Diversity, dynamics and activity of mesophilic Archaea in stratified feshwater lakes. Implications in biogeochemical cycles

Aquesta tesi doctoral va estudiar la diversitat (riquesa i abundància), la distribució i la dinàmica de les comunitats planctòniques d'Archaea presents a diferents llacs estratificats temperats d'aigua dolça per aportar evidencies sobre la seva distribució i la seva possible activitat en aquests ecosistemes en relació als cicles biogeoquímics presents en els mateixos. Es varen estudiar dos estanyols d'origen càrstic (l'Estanyol del Vilar durant cinc anys consecutius (2001-2005) i l'Estanyol de Can Coromina) i un llac d'origen volcànic (Llac Kivu) analitzant, per una banda, la seva comunitat planctònica d'Archaea mitjançant una aproximació molecular i, per una altra, la seva possible activitat en aquests ambients (p.e., la nitrificació i la fixació de carboni). Per contextualitzar els resultats, es va realitzar un anàlisi in silico dels patrons de distribució global dels Archaea mesòfils mitjançant un anàlisi a nivell de llinatge combinant seqüències del gen 16S rRNA amb diferents eines estadístiques i d'ecologia general.

CoDaPack. An Excel and Visual Basic based software of compositional data analysis. Current version and discussion form upcoming versions

In the eighties, John Aitchison (1986) developed a new methodological approach for the statistical analysis of compositional data. This new methodology was implemented in Basic routines grouped under the name CODA and later NEWCODA inMatlab (Aitchison, 1997). After that, several other authors have published extensions to this methodology: Marín-Fernández and others (2000), Barceló-Vidal and others (2001), Pawlowsky-Glahn and Egozcue (2001, 2002) and Egozcue and others (2003). (...)

Validation of order rank scales based on compositional data analysis: a proposal

Usually, psychometricians apply classical factorial analysis to evaluate construct validity of order rank scales. Nevertheless, these scales have particular characteristics that must be taken into account: total scores and rank are highly relevant

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed

Availability analysis of GMPLS connections based on physical network topology

This paper presents a study of connection availability in GMPLS over optical transport networks (OTN) taking into account different network topologies. Two basic path protection schemes are considered and compared with the no protection case. The selected topologies are heterogeneous in geographic coverage, network diameter, link lengths, and average node degree. Connection availability is also computed considering the reliability data of physical components and a well-known network availability model. Results show several correspondences between suitable path protection algorithms and several network topology characteristics

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage