A comparison of the alr and ilr transformations for kernel density estimation of compositional data

In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel density estimation techniques in the context of compositional data analysis. Indeed, they gave two options for the choice of the kernel to be used in the kernel estimator. One of these kernels is based on the use the alr transformation on the simplex SD jointly with the normal distribution on RD-1. However, these authors themselves recognized that this method has some deficiencies. A method for overcoming these dificulties based on recent developments for compositional data analysis and multivariate kernel estimation theory, combining the ilr transformation with the use of the normal density with a full bandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu- Figueras (2006). Here we present an extensive simulation study that compares both methods in practice, thus exploring the finite-sample behaviour of both estimators

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Numerical model of solid phase transformations governed by nucleation and growth: microstructure development during isothermal crystallization

A simple numerical model which calculates the kinetics of crystallization involving randomly distributed nucleation and isotropic growth is presented. The model can be applied to different thermal histories and no restrictions are imposed on the time and the temperature dependences of the nucleation and growth rates. We also develop an algorithm which evaluates the corresponding emerging grain-size distribution. The algorithm is easy to implement and particularly flexible, making it possible to simulate several experimental conditions. Its simplicity and minimal computer requirements allow high accuracy for two- and three-dimensional growth simulations. The algorithm is applied to explore the grain morphology development during isothermal treatments for several nucleation regimes. In particular, thermal nucleation, preexisting nuclei, and the combination of both nucleation mechanisms are analyzed. For the first two cases, the universal grain-size distribution is obtained. The high accuracy of the model is stated from its comparison to analytical predictions. Finally, the validity of the Kolmogorov-Johnson-Mehl-Avrami model SSSR, is verified for all the cases studied

Destabilizing Mutations Alter the Hydrogen Exchange Mechanism in Ribonuclease A

The effect of strongly destabilizing mutations, I106A and V108G of Ribonuclease A (RNase A), on its structure and stability has been determined by NMR. The solution structures of these variants are essentially equivalent to RNase A. The exchange rates of the most protected amide protons in RNase A (35ºC), the I106A variant (35ºC), and the V108G variant (10ºC) yield stability values of 9.9, 6.0, and 6.8 kcal/mol, respectively, when analyzed assuming an EX2 exchange mechanism. Thus, the destabilization induced by these mutations is propagated throughout the protein. Simulation of RNase A hydrogen exchange indicates that the most protected protons in RNase A and the V108G variant exchange via the EX2 regime, whereas those of I106A exchange through a mixed EX1 1 EX2 process. It is striking that a single point mutation can alter the overall exchange mechanism. Thus, destabilizing mutations joins high temperatures, high pH and the presence of denaturating agents as a factor that induces EX1 exchange in proteins. The calculations also indicate a shift from the EX2 to the EX1 mechanism for less protected groups within the same protein. This should be borne in mind when interpreting exchange data as a measure of local stability in less protected regions

A proposal for the diagnosis of uncertain dynamic systems based on interval models

The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. The methodology includes some algorithms to obtain in an automatic way the symbolic expression of the residual generators enhancing the structural isolability of the faults, in order to design the fault detection tests. These algorithms are based on the structural model of the system. The stages of fault detection, isolation, and identification are stated as constraint satisfaction problems in continuous domains and solved by means of interval based consistency techniques. The qualitative fault isolation is enhanced by a reasoning in which the signs of the symptoms are derived from analytical redundancy relations or bond graph models of the system. An initial and empirical analysis regarding the differences between interval-based and statistical-based techniques is presented in this thesis. The performance and efficiency of the contributions are illustrated through several application examples, covering different levels of complexity.

O2 activation at bioinspired complexes: dinuclear copper systems and mononuclear non-heme iron compounds. Mechanisms and catalytic applications in oxidative transformations

L'activació d'oxigen que té lloc en els éssers vius constitueix una font d'inspiració pel desenvolupament d'alternatives als oxidants tradicionals, considerats altament tòxics i nocius. En aquesta treball s'utilitzen compostos sintètics com a models del centre actiu de proteïnes dinuclears de coure i mononuclears de ferro de tipus no-hemo que participen en l'activació d'oxigen en els éssers vius. Els sistemes dinuclears de coure mostren un centre de tipus coure(III) bis(oxo) que és capaç de dur a terme l'ortho-hidroxilació de fenols de manera similar a la reacció que catalitza la proteïna tirosinasa. Per altra banda, els sistemes de ferro desenvolupats en aquest treball actuen com a models de les dioxigenases de Rieske i poden dur a terme l'hidroxilació estereoespecífica d'alcans i l'epoxidació i cis-dihidroxilació d'olefines utilitzant peròxid d'hidrogen com a agent oxidant. Tot plegat demostra que el desenvolupament de sistemes model constitueix una bona estratègia per l'estudi dels sistemes naturals.

Improvements in the ray tracing of implicit surfaces based on interval arithmetic

Las superfícies implícitas son útiles en muchas áreasde los gráficos por ordenador. Una de sus principales ventajas es que pueden ser fácilmente usadas como primitivas para modelado. Aun asi, no son muy usadas porque su visualización toma bastante tiempo. Cuando se necesita una visualización precisa, la mejor opción es usar trazado de rayos. Sin embargo, pequeñas partes de las superficies desaparecen durante la visualización. Esto ocurre por la truncación que se presenta en la representación en punto flotante de los ordenadores; algunos bits se puerden durante las operaciones matemáticas en los algoritmos de intersección. En este tesis se presentan algoritmos para solucionar esos problemas. La investigación se basa en el uso del Análisis Intervalar Modal el cual incluye herramientas para resolver problemas con incertidumbe cuantificada. En esta tesis se proporcionan los fundamentos matemáticos necesarios para el desarrollo de estos algoritmos.

Application of modal interval analysis to the simulation of the behaviour of dynamic systems with uncertain parameters

Els models matemàtics quantitatius són simplificacions de la realitat i per tant el comportament obtingut per simulació d'aquests models difereix dels reals. L'ús de models quantitatius complexes no és una solució perquè en la majoria dels casos hi ha alguna incertesa en el sistema real que no pot ser representada amb aquests models. Una forma de representar aquesta incertesa és mitjançant models qualitatius o semiqualitatius. Un model d'aquest tipus de fet representa un conjunt de models. La simulació del comportament de models quantitatius genera una trajectòria en el temps per a cada variable de sortida. Aquest no pot ser el resultat de la simulació d'un conjunt de models. Una forma de representar el comportament en aquest cas és mitjançant envolupants. L'envolupant exacta és complete, és a dir, inclou tots els possibles comportaments del model, i correcta, és a dir, tots els punts dins de l'envolupant pertanyen a la sortida de, com a mínim, una instància del model. La generació d'una envolupant així normalment és una tasca molt dura que es pot abordar, per exemple, mitjançant algorismes d'optimització global o comprovació de consistència. Per aquesta raó, en molts casos s'obtenen aproximacions a l'envolupant exacta. Una aproximació completa però no correcta a l'envolupant exacta és una envolupant sobredimensionada, mentre que una envolupant correcta però no completa és subdimensionada. Aquestes propietats s'han estudiat per diferents simuladors per a sistemes incerts.