Non-small cell lung cancer detection using microRNA expression profiling of bronchoalveolar lavage fluid and sputum.

PubMed

Kim, Julian O; Gazala, Sayf; Razzak, Rene; Guo, Linghong; Ghosh, Sunita; Roa, Wilson H; Bédard, Eric L R

2015-04-01

To assess if miRNA expression profiling of bronchoalveolar lavage (BAL) fluid and sputum could be used to detect early-stage non-small cell lung cancer (NSCLC). Hierarchical cluster analysis was performed on the expression levels of 5 miRNAs (miR-21, miR-143, miR-155, miR-210, and miR-372) which were quantified using RNA reverse transcription and quantitative real-time polymerase chain reaction in sputum and BAL samples from NSCLC cases and cancer-free controls. Cluster analysis of the miRNA expression levels in BAL samples from 21 NSCLC cases and sputum samples from 10 cancer-free controls yielded a diagnostic sensitivity of 85.7% and specificity of 100%. Cluster analysis of sputum samples from the same patients yielded a diagnostic sensitivity of 67.8% and specificity of 90%. miRNA expression profiling of sputum and BAL fluids represent a potential means to detect early-stage NSCLC. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Nuclear fusion at heavy water clusters collision with deuterized targets

NASA Astrophysics Data System (ADS)

Bolotin, Yu. L.; Inopin, E. V.; Lyashko, Yu. V.; Slabospitskij, R. P.

A review of research developed in different laboratories on animal heavy particle yield in D-D fusion reactions induced by heavy water cluster collisions with deuterized targets is presented. Analysis of data shows, on one hand, nontriviality of experimental results and inadequacy of their interpretation and, on the other hand, the multipromising prospects of such a research.

Desorption Induced by KEV Molecular and Cluster Projectiles.

NASA Astrophysics Data System (ADS)

Blain, Matthew Glenn

1990-01-01

A new experimental method has been developed for studying negative secondary ion (SI) emission from solid surfaces bombarded by polyatomic primary ions of 5 to 30 keV. The method is based on the time-of-flight (TOF) analysis of primary ions which are produced by either ^ {252}Cf fission fragment induced desorption or by extraction from a liquid metal ion source, and then accelerated into a field free region. The primary ions included organic monomer, dimer, and fragment ions of coronene and phenylalanine, (CsI)_ nCs ^{+} cluster ions, and Au _sp{n}{+} cluster ions. Secondary electrons, emitted from a target surface upon primary ion impact, are used to identify which primary ion has hit the surface. An event-by-event coincidence counting technique allows several secondary ion TOF spectra, correlated to several different primary ions, to be acquired simultaneously. Negative SI yields from organic (phenylalanine and dinitrostilbene), CsI, and Au surfaces have been measured for a number of different mono- and polyatomic primary ions. The results show, for example, yields ranging from 1 to 10% for phenylalanine (M-H) ^{ -}, 1 to 10% for I^{-} , and 1 to 5% for Au^{-} , with Cs_2I^ {+} and Cs_3I _sp{2}{+} clusters as projectiles. Yields for the same surfaces using Cs ^{+} primary ions are much less than 1%, indicating that SI yields are enhanced with clusters. A yield enhancement occurs when the SI yield per atom of a polyatomic projectile is greater than the SI yield of its monoatomic equivalent, at the same velocity. Thus, a (M-H) ^{-} yield increase of a factor of 50, when phenylalanine is bombarded with Cs_3I_sp{2} {+} instead of Cs^{+ }, represents a yield enhancement factor of 10. For the projectiles and samples studied, it was observed that the heavier the mass of the constituents of a projectile, the larger the enhancement effects, and that the largest yield enhancements (with CsI and Au _ n projectiles) occur for the organic target, phenylalanine. One possible explanation for the larger enhancements with organics, namely a thermal spike process, appears unlikely. Experiments with high and low melting point isomers of dinitrostilbene, bombarded with Cs _2I^{+} and Cs^{+} projectiles, showed larger Cs_2I^ {+} yield enhancements for the high melting point isomer.

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

PubMed Central

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective Segmentation of populations may facilitate development of targeted substance abuse prevention programs. We aimed to partition a national sample of university students according to profiles based on substance use. Participants We used 2008–2009 data from the National College Health Assessment from the American College Health Association. Our sample consisted of 111,245 individuals from 158 institutions. Method We partitioned the sample using cluster analysis according to current substance use behaviors. We examined the association of cluster membership with individual and institutional characteristics. Results Cluster analysis yielded six distinct clusters. Three individual factors—gender, year in school, and fraternity/sorority membership—were the most strongly associated with cluster membership. Conclusions In a large sample of university students, we were able to identify six distinct patterns of substance abuse. It may be valuable to target specific populations of college-aged substance users based on individual factors. However, comprehensive intervention will require a multifaceted approach. PMID:22686360

Study of quantitative and qualitative variations in essential oils of Sicilian Rosmarinus officinalis L.

PubMed

Tuttolomondo, Teresa; Dugo, Giacomo; Ruberto, Giuseppe; Leto, Claudio; Napoli, Edoardo M; Cicero, Nicola; Gervasi, Teresa; Virga, Giuseppe; Leone, Raffaele; Licata, Mario; La Bella, Salvatore

2015-01-01

In this study the chemical characterisation of 10 Sicilian Rosmarinus officinalis L. biotypes essential oils is reported. The main goal of this work was to analyse the relationship between the essential oils yield and the geographical distribution of the species plants. The essential oils were analysed by GC-FID and GC-MS. Hierarchical cluster analysis and principal component analysis statistical methods were used to cluster biotypes according to the essential oils chemical composition. The essential oil yield ranged from 0.8 to 2.3 (v/w). In total 82 compounds have been identified, these represent 96.7-99.9% of the essential oil. The most represented compounds in the essential oils were 1.8-cineole, linalool, α-terpineol, verbenone, α-pinene, limonene, bornyl acetate and terpinolene. The results show that the essential oil yield of the 10 biotypes is affected by the environmental characteristics of the sampling sites while the chemical composition is linked to the genetic characteristics of different biotypes.

A Cluster Analytic Approach to Identifying Predictors and Moderators of Psychosocial Treatment for Bipolar Depression: Results from STEP-BD

PubMed Central

Deckersbach, Thilo; Peters, Amy T.; Sylvia, Louisa G.; Gold, Alexandra K.; da Silva Magalhaes, Pedro Vieira; Henry, David B.; Frank, Ellen; Otto, Michael W.; Berk, Michael; Dougherty, Darin D.; Nierenberg, Andrew A.; Miklowitz, David J.

2016-01-01

Background We sought to address how predictors and moderators of psychotherapy for bipolar depression – identified individually in prior analyses – can inform the development of a metric for prospectively classifying treatment outcome in intensive psychotherapy (IP) versus collaborative care (CC) adjunctive to pharmacotherapy in the Systematic Treatment Enhancement Program (STEP-BD) study. Methods We conducted post-hoc analyses on 135 STEP-BD participants using cluster analysis to identify subsets of participants with similar clinical profiles and investigated this combined metric as a moderator and predictor of response to IP. We used agglomerative hierarchical cluster analyses and k-means clustering to determine the content of the clinical profiles. Logistic regression and Cox proportional hazard models were used to evaluate whether the resulting clusters predicted or moderated likelihood of recovery or time until recovery. Results The cluster analysis yielded a two-cluster solution: 1) “less-recurrent/severe” and 2) “chronic/recurrent.” Rates of recovery in IP were similar for less-recurrent/severe and chronic/recurrent participants. Less-recurrent/severe patients were more likely than chronic/recurrent patients to achieve recovery in CC (p = .040, OR = 4.56). IP yielded a faster recovery for chronic/recurrent participants, whereas CC led to recovery sooner in the less-recurrent/severe cluster (p = .034, OR = 2.62). Limitations Cluster analyses require list-wise deletion of cases with missing data so we were unable to conduct analyses on all STEP-BD participants. Conclusions A well-powered, parametric approach can distinguish patients based on illness history and provide clinicians with symptom profiles of patients that confer differential prognosis in CC vs. IP. PMID:27289316

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins.

PubMed

Kenn, Michael; Ribarics, Reiner; Ilieva, Nevena; Cibena, Michael; Karch, Rudolf; Schreiner, Wolfgang

2016-04-26

The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.

Spectrum of complex DNA damages depends on the incident radiation

NASA Astrophysics Data System (ADS)

Hada, M.; Sutherland, B.

Ionizing radiation induces clustered DNA damages in DNA-two or more abasic sites oxidized bases and strand breaks on opposite DNA strands within a few helical turns Clustered damages are considered to be difficult to repair and therefore potentially lethal and mutagenic damages Although induction of single strand breaks and isolated lesions has been studied extensively little is known of factors affecting induction of clusters other than double strand breaks DSB The aim of the present study was to determine whether the type of incident radiation could affect yield or spectra of specific clusters Genomic T7 DNA a simple 40 kbp linear blunt-ended molecule was irradiated in non-scavenging buffer conditions with Fe 970 MeV n Ti 980 MeV n C 293 MeV n Si 586 MeV n ions or protons 1 GeV n at the NASA Space Radiation Laboratory or with 100 kVp X-rays Irradiated DNA was treated with homogeneous Fpg or Nfo proteins or without enzyme treatment for DSB quantitation then electrophoresed in neutral agarose gels DSB Fpg-OxyPurine clusters and Nfo-Abasic clusters were quantified by number average length analysis The results show that the yields of all these complex damages depend on the incident radiation Although LETs are similar protons induced twice as many DSBs than did X-rays Further the spectrum of damage also depends on the radiation The yield damage Mbp Gy of all damages decreased with increasing linear energy transfer LET of the radiation The relative frequencies of DSBs to Abasic- and OxyBase clusters were higher

Comparing Dark Energy Survey and HST-CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

NASA Astrophysics Data System (ADS)

Palmese, A.; Lahav, O.; Banerji, M.; Gruen, D.; Jouvel, S.; Melchior, P.; Aleksić, J.; Annis, J.; Diehl, H. T.; Hartley, W. G.; Jeltema, T.; Romer, A. K.; Rozo, E.; Rykoff, E. S.; Seitz, S.; Suchyta, E.; Zhang, Y.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Benoit-Lévy, A.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Capozzi, D.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Crocce, M.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Desai, S.; Dietrich, J. P.; Doel, P.; Estrada, J.; Evrard, A. E.; Flaugher, B.; Frieman, J.; Gerdes, D. W.; Goldstein, D. A.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Li, T. S.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Miller, C. J.; Miquel, R.; Nord, B.; Ogando, R.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Tucker, D.; Vikram, V.

2016-12-01

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (five filters) with those from the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25 per cent of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysis of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f⋆ = (6.8 ± 1.7) × 10-3 within a radius of r200c ≃ 2 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both data sets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ˜100 000 clusters that will be observed within this survey and yield important information about galaxy evolution.

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

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

Palmese, A.; Lahav, O.; Banerji, M.

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (five filters) with those from the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25 per cent of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensingmore » studies with DES and CLASH. An analysis of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f(star) = (6.8 +/- 1.7) x 10(-3) within a radius of r(200c) similar or equal to 2 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both data sets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the similar to 100 000 clusters that will be observed within this survey and yield important information about galaxy evolution.« less

Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

PubMed

Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G

2012-10-01

The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Definition of management zones for enhancing cultivated land conservation using combined spatial data.

PubMed

Li, Yan; Shi, Zhou; Wu, Hao-Xiang; Li, Feng; Li, Hong-Yi

2013-10-01

The loss of cultivated land has increasingly become an issue of regional and national concern in China. Definition of management zones is an important measure to protect limited cultivated land resource. In this study, combined spatial data were applied to define management zones in Fuyang city, China. The yield of cultivated land was first calculated and evaluated and the spatial distribution pattern mapped; the limiting factors affecting the yield were then explored; and their maps of the spatial variability were presented using geostatistics analysis. Data were jointly analyzed for management zone definition using a combination of principal component analysis with a fuzzy clustering method, two cluster validity functions were used to determine the optimal number of cluster. Finally one-way variance analysis was performed on 3,620 soil sampling points to assess how well the defined management zones reflected the soil properties and productivity level. It was shown that there existed great potential for increasing grain production, and the amount of cultivated land played a key role in maintaining security in grain production. Organic matter, total nitrogen, available phosphorus, elevation, thickness of the plow layer, and probability of irrigation guarantee were the main limiting factors affecting the yield. The optimal number of management zones was three, and there existed significantly statistical differences between the crop yield and field parameters in each defined management zone. Management zone I presented the highest potential crop yield, fertility level, and best agricultural production condition, whereas management zone III lowest. The study showed that the procedures used may be effective in automatically defining management zones; by the development of different management zones, different strategies of cultivated land management and practice in each zone could be determined, which is of great importance to enhance cultivated land conservation, stabilize agricultural production, promote sustainable use of cultivated land and guarantee food security.

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

Application of a Self-Similar Pressure Profile to Sunyaev-Zeldovich Effect Data from Galaxy Clusters

NASA Technical Reports Server (NTRS)

Mroczkowski, Tony; Bonamente, Max; Carlstrom, John E.; Culverhouse, Thomas L.; Greer, Christopher; Hawkins, David; Hennessy, Ryan; Joy, Marshall; Lamb, James W.; Leitch, Erik M.;

Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases.

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of N monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl tert-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition.

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia.

PubMed

Cerón-Muñoz, M F; Tonhati, H; Costa, C N; Rojas-Sarmiento, D; Echeverri Echeverri, D M

2004-08-01

Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.

2007-01-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H

2007-08-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.

PubMed

Santiago-Rivas, Marimer; Schnur, Julie B; Jandorf, Lina

2016-12-01

This study aimed (i) to determine whether people could be differentiated on the basis of their sun protection belief profiles and individual characteristics and (ii) explore the use of a crowdsourcing web service for the assessment of sun protection beliefs. A sample of 500 adults completed an online survey of sun protection belief items using Amazon Mechanical Turk. A two-phased cluster analysis (i.e., hierarchical and non-hierarchical K-means) was utilized to determine clusters of sun protection barriers and facilitators. Results yielded three distinct clusters of sun protection barriers and three distinct clusters of sun protection facilitators. Significant associations between gender, age, sun sensitivity, and cluster membership were identified. Results also showed an association between barrier and facilitator cluster membership. The results of this study provided a potential alternative approach to developing future sun protection promotion initiatives in the population. Findings add to our knowledge regarding individuals who support, oppose, or are ambivalent toward sun protection and inform intervention research by identifying distinct subtypes that may best benefit from (or have a higher need for) skin cancer prevention efforts.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Genetic Variability among Lucerne Cultivars Based on Biochemical (SDS-PAGE) and Morphological Markers

NASA Astrophysics Data System (ADS)

Farshadfar, M.; Farshadfar, E.

The present research was conducted to determine the genetic variability of 18 Lucerne cultivars, based on morphological and biochemical markers. The traits studied were plant height, tiller number, biomass, dry yield, dry yield/biomass, dry leaf/dry yield, macro and micro elements, crude protein, dry matter, crude fiber and ash percentage and SDS- PAGE in seed and leaf samples. Field experiments included 18 plots of two meter rows. Data based on morphological, chemical and SDS-PAGE markers were analyzed using SPSSWIN soft ware and the multivariate statistical procedures: cluster analysis (UPGMA), principal component. Analysis of analysis of variance and mean comparison for morphological traits reflected significant differences among genotypes. Genotype 13 and 15 had the greatest values for most traits. The Genotypic Coefficient of Variation (GCV), Phenotypic Coefficient of Variation (PCV) and Heritability (Hb) parameters for different characters raged from 12.49 to 26.58% for PCV, hence the GCV ranged from 6.84 to 18.84%. The greatest value of Hb was 0.94 for stem number. Lucerne genotypes could be classified, based on morphological traits, into four clusters and 94% of the variance among the genotypes was explained by two PCAs: Based on chemical traits they were classified into five groups and 73.492% of variance was explained by four principal components: Dry matter, protein, fiber, P, K, Na, Mg and Zn had higher variance. Genotypes based on the SDS-PAGE patterns all genotypes were classified into three clusters. The greatest genetic distance was between cultivar 10 and others, therefore they would be suitable parent in a breeding program.

SSR analysis of genetic diversity and structure of the germplasm of faba bean (Vicia faba L.).

PubMed

El-Esawi, Mohamed A

Assessing the diversity and genetic structure of faba bean (Vicia faba L.) germplasm is essential to improve the quality and yield of this economically important crop. In this study, simple sequence repeats (SSRs) were utilized to evaluate the diversity and structure of 35 faba bean genotypes originating from three different geographical regions (Northern Africa, Eastern Africa, and Near East). All 15 SSR loci generated a total of 100 alleles. The allele number per locus varied from 4 to 11, with a mean of 6.67. The expected heterozygosity (H e ) of SSR loci ranged between 0.51 and 0.81, with a mean of 0.63. The PIC value also varied from 0.44 to 0.78, with an average of 0.58. The expected heterozygosity of 22 faba bean genotypes was higher than the observed one. Interestingly, AMOVA analysis showed that much of variability resided within accessions (79.2%). A highly significant difference among regions was also evidenced, and represented 5.3% of the total variation. Moreover, cluster analysis divided the 35 faba bean genotypes into two main clusters. The first main cluster comprised all faba bean genotypes originating from the Near East region, whereas the second main cluster comprised all the genotypes originating from the Northern and Eastern Africa regions, indicating that the Northern and Eastern African faba bean genotypes were more closely related to each other than to the Near East genotypes. Structure analysis also revealed that the 35 faba bean genotypes might be assigned to two populations, in complete accordance with cluster analysis data. In conclusion, this study showed high levels of diversity in the analysed genotypes of faba bean, and could be utilized in future breeding programmes to develop new cultivars of high yield. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Diversity in phenotypic and nutritional traits in vegetable amaranth (Amaranthus tricolor), a nutritionally underutilised crop.

PubMed

Shukla, Sudhir; Bhargava, Atul; Chatterjee, Avijeet; Pandey, Avinash Chandra; Mishra, Brij K

2010-01-15

Assessment of genetic diversity in a crop-breeding programme helps in the identification of diverse parental combinations to create segregating progenies with maximum genetic variability and facilitates introgression of desirable genes from diverse germplasm into the available genetic base. In the present study, 39 strains of vegetable amaranth (Amaranthus tricolor) were evaluated for eight morphological and seven quality traits for two test seasons to study the extent of genetic divergence among the strains. Multivariate analysis showed that the first four principal components contributed 67.55% of the variability. Cluster analysis grouped the strains into six clusters that displayed a wide range of diversity for most of the traits. Cluster analysis has proved to be an effective method in grouping strains that may facilitate effective management and utilisation in crop-breeding programmes. The diverse strains falling in different clusters were identified, which can be utilised in different hybridisation programmes to develop high-foliage-yielding varieties rich in nutritional components. Copyright (c) 2009 Society of Chemical Industry.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

On the Surface Mapping using Individual Cluster Impacts

PubMed Central

Fernandez-Lima, F.A.; Eller, M.J.; DeBord, J.D.; Verkhoturov, S.V.; Della-Negra, S.; Schweikert, E.A.

2011-01-01

This paper describes the advantages of using single impacts of large cluster projectiles (e.g. C60 and Au400) for surface mapping and characterization. The analysis of co-emitted time-resolved photon spectra, electron distributions and characteristic secondary ions shows that they can be used as surface fingerprints for target composition, morphology and structure. Photon, electron and secondary ion emission increases with the projectile cluster size and energy. The observed, high abundant secondary ion emission makes cluster projectiles good candidates for surface mapping of atomic and fragment ions (e.g., yield >1 per nominal mass) and molecular ions (e.g., few tens of percent in the 500 < m/z < 1500 range). PMID:22393269

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.

Intermediate to low-mass stellar content of Westerlund 1

NASA Astrophysics Data System (ADS)

Brandner, W.; Clark, J. S.; Stolte, A.; Waters, R.; Negueruela, I.; Goodwin, S. P.

2008-01-01

We have analysed near-infrared NTT/SofI observations of the starburst cluster Westerlund 1, which is among the most massive young clusters in the Milky Way. A comparison of colour-magnitude diagrams with theoretical main-sequence and pre-main sequence evolutionary tracks yields improved extinction and distance estimates of AKs = 1.13 ± 0.03 mag and d = 3.55 ± 0.17 kpc (DM = 12.75 ± 0.10 mag). The pre-main sequence population is best fit by a Palla & Stahler isochrone for an age of 3.2 Myr, while the main sequence population is in agreement with a cluster age of 3 to 5 Myr. An analysis of the structural parameters of the cluster yields that the half-mass radius of the cluster population increases towards lower mass, indicative of the presence of mass segregation. The cluster is clearly elongated with an eccentricity of 0.20 for stars with masses between 10 and 32 M_⊙, and 0.15 for stars with masses in the range 3 to 10 M_⊙. We derive the slope of the stellar mass function for stars with masses between 3.4 and 27 M_⊙. In an annulus with radii between 0.75 and 1.5 pc from the cluster centre, we obtain a slope of Γ = -1.3. Closer in, the mass function of Westerlund 1 is shallower with Γ = -0.6. The extrapolation of the mass function for stars with masses from 0.08 to 120 M_⊙ yields an initial total stellar mass of ≈52 000 M_⊙, and a present-day mass of 20 000 to 45 000 M_⊙ (about 10 times the stellar mass of the Orion nebula cluster, and 2 to 4 times the mass of the NGC 3603 young cluster), indicating that Westerlund 1 is the most massive starburst cluster identified to date in the Milky Way. Based on observations collected at the European Southern Observatory, La Silla, Chile, and retrieved from the ESO archive (Prog ID 67.C-0514).

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 magnetic field investigation on Cluster

NASA Technical Reports Server (NTRS)

Balogh, A.; Cowley, S. W. H.; Southwood, D. J.; Musmann, G.; Luhr, H.; Neubauer, F. M.; Glassmeier, K.-H.; Riedler, W.; Heyn, M. F.; Acuna, M. H.

1988-01-01

The magnetic field investigation of the Cluster four-spacecraft mission is designed to provide intercalibrated measurements of the B magnetic field vector. The instrumentation and data processing of the mission are discussed. The instrumentation is identical on the four spacecraft. It consists of two triaxial fluxgate sensors and of a failure tolerant data processing unit. The combined analysis of the four spacecraft data will yield such parameters as the current density vector, wave vectors, and the geometry and structure of discontinuities.

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.

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

PubMed

Weller, Claudia M; Wilbrink, Leopoldine A; Houwing-Duistermaat, Jeanine J; Koelewijn, Stephany C; Vijfhuizen, Lisanne S; Haan, Joost; Ferrari, Michel D; Terwindt, Gisela M; van den Maagdenberg, Arn M J M; de Vries, Boukje

2015-08-01

Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity. © International Headache Society 2014.

Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory

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

Morse, David C.

2006-10-15

Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules,more » and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of binary homopolymer blends and diblock copolymer melts.« less

Researcher Effects on Mortality Salience Research: A Meta-Analytic Moderator Analysis

ERIC Educational Resources Information Center

Yen, Chih-Long; Cheng, Chung-Ping

2013-01-01

A recent meta-analysis of 164 terror management theory (TMT) papers indicated that mortality salience (MS) yields substantial effects (r = 0.35) on worldview and self-esteem-related dependent variables (B. L. Burke, A. Martens, & E. H. Faucher, 2010). This study reanalyzed the data to explore the researcher effects of TMT. By cluster-analyzing…

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy.

PubMed

Alexander, Joe; Edwards, Roger A; Savoldelli, Alberto; Manca, Luigi; Grugni, Roberto; Emir, Birol; Whalen, Ed; Watt, Stephen; Brodsky, Marina; Parsons, Bruce

2017-07-20

More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs) and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN). We utilized three pivotal RCTs of pregabalin (398 North American patients) and the largest observational study of pregabalin (3159 German patients). We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores. Cluster analysis yielded six clusters (287-777 patients each) with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster) demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R 2 : 0.85-0.91; root mean square errors: 0.53-0.57). t tests did not show differences between observed and predicted pain scores in the 1955 patients who had not matched with RCT patients. The combination of cluster analyses, CEM, and ARMAX modeling enabled strong predictive capabilities with respect to pain scores. Integrating RCT and Observational Study data using CEM enabled effective use of Observational Study data to predict patient responses.

Network module detection: Affinity search technique with the multi-node topological overlap measure

PubMed Central

Li, Ai; Horvath, Steve

2009-01-01

Background Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. Findings We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Conclusion Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: PMID:19619323

Network module detection: Affinity search technique with the multi-node topological overlap measure.

PubMed

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

Co-clustering directed graphs to discover asymmetries and directional communities

PubMed Central

Rohe, Karl; Qin, Tai; Yu, Bin

2016-01-01

In directed graphs, relationships are asymmetric and these asymmetries contain essential structural information about the graph. Directed relationships lead to a new type of clustering that is not feasible in undirected graphs. We propose a spectral co-clustering algorithm called di-sim for asymmetry discovery and directional clustering. A Stochastic co-Blockmodel is introduced to show favorable properties of di-sim. To account for the sparse and highly heterogeneous nature of directed networks, di-sim uses the regularized graph Laplacian and projects the rows of the eigenvector matrix onto the sphere. A nodewise asymmetry score and di-sim are used to analyze the clustering asymmetries in the networks of Enron emails, political blogs, and the Caenorhabditis elegans chemical connectome. In each example, a subset of nodes have clustering asymmetries; these nodes send edges to one cluster, but receive edges from another cluster. Such nodes yield insightful information (e.g., communication bottlenecks) about directed networks, but are missed if the analysis ignores edge direction. PMID:27791058

Co-clustering directed graphs to discover asymmetries and directional communities.

PubMed

Rohe, Karl; Qin, Tai; Yu, Bin

2016-10-21

In directed graphs, relationships are asymmetric and these asymmetries contain essential structural information about the graph. Directed relationships lead to a new type of clustering that is not feasible in undirected graphs. We propose a spectral co-clustering algorithm called di-sim for asymmetry discovery and directional clustering. A Stochastic co-Blockmodel is introduced to show favorable properties of di-sim To account for the sparse and highly heterogeneous nature of directed networks, di-sim uses the regularized graph Laplacian and projects the rows of the eigenvector matrix onto the sphere. A nodewise asymmetry score and di-sim are used to analyze the clustering asymmetries in the networks of Enron emails, political blogs, and the Caenorhabditis elegans chemical connectome. In each example, a subset of nodes have clustering asymmetries; these nodes send edges to one cluster, but receive edges from another cluster. Such nodes yield insightful information (e.g., communication bottlenecks) about directed networks, but are missed if the analysis ignores edge direction.

Optimization of the neutron yield in fusion plasmas produced by Coulomb explosions of deuterium clusters irradiated by a petawatt laser.

PubMed

Bang, W; Dyer, G; Quevedo, H J; Bernstein, A C; Gaul, E; Donovan, M; Ditmire, T

2013-02-01

The kinetic energy of hot (multi-keV) ions from the laser-driven Coulomb explosion of deuterium clusters and the resulting fusion yield in plasmas formed from these exploding clusters has been investigated under a variety of conditions using the Texas Petawatt laser. An optimum laser intensity was found for producing neutrons in these cluster fusion plasmas with corresponding average ion energies of 14 keV. The substantial volume (1-10 mm(3)) of the laser-cluster interaction produced by the petawatt peak power laser pulse led to a fusion yield of 1.6×10(7) neutrons in a single shot with a 120 J, 170 fs laser pulse. Possible effects of prepulses are discussed.

Logistic Stick-Breaking Process

PubMed Central

Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.

2013-01-01

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593

Analysis of gamma-ray energies for 56 excited superdeformed rotational bands of nuclei of lanthanons La to Dy and of Hg, Tl, and Pb on the basis of the two-revolving-cluster model, with evaluation of moments of inertia and radii of revolution and assignment of nucleonic compositions to the clusters and the central sphere.

PubMed

Pauling, L

1992-08-01

Analysis of the gamma-ray energies of 28 excited superdeformed bands of lanthanon nuclei by application of the two-revolving-cluster model yields the result that the central sphere for all 28 has the semimagic-magic composition p40n50, with the range p8n12 to p14n18 for the clusters and the radius of revolution increasing from 7.31 to 7.76 fm. Similar analysis of 28 excited bands of Hg, Tl, and Pb nuclei leads to p56n82 (semimagic-magic) for the central sphere of 24 bands, p64n82 (semimagic-magic) for 2, and p64n90 (doubly semimagic) for 2, with cluster range p8n12 to p14n16 and values of the radius of revolution from 8.70 to 8.92 fm for 26 bands and 9.2 fm for 2.

Analysis of gamma-ray energies for 56 excited superdeformed rotational bands of nuclei of lanthanons La to Dy and of Hg, Tl, and Pb on the basis of the two-revolving-cluster model, with evaluation of moments of inertia and radii of revolution and assignment of nucleonic compositions to the clusters and the central sphere.

PubMed Central

Pauling, L

1992-01-01

Analysis of the gamma-ray energies of 28 excited superdeformed bands of lanthanon nuclei by application of the two-revolving-cluster model yields the result that the central sphere for all 28 has the semimagic-magic composition p40n50, with the range p8n12 to p14n18 for the clusters and the radius of revolution increasing from 7.31 to 7.76 fm. Similar analysis of 28 excited bands of Hg, Tl, and Pb nuclei leads to p56n82 (semimagic-magic) for the central sphere of 24 bands, p64n82 (semimagic-magic) for 2, and p64n90 (doubly semimagic) for 2, with cluster range p8n12 to p14n16 and values of the radius of revolution from 8.70 to 8.92 fm for 26 bands and 9.2 fm for 2. PMID:11607313

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Fatality rate of pedestrians and fatal crash involvement rate of drivers in pedestrian crashes: a case study of Iran.

PubMed

Kashani, Ali Tavakoli; Besharati, Mohammad Mehdi

2017-06-01

The aim of this study was to uncover patterns of pedestrian crashes. In the first stage, 34,178 pedestrian-involved crashes occurred in Iran during a four-year period were grouped into homogeneous clusters using a clustering analysis. Next, some in-cluster and inter-cluster crash patterns were analysed. The clustering analysis yielded six pedestrian crash groups. Car/van/pickup crashes on rural roads as well as heavy vehicle crashes were found to be less frequent but more likely to be fatal compared to other crash clusters. In addition, after controlling for crash frequency in each cluster, it was found that the fatality rate of each pedestrian age group as well as the fatal crash involvement rate of each driver age group varies across the six clusters. Results of present study has some policy implications including, promoting pedestrian safety training sessions for heavy vehicle drivers, imposing limitations over elderly heavy vehicle drivers, reinforcing penalties toward under 19 drivers and motorcyclists. In addition, road safety campaigns in rural areas may be promoted to inform people about the higher fatality rate of pedestrians on rural roads. The crash patterns uncovered in this study might also be useful for prioritizing future pedestrian safety research areas.

A proteome view of structural, functional, and taxonomic characteristics of major protein domain clusters.

PubMed

Sun, Chia-Tsen; Chiang, Austin W T; Hwang, Ming-Jing

2017-10-27

Proteome-scale bioinformatics research is increasingly conducted as the number of completely sequenced genomes increases, but analysis of protein domains (PDs) usually relies on similarity in their amino acid sequences and/or three-dimensional structures. Here, we present results from a bi-clustering analysis on presence/absence data for 6,580 unique PDs in 2,134 species with a sequenced genome, thus covering a complete set of proteins, for the three superkingdoms of life, Bacteria, Archaea, and Eukarya. Our analysis revealed eight distinctive PD clusters, which, following an analysis of enrichment of Gene Ontology functions and CATH classification of protein structures, were shown to exhibit structural and functional properties that are taxa-characteristic. For examples, the largest cluster is ubiquitous in all three superkingdoms, constituting a set of 1,472 persistent domains created early in evolution and retained in living organisms and characterized by basic cellular functions and ancient structural architectures, while an Archaea and Eukarya bi-superkingdom cluster suggests its PDs may have existed in the ancestor of the two superkingdoms, and others are single superkingdom- or taxa (e.g. Fungi)-specific. These results contribute to increase our appreciation of PD diversity and our knowledge of how PDs are used in species, yielding implications on species evolution.

Penalized unsupervised learning with outliers

PubMed Central

Witten, Daniela M.

2013-01-01

We consider the problem of performing unsupervised learning in the presence of outliers – that is, observations that do not come from the same distribution as the rest of the data. It is known that in this setting, standard approaches for unsupervised learning can yield unsatisfactory results. For instance, in the presence of severe outliers, K-means clustering will often assign each outlier to its own cluster, or alternatively may yield distorted clusters in order to accommodate the outliers. In this paper, we take a new approach to extending existing unsupervised learning techniques to accommodate outliers. Our approach is an extension of a recent proposal for outlier detection in the regression setting. We allow each observation to take on an “error” term, and we penalize the errors using a group lasso penalty in order to encourage most of the observations’ errors to exactly equal zero. We show that this approach can be used in order to develop extensions of K-means clustering and principal components analysis that result in accurate outlier detection, as well as improved performance in the presence of outliers. These methods are illustrated in a simulation study and on two gene expression data sets, and connections with M-estimation are explored. PMID:23875057

Cluster size dependence of high-order harmonic generation

NASA Astrophysics Data System (ADS)

Tao, Y.; Hagmeijer, R.; Bastiaens, H. M. J.; Goh, S. J.; van der Slot, P. J. M.; Biedron, S. G.; Milton, S. V.; Boller, K.-J.

2017-08-01

We investigate high-order harmonic generation (HHG) from noble gas clusters in a supersonic gas jet. To identify the contribution of harmonic generation from clusters versus that from gas monomers, we measure the high-order harmonic output over a broad range of the total atomic number density in the jet (from 3×1016 to 3 × 1018 {{cm}}-3) at two different reservoir temperatures (303 and 363 K). For the first time in the evaluation of the harmonic yield in such measurements, the variation of the liquid mass fraction, g, versus pressure and temperature is taken into consideration, which we determine, reliably and consistently, to be below 20% within our range of experimental parameters. By comparing the measured harmonic yield from a thin jet with the calculated corresponding yield from monomers alone, we find an increased emission of the harmonics when the average cluster size is less than 3000. Using g, under the assumption that the emission from monomers and clusters add up coherently, we calculate the ratio of the average single-atom response of an atom within a cluster to that of a monomer and find an enhancement of around 100 for very small average cluster size (∼200). We do not find any dependence of the cut-off frequency on the composition of the cluster jet. This implies that HHG in clusters is based on electrons that return to their parent ions and not to neighboring ions in the cluster. To fully employ the enhanced average single-atom response found for small average cluster sizes (∼200), the nozzle producing the cluster jet must provide a large liquid mass fraction at these small cluster sizes for increasing the harmonic yield. Moreover, cluster jets may allow for quasi-phase matching, as the higher mass of clusters allows for a higher density contrast in spatially structuring the nonlinear medium.

Investigating the long-term course of schizophrenia by sequence analysis.

PubMed

An der Heiden, Wolfram; Häfner, Heinz

2015-08-30

In the present study we set out to explore the long-term clinical course of schizophrenia in a holistic manner by adopting sequence analysis. Our aim was to identify course types of illness by means of cluster analysis. The study was based on course and outcome data for 107 patients followed up over 134 months after first admission in the ABC Schizophrenia Study. Focusing on the main syndromes (positive, negative, depressive and unspecific symptoms) and their combinations we looked for similarities in individual illness courses using the 'optimal matching' method. A cluster analysis performed on the resulting similarity matrix yielded two main groups (a 'improving' and a 'chronic' group), which comprised a total of six different types of illness course. The course types differed in both quantitative (frequency of syndromes and syndrome combinations) and qualitative terms (clinical presentation, sequence of syndromes). Cluster membership was only rarely, but clearly associated with sociodemographic characteristics, treatment data and other illness variables. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web

USGS Publications Warehouse

Luczkovich, J.J.; Ward, G.P.; Johnson, J.C.; Christian, R.R.; Baird, D.; Neckles, H.; Rizzo, W.M.

2002-01-01

We established trophic guilds of macroinvertebrate and fish taxa using correspondence analysis and a hierarchical clustering strategy for a seagrass food web in winter in the northeastern Gulf of Mexico. To create the diet matrix, we characterized the trophic linkages of macroinvertebrate and fish taxa present in Halodule wrightii seagrass habitat areas within the St. Marks National Wildlife Refuge (Florida) using binary data, combining dietary links obtained from relevant literature for macroinvertebrates with stomach analysis of common fishes collected during January and February of 1994. Heirarchical average-linkage cluster analysis of the 73 taxa of fishes and macroinvertebrates in the diet matrix yielded 14 clusters with diet similarity ??? 0.60. We then used correspondence analysis with three factors to jointly plot the coordinates of the consumers (identified by cluster membership) and of the 33 food sources. Correspondence analysis served as a visualization tool for assigning each taxon to one of eight trophic guilds: herbivores, detritivores, suspension feeders, omnivores, molluscivores, meiobenthos consumers, macrobenthos consumers, and piscivores. These trophic groups, cross-classified with major taxonomic groups, were further used to develop consumer compartments in a network analysis model of carbon flow in this seagrass ecosystem. The method presented here should greatly improve the development of future network models of food webs by providing an objective procedure for aggregating trophic groups.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

PubMed Central

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological signals. Conclusions The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression matrices. The experimental results presented herein demonstrate that it is a robust data integration technique able to produce good quality clustering solution that is representative for the whole set of expression matrices. PMID:24885407

A complete genetic linkage map and QTL analyses for bast fibre quality traits, yield and yield components in jute (Corchorus olitorius L.).

PubMed

Topdar, N; Kundu, A; Sinha, M K; Sarkar, D; Das, M; Banerjee, S; Kar, C S; Satya, P; Balyan, H S; Mahapatra, B S; Gupta, P K

2013-01-01

We report the first complete microsatellite genetic map of jute (Corchorus olitorius L.; 2n = 2x = 14) using an F6 recombinant inbred population. Of the 403 microsatellite markers screened, 82 were mapped on the seven linkage groups (LGs) that covered a total genetic distance of 799.9 cM, with an average marker interval of 10.7 cM. LG5 had the longest and LG7 the shortest genetic lengths, whereas LG1 had the maximum and LG7 the minimum number of markers. Segregation distortion of microsatellite loci was high (61%), with the majority of them (76%) skewed towards the female parent. Genomewide non-parametric single-marker analysis in combination with multiple quantitative trait loci (QTL)-models (MQM) mapping detected 26 definitive QTLs for bast fibre quality, yield and yield-related traits. These were unevenly distributed on six LGs, as colocalized clusters, at genomic sectors marked by 15 microsatellite loci. LG1 was the QTL-richest map sector, with the densest colocalized clusters of QTLs governing fibre yield, yield-related traits and tensile strength. Expectedly, favorable QTLs were derived from the desirable parents, except for nearly all of those of fibre fineness, which might be due to the creation of new gene combinations. Our results will be a good starting point for further genome analyses in jute.

Effect of mitochondrial complex I inhibition on Fe-S cluster protein activity

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

Mena, Natalia P.; Millennium Institute of Cell Dynamics and Biotechnology, Santiago; Bulteau, Anne Laure

2011-06-03

Highlights: {yields} Mitochondrial complex I inhibition resulted in decreased activity of Fe-S containing enzymes mitochondrial aconitase and cytoplasmic aconitase and xanthine oxidase. {yields} Complex I inhibition resulted in the loss of Fe-S clusters in cytoplasmic aconitase and of glutamine phosphoribosyl pyrophosphate amidotransferase. {yields} Consistent with loss of cytoplasmic aconitase activity, an increase in iron regulatory protein 1 activity was found. {yields} Complex I inhibition resulted in an increase in the labile cytoplasmic iron pool. -- Abstract: Iron-sulfur (Fe-S) clusters are small inorganic cofactors formed by tetrahedral coordination of iron atoms with sulfur groups. Present in numerous proteins, these clusters aremore » involved in key biological processes such as electron transfer, metabolic and regulatory processes, DNA synthesis and repair and protein structure stabilization. Fe-S clusters are synthesized mainly in the mitochondrion, where they are directly incorporated into mitochondrial Fe-S cluster-containing proteins or exported for cytoplasmic and nuclear cluster-protein assembly. In this study, we tested the hypothesis that inhibition of mitochondrial complex I by rotenone decreases Fe-S cluster synthesis and cluster content and activity of Fe-S cluster-containing enzymes. Inhibition of complex I resulted in decreased activity of three Fe-S cluster-containing enzymes: mitochondrial and cytosolic aconitases and xanthine oxidase. In addition, the Fe-S cluster content of glutamine phosphoribosyl pyrophosphate amidotransferase and mitochondrial aconitase was dramatically decreased. The reduction in cytosolic aconitase activity was associated with an increase in iron regulatory protein (IRP) mRNA binding activity and with an increase in the cytoplasmic labile iron pool. Since IRP activity post-transcriptionally regulates the expression of iron import proteins, Fe-S cluster inhibition may result in a false iron deficiency signal. Given that inhibition of complex I and iron accumulation are hallmarks of idiopathic Parkinson's disease, the findings reported here may have relevance for understanding the pathophysiology of this disease.« less

Assessment on induced genetic variability and divergence in the mutagenized lentil populations of microsperma and macrosperma cultivars developed using physical and chemical mutagenesis

PubMed Central

2017-01-01

Induced mutagenesis was employed to create genetic variation in the lentil cultivars for yield improvement. The assessments were made on genetic variability, character association, and genetic divergence among the twelve mutagenized populations and one parent population of each of the two lentil cultivars, developed by single and combination treatments with gamma rays and hydrazine hydrates. Analysis of variance revealed significant inter-population differences for the observed quantitative phenotypic traits. The sample mean of six treatment populations in each of the cultivar exhibited highly superior quantitative phenotypic traits compared to their parent cultivars. The higher values of heritability and genetic advance with a high genotypic coefficient of variation for most of the yield attributing traits confirmed the possibilities of lentil yield improvement through phenotypic selection. The number of pods and seeds per plant appeared to be priority traits in selection for higher yield due to their strong direct association with yield. The cluster analysis divided the total populations into three divergent groups in each lentil cultivar with parent genotypes in an independent group showing the high efficacy of the mutagens. Considering the highest contribution of yield trait to the genetic divergence among the clustered population, it was confirmed that the mutagenic treatments created a wide heritable variation for the trait in the mutant populations. The selection of high yielding mutants from the mutant populations of DPL 62 (100 Gy) and Pant L 406 (100Gy + 0.1% HZ) in the subsequent generation is expected to give elite lentil cultivars. Also, hybridization between members of the divergent group would produce diverse segregants for crop improvement. Apart from this, the induced mutations at loci controlling economically important traits in the selected high yielding mutants have successfully contributed in diversifying the accessible lentil genetic base and will definitely be of immense value to the future lentil breeding programmes in India. PMID:28922405

Antagonists in Mutual Antipathies: A Person-Oriented Approach

ERIC Educational Resources Information Center

Guroglu, Berna; Haselager, Gerbert J. T.; van Lieshout, Cornelis F. M.; Scholte, Ron H. J.

2009-01-01

This study investigated the heterogeneity of mutual antipathy relationships. Separate cluster analyses of peer interactions of early adolescents (mean age 11 years) and adolescents (mean age of 14) yielded 3 "types of individuals" in each age group, namely Prosocial, Antisocial, and Withdrawn. Prevalence analysis of the 6 possible combinations of…

Cluster Analysis of Acute Care Use Yields Insights for Tailored Pediatric Asthma Interventions.

PubMed

Abir, Mahshid; Truchil, Aaron; Wiest, Dawn; Nelson, Daniel B; Goldstick, Jason E; Koegel, Paul; Lozon, Marie M; Choi, Hwajung; Brenner, Jeffrey

2017-09-01

We undertake this study to understand patterns of pediatric asthma-related acute care use to inform interventions aimed at reducing potentially avoidable hospitalizations. Hospital claims data from 3 Camden city facilities for 2010 to 2014 were used to perform cluster analysis classifying patients aged 0 to 17 years according to their asthma-related hospital use. Clusters were based on 2 variables: asthma-related ED visits and hospitalizations. Demographics and a number of sociobehavioral and use characteristics were compared across clusters. Children who met the criteria (3,170) were included in the analysis. An examination of a scree plot showing the decline in within-cluster heterogeneity as the number of clusters increased confirmed that clusters of pediatric asthma patients according to hospital use exist in the data. Five clusters of patients with distinct asthma-related acute care use patterns were observed. Cluster 1 (62% of patients) showed the lowest rates of acute care use. These patients were least likely to have a mental health-related diagnosis, were less likely to have visited multiple facilities, and had no hospitalizations for asthma. Cluster 2 (19% of patients) had a low number of asthma ED visits and onetime hospitalization. Cluster 3 (11% of patients) had a high number of ED visits and low hospitalization rates, and the highest rates of multiple facility use. Cluster 4 (7% of patients) had moderate ED use for both asthma and other illnesses, and high rates of asthma hospitalizations; nearly one quarter received care at all facilities, and 1 in 10 had a mental health diagnosis. Cluster 5 (1% of patients) had extreme rates of acute care use. Differences observed between groups across multiple sociobehavioral factors suggest these clusters may represent children who differ along multiple dimensions, in addition to patterns of service use, with implications for tailored interventions. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Coherent clusters of inertial particles in homogeneous turbulence

NASA Astrophysics Data System (ADS)

Baker, Lucia; Frankel, Ari; Mani, Ali; Coletti, Filippo

2016-11-01

Clustering of heavy particles in turbulent flows manifests itself in a broad spectrum of physical phenomena, including sediment transport, cloud formation, and spray combustion. However, a clear topological definition of particle cluster has been lacking, limiting our ability to describe their features and dynamics. Here we introduce a definition of coherent cluster based on self-similarity, and apply it to the distribution of heavy particles in direct numerical simulations of homogeneous isotropic turbulence. We consider a range of particle Stokes numbers, with and without the effect of gravity. Clusters show self-similarity at length scales larger than twice the Kolmogorov length, with a specific fractal dimension. In the absence of gravity, clusters demonstrate a tendency to sample regions of the flow where strain is dominant over vorticity, and to align themselves with the local vorticity vector; when gravity is present, the clusters tend to align themselves with gravity, and their fall speed is different from the average settling velocity. This approach yields observations which are consistent with findings obtained from previous studies while opening new avenues for analysis of the topology and evolution of particle clusters in a wealth of applications.

Cluster analysis of novel isometric strength measures produces a valid and evidence-based classification structure for wheelchair track racing.

PubMed

Connick, Mark J; Beckman, Emma; Vanlandewijck, Yves; Malone, Laurie A; Blomqvist, Sven; Tweedy, Sean M

2017-11-25

The Para athletics wheelchair-racing classification system employs best practice to ensure that classes comprise athletes whose impairments cause a comparable degree of activity limitation. However, decision-making is largely subjective and scientific evidence which reduces this subjectivity is required. To evaluate whether isometric strength tests were valid for the purposes of classifying wheelchair racers and whether cluster analysis of the strength measures produced a valid classification structure. Thirty-two international level, male wheelchair racers from classes T51-54 completed six isometric strength tests evaluating elbow extensors, shoulder flexors, trunk flexors and forearm pronators and two wheelchair performance tests-Top-Speed (0-15 m) and Top-Speed (absolute). Strength tests significantly correlated with wheelchair performance were included in a cluster analysis and the validity of the resulting clusters was assessed. All six strength tests correlated with performance (r=0.54-0.88). Cluster analysis yielded four clusters with reasonable overall structure (mean silhouette coefficient=0.58) and large intercluster strength differences. Six athletes (19%) were allocated to clusters that did not align with their current class. While the mean wheelchair racing performance of the resulting clusters was unequivocally hierarchical, the mean performance of current classes was not, with no difference between current classes T53 and T54. Cluster analysis of isometric strength tests produced classes comprising athletes who experienced a similar degree of activity limitation. The strength tests reported can provide the basis for a new, more transparent, less subjective wheelchair racing classification system, pending replication of these findings in a larger, representative sample. This paper also provides guidance for development of evidence-based systems in other Para sports. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Farm, household, and farmer characteristics associated with changes in management practices and technology adoption among dairy smallholders.

PubMed

Martínez-García, Carlos Galdino; Ugoretz, Sarah Janes; Arriaga-Jordán, Carlos Manuel; Wattiaux, Michel André

2015-02-01

This study explored whether technology adoption and changes in management practices were associated with farm structure, household, and farmer characteristics and to identify processes that may foster productivity and sustainability of small-scale dairy farming in the central highlands of Mexico. Factor analysis of survey data from 44 smallholders identified three factors-related to farm size, farmer's engagement, and household structure-that explained 70 % of cumulative variance. The subsequent hierarchical cluster analysis yielded three clusters. Cluster 1 included the most senior farmers with fewest years of education but greatest years of experience. Cluster 2 included farmers who reported access to extension, cooperative services, and more management changes. Cluster 2 obtained 25 and 35 % more milk than farmers in clusters 1 and 3, respectively. Cluster 3 included the youngest farmers, with most years of education and greatest availability of family labor. Access to a network and membership in a community of peers appeared as important contributors to success. Smallholders gravitated towards easy to implement technologies that have immediate benefits. Nonusers of high investment technologies found them unaffordable because of cost, insufficient farm size, and lack of knowledge or reliable electricity. Multivariate analysis may be a useful tool in planning extension activities and organizing channels of communication to effectively target farmers with varying needs, constraints, and motivations for change and in identifying farmers who may exemplify models of change for others who manage farms that are structurally similar but performing at a lower level.

Multidimensional assessment of awareness in early-stage dementia: a cluster analytic approach.

PubMed

Clare, Linda; Whitaker, Christopher J; Nelis, Sharon M; Martyr, Anthony; Markova, Ivana S; Roth, Ilona; Woods, Robert T; Morris, Robin G

2011-01-01

Research on awareness in dementia has yielded variable and inconsistent associations between awareness and other factors. This study examined awareness using a multidimensional approach and applied cluster analytic techniques to identify associations between the level of awareness and other variables. Participants were 101 individuals with early-stage dementia (PwD) and their carers. Explicit awareness was assessed at 3 levels: performance monitoring in relation to memory, evaluative judgement in relation to memory, everyday activities and socio-emotional functioning, and metacognitive reflection in relation to the experience and impact of the condition. Implicit awareness was assessed with an emotional Stroop task. Different measures of explicit awareness scores were related only to a limited extent. Cluster analysis yielded 3 groups with differing degrees of explicit awareness. These groups showed no differences in implicit awareness. Lower explicit awareness was associated with greater age, lower MMSE scores, poorer recall and naming scores, lower anxiety and greater carer stress. Multidimensional assessment offers a more robust approach to classifying PwD according to level of awareness and hence to examining correlates and predictors of awareness. Copyright © 2011 S. Karger AG, Basel.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

A Massive Galaxy Cluster At z=1.45 From The XMM Cluster Survey: Discovery, Confirmation And Implications For The L-T Relation And Cosmology

NASA Astrophysics Data System (ADS)

Sabirli, Kivanc; Romer, A. K.; Davidson, M.; Stanford, S. A.; Viana, P. T.; Hilton, M.; Collins, C. A.; Kay, S. T.; Liddle, A. R.; Mann, R. G.; Miller, C. J.; Nichol, R. C.; West, M. J.; Conselice, C. J.; Spinrad, H.; Stern, D.; XCS Collaboration

2006-06-01

We report the discovery of the hottest cluster known at z > 1. It was identified as an extended X-ray source in the XMM Cluster Survey (XCS, Romer et al., 2001) and optical spectroscopy shows that 6 galaxies within a 60 arcsec diameter region lie at z = 1.45 ± 0.01. Hence its redshift is the highest currently known for a spectroscopically-confirmed cluster. Analysis of the X-ray spectra yields kT = 7.9+2.8-1.8 keV (90% confidence) and suggests that it is relatively massive for such a high redshift cluster.We acknowledge financial support from NASA grant NAG-11634 (AKR, RCN, KS, MD, PTPV), The Royal Astronomical Society's Hosie Request (MD, KS), PPARC (ARL, STK, RGM), the NASA XMM program (KS), the Institute of Astronomy at the University of Edinburgh (MD), Liverpool John Moores University (MH), Carnegie Mellon University (KS, AKR), and NSF grant AST-0205960 (MJW).

Self consistency grouping: a stringent clustering method

PubMed Central

2012-01-01

Background Numerous types of clustering like single linkage and K-means have been widely studied and applied to a variety of scientific problems. However, the existing methods are not readily applicable for the problems that demand high stringency. Methods Our method, self consistency grouping, i.e. SCG, yields clusters whose members are closer in rank to each other than to any member outside the cluster. We do not define a distance metric; we use the best known distance metric and presume that it measures the correct distance. SCG does not impose any restriction on the size or the number of the clusters that it finds. The boundaries of clusters are determined by the inconsistencies in the ranks. In addition to the direct implementation that finds the complete structure of the (sub)clusters we implemented two faster versions. The fastest version is guaranteed to find only the clusters that are not subclusters of any other clusters and the other version yields the same output as the direct implementation but does so more efficiently. Results Our tests have demonstrated that SCG yields very few false positives. This was accomplished by introducing errors in the distance measurement. Clustering of protein domain representatives by structural similarity showed that SCG could recover homologous groups with high precision. Conclusions SCG has potential for finding biological relationships under stringent conditions. PMID:23320864

Effect of two different treatments for reducing grape yield in Vitis vinifera cv Syrah on wine composition and quality: berry thinning versus cluster thinning.

PubMed

Gil, M; Esteruelas, M; González, E; Kontoudakis, N; Jiménez, J; Fort, F; Canals, J M; Hermosín-Gutiérrez, I; Zamora, F

2013-05-22

The influence of two treatments for reducing grape yield, cluster thinning and berry thinning, on red wine composition and quality were studied in a Vitis vinifera cv Syrah vineyard in AOC Penedès (Spain). Cluster thinning reduced grape yield per vine by around 40% whereas berry thinning only reduced it by around 20%. Cluster thinning grapes had higher soluble solids content than control grapes, and their resultant wines have greater anthocyanin and polysaccharide concentrations than the control wine. Wine obtained from berry thinning grapes had a higher total phenolic index, greater flavonol, proanthocyanidin, and polysaccharide concentrations, and lower titratable acidity than the control wine. Wines obtained from both treatments were sufficiently different from the control wine to be significantly distinguished by a trained panel in a triangular test. Even though both treatments seem to be effective at improving the quality of wine, berry thinning has the advantage because it has less impact on crop yield reduction.

Precise weak lensing constraints from deep high-resolution Ks images: VLT/HAWK-I analysis of the super-massive galaxy cluster RCS2 J 232727.7-020437 at z = 0.70

NASA Astrophysics Data System (ADS)

Schrabback, Tim; Schirmer, Mischa; van der Burg, Remco F. J.; Hoekstra, Henk; Buddendiek, Axel; Applegate, Douglas; Bradač, Maruša; Eifler, Tim; Erben, Thomas; Gladders, Michael D.; Hernández-Martín, Beatriz; Hildebrandt, Hendrik; Hoag, Austin; Klaes, Dominik; von der Linden, Anja; Marchesini, Danilo; Muzzin, Adam; Sharon, Keren; Stefanon, Mauro

2018-03-01

We demonstrate that deep good-seeing VLT/HAWK-I Ks images complemented with g + z-band photometry can yield a sensitivity for weak lensing studies of massive galaxy clusters at redshifts 0.7 ≲ z ≲ 1.1, which is almost identical to the sensitivity of HST/ACS mosaics of single-orbit depth. Key reasons for this good performance are the excellent image quality frequently achievable for Ks imaging from the ground, a highly effective photometric selection of background galaxies, and a galaxy ellipticity dispersion that is noticeably lower than for optically observed high-redshift galaxy samples. Incorporating results from the 3D-HST and UltraVISTA surveys we also obtained a more accurate calibration of the source redshift distribution than previously achieved for similar optical weak lensing data sets. Here we studied the extremely massive galaxy cluster RCS2 J232727.7-020437 (z = 0.699), combining deep VLT/HAWK-I Ks images (point spread function with a 0.''35 full width at half maximum) with LBT/LBC photometry. The resulting weak lensing mass reconstruction suggests that the cluster consists of a single overdensity, which is detected with a peak significance of 10.1σ. We constrained the cluster mass to M200c/(1015 M⊙) = 2.06-0.26+0.28(stat.) ± 0.12(sys.) assuming a spherical Navarro, Frenk & White model and simulation-based priors on the concentration, making it one of the most massive galaxy clusters known in the z ≳ 0.7 Universe. We also cross-checked the HAWK-I measurements through an analysis of overlapping HST/ACS images, yielding fully consistent estimates of the lensing signal. Based on observations conducted with the ESO Very Large Telescope, the Large Binocular Telescope, and the NASA/ESA Hubble Space Telescope, as detailed in the acknowledgements.

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

PubMed Central

Austin, Elena; Coull, Brent A.; Zanobetti, Antonella; Koutrakis, Petros

2013-01-01

Background Heterogeneity in the response to PM2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies. Objectives Use cluster analysis methods to identify spatial patterns in PM2.5 composition. Verify that the resulting clusters are distinct and informative. Methods 109 monitoring sites with 75% reported speciation data during the period 2003–2008 were selected. These sites were categorized based on their average PM2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources. Results Overall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location. Conclusions The framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research. PMID:23850585

Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web

USGS Publications Warehouse

Luczkovich, J.J.; Ward, G.P.; Johnson, J.C.; Christian, R.R.; Baird, D.; Neckles, H.; Rizzo, W.M.

2002-01-01

We established trophic guilds of macroinvertebrate and fish taxa using correspondence analysis and a hierarchical clustering strategy for a seagrass food web in winter in the northeastern Gulf of Mexico. To create the diet matrix, we characterized the trophic linkages of macroinvertebrate and fish taxa. present in Hatodule wrightii seagrass habitat areas within the St. Marks National Wildlife Refuge (Florida) using binary data, combining dietary links obtained from relevant literature for macroinvertebrates with stomach analysis of common fishes collected during January and February of 1994. Heirarchical average-linkage cluster analysis of the 73 taxa of fishes and macroinvertebrates in the diet matrix yielded 14 clusters with diet similarity greater than or equal to 0.60. We then used correspondence analysis with three factors to jointly plot the coordinates of the consumers (identified by cluster membership) and of the 33 food sources. Correspondence analysis served as a visualization tool for assigning each taxon to one of eight trophic guilds: herbivores, detritivores, suspension feeders, omnivores, molluscivores, meiobenthos consumers, macrobenthos consumers, and piscivores. These trophic groups, cross-classified with major taxonomic groups, were further used to develop consumer compartments in a network analysis model of carbon flow in this seagrass ecosystem. The method presented here should greatly improve the development of future network models of food webs by providing an objective procedure for aggregating trophic groups.

Effects of cluster thinning on vine photosynthesis, berry ripeness and flavonoid composition of Cabernet Sauvignon.

PubMed

Wang, Yu; He, Yan-Nan; Chen, Wei-Kai; He, Fei; Chen, Wu; Cai, Xiao-Dong; Duan, Chang-Qing; Wang, Jun

2018-05-15

Cluster thinning is a common practice for regulating vine yield and grape quality. The effects of cluster thinning on vine photosynthesis, berry ripeness and flavonoid composition of V. vinifera L. Cabernet Sauvignon were evaluated during two seasons. Half of the clusters were removed at pea-size and veraison relative to two controls, respectively. Both cluster thinning treatments significantly increased pruning weight and decreased yield. No effects of cluster thinning on berry growth, ripeness and flavonol composition were observed. Early cluster thinning decreased the photosynthetic rate at pea-size, but the effect diminished at post-veraison. Early cluster thinning significantly promoted the biosynthesis of anthocyanins but decreased the proportion of 3'5'-hydroxylated and acylated anthocyanins at veraison. Late cluster thinning decreased the proportions of 3'5'-hydroxylated and acylated anthocyanins. Additionally, Cluster thinning showed inconsistent effects on flavan-3-ol composition over the two seasons. Copyright © 2017 Elsevier Ltd. All rights reserved.

Kinetics of carbon clustering in detonation of high explosives: Does theory match experiment?

NASA Astrophysics Data System (ADS)

Velizhanin, Kirill; Watkins, Erik; Dattelbaum, Dana; Gustavsen, Richard; Aslam, Tariq; Podlesak, David; Firestone, Millicent; Huber, Rachel; Ringstrand, Bryan; Willey, Trevor; Bagge-Hansen, Michael; Hodgin, Ralph; Lauderbach, Lisa; van Buuren, Tony; Sinclair, Nicholas; Rigg, Paulo; Seifert, Soenke; Gog, Thomas

2017-06-01

Chemical reactions in detonation of carbon-rich high explosives yield carbon clusters as major constituents of the products. Efforts to model carbon clustering as a diffusion-limited irreversible coagulation of carbon clusters go back to the seminal paper by Shaw and Johnson. However, first direct experimental observations of the kinetics of clustering yielded cluster growth one to two orders of magnitude slower than theoretical predictions. Multiple efforts were undertaken to test and revise the basic assumptions of the model in order to achieve better agreement with experiment. We discuss our very recent direct experimental observations of carbon clustering dynamics and demonstrate that these new results are in much better agreement with the modified Shaw-Johnson model. The implications of this much better agreement on our present understanding of detonation carbon clustering processes and possible ways to increase the agreement between theory and experiment even further are discussed.

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

The hierarchical cluster analysis of oral health attitudes and behaviour using the Hiroshima University--Dental Behavioural Inventory (HU-DBI) among final year dental students in 17 countries.

PubMed

Komabayashi, Takashi; Kawamura, Makoto; Kim, Kang-Ju; Wright, Fredrick A C; Declerck, Dominique; Goiâs, Maria do Carmo Matias Freire; Hu, De-Yu; Honkala, Eino; Lévy, Gérard; Kalwitzki, Matthias; Polychronopoulou, Argy; Yip, Kevin Hak-Kong; Eli, Ilana; Kinirons, Martin J; Petti, Stefano; Srisilapanan, Patcharawan; Kwan, Stella Y L; Centore, Linda S

2006-10-01

To explore and describe international oral health attitudes/ behaviours among final year dental students. Validated translated versions of the Hiroshima University-Dental Behavioural Inventory (HU-DBI) questionnaire were administered to 1,096 final-year dental students in 17 countries. Hierarchical cluster analysis was conducted within the data to detect patterns and groupings. The overall response rate was 72%. The cluster analysis identified two main groups among the countries. Group 1 consisted of twelve countries: one Oceanic (Australia), one Middle-Eastern (Israel), seven European (Northern Ireland, England, Finland, Greece, Germany, Italy, and France) and three Asian (Korea, Thailand and Malaysia) countries. Group 2 consisted of five countries: one South American (Brazil), one European (Belgium) and three Asian (China, Indonesia and Japan) countries. The percentages of 'agree' responses in three HU-DBI questionnaire items were significantly higher in Group 2 than in Group 1. They include: "I worry about the colour of my teeth."; "I have noticed some white sticky deposits on my teeth."; and "I am bothered by the colour of my gums." Grouping the countries into international clusters yielded useful information for dentistry and dental education.

Cluster analysis of lowland and upland rice cultivars based on grain quality attributes

USDA-ARS?s Scientific Manuscript database

Rice is cropped in many countries all over the world and plays an important role in human nutrition as well as in agricultural economics, besides its social importance. Embrapa Rice and Beans is responsible for national rice enhancement programs and is conducting breeding projects to increase yield ...

Anticipated Work-Family Conflict: Effects of Role Salience and Self-Efficacy

ERIC Educational Resources Information Center

Cinamon, Rachel Gali

2010-01-01

The current study investigated how male and female university students' self-efficacy and their role salience contributed to the variance in their anticipated work-family conflict (WFC). Participants comprised 387 unmarried students (mean age 24 years). Cluster analysis yielded four profiles of participants who differed in their attributions of…

Gender Differences in Student Attitude for Seating Layout in College Classrooms

ERIC Educational Resources Information Center

Burgess, Brigitte; Kaya, Naz

2007-01-01

This study examined whether gender influenced college students' attitudes regarding classroom seating layout. Seating layouts included: a) rows of tablet-arm chairs, b) U-shaped, c) clusters, and d) rows of tables with individual chairs. The sample consisted of 912 college students. Factor analysis yielded two dimensions: "Feeling at Ease" and…

I. Excluded volume effects in Ising cluster distributions and nuclear multifragmentation. II. Multiple-chance effects in alpha-particle evaporation

NASA Astrophysics Data System (ADS)

Breus, Dimitry Eugene

In Part I, geometric clusters of the Ising model are studied as possible model clusters for nuclear multifragmentation. These clusters may not be considered as non-interacting (ideal gas) due to excluded volume effect which predominantly is the artifact of the cluster's finite size. Interaction significantly complicates the use of clusters in the analysis of thermodynamic systems. Stillinger's theory is used as a basis for the analysis, which within the RFL (Reiss, Frisch, Lebowitz) fluid-of-spheres approximation produces a prediction for cluster concentrations well obeyed by geometric clusters of the Ising model. If thermodynamic condition of phase coexistence is met, these concentrations can be incorporated into a differential equation procedure of moderate complexity to elucidate the liquid-vapor phase diagram of the system with cluster interaction included. The drawback of increased complexity is outweighted by the reward of greater accuracy of the phase diagram, as it is demonstrated by the Ising model. A novel nuclear-cluster analysis procedure is developed by modifying Fisher's model to contain cluster interaction and employing the differential equation procedure to obtain thermodynamic variables. With this procedure applied to geometric clusters, the guidelines are developed to look for excluded volume effect in nuclear multifragmentation. In Part II, an explanation is offered for the recently observed oscillations in the energy spectra of alpha-particles emitted from hot compound nuclei. Contrary to what was previously expected, the oscillations are assumed to be caused by the multiple-chance nature of alpha-evaporation. In a semi-empirical fashion this assumption is successfully confirmed by a technique of two-spectra decomposition which treats experimental alpha-spectra as having contributions from at least two independent emitters. Building upon the success of the multiple-chance explanation of the oscillations, Moretto's single-chance evaporation theory is augmented to include multiple-chance emission and tested on experimental data to yield positive results.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

PubMed

Schultz, K K; Bennett, T B; Nordlund, K V; Döpfer, D; Cook, N B

2016-09-01

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Extensions to the instantaneous normal mode analysis of cluster dynamics: Diffusion constants and the role of rotations in clusters

NASA Astrophysics Data System (ADS)

Adams, John E.; Stratt, Richard M.

1990-08-01

For the instantaneous normal mode analysis method to be generally useful in studying the dynamics of clusters of arbitrary size, it ought to yield values of atomic self-diffusion constants which agree with those derived directly from molecular dynamics calculations. The present study proposes that such agreement indeed can be obtained if a sufficiently sophisticated formalism for computing the diffusion constant is adopted, such as the one suggested by Madan, Keyes, and Seeley [J. Chem. Phys. 92, 7565 (1990)]. In order to implement this particular formalism, however, we have found it necessary to pay particular attention to the removal from the computed spectra of spurious rotational contributions. The utility of the formalism is demonstrated via a study of small argon clusters, for which numerous results generated using other approaches are available. We find the same temperature dependence of the Ar13 self-diffusion constant that Beck and Marchioro [J. Chem. Phys. 93, 1347 (1990)] do from their direct calculation of the velocity autocorrelation function: The diffusion constant rises quickly from zero to a liquid-like value as the cluster goes through (the finite-size equivalent of) the melting transition.

Typology of schizotypy in non-clinical young adults: Psychopathological and personality disorder traits correlates.

PubMed

Raynal, Patrick; Goutaudier, Nelly; Nidetch, Victoria; Chabrol, Henri

2016-12-30

Few typological studies address schizotypy in young adults. Schizotypal traits were assessed on 466 college students using the Schizotypal Personality Questionnaire-Brief (SPQ-B). Other measures evaluated personality traits previously associated with schizotypy (borderline, obsessionnal, and autistic traits), psychopathological symptoms (suicidal ideations, depressive and obsessive-compulsive symptoms) and psychosocial functioning. A factor analysis was first performed on SPQ-B results, leading to four factors: negative schizotypy, positive schizotypy, social anxiety, and reference ideas. Based on these factors, a cluster analysis was conducted, which yielded four clearly distinct groups characterized by "Low" (non schizotypy), "High schizotypy" (mixed positive and negative), "Positive schizotypy", and "Social impairment". Regarding personality disorder traits and psychopathological symptoms, the "High schizotypy" cluster scored higher than the "Positive" and the "Social impairment" groups, which scored higher than the "Low" cluster. The "Positive" group had higher levels of interpersonal relationships than in the "High" and the "Social impairment" clusters, suggesting that positive schizotypy was associated to benefits such as perceived social relationships. Nevertheless the "Positive" cluster was also linked to high levels of personality disorder traits and psychopathological symptoms, and to low academic achievement, at levels similar those observed in the "Social impairment" cluster, confirming an unhealthy side to positive schizotypy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The effect of billboard design specifications on driving: A pilot study.

