The role of electron localization in the atomic structure of transition-metal 13-atom clusters: the example of Co(13), Rh(13), and Hf(13)

The crystalline structure of transition-metals (TM) has been widely known for several decades, however, our knowledge on the atomic structure of TM clusters is still far from satisfactory, which compromises an atomistic understanding of the reactivity of TM clusters. For example, almost all density functional theory (DFT) calculations for TM clusters have been based on local (local density approximation-LDA) and semilocal (generalized gradient approximation-GGA) exchange-correlation functionals, however, it is well known that plain DFT fails to correct the self-interaction error, which affects the properties of several systems. To improve our basic understanding of the atomic and electronic properties of TM clusters, we report a DFT study within two nonlocal functionals, namely, the hybrid HSE (Heyd, Scuseria, and Ernzerhof) and GGA + U functionals, of the structural and electronic properties of the Co(13), Rh(13), and Hf(13) clusters. For Co(13) and Rh(13), we found that improved exchange-correlation functionals decrease the stability of open structures such as the hexagonal bilayer (HBL) and double simple-cubic (DSC) compared with the compact icosahedron (ICO) structure, however, DFT-GGA, DFT-GGA + U, and DFT-HSE yield very similar results for Hf(13). Thus, our results suggest that the DSC structure obtained by several plain DFT calculations for Rh(13) can be improved by the use of improved functionals. Using the sd hybridization analysis, we found that a strong hybridization favors compact structures, and hence, a correct description of the sd hybridization is crucial for the relative energy stability. For example, the sd hybridization decreases for HBL and DSC and increases for ICO in the case of Co(13) and Rh(13), while for Hf(13), the sd hybridization decreases for all configurations, and hence, it does not affect the relative stability among open and compact configurations.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

Classification of individuals with dyslipidaemia controlled by statins according to plasma biomarkers of oxidative stress using cluster analysis

Oxidative stress is a physiological condition that is associated with atherosclerosis. and it can be influenced by diet. Our objective was to group fifty-seven individuals with dyslipidaemia controlled by statins according to four oxidative biomarkers, and to evaluate the diet pattern and blood biochemistry differences between these groups. Blood samples were collected and the following parameters were evaluated: diet intake; plasma fatty acids; lipoprotein concentration; glucose; oxidised LDL (oxLDL); malondialdehyde (MDA): total antioxidant activity by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing ability power assays. Individuals were separated into five groups by cluster analysis. All groups showed a difference with respect to at least one of the four oxidative stress biomarkers. The separation of individuals in the first axis was based upon their total antioxidant activity. Clusters located on the right side showed higher total antioxidant activity, higher myristic fatty acid and lower arachidonic fatty acid proportions than clusters located on the left side. A negative correlation was observed between DPPH and the peroxidability index. The second axis showed differences in oxidation status as measured by MDA and oxLDL concentrations. Clusters located on the Upper side showed higher oxidative status and lower HDL cholesterol concentration than clusters located on the lower side. There were no differences in diet among the five clusters. Therefore, fatty acid synthesis and HDL cholesterol concentration seem to exert a more significant effect on the oxidative conditions of the individuals with dyslipidaemia controlled by statins than does their food intake.

Crotalus durissus collilineatus venom gland transcriptome: Analysis of gene expression profile

