Allozymatic divergence between border populations of two cryptic species of the Drosophila buzzatii cluster species (Diptera: Drosophilidae)

Drosophila antonietae and Drosophila gouveai are allopatric, cactophilic, cryptic and endemic of South America species, which aedeagus morphology is considered the main diagnostic character. In this work, single close populations from the edge distributions of each species, located in an ""introgressive corridor"", were analyzed regarding temporal isozenzymatic genetic variability. Isocitrate dehydrogenase (Idh) appeared as a diagnostic locus between D. antonieate and D. gouveai because each population was fixed for different alleles. Moreover, several polymorphic loci showed accentuated divergence in the allele frequency, as evidenced by Nei`s l(0.3188) and D (1.1432), and also by Reynolds` genetic distance and identity (1.3207 and 0.7331, respectively). Our results showed that, in spite of the very similar external morphology, related evolutionary histories, close distributions, and events of introgression in the studied area, these cryptic species have high allozymatic differentiation, and this is discussed here. (C) 2010 Elsevier Ltd. All rights reserved.

Refractory cluster headache in a patient with bruxism and obstructive sleep apnea: a case report

Introduction This is a case report of a 39-year-old patient with a 14-year history of clinically refractory cluster headache (CH), also presenting obstructive sleep apnea (OSA) and complaining of tooth-grinding during sleep. Discussion Treatment of OSA with an intra-oral device allowed an immediate reduction in frequency and intensity of CH events. Furthermore, CH attacks did not occur during the 12-month follow-up period.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Considerations in the design of a mixed-method cluster evaluation of a community programme for 'at-risk' young people

This article discusses the design of a comprehensive evaluation of a community development programme for young people 'at-risk' of self-harming behaviour. It outlines considerations in the design of the evaluation and focuses on the complexities and difficulties associated with the evaluation of a community development programme. The challenge was to fulfil the needs of the funding body for a broad, outcome-focused evaluation while remaining close enough to the programme to accurately represent its activities and potential effects at a community level. Specifically, the strengths and limitations of a mixed-method evaluation plan are discussed with recommendations for future evaluation practice.

A cluster of melioidosis cases from an endemic region is clonal and is linked to the water supply using molecular typing of Burkholderia pseudomallei isolates

Nine cases of melioidosis with four deaths occurred over a 28-month period in members of a small remote Aboriginal community in the top end of the Northern Territory of Australia. Typing by pulsed-field gel electrophoresis showed isolates of Burkholderia pseudomallei from six of the cases to be clonal and also identical to an isolate from the community water supply, but not to soil isolates. The clonality of the isolates found in this cluster contrasts with the marked genetic diversity of human and environmental isolates found in this region which is hyperendemic for B. pseudomallei. It is possible that the clonal bacteria persisted and were propagated in biofilm in the water supply system. While the exact mode of transmission to humans and the reasons for cessation of the outbreak remain uncertain, contamination of the unchlorinated community water supply is a likely explanation.

Balancing the number and size of sites: An economic approach to the optimal design of cluster samples

The design of randomized controlled trials entails decisions that have economic as well as statistical implications. In particular, the choice of an individual or cluster randomization design may affect the cost of achieving the desired level of power, other things being equal. Furthermore, if cluster randomization is chosen, the researcher must decide how to balance the number of clusters, or sites, and the size of each site. This article investigates these interrelated statistical and economic issues. Its principal purpose is to elucidate the statistical and economic trade-offs to assist researchers to employ randomized controlled trials that have desired economic, as well as statistical, properties. (C) 2003 Elsevier Inc. All rights reserved.

MOND virial theorem applied to a galaxy cluster

Large values for the mass-to-light ratio (ϒ) in self-gravitating systems is one of the most important evidences of dark matter. We propose a expression for the mass-to-light ratio in spherical systems using MOND. Results for the COMA cluster reveal that a modification of the gravity, as proposed by MOND, can reduce significantly this value.