PubMed

Marciano, Hadas; Setter, Pe'erly

2017-07-01

Decades of research on the effects of advertising billboards on road accident rates, driver performance, and driver visual scanning behavior, has produced no conclusive findings. We suggest that road safety researchers should shift their focus and attempt to identify the billboard characteristics that are most distracting to drivers. This line of research may produce concrete guidelines for permissible billboards that would be likely to reduce the influence of the billboards on road safety. The current study is a first step towards this end. A pool of 161 photos of real advertising billboards was used as stimuli within a triple task paradigm designed to simulate certain components of driving. Each trial consisted of one ongoing tracking task accompanied by two additional concurrent tasks: (1) billboard observation task; and (2) circle color change identification task. Five clusters of billboards, identified by conducting a cluster analysis of their graphic content, were used as a within variable in one-way ANOVAs conducted on performance level data collected from the multiple tasks. Cluster 5, labeled Loaded Billboards, yielded significantly deteriorated performance on the tracking task. Cluster 4, labeled Graphical Billboards, yielded deteriorated performance primarily on the color change identification task. Cluster 3, labeled Minimal Billboards, had no effect on any of these tasks. We strongly recommend that these clusters be systematically explored in experiments involving additional real driving settings, such as driving simulators and field studies. This will enable validation of the current results and help incorporate them into real driving situations. Copyright © 2017. Published by Elsevier Ltd.

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.

Static time-of-flight secondary ion mass spectrometry analysis of microelectronics related substrates using a polyatomic ion source

NASA Astrophysics Data System (ADS)

Ravanel, X.; Trouiller, C.; Juhel, M.; Wyon, C.; Kwakman, L. F. Tz.; Léonard, D.

2008-12-01

Recent time-of-flight secondary ion mass spectrometry studies using primary ion cluster sources such as Au n+, SF 5+, Bi n+ or C 60+ have shown the great advantages in terms of secondary ion yield enhancement and ion formation efficiency of polyatomic ion sources as compared to monoatomic ion sources like the commonly used Ga +. In this work, the effective gains provided by such a source in the static ToF-SIMS analysis of microelectronics devices were investigated. Firstly, the influence of the number of atoms in the primary cluster ion on secondary ion formation was studied for physically adsorbed di-isononyl phthalate (DNP) (plasticizer) and perfluoropolyether (PFPE). A drastic increase in secondary ion formation efficiency and a much lower detection limit were observed when using a polyatomic primary ion. Moreover, the yield of the higher mass species was much enhanced indicating a lower degree of fragmentation that can be explained by the fact that the primary ion energy is spread out more widely, or that there is a lower energy per incoming ion. Secondly, the influence of the number of Bi atoms in the Bi n primary ion on the information depth was studied using reference thermally grown silicon oxide samples. The information depth provided by a Bi n cluster was shown to be lowered when the number of atoms in the aggregate was increased.

Chemometric investigation of light-shade effects on essential oil yield and morphology of Moroccan Myrtus communis L.

PubMed

Fadil, Mouhcine; Farah, Abdellah; Ihssane, Bouchaib; Haloui, Taoufik; Lebrazi, Sara; Zghari, Badreddine; Rachiq, Saâd

2016-01-01

To investigate the effect of environmental factors such as light and shade on essential oil yield and morphological traits of Moroccan Myrtus communis, a chemometric study was conducted on 20 individuals growing under two contrasting light environments. The study of individual's parameters by principal component analysis has shown that essential oil yield, altitude, and leaves thickness were positively correlated between them and negatively correlated with plants height, leaves length and leaves width. Principal component analysis and hierarchical cluster analysis have also shown that the individuals of each sampling site were grouped separately. The one-way ANOVA test has confirmed the effect of light and shade on essential oil yield and morphological parameters by showing a statistically significant difference between them from the shaded side to the sunny one. Finally, the multiple linear model containing main, interaction and quadratic terms was chosen for the modeling of essential oil yield in terms of morphological parameters. Sun plants have a small height, small leaves length and width, but they are thicker and richer in essential oil than shade plants which have shown almost the opposite. The highlighted multiple linear model can be used to predict essential oil yield in the studied area.

[Optimization of cluster analysis based on drug resistance profiles of MRSA isolates].

PubMed

Tani, Hiroya; Kishi, Takahiko; Gotoh, Minehiro; Yamagishi, Yuka; Mikamo, Hiroshige

2015-12-01

We examined 402 methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from clinical specimens in our hospital between November 19, 2010 and December 27, 2011 to evaluate the similarity between cluster analysis of drug susceptibility tests and pulsed-field gel electrophoresis (PFGE). The results showed that the 402 strains tested were classified into 27 PFGE patterns (151 subtypes of patterns). Cluster analyses of drug susceptibility tests with the cut-off distance yielding a similar classification capability showed favorable results--when the MIC method was used, and minimum inhibitory concentration (MIC) values were used directly in the method, the level of agreement with PFGE was 74.2% when 15 drugs were tested. The Unweighted Pair Group Method with Arithmetic mean (UPGMA) method was effective when the cut-off distance was 16. Using the SIR method in which susceptible (S), intermediate (I), and resistant (R) were coded as 0, 2, and 3, respectively, according to the Clinical and Laboratory Standards Institute (CLSI) criteria, the level of agreement with PFGE was 75.9% when the number of drugs tested was 17, the method used for clustering was the UPGMA, and the cut-off distance was 3.6. In addition, to assess the reproducibility of the results, 10 strains were randomly sampled from the overall test and subjected to cluster analysis. This was repeated 100 times under the same conditions. The results indicated good reproducibility of the results, with the level of agreement with PFGE showing a mean of 82.0%, standard deviation of 12.1%, and mode of 90.0% for the MIC method and a mean of 80.0%, standard deviation of 13.4%, and mode of 90.0% for the SIR method. In summary, cluster analysis for drug susceptibility tests is useful for the epidemiological analysis of MRSA.

Self-organizing neural networks--an alternative way of cluster analysis in clinical chemistry.

PubMed

Reibnegger, G; Wachter, H

1996-04-15

Supervised learning schemes have been employed by several workers for training neural networks designed to solve clinical problems. We demonstrate that unsupervised techniques can also produce interesting and meaningful results. Using a data set on the chemical composition of milk from 22 different mammals, we demonstrate that self-organizing feature maps (Kohonen networks) as well as a modified version of error backpropagation technique yield results mimicking conventional cluster analysis. Both techniques are able to project a potentially multi-dimensional input vector onto a two-dimensional space whereby neighborhood relationships remain conserved. Thus, these techniques can be used for reducing dimensionality of complicated data sets and for enhancing comprehensibility of features hidden in the data matrix.

Role of isolated and clustered DNA damage and the post-irradiating repair process in the effects of heavy ion beam irradiation.

PubMed

Tokuyama, Yuka; Furusawa, Yoshiya; Ide, Hiroshi; Yasui, Akira; Terato, Hiroaki

2015-05-01

Clustered DNA damage is a specific type of DNA damage induced by ionizing radiation. Any type of ionizing radiation traverses the target DNA molecule as a beam, inducing damage along its track. Our previous study showed that clustered DNA damage yields decreased with increased linear energy transfer (LET), leading us to investigate the importance of clustered DNA damage in the biological effects of heavy ion beam radiation. In this study, we analyzed the yield of clustered base damage (comprising multiple base lesions) in cultured cells irradiated with various heavy ion beams, and investigated isolated base damage and the repair process in post-irradiation cultured cells. Chinese hamster ovary (CHO) cells were irradiated by carbon, silicon, argon and iron ion beams with LETs of 13, 55, 90 and 200 keV µm(-1), respectively. Agarose gel electrophoresis of the cells with enzymatic treatments indicated that clustered base damage yields decreased as the LET increased. The aldehyde reactive probe procedure showed that isolated base damage yields in the irradiated cells followed the same pattern. To analyze the cellular base damage process, clustered DNA damage repair was investigated using DNA repair mutant cells. DNA double-strand breaks accumulated in CHO mutant cells lacking Xrcc1 after irradiation, and the cell viability decreased. On the other hand, mouse embryonic fibroblast (Mef) cells lacking both Nth1 and Ogg1 became more resistant than the wild type Mef. Thus, clustered base damage seems to be involved in the expression of heavy ion beam biological effects via the repair process. © The Author 2015. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

A model for sputtering from solid surfaces bombarded by energetic clusters

NASA Astrophysics Data System (ADS)

Benguerba, Messaoud

2018-04-01

A model is developed to explain and predict the sputtering from solid surfaces bombarded by energetic clusters, on the basis of shock wave generated at the impact of cluster. Under the shock compression the temperature increases causing the vaporization of material that requires an internal energy behind the shock, at least, of about twice the cohesive energy of target. The sputtering is treated as a gas of vaporized particles from a hemispherical volume behind the shock front. The sputter yield per cluster atoms is given as a universal function depending on the ratio of target to cluster atomic density and the ratio of cluster velocity to the velocity calculated on the basis of an internal energy equals about twice cohesive energy. The predictions of the model for self sputter yield of copper, gold, tungsten and of silver bombarded by C60 clusters agree well, with the corresponding data simulated by molecular dynamics.

Subspace K-means clustering.

PubMed

Timmerman, Marieke E; Ceulemans, Eva; De Roover, Kim; Van Leeuwen, Karla

2013-12-01

To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning approaches. To evaluate subspace K-means, we performed a comparative simulation study, in which we manipulated the overlap of subspaces, the between-cluster variance, and the error variance. The study shows that the subspace K-means algorithm is sensitive to local minima but that the problem can be reasonably dealt with by using partitions of various cluster procedures as a starting point for the algorithm. Subspace K-means performs very well in recovering the true clustering across all conditions considered and appears to be superior to its competitor methods: K-means, reduced K-means, factorial K-means, mixtures of factor analyzers (MFA), and MCLUST. The best competitor method, MFA, showed a performance similar to that of subspace K-means in easy conditions but deteriorated in more difficult ones. Using data from a study on parental behavior, we show that subspace K-means analysis provides a rich insight into the cluster characteristics, in terms of both the relative positions of the clusters (via the centroids) and the shape of the clusters (via the within-cluster residuals).

Experimental study of fusion neutron and proton yields produced by petawatt-laser-irradiated D₂-³He or CD₄-³He clustering gases.

PubMed

Bang, W; Barbui, M; Bonasera, A; Quevedo, H J; Dyer, G; Bernstein, A C; Hagel, K; Schmidt, K; Gaul, E; Donovan, M E; Consoli, F; De Angelis, R; Andreoli, P; Barbarino, M; Kimura, S; Mazzocco, M; Natowitz, J B; Ditmire, T

2013-09-01

We report on experiments in which the Texas Petawatt laser irradiated a mixture of deuterium or deuterated methane clusters and helium-3 gas, generating three types of nuclear fusion reactions: D(d,^{3}He)n, D(d,t)p, and ^{3}He(d,p)^{4}He. We measured the yields of fusion neutrons and protons from these reactions and found them to agree with yields based on a simple cylindrical plasma model using known cross sections and measured plasma parameters. Within our measurement errors, the fusion products were isotropically distributed. Plasma temperatures, important for the cross sections, were determined by two independent methods: (1) deuterium ion time of flight and (2) utilizing the ratio of neutron yield to proton yield from D(d,^{3}He)n and ^{3}He(d,p)^{4}He reactions, respectively. This experiment produced the highest ion temperature ever achieved with laser-irradiated deuterium clusters.

The Formation and Early Evolution of Embedded Massive Star Clusters

NASA Astrophysics Data System (ADS)

Barnes, Peter

We propose to combine Spitzer, WISE, Herschel, and other archival spacecraft data with an existing ground- and space-based mm-wave to near-IR survey of molecular clouds over a large portion of the Milky Way, in order to systematically study the formation and early evolution of massive stars and star clusters, and provide new observational calibrations for a theoretical paradigm of this key astrophysical problem. Central Objectives: The Galactic Census of High- and Medium-mass Protostars (CHaMP) is a large, unbiased, uniform, and panchromatic survey of massive star and cluster formation and early evolution, covering 20°x6° of the Galactic Plane. Its uniqueness lies in the comprehensive molecular spectroscopy of 303 massive dense clumps, which have also been included in several archival spacecraft surveys. Our objective is a systematic demographic analysis of massive star and cluster formation, one which has not been possible without knowledge of our CHaMP cloud sample, including all clouds with embedded clusters as well as those that have not yet formed massive stars. For proto-clusters deeply embedded within dense molecular clouds, analysis of these space-based data will: 1. Yield a complete census of Young Stellar Objects in each cluster. 2. Allow systematic measurements of embedded cluster properties: spectral energy distributions, luminosity functions, protostellar and disk fractions, and how these vary with cluster mass, age, and density. Combined with other, similarly complete and unbiased infrared and mm data, CHaMP's goals include: 3. A detailed comparison of the embedded stellar populations with their natal dense gas to derive extinction maps, star formation efficiencies and feedback effects, and the kinematics, physics, and chemistry of the gas in and around the clusters. 4. Tying the demographics, age spreads, and timescales of the clusters, based on pre-Main Sequence evolution, to that of the dense gas clumps and Giant Molecular Clouds. 5. A measurement of the local star formation rate per gas mass surface density in the Milky Way, as well as examining arm versus interarm dependencies. Methods and Techniques: We will primarily use archival cryogenic-Spitzer, WISE, and Herschel data, and support this with existing data from ground- and space-based facilities, to conduct a comprehensive assay of critical metrics (as above) and provide observational calibration of theoretical models over the entire massive star formation process. The mm-wave molecular maps of 303 dense gas clumps in multiple species, comprising all the gas above a column density limit of 100 Msun/pc^2, are already inhand. We have also surveyed the embedded stellar content of these clumps, down to subsolar masses, in the near-infrared J, H, and K bands and with deep Warm Spitzer data. Relevance to NASA programs: Analysis to date of the space- and ground-based data has yielded several new insights into evolutionary timescales and the chemical & energy evolution of clumps during the cluster formation process. Investigations as described in this proposal will yield new demographic insights on how the properties and evolution of molecular clouds relate to the properties of massive stars and clusters that form within them, and significantly enhance the science return from these spacecraft missions. The large number of resulting data products are already being made publicly available to the astronomical community, providing crucial information for future NASA science targets. This research will be performed within the framework of a broad international collaboration spanning four continents. This ambitious but practical program will therefore maximise the science payoff from these archival data sets, provide enhanced legacy data for more advanced studies with the next generation of ground- and space-based instruments such as JWST, and open up several new windows into the discovery space of Galactic star formation & interstellar medium studies.

An ensemble framework for clustering protein-protein interaction networks.

PubMed

Asur, Sitaram; Ucar, Duygu; Parthasarathy, Srinivasan

2007-07-01

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. Supplementary data are available at Bioinformatics online.

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

NASA Astrophysics Data System (ADS)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

OSO 8 X-ray spectra of clusters of galaxies. II - Discussion

NASA Technical Reports Server (NTRS)

Smith, B. W.; Mushotzky, R. F.; Serlemitsos, P. J.

1979-01-01

An observational description of X-ray clusters of galaxies is given based on OSO 8 X-ray results for spatially integrated spectra of 20 such clusters and various correlations obtained from these results. It is found from a correlation between temperature and velocity dispersion that the X-ray core radius should be less than the galaxy core radius or, alternatively, that the polytropic index is about 1.1 for most of the 20 clusters. Analysis of a correlation between temperature and emission integral yields evidence that more massive clusters accumulate a larger fraction of their mass as intracluster gas. Galaxy densities and optical morphology, as they correlate with X-ray properties, are reexamined for indications as to how mass injection by galaxies affects the density structure of the gas. The physical arguments used to derive iron abundances from observed equivalent widths of iron line features in X-ray spectra are critically evaluated, and the associated uncertainties in abundances derived in this manner are estimated to be quite large.

Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2015-01-01

A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance.

PubMed

Klein, Anthony; Houtin, Hervé; Rond, Céline; Marget, Pascal; Jacquin, Françoise; Boucherot, Karen; Huart, Myriam; Rivière, Nathalie; Boutet, Gilles; Lejeune-Hénaut, Isabelle; Burstin, Judith

2014-06-01

Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea. The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9-71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.

Social Media Use and Depression and Anxiety Symptoms: A Cluster Analysis.

PubMed

Shensa, Ariel; Sidani, Jaime E; Dew, Mary Amanda; Escobar-Viera, César G; Primack, Brian A

2018-03-01

Individuals use social media with varying quantity, emotional, and behavioral at- tachment that may have differential associations with mental health outcomes. In this study, we sought to identify distinct patterns of social media use (SMU) and to assess associations between those patterns and depression and anxiety symptoms. In October 2014, a nationally-representative sample of 1730 US adults ages 19 to 32 completed an online survey. Cluster analysis was used to identify patterns of SMU. Depression and anxiety were measured using respective 4-item Patient-Reported Outcome Measurement Information System (PROMIS) scales. Multivariable logistic regression models were used to assess associations between clus- ter membership and depression and anxiety. Cluster analysis yielded a 5-cluster solu- tion. Participants were characterized as "Wired," "Connected," "Diffuse Dabblers," "Concentrated Dabblers," and "Unplugged." Membership in 2 clusters - "Wired" and "Connected" - increased the odds of elevated depression and anxiety symptoms (AOR = 2.7, 95% CI = 1.5-4.7; AOR = 3.7, 95% CI = 2.1-6.5, respectively, and AOR = 2.0, 95% CI = 1.3-3.2; AOR = 2.0, 95% CI = 1.3-3.1, respectively). SMU pattern characterization of a large population suggests 2 pat- terns are associated with risk for depression and anxiety. Developing educational interventions that address use patterns rather than single aspects of SMU (eg, quantity) would likely be useful.

Impact of SZ cluster residuals in CMB maps and CMB-LSS cross-correlations

NASA Astrophysics Data System (ADS)

Chen, T.; Remazeilles, M.; Dickinson, C.

2018-06-01

Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the computation of cross-correlation power spectra between CMB maps and the SDSS-IV large-scale structure data. Our cross-power spectrum analysis yields a 30σ detection at the cluster scale (ℓ = 1500-2500) and a 39σ detection on larger scales (ℓ = 500-1500) due to clustering of SZ clusters, giving an overall 54σ detection of SZ cluster residuals in the Planck CMB maps. The Planck 2015 NILC CMB map is shown to have 44 ± 4% of thermal SZ foreground emission left in it. Using the 'Constrained ILC' component separation technique, we construct an alternative Planck CMB map, the 2D-ILC map, which is shown to have negligible SZ contamination, at the cost of being slightly more contaminated by Galactic foregrounds and noise. We also discuss the impact of the SZ residuals in CMB maps on the measurement of the ISW effect, which is shown to be negligible based on our analysis.

Nuclear fusion driven by Coulomb explosion of homonuclear and heteronuclear deuterium- and tritium-containing clusters

NASA Astrophysics Data System (ADS)

Last, Isidore; Jortner, Joshua

2001-12-01

The ionization and Coulomb explosion of homonuclear Dn and Tn (n=959-8007) and heteronuclear (D2O)n and (T2O)n (n=459-2171) clusters in very intense (I=5×1014-5×1018 W cm-2) laser fields is studied using classical dynamics simulations. The efficiency of the d+d and d+t nuclear fusion driven by the Coulomb explosion (NFDCE) is explored. The d+d NFDCE of (D2O)n heteronuclear clusters is enhanced by energetic and kinematic effects for D+, while for (T2O)n heteronuclear clusters the kinetic energy of T+ is dominated by energetic effects. The cluster size dependence of the fusion reaction yield has been established. The heteronuclear clusters provide considerably higher d+d and d+t fusion reaction yields than the homonuclear clusters of the same size. The clusters consisting of both D and T atoms can provide highly efficient d+t fusion reactions.

Heterogeneous delays making parents synchronized: A coupled maps on Cayley tree model

NASA Astrophysics Data System (ADS)

Singh, Aradhana; Jalan, Sarika

2014-06-01

We study the phase synchronized clusters in the diffusively coupled maps on the Cayley tree networks for heterogeneous delay values. Cayley tree networks comprise of two parts: the inner nodes and the boundary nodes. We find that heterogeneous delays lead to various cluster states, such as; (a) cluster state consisting of inner nodes and boundary nodes, and (b) cluster state consisting of only boundary nodes. The former state may comprise of nodes from all the generations forming self-organized cluster or nodes from few generations yielding driven clusters depending upon on the parity of heterogeneous delay values. Furthermore, heterogeneity in delays leads to the lag synchronization between the siblings lying on the boundary by destroying the exact synchronization among them. The time lag being equal to the difference in the delay values. The Lyapunov function analysis sheds light on the destruction of the exact synchrony among the last generation nodes. To the end we discuss the relevance of our results with respect to their applications in the family business as well as in understanding the occurrence of genetic diseases.

Elevated Genetic Diversity in an F2:6 Population of Quinoa (Chenopodium quinoa) Developed through an Inter-ecotype Cross

PubMed Central

Benlhabib, Ouafae; Boujartani, Noura; Maughan, Peter J.; Jacobsen, Sven E.; Jellen, Eric N.

2016-01-01

Quinoa (Chenopodium quinoa) is a seed crop of the Andean highlands and Araucanian coastal regions of South America that has recently expanded in use and production beyond its native range. This is largely due to its superb nutritional value, consisting of protein that is rich in essential amino acids along with vitamins and minerals. Quinoa also presents a remarkable degree of tolerance to saline conditions, drought, and frost. The present study involved 72 F2:6 recombinant-inbred lines and parents developed through hybridization between highland (0654) and coastal (NL-6) germplasm groups. The purpose was to characterize the quinoa germplasm developed, to assess the discriminating potential of 21 agro-morpho-phenological traits, and to evaluate the extent of genetic variability recovered through selfing. A vast amount of genetic variation was detected among the 72 lines evaluated for quantitative and qualitative traits. Impressive transgressive segregation was measured for seed yield (22.42 g/plant), while plant height and maturity had higher heritabilities (73 and 89%, respectively). Other notable characters segregating in the population included panicle and stem color, panicle form, and resistance to downy mildew. In the Principal Component analysis, the first axis explained 74% of the total variation and was correlated to plant height, panicle size, stem diameter, biomass, mildew reaction, maturation, and seed yield; those traits are relevant discriminatory characters. Yield correlated positively with panicle length and biomass. Unweighted Pair Group Method with Arithmetic Mean-based cluster analysis identified three groups: one consisting of late, mildew-resistant, high-yielding lines; one having semi-late lines with intermediate yield and mildew susceptibility; and a third cluster consisting of early to semi-late accessions with low yield and mildew susceptibility. This study highlighted the extended diversity regenerated among the 72 accessions and helped to identify potentially adapted quinoa genotypes for production in the Moroccan coastal environment. PMID:27582753

SU-C-BRE-07: Sensitivity Analysis of the Threshold Energy for the Creation of Strand Breaks and of Single and Double Strand Break Clustering Conditions

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

Pater, P

Purpose: To analyse the sensitivity of the creation of strand breaks (SB) to the threshold energy (Eth) and thresholding method and to quantify the impact of clustering conditions on single strand break (SSB) and double strand break (DSB) yields. Methods: Monte Carlo simulations using Geant4-DNA were conducted for electron tracks of 280 eV to 220 keV in a geometrical DNA model composed of nucleosomes of 396 phospho-diester groups (PDGs) each. A strand break was created inside a PDG when the sum of all energy deposits (method 1) or energy transfers (method 2) was higher than Eth or when at leastmore » one interaction deposited (method 3) or transferred (method 4) an energy higher than Eth. SBs were then clustered into SSBs and DSBs using clustering scoring criteria from the literature and compared to our own. Results: The total number of SBs decreases as Eth is increased. In addition, thresholding on the energy transfers (methods 2 and 4) produces a higher SB count than when thresholding on energy deposits (methods 1 and 3). Method 2 produces a step-like function and should be avoided when attempting to optimize Eth. When SBs are grouped into damage patterns, clustering conditions can underestimated SSBs by up to 18 % and DSBs can be overestimated by up to 12 % compared to our own implementation. Conclusion: We show that two often underreported simulation parameters have a non-negligible effect on overall DNA damage yields. First more SBs are counted when using energy transfers to the PDG rather than energy deposits. Also, SBs grouped according to different clustering conditions can influence reported SSB and DSB by as much as 20%. Careful handling of these parameters is required when trying to compare DNA damage yields from different authors. Research funding from the governments of Canada and Quebec. PP acknowledges partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290)« less

A DNA-Encapsulated and Fluorescent Ag 10 6+ Cluster with a Distinct Metal-Like Core

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

Petty, Jeffrey T.; Ganguly, Mainak; Rankine, Ian J.

Silver cluster–DNA complexes are optical chromophores, and pairs of these conjugates can be toggled from fluorescently dim to bright states using DNA hybridization. This paper highlights spectral and structural differences for a specific cluster pair. We have previously characterized a cluster with low emission and violet absorption that forms a compact structure with single-stranded oligonucleotides. We now consider its counterpart with blue absorption and strong green emission. This cluster develops with a single-stranded/duplex DNA construct and is favored by low silver concentrations with ≲8 Ag+:DNA, an oxygen atmosphere, and neutral pH. The resulting cluster displays key signatures of a molecularmore » metal with well-defined absorption/emission bands at 490/550 nm, and with a fluorescence quantum yield of 15% and lifetime of 2.4 ns. The molecular cluster conjugates with the larger DNA host because it chromatographically elutes with the DNA and it exhibits circular dichroism. The silver cluster is identified as Ag106+ using two modes of mass spectrometry and elemental analysis. Our key finding is that it adopts a low-dimensional shape, as determined from a Ag K-edge extended X-ray absorption fine structure analysis. The Ag0 in this oxidized cluster segregates from the Ag+ via a sparse number of metal-like bonds and a denser network of silver–DNA bonds. This structure contrasts with the compact, octahedral-like shape of the violet counterpart to the blue cluster, which is also a Ag106+ species. We consider that the blue- and violet-absorbing clusters may be isomers with shapes that are controlled by the secondary structures of their DNA templates.« less

Para-hydrogen and helium cluster size distributions in free jet expansions based on Smoluchowski theory with kernel scaling.

PubMed

Kornilov, Oleg; Toennies, J Peter

2015-02-21

The size distribution of para-H2 (pH2) clusters produced in free jet expansions at a source temperature of T0 = 29.5 K and pressures of P0 = 0.9-1.96 bars is reported and analyzed according to a cluster growth model based on the Smoluchowski theory with kernel scaling. Good overall agreement is found between the measured and predicted, Nk = A k(a) e(-bk), shape of the distribution. The fit yields values for A and b for values of a derived from simple collision models. The small remaining deviations between measured abundances and theory imply a (pH2)k magic number cluster of k = 13 as has been observed previously by Raman spectroscopy. The predicted linear dependence of b(-(a+1)) on source gas pressure was verified and used to determine the value of the basic effective agglomeration reaction rate constant. A comparison of the corresponding effective growth cross sections σ11 with results from a similar analysis of He cluster size distributions indicates that the latter are much larger by a factor 6-10. An analysis of the three body recombination rates, the geometric sizes and the fact that the He clusters are liquid independent of their size can explain the larger cross sections found for He.

Water-soluble phosphine-protected Au9 clusters: Electronic structures and nuclearity conversion via phase transfer

NASA Astrophysics Data System (ADS)

Yao, Hiroshi; Tsubota, Shuhei

2017-08-01

In this article, isolation, exploration of electronic structures, and nuclearity conversion of water-soluble triphenylphosphine monosulfonate (TPPS)-protected nonagold (Au9) clusters are outlined. The Au9 clusters are obtained by the reduction of solutions containing TPPS and HAuCl4 and subsequent electrophoretic fractionation. Mass spectrometry and elemental analysis reveal the formation of [Au9(TPPS)8]5- nonagold cluster. UV-vis absorption and magnetic circular dichroism (MCD) spectra of aqueous [Au9(TPPS)8]5- are quite similar to those of [Au9(PPh3)8]3+ in organic solvent, so the solution-phase structures are likely similar for both systems. Simultaneous deconvolution analysis of absorption and MCD spectra demonstrates the presence of some weak electronic transitions that are essentially unresolved in the UV-vis absorption. Quantum chemical calculations for a model compound [Au9(pH3)8]3+ show that the possible (solution-phase) skeletal structure of the nonagold cluster has D2h core symmetry rather than C4-symmetrical centered crown conformation, which is known as the crystal form of the Au9 compound. Moreover, we find a new nuclearity conversion route from Au9 to Au8; that is, phase transfer of aqueous [Au9(TPPS)8]5- into chloroform using tetraoctylammonium bromide yields [Au8(TPPS)8]6- clusters in the absence of excess phosphine.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Lagged segmented Poincaré plot analysis for risk stratification in patients with dilated cardiomyopathy.

PubMed

Voss, Andreas; Fischer, Claudia; Schroeder, Rico; Figulla, Hans R; Goernig, Matthias

2012-07-01

The objectives of this study were to introduce a new type of heart-rate variability analysis improving risk stratification in patients with idiopathic dilated cardiomyopathy (DCM) and to provide additional information about impaired heart beat generation in these patients. Beat-to-beat intervals (BBI) of 30-min ECGs recorded from 91 DCM patients and 21 healthy subjects were analyzed applying the lagged segmented Poincaré plot analysis (LSPPA) method. LSPPA includes the Poincaré plot reconstruction with lags of 1-100, rotating the cloud of points, its normalized segmentation adapted to their standard deviations, and finally, a frequency-dependent clustering. The lags were combined into eight different clusters representing specific frequency bands within 0.012-1.153 Hz. Statistical differences between low- and high-risk DCM could be found within the clusters II-VIII (e.g., cluster IV: 0.033-0.038 Hz; p = 0.0002; sensitivity = 85.7 %; specificity = 71.4 %). The multivariate statistics led to a sensitivity of 92.9 %, specificity of 85.7 % and an area under the curve of 92.1 % discriminating these patient groups. We introduced the LSPPA method to investigate time correlations in BBI time series. We found that LSPPA contributes considerably to risk stratification in DCM and yields the highest discriminant power in the low and very low-frequency bands.

Using mini-rockwool blocks as growing media for limited-cluster tomato production

NASA Technical Reports Server (NTRS)

Logendra, L. S.; Gianfagna, T. J.; Janes, H. W.

2001-01-01

Rockwool is an excellent growing medium for the hydroponic production of tomato; however, the standard size rockwool blocks [4 x 4 x 2.5 inches (10 x 10 x 6.3 cm) or 3 x 3 x 2.5 inches (7.5 x 7.5 x 6.3 cm)] are expensive. The following experiments were conducted with less expensive minirock wool blocks (MRBs), on rayon polyester material (RPM) as a bench top liner, to reduce the production cost of tomatoes (Lycopersicon esculentum) grown in a limited-cluster, ebb and flood hydroponic cultivation system. Fruit yield for single-cluster plants growing in MRBs [2 x 2 x 1.6 inches (5 x 5 x 4 cm) and 1.6 x 1.6 x 1.6 inches (4 x 4 x 4 cm)] was not significantly different from plants grown in larger sized blocks (3 x 3 x 2.5 inches). When the bench top was lined with RPM, roots penetrated the RPM, and an extensive root mat developed between the RPM and the bench top. The fruit yield from plants on RPM was significantly increased compared to plants without RPM due to increases in fruit size and fruit number. RPM also significantly reduced the incidence of blossom-end rot. In a second experiment, single- and double-cluster plants were grown on RPM. Fruit yield for double-cluster plants was 40% greater than for single-cluster plants due to an increase in fruit number, although the fruit were smaller in size. As in the first experiment, fruit yield for all plants grown in MRBs was not significantly different from plants grown in the larger sized blocks. MRBs and a RPM bench liner are an effective combination in the production of limited-cluster hydroponic tomatoes.

Predictive Rate-Distortion for Infinite-Order Markov Processes

NASA Astrophysics Data System (ADS)

Marzen, Sarah E.; Crutchfield, James P.

2016-06-01

Predictive rate-distortion analysis suffers from the curse of dimensionality: clustering arbitrarily long pasts to retain information about arbitrarily long futures requires resources that typically grow exponentially with length. The challenge is compounded for infinite-order Markov processes, since conditioning on finite sequences cannot capture all of their past dependencies. Spectral arguments confirm a popular intuition: algorithms that cluster finite-length sequences fail dramatically when the underlying process has long-range temporal correlations and can fail even for processes generated by finite-memory hidden Markov models. We circumvent the curse of dimensionality in rate-distortion analysis of finite- and infinite-order processes by casting predictive rate-distortion objective functions in terms of the forward- and reverse-time causal states of computational mechanics. Examples demonstrate that the resulting algorithms yield substantial improvements.

HRI observations of the Pleiades

NASA Technical Reports Server (NTRS)

Harnden, F. R., Jr.; Caillault, J.-P.; Damiani, F.; Kashyap, V.; Micela, G.; Prosser, C.; Rosner, R.; Sciortino, S.; Stauffer, J.

1996-01-01

The preliminary analysis of the data from the first four Rosat high resolution imager (HRI) pointings provided many new faint Pleiades detections. The completion of the high resolution survey of the most source-confused regions of this open cluster will lead to the construction of proper X-ray luminosity functions and will yield a definitive assessment of the coronal emission of the Pleiades members.

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.

2018-06-01

The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.

Time-of-flight secondary ion mass spectrometry studies of cluster ion analysis for semiconductors and diffusion of manganese in gallium arsenide at low temperatures

NASA Astrophysics Data System (ADS)

Goacher, Robyn Elizabeth

Secondary Ion Mass Spectrometry (SIMS) is an established method for the quantitative analysis of dopants in semiconductors. The quasi-parallel mass acquisition of Time-of-Flight SIMS, along with the development of polyatomic primary ions, have rapidly increased the use of SIMS for analysis of organic and biological specimens. However, the advantages and disadvantages of using cluster primary ions for quantitative analysis of inorganic materials are not clear. The research described in this dissertation investigates the consequences of using polyatomic primary ions for the analysis of inorganic compounds in ToF-SIMS. Furthermore, the diffusion of Mn in GaAs, which is important in Spintronic material applications such as spin injection, is also studied by quantitative ToF-SIMS depth profiling. In the first portion of this work, it was discovered that primary ion bombardment of pre-sputtered compound semiconductors GaAs and InP for the purpose of spectral analysis resulted in the formation of cluster secondary ions, as well as atomic secondary ions (Chapter 2). In particular, bombardment using a cluster primary ion such as Bi3q + or C60q+ resulted in higher yields of high-mass cluster secondary ions. These cluster secondary ions did not have bulk stoichiometry, "non-stoichiometric", in contrast to the paradigm of stoichiometric cluster ions generated from salts. This is attributed to the covalent bonding of the compound semiconductors, as well as to preferential sputtering. The utility of high-mass cluster secondary ions in depth profiling is also discussed. Relative sensitivity factors (RSFs) calculated for ion-implanted Fe and Mn samples in GaAs also exhibit differences based on whether monatomic or polyatomic primary ions are utilized (Chapter 3). These RSFs are important for the quantitative conversion of intensity to concentration. When Bi 32+ primary ions are used for analysis instead of Bi + primary ions, there is a significantly higher proportion of Mn and Fe ions present in the spectra, as referenced to the matrix species. The magnitude of this effect differs depending on the sputtering ion, Cs or C60. The use of C60cluster primary ions for depth profiling of GaAs is also investigated (Chapter 4). In particular, for quantitative depth profiling, parameters such as depth resolution, ion and sputter yields, and relative sensitivity factors are pertinent to profiling thin layered structures quantitatively and quickly. C60 sputtering is compared to Cs sputtering in all of these aspects. It is found that 10 keV C60+ is advantageous for the analysis of metals (such as Au contacts on Si) but that previously reported roughness problems prohibit successful analysis in Si. For Al delta layers and quantum wells in GaAs, C60 q+ sputtering induced very little roughness in the sample, and resulted in high ion yields and excellent signal-to-noise as compared to Cs+ sputtering. However, the depth resolution of C60 is at best equivalent to 1 keV Cs+ and does not extend into the sub 2-nm range. Furthermore, C60 sputtering results in significant carbon implantation. In the second portion of this work, quantitative ToF-SIMS depth profiling was used to evaluate the diffusion of Mn into GaAs. Samples were prepared by Molecular Beam Epitaxy in the department of Physics. Mn diffusion from MnAs was investigated first, and Mn diffusion from layered epitaxial structures of GaAs / Ga1-xMnxAs / GaAs was investigated second. Diffusion experiments were conducted by annealing portions of the samples in sealed glass ampoules at low temperatures (200-400°C). Different sputtering rates were measured for MnAs and GaAs and the measured depth profiles were corrected for these effects. RSFs measured for Mn ion-implanted standards were used to calibrate the intensity scale. For diffusion from MnAs, thin MnAs layers resulted in no measurable changes except in the surface transient. For thick MnAs layers, it was determined that substantial loss of As occurred at 400°C, resulting in severe sample roughening, which inhibited proper SIMS analysis. Results for the diffusion of Mn out of a thick buried layer of Ga1-xMnxAs show that annealing induces diffusion of Mn species from the Ga1-xMnxAs layer into the neighboring GaAs with an activation energy of 0.69+/-0.09 eV. This results in doping of the GaAs layer, which is detrimental to spin injection for Spintronics devices.

Nitrogen efficiency of eastern Canadian dairy herds: Effect on production performance and farm profitability.

PubMed

Fadul-Pacheco, L; Pellerin, D; Chouinard, P Y; Wattiaux, M A; Duplessis, M; Charbonneau, É

2017-08-01

Nitrogen efficiency (milk N/dietary N; NE) can be used as a tool for the nutritional, economic, and environmental management of dairy farms. The aim of this study was to identify the characteristics of herds with varying NE and assess the effect on farm profitability. One hundred dairy herds located in Québec, Canada, comprising on average 42 ± 18 cows in lactation were visited from October 2014 to June 2015. Feed intake was measured over 24 h. Samples of each feedstuff were taken and sent to a commercial laboratory for analysis of chemical composition. Feeding management and feed prices were recorded. Milk yield was recorded and milk samples were collected over 2 consecutive milkings. Fat, protein, and milk urea N were analyzed. Balances of metabolizable protein (MP; MP supply - MP requirements) and rumen degradable protein (RDP; RDP supply - RDP requirement) were calculated. A hierarchical cluster analysis was conducted and allowed grouping the farms by their NE. Four clusters were identified with an average NE of 22.1 (NE22), 26.9 (NE27), 30.0 (NE30), and 35.8% (NE36). Herds in clusters NE30 and NE36 were fed diets with greater concentrations of starch, net energy for lactation, and nonfiber carbohydrates than those in the other 2 clusters. Moreover, the average proportion of corn silage was lower for herds in cluster NE22 compared with NE30 and NE36 (8.23 vs. 31.8 and 31.3% of total forages, respectively). In addition, crude protein of the diets declined from an average of 16.0 to 14.9% with increasing NE among clusters. Average dry matter intake declined from 26.1 to 22.5 kg/d as NE of clusters increased. Herds in cluster NE22 had lower yields of milk (28.7 vs. 31.8 kg/d), fat (1.15 vs. 1.29 kg/d), and protein (0.94 vs. 1.05 kg/d) than the other clusters. Also, milk urea N was greater for farms in cluster NE22 (13.2 mg/dL) than for farms in the other clusters (11.4 mg/dL). Furthermore, MP and RDP balances decreased from 263.2 to -153.7 g/d and from 594.7 to 486.9 g/d, respectively, with increasing NE among clusters. Income over feed cost increased from $14.3 to $17.3/cow per day (Can$) as NE among clusters augmented. Results from this study showed that some farms were able to achieve high NE by using lower levels of dietary N and having cows with lower DMI while maintaining milk performance. These farms had a potentially lower environmental impact, and they were more profitable. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Typologies of Post-divorce Coparenting and Parental Well-Being, Parenting Quality and Children's Psychological Adjustment.

PubMed

Lamela, Diogo; Figueiredo, Bárbara; Bastos, Alice; Feinberg, Mark

2016-10-01

The aim of this study was to identify post-divorce coparenting profiles and examine whether these profiles differentiate between levels of parents' well-being, parenting practices, and children's psychological problems. Cluster analysis was conducted with Portuguese heterosexual divorced parents (N = 314) to yield distinct post-divorce coparenting patterns. Clusters were based on parents' self-reported coparenting relationship assessed along four dimensions: agreement, exposure to conflict, undermining/support, and division of labor. A three cluster solution was found and replicated. Parents in the high-conflict coparenting group exhibited significantly lower life satisfaction, as well as significantly higher divorce-related negative affect and inconsistent parenting than parents in undermining and cooperative coparenting clusters. The cooperative coparenting group reported higher levels of positive family functioning and lower externalizing and internalizing problems in their children. These results suggested that a positive coparenting alliance may be a protective factor for individual and family outcomes after parental divorce.

Cluster size selectivity in the product distribution of ethene dehydrogenation on niobium clusters.

PubMed

Parnis, J Mark; Escobar-Cabrera, Eric; Thompson, Matthew G K; Jacula, J Paul; Lafleur, Rick D; Guevara-García, Alfredo; Martínez, Ana; Rayner, David M

2005-08-18

Ethene reactions with niobium atoms and clusters containing up to 25 constituent atoms have been studied in a fast-flow metal cluster reactor. The clusters react with ethene at about the gas-kinetic collision rate, indicating a barrierless association process as the cluster removal step. Exceptions are Nb8 and Nb10, for which a significantly diminished rate is observed, reflecting some cluster size selectivity. Analysis of the experimental primary product masses indicates dehydrogenation of ethene for all clusters save Nb10, yielding either Nb(n)C2H2 or Nb(n)C2. Over the range Nb-Nb6, the extent of dehydrogenation increases with cluster size, then decreases for larger clusters. For many clusters, secondary and tertiary product masses are also observed, showing varying degrees of dehydrogenation corresponding to net addition of C2H4, C2H2, or C2. With Nb atoms and several small clusters, formal addition of at least six ethene molecules is observed, suggesting a polymerization process may be active. Kinetic analysis of the Nb atom and several Nb(n) cluster reactions with ethene shows that the process is consistent with sequential addition of ethene units at rates corresponding approximately to the gas-kinetic collision frequency for several consecutive reacting ethene molecules. Some variation in the rate of ethene pick up is found, which likely reflects small energy barriers or steric constraints associated with individual mechanistic steps. Density functional calculations of structures of Nb clusters up to Nb(6), and the reaction products Nb(n)C2H2 and Nb(n)C2 (n = 1...6) are presented. Investigation of the thermochemistry for the dehydrogenation of ethene to form molecular hydrogen, for the Nb atom and clusters up to Nb6, demonstrates that the exergonicity of the formation of Nb(n)C2 species increases with cluster size over this range, which supports the proposal that the extent of dehydrogenation is determined primarily by thermodynamic constraints. Analysis of the structural variations present in the cluster species studied shows an increase in C-H bond lengths with cluster size that closely correlates with the increased thermodynamic drive to full dehydrogenation. This correlation strongly suggests that all steps in the reaction are barrierless, and that weakening of the C-H bonds is directly reflected in the thermodynamics of the overall dehydrogenation process. It is also demonstrated that reaction exergonicity in the initial partial dehydrogenation step must be carried through as excess internal energy into the second dehydrogenation step.

Fine mapping of a yield-enhancing QTL cluster associated with transgressive variation in an Oryza sativa x O. rufipogon cross.

PubMed

Xie, Xiaobo; Jin, Fengxue; Song, Mi-Hee; Suh, Jung-Pil; Hwang, Hung-Goo; Kim, Yeon-Gyu; McCouch, Susan R; Ahn, Sang-Nag

2008-03-01

A high-resolution physical map targeting a cluster of yield-related QTLs on the long arm of rice chromosome 9 has been constructed across a 37.4 kb region containing seven predicted genes. Using a series of BC3F4 nearly isogenic lines (NILs) derived from a cross between the Korean japonica cultivar Hwaseongbyeo and Oryza rufipogon (IRGC 105491), a total of seven QTLs for 1,000-grain weight, spikelets per panicle, grains per panicle, panicle length, spikelet density, heading date and plant height were identified in the cluster (P

Muscle ischaemia associated with NXP2 autoantibodies: a severe subtype of juvenile dermatomyositis.

PubMed

Aouizerate, Jessie; De Antonio, Marie; Bader-Meunier, Brigitte; Barnerias, Christine; Bodemer, Christine; Isapof, Arnaud; Quartier, Pierre; Melki, Isabelle; Charuel, Jean-Luc; Bassez, Guillaume; Desguerre, Isabelle; Gherardi, Romain K; Authier, François-Jérôme; Gitiaux, Cyril

2018-05-01

Myositis-specific autoantibodies (MSAs) are increasingly used to delineate distinct subgroups of JDM. The aim of our study was to explore without a priori hypotheses whether MSAs are associated with distinct clinical-pathological changes and severity in a monocentric JDM cohort. Clinical, biological and histological findings from 23 JDM patients were assessed. Twenty-six histopathological parameters were subjected to multivariate analysis. Autoantibodies included anti-NXP2 (9/23), anti-TIF1γ (4/23), anti-MDA5 (2/23), no MSAs (8/23). Multivariate analysis yielded two histopathological clusters. Cluster 1 (n = 11) showed a more severe and ischaemic pattern than cluster 2 (n = 12) assessed by: total score severity ⩾ 20 (100.0% vs 25.0%); visual analogic score ⩾6 (100.0% vs 25.0%); the vascular domain score >1 (100.0% vs 41.7%); microinfarcts (100% vs 58.3%); ischaemic myofibrillary loss (focal punched-out vacuoles) (90.9 vs 25%); and obvious capillary loss (81.8% vs 16.7). Compared with cluster 2, patients in cluster 1 had strikingly more often anti-NXP2 antibodies (7/11 vs 2/12), more pronounced muscle weakness, more gastrointestinal involvement and required more aggressive treatment. Furthermore, patients with anti-NXP2 antibodies, mostly assigned in the first cluster, also displayed more severe muscular disease, requiring more aggressive treatment and having a lower remission rate during the follow-up period. Marked muscle ischaemic involvement and the presence of anti-NXP2 autoantibodies are associated with more severe forms of JDM.

Denaturing gradient gel electrophoresis profiles of bacteria from the saliva of twenty four different individuals form clusters that showed no relationship to the yeasts present.

PubMed

M Weerasekera, Manjula; H Sissons, Chris; Wong, Lisa; A Anderson, Sally; R Holmes, Ann; D Cannon, Richard

2017-10-01

The aim was to investigate the relationship between groups of bacteria identified by cluster analysis of the DGGE fingerprints and the amounts and diversity of yeast present. Bacterial and yeast populations in saliva samples from 24 adults were analysed using denaturing gradient gel electrophoresis (DGGE) of the bacteria present and by yeast culture. Eubacterial DGGE banding patterns showed considerable variation between individuals. Seventy one different amplicon bands were detected, the band number per saliva sample ranged from 21 to 39 (mean±SD=29.3±4.9). Cluster and principal component analysis of the bacterial DGGE patterns yielded three major clusters containing 20 of the samples. Seventeen of the 24 (71%) saliva samples were yeast positive with concentrations up to 10 3 cfu/mL. Candida albicans was the predominant species in saliva samples although six other yeast species, including Candida dubliniensis, Candida tropicalis, Candida krusei, Candida guilliermondii, Candida rugosa and Saccharomyces cerevisiae, were identified. The presence, concentration, and species of yeast in samples showed no clear relationship to the bacterial clusters. Despite indications of in vitro bacteria-yeast interactions, there was a lack of association between the presence, identity and diversity of yeasts and the bacterial DGGE fingerprint clusters in saliva. This suggests significant ecological individual-specificity of these associations in highly complex in vivo oral biofilm systems under normal oral conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Para-hydrogen and helium cluster size distributions in free jet expansions based on Smoluchowski theory with kernel scaling

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

Kornilov, Oleg; Toennies, J. Peter

The size distribution of para-H{sub 2} (pH{sub 2}) clusters produced in free jet expansions at a source temperature of T{sub 0} = 29.5 K and pressures of P{sub 0} = 0.9–1.96 bars is reported and analyzed according to a cluster growth model based on the Smoluchowski theory with kernel scaling. Good overall agreement is found between the measured and predicted, N{sub k} = A k{sup a} e{sup −bk}, shape of the distribution. The fit yields values for A and b for values of a derived from simple collision models. The small remaining deviations between measured abundances and theory imply a (pH{submore » 2}){sub k} magic number cluster of k = 13 as has been observed previously by Raman spectroscopy. The predicted linear dependence of b{sup −(a+1)} on source gas pressure was verified and used to determine the value of the basic effective agglomeration reaction rate constant. A comparison of the corresponding effective growth cross sections σ{sub 11} with results from a similar analysis of He cluster size distributions indicates that the latter are much larger by a factor 6-10. An analysis of the three body recombination rates, the geometric sizes and the fact that the He clusters are liquid independent of their size can explain the larger cross sections found for He.« less

Efficient Synthesis of Ir-Polyoxometalate Cluster Using a Continuous Flow Apparatus and STM Investigation of Its Coassembly Behavior on HOPG Surface.

PubMed

Zhang, Junyong; Chang, Shaoqing; Suryanto, Bryan H R; Gong, Chunhua; Zeng, Xianghua; Zhao, Chuan; Zeng, Qingdao; Xie, Jingli

2016-06-06

Taking advantage of a continuous-flow apparatus, the iridium(III)-containing polytungstate cluster K12Na2H2[Ir2Cl8P2W20O72]·37H2O (1) was obtained in a reasonable yield (13% based on IrCl3·H2O). Compound 1 was characterized by Fourier transform IR, UV-visible, (31)P NMR, electrospray ionization mass spectrometry (ESI-MS), and thermogravimetric analysis measurements. (31)P NMR, ESI-MS, and elemental analysis all indicated 1 was a new polytungstate cluster compared with the reported K14[(IrCl4)KP2W20O72] compound. Intriguingly, the successful isolation of 1 relied on the custom-built flow apparatus, demonstrating the uniqueness of continuous-flow chemistry to achieve crystalline materials. The catalytic properties of 1 were assessed by investigating the activity on catalyzing the electro-oxidation of ruthenium tris-2,2'-bipyridine [Ru(bpy)3](2+/3+). The voltammetric behavior suggested a coupled catalytic behavior between [Ru(bpy)3](3+/2+) and 1. Furthermore, on the highly oriented pyrolytic graphite surface, 1,3,5-tris(10-carboxydecyloxy) benzene (TCDB) was used as the two-dimensional host network to coassemble cluster 1; the surface morphology was observed by scanning tunneling microscope technique. "S"-shape of 1 was observed, indicating that the cluster could be accommodated in the cavity formed by two TCDB host molecules, leading to a TCDB/cluster binary structure.

Temporality in British young women's magazines: food, cooking and weight loss.

PubMed

Spencer, Rosemary J; Russell, Jean M; Barker, Margo E

2014-10-01

The present study examines seasonal and temporal patterns in food-related content of two UK magazines for young women focusing on food types, cooking and weight loss. Content analysis of magazines from three time blocks between 1999 and 2011. Desk-based study. Ninety-seven magazines yielding 590 advertisements and 148 articles. Cluster analysis of type of food advertising produced three clusters of magazines, which reflected recognised food behaviours of young women: vegetarianism, convenience eating and weight control. The first cluster of magazines was associated with Christmas and Millennium time periods, with advertising of alcohol, coffee, cheese, vegetarian meat substitutes and weight-loss pills. Recipes were prominent in article content and tended to be for cakes/desserts, luxury meals and party food. The second cluster was associated with summer months and 2010 issues. There was little advertising for conventional foods in cluster 2, but strong representation of diet plans and foods for weight loss. Weight-loss messages in articles focused on short-term aesthetic goals, emphasising speedy weight loss without giving up nice foods or exercising. Cluster 3 magazines were associated with post-New Year and 2005 periods. Food advertising was for everyday foods and convenience products, with fewer weight-loss products than other clusters; conversely, article content had a greater prevalence of weight-loss messages. The cyclical nature of magazine content - indulgence and excess encouraged at Christmas, restraint recommended post-New Year and severe dieting advocated in the summer months - endorses yo-yo dieting behaviour and may not be conducive to public health.

Near-infrared spectroscopy of candidate red supergiant stars in clusters

NASA Astrophysics Data System (ADS)

Messineo, Maria; Zhu, Qingfeng; Ivanov, Valentin D.; Figer, Donald F.; Davies, Ben; Menten, Karl M.; Kudritzki, Rolf P.; Chen, C.-H. Rosie

2014-11-01

Context. Clear identifications of Galactic young stellar clusters farther than a few kpc from the Sun are rare, despite the large number of candidate clusters. Aims: We aim to improve the selection of candidate clusters rich in massive stars with a multiwavelength analysis of photometric Galactic data that range from optical to mid-infrared wavelengths. Methods: We present a photometric and spectroscopic analysis of five candidate stellar clusters, which were selected as overdensities with bright stars (Ks< 7 mag) in GLIMPSE and 2MASS images. Results: A total of 48 infrared spectra were obtained. The combination of photometry and spectroscopy yielded six new red supergiant stars with masses from 10 M⊙ to 15 M⊙. Two red supergiants are located at Galactic coordinates (l,b) = (16.°7, -0.°63) and at a distance of about ~3.9 kpc; four other red supergiants are members of a cluster at Galactic coordinates (l,b) = (49.°3, + 0.°72) and at a distance of ~7.0 kpc. Conclusions: Spectroscopic analysis of the brightest stars of detected overdensities and studies of interstellar extinction along their line of sights are fundamental to distinguish regions of low extinction from actual stellar clusters. The census of young star clusters containing red supergiants is incomplete; in the existing all-sky near-infrared surveys, they can be identified as overdensities of bright stars with infrared color-magnitude diagrams characterized by gaps. Based on observations collected at the European Southern Observatory (ESO Programme 60.A-9700(E), and 089.D-0876), and on observations collected at the UKIRT telescope (programme ID H243NS).MM is currently employed by the MPIfR. Part of this work was performed at RIT (2009), at ESA (2010), and at the MPIfR.Tables 3, 4, and 6 are available in electronic form at http://www.aanda.org

Pollen morphology and plant taxonomy of white oaks in eastern North America

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

Solomon, A.M.

An evaluation of possible approaches to fossil oak pollen identification utilized scanning electron microscopy to examine exine-surface features of 171 collections, representing 16 Quercus subgenus Lepidobalanus species and varieties of eastern North America. Twenty qualitative pollen morphological characters were defined and tabulated for each of 217 pollen grains. The data were subjected to cluster analysis and cluster diagrams were compared with published white oak taxonomy. Pollen morphology and plant taxonomy compared well in series of the subgenus Lepidobalanus due primarily to consistency of character presence and absence within species and varieties. Pollen morphology of white oaks appears to reflect plantmore » systematics above the species level. Use of routine SEM analysis to identify series of white oaks among fossil pollen grains likely will yield valid results. 38 references.« less

A new approach for evaluating flexible working hours.

PubMed

Giebel, Ole; Janssen, Daniela; Schomann, Carsten; Nachreiner, Friedhelm

2004-01-01

Recent studies on flexible working hours show at least some of these working time arrangements seem to be associated with impairing effects of health and well-being. According to available evidence, variability of working hours seems to play an important role. The question, however, is how this variability can be assessed and used to explain or predict impairments. Based on earlier methods used to assess shift-work effects, a time series analysis approach was applied to the matter of flexible working hours. Data on the working hours of 4 week's length of 137 respondents derived from a survey on flexible work hours involving 15 companies of different production and service sectors in Germany were converted to time series and analyzed by spectral analysis. A cluster analysis of the resulting power spectra yielded 5 clusters of flexible work hours. Analyzing these clusters for differences in reported impairments showed that workers who showed suppression of circadian and weekly rhythms experienced severest impairments, especially in circadian controlled functions like sleep and digestion. The results thus indicate that analyzing the periodicity of flexible working hours seems to be a promising approach for predicting impairments which should be investigated further in the future.

THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

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

Griffin, Rhiannon D.; Dai, Xinyu; Kochanek, Christopher S.

2016-01-15

We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% ofmore » the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections.« less

A Kinetic Analysis of the Auxin Transcriptome Reveals Cell Wall Remodeling Proteins That Modulate Lateral Root Development in Arabidopsis[W][OPEN

PubMed Central

Lewis, Daniel R.; Olex, Amy L.; Lundy, Stacey R.; Turkett, William H.; Fetrow, Jacquelyn S.; Muday, Gloria K.

2013-01-01

To identify gene products that participate in auxin-dependent lateral root formation, a high temporal resolution, genome-wide transcript abundance analysis was performed with auxin-treated Arabidopsis thaliana roots. Data analysis identified 1246 transcripts that were consistently regulated by indole-3-acetic acid (IAA), partitioning into 60 clusters with distinct response kinetics. We identified rapidly induced clusters containing auxin-response functional annotations and clusters exhibiting delayed induction linked to cell division temporally correlated with lateral root induction. Several clusters were enriched with genes encoding proteins involved in cell wall modification, opening the possibility for understanding mechanistic details of cell structural changes that result in root formation following auxin treatment. Mutants with insertions in 72 genes annotated with a cell wall remodeling function were examined for alterations in IAA-regulated root growth and development. This reverse-genetic screen yielded eight mutants with root phenotypes. Detailed characterization of seedlings with mutations in CELLULASE3/GLYCOSYLHYDROLASE9B3 and LEUCINE RICH EXTENSIN2, genes not normally linked to auxin response, revealed defects in the early and late stages of lateral root development, respectively. The genes identified here using kinetic insight into expression changes lay the foundation for mechanistic understanding of auxin-mediated cell wall remodeling as an essential feature of lateral root development. PMID:24045021

Planck 2015 results. XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Weller, J.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing of background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. Improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

Planck 2015 results: XXIV. Cosmology from Sunyaev-Zeldovich cluster counts

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

Ade, P. A. R.; Aghanim, N.; Arnaud, M.

In this work, we present cluster counts and corresponding cosmological constraints from the Planck full mission data set. Our catalogue consists of 439 clusters detected via their Sunyaev-Zeldovich (SZ) signal down to a signal-to-noise ratio of 6, and is more than a factor of 2 larger than the 2013 Planck cluster cosmology sample. The counts are consistent with those from 2013 and yield compatible constraints under the same modelling assumptions. Taking advantage of the larger catalogue, we extend our analysis to the two-dimensional distribution in redshift and signal-to-noise. We use mass estimates from two recent studies of gravitational lensing ofmore » background galaxies by Planck clusters to provide priors on the hydrostatic bias parameter, (1-b). In addition, we use lensing of cosmic microwave background (CMB) temperature fluctuations by Planck clusters as an independent constraint on this parameter. These various calibrations imply constraints on the present-day amplitude of matter fluctuations in varying degrees of tension with those from the Planck analysis of primary fluctuations in the CMB; for the lowest estimated values of (1-b) the tension is mild, only a little over one standard deviation, while it remains substantial (3.7σ) for the largest estimated value. We also examine constraints on extensions to the base flat ΛCDM model by combining the cluster and CMB constraints. The combination appears to favour non-minimal neutrino masses, but this possibility does little to relieve the overall tension because it simultaneously lowers the implied value of the Hubble parameter, thereby exacerbating the discrepancy with most current astrophysical estimates. In conclusion, improving the precision of cluster mass calibrations from the current 10%-level to 1% would significantly strengthen these combined analyses and provide a stringent test of the base ΛCDM model.« less

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

PubMed

Adamczak, Rafal; Meller, Jarek

2016-12-28

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

Nanoclusters first: a hierarchical phase transformation in a novel Mg alloy

NASA Astrophysics Data System (ADS)

Okuda, Hiroshi; Yamasaki, Michiaki; Kawamura, Yoshihito; Tabuchi, Masao; Kimizuka, Hajime

2015-09-01

The Mg-Y-Zn ternary alloy system contains a series of novel structures known as long-period stacking ordered (LPSO) structures. The formation process and its key concept from a viewpoint of phase transition are not yet clear. The current study reveals that the phase transformation process is not a traditional spinodal decomposition or structural transformation but, rather a novel hierarchical phase transformation. In this transformation, clustering occurs first, and the spatial rearrangement of the clusters induce a secondary phase transformation that eventually lead to two-dimensional ordering of the clusters. The formation process was examined using in situ synchrotron radiation small-angle X-ray scattering (SAXS). Rapid quenching from liquid alloy into thin ribbons yielded strongly supersaturated amorphous samples. The samples were heated at a constant rate of 10 K/min. and the scattering patterns were acquired. The SAXS analysis indicated that small clusters grew to sizes of 0.2 nm after they crystallized. The clusters distributed randomly in space grew and eventually transformed into a microstructure with two well-defined cluster-cluster distances, one for the segregation periodicity of LPSO and the other for the in-plane ordering in segregated layer. This transformation into the LPSO structure concomitantly introduces the periodical stacking fault required for the 18R structures.

Water-Soluble Phosphine-Protected Au₁₁ Clusters: Synthesis, Electronic Structure, and Chiral Phase Transfer in a Synergistic Fashion.

PubMed

Yao, Hiroshi; Iwatsu, Mana

2016-04-05

Synthesis of atomically precise, water-soluble phosphine-protected gold clusters is still currently limited probably due to a stability issue. We here present the synthesis, magic-number isolation, and exploration of the electronic structures as well as the asymmetric conversion of triphenylphosphine monosulfonate (TPPS)-protected gold clusters. Electrospray ionization mass spectrometry and elemental analysis result in the primary formation of Au11(TPPS)9Cl undecagold cluster compound. Magnetic circular dichroism (MCD) spectroscopy clarifies that extremely weak transitions are present in the low-energy region unresolved in the UV-vis absorption, which can be due to the Faraday B-terms based on the magnetically allowed transitions in the cluster. Asymmetric conversion without changing the nuclearity is remarkable by the chiral phase transfer in a synergistic fashion, which yields a rather small anisotropy factor (g-factor) of at most (2.5-7.0) × 10(-5). Quantum chemical calculations for model undecagold cluster compounds are then used to evaluate the optical and chiroptical responses induced by the chiral phase transfer. On this basis, we find that the Au core distortion is ignorable, and the chiral ion-pairing causes a slight increase in the CD response of the Au11 cluster.

Functional and bioinformatics analysis of an exopolysaccharide-related gene (epsN) from Lactobacillus kefiranofaciens ZW3.

PubMed

Wang, Jingrui; Tang, Wei; Zheng, Yongna; Xing, Zhuqing; Wang, Yanping

2016-09-01

A novel lactic acid bacteria strain Lactobacillus kefiranofaciens ZW3 exhibited the characteristics of high production of exopolysaccharide (EPS). The epsN gene, located in the eps gene cluster of this strain, is associated with EPS biosynthesis. Bioinformatics analysis of this gene was performed. The conserved domain analysis showed that the EpsN protein contained MATE-Wzx-like domains. Then the epsN gene was amplified to construct the recombinant expression vector pMG36e-epsN. The results showed that the EPS yields of the recombinants were significantly improved. By determining the yields of EPS and intracellular polysaccharide, it was considered that epsN gene could play its Wzx flippase role in the EPS biosynthesis. This is the first time to prove the effect of EpsN on L. kefiranofaciens EPS biosynthesis and further prove its functional property.

Measurement of liner slips, milking time, and milk yield.

PubMed

O'Callaghan, E J

1996-03-01

Liner slip or rapid air leakage past the mouthpiece of the milking machine liner is related to high rates of new cases of mastitis. A real time technique was developed to monitor the air flow into the milking machine cluster during liner slips as well as to monitor milking time and milk yield using a commercial type pipeline milking system. The air flow into the cluster was measured by recording the pressure differences across an orifice plate placed in the air bypass of an air-milk separator using a differential pressure transducer. Milk yield was recorded by counting the number of milk releases from an electronic milk meter. The release solenoids of the milk meter were linked to a computer. The start and end of milking were manually recorded by switching a two-pole switch connected to a digital input card on the computer, which was programmed to record air flow, milk yield, and milking time. Milk yield, milking time, and air flows during liner slips were recorded simultaneously at each milking unit in an 11-unit herringbone parlor. The system was tested with an experiment with a 4 x 4 Latin square design using four treatments (clusters) and four treatment groups (22 cows per group).

Molecular dynamics simulations with electronic stopping can reproduce experimental sputtering yields of metals impacted by large cluster ions

NASA Astrophysics Data System (ADS)

Tian, Jiting; Zhou, Wei; Feng, Qijie; Zheng, Jian

2018-03-01

An unsolved problem in research of sputtering from metals induced by energetic large cluster ions is that molecular dynamics (MD) simulations often produce sputtering yields much higher than experimental results. Different from the previous simulations considering only elastic atomic interactions (nuclear stopping), here we incorporate inelastic electrons-atoms interactions (electronic stopping, ES) into MD simulations using a friction model. In this way we have simulated continuous 45° impacts of 10-20 keV C60 on a Ag(111) surface, and found that the calculated sputtering yields can be very close to the experimental results when the model parameter is appropriately assigned. Conversely, when we ignore the effect of ES, the yields are much higher, just like the previous studies. We further expand our research to the sputtering of Au induced by continuous keV C60 or Ar100 bombardments, and obtain quite similar results. Our study indicates that the gap between the experimental and the simulated sputtering yields is probably induced by the ignorance of ES in the simulations, and that a careful treatment of this issue is important for simulations of cluster-ion-induced sputtering, especially for those aiming to compare with experiments.

Evaluation of genetic diversity in jackfruit (Artocarpus heterophyllus Lam.) based on amplified fragment length polymorphism markers.

PubMed

Shyamalamma, S; Chandra, S B C; Hegde, M; Naryanswamy, P

2008-07-22

Artocarpus heterophyllus Lam., commonly called jackfruit, is a medium-sized evergreen tree that bears high yields of the largest known edible fruit. Yet, it has been little explored commercially due to wide variation in fruit quality. The genetic diversity and genetic relatedness of 50 jackfruit accessions were studied using amplified fragment length polymorphism markers. Of 16 primer pairs evaluated, eight were selected for screening of genotypes based on the number and quality of polymorphic fragments produced. These primer combinations produced 5976 bands, 1267 (22%) of which were polymorphic. Among the jackfruit accessions, the similarity coefficient ranged from 0.137 to 0.978; the accessions also shared a large number of monomorphic fragments (78%). Cluster analysis and principal component analysis grouped all jackfruit genotypes into three major clusters. Cluster I included the genotypes grown in a jackfruit region of Karnataka, called Tamaka, with very dry conditions; cluster II contained the genotypes collected from locations having medium to heavy rainfall in Karnataka; cluster III grouped the genotypes in distant locations with different environmental conditions. Strong coincidence of these amplified fragment length polymorphism-based groupings with geographical localities as well as morphological characters was observed. We found moderate genetic diversity in these jackfruit accessions. This information should be useful for tree breeding programs, as part of our effort to popularize jackfruit as a commercial crop.

Effects of molecular weight and cationization agent on the sensitivity of Bi cluster secondary ion mass spectrometry.

PubMed

Fujii, Makiko; Shishido, Rie; Satoh, Takaya; Suzuki, Shigeru; Matsuo, Jiro

2016-07-30

Bi cluster secondary ion mass spectrometry (SIMS) is one of the most promising tools for precise analysis of synthetic polymers. However, the sensitivity in the high-mass region is still insufficient compared with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS). Accordingly, the effects of metal assistance (cationization agents) were investigated in this study. To investigate the effects caused by varying the ionization agent, three different polyethylene glycol (PEG) samples were prepared, one with an Ag-deposited film, and two others mixed with Ag and Na, respectively. The measurements were performed by using a commercial Bi cluster SIMS and MALDI-TOFMS systems. The mass spectrum obtained with MALDI-TOFMS was used as a reference molecular weight distribution to evaluate the effects of molecular weight and primary ion species (Bi + , Bi 3 + , Bi 3 2 + ) on the sensitivity of Bi cluster SIMS. The intensity of each secondary ion was the highest in Bi 3 2 + irradiation, and the lowest in Bi + irradiation. Regarding the cationization agents, the secondary ion yield was the highest for the sample mixed with Ag, while the degree of decay of sensitivity along with the increase in molecular weight was the smallest for the sample mixed with Na. It was suggested that the cationization mechanism consists of pre-formed ionization and gas-phase ionization processes. The sensitivity of Bi cluster SIMS decreases to approximately one-fiftieth in every 1000 u. These results might help in understanding the mechanism of cationization and further enhancement of secondary ion yields of polymers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait.

