923 resultados para density distribution
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A new method for high-resolution analyses of hair surface charge density under ambient conditions is presented in this paper. Electrostatic force microscopy (EFM) is used here to analyze changes in surface charge density in virgin hair, bleached hair, and hair treated with a cationic polymer. The atomic force microscopy technique is used concomitantly to analyze morphological changes in hair roughness and thickness. The EFM images depict exactly how the polymer is distributed on the surface of the hair fiber. The EFM's powerful analytical tools enabled us to evaluate the varying degrees of interaction between the hair fiber surface charge density and the cationic polymer. The surface charge density and the polymer's distribution in the hair fibers are presented in the light of EFM measurements. © 2006 Society of Cosmetic Scientists and the Socièété Française de Cosmétologie.
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Several studies suggest that, on a large scale, relief conditions influence the Atlantic Forest cover. The aim of this work was to explore these relationships on a local scale, in Caucaia do Alto, on the Ibiúna Plateau. Within an area of about 78 km2, the distribution of forest cover, divided into two successional stages, was associated with relief attribute data (slope, slope orientation and altitude). The mapping of the vegetation was based on the interpretation of stereoscopic pairs of aerial photographs, from April 2000, on a scale of 1:10,000, while the relief attributes were obtained by geoprocessing from digitalized topographic maps on a scale of 1:10,000. Statistical analyses, based on qui-square tests, revealed that there was a more extensive forest cover, irrespective of the successional stage, in steeper areas (>10 degrees) located at higher altitudes (>923 m), but no influence of the slope orientation. There was no sign of direct influence of relief on the forest cover through environmental gradients that might have contributed to the forest regeneration. Likewise, there was no evidence that these results could have been influenced by the distance from roads or urban areas or with respect to permanent preservation areas. Relief seems to influence the forest cover indirectly, since agricultural land use is preferably made in flatter and lower areas. These results suggest a general distribution pattern of the forest remnants, independent of the scale of study, on which relief indirectly has a strong influence, since it determines human occupation.
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The review focuses on the questions (1) how does the spatial heterogeneity of landscape influences carabid biodiversity, and (2) what are the main factors causing this biodiversity across nested spatial scales (study point - plant association - landscape level). The analysis of recent literature indicates that the spatial distribution of carabids differs at various spatial scales, and the factors responsible for the distribution are different. At the study point level most of the communities exhibit high variability of population density and diversity, which has no correlations with soil, and sometimes, vegetation, parameters. Most of the factors that contribute to formation of the communities are stochastic, simply because patches of a factor are much smaller than the size of a distinct carabid community. At the level of plant association, soil factors begin to play the role in driving the communities. At this level, litter depth, micro-climate and vegetation composition are the main factors. At the landscape level, geological factors, such as topography, landscape geochemistry, and history are playing important roles. As a conservation measure, spatial heterogeneity should be kept at all spatial scales at the same time to maintain carabid biodiversity in agricultural areas.
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In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. © 2010 Elsevier B.V. All rights reserved.
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Background: The aim of this study was to verify socioeconomic differences, nutrition, body balance and quality of life (QoL) in postmenopausal women with low bone mineral density (BMD) in two Amazonian communities. Methods: A total of 42 female volunteers participated in the study. The volunteers were separated into two groups: Villa (n= 20; 53±5.5 years) and City (n= 22; 56±7.9 years). The following evaluation instruments were used: dual energy X-ray absorptiometry (DXA); a socioeconomic questionnaire; a QoL questionnaire; a dietary habits questionnaire; and a balance test. Parametric and nonparametric tests were used. Results: The data showed significant differences in socioeconomic level (Δ%=+15.9%, p=0.000),lumbar spine L2-L4 (Δ%=+0.10%,p=0.007), balance(Δ%=+4.3%,p=0.03)and some important aspects of nutrition, such as the consumption of milk (Δ%=+34%, p=0.01) and alcohol (+14.8%, p=0.0001). These significant differences also contributed to the total QoL score (Δ%=+76.2%, p=0.000) and the majority of the QoL-related functions. Conclusion: This study verified that socioeconomic level, nutritional status, physical activity levels and QoL can influence the BMD of postmenopausal women. The study suggests new strategies for official health organizations to use in order to prevent and treat osteoporosis. In addition, this study can provide an orientation to physical activity, nutrition and medical professionals. © The Author(s), 2011.
