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.

Working in public health services in Brazil: The relationship between different rationalities

Success in a public health system is related to its ability to change its production process and to deal with general principles of the health system, such as universality and equity. The frameworks proposed by service marketing scholars have been developed primarily for private services; they focus on acceptance by the targeted client-users, and on the technical specifications of the new service delivery processes. Little attention has been given to the employees` point of view and their activities to maintain service operations modulated by innovation. In a public health system, workers make decisions in real time related to users` needs and the technical specifications of the process; therefore, it is very important to understand how the changes impact on employees` activities and on the quality delivered for citizens. This article discusses how changes implemented in Sao Paulo, Brazil impact the organizational parameters and working activities for front-line workers. (C) 2008 Elsevier Ltd. All rights reserved.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm

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.

Technical and economical evaluation of a harvester, working under different spacing and planting arrangement conditions in eucalypts plantations

Plantation spacing selection has the primary objective of assigning each tree enough space for maximum growth and best quality to be attained with a minimum cost. From the harvest standpoint, an increase in stand density directly implies a decrease of individual tree volume, reducing also harvester productive capacity. The objective of this research is to assess the effects of several initial spacings and arrangements in eucalyptus plantations on production capacity, operational capacity and costs of forest harvester. Real operational data were collected from two eucalypt plantations at different initial spacing of 6.0, 7.5, 9.0, 12 and 18 m(2) per tree. Simulation data were obtained from a forest harvester simulator. Using spacing (E), mean tree volume (MV), diameter at breast height (DBH) and height (H) values, a stepwise regression test procedure was run, and correlations computed in order to measure their participation in operational capacity. Operational costs were computed with an accounting method proposed by FAO. Mean tree volume (MV) explained 88% of forest harvester operational capacity. Spacing (E) affected 8.5% of harvester operational capacity; wider spacings were related to higher individual tree volumes. Harvesting operation costs were lower in wider spaced treatments.

EVALUATION OF FIVE SUGAR CANE PLANTERS

Brazil is the world biggest producer of sugar cane with an area of 7x10(6) hectares. Mainly the system used for planting is the semi-mechanized one, which consists in opening the furrows with a machine, manually allocating the fractioned stalks and then covering the furrows done by the machines. The great amount of human labor used in the semi-mechanized system is becoming harder to find and also more expensive, indicating the need of a fully mechanized operation. Currently in Brazil these agriculture machines industries offers six different types of fully mechanized sugar cane planters (two types of whole stalks for planting and four using mechanized harvested stalks known as billets). All of them plant in two furrows simultaneously in 1.5 m row spacing. This study analyzed five different machines and the following variables: Working Speed (km h(-1)); Effective Capacity (ha h(-1)), Drawbar Force (kgf), Draw Bar Power (in HP), Fuel Consumption (L h(-1)) and Costs (US$ ha(-1)) comparing them with the semi-mechanized system. This research also characterized the stalks for planting as viable gems number (%), non viable gems number (%) and billet length (m). And lastly the mechanized planting system is cheaper than the conventional one and none of the machines has an adequate mechanism for placing the right amount of sugar cane seed.

Quantification of carbamazepine, carbamazepine-10,11-epoxide, phenytoin and phenobarbital in plasma samples by stir bar-sorptive extraction and liquid chromatography

