Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Prokaryotic Gene Clusters: A Rich Toolbox for Synthetic Biology

PubMed Central

Fischbach, Michael; Voigt, Christopher A.

2014-01-01

Bacteria construct elaborate nanostructures, obtain nutrients and energy from diverse sources, synthesize complex molecules, and implement signal processing to react to their environment. These complex phenotypes require the coordinated action of multiple genes, which are often encoded in a contiguous region of the genome, referred to as a gene cluster. Gene clusters sometimes contain all of the genes necessary and sufficient for a particular function. As an evolutionary mechanism, gene clusters facilitate the horizontal transfer of the complete function between species. Here, we review recent work on a number of clusters whose functions are relevant to biotechnology. Engineering these clusters has been hindered by their regulatory complexity, the need to balance the expression of many genes, and a lack of tools to design and manipulate DNA at this scale. Advances in synthetic biology will enable the large-scale bottom-up engineering of the clusters to optimize their functions, wake up cryptic clusters, or to transfer them between organisms. Understanding and manipulating gene clusters will move towards an era of genome engineering, where multiple functions can be “mixed-and-matched” to create a designer organism. PMID:21154668

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Low-luminosity stellar mass functions in globular clusters

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

Richer, H.B.; Fahlman, G.G.; Buonanno, R.

New data are presented on cluster luminosity functions and mass functions for selected fields in the globular clusters M13 and M71, extending down the main sequence to at least 0.2 solar mass. In this experiment, CCD photometry data were obtained at the prime focus of the CFHT on the cluster fields that were far from the cluster center. Luminosity functions were constructed, using the ADDSTAR routine to correct for the background, and mass functions were derived using the available models. The mass functions obtained for M13 and M71 were compared to existing data for NGC 6397. Results show that (1)more » all three globular clusters display a marked change in slope at about 0.4 solar mass, with the slopes becoming considerably steeper toward lower masses; (2) there is no correlation between the slope of the mass function and metallicity; and (3) the low-mass slope of the mass function for M13 is much steeper than for NGC 6397 and M71. 22 refs.« less

An approach to functionally relevant clustering of the protein universe: Active site profile‐based clustering of protein structures and sequences

PubMed Central

Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.

2017-01-01

Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

The ACS Survey of Galactic Globular Clusters. VIII. Effects of Environment on Globular Cluster Global Mass Functions

NASA Astrophysics Data System (ADS)

Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael

2010-02-01

We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.

Galaxy clusters and cold dark matter - A low-density unbiased universe?

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue

1992-01-01

Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.

PubMed

Kim, Mi Ae; Shin, Seung Woo; Park, Jong Sook; Uh, Soo Taek; Chang, Hun Soo; Bae, Da Jeong; Cho, You Sook; Park, Hae Sim; Yoon, Ho Joo; Choi, Byoung Whui; Kim, Yong Hoon; Park, Choon Sik

2017-11-01

Asthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation. A uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters. Four subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation. Two different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two. Copyright © 2017 The Korean Academy of Asthma, Allergy and Clinical Immunology · The Korean Academy of Pediatric Allergy and Respiratory Disease

Slicing cluster mass functions with a Bayesian razor

NASA Astrophysics Data System (ADS)

Sealfon, C. D.

2010-08-01

We apply a Bayesian ``razor" to forecast Bayes factors between different parameterizations of the galaxy cluster mass function. To demonstrate this approach, we calculate the minimum size N-body simulation needed for strong evidence favoring a two-parameter mass function over one-parameter mass functions and visa versa, as a function of the minimum cluster mass.

Description of an α-cluster tail in 8Be and 20Ne: Delocalization of the α cluster by quantum penetration

NASA Astrophysics Data System (ADS)

Kanada-En'yo, Yoshiko

2014-10-01

We analyze the α-cluster wave functions in cluster states of ^8Be and ^{20}Ne by comparing the exact relative wave function obtained by the generator coordinate method (GCM) with various types of trial functions. For the trial functions, we adopt the fixed range shifted Gaussian of the Brink-Bloch (BB) wave function, the spherical Gaussian with the adjustable range parameter of the spherical Tohsaki-Horiuchi-Schuck-Röpke (sTHSR), the deformed Gaussian of the deformed THSR (dTHSR), and a function with the Yukawa tail (YT). The quality of the description of the exact wave function with a trial function is judged by the squared overlap between the trial function and the GCM wave function. A better result is obtained with the sTHSR wave function than the BB wave function, and further improvement can be made with the dTHSR wave function because these wave functions can describe the outer tail better. The YT wave function gives almost an equal quality to or even better quality than the dTHSR wave function, indicating that the outer tail of α-cluster states is characterized by the Yukawa-like tail rather than the Gaussian tail. In weakly bound α-cluster states with small α separation energy and the low centrifugal and Coulomb barriers, the outer tail part is the slowly damping function described well by the quantum penetration through the effective barrier. This outer tail characterizes the almost zero-energy free α gas behavior, i.e., the delocalization of the cluster.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

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.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Functional Interference Clusters in Cancer Patients With Bone Metastases: A Secondary Analysis of RTOG 9714

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

Chow, Edward, E-mail: Edward.Chow@sunnybrook.c; James, Jennifer; Barsevick, Andrea

Purpose: To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases. Methods: Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up.more » Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up. Results: There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders. Conclusion: Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.« less

Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

PubMed

Lewandowski, Kathryn E; Baker, Justin T; McCarthy, Julie M; Norris, Lesley A; Öngür, Dost

2018-04-01

Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2018, 24, 382-390).

The young star cluster population of M51 with LEGUS - II. Testing environmental dependences

NASA Astrophysics Data System (ADS)

Messa, Matteo; Adamo, A.; Calzetti, D.; Reina-Campos, M.; Colombo, D.; Schinnerer, E.; Chandar, R.; Dale, D. A.; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Elmegreen, B. G.; Fumagalli, M.; Johnson, K. E.; Kruijssen, J. M. D.; Östlin, G.; Shabani, F.; Smith, L. J.; Whitmore, B. C.

2018-06-01

It has recently been established that the properties of young star clusters (YSCs) can vary as a function of the galactic environment in which they are found. We use the cluster catalogue produced by the Legacy Extragalactic UV Survey (LEGUS) collaboration to investigate cluster properties in the spiral galaxy M51. We analyse the cluster population as a function of galactocentric distance and in arm and inter-arm regions. The cluster mass function exhibits a similar shape at all radial bins, described by a power law with a slope close to -2 and an exponential truncation around 105 M⊙. While the mass functions of the YSCs in the spiral arm and inter-arm regions have similar truncation masses, the inter-arm region mass function has a significantly steeper slope than the one in the arm region, a trend that is also observed in the giant molecular cloud mass function and predicted by simulations. The age distribution of clusters is dependent on the region considered, and is consistent with rapid disruption only in dense regions, while little disruption is observed at large galactocentric distances and in the inter-arm region. The fraction of stars forming in clusters does not show radial variations, despite the drop in the H2 surface density measured as a function of galactocentric distance. We suggest that the higher disruption rate observed in the inner part of the galaxy is likely at the origin of the observed flat cluster formation efficiency radial profile.

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

PubMed

Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

2016-01-01

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Equilibrium Structures and Absorption Spectra for SixOy Molecular Clusters using Density Functional Theory

DTIC Science & Technology

2017-05-05

dependent density functional theory (TD-DFT). The size of the clusters considered is relatively large compared to those considered in previous studies...are characterized by many different geometries, which potentially can be optimized with respect to specific materials design criteria, i.e., molecular...SixOy molecular clusters using density functional theory (DFT). The size of the clusters considered, however, is relatively large compared to those

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

PubMed

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p < 0.005 FDR-corrected vs . control group). No difference between patients and controls was found comparing the contralateral hypothalami. Conclusions The observed deranged functional connectivity between the posterior ipsilateral hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

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

Goudfrooij, Paul, E-mail: goudfroo@stsci.edu

We study mass functions of globular clusters derived from Hubble Space Telescope/Advanced Camera for Surveys images of the early-type merger remnant galaxy NGC 1316, which hosts a significant population of metal-rich globular clusters of intermediate age ({approx}3 Gyr). For the old, metal-poor ({sup b}lue{sup )} clusters, the peak mass of the mass function M{sub p} increases with internal half-mass density {rho}{sub h} as M{sub p}{proportional_to}{rho}{sub h}{sup 0.44}, whereas it stays approximately constant with galactocentric distance R{sub gal}. The mass functions of these clusters are consistent with a simple scenario in which they formed with a Schechter initial mass function andmore » evolved subsequently by internal two-body relaxation. For the intermediate-age population of metal-rich ({sup r}ed{sup )} clusters, the faint end of the previously reported power-law luminosity function of the clusters with R{sub gal} > 9 kpc is due to many of those clusters having radii larger than the theoretical maximum value imposed by the tidal field of NGC 1316 at their R{sub gal}. This renders disruption by two-body relaxation ineffective. Only a few such diffuse clusters are found in the inner regions of NGC 1316. Completeness tests indicate that this is a physical effect. Using comparisons with star clusters in other galaxies and cluster disruption calculations using published models, we hypothesize that most red clusters in the low-{rho}{sub h} tail of the initial distribution have already been destroyed in the inner regions of NGC 1316 by tidal shocking, and that several remaining low-{rho}{sub h} clusters will evolve dynamically to become similar to 'faint fuzzies' that exist in several lenticular galaxies. Finally, we discuss the nature of diffuse red clusters in early-type galaxies.« less

Luminosity Function of Faint Globular Clusters in M87

NASA Astrophysics Data System (ADS)

Waters, Christopher Z.; Zepf, Stephen E.; Lauer, Tod R.; Baltz, Edward A.; Silk, Joseph

2006-10-01

We present the luminosity function to very faint magnitudes for the globular clusters in M87, based on a 30 orbit Hubble Space Telescope (HST) WFPC2 imaging program. The very deep images and corresponding improved false source rejection allow us to probe the mass function further beyond the turnover than has been done before. We compare our luminosity function to those that have been observed in the past, and confirm the similarity of the turnover luminosity between M87 and the Milky Way. We also find with high statistical significance that the M87 luminosity function is broader than that of the Milky Way. We discuss how determining the mass function of the cluster system to low masses can constrain theoretical models of the dynamical evolution of globular cluster systems. Our mass function is consistent with the dependence of mass loss on the initial cluster mass given by classical evaporation, and somewhat inconsistent with newer proposals that have a shallower mass dependence. In addition, the rate of mass loss is consistent with standard evaporation models, and not with the much higher rates proposed by some recent studies of very young cluster systems. We also find that the mass-size relation has very little slope, indicating that there is almost no increase in the size of a cluster with increasing mass.

Thermodynamically accessible titanium clusters TiN, N = 2-32.

PubMed

Lazauskas, Tomas; Sokol, Alexey A; Buckeridge, John; Catlow, C Richard A; Escher, Susanne G E T; Farrow, Matthew R; Mora-Fonz, David; Blum, Volker W; Phaahla, Tshegofatso M; Chauke, Hasani R; Ngoepe, Phuti E; Woodley, Scott M

2018-05-10

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area. The results suggest a growth mechanism that is based on forming coordination centres by interpenetrating icosahedra, icositetrahedra and Frank-Kasper polyhedra. We identify centres of coordination, which act as centres of bulk nucleation in medium sized clusters and determine the morphological features of the cluster.

Defining functioning levels in patients with schizophrenia: A combination of a novel clustering method and brain SPECT analysis.

PubMed

Catherine, Faget-Agius; Aurélie, Vincenti; Eric, Guedj; Pierre, Michel; Raphaëlle, Richieri; Marine, Alessandrini; Pascal, Auquier; Christophe, Lançon; Laurent, Boyer

2017-12-30

This study aims to define functioning levels of patients with schizophrenia by using a method of interpretable clustering based on a specific functioning scale, the Functional Remission Of General Schizophrenia (FROGS) scale, and to test their validity regarding clinical and neuroimaging characterization. In this observational study, patients with schizophrenia have been classified using a hierarchical top-down method called clustering using unsupervised binary trees (CUBT). Socio-demographic, clinical, and neuroimaging SPECT perfusion data were compared between the different clusters to ensure their clinical relevance. A total of 242 patients were analyzed. A four-group functioning level structure has been identified: 54 are classified as "minimal", 81 as "low", 64 as "moderate", and 43 as "high". The clustering shows satisfactory statistical properties, including reproducibility and discriminancy. The 4 clusters consistently differentiate patients. "High" functioning level patients reported significantly the lowest scores on the PANSS and the CDSS, and the highest scores on the GAF, the MARS and S-QoL 18. Functioning levels were significantly associated with cerebral perfusion of two relevant areas: the left inferior parietal cortex and the anterior cingulate. Our study provides relevant functioning levels in schizophrenia, and may enhance the use of functioning scale. Copyright © 2017 Elsevier B.V. All rights reserved.

Adapted managerial mathematical model to study the functions and interactions between enterprises in high-tech cluster

NASA Astrophysics Data System (ADS)

Anguelov, Kiril P.; Kaynakchieva, Vesela G.

2017-12-01

The aim of the current study is to research and analyze Adapted managerial mathematical model to study the functions and interactions between enterprises in high-tech cluster, and his approbation in given high-tech cluster; to create high-tech cluster, taking into account the impact of relationships between individual units in the cluster-Leading Enterprises, network of Enterprises subcontractors, economic infrastructure.

A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.

Statistical Issues in Galaxy Cluster Cosmology

NASA Technical Reports Server (NTRS)

Mantz, Adam

2013-01-01

The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

NASA Astrophysics Data System (ADS)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties.

PubMed

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-25

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi 4 , NLi 5 , CLi 6 , BLI 7 and Al 12 Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability ([Formula: see text]) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

A novel symptom cluster analysis among ambulatory HIV/AIDS patients in Uganda.

PubMed

Namisango, Eve; Harding, Richard; Katabira, Elly T; Siegert, Richard J; Powell, Richard A; Atuhaire, Leonard; Moens, Katrien; Taylor, Steve

2015-01-01

Symptom clusters are gaining importance given HIV/AIDS patients experience multiple, concurrent symptoms. This study aimed to: determine clusters of patients with similar symptom combinations; describe symptom combinations distinguishing the clusters; and evaluate the clusters regarding patient socio-demographic, disease and treatment characteristics, quality of life (QOL) and functional performance. This was a cross-sectional study of 302 adult HIV/AIDS outpatients consecutively recruited at two teaching and referral hospitals in Uganda. Socio-demographic and seven-day period symptom prevalence and distress data were self-reported using the Memorial Symptom Assessment Schedule. QOL was assessed using the Medical Outcome Scale and functional performance using the Karnofsky Performance Scale. Symptom clusters were established using hierarchical cluster analysis with squared Euclidean distances using Ward's clustering methods based on symptom occurrence. Analysis of variance compared clusters on mean QOL and functional performance scores. Patient subgroups were categorised based on symptom occurrence rates. Five symptom occurrence clusters were identified: Cluster 1 (n=107), high-low for sensory discomfort and eating difficulties symptoms; Cluster 2 (n=47), high-low for psycho-gastrointestinal symptoms; Cluster 3 (n=71), high for pain and sensory disturbance symptoms; Cluster 4 (n=35), all high for general HIV/AIDS symptoms; and Cluster 5 (n=48), all low for mood-cognitive symptoms. The all high occurrence cluster was associated with worst functional status, poorest QOL scores and highest symptom-associated distress. Use of antiretroviral therapy was associated with all high symptom occurrence rate (Fisher's exact=4, P<0.001). CD4 count group below 200 was associated with the all high occurrence rate symptom cluster (Fisher's exact=41, P<0.001). Symptom clusters have a differential, affect HIV/AIDS patients' self-reported outcomes, with the subgroup experiencing high-symptom occurrence rates having a higher risk of poorer outcomes. Identification of symptom clusters could provide insights into commonly co-occurring symptoms that should be jointly targeted for management in patients with multiple complaints.

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

A catalogue of masses, structural parameters and velocity dispersion profiles of 112 Milky Way globular clusters

NASA Astrophysics Data System (ADS)

Baumgardt, H.; Hilker, M.

2018-05-01

We have determined masses, stellar mass functions and structural parameters of 112 Milky Way globular clusters by fitting a large set of N-body simulations to their velocity dispersion and surface density profiles. The velocity dispersion profiles were calculated based on a combination of more than 15,000 high-precision radial velocities which we derived from archival ESO/VLT and Keck spectra together with ˜20, 000 published radial velocities from the literature. Our fits also include the stellar mass functions of the globular clusters, which are available for 47 clusters in our sample, allowing us to self-consistently take the effects of mass segregation and ongoing cluster dissolution into account. We confirm the strong correlation between the global mass functions of globular clusters and their relaxation times recently found by Sollima & Baumgardt (2017). We also find a correlation of the escape velocity from the centre of a globular cluster and the fraction of first generation stars (FG) in the cluster recently derived for 57 globular clusters by Milone et al. (2017), but no correlation between the FG star fraction and the global mass function of a globular cluster. This could indicate that the ability of a globular cluster to keep the wind ejecta from the polluting star(s) is the crucial parameter determining the presence and fraction of second generation stars and not its later dynamical mass loss.

Distinct functional domains within the acidic cluster of tegument protein pp28 required for trafficking and cytoplasmic envelopment of human cytomegalovirus.

PubMed

Seo, Jun-Young; Jeon, Hyejin; Hong, Sookyung; Britt, William J

2016-10-01

Human cytomegalovirus UL99-encoded tegument protein pp28 contains a 16 aa acidic cluster that is required for pp28 trafficking to the assembly compartment (AC) and the virus assembly. However, functional signals within the acidic cluster of pp28 remain undefined. Here, we demonstrated that an acidic cluster rather than specific sorting signals was required for trafficking to the AC. Recombinant viruses with chimeric pp28 proteins expressing non-native acidic clusters exhibited delayed viral growth kinetics and decreased production of infectious virus, indicating that the native acidic cluster of pp28 was essential for wild-type virus assembly. These results suggested that the acidic cluster of pp28 has distinct functional domains required for trafficking and for efficient virus assembly. The first half (aa 44-50) of the acidic cluster was sufficient for pp28 trafficking, whereas the native acidic cluster consisting of aa 51-59 was required for the assembly of wild-type levels of infectious virus.

Uncertainties in the cluster-cluster correlation function

NASA Astrophysics Data System (ADS)

Ling, E. N.; Frenk, C. S.; Barrow, J. D.

1986-12-01

The bootstrap resampling technique is applied to estimate sampling errors and significance levels of the two-point correlation functions determined for a subset of the CfA redshift survey of galaxies and a redshift sample of 104 Abell clusters. The angular correlation function for a sample of 1664 Abell clusters is also calculated. The standard errors in xi(r) for the Abell data are found to be considerably larger than quoted 'Poisson errors'. The best estimate for the ratio of the correlation length of Abell clusters (richness class R greater than or equal to 1, distance class D less than or equal to 4) to that of CfA galaxies is 4.2 + 1.4 or - 1.0 (68 percentile error). The enhancement of cluster clustering over galaxy clustering is statistically significant in the presence of resampling errors. The uncertainties found do not include the effects of possible systematic biases in the galaxy and cluster catalogs and could be regarded as lower bounds on the true uncertainty range.

Text analysis of MEDLINE for discovering functional relationships among genes: evaluation of keyword extraction weighting schemes.

PubMed

Liu, Ying; Navathe, Shamkant B; Pivoshenko, Alex; Dasigi, Venu G; Dingledine, Ray; Ciliax, Brian J

2006-01-01

One of the key challenges of microarray studies is to derive biological insights from the gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the functional links among genes. However, the quality of the keyword lists significantly affects the clustering results. We compared two keyword weighting schemes: normalised z-score and term frequency-inverse document frequency (TFIDF). Two gene sets were tested to evaluate the effectiveness of the weighting schemes for keyword extraction for gene clustering. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords outperformed those produced from normalised z-score weighted keywords. The optimised algorithms should be useful for partitioning genes from microarray lists into functionally discrete clusters.

Cognitive Deficits in Executive Functions and Decision-Making Impairments Cluster Gambling Disorder Sub-types.

PubMed

Mallorquí-Bagué, Núria; Tolosa-Sola, Iris; Fernández-Aranda, Fernándo; Granero, Roser; Fagundo, Ana Beatriz; Lozano-Madrid, María; Mestre-Bach, Gemma; Gómez-Peña, Mónica; Aymamí, Neus; Borrás-González, Indira; Sánchez-González, Jessica; Baño, Marta; Del Pino-Gutiérrez, Amparo; Menchón, José M; Jiménez-Murcia, Susana

2018-03-01

To identify Gambling Disorder (GD) subtypes, in a population of men seeking treatment for GD, according to specific executive function domains (i.e., cognitive flexibility, inhibition and working memory as well as decision making) which are usually impaired in addictive behaviors. A total of 145 males ranging from 18 to 65 years diagnosed with GD were included in this study. All participants completed: (a) a set of questionnaires to assess psychopathological symptoms, personality and impulsivity traits, and (b) a battery of neuropsychological measures to test different executive functioning domains. Two clusters were identified based on the individual performance on the neuropsychological assessment. Cluster 1 [n = 106; labeled as Low Impaired Executive Function (LIEF)] was composed by patients with poor results in the neuropsychological assessment; cluster 2 patients [n = 46; labeled as High Impaired Executive Function (HIEF)] presented significantly higher deficits on the assessed domains and performed worse than the ones of LIEF cluster. Regarding the characterization of these two clusters, patients in cluster 2 were significantly older, unemployed and registered higher mean age of GD onset than patients in cluster 1. Additionally, patients in cluster 2 also obtained higher psychopathological symptoms, impulsivity (in both positive and negative urgency as well as sensation seeking) and some specific personality traits (higher harm avoidance as well as lower self-directedness and cooperativeness) than patients in cluster 1. The results of this study describe two different GD subtypes based on different cognitive domains (i.e., executive function performance). These two GD subtypes display different impulsivity and personality traits as well as clinical symptoms. The results provide new insight into the etiology and characterization of GD and have the potential to help improving current treatments.

Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey.

PubMed

Fens, Niki; van Rossum, Annelot G J; Zanen, Pieter; van Ginneken, Bram; van Klaveren, Rob J; Zwinderman, Aeilko H; Sterk, Peter J

2013-06-01

Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers. Adults between 50-75 years with a smoking history of at least 15 pack-years derived from a random population-based survey as part of the NELSON study underwent detailed assessment of pulmonary function, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor and cluster analyses were performed on the subgroup of subjects fulfilling the GOLD criteria for COPD (post-BD FEV1/FVC < 0.70). Three hundred subjects were recruited, of which 157 fulfilled the criteria for COPD and were included in the factor and cluster analysis. Four clusters were identified: cluster 1 (n = 35; 22%): mild COPD, limited symptoms and good quality of life. Cluster 2 (n = 48; 31%): low lung function, combined emphysema and chronic bronchitis and a distinct breath molecular profile. Cluster 3 (n = 60; 38%): emphysema predominant COPD with preserved lung function. Cluster 4 (n = 14; 9%): highly symptomatic COPD with mildly impaired lung function. In a leave-one-out validation analysis an accuracy of 97.4% was reached. This unbiased taxonomy for mild to moderate COPD reinforces clusters found in previous studies and thereby allows better phenotyping of COPD in the general (ex-) smoking population.

Hybrid approach of selecting hyperparameters of support vector machine for regression.

PubMed

Jeng, Jin-Tsong

2006-06-01

To select the hyperparameters of the support vector machine for regression (SVR), a hybrid approach is proposed to determine the kernel parameter of the Gaussian kernel function and the epsilon value of Vapnik's epsilon-insensitive loss function. The proposed hybrid approach includes a competitive agglomeration (CA) clustering algorithm and a repeated SVR (RSVR) approach. Since the CA clustering algorithm is used to find the nearly "optimal" number of clusters and the centers of clusters in the clustering process, the CA clustering algorithm is applied to select the Gaussian kernel parameter. Additionally, an RSVR approach that relies on the standard deviation of a training error is proposed to obtain an epsilon in the loss function. Finally, two functions, one real data set (i.e., a time series of quarterly unemployment rate for West Germany) and an identification of nonlinear plant are used to verify the usefulness of the hybrid approach.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

The Mass Function of Abell Clusters

NASA Astrophysics Data System (ADS)

Chen, J.; Huchra, J. P.; McNamara, B. R.; Mader, J.

1998-12-01

The velocity dispersion and mass functions for rich clusters of galaxies provide important constraints on models of the formation of Large-Scale Structure (e.g., Frenk et al. 1990). However, prior estimates of the velocity dispersion or mass function for galaxy clusters have been based on either very small samples of clusters (Bahcall and Cen 1993; Zabludoff et al. 1994) or large but incomplete samples (e.g., the Girardi et al. (1998) determination from a sample of clusters with more than 30 measured galaxy redshifts). In contrast, we approach the problem by constructing a volume-limited sample of Abell clusters. We collected individual galaxy redshifts for our sample from two major galaxy velocity databases, the NASA Extragalactic Database, NED, maintained at IPAC, and ZCAT, maintained at SAO. We assembled a database with velocity information for possible cluster members and then selected cluster members based on both spatial and velocity data. Cluster velocity dispersions and masses were calculated following the procedures of Danese, De Zotti, and di Tullio (1980) and Heisler, Tremaine, and Bahcall (1985), respectively. The final velocity dispersion and mass functions were analyzed in order to constrain cosmological parameters by comparison to the results of N-body simulations. Our data for the cluster sample as a whole and for the individual clusters (spatial maps and velocity histograms) in our sample is available on-line at http://cfa-www.harvard.edu/ huchra/clusters. This website will be updated as more data becomes available in the master redshift compilations, and will be expanded to include more clusters and large groups of galaxies.

Density functional theory and surface reactivity study of bimetallic AgnYm (n+m = 10) clusters

NASA Astrophysics Data System (ADS)

Hussain, Riaz; Hussain, Abdullah Ijaz; Chatha, Shahzad Ali Shahid; Hussain, Riaz; Hanif, Usman; Ayub, Khurshid

2018-06-01

Density functional theory calculations have been performed on pure silver (Agn), yttrium (Ym) and bimetallic silver yttrium clusters AgnYm (n + m = 2-10) for reactivity descriptors in order to realize sites for nucleophilic and electrophilic attack. The reactivity descriptors of the clusters, studied as a function of cluster size and shape, reveal the presence of different type of reactive sites in a cluster. The size and shape of the pure silver, yttrium and bimetallic silver yttrium cluster (n = 2-10) strongly influences the number and position of active sites for an electrophilic and/or nucleophilic attack. The trends of reactivities through reactivity descriptors are confirmed through comparison with experimental data for CO binding with silver clusters. Moreover, the adsorption of CO on bimetallic silver yttrium clusters is also evaluated. The trends of binding energies support the reactivity descriptors values. Doping of pure cluster with the other element also influence the hardness, softness and chemical reactivity of the clusters. The softness increases as we increase the number of silver atoms in the cluster, whereas the hardness decreases. The chemical reactivity increases with silver doping whereas it decreases by increasing yttrium concentration. Silver atoms are nucleophilic in small clusters but changed to electrophilic in large clusters.

Computational Investigation of the Geometrical and Electronic Structures of VGen-/0 (n = 1-4) Clusters by Density Functional Theory and Multiconfigurational CASSCF/CASPT2 Method.

PubMed

Tran, Van Tan; Nguyen, Minh Thao; Tran, Quoc Tri

2017-10-12

Density functional theory and the multiconfigurational CASSCF/CASPT2 method have been employed to study the low-lying states of VGe n -/0 (n = 1-4) clusters. For VGe -/0 and VGe 2 -/0 clusters, the relative energies and geometrical structures of the low-lying states are reported at the CASSCF/CASPT2 level. For the VGe 3 -/0 and VGe 4 -/0 clusters, the computational results show that due to the large contribution of the Hartree-Fock exact exchange, the hybrid B3LYP, B3PW91, and PBE0 functionals overestimate the energies of the high-spin states as compared to the pure GGA BP86 and PBE functionals and the CASPT2 method. On the basis of the pure GGA BP86 and PBE functionals and the CASSCF/CASPT2 results, the ground states of anionic and neutral clusters are defined, the relative energies of the excited states are computed, and the electron detachment energies of the anionic clusters are evaluated. The computational results are employed to give new assignments for all features in the photoelectron spectra of VGe 3 - and VGe 4 - clusters.

On the determination of age and mass functions of stars in young open star clusters from the analysis of their luminosity functions

NASA Astrophysics Data System (ADS)

Piskunov, A. E.; Belikov, A. N.; Kharchenko, N. V.; Sagar, R.; Subramaniam, A.

2004-04-01

We construct the observed luminosity functions of the remote young open clusters NGC 2383, 2384, 4103, 4755, 7510 and Hogg 15 from CCD observations of them. The observed LFs are corrected for field star contamination determined with the help of a Galactic star count model. In the case of Hogg 15 and NGC 2383 we also consider the additional contamination from neighbouring clusters NGC 4609 and 2384, respectively. These corrections provide a realistic pattern of cluster LF in the vicinity of the main-sequence (MS) turn-on point and at fainter magnitudes reveal the so-called H-feature arising as a result of the transition of the pre-MS phase to the MS, which is dependent on the cluster age. The theoretical LFs are constructed representing a cluster population model with continuous star formation for a short time-scale and a power-law initial mass function (IMF), and these are fitted to the observed LF. As a result, we are able to determine for each cluster a set of parameters describing the cluster population (the age, duration of star formation, IMF slope and percentage of field star contamination). It is found that in spite of the non-monotonic behaviour of observed LFs, cluster IMFs can be described as power-law functions with slopes similar to Salpeter's value. The present main-sequence turn-on cluster ages are several times lower than those derived from the fitting of theoretical isochrones to the turn-off region of the upper main sequences.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

PubMed

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

The Luminosity Function of Star Clusters in 20 Star-Forming Galaxies Based on Hubble Legacy Archive Photometry

NASA Astrophysics Data System (ADS)

Bowers, Ariel; Whitmore, B. C.; Chandar, R.; Larsen, S. S.

2014-01-01

Luminosity functions have been determined for star cluster populations in 20 nearby (4 - 30 Mpc), star-forming galaxies based on ACS source lists generated by the Hubble Legacy Archive (http://hla.stsci.edu). These cluster catalogs provide one of the largest sets of uniform, automatically-generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster luminosity function can be approximated by a power-law, dN/dL ∝ Lα, with an average value for α of -2.37 and rms scatter = 0.18. A comparison of fitting results based on methods which use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum-likelihood) method to give slightly more negative values of α for galaxies with steper luminosity functions. Our uniform database results in a small scatter (0.5 magnitude) in the correlation between the magnitude of the brightest cluster (Mbrightest) and Log of the number of clusters brighter than MI = -9 (Log N). We also examine the magnitude of the brightest cluster vs. Log SFR for a sample including LIRGS and ULIRGS.

Starburst clusters in the Galactic center

NASA Astrophysics Data System (ADS)

Habibi, Maryam

2014-09-01

The central region of the Galaxy is the most active site of star formation in the Milky Way, where massive stars have formed very recently and are still forming today. The rich population of massive stars in the Galactic center provide a unique opportunity to study massive stars in their birth environment and probe their initial mass function, which is the spectrum of stellar masses at their birth. The Arches cluster is the youngest among the three massive clusters in the Galactic center, providing a collection of high-mass stars and a very dense core which makes this cluster an excellent site to address questions about massive star formation, the stellar mass function and the dynamical evolution of massive clusters in the Galactic center. In this thesis, I perform an observational study of the Arches cluster using K_{s}-band imaging obtained with NAOS/CONICA at the VLT combined with Subaru/Cisco J-band data to gain a full understanding of the cluster mass distribution out to its tidal radius for the first time. Since the light from the Galactic center reaches us through the Galactic disc, the extinction correction is crucial when studying this region. I use a Bayesian method to construct a realistic extinction map of the cluster. It is shown in this study that the determination of the mass of the most massive star in the Arches cluster, which had been used in previous studies to establish an upper mass limit for the star formation process in the Milky Way, strongly depends on the assumed slope of the extinction law. Assuming the two regimes of widely used infrared extinction laws, I show that the difference can reach up to 30% for individually derived stellar masses and Δ A_{Ks}˜ 1 magnitude in acquired K_{s}-band extinction, while the present-day mass function slope changes by ˜ 0.17 dex. The present-day mass function slope derived assuming the more recent extinction law, which suggests a steeper wavelength dependence for the infrared extinction law, reveals an overpopulation of massive stars in the core (r<0.2 pc) with a flat slope of α_{Nishi}=-1.50 ±0.35 in comparison to the Salpeter slope of α=-2.3. The slope of the mass function increases to α_{Nishi}=-2.21 ±0.27 in the intermediate annulus (0.2

Dysregulation and functional roles of miR-183-96-182 cluster in cancer cell proliferation, invasion and metastasis

PubMed Central

Ma, Yi; Liang, A-Juan; Fan, Yu-Ping; Huang, Yi-Ran; Zhao, Xiao-Ming; Sun, Yun; Chen, Xiang-Feng

2016-01-01

Previous studies have reported aberrant expression of the miR-183-96-182 cluster in a variety of tumors, which indicates its' diagnostic or prognostic value. However, a key characteristic of the miR-183-96-182 cluster is its varied expression levels, and pleomorphic functional roles in different tumors or under different conditions. In most tumor types, the cluster is highly expressed and promotes tumorigenesis, cancer progression and metastasis; yet tumor suppressive effects have also been reported in some tumors. In the present study, we discuss the upstream regulators and the downstream target genes of miR-183-96-182 cluster, and highlight the dysregulation and functional roles of this cluster in various tumor cells. Newer insights summarized in this review will help readers understand the different facets of the miR-183-96-182 cluster in cancer development and progression. PMID:27081087

Vector dissimilarity and clustering.

PubMed

Lefkovitch, L P

1991-04-01

Based on the description of objects by m attributes, an m-element vector dissimilarity function is defined that, unlike scalar functions, retains the distinction among attributes. This function, which satisfies the conditions for a metric, allows the definition of betweenness, which can then be used for clustering. Applications to the subset-generation phase of conditional clustering and to nearest-neighbor-type algorithms are described.

Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.

PubMed

Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi

2016-01-01

The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.

Low work function, stable compound clusters and generation process

DOEpatents

Dinh, Long N.; Balooch, Mehdi; Schildbach, Marcus A.; Hamza, Alex V.; McLean, II, William

2000-01-01

Low work function, stable compound clusters are generated by co-evaporation of a solid semiconductor (i.e., Si) and alkali metal (i.e., Cs) elements in an oxygen environment. The compound clusters are easily patterned during deposition on substrate surfaces using a conventional photo-resist technique. The cluster size distribution is narrow, with a peak range of angstroms to nanometers depending on the oxygen pressure and the Si source temperature. Tests have shown that compound clusters when deposited on a carbon substrate contain the desired low work function property and are stable up to 600.degree. C. Using the patterned cluster containing plate as a cathode baseplate and a faceplate covered with phosphor as an anode, one can apply a positive bias to the faceplate to easily extract electrons and obtain illumination.

Gender differences in associations between DSM-5 posttraumatic stress disorder symptom clusters and functional impairment in war veterans.

PubMed

Meyer, Eric C; Konecky, Brian; Kimbrel, Nathan A; DeBeer, Bryann B; Marx, Brian P; Schumm, Jeremiah; Penk, Walter E; Gulliver, Suzy Bird; Morissette, Sandra B

2018-05-01

Understanding the links between posttraumatic stress disorder (PTSD) symptoms and functional impairment is essential for assisting veterans in transitioning to civilian life. Moreover, there may be differences between men and women in the relationships between PTSD symptoms and functional impairment. However, no prior studies have examined the links between functional impairment and the revised symptom clusters as defined in the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5; American Psychiatric Association, 2013) or whether the associations between PTSD symptom clusters and functional impairment differ by gender. We examined the associations between the DSM-5 PTSD symptom clusters and functional impairment in 252 trauma-exposed Iraq and Afghanistan war veterans (79 females). Regression analyses included demographic factors and exposure to both combat and military sexual trauma as covariates. In the total sample, both the intrusions cluster (β = .18, p = .045) and the negative alterations in cognition and mood cluster (β = .45, p < .001) were associated with global functional impairment. Among male veterans, global functional impairment was associated only with negative alterations in cognition and mood (β = .52, p < .001). However, by contrast, among female veterans, only marked alterations in arousal and reactivity were associated with global functional impairment (β = .35, p = .027). These findings suggest that there may be important gender differences with respect to the relationship between PTSD symptoms and functional impairment. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Mobility of large clusters on a semiconductor surface: Kinetic Monte Carlo simulation results

NASA Astrophysics Data System (ADS)

M, Esen; A, T. Tüzemen; M, Ozdemir

2016-01-01

The mobility of clusters on a semiconductor surface for various values of cluster size is studied as a function of temperature by kinetic Monte Carlo method. The cluster resides on the surface of a square grid. Kinetic processes such as the diffusion of single particles on the surface, their attachment and detachment to/from clusters, diffusion of particles along cluster edges are considered. The clusters considered in this study consist of 150-6000 atoms per cluster on average. A statistical probability of motion to each direction is assigned to each particle where a particle with four nearest neighbors is assumed to be immobile. The mobility of a cluster is found from the root mean square displacement of the center of mass of the cluster as a function of time. It is found that the diffusion coefficient of clusters goes as D = A(T)Nα where N is the average number of particles in the cluster, A(T) is a temperature-dependent constant and α is a parameter with a value of about -0.64 < α < -0.75. The value of α is found to be independent of cluster sizes and temperature values (170-220 K) considered in this study. As the diffusion along the perimeter of the cluster becomes prohibitive, the exponent approaches a value of -0.5. The diffusion coefficient is found to change by one order of magnitude as a function of cluster size.

