Associations of racial discrimination and parental discrimination coping messages with African American adolescent racial identity.

PubMed

Richardson, Bridget L; Macon, Tamarie A; Mustafaa, Faheemah N; Bogan, Erin D; Cole-Lewis, Yasmin; Chavous, Tabbye M

2015-06-01

Research links racial identity to important developmental outcomes among African American adolescents, but less is known about the contextual experiences that shape youths' racial identity. In a sample of 491 African American adolescents (48% female), associations of youth-reported experiences of racial discrimination and parental messages about preparation for racial bias with adolescents' later racial identity were examined. Cluster analysis resulted in four profiles of adolescents varying in reported frequency of racial discrimination from teachers and peers at school and frequency of parental racial discrimination coping messages during adolescents' 8th grade year. Boys were disproportionately over-represented in the cluster of youth experiencing more frequent discrimination but receiving fewer parental discrimination coping messages, relative to the overall sample. Also examined were clusters of adolescents' 11th grade racial identity attitudes about the importance of race (centrality), personal group affect (private regard), and perceptions of societal beliefs about African Americans (public regard). Girls and boys did not differ in their representation in racial identity clusters, but 8th grade discrimination/parent messages clusters were associated with 11th grade racial identity cluster membership, and these associations varied across gender groups. Boys experiencing more frequent discrimination but fewer parental coping messages were over-represented in the racial identity cluster characterized by low centrality, low private regard, and average public regard. The findings suggest that adolescents who experience racial discrimination but receive fewer parental supports for negotiating and coping with discrimination may be at heightened risk for internalizing stigmatizing experiences. Also, the findings suggest the need to consider the context of gender in adolescents' racial discrimination and parental racial socialization.

Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling.

PubMed

Chen, Vicky; Paisley, John; Lu, Xinghua

2017-03-14

Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Identifying knowledge activism in worker health and safety representation: A cluster analysis.

PubMed

Hall, Alan; Oudyk, John; King, Andrew; Naqvi, Syed; Lewchuk, Wayne

2016-01-01

Although worker representation in OHS has been widely recognized as contributing to health and safety improvements at work, few studies have examined the role that worker representatives play in this process. Using a large quantitative sample, this paper seeks to confirm findings from an earlier exploratory qualitative study that worker representatives can be differentiated by the knowledge intensive tactics and strategies that they use to achieve changes in their workplace. Just under 900 worker health and safety representatives in Ontario completed surveys which asked them to report on the amount of time they devoted to different types of representation activities (i.e., technical activities such as inspections and report writing vs. political activities such as mobilizing workers to build support), the kinds of conditions or hazards they tried to address through their representation (e.g., housekeeping vs. modifications in ventilation systems), and their reported success in making positive improvements. A cluster analysis was used to determine whether the worker representatives could be distinguished in terms of the relative time devoted to different activities and the clusters were then compared with reference to types of intervention efforts and outcomes. The cluster analysis identified three distinct groupings of representatives with significant differences in reported types of interventions and in their level of reported impact. Two of the clusters were consistent with the findings in the exploratory study, identified as knowledge activism for greater emphasis on knowledge based political activity and technical-legal representation for greater emphasis on formalized technical oriented procedures and legal regulations. Knowledge activists were more likely to take on challenging interventions and they reported more impact across the full range of interventions. This paper provides further support for the concepts of knowledge activism and technical-legal representation when differentiating the strategic orientations and impact of worker health and safety representatives, with important implications for education, political support and recruitment. © 2015 Wiley Periodicals, Inc.

The riddle of Tasmanian languages

PubMed Central

Bowern, Claire

2012-01-01

Recent work which combines methods from linguistics and evolutionary biology has been fruitful in discovering the history of major language families because of similarities in evolutionary processes. Such work opens up new possibilities for language research on previously unsolvable problems, especially in areas where information from other sources may be lacking. I use phylogenetic methods to investigate Tasmanian languages. Existing materials are so fragmentary that scholars have been unable to discover how many languages are represented in the sources. Using a clustering algorithm which identifies admixture, source materials representing more than one language are identified. Using the Neighbor-Net algorithm, 12 languages are identified in five clusters. Bayesian phylogenetic methods reveal that the families are not demonstrably related; an important result, given the importance of Tasmanian Aborigines for information about how societies have responded to population collapse in prehistory. This work provides insight into the societies of prehistoric Tasmania and illustrates a new utility of phylogenetics in reconstructing linguistic history. PMID:23015621

amoA-based consensus phylogeny of ammonia-oxidizing archaea and deep sequencing of amoA genes from soils of four different geographic regions

PubMed Central

Pester, Michael; Rattei, Thomas; Flechl, Stefan; Gröngröft, Alexander; Richter, Andreas; Overmann, Jörg; Reinhold-Hurek, Barbara; Loy, Alexander; Wagner, Michael

2012-01-01

Ammonia-oxidizing archaea (AOA) play an important role in nitrification and many studies exploit their amoA genes as marker for their diversity and abundance. We present an archaeal amoA consensus phylogeny based on all publicly available sequences (status June 2010) and provide evidence for the diversification of AOA into four previously recognized clusters and one newly identified major cluster. These clusters, for which we suggest a new nomenclature, harboured 83 AOA species-level OTU (using an inferred species threshold of 85% amoA identity). 454 pyrosequencing of amoA amplicons from 16 soils sampled in Austria, Costa Rica, Greenland and Namibia revealed that only 2% of retrieved sequences had no database representative on the species-level and represented 30–37 additional species-level OTUs. With the exception of an acidic soil from which mostly amoA amplicons of the Nitrosotalea cluster were retrieved, all soils were dominated by amoA amplicons from the Nitrososphaera cluster (also called group I.1b), indicating that the previously reported AOA from the Nitrosopumilus cluster (also called group I.1a) are absent or represent minor populations in soils. AOA richness estimates on the species level ranged from 8–83 co-existing AOAs per soil. Presence/absence of amoA OTUs (97% identity level) correlated with geographic location, indicating that besides contemporary environmental conditions also dispersal limitation across different continents and/or historical environmental conditions might influence AOA biogeography in soils. PMID:22141924

Butyrate production in phylogenetically diverse Firmicutes isolated from the chicken caecum

PubMed Central

Eeckhaut, Venessa; Van Immerseel, Filip; Croubels, Siska; De Baere, Siegrid; Haesebrouck, Freddy; Ducatelle, Richard; Louis, Petra; Vandamme, Peter

2011-01-01

Summary Sixteen butyrate‐producing bacteria were isolated from the caecal content of chickens and analysed phylogenetically. They did not represent a coherent phylogenetic group, but were allied to four different lineages in the Firmicutes phylum. Fourteen strains appeared to represent novel species, based on a level of ≤ 98.5% 16S rRNA gene sequence similarity towards their nearest validly named neighbours. The highest butyrate concentrations were produced by the strains belonging to clostridial clusters IV and XIVa, clusters which are predominant in the chicken caecal microbiota. In only one of the 16 strains tested, the butyrate kinase operon could be amplified, while the butyryl‐CoA : acetate CoA‐transferase gene was detected in eight strains belonging to clostridial clusters IV, XIVa and XIVb. None of the clostridial cluster XVI isolates carried this gene based on degenerate PCR analyses. However, another CoA‐transferase gene more similar to propionate CoA‐transferase was detected in the majority of the clostridial cluster XVI isolates. Since this gene is located directly downstream of the remaining butyrate pathway genes in several human cluster XVI bacteria, it may be involved in butyrate formation in these bacteria. The present study indicates that butyrate producers related to cluster XVI may play a more important role in the chicken gut than in the human gut. PMID:21375722

Primordial binary populations in low-density star clusters as seen by Chandra: globular clusters versus old open clusters

NASA Astrophysics Data System (ADS)

van den Berg, Maureen C.

2015-08-01

The binaries in the core of a star cluster are the energy source that prevents the cluster from experiencing core collapse. To model the dynamical evolution of a cluster, it is important to have constraints on the primordial binary content. X-ray observations of old star clusters are very efficient in detecting the close interacting binaries among the cluster members. The X-ray sources in star clusters are a mix of binaries that were dynamically formed and primordial binaries. In massive, dense star clusters, dynamical encounters play an important role in shaping the properties and numbers of the binaries. In contrast, in the low-density clusters the impact of dynamical encounters is presumed to be very small, and the close binaries detected in X-rays represent a primordial population. The lowest density globular clusters have current masses and central densities similar to those of the oldest open clusters in our Milky Way. I will discuss the results of studies with the Chandra X-ray Observatory that have nevertheless revealed a clear dichotomy: far fewer (if any at all) X-ray sources are detected in the central regions of the low-density globular clusters compared to the number of secure cluster members that have been detected in old open clusters (above a limiting X-ray luminosity of typically 4e30 erg/s). The low stellar encounter rates imply that dynamical destruction of binaries can be ignored at present, therefore an explanation must be sought elsewhere. I will discuss several factors that can shed light on the implied differences between the primordial close binary populations in the two types of star clusters.

Tumor-initiating cells of breast and prostate origin show alterations in the expression of genes related to iron metabolism

PubMed Central

Tomkova, Veronika; Korenkova, Vlasta; Langerova, Lucie; Simonova, Ekaterina; Zjablovskaja, Polina; Alberich-Jorda, Meritxell; Neuzil, Jiri; Truksa, Jaroslav

2017-01-01

The importance of iron in the growth and progression of tumors has been widely documented. In this report, we show that tumor-initiating cells (TICs), represented by spheres derived from the MCF7 cell line, exhibit higher intracellular labile iron pool, mitochondrial iron accumulation and are more susceptible to iron chelation. TICs also show activation of the IRP/IRE system, leading to higher iron uptake and decrease in iron storage, suggesting that level of properly assembled cytosolic iron-sulfur clusters (FeS) is reduced. This finding is confirmed by lower enzymatic activity of aconitase and FeS cluster biogenesis enzymes, as well as lower levels of reduced glutathione, implying reduced FeS clusters synthesis/utilization in TICs. Importantly, we have identified specific gene signature related to iron metabolism consisting of genes regulating iron uptake, mitochondrial FeS cluster biogenesis and hypoxic response (ABCB10, ACO1, CYBRD1, EPAS1, GLRX5, HEPH, HFE, IREB2, QSOX1 and TFRC). Principal component analysis based on this signature is able to distinguish TICs from cancer cells in vitro and also Leukemia-initiating cells (LICs) from non-LICs in the mouse model of acute promyelocytic leukemia (APL). Majority of the described changes were also recapitulated in an alternative model represented by MCF7 cells resistant to tamoxifen (TAMR) that exhibit features of TICs. Our findings point to the critical importance of redox balance and iron metabolism-related genes and proteins in the context of cancer and TICs that could be potentially used for cancer diagnostics or therapy. PMID:28031527

Swarm v2: highly-scalable and high-resolution amplicon clustering.

PubMed

Mahé, Frédéric; Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Polymorphism in magic-sized Au144(SR)60 clusters

NASA Astrophysics Data System (ADS)

Jensen, Kirsten M. Ø.; Juhas, Pavol; Tofanelli, Marcus A.; Heinecke, Christine L.; Vaughan, Gavin; Ackerson, Christopher J.; Billinge, Simon J. L.

2016-06-01

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. Here we present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. The study reveals structural polymorphism in these archetypal nanoclusters. In addition to confirming the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. The discovery of polymorphism may open up a new dimension in nanoscale engineering.

The Acid-Base Properties, Hydrolytic Mechanism, and Susceptibility to O2 Oxidation of Fe4S4(SR)4-2 Clusters

PubMed Central

Bruice, Thomas C.; Maskiewicz, Richard; Job, Robert

1975-01-01

The iron-sulfur cluster compounds Fe4S4(SR)4-2 [where —SR = —SCH3, —S—C(CH3)3, and —S— CH2—CH(CH3)2] have been found to represent the base species of weak acids of pKa comparable to that of carboxylic acids. The acid species Fe4S4(SR)4H- is most subject to reaction with O2 and to acid-catalyzed solvolysis, while the base species Fe4S4(SR)4-2 most readily undergoes ligand exchange. The kinetics for hydrolysis of the isobutyl mercaptide cluster salt has been investigated in detail and a mechanism involving the stepwise process [Formula: see text] has been proposed. The importance of the acid-base equilibria in determining the reactivity of the iron-sulfur clusters and its possible importance as a factor in the determination of the potentials of ferredoxins and high potential iron protein are discussed. PMID:16592211

Slider thickness promotes lubricity: from 2D islands to 3D clusters

NASA Astrophysics Data System (ADS)

Guerra, Roberto; Tosatti, Erio; Vanossi, Andrea

2016-05-01

The sliding of three-dimensional clusters and two-dimensional islands adsorbed on crystal surfaces represents an important test case to understand friction. Even for the same material, monoatomic islands and thick clusters will not as a rule exhibit the same friction, but specific differences have not been explored. Through realistic molecular dynamics simulations of the static friction of gold on graphite, an experimentally relevant system, we uncover as a function of gold thickness a progressive drop of static friction from monolayer islands, that are easily pinned, towards clusters, that slide more readily. The main ingredient contributing to this thickness-induced lubricity appears to be the increased effective rigidity of the atomic contact, acting to reduce the cluster interdigitation with the substrate. A second element which plays a role is the lateral contact size, which can accommodate the solitons typical of the incommensurate interface only above a critical contact diameter, which is larger for monolayer islands than for thick clusters. The two effects concur to make clusters more lubric than islands, and large sizes more lubric than smaller ones. These conclusions are expected to be of broader applicability in diverse nanotribological systems, where the role played by static, and dynamic, friction is generally quite important.

Slider thickness promotes lubricity: from 2D islands to 3D clusters.

PubMed

Guerra, Roberto; Tosatti, Erio; Vanossi, Andrea

2016-06-07

The sliding of three-dimensional clusters and two-dimensional islands adsorbed on crystal surfaces represents an important test case to understand friction. Even for the same material, monoatomic islands and thick clusters will not as a rule exhibit the same friction, but specific differences have not been explored. Through realistic molecular dynamics simulations of the static friction of gold on graphite, an experimentally relevant system, we uncover as a function of gold thickness a progressive drop of static friction from monolayer islands, that are easily pinned, towards clusters, that slide more readily. The main ingredient contributing to this thickness-induced lubricity appears to be the increased effective rigidity of the atomic contact, acting to reduce the cluster interdigitation with the substrate. A second element which plays a role is the lateral contact size, which can accommodate the solitons typical of the incommensurate interface only above a critical contact diameter, which is larger for monolayer islands than for thick clusters. The two effects concur to make clusters more lubric than islands, and large sizes more lubric than smaller ones. These conclusions are expected to be of broader applicability in diverse nanotribological systems, where the role played by static, and dynamic, friction is generally quite important.

The Mass Function of Young Star Clusters in the "Antennae" Galaxies.

PubMed

Zhang; Fall

1999-12-20

We determine the mass function of young star clusters in the merging galaxies known as the "Antennae" (NGC 4038/9) from deep images taken with the Wide Field Planetary Camera 2 on the refurbished Hubble Space Telescope. This is accomplished by means of reddening-free parameters and a comparison with stellar population synthesis tracks to estimate the intrinsic luminosity and age, and hence the mass, of each cluster. We find that the mass function of the young star clusters (with ages less, similar160 Myr) is well represented by a power law of the form psi&parl0;M&parr0;~M-2 over the range 104 less, similarM less, similar106 M middle dot in circle. This result may have important implications for our understanding of the origin of globular clusters during the early phases of galactic evolution.

Faculty Turnover: Discipline-Specific Attention Is Warranted

ERIC Educational Resources Information Center

Xu, Yonghong Jade

2008-01-01

This study investigated the importance of discipline variations in understanding faculty turnover behaviors. A representative sample of university faculty in Research and Doctoral universities was obtained from a national database. Faculty members, self-identified into a primary academic area, were grouped into eight discipline clusters according…

Polymorphism in magic-sized Au144(SR)60 clusters

DOE PAGES

Jensen, Kirsten M. O.; Juhas, Pavol; Tofanelli, Marcus A.; ...

2016-06-14

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. We present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. Our study reveals structural polymorphism in these archetypal nanoclusters. Additionally, in order to confirm the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. Finally,more » the discovery of polymorphism may open up a new dimension in nanoscale engineering.« less

Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis.

PubMed

Moore, Wendy C; Hastie, Annette T; Li, Xingnan; Li, Huashi; Busse, William W; Jarjour, Nizar N; Wenzel, Sally E; Peters, Stephen P; Meyers, Deborah A; Bleecker, Eugene R

2014-06-01

Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified 5 asthma subphenotypes that represent the severity spectrum of early-onset allergic asthma, late-onset severe asthma, and severe asthma with chronic obstructive pulmonary disease characteristics. Analysis of induced sputum from a subset of SARP subjects showed 4 sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophil (≥2%) and neutrophil (≥40%) percentages had characteristics of very severe asthma. To better understand interactions between inflammation and clinical subphenotypes, we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Participants in SARP who underwent sputum induction at 3 clinical sites were included in this analysis (n = 423). Fifteen variables, including clinical characteristics and blood and sputum inflammatory cell assessments, were selected using factor analysis for unsupervised cluster analysis. Four phenotypic clusters were identified. Cluster A (n = 132) and B (n = 127) subjects had mild-to-moderate early-onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of cluster C (n = 117) and D (n = 47) subjects who had moderate-to-severe asthma with frequent health care use despite treatment with high doses of inhaled or oral corticosteroids and, in cluster D, reduced lung function. The majority of these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophil percentages were the most important variables determining cluster assignment. This multivariate approach identified 4 asthma subphenotypes representing the severity spectrum from mild-to-moderate allergic asthma with minimal or eosinophil-predominant sputum inflammation to moderate-to-severe asthma with neutrophil-predominant or mixed granulocytic inflammation. Published by Mosby, Inc.

Sputum neutrophils are associated with more severe asthma phenotypes using cluster analysis

PubMed Central

Moore, Wendy C.; Hastie, Annette T.; Li, Xingnan; Li, Huashi; Busse, William W.; Jarjour, Nizar N.; Wenzel, Sally E.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Clinical cluster analysis from the Severe Asthma Research Program (SARP) identified five asthma subphenotypes that represent the severity spectrum of early onset allergic asthma, late onset severe asthma and severe asthma with COPD characteristics. Analysis of induced sputum from a subset of SARP subjects showed four sputum inflammatory cellular patterns. Subjects with concurrent increases in eosinophils (≥2%) and neutrophils (≥40%) had characteristics of very severe asthma. Objective To better understand interactions between inflammation and clinical subphenotypes we integrated inflammatory cellular measures and clinical variables in a new cluster analysis. Methods Participants in SARP at three clinical sites who underwent sputum induction were included in this analysis (n=423). Fifteen variables including clinical characteristics and blood and sputum inflammatory cell assessments were selected by factor analysis for unsupervised cluster analysis. Results Four phenotypic clusters were identified. Cluster A (n=132) and B (n=127) subjects had mild-moderate early onset allergic asthma with paucigranulocytic or eosinophilic sputum inflammatory cell patterns. In contrast, these inflammatory patterns were present in only 7% of Cluster C (n=117) and D (n=47) subjects who had moderate-severe asthma with frequent health care utilization despite treatment with high doses of inhaled or oral corticosteroids, and in Cluster D, reduced lung function. The majority these subjects (>83%) had sputum neutrophilia either alone or with concurrent sputum eosinophilia. Baseline lung function and sputum neutrophils were the most important variables determining cluster assignment. Conclusion This multivariate approach identified four asthma subphenotypes representing the severity spectrum from mild-moderate allergic asthma with minimal or eosinophilic predominant sputum inflammation to moderate-severe asthma with neutrophilic predominant or mixed granulocytic inflammation. PMID:24332216

Spatial suicide clusters in Australia between 2010 and 2012: a comparison of cluster and non-cluster among young people and adults.

PubMed

Robinson, Jo; Too, Lay San; Pirkis, Jane; Spittal, Matthew J

2016-11-22

A suicide cluster has been defined as a group of suicides that occur closer together in time and space than would normally be expected. We aimed to examine the extent to which suicide clusters exist among young people and adults in Australia and to determine whether differences exist between cluster and non-cluster suicides. Suicide data were obtained from the National Coronial Information System for the period 2010 and 2012. Data on date of death, postcode, age at the time of death, sex, suicide method, ICD-10 code for cause of death, marital status, employment status, and aboriginality were retrieved. We examined the presence of spatial clusters separately for youth suicides and adult suicides using the Scan statistic. Pearson's chi-square was used to compare the characteristics of cluster suicides with non-cluster suicides. We identified 12 spatial clusters between 2010 and 2012. Five occurred among young people (n = 53, representing 5.6% [53/940] of youth suicides) and seven occurred among adults (n = 137, representing 2.3% [137/5939] of adult suicides). Clusters ranged in size from three to 21 for youth and from three to 31 for adults. When compared to adults, suicides by young people were significantly more likely to occur as part of a cluster (difference = 3.3%, 95% confidence interval [CI] = 1.8 to 4.8, p < 0.0001). Suicides by people with an Indigenous background were also significantly more likely to occur in a cluster than suicide by non-Indigenous people and this was the case among both young people and adults. Suicide clusters have a significant negative impact on the communities in which they occur. As a result it is important to find effective ways of managing and containing suicide clusters. To date there is limited evidence for the effectiveness of those strategies typically employed, in particular in Indigenous settings, and developing this evidence base needs to be a future priority. Future research that examines in more depth the socio-demographic and clinical factors associated with suicide clusters is also warranted in order that appropriate interventions can be developed.

Swarm v2: highly-scalable and high-resolution amplicon clustering

PubMed Central

Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks. PMID:26713226

The SUNBIRD survey: characterizing the super star cluster populations of intensely star-forming galaxies

NASA Astrophysics Data System (ADS)

Randriamanakoto, Zara; Väisänen, Petri

2017-03-01

Super star clusters (SSCs) represent the youngest and most massive form of known gravitationally bound star clusters in the Universe. They are born abundantly in environments that trigger strong and violent star formation. We investigate the properties of these massive SSCs in a sample of 42 nearby starbursts and luminous infrared galaxies. The targets form the sample of the SUperNovae and starBursts in the InfraReD (SUNBIRD) survey that were imaged using near-infrared (NIR) K-band adaptive optics mounted on the Gemini/NIRI and the VLT/NaCo instruments. Results from i) the fitted power-laws to the SSC K-band luminosity functions, ii) the NIR brightest star cluster magnitude - star formation rate (SFR) relation and iii) the star cluster age and mass distributions have shown the importance of studying SSC host galaxies with high SFR levels to determine the role of the galactic environments in the star cluster formation, evolution and disruption mechanisms.

A person-centered approach to the multifaceted nature of young adult sexual behavior.

PubMed

McGuire, Jenifer K; Barber, Bonnie L

2010-07-01

Young adult sexual relationships were examined using a multifaceted, person-centered approach with data from Wave 7 (aged 20-21; N = 1,126) of the Michigan Study of Adolescent Life Transitions. The study utilized hierarchical cluster analyses based on the following measured variables: frequency of sex, importance of regularly having sex, satisfaction with sex life, experience of coercion for sex, and sexual risk reduction. Five distinct clusters emerged for females (Satisfied, Moderate, Active Unprotected, Pressured, and Inactive) and represented patterns such as more partners paired with less risk reduction (Active Unprotected), high satisfaction paired with frequent sex and high-risk reduction (Satisfied), or higher levels of coercion paired with low satisfaction and low-risk reduction (Pressured). Similar clusters emerged for males, with one additional cluster: the Dissatisfied cluster. Clusters differed with respect to relationship status, marital status, and psychological well-being (both males and females) and parental divorce, living situation, and sexual orientation (females only).

A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

PubMed Central

Nguyen, Nha; Vo, An; Choi, Inchan

2015-01-01

Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

DEFINITION OF MULTIVARIATE GEOCHEMICAL ASSOCIATIONS WITH POLYMETALLIC MINERAL OCCURRENCES USING A SPATIALLY DEPENDENT CLUSTERING TECHNIQUE AND RASTERIZED STREAM SEDIMENT DATA - AN ALASKAN EXAMPLE.

USGS Publications Warehouse

Jenson, Susan K.; Trautwein, C.M.

1984-01-01

The application of an unsupervised, spatially dependent clustering technique (AMOEBA) to interpolated raster arrays of stream sediment data has been found to provide useful multivariate geochemical associations for modeling regional polymetallic resource potential. The technique is based on three assumptions regarding the compositional and spatial relationships of stream sediment data and their regional significance. These assumptions are: (1) compositionally separable classes exist and can be statistically distinguished; (2) the classification of multivariate data should minimize the pair probability of misclustering to establish useful compositional associations; and (3) a compositionally defined class represented by three or more contiguous cells within an array is a more important descriptor of a terrane than a class represented by spatial outliers.

Global Maize Trade and Food Security: Implications from a Social Network Model

PubMed Central

Wu, Felicia; Guclu, Hasan

2013-01-01

In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability were decreased due to factors such as diversion to non-food uses, climatic factors, or plant diseases. Using data on imports and exports from the United Nations Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, while Japan and the Republic of Korea are the largest maize importers. In particular, the star-shaped cluster of the network that represents US maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which US maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide. PMID:23656551

Global maize trade and food security: implications from a social network model.

PubMed

Wu, Felicia; Guclu, Hasan

2013-12-01

In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.N. Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, whereas Japan and the Republic of Korea are the largest maize importers. In particular, the star-shaped cluster of the network that represents U.S. maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which U.S. maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide. © 2013 Society for Risk Analysis.

Bug Distribution and Pattern Classification.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…

Topological side-chain classification of beta-turns: ideal motifs for peptidomimetic development.

PubMed

Tran, Tran Trung; McKie, Jim; Meutermans, Wim D F; Bourne, Gregory T; Andrews, Peter R; Smythe, Mark L

2005-08-01

Beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. Beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi2, psi2, phi3 and psi3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C(alpha)-C(beta) vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C(alpha)-C(beta) vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Early Environment and Neurobehavioral Development Predict Adult Temperament Clusters

PubMed Central

Congdon, Eliza; Service, Susan; Wessman, Jaana; Seppänen, Jouni K.; Schönauer, Stefan; Miettunen, Jouko; Turunen, Hannu; Koiranen, Markku; Joukamaa, Matti; Järvelin, Marjo-Riitta; Veijola, Juha; Mannila, Heikki; Paunio, Tiina; Freimer, Nelson B.

2012-01-01

Background Investigation of the environmental influences on human behavioral phenotypes is important for our understanding of the causation of psychiatric disorders. However, there are complexities associated with the assessment of environmental influences on behavior. Methods/Principal Findings We conducted a series of analyses using a prospective, longitudinal study of a nationally representative birth cohort from Finland (the Northern Finland 1966 Birth Cohort). Participants included a total of 3,761 male and female cohort members who were living in Finland at the age of 16 years and who had complete temperament scores. Our initial analyses (Wessman et al., in press) provide evidence in support of four stable and robust temperament clusters. Using these temperament clusters, as well as independent temperament dimensions for comparison, we conducted a data-driven analysis to assess the influence of a broad set of life course measures, assessed pre-natally, in infancy, and during adolescence, on adult temperament. Results Measures of early environment, neurobehavioral development, and adolescent behavior significantly predict adult temperament, classified by both cluster membership and temperament dimensions. Specifically, our results suggest that a relatively consistent set of life course measures are associated with adult temperament profiles, including maternal education, characteristics of the family’s location and residence, adolescent academic performance, and adolescent smoking. Conclusions Our finding that a consistent set of life course measures predict temperament clusters indicate that these clusters represent distinct developmental temperament trajectories and that information about a subset of life course measures has implications for adult health outcomes. PMID:22815688

Comprehensive Genomic Analyses of the OM43 Clade, Including a Novel Species from the Red Sea, Indicate Ecotype Differentiation among Marine Methylotrophs

PubMed Central

Jimenez-Infante, Francy; Ngugi, David Kamanda; Vinu, Manikandan; Alam, Intikhab; Kamau, Allan Anthony; Blom, Jochen; Bajic, Vladimir B.

2015-01-01

The OM43 clade within the family Methylophilaceae of Betaproteobacteria represents a group of methylotrophs that play important roles in the metabolism of C1 compounds in marine environments and other aquatic environments around the globe. Using dilution-to-extinction cultivation techniques, we successfully isolated a novel species of this clade (here designated MBRS-H7) from the ultraoligotrophic open ocean waters of the central Red Sea. Phylogenomic analyses indicate that MBRS-H7 is a novel species that forms a distinct cluster together with isolate KB13 from Hawaii (Hawaii-Red Sea [H-RS] cluster) that is separate from the cluster represented by strain HTCC2181 (from the Oregon coast). Phylogenetic analyses using the robust 16S-23S internal transcribed spacer revealed a potential ecotype separation of the marine OM43 clade members, which was further confirmed by metagenomic fragment recruitment analyses that showed trends of higher abundance in low-chlorophyll and/or high-temperature provinces for the H-RS cluster but a preference for colder, highly productive waters for the HTCC2181 cluster. This potential environmentally driven niche differentiation is also reflected in the metabolic gene inventories, which in the case of the H-RS cluster include those conferring resistance to high levels of UV irradiation, temperature, and salinity. Interestingly, we also found different energy conservation modules between these OM43 subclades, namely, the existence of the NADH:quinone oxidoreductase complex I (NUO) system in the H-RS cluster and the nonhomologous NADH:quinone oxidoreductase (NQR) system in the HTCC2181 cluster, which might have implications for their overall energetic yields. PMID:26655752

AFLP-based genetic diversity assessment of commercially important tea germplasm in India.

PubMed

Sharma, R K; Negi, M S; Sharma, S; Bhardwaj, P; Kumar, R; Bhattachrya, E; Tripathi, S B; Vijayan, D; Baruah, A R; Das, S C; Bera, B; Rajkumar, R; Thomas, J; Sud, R K; Muraleedharan, N; Hazarika, M; Lakshmikumaran, M; Raina, S N; Ahuja, P S

2010-08-01

India has a large repository of important tea accessions and, therefore, plays a major role in improving production and quality of tea across the world. Using seven AFLP primer combinations, we analyzed 123 commercially important tea accessions representing major populations in India. The overall genetic similarity recorded was 51%. No significant differences were recorded in average genetic similarity among tea populations cultivated in various geographic regions (northwest 0.60, northeast and south both 0.59). UPGMA cluster analysis grouped the tea accessions according to geographic locations, with a bias toward China or Assam/Cambod types. Cluster analysis results were congruent with principal component analysis. Further, analysis of molecular variance detected a high level of genetic variation (85%) within and limited genetic variation (15%) among the populations, suggesting their origin from a similar genetic pool.

Beyond rankings: using cognitive mapping to understand what health care journals represent.

PubMed

Shewchuk, Richard M; O'connor, Stephen J; Williams, Eric S; Savage, Grant T

2006-03-01

Studies of journal ratings are often controversial. Indices, including impact factors, acceptance rates, expert opinions, and ratings of knowledge, relevance, and quality have been used to organize journals hierarchically. While there may be some validity in consensus rankings, it is unclear what purpose is actually achieved by these endeavors. Impact factors probably help researchers identify authoritative journals, but other rankings likely indicate little more than institutionalized perceptions of prestige. Ranking schema used to derive evaluative judgments do not provide information about the organization of journals from the perspective of substantive content, emphasis, or targeted audience. A cognitive mapping approach that examines how health care management faculty members represent their perceptions of North American health care-oriented journals is presented as an alternative. A card-sort task and importance rating scale was mailed to faculty of North American health management programs who participated in a previous journal ranking study conducted by the authors. Completed assessments were returned from 147 respondents for a response rate of 39%. Multidimensional scaling and hierarchical cluster analyses of data provided a three-dimensional, seven cluster map that illustrates the perceived similarities of journals. Dimension I contrasts Applied Management Practice with Health Policy journals. Dimension II contrasts specific domain with broad-based research journals. Dimension III contrasts finance-oriented with delivery-oriented journals. The seven clusters of perceptually similar journals were weighted in terms of respondent defined importance ascribed to each journal within a cluster. This framework supplements ratings by providing insight about how journals are cognitively organized by scholars.

A Polyphasic and Taxogenomic Evaluation Uncovers Arcobacter cryaerophilus as a Species Complex That Embraces Four Genomovars

PubMed Central

Pérez-Cataluña, Alba; Collado, Luis; Salgado, Oscar; Lefiñanco, Violeta; Figueras, María J.

2018-01-01

The species Arcobacter cryaerophilus is found in many food products of animal origin and is the dominating species in wastewater. In addition, it is associated with cases of farm animal and human infectious diseases,. The species embraces two subgroups i.e., 1A (LMG 24291T = LMG 9904T) and 1B (LMG 10829) that can be differentiated by their 16S rRNA-RFLP pattern. However, some authors, on the basis of the shared intermediate levels of DNA-DNA hybridization, have suggested abandoning the subgroup classification. This contradiction indicates that the taxonomy of this species is not yet resolved. The objective of the present study was to perform a taxonomic evaluation of the diversity of A. cryaerophilus. Genomic information was used along with a Multilocus Phylogenetic Analysis (MLPA) and phenotypic characterization on a group of 52 temporally and geographically dispersed strains, coming from different types of samples and hosts from nine countries. The MLPA analysis showed that those strains formed four clusters (I–IV). Values of Average Nucleotide Identity (ANI) and in silico DNA-DNA Hybridization (isDDH) obtained between 13 genomes representing strains of the four clusters were below the proposed cut-offs of 96 and 70%, respectively, confirming that each of the clusters represented a different genomic species. However, none of the evaluated phenotypic tests enabled their unequivocal differentiation into species. Therefore, the genomic delimited clusters should be considered genomovars of the species A. cryaerophilus. These genomovars could have different clinical importance, since only the cluster I included strains isolated from human specimens. The discovery of at least one stable distinctive phenotypic character would be needed to define each cluster or genomovar as a different species. Until then, we propose naming them “A. cryaerophilus gv. pseudocryaerophilus” (Cluster I = LMG 10229T), “A. cryaerophilus gv. crypticus” (Cluster II = LMG 9065T), “A. cryaerophilus gv. cryaerophilus” (Cluster III = LMG 24291T) and “A. cryaerophilus gv. occultus” (Cluster IV = LMG 29976T).

Thematic clustering of text documents using an EM-based approach

PubMed Central

2012-01-01

Clustering textual contents is an important step in mining useful information on the web or other text-based resources. The common task in text clustering is to handle text in a multi-dimensional space, and to partition documents into groups, where each group contains documents that are similar to each other. However, this strategy lacks a comprehensive view for humans in general since it cannot explain the main subject of each cluster. Utilizing semantic information can solve this problem, but it needs a well-defined ontology or pre-labeled gold standard set. In this paper, we present a thematic clustering algorithm for text documents. Given text, subject terms are extracted and used for clustering documents in a probabilistic framework. An EM approach is used to ensure documents are assigned to correct subjects, hence it converges to a locally optimal solution. The proposed method is distinctive because its results are sufficiently explanatory for human understanding as well as efficient for clustering performance. The experimental results show that the proposed method provides a competitive performance compared to other state-of-the-art approaches. We also show that the extracted themes from the MEDLINE® dataset represent the subjects of clusters reasonably well. PMID:23046528

A new hierarchical method to find community structure in networks

NASA Astrophysics Data System (ADS)

Saoud, Bilal; Moussaoui, Abdelouahab

2018-04-01

Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martinez-Medina, L. A.; Pichardo, B.; Moreno, E.

We present a dynamical study of the effect of the bar and spiral arms on the simulated orbits of open clusters in the Galaxy. Specifically, this work is devoted to the puzzling presence of high-altitude open clusters in the Galaxy. For this purpose we employ a very detailed observationally motivated potential model for the Milky Way and a careful set of initial conditions representing the newly born open clusters in the thin disk. We find that the spiral arms are able to raise an important percentage of open clusters (about one-sixth of the total employed in our simulations, depending onmore » the structural parameters of the arms) above the Galactic plane to heights beyond 200 pc, producing a bulge-shaped structure toward the center of the Galaxy. Contrary to what was expected, the spiral arms produce a much greater vertical effect on the clusters than the bar, both in quantity and height; this is due to the sharper concentration of the mass on the spiral arms, when compared to the bar. When a bar and spiral arms are included, spiral arms are still capable of raising an important percentage of the simulated open clusters through chaotic diffusion (as tested from classification analysis of the resultant high-z orbits), but the bar seems to restrain them, diminishing the elevation above the plane by a factor of about two.« less

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

PubMed

He, Yan; Caporaso, J Gregory; Jiang, Xiao-Tao; Sheng, Hua-Fang; Huse, Susan M; Rideout, Jai Ram; Edgar, Robert C; Kopylova, Evguenia; Walters, William A; Knight, Rob; Zhou, Hong-Wei

2015-01-01

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

GEMINI/GMOS SPECTROSCOPY OF 26 STRONG-LENSING-SELECTED GALAXY CLUSTER CORES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bayliss, Matthew B.; Gladders, Michael D.; Koester, Benjamin P.

2011-03-15

We present results from a spectroscopic program targeting 26 strong-lensing cluster cores that were visually identified in the Sloan Digital Sky Survey (SDSS) and the Second Red-Sequence Cluster Survey (RCS-2). The 26 galaxy cluster lenses span a redshift range of 0.2 < z < 0.65, and our spectroscopy reveals 69 unique background sources with redshifts as high as z = 5.200. We also identify redshifts for 262 cluster member galaxies and measure the velocity dispersions and dynamical masses for 18 clusters where we have redshifts for N {>=} 10 cluster member galaxies. We account for the expected biases in dynamicalmore » masses of strong-lensing-selected clusters as predicted by results from numerical simulations and discuss possible sources of bias in our observations. The median dynamical mass of the 18 clusters with N {>=} 10 spectroscopic cluster members is M {sub Vir} = 7.84 x 10{sup 14} M {sub sun} h {sup -1} {sub 0.7}, which is somewhat higher than predictions for strong-lensing-selected clusters in simulations. The disagreement is not significant considering the large uncertainty in our dynamical data, systematic uncertainties in the velocity dispersion calibration, and limitations of the theoretical modeling. Nevertheless our study represents an important first step toward characterizing large samples of clusters that are identified in a systematic way as systems exhibiting dramatic strong-lensing features.« less

Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

PubMed

Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin

2017-07-31

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.

Fundamental movement skills and motivational factors influencing engagement in physical activity.

PubMed

Kalaja, Sami; Jaakkola, Timo; Liukkonen, Jarmo; Watt, Anthony

2010-08-01

To assess whether subgroups based on children's fundamental movement skills, perceived competence, and self-determined motivation toward physical education vary with current self-reported physical activity, a sample of 316 Finnish Grade 7 students completed fundamental movement skills measures and self-report questionnaires assessing perceived competence, self-determined motivation toward physical education, and current physical activity. Cluster analysis indicated a three-cluster structure: "Low motivation/low skills profile," "High skills/low motivation profile," and "High skills/high motivation profile." Analysis of variance indicated that students in the third cluster engaged in significantly more physical activity than students of clusters one and two. These results provide support for previous claims regarding the importance of the relationship of fundamental movement skills with continuing engagement in physical activity. High fundamental movement skills, however, may represent only one element in maintaining adolescents' engagement in physical activity.

Conceptual clusters in figurative language production.

PubMed

Corts, Daniel P; Meyers, Kristina

2002-07-01

Although most prior research on figurative language examines comprehension, several recent studies on the production of such language have proved to be informative. One of the most noticeable traits of figurative language production is that it is produced at a somewhat random rate with occasional bursts of highly figurative speech (e.g., Corts & Pollio, 1999). The present article seeks to extend these findings by observing production during speech that involves a very high base rate of figurative language, making statistically defined bursts difficult to detect. In an analysis of three Baptist sermons, burst-like clusters of figurative language were identified. Further study indicated that these clusters largely involve a central root metaphor that represents the topic under consideration. An interaction of the coherence, along with a conceptual understanding of a topic and the relative importance of the topic to the purpose of the speech, is offered as the most likely explanation for the clustering of figurative language in natural speech.

VAX CLuster upgrade: Report of a CPC task force

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, J.; Berry, H.; Kessler, P.

The CSCF VAX cluster provides interactive computing for 100 users during prime time, plus a considerable amount of daytime and overnight batch processing. While this cluster represents less than 10% of the VAX computing power at BNL (6 MIPS out of 70), it has served as an important center for this larger network, supporting special hardware and software too expensive to maintain on every machine. In addition, it is the only unrestricted facility available to VAX/VMS users (other machines are typically dedicated to special projects). This committee's analysis shows that the cpu's on the CSCF cluster are currently badly oversaturated,more » frequently giving extremely poor interactive response. Short batch jobs (a necessary part of interactive work) typically take 3 to 4 times as long to execute as they would on an idle machine. There is also an immediate need for more scratch disk space and user permanent file space.« less

Ontology-based topic clustering for online discussion data

NASA Astrophysics Data System (ADS)

Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

2013-03-01

With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

Structure and formation of highly luminescent protein-stabilized gold clusters† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc05086k

PubMed Central

Chevrier, D. M.; Thanthirige, V. D.; Luo, Z.; Driscoll, S.; Cho, P.; MacDonald, M. A.; Yao, Q.; Guda, R.; Xie, J.; Johnson, E. R.; Chatt, A.; Zheng, N.

2018-01-01

Highly luminescent gold clusters simultaneously synthesized and stabilized by protein molecules represent a remarkable category of nanoscale materials with promising applications in bionanotechnology as sensors. Nevertheless, the atomic structure and luminescence mechanism of these gold clusters are still unknown after several years of developments. Herein, we report findings on the structure, luminescence and biomolecular self-assembly of gold clusters stabilized by the large globular protein, bovine serum albumin. We highlight the surprising identification of interlocked gold-thiolate rings as the main gold structural unit. Importantly, such gold clusters are in a rigidified state within the protein scaffold, offering an explanation for their highly luminescent character. Combined free-standing cluster synthesis (without protecting protein scaffold) with rigidifying and un-rigidifying experiments, were designed to further verify the luminescence mechanism and gold atomic structure within the protein. Finally, the biomolecular self-assembly process of the protein-stabilized gold clusters was elucidated by time-dependent X-ray absorption spectroscopy measurements and density functional theory calculations. PMID:29732064

Feature extraction using molecular planes for fuzzy relational clustering of a flexible dopamine reuptake inhibitor.

PubMed

Banerjee, Amit; Misra, Milind; Pai, Deepa; Shih, Liang-Yu; Woodley, Rohan; Lu, Xiang-Jun; Srinivasan, A R; Olson, Wilma K; Davé, Rajesh N; Venanzi, Carol A

2007-01-01

Six rigid-body parameters (Shift, Slide, Rise, Tilt, Roll, Twist) are commonly used to describe the relative displacement and orientation of successive base pairs in a nucleic acid structure. The present work adapts this approach to describe the relative displacement and orientation of any two planes in an arbitrary molecule-specifically, planes which contain important pharmacophore elements. Relevant code from the 3DNA software package (Nucleic Acids Res. 2003, 31, 5108-5121) was generalized to treat molecular fragments other than DNA bases as input for the calculation of the corresponding rigid-body (or "planes") parameters. These parameters were used to construct feature vectors for a fuzzy relational clustering study of over 700 conformations of a flexible analogue of the dopamine reuptake inhibitor, GBR 12909. Several cluster validity measures were used to determine the optimal number of clusters. Translational (Shift, Slide, Rise) rather than rotational (Tilt, Roll, Twist) features dominate clustering based on planes that are relatively far apart, whereas both types of features are important to clustering when the pair of planes are close by. This approach was able to classify the data set of molecular conformations into groups and to identify representative conformers for use as template conformers in future Comparative Molecular Field Analysis studies of GBR 12909 analogues. The advantage of using the planes parameters, rather than the combination of atomic coordinates and angles between molecular planes used in our previous fuzzy relational clustering of the same data set (J. Chem. Inf. Model. 2005, 45, 610-623), is that the present clustering results are independent of molecular superposition and the technique is able to identify clusters in the molecule considered as a whole. This approach is easily generalizable to any two planes in any molecule.

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.

Childhood adversity and personality disorders: results from a nationally representative population-based study.

PubMed

Afifi, Tracie O; Mather, Amber; Boman, Jonathon; Fleisher, William; Enns, Murray W; Macmillan, Harriet; Sareen, Jitender

2011-06-01

Although, a large population-based literature exists on the relationship between childhood adversity and Axis I mental disorders, research on the link between childhood adversity and Axis II personality disorders (PDs) relies mainly on clinical samples. The purpose of the current study was to examine the relationship between a range of childhood adversities and PDs in a nationally representative sample while adjusting for Axis I mental disorders. Data were from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; n=34,653; data collection 2004-2005); a nationally representative sample of the United States population aged 20 years and older. The results indicated that many types of childhood adversity were highly prevalent among individuals with PDs in the general population and childhood adversity was most consistently associated with schizotypal, antisocial, borderline, and narcissistic PDs. The most robust childhood adversity findings were for child abuse and neglect with cluster A and cluster B PDs after adjusting for all other types of childhood adversity, mood disorders, anxiety disorders, substance use disorders, other PD clusters, and sociodemographic variables (Odd Ratios ranging from 1.22 to 1.63). In these models, mood disorders, anxiety disorders, and substance use disorders also remained significantly associated with PD clusters (Odds Ratios ranging from 1.26 to 2.38). Further research is necessary to understand whether such exposure has a causal role in the association with PDs. In addition to preventing child maltreatment, it is important to determine ways to prevent impairment among those exposed to adversity, as this may reduce the development of PDs. Copyright © 2010 Elsevier Ltd. All rights reserved.

Diffusion Of Mass In Evaporating Multicomponent Drops

NASA Technical Reports Server (NTRS)

Bellan, Josette; Harstad, Kenneth G.

1992-01-01

Report summarizes study of diffusion of mass and related phenomena occurring in evaporation of dense and dilute clusters of drops of multicomponent liquids intended to represent fuels as oil, kerosene, and gasoline. Cluster represented by simplified mathematical model, including global conservation equations for entire cluster and conditions on boundary between cluster and ambient gas. Differential equations of model integrated numerically. One of series of reports by same authors discussing evaporation and combustion of sprayed liquid fuels.

Hierarchical structure and importance of patients' reasons for treatment choices in knee and hip osteoarthritis: a concept mapping study.

PubMed

Selten, Ellen M H; Geenen, Rinie; van der Laan, Willemijn H; van der Meulen-Dilling, Roelien G; Schers, Henk J; Nijhof, Marc W; van den Ende, Cornelia H M; Vriezekolk, Johanna E

2017-02-01

To improve patients' use of conservative treatment options of hip and knee OA, in-depth understanding of reasons underlying patients' treatment choices is required. The current study adopted a concept mapping method to thematically structure and prioritize reasons for treatment choice in knee and hip OA from a patients' perspective. Multiple reasons for treatment choices were previously identified using in-depth interviews. In consensus meetings, experts derived 51 representative reasons from the interviews. Thirty-six patients individually sorted the 51 reasons in two card-sorting tasks: one based on content similarity, and one based on importance of reasons. The individual sortings of the first card-sorting task provided input for a hierarchical cluster analysis (squared Euclidian distances, Ward's method). The importance of the reasons and clusters were examined using descriptive statistics. The hierarchical structure of reasons for treatment choices showed a core distinction between two categories of clusters: barriers [subdivided into context (e.g. the healthcare system) and disadvantages] and outcome (subdivided into treatment and personal life). At the lowest level, 15 clusters were identified of which the clusters Physical functioning, Risks and Prosthesis were considered most important when making a treatment decision for hip or knee OA. Patients' treatment choices in knee and hip OA are guided by contextual barriers, disadvantages of the treatment, outcomes of the treatment and consequences for personal life. The structured overview of reasons can be used to support shared decision-making. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A framework for graph-based synthesis, analysis, and visualization of HPC cluster job data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayo, Jackson R.; Kegelmeyer, W. Philip, Jr.; Wong, Matthew H.

The monitoring and system analysis of high performance computing (HPC) clusters is of increasing importance to the HPC community. Analysis of HPC job data can be used to characterize system usage and diagnose and examine failure modes and their effects. This analysis is not straightforward, however, due to the complex relationships that exist between jobs. These relationships are based on a number of factors, including shared compute nodes between jobs, proximity of jobs in time, etc. Graph-based techniques represent an approach that is particularly well suited to this problem, and provide an effective technique for discovering important relationships in jobmore » queuing and execution data. The efficacy of these techniques is rooted in the use of a semantic graph as a knowledge representation tool. In a semantic graph job data, represented in a combination of numerical and textual forms, can be flexibly processed into edges, with corresponding weights, expressing relationships between jobs, nodes, users, and other relevant entities. This graph-based representation permits formal manipulation by a number of analysis algorithms. This report presents a methodology and software implementation that leverages semantic graph-based techniques for the system-level monitoring and analysis of HPC clusters based on job queuing and execution data. Ontology development and graph synthesis is discussed with respect to the domain of HPC job data. The framework developed automates the synthesis of graphs from a database of job information. It also provides a front end, enabling visualization of the synthesized graphs. Additionally, an analysis engine is incorporated that provides performance analysis, graph-based clustering, and failure prediction capabilities for HPC systems.« less

a Snapshot Survey of X-Ray Selected Central Cluster Galaxies

NASA Astrophysics Data System (ADS)

Edge, Alastair

1999-07-01

Central cluster galaxies are the most massive stellar systems known and have been used as standard candles for many decades. Only recently have central cluster galaxies been recognised to exhibit a wide variety of small scale {<100 pc} features that can only be reliably detected with HST resolution. The most intriguing of these are dust lanes which have been detected in many central cluster galaxies. Dust is not expected to survive long in the hostile cluster environment unless shielded by the ISM of a disk galaxy or very dense clouds of cold gas. WFPC2 snapshot images of a representative subset of the central cluster galaxies from an X-ray selected cluster sample would provide important constraints on the formation and evolution of dust in cluster cores that cannot be obtained from ground-based observations. In addition, these images will allow the AGN component, the frequency of multiple nuclei, and the amount of massive-star formation in central cluster galaxies to be ass es sed. The proposed HST observatio ns would also provide high-resolution images of previously unresolved gravitational arcs in the most massive clusters in our sample resulting in constraints on the shape of the gravitational potential of these systems. This project will complement our extensive multi-frequency work on this sample that includes optical spectroscopy and photometry, VLA and X-ray images for the majority of the 210 targets.

Effects of cluster-shell competition and BCS-like pairing in 12C

NASA Astrophysics Data System (ADS)

Matsuno, H.; Itagaki, N.

2017-12-01

The antisymmetrized quasi-cluster model (AQCM) was proposed to describe α-cluster and jj-coupling shell models on the same footing. In this model, the cluster-shell transition is characterized by two parameters, R representing the distance between α clusters and Λ describing the breaking of α clusters, and the contribution of the spin-orbit interaction, very important in the jj-coupling shell model, can be taken into account starting with the α-cluster model wave function. Not only the closure configurations of the major shells but also the subclosure configurations of the jj-coupling shell model can be described starting with the α-cluster model wave functions; however, the particle-hole excitations of single particles have not been fully established yet. In this study we show that the framework of AQCM can be extended even to the states with the character of single-particle excitations. For ^{12}C, two-particle-two-hole (2p2h) excitations from the subclosure configuration of 0p_{3/2} corresponding to a BCS-like pairing are described, and these shell model states are coupled with the three α-cluster model wave functions. The correlation energy from the optimal configuration can be estimated not only in the cluster part but also in the shell model part. We try to pave the way to establish a generalized description of the nuclear structure.

Detecting the influence of ornamental Berberis thunbergii var. atropurpurea in invasive populations of Berberis thunbergii (Berberidaceae) using AFLP1.

PubMed

Lubell, Jessica D; Brand, Mark H; Lehrer, Jonathan M; Holsinger, Kent E

2008-06-01

Japanese barberry (Berberis thunbergii DC.) is a widespread invasive plant that remains an important landscape shrub represented by ornamental, purple-leaved forms of the botanical variety atropurpurea. These forms differ greatly in appearance from feral plants, bringing into question whether they contribute to invasive populations or whether the invasions represent self-sustaining populations derived from the initial introduction of the species in the late 19th century. In this study we used amplified fragment length polymorphism (AFLP) markers to determine whether genetic contributions from B. t. var. atropurpurea are found within naturalized Japanese barberry populations in southern New England. Bayesian clustering of AFLP genotypes and principal coordinate analysis distinguished B. t. var. atropurpurea genotypes from 85 plants representing five invasive populations. While a single feral plant resembled B. t. var. atropurpurea phenotypically and fell within the same genetic cluster, all other naturalized plants sampled were genetically distinct from the purple-leaved genotypes. Seven plants from two different sites possessed morphology consistent with Berberis vulgaris (common barberry) or B. ×ottawensis (B. thunbergii × B. vulgaris). Genetic analysis placed these plants in two clusters separate from B. thunbergii. Although the Bayesian analysis indicated some introgression of B. t. var. atropurpurea and B. vulgaris, these genotypes have had limited influence on extant feral populations of B. thunbergii.

The Productivity and Technical Efficiency of Textile Industry Clusters in India

NASA Astrophysics Data System (ADS)

Bhaskaran, E.

2013-09-01

The Indian textile industry is one the largest and oldest sectors in the country and among the most important in the economy in terms of output, investment and employment (E). The sector employs nearly 35 million people and after agriculture, is the second-highest employer in the country. Its importance is underlined by the fact that it accounts for around 4 % of Gross Domestic Product, 14 % of industrial production, 9 % of excise collections, 18 % of E in the industrial sector, and 16 % of the country's total exports (Ex) earnings. For inclusive growth and sustainable development most of the Textile Manufacturers has adopted the Cluster Development Approach. The objective is to study the physical and financial performance, correlation, regression and Data Envelopment Analysis by measuring technical efficiency (Ø), peer weights (λi), input slacks (S-), output slacks (S+) and return to scale of four textile clusters (TCs) namely IchalKaranji Textile Cluster, Maharashtra; Ludhiana Textile Cluster, Punjab; Tirupur Textile Cluster, Tamilnadu and Panipat Textile Cluster, Haryana in India. The methodology adopted is using Data Envelopment Analysis of Output Oriented Banker Charnes Cooper Model by taking number of units (U) and number of E as inputs and sales (S) and Ex in crores as an outputs. The non-zero λi's represents the weights for efficient clusters. The S > 0 obtained for one TC reveals the excess U (S-) and E (S-) and shortage in sales (S+) and Ex (S+). To conclude, for inclusive growth and sustainable development, the inefficient TC should increase their S/turnover and Ex, as decrease in number of enterprises and E is practically not possible. Moreover for sustainable development, the TC should strengthen infrastructure interrelationships, technology interrelationships, procurement interrelationships, production interrelationships and marketing interrelationships to decrease cost, increase productivity and efficiency to compete in the world market.

Population structure, genetic diversity and downy mildew resistance among Ocimum species germplasm.

PubMed

Pyne, Robert M; Honig, Josh A; Vaiciunas, Jennifer; Wyenandt, Christian A; Simon, James E

2018-04-23

The basil (Ocimum spp.) genus maintains a rich diversity of phenotypes and aromatic volatiles through natural and artificial outcrossing. Characterization of population structure and genetic diversity among a representative sample of this genus is severely lacking. Absence of such information has slowed breeding efforts and the development of sweet basil (Ocimum basilicum L.) with resistance to the worldwide downy mildew epidemic, caused by the obligate oomycete Peronospora belbahrii. In an effort to improve classification of relationships 20 EST-SSR markers with species-level transferability were developed and used to resolve relationships among a diverse panel of 180 Ocimum spp. accessions with varying response to downy mildew. Results obtained from nested Bayesian model-based clustering, analysis of molecular variance and unweighted pair group method using arithmetic average (UPGMA) analyses were synergized to provide an updated phylogeny of the Ocimum genus. Three (major) and seven (sub) population (cluster) models were identified and well-supported (P < 0.001) by PhiPT (Φ PT ) values of 0.433 and 0.344, respectively. Allelic frequency among clusters supported previously developed hypotheses of allopolyploid genome structure. Evidence of cryptic population structure was demonstrated for the k1 O. basilicum cluster suggesting prevalence of gene flow. UPGMA analysis provided best resolution for the 36-accession, DM resistant k3 cluster with consistently strong bootstrap support. Although the k3 cluster is a rich source of DM resistance introgression of resistance into the commercially important k1 accessions is impeded by reproductive barriers as demonstrated by multiple sterile F1 hybrids. The k2 cluster located between k1 and k3, represents a source of transferrable tolerance evidenced by fertile backcross progeny. The 90-accession k1 cluster was largely susceptible to downy mildew with accession 'MRI' representing the only source of DM resistance. High levels of genetic diversity support the observed phenotypic diversity among Ocimum spp. accessions. EST-SSRs provided a robust evaluation of molecular diversity and can be used for additional studies to increase resolution of genetic relationships in the Ocimum genus. Elucidation of population structure and genetic relationships among Ocimum spp. germplasm provide the foundation for improved DM resistance breeding strategies and more rapid response to future disease outbreaks.

The nature of the metal-CO interaction and bonding

NASA Technical Reports Server (NTRS)

Bagus, P. S.; Nelin, C. J.; Bauschlicher, C. W., Jr.

1984-01-01

The adsorption of CO on metal surfaces is represented by molecular orbital cluster models of CO at an on top site and adsorbed normal to the surface carbon end down. Ab initio SCF and MCSCF calculations are performed for several clusters. The new constrained space orbital variation CSOV approach is used to analyze the bonding and to compare CO adsorption on Al, representative of sp metals, with that on Cu, representative of transition metals. There is a large repulsion between the superposed free CO and metal charge distributions which is considerably smaller for Cu than for Al because there are fewer valence sigma electrons for Cu than for Al. The CSOV analysis shows that the metal to CO pi donation is much more important than the CO to metal sigma donation. It is also shown that for Cu, the d pi contribution to the metal pi donation is larger than the valence 4p pi contribution. The d pi donation is compared between Fe, Ni, and Cu and this donation and the metal-CO interaction are found to be different in the order Fe greater than Ni greater than Cu.

Determining requirements for patient-centred care: a participatory concept mapping study.

PubMed

Ogden, Kathryn; Barr, Jennifer; Greenfield, David

2017-11-28

Recognition of a need for patient-centred care is not new, however making patient-centred care a reality remains a challenge to organisations. We need empirical studies to extend current understandings, create new representations of the complexity of patient-centred care, and guide collective action toward patient-centred health care. To achieve these ends, the research aim was to empirically determine what organisational actions are required for patient-centred care to be achieved. We used an established participatory concept mapping methodology. Cross-sector stakeholders contributed to the development of statements for patient-centred care requirements, sorting statements into groupings according to similarity, and rating each statement according to importance, feasibility, and achievement. The resultant data were analysed to produce a visual concept map representing participants' conceptualisation of patient-centred care requirements. Analysis included the development of a similarity matrix, multidimensional scaling, hierarchical cluster analysis, selection of the number of clusters and their labels, identifying overarching domains and quantitative representation of rating data. The outcome was the development of a conceptual map for the Requirements of Patient-Centred Care Systems (ROPCCS). ROPCCS incorporates 123 statements sorted into 13 clusters. Cluster labels were: shared responsibility for personalised health literacy; patient provider dynamic for care partnership; collaboration; shared power and responsibility; resources for coordination of care; recognition of humanity - skills and attributes; knowing and valuing the patient; relationship building; system review evaluation and new models; commitment to supportive structures and processes; elements to facilitate change; professional identity and capability development; and explicit education and learning. The clusters were grouped into three overarching domains, representing a cross-sectoral approach: humanity and partnership; career spanning education and training; and health systems, policy and management. Rating of statements allowed the generation of go-zone maps for further interrogation of the relative importance, feasibility, and achievement of each patient-centred care requirement and cluster. The study has empirically determined requirements for patient-centred care through the development of ROPCCS. The unique map emphasises collaborative responsibility of stakeholders to ensure that patient-centred care is comprehensively progressed. ROPCCS allows the complex requirements for patient-centred care to be understood, implemented, evaluated, measured, and shown to be occurring.

Genetic diversity of stilbene metabolism in Vitis sylvestris

PubMed Central

Duan, Dong; Halter, David; Baltenweck, Raymonde; Tisch, Christine; Tröster, Viktoria; Kortekamp, Andreas; Hugueney, Philippe; Nick, Peter

2015-01-01

Stilbenes, as important secondary metabolites of grapevine, represent central phytoalexins and therefore constitute an important element of basal immunity. In this study, potential genetic variation in Vitis vinifera ssp. sylvestris, the ancestor of cultivated grapevine, was sought with respect to their output of stilbenes and potential use for resistance breeding. Considerable variation in stilbene inducibility was identified in V. vinifera ssp. sylvestris. Genotypic differences in abundance and profiles of stilbenes that are induced in response to a UV-C pulse are shown. Two clusters of stilbene ‘chemovars’ emerged: one cluster showed quick and strong accumulation of stilbenes, almost exclusively in the form of non-glycosylated resveratrol and viniferin, while the second cluster accumulated fewer stilbenes and relatively high proportions of piceatannol and the glycosylated piceid. For all 86 genotypes, a time dependence of the stilbene pattern was observed: piceid, resveratrol, and piceatannol accumulated earlier, whereas the viniferins were found later. It was further observed that the genotypic differences in stilbene accumulation were preceded by differential accumulation of the transcripts for chalcone synthase (CHS) and stilbene-related genes: phenylalanine ammonium lyase (PAL), stilbene synthase (StSy), and resveratrol synthase (RS). A screen of the population with respect to susceptibility to downy mildew of grapevine (Plasmopara viticola) revealed considerable variability. The subpopulation of genotypes with high stilbene inducibility was significantly less susceptible as compared with low-stilbene genotypes, and for representative genotypes it could be shown that the inducibility of stilbene synthase by UV correlated with the inducibility by the pathogen. PMID:25873669

Real-time in situ nanoclustering during initial stages of artificial aging of Al-Cu alloys

NASA Astrophysics Data System (ADS)

Zatsepin, Nadia A.; Dilanian, Ruben A.; Nikulin, Andrei Y.; Gao, Xiang; Muddle, Barry C.; Matveev, Victor N.; Sakata, Osami

2010-01-01

We report an experimental demonstration of real-time in situ x-ray diffraction investigations of clustering and dynamic strain in early stages of nanoparticle growth in Al-Cu alloys. Simulations involving a simplified model of local strain are well correlated with the x-ray diffraction data, suggesting a redistribution of point defects and the formation of nanoscale clusters in the bulk material. A modal, representative nanoparticle size is determined subsequent to the final stage of artificial aging. Such investigations are imperative for the understanding, and ultimately the control, of nanoparticle nucleation and growth in this technologically important alloy.

Titanium Insertion into CO Bonds in Anionic Ti-CO2 Complexes.

PubMed

Dodson, Leah G; Thompson, Michael C; Weber, J Mathias

2018-03-22

We explore the structures of [Ti(CO 2 ) y ] - cluster anions using infrared photodissociation spectroscopy and quantum chemistry calculations. The existence of spectral signatures of metal carbonyl CO stretching modes shows that insertion of titanium atoms into C-O bonds represents an important reaction during the formation of these clusters. In addition to carbonyl groups, the infrared spectra show that the titanium center is coordinated to oxalato, carbonato, and oxo ligands, which form along with the metal carbonyls. The presence of a metal oxalato ligand promotes C-O bond insertion in these systems. These results highlight the affinity of titanium for C-O bond insertion processes.

Super Star Clusters and H II Regions in Nuclear Rings

NASA Astrophysics Data System (ADS)

Filippenko, Alex

1996-07-01

We propose to obtain WFPC2 optical broad-band {F547M and F814W} and narrow-band Halpha+ionN2 {F658N} images of nuclear starburst rings in four nearby galaxies for which we already have ultraviolet {F220W} FOC data. Nuclear rings {or ``hot- spot'' regions} in barred spirals are some of the nearest and least obscured starburst regions, and HST images of nuclear rings in several galaxies show that the rings contain large populations of super star clusters similar to those recently discovered in other types of starburst systems. These compact clusters, many having luminosities exceeding that of the R136 cluster in 30 Doradus, represent a violent mode of star formation distinct from that seen in ordinary disk ionH2 regions, and the nuclear rings present us with an opportunity to study large numbers of these extreme clusters in relatively unobscured starburst environments. It has been suggested that super star clusters are present-day versions of young globular clusters. To evaluate this hypothesis, it is important to understand the physical properties and stellar contents of the clusters, but previous HST studies of nuclear ring galaxies have only used single-filter observations. Together with our UV data, new WFPC2 images will enable us to determine the H II region and cluster luminosity functions within nuclear rings, measure cluster radii, derive age and mass estimates for the clusters by comparison with evolutionary synthesis models, and study the structure and evolution of nuclear rings.

