Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

Conserved hydrophobic clusters on the surface of the Caf1A usher C-terminal domain are important for F1 antigen assembly

The outer membrane usher protein Caf1A of the plague pathogen Yersinia pestis is responsible for the assembly of a major surface antigen, the F1 capsule. The F1 capsule is mainly formed by thin linear polymers of Caf1 (capsular antigen fraction 1) protein subunits. The Caf1A usher promotes polymerization of subunits and secretion of growing polymers to the cell surface. The usher monomer (811 aa, 90.5 kDa) consists of a large transmembrane β-barrel that forms a secretion channel and three soluble domains. The periplasmic N-terminal domain binds chaperone-subunit complexes supplying new subunits for the growing fiber. The middle domain, which is structurally similar to Caf1 and other fimbrial subunits, serves as a plug that regulates the permeability of the usher. Here we describe the identification, characterization, and crystal structure of the Caf1A usher C-terminal domain (Caf1A(C)). Caf1A(C) is shown to be a periplasmic domain with a seven-stranded β-barrel fold. Analysis of C-terminal truncation mutants of Caf1A demonstrated that the presence of Caf1A(C) is crucial for the function of the usher in vivo, but that it is not required for the initial binding of chaperone-subunit complexes to the usher. Two clusters of conserved hydrophobic residues on the surface of Caf1A(C) were found to be essential for the efficient assembly of surface polymers. These clusters are conserved between the FGL family and the FGS family of chaperone-usher systems.

Cluster analysis for multivariable process control

This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.

Innovation clusters: key concepts

Innovation is easier to describe than it is to systematically analyse, and easier to analyse than it is to effectively promote. Part of the problem, of course, is the imprecise way in which the activity of innovation itself is conceptualised. To achieve more precision, the logic of analysis suggests that innovation should be should be systematically analysed and then divided into rough categories to produce a working taxonomy based on a number of key dimensions. A major part of the purpose of this paper is to develop such a working taxonomy.

Plant-symbiotic fungi as chemical engineers: multi-genome analysis of the Clavicipitaceae reveals dynamics of alkaloid Loci

The fungal family Clavicipitaceae includes plant symbionts and parasites that produce several psychoactive and bioprotective alkaloids. The family includes grass symbionts in the epichloae clade (Epichloë and Neotyphodium species), which are extraordinarily diverse both in their host interactions and in their alkaloid profiles. Epichloae produce alkaloids of four distinct classes, all of which deter insects, and some—including the infamous ergot alkaloids—have potent effects on mammals. The exceptional chemotypic diversity of the epichloae may relate to their broad range of host interactions, whereby some are pathogenic and contagious, others are mutualistic and vertically transmitted (seed-borne), and still others vary in pathogenic or mutualistic behavior. We profiled the alkaloids and sequenced the genomes of 10 epichloae, three ergot fungi (Claviceps species), a morning-glory symbiont (Periglandula ipomoeae), and a bamboo pathogen (Aciculosporium take), and compared the gene clusters for four classes of alkaloids. Results indicated a strong tendency for alkaloid loci to have conserved cores that specify the skeleton structures and peripheral genes that determine chemical variations that are known to affect their pharmacological specificities. Generally, gene locations in cluster peripheries positioned them near to transposon-derived, AT-rich repeat blocks, which were probably involved in gene losses, duplications, and neofunctionalizations. The alkaloid loci in the epichloae had unusual structures riddled with large, complex, and dynamic repeat blocks. This feature was not reflective of overall differences in repeat contents in the genomes, nor was it characteristic of most other specialized metabolism loci. The organization and dynamics of alkaloid loci and abundant repeat blocks in the epichloae suggested that these fungi are under selection for alkaloid diversification. We suggest that such selection is related to the variable life histories of the epichloae, their protective roles as symbionts, and their associations with the highly speciose and ecologically diverse cool-season grasses.

Extreme wind storms over Europe in present and future climate: a cluster analysis approach

Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.