Crotalus durissus rattlesnakes are responsible for the most lethal cases of snakebites in Brazil. Crotalus durissus collilineatus subspecies is related to a great number of accidents in Southeast and Central West regions, but few studies on its venom composition have been carried out to date. In an attempt to describe the transcriptional profile of the C. durissus collilineatus venom gland, we generated a cDNA library and the sequences obtained could be identified by similarity searches on existing databases. Out of 673 expressed sequence tags (ESTs) 489 produced readable sequences comprising 201 singletons and 47 clusters of two or more ESTs. One hundred and fifty reads (60.5%) produced significant hits to known sequences. The results showed a predominance of toxin-coding ESTs instead of transcripts coding for proteins involved in all cellular functions. The most frequent toxin was crotoxin, comprising 88% of toxin-coding sequences. Crotoxin B, a basic phospholipase A(2) (PLA(2)) subunit of crotoxin, was represented in more variable forms comparing to the non-enzymatic subunit (crotoxin A), and most sequences coding this molecule were identified as CB1 isoform from Crotalus durissus terrificus venom. Four percent of toxin-related sequences in this study were identified as growth factors, comprising five sequences for vascular endothelial growth factor (VEGF) and one for nerve growth factor (NGF) that showed 100% of identity with C. durissus terrificus NGF. We also identified two clusters for metalloprotease from PII class comprising 3% of the toxins, and two for serine proteases, including gyroxin (2.5%). The remaining 2.5% of toxin-coding ESTs represent singletons identified as homologue sequences to cardiotoxin, convulxin, angiotensin-converting enzyme inhibitor and C-type natriuretic peptide, Ohanin, crotamin and PLA(2) inhibitor. These results allowed the identification of the most common classes of toxins in C. durissus collilineatus snake venom, also showing some unknown classes for this subspecies and even for C. durissus species, such as cardiotoxins and VEGF. (C) 2009 Published by Elsevier Masson SAS.

XSophe-Sophe-XeprView (R). A computer simulation software suite (v. 1.1.3) for the analysis of continuous wave EPR spectra

The XSophe-Sophe-XeprView((R)) computer simulation software suite enables scientists to easily determine spin Hamiltonian parameters from isotropic, randomly oriented and single crystal continuous wave electron paramagnetic resonance (CW EPR) spectra from radicals and isolated paramagnetic metal ion centers or clusters found in metalloproteins, chemical systems and materials science. XSophe provides an X-windows graphical user interface to the Sophe programme and allows: creation of multiple input files, local and remote execution of Sophe, the display of sophelog (output from Sophe) and input parameters/files. Sophe is a sophisticated computer simulation software programme employing a number of innovative technologies including; the Sydney OPera HousE (SOPHE) partition and interpolation schemes, a field segmentation algorithm, the mosaic misorientation linewidth model, parallelization and spectral optimisation. In conjunction with the SOPHE partition scheme and the field segmentation algorithm, the SOPHE interpolation scheme and the mosaic misorientation linewidth model greatly increase the speed of simulations for most spin systems. Employing brute force matrix diagonalization in the simulation of an EPR spectrum from a high spin Cr(III) complex with the spin Hamiltonian parameters g(e) = 2.00, D = 0.10 cm(-1), E/D = 0.25, A(x) = 120.0, A(y) = 120.0, A(z) = 240.0 x 10(-4) cm(-1) requires a SOPHE grid size of N = 400 (to produce a good signal to noise ratio) and takes 229.47 s. In contrast the use of either the SOPHE interpolation scheme or the mosaic misorientation linewidth model requires a SOPHE grid size of only N = 18 and takes 44.08 and 0.79 s, respectively. Results from Sophe are transferred via the Common Object Request Broker Architecture (CORBA) to XSophe and subsequently to XeprView((R)) where the simulated CW EPR spectra (1D and 2D) can be compared to the experimental spectra. Energy level diagrams, transition roadmaps and transition surfaces aid the interpretation of complicated randomly oriented CW EPR spectra and can be viewed with a web browser and an OpenInventor scene graph viewer.

