Cluster Analysis of Business Data

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Cluster analysis using affinity aoefficient in order to identify religious beliefs profiles

International Scientific Forum, ISF 2013, ISF 2013, 12-14 December 2013, Tirana.

Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Effect of drift on segregation in two-component diffusion-limited aggregation

An effect of drift is investigated on the segregation pattern in diffusion-limited aggregation (DLA) with two components (A and B species). The sticking probability PAB (=PBA) between the different species is introduced into the DLA model with drift, where the sticking probability PAA (=PBB) between the same species equals 1. By using computer simulation it is found that the drift has an important effect on not only the morphology but also the segregation pattern. Under the drift and the small sticking probability, a characteristic pattern appears where elongated clusters of A species and of B species are periodically dispersed. The period decreases with increasing drift. The periodic structure of the deposits is characterized by an autocorrelation function. The shape of the cluster consisting of only A species (or B species) shows a vertically elongated filamentlike structure. Each cluster becomes vertically longer with decreasing sticking probability PAB. The segregation pattern is distinctly different from that with no drift and a small sticking probability PAA. The effect of the concentration on the segregation pattern is also shown.

Aggregation invariance in general clustering approaches

General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.

CCN2/CTGF silencing blocks cell aggregation in embryonal carcinoma P19 cell

Connective tissue growth factor (CCN2/CTGF) is a matricellular-secreted protein involved in extracellular matrix remodeling. The P19 cell line is an embryonic carcinoma line widely used as a cellular model for differentiation and migration studies. In the present study, we employed an exogenous source of CCN2 and small interference RNA to address the role of CCN2 in the P19 cell aggregation phenomenon. Our data showed that increasing CCN2 protein concentrations from 0.1 to 20 nM decreased the number of cell clusters and dramatically increased cluster size without changing proliferation or cell survival, suggesting that CCN2 induced aggregation. In addition, CCN2 specific silencing inhibited typical P19 cell aggregation, which could be partially rescued by 20 nM CCN2. The present study demonstrates that CCN2 is a key molecule for cell aggregation of embryonic P19 cells.

How do autoimmune diseases cluster in families? A systematic review and meta-analysis

Background: A primary characteristic of complex genetic diseases is that affected individuals tend to cluster in families (that is, familial aggregation). Aggregation of the same autoimmune condition, also referred to as familial autoimmune disease, has been extensively evaluated. However, aggregation of diverse autoimmune diseases, also known as familial autoimmunity, has been overlooked. Therefore, a systematic review and meta-analysis were performed aimed at gathering evidence about this topic. Methods: Familial autoimmunity was investigated in five major autoimmune diseases, namely, rheumatoid arthritis, systemic lupus erythematosus, autoimmune thyroid disease, multiple sclerosis and type 1 diabetes mellitus. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed. Articles were searched in Pubmed and Embase databases. Results: Out of a total of 61 articles, 44 were selected for final analysis. Familial autoimmunity was found in all the autoimmune diseases investigated. Aggregation of autoimmune thyroid disease, followed by systemic lupus erythematosus and rheumatoid arthritis, was the most encountered. Conclusions: Familial autoimmunity is a frequently seen condition. Further study of familial autoimmunity will help to decipher the common mechanisms of autoimmunity.

Cluster Coordination and Photoluminescence Properties of alpha-Ag2WO4 Microcrystals

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cluster Coordination and Photoluminescence Properties of alpha-Ag2WO4 Microcrystals

In this paper, we report our initial research to obtain hexagonal rod-like elongated silver tungstate (alpha-Ag2WO4) microcrystals by different methods [sonochemistry (SC), coprecipitation (CP), and conventional hydrothermal (CH)] and to study their cluster coordination and optical properties. These microcrystals were structurally characterized by X-ray diffraction (XRD), Rietveld refinements, Fourier transform infrared (FT-IR), X-ray absorption near-edge structure (XANES), and extended X-ray absorption fine structure (EXAFS) spectroscopies. The shape and average size of these alpha-Ag2WO4 microcrystals were observed by field-emission scanning electron microscopy (FE-SEM). The optical properties of these microcrystals were investigated by ultraviolet-visible (UV-vis) spectroscopy and photoluminescence (PL) measurements. XRD patterns and Rietveld refinement data confirmed that alpha-Ag2WO4 microcrystals have an orthorhombic structure. FT-IR spectra exhibited four IR-active modes in a range from 250 to 1000 cm(-1). XANES spectra at the W L-3-edge showed distorted octahedral [WO6] clusters in the lattice, while EXAFS analyses confirmed that W atoms are coordinated by six O atoms. FE-SEM images suggest that the alpha-Ag2WO4 microcrystals grow by aggregation and the Ostwald ripening process. PL properties of alpha-Ag2WO4 microcrystals decrease with an increase in the optical band-gap values (3.19-3.23 eV). Finally, we observed that large hexagonal rod-like alpha-Ag2WO4 microcrystals prepared by the SC method exhibited a major PL emission intensity relative to alpha-Ag2WO4 microcrystals prepared by the CP and CH methods.