PubMed

Solav, Dana; Camomilla, Valentina; Cereatti, Andrea; Barré, Arnaud; Aminian, Kamiar; Wolf, Alon

2017-09-06

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, which can be measured non-invasively in vivo, to identify the most accurate TCPEs. Moreover, TCPE pose estimations were compared with the estimations of two least squares minimization methods applied to the cluster of all markers, using rigid body (RBLS) and homogeneous deformation (HDLS) assumptions. Analysis was performed on previously collected in vivo treadmill gait data composed of simultaneous measurements of the gold-standard bone pose by bi-plane fluoroscopy tracking the subjects' knee prosthesis and a stereophotogrammetric system tracking skin-markers affected by soft tissue artifact. Femur orientation and position errors estimated from skin-marker clusters were computed for 18 subjects using clusters of up to 35 markers. Results based on gold-standard data revealed that instantaneous subsets of TCPEs exist which estimate the femur pose with reasonable accuracy (median root mean square error during stance/swing: 1.4/2.8deg for orientation, 1.5/4.2mm for position). A non-invasive and instantaneous criteria to select accurate TCPEs for pose estimation (4.8/7.3deg, 5.8/12.3mm), was compared with RBLS (4.3/6.6deg, 6.9/16.6mm) and HDLS (4.6/7.6deg, 6.7/12.5mm). Accounting for homogeneous deformation, using HDLS or selected TCPEs, yielded more accurate position estimations than RBLS method, which, conversely, yielded more accurate orientation estimations. Further investigation is required to devise effective criteria for cluster selection that could represent a significant improvement in bone pose estimation accuracy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

PubMed

Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

2015-09-01

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Using coordinate-based meta-analyses to explore structural imaging genetics.

PubMed

Janouschek, Hildegard; Eickhoff, Claudia R; Mühleisen, Thomas W; Eickhoff, Simon B; Nickl-Jockschat, Thomas

2018-05-05

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

NASA Astrophysics Data System (ADS)

Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

2014-10-01

Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

Cluster analysis of the organic peaks in bulk mass spectra obtained during the 2002 New England Air Quality Study with an Aerodyne aerosol mass spectrometer

NASA Astrophysics Data System (ADS)

Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.; Middlebrook, A. M.

2006-06-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter most probably originating from both, anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent as much as 5 µg/m3 organic aerosol mass - 17% of the total organic mass - that can be attributed to biogenic sources. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

A new application of hierarchical cluster analysis to investigate organic peaks in bulk mass spectra obtained with an Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Middlebrook, A. M.; Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.

2006-12-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

Cluster Analysis of the Organic Peaks in Bulk Mass Spectra Obtained During the 2002 New England Air Quality Study with an Aerodyne Aerosol Mass Spectrometer

NASA Astrophysics Data System (ADS)

Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M.; Bertman, S. B.; Middlebrook, A. M.

2006-12-01

We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel R. H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.

Advanced Electrochemistry of Individual Metal Clusters Electrodeposited Atom by Atom to Nanometer by Nanometer.

PubMed

Kim, Jiyeon; Dick, Jeffrey E; Bard, Allen J

2016-11-15

Metal clusters are very important as building blocks for nanoparticles (NPs) for electrocatalysis and electroanalysis in both fundamental and applied electrochemistry. Attention has been given to understanding of traditional nucleation and growth of metal clusters and to their catalytic activities for various electrochemical applications in energy harvesting as well as analytical sensing. Importantly, understanding the properties of these clusters, primarily the relationship between catalysis and morphology, is required to optimize catalytic function. This has been difficult due to the heterogeneities in the size, shape, and surface properties. Thus, methods that address these issues are necessary to begin understanding the reactivity of individual catalytic centers as opposed to ensemble measurements, where the effect of size and morphology on the catalysis is averaged out in the measurement. This Account introduces our advanced electrochemical approaches to focus on each isolated metal cluster, where we electrochemically fabricated clusters or NPs atom by atom to nanometer by nanometer and explored their electrochemistry for their kinetic and catalytic behavior. Such approaches expand the dimensions of analysis, to include the electrochemistry of (1) a discrete atomic cluster, (2) solely a single NP, or (3) individual NPs in the ensemble sample. Specifically, we studied the electrocatalysis of atomic metal clusters as a nascent electrocatalyst via direct electrodeposition on carbon ultramicroelectrode (C UME) in a femtomolar metal ion precursor. In addition, we developed tunneling ultramicroelectrodes (TUMEs) to study electron transfer (ET) kinetics of a redox probe at a single metal NP electrodeposited on this TUME. Owing to the small dimension of a NP as an active area of a TUME, extremely high mass transfer conditions yielded a remarkably high standard ET rate constant, k 0 , of 36 cm/s for outer-sphere ET reaction. Most recently, we advanced nanoscale scanning electrochemical microscopy (SECM) imaging to resolve the electrocatalytic activity of individual electrodeposited NPs within an ensemble sample yielding consistent high k 0 values of ≥2 cm/s for the hydrogen oxidation reaction (HOR) at different NPs. We envision that our advanced electrochemical approaches will enable us to systematically address structure effects on the catalytic activity, thus providing a quantitative guideline for electrocatalysts in energy-related applications.

Analysis of nonlinear relationships in dual epidemics, and its application to the management of grapevine downy and powdery mildews.

PubMed

Savary, Serge; Delbac, Lionel; Rochas, Amélie; Taisant, Guillaume; Willocquet, Laetitia

2009-08-01

Dual epidemics are defined as epidemics developing on two or several plant organs in the course of a cropping season. Agricultural pathosystems where such epidemics develop are often very important, because the harvestable part is one of the organs affected. These epidemics also are often difficult to manage, because the linkage between epidemiological components occurring on different organs is poorly understood, and because prediction of the risk toward the harvestable organs is difficult. In the case of downy mildew (DM) and powdery mildew (PM) of grapevine, nonlinear modeling and logistic regression indicated nonlinearity in the foliage-cluster relationships. Nonlinear modeling enabled the parameterization of a transmission coefficient that numerically links the two components, leaves and clusters, in DM and PM epidemics. Logistic regression analysis yielded a series of probabilistic models that enabled predicting preset levels of cluster infection risks based on DM and PM severities on the foliage at successive crop stages. The usefulness of this framework for tactical decision-making for disease control is discussed.

The Distance and Mass of the Galaxy Cluster Abell 1995 Derived from Sunyaev-Zeldovich Effect and X-Ray Measurements

NASA Technical Reports Server (NTRS)

Patel, Sandeep K.; Joy, Marshall; Carlstrom, John E.; Holder, Gilbert P.; Reese, Erik D.; Gomez, Percy L.; Hughes, John P.; Grego, Laura; Holzapfel, William L.

2000-01-01

We present multiwavelength observations of the Abell 1995 galaxy cluster. From an analysis of X-ray spectroscopy and imaging data, we derive the electron temperature, cluster core radius, and central electron number density. Using optical spectroscopy of 15 cluster members, we derive an accurate cluster redshift and velocity dispersion. Finally, the interferometric imaging of the Sunyaev-Zeldovich effect toward Abell 1995 at 28.5 GHz provides a measure of the integrated pressure through the cluster. The X-ray and Sunyaev-Zeldovich effect observations are combined to determine the angular diameter distance to the cluster of D(sub A) = 1294(sup +294 +438, sub -283 -458) Mpc (Statistical followed by systematic uncertainty), implying a Hubble constant of H(sub 0) = 52.2(sup +11.4 +18.5, sub -11.9 -17.7) km/s.Mpc for Omega(sub M) = 0.3 and Omega(sub lambda) = 0.7. We find a best-fit H(sub 0) of 46 km/s.Mpc for the Omega(sub M) = 1 and Omega(sub lambda) = 0 cosmology, and 48 km/s.Mpc for Omega(sub M) = 0.3 and Omega(sub lambda) = 0.0. The X-ray data are also used to derive a total cluster mass of M(sup HSE, sub tot)(r(sub 500)) = 5.18(sup +0.62, sub -0.48) x 10(exp 14)/h solar mass; the optical velocity dispersion yields an independent and consistent estimate of M(sup virial, sub tot)(r(sub 500)) = 6.35(sup +1.51, sub -1.19) X 10(exp 14) /h solar mass. Both of the total mass estimates are evaluated at a fiducial radius, r(sub 500) = 830 /h kpc, where the overdensity is 500 times the critical density. The total cluster mass is then combined with gas mass measurements to determine a cluster gas mass fraction of F(sub g) = 0.056(sup +0.010, sub -0.013) /h(sup 3/2) in combination with recent baryon density constraints, the measured gas mass fraction yields an upper limit on the mass density parameter of Omega(sub M) h(sup 1/2) <= 0.34(sup +/0.06, sub 0.05.

Investigating the health profile of patients with end-stage renal failure receiving peritoneal dialysis: a cluster analysis.

PubMed

Chan, M F; Wong, Frances K Y; Chow, Susan K Y

2010-03-01

To determine whether the patients with end stage renal failure can be differentiated into several subtypes based on five main variables. There is a lack of interventional research linking to clinical outcomes among the patients with end stage renal failure in Hong Kong and with no clear evidence of differences in terms of their clinical/health outcomes and characteristics. A cross-sectional survey. Data were collected using a structured questionnaire. One hundred and fifty-three patients with end stage renal failure were recruited during 2007 at three renal centres in Hong Kong. Five main variables were employed: predisposing characteristic, enabling resources, quality of life, symptom control and self-care adherence. A cluster analysis yielded two clusters. Each cluster represented a different profile of patients with end stage renal failure. Cluster A consisted of 49.7% (n = 76) and Cluster B consisted of 50.3% (n = 77) of the patients. Cluster A patients, more of whom were women, were older, less educated, had higher quality of life scores, a better adherence rate and more had received nursing care supports than patients in Cluster B. We have identified two groupings of patients with end stage renal failure who were experiencing unique health profile. Nursing support services may have an effect on patient health outcomes but only on a group of patients whose profile is similar to the patients in Cluster A and not for patients in Cluster B. A clear profile may help health care professional make appropriate strategies to target a specific group of patients to improve patient outcomes. The identification of risk for future health-care use could enable better targeting of interventional strategies in these groups. The results of this study might provide health care professionals with a model to design specified interventions to improve life quality for each profile group.

High-yield production of herbicidal thaxtomins and analogs in a nonpathogenic Streptomyces strain.

PubMed

Jiang, Guangde; Zhang, Yucheng; Powell, Magan M; Zhang, Peilan; Zuo, Ran; Zhang, Yi; Kallifidas, Dimitrios; Tieu, Albert M; Luesch, Hendrik; Loria, Rosemary; Ding, Yousong

2018-03-30

Thaxtomins are virulence factors of most plant pathogenic Streptomyces strains. Due to their potent herbicidal activity, attractive environmental compatibility and inherent biodegradability, thaxtomins are key active ingredients of bioherbicides approved by the United States Environmental Protection Agency. However, the low yield of thaxtomins in native Streptomyces producers limits their wide agricultural applications. Here, we describe the high-yield production of thaxtomins in a heterologous host. The thaxtomin gene cluster from S. scabiei 87.22 was cloned and expressed in S. albus J1074 after chromosomal integration. The production of thaxtomins and nitro-tryptophan analogs were observed using LC-MS analysis. When culturing the engineered S. albus J1074 in the minimal medium TMDc, the yield of the most abundant and herbicidal analog, thaxtomin A, was 10 times higher than S. scabiei 87.22, and optimization of the medium resulted in the highest yield of thaxtomin analogs at about 222 mg/L. Further engineering of the thaxtomin biosynthetic gene cluster through gene deletion led to the production of multiple biosynthetic intermediates important to the chemical synthesis of new analogs. Additionally, the versatility of the thaxtomin biosynthetic system in S. albus J1074 was capitalized to produce one unnatural fluorinated analog 5-F-thaxtomin A, whose structure was elucidated by a combination of MS and 1D and 2D NMR analyses. Natural and unnatural thaxtomins demonstrated potent herbicidal activity in radish seedling assays. These results indicated that S. albus J1074 has the potential to produce thaxtomins and thereof with high yield, fostering their agricultural applications. IMPORTANCE Thaxtomins are agriculturally valuable herbicidal natural products but the productivity of native producers is limiting. Heterologous expression of thaxtomin gene cluster in S. albus J1074 resulted in the highest yield of thaxtomins ever reported, representing a significant leap forward in its wide agricultural use. Furthermore, current synthetic routes to thaxtomins and analogs are lengthy, and two thaxtomin biosynthetic intermediates produced at high yields in this work can provide precursors and building blocks to advanced synthetic routes. Importantly, the production of 5-F-thaxtomin A in engineered S. albus J1074 demonstrated a viable alternative to chemical methods in the synthesis of new thaxtomin analogs. Moreover, our work presents an attractive synthetic biology strategy to improve the supply of herbicidal thaxtomins, likely finding general applications in the discovery and production of many other bioactive natural products. Copyright © 2018 American Society for Microbiology.

Genetic Diversity of Namibian Pennisetum glaucum (L.) R. BR. (Pearl Millet) Landraces Analyzed by SSR and Morphological Markers.

PubMed

McBenedict, Billy; Chimwamurombe, Percy; Kwembeya, Ezekeil; Maggs-Kölling, Gillian

2016-01-01

Current Pennisetum glaucum (L.) R. BR. cultivars in Namibia have overall poor performance posing a threat to the nation's food security because this crop is staple for over 70% of the Namibian population. The crop suffers from undesirable production traits such as susceptibility to diseases, low yield, and prolonged reproductive cycle. This study aimed to understand the genetic diversity of the crop in Namibia by simple sequence repeats (SSRs) and morphology analysis. A total of 1441 genotypes were collected from the National Gene Bank representing all the Namibian landraces. A sample of 96 genotypes was further analyzed by SSR using Shannon-Wiener diversity index and revealed a value of 0.45 indicating low genetic diversity. Ordination using Principal Coordinate Analysis (PCoA) on SSR data confirmed clusters generated by UPGMA for the 96 P. glaucum accessions. UPGMA phenograms of 29 morphological characterized genotypes were generated for SSR and morphology data and the two trees revealed 78% resemblance. Lodging susceptibility, tillering attitude, spike density, fodder yield potential, early vigour, and spike shape were the phenotypic characters upon which some clusters were based in both datasets. It is recommended that efforts should be made to widen the current gene pool in Namibia.

Genetic Diversity of Namibian Pennisetum glaucum (L.) R. BR. (Pearl Millet) Landraces Analyzed by SSR and Morphological Markers

PubMed Central

McBenedict, Billy; Chimwamurombe, Percy; Kwembeya, Ezekeil; Maggs-Kölling, Gillian

2016-01-01

Current Pennisetum glaucum (L.) R. BR. cultivars in Namibia have overall poor performance posing a threat to the nation's food security because this crop is staple for over 70% of the Namibian population. The crop suffers from undesirable production traits such as susceptibility to diseases, low yield, and prolonged reproductive cycle. This study aimed to understand the genetic diversity of the crop in Namibia by simple sequence repeats (SSRs) and morphology analysis. A total of 1441 genotypes were collected from the National Gene Bank representing all the Namibian landraces. A sample of 96 genotypes was further analyzed by SSR using Shannon-Wiener diversity index and revealed a value of 0.45 indicating low genetic diversity. Ordination using Principal Coordinate Analysis (PCoA) on SSR data confirmed clusters generated by UPGMA for the 96 P. glaucum accessions. UPGMA phenograms of 29 morphological characterized genotypes were generated for SSR and morphology data and the two trees revealed 78% resemblance. Lodging susceptibility, tillering attitude, spike density, fodder yield potential, early vigour, and spike shape were the phenotypic characters upon which some clusters were based in both datasets. It is recommended that efforts should be made to widen the current gene pool in Namibia. PMID:27433479

Multivariate analysis to evaluate genetic groups and production traits of crossbred Holstein × Zebu cows.

PubMed

Fraga, Angelina Bossi; de Lima Silva, Fabiane; Hongyu, Kuang; Da Silva Santos, Darlim; Murphy, Thomas Wayne; Lopes, Fernando Brito

2016-03-01

The objective of this research was to try to unveil the relationship between production traits and genotypic proportions of crossbred dairy cattle using principal component analysis (PCA) and cluster analysis. The herd consists of crossbred animals of Holstein (H) and Zebu (Z) (Gir and Guzerat) in different genotypic proportions; the composition of which varies from 12.5 to 100.0 % of the genetic group H. For this study, 834 milk production records from 257 cows from the years 1997 to 2014 were analyzed. The animals were all managed at a farm located in northeastern Brazil. The variables in the PCA were total milk yield per lactation (MY), milk yield adjusted to 305 days (MY305), lactation length (LL), and proportion of H and Z breeding. This analysis reduced the size of the sample space from the original five variables to two principal components (PCs) that together explained 89.4 % of the total variation. MY, MY305, LL, and genotypic proportion of H all contributed positively to PC1. The genotypic proportion of Z contributed negatively, which established a contrast between H and Z. Further cluster analysis identified two distinct groups when considering production performance and genotype of the animals. The high-performance group was predominantly Holstein breeding, while the lower performing group consisted mostly of Zebu. Under the environmental and management conditions in which this research was conducted, the best performances for the traits considered were achieved from cows whose genotypic proportion was between 38.0 and 94.0 % Holstein breeding.

Support vector machine learning-based fMRI data group analysis.

PubMed

Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A

2007-07-15

To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.

Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins.

PubMed Central

Mocz, G.

1995-01-01

Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields approximately 73% matching for correctly predicted and correctly rejected residues with approximately 60% overall success rate for the correctly recognized ones in three folding states: alpha-helix, beta-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain approximately 95% of prediction results. hydrogen bonding and hydrophobicity induces do not yet enable clear clustering and prediction. PMID:7549882

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

PubMed

Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

PubMed Central

Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

Partially supervised speaker clustering.

PubMed

Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

2012-05-01

Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical model-based distance metrics, 2) our advocated use of the cosine distance metric yields consistent increases in the speaker clustering performance as compared to the commonly used euclidean distance metric, 3) our partially supervised speaker clustering concept and strategies significantly improve the speaker clustering performance over the baselines, and 4) our proposed LSDA algorithm further leads to state-of-the-art speaker clustering performance.

Application of Artificial Intelligence For Euler Solutions Clustering

NASA Astrophysics Data System (ADS)

Mikhailov, V.; Galdeano, A.; Diament, M.; Gvishiani, A.; Agayan, S.; Bogoutdinov, Sh.; Graeva, E.; Sailhac, P.

Results of Euler deconvolution strongly depend on the selection of viable solutions. Synthetic calculations using multiple causative sources show that Euler solutions clus- ter in the vicinity of causative bodies even when they do not group densely about perimeter of the bodies. We have developed a clustering technique to serve as a tool for selecting appropriate solutions. The method RODIN, employed in this study, is based on artificial intelligence and was originally designed for problems of classification of large data sets. It is based on a geometrical approach to study object concentration in a finite metric space of any dimension. The method uses a formal definition of cluster and includes free parameters that facilitate the search for clusters of given proper- ties. Test on synthetic and real data showed that the clustering technique successfully outlines causative bodies more accurate than other methods of discriminating Euler solutions. In complicated field cases such as the magnetic field in the Gulf of Saint Malo region (Brittany, France), the method provides geologically insightful solutions. Other advantages of the clustering method application are: - Clusters provide solutions associated with particular bodies or parts of bodies permitting the analysis of different clusters of Euler solutions separately. This may allow computation of average param- eters for individual causative bodies. - Those measurements of the anomalous field that yield clusters also form dense clusters themselves. The application of cluster- ing technique thus outlines areas where the influence of different causative sources is more prominent. This allows one to focus on areas for reinterpretation, using different window sizes, structural indices and so on.

Seizure clustering.

PubMed

Haut, Sheryl R

2006-02-01

Seizure clusters, also known as repetitive or serial seizures, occur commonly in epilepsy. Clustering implies that the occurrence of one seizure may influence the probability of a subsequent seizure; thus, the investigation of the clustering phenomenon yields insights into both specific mechanisms of seizure clustering and more general concepts of seizure occurrence. Seizure clustering has been defined clinically as a number of seizures per unit time and, statistically, as a deviation from a random distribution, or interseizure interval dependence. This review explores the pathophysiology, epidemiology, and clinical implications of clustering, as well as other periodic patterns of seizure occurrence. Risk factors for experiencing clusters and potential precipitants of clustering are also addressed.

Spatial distribution and cluster analysis of retail drug shop characteristics and antimalarial behaviors as reported by private medicine retailers in western Kenya: informing future interventions.

PubMed

Rusk, Andria; Highfield, Linda; Wilkerson, J Michael; Harrell, Melissa; Obala, Andrew; Amick, Benjamin

2016-02-19

Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions. Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the null hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The null hypothesis was rejected with p values of 0.05 or less. A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area. Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

⁹⁹mTc pyrene derivative complex causes double-strand breaks in dsDNA mainly through cluster-mediated indirect effect in aqueous solution.

PubMed

Chung, Wei-Ju; Cui, Yujia; Huang, Feng-Yun J; Tu, Tzu-Hui; Yang, Tzu-Sen; Lo, Jem-Mau; Chiang, Chi-Shiun; Hsu, Ian C

2014-01-01

Radiation therapy for cancer patients works by ionizing damage to nuclear DNA, primarily by creating double-strand breaks (DSB). A major shortcoming of traditional radiation therapy is the set of side effect associated with its long-range interaction with nearby tissues. Low-energy Auger electrons have the advantage of an extremely short effective range, minimizing damage to healthy tissue. Consequently, the isotope ⁹⁹mTc, an Auger electron source, is currently being studied for its beneficial potential in cancer treatment. We examined the dose effect of a pyrene derivative ⁹⁹mTc complex on plasmid DNA by using gel electrophoresis in both aqueous and methanol solutions. In aqueous solutions, the average yield per decay for double-strand breaks is 0.011±0.005 at low dose range, decreasing to 0.0005±0.0003 in the presence of 1 M dimethyl sulfoxide (DMSO). The apparent yield per decay for single-strand breaks (SSB) is 0.04±0.02, decreasing to approximately a fifth with 1 M DMSO. In methanol, the average yield per decay of DSB is 0.54±0.06 and drops to undetectable levels in 2 M DMSO. The SSB yield per decay is 7.2±0.2, changing to 0.4±0.2 in the presence of 2 M DMSO. The 95% decrease in the yield of DSB in DMSO indicates that the main mechanism for DSB formation is through indirect effect, possibly by cooperative binding or clustering of intercalators. In the presence of non-radioactive ligands at a near saturation concentration, where radioactive Tc compounds do not form large clusters, the yield of SSB stays the same while the yield of DSB decreases to the value in DMSO. DSBs generated by ⁹⁹mTc conjugated to intercalators are primarily caused by indirect effects through clustering.

Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial result.

PubMed

Fretheim, Atle; Soumerai, Stephen B; Zhang, Fang; Oxman, Andrew D; Ross-Degnan, Dennis

2013-08-01

We reanalyzed the data from a cluster-randomized controlled trial (C-RCT) of a quality improvement intervention for prescribing antihypertensive medication. Our objective was to estimate the effectiveness of the intervention using both interrupted time-series (ITS) and RCT methods, and to compare the findings. We first conducted an ITS analysis using data only from the intervention arm of the trial because our main objective was to compare the findings from an ITS analysis with the findings from the C-RCT. We used segmented regression methods to estimate changes in level or slope coincident with the intervention, controlling for baseline trend. We analyzed the C-RCT data using generalized estimating equations. Last, we estimated the intervention effect by including data from both study groups and by conducting a controlled ITS analysis of the difference between the slope and level changes in the intervention and control groups. The estimates of absolute change resulting from the intervention were ITS analysis, 11.5% (95% confidence interval [CI]: 9.5, 13.5); C-RCT, 9.0% (95% CI: 4.9, 13.1); and the controlled ITS analysis, 14.0% (95% CI: 8.6, 19.4). ITS analysis can provide an effect estimate that is concordant with the results of a cluster-randomized trial. A broader range of comparisons from other RCTs would help to determine whether these are generalizable results. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimizing R with SparkR on a commodity cluster for biomedical research.

PubMed

Sedlmayr, Martin; Würfl, Tobias; Maier, Christian; Häberle, Lothar; Fasching, Peter; Prokosch, Hans-Ulrich; Christoph, Jan

2016-12-01

Medical researchers are challenged today by the enormous amount of data collected in healthcare. Analysis methods such as genome-wide association studies (GWAS) are often computationally intensive and thus require enormous resources to be performed in a reasonable amount of time. While dedicated clusters and public clouds may deliver the desired performance, their use requires upfront financial efforts or anonymous data, which is often not possible for preliminary or occasional tasks. We explored the possibilities to build a private, flexible cluster for processing scripts in R based on commodity, non-dedicated hardware of our department. For this, a GWAS-calculation in R on a single desktop computer, a Message Passing Interface (MPI)-cluster, and a SparkR-cluster were compared with regards to the performance, scalability, quality, and simplicity. The original script had a projected runtime of three years on a single desktop computer. Optimizing the script in R already yielded a significant reduction in computing time (2 weeks). By using R-MPI and SparkR, we were able to parallelize the computation and reduce the time to less than three hours (2.6 h) on already available, standard office computers. While MPI is a proven approach in high-performance clusters, it requires rather static, dedicated nodes. SparkR and its Hadoop siblings allow for a dynamic, elastic environment with automated failure handling. SparkR also scales better with the number of nodes in the cluster than MPI due to optimized data communication. R is a popular environment for clinical data analysis. The new SparkR solution offers elastic resources and allows supporting big data analysis using R even on non-dedicated resources with minimal change to the original code. To unleash the full potential, additional efforts should be invested to customize and improve the algorithms, especially with regards to data distribution. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Genetic variation in Indian populations of Scirpophaga incertulas as revealed by RAPD-PCR analysis.

PubMed

Kumar, L S; Sawant, A S; Gupta, V S; Ranjekar, P K

2001-02-01

Scirpophaga incertulas, commonly referred to as yellow stem borer, is a predominant pest of rice causing serious losses in its yield. Genetic variation among populations of Scirpophaga incertulas collected from 28 hotspot locations in India was examined using the randomly amplified polymorphic DNA-polymerase chain reaction (RAPD-PCR). In all, 32 primers were used and 354 amplification products were observed. No RAPD-PCR bands diagnostic to the pest population from any specific region were identified. Cluster analysis using UPGMA showed that, with the exception of the pest population from Pattambi, all the populations cluster as one group with GD values in the range of 6-22%, suggesting that gene flow between populations is independent of geographic distance and appears to be unrestricted. The relatively high GD value of 48% exhibited by the pest population from Pattambi was the only exception.

Study of the cluster structure of10Be and16C neutron-rich isotopes by means of intermediate energies breakup reactions

NASA Astrophysics Data System (ADS)

Dell'Aquila, D.; Acosta, L.; Auditore, L.; Cardella, G.; De Filippo, E.; De Luca, S.; Francalanza, L.; Gnoffo, B.; Lanzalone, G.; Lombardo, I.; Martorana, N. S.; Pagano, A.; Pagano, E. V.; Papa, M.; Pirrone, S.; Politi, G.; Quattrocchi, L.; Rizzo, F.; Rosato, E.; Russotto, P.; Trifirò, A.; Trimarchi, M.; Verde, G.; Vigilante, M.

2017-06-01

We describe the results of a new experiment aimed to investigate the possible existence of cluster structures in10Be and16C isotopes. They have been investigated at the FRIBs facility of INFN-LNS by means of an invariant mass analysis on correlated projectile breakup fragments carried out with the CHIMERA 4π detector. From the analysis of the6He+4He channel we found evidence of a new state in10Be at 13.5MeV excitation energy. Concerning16C, we investigated6He+10Be correlated fragments and we found a non-vanishing yield at about 20.5MeV in the corresponding excitation energy spectrum. Finally, we describe few details of a new experiment performed at the FRIBs facility where the CHIMERA detector was coupled to the FARCOS hodoscope, with the aim to improve the presently obtained results.

DNA damage induced by the direct effect of radiation

NASA Astrophysics Data System (ADS)

Yokoya, A.; Shikazono, N.; Fujii, K.; Urushibara, A.; Akamatsu, K.; Watanabe, R.

2008-10-01

We have studied the nature of DNA damage induced by the direct effect of radiation. The yields of single- (SSB) and double-strand breaks (DSB), base lesions and clustered damage were measured using the agarose gel electrophoresis method after exposing to various kinds of radiations to a simple model DNA molecule, fully hydrated closed-circular plasmid DNA (pUC18). The yield of SSB does not show significant dependence on linear energy transfer (LET) values. On the other hand, the yields of base lesions revealed by enzymatic probes, endonuclease III (Nth) and formamidopyrimidine DNA glycosylase (Fpg), which excise base lesions and leave a nick at the damage site, strongly depend on LET values. Soft X-ray photon (150 kVp) irradiation gives a maximum yield of the base lesions detected by the enzymatic probes as SSB and clustered damage, which is composed of one base lesion and proximate other base lesions or SSBs. The clustered damage is visualized as an enzymatically induced DSB. The yields of the enzymatically additional damages strikingly decrease with increasing levels of LET. These results suggest that in higher LET regions, the repair enzymes used as probes are compromised because of the dense damage clustering. The studies using simple plasmid DNA as a irradiation sample, however, have a technical difficulty to detect multiple SSBs in a plasmid DNA. To detect the additional SSBs induced in opposite strand of the first SSB, we have also developed a novel technique of DNA-denaturation assay. This allows us to detect multiply induced SSBs in both strand of DNA, but not induced DSB.

Vocal Affect Recognition and Psychopathy: Converging Findings Across Traditional and Cluster Analytic Approaches to Assessing the Construct

PubMed Central

Bagley, Amy D.; Abramowitz, Carolyn S.; Kosson, David S.

2010-01-01

Deficits in emotion processing have been widely reported to be central to psychopathy. However, few prior studies have examined vocal affect recognition in psychopaths, and these studies suffer from significant methodological limitations. Moreover, prior studies have yielded conflicting findings regarding the specificity of psychopaths’ affect recognition deficits. This study examined vocal affect recognition in 107 male inmates under conditions requiring isolated prosodic vs. semantic analysis of affective cues and compared subgroups of offenders identified via cluster analysis on vocal affect recognition. Psychopaths demonstrated deficits in vocal affect recognition under conditions requiring use of semantic cues and conditions requiring use of prosodic cues. Moreover, both primary and secondary psychopaths exhibited relatively similar emotional deficits in the semantic analysis condition compared to nonpsychopathic control participants. This study demonstrates that psychopaths’ vocal affect recognition deficits are not due to methodological limitations of previous studies and provides preliminary evidence that primary and secondary psychopaths exhibit generally similar deficits in vocal affect recognition. PMID:19413412

Dispersed or Clustered Housing for Adults with Intellectual Disability: A Systematic Review

ERIC Educational Resources Information Center

Mansell, Jim; Beadle-Brown, Julie

2009-01-01

Background: The purpose of this review was to evaluate the available research on the quality and costs of dispersed community-based housing when compared with clustered housing. Methods: Searches against specified criteria yielded 19 papers based on 10 studies presenting data comparing dispersed housing with some kind of clustered housing (village…

Pupil Clustering in English Secondary Schools: One Pattern or Several?

ERIC Educational Resources Information Center

Gorard, Stephen; Cheng, Shou Chen

2011-01-01

Previous international work has shown that clustering pupils with similar characteristics in particular schools yields no clear academic benefit, and can be disadvantageous both socially and personally. Understanding how and why this clustering happens, and how it may be reduced, is therefore important for policy. Yet previous work has tended to…

A model-based cluster analysis of social experiences in clinically anxious youth: links to emotional functioning.

PubMed

Suveg, Cynthia; Jacob, Marni L; Whitehead, Monica; Jones, Anna; Kingery, Julie Newman

2014-01-01

Social difficulties are commonly associated with anxiety disorders in youth, yet are not well specified in the literature. The aim of this study was to identify patterns of social experiences in clinically anxious children and examine the associations with indices of emotional functioning. A model-based cluster analysis was conducted on parent-, teacher-, and child-reports of social experiences with 64 children, ages 7-12 years (M = 8.86 years, SD = 1.59 years; 60.3% boys; 85.7% Caucasian) with a primary diagnosis of separation anxiety disorder, social phobia, and/or generalized anxiety disorder. Follow-up analyses examined cluster differences on indices of emotional functioning. Findings yielded three clusters of social experiences that were unrelated to diagnosis: (1) Unaware Children (elevated scores on parent- and teacher-reports of social difficulties but relatively low scores on child-reports, n = 12), (2) Average Functioning (relatively average scores across all informants, n = 44), and (3) Victimized and Lonely (elevated child-reports of overt and relational victimization and loneliness and relatively low scores on parent- and teacher-reports of social difficulties, n = 8). Youth in the Unaware Children cluster were rated as more emotionally dysregulated by teachers and had a greater number of diagnoses than youth in the Average Functioning group. In contrast, the Victimized and Lonely group self-reported greater frequency of negative affect and reluctance to share emotional experiences than the Average Functioning cluster. Overall, this study demonstrates that social maladjustment in clinically anxious children can manifest in a variety of ways and assessment should include multiple informants and methods.

[Does the Youth Psychopathic Traits Inventory (YPI) identify a clinically relevant subgroup among young offenders?].

PubMed

Mingers, Daniel; Köhler, Denis; Huchzermeier, Christian; Hinrichs, Günter

2017-01-01

Does the Youth Psychopathic Traits Inventory identify one or more high-risk subgroups among young offenders? Which recommendations for possible courses of action can be derived for individual clinical or forensic cases? Method: Model-based cluster analysis (Raftery, 1995) was conducted on a sample of young offenders (N = 445, age 14–22 years, M = 18.5, SD = 1.65). The resulting model was then tested for differences between clusters with relevant context variables of psychopathy. The variables included measures of intelligence, social competence, drug use, and antisocial behavior. Results: Three clusters were found (Low Trait, Impulsive/Irresponsible, Psychopathy) that differ highly significantly concerning YPI scores and the variables mentioned above. The YPI Scores Δ Low = 4.28 (Low Trait – Impulsive/Irresponsible) and Δ High = 6.86 (Impulsive/Irresponsible – Psychopathy) were determined to be thresholds between the clusters. The allocation of a person to be assessed within the calculated clusters allows for an orientation of consequent tests beyond the diagnosis of psychopathy. We conclude that the YPI is a valuable instrument for the assessment of young offenders, as it yields clinically and forensically relevant information concerning the cause and expected development of psychopathological behavior.

Use of Conserved Randomly Amplified Polymorphic DNA (RAPD) Fragments and RAPD Pattern for Characterization of Lactobacillus fermentum in Ghanaian Fermented Maize Dough

PubMed Central

Hayford, Alice E.; Petersen, Anne; Vogensen, Finn K.; Jakobsen, Mogens

1999-01-01

The present work describes the use of randomly amplified polymorphic DNA (RAPD) for the characterization of 172 dominant Lactobacillus isolates from present and previous studies of Ghanaian maize fermentation. Heterofermentative lactobacilli dominate the fermentation flora, since approximately 85% of the isolates belong to this group. Cluster analysis of the RAPD profiles obtained showed the presence of two main clusters. Cluster 1 included Lactobacillus fermentum, whereas cluster 2 comprised the remaining Lactobacillus spp. The two distinct clusters emerged at the similarity level of <50%. All isolates in cluster 1 showed similarity in their RAPD profile to the reference strains of L. fermentum included in the study. These isolates, yielding two distinct bands of approximately 695 and 773 bp with the primers used, were divided into four subclusters, indicating that several strains are involved in the fermentation and remain dominant throughout the process. The two distinct RAPD fragments were cloned, sequenced, and used as probes in Southern hybridization experiments. With one exception, Lactobacillus reuteri LMG 13045, the probes hybridized only to fragments of different sizes in EcoRI-digested chromosomal DNA of L. fermentum strains, thus indicating the specificity of the probes and variation within the L. fermentum isolates. PMID:10388723

Strain-Level Diversity of Secondary Metabolism in Streptomyces albus

PubMed Central

Seipke, Ryan F.

2015-01-01

Streptomyces spp. are robust producers of medicinally-, industrially- and agriculturally-important small molecules. Increased resistance to antibacterial agents and the lack of new antibiotics in the pipeline have led to a renaissance in natural product discovery. This endeavor has benefited from inexpensive high quality DNA sequencing technology, which has generated more than 140 genome sequences for taxonomic type strains and environmental Streptomyces spp. isolates. Many of the sequenced streptomycetes belong to the same species. For instance, Streptomyces albus has been isolated from diverse environmental niches and seven strains have been sequenced, consequently this species has been sequenced more than any other streptomycete, allowing valuable analyses of strain-level diversity in secondary metabolism. Bioinformatics analyses identified a total of 48 unique biosynthetic gene clusters harboured by Streptomyces albus strains. Eighteen of these gene clusters specify the core secondary metabolome of the species. Fourteen of the gene clusters are contained by one or more strain and are considered auxiliary, while 16 of the gene clusters encode the production of putative strain-specific secondary metabolites. Analysis of Streptomyces albus strains suggests that each strain of a Streptomyces species likely harbours at least one strain-specific biosynthetic gene cluster. Importantly, this implies that deep sequencing of a species will not exhaust gene cluster diversity and will continue to yield novelty. PMID:25635820

“Ligands-with-Benefits”: Naphthalene-Substituted Schiff Bases Yielding New Ni II Metal Clusters with Ferromagnetic and Emissive Properties and Undergoing Exciting Transformations

DOE PAGES

Perlepe, Panagiota S.; Cunha-Silva, Luis; Gagnon, Kevin J.; ...

2016-01-20

The initial employment of the fluorescent bridging ligand N-naphthalidene-2-amino-5-chlorobenzoic acid (nacbH 2) in metal cluster chemistry has led to new Ni 12 (1) and Ni 5 (2) clusters with wheel-like and molecular-chain topologies, respectively. The doubly-deprotonated nacb 2- ligands were found to adopt four different coordination modes within 1 and 2. The nature of the ligand has also allowed unexpected organic transformations to occur and ferromagnetic and emission behaviors to emerge. The combined work presented here demonstrates the ability of some "ligands-with-benefits" to yield beautiful structures with exciting topologies and interesting physicochemical properties.

“Ligands-with-Benefits”: Naphthalene-Substituted Schiff Bases Yielding New Ni II Metal Clusters with Ferromagnetic and Emissive Properties and Undergoing Exciting Transformations

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

Perlepe, Panagiota S.; Cunha-Silva, Luis; Gagnon, Kevin J.

The initial employment of the fluorescent bridging ligand N-naphthalidene-2-amino-5-chlorobenzoic acid (nacbH 2) in metal cluster chemistry has led to new Ni 12 (1) and Ni 5 (2) clusters with wheel-like and molecular-chain topologies, respectively. The doubly-deprotonated nacb 2- ligands were found to adopt four different coordination modes within 1 and 2. The nature of the ligand has also allowed unexpected organic transformations to occur and ferromagnetic and emission behaviors to emerge. The combined work presented here demonstrates the ability of some "ligands-with-benefits" to yield beautiful structures with exciting topologies and interesting physicochemical properties.

Towards a methodology for cluster searching to provide conceptual and contextual "richness" for systematic reviews of complex interventions: case study (CLUSTER).

PubMed

Booth, Andrew; Harris, Janet; Croot, Elizabeth; Springett, Jane; Campbell, Fiona; Wilkins, Emma

2013-09-28

Systematic review methodologies can be harnessed to help researchers to understand and explain how complex interventions may work. Typically, when reviewing complex interventions, a review team will seek to understand the theories that underpin an intervention and the specific context for that intervention. A single published report from a research project does not typically contain this required level of detail. A review team may find it more useful to examine a "study cluster"; a group of related papers that explore and explain various features of a single project and thus supply necessary detail relating to theory and/or context.We sought to conduct a preliminary investigation, from a single case study review, of techniques required to identify a cluster of related research reports, to document the yield from such methods, and to outline a systematic methodology for cluster searching. In a systematic review of community engagement we identified a relevant project - the Gay Men's Task Force. From a single "key pearl citation" we conducted a series of related searches to find contextually or theoretically proximate documents. We followed up Citations, traced Lead authors, identified Unpublished materials, searched Google Scholar, tracked Theories, undertook ancestry searching for Early examples and followed up Related projects (embodied in the CLUSTER mnemonic). Our structured, formalised procedure for cluster searching identified useful reports that are not typically identified from topic-based searches on bibliographic databases. Items previously rejected by an initial sift were subsequently found to inform our understanding of underpinning theory (for example Diffusion of Innovations Theory), context or both. Relevant material included book chapters, a Web-based process evaluation, and peer reviewed reports of projects sharing a common ancestry. We used these reports to understand the context for the intervention and to explore explanations for its relative lack of success. Additional data helped us to challenge simplistic assumptions on the homogeneity of the target population. A single case study suggests the potential utility of cluster searching, particularly for reviews that depend on an understanding of context, e.g. realist synthesis. The methodology is transparent, explicit and reproducible. There is no reason to believe that cluster searching is not generalizable to other review topics. Further research should examine the contribution of the methodology beyond improved yield, to the final synthesis and interpretation, possibly by utilizing qualitative sensitivity analysis.

Methane Production in Dairy Cows Correlates with Rumen Methanogenic and Bacterial Community Structure.

PubMed

Danielsson, Rebecca; Dicksved, Johan; Sun, Li; Gonda, Horacio; Müller, Bettina; Schnürer, Anna; Bertilsson, Jan

2017-01-01

Methane (CH 4 ) is produced as an end product from feed fermentation in the rumen. Yield of CH 4 varies between individuals despite identical feeding conditions. To get a better understanding of factors behind the individual variation, 73 dairy cows given the same feed but differing in CH 4 emissions were investigated with focus on fiber digestion, fermentation end products and bacterial and archaeal composition. In total 21 cows (12 Holstein, 9 Swedish Red) identified as persistent low, medium or high CH 4 emitters over a 3 month period were furthermore chosen for analysis of microbial community structure in rumen fluid. This was assessed by sequencing the V4 region of 16S rRNA gene and by quantitative qPCR of targeted Methanobrevibacter groups. The results showed a positive correlation between low CH 4 emitters and higher abundance of Methanobrevibacter ruminantium clade. Principal coordinate analysis (PCoA) on operational taxonomic unit (OTU) level of bacteria showed two distinct clusters ( P < 0.01) that were related to CH 4 production. One cluster was associated with low CH 4 production (referred to as cluster L) whereas the other cluster was associated with high CH 4 production (cluster H) and the medium emitters occurred in both clusters. The differences between clusters were primarily linked to differential abundances of certain OTUs belonging to Prevotella . Moreover, several OTUs belonging to the family Succinivibrionaceae were dominant in samples belonging to cluster L. Fermentation pattern of volatile fatty acids showed that proportion of propionate was higher in cluster L, while proportion of butyrate was higher in cluster H. No difference was found in milk production or organic matter digestibility between cows. Cows in cluster L had lower CH 4 /kg energy corrected milk (ECM) compared to cows in cluster H, 8.3 compared to 9.7 g CH 4 /kg ECM, showing that low CH 4 cows utilized the feed more efficient for milk production which might indicate a more efficient microbial population or host genetic differences that is reflected in bacterial and archaeal (or methanogens) populations.

Methane Production in Dairy Cows Correlates with Rumen Methanogenic and Bacterial Community Structure

PubMed Central

Danielsson, Rebecca; Dicksved, Johan; Sun, Li; Gonda, Horacio; Müller, Bettina; Schnürer, Anna; Bertilsson, Jan

2017-01-01

Methane (CH4) is produced as an end product from feed fermentation in the rumen. Yield of CH4 varies between individuals despite identical feeding conditions. To get a better understanding of factors behind the individual variation, 73 dairy cows given the same feed but differing in CH4 emissions were investigated with focus on fiber digestion, fermentation end products and bacterial and archaeal composition. In total 21 cows (12 Holstein, 9 Swedish Red) identified as persistent low, medium or high CH4 emitters over a 3 month period were furthermore chosen for analysis of microbial community structure in rumen fluid. This was assessed by sequencing the V4 region of 16S rRNA gene and by quantitative qPCR of targeted Methanobrevibacter groups. The results showed a positive correlation between low CH4 emitters and higher abundance of Methanobrevibacter ruminantium clade. Principal coordinate analysis (PCoA) on operational taxonomic unit (OTU) level of bacteria showed two distinct clusters (P < 0.01) that were related to CH4 production. One cluster was associated with low CH4 production (referred to as cluster L) whereas the other cluster was associated with high CH4 production (cluster H) and the medium emitters occurred in both clusters. The differences between clusters were primarily linked to differential abundances of certain OTUs belonging to Prevotella. Moreover, several OTUs belonging to the family Succinivibrionaceae were dominant in samples belonging to cluster L. Fermentation pattern of volatile fatty acids showed that proportion of propionate was higher in cluster L, while proportion of butyrate was higher in cluster H. No difference was found in milk production or organic matter digestibility between cows. Cows in cluster L had lower CH4/kg energy corrected milk (ECM) compared to cows in cluster H, 8.3 compared to 9.7 g CH4/kg ECM, showing that low CH4 cows utilized the feed more efficient for milk production which might indicate a more efficient microbial population or host genetic differences that is reflected in bacterial and archaeal (or methanogens) populations. PMID:28261182

Genetic divergence in the common bean (Phaseolus vulgaris L.) in the Cerrado-Pantanal ecotone.

PubMed

da Silva, F A; Corrêa, A M; Teodoro, P E; Lopes, K V; Corrêa, C C G

2017-03-30

Evaluating genetic diversity among genotypes is important for providing parameters for the identification of superior genotypes, because the choice of parents that form segregating populations is crucial. Our objectives were to i) evaluate agronomic performance; ii) compare clustering methods; iii) ascertain the relative contributions of the variables evaluated; and iv) identify the most promising hybrids to produce superior segregating populations. The trial was conducted in 2015 at the State University of Mato Grosso do Sul, Brazil. We used a randomized block design with three replications, and recorded the days to emergence, days to flowering, days to maturity, plant height, number of branches, number of pods, number of seeds per pod, weight of 100 grains, and productivity. The genetic diversity of the genotypes was determined by cluster analysis using two dissimilarity measures: the Euclidean distance and the standardized mean Mahalanobis distance using the Ward hierarchical method. The genotypes 'CNFC 10762', 'IAC Dawn', and 'BRS Style' had the highest grain yields, and clusters that were based on the Euclidean distance differed from those based on the Mahalanobis distance, the second being more precise. The yield grain character has greater relevance to the dispute. Hybrids with a high heterotic effect can be obtained by crossing 'IAC Alvorada' with 'CNFC 10762', 'IAC Alvorada' with 'CNFC 10764', and 'BRS Style' with 'IAC Alvorada'.

Molecular analysis of Hurler syndrome in Druze and Muslim Arab patients in Israel: Multiple allelic mutations of the IDUA gene in a small geographic area

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

Bach, G.; Moskowitz, S.M.; Tieu, P.T.

1993-08-01

The mutations underlying Hurler syndrome (mucopolysaccharidosis IH) in Druze and Muslim Israeli Arab patients have been characterized. Four alleles were identified, using a combination of (a) PCR amplification of reverse-transcribed RNA or genomic DNA segments, (b) cycle sequencing of PCR products, and (c) restriction-enzyme analysis. One allele has two amino acid substitutions, Gly[sub 409][yields]Arg in exon 9 and Ter[yields]Cys in exon 14. The other three alleles have mutations in exon 2 (Tyr[sub 64][yields]Ter), exon 7 (Gln[sub 310][yields]Ter), or exon 8 (Thr[sub 366][yields]Pro). Transfection of mutagenized cDNAs into Cos-1 cells showed that two missense mutations, Thr[sub 366][yields]Pro and Ter[yields]Cys, permitted themore » expression of only trace amounts of [alpha]-L-iduronidase activity, whereas Gly[sub 409][yields]Arg permitted the expression of 60% as much enzyme as did the normal cDNA. The nonsense mutations were associated with abnormalities of RNA processing: (1) both a very low level of mRNA and skipping of exon 2 for Tyr[sub 64][yields]Ter and (2) utilization of a cryptic splice site for Gln[sub 310][yields]Ter. In all instances, the probands were found homozygous, and the parents heterozygous, for the mutant alleles, as anticipated from the consanguinity in each family. The two-mutation allele was identified in a family from Gaza; the other three alleles were found in seven families, five of them Druze, residing in a very small area of northern Israel. Since such clustering suggests a classic founder effect, the presence of three mutant alleles of the IDUA gene was unexpected. 28 refs., 4 figs., 3 tabs.« less

Cluster analysis of dynamic contrast enhanced MRI reveals tumor subregions related to locoregional relapse for cervical cancer patients.

PubMed

Torheim, Turid; Groendahl, Aurora R; Andersen, Erlend K F; Lyng, Heidi; Malinen, Eirik; Kvaal, Knut; Futsaether, Cecilia M

2016-11-01

Solid tumors are known to be spatially heterogeneous. Detection of treatment-resistant tumor regions can improve clinical outcome, by enabling implementation of strategies targeting such regions. In this study, K-means clustering was used to group voxels in dynamic contrast enhanced magnetic resonance images (DCE-MRI) of cervical cancers. The aim was to identify clusters reflecting treatment resistance that could be used for targeted radiotherapy with a dose-painting approach. Eighty-one patients with locally advanced cervical cancer underwent DCE-MRI prior to chemoradiotherapy. The resulting image time series were fitted to two pharmacokinetic models, the Tofts model (yielding parameters K trans and ν e ) and the Brix model (A Brix , k ep and k el ). K-means clustering was used to group similar voxels based on either the pharmacokinetic parameter maps or the relative signal increase (RSI) time series. The associations between voxel clusters and treatment outcome (measured as locoregional control) were evaluated using the volume fraction or the spatial distribution of each cluster. One voxel cluster based on the RSI time series was significantly related to locoregional control (adjusted p-value 0.048). This cluster consisted of low-enhancing voxels. We found that tumors with poor prognosis had this RSI-based cluster gathered into few patches, making this cluster a potential candidate for targeted radiotherapy. None of the voxels clusters based on Tofts or Brix parameter maps were significantly related to treatment outcome. We identified one group of tumor voxels significantly associated with locoregional relapse that could potentially be used for dose painting. This tumor voxel cluster was identified using the raw MRI time series rather than the pharmacokinetic maps.

Hierarchical clustering of HPV genotype patterns in the ASCUS-LSIL triage study

PubMed Central

Wentzensen, Nicolas; Wilson, Lauren E.; Wheeler, Cosette M.; Carreon, Joseph D.; Gravitt, Patti E.; Schiffman, Mark; Castle, Philip E.

2010-01-01

Anogenital cancers are associated with about 13 carcinogenic HPV types in a broader group that cause cervical intraepithelial neoplasia (CIN). Multiple concurrent cervical HPV infections are common which complicate the attribution of HPV types to different grades of CIN. Here we report the analysis of HPV genotype patterns in the ASCUS-LSIL triage study using unsupervised hierarchical clustering. Women who underwent colposcopy at baseline (n = 2780) were grouped into 20 disease categories based on histology and cytology. Disease groups and HPV genotypes were clustered using complete linkage. Risk of 2-year cumulative CIN3+, viral load, colposcopic impression, and age were compared between disease groups and major clusters. Hierarchical clustering yielded four major disease clusters: Cluster 1 included all CIN3 histology with abnormal cytology; Cluster 2 included CIN3 histology with normal cytology and combinations with either CIN2 or high-grade squamous intraepithelial lesion (HSIL) cytology; Cluster 3 included older women with normal or low grade histology/cytology and low viral load; Cluster 4 included younger women with low grade histology/cytology, multiple infections, and the highest viral load. Three major groups of HPV genotypes were identified: Group 1 included only HPV16; Group 2 included nine carcinogenic types plus non-carcinogenic HPV53 and HPV66; and Group 3 included non-carcinogenic types plus carcinogenic HPV33 and HPV45. Clustering results suggested that colposcopy missed a prevalent precancer in many women with no biopsy/normal histology and HSIL. This result was confirmed by an elevated 2-year risk of CIN3+ in these groups. Our novel approach to study multiple genotype infections in cervical disease using unsupervised hierarchical clustering can address complex genotype distributions on a population level. PMID:20959485

The Projected Dark and Baryonic Ellipsoidal Structure of 20 CLASH Galaxy Clusters

NASA Astrophysics Data System (ADS)

Umetsu, Keiichi; Sereno, Mauro; Tam, Sut-Ieng; Chiu, I.-Non; Fan, Zuhui; Ettori, Stefano; Gruen, Daniel; Okumura, Teppei; Medezinski, Elinor; Donahue, Megan; Meneghetti, Massimo; Frye, Brenda; Koekemoer, Anton; Broadhurst, Tom; Zitrin, Adi; Balestra, Italo; Benítez, Narciso; Higuchi, Yuichi; Melchior, Peter; Mercurio, Amata; Merten, Julian; Molino, Alberto; Nonino, Mario; Postman, Marc; Rosati, Piero; Sayers, Jack; Seitz, Stella

2018-06-01

We reconstruct the two-dimensional (2D) matter distributions in 20 high-mass galaxy clusters selected from the CLASH survey by using the new approach of performing a joint weak gravitational lensing analysis of 2D shear and azimuthally averaged magnification measurements. This combination allows for a complete analysis of the field, effectively breaking the mass-sheet degeneracy. In a Bayesian framework, we simultaneously constrain the mass profile and morphology of each individual cluster, assuming an elliptical Navarro–Frenk–White halo characterized by the mass, concentration, projected axis ratio, and position angle (PA) of the projected major axis. We find that spherical mass estimates of the clusters from azimuthally averaged weak-lensing measurements in previous work are in excellent agreement with our results from a full 2D analysis. Combining all 20 clusters in our sample, we detect the elliptical shape of weak-lensing halos at the 5σ significance level within a scale of 2 {Mpc} {h}-1. The median projected axis ratio is 0.67 ± 0.07 at a virial mass of {M}vir}=(15.2+/- 2.8)× {10}14 {M}ȯ , which is in agreement with theoretical predictions from recent numerical simulations of the standard collisionless cold dark matter model. We also study misalignment statistics of the brightest cluster galaxy, X-ray, thermal Sunyaev–Zel’dovich effect, and strong-lensing morphologies with respect to the weak-lensing signal. Among the three baryonic tracers studied here, we find that the X-ray morphology is best aligned with the weak-lensing mass distribution, with a median misalignment angle of | {{Δ }}{PA}| =21^\\circ +/- 7^\\circ . We also conduct a stacked quadrupole shear analysis of the 20 clusters assuming that the X-ray major axis is aligned with that of the projected mass distribution. This yields a consistent axis ratio of 0.67 ± 0.10, suggesting again a tight alignment between the intracluster gas and dark matter. Based in part on data collected at the Subaru Telescope, which is operated by the National Astronomical Society of Japan.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms I: Revisiting Cluster-Based Inferences.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Sathian, K

2018-02-01

In a recent study, Eklund et al. employed resting-state functional magnetic resonance imaging data as a surrogate for null functional magnetic resonance imaging (fMRI) datasets and posited that cluster-wise family-wise error (FWE) rate-corrected inferences made by using parametric statistical methods in fMRI studies over the past two decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; this was principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggested otherwise. Here, we show that accounting for non-Gaussian signal components such as those arising from resting-state neural activity as well as physiological responses and motion artifacts in the null fMRI datasets yields first- and second-level general linear model analysis residuals with nearly uniform and Gaussian sACF. Further comparison with nonparametric permutation tests indicates that cluster-based FWE corrected inferences made with Gaussian spatial noise approximations are valid.

New experimental investigation of cluster structures in 10 Be and 16 C neutron-rich nuclei

NASA Astrophysics Data System (ADS)

Dell'Aquila, L.; Acosta, D.; Auditore, L.; Cardella, G.; De Filippo, E.; De Luca, S.; Francalanza, L.; Gnoffo, B.; Lanzalone, G.; Lombardo, I.; Martorana, N. S.; Norella, S.; Pagano, A.; Pagano, E. V.; Papa, M.; Pirrone, S.; Politi, G.; Quattrocchi, L.; Rizzo, F.; Russotto, P.; Trifirò, A.; Trimarchi, M.; Verde, G.; Vigilante, M.

2017-11-01

The existence of cluster structures in ^{10} Be and ^{16} C neutron-rich isotopes is investigated via projectile break-up reactions induced on polyethylene (CH _2 target. We used a fragmentation beam constituted by 55MeV/u ^{10} Be and 49MeV/u ^{16} C beams provided by the FRIBs facility at INFN-LNS. Invariant mass spectra of 4{He}+ 6 He and 6{He} + ^{10} Be breakup fragments are reconstructed by means of the CHIMERA 4π detector to investigate the presence of excited states of projectile nuclei characterized by cluster structure. In the first case, we suggest the presence of a new state in ^{10} Be at 13.5MeV. A non-vanishing yield corresponding to 20.6MeV excitation energy of ^{16} C was observed in the 6{He} + ^{10} Be cluster decay channel. To improve the results of the present analysis, a new experiment has been performed recently, taking advantage of the coupling of CHIMERA and FARCOS. In the paper we describe the data reduction process of the new experiment together with preliminary results.

Shear-driven dynamic clusters in a colloidal glass

NASA Astrophysics Data System (ADS)

Eisenmann, Christoph; Kim, Chanjoong; Mattsson, Johan; Weitz, David

2007-03-01

We investigate the effect of shear applied to a colloidal glass on a microscopic level using a shear device that can be mounted on top of a confocal microscope. We find that the glass yields at a critical strain of about 10%, independently of the shear rate. Surprisingly, the yielding is accompanied by an increase of cooperative particle movements and a formation of dynamic clusters which is in contrast to the normal glass transition where one typically finds heterogeneity increasing whilst moving towards the glass transition.

THE MASS-RICHNESS RELATION OF MaxBCG CLUSTERS FROM QUASAR LENSING MAGNIFICATION USING VARIABILITY

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

Bauer, Anne H.; Baltay, Charles; Ellman, Nancy

2012-04-10

Accurate measurement of galaxy cluster masses is an essential component not only in studies of cluster physics but also for probes of cosmology. However, different mass measurement techniques frequently yield discrepant results. The Sloan Digital Sky Survey MaxBCG catalog's mass-richness relation has previously been constrained using weak lensing shear, Sunyaev-Zeldovich (SZ), and X-ray measurements. The mass normalization of the clusters as measured by weak lensing shear is {approx}>25% higher than that measured using SZ and X-ray methods, a difference much larger than the stated measurement errors in the analyses. We constrain the mass-richness relation of the MaxBCG galaxy cluster catalogmore » by measuring the gravitational lensing magnification of type I quasars in the background of the clusters. The magnification is determined using the quasars' variability and the correlation between quasars' variability amplitude and intrinsic luminosity. The mass-richness relation determined through magnification is in agreement with that measured using shear, confirming that the lensing strength of the clusters implies a high mass normalization and that the discrepancy with other methods is not due to a shear-related systematic measurement error. We study the dependence of the measured mass normalization on the cluster halo orientation. As expected, line-of-sight clusters yield a higher normalization; however, this minority of haloes does not significantly bias the average mass-richness relation of the catalog.« less

A cluster pattern algorithm for the analysis of multiparametric cell assays.

PubMed

Kaufman, Menachem; Bloch, David; Zurgil, Naomi; Shafran, Yana; Deutsch, Mordechai

2005-09-01

The issue of multiparametric analysis of complex single cell assays of both static and flow cytometry (SC and FC, respectively) has become common in recent years. In such assays, the analysis of changes, applying common statistical parameters and tests, often fails to detect significant differences between the investigated samples. The cluster pattern similarity (CPS) measure between two sets of gated clusters is based on computing the difference between their density distribution functions' set points. The CPS was applied for the discrimination between two observations in a four-dimensional parameter space. The similarity coefficient (r) ranges between 0 (perfect similarity) to 1 (dissimilar). Three CPS validation tests were carried out: on the same stock samples of fluorescent beads, yielding very low r's (0, 0.066); and on two cell models: mitogenic stimulation of peripheral blood mononuclear cells (PBMC), and apoptosis induction in Jurkat T cell line by H2O2. In both latter cases, r indicated similarity (r < 0.23) within the same group, and dissimilarity (r > 0.48) otherwise. This classification and algorithm approach offers a measure of similarity between samples. It relies on the multidimensional pattern of the sample parameters. The algorithm compensates for environmental drifts in this apparatus and assay; it also may be applied to more than four dimensions.

Coupled protein-ligand dynamics in truncated hemoglobin N from atomistic simulations and transition networks.

PubMed

Cazade, Pierre-André; Berezovska, Ganna; Meuwly, Markus

2015-05-01

The nature of ligand motion in proteins is difficult to characterize directly using experiment. Specifically, it is unclear to what degree these motions are coupled. All-atom simulations are used to sample ligand motion in truncated Hemoglobin N. A transition network analysis including ligand- and protein-degrees of freedom is used to analyze the microscopic dynamics. Clustering of two different subsets of MD trajectories highlights the importance of a diverse and exhaustive description to define the macrostates for a ligand-migration network. Monte Carlo simulations on the transition matrices from one particular clustering are able to faithfully capture the atomistic simulations. Contrary to clustering by ligand positions only, including a protein degree of freedom yields considerably improved coarse grained dynamics. Analysis with and without imposing detailed balance agree closely which suggests that the underlying atomistic simulations are converged with respect to sampling transitions between neighboring sites. Protein and ligand dynamics are not independent from each other and ligand migration through globular proteins is not passive diffusion. Transition network analysis is a powerful tool to analyze and characterize the microscopic dynamics in complex systems. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Cross-genera transferability of rice and finger millet genomic SSRs to barnyard millet (Echinochloa spp.).

PubMed

Kalyana Babu, B; Sood, Salej; Kumar, Dinesh; Joshi, Anjeli; Pattanayak, A; Kant, Lakshmi; Upadhyaya, H D

2018-02-01

Barnyard millet ( Echinochloa spp.) is an important crop from nutritional point of view, nevertheless, the genetic information is very scarce. In the present investigation, rice and finger millet genomic SSRs were used for assessing cross transferability, identification of polymorphic markers, syntenic regions, genetic diversity and population structure analysis of barnyard millet genotypes. We observed 100% cross transferability for finger millet SSRs, of which 91% were polymorphic, while 71% of rice markers were cross transferable with 48% polymorphic out of them. Twenty-nine and sixteen highly polymorphic finger millet and rice SSRs yielded a mean of 4.3 and 3.38 alleles per locus in barnyard millet genotypes, respectively. The PIC values varied from 0.27 to 0.73 at an average of 0.54 for finger millet SSRs, whereas it was from 0.15 to 0.67 at an average of 0.44 for rice SSRs. High synteny was observed for markers related to panicle length, yield-related traits, spikelet fertility, plant height, root traits, leaf senescence, blast and brown plant hopper resistance. Although the rice SSRs located on chromosome 10 followed by chromosome 6 and 11 were found to be more transferable to barnyard millet, the finger millet SSRs were more polymorphic and transferable to barnyard millet genotypes. These SSR data of finger millet and rice individually as well as combined together grouped the 11 barnyard millet genotypes into 2 major clusters. The results of population structure analysis were similar to cluster analysis.

Improvements of high-throughput culturing yielded novel SAR11 strains and other abundant marine bacteria from the Oregon coast and the Bermuda Atlantic Time Series study site.

PubMed

Stingl, Ulrich; Tripp, Harry James; Giovannoni, Stephen J

2007-08-01

The introduction of high-throughput dilution-to-extinction culturing (HTC) of marine bacterioplankton using sterilized natural sea water as media yielded isolates of many abundant but previously uncultured marine bacterial clades. In early experiments, bacteria from the SAR11 cluster (class Alphaproteobacteria), which are presumed to be the most abundant prokaryotes on earth, were cultured. Although many additional attempts were made, no further strains of the SAR11 clade were obtained. Here, we describe improvements to the HTC technique, which led to the isolation of 17 new SAR11 strains from the Oregon coast and the Sargasso Sea, accounting for 28% and 31% of all isolates in these experiments. Phylogenetic analysis of the internal transcribed spacer (ITS) region showed that the isolates from the Oregon coast represent three different subclusters of SAR11, while isolates from the Sargasso Sea were more uniform and represented a single ITS cluster. A PCR assay proved the presence of proteorhodopsin (PR) in nearly all SAR11 isolates. Analysis of PR amino-acid sequences indicated that isolates from the Oregon coast were tuned to either green or blue light, while PRs from strains obtained from the Sargasso Sea were exclusively tuned to maximum absorbance in the blue. Interestingly, phylogenies based on PR and ITS did not correlate, suggesting lateral gene transfer. In addition to the new SAR11 strains, many novel strains belonging to clusters of previously uncultured or undescribed species of different bacterial phyla, including the first strain of the highly abundant alphaproteobacterial SAR116 clade, were isolated using the modified methods.

Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides.

PubMed

Melo, Armindo; Pinto, Edgar; Aguiar, Ana; Mansilha, Catarina; Pinho, Olívia; Ferreira, Isabel M P L V O

2012-07-01

A monitoring program of nitrate, nitrite, potassium, sodium, and pesticides was carried out in water samples from an intensive horticulture area in a vulnerable zone from north of Portugal. Eight collecting points were selected and water-analyzed in five sampling campaigns, during 1 year. Chemometric techniques, such as cluster analysis, principal component analysis (PCA), and discriminant analysis, were used in order to understand the impact of intensive horticulture practices on dug and drilled wells groundwater and to study variations in the hydrochemistry of groundwater. PCA performed on pesticide data matrix yielded seven significant PCs explaining 77.67% of the data variance. Although PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types. However, a visible differentiation between the water samples was obtained. Cluster and discriminant analysis grouped the eight collecting points into three clusters of similar characteristics pertaining to water contamination, indicating that it is necessary to improve the use of water, fertilizers, and pesticides. Inorganic fertilizers such as potassium nitrate were suspected to be the most important factors for nitrate contamination since highly significant Pearson correlation (r = 0.691, P < 0.01) was obtained between groundwater nitrate and potassium contents. Water from dug wells is especially prone to contamination from the grower and their closer neighbor's practices. Water from drilled wells is also contaminated from distant practices.

Similarities among receptor pockets and among compounds: analysis and application to in silico ligand screening.

PubMed

Fukunishi, Yoshifumi; Mikami, Yoshiaki; Nakamura, Haruki

2005-09-01

We developed a new method to evaluate the distances and similarities between receptor pockets or chemical compounds based on a multi-receptor versus multi-ligand docking affinity matrix. The receptors were classified by a cluster analysis based on calculations of the distance between receptor pockets. A set of low homologous receptors that bind a similar compound could be classified into one cluster. Based on this line of reasoning, we proposed a new in silico screening method. According to this method, compounds in a database were docked to multiple targets. The new docking score was a slightly modified version of the multiple active site correction (MASC) score. Receptors that were at a set distance from the target receptor were not included in the analysis, and the modified MASC scores were calculated for the selected receptors. The choice of the receptors is important to achieve a good screening result, and our clustering of receptors is useful to this purpose. This method was applied to the analysis of a set of 132 receptors and 132 compounds, and the results demonstrated that this method achieves a high hit ratio, as compared to that of a uniform sampling, using a receptor-ligand docking program, Sievgene, which was newly developed with a good docking performance yielding 50.8% of the reconstructed complexes at a distance of less than 2 A RMSD.

Integrating microarray analysis and the soybean genome to understand the soybeans iron deficiency response

PubMed Central

2009-01-01

Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553) genotype and 200 candidate genes in the IsoClark (PI547430) genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs) specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in soybean is a result of a mutation in a transcription factor(s), which controls the expression of genes required in inducing an iron stress response. PMID:19678937

Disassembly time of deuterium-cluster-fusion plasma irradiated by an intense laser pulse.

PubMed

Bang, W

2015-07-01

Energetic deuterium ions from large deuterium clusters (>10nm diameter) irradiated by an intense laser pulse (>10(16)W/cm(2)) produce DD fusion neutrons for a time interval determined by the geometry of the resulting fusion plasma. We present an analytical solution of this time interval, the plasma disassembly time, for deuterium plasmas that are cylindrical in shape. Assuming a symmetrically expanding deuterium plasma, we calculate the expected fusion neutron yield and compare with an independent calculation of the yield using the concept of a finite confinement time at a fixed plasma density. The calculated neutron yields agree quantitatively with the available experimental data. Our one-dimensional simulations indicate that one could expect a tenfold increase in total neutron yield by magnetically confining a 10-keV deuterium fusion plasma for 10ns.

Track structure in radiation biology: theory and applications.

