Estudi descriptiu de Tumors Germinals Seminoma (TGS) en un centre de Referència. 15 anys d'experiència.

El tumor germinal seminoma (TGS) suposa un 50% de tots els tumors testiculars, i tot i l'excel•lent pronòstic a llarg plaç, està experimentant un increment de la incidència en un grup de la població d’entre 15-35 anys. L'Hospital de la Santa Creu i Sant Pau (HSCSP) juntament amb Fundació Puigvert són centre de referència en el maneig del TGS. La intenció el treball és reportar de manera descriptiva i retrospectiva l’experiència acumulada en aquest centre al llarg dels últims 15 anys. L'aportació d'aquest estudi pretén unir esforços per tal de disminuir tractaments innecessaris en gran part dels estadis I i intentar aportar més dades en favor del tractament adaptat al risc. En aquest sentit, ha de ser un motiu més per intentar validar factors pronòstics ferms en futurs estudis i poder posicionar la teràpia adaptada al risc en una situació protocolitzada i consensuada a nivell internacional.

Epidemilogia de la Influença porcina

La influenza es una enfermedad de gran importancia debido a su impacto sanitario y social. La especie porcina tiene importancia epidemiológica debido a su capacidad de actuar como eslabón adaptando los virus aviares a los mamíferos. Un mejor conocimiento de la enfermedad en la especie porcina permitirá definir mejor los métodos de lucha frente la enfermedad tanto en la especie humana como en la porcina. En el presente proyecto se pretende determinar los subtipos de virus influenza actualmente presentes en la cabaña porcina de España y estimar su seroprevalencia, así como estudiar los factores de riesgo que predisponen a la presencia de los virus influenza en las granjas de porcino. Para ello, se realizará una encuesta seroepidemiológica en la que se recogerán muestras de suero de animales de distintas edades (cerdas y cerdos de engorde) y se reunirán datos correspondientes a las características de las distintas explotaciones mediante una encuesta epidemiológica. Por otro lado, y con el fin de determinar la dinámica de infección de la enfermedad, se llevará a cabo un estudio longitudinal en dos explotaciones de ciclo cerrado seropositivas frente a Influenza porcina. En éstas explotaciones se recogerán muestras de suero y de hisopos nasales de un lote entero de producción, en intervalos que oscilarán de semanalmente a mensualmente. Los animales se muestrearan desde las tres semanas de vida hasta que sean enviados al matadero (aproximadamente a los 6 meses de vida). A partir de las muestras obtenidas se realizaran pruebas diagnósticas de carácter virológico y serológico. Este estudio aportará información acerca de la diseminación de los virus influenza en las explotaciones de cerdos, por lo que refiere a su comportamiento endémico/epidémico, clinico/subclínico, etc.

Els templers a la Comanda de Miravet

Web on s'expliquen els ordes militars centrat en l'estudi d'un orde concret, els Templers, i en un lloc concret, Miravet.

El Projecte Biblioteca Multimedia Virtual

L'objectiu del projecte que s'exposa és el de crear serveis bibliotecaris virtuals, per donar suport a l'activitat docent i acadèmica dels estudis del Graduat Multimèdia a Distància oferts per la Fundació Politècnica de Catalunya (FPC) i la Universitat Oberta de Catalunya.

Les fundacions de Santa Maria de Cervià i Santa Maria de Vilabertran en el context de la societat feudal (1053-1069)

Descripció de l' evolució del llinatge dels senyors de Cervià i la fundació del monestir benedictí de Sta. Maria de Cervià l'any 1053 i de la canònica de Sta. Maria de Vilabertran l'any 1069 en el context de la societat catalana del segle XI

Compositional data analysis: where we are and where should we be heading?

We take stock of the present position of compositional data analysis, of what has beenachieved in the last 20 years, and then make suggestions as to what may be sensibleavenues of future research. We take an uncompromisingly applied mathematical view,that the challenge of solving practical problems should motivate our theoreticalresearch; and that any new theory should be thoroughly investigated to see if it mayprovide answers to previously abandoned practical considerations. Indeed a main themeof this lecture will be to demonstrate this applied mathematical approach by a number ofchallenging examples

Statistical modeling on coordinates

This paper is a first draft of the principle of statistical modelling on coordinates. Several causes —which would be long to detail—have led to this situation close to the deadline for submitting papers to CODAWORK’03. The main of them is the fast development of the approach along thelast months, which let appear previous drafts as obsolete. The present paper contains the essential parts of the state of the art of this approach from my point of view. I would like to acknowledge many clarifying discussions with the group of people working in this field in Girona, Barcelona, Carrick Castle, Firenze, Berlin, G¨ottingen, and Freiberg. They have given a lot of suggestions and ideas. Nevertheless, there might be still errors or unclear aspects which are exclusively my fault. I hope this contribution serves as a basis for further discussions and new developments

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

When a data set can be considered compositional?

