Fluctuating commutative geometry

We use the framework of noncommutative geometry to define a discrete model for fluctuating geometry. Instead of considering ordinary geometry and its metric fluctuations, we consider generalized geometries where topology and dimension can also fluctuate. The model describes the geometry of spaces with a countable number n of points. The spectral principle of Connes and Chamseddine is used to define dynamics. We show that this simple model has two phases. The expectation value , the average number of points in the universe, is finite in one phase and diverges in the other. Moreover, the dimension delta is a dynamical observable in our model, and plays the role of an order parameter. The computation of is discussed and an upper bound is found, < 2. We also address another discrete model defined on a fixed d = 1 dimension, where topology fluctuates. We comment on a possible spontaneous localization of topology.

Universalidade em matrizes aleatórias via problemas de Riemann-Hilbert

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise de ambiguidade em métodos de campo potenciais através de análise fatorial, Q-Modal

Este trabalho apresenta uma metodologia para o estudo da ambiguidade na interpretação de dados geofísicos. Várias soluções alternativas, representativas da região de maior ambiguidade no espaço de parâmetros são obtidas, sendo posteriormente grupadas e ordenadas pela análise fatorial modo Q. Esta metodologia foi aplicada a dados sintéticos de campo potencial simulando-se causas de ambiguidade como discretização e truncamento da anomalia e a presença de ruídos aleatório e geológico. Um único prisma foi usado como modelo interpretativo, sendo a espessura a principal causa de ambiguidade tanto na gravimetria como na magnetometria. Segue-se a profundidade do topo sempre associada à espessura, quando o sinal da anomalia é alto. Quando a anomalia tem sinal baixo, a largura torna-se o segundo parâmetro mais importante, também associada à espessura. Ao contrário da presença de interferências geológicas, a presença de ruído aleatório nos campos, não é fator importante na ambiguidade. A aplicação da metodologia a dados reais ilustra o papel desta análise na caracterização de soluções alternativas e a importância da informação a priori na caracterização das causas de ambiguidade. A metodologia apresentada pode ser empregada em diversos estágios de um programa de prospecção fornecendo em cada estágio uma análise dos principais fatores causadores da ambiguidade, que poderá ser util no planejamento dos estágios seguintes. Comparada a outros métodos de análise de ambiguidade, como por exemplo regiões de confiança, a metodologia estudada destaca-se por não precisar satisfazer premissas estatísticas sobre a distribuição dos erros.

Análise comparativa de três métodos de inversão aplicados a dados gravimétricos e magnéticos em perfil

Tradicionalmente, o método dos mínimos quadrados tem sido empregado na inversão não linear de dados de campo potencial. No caso em que as observações dos campos gravimétrico ou magnético contém apenas ruído Gaussiano. O método dos mínimos quadrados não apresenta problemas. Entretanto, quando as observações são perturbadas por ruído não Gaussiano, ou mesmo por ruído não aleatório, como é o caso de muitos ruídos geológicos, o método dos mínimos quadrados torna-se bastante ineficiente, e métodos alternativos devem ser empregados a fim de produzir interpretações realísticas. Neste trabalho, uma comparação é feita entre os métodos dos mínimos quadrados, dos mínimos absolutos e do ajuste-M, aplicados à inversão não linear de dados de campo potencial. A comparação é efetuada usando-se dados teóricos, onde diversas situações geológicas são simuladas. Os resultados mostram que na presença de ruído geológico, caracterizado por pequeno corpo raso acima do corpo principal, ou por corpo grande, adjacente ao corpo principal, o ajuste-M apresenta desempenho muito superior ao dos mínimos quadrados e dos mínimos absolutos. Na presença de ruído Gaussiano, entretanto, o ajuste-M tem um desempenho inferior aos outros dois métodos. Como o ruído Gaussiano é um ruído branco, parte dele pode ser removido por um filtro passa baixa adequado, sem muita perda do sinal, o que não ocorre com o ruído geológico que contém componentes importantes de baixo número de onda. Desse modo o ajuste-M se torna uma ferramenta importante na interpretação de áreas geologicamente complexas, onde é comum a contaminação das anomalias por ruído geológico. Os três métodos em estudo são aplicados a uma anomalia magnética real causada por uma intrusão de diabásio em forma de dique, em sedimentos arenosos da formação Piauí na Bacia do Parnaíba. Os três métodos apresentaram resultados semelhantes indicando que tanto o nível de ruído Gaussiano como geológico são baixos nesta anomalia.