PubMed

Nikjoo, H; Uehara, S; Wilson, W E; Hoshi, M; Goodhead, D T

1998-04-01

A brief review is presented of the basic concepts in track structure and the relative merit of various theoretical approaches adopted in Monte-Carlo track-structure codes are examined. In the second part of the paper, a formal cluster analysis is introduced to calculate cluster-distance distributions. Total experimental ionization cross-sections were least-square fitted and compared with the calculation by various theoretical methods. Monte-Carlo track-structure code Kurbuc was used to examine and compare the spectrum of the secondary electrons generated by using functions given by Born-Bethe, Jain-Khare, Gryzinsky, Kim-Rudd, Mott and Vriens' theories. The cluster analysis in track structure was carried out using the k-means method and Hartigan algorithm. Data are presented on experimental and calculated total ionization cross-sections: inverse mean free path (IMFP) as a function of electron energy used in Monte-Carlo track-structure codes; the spectrum of secondary electrons generated by different functions for 500 eV primary electrons; cluster analysis for 4 MeV and 20 MeV alpha-particles in terms of the frequency of total cluster energy to the root-mean-square (rms) radius of the cluster and differential distance distributions for a pair of clusters; and finally relative frequency distribution for energy deposited in DNA, single-strand break and double-strand breaks for 10MeV/u protons, alpha-particles and carbon ions. There are a number of Monte-Carlo track-structure codes that have been developed independently and the bench-marking presented in this paper allows a better choice of the theoretical method adopted in a track-structure code to be made. A systematic bench-marking of cross-sections and spectra of the secondary electrons shows differences between the codes at atomic level, but such differences are not significant in biophysical modelling at the macromolecular level. Clustered-damage evaluation shows: that a substantial proportion of dose ( 30%) is deposited by low-energy electrons; the majority of DNA damage lesions are of simple type; the complexity of damage increases with increased LET, while the total yield of strand breaks remains constant; and at high LET values nearly 70% of all double-strand breaks are of complex type.

Weighing the Giants - I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images

NASA Astrophysics Data System (ADS)

von der Linden, Anja; Allen, Mark T.; Applegate, Douglas E.; Kelly, Patrick L.; Allen, Steven W.; Ebeling, Harald; Burchat, Patricia R.; Burke, David L.; Donovan, David; Morris, R. Glenn; Blandford, Roger; Erben, Thomas; Mantz, Adam

2014-03-01

This is the first in a series of papers in which we measure accurate weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at redshifts 0.15 ≲ zCl ≲ 0.7, in order to calibrate X-ray and other mass proxies for cosmological cluster experiments. The primary aim is to improve the absolute mass calibration of cluster observables, currently the dominant systematic uncertainty for cluster count experiments. Key elements of this work are the rigorous quantification of systematic uncertainties, high-quality data reduction and photometric calibration, and the `blind' nature of the analysis to avoid confirmation bias. Our target clusters are drawn from X-ray catalogues based on the ROSAT All-Sky Survey, and provide a versatile calibration sample for many aspects of cluster cosmology. We have acquired wide-field, high-quality imaging using the Subaru Telescope and Canada-France-Hawaii Telescope for all 51 clusters, in at least three bands per cluster. For a subset of 27 clusters, we have data in at least five bands, allowing accurate photometric redshift estimates of lensed galaxies. In this paper, we describe the cluster sample and observations, and detail the processing of the SuprimeCam data to yield high-quality images suitable for robust weak-lensing shape measurements and precision photometry. For each cluster, we present wide-field three-colour optical images and maps of the weak-lensing mass distribution, the optical light distribution and the X-ray emission. These provide insights into the large-scale structure in which the clusters are embedded. We measure the offsets between X-ray flux centroids and the brightest cluster galaxies in the clusters, finding these to be small in general, with a median of 20 kpc. For offsets ≲100 kpc, weak-lensing mass measurements centred on the brightest cluster galaxies agree well with values determined relative to the X-ray centroids; miscentring is therefore not a significant source of systematic uncertainty for our weak-lensing mass measurements. In accompanying papers, we discuss the key aspects of our photometric calibration and photometric redshift measurements (Kelly et al.), and measure cluster masses using two methods, including a novel Bayesian weak-lensing approach that makes full use of the photometric redshift probability distributions for individual background galaxies (Applegate et al.). In subsequent papers, we will incorporate these weak-lensing mass measurements into a self-consistent framework to simultaneously determine cluster scaling relations and cosmological parameters.

Genetic Divergence and Heritability of 42 Coloured Upland Rice Genotypes (Oryzasativa) as Revealed by Microsatellites Marker and Agro-Morphological Traits

PubMed Central

Ahmad, Faiz; Hanafi, Mohamed Musa; Hakim, Md Abdul; Rafii, Mohd Y.; Arolu, Ibrahim Wasiu; Akmar Abdullah, Siti Nor

2015-01-01

Coloured rice genotypes have greater nutritious value and consumer demand for these varieties is now greater than ever. The documentation of these genotypes is important for the improvement of the rice plant. In this study, 42 coloured rice genotypes were selected for determination of their genetic divergence using 25 simple sequence repeat (SSR) primers and 15 agro-morphological traits. Twenty-one out of the 25 SSR primers showed distinct, reproducible polymorphism. A dendrogram constructed using the SSR primers clustered the 42 coloured rice genotypes into 7 groups. Further, principle component analysis showed 75.28% of total variations were explained by the first—three components. All agro-morphological traits showed significant difference at the (p≤0.05) and (p≤0.01) levels. From the dendrogram constructed using the agro-morphological traits, all the genotypes were clustered into four distinct groups. Pearson’s correlation coefficient showed that among the 15 agro-morphological traits, the yield contributing factor had positive correlation with the number of tillers, number of panicles, and panicle length. The heritability of the 15 traits ranged from 17.68 to 99.69%. Yield per plant and harvest index showed the highest value for both heritability and genetic advance. The information on the molecular and agro-morphological traits can be used in rice breeding programmes to improve nutritional value and produce higher yields. PMID:26393807

A taxonomy of epithelial human cancer and their metastases

PubMed Central

2009-01-01

Background Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination. Methods We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures. Results Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination. Conclusion Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile. PMID:20017941

The Neandertal type site revisited: Interdisciplinary investigations of skeletal remains from the Neander Valley, Germany

PubMed Central

Schmitz, Ralf W.; Serre, David; Bonani, Georges; Feine, Susanne; Hillgruber, Felix; Krainitzki, Heike; Pääbo, Svante; Smith, Fred H.

2002-01-01

The 1856 discovery of the Neandertal type specimen (Neandertal 1) in western Germany marked the beginning of human paleontology and initiated the longest-standing debate in the discipline: the role of Neandertals in human evolutionary history. We report excavations of cave sediments that were removed from the Feldhofer caves in 1856. These deposits have yielded over 60 human skeletal fragments, along with a large series of Paleolithic artifacts and faunal material. Our analysis of this material represents the first interdisciplinary analysis of Neandertal remains incorporating genetic, direct dating, and morphological dimensions simultaneously. Three of these skeletal fragments fit directly on Neandertal 1, whereas several others have distinctively Neandertal features. At least three individuals are represented in the skeletal sample. Radiocarbon dates for Neandertal 1, from which a mtDNA sequence was determined in 1997, and a second individual indicate an age of ≈40,000 yr for both. mtDNA analysis on the same second individual yields a sequence that clusters with other published Neandertal sequences. PMID:12232049

Analysis of trace fibers by IR-MALDESI imaging coupled with high resolving power MS

PubMed Central

Cochran, Kristin H.; Barry, Jeremy A.; Robichaud, Guillaume

2016-01-01

Trace evidence is a significant portion of forensic cases. Textile fibers are a common form of trace evidence that are gaining importance in criminal cases. Currently, qualitative techniques that do not yield structural information are primarily used for fiber analysis, but mass spectrometry is gaining an increasing role in this field. Mass spectrometry yields more quantitative structural information about the dye and polymer that can be used for more conclusive comparisons. Matrix-assisted laser desorption electrospray ionization (MALDESI) is a hybrid ambient ionization source being investigated for use in mass spectrometric fiber analysis. In this manuscript, IR-MALDESI was used as a source for mass spectrometry imaging (MSI) of a dyed nylon fiber cluster and single fiber. Information about the fiber polymer as well as the dye were obtained from a single fiber which was on the order of 10 μm in diameter. These experiments were performed directly from the surface of a tape lift of the fiber with a background of extraneous fibers. PMID:25081013

Analysis of trace fibers by IR-MALDESI imaging coupled with high resolving power MS.

PubMed

Cochran, Kristin H; Barry, Jeremy A; Robichaud, Guillaume; Muddiman, David C

2015-01-01

Trace evidence is a significant portion of forensic cases. Textile fibers are a common form of trace evidence that are gaining importance in criminal cases. Currently, qualitative techniques that do not yield structural information are primarily used for fiber analysis, but mass spectrometry is gaining an increasing role in this field. Mass spectrometry yields more quantitative structural information about the dye and polymer that can be used for more conclusive comparisons. Matrix-assisted laser desorption electrospray ionization (MALDESI) is a hybrid ambient ionization source being investigated for use in mass spectrometric fiber analysis. In this manuscript, IR-MALDESI was used as a source for mass spectrometry imaging (MSI) of a dyed nylon fiber cluster and single fiber. Information about the fiber polymer as well as the dye were obtained from a single fiber which was on the order of 10 μm in diameter. These experiments were performed directly from the surface of a tape lift of the fiber with a background of extraneous fibers.

Dietary patterns in middle-aged Irish men and women defined by cluster analysis.

PubMed

Villegas, R; Salim, A; Collins, M M; Flynn, A; Perry, I J

2004-12-01

To identify and characterise dietary patterns in a middle-aged Irish population sample and study associations between these patterns, sociodemographic and anthropometric variables and major risk factors for cardiovascular disease. A cross-sectional study. A group of 1473 men and women were sampled from 17 general practice lists in the South of Ireland. A total of 1018 attended for screening, with a response rate of 69%. Participants completed a detailed health and lifestyle questionnaire and provided a fasting blood sample for glucose, lipids and homocysteine. Dietary intake was assessed using a standard food-frequency questionnaire adapted for use in the Irish population. The food-frequency questionnaire was a modification of that used in the UK arm of the European Prospective Investigation into Cancer study, which was based on that used in the US Nurses' Health Study. Dietary patterns were assessed primarily by K-means cluster analysis, following initial principal components analysis to identify the seeds. Three dietary patterns were identified. These clusters corresponded to a traditional Irish diet, a prudent diet and a diet characterised by high consumption of alcoholic drinks and convenience foods. Cluster 1 (Traditional Diet) had the highest intakes of saturated fat (SFA), monounsaturated fat (MUFA) and percentage of total energy from fat, and the lowest polyunsaturated fat (PUFA) intake and ratio of polyunsaturated to saturated fat (P:S). Cluster 2 (Prudent Diet) was characterised by significantly higher intakes of fibre, PUFA, P:S ratio and antioxidant vitamins (vitamins C and E), and lower intakes of total fat, MUFA, SFA and cholesterol. Cluster 3 (Alcohol & Convenience Foods) had the highest intakes of alcohol, protein, cholesterol, vitamin B(12), vitamin B(6), folate, iron, phosphorus, selenium and zinc, and the lowest intakes of PUFA, vitamin A and antioxidant vitamins (vitamins C and E). There were significant differences between clusters in gender distribution, smoking status, physical activity, body mass index, waist circumference and serum homocysteine concentrations. In this general population sample, cluster analysis methods yielded two major dietary patterns: prudent and traditional. The prudent dietary pattern is associated with other health-seeking behaviours. Study of dietary patterns will help elucidate links between diet and disease and contribute to the development of healthy eating guidelines for health promotion.

Quantitative Evaluation of Head and Neck Cancer Treatment-Related Dysphagia in the Development of a Personalized Treatment Deintensification Paradigm.

PubMed

Quon, Harry; Hui, Xuan; Cheng, Zhi; Robertson, Scott; Peng, Luke; Bowers, Michael; Moore, Joseph; Choflet, Amanda; Thompson, Alex; Muse, Mariah; Kiess, Ana; Page, Brandi; Fakhry, Carole; Gourin, Christine; O'Hare, Jolyne; Graham, Peter; Szczesniak, Michal; Maclean, Julia; Cook, Ian; McNutt, Todd

2017-12-01

To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment-related dysphagia (HNCTD). Irradiated HNC subjects seen in follow-up care (April 2015 to December 2015) who prospectively completed the Sydney Swallow Questionnaire (SSQ) and the MD Anderson Dysphagia Inventory (MDADI) concurrently on the web interface to our Oncospace database were evaluated. A correlation matrix quantified the relationship between the SSQ and MDADI. Machine-learning unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis to establish its validity was performed. We identified 89 subjects. The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.69). K-means cluster analysis demonstrated that 3 unique statistical cohorts (elbow criterion) could be identified with CLUSPLOT analysis, confirming that 100% of variances were accounted for. Correlation coefficients between the individual items in the SSQ and the MDADI demonstrated weak to moderate negative correlation, except for SSQ17 (quality of life question). Pilot analysis demonstrates that the MDADI and SSQ are complementary. Three unique clusters of patients can be defined, suggesting that a unique dysphagia signature for HNCTD may be definable. Longitudinal studies relying on only a single PRO, such as MDADI, may be inadequate for classifying HNCTD. Copyright © 2017 Elsevier Inc. All rights reserved.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

AFLP-based genetic diversity and its comparison with diversity based on SSR, SAMPL, and phenotypic traits in bread wheat.

PubMed

Roy, J K; Lakshmikumaran, M S; Balyan, H S; Gupta, P K

2004-02-01

Data on AFLP (eight primer pairs) and 14 phenotypic traits, collected on 55 elite and exotic bread wheat genotypes, were utilized for estimations of genetic diversity. We earlier used these 55 genotypes for a similar study using SSRs and SAMPL. As many as 615 scorable AFLP bands visualized included 287 (46.6%) polymorphic bands. The phenotypic traits included yield and its component traits, as well as physiomorphological traits like flag leaf area. Dendrograms were prepared using cluster analysis based on Jaccard's similarity coefficients in case of AFLP and on squared Euclidean distances in case of phenotypic traits. PCA was conducted using AFLP data and a PCA plot was prepared, which was compared with clustering patterns in two dendrograms, one each for AFLP and phenotypic traits. The results were also compared with published results that included studies conducted elsewhere using entirely different wheat germplasm and our own SSR and SAMPL studies based on the same 55 genotypes used in the present study. It was shown that molecular markers are superior to phenotypic traits and that AFLP and SAMPL are superior to other molecular markers for estimation of genetic diversity. On the basis of AFLP analysis and keeping in view the yield performance and stability, a pair of genotypes (E3876 and E677) was recommended for hybridization in order to develop superior cultivars.

Chemical Composition of Juniperus communis L. Cone Essential Oil and Its Variability among Wild Populations in Kosovo.

PubMed

Hajdari, Avni; Mustafa, Behxhet; Nebija, Dashnor; Miftari, Elheme; Quave, Cassandra L; Novak, Johannes

2015-11-01

Ripe cones of Juniperus communis L. (Cupressaceae) were collected from five wild populations in Kosovo, with the aim of investigating the chemical composition and natural variation of essential oils between and within wild populations. Ripe cones were collected, air dried, crushed, and the essential oils obtained by hydrodistillation. The essential-oil constituents were identified by GC-FID and GC/MS analyses. The yield of essential oil differed depending on the population origins and ranged from 0.4 to 3.8% (v/w, based on the dry weight). In total, 42 compounds were identified in the essential oils of all populations. The principal components of the cone-essential oils were α-pinene, followed by β-myrcene, sabinene, and D-limonene. Taking into consideration the yield and chemical composition, the essential oil originating from various collection sites in Kosovo fulfilled the minimum requirements for J. communis essential oils of the European Pharmacopoeia. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to determine the influence of the geographical variations on the essential-oil composition. These statistical analyses suggested that the clustering of populations was not related to their geographic location, but rather appeared to be linked to local selective forces acting on the chemotype diversity. Copyright © 2015 Verlag Helvetica Chimica Acta AG, Zürich.

Guanidine: A Highly Efficient Stabilizer in Atmospheric New-Particle Formation.

PubMed

Myllys, Nanna; Ponkkonen, Tuomo; Passananti, Monica; Elm, Jonas; Vehkamäki, Hanna; Olenius, Tinja

2018-05-24

The role of a strong organobase, guanidine, in sulfuric acid-driven new-particle formation is studied using state-of-the-art quantum chemical methods and molecular cluster formation simulations. Cluster formation mechanisms at the molecular level are resolved, and theoretical results on cluster stability are confirmed with mass spectrometer measurements. New-particle formation from guanidine and sulfuric acid molecules occurs without thermodynamic barriers under studied conditions, and clusters are growing close to a 1:1 composition of acid and base. Evaporation rates of the most stable clusters are extremely low, which can be explained by the proton transfers and symmetrical cluster structures. We compare the ability of guanidine and dimethylamine to enhance sulfuric acid-driven particle formation and show that more than 2000-fold concentration of dimethylamine is needed to yield as efficient particle formation as in the case of guanidine. At similar conditions, guanidine yields 8 orders of magnitude higher particle formation rates compared to dimethylamine. Highly basic compounds such as guanidine may explain experimentally observed particle formation events at low precursor vapor concentrations, whereas less basic and more abundant bases such as ammonia and amines are likely to explain measurements at high concentrations.

Selection of Yeast Strains for Tequila Fermentation Based on Growth Dynamics in Combined Fructose and Ethanol Media.

PubMed

Aldrete-Tapia, J A; Miranda-Castilleja, D E; Arvizu-Medrano, S M; Hernández-Iturriaga, M

2018-02-01

The high concentration of fructose in agave juice has been associated with reduced ethanol tolerance of commercial yeasts used for tequila production and low fermentation yields. The selection of autochthonous strains, which are better adapted to agave juice, could improve the process. In this study, a 2-step selection process of yeasts isolated from spontaneous fermentations for tequila production was carried out based on analysis of the growth dynamics in combined conditions of high fructose and ethanol. First, yeast isolates (605) were screened to identify strains tolerant to high fructose (20%) and to ethanol (10%), yielding 89 isolates able to grow in both conditions. From the 89 isolates, the growth curves under 8 treatments of combined fructose (from 20% to 5%) and ethanol (from 0% to 10%) were obtained, and the kinetic parameters were analyzed with principal component analysis and k-means clustering. The resulting yeast strain groups corresponded to the fast, medium and slow growers. A second clustering of only the fast growers led to the selection of 3 Saccharomyces strains (199, 230, 231) that were able to grow rapidly in 4 out of the 8 conditions evaluated. This methodology differentiated strains phenotypically and could be further used for strain selection in other processes. A method to select yeast strains for fermentation taking into account the natural differences of yeast isolates. This methodology is based on the cell exposition to combinations of sugar and ethanol, which are the most important stress factors in fermentation. This strategy will help to identify the most tolerant strain that could improve ethanol yield and reduce fermentation time. © 2018 Institute of Food Technologists®.

Effect of Salinity on Biomass Yield and Physiological and Stem-Root Anatomical Characteristics of Purslane (Portulaca oleracea L.) Accessions

PubMed Central

Juraimi, Abdul Shukor; Rafii, M. Y.; Abdul Hamid, Azizah

2015-01-01

13 selected purslane accessions were subjected to five salinity levels 0, 8, 16, 24, and 32 dS m−1. Salinity effect was evaluated on the basis of biomass yield reduction, physiological attributes, and stem-root anatomical changes. Aggravated salinity stress caused significant (P < 0.05) reduction in all measured parameters and the highest salinity showed more detrimental effect compared to control as well as lower salinity levels. The fresh and dry matter production was found to increase in Ac1, Ac9, and Ac13 from lower to higher salinity levels but others were badly affected. Considering salinity effect on purslane physiology, increase in chlorophyll content was seen in Ac2, Ac4, Ac6, and Ac8 at 16 dS m−1 salinity, whereas Ac4, Ac9, and Ac12 showed increased photosynthesis at the same salinity levels compared to control. Anatomically, stem cortical tissues of Ac5, Ac9, and Ac12 were unaffected at control and 8 dS m−1 salinity but root cortical tissues did not show any significant damage except a bit enlargement in Ac12 and Ac13. A dendrogram was constructed by UPGMA based on biomass yield and physiological traits where all 13 accessions were grouped into 5 clusters proving greater diversity among them. The 3-dimensional principal component analysis (PCA) has also confirmed the output of grouping from cluster analysis. Overall, salinity stressed among all 13 purslane accessions considering biomass production, physiological growth, and anatomical development Ac9 was the best salt-tolerant purslane accession and Ac13 was the most affected accession. PMID:25802833

Analysis of QTLs for yield-related traits in Yuanjiang common wild rice (Oryza rufipogon Griff.).

PubMed

Fu, Qiang; Zhang, Peijiang; Tan, Lubin; Zhu, Zuofeng; Ma, Dan; Fu, Yongcai; Zhan, Xinchun; Cai, Hongwei; Sun, Chuanqing

2010-02-01

Using an accession of common wild rice (Oryza rufipogon Griff.) collected from Yuanjiang County, Yunnan Province, China, as the donor and an elite cultivar 93-11, widely used in two-line indica hybrid rice production in China, as the recurrent parent, an advanced backcross populations were developed. Through genotyping of 187 SSR markers and investigation of six yield-related traits of two generations (BC(4)F(2) and BC(4)F(4)), a total of 26 QTLs were detected by employing single point analysis and interval mapping in both generations. Of the 26 QTLs, the alleles of 10 (38.5%) QTLs originating from O. rufipogon had shown a beneficial effect for yield-related traits in the 93-11 genetic background. In addition, five QTLs controlling yield and its components were newly identified, indicating that there are potentially novel alleles in Yuanjiang common wild rice. Three regions underling significant QTLs for several yield-related traits were detected on chromosome 1, 7 and 12. The QTL clusters were founded and corresponding agronomic traits of those QTLs showed highly significant correlation, suggesting the pleiotropism or tight linkage. Fine-mapping and cloning of these yield-related QTLs from wild rice would be helpful to elucidating molecular mechanism of rice domestication and rice breeding in the future. Copyright 2010 Institute of Genetics and Developmental Biology and the Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Comparative genomic analysis of clinical and environmental Vibrio vulnificus isolates revealed biotype 3 evolutionary relationships.

PubMed

Koton, Yael; Gordon, Michal; Chalifa-Caspi, Vered; Bisharat, Naiel

2014-01-01

In 1996 a common-source outbreak of severe soft tissue and bloodstream infections erupted among Israeli fish farmers and fish consumers due to changes in fish marketing policies. The causative pathogen was a new strain of Vibrio vulnificus, named biotype 3, which displayed a unique biochemical and genotypic profile. Initial observations suggested that the pathogen erupted as a result of genetic recombination between two distinct populations. We applied a whole genome shotgun sequencing approach using several V. vulnificus strains from Israel in order to study the pan genome of V. vulnificus and determine the phylogenetic relationship of biotype 3 with existing populations. The core genome of V. vulnificus based on 16 draft and complete genomes consisted of 3068 genes, representing between 59 and 78% of the whole genome of 16 strains. The accessory genome varied in size from 781 to 2044 kbp. Phylogenetic analysis based on whole, core, and accessory genomes displayed similar clustering patterns with two main clusters, clinical (C) and environmental (E), all biotype 3 strains formed a distinct group within the E cluster. Annotation of accessory genomic regions found in biotype 3 strains and absent from the core genome yielded 1732 genes, of which the vast majority encoded hypothetical proteins, phage-related proteins, and mobile element proteins. A total of 1916 proteins (including 713 hypothetical proteins) were present in all human pathogenic strains (both biotype 3 and non-biotype 3) and absent from the environmental strains. Clustering analysis of the non-hypothetical proteins revealed 148 protein clusters shared by all human pathogenic strains; these included transcriptional regulators, arylsulfatases, methyl-accepting chemotaxis proteins, acetyltransferases, GGDEF family proteins, transposases, type IV secretory system (T4SS) proteins, and integrases. Our study showed that V. vulnificus biotype 3 evolved from environmental populations and formed a genetically distinct group within the E-cluster. The unique epidemiological circumstances facilitated disease outbreak and brought this genotype to the attention of the scientific community.

Coping profiles, perceived stress and health-related behaviors: a cluster analysis approach.

PubMed

Doron, Julie; Trouillet, Raphael; Maneveau, Anaïs; Ninot, Grégory; Neveu, Dorine

2015-03-01

Using cluster analytical procedure, this study aimed (i) to determine whether people could be differentiated on the basis of coping profiles (or unique combinations of coping strategies); and (ii) to examine the relationships between these profiles and perceived stress and health-related behaviors. A sample of 578 French students (345 females, 233 males; M(age)= 21.78, SD(age)= 2.21) completed the Perceived Stress Scale-14 ( Bruchon-Schweitzer, 2002), the Brief COPE ( Muller and Spitz, 2003) and a series of items measuring health-related behaviors. A two-phased cluster analytic procedure (i.e. hierarchical and non-hierarchical-k-means) was employed to derive clusters of coping strategy profiles. The results yielded four distinctive coping profiles: High Copers, Adaptive Copers, Avoidant Copers and Low Copers. The results showed that clusters differed significantly in perceived stress and health-related behaviors. High Copers and Avoidant Copers displayed higher levels of perceived stress and engaged more in unhealthy behavior, compared with Adaptive Copers and Low Copers who reported lower levels of stress and engaged more in healthy behaviors. These findings suggested that individuals' relative reliance on some strategies and de-emphasis on others may be a more advantageous way of understanding the manner in which individuals cope with stress. Therefore, cluster analysis approach may provide an advantage over more traditional statistical techniques by identifying distinct coping profiles that might best benefit from interventions. Future research should consider coping profiles to provide a deeper understanding of the relationships between coping strategies and health outcomes and to identify risk groups. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Low physical activity as a key differentiating factor in the potential high-risk profile for depressive symptoms in older adults.

PubMed

Holmquist, Sofie; Mattsson, Sabina; Schele, Ingrid; Nordström, Peter; Nordström, Anna

2017-09-01

The identification of potential high-risk groups for depression is of importance. The purpose of the present study was to identify high-risk profiles for depressive symptoms in older individuals, with a focus on functional performance. The population-based Healthy Ageing Initiative included 2,084 community-dwelling individuals (49% women) aged 70. Explorative cluster analysis was used to group participants according to functional performance level, using measures of basic mobility skills, gait variability, and grip strength. Intercluster differences in depressive symptoms (measured by the Geriatric Depression Scale [GDS]-15), physical activity (PA; measured objectively with the ActiGraph GT3X+), and a rich set of covariates were examined. The cluster analysis yielded a seven-cluster solution. One potential high-risk cluster was identified, with overrepresentation of individuals with GDS scores >5 (15.1 vs. 2.7% expected; relative risk = 6.99, P < .001); the prevalence of depressive symptoms was significantly lower in the other clusters (all P < .01). The potential high-risk cluster had significant overrepresentations of obese individuals (39.7 vs. 17.4% expected) and those with type 2 diabetes (24.7 vs. 8.5% expected), and underrepresentation of individuals who fulfilled the World Health Organization's PA recommendations (15.6 vs. 59.1% expected; all P < .01), as well as low levels of functional performance. The present study provided a potential high-risk profile for depressive symptoms among elderly community-dwelling individuals, which included low levels functional performance combined with low levels of PA. Including PA in medical screening of the elderly may aid in identification of potential high-risk individuals for depressive symptoms. © 2017 Wiley Periodicals, Inc.

Yields of Soviet underground nuclear explosions at Novaya Zemlya, 1964-1976, from seismic body and surface waves

PubMed Central

Sykes, Lynn R.; Wiggins, Graham C.

1986-01-01

Surface and body wave magnitudes are determined for 15 U.S.S.R. underground nuclear weapons tests conducted at Novaya Zemlya between 1964 and 1976 and are used to estimate yields. These events include the largest underground explosions detonated by the Soviet Union. A histogram of body wave magnitude (mb) values indicates a clustering of explosions at a few specific yields. The most pronounced cluster consists of six explosions of yield near 500 kilotons. Several of these seem to be tests of warheads for major strategic systems that became operational in the late 1970s. The largest Soviet underground explosion is estimated to have a yield of 3500 ± 600 kilotons, somewhat smaller than the yield of the largest U.S. underground test. A preliminary estimation of the significance of tectonic release is made by measuring the amplitude of Love waves. The bias in mb for Novaya Zemlya relative to the Nevada test site is about 0.35, nearly identical to that of the eastern Kazakhstan test site relative to Nevada. PMID:16593645

Relating Regime Structure to Probability Distribution and Preferred Structure of Small Errors in a Large Atmospheric GCM

NASA Astrophysics Data System (ADS)

Straus, D. M.

2007-12-01

The probability distribution (pdf) of errors is followed in identical twin studies using the COLA T63 AGCM, integrated with observed SST for 15 recent winters. 30 integrations per winter (for 15 winters) are available with initial errors that are extremely small. The evolution of the pdf is tested for multi-modality, and the results interpreted in terms of clusters / regimes found in: (a) the set of 15x30 integrations mentioned, and (b) a larger ensemble of 55x15 integrations made with the same GCM using the same SSTs. The mapping of pdf evolution and clusters is also carried out for each winter separately, using the clusters found in the 55-member ensemble for the same winter alone. This technique yields information on the change in regimes caused by different boundary forcing (Straus and Molteni, 2004; Straus, Corti and Molteni, 2006). Analysis of the growing errors in terms of baroclinic and barotropic components allows for interpretation of the corresponding instabilities.

Characterization of fluorescence in heat-treated silver-exchanged zeolites.

PubMed

De Cremer, Gert; Coutiño-Gonzalez, Eduardo; Roeffaers, Maarten B J; Moens, Bart; Ollevier, Jeroen; Van der Auweraer, Mark; Schoonheydt, Robert; Jacobs, Pierre A; De Schryver, Frans C; Hofkens, Johan; De Vos, Dirk E; Sels, Bert F; Vosch, Tom

2009-03-04

Thermal treatment of Ag(+)-exchanged zeolites yields discrete highly photostable luminescent clusters without formation of metallic nanoparticles. Different types of emitters with characteristic luminescence colors are observed, depending on the nature of the cocation, the amount of exchanged silver, and the host topology. The dominant emission bands in LTA samples are situated around 550 and 690 nm for the samples with, respectively, low and high silver content, while in FAU-type materials only a broad band around 550 nm is observed, regardless of the degree of exchange. Analysis of the fluorescent properties in combination with ESR spectroscopy suggests that a Ag(6)(+) cluster with doublet electronic ground state is associated with the appearance of the 690-nm emitter, having a decay of a few hundred microseconds. Tentatively, the nanosecond-decaying 550-nm emitter is assigned to the Ag(3)(+) cluster. This new class of photostable luminescent particles with tunable emission colors offers interesting perspectives for various applications such as biocompatible labels for intracellular imaging.

DNA Encapsulation of Ten Silver Atoms Produces a Bright, Modulatable, Near Infrared-Emitting Cluster

PubMed Central

Petty, Jeffrey T.; Fan, Chaoyang; Story, Sandra P.; Sengupta, Bidisha; Iyer, Ashlee St. John; Prudowsky, Zachary; Dickson, Robert M.

2010-01-01

Photostability, inherent fluorescence brightness, and optical modulation of fluorescence are key attributes distinguishing silver nanoclusters as fluorophores. DNA plays a central role both by protecting the clusters in aqueous environments and by directing their formation. Herein, we characterize a new near infrared-emitting cluster with excitation and emission maxima at 750 and 810 nm, respectively that is stabilized within C3AC3AC3TC3A. Following chromatographic resolution of the near infrared species, a stoichiometry of 10 Ag/oligonucleotide was determined. Combined with excellent photostability, the cluster’s 30% fluorescence quantum yield and 180,000 M−1cm−1 extinction coefficient give it a fluorescence brightness that significantly improves on that of the organic dye Cy7. Fluorescence correlation analysis shows an optically accessible dark state that can be directly depopulated with longer wavelength co-illumination. The coupled increase in total fluorescence demonstrates that enhanced sensitivity can be realized through Synchronously Amplified Fluorescence Image Recovery (SAFIRe), which further differentiates this new fluorophore. PMID:21116486

Molecular dynamics study of Al and Ni 3Al sputtering by Al clusters bombardment

NASA Astrophysics Data System (ADS)

Zhurkin, Eugeni E.; Kolesnikov, Anton S.

2002-06-01

The sputtering of Al and Ni 3Al (1 0 0) surfaces induced by impact of Al ions and Al N clusters ( N=2,4,6,9,13,55) with energies of 100 and 500 eV/atom is studied at atomic scale by means of classical molecular dynamics (MD). The MD code we used implements many-body tight binding potential splined to ZBL at short distances. Special attention has been paid to model dense cascades: we used quite big computation cells with lateral periodic and damped boundary conditions. In addition, long simulation times (10-25 ps) and representative statistics (up to 1000 runs per each case) were considered. The total sputtering yields, energy and time spectrums of sputtered particles, as well as preferential sputtering of compound target were analyzed, both in the linear and non-linear regimes. The significant "cluster enhancement" of sputtering yield was found for cluster sizes N⩾13. In parallel, we estimated collision cascade features depending on cluster size in order to interpret the nature of observed non-linear effects.

Disassembly time of deuterium-cluster-fusion plasma irradiated by an intense laser pulse

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

Bang, W.

Energetic deuterium ions from large deuterium clusters (>10 nm diameter) irradiated by an intense laser pulse (>10¹⁶ W/cm²) produce DD fusion neutrons for a time interval determined by the geometry of the resulting fusion plasma. We show an analytical solution of this time interval, the plasma disassembly time, for deuterium plasmas that are cylindrical in shape. Assuming a symmetrically expanding deuterium plasma, we calculate the expected fusion neutron yield and compare with an independent calculation of the yield using the concept of a finite confinement time at a fixed plasma density. The calculated neutron yields agree quantitatively with the availablemore » experimental data. Our one-dimensional simulations indicate that one could expect a tenfold increase in total neutron yield by magnetically confining a 10 - keV deuterium fusion plasma for 10 ns.« less

Disassembly time of deuterium-cluster-fusion plasma irradiated by an intense laser pulse

DOE PAGES

Bang, W.

2015-07-02

Energetic deuterium ions from large deuterium clusters (>10 nm diameter) irradiated by an intense laser pulse (>10¹⁶ W/cm²) produce DD fusion neutrons for a time interval determined by the geometry of the resulting fusion plasma. We show an analytical solution of this time interval, the plasma disassembly time, for deuterium plasmas that are cylindrical in shape. Assuming a symmetrically expanding deuterium plasma, we calculate the expected fusion neutron yield and compare with an independent calculation of the yield using the concept of a finite confinement time at a fixed plasma density. The calculated neutron yields agree quantitatively with the availablemore » experimental data. Our one-dimensional simulations indicate that one could expect a tenfold increase in total neutron yield by magnetically confining a 10 - keV deuterium fusion plasma for 10 ns.« less

Effects of radiation quality and oxygen on clustered DNA lesions and cell death.

PubMed

Stewart, Robert D; Yu, Victor K; Georgakilas, Alexandros G; Koumenis, Constantinos; Park, Joo Han; Carlson, David J

2011-11-01

Radiation quality and cellular oxygen concentration have a substantial impact on DNA damage, reproductive cell death and, ultimately, the potential efficacy of radiation therapy for the treatment of cancer. To better understand and quantify the effects of radiation quality and oxygen on the induction of clustered DNA lesions, we have now extended the Monte Carlo Damage Simulation (MCDS) to account for reductions in the initial lesion yield arising from enhanced chemical repair of DNA radicals under hypoxic conditions. The kinetic energy range and types of particles considered in the MCDS have also been expanded to include charged particles up to and including (56)Fe ions. The induction of individual and clustered DNA lesions for arbitrary mixtures of different types of radiation can now be directly simulated. For low-linear energy transfer (LET) radiations, cells irradiated under normoxic conditions sustain about 2.9 times as many double-strand breaks (DSBs) as cells irradiated under anoxic conditions. New experiments performed by us demonstrate similar trends in the yields of non-DSB (Fpg and Endo III) clusters in HeLa cells irradiated by γ rays under aerobic and hypoxic conditions. The good agreement among measured and predicted DSBs, Fpg and Endo III cluster yields suggests that, for the first time, it may be possible to determine nucleotide-level maps of the multitude of different types of clustered DNA lesions formed in cells under reduced oxygen conditions. As particle LET increases, the MCDS predicts that the ratio of DSBs formed under normoxic to hypoxic conditions by the same type of radiation decreases monotonically toward unity. However, the relative biological effectiveness (RBE) of higher-LET radiations compared to (60)Co γ rays (0.24 keV/μm) tends to increase with decreasing oxygen concentration. The predicted RBE of a 1 MeV proton (26.9 keV/μm) relative to (60)Co γ rays for DSB induction increases from 1.9 to 2.3 as oxygen concentration decreases from 100% to 0%. For a 12 MeV (12)C ion (681 keV/μm), the 'predicted RBE for DSB induction increases from 3.4 (100% O(2)) to 9.8 (0% O(2)). Estimates of linear-quadratic (LQ) cell survival model parameters (α and β) are closely correlated to the Monte Carlo-predicted trends in DSB induction for a wide range of particle types, energies and oxygen concentrations. The analysis suggests α is, as a first approximation, proportional to the initial number of DSBs per cell, and β is proportional to the square of the initial number of DSBs per cell. Although the reported studies provide some evidence supporting the hypothesis that DSBs are a biologically critical form of clustered DNA lesion, the induction of Fpg and Endo III clusters in HeLa cells irradiated by γ rays exhibits similar trends with oxygen concentration. Other types of non-DSB cluster may still play an important role in reproductive cell death. The MCDS captures many of the essential trends in the formation of clustered DNA lesions by ionizing radiation and provides useful information to probe the multiscale effects and interactions of ionizing radiation in cells and tissues. Information from Monte Carlo simulations of cluster induction may also prove useful for efforts to better exploit radiation quality and reduce the impact of tumor hypoxia in proton and carbon-ion radiation therapy.

Recognizing patterns of visual field loss using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Yousefi, Siamak; Goldbaum, Michael H.; Zangwill, Linda M.; Medeiros, Felipe A.; Bowd, Christopher

2014-03-01

Glaucoma is a potentially blinding optic neuropathy that results in a decrease in visual sensitivity. Visual field abnormalities (decreased visual sensitivity on psychophysical tests) are the primary means of glaucoma diagnosis. One form of visual field testing is Frequency Doubling Technology (FDT) that tests sensitivity at 52 points within the visual field. Like other psychophysical tests used in clinical practice, FDT results yield specific patterns of defect indicative of the disease. We used Gaussian Mixture Model with Expectation Maximization (GEM), (EM is used to estimate the model parameters) to automatically separate FDT data into clusters of normal and abnormal eyes. Principal component analysis (PCA) was used to decompose each cluster into different axes (patterns). FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal (i.e., glaucomatous) FDT results, recruited from a university-based, longitudinal, multi-center, clinical study on glaucoma. The GEM input was the 52-point FDT threshold sensitivities for all eyes. The optimal GEM model separated the FDT fields into 3 clusters. Cluster 1 contained 94% normal fields (94% specificity) and clusters 2 and 3 combined, contained 77% abnormal fields (77% sensitivity). For clusters 1, 2 and 3 the optimal number of PCA-identified axes were 2, 2 and 5, respectively. GEM with PCA successfully separated FDT fields from healthy and glaucoma eyes and identified familiar glaucomatous patterns of loss.

Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii.

PubMed

Im, Chak Han; Park, Young-Hoon; Hammel, Kenneth E; Park, Bokyung; Kwon, Soon Wook; Ryu, Hojin; Ryu, Jae-San

2016-07-01

Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type factors, and 28 insertion/deletion (InDel) markers were mapped. The map consisted of 12 linkage groups (LGs) spanning 1047.8cM, with an average interval length of 4.09cM. Four independent populations (Pd3, Pd8, Pd14, and Pd15) derived from crossing between four monokaryons from KNR2532 as a tester strain and 98 monokaryons from KNR2312 were used to characterize quantitative trait loci (QTL) for nine traits such as yield, quality, cap color, and earliness. Using composite interval mapping (CIM), 71 QTLs explaining between 5.82% and 33.17% of the phenotypic variations were identified. Clusters of more than five QTLs for various traits were identified in three genomic regions, on LGs 1, 7 and 9. Regardless of the population, 6 of the 9 traits studied and 18 of the 71 QTLs found in this study were identified in the largest cluster, LG1, in the range from 65.4 to 110.4cM. The candidate genes for yield encoding transcription factor, signal transduction, mycelial growth and hydrolase are suggested by using manual and computational analysis of genome sequence corresponding to QTL region with the highest likelihood odds (LOD) for yield. The genetic map and the QTLs established in this study will help breeders and geneticists to develop selection markers for agronomically important characteristics of mushrooms and to identify the corresponding genes. Copyright © 2016 Elsevier Inc. All rights reserved.

A classification of substance-dependent men on temperament and severity variables.

PubMed

Henderson, Melinda J; Galen, Luke W

2003-06-01

This study examined the validity of classifying substance abusers based on temperament and dependence severity, and expanded the scope of typology differences to proximal determinants of use (e.g., expectancies, motives). Patients were interviewed about substance use, depression, and family history of alcohol and drug abuse. Self-report instruments measuring temperament, expectancies, and motives were completed. Participants were 147 male veterans admitted to inpatient substance abuse treatment at a U.S. Department of Veterans Affairs medical center. Cluster analysis identified four types of users with two high substance problem severity and two low substance problem severity groups. Two, high problem severity, early onset groups differed only on the cluster variable of negative affectivity (NA), but showed differences on antisocial personality characteristics, hypochondriasis, and coping motives for alcohol. The two low problem severity groups were distinguished by age of onset and positive affectivity (PA). The late onset, low PA group had a higher incidence of depression, a greater tendency to use substances in solitary contexts, and lower enhancement motives for alcohol compared to the early onset, high PA cluster. The four-cluster solution yielded more distinctions on external criteria than the two-cluster solution. Such temperament variation within both high and low severity substance abusers may be important for treatment planning.

Real-time dynamics of RNA Polymerase II clustering in live human cells

NASA Astrophysics Data System (ADS)

Cisse, Ibrahim

2014-03-01

Transcription is the first step in the central dogma of molecular biology, when genetic information encoded on DNA is made into messenger RNA. How this fundamental process occurs within living cells (in vivo) is poorly understood,[1] despite extensive biochemical characterizations with isolated biomolecules (in vitro). For high-order organisms, like humans, transcription is reported to be spatially compartmentalized in nuclear foci consisting of clusters of RNA Polymerase II, the enzyme responsible for synthesizing all messenger RNAs. However, little is known of when these foci assemble or their relative stability. We developed an approach based on photo-activation localization microscopy (PALM) combined with a temporal correlation analysis, which we refer to as tcPALM. The tcPALM method enables the real-time characterization of biomolecular spatiotemporal organization, with single-molecule sensitivity, directly in living cells.[2] Using tcPALM, we observed that RNA Polymerase II clusters form transiently, with an average lifetime of 5.1 (+/- 0.4) seconds. Stimuli affecting transcription regulation yielded orders of magnitude changes in the dynamics of the polymerase clusters, implying that clustering is regulated and plays a role in the cells ability to effect rapid response to external signals. Our results suggest that the transient crowding of enzymes may aid in rate-limiting steps of genome regulation.

Quantitative application of the primary progressive aphasia consensus criteria.

PubMed

Wicklund, Meredith R; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Whitwell, Jennifer L; Josephs, Keith A

2014-04-01

To determine how well the consensus criteria could classify subjects with primary progressive aphasia (PPA) using a quantitative speech and language battery that matches the test descriptions provided by the consensus criteria. A total of 105 participants with a neurodegenerative speech and language disorder were prospectively recruited and underwent neurologic, neuropsychological, and speech and language testing and MRI in this case-control study. Twenty-one participants with apraxia of speech without aphasia served as controls. Select tests from the speech and language battery were chosen for application of consensus criteria and cutoffs were employed to determine syndromic classification. Hierarchical cluster analysis was used to examine participants who could not be classified. Of the 84 participants, 58 (69%) could be classified as agrammatic (27%), semantic (7%), or logopenic (35%) variants of PPA. The remaining 31% of participants could not be classified. Of the unclassifiable participants, 2 clusters were identified. The speech and language profile of the first cluster resembled mild logopenic PPA and the second cluster semantic PPA. Gray matter patterns of loss of these 2 clusters of unclassified participants also resembled mild logopenic and semantic variants. Quantitative application of consensus PPA criteria yields the 3 syndromic variants but leaves a large proportion unclassified. Therefore, the current consensus criteria need to be modified in order to improve sensitivity.

Uptake of methanol on mixed HNO3/H2O clusters: An absolute pickup cross section

NASA Astrophysics Data System (ADS)

Pysanenko, A.; Lengyel, J.; Fárník, M.

2018-04-01

The uptake of atmospheric oxidized organics on acid clusters is relevant for atmospheric new particle formation. We investigate the pickup of methanol (CH3OH) on mixed nitric acid-water clusters (HNO3)M(H2O)N by a combination of mass spectrometry and cluster velocity measurements in a molecular beam. The mass spectra of the mixed clusters exhibit (HNO3)m(H2O)nH+ series with m = 0-3 and n = 0-12. In addition, CH3OH.(HNO3)m(H2O)nH+ series with very similar patterns appear in the spectra after the methanol pickup. The velocity measurements prove that the undoped (HNO3)m(H2O)nH+ mass peaks in the pickup spectra originate from the neutral (HNO3)M(H2O)N clusters which have not picked up any CH3OH molecule, i.e., methanol has not evaporated upon the ionization. Thus the fraction of the doped clusters can be determined and the mean pickup cross section can be estimated, yielding σs ¯ ≈ 20 Å2. This is compared to the lower estimate of the mean geometrical cross section σg ¯ ≈ 60 Å2 obtained from the theoretical cluster geometries. Thus the "size" of the cluster corresponding to the methanol pickup is at least 3-times smaller than its geometrical size. We have introduced a method which can yield the absolute pickup cross sections relevant to the generation and growth of atmospheric aerosols, as illustrated in the example of methanol and nitric acid clusters.

RNA-Seq Analysis Using De Novo Transcriptome Assembly as a Reference for the Salmon Louse Caligus rogercresseyi

PubMed Central

Gallardo-Escárate, Cristian; Valenzuela-Muñoz, Valentina; Nuñez-Acuña, Gustavo

2014-01-01

Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I–II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I–II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions. PMID:24691066

RNA-Seq analysis using de novo transcriptome assembly as a reference for the salmon louse Caligus rogercresseyi.

PubMed

Gallardo-Escárate, Cristian; Valenzuela-Muñoz, Valentina; Nuñez-Acuña, Gustavo

2014-01-01

Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I-II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I-II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions.

Supramolecular clusters between carbohydrates and concave pyridines. Detection in the gas phase by resonance-enhanced multi-photon ionization reflectron time-of-flight mass spectrometer.

PubMed

Liebig, Timo; Lüning, Ulrich; Grotemeyer, Jürgen

2006-01-01

For the first time the formation of supramolecular clusters between concave pyridines and different carbohydrates could be observed in the gas phase. The different clusters have been investigated by means of laser desorption into a supersonic beam followed by resonant multi photon excitation yielding mass spectra with high intensity of the different cluster. These preliminary results open a way for the investigations of the hydrogen bonds in these compounds.

Assessing Nutritional Differences in Household Level Production and Consumption in African Villages

NASA Astrophysics Data System (ADS)

Markey, K.; Palm, C.; Wood, S.

2015-12-01

Studies of agriculture often focus on yields and calories, but overlook the production of diverse nutrients needed for human health. Nutritional production is particularly important in low-income countries, where foods produced correspond largely to those consumed. Through an analysis of crops, livestock, and animal products, this study aims to quantify the nutritional differences between household-level production and consumption in the Millennium Village at Bonsaaso, Ghana. By converting food items into their nutritional components it became clear that certain nutritional disparities existed between the two categories. In Bonsasso, 64-78% of households exhibited deficiencies in the consumption of Calcium, Fat, and/or Vitamin A despite less than 30% of households showing deficiencies on the production side. To better understand these differences, k-means clustering analysis was performed, placing households into groups characterized by nutritional means. By comparing the households in these groupings, it was clear that clusters formed around certain nutritional deficiencies. The socioeconomic characteristics of these groupings were then studied for correlations, concentrating on number of people at the household, sex and age of household head, and dependency ratio. It was found that clusters with high dependency ratios (the number of working persons in the household to non-working persons) exhibited a large variety of, and often drastic, nutritional deficiencies. In fact, the cluster with the highest average dependency ratio exhibited deficiencies in every nutrient. In light of these findings, regional policies may look to target households with a large number of dependents, and package nutrients for household distribution based on the characteristics of these clusters.

Text Summarization Model based on Facility Location Problem

NASA Astrophysics Data System (ADS)

Takamura, Hiroya; Okumura, Manabu

e propose a novel multi-document generic summarization model based on the budgeted median problem, which is a facility location problem. The summarization method based on our model is an extractive method, which selects sentences from the given document cluster and generates a summary. Each sentence in the document cluster will be assigned to one of the selected sentences, where the former sentece is supposed to be represented by the latter. Our method selects sentences to generate a summary that yields a good sentence assignment and hence covers the whole content of the document cluster. An advantage of this method is that it can incorporate asymmetric relations between sentences such as textual entailment. Through experiments, we showed that the proposed method yields good summaries on the dataset of DUC'04.

Geolocalization of Influenza Outbreak Within an Acute Care Population: A Layered-Surveillance Approach.

PubMed

Kannan, Vijay Christopher; Hodgson, Nicole; Lau, Andrew; Goodin, Kate; Dugas, Andrea Freyer; LoVecchio, Frank

2016-11-01

We seek to use a novel layered-surveillance approach to localize influenza clusters within an acute care population. The first layer of this system is a syndromic surveillance screen to guide rapid polymerase chain reaction testing. The second layer is geolocalization and cluster analysis of these patients. We posit that any identified clusters could represent at-risk populations who could serve as high-yield targets for preventive medical interventions. This was a prospective observational surveillance study. Patients were screened with a previously derived clinical decision guideline that has a 90% sensitivity and 30% specificity for influenza. Patients received points for the following signs and symptoms within the past 7 days: cough (2 points), headache (1 point), subjective fever (1 point), and documented fever at triage (temperature >38°C [100.4°F]) (1 point). Patients scoring 3 points or higher were indicated for influenza testing. Patients were tested with Xpert Flu (Cepheid, Sunnyvale, CA), a rapid polymerase chain reaction test. Positive results were mapped with ArcGIS (ESRI, Redlands, CA) and analyzed with kernel density estimation to create heat maps. There were 1,360 patients tested with Xpert Flu with retrievable addresses within the greater Phoenix metro area. One hundred sixty-seven (12%) of them tested positive for influenza A and 23 (2%) tested positive for influenza B. The influenza A virus exhibited a clear cluster pattern within this patient population. The densest cluster was located in an approximately 1-square-mile region southeast of our hospital. Our layered-surveillance approach was effective in localizing a cluster of influenza A outbreak. This region may house a high-yield target population for public health intervention. Further collaborative efforts will be made between our hospital and the Maricopa County Department of Public Health to perform a series of community vaccination events before the next influenza season. We hope these efforts will ultimately serve to reduce the burden of this disease on our patient population, and that this system will serve as a framework for future investigations locating at-risk populations. Copyright © 2016 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Using Open Clusters to Trace the Local Milky Way Rotation Curve and Velocity Field

NASA Astrophysics Data System (ADS)

Frinchaboy, Peter M.; Majewski, S. R.

2006-12-01

Establishing the rotation curve of the Milky Way is one of the fundamental contributions needed to understand the Galaxy and its mass distribution. We have undertaken a systematic spectroscopic survey of open star clusters which can serve as tracers of Galactic disk dynamics. We report on our initial sample of 67 clusters for which the Hydra multi-fiber spectrographs on the WIYN and Blanco telescopes have delivered 1-2 km/s radial velocities (RVs) of many dozens of stars in the fields of each cluster, which are used to derive cluster membership and bulk cluster kinematics when combined with Tycho-2 proper motions. The clusters selected for study have a broad spatial distribution in order to be sensitive to the disk velocity field in all Galactic quadrants and across a Galactocentric radius range as much as 3.0 kpc from the solar circle. Through analysis of the cluster sample, we find (1) the rotation velocity of the LSR is 221 (+2,-4) km/s, (2) the local rotation curve is declining with radius having a slope of -9.0 km/s/kpc, (3) we find (using R_0 = 8.5 kpc) the following Galactic parameters: A = 17.0 km/s/kpc and B = -8.9 km/s/kpc, which yields a Galaxy mass within of 1.5 R_0 of M = 0.9 ± 0.2 x 10^11 solar masses and a M/L of 5.9 in solar units. We also explore the distribution of the local velocity field and find evidence for non-circular motion due to the sprial arms.

Geographic Clusters of Basal Cell Carcinoma in a Northern California Health Plan Population.

PubMed

Ray, G Thomas; Kulldorff, Martin; Asgari, Maryam M

2016-11-01

Rates of skin cancer, including basal cell carcinoma (BCC), the most common cancer, have been increasing over the past 3 decades. A better understanding of geographic clustering of BCCs can help target screening and prevention efforts. Present a methodology to identify spatial clusters of BCC and identify such clusters in a northern California population. This retrospective study used a BCC registry to determine rates of BCC by census block group, and used spatial scan statistics to identify statistically significant geographic clusters of BCCs, adjusting for age, sex, and socioeconomic status. The study population consisted of white, non-Hispanic members of Kaiser Permanente Northern California during years 2011 and 2012. Statistically significant geographic clusters of BCC as determined by spatial scan statistics. Spatial analysis of 28 408 individuals who received a diagnosis of at least 1 BCC in 2011 or 2012 revealed distinct geographic areas with elevated BCC rates. Among the 14 counties studied, BCC incidence ranged from 661 to 1598 per 100 000 person-years. After adjustment for age, sex, and neighborhood socioeconomic status, a pattern of 5 discrete geographic clusters emerged, with a relative risk ranging from 1.12 (95% CI, 1.03-1.21; P = .006) for a cluster in eastern Sonoma and northern Napa Counties to 1.40 (95% CI, 1.15-1.71; P < .001) for a cluster in east Contra Costa and west San Joaquin Counties, compared with persons residing outside that cluster. In this study of a northern California population, we identified several geographic clusters with modestly elevated incidence of BCC. Knowledge of geographic clusters can help inform future research on the underlying etiology of the clustering including factors related to the environment, health care access, or other characteristics of the resident population, and can help target screening efforts to areas of highest yield.

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

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

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

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

HUBBLE OPENS ITS EYE ON THE UNIVERSE AND CAPTURES A COSMIC MAGNIFYING GLASS

NASA Technical Reports Server (NTRS)

2002-01-01

Scanning the heavens for the first time since the successful December 1999 servicing mission, NASA's Hubble Space Telescope has imaged a giant, cosmic magnifying glass, a massive cluster of galaxies called Abell 2218. This 'hefty' cluster resides in the constellation Draco, some 2 billion light-years from Earth. The cluster is so massive that its enormous gravitational field deflects light rays passing through it, much as an optical lens bends light to form an image. This phenomenon, called gravitational lensing, magnifies, brightens, and distorts images from faraway objects. The cluster's magnifying powers provides a powerful 'zoom lens' for viewing distant galaxies that could not normally be observed with the largest telescopes. This useful phenomenon has produced the arc-shaped patterns found throughout the Hubble picture. These 'arcs' are the distorted images of very distant galaxies, which lie 5 to 10 times farther than the lensing cluster. This distant population existed when the universe was just a quarter of its present age. Through gravitational lensing these remote objects are magnified, enabling scientists to study them in more detail. This analysis provides a direct glimpse of how star-forming regions are distributed in remote galaxies and yields other clues to the early evolution of galaxies. The picture is dominated by spiral and elliptical galaxies. Resembling a string of tree lights, the biggest and brightest galaxies are members of the foreground cluster. Researchers are intrigued by a tiny red dot just left of top center. This dot may be an extremely remote object made visible by the cluster's magnifying powers. Further investigation is needed to confirm the object's identity. The Hubble telescope first viewed this cluster in 1994, producing one of the most spectacular demonstrations of gravitational lensing up to that time. Scientists who analyzed that black-and-white picture discovered more than 50 remote, young galaxies. Hubble's latest multicolor image of the cluster will allow astronomers to probe in greater detail the internal structure of these early galaxies. The color picture already reveals several arc-shaped features that are embedded in the cluster and cannot be easily seen in the black-and-white image. The colors in this picture yield clues to the ages, distances, and temperatures of stars, the stuff of galaxies. Blue pinpoints hot young stars. The yellow-white color of several of the galaxies represents the combined light of many stars. Red identifies cool stars, old stars, and the glow of stars in distant galaxies. This view is only possible by combining Hubble's unique image quality with the rare lensing effect provided by the magnifying cluster. The picture was taken Jan. 11 to 13, 2000, with the Wide Field and Planetary Camera 2. Credits: NASA, Andrew Fruchter (STScI), and the ERO team (STScI, ST-ECF)

The open cluster IC 4665

NASA Technical Reports Server (NTRS)

Prosser, Charles F.

1993-01-01

The results of a combined astrometric, photometric, and spectroscopic program to identify members of the open cluster IC 4665 are presented. Numerous new proper motion/photometric candidate members and at least 23 M dwarfs with H-alpha emission have been identified. A reanalysis of IC 4665 age using different methods yields conflicting results ranging from about 3 X 10 exp 7 yr to the age of the Pleiades. This study provides a list of candidate cluster members in the intermediate and low-mass regime of this cluster. Future spectroscopic observations of these candidates should eventually identify true cluster members.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

Photochemistry of 1- and 2-Naphthols and Their Water Clusters: The Role of 1 ππ*(La ) Mediated Hydrogen Transfer to Carbon Atoms.

PubMed

Novak, Jurica; Prlj, Antonio; Basarić, Nikola; Corminboeuf, Clémence; Došlić, Nađa

2017-06-16

The computational analysis of the isomer- and conformer-dependent photochemistry of 1- and 2-naphthols and their microsolvated water clusters is motivated by their very different excited state reactivities. We present evidence that 1- and 2-naphthol follow distinct excited state deactivation pathways. The deactivation of 2-naphthols, 2-naphthol water clusters, as well as of the anti conformer of 1-naphthol is mediated by the optically dark 1 πσ* state. The dynamics of the 1 πσ* surface leads to the homolytic cleavage of the OH bond. On the contrary, the excited state deactivation of syn 1-naphthol and 1-naphthol water clusters follows an uncommon reaction pathway. Upon excitation to the bright 1 ππ*(L a ) state, a highly specific excited state hydrogen transfer (ESHT) to carbon atoms C8 and C5 takes place, yielding 1,8- and 1,5-naphthoquinone methides. The ESHT pathway arises from the intrinsic electronic properties of the 1 ππ*(L a ) state of 1-naphthols. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Energetic ion bombardment of Ag surfaces by C60+ and Ga+ projectiles.

PubMed

Sun, Shixin; Szakal, Christopher; Winograd, Nicholas; Wucher, Andreas

2005-10-01

The ion bombardment-induced release of particles from a metal surface is investigated using energetic fullerene cluster ions as projectiles. The total sputter yield as well as partial yields of neutral and charged monomers and clusters leaving the surface are measured and compared with corresponding data obtained with atomic projectile ions of similar impact kinetic energy. It is found that all yields are enhanced by about one order of magnitude under bombardment with the C60+ cluster projectiles compared with Ga+ ions. In contrast, the electronic excitation processes determining the secondary ion formation probability are unaffected. The kinetic energy spectra of sputtered particles exhibit characteristic differences which reflect the largely different nature of the sputtering process for both types of projectiles. In particular, it is found that under C60+ impact (1) the energy spectrum of sputtered atoms peaks at significantly lower kinetic energies than for Ga+ bombardment and (2) the velocity spectra of monomers and dimers are virtually identical, a finding which is in pronounced contrast to all published data obtained for atomic projectiles. The experimental findings are in reasonable agreement with recent molecular dynamics simulations.

Characterization of [4Fe-4S]-containing and cluster-free forms of Streptomyces WhiD

PubMed Central

Crack, Jason C.; den Hengst, Chris D.; Jakimowicz, Piotr; Subramanian, Sowmya; Johnson, Michael K.; Buttner, Mark J.; Thomson, Andrew J.; Le Brun, Nick E.

2009-01-01

WhiD, a member of the WhiB-like (Wbl) family of iron-sulfur proteins found exclusively within the actinomycetes, is required for the late stages of sporulation in Streptomyces coelicolor. Like all other Wbl proteins, WhiD has not so far been purified in a soluble form that contains a significant amount of cluster and characterization has relied on cluster-reconstituted protein. Thus, a major goal in Wbl research is to obtain and characterize native protein containing iron-sulfur clusters. Here we report the analysis of S. coelicolor WhiD purified anaerobically from E. coli as a soluble protein containing a single [4Fe-4S]2+ cluster ligated by four cysteines. Upon exposure to oxygen, spectral features associated with the [4Fe-4S] cluster were lost in a slow reaction that unusually yielded apo-WhiD directly without significant concentrations of cluster intermediates. This process was found to be highly pH dependent with an optimal stability observed between pH 7.0 and 8.0. Low molecular weight thiols, including a mycothiol analogue and thioredoxin, exerted a small but significant protective effect against WhiD cluster loss, an activity that could be of physiological importance. [4Fe-4S]2+ WhiD was found to react much more rapidly with superoxide than with either oxygen or hydrogen peroxide, which may also be of physiological significance. Loss of the [4Fe-4S] cluster to form apo-protein destabilized the protein fold significantly, but did not lead to complete unfolding. Finally, apo-WhiD exhibited negligible activity in an insulin-based disulfide reductase assay demonstrating that it does not function as a general protein disulfide reductase. PMID:19954209

Thermal and log-normal distributions of plasma in laser driven Coulomb explosions of deuterium clusters

NASA Astrophysics Data System (ADS)

Barbarino, M.; Warrens, M.; Bonasera, A.; Lattuada, D.; Bang, W.; Quevedo, H. J.; Consoli, F.; de Angelis, R.; Andreoli, P.; Kimura, S.; Dyer, G.; Bernstein, A. C.; Hagel, K.; Barbui, M.; Schmidt, K.; Gaul, E.; Donovan, M. E.; Natowitz, J. B.; Ditmire, T.

2016-08-01

In this work, we explore the possibility that the motion of the deuterium ions emitted from Coulomb cluster explosions is highly disordered enough to resemble thermalization. We analyze the process of nuclear fusion reactions driven by laser-cluster interactions in experiments conducted at the Texas Petawatt laser facility using a mixture of D2+3He and CD4+3He cluster targets. When clusters explode by Coulomb repulsion, the emission of the energetic ions is “nearly” isotropic. In the framework of cluster Coulomb explosions, we analyze the energy distributions of the ions using a Maxwell-Boltzmann (MB) distribution, a shifted MB distribution (sMB), and the energy distribution derived from a log-normal (LN) size distribution of clusters. We show that the first two distributions reproduce well the experimentally measured ion energy distributions and the number of fusions from d-d and d-3He reactions. The LN distribution is a good representation of the ion kinetic energy distribution well up to high momenta where the noise becomes dominant, but overestimates both the neutron and the proton yields. If the parameters of the LN distributions are chosen to reproduce the fusion yields correctly, the experimentally measured high energy ion spectrum is not well represented. We conclude that the ion kinetic energy distribution is highly disordered and practically not distinguishable from a thermalized one.

A very large ( θ E ≳ 40") strong gravitational lens selected with the Sunyaev–Zel’dovich effect: PLCK G287.0+32.9 ( z = 0.38)

DOE PAGES

Zitrin, Adi; Seitz, Stella; Monna, Anna; ...

2017-04-10

Since galaxy clusters sit at the high end of the mass function, the number of galaxy clusters both massive and concentrated enough to yield particularly large Einstein radii poses useful constraints on cosmological and structure formation models. To date, less than a handful of clusters are known to have Einstein radii exceedingmore » $$\\sim 40^{\\prime\\prime} $$ (for a source at $${z}_{s}\\simeq 2$$, nominally). Here, we report an addition to that list of the Sunyaev–Zel'dovich (SZ) selected cluster, PLCK G287.0+32.9 (z = 0.38), the second-highest SZ-mass (M 500) cluster from the Planck catalog. We present the first strong-lensing analysis of the cluster, identifying 20 sets of multiply imaged galaxies and candidates in new Hubble Space Telescope ( HST) data, including a long, $$l\\sim 22^{\\prime\\prime} $$ giant arc, as well as a quadruply imaged, apparently bright (magnified to $${J}_{{\\rm{F}}110{\\rm{W}}}=25.3$$ AB), likely high-redshift dropout galaxy at $${z}_{\\mathrm{phot}}=6.90$$ [6.13–8.43] (95% C.I.). Our analysis reveals a very large critical area (1.55 arcmin2, $${z}_{s}\\simeq 2$$), corresponding to an effective Einstein radius of $${\\theta }_{{\\rm{E}}}\\sim 42^{\\prime\\prime} $$. Furthermore, the model suggests the critical area will expand to 2.58 arcmin2 ($${\\theta }_{{\\rm{E}}}\\sim 54^{\\prime\\prime} $$) for sources at $${z}_{s}\\sim 10$$. Our work adds to recent efforts to model very massive clusters toward the launch of the James Webb Space Telescope, in order to identify the most useful cosmic lenses for studying the early universe. Spectroscopic redshifts for the multiply imaged galaxies and additional HST data will be necessary for refining the lens model and verifying the nature of the $$z\\sim 7$$ dropout.« less

A very large ( θ E ≳ 40") strong gravitational lens selected with the Sunyaev–Zel’dovich effect: PLCK G287.0+32.9 ( z = 0.38)

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

Zitrin, Adi; Seitz, Stella; Monna, Anna

Since galaxy clusters sit at the high end of the mass function, the number of galaxy clusters both massive and concentrated enough to yield particularly large Einstein radii poses useful constraints on cosmological and structure formation models. To date, less than a handful of clusters are known to have Einstein radii exceedingmore » $$\\sim 40^{\\prime\\prime} $$ (for a source at $${z}_{s}\\simeq 2$$, nominally). Here, we report an addition to that list of the Sunyaev–Zel'dovich (SZ) selected cluster, PLCK G287.0+32.9 (z = 0.38), the second-highest SZ-mass (M 500) cluster from the Planck catalog. We present the first strong-lensing analysis of the cluster, identifying 20 sets of multiply imaged galaxies and candidates in new Hubble Space Telescope ( HST) data, including a long, $$l\\sim 22^{\\prime\\prime} $$ giant arc, as well as a quadruply imaged, apparently bright (magnified to $${J}_{{\\rm{F}}110{\\rm{W}}}=25.3$$ AB), likely high-redshift dropout galaxy at $${z}_{\\mathrm{phot}}=6.90$$ [6.13–8.43] (95% C.I.). Our analysis reveals a very large critical area (1.55 arcmin2, $${z}_{s}\\simeq 2$$), corresponding to an effective Einstein radius of $${\\theta }_{{\\rm{E}}}\\sim 42^{\\prime\\prime} $$. Furthermore, the model suggests the critical area will expand to 2.58 arcmin2 ($${\\theta }_{{\\rm{E}}}\\sim 54^{\\prime\\prime} $$) for sources at $${z}_{s}\\sim 10$$. Our work adds to recent efforts to model very massive clusters toward the launch of the James Webb Space Telescope, in order to identify the most useful cosmic lenses for studying the early universe. Spectroscopic redshifts for the multiply imaged galaxies and additional HST data will be necessary for refining the lens model and verifying the nature of the $$z\\sim 7$$ dropout.« less

Relative age of Camelot crater and crater clusters near the Apollo 17 landing site

USGS Publications Warehouse

Lucchitta, B.K.

1979-01-01

Topographic profiles and depth-diameter ratios from the crater Camelot and craters of the central cluster in the Apollo 17 landing area suggest that these craters are of the same age. Therefore, layers that can be recognized in the deep-drill core and that can be identified as ejecta deposits from Camelot or from the cluster craters should yield similar emplacement ages. ?? 1979.

Crop Loss Relationships and Economic Injury Levels for Ferrisia gilli (Hemiptera: Pseudococcidae) Infesting Pistachio in California.

PubMed

Haviland, David R; Beede, Robert H; Daane, Kent M

2015-12-01

Ferrisia gilli Gullan (Hemiptera: Pseudococcidae) is a new pest in California pistachios, Pistacea vera L. We conducted a 3-yr field study to determine the type and amount of damage caused by F. gilli. Using pesticides, we established gradients of F. gilli densities in a commercial pistachio orchard near Tipton, CA, from 2005 to 2007. Each year, mealybug densities on pistachio clusters were recorded from May through September and cumulative mealybug-days were determined. At harvest time, nut yield per tree (5% dried weight) was determined, and subsamples of nuts were evaluated for market quality. Linear regression analysis of cumulative mealybug-days against fruit yield and nut quality measurements showed no relationships in 2005 and 2006, when mealybug densities were moderate. However, in 2007, when mealybug densities were very high, there was a negative correlation with yield (for every 1,000 mealybug-days, there was a decrease in total dry weight per tree of 0.105 kg) and percentage of split unstained nuts (for every 1,000 mealybug-days, there was a decrease in the percentage of split unstained of 0.560%), and a positive correlation between the percentage of closed kernel and closed blank nuts (for every 1,000 mealybug-days, there is an increase in the percentage of closed kernel and closed blank of 0.176 and 0.283%, respectively). The data were used to determine economic injury levels, showing that for each mealybug per cluster in May there was a 4.73% reduction in crop value associated with quality and a 0.866 kg reduction in yield per tree (4.75%). © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Iron-sulfur cluster disassembly in the FNR protein of Escherichia coli by O2: [4Fe-4S] to [2Fe-2S] conversion with loss of biological activity

PubMed Central

Khoroshilova, Natalia; Popescu, Codrina; Münck, Eckard; Beinert, Helmut; Kiley, Patricia J.

