Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

A Brazilian registry of juvenile dermatomyositis: onset features and classification of 189 cases

Objective To describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry. Methods Inclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data. Results Of the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%. Conclusion Evaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.

Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

Approximation de la distribution a posteriori d'un modèle Gamma-Poisson hiérarchique à effets mixtes

La méthode que nous présentons pour modéliser des données dites de "comptage" ou données de Poisson est basée sur la procédure nommée Modélisation multi-niveau et interactive de la régression de Poisson (PRIMM) développée par Christiansen et Morris (1997). Dans la méthode PRIMM, la régression de Poisson ne comprend que des effets fixes tandis que notre modèle intègre en plus des effets aléatoires. De même que Christiansen et Morris (1997), le modèle étudié consiste à faire de l'inférence basée sur des approximations analytiques des distributions a posteriori des paramètres, évitant ainsi d'utiliser des méthodes computationnelles comme les méthodes de Monte Carlo par chaînes de Markov (MCMC). Les approximations sont basées sur la méthode de Laplace et la théorie asymptotique liée à l'approximation normale pour les lois a posteriori. L'estimation des paramètres de la régression de Poisson est faite par la maximisation de leur densité a posteriori via l'algorithme de Newton-Raphson. Cette étude détermine également les deux premiers moments a posteriori des paramètres de la loi de Poisson dont la distribution a posteriori de chacun d'eux est approximativement une loi gamma. Des applications sur deux exemples de données ont permis de vérifier que ce modèle peut être considéré dans une certaine mesure comme une généralisation de la méthode PRIMM. En effet, le modèle s'applique aussi bien aux données de Poisson non stratifiées qu'aux données stratifiées; et dans ce dernier cas, il comporte non seulement des effets fixes mais aussi des effets aléatoires liés aux strates. Enfin, le modèle est appliqué aux données relatives à plusieurs types d'effets indésirables observés chez les participants d'un essai clinique impliquant un vaccin quadrivalent contre la rougeole, les oreillons, la rub\'eole et la varicelle. La régression de Poisson comprend l'effet fixe correspondant à la variable traitement/contrôle, ainsi que des effets aléatoires liés aux systèmes biologiques du corps humain auxquels sont attribués les effets indésirables considérés.

Die aeroelastische Stabilitätsanalyse – ein praxisnaher Ansatz zur intervalltheoretischen Betrachtung von Modellierungsunsicherheiten am Flugzeug

Die Untersuchung des dynamischen aeroelastischen Stabilitätsverhaltens von Flugzeugen erfordert sehr komplexe Rechenmodelle, welche die wesentlichen elastomechanischen und instationären aerodynamischen Eigenschaften der Konstruktion wiedergeben sollen. Bei der Modellbildung müssen einerseits Vereinfachungen und Idealisierungen im Rahmen der Anwendung der Finite Elemente Methode und der aerodynamischen Theorie vorgenommen werden, deren Auswirkungen auf das Simulationsergebnis zu bewerten sind. Andererseits können die strukturdynamischen Kenngrößen durch den Standschwingungsversuch identifiziert werden, wobei die Ergebnisse Messungenauigkeiten enthalten. Für eine robuste Flatteruntersuchung müssen die identifizierten Unwägbarkeiten in allen Prozessschritten über die Festlegung von unteren und oberen Schranken konservativ ermittelt werden, um für alle Flugzustände eine ausreichende Flatterstabilität sicherzustellen. Zu diesem Zweck wird in der vorliegenden Arbeit ein Rechenverfahren entwickelt, welches die klassische Flatteranalyse mit den Methoden der Fuzzy- und Intervallarithmetik verbindet. Dabei werden die Flatterbewegungsgleichungen als parameterabhängiges nichtlineares Eigenwertproblem formuliert. Die Änderung der komplexen Eigenlösung infolge eines veränderlichen Einflussparameters wird mit der Methode der numerischen Fortsetzung ausgehend von der nominalen Startlösung verfolgt. Ein modifizierter Newton-Iterations-Algorithmus kommt zur Anwendung. Als Ergebnis liegen die berechneten aeroelastischen Dämpfungs- und Frequenzverläufe in Abhängigkeit von der Fluggeschwindigkeit mit Unschärfebändern vor.