Residents’ perceptions of tourism impacts in Guimarães (Portugal): a cluster analysis

In this investigation, a cluster analysis was used to separate Guimara˜es (Portugal) residents into clusters according to their perceptions of the impacts of tourism development. This approach is uncommonly applied to Portugal data and is even rarer for world heritage sites. The world heritage designation is believed to make an area more attractive to tourists. The clustering procedure analysed 400 data observations from a Guimara˜es resident survey and revealed the existence of three clusters: the Sceptics, the Moderately Optimistic and the Enthusiasts. The results were consistent with the empirical literature’s results, with the emergent nature of the destination found to be relevant. The fact that tourism is relatively recent in this destination has its major reflex in the devaluation by most of the residents of the negative impacts of tourism development.

Guimarães residents’ perceptions towards tourism impacts: a cluster analysis

The present study was designed to assess and segment local residents with respect to their perceived impacts of Guimarães tourism development. The residents of this municipality (located in the northern part of Portugal) are quite strong in their support to tourism. However, they do not keep a homogeneous perception of tourism impacts. A clusters analysis using data from a survey of 400 Guimarães residents’ has revealed the existence of three clusters, according the different degrees of perceived tourism impacts: the Skeptics - moderate in relation to the benefits (averages range from 2.89-3.74) and the ones more concerned with its costs (averages range from 2.86-3.74); the Moderately optimistic - very optimistic about the benefits of tourism (averages range from 3.74-4.51) and conscious of the costs (averages range from 2.71-3.49); the Enthusiasts - very optimistic about tourism benefits (averages range from 2.92-4.52) and little worried about its costs (averages range from 1.78-3.26). Following the data from the survey, the findings are discussed and a few conclusions are extracted.

Effect of cylindrical filler aggregation on the electrical conductivity of composites

This work reports on the effect of carbon nanotube aggregation on the electrical conductivity and other network properties of polymer/carbon nanotube composites by modeling the carbon nanotubes as hard-core cylinders. It is shown that the conductivity decreases for increasing filler aggregation, and that this effect is more significant for higher cylinder volume fractions. It is also demonstrated, for volume fractions at which the giant component is present, that increasing the fraction of cylinders within clusters leads to a break of the giant component and the formation of a set of finite clusters. The decrease of the giant component with the increase of the fraction of cylinders within the cluster can be related to a decrease of the spanning probability due to a decrease of the number of cylinders between the clusters. Finally, it is demonstrated that the effect of aggregation can be understood by employing the network theory.

Paradoxo de inovação no cluster do vinho: o caso da região demarcada do Douro

Este artigo tem por principal objetivo analisar a problemática da inovação no âmbito do cluster de uma região vitivinícola europeia tradicional (Região Demarcada do Douro - Portugal), caracterizada pelo chamado modelo vitivinícola do terroir, uma estrutura econômica suportada por um elevado número de viticultores, pequenas e médias empresas vinícolas e elevada regulação ao longo de toda a cadeia produtiva, em que, claramente, emerge a questão da tradição versus inovação. A pesquisa utilizou o método Grounded Theory, e os resultados evidenciam uma concordância de as empresas permanecerem numa região tradicional, cuja legislação dificulta as inovações radicais, mas que, concomitantemente, assegura os valores da qualidade. Verifica-se uma transferência de valores tradicionais de um produto específico, o vinho do Porto, para os novos produtos lançados recentemente no mercado; e, simultaneamente, uma transferência do valor agregado do vinho do Porto para o valor do vínculo da família com o processo produtivo e com as terras da Região Demarcada do Douro.

Improving a Cluster Based Directional Channel Model in Realistic Macro-Cell Environment

In this paper a realistic directional channel model that is an extension of the COST 273 channel model is presented. The model uses a cluster of scatterers and visibility region generation based strategy with increased realism, due to the introduction of terrain and clutter information. New approaches for path-loss prediction and line of sight modeling are considered, affecting the cluster path gain model implementation. The new model was implemented using terrain, clutter, street and user mobility information for the city of Lisbon, Portugal. Some of the model's outputs are presented, mainly path loss and small/large-scale fading statistics.