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.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

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.

Outcrossing rate in sweet passion fruit based on molecular markers

P>Yellow and sweet passion fruit are insect-pollinated species native to the tropics. Fruits are used commercially for human consumption worldwide. The yellow passion fruit is an outcrossing species with self-incompatible flowers. However, the reproductive system of the sweet passion fruit (Passiflora alata) has not been well elucidated. The objective of this work was to characterize aspects of the mating system in the sweet passion fruit using random amplified polymorphic DNA (RAPD) and microsatellite markers, particularly the rate of outcrossing in P. alata progenies. A multilocus outcrossing rate of t(m) = 0.994 was determined from RAPD and t(m) = 0.940 from microsatellites, supporting P. alata as an outcrossing species. The fixation indices of the maternal generation (F(m)) were -0.200 and 0.071 with RAPD and microsatellite loci, respectively, indicating the absence of inbreeding in the maternal generation. The paternity correlation (r(p)) varied from -0.008 with RAPD markers to 0.208 with microsatellite markers, suggesting a low probability of finding full sibs within the progenies. The results demonstrated that all progenies assessed in this study were derived from outcrossing.

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.

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.

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.

Air Entrainment Processes in a Full-Scale Rectangular Dropshaft at Large Flows

Rectangular dropshafts, commonly used in sewers and storm water systems, are characterised by significant flow aeration. New detailed air-water flow measurements were conducted in a near-full-scale dropshaft at large discharges. In the shaft pool and outflow channel, the results demonstrated the complexity of different competitive air entrainment mechanisms. Bubble size measurements showed a broad range of entrained bubble sizes. Analysis of streamwise distributions of bubbles suggested further some clustering process in the bubbly flow although, in the outflow channel, bubble chords were in average smaller than in the shaft pool. A robust hydrophone was tested to measure bubble acoustic spectra and to assess its field application potential. The acoustic results characterised accurately the order of magnitude of entrained bubble sizes, but the transformation from acoustic frequencies to bubble radii did not predict correctly the probability distribution functions of bubble sizes.

Expertise and the perception of kinematic and situational probability information

Two experiments were conducted on the nature of expert perception in the sport of squash. In the first experiment, ten expert and fifteen novice players attempted to predict the direction and force of squash strokes from either a film display (occluded at variable time periods before and after the opposing player had struck the ball) or a matched point-light display (containing only the basic kinematic features of the opponent's movement pattern). Experts outperformed the novices under both display conditions, and the same basic time windows that characterised expert and novice pick-up of information in the film task also persisted in the point-light task. This suggests that the experts' perceptual advantage is directly related to their superior pick-up of essential kinematic information. In the second experiment, the vision of six expert and six less skilled players was occluded by remotely triggered liquid-crystal spectacles at quasi-random intervals during simulated match play. Players were required to complete their current stroke even when the display was occluded and their prediction performance was assessed with respect to whether they moved to the correct half of the court to match the direction and depth of the opponent's stroke. Consistent with experiment 1, experts were found to be superior in their advance pick-up of both directional and depth information when the display was occluded during the opponent's hitting action. However, experts also remained better than chance, and clearly superior to less skilled players, in their prediction performance under conditions where occlusion occurred before any significant pre-contact preparatory movement by the opposing player was visible. This additional source of expert superiority is attributable to their superior attunement to the information contained in the situational probabilities and sequential dependences within their opponent's pattern of play.

On the construction of nearest neighbour balanced row-column designs

Nearest–neighbour balance is considered a desirable property for an experiment to possess in situations where experimental units are influenced by their neighbours. This paper introduces a measure of the degree of nearest–neighbour balance of a design. The measure is used in an algorithm which generates nearest–neighbour balanced designs and is readily modified to obtain designs with various types of nearest–neighbour balance. Nearest–neighbour balanced designs are produced for a wide class of parameter settings, and in particular for those settings for which such designs cannot be found by existing direct combinatorial methods. In addition, designs with unequal row and column sizes, and designs with border plots are constructed using the approach presented here.

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.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).