A Brazilian registry of juvenile dermatomyositis: onset features and classification of 189 cases

ObjectiveTo describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry.MethodsInclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data.ResultsOf the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%.ConclusionEvaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.

Can a novel web-based computer test predict poor simulated driving performance? A pilot study with healthy and cognitive-impaired participants

BACKGROUND Driving a car is a complex instrumental activity of daily living and driving performance is very sensitive to cognitive impairment. The assessment of driving-relevant cognition in older drivers is challenging and requires reliable and valid tests with good sensitivity and specificity to predict safe driving. Driving simulators can be used to test fitness to drive. Several studies have found strong correlation between driving simulator performance and on-the-road driving. However, access to driving simulators is restricted to specialists and simulators are too expensive, large, and complex to allow easy access to older drivers or physicians advising them. An easily accessible, Web-based, cognitive screening test could offer a solution to this problem. The World Wide Web allows easy dissemination of the test software and implementation of the scoring algorithm on a central server, allowing generation of a dynamically growing database with normative values and ensures that all users have access to the same up-to-date normative values. OBJECTIVE In this pilot study, we present the novel Web-based Bern Cognitive Screening Test (wBCST) and investigate whether it can predict poor simulated driving performance in healthy and cognitive-impaired participants. METHODS The wBCST performance and simulated driving performance have been analyzed in 26 healthy younger and 44 healthy older participants as well as in 10 older participants with cognitive impairment. Correlations between the two tests were calculated. Also, simulated driving performance was used to group the participants into good performers (n=70) and poor performers (n=10). A receiver-operating characteristic analysis was calculated to determine sensitivity and specificity of the wBCST in predicting simulated driving performance. RESULTS The mean wBCST score of the participants with poor simulated driving performance was reduced by 52%, compared to participants with good simulated driving performance (P<.001). The area under the receiver-operating characteristic curve was 0.80 with a 95% confidence interval 0.68-0.92. CONCLUSIONS When selecting a 75% test score as the cutoff, the novel test has 83% sensitivity, 70% specificity, and 81% efficiency, which are good values for a screening test. Overall, in this pilot study, the novel Web-based computer test appears to be a promising tool for supporting clinicians in fitness-to-drive assessments of older drivers. The Web-based distribution and scoring on a central computer will facilitate further evaluation of the novel test setup. We expect that in the near future, Web-based computer tests will become a valid and reliable tool for clinicians, for example, when assessing fitness to drive in older drivers.

Efficient training of RBF networks for classification.

Radial Basis Function networks with linear outputs are often used in regression problems because they can be substantially faster to train than Multi-layer Perceptrons. For classification problems, the use of linear outputs is less appropriate as the outputs are not guaranteed to represent probabilities. We show how RBFs with logistic and softmax outputs can be trained efficiently using the Fisher scoring algorithm. This approach can be used with any model which consists of a generalised linear output function applied to a model which is linear in its parameters. We compare this approach with standard non-linear optimisation algorithms on a number of datasets.

Symmetric Interior Penalty DG Methods for the Compressible Navier-Stokes Equations I: Method Formulation

In this article we consider the development of discontinuous Galerkin finite element methods for the numerical approximation of the compressible Navier-Stokes equations. For the discretization of the leading order terms, we propose employing the generalization of the symmetric version of the interior penalty method, originally developed for the numerical approximation of linear self-adjoint second-order elliptic partial differential equations. In order to solve the resulting system of nonlinear equations, we exploit a (damped) Newton-GMRES algorithm. Numerical experiments demonstrating the practical performance of the proposed discontinuous Galerkin method with higher-order polynomials are presented.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Subspace wavepacket evolution with Newton polynomials

Time-dependent wavepacket evolution techniques demand the action of the propagator, exp(-iHt/(h)over-bar), on a suitable initial wavepacket. When a complex absorbing potential is added to the Hamiltonian for combating unwanted reflection effects, polynomial expansions of the propagator are selected on their ability to cope with non-Hermiticity. An efficient subspace implementation of the Newton polynomial expansion scheme that requires fewer dense matrix-vector multiplications than its grid-based counterpart has been devised. Performance improvements are illustrated with some benchmark one and two-dimensional examples. (C) 2001 Elsevier Science B.V. All rights reserved.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.