Scheduling in a two-machine flowshop for the minimization of the mean absolute deviation from a common due date

This paper addresses the minimization of the mean absolute deviation from a common due date in a two-machine flowshop scheduling problem. We present heuristics that use an algorithm, based on proposed properties, which obtains an optimal schedule fora given job sequence. A new set of benchmark problems is presented with the purpose of evaluating the heuristics. Computational experiments show that the developed heuristics outperform results found in the literature for problems up to 500 jobs. (C) 2007 Elsevier Ltd. All rights reserved.

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.

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

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

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.

Modelagem e simulação de um secador intermitente de fluxos contracorrentes para frutos do cafeeiro

Este trabalho foi realizado com o objetivo de desenvolver um modelo computacional para simular a secagem de frutos café em um secador intermitente de fluxos contracorrente, empregando a linguagem de simulação EXTEND™ e o Modelo de Thompson (THOMPSON; PEART; FOSTER, 1968). Para validação do modelo desenvolvido foram utilizados dados experimentais obtidos por Silva (1991), em que foram empregados três níveis de temperatura do ar de secagem de 60, 80 e 100 °C. O modelo desenvolvido foi validado, sendo constatados desvios absolutos de 1,8% b.u e 1,1 kg e erros relativos de 11% e 1,6% na previsão dos parâmetros teor de água final e consumo de lenha, respectivamente. O modelo validado foi empregado na condução de experimentos tipo comparação de cenários. O primeiro experimento refere a alterações do ciclo operacional em que foram alterados os tempos de movimentação e de parada do fluxo da massa de grãos. E o segundo refere à alteração da configuração do secador quanto às alturas das câmaras de secagem e descanso. O ciclo operacional com os tempos de movimentação de um minuto e de parada de dezesseis minutos, para a temperatura do ar de secagem de 100 °C, proporcionou o melhor desempenho, sendo constatado tempo secagem de 12,3 h, consumo de lenha de 109,5 kg, consumo específico de energia de 7660 kJ.kg-1 de água evaporada, e capacidade de secagem de 87,86 kg.h-1. Quanto à configuração do secador, o melhor desempenho ocorreu para altura da câmara de secagem de 2,3 m usando a temperatura do ar de secagem de 100 °C, em que foram simulados tempo de secagem de 12,0 h, consumo de lenha de 106,5 kg, consumo específico de energia, de 7433 kJ.kg-1 de água evaporada, e capacidade de secagem de 90 kg.h-1. Desse modo, na condução da secagem de frutos de café em um secador intermitente de fluxos contracorrentes é recomendado o ciclo operacional com tempos de movimentação de um minuto e o de parada de dezesseis minutos, e não empregar a câmara de descanso. Essa conclusão está fundamentada em índices de desempenho do secador. Ressalta-se que não foram simulados os impactos nos parâmetros de qualidade.

