Reduced calibration curve for proton computed tomography

The pCT deals with relatively thick targets like the human head or trunk. Thus, the fidelity of pCT as a tool for proton therapy planning depends on the accuracy of physical formulas used for proton interaction with thick absorbers. Although the actual overall accuracy of the proton stopping power in the Bethe-Bloch domain is about 1%, the analytical calculations and the Monte Carlo simulations with codes like TRIM/SRIM, MCNPX and GEANT4 do not agreed with each other. A tentative to validate the codes against experimental data for thick absorbers bring some difficulties: only a few data is available and the existing data sets have been acquired at different initial proton energies, and for different absorber materials. In this work we compare the results of our Monte Carlo simulations with existing experimental data in terms of reduced calibration curve, i.e. the range - energy dependence normalized on the range scale by the full projected CSDA range for given initial proton energy in a given material, taken from the NIST PSTAR database, and on the final proton energy scale - by the given initial energy of protons. This approach is almost energy and material independent. The results of our analysis are important for pCT development because the contradictions observed at arbitrary low initial proton energies could be easily scaled now to typical pCT energies. © 2010 American Institute of Physics.

Comparison of the GEANT4 releases 8.2 and 9.2 in terms of a pCT reduced calibration curve

The GEANT4 simulations are essential for the development of medical tomography with proton beams pCT. In the case of thin absorbers the latest releases of GEANT4 generate very similar final spectra which agree well with the results of other popular Monte Carlo codes like TRIM/SRIM, or MCNPX. For thick absorbers, however, the disagreements became evident. In a part, these disagreements are due to the known contradictions in the NIST PSTAR and SRIM reference data. Therefore, it is interesting to compare the GEANT4 results with each other, with experiment, and with diverse code results in a reduced form, which is free from this kind of doubts. In this work such comparison is done within the Reduced Calibration Curve concept elaborated for the proton beam tomography. © 2010 IEEE.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Interval multivariate curve resolution in the dereplication of HPLC-DAD data from Jatropha gossypifolia

Introduction Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. Objective To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. Methods Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). Results The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. Conclusion The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd. Extracts from J. gossypifolia were analyzed by HPLC-DAD and, dereplicated applying MCR-ALS. The method assisted in the detection of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. The application of MCR-ALS allowed solving problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. © 2013 American Dairy Science Association.

Diferentes abordagens para modelar a produção de leite de bovinos da raça Guzerá

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelos de regressão aleatória para a estimação de parâmetros genéticos da produção e constituintes do leite de búfalas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimação de parâmetros genéticos para características de crescimento em bovinos da raça Canchim com modelos de dimensão finita e infinita

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Inversão de dados sísmicos de reflexão a partir da curva do tempo de trânsito

