We aimed to characterize metabolites during tuberculosis (TB) disease and identify new pathophysiologic pathways involved in infection as well as biomarkers of TB onset, progression and resolution. Such data may inform development of new anti-tuberculosis drugs. Plasma samples from adults with newly diagnosed pulmonary TB disease and their matched, asymptomatic, sputum culture-negative househol...

The presented study deals with the interpretation of soil quality monitoring data using hierarchical cluster analysis (HCA) and principal components analysis (PCA). Both statistical methods contributed to the correct data classification and projection of the surface (0-20 cm) and subsurface (20-40 cm) soil layers of 36 sampling sites in the region of Burgas, Bulgaria. Clustering of the variable...

this paper presents results of hydro-chemical processes controlling groundwater chemical composition, using an integrated application of hierarchical cluster analysis and factor analysis of a major ion data set of groundwater from mighan playa aquifer. cluster analysis classified samples into four clusters(a, b, c and d) according to their dominant chemical composition: cluster a (dominant comp...

The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalanformations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta...

I review the main steps made so far towards a detailed (semi) analytical model for the hierarchical clustering of bound virialized objects (i.e., haloes) in the gravitational instability scenario. I focus on those models relying on the spherical collapse approximation which have led to the most complete description. The work is divided in two parts: a first one dealing with the mass function of...

This work analyzes the distribution of past CS229 projects by applying hierarchical agglomerative clustering. The clusters reveal which topics are very popular and which topics are more unique. Tracking the clusters over time also provides insight into how student projects have shifted over time. This knowledge will help future students select interesting and unique projects.

We describe the Hierarchical Classifier (HC), which is a hybrid architecture [1] built with the help of supervised training and unsu-pervised problem clustering. We prove a theorem giving the estimationˆR of HC risk. The proof works because of an improved way of computing cluster weights, introduced in this paper. Experiments show thatˆR is correlated with HC real error. This allows us to usê R...

Abstract In this study of the location and physical characteristics surroundings a series decorated caves in Nalón river basin Asturias (northern Iberia), spatial analysis, which included fieldwork use GIS, has defined external archaeological context (EAC) pre-Magdalenian art that area. The information been integrated with rock order to observe tendencies are statistically quantifiable by means...

Clustering has been widely used to partition data into groups so that the degree of association is high among members of the same group and low among members of diierent groups. Though many eeective and eecient clustering algorithms have been developed and deployed, most of them still suuer from the lack of automatic or online decision for optimal number of clusters. In this paper, we deene clu...

BACKGROUND AND AIMS Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in ...