A Generalized Quasi-Likelihood Estimator for Nonstationary Stochastic Processes−Asymptotic Properties and Examples

2010 Mathematics Subject Classification: 62F12, 62M05, 62M09, 62M10, 60G42.

Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow’s Milk

This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new), and respiratory rate predictor RRP) with three main components of cow’s milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p-value < 0.001 and R2 (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.

Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features

ACM Computing Classification System (1998): I.4.9, I.4.10.

Avaliação de Correlações e Equações de Estado para Determinação de Fatores de Compressibilidade de Gás Natural

O fator de compressibilidade (Z) de gás natural é utilizado em vários cálculos na engenharia de petróleo (avaliação de formações, perda de carga em tubulações, gradiente de pressão em poços de gás, cálculos de balanço de massa, medição de gás, compressão e processamento de gás). As fontes mais comuns de valores de Z são medições experimentais, caras e demoradas. Essa propriedade também é estimada por correlações empíricas, modelos baseados no princípio dos estados correspondentes ou equações de estado (EOS). Foram avaliadas as capacidades das EOS de Soave-Redlich-Kwong (SRK), Peng-Robinson (PR), Patel-Teja (PT), Patel-Teja-Valderrama (PTV), Schmidt-Wenzel (SW), Lawal-Lake-Silberberg (LLS) e AGA-8 para previsão desta propriedade em aproximadamente 2200 pontos de dados experimentais. Estes pontos foram divididos em quatro grupos: Grupo 1 (Presença de frações C7+, Grupo 2 (temperaturas inferiores a 258,15 K), Grupo 3 (pressões superiores a 10000 kPa) e Grupo 4 (pressões inferiores a 10000 kPa). Os cálculos utilizando as equações de estado sob diferentes esquemas de previsão de coeficientes binários de interação foram cuidadosamente investigados. Os resultados sugerem que a EOS AGA-8 apresenta os menores erros para pressões de até 70000 kPa. Entretanto, observou-se uma tendência de aumento nos desvios médios absolutos em função das concentrações de CO2 e H2S. As EOS PTV e a EOS SW são capazes de predizer o fator de compressibilidade (Z) com desvios médios absolutos entre os valores calculados e experimentais com precisão satisfatória para a maioria das aplicações, para uma variada faixa de temperatura e pressão. Este estudo também apresenta uma avaliação de 224 métodos de cálculo de Z onde foram utilizadas 8 correlações combinadas com 4 regras de mistura para estimativa de temperaturas e pressões pseudorreduzidas das amostras, junto com 7 métodos de caracterização das propriedades críticas da fração C7+, quando presente na composição do gás. Em função dos resultados são sugeridas, para diferentes tipos de sistemas, as melhores combinações de correlações com regras de mistura capazes de predizer fatores de compressibilidade (Z) com os menores erros absolutos médios relativos

Low-pressure solubilities and thermodynamics of solvation of eight gases in 1-butyl-3-methylimidazolium hexafluorophosphate

Experimental values for the solubility of carbon dioxide, ethane, methane, oxygen, nitrogen, hydrogen, argon and carbon monoxide in 1-butyl-3-methylimidazolium hexafluorophosphate, [bmim][PF6] - a room temperature ionic liquid - are reported as a function of temperature between 283 and 343 K and at pressures close to atmospheric. Carbon dioxide is the most soluble and hydrogen is the least soluble of the gases studied with mole fraction solubilities of the order of 10-2 and 10-4, respectively. All the mole fraction solubilities decrease with temperature except for hydrogen for which a maximum is observed at temperatures close to 310 K. From the variation of solubility, expressed as Henry's law constants, with temperature, the partial molar thermodynamic functions of solvation such as the standard Gibbs energy, the enthalpy, and the entropy are calculated. The precision of the experimental data, considered as the average absolute deviation of the Henry's law constants from appropriate smoothing equations, is better than ±1%. © 2005 Elsevier B.V. All rights reserved.

Comparison of selective genotyping strategies for prediction of breeding values in a population undergoing selection

Genomewide marker information can improve the reliability of breeding value predictions for young selection candidates in genomic selection. However, the cost of genotyping limits its use to elite animals, and how such selective genotyping affects predictive ability of genomic selection models is an open question. We performed a simulation study to evaluate the quality of breeding value predictions for selection candidates based on different selective genotyping strategies in a population undergoing selection. The genome consisted of 10 chromosomes of 100 cM each. After 5,000 generations of random mating with a population size of 100 (50 males and 50 females), generation G(0) (reference population) was produced via a full factorial mating between the 50 males and 50 females from generation 5,000. Different levels of selection intensities (animals with the largest yield deviation value) in G(0) or random sampling (no selection) were used to produce offspring of G(0) generation (G(1)). Five genotyping strategies were used to choose 500 animals in G(0) to be genotyped: 1) Random: randomly selected animals, 2) Top: animals with largest yield deviation values, 3) Bottom: animals with lowest yield deviations values, 4) Extreme: animals with the 250 largest and the 250 lowest yield deviations values, and 5) Less Related: less genetically related animals. The number of individuals in G(0) and G(1) was fixed at 2,500 each, and different levels of heritability were considered (0.10, 0.25, and 0.50). Additionally, all 5 selective genotyping strategies (Random, Top, Bottom, Extreme, and Less Related) were applied to an indicator trait in generation G(0), and the results were evaluated for the target trait in generation G(1), with the genetic correlation between the 2 traits set to 0.50. The 5 genotyping strategies applied to individuals in G(0) (reference population) were compared in terms of their ability to predict the genetic values of the animals in G(1) (selection candidates). Lower correlations between genomic-based estimates of breeding values (GEBV) and true breeding values (TBV) were obtained when using the Bottom strategy. For Random, Extreme, and Less Related strategies, the correlation between GEBV and TBV became slightly larger as selection intensity decreased and was largest when no selection occurred. These 3 strategies were better than the Top approach. In addition, the Extreme, Random, and Less Related strategies had smaller predictive mean squared errors (PMSE) followed by the Top and Bottom methods. Overall, the Extreme genotyping strategy led to the best predictive ability of breeding values, indicating that animals with extreme yield deviations values in a reference population are the most informative when training genomic selection models.

