An approximate solution method for boundary layer flow of a power law fluid over a flat plate

The work in this paper deals with the development of momentum and thermal boundary layers when a power law fluid flows over a flat plate. At the plate we impose either constant temperature, constant flux or a Newton cooling condition. The problem is analysed using similarity solutions, integral momentum and energy equations and an approximation technique which is a form of the Heat Balance Integral Method. The fluid properties are assumed to be independent of temperature, hence the momentum equation uncouples from the thermal problem. We first derive the similarity equations for the velocity and present exact solutions for the case where the power law index n = 2. The similarity solutions are used to validate the new approximation method. This new technique is then applied to the thermal boundary layer, where a similarity solution can only be obtained for the case n = 1.

The impact of agglomeration effects and accessibility on wages

This paper contributes to the empirical literature on the effects of agglomeration and road accessibility on productivity of firms by looking at the case of Spain. We approach productivity indirectly by using individual wages allocated at the NUTS III level. We use a repeated cross-section of individual micro-data for the years 1995, 2002 and 2006. The availability of interprovincial travel time data for each of the three years allows controlling for transport improvements over the period by using a market potential variable. Additionally, agglomeration is approached by employment density and we control for localization economies, human capital externalities and a large set of individual and workplace characteristics. Estimating by instrumental variables, our results show a positive and significant effect of market accessibility on wages and non linear effect for employment density.

Male vs Female Lupus. A comparison of ethnicity, clinical features, serology and outcome over a 30 year period

Un estudi observacional de pacients amb LES, atesos al University College de London Hospital entre 1976 i 2005, es va dur a terme per revisar les diferències entre homes i dones amb lupus pel que fa a les característiques clíniques, serologia i resultats. 439 dones i 45 homes van ser identificats. L'edat mitjana al diagnòstic va ser de 29,3 anys (12,6), sense diferències significatives entre homes i dones. El sexe femení es va associar significativament amb la presència d'úlceres orals i Ig M ACA. No hi va haver diferències significatives en la comparació de les altres variables. Durant aquest període de seguiment de trenta anys, relativament poques diferències han sorgit al comparar les freqüències de les característiques clíniques i serològiques en homes y dones amb lupus.

Estudio de la estructura y composición de carbonales (Acacia pennatula) en dos estadios de desarrollo. Diseño de protocolo para el seguimiento de la dinámica de la vegetación en el CIEA "El Limón", Estelí (Nicaragua)

Los carbonales son un tipo de bosque secundario originados por el abandono de un sistema de producción silvopastoril. Estos parches de bosque ocupan una superficie importante de la zona de amortiguamiento de la Reserva Natural del Tisey-La Estanzuela, área del bioma más amenazado del mundo, el Bosque Seco Tropical. La principal especie que compone esta comunidad vegetal es la Acacia pennatula, conocida comúnmente como carbón. Actualmente no hay muchos estudios sobre los carbonales, por lo que el presente proyecto pretende caracterizar la estructura y composición de la comunidad y describir algunos índices ecológicos básicos, en dos estadios diferentes. El análisis de los datos proporciona información de las principales diferencias en cuanto a estructura y composición que tienen lugar en los carbonales. La disminución natural de la densidad de individuos de A. pennatula con los años, parece tener un efecto positivo sobre la diversidad, composición y estructura de la comunidad. En base a estos datos, se ha diseñado un protocolo para realizar un estudio experimental de estas comunidades en el CIEA “El Limón”. En el protocolo, mediante diferentes tratamientos de tala en estadios tempranos, se obtendrán áreas de estudio que presenten un gradiente en la variable densidad de individuos de A. pennatula. El objetivo principal es describir y comparar la estructura, composición y dinámica del carbonal a lo largo del tiempo, y determinar que efecto tiene sobre la comunidad modificar esta variable. Los resultados obtenidos en el protocolo pueden utilizarse como base para desarrollar un plan de manejo para los carbonales que facilite la restauración del Bosque Tropical Seco y el aprovechamiento forestal.