Use of a Single L1 GPS Receiver for Monitoring Structures: First Results of the Detection of Millimetric Dynamic Oscillations

This paper presents preliminary results to determine small displacements of a global positioning system (GPS) antenna fastened to a structure using only one L1 GPS receiver. Vibrations, periodic or not, are common in large structures, such as bridges, footbridges, tall buildings, and towers under dynamic loads. The behavior in time and frequency leads to structural analysis studies. The hypothesis of this article is that any large structure that presents vibrations in the centimeter-to-millimeter range can be monitored by phase measurements of a single L1 receiver with a high data rate, as long as the direction of the displacement is pointing to a particular satellite. Within this scenario, the carrier phase will be modulated by antenna displacement. During a period of a few dozen seconds, the relative displacement to the satellite, the satellite clock, and the atmospheric phase delays can be assumed as a polynomial time function. The residuals from a polynomial adjustment contain the phase modulation owing to small displacements, random noise, receiver clock short time instabilities, and multipath. The results showed that it is possible to detect displacements of centimeters in the phase data of a single satellite and millimeters in the difference between the phases of two satellites. After applying a periodic nonsinusoidal displacement of 10 m to the antenna, it is clearly recovered in the difference of the residuals. The time domain spectrum obtained by the fast Fourier transform (FFT) exhibited a defined peak of the third harmonic much more than the random noise using the proposed third-degree polynomial model. DOI: 10.1061/(ASCE)SU.1943-5428.0000070. (C) 2012 American Society of Civil Engineers.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Quantifying the periodicty of Inter Movement Intervals of Leg Movements

ims: Periodic leg movements in sleep (PLMS) are a frequent finding in polysomnography. Most patients with restless legs syndrome (RLS) display PLMS. However, since PLMS are also often recorded in healthy elderly subjects, the clinical significance of PLMS is still discussed controversially. Leg movements are seen concurrently with arousals in obstructive sleep apnoea (OSA) may also appear periodically. Quantitative assessment of the periodicity of LM/PLM as measured by inter movement intervals (IMI) is difficult. This is mainly due to influencing factors like sleep architecture and sleep stage, medication, inter and intra patient variability, the arbitrary amplitude and sequence criteria which tend to broaden the IMI distributions or make them even multi-modal. Methods: Here a statistical method is presented that enables eliminating such effects from the raw data before analysing the statistics of IMI. Rather than studying the absolute size of IMI (measured in seconds) we focus on the shape of their distribution (suitably normalized IMI). To this end we employ methods developed in Random Matrix Theory (RMT). Patients: The periodicity of leg movements (LM) of four patient groups (10 to 15 each) showing LM without PLMS (group 1), OSA without PLMS (group 2), PLMS and OSA (group 3) as well as PLMS without OSA (group 4) are compared. Results: The IMI of patients without PLMS (groups 1 and 2) and with PLMS (groups 3 and 4) are statistically different. In patients without PLMS the distribution of normalized IMI resembles closely the one of random events. In contrary IMI of PLMS patients show features of periodic systems (e.g. a pendulum) when studied in normalized manner. Conclusions: For quantifying PLMS periodicity proper normalization of the IMI is crucial. Without this procedure important features are hidden when grouping LM/PLM over whole nights or across patients. The clinical significance of PLMS might be eluded when properly separating random LM from LM that show features of periodic systems.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

Vibrations, Posture, and the Stabilization of Gaze: An Experimental Study on Impedance Control