1997-01-01

The transcription factor FNR (fumarate nitrate reduction) requires the presence of an iron-sulfur (Fe-S) cluster for its function as a global transcription regulator in Escherichia coli when oxygen becomes scarce. To define the oxidation state and type of Fe-S cluster present in the active form of FNR, we have studied anaerobically purified FNR with Mössbauer spectroscopy. Our data showed that this form of FNR contained a [4Fe-4S]2+ cluster (δ = 0.45 mm/s; ΔEQ = 1.22 mm/s) and that the [4Fe-4S]2+ cluster was rapidly destroyed on exposure of FNR to air. Under these conditions, the yellow–green active form of FNR turned deep red; analysis of sulfide indicated that 70% of the labile sulfide was still present, suggesting that the Fe-S cluster had been converted into a different form. Little [3Fe-4S] cluster was, however, detected by EPR. According to Mössbauer spectroscopy, the [4Fe-4S]2+ cluster was converted in about 60% yield to a [2Fe-2S]2+ cluster (δ = 0.28 mm/s; ΔEQ = 0.58 mm/s) following 17 min of exposure to air. The [2Fe-2S]2+ cluster form of FNR was much more stable to oxygen, but was unable to sustain biological activity (e.g., DNA binding). However, DNA binding and the absorption spectrum characteristic of the [4Fe-4S]2+ cluster could be largely restored from the [2Fe-2S]2+ form when Cys, Fe, DTT, and the NifS protein were added. It has yet to be determined whether the form of FNR containing the [2Fe-2S]2+ cluster has any biological significance, e.g., as an in vivo intermediate that is more rapidly converted to the active form than the apoprotein. PMID:9177174

Elastic scattering of ^4He by ^6Li at E(^4He) = 24, 25, and 26 MeV

NASA Astrophysics Data System (ADS)

Bartosz, E. E.; Cathers, P. D.; Kemper, K. W.; Maréchal, F.; Rusek, K.

1998-11-01

A previous optical model analysis of the elastic scattering of ^4He by ^6Li at E(^4He) = 18.5 MeV (P. V. Green, K. W. Kemper, P. L. Kerr, K. Mohajeri, E. G. Myers, D. Robson, K. Rusek and I. J. Thompson, Phys. Rev. C 53) 2862 (1996)., as well as a cluster-folded continuum- discretized coupled channels analysis (K. Rusek, P. V. Green, P. L. Kerr, and K. W. Kemper, Phys. Rev. C 56) 1895 (1997)., resulted in a good description of the data set, but the optical model analysis yielded a poor description of the 25 MeV elastic scattering data measured at the same time. New elastic and inelastic scattering angular distribution cross sections are reported for ^4He + ^6Li at E(^4He) = 24, 25 and 26 MeV. Three energies were used to rule out anomalous scattering at 25 MeV. The results of a cluster-folded continuum- discretized coupled channels analysis similar to that used with the 18.5 MeV data are presented for the three new data sets at 24, 25, and 26 MeV.

Development and Application of Transcriptome-Derived Microsatellites in Actinidia eriantha (Actinidiaceae)

PubMed Central

Guo, Rui; Landis, Jacob B.; Moore, Michael J.; Meng, Aiping; Jian, Shuguang; Yao, Xiaohong; Wang, Hengchang

2017-01-01

Actinidia eriantha Benth. is a diploid perennial woody vine native to China and is recognized as a valuable species for commercial kiwifruit improvement with high levels of ascorbic acid as well as having been used in traditional Chinese medicine. Due to the lack of genomic resources for the species, microsatellite markers for population genetics studies are scarce. In this study, RNASeq was conducted on fruit tissue of A. eriantha, yielding 5,678,129 reads with a total output of 3.41 Gb. De novo assembly yielded 69,783 non-redundant unigenes (41.3 Mb), of which 21,730 were annotated using protein databases. A total of 8,658 EST-SSR loci were identified in 7,495 unigene sequences, for which primer pairs were successfully designed for 3,842 loci (44.4%). Among these, 183 primer pairs were assayed for PCR amplification, yielding 69 with detectable polymorphism in A. eriantha. Additionally, 61 of the 69 polymorphic loci could be successfully amplified in at least one other Actinidia species. Of these, 14 polymorphic loci (mean NA = 6.07 ± 2.30) were randomly selected for assessing levels of genetic diversity and population structure within A. eriantha. Finally, a neighbor-joining tree and Bayesian clustering analysis showed distinct clustering into two groups (K = 2), agreeing with the geographical distributions of these populations. Overall, our results will facilitate further studies of genetic diversity within A. eriantha and will aid in discriminating outlier loci involved in local adaptation. PMID:28890721

Statistical mixture design selective extraction of compounds with antioxidant activity and total polyphenol content from Trichilia catigua.

PubMed

Lonni, Audrey Alesandra Stinghen Garcia; Longhini, Renata; Lopes, Gisely Cristiny; de Mello, João Carlos Palazzo; Scarminio, Ieda Spacino

2012-03-16

Statistical design mixtures of water, methanol, acetone and ethanol were used to extract material from Trichilia catigua (Meliaceae) barks to study the effects of different solvents and their mixtures on its yield, total polyphenol content and antioxidant activity. The experimental results and their response surface models showed that quaternary mixtures with approximately equal proportions of all four solvents provided the highest yields, total polyphenol contents and antioxidant activities of the crude extracts followed by ternary design mixtures. Principal component and hierarchical clustering analysis of the HPLC-DAD spectra of the chromatographic peaks of 1:1:1:1 water-methanol-acetone-ethanol mixture extracts indicate the presence of cinchonains, gallic acid derivatives, natural polyphenols, flavanoids, catechins, and epicatechins. Copyright © 2011 Elsevier B.V. All rights reserved.

Integrin {alpha}{beta}1, {alpha}{sub v}{beta}, {alpha}{sub 6}{beta} effectors p130Cas, Src and talin regulate carcinoma invasion and chemoresistance

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

Sansing, Hope A.; Sarkeshik, Ali; Yates, John R.

2011-03-11

Research highlights: {yields} Proteomics of clustered integrin {alpha}{beta}1, {alpha}{sub v}{beta}, {alpha}{sub 6}{beta} receptors in oral carcinoma. {yields} p130Cas, Dek, Src and talin regulate oral carcinoma invasion. {yields} p130Cas, talin, Src and zyxin regulate oral carcinoma resistance to cisplatin. -- Abstract: Ligand engagement by integrins induces receptor clustering and formation of complexes at the integrin cytoplasmic face that controls cell signaling and cytoskeletal dynamics critical for adhesion-dependent processes. This study searches for a subset of integrin effectors that coordinates both tumor cell invasion and resistance to the chemotherapeutic drug cisplatin in oral carcinomas. Candidate integrin effectors were identified in a proteomicsmore » screen of proteins recruited to clustered integrin {alpha}{beta}1, {alpha}{sub v}{beta} or {alpha}{sub 6}{beta} receptors in oral carcinomas. Proteins with diverse functions including microtubule and actin binding proteins, and factors involved in trafficking, transcription and translation were identified in oral carcinoma integrin complexes. Knockdown of effectors in the oral carcinoma HN12 cells revealed that p130Cas, Dek, Src and talin were required for invasion through Matrigel. Disruption of talin or p130Cas by RNA interference increased resistance to cisplatin, whereas targeting Dek, Src or zyxin reduced HN12 resistance to cisplatin. Analysis of the spreading of HN12 cells on collagen I and laminin I revealed that a decrease in p130Cas or talin expression inhibited spreading on both matrices. Interestingly, a reduction in zyxin expression enhanced spreading on laminin I and inhibited spreading on collagen I. Reduction of Dek, Src, talin or zyxin expression reduced HN12 proliferation by 30%. Proliferation was not affected by a reduction in p130Cas expression. We conclude that p130Cas, Src and talin function in both oral carcinoma invasion and resistance to cisplatin.« less

Membership and Coronal Activity in the NGC 2232 and Cr 140 Open Clusters

NASA Technical Reports Server (NTRS)

Patten, Brian M.; Oliversen, Ronald J. (Technical Monitor)

2001-01-01

This is the second annual performance report for our grant "Membership and Coronal Activity in the NGC 2232 and Cr 140 Open Clusters." We propose to identify X-ray sources and extract net source counts in 8 archival ROSAT HRI images in the regions of the NGC 2232 and Cr 140 open clusters. These X-ray data will be combined with ground-based photometry and spectroscopy in order to identify G, K, and early-M type cluster members. At present, no members later than approximately F5 are currently known for either cluster. With ages of approximately 25 Myr and at a distance of just 320 - 360 pc, the combined late-type membership of the NGC 2232 and Cr 140 clusters will yield an almost unique sample of solar-type stars in the post-T Tauri/pre-main sequence phase of evolution. These stars will be used to assess the level and dispersion in coronal activity levels, as part of a probe of the importance of magnetic braking and the level of magnetic dynamo activity, for solar-type stars just before they reach the ZAMS. Over the past year we have successfully acquired all of the ground-based data necessary to support the analysis of the archival ROSAT X-ray data in the regions around both of these clusters. By the end of 2001 we expect to have completed the reduction and analysis of the ground-based photometry and spectroscopy and will begin the integration of these data with the ROSAT X-ray data. A certain amount of pressure to complete the work on NGC 2232 is coming from the SIRTF project, as this cluster may be a key component to a circumstellar disk evolution GTO program. We are only too happy to try to help and have worked to speed the analysis as much as possible. The primary activity to be undertaken in the next few months is the integration of the groundbased photometry and spectroscopy with the archival ROSAT X-ray data and then writing the paper summarizing our results. The most time consuming portion of this next phase is, of course, seeing the paper through publication in a peer-reviewed journal. Therefore, we have requested a no-cost extension to the grant to allow us to bring this project to a conclusion.

Structural and magnetic evolution of bimetallic MnAu clusters driven by asymmetric atomic migration.

PubMed

Wei, Xiaohui; Zhou, Rulong; Lefebvre, Williams; He, Kai; Le Roy, Damien; Skomski, Ralph; Li, Xingzhong; Shield, Jeffrey E; Kramer, Matthew J; Chen, Shuang; Zeng, Xiao Cheng; Sellmyer, David J

2014-03-12

The nanoscale structural, compositional, and magnetic properties are examined for annealed MnAu nanoclusters. The MnAu clusters order into the L1(0) structure, and monotonic size-dependences develop for the composition and lattice parameters, which are well reproduced by our density functional theory calculations. Simultaneously, Mn diffusion forms 5 Å nanoshells on larger clusters inducing significant magnetization in an otherwise antiferromagnetic system. The differing atomic mobilities yield new cluster nanostructures that can be employed generally to create novel physical properties.

Prediction of tautomer ratios by embedded-cluster integral equation theory

NASA Astrophysics Data System (ADS)

Kast, Stefan M.; Heil, Jochen; Güssregen, Stefan; Schmidt, K. Friedemann

2010-04-01

The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol-1) as well as for the full set of quantitative reaction data (2.0 kcal mol-1) among the SAMPL2 participants.

Bridging Zirconia Nodes within a Metal–Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires

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

Platero-Prats, Ana E.; League, Aaron B.; Bernales, Varinia

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis and differencemore » envelope density analysis, with electron microscopy imag-ing and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO xH y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield hetero-bimetallic metal-oxo nanowires. Finally, this bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering-resistance of these clusters during the hydrogenation of light olefins.« less

Bridging Zirconia Nodes within a Metal-Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires.

PubMed

Platero-Prats, Ana E; League, Aaron B; Bernales, Varinia; Ye, Jingyun; Gallington, Leighanne C; Vjunov, Aleksei; Schweitzer, Neil M; Li, Zhanyong; Zheng, Jian; Mehdi, B Layla; Stevens, Andrew J; Dohnalkova, Alice; Balasubramanian, Mahalingam; Farha, Omar K; Hupp, Joseph T; Browning, Nigel D; Fulton, John L; Camaioni, Donald M; Lercher, Johannes A; Truhlar, Donald G; Gagliardi, Laura; Cramer, Christopher J; Chapman, Karena W

2017-08-02

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis, and difference envelope density analysis, with electron microscopy imaging and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO x H y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield heterobimetallic metal-oxo nanowires. This bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering resistance of these clusters during the hydrogenation of light olefins.

Anatomy of a Merger: A Deep Chandra Observation of Abell 115

NASA Astrophysics Data System (ADS)

Forman, William R.

2017-08-01

A deep Chandra observation of Abell 115 provides a unique probe of the anatomy of cluster mergers. The X-ray image shows two prominent subclusters, A115N (north) and A115S (south) with a projected separation of almost 1 Mpc. The X-ray subclusters each have ram-pressure stripped tails that unambiguously indicate the directions of motion. The central BCG of A115N hosts the radio source 3C28 which shows a pair of jets, almost perpendicular to the direction of the sucluster's motion. The jets terminate in lobes each of which has a "tail" pointing IN the direction of motion of the subcluster. The Chandra analysis provides details of the merger including the velocities of the subclusters both through analysis of the cold front and a weak shock. The motion of A115N through the cluster generates counter-rotating vortices in the subcluster gas that form the two radio tails. Hydrodynamic modeling yields circulation velocities within the A115N sub cluster. Thus, the radio emitting plasma acts as a dye tracing the motions of the X-ray emitting plasma. A115S shows two "cores", one coincident with the BCG and a second appears as a ram pressure stripped tail.

Bridging Zirconia Nodes within a Metal–Organic Framework via Catalytic Ni-Hydroxo Clusters to Form Heterobimetallic Nanowires

DOE PAGES

Platero-Prats, Ana E.; League, Aaron B.; Bernales, Varinia; ...

2017-07-11

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. Notably, atomic layer deposition (ALD) in MOFs has recently emerged as a versatile approach to functionalize MOF surfaces with a wide variety of catalytic metal-oxo species. Understanding the structure of newly deposited species and how they are tethered within the MOF is critical to understanding how these components couple to govern the active material properties. By combining local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis and differencemore » envelope density analysis, with electron microscopy imag-ing and computational modeling, we resolve the precise atomic structure of metal-oxo species deposited in the MOF NU-1000 through ALD. These analyses demonstrate that deposition of NiO xH y clusters occurs selectively within the smallest pores of NU-1000, between the zirconia nodes, serving to connect these nodes along the c-direction to yield hetero-bimetallic metal-oxo nanowires. Finally, this bridging motif perturbs the NU-1000 framework structure, drawing the zirconia nodes closer together, and also underlies the sintering-resistance of these clusters during the hydrogenation of light olefins.« less

A reanalysis of cluster randomized trials showed interrupted time-series studies were valuable in health system evaluation.

PubMed

Fretheim, Atle; Zhang, Fang; Ross-Degnan, Dennis; Oxman, Andrew D; Cheyne, Helen; Foy, Robbie; Goodacre, Steve; Herrin, Jeph; Kerse, Ngaire; McKinlay, R James; Wright, Adam; Soumerai, Stephen B

2015-03-01

There is often substantial uncertainty about the impacts of health system and policy interventions. Despite that, randomized controlled trials (RCTs) are uncommon in this field, partly because experiments can be difficult to carry out. An alternative method for impact evaluation is the interrupted time-series (ITS) design. Little is known, however, about how results from the two methods compare. Our aim was to explore whether ITS studies yield results that differ from those of randomized trials. We conducted single-arm ITS analyses (segmented regression) based on data from the intervention arm of cluster randomized trials (C-RCTs), that is, discarding control arm data. Secondarily, we included the control group data in the analyses, by subtracting control group data points from intervention group data points, thereby constructing a time series representing the difference between the intervention and control groups. We compared the results from the single-arm and controlled ITS analyses with results based on conventional aggregated analyses of trial data. The findings were largely concordant, yielding effect estimates with overlapping 95% confidence intervals (CI) across different analytical methods. However, our analyses revealed the importance of a concurrent control group and of taking baseline and follow-up trends into account in the analysis of C-RCTs. The ITS design is valuable for evaluation of health systems interventions, both when RCTs are not feasible and in the analysis and interpretation of data from C-RCTs. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A clustering approach for the analysis of solar energy yields: A case study for concentrating solar thermal power plants

NASA Astrophysics Data System (ADS)

Peruchena, Carlos M. Fernández; García-Barberena, Javier; Guisado, María Vicenta; Gastón, Martín

2016-05-01

The design of Concentrating Solar Thermal Power (CSTP) systems requires a detailed knowledge of the dynamic behavior of the meteorology at the site of interest. Meteorological series are often condensed into one representative year with the aim of data volume reduction and speeding-up of energy system simulations, defined as Typical Meteorological Year (TMY). This approach seems to be appropriate for rather detailed simulations of a specific plant; however, in previous stages of the design of a power plant, especially during the optimization of the large number of plant parameters before a final design is reached, a huge number of simulations are needed. Even with today's technology, the computational effort to simulate solar energy system performance with one year of data at high frequency (as 1-min) may become colossal if a multivariable optimization has to be performed. This work presents a simple and efficient methodology for selecting number of individual days able to represent the electrical production of the plant throughout the complete year. To achieve this objective, a new procedure for determining a reduced set of typical weather data in order to evaluate the long-term performance of a solar energy system is proposed. The proposed methodology is based on cluster analysis and permits to drastically reduce computational effort related to the calculation of a CSTP plant energy yield by simulating a reduced number of days from a high frequency TMY.

An Information-Theoretic-Cluster Visualization for Self-Organizing Maps.

PubMed

Brito da Silva, Leonardo Enzo; Wunsch, Donald C

2018-06-01

Improved data visualization will be a significant tool to enhance cluster analysis. In this paper, an information-theoretic-based method for cluster visualization using self-organizing maps (SOMs) is presented. The information-theoretic visualization (IT-vis) has the same structure as the unified distance matrix, but instead of depicting Euclidean distances between adjacent neurons, it displays the similarity between the distributions associated with adjacent neurons. Each SOM neuron has an associated subset of the data set whose cardinality controls the granularity of the IT-vis and with which the first- and second-order statistics are computed and used to estimate their probability density functions. These are used to calculate the similarity measure, based on Renyi's quadratic cross entropy and cross information potential (CIP). The introduced visualizations combine the low computational cost and kernel estimation properties of the representative CIP and the data structure representation of a single-linkage-based grouping algorithm to generate an enhanced SOM-based visualization. The visual quality of the IT-vis is assessed by comparing it with other visualization methods for several real-world and synthetic benchmark data sets. Thus, this paper also contains a significant literature survey. The experiments demonstrate the IT-vis cluster revealing capabilities, in which cluster boundaries are sharply captured. Additionally, the information-theoretic visualizations are used to perform clustering of the SOM. Compared with other methods, IT-vis of large SOMs yielded the best results in this paper, for which the quality of the final partitions was evaluated using external validity indices.

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

DOE PAGES

Palmese, A.; Lahav, O.; Banerji, M.; ...

2016-08-20

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (5 filters) with those from the Hubble Space Telescope CLASH (17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25% of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysismore » of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f*=7.0+-2.2x10^-3 within a radius of r_200c~3 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both datasets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ~100 000 clusters that will be observed within this survey. The stacking of all the DES clusters would reduce the errors on f* estimates and deduce important information about galaxy evolution.« less

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

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

Palmese, A.; Lahav, O.; Banerji, M.

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (5 filters) with those from the Hubble Space Telescope CLASH (17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25% of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysismore » of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f*=7.0+-2.2x10^-3 within a radius of r_200c~3 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both datasets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ~100 000 clusters that will be observed within this survey. The stacking of all the DES clusters would reduce the errors on f* estimates and deduce important information about galaxy evolution.« less

Clinical Subtypes of Dementia with Lewy Bodies Based on the Initial Clinical Presentation.

PubMed

Morenas-Rodríguez, Estrella; Sala, Isabel; Subirana, Andrea; Pascual-Goñi, Elba; Sánchez-Saudinós, MaBelén; Alcolea, Daniel; Illán-Gala, Ignacio; Carmona-Iragui, María; Ribosa-Nogué, Roser; Camacho, Valle; Blesa, Rafael; Fortea, Juan; Lleó, Alberto

2018-06-04

Dementia with Lewy bodies (DLB) is a heterogeneous disease in which clinical presentation, symptoms, and evolution widely varies between patients. To investigate the existence of clinical subtypes in DLB based on the initial clinical presentation. 81 patients with a clinical diagnosis of probable DLB were consecutively included. All patients underwent a neurological evaluation including a structured questionnaire about neuropsychiatric symptoms and sleep, an assessment of motor impairment (Unified Parkinson Disease Rating Scale subscale III), and a formal neuropsychological evaluation. Onset of core symptoms (hallucinations, parkinsonism, and fluctuations) and dementia were systematically reviewed from medical records. We applied a K-means clustering method based on the initial clinical presentation. Cluster analysis yielded three different groups. Patients in cluster I (cognitive-predominant, n = 46) presented more frequently with cognitive symptoms (95.7%, n = 44, p < 0.001), and showed a longer duration from onset to DLB diagnosis (p < 0.001) than the other clusters. Patients in cluster II (neuropsychiatric-predominant, n = 22) were older at disease onset (78.1±5 versus 73.6±6.1 and 73.6±4.2 in clusters I and III, respectively, both p < 0.01), presented more frequently with psychotic symptoms (77.3%, n = 17), and had a shorter duration until the onset of hallucinations (p < 0.001). Patients in cluster III (parkinsonism-predominant, n = 13) showed a shorter time from onset to presence of parkinsonism (p < 0.001) and dementia (0.008). Three subtypes of clinical DLB can be defined when considering the differential initial presentations. The proposed subtypes have distinct clinical profiles and progression patterns.

Diversity of Bradyrhizobium strains nodulating Lupinus micranthus on both sides of the Western Mediterranean: Algeria and Spain.

PubMed

Bourebaba, Yasmina; Durán, David; Boulila, Farida; Ahnia, Hadjira; Boulila, Abdelghani; Temprano, Francisco; Palacios, José M; Imperial, Juan; Ruiz-Argüeso, Tomás; Rey, Luis

2016-06-01

Lupinus micranthus is a lupine distributed in the Mediterranean basin whose nitrogen fixing symbiosis has not been described in detail. In this study, 101 slow-growing nodule isolates were obtained from L. micranthus thriving in soils on both sides of the Western Mediterranean. The diversity of the isolates, 60 from Algeria and 41 from Spain, was addressed by multilocus sequence analysis of housekeeping genes (16S rRNA, atpD, glnII and recA) and one symbiotic gene (nodC). Using genomic fingerprints from BOX elements, 37 different profiles were obtained (22 from Algeria and 15 from Spain). Phylogenetic analysis based on 16S rRNA and concatenated atpD, glnII and recA sequences of a representative isolate of each BOX profile displayed a homogeneous distribution of profiles in six different phylogenetic clusters. All isolates were taxonomically ascribed to the genus Bradyrhizobium. Three clusters comprising 24, 6, and 4 isolates, respectively, accounted for most of the profiles. The largest cluster was close to the Bradyrhizobium canariense lineage, while the other two were related to B. cytisi/B. rifense. The three remaining clusters included only one isolate each, and were close to B. canariense, B. japonicum and B. elkanii species, respectively. In contrast, phylogenetic clustering of BOX profiles based on nodC sequences yielded only two phylogenetic groups. One of them included all the profiles except one, and belonged to symbiovar genistearum. The remaining profile, constituted by a strain related to B. elkanii, was not related to any well-defined symbiotic lineage, and may constitute both a new symbiovar and a new genospecies. Copyright © 2016 Elsevier GmbH. All rights reserved.

Wheat EST resources for functional genomics of abiotic stress

PubMed Central

Houde, Mario; Belcaid, Mahdi; Ouellet, François; Danyluk, Jean; Monroy, Antonio F; Dryanova, Ani; Gulick, Patrick; Bergeron, Anne; Laroche, André; Links, Matthew G; MacCarthy, Luke; Crosby, William L; Sarhan, Fathey

2006-01-01

Background Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. Results We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. Conclusion We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals. PMID:16772040

Characterization of synoptic patterns causing dust outbreaks that affect the Arabian Peninsula

NASA Astrophysics Data System (ADS)

Hermida, L.; Merino, A.; Sánchez, J. L.; Fernández-González, S.; García-Ortega, E.; López, L.

2018-01-01

Dust storms pose serious weather hazards in arid and semiarid regions of the earth. Understanding the main synoptic conditions that give rise to dust outbreaks is important for issuing forecasts and warnings to the public in cases of severe storms. The aim of the present study is to determine synoptic patterns that are associated with or even favor dust outbreaks over the Arabian Peninsula. In this respect, red-green-blue dust composite images from the Meteosat Second Generation (MSG) satellite are used to detect dust outbreaks affecting the Arabian Peninsula, with possible influences in southwestern Asia and northeastern Africa, between 2005 and 2013. The Meteosat imagery yielded a sample of 95 dust storm days. Meteorological fields from NCEP/NCAR reanalysis data of wind fields at 10 m and 250 hPa, mean sea level pressure, and geopotential heights at 850 and 500 hPa were obtained for the dust storm days. Using principal component analysis in T-mode and non-hierarchical k-means clustering, we obtained four major atmospheric circulation patterns associated with dust outbreaks during the study days. Cluster 4 had the largest number of days with dust events, which were constrained to summer, and cluster 3 had the fewest. In clusters 1, 2 and 3, the jet stream favored the entry of a low-pressure area or trough that varied in location between the three clusters. Their most northerly location was found in cluster 4, along with an extensive low-pressure area supporting strong winds over the Arabian Peninsula. The spatial distribution of aerosol optical depth for each cluster obtained was characterized using the Moderate Resolution Imaging Spectroradiometer data. Then, using METAR stations, clusters were also characterized in terms of frequency and visibility.

Genetic Diversity Analysis of Selected Capsicum annuum Genotypes based on Morpho-Physiological, Yield Characteristics and their Biochemical Properties.

PubMed

Ridzuan, Raihana; Yusop, Mohd Rafii; Mohammad Yusof, Martini; Ismail, Siti Izera; Miah, Gous; Magaji, Usman

2018-05-31

The assessment of the different desirable characters among the chili genotypes expanded the effective selection for crop improvement. Identification of genetically superior parents is important in assortment of the best parents to develop new chili hybrid. This study was done to assess the hereditary assorted variety of selected genotypes of Capsicum annuum based on their morpho-physiological and yield traits in two planting seasons. Further, their biochemical properties; capsaicinoids content (capsaicin and dihydrocapsaicin), add up to the content of phenolic and antioxidant action determination of unripe and ripe chili pepper fruits were carried out at dry fruits. AVPP9813 and Kulai 907 were observed to have high fruit yield with 541.39 g/plant and 502.64 g/plant, respectively. The most increased genotypic coefficient variation (GCV) and phenotypic coefficient of variation (PCV) were shown by the fruit number per plant (49.71% and 66.04%, respectively). High heritability was observed in yield characters viz-a-viz fruit weight, length and girth and indicated high genetic advance. Eight groups were obtained from the cluster analysis. For the biochemical analysis, the capsaicinoids content and total phenolic content were high in Chili Bangi 3 at unripe and ripe fruit stage while for antioxidant activity SDP203 was the highest in ripe dry fruit. Higher GCV and PCV combined with moderate to high heritability and high hereditary progress were seen in number of fruit per plant, fruit yield per plant and fruit weight per fruit. These findings are beneficial for chili pepper breeders to select desirable quantitative characters in C. annuum in their breeding program. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Deeper Insights into the Circumgalactic Medium using Multivariate Analysis Methods

NASA Astrophysics Data System (ADS)

Lewis, James; Churchill, Christopher W.; Nielsen, Nikole M.; Kacprzak, Glenn

2017-01-01

Drawing from a database of galaxies whose surrounding gas has absorption from MgII, called the MgII-Absorbing Galaxy Catalog (MAGIICAT, Neilsen et al 2013), we studied the circumgalactic medium (CGM) for a sample of 47 galaxies. Using multivariate analysis, in particular the k-means clustering algorithm, we determined that simultaneously examining column density (N), rest-frame B-K color, virial mass, and azimuthal angle (the projected angle between the galaxy major axis and the quasar line of sight) yields two distinct populations: (1) bluer, lower mass galaxies with higher column density along the minor axis, and (2) redder, higher mass galaxies with lower column density along the major axis. We support this grouping by running (i) two-sample, two-dimensional Kolmogorov-Smirnov (KS) tests on each of the six bivariate planes and (ii) two-sample KS tests on each of the four variables to show that the galaxies significantly cluster into two independent populations. To account for the fact that 16 of our 47 galaxies have upper limits on N, we performed Monte-Carlo tests whereby we replaced upper limits with random deviates drawn from a Schechter distribution fit, f(N). These tests strengthen the results of the KS tests. We examined the behavior of the MgII λ2796 absorption line equivalent width and velocity width for each galaxy population. We find that equivalent width and velocity width do not show similar characteristic distinctions between the two galaxy populations. We discuss the k-means clustering algorithm for optimizing the analysis of populations within datasets as opposed to using arbitrary bivariate subsample cuts. We also discuss the power of the k-means clustering algorithm in extracting deeper physical insight into the CGM in relationship to host galaxies.

Regression analysis on the variation in efficiency frontiers for prevention stage of HIV/AIDS.

PubMed

Kamae, Maki S; Kamae, Isao; Cohen, Joshua T; Neumann, Peter J

2011-01-01

To investigate how the cost effectiveness of preventing HIV/AIDS varies across possible efficiency frontiers (EFs) by taking into account potentially relevant external factors, such as prevention stage, and how the EFs can be characterized using regression analysis given uncertainty of the QALY-cost estimates. We reviewed cost-effectiveness estimates for the prevention and treatment of HIV/AIDS published from 2002-2007 and catalogued in the Tufts Medical Center Cost-Effectiveness Analysis (CEA) Registry. We constructed efficiency frontier (EF) curves by plotting QALYs against costs, using methods used by the Institute for Quality and Efficiency in Health Care (IQWiG) in Germany. We stratified the QALY-cost ratios by prevention stage, country of study, and payer perspective, and estimated EF equations using log and square-root models. A total of 53 QALY-cost ratios were identified for HIV/AIDS in the Tufts CEA Registry. Plotted ratios stratified by prevention stage were visually grouped into a cluster consisting of primary/secondary prevention measures and a cluster consisting of tertiary measures. Correlation coefficients for each cluster were statistically significant. For each cluster, we derived two EF equations - one based on the log model, and one based on the square-root model. Our findings indicate that stratification of HIV/AIDS interventions by prevention stage can yield distinct EFs, and that the correlation and regression analyses are useful for parametrically characterizing EF equations. Our study has certain limitations, such as the small number of included articles and the potential for study populations to be non-representative of countries of interest. Nonetheless, our approach could help develop a deeper appreciation of cost effectiveness beyond the deterministic approach developed by IQWiG.

Comparison of Genetic Diversity between Chinese and American Soybean (Glycine max (L.)) Accessions Revealed by High-Density SNPs

PubMed Central

Liu, Zhangxiong; Li, Huihui; Wen, Zixiang; Fan, Xuhong; Li, Yinghui; Guan, Rongxia; Guo, Yong; Wang, Shuming; Wang, Dechun; Qiu, Lijuan

2017-01-01

Soybean is one of the most important economic crops for both China and the United States (US). The exchange of germplasm between these two countries has long been active. In order to investigate genetic relationships between Chinese and US soybean germplasm, 277 Chinese soybean accessions and 300 US soybean accessions from geographically diverse regions were analyzed using 5,361 SNP markers. The genetic diversity and the polymorphism information content (PIC) of the Chinese accessions was higher than that of the US accessions. Population structure analysis, principal component analysis, and cluster analysis all showed that the genetic basis of Chinese soybeans is distinct from that of the USA. The groupings observed in clustering analysis reflected the geographical origins of the accessions; this conclusion was validated with both genetic distance analysis and relative kinship analysis. FST-based and EigenGWAS statistical analysis revealed high genetic variation between the two subpopulations. Analysis of the 10 loci with the strongest selection signals showed that many loci were located in chromosome regions that have previously been identified as quantitative trait loci (QTL) associated with environmental-adaptation-related and yield-related traits. The pattern of diversity among the American and Chinese accessions should help breeders to select appropriate parental accessions to enhance the performance of future soybean cultivars. PMID:29250088

Nuclear Fusion In Gases Of Deuterium Clusters And Hot Electron Generation In Droplet Sprays Under Irradiation With An Intense Femtosecond Laser

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

T. Ditmire; Zweiback, J; Cowan, T E

In conclusion, we have observed the production of 2.45 MeV deuterium fusion neutrons when a gas of deuterium clusters is irradiated with a 120 mJ, 35 fs laser pulse. When the focal position is optimized, we have observed as many as 10{sup 4} neutrons per laser shot. This yield is consistent with some simple estimates for the fusion yield. We also find that the fusion yield is a sensitive function of the deuterium cluster size in the target jet, a consequence of the Coulomb explosion origin of the fast deuterons. We also find that the neutron pulse duration is fast,more » with a characteristic burn time of well under 1 ns. This experiment may represent a means for producing a compact, table-top source of short pulse fusion neutrons for applications. Furthermore, we have measured hard x-ray yield from femtosecond laser interactions with both solid and micron scale droplet targets. Strong hard x-ray production is observed from both targets. However, the inferred electron temperature is somewhat higher in the case of irradiation of the droplets. These data are consistent with PIC simulations. This finding indicates that quite unique hot electron dynamics occur during the irradiation of wavelength scale particles by an intense laser field and likely warrants further study.« less

Taxonomic Identity of the Invasive Fruit Fly Pest, Bactrocera invadens: Concordance in Morphometry and DNA Barcoding

PubMed Central

Khamis, Fathiya M.; Masiga, Daniel K.; Mohamed, Samira A.; Salifu, Daisy; de Meyer, Marc; Ekesi, Sunday

2012-01-01

In 2003, a new fruit fly pest species was recorded for the first time in Kenya and has subsequently been found in 28 countries across tropical Africa. The insect was described as Bactrocera invadens, due to its rapid invasion of the African continent. In this study, the morphometry and DNA Barcoding of different populations of B. invadens distributed across the species range of tropical Africa and a sample from the pest's putative aboriginal home of Sri Lanka was investigated. Morphometry using wing veins and tibia length was used to separate B. invadens populations from other closely related Bactrocera species. The Principal component analysis yielded 15 components which correspond to the 15 morphometric measurements. The first two principal axes contributed to 90.7% of the total variance and showed partial separation of these populations. Canonical discriminant analysis indicated that only the first five canonical variates were statistically significant. The first two canonical variates contributed a total of 80.9% of the total variance clustering B. invadens with other members of the B. dorsalis complex while distinctly separating B. correcta, B. cucurbitae, B. oleae and B. zonata. The largest Mahalanobis squared distance (D2 = 122.9) was found to be between B. cucurbitae and B. zonata, while the lowest was observed between B. invadens populations against B. kandiensis (8.1) and against B. dorsalis s.s (11.4). Evolutionary history inferred by the Neighbor-Joining method clustered the Bactrocera species populations into four clusters. First cluster consisted of the B. dorsalis complex (B. invadens, B. kandiensis and B. dorsalis s. s.), branching from the same node while the second group was paraphyletic clades of B. correcta and B. zonata. The last two are monophyletic clades, consisting of B. cucurbitae and B. oleae, respectively. Principal component analysis using the genetic distances confirmed the clustering inferred by the NJ tree. PMID:23028649

The Effects of Temperature and Precipitation on the Yield of Zea Mays L. I the Southeastern United States

NASA Astrophysics Data System (ADS)

Stooksbury, David Emory

Three families of straightforward maize (Zea mays L.) yield/climate models using monthly temperature and precipitation terms are produced. One family of models uses USDA's Crop Reporting Districts (CRD) as its scale of aggregation. The other two families of models use three different district aggregates based on climate or yield patterns. The climate and yield districts are determined by using a two-stage cluster analysis. The CRD-based family of models perform as well as the climate and yield based models. All models explain between 80% and 90% of the variance in maize yield. The most important climate term affecting maize yield in the South is the daily maximum temperature at pollination time. The higher the maximum temperature, the lower the yield. Above normal minimum temperature during pollination increases yield in the Middle South. Weather that favors early planting and rapid vegetative growth increases yield. Ideal maize yield weather includes a dry period during planting followed by a warm period during vegetative growth. Moisture variables are important only during the planting and harvest periods when above normal precipitation delays field work and thereby reduces yield. The model results indicate that the dire predictions about the fate of Southern agriculture in a trace gas warmed world may not be true. This is due to the overwhelming influence of the daily maximum temperature on yield. An optimum aggregate for climate impact studies was not found. I postulate that this is due to the dynamic nature of the American maize production system. For most climate impact studies on a dynamic agricultural system, there does not need to be a concern about the model aggregation.

Quantitative application of the primary progressive aphasia consensus criteria

PubMed Central

Wicklund, Meredith R.; Duffy, Joseph R.; Strand, Edythe A.; Machulda, Mary M.; Whitwell, Jennifer L.

2014-01-01

Objective: To determine how well the consensus criteria could classify subjects with primary progressive aphasia (PPA) using a quantitative speech and language battery that matches the test descriptions provided by the consensus criteria. Methods: A total of 105 participants with a neurodegenerative speech and language disorder were prospectively recruited and underwent neurologic, neuropsychological, and speech and language testing and MRI in this case-control study. Twenty-one participants with apraxia of speech without aphasia served as controls. Select tests from the speech and language battery were chosen for application of consensus criteria and cutoffs were employed to determine syndromic classification. Hierarchical cluster analysis was used to examine participants who could not be classified. Results: Of the 84 participants, 58 (69%) could be classified as agrammatic (27%), semantic (7%), or logopenic (35%) variants of PPA. The remaining 31% of participants could not be classified. Of the unclassifiable participants, 2 clusters were identified. The speech and language profile of the first cluster resembled mild logopenic PPA and the second cluster semantic PPA. Gray matter patterns of loss of these 2 clusters of unclassified participants also resembled mild logopenic and semantic variants. Conclusions: Quantitative application of consensus PPA criteria yields the 3 syndromic variants but leaves a large proportion unclassified. Therefore, the current consensus criteria need to be modified in order to improve sensitivity. PMID:24598709

Comparison of Se and Te clusters produced by ion bombardment

NASA Astrophysics Data System (ADS)

Trzyna, Małgorzata

2017-01-01

Nanostructures based on tellurium and selenium are materials used as components for the manufacturing topological insulators. Therefore it is crucial to precisely characterize these materials. In this work the emission of selenium and tellurium cluster ions, sputtered by Bi+ primary ion guns, was investigated by using Time-of-Flight Secondary Ion Mass Spectrometry (TOF SIMS). It has been found that BixTex and BixSex clusters appear in addition to Sex and Tex clusters in the mass range up to 1300 m/z. Local maxima or minima (magic numbers) are observed in the ion intensity versus a number of atoms per cluster for both positive and negative ions spectra for all types of clusters and primary ions used. These extrema can be attributed to different yield and stability of certain clusters but also to fragmentation of high-mass clusters.

Electronic, Magnetic, and Redox Properties of [MFe(3)S(4)] Clusters (M = Cd, Cu, Cr) in Pyrococcus furiosus Ferredoxin.

PubMed

Staples, Christopher R.; Dhawan, Ish K.; Finnegan, Michael G.; Dwinell, Derek A.; Zhou, Zhi Hao; Huang, Heshu; Verhagen, Marc F. J. M.; Adams, Michael W. W.; Johnson, Michael K.

1997-12-03

The ground- and excited-state properties of heterometallic [CuFe(3)S(4)](2+,+), [CdFe(3)S(4)](2+,+), and [CrFe(3)S(4)](2+,+) cubane clusters assembled in Pyrococcus furiosus ferredoxin have been investigated by the combination of EPR and variable-temperature/variable-field magnetic circular dichroism (MCD) studies. The results indicate Cd(2+) incorporation into [Fe(3)S(4)](0,-) cluster fragments to yield S = 2 [CdFe(3)S(4)](2+) and S = (5)/(2) [CdFe(3)S(4)](+) clusters and Cu(+) incorporation into [Fe(3)S(4)](+,0) cluster fragments to yield S = (1)/(2) [CuFe(3)S(4)](2+) and S = 2 [CuFe(3)S(4)](+) clusters. This is the first report of the preparation of cubane type [CrFe(3)S(4)](2+,+) clusters, and the combination of EPR and MCD results indicates S = 0 and S = (3)/(2) ground states for the oxidized and reduced forms, respectively. Midpoint potentials for the [CdFe(3)S(4)](2+,+), [CrFe(3)S(4)](2+,+), and [CuFe(3)S(4)](2+,+) couples, E(m) = -470 +/- 15, -440 +/- 10, and +190 +/- 10 mV (vs NHE), respectively, were determined by EPR-monitored redox titrations or direct electrochemistry at a glassy carbon electrode. The trends in redox potential, ground-state spin, and electron delocalization of [MFe(3)S(4)](2+,+) clusters in P. furiosus ferredoxin are discussed as a function of heterometal (M = Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Tl).

Photometry and spectroscopy in the open cluster Alpha Persei, 2

NASA Technical Reports Server (NTRS)

Prosser, Charles F.

1993-01-01

Results from a combination of new spectroscopic and photometric observations in the lower main-sequence and pre-main sequence of the open cluster alpha Persei are presented. New echelle spectroscopy has provided radial and rotational velocity information for thirteen candidate members, three of which are nonmembers based on radial velocity, absence of a Li 6707A feature, and absence of H-alpha emission. A set of revised rotational velocity estimates for several slowly rotating candidates identified earlier is given, yielding rotational velocities as low as 7 km/s for two apparent cluster members. VRI photometry for several pre-main sequence members is given; the new (V,V-I(sub K)) photometry yields a more clearly defined pre-main sequence. A list of approximately 43 new faint candidate members based on the (V,V-I(sub K)) CCD photometry is presented in an effort to identify additional cluster members at very low masses. Low-dispersion spectra obtained for several of these candidates provide in some cases supporting evidence for cluster membership. The single brown dwarf candidate in this cluster is for the first time placed in a color-magnitude diagram with other cluster members, providing a better means for establishing its true status. Stars from among the list of new photometric candidates may provide the means for establishing a sequence of cluster members down to very faint magnitudes (V approximately 21) and consequently very low masses. New coordinate determinations for previous candidate members and finding charts for the new photometric candidates are provided in appendices.

SUPERMODEL ANALYSIS OF GALAXY CLUSTERS

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

Fusco-Femiano, R.; Cavaliere, A.; Lapi, A.

2009-11-01

We present the analysis of the X-ray brightness and temperature profiles for six clusters belonging to both the Cool Core (CC) and Non Cool Core (NCC) classes, in terms of the Supermodel (SM) developed by Cavaliere et al. Based on the gravitational wells set by the dark matter (DM) halos, the SM straightforwardly expresses the equilibrium of the intracluster plasma (ICP) modulated by the entropy deposited at the boundary by standing shocks from gravitational accretion, and injected at the center by outgoing blast waves from mergers or from outbursts of active galactic nuclei. The cluster set analyzed here highlights notmore » only how simply the SM represents the main dichotomy CC versus NCC clusters in terms of a few ICP parameters governing the radial entropy run, but also how accurately it fits even complex brightness and temperature profiles. For CC clusters like A2199 and A2597, the SM with a low level of central entropy straightforwardly yields the characteristic peaked profile of the temperature marked by a decline toward the center, without requiring currently strong radiative cooling and high mass deposition rates. NCC clusters like A1656 require instead a central entropy floor of a substantial level, and some like A2256 and even more A644 feature structured temperature profiles that also call for a definite floor extension; in such conditions the SM accurately fits the observations, and suggests that in these clusters the ICP has been just remolded by a merger event, in the way of a remnant cool core. The SM also predicts that DM halos with high concentration should correlate with flatter entropy profiles and steeper brightness in the outskirts; this is indeed the case with A1689, for which from X-rays we find concentration values c approx 10, the hallmark of an early halo formation. Thus, we show the SM to constitute a fast tool not only to provide wide libraries of accurate fits to X-ray temperature and density profiles, but also to retrieve from the ICP archives specific information concerning the physical histories of DM and baryons in the inner and the outer cluster regions.« less

Optimizing the ionization and energy absorption of laser-irradiated clusters

NASA Astrophysics Data System (ADS)

Kundu, M.; Bauer, D.

2008-03-01

It is known that rare-gas or metal clusters absorb incident laser energy very efficiently. However, due to the intricate dependencies on all the laser and cluster parameters, it is difficult to predict under which circumstances ionization and energy absorption are optimal. With the help of three-dimensional particle-in-cell simulations of xenon clusters (up to 17256 atoms), it is shown that for a given laser pulse energy and cluster, an optimum wavelength exists that corresponds to the approximate wavelength of the transient, linear Mie-resonance of the ionizing cluster at an early stage of negligible expansion. In a single ultrashort laser pulse, the linear resonance at this optimum wavelength yields much higher absorption efficiency than in the conventional, dual-pulse pump-probe setup of linear resonance during cluster expansion.

Extraction methods of Amaranthus sp. grain oil isolation.

PubMed

Krulj, Jelena; Brlek, Tea; Pezo, Lato; Brkljača, Jovana; Popović, Sanja; Zeković, Zoran; Bodroža Solarov, Marija

2016-08-01

Amaranthus sp. is a fast-growing crop with well-known beneficial nutritional values (rich in protein, fat, dietary fiber, ash, and minerals, especially calcium and sodium, and containing a higher amount of lysine than conventional cereals). Amaranthus sp. is an underexploited plant source of squalene, a compound of high importance in the food, cosmetic and pharmaceutical industries. This paper has examined the effects of the different extraction methods (Soxhlet, supercritical fluid and accelerated solvent extraction) on the oil and squalene yield of three genotypes of Amaranthus sp. grain. The highest yield of the extracted oil (78.1 g kg(-1) ) and squalene (4.7 g kg(-1) ) in grain was obtained by accelerated solvent extraction (ASE) in genotype 16. Post hoc Tukey's HSD test at 95% confidence limit showed significant differences between observed samples. Principal component analysis (PCA) and cluster analysis (CA) were used for assessing the effect of different genotypes and extraction methods on oil and squalene yield, and also the fatty acid composition profile. Using coupled PCA and CA of observed samples, possible directions for improving the quality of product can be realized. The results of this study indicate that it is very important to choose both the right genotype and the right method of extraction for optimal oil and squalene yield. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Gas stripping and mixing in galaxy clusters: a numerical comparison study

NASA Astrophysics Data System (ADS)

Heß, Steffen; Springel, Volker

2012-11-01

The ambient hot intrahalo gas in clusters of galaxies is constantly fed and stirred by infalling galaxies, a process that can be studied in detail with cosmological hydrodynamical simulations. However, different numerical methods yield discrepant predictions for crucial hydrodynamical processes, leading for example to different entropy profiles in clusters of galaxies. In particular, the widely used Lagrangian smoothed particle hydrodynamics (SPH) scheme is suspected to strongly damp fluid instabilities and turbulence, which are both crucial to establish the thermodynamic structure of clusters. In this study, we test to which extent our recently developed Voronoi particle hydrodynamics (VPH) scheme yields different results for the stripping of gas out of infalling galaxies and for the bulk gas properties of cluster. We consider both the evolution of isolated galaxy models that are exposed to a stream of intracluster medium or are dropped into cluster models, as well as non-radiative cosmological simulations of cluster formation. We also compare our particle-based method with results obtained with a fundamentally different discretization approach as implemented in the moving-mesh code AREPO. We find that VPH leads to noticeably faster stripping of gas out of galaxies than SPH, in better agreement with the mesh-code than with SPH. We show that despite the fact that VPH in its present form is not as accurate as the moving mesh code in our investigated cases, its improved accuracy of gradient estimates makes VPH an attractive alternative to SPH.

The Gaia-ESO Survey: the present-day radial metallicity distribution of the Galactic disc probed by pre-main-sequence clusters

NASA Astrophysics Data System (ADS)

Spina, L.; Randich, S.; Magrini, L.; Jeffries, R. D.; Friel, E. D.; Sacco, G. G.; Pancino, E.; Bonito, R.; Bravi, L.; Franciosini, E.; Klutsch, A.; Montes, D.; Gilmore, G.; Vallenari, A.; Bensby, T.; Bragaglia, A.; Flaccomio, E.; Koposov, S. E.; Korn, A. J.; Lanzafame, A. C.; Smiljanic, R.; Bayo, A.; Carraro, G.; Casey, A. R.; Costado, M. T.; Damiani, F.; Donati, P.; Frasca, A.; Hourihane, A.; Jofré, P.; Lewis, J.; Lind, K.; Monaco, L.; Morbidelli, L.; Prisinzano, L.; Sousa, S. G.; Worley, C. C.; Zaggia, S.

2017-05-01

Context. The radial metallicity distribution in the Galactic thin disc represents a crucial constraint for modelling disc formation and evolution. Open star clusters allow us to derive both the radial metallicity distribution and its evolution over time. Aims: In this paper we perform the first investigation of the present-day radial metallicity distribution based on [Fe/H] determinations in late type members of pre-main-sequence clusters. Because of their youth, these clusters are therefore essential for tracing the current interstellar medium metallicity. Methods: We used the products of the Gaia-ESO Survey analysis of 12 young regions (age < 100 Myr), covering Galactocentric distances from 6.67 to 8.70 kpc. For the first time, we derived the metal content of star forming regions farther than 500 pc from the Sun. Median metallicities were determined through samples of reliable cluster members. For ten clusters the membership analysis is discussed in the present paper, while for other two clusters (I.e. Chamaeleon I and Gamma Velorum) we adopted the members identified in our previous works. Results: All the pre-main-sequence clusters considered in this paper have close-to-solar or slightly sub-solar metallicities. The radial metallicity distribution traced by these clusters is almost flat, with the innermost star forming regions having [Fe/H] values that are 0.10-0.15 dex lower than the majority of the older clusters located at similar Galactocentric radii. Conclusions: This homogeneous study of the present-day radial metallicity distribution in the Galactic thin disc favours models that predict a flattening of the radial gradient over time. On the other hand, the decrease of the average [Fe/H] at young ages is not easily explained by the models. Our results reveal a complex interplay of several processes (e.g. star formation activity, initial mass function, supernova yields, gas flows) that controlled the recent evolution of the Milky Way. Based on observations made with the ESO/VLT, at Paranal Observatory, under program 188.B-3002 (The Gaia-ESO Public Spectroscopic Survey).Full Table 1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/601/A70

Organic dairy farmers put more emphasis on production traits than conventional farmers.

PubMed

Slagboom, M; Kargo, M; Edwards, D; Sørensen, A C; Thomasen, J R; Hjortø, L

2016-12-01

The overall aim of this research was to characterize the preferences of Danish dairy farmers for improvements in breeding goal traits. The specific aims were (1) to investigate the presence of heterogeneity in farmers' preferences by means of cluster analysis, and (2) to associate these clusters with herd characteristics and production systems (organic or conventional). We established a web-based survey to characterize the preferences of farmers for improvements in 10 traits, by means of pairwise rankings. We also collected a considerable number of herd characteristics. Overall, 106 organic farmers and 290 conventional farmers answered the survey, all with Holstein cows. The most preferred trait improvement was cow fertility, and the least preferred was calving difficulty. By means of cluster analysis, we identified 4 distinct clusters of farmers and named them according to the trait improvements that were most preferred: Health and Fertility, Production and Udder Health, Survival, and Fertility and Production. Some herd characteristics differed between clusters; for example, farmers in the Survival cluster had twice the percentage of dead cows in their herds compared with the other clusters, and farmers that gave the highest ranking to cow and heifer fertility had the lowest conception rate in their herds. This finding suggests that farmers prefer to improve traits that are more problematic in their herd. The proportion of organic and conventional farmers also differed between clusters; we found a higher proportion of organic farmers in the production-based clusters. When we analyzed organic and conventional data separately, we found that organic farmers ranked production traits higher than conventional farmers. The herds of organic farmers had lower milk yields and lower disease incidences, which might explain the high ranking of milk production and the low ranking of disease traits. This study shows that heterogeneity exists in farmers' preferences for improvements in breeding goal traits, that organic and conventional farmers differ in their preferences, and that herd characteristics can be linked to different farmer clusters. The results of this study could be used for the future development of breeding goals in Danish Holstein cows and for the development of customized total merit indices based on farmer preferences. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Multivalent ligands control stem cell behaviour in vitro and in vivo

NASA Astrophysics Data System (ADS)

Conway, Anthony; Vazin, Tandis; Spelke, Dawn P.; Rode, Nikhil A.; Healy, Kevin E.; Kane, Ravi S.; Schaffer, David V.

2013-11-01

There is broad interest in designing nanostructured materials that can interact with cells and regulate key downstream functions. In particular, materials with nanoscale features may enable control over multivalent interactions, which involve the simultaneous binding of multiple ligands on one entity to multiple receptors on another and are ubiquitous throughout biology. Cellular signal transduction of growth factor and morphogen cues (which have critical roles in regulating cell function and fate) often begins with such multivalent binding of ligands, either secreted or cell-surface-tethered to target cell receptors, leading to receptor clustering. Cellular mechanisms that orchestrate ligand-receptor oligomerization are complex, however, so the capacity to control multivalent interactions and thereby modulate key signalling events within living systems is currently very limited. Here, we demonstrate the design of potent multivalent conjugates that can organize stem cell receptors into nanoscale clusters and control stem cell behaviour in vitro and in vivo. The ectodomain of ephrin-B2, normally an integral membrane protein ligand, was conjugated to a soluble biopolymer to yield multivalent nanoscale conjugates that potently induce signalling in neural stem cells and promote their neuronal differentiation both in culture and within the brain. Super-resolution microscopy analysis yielded insights into the organization of the receptor-ligand clusters at the nanoscale. We also found that synthetic multivalent conjugates of ephrin-B1 strongly enhance human embryonic and induced pluripotent stem cell differentiation into functional dopaminergic neurons. Multivalent bioconjugates are therefore powerful tools and potential nanoscale therapeutics for controlling the behaviour of target stem cells in vitro and in vivo.

FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

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

Coe, Dan; Bradley, Larry; Zitrin, Adi, E-mail: DCoe@STScI.edu

2015-02-20

The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z >more » 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.« less

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

PubMed

Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

2011-10-01

This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

Molybdenum and carbon atom and carbon cluster sputtering under low-energy noble gas plasma bombardment

NASA Astrophysics Data System (ADS)

Oyarzabal, Eider

Exit-angle resolved Mo atom sputtering yield under Xe ion bombardment and carbon atom and cluster (C2 and C3) sputtering yields under Xe, Kr, Ar, Ne and He ion bombardment from a plasma are measured for low incident energies (75--225 eV). An energy-resolved quadrupole mass spectrometer (QMS) is used to detect the fraction of un-scattered sputtered neutrals that become ionized in the plasma; the angular distribution is obtained by changing the angle between the target and the QMS aperture. A one-dimensional Monte Carlo code is used to simulate the interaction of the plasma and the sputtered particles between the sample and the QMS. The elastic scattering cross-sections of C, C2 and C3 with the different bombarding gas neutrals is obtained by varying the distance between the sample and the QMS and by performing a best fit of the simulation results to the experimental results. Because the results obtained with the QMS are relative, the Mo atom sputtering results are normalized to the existing data in the literature and the total sputtering yield for carbon (C+C 2+C3) for each bombarding gas is obtained from weight loss measurements. The absolute sputtering yield for C, C2 and C 3 is then calculated from the integration of the measured angular distribution, taking into account the scattering and ionization of the sputtered particles between the sample and the QMS. The angular sputtering distribution for Mo has a maximum at theta=60°, and this maximum becomes less pronounced as the incident ion energy increases. The results of the Monte Carlo TRIDYN code simulation for the angular distribution of Mo atoms sputtered by Xe bombardment are in agreement with the experiments. For carbon sputtering under-cosine angular distributions of the sputtered atoms and clusters for all the studied bombarding gases are also observed. The C, C2 and C3 sputtering yield data shows a clear decrease of the atom to cluster (C/C2 and C/C3) sputtering ratio as the incident ion mass increases, changing from a carbon atom preferential erosion for the lower incident ion masses (He, Ne and Ar) to a cluster preferential erosion for the higher incident ion masses (Kr and Xe).

An efficient laser vaporization source for chemically modified metal clusters characterized by thermodynamics and kinetics

NASA Astrophysics Data System (ADS)

Masubuchi, Tsugunosuke; Eckhard, Jan F.; Lange, Kathrin; Visser, Bradley; Tschurl, Martin; Heiz, Ulrich

2018-02-01

A laser vaporization cluster source that has a room for cluster aggregation and a reactor volume, each equipped with a pulsed valve, is presented for the efficient gas-phase production of chemically modified metal clusters. The performance of the cluster source is evaluated through the production of Ta and Ta oxide cluster cations, TaxOy+ (y ≥ 0). It is demonstrated that the cluster source produces TaxOy+ over a wide mass range, the metal-to-oxygen ratio of which can easily be controlled by changing the pulse duration that influences the amount of reactant O2 introduced into the cluster source. Reaction kinetic modeling shows that the generation of the oxides takes place under thermalized conditions at less than 300 K, whereas metal cluster cores are presumably created with excess heat. These characteristics are also advantageous to yield "reaction intermediates" of interest via reactions between clusters and reactive molecules in the cluster source, which may subsequently be mass selected for their reactivity measurements.

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

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

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

DOE PAGES

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.; ...

2018-01-24

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Comparative genetic analysis of trichome-less and normal pod genotypes of Mucuna pruriens (Fabaceae).

PubMed

Dhawan, S S; Rai, G K; Darokar, M P; Lal, R K; Misra, H O; Khanuja, S P S

2011-09-15

Velvet bean (Mucuna pruriens) seeds contain the catecholic amino acid L-DoPA (L-3,4-dihydroxyphenylalanine), which is a neurotransmitter precursor and used for the treatment of Parkinson's disease and mental disorders. The great demand for L-DoPA is largely met by the pharmaceutical industry through extraction of the compound from wild populations of this plant; commercial exploitation of this compound is hampered because of its limited availability. The trichomes present on the pods can cause severe itching, blisters and dermatitis, discouraging cultivation. We screened genetic stocks of velvet bean for the trichome-less trait, along with high seed yield and L-DoPA content. The highest yielding trichome-less elite strain was selected and indentified on the basis of a PCR-based DNA fingerprinting method (RAPD), using deca-nucleotide primers. A genetic similarity index matrix was obtained through multivariant analysis using Nei and Li's coefficient. The similarity coefficients were used to generate a tree for cluster analysis using the UPGMA method. Analysis of amplification spectra of 408 bands obtained with 56 primers allowed us to distinguish a trichome-less elite strain of M. pruriens.

Worldwide Lineages of Clinical Pneumococci in a Japanese Teaching Hospital Identified by DiversiLab System.

PubMed

Kashiwaya, Kiyoshi; Saga, Tomoo; Ishii, Yoshikazu; Sakata, Ryuji; Iwata, Morihiro; Yoshizawa, Sadako; Chang, Bin; Ohnishi, Makoto; Tateda, Kazuhiro

2016-06-01

Pneumococcal Molecular Epidemiology Network (PMEN) clones are representatives of worldwide-spreading pathogens. DiversiLab system, a repetitive PCR system, has been proposed as a less labor-and time-intensive genotyping platform alternative to conventional methods. However, the utility and analysis parameters of DiversiLab for identifying worldwide lineages was not established. To evaluate and optimize the performance of DiversiLab for identifying worldwide pneumococcal lineages, we examined 245 consecutive isolates of clinical Streptococcus pneumoniae from all age-group patients at a teaching hospital in Japan. The capsular swelling reaction of all isolates yielded 24 different serotypes. Intensive visual observation (VO) of DiversiLab band pattern difference divided all isolates into 73 clusters. Multilocus sequence typing (MLST) of representative 73 isolates from each VO cluster yielded 51 different STs. Among them, PMEN-related lineages accounted for 63% (46/73). Although the serotype of PMEN-related isolates was identical to that of the original PMEN clone in 70% (32/46), CC156-related PMEN lineages, namely Greece(6B)-22 and Colombia(23F)-26, harbored various capsular types discordant to the original PMEN clones. Regarding automated analysis, genotyping by extended Jaccard (XJ) with a 75% similarity index cutoff (SIC) showed the highest correlation with serotyping (adjusted Rand's coefficient, 0.528). Elevating the SIC for XJ to 85% increased the discriminatory power sufficient for distinguishing two major PMEN-related isolates of Taiwan(19F)-14 and Netherlands(3)-31. These results demonstrated a potential utility of DiversiLab for identifying worldwide lineage of pneumococcus. An optimized parameters of automated analysis should be useful especially for comparison for reference strains by "identification" function of DiversiLab. Copyright © 2016 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Internal Cluster Validation on Earthquake Data in the Province of Bengkulu

NASA Astrophysics Data System (ADS)

Rini, D. S.; Novianti, P.; Fransiska, H.

2018-04-01

K-means method is an algorithm for cluster n object based on attribute to k partition, where k < n. There is a deficiency of algorithms that is before the algorithm is executed, k points are initialized randomly so that the resulting data clustering can be different. If the random value for initialization is not good, the clustering becomes less optimum. Cluster validation is a technique to determine the optimum cluster without knowing prior information from data. There are two types of cluster validation, which are internal cluster validation and external cluster validation. This study aims to examine and apply some internal cluster validation, including the Calinski-Harabasz (CH) Index, Sillhouette (S) Index, Davies-Bouldin (DB) Index, Dunn Index (D), and S-Dbw Index on earthquake data in the Bengkulu Province. The calculation result of optimum cluster based on internal cluster validation is CH index, S index, and S-Dbw index yield k = 2, DB Index with k = 6 and Index D with k = 15. Optimum cluster (k = 6) based on DB Index gives good results for clustering earthquake in the Bengkulu Province.

IDENTIFICATION OF MEMBERS IN THE CENTRAL AND OUTER REGIONS OF GALAXY CLUSTERS

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

Serra, Ana Laura; Diaferio, Antonaldo, E-mail: serra@ph.unito.it

2013-05-10

The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M{sub 200} {>=} 10{sup 14} h {sup -1} M{sub Sun} extracted from a cosmological N-body simulation of a {Lambda}CDM universe to test the ability of the caustic technique to identify the cluster galaxy members. We identify the true three-dimensional members as the gravitationally bound galaxies. The caustic technique uses the caustic location in the redshift diagram to separate the cluster members from the interlopers. Wemore » apply the technique to mock catalogs containing 1000 galaxies in the field of view of 12 h {sup -1} Mpc on a side at the cluster location. On average, this sample size roughly corresponds to 180 real galaxy members within 3r{sub 200}, similar to recent redshift surveys of cluster regions. The caustic technique yields a completeness, the fraction of identified true members, f{sub c} = 0.95 {+-} 0.03, within 3r{sub 200}. The contamination, the fraction of interlopers in the observed catalog of members, increases from f{sub i}=0.020{sup +0.046}{sub -0.015} at r{sub 200} to f{sub i}=0.08{sup +0.11}{sub -0.05} at 3r{sub 200}. No other technique for the identification of the members of a galaxy cluster provides such large completeness and small contamination at these large radii. The caustic technique assumes spherical symmetry and the asphericity of the cluster is responsible for most of the spread of the completeness and the contamination. By applying the technique to an approximately spherical system obtained by stacking the individual clusters, the spreads decrease by at least a factor of two. We finally estimate the cluster mass within 3r{sub 200} after removing the interlopers: for individual clusters, the mass estimated with the virial theorem is unbiased and within 30% of the actual mass; this spread decreases to less than 10% for the spherically symmetric stacked cluster.« less

Classification of Support Needs for Elderly Outpatients with Diabetes Who Live Alone.

PubMed

Miyawaki, Yoshiko; Shimizu, Yasuko; Seto, Natsuko

2016-02-01

To investigate the support needs of elderly patients with diabetes and to classify elderly patients with diabetes living alone on the basis of support needs. Support needs were derived from a literature review of relevant journals and interviews of outpatients as well as expert nurses in the field of diabetes to prepare a 45-item questionnaire. Each item was analyzed on a 4-point Likert scale. The study included 634 elderly patients with diabetes who were recruited from 3 hospitals in Japan. Exploratory factor analysis was performed to determine the underlying structure of support needs, followed by hierarchical cluster analysis to clarify the characteristics of patients living alone (n=104) who had common support needs. Exploratory factor analysis suggested a 5-factor solution with 23 items: (1) hope for class and gatherings, (2) hope for personal advice including emergency response, (3) supportlessness and hopelessness, (4) barriers to food preparation, (5) hope of safe medical therapy. The hierarchical cluster analysis of subjects yielded 7 clusters, including a no special-support needs group, a collective support group, a self-care support group, a personal-support focus group, a life-support group, a food-preparation support group and a healthcare-environment support group. The support needs of elderly patients with diabetes who live alone can be divided into 2 categories: life and self-care support. Implementation of these categories in outpatient-management programs in which contact time with patients is limited is important in the overall management of elderly patients with diabetes who are living alone. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Carbon atom and cluster sputtering under low-energy noble gas plasma bombardment

NASA Astrophysics Data System (ADS)

Oyarzabal, E.; Doerner, R. P.; Shimada, M.; Tynan, G. R.

2008-08-01

Exit-angle resolved carbon atom and cluster (C2 and C3) sputtering yields are measured during different noble gas (Xe, Kr, Ar, Ne, and He) ion bombardments from a plasma, for low incident energies (75-225 eV). A quadrupole mass spectrometer (QMS) is used to detect the fraction of sputtered neutrals that is ionized in the plasma and to obtain the angular distribution by changing the angle between the target normal and the QMS aperture. A one-dimensional Monte Carlo code is used to simulate the interaction of the plasma and the sputtered particles in the region between the sample and the QMS. The effective elastic scattering cross sections of C, C2, and C3 with the different bombarding gas neutrals are obtained by varying the distance between the sample and the QMS and by performing a best fit of the simulation results to the experimental results. The total sputtering yield (C+C2+C3) for each bombarding gas is obtained from weight-loss measurements and the sputtering yield for C, C2, and C3 is then calculated from the integration of the measured angular distribution, taking into account the scattering and ionization of the sputtered particles between the sample and the QMS. We observe undercosine angular distributions of the sputtered atoms and clusters for all the studied bombarding gases and a clear decrease of the atom to cluster (C2 and C3) sputtering ratio as the incident ion mass increases, changing from a carbon atom preferential erosion for the lower incident ion masses (He, Ne, and Ar) to a cluster preferential erosion for the higher incident ion masses (Kr and Xe).

Study of clusters and hypernuclei production within PHSD+FRIGA model

NASA Astrophysics Data System (ADS)

Kireyeu, Viktar; Le Fèvre, Arnaud; Bratkovskaya, Elena

2017-03-01

We report on the results on the dynamical modelling of cluster formation with the new combined PHSD+FRIGA model at Nuclotron and NICA energies. The FRIGA clusterization algorithm, which can be applied to the transport models, is based on the simulated annealing technique to obtain the most bound configuration of fragments and nucleons. The PHSD+FRIGA model is able to predict isotope yields as well as hypernucleus production. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the BM@N and MPD/NICA detectors.

Controlling transformations in the assembly of polyoxometalate clusters: {Mo11V7}, {Mo17V8} and {Mo72V30}.

PubMed

Miras, Haralampos N; Ochoa, M Nieves Corella; Long, De-Liang; Cronin, Leroy

2010-11-21

The reaction of molybdate with vanadium(V) in the presence of sulfite anions is explored showing how, via cation control, stepwise assembly through the {Mo(11)V(7)} cluster yields a {M(25)} cluster-based compound, [Mo(VI)(11)V(V)(5)V(IV)(2)O(52)(μ(9)-SO(3))(Mo(VI)(6)V(V)O(22))](10-) (1a), which was first discovered using cryospray mass spectrometry, whereas switching the cation away from ammonium allows the direct formation of the spherical 'Keplerate' {Mo(72)V(30)} cluster.