The relative vertex clustering value - a new criterion for the fast discovery of functional modules in protein interaction networks

PubMed Central

2015-01-01

Background Cellular processes are known to be modular and are realized by groups of proteins implicated in common biological functions. Such groups of proteins are called functional modules, and many community detection methods have been devised for their discovery from protein interaction networks (PINs) data. In current agglomerative clustering approaches, vertices with just a very few neighbors are often classified as separate clusters, which does not make sense biologically. Also, a major limitation of agglomerative techniques is that their computational efficiency do not scale well to large PINs. Finally, PIN data obtained from large scale experiments generally contain many false positives, and this makes it hard for agglomerative clustering methods to find the correct clusters, since they are known to be sensitive to noisy data. Results We propose a local similarity premetric, the relative vertex clustering value, as a new criterion allowing to decide when a node can be added to a given node's cluster and which addresses the above three issues. Based on this criterion, we introduce a novel and very fast agglomerative clustering technique, FAC-PIN, for discovering functional modules and protein complexes from a PIN data. Conclusions Our proposed FAC-PIN algorithm is applied to nine PIN data from eight different species including the yeast PIN, and the identified functional modules are validated using Gene Ontology (GO) annotations from DAVID Bioinformatics Resources. Identified protein complexes are also validated using experimentally verified complexes. Computational results show that FAC-PIN can discover functional modules or protein complexes from PINs more accurately and more efficiently than HC-PIN and CNM, the current state-of-the-art approaches for clustering PINs in an agglomerative manner. PMID:25734691

Diametrical clustering for identifying anti-correlated gene clusters.

PubMed

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

The Structure and Stability of Bn(+) Clusters

NASA Technical Reports Server (NTRS)

Ricca, Alessandra; Bauschlicher, Charles W., Jr.; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

The geometries of B+n clusters for n less than 14 have been optimized using density functional theory with the B3LYP functional. The most stable structure for each cluster is planar or quasi-planar. The B3LYP fragmentation energies are calibrated using coupled cluster theory. Overall, our corrected fragmentation energies are in reasonable agreement with experiment. Our results are compared with previous theoretical results.

Relations between the Woodcock-Johnson III Clinical Clusters and Measures of Executive Functions from the Delis-Kaplan Executive Function System

ERIC Educational Resources Information Center

Floyd, Randy G.; McCormack, Allison C.; Ingram, Elizabeth L.; Davis, Amy E.; Bergeron, Renee; Hamilton, Gloria

2006-01-01

This study examined the convergent relations between scores from four clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III) and measures of executive functions using a sample of school-aged children and a sample of adults. The WJ III clinical clusters included the Working Memory, Cognitive Fluency, Broad Attention,…

Analysis of multiplex gene expression maps obtained by voxelation.

PubMed

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental results confirm the hypothesis that genes with similar gene expression maps might have similar gene functions. The voxelation data takes into account the location information of gene expression level in mouse brain, which is novel in related research. The proposed approach can potentially be used to predict gene functions and provide helpful suggestions to biologists.

The insignificant evolution of the richness-mass relation of galaxy clusters

NASA Astrophysics Data System (ADS)

Andreon, S.; Congdon, P.

2014-08-01

We analysed the richness-mass scaling of 23 very massive clusters at 0.15 < z < 0.55 with homogenously measured weak-lensing masses and richnesses within a fixed aperture of 0.5 Mpc radius. We found that the richness-mass scaling is very tight (the scatter is <0.09 dex with 90% probability) and independent of cluster evolutionary status and morphology. This implies a close association between infall and evolution of dark matter and galaxies in the central region of clusters. We also found that the evolution of the richness-mass intercept is minor at most, and, given the minor mass evolution across the studied redshift range, the richness evolution of individual massive clusters also turns out to be very small. Finally, it was paramount to account for the cluster mass function and the selection function. Ignoring them would lead to larger biases than the (otherwise quoted) errors. Our study benefits from: a) weak-lensing masses instead of proxy-based masses thereby removing the ambiguity between a real trend and one induced by an accounted evolution of the used mass proxy; b) the use of projected masses that simplify the statistical analysis thereby not requiring consideration of the unknown covariance induced by the cluster orientation/triaxiality; c) the use of aperture masses as they are free of the pseudo-evolution of mass definitions anchored to the evolving density of the Universe; d) a proper accounting of the sample selection function and of the Malmquist-like effect induced by the cluster mass function; e) cosmological simulations for the computation of the cluster mass function, its evolution, and the mass growth of each individual cluster.

Development of New Open-Shell Perturbation and Coupled-Cluster Theories Based on Symmetric Spin Orbitals

NASA Technical Reports Server (NTRS)

Lee, Timothy J.; Arnold, James O. (Technical Monitor)

1994-01-01

A new spin orbital basis is employed in the development of efficient open-shell coupled-cluster and perturbation theories that are based on a restricted Hartree-Fock (RHF) reference function. The spin orbital basis differs from the standard one in the spin functions that are associated with the singly occupied spatial orbital. The occupied orbital (in the spin orbital basis) is assigned the delta(+) = 1/square root of 2(alpha+Beta) spin function while the unoccupied orbital is assigned the delta(-) = 1/square root of 2(alpha-Beta) spin function. The doubly occupied and unoccupied orbitals (in the reference function) are assigned the standard alpha and Beta spin functions. The coupled-cluster and perturbation theory wave functions based on this set of "symmetric spin orbitals" exhibit much more symmetry than those based on the standard spin orbital basis. This, together with interacting space arguments, leads to a dramatic reduction in the computational cost for both coupled-cluster and perturbation theory. Additionally, perturbation theory based on "symmetric spin orbitals" obeys Brillouin's theorem provided that spin and spatial excitations are both considered. Other properties of the coupled-cluster and perturbation theory wave functions and models will be discussed.

Novel Functions of MicroRNA-17-92 Cluster in the Endocrine System.

PubMed

Wan, Shan; Chen, Xiang; He, Yuedong; Yu, Xijie

2018-01-01

MiR-17-92 cluster is coded by MIR17HG in chromosome 13, which is highly conserved in vertebrates. Published literatures have proved that miR-17-92 cluster critically regulates tumorigenesis and metastasis. Recent researches showed that the miR-17-92 cluster also plays novel functions in the endocrine system. To summarize recent findings on the physiological and pathological roles of miR-17-92 cluster in bone, lipid and glucose metabolisms. MiR-17-92 cluster plays significant regulatory roles in bone development and metabolism through regulating the differentiation and function of osteoblasts and osteoclasts. In addition, miR-17- 92 cluster is nearly involved in every aspect of lipid metabolism. Last but not the least, the miR-17-92 cluster is closely bound up with pancreatic beta cell function, development of type 1 diabetes and insulin resistance. However, whether miR-17-92 cluster is involved in the communication among bone, fat and glucose metabolisms remains unknown. Growing evidence indicates that miR-17-92 cluster plays significant roles in bone, lipid and glucose metabolisms through a variety of signaling pathways. Fully understanding its modulating mechanisms may necessarily facilitate to comprehend the clinical and molecule features of some metabolic disorders such as osteoporosis, arthrosclerosis and diabetes mellitus. It may provide new drug targets to prevent and cure these disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Input clustering in the normal and learned circuits of adult barn owls.

PubMed

McBride, Thomas J; DeBello, William M

2015-05-01

Experience-dependent formation of synaptic input clusters can occur in juvenile brains. Whether this also occurs in adults is largely unknown. We previously reconstructed the normal and learned circuits of prism-adapted barn owls and found that changes in clustering of axo-dendritic contacts (putative synapses) predicted functional circuit strength. Here we asked whether comparable changes occurred in normal and prism-removed adults. Across all anatomical zones, no systematic differences in the primary metrics for within-branch or between-branch clustering were observed: 95-99% of contacts resided within clusters (<10-20 μm from nearest neighbor) regardless of circuit strength. Bouton volumes, a proxy measure of synaptic strength, were on average larger in the functionally strong zones, indicating that changes in synaptic efficacy contributed to the differences in circuit strength. Bootstrap analysis showed that the distribution of inter-contact distances strongly deviated from random not in the functionally strong zones but in those that had been strong during the sensitive period (60-250 d), indicating that clusters formed early in life were preserved regardless of current value. While cluster formation in juveniles appeared to require the production of new synapses, cluster formation in adults did not. In total, these results support a model in which high cluster dynamics in juveniles sculpt a potential connectivity map that is refined in adulthood. We propose that preservation of clusters in functionally weak adult circuits provides a storage mechanism for disused but potentially useful pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

A 4-dimethylaminobenzoate-functionalized Ti6-oxo cluster with a narrow band gap and enhanced photoelectrochemical activity: a combined experimental and computational study.

PubMed

Lv, Hai-Ting; Cui, Ying; Zhang, Yu-Min; Li, Hua-Min; Zou, Guo-Dong; Duan, Rui-Huan; Cao, Jun-Tao; Jing, Qiang-Shan; Fan, Yang

2017-09-28

Organic donor-π-bridge-acceptor (D-π-A) dyes with arylamines as an electron donor have been widely used as photosensitizers for dye-sensitized solar cells (DSSCs). However, titanium-oxo clusters (TOCs) functionalized with this kind of D-π-A structured dye-molecule have rarely been explored. In the present study, the 4-dimethylaminobenzoate-functionalized titanium-oxo cluster [Ti 6 (μ 3 -O) 6 (OiPr) 6 (DMABA) 6 ]·2C 6 H 5 CH 3 (DMABA = 4-dimethylaminobenzoate) was synthesized and structurally characterized by single-crystal X-ray diffraction. For comparison, two other Ti 6 -oxo clusters, namely [Ti 6 (μ 3 -O) 6 (OiPr) 6 (AD) 6 ] (AD = 1-adamantanecarboxylate) and [Ti 6 (μ 3 -O) 2 (μ 2 -O)(μ 2 -OiPr) 4 (OiPr) 10 (DMM) 2 ] (DMM = dimethylmalonate), were also studied. The DMABA-functionalized cluster exhibits a remarkably reduced band gap of ∼2.5 eV and much enhanced photocurrent response in comparison with the other two clusters. The electronic structures and electronic transitions of the clusters were studied by DFT and TDDFT calculations. The computational results suggest that the low-energy transitions of the DMABA-functionalized cluster have a substantial charge-transfer character arising from the DMABA → {Ti 6 } cluster core ligand-to-core charge transfer (LCCT), along with the DMABA-based intra-ligand charge transfer (ILCT). These low-energy charge transfer transitions provide efficient electron injection pathways for photon-to-electron conversion.

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayedmore » embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Measuring conservation of sequence features closely linked to function--such as binding-site clustering--makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

User’s guide for GcClust—An R package for clustering of regional geochemical data

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David B.

2016-04-08

GcClust is a software package developed by the U.S. Geological Survey for statistical clustering of regional geochemical data, and similar data such as regional mineralogical data. Functions within the software package are written in the R statistical programming language. These functions, their documentation, and a copy of the user’s guide are bundled together in R’s unit of sharable code, which is called a “package.” The user’s guide includes step-by-step instructions showing how the functions are used to cluster data and to evaluate the clustering results. These functions are demonstrated in this report using test data, which are included in the package.

The implementation of hybrid clustering using fuzzy c-means and divisive algorithm for analyzing DNA human Papillomavirus cause of cervical cancer

NASA Astrophysics Data System (ADS)

Andryani, Diyah Septi; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Clustering aims to classify the different patterns into groups called clusters. In this clustering method, we use n-mers frequency to calculate the distance matrix which is considered more accurate than using the DNA alignment. The clustering results could be used to discover biologically important sub-sections and groups of genes. Many clustering methods have been developed, while hard clustering methods considered less accurate than fuzzy clustering methods, especially if it is used for outliers data. Among fuzzy clustering methods, fuzzy c-means is one the best known for its accuracy and simplicity. Fuzzy c-means clustering uses membership function variable, which refers to how likely the data could be members into a cluster. Fuzzy c-means clustering works using the principle of minimizing the objective function. Parameters of membership function in fuzzy are used as a weighting factor which is also called the fuzzier. In this study we implement hybrid clustering using fuzzy c-means and divisive algorithm which could improve the accuracy of cluster membership compare to traditional partitional approach only. In this study fuzzy c-means is used in the first step to find partition results. Furthermore divisive algorithms will run on the second step to find sub-clusters and dendogram of phylogenetic tree. To find the best number of clusters is determined using the minimum value of Davies Bouldin Index (DBI) of the cluster results. In this research, the results show that the methods introduced in this paper is better than other partitioning methods. Finally, we found 3 clusters with DBI value of 1.126628 at first step of clustering. Moreover, DBI values after implementing the second step of clustering are always producing smaller IDB values compare to the results of using first step clustering only. This condition indicates that the hybrid approach in this study produce better performance of the cluster results, in term its DBI values.

Global survey of star clusters in the Milky Way. VI. Age distribution and cluster formation history

NASA Astrophysics Data System (ADS)

Piskunov, A. E.; Just, A.; Kharchenko, N. V.; Berczik, P.; Scholz, R.-D.; Reffert, S.; Yen, S. X.

2018-06-01

Context. The all-sky Milky Way Star Clusters (MWSC) survey provides uniform and precise ages, along with other relevant parameters, for a wide variety of clusters in the extended solar neighbourhood. Aims: In this study we aim to construct the cluster age distribution, investigate its spatial variations, and discuss constraints on cluster formation scenarios of the Galactic disk during the last 5 Gyrs. Methods: Due to the spatial extent of the MWSC, we have considered spatial variations of the age distribution along galactocentric radius RG, and along Z-axis. For the analysis of the age distribution we used 2242 clusters, which all lie within roughly 2.5 kpc of the Sun. To connect the observed age distribution to the cluster formation history we built an analytical model based on simple assumptions on the cluster initial mass function and on the cluster mass-lifetime relation, fit it to the observations, and determined the parameters of the cluster formation law. Results: Comparison with the literature shows that earlier results strongly underestimated the number of evolved clusters with ages t ≳ 100 Myr. Recent studies based on all-sky catalogues agree better with our data, but still lack the oldest clusters with ages t ≳ 1 Gyr. We do not observe a strong variation in the age distribution along RG, though we find an enhanced fraction of older clusters (t > 1 Gyr) in the inner disk. In contrast, the distribution strongly varies along Z. The high altitude distribution practically does not contain clusters with t < 1 Gyr. With simple assumptions on the cluster formation history, the cluster initial mass function and the cluster lifetime we can reproduce the observations. The cluster formation rate and the cluster lifetime are strongly degenerate, which does not allow us to disentangle different formation scenarios. In all cases the cluster formation rate is strongly declining with time, and the cluster initial mass function is very shallow at the high mass end.

The ergot alkaloid gene cluster: functional analyses and evolutionary aspects.

PubMed

Lorenz, Nicole; Haarmann, Thomas; Pazoutová, Sylvie; Jung, Manfred; Tudzynski, Paul

2009-01-01

Ergot alkaloids and their derivatives have been traditionally used as therapeutic agents in migraine, blood pressure regulation and help in childbirth and abortion. Their production in submerse culture is a long established biotechnological process. Ergot alkaloids are produced mainly by members of the genus Claviceps, with Claviceps purpurea as best investigated species concerning the biochemistry of ergot alkaloid synthesis (EAS). Genes encoding enzymes involved in EAS have been shown to be clustered; functional analyses of EAS cluster genes have allowed to assign specific functions to several gene products. Various Claviceps species differ with respect to their host specificity and their alkaloid content; comparison of the ergot alkaloid clusters in these species (and of clavine alkaloid clusters in other genera) yields interesting insights into the evolution of cluster structure. This review focuses on recently published and also yet unpublished data on the structure and evolution of the EAS gene cluster and on the function and regulation of cluster genes. These analyses have also significant biotechnological implications: the characterization of non-ribosomal peptide synthetases (NRPS) involved in the synthesis of the peptide moiety of ergopeptines opened interesting perspectives for the synthesis of ergot alkaloids; on the other hand, defined mutants could be generated producing interesting intermediates or only single peptide alkaloids (instead of the alkaloid mixtures usually produced by industrial strains).

The Mass Function in h+(chi) Persei

NASA Astrophysics Data System (ADS)

Bragg, Ann; Kenyon, Scott

2000-08-01

Knowledge of the stellar initial mass function (IMF) is critical to understanding star formation and galaxy evolution. Past studies of the IMF in open clusters have primarily used luminosity functions to determine mass functions, frequently in relatively sparse clusters. Our goal with this project is to derive a reliable, well- sampled IMF for a pair of very dense young clusters (h+(chi) Persei) with ages, 1-2 × 10^7 yr (e.g., Vogt A& A 11:359), where stellar evolution theory is robust. We will construct the HR diagram using both photometry and spectral types to derive more accurate stellar masses and ages than are possible using photometry alone. Results from the two clusters will be compared to examine the universality of the IMF. We currently have a spectroscopic sample covering an area within 9 arc-minutes of the center of each cluster taken with the FAST Spectrograph. The sample is complete to V=15.4 and contains ~ 1000 stars. We request 2 nights at WIYN/HYDRA to extend this sample to deeper magnitudes, allowing us to determine the IMF of the clusters to a lower limiting mass and to search for a pre-main sequence, theoretically predicted to be present for clusters of this age. Note that both clusters are contained within a single HYDRA field.

Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI

PubMed Central

Jung, Wi Hoon; Jang, Joon Hwan; Park, Jin Woo; Kim, Euitae; Goo, Eun-Hoe; Im, Oh-Soo; Kwon, Jun Soo

2014-01-01

As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders. PMID:25203441

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

PubMed

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

The NGC 7742 star cluster luminosity function: a population analysis revisited

NASA Astrophysics Data System (ADS)

de Grijs, Richard; Ma, Chao

2018-02-01

We re-examine the properties of the star cluster population in the circumnuclear starburst ring in the face-on spiral galaxy NGC 7742, whose young cluster mass function has been reported to exhibit significant deviations from the canonical power law. We base our reassessment on the clusters’ luminosities (an observational quantity) rather than their masses (a derived quantity), and confirm conclusively that the galaxy’s starburst-ring clusters—and particularly the youngest subsample, {log}(t {{{yr}}}-1)≤ 7.2—show evidence of a turnover in the cluster luminosity function well above the 90% completeness limit adopted to ensure the reliability of our results. This confirmation emphasizes the unique conundrum posed by this unusual cluster population.

Application of TALE-Based Approach for Dissecting Functional MicroRNA-302/367 in Cellular Reprogramming.

PubMed

Zhang, Zhonghui; Wu, Wen-Shu

2018-01-01

MicroRNAs are small 18-24 nt single-stranded noncoding RNA molecules involved in many biological processes, including stemness maintenance and cellular reprogramming. Current methods used in loss-of-function studies of microRNAs have several limitations. Here, we describe a new approach for dissecting miR-302/367 functions by transcription activator-like effectors (TALEs), which are natural effector proteins secreted by Xanthomonas and Ralstonia bacteria. Knockdown of the miR-302/367 cluster uses the Kruppel-associated box repressor domain fused with specific TALEs designed to bind the miR-302/367 cluster promoter. Knockout of the miR-302/367 cluster uses two pairs of TALE nucleases (TALENs) to delete the miR-302/367 cluster in human primary cells. Together, both TALE-based transcriptional repressor and TALENs are two promising approaches for loss-of-function studies of microRNA cluster in human primary cells.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Unsupervised Learning and Pattern Recognition of Biological Data Structures with Density Functional Theory and Machine Learning.

PubMed

Chen, Chien-Chang; Juan, Hung-Hui; Tsai, Meng-Yuan; Lu, Henry Horng-Shing

2018-01-11

By introducing the methods of machine learning into the density functional theory, we made a detour for the construction of the most probable density function, which can be estimated by learning relevant features from the system of interest. Using the properties of universal functional, the vital core of density functional theory, the most probable cluster numbers and the corresponding cluster boundaries in a studying system can be simultaneously and automatically determined and the plausibility is erected on the Hohenberg-Kohn theorems. For the method validation and pragmatic applications, interdisciplinary problems from physical to biological systems were enumerated. The amalgamation of uncharged atomic clusters validated the unsupervised searching process of the cluster numbers and the corresponding cluster boundaries were exhibited likewise. High accurate clustering results of the Fisher's iris dataset showed the feasibility and the flexibility of the proposed scheme. Brain tumor detections from low-dimensional magnetic resonance imaging datasets and segmentations of high-dimensional neural network imageries in the Brainbow system were also used to inspect the method practicality. The experimental results exhibit the successful connection between the physical theory and the machine learning methods and will benefit the clinical diagnoses.

Structure and functional dynamics of the mitochondrial Fe/S cluster synthesis complex.

PubMed

Boniecki, Michal T; Freibert, Sven A; Mühlenhoff, Ulrich; Lill, Roland; Cygler, Miroslaw

2017-11-03

Iron-sulfur (Fe/S) clusters are essential protein cofactors crucial for many cellular functions including DNA maintenance, protein translation, and energy conversion. De novo Fe/S cluster synthesis occurs on the mitochondrial scaffold protein ISCU and requires cysteine desulfurase NFS1, ferredoxin, frataxin, and the small factors ISD11 and ACP (acyl carrier protein). Both the mechanism of Fe/S cluster synthesis and function of ISD11-ACP are poorly understood. Here, we present crystal structures of three different NFS1-ISD11-ACP complexes with and without ISCU, and we use SAXS analyses to define the 3D architecture of the complete mitochondrial Fe/S cluster biosynthetic complex. Our structural and biochemical studies provide mechanistic insights into Fe/S cluster synthesis at the catalytic center defined by the active-site Cys of NFS1 and conserved Cys, Asp, and His residues of ISCU. We assign specific regulatory rather than catalytic roles to ISD11-ACP that link Fe/S cluster synthesis with mitochondrial lipid synthesis and cellular energy status.

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

PubMed

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

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

The cluster model of a hot dense vapor

NASA Astrophysics Data System (ADS)

Zhukhovitskii, D. I.

2015-04-01

We explore thermodynamic properties of a vapor in the range of state parameters where the contribution to thermodynamic functions from bound states of atoms (clusters) dominates over the interaction between the components of the vapor in free states. The clusters are assumed to be light and sufficiently "hot" for the number of bonds to be minimized. We use the technique of calculation of the cluster partition function for the cluster with a minimum number of interatomic bonds to calculate the caloric properties (heat capacity and velocity of sound) for an ideal mixture of the lightest clusters. The problem proves to be exactly solvable and resulting formulas are functions solely of the equilibrium constant of the dimer formation. These formulas ensure a satisfactory correlation with the reference data for the vapors of cesium, mercury, and argon up to moderate densities in both the sub- and supercritical regions. For cesium, we extend the model to the densities close to the critical one by inclusion of the clusters of arbitrary size. Knowledge of the cluster composition of the cesium vapor makes it possible to treat nonequilibrium phenomena such as nucleation of the supersaturated vapor, for which the effect of the cluster structural transition is likely to be significant.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

Density-functional theory study of the geometries, stabilities, and electronic properties of Au n Rb (n = 1-10) clusters: comparison with pure gold clusters

NASA Astrophysics Data System (ADS)

Hu, Yan-Fei; Jiang, Gang; Meng, Da-Qiao

2012-01-01

The density functional method with the relativistic effective core potential has been employed to investigate systematically the geometric structures, relative stabilities, growth-pattern behavior, and electronic properties of small bimetallic Au n Rb (n = 1-10) and pure gold Au n (n ≤ 11) clusters. For the geometric structures of the Au n Rb (n = 1-10) clusters, the dominant growth pattern is for a Rb-substituted Au n +1 cluster or one Au atom capped on a Au n -1Rb cluster, and the turnover point from a two-dimensional to a three-dimensional structure occurs at n = 4. Moreover, the stability of the ground-state structures of these clusters has been examined via an analysis of the average atomic binding energies, fragmentation energies, and the second-order difference of energies as a function of cluster size. The results exhibit a pronounced even-odd alternation phenomenon. The same pronounced even-odd alternations are found for the HOMO-LUMO gap, VIPs, VEAs, and the chemical hardness. In addition, about one electron charge transfers from the Au n host to the Rb atom in each corresponding Au n Rb cluster.

The Magellanic Bridge Cluster NGC 796: Deep Optical AO Imaging Reveals the Stellar Content and Initial Mass Function of a Massive Open Cluster

NASA Astrophysics Data System (ADS)

Kalari, Venu M.; Carraro, Giovanni; Evans, Christopher J.; Rubio, Monica

2018-04-01

NGC 796 is a massive young cluster located 59 kpc from us in the diffuse intergalactic medium of the 1/5–1/10 Z⊙ Magellanic Bridge, allowing us to probe variations in star formation and stellar evolution processes as a function of metallicity in a resolved fashion, and providing a link between resolved studies of nearby solar-metallicity and unresolved distant metal-poor clusters located in high-redshift galaxies. In this paper, we present adaptive optics griHα imaging of NGC 796 (at 0.″5, which is ∼0.14 pc at the cluster distance) along with optical spectroscopy of two bright members to quantify the cluster properties. Our aim is to explore whether star formation and stellar evolution vary as a function of metallicity by comparing the properties of NGC 796 to higher-metallicity clusters. We find an age of {20}-5+12 Myr from isochronal fitting of the cluster main sequence in the color–magnitude diagram. Based on the cluster luminosity function, we derive a top-heavy stellar initial mass function (IMF) with a slope α = 1.99 ± 0.2, hinting at a metallicity and/or environmental dependence of the IMF, which may lead to a top-heavy IMF in the early universe. Study of the Hα emission-line stars reveals that classical Be stars constitute a higher fraction of the total B-type stars when compared with similar clusters at greater metallicity, providing some support to the chemically homogeneous theory of stellar evolution. Overall, NGC 796 has a total estimated mass of 990 ± 200 M⊙, and a core radius of 1.4 ± 0.3 pc, which classifies it as a massive young open cluster, unique in the diffuse interstellar medium of the Magellanic Bridge.

Parcellation of left parietal tool representations by functional connectivity

PubMed Central

Garcea, Frank E.; Z. Mahon, Bradford

2014-01-01

Manipulating a tool according to its function requires the integration of visual, conceptual, and motor information, a process subserved in part by left parietal cortex. How these different types of information are integrated and how their integration is reflected in neural responses in the parietal lobule remains an open question. Here, participants viewed images of tools and animals during functional magnetic resonance imaging (fMRI). K-means clustering over time series data was used to parcellate left parietal cortex into subregions based on functional connectivity to a whole brain network of regions involved in tool processing. One cluster, in the inferior parietal cortex, expressed privileged functional connectivity to the left ventral premotor cortex. A second cluster, in the vicinity of the anterior intraparietal sulcus, expressed privileged functional connectivity with the left medial fusiform gyrus. A third cluster in the superior parietal lobe expressed privileged functional connectivity with dorsal occipital cortex. Control analyses using Monte Carlo style permutation tests demonstrated that the clustering solutions were outside the range of what would be observed based on chance ‘lumpiness’ in random data, or mere anatomical proximity. Finally, hierarchical clustering analyses were used to formally relate the resulting parcellation scheme of left parietal tool representations to previous work that has parcellated the left parietal lobule on purely anatomical grounds. These findings demonstrate significant heterogeneity in the functional organization of manipulable object representations in left parietal cortex, and outline a framework that generates novel predictions about the causes of some forms of upper limb apraxia. PMID:24892224

Structure and Stability of GeAu{sub n}, n = 1-10 clusters: A Density Functional Study

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

Priyanka,; Dharamvir, Keya; Sharma, Hitesh

2011-12-12

The structures of Germanium doped gold clusters GeAu{sub n} (n = 1-10) have been investigated using ab initio calculations based on density functional theory (DFT). We have obtained ground state geometries of GeAu{sub n} clusters and have it compared with Silicon doped gold clusters and pure gold clusters. The ground state geometries of the GeAu{sub n} clusters show patterns similar to silicon doped gold clusters except for n = 5, 6 and 9. The introduction of germanium atom increases the binding energy of gold clusters. The binding energy per atom of germanium doped cluster is smaller than the corresponding siliconmore » doped gold cluster. The HUMO-LOMO gap for Au{sub n}Ge clusters have been found to vary between 0.46 eV-2.09 eV. The mullikan charge analysis indicates that charge of order of 0.1e always transfers from germanium atom to gold atom.« less

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

Functional clustering of time series gene expression data by Granger causality

PubMed Central

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Integral field spectroscopy with GEMINI: Extragalactic star cluster in NGC1275

NASA Astrophysics Data System (ADS)

Trancho, Gelys; Miller, Bryan; García-Lorenzo, Begoña; Sánchez, Sebastián F.

2006-01-01

Studies of globular cluster systems play a critical role in our understanding of galaxy formation. Imaging with the Hubble Space Telescope has revealed that young star clusters are formed copiously in galaxy mergers, strengthening theories in which giant elliptical galaxies are formed by the merger of spirals [e.g. Whitmore, B.C., Schweizer, F., Leitherer, C., Borne, K., Robert, C., 1993. Astronomical Journal. 106, 1354; Miller, B.W., Whitmore, B.C., Schweizer, F., Fall, S.M., 1997. Astronomical Journal. 114, 2381; Zepf, S.E., Ashman, K.M., English, J., Freeman, K.C., Sharples, R.M., 1999. Astronomical Journal. 118, 752; Ashman, K.M., Zepf, S.E., 1992. Astrophysical Journal. 384, 50]. However, the formation and evolution of globular cluster systems is still not well understood. Ages and metallicities of the clusters are uncertain either because of degeneracy in the broad-band colors or due to variable reddening. Also, the luminosity function of the young clusters, which depends critically on the metallicities and ages of the clusters, appears to be single power-laws while the luminosity function of old clusters has a well-defined break. Either there is significant dynamical evolution of the cluster systems or metallicity affects the mass function of forming clusters. Spectroscopy of these clusters are needed to improve the metallicity and age measurements and to study the kinematics of young cluster systems. Therefore, we have obtained GMOS IFU data of 4 clusters in NGC1275. We will present preliminary results like metallicities, ages, and velocities of the star clusters from IFU spectroscopy.

Comprehensive identification and clustering of CLV3/ESR-related (CLE) genes in plants finds groups with potentially shared function.

PubMed

Goad, David M; Zhu, Chuanmei; Kellogg, Elizabeth A

2017-10-01

CLV3/ESR (CLE) proteins are important signaling peptides in plants. The short CLE peptide (12-13 amino acids) is cleaved from a larger pre-propeptide and functions as an extracellular ligand. The CLE family is large and has resisted attempts at classification because the CLE domain is too short for reliable phylogenetic analysis and the pre-propeptide is too variable. We used a model-based search for CLE domains from 57 plant genomes and used the entire pre-propeptide for comprehensive clustering analysis. In total, 1628 CLE genes were identified in land plants, with none recognizable from green algae. These CLEs form 12 groups within which CLE domains are largely conserved and pre-propeptides can be aligned. Most clusters contain sequences from monocots, eudicots and Amborella trichopoda, with sequences from Picea abies, Selaginella moellendorffii and Physcomitrella patens scattered in some clusters. We easily identified previously known clusters involved in vascular differentiation and nodulation. In addition, we found a number of discrete groups whose function remains poorly characterized. Available data indicate that CLE proteins within a cluster are likely to share function, whereas those from different clusters play at least partially different roles. Our analysis provides a foundation for future evolutionary and functional studies. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Tardigrade workbench: comparing stress-related proteins, sequence-similar and functional protein clusters as well as RNA elements in tardigrades

PubMed Central

2009-01-01

Background Tardigrades represent an animal phylum with extraordinary resistance to environmental stress. Results To gain insights into their stress-specific adaptation potential, major clusters of related and similar proteins are identified, as well as specific functional clusters delineated comparing all tardigrades and individual species (Milnesium tardigradum, Hypsibius dujardini, Echiniscus testudo, Tulinus stephaniae, Richtersius coronifer) and functional elements in tardigrade mRNAs are analysed. We find that 39.3% of the total sequences clustered in 58 clusters of more than 20 proteins. Among these are ten tardigrade specific as well as a number of stress-specific protein clusters. Tardigrade-specific functional adaptations include strong protein, DNA- and redox protection, maintenance and protein recycling. Specific regulatory elements regulate tardigrade mRNA stability such as lox P DICE elements whereas 14 other RNA elements of higher eukaryotes are not found. Further features of tardigrade specific adaption are rapidly identified by sequence and/or pattern search on the web-tool tardigrade analyzer http://waterbear.bioapps.biozentrum.uni-wuerzburg.de. The work-bench offers nucleotide pattern analysis for promotor and regulatory element detection (tardigrade specific; nrdb) as well as rapid COG search for function assignments including species-specific repositories of all analysed data. Conclusion Different protein clusters and regulatory elements implicated in tardigrade stress adaptations are analysed including unpublished tardigrade sequences. PMID:19821996

Tardigrade workbench: comparing stress-related proteins, sequence-similar and functional protein clusters as well as RNA elements in tardigrades.

PubMed

Förster, Frank; Liang, Chunguang; Shkumatov, Alexander; Beisser, Daniela; Engelmann, Julia C; Schnölzer, Martina; Frohme, Marcus; Müller, Tobias; Schill, Ralph O; Dandekar, Thomas

2009-10-12

Tardigrades represent an animal phylum with extraordinary resistance to environmental stress. To gain insights into their stress-specific adaptation potential, major clusters of related and similar proteins are identified, as well as specific functional clusters delineated comparing all tardigrades and individual species (Milnesium tardigradum, Hypsibius dujardini, Echiniscus testudo, Tulinus stephaniae, Richtersius coronifer) and functional elements in tardigrade mRNAs are analysed. We find that 39.3% of the total sequences clustered in 58 clusters of more than 20 proteins. Among these are ten tardigrade specific as well as a number of stress-specific protein clusters. Tardigrade-specific functional adaptations include strong protein, DNA- and redox protection, maintenance and protein recycling. Specific regulatory elements regulate tardigrade mRNA stability such as lox P DICE elements whereas 14 other RNA elements of higher eukaryotes are not found. Further features of tardigrade specific adaption are rapidly identified by sequence and/or pattern search on the web-tool tardigrade analyzer http://waterbear.bioapps.biozentrum.uni-wuerzburg.de. The work-bench offers nucleotide pattern analysis for promotor and regulatory element detection (tardigrade specific; nrdb) as well as rapid COG search for function assignments including species-specific repositories of all analysed data. Different protein clusters and regulatory elements implicated in tardigrade stress adaptations are analysed including unpublished tardigrade sequences.

Diverse specificity and effector function among human antibodies to HIV-1 envelope glycoprotein epitopes exposed by CD4 binding

DOE PAGES

Guan, Yongjun; Pazgier, Marzena; Sajadi, Mohammad M.; ...

2012-12-13

The HIV-1 envelope glycoprotein (Env) undergoes conformational transitions consequent to CD4 binding and coreceptor engagement during viral entry. The physical steps in this process are becoming defined, but less is known about their significance as targets of antibodies potentially protective against HIV-1 infection. Here we probe the functional significance of transitional epitope exposure by characterizing 41 human mAbs specific for epitopes exposed on trimeric Env after CD4 engagement. These mAbs recognize three epitope clusters: cluster A, the gp120 face occluded by gp41 in trimeric Env; cluster B, a region proximal to the coreceptor-binding site (CoRBS) and involving the V1/V2 domain;more » and cluster C, the coreceptor-binding site. The mAbs were evaluated functionally by antibody-dependent, cell-mediated cytotoxicity (ADCC) and for neutralization of Tiers 1 and 2 pseudoviruses. All three clusters included mAbs mediating ADCC. However, there was a strong potency bias for cluster A, which harbors at least three potent ADCC epitopes whose cognate mAbs have electropositive paratopes. Cluster A epitopes are functional ADCC targets during viral entry in an assay format using virion-sensitized target cells. In contrast, only cluster C contained epitopes that were recognized by neutralizing mAbs. There was significant diversity in breadth and potency that correlated with epitope fine specificity. In contrast, ADCC potency had no relationship with neutralization potency or breadth for any epitope cluster. In conclusion, Fc-mediated effector function and neutralization coselect with specificity in anti-Env antibody responses, but the nature of selection is distinct for these two antiviral activities.« less

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

Background The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. Results We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene,more » and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Conclusions Measuring conservation of sequence features closely linked to function - such as binding-site clustering - makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

The gamma-ray pulsar population of globular clusters: implications for the GeV excess

NASA Astrophysics Data System (ADS)

Hooper, Dan; Linden, Tim

2016-08-01

It has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecond pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.

The gamma-ray pulsar population of globular clusters: implications for the GeV excess

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

Hooper, Dan; Linden, Tim, E-mail: dhooper@fnal.gov, E-mail: linden.70@osu.edu

It has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecond pulsars in themore » Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

The gamma-ray pulsar population of globular clusters: Implications for the GeV excess

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

Hooper, Dan; Linden, Tim

In this study, it has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecondmore » pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

The gamma-ray pulsar population of globular clusters: Implications for the GeV excess

DOE PAGES

Hooper, Dan; Linden, Tim

2016-08-09

In this study, it has been suggested that the GeV excess, observed from the region surrounding the Galactic Center, might originate from a population of millisecond pulsars that formed in globular clusters. With this in mind, we employ the publicly available Fermi data to study the gamma-ray emission from 157 globular clusters, identifying a statistically significant signal from 25 of these sources (ten of which are not found in existing gamma-ray catalogs). We combine these observations with the predicted pulsar formation rate based on the stellar encounter rate of each globular cluster to constrain the gamma-ray luminosity function of millisecondmore » pulsars in the Milky Way's globular cluster system. We find that this pulsar population exhibits a luminosity function that is quite similar to those millisecond pulsars observed in the field of the Milky Way (i.e. the thick disk). After pulsars are expelled from a globular cluster, however, they continue to lose rotational kinetic energy and become less luminous, causing their luminosity function to depart from the steady-state distribution. Using this luminosity function and a model for the globular cluster disruption rate, we show that millisecond pulsars born in globular clusters can account for only a few percent or less of the observed GeV excess. Among other challenges, scenarios in which the entire GeV excess is generated from such pulsars are in conflict with the observed mass of the Milky Way's Central Stellar Cluster.« less

The Correlation Function of Galaxy Clusters and Detection of Baryon Acoustic Oscillations

NASA Astrophysics Data System (ADS)

Hong, T.; Han, J. L.; Wen, Z. L.; Sun, L.; Zhan, H.