Traditionally, compositional data has been identified with closed data, and the simplex has been considered as the natural sample space of this kind of data. In our opinion, the emphasis on the constrained nature ofcompositional data has contributed to mask its real nature. More crucial than the constraining property of compositional data is the scale-invariant property of this kind of data. Indeed, when we are considering only few parts of a full composition we are not working with constrained data but our data are still compositional. We believe that it is necessary to give a more precisedefinition of composition. This is the aim of this oral contribution

Spatial Analysis of Cell Composition Data

A version of Matheron’s discrete Gaussian model is applied to cell composition data.The examples are for map patterns of felsic metavolcanics in two different areas. Q-Qplots of the model for cell values representing proportion of 10 km x 10 km cell areaunderlain by this rock type are approximately linear, and the line of best fit can be usedto estimate the parameters of the model. It is also shown that felsic metavolcanics in theAbitibi area of the Canadian Shield can be modeled as a fractal

Conditional compositional biplots: theory and application

The biplot has proved to be a powerful descriptive and analytical tool in many areasof applications of statistics. For compositional data the necessary theoreticaladaptation has been provided, with illustrative applications, by Aitchison (1990) andAitchison and Greenacre (2002). These papers were restricted to the interpretation ofsimple compositional data sets. In many situations the problem has to be described insome form of conditional modelling. For example, in a clinical trial where interest isin how patients’ steroid metabolite compositions may change as a result of differenttreatment regimes, interest is in relating the compositions after treatment to thecompositions before treatment and the nature of the treatments applied. To study thisthrough a biplot technique requires the development of some form of conditionalcompositional biplot. This is the purpose of this paper. We choose as a motivatingapplication an analysis of the 1992 US President ial Election, where interest may be inhow the three-part composition, the percentage division among the three candidates -Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethniccomposition and on the urban-rural composition of the state. The methodology ofconditional compositional biplots is first developed and a detailed interpretation of the1992 US Presidential Election provided. We use a second application involving theconditional variability of tektite mineral compositions with respect to major oxidecompositions to demonstrate some hazards of simplistic interpretation of biplots.Finally we conjecture on further possible applications of conditional compositionalbiplots

Analyzing shapes as compositions of distances

We propose to analyze shapes as “compositions” of distances in Aitchison geometry asan alternate and complementary tool to classical shape analysis, especially when sizeis non-informative.Shapes are typically described by the location of user-chosen landmarks. Howeverthe shape – considered as invariant under scaling, translation, mirroring and rotation– does not uniquely define the location of landmarks. A simple approach is to usedistances of landmarks instead of the locations of landmarks them self. Distances arepositive numbers defined up to joint scaling, a mathematical structure quite similar tocompositions. The shape fixes only ratios of distances. Perturbations correspond torelative changes of the size of subshapes and of aspect ratios. The power transformincreases the expression of the shape by increasing distance ratios. In analogy to thesubcompositional consistency, results should not depend too much on the choice ofdistances, because different subsets of the pairwise distances of landmarks uniquelydefine the shape.Various compositional analysis tools can be applied to sets of distances directly or afterminor modifications concerning the singularity of the covariance matrix and yield resultswith direct interpretations in terms of shape changes. The remaining problem isthat not all sets of distances correspond to a valid shape. Nevertheless interpolated orpredicted shapes can be backtransformated by multidimensional scaling (when all pairwisedistances are used) or free geodetic adjustment (when sufficiently many distancesare used)

Comparing correspondence analysis and the log-ratio alternative for representing categorical data

We compare correspondance análisis to the logratio approach based on compositional data. We also compare correspondance análisis and an alternative approach using Hellinger distance, for representing categorical data in a contingency table. We propose a coefficient which globally measures the similarity between these approaches. This coefficient can be decomposed into several components, one component for each principal dimension, indicating the contribution of the dimensions to the difference between the two representations. These three methods of representation can produce quite similar results. One illustrative example is given

CoDa-dendrogram: A new exploratory too

The use of orthonormal coordinates in the simplex and, particularly, balance coordinates, has suggested the use of a dendrogram for the exploratory analysis of compositional data. The dendrogram is based on a sequential binary partition of a compositional vector into groups of parts. At each step of a partition, one group of parts isdivided into two new groups, and a balancing axis in the simplex between both groupsis defined. The set of balancing axes constitutes an orthonormal basis, and the projections of the sample on them are orthogonal coordinates. They can be represented in adendrogram-like graph showing: (a) the way of grouping parts of the compositional vector; (b) the explanatory role of each subcomposition generated in the partition process;(c) the decomposition of the total variance into balance components associated witheach binary partition; (d) a box-plot of each balance. This representation is useful tohelp the interpretation of balance coordinates; to identify which are the most explanatory coordinates; and to describe the whole sample in a single diagram independentlyof the number of parts of the sample