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.

Comparing population distributions from bin-aggregated sample data: an application to historical height data from France

This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.

Analyzing aggregate real exchange rate persistence through the lens of sectoral data

In this paper we analyze the persistence of aggregate real exchange rates (RERs) for a group of EU-15 countries by using sectoral data. The tight relation between aggregate and sectoral persistence recently investigated by Mayoral (2008) allows us to decompose aggregate RER persistence into the persistence of its different subcomponents. We show that the distribution of sectoral persistence is highly heterogeneous and very skewed to the right, and that a limited number of sectors are responsible for the high levels of persistence observed at the aggregate level. We use quantile regression to investigate whether the traditional theories proposed to account for the slow reversion to parity (lack of arbitrage due to nontradibilities or imperfect competition and price stickiness) are able to explain the behavior of the upper quantiles of sectoral persistence. We conclude that pricing to market in the intermediate goods sector together with price stickiness have more explanatory power than variables related to the tradability of the goods or their inputs.

A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

EU cohesion aid to Spain: a data set. Part I: 2000-06 planning period

In this paper we construct a data set on EU cohesion aid to Spain during the planning period 2000-06. The data are disaggregated by region, year and function and attempt to approximate the timing of actual executed expenditure on assisted projects.

What if there was a stronger pharmaceutical price competition in Spain? When regulation has a similar effect to collusion

This paper examines statins competition in the Spanish pharmaceutical market, where prices are highly regulated, and simulates a situation in which there is unrestricted price competition. A nested logit demand model is estimated with a panel of monthly data for pharmaceuticals prescribed from 1997 to 2005. The simulation indicates that the regulation of prices is similar in its effects to cooperation among producers, since the regulated prices are close to those that would be observed in a scenario of perfect collusion. Freedom to set prices and a regulatory framework with appropriate incentives would result in a general reduction in prices and may make the current veiled competition in the form of discounts to pharmacists become more visible. The decrease in prices would be partially offset by an increase in consumption but the net effect would be an overall decrease in expenditure. The counterfactual set-up would also lead to important changes in the market shares of both manufacturers and active ingredients, and a reversal of generic drugs. Therefore, pro-competitive regulation would be welfare-enhancing but would imply winners and losers.

Singling out individual inventors from patent data

An increasing number of studies have sprung up in recent years seeking to identify individual inventors from patent data. Different heuristics have been suggested to use their names and other information disclosed in patent documents in order to find out “who is who” in patents. This paper contributes to this literature by setting forth a methodology to identify them using patents applied to the European Patent Office (EPO hereafter). As in the large part of this literature, we basically follow a three-steps procedure: (1) the parsing stage, aimed at reducing the noise in the inventor’s name and other fields of the patent; (2) the matching stage, where name matching algorithms are used to group possible similar names; (3) the filtering stage, where additional information and different scoring schemes are used to filter out these potential same inventors. The paper includes some figures resulting of applying the algorithms to the set of European inventors applying to the EPO for a large period of time.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

How to use the standard model with own data?

In this work discuss the use of the standard model for the calculation of the solvency capital requirement (SCR) when the company aims to use the specific parameters of the model on the basis of the experience of its portfolio. In particular, this analysis focuses on the formula presented in the latest quantitative impact study (2010 CEIOPS) for non-life underwriting premium and reserve risk. One of the keys of the standard model for premium and reserves risk is the correlation matrix between lines of business. In this work we present how the correlation matrix between lines of business could be estimated from a quantitative perspective, as well as the possibility of using a credibility model for the estimation of the matrix of correlation between lines of business that merge qualitative and quantitative perspective.

Is real GDP stationary? Evidence from a panel unit root test with cross-sectional dependence and historical data

We use historical data that cover more than one century on real GDP for industrial countries and employ the Pesaran panel unit root test that allows for cross-sectional dependence to test for a unit root on real GDP. We find strong evidence against the unit root null. Our results are robust to the chosen group of countries and the sample period. Key words: real GDP stationarity, cross-sectional dependence, CIPS test. JEL Classification: C23, E32

L'intercanvi de llavors com a mecanisme per a la conservació de l'agrobiodiversitat. Estudi de cas: Vallès Oriental

En les últimes dècades hi ha hagut un interès creixent en la conservació de les varietats locals. En relació amb això, s’argumenta que els horts domèstics tenen un paper fonamental en el manteniment de la diversitat genètica. Pel que fa a l’objectiu, consisteix a analitzar la conservació de l’agrobiodiversitat a la comarca del Vallès Oriental mitjançant una anàlisi de la xarxa d’intercanvi, el nombre de varietats locals i el coneixement que hi està associat. Aquest còmput d’informació ha permès realitzar un inventari de totes les varietats locals, el seu coneixement associat, una anàlisi del context social dels hortelans i una anàlisi de les xarxes d’intercanvi, que evidencien si aquests factors afecten de forma directa o indirecta la millora i el manteniment de l’agrobiodiversitat.