2012-04-01

We calculate the correlation function of 13,904 galaxy clusters of z <= 0.4 selected from the cluster catalog of Wen et al. The correlation function can be fitted with a power-law model ξ(r) = (r/R 0)-γ on the scales of 10 h -1 Mpc <= r <= 50 h -1 Mpc, with a larger correlation length of R 0 = 18.84 ± 0.27 h -1 Mpc for clusters with a richness of R >= 15 and a smaller length of R 0 = 16.15 ± 0.13 h -1 Mpc for clusters with a richness of R >= 5. The power-law index of γ = 2.1 is found to be almost the same for all cluster subsamples. A pronounced baryon acoustic oscillations (BAO) peak is detected at r ~ 110 h -1 Mpc with a significance of ~1.9σ. By analyzing the correlation function in the range of 20 h -1 Mpc <= r <= 200 h -1 Mpc, we find that the constraints on distance parameters are Dv (zm = 0.276) = 1077 ± 55(1σ) Mpc and h = 0.73 ± 0.039(1σ), which are consistent with the cosmology derived from Wilkinson Microwave Anisotropy Probe (WMAP) seven-year data. However, the BAO signal from the cluster sample is stronger than expected and leads to a rather low matter density Ω m h 2 = 0.093 ± 0.0077(1σ), which deviates from the WMAP7 result by more than 3σ. The correlation function of the GMBCG cluster sample is also calculated and our detection of the BAO feature is confirmed.

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

PubMed

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

2005-01-01

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

Cool Core Bias in Sunyaev-Zel’dovich Galaxy Cluster Surveys

DOE PAGES

Lin, Henry W.; McDonald, Michael; Benson, Bradford; ...

2015-03-18

Sunyaev-Zeldovich (SZ) surveys find massive clusters of galaxies by measuring the inverse Compton scattering of cosmic microwave background off of intra-cluster gas. The cluster selection function from such surveys is expected to be nearly independent of redshift and cluster astrophysics. In this work, we estimate the effect on the observed SZ signal of centrally-peaked gas density profiles (cool cores) and radio emission from the brightest cluster galaxy (BCG) by creating mock observations of a sample of clusters that span the observed range of classical cooling rates and radio luminosities. For each cluster, we make simulated SZ observations by the Southmore » Pole Telescope and characterize the cluster selection function, but note that our results are broadly applicable to other SZ surveys. We find that the inclusion of a cool core can cause a change in the measured SPT significance of a cluster between 0.01%–10% at z > 0.3, increasing with cuspiness of the cool core and angular size on the sky of the cluster (i.e., decreasing redshift, increasing mass). We provide quantitative estimates of the bias in the SZ signal as a function of a gas density cuspiness parameter, redshift, mass, and the 1.4 GHz radio luminosity of the central AGN. Based on this work, we estimate that, for the Phoenix cluster (one of the strongest cool cores known), the presence of a cool core is biasing the SZ significance high by ~6%. The ubiquity of radio galaxies at the centers of cool core clusters will offset the cool core bias to varying degrees« less

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

Scalable properties of metal clusters: A comparative study of modern exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Koitz, Ralph; Soini, Thomas M.; Genest, Alexander; Trickey, S. B.; Rösch, Notker

2012-07-01

The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pdn with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Aun (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Cluster-cluster aggregation with particle replication and chemotaxy: a simple model for the growth of animal cells in culture

NASA Astrophysics Data System (ADS)

Alves, S. G.; Martins, M. L.

2010-09-01

Aggregation of animal cells in culture comprises a series of motility, collision and adhesion processes of basic relevance for tissue engineering, bioseparations, oncology research and in vitro drug testing. In the present paper, a cluster-cluster aggregation model with stochastic particle replication and chemotactically driven motility is investigated as a model for the growth of animal cells in culture. The focus is on the scaling laws governing the aggregation kinetics. Our simulations reveal that in the absence of chemotaxy the mean cluster size and the total number of clusters scale in time as stretched exponentials dependent on the particle replication rate. Also, the dynamical cluster size distribution functions are represented by a scaling relation in which the scaling function involves a stretched exponential of the time. The introduction of chemoattraction among the particles leads to distribution functions decaying as power laws with exponents that decrease in time. The fractal dimensions and size distributions of the simulated clusters are qualitatively discussed in terms of those determined experimentally for several normal and tumoral cell lines growing in culture. It is shown that particle replication and chemotaxy account for the simplest cluster size distributions of cellular aggregates observed in culture.

The cluster model of a hot dense vapor

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

Zhukhovitskii, D. I., E-mail: dmr@ihed.ras.ru

2015-04-28

We explore thermodynamic properties of a vapor in the range of state parameters where the contribution to thermodynamic functions from bound states of atoms (clusters) dominates over the interaction between the components of the vapor in free states. The clusters are assumed to be light and sufficiently “hot” for the number of bonds to be minimized. We use the technique of calculation of the cluster partition function for the cluster with a minimum number of interatomic bonds to calculate the caloric properties (heat capacity and velocity of sound) for an ideal mixture of the lightest clusters. The problem proves tomore » be exactly solvable and resulting formulas are functions solely of the equilibrium constant of the dimer formation. These formulas ensure a satisfactory correlation with the reference data for the vapors of cesium, mercury, and argon up to moderate densities in both the sub- and supercritical regions. For cesium, we extend the model to the densities close to the critical one by inclusion of the clusters of arbitrary size. Knowledge of the cluster composition of the cesium vapor makes it possible to treat nonequilibrium phenomena such as nucleation of the supersaturated vapor, for which the effect of the cluster structural transition is likely to be significant.« less

Recent advances in the Suf Fe-S cluster biogenesis pathway: Beyond the Proteobacteria.

PubMed

Outten, F Wayne

2015-06-01

Fe-S clusters play critical roles in cellular function throughout all three kingdoms of life. Consequently, Fe-S cluster biogenesis systems are present in most organisms. The Suf (sulfur formation) system is the most ancient of the three characterized Fe-S cluster biogenesis pathways, which also include the Isc and Nif systems. Much of the first work on the Suf system took place in Gram-negative Proteobacteria used as model organisms. These early studies led to a wealth of biochemical, genetic, and physiological information on Suf function. From those studies we have learned that SufB functions as an Fe-S scaffold in conjunction with SufC (and in some cases SufD). SufS and SufE together mobilize sulfur for cluster assembly and SufA traffics the complete Fe-S cluster from SufB to target apo-proteins. However, recent progress on the Suf system in other organisms has opened up new avenues of research and new hypotheses about Suf function. This review focuses primarily on the most recent discoveries about the Suf pathway and where those new models may lead the field. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases. Copyright © 2014 Elsevier B.V. All rights reserved.

Clustering of galaxies with f(R) gravity

NASA Astrophysics Data System (ADS)

Capozziello, Salvatore; Faizal, Mir; Hameeda, Mir; Pourhassan, Behnam; Salzano, Vincenzo; Upadhyay, Sudhaker

2018-02-01

Based on thermodynamics, we discuss the galactic clustering of expanding Universe by assuming the gravitational interaction through the modified Newton's potential given by f(R) gravity. We compute the corrected N-particle partition function analytically. The corrected partition function leads to more exact equations of state of the system. By assuming that the system follows quasi-equilibrium, we derive the exact distribution function that exhibits the f(R) correction. Moreover, we evaluate the critical temperature and discuss the stability of the system. We observe the effects of correction of f(R) gravity on the power-law behaviour of particle-particle correlation function also. In order to check the feasibility of an f(R) gravity approach to the clustering of galaxies, we compare our results with an observational galaxy cluster catalogue.

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

NASA Astrophysics Data System (ADS)

Matsuno, H.; Itagaki, N.

2017-12-01

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

Multi-scale clustering of functional data with application to hydraulic gradients in wetlands

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Sharp, Julia L.; Peck, Rory G.; Rosenberry, Donald O.

2011-01-01

A new set of methods are developed to perform cluster analysis of functions, motivated by a data set consisting of hydraulic gradients at several locations distributed across a wetland complex. The methods build on previous work on clustering of functions, such as Tarpey and Kinateder (2003) and Hitchcock et al. (2007), but explore functions generated from an additive model decomposition (Wood, 2006) of the original time se- ries. Our decomposition targets two aspects of the series, using an adaptive smoother for the trend and circular spline for the diurnal variation in the series. Different measures for comparing locations are discussed, including a method for efficiently clustering time series that are of different lengths using a functional data approach. The complicated nature of these wetlands are highlighted by the shifting group memberships depending on which scale of variation and year of the study are considered.

Theoretical Analysis of Optical Absorption and Emission in Mixed Noble Metal Nanoclusters.

PubMed

Day, Paul N; Pachter, Ruth; Nguyen, Kiet A

2018-04-26

In this work, we studied theoretically two hybrid gold-silver clusters, which were reported to have dual-band emission, using density functional theory (DFT) and linear and quadratic response time-dependent DFT (TDDFT). Hybrid functionals were found to successfully predict absorption and emission, although explanation of the NIR emission from the larger cluster (cluster 1) requires significant vibrational excitation in the final state. For the smaller cluster (cluster 2), the Δ H(0-0) value calculated for the T1 → S0 transition, using the PBE0 functional, is in good agreement with the measured NIR emission, and the calculated T2 → S0 value is in fair agreement with the measured visible emission. The calculated T1 → S0 phosphorescence Δ H(0-0) for cluster 1 is close to the measured visible emission energy. In order for the calculated phosphorescence for cluster 1 to agree with the intense NIR emission reported experimentally, the vibrational energy of the final state (S0) is required to be about 0.7 eV greater than the zero-point vibrational energy.

Theoretical study on the spectroscopic properties of CO3(*-).nH2O clusters: extrapolation to bulk.

PubMed

Pathak, Arup K; Mukherjee, Tulsi; Maity, Dilip K

2008-10-24

Vertical detachment energies (VDE) and UV/Vis absorption spectra of hydrated carbonate radical anion clusters, CO(3)(*-).nH(2)O (n=1-8), are determined by means of ab initio electronic structure theory. The VDE values of the hydrated clusters are calculated with second-order Moller-Plesset perturbation (MP2) and coupled cluster theory using the 6-311++G(d,p) set of basis functions. The bulk VDE value of an aqueous carbonate radical anion solution is predicted to be 10.6 eV from the calculated weighted average VDE values of the CO(3)(*-).nH(2)O clusters. UV/Vis absorption spectra of the hydrated clusters are calculated by means of time-dependent density functional theory using the Becke three-parameter nonlocal exchange and the Lee-Yang-Parr nonlocal correlation functional (B3LYP). The simulated UV/Vis spectrum of the CO(3)(*-).8H(2)O cluster is in excellent agreement with the reported experimental spectrum for CO(3)(*-) (aq), obtained based on pulse radiolysis experiments.

Structural, electronic, vibrational and optical properties of Bin clusters

NASA Astrophysics Data System (ADS)

Liang, Dan; Shen, Wanting; Zhang, Chunfang; Lu, Pengfei; Wang, Shumin

2017-10-01

The neutral, anionic and cationic bismuth clusters with the size n up to 14 are investigated by using B3LYP functional within the regime of density functional theory and the LAN2DZ basis set. By analysis of the geometries of the Bin (n = 2-14) clusters, where cationic and anionic bismuth clusters are largely similar to those of neutral ones, a periodic effect by adding units with one to four atoms into smaller cluster to form larger cluster is drawn for the stable structures of bismuth clusters. An even-odd alteration is shown for the properties of the clusters, such as the calculated binding energies and dissociation energies, as well as frontier orbital energies, electron affinities, ionization energies. All the properties indicate that the Bi4 cluster is the most possible existence in bismuth-containing materials, which supports the most recent experiment. The orbital compositions, infrared and Raman activities and the ultraviolet absorption of the most possible tetramer bismuth cluster are given in detail to reveal the periodic tendency of adding bismuth atoms and the stability of tetramer bismuth cluster.

Resolving the problem of galaxy clustering on small scales: any new physics needed?

NASA Astrophysics Data System (ADS)

Kang, X.

2014-02-01

Galaxy clustering sets strong constraints on the physics governing galaxy formation and evolution. However, most current models fail to reproduce the clustering of low-mass galaxies on small scales (r < 1 Mpc h-1). In this paper, we study the galaxy clusterings predicted from a few semi-analytical models. We first compare two Munich versions, Guo et al. and De Lucia & Blaizot. The Guo11 model well reproduces the galaxy stellar mass function, but overpredicts the clustering of low-mass galaxies on small scales. The DLB07 model provides a better fit to the clustering on small scales, but overpredicts the stellar mass function. These seem to be puzzling. The clustering on small scales is dominated by galaxies in the same dark matter halo, and there is slightly more fraction of satellite galaxies residing in massive haloes in the Guo11 model, which is the dominant contribution to the clustering discrepancy between the two models. However, both models still overpredict the clustering at 0.1 < r < 10 Mpc h-1 for low-mass galaxies. This is because both models overpredict the number of satellites by 30 per cent in massive haloes than the data. We show that the Guo11 model could be slightly modified to simultaneously fit the stellar mass function and clusterings, but that cannot be easily achieved in the DLB07 model. The better agreement of DLB07 model with the data actually comes as a coincidence as it predicts too many low-mass central galaxies which are less clustered and thus brings down the total clustering. Finally, we show the predictions from the semi-analytical models of Kang et al. We find that this model can simultaneously fit the stellar mass function and galaxy clustering if the supernova feedback in satellite galaxies is stronger. We conclude that semi-analytical models are now able to solve the small-scales clustering problem, without invoking of any other new physics or changing the dark matter properties, such as the recent favoured warm dark matter.

Effective scheme for partitioning covalent bonds in density-functional embedding theory: From molecules to extended covalent systems.

PubMed

Huang, Chen; Muñoz-García, Ana Belén; Pavone, Michele

2016-12-28

Density-functional embedding theory provides a general way to perform multi-physics quantum mechanics simulations of large-scale materials by dividing the total system's electron density into a cluster's density and its environment's density. It is then possible to compute the accurate local electronic structures and energetics of the embedded cluster with high-level methods, meanwhile retaining a low-level description of the environment. The prerequisite step in the density-functional embedding theory is the cluster definition. In covalent systems, cutting across the covalent bonds that connect the cluster and its environment leads to dangling bonds (unpaired electrons). These represent a major obstacle for the application of density-functional embedding theory to study extended covalent systems. In this work, we developed a simple scheme to define the cluster in covalent systems. Instead of cutting covalent bonds, we directly split the boundary atoms for maintaining the valency of the cluster. With this new covalent embedding scheme, we compute the dehydrogenation energies of several different molecules, as well as the binding energy of a cobalt atom on graphene. Well localized cluster densities are observed, which can facilitate the use of localized basis sets in high-level calculations. The results are found to converge faster with the embedding method than the other multi-physics approach ONIOM. This work paves the way to perform the density-functional embedding simulations of heterogeneous systems in which different types of chemical bonds are present.

Equilibrium Structures and Absorption Spectra for SixOy-nH2O Molecular Clusters using Density Functional Theory

DTIC Science & Technology

2017-05-04

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6390--17-9723 Equilibrium Structures and Absorption Spectra for SixOy-nH2O Molecular...Absorption Spectra for SixOy-nH2O Molecular Clusters using Density Functional Theory L. Huang, S.G. Lambrakos, and L. Massa1 Naval Research Laboratory, Code...and time-dependent density functional theory (TD-DFT). The size of the clusters considered is relatively large compared to those considered in

Cluster-modified function projective synchronisation of complex networks with asymmetric coupling

NASA Astrophysics Data System (ADS)

Wang, Shuguo

2018-02-01

This paper investigates the cluster-modified function projective synchronisation (CMFPS) of a generalised linearly coupled network with asymmetric coupling and nonidentical dynamical nodes. A novel synchronisation scheme is proposed to achieve CMFPS in community networks. We use adaptive control method to derive CMFPS criteria based on Lyapunov stability theory. Each cluster of networks is synchronised with target system by state transformation with scaling function matrix. Numerical simulation results are presented finally to illustrate the effectiveness of this method.

Distant Massive Clusters and Cosmology

NASA Technical Reports Server (NTRS)

Donahue, Megan

1999-01-01

We present a status report of our X-ray study and analysis of a complete sample of distant (z=0.5-0.8), X-ray luminous clusters of galaxies. We have obtained ASCA and ROSAT observations of the five brightest Extended Medium Sensitivity (EMSS) clusters with z > 0.5. We have constructed an observed temperature function for these clusters, and measured iron abundances for all of these clusters. We have developed an analytic expression for the behavior of the mass-temperature relation in a low-density universe. We use this mass-temperature relation together with a Press-Schechter-based model to derive the expected temperature function for different values of Omega-M. We combine this analysis with the observed temperature functions at redshifts from 0 - 0.8 to derive maximum likelihood estimates for the value of Omega-M. We report preliminary results of this analysis.

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

PubMed

Zhang; Fall

1999-12-20

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

Effect of nanoscale size and medium on metal work function in oleylamine-capped gold nanocrystals

NASA Astrophysics Data System (ADS)

Abdellatif, M. H.; Ghosh, S.; Liakos, I.; Scarpellini, A.; Marras, S.; Diaspro, A.; Salerno, M.

2016-02-01

The work function is an important material property with several applications in photonics and optoelectronics. We aimed to characterize the work function of clusters resulting from gold nanocrystals capped with oleylamine surfactant and drop-casted onto gold substrate. We used scanning Kelvin probe microscopy to investigate the work function, and complemented our study mainly with X-ray diffraction and X-ray photoelectron spectroscopy. The oleylamine works as an electron blocking layer through which the electrical conduction takes place by tunneling effect. The surface potential appears to depend on the size of the clusters, which can be ascribed to their difference in effective work function with the substrate. The charge state of gold clusters is discussed in comparison with theory, and their capacitance is calculated from a semi-analytical equation. The results suggest that at the nanoscale the work function is not an intrinsic property of a material but rather depends on the size and morphology of the clusters, including also effects of the surrounding materials.

Critical Analysis of Cluster Models and Exchange-Correlation Functionals for Calculating Magnetic Shielding in Molecular Solids.

PubMed

Holmes, Sean T; Iuliucci, Robbie J; Mueller, Karl T; Dybowski, Cecil

2015-11-10

Calculations of the principal components of magnetic-shielding tensors in crystalline solids require the inclusion of the effects of lattice structure on the local electronic environment to obtain significant agreement with experimental NMR measurements. We assess periodic (GIPAW) and GIAO/symmetry-adapted cluster (SAC) models for computing magnetic-shielding tensors by calculations on a test set containing 72 insulating molecular solids, with a total of 393 principal components of chemical-shift tensors from 13C, 15N, 19F, and 31P sites. When clusters are carefully designed to represent the local solid-state environment and when periodic calculations include sufficient variability, both methods predict magnetic-shielding tensors that agree well with experimental chemical-shift values, demonstrating the correspondence of the two computational techniques. At the basis-set limit, we find that the small differences in the computed values have no statistical significance for three of the four nuclides considered. Subsequently, we explore the effects of additional DFT methods available only with the GIAO/cluster approach, particularly the use of hybrid-GGA functionals, meta-GGA functionals, and hybrid meta-GGA functionals that demonstrate improved agreement in calculations on symmetry-adapted clusters. We demonstrate that meta-GGA functionals improve computed NMR parameters over those obtained by GGA functionals in all cases, and that hybrid functionals improve computed results over the respective pure DFT functional for all nuclides except 15N.

The Low End of the Initial Mass Function in Young Clusters. II. Evidence for Primordial Mass Segregation in NGC 330 in the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sirianni, Marco; Nota, Antonella; De Marchi, Guido; Leitherer, Claus; Clampin, Mark

2002-11-01

As part of a larger program aimed at investigating the universality of the initial mass function (IMF) at low masses in a number of young clusters in the LMC and SMC, we present a new study of the low end of the stellar IMF of NGC 330, the richest young star cluster in the SMC, from deep broadband V and I images obtained with HST/WFPC2. We detect stars down to a limiting magnitude of m555=24.9, which corresponds to stellar masses of ~0.8Msolar at the distance of the SMC. A comparison of the cluster color-magnitude diagram with theoretical evolutionary tracks indicates an age of ~30 Myr for NGC 330, in agreement with previous published results. We derive the cluster luminosity function, which we correct for background contamination using an adjacent SMC field, and construct the mass function in the 1-7Msolar mass range. Given the young cluster age, the MF can well approximate the IMF. We find that the IMF in the central cluster regions (within 30") is well reproduced by a power law with a slope consistent with Salpeter's. In addition, the richness of the cluster allows us to investigate the IMF as a function of radial distance from the center. We find that the IMF becomes steeper at increasing distances from the cluster center (between 30" and 90"), with the number of massive stars (>5Msolar) decreasing from the core to the outskirts of the cluster 5 times more rapidly than the less-massive objects (~=1Msolar). We believe the observed mass segregation to be of a primordial nature rather than dynamical since the age of NGC 330 is 10 times shorter than the expected relaxation time of the cluster. Based on observations with the NASA/ESA Hubble Space Telescope obtained at the Space Telescope Science Institute, which is operated by AURA for NASA under contract NAS5-26555.

Recent advances in the Suf Fe-S cluster biogenesis pathway: Beyond the Proteobacteria

PubMed Central

Outten, F. Wayne

2014-01-01

Fe-S clusters play critical roles in cellular function throughout all three kingdoms of life. Consequently, Fe-S cluster biogenesis systems are present in most organisms. The Suf (sulfur formation) system is the most ancient of the three characterized Fe-S cluster biogenesis pathways, which also include the Isc and Nif systems. Much of the first work on the Suf system took place in Gram-negative Proteobacteria used as model organisms. These early studies led to a wealth of biochemical, genetic, and physiological information on Suf function. From those studies we have learned that SufB functions as an Fe-S scaffold in conjunction with SufC (and in some cases SufD). SufS and SufE together mobilize sulfur for cluster assembly and SufA traffics the complete Fe-S cluster from SufB to target apo-proteins. However, recent progress on the Suf system in other organisms has opened up new avenues of research and new hypotheses about Suf function. This review focuses primarily on the most recent discoveries about the Suf pathway and where those new models may lead the field. PMID:25447545

Bacillus cereus-type polyhydroxyalkanoate biosynthetic gene cluster contains R-specific enoyl-CoA hydratase gene.

PubMed

Kihara, Takahiro; Hiroe, Ayaka; Ishii-Hyakutake, Manami; Mizuno, Kouhei; Tsuge, Takeharu

2017-08-01

Bacillus cereus and Bacillus megaterium both accumulate polyhydroxyalkanoate (PHA) but their PHA biosynthetic gene (pha) clusters that code for proteins involved in PHA biosynthesis are different. Namely, a gene encoding MaoC-like protein exists in the B. cereus-type pha cluster but not in the B. megaterium-type pha cluster. MaoC-like protein has an R-specific enoyl-CoA hydratase (R-hydratase) activity and is referred to as PhaJ when involved in PHA metabolism. In this study, the pha cluster of B. cereus YB-4 was characterized in terms of PhaJ's function. In an in vitro assay, PhaJ from B. cereus YB-4 (PhaJ YB4 ) exhibited hydration activity toward crotonyl-CoA. In an in vivo assay using Escherichia coli as a host for PHA accumulation, the recombinant strain expressing PhaJ YB4 and PHA synthase led to increased PHA accumulation, suggesting that PhaJ YB4 functioned as a monomer supplier. The monomer composition of the accumulated PHA reflected the substrate specificity of PhaJ YB4 , which appeared to prefer short chain-length substrates. The pha cluster from B. cereus YB-4 functioned to accumulate PHA in E. coli; however, it did not function when the phaJ YB4 gene was deleted. The B. cereus-type pha cluster represents a new example of a pha cluster that contains the gene encoding PhaJ.

The relationship between sleep-wake cycle and cognitive functioning in young people with affective disorders.

PubMed

Carpenter, Joanne S; Robillard, Rébecca; Lee, Rico S C; Hermens, Daniel F; Naismith, Sharon L; White, Django; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B

2015-01-01

Although early-stage affective disorders are associated with both cognitive dysfunction and sleep-wake disruptions, relationships between these factors have not been specifically examined in young adults. Sleep and circadian rhythm disturbances in those with affective disorders are considerably heterogeneous, and may not relate to cognitive dysfunction in a simple linear fashion. This study aimed to characterise profiles of sleep and circadian disturbance in young people with affective disorders and examine associations between these profiles and cognitive performance. Actigraphy monitoring was completed in 152 young people (16-30 years; 66% female) with primary diagnoses of affective disorders, and 69 healthy controls (18-30 years; 57% female). Patients also underwent detailed neuropsychological assessment. Actigraphy data were processed to estimate both sleep and circadian parameters. Overall neuropsychological performance in patients was poor on tasks relating to mental flexibility and visual memory. Two hierarchical cluster analyses identified three distinct patient groups based on sleep variables and three based on circadian variables. Sleep clusters included a 'long sleep' cluster, a 'disrupted sleep' cluster, and a 'delayed and disrupted sleep' cluster. Circadian clusters included a 'strong circadian' cluster, a 'weak circadian' cluster, and a 'delayed circadian' cluster. Medication use differed between clusters. The 'long sleep' cluster displayed significantly worse visual memory performance compared to the 'disrupted sleep' cluster. No other cognitive functions differed between clusters. These results highlight the heterogeneity of sleep and circadian profiles in young people with affective disorders, and provide preliminary evidence in support of a relationship between sleep and visual memory, which may be mediated by use of antipsychotic medication. These findings have implications for the personalisation of treatments and improvement of functioning in young adults early in the course of affective illness.

Analysis of NFU-1 metallocofactor binding-site substitutions-impacts on iron-sulfur cluster coordination and protein structure and function.

PubMed

Wesley, Nathaniel A; Wachnowsky, Christine; Fidai, Insiya; Cowan, J A

2017-11-01

Iron-sulfur (Fe/S) clusters are ancient prosthetic groups found in numerous metalloproteins and are conserved across all kingdoms of life due to their diverse, yet essential functional roles. Genetic mutations to a specific subset of mitochondrial Fe/S cluster delivery proteins are broadly categorized as disease-related under multiple mitochondrial dysfunction syndrome (MMDS), with symptoms indicative of a general failure of the metabolic system. Multiple mitochondrial dysfunction syndrome 1 (MMDS1) arises as a result of the missense mutation in NFU1, an Fe/S cluster scaffold protein, which substitutes a glycine near the Fe/S cluster-binding pocket to a cysteine (p.Gly208Cys). This substitution has been shown to promote protein dimerization such that cluster delivery to NFU1 is blocked, preventing downstream cluster trafficking. However, the possibility of this additional cysteine, located adjacent to the cluster-binding site, serving as an Fe/S cluster ligand has not yet been explored. To fully understand the consequences of this Gly208Cys replacement, complementary substitutions at the Fe/S cluster-binding pocket for native and Gly208Cys NFU1 were made, along with six other variants. Herein, we report the results of an investigation on the effect of these substitutions on both cluster coordination and NFU1 structure and function. The data suggest that the G208C substitution does not contribute to cluster binding. Rather, replacement of the glycine at position 208 changes the oligomerization state as a result of global structural alterations that result in the downstream effects manifest as MMDS1, but does not perturb the coordination chemistry of the Fe-S cluster. © 2017 Federation of European Biochemical Societies.

Real-Time Kinetic Probes Support Monothiol Glutaredoxins As Intermediate Carriers in Fe-S Cluster Biosynthetic Pathways.

PubMed

Vranish, James N; Das, Deepika; Barondeau, David P

2016-11-18

Iron-sulfur (Fe-S) clusters are protein cofactors that are required for many essential cellular functions. Fe-S clusters are synthesized and inserted into target proteins by an elaborate biosynthetic process. The insensitivity of most Fe-S assembly and transfer assays requires high concentrations for components and places major limits on reaction complexity. Recently, fluorophore labels were shown to be effective at reporting cluster content for Fe-S proteins. Here, the incorporation of this labeling approach allowed the design and interrogation of complex Fe-S cluster biosynthetic reactions that mimic in vivo conditions. A bacterial Fe-S assembly complex, composed of the cysteine desulfurase IscS and scaffold protein IscU, was used to generate [2Fe-2S] clusters for transfer to mixtures of putative intermediate carrier and acceptor proteins. The focus of this study was to test whether the monothiol glutaredoxin, Grx4, functions as an obligate [2Fe-2S] carrier protein in the Fe-S cluster distribution network. Interestingly, [2Fe-2S] clusters generated by the IscS-IscU complex transferred to Grx4 at rates comparable to previous assays using uncomplexed IscU as a cluster source in chaperone-assisted transfer reactions. Further, we provide evidence that [2Fe-2S]-Grx4 delivers clusters to multiple classes of Fe-S targets via direct ligand exchange in a process that is both dynamic and reversible. Global fits of cluster transfer kinetics support a model in which Grx4 outcompetes terminal target proteins for IscU-bound [2Fe-2S] clusters and functions as an intermediate cluster carrier. Overall, these studies demonstrate the power of chemically conjugated fluorophore reporters for unraveling mechanistic details of biological metal cofactor assembly and distribution networks.

Effects of cosmic string velocities and the origin of globular clusters

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

Lin, Ling; Yamanouchi, Shoma; Brandenberger, Robert, E-mail: ling.lin2@mail.mcgill.ca, E-mail: shoma.yamanouchi@mail.mcgill.ca, E-mail: rhb@physics.mcgill.ca

2015-12-01

With the hypothesis that cosmic string loops act as seeds for globular clusters in mind, we study the role that velocities of these strings will play in determining the mass distribution of globular clusters. Loops with high enough velocities will not form compact and roughly spherical objects and can hence not be the seeds for globular clusters. We compute the expected number density and mass function of globular clusters as a function of both the string tension and the peak loop velocity, and compare the results with the observational data on the mass distribution of globular clusters in our Milkymore » Way. We determine the critical peak string loop velocity above which the agreement between the string loop model for the origin of globular clusters (neglecting loop velocities) and observational data is lost.« less

A conserved gene cluster as a putative functional unit in insect innate immunity.

PubMed

Somogyi, Kálmán; Sipos, Botond; Pénzes, Zsolt; Andó, István

2010-11-05

The Nimrod gene superfamily is an important component of the innate immune response. The majority of its member genes are located in close proximity within the Drosophila melanogaster genome and they lie in a larger conserved cluster ("Nimrod cluster"), made up of non-related groups (families, superfamilies) of genes. This cluster has been a part of the Arthropod genomes for about 300-350 million years. The available data suggest that the Nimrod cluster is a functional module of the insect innate immune response. Copyright © 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Cluster Differences Scaling with a Within-Clusters Loss Component and a Fuzzy Successive Approximation Strategy To Avoid Local Minima.

ERIC Educational Resources Information Center

Heiser, Willem J.; And Others

1997-01-01

The least squares loss function of cluster differences scaling, originally defined only on residuals of pairs allocated to different clusters, is extended with a loss component for pairs allocated to the same cluster. Findings show that this makes the method equivalent to multidimensional scaling with cluster constraints on the coordinates. (SLD)

The cluster galaxy circular velocity function

NASA Astrophysics Data System (ADS)

Desai, V.; Dalcanton, J. J.; Mayer, L.; Reed, D.; Quinn, T.; Governato, F.

2004-06-01

We present galaxy circular velocity functions (GCVFs) for 34 low-redshift (z<~ 0.15) clusters identified in the Sloan Digital Sky Survey (SDSS), for 15 clusters drawn from dark matter simulations of hierarchical structure growth in a ΛCDM cosmology, and for ~22 000 SDSS field galaxies. We find that the simulations successfully reproduce the shape, amplitude and scatter in the observed distribution of cluster galaxy circular velocities. The power-law slope of the observed cluster GCVF is ~-2.4, independent of cluster velocity dispersion. The average slope of the simulated GCVFs is somewhat steeper, although formally consistent given the errors. We find that the effects of baryons on galaxy rotation curves is to flatten the simulated cluster GCVF into better agreement with observations. The cumulative GCVFs of the simulated clusters are very similar across a wide range of cluster masses, provided individual subhalo circular velocities are scaled by the circular velocities of the parent cluster. The scatter is consistent with that measured in the cumulative, scaled observed cluster GCVF. Finally, the observed field GCVF deviates significantly from a power law, being flatter than the cluster GCVF at circular velocities less than 200 km s-1.

The young star cluster population of M51 with LEGUS - I. A comprehensive study of cluster formation and evolution

NASA Astrophysics Data System (ADS)

Messa, M.; Adamo, A.; Östlin, G.; Calzetti, D.; Grasha, K.; Grebel, E. K.; Shabani, F.; Chandar, R.; Dale, D. A.; Dobbs, C. L.; Elmegreen, B. G.; Fumagalli, M.; Gouliermis, D. A.; Kim, H.; Smith, L. J.; Thilker, D. A.; Tosi, M.; Ubeda, L.; Walterbos, R.; Whitmore, B. C.; Fedorenko, K.; Mahadevan, S.; Andrews, J. E.; Bright, S. N.; Cook, D. O.; Kahre, L.; Nair, P.; Pellerin, A.; Ryon, J. E.; Ahmad, S. D.; Beale, L. P.; Brown, K.; Clarkson, D. A.; Guidarelli, G. C.; Parziale, R.; Turner, J.; Weber, M.

2018-01-01

Recently acquired WFC3 UV (F275W and F336W) imaging mosaics under the Legacy Extragalactic UV Survey (LEGUS), combined with archival ACS data of M51, are used to study the young star cluster (YSC) population of this interacting system. Our newly extracted source catalogue contains 2834 cluster candidates, morphologically classified to be compact and uniform in colour, for which ages, masses and extinction are derived. In this first work we study the main properties of the YSC population of the whole galaxy, considering a mass-limited sample. Both luminosity and mass functions follow a power-law shape with slope -2, but at high luminosities and masses a dearth of sources is observed. The analysis of the mass function suggests that it is best fitted by a Schechter function with slope -2 and a truncation mass at 1.00 ± 0.12 × 105 M⊙. Through Monte Carlo simulations, we confirm this result and link the shape of the luminosity function to the presence of a truncation in the mass function. A mass limited age function analysis, between 10 and 200 Myr, suggests that the cluster population is undergoing only moderate disruption. We observe little variation in the shape of the mass function at masses above 1 × 104 M⊙ over this age range. The fraction of star formation happening in the form of bound clusters in M51 is ∼ 20 per cent in the age range 10-100 Myr and little variation is observed over the whole range from 1 to 200 Myr.

From Head to Sword: The Clustering Properties of Stars in Orion

NASA Astrophysics Data System (ADS)

Gomez, Mercedes; Lada, Charles J.

1998-04-01

We investigate the structure in the spatial distributions of optically selected samples of young stars in the Head (lambda Orionis) and in the Sword (Orion A) regions of the constellation of Orion with the aid of stellar surface density maps and the two-point angular correlation function. The distributions of young stars in both regions are found to be nonrandom and highly clustered. Stellar surface density maps reveal three distinct clusters in the lambda Ori region. The two-point correlation function displays significant features at angular scales that correspond to the radii and separations of the three clusters identified in the surface density maps. Most young stars in the lambda Ori region (~80%) are presently found within these three clusters, consistent with the idea that the majority of young stars in this region were formed in dense protostellar clusters that have significantly expanded since their formation. Over a scale of ~0.05d-0.5d the correlation function is well described by a single power law that increases smoothly with decreasing angular scale. This suggests that, within the clusters, the stars either are themselves hierarchically clustered or have a volume density distribution that falls steeply with radius. The relative lack of Hα emission-line stars in the one cluster in this region that contains OB stars suggests a timescale for emission-line activity of less than 4 Myr around late-type stars in the cluster and may indicate that the lifetimes of protoplanetary disks around young stellar objects are reduced in clusters containing O stars. The spatial distribution of young stars in the Orion A region is considerably more complex. The angular correlation function of the OB stars (which are mostly foreground to the Orion A molecular cloud) is very similar to that of the Hα stars (which are located mostly within the molecular cloud) and significantly different from that of the young stars in the lambda Ori region. This suggests that, although spatially separated, both populations in the Orion A region may have originated from a similar fragmentation process. Stellar surface density maps and modeling of the angular correlation function suggest that somewhat less than half of the OB and Hα stars in the Orion A cloud are presently within well-defined stellar clusters. Although all the OB stars could have originated in rich clusters, a significant fraction of the Hα stars appear to have formed outside such clusters in a more spatially dispersed manner. The close similarity of the angular correlation functions of the OB and Hα stars toward the molecular cloud, in conjunction with the earlier indications of a relatively high star formation rate and high gas pressure in this cloud, is consistent with the idea that older, foreground OB stars triggered the current episode of star formation in the Orion A cloud. One of the OB clusters (Upper Sword) that is foreground to the cloud does not appear to be associated with any of the clusterings of emission-line stars, again suggesting a timescale (<4 Myr) for emission-line activity and disk lifetimes around late-type stars born in OB clusters.

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI).

PubMed

Fyffe, Denise; Kalpakjian, Claire Z; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C; Tulsky, David S; Jette, Alan M

2016-09-01

To provide validation of functional ability levels for the Spinal Cord Injury - Functional Index (SCI-FI). Cross-sectional. Inpatient rehabilitation hospital and community settings. A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Not Applicable. Spinal Cord Injury-Functional Index (SCI-FI). Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed.

Combining Multiobjective Optimization and Cluster Analysis to Study Vocal Fold Functional Morphology

PubMed Central

Palaparthi, Anil; Riede, Tobias

2017-01-01

Morphological design and the relationship between form and function have great influence on the functionality of a biological organ. However, the simultaneous investigation of morphological diversity and function is difficult in complex natural systems. We have developed a multiobjective optimization (MOO) approach in association with cluster analysis to study the form-function relation in vocal folds. An evolutionary algorithm (NSGA-II) was used to integrate MOO with an existing finite element model of the laryngeal sound source. Vocal fold morphology parameters served as decision variables and acoustic requirements (fundamental frequency, sound pressure level) as objective functions. A two-layer and a three-layer vocal fold configuration were explored to produce the targeted acoustic requirements. The mutation and crossover parameters of the NSGA-II algorithm were chosen to maximize a hypervolume indicator. The results were expressed using cluster analysis and were validated against a brute force method. Results from the MOO and the brute force approaches were comparable. The MOO approach demonstrated greater resolution in the exploration of the morphological space. In association with cluster analysis, MOO can efficiently explore vocal fold functional morphology. PMID:24771563

MicroRNA-424/503 cluster members regulate bovine granulosa cell proliferation and cell cycle progression by targeting SMAD7 gene through activin signalling pathway.