Longitudinal Study of Career Cluster Persistence from 8th Grade to 12th Grade with a Focus on the Science, Technology, Engineering, & Math Career Cluster

NASA Astrophysics Data System (ADS)

Wagner, Judson

Today's technology driven global economy has put pressure on the American education system to produce more students who are prepared for careers in Science, Technology, Engineering, and Math (STEM). Adding to this pressure is the demand for a more diverse workforce that can stimulate the development of new ideas and innovation. This in turn requires more female and under represented minority groups to pursue future careers in STEM. Though STEM careers include many of the highest paid professionals, school systems are dealing with exceptionally high numbers of students, especially female and under represented minorities, who begin but do not persist to STEM degree completion. Using the Expectancy-Value Theory (EVT) framework that attributes student motivation to a combination of intrinsic, utility, and attainment values, this study analyzed readily available survey data to gauge students' career related values. These values were indirectly investigated through a longitudinal approach, spanning five years, on the predictive nature of 8 th grade survey-derived recommendations for students to pursue a future in a particular career cluster. Using logistic regression analysis, it was determined that this 8 th grade data, particularly in STEM, provides significantly high probabilities of a 12th grader's average grade, SAT-Math score, the math and science elective courses they take, and most importantly, interest in the same career cluster.

Co-citation Network Analysis of Religious Texts

NASA Astrophysics Data System (ADS)

Murai, Hajime; Tokosumi, Akifumi

This paper introduces a method of representing in a network the thoughts of individual authors of dogmatic texts numerically and objectively by means of co-citation analysis and a method of distinguishing between the thoughts of various authors by clustering and analysis of clustered elements, generated by the clustering process. Using these methods, this paper creates and analyzes the co-citation networks for five authoritative Christian theologians through history (Augustine, Thomas Aquinas, Jean Calvin, Karl Barth, John Paul II). These analyses were able to extract the core element of Christian thought (Jn 1:14, Ph 2:6, Ph 2:7, Ph 2:8, Ga 4:4), as well as distinctions between the individual theologians in terms of their sect (Catholic or Protestant) and era (thinking about the importance of God's creation and the necessity of spreading the Gospel). By supplementing conventional literary methods in areas such as philosophy and theology, with these numerical and objective methods, it should be possible to compare the characteristics of various doctrines. The ability to numerically and objectively represent the characteristics of various thoughts opens up the possibilities of utilizing new information technology, such as web ontology and the Artificial Intelligence, in order to process information about ideological thoughts in the future.

Deprotonated Water Dimers: The Building Blocks of Segmented Water Chains on Rutile RuO2(110)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Rentao; Cantu Cantu, David; Glezakou, Vassiliki Alexandra

2015-10-15

Despite the importance of RuO2 in photocatalytic water splitting and catalysis in general, the interactions of water with even its most stable (110) surface are not well-understood. In this study we employ a combination of high-resolution scanning tunneling microscopy imaging with density functional theory based ab initio molecular dynamics, and we follow the formation and binding of linear water clusters on coordinatively unsaturated ruthenium rows. We find that clusters of all sizes (dimers, trimers, tetramers, extended chains) are stabilized by donating one proton per every two water molecules to the surface bridge bonded oxygen sites, in contrast with water monomersmore » that do not show a significant propensity for dissociation. The clusters with odd number of water molecules are less stable than the clusters with even number, and are generally not observed under thermal equilibrium. For all clusters with even numbers, the dissociated dimers represent the fundamental building blocks with strong intra-dimer hydrogen bonds and only very weak inter-dimer interactions resulting in segmented water chains.« less

Determining Performance Levels of Competencies for Job Entry Required of Beginning Farm Operators. Final Report.

ERIC Educational Resources Information Center

Avery, John H.

A sample of 145 people representing eighty farm operations and a statewide sample of 233 agricultural and agribusiness workers participated in a study to identify competencies, their importance (on a one to five rating scale), and the performance level required of a beginning farm operator in each of the following five cluster areas considered…

Structure based alignment and clustering of proteins (STRALCP)

DOEpatents

Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

2013-06-18

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

Local and regional components of aerosol in a heavily trafficked street canyon in central London derived from PMF and cluster analysis of single-particle ATOFMS spectra.

PubMed

Giorio, Chiara; Tapparo, Andrea; Dall'Osto, Manuel; Beddows, David C S; Esser-Gietl, Johanna K; Healy, Robert M; Harrison, Roy M

2015-03-17

Positive matrix factorization (PMF) has been applied to single particle ATOFMS spectra collected on a six lane heavily trafficked road in central London (Marylebone Road), which well represents an urban street canyon. PMF analysis successfully extracted 11 factors from mass spectra of about 700,000 particles as a complement to information on particle types (from K-means cluster analysis). The factors were associated with specific sources and represent the contribution of different traffic related components (i.e., lubricating oils, fresh elemental carbon, organonitrogen and aromatic compounds), secondary aerosol locally produced (i.e., nitrate, oxidized organic aerosol and oxidized organonitrogen compounds), urban background together with regional transport (aged elemental carbon and ammonium) and fresh sea spray. An important result from this study is the evidence that rapid chemical processes occur in the street canyon with production of secondary particles from road traffic emissions. These locally generated particles, together with aging processes, dramatically affected aerosol composition producing internally mixed particles. These processes may become important with stagnant air conditions and in countries where gasoline vehicles are predominant and need to be considered when quantifying the impact of traffic emissions.

Identification and manipulation of the pleuromutilin gene cluster from Clitopilus passeckerianus for increased rapid antibiotic production

NASA Astrophysics Data System (ADS)

Bailey, Andy M.; Alberti, Fabrizio; Kilaru, Sreedhar; Collins, Catherine M.; de Mattos-Shipley, Kate; Hartley, Amanda J.; Hayes, Patrick; Griffin, Alison; Lazarus, Colin M.; Cox, Russell J.; Willis, Christine L.; O'Dwyer, Karen; Spence, David W.; Foster, Gary D.

2016-05-01

Semi-synthetic derivatives of the tricyclic diterpene antibiotic pleuromutilin from the basidiomycete Clitopilus passeckerianus are important in combatting bacterial infections in human and veterinary medicine. These compounds belong to the only new class of antibiotics for human applications, with novel mode of action and lack of cross-resistance, representing a class with great potential. Basidiomycete fungi, being dikaryotic, are not generally amenable to strain improvement. We report identification of the seven-gene pleuromutilin gene cluster and verify that using various targeted approaches aimed at increasing antibiotic production in C. passeckerianus, no improvement in yield was achieved. The seven-gene pleuromutilin cluster was reconstructed within Aspergillus oryzae giving production of pleuromutilin in an ascomycete, with a significant increase (2106%) in production. This is the first gene cluster from a basidiomycete to be successfully expressed in an ascomycete, and paves the way for the exploitation of a metabolically rich but traditionally overlooked group of fungi.

Fe-S cluster assembly in the supergroup Excavata.

PubMed

Peña-Diaz, Priscila; Lukeš, Julius

2018-04-05

The majority of established model organisms belong to the supergroup Opisthokonta, which includes yeasts and animals. While enlightening, this focus has neglected protists,  organisms that represent the bulk of eukaryotic diversity and are often regarded as primitive eukaryotes. One of these is the "supergroup" Excavata, which comprises unicellular flagellates of diverse lifestyles and contains species of medical importance, such as Trichomonas, Giardia, Naegleria, Trypanosoma and Leishmania. Excavata exhibits a continuum in mitochondrial forms, ranging from classical aerobic, cristae-bearing mitochondria to mitochondria-related organelles, such as hydrogenosomes and mitosomes, to the extreme case of a complete absence of the organelle. All forms of mitochondria house a machinery for the assembly of Fe-S clusters, ancient cofactors required in various biochemical activities needed to sustain every extant cell. In this review, we survey what is known about the Fe-S cluster assembly in the supergroup Excavata. We aim to bring attention to the diversity found in this group, reflected in gene losses and gains that have shaped the Fe-S cluster biogenesis pathways.

Script identification from images using cluster-based templates

DOEpatents

Hochberg, J.G.; Kelly, P.M.; Thomas, T.R.

1998-12-01

A computer-implemented method identifies a script used to create a document. A set of training documents for each script to be identified is scanned into the computer to store a series of exemplary images representing each script. Pixels forming the exemplary images are electronically processed to define a set of textual symbols corresponding to the exemplary images. Each textual symbol is assigned to a cluster of textual symbols that most closely represents the textual symbol. The cluster of textual symbols is processed to form a representative electronic template for each cluster. A document having a script to be identified is scanned into the computer to form one or more document images representing the script to be identified. Pixels forming the document images are electronically processed to define a set of document textual symbols corresponding to the document images. The set of document textual symbols is compared to the electronic templates to identify the script. 17 figs.

Script identification from images using cluster-based templates

DOEpatents

Hochberg, Judith G.; Kelly, Patrick M.; Thomas, Timothy R.

1998-01-01

A computer-implemented method identifies a script used to create a document. A set of training documents for each script to be identified is scanned into the computer to store a series of exemplary images representing each script. Pixels forming the exemplary images are electronically processed to define a set of textual symbols corresponding to the exemplary images. Each textual symbol is assigned to a cluster of textual symbols that most closely represents the textual symbol. The cluster of textual symbols is processed to form a representative electronic template for each cluster. A document having a script to be identified is scanned into the computer to form one or more document images representing the script to be identified. Pixels forming the document images are electronically processed to define a set of document textual symbols corresponding to the document images. The set of document textual symbols is compared to the electronic templates to identify the script.

Structure and dynamics of optically directed self-assembly of nanoparticles

PubMed Central

Roy, Debjit; Mondal, Dipankar; Goswami, Debabrata

2016-01-01

Self-assembly of nanoparticles leading to the formation of colloidal clusters often serves as the representative analogue for understanding molecular assembly. Unravelling the in situ structure and dynamics of such clusters in liquid suspensions is highly challenging. Presently colloidal clusters are first isolated from their generating environment and then their structures are probed by light scattering methods. In order to measure the in situ structure and dynamics of colloidal clusters, we have generated them using the high-repetition-rate femtosecond laser pulse optical tweezer. Since the constituent of our dimer, trimer or tetramer clusters are 250 nm radius two-photon resonant fluorophore coated nanospheres under the optical trap, they inherently produce Two-Photon Fluorescence, which undergo intra-nanosphere Fluorescence Energy Transfer. This unique energy transfer signature, in turn, enables us to visualize structures and orientations of these colloidal clusters during the process of their formation and subsequent dynamics in a liquid suspension. We also show that due to shape-birefringence, orientation and structural control of these colloidal clusters are possible as the polarization of the trapping laser is changed from linear to circular. We thus report important progress in sampling the smallest possible aggregates of nanoparticles, dimers, trimers or tetramers, formed early in the self-assembly process. PMID:27006305

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

PubMed

Vigre, Håkan; Domingues, Ana Rita Coutinho Calado; Pedersen, Ulrik Bo; Hald, Tine

2016-03-01

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters. © 2016 Society for Risk Analysis.

Metal Sulfide Cluster Complexes and their Biogeochemical Importance in the Environment

NASA Astrophysics Data System (ADS)

Luther, George W.; Rickard, David T.

2005-10-01

Aqueous clusters of FeS, ZnS and CuS constitute a major fraction of the dissolved metal load in anoxic oceanic, sedimentary, freshwater and deep ocean vent environments. Their ubiquity explains how metals are transported in anoxic environmental systems. Thermodynamic and kinetic considerations show that they have high stability in oxic aqueous environments, and are also a significant fraction of the total metal load in oxic river waters. Molecular modeling indicates that the clusters are very similar to the basic structural elements of the first condensed phase forming from aqueous solutions in the Fe-S, Zn-S and Cu-S systems. The structure of the first condensed phase is determined by the structure of the cluster in solution. This provides an alternative explanation of Ostwald's Rule, where the most soluble, metastable phases form before the stable phases. For example, in the case of FeS, we showed that the first condensed phase is nanoparticulate, metastable mackinawite with a particle size of 2 nm consisting of about 150 FeS subunits, representing the end of a continuum between aqueous FeS clusters and condensed material. These metal sulfide clusters and nanoparticles are significant in biogeochemistry. Metal sulfide clusters reduce sulfide and metal toxicity and help drive ecology. FeS cluster formation drives vent ecology and AgS cluster formation detoxifies Ag in Daphnia magna neonates. We also note a new reaction between FeS and DNA and discuss the potential role of FeS clusters in denaturing DNA.

The Core Values that Support Health, Safety, and Well-being at Work

PubMed Central

Zwetsloot, Gerard I.J.M.; Scheppingen, Arjella R. van; Bos, Evelien H.; Dijkman, Anja; Starren, Annick

2013-01-01

Background Health, safety, and well-being (HSW) at work represent important values in themselves. It seems, however, that other values can contribute to HSW. This is to some extent reflected in the scientific literature in the attention paid to values like trust or justice. However, an overview of what values are important for HSW was not available. Our central research question was: what organizational values are supportive of health, safety, and well-being at work? Methods The literature was explored via the snowball approach to identify values and value-laden factors that support HSW. Twenty-nine factors were identified as relevant, including synonyms. In the next step, these were clustered around seven core values. Finally, these core values were structured into three main clusters. Results The first value cluster is characterized by a positive attitude toward people and their “being”; it comprises the core values of interconnectedness, participation, and trust. The second value cluster is relevant for the organizational and individual “doing”, for actions planned or undertaken, and comprises justice and responsibility. The third value cluster is relevant for “becoming” and is characterized by the alignment of personal and organizational development; it comprises the values of growth and resilience. Conclusion The three clusters of core values identified can be regarded as “basic value assumptions” that underlie both organizational culture and prevention culture. The core values identified form a natural and perhaps necessary aspect of a prevention culture, complementary to the focus on rational and informed behavior when dealing with HSW risks. PMID:24422174

Spatial clustering of fatal, and non-fatal, suicide in new South Wales, Australia: implications for evidence-based prevention.

PubMed

Torok, Michelle; Konings, Paul; Batterham, Philip J; Christensen, Helen

2017-10-06

Rates of suicide appear to be increasing, indicating a critical need for more effective prevention initiatives. To increase the efficacy of future prevention initiatives, we examined the spatial distribution of suicide deaths and suicide attempts in New South Wales (NSW), Australia, to identify where high incidence 'suicide clusters' were occurring. Such clusters represent candidate regions where intervention is critically needed, and likely to have the greatest impact, thus providing an evidence-base for the targeted prioritisation of resources. Analysis is based on official suicide mortality statistics for NSW, provided by the Australian Bureau of Statistics, and hospital separations for non-fatal intentional self-harm, provided through the NSW Health Admitted Patient Data Collection at a Statistical Area 2 (SA2) geography. Geographical Information System (GIS) techniques were applied to detect suicide clusters occurring between 2005 and 2013 (aggregated), for persons aged over 5 years. The final dataset contained 5466 mortality and 86,017 non-fatal intentional self-harm cases. In total, 25 Local Government Areas were identified as primary or secondary likely candidate regions for intervention. Together, these regions contained approximately 200 SA2 level suicide clusters, which represented 46% (n = 39,869) of hospital separations and 43% (n = 2330) of suicide deaths between 2005 and 2013. These clusters primarily converged on the Eastern coastal fringe of NSW. Crude rates of suicide deaths and intentional self-harm differed at the Local Government Areas (LGA) level in NSW. There was a tendency for primary suicide clusters to occur within metropolitan and coastal regions, rather than rural areas. The findings demonstrate the importance of taking geographical variation of suicidal behaviour into account, prior to development and implementation of prevention initiatives, so that such initiatives can target key problem areas where they are likely to have maximal impact.

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

NASA Technical Reports Server (NTRS)

Fisher, Douglas H. (Principal Investigator)

1995-01-01

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.

PubMed

Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun

2014-10-27

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

Understanding the motives for food choice in Western Balkan Countries.

PubMed

Milošević, Jasna; Žeželj, Iris; Gorton, Matthew; Barjolle, Dominique

2012-02-01

Substantial empirical evidence exists regarding the importance of different factors underlying food choice in Western Europe. However, research results on eating habits and food choice in the Western Balkan Countries (WBCs) remain scarce. A Food Choice Questionnaire (FCQ), an instrument that measures the reported importance of nine factors underlying food choice, was administered to a representative sample of 3085 adult respondents in six WBCs. The most important factors reported are sensory appeal, purchase convenience, and health and natural content; the least important are ethical concern and familiarity. The ranking of food choice motives across WBCs was strikingly similar. Factor analysis revealed eight factors compared to nine in the original FCQ model: health and natural content scales loaded onto one factor as did familiarity and ethical concern; the convenience scale items generated two factors, one related to purchase convenience and the other to preparation convenience. Groups of consumers with similar motivational profiles were identified using cluster analysis. Each cluster has distinct food purchasing behavior and socio-economic characteristics, for which appropriate public health communication messages can be drawn. Copyright © 2011 Elsevier Ltd. All rights reserved.

Familial cancer syndromes and clusters.

PubMed

Birch, J M

1994-07-01

The study of rare families in which a variety of cancers occur, usually at an early age and with patterns consistent with a common hereditary mechanism, has contributed much to our understanding of the process of carcinogenesis. So far, genes identified as having a role in cancer predisposition in these families have also been important in the histogenesis of sporadic cancers. In the two most clearly defined cancer family syndromes, the Li-Fraumeni syndrome and Lynch syndrome II, the genes involved predispose to diverse but specific constellations of cancers. Genes associated with site-specific familial cancer clusters may also give rise to increased susceptibility to other cancers, and site-specific clusters may represent one end of a spectrum. A consistent feature of familial cancer syndromes is the variable expression within and between families. A challenge for the future will be to determine other factors which may interact with the principal genes involved, giving rise to this variability.

An effective trust-based recommendation method using a novel graph clustering algorithm

NASA Astrophysics Data System (ADS)

Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

2015-10-01

Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

LoCuSS: weak-lensing mass calibration of galaxy clusters

NASA Astrophysics Data System (ADS)

Okabe, Nobuhiro; Smith, Graham P.

2016-10-01

We present weak-lensing mass measurements of 50 X-ray luminous galaxy clusters at 0.15 ≤ z ≤ 0.3, based on uniform high-quality observations with Suprime-Cam mounted on the 8.2-m Subaru telescope. We pay close attention to possible systematic biases, aiming to control them at the ≲4 per cent level. The dominant source of systematic bias in weak-lensing measurements of the mass of individual galaxy clusters is contamination of background galaxy catalogues by faint cluster and foreground galaxies. We extend our conservative method for selecting background galaxies with (V - I') colours redder than the red sequence of cluster members to use a colour-cut that depends on cluster-centric radius. This allows us to define background galaxy samples that suffer ≤1 per cent contamination, and comprise 13 galaxies per square arcminute. Thanks to the purity of our background galaxy catalogue, the largest systematic that we identify in our analysis is a shape measurement bias of 3 per cent, that we measure using simulations that probe weak shears up to g = 0.3. Our individual cluster mass and concentration measurements are in excellent agreement with predictions of the mass-concentration relation. Equally, our stacked shear profile is in excellent agreement with the Navarro Frenk and White profile. Our new Local Cluster Substructure Survey mass measurements are consistent with the Canadian Cluster Cosmology Project and Cluster Lensing And Supernova Survey with Hubble surveys, and in tension with the Weighing the Giants at ˜1σ-2σ significance. Overall, the consensus at z ≤ 0.3 that is emerging from these complementary surveys represents important progress for cluster mass calibration, and augurs well for cluster cosmology.

A quantitative study of the clustering of polycyclic aromatic hydrocarbons at high temperatures.

PubMed

Totton, Tim S; Misquitta, Alston J; Kraft, Markus

2012-03-28

The clustering of polycyclic aromatic hydrocarbon (PAH) molecules is investigated in the context of soot particle inception and growth using an isotropic potential developed from the benchmark PAHAP potential. This potential is used to estimate equilibrium constants of dimerisation for five representative PAH molecules based on a statistical mechanics model. Molecular dynamics simulations are also performed to study the clustering of homomolecular systems at a range of temperatures. The results from both sets of calculations demonstrate that at flame temperatures pyrene (C(16)H(10)) dimerisation cannot be a key step in soot particle formation and that much larger molecules (e.g. circumcoronene, C(54)H(18)) are required to form small clusters at flame temperatures. The importance of using accurate descriptions of the intermolecular interactions is demonstrated by comparing results to those calculated with a popular literature potential with an order of magnitude variation in the level of clustering observed. By using an accurate intermolecular potential we are able to show that physical binding of PAH molecules based on van der Waals interactions alone can only be a viable soot inception mechanism if concentrations of large PAH molecules are significantly higher than currently thought.

Selection of representative embankments based on rough set - fuzzy clustering method

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.

BinSanity: unsupervised clustering of environmental microbial assemblies using coverage and affinity propagation

PubMed Central

Heidelberg, John F.; Tully, Benjamin J.

2017-01-01

Metagenomics has become an integral part of defining microbial diversity in various environments. Many ecosystems have characteristically low biomass and few cultured representatives. Linking potential metabolisms to phylogeny in environmental microorganisms is important for interpreting microbial community functions and the impacts these communities have on geochemical cycles. However, with metagenomic studies there is the computational hurdle of ‘binning’ contigs into phylogenetically related units or putative genomes. Binning methods have been implemented with varying approaches such as k-means clustering, Gaussian mixture models, hierarchical clustering, neural networks, and two-way clustering; however, many of these suffer from biases against low coverage/abundance organisms and closely related taxa/strains. We are introducing a new binning method, BinSanity, that utilizes the clustering algorithm affinity propagation (AP), to cluster assemblies using coverage with compositional based refinement (tetranucleotide frequency and percent GC content) to optimize bins containing multiple source organisms. This separation of composition and coverage based clustering reduces bias for closely related taxa. BinSanity was developed and tested on artificial metagenomes varying in size and complexity. Results indicate that BinSanity has a higher precision, recall, and Adjusted Rand Index compared to five commonly implemented methods. When tested on a previously published environmental metagenome, BinSanity generated high completion and low redundancy bins corresponding with the published metagenome-assembled genomes. PMID:28289564

Clustering analysis of proteins from microbial genomes at multiple levels of resolution.

PubMed

Zaslavsky, Leonid; Ciufo, Stacy; Fedorov, Boris; Tatusova, Tatiana

2016-08-31

Microbial genomes at the National Center for Biotechnology Information (NCBI) represent a large collection of more than 35,000 assemblies. There are several complexities associated with the data: a great variation in sampling density since human pathogens are densely sampled while other bacteria are less represented; different protein families occur in annotations with different frequencies; and the quality of genome annotation varies greatly. In order to extract useful information from these sophisticated data, the analysis needs to be performed at multiple levels of phylogenomic resolution and protein similarity, with an adequate sampling strategy. Protein clustering is used to construct meaningful and stable groups of similar proteins to be used for analysis and functional annotation. Our approach is to create protein clusters at three levels. First, tight clusters in groups of closely-related genomes (species-level clades) are constructed using a combined approach that takes into account both sequence similarity and genome context. Second, clustroids of conservative in-clade clusters are organized into seed global clusters. Finally, global protein clusters are built around the the seed clusters. We propose filtering strategies that allow limiting the protein set included in global clustering. The in-clade clustering procedure, subsequent selection of clustroids and organization into seed global clusters provides a robust representation and high rate of compression. Seed protein clusters are further extended by adding related proteins. Extended seed clusters include a significant part of the data and represent all major known cell machinery. The remaining part, coming from either non-conservative (unique) or rapidly evolving proteins, from rare genomes, or resulting from low-quality annotation, does not group together well. Processing these proteins requires significant computational resources and results in a large number of questionable clusters. The developed filtering strategies allow to identify and exclude such peripheral proteins limiting the protein dataset in global clustering. Overall, the proposed methodology allows the relevant data at different levels of details to be obtained and data redundancy eliminated while keeping biologically interesting variations.

Radiative Feedback of Forming Star Clusters on Their GMC Environments: Theory and Simulation

NASA Astrophysics Data System (ADS)

Howard, C. S.; Pudritz, R. E.; Harris, W. E.

2013-07-01

Star clusters form from dense clumps within a molecular cloud. Radiation from these newly formed clusters feeds back on their natal molecular cloud through heating and ionization which ultimately stops gas accretion into the cluster. Recent studies suggest that radiative feedback effects from a single cluster may be sufficient to disrupt an entire cloud over a short timescale. Simulating cluster formation on a large scale, however, is computationally demanding due to the high number of stars involved. For this reason, we present a model for representing the radiative output of an entire cluster which involves randomly sampling an initial mass function (IMF) as the cluster accretes mass. We show that this model is able to reproduce the star formation histories of observed clusters. To examine the degree to which radiative feedback shapes the evolution of a molecular cloud, we use the FLASH adaptive-mesh refinement hydrodynamics code to simulate cluster formation in a turbulent cloud. Unlike previous studies, sink particles are used to represent a forming cluster rather than individual stars. Our cluster model is then coupled with a raytracing scheme to treat radiative transfer as the clusters grow in mass. This poster will outline the details of our model and present preliminary results from our 3D hydrodynamical simulations.

Combining analytical hierarchy process and agglomerative hierarchical clustering in search of expert consensus in green corridors development management.

PubMed

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts-landscape architects, regional planners, and geographers-revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Combining Analytical Hierarchy Process and Agglomerative Hierarchical Clustering in Search of Expert Consensus in Green Corridors Development Management

NASA Astrophysics Data System (ADS)

Shapira, Aviad; Shoshany, Maxim; Nir-Goldenberg, Sigal

2013-07-01

Environmental management and planning are instrumental in resolving conflicts arising between societal needs for economic development on the one hand and for open green landscapes on the other hand. Allocating green corridors between fragmented core green areas may provide a partial solution to these conflicts. Decisions regarding green corridor development require the assessment of alternative allocations based on multiple criteria evaluations. Analytical Hierarchy Process provides a methodology for both a structured and consistent extraction of such evaluations and for the search for consensus among experts regarding weights assigned to the different criteria. Implementing this methodology using 15 Israeli experts—landscape architects, regional planners, and geographers—revealed inherent differences in expert opinions in this field beyond professional divisions. The use of Agglomerative Hierarchical Clustering allowed to identify clusters representing common decisions regarding criterion weights. Aggregating the evaluations of these clusters revealed an important dichotomy between a pragmatist approach that emphasizes the weight of statutory criteria and an ecological approach that emphasizes the role of the natural conditions in allocating green landscape corridors.

Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing

PubMed Central

Nguyen, Minh Q.; Wu, Youmei; Bonilla, Lauren S.; von Buchholtz, Lars J.

2017-01-01

The trigeminal ganglion contains somatosensory neurons that detect a range of thermal, mechanical and chemical cues and innervate unique sensory compartments in the head and neck including the eyes, nose, mouth, meninges and vibrissae. We used single-cell sequencing and in situ hybridization to examine the cellular diversity of the trigeminal ganglion in mice, defining thirteen clusters of neurons. We show that clusters are well conserved in dorsal root ganglia suggesting they represent distinct functional classes of somatosensory neurons and not specialization associated with their sensory targets. Notably, functionally important genes (e.g. the mechanosensory channel Piezo2 and the capsaicin gated ion channel Trpv1) segregate into multiple clusters and often are expressed in subsets of cells within a cluster. Therefore, the 13 genetically-defined classes are likely to be physiologically heterogeneous rather than highly parallel (i.e., redundant) lines of sensory input. Our analysis harnesses the power of single-cell sequencing to provide a unique platform for in silico expression profiling that complements other approaches linking gene-expression with function and exposes unexpected diversity in the somatosensory system. PMID:28957441

Evolution of Fe/S cluster biogenesis in the anaerobic parasite Blastocystis

PubMed Central

Tsaousis, Anastasios D.; Ollagnier de Choudens, Sandrine; Gentekaki, Eleni; Long, Shaojun; Gaston, Daniel; Stechmann, Alexandra; Vinella, Daniel; Py, Béatrice; Fontecave, Marc; Barras, Frédéric; Lukeš, Julius; Roger, Andrew J.

2012-01-01

Iron/sulfur cluster (ISC)-containing proteins are essential components of cells. In most eukaryotes, Fe/S clusters are synthesized by the mitochondrial ISC machinery, the cytosolic iron/sulfur assembly system, and, in photosynthetic species, a plastid sulfur-mobilization (SUF) system. Here we show that the anaerobic human protozoan parasite Blastocystis, in addition to possessing ISC and iron/sulfur assembly systems, expresses a fused version of the SufC and SufB proteins of prokaryotes that it has acquired by lateral transfer from an archaeon related to the Methanomicrobiales, an important lineage represented in the human gastrointestinal tract microbiome. Although components of the Blastocystis ISC system function within its anaerobic mitochondrion-related organelles and can functionally replace homologues in Trypanosoma brucei, its SufCB protein has similar biochemical properties to its prokaryotic homologues, functions within the parasite’s cytosol, and is up-regulated under oxygen stress. Blastocystis is unique among eukaryotic pathogens in having adapted to its parasitic lifestyle by acquiring a SUF system from nonpathogenic Archaea to synthesize Fe/S clusters under oxygen stress. PMID:22699510

Analysis of Rainfall and PM2.5 Data Using Clustered Trajectory Analysis for National Park Sites in the Western U.S.

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Hafner, W.; Jaffe, D.

2005-12-01

We calculated daily kinematic back-trajectories using the NOAA-HYSPLIT model to analyze 7 years of PM2.5 data from National Park sites in the Western U.S. (Glacier N.P., Mount Rainier N.P., Sequoia N.P., Rocky Mountain N.P. and Denali N.P.) The back-trajectories were clustered using a k-means clustering algorithm to segregate the trajectories into 6 main transport patterns. We calculated trajectory clusters for 1, 5 and 10 days to represent short, medium and long-range flow patterns. Some trajectory types and clusters show marked seasonality. Generally faster flow patterns are more prevalent in winter and slower/stagnant patterns are more prevalent in summer. In addition, we found significant inter-annual variability that may be important for explaining variations in rainfall and/or pollutant concentrations. The 5 and 10-day analyses revealed that, for the 4 non-Alaskan sites, trajectories from Asia tend to be less frequent in the summer, compared to the rest of the year. The clusters of different duration show very different predictive power for rainfall and PM2.5. We found that the 1-day clusters are a better predictor for precipitation and PM2.5 concentrations, as compared to the 5 and 10-day clusters. At each of the sites, there is at least one cluster with an average PM2.5 concentration that is different than the average for the site, indicating distinctive transport patterns. The same is true for 5 and 10-day clusters. Interestingly, only one site, Mount Rainier N.P., shows seasonal differences in PM2.5 concentrations between the clusters that differ from the average.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Data Clustering

NASA Astrophysics Data System (ADS)

Wagstaff, Kiri L.

2012-03-01

On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained clustering, in which some partial information about item assignments or other components of the resulting output are already known and must be accommodated by the solution. Some algorithms seek a partition of the data set into distinct clusters, while others build a hierarchy of nested clusters that can capture taxonomic relationships. Some produce a single optimal solution, while others construct a probabilistic model of cluster membership. More formally, clustering algorithms operate on a data set X composed of items represented by one or more features (dimensions). These could include physical location, such as right ascension and declination, as well as other properties such as brightness, color, temporal change, size, texture, and so on. Let D be the number of dimensions used to represent each item, xi ∈ RD. The clustering goal is to produce an organization P of the items in X that optimizes an objective function f : P -> R, which quantifies the quality of solution P. Often f is defined so as to maximize similarity within a cluster and minimize similarity between clusters. To that end, many algorithms make use of a measure d : X x X -> R of the distance between two items. A partitioning algorithm produces a set of clusters P = {c1, . . . , ck} such that the clusters are nonoverlapping (c_i intersected with c_j = empty set, i != j) subsets of the data set (Union_i c_i=X). Hierarchical algorithms produce a series of partitions P = {p1, . . . , pn }. For a complete hierarchy, the number of partitions n’= n, the number of items in the data set; the top partition is a single cluster containing all items, and the bottom partition contains n clusters, each containing a single item. For model-based clustering, each cluster c_j is represented by a model m_j , such as the cluster center or a Gaussian distribution. The wide array of available clustering algorithms may seem bewildering, and covering all of them is beyond the scope of this chapter. Choosing among them for a particular application involves considerations of the kind of data being analyzed, algorithm runtime efficiency, and how much prior knowledge is available about the problem domain, which can dictate the nature of clusters sought. Fundamentally, the clustering method and its representations of clusters carries with it a definition of what a cluster is, and it is important that this be aligned with the analysis goals for the problem at hand. In this chapter, I emphasize this point by identifying for each algorithm the cluster representation as a model, m_j , even for algorithms that are not typically thought of as creating a “model.” This chapter surveys a basic collection of clustering methods useful to any practitioner who is interested in applying clustering to a new data set. The algorithms include k-means (Section 25.2), EM (Section 25.3), agglomerative (Section 25.4), and spectral (Section 25.5) clustering, with side mentions of variants such as kernel k-means and divisive clustering. The chapter also discusses each algorithm’s strengths and limitations and provides pointers to additional in-depth reading for each subject. Section 25.6 discusses methods for incorporating domain knowledge into the clustering process. This chapter concludes with a brief survey of interesting applications of clustering methods to astronomy data (Section 25.7). The chapter begins with k-means because it is both generally accessible and so widely used that understanding it can be considered a necessary prerequisite for further work in the field. EM can be viewed as a more sophisticated version of k-means that uses a generative model for each cluster and probabilistic item assignments. Agglomerative clustering is the most basic form of hierarchical clustering and provides a basis for further exploration of algorithms in that vein. Spectral clustering permits a departure from feature-vector-based clustering and can operate on data sets instead represented as affinity, or similarity matrices—cases in which only pairwise information is known. The list of algorithms covered in this chapter is representative of those most commonly in use, but it is by no means comprehensive. There is an extensive collection of existing books on clustering that provide additional background and depth. Three early books that remain useful today are Anderberg’s Cluster Analysis for Applications [3], Hartigan’s Clustering Algorithms [25], and Gordon’s Classification [22]. The latter covers basics on similarity measures, partitioning and hierarchical algorithms, fuzzy clustering, overlapping clustering, conceptual clustering, validations methods, and visualization or data reduction techniques such as principal components analysis (PCA),multidimensional scaling, and self-organizing maps. More recently, Jain et al. provided a useful and informative survey [27] of a variety of different clustering algorithms, including those mentioned here as well as fuzzy, graph-theoretic, and evolutionary clustering. Everitt’s Cluster Analysis [19] provides a modern overview of algorithms, similarity measures, and evaluation methods.

Role and Regulation of the Flp/Tad Pilus in the Virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193

PubMed Central

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E. Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers. PMID:24040039

Role and regulation of the Flp/Tad pilus in the virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193.

PubMed

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers.

How Well Do We Know The Supernova Equation of State?

NASA Astrophysics Data System (ADS)

Hempel, Matthias; Oertel, Micaela; Typel, Stefan; Klähn, Thomas

We give an overview about equations of state (EOS) which are currently available for simulations of core-collapse supernovae and neutron star mergers. A few selected important aspects of the EOS, such as the symmetry energy, the maximum mass of neutron stars, and cluster formation, are confronted with constraints from experiments and astrophysical observations. There are just very few models which are compatible even with this very restricted set of constraints. These remaining models illustrate the uncertainty of the uniform nuclear matter EOS at high densities. In addition, at finite temperatures the medium modifications of nuclear clusters represent a conceptual challenge. In conclusion, there has been significant development in the recent years, but there is still need for further improved general purpose EOS tables.

A Survey on Sentiment Classification in Face Recognition

NASA Astrophysics Data System (ADS)

Qian, Jingyu

2018-01-01

Face recognition has been an important topic for both industry and academia for a long time. K-means clustering, autoencoder, and convolutional neural network, each representing a design idea for face recognition method, are three popular algorithms to deal with face recognition problems. It is worthwhile to summarize and compare these three different algorithms. This paper will focus on one specific face recognition problem-sentiment classification from images. Three different algorithms for sentiment classification problems will be summarized, including k-means clustering, autoencoder, and convolutional neural network. An experiment with the application of these algorithms on a specific dataset of human faces will be conducted to illustrate how these algorithms are applied and their accuracy. Finally, the three algorithms are compared based on the accuracy result.

A simple, efficient polarizable coarse-grained water model for molecular dynamics simulations.

PubMed

Riniker, Sereina; van Gunsteren, Wilfred F

2011-02-28

The development of coarse-grained (CG) models that correctly represent the important features of compounds is essential to overcome the limitations in time scale and system size currently encountered in atomistic molecular dynamics simulations. Most approaches reported in the literature model one or several molecules into a single uncharged CG bead. For water, this implicit treatment of the electrostatic interactions, however, fails to mimic important properties, e.g., the dielectric screening. Therefore, a coarse-grained model for water is proposed which treats the electrostatic interactions between clusters of water molecules explicitly. Five water molecules are embedded in a spherical CG bead consisting of two oppositely charged particles which represent a dipole. The bond connecting the two particles in a bead is unconstrained, which makes the model polarizable. Experimental and all-atom simulated data of liquid water at room temperature are used for parametrization of the model. The experimental density and the relative static dielectric permittivity were chosen as primary target properties. The model properties are compared with those obtained from experiment, from clusters of simple-point-charge water molecules of appropriate size in the liquid phase, and for other CG water models if available. The comparison shows that not all atomistic properties can be reproduced by a CG model, so properties of key importance have to be selected when coarse graining is applied. Yet, the CG model reproduces the key characteristics of liquid water while being computationally 1-2 orders of magnitude more efficient than standard fine-grained atomistic water models.

Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

PubMed

Chen, Xueying; Zhao, Min; Qu, Hong

2015-01-01

T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis.

Analysing and Navigating Natural Products Space for Generating Small, Diverse, But Representative Chemical Libraries.

PubMed

O'Hagan, Steve; Kell, Douglas B

2018-01-01

Armed with the digital availability of two natural products libraries, amounting to some 195 885 molecular entities, we ask the question of how we can best sample from them to maximize their "representativeness" in smaller and more usable libraries of 96, 384, 1152, and 1920 molecules. The term "representativeness" is intended to include diversity, but for numerical reasons (and the likelihood of being able to perform a QSAR) it is necessary to focus on areas of chemical space that are more highly populated. Encoding chemical structures as fingerprints using the RDKit "patterned" algorithm, we first assess the granularity of the natural products space using a simple clustering algorithm, showing that there are major regions of "denseness" but also a great many very sparsely populated areas. We then apply a "hybrid" hierarchical K-means clustering algorithm to the data to produce more statistically robust clusters from which representative and appropriate numbers of samples may be chosen. There is necessarily again a trade-off between cluster size and cluster number, but within these constraints, libraries containing 384 or 1152 molecules can be found that come from clusters that represent some 18 and 30% of the whole chemical space, with cluster sizes of, respectively, 50 and 27 or above, just about sufficient to perform a QSAR. By using the online availability of molecules via the Molport system (www.molport.com), we are also able to construct (and, for the first time, provide the contents of) a small virtual library of available molecules that provided effective coverage of the chemical space described. Consistent with this, the average molecular similarities of the contents of the libraries developed is considerably smaller than is that of the original libraries. The suggested libraries may have use in molecular or phenotypic screening, including for determining possible transporter substrates. © 2017 The Authors. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Gene transfer agent (GTA) genes reveal diverse and dynamic Roseobacter and Rhodobacter populations in the Chesapeake Bay.

PubMed

Zhao, Yanlin; Wang, Kui; Budinoff, Charles; Buchan, Alison; Lang, Andrew; Jiao, Nianzhi; Chen, Feng

2009-03-01

Within the bacterial class Alphaproteobacteria, the order Rhodobacterales contains the Roseobacter and Rhodobacter clades. Roseobacters are abundant and play important biogeochemical roles in marine environments. Roseobacter and Rhodobacter genomes contain a conserved gene transfer agent (GTA) gene cluster, and GTA-mediated gene transfer has been observed in these groups of bacteria. In this study, we investigated the genetic diversity of these two groups in Chesapeake Bay surface waters using a specific PCR primer set targeting the conserved Rhodobacterales GTA major capsid protein gene (g5). The g5 gene was successfully amplified from 26 Rhodobacterales isolates and the bay microbial communities using this primer set. Four g5 clone libraries were constructed from microbial assemblages representing different regions and seasons of the bay and yielded diverse sequences. In total, 12 distinct g5 clusters could be identified among 158 Chesapeake Bay clones, 11 fall within the Roseobacter clade, and one falls in the Rhodobacter clade. The vast majority of the clusters (10 out of 12) lack cultivated representatives. The composition of g5 sequences varied dramatically along the bay during the wintertime, and a distinct Roseobacter population composition between winter and summer was observed. The congruence between g5 and 16S rRNA gene phylogenies indicates that g5 may serve as a useful genetic marker to investigate diversity and abundance of Roseobacter and Rhodobacter in natural environments. The presence of the g5 gene in the natural populations of Roseobacter and Rhodobacter implies that genetic exchange through GTA transduction could be an important mechanism for maintaining the metabolic flexibility of these groups of bacteria.

Discovery of a Galaxy Cluster with a Violently Starbursting Core at z = 2.506

NASA Astrophysics Data System (ADS)

Wang, Tao; Elbaz, David; Daddi, Emanuele; Finoguenov, Alexis; Liu, Daizhong; Schreiber, Corentin; Martín, Sergio; Strazzullo, Veronica; Valentino, Francesco; van der Burg, Remco; Zanella, Anita; Ciesla, Laure; Gobat, Raphael; Le Brun, Amandine; Pannella, Maurilio; Sargent, Mark; Shu, Xinwen; Tan, Qinghua; Cappelluti, Nico; Li, Yanxia

2016-09-01

We report the discovery of a remarkable concentration of massive galaxies with extended X-ray emission at z spec = 2.506, which contains 11 massive (M * ≳ 1011 M ⊙) galaxies in the central 80 kpc region (11.6σ overdensity). We have spectroscopically confirmed 17 member galaxies with 11 from CO and the remaining ones from Hα. The X-ray luminosity, stellar mass content, and velocity dispersion all point to a collapsed, cluster-sized dark matter halo with mass M 200c = 1013.9±0.2 M ⊙, making it the most distant X-ray-detected cluster known to date. Unlike other clusters discovered so far, this structure is dominated by star-forming galaxies (SFGs) in the core with only 2 out of the 11 massive galaxies classified as quiescent. The star formation rate (SFR) in the 80 kpc core reaches ˜3400 M ⊙ yr-1 with a gas depletion time of ˜200 Myr, suggesting that we caught this cluster in rapid build-up of a dense core. The high SFR is driven by both a high abundance of SFGs and a higher starburst fraction (˜25%, compared to 3%-5% in the field). The presence of both a collapsed, cluster-sized halo and a predominant population of massive SFGs suggests that this structure could represent an important transition phase between protoclusters and mature clusters. It provides evidence that the main phase of massive galaxy passivization will take place after galaxies accrete onto the cluster, providing new insights into massive cluster formation at early epochs. The large integrated stellar mass at such high redshift challenges our understanding of massive cluster formation.

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

PubMed

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Methamphetamine injecting is associated with phylogenetic clustering of hepatitis C virus infection among street-involved youth in Vancouver, Canada*

PubMed Central

Cunningham, Evan; Jacka, Brendan; DeBeck, Kora; Applegate, Tanya A; Harrigan, P. Richard; Krajden, Mel; Marshall, Brandon DL; Montaner, Julio; Lima, Viviane Dias; Olmstead, Andrea; Milloy, M-J; Wood, Evan; Grebely, Jason

2015-01-01

Background Among prospective cohorts of people who inject drugs (PWID), phylogenetic clustering of HCV infection has been observed. However, the majority of studies have included older PWID, representing distant transmission events. The aim of this study was to investigate phylogenetic clustering of HCV infection among a cohort of street-involved youth. Methods Data were derived from a prospective cohort of street-involved youth aged 14–26 recruited between 2005 and 2012 in Vancouver, Canada (At Risk Youth Study, ARYS). HCV RNA testing and sequencing (Core-E2) were performed on HCV positive participants. Phylogenetic trees were inferred using maximum likelihood methods and clusters were identified using ClusterPicker (Core-E2 without HVR1, 90% bootstrap threshold, 0.05 genetic distance threshold). Results Among 945 individuals enrolled in ARYS, 16% (n=149, 100% recent injectors) were HCV antibody positive at baseline interview (n=86) or seroconverted during follow-up (n=63). Among HCV antibody positive participants with available samples (n=131), 75% (n=98) had detectable HCV RNA and 66% (n=65, mean age 23, 58% with recent methamphetamine injection, 31% female, 3% HIV+) had available Core-E2 sequences. Of those with Core-E2 sequence, 14% (n=9) were in a cluster (one cluster of three) or pair (two pairs), with all reporting recent methamphetamine injection. Recent methamphetamine injection was associated with membership in a cluster or pair (P=0.009). Conclusion In this study of street-involved youth with HCV infection and recent injecting, 14% demonstrated phylogenetic clustering. Phylogenetic clustering was associated with recent methamphetamine injection, suggesting that methamphetamine drug injection may play an important role in networks of HCV transmission. PMID:25977204

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

DISCOVERY OF A GALAXY CLUSTER WITH A VIOLENTLY STARBURSTING CORE AT z = 2.506

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Tao; Elbaz, David; Daddi, Emanuele

2016-09-01

We report the discovery of a remarkable concentration of massive galaxies with extended X-ray emission at z {sub spec} = 2.506, which contains 11 massive (M {sub *} ≳ 10{sup 11} M {sub ⊙}) galaxies in the central 80 kpc region (11.6 σ overdensity). We have spectroscopically confirmed 17 member galaxies with 11 from CO and the remaining ones from H α . The X-ray luminosity, stellar mass content, and velocity dispersion all point to a collapsed, cluster-sized dark matter halo with mass M {sub 200} {sub c} = 10{sup 13.9±0.2} M {sub ⊙}, making it the most distant X-ray-detectedmore » cluster known to date. Unlike other clusters discovered so far, this structure is dominated by star-forming galaxies (SFGs) in the core with only 2 out of the 11 massive galaxies classified as quiescent. The star formation rate (SFR) in the 80 kpc core reaches ∼3400 M {sub ⊙} yr{sup −1} with a gas depletion time of ∼200 Myr, suggesting that we caught this cluster in rapid build-up of a dense core. The high SFR is driven by both a high abundance of SFGs and a higher starburst fraction (∼25%, compared to 3%–5% in the field). The presence of both a collapsed, cluster-sized halo and a predominant population of massive SFGs suggests that this structure could represent an important transition phase between protoclusters and mature clusters. It provides evidence that the main phase of massive galaxy passivization will take place after galaxies accrete onto the cluster, providing new insights into massive cluster formation at early epochs. The large integrated stellar mass at such high redshift challenges our understanding of massive cluster formation.« less

Spectral characteristics and the extent of paleosols of the Palouse formation

NASA Technical Reports Server (NTRS)

Frazier, B. E.; Busacca, A.; Cheng, Y.; Wherry, D.; Hart, J.; Gill, S.

1986-01-01

Spectral relationships were investigated for several bare soil fields which were in summer fallow rotation on the date of the imagery. Printouts of each band were examined and compared to aerial photography. Bands with dissimilar reflectance patterns for known areas were then combined using ratio techniques which were proven useful in other studies (Williams, 1983). Selected ratios were Thematic Mapper (TM) 1/TM4, TM3/TM4, and TM5/TM4. Cluster analyses and Baysian and Fastclass classifier images were produced using the three ratio images. Plots of cluster analysis outputs revealed distinct groupings of reflectance data representing green crops, ripened crops, soil and green plants, and bare soil. Bare soil was represented by a line of clusters on plots of the ratios TM5/TM4 and TM3/TM4. The soil line was investigated further to determine factors involved in the distributin of clusters alone the line. The clusters representing the bare soil line were also studied by plotting the Tm5/TM4, TM1/TM4 dimension. A total of 76 soil samples were gathered and analyzed for organic carbon.

Cluster analysis of the national weight control registry to identify distinct subgroups maintaining successful weight loss.

PubMed

Ogden, Lorraine G; Stroebele, Nanette; Wyatt, Holly R; Catenacci, Victoria A; Peters, John C; Stuht, Jennifer; Wing, Rena R; Hill, James O

2012-10-01

The National Weight Control Registry (NWCR) is the largest ongoing study of individuals successful at maintaining weight loss; the registry enrolls individuals maintaining a weight loss of at least 13.6 kg (30 lb) for a minimum of 1 year. The current report uses multivariate latent class cluster analysis to identify unique clusters of individuals within the NWCR that have distinct experiences, strategies, and attitudes with respect to weight loss and weight loss maintenance. The cluster analysis considers weight and health history, weight control behaviors and strategies, effort and satisfaction with maintaining weight, and psychological and demographic characteristics. The analysis includes 2,228 participants enrolled between 1998 and 2002. Cluster 1 (50.5%) represents a weight-stable, healthy, exercise conscious group who are very satisfied with their current weight. Cluster 2 (26.9%) has continuously struggled with weight since childhood; they rely on the greatest number of resources and strategies to lose and maintain weight, and report higher levels of stress and depression. Cluster 3 (12.7%) represents a group successful at weight reduction on the first attempt; they were least likely to be overweight as children, are maintaining the longest duration of weight loss, and report the least difficulty maintaining weight. Cluster 4 (9.9%) represents a group less likely to use exercise to control weight; they tend to be older, eat fewer meals, and report more health problems. Further exploration of the unique characteristics of these clusters could be useful for tailoring future weight loss and weight maintenance programs to the specific characteristics of an individual.

Drought prediction till 2100 under RCP 8.5 climate change scenarios for Korea

NASA Astrophysics Data System (ADS)

Park, Chang-Kyun; Byun, Hi-Ryong; Deo, Ravinesh; Lee, Bo-Ra

2015-07-01

An important step in mitigating the negative impacts of drought requires effective methodologies for predicting the future events. This study utilises the daily Effective Drought Index (EDI) to precisely and quantitatively predict future drought occurrences in Korea over the period 2014-2100. The EDI is computed from precipitation data generated by the regional climate model (HadGEM3-RA) under the Representative Concentration Pathway (RCP 8.5) scenario. Using this data for 678 grid points (12.5 km interval) groups of cluster regions with similar climates, the G1 (Northwest), G2 (Middle), G3 (Northeast) and G4 (Southern) regions, are constructed. Drought forecasting period is categorised into the early phase (EP, 2014-2040), middle phase (MP, 2041-2070) and latter phase (LP, 2071-2100). Future drought events are quantified and ranked according to the duration and intensity. Moreover, the occurrences of drought (when, where, how severe) within the clustered regions are represented as a spatial map over Korea. Based on the grid-point averages, the most severe future drought throughout the 87-year period are expected to occur in Namwon around 2039-2041 with peak intensity (minimum EDI) -3.54 and projected duration of 580 days. The most severe drought by cluster analysis is expected to occur in the G3 region with a mean intensity of -2.85 in 2027. Within the spatial area of investigation, 6.6 years of drought periodicity and a slight decrease in the peak intensity is noted. Finally a spatial-temporal drought map is constructed for all clusters and time-periods under consideration.

Drought Prediction till 2100 Under RCP 8.5 Climate Change Scenarios for Korea

NASA Astrophysics Data System (ADS)

Byun, H. R.; Park, C. K.; Deo, R. C.

2014-12-01

An important step in mitigating the negative impacts of drought requires effective methodologies for predicting the future events. This study utilizes the daily Effective Drought Index (EDI) to precisely and quantitatively predict future drought occurrences in Korea over the period 2014-2100. The EDI is computed from precipitation data generated by the regional climate model (HadGEM3-RA) under the Representative Concentration Pathway (RCP 8.5) scenario. Using this data for 678 grid points (12.5 km interval) groups of cluster regions with similar climates, the G1 (Northwest), G2 (Middle), G3 (Northeast) and G4 (Southern) regions, are constructed. Drought forecasting period is categorised into the early phase (EP, 2014-2040), middle phase (MP, 2041-2070) and latter phase (LP, 2071-2100). Future drought events are quantified and ranked according to the duration and intensity. Moreover, the occurrences of drought (when, where, how severe) within the clustered regions are represented as a spatial map over Korea. Based on the grid-point averages, the most severe future drought throughout the 87-year period are expected to occur in Namwon around 2039-2041 with peak intensity (minimum EDI) -3.54 and projected duration of 580 days. The most severe drought by cluster analysis is expected to occur in the G3 region with a mean intensity of -2.85 in 2027. Within the spatial area of investigation, 6 years of drought periodicity and a slight decrease in the peak intensity is noted. Finally a spatial-temporal drought map is constructed for all clusters and time-periods under consideration.

Characterization of Heterogeneity in Childhood Immunization Coverage in Central Florida Using Immunization Registry Data.

PubMed

Thompson, Kimberly M; Logan, Grace E

2016-07-01

Despite high vaccine coverage in the United States in general, and in the State of Florida specifically, some children miss scheduled vaccines due to health system failures or vaccine refusal by their parents. Recent experiences with outbreaks in the United States suggest that geographic clustering of un(der)vaccinated populations represent a threat to the elimination status of some vaccine-preventable diseases. Immunization registries continue to expand and play an important role in efforts to track vaccine coverage and use. Using nearly 700,000 de-identified immunization records from the Florida Department of Health immunization information system (Florida SHOTS™) for children born during 2003-2014, we explored heterogeneity and potential clustering of un(der)vaccinated children in six counties in central Florida-Brevard, Lake, Orange, Oseola, Polk, and Seminole-that represent a high-risk area for importation due to family tourist attractions in the area. By zip code, we mapped the population density, the percent of children with religious exemptions, the percent of children on track or overdue for each vaccine series without and with exemptions, and the numbers of children with no recorded dose of each vaccine. Overall, we found some heterogeneity in coverage among the counties and zip codes, but relatively consistent and high coverage. We found that some children with an exemption in the system received the vaccines we analyzed, but exemption represents a clear risk factor for un(der)immunization. We identified many challenges associated with using immunization registry data for spatial analysis and potential opportunities to improve registries to better support future analyses. © 2015 Society for Risk Analysis.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

Diverse characteristics of the urinary excretion of amino acids in humans and the use of amino acid supplementation to reduce fatigue and sub-health in adults.

PubMed

Dunstan, R H; Sparkes, D L; Macdonald, M M; De Jonge, X Janse; Dascombe, B J; Gottfries, J; Gottfries, C-G; Roberts, T K

2017-03-23

The excretion of amino acids in urine represents an important avenue for the loss of key nutrients. Some amino acids such as glycine and histidine are lost in higher abundance than others. These two amino acids perform important physiological functions and are required for the synthesis of key proteins such as haemoglobin and collagen. Stage 1 of this study involved healthy subjects (n = 151) who provided first of the morning urine samples and completed symptom questionnaires. Urine was analysed for amino acid composition by gas chromatography. Stage 2 involved a subset of the initial cohort (n = 37) who completed a 30 day trial of an amino acid supplement and subsequent symptom profile evaluation. Analyses of urinary amino acid profiles revealed that three groups could be objectively defined from the 151 participants using k-means clustering. The amino acid profiles were significantly different between each of the clusters (Wilks' Lambda = 0.13, p < 0.0001). Cluster 1 had the highest loss of amino acids with histidine being the most abundant component. Cluster 2 had glycine present as the most abundant urinary amino acid and cluster 3 had equivalent abundances of glycine and histidine. Strong associations were observed between urinary proline concentrations and fatigue/pain scores (r = .56 to .83) for females in cluster 1, with several other differential sets of associations observed for the other clusters. Different phenotypic subsets exist in the population based on amino acid excretion characteristics found in urine. Provision of the supplement resulted in significant improvements in reported fatigue and sleep for 81% of the trial cohort with all females reporting improvements in fatigue. The study was registered on the 18th April 2011 with the Australian New Zealand Clinical Trials Registry ( ACTRN12611000403932 ).

The SEQUEST Family Tree

NASA Astrophysics Data System (ADS)

Tabb, David L.

2015-11-01

Since its introduction in 1994, SEQUEST has gained many important new capabilities, and a host of successor algorithms have built upon its successes. This Account and Perspective maps the evolution of this important tool and charts the relationships among contributions to the SEQUEST legacy. Many of the changes represented improvements in computing speed by clusters and graphics cards. Mass spectrometry innovations in mass accuracy and activation methods led to shifts in fragment modeling and scoring strategies. These changes, as well as the movement of laboratories and lab members, have led to great diversity among the members of the SEQUEST family.

The Impact of Clinical, Demographic and Risk Factors on Rates of HIV Transmission: A Population-based Phylogenetic Analysis in British Columbia, Canada

PubMed Central

Poon, Art F. Y.; Joy, Jeffrey B.; Woods, Conan K.; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J.; Hogg, Robert S.; Montaner, Julio S. G.; Harrigan, P. Richard

2015-01-01

Background. The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. Methods. We reconstructed molecular phylogenies from 27 296 anonymized bulk HIV pol sequences representing 7747 individuals in BC—about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Results. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Conclusions. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. PMID:25312037

Chaperone expression profiles correlate with distinct physiological states of Plasmodium falciparum in malaria patients

PubMed Central

2010-01-01

Background Molecular chaperones have been shown to be important in the growth of the malaria parasite Plasmodium falciparum and inhibition of chaperone function by pharmacological agents has been shown to abrogate parasite growth. A recent study has demonstrated that clinical isolates of the parasite have distinct physiological states, one of which resembles environmental stress response showing up-regulation of specific molecular chaperones. Methods Chaperone networks operational in the distinct physiological clusters in clinical malaria parasites were constructed using cytoscape by utilizing their clinical expression profiles. Results Molecular chaperones show distinct profiles in the previously defined physiologically distinct states. Further, expression profiles of the chaperones from different cellular compartments correlate with specific patient clusters. While cluster 1 parasites, representing a starvation response, show up-regulation of organellar chaperones, cluster 2 parasites, which resemble active growth based on glycolysis, show up-regulation of cytoplasmic chaperones. Interestingly, cytoplasmic Hsp90 and its co-chaperones, previously implicated as drug targets in malaria, cluster in the same group. Detailed analysis of chaperone expression in the patient cluster 2 reveals up-regulation of the entire Hsp90-dependent pro-survival circuitries. In addition, cluster 2 also shows up-regulation of Plasmodium export element (PEXEL)-containing Hsp40s thought to have regulatory and host remodeling roles in the infected erythrocyte. Conclusion In all, this study demonstrates an intimate involvement of parasite-encoded chaperones, PfHsp90 in particular, in defining pathogenesis of malaria. PMID:20719001

Mitochondrial filaments and clusters as intracellular power-transmitting cables.

PubMed

Skulachev, V P

2001-01-01

Mitochondria exist in two interconverting forms; as small isolated particles, and as extended filaments, networks or clusters connected with intermitochondrial junctions. Extended mitochondria can represent electrically united systems, which can facilitate energy delivery from the cell periphery to the cell core and organize antioxidant defence of the cell interior when O2 is consumed by mitochondrial clusters near the the outer cell membrane, and protonic potential is transmitted to the cell core mitochondria to form ATP. As to small mitochondria, they might represent a transportable form of these organelles.

A channel differential EZW coding scheme for EEG data compression.

PubMed

Dehkordi, Vahid R; Daou, Hoda; Labeau, Fabrice

2011-11-01

In this paper, a method is proposed to compress multichannel electroencephalographic (EEG) signals in a scalable fashion. Correlation between EEG channels is exploited through clustering using a k-means method. Representative channels for each of the clusters are encoded individually while other channels are encoded differentially, i.e., with respect to their respective cluster representatives. The compression is performed using the embedded zero-tree wavelet encoding adapted to 1-D signals. Simulations show that the scalable features of the scheme lead to a flexible quality/rate tradeoff, without requiring detailed EEG signal modeling.

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Using concept mapping to mobilize a Black faith community to address HIV

PubMed Central

Szaflarski, Magdalena; Vaughn, Lisa M; McLinden, Daniel; Wess, Yolanda; Ruffner, Andrew

2017-01-01

Research that partners with community stakeholders increases contextual relevance and community buy-in and maximizes the chance for intervention success. Within a framework of an academic-community partnership, this project assessed a Black faith-community’s needs and opportunities to address HIV. We used concept mapping to identify/prioritize specific HIV-related strategies that would be acceptable to congregations. Ninety stakeholders brainstormed strategies to address HIV; 21 sorted strategies into groups and rated their importance and feasibility. Multidimensional scaling and cluster analysis were applied to the sorting to produce maps that illustrated the stakeholders’ conceptual thinking about HIV interventions. Of 278 responses, 93 were used in the sorting task. The visual maps represented eight clusters: church acceptance of people living with HIV; education (most feasible); mobilization and communication; church/leaders’ empowerment; church involvement/collaboration; safety/HIV prevention; media outreach; and, stigma (most important). Concept mapping clarified multifaceted issues of HIV in the Black faith community. The results will guide HIV programming in congregations. PMID:28239439

Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

DOE PAGES

Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.; ...

2014-11-13

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

Engraftment and reversal of diabetes after intramuscular transplantation of neonatal porcine islet-like clusters.

PubMed

Wolf-van Buerck, Lelia; Schuster, Marion; Baehr, Andrea; Mayr, Tanja; Guethoff, Sonja; Abicht, Jan; Reichart, Bruno; Nam-Apostolopoulos, Yun-Chung; Klymiuk, Nikolai; Wolf, Eckhard; Seissler, Jochen

2015-01-01

Intraportal infusion is currently the method of choice for clinical islet cell transplantation but suffers from poor efficacy. As the liver may not represent an optimal transplantation site for Langerhans islets, we examined the potential of neonatal porcine islet-like clusters (NPICCs) to engraft in skeletal muscle as an alternative transplantation site. Neonatal porcine islet-like clusters were isolated from 2- to 5-day-old piglets and either transplanted under the kidney capsule (s.k.) or injected into the lower hindlimb muscle (i.m.) of streptozotocin-diabetic NOD-SCID IL2rγ(-/-) (NSG) mice. Survival, vascularization, maturation, and functional activity were analyzed by intraperitoneal glucose tolerance testing and immunohistochemical analyses. Intramuscular transplantation of NPICCs resulted in development of normoglycemia and restored glucose homeostasis. Time to reversal of diabetes and glucose tolerance (AUC glucose and AUC insulin) did not significantly differ as compared to s.k. transplantation. Intramuscular grafts exhibited rapid neovascularization and graft composition with cytokeratin-positive ductal cells and beta cells at post-transplant weeks 2 and 8 and after establishment of normoglycemia was comparable in both groups. Intramuscular injection represents a minimally invasive but efficient alternative for transplantation of NPICCs and, thus, offers an attractive alternative site for xenotransplantation approaches. These findings may have important implications for improving the outcome and the monitoring of pig islet xenotransplantation. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cameron, Maria K., E-mail: cameron@math.umd.edu

We develop computational tools for spectral analysis of stochastic networks representing energy landscapes of atomic and molecular clusters. Physical meaning and some properties of eigenvalues, left and right eigenvectors, and eigencurrents are discussed. We propose an approach to compute a collection of eigenpairs and corresponding eigencurrents describing the most important relaxation processes taking place in the system on its way to the equilibrium. It is suitable for large and complex stochastic networks where pairwise transition rates, given by the Arrhenius law, vary by orders of magnitude. The proposed methodology is applied to the network representing the Lennard-Jones-38 cluster created bymore » Wales's group. Its energy landscape has a double funnel structure with a deep and narrow face-centered cubic funnel and a shallower and wider icosahedral funnel. However, the complete spectrum of the generator matrix of the Lennard-Jones-38 network has no appreciable spectral gap separating the eigenvalue corresponding to the escape from the icosahedral funnel. We provide a detailed description of the escape process from the icosahedral funnel using the eigencurrent and demonstrate a superexponential growth of the corresponding eigenvalue. The proposed spectral approach is compared to the methodology of the Transition Path Theory. Finally, we discuss whether the Lennard-Jones-38 cluster is metastable from the points of view of a mathematician and a chemical physicist, and make a connection with experimental works.« less

Pore-scale micro-computed-tomography imaging: Nonwetting-phase cluster-size distribution during drainage and imbibition

NASA Astrophysics Data System (ADS)

Georgiadis, A.; Berg, S.; Makurat, A.; Maitland, G.; Ott, H.