Comparação entre os estimadores de mínimos quadrados ordinários e mínimos desvios absolutos em modelos de regressão linear simples -: uma aplicação na energia na agricultura

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Associação e seleção genômica para características relacionadas à eficiência reprodutiva de fêmeas da raça Nelore

Pós-graduação em Zootecnia - FCAV

Experimental and theoretical studies of the redox potentials of cyclic nitroxides

The redox potentials of 25 cyclic nitroxides from four different structural classes (pyrrolidine, piperidine, isoindoline, and azaphenalene) were determined experimentally by cyclic voltammetry in acetonitrile, and also via high-level ab initio molecular orbital calculations. It is shown that the potentials are influenced by the type of ring system, ring substituents and/or groups surrounding the radical moiety. For the pyrrolidine, piperidine, and isoindolines there is excellent agreement (mean absolute deviation of 0.05 V) between the calculated and experimental oxidation potentials; for the azaphenalenes, however, there is an extraordinary discrepancy (mean absolute deviation of 0.60 V), implying that their one-electron oxidation might involve additional processes not considered in the theoretical calculations. This recently developed azaphenalene class of nitroxide represents a new variant of a nitroxide ring fused to an aromatic system and details of the synthesis of five derivatives involving differing aryl substitution are also presented.

Computational design of cyclic nitroxides as efficient redox mediators for dye-sensitized solar cells

Cyclic nitroxide radicals represent promising alternatives to the iodine-based redox mediator commonly used in dye-sensitized solar cells (DSSCs). To date DSSCs with nitroxide-based redox mediators have achieved energy conversion efficiencies of just over 5 % but efficiencies of over 15 % might be achievable, given an appropriate mediator. The efficacy of the mediator depends upon two main factors: it must reversibly undergo one-electron oxidation and it must possess an oxidation potential in a range of 0.600-0.850 V (vs. a standard hydrogen electrode (SHE) in acetonitrile at 25 °C). Herein, we have examined the effect that structural modifications have on the value of the oxidation potential of cyclic nitroxides as well as the reversibility of the oxidation process. These included alterations to the N-containing skeleton (pyrrolidine, piperidine, isoindoline, azaphenalene, etc.), as well as the introduction of different substituents (alkyl-, methoxy-, amino-, carboxy-, etc.) to the ring. Standard oxidation potentials were calculated using high-level ab initio methodology that was demonstrated to be very accurate (with a mean absolute deviation from experimental values of only 16 mV). An optimal value of 1.45 for the electrostatic scaling factor for UAKS radii in acetonitrile solution was obtained. Established trends in the values of oxidation potentials were used to guide molecular design of stable nitroxides with desired E° ox and a number of compounds were suggested for potential use as enhanced redox mediators in DSSCs. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovery and replication of gene influences on brain structure using LASSO regression

We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4, and CDH13. The top genes we identified with this method also displayed significant and widespread post hoc effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2.We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8±2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

A robust optimization approach for index tracking problem

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as possible to a target index without purchasing all index components. The main purpose is to minimize the tracking error between the returns of the selected portfolio and a benchmark. In this paper, quadratic as well as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input data using a tractable robust framework that controls the level of conservatism while maintaining linearity. The linearity of the proposed robust optimization models allows a simple implementation of an ordinary optimization software package to find the optimal robust solution. The proposed model of this paper employs Morgan Stanley Capital International Index as the target index and the results are reported for six national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of the proposed models is evaluated using several financial criteria e.g. information ratio, market ratio, Sharpe ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of tracking error while raising values of portfolio performance measures.

Correlation of thermodynamic properties of chloromethanes

A correlation for entropy and enthalpy based on the two-parameter law of corresponding states and the reference substance concept has been obtained. For 199 points tested, the over-all average absolute deviation and the maximum deviations in the calculated values of entropy with the available data are 0.74 and 7.20%. The corresponding deviations of enthalpy are 1.86 and 15.0%, respectively. A compressibility chart for chloromethanes has been made and shown to be superior to existing charts. For 102 points tested, the average absolute and maximum deviations in the compressibilities were 1.80 and 19.5%, respectively.

Fugacity coefficients. Enthalpy, and second virial coefficients of boron trifluoride

Fugacity coefficients and isothermal changes of enthalpy have been calculated and reported. The calculations cover a temperature range of 0° to 75°C. up to gas densities of 1.0 gram per cc. The generalized Benedict-Webb-Rubin constants evaluated from generalized PVT relations is found to predict the experimental data with an over-all absolute deviation of 3.1%. Second virial coefficients and potential energy parameters for Lennard-Jones (12-6) potential energy function are reported also.