, phosphate, sulfate, nitrite, oxalate; fumarate, formate, succinate and acetate; lithium, sodium, potassium, magnesium, calcium and ammonium). Results indicate that major ions represented 21.2% particulate matter mass. Nitrate, sulfate, and ammonium, respectively, presented the highest concentration levels, indicating that biodiesel may also be a significant source for these ions, especially nitrate. Dibenzo[a,h]anthracene and indeno[1,2,3,-cd]pyrene were the main PAH found, and a higher fraction of PAH particles was found in diameters lower than 0.25 mu m in Londrina bus station. The fine and ultrafine particles were dominant among the PM evaluated, suggesting that biodiesel decreases the total PAH emission. However, it does also increase the fraction of fine and ultrafine particles when compared to diesel.
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The objective of this study was to determine the size and composition of atmospheric aerosols in the downtown area of the city of So Paulo, Brazil, for a polluted and an unpolluted period. Aerosols were sampled with a portable air sampler (PAS), Micro-Orifice Uniform Deposit Impactor (MOUDI), and Scanning Mobility Particle Sizer. At the study site, air quality is poor, especially during the winter, high concentrations of pollutants being emitted primarily by the light- and heavy-duty vehicle fleet. We analyzed mass, black carbon (BC), Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sn, Zr, and Pb. During the polluted period, diurnal PM(10) was higher than nocturnal PM(10), whereas the inverse was true during the unpolluted period. The FPM was rich in BC, S, and Pb, whereas CPM was rich in Al, Si, Ca, Ti, and Fe. Mass balance was performed by category: ammonium sulfate, sodium chloride, crustal material, BC, and other. The PAS-determined FPM was mainly BC. The MOUDI-determined FPM crustal material explained more mass than did ammonium sulfate and BC during the polluted period, whereas ammonium sulfate had the largest mass during the unpolluted period. Crustal material was the major CPM component, followed by ammonium sulfate and BC. During the unpolluted period, FPM concentrations were lower, whereas those of ammonium sulfate were relatively higher, especially at night, and particle number was inversely proportional to particle size. Aerosol growth was more intense during the polluted period.
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In the past decades, all of the efforts at quantifying systems complexity with a general tool has usually relied on using Shannon's classical information framework to address the disorder of the system through the Boltzmann-Gibbs-Shannon entropy, or one of its extensions. However, in recent years, there were some attempts to tackle the quantification of algorithmic complexities in quantum systems based on the Kolmogorov algorithmic complexity, obtaining some discrepant results against the classical approach. Therefore, an approach to the complexity measure is proposed here, using the quantum information formalism, taking advantage of the generality of the classical-based complexities, and being capable of expressing these systems' complexity on other framework than its algorithmic counterparts. To do so, the Shiner-Davison-Landsberg (SDL) complexity framework is considered jointly with linear entropy for the density operators representing the analyzed systems formalism along with the tangle for the entanglement measure. The proposed measure is then applied in a family of maximally entangled mixed state.
Resumo:
This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shannon entropy for general pattern recognition, and proposes a multi-q approach to improve pattern analysis using entropy. A series of experiments were carried out for the problem of classifying image patterns. Given a dataset of 40 pattern classes, the goal of our image case study is to assess how well the different entropies can be used to determine the class of a newly given image sample. Our experiments show that the Tsallis entropy using the proposed multi-q approach has great advantages over the Boltzmann-Gibbs-Shannon entropy for pattern classification, boosting image recognition rates by a factor of 3. We discuss the reasons behind this success, shedding light on the usefulness of the Tsallis entropy and the multi-q approach. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
In this analysis a 3.5 years data set of aerosol and precipitation chemistry, obtained in a remote site in Central Amazonia (Balbina, (1A degrees 55' S, 59A degrees 29' W, 174 m a.s.l.), about 200 km north of Manaus) is discussed. Aerosols were sampled using stacked filter units (SFU), which separate fine (d < 2.5 mu m) and coarse mode (2.5 mu m < d < 10.0 mu m) aerosol particles. Filters were analyzed for particulate mass (PM), Equivalent Black Carbon (BCE) and elemental composition by Particle Induced X-Ray Emission (PIXE). Rainwater samples were collected using a wet-only sampler and samples were analyzed for pH and ionic composition, which was determined using ionic chromatography (IC). Natural sources dominated the aerosol mass during the wet season, when it was predominantly of natural biogenic origin mostly in the coarse mode, which comprised up to 81% of PM10. Biogenic aerosol from both primary emissions and secondary organic aerosol dominates the fine mode in the wet season, with very low concentrations (average 2.2 mu g m(-3)). Soil dust was responsible for a minor fraction of the aerosol mass (less than 17%). Sudden increases in the concentration of elements as Al, Ti and Fe were also observed, both in fine and coarse mode (mostly during the April-may months), which we attribute to episodes of Saharan dust transport. During the dry periods, a significant contribution to the fine aerosols loading was observed, due to the large-scale transport of smoke from biomass burning in other portions of the Amazon basin. This contribution is associated with the enhancement of the concentration of S, K, Zn and BCE. Chlorine, which is commonly associated to sea salt and also to biomass burning emissions, presented higher concentration not only during the dry season but also for the April-June months, due to the establishment of more favorable meteorological conditions to the transport of Atlantic air masses to Central Amazonia. The chemical composition of rainwater was similar to those ones observed in other remote sites in tropical forests. The volume-weighted mean (VWM) pH was 4.90. The most important contribution to acidity was from weak organic acids. The organic acidity was predominantly associated with the presence of acetic acid instead of formic acid, which is more often observed in pristine tropical areas. Wet deposition rates for major species did not differ significantly between dry and wet season, except for NH4+, citrate and acetate, which had smaller deposition rates during dry season. While biomass burning emissions were clearly identified in the aerosol component, it did not present a clear signature in rainwater. The biogenic component and the long-range transport of sea salt were observed both in aerosols and rainwater composition. The results shown here indicate that in Central Amazonia it is still possible to observe quite pristine atmospheric conditions, relatively free of anthropogenic influences.
