50 resultados para linear model

em Scielo Saúde Pública - SP


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A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

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In this article a two-dimensional transient boundary element formulation based on the mass matrix approach is discussed. The implicit formulation of the method to deal with elastoplastic analysis is considered, as well as the way to deal with viscous damping effects. The time integration processes are based on the Newmark rhoand Houbolt methods, while the domain integrals for mass, elastoplastic and damping effects are carried out by the well known cell approximation technique. The boundary element algebraic relations are also coupled with finite element frame relations to solve stiffened domains. Some examples to illustrate the accuracy and efficiency of the proposed formulation are also presented.

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OBJECTIVE To analyze the coverage of a cervical cancer screening program in a city with a high incidence of the disease in addition to the factors associated with non-adherence to the current preventive program.METHODS A cross-sectional study based on household surveys was conducted. The sample was composed of women between 25 and 59 years of age of the city of Boa Vista, RR, Northern Brazil who were covered by the cervical cancer screening program. The cluster sampling method was used. The dependent variable was participation in a women’s health program, defined as undergoing at least one Pap smear in the 36 months prior to the interview; the explanatory variables were extracted from individual data. A generalized linear model was used.RESULTS 603 women were analyzed, with an mean age of 38.2 years (SD = 10.2). Five hundred and seventeen women underwent the screening test, and the prevalence of adherence in the last three years was up to 85.7% (95%CI 82.5;88.5). A high per capita household income and recent medical consultation were associated with the lower rate of not being tested in multivariate analysis. Disease ignorance, causes, and prevention methods were correlated with chances of non-adherence to the screening system; 20.0% of the women were reported to have undergone opportunistic and non-routine screening.CONCLUSIONS The informed level of coverage is high, exceeding the level recommended for the control of cervical cancer. The preventive program appears to be opportunistic in nature, particularly for the most vulnerable women (with low income and little information on the disease). Studies on the diagnostic quality of cervicovaginal cytology and therapeutic schedules for positive cases are necessary for understanding the barriers to the control of cervical cancer.

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Observational and experimental studies have shown that increased concealment of bird nests reduces nest predation rates. The objective of the present study was to evaluate differences in predation rates between two experimental manipulations of artificial ground nests (i.e., clearing an area around the artificial nest or leaving it as natural as possible), and test whether environmental variables also affected nest predation in an undisturbed area of Amazonian forest in eastern Brazil. A generalized linear model was used to examine the influence of five variables (manipulation type, perpendicular distance from the main trail, total basal area of trees surrounding the nest site, understorey density, and liana quantity) on nest predation rates. Model results, showed that manipulation type was the only variable that significantly affected nest predation rates. Thus, to avoid systematic biases, the influence of nest site manipulation must be taken into consideration when conducting experiments with artificial nests.

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Different urban structures might affect the life history parameters of Aedes aegypti and, consequently, dengue transmission. Container productivity, probability of daily survival (PDS) and dispersal rates were estimated for mosquito populations in a high income neighbourhood of Rio de Janeiro. Results were contrasted with those previously found in a suburban district, as well as those recorded in a slum. After inspecting 1,041 premises, domestic drains and discarded plastic pots were identified as the most productive containers, collectively holding up to 80% of the total pupae. In addition, three cohorts of dust-marked Ae. aegypti females were released and recaptured daily using BGS-Traps, sticky ovitraps and backpack aspirators in 50 randomly selected houses; recapture rate ranged from 5-12.2% within cohorts. PDS was determined by two models and ranged from 0.607-0.704 (exponential model) and 0.659-0.721 (non-linear model), respectively. Mean distance travelled varied from 57-122 m, with a maximum dispersal of 263 m. Overall, lower infestation indexes and adult female survival were observed in the high income neighbourhood, suggesting a lower dengue transmission risk in comparison to the suburban area and the slum. Since results show that urban structure can influence mosquito biology, specific control strategies might be used in order to achieve cost-effective Ae. aegypti control.

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In the present paper, we evaluate the relationship between climate variables and population density of Lutzomyia longipalpis in Montes Claros, an area of active transmission of American visceral leishmaniasis (AVL) in Brazil. Entomological captures were performed in 10 selected districts of the city, between September 2002-August 2003. A total of 773 specimens of L. longipalpiswere captured in the period and the population density could be associated with local climate variables (cumulative rainfall, average temperature and relative humidity) through a mathematical linear model with a determination coefficient (Rsqr) of 0.752. Although based on an oversimplified statistical analysis, as far as the vector is concerned, this approach showed to be potentially useful as a starting point to guide control measures for AVL in Montes Claros.

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Dipteran larvae were collected from rabbit (Oryctolagus cunniculus L.) carcasses during the four seasons in 2005 in the southernmost state of Rio Grande do Sul, Brazil. The larvae were fed ground beef at ambient temperatures following collection from carcasses. The development of each species under these conditions was estimated. The most abundant species in the carcasses were Lucilia eximia (Wiedemann) and Chrysomya albiceps (Wiedemann) (Calliphoridae), and they were found in all seasons. The data were fitted to a linear model that describes the relationship between temperature and linear developmental rating. These two species are primary forensic indicators in southern Brazil. Other species such as Hemilucilia semidiaphana (Rondani) (Calliphoridae), Synthesiomyia nudiseta (Wulp), Muscina stabulans (Fallen) (Muscidae), and Fannia pusio (Wiedemann) (Fanniidae) were forensically less important because they only occurred in high frequency in certain seasons and during the first days of carcass decomposition.

