Potenciais efeitos das mudanças climáticas futuras sobre a distribuiçãode um anuro da Caatinga Rhinella granulosa (Anura, Bufonidae)

Neste estudo, usamos dois tipos de modelagem de distribuição de espécies (correlativo e mecanístico), com o objetivo de avaliar o efeito das mudanças climáticas sob a distribuição geográfica de Rhinella granulosa (Spix, 1824), espécie inserida principalmente no bioma Caatinga. Avaliamos a predição, levantada por outros autores, de que espécies de anfíbios distribuídos em climas quentes terão suas distribuições espaciais restringidas por aumento da temperatura considerando cenários futuros. Na abordagem correlativa, os resultados mostraram que as distribuições espaciais geradas pelo modelo de distância Euclidiana foram mais conservativas, ou seja, as áreas que apresentaram menor distância do nicho ótimo se restringiram às áreas de distribuição real da espécie (Caatinga) e às pequenas regiões que abrangem o bioma Cerrado. A abordagem mecanística apresentou resultados menos conservativos, onde o habitat indicado como adequado para R. granulosa está contido em grande parte da América do Sul, formando uma extensa área contínua. No geral, verificou-se que R. granulosa não sofrerá forte influência climática sobre sua distribuição geográfica no futuro, pelo menos até 2080, provavelmente por apresentar uma fisiologia extremamente tolerante às altas temperaturas e por possuir adaptações para suportar clima quente e seco.

Automatización de una línea para procesado de pescado

Este proyecto surge de una necesidad industrial por parte de una empresa dedicada al procesado y envasado de pescado fresco y congelado (Elaborados Freiremar S.A). Para satisfacer esta necesidad, se decidió colocar una línea de proceso totalmente automatizada. Dicha automatización, consta de 3 partes totalmente diferenciales pero relacionadas entre ellas, puesto que sin alguna de estas partes la línea no podría funcionar correctamente. El software de control (PLC) se encarga de controlar y actuar sobre la máquina con los diferentes sensores, células de carga, motores… La SCADA en Visual Basic (Pantalla táctil)se encarga de mantener una comunicación continua con el software de control, y va almacenando todos los datos referentes a la línea y sus rendimientos. El software de consultas se instala en un PC de oficinas y se utiliza para sacar informes con todos los datos obtenidos del SCADA en Visual Basic.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Nuclear Factor I genomic binding associates with chromatin boundaries.

BACKGROUND: The Nuclear Factor I (NFI) family of DNA binding proteins (also called CCAAT box transcription factors or CTF) is involved in both DNA replication and gene expression regulation. Using chromatin immuno-precipitation and high throughput sequencing (ChIP-Seq), we performed a genome-wide mapping of NFI DNA binding sites in primary mouse embryonic fibroblasts. RESULTS: We found that in vivo and in vitro NFI DNA binding specificities are indistinguishable, as in vivo ChIP-Seq NFI binding sites matched predictions based on previously established position weight matrix models of its in vitro binding specificity. Combining ChIP-Seq with mRNA profiling data, we found that NFI preferentially associates with highly expressed genes that it up-regulates, while binding sites were under-represented at expressed but unregulated genes. Genomic binding also correlated with markers of transcribed genes such as histone modifications H3K4me3 and H3K36me3, even outside of annotated transcribed loci, implying NFI in the control of the deposition of these modifications. Positional correlation between + and - strand ChIP-Seq tags revealed that, in contrast to other transcription factors, NFI associates with a nucleosomal length of cleavage-resistant DNA, suggesting an interaction with positioned nucleosomes. In addition, NFI binding prominently occurred at boundaries displaying discontinuities in histone modifications specific of expressed and silent chromatin, such as loci submitted to parental allele-specific imprinted expression. CONCLUSIONS: Our data thus suggest that NFI nucleosomal interaction may contribute to the partitioning of distinct chromatin domains and to epigenetic gene expression regulation.NFI ChIP-Seq and input control DNA data were deposited at Gene Expression Omnibus (GEO) repository under accession number GSE15844. Gene expression microarray data for mouse embryonic fibroblasts are on GEO accession number GSE15871.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Creación de una aplicación web basada en software libre para la visualización y consulta de información catastral del Ajuntament de Cerdanyola del Vallès

La aplicación web creada tiene como objetivo convertirse en un instrumento útil para la consulta de información catastral del municipio de Cerdanyola del Vallès, ampliando el alcance de la información al personal del Ajuntament. Entre esta información, se incluye cartografía catastral urbana y rústica de diferentes años y la posibilidad de efectuar una serie de consultas alfanuméricas sencillas sobre la misma.

