990 resultados para Down-sample algorithm


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This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.

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Experimental and clinical studies have established that zinc metabolism is altered in individuals with Down syndrome (DS). The present study intends to evaluate the nutritional status of zinc in children with DS by determining their biochemical and dietary parameters. The investigation was carried out on a group of children with DS (n = 35) and compared with a control group (n = 33), both aging between 4 and 11 years. Weight-for-age, height-for-age, and weight-for-height indexes and diet were evaluated by using a 3-day dietary record. Zinc was evaluated in plasma, erythrocytes, and 24-h urine collection by using the method of atomic absorption spectroscopy. The frequency of short stature was higher in children with DS. Both groups presented high protein content, adequate concentrations of lipids and carbohydrates, and deficit in calories. Adequate zinc intake was observed in 40% of children with DS and in 67% of the control group. Zinc concentrations were significantly lower in plasma and urine and higher in erythrocytes of children with DS. The results allowed us to conclude that the altered zinc nutritional status of individuals with Down syndrome contributes to clinical disturbances that usually appear with aging in these patients.

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A three-phase hollow-fiber liquid-phase microextraction method for the analysis of rosiglitazone and its metabolites N-desmethyl rosiglitazone and p-hydroxy rosiglitazone in microsomal preparations is described for the first time. The drug and metabolites HPLC determination was carried out using an X-Terra RP-18 column, at 22 degrees C. The mobile phase was composed of water, acetonitrile and acetic acid (85:15:0.5, v/v/v) and the detection was performed at 245 nm. The hollow-fiber liquid-phase microextraction procedure was optimized using multifactorial experiments and the following optimal condition was established: sample agitation at 1750 rpm, extraction for 30 min, hydrochloric acid 0.01 mol/L as acceptor phase, 1-octanol as organic phase, and donor phase pH adjustment to 8.0. The recovery rates, obtained by using 1 mL of microsomal preparation, were 47-70%. The method presented LOQs of 50 ng/mL and it was linear over the concentration range of 50-6000 ng/mL, with correlation coefficients (r) higher than 0.9960, for all analytes. The validated method was employed to study the in vitro biotransformation of rosiglitazone using rat liver microsomal fraction.

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Despite the necessity to differentiate chemical species of mercury in clinical specimens, there area limited number of methods for this purpose. Then, this paper describes a simple method for the determination of methylmercury and inorganic mercury in blood by using liquid chromatography with inductively coupled mass spectrometry (LC-ICP-MS) and a fast sample preparation procedure. Prior to analysis, blood (250 mu L) is accurately weighed into 15-mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCI was added to the samples following sonication for 15 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of mercury species was accomplished in less than 5 min on a C18 reverse-phase column with a mobile phase containing 0.05% (v/v) mercaptoethanol, 0.4% (m/v) L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% (v/v) methanol. The method detection limits were found to be 0.25 mu g L(-1) and 0.1 mu Lg L(-1) for inorganic mercury and methylmercury, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). The proposed method was also applied to the speciation of mercury in blood samples collected from fish-eating communities and from rats exposed to thimerosal. With the proposed method there is a considerable reduction of the time of sample preparation prior to speciation of Hg by LC-ICP-MS. Finally, after the application of the proposed method, we demonstrated an interesting in vivo ethylmercury conversion to inorganic mercury. (C) 2009 Elsevier B.V. All rights reserved.

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A simple method for mercury speciation in hair samples with a fast sample preparation procedure using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry is proposed. Prior to analysis, 50 mg of hair samples were accurately weighed into 15 mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCl was added to the samples following sonication for 10 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of inorganic mercury (Ino-Hg), methylmercury (Met-Hg) and ethylmercury (Et-Hg) was accomplished in less than 8 min on a C18 reverse phase column with a mobile phase containing 0.05% v/v mercaptoethanol, 0.4% m/v L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% v/v methanol. The method detection limits were found to be 15 ng g(-1), 10 ng g(-1) and 38 ng g(-1), for inorganic mercury, methylmercury and ethylmercury, respectively. Sample throughput is 4 samples h(-1) (duplicate). A considerable improvement in the time of analysis was achieved when compared to other published methods. Method accuracy is traceable to Certified Reference Materials (CRMs) 85 and 86 human hair from the International Atomic Energy Agency (IAEA). Finally, the proposed method was successfully applied to the speciation of mercury in hair samples collected from fish-eating communities of the Brazilian Amazon.

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A simple method with a fast sample preparation procedure for total and inorganic mercury determinations in blood samples is proposed based on flow injection cold vapor inductively coupled plasma mass spectrometry (FI-CVICP-MS). Aliquots of whole blood (500 mL) are diluted 1 + 1 v/v with 10.0% v/v tetramethylammonium hydroxide (TMAH) solution, incubated for 3 h at room temperature and then further diluted 1 + 4 v/v with 2.0% v/v HCl. The inorganic Hg was released by online addition of L-cysteine and then reduced to elemental Hg by SnCl(2). On the other hand, total mercury was determined by on-line addition of KMnO(4) and then reduced to elemental Hg by NaBH(4). Samples were calibrated against matrix-matching. The method detection limit was found to be 0.80 mu g L(-1) and 0.08 mu g L(-1) for inorganic and total mercury, respectively. Sample throughput is 20 samples h(-1). The method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). For additional validation purposes, human whole blood samples were analyzed by the proposed method and by an established CV AAS method, with no statistical difference between the two techniques at 95% confidence level on applying the t-test.

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A simple and fast method is described for simultaneous determination of methylmercury (MeHg), ethylmercury (Et-Hg) and inorganic mercury (Ino-Hg) in blood samples by using capillary gas chromatography-inductively coupled plasma mass spectrometry (GC-ICP-MS) after derivatization and alkaline digestion. Closed-vessel microwave assisted digestion conditions with tetramethylammonium hydroxide (TMAH) have been optimized. Derivatization by using ethylation and propylation procedures have also been evaluated and compared. The absolute detection limits (using a 1 mu L injection) obtained by GC-ICP-MS with ethylation were 40 fg for MeHg and Ino-Hg, respectively, and with propylation were 50, 20 and 50 fg for MeHg, Et-Hg and Ino-Hg, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). Additional validation is provided based on the comparison of results obtained for mercury speciation in blood samples with the proposed procedure and with a previously reported LC-ICP-MS method. With the new proposed procedure no tedious clean-up steps are required and a considerable improvement of the time of analysis was achieved compared to other methods using GC separation.

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The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

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Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

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A study was conducted to examine the relationships among eating pathology, weight dissatisfaction and dieting, and unwanted sexual experiences in childhood. An unselected community sample of 201 young and 268 middle-aged women were administered questionnaires assessing eating behaviors and attitudes, and past and current sexual abuse. Results showed differential relationships among these factors for the two age cohorts: for young women, past sexual abuse predicted weight dissatisfaction, but not dieting or disordered eating behaviors, whereas for middle-aged women, past abuse was predictive of disordered eating, but not dieting or weight dissatisfaction. Current physical or sexual abuse was also found to be predictive of disordered eating for the young women. These findings underscore the complexity of the relationships among unwanted sexual experiences and eating and weight pathology, and suggest that the timing of sexual abuse, and the age of the woman, are important mediating factors. (C) 1998 Elsevier Science Inc.

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Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.