2013-09-01

We investigated the cluster-size distribution of the residual nonwetting phase in a sintered glass-bead porous medium at two-phase flow conditions, by means of micro-computed-tomography (μCT) imaging with pore-scale resolution. Cluster-size distribution functions and cluster volumes were obtained by image analysis for a range of injected pore volumes under both imbibition and drainage conditions; the field of view was larger than the porosity-based representative elementary volume (REV). We did not attempt to make a definition for a two-phase REV but used the nonwetting-phase cluster-size distribution as an indicator. Most of the nonwetting-phase total volume was found to be contained in clusters that were one to two orders of magnitude larger than the porosity-based REV. The largest observed clusters in fact ranged in volume from 65% to 99% of the entire nonwetting phase in the field of view. As a consequence, the largest clusters observed were statistically not represented and were found to be smaller than the estimated maximum cluster length. The results indicate that the two-phase REV is larger than the field of view attainable by μCT scanning, at a resolution which allows for the accurate determination of cluster connectivity.

Work stress and mental health in a changing society.

PubMed

Kopp, Maria S; Stauder, Adrienne; Purebl, György; Janszky, Imre; Skrabski, Arpád

2008-06-01

The aim of this representative study in the Hungarian population was to analyse the association between work-related factors and self-reported mental and physical health after controlling for negative affect and hostility as personality traits. The effects of job related factors on Beck Depression Score, WHO well-being score and self-rated health (SRH) were analysed in a representative sample of 3153 male and 2710 female economically active Hungarians. In both genders negative affect was the most important correlate of depression, well-being and SRH, whereas hostility was closely associated only with depression. Job insecurity, low control and low social support at work, weekend work hours, job-related life events and dissatisfaction with work and with boss were independent mental health risk factors, but there were important gender differences. Job related factors seem to be equally important predictors of mental health as social support from family. The results of this large national representative study indicate that independent of negative affect and hostility, a cluster of stressful work-related psychosocial conditions accounts for a substantial part of variation in self-reported mental and physical health of the economically active population in Hungary.

Cluster Interest Inventory.

ERIC Educational Resources Information Center

Herzog, Douglas

The Cluster Interest Inventory is designed to familiarize students with representative occupations in 13 career clusters: (1) agribusiness and natural resources, (2) business marketing, and office occupations, (3) communications and media, (4) consumer and homemaker, (5) fine arts and humanities, (6) health, (7) manufacturing and processing, (8)…

Identifying clusters of falls-related hospital admissions to inform population targets for prioritising falls prevention programmes

PubMed Central

Finch, Caroline F; Stephan, Karen; Shee, Anna Wong; Hill, Keith; Haines, Terry P; Clemson, Lindy; Day, Lesley

2015-01-01

Background There has been limited research investigating the relationship between injurious falls and hospital resource use. The aims of this study were to identify clusters of community-dwelling older people in the general population who are at increased risk of being admitted to hospital following a fall and how those clusters differed in their use of hospital resources. Methods Analysis of routinely collected hospital admissions data relating to 45 374 fall-related admissions in Victorian community-dwelling older adults aged ≥65 years that occurred during 2008/2009 to 2010/2011. Fall-related admission episodes were identified based on being admitted from a private residence to hospital with a principal diagnosis of injury (International Classification of Diseases (ICD)-10-AM codes S00 to T75) and having a first external cause of a fall (ICD-10-AM codes W00 to W19). A cluster analysis was performed to identify homogeneous groups using demographic details of patients and information on the presence of comorbidities. Hospital length of stay (LOS) was compared across clusters using competing risks regression. Results Clusters based on area of residence, demographic factors (age, gender, marital status, country of birth) and the presence of comorbidities were identified. Clusters representing hospitalised fallers with comorbidities were associated with longer LOS compared with other cluster groups. Clusters delineated by demographic factors were also associated with increased LOS. Conclusions All patients with comorbidity, and older women without comorbidities, stay in hospital longer following a fall and hence consume a disproportionate share of hospital resources. These findings have important implications for the targeting of falls prevention interventions for community-dwelling older people. PMID:25618735

Multi-temporal clustering of continental floods and associated atmospheric circulations

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Yongqiang

2017-12-01

Investigating clustering of floods has important social, economic and ecological implications. This study examines the clustering of Australian floods at different temporal scales and its possible physical mechanisms. Flood series with different severities are obtained by peaks-over-threshold (POT) sampling in four flood thresholds. At intra-annual scale, Cox regression and monthly frequency methods are used to examine whether and when the flood clustering exists, respectively. At inter-annual scale, dispersion indices with four-time variation windows are applied to investigate the inter-annual flood clustering and its variation. Furthermore, the Kernel occurrence rate estimate and bootstrap resampling methods are used to identify flood-rich/flood-poor periods. Finally, seasonal variation of horizontal wind at 850 hPa and vertical wind velocity at 500 hPa are used to investigate the possible mechanisms causing the temporal flood clustering. Our results show that: (1) flood occurrences exhibit clustering at intra-annual scale, which are regulated by climate indices representing the impacts of the Pacific and Indian Oceans; (2) the flood-rich months occur from January to March over northern Australia, and from July to September over southwestern and southeastern Australia; (3) stronger inter-annual clustering takes place across southern Australia than northern Australia; and (4) Australian floods are characterised by regional flood-rich and flood-poor periods, with 1987-1992 identified as the flood-rich period across southern Australia, but the flood-poor period across northern Australia, and 2001-2006 being the flood-poor period across most regions of Australia. The intra-annual and inter-annual clustering and temporal variation of flood occurrences are in accordance with the variation of atmospheric circulation. These results provide relevant information for flood management under the influence of climate variability, and, therefore, are helpful for developing flood hazard mitigation schemes.

The Atacama Cosmology Telescope: Physical Properties and Purity of a Galaxy Cluster Sample Selected Via the Sunyaev-Zel'Dovich Effect

NASA Technical Reports Server (NTRS)

Menanteau, Felipe; Gonzalez, Jorge; Juin, Jean-Baptiste; Marriage, Tobias; Reese, Erik D.; Acquaviva, Viviana; Aguirre, Paula; Appel, John Willam; Baker, Andrew J.; Barrientos, L. Felipe;

The Nature of LSB galaxies revealed by their Globular Clusters

NASA Astrophysics Data System (ADS)

Kissler-Patig, Markus

2005-07-01

Low Surface Brightness {LSB} galaxies encompass many of the extremes in galaxy properties. Their understanding is essential to complete our picture of galaxy formation and evolution. Due to their historical under-representation on galaxy surveys, their importance to many areas of astronomy has only recently began to be realized. Globular clusters are superb tracers of the formation histories of galaxies and have been extensively used as such in high surface brightness galaxies. We propose to investigate the nature of massive LSB galaxies by studying their globular cluster systems. No globular cluster study has been reported for LSB galaxies to date. Yet, both the presence or absence of globular clusters set very strong constraints on the conditions prevailing during LSB galaxy formation and evolution. Both in dwarf and giant high surface brightness {HSB} galaxies, globular clusters are known to form as a constant fraction of baryonic mass. Their presence/absence immediately indicates similarities or discrepancies in the formation and evolution conditions of LSB and HSB galaxies. In particular, the presence/absence of metal-poor halo globular clusters infers similarities/differences in the halo formation and assembly processes of LSB vs. HSB galaxies, while the presence/absence of metal-rich globular clusters can be used to derive the occurrence and frequency of violent events {such as mergers} in the LSB galaxy assembly history. Two band imaging with ACS will allow us to identify the globular clusters {just resolved at the selected distance} and to determine their metallicity {potentially their rough age}. The composition of the systems will be compared to the extensive census built up on HSB galaxies. Our representative sample of six LSB galaxies {cz < 2700 km/s} are selected such, that a large system of globular clusters is expected. Globular clusters will constrain phases of LSB galaxy formation and evolution that can currently not be probed by other means. HST/ACS imaging is the only facility capable of studying the globular cluster systems of LSB galaxies given their distance and relative scarcity.

Load Weight Classification of The Quayside Container Crane Based On K-Means Clustering Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Bingqian; Hu, Xiong; Tang, Gang; Wang, Yide

2017-07-01

The precise knowledge of the load weight of each operation of the quayside container crane is important for accurately assessing the service life of the crane. The load weight is directly related to the vibration intensity. Through the study on the vibration of the hoist motor of the crane in radial and axial directions, we can classify the load using K-means clustering algorithm and quantitative statistical analysis. Vibration in radial direction is significantly and positively correlated with that in axial direction by correlation analysis, which means that we can use the data only in one of the directions to carry out the study improving then the efficiency without degrading the accuracy of load classification. The proposed method can well represent the real-time working condition of the crane.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

Evolutionary analysis of groundwater flow: Application of multivariate statistical analysis to hydrochemical data in the Densu Basin, Ghana

NASA Astrophysics Data System (ADS)

Yidana, Sandow Mark; Bawoyobie, Patrick; Sakyi, Patrick; Fynn, Obed Fiifi

2018-02-01

An evolutionary trend has been postulated through the analysis of hydrochemical data of a crystalline rock aquifer system in the Densu Basin, Southern Ghana. Hydrochemcial data from 63 groundwater samples, taken from two main groundwater outlets (Boreholes and hand dug wells) were used to postulate an evolutionary theory for the basin. Sequential factor and hierarchical cluster analysis were used to disintegrate the data into three factors and five clusters (spatial associations). These were used to characterize the controls on groundwater hydrochemistry and its evolution in the terrain. The dissolution of soluble salts and cation exchange processes are the dominant processes controlling groundwater hydrochemistry in the terrain. The trend of evolution of this set of processes follows the pattern of groundwater flow predicted by a calibrated transient groundwater model in the area. The data suggest that anthropogenic activities represent the second most important process in the hydrochemistry. Silicate mineral weathering is the third most important set of processes. Groundwater associations resulting from Q-mode hierarchical cluster analysis indicate an evolutionary pattern consistent with the general groundwater flow pattern in the basin. These key findings are at variance with results of previous investigations and indicate that when carefully done, groundwater hydrochemical data can be very useful for conceptualizing groundwater flow in basins.

Identifying multi-level culturally appropriate smoking cessation strategies for Aboriginal health staff: a concept mapping approach.

PubMed

Dawson, Anna P; Cargo, Margaret; Stewart, Harold; Chong, Alwin; Daniel, Mark

2013-02-01

Aboriginal Australians, including Aboriginal Health Workers (AHWs), smoke at rates double the non-Aboriginal population. This study utilized concept mapping methodology to identify and prioritize culturally relevant strategies to promote smoking cessation in AHWs. Stakeholder participants included AHWs, other health service employees and tobacco control personnel. Smoking cessation strategies (n = 74) were brainstormed using 34 interviews, 3 focus groups and a stakeholder workshop. Stakeholders sorted strategies into meaningful groups and rated them on perceived importance and feasibility. A concept map was developed using multi-dimensional scaling and hierarchical cluster analyses. Ten unique clusters of smoking cessation strategies were depicted that targeted individuals, family and peers, community, workplace and public policy. Smoking cessation resources and services were represented in addition to broader strategies addressing social and environmental stressors that perpetuate smoking and make quitting difficult. The perceived importance and feasibility of clusters were rated differently by participants working in health services that were government-coordinated compared with community-controlled. For health service workers within vulnerable populations, these findings clearly implicate a need for contextualized strategies that mitigate social and environmental stressors in addition to conventional strategies for tobacco control. The concept map is being applied in knowledge translation to guide development of smoking cessation programs for AHWs.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Variability in body size and shape of UK offshore workers: A cluster analysis approach.

PubMed

Stewart, Arthur; Ledingham, Robert; Williams, Hector

2017-01-01

Male UK offshore workers have enlarged dimensions compared with UK norms and knowledge of specific sizes and shapes typifying their physiques will assist a range of functions related to health and ergonomics. A representative sample of the UK offshore workforce (n = 588) underwent 3D photonic scanning, from which 19 extracted dimensional measures were used in k-means cluster analysis to characterise physique groups. Of the 11 resulting clusters four somatotype groups were expressed: one cluster was muscular and lean, four had greater muscularity than adiposity, three had equal adiposity and muscularity and three had greater adiposity than muscularity. Some clusters appeared constitutionally similar to others, differing only in absolute size. These cluster centroids represent an evidence-base for future designs in apparel and other applications where body size and proportions affect functional performance. They also constitute phenotypic evidence providing insight into the 'offshore culture' which may underpin the enlarged dimensions of offshore workers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular Subtyping to Detect Human Listeriosis Clusters

PubMed Central

Sauders, Brian D.; Fortes, Esther D.; Morse, Dale L.; Dumas, Nellie; Kiehlbauch, Julia A.; Schukken, Ynte; Hibbs, Jonathan R.

2003-01-01

We analyzed the diversity (Simpson’s Index, D) and distribution of Listeria monocytogenes in human listeriosis cases in New York State (excluding New York City) from November 1996 to June 2000 by using automated ribotyping and pulsed-field gel electrophoresis (PFGE). We applied a scan statistic (p<0.05) to detect listeriosis clusters caused by a specific Listeria monocytogenes subtype. Of 131 human isolates, 34 (D=0.923) ribotypes and 74 (D=0.975) PFGE types were found. Nine (31% of cases) clusters were identified by ribotype or PFGE; five (18% of cases) clusters were identified by using both methods. Two of the nine clusters (13% of cases) identified corresponded with investigated multistate listeriosis outbreaks. While most human listeriosis cases are considered sporadic, highly discriminatory molecular subtyping approaches thus indicated that 13% to 31% of cases reported in New York State may represent single-source clusters. Listeriosis control and reduction efforts should include broad-based subtyping of human isolates and consider that a large number of cases may represent outbreaks. PMID:12781006

Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

PubMed

Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

2009-02-01

Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

Oxygen Vacancy Linear Clustering in a Perovskite Oxide

DOE PAGES

Eom, Kitae; Choi, Euiyoung; Choi, Minsu; ...

2017-07-14

Oxygen vacancies have been implicitly assumed isolated ones, and understanding oxide materials possibly containing oxygen vacancies remains elusive within the scheme of the isolated vacancies, although the oxygen vacancies have been playing a decisive role in oxide materials. We report the presence of oxygen vacancy linear clusters and their orientation along a specific crystallographic direction in SrTiO 3, a representative of a perovskite oxide. The presence of the linear clusters and associated electron localization was revealed by an electronic structure represented in the increase in the Ti 2+ valence state or corresponding Ti 3d 2 electronic configuration along with divacancymore » cluster model analysis and transport measurement. The orientation of the linear clusters along the [001] direction in perovskite SrTiO 3 was verified by further X-ray diffuse scattering analysis. And because SrTiO 3 is an archetypical perovskite oxide, the vacancy linear clustering with the specific aligned direction and electron localization can be extended to a wide variety of the perovskite oxides.« less

Oxygen Vacancy Linear Clustering in a Perovskite Oxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eom, Kitae; Choi, Euiyoung; Choi, Minsu

Oxygen vacancies have been implicitly assumed isolated ones, and understanding oxide materials possibly containing oxygen vacancies remains elusive within the scheme of the isolated vacancies, although the oxygen vacancies have been playing a decisive role in oxide materials. We report the presence of oxygen vacancy linear clusters and their orientation along a specific crystallographic direction in SrTiO 3, a representative of a perovskite oxide. The presence of the linear clusters and associated electron localization was revealed by an electronic structure represented in the increase in the Ti 2+ valence state or corresponding Ti 3d 2 electronic configuration along with divacancymore » cluster model analysis and transport measurement. The orientation of the linear clusters along the [001] direction in perovskite SrTiO 3 was verified by further X-ray diffuse scattering analysis. And because SrTiO 3 is an archetypical perovskite oxide, the vacancy linear clustering with the specific aligned direction and electron localization can be extended to a wide variety of the perovskite oxides.« less

Spectral gene set enrichment (SGSE).

PubMed

Frost, H Robert; Li, Zhigang; Moore, Jason H

2015-03-03

Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes the statistical association between gene sets and principal components (PCs) using our principal component gene set enrichment (PCGSE) method. The overall statistical association between each gene set and the spectral structure of the data is then computed by combining the PC-level p-values using the weighted Z-method with weights set to the PC variance scaled by Tracy-Widom test p-values. Using simulated data, we show that the SGSE algorithm can accurately recover spectral features from noisy data. To illustrate the utility of our method on real data, we demonstrate the superior performance of the SGSE method relative to standard cluster-based techniques for testing the association between MSigDB gene sets and the variance structure of microarray gene expression data. Unsupervised gene set testing can provide important information about the biological signal held in high-dimensional genomic data sets. Because it uses the association between gene sets and samples PCs to generate a measure of unsupervised enrichment, the SGSE method is independent of cluster or network creation algorithms and, most importantly, is able to utilize the statistical significance of PC eigenvalues to ignore elements of the data most likely to represent noise.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

The adiposity of children is associated with their lifestyle behaviours: a cluster analysis of school-aged children from 12 nations.

PubMed

Dumuid, Dorothea; Olds, T; Lewis, L K; Martin-Fernández, J A; Barreira, T; Broyles, S; Chaput, J-P; Fogelholm, M; Hu, G; Kuriyan, R; Kurpad, A; Lambert, E V; Maia, J; Matsudo, V; Onywera, V O; Sarmiento, O L; Standage, M; Tremblay, M S; Tudor-Locke, C; Zhao, P; Katzmarzyk, P; Gillison, F; Maher, C

2018-02-01

The relationship between children's adiposity and lifestyle behaviour patterns is an area of growing interest. The objectives of this study are to identify clusters of children based on lifestyle behaviours and compare children's adiposity among clusters. Cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment were used. the participants were children (9-11 years) from 12 nations (n = 5710). 24-h accelerometry and self-reported diet and screen time were clustering input variables. Objectively measured adiposity indicators were waist-to-height ratio, percent body fat and body mass index z-scores. sex-stratified analyses were performed on the global sample and repeated on a site-wise basis. Cluster analysis (using isometric log ratios for compositional data) was used to identify common lifestyle behaviour patterns. Site representation and adiposity were compared across clusters using linear models. Four clusters emerged: (1) Junk Food Screenies, (2) Actives, (3) Sitters and (4) All-Rounders. Countries were represented differently among clusters. Chinese children were over-represented in Sitters and Colombian children in Actives. Adiposity varied across clusters, being highest in Sitters and lowest in Actives. Children from different sites clustered into groups of similar lifestyle behaviours. Cluster membership was linked with differing adiposity. Findings support the implementation of activity interventions in all countries, targeting both physical activity and sedentary time. © 2016 World Obesity Federation.

iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure.

PubMed

Limpiti, Tulaya; Amornbunchornvej, Chainarong; Intarapanich, Apichart; Assawamakin, Anunchai; Tongsima, Sissades

2014-01-01

Understanding genetic differences among populations is one of the most important issues in population genetics. Genetic variations, e.g., single nucleotide polymorphisms, are used to characterize commonality and difference of individuals from various populations. This paper presents an efficient graph-based clustering framework which operates iteratively on the Neighbor-Joining (NJ) tree called the iNJclust algorithm. The framework uses well-known genetic measurements, namely the allele-sharing distance, the neighbor-joining tree, and the fixation index. The behavior of the fixation index is utilized in the algorithm's stopping criterion. The algorithm provides an estimated number of populations, individual assignments, and relationships between populations as outputs. The clustering result is reported in the form of a binary tree, whose terminal nodes represent the final inferred populations and the tree structure preserves the genetic relationships among them. The clustering performance and the robustness of the proposed algorithm are tested extensively using simulated and real data sets from bovine, sheep, and human populations. The result indicates that the number of populations within each data set is reasonably estimated, the individual assignment is robust, and the structure of the inferred population tree corresponds to the intrinsic relationships among populations within the data.

Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003

NASA Astrophysics Data System (ADS)

Di Salvo, Roberto; Montalto, Placido; Nunnari, Giuseppe; Neri, Marco; Puglisi, Giuseppe

2013-02-01

Time series clustering is an important task in data analysis issues in order to extract implicit, previously unknown, and potentially useful information from a large collection of data. Finding useful similar trends in multivariate time series represents a challenge in several areas including geophysics environment research. While traditional time series analysis methods deal only with univariate time series, multivariate time series analysis is a more suitable approach in the field of research where different kinds of data are available. Moreover, the conventional time series clustering techniques do not provide desired results for geophysical datasets due to the huge amount of data whose sampling rate is different according to the nature of signal. In this paper, a novel approach concerning geophysical multivariate time series clustering is proposed using dynamic time series segmentation and Self Organizing Maps techniques. This method allows finding coupling among trends of different geophysical data recorded from monitoring networks at Mt. Etna spanning from 1996 to 2003, when the transition from summit eruptions to flank eruptions occurred. This information can be used to carry out a more careful evaluation of the state of volcano and to define potential hazard assessment at Mt. Etna.

Mapping Perceptions of Lupus Medication Decision-Making Facilitators: The Importance of Patient Context.

PubMed

Qu, Haiyan; Shewchuk, Richard M; Alarcón, Graciela; Fraenkel, Liana; Leong, Amye; Dall'Era, Maria; Yazdany, Jinoos; Singh, Jasvinder A

2016-12-01

Numerous factors can impede or facilitate patients' medication decision-making and adherence to physicians' recommendations. Little is known about how patients and physicians jointly view issues that affect the decision-making process. Our objective was to derive an empirical framework of patient-identified facilitators to lupus medication decision-making from key stakeholders (including 15 physicians, 5 patients/patient advocates, and 8 medical professionals) using a patient-centered cognitive mapping approach. We used nominal group patient panels to identify facilitators to lupus treatment decision-making. Stakeholders independently sorted the identified facilitators (n = 98) based on their similarities and rated the importance of each facilitator in patient decision-making. Data were analyzed using multidimensional scaling and hierarchical cluster analysis. A cognitive map was derived that represents an empirical framework of facilitators for lupus treatment decisions from multiple stakeholders' perspectives. The facilitator clusters were 1) hope for a normal/healthy life, 2) understand benefits and effectiveness of taking medications, 3) desire to minimize side effects, 4) medication-related data, 5) medication effectiveness for "me," 6) family focus, 7) confidence in physician, 8) medication research, 9) reassurance about medication, and 10) medication economics. Consideration of how different stakeholders perceive the relative importance of lupus medication decision-making clusters is an important step toward improving patient-physician communication and effective shared decision-making. The empirically derived framework of medication decision-making facilitators can be used as a guide to develop a lupus decision aid that focuses on improving physician-patient communication. © 2016, American College of Rheumatology.

Coresets vs clustering: comparison of methods for redundancy reduction in very large white matter fiber sets

NASA Astrophysics Data System (ADS)

Alexandroni, Guy; Zimmerman Moreno, Gali; Sochen, Nir; Greenspan, Hayit

2016-03-01

Recent advances in Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) of white matter in conjunction with improved tractography produce impressive reconstructions of White Matter (WM) pathways. These pathways (fiber sets) often contain hundreds of thousands of fibers, or more. In order to make fiber based analysis more practical, the fiber set needs to be preprocessed to eliminate redundancies and to keep only essential representative fibers. In this paper we demonstrate and compare two distinctive frameworks for selecting this reduced set of fibers. The first framework entails pre-clustering the fibers using k-means, followed by Hierarchical Clustering and replacing each cluster with one representative. For the second clustering stage seven distance metrics were evaluated. The second framework is based on an efficient geometric approximation paradigm named coresets. Coresets present a new approach to optimization and have huge success especially in tasks requiring large computation time and/or memory. We propose a modified version of the coresets algorithm, Density Coreset. It is used for extracting the main fibers from dense datasets, leaving a small set that represents the main structures and connectivity of the brain. A novel approach, based on a 3D indicator structure, is used for comparing the frameworks. This comparison was applied to High Angular Resolution Diffusion Imaging (HARDI) scans of 4 healthy individuals. We show that among the clustering based methods, that cosine distance gives the best performance. In comparing the clustering schemes with coresets, Density Coreset method achieves the best performance.

Active Learning Using Hint Information.

PubMed

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

What is needed to implement a computer-assisted health risk assessment tool? An exploratory concept mapping study.

PubMed

Ahmad, Farah; Norman, Cameron; O'Campo, Patricia

2012-12-19

Emerging eHealth tools could facilitate the delivery of comprehensive care in time-constrained clinical settings. One such tool is interactive computer-assisted health-risk assessments (HRA), which may improve provider-patient communication at the point of care, particularly for psychosocial health concerns, which remain under-detected in clinical encounters. The research team explored the perspectives of healthcare providers representing a variety of disciplines (physicians, nurses, social workers, allied staff) regarding the factors required for implementation of an interactive HRA on psychosocial health. The research team employed a semi-qualitative participatory method known as Concept Mapping, which involved three distinct phases. First, in face-to-face and online brainstorming sessions, participants responded to an open-ended central question: "What factors should be in place within your clinical setting to support an effective computer-assisted screening tool for psychosocial risks?" The brainstormed items were consolidated by the research team. Then, in face-to-face and online sorting sessions, participants grouped the items thematically as 'it made sense to them'. Participants also rated each item on a 5-point scale for its 'importance' and 'action feasibility' over the ensuing six month period. The sorted and rated data was analyzed using multidimensional scaling and hierarchical cluster analyses which produced visual maps. In the third and final phase, the face-to-face Interpretation sessions, the concept maps were discussed and illuminated by participants collectively. Overall, 54 providers participated (emergency care 48%; primary care 52%). Participants brainstormed 196 items thought to be necessary for the implementation of an interactive HRA emphasizing psychosocial health. These were consolidated by the research team into 85 items. After sorting and rating, cluster analysis revealed a concept map with a seven-cluster solution: 1) the HRA's equitable availability; 2) the HRA's ease of use and appropriateness; 3) the content of the HRA survey; 4) patient confidentiality and choice; 5) patient comfort through humanistic touch; 6) professional development, care and workload; and 7) clinical management protocol. Drawing insight from the theoretical lens of Sociotechnical theory, the seven clusters of factors required for HRA implementation could be read as belonging to three overarching aspects : Technical (cluster 1, 2 and 3), Social-Patient (cluster 4 and 5), and Social-Provider (cluster 6 and 7). Participants rated every one of the clusters as important, with mean scores from 4.0 to 4.5. Their scores for feasibility were somewhat lower, ranging from 3.4 to. 4.3. Comparing the scores for importance and feasibility, a significant difference was found for one cluster from each region (cluster 2, 5, 6). The cluster on professional development, care and workload was perceived as especially challenging in emergency department settings, and possible reasons were discussed in the interpretation sessions. A number of intertwined multilevel factors emerged as important for the implementation of a computer-assisted, interactive HRA with a focus on psychosocial health. Future developments in this area could benefit from systems thinking and insights from theoretical perspectives, such as sociotechnical system theory for joint optimization and responsible autonomy, with emphasis on both the technical and social aspects of HRA implementation.

An efficient and scalable graph modeling approach for capturing information at different levels in next generation sequencing reads

PubMed Central

2013-01-01

Background Next generation sequencing technologies have greatly advanced many research areas of the biomedical sciences through their capability to generate massive amounts of genetic information at unprecedented rates. The advent of next generation sequencing has led to the development of numerous computational tools to analyze and assemble the millions to billions of short sequencing reads produced by these technologies. While these tools filled an important gap, current approaches for storing, processing, and analyzing short read datasets generally have remained simple and lack the complexity needed to efficiently model the produced reads and assemble them correctly. Results Previously, we presented an overlap graph coarsening scheme for modeling read overlap relationships on multiple levels. Most current read assembly and analysis approaches use a single graph or set of clusters to represent the relationships among a read dataset. Instead, we use a series of graphs to represent the reads and their overlap relationships across a spectrum of information granularity. At each information level our algorithm is capable of generating clusters of reads from the reduced graph, forming an integrated graph modeling and clustering approach for read analysis and assembly. Previously we applied our algorithm to simulated and real 454 datasets to assess its ability to efficiently model and cluster next generation sequencing data. In this paper we extend our algorithm to large simulated and real Illumina datasets to demonstrate that our algorithm is practical for both sequencing technologies. Conclusions Our overlap graph theoretic algorithm is able to model next generation sequencing reads at various levels of granularity through the process of graph coarsening. Additionally, our model allows for efficient representation of the read overlap relationships, is scalable for large datasets, and is practical for both Illumina and 454 sequencing technologies. PMID:24564333

Non-Small-Cell Lung Cancer Molecular Signatures Recapitulate Lung Developmental Pathways

PubMed Central

Borczuk, Alain C.; Gorenstein, Lyall; Walter, Kristin L.; Assaad, Adel A.; Wang, Liqun; Powell, Charles A.

2003-01-01

Current paradigms hold that lung carcinomas arise from pleuripotent stem cells capable of differentiation into one or several histological types. These paradigms suggest lung tumor cell ontogeny is determined by consequences of gene expression that recapitulate events important in embryonic lung development. Using oligonucleotide microarrays, we acquired gene profiles from 32 microdissected non-small-cell lung tumors. We determined the 100 top-ranked marker genes for adenocarcinoma, squamous cell, large cell, and carcinoid using nearest neighbor analysis. Results were validated by immunostaining for 11 selected proteins using a tissue microarray representing 80 tumors. Gene expression data of lung development were accessed from a publicly available dataset generated with the murine Mu11k genome microarray. Self-organized mapping identified two temporally distinct clusters of murine orthologues. Supervised clustering of lung development data showed large-cell carcinoma gene orthologues were in a cluster expressed in pseudoglandular and canalicular stages whereas adenocarcinoma homologues were predominantly in a cluster expressed later in the terminal sac and alveolar stages of murine lung development. Representative large-cell genes (E2F3, MYBL2, HDAC2, CDK4, PCNA) are expressed in the nucleus and are associated with cell cycle and proliferation. In contrast, adenocarcinoma genes are associated with lung-specific transcription pathways (SFTPB, TTF-1), cell adhesion, and signal transduction. In sum, non-small-cell lung tumors histology gene profiles suggest mechanisms relevant to ontogeny and clinical course. Adenocarcinoma genes are associated with differentiation and glandular formation whereas large-cell genes are associated with proliferation and differentiation arrest. The identification of developmentally regulated pathways active in tumorigenesis provides insights into lung carcinogenesis and suggests early steps may differ according to the eventual tumor morphology. PMID:14578194

Measuring the Mass Distribution in Z is Approximately 0.2 Cluster Lenses with XMM, HST and CFHT

NASA Technical Reports Server (NTRS)

2004-01-01

Being the most massive gravitationally bound objects in the Universe, clusters of galaxies are prime targets for studies of structure formation and evolution. Specifically the comoving space density of virialized clusters of a given mass (or X-ray temperature), but also the frequency and degree of substructure, as well as the shape of the cluster mass profile are quantities whose current values and evolution as a function of lookback time can provide important constraints on the cosmological and physical parameters of structure formation theories. The project funded by NASA grant NAG 5-10041 intended to take such studies to a new level by combining observations of a well-selected cluster sample by three state-of-the-art telescopes: HST, to accurately measure the mass distribution in the cluster core (approx. 0.5 h(sup -1)(sub 50) Mpc) via strong gravitational lensing; CFHT, to measure the large scale mass distribution out to approx. 3 Mpc via weak lensing; and XMM, to measure the gas density and temperature distribution accurately on intermediate scales < 1.5 Mpc. XMM plays a pivotal role in this context as the calibration of X-ray mass measurements through accurate, spatially resolved X-ray temperature measurements (particularly in the cosmologically most sensitive range of kT> 5 keV) is central to the questions outlined above. This set of observations promised to yield the best cluster mass measurements obtained so far for a representative sample, thus allowing us to: 1) Measure the high-mass end of the local cluster mass function; 2) Test predictions of a universal cluster mass profile; 3) calibrate the mass-temperature and temperature-luminosity relations for clusters and the scatter around these relations, which is vital for studies of cluster evolution using the X-ray temperature and X-ray luminosity functions.

Multiscale visual quality assessment for cluster analysis with self-organizing maps

NASA Astrophysics Data System (ADS)

Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

2011-01-01

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

Text mining to decipher free-response consumer complaints: insights from the NHTSA vehicle owner's complaint database.

PubMed

Ghazizadeh, Mahtab; McDonald, Anthony D; Lee, John D

2014-09-01

This study applies text mining to extract clusters of vehicle problems and associated trends from free-response data in the National Highway Traffic Safety Administration's vehicle owner's complaint database. As the automotive industry adopts new technologies, it is important to systematically assess the effect of these changes on traffic safety. Driving simulators, naturalistic driving data, and crash databases all contribute to a better understanding of how drivers respond to changing vehicle technology, but other approaches, such as automated analysis of incident reports, are needed. Free-response data from incidents representing two severity levels (fatal incidents and incidents involving injury) were analyzed using a text mining approach: latent semantic analysis (LSA). LSA and hierarchical clustering identified clusters of complaints for each severity level, which were compared and analyzed across time. Cluster analysis identified eight clusters of fatal incidents and six clusters of incidents involving injury. Comparisons showed that although the airbag clusters across the two severity levels have the same most frequent terms, the circumstances around the incidents differ. The time trends show clear increases in complaints surrounding the Ford/Firestone tire recall and the Toyota unintended acceleration recall. Increases in complaints may be partially driven by these recall announcements and the associated media attention. Text mining can reveal useful information from free-response databases that would otherwise be prohibitively time-consuming and difficult to summarize manually. Text mining can extend human analysis capabilities for large free-response databases to support earlier detection of problems and more timely safety interventions.

Structural analysis of the PSD-95 cluster by electron tomography and CEMOVIS: a proposal for the application of the genetically encoded metallothionein tag.

PubMed

Hirabayashi, Ai; Fukunaga, Yuko; Miyazawa, Atsuo

2014-06-01

Postsynaptic density-95 (PSD-95) accumulates at excitatory postsynapses and plays important roles in the clustering and anchoring of numerous proteins at the PSD. However, a detailed ultrastructural analysis of clusters exclusively consisting of PSD-95 has never been performed. Here, we employed a genetically encoded tag, three tandem repeats of metallothionein (3MT), to study the structure of PSD-95 clusters in cells by electron tomography and cryo-electron microscopy of vitreous sections. We also performed conventional transmission electron microscopy (TEM). Cultured hippocampal neurons expressing a fusion protein of PSD-95 coupled to 3MT (PDS-95-3MT) were incubated with CdCl2 to result in the formation of Cd-bound PSD-95-3MT. Two types of electron-dense deposits composed of Cd-bound PSD-95-3MT were observed in these cells by TEM, as reported previously. Electron tomography revealed the presence of membrane-shaped structures representing PSD-95 clusters at the PSD and an ellipsoidal structure located in the non-synaptic cytoplasm. By TEM, the PSD-95 clusters appeared to be composed of a number of dense cores. In frozen hydrated sections, these dense cores were also found beneath the postsynaptic membrane. Taken together, our findings suggest that dense cores of PSD-95 aggregate to form the larger clusters present in the PSD and the non-synaptic cytoplasm. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Method of identifying clusters representing statistical dependencies in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

Approach is first to cluster and then to compute spatial boundaries for resulting clusters. Next step is to compute, from set of Monte Carlo samples obtained from scrambled data, estimates of probabilities of obtaining at least as many points within boundaries as were actually observed in original data.

The "p"-Median Model as a Tool for Clustering Psychological Data

ERIC Educational Resources Information Center

Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

2010-01-01

The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada.

PubMed

Poon, Art F Y; Joy, Jeffrey B; Woods, Conan K; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J; Hogg, Robert S; Montaner, Julio S G; Harrigan, P Richard

2015-03-15

The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. We reconstructed molecular phylogenies from 27,296 anonymized bulk HIV pol sequences representing 7747 individuals in BC-about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Emergence of Novel Human Norovirus GII.17 Strains Correlates With Changes in Blockade Antibody Epitopes.

PubMed

Lindesmith, Lisa C; Kocher, Jacob F; Donaldson, Eric F; Debbink, Kari; Mallory, Michael L; Swann, Excel W; Brewer-Jensen, Paul D; Baric, Ralph S

2017-12-05

Human norovirus is a significant public health burden, with >30 genotypes causing endemic levels of disease and strains from the GII.4 genotype causing serial pandemics as the virus evolves new ligand binding and antigenicity features. During 2014-2015, genotype GII.17 cluster IIIb strains emerged as the leading cause of norovirus infection in select global locations. Comparison of capsid sequences indicates that GII.17 is evolving at previously defined GII.4 antibody epitopes. Antigenicity of virus-like particles (VLPs) representative of clusters I, II, and IIIb GII.17 strains were compared by a surrogate neutralization assay based on antibody blockade of ligand binding. Sera from mice immunized with a single GII.17 VLP identified antigenic shifts between each cluster of GII.17 strains. Ligand binding of GII.17 cluster IIIb VLP was blocked only by antisera from mice immunized with cluster IIIb VLPs. Exchange of residues 393-396 from GII.17.2015 into GII.17.1978 ablated ligand binding and altered antigenicity, defining an important varying epitope in GII.17. The capsid sequence changes in GII.17 strains result in loss of blockade antibody binding, indicating that viral evolution, specifically at residues 393-396, may have contributed to the emergence of cluster IIIb strains and the persistence of GII.17 in human populations. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Protonation/reduction dynamics at the [4Fe-4S] cluster of the hydrogen-forming cofactor in [FeFe]-hydrogenases.

PubMed

Senger, Moritz; Mebs, Stefan; Duan, Jifu; Shulenina, Olga; Laun, Konstantin; Kertess, Leonie; Wittkamp, Florian; Apfel, Ulf-Peter; Happe, Thomas; Winkler, Martin; Haumann, Michael; Stripp, Sven T

2018-01-31

The [FeFe]-hydrogenases of bacteria and algae are the most efficient hydrogen conversion catalysts in nature. Their active-site cofactor (H-cluster) comprises a [4Fe-4S] cluster linked to a unique diiron site that binds three carbon monoxide (CO) and two cyanide (CN - ) ligands. Understanding microbial hydrogen conversion requires elucidation of the interplay of proton and electron transfer events at the H-cluster. We performed real-time spectroscopy on [FeFe]-hydrogenase protein films under controlled variation of atmospheric gas composition, sample pH, and reductant concentration. Attenuated total reflection Fourier-transform infrared spectroscopy was used to monitor shifts of the CO/CN - vibrational bands in response to redox and protonation changes. Three different [FeFe]-hydrogenases and several protein and cofactor variants were compared, including element and isotopic exchange studies. A protonated equivalent (HoxH) of the oxidized state (Hox) was found, which preferentially accumulated at acidic pH and under reducing conditions. We show that the one-electron reduced state Hred' represents an intrinsically protonated species. Interestingly, the formation of HoxH and Hred' was independent of the established proton pathway to the diiron site. Quantum chemical calculations of the respective CO/CN - infrared band patterns favored a cysteine ligand of the [4Fe-4S] cluster as the protonation site in HoxH and Hred'. We propose that proton-coupled electron transfer facilitates reduction of the [4Fe-4S] cluster and prevents premature formation of a hydride at the catalytic diiron site. Our findings imply that protonation events both at the [4Fe-4S] cluster and at the diiron site of the H-cluster are important in the hydrogen conversion reaction of [FeFe]-hydrogenases.

New Cepheid variables in the young open clusters Berkeley 51 and Berkeley 55

NASA Astrophysics Data System (ADS)

Lohr, M. E.; Negueruela, I.; Tabernero, H. M.; Clark, J. S.; Lewis, F.; Roche, P.

2018-05-01

As part of a wider investigation of evolved massive stars in Galactic open clusters, we have spectroscopically identified three candidate classical Cepheids in the little-studied clusters Berkeley 51, Berkeley 55 and NGC 6603. Using new multi-epoch photometry, we confirm that Be 51 #162 and Be 55 #107 are bona fide Cepheids, with pulsation periods of 9.83±0.01 d and 5.850±0.005 d respectively, while NGC 6603 star W2249 does not show significant photometric variability. Using the period-luminosity relationship for Cepheid variables, we determine a distance to Be 51 of 5.3^{+1.0}_{-0.8} kpc and an age of 44^{+9}_{-8} Myr, placing it in a sparsely-attested region of the Perseus arm. For Be 55, we find a distance of 2.2±0.3 kpc and age of 63^{+12}_{-11} Myr, locating the cluster in the Local arm. Taken together with our recent discovery of a long-period Cepheid in the starburst cluster VdBH222, these represent an important increase in the number of young, massive Cepheids known in Galactic open clusters. We also consider new Gaia (data release 2) parallaxes and proper motions for members of Be 51 and Be 55; the uncertainties on the parallaxes do not allow us to refine our distance estimates to these clusters, but the well-constrained proper motion measurements furnish further confirmation of cluster membership. However, future final Gaia parallaxes for such objects should provide valuable independent distance measurements, improving the calibration of the period-luminosity relationship, with implications for the distance ladder out to cosmological scales.

Intersection Detection Based on Qualitative Spatial Reasoning on Stopping Point Clusters

NASA Astrophysics Data System (ADS)

Zourlidou, S.; Sester, M.

2016-06-01

The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location - thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster) and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

Familial aggregation of suicide explained by cluster B traits: a three-group family study of suicide controlling for major depressive disorder.

PubMed

McGirr, Alexander; Alda, Martin; Séguin, Monique; Cabot, Sophie; Lesage, Alain; Turecki, Gustavo

2009-10-01

There is substantial evidence suggesting that suicide aggregates in families. However, the extent of overlap between the liability to suicide and psychiatric disorders, particularly major depressive disorder, remains an important issue. Similarly, factors that account for the familial transmission of suicidal behavior remain unclear. Thus, through direct and blind assessment of first-degree relatives, the authors conducted a family study of suicide by examining three proband groups: probands who committed suicide in the context of major depressive disorder, living depressed probands with no history of suicidal behavior, and psychiatrically normal community comparison probands. Participants were 718 first-degree relatives from 120 families: 296 relatives of 51 depressed probands who committed suicide, 185 relatives of 34 nonsuicidal depressed probands, and 237 relatives of 35 community comparison subjects. Psychopathology, suicidal behavior, and behavioral measures were assessed via interviews. The relatives of probands who committed suicide had higher levels of suicidal behavior (10.8%) than the relatives of nonsuicidal depressed probands (6.5%) and community comparison probands (3.4%). Testing cluster B traits as intermediate phenotypes of suicide showed that the relatives of depressed probands who committed suicide had elevated levels of cluster B traits; familial predisposition to suicide was associated with increased levels of cluster B traits; cluster B traits demonstrated familial aggregation and were associated with suicide attempts among relatives; and cluster B traits mediated, at least in part, the relationship between familial predisposition and suicide attempts among relatives. Analyses were repeated for severity of attempts, where cluster B traits also met criteria for endophenotypes of suicide. Familial transmission of suicide and major depression, while partially overlapping, are distinct. Cluster B traits and impulsive-aggressive behavior represent intermediate phenotypes of suicide.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

What is the role and authority of gatekeepers in cluster randomized trials in health research?

PubMed Central

2012-01-01

This article is part of a series of papers examining ethical issues in cluster randomized trials (CRTs) in health research. In the introductory paper in this series, we set out six areas of inquiry that must be addressed if the CRT is to be set on a firm ethical foundation. This paper addresses the sixth of the questions posed, namely, what is the role and authority of gatekeepers in CRTs in health research? ‘Gatekeepers’ are individuals or bodies that represent the interests of cluster members, clusters, or organizations. The need for gatekeepers arose in response to the difficulties in obtaining informed consent because of cluster randomization, cluster-level interventions, and cluster size. In this paper, we call for a more restrictive understanding of the role and authority of gatekeepers. Previous papers in this series have provided solutions to the challenges posed by informed consent in CRTs without the need to invoke gatekeepers. We considered that consent to randomization is not required when cluster members are approached for consent at the earliest opportunity and before any study interventions or data-collection procedures have started. Further, when cluster-level interventions or cluster size means that obtaining informed consent is not possible, a waiver of consent may be appropriate. In this paper, we suggest that the role of gatekeepers in protecting individual interests in CRTs should be limited. Generally, gatekeepers do not have the authority to provide proxy consent for cluster members. When a municipality or other community has a legitimate political authority that is empowered to make such decisions, cluster permission may be appropriate; however, gatekeepers may usefully protect cluster interests in other ways. Cluster consultation may ensure that the CRT addresses local health needs, and is conducted in accord with local values and customs. Gatekeepers may also play an important role in protecting the interests of organizations, such as hospitals, nursing homes, general practices, and schools. In these settings, permission to access the organization relies on resource implications and adherence to institutional policies. PMID:22834691

Geographic Clustering of Cardiometabolic Risk Factors in Metropolitan Centres in France and Australia

PubMed Central

Paquet, Catherine; Chaix, Basile; Howard, Natasha J.; Coffee, Neil T.; Adams, Robert J.; Taylor, Anne W.; Thomas, Frédérique; Daniel, Mark

2016-01-01

Understanding how health outcomes are spatially distributed represents a first step in investigating the scale and nature of environmental influences on health and has important implications for statistical power and analytic efficiency. Using Australian and French cohort data, this study aimed to describe and compare the extent of geographic variation, and the implications for analytic efficiency, across geographic units, countries and a range of cardiometabolic parameters (Body Mass Index (BMI) waist circumference, blood pressure, resting heart rate, triglycerides, cholesterol, glucose, HbA1c). Geographic clustering was assessed using Intra-Class Correlation (ICC) coefficients in biomedical cohorts from Adelaide (Australia, n = 3893) and Paris (France, n = 6430) for eight geographic administrative units. The median ICC was 0.01 suggesting 1% of risk factor variance attributable to variation between geographic units. Clustering differed by cardiometabolic parameters, administrative units and countries and was greatest for BMI and resting heart rate in the French sample, HbA1c in the Australian sample, and for smaller geographic units. Analytic inefficiency due to clustering was greatest for geographic units in which participants were nested in fewer, larger geographic units. Differences observed in geographic clustering across risk factors have implications for choice of geographic unit in sampling and analysis, and highlight potential cross-country differences in the distribution, or role, of environmental features related to cardiometabolic health. PMID:27213423

Whole-genome sequencing of Aspergillus tubingensis G131 and overview of its secondary metabolism potential.

PubMed

Choque, Elodie; Klopp, Christophe; Valiere, Sophie; Raynal, José; Mathieu, Florence

2018-03-15

Black Aspergilli represent one of the most important fungal resources of primary and secondary metabolites for biotechnological industry. Having several black Aspergilli sequenced genomes should allow targeting the production of certain metabolites with bioactive properties. In this study, we report the draft genome of a black Aspergilli, A. tubingensis G131, isolated from a French Mediterranean vineyard. This 35 Mb genome includes 10,994 predicted genes. A genomic-based discovery identifies 80 secondary metabolites biosynthetic gene clusters. Genomic sequences of these clusters were blasted on 3 chosen black Aspergilli genomes: A. tubingensis CBS 134.48, A. niger CBS 513.88 and A. kawachii IFO 4308. This comparison highlights different levels of clusters conservation between the four strains. It also allows identifying seven unique clusters in A. tubingensis G131. Moreover, the putative secondary metabolites clusters for asperazine and naphtho-gamma-pyrones production were proposed based on this genomic analysis. Key biosynthetic genes required for the production of 2 mycotoxins, ochratoxin A and fumonisin, are absent from this draft genome. Even if intergenic sequences of these mycotoxins biosynthetic pathways are present, this could not lead to the production of those mycotoxins by A. tubingensis G131. Functional and bioinformatics analyses of A. tubingensis G131 genome highlight its potential for metabolites production in particular for TAN-1612, asperazine and naphtho-gamma-pyrones presenting antioxidant, anticancer or antibiotic properties.

Heterolobosean amoebae from Arctic and Antarctic extremes: 18 novel strains of Allovahlkampfia, Vahlkampfia and Naegleria.

PubMed

Tyml, Tomáš; Skulinová, Kateřina; Kavan, Jan; Ditrich, Oleg; Kostka, Martin; Dyková, Iva

2016-10-01

The diversity of heterolobosean amoebae, important members of soil, marine and freshwater microeukaryote communities in the temperate zones, is greatly under-explored in high latitudes. To address this imbalance, we studied the diversity of this group of free-living amoebae in the Arctic and the Antarctic using culture dependent methods. Eighteen strain representatives of three heterolobosean genera, Allovahlkampfia Walochnik et Mulec, 2009 (1 strain), Vahlkampfia Chatton et Lalung-Bonnaier, 1912 (2) and Naegleria Alexeieff, 1912 (15) were isolated from 179 samples of wet soil and fresh water with sediments collected in 6 localities. The Allovahkampfia strain is the first representative of the genus from the Antarctic; 14 strains (7 from the Arctic, 7 from the Antarctic) of the highly represented genus Naegleria complete the 'polar' cluster of five Naegleria species previously known from the Arctic and Sub-Antarctic regions, whereas one strain enriches the 'dobsoni' cluster of Naegleria strains of diverse origin. Present isolations of Naegleria polarisDe Jonckheere, 2006 from Svalbard, in the Arctic and Vega Island, in the Antarctic and N. neopolarisDe Jonckheere, 2006 from Svalbard and Greenland in the Arctic, and James Ross Island, the Antarctic demonstrate their bipolar distribution, which in free-living amoebae has so far only been known for Vermistella Morand et Anderson, 2007. Copyright © 2016 Elsevier GmbH. All rights reserved.

Thermal wake/vessel detection technique

DOEpatents

Roskovensky, John K [Albuquerque, NM; Nandy, Prabal [Albuquerque, NM; Post, Brian N [Albuquerque, NM

2012-01-10

A computer-automated method for detecting a vessel in water based on an image of a portion of Earth includes generating a thermal anomaly mask. The thermal anomaly mask flags each pixel of the image initially deemed to be a wake pixel based on a comparison of a thermal value of each pixel against other thermal values of other pixels localized about each pixel. Contiguous pixels flagged by the thermal anomaly mask are grouped into pixel clusters. A shape of each of the pixel clusters is analyzed to determine whether each of the pixel clusters represents a possible vessel detection event. The possible vessel detection events are represented visually within the image.

A Detailed Study of Chemical Enrichment History of Galaxy Clusters out to Virial Radius

NASA Astrophysics Data System (ADS)

Loewenstein, Michael

The origin of the metal enrichment of the intracluster medium (ICM) represents a fundamental problem in extragalactic astrophysics, with implications for our understanding of how stars and galaxies form, the nature of Type Ia supernova (SNIa) progenitors, and the thermal history of the ICM. These heavy elements are ultimately synthesized by supernova (SN) explosions; however, the details of the sites of metal production and mechanisms that transport metals to the ICM remain unclear. To make progress, accurate abundance profiles for multiple elements extending from the cluster core out to the virial radius (r180) are required for a significant cluster sample. We propose an X-ray spectroscopic study of a carefully-chosen sample of archival Suzaku and XMM-Newton observations of 23 clusters: XMM-Newton data probe the cluster temperature and abundances out to (0.5-1)r500, while Suzaku data probe the cluster outskirts. A method devised by our team to utilize all elements with emission lines in the X-ray bandpass to measure the relative contributions of supernova explosions by direct modeling of their X-ray spectra will be applied in order to constrain the demographics of the enriching supernova population. In addition we will conduct a stacking analysis of our already existing Suzaku and XMM-Newton cluster spectra to search for weak emssion lines that are important SN diagnostics, and to look for trends with cluster mass and redshift. The funding we propose here will also support the data analysis of our recent Suzaku observations of the archetypal cluster A3112 (200 ks each on the core and outskirts). Our data analysis, intepreted using theoretical models we have developed, will enable us to constrain the star formation history, SN demographics, and nature of SNIa progenitors associated with galaxy cluster stellar populations - and, hence, directly addresess NASA s Strategic Objective 2.4.2 in Astrophysics that aims to improve the understanding of how the Universe works, and explore how it began and evolved.

Charging and hybridization in the finite cluster model

NASA Technical Reports Server (NTRS)

Bauschlicher, C. W., Jr.; Bagus, P. S.; Nelin, C. J.

1984-01-01

Cluster wavefunctions which have appropriate hybridization and polarization lead to reasonable properties for the interaction of an adsorbate with a solid surface. However, for Al clusters, it was found that the atomic change distribution is not uniform. The finite cluster size leads to changes not representative for an extended system. This effect appears to be dependent on the particular materials being studied; it does not occur in all cases.

A Cluster of Legionella-Associated Pneumonia Cases in a Population of Military Recruits

DTIC Science & Technology

2007-06-01

this cluster may suggest a previously unrecognized suscep- FIG. 1. Phylogenic analysis of the training center strain (represented by the MCRD consensus...military recruits during population- based surveillance for pneumonia pathogens. Results were confirmed by sequence analysis . Cases cluster tightly...17 April 2007 A Legionella cluster was identified through retrospective PCR analysis of 240 throat swab samples from X-ray-confirmed pneumonia cases

Structure of clusters and building blocks in amylopectin from African rice accessions.

PubMed

Gayin, Joseph; Abdel-Aal, El-Sayed M; Marcone, Massimo; Manful, John; Bertoft, Eric

2016-09-05

Enzymatic hydrolysis in combination with gel-permeation and anion-exchange chromatography techniques were employed to characterise the composition of clusters and building blocks of amylopectin from two African rice (Oryza glaberrima) accessions-IRGC 103759 and TOG 12440. The samples were compared with one Asian rice (Oryza sativa) sample (cv WITA 4) and one O. sativa×O. glaberrima cross (NERICA 4). The average DP of clusters from the African rice accessions (ARAs) was marginally larger (DP=83) than in WITA 4 (DP=81). However, regarding average number of chains, clusters from the ARAs represented both the smallest and largest clusters. Overall, the result suggested that the structure of clusters in TOG 12440 was dense with short chains and high degree of branching, whereas the situation was the opposite in NERICA 4. IRGC 103759 and WITA 4 possessed clusters with intermediate characteristics. The commonest type of building blocks in all samples was group 2 (single branched dextrins) representing 40.3-49.4% of the blocks, while groups 3-6 were found in successively lower numbers. The average number of building blocks in the clusters was significantly larger in NERICA 4 (5.8) and WITA 4 (5.7) than in IRGC 103759 and TOG 12440 (5.1 and 5.3, respectively). Copyright © 2016 Elsevier Ltd. All rights reserved.

Cluster compression algorithm: A joint clustering/data compression concept

NASA Technical Reports Server (NTRS)

Hilbert, E. E.

1977-01-01

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Messier 35 (NGC 2168) DANCe. I. Membership, proper motions, and multiwavelength photometry

NASA Astrophysics Data System (ADS)

Bouy, H.; Bertin, E.; Barrado, D.; Sarro, L. M.; Olivares, J.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Ribas, Á.; Beletsky, Y.

2015-03-01

Context. Messier 35 (NGC 2168) is an important young nearby cluster. Its age, richness and relative proximity make it an ideal target for stellar evolution studies. The Kepler K2 mission recently observed it and provided a high accuracy photometric time series of a large number of sources in this area of the sky. Identifying the cluster's members is therefore of high importance to optimize the interpretation and analysis of the Kepler K2 data. Aims: We aim to identify the cluster's members by deriving membership probabilities for the sources within 1° of the cluster's center, which is farther away than equivalent previous studies. Methods: We measure accurate proper motions and multiwavelength (optical and near-infrared) photometry using ground-based archival images of the cluster. We use these measurements to compute membership probabilities. The list of candidate members from the literature is used as a training set to identify the cluster's locus in a multidimensional space made of proper motions, luminosities, and colors. Results: The final catalog includes 338 892 sources with multiwavelength photometry. Approximately half (194 452) were detected at more than two epochs and we measured their proper motion and used it to derive membership probability. A total of 4349 candidate members with membership probabilities greater than 50% are found in this sample in the luminosity range between 10 mag and 22 mag. The slow proper motion of the cluster and the overlap of its sequence with the field and background sequences in almost all color-magnitude and color-color diagrams complicate the analysis and the contamination level is expected to be significant. Our study, nevertheless, provides a coherent and quantitative membership analysis of Messier 35 based on a large fraction of the best ground-based data sets obtained over the past 18 years. As such, it represents a valuable input for follow-up studies using, in particular, the Kepler K2 photometric time series. Table 3 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/575/A120

Clustering of GPS velocities in the Mojave Block, southeastern California

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

We find subdivisions within the Mojave Block using cluster analysis to identify groupings in the velocities observed at GPS stations there. The clusters are represented on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. The most significant representation as judged by the gap test involves 4 clusters within the Mojave Block. The fault systems bounding the clusters from east to west are 1) the faults defining the eastern boundary of the Northeast Mojave Domain extended southward to connect to the Hector Mine rupture, 2) the Calico-Paradise fault system, 3) the Landers-Blackwater fault system, and 4) the Helendale-Lockhart fault system. This division of the Mojave Block is very similar to that proposed by Meade and Hager. However, no cluster boundary coincides with the Garlock Fault, the northern boundary of the Mojave Block. Rather, the clusters appear to continue without interruption from the Mojave Block north into the southern Walker Lane Belt, similar to the continuity across the Garlock Fault of the shear zone along the Blackwater-Little Lake fault system observed by Peltzer et al. Mapped traces of individual faults in the Mojave Block terminate within the block and do not continue across the Garlock Fault [Dokka and Travis, ].

A novel family of sequence-specific endoribonucleases associated with the clustered regularly interspaced short palindromic repeats.

PubMed

Beloglazova, Natalia; Brown, Greg; Zimmerman, Matthew D; Proudfoot, Michael; Makarova, Kira S; Kudritska, Marina; Kochinyan, Samvel; Wang, Shuren; Chruszcz, Maksymilian; Minor, Wladek; Koonin, Eugene V; Edwards, Aled M; Savchenko, Alexei; Yakunin, Alexander F

2008-07-18

Clustered regularly interspaced short palindromic repeats (CRISPRs) together with the associated CAS proteins protect microbial cells from invasion by foreign genetic elements using presently unknown molecular mechanisms. All CRISPR systems contain proteins of the CAS2 family, suggesting that these uncharacterized proteins play a central role in this process. Here we show that the CAS2 proteins represent a novel family of endoribonucleases. Six purified CAS2 proteins from diverse organisms cleaved single-stranded RNAs preferentially within U-rich regions. A representative CAS2 enzyme, SSO1404 from Sulfolobus solfataricus, cleaved the phosphodiester linkage on the 3'-side and generated 5'-phosphate- and 3'-hydroxyl-terminated oligonucleotides. The crystal structure of SSO1404 was solved at 1.6A resolution revealing the first ribonuclease with a ferredoxin-like fold. Mutagenesis of SSO1404 identified six residues (Tyr-9, Asp-10, Arg-17, Arg-19, Arg-31, and Phe-37) that are important for enzymatic activity and suggested that Asp-10 might be the principal catalytic residue. Thus, CAS2 proteins are sequence-specific endoribonucleases, and we propose that their role in the CRISPR-mediated anti-phage defense might involve degradation of phage or cellular mRNAs.

Hydrochemical and multivariate analysis of groundwater quality in the northwest of Sinai, Egypt.

PubMed

El-Shahat, M F; Sadek, M A; Salem, W M; Embaby, A A; Mohamed, F A

2017-08-01

The northwestern coast of Sinai is home to many economic activities and development programs, thus evaluation of the potentiality and vulnerability of water resources is important. The present work has been conducted on the groundwater resources of this area for describing the major features of groundwater quality and the principal factors that control salinity evolution. The major ionic content of 39 groundwater samples collected from the Quaternary aquifer shows high coefficients of variation reflecting asymmetry of aquifer recharge. The groundwater samples have been classified into four clusters (using hierarchical cluster analysis), these match the variety of total dissolvable solids, water types and ionic orders. The principal component analysis combined the ionic parameters of the studied groundwater samples into two principal components. The first represents about 56% of the whole sample variance reflecting a salinization due to evaporation, leaching, dissolution of marine salts and/or seawater intrusion. The second represents about 15.8% reflecting dilution with rain water and the El-Salam Canal. Most groundwater samples were not suitable for human consumption and about 41% are suitable for irrigation. However, all groundwater samples are suitable for cattle, about 69% and 15% are suitable for horses and poultry, respectively.

Old metal oxide clusters in new applications: spontaneous reduction of Keggin and Dawson polyoxometalate layers by a metallic electrode for improving efficiency in organic optoelectronics.

PubMed

Vasilopoulou, Maria; Douvas, Antonios M; Palilis, Leonidas C; Kennou, Stella; Argitis, Panagiotis

2015-06-03

The present study is aimed at investigating the solid state reduction of a representative series of Keggin and Dawson polyoxometalate (POM) films in contact with a metallic (aluminum) electrode and at introducing them as highly efficient cathode interlayers in organic optoelectronics. We show that, upon reduction, up to four electrons are transferred from the metallic electrode to the POM clusters of the Keggin series dependent on addenda substitution, whereas a six electron reduction was observed in the case of the Dawson type clusters. The high degree of their reduction by Al was found to be of vital importance in obtaining effective electron transport through the cathode interface. A large improvement in the operational characteristics of organic light emitting devices and organic photovoltaics based on a wide range of different organic semiconducting materials and incorporating reduced POM/Al cathode interfaces was achieved as a result of the large decrease of the electron injection/extraction barrier, the enhanced electron transport and the reduced recombination losses in our reduced POM modified devices.

Oblate-Earth Effects on the Calculation of Ec During Spacecraft Reentry

NASA Technical Reports Server (NTRS)

Bacon, John B.; Matney, Mark J.

2017-01-01

The bulge in the Earth at its equator has been shown to lead to a clustering of natural decays biased to occur towards the equator and away from the orbit's extreme latitudes. Such clustering must be considered when predicting the Expectation of Casualty (Ec) during a natural decay because of the clustering of the human population in the same lower latitudes. This study expands upon prior work, and formalizes the correction that must be made to the calculation of the average exposed population density as a result of this effect. Although a generic equation can be derived from this work to approximate the effects of gravitational and atmospheric perturbations on a final decay, such an equation averages certain important subtleties in achieving a best fit over all conditions. The authors recommend that direct simulation be used to calculate the true Ec for any specific entry as a more accurate method. A generic equation is provided, represented as a function of ballistic number and inclination of the entering spacecraft over the credible range of ballistic numbers.

Global Establishment Risk of Economically Important Fruit Fly Species (Tephritidae)

PubMed Central

Qin, Yujia; Paini, Dean R.; Wang, Cong; Fang, Yan; Li, Zhihong

2015-01-01

The global invasion of Tephritidae (fruit flies) attracts a great deal of attention in the field of plant quarantine and invasion biology because of their economic importance. Predicting which one in hundreds of potential invasive fruit fly species is most likely to establish in a region presents a significant challenge, but can be facilitated using a self organising map (SOM), which is able to analyse species associations to rank large numbers of species simultaneously with an index of establishment. A global presence/absence dataset including 180 economically significant fruit fly species in 118 countries was analysed using a SOM. We compare and contrast ranked lists from six countries selected from each continent, and also show that those countries geographically close were clustered together by the SOM analysis because they have similar fruit fly assemblages. These closely clustered countries therefore represent greater threats to each other as sources of invasive fruit fly species. Finally, we indicate how this SOM method could be utilized as an initial screen to support prioritizing fruit fly species for further research into their potential to invade a region. PMID:25588025

A preliminary report on the genetic variation in pointed gourd (Trichosanthes dioica Roxb.) as assessed by random amplified polymorphic DNA.

PubMed

Adhikari, S; Biswas, A; Bandyopadhyay, T K; Ghosh, P D

2014-06-01

Pointed gourd (Trichosanthes dioica Roxb.) is an economically important cucurbit and is extensively propagated through vegetative means, viz vine and root cuttings. As the accessions are poorly characterized it is important at the beginning of a breeding programme to discriminate among available genotypes to establish the level of genetic diversity. The genetic diversity of 10 pointed gourd races, referred to as accessions was evaluated. DNA profiling was generated using 10 sequence independent RAPD markers. A total of 58 scorable loci were observed out of which 18 (31.03%) loci were considered polymorphic. Genetic diversity parameters [average and effective number of alleles, Shannon's index, percent polymorphism, Nei's gene diversity, polymorphic information content (PIC)] for RAPD along with UPGMA clustering based on Jaccard's coefficient were estimated. The UPGMA dendogram constructed based on RAPD analysis in 10 pointed gourd accessions were found to be grouped in a single cluster and may represent members of one heterotic group. RAPD analysis showed promise as an effective tool in estimating genetic polymorphism in different accessions of pointed gourd.

