Methods to verify parameter equality in nonlinear regression models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic parameters of milk, fat, and protein yields in the first three lactations, using an animal model and restricted maximum likelihood

Milk, fat, and protein yields of Holstein cows from the States of New York and California in the United States were used to estimate (co)variances among yields in the first three lactations, using an animal model and a derivative-free restricted maximum likelihood (REML) algorithm, and to verify if yields in different lactations are the same trait. The data were split in 20 samples, 10 from each state, with means of 5463 and 5543 cows per sample from California and New York. Mean heritability estimates for milk, fat, and protein yields for California data were, respectively, 0.34, 0.35, and 0.40 for first; 0.31, 0.33, and 0.39 for second; and 0.28, 0.31, and 0.37 for third lactations. For New York data, estimates were 0.35, 0.40, and 0.34 for first; 0.34, 0.44, and 0.38 for second; and 0.32, 0.43, and 0.38 for third lactations. Means of estimates of genetic correlations between first and second, first and third, and second and third lactations for California data were 0.86, 0.77, and 0.96 for milk; 0.89, 0.84, and 0.97 for fat; and 0.90, 0.84, and 0.97 for protein yields. Mean estimates for New York data were 0.87, 0.81, and 0.97 for milk; 0.91, 0.86, and 0.98 for fat; and 0.88, 0.82, and 0.98 for protein yields. Environmental correlations varied from 0.30 to 0.50 and were larger between second and third lactations. Phenotypic correlations were similar for both states and varied from 0.52 to 0.66 for milk, fat and protein yields. These estimates are consistent with previous estimates obtained with animal models. Yields in different lactations are not statistically the same trait but for selection programs such yields can be modelled as the same trait because of the high genetic correlations.

Ovarian follicle diameter at timed insemination and estrous response influence likelihood of ovulation and pregnancy after estrous synchronization with progesterone or progestin-based protocols in suckled Bos indicus cows

The objectives of the present study were to evaluate factors associated with estrous synchronization responses and pregnancy per insemination (P/AI) in Bos indicus beef cows submitted to progesterone-based fixed-time artificial insemination (FTAI) protocols. A total of 2388 cows (1869 Nellore and 519 crossbred Nellore x Angus) from 10 commercial farms were evaluated to determine the relationships among breed, body condition score (BCS) on the first day of the FTAI protocol, the occurrence of estrus between progesterone device removal and FTAI and diameter of largest ovarian follicle (LF) at FTAI on estrous synchronization responses and P/AI. Cows (n=412 primiparous; 1976 multiparous) received an intravaginal device containing progesterone or an ear implant containing norgestomet (a progestin), and an injection of estradiol at the beginning of the estrous synchronization protocol. Body condition was scored using a 1-5 scale on the first day of the FTAI protocol and at 30-60 days postpartum. Females received 300IU of equine chorionic gonadotropin (eCG) and PGF(2 alpha) on the day the progesterone device/implant was removed and were inseminated 48-60h later. At insemination, cows (n=2388) were submitted to an ultrasonographic exam to determine the diameter of the LF. Follicles were classified into four categories based on mean and standard deviation (SD) of the LF (LF1 = two SD below the mean; LF2 = mean minus one SD; LF3 = mean plus one SD; LF4 = two SD above the mean). Ovulation rate was determined in a subset of cows (n=813) by three consecutive ultrasonographic exams: (1) at time of progesterone device/implant removal, (2) at time of FTAI and (3) 48 h after FTAI. Ovulation was defined as the disappearance of a large follicle (>= 8.0 mm) that was previously recorded. Estrus was determined in a subset of the cows (n = 445) by the activation of a detection of estrous patch placed on the tail head on the day of progesterone device/implant removal. Pregnancy was diagnosed 30 days after FTAI. Pregnancy was influenced (P = 0.001) by follicle diameter [LF1 = 27.5% (81/295), LF2 = 46.6% (328/705), LF3 = 57.9% (647/1118), LF4 = 63.3% (171/270)] and the occurrence of estrus [estrus = 67.7% (174/257) and no estrus = 36.2% (68/188)]. Follicle diameter at FTAI influenced ovulation rate [LF1 = 42.5% (34/80), LF2 = 73.9% (161/218), LF3 = 95.8% (407/425), LF4 = 97.8% (88/90)], the occurrence of estrus [LF1 = 54.8% (51/93), LF2 = 33.6% (43/128), LF3 = 68.9% (126/183), LF4 = 90.2% (37/41)] and P/AI among cows that had ovulations [LF1 =32.4% (11/34), LF2 = 50.3% (81/161), LF3 = 60.0% (244/407), LF4 = 68.2% (60/88)]. Improving estrous responses between progesterone device withdrawal and FTAI and increasing the diameter of the LF at FTAI may be important aspects to achieve improved estrous synchronization responses and P/AI following progesterone/progestin and estradiol based FTAI protocols in suckled Bos indicus cows. (C) 2010 Elsevier B.V. All rights reserved.

Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

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

Heritability estimates and genetic correlations for body weight and scrotal circumference adjusted to 12 and 18 months of age for male Nellore cattle

Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12 BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 +/- 0.11, 0.21 +/- 0.13, 0.21 +/- 0.11, -0.08 +/- 0.15, 0.16 +/- 0.12 and 0.89 +/- 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12 suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter it is suggested that the practice of individual selection for these traits is possible.