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The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

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The objective of this work was to evaluate the effects of single-nucleotide polymorphisms (SNPs) in the genes IGF1 (AF_017143.1:g.198C>T), MSTN (AF_320998.1:g.433C>A), MYOD1 (NC_007313:g.1274A>G) and MYF5 (NC_007303:g.1911A>G) on carcass and meat traits in Nelore (Bos indicus) and Nelore x B. taurus. A total of 300 animals were genotyped and phenotyped for rib eye area (REA), backfat thickness (BT), intramuscular fat (IF), shear force (SF) and myofibrillar fragmentation index (MFI). The effects of allele substitution for each SNP were estimated by regression of the evaluated phenotypes on the number of copies of a particular allele using the general linear model. The polymorphism at IGF1 was non-informative in Nelore animals. In crossbred animals, the IGF1 C allele was associated with greater REA. However, this relation was not significant after Bonferroni correction for multiple testing. The A allele of the MSTN polymorphism was absent in Nelore cattle and was only found in two crossbred animals. The polymorphisms of MYOD1 and MYF5 were little informative in Nelore animals with G allele frequency of 0.097 and A allele frequency of 0.031, respectively. These markers show no association with the analyzed traits in the total sample of evaluated animals.

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The objective of this work was to assess the genetic diversity and population structure of wheat genotypes, to detect significant and stable genetic associations, as well as to evaluate the efficiency of statistical models to identify chromosome regions responsible for the expression of spike-related traits. Eight important spike characteristics were measured during five growing seasons in Serbia. A set of 30 microsatellite markers positioned near important agronomic loci was used to evaluate genetic diversity, resulting in a total of 349 alleles. The marker-trait associations were analyzed using the general linear and mixed linear models. The results obtained for number of allelic variants per locus (11.5), average polymorphic information content value (0.68), and average gene diversity (0.722) showed that the exceptional level of polymorphism in the genotypes is the main requirement for association studies. The population structure estimated by model-based clustering distributed the genotypes into six subpopulations according to log probability of data. Significant and stable associations were detected on chromosomes 1B, 2A, 2B, 2D, and 6D, which explained from 4.7 to 40.7% of total phenotypic variations. The general linear model identified a significantly larger number of marker-trait associations (192) than the mixed linear model (76). The mixed linear model identified nine markers associated to six traits.

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The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

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The deviations observed in the solubility of ibuprofen (IBP) and naproxen (NAP) in propylene glycol (PG) + water (W) cosolvent mixtures with respect to the logarithmic-linear model proposed by Yalkowsky have been analyzed at 25.00 ± 0.05 ºC. Negative deviations were obtained in all cosolvent compositions for both drugs; they were greater for IBP. Another treatment, based on Gibbs free energy relationships, was also employed showing an apparent hydrophobicity chameleonic effect, because at low PG proportions NAP is more hydrophobic, whereas at high PG proportions IBP is more hydrophobic. The results are discussed in terms of solute-solvent and solvent-solvent interactions.

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The objective of this manuscript is to describe a practical experiment that can be employed for teaching concepts related to design of experiments using Matlab or Octave computing environment to beginners, undergraduate and graduate students. The classical experiment for determination of Fe (II) using o-phenanthroline was selected because it is easy to understand, and all the required materials are readily available in most analytical laboratories. The approach used in this tutorial is divided in two steps: first, the students are introduced to the concept of multivariate effects, how to calculate and interpret them, and the construction and evaluation of a linear model to describe the experimental domain by using a 2³ factorial design. Second, an extension of the factorial design by adding axial points is described, thereby, providing a central composite design. The quadratic model is then introduced and used to build the response surface.

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ABSTRACT This study aimed to estimate the genetic correlation among selection ages (juvenile - adult) and efficiency of early selection for the height, diameter, and volume traits of individuals from Pinus taeda families propagated via somatic embryogenesis. This study was carried out by genetic-statistical analysis, estimation procedure of variance (Reml), and prediction components of breeding values (Blup), using the Selegen-Reml/Blup software. Genetic correlations among juvenile ages and rotation age were performed by applying the linear model developed by Lambeth (1980). In accordance with results of the established model, the early selection can be performed in clones of Pinus taeda with high selection efficiency. Ages from 4 to 6 years old are enough to select Pinus taeda clones propagated via somatic embryogenesis for harvesting at 8 and 12 years old; and 6 to 10 years old are enough to select them for harvesting at 20 years old. On the basis of the genetic correlations estimates from the environments, the clones' selection of Pinus taeda propagated via somatic embryogenesis should be developed specifically for each environment. The clones' selection can be performed considering the diameter due to the high correlation between volume and diameter.

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The determination of volumetric water content of soils is an important factor in irrigation management. Among the indirect methods for estimating, the time-domain reflectometry (TDR) technique has received a significant attention. Like any other technique, it has advantages and disadvantages, but its greatest disadvantage is the need of calibration and high cost of acquisition. The main goal of this study was to establish a calibration model for the TDR equipment, Trase System Model 6050X1, to estimate the volumetric water content in a Distroferric Red Latosol. The calibration was carried out in a laboratory with disturbed soil samples under study, packed in PVC columns of a volume of 0.0078m³. The TDR probes were handcrafted with three rods and 0.20m long. They were vertically installed in soil columns, with a total of five probes per column and sixteen columns. The weightings were carried out in a digital scale, while daily readings of dielectric constant were obtained in TDR equipment. The linear model θν = 0.0103 Ka + 0.1900 to estimate the studied volumetric water content showed an excellent coefficient of determination (0.93), enabling the use of probes in indirect estimation of soil moisture.