154 resultados para Geo-statistical model
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Pós-graduação em Ciência dos Materiais - FEIS
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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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Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA
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The continuous trait age at subsequent rebreeding (ASR) was evaluated using survival analysis in Nellore breed cows that conceived for the first time at approximately 14 months of age. This methodology was chosen because the restricted breeding season produces censored data. The dataset contained 2885 records of ASR (in days). Records of females that did not produce calves in the following year after being exposed to a sire were considered censored (48.3% of the total). The statistical model used was a Weibull mixed survival model, which included fixed effects of contemporary groups (CG) and period and a random effect of individual animal. The effect of contemporary groups on ASR was significant (P < 0.01). Heritabilities obtained for ASR were 0.03 and 0.04 in logarithmic and original scales, respectively. These results indicate that the genetic selection response for subsequent reproduction of 2-year-old Nellore breed females is not expected to be effective based on survival analysis. Furthermore, these results suggest that environmental improvement is fundamental to this important trait. It should be highlighted that an increase in the average date of birth can produce an adverse effect in the future, since this cannot be compensated by genetic improvement.
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The prime movers behind the prehistoric colonization of Remote Oceania, and in particular the large c. 2000-year temporal gap (i.e. long pause') seen between West and East Polynesia, has long been major point of interest in the Pacific. To address these events and the processes that may have led to the known chronological disparity of these diasporas, we present results from two different, but equally powerful, analytical tools which are used to examine Polynesian seafaring capabilities and trajectories. The first is a statistical model known as Seascape, which simulates voyages, while the second uses ease of eastward travel estimates based on land distribution and wind pattern analysis. These analyses were done with the goal of determining the potential role of environmental factors in the colonization process, particularly as they relate to the long pause. We show that the eastern boundary of West Polynesia, the limit of the initial colonization pulse, is marked by a discontinuity in land distribution, where the distances travelers would have to cross in order to reach islands further to the east become significantly larger. At the same time, in West Polynesia, the frequency and intensity of winds favorable to eastward displacement decrease continuously from west to east. As far as winds are concerned, eastward travel in West Polynesia is favored in the northern and southern areas and much more difficult across the central portion. Favorable winds have a clear seasonality, and eastward displacement along the northern area is much easier under El Nino conditions. Voyaging simulations show that intentional eastward voyages departing from Tonga and Samoa, when undertaken with vessels capable of sailing efficiently against the wind, afford a viable route toward several island groups in East Polynesia, with trips starting in Samoa having a higher probability of success.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Genética e Melhoramento Animal - 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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Background Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.
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Time series tendencies are an important tool for different sectors such as the scientific community, industries and environmental protection agencies who can evaluate the variability of a specific parameter in time, what is very important piece of information for establishing corrective and preventive actions. This work presents a time series model of main physical, chemical and biological parameters of the Water Quality Index (WQI) determined for different selected points of a hydrographical basin form May/2006 to Aug/2010. The statistical model Arima enabled a better understanding of the physical, chemical and biological processes that most clearly influences WQI. The Arima model allowed the assessment of the trend of several parameters used in the calculation of the WQI, showing that dissolved oxygen, turbidity, total nitrogen, and fecal E. coli were highly correlated and are the parameters that caused the index changes over time.