Quantification of the hydrophobic interaction by simulations of the aggregation of small hydrophobic solutes in water

The hydrophobic interaction, the tendency for nonpolar molecules to aggregate in solution, is a major driving force in biology. In a direct approach to the physical basis of the hydrophobic effect, nanosecond molecular dynamics simulations were performed on increasing numbers of hydrocarbon solute molecules in water-filled boxes of different sizes. The intermittent formation of solute clusters gives a free energy that is proportional to the loss in exposed molecular surface area with a constant of proportionality of 45 ± 6 cal/mol⋅Å2. The molecular surface area is the envelope of the solute cluster that is impenetrable by solvent and is somewhat smaller than the more traditional solvent-accessible surface area, which is the area transcribed by the radius of a solvent molecule rolled over the surface of the cluster. When we apply a factor relating molecular surface area to solvent-accessible surface area, we obtain 24 cal/mol⋅Å2. Ours is the first direct calculation, to our knowledge, of the hydrophobic interaction from molecular dynamics simulations; the excellent qualitative and quantitative agreement with experiment proves that simple van der Waals interactions and atomic point-charge electrostatics account for the most important driving force in biology.

Classic beta-amyloid deposits cluster around large diameter blood vessels rather than capillaries in sporadic Alzheimer's disease

Various hypotheses could explain the relationship between beta-amyloid (Abeta) deposition and the vasculature in Alzheimer's disease (AD). Amyloid deposition may reduce capillary density, affect endothelial cells of blood vessels, result in diffusion from blood vessels, or interfere with the perivascular clearance mechanism. Hence, the spatial pattern of the classic ('cored') type of Abeta deposit was studied in the upper laminae (I,II/III) of the superior frontal gyrus in nine cases of sporadic AD (SAD). Sections were immunostained with antibodies against Abeta and with collagen IV to study the relationships between the spatial distribution of the classic deposits and the blood vessel profiles. Both the classic deposits and blood vessel profiles were distributed in clusters. In all cases, there was a positive spatial correlation between the clusters of the classic deposits and the larger diameter (>10 microm) blood vessel profiles and especially the vertically penetrating arterioles. In only 1 case, was there a significant spatial correlation between the clusters of the classic deposits and the smaller diameter (<10 microm) capillaries. There were no negative correlations between the density of Abeta deposits and the smaller diameter capillaries. In 9/11 cases, the clusters of the classic deposits were significantly larger than those of the clusters of the larger blood vessel profiles. In addition, the density of the classic deposits declined as a negative exponential function with distance from a vertically penetrating arteriole. These results suggest that the classic Abeta deposits cluster around the larger blood vessels in the upper laminae of the frontal cortex. This aggregation could result from diffusion of proteins from blood vessels or from overloading the system of perivascular clearance from the brain.

A statistical method for the identification and aggregation of regional linguistic variation

This paper introduces a method for the analysis of regional linguistic variation. The method identifies individual and common patterns of spatial clustering in a set of linguistic variables measured over a set of locations based on a combination of three statistical techniques: spatial autocorrelation, factor analysis, and cluster analysis. To demonstrate how to apply this method, it is used to analyze regional variation in the values of 40 continuously measured, high-frequency lexical alternation variables in a 26-million-word corpus of letters to the editor representing 206 cities from across the United States.

Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.

Exact solutions for cluster-growth kinetics with evolving size and shape profiles

In this paper we construct a model for the simultaneous compaction by which clusters are restructured, and growth of clusters by pairwise coagulation. The model has the form of a multicomponent aggregation problem in which the components are cluster mass and cluster diameter. Following suitable approximations, exact explicit solutions are derived which may be useful for the verification of simulations of such systems. Numerical simulations are presented to illustrate typical behaviour and to show the accuracy of approximations made in deriving the model. The solutions are then simplified using asymptotic techniques to show the relevant timescales of the kinetic processes and elucidate the shape of the cluster distribution functions at large times.