Biotransformation/separation routes to obtain pure enantiomers

The objective of the work presented in this thesis was the development of an innovative approach for the separation of enantiomers of secondary alcohols, combining the use of an ionic liquid (IL) - both as solvent for conducting enzymatic kinetic resolution and as acylating agent - with the use of carbon dioxide (CO2) as solvent for extraction. Menthol was selected for testing this reaction/separation approach due to the increasing demand for this substance, which is widely used in the pharmaceutical, cosmetics and food industries. With a view to using an ionic ester as acylating agent, whose conversion led to the release of ethanol, and due to the need to remove this alcohol so as to drive reaction equilibrium forward, a phase equilibrium study was conducted for the ehtanol/(±)-menthol/CO2 system, at pressures between 8 and 10 MPa and temperatures between 40 and 50 oC. It was found that CO2 is more selective towards ethanol, especially at the lowest pressure and highest temperature tested, leading to separation factors in the range 1.6-7.6. The pressure-temperature-composition data obtained were correlated with the Peng-Robinson equation of state and the Mathias-Klotz-Prausnitz mixing rule. The model fit the experimental results well, with an average absolute deviation (AAD) of 3.7 %. The resolution of racemic menthol was studied using two lipases, namely lipase from Candida rugosa (CRL) and immobilized lipase B from Candida antarctica (CALB), and two ionic acylating esters. No reaction was detected in either case. (R,S)-1-phenylethanol was used next, and it was found that with CRL low, nonselective, conversion of the alcohol took place, whereas CALB led to an enantiomeric excess (ee) of the substrate of 95%, at 30% conversion. Other acylating agents were tested for the resolution of (±)-menthol, namely vinyl esters and acid anhydrides, using several lipases and varying other parameters that affect conversion and enantioselectivity, such as substrate concentration, solvent and temperature. One such acylating agent was propionic anhydride. It was thus performed a phase equilibrium study on the propionic anhydride/CO2 system, at temperatures between 35 and 50 oC. This study revealed that, at 35 oC and pressures from 7 MPa, the system is monophasic for all compositions. The enzymatic catalysis studies carried out with propionic anhydride revealed that the extent of noncatalyzed reaction was high, with a negative effect on enantioselectivity. These studies showed also that it was possible to reduce considerably the impact of the noncatalyzed reaction relative to the reaction catalyzed by CRL by lowering temperature to 4 oC. Vinyl decanoate was shown to lead to the best results at conditions amenable to a process combining the use of supercritical CO2 as agent for post-reaction separation. The use of vinyl decanoate in a number of IL solvents, namely [bmim][PF6], [bmim][BF4], [hmim][PF6], [omim][PF6], and [bmim][Tf2N], led to an enantiomeric excess of product (eep) values of over 96%, at about 50% conversion, using CRL. In n-hexane and supercritical CO2, reaction progressed more slowly.(...)

Results of computer assisted navigation in Total Knee Arthroplasty (TKA): comparison with the conventional method

The aim of this retrospective study was to compare the clinical and radiographic results after TKA (PFC, DePuy), performed either by computer assisted navigation (CAS, Brainlab, Johnson&Johnson) or by conventional means. Material and methods: Between May and December 2006 we reviewed 36 conventional TKA performed between 2002 and 2003 (group A) and 37 navigated TKA performed between 2005 and 2006 (group B) by the same experienced surgeon. The mean age in group A was 74 years (range 62-90) and 73 (range 58-85) in group B with a similar age distribution. The preoperative mechanical axes in group A ranged from -13° varus to +13° valgus (mean absolute deviation 6.83°, SD 3.86), in group B from -13° to +16° (mean absolute deviation 5.35, SD 4.29). Patients with a previous tibial osteotomy or revision arthroplasty were excluded from the study. Examination was done by an experienced orthopedic resident independent of the surgeon. All patients had pre- and postoperative long standing radiographs. The IKSS and the WOMAC were utilized to determine the clinical outcome. Patient's degree of satisfaction was assessed on a visual analogous scale (VAS). Results: 32 of the 37 navigated TKAs (86,5%) showed a postoperative mechanical axis within the limits of 3 degrees of valgus or varus deviation compared to only 24 (66%) of the 36 standard TKAs. This difference was significant (p = 0.045). The mean absolute deviation from neutral axis was 3.00° (range -5° to +9°, SD: 1.75) in group A in comparison to 1.54° (range -5° to +4°, SD: 1.41) in group B with a highly significant difference (p = 0.000). Furthermore, both groups showed a significant postoperative improvement of their mean IKSS-values (group A: 89 preoperative to 169 postoperative, group B 88 to 176) without a significant difference between the two groups. Neither the WOMAC nor the patient's degree of satisfaction - as assessed by VAS - showed significant differences. Operation time was significantly higher in group B (mean 119.9 min.) than in group A (mean 99.6 min., p <0.000). Conclusion: Our study showed consistent significant improvement of postoperative frontal alignment in TKA by computer assisted navigation (CAS) compared to standard methods, even in the hands of a surgeon well experienced in standard TKA implantation. However, the follow-up time of this study was not long enough to judge differences in clinical outcome. Thus, the relevance of computer navigation for clinical outcome and survival of TKA remains to be proved in long term studies to justify the longer operation time. References 1 Stulberg SD. Clin Orth Rel Res. 2003;(416):177-84. 2 Chauhan SK. JBJS Br. 2004;86(3):372-7. 3 Bäthis H, et al. Orthopäde. 2006;35(10):1056-65.