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

PubMed

Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

2018-02-01

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

A scheme for racquet sports video analysis with the combination of audio-visual information

NASA Astrophysics Data System (ADS)

Xing, Liyuan; Ye, Qixiang; Zhang, Weigang; Huang, Qingming; Yu, Hua

2005-07-01

As a very important category in sports video, racquet sports video, e.g. table tennis, tennis and badminton, has been paid little attention in the past years. Considering the characteristics of this kind of sports video, we propose a new scheme for structure indexing and highlight generating based on the combination of audio and visual information. Firstly, a supervised classification method is employed to detect important audio symbols including impact (ball hit), audience cheers, commentator speech, etc. Meanwhile an unsupervised algorithm is proposed to group video shots into various clusters. Then, by taking advantage of temporal relationship between audio and visual signals, we can specify the scene clusters with semantic labels including rally scenes and break scenes. Thirdly, a refinement procedure is developed to reduce false rally scenes by further audio analysis. Finally, an exciting model is proposed to rank the detected rally scenes from which many exciting video clips such as game (match) points can be correctly retrieved. Experiments on two types of representative racquet sports video, table tennis video and tennis video, demonstrate encouraging results.

Folksonomies and clustering in the collaborative system CiteULike

NASA Astrophysics Data System (ADS)

Capocci, Andrea; Caldarelli, Guido

2008-06-01

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.

Cluster evolution during the early stages of heating explosives and its relationship to sensitivity: a comparative study of TATB, β-HMX and PETN by molecular reactive force field simulations.

PubMed

Wen, Yushi; Zhang, Chaoyang; Xue, Xianggui; Long, Xinping

2015-05-14

Clustering is experimentally and theoretically verified during the complicated processes involved in heating high explosives, and has been thought to influence their detonation properties. However, a detailed description of the clustering that occurs has not been fully elucidated. We used molecular dynamic simulations with an improved reactive force field, ReaxFF_lg, to carry out a comparative study of cluster evolution during the early stages of heating for three representative explosives: 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), β-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) and pentaerythritol tetranitrate (PETN). These representatives vary greatly in their oxygen balance (OB), molecular structure, stability and experimental sensitivity. We found that when heated, TATB, HMX and PETN differ in the size, amount, proportion and lifetime of their clusters. We also found that the clustering tendency of explosives decreases as their OB becomes less negative. We propose that the relationship between OB and clustering can be attributed to the role of clustering in detonation. That is, clusters can form more readily in a high explosive with a more negative OB, which retard its energy release, secondary decomposition, further decomposition to final small molecule products and widen its detonation reaction zone. Moreover, we found that the carbon content of the clusters increases during clustering, in accordance with the observed soot, which is mainly composed of carbon as the final product of detonation or deflagration.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes

PubMed Central

Skinnider, Michael A.; Merwin, Nishanth J.; Johnston, Chad W.

2017-01-01

Abstract Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. PMID:28460067

Understanding drugs in breast cancer through drug sensitivity screening.

PubMed

Uhr, Katharina; Prager-van der Smissen, Wendy J C; Heine, Anouk A J; Ozturk, Bahar; Smid, Marcel; Göhlmann, Hinrich W H; Jager, Agnes; Foekens, John A; Martens, John W M

2015-01-01

With substantial numbers of breast tumors showing or acquiring treatment resistance, it is of utmost importance to develop new agents for the treatment of the disease, to know their effectiveness against breast cancer and to understand their relationships with other drugs to best assign the right drug to the right patient. To achieve this goal drug screenings on breast cancer cell lines are a promising approach. In this study a large-scale drug screening of 37 compounds was performed on a panel of 42 breast cancer cell lines representing the main breast cancer subtypes. Clustering, correlation and pathway analyses were used for data analysis. We found that compounds with a related mechanism of action had correlated IC50 values and thus grouped together when the cell lines were hierarchically clustered based on IC50 values. In total we found six clusters of drugs of which five consisted of drugs with related mode of action and one cluster with two drugs not previously connected. In total, 25 correlated and four anti-correlated drug sensitivities were revealed of which only one drug, Sirolimus, showed significantly lower IC50 values in the luminal/ERBB2 breast cancer subtype. We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

Clustering and phase behaviour of attractive active particles with hydrodynamics.

PubMed

Navarro, Ricard Matas; Fielding, Suzanne M

2015-10-14

We simulate clustering, phase separation and hexatic ordering in a monolayered suspension of active squirming disks subject to an attractive Lennard-Jones-like pairwise interaction potential, taking hydrodynamic interactions between the particles fully into account. By comparing the hydrodynamic case with counterpart simulations for passive and active Brownian particles, we elucidate the relative roles of self-propulsion, interparticle attraction, and hydrodynamic interactions in determining clustering and phase behaviour. Even in the presence of an attractive potential, we find that hydrodynamic interactions strongly suppress the motility induced phase separation that might a priori have been expected in a highly active suspension. Instead, we find only a weak tendency for the particles to form stringlike clusters in this regime. At lower activities we demonstrate phase behaviour that is broadly equivalent to that of the counterpart passive system at low temperatures, characterized by regimes of gas-liquid, gas-solid and liquid-solid phase coexistence. In this way, we suggest that a dimensionless quantity representing the level of activity relative to the strength of attraction plays the role of something like an effective non-equilibrium temperature, counterpart to the (dimensionless) true thermodynamic temperature in the passive system. However there are also some important differences from the equilibrium case, most notably with regards the degree of hexatic ordering, which we discuss carefully.

Environmental filtering of eudicot lineages underlies phylogenetic clustering in tropical South American flooded forests.

PubMed

Aldana, Ana M; Carlucci, Marcos B; Fine, Paul V A; Stevenson, Pablo R

2017-02-01

The phylogenetic community assembly approach has been used to elucidate the role of ecological and historical processes in shaping tropical tree communities. Recent studies have shown that stressful environments, such as seasonally dry, white-sand and flooded forests tend to be phylogenetically clustered, arguing for niche conservatism as the main driver for this pattern. Very few studies have attempted to identify the lineages that contribute to such assembly patterns. We aimed to improve our understanding of the assembly of flooded forest tree communities in Northern South America by asking the following questions: are seasonally flooded forests phylogenetically clustered? If so, which angiosperm lineages are over-represented in seasonally flooded forests? To assess our hypotheses, we investigated seasonally flooded and terra firme forests from the Magdalena, Orinoco and Amazon Basins, in Colombia. Our results show that, regardless of the river basin in which they are located, seasonally flooded forests of Northern South America tend to be phylogenetically clustered, which means that the more abundant taxa in these forests are more closely related to each other than expected by chance. Based on our alpha and beta phylodiversity analyses we interpret that eudicots are more likely to adapt to extreme environments such as seasonally flooded forests, which indicates the importance of environmental filtering in the assembly of the Neotropical flora.

Naturally selected hepatitis C virus polymorphisms confer broad neutralizing antibody resistance.

PubMed

Bailey, Justin R; Wasilewski, Lisa N; Snider, Anna E; El-Diwany, Ramy; Osburn, William O; Keck, Zhenyong; Foung, Steven K H; Ray, Stuart C

2015-01-01

For hepatitis C virus (HCV) and other highly variable viruses, broadly neutralizing mAbs are an important guide for vaccine development. The development of resistance to anti-HCV mAbs is poorly understood, in part due to a lack of neutralization testing against diverse, representative panels of HCV variants. Here, we developed a neutralization panel expressing diverse, naturally occurring HCV envelopes (E1E2s) and used this panel to characterize neutralizing breadth and resistance mechanisms of 18 previously described broadly neutralizing anti-HCV human mAbs. The observed mAb resistance could not be attributed to polymorphisms in E1E2 at known mAb-binding residues. Additionally, hierarchical clustering analysis of neutralization resistance patterns revealed relationships between mAbs that were not predicted by prior epitope mapping, identifying 3 distinct neutralization clusters. Using this clustering analysis and envelope sequence data, we identified polymorphisms in E2 that confer resistance to multiple broadly neutralizing mAbs. These polymorphisms, which are not at mAb contact residues, also conferred resistance to neutralization by plasma from HCV-infected subjects. Together, our method of neutralization clustering with sequence analysis reveals that polymorphisms at noncontact residues may be a major immune evasion mechanism for HCV, facilitating viral persistence and presenting a challenge for HCV vaccine development.

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

ERIC Educational Resources Information Center

Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

2012-01-01

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

A dynamical study of Galactic globular clusters under different relaxation conditions

NASA Astrophysics Data System (ADS)

Zocchi, A.; Bertin, G.; Varri, A. L.

2012-03-01

Aims: We perform a systematic combined photometric and kinematic analysis of a sample of globular clusters under different relaxation conditions, based on their core relaxation time (as listed in available catalogs), by means of two well-known families of spherical stellar dynamical models. Systems characterized by shorter relaxation time scales are expected to be better described by isotropic King models, while less relaxed systems might be interpreted by means of non-truncated, radially-biased anisotropic f(ν) models, originally designed to represent stellar systems produced by a violent relaxation formation process and applied here for the first time to the study of globular clusters. Methods: The comparison between dynamical models and observations is performed by fitting simultaneously surface brightness and velocity dispersion profiles. For each globular cluster, the best-fit model in each family is identified, along with a full error analysis on the relevant parameters. Detailed structural properties and mass-to-light ratios are also explicitly derived. Results: We find that King models usually offer a good representation of the observed photometric profiles, but often lead to less satisfactory fits to the kinematic profiles, independently of the relaxation condition of the systems. For some less relaxed clusters, f(ν) models provide a good description of both observed profiles. Some derived structural characteristics, such as the total mass or the half-mass radius, turn out to be significantly model-dependent. The analysis confirms that, to answer some important dynamical questions that bear on the formation and evolution of globular clusters, it would be highly desirable to acquire larger numbers of accurate kinematic data-points, well distributed over the cluster field. Appendices are available in electronic form at http://www.aanda.org

Protein domain organisation: adding order.

PubMed

Kummerfeld, Sarah K; Teichmann, Sarah A

2009-01-29

Domains are the building blocks of proteins. During evolution, they have been duplicated, fused and recombined, to produce proteins with novel structures and functions. Structural and genome-scale studies have shown that pairs or groups of domains observed together in a protein are almost always found in only one N to C terminal order and are the result of a single recombination event that has been propagated by duplication of the multi-domain unit. Previous studies of domain organisation have used graph theory to represent the co-occurrence of domains within proteins. We build on this approach by adding directionality to the graphs and connecting nodes based on their relative order in the protein. Most of the time, the linear order of domains is conserved. However, using the directed graph representation we have identified non-linear features of domain organization that are over-represented in genomes. Recognising these patterns and unravelling how they have arisen may allow us to understand the functional relationships between domains and understand how the protein repertoire has evolved. We identify groups of domains that are not linearly conserved, but instead have been shuffled during evolution so that they occur in multiple different orders. We consider 192 genomes across all three kingdoms of life and use domain and protein annotation to understand their functional significance. To identify these features and assess their statistical significance, we represent the linear order of domains in proteins as a directed graph and apply graph theoretical methods. We describe two higher-order patterns of domain organisation: clusters and bi-directionally associated domain pairs and explore their functional importance and phylogenetic conservation. Taking into account the order of domains, we have derived a novel picture of global protein organization. We found that all genomes have a higher than expected degree of clustering and more domain pairs in forward and reverse orientation in different proteins relative to random graphs with identical degree distributions. While these features were statistically over-represented, they are still fairly rare. Looking in detail at the proteins involved, we found strong functional relationships within each cluster. In addition, the domains tended to be involved in protein-protein interaction and are able to function as independent structural units. A particularly striking example was the human Jak-STAT signalling pathway which makes use of a set of domains in a range of orders and orientations to provide nuanced signaling functionality. This illustrated the importance of functional and structural constraints (or lack thereof) on domain organisation.

Cluster analysis of the hot subdwarfs in the PG survey

NASA Technical Reports Server (NTRS)

Thejll, Peter; Charache, Darryl; Shipman, Harry L.

1989-01-01

Application of cluster analysis to the hot subdwarfs in the Palomar Green (PG) survey of faint blue high-Galactic-latitude objects is assessed, with emphasis on data noise and the number of clusters to subdivide the data into. The data used in the study are presented, and cluster analysis, using the CLUSTAN program, is applied to it. Distances are calculated using the Euclidean formula, and clustering is done by Ward's method. The results are discussed, and five groups representing natural divisions of the subdwarfs in the PG survey are presented.

Representation of Tinnitus in the US Newspaper Media and in Facebook Pages: Cross-Sectional Analysis of Secondary Data

PubMed Central

Ratinaud, Pierre; Andersson, Gerhard

2018-01-01

Background When people with health conditions begin to manage their health issues, one important issue that emerges is the question as to what exactly do they do with the information that they have obtained through various sources (eg, news media, social media, health professionals, friends, and family). The information they gather helps form their opinions and, to some degree, influences their attitudes toward managing their condition. Objective This study aimed to understand how tinnitus is represented in the US newspaper media and in Facebook pages (ie, social media) using text pattern analysis. Methods This was a cross-sectional study based upon secondary analyses of publicly available data. The 2 datasets (ie, text corpuses) analyzed in this study were generated from US newspaper media during 1980-2017 (downloaded from the database US Major Dailies by ProQuest) and Facebook pages during 2010-2016. The text corpuses were analyzed using the Iramuteq software using cluster analysis and chi-square tests. Results The newspaper dataset had 432 articles. The cluster analysis resulted in 5 clusters, which were named as follows: (1) brain stimulation (26.2%), (2) symptoms (13.5%), (3) coping (19.8%), (4) social support (24.2%), and (5) treatment innovation (16.4%). A time series analysis of clusters indicated a change in the pattern of information presented in newspaper media during 1980-2017 (eg, more emphasis on cluster 5, focusing on treatment inventions). The Facebook dataset had 1569 texts. The cluster analysis resulted in 7 clusters, which were named as: (1) diagnosis (21.9%), (2) cause (4.1%), (3) research and development (13.6%), (4) social support (18.8%), (5) challenges (11.1%), (6) symptoms (21.4%), and (7) coping (9.2%). A time series analysis of clusters indicated no change in information presented in Facebook pages on tinnitus during 2011-2016. Conclusions The study highlights the specific aspects about tinnitus that the US newspaper media and Facebook pages focus on, as well as how these aspects change over time. These findings can help health care providers better understand the presuppositions that tinnitus patients may have. More importantly, the findings can help public health experts and health communication experts in tailoring health information about tinnitus to promote self-management, as well as assisting in appropriate choices of treatment for those living with tinnitus. PMID:29739734

Metabolic syndrome: pathophysiology, management, and modulation by natural compounds

PubMed Central

Rochlani, Yogita; Pothineni, Naga Venkata; Kovelamudi, Swathi; Mehta, Jawahar L.

2017-01-01

Metabolic syndrome (MetS) represents a cluster of metabolic abnormalities that include hypertension, central obesity, insulin resistance, and atherogenic dyslipidemia, and is strongly associated with an increased risk for developing diabetes and atherosclerotic and nonatherosclerotic cardiovascular disease (CVD). The pathogenesis of MetS involves both genetic and acquired factors that contribute to the final pathway of inflammation that leads to CVD. MetS has gained significant importance recently due to the exponential increase in obesity worldwide. Early diagnosis is important in order to employ lifestyle and risk factor modification. Here, we review the epidemiology and pathogenesis of MetS, the role of inflammation in MetS, and summarize existing natural therapies for MetS. PMID:28639538

Dark matter searches with Cherenkov telescopes: nearby dwarf galaxies or local galaxy clusters?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sánchez-Conde, Miguel A.; Cannoni, Mirco; Gómez, Mario E.

2011-12-01

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure.more » Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We find that the level of the annihilation flux from these targets is below the sensitivities of current IACTs and the future CTA.« less

Dark Matter Searches with Cherenkov Telescopes: Nearby Dwarf Galaxies or Local Galaxy Clusters?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez-Conde, Miguel A.; /KIPAC, Menlo Park /SLAC /IAC, La Laguna /Laguna U., Tenerife; Cannoni, Mirco

2012-06-06

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure.more » Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We find that the level of the annihilation flux from these targets is below the sensitivities of current IACTs and the future CTA.« less

Dark matter searches with Cherenkov telescopes: nearby dwarf galaxies or local galaxy clusters?

NASA Astrophysics Data System (ADS)

Sánchez-Conde, Miguel A.; Cannoni, Mirco; Zandanel, Fabio; Gómez, Mario E.; Prada, Francisco

2011-12-01

In this paper, we compare dwarf galaxies and galaxy clusters in order to elucidate which object class is the best target for gamma-ray DM searches with imaging atmospheric Cherenkov telescopes (IACTs). We have built a mixed dwarfs+clusters sample containing some of the most promising nearby dwarf galaxies (Draco, Ursa Minor, Wilman 1 and Segue 1) and local galaxy clusters (Perseus, Coma, Ophiuchus, Virgo, Fornax, NGC 5813 and NGC 5846), and then compute their DM annihilation flux profiles by making use of the latest modeling of their DM density profiles. We also include in our calculations the effect of DM substructure. Willman 1 appears as the best candidate in the sample. However, its mass modeling is still rather uncertain, so probably other candidates with less uncertainties and quite similar fluxes, namely Ursa Minor and Segue 1, might be better options. As for galaxy clusters, Virgo represents the one with the highest flux. However, its large spatial extension can be a serious handicap for IACT observations and posterior data analysis. Yet, other local galaxy cluster candidates with more moderate emission regions, such as Perseus, may represent good alternatives. After comparing dwarfs and clusters, we found that the former exhibit annihilation flux profiles that, at the center, are roughly one order of magnitude higher than those of clusters, although galaxy clusters can yield similar, or even higher, integrated fluxes for the whole object once substructure is taken into account. Even when any of these objects are strictly point-like according to the properties of their annihilation signals, we conclude that dwarf galaxies are best suited for observational strategies based on the search of point-like sources, while galaxy clusters represent best targets for analyses that can deal with rather extended emissions. Finally, we study the detection prospects for present and future IACTs in the framework of the constrained minimal supersymmetric standard model. We find that the level of the annihilation flux from these targets is below the sensitivities of current IACTs and the future CTA.

Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

PubMed

Barkan, David T; Cheng, Xiao-Li; Celino, Herodion; Tran, Tran T; Bhandari, Ashok; Craik, Charles S; Sali, Andrej; Smythe, Mark L

2016-11-23

Disulfide-rich peptides (DRPs) are found throughout nature. They are suitable scaffolds for drug development due to their small cores, whose disulfide bonds impart extraordinary chemical and biological stability. A challenge in developing a DRP therapeutic is to engineer binding to a specific target. This challenge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage display library and by (ii) panning multiple libraries encoding structurally distinct scaffolds. Here, we implement a protocol for defining these diverse scaffolds, based on clustering structurally defined DRPs according to their conformational similarity. We developed and applied a hierarchical clustering protocol based on DRP structural similarity, followed by two post-processing steps, to classify 806 unique DRP structures into 81 clusters. The 20 most populated clusters comprised 85% of all DRPs. Representative scaffolds were selected from each of these clusters; the representatives were structurally distinct from one another, but similar to other DRPs in their respective clusters. To demonstrate the utility of the clusters, phage libraries were constructed for three of the representative scaffolds and panned against interleukin-23. One library produced a peptide that bound to this target with an IC 50 of 3.3 μM. Most DRP clusters contained members that were diverse in sequence, host organism, and interacting proteins, indicating that cluster members were functionally diverse despite having similar structure. Only 20 peptide scaffolds accounted for most of the natural DRP structural diversity, providing suitable starting points for seeding phage display experiments. Through selection of the scaffold surface to vary in phage display, libraries can be designed that present sequence diversity in architecturally distinct, biologically relevant combinations of secondary structures. We supported this hypothesis with a proof-of-concept experiment in which three phage libraries were constructed and panned against the IL-23 target, resulting in a single-digit μM hit and suggesting that a collection of libraries based on the full set of 20 scaffolds increases the potential to identify efficiently peptide binders to a protein target in a drug discovery program.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-08-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics |*| the infamous |*|gastrophysics|*| in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-09-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics -- the infamous ``gastrophysics''-- in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

Cross-entropy clustering framework for catchment classification

NASA Astrophysics Data System (ADS)

Tongal, Hakan; Sivakumar, Bellie

2017-09-01

There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

Spatial clustering of pixels of a multispectral image

DOEpatents

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

Identification of uncommon objects in containers

DOEpatents

Bremer, Peer-Timo; Kim, Hyojin; Thiagarajan, Jayaraman J.

2017-09-12

A system for identifying in an image an object that is commonly found in a collection of images and for identifying a portion of an image that represents an object based on a consensus analysis of segmentations of the image. The system collects images of containers that contain objects for generating a collection of common objects within the containers. To process the images, the system generates a segmentation of each image. The image analysis system may also generate multiple segmentations for each image by introducing variations in the selection of voxels to be merged into a segment. The system then generates clusters of the segments based on similarity among the segments. Each cluster represents a common object found in the containers. Once the clustering is complete, the system may be used to identify common objects in images of new containers based on similarity between segments of images and the clusters.

Patterns of Dysmorphic Features in Schizophrenia

PubMed Central

Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

2011-01-01

Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P < 0.05), median number of dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

Clustering of GPS velocities in the Mojave Block, southeastern California

NASA Astrophysics Data System (ADS)

Savage, J. C.; Simpson, R. W.

2013-04-01

find subdivisions within the Mojave Block using cluster analysis to identify groupings in the velocities observed at GPS stations there. The clusters are represented on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. The most significant representation as judged by the gap test involves 4 clusters within the Mojave Block. The fault systems bounding the clusters from east to west are 1) the faults defining the eastern boundary of the Northeast Mojave Domain extended southward to connect to the Hector Mine rupture, 2) the Calico-Paradise fault system, 3) the Landers-Blackwater fault system, and 4) the Helendale-Lockhart fault system. This division of the Mojave Block is very similar to that proposed by Meade and Hager []. However, no cluster boundary coincides with the Garlock Fault, the northern boundary of the Mojave Block. Rather, the clusters appear to continue without interruption from the Mojave Block north into the southern Walker Lane Belt, similar to the continuity across the Garlock Fault of the shear zone along the Blackwater-Little Lake fault system observed by Peltzer et al. []. Mapped traces of individual faults in the Mojave Block terminate within the block and do not continue across the Garlock Fault [Dokka and Travis, ].

Formation and Assembly of Massive Star Clusters

NASA Astrophysics Data System (ADS)

McMillan, Stephen

The formation of stars and star clusters is a major unresolved problem in astrophysics. It is central to modeling stellar populations and understanding galaxy luminosity distributions in cosmological models. Young massive clusters are major components of starburst galaxies, while globular clusters are cornerstones of the cosmic distance scale and represent vital laboratories for studies of stellar dynamics and stellar evolution. Yet how these clusters form and how rapidly and efficiently they expel their natal gas remain unclear, as do the consequences of this gas expulsion for cluster structure and survival. Also unclear is how the properties of low-mass clusters, which form from small-scale instabilities in galactic disks and inform much of our understanding of cluster formation and star-formation efficiency, differ from those of more massive clusters, which probably formed in starburst events driven by fast accretion at high redshift, or colliding gas flows in merging galaxies. Modeling cluster formation requires simulating many simultaneous physical processes, placing stringent demands on both software and hardware. Simulations of galaxies evolving in cosmological contexts usually lack the numerical resolution to simulate star formation in detail. They do not include detailed treatments of important physical effects such as magnetic fields, radiation pressure, ionization, and supernova feedback. Simulations of smaller clusters include these effects, but fall far short of the mass of even single young globular clusters. With major advances in computing power and software, we can now directly address this problem. We propose to model the formation of massive star clusters by integrating the FLASH adaptive mesh refinement magnetohydrodynamics (MHD) code into the Astrophysical Multi-purpose Software Environment (AMUSE) framework, to work with existing stellar-dynamical and stellar evolution modules in AMUSE. All software will be freely distributed on-line, allowing open access to state-of- the-art simulation techniques within a modern, modular software environment. We will follow the gravitational collapse of 0.1-10 million-solar mass gas clouds through star formation and coalescence into a star cluster, modeling in detail the coupling of the gas and the newborn stars. We will study the effects of star formation by detecting accreting regions of gas in self-gravitating, turbulent, MHD, FLASH models that we will translate into collisional dynamical systems of stars modeled with an N-body code, coupled together in the AMUSE framework. Our FLASH models will include treatments of radiative transfer from the newly formed stars, including heating and radiative acceleration of the surrounding gas. Specific questions to be addressed are: (1) How efficiently does the gas in a star forming region form stars, how does this depend on mass, metallicity, and other parameters, and what terminates star formation? What observational predictions can be made to constrain our models? (2) How important are different mechanisms for driving turbulence and removing gas from a cluster: accretion, radiative feedback, and mechanical feedback? (3) How does the infant mortality rate of young clusters depend on the initial properties of the parent cloud? (4) What are the characteristic formation timescales of massive star clusters, and what observable imprints does the assembly process leave on their structure at an age of 10-20 Myr, when formation is essentially complete and many clusters can be observed? These studies are directly relevant to NASA missions at many electromagnetic wavelengths, including Chandra, GALEX, Hubble, and Spitzer. Each traces different aspects of cluster formation and evolution: X-rays trace supernovae, ultraviolet traces young stars, visible colors can distinguish between young blue stars and older red stars, and the infrared directly shows young embedded star clusters.

Interactions of iron-bound frataxin with ISCU and ferredoxin on the cysteine desulfurase complex leading to Fe-S cluster assembly.

PubMed

Cai, Kai; Frederick, Ronnie O; Tonelli, Marco; Markley, John L

2018-06-01

Frataxin (FXN) is involved in mitochondrial iron‑sulfur (Fe-S) cluster biogenesis and serves to accelerate Fe-S cluster formation. FXN deficiency is associated with Friedreich ataxia, a neurodegenerative disease. We have used a combination of isothermal titration calorimetry and multinuclear NMR spectroscopy to investigate interactions among the components of the biological machine that carries out the assembly of iron‑sulfur clusters in human mitochondria. Our results show that FXN tightly binds a single Fe 2+ but not Fe 3+ . While FXN (with or without bound Fe 2+ ) does not bind the scaffold protein ISCU directly, the two proteins interact mutually when each is bound to the cysteine desulfurase complex ([NFS1] 2 :[ISD11] 2 :[Acp] 2 ), abbreviated as (NIA) 2 , where "N" represents the cysteine desulfurase (NFS1), "I" represents the accessory protein (ISD11), and "A" represents acyl carrier protein (Acp). FXN binds (NIA) 2 weakly in the absence of ISCU but more strongly in its presence. Fe 2+ -FXN binds to the (NIA) 2 -ISCU 2 complex without release of iron. However, upon the addition of both l-cysteine and a reductant (either reduced FDX2 or DTT), Fe 2+ is released from FXN as consistent with Fe 2+ -FXN being the proximal source of iron for Fe-S cluster assembly. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Finding Clothing That Fit through Cluster Analysis and Objective Interestingness Measures

NASA Astrophysics Data System (ADS)

Peña, Isis; Viktor, Herna L.; Paquet, Eric

Clothes should fit consumers well, be aesthetically pleasing and comfortable. However, repeated studies of customers’ levels of satisfaction indicate that this is often not the case. For example, more robust males often find it difficult to find pants that are the correct length and fit their waists well. What, then, are the typical body profiles of the population? Would it be possible to identify the measurements that are of importance for different sizes and genders? Furthermore, assuming that we have access to an anthropometric database would there be a way to guide the data mining process to discover only those relevant body measurements that are of the most interest for apparel designers? This paper describes our results when addressing these questions through cluster analysis and interestingness measures-based feature selection. We explore a database containing anthropometric measurements as well as 3-D body scans, of a representative sample of the Dutch population.

Aspergillus mulundensis sp. nov., a new species for the fungus producing the antifungal echinocandin lipopeptides, mulundocandins.

PubMed

Bills, Gerald F; Yue, Qun; Chen, Li; Li, Yan; An, Zhiqiang; Frisvad, Jens C

2016-03-01

The invalidly published name Aspergillus sydowii var. mulundensis was proposed for a strain of Aspergillus that produced new echinocandin metabolites designated as the mulundocadins. Reinvestigation of this strain (Y-30462=DSMZ 5745) using phylogenetic, morphological, and metabolic data indicated that it is a distinct and novel species of Aspergillus sect. Nidulantes. The taxonomic novelty, Aspergillus mulundensis, is introduced for this historically important echinocandin-producing strain. The closely related A. nidulans FGSC A4 has one of the most extensively characterized secondary metabolomes of any filamentous fungus. Comparison of the full-genome sequences of DSMZ 5745 and FGSC A4 indicated that the two strains share 33 secondary metabolite biosynthetic gene clusters. These shared gene clusters represent ~45% of the total secondary metabolome of each strain, thus indicating a high level intraspecific divergence in terms of secondary metabolism.

Emerging Multifunctional Metal-Organic Framework Materials.

PubMed

Li, Bin; Wen, Hui-Min; Cui, Yuanjing; Zhou, Wei; Qian, Guodong; Chen, Banglin

2016-10-01

Metal-organic frameworks (MOFs), also known as coordination polymers, represent an interesting type of solid crystalline materials that can be straightforwardly self-assembled through the coordination of metal ions/clusters with organic linkers. Owing to the modular nature and mild conditions of MOF synthesis, the porosities of MOF materials can be systematically tuned by judicious selection of molecular building blocks, and a variety of functional sites/groups can be introduced into metal ions/clusters, organic linkers, or pore spaces through pre-designing or post-synthetic approaches. These unique advantages enable MOFs to be used as a highly versatile and tunable platform for exploring multifunctional MOF materials. Here, the bright potential of MOF materials as emerging multifunctional materials is highlighted in some of the most important applications for gas storage and separation, optical, electric and magnetic materials, chemical sensing, catalysis, and biomedicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Omics and multi-omics approaches to study the biosynthesis of secondary metabolites in microorganisms.

PubMed

Palazzotto, Emilia; Weber, Tilmann

2018-04-12

Natural products produced by microorganisms represent the main source of bioactive molecules. The development of high-throughput (omics) techniques have importantly contributed to the renaissance of new antibiotic discovery increasing our understanding of complex mechanisms controlling the expression of biosynthetic gene clusters (BGCs) encoding secondary metabolites. In this context this review highlights recent progress in the use and integration of 'omics' approaches with focuses on genomics, transcriptomics, proteomics metabolomics meta-omics and combined omics as powerful strategy to discover new antibiotics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Query by example video based on fuzzy c-means initialized by fixed clustering center

NASA Astrophysics Data System (ADS)

Hou, Sujuan; Zhou, Shangbo; Siddique, Muhammad Abubakar

2012-04-01

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach.

Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: the myoglobin case.

PubMed

Papaleo, Elena; Mereghetti, Paolo; Fantucci, Piercarlo; Grandori, Rita; De Gioia, Luca

2009-01-01

Several molecular dynamics (MD) simulations were used to sample conformations in the neighborhood of the native structure of holo-myoglobin (holo-Mb), collecting trajectories spanning 0.22 micros at 300 K. Principal component (PCA) and free-energy landscape (FEL) analyses, integrated by cluster analysis, which was performed considering the position and structures of the individual helices of the globin fold, were carried out. The coherence between the different structural clusters and the basins of the FEL, together with the convergence of parameters derived by PCA indicates that an accurate description of the Mb conformational space around the native state was achieved by multiple MD trajectories spanning at least 0.14 micros. The integration of FEL, PCA, and structural clustering was shown to be a very useful approach to gain an overall view of the conformational landscape accessible to a protein and to identify representative protein substates. This method could be also used to investigate the conformational and dynamical properties of Mb apo-, mutant, or delete versions, in which greater conformational variability is expected and, therefore identification of representative substates from the simulations is relevant to disclose structure-function relationship.

Using background knowledge for picture organization and retrieval

NASA Astrophysics Data System (ADS)

Quintana, Yuri

1997-01-01

A picture knowledge base management system is described that is used to represent, organize and retrieve pictures from a frame knowledge base. Experiments with human test subjects were conducted to obtain further descriptions of pictures from news magazines. These descriptions were used to represent the semantic content of pictures in frame representations. A conceptual clustering algorithm is described which organizes pictures not only on the observable features, but also on implicit properties derived from the frame representations. The algorithm uses inheritance reasoning to take into account background knowledge in the clustering. The algorithm creates clusters of pictures using a group similarity function that is based on the gestalt theory of picture perception. For each cluster created, a frame is generated which describes the semantic content of pictures in the cluster. Clustering and retrieval experiments were conducted with and without background knowledge. The paper shows how the use of background knowledge and semantic similarity heuristics improves the speed, precision, and recall of queries processed. The paper concludes with a discussion of how natural language processing of can be used to assist in the development of knowledge bases and the processing of user queries.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure.

PubMed

Zhang, Wen; Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

PubMed Central

Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods. PMID:27579031

A local search for a graph clustering problem

NASA Astrophysics Data System (ADS)

Navrotskaya, Anna; Il'ev, Victor

2016-10-01

In the clustering problems one has to partition a given set of objects (a data set) into some subsets (called clusters) taking into consideration only similarity of the objects. One of most visual formalizations of clustering is graph clustering, that is grouping the vertices of a graph into clusters taking into consideration the edge structure of the graph whose vertices are objects and edges represent similarities between the objects. In the graph k-clustering problem the number of clusters does not exceed k and the goal is to minimize the number of edges between clusters and the number of missing edges within clusters. This problem is NP-hard for any k ≥ 2. We propose a polynomial time (2k-1)-approximation algorithm for graph k-clustering. Then we apply a local search procedure to the feasible solution found by this algorithm and hold experimental research of obtained heuristics.

Allosteric binding sites in Rab11 for potential drug candidates

PubMed Central

2018-01-01

Rab11 is an important protein subfamily in the RabGTPase family. These proteins physiologically function as key regulators of intracellular membrane trafficking processes. Pathologically, Rab11 proteins are implicated in many diseases including cancers, neurodegenerative diseases and type 2 diabetes. Although they are medically important, no previous study has found Rab11 allosteric binding sites where potential drug candidates can bind to. In this study, by employing multiple clustering approaches integrating principal component analysis, independent component analysis and locally linear embedding, we performed structural analyses of Rab11 and identified eight representative structures. Using these representatives to perform binding site mapping and virtual screening, we identified two novel binding sites in Rab11 and small molecules that can preferentially bind to different conformations of these sites with high affinities. After identifying the binding sites and the residue interaction networks in the representatives, we computationally showed that these binding sites may allosterically regulate Rab11, as these sites communicate with switch 2 region that binds to GTP/GDP. These two allosteric binding sites in Rab11 are also similar to two allosteric pockets in Ras that we discovered previously. PMID:29874286

Organic positive ions in aircraft gas-turbine engine exhaust

NASA Astrophysics Data System (ADS)

Sorokin, Andrey; Arnold, Frank

Volatile organic compounds (VOCs) represent a significant fraction of atmospheric aerosol. However the role of organic species emitted by aircraft (as a consequence of the incomplete combustion of fuel in the engine) in nucleation of new volatile particles still remains rather speculative and requires a much more detailed analysis of the underlying mechanisms. Measurements in aircraft exhaust plumes have shown the presence of both different non-methane VOCs (e.g. PartEmis project) and numerous organic cluster ions (MPIK-Heidelberg). However the link between detected organic gas-phase species and measured mass spectrum of cluster ions is uncertain. Unfortunately, up to now there are no models describing the thermodynamics of the formation of primary organic cluster ions in the exhaust of aircraft engines. The aim of this work is to present first results of such a model development. The model includes the block of thermodynamic data based on proton affinities and gas basicities of organic molecules and the block of non-equilibrium kinetics of the cluster ions evolution in the exhaust. The model predicts important features of the measured spectrum of positive ions in the exhaust behind aircraft. It is shown that positive ions emitted by aircraft engines into the atmosphere mostly consist of protonated and hydrated organic cluster ions. The developed model may be explored also in aerosol investigations of the background atmosphere as well as in the analysis of the emission of fine aerosol particles by automobiles.

Physiological oxygen prevents frequent silencing of the DLK1-DIO3 cluster during human embryonic stem cells culture.

PubMed

Xie, Pingyuan; Sun, Yi; Ouyang, Qi; Hu, Liang; Tan, Yueqiu; Zhou, Xiaoying; Xiong, Bo; Zhang, Qianjun; Yuan, Ding; Pan, Yi; Liu, Tiancheng; Liang, Ping; Lu, Guangxiu; Lin, Ge

2014-02-01

Genetic and epigenetic alterations are observed in long-term culture (>30 passages) of human embryonic stem cells (hESCs); however, little information is available in early cultures. Through a large-scale gene expression analysis between initial-passage hESCs (ihESCs, <10 passages) and early-passage hESCs (ehESCs, 20-30 passages) of 12 hESC lines, we found that the DLK1-DIO3 gene cluster was normally expressed and showed normal methylation pattern in ihESC, but was frequently silenced after 20 passages. Both the DLK1-DIO3 active status in ihESCs and the inactive status in ehESCs were inheritable during differentiation. Silencing of the DLK1-DIO3 cluster did not seem to compromise the multilineage differentiation ability of hESCs, but was associated with reduced DNA damage-induced apoptosis in ehESCs and their differentiated hepatocyte-like cell derivatives, possibly through attenuation of the expression and phosphorylation of p53. Furthermore, we demonstrated that 5% oxygen, instead of the commonly used 20% oxygen, is required for preserving the expression of the DLK1-DIO3 cluster. Overall, the data suggest that active expression of the DLK1-DIO3 cluster represents a new biomarker for epigenetic stability of hESCs and indicates the importance of using a proper physiological oxygen level during the derivation and culture of hESCs. © AlphaMed Press.

The geometry of chaotic dynamics — a complex network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Heitzig, J.; Donges, J. F.; Zou, Y.; Marwan, N.; Kurths, J.

2011-12-01

Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently ɛ-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using ɛ-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that ɛ-recurrence networks exhibit an important link between dynamical systems and graph theory.

Perceptions of firms within a cluster regarding the cluster's function and success: Amish furniture manufacturing in Ohio

Treesearch

Matthew S. Bumgardner; Gary W. Graham; P. Charles Goebel; Robert L. Romig

2011-01-01

The Amish-based furniture manufacturing cluster in and around Holmes County, OH, is home to some 400 shops and has become an important regional driver of demand for hardwood products. The cluster has expanded even as the broader domestic furniture industry has declined. Clustering dynamics are seen as important to the success, but little information has been available...

Clustering by neurocognition for fine-mapping of the schizophrenia susceptibility loci on chromosome 6p

PubMed Central

Lin, Sheng-Hsiang; Liu, Chih-Min; Liu, Yu-Li; Fann, Cathy Shen-Jang; Hsiao, Po-Chang; Wu, Jer-Yuarn; Hung, Shuen-Iu; Chen, Chun-Houh; Wu, Han-Ming; Jou, Yuh-Shan; Liu, Shi K.; Hwang, Tzung J.; Hsieh, Ming H.; Chang, Chien-Ching; Yang, Wei-Chih; Lin, Jin-Jia; Chou, Frank Huang-Chih; Faraone, Stephen V.; Tsuang, Ming T.; Hwu, Hai-Gwo; Chen, Wei J.

2009-01-01

Chromosome 6p is one of the most commonly implicated regions in the genome-wide linkage scans of schizophrenia, whereas further association studies for markers in this region were inconsistent likely due to heterogeneity. This study aimed to identify more homogeneous subgroups of families for fine mapping on regions around markers D6S296 and D6S309 (both in 6p24.3) as well as D6S274 (in 6p22.3) by means of similarity in neurocognitive functioning. A total of 160 families of patients with schizophrenia comprising at least two affected siblings who had data for 8 neurocognitive test variables of the Continuous Performance Test (CPT) and the Wisconsin Card Sorting Test (WCST) were subjected to cluster analysis with data visualization using the test scores of both affected siblings. Family clusters derived were then used separately in family-based association tests for 64 single nucleotide polymorphisms covering the region of 6p24.3 and 6p22.3. Three clusters were derived from the family-based clustering, with deficit cluster 1 representing deficit on the CPT, deficit cluster 2 representing deficit on both the CPT and the WCST, and a third cluster of non-deficit. After adjustment using false discovery rate for multiple testing, SNP rs13873 and haplotype rs1225934-rs13873 on BMP6-TXNDC5 genes were significantly associated with schizophrenia for the deficit cluster 1 but not for the deficit cluster 2 or non-deficit cluster. Our results provide further evidence that the BMP6-TXNDC5 locus on 6p24.3 may play a role in the selective impairments on sustained attention of schizophrenia. PMID:19694819

Assessing the hydrocarbon degrading potential of indigenous bacteria isolated from crude oil tank bottom sludge and hydrocarbon-contaminated soil of Azzawiya oil refinery, Libya.

PubMed

Mansur, Abdulatif A; Adetutu, Eric M; Kadali, Krishna K; Morrison, Paul D; Nurulita, Yuana; Ball, Andrew S

2014-09-01

The disposal of hazardous crude oil tank bottom sludge (COTBS) represents a significant waste management burden for South Mediterranean countries. Currently, the application of biological systems (bioremediation) for the treatment of COTBS is not widely practiced in these countries. Therefore, this study aims to develop the potential for bioremediation in this region through assessment of the abilities of indigenous hydrocarbonoclastic microorganisms from Libyan Hamada COTBS for the biotreatment of Libyan COTBS-contaminated environments. Bacteria were isolated from COTBS, COTBS-contaminated soil, treated COTBS-contaminated soil, and uncontaminated soil using Bushnell Hass medium amended with Hamada crude oil (1 %) as the main carbon source. Overall, 49 bacterial phenotypes were detected, and their individual abilities to degrade Hamada crude and selected COBTS fractions (naphthalene, phenanthrene, eicosane, octadecane and hexane) were evaluated using MT2 Biolog plates. Analyses using average well colour development showed that ~90 % of bacterial isolates were capable of utilizing representative aromatic fractions compared to 51 % utilization of representative aliphatics. Interestingly, more hydrocarbonoclastic isolates were obtained from treated contaminated soils (42.9 %) than from COTBS (26.5 %) or COTBS-contaminated (30.6 %) and control (0 %) soils. Hierarchical cluster analysis (HCA) separated the isolates into two clusters with microorganisms in cluster 2 being 1.7- to 5-fold better at hydrocarbon degradation than those in cluster 1. Cluster 2 isolates belonged to the putative hydrocarbon-degrading genera; Pseudomonas, Bacillus, Arthrobacter and Brevundimonas with 57 % of these isolates being obtained from treated COTBS-contaminated soil. Overall, this study demonstrates that the potential for PAH degradation exists for the bioremediation of Hamada COTBS-contaminated environments in Libya. This represents the first report on the isolation of hydrocarbonoclastic bacteria from Libyan COTBS and COTBS-contaminated soil.

Identifying pathogenic processes by integrating microarray data with prior knowledge

PubMed Central

2014-01-01

Background It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogenic pathways are still not completely understood. Often the set of genes or proteins identified as altered in genome-wide screens show a poor overlap with canonical disease pathways. These findings are difficult to interpret, yet crucial in order to improve the understanding of the molecular processes underlying the disease progression. We present a novel method for identifying groups of connected molecules from a set of differentially expressed genes. These groups represent functional modules sharing common cellular function and involve signaling and regulatory events. Specifically, our method makes use of Bayesian statistics to identify groups of co-regulated genes based on the microarray data, where external information about molecular interactions and connections are used as priors in the group assignments. Markov chain Monte Carlo sampling is used to search for the most reliable grouping. Results Simulation results showed that the method improved the ability of identifying correct groups compared to traditional clustering, especially for small sample sizes. Applied to a microarray heart failure dataset the method found one large cluster with several genes important for the structure of the extracellular matrix and a smaller group with many genes involved in carbohydrate metabolism. The method was also applied to a microarray dataset on melanoma cancer patients with or without metastasis, where the main cluster was dominated by genes related to keratinocyte differentiation. Conclusion Our method found clusters overlapping with known pathogenic processes, but also pointed to new connections extending beyond the classical pathways. PMID:24758699

Exploring Interfacial Events in Gold-Nanocluster-Sensitized Solar Cells: Insights into the Effects of the Cluster Size and Electrolyte on Solar Cell Performance.

PubMed

Abbas, Muhammad A; Kim, Tea-Yon; Lee, Sang Uck; Kang, Yong Soo; Bang, Jin Ho

2016-01-13

Gold nanoclusters (Au NCs) with molecule-like behavior have emerged as a new light harvester in various energy conversion systems. Despite several important strides made recently, efforts toward the utilization of NCs as a light harvester have been primarily restricted to proving their potency and feasibility. In solar cell applications, ground-breaking research with a power conversion efficiency (PCE) of more than 2% has recently been reported. Because of the lack of complete characterization of metal cluster-sensitized solar cells (MCSSCs), however, comprehensive understanding of the interfacial events and limiting factors which dictate their performance remains elusive. In this regard, we provide deep insight into MCSSCs for the first time by performing in-depth electrochemical impedance spectroscopy (EIS) analysis combined with physical characterization and density functional theory (DFT) calculations of Au NCs. In particular, we focused on the effect of the size of the Au NCs and electrolytes on the performance of MCSSCs and reveal that they are significantly influential on important solar cell characteristics such as the light absorption capability, charge injection kinetics, interfacial charge recombination, and charge transport. Besides offering comprehensive insights, this work represents an important stepping stone toward the development of MCSSCs by accomplishing a new PCE record of 3.8%.

Multivariate analysis in a genetic divergence study of Psidium guajava.

PubMed

Nogueira, A M; Ferreira, M F S; Guilhen, J H S; Ferreira, A

2014-12-18

The family Myrtaceae is widespread in the Atlantic Forest and is well-represented in the Espírito Santo State in Brazil. In the genus Psidium of this family, guava (Psidium guajava L.) is the most economically important species. Guava is widely cultivated in tropical and subtropical countries; however, the widespread cultivation of only a small number of guava tree cultivars may cause the genetic vulnerability of this crop, making the search for promising genotypes in natural populations important for breeding programs and conservation. In this study, the genetic diversity of 66 guava trees sampled in the southern region of Espírito Santo and in Caparaó, MG, Brazil were evaluated. A total of 28 morphological descriptors (11 quantitative and 17 multicategorical) and 18 microsatellite markers were used. Principal component, discriminant and cluster analyses, descriptive analyses, and genetic diversity analyses using simple sequence repeats were performed. Discrimination of accessions using molecular markers resulted in clustering of genotypes of the same origin, which was not observed using morphological data. Genetic diversity was detected between and within the localities evaluated, regardless of the methodology used. Genetic differentiation among the populations using morphological and molecular data indicated the importance of the study area for species conservation, genetic erosion estimation, and exploitation in breeding programs.

Quantitative chemical tagging, stellar ages and the chemo-dynamical evolution of the Galactic disc

NASA Astrophysics Data System (ADS)

Mitschang, A. W.; De Silva, G.; Zucker, D. B.; Anguiano, B.; Bensby, T.; Feltzing, S.

2014-03-01

The early science results from the new generation of high-resolution stellar spectroscopic surveys, such as Galactic Archaeology with HERMES (GALAH) and the Gaia European Southern Observatory survey (Gaia-ESO), will represent major milestones in the quest to chemically tag the Galaxy. Yet this technique to reconstruct dispersed coeval stellar groups has remained largely untested until recently. We build on previous work that developed an empirical chemical tagging probability function, which describes the likelihood that two field stars are conatal, that is, they were formed in the same cluster environment. In this work, we perform the first ever blind chemical tagging experiment, i.e. tagging stars with no known or otherwise discernible associations, on a sample of 714 disc field stars with a number of high-quality high-resolution homogeneous metal abundance measurements. We present evidence that chemical tagging of field stars does identify coeval groups of stars, yet these groups may not represent distinct formation sites, e.g. as in dissolved open clusters, as previously thought. Our results point to several important conclusions, among them that group finding will be limited strictly to chemical abundance space, e.g. stellar ages, kinematics, colours, temperature and surface gravity do not enhance the detectability of groups. We also demonstrate that in addition to its role in probing the chemical enrichment and kinematic history of the Galactic disc, chemical tagging represents a powerful new stellar age determination technique.

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

PubMed

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast

USGS Publications Warehouse

Field, Edward; Milner, Kevin R.; Hardebeck, Jeanne L.; Page, Morgan T.; van der Elst, Nicholas; Jordan, Thomas H.; Michael, Andrew J.; Shaw, Bruce E.; Werner, Maximillan J.

2017-01-01

We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of M≥2.5 events, conditioned on any prior M≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as will any subsequent version or competing model, potential usefulness needs to be considered in the context of actual applications.

Graph-Based Object Class Discovery

NASA Astrophysics Data System (ADS)

Xia, Shengping; Hancock, Edwin R.

We are interested in the problem of discovering the set of object classes present in a database of images using a weakly supervised graph-based framework. Rather than making use of the ”Bag-of-Features (BoF)” approach widely used in current work on object recognition, we represent each image by a graph using a group of selected local invariant features. Using local feature matching and iterative Procrustes alignment, we perform graph matching and compute a similarity measure. Borrowing the idea of query expansion , we develop a similarity propagation based graph clustering (SPGC) method. Using this method class specific clusters of the graphs can be obtained. Such a cluster can be generally represented by using a higher level graph model whose vertices are the clustered graphs, and the edge weights are determined by the pairwise similarity measure. Experiments are performed on a dataset, in which the number of images increases from 1 to 50K and the number of objects increases from 1 to over 500. Some objects have been discovered with total recall and a precision 1 in a single cluster.

Application of Classification Methods for Forecasting Mid-Term Power Load Patterns

NASA Astrophysics Data System (ADS)

Piao, Minghao; Lee, Heon Gyu; Park, Jin Hyoung; Ryu, Keun Ho

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper consists of three stages: (i) data preprocessing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

Reducing the Volume of NASA Earth-Science Data

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Braverman, Amy J.; Guillaume, Alexandre

2010-01-01

A computer program reduces data generated by NASA Earth-science missions into representative clusters characterized by centroids and membership information, thereby reducing the large volume of data to a level more amenable to analysis. The program effects an autonomous data-reduction/clustering process to produce a representative distribution and joint relationships of the data, without assuming a specific type of distribution and relationship and without resorting to domain-specific knowledge about the data. The program implements a combination of a data-reduction algorithm known as the entropy-constrained vector quantization (ECVQ) and an optimization algorithm known as the differential evolution (DE). The combination of algorithms generates the Pareto front of clustering solutions that presents the compromise between the quality of the reduced data and the degree of reduction. Similar prior data-reduction computer programs utilize only a clustering algorithm, the parameters of which are tuned manually by users. In the present program, autonomous optimization of the parameters by means of the DE supplants the manual tuning of the parameters. Thus, the program determines the best set of clustering solutions without human intervention.

Observing Globular Cluster RR Lyrae Variables with the BYU West Mountain Observatory

NASA Astrophysics Data System (ADS)

Jeffery, E. J.; Joner, M. D.

2016-06-01

We have utilized the 0.9-meter telescope of the Brigham Young University West Mountain Observatory to secure data on six northern hemisphere globular clusters. Here we present representative observations of RR Lyrae stars located in these clusters, including light curves. We compare light curves produced using both DAOPHOT and ISIS software packages. Light curve fitting is done with FITLC. We find that for well-separated stars, DAOPHOT and ISIS provide comparable results. However, for stars within the cluster core, ISIS provides superior results. These improved techniques will allow us to better measure the properties of cluster variable stars.

Cluster analysis of molecular simulation trajectories for systems where both conformation and orientation of the sampled states are important.

PubMed

Abramyan, Tigran M; Snyder, James A; Thyparambil, Aby A; Stuart, Steven J; Latour, Robert A

2016-08-05

Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed-state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Joint scaling properties of Sunyaev-Zel'dovich and optical richness observables in an optically-selected galaxy cluster sample

NASA Astrophysics Data System (ADS)

Greer, Christopher Holland

Galaxy cluster abundance measurements are an important tool used to study the universe as a whole. The advent of multiple large-area galaxy cluster surveys across multiple ensures that cluster measurements will play a key role in understanding the dark energy currently thought to be accelerating the universe. The main systematic limitation at the moment is the understanding of the observable-mass relation. Recent theoretical work has shown that combining samples of clusters from surveys at different wavelengths can mitigate this systematic limitation. Precise measurements of the scatter in the observable-mass relation can lead to further improvements. We present Combined Array for Research in Millimeter-wave Astronomy (CARMA) observations of the Sunyaev-Zel'dovich (SZ) signal for 28 galaxy clusters selected from the Sloan Digital Sky Survey (SDSS) maxBCG catalog. This cluster sample represents a complete, volume-limited sample of the richest galaxy clusters in the SDSS between redshifts 0.2 ≥ z ≥ 0.3, as measured by the RedMaPPer algorithm being developed for the Dark Energy Survey (DES; Rykoff et al. 2012). We develop a formalism that uses the cluster abundance in tandem with the galaxy richness measurements from SDSS and the SZ signal measurements from CARMA to calibrate the SZ and optical observable-mass relations. We find that the scatter in richness at fixed mass is σlog λ| M = 0.24+0.09-0.07 using SZ signal calculated by integrating a cluster pressure profile to a radius of 1 Mpc at the redshift of the cluster. We also calculate the SZ signal at R500 and find that the choice of scaling relation used to determined R500 has a non-trivial effect on the constraints of the observable-mass relationship. Finally, we investigate the source of disagreement between the positions of the SZ signal and SDSS Brightest Cluster Galaxies (BCGs). Improvements to the richness calculator that account for blue BCGs in the cores of cool-core X-ray clusters, as well as multiple BCGs in merger situations will help reduce σ log λ|M further. This work is the first independent calibration of the RedMaPPer algorithm that is being designed for the Dark Energy Survey.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets. PMID:25350106

Topic modeling for cluster analysis of large biological and medical datasets.

PubMed

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

The potential of clustering methods to define intersection test scenarios: Assessing real-life performance of AEB.

PubMed

Sander, Ulrich; Lubbe, Nils

2018-04-01

Intersection accidents are frequent and harmful. The accident types 'straight crossing path' (SCP), 'left turn across path - oncoming direction' (LTAP/OD), and 'left-turn across path - lateral direction' (LTAP/LD) represent around 95% of all intersection accidents and one-third of all police-reported car-to-car accidents in Germany. The European New Car Assessment Program (Euro NCAP) have announced that intersection scenarios will be included in their rating from 2020; however, how these scenarios are to be tested has not been defined. This study investigates whether clustering methods can be used to identify a small number of test scenarios sufficiently representative of the accident dataset to evaluate Intersection Automated Emergency Braking (AEB). Data from the German In-Depth Accident Study (GIDAS) and the GIDAS-based Pre-Crash Matrix (PCM) from 1999 to 2016, containing 784 SCP and 453 LTAP/OD accidents, were analyzed with principal component methods to identify variables that account for the relevant total variances of the sample. Three different methods for data clustering were applied to each of the accident types, two similarity-based approaches, namely Hierarchical Clustering (HC) and Partitioning Around Medoids (PAM), and the probability-based Latent Class Clustering (LCC). The optimum number of clusters was derived for HC and PAM with the silhouette method. The PAM algorithm was both initiated with random start medoid selection and medoids from HC. For LCC, the Bayesian Information Criterion (BIC) was used to determine the optimal number of clusters. Test scenarios were defined from optimal cluster medoids weighted by their real-life representation in GIDAS. The set of variables for clustering was further varied to investigate the influence of variable type and character. We quantified how accurately each cluster variation represents real-life AEB performance using pre-crash simulations with PCM data and a generic algorithm for AEB intervention. The usage of different sets of clustering variables resulted in substantially different numbers of clusters. The stability of the resulting clusters increased with prioritization of categorical over continuous variables. For each different set of cluster variables, a strong in-cluster variance of avoided versus non-avoided accidents for the specified Intersection AEB was present. The medoids did not predict the most common Intersection AEB behavior in each cluster. Despite thorough analysis using various cluster methods and variable sets, it was impossible to reduce the diversity of intersection accidents into a set of test scenarios without compromising the ability to predict real-life performance of Intersection AEB. Although this does not imply that other methods cannot succeed, it was observed that small changes in the definition of a scenario resulted in a different avoidance outcome. Therefore, we suggest using limited physical testing to validate more extensive virtual simulations to evaluate vehicle safety. Copyright © 2018 Elsevier Ltd. All rights reserved.

Genotypic relationships among strains classified under the (Pasteurella) haemolytica-complex as indicated by ribotyping and multilocus enzyme electrophoresis.

PubMed

Angen, O; Caugant, D A; Olsen, J E; Bisgaard, M

1997-10-01

Two-hundred and one strains classified under the (Pasteurella) haemolytica-complex isolated from cattle, sheep, deer, pigs, hares and rabbits were investigated by ribotyping. Fifty-nine of these strains were selected for further studies using multilocus enzyme electrophoresis (MEE). A correlation between the clusters identified by ribotyping and MEE was demonstrated and the results furthermore indicated that a genetic basis exists for most clusters previously outlined by the use of quantitative evaluation of phenotypic data. The taxonomic relevance of ornithine decarboxylase and fermentation of L-arabinose, D-sorbitol and glucosides for taxonomic delineation within the (P.) haemolytica-complex was supported. A taxonomic importance was further indicated for ONPG, ONPX, ONPF, meso-inositol, D-xylose, maltose, dextrine and NPG in relation to some of the taxa. Within the porcine taxon 15, however, differences in ornithine decarboxylase did not correspond to genetic clusters. Six lineages were revealed by MEE. Lineage A contained electrophoretic types (ETs) representing biogroups 1, 3A-3H, 8A and 9, indicating a genetic relationship between these groups--an observation which was supported by ribotyping. Lineage B included biogroup 8D, 3 strains from biogroup 10 and a single strain from biogroup 1 and taxon 18/biovar 1. Lineage C contained strains allocated to biogroup 6 from ruminants and the porcine taxon 15. The similarity between these two groups was accentuated by ribotyping. Lineage D and the single isolate in lineage E contained strains allocated to biogroups 7, 10, 8B and 8C, in addition to single strains from biogroups 6 and 9. The same strains were found in the heterogenous ribotype cluster 17. Lineage F contained strains representing the leprine taxon 20 and the ruminant (P.) granulomatis. Ribotyping indicated that the ruminant biogroup 3J was affiliated with both taxon 20 and (P.) granulomatis.

Climbing the Ladder of Star Formation Feedback

NASA Astrophysics Data System (ADS)

Frank, Adam

2012-10-01

While much is understood about isolated star formation, the opposite is true for star formation in clusters of both low and high mass. In particular the mechanisms by which many coevally formed stars affect their parent cloud environment remains poorly characterized. Fundamental questions such as interplay between multiple outflows, ionization fronts and turbulence are just beginning to be fully articulated. Distinguishing between the nature of feedback in clusters of different mass is also critical. In high mass clusters O stars are expected to dominate energetics while in low mass clusters multiple collimated outflows may represent the dominant feedback mechanism. Thus the issue of feedback modalities in clusters of different masses represents one of the major challenges to the next generation of star formation studies. In this proposal we seek to carry forward a focused theoretical study of feedback in both low and high-mass cluster environments with direct connections to observations. Using a state-of-the-art Adaptive Mesh Refinement MHD multi-physics code {developed by our group} we propose two computational studies: {1} multiple, interacting outflows and their role in altering the properties of a parent low mass cluster {2} Poorly collimated outburst/outflows from massive star{s} and their effect on high mass cluster star forming environments. In both cases we will use initial conditions derived from high-resolution AMR MHD simulations of cloud/cluster formation. Synthetic observations derived from the simulations {in a variety of emission lines from ions to atoms to molecules} will allow for direct contact with HST and other star formation databases.

Comparative Genomic Hybridization Analysis of Two Predominant Nordic Group I (Proteolytic) Clostridium botulinum Type B Clusters▿ †

PubMed Central

Lindström, Miia; Hinderink, Katja; Somervuo, Panu; Kiviniemi, Katri; Nevas, Mari; Chen, Ying; Auvinen, Petri; Carter, Andrew T.; Mason, David R.; Peck, Michael W.; Korkeala, Hannu

2009-01-01

Comparative genomic hybridization analysis of 32 Nordic group I Clostridium botulinum type B strains isolated from various sources revealed two homogeneous clusters, clusters BI and BII. The type B strains differed from reference strain ATCC 3502 by 413 coding sequence (CDS) probes, sharing 88% of all the ATCC 3502 genes represented on the microarray. The two Nordic type B clusters differed from each other by their response to 145 CDS probes related mainly to transport and binding, adaptive mechanisms, fatty acid biosynthesis, the cell membranes, bacteriophages, and transposon-related elements. The most prominent differences between the two clusters were related to resistance to toxic compounds frequently found in the environment, such as arsenic and cadmium, reflecting different adaptive responses in the evolution of the two clusters. Other relatively variable CDS groups were related to surface structures and the gram-positive cell wall, suggesting that the two clusters possess different antigenic properties. All the type B strains carried CDSs putatively related to capsule formation, which may play a role in adaptation to different environmental and clinical niches. Sequencing showed that representative strains of the two type B clusters both carried subtype B2 neurotoxin genes. As many of the type B strains studied have been isolated from foods or associated with botulism, it is expected that the two group I C. botulinum type B clusters present a public health hazard in Nordic countries. Knowing the genetic and physiological markers of these clusters will assist in targeting control measures against these pathogens. PMID:19270141

Task shifting of frontline community health workers for cardiovascular risk reduction: design and rationale of a cluster randomised controlled trial (DISHA study) in India.

PubMed

Jeemon, Panniyammakal; Narayanan, Gitanjali; Kondal, Dimple; Kahol, Kashvi; Bharadwaj, Ashok; Purty, Anil; Negi, Prakash; Ladhani, Sulaiman; Sanghvi, Jyoti; Singh, Kuldeep; Kapoor, Deksha; Sobti, Nidhi; Lall, Dorothy; Manimunda, Sathyaprakash; Dwivedi, Supriya; Toteja, Gurudyal; Prabhakaran, Dorairaj

2016-03-15

Effective task-shifting interventions targeted at reducing the global cardiovascular disease (CVD) epidemic in low and middle-income countries (LMICs) are urgently needed. DISHA is a cluster randomised controlled trial conducted across 10 sites (5 in phase 1 and 5 in phase 2) in India in 120 clusters. At each site, 12 clusters were randomly selected from a district. A cluster is defined as a small village with 250-300 households and well defined geographical boundaries. They were then randomly allocated to intervention and control clusters in a 1:1 allocation sequence. If any of the intervention and control clusters were <10 km apart, one was dropped and replaced with another randomly selected cluster from the same district. The study included a representative baseline cross-sectional survey, development of a structured intervention model, delivery of intervention for a minimum period of 18 months by trained frontline health workers (mainly Anganwadi workers and ASHA workers) and a post intervention survey in a representative sample. The study staff had no information on intervention allocation until the completion of the baseline survey. In order to ensure comparability of data across sites, the DISHA study follows a common protocol and manual of operation with standardized measurement techniques. Our study is the largest community based cluster randomised trial in low and middle-income country settings designed to test the effectiveness of 'task shifting' interventions involving frontline health workers for cardiovascular risk reduction. CTRI/2013/10/004049 . Registered 7 October 2013.

Customized recommendations for production management clusters of North American automatic milking systems.

