Some heuristic algorithms for total tardiness minimization in a flowshop with blocking

The flowshop scheduling problem with blocking in-process is addressed in this paper. In this environment, there are no buffers between successive machines: therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Heuristic approaches are proposed to minimize the total tardiness criterion. A constructive heuristic that explores specific characteristics of the problem is presented. Moreover, a GRASP-based heuristic is proposed and Coupled with a path relinking strategy to search for better outcomes. Computational tests are presented and the comparisons made with an adaptation of the NEH algorithm and with a branch-and-bound algorithm indicate that the new approaches are promising. (c) 2007 Elsevier Ltd. All rights reserved.

Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

A new oxovanadium(IV)-cucurbit[6]uril complex: Properties and potential for confined heterogeneous catalytic oxidation reactions

This work presents a new oxovanadium(IV)-cucurbit[6]uril complex, which combines the catalytic properties of the metal ion with the size-excluding properties of the macrocycle cavity. In this coordination compound, the VO(2-) ions are coordinated to the oxygen atoms located at the rim of the macrocycle in slightly distorted square-pyramidal configurations, which are in fact C(2v) symmetries. This combination results in a size-selective heterogeneous catalyst, which is able to oxidize linear alkanes like n-pentane at room temperature, but not styrene, cyclohexane or z-cyclooctene, which are too big to enter the cucurbit[6]uril cavity. The results presented here contribute to understanding the mechanism of alkane catalytic oxidation by oxovanadium(IV) complexes. (C) 2010 Elsevier Ltd. All rights reserved.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

Spectrum and Prevalence of FP/TMEM127 Gene Mutations in Pheochromocytomas and Paragangliomas

Context Pheochromocytomas and paragangliomas are genetically heterogeneous neural crest-derived neoplasms. We recently identified germline mutations of the novel transmembrane-encoding gene FP/TMEM127 in familial and sporadic pheochromocytomas consistent with a tumor suppressor effect. Objectives To examine the prevalence and spectrum of FP/TMEM127 mutations in pheochromocytomas and paragangliomas and to test the effect of mutations in vitro. Design, Setting, and Participants We sequenced the FP/TMEM127 gene in 990 individuals with pheochromocytomas and/or paragangliomas, including 898 previously unreported cases without mutations in other susceptibility genes from 8 independent worldwide referral centers between January 2009 and June 2010. A multiplex polymerase chain reaction-based method was developed to screen for large gene deletions in 545 of these samples. Confocal microscopy of 5 transfected mutant proteins was used to determine their subcellular localization. Main Outcome Measures The frequency and type of FP/TMEM127 mutation or deletion was assessed and correlated with clinical variables; the subcellular localization of 5 overexpressed mutants was compared with wild-type FP/TMEM127 protein. Results We identified 19 potentially pathogenic FP/TMEM127 germline mutations in 20 independent families, but no large deletions were detected. All mutation carriers had adrenal tumors, including 7 bilateral (P=2.7 x 10(-4)) and/or with familial disease (5 of 20 samples; P=.005). The median age at disease onset in the FP/TMEM127 mutation group was similar to that of patients without a mutation (41.5 vs 45 years, respectively; P=.54). The most common presentation was that of a single benign adrenal tumor in patients older than 40 years. Malignancy was seen in 1 mutation carrier (5%). Expression of 5 novel FP/TMEM127 mutations in cell lines revealed diffuse localization of the mutant proteins in contrast with the discrete multiorganelle distribution of wild-type TMEM127. Conclusions Germline mutations of FP/TMEM127 were associated with pheochromocytoma but not paraganglioma and occured in an age group frequently excluded from genetic screening algorithms. Disease-associated mutations disrupt intracellular distribution of the FP/TMEM127 protein. JAMA. 2010;304(23):2611-2619 www.jama.com

Most of the patients presenting myocardial infarction would not be eligible for intensive lipid-lowering based on clinical algorithms or plasma C-reactive protein

Objective: The study we assessed how often patients who are manifesting a myocardial infarction (MI) would not be considered candidates for intensive lipid-lowering therapy based on the current guidelines. Methods: In 355 consecutive patients manifesting ST elevation MI (STEMI), admission plasma C-reactive protein (CRP) was measured and Framingham risk score (FRS), PROCAM risk score, Reynolds risk score, ASSIGN risk score, QRISK, and SCORE algorithms were applied. Cardiac computed tomography and carotid ultrasound were performed to assess the coronary artery calcium score (CAC), carotid intima-media thickness (cIMT) and the presence of carotid plaques. Results: Less than 50% of STEMI patients would be identified as having high risk before the event by any of these algorithms. With the exception of FRS (9%), all other algorithms would assign low risk to about half of the enrolled patients. Plasma CRP was <1.0 mg/L in 70% and >2 mg/L in 14% of the patients. The average cIMT was 0.8 +/- 0.2 mm and only in 24% of patients was >= 1.0 mm. Carotid plaques were found in 74% of patients. CAC > 100 was found in 66% of patients. Adding CAC >100 plus the presence of carotid plaque, a high-risk condition would be identified in 100% of the patients using any of the above mentioned algorithms. Conclusion: More than half of patients manifesting STEMI would not be considered as candidates for intensive preventive therapy by the current clinical algorithms. The addition of anatomical parameters such as CAC and the presence of carotid plaques can substantially reduce the CVD risk underestimation. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