PubMed

Pande, Hari Om; Tesfaye, Dawit; Hoelker, Michael; Gebremedhn, Samuel; Held, Eva; Neuhoff, Christiane; Tholen, Ernst; Schellander, Karl; Wondim, Dessie Salilew

2018-05-01

The granulosa cells are indispensable for follicular development and its function is orchestrated by several genes, which in turn posttranscriptionally regulated by microRNAs (miRNA). In our previous study, the miRRNA-424/503 cluster was found to be highly abundant in bovine granulosa cells (bGCs) of preovulatory dominant follicle compared to subordinate counterpart at day 19 of the bovine estrous cycle. Other study also indicated the involvement of miR-424/503 cluster in tumour cell resistance to apoptosis suggesting this miRNA cluster may involve in cell survival. However, the role of miR-424/503 cluster in granulosa cell function remains elusive Therefore, this study aimed to investigate the role of miRNA-424/503 cluster in bGCs function using microRNA gain- and loss-of-function approaches. The role of miR-424/503 cluster members in granulosa cell function was investigated by overexpressing or inhibiting its activity in vitro cultured granulosa cells using miR-424/503 mimic or inhibitor, respectively. Luciferase reporter assay showed that SMAD7 and ACVR2A are the direct targets of the miRNA-424/503 cluster members. In line with this, overexpression of miRNA-424/503 cluster members using its mimic and inhibition of its activity by its inhibitor reduced and increased, respectively the expression of SMAD7 and ACVR2A. Furthermore, flow cytometric analysis indicated that overexpression of miRNA-424/503 cluster members enhanced bGCs proliferation by promoting G1- to S- phase cell cycle transition. Modulation of miRNA-424/503 cluster members tended to increase phosphorylation of SMAD2/3 in the Activin signalling pathway. Moreover, sequence specific knockdown of SMAD7, the target gene of miRNA-424/503 cluster members, using small interfering RNA also revealed similar phenotypic and molecular alterations observed when miRNA-424/503 cluster members were overexpressed. Similarly, to get more insight about the role of miRNA-424/503 cluster members in activin signalling pathway, granulosa cells were treated with activin A. Activin A treatment increased cell proliferation and downregulation of both miRNA-424/503 members and its target gene, indicated the presence of negative feedback loop between activin A and the expression of miRNA-424/503. This study suggests that the miRNA-424/503 cluster members are involved in regulating bovine granulosa cell proliferation and cell cycle progression. Further, miRNA-424/503 cluster members target the SMAD7 and ACVR2A genes which are involved in the activin signalling pathway.

CORM: An R Package Implementing the Clustering of Regression Models Method for Gene Clustering

PubMed Central

Shi, Jiejun; Qin, Li-Xuan

2014-01-01

We report a new R package implementing the clustering of regression models (CORM) method for clustering genes using gene expression data and provide data examples illustrating each clustering function in the package. The CORM package is freely available at CRAN from http://cran.r-project.org. PMID:25452684

Cluster-cluster clustering

NASA Technical Reports Server (NTRS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

A Bridging [4Fe-4S] Cluster and Nucleotide Binding Are Essential for Function of the Cfd1-Nbp35 Complex as a Scaffold in Iron-Sulfur Protein Maturation*

PubMed Central

Netz, Daili J. A.; Pierik, Antonio J.; Stümpfig, Martin; Bill, Eckhard; Sharma, Anil K.; Pallesen, Leif J.; Walden, William E.; Lill, Roland

2012-01-01

The essential P-loop NTPases Cfd1 and Nbp35 of the cytosolic iron-sulfur (Fe-S) protein assembly machinery perform a scaffold function for Fe-S cluster synthesis. Both proteins contain a nucleotide binding motif of unknown function and a C-terminal motif with four conserved cysteine residues. The latter motif defines the Mrp/Nbp35 subclass of P-loop NTPases and is suspected to be involved in transient Fe-S cluster binding. To elucidate the function of these two motifs, we first created cysteine mutant proteins of Cfd1 and Nbp35 and investigated the consequences of these mutations by genetic, cell biological, biochemical, and spectroscopic approaches. The two central cysteine residues (CPXC) of the C-terminal motif were found to be crucial for cell viability, protein function, coordination of a labile [4Fe-4S] cluster, and Cfd1-Nbp35 hetero-tetramer formation. Surprisingly, the two proximal cysteine residues were dispensable for all these functions, despite their strict evolutionary conservation. Several lines of evidence suggest that the C-terminal CPXC motifs of Cfd1-Nbp35 coordinate a bridging [4Fe-4S] cluster. Upon mutation of the nucleotide binding motifs Fe-S clusters could no longer be assembled on these proteins unless wild-type copies of Cfd1 and Nbp35 were present in trans. This result indicated that Fe-S cluster loading on these scaffold proteins is a nucleotide-dependent step. We propose that the bridging coordination of the C-terminal Fe-S cluster may be ideal for its facile assembly, labile binding, and efficient transfer to target Fe-S apoproteins, a step facilitated by the cytosolic iron-sulfur (Fe-S) protein assembly proteins Nar1 and Cia1 in vivo. PMID:22362766

Cluster analysis differentiates high and low community functioning in schizophrenia: Subgroups differ on working memory but not other neurocognitive domains.

PubMed

Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J

2015-10-01

Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Counts of galaxy clusters as cosmological probes: the impact of baryonic physics

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

Balaguera-Antolínez, Andrés; Porciani, Cristiano, E-mail: abalan@astro.uni-bonn.de, E-mail: porciani@astro.uni-bonn.de

2013-04-01

The halo mass function from N-body simulations of collisionless matter is generally used to retrieve cosmological parameters from observed counts of galaxy clusters. This neglects the observational fact that the baryonic mass fraction in clusters is a random variable that, on average, increases with the total mass (within an overdensity of 500). Considering a mock catalog that includes tens of thousands of galaxy clusters, as expected from the forthcoming generation of surveys, we show that the effect of a varying baryonic mass fraction will be observable with high statistical significance. The net effect is a change in the overall normalizationmore » of the cluster mass function and a milder modification of its shape. Our results indicate the necessity of taking into account baryonic corrections to the mass function if one wants to obtain unbiased estimates of the cosmological parameters from data of this quality. We introduce the formalism necessary to accomplish this goal. Our discussion is based on the conditional probability of finding a given value of the baryonic mass fraction for clusters of fixed total mass. Finally, we show that combining information from the cluster counts with measurements of the baryonic mass fraction in a small subsample of clusters (including only a few tens of objects) will nearly optimally constrain the cosmological parameters.« less

A first-principles study of the influence of helium atoms on the optical response of small silver clusters.

PubMed

Pereiro, M; Baldomir, D; Arias, J E

2011-02-28

Optical excitation spectra of Ag(n) and Ag(n)@He(60) (n = 2, 8) clusters are investigated in the framework of the time-dependent density functional theory (TDDFT) within the linear response regime. We have performed the ab initio calculations for two different exact exchange functionals (GGA-exact and LDA-exact). The computed spectra of Ag(n)@He(60) clusters with the GGA-exact functional accounting for exchange-correlation effects are found to be generally in a relatively good agreement with the experiment. A strategy is proposed to obtain the ground-state structures of the Ag(n)@He(60) clusters and in the initial process of the geometry optimization, the He environment is simulated with buckyballs. A redshift of the silver clusters spectra is observed in the He environment with respect to the ones of bare silver clusters. This observation is discussed and explained in terms of a contraction of the Ag-He bonding length and a consequent confinement of the s valence electrons in silver clusters. Likewise, the Mie-Gans predictions combined with our TDDFT calculations also show that the dielectric effect produced by the He matrix is considerably less important in explaining the redshifting observed in the optical spectra of Ag(n)@He(60) clusters.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

Fe-S Cluster Hsp70 Chaperones: The ATPase Cycle and Protein Interactions.

PubMed

Dutkiewicz, Rafal; Nowak, Malgorzata; Craig, Elizabeth A; Marszalek, Jaroslaw

2017-01-01

Hsp70 chaperones and their obligatory J-protein cochaperones function together in many cellular processes. Via cycles of binding to short stretches of exposed amino acids on substrate proteins, Hsp70/J-protein chaperones not only facilitate protein folding but also drive intracellular protein transport, biogenesis of cellular structures, and disassembly of protein complexes. The biogenesis of iron-sulfur (Fe-S) clusters is one of the critical cellular processes that require Hsp70/J-protein action. Fe-S clusters are ubiquitous cofactors critical for activity of proteins performing diverse functions in, for example, metabolism, RNA/DNA transactions, and environmental sensing. This biogenesis process can be divided into two sequential steps: first, the assembly of an Fe-S cluster on a conserved scaffold protein, and second, the transfer of the cluster from the scaffold to a recipient protein. The second step involves Hsp70/J-protein chaperones. Via binding to the scaffold, chaperones enable cluster transfer to recipient proteins. In eukaryotic cells mitochondria have a key role in Fe-S cluster biogenesis. In this review, we focus on methods that enabled us to dissect protein interactions critical for the function of Hsp70/J-protein chaperones in the mitochondrial process of Fe-S cluster biogenesis in the yeast Saccharomyces cerevisiae. © 2017 Elsevier Inc. All rights reserved.

Role of Nfu1 and Bol3 in iron-sulfur cluster transfer to mitochondrial clients

PubMed Central

Melber, Andrew; Na, Un; Vashisht, Ajay; Weiler, Benjamin D; Lill, Roland; Wohlschlegel, James A; Winge, Dennis R

2016-01-01

Iron-sulfur (Fe-S) clusters are essential for many cellular processes, ranging from aerobic respiration, metabolite biosynthesis, ribosome assembly and DNA repair. Mutations in NFU1 and BOLA3 have been linked to genetic diseases with defects in mitochondrial Fe-S centers. Through genetic studies in yeast, we demonstrate that Nfu1 functions in a late step of [4Fe-4S] cluster biogenesis that is of heightened importance during oxidative metabolism. Proteomic studies revealed Nfu1 physical interacts with components of the ISA [4Fe-4S] assembly complex and client proteins that need [4Fe-4S] clusters to function. Additional studies focused on the mitochondrial BolA proteins, Bol1 and Bol3 (yeast homolog to human BOLA3), revealing that Bol1 functions earlier in Fe-S biogenesis with the monothiol glutaredoxin, Grx5, and Bol3 functions late with Nfu1. Given these observations, we propose that Nfu1, assisted by Bol3, functions to facilitate Fe-S transfer from the biosynthetic apparatus to the client proteins preventing oxidative damage to [4Fe-4S] clusters. DOI: http://dx.doi.org/10.7554/eLife.15991.001 PMID:27532773

Stable isomers and electronic, vibrational, and optical properties of WS2 nano-clusters: A first-principles study

NASA Astrophysics Data System (ADS)

Hafizi, Roohollah; Hashemifar, S. Javad; Alaei, Mojtaba; Jangrouei, MohammadReza; Akbarzadeh, Hadi

2016-12-01

In this paper, we employ an evolutionary algorithm along with the full-potential density functional theory (DFT) computations to perform a comprehensive search for the stable structures of stoichiometric (WS2)n nano-clusters (n = 1 - 9), within three different exchange-correlation functionals. Our results suggest that n = 5 and 8 are possible candidates for the low temperature magic sizes of WS2 nano-clusters while at temperatures above 500 Kelvin, n = 7 exhibits a comparable relative stability with n = 8. The electronic properties and energy gap of the lowest energy isomers were computed within several schemes, including semilocal Perdew-Burke-Ernzerhof and Becke-Lee-Yang-Parr functionals, hybrid B3LYP functional, many body based DFT+GW approach, ΔSCF method, and time dependent DFT calculations. Vibrational spectra of the lowest lying isomers, computed by the force constant method, are used to address IR spectra and thermal free energy of the clusters. Time dependent density functional calculation in a real time domain is applied to determine the full absorption spectra and optical gap of the lowest energy isomers of the WS2 nano-clusters.

Structure-Based Phylogenetic Analysis of the Lipocalin Superfamily.

PubMed

Lakshmi, Balasubramanian; Mishra, Madhulika; Srinivasan, Narayanaswamy; Archunan, Govindaraju

2015-01-01

Lipocalins constitute a superfamily of extracellular proteins that are found in all three kingdoms of life. Although very divergent in their sequences and functions, they show remarkable similarity in 3-D structures. Lipocalins bind and transport small hydrophobic molecules. Earlier sequence-based phylogenetic studies of lipocalins highlighted that they have a long evolutionary history. However the molecular and structural basis of their functional diversity is not completely understood. The main objective of the present study is to understand functional diversity of the lipocalins using a structure-based phylogenetic approach. The present study with 39 protein domains from the lipocalin superfamily suggests that the clusters of lipocalins obtained by structure-based phylogeny correspond well with the functional diversity. The detailed analysis on each of the clusters and sub-clusters reveals that the 39 lipocalin domains cluster based on their mode of ligand binding though the clustering was performed on the basis of gross domain structure. The outliers in the phylogenetic tree are often from single member families. Also structure-based phylogenetic approach has provided pointers to assign putative function for the domains of unknown function in lipocalin family. The approach employed in the present study can be used in the future for the functional identification of new lipocalin proteins and may be extended to other protein families where members show poor sequence similarity but high structural similarity.

On the accuracy of density-functional theory exchange-correlation functionals for H bonds in small water clusters: Benchmarks approaching the complete basis set limit

NASA Astrophysics Data System (ADS)

Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias

2007-11-01

The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Møller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.

On the accuracy of density-functional theory exchange-correlation functionals for H bonds in small water clusters: benchmarks approaching the complete basis set limit.

PubMed

Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias

2007-11-14

The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Moller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.

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.

Identification of Loci and Functional Characterization of Trichothecene Biosynthesis Genes in Filamentous Fungi of the Genus Trichoderma▿†

PubMed Central

Cardoza, R. E.; Malmierca, M. G.; Hermosa, M. R.; Alexander, N. J.; McCormick, S. P.; Proctor, R. H.; Tijerino, A. M.; Rumbero, A.; Monte, E.; Gutiérrez, S.

2011-01-01

Trichothecenes are mycotoxins produced by Trichoderma, Fusarium, and at least four other genera in the fungal order Hypocreales. Fusarium has a trichothecene biosynthetic gene (TRI) cluster that encodes transport and regulatory proteins as well as most enzymes required for the formation of the mycotoxins. However, little is known about trichothecene biosynthesis in the other genera. Here, we identify and characterize TRI gene orthologues (tri) in Trichoderma arundinaceum and Trichoderma brevicompactum. Our results indicate that both Trichoderma species have a tri cluster that consists of orthologues of seven genes present in the Fusarium TRI cluster. Organization of genes in the cluster is the same in the two Trichoderma species but differs from the organization in Fusarium. Sequence and functional analysis revealed that the gene (tri5) responsible for the first committed step in trichothecene biosynthesis is located outside the cluster in both Trichoderma species rather than inside the cluster as it is in Fusarium. Heterologous expression analysis revealed that two T. arundinaceum cluster genes (tri4 and tri11) differ in function from their Fusarium orthologues. The Tatri4-encoded enzyme catalyzes only three of the four oxygenation reactions catalyzed by the orthologous enzyme in Fusarium. The Tatri11-encoded enzyme catalyzes a completely different reaction (trichothecene C-4 hydroxylation) than the Fusarium orthologue (trichothecene C-15 hydroxylation). The results of this study indicate that although some characteristics of the tri/TRI cluster have been conserved during evolution of Trichoderma and Fusarium, the cluster has undergone marked changes, including gene loss and/or gain, gene rearrangement, and divergence of gene function. PMID:21642405

A Geometric and Electrostatic Study of the [4Fe-4S] Cluster of Adenosine-5´-Phosphosulfate Reductase from Broken Symmetry Density Functional Calculations and Extended X-ray Absorption Fine Structure Spectroscopy

PubMed Central

Bhave, Devayani P.; Han, Wen-Ge; Pazicni, Samuel; Penner-Hahn, James E.; Carroll, Kate S.; Noodleman, Louis

2011-01-01

Adenosine-5’-phosphosulfate reductase (APSR) is an iron-sulfur protein that catalyses the reduction of adenosine-5’-phosphosulfate (APS) to sulfite. APSR coordinates to a [4Fe-4S] cluster via a conserved CC-X~80-CXXC motif and the cluster is essential for catalysis. Despite extensive functional, structural and spectroscopic studies, the exact role of the iron-sulfur cluster in APS reduction remains unknown. To gain an understanding into the role of the cluster, density functional theory (DFT) analysis and extended X-ray fine structure spectroscopy (EXAFS) have been performed to reveal insights into the coordination, geometry and electrostatics of the [4Fe-4S] cluster. XANES data confirms that the cluster is in the [4Fe-4S]2+ state in both native and substrate-bound APSR while EXAFS data recorded at ~0.1 Å resolution indicates that there is no significant change in the structure of the [4Fe-4S] cluster between the native and substrate-bound forms of the protein. On the other hand, DFT calculations provide an insight into the subtle differences between the geometry of the cluster in the native and APS-bound forms of APSR. A comparison between models with and without the tandem cysteine pair coordination of the cluster suggests a role for the unique coordination in facilitating a compact geometric structure and ‘fine-tuning’ the electronic structure to prevent reduction of the cluster. Further, calculations using models in which residue Lys144 is mutated to Ala confirm the finding that Lys144 serves as a crucial link in the interactions involving the [4Fe-4S] cluster and APS. PMID:21678934

Regulation of human Nfu activity in Fe-S cluster delivery-characterization of the interaction between Nfu and the HSPA9/Hsc20 chaperone complex.

PubMed

Wachnowsky, Christine; Liu, Yushi; Yoon, Taejin; Cowan, J A

2018-01-01

Iron-sulfur cluster biogenesis is a complex, but highly regulated process that involves de novo cluster formation from iron and sulfide ions on a scaffold protein, and subsequent delivery to final targets via a series of Fe-S cluster-binding carrier proteins. The process of cluster release from the scaffold/carrier for transfer to the target proteins may be mediated by a dedicated Fe-S cluster chaperone system. In human cells, the chaperones include heat shock protein HSPA9 and the J-type chaperone Hsc20. While the role of chaperones has been somewhat clarified in yeast and bacterial systems, many questions remain over their functional roles in cluster delivery and interactions with a variety of human Fe-S cluster proteins. One such protein, Nfu, has recently been recognized as a potential interaction partner of the chaperone complex. Herein, we examined the ability of human Nfu to function as a carrier by interacting with the human chaperone complex. Human Nfu is shown to bind to both chaperone proteins with binding affinities similar to those observed for IscU binding to the homologous HSPA9 and Hsc20, while Nfu can also stimulate the ATPase activity of HSPA9. Additionally, the chaperone complex was able to promote Nfu function by enhancing the second-order rate constants for Fe-S cluster transfer to target proteins and providing directionality in cluster transfer from Nfu by eliminating promiscuous transfer reactions. Together, these data support a hypothesis in which Nfu can serve as an alternative carrier protein for chaperone-mediated cluster release and delivery in Fe-S cluster biogenesis and trafficking. © 2017 Federation of European Biochemical Societies.

HST-WFPC2 Observations of the Star Clusters in the Giant H II Regions of M33

NASA Astrophysics Data System (ADS)

Lee, Myung Gyoon; Park, Hong Soo; Kim, Sang Chul; Waller, William H.; Parker, Joel Wm.; Malumuth, Eliot M.; Hodge, Paul W.

We present a photometric study of the stars in ionizing star clusters embedded in several giant H II regions of M33 (CC93, IC 142, NGC 595, MA2, NGC 604 and NGC 588). Our photometry is based on the HST-WFPC2 images of these clusters. Color-magnitude diagrams and color-color diagrams of these clusters are obtained and are used for estimating the reddenings and ages of the clusters. The luminosity functions (LFs) and initial mass functions (IMFs) of the massive stars in these clusters are also derived. The slopes of the IMFs range from Γ = -0.5 to -2.1. Interestingly, it is found that the IMFs get steeper with increasing galactocentric distance and with decreasing [O/H] abundance.

Structure, electronic and magnetic properties of Mn{sub n} (n=2-8) clusters: A DFT investigation

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

Kumar, Vipin; Roy, Debesh R., E-mail: drr@ashd.svnit.ac.in

2016-05-06

A detail studyon the stability, electronic and magnetic properties of Mn{sub n} (n=2-8) cluster series is performed under the utilization ofdensity functional theory (DFT). The binding energy (B.E.), HOMO-LUMO energy gap (HLG), chemical hardness (η), ionization potential (I.P.), electron affinity (E.A)and electronegativity (χ) of these clusters are predicted. We have also studied the magnetic moments associated with the stable cluster isomers. The lowest energy structures for each cluster sizes aredetermined with a systematic search imposing all possible initial magnetic configuration on the cluster. All the calculations are carried out using a popular GGA functional PBE as proposed by Pardew, Burkemore » and Ernzerhof and implemented in the VASP program.« less

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

Analysis of the Structures and Properties of (GaSb)n (n = 4-9) Clusters through Density Functional Theory.

PubMed

Lu, Qi Liang; Luo, Qi Quan; Huang, Shou Guo; Li, Yi De; Wan, Jian Guo

2016-07-07

An optimization strategy combining global semiempirical quantum mechanical search with all-electron density functional theory was adopted to determine the lowest energy structure of (GaSb)n clusters up to n = 9. The growth pattern of the clusters differed from those of previously reported group III-V binary clusters. A cagelike configuration was found for cluster sizes n ≤ 7. The structure of (GaSb)6 deviated from that of other III-V clusters. Competition existed between core-shell and hollow cage structures of (GaSb)7. Novel noncagelike structures were energetically preferred over the cages for the (GaSb)8 and (GaSb)9 clusters. Electronic properties, such as vertical ionization potential, adiabatic electron affinities, HOMO-LUMO gaps, and average on-site charges on Ga or Sb atoms, as well as binding energies, were computed.

Electronic and magnetic properties of small rhodium clusters

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

Soon, Yee Yeen; Yoon, Tiem Leong; Lim, Thong Leng

2015-04-24

We report a theoretical study of the electronic and magnetic properties of rhodium-atomic clusters. The lowest energy structures at the semi-empirical level of rhodium clusters are first obtained from a novel global-minimum search algorithm, known as PTMBHGA, where Gupta potential is used to describe the atomic interaction among the rhodium atoms. The structures are then re-optimized at the density functional theory (DFT) level with exchange-correlation energy approximated by Perdew-Burke-Ernzerhof generalized gradient approximation. For the purpose of calculating the magnetic moment of a given cluster, we calculate the optimized structure as a function of the spin multiplicity within the DFT framework.more » The resultant magnetic moments with the lowest energies so obtained allow us to work out the magnetic moment as a function of cluster size. Rhodium atomic clusters are found to display a unique variation in the magnetic moment as the cluster size varies. However, Rh{sub 4} and Rh{sub 6} are found to be nonmagnetic. Electronic structures of the magnetic ground-state structures are also investigated within the DFT framework. The results are compared against those based on different theoretical approaches available in the literature.« less

Choosing the Number of Clusters in K-Means Clustering

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

Steinley (2007) provided a lower bound for the sum-of-squares error criterion function used in K-means clustering. In this article, on the basis of the lower bound, the authors propose a method to distinguish between 1 cluster (i.e., a single distribution) versus more than 1 cluster. Additionally, conditional on indicating there are multiple…

Adsorption and Desorption of Hydrogen by Gas-Phase Palladium Clusters Revealed by In Situ Thermal Desorption Spectroscopy.

PubMed

Takenouchi, Masato; Kudoh, Satoshi; Miyajima, Ken; Mafuné, Fumitaka

2015-07-02

Adsorption and desorption of hydrogen by gas-phase Pd clusters, Pdn(+), were investigated by thermal desorption spectroscopy (TDS) experiments and density functional theory (DFT) calculations. The desorption processes were examined by heating the clusters that had adsorbed hydrogen at room temperature. The clusters remaining after heating were monitored by mass spectrometry as a function of temperature up to 1000 K, and the temperature-programmed desorption (TPD) curve was obtained for each Pdn(+). It was found that hydrogen molecules were released from the clusters into the gas phase with increasing temperature until bare Pdn(+) was formed. The threshold energy for desorption, estimated from the TPD curve, was compared to the desorption energy calculated by using DFT, indicating that smaller Pdn(+) clusters (n ≤ 6) tended to have weakly adsorbed hydrogen molecules, whereas larger Pdn(+) clusters (n ≥ 7) had dissociatively adsorbed hydrogen atoms on the surface. Highly likely, the nonmetallic nature of the small Pd clusters prevents hydrogen molecule from adsorbing dissociatively on the surface.

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

Characterizing decision-making and reward processing in bipolar disorder: A cluster analysis.

PubMed

Jiménez, E; Solé, B; Arias, B; Mitjans, M; Varo, C; Reinares, M; Bonnín, C M; Salagre, E; Ruíz, V; Torres, I; Tomioka, Y; Sáiz, P A; García-Portilla, M P; Burón, P; Bobes, J; Martínez-Arán, A; Torrent, C; Vieta, E; Benabarre, A

2018-05-25

The presence of abnormalities in emotional decision-making and reward processing among bipolar patients (BP) has been well rehearsed. These disturbances are not limited to acute phases and are common even during remission. In recent years, the existence of discrete cognitive profiles in this psychiatric population has been replicated. However, emotional decision making and reward processing domains have barely been studied. Therefore, our aim was to explore the existence of different profiles on the aforementioned cognitive dimensions in BP. The sample consisted of 126 euthymic BP. Main sociodemographic, clinical, functioning, and neurocognitive variables were gathered. A hierarchical-clustering technique was used to identify discrete neurocognitive profiles based on the performance in the Iowa Gambling Task. Afterward, the resulting clusters were compared using ANOVA or Chi-squared Test, as appropriate. Evidence for the existence of three different profiles was provided. Cluster 1 was mainly characterized by poor decision ability. Cluster 2 presented the lowest sensitivity to punishment. Finally, cluster 3 presented the best decision-making ability and the highest levels of punishment sensitivity. Comparison between the three clusters indicated that cluster 2 was the most functionally impaired group. The poorest outcomes in attention, executive function domains, and social cognition were also observed within the same group. In conclusion, similarly to that observed in "cold cognitive" domains, our results suggest the existence of three discrete cognitive profiles concerning emotional decision making and reward processing. Amongst all the indexes explored, low punishment sensitivity emerge as a potential correlate of poorer cognitive and functional outcomes in bipolar disorder. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.

[Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses].

PubMed

Ning, P; Guo, Y F; Sun, T Y; Zhang, H S; Chai, D; Li, X M

2016-09-01

To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis. A population sample of adult patients in Donghuamen community, Dongcheng district and Qinghe community, Haidian district, Beijing from April 2012 to January 2015, who had wheeze within the last 12 months, underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, total serum IgE levels, blood eosinophil level and a peak flow diary. Nine variables were chosen as evaluating parameters, including pre-salbutamol forced expired volume in one second(FEV1)/forced vital capacity(FVC) ratio, pre-salbutamol FEV1, percentage of post-salbutamol change in FEV1, residual capacity, diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level, peak expiratory flow(PEF) variability, serum IgE level, cumulative tobacco cigarette consumption (pack-years) and respiratory symptoms (cough and expectoration). Subjects' different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified. (1) Four clusters were identified by hierarchical cluster analysis. Cluster 1 was chronic bronchitis in smokers with normal pulmonary function. Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease (COPD) patients with mild airflow limitation. Cluster 3 included COPD patients with heavy smoking, poor quality of life and severe airflow limitation. Cluster 4 recognized atopic patients with mild airflow limitation, elevated serum IgE and clinical features of asthma. Significant differences were revealed regarding pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, maximal mid-expiratory flow curve(MMEF)% pred, carbon monoxide diffusing capacity per liter of alveolar(DLCO)/(VA)% pred, residual volume(RV)% pred, total serum IgE level, smoking history (pack-years), St.George's respiratory questionnaire(SGRQ) score, acute exacerbation in the past one year, PEF variability and allergic dermatitis (P<0.05). (2) Four clusters were also identified by two-step cluster analysis as followings, cluster 1, COPD patients with moderate to severe airflow limitation; cluster 2, asthma and COPD patients with heavy smoking, airflow limitation and increased airways reversibility; cluster 3, patients having less smoking and normal pulmonary function with wheezing but no chronic cough; cluster 4, chronic bronchitis patients with normal pulmonary function and chronic cough. Significant differences were revealed regarding gender distribution, respiratory symptoms, pre-salbutamol FEV1/FVC%, pre-salbutamol FEV1% pred, post-salbutamol change in FEV1%, MMEF% pred, DLCO/VA% pred, RV% pred, PEF variability, total serum IgE level, cumulative tobacco cigarette consumption (pack-years), and SGRQ score (P<0.05). By different cluster analyses, distinct clinical phenotypes of chronic airway diseases are identified. Thus, individualized treatments may guide doctors to provide based on different phenotypes.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

LoCuSS: connecting the dominance and shape of brightest cluster galaxies with the assembly history of massive clusters

NASA Astrophysics Data System (ADS)

Smith, Graham P.; Khosroshahi, Habib G.; Dariush, A.; Sanderson, A. J. R.; Ponman, T. J.; Stott, J. P.; Haines, C. P.; Egami, E.; Stark, D. P.

2010-11-01

We study the luminosity gap, Δm12, between the first- and second-ranked galaxies in a sample of 59 massive (~1015Msolar) galaxy clusters, using data from the Hale Telescope, the Hubble Space Telescope, Chandra and Spitzer. We find that the Δm12 distribution, p(Δm12), is a declining function of Δm12 to which we fitted a straight line: p(Δm12) ~ -(0.13 +/- 0.02)Δm12. The fraction of clusters with `large' luminosity gaps is p(Δm12 >= 1) = 0.37 +/- 0.08, which represents a 3σ excess over that obtained from Monte Carlo simulations of a Schechter function that matches the mean cluster galaxy luminosity function. We also identify four clusters with `extreme' luminosity gaps, Δm12 >= 2, giving a fraction of . More generally, large luminosity gap clusters are relatively homogeneous, with elliptical/discy brightest cluster galaxies (BCGs), cuspy gas density profiles (i.e. strong cool cores), high concentrations and low substructure fractions. In contrast, small luminosity gap clusters are heterogeneous, spanning the full range of boxy/elliptical/discy BCG morphologies, the full range of cool core strengths and dark matter concentrations, and have large substructure fractions. Taken together, these results imply that the amplitude of the luminosity gap is a function of both the formation epoch and the recent infall history of the cluster. `BCG dominance' is therefore a phase that a cluster may evolve through and is not an evolutionary `cul-de-sac'. We also compare our results with semi-analytic model predictions based on the Millennium Simulation. None of the models is able to reproduce all of the observational results on Δm12, underlining the inability of the current generation of models to match the empirical properties of BCGs. We identify the strength of active galactic nucleus feedback and the efficiency with which cluster galaxies are replenished after they merge with the BCG in each model as possible causes of these discrepancies.

Use of DAVID algorithms for gene functional classification in a non-model organism, rainbow trout

USDA-ARS?s Scientific Manuscript database

Gene functional clustering is essential in transcriptome data analysis but software programs are not always suitable for use with non-model species. The DAVID Gene Functional Classification Tool has been widely used for soft clustering in model species, but requires adaptations for use in non-model ...

Familial Clustering of Executive Functioning in Affected Sibling Pair Families with ADHD

ERIC Educational Resources Information Center

Slaats-Willemse, Dorine; Swaab-Barneveld, Hanna; De Sonneville, Leo; Buitelaar, Jan

2005-01-01

Objective: To investigate familial clustering of executive functioning (i.e., response inhibition, fine visuomotor functioning, and attentional control) in attention-deficit/hyperactivity disorder (ADHD)-affected sibling pairs. Method: Fifty-two affected sibling pairs aged 6 to 18 years and diagnosed with ADHD according to DSM-IV performed the…

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena.

PubMed

De Domenico, Manlio

2017-04-21

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Structure and Electronic Properties of Neutral and Negatively Charged RhBn Clusters (n = 3-10): A Density Functional Theory Study.

PubMed

Li, Peifang; Mei, Tingting; Lv, Linxia; Lu, Cheng; Wang, Weihua; Bao, Gang; Gutsev, Gennady L

2017-08-31

The geometrical structure and electronic properties of the neutral RhB n and singly negatively charged RhB n - clusters are obtained in the range of 3 ≤ n ≤ 10 using the unbiased CALYPSO structure search method and density functional theory (DFT). A combination of the PBE0 functional and the def2-TZVP basis set is used for determining global minima on potential energy surfaces of the Rh-doped B n clusters. The photoelectron spectra of the anions are simulated using the time-dependent density functional theory (TD-DFT) method. Good agreement between our simulated and experimentally obtained photoelectron spectra for RhB 9 - provides support to the validity of our theoretical method. The relative stabilities of the ground-state RhB n and RhB n - clusters are estimated using the calculated binding energies, second-order total energy differences, and HOMO-LUMO gaps. It is found that RhB 7 and RhB 8 - are the most stable species in the neutral and anionic series, respectively. The chemical bonding analysis reveals that the RhB 8 - cluster possesses two sets of delocalized σ and π bonds. In both cases, the Hückel 4N + 2 rule is fulfilled and this cluster possesses both σ and π aromaticities.

Tangled web of interactions among proteins involved in iron–sulfur cluster assembly as unraveled by NMR, SAXS, chemical crosslinking, and functional studies☆

PubMed Central

Kim, Jin Hae; Bothe, Jameson R.; Alderson, T. Reid; Markley, John L.

2014-01-01

Proteins containing iron–sulfur (Fe–S) clusters arose early in evolution and are essential to life. Organisms have evolved machinery consisting of specialized proteins that operate together to assemble Fe–S clusters efficiently so as to minimize cellular exposure to their toxic constituents: iron and sulfide ions. To date, the best studied system is the iron sulfur cluster (isc) operon of Escherichia coli, and the eight ISC proteins it encodes. Our investigations over the past five years have identified two functional conformational states for the scaffold protein (IscU) and have shown that the other ISC proteins that interact with IscU prefer to bind one conformational state or the other. From analyses of the NMR spectroscopy-derived network of interactions of ISC proteins and small-angle X-ray scattering (SAXS), chemical crosslinking experiments, and functional assays, we have constructed working models for Fe–S cluster assembly and delivery. Future work is needed to validate and refine what has been learned about the E. coli system and to extend these findings to the homologous Fe–S cluster biosynthetic machinery of yeast and human mitochondria. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases. PMID:25450980

Visual Field Map Clusters in Macaque Extrastriate Visual Cortex

PubMed Central

Kolster, Hauke; Mandeville, Joseph B.; Arsenault, John T.; Ekstrom, Leeland B.; Wald, Lawrence L.; Vanduffel, Wim

2009-01-01

The macaque visual cortex contains more than 30 different functional visual areas, yet surprisingly little is known about the underlying organizational principles that structure its components into a complete ‘visual’ unit. A recent model of visual cortical organization in humans suggests that visual field maps are organized as clusters. Clusters minimize axonal connections between individual field maps that represent common visual percepts, with different clusters thought to carry out different functions. Experimental support for this hypothesis, however, is lacking in macaques, leaving open the question of whether it is unique to humans or a more general model for primate vision. Here we show, using high-resolution BOLD fMRI data in the awake monkey at 7 Tesla, that area MT/V5 and its neighbors are organized as a cluster with a common foveal representation and a circular eccentricity map. This novel view on the functional topography of area MT/V5 and satellites indicates that field map clusters are evolutionarily preserved and may be a fundamental organizational principle of the old world primate visual cortex. PMID:19474330

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

PubMed

Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

Density functional study on structure and stability of bimetallic AuNZn (N<=6) clusters and their cations

NASA Astrophysics Data System (ADS)

Tanaka, Hiromasa; Neukermans, Sven; Janssens, Ewald; Silverans, Roger E.; Lievens, Peter

2003-10-01

A systematic study on the structure and stability of zinc doped gold clusters has been performed by density functional theory calculations. All the lowest-energy isomers found have a planar structure and resemble pure gold clusters in shape. Stable isomers tend to equally delocalize valence s electrons of the constituent atoms over the entire structure and maximize the number of Au-Zn bonds in the structure. This is because the Au-Zn bond is stronger than the Au-Au bond and gives an extra σ-bonding interaction by the overlap between vacant Zn 4p and valence Au 6s(5d) orbitals. No three-dimensional isomers were found for Au5Zn+ and Au4Zn clusters containing six delocalized valence electrons. This result reflects that these clusters have a magic number of delocalized electrons for two-dimensional systems. Calculated vertical ionization energies and dissociation energies as a function of the cluster size show odd-even behavior, in agreement with recent mass spectrometric observations [Tanaka et al., J. Am. Chem. Soc. 125, 2862 (2003)].

Stability and migration of large oxygen clusters in UO(2+x): density functional theory calculations.

PubMed

Andersson, D A; Espinosa-Faller, F J; Uberuaga, B P; Conradson, S D

2012-06-21

Using ab initio molecular dynamics simulations and nudged elastic band calculations we examine the finite temperature stability, transition pathways, and migration mechanisms of large oxygen clusters in UO(2+x). Here we specifically consider the recently proposed split quad-interstitial and cuboctahedral oxygen clusters. It is shown that isolated cuboctahedral clusters may transform into more stable configurations that are closely linked to the split quad-interstitial. The split quad-interstitial is stable with respect to single interstitials occupying the empty octahedral holes of the UO(2) lattice. In order to better understand discrepancies between theory and experiments, the simulated atomic pair distribution functions for the split quad-interstitial structures are analyzed with respect to the distribution function for U(4)O(9) previously obtained from neutron diffraction data. Our nudged elastic band calculations suggest that the split quad-interstitial may migrate by translating one of its constituent di-interstitial clusters via a barrier that is lower than the corresponding barrier for individual interstitials, but higher than the barrier for the most stable di-interstitial cluster.

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.

MicroRNA cluster miR-17-92 Cluster in Exosomes Enhance Neuroplasticity and Functional Recovery After Stroke in Rats.

