M. Fernández-Martínez

Prevalence of dementia and major dementia subtypes in Spanish populations: A reanalysis of dementia prevalence surveys, 1990-2008

BackgroundThis study describes the prevalence of dementia and major dementia subtypes in Spanish elderly.MethodsWe identified screening surveys, both published and unpublished, in Spanish populations, which fulfilled specific quality criteria and targeted prevalence of dementia in populations aged 70 years and above. Surveys covering 13 geographically different populations were selected (prevalence period: 1990-2008). Authors of original surveys provided methodological details of their studies through a systematic questionnaire and also raw age-specific data. Prevalence data were compared using direct adjustment and logistic regression.ResultsThe reanalyzed study population (aged 70 year and above) was composed of Central and North-Eastern Spanish sub-populations obtained from 9 surveys and totaled 12,232 persons and 1,194 cases of dementia (707 of Alzheimers disease, 238 of vascular dementia). Results showed high variation in age- and sex-specific prevalence across studies. The reanalyzed prevalence of dementia was significantly higher in women; increased with age, particularly for Alzheimers disease; and displayed a significant geographical variation among men. Prevalence was lowest in surveys reporting participation below 85%, studies referred to urban-mixed populations and populations diagnosed by psychiatrists.ConclusionPrevalence of dementia and Alzheimers disease in Central and North-Eastern Spain is higher in females, increases with age, and displays considerable geographic variation that may be method-related. People suffering from dementia and Alzheimers disease in Spain may approach 600,000 and 400,000 respectively. However, existing studies may not be completely appropriate to infer prevalence of dementia and its subtypes in Spain until surveys in Southern Spain are conducted.

Prevalence and European comparison of dementia in a ≥75-year-old composite population in Spain.

Virués‐Ortega J, de Pedro‐Cuesta J, Vega S, Seijo‐Martínez M, Saz P, Rodríguez F, Rodríguez‐Laso Á, Reñé R, de las Heras SP, Mateos R, Martínez‐Martín P, Mahillo‐Fernández I, López‐Pousa S, Lobo A, Reglà JL, Gascón J, García FJ, Fernández‐Martínez M, Boix R, Bermejo‐Pareja F, Bergareche A, Sánchez‐Sánchez F, de Arce A, del Barrio JL; On behalf of the Spanish Epidemiological Studies on Ageing Group. Prevalence and European comparison of dementia in a ≥75‐year‐old composite population in Spain. 
Acta Neurol Scand: 2011: 123: 316–324. 
© 2010 John Wiley & Sons A/S.

Comparación entre biodanza en medio acuático y stretching en la mejora de la calidad de vida y dolor en los pacientes con fibromialgia

OBJECTIVE To determine the level of improvement, as regards pain, impact on fibromyalgia and depression, achieved by patients with fibromyalgia by comparing aquatic biodanza and stretching exercises. DESIGN Randomised controlled trial with two intervention groups. LOCATION Five health centres (Almeria). PATIENTS A total of 82 fibromyalgia patients between 18 and 65 years old, diagnosed by American College of Rheumatology criteria, were included, with 12 patients declining to take part in the study. The 70 remaining patients were randomly assigned to two groups of 35 patients each: aquatic biodanza and stretching exercises. Those who did not attend in at least 14 sessions or changed their treatment during the studio were excluded. The final sample consisted of 19 patients in aquatic biodanza group and 20 in stretching group. The limitations of the study included, the open evaluation design and a sample size reduced by defaults. MAIN MEASURES The outcome measures were sociodemographic data, quality of life (Fibromyalgia Impact Questionnaire), pain (McGill-Melzack questionnaire; and Visual Analogue Scale), pressure algometry (Wagner FPI10 algometer) and depression (Beck Inventory). These were carried out before and after a 12-week therapy. RESULTS The mean age of the sample was 55.41 years. The mean period from diagnosis was 13.44 years. The sample consisted mainly of housewives. There were significant differences (P<.05) between groups, in pain (P<.01), fibromyalgia impact (P<.01), and depression (P<.04) after the treatment. CONCLUSIONS The biodanza aquatic exercises improve pain and quality of life in fibromyalgia patients.

