165 resultados para Negative Binomial Regression Model (NBRM)
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Agronegócio e Desenvolvimento - Tupã
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.
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This study was designed to present the feasibility of an in vivo image-guided percutaneous cryoablation of the porcine vertebral body. Methods The institutional animal care committee approved this study. Cone-beam computed tomography (CBCT)-guided vertebral cryoablations (n = 22) were performed in eight pigs with short, 2-min, single or double-freezing protocols. Protective measures to nerves included dioxide carbon (CO2) epidural injections and spinal canal temperature monitoring. Clinical, radiological, and pathological data with light (n = 20) or transmission electron (n = 2) microscopic analyses were evaluated after 6 days of clinical follow-up and euthanasia. Results CBCT/fluoroscopic-guided transpedicular vertebral body cryoprobe positioning and CO2 epidural injection were successful in all procedures. No major complications were observed in seven animals (87.5 %, n = 8). A minor complication was observed in one pig (12.5 %, n = 1). Logistic regression model analysis showed the cryoprobe-spinal canal (Cp-Sc) distance as the most efficient parameter to categorize spinal canal temperatures lower than 19 °C (p<0.004), with a significant Pearson’s correlation test (p < 0.041) between the Cp-Sc distance and the lowest spinal canal temperatures. Ablation zones encompassed pedicles and the posterior wall of the vertebral bodies with an inflammatory rim, although no inflammatory infiltrate was depicted in the surrounding neural structures at light microscopy. Ultrastructural analyses evidenced myelin sheath disruption in some large nerve fibers, although neurological deficits were not observed. Conclusions CBCT-guided vertebral cryoablation of the porcine spine is feasible under a combination of a short freezing protocol and protective measures to the surrounding nerves. Ultrastructural analyses may be helpful assess the early modifications of the nerve fibers.
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A field trial was carried out in Brazil in March 2002 with the aim to evaluate the effects of different timing and extension of weedy period on maize productivity. The hybrid Pioneer 30K75 was sowed under 7 t ha(-1) mulching promoted by glyphosate spraying. The treatments were divided in two groups: In the first group, weeds were maintained since the maize sowing until different periods in the crop cycle: 0, 14, 28, 42, 56, 70, and 150 days (harvesting time). In the second group, the maize crop was kept weed free for the same periods of the first group. Weed control was done through hand hoeing. A complete randomized blocks experimental design with five replications was used for plots distribution in the field. Nonlinear regression model was used to study the effects of weedy or weedfree periods on maize productivity. Weed community included 13 families and 31 species. Asteraceae, Poaceae, and Euphorbiaceae were the most abundant families. Results showed that under no tillage condition with 7 t ha-1 mulching at sowing time, the maize crop could cohabit with weed community for 54 days without any yield lost. on the other hand, if the crop was kept weed free for 27 days, the weed interference was not enable to reduce maize production. According to these results one weed control measure between 27 and 54 days after crop emergence could be enough to avoid any reduction in maize productivity.
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Com o objetivo de obter uma equação que, através de parâmetros lineares dimensionais das folhas, permita a estimativa da área foliar de Brachiaria decumbens Stapf. e Brachiaria brizantha (Hochst.) Stapf., estudaram-se correlações entre a área foliar real (Sf) e parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. Todas as equações, exponenciais, geométricas ou lineares simples, permitiram boas estimativas da área foliar. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, considerando o coeficiente linear igual a zero. Desse modo, a estimativa da área foliar de B. decumbens pode ser feita pela fórmula Sf = 0,9810 x (C x L), ou seja, 98,10% do produto entre o comprimento ao longo da nervura principal e a largura máxima, enquanto que, para a B. brizantha a estimativa da área foliar pode ser feita pela fórmula SF = 0,7468 x (C x L), ou seja 74,68% do produto entre o comprimento ao longo da nervura principal e a largura máxima da folha.
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The aim of this research was to obtain a mathematical equation to estimate the leaf area of Ageratum conyzoides based on linear measures of its leaf blade. Correlation studies were done using real leaf area (Sf), leaf length (C) and the maximum leaf width (L), in about 200 leaf blades. The evaluated statistic models were: linear Y = a + bx; simple linear Y = bx; geometric Y = ax(b); and exponential Y = ab(x). The evaluated linear, exponential and geometric models can be used in the billygoat weed leaf area estimation. In the practical sense, the simple linear regression model is suggested using the C*L multiplication product and taking the linear coefficient equal to zero, because it showed weak-alteration on sum of squares error and satisfactory residual analysis. Thus, an estimate of A conyzoides leaf area can be obtained using the equation Sf = 0.6789*(C*L), with a determination coefficient of 0.8630.