Expressed sequence tags from Atta laevigata and identification of candidate genes for the control of pest leaf-cutting ants.

Leafcutters are the highest evolved within Neotropical ants in the tribe Attini and model systems for studying caste formation, labor division and symbiosis with microorganisms. Some species of leafcutters are agricultural pests controlled by chemicals which affect other animals and accumulate in the environment. Aiming to provide genetic basis for the study of leafcutters and for the development of more specific and environmentally friendly methods for the control of pest leafcutters, we generated expressed sequence tag data from Atta laevigata, one of the pest ants with broad geographic distribution in South America. Results: The analysis of the expressed sequence tags allowed us to characterize 2,006 unique sequences in Atta laevigata. Sixteen of these genes had a high number of transcripts and are likely positively selected for high level of gene expression, being responsible for three basic biological functions: energy conservation through redox reactions in mitochondria; cytoskeleton and muscle structuring; regulation of gene expression and metabolism. Based on leafcutters lifestyle and reports of genes involved in key processes of other social insects, we identified 146 sequences potential targets for controlling pest leafcutters. The targets are responsible for antixenobiosis, development and longevity, immunity, resistance to pathogens, pheromone function, cell signaling, behavior, polysaccharide metabolism and arginine kynase activity. Conclusion: The generation and analysis of expressed sequence tags from Atta laevigata have provided important genetic basis for future studies on the biology of leaf-cutting ants and may contribute to the development of a more specific and environmentally friendly method for the control of agricultural pest leafcutters.

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.

The integrated lot sizing and cutting stock problem in a furniture factory

This work studies the integrated lot sizing and cutting stock problem, where the goal is to capture the dependency that exists between two important decisions in the production process, in order to economize raw materials and also reduce production and inventory costs. The integrated lot sizing and cutting stock problem is studied in a small furniture factory that produces wardrobes, dressing tables and cupboards and the lot sizing and cutting stock decisions are taken by the production manager. A column-generation technique is used to solve a linear relaxation of the proposed model. The computational results, using real data from the factory, show that it is possible to reduce total inventory and raw material costs when integrated planning is used. © 2013 IFAC.

The one-dimensional cutting stock problem with usable leftovers - A survey

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

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

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

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

Random regression models using different functions to model milk flow in dairy cows

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

Integrated cutting machine programming and lot sizing in furniture industry

In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.

Shared Escovopsis parasites between leaf-cutting and non-leaf-cutting ants in the higher attine fungus-growing ant symbiosis

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

Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

Effects of tributyltin exposure in hermit crabs: Clibanarius vittatus as a model

Tributyltin (TBT) contamination affects the reproductive system of many species of invertebrates worldwide. The present study was designed to evaluate the effects of exposure to TBT pollution on the reproduction of the hermit crab Clibanarius vittatus. An orthogonal experiment was designed with two treatments: contamination (with or without TBT in the food) and crab sex (males and females). The animals were reared in the laboratory for nine months, and macroscopic and histological analyses of reproductive organs were carried out after the end of the experiment. Tributyltin was recorded in exposed crabs, but no morphological alterations were detected in the gonads of males, regardless of whether they were exposed to TBT. In contrast, females exposed to TBT displayed disorganization and atrophy of their ovaries, thus directly affecting reproduction in this hermit crab species. This effect observed in female hermit crabs may harm populations located in harbor regions, where TBT concentration is high, even after the worldwide TBT ban.

Considerations for Assessing Maximum Critical Temperatures in Small Ectothermic Animals: Insights from Leaf-Cutting Ants

The thermal limits of individual animals were originally proposed as a link between animal physiology and thermal ecology. Although this link is valid in theory, the evaluation of physiological tolerances involves some problems that are the focus of this study. One rationale was that heating rates shall influence upper critical limits, so that ecological thermal limits need to consider experimental heating rates. In addition, if thermal limits are not surpassed in experiments, subsequent tests of the same individual should yield similar results or produce evidence of hardening. Finally, several non-controlled variables such as time under experimental conditions and procedures may affect results. To analyze these issues we conducted an integrative study of upper critical temperatures in a single species, the ant Atta sexdens rubropiosa, an animal model providing large numbers of individuals of diverse sizes but similar genetic makeup. Our specific aims were to test the 1) influence of heating rates in the experimental evaluation of upper critical temperature, 2) assumptions of absence of physical damage and reproducibility, and 3) sources of variance often overlooked in the thermal-limits literature; and 4) to introduce some experimental approaches that may help researchers to separate physiological and methodological issues. The upper thermal limits were influenced by both heating rates and body mass. In the latter case, the effect was physiological rather than methodological. The critical temperature decreased during subsequent tests performed on the same individual ants, even one week after the initial test. Accordingly, upper thermal limits may have been overestimated by our (and typical) protocols. Heating rates, body mass, procedures independent of temperature and other variables may affect the estimation of upper critical temperatures. Therefore, based on our data, we offer suggestions to enhance the quality of measurements, and offer recommendations to authors aiming to compile and analyze databases from the literature.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

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.

The General Curvilinear Environmental Model (GCEM)

[EN] The General Curvilinear Environmental Model is a high-resolution system composed of the General Curvilinear Coastal Ocean Model (GCCOM) and the General Curvilinear Atmospheric Model (GCAM). Both modules are capable of reading a general curvilinear grid, orthogonal as well as non-orthogonal in all three directions. These two modules are weakly coupled using the distributed coupling toolkit (DCT). The model can also be nested within larger models and users are able to interact with the model and run it using a web based computational environment.