Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

An estimate of biometric parameters in eucalyptus clone plantations in Southern Bahia: an application of the airborne laser scanning (ALS) technology

The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.

PROPOSAL OF A PERFORMANCE MEASURING SYSTEM APPLIED TO AGRICULTURAL MECHANIZATION

The leaders` organizations of several different sectors have as characteristic to measure their own performance in a systematic way. However, this concept is still unusual in agricultural enterprises, including the mechanization sector. Mechanization has an important role on the production costs and to know its performance is a key factor for the agricultural enterprise success. This work was generated by the importance that measurement of performance has for the management and the mechanization impact on the production costs. Its aim is to propose an integrated performance measurement system to give support to agricultural management. The methodology was divided in two steps: adjustment of a conceptual model based on Balanced Score Card - BSC; application of the model in a study case at sugar cane mill. The adjustment and the application of the conceptual model allowed to obtain the performance index in a systematic way, that are associated to: costs and deadline ( traditionally used); control and improvement on the quality of operations and support process; environmental preservation; safety; health; employees satisfaction; development of information systems. The adjusted model helped the development of the performance measurement system for the mechanized management systems and the index allows an integrated view of the enterprise, related to its strategic objectives.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Canonical discriminant analysis applied to broiler chicken performance

The mechanisms involved in the control of growth in chickens are too complex to be explained only under univariate analysis because all related traits are biologically correlated. Therefore, we evaluated broiler chicken performance under a multivariate approach, using the canonical discriminant analysis. A total of 1920 chicks from eight treatments, defined as the combination of four broiler chicken strains (Arbor Acres, AgRoss 308, Cobb 500 and RX) from both sexes, were housed in 48 pens. Average feed intake, average live weight, feed conversion and carcass, breast and leg weights were obtained for days 1 to 42. Canonical discriminant analysis was implemented by SAS((R)) CANDISC procedure and differences between treatments were obtained by the F-test (P < 0.05) over the squared Mahalanobis` distances. Multivariate performance from all treatments could be easily visualised because one graph was obtained from two first canonical variables, which explained 96.49% of total variation, using a SAS((R)) CONELIP macro. A clear distinction between sexes was found, where males were better than females. Also between strains, Arbor Acres, AgRoss 308 and Cobb 500 (commercial) were better than RX (experimental), Evaluation of broiler chicken performance was facilitated by the fact that the six original traits were reduced to only two canonical variables. Average live weight and carcass weight (first canonical variable) were the most important traits to discriminate treatments. The contrast between average feed intake and average live weight plus feed conversion (second canonical variable) were used to classify them. We suggest analysing performance data sets using canonical discriminant analysis.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

X ray densitometry applied to technological evaluation of MDF panels of eucalyptus

MDF panels from eucalyptus wood fibers were manufactured in laboratory and industrial production and had their apparent density profile determined by X-ray densitometry. The MDF panels apparent density parameters (maximum density of the superior and inferior faces; medium and minimum density) were determined and compared. The results indicated that the density values of the MDF panels made in the laboratory and in industrial line did not show significant statistical differences, indicating the similarities in the pressing phase of the fibers of both kinds. However, for MDF panels of laboratory and production line, the values of maximum, mean and minimum densities showed statistically significant correlations. The determination of the density profile for MDF panels by X-ray densitometry is important for the evaluation of pressing phase and other variables of the industrial process of production, as well for the determination of the technological properties.

THE MONTHLY RAINFALL IN THE RIO DE JANEIRO STATE, BRAZIL: SEASONALITY AND TREND

The objective of this work was to carry a descriptive analysis in the monthly precipitation of rainfall stations from Rio de Janeiro State, Brazil, using data of position and dispersion and graphical analyses, and to verify the presence of seasonality and trend in these data, with a study about the application of models of time series. The descriptive statistics was to characterize the general behavior of the series in three stations selected which present consistent historical series. The methodology of analysis of variance in randomized blocks and the determination of models of multiple linear regression, considering years and months as predictors variables, disclosed the presence of seasonality, what allowed to infer on the occurrence of repetitive natural phenomena throughout the time and absence of trend in the data. It was applied the methodology of multiple linear regression to removal the seasonality of these time series. The original data had been deducted from the estimates made by the adjusted model and the analysis of variance in randomized blocks for the residues of regression was preceded again. With the results obtained it was possible to conclude that the monthly rainfall present seasonality and they don`t present trend, the analysis of multiple regression was efficient in the removal of the seasonality, and the rainfall can be studied by means of time series.