Vibrations, Posture, and the Stabilization of Gaze: An Experimental Study on Impedance Control R. KREDEL, A. GRIMM & E.-J. HOSSNER University of Bern, Switzerland Introduction Franklin and Wolpert (2011) identify impedance control, i.e., the competence to resist changes in position, velocity or acceleration caused by environmental disturbances, as one of five computational mechanisms which allow for skilled and fluent sen-sorimotor behavior. Accordingly, impedance control is of particular interest in situa-tions in which the motor task exhibits unpredictable components as it is the case in downhill biking or downhill skiing. In an experimental study, the question is asked whether impedance control, beyond its benefits for motor control, also helps to stabi-lize gaze what, in turn, may be essential for maintaining other control mechanisms (e.g., the internal modeling of future states) in an optimal range. Method In a 3x2x4 within-subject ANOVA design, 72 participants conducted three tests on visual acuity and contrast (Landolt / Grating and Vernier) in two different postures (standing vs. squat) on a platform vibrating at four different frequencies (ZEPTOR; 0 Hz, 4 Hz, 8 Hz, 12 Hz; no random noise; constant amplitude) in a counterbalanced or-der with 1-minute breaks in-between. In addition, perceived exertion (Borg) was rated by participants after each condition. Results For Landolt and Grating, significant main effects for posture and frequency are re-vealed, representing lower acuity/contrast thresholds for standing and for higher fre-quencies in general, as well as a significant interaction (p < .05), standing for in-creasing posture differences with increasing frequencies. Overall, performance could be maintained at the 0 Hz/standing level up to a frequency of 8 Hz, if bending of the knees was allowed. The fact that this result is not only due to exertion is proved by the Borg ratings showing significant main effects only, i.e., higher exertion scores for standing and for higher frequencies, but no significant interaction (p > .40). The same pattern, although not significant, is revealed for the Vernier test. Discussion Apparently, postures improving impedance control not only turn out to help to resist disturbances but also assist in stabilizing gaze in spite of these perturbations. Con-sequently, studying the interaction of these control mechanisms in complex unpre-dictable environments seems to be a fruitful field of research for the future. References Franklin, D. W., & Wolpert, D. M. (2011). Computational mechanisms of sensorimotor control. Neuron, 72, 425-442.

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill sampling criteria balancing exploitation and exploration such as the Expected Hypervolume Improvement. Here we consider Kriging metamodels not only for selecting new points, but as a tool for estimating the whole Pareto front and quantifying how much uncertainty remains on it at any stage of Kriging-based multi-objective optimization algorithms. Our approach relies on the Gaussian process interpretation of Kriging, and bases upon conditional simulations. Using concepts from random set theory, we propose to adapt the Vorob’ev expectation and deviation to capture the variability of the set of non-dominated points. Numerical experiments illustrate the potential of the proposed workflow, and it is shown on examples how Gaussian process simulations and the estimated Vorob’ev deviation can be used to monitor the ability of Kriging-based multi-objective optimization algorithms to accurately learn the Pareto front.

Implementación de instrumentación virtual con LaBVIEW

El objetivo del PFC es el diseño e implementación de una aplicación que funcione como osciloscopio, analizador de espectro y generador de funciones virtual, todo dentro de la misma aplicacion. Mediante una tarjeta de adquisición de datos tomaremos muestras de señales del mundo real (sistema analógico) para generar datos que puedan ser manipulados por un ordenador (sistema digital). Con esta misma tarjeta también se podrán generar señales básicas, tales como señales senoidales, cuadradas.... y además se ha añadido la funcionalidad de generar señales moduladas en frecuencia, señales tipo Chirp (usadas comúnmente tanto en aplicaciones sonar y radar, como en transmisión óptica) o PRN (ruido pseudo-aleatorio que consta de una secuencia determinista de pulsos que se repite cada periodo, usada comúnmente en receptores GPS), como también señales ampliamente conocidas como el ruido blanco Gaussiano o el ruido blanco uniforme. La aplicación mostrará con detalle las señales adquiridas y analizará de diversas maneras esas señales. Posee la función de enventanado de los tipos de ventana mas comunes, respuesta en frecuencia, transformada de Fourier, etc. La configuración es elegida por el usuario en un entorno amigable y de visualización atractiva. The objective of the PFC is the design and implementation of an application that works as oscilloscope, spectrum analyzer and virtual signal generator, all within the same application. Through a data acquisition card, the user can take samples of real-world signals (analog system) to generate data that can be manipulated by a computer (digital system). This same card can also generate basic signals, such as sine waves, square waves, sawtooth waves.... and further has added other functionalities as frequency modulated signals generation, Chirp signals type generation (commonly used in both sonar and radar applications, such as optical transmission) or PRN (pseudo-random noise sequence comprising a deterministic pulse that repeats every period, commonly used in GPS receivers). It also can generate widely known as Gaussian white noise signals or white noise uniform signals. The application will show in detail the acquired signals and will analyze these signals in different ways selected by the user. Windowing function has the most common window types, frequency response, Fourier transform are examples of what kind of analyzing that can be processed. The configuration is chosen by the user throught friendly and attractive displays and panels.

Experimental evidence of a hard transition to chaos

A generic, sudden transition to chaos has been experimentally verified using electronic circuits. The particular system studied involves the near resonance of two coupled oscillators at 2:1 frequency ratio when the damping of the first oscillator becomes negative. We identified in the experiment all types of orbits described by theory. We also found that a theoretical, ID limit map fits closely a map of the experimental attractor which, however, could be strongly disturbed by noise. In particular, we found noisy periodic orbits, in good agreement with noise theory.