Analysis of functional networks involved in motor execution and motor imagery using combined hierarchical clustering analysis and independent component analysis

Cognitive experiments involving motor execution (ME) and motor imagery (MI) have been intensively studied using functional magnetic resonance imaging (fMRI). However, the functional networks of a multitask paradigm which include ME and MI were not widely explored. In this article, we aimed to investigate the functional networks involved in MI and ME using a method combining the hierarchical clustering analysis (HCA) and the independent component analysis (ICA). Ten right-handed subjects were recruited to participate a multitask experiment with conditions such as visual cue, MI, ME and rest. The results showed that four activation clusters were found including parts of the visual network, ME network, the MI network and parts of the resting state network. Furthermore, the integration among these functional networks was also revealed. The findings further demonstrated that the combined HCA with ICA approach was an effective method to analyze the fMRI data of multitasks.

Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.

Hidden Markov analysis describes dive patterns in semiaquatic animals

Existing methods of dive analysis, developed for fully aquatic animals, tend to focus on frequency of behaviors rather than transitions between them. They, therefore, do not account for the variability of behavior of semiaquatic animals, and the switching between terrestrial and aquatic environments. This is the first study to use hidden Markov models (HMM) to divide dives of a semiaquatic animal into clusters and thus identify the environmental predictors of transition between behavioral modes. We used 18 existing data sets of the dives of 14 American mink (Neovison vison) fitted with time-depth recorders in lowland England. Using HMM, we identified 3 behavioral states (1, temporal cluster of dives; 2, more loosely aggregated diving within aquatic activity; and 3, terminal dive of a cluster or a single, isolated dive). Based on the higher than expected proportion of dives in State 1, we conclude that mink tend to dive in clusters. We found no relationship between temperature and the proportion of dives in each state or between temperature and the rate of transition between states, meaning that in our study area, mink are apparently not adopting different diving strategies at different temperatures. Transition analysis between states has shown that there is no correlation between ambient temperature and the likelihood of mink switching from one state to another, that is, changing foraging modes. The variables provided good discrimination and grouped into consistent states well, indicating promise for further application of HMM and other state transition analyses in studies of semiaquatic animals.

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles

Background: The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. New method: We propose a complete pipeline for the cluster analysis of ERP data. To increase the signalto-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA)to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). Results: After validating the pipeline on simulated data, we tested it on data from two experiments – a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.

Measurement of the epicycle frequency in the Galactic disc and initial velocities of open clusters

A new method to measure the epicycle frequency kappa in the Galactic disc is presented. We make use of the large data base on open clusters completed by our group to derive the observed velocity vector (amplitude and direction) of the clusters in the Galactic plane. In the epicycle approximation, this velocity is equal to the circular velocity given by the rotation curve, plus a residual or perturbation velocity, of which the direction rotates as a function of time with the frequency kappa. Due to the non-random direction of the perturbation velocity at the birth time of the clusters, a plot of the present-day direction angle of this velocity as a function of the age of the clusters reveals systematic trends from which the epicycle frequency can be obtained. Our analysis considers that the Galactic potential is mainly axis-symmetric, or in other words, that the effect of the spiral arms on the Galactic orbits is small; in this sense, our results do not depend on any specific model of the spiral structure. The values of kappa that we obtain provide constraints on the rotation velocity of the in particular, V(0) is found to be 230 +/- 15 km s(-1) even if the scale (R(0) = 7.5 kpc) of the Galaxy is adopted. The measured kappa at the solar radius is 43 +/- 5 km s(-1) kpc(-1). The distribution of initial velocities of open clusters is discussed.

An analysis of the composite stellar population in M32

We obtained long-slit spectra of high signal-to-noise ratio of the galaxy M32 with the Gemini Multi-Object Spectrograph at the Gemini-North telescope. We analysed the integrated spectra by means of full spectral fitting in order to extract the mixture of stellar populations that best represents its composite nature. Three different galactic radii were analysed, from the nuclear region out to 2 arcmin from the centre. This allows us to compare, for the first time, the results of integrated light spectroscopy with those of resolved colour-magnitude diagrams from the literature. As a main result we propose that an ancient and an intermediate-age population co-exist in M32, and that the balance between these two populations change between the nucleus and outside one effective radius (1r(eff)) in the sense that the contribution from the intermediate population is larger at the nuclear region. We retrieve a smaller signal of a young population at all radii whose origin is unclear and may be a contamination from horizontal branch stars, such as the ones identified by Brown et al. in the nuclear region. We compare our metallicity distribution function for a region 1 to 2 arcmin from the centre to the one obtained with photometric data by Grillmair et al. Both distributions are broad, but our spectroscopically derived distribution has a significant component with [Z/Z(circle dot)] <= -1, which is not found by Grillmair et al.