Characterisation of Australian isolates of Fusarium oxysporum f. sp cubense by DNA fingerprinting analysis

Genetic variation among Australian isolates of the fungus Fusarium oxysporum f. sp. cubense (Foc), which causes Fusarium wilt in banana, was examined using DNA amplification fingerprinting (DAF). Ninety-four isolates which represented Races 1, 2, 3, and 4, and vegetative compatibility groups (VCGs) 0120, 0124, 0125, 0128, 0129, 01211, 01213/16, and 01220 were analysed. The genetic relatedness among isolates within each VCG, and between the 8 different VCGs of Foc present in Australia was determined. The DNA fingerprint patterns were VCG-specific, with each VCG representing a unique genotype. The genetic similarity among isolates within each VCG ranged from 97% to 100%. Among the different VCGs of Foc, 3 major clusters were distinguished which corresponded with race. All Race 1 and 2 isolates (VCGs 0124, 0125, 0128, and 01220) were closely related and clustered together, the Race 3 isolates from Heliconia clustered separately, and all Race 4 isolates (VCGs 0120, 0129, 01211, and 01213/16) clustered together. Fifteen isolates from Alstonville, NSW, were characterised because although they were classified as Race 2 based on their recovery from cooking banana cultivars, they belonged in VCG 0124, which had previously contained only Race 1 isolates. The occurrence of more than one race within a VCG means that vegetative compatibility grouping cannot be used to assign pathotype to pathogenic race as previously thought. It was possible to distinguish the Race 1 and Race 2 isolates within VCG 0124 using DNA fingerprinting, as each race produced a unique DNA fingerprint pattern. Among the Australian isolates, DNA fingerprinting analysis identified 9 different VCGs and genotypes of Foc.

Adoption of Strategic Alliances by Shoes Industries of the Vale do Rio dos Sinos-RS and Franca-SP clusters: an exploratory study

The new environment of the companies, result of the relative opening of the market caused by the globalization has set a new challenge to assure the continuity of the businesses. Competitive strategies have been implemented aiming to overcome such challenge and, amongst them, strategic alliances have shown to be a viable alternative. In this context, this article has as objective to investigate the degree of use of strategic alliances by the medium and large companies of the shoes industries located in clusters of Vale do Rio dos Sinos (RS) and Franca (SP). This exploratory and descriptive research had the participation of 54 companies, being 3 from Vale do Rio dos Sinos and 21 from Franca, which answered a questionnaire with closed questions. The analysis of the data was given through descriptive statistics. Main conclusions, follow as: (1) the majority of the companies have joint activities; (2) the companies are nearer to alliances that do business than to the strategic ones; (3) alliances with competitors are inexpressive - suppliers and customers predominate; (4) the control of alliances result is insufficient; (5) trust and adequate partner are determinative factors.

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.

Identification of FAM46D as a novel cancer/testis antigen using EST data and serological analysis

Cancer/testis Antigens (CTAs) are immunogenic proteins with a restricted expression pattern in normal tissues and aberrant expression in different types of tumors being considered promising candidates for immunotherapy. We used the alignment between EST sequences and the human genome sequence to identify novel CT genes. By examining the EST tissue composition of known CT clusters we defined parameters for the selection of 1184 EST clusters corresponding to putative CT genes. The expression pattern of 70 CT gene candidates was evaluated by RT-PCR in 21 normal tissues, 17 tumor cell lines and 160 primary tumors. We were able to identify 4 CT genes expressed in different types of tumors. The presence of antibodies against the protein encoded by 1 of these 4 CT genes (FAM46D) was exclusively detected in plasma samples from cancer patients. Due to its restricted expression pattern and immunogenicity FAM46D represents a novel target for cancer immunotherapy. (c) 2009 Elsevier Inc. All rights reserved.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. 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.

Analysis of the Nicotiana tabacum Stigma/Style Transcriptome Reveals Gene Expression Differences between Wet and Dry Stigma Species