A sensitive and reproducible stir bar-sorptive extraction and high-performance liquid chromatography-UV detection (SBSE/HPLC-UV) method for therapeutic drug monitoring of carbamazepine, carbamazepine-10,11-epoxide, phenytoin and phenobarbital in plasma samples is described and compared with a liquid:liquid extraction (LLE/HPLC-UV) method. Important factors in the optimization of SBSE efficiency such as pH, extraction time and desorption conditions (solvents, mode magnetic stir, mode ultrasonic stir, time and number of steps) assured recoveries ranging from 72 to 86%, except for phenytoin (62%). Separation was obtained using a reverse phase C-18 column with UV detection (210 nm). The mobile phase consisted of water: acetonitrile (78:22, v/v). The SBSE/HPLC-UV method was linear over a working range of 0.08-40.0 mu g mL(-1) for carbamazepine, carbamazepine-10,11-epoxide and phenobarbital and 0.125-40.0 mu g mL(-1) for phenytoin, The intra-assay and inter-assay precision and accuracy were studied at three concentrations (1.0, 4.0 and 20.0 mu g mL(-1)). The intra-assay coefficients of variation (CVs) for all compounds were less than 8.8% and all inter-CVs were less than 10%. Limits of quantification were 0.08 mu g mL(-1) for carbamazepine, carbamazepine-10,11-epoxide and phenobarbital and 0.125 mu g mL(-1) for phenytoin. No interference of the drugs normally associated with antiepileptic drugs was observed. Based on figures of merit results, the SBSE/HPLC-UV proved adequate for antiepileptic drugs analyses from therapeutic levels. This method was successfully applied to the analysis of real samples and was as effective as the LLE/HPLC-UV method. (c) 2008 Elsevier B.V. All rights reserved.

Rifampicin determination in plasma by stir bar-sorptive extraction and liquid chromatography

A sensitive and reproducible stir bar-sorptive extraction and high performance liquid chromatography-UV detection (SBSE/HPLC-UV) method for therapeutic drug monitoring of rifampicin in plasma samples is described and compared with a liquid:liquid extraction (LLE/HPLC-UV) method. This miniaturized method can result in faster analysis, higher sample throughput, lower solvent consumption and less workload per sample while maintaining or even improving sensitivity. Important factors in the optimization of SBSE efficiency such as pH, temperature, extraction time and desorption conditions (solvents, mode magnetic stir, mode ultrasonic stir, time and number of steps) were optimized recoveries ranging from 75 to 80%. Separation was obtained using a reverse phase C(8) column with UV detection (254 nm). The mobile phase consisted of methanol:0.25 N sodium acetate buffer, pH 5.0 (58:42, v/v). The SBSE/HPLC-UV method was linear over a working range of 0.125-50.0 mu g mL(-1). The intra-assay and inter-assay precision and accuracy were studied at three concentrations (1.25, 6.25 and 25.0 mu g mL(-1)). The intra-assay coefficients of variation (CVs) for all compounds were less than 10% and all inter-CVs were less than 10%. Limits of quantification were 0.125 mu g mL(-1). Stability studies showed rifampicin was stable in plasma for 12 h after thawing; the samples were also stable for 24 h after preparation. Based on the figures of merit results, the SBSE/HPLC-UV proved to be adequate to the rifampicin analyses from therapeutic to toxic levels. This method was successfully applied to the analysis of real samples and was as effective as the LLE/HPLC-UV method. (C) 2009 Elsevier B.V. All rights reserved.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Challenges and Recommendations for Placebo Controls in Randomized Trials in Physical and Rehabilitation Medicine A Report of the International Placebo Symposium Working Group

Compared with other specialties, the field of physical and rehabilitation medicine has not received the deserved recognition from clinicians and researchers in the scientific community. One of the reasons is the lack of sound evidence to support the traditional physical and rehabilitation medicine treatments. The best way to change this disadvantage is through a well conducted clinical research, such as standard placebo- or sham-controlled randomized clinical trials. Therefore, having placebo groups in clinical trials is essential to improve the level of evidence-based practice in physical and rehabilitation medicine that ultimately translates to better clinical care. To address the challenges for the use of placebo in physical and rehabilitation medicine and randomized clinical trials and to create useful recommendations, we convened a working group during the inaugural International Symposium in Placebo (February 2009, in Sao Paulo, Brazil) in which the following topics were discussed: (1) current status of randomized clinical trials in physical and rehabilitation medicine, (2) challenges for the use of placebo in physical and rehabilitation medicine, (3) bioethics, (4) use of placebo in acupuncture trials and for the treatment of low-back pain, (5) mechanisms of placebo, and (6) insights from other specialties. The current article represents the consensus report from the working group.

Can Mobile Units Improve the Strategies for Cervical Cancer Prevention?

