Conceptual Design of Monocolumn Production and Storage With Dry Tree Capability

A new concept and a preliminary study for a monocolumn floating unit are introduced, aimed at exploring and producing oil in ultradeep waters. This platform, which combines two relevant features-great oil storage capacity and dry tree production capability-comprises two bodies with relatively independent heave motions between them. A parametric model is used to define the main design characteristics of the floating units. A set of design alternatives is generated using this procedure. These solutions are evaluated in terms of stability requirements and dynamic response. A mathematical model is developed to estimate the first order heave and pitch motions of the platform. Experimental tests are carried out in order to calibrate this model. The response of each body alone is estimated numerically using the WAMIT (R) code. This paper also includes a preliminary study on the platform mooring system and appendages. The study of the heave plates presents the gain, in terms of decreasing the motions, achieved by the introduction of the appropriate appendages to the platform. [DOI: 10.1115/1.4001429]

Wine industry residues extracts as natural antioxidants in raw and cooked chicken meat during frozen storage

The effect of Isabel (IGE) and Niagara (NGE) grape seed and peel extracts on lipid oxidation, instrumental colour, pH and sensory properties of raw and cooked processed chicken meat stored at -18 degrees C for nine months was evaluated. The pH of raw and cooked samples was not affected by the addition of grape extracts. IGE and NGE were effective in inhibiting the lipid oxidation of raw and cooked chicken meat, with results comparable to synthetic antioxidants. The extracts caused alterations in colour, as evidenced by the instrumental (darkening and lower intensity of red and yellow colour) and sensory results of cooked samples. In the sensory evaluation of odour and flavour, IGE produced satisfactory results, which did not differ from synthetic antioxidants. These findings suggest that the ICE and NGE are effective in retarding lipid oxidation of raw and cooked chicken meat during frozen storage. (c) 2011 Elsevier Ltd. All rights reserved.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Storage as a tool to improve wood fuel quality

This work analysed the influence of storage in the quality of forest biomass for energy generation in the region of Lages, Brazil. Logs of Pinus taeda L. and Eucalyptus dunnii Maiden were harvested and piled during the four different seasons: spring, summer, fall and winter. The analyses were performed immediately after harvesting (without being stored), after two, four and six months of storage. The evaluated properties were: moisture content, gross and net calorific value, ash content and solubility in cold water, hot water and sodium hydroxide. The species composition, storage span, harvesting season and storage season influenced the forest biomass characteristics. In general, eucalyptus presented better results than pine, losing moisture faster, having less alteration in the chemical composition and producing greater energetic gain over storage time. For both species, the ideal storage time was four months. Furthermore, spring and summer were the best harvesting seasons. Thus, if the forest biomass is harvested at the end of winter or beginning of spring with subsequent storage during the summer, this biomass will have the best performance for energy production. (C) 2011 Elsevier Ltd. All rights reserved.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

Distribution and storage characterization of soil solution for drip irrigation

The increased use of marginal quality water with drip irrigation requires sound fertigation practices that reconcile environmental concerns with viable crop production objectives. We conducted experiments to characterize dynamics and patterns of soil solution within wet bulb formed by drip irrigation. Time-domain reflectometry probes were used to monitor the distribution of potassium nitrate (KNO(3)) and water distribution from drippers discharging at constant flow rates of 2, 4 and 8 L h(-1) in soil-filled containers. Considering results from different profiles, we observed greater solute storage near the dripper decreasing gradually towards the wetting front. About half of the applied KNO(3) solution (48%) was stored in the first layer (0-0.10 m) for all experiments, 29% was stored in the next layer (0.10-0.20 m). Comparing different dripper flow rates, we observed higher solution storage for 4 L h(-1), with 45, 53 and 47% of applied KNO(3) solution accumulating in the first layer (0-0.10 m) for dripper flow rates of 2, 4 and 8 L h(-1), respectively. The results suggest that based on the volume and frequency used in this experiment, it would be advantageous to apply small amounts of solution at more frequent intervals to reduce deep percolation losses of applied water and solutes.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Nutritional Quality of Sorghum Seeds: Storage Proteins and Amino Acids

One sorghum commercial genotype (MASSA 03) and nine ICRISAT high-lysine genotypes from India were analyzed for storage protein content, distribution profile, and soluble amino acid concentrations. Storage proteins fraction were extracted and separated by SDS-PAGE. Soluble amino acids contents were determined by HPLC. Variations in intensity and appearance and disappearance of protein bands were observed among the sorghum genotypes suggesting genetic variability. Amino acid profile also indicated large variations in the amino acid concentrations. The high lysine and threonine soluble concentrations observed in the seeds of the sorghum genotypes encouraged the use of these genotypes as potential food source due to the better balanced amino acids profile.

Influence of egg pre-storage heating period and storage length on incubation results

This experiment aimed at evaluating the influence of different heating times of settable eggs of Cobb 500 (R) broiler breeders before submitting them to different storage periods on egg weight loss, embryo mortality, and hatchability. A total number of 1,980 eggs were distributed in a completely randomized experimental design with a 3 x 3 factorial arrangement, comprising nine treatments with 22 replicates of 10 eggs each. The following factors were analyzed: pre-storage heating periods (0, 6, 12 hours at 36.92 degrees C) and storage periods (4, 9, 14 days at 12.06 degrees C). After storage, eggs were incubated under usual conditions, and were transferred to the hatcher at 442 hours of incubation. Eggs were weighed before heating, incubation, and transference to determine weight loss. Partial hatchability was determined at 480 hours, and total hatchability at 498 hours of incubation. Embryo mortality was determined in non-hatched eggs. It was concluded that heating eggs for six hour before storage improves incubation results as it decreases incubation length and late embryo mortality, therefore its use can be indicated in commercial operations. Storing eggs for 14 days and pre-heating for 14 days and pre-heating for 12 hours severely impair incubation results, and therefore are not recommended.