A method to determine agro-climatic zones based on correlation and cluster analyses

NASA Astrophysics Data System (ADS)

Borges Valeriano, Taynara Tuany; de Souza Rolim, Glauco; de Oliveira Aparecido, Lucas Eduardo

2017-12-01

Determining agro-climatic zones (ACZs) is traditionally made by cross-comparing meteorological elements such as air temperature, rainfall, and water deficit (DEF). This study proposes a new method based on correlations between monthly DEFs during the crop cycle and annual yield and performs a multivariate cluster analysis on these correlations. This `correlation method' was applied to all municipalities in the state of São Paulo to determine ACZs for coffee plantations. A traditional ACZ method for coffee, which is based on temperature and DEF ranges (Evangelista et al.; RBEAA, 6:445-452, 2002), was applied to the study area to compare against the correlation method. The traditional ACZ classified the "Alta Mogina," "Média Mogiana," and "Garça and Marília" regions as traditional coffee regions that were either suitable or even restricted for coffee plantations. These traditional regions have produced coffee since 1800 and should not be classified as restricted. The correlation method classified those areas as high-producing regions and expanded them into other areas. The proposed method is innovative, because it is more detailed than common ACZ methods. Each developmental crop phase was analyzed based on correlations between the monthly DEF and yield, improving the importance of crop physiology in relation to climate.

Chemistry of group 9 dimetallaborane analogues of octaborane(12).

PubMed

Barik, Subrat Kumar; Roy, Dipak Kumar; Ghosh, Sundargopal

2015-01-14

We report the synthesis, isolation and structural characterization of several moderately air stable nido-metallaboranes that represent boron rich open cage systems. The reaction of [Cp*CoCl]2, (Cp* = η(5)-C5Me5), with [BH3·thf] in toluene at ice cold temperature, followed by thermolysis in boiling toluene produced [(Cp*Co)B9H13], 1 [(Cp*Co)2B8H12], 2 and [(Cp*Co)2B6H10] 3. Building upon our earlier reactivity studies on rhodaboranes, we continue to explore the reactivity of dicobalt analogues of octaborane(12) cluster 3 with [Fe2(CO)9] and [Ru3(CO)12] at ambient conditions that yielded novel fused clusters [Fe2(CO)6(Cp*Co)2B6H10], 4 and [Ru4(CO)11(Cp*Co)2B3H3], 5 respectively. In an attempt to synthesize a heterometallic metallaborane compound we performed the reaction of [(Cp*Rh)2B6H10], 6 with [Cp*IrH4] that yielded a Ir-Ir double bonded compound [(Cp*Ir)2H3][B(OH)4], 7. All the new compounds have been characterized by IR, (1)H, (11)B, (13)C NMR spectroscopy, and the molecular structures were unambiguously established by X-ray diffraction analysis.

Variation in essential oil composition of Teucrium hircanicum L. from Iran-A rich source of (E)-α-bergamotene.

PubMed

Rahimi, Mohammad Ali; Nazeri, Vahideh; Andi, Seyed Ali; Sefidkon, Fatemeh

2018-05-21

In present work, the chemical composition of the essential oils obtained from dried flowering aerial parts of Teucrium hircanicum L. (Labiatae) originated from ten wild populations in Iran was analyzed by a GC-FID and GC/MS system. The oil yields varied from 0.04% to 0.1%. A total of thirty-two compounds representing 67.6-97.7% of the oil were identified. The essential oil was found to be rich in sesquiterpene hydrocarpons (E)-α-bergamotene (17.5-86.9%) and (E)-β-farnesene (0.5-21.4%). Of the total identified compounds, sesquiterpene hydrocarpons (36.1-89.7%) were included the greatest essential oil fraction in all the populations, followed by oxygenated monoterpenes (2.2-21.6%), oxygenated sesquiterpenes (0.0-14.4%) and monoterepene hydrocarbons (0.0-9.5%). Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were used to distinguish any geographical variations, indicating that the clustering of populations is related to their geographic origin. According to the GC/MS analysis, two chemotypes consisting of (E)-α-bergamotene and (E)-α-bergamotene-(E)-β-farnesene were identified in the populations.

Early Results from Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Dai, Xinyu; Griffin, Rhiannon; Nugent, Jenna; Kochanek, Christopher S.; Bregman, Joel N.

2016-04-01

The Swift AGN and Cluster Survey (SACS) uses 125 deg^2 of Swift X-ray Telescope serendipitous fields with variable depths surrounding gamma-ray bursts to provide a medium depth (4 × 10^-15 erg cm^-2 s^-1) and area survey filling the gap between deep, narrow Chandra/XMM-Newton surveys and wide, shallow ROSAT surveys. Here, we present the first two papers in a series of publications for SACS. In the first paper, we introduce our method and catalog of 22,563 point sources and 442 extended sources. SACS provides excellent constraints on the AGN and cluster number counts at the bright end with negligible uncertainties due to cosmic variance, and these constraints are consistent with previous measurements. The depth and areal coverage of SACS is well suited for galaxy cluster surveys outside the local universe, reaching z > 1 for massive clusters. In the second paper, we use SDSS DR8 data to study the 203 extended SACS sources that are located within the SDSS footprint. We search for galaxy over-densities in 3-D space using SDSS galaxies and their photometric redshifts near the Swift galaxy cluster candidates. We find 103 Swift clusters with a > 3σ over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmations as galaxy clusters. We present a series of cluster properties including the redshift, BCG magnitude, BCG-to-X-ray center offset, optical richness, X-ray luminosity and red sequences. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≤ 0.3 and 80% complete for z ≤ 0.4, consistent with the survey depth of SDSS. These analysis results suggest that our Swift cluster selection algorithm presented in our first paper has yielded a statistically well-defined cluster sample for further studying cluster evolution and cosmology. In the end, we will discuss our ongoing optical identification of z>0.5 cluster sample, using MDM, KPNO, CTIO, and Magellan data, and discuss SACS as a pilot for eROSITA deep surveys.

MACS: The impact of environment on galaxy evolution at z>0.5

NASA Astrophysics Data System (ADS)

Ma, Cheng-Jiun

2010-08-01

In order to investigate galaxy evolution in environments of greatly varying density, we conduct an extensive spectroscopic survey of galaxies in eight X-ray luminous clusters at redshift higher than 0.5. Unlike most spectroscopic surveys of cluster galaxies, we sample the galaxy population beyond the virial radius of each cluster (out to ˜6 Mpc), thereby probing regions that differ by typically two orders of magnitude in galaxy density. Galaxies are classified by spectroscopic type into emission-line, absorption-line, post starburst (E+A), and starburst (e(a) and e(b)) galaxies, and the spatial distribution of each type is used as a diagnostic of the presence and efficiency of different physical mechanisms of galaxy evolution. Our analysis yields the perhaps strongest confirmation so far of the morphology-density relation for emission- and absorption-line galaxies. In addition, we find E+A galaxies to be exclusively located within the ram-pressure stripping radius of each cluster. Taking advantage of this largest sample of E+A galaxies in clusters compiled to date, the spatial profile of the distribution of E+A galaxies can be studied for the first time. We show that ram-pressure stripping is the dominant, and possibly only, physical mechanism to cause the post-starburst phase of cluster galaxies. In addition, two particular interesting clusters are studied individually. For MACS J0717.5+3745, a clear morphology-density correlation is observed for lenticular (S0) galaxies around this cluster, but becomes insignificant toward the center of cluster. We interpret this finding as evidence of the creation of S0s being triggered primarily in environments of low to intermediate density. In MACS J0025.4-1225, a cluster undergoing a major merger, all faint E+A galaxies are observed to lie near the peak of the X-ray surface brightness, strongly suggesting that starbursts are enhanced as well as terminated during cluster mergers. We conclude that ram-pressure stripping and/or tidal destruction are central to the evolution of galaxies clusters, and that wide-field spectroscopic surveys around clusters are essential to distinguish between competing physical effects driving galaxy evolution in different environments.

Orientation of Calcium in the Mn4Ca Cluster of the Oxygen-Evolving Complex Determined Using Polarized Strontium EXAFS of Photosystem II Membranes†

PubMed Central

Cinco, Roehl M.; Robblee, John H.; Messinger, Johannes; Fernandez, Carmen; Holman, Karen L. McFarlane; Sauer, Kenneth; Yachandra, Vittal K.

2014-01-01

The oxygen-evolving complex of photosystem II (PS II) in green plants and algae contains a cluster of four Mn atoms in the active site, which catalyzes the photoinduced oxidation of water to dioxygen. Along with Mn, calcium and chloride ions are necessary cofactors for proper functioning of the complex. The current study using polarized Sr EXAFS on oriented Sr-reactivated samples shows that Fourier peak II, which fits best to Mn at 3.5 Å rather than lighter atoms (C, N, O, or Cl), is dichroic, with a larger magnitude at 10° (angle between the PS II membrane normal and the X-ray electric field vector) and a smaller magnitude at 80°. Analysis of the dichroism of the Sr EXAFS yields a lower and upper limit of 0° and 23° for the average angle between the Sr–Mn vectors and the membrane normal and an isotropic coordination number (number of Mn neighbors to Sr) of 1 or 2 for these layered PS II samples. The results confirm the contention that Ca (Sr) is proximal to the Mn cluster and lead to refined working models of the heteronuclear Mn4Ca cluster of the oxygen-evolving complex in PS II. PMID:15491134

A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering.

PubMed

Cheng, De; Nie, Feiping; Sun, Jiande; Gong, Yihong

2017-07-01

Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also be of low quality. We address this drawback by allowing the data graph itself to be adaptively adjusted in the clustering procedure. In particular, our proposed weight adaptive Laplacian (WAL) method learns a new data similarity matrix that can adaptively adjust the initial graph according to the similarity weight in the input data graph. We develop three versions of these methods based on the L2-norm, fuzzy entropy regularizer, and another exponential-based weight strategy, that yield three new graph-based clustering objectives. We derive optimization algorithms to solve these objectives. Experimental results on synthetic data sets and real-world benchmark data sets exhibit the effectiveness of these new graph-based clustering methods.

Photosensitized Reduction of Carbon Dioxide in Solution Using Noble-Metal Clusters for Electron Transfer

NASA Astrophysics Data System (ADS)

Toshima, Naoki; Yamaji, Yumi; Teranishi, Toshiharu; Yonezawa, Tetsu

1995-03-01

Carbon dioxide was reduced to methane by visible-light irradiation of a solution composed of tris(bipyridine)ruthenium(III) as photosensitizer, ethylenediaminetetraacetic acid disodium salt as sacrificial reagent, methyl viologen as electron relay, and a colloidal dispersion of polymer-protected noble-metal clusters, prepared by alcohol-reduction, as catalyst. Among the noble-metal clusters examined, Pt clusters showed the highest activity for the formation of methane as well as hydrogen. In order to improve the activity, oxidized clusters and bimetallic clusters were also applied. For example, the CH4 yield in 3-h irradiation increased from 51 x 10-3 μmol with unoxidized Pt clusters to 72 x 10-3 μmol with partially oxidized ones. In the case of Pt/Ru bimetalic systems, the improvement of the catalytic activity by air treatment was much greater than in case of monometallic clusters.

Chronology of the halo globular cluster system formation.

NASA Astrophysics Data System (ADS)

Salaris, M.; Weiss, A.

1997-11-01

Using up-to-date stellar models and isochrones we determine the age of 25 galactic halo clusters. The clusters are distributed into four groups according to metallicity. We measure the absolute age of a reference cluster in each group, and then find the relative ages of the other clusters relative to this one. This combination yields the most reliable results. We find that the oldest cluster group on average is 11.8+/-0.9Gyr or 12.3+/-0.3Gyr old, depending on whether we include Arp 2 and Rup 106. The average age of all clusters is about 10.5Gyr. Questions concerning a common age for all clusters and a relation between metallicity and age are addressed. The groups of lower metallicity appear to be coeval, but our results indicate that globally the sample has an age spread, and age and metallicity are correlated but not with a simple linear relation.

Comparison of five cluster validity indices performance in brain [18 F]FET-PET image segmentation using k-means.

PubMed

Abualhaj, Bedor; Weng, Guoyang; Ong, Melissa; Attarwala, Ali Asgar; Molina, Flavia; Büsing, Karen; Glatting, Gerhard

2017-01-01

Dynamic [ 18 F]fluoro-ethyl-L-tyrosine positron emission tomography ([ 18 F]FET-PET) is used to identify tumor lesions for radiotherapy treatment planning, to differentiate glioma recurrence from radiation necrosis and to classify gliomas grading. To segment different regions in the brain k-means cluster analysis can be used. The main disadvantage of k-means is that the number of clusters must be pre-defined. In this study, we therefore compared different cluster validity indices for automated and reproducible determination of the optimal number of clusters based on the dynamic PET data. The k-means algorithm was applied to dynamic [ 18 F]FET-PET images of 8 patients. Akaike information criterion (AIC), WB, I, modified Dunn's and Silhouette indices were compared on their ability to determine the optimal number of clusters based on requirements for an adequate cluster validity index. To check the reproducibility of k-means, the coefficients of variation CVs of the objective function values OFVs (sum of squared Euclidean distances within each cluster) were calculated using 100 random centroid initialization replications RCI 100 for 2 to 50 clusters. k-means was performed independently on three neighboring slices containing tumor for each patient to investigate the stability of the optimal number of clusters within them. To check the independence of the validity indices on the number of voxels, cluster analysis was applied after duplication of a slice selected from each patient. CVs of index values were calculated at the optimal number of clusters using RCI 100 to investigate the reproducibility of the validity indices. To check if the indices have a single extremum, visual inspection was performed on the replication with minimum OFV from RCI 100 . The maximum CV of OFVs was 2.7 × 10 -2 from all patients. The optimal number of clusters given by modified Dunn's and Silhouette indices was 2 or 3 leading to a very poor segmentation. WB and I indices suggested in median 5, [range 4-6] and 4, [range 3-6] clusters, respectively. For WB, I, modified Dunn's and Silhouette validity indices the suggested optimal number of clusters was not affected by the number of the voxels. The maximum coefficient of variation of WB, I, modified Dunn's, and Silhouette validity indices were 3 × 10 -2 , 1, 2 × 10 -1 and 3 × 10 -3 , respectively. WB-index showed a single global maximum, whereas the other indices showed also local extrema. From the investigated cluster validity indices, the WB-index is best suited for automated determination of the optimal number of clusters for [ 18 F]FET-PET brain images for the investigated image reconstruction algorithm and the used scanner: it yields meaningful results allowing better differentiation of tissues with higher number of clusters, it is simple, reproducible and has an unique global minimum. © 2016 American Association of Physicists in Medicine.

Performance of cancer cluster Q-statistics for case-control residential histories

PubMed Central

Sloan, Chantel D.; Jacquez, Geoffrey M.; Gallagher, Carolyn M.; Ward, Mary H.; Raaschou-Nielsen, Ole; Nordsborg, Rikke Baastrup; Meliker, Jaymie R.

2012-01-01

Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. Using residential histories from two cancer case-control studies, we created simulated clusters to examine Q-statistic performance. Results suggest the intersection of cases with significant clustering over their life course, Qi, with cases who are constituents of significant local clusters at given times, Qit, yielded the best performance, which improved with increasing cluster size. Upon comparison, a larger proportion of true positives were detected with Kulldorf’s spatial scan method if the time of clustering was provided. We recommend using Q-statistics to identify when and where clustering may have occurred, followed by the scan method to localize the candidate clusters. Future work should investigate the generalizability of these findings. PMID:23149326

Extreme ionization of Xe clusters driven by ultraintense laser fields

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

Heidenreich, Andreas; Last, Isidore; Jortner, Joshua

We applied theoretical models and molecular dynamics simulations to explore extreme multielectron ionization in Xe{sub n} clusters (n=2-2171, initial cluster radius R{sub 0}=2.16-31.0 A ring ) driven by ultraintense infrared Gaussian laser fields (peak intensity I{sub M}=10{sup 15}-10{sup 20} W cm{sup -2}, temporal pulse length {tau}=10-100 fs, and frequency {nu}=0.35 fs{sup -1}). Cluster compound ionization was described by three processes of inner ionization, nanoplasma formation, and outer ionization. Inner ionization gives rise to high ionization levels (with the formation of (Xe{sup q+}){sub n} with q=2-36), which are amenable to experimental observation. The cluster size and laser intensity dependence of themore » inner ionization levels are induced by a superposition of barrier suppression ionization (BSI) and electron impact ionization (EII). The BSI was induced by a composite field involving the laser field and an inner field of the ions and electrons, which manifests ignition enhancement and screening retardation effects. EII was treated using experimental cross sections, with a proper account of sequential impact ionization. At the highest intensities (I{sub M}=10{sup 18}-10{sup 20} W cm{sup -2}) inner ionization is dominated by BSI. At lower intensities (I{sub M}=10{sup 15}-10{sup 16} W cm{sup -2}), where the nanoplasma is persistent, the EII contribution to the inner ionization yield is substantial. It increases with increasing the cluster size, exerts a marked effect on the increase of the (Xe{sup q+}){sub n} ionization level, is most pronounced in the cluster center, and manifests a marked increase with increasing the pulse length (i.e., becoming the dominant ionization channel (56%) for Xe{sub 2171} at {tau}=100 fs). The EII yield and the ionization level enhancement decrease with increasing the laser intensity. The pulse length dependence of the EII yield at I{sub M}=10{sup 15}-10{sup 16} W cm{sup -2} establishes an ultraintense laser pulse length control mechanism of extreme ionization products.« less

Underestimated role of the secondary electron emission in the space

NASA Astrophysics Data System (ADS)

Nemecek, Zdenek; Richterova, Ivana; Safrankova, Jana; Pavlu, Jiri; Vaverka, Jakub; Nouzak, Libor

2016-07-01

Secondary electron emission (SEE) is one of many processes that charges surfaces of bodies immersed into a plasma. Until present, a majority of considerations in theories and experiments is based on the sixty year old description of an interaction of planar metallic surfaces with electrons, thus the effects of a surface curvature, roughness, presence of clusters as well as an influence of the material conductance on different aspects of this interaction are neglected. Dust grains or their clusters can be frequently found in many space environments - interstellar clouds, atmospheres of planets, tails of comets or planetary rings are only typical examples. The grains are exposed to electrons of different energies and they can acquire positive or negative charge during this interaction. We review the progress in experimental investigations and computer simulations of the SEE from samples relevant to space that was achieved in course of the last decade. We present a systematic study of well-defined systems that starts from spherical grains of various diameters and materials, and it continues with clusters consisting of different numbers of small spherical grains that can be considered as examples of real irregularly shaped space grains. The charges acquired by investigated objects as well as their secondary emission yields are calculated using the SEE model. We show that (1) the charge and surface potential of clusters exposed to the electron beam are influenced by the number of grains and by their geometry within a particular cluster, (2) the model results are in an excellent agreement with the experiment, and (3) there is a large difference between charging of a cluster levitating in the free space and that attached to a planar surface. The calculation provides a reduction of the secondary electron emission yield of the surface covered by dust clusters by a factor up to 1.5 with respect to the yield of a smooth surface. (4) These results are applied on charging of the lunar surface and the dust grains levitating above it, and it is shown that the SEE is more important for isolated dust grains than for the lunar surface covered by them.

Activation and products of the cryptic secondary metabolite biosynthetic gene clusters by rifampin resistance (rpoB) mutations in actinomycetes.

PubMed

Tanaka, Yukinori; Kasahara, Ken; Hirose, Yutaka; Murakami, Kiriko; Kugimiya, Rie; Ochi, Kozo

2013-07-01

A subset of rifampin resistance (rpoB) mutations result in the overproduction of antibiotics in various actinomycetes, including Streptomyces, Saccharopolyspora, and Amycolatopsis, with H437Y and H437R rpoB mutations effective most frequently. Moreover, the rpoB mutations markedly activate (up to 70-fold at the transcriptional level) the cryptic/silent secondary metabolite biosynthetic gene clusters of these actinomycetes, which are not activated under general stressful conditions, with the exception of treatment with rare earth elements. Analysis of the metabolite profile demonstrated that the rpoB mutants produced many metabolites, which were not detected in the wild-type strains. This approach utilizing rifampin resistance mutations is characterized by its feasibility and potential scalability to high-throughput studies and would be useful to activate and to enhance the yields of metabolites for discovery and biochemical characterization.

Resilient, undercontrolled, and overcontrolled personality prototypes among persons with spinal cord injury.

PubMed

Berry, Jack W; Elliott, Timothy R; Rivera, Patricia

2007-12-01

A sample of 199 persons with spinal cord injury (SCI) were assessed on Big Five personality dimensions using the NEO Five-Factor Inventory (NEO-FFI; Costa & McCrae, 1992) at admission to an inpatient medical rehabilitation program. A cluster analysis of the baseline NEO-FFI yielded 3 cluster prototypes that resemble resilient, undercontrolled, and overcontrolled prototypes identified in many previous studies of children and adult community samples. Compared with normative samples, this sample had significantly fewer resilient prototypes and significantly more overcontrolled and undercontrolled prototypes. Undercontrolled individuals were the modal prototype. The resilient and undercontrolled types were better adjusted than the overcontrolled types, showing lower levels of depression at admission and higher acceptance of disability at discharge. The resilient type at admission predicted the most effective reports of social problem-solving abilities at discharge and the overcontrolled type the least. We discuss the implications of these results for assessment and interventions in rehabilitation settings.

Analysis of Genetic Diversity and Structure Pattern of Indigofera Pseudotinctoria in Karst Habitats of the Wushan Mountains Using AFLP Markers.

PubMed

Fan, Yan; Zhang, Chenglin; Wu, Wendan; He, Wei; Zhang, Li; Ma, Xiao

2017-10-16

Indigofera pseudotinctoria Mats is an agronomically and economically important perennial legume shrub with a high forage yield, protein content and strong adaptability, which is subject to natural habitat fragmentation and serious human disturbance. Until now, our knowledge of the genetic relationships and intraspecific genetic diversity for its wild collections is still poor, especially at small spatial scales. Here amplified fragment length polymorphism (AFLP) technology was employed for analysis of genetic diversity, differentiation, and structure of 364 genotypes of I. pseudotinctoria from 15 natural locations in Wushan Montain, a highly structured mountain with typical karst landforms in Southwest China. We also tested whether eco-climate factors has affected genetic structure by correlating genetic diversity with habitat features. A total of 515 distinctly scoreable bands were generated, and 324 of them were polymorphic. The polymorphic information content (PIC) ranged from 0.694 to 0.890 with an average of 0.789 per primer pair. On species level, Nei's gene diversity ( H j ), the Bayesian genetic diversity index ( H B ) and the Shannon information index ( I ) were 0.2465, 0.2363 and 0.3772, respectively. The high differentiation among all sampling sites was detected ( F ST = 0.2217, G ST = 0.1746, G' ST = 0.2060, θ B = 0.1844), and instead, gene flow among accessions ( N m = 1.1819) was restricted. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. The population genetic structure resolved by the UPGMA tree, principal coordinate analysis, and Bayesian-based cluster analyses irrefutably grouped all accessions into two distinct clusters, i.e., lowland and highland groups. This structure pattern may indicate joint effects by the neutral evolution and natural selection. Restricted N m was observed across all accessions, and genetic barriers were detected between adjacent accessions due to specifically geographical landform.

Psychometric properties of the Social Interaction Anxiety Scale and separation criterion between Spanish youths with and without subtypes of social anxiety.

PubMed

Zubeidat, Ihab; Salinas, José María; Sierra, Juan Carlos; Fernández-Parra, Antonio

2007-01-01

In this study, we analyzed the reliability and validity of the Social Interaction Anxiety Scale (SIAS) and propose a separation criterion between youths with specific and generalized social anxiety and youths without social anxiety. A sample of 1012 Spanish youths attending school completed the SIAS, the Liebowitz Social Anxiety Scale, the Social Avoidance and Distress Scale, the Fear of Negative Evaluation Scale, the Youth Self-Report for Ages 11-18 and the Minnesota Multiphasic Personality Inventory-Adolescent. The factor analysis suggests the existence of three factors in the SIAS, the first two of which explain most of the variance of the construct assessed. Internal consistency is adequate in the first two factors. The SIAS features an adequate theoretical validity with the scores of different variables related to social interaction. Analysis of the criterion scores yields three groups pertaining to three clearly differentiated clusters. In the third cluster, two of social anxiety groups - specific and generalized - have been identified by means of a quantitative separation criterion.

NGC 346: Looking in the Cradle of a Massive Star Cluster

NASA Astrophysics Data System (ADS)

Gouliermis, Dimitrios A.; Hony, Sacha

2017-03-01

How does a star cluster of more than few 10,000 solar masses form? We present the case of the cluster NGC 346 in the Small Magellanic Cloud, still embedded in its natal star-forming region N66, and we propose a scenario for its formation, based on observations of the rich stellar populations in the region. Young massive clusters host a high fraction of early-type stars, indicating an extremely high star formation efficiency. The Milky Way galaxy hosts several young massive clusters that fill the gap between young low-mass open clusters and old massive globular clusters. Only a handful, though, are young enough to study their formation. Moreover, the investigation of their gaseous natal environments suffers from contamination by the Galactic disk. Young massive clusters are very abundant in distant starburst and interacting galaxies, but the distance of their hosting galaxies do not also allow a detailed analysis of their formation. The Magellanic Clouds, on the other hand, host young massive clusters in a wide range of ages with the youngest being still embedded in their giant HII regions. Hubble Space Telescope imaging of such star-forming complexes provide a stellar sampling with a high dynamic range in stellar masses, allowing the detailed study of star formation at scales typical for molecular clouds. Our cluster analysis on the distribution of newly-born stars in N66 shows that star formation in the region proceeds in a clumpy hierarchical fashion, leading to the formation of both a dominant young massive cluster, hosting about half of the observed pre-main-sequence population, and a self-similar dispersed distribution of the remaining stars. We investigate the correlation between stellar surface density (and star formation rate derived from star-counts) and molecular gas surface density (derived from dust column density) in order to unravel the physical conditions that gave birth to NGC 346. A power law fit to the data yields a steep correlation between these two parameters with a considerable scatter. The fraction of stellar over the total (gas plus young stars) mass is found to be systematically higher within the central 15 pc (where the young massive cluster is located) than outside, which suggests variations in the star formation efficiency within the same star-forming complex. This trend possibly reflects a change of star formation efficiency in N66 between clustered and non-clustered star formation. Our findings suggest that the formation of NGC 346 is the combined result of star formation regulated by turbulence and of early dynamical evolution induced by the gravitational potential of the dense interstellar medium.

Characterization of Mycobacterium tuberculosis isolates from Hebei, China: genotypes and drug susceptibility phenotypes.

PubMed

Li, Yanan; Cao, Xinrui; Li, Shiming; Wang, Hao; Wei, Jianlin; Liu, Peng; Wang, Jing; Zhang, Zhi; Gao, Huixia; Li, Machao; Wan, Kanglin; Dai, Erhei

2016-03-03

Tuberculosis remains a major public health problem in China. The Hebei province is located in the Beijing-Tianjin-Hebei integration region; however little information about the genetic diversity of Mycobacterium tuberculosis was available in this area. This study describes the first attempt to map the molecular epidemiology of MTB strains isolated from Hebei. Spoligotyping and 15-locus MIRU-VNTR were performed in combination to yield specific genetic profiles of 1017 MTB strains isolated from ten cities in the Hebei province in China during 2014. Susceptibility testing to first line anti-TB drugs was also conducted for all strains using the L-J proportion method. Based on the SpolDB4.0 database, the predominant spoligotype belonged to the Beijing family (90.5%), followed by T family (6.3%). Using 15-locus MIRU-VNTR clustering analysis, 846 different patterns were identified, including 84 clusters (2-17 strains per cluster) and 764 individual types. Drug susceptibility pattern showed that 347 strains (34.1%) were resistant to at least one of the first line drugs, including 134 (13.2%) multi-drug resistance strains. Statistical analysis indicated that drug resistance was associated with treatment history. The Beijing family was associated with genetic clustering. However, no significant difference was observed between the Beijing and non-Beijing family in gender, age, treatment history and drug resistance. The Mycobacterium tuberculosis strains in Hebei exhibit high genetic diversity. The Beijing family is the most prevalent lineage in this area. Spoligotyping in combination with 15-locus MIRU-VNTR is a useful tool to study the molecular epidemiology of the MTB strains in Hebei.

Vineyard floor management and cluster thinning inconsistently affect ‘Pinot noir’ crop load, berry composition, and wine quality

USDA-ARS?s Scientific Manuscript database

A 3-year field study was developed to determine relationships between crop load metrics and berry composition for ‘Pinot noir’ in a cool-climate through the manipulation of vegetative growth and fruit yield using competitive cover cropping and cluster thinning, respectively. To alter vine vigor, per...

Star-like supramolecular polymers fabricated by a Keplerate cluster with cationic terminated polymers and their self-assembly into vesicles.

PubMed

Zhang, Qian; He, Lipeng; Wang, Hui; Zhang, Cheng; Liu, Weisheng; Bu, Weifeng

2012-07-18

The electrostatic combination of a Keplerate cluster, [Mo(132)O(372)(CH(3)COO)(30)(H(2)O)(72)](42-) with cationic terminated poly(styrene) yields polyoxometalate-based supramolecular star polymers, which can further self-assemble into vesicular aggregates in CHCl(3)-MeOH mixed solvent.

Metal-assisted SIMS and cluster ion bombardment for ion yield enhancement

NASA Astrophysics Data System (ADS)

Heile, A.; Lipinsky, D.; Wehbe, N.; Delcorte, A.; Bertrand, P.; Felten, A.; Houssiau, L.; Pireaux, J.-J.; De Mondt, R.; Van Vaeck, L.; Arlinghaus, H. F.

2008-12-01

In addition to structural information, a detailed knowledge of the local chemical environment proves to be of ever greater importance, for example for the development of new types of materials as well as for specific modifications of surfaces and interfaces in multiple fields of materials science or various biomedical and chemical applications. But the ongoing miniaturization and therefore reduction of the amount of material available for analysis constitute a challenge to the detection limits of analytical methods. In the case of time-of-flight secondary ion mass spectrometry (TOF-SIMS), several methods of secondary ion yield enhancement have been proposed. This paper focuses on the investigation of the effects of two of these methods, metal-assisted SIMS and polyatomic primary ion bombardment. For this purpose, thicker layers of polystyrene (PS), both pristine and metallized with different amounts of gold, were analyzed using monoatomic (Ar +, Ga +, Xe +, Bi +) and polyatomic (SF 5+, Bi 3+, C 60+) primary ions. It was found that polyatomic ions generally induce a significant increase of the secondary ion yield. On the other hand, with gold deposition, a yield enhancement can only be detected for monoatomic ion bombardment.

Discovering Massive z > 1 Galaxy Clusters with Spitzer and SPTpol

NASA Astrophysics Data System (ADS)

Bleem, Lindsey; Brodwin, Mark; Ashby, Matthew; Stalder, Brian; Klein, Matthias; Gladders, Michael; Stanford, Spencer; Canning, Rebecca

2018-05-01

We propose to obtain Spitzer/IRAC imaging of 50 high-redshift galaxy cluster candidates derived from two new completed SZ cluster surveys by the South Pole Telescope. Clusters from the deep SPTpol 500-square-deg main survey will extend high-redshift SZ cluster science to lower masses (median M500 2x10^14Msun) while systems drawn from the wider 2500-sq-deg SPTpol Extended Cluster Survey are some of the rarest most massive high-z clusters in the observable universe. The proposed small 10 h program will enable (1) confirmation of these candidates as high-redshift clusters, (2) measurements of the cluster redshifts (sigma_z/(1+z) 0.03), and (3) estimates of the stellar masses of the brightest cluster members. These observations will yield exciting and timely targets for the James Webb Space Telescope--and, combined with lower-z systems--will both extend cluster tests of dark energy to z>1 as well as enable studies of galaxy evolution in the richest environments for a mass-limited cluster sample from 0

Macula segmentation and fovea localization employing image processing and heuristic based clustering for automated retinal screening.

PubMed

R, GeethaRamani; Balasubramanian, Lakshmi

2018-07-01

Macula segmentation and fovea localization is one of the primary tasks in retinal analysis as they are responsible for detailed vision. Existing approaches required segmentation of retinal structures viz. optic disc and blood vessels for this purpose. This work avoids knowledge of other retinal structures and attempts data mining techniques to segment macula. Unsupervised clustering algorithm is exploited for this purpose. Selection of initial cluster centres has a great impact on performance of clustering algorithms. A heuristic based clustering in which initial centres are selected based on measures defining statistical distribution of data is incorporated in the proposed methodology. The initial phase of proposed framework includes image cropping, green channel extraction, contrast enhancement and application of mathematical closing. Then, the pre-processed image is subjected to heuristic based clustering yielding a binary map. The binary image is post-processed to eliminate unwanted components. Finally, the component which possessed the minimum intensity is finalized as macula and its centre constitutes the fovea. The proposed approach outperforms existing works by reporting that 100%,of HRF, 100% of DRIVE, 96.92% of DIARETDB0, 97.75% of DIARETDB1, 98.81% of HEI-MED, 90% of STARE and 99.33% of MESSIDOR images satisfy the 1R criterion, a standard adopted for evaluating performance of macula and fovea identification. The proposed system thus helps the ophthalmologists in identifying the macula thereby facilitating to identify if any abnormality is present within the macula region. Copyright © 2018 Elsevier B.V. All rights reserved.

An investigation into anti-proliferative effects of microRNAs encoded by the miR-106a-363 cluster on human carcinoma cells and keratinocytes using microarray profiling of miRNA transcriptomes

PubMed Central

Khuu, Cuong; Jevnaker, Anne-Marthe; Bryne, Magne; Osmundsen, Harald

2014-01-01

Transfection of human oral squamous carcinoma cells (clone E10) with mimics for unexpressed miR-20b or miR-363-5p, encoded by the miR-106a-363 cluster (miR-20b, miR-106a, miR-363-3p, or miR-363-5p), caused 40–50% decrease in proliferation. Transfection with mimics for miR-18a or miR-92a, encoded by the miR-17-92 cluster (all members being expressed in E10 cells), had no effect on proliferation. In contrast, mimic for the sibling miRNA-19a yielded about 20% inhibition of proliferation. To investigate miRNA involvement profiling of miRNA transcriptomes were carried out using deoxyoligonucleotide microarrays. In transfectants for miR-19a, or miR-20b or miR-363-5p most differentially expressed miRNAs exhibited decreased expression, including some miRNAs encoded in paralogous miR-17-92—or miR-106b-25 cluster. Only in cells transfected with miR-19a mimic significantly increased expression of miR-20b observed—about 50-fold as judged by qRT-PCR. Further studies using qRT-PCR showed that transfection of E10 cells with mimic for miRNAs encoded by miR-17-92 - or miR-106a-363 - or the miR-106b-25 cluster confirmed selective effect on expression on sibling miRNAs. We conclude that high levels of miRNAs encoded by the miR-106a-363 cluster may contribute to inhibition of proliferation by decreasing expression of several sibling miRNAs encoded by miR-17-92 or by the miR-106b-25 cluster. The inhibition of proliferation observed in miR-19a-mimic transfectants is likely caused by the miR-19a-dependent increase in the levels of miR-20b and miR-106a. Bioinformatic analysis of differentially expressed miRNAs from miR-106a, miR-20b and miR-363-5p transfectants, but not miR-92a transfectants, yielded significant associations to “Cellular Growth and Proliferation” and “Cell Cycle.” Western blotting results showed that levels of affected proteins to differ between transfectants, suggesting that different anti-proliferative mechanisms may operate in these transfectants. PMID:25202322

SACE_5599, a putative regulatory protein, is involved in morphological differentiation and erythromycin production in Saccharopolyspora erythraea.

PubMed

Kirm, Benjamin; Magdevska, Vasilka; Tome, Miha; Horvat, Marinka; Karničar, Katarina; Petek, Marko; Vidmar, Robert; Baebler, Spela; Jamnik, Polona; Fujs, Štefan; Horvat, Jaka; Fonovič, Marko; Turk, Boris; Gruden, Kristina; Petković, Hrvoje; Kosec, Gregor

2013-12-17

Erythromycin is a medically important antibiotic, biosynthesized by the actinomycete Saccharopolyspora erythraea. Genes encoding erythromycin biosynthesis are organized in a gene cluster, spanning over 60 kbp of DNA. Most often, gene clusters encoding biosynthesis of secondary metabolites contain regulatory genes. In contrast, the erythromycin gene cluster does not contain regulatory genes and regulation of its biosynthesis has therefore remained poorly understood, which has for a long time limited genetic engineering approaches for erythromycin yield improvement. We used a comparative proteomic approach to screen for potential regulatory proteins involved in erythromycin biosynthesis. We have identified a putative regulatory protein SACE_5599 which shows significantly higher levels of expression in an erythromycin high-producing strain, compared to the wild type S. erythraea strain. SACE_5599 is a member of an uncharacterized family of putative regulatory genes, located in several actinomycete biosynthetic gene clusters. Importantly, increased expression of SACE_5599 was observed in the complex fermentation medium and at controlled bioprocess conditions, simulating a high-yield industrial fermentation process in the bioreactor. Inactivation of SACE_5599 in the high-producing strain significantly reduced erythromycin yield, in addition to drastically decreasing sporulation intensity of the SACE_5599-inactivated strains when cultivated on ABSM4 agar medium. In contrast, constitutive overexpression of SACE_5599 in the wild type NRRL23338 strain resulted in an increase of erythromycin yield by 32%. Similar yield increase was also observed when we overexpressed the bldD gene, a previously identified regulator of erythromycin biosynthesis, thereby for the first time revealing its potential for improving erythromycin biosynthesis. SACE_5599 is the second putative regulatory gene to be identified in S. erythraea which has positive influence on erythromycin yield. Like bldD, SACE_5599 is involved in morphological development of S. erythraea, suggesting a very close relationship between secondary metabolite biosynthesis and morphological differentiation in this organism. While the mode of action of SACE_5599 remains to be elucidated, the manipulation of this gene clearly shows potential for improvement of erythromycin production in S. erythraea in industrial setting. We have also demonstrated the applicability of the comparative proteomics approach for identifying new regulatory elements involved in biosynthesis of secondary metabolites in industrial conditions.

SACE_5599, a putative regulatory protein, is involved in morphological differentiation and erythromycin production in Saccharopolyspora erythraea

PubMed Central

2013-01-01

Background Erythromycin is a medically important antibiotic, biosynthesized by the actinomycete Saccharopolyspora erythraea. Genes encoding erythromycin biosynthesis are organized in a gene cluster, spanning over 60 kbp of DNA. Most often, gene clusters encoding biosynthesis of secondary metabolites contain regulatory genes. In contrast, the erythromycin gene cluster does not contain regulatory genes and regulation of its biosynthesis has therefore remained poorly understood, which has for a long time limited genetic engineering approaches for erythromycin yield improvement. Results We used a comparative proteomic approach to screen for potential regulatory proteins involved in erythromycin biosynthesis. We have identified a putative regulatory protein SACE_5599 which shows significantly higher levels of expression in an erythromycin high-producing strain, compared to the wild type S. erythraea strain. SACE_5599 is a member of an uncharacterized family of putative regulatory genes, located in several actinomycete biosynthetic gene clusters. Importantly, increased expression of SACE_5599 was observed in the complex fermentation medium and at controlled bioprocess conditions, simulating a high-yield industrial fermentation process in the bioreactor. Inactivation of SACE_5599 in the high-producing strain significantly reduced erythromycin yield, in addition to drastically decreasing sporulation intensity of the SACE_5599-inactivated strains when cultivated on ABSM4 agar medium. In contrast, constitutive overexpression of SACE_5599 in the wild type NRRL23338 strain resulted in an increase of erythromycin yield by 32%. Similar yield increase was also observed when we overexpressed the bldD gene, a previously identified regulator of erythromycin biosynthesis, thereby for the first time revealing its potential for improving erythromycin biosynthesis. Conclusions SACE_5599 is the second putative regulatory gene to be identified in S. erythraea which has positive influence on erythromycin yield. Like bldD, SACE_5599 is involved in morphological development of S. erythraea, suggesting a very close relationship between secondary metabolite biosynthesis and morphological differentiation in this organism. While the mode of action of SACE_5599 remains to be elucidated, the manipulation of this gene clearly shows potential for improvement of erythromycin production in S. erythraea in industrial setting. We have also demonstrated the applicability of the comparative proteomics approach for identifying new regulatory elements involved in biosynthesis of secondary metabolites in industrial conditions. PMID:24341557

Genetic diversity among Puccinia melanocephala isolates from Brazil assessed using simple sequence repeat markers.

PubMed

Peixoto-Junior, R F; Creste, S; Landell, M G A; Nunes, D S; Sanguino, A; Campos, M F; Vencovsky, R; Tambarussi, E V; Figueira, A

2014-09-26

Brown rust (causal agent Puccinia melanocephala) is an important sugarcane disease that is responsible for large losses in yield worldwide. Despite its importance, little is known regarding the genetic diversity of this pathogen in the main Brazilian sugarcane cultivation areas. In this study, we characterized the genetic diversity of 34 P. melanocephala isolates from 4 Brazilian states using loci identified from an enriched simple sequence repeat (SSR) library. The aggressiveness of 3 isolates from major sugarcane cultivation areas was evaluated by inoculating an intermediately resistant and a susceptible cultivar. From the enriched library, 16 SSR-specific primers were developed, which produced scorable alleles. Of these, 4 loci were polymorphic and 12 were monomorphic for all isolates evaluated. The molecular characterization of the 34 isolates of P. melanocephala conducted using 16 SSR loci revealed the existence of low genetic variability among the isolates. The average estimated genetic distance was 0.12. Phenetic analysis based on Nei's genetic distance clustered the isolates into 2 major groups. Groups I and II included 18 and 14 isolates, respectively, and both groups contained isolates from all 4 geographic regions studied. Two isolates did not cluster with these groups. It was not possible to obtain clusters according to location or state of origin. Analysis of disease severity data revealed that the isolates did not show significant differences in aggressiveness between regions.

Diagnostic Criteria for Cannabis Withdrawal Syndrome

PubMed Central

Gorelick, David A.; Levin, Kenneth H.; Copersino, Marc L.; Heishman, Stephen J.; Liu, Fang; Boggs, Douglas L.; Kelly, Deanna L.

2011-01-01

Objective Cannabis withdrawal occurs in frequent users who quit, but there are no accepted diagnostic criteria for a cannabis withdrawal syndrome (CWS). This study evaluated diagnostic criteria for CWS proposed in DSM-V and two earlier proposals. Method A convenience sample of 384 adult, non-treatment-seeking lifetime cannabis smokers provided retrospective self-report data on their “most difficult” quit attempt without formal treatment, which was used in this secondary analysis. Prevalence, time of onset, and peak intensity (5-point Likert scale) for 39 withdrawal symptoms (drawn from the literature) were assessed via computer-administered questionnaire. Subject groups were compared using chi-square or ANOVA. Symptom clustering was evaluated with principal components analysis. Results 40.9% of subjects met the DSM-V criterion of ≥ 3 symptoms from a list of 7. There were no associations with sex, race, or type of cannabis preparation used. There were significant positive associations between duration or frequency of cannabis use prior to the quit attempt and experiencing CWS. Subjects with CWS had a significantly shorter duration of abstinence. Alternative syndromal criteria (dropping physical symptoms from DSM-V list; requiring ≥ 2or ≥ 4 symptoms from a list of 11) yielded a similar prevalence of CWS and similar associations with prior cannabis use and relapse. The PCA yielded 12 factors, including some symptom clusters not included in DSM-V. Conclusions Findings support the concurrent and predictive validity of the proposed DSM-V CWS, but suggest that the list of withdrawal symptoms and number required for diagnosis warrant further evaluation. PMID:22153944

CLASH: MASS DISTRIBUTION IN AND AROUND MACS J1206.2-0847 FROM A FULL CLUSTER LENSING ANALYSIS

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

Umetsu, Keiichi; Koch, Patrick M.; Lin, Kai-Yang

2012-08-10

We derive an accurate mass distribution of the galaxy cluster MACS J1206.2-0847 (z = 0.439) from a combined weak-lensing distortion, magnification, and strong-lensing analysis of wide-field Subaru BVR{sub c} I{sub c} z' imaging and our recent 16-band Hubble Space Telescope observations taken as part of the Cluster Lensing And Supernova survey with Hubble program. We find good agreement in the regions of overlap between several weak- and strong-lensing mass reconstructions using a wide variety of modeling methods, ensuring consistency. The Subaru data reveal the presence of a surrounding large-scale structure with the major axis running approximately northwest-southeast (NW-SE), aligned withmore » the cluster and its brightest galaxy shapes, showing elongation with a {approx}2: 1 axis ratio in the plane of the sky. Our full-lensing mass profile exhibits a shallow profile slope dln {Sigma}/dln R {approx} -1 at cluster outskirts (R {approx}> 1 Mpc h{sup -1}), whereas the mass distribution excluding the NW-SE excess regions steepens farther out, well described by the Navarro-Frenk-White form. Assuming a spherical halo, we obtain a virial mass M{sub vir} = (1.1 {+-} 0.2 {+-} 0.1) Multiplication-Sign 10{sup 15} M{sub Sun} h{sup -1} and a halo concentration c{sub vir} = 6.9 {+-} 1.0 {+-} 1.2 (c{sub vir} {approx} 5.7 when the central 50 kpc h{sup -1} is excluded), which falls in the range 4 {approx}< (c) {approx}< 7 of average c(M, z) predictions for relaxed clusters from recent {Lambda} cold dark matter simulations. Our full-lensing results are found to be in agreement with X-ray mass measurements where the data overlap, and when combined with Chandra gas mass measurements, they yield a cumulative gas mass fraction of 13.7{sup +4.5}{sub -3.0}% at 0.7 Mpc h{sup -1}( Almost-Equal-To 1.7 r{sub 2500}), a typical value observed for high-mass clusters.« less

New z>2 clusters unveiled by Planck, Herschel & Spitzer - prospects for JWST & Euclid

NASA Astrophysics Data System (ADS)

Dole, Herve A.

2015-08-01

Searching for z>2 clusters/protoclusters is an active field in cosmology, and quite successfull using wide near-infrared surveys (e.g. Spitzer). We present a new approach by selecting highly star forming high-z cluster candidates over the whole sky using Planck, taking benefit of the redshifted far-infrared peak into the Planck submillimetre channels and a clean component separation (among which Galactic cirrus & CMB). Out of more than 1000 Planck high-z candidates, about 230 were confirmed by a Herschel/SPIRE follow-up as significant overdensities of red sources, confirming their high-z spectral energy distribution and high star formation rates (typically 700 Msun/yr per SPIRE source, and >5000 Msun/yr for each structure). These overdensities could be protoclusters in their intense star formation phase. Few targets have spectroscopic redshift (in the NIR and mm) confirmations, all in the range 1.7-2.3, while photometric analysis indicates z>2 for all the Planck counterparts.The key points here are the wavelength plus the angular and resolution coverage from Planck, Herschel and Spitzer. 40 fields were followed-up by Spitzer down to 1uJy 5sigma, and show unambiguous presence of galaxy overdensities compatible with z~2 based on color analysis on 4 band photometry (J, K, 3.6 and 4.5um). These targetted Spitzer observations can serve as pilot project for the more extended data coming in the next decade with JWST and Euclid.This new window on the high-z (z>2) protocluster may yield powerful constraints on structure formation (e.g., SFR vs environnement at high-z, z>2 mass assembly in clusters, bias). Furthermore, these objects will allow to better quantify the prediction for clusters to be detected by WFIRST and Euclid. Finally, these clusters will help us extending the current search for high-z clusters, in nice complementarity with current selections in the near-infrared (dominated by stellar mass) and the millimeter (dominated by hot gas and SZ effect), using the far-infrared and submillimetre (dominated by star formation). My talk will review all these aspects.

New z>2 clusters unveiled by Planck, Herschel & Spitzer - prospects for JWST, Euclid, WFIRST

NASA Astrophysics Data System (ADS)

Dole, Herve A.

2015-08-01

Searching for z>2 clusters/protoclusters is an active field in cosmology, and quite successfull using wide near-infrared surveys (e.g. Spitzer). We present a new approach by selecting highly star forming high-z cluster candidates over the whole sky using Planck, taking benefit of the redshifted far-infrared peak into the Planck submillimetre channels and a clean component separation (among which Galactic cirrus & CMB). Out of more than 1000 Planck high-z candidates, about 230 were confirmed by a Herschel/SPIRE follow-up as significant overdensities of red sources, confirming their high-z spectral energy distribution and high star formation rates (typically 700 Msun/yr per SPIRE source, and >5000 Msun/yr for each structure). These overdensities could be protoclusters in their intense star formation phase. Few targets have spectroscopic redshift (in the NIR and mm) confirmations, all in the range 1.7-2.3, while photometric analysis indicates z>2 for all the Planck counterparts.The key points here are the wavelength plus the angular and resolution coverage from Planck, Herschel and Spitzer. 40 fields were followed-up by Spitzer down to 1uJy 5sigma, and show unambiguous presence of galaxy overdensities compatible with z~2 based on color analysis on 4 band photometry (J, K, 3.6 and 4.5um). These targetted Spitzer observations can serve as pilot project for the more extended data coming in the next decade with JWST and Euclid.This new window on the high-z (z>2) protocluster may yield powerful constraints on structure formation (e.g., SFR vs environnement at high-z, z>2 mass assembly in clusters, bias). Furthermore, these objects will allow to better quantify the prediction for clusters to be detected by WFIRST and Euclid. Finally, these clusters will help us extending the current search for high-z clusters, in nice complementarity with current selections in the near-infrared (dominated by stellar mass) and the millimeter (dominated by hot gas and SZ effect), using the far-infrared and submillimetre (dominated by star formation). My talk will review all these aspects.

Low-temperature, high yield synthesis, and convenient isolation of the high-electron-density cluster compound Ta6Br14.8H2O for use in biomacromolecular crystallographic phase determination.

PubMed

Hay, Daniel N T; Messerle, Louis

2002-09-01

Reduction of TaBr(5) with Ga in the presence of KBr in a sealed borosilicate ampule at 400 degrees, followed by aqueous Soxhlet extraction and addition of stannous bromide and hydrobromic acid to the extract, yielded Ta(6)Br(14).8H(2)O in 80-84% yield. The new procedure provides a convenient, low temperature, high yield route to the synthesis of the title compound from inexpensive precursors.

Dynamic Reactive Ionization with Cluster Secondary Ion Mass Spectrometry

NASA Astrophysics Data System (ADS)

Tian, Hua; Wucher, Andreas; Winograd, Nicholas

2016-02-01

Gas cluster ion beams (GCIB) have been tuned to enhance secondary ion yields by doping small gas molecules such as CH4, CO2, and O2 into an Ar cluster projectile, Arn + ( n = 1000-10,000) to form a mixed cluster. The `tailored beam' has the potential to expand the application of secondary ion mass spectrometry for two- and three-dimensional molecular specific imaging. Here, we examine the possibility of further enhancing the ionization by doping HCl into the Ar cluster. Water deposited on the target surface facilitates the dissociation of HCl. This concerted effect, occurring only at the impact site of the cluster, arises since the HCl is chemically induced to ionize to H+ and Cl- , allowing improved protonation of neutral molecular species. This hypothesis is confirmed by depth profiling through a trehalose thin film exposed to D2O vapor, resulting in ~20-fold increase in protonated molecules. The results show that it is possible to dynamically maintain optimum ionization conditions during depth profiling by proper adjustment of the water vapor pressure. H-D exchange in the trehalose molecule M was monitored upon deposition of D2O on the target surface, leading to the observation of [Mn* + H]+ or [Mn* + D]+ ions, where n = 1-8 hydrogen atoms in the trehalose molecule M have been replaced by deuterium. In general, we discuss the role of surface chemistry and dynamic reactive ionization of organic molecules in increasing the secondary ion yield.

Genetic characteristics of Streptococcus dysgalactiae isolated from cage cultured cobia, Rachycentron canadum (L.).

PubMed

Tsai, M-A; Wang, P-C; Yoshida, T; Chen, S-C

2015-12-01

Disease outbreaks occurred during 2007-2013 in Taiwan with 2.5-10% mortality among the cage cultured cobia, Rachycentron canadum (L.), characterized by the presence of polyserositis, pericarditis and peritonitis. The micro-organisms isolated from internal organs were Gram-positive cocci. The isolates were confirmed as Streptococcus dysgalactiae by a polymerase chain reaction assay that yielded the expected specific 259 bp amplicon. Additionally, partial sequence of the 16S-23S rDNA intergenic spacer region of the GCS strain isolates from fish was also compared and produced 100% sequence identity with S. dysgalactiae (GenBank accession number AB252398). The genetic characterization was then determined by pulsed-field gel electrophoresis (PFGE) analysis. Based on PFGE, the Apa I or Sma I digestion patterns of chromosomal DNA of these isolates were grouped into three main clusters. Taiwanese strains were divided into two clusters, and the tet(M) gene was detected in cluster 1 (pulsotypes: A1-A2 and S1-S3), but not in cluster 2 strains (pulsotypes: A3-A4 and S4-S5). Three Japanese strains from amberjack, Seriola dumerili (Risso), were grouped into cluster 3 (pulsotypes: A5-A7 and S6-S8) and displayed no mortality to cobia in the challenge experiment. Conversely, Taiwanese strains from cobia and snubnose pompano, Trachinotus blochii (L.), displayed a mortality rate of 50-87.5% in cobia. © 2014 John Wiley & Sons Ltd.

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

Hajian, Amir; Bond, J. Richard; Battaglia, Nicholas

We measure a significant correlation between the thermal Sunyaev-Zel'dovich effect in the Planck and WMAP maps and an X-ray cluster map based on ROSAT. We use the 100, 143 and 343 GHz Planck maps and the WMAP 94 GHz map to obtain this cluster cross spectrum. We check our measurements for contamination from dusty galaxies using the cross correlations with the 217, 545 and 857 GHz maps from Planck. Our measurement yields a direct characterization of the cluster power spectrum over a wide range of angular scales that is consistent with large cosmological simulations. The amplitude of this signal dependsmore » on cosmological parameters that determine the growth of structure (σ{sub 8} and Ω M) and scales as σ{sub 8}{sup 7.4} and Ω M{sup 1.9} around the multipole (ℓ) ∼ 1000. We constrain σ{sub 8} and Ω M from the cross-power spectrum to be σ{sub 8}(Ω M/0.30){sup 0.26} = 0.8±0.02. Since this cross spectrum produces a tight constraint in the σ{sub 8} and Ω M plane the errors on a σ{sub 8} constraint will be mostly limited by the uncertainties from external constraints. Future cluster catalogs, like those from eRosita and LSST, and pointed multi-wavelength observations of clusters will improve the constraining power of this cross spectrum measurement. In principle this analysis can be extended beyond σ{sub 8} and Ω M to constrain dark energy or the sum of the neutrino masses.« less

Modeling of the HiPco process for carbon nanotube production. II. Reactor-scale analysis

NASA Technical Reports Server (NTRS)

Gokcen, Tahir; Dateo, Christopher E.; Meyyappan, M.

2002-01-01

The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.

RUPRECHT 147: THE OLDEST NEARBY OPEN CLUSTER AS A NEW BENCHMARK FOR STELLAR ASTROPHYSICS

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

Curtis, Jason L.; Wright, Jason T.; Wolfgang, Angie

2013-05-15

Ruprecht 147 is a hitherto unappreciated open cluster that holds great promise as a standard in fundamental stellar astrophysics. We have conducted a radial velocity survey of astrometric candidates with Lick, Palomar, and MMT observatories and have identified over 100 members, including 5 blue stragglers, 11 red giants, and 5 double-lined spectroscopic binaries (SB2s). We estimate the cluster metallicity from spectroscopic analysis, using Spectroscopy Made Easy (SME), and find it to be [M/H] = +0.07 {+-} 0.03. We have obtained deep CFHT/MegaCam g'r'i'z' photometry and fit Padova isochrones to the (g' - i') and Two Micron All Sky Survey (Jmore » - K{sub S} ) color-magnitude diagrams, using the {tau}{sup 2} maximum-likelihood procedure of Naylor, and an alternative method using two-dimensional cross-correlations developed in this work. We find best fits for Padova isochrones at age t = 2.5 {+-} 0.25 Gyr, m - M = 7.35 {+-} 0.1, and A{sub V} = 0.25 {+-} 0.05, with additional uncertainty from the unresolved binary population and possibility of differential extinction across this large cluster. The inferred age is heavily dependent on our choice of stellar evolution model: fitting Dartmouth and PARSEC models yield age parameters of 3 Gyr and 3.25 Gyr, respectively. At {approx}300 pc and {approx}3 Gyr, Ruprecht 147 is by far the oldest nearby star cluster.« less

Medium-resolution Spectroscopy of Red Giant Branch Stars in ω Centauri

NASA Astrophysics Data System (ADS)

An, Deokkeun; Lee, Young Sun; In Jung, Jae; Rey, Soo-Chang; Rhee, Jaehyon; Lee, Jae-Woo; Lee, Young-Wook; Joe, Young Hoon

2017-10-01

We present [Fe/H] and [Ca/Fe] of ˜600 red giant branch (RGB) members of the globular cluster Omega Centauri (ω {Cen}). We collect medium-resolution (R˜ 2000) spectra using the Blanco 4 m telescope at the Cerro Tololo Inter-American Observatory equipped with Hydra, the fiber-fed multi-object spectrograph. We demonstrate that blending of stellar light in optical fibers severely limits the accuracy of spectroscopic parameters in the crowded central region of the cluster. When photometric temperatures are taken in the spectroscopic analysis, our kinematically selected cluster members, excluding those that are strongly affected by flux from neighboring stars, include relatively fewer stars at intermediate metallicity ([{Fe}/{{H}}]˜ -1.5) than seen in the previous high-resolution survey for brighter giants in Johnson & Pilachowski. As opposed to the trend of increasing [Ca/Fe] with [Fe/H] found by those authors, our [Ca/Fe] estimates, based on Ca II H & K measurements, show essentially the same mean [Ca/Fe] for most of the metal-poor and metal-intermediate populations in this cluster, suggesting that mass- or metallicity-dependent SN II yields may not be necessary in their proposed chemical evolution scenario. Metal-rich cluster members in our sample show a large spread in [Ca/Fe], and do not exhibit a clear bimodal distribution in [Ca/Fe]. We also do not find convincing evidence for a radial metallicity gradient among RGB stars in ω {Cen}.

Preoptimised VB: a fast method for the ground and excited states of ionic clusters I. Localised preoptimisation for (ArCO) +, (ArN 2) + and N 4+

NASA Astrophysics Data System (ADS)

Langenberg, J. H.; Bucur, I. B.; Archirel, P.

1997-09-01

We show that in the simple case of van der Waals ionic clusters, the optimisation of orbitals within VB can be easily simulated with the help of pseudopotentials. The procedure yields the ground and the first excited states of the cluster simultaneously. This makes the calculation of potential energy surfaces for tri- and tetraatomic clusters possible, with very acceptable computation times. We give potential curves for (ArCO) +, (ArN 2) + and N 4+. An application to the simulation of the SCF method is shown for Na +H 2O.

Application of adaptive cluster sampling to low-density populations of freshwater mussels

USGS Publications Warehouse

Smith, D.R.; Villella, R.F.; Lemarie, D.P.

2003-01-01

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

The Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Danae Griffin, Rhiannon; Dai, Xinyu; Kochanek, Christopher S.; Bregman, Joel N.; Nugent, Jenna

2016-01-01

The Swift active galactic nucleus (AGN) and Cluster Survey (SACS) uses 125 deg^2 of Swift X-ray Telescope serendipitous fields with variable depths surrounding X-ray bursts to provide a medium depth (4 × 10^-15 erg cm^-2 s^-1) and area survey filling the gap between deep, narrow Chandra/XMM-Newton surveys and wide, shallow ROSAT surveys. Here, we present the first two papers in a series of publications for SACS. In the first paper, we introduce our method and catalog of 22,563 point sources and 442 extended sources. We examine the number counts of the AGN and galaxy cluster populations. SACS provides excellent constraints on the AGN number counts at the bright end with negligible uncertainties due to cosmic variance, and these constraints are consistent with previous measurements. The depth and areal coverage of SACS is well suited for galaxy cluster surveys outside the local universe, reaching z ˜ 1 for massive clusters. In the second paper, we use Sloan Digital Sky Survey (SDSS) DR8 data to study the 203 extended SACS sources that are located within the SDSS footprint. We search for galaxy over-densities in 3-D space using SDSS galaxies and their photometric redshifts near the Swift galaxy cluster candidates. We find 103 Swift clusters with a > 3σ over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmations as galaxy clusters. We present a series of cluster properties including the redshift, BCG magnitude, BCG-to-X-ray center offset, optical richness, X-ray luminosity and red sequences. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≤ 0.3 and 80% complete for z ≤ 0.4, consistent with the survey depth of SDSS. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 2 and 1 matches in optical, X-ray and SZ catalogs, respectively, so the majority of these clusters are new detections. These analysis results suggest that our Swift cluster selection algorithm presented in our first paper has yielded a statistically well-defined cluster sample for further studying cluster evolution and cosmology.

CLASH: Joint analysis of strong-lensing, weak-lensing shear, and magnification data for 20 galaxy clusters*

DOE PAGES

Umetsu, Keiichi; Zitrin, Adi; Gruen, Daniel; ...

2016-04-20

Here, we present a comprehensive analysis of strong-lensing, weak-lensing shear and magnification data for a sample of 16 X-ray-regular and 4 high-magnification galaxy clusters atmore » $$0.19\\lesssim z\\lesssim 0.69$$ selected from Cluster Lensing And Supernova survey with Hubble (CLASH). Our analysis combines constraints from 16-band Hubble Space Telescope observations and wide-field multi-color imaging taken primarily with Suprime-Cam on the Subaru Telescope, spanning a wide range of cluster radii (10''–16'). We reconstruct surface mass density profiles of individual clusters from a joint analysis of the full lensing constraints, and determine masses and concentrations for all of the clusters. We find the internal consistency of the ensemble mass calibration to be ≤5% ± 6% in the one-halo regime (200–2000 kpc h –1) compared to the CLASH weak-lensing-only measurements of Umetsu et al. For the X-ray-selected subsample of 16 clusters, we examine the concentration–mass (c–M) relation and its intrinsic scatter using a Bayesian regression approach. Our model yields a mean concentration of $$c{| }_{z=0.34}=3.95\\pm 0.35$$ at M200c sime 14 × 1014 M⊙ and an intrinsic scatter of $$\\sigma (\\mathrm{ln}{c}_{200{\\rm{c}}})=0.13\\pm 0.06$$, which is in excellent agreement with Λ cold dark matter predictions when the CLASH selection function based on X-ray morphological regularity and the projection effects are taken into account. We also derive an ensemble-averaged surface mass density profile for the X-ray-selected subsample by stacking their individual profiles. The stacked lensing signal is detected at 33σ significance over the entire radial range ≤4000 kpc h –1, accounting for the effects of intrinsic profile variations and uncorrelated large-scale structure along the line of sight. The stacked mass profile is well described by a family of density profiles predicted for cuspy dark-matter-dominated halos in gravitational equilibrium, namely, the Navarro–Frenk–White (NFW), Einasto, and DARKexp models, whereas the single power-law, cored isothermal and Burkert density profiles are disfavored by the data. We show that cuspy halo models that include the large-scale two-halo term provide improved agreement with the data. For the NFW halo model, we measure a mean concentration of $${c}_{200{\\rm{c}}}={3.79}_{-0.28}^{+0.30}$$ at $${M}_{200{\\rm{c}}}={14.1}_{-1.0}^{+1.0}\\times {10}^{14}\\;{M}_{\\odot }$$, demonstrating consistency between the complementary analysis methods.« less

Iron-carbide cluster thermal dynamics for catalyzed carbon nanotube growth

NASA Astrophysics Data System (ADS)

Ding, Feng; Bolton, Kim; Rosén, Arne

2004-07-01

Molecular dynamics simulations have been used to study the thermal behavior of FeN-mCm clusters where N, the total number of atoms, extends up to 2400. Comparison of the computed results with experimental data shows that the simulations yield the correct trends for the liquid-solid region of the iron-carbide phase diagram as well as the correct dependence of cluster melting point as a function of cluster size. The calculation indicates that, when carbon nanotubes (CNTs) are grown on large (>3-4 nm) catalyst particles at low temperatures (<1200 K), the catalyst particles are not completely molten. It is argued that the mechanism of CNT growth under these conditions may be governed by the surface melting of the cluster. .

BSA Au clusters as a probe for enhanced fluorescence detection using multipulse excitation scheme.

PubMed

Raut, Sangram L; Rich, Ryan; Fudala, Rafal; Kokate, R; Kimball, J D; Borejdo, Julian; Vishwanatha, Jamboor K; Gryczynski, Zygmunt; Gryczynski, Ignacy

2014-01-01

Although BSA Au clusters fluoresce in red region (λmax: 650 nm), they are of limited use due to low fluorescence quantum yield (~6%). Here we report an enhanced fluorescence imaging application of fluorescent bio-nano probe BSA Au clusters using multipulse excitation scheme. Multipulse excitation takes advantage of long fluorescence lifetime (> 1 µs) of BSA Au clusters and enhances its fluorescence intensity 15 times over short lived cellular auto-fluorescence. Moreover we have also shown that by using time gated detection strategy signal (fluorescence of BSA Au clusters) to noise (auto-fluorescence) ratio can be increased by 30 fold. Thereby with multipulse excitation long lifetime probes can be used to develop biochemical assays and perform optical imaging with zero background.

Clustering of change patterns using Fourier coefficients.

PubMed

Kim, Jaehee; Kim, Haseong

2008-01-15

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a time period because biologically related gene groups can share the same change patterns. Many clustering algorithms have been proposed to group observation data. However, because of the complexity of the underlying functions there have not been many studies on grouping data based on change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. The sample Fourier coefficients not only provide information about the underlying functions, but also reduce the dimension. In addition, as their limiting distribution is a multivariate normal, a model-based clustering method incorporating statistical properties would be appropriate. This work is aimed at discovering gene groups with similar change patterns that share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. The model-based method is advantageous over other methods in our proposed model because the sample Fourier coefficients asymptotically follow the multivariate normal distribution. Change patterns are automatically estimated with the Fourier representation in our model. Our model was tested in simulations and on real gene data sets. The simulation results showed that the model-based clustering method with the sample Fourier coefficients has a lower clustering error rate than K-means clustering. Even when the number of repeated time points was small, the same results were obtained. We also applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns. The R program is available upon the request.

A novel Rieske-type protein derived from an apoptosis-inducing factor-like (AIFL) transcript with a retained intron 4 induces change in mitochondrial morphology and growth arrest

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

Murata, Yasuhiko, E-mail: 97318@ib.k.u-tokyo.ac.jp; Furuyama, Isao; Oda, Shoji

2011-04-01

Highlights: {yields} A novel major transcript, AIFL-I4, is found. {yields} Nuclear localization of AIFL-I4 induces mitochondrial morphology change and suppression of cell proliferation. {yields} AIFL-I4 mutant with a lesion in [2Fe-2S] cluster binding site does not induce these phenotypes. {yields} [2Fe-2S] cluster binding site is essential for these phenotypes. -- Abstract: Apoptosis-inducing factor-like (AIFL) protein contains a Rieske domain and pyridine nucleotide-disulfide oxidoreductase (Pyr{sub r}edox) domain that shows 35% homology to that of apoptosis-inducing factor (AIF) protein. We identified a novel major transcript of the medaka (Oryzias latipes) AIFL gene that retained intron 4 (AIFL-I4) in embryos and tissues frommore » adult fish. The product of this transcript, AIFL-I4 protein, lacked the Pyr{sub r}edox domain because of a nonsense codon in intron 4. Both AIFL-I4 and full-length AIFL (fAIFL) transcripts were highly expressed in the brain and late embryos, and relative fAIFL and AIFL-I4 expression levels differed among tissues. Transient expression of AIFL-I4 and fAIFL tagged with GFP showed that AIFL-I4 localized in the nucleus, while fAIFL localized throughout the cytoplasm. We also found that overexpression of AIFL-I4 induced a change in mitochondrial morphology and suppression of cell proliferation. AIFL-I4 mutant with a lesion in [2Fe-2S] cluster binding site of the Rieske domain did not induce these phenotypes. This report is the first to demonstrate nuclear localization of a Rieske-type protein translated from the AIFL gene. Our data suggested that the [2Fe-2S] cluster binding site was essential for the nuclear localization and involved in mitochondrial morphology and suppression of cell proliferation.« less

VizieR Online Data Catalog: WOCS. LXXV. Hyades&Praesepe stellar lithium data (Cummings+, 2017)

NASA Astrophysics Data System (ADS)

Cummings, J. D.; Deliyannis, C. P.; Maderak, R. M.; Steinhauer, A.

2018-05-01

The Hyades and Praesepe open star clusters were both observed using the Hydra multi-object spectrograph on the WIYN 3.5-meter telescope using the 316@63.4 echelle grating in order 8 with the X19 filter. The spectra span from 6450 to 6850 Å. All Hyades stars and a majority of Praesepe stars were observed with blue cable, which yielded R~13600. The remaining Praesepe stars were observed with the red cable, which yielded a moderately higher R~17600. The Hyades data were acquired over seven nights from 2009 February 2 to 23. Using two red-cable configurations, we obtained spectra of 34 Praesepe candidate cluster members on 1997 November 16 and 18. Using seven blue cable configurations, we obtained spectra of 66 candidate cluster members during seven nights on 2001 December 2; 2005 May 1 and 2; 2006 January 25 and 26; and 2006 February 2 and 3. (2 data files).

