A comparative analysis of Cobb-Douglas model with additive and multiplicative error

This paper dis cusses the fitting of a Cobb-Doug las response curve Yi = αXβi, with additive error, Yi = αXβi + e i, instead of the usual multiplicative error Yi = αXβi (1 + e i). The estimation of the parameters A and B is discussed. An example is given with use of both types of error.

Long-term habituation (LTH) in the crab Chasmagnathus: a model for behavioral and mechanistic studies of memory

A decade of studies on long-term habituation (LTH) in the crab Chasmagnathus is reviewed. Upon sudden presentation of a passing object overhead, the crab reacts with an escape response that habituates promptly and for at least five days. LTH proved to be an instance of associative memory and showed context, stimulus frequency and circadian phase specificity. A strong training protocol (STP) (³15 trials, intertrial interval (ITI) of 171 s) invariably yielded LTH, while a weak training protocol (WTP) (£10 trials, ITI = 171 s) invariably failed. STP was used with a presumably amnestic agent and WTP with a presumably hypermnestic agent. Remarkably, systemic administration of low doses was effective, which is likely to be due to the lack of an endothelial blood-brain barrier. LTH was blocked by inhibitors of protein and RNA synthesis, enhanced by protein kinase A (PKA) activators and reduced by PKA inhibitors, facilitated by angiotensin II and IV and disrupted by saralasin. The presence of angiotensins and related compounds in the crab brain was demonstrated. Diverse results suggest that LTH includes two components: an initial memory produced by spaced training and mainly expressed at an initial phase of testing, and a retraining memory produced by massed training and expressed at a later phase of testing (retraining). The initial memory would be associative, context specific and sensitive to cycloheximide, while the retraining memory would be nonassociative, context independent and insensitive to cycloheximide

Animal model for age- and sex-related genotoxicity of diethylstilbestrol

Environmental xenoestrogens pose a significant health risk for all living organisms. There is growing evidence concerning the different susceptibility to xenoestrogens of developing and adult organisms, but little is known about their genotoxicity in pre-pubertal mammals. In the present study, we developed an animal model to test the sex- and age-specific genotoxicity of the synthetic estrogen diethylstilbestrol (DES) on the reticulocytes of 3-week-old pre-pubertal and 12-week-old adult BALB/CJ mice using the in vivo micronucleus (MN) assay. DES was administered intraperitoneally at doses of 0.05, 0.5, and 5 µg/kg for 3 days and animals were sampled 48, 72 and 96 h, and 2 weeks after exposure. Five animals were analyzed for each dose, sex, and age group. After the DES dose of 0.05 µg/kg, pre-pubertal mice showed a significant increase in MN frequency (P < 0.001), while adults continued to show reference values (5.3 vs 1.0 MN/1000 reticulocytes). At doses of 0.5 and 5 µg/kg, MN frequency significantly increased in both age groups. In pre-pubertal male animals, MN frequency remained above reference values for 2 weeks after exposure. Our animal model for pre-pubertal genotoxicity assessment using the in vivo MN assay proved to be sensitive enough to distinguish age and sex differences in genome damage caused by DES. This synthetic estrogen was found to be more genotoxic in pre-pubertal mice, males in particular. Our results are relevant for future investigations and the preparation of legislation for drugs and environmentally emitted agents, which should incorporate specific age and gender susceptibility.

Comparison of the homeostasis model assessment and quantitative insulin sensitivity check index with data from forearm metabolic studies for the in vivo assessment of insulin sensitivity

The present study was designed to compare the homeostasis model assessment (HOMA) and quantitative insulin sensitivity check index (QUICKI) with data from forearm metabolic studies of healthy individuals and of subjects in various pathological states. Fifty-five healthy individuals and 112 patients in various pathological states, including type 2 diabetes mellitus, essential hypertension and others, were studied after an overnight fast and for 3 h after ingestion of 75 g of glucose, by HOMA, QUICKI and the forearm technique to estimate muscle uptake of glucose combined with indirect calorimetry (oxidative and non-oxidative glucose metabolism). The patients showed increased HOMA (1.88 ± 0.14 vs 1.13 ± 0.10 pmol/l x mmol/l) and insulin/glucose (I/G) index (1.058.9 ± 340.9 vs 518.6 ± 70.7 pmol/l x (mg/100 ml forearm)-1), and decreased QUICKI (0.36 ± 0.004 vs 0.39 ± 0.006 (µU/ml + mg/dl)-1) compared with the healthy individuals. Analysis of the data for the group as a whole (patients and healthy individuals) showed that the estimate of insulin resistance by HOMA was correlated with data obtained in the forearm metabolic studies (glucose uptake: r = -0.16, P = 0.04; non-oxidative glucose metabolism: r = -0.20. P = 0.01, and I/G index: r = 0.17, P = 0.03). The comparison of QUICKI with data of the forearm metabolic studies showed significant correlation between QUICKI and non-oxidative glucose metabolism (r = 0.17, P = 0.03) or I/G index (r = -0.37, P < 0.0001). The HOMA and QUICKI are good estimates of insulin sensitivity as data derived from forearm metabolic studies involving direct measurements of insulin action on muscle glucose metabolism.

Analysis of variance of primary data on plant growth analysis

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Growth and yield prediction using the modified Buckman model

A model to manage even-aged stands was developed using a modification of the Buckman model. Data from Eucalyptus urophylla and Eucalyptus cloeziana stands located in the Northern region of Minas Gerais State, Brazil were used in the formulation of the system. The proposed model generated precise and unbiased estimates in non-thinned stands.

Determination of total accumulated rainfall, global radiation, evapotranspiration and degree-days originated from the ECMWF model to sugar cane crop

The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.

Calibration of the century, apsim and ndicea models of decomposition and n mineralization of plant residues in the humid tropics

The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.

Simulation of soybean growth and yield under northeastern Amazon climatic conditions

The objective of this work was to parameterize, calibrate, and validate a new version of the soybean growth and yield model developed by Sinclair, under natural field conditions in northeastern Amazon. The meteorological data and the values of soybean growth and leaf area were obtained from an agrometeorological experiment carried out in Paragominas, PA, Brazil, from 2006 to 2009. The climatic conditions during the experiment were very distinct, with a slight reduction in rainfall in 2007, due to the El Niño phenomenon. There was a reduction in the leaf area index (LAI) and in biomass production during this year, which was reproduced by the model. The simulation of the LAI had root mean square error (RMSE) of 0.55 to 0.82 m² m-2, from 2006 to 2009. The simulation of soybean yield for independent data showed a RMSE of 198 kg ha-1, i.e., an overestimation of 3%. The model was calibrated and validated for Amazonian climatic conditions, and can contribute positively to the improvement of the simulations of the impacts of land use change in the Amazon region. The modified version of the Sinclair model is able to adequately simulate leaf area formation, total biomass, and soybean yield, under northeastern Amazon climatic conditions.

Simulating maize yield in sub‑tropical conditions of southern Brazil using Glam model

The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km²), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km²). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.