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The success of fig trees in tropical ecosystems is evidenced by the great diversity (+750 species) and wide geographic distribution of the genus. We assessed the contribution of environmental variables on the species richness and density of fig trees in fragments of seasonal semideciduous forest (SSF) in Brazil. We assessed 20 forest fragments in three regions in Sao Paulo State, Brazil. Fig tree richness and density was estimated in rectangular plots, comprising 31.4 ha sampled. Both richness and fig tree density were linearly modeled as function of variables representing (1) fragment metrics, (2) forest structure, and (3) landscape metrics expressing water drainage in the fragments. Model selection was performed by comparing the AIC values (Akaike Information Criterion) and the relative weight of each model (wAIC). Both species richness and fig tree density were better explained by the water availability in the fragment (meter of streams/ha): wAICrichness = 0.45, wAICdensity = 0.96. The remaining variables related to anthropic perturbation and forest structure were of little weight in the models. The rainfall seasonality in SSF seems to select for both establishment strategies and morphological adaptations in the hemiepiphytic fig tree species. In the studied SSF, hemiepiphytes established at lower heights in their host trees than reported for fig trees in evergreen rainforests. Some hemiepiphytic fig species evolved superficial roots extending up to 100 m from their trunks, resulting in hectare-scale root zones that allow them to efficiently forage water and soil nutrients. The community of fig trees was robust to variation in forest structure and conservation level of SSF fragments, making this group of plants an important element for the functioning of seasonal tropical forests. © 2013 Elsevier Masson SAS. All rights reserved.
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The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.
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The association of genetic polymorphism in the estrogen receptor alpha (ERα) gene and risk for diseases including breast cancer (BC) has been the subject of great interest. Objective: Checking on women with high breast density after menopause, the frequency of the Pvull and Xbal polymorphisms of the ERα gene and the correlation between them and the known risk factors for breast cancer. Method: Observational study with 308 women between 45 and 65 years old with high breast density, without hormonal therapy, menstruation for a year or more, breast and ovarian cancer history. It was characterized in clinical history and physical examination: menarche, menopause, parity, family history of BC, smoking, alcohol intake and body mass index. Results: The allelic and genotypic frequencies for ERα-Pvull and Xbal: p=43.99%; p=56.01%; pp=32.14%; Pp=47.73% and PP=20.13%; X=41.56%; x=58.44%; xx=33.44%; Xx=50.00% and XX=16.56%, respectively. The most frequent risk factors for BC: menarche before 12 years old (35.38%), nulliparity or first child after 28 years old (41.66%), family history of BC (19.16%) and overweight/obesity (62.01%). Conclusion: Allelic and genotypic distribution similar to literature. The risk factors for BC were more prevalent in women with high breast density but without significant associations with these polymorphisms. © 2013 Informa UK Ltd. All rights reserved.
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In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Multivariate morphometrics and image analysis were used to determine the number of well-delineated infrageneric taxa of Sirodotia in North America. Three groupings were distinguished from 25 populations examined from Newfoundland and Quebec in the north to central Mexico in the south. These groupings were statistically related to 10 type specimens, and the following species were recognized: Sirodotia huillensis (Welwitsch ex W. et G. S. West) Skuja (syn. S. ateleia Skuja), S. suecica Kylin (syn. S. acuminata Skuja ex Flint and S. fennica Skuja), and S. tenuissima (Collins) Skuja ex Flint. These species are differentiated on the basis of whorl shape and degree of separation at maturity (S. suecica, rounded and appressed; S. huillensis and S. tenuissima, truncated apex and separated), the density of spermatangia (S. huillensis, dense clusters, S. suecica and S. tenuissima, sparsely aggregated), and the mode of germination of the gonimoblast initial (S. suecica and S. tenuissima,from the nonprotuberant side of the fertilized carpogonium; S. huillensis from the protuberant side). Sirodotia huillensis was found only in the desert-chaparral, whereas S. suecica and S. tenuissima occurred from south-temperate to boreal regions in cool (temperature 8-18-degrees-C), low ion (specific conductance 10-99 muS.cm-1), and mildly acidic to neutral (pH 5.7-7.3) waters.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The use of relatively low numbers of sires in cattle breeding programs, particularly on those for carcass and weight traits in Nellore beef cattle (Bos indicus) in Brazil, has always raised concerns about inbreeding, which affects conservation of genetic resources and sustainability of this breed. Here, we investigated the distribution of autozygosity levels based on runs of homozygosity (ROH) in a sample of 1,278 Nellore cows, genotyped for over 777,000 SNPs. We found ROH segments larger than 10 Mb in over 70% of the samples, representing signatures most likely related to the recent massive use of few sires. However, the average genome coverage by ROH (>1 Mb) was lower than previously reported for other cattle breeds (4.58%). In spite of 99.98% of the SNPs being included within a ROH in at least one individual, only 19.37% of the markers were encompassed by common ROH, suggesting that the ongoing selection for weight, carcass and reproductive traits in this population is too recent to have produced selection signatures in the form of ROH. Three short-range highly prevalent ROH autosomal hotspots (occurring in over 50% of the samples) were observed, indicating candidate regions most likely under selection since before the foundation of Brazilian Nellore cattle. The putative signatures of selection on chromosomes 4, 7, and 12 may be involved in resistance to infectious diseases and fertility, and should be subject of future investigation.