Accurate calculations of intermolecular interaction energies using explicitly correlated coupled cluster wave functions and a dispersion-weighted MP2 method.

Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.

Genetic Variation in the TP53 Pathway and Bladder Cancer Risk. A Comprehensive Analysis

Introduction: Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro), still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk. Material and Methods: We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998–2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized logistic regression analysis to assess multiple SNPs simultaneously. Results: Based on classical analyses, SNPs in BAK1 (1), IGF1R (5), P53AIP1 (1), PMAIP1 (2), SERINPB5 (3), TP63 (3), and TP73 (1) showed significant associations at p-value#0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value$0.8). LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05–1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation. Discussion: We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.

Validação computacional de métodos compostos no estudo de propriedades moleculares

Composite methods using ONIOM and different basis sets have been used to calculate proton and electron affinities for a set of alcohols at QCISD(T)/6-311++G(2df,p) level of theory. The study was carried out considering HF, MP2 and DFT (25 exchange correlation functional) methods. The calculation performed at ONIOM2(QCISD(T)/6-311++G(2df,p):HF/6-31G(d))//ONIOM2(O3LYP/6-31G(d):HF/6-31G(d)) resulted in the smallest average absolute deviation for AP and AE, 4,75 kJ/mol e 0,43 eV, respectively.

Estimation of transpiration of the 'Valencia' orange young plant using thermal dissipation probe method

Most studies on measures of transpiration of plants, especially woody fruit, relies on methods of heat supply in the trunk. This study aimed to calibrate the Thermal Dissipation Probe Method (TDP) to estimate the transpiration, study the effects of natural thermal gradients and determine the relation between outside diameter and area of xylem in 'Valencia' orange young plants. TDP were installed in 40 orange plants of 15 months old, planted in boxes of 500 L, in a greenhouse. It was tested the correction of the natural thermal differences (DTN) for the estimation based on two unheated probes. The area of the conductive section was related to the outside diameter of the stem by means of polynomial regression. The equation for estimation of sap flow was calibrated having as standard lysimeter measures of a representative plant. The angular coefficient of the equation for estimating sap flow was adjusted by minimizing the absolute deviation between the sap flow and daily transpiration measured by lysimeter. Based on these results, it was concluded that the method of TDP, adjusting the original calibration and correction of the DTN, was effective in transpiration assessment.

Metodologia baseada em técnicas de mineração de dados para suporte à certificação de raças de ovinos

RESUMO O objetivo deste trabalho foi desenvolver uma metodologia baseada em técnicas de mineração de dados para selecionar os principais marcadores SNP (Single Nucleotide Polymorphism) para as raças de ovinos: Crioula, Morada Nova e Santa Inês. Os dados utilizados foram obtidos do Consórcio Internacional de Ovinos e são compostos por 72 animais das raças citadas, e cada animal possui 49.034 marcadores SNP. Considerando que o número de atributos (marcadores) é muito maior que o de observações (animais), foram aplicadas as técnicas de predição LASSO (Least Absolute Shrinkage and Selection Operator), Random Forest e Boosting para a geração de modelos preditivos que incorporam métodos de seleção de atributos. Os resultados revelaram que os modelos preditivos selecionaram os principais marcadores SNP para identificação das raças estudadas. O modelo LASSO selecionou um total de 29 marcadores relevantes. A partir dos modelos Random Forest e Boosting, foram obtidos 27 e 20 marcadores importantes, respectivamente. Por meio da intersecção dos modelos gerados, identificou-se um subconjunto de 18 marcadores com maior potencial de identificação das raças.

Projected gradient approach to the numerical solution of the SCoTLASS

The SCoTLASS problem-principal component analysis modified so that the components satisfy the Least Absolute Shrinkage and Selection Operator (LASSO) constraint-is reformulated as a dynamical system on the unit sphere. The LASSO inequality constraint is tackled by exterior penalty function. A globally convergent algorithm is developed based on the projected gradient approach. The algorithm is illustrated numerically and discussed on a well-known data set. (c) 2004 Elsevier B.V. All rights reserved.