PubMed

Xin, Hongqi; Katakowski, Mark; Wang, Fengjie; Qian, Jian-Yong; Liu, Xian Shuang; Ali, Meser M; Buller, Benjamin; Zhang, Zheng Gang; Chopp, Michael

2017-03-01

Multipotent mesenchymal stromal cell (MSC) harvested exosomes are hypothesized as the major paracrine effectors of MSCs. In vitro, the miR-17-92 cluster promotes oligodendrogenesis, neurogenesis, and axonal outgrowth. We, therefore, investigated whether the miR-17-92 cluster-enriched exosomes harvested from MSCs transfected with an miR-17-92 cluster plasmid enhance neurological recovery compared with control MSC-derived exosomes. Rats subjected to 2 hours of transient middle cerebral artery occlusion were intravenously administered miR-17-92 cluster-enriched exosomes, control MSC exosomes, or liposomes and were euthanized 28 days post-middle cerebral artery occlusion. Histochemistry, immunohistochemistry, and Golgi-Cox staining were used to assess dendritic, axonal, synaptic, and myelin remodeling. Expression of phosphatase and tensin homolog and activation of its downstream proteins, protein kinase B, mechanistic target of rapamycin, and glycogen synthase kinase 3β in the peri-infarct region were measured by means of Western blots. Compared with the liposome treatment, both exosome treatment groups exhibited significant improvement of functional recovery, but miR-17-92 cluster-enriched exosome treatment had significantly more robust effects on improvement of neurological function and enhancements of oligodendrogenesis, neurogenesis, and neurite remodeling/neuronal dendrite plasticity in the ischemic boundary zone (IBZ) than the control MSC exosome treatment. Moreover, miR-17-92 cluster-enriched exosome treatment substantially inhibited phosphatase and tensin homolog, a validated miR-17-92 cluster target gene, and subsequently increased the phosphorylation of phosphatase and tensin homolog downstream proteins, protein kinase B, mechanistic target of rapamycin, and glycogen synthase kinase 3β compared with control MSC exosome treatment. Our data suggest that treatment of stroke with tailored exosomes enriched with the miR-17-92 cluster increases neural plasticity and functional recovery after stroke, possibly via targeting phosphatase and tensin homolog to activate the PI3K/protein kinase B/mechanistic target of rapamycin/glycogen synthase kinase 3β signaling pathway. © 2017 American Heart Association, Inc.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

A Study of the Dependence of the Properties of Galaxy Clusters on Cluster Morphology.

NASA Astrophysics Data System (ADS)

Lugger, Phyllis Minnie

1982-03-01

A quantitative study of the properties of clusters of galaxies as a function of cluster morphology has been carried out using photographic plates obtained with the Palomar 48 inch Schmidt telescope. Surface brightness profiles of 35 first ranked cluster galaxies and luminosity functions of nine clusters are presented and analyzed. The dispersion in the metric magnitudes of first ranked galaxies is quite small ((TURN) 0.4 mag) which is consistent with the results of Kristian, Sandage and Westphal as well as Hoessel, Gunn and Thuan. For the cD (supergiant elliptical) galaxy sample, the mean metric magnitude is (TURN) 0.5 mag brighter than for the non-cD galaxies. The dispersion in the metric magnitudes for the 10 cD galaxies studied is found to be much smaller ((sigma) (TURN) 0.1 mag) than the dispersion in the metric magnitudes of the non-cD first ranked galaxies ((sigma) (TURN) 0.4 mag). The de Vaucouleurs effective radius - magnitude relation determined in the present study for first ranked galaxies (log r(,e) = -0.2 M + const.) is consistent with the extrapolations to brighter magnitudes of the range of relations found by Strom and Strom. The average residuals from the mean radius-magnitude relation for the cD and non-cD galaxy samples were not found to differ at a significant level. Luminosity functions for the region within 0.5 Mpc of the cluster center for three of the clusters studied (A1656, A2147, and A2199) show a deficit of bright galaxies when compared to a concentric annular region with bounds of 0.5 and 1.0 Mpc. Characteristic magnitudes for the nine clusters (determined from square regions 4.6 Mpc on a side) show no significant correlation with cluster morphology, central density, or total magnitude of the first ranked galaxy. The mean values of the Schechter function parameters M('*) and (alpha) are in very good agreement with the previous determinations by Schechter and by Dressler. The differential luminosity functions for A569 and A1656 do not rise monotonically to fainter magnitudes but instead show dips. These data are used to test predictions of several recent theories of the dynamical evolution of clusters of galaxies.

Identification and analysis of evolutionary selection pressures acting at the molecular level in five forkhead subfamilies.

PubMed

Fetterman, Christina D; Rannala, Bruce; Walter, Michael A

2008-09-24

Members of the forkhead gene family act as transcription regulators in biological processes including development and metabolism. The evolution of forkhead genes has not been widely examined and selection pressures at the molecular level influencing subfamily evolution and differentiation have not been explored. Here, in silico methods were used to examine selection pressures acting on the coding sequence of five multi-species FOX protein subfamily clusters; FoxA, FoxD, FoxI, FoxO and FoxP. Application of site models, which estimate overall selection pressures on individual codons throughout the phylogeny, showed that the amino acid changes observed were either neutral or under negative selection. Branch-site models, which allow estimated selection pressures along specified lineages to vary as compared to the remaining phylogeny, identified positive selection along branches leading to the FoxA3 and Protostomia clades in the FoxA cluster and the branch leading to the FoxO3 clade in the FoxO cluster. Residues that may differentiate paralogs were identified in the FoxA and FoxO clusters and residues that differentiate orthologs were identified in the FoxA cluster. Neutral amino acid changes were identified in the forkhead domain of the FoxA, FoxD and FoxP clusters while positive selection was identified in the forkhead domain of the Protostomia lineage of the FoxA cluster. A series of residues under strong negative selection adjacent to the N- and C-termini of the forkhead domain were identified in all clusters analyzed suggesting a new method for refinement of domain boundaries. Extrapolation of domains among cluster members in conjunction with selection pressure information allowed prediction of residue function in the FoxA, FoxO and FoxP clusters and exclusion of known domain function in residues of the FoxA and FoxI clusters. Consideration of selection pressures observed in conjunction with known functional information allowed prediction of residue function and refinement of domain boundaries. Identification of residues that differentiate orthologs and paralogs provided insight into the development and functional consequences of paralogs and forkhead subfamily composition differences among species. Overall we found that after gene duplication of forkhead family members, rapid differentiation and subsequent fixation of amino acid changes through negative selection has occurred.

Star Formation in NGC 6531-Evidence From the age Spread and Initial Mass Function

NASA Astrophysics Data System (ADS)

Forbes, Douglas

1996-09-01

The results of a photometric UBV study of the young open cluster NGC 6531 are presented. The cluster is found to have a mean reddening E(B-V)=0.28±0.04 (s.d.) and distance modulus (V0-Mv)=10.70±0.13 (s.e.), and 105±11 likely cluster members have been identified within the cluster coronal radius of 9 arcmin. A comparison of the high-luminosity end of the cluster color-magnitude diagram to the evolutionary models by Maeder & Meynet [A&AS, 76, 411(1988)] suggests a nuclear age of (8±2) Myr. The very clear gap in the distribution of stars with 0≤(B-V)0≤0.20, corresponding to the "burn-off" of 3He in stars contracting to the main sequence [Ulrich, ApJ, 168, 57 (1971)], implies a contraction age of (8±3) Myr. There would seem to be no evidence of a spread in the ages of cluster stars, as has been observed in several other young open clusters [Herbst & Miller, AJ, 87, 1478 (1982)]. The initial mass function (IMF) constructed from the cluster luminosity function and the mass-luminosity relation given by Scab (1986) shows good agreement with the field star IMF, and with the IMFS of a number of clusters of similar age and richness. The relative deficiency of low-mass stars seen by Herbst and Miller in NGC 3293 (a cluster of quite similar age and reddening) is not evident in NGC 6531.

Infrared Multiple Photon Dissociation Spectroscopy Of Metal Cluster-Adducts

NASA Astrophysics Data System (ADS)

Cox, D. M.; Kaldor, A.; Zakin, M. R.

1987-01-01

Recent development of the laser vaporization technique combined with mass-selective detection has made possible new studies of the fundamental chemical and physical properties of unsupported transition metal clusters as a function of the number of constituent atoms. A variety of experimental techniques have been developed in our laboratory to measure ionization threshold energies, magnetic moments, and gas phase reactivity of clusters. However, studies have so far been unable to determine the cluster structure or the chemical state of chemisorbed species on gas phase clusters. The application of infrared multiple photon dissociation IRMPD to obtain the IR absorption properties of metal cluster-adsorbate species in a molecular beam is described here. Specifically using a high power, pulsed CO2 laser as the infrared source, the IRMPD spectrum for methanol chemisorbed on small iron clusters is measured as a function of the number of both iron atoms and methanols in the complex for different methanol isotopes. Both the feasibility and potential utility of IRMPD for characterizing metal cluster-adsorbate interactions are demonstrated. The method is generally applicable to any cluster or cluster-adsorbate system dependent only upon the availability of appropriate high power infrared sources.

CO2 adsorption on gas-phase Cu4-xPtx (x = 0-4) clusters: a DFT study.

PubMed

Gálvez-González, Luis E; Juárez-Sánchez, J Octavio; Pacheco-Contreras, Rafael; Garzón, Ignacio L; Paz-Borbón, Lauro Oliver; Posada-Amarillas, Alvaro

2018-06-13

Transition and noble metal clusters have proven to be critical novel materials, potentially offering major advantages over conventional catalysts in a range of value-added catalytic processess such as carbon dioxide transformation to methanol. In this work, a systematic computational study of CO2 adsorption on gas-phase Cu4-xPtx (x = 0-4) clusters is performed. An exhaustive potential energy surface exploration is initially performed using our recent density functional theory basin-hopping global optimization implementation. Ground-state and low-lying energy isomers are identified for Cu4-xPtx clusters. Secondly, a CO2 molecule adsorption process is analyzed on the ground-state Cu4-xPtx configurations, as a function of cluster composition. Our results show that the gas-phase linear CO2 molecule is deformed upon adsorption, with its bend angle varying from about 132° to 139°. Cu4-xPtx cluster geometries remain unchanged after CO2 adsorption, with the exception of Cu3Pt1 and Pt4 clusters. For these particular cases, a structural conversion between the ground-state geometry and the corresponding first isomer configurations is found to be assisted by the CO2 adsorption. For all clusters, the energy barriers between the ground-state and first isomer structures are explored. Our calculated CO2 adsorption energies are found to be larger for Pt-rich clusters, exhibiting a volcano-type plot. The overall effect of a hybrid functional including dispersion forces is also discussed.

T7 RNA Polymerase Functions In Vitro without Clustering

PubMed Central

Finan, Kieran; Torella, Joseph P.; Kapanidis, Achillefs N.; Cook, Peter R.

2012-01-01

Many nucleic acid polymerases function in clusters known as factories. We investigate whether the RNA polymerase (RNAP) of phage T7 also clusters when active. Using ‘pulldowns’ and fluorescence correlation spectroscopy we find that elongation complexes do not interact in vitro with a Kd<1 µM. Chromosome conformation capture also reveals that genes located 100 kb apart on the E. coli chromosome do not associate more frequently when transcribed by T7 RNAP. We conclude that if clustering does occur in vivo, it must be driven by weak interactions, or mediated by a phage-encoded protein. PMID:22768341

Black hole binaries dynamically formed in globular clusters

NASA Astrophysics Data System (ADS)

Park, Dawoo; Kim, Chunglee; Lee, Hyung Mok; Bae, Yeong-Bok; Belczynski, Krzysztof

2017-08-01

We investigate properties of black hole (BH) binaries formed in globular clusters via dynamical processes, using directN-body simulations. We pay attention to effects of BH mass function on the total mass and mass ratio distributions of BH binaries ejected from clusters. First, we consider BH populations with two different masses in order to learn basic differences from models with single-mass BHs only. Secondly, we consider continuous BH mass functions adapted from recent studies on massive star evolution in a low metallicity environment, where globular clusters are formed. In this work, we consider only binaries that are formed by three-body processes and ignore stellar evolution and primordial binaries for simplicity. Our results imply that most BH binary mergers take place after they get ejected from the cluster. Also, mass ratios of dynamically formed binaries should be close to 1 or likely to be less than 2:1. Since the binary formation efficiency is larger for higher-mass BHs, it is likely that a BH mass function sampled by gravitational-wave observations would be weighed towards higher masses than the mass function of single BHs for a dynamically formed population. Applying conservative assumptions regarding globular cluster populations such as small BH mass fraction and no primordial binaries, the merger rate of BH binaries originated from globular clusters is estimated to be at least 6.5 yr-1 Gpc-3. Actual rate can be up to more than several times of our conservative estimate.

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

PubMed Central

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression

PubMed Central

Poole, William; Leinonen, Kalle; Shmulevich, Ilya

2017-01-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C. PMID:28170390

Multiscale mutation clustering algorithm identifies pan-cancer mutational clusters associated with pathway-level changes in gene expression.

PubMed

Poole, William; Leinonen, Kalle; Shmulevich, Ilya; Knijnenburg, Theo A; Bernard, Brady

2017-02-01

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, phosphorylation sites, and known single nucleotide variants. We statistically associated these multiscale clusters with gene expression and drug response data to illuminate the functional and clinical consequences of mutations in our clusters. Interestingly, we find multiple clusters within individual genes that have differential functional associations: these include PTEN, FUBP1, and CDH1. This methodology has potential implications in identifying protein regions for drug targets, understanding the biological underpinnings of cancer, and personalizing cancer treatments. Toward this end, we have made the mutation clusters and the clustering algorithm available to the public. Clusters and pathway associations can be interactively browsed at m2c.systemsbiology.net. The multiscale mutation clustering algorithm is available at https://github.com/IlyaLab/M2C.

Associations between Functional Milestones and Psychiatric Admissions in an Urban Area: Utility of a Cluster-Analytical Approach.

PubMed

Montemagni, Cristiana; Frieri, Tiziana; Villari, Vincenzo; Rocca, Paola

2018-06-01

The purpose of the study was to identify homogenous subgroups, based upon achievement of two functional milestones (marriage and employment) and Global Assessment of Functioning (GAF) score in a sample of 848 acute patients admitted to the Psychiatric Emergency Service (PES) of the Città della Salute e della Scienza di Torino, during a 24-months period. A two-step cluster-analysis, using GAF total score and the achievements in the two milestones as input data was performed. In order to examine whether the identified subgroups differed in external variables that were not included in the clustering process, and consequently to validate the found functional profiles, chi-square tests for categorical variables and analyses of variance (ANOVA) for continuous variables were performed. Five clusters were found. Employed patients (Clusters 4 and 5) had more years of education, less illness chronicity (shorter duration of illness and lower proportion of previous voluntary hospitalizations), lower use of mental health resources in the last year yet higher treatment adherence, larger network size, and higher ordinary discharge. Married inpatients (Clusters 3 and 5) had lower frequencies of substance abuse. The remarkably high rate of unemployment in this inpatients' sample, and the evidence of associations between unemployment and poorer functioning, argue for further research and development of evidence-based supported employment programs, that put forth diligent effort in helping people obtain work quickly and sustain; they may also help to reduce health care service use among that clientele.

Reactions of mixed silver-gold cluster cations AgmAun+ (m+n=4,5,6) with CO: Radiative association kinetics and density functional theory computations

NASA Astrophysics Data System (ADS)

Neumaier, Marco; Weigend, Florian; Hampe, Oliver; Kappes, Manfred M.

2006-09-01

Near thermal energy reactive collisions of small mixed metal cluster cations AgmAun+ (m +n=4, 5, and 6) with carbon monoxide have been studied in the room temperature Penning trap of a Fourier transform ion-cyclotron-resonance mass spectrometer as a function of cluster size and composition. The tetrameric species AgAu3+ and Ag2Au2+ are found to react dissociatively by way of Au or Ag atom loss, respectively, to form the cluster carbonyl AgAu2CO+. In contrast, measurements on a selection of pentamers and hexamers show that CO is added with absolute rate constants that decrease with increasing silver content. Experimentally determined absolute rate constants for CO adsorption were analyzed using the radiative association kinetics model to obtain cluster cation-CO binding energies ranging from 0.77to1.09eV. High-level ab initio density functional theory (DFT) computations identifying the lowest-energy cluster isomers and the respective CO adsorption energies are in good agreement with the experimental findings clearly showing that CO binds in a "head-on" fashion to a gold atom in the mixed clusters. DFT exploration of reaction pathways in the case of Ag2Au2+ suggests that exoergicities are high enough to access the minimum energy products for all reactive clusters probed.

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI)

PubMed Central

Fyffe, Denise; Kalpakjian, Claire Z.; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C.; Tulsky, David S.; Jette, Alan M.

2016-01-01

Objective: To provide validation of functional ability levels for the Spinal Cord Injury – Functional Index (SCI-FI). Design: Cross-sectional. Setting: Inpatient rehabilitation hospital and community settings. Participants: A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Interventions: Not Applicable. Main Outcome Measures: Spinal Cord Injury-Functional Index (SCI-FI). Results: Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. Conclusions: These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed. PMID:26781769

Brain structure and function correlates of cognitive subtypes in schizophrenia.

PubMed

Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan

2015-10-30

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Clustering in the SDSS Redshift Survey

NASA Astrophysics Data System (ADS)

Zehavi, I.; Blanton, M. R.; Frieman, J. A.; Weinberg, D. H.; SDSS Collaboration

2002-05-01

We present measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our current sample consists of roughly 80,000 galaxies with redshifts in the range 0.02 < z < 0.2, covering about 1200 square degrees. We measure the clustering in redshift space and in real space. The two-dimensional correlation function ξ (rp,π ) shows clear signatures of redshift distortions, both the small-scale ``fingers-of-God'' effect and the large-scale compression. The inferred real-space correlation function is well described by a power law. The SDSS is especially suitable for investigating the dependence of clustering on galaxy properties, due to the wealth of information in the photometric survey. We focus on the dependence of clustering on color and on luminosity.

Investigating Open Clusters Melotte 111 and NGC 6811

NASA Astrophysics Data System (ADS)

Gunshefski, Linda; Paust, Nathaniel E. Q.; van Belle, Gerard

2018-01-01

We present photometry and color-magnitude diagrams for the open clusters Melotte 111 (Coma Bernices) and NGC 6811. These clusters were observed with Lowell Observatory’s Discovery Channel Telescope Large Monolithic Imager in the V and I bands. The images were reduced with IRAF and photometry was performed with DAOPHOT/ALLSTAR. The resulting photometry extends many magnitudes below the main sequence turnoff. Both clusters are located nearby, (Melotte 111 d=86 pc and NGC 6811 d=1,107) and are evolutionarily young (Melotte 111, age=450 Myr and NGC 6811, age=1,000 Myr). This work marks the first step of a project to determine the cluster main sequence mass functions and examine how the mass functions evolve in young stellar populations.

Significance tests for functional data with complex dependence structure.

PubMed

Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J

2015-01-01

We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.

Multiconstrained gene clustering based on generalized projections

PubMed Central

2010-01-01

Background Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constraints such as gene expressions, Gene Ontology (GO) annotations and gene network structures. How to integrate multiple pieces of constraints for an optimal clustering solution still remains an unsolved problem. Results We propose a novel multiconstrained gene clustering (MGC) method within the generalized projection onto convex sets (POCS) framework used widely in image reconstruction. Each constraint is formulated as a corresponding set. The generalized projector iteratively projects the clustering solution onto these sets in order to find a consistent solution included in the intersection set that satisfies all constraints. Compared with previous MGC methods, POCS can integrate multiple constraints from different nature without distorting the original constraints. To evaluate the clustering solution, we also propose a new performance measure referred to as Gene Log Likelihood (GLL) that considers genes having more than one function and hence in more than one cluster. Comparative experimental results show that our POCS-based gene clustering method outperforms current state-of-the-art MGC methods. Conclusions The POCS-based MGC method can successfully combine multiple constraints from different nature for gene clustering. Also, the proposed GLL is an effective performance measure for the soft clustering solutions. PMID:20356386

Probing the structural and electronic properties of cationic rubidium-gold clusters: [AunRb]+ (n = 1-10)

NASA Astrophysics Data System (ADS)

Zhao, Ya-Ru; Zhang, Hai-Rong; Qian, Yu; Duan, Xu-Chao; Hu, Yan-Fei

2016-03-01

Density functional theory has been applied to study the geometric structures, relative stabilities, and electronic properties of cationic [AunRb]+ and Aun + 1+ (n = 1-10) clusters. For the lowest energy structures of [AunRb]+ clusters, the planar to three-dimensional transformation is found to occur at cluster size n = 4 and the Rb atoms prefer being located at the most highly coordinated position. The trends of the averaged atomic binding energies, fragmentation energies, second-order difference of energies, and energy gaps show pronounced even-odd alternations. It indicated that the clusters containing odd number of atoms maintain greater stability than the clusters in the vicinity. In particular, the [Au6Rb]+ clusters are the most stable isomer for [AunRb]+ clusters in the region of n = 1-10. The charges in [AunRb]+ clusters transfer from the Rb atoms to Aun host. Density of states revealed that the Au-5d, Au-5p, and Rb-4p orbitals hardly participated in bonding. In addition, it is found that the most favourable channel of the [AunRb]+ clusters is Rb+ cation ejection. The electronic localisation function (ELF) analysis of the [AunRb]+ clusters shown that strong interactions are not revealed in this study.

Role of Anions Associated with the Formation and Properties of Silver Clusters.

PubMed

Wang, Quan-Ming; Lin, Yu-Mei; Liu, Kuan-Guan

2015-06-16

Metal clusters have been very attractive due to their aesthetic structures and fascinating properties. Different from nanoparticles, each cluster of a macroscopic sample has a well-defined structure with identical composition, size, and shape. As the disadvantages of polydispersity are ruled out, informative structure-property relationships of metal clusters can be established. The formation of a high-nuclearity metal cluster involves the organization of metal ions into a complex entity in an ordered way. To achieve controllable preparation of metal clusters, it is helpful to introduce a directing agent in the formation process of a cluster. To this end, anion templates have been used to direct the formation of high nuclearity clusters. In this Account, the role of anions played in the formation of a variety of silver clusters has been reviewed. Silver ions are positively charged, so anionic species could be utilized to control the formation of silver clusters on the basis of electrostatic interactions, and the size and shape of the resulted clusters can be dictated by the templating anions. In addition, since the anion is an integral component in the silver clusters described, the physical properties of the clusters can be modulated by functional anions. The templating effects of simple inorganic anions and polyoxometales are shown in silver alkynyl clusters and silver thiolate clusters. Intercluster compounds are also described regarding the importance of anions in determining the packing of the ion pairs and making contribution to electron communications between the positive and negative counterparts. The role of the anions is threefold: (a) an anion is advantageous in stabilizing a cluster via balancing local positive charges of the metal cations; (b) an anion template could help control the size and shape of a cluster product; (c) an anion can be a key factor in influencing the function of a cluster through bringing in its intrinsic properties. Properties including electron communication, luminescent thermochromism, single-molecule magnet, and intercluster charge transfer associated with anion-directed silver clusters have been discussed. We intend to attract chemists' attention to the role that anions could play in determining the structures and properties of metal complexes, especially clusters. We hope that this Account will stimulate more efforts in exploiting new role of anions in various metal cluster systems. Anions can do much more than counterions for charge balance, and they should be considered in the design and synthesis of cluster-based functional materials.

Calibrating First-Order Strong Lensing Mass Estimates in Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Reed, Brendan; Remolian, Juan; Sharon, Keren; Li, Nan; SPT Clusters Cooperation

2018-01-01

We investigate methods to reduce the statistical and systematic errors inherent to using the Einstein Radius as a first-order mass estimate in strong lensing galaxy clusters. By finding an empirical universal calibration function, we aim to enable a first-order mass estimate of large cluster data sets in a fraction of the time and effort of full-scale strong lensing mass modeling. We use 74 simulated cluster data from the Argonne National Laboratory in a lens redshift slice of [0.159, 0.667] with various source redshifts in the range of [1.23, 2.69]. From the simulated density maps, we calculate the exact mass enclosed within the Einstein Radius. We find that the mass inferred from the Einstein Radius alone produces an error width of ~39% with respect to the true mass. We explore an array of polynomial and exponential correction functions with dependence on cluster redshift and projected radii of the lensed images, aiming to reduce the statistical and systematic uncertainty. We find that the error on the the mass inferred from the Einstein Radius can be reduced significantly by using a universal correction function. Our study has implications for current and future large galaxy cluster surveys aiming to measure cluster mass, and the mass-concentration relation.

Micro-heterogeneity versus clustering in binary mixtures of ethanol with water or alkanes.

PubMed

Požar, Martina; Lovrinčević, Bernarda; Zoranić, Larisa; Primorać, Tomislav; Sokolić, Franjo; Perera, Aurélien

2016-08-24

Ethanol is a hydrogen bonding liquid. When mixed in small concentrations with water or alkanes, it forms aggregate structures reminiscent of, respectively, the direct and inverse micellar aggregates found in emulsions, albeit at much smaller sizes. At higher concentrations, micro-heterogeneous mixing with segregated domains is found. We examine how different statistical methods, namely correlation function analysis, structure factor analysis and cluster distribution analysis, can describe efficiently these morphological changes in these mixtures. In particular, we explain how the neat alcohol pre-peak of the structure factor evolves into the domain pre-peak under mixing conditions, and how this evolution differs whether the co-solvent is water or alkane. This study clearly establishes the heuristic superiority of the correlation function/structure factor analysis to study the micro-heterogeneity, since cluster distribution analysis is insensitive to domain segregation. Correlation functions detect the domains, with a clear structure factor pre-peak signature, while the cluster techniques detect the cluster hierarchy within domains. The main conclusion is that, in micro-segregated mixtures, the domain structure is a more fundamental statistical entity than the underlying cluster structures. These findings could help better understand comparatively the radiation scattering experiments, which are sensitive to domains, versus the spectroscopy-NMR experiments, which are sensitive to clusters.

Mammalian Fe-S cluster biogenesis and its implication in disease.

PubMed

Beilschmidt, Lena K; Puccio, Hélène M

2014-05-01

Iron-sulfur (Fe-S) clusters are inorganic cofactors that are ubiquitous and essential. Due to their chemical versatility, Fe-S clusters are implicated in a wide range of protein functions including mitochondrial respiration and DNA repair. Composed of iron and sulfur, they are sensible to oxygen and their biogenesis requires a highly conserved protein machinery that facilitates assembly of the cluster as well as its insertion into apoproteins. Mitochondria are the central cellular compartment for Fe-S cluster biogenesis in eukaryotic cells and the importance of proper function of this biogenesis for life is highlighted by a constantly increasing number of human genetic diseases that are associated with dysfunction of this Fe-S cluster biogenesis pathway. Although these disorders are rare and appear dissimilar, common aspects are found among them. This review will give an overview on what is known on mammalian Fe-S cluster biogenesis today, by putting it into the context of what is known from studies from lower model organisms, and focuses on the associated diseases, by drawing attention to the respective mutations. Finally, it outlines the importance of adequate cellular and murine models to uncover not only each protein function, but to resolve their role and requirement throughout the mammalian organism. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Cognitive profiles in euthymic patients with bipolar disorders: results from the FACE-BD cohort.

PubMed

Roux, Paul; Raust, Aurélie; Cannavo, Anne Sophie; Aubin, Valérie; Aouizerate, Bruno; Azorin, Jean-Michel; Bellivier, Frank; Belzeaux, Raoul; Bougerol, Thierry; Cussac, Iréna; Courtet, Philippe; Etain, Bruno; Gard, Sébastien; Job, Sophie; Kahn, Jean-Pierre; Leboyer, Marion; Olié, Emilie; Henry, Chantal; Passerieux, Christine

2017-03-01

Although cognitive deficits are a well-established feature of bipolar disorders (BD), even during periods of euthymia, little is known about cognitive phenotype heterogeneity among patients with BD. We investigated neuropsychological performance in 258 euthymic patients with BD recruited via the French network of expert centers for BD. We used a test battery assessing six domains of cognition. Hierarchical cluster analysis of the cross-sectional data was used to determine the optimal number of subgroups and to assign each patient to a specific cognitive cluster. Subsequently, subjects from each cluster were compared on demographic, clinical functioning, and pharmacological variables. A four-cluster solution was identified. The global cognitive performance was above normal in one cluster and below normal in another. The other two clusters had a near-normal cognitive performance, with above and below average verbal memory, respectively. Among the four clusters, significant differences were observed in estimated intelligence quotient and social functioning, which were lower for the low cognitive performers compared to the high cognitive performers. These results confirm the existence of several distinct cognitive profiles in BD. Identification of these profiles may help to develop profile-specific cognitive remediation programs, which might improve functioning in BD. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Structure and stability of clusters of β-alanine in the gas phase: importance of the nature of intermolecular interactions.

PubMed

Piekarski, Dariusz Grzegorz; Díaz-Tendero, Sergio

2017-02-15

We present a theoretical study of neutral clusters of β-alanine molecules in the gas phase, (β-ala) n n ≤ 5. Classical molecular dynamics simulations carried out with different internal excitation energies provide information on the clusters formation and their thermal decomposition limits. We also present an assessment study performed with different families of density functionals using the dimer, (β-ala) 2 , as a benchmark system. The M06-2X functional provides the best agreement in geometries and relative energies in comparison with the reference values computed with the MP2 and CCSD(T) methods. The structure, stability, dissociation energies and vertical ionization potentials of the studied clusters have been investigated using this functional in combination with the 6-311++G(d,p) basis set. An exhaustive analysis of intermolecular interactions is also presented. These results provide new insights into the stability, interaction nature and formation mechanisms of clusters of amino acids in the gas phase.

Cosmology with EMSS Clusters of Galaxies

NASA Technical Reports Server (NTRS)

Donahue, Megan; Voit, G. Mark

1999-01-01

We use ASCA observations of the Extended Medium Sensitivity Survey sample of clusters of galaxies to construct the first z = 0.5 - 0.8 cluster temperature function. This distant cluster temperature function, when compared to local z approximately 0 and to a similar moderate redshift (z = 0.3 - 0.4) temperature function strongly constrains the matter density of the universe. Best fits to the distributions of temperatures and redshifts of these cluster samples results in Omega(sub M) = 0.45 +/- 0.1 if Lambda = 0 and Omega = 0.27 +/- 0.1 if Lambda + Omega(sub M) = 1. The uncertainties are 1sigma statistical. We examine the systematics of our approach and find that systematics, stemming mainly from model assumptions and not measurement errors, are about the same size as the statistical uncertainty +/- 0.1. In this poster proceedings, we clarify the issue of a8 as reported in our paper Donahue & Voit (1999), since this was a matter of discussion at the meeting.

Covalent functionalization of octagraphene with magnetic octahedral B6- and non-planar C6- clusters

NASA Astrophysics Data System (ADS)

Chigo-Anota, E.; Cárdenas-Jirón, G.; Salazar Villanueva, M.; Bautista Hernández, A.; Castro, M.

2017-10-01

The interaction between the magnetic boron octahedral (B6-) and non-planar (C6-) carbon clusters with semimetal nano-sheet of octa-graphene (C64H24) in the gas phase is studied by means of DFT calculations. These results reveal that non-planar-1 (anion) carbon cluster exhibits structural stability, low chemical reactivity, magnetic (1.0 magneton bohr) and semiconductor behavior. On the other hand, there is chemisorption phenomena when the stable B6- and C6- clusters are absorbed on octa-graphene nanosheets. Such absorption generates high polarity and the low-reactivity remains as on the individual pristine cases. Electronic charge transference occurs from the clusters toward the nanosheets, producing a reduction of the work function for the complexes and also induces a magnetic behavior on the functionalized sheets. The quantum descriptors obtained for these systems reveal that they are feasible candidates for the design of molecular circuits, magnetic devices, and nano-vehicles for drug delivery.

Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters.

PubMed

Pathak, A K; Mukherjee, T; Maity, D K

2007-07-28

We report vertical detachment energy (VDE) and IR spectra of Br2.-.(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2.-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150 K. A linear relationship is obtained for VDE versus (n+3)(-1/3) and bulk VDE of Br2.- aqueous solution is calculated as 10.01 eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by approximately 0.5 eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by approximately 6.4 eV. Calculated IR spectra show that the formation of Br2.--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2.-.(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.

Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters

NASA Astrophysics Data System (ADS)

Pathak, A. K.; Mukherjee, T.; Maity, D. K.

2007-07-01

We report vertical detachment energy (VDE) and IR spectra of Br2•-•(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2•-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150K. A linear relationship is obtained for VDE versus (n+3)-1/3 and bulk VDE of Br2•- aqueous solution is calculated as 10.01eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by ˜0.5eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by ˜6.4eV. Calculated IR spectra show that the formation of Br2•--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2•-•(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.

The Seven Sisters DANCe. I. Empirical isochrones, luminosity, and mass functions of the Pleiades cluster

NASA Astrophysics Data System (ADS)

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

2015-05-01

Context. The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 million unique sources in a region encompassing ~80 deg2 centered on the Pleiades cluster. Aims: We aim at deriving a complete census of the Pleiades and measure the mass and luminosity functions of the cluster. Methods: Using the probabilistic selection method previously described, we identified high probability members in the DANCe (i ≥ 14 mag) and Tycho-2 (V ≲ 12 mag) catalogues and studied the properties of the cluster over the corresponding luminosity range. Results: We find a total of 2109 high-probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to ~0.025 M⊙. The size, sensitivity, and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Conclusions: Our census supersedes previous studies of the Pleiades cluster populations, in terms of both sensitivity and accuracy. Based on service observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.Table 1 and Appendices are available in electronic form at http://www.aanda.orgDANCe catalogs (Tables 6 and 7) and full Tables 2-5 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A148

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

Treesearch

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

2011-01-01

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

Spectroscopic constraints on the form of the stellar cluster mass function

NASA Astrophysics Data System (ADS)

Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

2012-05-01

This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (<10 Myr) clusters, however this has proven difficult due to low-number statistics. In this contribution we use an alternative method based on the luminosities of the brightest clusters, combined with their ages. The advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering.

PubMed

Boari de Lima, Elisa; Meira, Wagner; Melo-Minardi, Raquel Cardoso de

2016-06-01

As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem's complexity. Hence, this work's purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data; domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem; and the identification of residues responsible for specificity.

Isofunctional Protein Subfamily Detection Using Data Integration and Spectral Clustering

PubMed Central

Boari de Lima, Elisa; Meira, Wagner; de Melo-Minardi, Raquel Cardoso

2016-01-01

As increasingly more genomes are sequenced, the vast majority of proteins may only be annotated computationally, given experimental investigation is extremely costly. This highlights the need for computational methods to determine protein functions quickly and reliably. We believe dividing a protein family into subtypes which share specific functions uncommon to the whole family reduces the function annotation problem’s complexity. Hence, this work’s purpose is to detect isofunctional subfamilies inside a family of unknown function, while identifying differentiating residues. Similarity between protein pairs according to various properties is interpreted as functional similarity evidence. Data are integrated using genetic programming and provided to a spectral clustering algorithm, which creates clusters of similar proteins. The proposed framework was applied to well-known protein families and to a family of unknown function, then compared to ASMC. Results showed our fully automated technique obtained better clusters than ASMC for two families, besides equivalent results for other two, including one whose clusters were manually defined. Clusters produced by our framework showed great correspondence with the known subfamilies, besides being more contrasting than those produced by ASMC. Additionally, for the families whose specificity determining positions are known, such residues were among those our technique considered most important to differentiate a given group. When run with the crotonase and enolase SFLD superfamilies, the results showed great agreement with this gold-standard. Best results consistently involved multiple data types, thus confirming our hypothesis that similarities according to different knowledge domains may be used as functional similarity evidence. Our main contributions are the proposed strategy for selecting and integrating data types, along with the ability to work with noisy and incomplete data; domain knowledge usage for detecting subfamilies in a family with different specificities, thus reducing the complexity of the experimental function characterization problem; and the identification of residues responsible for specificity. PMID:27348631

Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting

PubMed Central

Veatch, Sarah L.; Machta, Benjamin B.; Shelby, Sarah A.; Chiang, Ethan N.; Holowka, David A.; Baird, Barbara A.

2012-01-01

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins. PMID:22384026

Formation of young massive clusters from turbulent molecular clouds

NASA Astrophysics Data System (ADS)

Fujii, Michiko; Portegies Zwart, Simon

2015-08-01

We simulate the formation and evolution of young star clusters using smoothed-particle hydrodynamics (SPH) and direct N-body methods. We start by performing SPH simulations of the giant molecular cloud with a turbulent velocity field, a mass of 10^4 to 10^6 M_sun, and a density between 17 and 1700 cm^-3. We continue the SPH simulations for a free-fall time scale, and analyze the resulting structure of the collapsed cloud. We subsequently replace a density-selected subset of SPH particles with stars. As a consequence, the local star formation efficiency exceeds 30 per cent, whereas globally only a few per cent of the gas is converted to stars. The stellar distribution is very clumpy with typically a dozen bound conglomerates that consist of 100 to 10000 stars. We continue to evolve the stars dynamically using the collisional N-body method, which accurately treats all pairwise interactions, stellar collisions and stellar evolution. We analyze the results of the N-body simulations at 2 Myr and 10 Myr. From dense massive molecular clouds, massive clusters grow via hierarchical merging of smaller clusters. The shape of the cluster mass function that originates from an individual molecular cloud is consistent with a Schechter function with a power-law slope of beta = -1.73 at 2 Myr and beta = -1.67 at 10 Myr, which fits to observed cluster mass function of the Carina region. The superposition of mass functions have a power-law slope of < -2, which fits the observed mass function of star clusters in the Milky Way, M31 and M83. We further find that the mass of the most massive cluster formed in a single molecular cloud with a mass of M_g scales with 6.1 M_g^0.51 which also agrees with recent observation in M51. The molecular clouds which can form massive clusters are much denser than those typical in the Milky Way. The velocity dispersion of such molecular clouds reaches 20 km/s and it is consistent with the relative velocity of the molecular clouds observed near NGC 3603 and Westerlund 2, for which a triggered star formation by cloud-cloud collisions is suggested.

Threshold photoionization and density functional theory studies of bimetallic-carbide nanocrystals and fragments: Ta3ZrC(y) (y = 0-4).

PubMed

Dryza, V; Metha, G F

2009-06-28

Gas-phase bimetallic tantalum-zirconium-carbide clusters are generated using a constructed double ablation cluster source. The Ta(3)ZrC(y) (y = 0-4) clusters are examined by photoionization efficiency spectroscopy to extract experimental ionization energies (IEs). The IE trend for the Ta(3)ZrC(y) cluster series is reasonably similar to that of the Ta(4)C(y) cluster series [V. Dryza et al., J. Phys. Chem. A 109, 11180 (2005)], although the IE reductions upon carbon addition are greater for the former. Complementary density functional theory calculations are performed for the various isomers constructed by attaching carbon atoms to the different faces of the tetrahedral Ta(3)Zr cluster. The good agreement between the experimental IE trend and that calculated for these isomers support a 2x2x2 face centered cubic nanocrystal structure for Ta(4)ZrC(4) and nanocrystal fragment structures for the smaller clusters.

