Dynamic positioning systems: An experimental analysis of sliding mode control

Vessel dynamic positioning (DP) systems are based on conventional PID-type controllers and an extended Kalman filter. However, they present a difficult tuning procedure, and the closed-loop performance varies with environmental or loading conditions since the dynamics of the vessel are eminently nonlinear. Gain scheduling is normally used to address the nonlinearity of the system. To overcome these problems, a sliding mode control was evaluated. This controller is robust to variations in environmental and loading conditions, it maintains performance and stability for a large range of conditions, and presents an easy tuning methodology. The performance of the controller was evaluated numerically and experimentally in order to address its effectiveness. The results are compared with those obtained from conventional PID controller. (c) 2010 Elsevier Ltd. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Gas Chromatographic Analysis of Dimethyltryptamine and beta-Carboline Alkaloids in Ayahuasca, an Amazonian Psychoactive Plant Beverage

Introduction - Ayahuasca is obtained by infusing the pounded stems of Banisteriopsis caapi in combination with the leaves of Psychotria viridis. P. viridis is rich in the psychedelic indole N,N-dimethyltryptamine, whereas B. caapi contains substantial amounts of beta-carboline alkaloids, mainly harmine, harmaline and tetrahydroharmine, which are monoamine-oxidase inhibitors. Because of differences in composition in ayahuasca preparations, a method to measure their main active constituents is needed. Objective - To develop a gas chromatographic method for the simultaneous determination of dimethyltryptamine and the main beta-carbolines found in ayahuasca preparations. Methodology - The alkaloids were extracted by means of solid phase extraction (C(18)) and detected by gas chromatography with nitrogen/phosphorous detector. Results - The lower limit of quantification (LLOQ) was 0.02 mg/mL for all analytes. The calibration curves were linear over a concentration range of 0.02-4.0 mg/mL (r(2) > 0.99). The method was also precise (RSD < 10%). Conclusion - A simple gas chromatographic method to determine the main alkaloids found in ayahuasca was developed and validated. The method can be useful to estimate administered doses in animals and humans for further pharmacological and toxicological investigations of ayahuasca. Copyright (C) 2009 John Wiley & Sons, Ltd.

A comparison of segmental and wrist-to-ankle methodologies of bioimpedance analysis

The common approach of bioelectrical impedance analysis to estimate body water uses a wrist-to-ankle methodology which, although not indicated by theory, has the advantage of ease of application particularly for clinical studies involving patients with debilitating diseases. A number of authors have suggested the use of a segmental protocol in which the impedances of the trunk and limbs are measured separately to provide a methodology more in keeping with basic theory. The segmental protocol hits not, however, been generally adopted, partly because of the increased complexity involved in its application, and partly because studies comparing the two methodologies have not clearly demonstrated a significant improvement from the segmental methodology. We have conducted a small pilot study involving ten subjects to investigate the efficacy of the two methodologies in a group of normal subjects. The study did not require the independent measure of body water, by for example isotope dilution, as the subjects were maintained in a state of constant hydration with only the distribution between limbs and trunk changing as a result of change in posture. The results demonstrate a significant difference between the two methodologies in predicting the expected constancy of body water in this study, with the segmental methodology indicating a mean percentage change in extracellular water of -2.2%; which was not significantly different from the expected null result, whereas the wrist-to-ankle methodology indicated a mean percentage change in extracellular water of -6.6%. This is significantly different from the null result, and from the value obtained from the segmental methodology (p = 0.006). Similar results were obtained using estimates of total body water from the two methodologies. (C) 1998 Elsevier Science Ltd. All rights reserved.