PubMed

Tremblay, Marlène; Hess, Justin P; Christenson, Brock M; McIntyre, Kolby K; Smink, Ben; van der Kamp, Arjen J; de Jong, Lisanne G; Döpfer, Dörte

2016-07-01

Automatic milking systems (AMS) are implemented in a variety of situations and environments. Consequently, there is a need to characterize individual farming practices and regional challenges to streamline management advice and objectives for producers. Benchmarking is often used in the dairy industry to compare farms by computing percentile ranks of the production values of groups of farms. Grouping for conventional benchmarking is commonly limited to the use of a few factors such as farms' geographic region or breed of cattle. We hypothesized that herds' production data and management information could be clustered in a meaningful way using cluster analysis and that this clustering approach would yield better peer groups of farms than benchmarking methods based on criteria such as country, region, breed, or breed and region. By applying mixed latent-class model-based cluster analysis to 529 North American AMS dairy farms with respect to 18 significant risk factors, 6 clusters were identified. Each cluster (i.e., peer group) represented unique management styles, challenges, and production patterns. When compared with peer groups based on criteria similar to the conventional benchmarking standards, the 6 clusters better predicted milk produced (kilograms) per robot per day. Each cluster represented a unique management and production pattern that requires specialized advice. For example, cluster 1 farms were those that recently installed AMS robots, whereas cluster 3 farms (the most northern farms) fed high amounts of concentrates through the robot to compensate for low-energy feed in the bunk. In addition to general recommendations for farms within a cluster, individual farms can generate their own specific goals by comparing themselves to farms within their cluster. This is very comparable to benchmarking but adds the specific characteristics of the peer group, resulting in better farm management advice. The improvement that cluster analysis allows for is characterized by the multivariable approach and the fact that comparisons between production units can be accomplished within a cluster and between clusters as a choice. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Deficits in Category Learning in Older Adults: Rule-Based Versus Clustering Accounts

PubMed Central

2017-01-01

Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory, and often on the process of learning relationships through trial and error. Categorization studies allow researchers to more accurately characterize age differences in cognition: whether older adults show declines in the way in which they represent categories with simple rules or declines in representing categories by similarity to past examples. In the current study, young and older adults participated in a set of classic category learning problems, which allowed us to distinguish between three hypotheses: (a) rule-complexity: categories were represented exclusively with rules and older adults had differential difficulty when more complex rules were required, (b) rule-specific: categories could be represented either by rules or by similarity, and there were age deficits in using rules, and (c) clustering: similarity was mainly used and older adults constructed a less-detailed representation by lumping more items into fewer clusters. The ordinal levels of performance across different conditions argued against rule-complexity, as older adults showed greater deficits on less complex categories. The data also provided evidence against rule-specificity, as single-dimensional rules could not explain age declines. Instead, computational modeling of the data indicated that older adults utilized fewer conceptual clusters of items in memory than did young adults. PMID:28816474

Receptive field optimisation and supervision of a fuzzy spiking neural network.

PubMed

Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather

2011-04-01

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

Measurement of surface roughness changes of unpolished and polished enamel following erosion

PubMed Central

Austin, Rupert S.; Parkinson, Charles R.; Hasan, Adam; Bartlett, David W.

2017-01-01

Objectives To determine if Sa roughness data from measuring one central location of unpolished and polished enamel were representative of the overall surfaces before and after erosion. Methods Twenty human enamel sections (4x4 mm) were embedded in bis-acryl composite and randomised to either a native or polishing enamel preparation protocol. Enamel samples were subjected to an acid challenge (15 minutes 100 mL orange juice, pH 3.2, titratable acidity 41.3mmol OH/L, 62.5 rpm agitation, repeated for three cycles). Median (IQR) surface roughness [Sa] was measured at baseline and after erosion from both a centralised cluster and four peripheral clusters. Within each cluster, five smaller areas (0.04 mm2) provided the Sa roughness data. Results For both unpolished and polished enamel samples there were no significant differences between measuring one central cluster or four peripheral clusters, before and after erosion. For unpolished enamel the single central cluster had a median (IQR) Sa roughness of 1.45 (2.58) μm and the four peripheral clusters had a median (IQR) of 1.32 (4.86) μm before erosion; after erosion there were statistically significant reductions to 0.38 (0.35) μm and 0.34 (0.49) μm respectively (p<0.0001). Polished enamel had a median (IQR) Sa roughness 0.04 (0.17) μm for the single central cluster and 0.05 (0.15) μm for the four peripheral clusters which statistically significantly increased after erosion to 0.27 (0.08) μm for both (p<0.0001). Conclusion Measuring one central cluster of unpolished and polished enamel was representative of the overall enamel surface roughness, before and after erosion. PMID:28771562

Extension of the classical classification of β-turns

PubMed Central

de Brevern, Alexandre G.

2016-01-01

The functional properties of a protein primarily depend on its three-dimensional (3D) structure. These properties have classically been assigned, visualized and analysed on the basis of protein secondary structures. The β-turn is the third most important secondary structure after helices and β-strands. β-turns have been classified according to the values of the dihedral angles φ and ψ of the central residue. Conventionally, eight different types of β-turns have been defined, whereas those that cannot be defined are classified as type IV β-turns. This classification remains the most widely used. Nonetheless, the miscellaneous type IV β-turns represent 1/3rd of β-turn residues. An unsupervised specific clustering approach was designed to search for recurrent new turns in the type IV category. The classical rules of β-turn type assignment were central to the approach. The four most frequently occurring clusters defined the new β-turn types. Unexpectedly, these types, designated IV1, IV2, IV3 and IV4, represent half of the type IV β-turns and occur more frequently than many of the previously established types. These types show convincing particularities, in terms of both structures and sequences that allow for the classical β-turn classification to be extended for the first time in 25 years. PMID:27627963

Extension of the classical classification of β-turns.

PubMed

de Brevern, Alexandre G

2016-09-15

The functional properties of a protein primarily depend on its three-dimensional (3D) structure. These properties have classically been assigned, visualized and analysed on the basis of protein secondary structures. The β-turn is the third most important secondary structure after helices and β-strands. β-turns have been classified according to the values of the dihedral angles φ and ψ of the central residue. Conventionally, eight different types of β-turns have been defined, whereas those that cannot be defined are classified as type IV β-turns. This classification remains the most widely used. Nonetheless, the miscellaneous type IV β-turns represent 1/3(rd) of β-turn residues. An unsupervised specific clustering approach was designed to search for recurrent new turns in the type IV category. The classical rules of β-turn type assignment were central to the approach. The four most frequently occurring clusters defined the new β-turn types. Unexpectedly, these types, designated IV1, IV2, IV3 and IV4, represent half of the type IV β-turns and occur more frequently than many of the previously established types. These types show convincing particularities, in terms of both structures and sequences that allow for the classical β-turn classification to be extended for the first time in 25 years.

A Novel Family of Sequence-specific Endoribonucleases Associated with the Clustered Regularly Interspaced Short Palindromic Repeats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beloglazova, Natalia; Brown, Greg; Zimmerman, Matthew D.

Clustered regularly interspaced short palindromic repeats (CRISPRs) together with the associated CAS proteins protect microbial cells from invasion by foreign genetic elements using presently unknown molecular mechanisms. All CRISPR systems contain proteins of the CAS2 family, suggesting that these uncharacterized proteins play a central role in this process. Here we show that the CAS2 proteins represent a novel family of endoribonucleases. Six purified CAS2 proteins from diverse organisms cleaved single-stranded RNAs preferentially within U-rich regions. A representative CAS2 enzyme, SSO1404 from Sulfolobus solfataricus, cleaved the phosphodiester linkage on the 3'-side and generated 5'-phosphate- and 3'-hydroxyl-terminated oligonucleotides. The crystal structure ofmore » SSO1404 was solved at 1.6{angstrom} resolution revealing the first ribonuclease with a ferredoxin-like fold. Mutagenesis of SSO1404 identified six residues (Tyr-9, Asp-10, Arg-17, Arg-19, Arg-31, and Phe-37) that are important for enzymatic activity and suggested that Asp-10 might be the principal catalytic residue. Thus, CAS2 proteins are sequence-specific endoribonucleases, and we propose that their role in the CRISPR-mediated anti-phage defense might involve degradation of phage or cellular mRNAs.« less

Nonribosomal peptides and polyketides of Burkholderia: new compounds potentially implicated in biocontrol and pharmaceuticals.

PubMed

Esmaeel, Qassim; Pupin, Maude; Jacques, Philippe; Leclère, Valérie

2017-05-25

Bacteria belonging to the genus Burkholderia live in various ecological niches and present a significant role in the environments through the excretion of a wide variety of secondary metabolites including modular nonribosomal peptides (NRPs) and polyketides (PKs). These metabolites represent a widely distributed biomedically and biocontrol important class of natural products including antibiotics, siderophores, and anticancers as well as biopesticides that are considered as a novel source that can be used to defend ecological niche from competitors and to promote plant growth. The aim of this review is to present all NRPs produced or potentially produced by strains of Burkholderia, as NRPs represent a major source of active compounds implicated in biocontrol. The review is a compilation of results from a large screening we have performed on 48 complete sequenced genomes available in NCBI to identify NRPS gene clusters, and data found in the literature mainly because some interesting compounds are produced by strains not yet sequenced. In addition to NRPs, hybrids NRPs/PKs are also included. Specific features about biosynthetic gene clusters and structures of the modular enzymes responsible for the synthesis, the biological activities, and the potential uses in agriculture and pharmaceutical of NRPs and hybrids NRPs/PKs will also be discussed.

Environmental, health and economic conditions perceived by 50 rural communities in Bangladesh.

PubMed

Ohtsuka, Ryutaro; Inaoka, Tsukasa; Moji, Kazuhiko; Karim, Enamul; Yoshinaga, Mari

2002-12-01

For randomly selected 50 villages in Bangladesh, an interview survey with a structured questionnaire was conducted to reveal their perception on the environmental, health and economic conditions at present and for the past 10-year change. The eight following items were analyzed in this paper: air pollution and water pollution, which represent environmental conditions with close relation to health conditions, soil degradation and deforestation, which represent environmental conditions with close relation to economic conditions, epidemic diseases and malnutrition, which represent health conditions, and poverty and jobless, which represent economic conditions. Among the 50 villages, deforestation was most frequently perceived serious at present and worsened in the past 10 years. Of the remaining seven items, those related to economic conditions were more seriously perceived than those related to health and environmental conditions. As revealed by the cluster analysis for the inter-item relations, epidemic diseases, which formed the same cluster with the environmental items, were recognized less serious whereas malnutrition, which formed the same cluster with the economic items, was recognized more serious. These findings are useful not only for rural development programs but also for mitigation programs toward health and environmental hazards in Bangladesh.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Contreras Pena, C.; Catelan, M.; Grundahl, F.

We present BV photometry of the Galactic globular cluster NGC 6402 (M14), based on 65 V frames and 67 B frames, reaching two magnitudes below the turnoff level. This represents, to the best of our knowledge, the deepest color-magnitude diagram (CMD) of NGC 6402 available in the literature. Statistical decontamination of field stars as well as differential reddening corrections are performed in order to derive a precise ridgeline and hence physical parameters of the cluster. We discuss previous attempts at deriving a reddening value for the cluster, and argue in favor of a value E(B - V) = 0.57 {+-}more » 0.02, which is significantly higher than indicated by either the Burstein and Heiles or Schlegel et al. (corrected according to Bonifacio et al.) interstellar dust maps. Differential reddening across the face of the cluster, which we find to be present at the level of {Delta}E(B - V) Almost-Equal-To 0.17 mag, is taken into account in our analysis. We measure several metallicity indicators based on the position of the red giant branch (RGB) in the cluster CMD. These give a metallicity of [Fe/H] = -1.38 {+-} 0.07 on the Zinn and West scale and [Fe/H] = -1.28 {+-} 0.08 on the new Carretta et al. (UVES) scale. We also provide measurements of other important photometric parameters for this cluster, including the position of the RGB luminosity function ''bump'' and the horizontal branch morphology. We compare the NGC 6402 ridgeline with that of NGC 5904 (M5) derived by Sandquist et al., and find evidence that NGC 6402 and M5 have approximately the same age to within the uncertainties, although the possibility that M14 may be slightly older cannot be ruled out.« less

Stable clustering and the resolution of dissipationless cosmological N-body simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sylos Labini, Francesco

2017-10-01

The determination of the resolution of cosmological N-body simulations, I.e. the range of scales in which quantities measured in them represent accurately the continuum limit, is an important open question. We address it here using scale-free models, for which self-similarity provides a powerful tool to control resolution. Such models also provide a robust testing ground for the so-called stable clustering approximation, which gives simple predictions for them. Studying large N-body simulations of such models with different force smoothing, we find that these two issues are in fact very closely related: our conclusion is that the accuracy of two-point statistics in the non-linear regime starts to degrade strongly around the scale at which their behaviour deviates from that predicted by the stable clustering hypothesis. Physically the association of the two scales is in fact simple to understand: stable clustering fails to be a good approximation when there are strong interactions of structures (in particular merging) and it is precisely such non-linear processes which are sensitive to fluctuations at the smaller scales affected by discretization. Resolution may be further degraded if the short distance gravitational smoothing scale is larger than the scale to which stable clustering can propagate. We examine in detail the very different conclusions of studies by Smith et al. and Widrow et al. and find that the strong deviations from stable clustering reported by these works are the results of over-optimistic assumptions about scales resolved accurately by the measured power spectra, and the reliance on Fourier space analysis. We emphasize the much poorer resolution obtained with the power spectrum compared to the two-point correlation function.

Clustering of Multiple Risk Behaviors Among a Sample of 18-Year-Old Australians and Associations With Mental Health Outcomes: A Latent Class Analysis.

PubMed

Champion, Katrina E; Mather, Marius; Spring, Bonnie; Kay-Lambkin, Frances; Teesson, Maree; Newton, Nicola C

2018-01-01

Risk behaviors commonly co-occur, typically emerge in adolescence, and become entrenched by adulthood. This study investigated the clustering of established (physical inactivity, diet, smoking, and alcohol use) and emerging (sedentary behavior and sleep) chronic disease risk factors among young Australian adults, and examined how clusters relate to mental health. The sample was derived from the long-term follow-up of a cohort of Australians. Participants were initially recruited at school as part of a cluster randomized controlled trial. A total of 853 participants (M age  = 18.88 years, SD = 0.42) completed an online self-report survey as part of the 5-year follow-up for the RCT. The survey assessed six behaviors (binge drinking and smoking in the past 6 months, moderate-to-vigorous physical activity/week, sitting time/day, fruit and vegetable intake/day, and sleep duration/night). Each behavior was represented by a dichotomous variable reflecting adherence to national guidelines. Exploratory analyses were conducted. Clusters were identified using latent class analysis. Three classes emerged: "moderate risk" (moderately likely to binge drink and not eat enough fruit, high probability of insufficient vegetable intake; Class 1, 52%); "inactive, non-smokers" (high probabilities of not meeting guidelines for physical activity, sitting time and fruit/vegetable consumption, very low probability of smoking; Class 2, 24%), and "smokers and binge drinkers" (high rates of smoking and binge drinking, poor fruit/vegetable intake; Class 3, 24%). There were significant differences between the classes in terms of psychological distress ( p  = 0.003), depression ( p  < 0.001), and anxiety ( p  = 0.003). Specifically, Class 3 ("smokers and binge drinkers") showed higher levels of distress, depression, and anxiety than Class 1 ("moderate risk"), while Class 2 ("inactive, non-smokers") had greater depression than the "moderate risk" group. Results indicate that risk behaviors are prevalent and clustered in 18-year old Australians. Mental health symptoms were significantly greater among the two classes that were characterized by high probabilities of engaging in multiple risk behaviors (Classes 2 and 3). An examination of the clustering of lifestyle risk behaviors is important to guide the development of preventive interventions. Our findings reinforce the importance of delivering multiple health interventions to reduce disease risk and improve mental well-being.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Probabilistic distributions of pinhole defects in atomic layer deposited films on polymeric substrates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yersak, Alexander S., E-mail: alexander.yersak@colorado.edu; Lee, Yung-Cheng

Pinhole defects in atomic layer deposition (ALD) coatings were measured in an area of 30 cm{sup 2} in an ALD reactor, and these defects were represented by a probabilistic cluster model instead of a single defect density value with number of defects over area. With the probabilistic cluster model, the pinhole defects were simulated over a manufacturing scale surface area of ∼1 m{sup 2}. Large-area pinhole defect simulations were used to develop an improved and enhanced design method for ALD-based devices. A flexible thermal ground plane (FTGP) device requiring ALD hermetic coatings was used as an example. Using a single defectmore » density value, it was determined that for an application with operation temperatures higher than 60 °C, the FTGP device would not be possible. The new probabilistic cluster model shows that up to 40.3% of the FTGP would be acceptable. With this new approach the manufacturing yield of ALD-enabled or other thin film based devices with different design configurations can be determined. It is important to guide process optimization and control and design for manufacturability.« less

Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering

PubMed Central

Wright, Margaret J.; Thompson, Paul M.; Vidal, René

2015-01-01

We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748

Cluster Dynamical Mean Field Methods and the Momentum-selective Mott transition

NASA Astrophysics Data System (ADS)

Gull, Emanuel

2011-03-01

Innovations in methodology and computational power have enabled cluster dynamical mean field calculations of the Hubbard model with interaction strengths and band structures representative of high temperature copper oxide superconductors, for clusters large enough that the thermodyamic limit behavior may be determined. We present the methods and show how extrapolations to the thermodynamic limit work in practice. We show that the Hubbard model with next-nearest neighbor hopping at intermediate interaction strength captures much of the exotic behavior characteristic of the high temperature superconductors. An important feature of the results is a pseudogap for hole doping but not for electron doping. The pseudogap regime is characterized by a gap for momenta near Brillouin zone face and gapless behavior near the zone diagonal. for dopings outside of the pseudogap regime we find scattering rates which vary around the fermi surface in a way consistent with recent transport measurements. Using the maximum entropy method we calculate spectra, self-energies, and response functions for Raman spectroscopy and optical conductivities, finding results also in good agreement with experiment. Olivier Parcollet, Philipp Werner, Nan Lin, Michel Ferrero, Antoine Georges, Andrew J. Millis; NSF-DMR-0705847.

Robust X-ray angular correlations for the study of meso-structures

DOE PAGES

Lhermitte, Julien R.; Tian, Cheng; Stein, Aaron; ...

2017-05-08

As self-assembling nanomaterials become more sophisticated, it is becoming increasingly important to measure the structural order of finite-sized assemblies of nano-objects. These mesoscale clusters represent an acute challenge to conventional structural probes, owing to the range of implicated size scales (10 nm to several micrometres), the weak scattering signal and the dynamic nature of meso-clusters in native solution environments. The high X-ray flux and coherence of modern synchrotrons present an opportunity to extract structural information from these challenging systems, but conventional ensemble X-ray scattering averages out crucial information about local particle configurations. Conversely, a single meso-cluster scatters too weakly tomore » recover the full diffraction pattern. Using X-ray angular cross-correlation analysis, it is possible to combine multiple noisy measurements to obtain robust structural information. This paper explores the key theoretical limits and experimental challenges that constrain the application of these methods to probing structural order in real nanomaterials. A metric is presented to quantify the signal-to-noise ratio of angular correlations, and it is used to identify several experimental artifacts that arise. In particular, it is found that background scattering, data masking and inter-cluster interference profoundly affect the quality of correlation analyses. A robust workflow is demonstrated for mitigating these effects and extracting reliable angular correlations from realistic experimental data.« less

Increasing the source/sink ratio in Vitis vinifera (cv Sangiovese) induces extensive transcriptome reprogramming and modifies berry ripening

PubMed Central

2011-01-01

Background Cluster thinning is an agronomic practice in which a proportion of berry clusters are removed from the vine to increase the source/sink ratio and improve the quality of the remaining berries. Until now no transcriptomic data have been reported describing the mechanisms that underlie the agronomic and biochemical effects of thinning. Results We profiled the transcriptome of Vitis vinifera cv. Sangiovese berries before and after thinning at veraison using a genome-wide microarray representing all grapevine genes listed in the latest V1 gene prediction. Thinning increased the source/sink ratio from 0.6 to 1.2 m2 leaf area per kg of berries and boosted the sugar and anthocyanin content at harvest. Extensive transcriptome remodeling was observed in thinned vines 2 weeks after thinning and at ripening. This included the enhanced modulation of genes that are normally regulated during berry development and the induction of a large set of genes that are not usually expressed. Conclusion Cluster thinning has a profound effect on several important cellular processes and metabolic pathways including carbohydrate metabolism and the synthesis and transport of secondary products. The integrated agronomic, biochemical and transcriptomic data revealed that the positive impact of cluster thinning on final berry composition reflects a much more complex outcome than simply enhancing the normal ripening process. PMID:22192855

An assessment of the effects of cell size on AGNPS modeling of watershed runoff

USGS Publications Warehouse

Wu, S.-S.; Usery, E.L.; Finn, M.P.; Bosch, D.D.

2008-01-01

This study investigates the changes in simulated watershed runoff from the Agricultural NonPoint Source (AGNPS) pollution model as a function of model input cell size resolution for eight different cell sizes (30 m, 60 m, 120 m, 210 m, 240 m, 480 m, 960 m, and 1920 m) for the Little River Watershed (Georgia, USA). Overland cell runoff (area-weighted cell runoff), total runoff volume, clustering statistics, and hot spot patterns were examined for the different cell sizes and trends identified. Total runoff volumes decreased with increasing cell size. Using data sets of 210-m cell size or smaller in conjunction with a representative watershed boundary allows one to model the runoff volumes within 0.2 percent accuracy. The runoff clustering statistics decrease with increasing cell size; a cell size of 960 m or smaller is necessary to indicate significant high-runoff clustering. Runoff hot spot areas have a decreasing trend with increasing cell size; a cell size of 240 m or smaller is required to detect important hot spots. Conclusions regarding cell size effects on runoff estimation cannot be applied to local watershed areas due to the inconsistent changes of runoff volume with cell size; but, optimal cells sizes for clustering and hot spot analyses are applicable to local watershed areas due to the consistent trends.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

PubMed

Skinnider, Michael A; Merwin, Nishanth J; Johnston, Chad W; Magarvey, Nathan A

2017-07-03

Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Haplotype analysis of the apolipoprotein gene cluster on human chromosome 11

PubMed Central

Olivier, Michael; Wang, Xujing; Cole, Regina; Gau, Brian; Kim, Jessica; Rubin, Edward M.; Pennacchio, Len A.

2009-01-01

Members of the apolipoprotein gene cluster (APOA1/C3/A4/A5) on human chromosome 11q23 play an important role in lipid metabolism. Polymorphisms in both APOA5 and APOC3 are strongly associated with plasma triglyceride concentrations. The close genomic locations of these two genes as well as their functional similarity have hindered efforts to define whether each gene independently influences human triglyceride concentrations. In this study, we examined the linkage disequilibrium and haplotype structure of 49 SNPs in a 150-kb region spanning the gene cluster. We identified a total of five common APOA5 haplotypes with a frequency of greater than 8% in samples of northern European origin. The APOA5 haplotype block did not extend past the 7 SNPs in the gene and was separated from the other apolipoprotein gene in the cluster by a region of significantly increased recombination. Furthermore, one previously identified triglyceride risk haplotype of APOA5 (APOA5*3) showed no association with three APOC3 SNPs previously associated with triglyceride concentrations, in contrast to the other risk haplotype (APOA5*2), which was associated with all three minor APOC3 SNP alleles. These results highlight the complex genetic relationship between APOA5 and APOC3 and support the notion that APOA5 represents an independent risk gene affecting plasma triglyceride concentrations in humans. PMID:15081120

Inferring Phylogenetic Relationships of Indian Citron (Citrus medica L.) based on rbcL and matK Sequences of Chloroplast DNA.

PubMed

Uchoi, Ajit; Malik, Surendra Kumar; Choudhary, Ravish; Kumar, Susheel; Rohini, M R; Pal, Digvender; Ercisli, Sezai; Chaudhury, Rekha

2016-06-01

Phylogenetic relationships of Indian Citron (Citrus medica L.) with other important Citrus species have been inferred through sequence analyses of rbcL and matK gene region of chloroplast DNA. The study was based on 23 accessions of Citrus genotypes representing 15 taxa of Indian Citrus, collected from wild, semi-wild, and domesticated stocks. The phylogeny was inferred using the maximum parsimony (MP) and neighbor-joining (NJ) methods. Both MP and NJ trees separated all the 23 accessions of Citrus into five distinct clusters. The chloroplast DNA (cpDNA) analysis based on rbcL and matK sequence data carried out in Indian taxa of Citrus was useful in differentiating all the true species and species/varieties of probable hybrid origin in distinct clusters or groups. Sequence analysis based on rbcL and matK gene provided unambiguous identification and disposition of true species like C. maxima, C. medica, C. reticulata, and related hybrids/cultivars. The separation of C. maxima, C. medica, and C. reticulata in distinct clusters or sub-clusters supports their distinctiveness as the basic species of edible Citrus. However, the cpDNA sequence analysis of rbcL and matK gene could not find any clear cut differentiation between subgenera Citrus and Papeda as proposed in Swingle's system of classification.

Regulated Assembly of Vacuolar ATPase Is Increased during Cluster Disruption-induced Maturation of Dendritic Cells through a Phosphatidylinositol 3-Kinase/mTOR-dependent Pathway*

PubMed Central

Liberman, Rachel; Bond, Sarah; Shainheit, Mara G.; Stadecker, Miguel J.; Forgac, Michael

2014-01-01

The vacuolar (H+)-ATPases (V-ATPases) are ATP-driven proton pumps composed of a peripheral V1 domain and a membrane-embedded V0 domain. Regulated assembly of V1 and V0 represents an important regulatory mechanism for controlling V-ATPase activity in vivo. Previous work has shown that V-ATPase assembly increases during maturation of bone marrow-derived dendritic cells induced by activation of Toll-like receptors. This increased assembly is essential for antigen processing, which is dependent upon an acidic lysosomal pH. Cluster disruption of dendritic cells induces a semi-mature phenotype associated with immune tolerance. Thus, semi-mature dendritic cells are able to process and present self-peptides to suppress autoimmune responses. We have investigated V-ATPase assembly in bone marrow-derived, murine dendritic cells and observed an increase in assembly following cluster disruption. This increased assembly is not dependent upon new protein synthesis and is associated with an increase in concanamycin A-sensitive proton transport in FITC-loaded lysosomes. Inhibition of phosphatidylinositol 3-kinase with wortmannin or mTORC1 with rapamycin effectively inhibits the increased assembly observed upon cluster disruption. These results suggest that the phosphatidylinositol 3-kinase/mTOR pathway is involved in controlling V-ATPase assembly during dendritic cell maturation. PMID:24273170

Integrating an artificial intelligence approach with k-means clustering to model groundwater salinity: the case of Gaza coastal aquifer (Palestine)

NASA Astrophysics Data System (ADS)

Alagha, Jawad S.; Seyam, Mohammed; Md Said, Md Azlin; Mogheir, Yunes

2017-12-01

Artificial intelligence (AI) techniques have increasingly become efficient alternative modeling tools in the water resources field, particularly when the modeled process is influenced by complex and interrelated variables. In this study, two AI techniques—artificial neural networks (ANNs) and support vector machine (SVM)—were employed to achieve deeper understanding of the salinization process (represented by chloride concentration) in complex coastal aquifers influenced by various salinity sources. Both models were trained using 11 years of groundwater quality data from 22 municipal wells in Khan Younis Governorate, Gaza, Palestine. Both techniques showed satisfactory prediction performance, where the mean absolute percentage error (MAPE) and correlation coefficient ( R) for the test data set were, respectively, about 4.5 and 99.8% for the ANNs model, and 4.6 and 99.7% for SVM model. The performances of the developed models were further noticeably improved through preprocessing the wells data set using a k-means clustering method, then conducting AI techniques separately for each cluster. The developed models with clustered data were associated with higher performance, easiness and simplicity. They can be employed as an analytical tool to investigate the influence of input variables on coastal aquifer salinity, which is of great importance for understanding salinization processes, leading to more effective water-resources-related planning and decision making.

The Porcelain Crab Transcriptome and PCAD, the Porcelain Crab Microarray and Sequence Database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tagmount, Abderrahmane; Wang, Mei; Lindquist, Erika

2010-01-27

Background: With the emergence of a completed genome sequence of the freshwater crustacean Daphnia pulex, construction of genomic-scale sequence databases for additional crustacean sequences are important for comparative genomics and annotation. Porcelain crabs, genus Petrolisthes, have been powerful crustacean models for environmental and evolutionary physiology with respect to thermal adaptation and understanding responses of marine organisms to climate change. Here, we present a large-scale EST sequencing and cDNA microarray database project for the porcelain crab Petrolisthes cinctipes. Methodology/Principal Findings: A set of ~;;30K unique sequences (UniSeqs) representing ~;;19K clusters were generated from ~;;98K high quality ESTs from a set ofmore » tissue specific non-normalized and mixed-tissue normalized cDNA libraries from the porcelain crab Petrolisthes cinctipes. Homology for each UniSeq was assessed using BLAST, InterProScan, GO and KEGG database searches. Approximately 66percent of the UniSeqs had homology in at least one of the databases. All EST and UniSeq sequences along with annotation results and coordinated cDNA microarray datasets have been made publicly accessible at the Porcelain Crab Array Database (PCAD), a feature-enriched version of the Stanford and Longhorn Array Databases.Conclusions/Significance: The EST project presented here represents the third largest sequencing effort for any crustacean, and the largest effort for any crab species. Our assembly and clustering results suggest that our porcelain crab EST data set is equally diverse to the much larger EST set generated in the Daphnia pulex genome sequencing project, and thus will be an important resource to the Daphnia research community. Our homology results support the pancrustacea hypothesis and suggest that Malacostraca may be ancestral to Branchiopoda and Hexapoda. Our results also suggest that our cDNA microarrays cover as much of the transcriptome as can reasonably be captured in EST library sequencing approaches, and thus represent a rich resource for studies of environmental genomics.« less

The applicability and effectiveness of cluster analysis

NASA Technical Reports Server (NTRS)

Ingram, D. S.; Actkinson, A. L.

1973-01-01

An insight into the characteristics which determine the performance of a clustering algorithm is presented. In order for the techniques which are examined to accurately cluster data, two conditions must be simultaneously satisfied. First the data must have a particular structure, and second the parameters chosen for the clustering algorithm must be correct. By examining the structure of the data from the Cl flight line, it is clear that no single set of parameters can be used to accurately cluster all the different crops. The effectiveness of either a noniterative or iterative clustering algorithm to accurately cluster data representative of the Cl flight line is questionable. Thus extensive a prior knowledge is required in order to use cluster analysis in its present form for applications like assisting in the definition of field boundaries and evaluating the homogeneity of a field. New or modified techniques are necessary for clustering to be a reliable tool.

Data Acquisition and Analysis for Camouflage Design

DTIC Science & Technology

1981-04-01

were clustered to produce a facsimile of the original scene in 39 49 or 5 average representative colors in CIELAB notation with spectral reflectance...result of the Euclidean clustering or averaging carried out in 1976 CIELAB color space. The size and shape of these domains, along with color, provide...Reflectance Calibration .... ...... 49 Figure O-i CIE 1976 (L*a*b*) Uniform Color Coordinate System (ClELAO) 53 Figure B-2 CIELAB Clustering

Genetic variation in resistance to blast (Pyricularia oryzae Cavara) in rice (Oryza sativa L.) germplasms of Bangladesh

PubMed Central

Khan, Mohammad Ashik Iqbal; Latif, Mohammad Abdul; Khalequzzaman, Mohammad; Tomita, Asami; Ali, Mohammad Ansar; Fukuta, Yoshimichi

2017-01-01

Genetic variation in blast resistance was clarified in 334 Bangladesh rice accessions from 4 major ecotypes (Aus, Aman, Boro and Jhum). Cluster analysis of polymorphism data of 74 SSR markers separated these accessions into cluster I (corresponding to the Japonica Group) and cluster II (corresponding to the Indica Group). Cluster II accessions were represented with high frequency in all ecotypes. Cluster II was further subdivided into subclusters IIa and IIb. Subcluster IIa accessions were represented with high frequency in only Aus and Jhum ecotypes. Cluster I accessions were more frequent in the Aman ecotype than in other ecotypes. Distinct variations in resistance were found, and accessions were classified into 4 groups (A1, A2, B1 and B2) based on their reactions to standard differential blast isolates. The most susceptible group was A2 (which included susceptible variety Lijiangxintuanheigu, most of the differential varieties, and a few Bangladesh accessions), followed in order by A1, B2 and B1 (the most resistant). Accessions from 4 ecotypes fell with different frequencies into each of these resistance groups. These results demonstrated that Japonica Group accessions were found mainly in Aman, and Indica Group accessions were distributed across all ecotypes. Susceptible accessions were limited in Aus and Aman. PMID:29398943

Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL.

PubMed

Wang, Lili; Palmer, Andrew J; Cocker, Fiona; Sanderson, Kristy

2017-01-09

No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population. Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods. The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: -0.18, SE: -0.01, p < 0.001), MM3+ (β: -0.23, SE: -0.02, p < 0.001), cluster-1 (β: -0.10, SE: 0.01, p < 0.001) and cluster-2 (β: -0.36, SE: 0.01, p < 0.001). Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.

Clustering of European winter storms: A multi-model perspective

NASA Astrophysics Data System (ADS)

Renggli, Dominik; Buettner, Annemarie; Scherb, Anke; Straub, Daniel; Zimmerli, Peter

2016-04-01

The storm series over Europe in 1990 (Daria, Vivian, Wiebke, Herta) and 1999 (Anatol, Lothar, Martin) are very well known. Such clusters of severe events strongly affect the seasonally accumulated damage statistics. The (re)insurance industry has quantified clustering by using distribution assumptions deduced from the historical storm activity of the last 30 to 40 years. The use of storm series simulated by climate models has only started recently. Climate model runs can potentially represent 100s to 1000s of years, allowing a more detailed quantification of clustering than the history of the last few decades. However, it is unknown how sensitive the representation of clustering is to systematic biases. Using a multi-model ensemble allows quantifying that uncertainty. This work uses CMIP5 decadal ensemble hindcasts to study clustering of European winter storms from a multi-model perspective. An objective identification algorithm extracts winter storms (September to April) in the gridded 6-hourly wind data. Since the skill of European storm predictions is very limited on the decadal scale, the different hindcast runs are interpreted as independent realizations. As a consequence, the available hindcast ensemble represents several 1000 simulated storm seasons. The seasonal clustering of winter storms is quantified using the dispersion coefficient. The benchmark for the decadal prediction models is the 20th Century Reanalysis. The decadal prediction models are able to reproduce typical features of the clustering characteristics observed in the reanalysis data. Clustering occurs in all analyzed models over the North Atlantic and European region, in particular over Great Britain and Scandinavia as well as over Iberia (i.e. the exit regions of the North Atlantic storm track). Clustering is generally weaker in the models compared to reanalysis, although the differences between different models are substantial. In contrast to existing studies, clustering is driven by weak and moderate events, and not by extreme storms. Thus, the decision which climate model to use to quantify clustering can have a substantial impact on the risk assessment in the (re)insurance business.

High- and low-level hierarchical classification algorithm based on source separation process

NASA Astrophysics Data System (ADS)

Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

2016-10-01

High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance semantic capabilities and give good identification rates.

Novel gastric helicobacters and oral campylobacters are present in captive and wild cetaceans

PubMed Central

Goldman, Cinthia G.; Matteo, Mario J.; Loureiro, Julio D.; Almuzara, Marisa; Barberis, Claudia; Vay, Carlos; Catalano, Mariana; Heredia, Sergio Rodríguez; Mantero, Paula; Boccio, Jose R.; Zubillaga, Marcela B.; Cremaschi, Graciela A.; Solnick, Jay V.; Perez-Perez, Guillermo I.; Blaser, Martin J.

2011-01-01

The mammalian gastric and oral mucosa may be colonized by mixed Helicobacter and Campylobacter species, respectively, in individual animals. To better characterize the presence and distribution of Helicobacter and Campylobacter among marine mammals, we used PCR and 16S rDNA sequence analysis to examine gastric and oral samples from ten dolphins (Tursiops gephyreus), one killer whale (Orcinus orca), one false killer whale (Pseudorca crassidens), and three wild La Plata river dolphins (Pontoporia blainvillei). Helicobacter spp. DNA was widely distributed in gastric and oral samples from both captive and wild cetaceans. Phylogenetic analysis demonstrated two Helicobacter sequence clusters, one closely related to H. cetorum, a species isolated from dolphins and whales in North America. The second related cluster was to sequences obtained from dolphins in Australia and to gastric non-Helicobacter pylori helicobacters, and may represent a novel taxonomic group. Dental plaque sequences from four dolphins formed a third cluster within the Campylobacter genus that likely represents a novel species isolated from marine mammals. Identification of identical Helicobacter spp. DNA sequences from dental plaque, saliva and gastric fluids from the same hosts, suggests that the oral cavity may be involved in transmission. These results demonstrate that Helicobacter and Campylobacter species are commonly distributed in marine mammals, and identify taxonomic clusters that may represent novel species. PMID:21592686

The Influence of the Host Plant Is the Major Ecological Determinant of the Presence of Nitrogen-Fixing Root Nodule Symbiont Cluster II Frankia Species in Soil

PubMed Central

Battenberg, Kai; Wren, Jannah A.; Hillman, Janell; Edwards, Joseph; Huang, Liujing

2016-01-01

ABSTRACT The actinobacterial genus Frankia establishes nitrogen-fixing root nodule symbioses with specific hosts within the nitrogen-fixing plant clade. Of four genetically distinct subgroups of Frankia, cluster I, II, and III strains are capable of forming effective nitrogen-fixing symbiotic associations, while cluster IV strains generally do not. Cluster II Frankia strains have rarely been detected in soil devoid of host plants, unlike cluster I or III strains, suggesting a stronger association with their host. To investigate the degree of host influence, we characterized the cluster II Frankia strain distribution in rhizosphere soil in three locations in northern California. The presence/absence of cluster II Frankia strains at a given site correlated significantly with the presence/absence of host plants on the site, as determined by glutamine synthetase (glnA) gene sequence analysis, and by microbiome analysis (16S rRNA gene) of a subset of host/nonhost rhizosphere soils. However, the distribution of cluster II Frankia strains was not significantly affected by other potential determinants such as host-plant species, geographical location, climate, soil pH, or soil type. Rhizosphere soil microbiome analysis showed that cluster II Frankia strains occupied only a minute fraction of the microbiome even in the host-plant-present site and further revealed no statistically significant difference in the α-diversity or in the microbiome composition between the host-plant-present or -absent sites. Taken together, these data suggest that host plants provide a factor that is specific for cluster II Frankia strains, not a general growth-promoting factor. Further, the factor accumulates or is transported at the site level, i.e., beyond the host rhizosphere. IMPORTANCE Biological nitrogen fixation is a bacterial process that accounts for a major fraction of net new nitrogen input in terrestrial ecosystems. Transfer of fixed nitrogen to plant biomass is especially efficient via root nodule symbioses, which represent evolutionarily and ecologically specialized mutualistic associations. Frankia spp. (Actinobacteria), especially cluster II Frankia spp., have an extremely broad host range, yet comparatively little is known about the soil ecology of these organisms in relation to the host plants and their rhizosphere microbiomes. This study reveals a strong influence of the host plant on soil distribution of cluster II Frankia spp. PMID:27795313

Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

NASA Astrophysics Data System (ADS)

Yasid, A.

2018-01-01

Clustering analysis is important in datamining for unsupervised data, cause no adequate prior knowledge. One of the important tasks is defining the number of clusters without user involvement that is known as automatic clustering. This study intends on acquiring cluster number automatically utilizing forced strategy differential evolution (AC-FSDE). Two mutation parameters, namely: constant parameter and variable parameter are employed to boost differential evolution performance. Four well-known benchmark datasets were used to evaluate the algorithm. Moreover, the result is compared with other state of the art automatic clustering methods. The experiment results evidence that AC-FSDE is better or competitive with other existing automatic clustering algorithm.

An improved initialization center k-means clustering algorithm based on distance and density

NASA Astrophysics Data System (ADS)

Duan, Yanling; Liu, Qun; Xia, Shuyin

2018-04-01

Aiming at the problem of the random initial clustering center of k means algorithm that the clustering results are influenced by outlier data sample and are unstable in multiple clustering, a method of central point initialization method based on larger distance and higher density is proposed. The reciprocal of the weighted average of distance is used to represent the sample density, and the data sample with the larger distance and the higher density are selected as the initial clustering centers to optimize the clustering results. Then, a clustering evaluation method based on distance and density is designed to verify the feasibility of the algorithm and the practicality, the experimental results on UCI data sets show that the algorithm has a certain stability and practicality.

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades

PubMed Central

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-01-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency−frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency−MARSE, and average frequency−peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes. PMID:29104245

A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades.

PubMed

Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean

2017-11-01

The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency-frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency-MARSE, and average frequency-peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes.

Dynamic communities in multichannel data: an application to the foreign exchange market during the 2007-2008 credit crisis.

PubMed

Fenn, Daniel J; Porter, Mason A; McDonald, Mark; Williams, Stacy; Johnson, Neil F; Jones, Nick S

2009-09-01

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.

Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007-2008 credit crisis

NASA Astrophysics Data System (ADS)

Fenn, Daniel J.; Porter, Mason A.; McDonald, Mark; Williams, Stacy; Johnson, Neil F.; Jones, Nick S.

2009-09-01

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.

A self-consistent density based embedding scheme applied to the adsorption of CO on Pd(111)

NASA Astrophysics Data System (ADS)

Lahav, D.; Klüner, T.

2007-06-01

We derive a variant of a density based embedded cluster approach as an improvement to a recently proposed embedding theory for metallic substrates (Govind et al 1999 J. Chem. Phys. 110 7677; Klüner et al 2001 Phys. Rev. Lett. 86 5954). In this scheme, a local region in space is represented by a small cluster which is treated by accurate quantum chemical methodology. The interaction of the cluster with the infinite solid is taken into account by an effective one-electron embedding operator representing the surrounding region. We propose a self-consistent embedding scheme which resolves intrinsic problems of the former theory, in particular a violation of strict density conservation. The proposed scheme is applied to the well-known benchmark system CO/Pd(111).

A Locus Encoding Variable Defense Systems against Invading DNA Identified in Streptococcus suis

PubMed Central

Okura, Masatoshi; Nozawa, Takashi; Watanabe, Takayasu; Murase, Kazunori; Nakagawa, Ichiro; Takamatsu, Daisuke; Osaki, Makoto; Sekizaki, Tsutomu; Gottschalk, Marcelo; Hamada, Shigeyuki

2017-01-01

Streptococcus suis, an important zoonotic pathogen, is known to have an open pan-genome and to develop a competent state. In S. suis, limited genetic lineages are suggested to be associated with zoonosis. However, little is known about the evolution of diversified lineages and their respective phenotypic or ecological characteristics. In this study, we performed comparative genome analyses of S. suis, with a focus on the competence genes, mobile genetic elements, and genetic elements related to various defense systems against exogenous DNAs (defense elements) that are associated with gene gain/loss/exchange mediated by horizontal DNA movements and their restrictions. Our genome analyses revealed a conserved competence-inducing peptide type (pherotype) of the competence system and large-scale genome rearrangements in certain clusters based on the genome phylogeny of 58 S. suis strains. Moreover, the profiles of the defense elements were similar or identical to each other among the strains belonging to the same genomic clusters. Our findings suggest that these genetic characteristics of each cluster might exert specific effects on the phenotypic or ecological differences between the clusters. We also found certain loci that shift several types of defense elements in S. suis. Of note, one of these loci is a previously unrecognized variable region in bacteria, at which strains of distinct clusters code for different and various defense elements. This locus might represent a novel defense mechanism that has evolved through an arms race between bacteria and invading DNAs, mediated by mobile genetic elements and genetic competence. PMID:28379509

A MEGACAM SURVEY OF OUTER HALO SATELLITES. II. BLUE STRAGGLERS IN THE LOWEST STELLAR DENSITY SYSTEMS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santana, Felipe A.; Munoz, Ricardo R.; Geha, Marla

2013-09-10

We present a homogeneous study of blue straggler stars across 10 outer halo globular clusters, 3 classical dwarf spheroidal galaxies, and 9 ultra-faint galaxies based on deep and wide-field photometric data taken with MegaCam on the Canada-France-Hawaii Telescope. We find blue straggler stars to be ubiquitous among these Milky Way satellites. Based on these data, we can test the importance of primordial binaries or multiple systems on blue straggler star formation in low-density environments. For the outer halo globular clusters, we find an anti-correlation between the specific frequency of blue stragglers and absolute magnitude, similar to that previously observed formore » inner halo clusters. When plotted against density and encounter rate, the frequency of blue stragglers is well fit by a single trend with a smooth transition between dwarf galaxies and globular clusters; this result points to a common origin for these satellites' blue stragglers. The fraction of blue stragglers stays constant and high in the low encounter rate regime spanned by our dwarf galaxies, and decreases with density and encounter rate in the range spanned by our globular clusters. We find that young stars can mimic blue stragglers in dwarf galaxies only if their ages are 2.5 {+-} 0.5 Gyr and they represent {approx}1%-7% of the total number of stars, which we deem highly unlikely. These results point to mass-transfer or mergers of primordial binaries or multiple systems as the dominant blue straggler formation mechanism in low-density systems.« less

Clustering high dimensional data using RIA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, Nazrina

2015-05-15

Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily andmore » hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.« less

Representation of Tinnitus in the US Newspaper Media and in Facebook Pages: Cross-Sectional Analysis of Secondary Data.

PubMed

Manchaiah, Vinaya; Ratinaud, Pierre; Andersson, Gerhard

2018-05-08

When people with health conditions begin to manage their health issues, one important issue that emerges is the question as to what exactly do they do with the information that they have obtained through various sources (eg, news media, social media, health professionals, friends, and family). The information they gather helps form their opinions and, to some degree, influences their attitudes toward managing their condition. This study aimed to understand how tinnitus is represented in the US newspaper media and in Facebook pages (ie, social media) using text pattern analysis. This was a cross-sectional study based upon secondary analyses of publicly available data. The 2 datasets (ie, text corpuses) analyzed in this study were generated from US newspaper media during 1980-2017 (downloaded from the database US Major Dailies by ProQuest) and Facebook pages during 2010-2016. The text corpuses were analyzed using the Iramuteq software using cluster analysis and chi-square tests. The newspaper dataset had 432 articles. The cluster analysis resulted in 5 clusters, which were named as follows: (1) brain stimulation (26.2%), (2) symptoms (13.5%), (3) coping (19.8%), (4) social support (24.2%), and (5) treatment innovation (16.4%). A time series analysis of clusters indicated a change in the pattern of information presented in newspaper media during 1980-2017 (eg, more emphasis on cluster 5, focusing on treatment inventions). The Facebook dataset had 1569 texts. The cluster analysis resulted in 7 clusters, which were named as: (1) diagnosis (21.9%), (2) cause (4.1%), (3) research and development (13.6%), (4) social support (18.8%), (5) challenges (11.1%), (6) symptoms (21.4%), and (7) coping (9.2%). A time series analysis of clusters indicated no change in information presented in Facebook pages on tinnitus during 2011-2016. The study highlights the specific aspects about tinnitus that the US newspaper media and Facebook pages focus on, as well as how these aspects change over time. These findings can help health care providers better understand the presuppositions that tinnitus patients may have. More importantly, the findings can help public health experts and health communication experts in tailoring health information about tinnitus to promote self-management, as well as assisting in appropriate choices of treatment for those living with tinnitus. ©Vinaya Manchaiah, Pierre Ratinaud, Gerhard Andersson. Originally published in the Interactive Journal of Medical Research (http://www.i-jmr.org/), 08.05.2018.

Deriving spatial patterns from a novel database of volcanic rock geochemistry in the Virunga Volcanic Province, East African Rift

NASA Astrophysics Data System (ADS)

Poppe, Sam; Barette, Florian; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2016-04-01

The Virunga Volcanic Province (VVP) is situated within the western branch of the East-African Rift. The geochemistry and petrology of its' volcanic products has been studied extensively in a fragmented manner. They represent a unique collection of silica-undersaturated, ultra-alkaline and ultra-potassic compositions, displaying marked geochemical variations over the area occupied by the VVP. We present a novel spatially-explicit database of existing whole-rock geochemical analyses of the VVP volcanics, compiled from international publications, (post-)colonial scientific reports and PhD theses. In the database, a total of 703 geochemical analyses of whole-rock samples collected from the 1950s until recently have been characterised with a geographical location, eruption source location, analytical results and uncertainty estimates for each of these categories. Comparative box plots and Kruskal-Wallis H tests on subsets of analyses with contrasting ages or analytical methods suggest that the overall database accuracy is consistent. We demonstrate how statistical techniques such as Principal Component Analysis (PCA) and subsequent cluster analysis allow the identification of clusters of samples with similar major-element compositions. The spatial patterns represented by the contrasting clusters show that both the historically active volcanoes represent compositional clusters which can be identified based on their contrasted silica and alkali contents. Furthermore, two sample clusters are interpreted to represent the most primitive, deep magma source within the VVP, different from the shallow magma reservoirs that feed the eight dominant large volcanoes. The samples from these two clusters systematically originate from locations which 1. are distal compared to the eight large volcanoes and 2. mostly coincide with the surface expressions of rift faults or NE-SW-oriented inherited Precambrian structures which were reactivated during rifting. The lava from the Mugogo eruption of 1957 belongs to these primitive clusters and is the only known to have erupted outside the current rift valley in historical times. We thus infer there is a distributed hazard of vent opening susceptibility additional to the susceptibility associated with the main Virunga edifices. This study suggests that the statistical analysis of such geochemical database may help to understand complex volcanic plumbing systems and the spatial distribution of volcanic hazards in active and poorly known volcanic areas such as the Virunga Volcanic Province.

Clusters of genetic diseases in Brazil.

PubMed

Cardoso, Gabriela Costa; de Oliveira, Marcelo Zagonel; Paixão-Côrtes, Vanessa Rodrigues; Castilla, Eduardo Enrique; Schuler-Faccini, Lavínia

2018-06-02

The aim of this paper is to present a database of isolated communities (CENISO) with high prevalence of genetic disorders or congenital anomalies in Brazil. We used two strategies to identify such communities: (1) a systematic literature review and (2) a "rumor strategy" based on anecdotal accounts. All rumors and reports were validated in a stepwise process. The bibliographical search identified 34 rumors and 245 rumors through the rumor strategy, and 144 were confirmed. A database like this one presented here represents an important tool for the planning of health priorities for rare diseases in low- and middle-income countries with large populations.

Poverty and blindness in Pakistan: results from the Pakistan national blindness and visual impairment survey.

PubMed

Gilbert, Clare E; Shah, S P; Jadoon, M Z; Bourne, R; Dineen, B; Khan, M A; Johnson, G J; Khan, M D

2008-01-05

To explore the association between blindness and deprivation in a nationally representative sample of adults in Pakistan. Cross sectional population based survey. 221 rural and urban clusters selected randomly throughout Pakistan. Nationally representative sample of 16 507 adults aged 30 or above (95.3% response rate). Associations between visual impairment and poverty assessed by a cluster level deprivation index and a household level poverty indicator; prevalence and causes of blindness; measures of the rate of uptake and quality of eye care services. 561 blind participants (<3/60 in the better eye) were identified during the survey. Clusters in urban Sindh province were the most affluent, whereas rural areas in Balochistan were the poorest. The prevalence of blindness in adults living in affluent clusters was 2.2%, compared with 3.7% in medium clusters and 3.9% in poor clusters (P<0.001 for affluent v poor). The highest prevalence of blindness was found in rural Balochistan (5.2%). The prevalence of total blindness (bilateral no light perception) was more than three times higher in poor clusters than in affluent clusters (0.24% v 0.07%, P<0.001). The prevalences of blindness caused by cataract, glaucoma, and corneal opacity were lower in affluent clusters and households. Reflecting access to eye care services, cataract surgical coverage was higher in affluent clusters (80.6%) than in medium (76.8%) and poor areas (75.1%). Intraocular lens implantation rates were significantly lower in participants from poorer households. 10.2% of adults living in affluent clusters presented to the examination station wearing spectacles, compared with 6.7% in medium clusters and 4.4% in poor cluster areas. Spectacle coverage in affluent areas was more than double that in poor clusters (23.5% v 11.1%, P<0.001). Blindness is associated with poverty in Pakistan; lower access to eye care services was one contributory factor. To reduce blindness, strategies targeting poor people will be needed. These interventions may have an impact on deprivation in Pakistan.

Illinois Occupational Skill Standards: Housekeeping Management Cluster.

ERIC Educational Resources Information Center

Illinois Occupational Skill Standards and Credentialing Council, Carbondale.

This document contains 44 occupational skill standards for the housekeeping management occupational cluster, as required for the state of Illinois. Skill standards, which were developed by committees that included educators and representatives from business, industry, and labor, are intended to promote education and training investment and ensure…

Atomic Cluster Ionization and Attosecond Generation at Long Wavelengths

DTIC Science & Technology

2015-10-31

fellowships for further studies in science, mathematics, engineering or technology fields: Student Metrics This section only applies to graduating...order to investigate this we use a modified Lewenstein quantum model in which the cluster is represented by a 1D Coulomb potential for the parent ion

What is needed to implement a computer-assisted health risk assessment tool? An exploratory concept mapping study

PubMed Central

2012-01-01

Background Emerging eHealth tools could facilitate the delivery of comprehensive care in time-constrained clinical settings. One such tool is interactive computer-assisted health-risk assessments (HRA), which may improve provider-patient communication at the point of care, particularly for psychosocial health concerns, which remain under-detected in clinical encounters. The research team explored the perspectives of healthcare providers representing a variety of disciplines (physicians, nurses, social workers, allied staff) regarding the factors required for implementation of an interactive HRA on psychosocial health. Methods The research team employed a semi-qualitative participatory method known as Concept Mapping, which involved three distinct phases. First, in face-to-face and online brainstorming sessions, participants responded to an open-ended central question: “What factors should be in place within your clinical setting to support an effective computer-assisted screening tool for psychosocial risks?” The brainstormed items were consolidated by the research team. Then, in face-to-face and online sorting sessions, participants grouped the items thematically as ‘it made sense to them’. Participants also rated each item on a 5-point scale for its ‘importance’ and ‘action feasibility’ over the ensuing six month period. The sorted and rated data was analyzed using multidimensional scaling and hierarchical cluster analyses which produced visual maps. In the third and final phase, the face-to-face Interpretation sessions, the concept maps were discussed and illuminated by participants collectively. Results Overall, 54 providers participated (emergency care 48%; primary care 52%). Participants brainstormed 196 items thought to be necessary for the implementation of an interactive HRA emphasizing psychosocial health. These were consolidated by the research team into 85 items. After sorting and rating, cluster analysis revealed a concept map with a seven-cluster solution: 1) the HRA’s equitable availability; 2) the HRA’s ease of use and appropriateness; 3) the content of the HRA survey; 4) patient confidentiality and choice; 5) patient comfort through humanistic touch; 6) professional development, care and workload; and 7) clinical management protocol. Drawing insight from the theoretical lens of Sociotechnical theory, the seven clusters of factors required for HRA implementation could be read as belonging to three overarching aspects : Technical (cluster 1, 2 and 3), Social-Patient (cluster 4 and 5), and Social-Provider (cluster 6 and 7). Participants rated every one of the clusters as important, with mean scores from 4.0 to 4.5. Their scores for feasibility were somewhat lower, ranging from 3.4 to. 4.3. Comparing the scores for importance and feasibility, a significant difference was found for one cluster from each region (cluster 2, 5, 6). The cluster on professional development, care and workload was perceived as especially challenging in emergency department settings, and possible reasons were discussed in the interpretation sessions. Conclusion A number of intertwined multilevel factors emerged as important for the implementation of a computer-assisted, interactive HRA with a focus on psychosocial health. Future developments in this area could benefit from systems thinking and insights from theoretical perspectives, such as sociotechnical system theory for joint optimization and responsible autonomy, with emphasis on both the technical and social aspects of HRA implementation. PMID:23253913

A cluster analytic study of the Wechsler Intelligence Test for Children-IV in children referred for psychoeducational assessment due to persistent academic difficulties.

PubMed

Hale, Corinne R; Casey, Joseph E; Ricciardi, Philip W R

2014-02-01

Wechsler Intelligence Test for Children-IV core subtest scores of 472 children were cluster analyzed to determine if reliable and valid subgroups would emerge. Three subgroups were identified. Clusters were reliable across different stages of the analysis as well as across algorithms and samples. With respect to external validity, the Globally Low cluster differed from the other two clusters on Wechsler Individual Achievement Test-II Word Reading, Numerical Operations, and Spelling subtests, whereas the latter two clusters did not differ from one another. The clusters derived have been identified in studies using previous WISC editions. Clusters characterized by poor performance on subtests historically associated with the VIQ (i.e., VCI + WMI) and PIQ (i.e., POI + PSI) did not emerge, nor did a cluster characterized by low scores on PRI subtests. Picture Concepts represented the highest subtest score in every cluster, failing to vary in a predictable manner with the other PRI subtests.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

m-BIRCH: an online clustering approach for computer vision applications

NASA Astrophysics Data System (ADS)

Madan, Siddharth K.; Dana, Kristin J.

2015-03-01

We adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), to incrementally cluster large datasets of features commonly used in multimedia and computer vision. We call the adapted version modified-BIRCH (m-BIRCH). The algorithm uses only a fraction of the dataset memory to perform clustering, and updates the clustering decisions when new data comes in. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in data summarization. We use m-BIRCH to cluster 840K color SIFT descriptors, and 60K outlier corrupted grayscale patches. We use the algorithm to cluster datasets consisting of challenging non-convex clustering patterns. Our implementation of the algorithm provides an useful clustering tool and is made publicly available.

Gas loss in simulated galaxies as they fall into clusters

PubMed Central

Cen, Renyue; Pop, Ana Roxana; Bahcall, Neta A.

2014-01-01

We use high-resolution cosmological hydrodynamic galaxy formation simulations to gain insights into how galaxies lose their cold gas at low redshift as they migrate from the field to the high-density regions of clusters of galaxies. We find that beyond three cluster virial radii, the fraction of gas-rich galaxies is constant, representing the field. Within three cluster-centric radii, the fraction of gas-rich galaxies declines steadily with decreasing radius, reaching <10% near the cluster center. Our results suggest galaxies start to feel the effect of the cluster environment on their gas content well beyond the cluster virial radius. We show that almost all gas-rich galaxies at the cluster virial radius are falling in for the first time at nearly radial orbits. Furthermore, we find that almost no galaxy moving outward at the cluster virial radius is gas-rich (with a gas-to-baryon ratio greater than 1%). These results suggest that galaxies that fall into clusters lose their cold gas within a single radial round-trip. PMID:24843167

Gas loss in simulated galaxies as they fall into clusters.

PubMed

Cen, Renyue; Pop, Ana Roxana; Bahcall, Neta A

2014-06-03

We use high-resolution cosmological hydrodynamic galaxy formation simulations to gain insights into how galaxies lose their cold gas at low redshift as they migrate from the field to the high-density regions of clusters of galaxies. We find that beyond three cluster virial radii, the fraction of gas-rich galaxies is constant, representing the field. Within three cluster-centric radii, the fraction of gas-rich galaxies declines steadily with decreasing radius, reaching <10% near the cluster center. Our results suggest galaxies start to feel the effect of the cluster environment on their gas content well beyond the cluster virial radius. We show that almost all gas-rich galaxies at the cluster virial radius are falling in for the first time at nearly radial orbits. Furthermore, we find that almost no galaxy moving outward at the cluster virial radius is gas-rich (with a gas-to-baryon ratio greater than 1%). These results suggest that galaxies that fall into clusters lose their cold gas within a single radial round-trip.

Fundamental Theory of Crystal Decomposition

DTIC Science & Technology

1991-05-01

rather than combine them as is often the case in a computation based on the density functional method.4 In the Case of a cluster embedded in a...classical lattice, special care needs to be taken to ensure that mathematical consistency is achieved between the cluster and the embedding lattice. This has...localizing potential or KKLP. Simulation of a large crystallite or an infinite lattice containing a point defect represented by a cluster and a

Aqueous sulfate separation by crystallization of sulfate–water clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Custelcean, Radu; Williams, Neil J.; Seipp, Charles A.

An effective approach to separating sulfates from aqueous solutions is based on the crystallization of extended [SO 4(H 2O) 5 2-] n sulfate–water clusters with a bis(guanidinium) ligand. The ligand was generated in situ by hydrazone condensation in water, thus avoiding elaborate syntheses, tedious purifications, and organic solvents. Crystallization of sulfate–water clusters represents an alternative to the now established sulfate separation strategies that involve encapsulating the “naked” anion.

Aqueous sulfate separation by crystallization of sulfate–water clusters

DOE PAGES

Custelcean, Radu; Williams, Neil J.; Seipp, Charles A.

2015-08-07

An effective approach to separating sulfates from aqueous solutions is based on the crystallization of extended [SO 4(H 2O) 5 2-] n sulfate–water clusters with a bis(guanidinium) ligand. The ligand was generated in situ by hydrazone condensation in water, thus avoiding elaborate syntheses, tedious purifications, and organic solvents. Crystallization of sulfate–water clusters represents an alternative to the now established sulfate separation strategies that involve encapsulating the “naked” anion.

Fe-S Clusters and MutY Base Excision Repair Glycosylases: Purification, Kinetics, and DNA Affinity Measurements.

PubMed

Nuñez, Nicole N; Majumdar, Chandrima; Lay, Kori T; David, Sheila S

2018-01-01

A growing number of iron-sulfur (Fe-S) cluster cofactors have been identified in DNA repair proteins. MutY and its homologs are base excision repair (BER) glycosylases that prevent mutations associated with the common oxidation product of guanine (G), 8-oxo-7,8-dihydroguanine (OG) by catalyzing adenine (A) base excision from inappropriately formed OG:A mispairs. The finding of an [4Fe-4S] 2+ cluster cofactor in MutY, Endonuclease III, and structurally similar BER enzymes was surprising and initially thought to represent an example of a purely structural role for the cofactor. However, in the two decades subsequent to the initial discovery, purification and in vitro analysis of bacterial MutYs and mammalian homologs, such as human MUTYH and mouse Mutyh, have demonstrated that proper Fe-S cluster coordination is required for OG:A substrate recognition and adenine excision. In addition, the Fe-S cluster in MutY has been shown to be capable of redox chemistry in the presence of DNA. The work in our laboratory aimed at addressing the importance of the MutY Fe-S cluster has involved a battery of approaches, with the overarching hypothesis that understanding the role(s) of the Fe-S cluster is intimately associated with understanding the biological and chemical properties of MutY and its unique damaged DNA substrate as a whole. In this chapter, we focus on methods of enzyme expression and purification, detailed enzyme kinetics, and DNA affinity assays. The methods described herein have not only been leveraged to provide insight into the roles of the MutY Fe-S cluster but have also been provided crucial information needed to delineate the impact of inherited variants of the human homolog MUTYH associated with a colorectal cancer syndrome known as MUTYH-associated polyposis or MAP. Notably, many MAP-associated variants have been found adjacent to the Fe-S cluster further underscoring the intimate relationship between the cofactor, MUTYH-mediated DNA repair, and disease. © 2018 Elsevier Inc. All rights reserved.

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

PubMed

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

Not all stars form in clusters - measuring the kinematics of OB associations with Gaia

NASA Astrophysics Data System (ADS)

Ward, Jacob L.; Kruijssen, J. M. Diederik

2018-04-01

It is often stated that star clusters are the fundamental units of star formation and that most (if not all) stars form in dense stellar clusters. In this monolithic formation scenario, low-density OB associations are formed from the expansion of gravitationally bound clusters following gas expulsion due to stellar feedback. N-body simulations of this process show that OB associations formed this way retain signs of expansion and elevated radial anisotropy over tens of Myr. However, recent theoretical and observational studies suggest that star formation is a hierarchical process, following the fractal nature of natal molecular clouds and allowing the formation of large-scale associations in situ. We distinguish between these two scenarios by characterizing the kinematics of OB associations using the Tycho-Gaia Astrometric Solution catalogue. To this end, we quantify four key kinematic diagnostics: the number ratio of stars with positive radial velocities to those with negative radial velocities, the median radial velocity, the median radial velocity normalized by the tangential velocity, and the radial anisotropy parameter. Each quantity presents a useful diagnostic of whether the association was more compact in the past. We compare these diagnostics to models representing random motion and the expanding products of monolithic cluster formation. None of these diagnostics show evidence of expansion, either from a single cluster or multiple clusters, and the observed kinematics are better represented by a random velocity distribution. This result favours the hierarchical star formation model in which a minority of stars forms in bound clusters and large-scale, hierarchically structured associations are formed in situ.

Assessment of Social Vulnerability Identification at Local Level around Merapi Volcano - A Self Organizing Map Approach

NASA Astrophysics Data System (ADS)

Lee, S.; Maharani, Y. N.; Ki, S. J.