Abundància i persistència de Faecalibacteriun prausnitzii en la Malaltia de Crohn

Faecalibacterium prausnitzii és un del bacteris anaeròbis més abundants entre les espècies comensals del tracte intestinal humà sa. Aquesta espècie és una de les principals productores de butirat a l'intestí (que és la principal font d’energia per als colonòcits), però també s'ha suggerit que pot produir compostos antiinflamatoris i intervenir en la regulació de vàries rutes metabòliques de l’hoste. F. prausnitzii és un bacteri difícil de cultivar, ja que presenta una elevada sensibilitat a l'oxigen i presenta uns requeriments nutricionals molt exigents, el que ha compromès considerablement el nombre d’estudis basats en aïllats d’aquesta espècie. No obstant això, en els darrers anys l’interès en aquest bacteri està creixent ja que s’ha evidenciat que les poblacions de F. prausnitzii són variables en diferents grups d'edat i que es veuen reduïdes en certs trastorns intestinals com ara la malaltia inflamatòria intestinal i el càncer colorectal. L’objectiu d'aquest treball ha estat aprofundir en el rol que desenvolupa F. prausnitzii com un dels principals bacteris comensals del tracte intestinal humà. En primer lloc, s’ha dissenyat, optimitzat i validat un nou mètode molecular per determinar l’abundància d’aquesta espècie en mostres del tracte gastrointesinal, i s’ha demostrat la seva possible aplicació per ajudar al diagnòstic de la malaltia de Crohn. En segon lloc, s’ha dut a terme un estudi de les característiques filogenètiques i fenotípiques dels aïllats de F. Prausnitzii disponibles en l'actualitat a fi de coneixre’n millor la diversitat genètica i fenotípica i dilucidar quins factors són crucials en comprometre la població d’aquest bacteri en un intestí malalt. L’anàlisi de les soques ha revelat que F. prausnitzii inclou Principalment dos filogrups, nutricionalment versàtils i molt sensibles a canvis en les condicions ecològiques que pot patir l’intestí de l’hoste sota certes malalties intestinals. En conclusió, els resultat obtinguts en aquest estudi mostren que F. prausnitzii és una espècie ben establerta al còlon sa, amb una elvada versatilitat metabòlica ja que és capaç d’ interactuar amb carbohidrats de diferent estructura i complexitat. S’ha corroborat que aquest microorganisme seria un bon indicador de salut intestinal ja que la seva abundància es veu significativament reduida en pacients amb malaltia de Crohn. Aquests resultats concorden amb els obtinguts per proves fisiològiques que mostren una elevada sensibilitat de l’espècie a determinades condicions relacionades amb malalties intestinals. Estudis futurs s’orientaran a comprendre millor quins factros derrivats de la interacció amb l’hoste també determinen la persistència d’aquesta espècie en un intestí sa o malalt.

La capa de persistènica : Java Data Objects

L'objectiu que es proposa aquest document és conèixer la problemàtica de la persistència dels objectes, trobar i estudiar les diferents solucions existents i estudiar-ne una de concreta, la capa de persistència JDO.

An Ontology for Open Rubric Exchange on the Web

While the Internet has given educators access to a steady supply of Open Educational Resources, the educational rubrics commonly shared on the Web are generally in the form of static, non-semantic presentational documents or in the proprietary data structures of commercial content and learning management systems.With the advent of Semantic Web Standards, producers of online resources have a new framework to support the open exchange of software-readable datasets. Despite these advances, the state of the art of digital representation of rubrics as sharable documents has not progressed.This paper proposes an ontological model for digital rubrics. This model is built upon the Semantic Web Standards of the World Wide Web Consortium (W3C), principally the Resource Description Framework (RDF) and Web Ontology Language (OWL).

Application of compositional data analysis to geochemical data of marine sediments

In an earlier investigation (Burger et al., 2000) five sediment cores near the RodriguesTriple Junction in the Indian Ocean were studied applying classical statistical methods(fuzzy c-means clustering, linear mixing model, principal component analysis) for theextraction of endmembers and evaluating the spatial and temporal variation ofgeochemical signals. Three main factors of sedimentation were expected by the marinegeologists: a volcano-genetic, a hydro-hydrothermal and an ultra-basic factor. Thedisplay of fuzzy membership values and/or factor scores versus depth providedconsistent results for two factors only; the ultra-basic component could not beidentified. The reason for this may be that only traditional statistical methods wereapplied, i.e. the untransformed components were used and the cosine-theta coefficient assimilarity measure.During the last decade considerable progress in compositional data analysis was madeand many case studies were published using new tools for exploratory analysis of thesedata. Therefore it makes sense to check if the application of suitable data transformations,reduction of the D-part simplex to two or three factors and visualinterpretation of the factor scores would lead to a revision of earlier results and toanswers to open questions . In this paper we follow the lines of a paper of R. Tolosana-Delgado et al. (2005) starting with a problem-oriented interpretation of the biplotscattergram, extracting compositional factors, ilr-transformation of the components andvisualization of the factor scores in a spatial context: The compositional factors will beplotted versus depth (time) of the core samples in order to facilitate the identification ofthe expected sources of the sedimentary process.Kew words: compositional data analysis, biplot, deep sea sediments