Role of isostaticity and load-bearing microstructure in the elasticity of yielded colloidal gels.

PubMed

Hsiao, Lilian C; Newman, Richmond S; Glotzer, Sharon C; Solomon, Michael J

2012-10-02

We report a simple correlation between microstructure and strain-dependent elasticity in colloidal gels by visualizing the evolution of cluster structure in high strain-rate flows. We control the initial gel microstructure by inducing different levels of isotropic depletion attraction between particles suspended in refractive index matched solvents. Contrary to previous ideas from mode coupling and micromechanical treatments, our studies show that bond breakage occurs mainly due to the erosion of rigid clusters that persist far beyond the yield strain. This rigidity contributes to gel elasticity even when the sample is fully fluidized; the origin of the elasticity is the slow Brownian relaxation of rigid, hydrodynamically interacting clusters. We find a power-law scaling of the elastic modulus with the stress-bearing volume fraction that is valid over a range of volume fractions and gelation conditions. These results provide a conceptual framework to quantitatively connect the flow-induced microstructure of soft materials to their nonlinear rheology.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Ge(14)[Ge(SiMe(3))(3)](5)Li(3)(THF)(6): the largest metalloid cluster compound of germanium: on the way to fullerene-like compounds?

PubMed

Schenk, Christian; Schnepf, Andreas

2008-10-14

The reaction of GeBr with LiGe(SiMe(3))(3) yields the largest metalloid cluster compound of germanium Ge(14)[Ge(SiMe(3))(3)](5)Li(3)(THF)(6), in which 14 germanium atoms are arranged as a hollow sphere in the cluster core, showing that in the case of germanium also fullerene-like compounds might be present in the borderland between the molecular and solid states.

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-08-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-05-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Sample preparation for sequencing hits from one-bead-one-peptide combinatorial libraries by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Martínez-Ceron, María C; Giudicessi, Silvana L; Marani, Mariela M; Albericio, Fernando; Cascone, Osvaldo; Erra-Balsells, Rosa; Camperi, Silvia A

2010-05-15

Optimization of bead analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) after the screening of one-bead-one-peptide combinatorial libraries was achieved, involving the fine-tuning of the whole process. Guanidine was replaced by acetonitrile (MeCN)/acetic acid (AcOH)/water (H(2)O), improving matrix crystallization. Peptide-bead cleavage with NH(4)OH was cheaper and safer than, yet as efficient as, NH(3)/tetrahydrofuran (THF). Peptide elution in microtubes instead of placing the beads in the sample plate yielded more sample aliquots. Successive dry layers deposit sample preparation was better than the dried droplet method. Among the matrices analyzed, alpha-cyano-4-hydroxycinnamic acid resulted in the best peptide ion yield. Cluster formation was minimized by the addition of additives to the matrix. Copyright 2010 Elsevier Inc. All rights reserved.

Dynamics of photoprocesses induced by femtosecond infrared radiation in free molecules and clusters of iron pentacarbonyl

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

Kompanets, V. O.; Lokhman, V. N.; Poydashev, D. G., E-mail: poydashev@isan.troitsk.ru

2016-04-15

The dynamics of photoprocesses induced by femtosecond infrared radiation in free Fe(CO){sub 5} molecules and their clusters owing to the resonant excitation of vibrations of CO bonds in the 5-μm range has been studied. The technique of infrared excitation and photoionization probing (λ = 400 nm) by femtosecond pulses has been used in combination with time-of-flight mass spectrometry. It has been found that an infrared pulse selectively excites vibrations of CO bonds in free molecules, which results in a decrease in the yield of the Fe(CO){sub 5}{sup +} molecular ion. Subsequent relaxation processes have been analyzed and the results havemore » been interpreted. The time of the energy transfer from excited vibrations to other vibrations of the molecule owing to intramolecular relaxation has been measured. The dynamics of dissociation of [Fe(CO){sub 5}]{sub n} clusters irradiated by femtosecond infrared radiation has been studied. The time dependence of the yield of free molecules has been measured under different infrared laser excitation conditions. We have proposed a model that well describes the results of the experiment and makes it possible, in particular, to calculate the profile of variation of the temperature of clusters within the “evaporation ensemble” concept. The intramolecular and intracluster vibrational relaxation rates in [Fe(CO){sub 5}]{sub n} clusters have been estimated.« less

A Metabolic Gene Cluster in the Wheat W1 and the Barley Cer-cqu Loci Determines β-Diketone Biosynthesis and Glaucousness

PubMed Central

Lee, Wing-Sham; Malitsky, Sergey; Almekias-Siegl, Efrat; Levy, Matan; Ben-Zvi, Gil; Alkan, Noam; Uauy, Cristobal; Jetter, Reinhard

2016-01-01

The glaucous appearance of wheat (Triticum aestivum) and barley (Hordeum vulgare) plants, that is the light bluish-gray look of flag leaf, stem, and spike surfaces, results from deposition of cuticular β-diketone wax on their surfaces; this phenotype is associated with high yield, especially under drought conditions. Despite extensive genetic and biochemical characterization, the molecular genetic basis underlying the biosynthesis of β-diketones remains unclear. Here, we discovered that the wheat W1 locus contains a metabolic gene cluster mediating β-diketone biosynthesis. The cluster comprises genes encoding proteins of several families including type-III polyketide synthases, hydrolases, and cytochrome P450s related to known fatty acid hydroxylases. The cluster region was identified in both genetic and physical maps of glaucous and glossy tetraploid wheat, demonstrating entirely different haplotypes in these accessions. Complementary evidence obtained through gene silencing in planta and heterologous expression in bacteria supports a model for a β-diketone biosynthesis pathway involving members of these three protein families. Mutations in homologous genes were identified in the barley eceriferum mutants defective in β-diketone biosynthesis, demonstrating a gene cluster also in the β-diketone biosynthesis Cer-cqu locus in barley. Hence, our findings open new opportunities to breed major cereal crops for surface features that impact yield and stress response. PMID:27225753

A Metabolic Gene Cluster in the Wheat W1 and the Barley Cer-cqu Loci Determines β-Diketone Biosynthesis and Glaucousness.

PubMed

Hen-Avivi, Shelly; Savin, Orna; Racovita, Radu C; Lee, Wing-Sham; Adamski, Nikolai M; Malitsky, Sergey; Almekias-Siegl, Efrat; Levy, Matan; Vautrin, Sonia; Bergès, Hélène; Friedlander, Gilgi; Kartvelishvily, Elena; Ben-Zvi, Gil; Alkan, Noam; Uauy, Cristobal; Kanyuka, Kostya; Jetter, Reinhard; Distelfeld, Assaf; Aharoni, Asaph

2016-06-01

The glaucous appearance of wheat (Triticum aestivum) and barley (Hordeum vulgare) plants, that is the light bluish-gray look of flag leaf, stem, and spike surfaces, results from deposition of cuticular β-diketone wax on their surfaces; this phenotype is associated with high yield, especially under drought conditions. Despite extensive genetic and biochemical characterization, the molecular genetic basis underlying the biosynthesis of β-diketones remains unclear. Here, we discovered that the wheat W1 locus contains a metabolic gene cluster mediating β-diketone biosynthesis. The cluster comprises genes encoding proteins of several families including type-III polyketide synthases, hydrolases, and cytochrome P450s related to known fatty acid hydroxylases. The cluster region was identified in both genetic and physical maps of glaucous and glossy tetraploid wheat, demonstrating entirely different haplotypes in these accessions. Complementary evidence obtained through gene silencing in planta and heterologous expression in bacteria supports a model for a β-diketone biosynthesis pathway involving members of these three protein families. Mutations in homologous genes were identified in the barley eceriferum mutants defective in β-diketone biosynthesis, demonstrating a gene cluster also in the β-diketone biosynthesis Cer-cqu locus in barley. Hence, our findings open new opportunities to breed major cereal crops for surface features that impact yield and stress response. © 2016 American Society of Plant Biologists. All rights reserved.

Relationships and redundancies of selected hemodynamic and structural parameters for characterizing virtual treatment of cerebral aneurysms with flow diverter devices.

PubMed

Karmonik, C; Anderson, J R; Beilner, J; Ge, J J; Partovi, S; Klucznik, R P; Diaz, O; Zhang, Y J; Britz, G W; Grossman, R G; Lv, N; Huang, Q

2016-07-26

To quantify the relationship and to demonstrate redundancies between hemodynamic and structural parameters before and after virtual treatment with a flow diverter device (FDD) in cerebral aneurysms. Steady computational fluid dynamics (CFD) simulations were performed for 10 cerebral aneurysms where FDD treatment with the SILK device was simulated by virtually reducing the porosity at the aneurysm ostium. Velocity and pressure values proximal and distal to and at the aneurysm ostium as well as inside the aneurysm were quantified. In addition, dome-to-neck ratios and size ratios were determined. Multiple correlation analysis (MCA) and hierarchical cluster analysis (HCA) were conducted to demonstrate dependencies between both structural and hemodynamic parameters. Velocities in the aneurysm were reduced by 0.14m/s on average and correlated significantly (p<0.05) with velocity values in the parent artery (average correlation coefficient: 0.70). Pressure changes in the aneurysm correlated significantly with pressure values in the parent artery and aneurysm (average correlation coefficient: 0.87). MCA found statistically significant correlations between velocity values and between pressure values, respectively. HCA sorted velocity parameters, pressure parameters and structural parameters into different hierarchical clusters. HCA of aneurysms based on the parameter values yielded similar results by either including all (n=22) or only non-redundant parameters (n=2, 3 and 4). Hemodynamic and structural parameters before and after virtual FDD treatment show strong inter-correlations. Redundancy of parameters was demonstrated with hierarchical cluster analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nucleophilic ring opening of bridging thietanes in open triosmium cluster complexes

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

Adams, R.D.; Belinski, J.A.

1992-07-01

The complexes Os{sub 3}(CO){sub 9}({mu}{sub 3}-S)[{mu}-SCH{sub 2}CMe{sub 2}CMe{sub 2}CH{sub 2}] (1) and Os{sub 3}(CO){sub 9}({mu}{sub 3}-S)[{mu}-SCH{sub 2}CH{sub 2}CH{sub 2}] (2) were obtained from the reactions of Os{sub 3}(CO){sub 10}({mu}{sub 3}-S) with 3,3-dimethylthietane (DMT) and thietane, respectively, at -42 {degree}C in the presence of Me{sub 3}NO. Compound 1 was characterized by a single-crystal X-ray diffraction analysis and was found to contain a DMT group bridging two of the nonbonded metal atoms in the open cluster of three metal atoms by using both lone pairs of electrons on the sulfur atom. Compound 1 reacted with bis(triphenylphosphine)nitrogen(1+) chloride ([PPN]Cl) at 25 {degrees}C tomore » yield the salt [PPN][Os{sub 3}-(CO){sub 9}({mu}-SCH{sub 2}CMe{sub 2}CH{sub 2}Cl)({mu}{sub 3}-S)] (3; 76%), in which the chloride ion was added to one of the methylene groups of the DMT ring in a process that caused the ring to open by cleavage of one of the carbon-sulfur bonds. A 4-chloro-3,3-dimethylpropanethiolate ligand bridges the open edge of the anionic triosmium cluster. Compound 3 was converted to the neutral complex Os{sub 3}(CO){sub 9}[{mu}-SCH{sub 2}CMe{sub 2}CMe{sub 2}CH{sub 2}Cl]({mu}{sub 3}-S)({mu}-H) (4) by reaction with HCl at 25 {degrees}C. Compound 4 is structurally similar to 3, except that is contains a hydride ligand bridging one of the two metal-metal bonds. Compounds 1 and 2 react with HCl in CH{sub 2}Cl{sub 2} solvent to yield the neutral compounds 4 and Os{sub 3}(CO){sub 9}[{mu}-SCH{sub 2}CH{sub 2}CH{sub 2}Cl]({mu}{sub 3}-S)({mu}-H) (5) in 89% and 90% yields, respectively, in one step. 11 refs., 3 figs., 10 tabs.« less

Allozyme evidence for crane systematics and polymorphisms within populations of Sandhill, Sarus, Siberian and Whooping Cranes

USGS Publications Warehouse

Dessauer, H.C.; Gee, G.F.; Rogers, J.S.

1992-01-01

Electrophoretic analysis of proteins yielded evidence on the relationships of species of cranes and on genetic diversity within populations of some species. Diversity within the Greater Sandhill crane and a Florida population of the Florida Sandhill crane was similar to that of most other vertebrates, but diversity was low in the Mississippi Sandhill crane, in the Okefenokee population of the Florida Sandhill crane, and within the Siberian and Sarus cranes. Diversity was surprisingly high among whooping cranes, whose number dropped to less than 25 early in this century. Phylogenetic analysis, using both character state and distance algorithms, yielded highly concordant trees for the 15 species. The African crowned cranes (Balearica) were widely divergent from all other cranes. Species of Anthropoides, Bugeranus, and Grus clustered closely but sorted into two lineages: a Whooper Group consisted of the whooping, common, hooded, black-necked, white-naped, and red-crowned cranes of genus Grus; and a Sandhill Group included the Sandhill, Siberian, Sarus, and Brolga cranes of genus Grus, the wattled crane of genus Bugeranus, and the Demoiselle and blue cranes of genus Anthropoides.

A robust, high-throughput method for computing maize ear, cob, and kernel attributes automatically from images.

PubMed

Miller, Nathan D; Haase, Nicholas J; Lee, Jonghyun; Kaeppler, Shawn M; de Leon, Natalia; Spalding, Edgar P

2017-01-01

Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily-obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low-cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding-window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter-scale differences among ear, cob, and kernel traits that ranged more than 2.5-fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high-throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Patients' health beliefs and coping prior to autologous peripheral stem cell transplantation.

PubMed

Frick, E; Fegg, M J; Tyroller, M; Fischer, N; Bumeder, I

2007-03-01

The aim of this study was to determine the associations between health locus of control (LoC), causal attributions and coping in tumour patients prior to autologous peripheral blood stem cell transplantation. Patients completed the Questionnaire of Health Related Control Expectancies, the Questionnaire of Personal Illness Causes (QPIC), and the Freiburg Questionnaire of Coping with Illness. A total of 126 patients (45% women; 54% suffering from a multiple myeloma, 29% from non-Hodgkin lymphomas, and 17% from other malignancies) participated in the study. Cluster analysis yielded four LoC clusters: 'fatalistic external', 'powerful others', 'yeah-sayer' and 'double external'. Self-blaming QPIC items were positively correlated with depressive coping, and 'fate or destiny' attributions with religious coping (P<0.001). The highest scores were found for 'active coping' in the LoC clusters 'powerful others' and 'yeah-sayer'. External LoC and an active coping style prevail before undergoing autologous peripheral blood stem cell transplantation, whereas the depressive coping is less frequent, associated with self-blaming causal attributions. Health beliefs include causal and control attributions, which can improve or impair the patient's adjustment. A mixture between internal and external attributions seems to be most adaptive.

Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis.

PubMed

Fröhlich, Kilian; Winder, Klemens; Linker, Ralf A; Engelhorn, Tobias; Dörfler, Arnd; Lee, De-Hyung; Hilz, Max J; Schwab, Stefan; Seifert, Frank

2018-06-01

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.

Clustering-based Filtering to Detect Isolated and Intermittent Pulses in Radio Astronomy Data

NASA Astrophysics Data System (ADS)

Wagstaff, Kiri; Tang, B.; Lazio, T. J.; Spolaor, S.

2013-01-01

Radio-emitting neutron stars (pulsars) produce a series of periodic pulses at radio frequencies. Dispersion, caused by propagation through the interstellar medium, delays signals at lower frequencies more than higher frequencies. This well understood effect can be reversed though de-dispersion at the appropriate dispersion measure (DM). The periodic nature of a pulsar provides multiple samples of signals at the same DM, increasing the reliability of any candidate detection. However, existing methods for pulsar detection are ineffective for many pulse-emitting phenomena now being discovered. Sources exhibit a wide range of pulse repetition rates, from highly regular canonical pulsars to intermittent and nulling pulsars to rotating radio transients (RRATs) that may emit only a few pulses per hour. Other source types may emit only a few pulses, or even only a single pulse. We seek to broaden the scope of radio signal analysis to enable the detection of isolated and intermittent pulses. Without a requirement that detected sources be periodic, we find that a typical de-dispersion search yields results that are often dominated by spurious detections from radio frequency interference (RFI). These occur across the DM range, so filtering out DM-0 signals is insufficient. We employ DBSCAN data clustering to identify groups within the de-dispersion results, using information for each candidate about time, DM, SNR, and pulse width. DBSCAN is a density-based clustering algorithm that offers two advantages over other clustering methods: 1) the number of clusters need not to be specified, and 2) there is no model of expected cluster shape (such as the Gaussian assumption behind EM clustering). Each data cluster can be selectively masked or investigated to facilitate the process of sifting through hundreds of thousands of detections to focus on those of true interest. Using data obtained by the Byrd Green Bank Telescope (GBT), we show how this approach can help separate RFI from difficult to find single and intermittent pulses.

Cluster-Continuum Calculations of Hydration Free Energies of Anions and Group 12 Divalent Cations.

PubMed

Riccardi, Demian; Guo, Hao-Bo; Parks, Jerry M; Gu, Baohua; Liang, Liyuan; Smith, Jeremy C

2013-01-08

Understanding aqueous phase processes involving group 12 metal cations is relevant to both environmental and biological sciences. Here, quantum chemical methods and polarizable continuum models are used to compute the hydration free energies of a series of divalent group 12 metal cations (Zn(2+), Cd(2+), and Hg(2+)) together with Cu(2+) and the anions OH(-), SH(-), Cl(-), and F(-). A cluster-continuum method is employed, in which gas-phase clusters of the ion and explicit solvent molecules are immersed in a dielectric continuum. Two approaches to define the size of the solute-water cluster are compared, in which the number of explicit waters used is either held constant or determined variationally as that of the most favorable hydration free energy. Results obtained with various polarizable continuum models are also presented. Each leg of the relevant thermodynamic cycle is analyzed in detail to determine how different terms contribute to the observed mean signed error (MSE) and the standard deviation of the error (STDEV) between theory and experiment. The use of a constant number of water molecules for each set of ions is found to lead to predicted relative trends that benefit from error cancellation. Overall, the best results are obtained with MP2 and the Solvent Model D polarizable continuum model (SMD), with eight explicit water molecules for anions and 10 for the metal cations, yielding a STDEV of 2.3 kcal mol(-1) and MSE of 0.9 kcal mol(-1) between theoretical and experimental hydration free energies, which range from -72.4 kcal mol(-1) for SH(-) to -505.9 kcal mol(-1) for Cu(2+). Using B3PW91 with DFT-D3 dispersion corrections (B3PW91-D) and SMD yields a STDEV of 3.3 kcal mol(-1) and MSE of 1.6 kcal mol(-1), to which adding MP2 corrections from smaller divalent metal cation water molecule clusters yields very good agreement with the full MP2 results. Using B3PW91-D and SMD, with two explicit water molecules for anions and six for divalent metal cations, also yields reasonable agreement with experimental values, due in part to fortuitous error cancellation associated with the metal cations. Overall, the results indicate that the careful application of quantum chemical cluster-continuum methods provides valuable insight into aqueous ionic processes that depend on both local and long-range electrostatic interactions with the solvent.

Impact of reflective mulch on yield of strawberry plants and incidence of damage by tarnished plant bug (Heteroptera: Miridae).

PubMed

Rhainds, N; Kovach, J; Dosa, E L; English-Loeb, G

2001-12-01

The current study investigated the impact of reflective mulch on yield of strawberry plants and incidence of damage by tarnished plant bugs, Lygus lineolaris (Palisot de Beauvois), for three strawberry cultivars: 'Honeoye', 'Earliglow', and two sibling Dayneutrals ('Tribute' and 'Tristar', herein considered as one cultivar). Of all cultivars tested, Honeoye was the most productive and least susceptible to tarnished plant bug. For Earliglow and Honeoye, reflective mulch enhanced productivity of strawberry plants and suppressed density of nymphs per flower cluster and proportion of damaged fruits, but did not significantly impact numbers of nymphs or damaged fruits per hectare, Results with Dayneutrals were not consistently significant. Both in the presence or absence of reflective mulch, proportion of damaged fruits increased with increasing density of nymphs per flower cluster and with decreasing number of fruits harvested per row section, suggesting that planting productive strawberry cultivars or maintaining cultural practices that promote high yield may provide an effective line of defense against tarnished plant bug. These results also suggest that reflective mulch may suppress incidence of damage by tarnished plant bug both directly, by reducing number of nymphs per flower cluster, and indirectly, by enhancing productivity of strawberry plants. Economic analyses evaluating costs and benefits of using reflective mulch, as well as studies investigating mechanisms that underlie the impact of reflective mulch on yield and incidence of damage by tarnished plant bug, are still needed before reflective mulch can be implemented as a management strategy in commercial strawberry fields.

Fundamental studies of gas phase ionic reactions by ion mobility spectrometry

NASA Technical Reports Server (NTRS)

Giles, K.; Knighton, W. B.; Sahlstrom, K. E.; Grimsrud, E. P.

1995-01-01

Ion mobility spectrometry (IMS) provides a promising approach to the study of gas phase ionic reactions in buffer gases at unusually high pressures. This point is illustrated here by studies of the Sn2 nucleophilic displacement reaction, Cl(-) + CH3Br yields Br + CH3Br, using IMS at atmospheric pressure. The equilibrium clustering reaction, Cl(-)(CHCI3)(n - 1) + CHCI3 yields Cl(-)(CHCI3)(n), where n = 1 and 2, and the effect of clustering on the Sn2 reaction with CH3Br have also been characterized by this IMS-based kinetic method. Present problems and anticipated improvements in the application of ion mobility spectrometry to studies of other gas phase ionic processes are discussed.

EVIDENCE OF AGB POLLUTION IN GALACTIC GLOBULAR CLUSTERS FROM THE Mg–Al ANTICORRELATIONS OBSERVED BY THE APOGEE SURVEY

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

Ventura, P.; Dell’Agli, F.; D’Antona, F.

We study the formation of multiple populations in globular clusters (GCs), under the hypothesis that stars in the second generation formed from the winds of intermediate-mass stars, ejected during the asymptotic giant branch (AGB) phase, possibly diluted with pristine gas, sharing the same chemical composition of first-generation stars. To this aim, we use the recent Apache Point Observatory Galactic Evolution Experiment (APOGEE) data, which provide the surface chemistry of a large sample of giant stars, belonging to clusters that span a wide metallicity range. The APOGEE data set is particularly suitable to discriminate among the various pollution scenarios proposed somore » far, as it provides the surface abundances of Mg and Al, the two elements involved in a nuclear channel extremely sensitive to the temperature, hence to the metallicity of the polluters. The present analysis shows a remarkable agreement between the observations and the theoretical yields from massive AGB stars. In particular, the observed extension of the depletion of Mg and O and the increase in Al is well reproduced by the models and the trend with the metallicity is also fully accounted for. This study further supports the idea that AGB stars were the key players in the pollution of the intra-cluster medium, from which additional generations of stars formed in GCs.« less

Alcohol outlets and clusters of violence

PubMed Central

2011-01-01

Background Alcohol related violence continues to be a major public health problem in the United States. In particular, there is substantial evidence of an association between alcohol outlets and assault. However, because the specific geographic relationships between alcohol outlets and the distribution of violence remains obscured, it is important to identify the spatial linkages that may exist, enhancing public health efforts to curb both violence and morbidity. Methods The present study utilizes police-recorded data on simple and aggravated assaults in Cincinnati, Ohio. Addresses of alcohol outlets for Cincinnati, including all bars, alcohol-serving restaurants, and off-premise liquor and convenience stores were obtained from the Ohio Division of Liquor Control and geocoded for analysis. A combination of proximity analysis, spatial cluster detection approaches and a geographic information system were used to identify clusters of alcohol outlets and the distribution of violence around them. Results A brief review of the empirical work relating to alcohol outlet density and violence is provided, noting that the majority of this literature is cross-sectional and ecological in nature, yielding a somewhat haphazard and aggregate view of how outlet type(s) and neighborhood characteristics like social organization and land use are related to assaultive violence. The results of the statistical analysis for Cincinnati suggest that while alcohol outlets are not problematic per se, assaultive violence has a propensity to cluster around agglomerations of alcohol outlets. This spatial relationship varies by distance and is also related to the characteristics of the alcohol outlet agglomeration. Specifically, spatially dense distributions of outlets appear to be more prone to clusters of assaultive violence when compared to agglomerations with a lower density of outlets. Conclusion With a more thorough understanding of the spatial relationships between alcohol outlets and the distribution of assaults, policymakers in urban areas can make more informed regulatory decisions regarding alcohol licenses. Further, this research suggests that public health officials and epidemiologists need to develop a better understanding of what actually occurs in and around alcohol outlets, determining what factors (whether outlet, neighborhood, or spatially related) help fuel their relationship with violence and other alcohol-related harm. PMID:21542932

Evaluation of the courtship and of the hybrid male sterility among Drosophila buzzatii cluster species (Diptera, Drosophilidae).

PubMed

Machado, L P; Castro, J P; Madi-Ravazzi, L

2002-11-01

In the Drosophila repleta group the establishment of subgroups and complexes made on the basis of morphological and cytological evidences is supported by tests of reproductive isolation. Among species in the repleta group, the buzzatii cluster, due to its polymorphism and polytipism, is an excellent material for ecological and speciation studies. Some interspecific crosses involving Drosophila seriema, Drosophila sp. B, D. koepferae and D. buzzatii strains were completely sterile while others involving strains from these species produced F1 hybrids that did not yield F2. In the present work, data on courtship duration and copula occurrence obtained in the analysis of flies from parental sterile crosses and on spermatozoon mobility observed in F1 hybrids that did not yield F2 are presented. Copula did not occur during one hour of observation and the spermatozoon also did not show mobility at any of the analyzed stages (3, 7, 9 and 10 days old). There was a high variation in courtship average duration and in the percentage of males that courted the females. The reproductive isolation mechanisms indicated by these observations were pre and post-zygotic, as supported by the absence of copula and male sterility. Data obtained also showed the occurrence of different degrees of reproductive compatibility among the strains classified as the same species but from distinct geographic localities.

Grapevine canopy reflectance and yield

NASA Technical Reports Server (NTRS)

Minden, K. A.; Philipson, W. R.

1982-01-01

Field spectroradiometric and airborne multispectral scanner data were applied in a study of Concord grapevines. Spectroradiometric measurements of 18 experimental vines were collected on three dates during one growing season. Spectral reflectance, determined at 30 intervals from 0.4 to 1.1 microns, was correlated with vine yield, pruning weight, clusters/vine, and nitrogen input. One date of airborne multispectral scanner data (11 channels) was collected over commercial vineyards, and the average radiance values for eight vineyard sections were correlated with the corresponding average yields. Although some correlations were significant, they were inadequate for developing a reliable yield prediction model.

The extracellular Leucine-Rich Repeat superfamily; a comparative survey and analysis of evolutionary relationships and expression patterns

PubMed Central

Dolan, Jackie; Walshe, Karen; Alsbury, Samantha; Hokamp, Karsten; O'Keeffe, Sean; Okafuji, Tatsuya; Miller, Suzanne FC; Tear, Guy; Mitchell, Kevin J

2007-01-01

Background Leucine-rich repeats (LRRs) are highly versatile and evolvable protein-ligand interaction motifs found in a large number of proteins with diverse functions, including innate immunity and nervous system development. Here we catalogue all of the extracellular LRR (eLRR) proteins in worms, flies, mice and humans. We use convergent evidence from several transmembrane-prediction and motif-detection programs, including a customised algorithm, LRRscan, to identify eLRR proteins, and a hierarchical clustering method based on TribeMCL to establish their evolutionary relationships. Results This yields a total of 369 proteins (29 in worm, 66 in fly, 135 in mouse and 139 in human), many of them of unknown function. We group eLRR proteins into several classes: those with only LRRs, those that cluster with Toll-like receptors (Tlrs), those with immunoglobulin or fibronectin-type 3 (FN3) domains and those with some other domain. These groups show differential patterns of expansion and diversification across species. Our analyses reveal several clusters of novel genes, including two Elfn genes, encoding transmembrane proteins with eLRRs and an FN3 domain, and six genes encoding transmembrane proteins with eLRRs only (the Elron cluster). Many of these are expressed in discrete patterns in the developing mouse brain, notably in the thalamus and cortex. We have also identified a number of novel fly eLRR proteins with discrete expression in the embryonic nervous system. Conclusion This study provides the necessary foundation for a systematic analysis of the functions of this class of genes, which are likely to include prominently innate immunity, inflammation and neural development, especially the specification of neuronal connectivity. PMID:17868438

An HST Survey of Intermediate Luminosity X-ray Objects

NASA Astrophysics Data System (ADS)

Roye, E. W.; Colbert, E. J. M.; Heckman, T.; Ptak, R. F.; van der Marel, R. P.

2003-03-01

We searched for optical counterparts to 54 Intermediate-luminosity X-ray Objects (IXOs, a.k.a. ULXs) using HST WFPC2 archive data, and have uncovered a high yield of intriguing possible correlations. A total of 124 IXOs were identified from searching all of the Chandra ACIS archival galaxy data as of July 17, 2002. Archival WFPC2 data were available for 54 of these IXOs. The optical data utilized in this study consisted of 121 HST WFPC2 associations (stacked images). We will discuss the various methods used to register the HST WFPC2 images with the Chandra X-ray images. Our preliminary analysis indicates that 37 ( ˜70%) of the 54 IXOs have at least one 4 sigma counterpart within 1" of the IXO position, and ˜25% have unique counterparts (mostly in elliptical galaxies). The detection limit of the counterparts was typically 24-25 magnitudes in B, V, and R. The absolute magnitudes of many of the found counterparts appeared to correspond roughly to either the expected magnitudes for globular clusters, or the expected magnitudes for the brightest stars. Initial results illustrate that of the 37 IXOs with counterparts, 25 ( ˜70%) were in spiral, irregular, and merger galaxies, where the counterparts were often diffuse or clump-like sources. The counterparts found in elliptical galaxies were primarily single luminous point-sources, most likely globular clusters. We will discuss the results of color analysis for fields where counterparts in multiple bands exist, particularly for cases where a single counterpart is found. A preliminary finding in elliptical galaxies is that globular clusters associated with IXOs tend to be red, suggesting that IXOs are not found in metal-poor globular clusters.

Consumer behaviour towards vegetables: a study on domestic processing of broccoli and carrots by Dutch households.

PubMed

Bongoni, R; Verkerk, R; Dekker, M; Steenbekkers, L P A

2015-06-01

Preferences for sensory properties (e.g. taste and texture) are assumed to control cooking behaviour with respect to vegetables. Conditions such as the cooking method, amount of water used and the time-temperature profile determine the nutritional quality (e.g. vitamins and phytochemicals) of cooked vegetables. Information on domestic processing and any underlying motives can be used to inform consumers about cooking vegetables that are equally liked and are nutrient-rich. Two online self-reporting questionnaires were used to identify domestic processing conditions of broccoli and carrots by Dutch households. Questions on various aspects of domestic processing and consumer motives were included. Descriptive data analysis and hierarchical cluster analysis were performed for both vegetables, separately, to group consumers with similar motives and behaviour towards vegetables. Approximately 70% of consumers boiled vegetables, 8-9% steamed vegetables, 10-15% stir fried raw vegetables and 8-10% stir fried boiled vegetables. Mainly texture was used as a way to decide the 'doneness' of the vegetables. For both vegetables, three clusters of consumers were identified: texture-orientated, health-orientated, or taste-orientated. The texture-orientated consumers are identified as the most prevalent (56-59%) group in the present study. Statistically significant associations are found between domestic processing conditions and clusters, whereas no such association are found between demographic details and clusters. A wide variation in domestic processing of broccoli and carrots is found in the present study. Mainly sensory properties (i.e. texture and taste) determined the domestic processing conditions. The findings of the present study can be used to optimise cooking to yield vegetables that meet consumer's specific sensory preference and are higher in nutrients, and as well as to communicate with target consumer groups. © 2014 The British Dietetic Association Ltd.

Fungal diversity, dominance, and community structure in the rhizosphere of clonal Picea mariana plants throughout nursery production chronosequences.

PubMed

Vujanovic, V; Hamelin, R C; Bernier, L; Vujanovic, G; St-Arnaud, M

2007-11-01

Fungal diversity in the rhizosphere of healthy and diseased clonal black spruce (Picea mariana) plants was analyzed with regard to nursery production chronosequences. The four key production stages were sampled: mother plants (MP), 8-week-old cuttings (B + 0), second-year cuttings (B + 1), and third-year cuttings (B + 2). A total of 45 fungal taxa were isolated and identified based on cultural, phenotypic, and molecular characters. Members of phylum Ascomycota dominated, followed by Basidiomycota and Zygomycota. Diagnosis characters and distance analysis of the internal transcribed spacer rDNA sequences allowed the identification of 39 ascomycetous taxa. Many belong to the order Hypocreales, families Hypocreaceae and Nectriaceae, which contain many clusters of potentially pathogenic taxa (Cylindrocladium, Fusarium, and Neonectria) and are also ecologically associated with antagonistic taxa (Chaetomium, Hypocrea, Microsphaeropsis, Penicillium, Paecilomyces, Verticillium, Trichoderma, and Sporothrix). This is also the first report of a Cylindrocladium canadense association with disease symptoms and relation with Pestalotiopsis, Fusarium, Exserochilum, Rhizoctonia, and Xenochalara fungal consortia. Both production chronosequence and plant health considerably influenced fungal taxa assemblages. Unweighted pair-group arithmetic average clustering showed that isolates from MP, B + 0, and B + 1 plant rhizospheres clustered together within healthy or diseased health classes, whereas isolates from healthy and diseased B + 2 plants clustered together. Canonical correspondence analysis revealed substantial alteration in community assemblages with regard to plant health and yielded a principal axis direction that regrouped taxa associated with diseased plant rhizosphere soil, whereas the opposite axis direction was associated with healthy plants. Two diversity indices were defined and applied to assess the fungal taxa contribution (Tc) and persistence (Pi) throughout the production.

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

N-(1-Naphthyl) Ethylenediamine Dinitrate: A New Matrix for Negative Ion MALDI-TOF MS Analysis of Small Molecules

NASA Astrophysics Data System (ADS)

Chen, Rui; Chen, Suming; Xiong, Caiqiao; Ding, Xunlei; Wu, Chih-Che; Chang, Huan-Cheng; Xiong, Shaoxiang; Nie, Zongxiu

2012-09-01

An organic salt, N-(1-naphthyl) ethylenediamine dinitrate (NEDN), with rationally designed properties of a strong UV absorbing chromophore, hydrogen binding and nitrate anion donors, has been employed as a matrix to analyze small molecules ( m/z < 1000) such as oligosaccharides, peptides, metabolites and explosives using negative ion matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Compared with conventional matrixes such as α-cyano-4-hydroxycinnamic acid (CCA) and 2,5-dihydroxybenzoic acid (DHB), NEDN provides a significant improvement in detection sensitivity and yields very few matrix-associated fragment and cluster ions interfering with MS analysis. For low-molecular-weight saccharides, the lowest detection limit achieved ranges from 500 amol to 5 pmol, depending on the molecular weight and the structure of the analytes. Additionally, the mass spectra in the lower mass range ( m/z < 200) consist of only nitrate and nitric acid cluster ions, making the matrix particularly useful for structural identification of oligosaccharides by post-source decay (PSD) MALDI-MS. Such a characteristic is illustrated by using maltoheptaose as a model system. This work demonstrates that NEDN is a novel negative ion-mode matrix for MALDI-MS analysis of small molecules with nitrate anion attachment.

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.

Opening the Window on Galaxy Assembly: Ages and Structural Parameters of Globular Clusters Towards the Galactic Bulge

NASA Astrophysics Data System (ADS)

Cohen, Roger

2015-10-01

The primary aim of this program is to undertake a systematic investigation of highly reddened Galactic globular clusters (GGCs) located towards the Galactic bulge. These clusters have been excluded from deep space-based photometric surveys due to their severe total and differential extinction. We will exploit the photometric depth and homogeneity of two existing Treasury programs (the ACS GGC Treasury Survey and the WFC3 Bulge Treasury Program) along with the unique optical+IR parallel imaging capabilities of HST to finally place the bulge GGCs in the context of their optically well-studied counterparts. Specifically, by leveraging ACS/WFC together with WFC3/IR, we first exploit the reddening sensitivity at optical wavelengths to map severe, small-scale differential reddening in the cluster cores. Corrected two-color WFC3/IR photometry will then be used to measure cluster ages to better than 1 Gyr relative precision, finally completing the age-metallicity relation of the Milky Way GGC system. Ages are obtained using a demonstrated procedure which is strictly differential, and therefore insensitive to total distance, reddening, reddening law, or photometric calibration uncertainties. At the same time, deep archival Treasury survey imaging of the Galactic bulge will be used to decontaminate cluster luminosity functions, yielding measurements of bulge GGC mass functions and mass segregation on par with results from the ACS GGC Treasury survey. Finally, the imaging which we propose will be combined with existing wide-field near-IR PSF photometry, yielding complete radial number density profiles, structural and morphological parameters.

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

NASA Technical Reports Server (NTRS)

Ponomarev, Artem; Cucinotta, F.

2011-01-01

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

The origin of low mass particles within and beyond the dust coma envelopes of Comet Halley

NASA Technical Reports Server (NTRS)

Simpson, J. A.; Rabinowitz, D.; Tuzzolino, A. J.; Ksanfomality, L. V.; Sagdeev, R. Z.

1987-01-01

Measurements from the Dust Counter and Mass Analyzer (DUCMA) instruments on VEGA-1 and -2 revealed unexpected fluxes of low mass (up to 10 to the minus 13th power g) dust particles at very great distances from the nucleus (300,000 to 600,000 km). These particles are detected in clusters (10 sec duration), preceded and followed by relatively long time intervals during which no dust is detected. This cluster phenomenon also occurs inside the envelope boundaries. Clusters of low mass particles are intermixed with the overall dust distribution throughout the coma. The clusters account for many of the short-term small-scale intensity enhancements previously ascribed to microjets in the coma. The origin of these clusters appears to be emission from the nucleus of large conglomerates which disintegrate in the coma to yield clusters of discrete, small particles continuing outward to the distant coma.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

The LABOCA/ACT Survey of Clusters at All Redshifts: Multiwavelength Analysis of Background Submillimeter Galaxies

NASA Astrophysics Data System (ADS)

Aguirre, Paula; Lindner, Robert R.; Baker, Andrew J.; Bond, J. Richard; Dünner, Rolando; Galaz, Gaspar; Gallardo, Patricio; Hilton, Matt; Hughes, John P.; Infante, Leopoldo; Lima, Marcos; Menten, Karl M.; Sievers, Jonathan; Weiss, Axel; Wollack, Edward J.

2018-03-01

We present a multiwavelength analysis of 48 submillimeter galaxies (SMGs) detected in the Large APEX Bolometer Camera/Atacama Cosmology Telescope (ACT) Survey of Clusters at All Redshifts, LASCAR, which acquired new 870 μm and Australia Telescope Compact Array 2.1 GHz observations of 10 galaxy clusters detected through their Sunyaev–Zel’dovich effect (SZE) signal by the ACT. Far-infrared observations were also conducted with the Photodetector Array Camera and Spectrometer (100/160 μm) and SPIRE (250/350/500 μm) instruments on Herschel for sample subsets of five and six clusters. LASCAR 870 μm maps were reduced using a multiscale iterative pipeline that removes the SZE increment signal, yielding point-source sensitivities of σ ∼ 2 mJy beam‑1. We detect in total 49 sources at the 4σ level and conduct a detailed multiwavelength analysis considering our new radio and far-IR observations plus existing near-IR and optical data. One source is identified as a foreground galaxy, 28 SMGs are matched to single radio sources, four have double radio counterparts, and 16 are undetected at 2.1 GHz but tentatively associated in some cases to near-IR/optical sources. We estimate photometric redshifts for 34 sources with secure (25) and tentative (9) matches at different wavelengths, obtaining a median z={2.8}-1.7+2.1. Compared to previous results for single-dish surveys, our redshift distribution has a comparatively larger fraction of sources at z > 3, and the high-redshift tail is more extended. This is consistent with millimeter spectroscopic confirmation of a growing number of high-z SMGs and relevant for testing of cosmological models. Analytical lens modeling is applied to estimate magnification factors for 42 SMGs at clustercentric radii >1.‧2 with the demagnified flux densities and source-plane areas, we obtain integral number counts that agree with previous submillimeter surveys.

Multiple-locus variable-number tandem repeat analysis for molecular typing of Aspergillus fumigatus

PubMed Central

2010-01-01

Background Multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA) is a prominent subtyping method to resolve closely related microbial isolates to provide information for establishing genetic patterns among isolates and to investigate disease outbreaks. The usefulness of MLVA was recently demonstrated for the avian major pathogen Chlamydophila psittaci. In the present study, we developed a similar method for another pathogen of birds: the filamentous fungus Aspergillus fumigatus. Results We selected 10 VNTR markers located on 4 different chromosomes (1, 5, 6 and 8) of A. fumigatus. These markers were tested with 57 unrelated isolates from different hosts or their environment (53 isolates from avian species in France, China or Morocco, 3 isolates from humans collected at CHU Henri Mondor hospital in France and the reference strain CBS 144.89). The Simpson index for individual markers ranged from 0.5771 to 0.8530. A combined loci index calculated with all the markers yielded an index of 0.9994. In a second step, the panel of 10 markers was used in different epidemiological situations and tested on 277 isolates, including 62 isolates from birds in Guangxi province in China, 95 isolates collected in two duck farms in France and 120 environmental isolates from a turkey hatchery in France. A database was created with the results of the present study http://minisatellites.u-psud.fr/MLVAnet/. Three major clusters of isolates were defined by using the graphing algorithm termed Minimum Spanning Tree (MST). The first cluster comprised most of the avian isolates collected in the two duck farms in France, the second cluster comprised most of the avian isolates collected in poultry farms in China and the third one comprised most of the isolates collected in the turkey hatchery in France. Conclusions MLVA displayed excellent discriminatory power. The method showed a good reproducibility. MST analysis revealed an interesting clustering with a clear separation between isolates according to their geographic origin rather than their respective hosts. PMID:21143842

Unrepaired clustered DNA lesions induce chromosome breakage in human cells

PubMed Central

Asaithamby, Aroumougame; Hu, Burong; Chen, David J.

2011-01-01

Clustered DNA damage induced by ionizing radiation is refractory to repair and may trigger carcinogenic events for reasons that are not well understood. Here, we used an in situ method to directly monitor induction and repair of clustered DNA lesions in individual cells. We showed, consistent with biophysical modeling, that the kinetics of loss of clustered DNA lesions was substantially compromised in human fibroblasts. The unique spatial distribution of different types of DNA lesions within the clustered damages, but not the physical location of these damages within the subnuclear domains, determined the cellular ability to repair the damage. We then examined checkpoint arrest mechanisms and yield of gross chromosomal aberrations. Induction of nonrepairable clustered damage affected only G2 accumulation but not the early G2/M checkpoint. Further, cells that were released from the G2/M checkpoint with unrepaired clustered damage manifested a spectrum of chromosome aberrations in mitosis. Difficulties associated with clustered DNA damage repair and checkpoint release before the completion of clustered DNA damage repair appear to promote genome instability that may lead to carcinogenesis. PMID:21527720

Genetic diversity of bread wheat genotypes in Iran for some nutritional value and baking quality traits.

PubMed

Amiri, Reza; Sasani, Shahryar; Jalali-Honarmand, Saeid; Rasaei, Ali; Seifolahpour, Behnaz; Bahraminejad, Sohbat

2018-02-01

Genetic variation among 78 irrigated bread wheat genotypes was studied for their nutritional value and baking quality traits as well as some agronomic traits. The experiment was conducted in a randomized complete block design with three replicates under normal and terminal drought stress conditions in Kermanshah, Iran during 2012-2013 cropping season. The results of combined ANOVA indicated highly significant genotypic differences for all traits. All studied traits except grain yield, hectoliter weight and grain fiber content were significantly affected by genotype × environment interaction. Drought stress reduced grain yield, thousand kernel weight, gluten index, grain starch content and hectoliter weight and slightly promoted grain protein and fiber contents, falling number, total gluten and ratio of wet gluten to grain protein content. Grain yield by 31.66% and falling number by 9.20% attained the highest decrease and increase due to drought stress. There were negative and significant correlations among grain yield with grain protein and fiber contents under both conditions. Results of cluster analysis showed that newer genotypes had more grain yield and gluten index than older ones, but instead, they had the lower grain protein and fiber contents. It is thought that wheat breeders have bred cultivars with high grain yield, low protein content, and improved bread-making attributes during last seven decades. While older genotypes indicated significantly higher protein contents, and some of them had higher gluten index. We concluded from this study that it is imperative for breeders to pay more attention to improve qualitative traits coordinated to grain yield.

Effect of nanoconfinement on the sputter yield in ultrathin polymeric films: Experiments and model

NASA Astrophysics Data System (ADS)

Cristaudo, Vanina; Poleunis, Claude; Delcorte, Arnaud

2018-06-01

This fundamental contribution on secondary ion mass spectrometry (SIMS) polymer depth-profiling by large argon clusters investigates the dependence of the sputter yield volume (Y) on the thickness (d) of ultrathin films as a function of the substrate nature, i.e. hard vs soft. For this purpose, thin films of polystyrene (PS) oligomers (∼4,000 amu) are spin-coated, respectively, onto silicon and poly (methyl methacrylate) supports and, then, bombarded by 10 keV Ar3000+ ions. The investigated thickness ranges from 15 to 230 nm. Additionally, the influence of the polymer molecular weight on Y(d) for PS thin films on Si is explored. The sputtering efficiency is found to be strongly dependent on the overlayer thickness, only in the case of the silicon substrate. A simple phenomenological model is proposed for the description of the thickness influence on the sputtering yield. Molecular dynamics (MD) simulations conducted on amorphous films of polyethylene-like oligomers of increasing thickness (from 2 to 20 nm), under comparable cluster bombardment conditions, predict a significant increase of the sputtering yield for ultrathin layers on hard substrates, induced by energy confinement in the polymer, and support our phenomenological model.

Classification of LC columns based on the QSRR method and selectivity toward moclobemide and its metabolites.

PubMed

Plenis, Alina; Olędzka, Ilona; Bączek, Tomasz

2013-05-05

This paper focuses on a comparative study of the column classification system based on the quantitative structure-retention relationships (QSRR method) and column performance in real biomedical analysis. The assay was carried out for the LC separation of moclobemide and its metabolites in human plasma, using a set of 24 stationary phases. The QSRR models established for the studied stationary phases were compared with the column test performance results under two chemometric techniques - the principal component analysis (PCA) and the hierarchical clustering analysis (HCA). The study confirmed that the stationary phase classes found closely related by the QSRR approach yielded comparable separation for moclobemide and its metabolites. Therefore, the QSRR method could be considered supportive in the selection of a suitable column for the biomedical analysis offering the selection of similar or dissimilar columns with a relatively higher certainty. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessing genetic divergence in interspecific hybrids of Aechmea gomosepala and A. recurvata var. recurvata using inflorescence characteristics and sequence-related amplified polymorphism markers.

PubMed

Zhang, F; Ge, Y Y; Wang, W Y; Shen, X L; Yu, X Y

2012-12-03

Conventional hybridization and selection techniques have aided the development of new ornamental crop cultivars. However, little information is available on the genetic divergence of bromeliad hybrids. In the present study, we investigated the genetic variability in interspecific hybrids of Aechmea gomosepala and A. recurvata var. recurvata using inflorescence characteristics and sequence-related amplified polymorphism (SRAP) markers. The morphological analysis showed that the putative hybrids were intermediate between both parental species with respect to inflorescence characteristics. The 16 SRAP primer combinations yield 265 bands, among which 154 (57.72%) were polymorphic. The genetic similarity was an average of 0.59 and ranged from 0.21 to 0.87, indicating moderate genetic divergence among the hybrids. The unweighted pair group method with arithmetic average (UPGMA)-based cluster analysis distinguished the hybrids from their parents with a genetic distance coefficient of 0.54. The cophenetic correlation was 0.93, indicating a good fit between the dendrogram and the original distance matrix. The two-dimensional plot from the principal coordinate analysis showed that the hybrids were intermediately dispersed between both parents, corresponding to the results of the UPGMA cluster and the morphological analysis. These results suggest that SRAP markers could help to identify breeders, characterize F(1) hybrids of bromeliads at an early stage, and expedite genetic improvement of bromeliad cultivars.

Using Cluster Analysis to Examine Husband-Wife Decision Making

ERIC Educational Resources Information Center

Bonds-Raacke, Jennifer M.

2006-01-01

Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

Trimetallic nitride template endohedral metallofullerenes: discovery, structural characterization, reactivity, and applications.

PubMed

Zhang, Jianyuan; Stevenson, Steven; Dorn, Harry C

2013-07-16

Shortly after the discovery of the carbon fullerene allotrope, C₆₀, researchers recognized that the hollow spheroidal shape could accommodate metal atoms, or clusters, which quickly led to the discovery of endohedral metallofullerenes (EMFs). In the past 2 decades, the unique features of EMFs have attracted broad interest in many fields, including inorganic chemistry, organic chemistry, materials chemistry, and biomedical chemistry. Some EMFs produce new metallic clusters that do not exist outside of a fullerene cage, and some other EMFs can boost the efficiency of magnetic resonance (MR) imaging 10-50-fold, in comparison with commercial contrast agents. In 1999, the Dorn laboratory discovered the trimetallic nitride template (TNT) EMFs, which consist of a trimetallic nitride cluster and a host fullerene cage. The TNT-EMFs (A₃N@C2n, n = 34-55, A = Sc, Y, or lanthanides) are typically formed in relatively high yields (sometimes only exceeded by empty-cage C₆₀ and C₇₀, but yields may decrease with increasing TNT cluster size), and exhibit high chemical and thermal stability. In this Account, we give an overview of TNT-EMF research, starting with the discovery of these structures and then describing their synthesis and applications. First, we describe our serendipitous discovery of the first member of this class, Sc₃N@Ih-C₈₀. Second, we discuss the methodology for the synthesis of several TNT-EMFs. These results emphasize the importance of chemically adjusting plasma temperature, energy, and reactivity (CAPTEAR) to optimize the type and yield of TNT-EMFs produced. Third, we review the approaches that are used to separate and purify pristine TNT-EMF molecules from their corresponding product mixtures. Although we used high-performance liquid chromatography (HPLC) to separate TNT-EMFs in early studies, we have more recently achieved facile separation based on the reduced chemical reactivity of the TNT-EMFs. These improved production yields and separation protocols have allowed industrial researchers to scale up the production of TNT-EMFs for commercial use. Fourth, we summarize the structural features of individual members of the TNT-EMF class, including cage structures, cluster arrangement, and dynamics. Fifth, we illustrate typical functionalization reactions of the TNT-EMFs, particularly cycloadditions and radical reactions, and describe the characterization of their derivatives. Finally, we illustrate the unique magnetic and electronic properties of specific TNT-EMFs for biomedicine and molecular device applications.

Multiattribute evaluation of regional cotton variety trials.

PubMed

Basford, K E; Kroonenberg, P M; Delacy, I H; Lawrence, P K

1990-02-01

The Australian Cotton Cultivar Trials (ACCT) are designed to investigate various cotton [Gossypium hirsutum (L.)] lines in several locations in New South Wales and Queensland each year. If these lines are to be assessed by the simultaneous use of yield and lint quality data, then a multivariate technique applicable to three-way data is desirable. Two such techniques, the mixture maximum likelihood method of clustering and three-mode principal component analysis, are described and used to analyze these data. Applied together, the methods enhance each other's usefulness in interpreting the information on the line response patterns across the locations. The methods provide a good integration of the responses across environments of the entries for the different attributes in the trials. For instance, using yield as the sole criterion, the excellence of the namcala and coker group for quality is overlooked. The analyses point to a decision in favor of either high yields of moderate to good quality lint or moderate yield but superior lint quality. The decisions indicated by the methods confirmed the selections made by the plant breeders. The procedures provide a less subjective, relatively easy to apply and interpret analytical method of describing the patterns of performance and associations in complex multiattribute and multilocation trials. This should lead to more efficient selection among lines in such trials.

1H-NMR and UPLC-MS metabolomics: Functional tools for exploring chemotypic variation in Sceletium tortuosum from two provinces in South Africa.

PubMed

Zhao, Jianping; Khan, Ikhlas A; Combrinck, Sandra; Sandasi, Maxleene; Chen, Weiyang; Viljoen, Alvaro M

2018-05-17

Sceletium tortuosum (Aizoaceae) is widely recognised for the treatment of stress, anxiety and depression, as well as for obsessive compulsive disorders. A comprehensive intraspecies chemotypic variation study, using samples harvested from two distinct regions of South Africa, was done using both proton nuclear magnetic resonance ( 1 H-NMR) spectroscopy of methanol extracts (N = 145) and ultra performance liquid chromatography-mass spectrometry (UPLC-MS) of acid/base extracts (N = 289). Chemometric analysis of the 1 H-NMR data indicated two main clusters that were region-specific (Northern Cape and Western Cape provinces). Two dimensional (2D) NMR was used to identify analytes that contributed to the clustering as revealed by the S-plot. The sceletium alkaloids, pinitol and two alkylamines, herein reported for the first time from S. tortuosum, were identified as markers that distinguished the two groups. Relative quantification of the marker analytes conducted by qNMR indicated that samples from the Northern Cape generally contained higher concentrations of all the markers than samples from the Western Cape. Quantitative analysis of the four mesembrine alkaloids using a validated UPLC-photo diode array (PDA) detection method confirmed the results of qNMR with regard to the total alkaloid concentrations. Samples from the Northern Cape Province were found to contain, on average, very high total alkaloids, ranging from 4938.0 to 9376.8 mg/kg dry w. Regarding the Western Cape samples, the total yields of the four mesembrine alkaloids were substantially lower (averages 16.4-4143.2 mg/kg). Hierarchical cluster analysis of the UPLC-MS data, based on the alkaloid chemistry, revealed three branches, with one branch comprising samples primarily from the Northern Cape that seemed somewhat chemically conserved, while the other two branches represented mainly samples from the Western Cape. The construction of an orthogonal projections to latent structures-discriminant analysis model and subsequent loadings plot, allowed alkaloid markers to be identified for each cluster. The diverse sceletium alkaloid chemistry of samples from the three clusters may facilitate the recognition of alkaloid profiles, rather than individual compounds, that exert targeted effects on various brain receptors involved in stress, anxiety or depression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real-world problems effectively, more robust superpixel algorithms must be developed.

Non-invasive Characterization of the Histopathologic Features of Pulmonary Nodules of the Lung Adenocarcinoma Spectrum using Computer Aided Nodule Assessment and Risk Yield (CANARY) – a Pilot Study

PubMed Central

Maldonado, Fabien; Boland, Jennifer M.; Raghunath, Sushravya; Aubry, Marie Christine; Bartholmai, Brian J.; deAndrade, Mariza; Hartman, Thomas E.; Karwoski, Ronald A.; Rajagopalan, Srinivasan; Sykes, Anne-Marie; Yang, Ping; Yi, Eunhee S.; Robb, Richard A.; Peikert, Tobias

2013-01-01

Introduction Pulmonary nodules of the adenocarcinoma spectrum are characterized by distinctive morphological and radiological features and variable prognosis. Non-invasive high-resolution computed-tomography (HRCT)-based risk stratification tools are needed to individualize their management. Methods Radiological measurements of histopathologic tissue invasion were developed in a training set of 54 pulmonary nodules of the adenocarcinoma spectrum and validated in 86 consecutively resected nodules. Nodules were isolated and characterized by computer-aided analysis and data were analyzed by Spearman correlation, sensitivity, specificity as well as the positive and negative predictive values. Results Computer Aided Nodule Assessment and Risk Yield (CANARY) can non-invasively characterize pulmonary nodules of the adenocarcinoma spectrum. Unsupervised clustering analysis of HRCT data identified 9 unique exemplars representing the basic radiologic building blocks of these lesions. The exemplar distribution within each nodule correlated well with the proportion of histologic tissue invasion, Spearman R=0.87,p < 0.0001 and 0.89,p < 0.0001 for the training and the validation set, respectively. Clustering of the exemplars in three-dimensional space corresponding to tissue invasion and lepidic growth was used to develop a CANARY decision algorithm, which successfully categorized these pulmonary nodules as “aggressive” (invasive adenocarcinoma) or “indolent” (adenocarcinoma in situ and minimally invasive adenocarcinoma). Sensitivity, specificity, positive predictive value and negative predictive value of this approach for the detection of “aggressive” lesions were 95.4%, 96.8%, 95.4% and 96.8%, respectively in the training set and 98.7%, 63.6%, 94.9% and 87.5%, respectively in the validation set. Conclusion CANARY represents a promising tool to non-invasively risk stratify pulmonary nodules of the adenocarcinoma spectrum. PMID:23486265

Psychological profiles in patients with Sjögren's syndrome related to fatigue: a cluster analysis.

PubMed

van Leeuwen, Ninke; Bossema, Ercolie R; Knoop, Hans; Kruize, Aike A; Bootsma, Hendrika; Bijlsma, Johannes W J; Geenen, Rinie

2015-05-01

Fatigue is a highly prevalent and debilitating symptom in the autoimmune disease SS. Although the disease process plays a role in fatigue, psychological factors may influence fatigue and the ability to deal with its consequences. Profiles of co-occurring psychological factors may suggest potential targets for the treatment of fatigue. The aim of this study was to identify psychological profiles in patients with SS and the accompanying levels of fatigue. Three hundred patients with primary SS (mean age 57 years, 93% female) completed questionnaires on fatigue (multidimensional fatigue inventory), physical activity cognitions (TAMPA-SK), illness cognitions, cognitive regulation, emotion processing and regulation [Toronto Alexithymia Scale 20, Emotion Regulation Questionnaire (ERQ), Berkeley Expressivity Questionnaire], coping strategies (Brief COPE) and social support. Principal axis factor analysis (oblimin rotation) yielded six psychological factors: social support, negative thinking, positive thinking, emotional expressivity, avoidance and alexithymia (i.e. the inability to differentiate emotions). Using cluster analyses, these factors were grouped in four psychological profiles: functional (39%), alexithymic (27%), self-reliant (23%) and dysfunctional (11%). Irrespective of the psychological profile, the level of fatigue was substantially higher in patients than in the general population. Patients with a dysfunctional or an alexithymic profile reported more fatigue than those with a self-reliant profile. Our study in SS yielded four psychological profiles that were differentially associated with fatigue. These profiles can be used to examine determinants and prognosis of fatigue as well as the possibility of customizing cognitive behavioural interventions for chronic fatigue. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Searching for the missing baryons with the VSA and WMAP

NASA Astrophysics Data System (ADS)

Genova-Santos, Ricardo

2004-12-01

The hot diffuse gas in the local Universe which could host the missing baryons, could produce detectable thermal Sunyaev-Zel’dovich effect (tSZE). With this aim, in this work, I present the discussion of the search of this gas, via two different ways. Both takes into account this fact: Firstly, the search for the imprint of the tSZE in the first year data of the WMAP satellite, by applying a pixel to pixel correlation method between this data and a template constructed from the Two Micron All Sky Survey (2MASS) Extended Source Catalogue, which it has been assumed that trace the distribution of this hot gas. This analysis has yielded a detection of 35 7 µK in ¢ ¡ the 26 d eg2 of the sky containing the largest projected galaxy density. Nevertheless, this signal is mostly due to the contribution from galaxy clusters subtending an angular size of 20 30 . When ¡ £ the regions affected by the clusters are removed from the analysis, it is found a decrement of 96 37 µK in 0 8 d eg2 of the sky. Nevertheless, most of this signal comes from five different ¢ ¡ ¤ cluster candidates in the Zone of Avoidance (ZoA), present in the Clusters in the ZoA catalogue (CIZA). Hence, it is not found any clear evidence of structures larger than clusters, as it would be the case of this hot gas, contributing to the tSZE signal in the WMAP data. Secondly, interferometric imaging at 33 GH z of the well known Corona Borealis supercluster with the Very Small Array (VSA). The maps built up from these observations, apart from the common Cosmic Microwave Background (CMB) primordial fluctuations, show the presence of two intriguing strong negative features near the centre of the core of the supercluster [1]. It is discussed the possibility of being caused by CMB fluctuations, or by tSZ signals related to either unknown distant galaxy clusters or to diffuse extended warm/hot gas.

Star Formation History In Merging Galaxies

NASA Astrophysics Data System (ADS)

Chien, Li-Hsin

2009-01-01

Interacting and merging galaxies are believed to play an important role in many aspects of galactic evolution. Their violent interactions can trigger starbursts, which lead to formation of young globular clusters. Therefore the ages of these young globular clusters can be interpreted to yield the timing of interaction-triggered events, and thus provide a key to reconstruct the star formation history in merging galaxies. The link between galaxy interaction and star formation is well established, but the triggers of star formation in interacting galaxies are still not understood. To date there are two competing formulas that describe the star formation mechanism--density-dependent and shock-induced rules. Numerical models implementing the two rules predict significantly different star formation histories in merging galaxies. My dissertation combines these two distinct areas of astrophysics, stellar evolution and galactic dynamics, to investigate the star formation history in galaxies at various merging stages. Begin with NGC 4676 as an example, I will briefly describe its model and illustrate the idea of using the ages of clusters to constrain the modeling. The ages of the clusters are derived from spectra that were taken with multi-object spectroscopy on Keck. Using NGC 7252 as a second example, I will present a state of the art dynamical model which predicts NGC7252's star formation history and other properties. I will then show a detailed comparison and analysis between the clusters and the modeling. In the end, I will address this important link as the key to answer the fundamental question of my thesis: what is the trigger of star formation in merging galaxies?

LoCuSS: THE MASS DENSITY PROFILE OF MASSIVE GALAXY CLUSTERS AT z = 0.2 {sup ,}

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

Okabe, Nobuhiro; Umetsu, Keiichi; Smith, Graham P.

We present a stacked weak-lensing analysis of an approximately mass-selected sample of 50 galaxy clusters at 0.15 < z < 0.3, based on observations with Suprime-Cam on the Subaru Telescope. We develop a new method for selecting lensed background galaxies from which we estimate that our sample of red background galaxies suffers just 1% contamination. We detect the stacked tangential shear signal from the full sample of 50 clusters, based on this red sample of background galaxies, at a total signal-to-noise ratio of 32.7. The Navarro-Frenk-White model is an excellent fit to the data, yielding sub-10% statistical precision on massmore » and concentration: M{sub vir}=7.19{sup +0.53}{sub -0.50} Multiplication-Sign 10{sup 14} h{sup -1} M{sub sun}, c{sub vir}=5.41{sup +0.49}{sub -0.45} (c{sub 200}=4.22{sup +0.40}{sub -0.36}). Tests of a range of possible systematic errors, including shear calibration and stacking-related issues, indicate that they are subdominant to the statistical errors. The concentration parameter obtained from stacking our approximately mass-selected cluster sample is broadly in line with theoretical predictions. Moreover, the uncertainty on our measurement is comparable with the differences between the different predictions in the literature. Overall, our results highlight the potential for stacked weak-lensing methods to probe the mean mass density profile of cluster-scale dark matter halos with upcoming surveys, including Hyper-Suprime-Cam, Dark Energy Survey, and KIDS.« less

Water network-mediated, electron-induced proton transfer in [C5H5N ṡ (H2O)n]- clusters

NASA Astrophysics Data System (ADS)

DeBlase, Andrew F.; Wolke, Conrad T.; Weddle, Gary H.; Archer, Kaye A.; Jordan, Kenneth D.; Kelly, John T.; Tschumper, Gregory S.; Hammer, Nathan I.; Johnson, Mark A.

2015-10-01

The role of proton-assisted charge accommodation in electron capture by a heterocyclic electron scavenger is investigated through theoretical analysis of the vibrational spectra of cold, gas phase [Py ṡ (H2O)n=3-5]- clusters. These radical anions are formed when an excess electron is attached to water clusters containing a single pyridine (Py) molecule in a supersonic jet ion source. Under these conditions, the cluster ion distribution starts promptly at n = 3, and the photoelectron spectra, combined with vibrational predissociation spectra of the Ar-tagged anions, establish that for n > 3, these species are best described as hydrated hydroxide ions with the neutral pyridinium radical, PyH(0), occupying one of the primary solvation sites of the OH-. The n = 3 cluster appears to be a special case where charge localization on Py and hydroxide is nearly isoenergetic, and the nature of this species is explored with ab initio molecular dynamics calculations of the trajectories that start from metastable arrangements of the anion based on a diffuse, essentially dipole-bound electron. These calculations indicate that the reaction proceeds via a relatively slow rearrangement of the water network to create a favorable hydration configuration around the water molecule that eventually donates a proton to the Py nitrogen atom to yield the product hydroxide ion. The correlation between the degree of excess charge localization and the evolving shape of the water network revealed by this approach thus provides a microscopic picture of the "solvent coordinate" at the heart of a prototypical proton-coupled electron transfer reaction.

Mining the modular structure of protein interaction networks.

PubMed

Berenstein, Ariel José; Piñero, Janet; Furlong, Laura Inés; Chernomoretz, Ariel

2015-01-01

Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However, due to respective technical idiosyncrasies they might produce dissimilar modular decompositions of a given network. In this contribution, we aimed to analyze how alternative modular descriptions could condition the outcome of follow-up network biology analysis. We considered a human protein interaction network and two paradigmatic cluster recognition algorithms, namely: the Clauset-Newman-Moore and the infomap procedures. We analyzed to what extent both methodologies yielded different results in terms of granularity and biological congruency. In addition, taking into account Guimera's cartographic role characterization of network nodes, we explored how the adoption of a given clustering methodology impinged on the ability to highlight relevant network meso-scale connectivity patterns. As a case study we considered a set of aging related proteins and showed that only the high-resolution modular description provided by infomap, could unveil statistically significant associations between them and inter/intra modular cartographic features. Besides reporting novel biological insights that could be gained from the discovered associations, our contribution warns against possible technical concerns that might affect the tools used to mine for interaction patterns in network biology studies. In particular our results suggested that sub-optimal partitions from the strict point of view of their modularity levels might still be worth being analyzed when meso-scale features were to be explored in connection with external source of biological knowledge.

SPECTROSCOPIC ABUNDANCES AND MEMBERSHIP IN THE WOLF 630 MOVING GROUP

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

Bubar, Eric J.; King, Jeremy R., E-mail: ebubar@gmail.co, E-mail: jking2@ces.clemson.ed

The concept of kinematic assemblages evolving from dispersed stellar clusters has remained contentious since Eggen's initial formulation of moving groups in the 1960s. With high-quality parallaxes from the Hipparcos space astrometry mission, distance measurements for thousands of nearby, seemingly isolated stars are currently available. With these distances, a high-resolution spectroscopic abundance analysis can be brought to bear on the alleged members of these moving groups. If a structure is a relic of an open cluster, the members can be expected to be monolithic in age and abundance in as much as homogeneity is observed in young open clusters. In thismore » work, we have examined 34 putative members of the proposed Wolf 630 moving group using high-resolution stellar spectroscopy. The stars of the sample have been chemically tagged to determine abundance homogeneity and confirm the existence of a homogeneous subsample of 19 stars. Fitting the homogeneous subsample with Yale-Yonsei isochrones yields a single evolutionary sequence of {approx}2.7 {+-} 0.5 Gyr. It is concluded that this 19 star subsample of the Wolf 630 moving group sample of 34 stars could represent a dispersed cluster with an ([Fe/H]) = -0.01 {+-} 0.02 and an age of 2.7 {+-} 0.5 Gyr. In addition, chemical abundances of Na and Al in giants are examined for indications of enhancements as observed in field giants of old open clusters; overexcitation/ionization effects are explored in the cooler dwarfs of the sample; and oxygen is derived from the infrared triplet and the forbidden line at {lambda}6300.« less

Characterization and analysis of a transcriptome from the boreal spider crab Hyas araneus.