A presente Dissertação de Mestrado tem como objetivo o estudo do problema de inversão sísmica baseada em refletores planos para arranjo fonte-comum (FC) e ponto-médiocomum (PMC). O modelo direto é descrito por camadas homogêneas, isotrópicas com interfaces plano-horizontais. O problema é relacionado ao empilhamento NMO baseado na otimização da função semblance, para seções PMC corrigidas de sobretempo normal (NMO). O estudo foi baseado em dois princípios. O primeiro princípio adotado foi de combinar dois grupos de métodos de inversão: um Método Global e um Método Local. O segundo princípio adotado foi o de cascata, segundo a teoria Wichert-Herglotz-Bateman, que estabelece que para conhecer uma camada inferior tem-se que conhecer primeiro a camada superior (dissecação). A aplicação do estudo é voltada à simulação sísmica de Bacia Sedimentar do Solimões e de Bacia Marinha para se obter uma distribuição local 1D de velocidades e espessuras para a subsuperfície em horizontes alvo. Sendo assim, limitamos a inversão entre 4 e 11 refletores, uma vez que na prática a indústria limita uma interpretação realizada apenas em número equivalente de 3 a 4 refletores principais. Ressalta-se que este modelo é aplicável como condição inicial ao imageamento de seções sísmicas em regiões geologicamente complexas com variação horizontal suave de velocidades. Os dados sintéticos foram gerados a partir dos modelos relacionados a informações geológicas, o que corresponde a uma forte informação a priori no modelo de inversão. Para a construção dos modelos relacionados aos projetos da Rede Risco Exploratório (FINEP) e de formação de recursos humanos da ANP em andamento, analisamos os seguintes assuntos relevantes: (1) Geologia de bacias sedimentares terrestre dos Solimões e ma rinha (estratigráfica, estrutural, tectônica e petrolífera); (2) Física da resolução vertical e horizontal; e (3) Discretização temporal-espacial no cubo de multi-cobertura. O processo de inversão é dependente do efeito da discretização tempo-espacial do campo de ondas, dos parâmetros físicos do levantamento sísmico, e da posterior reamostragem no cubo de cobertura múltipla. O modelo direto empregado corresponde ao caso do operador do empilhamento NMO (1D), considerando uma topografia de observação plana. O critério básico tomado como referência para a inversão e o ajuste de curvas é a norma 2 (quadrática). A inversão usando o presente modelo simples é computacionalmente atrativa por ser rápida, e conveniente por permitir que vários outros recursos possam ser incluídos com interpretação física lógica; por exemplo, a Zona de Fresnel Projetada (ZFP), cálculo direto da divergência esférica, inversão Dix, inversão linear por reparametrização, informações a priori, regularização. A ZFP mostra ser um conceito út il para estabelecer a abertura da janela espacial da inversão na seção tempo-distância, e representa a influência dos dados na resolução horizontal. A estimativa da ZFP indica uma abertura mínima com base num modelo adotado, e atualizável. A divergência esférica é uma função suave, e tem base física para ser usada na definição da matriz ponderação dos dados em métodos de inversão tomográfica. A necessidade de robustez na inversão pode ser analisada em seções sísmicas (FC, PMC) submetida a filtragens (freqüências de cantos: 5;15;75;85; banda-passante trapezoidal), onde se pode identificar, comparar e interpretar as informações contidas. A partir das seções, concluímos que os dados são contaminados com pontos isolados, o que propõe métodos na classe dos considerados robustos, tendo-se como referência a norma 2 (quadrados- mínimos) de ajuste de curvas. Os algoritmos foram desenvolvidos na linguagem de programação FORTRAN 90/95, usando o programa MATLAB para apresentação de resultados, e o sistema CWP/SU para modelagem sísmica sintética, marcação de eventos e apresentação de resultados.

Growth curve of female collared peccaries (Pecari tajacu) raised in captivity in the Brazilian Amazon Region

Com o objetivo de ajustar modelos não-lineares, foram utilizados registros mensais do peso de 10 fêmeas de cateto (Pecari tajacu) coletados durante dois anos, no criatório do campo experimental Álvaro Adolfo da Embrapa Amazônia Oriental, Belém, PA. Utilizaram-se os modelos de Von Bertalanffy, Brody, Gompertz e Logístico. Os parâmetros foram estimados usando o procedimento NLIN do aplicativo SAS. Os critérios utilizados para verificar o ajuste dos modelos foram: desvio padrão assintótico (ASD); coeficiente de determinação (R²); desvio médio absoluto dos resíduos (ARD) e o índice assintótico (AR). Os modelos Brody e Logístico estimaram, respectivamente, o maior (19,44kg) e o menor (19,18kg) peso assintótico (A), caracterizando a menor (0,0064kg/dia) e a maior (0,0113kg/dia) taxa de maturação (K), haja vista a natureza antagônica entre estes parâmetros, comprovada pela correlação fenotípica variando entre -0,75 à -0,47. O modelo Brody estimou o menor valor para o ARD, fator limitante para caracterizar o menor valor para o AR por este modelo. Considerando o AR, o modelo Brody apresentou o melhor ajuste, contudo, pelos valores encontrados, os demais modelos também apresentaram ajuste adequando aos dados ponderais da referida espécie/sexo. Com base no AR adotado neste trabalho, recomenda-se o modelo Brody para ajustar a curva de crescimento de fêmeas de cateto (Pecari tajacu). Em razão dos valores estimados, sobretudo, para a K, essa característica pode ser incluída em um índice de seleção. Contudo, estudos com grupos mais representativos e criados em outras condições se faz oportuno.

Use of mathematical models in the study of bodily growth in GIFT strain Nile tilapia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influence of salts on the coexistence curve and protein partitioning in nonionic aqueous two-phase micellar systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)