Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Visualizing non-linear control system performance by means of multidimensional scaling

This paper addresses the use of multidimensional scaling in the evaluation of controller performance. Several nonlinear systems are analyzed based on the closed loop time response under the action of a reference step input signal. Three alternative performance indices, based on the time response, Fourier analysis, and mutual information, are tested. The numerical experiments demonstrate the feasibility of the proposed methodology and motivate its extension for other performance measures and new classes of nonlinearities.

Multi-bit sigma-delta modulators with enhanced dynamic-range using non-linear DAC for hearing aids

15th IEEE International Conference on Electronics, Circuits and Systems, Malta

Numerical solution of a PDE system with non-linear steady state conditions that translates the air stripping pollutants removal

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the “best fit” model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (“cheap”) and B- (“expensive”) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to “ideal” experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal “filling”) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Desarrollo de Algoritmos Numéricos para el Estudio de la Propagación no Lineal de Ondas en Aplicaciones Aeroespaciales y Astrofísicas. Develop to Numerical Algorithms to Study non-Linear Waves Propagation in Aerospace and Astrophysics Applications.

En este proyecto se desarrollarán algoritmos numéricos para sistemas no lineales hiperbólicos-parabólicos de ecuaciones diferenciales en derivadas parciales. Dichos sistemas tienen aplicación en propagación de ondas en ámbitos aeroespaciales y astrofísicos.Objetivos generales: 1)Desarrollo y mejora de algoritmos numéricos con la finalidad de incrementar la calidad en la simulación de propagación e interacción de ondas gasdinámicas y magnetogasdinámicas no lineales. 2)Desarrollo de códigos computacionales con la finalidad de simular flujos gasdinámicos de elevada entalpía incluyendo cambios químicos, efectos dispersivos y difusivos.3)Desarrollo de códigos computacionales con la finalidad de simular flujos magnetogasdinámicos ideales y reales.4)Aplicación de los nuevos algoritmos y códigos computacionales a la solución del flujo aerotermodinámico alrededor de cuerpos que ingresan en la atmósfera terrestre. 5)Aplicación de los nuevos algoritmos y códigos computacionales a la simulación del comportamiento dinámico no lineal de arcos magnéticos en la corona solar. 6)Desarrollo de nuevos modelos para describir el comportamiento no lineal de arcos magnéticos en la corona solar.Este proyecto presenta como objetivo principal la introducción de mejoras en algoritmos numéricos para simular la propagación e interacción de ondas no lineales en dos medios gaseosos: aquellos que no poseen carga eléctrica libre (flujos gasdinámicos) y aquellos que tienen carga eléctrica libre (flujos magnetogasdinámicos). Al mismo tiempo se desarrollarán códigos computacionales que implementen las mejoras de las técnicas numéricas.Los algoritmos numéricos se aplicarán con la finalidad de incrementar el conocimiento en tópicos de interés en la ingeniería aeroespacial como es el cálculo del flujo de calor y fuerzas aerotermodinámicas que soportan objetos que ingresan a la atmósfera terrestre y en temas de astrofísica como la propagación e interacción de ondas, tanto para la transferencia de energía como para la generación de inestabilidades en arcos magnéticos de la corona solar. Estos dos temas poseen en común las técnicas y algoritmos numéricos con los que serán tratados. Las ecuaciones gasdinámicas y magnetogasdinámicas ideales conforman sistemas hiperbólicos de ecuaciones diferenciales y pueden ser solucionados utilizando "Riemann solvers" junto con el método de volúmenes finitos (Toro 1999; Udrea 1999; LeVeque 1992 y 2005). La inclusión de efectos difusivos genera que los sistemas de ecuaciones resulten hiperbólicos-parabólicos. La contribución parabólica puede ser considerada como términos fuentes y tratada adicionalmente tanto en forma explícita como implícita (Udrea 1999; LeVeque 2005).Para analizar el flujo alrededor de cuerpos que ingresan en la atmósfera se utilizarán las ecuaciones de Navier-Stokes químicamente activas, mientras la temperatura no supere los 6000K. Para mayores temperaturas es necesario considerar efectos de ionización (Anderson, 1989). Tanto los efectos difusivos como los cambios químicos serán considerados como términos fuentes en las ecuaciones de Euler. Para tratar la propagación de ondas, transferencia de energía e inestabilidades en arcos magnéticos de la corona solar se utilizarán las ecuaciones de la magnetogasdinámica ideal y real. En este caso será también conveniente implementar términos fuente para el tratamiento de fenómenos de transporte como el flujo de calor y el de radiación. Los códigos utilizarán la técnica de volúmenes finitos, junto con esquemas "Total Variation Disminishing - TVD" sobre mallas estructuradas y no estructuradas.

Non-linear model reduction and control of molten carbonate fuel cell systems with internal reforming fuel cell systems with internal reforming

Magdeburg, Univ., Diss, 2007

Design of biped robot walking based on non-linear periodical oscillations

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2012

Predicting trabecular bone microdamage initiation and accumulation using a non-linear perfect damage model

Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions

Quasiconformal maps, analytic capacity, and non linear potentials

"Vegeu el resum a l'inici del document del fitxer adjunt."