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

Glutathione-complexed [2Fe-2S] clusters function in Fe-S cluster storage and trafficking.

PubMed

Fidai, Insiya; Wachnowsky, Christine; Cowan, J A

2016-10-01

Glutathione-coordinated [2Fe-2S] complex is a non-protein-bound [2Fe-2S] cluster that is capable of reconstituting the human iron-sulfur cluster scaffold protein IscU. This complex demonstrates physiologically relevant solution chemistry and is a viable substrate for iron-sulfur cluster transport by Atm1p exporter protein. Herein, we report on some of the possible functional and physiological roles for this novel [2Fe-2S](GS4) complex in iron-sulfur cluster biosynthesis and quantitatively characterize its role in the broader network of Fe-S cluster transfer reactions. UV-vis and circular dichroism spectroscopy have been used in kinetic studies to determine second-order rate constants for [2Fe-2S] cluster transfer from [2Fe-2S](GS4) complex to acceptor proteins, such as human IscU, Schizosaccharomyces pombe Isa1, human and yeast glutaredoxins (human Grx2 and Saccharomyces cerevisiae Grx3), and human ferredoxins. Second-order rate constants for cluster extraction from these holo proteins were also determined by varying the concentration of glutathione, and a likely common mechanism for cluster uptake was determined by kinetic analysis. The results indicate that the [2Fe-2S](GS4) complex is stable under physiological conditions, and demonstrates reversible cluster exchange with a wide range of Fe-S cluster proteins, thereby supporting a possible physiological role for such centers.

Generalized fuzzy C-means clustering algorithm with improved fuzzy partitions.

PubMed

Zhu, Lin; Chung, Fu-Lai; Wang, Shitong

2009-06-01

The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithms, and it should not be forced to fix at the usual value m = 2. In view of its distinctive features in applications and its limitation in having m = 2 only, a recent advance of fuzzy clustering called fuzzy c-means clustering with improved fuzzy partitions (IFP-FCM) is extended in this paper, and a generalized algorithm called GIFP-FCM for more effective clustering is proposed. By introducing a novel membership constraint function, a new objective function is constructed, and furthermore, GIFP-FCM clustering is derived. Meanwhile, from the viewpoints of L(p) norm distance measure and competitive learning, the robustness and convergence of the proposed algorithm are analyzed. Furthermore, the classical fuzzy c-means algorithm (FCM) and IFP-FCM can be taken as two special cases of the proposed algorithm. Several experimental results including its application to noisy image texture segmentation are presented to demonstrate its average advantage over FCM and IFP-FCM in both clustering and robustness capabilities.

A phase cell cluster expansion for Euclidean field theories

NASA Astrophysics Data System (ADS)

Battle, Guy A., III; Federbush, Paul

1982-08-01

We adapt the cluster expansion first used to treat infrared problems for lattice models (a mass zero cluster expansion) to the usual field theory situation. The field is expanded in terms of special block spin functions and the cluster expansion given in terms of the expansion coefficients (phase cell variables); the cluster expansion expresses correlation functions in terms of contributions from finite coupled subsets of these variables. Most of the present work is carried through in d space time dimensions (for φ24 the details of the cluster expansion are pursued and convergence is proven). Thus most of the results in the present work will apply to a treatment of φ34 to which we hope to return in a succeeding paper. Of particular interest in this paper is a substitute for the stability of the vacuum bound appropriate to this cluster expansion (for d = 2 and d = 3), and a new method for performing estimates with tree graphs. The phase cell cluster expansions have the renormalization group incorporated intimately into their structure. We hope they will be useful ultimately in treating four dimensional field theories.

Relation between the Dynamics of Glassy Clusters and Characteristic Features of their Energy Landscape

NASA Astrophysics Data System (ADS)

De, Sandip; Schaefer, Bastian; Sadeghi, Ali; Sicher, Michael; Kanhere, D. G.; Goedecker, Stefan

2014-02-01

Based on a recently introduced metric for measuring distances between configurations, we introduce distance-energy (DE) plots to characterize the potential energy surface of clusters. Producing such plots is computationally feasible on the density functional level since it requires only a few hundred stable low energy configurations including the global minimum. By using standard criteria based on disconnectivity graphs and the dynamics of Lennard-Jones clusters, we show that the DE plots convey the necessary information about the character of the potential energy surface and allow us to distinguish between glassy and nonglassy systems. We then apply this analysis to real clusters at the density functional theory level and show that both glassy and nonglassy clusters can be found in simulations. It turns out that among our investigated clusters only those can be synthesized experimentally which exhibit a nonglassy landscape.

Large-Scale Structure Studies with the REFLEX Cluster Survey

NASA Astrophysics Data System (ADS)

Schuecker, P.; Bohringer, H.; Guzzo, L.; Collins, C.; Neumann, D. M.; Schindler, S.; Voges, W.

1998-12-01

First preliminary results of the ROSAT ESO Flux-Limited X-Ray (REFLEX) Cluster Survey are described. The survey covers 13,924 square degrees of the southern hemisphere. The present sample consists of about 470 rich clusters (1/3 non Abell/ACO clusters) with X-ray fluxes S >= 3.0 times 10^{-12} erg s^{-1} cm^{-2} (0.1-2.4 keV) and redshifts z <= 0.3. In contrast to other low-redshift surveys, the cumulative flux-number counts have an almost Euclidean slope. Comoving cluster number densities are found to be almost redshift-independent throughout the total survey volume. The X-ray luminosity function is well described by a Schechter function. The power spectrum of the number density fluctuations could be measured on scales up to 400 h^{-1} Mpc. A deeper survey with about 800 galaxy clusters in the same area is in progress.

Onset of carbon-carbon bonding in the Nb(5)C(y) (y = 0-6) clusters: a threshold photo-ionisation and density functional theory study.

PubMed

Dryza, Viktoras; Gascooke, Jason R; Buntine, Mark A; Metha, Gregory F

2009-02-21

We have used photo-ionisation efficiency spectroscopy to determine the ionisation potentials (IPs) of the niobium-carbide clusters, Nb(5)C(y) (y = 0-6). Of these clusters Nb(5)C(2) and Nb(5)C(3) exhibit the lowest IPs. Complementary density functional theory calculations have been performed to locate the lowest energy isomers for each cluster. By comparing the experimental IPs with those calculated for candidate isomers, the structures of the Nb(5)C(y) clusters observed in the experiment are inferred. For all these structures, the underlying Nb(5) cluster has either a "prolate" or "oblate" trigonal bipyramid geometry. Both Nb(5)C(5) and Nb(5)C(6) are shown to contain carbon-carbon bonding in the form of one and two molecular C(2) units, respectively.

A Class of Manifold Regularized Multiplicative Update Algorithms for Image Clustering.

PubMed

Yang, Shangming; Yi, Zhang; He, Xiaofei; Li, Xuelong

2015-12-01

Multiplicative update algorithms are important tools for information retrieval, image processing, and pattern recognition. However, when the graph regularization is added to the cost function, different classes of sample data may be mapped to the same subspace, which leads to the increase of data clustering error rate. In this paper, an improved nonnegative matrix factorization (NMF) cost function is introduced. Based on the cost function, a class of novel graph regularized NMF algorithms is developed, which results in a class of extended multiplicative update algorithms with manifold structure regularization. Analysis shows that in the learning, the proposed algorithms can efficiently minimize the rank of the data representation matrix. Theoretical results presented in this paper are confirmed by simulations. For different initializations and data sets, variation curves of cost functions and decomposition data are presented to show the convergence features of the proposed update rules. Basis images, reconstructed images, and clustering results are utilized to present the efficiency of the new algorithms. Last, the clustering accuracies of different algorithms are also investigated, which shows that the proposed algorithms can achieve state-of-the-art performance in applications of image clustering.

Quark cluster model for deep-inelastic lepton-deuteron scattering

NASA Astrophysics Data System (ADS)

Yen, G.; Vary, J. P.; Harindranath, A.; Pirner, H. J.

1990-10-01

We evaluate the contribution of quasifree nucleon knockout and of inelastic lepton-nucleon scattering in inclusive electron-deuteron reactions at large momentum transfer. We examine the degree of quantitative agreement with deuteron wave functions from the Reid soft-core and Bonn realistic nucleon-nucleon interactions. For the range of data available there is strong sensitivity to the tensor correlations which are distinctively different in these two deuteron models. At this stage of the analyses the Reid soft-core wave function provides a reasonable description of the data while the Bonn wave function does not. We then include a six-quark cluster component whose relative contribution is based on an overlap criterion and obtain a good description of all the data with both interactions. The critical separation at which overlap occurs (formation of six-quark clusters) is taken to be 1.0 fm and the six-quark cluster probability is 4.7% for Reid and 5.4% for Bonn. As a consequence the quark cluster model with either Reid or Bonn wave function describe the SLAC inclusive electron-deuteron scattering data equally well. We then show how additional data would be decisive in resolving which model is ultimately more correct.

Electronic effects on melting: Comparison of aluminum cluster anions and cations

NASA Astrophysics Data System (ADS)

Starace, Anne K.; Neal, Colleen M.; Cao, Baopeng; Jarrold, Martin F.; Aguado, Andrés; López, José M.

2009-07-01

Heat capacities have been measured as a function of temperature for aluminum cluster anions with 35-70 atoms. Melting temperatures and latent heats are determined from peaks in the heat capacities; cohesive energies are obtained for solid clusters from the latent heats and dissociation energies determined for liquid clusters. The melting temperatures, latent heats, and cohesive energies for the aluminum cluster anions are compared to previous measurements for the corresponding cations. Density functional theory calculations have been performed to identify the global minimum energy geometries for the cluster anions. The lowest energy geometries fall into four main families: distorted decahedral fragments, fcc fragments, fcc fragments with stacking faults, and "disordered" roughly spherical structures. The comparison of the cohesive energies for the lowest energy geometries with the measured values allows us to interpret the size variation in the latent heats. Both geometric and electronic shell closings contribute to the variations in the cohesive energies (and latent heats), but structural changes appear to be mainly responsible for the large variations in the melting temperatures with cluster size. The significant charge dependence of the latent heats found for some cluster sizes indicates that the electronic structure can change substantially when the cluster melts.

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species.

PubMed

Wang, Yi; Coleman-Derr, Devin; Chen, Guoping; Gu, Yong Q

2015-07-01

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that is useful for genome wide comparisons and visualization of orthologous clusters. OrthoVenn provides coverage of vertebrates, metazoa, protists, fungi, plants and bacteria for the comparison of orthologous clusters and also supports uploading of customized protein sequences from user-defined species. An interactive Venn diagram, summary counts, and functional summaries of the disjunction and intersection of clusters shared between species are displayed as part of the OrthoVenn result. OrthoVenn also includes in-depth views of the clusters using various sequence analysis tools. Furthermore, OrthoVenn identifies orthologous clusters of single copy genes and allows for a customized search of clusters of specific genes through key words or BLAST. OrthoVenn is an efficient and user-friendly web server freely accessible at http://probes.pw.usda.gov/OrthoVenn or http://aegilops.wheat.ucdavis.edu/OrthoVenn. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Ab initio calculations of optical properties of silver clusters: cross-over from molecular to nanoscale behavior

NASA Astrophysics Data System (ADS)

Titantah, John T.; Karttunen, Mikko

2016-05-01

Electronic and optical properties of silver clusters were calculated using two different ab initio approaches: (1) based on all-electron full-potential linearized-augmented plane-wave method and (2) local basis function pseudopotential approach. Agreement is found between the two methods for small and intermediate sized clusters for which the former method is limited due to its all-electron formulation. The latter, due to non-periodic boundary conditions, is the more natural approach to simulate small clusters. The effect of cluster size is then explored using the local basis function approach. We find that as the cluster size increases, the electronic structure undergoes a transition from molecular behavior to nanoparticle behavior at a cluster size of 140 atoms (diameter ~1.7 nm). Above this cluster size the step-like electronic structure, evident as several features in the imaginary part of the polarizability of all clusters smaller than Ag147, gives way to a dominant plasmon peak localized at wavelengths 350 nm ≤ λ ≤ 600 nm. It is, thus, at this length-scale that the conduction electrons' collective oscillations that are responsible for plasmonic resonances begin to dominate the opto-electronic properties of silver nanoclusters.

Density functional theory study on the metal-support interaction between a Au9 cluster and an anatase TiO2(001) surface.

PubMed

Jiang, Zong-You; Zhao, Zong-Yan

2017-08-23

Noble metals supported on TiO 2 surfaces have shown extraordinary photocatalytic properties in many important processes such as hydrogenation, water splitting, degradation of hazards, and so on. Using density functional theory calculations, this work has systematically investigated the microstructure and electronic structure of three different Au 9 isomers loaded on anatase TiO 2 (001) surface. The calculated results show that the interaction between the Au 9 cluster and the TiO 2 support is closely related to the adsorption site and the stability of the Au 9 cluster in the gas phase. The adsorption energy of the 2D configuration is larger than that of the 3D configuration of the Au 9 cluster, owing to the stronger interactions between more adsorption sites. The stable adsorption site for Au 9 clusters deposited on the anatase TiO 2 (001) surface tends to be the O 2c -O 2c hollow site. The presentation of the MIGS of the Au 9 cluster, the disappearance of surface states of the TiO 2 (001) surface, and the shifting of the Fermi level from the top of the valence band to the bottom of the conduction band suggest strong interactions between the Au 9 clusters and the TiO 2 (001) surface. Importantly, the electron transfer from the Au 9 clusters to the TiO 2 support occurs mainly through Au-O 2c interactions, which are mainly localized at the contact layer of the Au 9 clusters. These conclusions are useful to understand various physical and chemical properties of noble metal clusters loaded onto an oxide surface, and helpful to design novel metal/semiconductor functional composite materials and devices.

The contribution of dissolving star clusters to the population of ultra faint objects in the outer halo of the Milky Way

NASA Astrophysics Data System (ADS)

Contenta, Filippo; Gieles, Mark; Balbinot, Eduardo; Collins, Michelle L. M.

2017-04-01

In the last decade, several ultra faint objects (UFOs, MV ≳ -3.5) have been discovered in the outer halo of the Milky Way. For some of these objects, it is not clear whether they are star clusters or (ultra faint) dwarf galaxies. In this work, we quantify the contribution of star clusters to the population of UFOs. We extrapolated the mass and Galactocentric radius distribution of the globular clusters using a population model, finding that the Milky Way contains about 3.3^{+7.3}_{-1.6} star clusters with MV ≳ -3.5 and Galactocentric radius ≥20 kpc. To understand whether dissolving clusters can appear as UFOs, we run a suite of direct N-body models, varying the orbit, the Galactic potential, the binary fraction and the black hole (BH) natal kick velocities. In the analyses, we consider observational biases such as luminosity limit, field stars and line-of-sight projection. We find that star clusters contribute to both the compact and the extended population of UFOs: clusters without BHs appear compact with radii ˜5 pc, while clusters that retain their BHs after formation have radii ≳ 20 pc. The properties of the extended clusters are remarkably similar to those of dwarf galaxies: high-inferred mass-to-light ratios due to binaries, binary properties mildly affected by dynamical evolution, no observable mass segregation and flattened stellar mass function. We conclude that the slope of the stellar mass function as a function of Galactocentric radius and the presence/absence of cold streams can discriminate between dark matter-free and dark matter-dominated UFOs.

The Secrets of the Nearest Starburst Cluster. II. The Present-Day Mass Function in NGC 3603

NASA Astrophysics Data System (ADS)

Stolte, Andrea; Brandner, Wolfgang; Brandl, Bernhard; Zinnecker, Hans

2006-07-01

Based on deep Very Large Telescope Infrared Spectrometer and Array Camera JHK photometry, we have derived the present-day mass function (MF) of the central starburst cluster NGC 3603 YC (Young Cluster) in the giant H II region NGC 3603. The effects of field contamination, individual reddening, and a possible binary contribution are investigated. The MF slopes resulting from the different methods are compared and lead to a surprisingly consistent cluster MF with a slope of Γ=-0.9+/-0.15. Analyzing different radial annuli around the cluster core, no significant change in the slope of the MF is observed. However, mass segregation in the cluster is evidenced by the increasing depletion of the high-mass tail of the stellar mass distribution with increasing radius. We discuss the indications of mass segregation with respect to the changes observed in the binned and cumulative stellar MFs and argue that the cumulative function, as well as the fraction of high- to low-mass stars, provides better indicators for mass segregation than the MF slope alone. Finally, the observed MF and starburst morphology of NGC 3603 YC are discussed in the context of massive local star-forming regions such as the Galactic center Arches cluster, R136/30 Dor in the LMC, and the Orion Trapezium cluster, all providing resolved templates for extragalactic star formation. Despite the similarity in the observed MF slopes, dynamical considerations suggest that the starburst clusters do not form gravitationally bound systems over a Hubble time. Both the environment (gravitational potential of the Milky Way) and the concentration of stars in the cluster core determine the dynamical stability of a dense star cluster, such that the long-term evolution of a starburst is not exclusively determined by the stellar evolution of its members, as frequently assumed for globular cluster systems. Based on observations obtained at the ESO Very Large Telescope on Paranal, Chile, under programs 63.I-0015 and 65.I-0135.

Computational chemistry of modified [MFe3S4] and [M2Fe2S4] clusters: assessment of trends in electronic structure and properties.

PubMed

Jensen, Kasper P; Ooi, Bee-Lean; Christensen, Hans E M

2008-12-18

The aim of this work is to understand the molecular evolution of iron-sulfur clusters in terms of electronic structure and function. Metal-substituted models of biological [Fe(4)S(4)] clusters in oxidation states [M(x)Fe(4-x)S(4)](3+/2+/1+) have been studied by density functional theory (M = Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pd, with x = 1 or 2). Most of these clusters have not been characterized before. For those that have been characterized experimentally, very good agreement is obtained, implying that also the predicted structures and properties of new clusters are accurate. Mean absolute errors are 0.024 A for bond lengths ([Fe(4)S(4)], [NiFe(3)S(4)], [CoFe(3)S(4)]) and 0.09 V for shifts in reduction potentials relative to the [Fe(4)S(4)] cluster. All structures form cuboidal geometries similar to the all-iron clusters, except the Pd-substituted clusters, which instead form highly distorted trigonal and tetragonal local sites in compromised, pseudocuboidal geometries. In contrast to other electron-transfer sites, cytochromes, blue copper proteins, and smaller iron-sulfur clusters, we find that the [Fe(4)S(4)] clusters are very insensitive to metal substitution, displaying quite small changes in reorganization energies and reduction potentials upon substitution. Thus, the [Fe(4)S(4)] clusters have an evolutionary advantage in being robust to pollution from other metals, still retaining function. We analyze in detail the electronic structure of individual clusters and rationalize spin couplings and redox activity. Often, several configurations are very close in energy, implying possible use as spin-crossover systems, and spin states are predicted accurately in all but one case ([CuFe(3)S(4)]). The results are anticipated to be helpful in defining new molecular systems with catalytic and magnetic properties.

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

Cosmological Constraints from Galaxy Clustering and the Mass-to-number Ratio of Galaxy Clusters

NASA Astrophysics Data System (ADS)

Tinker, Jeremy L.; Sheldon, Erin S.; Wechsler, Risa H.; Becker, Matthew R.; Rozo, Eduardo; Zu, Ying; Weinberg, David H.; Zehavi, Idit; Blanton, Michael R.; Busha, Michael T.; Koester, Benjamin P.

2012-01-01

We place constraints on the average density (Ω m ) and clustering amplitude (σ8) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, wp (rp ), and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our wp (rp ) measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct nonlinear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both wp (rp ) and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Ω m or σ8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, without the use of abundance information. Using wp (rp ) and M/N alone, we find Ω0.5 m σ8 = 0.465 ± 0.026, with individual constraints of Ω m = 0.29 ± 0.03 and σ8 = 0.85 ± 0.06. Combined with current cosmic microwave background data, these constraints are Ω m = 0.290 ± 0.016 and σ8 = 0.826 ± 0.020. All errors are 1σ. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG cluster sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.

From Lipid Homeostasis to Differentiation: Old and New Functions of the Zinc Cluster Proteins Ecm22, Upc2, Sut1 and Sut2.

PubMed

Joshua, Ifeoluwapo Matthew; Höfken, Thomas

2017-04-05

Zinc cluster proteins are a large family of transcriptional regulators with a wide range of biological functions. The zinc cluster proteins Ecm22, Upc2, Sut1 and Sut2 have initially been identified as regulators of sterol import in the budding yeast Saccharomyces cerevisiae . These proteins also control adaptations to anaerobic growth, sterol biosynthesis as well as filamentation and mating. Orthologs of these zinc cluster proteins have been identified in several species of Candida . Upc2 plays a critical role in antifungal resistance in these important human fungal pathogens. Upc2 is therefore an interesting potential target for novel antifungals. In this review we discuss the functions, mode of actions and regulation of Ecm22, Upc2, Sut1 and Sut2 in budding yeast and Candida .

Anharmonic effects in the quantum cluster equilibrium method

NASA Astrophysics Data System (ADS)

von Domaros, Michael; Perlt, Eva

2017-03-01

The well-established quantum cluster equilibrium (QCE) model provides a statistical thermodynamic framework to apply high-level ab initio calculations of finite cluster structures to macroscopic liquid phases using the partition function. So far, the harmonic approximation has been applied throughout the calculations. In this article, we apply an important correction in the evaluation of the one-particle partition function and account for anharmonicity. Therefore, we implemented an analytical approximation to the Morse partition function and the derivatives of its logarithm with respect to temperature, which are required for the evaluation of thermodynamic quantities. This anharmonic QCE approach has been applied to liquid hydrogen chloride and cluster distributions, and the molar volume, the volumetric thermal expansion coefficient, and the isobaric heat capacity have been calculated. An improved description for all properties is observed if anharmonic effects are considered.

Exploring N-Rich Phases in Li(x)N(y) Clusters for Hydrogen Storage at Nanoscale.

PubMed

Bhattacharya, Amrita; Bhattacharya, Saswata

2015-09-17

We have performed cascade genetic algorithm and ab initio atomistic thermodynamics under the framework of first-principles-based hybrid density functional theory to study the (meta-)stability of a wide range of Li(x)N(y) clusters. We found that hybrid xc-functional is essential to address this problem as a local/semilocal functional simply fails even to predict a qualitative prediction. Most importantly, we find that though in bulk lithium nitride, the Li-rich phase, that is, Li3N, is the stable stoichiometry; in small Li(x)N(y) clusters, N-rich phases are more stable at thermodynamic equilibrium. We further show that these N-rich clusters are promising hydrogen storage material because of their easy adsorption and desorption ability at respectively low (≤300 K) and moderately high temperature (≥600 K).

Block clustering based on difference of convex functions (DC) programming and DC algorithms.

PubMed

Le, Hoai Minh; Le Thi, Hoai An; Dinh, Tao Pham; Huynh, Van Ngai

2013-10-01

We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.

Functionalizing graphene by embedded boron clusters

NASA Astrophysics Data System (ADS)

Quandt, Alexander; Özdoğan, Cem; Kunstmann, Jens; Fehske, Holger

2008-08-01

We present a model system that might serve as a blueprint for the controlled layout of graphene based nanodevices. The systems consists of chains of B7 clusters implanted in a graphene matrix, where the boron clusters are not directly connected. We show that the graphene matrix easily accepts these alternating B7-C6 chains and that the implanted boron components may dramatically modify the electronic properties of graphene based nanomaterials. This suggests a functionalization of graphene nanomaterials, where the semiconducting properties might be supplemented by parts of the graphene matrix itself, but the basic wiring will be provided by alternating chains of implanted boron clusters that connect these areas.

Ab initio calculation of one-nucleon halo states

NASA Astrophysics Data System (ADS)

Rodkin, D. M.; Tchuvil'sky, Yu M.

2018-02-01

We develop an approach to microscopic and ab initio description of clustered systems, states with halo nucleon and one-nucleon resonances. For these purposes a basis combining ordinary shell-model components and cluster-channel terms is built up. The transformation of clustered wave functions to the uniform Slater-determinant type is performed using the concept of cluster coefficients. The resulting basis of orthonormalized wave functions is used for calculating the eigenvalues and the eigenvectors of Hamiltonians built in the framework of ab initio approaches. Calculations of resonance and halo states of 5He, 9Be and 9B nuclei demonstrate that the approach is workable and labor-saving.

Impact-parameter dependence of the energy loss of fast molecular clusters in hydrogen

NASA Astrophysics Data System (ADS)

Fadanelli, R. C.; Grande, P. L.; Schiwietz, G.

2008-03-01

The electronic energy loss of molecular clusters as a function of impact parameter is far less understood than atomic energy losses. For instance, there are no analytical expressions for the energy loss as a function of impact parameter for cluster ions. In this work, we describe two procedures to evaluate the combined energy loss of molecules: Ab initio calculations within the semiclassical approximation and the coupled-channels method using atomic orbitals; and simplified models for the electronic cluster energy loss as a function of the impact parameter, namely the molecular perturbative convolution approximation (MPCA, an extension of the corresponding atomic model PCA) and the molecular unitary convolution approximation (MUCA, a molecular extension of the previous unitary convolution approximation UCA). In this work, an improved ansatz for MPCA is proposed, extending its validity for very compact clusters. For the simplified models, the physical inputs are the oscillators strengths of the target atoms and the target-electron density. The results from these models applied to an atomic hydrogen target yield remarkable agreement with their corresponding ab initio counterparts for different angles between cluster axis and velocity direction at specific energies of 150 and 300 keV/u.

Identifying the heterogeneity of young adult rhinitis through cluster analysis in the Isle of Wight birth cohort.

PubMed

Kurukulaaratchy, Ramesh J; Zhang, Hongmei; Patil, Veeresh; Raza, Abid; Karmaus, Wilfried; Ewart, Susan; Arshad, S Hasan

2015-01-01

Rhinitis affects many young adults and often shows comorbidity with asthma. We hypothesized that young adult rhinitis, like asthma, exhibits clinical heterogeneity identifiable by means of cluster analysis. Participants in the Isle of Wight birth cohort (n = 1456) were assessed at 1, 2, 4, 10, and 18 years of age. Cluster analysis was performed on those with rhinitis at age 18 years (n = 468) by using 13 variables defining clinical characteristics. Four clusters were identified. Patients in cluster 1 (n = 128 [27.4%]; ie, moderate childhood-onset rhinitis) had high atopy and eczema prevalence and high total IgE levels but low asthma prevalence. They showed the best lung function at 18 years of age, with normal fraction of exhaled nitric oxide (Feno), low bronchial hyperresponsiveness (BHR), and low bronchodilator reversibility (BDR) but high rhinitis symptoms and treatment. Patients in cluster 2 (n = 199 [42.5%]; ie, mild-adolescence-onset female rhinitis) had the lowest prevalence of comorbid atopy, asthma, and eczema. They had normal lung function and low BHR, BDR, Feno values, and total IgE levels plus low rhinitis symptoms, severity, and treatment. Patients in cluster 3 (n = 59 [12.6%]; ie, severe earliest-onset rhinitis with asthma) had the youngest rhinitis onset plus the highest comorbid asthma (of simultaneous onset) and atopy. They showed the most obstructed lung function with high BHR, BDR, and Feno values plus high rhinitis symptoms, severity, and treatment. Patient 4 in cluster 4 (n = 82 [17.5%]; ie, moderate childhood-onset male rhinitis with asthma) had high atopy, intermediate asthma, and low eczema. They had impaired lung function with high Feno values and total IgE levels but intermediate BHR and BDR. They had moderate rhinitis symptoms. Clinically distinctive adolescent rhinitis clusters are apparent with varying sex and asthma associations plus differing rhinitis severity and treatment needs. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Comparison of Cluster, Slab, and Analytic Potential Models for the Dimethyl Methylphosphonate (DMMP)/TiO2 (110) Intermolecular Interaction

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

Yang, Li; Tunega, Daniel; Xu, Lai

2013-08-29

In a previous study (J. Phys. Chem. C 2011, 115, 12403) cluster models for the TiO2 rutile (110) surface and MP2 calculations were used to develop an analytic potential energy function for dimethyl methylphosphonate (DMMP) interacting with this surface. In the work presented here, this analytic potential and MP2 cluster models are compared with DFT "slab" calculations for DMMP interacting with the TiO2 (110) surface and with DFT cluster models for the TiO2 (110) surface. The DFT slab calculations were performed with the PW91 and PBE functionals. The analytic potential gives DMMP/ TiO2 (110) potential energy curves in excellent agreementmore » with those obtained from the slab calculations. The cluster models for the TiO2 (110) surface, used for the MP2 calculations, were extended to DFT calculations with the B3LYP, PW91, and PBE functional. These DFT calculations do not give DMMP/TiO2 (110) interaction energies which agree with those from the DFT slab calculations. Analyses of the wave functions for these cluster models show that they do not accurately represent the HOMO and LUMO for the surface, which should be 2p and 3d orbitals, respectively, and the models also do not give an accurate band gap. The MP2 cluster models do not accurately represent the LUMO and that they give accurate DMMP/TiO2 (110) interaction energies is apparently fortuitous, arising from their highly inaccurate band gaps. Accurate cluster models, consisting of 7, 10, and 15 Ti-atoms and which have the correct HOMO and LUMO properties, are proposed. The work presented here illustrates the care that must be taken in "constructing" cluster models which accurately model surfaces.« less

Stepwise Assembly and Characterization of DNA Linked Two-Color Quantum Dot Clusters.

PubMed

Coopersmith, Kaitlin; Han, Hyunjoo; Maye, Mathew M

2015-07-14

The DNA-mediated self-assembly of multicolor quantum dot (QD) clusters via a stepwise approach is described. The CdSe/ZnS QDs were synthesized and functionalized with an amphiphilic copolymer, followed by ssDNA conjugation. At each functionalization step, the QDs were purified via gradient ultracentrifugation, which was found to remove excess polymer and QD aggregates, allowing for improved conjugation yields and assembly reactivity. The QDs were then assembled and disassembled in a stepwise manner at a ssDNA functionalized magnetic colloid, which provided a convenient way to remove unreacted QDs and ssDNA impurities. After assembly/disassembly, the clusters' optical characteristics were studied by fluorescence spectroscopy and the assembly morphology and stoichiometry was imaged via electron microscopy. The results indicate that a significant amount of QD-to-QD energy transfer occurred in the clusters, which was studied as a function of increasing acceptor-to-donor ratios, resulting in increased QD acceptor emission intensities compared to controls.

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Optimization of self-interstitial clusters in 3C-SiC with genetic algorithm

NASA Astrophysics Data System (ADS)

Ko, Hyunseok; Kaczmarowski, Amy; Szlufarska, Izabela; Morgan, Dane

2017-08-01

Under irradiation, SiC develops damage commonly referred to as black spot defects, which are speculated to be self-interstitial atom clusters. To understand the evolution of these defect clusters and their impacts (e.g., through radiation induced swelling) on the performance of SiC in nuclear applications, it is important to identify the cluster composition, structure, and shape. In this work the genetic algorithm code StructOpt was utilized to identify groundstate cluster structures in 3C-SiC. The genetic algorithm was used to explore clusters of up to ∼30 interstitials of C-only, Si-only, and Si-C mixtures embedded in the SiC lattice. We performed the structure search using Hamiltonians from both density functional theory and empirical potentials. The thermodynamic stability of clusters was investigated in terms of their composition (with a focus on Si-only, C-only, and stoichiometric) and shape (spherical vs. planar), as a function of the cluster size (n). Our results suggest that large Si-only clusters are likely unstable, and clusters are predominantly C-only for n ≤ 10 and stoichiometric for n > 10. The results imply that there is an evolution of the shape of the most stable clusters, where small clusters are stable in more spherical geometries while larger clusters are stable in more planar configurations. We also provide an estimated energy vs. size relationship, E(n), for use in future analysis.

Dispersion- and Exchange-Corrected Density Functional Theory for Sodium Ion Hydration.

PubMed

Soniat, Marielle; Rogers, David M; Rempe, Susan B

2015-07-14

A challenge in density functional theory is developing functionals that simultaneously describe intermolecular electron correlation and electron delocalization. Recent exchange-correlation functionals address those two issues by adding corrections important at long ranges: an atom-centered pairwise dispersion term to account for correlation and a modified long-range component of the electron exchange term to correct for delocalization. Here we investigate how those corrections influence the accuracy of binding free energy predictions for sodium-water clusters. We find that the dual-corrected ωB97X-D functional gives cluster binding energies closest to high-level ab initio methods (CCSD(T)). Binding energy decomposition shows that the ωB97X-D functional predicts the smallest ion-water (pairwise) interaction energy and larger multibody contributions for a four-water cluster than most other functionals - a trend consistent with CCSD(T) results. Also, ωB97X-D produces the smallest amounts of charge transfer and the least polarizable waters of the density functionals studied, which mimics the lower polarizability of CCSD. When compared with experimental binding free energies, however, the exchange-corrected CAM-B3LYP functional performs best (error <1 kcal/mol), possibly because of its parametrization to experimental formation enthalpies. For clusters containing more than four waters, "split-shell" coordination must be considered to obtain accurate free energies in comparison with experiment.

Wavelet-based clustering of resting state MRI data in the rat.

PubMed

Medda, Alessio; Hoffmann, Lukas; Magnuson, Matthew; Thompson, Garth; Pan, Wen-Ju; Keilholz, Shella

2016-01-01

While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas. Copyright © 2015 Elsevier Inc. All rights reserved.

The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1990-01-01

The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

Investigation of dislocation cluster evolution during directional solidification of multicrystalline silicon

NASA Astrophysics Data System (ADS)

Oriwol, Daniel; Trempa, Matthias; Sylla, Lamine; Leipner, Hartmut S.

2017-04-01

Dislocation clusters are the main crystal defects in multicrystalline silicon and are detrimental for solar cell efficiency. They were formed during the silicon ingot casting due to the relaxation of strain energy. The evolution of the dislocation clusters was studied by means of automated analysing tools of the standard wafer and cell production giving information about the cluster development as a function of the ingot height. Due to the observation of the whole wafer surface the point of view is of macroscopic nature. It was found that the dislocations tend to build clusters of high density which usually expand in diameter as a function of ingot height. According to their structure the dislocation clusters can be divided into light and dense clusters. The appearance of both types shows a clear dependence on the orientation of the grain growth direction. Additionally, a process of annihilation of dislocation clusters during the crystallization has been observed. To complement the macroscopic description, the dislocation clusters were also investigates by TEM. It is shown that the dislocations within the subgrain boundaries are closely arranged. Distances of 40-30 nm were found. These results lead to the conclusion that the dislocation density within the cluster structure is impossible to quantify by means of etch pit counting.

Iron binding activity is essential for the function of IscA in iron-sulphur cluster biogenesis

PubMed Central

Landry, Aaron P.; Cheng, Zishuo; Ding, Huangen

2013-01-01

Iron-sulphur cluster biogenesis requires coordinated delivery of iron and sulphur to scaffold proteins, followed by transfer of the assembled clusters from scaffold proteins to target proteins. This complex process is accomplished by a group of dedicated iron-sulphur cluster assembly proteins that are conserved from bacteria to humans. While sulphur in iron-sulphur clusters is provided by L-cysteine via cysteine desulfurase, the iron donor(s) for iron-sulphur cluster assembly remains largely elusive. Here we report that among the primary iron-sulphur cluster assembly proteins, IscA has a unique and strong binding activity for mononuclear iron in vitro and in vivo. Furthermore, the ferric iron centre tightly bound in IscA can be readily extruded by L-cysteine, followed by reduction to ferrous iron for iron-sulphur cluster biogenesis. Substitution of the highly conserved residue tyrosine 40 with phenylalanine (Y40F) in IscA results in a mutant protein that has a diminished iron binding affinity but retains the iron-sulphur cluster binding activity. Genetic complementation studies show that the IscA Y40F mutant is inactive in vivo, suggesting that the iron binding activity is essential for the function of IscA in iron-sulphur cluster biogenesis. PMID:23258274

Geometrical, electronic, and magnetic properties of CunFe (n=1-12) clusters: A density functional study

NASA Astrophysics Data System (ADS)

Ling, Wang; Dong, Die; Shi-Jian, Wang; Zheng-Quan, Zhao

2015-01-01

The geometrical, electronic, and magnetic properties of small CunFe (n=1-12) clusters have been investigated by using density functional method B3LYP and LanL2DZ basis set. The structural search reveals that Fe atoms in low-energy CunFe isomers tend to occupy the position with the maximum coordination number. The ground state CunFe clusters possess planar structure for n=2-5 and three-dimensional (3D) structure for n=6-12. The electronic properties of CunFe clusters are analyzed through the averaged binding energy, the second-order energy difference and HOMO-LUMO energy gap. It is found that the magic numbers of stability are 1, 3, 7 and 9 for the ground state CunFe clusters. The energy gap of Fe-encapsulated cage clusters is smaller than that of other configurations. The Cu5Fe and Cu7Fe clusters have a very large energy gap (>2.4 eV). The vertical ionization potential (VIP), electron affinity (EA) and photoelectron spectra are also calculated and simulated theoretically for all the ground-state clusters. The magnetic moment analyses for the ground-state CunFe clusters show that Fe atom can enhance the magnetic moment of the host cluster and carries most of the total magnetic moment.

Iron binding activity is essential for the function of IscA in iron-sulphur cluster biogenesis.

PubMed

Landry, Aaron P; Cheng, Zishuo; Ding, Huangen

2013-03-07

Iron-sulphur cluster biogenesis requires coordinated delivery of iron and sulphur to scaffold proteins, followed by transfer of the assembled clusters from scaffold proteins to target proteins. This complex process is accomplished by a group of dedicated iron-sulphur cluster assembly proteins that are conserved from bacteria to humans. While sulphur in iron-sulphur clusters is provided by L-cysteine via cysteine desulfurase, the iron donor(s) for iron-sulphur cluster assembly remains largely elusive. Here we report that among the primary iron-sulphur cluster assembly proteins, IscA has a unique and strong binding activity for mononuclear iron in vitro and in vivo. Furthermore, the ferric iron centre tightly bound in IscA can be readily extruded by l-cysteine, followed by reduction to ferrous iron for iron-sulphur cluster biogenesis. Substitution of the highly conserved residue tyrosine 40 with phenylalanine (Y40F) in IscA results in a mutant protein that has a diminished iron binding affinity but retains the iron-sulphur cluster binding activity. Genetic complementation studies show that the IscA Y40F mutant is inactive in vivo, suggesting that the iron binding activity is essential for the function of IscA in iron-sulphur cluster biogenesis.