The success of plant reproduction depends on pollen-pistil interactions occurring at the stigma/style. These interactions vary depending on the stigma type: wet or dry. Tobacco (Nicotiana tabacum) represents a model of wet stigma, and its stigmas/styles express genes to accomplish the appropriate functions. For a large-scale study of gene expression during tobacco pistil development and preparation for pollination, we generated 11,216 high-quality expressed sequence tags (ESTs) from stigmas/styles and created the TOBEST database. These ESTs were assembled in 6,177 clusters, from which 52.1% are pistil transcripts/genes of unknown function. The 21 clusters with the highest number of ESTs (putative higher expression levels) correspond to genes associated with defense mechanisms or pollen-pistil interactions. The database analysis unraveled tobacco sequences homologous to the Arabidopsis (Arabidopsis thaliana) genes involved in specifying pistil identity or determining normal pistil morphology and function. Additionally, 782 independent clusters were examined by macroarray, revealing 46 stigma/style preferentially expressed genes. Real-time reverse transcription-polymerase chain reaction experiments validated the pistil-preferential expression for nine out of 10 genes tested. A search for these 46 genes in the Arabidopsis pistil data sets demonstrated that only 11 sequences, with putative equivalent molecular functions, are expressed in this dry stigma species. The reverse search for the Arabidopsis pistil genes in the TOBEST exposed a partial overlap between these dry and wet stigma transcriptomes. The TOBEST represents the most extensive survey of gene expression in the stigmas/styles of wet stigma plants, and our results indicate that wet and dry stigmas/styles express common as well as distinct genes in preparation for the pollination process.

Quaternary continental weathering geochronology by laser-heating Ar-40/Ar-39 analysis of supergene cryptomelane

Incremental laser-heating analyses of supergene cryptomelane clusters extracted from three distinct weathering profiles from the Mary Valley region, southeast Queensland, Australia, yield reproducible and well-defined plateau ages ranging from 346 +/- 15 to 291 +/- 14 ka (2 a). Precipitation of supergene cryptomelane in this period implies that relative humid climate prevailed in southeast Queensland from 340 to 290 ha, a result consistent with oxygen isotope analyses of marine sediments from Ocean Drilling Program Site 820 and with regional pollen and spore records. These results, the first report on the precise Ar-40/Ar-39 dating of Quaternary supergene cryptomelane, indicate that Ar-40/Ar-39 analysis of pedogenic minerals provides a reliable geochronometer for the study of Quaternary surficial processes useful in the study of soil formation rates, continental paleoclimates, and archaeological sites devoid of datable volcanic minerals.

Analysis of the microbial community structure and function of a laboratory scale enhanced biological phosphorus removal reactor

A laboratory scale sequencing batch reactor (SBR) operating for enhanced biological phosphorus removal (EBPR) and fed with a mixture of volatile fatty acids (VFAs) showed stable and efficient EBPR capacity over a four-year-period. Phosphorus (P), poly-beta-hydroxyalkanoate (PHA) and glycogen cycling consistent with classical anaerobic/aerobic EBPR were demonstrated with the order of anaerobic VFA uptake being propionate, acetate then butyrate. The SBR was operated without pH control and 63.67+/-13.86 mg P l(-1) was released anaerobically. The P% of the sludge fluctuated between 6% and 10% over the operating period (average of 8.04+/-1.31%). Four main morphological types of floc-forming bacteria were observed in the sludge during one year of in-tensive microscopic observation. Two of them were mainly responsible for anaerobic/aerobic P and PHA transformations. Fluorescence in situ hybridization (FISH) and post-FISH chemical staining for intracellular polyphosphate and PHA were used to determine that 'Candidatus Accumulibacter phosphatis' was the most abundant polyphosphate accumulating organism (PAO), forming large clusters of coccobacilli (1.0-1.5 mum) and comprising 53% of the sludge bacteria. Also by these methods, large coccobacillus-shaped gammaproteobacteria (2.5-3.5 mum) from a recently described novel cluster were glycogen-accumulating organisms (GAOs) comprising 13% of the bacteria. Tetrad-forming organisms (TFOs) consistent with the 'G bacterium' morphotype were alphaproteobacteria , but not Amaricoccus spp., and comprised 25% of all bacteria. According to chemical staining, TFOs were occasionally able to store PHA anaerobically and utilize it aerobically.

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.