2015-12-01

The application of Self-Organizing Map (SOM) to analyze social vulnerability to recognize the resilience within sites is a challenging tasks. The aim of this study is to propose a computational method to identify the sites according to their similarity and to determine the most relevant variables to characterize the social vulnerability in each cluster. For this purposes, SOM is considered as an effective platform for analysis of high dimensional data. By considering the cluster structure, the characteristic of social vulnerability of the sites identification can be fully understand. In this study, the social vulnerability variable is constructed from 17 variables, i.e. 12 independent variables which represent the socio-economic concepts and 5 dependent variables which represent the damage and losses due to Merapi eruption in 2010. These variables collectively represent the local situation of the study area, based on conducted fieldwork on September 2013. By using both independent and dependent variables, we can identify if the social vulnerability is reflected onto the actual situation, in this case, Merapi eruption 2010. However, social vulnerability analysis in the local communities consists of a number of variables that represent their socio-economic condition. Some of variables employed in this study might be more or less redundant. Therefore, SOM is used to reduce the redundant variable(s) by selecting the representative variables using the component planes and correlation coefficient between variables in order to find the effective sample size. Then, the selected dataset was effectively clustered according to their similarities. Finally, this approach can produce reliable estimates of clustering, recognize the most significant variables and could be useful for social vulnerability assessment, especially for the stakeholder as decision maker. This research was supported by a grant 'Development of Advanced Volcanic Disaster Response System considering Potential Volcanic Risk around Korea' [MPSS-NH-2015-81] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea. Keywords: Self-organizing map, Component Planes, Correlation coefficient, Cluster analysis, Sites identification, Social vulnerability, Merapi eruption 2010

Rigid-Cluster Models of Conformational Transitions in Macromolecular Machines and Assemblies

PubMed Central

Kim, Moon K.; Jernigan, Robert L.; Chirikjian, Gregory S.

2005-01-01

We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarse-grained elastic network interpolation (ENI) in which, for example, only Cα atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a Cα coarse-grained model is >(300,000)2. However, it reduces to (84)2 when we apply the rigid-cluster model with icosahedral symmetry constraints. The computational cost of the interpolation no longer scales heavily with the size of structures; instead, it depends strongly on the minimal number of rigid clusters into which the system can be decomposed. PMID:15833998

Proposal of a Consensus Set of Hypervariable Mycobacterial Interspersed Repetitive-Unit–Variable-Number Tandem-Repeat Loci for Subtyping of Mycobacterium tuberculosis Beijing Isolates

PubMed Central

Allix-Béguec, Caroline; Wahl, Céline; Hanekom, Madeleine; Nikolayevskyy, Vladyslav; Drobniewski, Francis; Maeda, Shinji; Campos-Herrero, Isolina; Mokrousov, Igor; Niemann, Stefan; Kontsevaya, Irina; Rastogi, Nalin; Samper, Sofia; Sng, Li-Hwei; Warren, Robin M.

2014-01-01

Mycobacterium tuberculosis Beijing strains represent targets of special importance for molecular surveillance of tuberculosis (TB), especially because they are associated with spread of multidrug resistance in some world regions. Standard 24-locus mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) typing lacks resolution power for accurately discriminating closely related clones that often compose Beijing strain populations. Therefore, we evaluated a set of 7 additional, hypervariable MIRU-VNTR loci for better resolution and tracing of such strains, using a collection of 535 Beijing isolates from six world regions where these strains are known to be prevalent. The typeability and interlaboratory reproducibility of these hypervariable loci were lower than those of the 24 standard loci. Three loci (2163a, 3155, and 3336) were excluded because of their redundant variability and/or more frequent noninterpretable results compared to the 4 other markers. The use of the remaining 4-locus set (1982, 3232, 3820, and 4120) increased the number of types by 52% (from 223 to 340) and reduced the clustering rate from 58.3 to 36.6%, when combined with the use of the standard 24-locus set. Known major clonal complexes/24-locus-based clusters were all subdivided, although the degree of subdivision varied depending on the complex. Only five single-locus variations were detected among the hypervariable loci of an additional panel of 92 isolates, representing 15 years of clonal spread of a single Beijing strain in a geographically restricted setting. On this calibrated basis, we propose this 4-locus set as a consensus for subtyping Beijing clonal complexes and clusters, after standard typing. PMID:24172154

Proposal of a consensus set of hypervariable mycobacterial interspersed repetitive-unit-variable-number tandem-repeat loci for subtyping of Mycobacterium tuberculosis Beijing isolates.

PubMed

Allix-Béguec, Caroline; Wahl, Céline; Hanekom, Madeleine; Nikolayevskyy, Vladyslav; Drobniewski, Francis; Maeda, Shinji; Campos-Herrero, Isolina; Mokrousov, Igor; Niemann, Stefan; Kontsevaya, Irina; Rastogi, Nalin; Samper, Sofia; Sng, Li-Hwei; Warren, Robin M; Supply, Philip

2014-01-01

Mycobacterium tuberculosis Beijing strains represent targets of special importance for molecular surveillance of tuberculosis (TB), especially because they are associated with spread of multidrug resistance in some world regions. Standard 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing lacks resolution power for accurately discriminating closely related clones that often compose Beijing strain populations. Therefore, we evaluated a set of 7 additional, hypervariable MIRU-VNTR loci for better resolution and tracing of such strains, using a collection of 535 Beijing isolates from six world regions where these strains are known to be prevalent. The typeability and interlaboratory reproducibility of these hypervariable loci were lower than those of the 24 standard loci. Three loci (2163a, 3155, and 3336) were excluded because of their redundant variability and/or more frequent noninterpretable results compared to the 4 other markers. The use of the remaining 4-locus set (1982, 3232, 3820, and 4120) increased the number of types by 52% (from 223 to 340) and reduced the clustering rate from 58.3 to 36.6%, when combined with the use of the standard 24-locus set. Known major clonal complexes/24-locus-based clusters were all subdivided, although the degree of subdivision varied depending on the complex. Only five single-locus variations were detected among the hypervariable loci of an additional panel of 92 isolates, representing 15 years of clonal spread of a single Beijing strain in a geographically restricted setting. On this calibrated basis, we propose this 4-locus set as a consensus for subtyping Beijing clonal complexes and clusters, after standard typing.

Catchment classification by runoff behaviour with self-organizing maps (SOM)

NASA Astrophysics Data System (ADS)

Ley, R.; Casper, M. C.; Hellebrand, H.; Merz, R.

2011-09-01

Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation. In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment. Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments. As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.

Catchment classification by runoff behaviour with self-organizing maps (SOM)

NASA Astrophysics Data System (ADS)

Ley, R.; Casper, M. C.; Hellebrand, H.; Merz, R.

2011-03-01

Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisation, prediction in ungauged catchments, model parameterisation. In this study, we investigate hydrological similarity of catchments with respect to their response behaviour. We analyse more than 8200 event runoff coefficients (ERCs) and flow duration curves of 53 gauged catchments in Rhineland-Palatinate, Germany, for the period from 1993 to 2008, covering a huge variability of weather and runoff conditions. The spatio-temporal variability of event-runoff coefficients and flow duration curves are assumed to represent how different catchments "transform" rainfall into runoff. From the runoff coefficients and flow duration curves we derive 12 signature indices describing various aspects of catchment response behaviour to characterise each catchment. Hydrological similarity of catchments is defined by high similarities of their indices. We identify, analyse and describe hydrologically similar catchments by cluster analysis using Self-Organizing Maps (SOM). As a result of the cluster analysis we get five clusters of similarly behaving catchments where each cluster represents one differentiated class of catchments. As catchment response behaviour is supposed to be dependent on its physiographic and climatic characteristics, we compare groups of catchments clustered by response behaviour with clusters of catchments based on catchment properties. Results show an overlap of 67% between these two pools of clustered catchments which can be improved using the topologic correctness of SOMs.

Past year non-medical opioid use and abuse and PTSD diagnosis: Interactions with sex and associations with symptom clusters

PubMed Central

Smith, Kathryn Z.; Smith, Philip H.; Cercone, Sarah A.; McKee, Sherry A.; Homish, Gregory G.

2016-01-01

Introduction Few studies have examined the associations between posttraumatic stress disorder (PTSD) and non-medical opioid use (NMOU), particularly in general U.S. samples. Methods We analyzed data from wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample of non-institutionalized adults, to examine (1) the relationship between PTSD diagnosis with NMOU, Opioid Use Disorder diagnosis, and average monthly frequency of NMOU; and (2) the relationship between PTSD symptom clusters with NMOU, Opioid Use Disorder diagnosis, and average monthly frequency of NMOU. We also explored sex differences among these associations. Results In the adjusted model, a past year PTSD diagnosis was associated with higher odds of past year NMOU for women and men, but the association was stronger for women. In addition, a PTSD was associated with higher odds of an Opioid Use Disorder diagnosis for women, but not for men. With regards to the relationship between specific symptom clusters among those with a past year PTSD diagnosis, important sex differences emerged. For women, the avoidance symptom cluster was associated with higher odds of NMOU, an Opioid Use Disorder diagnosis, and average monthly frequency of NMOU, while for men the arousal/reactivity cluster was associated with higher odds of NMOU, an Opioid Use Disorder diagnosis, and average monthly frequency of NMOU. In addition, for men, the avoidance symptom cluster was associated with higher odds of an Opioid Use Disorder diagnosis, but a lower rate of average monthly frequency of NMOU. Conclusions Results add to the literature showing an association between PTSD and NMOU and suggest that PTSD is more strongly associated with substance use for women than men. Further, results based on individual symptom clusters suggest that men and women with PTSD may be motivated to use substances for different reasons. PMID:26946448

Patterns of amino acid conservation in human and animal immunodeficiency viruses.

PubMed

Voitenko, Olga S; Dhroso, Andi; Feldmann, Anna; Korkin, Dmitry; Kalinina, Olga V

2016-09-01

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity. We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development. A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/ voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Developing a model for effective leadership in healthcare: a concept mapping approach.

PubMed

Hargett, Charles William; Doty, Joseph P; Hauck, Jennifer N; Webb, Allison Mb; Cook, Steven H; Tsipis, Nicholas E; Neumann, Julie A; Andolsek, Kathryn M; Taylor, Dean C

2017-01-01

Despite increasing awareness of the importance of leadership in healthcare, our understanding of the competencies of effective leadership remains limited. We used a concept mapping approach (a blend of qualitative and quantitative analysis of group processes to produce a visual composite of the group's ideas) to identify stakeholders' mental model of effective healthcare leadership, clarifying the underlying structure and importance of leadership competencies. Literature review, focus groups, and consensus meetings were used to derive a representative set of healthcare leadership competency statements. Study participants subsequently sorted and rank-ordered these statements based on their perceived importance in contributing to effective healthcare leadership in real-world settings. Hierarchical cluster analysis of individual sortings was used to develop a coherent model of effective leadership in healthcare. A diverse group of 92 faculty and trainees individually rank-sorted 33 leadership competency statements. The highest rated statements were "Acting with Personal Integrity", "Communicating Effectively", "Acting with Professional Ethical Values", "Pursuing Excellence", "Building and Maintaining Relationships", and "Thinking Critically". Combining the results from hierarchical cluster analysis with our qualitative data led to a healthcare leadership model based on the core principle of Patient Centeredness and the core competencies of Integrity, Teamwork, Critical Thinking, Emotional Intelligence, and Selfless Service. Using a mixed qualitative-quantitative approach, we developed a graphical representation of a shared leadership model derived in the healthcare setting. This model may enhance learning, teaching, and patient care in this important area, as well as guide future research.

An empirical evaluation of the structure of DSM-IV personality disorders in a nationally representative sample: results of confirmatory factor analysis in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2.

PubMed

Cox, Brian J; Clara, Ian P; Worobec, Lydia M; Grant, Bridget F

2012-12-01

Individual personality disorders (PD) are grouped into three clusters in the DSM-IV (A, B, and C). There is very little empirical evidence available concerning the validity of this model in the general population. The current study included all 10 of the DSM-IV PD assessed in Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Confirmatory factor analysis was used to evaluate three plausible models of the structure of Axis II personality disorders (the current hierarchical DSM-IV three-factor model in which individual PD are believed to load on their assigned clusters, which in turn load onto a single Axis II factor; a general single-factor model; and three independent factors). Each of these models was tested in both the total and also separately for gender. The higher order DSM-IV model demonstrated good fit to the data on a number of goodness-of-fit indices. The results for this model were very similar across genders. A model of PD based on the current DSM-IV hierarchical conceptualization of a higher order classification scheme received strong empirical support through confirmatory factor analysis using a number of goodness-of-fit indices in a nationally representative sample. Other models involving broad, higher order personality domains such as neuroticism in relation to personality disorders have yet to be tested in epidemiologic surveys and represent an important avenue for future research.

Self-assembly of a tetrahedral 58-nuclear barium vanadium oxide cluster.

PubMed

Kastner, Katharina; Puscher, Bianka; Streb, Carsten

2013-01-07

We report the synthesis and characterization of a molecular barium vanadium oxide cluster featuring high nuclearity and high symmetry. The tetrameric, 2.3 nm cluster H(5)[Ba(10)(NMP)(14)(H(2)O)(8)[V(12)O(33)](4)Br] is based on a bromide-centred, octahedral barium scaffold which is capped by four previously unknown [V(12)O(33)](6-) clusters in a tetrahedral fashion. The compound represents the largest polyoxovanadate-based heterometallic cluster known to date. The cluster is formed in organic solution and it is suggested that the bulky N-methyl-2-pyrrolidone (NMP) solvent ligands allow the isolation of this giant molecule and prevent further condensation to a solid-state metal oxide. The cluster is fully characterized using single-crystal XRD, elemental analysis, ESI mass spectrometry and other spectroscopic techniques.

Comparative genomic analysis in the fungus Fusarium for production of toxins of concern to food safety

USDA-ARS?s Scientific Manuscript database

SUMMARY Comparative analysis of 207 genomes representing 159 species of the fungus Fusarium detected 9403 known and putative secondary metabolite (SM) biosynthetic gene clusters. The clusters included those responsible for synthesis of mycotoxins, plant hormones and pigments, and varied in distribut...

Electron transfer from alpha-keggin anions to dioxygen

Treesearch

Yurii V. Geletii; Rajai H. Atalla; Craig L. Hill; Ira A. Weinstock

2004-01-01

Polyoxometalates (POMs), of which alpha-Keggin anions are representative, are a diverse and rapidly growing class of water-soluble cluster-anion structures with applications ranging from molecular catalysis to materials. [1] POMs are inexpensive, minimally or non-toxic, negatively charged clusters comprised of early transition-metals, usually in their do electronic...

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

2014-01-01

This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

Accounting Cluster Demonstration Program at Aloha High School. Final Report.

ERIC Educational Resources Information Center

Beaverton School District 48, OR.

A model high school accounting cluster program was planned, developed, implemented, and evaluated in the Beaverton, Oregon, school district. The curriculum was developed with the help of representatives from the accounting occupations in the Portland metropolitan area. Through management interviews, identification of on-the job requirements, and…

Individual Differences in Achievement Goals: A Longitudinal Study of Cognitive, Emotional, and Achievement Outcomes

ERIC Educational Resources Information Center

Daniels, Lia M.; Haynes, Tara L.; Stupnisky, Robert H.; Perry, Raymond P.; Newall, Nancy E.; Pekrun, Reinhard

2008-01-01

Within achievement goal theory debate remains regarding the adaptiveness of certain combinations of goals. Assuming a multiple-goals perspective, we used cluster analysis to classify 1002 undergraduate students according to their mastery and performance-approach goals. Four clusters emerged, representing different goal combinations: high…

ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

PubMed

Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

The nature of plant species.

PubMed

Rieseberg, Loren H; Wood, Troy E; Baack, Eric J

2006-03-23

Many botanists doubt the existence of plant species, viewing them as arbitrary constructs of the human mind, as opposed to discrete, objective entities that represent reproductively independent lineages or 'units of evolution'. However, the discreteness of plant species and their correspondence with reproductive communities have not been tested quantitatively, allowing zoologists to argue that botanists have been overly influenced by a few 'botanical horror stories', such as dandelions, blackberries and oaks. Here we analyse phenetic and/or crossing relationships in over 400 genera of plants and animals. We show that although discrete phenotypic clusters exist in most genera (> 80%), the correspondence of taxonomic species to these clusters is poor (< 60%) and no different between plants and animals. Lack of congruence is caused by polyploidy, asexual reproduction and over-differentiation by taxonomists, but not by contemporary hybridization. Nonetheless, crossability data indicate that 70% of taxonomic species and 75% of phenotypic clusters in plants correspond to reproductively independent lineages (as measured by postmating isolation), and thus represent biologically real entities. Contrary to conventional wisdom, plant species are more likely than animal species to represent reproductively independent lineages.

Spiking neural networks on high performance computer clusters

NASA Astrophysics Data System (ADS)

Chen, Chong; Taha, Tarek M.

2011-09-01

In this paper we examine the acceleration of two spiking neural network models on three clusters of multicore processors representing three categories of processors: x86, STI Cell, and NVIDIA GPGPUs. The x86 cluster utilized consists of 352 dualcore AMD Opterons, the Cell cluster consists of 320 Sony Playstation 3s, while the GPGPU cluster contains 32 NVIDIA Tesla S1070 systems. The results indicate that the GPGPU platform can dominate in performance compared to the Cell and x86 platforms examined. From a cost perspective, the GPGPU is more expensive in terms of neuron/s throughput. If the cost of GPGPUs go down in the future, this platform will become very cost effective for these models.

Two- and three-cluster decays of light nuclei within a hyperspherical harmonics approach

NASA Astrophysics Data System (ADS)

Vasilevsky, V. S.; Lashko, Yu. A.; Filippov, G. F.

2018-06-01

We consider a set of three-cluster systems (4He, 7Li, 7Be, 8Be, 10Be) within a microscopic model which involves hyperspherical harmonics to represent intercluster motion. We selected three-cluster systems which have at least one binary channel. Our aim is to study whether hyperspherical harmonics are able, and under what conditions, to describe two-body channel(s) (nondemocratic motion) or if they are suitable for describing the three-cluster continuum only (democratic motion). It is demonstrated that a rather restricted number of hyperspherical harmonics allows us to describe bound states and scattering states in the two-body continuum for a three-cluster system.

SAR image segmentation using skeleton-based fuzzy clustering

NASA Astrophysics Data System (ADS)

Cao, Yun Yi; Chen, Yan Qiu

2003-06-01

SAR image segmentation can be converted to a clustering problem in which pixels or small patches are grouped together based on local feature information. In this paper, we present a novel framework for segmentation. The segmentation goal is achieved by unsupervised clustering upon characteristic descriptors extracted from local patches. The mixture model of characteristic descriptor, which combines intensity and texture feature, is investigated. The unsupervised algorithm is derived from the recently proposed Skeleton-Based Data Labeling method. Skeletons are constructed as prototypes of clusters to represent arbitrary latent structures in image data. Segmentation using Skeleton-Based Fuzzy Clustering is able to detect the types of surfaces appeared in SAR images automatically without any user input.

The terrain signatures of administrative units: a tool for environmental assessment.

PubMed

Miliaresis, George Ch

2009-03-01

The quantification of knowledge related to the terrain and the landuse/landcover of administrative units in Southern Greece (Peloponnesus) is performed from the CGIAR-CSI SRTM digital elevation model and the CORINE landuse/landcover database. Each administrative unit is parametrically represented by a set of attributes related to its relief. Administrative units are classified on the basis of K-means cluster analysis in an attempt to see how they are organized into groups and cluster derived geometric signatures are defined. Finally each cluster is parametrically represented on the basis of the occurrence of the Corine landuse/landcover classes included and thus, landcover signatures are derived. The geometric and the landuse/landcover signatures revealed a terrain dependent landuse/landcover organization that was used in the assessment of the forest fires impact at moderate resolution scale.

How mutation affects evolutionary games on graphs

PubMed Central

Allen, Benjamin; Traulsen, Arne; Tarnita, Corina E.; Nowak, Martin A.

2011-01-01

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory, specifically the analysis of coalescing random walks via generating functions. These techniques allow us to derive exact identity-by-descent (IBD) probabilities, which characterize spatial assortment on lattices and Cayley trees. From these IBD probabilities we obtain exact conditions for the evolution of cooperation and other game strategies, showing the dual effects of graph topology and mutation rate. High mutation rates diminish the clustering of cooperators, hindering their evolutionary success. Our model can represent either genetic evolution with mutation, or social imitation processes with random strategy exploration. PMID:21473871

Designing coastal conservation to deliver ecosystem and human well-being benefits.

PubMed

Annis, Gust M; Pearsall, Douglas R; Kahl, Katherine J; Washburn, Erika L; May, Christopher A; Franks Taylor, Rachael; Cole, James B; Ewert, David N; Game, Edward T; Doran, Patrick J

2017-01-01

Conservation scientists increasingly recognize that incorporating human values into conservation planning increases the chances for success by garnering broader project acceptance. However, methods for defining quantitative targets for the spatial representation of human well-being priorities are less developed. In this study we employ an approach for identifying regionally important human values and establishing specific spatial targets for their representation based on stakeholder outreach. Our primary objective was to develop a spatially-explicit conservation plan that identifies the most efficient locations for conservation actions to meet ecological goals while sustaining or enhancing human well-being values within the coastal and nearshore areas of the western Lake Erie basin (WLEB). We conducted an optimization analysis using 26 features representing ecological and human well-being priorities (13 of each), and included seven cost layers. The influence that including human well-being had on project results was tested by running five scenarios and setting targets for human well-being at different levels in each scenario. The most important areas for conservation to achieve multiple goals are clustered along the coast, reflecting a concentration of existing or potentially restorable coastal wetlands, coastal landbird stopover habitat and terrestrial biodiversity, as well as important recreational activities. Inland important areas tended to cluster around trails and high quality inland landbird stopover habitat. Most concentrated areas of importance also are centered on lands that are already conserved, reflecting the lower costs and higher benefits of enlarging these conserved areas rather than conserving isolated, dispersed areas. Including human well-being features in the analysis only influenced the solution at the highest target levels.

Designing coastal conservation to deliver ecosystem and human well-being benefits

PubMed Central

Pearsall, Douglas R.; Kahl, Katherine J.; Washburn, Erika L.; May, Christopher A.; Franks Taylor, Rachael; Cole, James B.; Ewert, David N.; Game, Edward T.; Doran, Patrick J.

2017-01-01

Conservation scientists increasingly recognize that incorporating human values into conservation planning increases the chances for success by garnering broader project acceptance. However, methods for defining quantitative targets for the spatial representation of human well-being priorities are less developed. In this study we employ an approach for identifying regionally important human values and establishing specific spatial targets for their representation based on stakeholder outreach. Our primary objective was to develop a spatially-explicit conservation plan that identifies the most efficient locations for conservation actions to meet ecological goals while sustaining or enhancing human well-being values within the coastal and nearshore areas of the western Lake Erie basin (WLEB). We conducted an optimization analysis using 26 features representing ecological and human well-being priorities (13 of each), and included seven cost layers. The influence that including human well-being had on project results was tested by running five scenarios and setting targets for human well-being at different levels in each scenario. The most important areas for conservation to achieve multiple goals are clustered along the coast, reflecting a concentration of existing or potentially restorable coastal wetlands, coastal landbird stopover habitat and terrestrial biodiversity, as well as important recreational activities. Inland important areas tended to cluster around trails and high quality inland landbird stopover habitat. Most concentrated areas of importance also are centered on lands that are already conserved, reflecting the lower costs and higher benefits of enlarging these conserved areas rather than conserving isolated, dispersed areas. Including human well-being features in the analysis only influenced the solution at the highest target levels. PMID:28241018

Density-based clustering analyses to identify heterogeneous cellular sub-populations

NASA Astrophysics Data System (ADS)

Heaster, Tiffany M.; Walsh, Alex J.; Landman, Bennett A.; Skala, Melissa C.

2017-02-01

Autofluorescence microscopy of NAD(P)H and FAD provides functional metabolic measurements at the single-cell level. Here, density-based clustering algorithms were applied to metabolic autofluorescence measurements to identify cell-level heterogeneity in tumor cell cultures. The performance of the density-based clustering algorithm, DENCLUE, was tested in samples with known heterogeneity (co-cultures of breast carcinoma lines). DENCLUE was found to better represent the distribution of cell clusters compared to Gaussian mixture modeling. Overall, DENCLUE is a promising approach to quantify cell-level heterogeneity, and could be used to understand single cell population dynamics in cancer progression and treatment.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-08-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

PubMed Central

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-01-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features. PMID:26705504

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

Genome-Wide Analysis of NBS-LRR Genes in Sorghum Genome Revealed Several Events Contributing to NBS-LRR Gene Evolution in Grass Species

PubMed Central

Yang, Xiping; Wang, Jianping

2016-01-01

The nucleotide-binding site (NBS)–leucine-rich repeat (LRR) gene family is crucially important for offering resistance to pathogens. To explore evolutionary conservation and variability of NBS-LRR genes across grass species, we identified 88, 107, 24, and 44 full-length NBS-LRR genes in sorghum, rice, maize, and Brachypodium, respectively. A comprehensive analysis was performed on classification, genome organization, evolution, expression, and regulation of these NBS-LRR genes using sorghum as a representative of grass species. In general, the full-length NBS-LRR genes are highly clustered and duplicated in sorghum genome mainly due to local duplications. NBS-LRR genes have basal expression levels and are highly potentially targeted by miRNA. The number of NBS-LRR genes in the four grass species is positively correlated with the gene clustering rate. The results provided a valuable genomic resource and insights for functional and evolutionary studies of NBS-LRR genes in grass species. PMID:26792976

Cluster analysis reveals subclinical subgroups with shared autistic and schizotypal traits.

PubMed

Ford, Talitha C; Apputhurai, Pragalathan; Meyer, Denny; Crewther, David P

2018-07-01

Autism and schizophrenia spectrum research is typically based on coarse diagnostic classification, which overlooks individual variation within clinical groups. This method limits the identification of underlying cognitive, genetic and neural correlates of specific symptom dimensions. This study, therefore, aimed to identify homogenous subclinical subgroups of specific autistic and schizotypal traits dimensions, that may be utilised to establish more effective diagnostic and treatment practices. Latent profile analysis of subscale scores derived from an autism-schizotypy questionnaire, completed by 1678 subclinical adults aged 18-40 years (1250 females), identified a local optimum of eight population clusters: High, Moderate and Low Psychosocial Difficulties; High, Moderate and Low Autism-Schizotypy; High Psychosis-Proneness; and Moderate Schizotypy. These subgroups represent the convergent and discriminant dimensions of autism and schizotypy in the subclinical population, and highlight the importance of examining subgroups of specific symptom characteristics across these spectra in order to identify the underlying genetic and neural correlates that can be utilised to advance diagnostic and treatment practices. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular dynamics simulation of metallic impurity diffusion in liquid lead-bismuth eutectic (LBE)

NASA Astrophysics Data System (ADS)

Gao, Yun; Takahashi, Minoru; Cavallotti, Carlo; Raos, Guido

2018-04-01

Corrosion of stainless steels by lead-bismuth eutectic (LBE) is an important problem which depends, amongst other things, on the diffusion of the steel components inside this liquid alloy. Here we present the results of classical molecular dynamics simulations of the diffusion of Fe and Ni within LBE. The simulations complement experimental studies of impurity diffusion by our group and provide an atomic-level understanding of the relevant diffusion phenomena. They are based on the embedded atom method (EAM) to represent many-body interactions among atoms. The EAM potentials employed in our simulations have been validated against ab initio density functional calculations. We show that the experimental and simulation results for the temperature-dependent viscosity of LBE and the impurity diffusion coefficients can be reconciled by assuming that the Ni and Fe diffuse mainly as nanoscopic clusters below 1300 K. The average Fe and Ni cluster sizes decrease with increasing the temperature and there is essentially single-atom diffusion at higher temperatures.

The Ursa Major cluster of galaxies - III. Optical observations of dwarf galaxies and the luminosity function down to MR=-11

NASA Astrophysics Data System (ADS)

Trentham, Neil; Tully, R. Brent; Verheijen, Marc A. W.

2001-07-01

Results are presented of a deep optical survey of the Ursa Major cluster, a spiral-rich cluster of galaxies at a distance of 18.6Mpc which contains about 30 per cent of the light but only 5 per cent of the mass of the nearby Virgo cluster. Fields around known cluster members and a pattern of blind fields along the major and minor axes of the cluster were studied with mosaic CCD cameras on the Canada-France-Hawaii Telescope. The dynamical crossing time for the Ursa Major cluster is only slightly less than a Hubble time. Most galaxies in the local Universe exist in similar moderate-density environments. The Ursa Major cluster is therefore a good place to study the statistical properties of dwarf galaxies, since this structure is at an evolutionary stage representative of typical environments, yet has enough galaxies that reasonable counting statistics can be accumulated. The main observational results of our survey are as follows. (i) The galaxy luminosity function is flat, with a logarithmic slope α=-1.1 for -17

A Clustering Graph Generator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winlaw, Manda; De Sterck, Hans; Sanders, Geoffrey

In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps tomore » understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.« less

Multilocus Sequence Typing Reveals a New Cluster of Closely Related Candida tropicalis Genotypes in Italian Patients With Neurological Disorders.

PubMed

Scordino, Fabio; Giuffrè, Letterio; Barberi, Giuseppina; Marino Merlo, Francesca; Orlando, Maria Grazia; Giosa, Domenico; Romeo, Orazio

2018-01-01

Candida tropicalis is a pathogenic yeast that has emerged as an important cause of candidemia especially in elderly patients with hematological malignancies. Infections caused by this species are mainly reported from Latin America and Asian-Pacific countries although recent epidemiological data revealed that C. tropicalis accounts for 6-16.4% of the Candida bloodstream infections (BSIs) in Italy by representing a relevant issue especially for patients receiving long-term hospital care. The aim of this study was to describe the genetic diversity of C. tropicalis isolates contaminating the hands of healthcare workers (HCWs) and hospital environments and/or associated with BSIs occurring in patients with different neurological disorders and without hematological disease. A total of 28 C. tropicalis isolates were genotyped using multilocus sequence typing analysis of six housekeeping ( ICL1, MDR1, SAPT2, SAPT4, XYR1 , and ZWF1 ) genes and data revealed the presence of only eight diploid sequence types (DSTs) of which 6 (75%) were completely new. Four eBURST clonal complexes (CC2, CC10, CC11, and CC33) contained all DSTs found in this study and the CC33 resulted in an exclusive, well-defined, clonal cluster from Italy. In conclusion, C. tropicalis could represent an important cause of BSIs in long-term hospitalized patients with no underlying hematological disease. The findings of this study also suggest a potential horizontal transmission of a specific C. tropicalis clone through hands of HCWs and expand our understanding of the molecular epidemiology of this pathogen whose population structure is still far from being fully elucidated as its complexity increases as different categories of patients and geographic areas are examined.

Marine sediment-derived Streptomyces bacteria from British Columbia, Canada are a promising microbiota resource for the discovery of antimicrobial natural products.

PubMed

Dalisay, Doralyn S; Williams, David E; Wang, Xiao Ling; Centko, Ryan; Chen, Jessie; Andersen, Raymond J

2013-01-01

Representatives of the genus Streptomyces from terrestrial sources have been the focus of intensive research for the last four decades because of their prolific production of chemically diverse and biologically important compounds. However, metabolite research from this ecological niche had declined significantly in the past years because of the rediscovery of the same bioactive compounds and redundancy of the sample strains. More recently, a new picture has begun to emerge in which marine-derived Streptomyces bacteria have become the latest hot spot as new source for unique and biologically active compounds. Here, we investigated the marine sediments collected in the temperate cold waters from British Columbia, Canada as a valuable source for new groups of marine-derived Streptomyces with antimicrobial activities. We performed culture dependent isolation from 49 marine sediments samples and obtained 186 Streptomyces isolates, 47 of which exhibited antimicrobial activities. Phylogenetic analyses of the active isolates resulted in the identification of four different clusters of bioactive Streptomyces including a cluster with isolates that appear to represent novel species. Moreover, we explored whether these marine-derived Streptomyces produce new secondary metabolites with antimicrobial properties. Chemical analyses revealed structurally diverse secondary metabolites, including four new antibacterial novobiocin analogues. We conducted structure-activity relationships (SAR) studies of these novobiocin analogues against methicillin-resistant Staphylococcus aureus (MRSA). In this study, we revealed the importance of carbamoyl and OMe moieties at positions 3" and 4" of novobiose as well as the hydrogen substituent at position 5 of hydroxybenzoate ring for the anti-MRSA activity. Changes in the substituents at these positions dramatically impede or completely eliminate the inhibitory activity of novobiocins against MRSA.

Genetic diversity and structure of core collection of winter mushroom (Flammulina velutipes) developed by genomic SSR markers.

PubMed

Liu, Xiao Bin; Li, Jing; Yang, Zhu L

2018-01-01

A core collection is a subset of an entire collection that represents as much of the genetic diversity of the entire collection as possible. The establishment of a core collection for crops is practical for efficient management and use of germplasm. However, the establishment of a core collection of mushrooms is still in its infancy, and no established core collection of the economically important species Flammulina velutipes has been reported. We established the first core collection of F. velutipes , containing 32 strains based on 81 genetically different F. veltuipes strains. The allele retention proportion of the core collection for the entire collection was 100%. Moreover, the genetic diversity parameters (the effective number of alleles, Nei's expected heterozygosity, the number of observed heterozygosity, and Shannon's information index) of the core collection showed no significant differences from the entire collection ( p  > 0.01). Thus, the core collection is representative of the genetic diversity of the entire collection. Genetic structure analyses of the core collection revealed that the 32 strains could be clustered into 6 groups, among which groups 1 to 3 were cultivars and groups 4 to 6 were wild strains. The wild strains from different locations harbor their own specific alleles, and were clustered stringently in accordance with their geographic origins. Genetic diversity analyses of the core collection revealed that the wild strains possessed greater genetic diversity than the cultivars. We established the first core collection of F. velutipes in China, which is an important platform for efficient breeding of this mushroom in the future. In addition, the wild strains in the core collection possess favorable agronomic characters and produce unique bioactive compounds, adding value to the platform. More attention should be paid to wild strains in further strain breeding.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the Northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

NASA Astrophysics Data System (ADS)

Savage, J. C.; Simpson, R. W.

2013-09-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Shaping Globular Clusters with Black Holes

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-03-01

How many black holes lurk within the dense environments of globular clusters, and how do these powerful objects shape the properties of the cluster around them? One such cluster, NGC 3201, is now helping us to answer these questions.Hunting Stellar-Mass Black HolesSince the detection of merging black-hole binaries by the Laser Interferometer Gravitational-Wave Observatory (LIGO), the dense environments of globular clusters have received increasing attention as potential birthplaces of these compact binary systems.The central region of the globular star cluster NGC 3201, as viewed by Hubble. The black hole is in orbit with the star marked by the blue circle. [NASA/ESA]In addition, more and more stellar-mass black-hole candidates have been observed within globular clusters, lurking in binary pairs with luminous, non-compact companions. The most recent of these detections, found in the globular cluster NGC 3201, stands alone as the first stellar-mass black hole candidate discovered via radial velocity observations: the black holes main-sequence companion gave away its presence via a telltale wobble.Now a team of scientists led by Kyle Kremer (CIERA and Northwestern University) is using models of this system to better understand the impact that black holes might have on their host clusters.A Model ClusterThe relationship between black holes and their host clusters is complicated. Though the cluster environment can determine the dynamical evolution of the black holes, the retention rate of black holes in a globular cluster (i.e., how many remain in the cluster when they are born as supernovae, rather than being kicked out during the explosion) influences how the host cluster evolves.Kremer and collaborators track this complex relationship by modeling the evolution of a cluster similar to NGC 3201 with a Monte Carlo code. The code incorporates physics relevant to the evolution of black holes and black-hole binaries in globular clusters, such as two-body relaxation, single and binary star evolution, galactic tides, and multi-body encounters. From their grid of models with varying input parameters, the authors then determine which fit best to NGC 3201s final observational properties.Surface brightness profiles for all globular-cluster models at late times compared to observations of NGC 3201 (yellow circles). Blue lines represent models with few retained black holes; black lines represent models with many retained black holes. [Kremer et al. 2018]Retention MattersKremer and collaborators find that the models that best represent NGC 3201 all retain more than 200 black holes at the end of the simulation; models that lost too many black holes due to natal kicks did not match observations of NGC 3201 as well. The models with large numbers of retained black holes also harbored binaries just like the one recently detected in NGC 3201.Models that retain few black holes, on the other hand, may instead be good descriptions of so-called core-collapsed globular clusters observed in the Milky Way. The authors demonstrate that these clusters could contain black holes in binaries with stars known as blue stragglers, which may also be detectable with radial velocity techniques.Kremer and collaborators results suggest that globular clusters similar to NGC 3201 contain hundreds of invisible black holes waiting to be discovered, and they indicate some of the differences in cluster properties caused by hosting such a large population of black holes. We can hope that future observations and modeling will continue to illuminate the complicated relationship between globular clusters and the black holes that live in them.CitationKyle Kremer et al 2018 ApJL 855 L15. doi:10.3847/2041-8213/aab26c

Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010.

PubMed

Jentsch, Franziska; Allen, Jennifer; Fuchs, Judith; von der Lippe, Elena

2017-04-04

Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this study investigates the extent to which risk clusters are observed in a representative sample of women aged 65 and older in Germany. Additionally, the structural composition of the clusters is systematically compared with data and findings from other countries. A pooled data set of Germany's representative cross-sectional surveys GEDA09 and GEDA10 was used. The cohort comprised 4,617 women aged 65 and older. Specific risk clusters based on five MHRFs are identified, using hierarchical cluster analysis. The MHRFs were defined as current smoking (daily or occasionally), risk alcohol consumption (according to the Alcohol Use Disorders Identification Test, a sum score of 4 or more points), physical inactivity (less active than 5 days per week for at least 30 min and lack of sports-related activity in the last three months), low intake of fruits and vegetables (less than one serving of fruits and one of vegetables per day), and obesity (a body mass index equal to or greater than 30). A total of 4,292 cases with full information on these factors are included in the cluster analysis. Extended analyses were also performed to include the number of chronic diseases by age and socioeconomic status of group members. A total of seven risk clusters were identified. In a comparison with data from international studies, the seven risk clusters were found to be stable with a high degree of structural equivalency. Evidence of the stability of risk clusters across various study populations provides a useful starting point for long-term targeted health interventions. The structural clusters provide information through which various MHRFs can be evaluated simultaneously.

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

Using Massive Star Clusters in Merger Remnants To Provide Reference Colors of Intermediate-Age Stellar Populations

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2009-07-01

Much current research in cosmology and galaxy formation relies on an accurate interpretation of colors of galaxies in terms of their evolutionary state, i.e., in terms of ages and metallicities. One particularly important topic is the ability to identify early-type galaxies at "intermediate" ages { 500 Myr - 5 Gyr}, i.e., the period between the end of star formation and half the age of the universe. Currently, integrated-light studies must rely on population synthesis models which rest upon spectral libraries of stars in the solar neighborhood. These models have a difficult time correctly incorporating short-lived evolutionary phases such as thermally pulsing AGB stars, which produce up to 80% of the flux in the near-IR in this age range. Furthermore, intermediate-age star clusters in the Local Group do not represent proper templates against which to calibrate population synthesis models in this age range, because their masses are too low to render the effect of stochastic fluctuations due to the number of bright RGB and AGB stars negligible. As a consequence, current population synthesis models have trouble reconciling the evolutionary state of high-redshift galaxies from optical versus near-IR colors. We propose a simple and effective solution to this issue, namely obtaining high-quality EMPIRICAL colors of massive globular clusters in galaxy merger remnants which span this important age range. These colors should serve as relevant references, both to identify intermediate-age objects in the local and distant universe and as calibrators for population synthesis modellers.

Discovery of the type VII ESX-1 secretion needle?

PubMed

Ates, Louis S; Brosch, Roland

2017-01-01

Mycobacterium tuberculosis, the etiological agent of human tuberculosis, harbours five ESAT-6/type VII secretion (ESX/T7S) systems. The first esx gene clusters were identified during the genome-sequencing project of M. tuberculosis H37Rv. Follow-up studies revealed additional genes playing important roles in ESX/T7S systems. Among the latter genes, one can find those that encode Pro-Glu (PE) and Pro-Pro-Glu (PPE) proteins as well as a gene cluster that is encoded >260 kb upstream of the esx-1 locus and encodes ESX-1 secretion-associated proteins EspA (Rv3616c), EspC (Rv3615c) and EspD (Rv3614c). The espACD cluster has been suggested to have an important function in ESX-1 secretion since EspA-EspC and EsxA-EsxB are mutually co-dependent on each other for secretion. However, the molecular mechanism of this co-dependence and interaction between the substrates remained unknown. In this issue of Molecular Microbiology, Lou and colleagues show that EspC forms high-molecular weight polymerization complexes that resemble selected components of type II, III and/or IV secretion systems of Gram-negative bacteria. Indeed, EspC-multimeric complexes form filamentous structures that could well represent a secretion needle of ESX-1 type VII secretion systems. This exciting observation opens new avenues for research to discover and characterize ESX/T7S components and elucidates the co-dependence of EsxA/B secretion with EspA/C. © 2016 John Wiley & Sons Ltd.

The Plastic Surgery Match: A Quantitative Analysis of Applicant Impressions From the Interview Visit.

PubMed

Frojo, Gianfranco; Tadisina, Kashyap Komarraju; Pressman, Zachary; Chibnall, John T; Lin, Alexander Y; Kraemer, Bruce A

2016-12-01

The integrated plastic surgery match is a competitive process not only for applicants but also for programs vying for highly qualified candidates. Interactions between applicants and program constituents are limited to a single interview visit. The authors aimed to identify components of the interview visit that influence applicant decision making when determining a final program rank list. Thirty-six applicants who were interviewed (100% response) completed the survey. Applicants rated the importance of 20 elements of the interview visit regarding future ranking of the program on a 1 to 5 Likert scale. Data were analyzed using descriptive statistics, hierarchical cluster analysis, analysis of variance, and Pearson correlations. A literature review was performed regarding the plastic surgery integrated residency interview process. Survey questions were categorized into four groups based on mean survey responses:1. Interactions with faculty and residents (mean response > 4),2. Information about the program (3.5-4),3. Ancillaries (food, amenities, stipends) (3-3.5),4. Hospital tour, hotel (<3).Hierarchical item cluster analysis and analysis of variance testing validated these groupings. Average summary scores were calculated for the items representing Interactions, Information, and Ancillaries. Correlation analysis between clusters yielded no significant correlations. A review of the literature yielded a paucity of data on analysis of the interview visit. The interview visit consists of a discrete hierarchy of perceived importance by applicants. The strongest independent factor in determining future program ranking is the quality of interactions between applicants and program constituents on the interview visit. This calls for further investigation and optimization of the interview visit experience.

Parkinson's Disease Subtypes in the Oxford Parkinson Disease Centre (OPDC) Discovery Cohort.

PubMed

Lawton, Michael; Baig, Fahd; Rolinski, Michal; Ruffman, Claudio; Nithi, Kannan; May, Margaret T; Ben-Shlomo, Yoav; Hu, Michele T M

2015-01-01

Within Parkinson's there is a spectrum of clinical features at presentation which may represent sub-types of the disease. However there is no widely accepted consensus of how best to group patients. Use a data-driven approach to unravel any heterogeneity in the Parkinson's phenotype in a well-characterised, population-based incidence cohort. 769 consecutive patients, with mean disease duration of 1.3 years, were assessed using a broad range of motor, cognitive and non-motor metrics. Multiple imputation was carried out using the chained equations approach to deal with missing data. We used an exploratory and then a confirmatory factor analysis to determine suitable domains to include within our cluster analysis. K-means cluster analysis of the factor scores and all the variables not loading into a factor was used to determine phenotypic subgroups. Our factor analysis found three important factors that were characterised by: psychological well-being features; non-tremor motor features, such as posture and rigidity; and cognitive features. Our subsequent five cluster model identified groups characterised by (1) mild motor and non-motor disease (25.4%), (2) poor posture and cognition (23.3%), (3) severe tremor (20.8%), (4) poor psychological well-being, RBD and sleep (18.9%), and (5) severe motor and non-motor disease with poor psychological well-being (11.7%). Our approach identified several Parkinson's phenotypic sub-groups driven by largely dopaminergic-resistant features (RBD, impaired cognition and posture, poor psychological well-being) that, in addition to dopaminergic-responsive motor features may be important for studying the aetiology, progression, and medication response of early Parkinson's.

60 micron luminosity evolution of rich clusters of galaxies

NASA Technical Reports Server (NTRS)

Kelly, Douglas M.; Rieke, George H.

1990-01-01

The average 60-micron flux has been determined for a collection of optically selected galaxy clusters at redshifts ranging from 0.30 to 0.92. The result, 26 mJy per cluster, represents the faintest flux determination known of using the IRAS data base. The flux from this set of clusters has been compared to the 60-micron flux from a sample of nearby galaxy clusters. It is found that the far-infrared luminosity evolution in cluster galaxies can be no more than a factor of 1.7 from z = 0.4 to the present epoch. This upper limit is close to the evolution predicted for simple aging of the stellar populations. Additional processes such as mergers, cannibalism, or enhanced rates of starbursts appear to occur at a low enough level that they have little influence on the far-infrared emission from clusters over this redshift range.

60 micron luminosity evolution of rich clusters of galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, D.M.; Rieke, G.H.

1990-10-01

The average 60-micron flux has been determined for a collection of optically selected galaxy clusters at redshifts ranging from 0.30 to 0.92. The result, 26 mJy per cluster, represents the faintest flux determination known of using the IRAS data base. The flux from this set of clusters has been compared to the 60-micron flux from a sample of nearby galaxy clusters. It is found that the far-infrared luminosity evolution in cluster galaxies can be no more than a factor of 1.7 from z = 0.4 to the present epoch. This upper limit is close to the evolution predicted for simplemore » aging of the stellar populations. Additional processes such as mergers, cannibalism, or enhanced rates of starbursts appear to occur at a low enough level that they have little influence on the far-infrared emission from clusters over this redshift range. 38 refs.« less

A segmentation/clustering model for the analysis of array CGH data.

PubMed

Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

2007-09-01

Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

Spatial arrangement of legionella colonies in intact biofilms from a model cooling water system.

PubMed

Taylor, Michael; Ross, Kirstin; Bentham, Richard

2013-01-01

There is disagreement among microbiologists about whether Legionella requires a protozoan host in order to replicate. This research sought to determine where in biofilm Legionellae are found and whether all biofilm associated Legionella would be located within protozoan hosts. While it is accepted that Legionella colonizes biofilm, its life cycle and nutritional fastidiousness suggest that Legionella employs multiple survival strategies to persist within microbial systems. Fluorescent in situ hybridization (FISH) and confocal laser scanning microscopy (CLSM) demonstrated an undulating biofilm surface architecture and a roughly homogenous distribution of heterotrophic bacteria with clusters of protozoa. Legionella displayed 3 distinct spatial arrangements either contained within or directly associated with protozoa, or dispersed in loosely associated clusters or in tightly packed aggregations of cells forming dense colonial clusters. The formation of discreet clusters of tightly packed Legionella suggests that colony formation is influenced by specific environmental conditions allowing for limited extracellular replication. This work represents the first time that an environmentally representative, multispecies biofilm containing Legionella has been fluorescently tagged and Legionella colony morphology noted within a complex microbial system.

Identification of Staphylococcus spp. using (GTG)₅-PCR fingerprinting.

PubMed

Svec, Pavel; Pantůček, Roman; Petráš, Petr; Sedláček, Ivo; Nováková, Dana

2010-12-01

A group of 212 type and reference strains deposited in the Czech Collection of Microorganisms (Brno, Czech Republic) and covering 41 Staphylococcus species comprising 21 subspecies was characterised using rep-PCR fingerprinting with the (GTG)₅ primer in order to evaluate this method for identification of staphylococci. All strains were typeable using the (GTG)₅ primer and generated PCR products ranging from 200 to 4500 bp. Numerical analysis of the obtained fingerprints revealed (sub)species-specific clustering corresponding with the taxonomic position of analysed strains. Taxonomic position of selected strains representing the (sub)species that were distributed over multiple rep-PCR clusters was verified and confirmed by the partial rpoB gene sequencing. Staphylococcus caprae, Staphylococcus equorum, Staphylococcus sciuri, Staphylococcus piscifermentans, Staphylococcus xylosus, and Staphylococcus saprophyticus revealed heterogeneous fingerprints and each (sub)species was distributed over several clusters. However, representatives of the remaining Staphylococcus spp. were clearly separated in single (sub)species-specific clusters. These results showed rep-PCR with the (GTG)₅ primer as a fast and reliable method applicable for differentiation and straightforward identification of majority of Staphylococcus spp. Copyright © 2010 Elsevier GmbH. All rights reserved.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

2011-12-01

Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis. © 2011 IEEE

New detections of embedded clusters in the Galactic halo

NASA Astrophysics Data System (ADS)

Camargo, D.; Bica, E.; Bonatto, C.

2016-09-01

Context. Until recently it was thought that high Galactic latitude clouds were a non-star-forming ensemble. However, in a previous study we reported the discovery of two embedded clusters (ECs) far away from the Galactic plane (~ 5 kpc). In our recent star cluster catalogue we provided additional high and intermediate latitude cluster candidates. Aims: This work aims to clarify whether our previous detection of star clusters far away from the disc represents just an episodic event or whether star cluster formation is currently a systematic phenomenon in the Galactic halo. We analyse the nature of four clusters found in our recent catalogue and report the discovery of three new ECs each with an unusually high latitude and distance from the Galactic disc midplane. Methods: The analysis is based on 2MASS and WISE colour-magnitude diagrams (CMDs), and stellar radial density profiles (RDPs). The CMDs are built by applying a field-star decontamination procedure, which uncovers the cluster's intrinsic CMD morphology. Results: All of these clusters are younger than 5 Myr. The high-latitude ECs C 932, C 934, and C 939 appear to be related to a cloud complex about 5 kpc below the Galactic disc, under the Local arm. The other clusters are above the disc, C 1074 and C 1100 with a vertical distance of ~3 kpc, C 1099 with ~ 2 kpc, and C 1101 with ~1.8 kpc. Conclusions: According to the derived parameters ECs located below and above the disc occur, which gives evidence of widespread star cluster formation throughout the Galactic halo. This study therefore represents a paradigm shift, by demonstrating that a sterile halo must now be understood as a host for ongoing star formation. The origin and fate of these ECs remain open. There are two possibilities for their origin, Galactic fountains or infall. The discovery of ECs far from the disc suggests that the Galactic halo is more actively forming stars than previously thought. Furthermore, since most ECs do not survive the infant mortality, stars may be raining from the halo into the disc, and/or the halo may be harbouring generations of stars formed in clusters like those detected in our survey.

Accounting for Subgroup Structure in Line-Transect Abundance Estimates of False Killer Whales (Pseudorca crassidens) in Hawaiian Waters

PubMed Central

Bradford, Amanda L.; Forney, Karin A.; Oleson, Erin M.; Barlow, Jay

2014-01-01

For biological populations that form aggregations (or clusters) of individuals, cluster size is an important parameter in line-transect abundance estimation and should be accurately measured. Cluster size in cetaceans has traditionally been represented as the total number of individuals in a group, but group size may be underestimated if group members are spatially diffuse. Groups of false killer whales (Pseudorca crassidens) can comprise numerous subgroups that are dispersed over tens of kilometers, leading to a spatial mismatch between a detected group and the theoretical framework of line-transect analysis. Three stocks of false killer whales are found within the U.S. Exclusive Economic Zone of the Hawaiian Islands (Hawaiian EEZ): an insular main Hawaiian Islands stock, a pelagic stock, and a Northwestern Hawaiian Islands (NWHI) stock. A ship-based line-transect survey of the Hawaiian EEZ was conducted in the summer and fall of 2010, resulting in six systematic-effort visual sightings of pelagic (n = 5) and NWHI (n = 1) false killer whale groups. The maximum number and spatial extent of subgroups per sighting was 18 subgroups and 35 km, respectively. These sightings were combined with data from similar previous surveys and analyzed within the conventional line-transect estimation framework. The detection function, mean cluster size, and encounter rate were estimated separately to appropriately incorporate data collected using different methods. Unlike previous line-transect analyses of cetaceans, subgroups were treated as the analytical cluster instead of groups because subgroups better conform to the specifications of line-transect theory. Bootstrap values (n = 5,000) of the line-transect parameters were randomly combined to estimate the variance of stock-specific abundance estimates. Hawai’i pelagic and NWHI false killer whales were estimated to number 1,552 (CV = 0.66; 95% CI = 479–5,030) and 552 (CV = 1.09; 95% CI = 97–3,123) individuals, respectively. Subgroup structure is an important factor to consider in line-transect analyses of false killer whales and other species with complex grouping patterns. PMID:24587372

Accounting for subgroup structure in line-transect abundance estimates of false killer whales (Pseudorca crassidens) in Hawaiian waters.

PubMed

Bradford, Amanda L; Forney, Karin A; Oleson, Erin M; Barlow, Jay

2014-01-01

For biological populations that form aggregations (or clusters) of individuals, cluster size is an important parameter in line-transect abundance estimation and should be accurately measured. Cluster size in cetaceans has traditionally been represented as the total number of individuals in a group, but group size may be underestimated if group members are spatially diffuse. Groups of false killer whales (Pseudorca crassidens) can comprise numerous subgroups that are dispersed over tens of kilometers, leading to a spatial mismatch between a detected group and the theoretical framework of line-transect analysis. Three stocks of false killer whales are found within the U.S. Exclusive Economic Zone of the Hawaiian Islands (Hawaiian EEZ): an insular main Hawaiian Islands stock, a pelagic stock, and a Northwestern Hawaiian Islands (NWHI) stock. A ship-based line-transect survey of the Hawaiian EEZ was conducted in the summer and fall of 2010, resulting in six systematic-effort visual sightings of pelagic (n = 5) and NWHI (n = 1) false killer whale groups. The maximum number and spatial extent of subgroups per sighting was 18 subgroups and 35 km, respectively. These sightings were combined with data from similar previous surveys and analyzed within the conventional line-transect estimation framework. The detection function, mean cluster size, and encounter rate were estimated separately to appropriately incorporate data collected using different methods. Unlike previous line-transect analyses of cetaceans, subgroups were treated as the analytical cluster instead of groups because subgroups better conform to the specifications of line-transect theory. Bootstrap values (n = 5,000) of the line-transect parameters were randomly combined to estimate the variance of stock-specific abundance estimates. Hawai'i pelagic and NWHI false killer whales were estimated to number 1,552 (CV = 0.66; 95% CI = 479-5,030) and 552 (CV = 1.09; 95% CI = 97-3,123) individuals, respectively. Subgroup structure is an important factor to consider in line-transect analyses of false killer whales and other species with complex grouping patterns.

Variability of O3 and NO2 profile shapes during DISCOVER-AQ: Implications for satellite observations and comparisons to model-simulated profiles

NASA Astrophysics Data System (ADS)

Flynn, Clare Marie; Pickering, Kenneth E.; Crawford, James H.; Weinheimer, Andrew J.; Diskin, Glenn; Thornhill, K. Lee; Loughner, Christopher; Lee, Pius; Strode, Sarah A.

2016-12-01

To investigate the variability of in situ profile shapes under a variety of meteorological and pollution conditions, results are presented of an agglomerative hierarchical cluster analysis of the in situ O3 and NO2 profiles for each of the four campaigns of the NASA DISCOVER-AQ mission. Understanding the observed profile variability for these trace gases is useful for understanding the accuracy of the assumed profile shapes used in satellite retrieval algorithms as well as for understanding the correlation between satellite column observations and surface concentrations. The four campaigns of the DISCOVER-AQ mission took place in Maryland during July 2011, the San Joaquin Valley of California during January-February 2013, the Houston, Texas, metropolitan region during September 2013, and the Denver-Front Range region of Colorado during July-August 2014. Several distinct profile clusters emerged for the California, Texas, and Colorado campaigns for O3, indicating significant variability of O3 profile shapes, while the Maryland campaign presented only one distinct O3 cluster. In contrast, very few distinct profile clusters emerged for NO2 during any campaign for this particular clustering technique, indicating the NO2 profile behavior was relatively uniform throughout each campaign. However, changes in NO2 profile shape were evident as the boundary layer evolved through the day, but they were apparently not significant enough to yield more clusters. The degree of vertical mixing (as indicated by temperature lapse rate) associated with each cluster exerted an important influence on the shapes of the median cluster profiles for O3, as well as impacted the correlations between the associated column and surface data for each cluster for O3. The correlation analyses suggest satellites may have the best chance to relate to surface O3 under the conditions encountered during the Maryland campaign Clusters 1 and 2, which include deep, convective boundary layers and few interruptions to this connection from complex meteorology, chemical environments, or orography. The regional CMAQ model captured the shape factors for O3, and moderately well captured the NO2 shape factors, for the conditions associated with the Maryland campaign, suggesting that a regional air quality model may adequately specify a priori profile shapes for remote sensing retrievals. CMAQ shape factor profiles were not as well represented for the other regions.

Novel Methanotrophs of the Family Methylococcaceae from Different Geographical Regions and Habitats

PubMed Central

Islam, Tajul; Larsen, Øivind; Torsvik, Vigdis; Øvreås, Lise; Panosyan, Hovik; Murrell, J. Colin; Birkeland, Nils-Kåre; Bodrossy, Levente

2015-01-01

Terrestrial methane seeps and rice paddy fields are important ecosystems in the methane cycle. Methanotrophic bacteria in these ecosystems play a key role in reducing methane emission into the atmosphere. Here, we describe three novel methanotrophs, designated BRS-K6, GFS-K6 and AK-K6, which were recovered from three different habitats in contrasting geographic regions and ecosystems: waterlogged rice-field soil and methane seep pond sediments from Bangladesh; and warm spring sediments from Armenia. All isolates had a temperature range for growth of 8–35 °C (optimal 25–28 °C) and a pH range of 5.0–7.5 (optimal 6.4–7.0). 16S rRNA gene sequences showed that they were new gammaproteobacterial methanotrophs, which form a separate clade in the family Methylococcaceae. They fell into a cluster with thermotolerant and mesophilic growth tendency, comprising the genera Methylocaldum-Methylococcus-Methyloparacoccus-Methylogaea. So far, growth below 15 °C of methanotrophs from this cluster has not been reported. The strains possessed type I intracytoplasmic membranes. The genes pmoA, mxaF, cbbL, nifH were detected, but no mmoX gene was found. Each strain probably represents a novel species either belonging to the same novel genus or each may even represent separate genera. These isolates extend our knowledge of methanotrophic Gammaproteobacteria and their physiology and adaptation to different ecosystems. PMID:27682101

Consumer preferences for mild cheddar cheese flavors.

PubMed

Drake, S L; Gerard, P D; Drake, M A

2008-11-01

Flavor is an important factor in consumer selection of cheeses. Mild Cheddar cheese is the classification used to describe Cheddar cheese that is not aged extensively and has a "mild" flavor. However, there is no legal definition or age limit for Cheddar cheese to be labeled mild, medium, or sharp, nor are the flavor profiles or flavor expectations of these cheeses specifically defined. The objectives of this study were to document the distinct flavor profiles among commercially labeled mild Cheddar cheeses, and to characterize if consumer preferences existed for specific mild Cheddar cheese flavors or flavor profiles. Flavor descriptive sensory profiles of a representative array of commercial Cheddar cheeses labeled as mild (n= 22) were determined using a trained sensory panel and an established cheese flavor sensory language. Nine representative Cheddar cheeses were selected for consumer testing. Consumers (n= 215) assessed the cheeses for overall liking and other consumer liking attributes. Internal preference mapping, cluster analysis, and discriminant analysis were conducted. Mild Cheddar cheeses were diverse in flavor with many displaying flavors typically associated with more age. Four distinct consumer clusters were identified. The key drivers of liking for mild Cheddar cheese were: color, cooked/milky, whey and brothy flavors, and sour taste. Consumers have distinct flavor and color preferences for mild Cheddar cheese. These results can help manufacturers understand consumer preferences for mild Cheddar cheese.

Using archetypes to create user panels for usability studies: Streamlining focus groups and user studies.

PubMed

Stavrakos, S-K; Ahmed-Kristensen, S; Goldman, T

2016-09-01

Designers at the conceptual phase of products such as headphones, stress the importance of comfort, e.g. executing comfort studies and the need for a reliable user panel. This paper proposes a methodology to issue a reliable user panel to represent large populations and validates the proposed framework to predict comfort factors, such as physical fit. Data of 200 heads was analyzed by forming clusters, 9 archetypal people were identified out of a 200 people's ear database. The archetypes were validated by comparing the archetypes' responses on physical fit against those of 20 participants interacting with 6 headsets. This paper suggests a new method of selecting representative user samples for prototype testing compared to costly and time consuming methods which relied on the analysis of human geometry of large populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Food habits of fishes on an exposed sandy beach at Fukiagehama, South-West Kyushu Island, Japan

NASA Astrophysics Data System (ADS)

Nakane, Yukinori; Suda, Yusuke; Sano, Mitsuhiko

2011-06-01

To clarify the feeding habits and major food sources of sandy beach fishes, the gut contents of 55 fish species collected on a sandy beach at Fukiagehama, South-West Kyushu Island, Japan, were examined. Ontogenetic changes in food preference were recognized in nine species ( Hypoatherina valenciennei, Lateolabrax japonicus, Trachurus japonicus, Sillago japonica, Sphyraena japonica, Paralichthys olivaceus, Heteromycteris japonica, Paraplagusia japonica, and Takifugu niphobles). A cluster analysis based on dietary overlaps showed that the sandy beach fish assemblage comprised six trophic groups (mysid, amphipod, zooplankton, juvenile fish, terrestrial insect, and mollusk feeders). Of these, the first three groups were the most abundantly represented, whereas the last two were represented by only a single species. These results indicated that epibenthic macrofauna, such as mysids and gammaridean amphipods, and zooplankton, were important food resources for the fish assemblage at the study site, but infaunal macrobenthos, such as polychaetes and bivalves, being relatively unimportant.

Diversity in Older Adults' Use of the Internet: Identifying Subgroups Through Latent Class Analysis.

PubMed

van Boekel, Leonieke C; Peek, Sebastiaan Tm; Luijkx, Katrien G

2017-05-24

As for all individuals, the Internet is important in the everyday life of older adults. Research on older adults' use of the Internet has merely focused on users versus nonusers and consequences of Internet use and nonuse. Older adults are a heterogeneous group, which may implicate that their use of the Internet is diverse as well. Older adults can use the Internet for different activities, and this usage can be of influence on benefits the Internet can have for them. The aim of this paper was to describe the diversity or heterogeneity in the activities for which older adults use the Internet and determine whether diversity is related to social or health-related variables. We used data of a national representative Internet panel in the Netherlands. Panel members aged 65 years and older and who have access to and use the Internet were selected (N=1418). We conducted a latent class analysis based on the Internet activities that panel members reported to spend time on. Second, we described the identified clusters with descriptive statistics and compared the clusters using analysis of variance (ANOVA) and chi-square tests. Four clusters were distinguished. Cluster 1 was labeled as the "practical users" (36.88%, n=523). These respondents mainly used the Internet for practical and financial purposes such as searching for information, comparing products, and banking. Respondents in Cluster 2, the "minimizers" (32.23%, n=457), reported lowest frequency on most Internet activities, are older (mean age 73 years), and spent the smallest time on the Internet. Cluster 3 was labeled as the "maximizers" (17.77%, n=252); these respondents used the Internet for various activities, spent most time on the Internet, and were relatively younger (mean age below 70 years). Respondents in Cluster 4, the "social users," mainly used the Internet for social and leisure-related activities such as gaming and social network sites. The identified clusters significantly differed in age (P<.001, ω 2 =0.07), time spent on the Internet (P<.001, ω 2 =0.12), and frequency of downloading apps (P<.001, ω 2 =0.14), with medium to large effect sizes. Social and health-related variables were significantly different between the clusters, except social and emotional loneliness. However, effect sizes were small. The minimizers scored significantly lower on psychological well-being, instrumental activities of daily living (iADL), and experienced health compared with the practical users and maximizers. Older adults are a diverse group in terms of their activities on the Internet. This underlines the importance to look beyond use versus nonuse when studying older adults' Internet use. The clusters we have identified in this study can help tailor the development and deployment of eHealth intervention to specific segments of the older population. ©Leonieke C van Boekel, Sebastiaan TM Peek, Katrien G Luijkx. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 24.05.2017.