Analysis of the convective evaporation of nondilute clusters of drops

NASA Technical Reports Server (NTRS)

Bellan, J.; Harstad, K.

1987-01-01

The penetration distance of an outer flow into a drop cluster volume is the critical, evaporation mode-controlling parameter in the present model for nondilute drop clusters' convective evaporation. The model is found to perform well for such low penetration distances as those obtained for dense clusters in hot environments and low relative velocities between the outer gases and the cluster. For large penetration distances, however, the predictive power of the model deteriorates; in addition, the evaporation time is found to be a weak function of the initial relative velocity and a strong function of the initial drop temperature. The results generally show that the interior drop temperature was transient throughout the drop lifetime, although temperature nonuniformities persisted up to the first third of the total evaporation time at most.

Why do gallium clusters have a higher melting point than the bulk?

PubMed

Chacko, S; Joshi, Kavita; Kanhere, D G; Blundell, S A

2004-04-02

Density functional molecular dynamical simulations have been performed on Ga17 and Ga13 clusters to understand the recently observed higher-than-bulk melting temperatures in small gallium clusters [Phys. Rev. Lett. 91, 215508 (2003)

Centromere proteins CENP-C and CAL1 functionally interact in meiosis for centromere clustering, pairing, and chromosome segregation.

PubMed

Unhavaithaya, Yingdee; Orr-Weaver, Terry L

2013-12-03

Meiotic chromosome segregation involves pairing and segregation of homologous chromosomes in the first division and segregation of sister chromatids in the second division. Although it is known that the centromere and kinetochore are responsible for chromosome movement in meiosis as in mitosis, potential specialized meiotic functions are being uncovered. Centromere pairing early in meiosis I, even between nonhomologous chromosomes, and clustering of centromeres can promote proper homolog associations in meiosis I in yeast, plants, and Drosophila. It was not known, however, whether centromere proteins are required for this clustering. We exploited Drosophila mutants for the centromere proteins centromere protein-C (CENP-C) and chromosome alignment 1 (CAL1) to demonstrate that a functional centromere is needed for centromere clustering and pairing. The cenp-C and cal1 mutations result in C-terminal truncations, removing the domains through which these two proteins interact. The mutants show striking genetic interactions, failing to complement as double heterozygotes, resulting in disrupted centromere clustering and meiotic nondisjunction. The cluster of meiotic centromeres localizes to the nucleolus, and this association requires centromere function. In Drosophila, synaptonemal complex (SC) formation can initiate from the centromere, and the SC is retained at the centromere after it disassembles from the chromosome arms. Although functional CENP-C and CAL1 are dispensable for assembly of the SC, they are required for subsequent retention of the SC at the centromere. These results show that integral centromere proteins are required for nuclear position and intercentromere associations in meiosis.

The Second Most Distant Cluster of Galaxies in the Extended Medium Sensitivity Survey

NASA Technical Reports Server (NTRS)

Donahue, Megan; Voit, G. Mark; Scharf, Caleb A.; Gioia, Isabella M.; Mullis, Christopher R.; Hughes, John P.; Stocke, John T.

1999-01-01

We report on our ASCA, Keck, and ROSAT observations of MS 1137.5+6625, the second most distant cluster of galaxies in the Einstein Extended Medium Sensitivity Survey (EMSS), at redshift 0.78. We now have a full set of X-ray temperatures, optical velocity dispersions, and X-ray images for a complete, high-redshift sample of clusters of galaxies drawn from the EMSS. Our ASCA observations of MS 1137.5 +6625 yield a temperature of 5.7 (+2.1)(-1.1) keV and a metallicity of 0.43 (+40)(-3.7) solar, with 90% confidence limits. Keck II spectroscopy of 22 cluster members reveals a velocity dispersion of 884 (+185)(-124) km 24/s. This cluster is the most distant in the sample with a detected iron line. We also derive a mean abundance at z = 0.8 by simultaneously fitting X-ray data for the two z = 0.8 clusters, and obtain an abundance of Z(sub Fe) = 0.33 (+.26)(-.23). Our ROSAT observations show that MS 1137.5+6625 is regular and highly centrally concentrated. Fitting of a Beta model to the X-ray surface brightness yields a core radius of only 71/h kpc (q(sub o) = 0.1) with Beta = 0.70(+.45)(-.15) The gas mass interior to 0.5/h Mpc is thus 1.2 (+0.2)(-0.3) X 10(exp 13) h(exp - 5/2) Solar Mass (q(sub o) = 0.1). If the cluster's gas is nearly isothermal and in hydrostatic equilibrium with the cluster potential, the total mass of the cluster within this same region is 2.1(+1.5)(-0.8) X 10exp 14)/h Solar Mass, giving a gas fraction of 0.06 +/-0.04 h (exp -3/2). This cluster is the highest redshift EMSS cluster showing evidence for a possible cooling flow (about 20-400 Solar Mass/yr). The velocity dispersion, temperature, gas fraction, and iron abundance of MS 1137.5+6625 are all statistically the same as those properties in lower red- shift clusters of similar luminosity. With this cluster's temperature now in hand, we derive a high-redshift temperature function for EMSS clusters at 0.5 < z < 0.9 and compare it with temperature functions at lower redshifts, showing that the evolution of the temperature function is relatively modest. Supplementing our high-redshift sample with other data from the literature, we demonstrate that neither the cluster luminosity-temperature relation, nor cluster metallicities, nor the cluster gas evolved with redshift. The very modest degree of evolution in the luminosity-temperature relation inferred from these data is inconsistent with the absence of evolution in the X-ray luminosity functions derived from ROSAT cluster surveys if a critical density structure formation model is assumed.

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-12-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Topological defect clustering and plastic deformation mechanisms in functionalized graphene

NASA Astrophysics Data System (ADS)

Nunes, Ricardo; Araujo, Joice; Chacham, Helio

2011-03-01

We present ab initio results suggesting that strain plays a central role in the clustering of topological defects in strained and functionalized graphene models. We apply strain onto the topological-defect graphene networks from our previous work, and obtain topological-defect clustering patterns which are in excellent agreement with recent observations in samples of reduced graphene oxide. In our models, the graphene layer, containing an initial concentration of isolated topological defects, is covered by hydrogen or hydroxyl groups. Our results also suggest a rich variety of plastic deformation mechanism in functionalized graphene systems. We acknowledge support from the Brazilian agencies: CNPq, Fapemig, and INCT-Materiais de Carbono.

Classifying proteins into functional groups based on all-versus-all BLAST of 10 million proteins.

PubMed

Kolker, Natali; Higdon, Roger; Broomall, William; Stanberry, Larissa; Welch, Dean; Lu, Wei; Haynes, Winston; Barga, Roger; Kolker, Eugene

2011-01-01

To address the monumental challenge of assigning function to millions of sequenced proteins, we completed the first of a kind all-versus-all sequence alignments using BLAST for 9.9 million proteins in the UniRef100 database. Microsoft Windows Azure produced over 3 billion filtered records in 6 days using 475 eight-core virtual machines. Protein classification into functional groups was then performed using Hive and custom jars implemented on top of Apache Hadoop utilizing the MapReduce paradigm. First, using the Clusters of Orthologous Genes (COG) database, a length normalized bit score (LNBS) was determined to be the best similarity measure for classification of proteins. LNBS achieved sensitivity and specificity of 98% each. Second, out of 5.1 million bacterial proteins, about two-thirds were assigned to significantly extended COG groups, encompassing 30 times more assigned proteins. Third, the remaining proteins were classified into protein functional groups using an innovative implementation of a single-linkage algorithm on an in-house Hadoop compute cluster. This implementation significantly reduces the run time for nonindexed queries and optimizes efficient clustering on a large scale. The performance was also verified on Amazon Elastic MapReduce. This clustering assigned nearly 2 million proteins to approximately half a million different functional groups. A similar approach was applied to classify 2.8 million eukaryotic sequences resulting in over 1 million proteins being assign to existing KOG groups and the remainder clustered into 100,000 functional groups.

Identification of alterations associated with age in the clustering structure of functional brain networks.

PubMed

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Time dependent density functional calculation of plasmon response in clusters

NASA Astrophysics Data System (ADS)

Wang, Feng; Zhang, Feng-Shou; Eric, Suraud

2003-02-01

We have introduced a theoretical scheme for the efficient description of the optical response of a cluster based on the time-dependent density functional theory. The practical implementation is done by means of the fully fledged time-dependent local density approximation scheme, which is solved directly in the time domain without any linearization. As an example we consider the simple Na2 cluster and compute its surface plasmon photoabsorption cross section, which is in good agreement with the experiments.

Density functional study of structural and electronic properties of bimetallic silver-gold clusters: Comparison with pure gold and silver clusters

NASA Astrophysics Data System (ADS)

Bonacic-Koutecky, Vlasta; Burda, Jaroslav; Mitric, Roland; Ge, Maofa; Zampella, Giuseppe; Fantucci, Piercarlo

2002-08-01

Bimetallic silver-gold clusters offer an excellent opportunity to study changes in metallic versus "ionic" properties involving charge transfer as a function of the size and the composition, particularly when compared to pure silver and gold clusters. We have determined structures, ionization potentials, and vertical detachment energies for neutral and charged bimetallic AgmAun 3[less-than-or-equal](m+n)[less-than-or-equal]5 clusters. Calculated VDE values compare well with available experimental data. In the stable structures of these clusters Au atoms assume positions which favor the charge transfer from Ag atoms. Heteronuclear bonding is usually preferred to homonuclear bonding in clusters with equal numbers of hetero atoms. In fact, stable structures of neutral Ag2Au2, Ag3Au3, and Ag4Au4 clusters are characterized by the maximum number of hetero bonds and peripheral positions of Au atoms. Bimetallic tetramer as well as hexamer are planar and have common structural properties with corresponding one-component systems, while Ag4Au4 and Ag8 have 3D forms in contrast to Au8 which assumes planar structure. At the density functional level of theory we have shown that this is due to participation of d electrons in bonding of pure Aun clusters while s electrons dominate bonding in pure Agm as well as in bimetallic clusters. In fact, Aun clusters remain planar for larger sizes than Agm and AgnAun clusters. Segregation between two components in bimetallic systems is not favorable, as shown in the example of Ag5Au5 cluster. We have found that the structures of bimetallic clusters with 20 atoms Ag10Au10 and Ag12Au8 are characterized by negatively charged Au subunits embedded in Ag environment. In the latter case, the shape of Au8 is related to a pentagonal bipyramid capped by one atom and contains three exposed negatively charged Au atoms. They might be suitable for activating reactions relevant to catalysis. According to our findings the charge transfer in bimetallic clusters is responsible for formation of negatively charged gold subunits which are expected to be reactive, a situation similar to that of gold clusters supported on metal oxides.

Biased immunoglobulin light chain gene usage in the shark1

PubMed Central

Iacoangeli, Anna; Lui, Anita; Naik, Ushma; Ohta, Yuko; Flajnik, Martin; Hsu, Ellen

2015-01-01

This study of a large family of kappa light (L) chain clusters in nurse shark completes the characterization of its classical immunoglobulin (Ig) gene content (two heavy chain classes, mu and omega, and four L chain isotopes, kappa, lambda, sigma, and sigma-2). The shark kappa clusters are minigenes consisting of a simple VL-JL-CL array, where V to J recombination occurs over a ~500 bp interval, and functional clusters are widely separated by at least 100 kb. Six out of ca. 39 kappa clusters are pre-rearranged in the germline (GL-joined). Unlike the complex gene organization and multistep assembly process of Ig in mammals, each shark Ig rearrangement, somatic or in the germline, appears to be an independent event localized to the minigene. This study examined the expression of functional, non-productive, and sterile transcripts of the kappa clusters compared to the other three L chain isotypes. Kappa cluster usage was investigated in young sharks, and a skewed pattern of split gene expression was observed, one similar in functional and non-productive rearrangements. These results show that the individual activation of the spatially distant kappa clusters is non-random. Although both split and GL-joined kappa genes are expressed, the latter are prominent in young animals and wane with age. We speculate that, in the shark, the differential activation of the multiple isotypes can be advantageously used in receptor editing. PMID:26342033

Biased Immunoglobulin Light Chain Gene Usage in the Shark.

PubMed

Iacoangeli, Anna; Lui, Anita; Naik, Ushma; Ohta, Yuko; Flajnik, Martin; Hsu, Ellen

2015-10-15

This study of a large family of κ L chain clusters in nurse shark completes the characterization of its classical Ig gene content (two H chain isotypes, μ and ω, and four L chain isotypes, κ, λ, σ, and σ-2). The shark κ clusters are minigenes consisting of a simple VL-JL-CL array, where V to J recombination occurs over an ~500-bp interval, and functional clusters are widely separated by at least 100 kb. Six out of ~39 κ clusters are prerearranged in the germline (germline joined). Unlike the complex gene organization and multistep assembly process of Ig in mammals, each shark Ig rearrangement, somatic or in the germline, appears to be an independent event localized to the minigene. This study examined the expression of functional, nonproductive, and sterile transcripts of the κ clusters compared with the other three L chain isotypes. κ cluster usage was investigated in young sharks, and a skewed pattern of split gene expression was observed, one similar in functional and nonproductive rearrangements. These results show that the individual activation of the spatially distant κ clusters is nonrandom. Although both split and germline-joined κ genes are expressed, the latter are prominent in young animals and wane with age. We speculate that, in the shark, the differential activation of the multiple isotypes can be advantageously used in receptor editing. Copyright © 2015 by The American Association of Immunologists, Inc.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Associations Between Personality Disorder Characteristics, Psychological Symptoms, and Sexual Functioning in Young Women.

PubMed

Grauvogl, Andrea; Pelzer, Britt; Radder, Veerle; van Lankveld, Jacques

2018-02-01

Recently, the etiology of sexual dysfunctions in women has been approached from different angles. In clinical practice and in previous studies, it has been observed that women with sexual problems experience anxiety problems and express more rigid and perfectionistic personality traits than women without these problems. To investigate whether personality disorder characteristics according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) and psychological symptoms are associated with sexual problems in women. 188 women 18 to 25 years old participated in this cross-sectional study. Questionnaires measuring sexual functioning (Female Sexual Function Index), personality disorder characteristics (Assessment of DSM-IV-TR Personality Disorders Questionnaire), and psychological symptoms (Brief Symptom Inventory and Center for Epidemiological Studies Depression Scale) were used. The main outcome measure used was sexual functioning assessed by self-report. Results, using analysis of variance, indicated that women with sexual problems report significantly more cluster A (specifically schizoid) and C (specifically avoidant and obsessive-compulsive) personality disorder characteristics than women without sexual problems. Furthermore, using multiple regression analyses, higher cluster A (specifically schizoid) and lower cluster B (specifically borderline and antisocial) personality disorder characteristics indicated lower levels of sexual functioning. Psychological symptoms partly mediated the effect of cluster A personality disorder characteristics on sexual functioning. The results of this study indicate that clinical practice should extend its scope by focusing more on improving adaptive personality characteristics, such as extraversion and individualism seen in cluster B personality characteristics, and decreasing the perfectionistic, introvert, and self-doubting characteristics seen in cluster C personality characteristics. Because of the correlational design and use of self-report measures, causal relations cannot be established between personality disorder characteristics and sexual functioning. Overall, the results indicate that personality disorder characteristics can play an important associative role in the development and maintenance of sexual functioning problems in women. Grauvogl A, Pelzer B, Radder V, van Lankveld J. Associations Between Personality Disorder Characteristics, Psychological Symptoms, and Sexual Functioning in Young Women. J Sex Med 2018;15:192-200. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Volume shift and charge instability of simple-metal clusters

NASA Astrophysics Data System (ADS)

Brajczewska, M.; Vieira, A.; Fiolhais, C.; Perdew, J. P.

1996-12-01

Experiment indicates that small clusters show changes (mostly contractions) of the bond lengths with respect to bulk values. We use the stabilized jellium model to study the self-expansion and self-compression of spherical clusters (neutral or ionized) of simple metals. Results from Kohn - Sham density functional theory are presented for small clusters of Al and Na, including negatively-charged ones. We also examine the stability of clusters with respect to charging.

Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications.

PubMed

Howrylak, Judie A; Fuhlbrigge, Anne L; Strunk, Robert C; Zeiger, Robert S; Weiss, Scott T; Raby, Benjamin A

2014-05-01

Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P < .0001) or additional controller medications (P = .001), as well as longitudinal differences in pulmonary function (P < .0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P = .02) and nedocromil (P = .01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P = .12) and nedocromil (P = .56) compared with placebo. Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference

PubMed Central

Stone, Eric A.; Ayroles, Julien F.

2009-01-01

In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432

Symptom Clusters in People Living with HIV Attending Five Palliative Care Facilities in Two Sub-Saharan African Countries: A Hierarchical Cluster Analysis.

PubMed

Moens, Katrien; Siegert, Richard J; Taylor, Steve; Namisango, Eve; Harding, Richard

2015-01-01

Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries. Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores. Among the sample (N=217) the mean age was 36.5 (SD 9.0), 73.2% were female, and 49.1% were on antiretroviral therapy (ART). The cluster analysis produced five symptom clusters identified as: 1) dermatological; 2) generalised anxiety and elimination; 3) social and image; 4) persistently present; and 5) a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, p<0.001); being on ART (highest proportions for clusters two and three, p=0.012); global distress (F=26.8, p<0.001), physical distress (F=36.3, p<0.001) and psychological distress subscale (F=21.8, p<0.001) (all subscales worst for cluster one, best for cluster four). The greatest burden is associated with cluster one, and should be prioritised in clinical management. Further symptom cluster research in people living with HIV with longitudinally collected symptom data to test cluster stability and identify common symptom trajectories is recommended.

PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1

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

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1more » Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.« less

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

NASA Technical Reports Server (NTRS)

2004-01-01

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

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

Chandar, Rupali; Fall, S. Michael; Whitmore, Bradley C., E-mail: Rupali.Chandar@utoledo.ed, E-mail: fall@stsci.ed, E-mail: whitmore@stsci.ed

We compare the observed bivariate distribution of masses (M) and ages (tau) of star clusters in the Large Magellanic Cloud (LMC) with the predicted distributions g(M, tau) from three idealized models for the disruption of star clusters: (1) sudden mass-dependent disruption, (2) gradual mass-dependent disruption, and (3) gradual mass-independent disruption. The model with mass-independent disruption provides a good, first-order description of these cluster populations, with g(M, tau) {proportional_to} M {sup beta}tau{sup g}amma, beta = -1.8 +- 0.2 and gamma = -0.8 +- 0.2, at least for clusters with ages tau {approx}< 10{sup 9} yr and masses M {approx}> 10{sup 3}more » M{sub sun} (more specifically, tau {approx}< 10{sup 7}(M/10{sup 2} M{sub sun}){sup 1.3} yr). This model predicts that the clusters should have a power-law luminosity function, dN/dL {proportional_to} L {sup -1.8}, in agreement with observations. The first two models, on the other hand, fare poorly when describing the observations, refuting previous claims that mass-dependent disruption of star clusters is observed in the LMC over the studied M-tau domain. Clusters in the SMC can be described by the same g(M, tau) distribution as for the LMC, but with smaller samples and hence larger uncertainties. The successful g(M, tau) model for clusters in the Magellanic Clouds is virtually the same as the one for clusters in the merging Antennae galaxies, but extends the domain of validity to lower masses and to older ages. This indicates that the dominant disruption processes are similar in these very different galaxies over at least tau {approx}< 10{sup 8} yr and possibly tau {approx}< 10{sup 9} yr. The mass functions for young clusters in the LMC are power laws, while that for ancient globular clusters is peaked. We show that the observed shapes of these mass functions are consistent with expectations from the simple evaporation model presented by McLaughlin and Fall.« less

PRIMUS: Galaxy Clustering as a Function of Luminosity and Color at 0.2 < z < 1

NASA Astrophysics Data System (ADS)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Moustakas, John; Aird, James; Blanton, Michael R.; Bray, Aaron D.; Cool, Richard J.; Eisenstein, Daniel J.; Mendez, Alexander J.; Wong, Kenneth C.; Zhu, Guangtun

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(rp , π) and wp (rp ), using volume-limited samples constructed from a parent sample of over ~130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg2 of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h -1 < rp < 1 Mpc h -1) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b gal ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ~ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that "cosmic variance" can be a significant source of uncertainty for high-redshift clustering measurements.

The Effects of Single and Close Binary Evolution on the Stellar Mass Function

NASA Astrophysics Data System (ADS)

Schneider, R. N. F.; Izzard, G. R.; de Mink, S.; Langer, N., Stolte, A., de Koter, A.; Gvaramadze, V. V.; Hussmann, B.; Liermann, A.; Sana, H.

2013-06-01

Massive stars are almost exclusively born in star clusters, where stars in a cluster are expected to be born quasi-simultaneously and with the same chemical composition. The distribution of their birth masses favors lower over higher stellar masses, such that the most massive stars are rare, and the existence of an stellar upper mass limit is still debated. The majority of massive stars are born as members of close binary systems and most of them will exchange mass with a close companion during their lifetime. We explore the influence of single and binary star evolution on the high mass end of the stellar mass function using a rapid binary evolution code. We apply our results to two massive Galactic star clusters and show how the shape of their mass functions can be used to determine cluster ages and comment on the stellar upper mass limit in view of our new findings.

Clustering and pasta phases in nuclear density functional theory

DOE PAGES

Schuetrumpf, Bastian; Zhang, Chunli; Nazarewicz, Witold

2017-05-23

Nuclear density functional theory is the tool of choice in describing properties of complex nuclei and intricate phases of bulk nucleonic matter. It is a microscopic approach based on an energy density functional representing the nuclear interaction. An attractive feature of nuclear DFT is that it can be applied to both finite nuclei and pasta phases appearing in the inner crust of neutron stars. While nuclear pasta clusters in a neutron star can be easily characterized through their density distributions, the level of clustering of nucleons in a nucleus can often be difficult to assess. To this end, we usemore » the concept of nucleon localization. We demonstrate that the localization measure provides us with fingerprints of clusters in light and heavy nuclei, including fissioning systems. Furthermore we investigate the rod-like pasta phase using twist-averaged boundary conditions, which enable calculations in finite volumes accessible by state of the art DFT solvers.« less

Galaxy Cluster Bulk Flows and Collision Velocities in QUMOND

NASA Astrophysics Data System (ADS)

Katz, Harley; McGaugh, Stacy; Teuben, Peter; Angus, G. W.

2013-07-01

We examine the formation of clusters of galaxies in numerical simulations of a QUMOND cosmogony with massive sterile neutrinos. Clusters formed in these exploratory simulations develop higher velocities than those found in ΛCDM simulations. The bulk motions of clusters attain ~1000 km s-1 by low redshift, comparable to observations whereas ΛCDM simulated clusters tend to fall short. Similarly, high pairwise velocities are common in cluster-cluster collisions like the Bullet Cluster. There is also a propensity for the most massive clusters to be larger in QUMOND and to appear earlier than in ΛCDM, potentially providing an explanation for "pink elephants" like El Gordo. However, it is not obvious that the cluster mass function can be recovered.

Al7CX (X=Li-Cs) clusters: Stability and the prospect for cluster materials

NASA Astrophysics Data System (ADS)

Ashman, C.; Khanna, S. N.; Pederson, M. R.; Kortus, J.

2000-12-01

Al7C clusters, recently found to have a high-electron affinity and exceptional stability, are shown to form ionic molecules when combined with alkali-metal atoms. Our studies, based on an ab initio gradient-corrected density-functional scheme, show that Al7CX (X=Li-Cs) clusters have a very low-electron affinity and a high-ionization potential. When combined, the two- and four-atom composite clusters of Al7CLi units leave the Al7C clusters almost intact. Preliminary studies indicate that Al7CLi may be suitable to form cluster-based materials.

An exploration of links between early parenting experiences and personality disorder type and disordered personality functioning.

PubMed

Parker, G; Roy, K; Wilhelm, K; Mitchell, P; Austin, M P; Hadzi-Pavlovic, D

1999-01-01

Reports of early parenting were assessed using two measures, the Parental Bonding Index (PBI) and the Measure of Parenting Style (MOPS), in a sample of 265 patients with DSM-defined major depressive disorder. Psychiatrists then rated the extent to which sample members evidenced the personality "styles" underpinning 15 separate personality disorders, returning personality vignette scores. The extent of disordered functioning was also assessed across "parameters" and "domains" by psychiatrists, referrers, and family members, using a range of measures. Those with higher scores on vignettes measuring borderline, anxious, depressive, and self-defeating personality style rated parents as uncaring, overcontrolling, and abusive. When vignettes were consolidated into scores akin to the DSM clusters, the most consistent links between perceived dysfunctional parenting were with the Cluster C (anxious), and Cluster B (dramatic) styles and were nonsignificant for Cluster A (eccentric) style. Meeting criteria for an increasing number of personality disorder clusters was associated with increasing levels of adverse parenting. Multiple regression analyses indicated that disordered functioning (as assessed by the three independent rater groups) was most distinctly associated with paternal indifference and maternal overcontrol.

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

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

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Zhang, Gang

2013-12-15

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme ismore » confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.« less

A density functional theory study on the structural and electronic properties of PbxSbySez (x + y + z = 2, 3) clusters

NASA Astrophysics Data System (ADS)

Peköz, Rengi˙n; Erkoç, Şaki˙r

2018-01-01

The structural and electronic properties of neutral ternary PbxSbySez clusters (x + y + z = 2, 3) in their ground states have been explored by means of density functional theory calculations. The geometric structures and binding energies are systematically explored and for the most stable configurations of each cluster type vibrational frequencies, charges on atoms, energy difference between highest occupied and lowest unoccupied molecular orbitals, and the possible dissociations channels have been analyzed. Depending on being binary or ternary cluster and composition, the most energetic structures have singlet, doublet or triplet ground states, and trimers prefer to form isosceles, equilateral or scalene triangle structure.

Application of cluster technology in location-based service

NASA Astrophysics Data System (ADS)

Chen, Jing; Wang, Xiaoman; Gong, Jianya

2005-10-01

This paper introduces the principle, algorithmic and realization of the Load Balancing Technology. It also designs a clustered method in the application of Location-Based Service (LBS), and explains its function characteristics and its whole system structure, followed by some experimental comparisons, showing that the Cluster Technology could ensure a LBS's continuous running and the sharing of fault-tolerance and cluster.

Understanding and Practical Use of Ligand and Metal Exchange Reactions in Thiolate-Protected Metal Clusters to Synthesize Controlled Metal Clusters.

PubMed

Niihori, Yoshiki; Hossain, Sakiat; Sharma, Sachil; Kumar, Bharat; Kurashige, Wataru; Negishi, Yuichi

2017-05-01

It is now possible to accurately synthesize thiolate (SR)-protected gold clusters (Au n (SR) m ) with various chemical compositions with atomic precision. The geometric structure, electronic structure, physical properties, and functions of these clusters are well known. In contrast, the ligand or metal atom exchange reactions between these clusters and other substances have not been studied extensively until recently, even though these phenomena were observed during early studies. Understanding the mechanisms of these reactions could allow desired functional metal clusters to be produced via exchange reactions. Therefore, we have studied the exchange reactions between Au n (SR) m and analogous clusters and other substances for the past four years. The results have enabled us to gain deep understanding of ligand exchange with respect to preferential exchange sites, acceleration means, effect on electronic structure, and intercluster exchange. We have also synthesized several new metal clusters using ligand and metal exchange reactions. In this account, we summarize our research on ligand and metal exchange reactions. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Low-end mass function of the Quintuplet cluster

NASA Astrophysics Data System (ADS)

Shin, Jihye; Kim, Sungsoo S.

2016-08-01

The Quintuplet and Arches clusters, which were formed in the harsh environment of the Galactic Centre (GC) a few million years ago, have been excellent targets for studying the effects of a star-forming environment on the initial mass function (IMF). In order to estimate the shape of the low-end IMF of the Arches cluster, Shin & Kim devised a novel photometric method that utilizes pixel intensity histograms (PIHs) of the observed images. Here, we apply the PIH method to the Quintuplet cluster and estimate the shape of its low-end IMF below the magnitude of completeness limit as set by conventional photometry. We found that the low-end IMF of the Quintuplet is consistent with that found for the Arches cluster-Kroupa MF, with a significant number of low-mass stars below 1 M⊙. We conclude that the most likely IMFs of the Quintuplet and the Arches clusters are not too different from the IMFs found in the Galactic disc. We also find that the observed PIHs and stellar number density profiles of both clusters are best reproduced when the clusters are assumed to be at three-dimensional distances of approximately 100 pc from the GC.

The miR-290-295 cluster as multi-faceted players in mouse embryonic stem cells.

PubMed

Yuan, Kai; Ai, Wen-Bing; Wan, Lin-Yan; Tan, Xiao; Wu, Jiang-Feng

2017-01-01

Increasing evidence indicates that embryonic stem cell specific microRNAs (miRNAs) play an essential role in the early development of embryo. Among them, the miR-290-295 cluster is the most highly expressed in the mouse embryonic stem cells and involved in various biological processes. In this paper, we reviewed the research progress of the function of the miR-290-295 cluster in embryonic stem cells. The miR-290-295 cluster is involved in regulating embryonic stem cell pluripotency maintenance, self-renewal, and reprogramming somatic cells to an embryonic stem cell-like state. Moreover, the miR-290-295 cluster has a latent pro-survival function in embryonic stem cells and involved in tumourigenesis and senescence with a great significance. Elucidating the interaction between the miR-290-295 cluster and other modes of gene regulation will provide us new ideas on the biology of pluripotent stem cells. In the near future, the broad prospects of the miRNA cluster will be shown in the stem cell field, such as altering cell identities with high efficiency through the transient introduction of tissue-specific miRNA cluster.

Perspective: Size selected clusters for catalysis and electrochemistry

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

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro

We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

Perspective: Size selected clusters for catalysis and electrochemistry

DOE PAGES

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; ...

2018-03-15

We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition,more » cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.« less

Perspective: Size selected clusters for catalysis and electrochemistry

NASA Astrophysics Data System (ADS)

Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; Vajda, Stefan

2018-03-01

Size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization, and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions, and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modeling based on density functional theory sampling of local minima and energy barriers or ab initio molecular dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Finally, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.

MicroRNA cluster miR-17-92 regulates multiple functionally related voltage-gated potassium channels in chronic neuropathic pain

PubMed Central

Sakai, Atsushi; Saitow, Fumihito; Maruyama, Motoyo; Miyake, Noriko; Miyake, Koichi; Shimada, Takashi; Okada, Takashi; Suzuki, Hidenori

2017-01-01

miR-17-92 is a microRNA cluster with six distinct members. Here, we show that the miR-17-92 cluster and its individual members modulate chronic neuropathic pain. All cluster members are persistently upregulated in primary sensory neurons after nerve injury. Overexpression of miR-18a, miR-19a, miR-19b and miR-92a cluster members elicits mechanical allodynia in rats, while their blockade alleviates mechanical allodynia in a rat model of neuropathic pain. Plausible targets for the miR-17-92 cluster include genes encoding numerous voltage-gated potassium channels and their modulatory subunits. Single-cell analysis reveals extensive co-expression of miR-17-92 cluster and its predicted targets in primary sensory neurons. miR-17-92 downregulates the expression of potassium channels, and reduced outward potassium currents, in particular A-type currents. Combined application of potassium channel modulators synergistically alleviates mechanical allodynia induced by nerve injury or miR-17-92 overexpression. miR-17-92 cluster appears to cooperatively regulate the function of multiple voltage-gated potassium channel subunits, perpetuating mechanical allodynia. PMID:28677679

The Formation and Evolution of Star Clusters in Interacting Galaxies

NASA Astrophysics Data System (ADS)

Maji, Moupiya; Zhu, Qirong; Li, Yuexing; Charlton, Jane; Hernquist, Lars; Knebe, Alexander

2017-08-01

Observations of globular clusters show that they have universal lognormal mass functions with a characteristic peak at ˜ 2× {10}5 {M}⊙ , but the origin of this peaked distribution is highly debated. Here we investigate the formation and evolution of star clusters (SCs) in interacting galaxies using high-resolution hydrodynamical simulations performed with two different codes in order to mitigate numerical artifacts. We find that massive SCs in the range of ˜ {10}5.5{--}{10}7.5 {M}⊙ form preferentially in the highly shocked regions produced by galaxy interactions. The nascent cluster-forming clouds have high gas pressures in the range of P/k˜ {10}8{--}{10}12 {{K}} {{cm}}-3, which is ˜ {10}4{--}{10}8 times higher than the typical pressure of the interstellar medium but consistent with recent observations of a pre-super-SC cloud in the Antennae Galaxies. Furthermore, these massive SCs have quasi-lognormal initial mass functions with a peak around ˜ {10}6 {M}⊙ . The number of clusters declines with time due to destructive processes, but the shape and the peak of the mass functions do not change significantly during the course of galaxy collisions. Our results suggest that gas-rich galaxy mergers may provide a favorable environment for the formation of massive SCs such as globular clusters, and that the lognormal mass functions and the unique peak may originate from the extreme high-pressure conditions of the birth clouds and may survive the dynamical evolution.

Deconstructing Bipolar Disorder and Schizophrenia: A cross-diagnostic cluster analysis of cognitive phenotypes.

PubMed

Lee, Junghee; Rizzo, Shemra; Altshuler, Lori; Glahn, David C; Miklowitz, David J; Sugar, Catherine A; Wynn, Jonathan K; Green, Michael F

2017-02-01

Bipolar disorder (BD) and schizophrenia (SZ) show substantial overlap. It has been suggested that a subgroup of patients might contribute to these overlapping features. This study employed a cross-diagnostic cluster analysis to identify subgroups of individuals with shared cognitive phenotypes. 143 participants (68 BD patients, 39 SZ patients and 36 healthy controls) completed a battery of EEG and performance assessments on perception, nonsocial cognition and social cognition. A K-means cluster analysis was conducted with all participants across diagnostic groups. Clinical symptoms, functional capacity, and functional outcome were assessed in patients. A two-cluster solution across 3 groups was the most stable. One cluster including 44 BD patients, 31 controls and 5 SZ patients showed better cognition (High cluster) than the other cluster with 24 BD patients, 35 SZ patients and 5 controls (Low cluster). BD patients in the High cluster performed better than BD patients in the Low cluster across cognitive domains. Within each cluster, participants with different clinical diagnoses showed different profiles across cognitive domains. All patients are in the chronic phase and out of mood episode at the time of assessment and most of the assessment were behavioral measures. This study identified two clusters with shared cognitive phenotype profiles that were not proxies for clinical diagnoses. The finding of better social cognitive performance of BD patients than SZ patients in the Lowe cluster suggest that relatively preserved social cognition may be important to identify disease process distinct to each disorder. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantum annealing for combinatorial clustering

NASA Astrophysics Data System (ADS)

Kumar, Vaibhaw; Bass, Gideon; Tomlin, Casey; Dulny, Joseph

2018-02-01

Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points. The straightforward approach involves examining all the possible assignments of points to each of the clusters. This approach guarantees the solution will be a global minimum; however, the number of possible assignments scales quickly with the number of data points and becomes computationally intractable even for very small datasets. In order to circumvent this issue, cost function minima are found using popular local search-based heuristic approaches such as k-means and hierarchical clustering. Due to their greedy nature, such techniques do not guarantee that a global minimum will be found and can lead to sub-optimal clustering assignments. Other classes of global search-based techniques, such as simulated annealing, tabu search, and genetic algorithms, may offer better quality results but can be too time-consuming to implement. In this work, we describe how quantum annealing can be used to carry out clustering. We map the clustering objective to a quadratic binary optimization problem and discuss two clustering algorithms which are then implemented on commercially available quantum annealing hardware, as well as on a purely classical solver "qbsolv." The first algorithm assigns N data points to K clusters, and the second one can be used to perform binary clustering in a hierarchical manner. We present our results in the form of benchmarks against well-known k-means clustering and discuss the advantages and disadvantages of the proposed techniques.

The expression of Mirc1/Mir17-92 cluster in sputum samples correlates with pulmonary exacerbations in cystic fibrosis patients.

PubMed

Krause, Kathrin; Kopp, Benjamin T; Tazi, Mia F; Caution, Kyle; Hamilton, Kaitlin; Badr, Asmaa; Shrestha, Chandra; Tumin, Dmitry; Hayes, Don; Robledo-Avila, Frank; Hall-Stoodley, Luanne; Klamer, Brett G; Zhang, Xiaoli; Partida-Sanchez, Santiago; Parinandi, Narasimham L; Kirkby, Stephen E; Dakhlallah, Duaa; McCoy, Karen S; Cormet-Boyaka, Estelle; Amer, Amal O

2018-07-01

Cystic fibrosis (CF) is a multi-organ disorder characterized by chronic sino-pulmonary infections and inflammation. Many patients with CF suffer from repeated pulmonary exacerbations that are predictors of worsened long-term morbidity and mortality. There are no reliable markers that associate with the onset or progression of an exacerbation or pulmonary deterioration. Previously, we found that the Mirc1/Mir17-92a cluster which is comprised of 6 microRNAs (Mirs) is highly expressed in CF mice and negatively regulates autophagy which in turn improves CF transmembrane conductance regulator (CFTR) function. Therefore, here we sought to examine the expression of individual Mirs within the Mirc1/Mir17-92 cluster in human cells and biological fluids and determine their role as biomarkers of pulmonary exacerbations and response to treatment. Mirc1/Mir17-92 cluster expression was measured in human CF and non-CF plasma, blood-derived neutrophils, and sputum samples. Values were correlated with pulmonary function, exacerbations and use of CFTR modulators. Mirc1/Mir17-92 cluster expression was not significantly elevated in CF neutrophils nor plasma when compared to the non-CF cohort. Cluster expression in CF sputum was significantly higher than its expression in plasma. Elevated CF sputum Mirc1/Mir17-92 cluster expression positively correlated with pulmonary exacerbations and negatively correlated with lung function. Patients with CF undergoing treatment with the CFTR modulator Ivacaftor/Lumacaftor did not demonstrate significant change in the expression Mirc1/Mir17-92 cluster after six months of treatment. Mirc1/Mir17-92 cluster expression is a promising biomarker of respiratory status in patients with CF including pulmonary exacerbation. Published by Elsevier B.V.

