A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

Resistance to thyroid hormone and down syndrome: coincidental association or genetic linkage?

We report the first case of RTH and DS. Although this congruence could be coincidental, we cannot exclude a possible linkage between both syndromes.

Integració a la plataforma webDTI de tècniques de clustering de fibres i visualització de clústers

Estudi, disseny i implementació de diferents tècniques d’agrupament defibres (clustering) per tal d’integrar a la plataforma DTIWeb diferentsalgorismes de clustering i tècniques de visualització de clústers de fibres de forma quefaciliti la interpretació de dades de DTI als especialistes

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Vectorial capacity, basic reproduction number, force of infection and all that: formal notation to complete and adjust their classical concepts and equations

A dimensional analysis of the classical equations related to the dynamics of vector-borne infections is presented. It is provided a formal notation to complete the expressions for the Ross' Threshold Theorem, the Macdonald's basic reproduction "rate" and sporozoite "rate", Garret-Jones' vectorial capacity and Dietz-Molineaux-Thomas' force of infection. The analysis was intended to provide a formal notation that complete the classical equations proposed by these authors.

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.

Construction and characterisation of a complete reverse genetics system of dengue virus type 3

Dengue virulence and fitness are important factors that determine disease outcome. However, dengue virus (DENV) molecular biology and pathogenesis are not completely elucidated. New insights on those mechanisms have been facilitated by the development of reverse genetic systems in the past decades. Unfortunately, instability of flavivirus genomes cloned in Escherichia coli has been a major problem in these systems. Here, we describe the development of a complete reverse genetics system, based on the construction of an infectious clone and replicon for a low passage DENV-3 genotype III of a clinical isolate. Both constructs were assembled into a newly designed yeast- E. coli shuttle vector by homologous recombination technique and propagated in yeast to prevent any possible genome instability in E. coli . RNA transcripts derived from the infectious clone are infectious upon transfection into BHK-21 cells even after repeated passages of the plasmid in yeast. Transcript-derived DENV-3 exhibited growth kinetics, focus formation size comparable to original DENV-3 in mosquito C6/36 cell culture. In vitro characterisation of DENV-3 replicon confirmed its identity and ability to replicate transiently in BHK-21 cells. The reverse genetics system reported here is a valuable tool that will facilitate further molecular studies in DENV replication, virus attenuation and pathogenesis.

High-frequency linkage of co-expressing T-DNA in transgenic Arabidopsis thaliana transformed by vacuum-infiltration of Agrobacterium tumefaciens

The efficiency of co-expression and linkage of distinct T-DNAs present in separate Agrobacterium tumefaciens was analysed in Arabidopsis thaliana transformed by the vacuum infiltration method. Co-expression was monitored by the synthesis of three bacterial proteins involved in the production of polyhydroxybutyrate (PHB) in the plastids. Out of 80 kanamycin-resistant transgenic plants analysed, 13 plants were co-transformed with the two distinct T-DNAs and produced PHB. Of those, 7 lines had a kanamycin-resistance segregation ratio consistent with the presence of a single functional insert. Genetic linkage between the distinct T-DNAs was demonstrated for all 13 PHB-producing lines, while physical linkage between the distinct T-DNAs was shown for 12 out of 13 lines. T-DNAs were frequently linked in an inverted orientation about the left borders. Transformation of A. thaliana by the co-infiltration of two A. tumefaciens containing distinct T-DNAs is, thus, an efficient approach for the integration and expression of several transgenes at a single locus. This approach will facilitate the creation and study of novel metabolic pathways requiring the expression of numerous transgenes.

Complete genome sequence of a clinical Bordetella pertussis isolate from Brazil

There has been a resurgence in the number of pertussis cases in Brazil and around the world. Here, the genome of a clinical Bordetella pertussis strain (Bz181) that was recently isolated in Brazil is reported. Analysis of the virulence-associated genes defining the pre- and post-vaccination lineages revealed the presence of the prn2-ptxS1A-fim3B-ptxP3 allelic profile in Bz181, which is characteristic of the current pandemic lineage. A putative metallo-β-lactamase gene presenting all of the conserved zinc-binding motifs that characterise the catalytic site was identified, in addition to a multidrug efflux pump of the RND family that could confer resistance to erythromycin, which is the antibiotic of choice for treating pertussis disease.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

Clustering of risk behaviors with cigarette consumption: a population-based survey.

