Prediction of Childhood Asthma Using Conditional Probability and Discrete Event Simulation

Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

On the inverse windowed Fourier transform

The inversion problem concerning the windowed Fourier transform is considered. It is shown that, out of the infinite solutions that the problem admits, the windowed Fourier transform is the "optimal" solution according to a maximum-entropy selection criterion.

The continuous wavelet transform as a maximum entropy solution of the corresponding inverse problem

The continuous wavelet transform is obtained as a maximumentropy solution of the corresponding inverse problem. It is well knownthat although a signal can be reconstructed from its wavelet transform,the expansion is not unique due to the redundancy of continuous wavelets.Hence, the inverse problem has no unique solution. If we want to recognizeone solution as "optimal", then an appropriate decision criterion hasto be adopted. We show here that the continuous wavelet transform is an"optimal" solution in a maximum entropy sense.

On wideband deconvolution using wavelet transform

A discussion on the expression proposed in [1]–[3]for deconvolving the wideband density function is presented. Weprove here that such an expression reduces to be proportionalto the wideband correlation receiver output, or continuous wavelettransform of the received signal with respect to the transmittedone. Moreover, we show that the same result has been implicitlyassumed in [1], when the deconvolution equation is derived. Westress the fact that the analyzed approach is just the orthogonalprojection of the density function onto the image of the wavelettransform with respect to the transmitted signal. Consequently,the approach can be considered a good representation of thedensity function only under the prior knowledge that the densityfunction belongs to such a subspace. The choice of the transmittedsignal is thus crucial to this approach.

Unidirectional quantum walks: Evolution and exit times

In this paper we focus our attention on a particle that follows a unidirectional quantum walk, an alternative version of the currently widespread discrete-time quantum walk on a line. Here the walker at each time step can either remain in place or move in a fixed direction, e.g., rightward or upward. While both formulations are essentially equivalent, the present approach leads us to consider discrete Fourier transforms, which eventually results in obtaining explicit expressions for the wave functions in terms of finite sums and allows the use of efficient algorithms based on the fast Fourier transform. The wave functions here obtained govern the probability of finding the particle at any given location but determine as well the exit-time probability of the walker from a fixed interval, which is also analyzed.

Indicators for the characterization of discrete Choquet integrals

Ordered weighted averaging (OWA) operators and their extensions are powerful tools used in numerous decision-making problems. This class of operator belongs to a more general family of aggregation operators, understood as discrete Choquet integrals. Aggregation operators are usually characterized by indicators. In this article four indicators usually associated with the OWA operator are extended to discrete Choquet integrals: namely, the degree of balance, the divergence, the variance indicator and Renyi entropies. All of these indicators are considered from a local and a global perspective. Linearity of indicators for linear combinations of capacities is investigated and, to illustrate the application of results, indicators of the probabilistic ordered weighted averaging -POWA- operator are derived. Finally, an example is provided to show the application to a specific context.

Discrete distributions when modeling the disability severity score of motor victims

Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

Modelling syntectonic sedimentation: combining a discrete element model of tectonic. Deformation and process-based sedimentary Model in 3D.

This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.

An octree isosurface codification based on discrete planes

Describes a method to code a decimated model of an isosurface on an octree representation while maintaining volume data if it is needed. The proposed technique is based on grouping the marching cubes (MC) patterns into five configurations according the topology and the number of planes of the surface that are contained in a cell. Moreover, the discrete number of planes on which the surface lays is fixed. Starting from a complete volume octree, with the isosurface codified at terminal nodes according to the new configuration, a bottom-up strategy is taken for merging cells. Such a strategy allows one to implicitly represent co-planar faces in the upper octree levels without introducing any error. At the end of this merging process, when it is required, a reconstruction strategy is applied to generate the surface contained in the octree intersected leaves. Some examples with medical data demonstrate that a reduction of up to 50% in the number of polygons can be achieved

Programació d'una aplicació gràfica per l'anàlisi de senyals usant LDB (Local Discriminant Bases) i MLDB (Modified LDB)

Tot seguit presentem un entorn per analitzar senyals de tot tipus amb LDB (Local Discriminant Bases) i MLDB (Modified Local Discriminant Bases). Aquest entorn utilitza funcions desenvolupades en el marc d’una tesi en fase de desenvolupament. Per entendre part d’aquestes funcions es requereix un nivell de coneixement avançat de processament de senyals. S’han extret dels treballs realitzats per Naoki Saito [3], que s’han agafat com a punt de partida per la realització de l’algorisme de la tesi doctoral no finalitzada de Jose Antonio Soria. Aquesta interfície desenvolupada accepta la incorporació de nous paquets i funcions. Hem deixat un menú preparat per integrar Sinus IV packet transform i Cosine IV packet transform, tot i que també podem incorporar-n’hi altres. L’aplicació consta de dues interfícies, un Assistent i una interfície principal. També hem creat una finestra per importar i exportar les variables desitjades a diferents entorns. Per fer aquesta aplicació s’han programat tots els elements de les finestres, en lloc d’utilitzar el GUIDE (Graphical User Interface Development Enviroment) de MATLAB, per tal que sigui compatible entre les diferents versions d’aquest programa. En total hem fet 73 funcions en la interfície principal (d’aquestes, 10 pertanyen a la finestra d’importar i exportar) i 23 en la de l’Assistent. En aquest treball només explicarem 6 funcions i les 3 de creació d’aquestes interfícies per no fer-lo excessivament extens. Les funcions que explicarem són les més importants, ja sigui perquè s’utilitzen sovint, perquè, segons la complexitat McCabe, són les més complicades o perquè són necessàries pel processament del senyal. Passem cada entrada de dades per part de l’usuari per funcions que ens detectaran errors en aquesta entrada, com eliminació de zeros o de caràcters que no siguin números, com comprovar que són enters o que estan dins dels límits màxims i mínims que li pertoquen.