Global properties of `ordinary` early-type galaxies: photometry and spectroscopy of stars and globular clusters in NGC 4494

We present a comprehensive analysis of the spatial, kinematic and chemical properties of stars and globular clusters (GCs) in the `ordinary` elliptical galaxy NGC 4494 using data from the Keck and Subaru telescopes. We derive galaxy surface brightness and colour profiles out to large galactocentric radii. We compare the latter to metallicities derived using the near-infrared Calcium Triplet. We obtain stellar kinematics out to similar to 3.5 effective radii. The latter appear flattened or elongated beyond similar to 1.8 effective radii in contrast to the relatively round photometric isophotes. In fact, NGC 4494 may be a flattened galaxy, possibly even an S0, seen at an inclination of similar to 45 degrees. We publish a catalogue of 431 GC candidates brighter than i(0) = 24 based on the photometry, of which 109 are confirmed spectroscopically and 54 have measured spectroscopic metallicities. We also report the discovery of three spectroscopically confirmed ultra-compact dwarfs around NGC 4494 with measured metallicities of -0.4 less than or similar to [Fe/H] less than or similar to -0.3. Based on their properties, we conclude that they are simply bright GCs. The metal-poor GCs are found to be rotating with similar amplitude as the galaxy stars, while the metal-rich GCs show marginal rotation. We supplement our analysis with available literature data and results. Using model predictions of galaxy formation, and a suite of merger simulations, we find that many of the observational properties of NGC 4494 may be explained by formation in a relatively recent gas-rich major merger. Complete studies of individual galaxies incorporating a range of observational avenues and methods such as the one presented here will be an invaluable tool for constraining the fine details of galaxy formation models, especially at large galactocentric radii.

The Genetics of Alzheimer`s Disease in Brazil: 10 Years of Analysis in a Unique Population

Alzheimer`s Disease (AD) is the most common type of dementia among the elderly, with devastating consequences for the patient, their relatives, and caregivers. More than 300 genetic polymorphisms have been involved with AD, demonstrating that this condition is polygenic and with a complex pattern of inheritance. This paper aims to report and compare the results of AD genetics studies in case-control and familial analysis performed in Brazil since our first publication, 10 years ago. They include the following genes/markers: Apolipoprotein E (APOE), 5-hidroxytryptamine transporter length polymorphic region (5-HTTLPR), brain-derived neurotrophin factor (BDNF), monoamine oxidase A (MAO-A), and two simple-sequence tandem repeat polymorphisms (DXS1047 and D10S1423). Previously unpublished data of the interleukin-1 alpha (IL-1 alpha) and interleukin-1 beta (IL-1 beta) genes are reported here briefly. Results from others Brazilian studies with AD patients are also reported at this short review. Four local families studied with various markers at the chromosome 21, 19, 14, and 1 are briefly reported for the first time. The importance of studying DNA samples from Brazil is highlighted because of the uniqueness of its population, which presents both intense ethnical miscegenation, mainly at the east coast, but also clusters with high inbreeding rates in rural areas at the countryside. We discuss the current stage of extending these studies using high-throughput methods of large-scale genotyping, such as single nucleotide polymorphism microarrays, associated with bioinformatics tools that allow the analysis of such extensive number of genetics variables, with different levels of penetrance. There is still a long way between the huge amount of data gathered so far and the actual application toward the full understanding of AD, but the final goal is to develop precise tools for diagnosis and prognosis, creating new strategies for better treatments based on genetic profile.

Phylogenetic analysis of a near-full-length sequence of an erythrovirus genotype 3 strain isolated in Brazil

Human parvovirus B19 is the only member of the genus Erythrovirus that causes human disease. Recent findings of several strains with considerable sequence divergence from B19 have suggested a new classification for parvovirus genotypes as 1 (B19), 2 (A-6 and LaLi) and 3 (V9). In their overall DNA sequence, the three genotypes differ by similar to 10%. Here, we report the isolation of a genotype-3-related strain named BR543 during a prospective study conducted in Sao Paulo, Brazil. Analysis of the nearly full-length genome sequence of BR543 indicates that this B19 variant sequence clusters with Gh2768, a strain from Ghana belonging to subtype 3b, and showed mostly synonymous substitutions.