Bio-Dis and the Paddle Dissolution Apparatuses Applied to the Release Characterization of Ketoprofen from Hypromellose Matrices

The purposes of this work were: (1) to comparatively evaluate the effects of hypromellose viscosity grade and content on ketoprofen release from matrix tablets, using Bio-Dis and the paddle apparatuses, (2) to investigate the influence of the pH of the dissolution medium on drug release. Furthermore, since direct compression had not shown to be appropriate to obtain the matrices under study, it was also an objective (3) to evaluate the impact of granulation on drug release process. Six formulations of ketoprofen matrix tablets were obtained by compression, with or without previous granulation, varying the content and viscosity grade of hypromellose. Dissolution tests were carried out at a fixed pH, in each experiment, with the paddle method (pH 4.5, 6.0, 6.8, or 7.2), while a pH gradient was used in Bio-Dis (pH 1.2 to 7.2). The higher the hypromellose viscosity grade and content were, the lower the amount of ketoprofen released was in both apparatuses, the content effect being more expressive. Drug dissolution enhanced with the increase of the pH of the medium due to its pH-dependent solubility. Granulation caused an increase in drug dissolution and modified the mechanism of the release process.

Phase diagrams of a CTAB/organic solvent/buffer system applied to extraction of enzymes by reverse micelles

A partial pseudo-ternary phase diagram has been studied for the cethyltrimethylammonium bromide/isooctane:hexanol:butanol/potassium phosphate buffer system, where the two-phase diagram consisting of the reverse micelle phase (L-2) in equilibrium with the solvent is indicated. Based on these diagrams two-phase systems of reverse micelles were prepared with different compositions of the compounds and used for extraction and recovery of two enzymes, and the percentage of enzyme recovery yield monitored. The enzymes glucose-6-phosphate dehydrogenase (G6PD) and xylose redutase (XR) obtained from Candida guilliermondii yeast were used in the extraction procedures. The recovery yield data indicate that micelles having different composition give selective extraction of enzymes. The method can thus be used to optimize enzyme extraction processes. (c) 2007 Elsevier B.V. All rights reserved.

Characterization of Brazilian lager and brown ale beers based on color, phenolic compounds, and antioxidant activity using chemometrics

BACKGROUND: Epidemiological studies have shown that beer has positive effects on inhibiting atherosclerosis, decreasing the content of serum low-density lipoprotein cholesterol and triglycerides, by acting as in vivo free radical scavenger. In this research, the antioxidant activity of commercial Brazilian beers (n = 29) was determined by the oxygen radical absorbance capacity (ORAC) and 1,1 -diphenyl-2-picrylhydrazyl (DPPH(center dot)) assays and results were analyzed by chemometrics. RESULTS: The brown ale samples (n = 11) presented higher (P < 0.05) flavonoids (124.01 mg L(-1)), total phenolics (362.22 mg L(-1)), non-flavonoid phenolics (238.21 mg L(-1)), lightness (69.48), redness (35.75), yellowness (55.71), color intensity (66.86), hue angle (59.14), color saturation (0.9620), DPPH(center dot) values (30.96% inhibition), and ORAC values (3,659.36 mu mol Trolox equivalents L(-1)), compared to lager samples (n = 18). Brown ale beers presented higher antioxidant properties (P < 0.05) measured by ORAC (1.93 times higher) and DPPH (1.65 times higher) compared to lager beer. ORAC values correlated well with the content of flavonoids (r = 0.47; P = 0.01), total phenolic compounds (r = 0.44; P < 0.01) and DPPH (r = 0.67; P < 0.01). DPPH values also correlated well to the content of flavonoids (r = 0.69; P < 0.01), total phenolic compounds (r = 0.60; P < 0.01), and non-flavonoid compounds (r = 0.46; P = 0.01). CONCLUSION: The results suggest that brown ale beers, and less significantly lager beers, could be sources of bioactive compounds with suitable free radical scavenging properties. (C) 2010 Society of Chemical Industry

Comparative study of laser and LED systems of low intensity applied to tendon healing

The aim of this study was to compare the effects of Low-intensity Laser Therapy (LILT) and Light Emitting Diode Therapy (LEDT) of low intensity on the treatment of lesioned Achilles tendon of rats. The experimental model consisted of a partial mechanical lesion on the right Achilles tendon deep portion of 90 rats. One hour after the lesion, the injured animals received applications of laser/LED (685, 830/630, 880 nm), and the same procedure was repeated at 24-h intervals, for 10 days. The healing process and deposition of collagen were evaluated based on a polarization microscopy analysis of the alignment and organization of collagen bundles, through the birefringence (optical retardation-OR). The results showed a real efficiency of treatments based on LEDT and confirmed that LILT seems to be effective on healing process. Although absence of coherence of LED light, tendon healing treatment with this feature was satisfactory and can certainly replace treatments based on laser light applications. Applications of infrared laser at 830 nm and LED 880 nm were more efficient when the aim is a good organization, aggregation, and alignment of the collagen bundles on tendon healing. However, more research is needed for a safety and more efficient determination of a protocol with LED.

The collision branching process

We consider a branching model, which we call the collision branching process (CBP), that accounts for the effect of collisions, or interactions, between particles or individuals. We establish that there is a unique CBP, and derive necessary and sufficient conditions for it to be nonexplosive. We review results on extinction probabilities, and obtain explicit expressions for the probability of explosion and the expected hitting times. The upwardly skip-free case is studied in some detail.

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments.