An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.

Self-Scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach

This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

Avaliação do potencial eólico para geração de energia eléctrica

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

Measurement of the forward-backward asymmetry of electron and muon pair-production in pp collisions at s√ = 7 TeV with the ATLAS detector

This paper presents measurements from the ATLAS experiment of the forward-backward asymmetry in the reaction pp→Z/γ∗→l+l−, with l being electrons or muons, and the extraction of the effective weak mixing angle. The results are based on the full set of data collected in 2011 in pp collisions at the LHC at s√ = 7 TeV, corresponding to an integrated luminosity of 4.8 fb−1. The measured asymmetry values are found to be in agreement with the corresponding Standard Model predictions. The combination of the muon and electron channels yields a value of the effective weak mixing angle of 0.2308±0.0005(stat.)±0.0006(syst.)±0.0009(PDF), where the first uncertainty corresponds to data statistics, the second to systematic effects and the third to knowledge of the parton density functions. This result agrees with the current world average from the Particle Data Group fit.

Modeling and simulation of population balances for particulate processes

This work focuses on the modeling and numerical approximations of population balance equations (PBEs) for the simulation of different phenomena occurring in process engineering. The population balance equation (PBE) is considered to be a statement of continuity. It tracks the change in particle size distribution as particles are born, die, grow or leave a given control volume. In the population balance models the one independent variable represents the time, the other(s) are property coordinate(s), e.g., the particle volume (size) in the present case. They typically describe the temporal evolution of the number density functions and have been used to model various processes such as granulation, crystallization, polymerization, emulsion and cell dynamics. The semi-discrete high resolution schemes are proposed for solving PBEs modeling one and two-dimensional batch crystallization models. The schemes are discrete in property coordinates but continuous in time. The resulting ordinary differential equations can be solved by any standard ODE solver. To improve the numerical accuracy of the schemes a moving mesh technique is introduced in both one and two-dimensional cases ...

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Algorisme d'optimització global de les mesures de semblança quàntica molecular

Les Mesures de Semblança Quàntica Molecular (MSQM) requereixen la maximització del solapament de les densitats electròniques de les molècules que es comparen. En aquest treball es presenta un algorisme de maximització de les MSQM, que és global en el límit de densitatselectròniques deformades a funcions deltes de Dirac. A partir d'aquest algorisme se'n deriva l'equivalent per a densitats no deformades

Sobre les relacions lineals d'energia lliure: mesures de semblança molecular quàntica sobre funcions de densitat electrònica modificad

En aquest treball es presenta l'ús de funcions de densitat electrònica de forat de Fermi per incrementar el paper que pren una regió molecular concreta, considerada com a responsable de la reactivitat molecular, tot i mantenir la mida de la funció de densitat original. Aquestes densitats s'utilitzen per fer mesures d'autosemblança molecular quàntica i es presenten com una alternativa a l'ús de fragments moleculars aillats en estudis de relació entre estructura i propietat. El treball es complementa amb un exemple pràctic, on es correlaciona l'autosemblanca molecular a partir de densitats modificades amb l'energia d'una reacció isodòsmica

A generalization of histogram type estimators

We introduce simple nonparametric density estimators that generalize theclassical histogram and frequency polygon. The new estimators are expressed as linear combination of density functions that are piecewisepolynomials, where the coefficients are optimally chosen in order to minimize the integrated square error of the estimator. We establish the asymptotic behaviour of the proposed estimators, and study theirperformance in a simulation study.

Hypernormal densities

We propose a new family of density functions that possess both flexibilityand closed form expressions for moments and anti-derivatives, makingthem particularly appealing for applications. We illustrate its usefulnessby applying our new family to obtain density forecasts of U.S. inflation.Our methods generate forecasts that improve on standard methods based on AR-ARCH models relying on normal or Student's t-distributional assumptions.

Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Generalized Langevin equations: Anomalous diffusion and probability distributions

We study the motion of a particle governed by a generalized Langevin equation. We show that, when no fluctuation-dissipation relation holds, the long-time behavior of the particle may be from stationary to superdiffusive, along with subdiffusive and diffusive. When the random force is Gaussian, we derive the exact equations for the joint and marginal probability density functions for the position and velocity of the particle and find their solutions.

Elicitation of subjective crop yield PDF

En este trabajo se investiga la coherencia y confiabilidad de estimaciones de funciones de densidad de probabilidad (FDP) subjetivas de rendimientos de cultivos realizadas por un amplio grupo de agricultores. Se utilizaron tres técnicas de elicitación diferentes: el método de estimación de FDP en dos pasos, la distribución Triangular y la distribución Beta. Los sujetos entrevistados ofrecieron estimaciones para los valores puntuales de rendimientos de cultivos (medio, máximo posible, más frecuente y mínimo posible) y para las FDP basadas en la estimación de intervalos. Para evaluar la persistencia, se utilizaron los conceptos de persistencia temporal y persistencia metodológica. Los resultados son interesantes para juzgar la adecuación de las técnicas de estimación de probabilidades subjetivas a los sistemas de ayuda en la toma de decisiones en agricultura.

Percepción por los expertos de la función de densidad de probabilidad de los rendimientos de cultivos

En la literatura sobre determinación subjetiva de funciones de densidad de probabilidad (f.d.p.) de rendimientos de cultivos, se ha señalado que los agricultores tienden a percibir f.d.p. muy «estrechas» (con varianza baja), un resultado que coincide con el señalado en otros contextos experimentales. En este trabajo se ha constatado que investigadores y expertos en producción vegetal tienen también una pobre percepción de la forma de la f.d.p. Este sesgo en la percepción de la f.d.p. sería compartido por agricultores y expertos, estos últimos con una buena formación estadística. Sin embargo ambos grupos realizan un trabajo diario exitoso que implica frecuentemente discriminar entre f.d.p. de rendimientos de cultivos.

Segmentation d’images intravasculaires ultrasonores

L'imagerie intravasculaire ultrasonore (IVUS) est une technologie médicale par cathéter qui produit des images de coupe des vaisseaux sanguins. Elle permet de quantifier et d'étudier la morphologie de plaques d'athérosclérose en plus de visualiser la structure des vaisseaux sanguins (lumière, intima, plaque, média et adventice) en trois dimensions. Depuis quelques années, cette méthode d'imagerie est devenue un outil de choix en recherche aussi bien qu'en clinique pour l'étude de la maladie athérosclérotique. L'imagerie IVUS est par contre affectée par des artéfacts associés aux caractéristiques des capteurs ultrasonores, par la présence de cônes d'ombre causés par les calcifications ou des artères collatérales, par des plaques dont le rendu est hétérogène ou par le chatoiement ultrasonore (speckle) sanguin. L'analyse automatisée de séquences IVUS de grande taille représente donc un défi important. Une méthode de segmentation en trois dimensions (3D) basée sur l'algorithme du fast-marching à interfaces multiples est présentée. La segmentation utilise des attributs des régions et contours des images IVUS. En effet, une nouvelle fonction de vitesse de propagation des interfaces combinant les fonctions de densité de probabilité des tons de gris des composants de la paroi vasculaire et le gradient des intensités est proposée. La segmentation est grandement automatisée puisque la lumière du vaisseau est détectée de façon entièrement automatique. Dans une procédure d'initialisation originale, un minimum d'interactions est nécessaire lorsque les contours initiaux de la paroi externe du vaisseau calculés automatiquement sont proposés à l'utilisateur pour acceptation ou correction sur un nombre limité d'images de coupe longitudinale. La segmentation a été validée à l'aide de séquences IVUS in vivo provenant d'artères fémorales provenant de différents sous-groupes d'acquisitions, c'est-à-dire pré-angioplastie par ballon, post-intervention et à un examen de contrôle 1 an suivant l'intervention. Les résultats ont été comparés avec des contours étalons tracés manuellement par différents experts en analyse d'images IVUS. Les contours de la lumière et de la paroi externe du vaisseau détectés selon la méthode du fast-marching sont en accord avec les tracés manuels des experts puisque les mesures d'aire sont similaires et les différences point-à-point entre les contours sont faibles. De plus, la segmentation par fast-marching 3D s'est effectuée en un temps grandement réduit comparativement à l'analyse manuelle. Il s'agit de la première étude rapportée dans la littérature qui évalue la performance de la segmentation sur différents types d'acquisition IVUS. En conclusion, la segmentation par fast-marching combinant les informations des distributions de tons de gris et du gradient des intensités des images est précise et efficace pour l'analyse de séquences IVUS de grandes tailles. Un outil de segmentation robuste pourrait devenir largement répandu pour la tâche ardue et fastidieuse qu'est l'analyse de ce type d'images.