PubMed

Harms, Lars; Frickenhaus, Stephan; Schiffer, Melanie; Mark, Felix C; Storch, Daniela; Pörtner, Hans-Otto; Held, Christoph; Lucassen, Magnus

2013-12-01

Research investigating the genetic basis of physiological responses has significantly broadened our understanding of the mechanisms underlying organismic response to environmental change. However, genomic data are currently available for few taxa only, thus excluding physiological model species from this approach. In this study we report the transcriptome of the model organism Hyas araneus from Spitsbergen (Arctic). We generated 20,479 transcripts, using the 454 GS FLX sequencing technology in combination with an Illumina HiSeq sequencing approach. Annotation by Blastx revealed 7159 blast hits in the NCBI non-redundant protein database. The comparison between the spider crab H. araneus transcriptome and EST libraries of the European lobster Homarus americanus and the porcelain crab Petrolisthes cinctipes yielded 3229/2581 sequences with a significant hit, respectively. The clustering by the Markov Clustering Algorithm (MCL) revealed a common core of 1710 clusters present in all three species and 5903 unique clusters for H. araneus. The combined sequencing approaches generated transcripts that will greatly expand the limited genomic data available for crustaceans. We introduce the MCL clustering for transcriptome comparisons as a simple approach to estimate similarities between transcriptomic libraries of different size and quality and to analyze homologies within the selected group of species. In particular, we identified a large variety of reverse transcriptase (RT) sequences not only in the H. araneus transcriptome and other decapod crustaceans, but also sea urchin, supporting the hypothesis of a heritable, anti-viral immunity and the proposed viral fragment integration by host-derived RTs in marine invertebrates. © 2013.

The co-occurrence of autistic traits and borderline personality disorder traits is associated to increased suicidal ideation in nonclinical young adults.

PubMed

Chabrol, Henri; Raynal, Patrick

2018-04-01

The co-occurrence of Autism Spectrum Disorder (ASD) and Borderline Personality Disorder (BPD) is not rare and has been linked to increased suicidality. Despite this significant comorbidity between ASD and BPD, no study had examined the co-occurrence of autistic traits and borderline personality disorder traits in the general population. The aim of the present study was to examine the co-occurrence of autistic and borderline traits in a non-clinical sample of young adults and its influence on the levels of suicidal ideation and depressive symptomatology. Participants were 474 college students who completed self-report questionnaires. Data were analysed using correlation and cluster analyses. Borderline personality traits and autistic traits were weakly correlated. However, cluster analysis yielded four groups: a low traits group, a borderline traits group, an autistic traits group, and a group characterized by high levels of both traits. Cluster analysis revealed that autistic and borderline traits can co-occur in a significant proportion of young adults. The high autistic and borderline traits group constituted 17% of the total sample and had higher level of suicidal ideation than the borderline traits group, despite similar levels of depressive symptoms. This result suggests that the higher suicidality observed in patients with comorbid ASD and BPD may extent to non-clinical individuals with high levels of co-occurrent autistic and borderline traits. Copyright © 2018 Elsevier Inc. All rights reserved.

Bacterial biofilm composition in caries and caries-free subjects.

PubMed

Wolff, D; Frese, C; Maier-Kraus, T; Krueger, T; Wolff, B

2013-01-01

Certain major pathogens such as Streptococcus mutans, Lactobacillus spp. and others have been reported to be involved in caries initiation and progression. Yet, in addition to those leading pathogens, microbial communities seem to be much more diverse and individually differing. The aim of this study, therefore, was to analyze the bacterial composition of carious dentin and the plaque of caries-free patients by using a custom-made, real-time quantitative polymerase chain reaction assay (RQ-PCR). The study included 26 patients with caries and 28 caries-free controls. Decayed tooth substance and plaque samples were harvested. Bacterial DNA was extracted and tested for the presence of 43 bacterial species or species groups using RQ-PCR. Relative quantification revealed that Propionibacterium acidifaciens was significantly more abundant in caries samples than were other microorganisms (fold change 169.12, p = 0.023). In the caries-free samples, typical health-associated species were significantly more prevalent. Unsupervised hierarchical cluster analysis showed a high abundance of P. acidifaciens in caries subjects and distinct but individually differing bacterial clusters in the caries-free subjects. The distribution of 11 bacteria allowed full discrimination between caries and caries-free subjects. Within the investigated cohort, P. acidifaciens was the only pathogen significantly more abundant in caries subjects. Cluster analysis yielded a diverse flora in caries-free subjects, whereas it was narrowed down to a small range of a few outcompeting members in caries subjects. Copyright © 2012 S. Karger AG, Basel.

Definition and structure of body-relatedness from the perspective of patients with severe somatoform disorder and their therapists.

PubMed

Kalisvaart, Hanneke; van Broeckhuysen, Saskia; Bühring, Martina; Kool, Marianne B; van Dulmen, Sandra; Geenen, Rinie

2012-01-01

How a patient is connected with one's body is core to rehabilitation of somatoform disorder but a common model to describe body-relatedness is missing. The aim of our study was to investigate the components and hierarchical structure of body-relatedness as perceived by patients with severe somatoform disorder and their therapists. Interviews with patients and therapists yielded statements about components of body-relatedness. Patients and therapists individually sorted these statements according to similarity. Hierarchical cluster analysis was applied to these sortings. Analysis of variance was used to compare the perceived importance of the statements between patients and therapists. The hierarchical structure included 71 characteristics of body-relatedness. It consisted of three levels with eight clusters at the lowest level: 1) understanding, 2) acceptance, 3) adjustment, 4) respect for the body, 5) regulation, 6) confidence, 7) self-esteem, and 8) autonomy. The cluster 'understanding' was considered most important by patients and therapists. Patients valued 'regulating the body' more than therapists. According to patients with somatoform disorders and their therapists, body-relatedness includes awareness of the body and self by understanding, accepting and adjusting to bodily signals, by respecting and regulating the body, by confiding and esteeming oneself and by being autonomous. This definition and structure of body-relatedness may help professionals to improve interdisciplinary communication, assessment, and treatment, and it may help patients to better understand their symptoms and treatment. (German language abstract, Abstract S1; Spanish language abstract, Abstract S2).

Cluster-based analysis improves predictive validity of spike-triggered receptive field estimates

PubMed Central

Malone, Brian J.

2017-01-01

Spectrotemporal receptive field (STRF) characterization is a central goal of auditory physiology. STRFs are often approximated by the spike-triggered average (STA), which reflects the average stimulus preceding a spike. In many cases, the raw STA is subjected to a threshold defined by gain values expected by chance. However, such correction methods have not been universally adopted, and the consequences of specific gain-thresholding approaches have not been investigated systematically. Here, we evaluate two classes of statistical correction techniques, using the resulting STRF estimates to predict responses to a novel validation stimulus. The first, more traditional technique eliminated STRF pixels (time-frequency bins) with gain values expected by chance. This correction method yielded significant increases in prediction accuracy, including when the threshold setting was optimized for each unit. The second technique was a two-step thresholding procedure wherein clusters of contiguous pixels surviving an initial gain threshold were then subjected to a cluster mass threshold based on summed pixel values. This approach significantly improved upon even the best gain-thresholding techniques. Additional analyses suggested that allowing threshold settings to vary independently for excitatory and inhibitory subfields of the STRF resulted in only marginal additional gains, at best. In summary, augmenting reverse correlation techniques with principled statistical correction choices increased prediction accuracy by over 80% for multi-unit STRFs and by over 40% for single-unit STRFs, furthering the interpretational relevance of the recovered spectrotemporal filters for auditory systems analysis. PMID:28877194

Managing for desired experiences and site preferences: the case of fee-fishing anglers.

PubMed

Schuett, Michael A; Pierskalla, Chad D

2007-02-01

Fee-fishing involves paying a fee for the privilege of fishing a body of water where fish populations are enhanced by stocking fish. Past literature on this activity has focused more on the operation of the enterprise and management of the fish than the people and site characteristics. The objectives of the study were to profile anglers and describe their site/management preferences. This study utilized an on-site interview and mail-back questionnaire at fee-fishing establishments in West Virginia (n = 212). Factor analysis of desired recreation experiences yielded five factors: Experience nature & adventure, Stress release & relaxation, Trophy fishing, Escape, and Family time. Cluster analysis showed that these anglers can be segmented into two distinct clusters, differing by sociodemographic characteristics, fishing behavior, and site/management preferences. The findings from this study provide baseline data to aid public resource managers and fee-fishing business owners in determining how to provide satisfying outdoor experiences and deliver desired services on-site. Future research will be needed from additional fee-fishing sites to obtain more detail about this outdoor recreation cohort and be able to generalize to a larger population of participants.

Geomorphological activity at a rock glacier front detected with a 3D density-based clustering algorithm

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2017-02-01

Acquisition of high density point clouds using terrestrial laser scanners (TLSs) has become commonplace in geomorphic science. The derived point clouds are often interpolated onto regular grids and the grids compared to detect change (i.e. erosion and deposition/advancement movements). This procedure is necessary for some applications (e.g. digital terrain analysis), but it inevitably leads to a certain loss of potentially valuable information contained within the point clouds. In the present study, an alternative methodology for geomorphological analysis and feature detection from point clouds is proposed. It rests on the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN), applied to TLS data for a rock glacier front slope in the Swiss Alps. The proposed methods allowed the detection and isolation of movements directly from point clouds which yield to accuracies in the following computation of volumes that depend only on the actual registered distance between points. We demonstrated that these values are more conservative than volumes computed with the traditional DEM comparison. The results are illustrated for the summer of 2015, a season of enhanced geomorphic activity associated with exceptionally high temperatures.

Managing for Desired Experiences and Site Preferences: The Case of Fee-Fishing Anglers

NASA Astrophysics Data System (ADS)

Schuett, Michael A.; Pierskalla, Chad D.

2007-02-01

Fee-fishing involves paying a fee for the privilege of fishing a body of water where fish populations are enhanced by stocking fish. Past literature on this activity has focused more on the operation of the enterprise and management of the fish than the people and site characteristics. The objectives of the study were to profile anglers and describe their site/management preferences. This study utilized an on-site interview and mail-back questionnaire at fee-fishing establishments in West Virginia ( n = 212). Factor analysis of desired recreation experiences yielded five factors: Experience nature & adventure, Stress release & relaxation, Trophy fishing, Escape, and Family time. Cluster analysis showed that these anglers can be segmented into two distinct clusters, differing by sociodemographic characteristics, fishing behavior, and site/management preferences. The findings from this study provide baseline data to aid public resource managers and fee-fishing business owners in determining how to provide satisfying outdoor experiences and deliver desired services on-site. Future research will be needed from additional fee-fishing sites to obtain more detail about this outdoor recreation cohort and be able to generalize to a larger population of participants.

Study of Clusters and Hypernuclei production within PHSD+FRIGA model

NASA Astrophysics Data System (ADS)

Kireyeu, V.; Le Fèvre, A.; Bratkovskaya, E.

2017-01-01

We report on the results on the dynamical modelling of cluster formation with the new combined PHSD+FRIGA model at Nuclotron and NICA energies. The FRIGA clusterisation algorithm, which can be applied to the transport models, is based on the simulated annealing technique to obtain the most bound configuration of fragments and nucleons. The PHSD+FRIGA model is able to predict isotope yields as well as hyper-nucleus production. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the BM@N and MPD/NICA detectors.

Strong lensing analysis of PLCK G004.5-19.5, a Planck-discovered cluster hosting a radio relic at z = 0.52

NASA Astrophysics Data System (ADS)

Sifón, Cristóbal; Menanteau, Felipe; Hughes, John P.; Carrasco, Mauricio; Barrientos, L. Felipe

2014-02-01

Context. The recent discovery of a large number of galaxy clusters using the Sunyaev-Zel'dovich (SZ) effect has opened a new era on the study of the most massive clusters in the Universe. Multiwavelength analyses are required to understand the properties of these new sets of clusters, which are a sensitive probe of cosmology. Aims: We aim for a multiwavelength characterization of PLCK G004.5-19.5, one of the most massive X-ray validated SZ effect-selected galaxy clusters discovered by the Planck satellite. Methods: We have observed PLCK G004.5-19.5 with GMOS on the 8.1 m-Gemini South Telescope for optical imaging and spectroscopy, and performed a strong lensing analysis. We also searched for associated radio emission in published catalogs. Results: An analysis of the optical images confirms that this is a massive cluster, with a dominant central galaxy and an accompanying red sequence of galaxies, plus a 14″-long strong lensing arc. Longslit spectroscopy of six cluster members shows that the cluster is at z = 0.516 ± 0.002. We also targeted the strongly lensed arc, and found zarc = 1.601. We use LensTool to carry out a strong lensing analysis, from which we measure a median Einstein radius θE(zs = 1.6) ≃ 30″ and estimate an enclosed mass ME = 2.45-0.47+0.45 × 1014 M⊙. By extrapolating a Navarro-Frenk-White profile, we find a total mass M500SL = 4.0-1.0+2.1 × 1014 M⊙. We also include a constraint on the mass from previous X-ray observations, which yields a slightly higher mass, M500SL+X = 6.7-1.3+2.6 × 1014 M⊙, consistent with the value from strong lensing alone. Intermediate-resolution radio images from the TIFR GMRT Sky Survey at 150 MHz reveal that PLCK G004.5-19.5 hosts a powerful radio relic on scales ≲500 kpc. Emission at the same location is also detected in low-resolution images at 843 MHz and 1.4 GHz. This is one of the higher redshift radio relics known to date. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation (NSF) on behalf of the Gemini partnership: the NSF (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), Comisión Nacional de Investigación Científica y Tecnológica (CONICYT, Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil), and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).

Genetic divergence in northern Benin sorghum (Sorghum bicolor L. Moench) landraces as revealed by agromorphological traits and selection of candidate genotypes.

PubMed

Dossou-Aminon, Innocent; Loko, Laura Yêyinou; Adjatin, Arlette; Ewédjè, Eben-Ezer B K; Dansi, Alexandre; Rakshit, Sujay; Cissé, Ndiaga; Patil, Jagannath Vishnu; Agbangla, Clément; Sanni, Ambaliou; Akoègninou, Akpovi; Akpagana, Koffi

2015-01-01

Sorghum [Sorghum bicolor (L.) Moench] is an important staple food crop in northern Benin. In order to assess its diversity in Benin, 142 accessions of landraces collected from Northern Benin were grown in Central Benin and characterised using 10 qualitative and 14 quantitative agromorphological traits. High variability among both qualitative and quantitative traits was observed. Grain yield (0.72-10.57 tons/ha), panicle weight (15-215.95 g), days to 50% flowering (57-200 days), and plant height (153.27-636.5 cm) were among traits that exhibited broader variability. Correlations between quantitative traits were determined. Grain yield for instance exhibited highly positive association with panicle weight (r = 0.901, P = 0.000) and 100 seed weight (r = 0.247, P = 0.000). UPGMA cluster analysis classified the 142 accessions into 89 morphotypes. Based on multivariate analysis, twenty promising sorghum genotypes were selected. Among them, AT41, AT14, and AT29 showed early maturity (57 to 66 days to 50% flowering), high grain yields (4.85 to 7.85 tons/ha), and shorter plant height (153.27 to 180.37 cm). The results obtained will help enhancing sorghum production and diversity and developing new varieties that will be better adapted to the current soil and climate conditions in Benin.

ISSR, ERIC and RAPD techniques to detect genetic diversity in the aphid pathogen Pandora neoaphidis.

PubMed

Tymon, Anna M; Pell, Judith K

2005-03-01

The entomopathogenic fungus Pandora neoaphidis is an important natural enemy of aphids. ISSR, ERIC (Enterobacterial Repetitive Intergenic Consensus) and RAPD PCR-based DNA fingerprint analyses were undertaken to study intra-specific variation amongst 30 isolates of P. neoaphidis worldwide, together with six closely related species of Entomophthorales. All methods yielded scorable binary characters, and distance matrices were constructed from both individual and combined data sets. Neighbour-joining was used to construct consensus phylogenetic trees which showed that although P. neoaphidis isolates were highly polymorphic they separated into a monophyletic group compared with the other Entomophthorales tested. Three distinct subclades were found, with UK isolates occupying two of these. No specific correlation with aphid host species was established for any of the isolates apart from those in one cluster which contained isolates obtained from nettle aphid, Microlophium carnosum. ERIC, ISSR and RAPD analysis allowed the rapid genetic characterisation and differentiation of isolates with the generation of potential isolate- and cluster specific-diagnostic DNA markers.

Resilient, Undercontrolled, and Overcontrolled Personality Prototypes Among Persons With Spinal Cord Injury

PubMed Central

Berry, Jack W.; Elliott, Timothy R.; Rivera, Patricia

2008-01-01

A sample of 199 persons with spinal cord injury (SCI) were assessed on Big Five personality dimensions using the NEO Five-Factor Inventory (NEO–FFI; Costa & McCrae, 1992) at admission to an inpatient medical rehabilitation program. A cluster analysis of the baseline NEO–FFI yielded 3 cluster prototypes that resemble resilient, undercontrolled, and overcontrolled prototypes identified in many previous studies of children and adult community samples. Compared with normative samples, this sample had significantly fewer resilient prototypes and significantly more overcontrolled and undercontrolled prototypes. Undercontrolled individuals were the modal prototype. The resilient and undercontrolled types were better adjusted than the overcontrolled types, showing lower levels of depression at admission and higher acceptance of disability at discharge. The resilient type at admission predicted the most effective reports of social problem-solving abilities at discharge and the overcontrolled type the least. We discuss the implications of these results for assessment and interventions in rehabilitation settings. PMID:18001229

Perfectionism in African American students: relationship to racial identity, GPA, self-esteem, and depression.

PubMed

Elion, Audrey A; Wang, Kenneth T; Slaney, Robert B; French, Bryana H

2012-04-01

This study examined 219 African American college students at predominantly White universities using the constructs of perfectionism, academic achievement, self-esteem, depression, and racial identity. Cluster analysis was performed using the Almost Perfect Scale-Revised (APS-R), which yielded three clusters that represented adaptive perfectionists, maladaptive perfectionists, and nonperfectionists. These three groups were compared on their scores on the Rosenberg Self-Esteem Scale (RSES), the Center for Epidemiological Studies-Depression Scale (CES-D), the Cross Racial Identity Scale (CRIS), and Grade Point Average (GPA). Adaptive perfectionists reported higher self-esteem and lower depression scores than both the nonperfectionists and maladaptive perfectionists. Adaptive perfectionists had higher GPAs than nonperfectionists. On the racial identity scales, maladaptive perfectionists had higher scores on Pre-Encounter Self Hatred and Immersion-Emersion Anti-White subscales than adaptive perfectionists. The cultural and counseling implications of this study are discussed and integrated. Finally, recommendations are made for future studies of African American college students and perfectionism. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering.

PubMed

Chah, E; Hok, V; Della-Chiesa, A; Miller, J J H; O'Mara, S M; Reilly, R B

2011-02-01

This study presents a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means clustering. The performance of the proposed method was compared against previously reported algorithms such as principal component analysis (PCA) and amplitude-based feature extraction. Two types of classifier (namely k-means and classification expectation-maximization) were incorporated within the spike sorting algorithms, in order to find a suitable classifier for the feature sets. Simulated data sets and in-vivo tetrode multichannel recordings were employed to assess the performance of the spike sorting algorithms. The results show that the proposed algorithm yields significantly improved performance with mean sorting accuracy of 73% and sorting error of 10% compared to PCA which combined with k-means had a sorting accuracy of 58% and sorting error of 10%.A correction was made to this article on 22 February 2011. The spacing of the title was amended on the abstract page. No changes were made to the article PDF and the print version was unaffected.

Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function.

PubMed

Yin, Jiandong; Sun, Hongzan; Yang, Jiawen; Guo, Qiyong

2014-01-01

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection.

Comparison of K-Means and Fuzzy c-Means Algorithm Performance for Automated Determination of the Arterial Input Function

PubMed Central

Yin, Jiandong; Sun, Hongzan; Yang, Jiawen; Guo, Qiyong

2014-01-01

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection. PMID:24503700

Integration of Genomic and Other Epidemiologic Data to Investigate and Control a Cross-Institutional Outbreak of Streptococcus pyogenes.

PubMed

Chalker, Victoria J; Smith, Alyson; Al-Shahib, Ali; Botchway, Stella; Macdonald, Emily; Daniel, Roger; Phillips, Sarah; Platt, Steven; Doumith, Michel; Tewolde, Rediat; Coelho, Juliana; Jolley, Keith A; Underwood, Anthony; McCarthy, Noel D

2016-06-01

Single-strain outbreaks of Streptococcus pyogenes infections are common and often go undetected. In 2013, two clusters of invasive group A Streptococcus (iGAS) infection were identified in independent but closely located care homes in Oxfordshire, United Kingdom. Investigation included visits to each home, chart review, staff survey, microbiologic sampling, and genome sequencing. S. pyogenes emm type 1.0, the most common circulating type nationally, was identified from all cases yielding GAS isolates. A tailored whole-genome reference population comprising epidemiologically relevant contemporaneous isolates and published isolates was assembled. Data were analyzed independently using whole-genome multilocus sequencing and single-nucleotide polymorphism analyses. Six isolates from staff and residents of the homes formed a single cluster that was separated from the reference population by both analytical approaches. No further cases occurred after mass chemoprophylaxis and enhanced infection control. Our findings demonstrate the ability of 2 independent analytical approaches to enable robust conclusions from nonstandardized whole-genome analysis to support public health practice.

Positive psychological effects of space missions

NASA Astrophysics Data System (ADS)

Ritsher, Jennifer Boyd; Ihle, Eva C.; Kanas, Nick

2005-07-01

Being in space is a powerful experience that can have an enduring, positive impact on the psychological well-being of astronauts and cosmonauts. We sought to examine the frequency, intensity and distribution of such salutogenic experiences among persons who have flown in space, using a questionnaire we developed based on the scientific literature and first person accounts. All participants reported positive effects of being in space, but the degree of change varied widely, and some experiences were particularly common. Three of our five predicted attitude behavior relationships were supported by the data. Response patterns did not vary according to demographics or time in space. Cluster analysis yielded two groups of participants. One group was generally more reactive and also placed a higher priority on perceptions of space than did the other group. We conclude that positive experiences are common among space travelers and seem to cluster into meaningful patterns that may be consequential for Mars missions. We consider the possible selection, training, and monitoring issues raised by our findings.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

PubMed

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Survey of Open Clusters in the u'g'r'i'z' Filter System. 3. Results for the Cluster NGC 188

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

Fornal, Bartosz; Tucker, Douglas L.; Smith, J.Allyn

2006-11-01

The authors continue the series of papers describing the results of a photometric survey of open star clusters, primarily in the southern hemisphere, taken in the u'g'r'i'z' filter system. The entire observed sample covered more than 100 clusters, but here they present data only on NGC 188, which is one of the oldest open clusters known in the Milky Way. They fit the Padova theoretical isochrones to the data. Assuming a solar metallicity for NGC 188, they find a distance of 1700 {+-} 100 pc, an age of 7.5 {+-} 0.7 Gyr, and a reddening E(B-V) of 0.025 {+-} 0.005.more » This yields a distance modulus of 11.23 {+-} 0.14.« less

Beam Design and User Scheduling for Nonorthogonal Multiple Access With Multiple Antennas Based on Pareto Optimality

NASA Astrophysics Data System (ADS)

Seo, Junyeong; Sung, Youngchul

2018-06-01

In this paper, an efficient transmit beam design and user scheduling method is proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical zeroforcing (ZF) across clusters to control inter-cluster interference (ICI) and Pareto-optimal beam design with successive interference cancellation (SIC) to two users in each cluster to remove interference to strong users and leverage signal-to-interference-plus-noise ratios (SINRs) of interference-experiencing weak users. The proposed method has flexibility to control the rates of strong and weak users and numerical results show that the proposed method yields good performance.

Study of Electron Ionization and Fragmentation of Non-hydrated and Hydrated Tetrahydrofuran Clusters

NASA Astrophysics Data System (ADS)

Neustetter, Michael; Mahmoodi-Darian, Masoomeh; Denifl, Stephan

2017-05-01

Mass spectroscopic investigations on tetrahydrofuran (THF, C4H8O), a common model molecule of the DNA-backbone, have been carried out. We irradiated isolated THF and (hydrated) THF clusters with low energy electrons (electron energy 70 eV) in order to study electron ionization and ionic fragmentation. For elucidation of fragmentation pathways, deuterated TDF (C4D8O) was investigated as well. One major observation is that the cluster environment shows overall a protective behavior on THF. However, also new fragmentation channels open in the cluster. In this context, we were able to solve a discrepancy in the literature about the fragment ion peak at mass 55 u in the electron ionization mass spectrum of THF. We ascribe this ion yield to the fragmentation of ionized THF clusters.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering

PubMed Central

Almeida, Fernando R.; Brayner, Angelo; Rodrigues, Joel J. P. C.; Maia, Jose E. Bessa

2017-01-01

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering. To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE). PMID:28590450

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

PubMed

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Clustered Single Cellulosic Fiber Dissolution Kinetics and Mechanisms through Optical Microscopy under Limited Dissolving Conditions.

PubMed

Mäkelä, Valtteri; Wahlström, Ronny; Holopainen-Mantila, Ulla; Kilpeläinen, Ilkka; King, Alistair W T

2018-05-14

Herein, we describe a new method of assessing the kinetics of dissolution of single fibers by dissolution under limited dissolving conditions. The dissolution is followed by optical microscopy under limited dissolving conditions. Videos of the dissolution were processed in ImageJ to yield kinetics for dissolution, based on the disappearance of pixels associated with intact fibers. Data processing was performed using the Python language, utilizing available scientific libraries. The methods of processing the data include clustering of the single fiber data, identifying clusters associated with different fiber types, producing average dissolution traces and also extraction of practical parameters, such as, time taken to dissolve 25, 50, 75, 95, and 99.5% of the clustered fibers. In addition to these simple parameters, exponential fitting was also performed yielding rate constants for fiber dissolution. Fits for sample and cluster averages were variable, although demonstrating first-order kinetics for dissolution overall. To illustrate this process, two reference pulps (a bleached softwood kraft pulp and a bleached hardwood pre-hydrolysis kraft pulp) and their cellulase-treated versions were analyzed. As expected, differences in the kinetics and dissolution mechanisms between these samples were observed. Our initial interpretations are presented, based on the combined mechanistic observations and single fiber dissolution kinetics for these different samples. While the dissolution mechanisms observed were similar to those published previously, the more direct link of mechanistic information with the kinetics improve our understanding of cell wall structure and pre-treatments, toward improved processability.

Metabolic engineering of Pseudomonas putida for production of docosahexaenoic acid based on a myxobacterial PUFA synthase.

PubMed

Gemperlein, Katja; Zipf, Gregor; Bernauer, Hubert S; Müller, Rolf; Wenzel, Silke C

2016-01-01

Long-chain polyunsaturated fatty acids (LC-PUFAs) can be produced de novo via polyketide synthase-like enzymes known as PUFA synthases, which are encoded by pfa biosynthetic gene clusters originally discovered from marine microorganisms. Recently similar gene clusters were detected and characterized in terrestrial myxobacteria revealing several striking differences. As the identified myxobacterial producers are difficult to handle genetically and grow very slowly we aimed to establish heterologous expression platforms for myxobacterial PUFA synthases. Here we report the heterologous expression of the pfa gene cluster from Aetherobacter fasciculatus (SBSr002) in the phylogenetically distant model host bacteria Escherichia coli and Pseudomonas putida. The latter host turned out to be the more promising PUFA producer revealing higher production rates of n-6 docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA). After several rounds of genetic engineering of expression plasmids combined with metabolic engineering of P. putida, DHA production yields were eventually increased more than threefold. Additionally, we applied synthetic biology approaches to redesign and construct artificial versions of the A. fasciculatus pfa gene cluster, which to the best of our knowledge represents the first example of a polyketide-like biosynthetic gene cluster modulated and synthesized for P. putida. Combination with the engineering efforts described above led to a further increase in LC-PUFA production yields. The established production platform based on synthetic DNA now sets the stage for flexible engineering of the complex PUFA synthase. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

PubMed

Li, Faji; Wen, Weie; He, Zhonghu; Liu, Jindong; Jin, Hui; Cao, Shuanghe; Geng, Hongwei; Yan, Jun; Zhang, Pingzhi; Wan, Yingxiu; Xia, Xianchun

2018-06-01

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

Stabilization of Reduced Molybdenum-Iron-Sulfur Single and Double Cubane Clusters by Cyanide Ligation

PubMed Central

Pesavento, Russell P.; Berlinguette, Curtis P.; Holm, R. H.

2008-01-01

Recent work has shown that cyanide ligation increases the redox potentials of Fe4S4 clusters, enabling the isolation of [Fe4S4(CN)4]4−, the first synthetic Fe4S4 cluster obtained in the all-ferrous oxidation state (Scott, T. A.; Berlinguette, C. P.; Holm, R. H.; Zhou, H.-C., Proc. Natl. Acad. Sci. USA 2005, 102, 9741). The generality of reduced cluster stabilization has been examined with MoFe3S4 clusters. Reaction of single cubane [(Tp)MoFe3S4(PEt3)3]1+ and edge-bridged double cubane [(Tp)2Mo2Fe6S8(PEt3)4] with cyanide in acetonitrile affords [(Tp)MoFe3S4(CN)3]2− (2) and [(Tp)2Mo2Fe6S8(CN)4]4− (5), respectively. Reduction of 2 with KC14H10 yields [(Tp)MoFe3S4(CN)3]3− (3). Clusters were isolated in ca. 70–90% yields as Et4N+ or Bu4N+ salts; Clusters 3 and 5 contain all-ferrous cores; 3 is the first [MoFe3S4]1+ cluster isolated in substance. The structures of 2 and 3 are very similar; the volume of the reduced cluster core is slightly larger (2.5%), a usual effect upon reduction of cubane-type Fe4S4 and MFe3S4 clusters. Redox potentials and 57Fe isomer shifts of [(Tp)MoFe3S4L3]2−,3 and [(Tp)2Mo2Fe6S8L4]4−,3− clusters with L = CN, PhS, halide, and PEt3 are compared. Clusters with π-donor ligands (L = halide, PhS) exhibit larger isomer shifts and lower (more negative) redox potentials while π-acceptor ligands (L = CN, PEt3) induce smaller isomer shifts and higher (less negative) redox potentials. When potentials of 3/2 and [(Tp)MoFe3S4(SPh)3]3−/2− are compared, cyanide stabilizes 3 by 270 mV vs. the reduced thiolate cluster, commensurate with the 310 mV stabilization of [Fe4S4(CN)4]4− vs. [Fe4S4(SPh)4]4− where four ligands differ. These results demonstrate the efficacy of cyanide stabilization of lower cluster oxidation states. (Tp = hydrotris(pyrazolyl)borate(1−)). PMID:17279830

Stabilization of reduced molybdenum-iron-sulfur single- and double-cubane clusters by cyanide ligation.

PubMed

Pesavento, Russell P; Berlinguette, Curtis P; Holm, R H

2007-01-22

Recent work has shown that cyanide ligation increases the redox potentials of Fe(4)S(4) clusters, enabling the isolation of [Fe(4)S(4)(CN)4]4-, the first synthetic Fe(4)S(4) cluster obtained in the all-ferrous oxidation state (Scott, T. A.; Berlinguette, C. P.; Holm, R. H.; Zhou, H.-C. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 9741). The generality of reduced cluster stabilization has been examined with MoFe(3)S(4) clusters. Reaction of single-cubane [(Tp)MoFe(3)S(4)(PEt(3))3]1+ and edge-bridged double-cubane [(Tp)2Mo(2)Fe(6)S(8)(PEt(3))4] with cyanide in acetonitrile affords [(Tp)MoFe(3)S(4)(CN)3]2- (2) and [(Tp)2Mo(2)Fe(6)S(8)(CN)4]4- (5), respectively. Reduction of 2 with KC(14)H(10) yields [(Tp)MoFe(3)S(4)(CN)3]3- (3). Clusters were isolated in approximately 70-90% yields as Et(4)N+ or Bu(4)N+ salts; clusters 3 and 5 contain all-ferrous cores, and 3 is the first [MoFe(3)S(4)]1+ cluster isolated in substance. The structures of 2 and 3 are very similar; the volume of the reduced cluster core is slightly larger (2.5%), a usual effect upon reduction of cubane-type Fe(4)S(4) and MFe(3)S(4) clusters. Redox potentials and 57Fe isomer shifts of [(Tp)MoFe(3)S(4)L3]2-,3- and [(Tp)2Mo(2)Fe(6)S(8)L(4)]4-,3- clusters with L = CN-, PhS-, halide, and PEt3 are compared. Clusters with pi-donor ligands (L = halide, PhS) exhibit larger isomer shifts and lower (more negative) redox potentials, while pi-acceptor ligands (L = CN, PEt3) induce smaller isomer shifts and higher (less-negative) redox potentials. When the potentials of 3/2 and [(Tp)MoFe(3)S(4)(SPh)3]3-/2- are compared, cyanide stabilizes 3 by 270 mV versus the reduced thiolate cluster, commensurate with the 310 mV stabilization of [Fe(4)S(4)(CN)4]4- versus [Fe(4)S(4)(SPh)4]4- where four ligands differ. These results demonstrate the efficacy of cyanide stabilization of lower cluster oxidation states. (Tp = hydrotris(pyrazolyl)borate(1-)).

From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

PubMed Central

Jiménez, Daniel; Dorado, Hugo; Cock, James; Prager, Steven D.; Delerce, Sylvain; Grillon, Alexandre; Andrade Bejarano, Mercedes; Benavides, Hector; Jarvis, Andy

2016-01-01

Agriculture research uses “recommendation domains” to develop and transfer crop management practices adapted to specific contexts. The scale of recommendation domains is large when compared to individual production sites and often encompasses less environmental variation than farmers manage. Farmers constantly observe crop response to management practices at a field scale. These observations are of little use for other farms if the site and the weather are not described. The value of information obtained from farmers’ experiences and controlled experiments is enhanced when the circumstances under which it was generated are characterized within the conceptual framework of a recommendation domain, this latter defined by Non-Controllable Factors (NCFs). Controllable Factors (CFs) refer to those which farmers manage. Using a combination of expert guidance and a multi-stage analytic process, we evaluated the interplay of CFs and NCFs on plantain productivity in farmers’ fields. Data were obtained from multiple sources, including farmers. Experts identified candidate variables likely to influence yields. The influence of the candidate variables on yields was tested through conditional forests analysis. Factor analysis then clustered harvests produced under similar NCFs, into Homologous Events (HEs). The relationship between NCFs, CFs and productivity in intercropped plantain were analyzed with mixed models. Inclusion of HEs increased the explanatory power of models. Low median yields in monocropping coupled with the occasional high yields within most HEs indicated that most of these farmers were not using practices that exploited the yield potential of those HEs. Varieties grown by farmers were associated with particular HEs. This indicates that farmers do adapt their management to the particular conditions of their HEs. Our observations confirm that the definition of HEs as recommendation domains at a small-scale is valid, and that the effectiveness of distinct management practices for specific micro-recommendation domains can be identified with the methodologies developed. PMID:26930552

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

PubMed Central

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PubMed

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Calculation of the wetting parameter from a cluster model in the framework of nanothermodynamics.

PubMed

García-Morales, V; Cervera, J; Pellicer, J

2003-06-01

The critical wetting parameter omega(c) determines the strength of interfacial fluctuations in critical wetting transitions. In this Brief Report, we calculate omega(c) from considerations on critical liquid clusters inside a vapor phase. The starting point is a cluster model developed by Hill and Chamberlin in the framework of nanothermodynamics [Proc. Natl. Acad. Sci. USA 95, 12779 (1998)]. Our calculations yield results for omega(c) between 0.52 and 1.00, depending on the degrees of freedom considered. The findings are in agreement with previous experimental results and give an idea of the universal dynamical behavior of the clusters when approaching criticality. We suggest that this behavior is a combination of translation and vortex rotational motion (omega(c)=0.84).

Approximate solution of coupled cluster equations: application to the coupled cluster doubles method and non-covalent interacting systems.

PubMed

Smiga, Szymon; Fabiano, Eduardo

2017-11-15

We have developed a simplified coupled cluster (SCC) methodology, using the basic idea of scaled MP2 methods. The scheme has been applied to the coupled cluster double equations and implemented in three different non-iterative variants. This new method (especially the SCCD[3] variant, which utilizes a spin-resolved formalism) has been found to be very efficient and to yield an accurate approximation of the reference CCD results for both total and interaction energies of different atoms and molecules. Furthermore, we demonstrate that the equations determining the scaling coefficients for the SCCD[3] approach can generate non-empirical SCS-MP2 scaling coefficients which are in good agreement with previous theoretical investigations.

The Dynamical Properties of Virgo Cluster Galaxies

NASA Astrophysics Data System (ADS)

Ouellette, Nathalie N.-Q.

By virtue of its proximity, the Virgo Cluster is an ideal laboratory for us to test our understanding of the formation of structure in our Universe. In this spirit, we present a dynamical study of 33 gas-poor and 34 gas-rich Virgo galaxies as part of the Spectroscopic and H-band Imaging of Virgo survey. Our final spectroscopic data set was acquired at the 3.5-m telescope at the Apache Point Observatory. Halpha rotation curves for the gas-rich galaxies were modelled with a multi-parameter fit function from which various velocity measurements were inferred. Analog values were measured off of the observed rotation curves, but yielded noisier scaling relations, such as the luminosity-velocity relation (also known as the Tully-Fisher relation). Our best i -band Tully-Fisher relation has slope alpha = --7.2 +/- 0.5 and intercept Mi(2.3) = --21.5 +/- 1.1 mag, matching similar previous studies. Our study takes advantage of our own, as well as literature, data; we plan to continue expanding our compilation in order to build the largest Tully-Fisher relation for a cluster to date. Following extensive testing of the IDL routine pPXF , extended velocity dispersion profiles were extracted for our gas-poor galaxies. Considering the lack of a common standard for the measurement of a fiducial galaxy velocity dispersion in the literature, we have endeavoured to rectify this situation by determining the radius at which the measured velocity dispersion, coupled with the galaxy luminosity, yields the tightest Faber-Jackson relation. We found that radius to be 1.5 R e, which exceeds the extent of most dispersion profiles in other works. The slope of our Faber-Jackson relation is alpha = --4.3 +/- 0.2, which closely matches the virial value of 4. This analysis will soon be applied to a study of the Virgo Cluster Fundamental Plane. Rotation correction of our dispersion profiles will also permit the study of galaxies' velocity dispersion profile shapes in an attempt to refine our understanding of the overall manifold of galaxy structural parameters.

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

Site-specific vibrational spectral signatures of water molecules in the magic H3O+(H2O)20 and Cs+(H2O)20 clusters

PubMed Central

Fournier, Joseph A.; Wolke, Conrad T.; Johnson, Christopher J.; Johnson, Mark A.; Heine, Nadja; Gewinner, Sandy; Schöllkopf, Wieland; Esser, Tim K.; Fagiani, Matias R.; Knorke, Harald; Asmis, Knut R.

2014-01-01

Theoretical models of proton hydration with tens of water molecules indicate that the excess proton is embedded on the surface of clathrate-like cage structures with one or two water molecules in the interior. The evidence for these structures has been indirect, however, because the experimental spectra in the critical H-bonding region of the OH stretching vibrations have been too diffuse to provide band patterns that distinguish between candidate structures predicted theoretically. Here we exploit the slow cooling afforded by cryogenic ion trapping, along with isotopic substitution, to quench water clusters attached to the H3O+ and Cs+ ions into structures that yield well-resolved vibrational bands over the entire 215- to 3,800-cm−1 range. The magic H3O+(H2O)20 cluster yields particularly clear spectral signatures that can, with the aid of ab initio predictions, be traced to specific classes of network sites in the predicted pentagonal dodecahedron H-bonded cage with the hydronium ion residing on the surface. PMID:25489068

Site-specific vibrational spectral signatures of water molecules in the magic H 3O +(H 2O) 20 and Cs +(H 2O) 20 clusters

DOE PAGES

Fournier, Joseph A.; Wolke, Conrad T.; Johnson, Christopher J.; ...

2014-12-08

Here, theoretical models of proton hydration with tens of water molecules indicate that the excess proton is embedded on the surface of clathrate-like cage structures with one or two water molecules in the interior. The evidence for these structures has been indirect, however, because the experimental spectra in the critical H-bonding region of the OH stretching vibrations have been too diffuse to provide band patterns that distinguish between candidate structures predicted theoretically. Here we exploit the slow cooling afforded by cryogenic ion trapping, along with isotopic substitution, to quench water clusters attached to the H 3O + and Cs +more » ions into structures that yield well-resolved vibrational bands over the entire 215- to 3,800-cm -1 range. The magic H 3O +(H 2O) 20 cluster yields particularly clear spectral signatures that can, with the aid of ab initio predictions, be traced to specific classes of network sites in the predicted pentagonal dodecahedron H-bonded cage with the hydronium ion residing on the surface.« less

Experimental and theoretical study on activation of the C-H bond in pyridine by [M(m)]- (M = Cu, Ag, Au, m = 1-3).

PubMed

Liu, Xiao-Jing; Hamilton, I P; Han, Ke-Li; Tang, Zi-Chao

2010-09-21

Activation of the C-H bond of pyridine by [M(m)](-) (M = Cu, Ag, Au, m = 1-3) is investigated by experiment and theory. Complexes of coinage metal clusters and the pyridyl group, [M(m)-C(5)H(4)N](-), are produced from reactions between metal clusters formed by laser ablation of coinage metal samples and pyridine molecules seeded in argon carrier gas. We examine the structure and formation mechanism of these pyridyl-coinage metal complexes. Our study shows that C(5)H(4)N bonds to the metal clusters through a M-C sigma bond and [M(m)-C(5)H(4)N](-) is produced via a stepwise mechanism. The first step is a direct insertion reaction between [M(m)](-) and C(5)H(5)N with activation of the C-H bond to yield the intermediate [HM(m)-C(5)H(4)N](-). The second step is H atom abstraction by a neutral metal atom to yield [M(m)-C(5)H(4)N](-).

Manifestation of quark clusters in the emission of cumulative protons in the experiment on the fragmentation of carbon ions

NASA Astrophysics Data System (ADS)

Abramov, B. M.; Alekseev, P. N.; Borodin, Yu. A.; Bulychjov, S. A.; Dukhovskoy, I. A.; Krutenkova, A. P.; Kulikov, V. V.; Martemyanov, M. A.; Matsyuk, M. A.; Turdakina, E. N.; Khanov, A. I.

2013-06-01

The proton yields at an angle of 3.5° have been measured in the FRAGM experiment on the fragmentation of carbon ions with the energies T 0 = 0.6, 0.95, and 2.0 GeV/nucleon on a beryllium target at the heavy-ion accelerator complex TWAC (terawatt accumulator, Institute for Theoretical and Experimental Physics). The data are represented in the form of the dependences of the invariant cross section for proton yield on the cumulative variable x in the range of 0.9 < x < 2.4. This invariant cross section varies within six orders of magnitude. The proton spectra have been analyzed within the theoretical approach of the fragmentation of quark clusters with the fragmentation functions obtained in the quark-gluon string model. The probabilities of the existence of six- and nine-quark clusters in the carbon nuclei are estimated as 8-12 and 0.2-0.6%, respectively. The results are compared to the estimated of quark effects obtained by other methods.

Effect of small versus large clusters of fish school on the yield of a purse-seine small pelagic fishery including a marine protected area.

PubMed

Hieu, Nguyen Trong; Brochier, Timothée; Tri, Nguyen-Huu; Auger, Pierre; Brehmer, Patrice

2014-09-01

We consider a fishery model with two sites: (1) a marine protected area (MPA) where fishing is prohibited and (2) an area where the fish population is harvested. We assume that fish can migrate from MPA to fishing area at a very fast time scale and fish spatial organisation can change from small to large clusters of school at a fast time scale. The growth of the fish population and the catch are assumed to occur at a slow time scale. The complete model is a system of five ordinary differential equations with three time scales. We take advantage of the time scales using aggregation of variables methods to derive a reduced model governing the total fish density and fishing effort at the slow time scale. We analyze this aggregated model and show that under some conditions, there exists an equilibrium corresponding to a sustainable fishery. Our results suggest that in small pelagic fisheries the yield is maximum for a fish population distributed among both small and large clusters of school.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Subtypes of female juvenile offenders: a cluster analysis of the Millon Adolescent Clinical Inventory.

PubMed

Stefurak, Tres; Calhoun, Georgia B

2007-01-01

The current study sought to explore subtypes of adolescents within a sample of female juvenile offenders. Using the Millon Adolescent Clinical Inventory with 101 female juvenile offenders, a two-step cluster analysis was performed beginning with a Ward's method hierarchical cluster analysis followed by a K-Means iterative partitioning cluster analysis. The results suggest an optimal three-cluster solution, with cluster profiles leading to the following group labels: Externalizing Problems, Depressed/Interpersonally Ambivalent, and Anxious Prosocial. Analysis along the factors of age, race, offense typology and offense chronicity were conducted to further understand the nature of found clusters. Only the effect for race was significant with the Anxious Prosocial and Depressed Intepersonally Ambivalent clusters appearing disproportionately comprised of African American girls. To establish external validity, clusters were compared across scales of the Behavioral Assessment System for Children - Self Report of Personality, and corroborative distinctions between clusters were found here.

[Cluster analysis in biomedical researches].

PubMed

Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

2013-01-01

Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.

Developing a typology of African Americans with limited literacy based on preventive health practice orientation: implications for colorectal cancer screening strategies.

PubMed

Gordon, Thomas F; Bass, Sarah Bauerle; Ruzek, Sheryl B; Wolak, Caitlin; Rovito, Michael J; Ruggieri, Dominique G; Ward, Stephanie; Paranjape, Anuradha; Greener, Judith

2014-01-01

Preventive health messages are often tailored to reach broad sociodemographic groups. However, within groups, there may be considerable variation in perceptions of preventive health practices, such as colorectal cancer screening. Segmentation analysis provides a tool for crafting messages that are tailored more closely to the mental models of targeted individuals or subgroups. This study used cluster analysis, a psychosocial marketing segmentation technique, to develop a typology of colorectal cancer screening orientation among 102 African American clinic patients between the ages of 50 and 74 years with limited literacy. Patients were from a general internal medicine clinic in a large urban teaching hospital, a subpopulation known to have high rates of colorectal cancer and low rates of screening. Preventive screening orientation variables included the patients' responses to questions involving personal attitudes and preferences toward preventive screening and general prevention practices. A k-means cluster analysis yielded three clusters of patients on the basis of their screening orientation: ready screeners (50.0%), cautious screeners (30.4%), and fearful avoiders (19.6%). The resulting typology clearly defines important subgroups on the basis of their preventive health practice perceptions. The authors propose that the development of a validated typology of patients on the basis of their preventive health perceptions could be applicable to a variety of health concerns. Such a typology would serve to standardize how populations are characterized and would provide a more accurate view of their preventive health-related attitudes, values, concerns, preferences, and behaviors. Used with standardized assessment tools, it would provide an empirical basis for tailoring health messages and improving medical communication.

Neural activity in relation to empirically derived personality syndromes in depression using a psychodynamic fMRI paradigm

PubMed Central

Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik

2013-01-01

Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644

Innate responses to gene knockouts impact overlapping gene networks and vary with respect to resistance to viral infection.

PubMed

Liu, Yonghong; Liu, Yuanyuan; Wu, Jiaming; Roizman, Bernard; Zhou, Grace Guoying

2018-04-03

Analyses of the levels of mRNAs encoding IFIT1, IFI16, RIG-1, MDA5, CXCL10, LGP2, PUM1, LSD1, STING, and IFNβ in cell lines from which the gene encoding LGP2, LSD1, PML, HDAC4, IFI16, PUM1, STING, MDA5, IRF3, or HDAC 1 had been knocked out, as well as the ability of these cell lines to support the replication of HSV-1, revealed the following: ( i ) Cell lines lacking the gene encoding LGP2, PML, or HDAC4 (cluster 1) exhibited increased levels of expression of partially overlapping gene networks. Concurrently, these cell lines produced from 5 fold to 12 fold lower yields of HSV-1 than the parental cells. ( ii ) Cell lines lacking the genes encoding STING, LSD1, MDA5, IRF3, or HDAC 1 (cluster 2) exhibited decreased levels of mRNAs of partially overlapping gene networks. Concurrently, these cell lines produced virus yields that did not differ from those produced by the parental cell line. The genes up-regulated in cell lines forming cluster 1, overlapped in part with genes down-regulated in cluster 2. The key conclusions are that gene knockouts and subsequent selection for growth causes changes in expression of multiple genes, and hence the phenotype of the cell lines cannot be ascribed to a single gene; the patterns of gene expression may be shared by multiple knockouts; and the enhanced immunity to viral replication by cluster 1 knockout cell lines but not by cluster 2 cell lines suggests that in parental cells, the expression of innate resistance to infection is specifically repressed.

THE YOUNG OPEN CLUSTERS KING 12, NGC 7788, AND NGC 7790: PRE-MAIN-SEQUENCE STARS AND EXTENDED STELLAR HALOS

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

Davidge, T. J.

2012-12-20

The stellar contents of the open clusters King 12, NGC 7788, and NGC 7790 are investigated using MegaCam images. Comparisons with isochrones yield an age <20 Myr for King 12, 20-40 Myr for NGC 7788, and 60-80 Myr for NGC 7790 based on the properties of stars near the main-sequence turnoff (MSTO) in each cluster. The reddening of NGC 7788 is much larger than previously estimated. The luminosity functions (LFs) of King 12 and NGC 7788 show breaks that are attributed to the onset of pre-main-sequence (PMS) objects, and comparisons with models of PMS evolution yield ages that are consistentmore » with those measured from stars near the MSTO. In contrast, the r' LF of main-sequence stars in NGC 7790 is matched to r' = 20 by a model that is based on the solar neighborhood mass function. The structural properties of all three clusters are investigated by examining the two-point angular correlation function of blue main-sequence stars. King 12 and NGC 7788 are each surrounded by a stellar halo that extends out to a radius of 5 arcmin ({approx}3.4 pc). It is suggested that these halos form in response to large-scale mass ejection early in the evolution of the clusters, as predicted by models. In contrast, blue main-sequence stars in NGC 7790 are traced out to a radius of {approx}7.5 arcmin ({approx}5.5 pc), with no evidence of a halo. It is suggested that all three clusters may have originated in the same star-forming complex, but not in the same giant molecular cloud.« less

Oxygen-Centered Hexatantalum Tetradecaimido Cluster Complexes

PubMed Central

Krinsky, Jamin L.; Anderson, Laura L.; Arnold, John; Bergman, Robert G.

2008-01-01

The syntheses and characterization of several octahedral hexatantalum cluster compounds of formula (ArN)14Ta6O are described (Ar = Ph, p-MeC6H4, p-MeOC6H4, p-t-BuC6H4, p-BrC6H4, m-ClC6H4). Treatment of Bn3Ta=N-t-Bu (Bn = CH2C6H5) or pentakis(dimethylamido)tantalum with an excess of the appropriate aniline and stoichiometric water or tantalum oxide afforded varying yields of arylimido clusters. The structures of two species were confirmed by X-ray diffraction (XRD), while the identity of the central oxygen atom was elucidated by electrospray mass spectrometry (MS) using 17O/18O-enriched material. The title species are very air- and moisture-sensitive but quite thermally stable in solution. Experimentally determined optical properties and oxidation/reduction potentials, as well as some computational results, indicate that they possess an electronic structure wherein the highest occupied molecular orbitals are ligand-centered, while the lowest unoccupied orbitals are metal-centered and delocalized throughout the tantalum cage. Whereas chemical oxidation resulted in cluster decomposition, reduction with decamethylcobaltocene yielded stable salts of formula [Cp*2Co][(ArN)14Ta6O] (Ar = Ph, Ar = p-MeC6H4). Small-molecule reactivity studies on one of these clusters showed that its imido functionalities are moderately reactive toward oxide donors but inert with respect to metallaheterocycle-forming processes. Clean imido/oxo exchange was observed with aldehydes and ketones, leading cleanly to organic imines with no soluble byproducts being observed. This exchange was also observed with a rhenium oxo compound (generating an imidorhenium complex as the only soluble species). All 14 imido groups were transferred in these reactions, and no mixed-ligand cluster intermediates were ever observed. PMID:18163614

From clusters to bulk: A relativistic density functional investigation on a series of gold clusters Aun, n=6,…,147

NASA Astrophysics Data System (ADS)

Häberlen, Oliver D.; Chung, Sai-Cheong; Stener, Mauro; Rösch, Notker

1997-03-01

A series of gold clusters spanning the size range from Au6 through Au147 (with diameters from 0.7 to 1.7 nm) in icosahedral, octahedral, and cuboctahedral structure has been theoretically investigated by means of a scalar relativistic all-electron density functional method. One of the main objectives of this work was to analyze the convergence of cluster properties toward the corresponding bulk metal values and to compare the results obtained for the local density approximation (LDA) to those for a generalized gradient approximation (GGA) to the exchange-correlation functional. The average gold-gold distance in the clusters increases with their nuclearity and correlates essentially linearly with the average coordination number in the clusters. An extrapolation to the bulk coordination of 12 yields a gold-gold distance of 289 pm in LDA, very close to the experimental bulk value of 288 pm, while the extrapolated GGA gold-gold distance is 297 pm. The cluster cohesive energy varies linearly with the inverse of the calculated cluster radius, indicating that the surface-to-volume ratio is the primary determinant of the convergence of this quantity toward bulk. The extrapolated LDA binding energy per atom, 4.7 eV, overestimates the experimental bulk value of 3.8 eV, while the GGA value, 3.2 eV, underestimates the experiment by almost the same amount. The calculated ionization potentials and electron affinities of the clusters may be related to the metallic droplet model, although deviations due to the electronic shell structure are noticeable. The GGA extrapolation to bulk values yields 4.8 and 4.9 eV for the ionization potential and the electron affinity, respectively, remarkably close to the experimental polycrystalline work function of bulk gold, 5.1 eV. Gold 4f core level binding energies were calculated for sites with bulk coordination and for different surface sites. The core level shifts for the surface sites are all positive and distinguish among the corner, edge, and face-centered sites; sites in the first subsurface layer show still small positive shifts.

Spotting effect in microarray experiments

PubMed Central

Mary-Huard, Tristan; Daudin, Jean-Jacques; Robin, Stéphane; Bitton, Frédérique; Cabannes, Eric; Hilson, Pierre

2004-01-01

Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis. PMID:15151695

Joint cosmic microwave background and weak lensing analysis: constraints on cosmological parameters.

PubMed

Contaldi, Carlo R; Hoekstra, Henk; Lewis, Antony

2003-06-06

We use cosmic microwave background (CMB) observations together with the red-sequence cluster survey weak lensing results to derive constraints on a range of cosmological parameters. This particular choice of observations is motivated by their robust physical interpretation and complementarity. Our combined analysis, including a weak nucleosynthesis constraint, yields accurate determinations of a number of parameters including the amplitude of fluctuations sigma(8)=0.89+/-0.05 and matter density Omega(m)=0.30+/-0.03. We also find a value for the Hubble parameter of H(0)=70+/-3 km s(-1) Mpc(-1), in good agreement with the Hubble Space Telescope key-project result. We conclude that the combination of CMB and weak lensing data provides some of the most powerful constraints available in cosmology today.

Sub-micrometer 20MeV protons or 45MeV lithium spot irradiation enhances yields of dicentric chromosomes due to clustering of DNA double-strand breaks.

PubMed

Schmid, T E; Friedland, W; Greubel, C; Girst, S; Reindl, J; Siebenwirth, C; Ilicic, K; Schmid, E; Multhoff, G; Schmitt, E; Kundrát, P; Dollinger, G

2015-11-01

In conventional experiments on biological effects of radiation types of diverse quality, micrometer-scale double-strand break (DSB) clustering is inherently interlinked with clustering of energy deposition events on nanometer scale relevant for DSB induction. Due to this limitation, the role of the micrometer and nanometer scales in diverse biological endpoints cannot be fully separated. To address this issue, hybrid human-hamster AL cells have been irradiated with 45MeV (60keV/μm) lithium ions or 20MeV (2.6keV/μm) protons quasi-homogeneously distributed or focused to 0.5×1μm(2) spots on regular matrix patterns (point distances up to 10.6×10.6μm), with pre-defined particle numbers per spot to provide the same mean dose of 1.7Gy. The yields of dicentrics and their distribution among cells have been scored. In parallel, track-structure based simulations of DSB induction and chromosome aberration formation with PARTRAC have been performed. The results show that the sub-micrometer beam focusing does not enhance DSB yields, but significantly affects the DSB distribution within the nucleus and increases the chance to form DSB pairs in close proximity, which may lead to increased yields of chromosome aberrations. Indeed, the experiments show that focusing 20 lithium ions or 451 protons per spot on a 10.6μm grid induces two or three times more dicentrics, respectively, than a quasi-homogenous irradiation. The simulations reproduce the data in part, but in part suggest more complex behavior such as saturation or overkill not seen in the experiments. The direct experimental demonstration that sub-micrometer clustering of DSB plays a critical role in the induction of dicentrics improves the knowledge on the mechanisms by which these lethal lesions arise, and indicates how the assumptions of the biophysical model could be improved. It also provides a better understanding of the increased biological effectiveness of high-LET radiation. Copyright © 2015 Elsevier B.V. All rights reserved.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.

Hydrogen bonding interaction of small acetaldehyde clusters studied with core-electron excitation spectroscopy in the oxygen K-edge region

NASA Astrophysics Data System (ADS)

Tabayashi, K.; Chohda, M.; Yamanaka, T.; Tsutsumi, Y.; Takahashi, O.; Yoshida, H.; Taniguchi, M.

2010-06-01

In order to examine inner-shell electron excitation spectra of molecular clusters with strong multipole interactions, excitation spectra and time-of-flight (TOF) fragment-mass spectra of small acetaldehyde (AA) clusters have been studied under the beam conditions. The TOF spectra at the oxygen K-edge region showed an intense growth of the protonated clusters, MnH+ (M=CH3CHO) in the cluster beams. "cluster-specific" excitation spectra could be generated by monitoring partial-ion-yields of the protonated clusters. The most intense band of O1s→π*CO was found to shift to a higher energy by 0.15 eV relative to the monomer band upon clusterization. X-ray absorption spectra (XAS) were also calculated for the representative dimer configurations using a computer modelling program based on the density functional theory. The XAS prediction for the most stable (non-planar) configuration was found to give a close comparison with the cluster-band shift observed. The band shift was interpreted as being due to the HOMO-LUMO interaction within the complex where a contribution of vibrationally blue-shifting hydrogen bonding could be identified.

LoCuSS: the near-infrared luminosity and weak-lensing mass scaling relation of galaxy clusters

NASA Astrophysics Data System (ADS)

Mulroy, Sarah L.; Smith, Graham P.; Haines, Chris P.; Marrone, Daniel P.; Okabe, Nobuhiro; Pereira, Maria J.; Egami, Eiichi; Babul, Arif; Finoguenov, Alexis; Martino, Rossella

2014-10-01

We present the first scaling relation between weak-lensing galaxy cluster mass, MWL, and near-infrared luminosity, LK. Our results are based on 17 clusters observed with wide-field instruments on Subaru, the United Kingdom Infrared Telescope, the Mayall Telescope, and the MMT. We concentrate on the relation between projected 2D weak-lensing mass and spectroscopically confirmed luminosity within 1 Mpc, modelled as M_WL ∝ LK^b, obtaining a power-law slope of b=0.83^{+0.27}_{-0.24} and an intrinsic scatter of σ _{lnM_WL|LK}=10^{+8}_{-5} per cent. Intrinsic scatter of ˜10 per cent is a consistent feature of our results regardless of how we modify our approach to measuring the relationship between mass and light. For example, deprojecting the mass and measuring both quantities within r500, that is itself obtained from the lensing analysis, yields σ _{lnM_WL|LK}=10^{+7}_{-5} per cent and b=0.97^{+0.17}_{-0.17}. We also find that selecting members based on their (J - K) colours instead of spectroscopic redshifts neither increases the scatter nor modifies the slope. Overall our results indicate that near-infrared luminosity measured on scales comparable with r500 (typically 1 Mpc for our sample) is a low scatter and relatively inexpensive proxy for weak-lensing mass. Near-infrared luminosity may therefore be a useful mass proxy for cluster cosmology experiments.

Benchmarking fully analytic DFT force fields for vibrational spectroscopy: A study on halogenated compounds

NASA Astrophysics Data System (ADS)

Pietropolli Charmet, Andrea; Cornaton, Yann

2018-05-01

This work presents an investigation of the theoretical predictions yielded by anharmonic force fields having the cubic and quartic force constants are computed analytically by means of density functional theory (DFT) using the recursive scheme developed by M. Ringholm et al. (J. Comput. Chem. 35 (2014) 622). Different functionals (namely B3LYP, PBE, PBE0 and PW86x) and basis sets were used for calculating the anharmonic vibrational spectra of two halomethanes. The benchmark analysis carried out demonstrates the reliability and overall good performances offered by hybrid approaches, where the harmonic data obtained at the coupled cluster with single and double excitations level of theory augmented by a perturbational estimate of the effects of connected triple excitations, CCSD(T), are combined with the fully analytic higher order force constants yielded by DFT functionals. These methods lead to reliable and computationally affordable calculations of anharmonic vibrational spectra with an accuracy comparable to that yielded by hybrid force fields having the anharmonic force fields computed at second order Møller-Plesset perturbation theory (MP2) level of theory using numerical differentiation but without the corresponding potential issues related to computational costs and numerical errors.

Integrated cosmological probes: Extended analysis

NASA Astrophysics Data System (ADS)

Nicola, Andrina; Refregier, Alexandre; Amara, Adam

2017-04-01

Recent progress in cosmology has relied on combining different cosmological probes. In an earlier work, we implemented an integrated approach to cosmology where the probes are combined into a common framework at the map level. This has the advantage of taking full account of the correlations between the different probes, to provide a stringent test of systematics and of the validity of the cosmological model. We extend this analysis to include not only cosmic microwave background (CMB) temperature, galaxy clustering, and weak lensing from the Sloan Digital Sky Survey (SDSS) but also CMB lensing, weak lensing from Dark Energy Survey Science Verification (DES SV) data, type Ia supernova, and H0 measurements. This yields 12 auto- and cross-power spectra which include the CMB temperature power spectrum, cosmic shear, galaxy clustering, galaxy-galaxy lensing, CMB lensing cross-correlation along with other cross-correlations, as well as background probes. Furthermore, we extend the treatment of systematic uncertainties by studying the impact of intrinsic alignments, baryonic corrections, residual foregrounds in the CMB temperature, and calibration factors for the different power spectra. For Λ CDM , we find results that are consistent with our earlier work. Given our enlarged data set and systematics treatment, this confirms the robustness of our analysis and results. Furthermore, we find that our best-fit cosmological model gives a good fit to all the data we consider with no signs of tensions within our analysis. We also find our constraints to be consistent with those found by the joint analysis of the WMAP9, SPT, and ACT CMB experiments and the KiDS weak lensing survey. Comparing with the Planck Collaboration results, we see a broad agreement, but there are indications of a tension from the marginalized constraints in most pairs of cosmological parameters. Since our analysis includes CMB temperature Planck data at 10 <ℓ<610 , the tension appears to arise between the Planck high-ℓ modes and the other measurements. Furthermore, we find the constraints on the probe calibration parameters to be in agreement with expectations, showing that the data sets are mutually consistent. In particular, this yields a confirmation of the amplitude calibration of the weak lensing measurements from the SDSS, DES SV, and Planck CMB lensing from our integrated analysis.

Group additivity-Pourbaix diagrams advocate thermodynamically stable nanoscale clusters in aqueous environments

PubMed Central

Wills, Lindsay A.; Qu, Xiaohui; Chang, I-Ya; Mustard, Thomas J. L.; Keszler, Douglas A.; Persson, Kristin A.; Cheong, Paul Ha-Yeon

2017-01-01

The characterization of water-based corrosion, geochemical, environmental and catalytic processes rely on the accurate depiction of stable phases in a water environment. The process is aided by Pourbaix diagrams, which map the equilibrium solid and solution phases under varying conditions of pH and electrochemical potential. Recently, metastable or possibly stable nanometric aqueous clusters have been proposed as intermediate species in non-classical nucleation processes. Herein, we describe a Group Additivity approach to obtain Pourbaix diagrams with full consideration of multimeric cluster speciation from computations. Comparisons with existing titration results from experiments yield excellent agreement. Applying this Group Additivity-Pourbaix approach to Group 13 elements, we arrive at a quantitative evaluation of cluster stability, as a function of pH and concentration, and present compelling support for not only metastable but also thermodynamically stable multimeric clusters in aqueous solutions. PMID:28643782

Ten Billion Years of Brightest Cluster Galaxy Alignments

NASA Astrophysics Data System (ADS)

West, Michael J.

2017-07-01

Astronomers long assumed that galaxies are randomly oriented in space. However, it's now clear that some have preferred orientations with respect to their surroundings. Chief among these are the giant ellipticals found at the centers of rich galaxy clusters, whose major axes are often aligned with those of their host clusters - a remarkable coherence of structures over millions of light years. A better understanding of these alignments can yield new insights into the processes that have shaped galaxies over the history of the universe. Using Hubble Space Telescope observations of high-redshift galaxy clusters, we show for the first time that such alignments are seen at epochs when the universe was only one-third its current age. These results suggest that the brightest galaxies in clusters are the product of a special formation history, one influenced by development of the cosmic web over billions of years.

New mechanisms of cluster diffusion on metal fcc(100) surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Salo, Petri; Alatalo, Matti; Ala-Nissila, Tapio

2001-03-01

We have studied atomic mechanisms of the diffusion of small clusters on the fcc(100) metal surfaces using semi-empirical and ab-initio molecular static calculations. Primary goal of these studies was to investigate possible many-body mechanisms of cluster motion which can contribute to low temperature crystal growth. We used embedded atom and Glue potentials in semi-empirical simulations of Cu and Al. Combination of the Nudged Elastic Band and Eigenvector Following methods allowed us to find all the possible transition paths for cluster movements on flat terrace. In case of Cu(001) we have found several new mechanisms for diffusion of clusters, including mechanisms called row-shearing and dimer-rotating in which a whole row inside an island moves according to a concerted jump and a dimer rotates at the periphery of an island, respectively. In some cases these mechanisms yield a lower energy barrier than the standard mechanisms.

Optimal control of the strong-field ionization of silver clusters in helium droplets

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

Truong, N. X.; Goede, S.; Przystawik, A.

Optimal control techniques combined with femtosecond laser pulse shaping are applied to steer and enhance the strong-field induced emission of highly charged atomic ions from silver clusters embedded in helium nanodroplets. With light fields shaped in amplitude and phase we observe a substantial increase of the Ag{sup q+} yield for q>10 when compared to bandwidth-limited and optimally stretched pulses. A remarkably simple double-pulse structure, containing a low-intensity prepulse and a stronger main pulse, turns out to produce the highest atomic charge states up to Ag{sup 20+}. A negative chirp during the main pulse hints at dynamic frequency locking to themore » cluster plasmon. A numerical optimal control study on pure silver clusters with a nanoplasma model converges to a similar pulse structure and corroborates that the optimal light field adapts to the resonant excitation of cluster surface plasmons for efficient ionization.« less

Footprinting of Inhibitor Interactions of In Silico Identified Inhibitors of Trypanothione Reductase of Leishmania Parasite

PubMed Central

Venkatesan, Santhosh K.; Dubey, Vikash Kumar

2012-01-01

Structure-based virtual screening of NCI Diversity set II compounds was performed to indentify novel inhibitor scaffolds of trypanothione reductase (TR) from Leishmania infantum. The top 50 ranked hits were clustered using the AuPoSOM tool. Majority of the top-ranked compounds were Tricyclic. Clustering of hits yielded four major clusters each comprising varying number of subclusters differing in their mode of binding and orientation in the active site. Moreover, for the first time, we report selected alkaloids and dibenzothiazepines as inhibitors of Leishmania infantum TR. The mode of binding observed among the clusters also potentiates the probable in vitro inhibition kinetics and aids in defining key interaction which might contribute to the inhibition of enzymatic reduction of T[S] 2. The method provides scope for automation and integration into the virtual screening process employing docking softwares, for clustering the small molecule inhibitors based upon protein-ligand interactions. PMID:22550471

Monoatomic and cluster beam effect on ToF-SIMS spectra of self-assembled monolayers on gold

NASA Astrophysics Data System (ADS)

Tuccitto, N.; Torrisi, V.; Delfanti, I.; Licciardello, A.

2008-12-01

Self-assembled monolayers represent well-defined systems that is a good model surface to study the effect of primary ion beams used in secondary ion mass spectrometry. The effect of polyatomic primary beams on both aliphatic and aromatic self-assembled monolayers has been studied. In particular, we analysed the variation of the relative secondary ion yield of both substrate metal-cluster (Au n-) in comparison with the molecular ions (M -) and clusters (M xAu y-) by using Bi +, Bi 3+, Bi 5+ beams. Moreover, the differences in the secondary ion generation efficiency are discussed. The main effect of the cluster beams is related to an increased formation of low-mass fragments and to the enhancement of the substrate related gold-clusters. The results show that, at variance of many other cases, the static SIMS of self-assembled monolayers does not benefit of the use of polyatomic primary ions.