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Mining operations around the world make extensive use of blasthole sampling for short-term planning, which has two undisputed advantages: (1) blastholes are closely spaced providing relatively high sampling density per ton, and (2) there is no additional cost since the blastholes must be drilled anyway. However, blasthole sampling usually presents poor sampling precision, and the inconstant sampling bias caused by particle size and density segregation is an even more serious problem, generally precluding representativeness. One of the main causes of this bias is a highly varying loss of fines, which can lead to both under- and over-estimation of grade depending on the ore type and the gangue. This study validates a new, modified sectorial sampler, designed to reduce the loss of fines and thereby increase sampling accuracy for narrow-diameter blasthole sampling. First results show a significantly improved estimation of gold grade as well as the minimization of the loss of fines.
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Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.
Resumo:
Bioenergetic analysis may be applied in order to predict microbial growth yields, based on the Gibbs energy dissipation and mass conservation principles of the overall growth reaction. The bioenergetics of the photoautotrophic growth of the cyanobacterium Arthrospira (Spirulina) platensis was investigated in different bioreactor configurations (tubular photobioreactor and open ponds) using different nitrogen sources (nitrate and urea) and under different light intensity conditions to determine the best growing conditions in terms of Gibbs energy dissipation, number of photons to sustain cell growth and phototrophic energy yields distribution in relation to the ATP and NADPH formation, and release of heat. Although an increase in the light intensity increased the Gibbs energy dissipated for cell growth and maintenance with both nitrogen sources, it did not exert any appreciable influence on the moles of photons absorbed by the system to produce one C-mol biomass. On the other hand, both bioenergetic parameters were higher in cultures with nitrate than with urea, likely because of the higher energy requirements needed to reduce the former nitrogen source to ammonia. They appreciably increased also when open ponds were substituted by the tubular photobioreactor, where a more efficient light distribution ensured a remarkably higher cell mass concentration. The estimated percentages of the energy absorbed by the cell showed that, compared with nitrate, the use of urea as nitrogen source allowed the system to address higher energy fractions to ATP production and light fixation by the photosynthetic apparatus, as well as a lower fraction released as heat. The best energy yields values on Gibbs energy necessary for cell growth and maintenance were achieved in up to 4-5 days of cultivation, indicating that it would be the optimum range to maintain cell growth. Thanks to this better bioenergetic situation, urea appears to be a quite promising low-cost, alternative nitrogen source for Arthrospira platensis cultures in photobioreactors. (C) 2011 Elsevier Ltd. All rights reserved.
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The nonequilibrium stationary state of an irreversible spherical model is investigated on hypercubic lattices. The model is defined by Langevin equations similar to the reversible case, but with asymmetric transition rates. In spite of being irreversible, we have succeeded in finding an explicit form for the stationary probability distribution, which turns out to be of the Boltzmann-Gibbs type. This enables one to evaluate the exact form of the entropy production rate at the stationary state, which is non-zero if the dynamical rules of the transition rates are asymmetric.
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The extension of Boltzmann-Gibbs thermostatistics, proposed by Tsallis, introduces an additional parameter q to the inverse temperature beta. Here, we show that a previously introduced generalized Metropolis dynamics to evolve spin models is not local and does not obey the detailed energy balance. In this dynamics, locality is only retrieved for q = 1, which corresponds to the standard Metropolis algorithm. Nonlocality implies very time-consuming computer calculations, since the energy of the whole system must be reevaluated when a single spin is flipped. To circumvent this costly calculation, we propose a generalized master equation, which gives rise to a local generalized Metropolis dynamics that obeys the detailed energy balance. To compare the different critical values obtained with other generalized dynamics, we perform Monte Carlo simulations in equilibrium for the Ising model. By using short-time nonequilibrium numerical simulations, we also calculate for this model the critical temperature and the static and dynamical critical exponents as functions of q. Even for q not equal 1, we show that suitable time-evolving power laws can be found for each initial condition. Our numerical experiments corroborate the literature results when we use nonlocal dynamics, showing that short-time parameter determination works also in this case. However, the dynamics governed by the new master equation leads to different results for critical temperatures and also the critical exponents affecting universality classes. We further propose a simple algorithm to optimize modeling the time evolution with a power law, considering in a log-log plot two successive refinements.