Diversity in Older Adults’ Use of the Internet: Identifying Subgroups Through Latent Class Analysis

PubMed Central

van Boekel, Leonieke C; Peek, Sebastiaan TM; Luijkx, Katrien G

2017-01-01

Background As for all individuals, the Internet is important in the everyday life of older adults. Research on older adults’ use of the Internet has merely focused on users versus nonusers and consequences of Internet use and nonuse. Older adults are a heterogeneous group, which may implicate that their use of the Internet is diverse as well. Older adults can use the Internet for different activities, and this usage can be of influence on benefits the Internet can have for them. Objective The aim of this paper was to describe the diversity or heterogeneity in the activities for which older adults use the Internet and determine whether diversity is related to social or health-related variables. Methods We used data of a national representative Internet panel in the Netherlands. Panel members aged 65 years and older and who have access to and use the Internet were selected (N=1418). We conducted a latent class analysis based on the Internet activities that panel members reported to spend time on. Second, we described the identified clusters with descriptive statistics and compared the clusters using analysis of variance (ANOVA) and chi-square tests. Results Four clusters were distinguished. Cluster 1 was labeled as the “practical users” (36.88%, n=523). These respondents mainly used the Internet for practical and financial purposes such as searching for information, comparing products, and banking. Respondents in Cluster 2, the “minimizers” (32.23%, n=457), reported lowest frequency on most Internet activities, are older (mean age 73 years), and spent the smallest time on the Internet. Cluster 3 was labeled as the “maximizers” (17.77%, n=252); these respondents used the Internet for various activities, spent most time on the Internet, and were relatively younger (mean age below 70 years). Respondents in Cluster 4, the “social users,” mainly used the Internet for social and leisure-related activities such as gaming and social network sites. The identified clusters significantly differed in age (P<.001, ω2=0.07), time spent on the Internet (P<.001, ω2=0.12), and frequency of downloading apps (P<.001, ω2=0.14), with medium to large effect sizes. Social and health-related variables were significantly different between the clusters, except social and emotional loneliness. However, effect sizes were small. The minimizers scored significantly lower on psychological well-being, instrumental activities of daily living (iADL), and experienced health compared with the practical users and maximizers. Conclusions Older adults are a diverse group in terms of their activities on the Internet. This underlines the importance to look beyond use versus nonuse when studying older adults’ Internet use. The clusters we have identified in this study can help tailor the development and deployment of eHealth intervention to specific segments of the older population. PMID:28539302

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Characteristics of airflow and particle deposition in COPD current smokers

NASA Astrophysics Data System (ADS)

Zou, Chunrui; Choi, Jiwoong; Haghighi, Babak; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long

2017-11-01

A recent imaging-based cluster analysis of computed tomography (CT) lung images in a chronic obstructive pulmonary disease (COPD) cohort identified four clusters, viz. disease sub-populations. Cluster 1 had relatively normal airway structures; Cluster 2 had wall thickening; Cluster 3 exhibited decreased wall thickness and luminal narrowing; Cluster 4 had a significant decrease of luminal diameter and a significant reduction of lung deformation, thus having relatively low pulmonary functions. To better understand the characteristics of airflow and particle deposition in these clusters, we performed computational fluid and particle dynamics analyses on representative cluster patients and healthy controls using CT-based airway models and subject-specific 3D-1D coupled boundary conditions. The results show that particle deposition in central airways of cluster 4 patients was noticeably increased especially with increasing particle size despite reduced vital capacity as compared to other clusters and healthy controls. This may be attributable in part to significant airway constriction in cluster 4. This study demonstrates the potential application of cluster-guided CFD analysis in disease populations. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837.

Nitrogenase assembly

PubMed Central

Hu, Yilin; Ribbe, Markus W.

2013-01-01

Nitrogenase contains two unique metalloclusters: the P-cluster and the M-cluster. The assembly processes of P- and M-clusters are arguably the most complicated processes in bioinorganic chemistry. There is considerable interest in decoding the biosynthetic mechanisms of the P- and M-clusters, because these clusters are not only biologically important, but also chemically unprecedented. Understanding the assembly mechanisms of these unique metalloclusters is crucial for understanding the structure-function relationship of nitrogenase. Here, we review the recent advances in this research area, with an emphasis on our work that provide important insights into the biosynthetic pathways of these high-nuclearity metal centers. PMID:23232096

Diverse Bacteria Affiliated with the Genera Microvirga, Phyllobacterium, and Bradyrhizobium Nodulate Lupinus micranthus Growing in Soils of Northern Tunisia

PubMed Central

Msaddak, Abdelhakim; Durán, David; Rejili, Mokhtar; Mars, Mohamed; Ruiz-Argüeso, Tomás; Imperial, Juan; Palacios, José

2017-01-01

ABSTRACT The genetic diversity of bacterial populations nodulating Lupinus micranthus in five geographical sites from northern Tunisia was examined. Phylogenetic analyses of 50 isolates based on partial sequences of recA and gyrB grouped strains into seven clusters, five of which belong to the genus Bradyrhizobium (28 isolates), one to Phyllobacterium (2 isolates), and one, remarkably, to Microvirga (20 isolates). The largest Bradyrhizobium cluster (17 isolates) grouped with the B. lupini species, and the other five clusters were close to different recently defined Bradyrhizobium species. Isolates close to Microvirga were obtained from nodules of plants from four of the five sites sampled. We carried out an in-depth phylogenetic study with representatives of the seven clusters using sequences from housekeeping genes (rrs, recA, glnII, gyrB, and dnaK) and obtained consistent results. A phylogeny based on the sequence of the symbiotic gene nodC identified four groups, three formed by Bradyrhizobium isolates and one by the Microvirga and Phyllobacterium isolates. Symbiotic behaviors of the representative strains were tested, and some congruence between symbiovars and symbiotic performance was observed. These data indicate a remarkable diversity of L. micranthus root nodule symbionts in northern Tunisia, including strains from the Bradyrhizobiaceae, Methylobacteriaceae, and Phyllobacteriaceae families, in contrast with those of the rhizobial populations nodulating lupines in the Old World, including L. micranthus from other Mediterranean areas, which are nodulated mostly by Bradyrhizobium strains. IMPORTANCE Lupinus micranthus is a legume broadly distributed in the Mediterranean region and plays an important role in soil fertility and vegetation coverage by fixing nitrogen and solubilizing phosphate in semiarid areas. Direct sowing to extend the distribution of this indigenous legume can contribute to the prevention of soil erosion in pre-Saharan lands of Tunisia. However, rhizobial populations associated with L. micranthus are poorly understood. In this context, the diversity of endosymbionts of this legume was investigated. Most Lupinus species are nodulated by Bradyrhizobium strains. This work showed that about half of the isolates from northern Tunisian soils were in fact Bradyrhizobium symbionts, but the other half were found unexpectedly to be bacteria within the genera Microvirga and Phyllobacterium. These unusual endosymbionts may have a great ecological relevance. Inoculation with the appropriate selected symbiotic bacterial partners will increase L. micranthus survival with consequent advantages for the environment in semiarid areas of Tunisia. PMID:28062461

Diverse Bacteria Affiliated with the Genera Microvirga, Phyllobacterium, and Bradyrhizobium Nodulate Lupinus micranthus Growing in Soils of Northern Tunisia.

PubMed

Msaddak, Abdelhakim; Durán, David; Rejili, Mokhtar; Mars, Mohamed; Ruiz-Argüeso, Tomás; Imperial, Juan; Palacios, José; Rey, Luis

2017-03-15

The genetic diversity of bacterial populations nodulating Lupinus micranthus in five geographical sites from northern Tunisia was examined. Phylogenetic analyses of 50 isolates based on partial sequences of recA and gyrB grouped strains into seven clusters, five of which belong to the genus Bradyrhizobium (28 isolates), one to Phyllobacterium (2 isolates), and one, remarkably, to Microvirga (20 isolates). The largest Bradyrhizobium cluster (17 isolates) grouped with the B. lupini species, and the other five clusters were close to different recently defined Bradyrhizobium species. Isolates close to Microvirga were obtained from nodules of plants from four of the five sites sampled. We carried out an in-depth phylogenetic study with representatives of the seven clusters using sequences from housekeeping genes ( rrs , recA , glnII , gyrB , and dnaK ) and obtained consistent results. A phylogeny based on the sequence of the symbiotic gene nodC identified four groups, three formed by Bradyrhizobium isolates and one by the Microvirga and Phyllobacterium isolates. Symbiotic behaviors of the representative strains were tested, and some congruence between symbiovars and symbiotic performance was observed. These data indicate a remarkable diversity of L. micranthus root nodule symbionts in northern Tunisia, including strains from the Bradyrhizobiaceae , Methylobacteriaceae , and Phyllobacteriaceae families, in contrast with those of the rhizobial populations nodulating lupines in the Old World, including L. micranthus from other Mediterranean areas, which are nodulated mostly by Bradyrhizobium strains. IMPORTANCE Lupinus micranthus is a legume broadly distributed in the Mediterranean region and plays an important role in soil fertility and vegetation coverage by fixing nitrogen and solubilizing phosphate in semiarid areas. Direct sowing to extend the distribution of this indigenous legume can contribute to the prevention of soil erosion in pre-Saharan lands of Tunisia. However, rhizobial populations associated with L. micranthus are poorly understood. In this context, the diversity of endosymbionts of this legume was investigated. Most Lupinus species are nodulated by Bradyrhizobium strains. This work showed that about half of the isolates from northern Tunisian soils were in fact Bradyrhizobium symbionts, but the other half were found unexpectedly to be bacteria within the genera Microvirga and Phyllobacterium These unusual endosymbionts may have a great ecological relevance. Inoculation with the appropriate selected symbiotic bacterial partners will increase L. micranthus survival with consequent advantages for the environment in semiarid areas of Tunisia. Copyright © 2017 American Society for Microbiology.

On the modification Highly Connected Subgraphs (HCS) algorithm in graph clustering for weighted graph

NASA Astrophysics Data System (ADS)

Albirri, E. R.; Sugeng, K. A.; Aldila, D.

2018-04-01

Nowadays, in the modern world, since technology and human civilization start to progress, all city in the world is almost connected. The various places in this world are easier to visit. It is an impact of transportation technology and highway construction. The cities which have been connected can be represented by graph. Graph clustering is one of ways which is used to answer some problems represented by graph. There are some methods in graph clustering to solve the problem spesifically. One of them is Highly Connected Subgraphs (HCS) method. HCS is used to identify cluster based on the graph connectivity k for graph G. The connectivity in graph G is denoted by k(G)> \\frac{n}{2} that n is the total of vertices in G, then it is called as HCS or the cluster. This research used literature review and completed with simulation of program in a software. We modified HCS algorithm by using weighted graph. The modification is located in the Process Phase. Process Phase is used to cut the connected graph G into two subgraphs H and \\bar{H}. We also made a program by using software Octave-401. Then we applied the data of Flight Routes Mapping of One of Airlines in Indonesia to our program.

Guasom Analysis Of The Alhambra Survey

NASA Astrophysics Data System (ADS)

Garabato, Daniel; Manteiga, Minia; Dafonte, Carlos; Álvarez, Marco A.

2017-10-01

GUASOM is a data mining tool designed for knowledge discovery in large astronomical spectrophotometric archives developed in the framework of Gaia DPAC (Data Processing and Analysis Consortium). Our tool is based on a type of unsupervised learning Artificial Neural Networks named Self-organizing maps (SOMs). SOMs permit the grouping and visualization of big amount of data for which there is no a priori knowledge and hence they are very useful for analyzing the huge amount of information present in modern spectrophotometric surveys. SOMs are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Each cluster has a representative, called prototype which is a virtual pattern that better represents or resembles the set of input patterns belonging to such a cluster. Prototypes make easier the task of determining the physical nature and properties of the objects populating each cluster. Our algorithm has been tested on the ALHAMBRA survey spectrophotometric observations, here we present our results concerning the survey segmentation, visualization of the data structure, separation between types of objects (stars and galaxies), data homogeneity of neurons, cluster prototypes, redshift distribution and crossmatch with other databases (Simbad).

Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England.

PubMed

Vaganay, Arnaud

2016-01-01

For pilot or experimental employment programme results to apply beyond their test bed, researchers must select 'clusters' (i.e. the job centres delivering the new intervention) that are reasonably representative of the whole territory. More specifically, this requirement must account for conditions that could artificially inflate the effect of a programme, such as the fluidity of the local labour market or the performance of the local job centre. Failure to achieve representativeness results in Cluster Sampling Bias (CSB). This paper makes three contributions to the literature. Theoretically, it approaches the notion of CSB as a human behaviour. It offers a comprehensive theory, whereby researchers with limited resources and conflicting priorities tend to oversample 'effect-enhancing' clusters when piloting a new intervention. Methodologically, it advocates for a 'narrow and deep' scope, as opposed to the 'wide and shallow' scope, which has prevailed so far. The PILOT-2 dataset was developed to test this idea. Empirically, it provides evidence on the prevalence of CSB. In conditions similar to the PILOT-2 case study, investigators (1) do not sample clusters with a view to maximise generalisability; (2) do not oversample 'effect-enhancing' clusters; (3) consistently oversample some clusters, including those with higher-than-average client caseloads; and (4) report their sampling decisions in an inconsistent and generally poor manner. In conclusion, although CSB is prevalent, it is still unclear whether it is intentional and meant to mislead stakeholders about the expected effect of the intervention or due to higher-level constraints or other considerations.

Morphological and Genetic Diversity of Rhizobia Nodulating Cowpea (Vigna unguiculata L.) from Agricultural Soils of Lower Eastern Kenya.

PubMed

Ondieki, Damaris K; Nyaboga, Evans N; Wagacha, John M; Mwaura, Francis B

2017-01-01

Limited nitrogen (N) content in the soil is a major challenge to sustainable and high crop production in many developing countries. The nitrogen fixing symbiosis of legumes with rhizobia plays an important role in supplying sufficient N for legumes and subsequent nonleguminous crops. To identify rhizobia strains which are suitable for bioinoculant production, characterization of rhizobia is a prerequisite. The objective of this study was to assess the morphological and genetic diversity of rhizobia that nodulates cowpea in agricultural soils of lower eastern Kenya. Twenty-eight rhizobia isolates were recovered from soil samples collected from farmers' fields in Machakos, Makueni, and Kitui counties in lower eastern Kenya and characterized based on morphological characteristics. Thirteen representative isolates were selected and characterized using BOX repetitive element PCR fingerprinting. Based on the dendrogram generated from morphological characteristics, the test isolates were distributed into two major clusters at a similarity of 75%. Phylogenetic tree, based on BOX repetitive element PCR, grouped the isolates into two clusters at 90% similarity level. The clustering of the isolates did not show a relationship to the origin of soil samples, although the isolates were genetically diverse. This study is a prerequisite to the selection of suitable cowpea rhizobia to develop bioinoculants for sustainable crop production in Kenya.

Coevolutionary dynamics of opinion propagation and social balance: The key role of small-worldness

NASA Astrophysics Data System (ADS)

Chen, Yan; Chen, Lixue; Sun, Xian; Zhang, Kai; Zhang, Jie; Li, Ping

2014-03-01

The propagation of various opinions in social networks, which influences human inter-relationships and even social structure, and hence is a most important part of social life. We have incorporated social balance into opinion propagation in social networks are influenced by social balance. The edges in networks can represent both friendly or hostile relations, and change with the opinions of individual nodes. We introduce a model to characterize the coevolutionary dynamics of these two dynamical processes on Watts-Strogatz (WS) small-world network. We employ two distinct evolution rules (i) opinion renewal; and (ii) relation adjustment. By changing the rewiring probability, and thus the small-worldness of the WS network, we found that the time for the system to reach balanced states depends critically on both the average path length and clustering coefficient of the network, which is different than other networked process like epidemic spreading. In particular, the system equilibrates most quickly when the underlying network demonstrates strong small-worldness, i.e., small average path lengths and large clustering coefficient. We also find that opinion clusters emerge in the process of the network approaching the global equilibrium, and a measure of global contrariety is proposed to quantify the balanced state of a social network.

Is nitrogen transfer among plants enhanced by contrasting nutrient-acquisition strategies?

PubMed

Teste, François P; Veneklaas, Erik J; Dixon, Kingsley W; Lambers, Hans

2015-01-01

Nitrogen (N) transfer among plants has been found where at least one plant can fix N2 . In nutrient-poor soils, where plants with contrasting nutrient-acquisition strategies (without N2 fixation) co-occur, it is unclear if N transfer exists and what promotes it. A novel multi-species microcosm pot experiment was conducted to quantify N transfer between arbuscular mycorrhizal (AM), ectomycorrhizal (EM), dual AM/EM, and non-mycorrhizal cluster-rooted plants in nutrient-poor soils with mycorrhizal mesh barriers. We foliar-fed plants with a K(15) NO3 solution to quantify one-way N transfer from 'donor' to 'receiver' plants. We also quantified mycorrhizal colonization and root intermingling. Transfer of N between plants with contrasting nutrient-acquisition strategies occurred at both low and high soil nutrient levels with or without root intermingling. The magnitude of N transfer was relatively high (representing 4% of donor plant N) given the lack of N2 fixation. Receiver plants forming ectomycorrhizas or cluster roots were more enriched compared with AM-only plants. We demonstrate N transfer between plants of contrasting nutrient-acquisition strategies, and a preferential enrichment of cluster-rooted and EM plants compared with AM plants. Nutrient exchanges among plants are potentially important in promoting plant coexistence in nutrient-poor soils. © 2014 John Wiley & Sons Ltd.

The network structure of sex partner meeting places reported by HIV-infected MSM: Opportunities for HIV targeted control.

PubMed

Brantley, Meredith; Schumacher, Christina; Fields, Errol L; Perin, Jamie; Safi, Amelia Greiner; Ellen, Jonathan M; Muvva, Ravikiran; Chaulk, Patrick; Jennings, Jacky M

2017-06-01

Baltimore, Maryland ranks among U.S. cities with the highest incidence of HIV infection among men who have sex with men (MSM). HIV screening at sex partner meeting places or venues frequented by MSM with new diagnoses and/or high HIV viral load may reduce transmission by identifying and linking infected individuals to care. We investigated venue-based clustering of newly diagnosed MSM to identify high HIV transmission venues. HIV surveillance data from MSM diagnosed between October 2012-June 2014 and reporting ≥1 sex partner meeting place were examined. Venue viral load was defined according to the geometric mean viral load of the cluster of cases that reported the venue and classified as high (>50,000 copies/mL), moderate (1500-50,000 copies/mL), and low (<1500 copies/mL). 143 MSM provided information on ≥1 sex partner meeting place, accounting for 132 unique venues. Twenty-six venues were reported by > 1 MSM; of these, a tightly connected cluster of six moderate viral load sex partner meeting places emerged, representing 66% of reports. Small, dense networks of moderate to high viral load venues may be important for targeted HIV control among MSM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evolution of the early-type galaxy fraction in clusters since z = 0.8

NASA Astrophysics Data System (ADS)

Simard, L.; Clowe, D.; Desai, V.; Dalcanton, J. J.; von der Linden, A.; Poggianti, B. M.; White, S. D. M.; Aragón-Salamanca, A.; De Lucia, G.; Halliday, C.; Jablonka, P.; Milvang-Jensen, B.; Saglia, R. P.; Pelló, R.; Rudnick, G. H.; Zaritsky, D.

2009-12-01

We study the morphological content of a large sample of high-redshift clusters to determine its dependence on cluster mass and redshift. Quantitative morphologies are based on PSF-convolved, 2D bulge+disk decompositions of cluster and field galaxies on deep Very Large Telescope FORS2 images of eighteen, optically-selected galaxy clusters at 0.45 < z < 0.80 observed as part of the ESO Distant Cluster Survey (“EDisCS”). Morphological content is characterized by the early-type galaxy fraction f_et, and early-type galaxies are objectively selected based on their bulge fraction and image smoothness. This quantitative selection is equivalent to selecting galaxies visually classified as E or S0. Changes in early-type fractions as a function of cluster velocity dispersion, redshift and star-formation activity are studied. A set of 158 clusters extracted from the Sloan Digital Sky Survey is analyzed exactly as the distant EDisCS sample to provide a robust local comparison. We also compare our results to a set of clusters from the Millennium Simulation. Our main results are: (1) the early-type fractions of the SDSS and EDisCS clusters exhibit no clear trend as a function of cluster velocity dispersion. (2) Mid-z EDisCS clusters around σ = 500 km s-1 have f_et ≃ 0.5 whereas high-z EDisCS clusters have f_et ≃ 0.4. This represents a ~25% increase over a time interval of 2 Gyr. (3) There is a marked difference in the morphological content of EDisCS and SDSS clusters. None of the EDisCS clusters have early-type galaxy fractions greater than 0.6 whereas half of the SDSS clusters lie above this value. This difference is seen in clusters of all velocity dispersions. (4) There is a strong and clear correlation between morphology and star formation activity in SDSS and EDisCS clusters in the sense that decreasing fractions of [OII] emitters are tracked by increasing early-type fractions. This correlation holds independent of cluster velocity dispersion and redshift even though the fraction of [OII] emitters decreases from z ˜0.8 to z ˜ 0.06 in all environments. Our results pose an interesting challenge to structural transformation and star formation quenching processes that strongly depend on the global cluster environment (e.g., a dense ICM) and suggest that cluster membership may be of lesser importance than other variables in determining galaxy properties. Based on observations obtained in visitor and service modes at the ESO Very Large Telescope (VLT) as part of the Large Programme 166.A-0162 (the ESO Distant Cluster Survey). Also based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with proposal 9476. Support for this proposal was provided by NASA through a grant from the Space Telescope Science Institute. Table [see full textsee full textsee full textsee full textsee full text] is only available in electronic form at http://www.aanda.org

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Characterization and Detection of a Widely Distributed Gene Cluster That Predicts Anaerobic Choline Utilization by Human Gut Bacteria

PubMed Central

Martínez-del Campo, Ana; Bodea, Smaranda; Hamer, Hilary A.; Marks, Jonathan A.; Haiser, Henry J.; Turnbaugh, Peter J.

2015-01-01

ABSTRACT Elucidation of the molecular mechanisms underlying the human gut microbiota’s effects on health and disease has been complicated by difficulties in linking metabolic functions associated with the gut community as a whole to individual microorganisms and activities. Anaerobic microbial choline metabolism, a disease-associated metabolic pathway, exemplifies this challenge, as the specific human gut microorganisms responsible for this transformation have not yet been clearly identified. In this study, we established the link between a bacterial gene cluster, the choline utilization (cut) cluster, and anaerobic choline metabolism in human gut isolates by combining transcriptional, biochemical, bioinformatic, and cultivation-based approaches. Quantitative reverse transcription-PCR analysis and in vitro biochemical characterization of two cut gene products linked the entire cluster to growth on choline and supported a model for this pathway. Analyses of sequenced bacterial genomes revealed that the cut cluster is present in many human gut bacteria, is predictive of choline utilization in sequenced isolates, and is widely but discontinuously distributed across multiple bacterial phyla. Given that bacterial phylogeny is a poor marker for choline utilization, we were prompted to develop a degenerate PCR-based method for detecting the key functional gene choline TMA-lyase (cutC) in genomic and metagenomic DNA. Using this tool, we found that new choline-metabolizing gut isolates universally possessed cutC. We also demonstrated that this gene is widespread in stool metagenomic data sets. Overall, this work represents a crucial step toward understanding anaerobic choline metabolism in the human gut microbiota and underscores the importance of examining this microbial community from a function-oriented perspective. PMID:25873372

Genetic diversity of Syrian Arabian horses.

PubMed

Almarzook, S; Reissmann, M; Arends, D; Brockmann, G A

2017-08-01

Although Arabian horses have been bred in strains for centuries and pedigrees have been recorded in studbooks, to date, little is known about the genetic diversity within and between these strains. In this study, we tested if the three main strains of Syrian Arabian horses descend from three founders as suggested by the studbook. We examined 48 horses representing Saglawi (n = 18), Kahlawi (n = 16) and Hamdani (n = 14) strains using the Equine SNP70K BeadChip. For comparison, an additional 24 Arabian horses from the USA and three Przewalski's horses as an out group were added. Observed heterozygosis (H o ) ranged between 0.30 and 0.32, expected heterozygosity (H e ) between 0.30 and 0.31 and inbreeding coefficients (F is ) between -0.02 and -0.05, indicating high genetic diversity within Syrian strains. Likewise, the genetic differentiation between the three Syrian strains was very low (F st  < 0.05). Hierarchical clustering showed a clear distinction between Arabian and Przewalski's horses. Among Arabian horses, we found three clusters containing either horses from the USA or horses from Syria or horses from Syria and the USA together. Individuals from the same Syrian Arabian horse strain were spread across different sub-clusters. When analyzing Syrian Arabian horses alone, the best population differentiation was found with three distinct clusters. In contrast to expectations from the studbook, these clusters did not coincide with strain affiliation. Although this finding supports the hypothesis of three founders, the genetic information is not consistent with the currently used strain designation system. The information can be used to reconsider the current breeding practice. Beyond that, Syrian Arabian horses are an important reservoir for genetic diversity. © 2017 Stichting International Foundation for Animal Genetics.

One year nationwide evaluation of 24-locus MIRU-VNTR genotyping on Slovenian Mycobacterium tuberculosis isolates.

PubMed

Bidovec-Stojkovic, Urska; Zolnir-Dovc, Manca; Supply, Philip

2011-10-01

Slovenia is one of the few countries where IS6110 RFLP is applied for genotyping M. tuberculosis at a nationwide level, which has been in effect since 2000. Based on S6110 RFLP clustering, typical risk factors and routes of M. tuberculosis transmission were identified, such as alcohol abuse, homelessness, and bars. However, IS6110 RFLP typing suffers from important limitations including a long wait for results, which reduces the potential benefit of molecular-guided tuberculosis (TB) control. PCR-based 24-locus MIRU-VNTR typing combined with spoligotyping has recently emerged as a potential alternative for faster, large-scale genotyping of M. tuberculosis. We compared these genotyping methods for analyzing 196 Slovenian Mycobacterium tuberculosis isolates representing 97.5% of all culture-positive cases included in the Slovenian TB Registry in 2008. IS6110 RFLP and 24-locus MIRU-VNTR typing combined with spoligotyping identified 157 and 155 distinct profiles, 135 and 125 unique isolates, and 61 and 71 clustered isolates grouped into 22 and 29 clusters, respectively. The discriminatory indexes were very close, at 0.9963 and 0.9965, respectively. The majority of the molecular clusters defined by either of the two methods were identical, including in the few cases for which epidemiological links were available. The differences frequently consisted of single-band changes in IS6170-RFLP profiles subdividing a MIRU-VNTR/spoligotype-based cluster. Our one-year nationwide study showed that the results of 24-locus MIRU-VNTR typing combined with spoligotyping reached a high level of concordance with those obtained from IS6110 RFLP typing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Patterns of Childhood Abuse and Neglect in a Representative German Population Sample

PubMed Central

Schilling, Christoph; Weidner, Kerstin; Brähler, Elmar; Glaesmer, Heide; Häuser, Winfried; Pöhlmann, Karin

2016-01-01

Background Different types of childhood maltreatment, like emotional abuse, emotional neglect, physical abuse, physical neglect and sexual abuse are interrelated because of their co-occurrence. Different patterns of childhood abuse and neglect are associated with the degree of severity of mental disorders in adulthood. The purpose of this study was (a) to identify different patterns of childhood maltreatment in a representative German community sample, (b) to replicate the patterns of childhood neglect and abuse recently found in a clinical German sample, (c) to examine whether participants reporting exposure to specific patterns of child maltreatment would report different levels of psychological distress, and (d) to compare the results of the typological approach and the results of a cumulative risk model based on our data set. Methods In a cross-sectional survey conducted in 2010, a representative random sample of 2504 German participants aged between 14 and 92 years completed the Childhood Trauma Questionnaire (CTQ). General anxiety and depression were assessed by standardized questionnaires (GAD-2, PHQ-2). Cluster analysis was conducted with the CTQ-subscales to identify different patterns of childhood maltreatment. Results Three different patterns of childhood abuse and neglect could be identified by cluster analysis. Cluster one showed low values on all CTQ-scales. Cluster two showed high values in emotional and physical neglect. Only cluster three showed high values in physical and sexual abuse. The three patterns of childhood maltreatment showed different degrees of depression (PHQ-2) and anxiety (GAD-2). Cluster one showed lowest levels of psychological distress, cluster three showed highest levels of mental distress. Conclusion The results show that different types of childhood maltreatment are interrelated and can be grouped into specific patterns of childhood abuse and neglect, which are associated with differing severity of psychological distress in adulthood. The results correspond to those recently found in a German clinical sample and support a typological approach in the research of maltreatment. While cumulative risk models focus on the number of maltreatment types, the typological approach takes the number as well as the severity of the maltreatment types into account. Thus, specific patterns of maltreatment can be examined with regard to specific long-term psychological consequences. PMID:27442446

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

PubMed

Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

2012-11-02

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.

Characterizing the Small Scale Structure in Clusters of Galaxies

NASA Technical Reports Server (NTRS)

Forman, William R.

2001-01-01

We studied galaxy clusters Abell 119, Abell 754, and Abell 1750, using data from the ASCA and ROSAT satellites. In addition, we completed the paper "Merging Binary Clusters". In this paper we study three prominent bi-modal X-ray clusters: A3528, A1750 and A3395. Since the sub-clusters in these systems have projected separations of 0.93, 1.00 and 0.67 Mpc respectively, we examine their X-ray and optical observations to investigate the dynamics and possible merging of these sub-clusters. Using data taken with ROSAT and ASCA, we analyze the temperature and surface brightness distributions. We also analyze the velocity distributions of the three clusters using new measurements supplemented with previously published data. We examined both the overall cluster properties as well as the two sub-cluster elements in each. These results were then applied to the determination of the overall cluster masses, that demonstrate excellent consistency between the various methods used. While the characteristic parameters of the sub-clusters are typical of isolated objects, our temperature results for the regions between the two sub-clusters clearly confirm the presence of merger activity that is suggested by the surface brightness distributions. These three clusters represent a progression of equal-sized sub-cluster mergers, starting from initial contact to immediately before first core passage.

The transcriptome of a complete episode of acute otitis media.

PubMed

Hernandez, Michelle; Leichtle, Anke; Pak, Kwang; Webster, Nicholas J; Wasserman, Stephen I; Ryan, Allen F

2015-04-03

Otitis media is the most common disease of childhood, and represents an important health challenge to the 10-15% of children who experience chronic/recurrent middle ear infections. The middle ear undergoes extensive modifications during otitis media, potentially involving changes in the expression of many genes. Expression profiling offers an opportunity to discover novel genes and pathways involved in this common childhood disease. The middle ears of 320 WBxB6 F1 hybrid mice were inoculated with non-typeable Haemophilus influenzae (NTHi) or PBS (sham control). Two independent samples were generated for each time point and condition, from initiation of infection to resolution. RNA was profiled on Affymetrix mouse 430 2.0 whole-genome microarrays. Approximately 8% of the sampled transcripts defined the signature of acute NTHi-induced otitis media across time. Hierarchical clustering of signal intensities revealed several temporal gene clusters. Network and pathway enrichment analysis of these clusters identified sets of genes involved in activation of the innate immune response, negative regulation of immune response, changes in epithelial and stromal cell markers, and the recruitment/function of neutrophils and macrophages. We also identified key transcriptional regulators related to events in otitis media, which likely determine the expression of these gene clusters. A list of otitis media susceptibility genes, derived from genome-wide association and candidate gene studies, was significantly enriched during the early induction phase and the middle re-modeling phase of otitis but not in the resolution phase. Our results further indicate that positive versus negative regulation of inflammatory processes occur with highly similar kinetics during otitis media, underscoring the importance of anti-inflammatory responses in controlling pathogenesis. The results characterize the global gene response during otitis media and identify key signaling and transcription factor networks that control the defense of the middle ear against infection. These networks deserve further attention, as dysregulated immune defense and inflammatory responses may contribute to recurrent or chronic otitis in children.

"To be or not to be Retained … That's the Question!" Retention, Self-esteem, Self-concept, Achievement Goals, and Grades.

PubMed

Peixoto, Francisco; Monteiro, Vera; Mata, Lourdes; Sanches, Cristina; Pipa, Joana; Almeida, Leandro S

2016-01-01

Keeping students back in the same grade - retention - has always been a controversial issue in Education, with some defending it as a beneficial remedial practice and others arguing against its detrimental effects. This paper undertakes an analysis of this issue, focusing on the differences in student motivation and self-related variables according to their retention related status, and the interrelationship between retention and these variables. The participants were 695 students selected from two cohorts (5th and 7th graders) of a larger group of students followed over a 3-year project. The students were assigned to four groups according to their retention-related status over time: (1) students with past and recent retention; (2) students with past but no recent retention; (3) students with no past but recent retention; (4) students with no past or recent retention. Measures of achievement goal orientations, self-concept, self-esteem, importance given to school subjects and Grade Point Average (GPA) were collected for all students. Repeated measures MANCOVA analyses were carried out showing group differences in self-esteem, academic self-concept, importance attributed to academic competencies, task and avoidance orientation and academic achievement. To attain a deeper understanding of these results and to identify profiles across variables, a cluster analysis based on achievement goals was conducted and four clusters were identified. Students who were retained at the end of the school year are mainly represented in clusters with less adaptive motivational profiles and almost absent from clusters exhibiting more adaptive ones. Findings highlight that retention leaves a significant mark that remains even when students recover academic achievement and retention is in the distant past. This is reflected in the low academic self-concept as well as in the devaluation of academic competencies and in the avoidance orientation which, taken together, can undermine students' academic adjustment and turn retention into a risk factor.

“To be or not to be Retained … That’s the Question!” Retention, Self-esteem, Self-concept, Achievement Goals, and Grades

PubMed Central

Peixoto, Francisco; Monteiro, Vera; Mata, Lourdes; Sanches, Cristina; Pipa, Joana; Almeida, Leandro S.

2016-01-01

Keeping students back in the same grade – retention – has always been a controversial issue in Education, with some defending it as a beneficial remedial practice and others arguing against its detrimental effects. This paper undertakes an analysis of this issue, focusing on the differences in student motivation and self-related variables according to their retention related status, and the interrelationship between retention and these variables. The participants were 695 students selected from two cohorts (5th and 7th graders) of a larger group of students followed over a 3-year project. The students were assigned to four groups according to their retention-related status over time: (1) students with past and recent retention; (2) students with past but no recent retention; (3) students with no past but recent retention; (4) students with no past or recent retention. Measures of achievement goal orientations, self-concept, self-esteem, importance given to school subjects and Grade Point Average (GPA) were collected for all students. Repeated measures MANCOVA analyses were carried out showing group differences in self-esteem, academic self-concept, importance attributed to academic competencies, task and avoidance orientation and academic achievement. To attain a deeper understanding of these results and to identify profiles across variables, a cluster analysis based on achievement goals was conducted and four clusters were identified. Students who were retained at the end of the school year are mainly represented in clusters with less adaptive motivational profiles and almost absent from clusters exhibiting more adaptive ones. Findings highlight that retention leaves a significant mark that remains even when students recover academic achievement and retention is in the distant past. This is reflected in the low academic self-concept as well as in the devaluation of academic competencies and in the avoidance orientation which, taken together, can undermine students’ academic adjustment and turn retention into a risk factor. PMID:27790167

Spheroid Culture of Head and Neck Cancer Cells Reveals an Important Role of EGFR Signalling in Anchorage Independent Survival.

PubMed

Braunholz, Diana; Saki, Mohammad; Niehr, Franziska; Öztürk, Merve; Borràs Puértolas, Berta; Konschak, Robert; Budach, Volker; Tinhofer, Ingeborg

2016-01-01

In solid tumours millions of cells are shed into the blood circulation each day. Only a subset of these circulating tumour cells (CTCs) survive, many of them presumable because of their potential to form multi-cellular clusters also named spheroids. Tumour cells within these spheroids are protected from anoikis, which allows them to metastasize to distant organs or re-seed at the primary site. We used spheroid cultures of head and neck squamous cell carcinoma (HNSCC) cell lines as a model for such CTC clusters for determining the role of the epidermal growth factor receptor (EGFR) in cluster formation ability and cell survival after detachment from the extra-cellular matrix. The HNSCC cell lines FaDu, SCC-9 and UT-SCC-9 (UT-SCC-9P) as well as its cetuximab (CTX)-resistant sub-clone (UT-SCC-9R) were forced to grow in an anchorage-independent manner by coating culture dishes with the anti-adhesive polymer poly-2-hydroxyethylmethacrylate (poly-HEMA). The extent of apoptosis, clonogenic survival and EGFR signalling under such culture conditions was evaluated. The potential of spheroid formation in suspension culture was found to be positively correlated with the proliferation rate of HNSCC cell lines as well as their basal EGFR expression levels. CTX and gefitinib blocked, whereas the addition of EGFR ligands promoted anchorage-independent cell survival and spheroid formation. Increased spheroid formation and growth were associated with persistent activation of EGFR and its downstream signalling component (MAPK/ERK). Importantly, HNSCC cells derived from spheroid cultures retained their clonogenic potential in the absence of cell-matrix contact. Addition of CTX under these conditions strongly inhibited colony formation in CTX-sensitive cell lines but not their resistant subclones. Altogether, EGFR activation was identified as crucial factor for anchorage-independent survival of HNSCC cells. Targeting EGFR in CTC cluster formation might represent an attractive anti-metastatic treatment approach in HNSCC.

Characterizing the degree of convective clustering using radar reflectivity and its application to evaluating model simulations

NASA Astrophysics Data System (ADS)

Cheng, W. Y.; Kim, D.; Rowe, A.; Park, S.

2017-12-01

Despite the impact of mesoscale convective organization on the properties of convection (e.g., mixing between updrafts and environment), parameterizing the degree of convective organization has only recently been attempted in cumulus parameterization schemes (e.g., Unified Convection Scheme UNICON). Additionally, challenges remain in determining the degree of convective organization from observations and in comparing directly with the organization metrics in model simulations. This study addresses the need to objectively quantify the degree of mesoscale convective organization using high quality S-PolKa radar data from the DYNAMO field campaign. One of the most noticeable aspects of mesoscale convective organization in radar data is the degree of convective clustering, which can be characterized by the number and size distribution of convective echoes and the distance between them. We propose a method of defining contiguous convective echoes (CCEs) using precipitating convective echoes identified by a rain type classification algorithm. Two classification algorithms, Steiner et al. (1995) and Powell et al. (2016), are tested and evaluated against high-resolution WRF simulations to determine which method better represents the degree of convective clustering. Our results suggest that the CCEs based on Powell et al.'s algorithm better represent the dynamical properties of the convective updrafts and thus provide the basis of a metric for convective organization. Furthermore, through a comparison with the observational data, the WRF simulations driven by the DYNAMO large-scale forcing, similarly applied to UNICON Single Column Model simulations, will allow us to evaluate the ability of both WRF and UNICON to simulate convective clustering. This evaluation is based on the physical processes that are explicitly represented in WRF and UNICON, including the mechanisms leading to convective clustering, and the feedback to the convective properties.

Automatic detection of erythemato-squamous diseases using k-means clustering.

PubMed

Ubeyli, Elif Derya; Doğdu, Erdoğan

2010-04-01

A new approach based on the implementation of k-means clustering is presented for automated detection of erythemato-squamous diseases. The purpose of clustering techniques is to find a structure for the given data by finding similarities between data according to data characteristics. The studied domain contained records of patients with known diagnosis. The k-means clustering algorithm's task was to classify the data points, in this case the patients with attribute data, to one of the five clusters. The algorithm was used to detect the five erythemato-squamous diseases when 33 features defining five disease indications were used. The purpose is to determine an optimum classification scheme for this problem. The present research demonstrated that the features well represent the erythemato-squamous diseases and the k-means clustering algorithm's task achieved high classification accuracies for only five erythemato-squamous diseases.

Novel size-dependent chemistry within ionized van der Waals clusters of 1,1-difluoroethane

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coolbaugh, M.T.; Peifer, W.R.; Garvey, J.F.

1990-02-22

The authors present in this paper evidence for size-dependent cluster chemistry occurring in van der Waals clusters of 1,1-difluoroethane. Clusters of C{sub 2}H{sub 4}F{sub 2} are produced from a neat adiabatic expansion and are ionized via electron impact. In addition to the anticipated fragment ions, we observe ions with the general empirical formula of M{sub n}H{sup +} (where n {ge} 4). The reactive process that generates this species cannot be rationalized in terms of intramolecular analogues of known gas-phase bimolecular ion-molecular reactions. Hence, we fell the production of this product cluster ion represents an additional example of a brand newmore » class of ion-molecule reactions that can only occur within the unique solvated environment of the cluster.« less

Understanding 3D human torso shape via manifold clustering

NASA Astrophysics Data System (ADS)

Li, Sheng; Li, Peng; Fu, Yun

2013-05-01

Discovering the variations in human torso shape plays a key role in many design-oriented applications, such as suit designing. With recent advances in 3D surface imaging technologies, people can obtain 3D human torso data that provide more information than traditional measurements. However, how to find different human shapes from 3D torso data is still an open problem. In this paper, we propose to use spectral clustering approach on torso manifold to address this problem. We first represent high-dimensional torso data in a low-dimensional space using manifold learning algorithm. Then the spectral clustering method is performed to get several disjoint clusters. Experimental results show that the clusters discovered by our approach can describe the discrepancies in both genders and human shapes, and our approach achieves better performance than the compared clustering method.

Non Thermal Emission from Clusters of Galaxies: the Importance of a Joint LOFAR/Simbol-X View

NASA Astrophysics Data System (ADS)

Ferrari, C.

2009-05-01

Deep radio observations of galaxy clusters have revealed the existence of diffuse radio sources (``halos'' and ``relics'') related to the presence of relativistic electrons and weak magnetic fields in the intracluster volume. I will outline our current knowledge about the presence and properties of this non-thermal cluster component. Despite the recent progress made in observational and theoretical studies of the non-thermal emission in galaxy clusters, a number of open questions about its origin and its effects on the thermo-dynamical evolution of galaxy clusters need to be answered. I will show the importance of combining galaxy cluster observations by new-generation instruments such as LOFAR and Simbol-X. A deeper knowledge of the non-thermal cluster component, together with statistical studies of radio halos and relics, will allow to test the current cluster formation scenario and to better constrain the physics of large scale structure evolution.

Characterization of a Major Cluster of nif, fix, and Associated Genes in a Sugarcane Endophyte, Acetobacter diazotrophicus

PubMed Central

Lee, Sunhee; Reth, Alexander; Meletzus, Dietmar; Sevilla, Myrna; Kennedy, Christina

2000-01-01

A major 30.5-kb cluster of nif and associated genes of Acetobacter diazotrophicus (syn. Gluconacetobacter diazotrophicus), a nitrogen-fixing endophyte of sugarcane, was sequenced and analyzed. This cluster represents the largest assembly of contiguous nif-fix and associated genes so far characterized in any diazotrophic bacterial species. Northern blots and promoter sequence analysis indicated that the genes are organized into eight transcriptional units. The overall arrangement of genes is most like that of the nif-fix cluster in Azospirillum brasilense, while the individual gene products are more similar to those in species of Rhizobiaceae or in Rhodobacter capsulatus. PMID:11092875

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Generalized clustering conditions of Jack polynomials at negative Jack parameter {alpha}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernevig, B. Andrei; Department of Physics, Princeton University, Princeton, New Jersey 08544; Haldane, F. D. M.

We present several conjectures on the behavior and clustering properties of Jack polynomials at a negative parameter {alpha}=-(k+1/r-1), with partitions that violate the (k,r,N)- admissibility rule of [Feigin et al. [Int. Math. Res. Notices 23, 1223 (2002)]. We find that the ''highest weight'' Jack polynomials of specific partitions represent the minimum degree polynomials in N variables that vanish when s distinct clusters of k+1 particles are formed, where s and k are positive integers. Explicit counting formulas are conjectured. The generalized clustering conditions are useful in a forthcoming description of fractional quantum Hall quasiparticles.

Bayesian Decision Theoretical Framework for Clustering

ERIC Educational Resources Information Center

Chen, Mo

2011-01-01

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

Comparison of the quadratic configuration interaction and coupled cluster approaches to electron correlation including the effect of triple excitations

NASA Technical Reports Server (NTRS)

Taylor, Peter R.; Lee, Timothy J.; Rendell, Alistair P.

1990-01-01

The recently proposed quadratic configuration interaction (QCI) method is compared with the more rigorous coupled cluster (CC) approach for a variety of chemical systems. Some of these systems are well represented by a single-determinant reference function and others are not. The finite order singles and doubles correlation energy, the perturbational triples correlation energy, and a recently devised diagnostic for estimating the importance of multireference effects are considered. The spectroscopic constants of CuH, the equilibrium structure of cis-(NO)2 and the binding energies of Be3, Be4, Mg3, and Mg4 were calculated using both approaches. The diagnostic for estimating multireference character clearly demonstrates that the QCI method becomes less satisfactory than the CC approach as non-dynamical correlation becomes more important, in agreement with a perturbational analysis of the two methods and the numerical estimates of the triple excitation energies they yield. The results for CuH show that the differences between the two methods become more apparent as the chemical systems under investigation becomes more multireference in nature and the QCI results consequently become less reliable. Nonetheless, when the system of interest is dominated by a single reference determinant both QCI and CC give very similar results.

Circadian and seasonal variation of migraine attacks in children.

PubMed

Soriani, Stefano; Fiumana, Elisa; Manfredini, Roberto; Boari, Benedetta; Battistella, Pier Antonio; Canetta, Elisabetta; Pedretti, Stefania; Borgna-Pignatti, Caterina

2006-01-01

To investigate the rhythmicity of migraine episodes without aura in a pediatric population. Time of occurrence of 2517 migraine attacks in 115 children was recorded, by means of a diary, both by hourly and monthly intervals. A significant circadian variation, characterized by a peak in the afternoon (P < .001) and one in the early morning (P= .002) was found. A seasonal peak was also observed between November and January, while a nadir was observed in July. The clustering of attacks in the morning and midday and in autumn-winter, with a minimum frequency in July, suggests that school activities may represent an important cause of migraine.

Pleiades Visions

NASA Astrophysics Data System (ADS)

Whitehouse, M.

2016-01-01

Pleiades Visions (2012) is my new musical composition for organ that takes inspiration from traditional lore and music associated with the Pleiades (Seven Sisters) star cluster from Australian Aboriginal, Native American, and Native Hawaiian cultures. It is based on my doctoral dissertation research incorporating techniques from the fields of ethnomusicology and cultural astronomy; this research likely represents a new area of inquiry for both fields. This large-scale work employs the organ's vast sonic resources to evoke the majesty of the night sky and the expansive landscapes of the homelands of the above-mentioned peoples. Other important themes in Pleiades Visions are those of place, origins, cosmology, and the creation of the world.

Particular Distribution of Enterobacter cloacae Strains Isolated from Urinary Tract Infection within Clonal Complexes.

PubMed

Akbari, Majid; Bakhshi, Bita; Najar Peerayeh, Shahin

2016-01-01

Based on biochemical properties, Enterobacter cloacae represents a large complex of at least 13 variant species, subspecies, and genotypes that progressively identified as the most species causing hospital-acquired infections. The aim of this study was to determine the relevance between phylogenetically related strains within the E. cloacae complex and the frequency of urinary tract infection caused by them. A 268-bp fragment was obtained from hsp60 gene for 50 clinical E. cloacae isolates from urine cultures of inpatients that admitted to six hospitals in Tehran, Iran during December 2012 to November 2013. The 107 nucleotide sequences were analyzed and the evolutionary distances of sequences were computed and neighbor-joining tree was calculated. It showed that all of the genetic clusters have not an equal involvement in pathogenesis of urinary tract infections. Three superior clusters were found, together representing more than two third (80%) of the isolates (cluster VI with 25 members; clusters III and VIII with 9 and 6 members, respectively) and some genetic clusters were absent (IV, X, XII, and xiii), some of which are supposed to be associated with plants and no human infection has been reported. This study, for the first time, reports the unequal contribution of E. cloacae complex subspecies and clusters in urinary tract infections in Iran and together with studies from other countries suggest that the subspecies of E.hormaechei subsp. Oharae is the most prevalent E. cloacae complex subspecies regardless of country under study.

Surface passivation for tight-binding calculations of covalent solids.

PubMed

Bernstein, N

2007-07-04

Simulation of a cluster representing a finite portion of a larger covalently bonded system requires the passivation of the cluster surface. We compute the effects of an explicit hybrid orbital passivation (EHOP) on the atomic structure in a model bulk, three-dimensional, narrow gap semiconductor, which is very different from the wide gap, quasi-one-dimensional organic molecules where most passivation schemes have been studied in detail. The EHOP approach is directly applicable to minimal atomic orbital basis methods such as tight-binding. Each broken bond is passivated by a hybrid created from an explicitly expressed linear combination of basis orbitals, chosen to represent the contribution of the missing neighbour, e.g. a sp(3) hybrid for a single bond. The method is tested by computing the forces on atoms near a point defect as a function of cluster geometry. We show that, compared to alternatives such as pseudo-hydrogen passivation, the force on an atom converges to the correct bulk limit more quickly as a function of cluster radius, and that the force is more stable with respect to perturbations in the position of the cluster centre. The EHOP method also obviates the need for parameterizing the interactions between the system atoms and the passivating atoms. The method is useful for cluster calculations of non-periodic defects in large systems and for hybrid schemes that simulate large systems by treating finite regions with a quantum-mechanical model, coupled to an interatomic potential description of the rest of the system.

Surface passivation for tight-binding calculations of covalent solids

NASA Astrophysics Data System (ADS)

Bernstein, N.

2007-07-01

Simulation of a cluster representing a finite portion of a larger covalently bonded system requires the passivation of the cluster surface. We compute the effects of an explicit hybrid orbital passivation (EHOP) on the atomic structure in a model bulk, three-dimensional, narrow gap semiconductor, which is very different from the wide gap, quasi-one-dimensional organic molecules where most passivation schemes have been studied in detail. The EHOP approach is directly applicable to minimal atomic orbital basis methods such as tight-binding. Each broken bond is passivated by a hybrid created from an explicitly expressed linear combination of basis orbitals, chosen to represent the contribution of the missing neighbour, e.g. a sp3 hybrid for a single bond. The method is tested by computing the forces on atoms near a point defect as a function of cluster geometry. We show that, compared to alternatives such as pseudo-hydrogen passivation, the force on an atom converges to the correct bulk limit more quickly as a function of cluster radius, and that the force is more stable with respect to perturbations in the position of the cluster centre. The EHOP method also obviates the need for parameterizing the interactions between the system atoms and the passivating atoms. The method is useful for cluster calculations of non-periodic defects in large systems and for hybrid schemes that simulate large systems by treating finite regions with a quantum-mechanical model, coupled to an interatomic potential description of the rest of the system.

Definition of run-off-road crash clusters-For safety benefit estimation and driver assistance development.

PubMed

Nilsson, Daniel; Lindman, Magdalena; Victor, Trent; Dozza, Marco

2018-04-01

Single-vehicle run-off-road crashes are a major traffic safety concern, as they are associated with a high proportion of fatal outcomes. In addressing run-off-road crashes, the development and evaluation of advanced driver assistance systems requires test scenarios that are representative of the variability found in real-world crashes. We apply hierarchical agglomerative cluster analysis to define similarities in a set of crash data variables, these clusters can then be used as the basis in test scenario development. Out of 13 clusters, nine test scenarios are derived, corresponding to crashes characterised by: drivers drifting off the road in daytime and night-time, high speed departures, high-angle departures on narrow roads, highways, snowy roads, loss-of-control on wet roadways, sharp curves, and high speeds on roads with severe road surface conditions. In addition, each cluster was analysed with respect to crash variables related to the crash cause and reason for the unintended lane departure. The study shows that cluster analysis of representative data provides a statistically based method to identify relevant properties for run-off-road test scenarios. This was done to support development of vehicle-based run-off-road countermeasures and driver behaviour models used in virtual testing. Future studies should use driver behaviour from naturalistic driving data to further define how test-scenarios and behavioural causation mechanisms should be included. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exhaustive comparison and classification of ligand-binding surfaces in proteins

PubMed Central

Murakami, Yoichi; Kinoshita, Kengo; Kinjo, Akira R; Nakamura, Haruki

2013-01-01

Many proteins function by interacting with other small molecules (ligands). Identification of ligand-binding sites (LBS) in proteins can therefore help to infer their molecular functions. A comprehensive comparison among local structures of LBSs was previously performed, in order to understand their relationships and to classify their structural motifs. However, similar exhaustive comparison among local surfaces of LBSs (patches) has never been performed, due to computational complexity. To enhance our understanding of LBSs, it is worth performing such comparisons among patches and classifying them based on similarities of their surface configurations and electrostatic potentials. In this study, we first developed a rapid method to compare two patches. We then clustered patches corresponding to the same PDB chemical component identifier for a ligand, and selected a representative patch from each cluster. We subsequently exhaustively as compared the representative patches and clustered them using similarity score, PatSim. Finally, the resultant PatSim scores were compared with similarities of atomic structures of the LBSs and those of the ligand-binding protein sequences and functions. Consequently, we classified the patches into ∼2000 well-characterized clusters. We found that about 63% of these clusters are used in identical protein folds, although about 25% of the clusters are conserved in distantly related proteins and even in proteins with cross-fold similarity. Furthermore, we showed that patches with higher PatSim score have potential to be involved in similar biological processes. PMID:23934772

Molecular evolution of the HoxA cluster in the three major gnathostome lineages

PubMed Central

Chiu, Chi-hua; Amemiya, Chris; Dewar, Ken; Kim, Chang-Bae; Ruddle, Frank H.; Wagner, Günter P.

2002-01-01

The duplication of Hox clusters and their maintenance in a lineage has a prominent but little understood role in chordate evolution. Here we examined how Hox cluster duplication may influence changes in cluster architecture and patterns of noncoding sequence evolution. We sequenced the entire duplicated HoxAa and HoxAb clusters of zebrafish (Danio rerio) and extended the 5′ (posterior) part of the HoxM (HoxA-like) cluster of horn shark (Heterodontus francisci) containing the hoxa11 and hoxa13 orthologs as well as intergenic and flanking noncoding sequences. The duplicated HoxA clusters in zebrafish each house considerably fewer genes and are dramatically shorter than the single HoxA clusters of human and horn shark. We compared the intergenic sequences of the HoxA clusters of human, horn shark, zebrafish (Aa, Ab), and striped bass and found extensive conservation of noncoding sequence motifs, i.e., phylogenetic footprints, between the human and horn shark, representing two of the three gnathostome lineages. These are putative cis-regulatory elements that may play a role in the regulation of the ancestral HoxA cluster. In contrast, homologous regions of the duplicated HoxAa and HoxAb clusters of zebrafish and the HoxA cluster of striped bass revealed a striking loss of conservation of these putative cis-regulatory sequences in the 3′ (anterior) segment of the cluster, where zebrafish only retains single representatives of group 1, 3, 4, and 5 (HoxAa) and group 2 (HoxAb) genes and in the 5′ part of the clusters, where zebrafish retains two copies of the group 13, 11, and 9 genes, i.e., AbdB-like genes. In analyzing patterns of cis-sequence evolution in the 5′ part of the clusters, we explicitly looked for evidence of complementary loss of conserved noncoding sequences, as predicted by the duplication-degeneration-complementation model in which genetic redundancy after gene duplication is resolved because of the fixation of complementary degenerative mutations. Our data did not yield evidence supporting this prediction. We conclude that changes in the pattern of cis-sequence conservation after Hox cluster duplication are more consistent with being the outcome of adaptive modification rather than passive mechanisms that erode redundancy created by the duplication event. These results support the view that genome duplications may provide a mechanism whereby master control genes undergo radical modifications conducive to major alterations in body plan. Such genomic revolutions may contribute significantly to the evolutionary process. PMID:11943847

The Schoolwide Cluster Grouping Model: Restructuring Gifted Education Services for the 21st Century

ERIC Educational Resources Information Center

Brulles, Dina; Winebrenner, Susan

2011-01-01

Schools today are experiencing dramatic changes in how they serve gifted students. Gifted programs that have prevailed for years are disappearing. In response, an increasing number of schools are turning to the Schoolwide Cluster Grouping Model (SCGM) to serve their gifted students. When implemented well, the SCGM represents one viable solution…

Do Country Stereotypes Exist in PISA? A Clustering Approach for Large, Sparse, and Weighted Data

ERIC Educational Resources Information Center

Saarela, Mirka; Kärkkäinen, Tommi

2015-01-01

Certain stereotypes can be associated with people from different countries. For example, the Italians are expected to be emotional, the Germans functional, and the Chinese hard-working. In this study, we cluster all 15-year-old students representing the 68 different nations and territories that participated in the latest Programme for…

Using Self-Organizing Map (SOM) Clusters of Ozonesonde Profiles to Evaluate Climatologies and Create Linkages between Meteorology and Pollution

NASA Astrophysics Data System (ADS)

Stauffer, R. M.; Thompson, A. M.; Young, G. S.; Oltmans, S. J.; Johnson, B.

2016-12-01

Ozone (O3) climatologies are typically created by averaging ozonesonde profiles on a monthly or seasonal basis, either for specific regions or zonally. We demonstrate the advantages of using a statistical clustering technique, self-organizing maps (SOM), over this simple averaging, through analysis of more than 4500 sonde profiles taken from the long-term US sites at Boulder, CO; Huntsville, AL; Trinidad Head, CA; and Wallops Island, VA. First, we apply SOM to O3 mixing ratios from surface to 12 km amsl. At all four sites, profiles in SOM clusters exhibit similar tropopause height, 500 hPa height and temperature, and total and tropospheric column O3. Second, when profiles from each SOM cluster are compared to monthly O3 means, near-tropopause O3 in three of the clusters is double (over +100 ppbv) the climatological O3 mixing ratio. The three clusters include 13-16% of all profiles, mostly from winter and spring. Large mid-tropospheric deviations from monthly means are found in two highly-populated clusters that represent either distinctly polluted (summer) or clean O3 (fall-winter, high tropopause) profiles. Thus, SOM indeed appear to represent US O3 profile statistics better than conventional climatologies. In the case of Trinidad Head, SOM clusters of O3 profile data from the lower troposphere (surface-6 km amsl) can discriminate background vs polluted O3 and the meteorology associated with each. Two of nine O3 clusters exhibit thin layers ( 100s of m thick) of high O3, typically between 1 and 4 km. Comparisons between clusters and downwind, high-altitude surface O3 measurements display a marked impact of the elevated tropospheric O­­3. Days corresponding to the high O3 clusters exhibit hourly surface O3 anomalies at surface sites of +5 -10 ppbv compared to a climatology; the anomalies can last up to four days. We also explore applications of SOM to tropical ozonesonde profiles, where tropospheric O3 variability is generally smaller.

Clustering in analytical chemistry.

PubMed

Drab, Klaudia; Daszykowski, Michal

2014-01-01

Data clustering plays an important role in the exploratory analysis of analytical data, and the use of clustering methods has been acknowledged in different fields of science. In this paper, principles of data clustering are presented with a direct focus on clustering of analytical data. The role of the clustering process in the analytical workflow is underlined, and its potential impact on the analytical workflow is emphasized.

Geotemporal Analysis of Neisseria meningitidis Clones in the United States: 2000–2005

PubMed Central

Wiringa, Ann E.; Shutt, Kathleen A.; Marsh, Jane W.; Cohn, Amanda C.; Messonnier, Nancy E.; Zansky, Shelley M.; Petit, Susan; Farley, Monica M.; Gershman, Ken; Lynfield, Ruth; Reingold, Arthur; Schaffner, William; Thompson, Jamie; Brown, Shawn T.; Lee, Bruce Y.; Harrison, Lee H.

2013-01-01

Background The detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic. Methods Meningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model. Results Among 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States. Conclusions Around 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations. PMID:24349182

Comparison of Cluster, Slab, and Analytic Potential Models for the Dimethyl Methylphosphonate (DMMP)/TiO2 (110) Intermolecular Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Li; Tunega, Daniel; Xu, Lai

2013-08-29

In a previous study (J. Phys. Chem. C 2011, 115, 12403) cluster models for the TiO2 rutile (110) surface and MP2 calculations were used to develop an analytic potential energy function for dimethyl methylphosphonate (DMMP) interacting with this surface. In the work presented here, this analytic potential and MP2 cluster models are compared with DFT "slab" calculations for DMMP interacting with the TiO2 (110) surface and with DFT cluster models for the TiO2 (110) surface. The DFT slab calculations were performed with the PW91 and PBE functionals. The analytic potential gives DMMP/ TiO2 (110) potential energy curves in excellent agreementmore » with those obtained from the slab calculations. The cluster models for the TiO2 (110) surface, used for the MP2 calculations, were extended to DFT calculations with the B3LYP, PW91, and PBE functional. These DFT calculations do not give DMMP/TiO2 (110) interaction energies which agree with those from the DFT slab calculations. Analyses of the wave functions for these cluster models show that they do not accurately represent the HOMO and LUMO for the surface, which should be 2p and 3d orbitals, respectively, and the models also do not give an accurate band gap. The MP2 cluster models do not accurately represent the LUMO and that they give accurate DMMP/TiO2 (110) interaction energies is apparently fortuitous, arising from their highly inaccurate band gaps. Accurate cluster models, consisting of 7, 10, and 15 Ti-atoms and which have the correct HOMO and LUMO properties, are proposed. The work presented here illustrates the care that must be taken in "constructing" cluster models which accurately model surfaces.« less

The nature of plant species

PubMed Central

Rieseberg, Loren H.; Wood, Troy E.; Baack, Eric J.

2008-01-01

Many botanists doubt the existence of plant species1–5, viewing them as arbitrary constructs of the human mind, as opposed to discrete, objective entities that represent reproductively independent lineages or ‘units of evolution’. However, the discreteness of plant species and their correspondence with reproductive communities have not been tested quantitatively, allowing zoologists to argue that botanists have been overly influenced by a few ‘botanical horror stories’, such as dandelions, blackberries and oaks6,7. Here we analyse phenetic and/or crossing relationships in over 400 genera of plants and animals. We show that although discrete phenotypic clusters exist in most genera (>80%), the correspondence of taxonomic species to these clusters is poor (<60%) and no different between plants and animals. Lack of congruence is caused by polyploidy, asexual reproduction and over-differentiation by taxonomists, but not by contemporary hybridization. Nonetheless, crossability data indicate that 70% of taxonomic species and 75% of phenotypic clusters in plants correspond to reproductively independent lineages (as measured by postmating isolation), and thus represent biologically real entities. Contrary to conventional wisdom8, plant species are more likely than animal species to represent reproductively independent lineages. PMID:16554818

Complete genome sequence of the bacteriochlorophyll a-containing Roseibacterium elongatum type strain (DSM 19469T), a representative of the Roseobacter group isolated from Australian coast sand

PubMed Central

Riedel, Thomas; Fiebig, Anne; Göker, Markus; Klenk, Hans-Peter

2014-01-01

Roseibacterium elongatum Suzuki et al. 2006 is a pink-pigmented and bacteriochlorophyll a-producing representative of the Roseobacter group within the alphaproteobacterial family Rhodobacteraceae. Representatives of the marine ‘Roseobacter group’ were found to be abundant in the ocean and play an important role in global and biogeochemical processes. In the present study we describe the features of R. elongatum strain OCh 323T together with its genome sequence and annotation. The 3,555,102 bp long genome consists of one circular chromosome with no extrachromosomal elements and is one of the smallest known Roseobacter genomes. It contains 3,540 protein-coding genes and 59 RNA genes. Genome analysis revealed the presence of a photosynthetic gene cluster, which putatively enables a photoheterotrophic lifestyle. Gene sequences associated with quorum sensing, motility, surface attachment, and thiosulfate and carbon monoxide oxidation could be detected. The genome was sequenced as part of the activities of the Transregional Collaborative Research Centre 51 (TRR51) funded by the German Research Foundation (DFG). PMID:25197467

Complete genome sequence of the bacteriochlorophyll a-containing Roseibacterium elongatum type strain (DSM 19469(T)), a representative of the Roseobacter group isolated from Australian coast sand.

PubMed

Riedel, Thomas; Fiebig, Anne; Göker, Markus; Klenk, Hans-Peter

2014-06-15

Roseibacterium elongatum Suzuki et al. 2006 is a pink-pigmented and bacteriochlorophyll a-producing representative of the Roseobacter group within the alphaproteobacterial family Rhodobacteraceae. Representatives of the marine 'Roseobacter group' were found to be abundant in the ocean and play an important role in global and biogeochemical processes. In the present study we describe the features of R. elongatum strain OCh 323(T) together with its genome sequence and annotation. The 3,555,102 bp long genome consists of one circular chromosome with no extrachromosomal elements and is one of the smallest known Roseobacter genomes. It contains 3,540 protein-coding genes and 59 RNA genes. Genome analysis revealed the presence of a photosynthetic gene cluster, which putatively enables a photoheterotrophic lifestyle. Gene sequences associated with quorum sensing, motility, surface attachment, and thiosulfate and carbon monoxide oxidation could be detected. The genome was sequenced as part of the activities of the Transregional Collaborative Research Centre 51 (TRR51) funded by the German Research Foundation (DFG).

