Desarrollo de una aplicación gráfica de visualización y análisis de moléculas

Actualment la informàtica gràfica troba un ampli camp d'aplicació en la visualització de dades. Visualitzar dades científiques és especialment important per a fer-ho servir en la recerca, l'anàlisi i l'ensenyament. Aquest treball tracta de la visualització de molècules, que es pot emprar en diferents camps, com ara la química, la mineralogia o la farmàcia.

Antibiotic prophylaxis to prevent local infection in oral surgery: use or abuse?

Antibiotics have a well-documented efficacy in the treatment of established infections and as prophylactic agents in medically compromised patients. However, the systematic administration of antibiotics to prevent local infections in fit patients is much more controversial. The aim of this paper is to reflect on the justification for prophylactic usage of antibiotics to prevent wound infection and to reason out the most appropriate antibiotic guidelines taking into account available scientific data and studies by other authors. Numerous clinical trials question the efficacy of antibiotics in preventing wound infection. While some studies establish that antibiotics reduce the incidence of postoperative infections, others compare their efficacy to that of placebo. Thus, scientific literature suggests that every oral surgical intervention is not tributary of systematic antibiotic prophylaxis to prevent local infections. Intrinsic surgical risk factors and the patient"s individual circumstances must be taken into account. Even though the efficacy of other antibiotics cannot be ruled out due to our limited comprehension of the bacteriologic interrelations intervening in the pathogenesis of postextraction local infection, the amoxicillin-clavulanic acid combination theoretically covers the complete odontogenic bacterial spectrum in Spain. When the prophylactic use of antibiotics is indicated, this should be performed preoperatively, at high doses, and its extent should not exceed 24 hours. Special attention should be paid to antiinfectious local measures that can minimize infection risk during the wound"s healing period

The Quaternary Active Faults Database of Iberia (QAFI v.2.0)

The Quaternary Active Faults Database of Iberia (QAFI) is an initiative lead by the Institute of Geology and Mines of Spain (IGME) for building a public repository of scientific data regarding faults having documented activity during the last 2.59 Ma (Quaternary). QAFI also addresses a need to transfer geologic knowledge to practitioners of seismic hazard and risk in Iberia by identifying and characterizing seismogenic fault-sources. QAFI is populated by the information freely provided by more than 40 Earth science researchers, storing to date a total of 262 records. In this article we describe the development and evolution of the database, as well as its internal architecture. Aditionally, a first global analysis of the data is provided with a special focus on length and slip-rate fault parameters. Finally, the database completeness and the internal consistency of the data are discussed. Even though QAFI v.2.0 is the most current resource for calculating fault-related seismic hazard in Iberia, the database is still incomplete and requires further review.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Two different 3D biogeochemical models for the NW mediterranean sea: validation with Meris data and intercomparison

Report for the scientific sojourn carried out at the University of New South Wales from February to June the 2007. Two different biogeochemical models are coupled to a three dimensional configuration of the Princeton Ocean Model (POM) for the Northwestern Mediterranean Sea (Ahumada and Cruzado, 2007). The first biogeochemical model (BLANES) is the three-dimensional version of the model described by Bahamon and Cruzado (2003) and computes the nitrogen fluxes through six compartments using semi-empirical descriptions of biological processes. The second biogeochemical model (BIOMEC) is the biomechanical NPZD model described in Baird et al. (2004), which uses a combination of physiological and physical descriptions to quantify the rates of planktonic interactions. Physical descriptions include, for example, the diffusion of nutrients to phytoplankton cells and the encounter rate of predators and prey. The link between physical and biogeochemical processes in both models is expressed by the advection-diffusion of the non-conservative tracers. The similarities in the mathematical formulation of the biogeochemical processes in the two models are exploited to determine the parameter set for the biomechanical model that best fits the parameter set used in the first model. Three years of integration have been carried out for each model to reach the so called perpetual year run for biogeochemical conditions. Outputs from both models are averaged monthly and then compared to remote sensing images obtained from sensor MERIS for chlorophyll.

Still in the Era of Area Studies? Political-Scientific Perspectives on European Competition Policy in the 2000s

This note reviews the political-scientific literature on European competition policy (ECP) in the 2000s. Based on a data set extracted from four well-known journals, and using an upfront methodology and explicit criteria, it analyzes the literature both quantitatively and qualitatively. On the quantitative side, it shows that, although a few sub-policy areas are still neglected, ECP is not the under-researched policy it used to be. On the qualitative side, the literature has greatly improved since the 1990s: Almost all articles now present a clear research question, and most advance specific theoretical claims/hypotheses. Yet, improvements can be made on research design, statistical testing, and, above all, state-of-the-art theorizing (e.g. in the game-theoretical treatment of delegation problems). Indeed, it is paradoxical that ECP specialists do not pay more attention to theoretical questions which are so central to the actual policy area they study.

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners.

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners. JEL classification: O31, O33, O38. Key words: Determinants R&D cooperation, industry-university flows, PhD research workers.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Monitoring procedures in environmental geochemistry and compositional data analysis theory

First discussion on compositional data analysis is attributable to Karl Pearson, in 1897. However, notwithstanding the recent developments on algebraic structure of the simplex, more than twenty years after Aitchison’s idea of log-transformations of closed data, scientific literature is again full of statistical treatments of this type of data by using traditional methodologies. This is particularly true in environmental geochemistry where besides the problem of the closure, the spatial structure (dependence) of the data have to be considered. In this work we propose the use of log-contrast values, obtained by asimplicial principal component analysis, as LQGLFDWRUV of given environmental conditions. The investigation of the log-constrast frequency distributions allows pointing out the statistical laws able togenerate the values and to govern their variability. The changes, if compared, for example, with the mean values of the random variables assumed as models, or other reference parameters, allow definingmonitors to be used to assess the extent of possible environmental contamination. Case study on running and ground waters from Chiavenna Valley (Northern Italy) by using Na+, K+, Ca2+, Mg2+, HCO3-, SO4 2- and Cl- concentrations will be illustrated

Random assignment of intervention points in two phase single-case designs: data-division-specific distributions

The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized.

Lattices for 3-Dimensional Fuzzy Data generated by Fuzzy Galois Connections

Vagueness and high dimensional space data are usual features of current data. The paper is an approach to identify conceptual structures among fuzzy three dimensional data sets in order to get conceptual hierarchy. We propose a fuzzy extension of the Galois connections that allows to demonstrate an isomorphism theorem between fuzzy sets closures which is the basis for generating lattices ordered-sets

RiskDiff: A web tool for the analysis of the difference due to risk and demographic factors for incidence or mortality data.

Background Analysing the observed differences for incidence or mortality of a particular disease between two different situations (such as time points, geographical areas, gender or other social characteristics) can be useful both for scientific or administrative purposes. From an epidemiological and public health point of view, it is of great interest to assess the effect of demographic factors in these observed differences in order to elucidate the effect of the risk of developing a disease or dying from it. The method proposed by Bashir and Estève, which splits the observed variation into three components: risk, population structure and population size is a common choice at practice. Results A web-based application, called RiskDiff has been implemented (available at http://rht.iconcologia.net/riskdiff.htm webcite), to perform this kind of statistical analyses, providing text and graphical summaries. Code from the implemented functions in R is also provided. An application to cancer mortality data from Catalonia is used for illustration. Conclusions Combining epidemiological with demographical factors is crucial for analysing incidence or mortality from a disease, especially if the population pyramids show substantial differences. The tool implemented may serve to promote and divulgate the use of this method to give advice for epidemiologic interpretation and decision making in public health.

Reconstructing native American migrations from whole-genome and whole-exome data.

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern American ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.