VKORC1 polymorphisms in Brazilians: comparison with the Portuguese and Portuguese-speaking Africans and pharmacogenetic implications

Aims: The heterogeneity of the Brazilian population renders the extrapolation of pharmacogenomic data derived from well-defined ethnic groups inappropriate. We investigated the influence of self-reported `race/color`, geographical origin and genetic ancestry on the distribution of four VKORC1 SNPs and haplotypes in Brazilians. Comparative data were obtained from two major ancestral roots of Brazilians: Portuguese and Africans from former Portuguese colonies. Materials & methods: A total of 1037 healthy adults Brazilians, recruited at four different geographical regions and self identified as white, brown or black (race/color categories), 89 Portuguese and 216 Africans from Angola and Mozambique were genotyped for the VKORC1 3673G>A (rs9923231), 5808T>G (rs2884737), 6853G>C (rs8050894) and 9041G>A (rs7294) polymorphisms using TaqMan (R) (Applied Biosystems, CA, USA) assays. VKORC1 haplotypes were statistically inferred using the haplo.stats software. We inferred the statistical association between the distribution of the VKORC1 polymorphisms among Brazilians and self-reported color, geographical region and genetic ancestry by fitting multinomial log linear models via neural networks. Individual proportions of European and African ancestry were used to assess the impact of genetic admixture on the frequency distribution of VKORC1 polymorphisms among Brazilians, and for the comparison of Brazilians with Portuguese and Africans. Results: The frequency distribution of the 3673G>A and 5808T>G polymorphisms, and VKORC1 haplotypes among Brazilians varies across geographical regions, within self-reported color categories and according to the individual proportions of European and African genetic ancestry. Notably, the frequency of the warfarin sensitive VKORC1 3673A allele and the distribution of VKORC1 haplotypes varied continuously as the individual proportion of European ancestry increased in the entire cohort, independently of race/color categorization and geographical origin. Brazilians with more than 80% African ancestry differ significantly from Angolans and Mozambicans in frequency of the 3673G>A, 5808T>G and 6853G>C polymorphisms and haplotype distribution, whereas no such differences are observed between Brazilians with more than 90% European ancestry and Portuguese individuals. Conclusion: The diversity of the Brazilian population, evident in the distribution of VKORC1 polymorphisms, must be taken into account in the design of pharmacogenetic clinical trials and dealt with as a continuous variable. Warfarin dosing algorithms that include `race` terms defined for other populations are clearly not applicable to the heterogeneous and extensively admixed Brazilian population.

Neuropsychological Profile of Brazilian Older Adults with Heterogeneous Educational Backgrounds

Education significantly impacts cognitive performance of older adults even in the absence of dementia. Some cognitive tests seem less vulnerable to the influence of education and thus may be more suitable for cognitive assessment of older adults with heterogeneous backgrounds. The objective of this study was to investigate which tests in a cognitive battery were less influenced by educational levels in a sample of cognitively unimpaired older Brazilians. In addition, we evaluated the impact of very high educational levels on cognitive performance. The cognitive battery consisted of the Mini Mental State Examination (MMSE), Cambridge Cognitive Test (CAMCOG), Clock Drawing Test, Short Cognitive Performance Test (SKT), Rivermead Behavioural Memory Test (RBMT), Fuld Object Memory Evaluation (FOME), Verbal Fluency Test (VF) fruit category, Trail Making Test A and B, WAIS-R Vocabulary, and Block Design. Education did not exert a significant influence on the RBMT, FOME, and VF (p < .05). Subjects with very high educational levels had similar performance on the latter tests when compared with those with intermediate and low levels of education. In conclusion, the RBMT, FOME, and VF fruit category seem to be appropriate tools for the assessment of cognitive function in elderly Brazilians with varying degrees of educational attainment.

A NEW METHOD TO OBTAIN GOOD ANATOMICAL SLIDES OF HETEROGENEOUS PLANT PARTS

A new method is presented to prepare anatomical slides of plant materials including a combination of soft and hard tissues, such as stems with cambial variants, arboreal monocotyledons, and tree bark The method integrates previous techniques aimed at softening the samples and making them thereby more homogeneous, with the use of anti-tearing polystyrene foam solution In addition, we suggest two other alternatives to protect the sections from tearing adhesive tape and/or Mayer`s albumin adhesive, both combined with the polystyrene foam solution This solution is cheap and easy to make by dissolving any packaging polystyrene m butyl acetate It is applied before each section is cut on a sliding microtome and ensures that all the tissues in the section will hold together This novel microtechnical procedure will facilitate the study of heterogeneous plant portions, as shown in some illustrated examples

Learning of shared attention in sociable robotics

Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.

Extending the use of canonical and microcanonical Monte Carlo algorithms to spin models

We describe the canonical and microcanonical Monte Carlo algorithms for different systems that can be described by spin models. Sites of the lattice, chosen at random, interchange their spin values, provided they are different. The canonical ensemble is generated by performing exchanges according to the Metropolis prescription whereas in the microcanonical ensemble, exchanges are performed as long as the total energy remains constant. A systematic finite size analysis of intensive quantities and a comparison with results obtained from distinct ensembles are performed and the quality of results reveal that the present approach may be an useful tool for the study of phase transitions, specially first-order transitions. (C) 2009 Elsevier B.V. All rights reserved.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.