Algoritmos genéticos en control activo de ruido

Este proyecto se centra en la implementación de un sistema de control activo de ruido mediante algoritmos genéticos. Para ello, se ha tenido en cuenta el tipo de ruido que se quiere cancelar y el diseño del controlador, parte fundamental del sistema de control. El control activo de ruido sólo es eficaz a bajas frecuencias, hasta los 250 Hz, justo para las cuales los elementos pasivos pierden efectividad, y en zonas o recintos de pequeñas dimensiones y conductos. El controlador ha de ser capaz de seguir todas las posibles variaciones del campo acústico que puedan producirse (variaciones de fase, de frecuencia, de amplitud, de funciones de transferencia electro-acústicas, etc.). Su funcionamiento está basado en algoritmos FIR e IIR adaptativos. La elección de un tipo de filtro u otro depende de características tales como linealidad, causalidad y número de coeficientes. Para que la función de transferencia del controlador siga las variaciones que surgen en el entorno acústico de cancelación, tiene que ir variando el valor de los coeficientes del filtro mediante un algoritmo adaptativo. En este proyecto se emplea como algoritmo adaptativo un algoritmo genético, basado en la selección biológica, es decir, simulando el comportamiento evolutivo de los sistemas biológicos. Las simulaciones se han realizado con dos tipos de señales: ruido de carácter aleatorio (banda ancha) y ruido periódico (banda estrecha). En la parte final del proyecto se muestran los resultados obtenidos y las conclusiones al respecto. Summary. This project is focused on the implementation of an active noise control system using genetic algorithms. For that, it has been taken into account the noise type wanted to be canceled and the controller design, a key part of the control system. The active noise control is only effective at low frequencies, up to 250 Hz, for which the passive elements lose effectiveness, and in small areas or enclosures and ducts. The controller must be able to follow all the possible variations of the acoustic field that might be produced (phase, frequency, amplitude, electro-acoustic transfer functions, etc.). It is based on adaptive FIR and IIR algorithms. The choice of a kind of filter or another depends on characteristics like linearity, causality and number of coefficients. Moreover, the transfer function of the controller has to be changing filter coefficients value thought an adaptive algorithm. In this project a genetic algorithm is used as adaptive algorithm, based on biological selection, simulating the evolutionary behavior of biological systems. The simulations have been implemented with two signal types: random noise (broadband) and periodic noise (narrowband). In the final part of the project the results and conclusions are shown.

Contribution of individual to collective brands

Traditionally, literature estimates the equity of a brand or its extension but it pays little attention to collective brand equity even though collective branding is increasingly used to differentiate the homogenous products of different firms or organizations. We propose an approach that estimates the incremental effect of individual brands (or the contribution of individual brands) on collective brand equity through the various stages of a consumer hierarchical buying choice process in which decisions are nested: “whether to buy”, “what collective brand to buy” and “what individual brand to buy”. This proposal follows the approach of the Random Utility Theory, and it is theoretically argued through the Associative Networks Theory and the cybernetic model of decision making. The empirical analysis carried out in the area of collective brands in Spanish tourism finds a three-stage hierarchical sequence, and estimates the contribution of individual brands to the equity of the collective brands of “Sun, Sea and Sand” and of “World Heritage Cities”.

Evidence of altered prefrontal-thalamic circuitry in schizophrenia: An optimised diffusion MRI study

MRI diffusion tensor imaging (DTI), optimized for measuring the trace of the diffusion tensor, was used to investigate microstructural changes in the brains of 12 individuals with schizophrenia compared with 12 matched control subjects. To control for the effects of anatomic variation between subject groups, all participants' diffusion images were non-linearly registered to standard anatomical space. Significant statistical differences in mean diffusivity (MD) measures between the two groups were determined on a pixel-by-pixel basis, using Gaussian random field theory. We found significantly elevated MD measures within temporal, parietal and prefrontal cortical regions in the schizophrenia group (P > 0.001), especially within the medial frontal gyrus and anterior cingulate. The dorsal medial and anterior nucleus of the thalamus, including the caudate, also exhibited significantly increased MD in the schizophrenia group (P > 0.001). This study has shown for the first time that MD measures offer an alternative strategy for investigating altered prefrontal-thalamic circuitry in schizophrenia. (c) 2006 Elsevier Inc. All rights reserved.