A comparison of three Hurst exponent approaches to predict nascent bubbles in S&P500 stocks

In this paper, three approaches to calculate the self-similarity exponent of a time series are compared in order to determine which one performs best to identify the transition from random efficient market behavior (EM) to herding behavior (HB) and hence, to find out the beginning of a market bubble. In particular, classical Detrended Fluctuation Analysis (DFA), Generalized Hurst Exponent (GHE) and GM2 (one of Geometric Method-based algorithms) were applied for self-similarity exponent calculation purposes. Traditionally, researchers have been focused on identifying the beginning of a crash. Instead of this, we are pretty interested in identifying the beginning of the transition process from EM to a market bubble onset, what we consider could be more interesting. The relevance of self-similarity index in such a context lies on the fact that it becomes a suitable indicator which allows to identify the raising of HB in financial markets. Overall, we could state that the greater the self-similarity exponent in financial series, the more likely the transition process to HB could start. This fact is illustrated through actual S\&P500 stocks.

Fractal dimension for fractal structures: Applications to the domain of words

Abstract A fractal structure is a tool that is used to study the fractal behavior of a space. In this paper, we show how to apply a new concept of fractal dimension for fractal structures, extending the use of the box-counting dimension to new contexts. In particular, we define a fractal structure on the domain of words and show how to use the new fractal dimension to study the fractal pattern of a language generated by a regular expression, how to calculate the efficiency of an encoding language and how to estimate the number of nodes of a given depth in a search tree.

How to calculate the Hausdorff dimension using fractal structures

In this paper, we provide the first known overall algorithm to calculate the Hausdorff dimension of any compact Euclidean subset. This novel approach is based on both a new discrete model of fractal dimension for a fractal structure which considers finite coverings and a theoretical result that the authors contributed previously in 14]. This new procedure combines fractal techniques with tools from Machine Learning Theory. In particular, we use a support vector machine to decide the value of the Hausdorff dimension. In addition to that, we artificially generate a wide collection of examples that allows us to train our algorithm and to test its performance by external proof. Some analyses about the accuracy of this approach are also provided.

Testing the Self-Similarity Exponent to Feature Extraction in Motor Imagery Based Brain Computer Interface Systems

A Brain Computer Interface (BCI) system is a tool not requiring any muscle action to transmit information. Acquisition, preprocessing, feature extraction (FE), and classification of electroencephalograph (EEG) signals constitute the main steps of a motor imagery BCI. Among them, FE becomes crucial for BCI, since the underlying EEG knowledge must be properly extracted into a feature vector. Linear approaches have been widely applied to FE in BCI, whereas nonlinear tools are not so common in literature. Thus, the main goal of this paper is to check whether some Hurst exponent and fractal dimension based estimators become valid indicators to FE in motor imagery BCI. The final results obtained were not optimal as expected, which may be due to the fact that the nature of the analyzed EEG signals in these motor imagery tasks were not self-similar enough.

Near-Earth object hazardous impact: A Multi-Criteria Decision Making approach

The impact of a near-Earth object (NEO) may release large amounts of energy and cause serious damage. Several NEO hazard studies conducted over the past few years provide forecasts, impact probabilities and assessment ratings, such as the Torino and Palermo scales. These high-risk NEO assessments involve several criteria, including impact energy, mass, and absolute magnitude. The main objective of this paper is to provide the first Multi-Criteria Decision Making (MCDM) approach to classify hazardous NEOs. Our approach applies a combination of two methods from a widely utilized decision making theory. Specifically, the Analytic Hierarchy Process (AHP) methodology is employed to determine the criteria weights, which influence the decision making, and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is used to obtain a ranking of alternatives (potentially hazardous NEOs). In addition, NEO datasets provided by the NASA Near-Earth Object Program are utilized. This approach allows the classification of NEOs by descending order of their TOPSIS ratio, a single quantity that contains all of the relevant information for each object.

Counterexamples for IFS-attractors

Abstract In this paper, we deal with the part of Fractal Theory related to finite families of (weak) contractions, called iterated function systems (IFS, herein). An attractor is a compact set which remains invariant for such a family. Thus, we consider spaces homeomorphic to attractors of either IFS or weak IFS, as well, which we will refer to as Banach and topological fractals, respectively. We present a collection of counterexamples in order to show that all the presented definitions are essential, though they are not equivalent in general.

Optimal sampling patterns for Zernike polynomials

A pattern of interpolation nodes on the disk is studied, for which the interpolation problem is theoretically unisolvent, and which renders a minimal numerical condition for the collocation matrix when the standard basis of Zernike polynomials is used. It is shown that these nodes have an excellent performance also from several alternative points of view, providing a numerically stable surface reconstruction, starting from both the elevation and the slope data. Sampling at these nodes allows for a more precise recovery of the coefficients in the Zernike expansion of a wavefront or of an optical surface.