On [summation of 1 raised to the power 1] equivalence relations over the natural numbers

"Vegeu el resum a l'inici del document del fitxer adjunt"

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

Hilbert space on probability density functions with Aitchison geometry

Compositional data analysis motivated the introduction of a complete Euclidean structure in the simplex of D parts. This was based on the early work of J. Aitchison (1986) and completed recently when Aitchinson distance in the simplex was associated with an inner product and orthonormal bases were identified (Aitchison and others, 2002; Egozcue and others, 2003). A partition of the support of a random variable generates a composition by assigning the probability of each interval to a part of the composition. One can imagine that the partition can be refined and the probability density would represent a kind of continuous composition of probabilities in a simplex of infinitely many parts. This intuitive idea would lead to a Hilbert-space of probability densitiesby generalizing the Aitchison geometry for compositions in the simplex into the set probability densities

Distributions on the simplex

The simplex, the sample space of compositional data, can be structured as a real Euclidean space. This fact allows to work with the coefficients with respect to an orthonormal basis. Over these coefficients we apply standard real analysis, inparticular, we define two different laws of probability trought the density function and we study their main properties

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Adding new components to the knowledge plane GMPLS over WDM networks

A recent study defines a new network plane: the knowledge plane. The incorporation of the knowledge plane over the network allows having more accurate information of the current and future network states. In this paper, the introduction and management of the network reliability information in the knowledge plane is proposed in order to improve the quality of service with protection routing algorithms in GMPLS over WDM networks. Different experiments prove the efficiency and scalability of the proposed scheme in terms of the percentage of resources used to protect the network

Sobre els mapes de semblança quàntica molecular

Partint de les definicions usuals de Mesures de Semblança Quàntica (MSQ), es considera la dependència d'aquestes mesures respecte de la superposició molecular. Pel cas particular en qnè els sistemes comparats siguin una molècula i un Àtom i que les mesures es calculin amb l'aproximació EASA, les MSQ esdevenen funcions de les tres coordenades de l'espai. Mantenint fixa una de les tres coordenades, es pot representar fàcilment la variació del valor de semblança en un pla determinat, i obtenir els anomenats mapes de semblança. En aquest article, es comparen els mapes de semblança obtinguts amb diferents MSQ per a sistemes senzills

A comparison of the alr and ilr transformations for kernel density estimation of compositional data

In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel densityestimation techniques in the context of compositional data analysis. Indeed, they gavetwo options for the choice of the kernel to be used in the kernel estimator. One ofthese kernels is based on the use the alr transformation on the simplex SD jointly withthe normal distribution on RD-1. However, these authors themselves recognized thatthis method has some deficiencies. A method for overcoming these dificulties based onrecent developments for compositional data analysis and multivariate kernel estimationtheory, combining the ilr transformation with the use of the normal density with a fullbandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu-Figueras (2006). Here we present an extensive simulation study that compares bothmethods in practice, thus exploring the finite-sample behaviour of both estimators

Consumption heterogenity over the business cycle

We study consumption heterogeneity over the business cycle. Using household panel data from 1984 to 2010 in the US we find that the welfare cost of the business cycle is non-negligible, once agents heterogeneity is taken into account, and sums to about 1% of yearly consumption. This is due to the structure of comovements between the different parts of the consumption distribution, in particular the tails are highly volatile and negatively related to each other. We also find that business cycle fluctuations originating from exogenous financial shocks only hit the top end of the consumption distribution and therefore reduce consumption inequality.

Kuranishi type Moduli Spaces for proper CR submersions fibering over the circle

Kuranishi's fundamental result (1962) associates to any compact complex manifold X&sub&0&/sub& a finite-dimensional analytic space which has to be thought of as a local moduli space of complex structures close to X&sub&0&/sub&. In this paper, we give an analogous statement for Levi-flat CR manifolds fibering properly over the circle by describing explicitely an infinite-dimensional Kuranishi type local moduli space of Levi-flat CR structures. We interpret this result in terms of Kodaira-Spencer deformation theory making clear the likenesses as well as the differences with the classical case. The article ends with applications and examples.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment