Fractal dimension for Gaussian colored processes

The exact analytical expression for the Hausdorff dimension of free processes driven by Gaussian noise in n-dimensional space is obtained. The fractal dimension solely depends on the time behavior of the arbitrary correlation function of the noise, ranging from DX=1 for Orstein-Uhlenbeck input noise to any real number greater than 1 for fractional Brownian motions.

Comments on "On the relationship between fractal dimension and the performance of multi-resonant dipole antennas using Koch curves"

Comentaris referits a l'article següent: K. J. Vinoy, J. K. Abraham, and V. K. Varadan, “On the relationshipbetween fractal dimension and the performance of multi-resonant dipoleantennas using Koch curves,” IEEE Transactions on Antennas and Propagation, 2003, vol. 51, p. 2296–2303.

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.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

On Hyperbolic once-punctured-torus bundles II. Fractal tessellations of the plane

We describe fractal tessellations of the complex plane that arise naturally from Cannon-Thurston maps associated to complete, hyperbolic, once-punctured-torus bundles. We determine the symmetry groups of these tessellations.

Hopf bifurcation for degenerate singular points of multiplicity 2n-1 in dimension 3

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The Cuntz semigroup, the Elliott conjecture, and dimension functions on C*-Algebras

We prove that the Cuntz semigroup is recovered functorially from the Elliott invariant for a large class of C¤-algebras. In particular, our results apply to the largest class of simple C¤-algebras for which K-theoretic classification can be hoped for. This work has three significant consequences. First, it provides new conceptual insight into Elliott's classification program, proving that the usual form of the Elliott conjecture is equivalent, among Z-stable algebras, to a conjecture which is in general substantially weaker and for which there are no known counterexamples. Second and third, it resolves, for the class of algebras above, two conjectures of Blackadar and Handelman concerning the basic structure of dimension functions on C¤-algebras. We also prove in passing that the Kuntz-Pedersen semigroup is recovered functorially from the Elliott invariant for all simple unital C¤-algebras of interest.

The ‘Global Dimension’ of Contemporary Politics. An Argument for Taking ‘Global’ Seriously

Recent years have seen a striking proliferation of the term ‘global’ in public and political discourse. The popularity of the term is a manifestation of the fact that there is a widespread notion that contemporary social reality is ‘global’. The acknowledgment of this notion has important political implications and raises questions about the role played by the idea of the ‘global’ in policy making. These questions, in turn, expose even more fundamental issues about whether the term ‘global’ indicates a difference in kind, even an ontological shift, and, if so, how to approach it. This paper argues that the notion of ‘global’, in other words the ‘global dimension’, is a significant aspect of contemporary politics that needs to be investigated. The paper argues that in the globalization discourse of International Studies ‘global’ is ‘naturalized’, which means that it is taken for granted and assumed to be self-evident. The term ‘global’ is used mainly in a descriptive way and subsumed under the rubric of ‘globalization’. ‘Global’ tends to be equated with transnational and/or world-wide; hence, it addresses quantitative differences in degree but not (alleged) differences in kind. In order to advance our understanding of contemporary politics, ‘global’ needs to be taken seriously. This means, firstly, to understand and to conceptualize ‘global’ as a social category; and, secondly, to uncover ‘global’ as a ‘naturalized’ concept in the Political and International Studies strand of the globalization discourse in order to rescue it for innovative new approaches in the investigation of contemporary politics. In order to do so, the paper suggests adopting a strong linguistic approach starting with the analysis of the word ‘global’. Based on insights from post-structuralism as well as cognitive and general constructivist perspectives it argues that a frame-based corpus linguistic analysis offers the possibility of investigating the collective/social meaning(s) of global in order to operationalize them for the analysis of the ‘global dimension’ of contemporary politics.

Monopoles in arbitrary dimension

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Blow-up, concentration phenomenon and global existence for the Keller-Segel model in high dimension

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Gaussian estimates for the density of the non-linear stochastic heat equation in any space dimension

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

Temperamental Dimension and Anxiety Problems in a Clinical Sample of Three- to Six-year old Children: A Study of Variables

In the last few years, many researchers have studied the presence of common dimensions of temperament in subjects with symptoms of anxiety. The aim of this study is to examine the association between temperamental dimensions (high negative affect and activity level) and anxiety problems in clinicalpreschool children. A total of 38 children, ages 3 to 6 years, from the Infant and Adolescent Mental Health Center of Girona and the Center of Diagnosis and Early Attention of Sabadell and Olot were evaluated by parents and psychologists. Their parents completed several screening scales and, subsequently, clinical child psychopathology professionals carried out diagnostic interviews with children from the sample who presented signs of anxiety. Findings showed that children with high levels of negative affect and low activity level have pronounced symptoms of anxiety. However, children with anxiety disorders do not present different temperament styles from their peers without these pathologies

Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size

This paper analyzes whether standard covariance matrix tests work whendimensionality is large, and in particular larger than sample size. Inthe latter case, the singularity of the sample covariance matrix makeslikelihood ratio tests degenerate, but other tests based on quadraticforms of sample covariance matrix eigenvalues remain well-defined. Westudy the consistency property and limiting distribution of these testsas dimensionality and sample size go to infinity together, with theirratio converging to a finite non-zero limit. We find that the existingtest for sphericity is robust against high dimensionality, but not thetest for equality of the covariance matrix to a given matrix. For thelatter test, we develop a new correction to the existing test statisticthat makes it robust against high dimensionality.

The left-right dimension in Latin America

We present voters' self-placement and 68 political party locations on the left-right dimension in 17 Latin American countries. Innovative calculations are based on data from Latinobarometer annual surveys from 1995 to 2002. Our preliminary analysis of the results suggests that most Latin American voters are relatively highly ideological and rather consistently located on the left-right dimension, but they have very high levels of political alienation regarding the party system. Both voters' self-placement and the corresponding party locations are presently highly polarized between the center and the right, with a significant weakness of leftist or broadly appealing 'populist' positions.