Quantitative analysis of nano-pore geomaterials and representative sampling for digital rock physics

NASA Astrophysics Data System (ADS)

Yoon, H.; Dewers, T. A.

2014-12-01

Geomaterials containing nano-pores (e.g., shales and carbonate rocks) have become increasingly important for emerging problems such as unconventional gas and oil resources, enhanced oil recovery, and geologic storage of CO2. Accurate prediction of coupled geophysical and chemical processes at the pore scale requires realistic representation of pore structure and topology. This is especially true for chalk materials, where pore networks are small and complex, and require characterization at sub-micron scale. In this work, we apply laser scanning confocal microscopy to characterize pore structures and microlithofacies at micron- and greater scales and dual focused ion beam-scanning electron microscopy (FIB-SEM) for 3D imaging of nanometer-to-micron scale microcracks and pore distributions. With imaging techniques advanced for nano-pore characterization, a problem of scale with FIB-SEM images is how to take nanometer scale information and apply it to the thin-section or larger scale. In this work, several texture characterization techniques including graph-based spectral segmentation, support vector machine, and principal component analysis are applied for segmentation clusters represented by 1-2 FIB-SEM samples per each cluster. Geometric and topological properties are analyzed and lattice-Boltzmann method (LBM) is used to obtain permeability at several different scales. Upscaling of permeability to the Darcy scale (e.g., the thin-section scale) with image dataset will be discussed with emphasis on understanding microfracture-matrix interaction, representative volume for FIB-SEM sampling, and multiphase flow and reactive transport. Funding from the DOE Basic Energy Sciences Geosciences Program is gratefully acknowledged. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Exploring the Host Parasitism of the Migratory Plant-Parasitic Nematode Ditylenchus destuctor by Expressed Sequence Tags Analysis

PubMed Central

Peng, Huan; Gao, Bing-li; Kong, Ling-an; Yu, Qing; Huang, Wen-kun; He, Xu-feng; Long, Hai-bo; Peng, De-liang

2013-01-01

The potato rot nematode, Ditylenchus destructor, is a very destructive nematode pest on many agriculturally important crops worldwide, but the molecular characterization of its parasitism of plant has been limited. The effectors involved in nematode parasitism of plant for several sedentary endo-parasitic nematodes such as Heterodera glycines, Globodera rostochiensis and Meloidogyne incognita have been identified and extensively studied over the past two decades. Ditylenchus destructor, as a migratory plant parasitic nematode, has different feeding behavior, life cycle and host response. Comparing the transcriptome and parasitome among different types of plant-parasitic nematodes is the way to understand more fully the parasitic mechanism of plant nematodes. We undertook the approach of sequencing expressed sequence tags (ESTs) derived from a mixed stage cDNA library of D. destructor. This is the first study of D. destructor ESTs. A total of 9800 ESTs were grouped into 5008 clusters including 3606 singletons and 1402 multi-member contigs, representing a catalog of D. destructor genes. Implementing a bioinformatics' workflow, we found 1391 clusters have no match in the available gene database; 31 clusters only have similarities to genes identified from D. africanus, the most closely related species to D. destructor; 1991 clusters were annotated using Gene Ontology (GO); 1550 clusters were assigned enzyme commission (EC) numbers; and 1211 clusters were mapped to 181 KEGG biochemical pathways. 22 ESTs had similarities to reported nematode effectors. Interestedly, most of the effectors identified in this study are involved in host cell wall degradation or modification, such as 1,4-beta-glucanse, 1,3-beta-glucanse, pectate lyase, chitinases and expansin, or host defense suppression such as calreticulin, annexin and venom allergen-like protein. This result implies that the migratory plant-parasitic nematode D. destructor secrets similar effectors to those of sedentary plant nematodes. Finally we further characterized the two D. destructor expansin proteins. PMID:23922743

Genetic characterization of the hemagglutinin genes of wild-type measles virus circulating in china, 1993-2009.

PubMed

Xu, Songtao; Zhang, Yan; Zhu, Zhen; Liu, Chunyu; Mao, Naiying; Ji, Yixin; Wang, Huiling; Jiang, Xiaohong; Li, Chongshan; Tang, Wei; Feng, Daxing; Wang, Changyin; Zheng, Lei; Lei, Yue; Ling, Hua; Zhao, Chunfang; Ma, Yan; He, Jilan; Wang, Yan; Li, Ping; Guan, Ronghui; Zhou, Shujie; Zhou, Jianhui; Wang, Shuang; Zhang, Hong; Zheng, Huanying; Liu, Leng; Ma, Hemuti; Guan, Jing; Lu, Peishan; Feng, Yan; Zhang, Yanjun; Zhou, Shunde; Xiong, Ying; Ba, Zhuoma; Chen, Hui; Yang, Xiuhui; Bo, Fang; Ma, Yujie; Liang, Yong; Lei, Yake; Gu, Suyi; Liu, Wei; Chen, Meng; Featherstone, David; Jee, Youngmee; Bellini, William J; Rota, Paul A; Xu, Wenbo

2013-01-01

China experienced several large measles outbreaks in the past two decades, and a series of enhanced control measures were implemented to achieve the goal of measles elimination. Molecular epidemiologic surveillance of wild-type measles viruses (MeV) provides valuable information about the viral transmission patterns. Since 1993, virologic surveillnace has confirmed that a single endemic genotype H1 viruses have been predominantly circulating in China. A component of molecular surveillance is to monitor the genetic characteristics of the hemagglutinin (H) gene of MeV, the major target for virus neutralizing antibodies. Analysis of the sequences of the complete H gene from 56 representative wild-type MeV strains circulating in China during 1993-2009 showed that the H gene sequences were clustered into 2 groups, cluster 1 and cluster 2. Cluster1 strains were the most frequently detected cluster and had a widespread distribution in China after 2000. The predicted amino acid sequences of the H protein were relatively conserved at most of the functionally significant amino acid positions. However, most of the genotype H1 cluster1 viruses had an amino acid substitution (Ser240Asn), which removed a predicted N-linked glycosylation site. In addition, the substitution of Pro397Leu in the hemagglutinin noose epitope (HNE) was identified in 23 of 56 strains. The evolutionary rate of the H gene of the genotype H1 viruses was estimated to be approximately 0.76×10(-3) substitutions per site per year, and the ratio of dN to dS (dN/dS) was <1 indicating the absence of selective pressure. Although H genes of the genotype H1 strains were conserved and not subjected to selective pressure, several amino acid substitutions were observed in functionally important positions. Therefore the antigenic and genetic properties of H genes of wild-type MeVs should be monitored as part of routine molecular surveillance for measles in China.

A cluster-analytic approach towards multidimensional health-related behaviors in adolescents: the MoMo-Study

PubMed Central

2012-01-01

Background Although knowledge on single health-related behaviors and their association with health parameters is available, research on multiple health-related behaviors is needed to understand the interactions among these behaviors. The aims of the study were (a) to identify typical health-related behavior patterns in German adolescents focusing on physical activity, media use and dietary behavior; (b) to describe the socio-demographic correlates of the identified clusters and (c) to study their association with overweight. Methods Within the framework of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS) and the “Motorik-Modul” (MoMo), 1,643 German adolescents (11–17 years) completed a questionnaire assessing the amount and type of weekly physical activity in sports clubs and during leisure time, weekly use of television, computer and console games and the frequency and amount of food consumption. From this data the three indices ‘physical activity’, ‘media use’ and ‘healthy nutrition’ were derived and included in a cluster analysis conducted with Ward’s Method and K-means analysis. Chi-square tests were performed to identify socio-demographic correlates of the clusters as well as their association with overweight. Results Four stable clusters representing typical health-related behavior patterns were identified: Cluster 1 (16.2%)—high scores in physical activity index and average scores in media use index and healthy nutrition index; cluster 2 (34.6%)—high healthy nutrition score and below average scores in the other two indices; cluster 3 (18.4%)—low physical activity score, low healthy nutrition score and very high media use score; cluster 4 (30.5%)—below average scores on all three indices. Boys were overrepresented in the clusters 1 and 3, and the relative number of adolescents with low socio-economic status as well as overweight was significantly higher than average in cluster 3. Conclusions Meaningful and stable clusters of health-related behavior were identified. These results confirm findings of another youth study hence supporting the assumption that these clusters represent typical behavior patterns of adolescents. These results are particularly relevant for the characterization of target groups for primary prevention of lifestyle diseases. PMID:23273134

Utilization of Molecular, Phenotypic, and Geographical Diversity to Develop Compact Composite Core Collection in the Oilseed Crop, Safflower (Carthamus tinctorius L.) through Maximization Strategy

PubMed Central

Kumar, Shivendra; Ambreen, Heena; Variath, Murali T.; Rao, Atmakuri R.; Agarwal, Manu; Kumar, Amar; Goel, Shailendra; Jagannath, Arun

2016-01-01

Safflower (Carthamus tinctorius L.) is a dryland oilseed crop yielding high quality edible oil. Previous studies have described significant phenotypic variability in the crop and used geographical distribution and phenotypic trait values to develop core collections. However, the molecular diversity component was lacking in the earlier collections thereby limiting their utility in breeding programs. The present study evaluated the phenotypic variability for 12 agronomically important traits during two growing seasons (2011–12 and 2012–13) in a global reference collection of 531 safflower accessions, assessed earlier by our group for genetic diversity and population structure using AFLP markers. Significant phenotypic variation was observed for all the agronomic traits in the representative collection. Cluster analysis of phenotypic data grouped the accessions into five major clusters. Accessions from the Indian Subcontinent and America harbored maximal phenotypic variability with unique characters for a few traits. MANOVA analysis indicated significant interaction between genotypes and environment for both the seasons. Initially, six independent core collections (CC1–CC6) were developed using molecular marker and phenotypic data for two seasons through POWERCORE and MSTRAT. These collections captured the entire range of trait variability but failed to include complete genetic diversity represented in 19 clusters reported earlier through Bayesian analysis of population structure (BAPS). Therefore, we merged the three POWERCORE core collections (CC1–CC3) to generate a composite core collection, CartC1 and three MSTRAT core collections (CC4–CC6) to generate another composite core collection, CartC2. The mean difference percentage, variance difference percentage, variable rate of coefficient of variance percentage, coincidence rate of range percentage, Shannon's diversity index, and Nei's gene diversity for CartC1 were 11.2, 43.7, 132.4, 93.4, 0.47, and 0.306, respectively while the corresponding values for CartC2 were 9.3, 58.8, 124.6, 95.8, 0.46, and 0.301. Each composite core collection represented the complete range of phenotypic and genetic variability of the crop including 19 BAPS clusters. This is the first report describing development of core collections in safflower using molecular marker data with phenotypic values and geographical distribution. These core collections will facilitate identification of genetic determinants of trait variability and effective utilization of the prevalent diversity in crop improvement programs. PMID:27807441

Developing a model for effective leadership in healthcare: a concept mapping approach

PubMed Central

Hargett, Charles William; Doty, Joseph P; Hauck, Jennifer N; Webb, Allison MB; Cook, Steven H; Tsipis, Nicholas E; Neumann, Julie A; Andolsek, Kathryn M; Taylor, Dean C

2017-01-01

Purpose Despite increasing awareness of the importance of leadership in healthcare, our understanding of the competencies of effective leadership remains limited. We used a concept mapping approach (a blend of qualitative and quantitative analysis of group processes to produce a visual composite of the group’s ideas) to identify stakeholders’ mental model of effective healthcare leadership, clarifying the underlying structure and importance of leadership competencies. Methods Literature review, focus groups, and consensus meetings were used to derive a representative set of healthcare leadership competency statements. Study participants subsequently sorted and rank-ordered these statements based on their perceived importance in contributing to effective healthcare leadership in real-world settings. Hierarchical cluster analysis of individual sortings was used to develop a coherent model of effective leadership in healthcare. Results A diverse group of 92 faculty and trainees individually rank-sorted 33 leadership competency statements. The highest rated statements were “Acting with Personal Integrity”, “Communicating Effectively”, “Acting with Professional Ethical Values”, “Pursuing Excellence”, “Building and Maintaining Relationships”, and “Thinking Critically”. Combining the results from hierarchical cluster analysis with our qualitative data led to a healthcare leadership model based on the core principle of Patient Centeredness and the core competencies of Integrity, Teamwork, Critical Thinking, Emotional Intelligence, and Selfless Service. Conclusion Using a mixed qualitative-quantitative approach, we developed a graphical representation of a shared leadership model derived in the healthcare setting. This model may enhance learning, teaching, and patient care in this important area, as well as guide future research. PMID:29355249

Identification of clinically relevant phenotypes in patients with Ebstein anomaly.

PubMed

Cabrera, Rodrigo; Miranda-Fernández, Marta Catalina; Huertas-Quiñones, Victor Manuel; Carreño, Marisol; Pineda, Ivonne; Restrepo, Carlos M; Silva, Claudia Tamar; Quero, Rossi; Cano, Juan David; Manrique, Diana Carolina; Camacho, Camila; Tabares, Sebastián; García, Alberto; Sandoval, Néstor; Moreno Medina, Karen Julieth; Dennis Verano, Rodolfo José

2018-03-01

Ebstein anomaly (EA) is a heterogeneous congenital heart defect (CHD), frequently accompanied by diverse cardiac and extracardiac comorbidities, resulting in a wide range of clinical outcomes. Phenotypic characterization of EA patients has the potential to identify variables that influence prognosis and subgroups with distinct contributing factors. A comprehensive cross-sectional phenotypic characterization of 147 EA patients from one of the main referral institutions for CHD in Colombia was carried out. The most prevalent comorbidities and distinct subgroups within the patient cohort were identified through cluster analysis. The most prevalent cardiac comorbidities identified were atrial septal defect (61%), Wolff-Parkinson-White syndrome (WPW; 27%), and right ventricular outflow tract obstruction (25%). Cluster analysis showed that patients can be classified into 2 distinct subgroups with defined phenotypes that determine disease severity and survival. Patients in cluster 1 represented a particularly homogeneous subgroup with a milder spectrum of disease, including only patients with WPW and/or supraventricular tachycardia (SVT). Cluster 2 included patients with more diverse cardiovascular comorbidities. This study represents one of the largest phenotypic characterizations of EA patients reported. The data show that EA is a heterogeneous disease, very frequently associated with cardiovascular and noncardiovascular comorbidities. Patients with WPW and SVT represent a homogeneous subgroup that presents with a less severe spectrum of disease and better survival when adequately managed. This should be considered when searching for genetic causes of EA and in the clinical setting. © 2018 Wiley Periodicals, Inc.

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

PubMed

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

State of stress and crustal fluid migration related to west-dipping structures in the slab-forearc system in the northern Chilean subduction zone

NASA Astrophysics Data System (ADS)

Salazar, P.; Kummerow, J.; Wigger, P.; Shapiro, S.; Asch, G.

2017-03-01

Previous studies in the forearc of the northern Chilean subduction zone have identified important tectonic features in the upper crust. As a result of these works, the West Fissure Fault System (WFFS) has recently been imaged using microseismic events. The WFFS is the westward-dipping, sharp lower boundary of the northern Chilean forearc and is geometrically opposed to subduction of the Nazca plate. The present article builds on this previous work and is novel in that it characterizes this structure's stress distribution using focal mechanisms and stress tensor analysis. The results of the stress tensor analysis show that the state of stress in the WFFS is related to its strike-slip tectonic context and likely represents a manifestation of local forces associated with the highest areas in the Andes. Two seismic clusters have also been identified; these clusters may be associated with a blind branch of the WFFS. We studied these clusters in order to determine their sources and possible connection with fluid migration across the upper plate. We observed that the two clusters differ from one another in some regards. The central cluster has characteristics consistent with an earthquake swarm with two clearly identifiable phases. Conversely, the SW cluster has a clear main shock associated with it, and it can be separated into two subclusters (A and A΄). In contrast, similarities among the two clusters suggest that the clusters may have a common origin. The b-values for both clusters are characteristic of tectonic plate boundaries. The spatial spreading, which is approximately confined to one plane, reflects progressive growth of the main fracture underlying the swarm and subcluster A. We also find that earthquakes themselves trigger aftershocks near the borders of their rupture areas. In addition, the spatio-temporal migration of hypocentres, as well as their spatial correlation with areas that are interpreted to be fluid migration zones, suggest that there is a close relationship between fluid movement and the earthquake sources associated with the swarm and subcluster A. These observations point to stick-slip behaviour of the rupture propagation, which can be explained by earthquake-induced stress transfer and fluid flow in a fluid-permeated, critically loaded fault zone.

Holographic vortices in the presence of dark matter sector

NASA Astrophysics Data System (ADS)

Rogatko, Marek; Wysokinski, Karol I.

2015-12-01

The dark matter seem to be an inevitable ingredient of the total matter configuration in the Universe and the knowledge how the dark matter affects the properties of superconductors is of vital importance for the experiments aimed at its direct detection. The homogeneous magnetic field acting perpendicularly to the surface of (2+1) dimensional s-wave holographic superconductor in the theory with dark matter sector has been modeled by the additional U(1)-gauge field representing dark matter and coupled to the Maxwell one. As expected the free energy for the vortex configuration turns out to be negative. Importantly its value is lower in the presence of dark matter sector. This feature can explain why in the Early Universe first the web of dark matter appeared and next on these gratings the ordinary matter forming cluster of galaxies has formed.

Some remarks on extragalactic globular clusters

NASA Astrophysics Data System (ADS)

Richtler, Tom

2006-03-01

I comment (in a review fashion) on a few selected topics in the field of extragalactic globular clusters with strong emphasis on recent work. The topics are: bimodality in the colour distribution of cluster systems, young massive clusters, and the brightest old clusters. Globular cluster research, per- haps more than ever, has lead to important (at least to astronomers) progress and problems in galaxy structure and formation.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

On the multi-scale description of micro-structured fluids composed of aggregating rods

NASA Astrophysics Data System (ADS)

Perez, Marta; Scheuer, Adrien; Abisset-Chavanne, Emmanuelle; Ammar, Amine; Chinesta, Francisco; Keunings, Roland

2018-05-01

When addressing the flow of concentrated suspensions composed of rods, dense clusters are observed. Thus, the adequate modelling and simulation of such a flow requires addressing the kinematics of these dense clusters and their impact on the flow in which they are immersed. In a former work, we addressed a first modelling framework of these clusters, assumed so dense that they were considered rigid and their kinematics (flow-induced rotation) were totally defined by a symmetric tensor c with unit trace representing the cluster conformation. Then, the rigid nature of the clusters was relaxed, assuming them deformable, and a model giving the evolution of both the cluster shape and its microstructural orientation descriptor (the so-called shape and orientation tensors) was proposed. This paper compares the predictions coming from those models with finer-scale discrete simulations inspired from molecular dynamics modelling.

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fluckiger, L.; Rupp, D.; Adolph, M.

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

Time-resolved x-ray imaging of a laser-induced nanoplasma and its neutral residuals

DOE PAGES

Fluckiger, L.; Rupp, D.; Adolph, M.; ...

2016-04-13

The evolution of individual, large gas-phase xenon clusters, turned into a nanoplasma by a high power infrared laser pulse, is tracked from femtoseconds up to nanoseconds after laser excitation via coherent diffractive imaging, using ultra-short soft x-ray free electron laser pulses. A decline of scattering signal at high detection angles with increasing time delay indicates a softening of the cluster surface. Here we demonstrate, for the first time a representative speckle pattern of a new stage of cluster expansion for xenon clusters after a nanosecond irradiation. The analysis of the measured average speckle size and the envelope of the intensitymore » distribution reveals a mean cluster size and length scale of internal density fluctuations. Furthermore, the measured diffraction patterns were reproduced by scattering simulations which assumed that the cluster expands with pronounced internal density fluctuations hundreds of picoseconds after excitation.« less

Molecular growth from a Mo176 to a Mo248 cluster

NASA Astrophysics Data System (ADS)

Müller, A.; Shah, Syed Q. N.; Bögge, H.; Schmidtmann, M.

1999-01-01

In polyoxometalate chemistry a large variety of compounds, clusters and solid-state structures can be formed by the linking together of well-defined metal-oxygen building blocks, . These species exhibit unusual topological and electronic properties, andfind applications ranging from medicine to industrial processes. The recently reported ring-shaped mixed-valence polyoxomolybdates of the type {Mo154} (refs 5, 6) and {Mo176} (refs 7, 8) represent a new class of giant clusters with nanometre-sized cavities and interesting properties for host-guest chemistry. Here we describe the formation of related clusters of the type {Mo248} formed by addition of further units to the inner surface of the {Mo176 } `wheel'. The additional units arrange themselves into two {Mo36} `hub-caps' on the initial wheel-clusters that are not stable in isolation. These findings reveal a new pathway to the development of complex coordination clusters.

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

PubMed Central

Bushel, Pierre R; Wolfinger, Russell D; Gibson, Greg

2007-01-01

Background Commonly employed clustering methods for analysis of gene expression data do not directly incorporate phenotypic data about the samples. Furthermore, clustering of samples with known phenotypes is typically performed in an informal fashion. The inability of clustering algorithms to incorporate biological data in the grouping process can limit proper interpretation of the data and its underlying biology. Results We present a more formal approach, the modk-prototypes algorithm, for clustering biological samples based on simultaneously considering microarray gene expression data and classes of known phenotypic variables such as clinical chemistry evaluations and histopathologic observations. The strategy involves constructing an objective function with the sum of the squared Euclidean distances for numeric microarray and clinical chemistry data and simple matching for histopathology categorical values in order to measure dissimilarity of the samples. Separate weighting terms are used for microarray, clinical chemistry and histopathology measurements to control the influence of each data domain on the clustering of the samples. The dynamic validity index for numeric data was modified with a category utility measure for determining the number of clusters in the data sets. A cluster's prototype, formed from the mean of the values for numeric features and the mode of the categorical values of all the samples in the group, is representative of the phenotype of the cluster members. The approach is shown to work well with a simulated mixed data set and two real data examples containing numeric and categorical data types. One from a heart disease study and another from acetaminophen (an analgesic) exposure in rat liver that causes centrilobular necrosis. Conclusion The modk-prototypes algorithm partitioned the simulated data into clusters with samples in their respective class group and the heart disease samples into two groups (sick and buff denoting samples having pain type representative of angina and non-angina respectively) with an accuracy of 79%. This is on par with, or better than, the assignment accuracy of the heart disease samples by several well-known and successful clustering algorithms. Following modk-prototypes clustering of the acetaminophen-exposed samples, informative genes from the cluster prototypes were identified that are descriptive of, and phenotypically anchored to, levels of necrosis of the centrilobular region of the rat liver. The biological processes cell growth and/or maintenance, amine metabolism, and stress response were shown to discern between no and moderate levels of acetaminophen-induced centrilobular necrosis. The use of well-known and traditional measurements directly in the clustering provides some guarantee that the resulting clusters will be meaningfully interpretable. PMID:17408499

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

An improved clustering algorithm based on reverse learning in intelligent transportation

NASA Astrophysics Data System (ADS)

Qiu, Guoqing; Kou, Qianqian; Niu, Ting

2017-05-01

With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.

Cluster kinetics model for mixtures of glassformers

NASA Astrophysics Data System (ADS)

Brenskelle, Lisa A.; McCoy, Benjamin J.

2007-10-01

For glassformers we propose a binary mixture relation for parameters in a cluster kinetics model previously shown to represent pure compound data for viscosity and dielectric relaxation as functions of either temperature or pressure. The model parameters are based on activation energies and activation volumes for cluster association-dissociation processes. With the mixture parameters, we calculated dielectric relaxation times and compared the results to experimental values for binary mixtures. Mixtures of sorbitol and glycerol (seven compositions), sorbitol and xylitol (three compositions), and polychloroepihydrin and polyvinylmethylether (three compositions) were studied.

Simulating radiative feedback and star cluster formation in GMCs - II. Mass dependence of cloud destruction and cluster properties

NASA Astrophysics Data System (ADS)

Howard, Corey S.; Pudritz, Ralph E.; Harris, William E.

2017-09-01

The process of radiative feedback in giant molecular clouds (GMCs) is an important mechanism for limiting star cluster formation through the heating and ionization of the surrounding gas. We explore the degree to which radiative feedback affects early (≲5 Myr) cluster formation in GMCs having masses that range from 104 to 106 M⊙ using the flash code. The inclusion of radiative feedback lowers the efficiency of cluster formation by 20-50 per cent relative to hydrodynamic simulations. Two models in particular - 5 × 104 and 105 M⊙ - show the largest suppression of the cluster formation efficiency, corresponding to a factor of ˜2. For these clouds only, the internal energy, a measure of the energy injected by radiative feedback, exceeds the gravitational potential for a significant amount of time. We find a clear relation between the maximum cluster mass, Mc,max, formed in a GMC and the mass of the GMC itself, MGMC: Mc,max ∝ M_{GMC}^{0.81}. This scaling result suggests that young globular clusters at the necessary scale of 106 M⊙ form within host GMCs of masses near ˜5 × 107 M⊙. We compare simulated cluster mass distributions to the observed embedded cluster mass function [d log (N)/dlog (M) ∝ Mβ where β = -1] and find good agreement (β = -0.99 ± 0.14) only for simulations including radiative feedback, indicating this process is important in controlling the growth of young clusters. However, the high star formation efficiencies, which range from 16 to 21 per cent, and high star formation rates compared to locally observed regions suggest other feedback mechanisms are also important during the formation and growth of stellar clusters.

Public priorities for osteoporosis and fracture research: results from a general population survey.

PubMed

Paskins, Zoe; Jinks, Clare; Mahmood, Waheed; Jayakumar, Prakash; Sangan, Caroline B; Belcher, John; Gwilym, Stephen

2017-12-01

This is the first national study of public and patient research priorities in osteoporosis and fracture. We have identified new research areas of importance to members of the public, particularly 'access to information from health professionals'. The findings are being incorporated into the research strategy of the National Osteoporosis Society. This study aimed to prioritise, with patients and public members, research topics for the osteoporosis research agenda. An e-survey to identify topics for research was co-designed with patient representatives. A link to the e-survey was disseminated to supporters of the UK National Osteoporosis Society (NOS) in a monthly e-newsletter. Responders were asked to indicate their top priority for research across four topics (understanding and preventing osteoporosis, living with osteoporosis, treating osteoporosis and treating fractures) and their top three items within each topic. Descriptive statistics were used to describe demographics and item ranking. A latent class analysis was applied to identify a substantive number of clusters with different combinations of binary responses. One thousand one hundred eighty-eight (7.4%) respondents completed the e-survey. The top three items overall were 'Having easy access to advice and information from health professionals' (63.8%), 'Understanding further the safety and benefit of osteoporosis drug treatments' (49.9%) and 'Identifying the condition early by screening' (49.2%). Latent class analysis revealed distinct clusters of responses within each topic including primary care management and self-management. Those without a history of prior fracture or aged under 70 were more likely to rate items within the cluster of self-management as important (21.0 vs 12.9 and 19.8 vs 13.3%, respectively). This is the first study of public research priorities in osteoporosis and has identified new research areas of importance to members of the public including access to information. The findings are being incorporated into the research strategy of the National Osteoporosis Society.

Combining Mixture Components for Clustering*

PubMed Central

Baudry, Jean-Patrick; Raftery, Adrian E.; Celeux, Gilles; Lo, Kenneth; Gottardo, Raphaël

2010-01-01

Model-based clustering consists of fitting a mixture model to data and identifying each cluster with one of its components. Multivariate normal distributions are typically used. The number of clusters is usually determined from the data, often using BIC. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to represent one non-Gaussian cluster by a mixture of two or more Gaussian distributions. If the number of mixture components is interpreted as the number of clusters, this can lead to overestimation of the number of clusters. This is because BIC selects the number of mixture components needed to provide a good approximation to the density, rather than the number of clusters as such. We propose first selecting the total number of Gaussian mixture components, K, using BIC and then combining them hierarchically according to an entropy criterion. This yields a unique soft clustering for each number of clusters less than or equal to K. These clusterings can be compared on substantive grounds, and we also describe an automatic way of selecting the number of clusters via a piecewise linear regression fit to the rescaled entropy plot. We illustrate the method with simulated data and a flow cytometry dataset. Supplemental Materials are available on the journal Web site and described at the end of the paper. PMID:20953302

The correlation of metrics in complex networks with applications in functional brain networks

NASA Astrophysics Data System (ADS)

Li, C.; Wang, H.; de Haan, W.; Stam, C. J.; Van Mieghem, P.

2011-11-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients between widely studied network metrics in three network models (Bárabasi-Albert graphs, Erdös-Rényi random graphs and Watts-Strogatz small-world graphs) as well as in functional brain networks of healthy subjects. The metric correlations, which we have observed and theoretically explained, motivate us to propose a small representative set of metrics by including only one metric from each subset of mutually strongly dependent metrics. The following contributions are considered important. (a) A network with a given degree distribution can indeed be characterized by a small representative set of metrics. (b) Unweighted networks, which are obtained from weighted functional brain networks with a fixed threshold, and Erdös-Rényi random graphs follow a similar degree distribution. Moreover, their metric correlations and the resultant representative metrics are similar as well. This verifies the influence of degree distribution on metric correlations. (c) Most metric correlations can be explained analytically. (d) Interestingly, the most studied metrics so far, the average shortest path length and the clustering coefficient, are strongly correlated and, thus, redundant. Whereas spectral metrics, though only studied recently in the context of complex networks, seem to be essential in network characterizations. This representative set of metrics tends to both sufficiently and effectively characterize networks with a given degree distribution. In the study of a specific network, however, we have to at least consider the representative set so that important network properties will not be neglected.

Cluster structures influenced by interaction with a surface.

PubMed

Witt, Christopher; Dieterich, Johannes M; Hartke, Bernd

2018-05-30

Clusters on surfaces are vitally important for nanotechnological applications. Clearly, cluster-surface interactions heavily influence the preferred cluster structures, compared to clusters in vacuum. Nevertheless, systematic explorations and an in-depth understanding of these interactions and how they determine the cluster structures are still lacking. Here we present an extension of our well-established non-deterministic global optimization package OGOLEM from isolated clusters to clusters on surfaces. Applying this approach to intentionally simple Lennard-Jones test systems, we produce a first systematic exploration that relates changes in cluster-surface interactions to resulting changes in adsorbed cluster structures.

Molecular Dynamics Simulations of the [2Fe-2S] Cluster-Binding Domain of NEET Proteins Reveal Key Molecular Determinants That Induce Their Cluster Transfer/Release.

PubMed

Pesce, Luca; Calandrini, Vania; Marjault, Henri-Baptiste; Lipper, Colin H; Rossetti, Gulia; Mittler, Ron; Jennings, Patricia A; Bauer, Andreas; Nechushtai, Rachel; Carloni, Paolo

2017-11-30

The NEET proteins are a novel family of iron-sulfur proteins characterized by an unusual three cysteine and one histidine coordinated [2Fe-2S] cluster. Aberrant cluster release, facilitated by the breakage of the Fe-N bond, is implicated in a variety of human diseases, including cancer. Here, the molecular dynamics in the multi-microsecond timescale, along with quantum chemical calculations, on two representative members of the family (the human NAF-1 and mitoNEET proteins), show that the loss of the cluster is associated with a dramatic decrease in secondary and tertiary structure. In addition, the calculations provide a mechanism for cluster release and clarify, for the first time, crucial differences existing between the two proteins, which are reflected in the experimentally observed difference in the pH-dependent cluster reactivity. The reliability of our conclusions is established by an extensive comparison with the NMR data of the solution proteins, in part measured in this work.

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

ERIC Educational Resources Information Center

Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.

2009-01-01

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

Incremental Criterion Validity of the WJ-III COG Clinical Clusters: Marginal Predictive Effects beyond the General Factor

ERIC Educational Resources Information Center

McGill, Ryan J.

2015-01-01

The current study examined the incremental validity of the clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ-III COG) for predicting scores on the Woodcock-Johnson III Tests of Achievement (WJ-III ACH). All participants were children and adolescents (N = 4,722) drawn from the nationally representative WJ-III…

Isolation and molecular characterization of newly emerging avian reovirus variants and novel strains in Pennsylvania, USA, 2011-2014.

PubMed

Lu, Huaguang; Tang, Yi; Dunn, Patricia A; Wallner-Pendleton, Eva A; Lin, Lin; Knoll, Eric A

2015-10-15

Avian reovirus (ARV) infections of broiler and turkey flocks have caused significant clinical disease and economic losses in Pennsylvania (PA) since 2011. Most of the ARV-infected birds suffered from severe arthritis, tenosynovitis, pericarditis and depressed growth or runting-stunting syndrome (RSS). A high morbidity (up to 20% to 40%) was observed in ARV-affected flocks, and the flock mortality was occasionally as high as 10%. ARV infections in turkeys were diagnosed for the first time in PA in 2011. From 2011 to 2014, a total of 301 ARV isolations were made from affected PA poultry. The molecular characterization of the Sigma C gene of 114 field isolates, representing most ARV outbreaks, revealed that only 21.93% of the 114 sequenced ARV isolates were in the same genotyping cluster (cluster 1) as the ARV vaccine strains (S1133, 1733, and 2048), whereas 78.07% of the sequenced isolates were in genotyping clusters 2, 3, 4, 5, and 6 (which were distinct from the vaccine strains) and represented newly emerging ARV variants. In particular, genotyping cluster 6 was a new ARV genotype that was identified for the first time in 10 novel PA ARV variants of field isolates.

Impact of metal and anion substitutions on the hydrogen storage properties of M-BTT metal-organic frameworks.

PubMed

Sumida, Kenji; Stück, David; Mino, Lorenzo; Chai, Jeng-Da; Bloch, Eric D; Zavorotynska, Olena; Murray, Leslie J; Dincă, Mircea; Chavan, Sachin; Bordiga, Silvia; Head-Gordon, Martin; Long, Jeffrey R

2013-01-23

Microporous metal-organic frameworks are a class of materials being vigorously investigated for mobile hydrogen storage applications. For high-pressure storage at ambient temperatures, the M(3)[(M(4)Cl)(3)(BTT)(8)](2) (M-BTT; BTT(3-) = 1,3,5-benzenetristetrazolate) series of frameworks are of particular interest due to the high density of exposed metal cation sites on the pore surface. These sites give enhanced zero-coverage isosteric heats of adsorption (Q(st)) approaching the optimal value for ambient storage applications. However, the Q(st) parameter provides only a limited insight into the thermodynamics of the individual adsorption sites, the tuning of which is paramount for optimizing the storage performance. Here, we begin by performing variable-temperature infrared spectroscopy studies of Mn-, Fe-, and Cu-BTT, allowing the thermodynamics of H(2) adsorption to be probed experimentally. This is complemented by a detailed DFT study, in which molecular fragments representing the metal clusters within the extended solid are simulated to obtain a more thorough description of the structural and thermodynamic aspects of H(2) adsorption at the strongest binding sites. Then, the effect of substitutions at the metal cluster (metal ion and anion within the tetranuclear cluster) is discussed, showing that the configuration of this unit indeed plays an important role in determining the affinity of the framework toward H(2). Interestingly, the theoretical study has identified that the Zn-based analogs would be expected to facilitate enhanced adsorption profiles over the compounds synthesized experimentally, highlighting the importance of a combined experimental and theoretical approach to the design and synthesis of new frameworks for H(2) storage applications.

Overlapping communities from dense disjoint and high total degree clusters

NASA Astrophysics Data System (ADS)

Zhang, Hongli; Gao, Yang; Zhang, Yue

2018-04-01

Community plays an important role in the field of sociology, biology and especially in domains of computer science, where systems are often represented as networks. And community detection is of great importance in the domains. A community is a dense subgraph of the whole graph with more links between its members than between its members to the outside nodes, and nodes in the same community probably share common properties or play similar roles in the graph. Communities overlap when nodes in a graph belong to multiple communities. A vast variety of overlapping community detection methods have been proposed in the literature, and the local expansion method is one of the most successful techniques dealing with large networks. The paper presents a density-based seeding method, in which dense disjoint local clusters are searched and selected as seeds. The proposed method selects a seed by the total degree and density of local clusters utilizing merely local structures of the network. Furthermore, this paper proposes a novel community refining phase via minimizing the conductance of each community, through which the quality of identified communities is largely improved in linear time. Experimental results in synthetic networks show that the proposed seeding method outperforms other seeding methods in the state of the art and the proposed refining method largely enhances the quality of the identified communities. Experimental results in real graphs with ground-truth communities show that the proposed approach outperforms other state of the art overlapping community detection algorithms, in particular, it is more than two orders of magnitude faster than the existing global algorithms with higher quality, and it obtains much more accurate community structure than the current local algorithms without any priori information.

Phylogeny of 54 representative strains of species in the family Pasteurellaceae as determined by comparison of 16S rRNA sequences.

PubMed Central

Dewhirst, F E; Paster, B J; Olsen, I; Fraser, G J

1992-01-01

Virtually complete 16S rRNA sequences were determined for 54 representative strains of species in the family Pasteurellaceae. Of these strains, 15 were Pasteurella, 16 were Actinobacillus, and 23 were Haemophilus. A phylogenetic tree was constructed based on sequence similarity, using the Neighbor-Joining method. Fifty-three of the strains fell within four large clusters. The first cluster included the type strains of Haemophilus influenzae, H. aegyptius, H. aphrophilus, H. haemolyticus, H. paraphrophilus, H. segnis, and Actinobacillus actinomycetemcomitans. This cluster also contained A. actinomycetemcomitans FDC Y4, ATCC 29522, ATCC 29523, and ATCC 29524 and H. aphrophilus NCTC 7901. The second cluster included the type strains of A. seminis and Pasteurella aerogenes and H. somnus OVCG 43826. The third cluster was composed of the type strains of Pasteurella multocida, P. anatis, P. avium, P. canis, P. dagmatis, P. gallinarum, P. langaa, P. stomatis, P. volantium, H. haemoglobinophilus, H. parasuis, H. paracuniculus, H. paragallinarum, and A. capsulatus. This cluster also contained Pasteurella species A CCUG 18782, Pasteurella species B CCUG 19974, Haemophilus taxon C CAPM 5111, H. parasuis type 5 Nagasaki, P. volantium (H. parainfluenzae) NCTC 4101, and P. trehalosi NCTC 10624. The fourth cluster included the type strains of Actinobacillus lignieresii, A. equuli, A. pleuropneumoniae, A. suis, A. ureae, H. parahaemolyticus, H. parainfluenzae, H. paraphrohaemolyticus, H. ducreyi, and P. haemolytica. This cluster also contained Actinobacillus species strain CCUG 19799 (Bisgaard taxon 11), A. suis ATCC 15557, H. ducreyi ATCC 27722 and HD 35000, Haemophilus minor group strain 202, and H. parainfluenzae ATCC 29242. The type strain of P. pneumotropica branched alone to form a fifth group. The branching of the Pasteurellaceae family tree was quite complex. The four major clusters contained multiple subclusters. The clusters contained both rapidly and slowly evolving strains (indicated by differing numbers of base changes incorporated into the 16S rRNA sequence relative to outgroup organisms). While the results presented a clear picture of the phylogenetic relationships, the complexity of the branching will make division of the family into genera a difficult and somewhat subjective task. We do not suggest any taxonomic changes at this time. PMID:1548238

Insights into the 1.59-Mbp largest plasmid of Azospirillum brasilense CBG497.

PubMed

Acosta-Cruz, Erika; Wisniewski-Dyé, Florence; Rouy, Zoé; Barbe, Valérie; Valdés, María; Mavingui, Patrick

2012-09-01

The plant growth-promoting proteobacterium Azospirillum brasilense enhances growth of many economically important crops, such as wheat, maize, and rice. The sequencing and annotation of the 1.59-Mbp replicon of A. brasilense CBG497, a strain isolated from a maize rhizosphere grown on an alkaline soil in the northeast of Mexico, revealed a GC content of 68.7 % and the presence of 1,430 potential protein-encoding genes, 1,147 of them classified into clusters of orthologous groups categories, and 16 tRNA genes representing 11 tRNA species. The presence of sixty-two genes representatives of the minimal gene set and chromid core genes suggests its importance in bacterial survival. The phaAB → G operon, reported as involved in the bacterial adaptation to alkaline pH in the presence of K(+), was also found on this replicon and detected in several Azospirillum strains. Phylogenetic analysis suggests that it was laterally acquired. We were not able to show its inference on the adaptation to basic pH, giving a hint about the presence of an alternative system for adaptation to alkaline pH.

Psychosocial Clusters and their Associations with Well-Being and Health: An Empirical Strategy for Identifying Psychosocial Predictors Most Relevant to Racially/Ethnically Diverse Women’s Health

PubMed Central

Jabson, Jennifer M.; Bowen, Deborah; Weinberg, Janice; Kroenke, Candyce; Luo, Juhua; Messina, Catherine; Shumaker, Sally; Tindle, Hilary A.

2016-01-01

BACKGROUND Strategies for identifying the most relevant psychosocial predictors in studies of racial/ethnic minority women’s health are limited because they largely exclude cultural influences and they assume that psychosocial predictors are independent. This paper proposes and tests an empirical solution. METHODS Hierarchical cluster analysis, conducted with data from 140,652 Women’s Health Initiative participants, identified clusters among individual psychosocial predictors. Multivariable analyses tested associations between clusters and health outcomes. RESULTS A Social Cluster and a Stress Cluster were identified. The Social Cluster was positively associated with well-being and inversely associated with chronic disease index, and the Stress Cluster was inversely associated with well-being and positively associated with chronic disease index. As hypothesized, the magnitude of association between clusters and outcomes differed by race/ethnicity. CONCLUSIONS By identifying psychosocial clusters and their associations with health, we have taken an important step toward understanding how individual psychosocial predictors interrelate and how empirically formed Stress and Social clusters relate to health outcomes. This study has also demonstrated important insight about differences in associations between these psychosocial clusters and health among racial/ethnic minorities. These differences could signal the best pathways for intervention modification and tailoring. PMID:27279761

Combination of multilocus sequence typing and pulsed-field gel electrophoresis reveals an association of molecular clonality with the emergence of extensive-drug resistance (XDR) in Salmonella.

PubMed

Cao, Yongzhong; Shen, Yongxiu; Cheng, Lingling; Zhang, Xiaorong; Wang, Chao; Wang, Yan; Zhou, Xiaohui; Chao, Guoxiang; Wu, Yantao

2018-03-01

Salmonellae is one of the most important foodborne pathogens and becomes resistant to multiple antibiotics, which represents a significant challenge to food industry and public health. However, a molecular signature that can be used to distinguish antimicrobial resistance profile, particularly multi-drug resistance or extensive-drug resistance (XDR). In the current study, 168 isolates from the chicken and pork production chains and ill chickens were characterized by serotyping, antimicrobial susceptibility test, multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE). The results showed that these isolates belonged to 13 serotypes, 14 multilocus sequence types (STs), 94 PFGE genotypes, and 70 antimicrobial resistant profiles. S. Enteritidis, S. Indiana, and S. Derby were the predominant serotypes, corresponding to the ST11, ST17, and ST40 clones, respectively and the PFGE Cluster A, Cluster E, and Cluster D, respectively. Among the ST11-S. Enteritidis (Cluster A) and the ST40-S. Derby (Cluster D) clones, the majority of isolates were resistant to 4-8 antimicrobial agents, whereas in the ST17S. Indiana (Cluster E) clone, isolates showed extensive-drug resistance (XDR) to 9-16 antimicrobial agents. The bla TEM-1-like gene was prevalent in the ST11 and ST17 clones corresponding to high ampicillin resistance. The bla TEM-1-like , bla CTX-M , bla OXA-1-like , sul1, aaC4, aac(6')-1b, dfrA17, and floR gene complex was highly prevalent among isolates of ST17, corresponding to an XDR phenotype. These results demonstrated the association of the resistant phenotypes and genotypes with ST clone and PFGE cluster. Our results also indicated that the newly identified gene complex comprising bla TEM-1-like , bla CTX-M , bla OXA-1-like , sul1, aaC4, aac(6')-1b, dfrA17, and floR, was responsible for the emergence of the ST17S. Indiana XDR clone. ST17 could be potentially used as a molecular signature to distinguish S. Indiana XDR clone. Copyright © 2017 Elsevier GmbH. All rights reserved.

Typology of adults diagnosed with mental disorders based on socio-demographics and clinical and service use characteristics

PubMed Central

2011-01-01

Background Mental disorder is a leading cause of morbidity worldwide. Its cost and negative impact on productivity are substantial. Consequently, improving mental health-care system efficiency - especially service utilisation - is a priority. Few studies have explored the use of services by specific subgroups of persons with mental disorder; a better understanding of these individuals is key to improving service planning. This study develops a typology of individuals, diagnosed with mental disorder in a 12-month period, based on their individual characteristics and use of services within a Canadian urban catchment area of 258,000 persons served by a psychiatric hospital. Methods From among the 2,443 people who took part in the survey, 406 (17%) experienced at least one episode of mental disorder (as per the Composite International Diagnostic Interview (CIDI)) in the 12 months pre-interview. These individuals were selected for cluster analysis. Results Analysis yielded four user clusters: people who experienced mainly anxiety disorder; depressive disorder; alcohol and/or drug disorder; and multiple mental and dependence disorder. Two clusters were more closely associated with females and anxiety or depressive disorders. In the two other clusters, males were over-represented compared with the sample as a whole, namely, substance abuses with or without concomitant mental disorder. Clusters with the greatest number of mental disorders per subject used a greater number of mental health-care services. Conversely, clusters associated exclusively with dependence disorders used few services. Conclusion The study found considerable heterogeneity among socio-demographic characteristics, number of disorders, and number of health-care services used by individuals with mental or dependence disorders. Cluster analysis revealed important differences in service use with regard to gender and age. It reinforces the relevance of developing targeted programs for subgroups of individuals with mental and/or dependence disorders. Strategies aimed at changing low service users' attitude (youths and males) or instituting specialised programs for that particular clientele should be promoted. Finally, as concomitant disorders are frequent among individuals with mental disorder, psychological services and/or addiction programs must be prioritised as components of integrated services when planning treatment. PMID:21507251

Classification Scheme for Centuries of Reconstructed Streamflow Droughts in Water Resources Planning

NASA Astrophysics Data System (ADS)

Stagge, J.; Rosenberg, D. E.

2017-12-01

New advances in reconstructing streamflow from tree rings have permitted the reconstruction of flows back to the 1400s or earlier at a monthly, rather than annual, time scale. This is a critical step for incorporating centuries of streamflow reconstructions into water resources planning. Expanding the historical record is particularly important where the observed record contains few of these rare, but potentially disastrous extreme events. We present how a paleo-drought clustering approach was incorporated alongside more traditional water management planning in the Weber River basin, northern Utah. This study used newly developed monthly reconstructions of flow since 1430 CE and defined drought events as flow less than the 50th percentile during at least three contiguous months. Characteristics for each drought event included measures of drought duration, severity, cumulative loss, onset, seasonality, recession rate, and recovery rate. Reconstructed drought events were then clustered by hierarchical clustering to determine distinct drought "types" and the historical event that best represents the centroid of each cluster. The resulting 144 reconstructed drought events in the Weber basin clustered into nine distinct types, of which four were severe enough to potentially require drought management. Using the characteristic drought event for each of the severe drought clusters, water managers were able to estimate system reliability and the historical return frequency for each drought type. Plotting drought duration and severity from centuries of historical reconstructed events alongside observed events and climate change projections further placed recent events into a historical context. For example, the drought of record for the Weber River remains the most severe event in the record with regard to minimum flow percentile (1930, 7 years), but is far from the longest event in the longer historical record, where events beginning in 1658 and 1705 both lasted longer than 13 years. The proposed drought clustering approach provides a powerful tool for merging historical reconstructions, observations, and climate change projections in water resources planning, while also providing a framework to make use of valuable and increasingly available tree-ring reconstructions of monthly streamflow.

Quantifying the abundance of faint, low-redshift satellite galaxies in the COSMOS survey

NASA Astrophysics Data System (ADS)

Xi, ChengYu; Taylor, James E.; Massey, Richard J.; Rhodes, Jason; Koekemoer, Anton; Salvato, Mara

2018-06-01

Faint dwarf satellite galaxies are important as tracers of small-scale structure, but remain poorly characterized outside the Local Group, due to the difficulty of identifying them consistently at larger distances. We review a recently proposed method for estimating the average satellite population around a given sample of nearby bright galaxies, using a combination of size and magnitude cuts (to select low-redshift dwarf galaxies preferentially) and clustering measurements (to estimate the fraction of true satellites in the cut sample). We test this method using the high-precision photometric redshift catalog of the COSMOS survey, exploring the effect of specific cuts on the clustering signal. The most effective of the size-magnitude cuts considered recover the clustering signal around low-redshift primaries (z < 0.15) with about two-thirds of the signal and 80% of the signal-to-noise ratio obtainable using the full COSMOS photometric redshifts. These cuts are also fairly efficient, with more than one third of the selected objects being clustered satellites. We conclude that structural selection represents a useful tool in characterizing dwarf populations to fainter magnitudes and/or over larger areas than are feasible with spectroscopic surveys. In reviewing the low-redshift content of the COSMOS field, we also note the existence of several dozen objects that appear resolved or partially resolved in the HST imaging, and are confirmed to be local (at distances of ˜250 Mpc or less) by their photometric or spectroscopic redshifts. This underlines the potential for future space-based surveys to reveal local populations of intrinsically faint galaxies through imaging alone.

Layer-Specific fMRI Reflects Different Neuronal Computations at Different Depths in Human V1

PubMed Central

Olman, Cheryl A.; Harel, Noam; Feinberg, David A.; He, Sheng; Zhang, Peng; Ugurbil, Kamil; Yacoub, Essa

2012-01-01

Recent work has established that cerebral blood flow is regulated at a spatial scale that can be resolved by high field fMRI to show cortical columns in humans. While cortical columns represent a cluster of neurons with similar response properties (spanning from the pial surface to the white matter), important information regarding neuronal interactions and computational processes is also contained within a single column, distributed across the six cortical lamina. A basic understanding of underlying neuronal circuitry or computations may be revealed through investigations of the distribution of neural responses at different cortical depths. In this study, we used T2-weighted imaging with 0.7 mm (isotropic) resolution to measure fMRI responses at different depths in the gray matter while human subjects observed images with either recognizable or scrambled (physically impossible) objects. Intact and scrambled images were partially occluded, resulting in clusters of activity distributed across primary visual cortex. A subset of the identified clusters of voxels showed a preference for scrambled objects over intact; in these clusters, the fMRI response in middle layers was stronger during the presentation of scrambled objects than during the presentation of intact objects. A second experiment, using stimuli targeted at either the magnocellular or the parvocellular visual pathway, shows that laminar profiles in response to parvocellular-targeted stimuli peak in more superficial layers. These findings provide new evidence for the differential sensitivity of high-field fMRI to modulations of the neural responses at different cortical depths. PMID:22448223

Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968

Genetic structure and demographic history should inform conservation: Chinese cobras currently treated as homogenous show population divergence.

PubMed

Lin, Long-Hui; Qu, Yan-Fu; Li, Hong; Zhou, Kai-Ya; Ji, Xiang

2012-01-01

An understanding of population structure and genetic diversity is crucial for wildlife conservation and for determining the integrity of wildlife populations. The vulnerable Chinese cobra (Naja atra) has a distribution from the mouth of the Yangtze River down to northern Vietnam and Laos, within which several large mountain ranges and water bodies may influence population structure. We combined 12 microsatellite loci and 1117 bp of the mitochondrial cytochrome b gene to explore genetic structure and demographic history in this species, using 269 individuals from various localities in Mainland China and Vietnam. High levels of genetic variation were identified for both mtDNA and microsatellites. mtDNA data revealed two main (Vietnam + southern China + southwestern China; eastern + southeastern China) and one minor (comprising only two individuals from the westernmost site) clades. Microsatellite data divided the eastern + southeastern China clade further into two genetic clusters, which include individuals from the eastern and southeastern regions, respectively. The Luoxiao and Nanling Mountains may be important barriers affecting the diversification of lineages. In the haplotype network of cytchrome b, many haplotypes were represented within a "star" cluster and this and other tests suggest recent expansion. However, microsatellite analyses did not yield strong evidence for a recent bottleneck for any population or genetic cluster. The three main clusters identified here should be considered as independent management units for conservation purposes. The release of Chinese cobras into the wild should cease unless their origin can be determined, and this will avoid problems arising from unnatural homogenization.

Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

WINGS-SPE. III. Equivalent width measurements, spectral properties, and evolution of local cluster galaxies

NASA Astrophysics Data System (ADS)

Fritz, J.; Poggianti, B. M.; Cava, A.; Moretti, A.; Varela, J.; Bettoni, D.; Couch, W. J.; D'Onofrio D'Onofrio, M.; Dressler, A.; Fasano, G.; Kjærgaard, P.; Marziani, P.; Moles, M.; Omizzolo, A.

2014-06-01

Context. Cluster galaxies are the ideal sites to look at when studying the influence of the environment on the various aspects of the evolution of galaxies, such as the changes in their stellar content and morphological transformations. In the framework of wings, the WIde-field Nearby Galaxy-cluster Survey, we have obtained optical spectra for ~6000 galaxies selected in fields centred on 48 local (0.04 < z < 0.07) X-ray selected clusters to tackle these issues. Aims: By classifying the spectra based on given spectral lines, we investigate the frequency of the various spectral types as a function of both the clusters' properties and the galaxies' characteristics. In this way, using the same classification criteria adopted for studies at higher redshift, we can consistently compare the properties of the local cluster population to those of their more distant counterparts. Methods: We describe a method that we have developed to automatically measure the equivalent width of spectral lines in a robust way, even in spectra with a non optimal signal-to-noise ratio. This way, we can derive a spectral classification reflecting the stellar content, based on the presence and strength of the [Oii] and Hδ lines. Results: After a quality check, we are able to measure 4381 of the ~6000 originally observed spectra in the fields of 48 clusters, of which 2744 are spectroscopically confirmed cluster members. The spectral classification is then analysed as a function of galaxies' luminosity, stellar mass, morphology, local density, and host cluster's global properties and compared to higher redshift samples (MORPHS and EDisCS). The vast majority of galaxies in the local clusters population are passive objects, being also the most luminous and massive. At a magnitude limit of MV < -18, galaxies in a post-starburst phase represent only ~11% of the cluster population, and this fraction is reduced to ~5% at MV < -19.5, which compares to the 18% at the same magnitude limit for high-z clusters. "Normal" star-forming galaxies (e(c)) are proportionally more common in local clusters. Conclusions: The relative occurrence of post-starbursts suggests a very similar quenching efficiency in clusters at redshifts in the 0 to ~1 range. Furthermore, more important than the global environment, the local density seems to be the main driver of galaxy evolution in local clusters at least with respect to their stellar populations content. Based on observations taken at the Anglo Australian Telescope (3.9 m- AAT) and at the William Herschel Telescope (4.2 m-WHT).Full Table A.1 is available in electronic form at both the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/566/A32 and by querying the wings database at http://web.oapd.inaf.it/wings/new/index.htmlAppendices are available in electronic form at http://www.aanda.org

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

PubMed Central

Rahman, Quazi Abidur; Pirbaglou, Meysam; Ritvo, Paul; Heffernan, Jane M; Clarke, Hance; Katz, Joel

2017-01-01

Background Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use. Objective The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement. Methods User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD). Results The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008). Conclusions Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems. PMID:28701291

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation.

PubMed

Rahman, Quazi Abidur; Janmohamed, Tahir; Pirbaglou, Meysam; Ritvo, Paul; Heffernan, Jane M; Clarke, Hance; Katz, Joel

2017-07-12

Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use. The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement. User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD). The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008). Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems. ©Quazi Abidur Rahman, Tahir Janmohamed, Meysam Pirbaglou, Paul Ritvo, Jane M Heffernan, Hance Clarke, Joel Katz. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 12.07.2017.

Distinct pathological profiles of inmates showcasing cluster B personality traits, mental disorders and substance use regarding violent behaviors.

PubMed

Dellazizzo, Laura; Dugré, Jules R; Berwald, Marieke; Stafford, Marie-Christine; Côté, Gilles; Potvin, Stéphane; Dumais, Alexandre

2017-12-06

High rates of violence are found amid offenders with severe mental illnesses (SMI), substance use disorders (SUDs) and Cluster B personality disorders. Elevated rates of comorbidity lead to inconsistencies when it comes to this relationship. Furthermore, overlapping Cluster B personality traits have been associated with violence. Using multiple correspondence analysis and cluster analysis, this study was designed to differentiate profiles of 728 male inmates from penitentiary and psychiatric settings marked by personality traits, SMI and SUDs following different violent patterns. Six significantly differing clusters emerged. Cluster 1, "Sensation seekers", presented recklessness with SUDs and low prevalence's of SMI and auto-aggression. Two clusters committed more sexual offenses. While Cluster 2, "Opportunistic-sexual offenders", had more antisocial lifestyles and SUDs, Cluster 6, "Emotional-sexual offenders", displayed more emotional disturbances with SMI and violence. Clusters 3 and 4, representing "Life-course-persistent offenders", shared early signs of persistent antisocial conduct and severe violence. Cluster 3, "Early-onset violent delinquents", emerged as more severely antisocial with SUDs. Cluster 4, "Early-onset unstable-mentally ill delinquents", were more emotionally driven, with SMI and auto-aggression. Cluster 5, "Late-start offenders", was less severely violent, and emotionally driven with antisocial behavior beginning later. This study suggests the presence of specific psychopathological organizations in violent inmates. Copyright © 2017 Elsevier B.V. All rights reserved.

Cluster Stability Estimation Based on a Minimal Spanning Trees Approach

NASA Astrophysics Data System (ADS)

Volkovich, Zeev (Vladimir); Barzily, Zeev; Weber, Gerhard-Wilhelm; Toledano-Kitai, Dvora

2009-08-01

Among the areas of data and text mining which are employed today in science, economy and technology, clustering theory serves as a preprocessing step in the data analyzing. However, there are many open questions still waiting for a theoretical and practical treatment, e.g., the problem of determining the true number of clusters has not been satisfactorily solved. In the current paper, this problem is addressed by the cluster stability approach. For several possible numbers of clusters we estimate the stability of partitions obtained from clustering of samples. Partitions are considered consistent if their clusters are stable. Clusters validity is measured as the total number of edges, in the clusters' minimal spanning trees, connecting points from different samples. Actually, we use the Friedman and Rafsky two sample test statistic. The homogeneity hypothesis, of well mingled samples within the clusters, leads to asymptotic normal distribution of the considered statistic. Resting upon this fact, the standard score of the mentioned edges quantity is set, and the partition quality is represented by the worst cluster corresponding to the minimal standard score value. It is natural to expect that the true number of clusters can be characterized by the empirical distribution having the shortest left tail. The proposed methodology sequentially creates the described value distribution and estimates its left-asymmetry. Numerical experiments, presented in the paper, demonstrate the ability of the approach to detect the true number of clusters.

Characterization of toxin complex gene clusters and insect toxicity of bacteria representing four subgroups of Pseudomonas fluorescens

USDA-ARS?s Scientific Manuscript database

Ten strains representing four lineages of Pseudomonas (P. chlororaphis, P. corrugata, P. koreensis, and P. fluorescens subgroups) were evaluated for toxicity to the tobacco hornworm Manduca sexta and the fruit fly Drosophila melanogaster. The three strains within the P. chlororaphis subgroup exhibi...

Cluster Sampling Bias in Government-Sponsored Evaluations: A Correlational Study of Employment and Welfare Pilots in England

PubMed Central

2016-01-01

For pilot or experimental employment programme results to apply beyond their test bed, researchers must select ‘clusters’ (i.e. the job centres delivering the new intervention) that are reasonably representative of the whole territory. More specifically, this requirement must account for conditions that could artificially inflate the effect of a programme, such as the fluidity of the local labour market or the performance of the local job centre. Failure to achieve representativeness results in Cluster Sampling Bias (CSB). This paper makes three contributions to the literature. Theoretically, it approaches the notion of CSB as a human behaviour. It offers a comprehensive theory, whereby researchers with limited resources and conflicting priorities tend to oversample ‘effect-enhancing’ clusters when piloting a new intervention. Methodologically, it advocates for a ‘narrow and deep’ scope, as opposed to the ‘wide and shallow’ scope, which has prevailed so far. The PILOT-2 dataset was developed to test this idea. Empirically, it provides evidence on the prevalence of CSB. In conditions similar to the PILOT-2 case study, investigators (1) do not sample clusters with a view to maximise generalisability; (2) do not oversample ‘effect-enhancing’ clusters; (3) consistently oversample some clusters, including those with higher-than-average client caseloads; and (4) report their sampling decisions in an inconsistent and generally poor manner. In conclusion, although CSB is prevalent, it is still unclear whether it is intentional and meant to mislead stakeholders about the expected effect of the intervention or due to higher-level constraints or other considerations. PMID:27504823

OmegaWINGS: The First Complete Census of Post-starburst Galaxies in Clusters in the Local Universe

NASA Astrophysics Data System (ADS)

Paccagnella, A.; Vulcani, B.; Poggianti, B. M.; Fritz, J.; Fasano, G.; Moretti, A.; Jaffé, Yara L.; Biviano, A.; Gullieuszik, M.; Bettoni, D.; Cava, A.; Couch, W.; D'Onofrio, M.

2017-04-01

Galaxies that abruptly interrupt their star formation in < 1.5 {Gyr} present recognizable features in their spectra (no emission and Hδ in absorption) and are called post-starburst (PSB) galaxies. By studying their stellar population properties and their location within the clusters, we obtain valuable insights on the physical processes responsible for star formation quenching. We present the first complete characterization of PSB galaxies in clusters at 0.04< z< 0.07, based on WINGS and OmegaWINGS data, and contrast their properties to those of passive (PAS) and emission-line (EML) galaxies. For V< 20, PSBs represent 7.2 ± 0.2% of cluster galaxies within 1.2 virial radii. Their incidence slightly increases from the outskirts toward the cluster center and from the least toward the most luminous and massive clusters, defined in terms of X-ray luminosity and velocity dispersion. The phase-space analysis and velocity-dispersion profile suggest that PSBs represent a combination of galaxies with different accretion histories. Moreover, PSBs with the strongest Hδ are consistent with being recently accreted. PSBs have stellar masses, magnitudes, colors, and morphologies intermediate between PAS and EML galaxies, typical of a population in transition from being star-forming to passive. Comparing the fraction of PSBs to the fraction of galaxies in transition on longer timescales, we estimate that the short-timescale star formation quenching channel contributes two times more than the long timescale one to the growth of the passive population. Processes like ram-pressure stripping and galaxy-galaxy interactions are more efficient than strangulation in affecting star formation.

The epidemiology of personality disorders in the Sao Paulo Megacity general population.

PubMed

Santana, Geilson Lima; Coelho, Bruno Mendonca; Wang, Yuan-Pang; Chiavegatto Filho, Alexandre Dias Porto; Viana, Maria Carmen; Andrade, Laura Helena

2018-01-01

Most studies on the epidemiology of personality disorders (PDs) have been conducted in high-income countries and may not represent what happens in most part of the world. In the last decades, population growth has been concentrated in low- and middle-income countries, with rapid urbanization, increasing inequalities and escalation of violence. Our aim is to estimate the prevalence of PDs in the Sao Paulo Metropolitan Area, one of the largest megacities of the world. We examined sociodemographic correlates, the influence of urban stressors, the comorbidity with other mental disorders, functional impairment and treatment. A representative household sample of 2,942 adults was interviewed using the WHO-Composite International Diagnostic Interview and the International Personality Disorder Examination-Screening Questionnaire. Diagnoses were multiply imputed, and analyses used multivariable regression. Prevalence estimates were 4.3% (Cluster A), 2.7% (Cluster B), 4.6% (Cluster C) and 6.8% (any PD). Cumulative exposure to violence was associated with all PDs except Cluster A, although urbanicity, migration and neighborhood social deprivation were not significant predictors. Comorbidity was the rule, and all clusters were associated with other mental disorders. Lack of treatment is a reality in Greater Sao Paulo, and this is especially true for PDs. With the exception of Cluster C, non-comorbid PDs remained largely untreated in spite of functional impairment independent of other mental disorders. Personality disorders are prevalent, clinically significant and undertreated, and public health strategies must address the unmet needs of these subjects. Our results may reflect what happens in other developing world megacities, and future studies are expected in other low- and middle-income countries.