Temporal and spatial distribution of Leishmania mexicana infections in a population of Neotoma micropus

A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.

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.

Creación de una web de gestión de álbumesfotográficos utilizando tecnología Java EE

El present treball de fi de carrera es planteja en base a l'anàlisi, planificació i desenvolupament d'una aplicació web basada en el model Java EE i que permetrà als usuaris del sistema la creació de col leccions digitals de fotografies.

Creació d'una eina en Java que a partir d'OWL i JESS generi SCORM

Aquest projecte consisteix en generar un programa escrit en llenguatge Java, que utilitzant un motor d'inferència a través d'una llibreria anomenada JESS, pugui llegir un document en format OWL que és una representació de l'ontologia (representació del coneixement) sobre una assignatura, transformant-lo al format de triples que és capaç d'interpretar JESS.

Anàlisi, disseny i implementació d'una pàgina web i de la gestió del seu contingut mitjançant Java/J2EE.

Els principals objectius del TFC ha estat l'anàlisi, disseny i implementació d'una web per a una empresa d'automoció i donar-li a l'empresa la capacitat de gestionar el contingut de la web, cosa que fins ara no podia fer. To això utilitzant la tecnologia Java i J2EE.

JWQ : Java WebQuest

L¿objectiu principal d¿aquest projecte és el de donar resposta a la necessitat de uncol·lectiu de professors i alumnes de magisteri de disposar d¿una eina de pràctiques per larealització de WebQuests.

Desarrollo para Internet con tecnología Java : Sistema de reservas para hoteles

En aquest projecte es presenta la creació d'un sistema de reserves per a hotels orientat a Internet que utilitza tecnologia Java. D'una manera especial, s'exposen les tecnologies J2EE, que es poden aplicar des de dos vessants diferents: en primer lloc, des del vessant d'implementació amb tecnologies J2EE, i, en segon lloc, des del vessant d'arquitectura J2EE, amb les diferents solucions aplicables per a cada capa de negoci.

Spatial analysis of the distribution of leprosy in the State of Ceará, Northeast Brazil

The aim of this study was to describe spatial patterns of the distribution of leprosy and to investigate spatial clustering of incidence rates in the state of Ceará, Northeast Brazil. The average incidence rate of leprosy for the period of 1991 to 1999 was calculated for each municipality of Ceará. Maps were used to describe the spatial distribution of the disease, and spatial statistics were applied to explore large- and small-scale variations of incidence rates. Three regions were identified in which the incidence of leprosy was particularly high. A spatial gradient in the incidence rates was identified, with a tendency of high rates to be concentrated on the North-South axis in the middle region of the state. Moran's I statistic indicated that a significant spatial autocorrelation also existed. The spatial distribution of leprosy in Ceará is heterogeneous. The reasons for spatial clustering of disease rates are not known, but might be related to an heterogeneous distribution of other factors such as crowding, social inequality, and environmental characteristics which by themselves determine the transmission of Mycobacterium leprae.

Fine-scale spatial genetic structure and gene dispersal in Silene latifolia.

Plants are sessile organisms, often characterized by limited dispersal. Seeds and pollen are the critical stages for gene flow. Here we investigate spatial genetic structure, gene dispersal and the relative contribution of pollen vs seed in the movement of genes in a stable metapopulation of the white campion Silene latifolia within its native range. This short-lived perennial plant is dioecious, has gravity-dispersed seeds and moth-mediated pollination. Direct measures of pollen dispersal suggested that large populations receive more pollen than small isolated populations and that most gene flow occurs within tens of meters. However, these studies were performed in the newly colonized range (North America) where the specialist pollinator is absent. In the native range (Europe), gene dispersal could fall on a different spatial scale. We genotyped 258 individuals from large and small (15) subpopulations along a 60 km, elongated metapopulation in Europe using six highly variable microsatellite markers, two X-linked and four autosomal. We found substantial genetic differentiation among subpopulations (global F(ST)=0.11) and a general pattern of isolation by distance over the whole sampled area. Spatial autocorrelation revealed high relatedness among neighboring individuals over hundreds of meters. Estimates of gene dispersal revealed gene flow at the scale of tens of meters (5-30 m), similar to the newly colonized range. Contrary to expectations, estimates of dispersal based on X and autosomal markers showed very similar ranges, suggesting similar levels of pollen and seed dispersal. This may be explained by stochastic events of extensive seed dispersal in this area and limited pollen dispersal.

Spatial distribution of schistosomiasis foci on Itamaracá Island, Pernambuco, Brazil

Acute cases of schistosomiasis have been found on the coastal area of Pernambuco, Brazil, due to environmental disturbances and disorderly occupation of the urban areas. This study identifies and spatially marks the main foci of the snail host species, Biomphalaria glabrata on Itamaracá Island. The chaotic occupation of the beach resorts has favoured the emergence of transmission foci, thus exposing residents and tourists to the risk of infection. A database covering five years of epidemiological investigation on snails infected by Schistosoma mansoni in the island was produced with information from the geographic positioning of the foci, number of snails collected, number of snails tested positive, and their infection rate. The spatial position of the foci were recorded through the Global Positioning System (GPS), and the geographical coordinates were imported by AutoCad. The software packages ArcView and Spring were used for data processing and spatial analysis. AutoCad 2000 was used to plot the pairs of coordinates obtained from GPS. Between 1998 and 2002 5009 snails, of which 12.2% were positive for S. mansoni, were collected in Forte Beach. A total of 27 foci and areas of environmental risk were identified and spatially analyzed allowing the identification of the areas exposed to varying degrees of risk.

Desarrollo en Java EE de una Librería virtual

Aquest treball de final de carrera consisteix en el desenvolupament, implementació i desplegament d'una aplicació utilitzant la tecnologia JavaE, d'una aplicació per la venda de llibres mitjançant la Web.