La figura di Nikola Tesla (1856-1943) in Tajna Nikole Tesle (1980)

Nikola Tesla è considerato, dai divulgatori scientifici che di lui si occupano, una figura chiave nella storia della scienza moderna e contemporanea, per l’importanza che hanno avuto le sue ricerche nello sviluppo di tecnologie del XX e XXI secolo. La sua attuale scarsa fama nel piano accademico contrasta con un’abbondante presenza di un Nikola Tesla come personaggio di finzione nelle arti popolari. Questa ricezione ambigua di Tesla potrebbe essere di fatto relazionata con il carattere utopico e visionario delle sue speranze nella scienza come mezzo di conoscenza per il miglioramento della società umana. Questo breve saggio si propone di analizzare come venga presentato il personaggio di Nikola Tesla nel lungometraggio jugoslavo Tajna Nikole Tesle, contribuendo così alla comprensione di come la narrativa di finzione possa sfruttare l’immagine di uno scienziato relativamente agli interessi politici legati a specifici contesti socio-storici.

Entorn web per a consultes on-line sobre bases de dades d'imatges

Creació d'un entorn web que consisteix en un sistema per fer consultes en línia a bases de dades d'imatges. Aquestes consultes es fan per contingut, a partir de mètodes creats pel grup de recerca CAT (Color and Texture) del CVC (Centre de Visió per Computador). L'aplicació web permet afegir nous mètodes que els membres del grup han programat amb Matlab.

Uncovering hidden duplicated content in public transcriptomics data.

As part of the development of the database Bgee (a dataBase for Gene Expression Evolution), we annotate and analyse expression data from different types and different sources, notably Affymetrix data from GEO and ArrayExpress, and RNA-Seq data from SRA. During our quality control procedure, we have identified duplicated content in GEO and ArrayExpress, affecting ∼14% of our data: fully or partially duplicated experiments from independent data submissions, Affymetrix chips reused in several experiments, or reused within an experiment. We present here the procedure that we have established to filter such duplicates from Affymetrix data, and our procedure to identify future potential duplicates in RNA-Seq data. Database URL: http://bgee.unil.ch/

Uso de la adrenalina autoinyectable (AAI) en pacientes con antecedentes de anafilaxia

La adrenalina autoinyectable (AAI) es un tratamiento que debe prescribirse a aquellos pacientes que han sufrido una reacción anafiláctica y son susceptibles de sufrir otra. En nuestro estudio, mediante una encuesta, valoramos el uso y el manejo de la AAI en pacientes a los que se les prescribió AAI y que siguen controles en nuestras consultas.

CRM : Centro Metalúrgico de Sabadell

El proyecto está basado en la creación de una herramienta para poder gestionar las relaciones que el Centro Metalúrgico de Sabadell tiene con sus clientes. La tarea a desarrollar es un CRM (Custom Relationship Management) para gestionar todos los servicios y ofertas que ofrece el centro con sus clientes, desde cursos impartidos u organizados, consultas que tienen los empleados de los socios, asesoramientos, acciones de los clientes pero también información útil para conocer el estado de acciones comerciales con un cliente, contactos de un socio, así como sus empleados.

Comparación de datos de expresión génica del servidor local con datos de una base de datos remota

En la presente memoria se detalla con precisión las diversas fases del trabajo para construir una aplicación web en el servidor http://revolutionresearch.uab.es que permite enriquecer los clusters de la microarray del usuario con información biomédica de una base de datos remota. Los clusters de origen estadístico (o no) de la microarray del usuario se enriquecen a partir de cruzar sus genes marcadores con la base de datos de genes marcadores de microarrays (base de datos remota) con clusters basados en información biomédica. La base de datos de genes marcadores de microarrays ha sido obtenida a partir de la base de datos de GEO Profiles del NCBI.

Valor del ADN-VPH en el cribado de la población oportunista en el departamento 6 de Valencia

La infecció pel Virus del Papil.loma Humà (VPH) és la causa principal de gairebé tots els casos de càncer cervical. En països on s'apliquen de manera programada tècniques de detecció, hi ha una disminució de la incidència i la mortalitat del càncer cervical. La detecció del VPH és un avenç important per a la prevenció del càncer en permetre un diagnòstic precoç de lesions cancerígenes. És per això que, es va decidir estudiar durant un any a la població de pacients que acudien a les consultes de ginecologia i aplicar si estava indicat el protocol de detecció de l'ADN-VPH segons les indicacions de l’Asociació Espanyola de Patologia Cervical i Colposcopia (AEPCC) per després traure conclusions.

Acceleració d'operacions SQL en GPU

L'objectiu principal d'aquest projecte és avaluar la tecnologia GPU per determinar si pot ser útil en el sector de les bases de dades. En concret s'utilitza el problema específic de les consultes analítiques amb la finalitat de intentar obtenir un temps de resposta més ràpid. Per aconseguir-ho s'executa el benchmark estàndard TCP-H per poder realitzar la comparació entre tres sistemes de gestió de bases de dades CPU amb un altre implementat per GPU.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.