Predicting sprint running times from isokinetic and squat lift tests: A regression analysis

This study examined the relationship between isokinetic hip extensor/hip flexor strength, 1-RM squat strength, and sprint running performance for both a sprint-trained and non-sprint-trained group. Eleven male sprinters and 8 male controls volunteered for the study. On the same day subjects ran 20-m sprints from both a stationary start and with a 50-m acceleration distance, completed isokinetic hip extension/flexion exercises at 1.05, 4.74, and 8.42 rad.s(-1), and had their squat strength estimated. Stepwise multiple regression analysis showed that equations for predicting both 20-m maximum velocity nm time and 20-m acceleration time may be calculated with an error of less than 0.05 sec using only isokinetic and squat strength data. However, a single regression equation for predicting both 20-m acceleration and maximum velocity run times from isokinetic or squat tests was not found. The regression analysis indicated that hip flexor strength at all test velocities was a better predictor of sprint running performance than hip extensor strength.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Analysis of proximal femur DXA scans in growing children: Comparisons of different protocols for cross-sectional 8-month and 7-year longitudinal data

Dual-energy X-ray absorptiometry (DXA) is a widely used method for measuring bone mineral in the growing skeleton. Because scan analysis in children offers a number of challenges, we compared DXA results using six analysis methods at the total proximal femur (PF) and five methods at the femoral neck (FN), In total we assessed 50 scans (25 boys, 25 girls) from two separate studies for cross-sectional differences in bone area, bone mineral content (BMC), and areal bone mineral density (aBMD) and for percentage change over the short term (8 months) and long term (7 years). At the proximal femur for the short-term longitudinal analysis, there was an approximate 3.5% greater change in bone area and BMC when the global region of interest (ROI) was allowed to increase in size between years as compared with when the global ROI was held constant. Trend analysis showed a significant (p < 0.05) difference between scan analysis methods for bone area and BMC across 7 years. At the femoral neck, cross-sectional analysis using a narrower (from default) ROI, without change in location, resulted in a 12.9 and 12.6% smaller bone area and BMC, respectively (both p < 0.001), Changes in FN area and BMC over 8 months were significantly greater (2.3 %, p < 0.05) using a narrower FN rather than the default ROI, Similarly, the 7-year longitudinal data revealed that differences between scan analysis methods were greatest when the narrower FN ROI was maintained across all years (p < 0.001), For aBMD there were no significant differences in group means between analysis methods at either the PF or FN, Our findings show the need to standardize the analysis of proximal femur DXA scans in growing children.

Solid-phase microextraction using poly(pyrrole) film and liquid chromatography with UV detection for analysis of antidepressants in plasma samples

Poly(pyrrole) (PPY) coating was prepared on a stainless-steel (SS) wire for solid-phase microextraction (SPME) by electrochemical deposition (cyclic voltammetric). The PPY was evaluated by analyzing new-generation antidepressants (mirtazapine, citalopram, paroxetine, duloxetine, fluoxetine, and sertraline) in plasma sample by SPME and liquid chromatography with UV detection (LC-UV). The effect of electrolyte Solution (lithium perchlorate or tetrabutylammonium perchlorate) and the number of cycles (50, 100 or 200) applied during the polymerization process on the SPME performance was evaluated. Important factors in the optimization of SPME efficiency such as extraction time, temperature, pH, influence of plasma proteins on sorption mechanisms, and desorption conditions are discussed. The SPME-PPY/LC method showed to be linear in concentrations ranging from the limit of quantification (LOQ) to 1200 ng mL(-1). The LOQ values range from 16 to 25 ng mL-1. The inter-day precision of the SPME-PPY/LC method presented coefficient of variation (CV) lower than 15%. Based on analytical validation results, the SPME-PPY/LC methodology showed to be adequate for antidepressant analysis, from therapeutic to toxic levels. In order to evaluate the proposed method for clinical use, the SPME-PPY/LC method was applied to the analysis of plasma samples from elderly depressed patients. (c) 2009 Elsevier B.V. All rights reserved,

Microextraction in packed sorbent for analysis of antidepressants in human plasma by liquid chromatography and spectrophotometric detection