Batch and filter approaches to spacecraft sensor alignment estimation

Two Kalman-filter formulations are presented for the estimation of spacecraft sensor misalignments from inflight data. In the first the sensor misalignments are part of the filter state variable; in the second the state vector contains only dynamical variables, but the sensitivities of the filter innovations to the misalignments are calculated within the Kalman filter. This procedure permits the misalignments to be estimated in batch mode as well as a much smaller dimension for the Kalman filter state vector. This results not only in a significantly smaller computational burden but also in a smaller sensitivity of the misalignment estimates to outliers in the data. Numerical simulations of the filter performance are presented.

Bayesian and multivariate methods applied to favorability quantification in recôncavo Basin and Ribeira Belt, Brazil

A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

Repeatability and heritability of response to superovulation in Holstein cows

The objective of this study was to estimate the relative effects of genetic and phenotypic factors on the efficacy and efficiency of superovulation for Holstein-Friesian cows reared in Brazil. A database, established by the Associacao Brasileira de Criadores de Bovinos da Raca Holandesa, consisting of a total of 5387 superovulations of 2941 cows distributed over 473 herds and sired by 690 bulls was used for the analysis. The records were analyzed by MTDFREML (Multiple Trait Derivative-Free Restricted Maximum Likelihood), using a repeatability animal model. The fixed effects included in the model were contemporaneous group (veterinarian, herd, year and season of the superovulation); number of semen doses; cow age; and superovulation order. The estimated repeatability of the number of the transferable embryos was low (0.13), and the estimated heritability was 0.03. These results indicate that environmental factors play a critical role in the response of a cow to a superovulation treatment. There is little evidence that future responses to superovulation by individual females can be predicted by previous treatment(s) or that superovulation response is an heritable trait.

Study of a fuel cell cogeneration system applied to a Brazilian tertiary sector

In this paper, a methodology for the study of a molten carbonate fuel cell cogeneration system and applied to a computer center building is developed. This system permits the recovery of waste heat, available between 600°C and 700°C, which can be used to the production of steam, hot and cold water, hot and cold air, depending on the recuperation equipment associated. Initially, some technical information about the most diffusing types of the fuel cell demonstration in the world are presented. In conclusion, the fuel cell cogeneration system may have an excellent opportunity to strengthen the decentralized energy production in the Brazilian tertiary sector.

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

A general technique to embed non-uniform discontinuities into standard solid finite elements

A general technique to embed non-uniform displacement discontinuities into standard solid finite elements is presented. The technique is based on the decomposition of the kinematic fields into a component related to the deformation of the solid portion of the element and one related to the rigid-body motion due to a displacement discontinuity. This decomposition simplifies the incorporation of discontinuity interfaces and provides a suitable framework to account for non-uniform discontinuity modes. The present publication addresses two families of finite element formulations: displacement-based and stress hybrid finite element. © 2005 Elsevier Ltd. All rights reserved.

End-to-end validation of EPS / MetOp GOME-2 trace gas data

Within the next decade, the improved version 2 of Global Ozone Monitoring Experiment (GOME-2), a ultraviolet-visible spectrometer dedicated to the observation of key atmospheric trace species from space, will be launched successively on board three EUMETSAT Polar System (EPS) MetOp satellites. Starting with the launch of MetOp-1 scheduled for summer 2006, the GOME-2 series will extend till 2020 the global monitoring of atmospheric composition pioneered with ERS-2 GOME-1 since 1995 and enhanced with Envisat SCIAMACHY since 2002 and EOS-Aura OMI since 2004. For more than a decade, an international pool of scientific teams active in ground-and space-based ultraviolet-visible remote sensing have contributed to the successful post-launch validation of trace gas data products and the associated maturation of retrieval algorithms for the latter satellites, ensuring that geophysical data products are/become reliable and accurate enough for intended research and applications. Building on this experience, this consortium plans now to develop and carry out appropriate validation of a list of GOME-2 trace gas column data of both tropospheric and stratospheric relevance: nitrogen dioxide (NO 2), ozone (O 3), bromine monoxide (BrO), chlorine dioxide (OClO), formaldehyde (HCHO), and sulphur dioxide (SO 2). The proposed investigation will combine four complementary approaches resulting in an end-to-end validation of expected column data products.

GDP 4.0 transfer to SGP 3.0 for SCIAMACHY no2 column processing: Verification with SDOAS / GDOAS prototype algorithms and delta-validation with NDACC / UV-visible network data

Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

Evidence for 2.35 to 2.30 Ga juvenile crustal growth in the northwest Borborema Province, NE Brazil

The c. 600 Ma Brasiliano Borborema Province of NE Brazil comprises a complex collage of Precambrian crustal blocks cut by a series of continental-scale shear zones. The predominant basement rocks in the province are 2.1-2.0 Ga Transamazonian gneisses of both juvenile and reworked nature. U-Pb zircon and Sm-Nd whole-rock studies of tonalite-trondhjemite-granodiorite basement gneisses in the NW Ceará or Médio Coreaú domain in the northwestern part of the Borborema Province indicate that this represents a continental fragment formed by 2.35-2.30 Ga juvenile crust. This block has no apparent genetic affinity with any other basement gneisses in the Borborema Province, and it does not represent the tectonized margin of the c. 2.1-2.0 Ga São Luis Craton to the NW. The petrological and geochemical characteristics, as well as the Nd-isotopic signatures of these gneisses, are consistent with their genesis in an island arc setting. This finding documents a period of crustal growth during a period of the Earth's history which is known for its tectonic quiescence and paucity of crust formation. © Geological Society of London 2009.

Solving the Levins' paradox in the logistic model to the population growth

We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.