Cervical cancer is a serious public health problem in women in developing countries because of absence or ineffectiveness of screening programs. Several biases to access medical care and inequity of public health system in a continental country like Brazil limit the implementation of adequate programs to appropriately prevent the cervical cancer. Therefore, the aim of this study was to evaluate the results of applying the mobile unit (MU) for cervical cancer screening. From May 2003 to May 2004, a cervical cancer screening was offered to women aged 20-69 years, residing in 19 municipal districts of the Barretos county region, in Sao Paulo. Out of the 9,560 examination available, 2,964 (31%) women underwent screening. The medium distance traveled by the MU was 45 km. The medium time spent by women in the MU for completion of the questionnaire and doing the exam was 20 minutes. It was observed that 17.0% of women screened had never had the test or had not had it repeated within the last 3 years. The negative response was more common among women aged 20 to 29 years and 60 to 69 years and among women with less schooling and lower socio-economic income (P < 0.05). MU can significantly overcome the chronic deficiency of public health system accessibility offering opportunity to these women to participate in screening programs. Diagn. Cytopathol. 2010;38:727-730. (C) 2009 Wiley-Liss, Inc.

Program for Prostate Cancer Screening Using a Mobile Unit: Results From Brazil

OBJECTIVES To evaluate the initial results of a prostate cancer screening program using mobile units in Brazil. METHODS Since 2004, we have conducted a program of prostate cancer screening using mobile units across 231 municipalities from 6 Brazilian states. RESULTS A total of 17 571 men were evaluated by clinical history, digital rectal examination (DRE), and serum free and total prostate-specific antigen (PSA) levels. The recommendations for biopsy were a PSA level of >= 4.0 ng/mL, DRE findings suspicious for cancer, or a PSA level of 2.5-4.0 ng/mL with a percent-free PSA level <15%. The biopsy protocol included 12 biopsy cores from the peripheral zone, 2 from the transition zone, and additional sampling of suspicious areas. The cumulative cancer detection rate was 3.7%. The main indication for biopsy was a PSA level of >= 4.0 ng/mL (51.2%), with a positive predictive value (PPV) of 44.1%. Another 19.7% of biopsied men had suspicious DRE findings with a normal PSA level (PPV 23.5%). A percent-free PSA level of <15% in men with a PSA level of 2.5-4.0 ng/mL and normal DRE findings yielded a PPV of 31.1%. The PPV was greater (70.9%) for the 7.1% of men with both suspicious DRE findings and a PSA level of >4.0 ng/mL. Most cancers were Stage T1-T2 (93.4%), and the percentage of Gleason score of >= 7 was 32.5%. The proportion of insignificant cancers according to Epstein`s criteria was 13.5%. CONCLUSIONS A mobile prostate cancer screening unit enabled an underserved population to gain access to specialized care through the public healthcare system. The cancer detection rate in this population was similar to those from international studies. UROLOGY 76: 1052-1057, 2010. (C) 2010 Published by Elsevier Inc.

Processing Speed and Working Memory Span: Their Differential Role in Superficial and Deep Memory Processes in Schizophrenia

Previous work has suggested that decrement in both processing speed and working memory span plays a role in the memory impairment observed in patients with schizophrenia. We undertook a study to examine simultaneously the effect of these two factors. A sample of 49 patients with schizophrenia and 43 healthy controls underwent a battery of verbal and visual memory tasks. Superficial and deep encoding memory measures were tallied. We conducted regression analyses on the various memory measures, using processing speed and working memory span as independent variables. In the patient group, processing speed was a significant predictor of superficial and deep memory measures in verbal and visual memory. Working memory span was an additional significant predictor of the deep memory measures only. Regression analyses involving all participants revealed that the effect of diagnosis on all the deep encoding memory measures was reduced to non-significance when processing speed was entered in the regression. Decreased processing speed is involved in verbal and visual memory deficit in patients, whether the task require superficial or deep encoding. Working memory is involved only insofar as the task requires a certain amount of effort. (JINS, 2011, 17, 485-493)