A sensitive and reproducible method by microextraction packed sorbent and liquid chromatography with UV detection (MEPS/LC-UV) is described for the determination of new generation antidepressants (sertraline, mirtazapine, fluoxetine, citalopram and paroxetine) in human plasma samples. The MEPS variables, such as sample volume, pH, number of extraction cycles (draw-eject), and desorption conditions (solvent and solvent volume of elution) influenced the MEPS/LC efficiency significantly. Important factors in the optimization of MEPS efficiency, as well as washing steps and carryover effect are discussed. The analyses were carried out using small sample volumes (400 mu L.), and in a short time period (3 min for the entire sample preparation step). The MEPS/LC-UV method was shown to be linear at concentrations ranging from the limit of quantification (LOQ) to 1000 ng mL(-1). The LOQ values ranged from 10 to 25 ng mL(-1). The inter-day precision of the method presented coefficient of the variation ranging from 1.3% to 8.7%. On the basis of analytical validation, it is shown that the MEPS/LC-UV methodology is adequate for antidepressant analysis, from therapeutic to toxic levels. In order to evaluate the proposed method for clinical use, the MEPS/LC-UV method was applied to analysis of plasma samples from elderly depressed patients. (C) 2010 Elsevier B.V. All rights reserved.

High-breakdown linear discriminant analysis

The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Identification of genetic alterations by multiple ligation-dependent probe amplification (MLPA) analysis in oligodendrogliomas

Concurrent deletion at 1p/19q is a common signature of oligodendrogliomas, and it may, be identified in low-grade tumours (grade II) suggesting it represents an early event in the development of these brain neoplasms. Additional non-random changes primarily involve CDKN2A, PTEN and EGFR. Identification of all of these genetic changes has become an additional parameter in the evaluation of the clinical patients` prognosis, including good response to conventional chemotherapy. Multiple ligation-dependent probe amplification (MLPA) analysis is a new methodology that allows an easy identification of the oligodendrogliomas` abnormalities in a single step. No need of the respective constitutional DNA from each patient is another advantage of this method. We used MLPA kits P088 and P105 to determine the molecular characteristics of a series of 40 oligodendrogliomas. Deletions at I p and 19q were identified in 45% and 65% of cases, respectively. Alterations of EGFR, CDKN2A, ERBB2, PTEN and TP53 were also identified in variable frequencies among 7% to 35% of tumours. These findings demonstrate that MLPA is a reliable technique to the detection of molecular genetic changes in oligodendrogliomas.

Analysis of four gutta-percha techniques used to fill mesial root canals of mandibular molars

P>Aim To compare the percentage of gutta-percha, sealer and voids and the influence of isthmuses in mesial root canals of mandibular molars filled with different techniques. Methodology Canals in 60 mesial roots of mandibular first molars were prepared with ProTaper instruments to size F2 (size 25, 0.08 taper) and filled using a single-cone, lateral compaction, System B or Thermafil techniques. An epoxy resin sealer was labelled with Rhodamine-B dye to allow analysis under a confocal microscope. The percentage of gutta-percha, sealer and area of voids was calculated at 2, 4 and 6 mm from the apex, using Image Tool 3.0 software. Statistical analysis was performed using nonparametric Kruskal-Wallis and Dunn tests (P < 0.05). The influence of isthmuses on the presence or absence of voids was evaluated using the Fisher test. Results At the 2 mm level, the percentage of gutta-percha, sealer and voids was similar amongst the System B, lateral compaction and single-cone techniques. The single-cone technique revealed significantly less gutta-percha, more sealer and voids in comparison with the Thermafil technique at the 2 and 4 mm level (P < 0.05). The analysis of all sections (2, 4 and 6 mm) revealed that more gutta-percha and less sealer and voids were found in root canals filled with Thermafil and System B techniques (P < 0.05). The Fisher test revealed that the presence of isthmuses increased the occurence of voids in the lateral compaction group only (P < 0.05). Conclusion Gutta-percha, sealer filled area and voids were dependent on the canal-filling technique. The presence of isthmuses may influence the quality of root filling.