Estimates of covariance functions for growth of Nelore cattle applying a parametric correlation structure to model within-animal correlations

A total of 20,065 weights recorded on 3016 Nelore animals were used to estimate covariance functions for growth from birth to 630 days of age, assuming a parametric correlation structure to model within-animal correlations. The model of analysis included fixed effects of contemporary groups and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Genetic effects of the animal and its dam and maternal permanent environmental effects were modelled by random regressions on Legendre polynomials of age at recording. Changes in direct permanent environmental effect variances were modelled by a polynomial variance function, together with a parametric correlation function to account for correlations between ages. Stationary and nonstationary models were used to model within-animal correlations between different ages. Residual variances were considered homogeneous or heterogeneous, with changes modelled by a step or polynomial function of age at recording. Based on Bayesian information criterion, a model with a cubic variance function combined with a nonstationary correlation function for permanent environmental effects, with 49 parameters to be estimated, fitted best. Modelling within-animal correlations through a parametric correlation structure can describe the variation pattern adequately. Moreover, the number of parameters to be estimated can be decreased substantially compared to a model fitting random regression on Legendre polynomial of age. © 2004 Elsevier B.V. All rights reserved.

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.

On a model for the growth of an invasive avascular tumor

This paper is devoted to study the 1D model of invasive avascular tumor growth, which takes into account cell division, death, and motility, proposed by Kolobov and collaborators in 2009. First, we examine the existence and uniqueness of the solution to this model. Second, we studied qualitatively and numerically the traveling wave solutions. Finally, we show some numerical simulations for the cell density and nutrient concentration. © 2013 NSP Natural Sciences Publishing Cor.

Effect of melatonin on tumor growth and angiogenesis in xenograft model of breast cancer

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

A statistical model of aggregate fragmentation

Processo FAPESP: 11/08171-3

Polynomials to model the growth of young bulls in performance tests

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Critical points on growth curves in autoregressive and mixed models

Adjusting autoregressive and mixed models to growth data fits discontinuous functions, which makes it difficult to determine critical points. In this study we propose a new approach to determine the critical stability point of cattle growth using a first-order autoregressive model and a mixed model with random asymptote, using the deterministic portion of the models. Three functions were compared: logistic, Gompertz, and Richards. The Richards autoregressive model yielded the best fit, but the critical growth values were adjusted very early, and for this purpose the Gompertz model was more appropriate.

Bacterial cellulose-hydroxyapatite composites with osteogenic growth peptide (OGP) or pentapeptide OGP on bone regeneration in critical-size calvarial defect model

This study aimed to evaluate the potential of bacterial cellulose-hydroxyapatite (BC-HA) composites associated with osteogenic growth peptide (OGP) or pentapeptide OGP(10–14) in bone regeneration in critical-size calvarial defects in mice. In this study, the BC-HA, BC-HA-OGP, and BC-HA-OGP(10–14) membranes were analyzed at 3, 7, 15, 30, 60, and 90 days. In each period, the specimens were evaluated by micro-computed tomography (µCT), descriptive histology, gene expression of bone biomarkers by qPCR and VEGFR-2 (vascular endothelial growth factor) quantification by ELISA. Three days post-operative, Runx2, Tnfrsf11b and Bglap bone biomarkers were upregulated mainly by BC-HA OGP and BC-HA OGP(10–14) membranes, suggesting an acceleration of the osteoblast differentiation/activity with the use of these biomaterials. At 60 and 90 days, a high percentage of bone formation was observed by µCT for BC-HA and BC-HA OGP(10–14) membranes. High expression of some bone biomarkers, such as Alpl, Spp1, and Tnfrsf11b, was also observed for the same membranes on days 60 and 90. In conclusion, the BC-HA membrane promoted a better bone formation in critical-size mice calvarial defects. Nevertheless, incorporation of the peptides at the concentration of 10−9 mol L−1 did not improve bone regeneration potential in the long-term.

A NEO-KALECKIAN MODEL OF PROFIT SHARING, CAPACITY UTILIZATION AND ECONOMIC GROWTH

This paper sets forth a Neo-Kaleckian model of capacity utilization and growth with distribution featuring a profit-sharing arrangement. While a given proportion of firms compensate workers with only a base wage, the remaining proportion do so with a base wage and a share of profits. Consistent with the empirical evidence, workers hired by profit-sharing firms have a higher productivity than their counterparts in base-wage firms. While a higher profit-sharing coefficient raises capacity utilization and growth irrespective of the distribution of compensation strategies across firms, a higher frequency of profit-sharing firms does likewise only if the profit-sharing coefficient is sufficiently high.

Predicting Growth of Panicum maximum: An Adaptation of the CROPGRO-Perennial Forage Model

Warm-season grasses are economically important for cattle production in tropical regions and tools to aid in management and research on these forages would be highly beneficial both in research and the industry. This research was conducted to adapt the CROPGRO-Perennial Forage model to simulate growth of the tropical species guineagrass (Panicum maximum Jacq. cv. 'Tanzania') and to describe model adaptation for this species. To develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation, and partitioning during a 17-mo experiment with Tanzania guineagrass in Piracicaba, SP, Brazil. Compared with starting parameters for palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. 'Xaraes'], dormancy effects of the perennial forage model had to be minimized, partitioning to storage tissue or root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield was 6576 kg ha(-1), averaged across 11 regrowth cycles of 35 (summer) or 63 d (winter), with a RMSE of 494 kg ha(-1) (Willmott's index of agreement d = 0.985, simulated/observed ratio = 1.014). The model also gave good predictions against an independent data set, with similar RMSE, ratio, and d. The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of guineagrass and can be used to simulate growth.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Physical model of PD behavior and relevant damage growth from micro-cavities in polyethylene-based material under AC voltage

In the framework of developing defect-based life models, in which breakdown is explicitly associated with partial discharge (PD)-induced damage growth from a defect, ageing tests and PD measurements were carried out in the lab on polyethylene (PE) layered specimens containing artificial cavities. PD activity was monitored continuously during aging. A quasi-deterministic series of stages can be observed in the behavior of the main PD parameters (i.e. discharge repetition rate and amplitude). Phase-resolved PD patterns at various ageing stages were reproduced by numerical simulation which is based on a physical discharge model devoid of adaptive parameters. The evolution of the simulation parameters provides insight into the physical-chemical changes taking place at the dielectric/cavity interface during the aging process. PD activity shows similar time behavior under constant cavity gas volume and constant cavity gas pressure conditions, suggesting that the variation of PD parameters may not be attributed to the variation of the gas pressure. Brownish PD byproducts, consisting of oxygen containing moieties, and degradation pits were found at the dielectric/cavity interface. It is speculated that the change of PD activity is related to the composition of the cavity gas, as well as to the properties of dielectric/cavity interface.