OBJECTIVE: This study assessed clustering of multiple risk behaviors (i.e., low leisure-time physical activity, low fruits/vegetables intake, and high alcohol consumption) with level of cigarette consumption. METHODS: Data from the 2002 Swiss Health Survey, a population-based cross-sectional telephone survey assessing health and self-reported risk behaviors, were used. 18,005 subjects (8052 men and 9953 women) aged 25 years old or more participated. RESULTS: Smokers more frequently had low leisure time physical activity, low fruits/vegetables intake, and high alcohol consumption than non- and ex-smokers. Frequency of each risk behavior increased steadily with cigarette consumption. Clustering of risk behaviors increased with cigarette consumption in both men and women. For men, the odds ratios of multiple (> or =2) risk behaviors other than smoking, adjusted for age, nationality, and educational level, were 1.14 (95% confidence interval: 0.97, 1.33) for ex-smokers, 1.24 (0.93, 1.64) for light smokers (1-9 cigarettes/day), 1.72 (1.36, 2.17) for moderate smokers (10-19 cigarettes/day), and 3.07 (2.59, 3.64) for heavy smokers (> or =20 cigarettes/day) versus non-smokers. Similar odds ratios were found for women for corresponding groups, i.e., 1.01 (0.86, 1.19), 1.26 (1.00, 1.58), 1.62 (1.33, 1.98), and 2.75 (2.30, 3.29). CONCLUSIONS: Counseling and intervention with smokers should take into account the strong clustering of risk behaviors with level of cigarette consumption.

Acute abdomen secondary to complete tubular colonic duplication.

We report the case of a 6-month-old infant who presented with a complete duplication of the large intestine, debuting clinically with acute abdomen and severe metabolic disorders. We discuss the pathogenesis and morphology of the lesions, diagnostic difficulties and peculiarities of surgical treatment.

Parvovirus B19 1A complete genome from a fatal case in Brazil

Parvovirus B19 (B19V) infects individuals worldwide and is associated with an ample range of pathologies and clinical manifestations. B19V is classified into three distinct genotypes, all identified in Brazil. Here, we report a complete sequence of a B19V genotype 1A that was obtained by high-throughput metagenomic sequencing. This genome provides information that will contribute to the studies on B19V epidemiology and evolution.

Complete genome of a dengue virus serotype 4 strain from Amazonas, Brazil

Dengue virus (DENV) infections represent a significant concern for public health worldwide, being considered as the most prevalent arthropod-borne virus regarding the number of reported cases. In this study, we report the complete genome sequencing of a DENV serotype 4 isolate, genotype II, obtained in the city of Manaus, directly from the serum sample, applying Ion Torrent sequencing technology. The use of a massive sequencing technology allowed the detection of two variable sites, one in the coding region for the viral envelope protein and the other in the nonstructural 1 coding region within viral populations.

Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering ofcompositional data in situations where observations are constituted by trajectories ofcompositional data, that is, by sequences of composition measurements along a domain.Observed trajectories are known as “functional data” and several methods have beenproposed for their analysis.In particular, methods for clustering functional data, known as Functional ClusterAnalysis (FCA), have been applied by practitioners and scientists in many fields. To ourknowledge, FCA techniques have not been extended to cope with the problem ofclustering compositional data trajectories. In order to extend FCA techniques to theanalysis of compositional data, FCA clustering techniques have to be adapted by using asuitable compositional algebra.The present work centres on the following question: given a sample of compositionaldata trajectories, how can we formulate a segmentation procedure giving homogeneousclasses? To address this problem we follow the steps described below.First of all we adapt the well-known spline smoothing techniques in order to cope withthe smoothing of compositional data trajectories. In fact, an observed curve can bethought of as the sum of a smooth part plus some noise due to measurement errors.Spline smoothing techniques are used to isolate the smooth part of the trajectory:clustering algorithms are then applied to these smooth curves.The second step consists in building suitable metrics for measuring the dissimilaritybetween trajectories: we propose a metric that accounts for difference in both shape andlevel, and a metric accounting for differences in shape only.A simulation study is performed in order to evaluate the proposed methodologies, usingboth hierarchical and partitional clustering algorithm. The quality of the obtained resultsis assessed by means of several indices