On the link between energy equipartition and radial variation in the stellar mass function of star clusters

NASA Astrophysics Data System (ADS)

Webb, Jeremy J.; Vesperini, Enrico

2017-01-01

We make use of N-body simulations to determine the relationship between two observable parameters that are used to quantify mass segregation and energy equipartition in star clusters. Mass segregation can be quantified by measuring how the slope of a cluster's stellar mass function α changes with clustercentric distance r, and then calculating δ _α = d α (r)/d ln(r/r_m), where rm is the cluster's half-mass radius. The degree of energy equipartition in a cluster is quantified by η, which is a measure of how stellar velocity dispersion σ depends on stellar mass m via σ(m) ∝ m-η. Through a suite of N-body star cluster simulations with a range of initial sizes, binary fractions, orbits, black hole retention fractions, and initial mass functions, we present the co-evolution of δα and η. We find that measurements of the global η are strongly affected by the radial dependence of σ and mean stellar mass and the relationship between η and δα depends mainly on the cluster's initial conditions and the tidal field. Within rm, where these effects are minimized, we find that η and δα initially share a linear relationship. However, once the degree of mass segregation increases such that the radial dependence of σ and mean stellar mass become a factor within rm, or the cluster undergoes core collapse, the relationship breaks down. We propose a method for determining η within rm from an observational measurement of δα. In cases where η and δα can be measured independently, this new method offers a way of measuring the cluster's dynamical state.

Clustering P-Wave Receiver Functions To Constrain Subsurface Seismic Structure

NASA Astrophysics Data System (ADS)

Chai, C.; Larmat, C. S.; Maceira, M.; Ammon, C. J.; He, R.; Zhang, H.

2017-12-01

The acquisition of high-quality data from permanent and temporary dense seismic networks provides the opportunity to apply statistical and machine learning techniques to a broad range of geophysical observations. Lekic and Romanowicz (2011) used clustering analysis on tomographic velocity models of the western United States to perform tectonic regionalization and the velocity-profile clusters agree well with known geomorphic provinces. A complementary and somewhat less restrictive approach is to apply cluster analysis directly to geophysical observations. In this presentation, we apply clustering analysis to teleseismic P-wave receiver functions (RFs) continuing efforts of Larmat et al. (2015) and Maceira et al. (2015). These earlier studies validated the approach with surface waves and stacked EARS RFs from the USArray stations. In this study, we experiment with both the K-means and hierarchical clustering algorithms. We also test different distance metrics defined in the vector space of RFs following Lekic and Romanowicz (2011). We cluster data from two distinct data sets. The first, corresponding to the western US, was by smoothing/interpolation of receiver-function wavefield (Chai et al. 2015). Spatial coherence and agreement with geologic region increase with this simpler, spatially smoothed set of observations. The second data set is composed of RFs for more than 800 stations of the China Digital Seismic Network (CSN). Preliminary results show a first order agreement between clusters and tectonic region and each region cluster includes a distinct Ps arrival, which probably reflects differences in crustal thickness. Regionalization remains an important step to characterize a model prior to application of full waveform and/or stochastic imaging techniques because of the computational expense of these types of studies. Machine learning techniques can provide valuable information that can be used to design and characterize formal geophysical inversion, providing information on spatial variability in the subsurface geology.

Integrative analysis of signaling pathways and diseases associated with the miR-106b/25 cluster and their function study in berberine-induced multiple myeloma cells.

PubMed

Gu, Chunming; Li, Tianfu; Yin, Zhao; Chen, Shengting; Fei, Jia; Shen, Jianping; Zhang, Yuan

2017-05-01

Berberine (BBR), a traditional Chinese herbal medicine compound, has emerged as a novel class of anti-tumor agent. Our previous microRNA (miRNA) microarray demonstrated that miR-106b/25 was significantly down-regulated in BBR-treated multiple myeloma (MM) cells. Here, systematic integration showed that miR-106b/25 cluster is involved in multiple cancer-related signaling pathways and tumorigenesis. MiREnvironment database revealed that multiple environmental factors (drug, ionizing radiation, hypoxia) affected the miR-106b/25 cluster expression. By targeting the seed region in the miRNA, tiny anti-mir106b/25 cluster (t-anti-mir106b/25 cluster) significantly induced suppression in cell viability and colony formation. Western blot validated that t-anti-miR-106b/25 cluster effectively inhibited the expression of P38 MAPK and phospho-P38 MAPK in MM cells. These findings indicated the miR-106b/25 cluster functioned as oncogene and might provide a novel molecular insight into MM.

What is your patient’s cognitive profile? Three distinct subgroups of cognitive function in persons with heart failure

PubMed Central

Hawkins, Misty A.W.; Schaefer, Julie T.; Gunstad, John; Dolansky, Mary A.; Redle, Joseph D.; Josephson, Richard; Moore, Shirley M.; Hughes, Joel W.

2014-01-01

Purpose To determine whether patients with heart failure (HF) have distinct profiles of cognitive impairment. Background Cognitive impairment is common in HF. Recent work found three cognitive profiles in HF patients— (1) intact, (2) impaired, and (3) memory-impaired. We examined the reproducibility of these profiles and clarified mechanisms. Methods HF patients (68.6±9.7years; N=329) completed neuropsychological testing. Composite scores were created for cognitive domains and used to identify clusters via agglomerative-hierarchical cluster analysis. Results A 3-cluster solution emerged. Cluster 1 (n=109) had intact cognition. Cluster 2 (n=123) was impaired across all domains. Cluster 3 (n=97) had impaired memory only. Clusters differed in age, race, education, SES, IQ, BMI, and diabetes (ps ≤.026) but not in mood, anxiety, cardiovascular, or pulmonary disease (ps≥.118). Conclusions We replicated three distinct patterns of cognitive function in persons with HF. These profiles may help providers offer tailored care to patients with different cognitive and clinical needs. PMID:25510559

MOCASSIN-prot: a multi-objective clustering approach for protein similarity networks.

PubMed

Keel, Brittney N; Deng, Bo; Moriyama, Etsuko N

2018-04-15

Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary history of proteins is hence best modeled through networks that incorporate information both from the sequence divergence and the domain content. Here, a game-theoretic approach proposed for protein network construction is adapted into the framework of multi-objective optimization, and extended to incorporate clustering refinement procedure. The new method, MOCASSIN-prot, was applied to cluster multi-domain proteins from ten genomes. The performance of MOCASSIN-prot was compared against two protein clustering methods, Markov clustering (TRIBE-MCL) and spectral clustering (SCPS). We showed that compared to these two methods, MOCASSIN-prot, which uses both domain composition and quantitative sequence similarity information, generates fewer false positives. It achieves more functionally coherent protein clusters and better differentiates protein families. MOCASSIN-prot, implemented in Perl and Matlab, is freely available at http://bioinfolab.unl.edu/emlab/MOCASSINprot. emoriyama2@unl.edu. Supplementary data are available at Bioinformatics online.

Nonlocalized clustering: a new concept in nuclear cluster structure physics.

PubMed

Zhou, Bo; Funaki, Y; Horiuchi, H; Ren, Zhongzhou; Röpke, G; Schuck, P; Tohsaki, A; Xu, Chang; Yamada, T

2013-06-28

We investigate the α+^{16}O cluster structure in the inversion-doublet band (Kπ=0(1)±}) states of 20Ne with an angular-momentum-projected version of the Tohsaki-Horiuchi-Schuck-Röpke (THSR) wave function, which was successful "in its original form" for the description of, e.g., the famous Hoyle state. In contrast with the traditional view on clusters as localized objects, especially in inversion doublets, we find that these single THSR wave functions, which are based on the concept of nonlocalized clustering, can well describe the Kπ=0(1)- band and the Kπ=0(1)+ band. For instance, they have 99.98% and 99.87% squared overlaps for 1- and 3- states (99.29%, 98.79%, and 97.75% for 0+, 2+, and 4+ states), respectively, with the corresponding exact solution of the α+16O resonating group method. These astounding results shed a completely new light on the physics of low energy nuclear cluster states in nuclei: The clusters are nonlocalized and move around in the whole nuclear volume, only avoiding mutual overlap due to the Pauli blocking effect.

A two-step initial mass function:. Consequences of clustered star formation for binary properties

NASA Astrophysics Data System (ADS)

Durisen, R. H.; Sterzik, M. F.; Pickett, B. K.

2001-06-01

If stars originate in transient bound clusters of moderate size, these clusters will decay due to dynamic interactions in which a hard binary forms and ejects most or all the other stars. When the cluster members are chosen at random from a reasonable initial mass function (IMF), the resulting binary characteristics do not match current observations. We find a significant improvement in the trends of binary properties from this scenario when an additional constraint is taken into account, namely that there is a distribution of total cluster masses set by the masses of the cloud cores from which the clusters form. Two distinct steps then determine final stellar masses - the choice of a cluster mass and the formation of the individual stars. We refer to this as a ``two-step'' IMF. Simple statistical arguments are used in this paper to show that a two-step IMF, combined with typical results from dynamic few-body system decay, tends to give better agreement between computed binary characteristics and observations than a one-step mass selection process.

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

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.

Insight from first principles into the stability and magnetism of alkali-metal superoxide nanoclusters

NASA Astrophysics Data System (ADS)

Arcelus, Oier; Suaud, Nicolas; Katcho, Nebil A.; Carrasco, Javier

2017-05-01

Alkali-metal superoxides are gaining increasing interest as 2p magnetic materials for information and energy storage. Despite significant research efforts on bulk materials, gaps in our knowledge of the electronic and magnetic properties at the nanoscale still remain. Here, we focused on the role that structural details play in determining stability, electronic structure, and magnetic couplings of (MO2)n (M = Li, Na, and K, with n = 2-8) clusters. Using first-principles density functional theory based on the Perdew-Burke-Ernzerhof and Heyd-Scuseria-Ernzerhof functionals, we examined the effect of atomic structure on the relative stability of different polymorphs within each investigated cluster size. We found that small clusters prefer to form planar-ring structures, whereas non-planar geometries become more stable when increasing the cluster size. However, the crossover point depends on the nature of the alkali metal. Our analysis revealed that electrostatic interactions govern the highly ionic M-O2 bonding and ultimately control the relative stability between 2-D and 3-D geometries. In addition, we analyzed the weak magnetic couplings between superoxide molecules in (NaO2)4 clusters comparing model Hamiltonian methods based on Wannier function projections onto πg states with wave function-based multi-reference calculations.

Subspecialization in the human posterior medial cortex

PubMed Central

Bzdok, Danilo; Heeger, Adrian; Langner, Robert; Laird, Angela R.; Fox, Peter T.; Palomero-Gallagher, Nicola; Vogt, Brent A.; Zilles, Karl; Eickhoff, Simon B.

2014-01-01

The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-constrained but not task-unconstrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications. PMID:25462801

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

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

Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico

2013-12-01

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noisemore » introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.« less

The Initial Mass Function of the Arches Cluster

NASA Astrophysics Data System (ADS)

Hosek, Matthew; Lu, Jessica; Anderson, Jay; Ghez, Andrea; Morris, Mark; Do, Tuan; Clarkson, William; Albers, Saundra; Weisz, Daniel

2018-01-01

The Arches star cluster is only 26 pc (in projection) from Sgr A*, the supermassive black hole at the Galactic Center. This young massive cluster allows us to examine the impact of the extreme Galactic Center environment on the stellar Initial Mass Function (IMF). However, measuring the IMF of the Arches is challenging due to the highly variable extinction along the line of sight, which makes it difficult to separate cluster members from the field stars. We use high-precision proper motion and photometric measurements obtained with the Hubble Space Telescope to calculate cluster membership probabilities for stars down to ~2 M_sun out to the outskirts of the cluster (3 pc). In addition, we measure the effective temperatures of a small sample of cluster members in order to calibrate the mass-luminosity relationship using using Keck OSIRS K-band spectroscopy. We forward model these observations to simultaneously constrain the cluster IMF, age, distance, and extinction. We obtain an IMF that is shallower than what is observed locally, with a higher fraction of high-mass stars to low mass stars (i.e., “top-heavy”). We will compare the IMF of the Arches to similar clusters in the Galactic disk and quantify the effect of the GC environment on the star formation process.

Structural, electronic, and magnetic properties of Y(n)O (n=2-14) clusters: Density functional study.

PubMed

Yang, Zhi; Xiong, Shi-Jie

2008-09-28

The geometries stability, electronic properties, and magnetism of Y(n)O clusters up to n=14 are systematically studied with density functional theory. In the lowest-energy structures of Y(n)O clusters, the equilibrium site of the oxygen atom gradually moves from an outer site of the cluster, via a surface site, and finally, to an interior site as the number of the Y atoms increases from 2 to 14. Starting from n=12, the O atom falls into the center of the cluster with the Y atoms forming the outer frame. The results show that clusters with n=2, 4, 8, and 12 are more stable than their respective neighbors, and that the total magnetic moments of Y(n)O clusters are all quite small except Y(12)O cluster. The lowest-energy structure of Y(12)O cluster is a perfect icosahedron with a large magnetic moment 6mu(B). In addition, we find that the total magnetic moments are quenched for n=2, 6, and 8 due to the closed-shell electronic configuration. The calculated ionization potentials and electron affinities are in good agreement with the experimental results, which imply that the present theoretical treatments are satisfactory.

Probing the structural evolution of ruthenium doped germanium clusters: Photoelectron spectroscopy and density functional theory calculations

PubMed Central

Jin, Yuanyuan; Lu, Shengjie; Hermann, Andreas; Kuang, Xiaoyu; Zhang, Chuanzhao; Lu, Cheng; Xu, Hongguang; Zheng, Weijun

2016-01-01

We present a combined experimental and theoretical study of ruthenium doped germanium clusters, RuGen− (n = 3–12), and their corresponding neutral species. Photoelectron spectra of RuGen− clusters are measured at 266 nm. The vertical detachment energies (VDEs) and adiabatic detachment energies (ADEs) are obtained. Unbiased CALYPSO structure searches confirm the low-lying structures of anionic and neutral ruthenium doped germanium clusters in the size range of 3 ≤ n ≤ 12. Subsequent geometry optimizations using density functional theory (DFT) at PW91/LANL2DZ level are carried out to determine the relative stability and electronic properties of ruthenium doped germanium clusters. It is found that most of the anionic and neutral clusters have very similar global features. Although the global minimum structures of the anionic and neutral clusters are different, their respective geometries are observed as the low-lying isomers in either case. In addition, for n > 8, the Ru atom in RuGen−/0 clusters is absorbed endohedrally in the Ge cage. The theoretically predicted vertical and adiabatic detachment energies are in good agreement with the experimental measurements. The excellent agreement between DFT calculations and experiment enables a comprehensive evaluation of the geometrical and electronic structures of ruthenium doped germanium clusters. PMID:27439955

Searching for the missing baryons in clusters

PubMed Central

Rasheed, Bilhuda; Bahcall, Neta; Bode, Paul

2011-01-01

Observations of clusters of galaxies suggest that they contain fewer baryons (gas plus stars) than the cosmic baryon fraction. This “missing baryon” puzzle is especially surprising for the most massive clusters, which are expected to be representative of the cosmic matter content of the universe (baryons and dark matter). Here we show that the baryons may not actually be missing from clusters, but rather are extended to larger radii than typically observed. The baryon deficiency is typically observed in the central regions of clusters (∼0.5 the virial radius). However, the observed gas-density profile is significantly shallower than the mass-density profile, implying that the gas is more extended than the mass and that the gas fraction increases with radius. We use the observed density profiles of gas and mass in clusters to extrapolate the measured baryon fraction as a function of radius and as a function of cluster mass. We find that the baryon fraction reaches the cosmic value near the virial radius for all groups and clusters above . This suggests that the baryons are not missing, they are simply located in cluster outskirts. Heating processes (such as shock-heating of the intracluster gas, supernovae, and Active Galactic Nuclei feedback) likely contribute to this expanded distribution. Upcoming observations should be able to detect these baryons. PMID:21321229

Calibrating the Planck cluster mass scale with CLASH

NASA Astrophysics Data System (ADS)

Penna-Lima, M.; Bartlett, J. G.; Rozo, E.; Melin, J.-B.; Merten, J.; Evrard, A. E.; Postman, M.; Rykoff, E.

2017-08-01

We determine the mass scale of Planck galaxy clusters using gravitational lensing mass measurements from the Cluster Lensing And Supernova survey with Hubble (CLASH). We have compared the lensing masses to the Planck Sunyaev-Zeldovich (SZ) mass proxy for 21 clusters in common, employing a Bayesian analysis to simultaneously fit an idealized CLASH selection function and the distribution between the measured observables and true cluster mass. We used a tiered analysis strategy to explicitly demonstrate the importance of priors on weak lensing mass accuracy. In the case of an assumed constant bias, bSZ, between true cluster mass, M500, and the Planck mass proxy, MPL, our analysis constrains 1-bSZ = 0.73 ± 0.10 when moderate priors on weak lensing accuracy are used, including a zero-mean Gaussian with standard deviation of 8% to account for possible bias in lensing mass estimations. Our analysis explicitly accounts for possible selection bias effects in this calibration sourced by the CLASH selection function. Our constraint on the cluster mass scale is consistent with recent results from the Weighing the Giants program and the Canadian Cluster Comparison Project. It is also consistent, at 1.34σ, with the value needed to reconcile the Planck SZ cluster counts with Planck's base ΛCDM model fit to the primary cosmic microwave background anisotropies.

Spectroscopic and functional characterization of iron-sulfur cluster-bound forms of Azotobacter vinelandii (Nif)IscA.

PubMed

Mapolelo, Daphne T; Zhang, Bo; Naik, Sunil G; Huynh, Boi Hanh; Johnson, Michael K

2012-10-16

The mechanism of [4Fe-4S] cluster assembly on A-type Fe-S cluster assembly proteins, in general, and the specific role of (Nif)IscA in the maturation of nitrogen fixation proteins are currently unknown. To address these questions, in vitro spectroscopic studies (UV-visible absorption/CD, resonance Raman and Mössbauer) have been used to investigate the mechanism of [4Fe-4S] cluster assembly on Azotobacter vinelandii(Nif)IscA, and the ability of (Nif)IscA to accept clusters from NifU and to donate clusters to the apo form of the nitrogenase Fe-protein. The results show that (Nif)IscA can rapidly and reversibly cycle between forms containing one [2Fe-2S](2+) and one [4Fe-4S](2+) cluster per homodimer via DTT-induced two-electron reductive coupling of two [2Fe-2S](2+) clusters and O(2)-induced [4Fe-4S](2+) oxidative cleavage. This unique type of cluster interconversion in response to cellular redox status and oxygen levels is likely to be important for the specific role of A-type proteins in the maturation of [4Fe-4S] cluster-containing proteins under aerobic growth or oxidative stress conditions. Only the [4Fe-4S](2+)-(Nif)IscA was competent for rapid activation of apo-nitrogenase Fe protein under anaerobic conditions. Apo-(Nif)IscA was shown to accept clusters from [4Fe-4S] cluster-bound NifU via rapid intact cluster transfer, indicating a potential role as a cluster carrier for delivery of clusters assembled on NifU. Overall the results support the proposal that A-type proteins can function as carrier proteins for clusters assembled on U-type proteins and suggest that they are likely to supply [2Fe-2S] clusters rather than [4Fe-4S] for the maturation of [4Fe-4S] cluster-containing proteins under aerobic or oxidative stress growth conditions.

Spectroscopic and Functional Characterization of Iron-Sulfur Cluster-Bound Forms of Azotobacter vinelandii NifIscA†

PubMed Central

Mapolelo, Daphne T.; Zhang, Bo; Naik, Sunil G.; Huynh, Boi Hanh; Johnson, Michael K.

2012-01-01

The mechanism of [4Fe-4S] cluster assembly on A-type Fe-S cluster assembly proteins, in general, and the specific role of NifIscA in the maturation of nitrogen fixation proteins are currently unknown. To address these questions, in vitro spectroscopic studies (UV–visible absorption/CD, resonance Raman and Mössbauer) have been used to investigate the mechanism of [4Fe-4S] cluster assembly on Azotobacter vinelandii NifIscA, and the ability of NifIscA to accept clusters from NifU and to donate clusters to the apo form of the nitrogenase Fe-protein. The results show that NifIscA can rapidly and reversibly cycle between forms containing one [2Fe-2S]2+ and one [4Fe-4S]2+ cluster per homodimer via DTT-induced two-electron reductive coupling of two [2Fe-2S]2+ clusters and O2-induced [4Fe-4S]2+ oxidative cleavage. This unique type of cluster interconversion in response to cellular redox status and oxygen levels is likely to be important for the specific role of A-type proteins in the maturation of [4Fe-4S] cluster-containing proteins under aerobic growth or oxidative stress conditions. Only the [4Fe-4S]2+-NifIscA was competent for rapid activation of apo-nitrogenase Fe protein under anaerobic conditions. Apo-NifIscA was shown to accept clusters from [4Fe-4S] cluster-bound NifU via rapid intact cluster transfer, indicating a potential role as a cluster carrier for delivery of clusters assembled on NifU. Overall the results support the proposal that A-type proteins can function as carrier proteins for clusters assembled on U-type proteins and suggest that they are likely to supply [2Fe-2S] clusters rather than [4Fe-4S] for the maturation of [4Fe-4S] cluster-containing proteins under aerobic or oxidative stress growth conditions. PMID:23003323

Studying the varied shapes of gold clusters by an elegant optimization algorithm that hybridizes the density functional tight-binding theory and the density functional theory

NASA Astrophysics Data System (ADS)

Yen, Tsung-Wen; Lim, Thong-Leng; Yoon, Tiem-Leong; Lai, S. K.

2017-11-01

We combined a new parametrized density functional tight-binding (DFTB) theory (Fihey et al. 2015) with an unbiased modified basin hopping (MBH) optimization algorithm (Yen and Lai 2015) and applied it to calculate the lowest energy structures of Au clusters. From the calculated topologies and their conformational changes, we find that this DFTB/MBH method is a necessary procedure for a systematic study of the structural development of Au clusters but is somewhat insufficient for a quantitative study. As a result, we propose an extended hybridized algorithm. This improved algorithm proceeds in two steps. In the first step, the DFTB theory is employed to calculate the total energy of the cluster and this step (through running DFTB/MBH optimization for given Monte-Carlo steps) is meant to efficiently bring the Au cluster near to the region of the lowest energy minimum since the cluster as a whole has explicitly considered the interactions of valence electrons with ions, albeit semi-quantitatively. Then, in the second succeeding step, the energy-minimum searching process will continue with a skilledly replacement of the energy function calculated by the DFTB theory in the first step by one calculated in the full density functional theory (DFT). In these subsequent calculations, we couple the DFT energy also with the MBH strategy and proceed with the DFT/MBH optimization until the lowest energy value is found. We checked that this extended hybridized algorithm successfully predicts the twisted pyramidal structure for the Au40 cluster and correctly confirms also the linear shape of C8 which our previous DFTB/MBH method failed to do so. Perhaps more remarkable is the topological growth of Aun: it changes from a planar (n =3-11) → an oblate-like cage (n =12-15) → a hollow-shape cage (n =16-18) and finally a pyramidal-like cage (n =19, 20). These varied forms of the cluster's shapes are consistent with those reported in the literature.

The Low-mass Population in the Young Cluster Stock 8: Stellar Properties and Initial Mass Function

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

Jose, Jessy; Herczeg, Gregory J.; Fang, Qiliang

The evolution of H ii regions/supershells can trigger a new generation of stars/clusters at their peripheries, with environmental conditions that may affect the initial mass function, disk evolution, and star formation efficiency. In this paper we study the stellar content and star formation processes in the young cluster Stock 8, which itself is thought to be formed during the expansion of a supershell. We present deep optical photometry along with JHK and 3.6 and 4.5 μ m photometry from UKIDSS and Spitzer -IRAC. We use multicolor criteria to identify the candidate young stellar objects in the region. Using evolutionary models,more » we obtain a median log(age) of ∼6.5 (∼3.0 Myr) with an observed age spread of ∼0.25 dex for the cluster. Monte Carlo simulations of the population of Stock 8, based on estimates for the photometric uncertainty, differential reddening, binarity, and variability, indicate that these uncertainties introduce an age spread of ∼0.15 dex. The intrinsic age spread in the cluster is ∼0.2 dex. The fraction of young stellar objects surrounded by disks is ∼35%. The K -band luminosity function of Stock 8 is similar to that of the Trapezium cluster. The initial mass function (IMF) of Stock 8 has a Salpeter-like slope at >0.5 M {sub ⊙} and flattens and peaks at ∼0.4 M {sub ⊙}, below which it declines into the substellar regime. Although Stock 8 is surrounded by several massive stars, there seems to be no severe environmental effect in the form of the IMF due to the proximity of massive stars around the cluster.« less

Relaxation and collective excitations of cluster nano-plasmas

NASA Astrophysics Data System (ADS)

Reinholz, Heidi; Röpke, Gerd; Broda, Ingrid; Morozov, Igor; Bystryi, Roman; Lavrinenko, Yaroslav

2018-01-01

Nano-plasmas produced, for example, in clusters after short-pulse laser irradiation, can show collective excitations, as derived from the time evolution of fluctuations in thermodynamic equilibrium. Molecular dynamical simulations are performed for various cluster sizes. New data are obtained for the minimum value of the stationary cluster charge. The bi-local autocorrelation function gives the spatial structure of the eigenmodes, for which energy eigenvalues are obtained. By varying the cluster size, starting from a few-particle cluster, the emergence of macroscopic properties such as collective excitations is shown.

Orbit Clustering Based on Transfer Cost

NASA Technical Reports Server (NTRS)

Gustafson, Eric D.; Arrieta-Camacho, Juan J.; Petropoulos, Anastassios E.

2013-01-01

We propose using cluster analysis to perform quick screening for combinatorial global optimization problems. The key missing component currently preventing cluster analysis from use in this context is the lack of a useable metric function that defines the cost to transfer between two orbits. We study several proposed metrics and clustering algorithms, including k-means and the expectation maximization algorithm. We also show that proven heuristic methods such as the Q-law can be modified to work with cluster analysis.

Functional and molecular alterations in T Cells induced by CCL5.

PubMed

Cridge, T J; Horowitz, K M; Marinucci, M N; Rose, K M; Wells, M; Werner, M T; Kurt, Robert A

2006-01-01

To delineate whether, and the extent to which, CCL5 could impact T cell function we examined cytokine production and proliferative ability following CCL5 treatment in vitro. We report a decreased ability of splenic T cells to produce IFN-? and TNF-a as well as proliferate in response to crosslinking with antibody to CD3 after 72, but not 24 hours of CCL5 exposure. To identify a mechanism by which CCL5 modulated T cell function, we examined T cell receptor translocation and lipid raft clustering. After exposure to CCL5, T cells were less efficient at translocating the TCR and clustering lipid rafts. Since TCR translocation and lipid raft clustering are required for creation of an immunological synapse, these data suggest that extended exposure to CCL5 may impact T cell effector function by modulating the ability to create a functional immunological synapse.

Low-temperature cluster catalysis.

PubMed

Judai, Ken; Abbet, Stéphane; Wörz, Anke S; Heiz, Ulrich; Henry, Claude R

2004-03-10

Free and supported metal clusters reveal unique chemical and physical properties, which vary as a function of size as each cluster possesses a characteristic electron confinement. Several previous experimental results showed that the outcome of a given chemical reaction can be controlled by tuning the cluster size. However, none of the examples indicate that clusters prepared in the gas phase and then deposited on a support material are indeed catalytically active over several reaction cycles nor that their catalytic properties remain constant during such a catalytic process. In this work we report turn-over frequencies (TOF) for Pd(n) (n = 4, 8, 30) clusters using pulsed molecular beam experiments. The obtained results illustrate that the catalytic reactivity for the NO reduction by CO (CO + NO --> 1/2N(2) + CO(2)) is indeed a function of cluster size and that the measured TOF remain constant at a given temperature. More interestingly, the temperature of maximal reactivity is at least 100 K lower than observed for palladium nanoparticles or single crystals. One reason for this surprising observation is the character of the binding sites of these small clusters: N(2) forms already at relatively low temperatures (400 and 450 K) and therefore poisoning by adsorbed nitrogen adatoms is prevented. Thus, small clusters not only open the possibility of tuning a catalytic process by changing cluster size, but also of catalyzing chemical reactions at low temperatures.

Inactivation of iron-sulfur cluster biogenesis regulator SufR in Synechocystis sp. PCC 6803 induces unique iron-dependent protein-level responses.

PubMed

Vuorijoki, Linda; Tiwari, Arjun; Kallio, Pauli; Aro, Eva-Mari

2017-05-01

Iron-sulfur (Fe-S) clusters are protein-bound cofactors associated with cellular electron transport and redox sensing, with multiple specific functions in oxygen-evolving photosynthetic cyanobacteria. The aim here was to elucidate protein-level effects of the transcriptional repressor SufR involved in the regulation of Fe-S cluster biogenesis in the cyanobacterium Synechocystis sp. PCC 6803. The approach was to quantitate 94 pre-selected target proteins associated with various metabolic functions using SRM in Synechocystis. The evaluation was conducted in response to sufR deletion under different iron conditions, and complemented with EPR analysis on the functionality of the photosystems I and II as well as with RT-qPCR to verify the effects of SufR also on transcript level. The results on both protein and transcript levels show that SufR acts not only as a repressor of the suf operon when iron is available but also has other direct and indirect functions in the cell, including maintenance of the expression of pyruvate:ferredoxin oxidoreductase NifJ and other Fe-S cluster proteins under iron sufficient conditions. Furthermore, the results imply that in the absence of iron the suf operon is repressed by some additional regulatory mechanism independent of SufR. The study demonstrates that Fe-S cluster metabolism in Synechocystis is stringently regulated, and has complex interactions with multiple primary functions in the cell, including photosynthesis and central carbon metabolism. The study provides new insight into the regulation of Fe-S cluster biogenesis via suf operon, and the associated wide-ranging protein-level changes in photosynthetic cyanobacteria. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A Functional Bikaverin Biosynthesis Gene Cluster in Rare Strains of Botrytis cinerea Is Positively Controlled by VELVET

PubMed Central

Schumacher, Julia; Gautier, Angélique; Morgant, Guillaume; Studt, Lena; Ducrot, Paul-Henri; Le Pêcheur, Pascal; Azeddine, Saad; Fillinger, Sabine; Leroux, Pierre; Tudzynski, Bettina; Viaud, Muriel

2013-01-01

The gene cluster responsible for the biosynthesis of the red polyketidic pigment bikaverin has only been characterized in Fusarium ssp. so far. Recently, a highly homologous but incomplete and nonfunctional bikaverin cluster has been found in the genome of the unrelated phytopathogenic fungus Botrytis cinerea. In this study, we provided evidence that rare B. cinerea strains such as 1750 have a complete and functional cluster comprising the six genes orthologous to Fusarium fujikuroi ffbik1-ffbik6 and do produce bikaverin. Phylogenetic analysis confirmed that the whole cluster was acquired from Fusarium through a horizontal gene transfer (HGT). In the bikaverin-nonproducing strain B05.10, the genes encoding bikaverin biosynthesis enzymes are nonfunctional due to deleterious mutations (bcbik2-3) or missing (bcbik1) but interestingly, the genes encoding the regulatory proteins BcBIK4 and BcBIK5 do not harbor deleterious mutations which suggests that they may still be functional. Heterologous complementation of the F. fujikuroi Δffbik4 mutant confirmed that bcbik4 of strain B05.10 is indeed fully functional. Deletion of bcvel1 in the pink strain 1750 resulted in loss of bikaverin and overproduction of melanin indicating that the VELVET protein BcVEL1 regulates the biosynthesis of the two pigments in an opposite manner. Although strain 1750 itself expresses a truncated BcVEL1 protein (100 instead of 575 aa) that is nonfunctional with regard to sclerotia formation, virulence and oxalic acid formation, it is sufficient to regulate pigment biosynthesis (bikaverin and melanin) and fenhexamid HydR2 type of resistance. Finally, a genetic cross between strain 1750 and a bikaverin-nonproducing strain sensitive to fenhexamid revealed that the functional bikaverin cluster is genetically linked to the HydR2 locus. PMID:23308280

Segregation of face sensitive areas within the fusiform gyrus using global signal regression? A study on amygdala resting-state functional connectivity.

PubMed

Kruschwitz, Johann D; Meyer-Lindenberg, Andreas; Veer, Ilya M; Wackerhagen, Carolin; Erk, Susanne; Mohnke, Sebastian; Pöhland, Lydia; Haddad, Leila; Grimm, Oliver; Tost, Heike; Romanczuk-Seiferth, Nina; Heinz, Andreas; Walter, Martin; Walter, Henrik

2015-10-01

The application of global signal regression (GSR) to resting-state functional magnetic resonance imaging data and its usefulness is a widely discussed topic. In this article, we report an observation of segregated distribution of amygdala resting-state functional connectivity (rs-FC) within the fusiform gyrus (FFG) as an effect of GSR in a multi-center-sample of 276 healthy subjects. Specifically, we observed that amygdala rs-FC was distributed within the FFG as distinct anterior versus posterior clusters delineated by positive versus negative rs-FC polarity when GSR was performed. To characterize this effect in more detail, post hoc analyses revealed the following: first, direct overlays of task-functional magnetic resonance imaging derived face sensitive areas and clusters of positive versus negative amygdala rs-FC showed that the positive amygdala rs-FC cluster corresponded best with the fusiform face area, whereas the occipital face area corresponded to the negative amygdala rs-FC cluster. Second, as expected from a hierarchical face perception model, these amygdala rs-FC defined clusters showed differential rs-FC with other regions of the visual stream. Third, dynamic connectivity analyses revealed that these amygdala rs-FC defined clusters also differed in their rs-FC variance across time to the amygdala. Furthermore, subsample analyses of three independent research sites confirmed reliability of the effect of GSR, as revealed by similar patterns of distinct amygdala rs-FC polarity within the FFG. In this article, we discuss the potential of GSR to segregate face sensitive areas within the FFG and furthermore discuss how our results may relate to the functional organization of the face-perception circuit. © 2015 Wiley Periodicals, Inc.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

Functional Status, Quality of Life, and Costs Associated With Fibromyalgia Subgroups: A Latent Profile Analysis.

PubMed

Luciano, Juan V; Forero, Carlos G; Cerdà-Lafont, Marta; Peñarrubia-María, María Teresa; Fernández-Vergel, Rita; Cuesta-Vargas, Antonio I; Ruíz, José M; Rozadilla-Sacanell, Antoni; Sirvent-Alierta, Elena; Santo-Panero, Pilar; García-Campayo, Javier; Serrano-Blanco, Antoni; Pérez-Aranda, Adrián; Rubio-Valera, María

2016-10-01

Although fibromyalgia syndrome (FM) is considered a heterogeneous condition, there is no generally accepted subgroup typology. We used hierarchical cluster analysis and latent profile analysis to replicate Giesecke's classification in Spanish FM patients. The second aim was to examine whether the subgroups differed in sociodemographic characteristics, functional status, quality of life, and in direct and indirect costs. A total of 160 FM patients completed the following measures for cluster derivation: the Center for Epidemiological Studies-Depression Scale, the Trait Anxiety Inventory, the Pain Catastrophizing Scale, and the Control over Pain subscale. Pain threshold was measured with a sphygmomanometer. In addition, the Fibromyalgia Impact Questionnaire-Revised, the EuroQoL-5D-3L, and the Client Service Receipt Inventory were administered for cluster validation. Two distinct clusters were identified using hierarchical cluster analysis ("hypersensitive" group, 69.8% and "functional" group, 30.2%). In contrast, the latent profile analysis goodness-of-fit indices supported the existence of 3 FM patient profiles: (1) a "functional" profile (28.1%) defined as moderate tenderness, distress, and pain catastrophizing; (2) a "dysfunctional" profile (45.6%) defined by elevated tenderness, distress, and pain catastrophizing; and (3) a "highly dysfunctional and distressed" profile (26.3%) characterized by elevated tenderness and extremely high distress and catastrophizing. We did not find significant differences in sociodemographic characteristics between the 2 clusters or among the 3 profiles. The functional profile was associated with less impairment, greater quality of life, and lower health care costs. We identified 3 distinct profiles which accounted for the heterogeneity of FM patients. Our findings might help to design tailored interventions for FM patients.

Multi-particle correlations in transverse momenta from statistical clusters

NASA Astrophysics Data System (ADS)

Bialas, Andrzej; Bzdak, Adam

2016-09-01

We evaluate n-particle (n = 2 , 3 , 4 , 5) transverse momentum correlations for pions and kaons following from the decay of statistical clusters. These correlation functions could provide strong constraints on a possible existence of thermal clusters in the process of particle production.

Disrupted brain network functional dynamics and hyper-correlation of structural and functional connectome topology in patients with breast cancer prior to treatment.

PubMed

Kesler, Shelli R; Adams, Marjorie; Packer, Melissa; Rao, Vikram; Henneghan, Ashley M; Blayney, Douglas W; Palesh, Oxana

2017-03-01

Several previous studies have demonstrated that cancer chemotherapy is associated with brain injury and cognitive dysfunction. However, evidence suggests that cancer pathogenesis alone may play a role, even in non-CNS cancers. Using a multimodal neuroimaging approach, we measured structural and functional connectome topology as well as functional network dynamics in newly diagnosed patients with breast cancer. Our study involved a novel, pretreatment assessment that occurred prior to the initiation of any cancer therapies, including surgery with anesthesia. We enrolled 74 patients with breast cancer age 29-65 and 50 frequency-matched healthy female controls who underwent anatomic and resting-state functional MRI as well as cognitive testing. Compared to controls, patients with breast cancer demonstrated significantly lower functional network dynamics ( p  = .046) and cognitive functioning ( p  < .02, corrected). The breast cancer group also showed subtle alterations in structural local clustering and functional local clustering ( p  < .05, uncorrected) as well as significantly increased correlation between structural global clustering and functional global clustering compared to controls ( p  = .03). This hyper-correlation between structural and functional topologies was significantly associated with cognitive dysfunction ( p  = .005). Our findings could not be accounted for by psychological distress and suggest that non-CNS cancer may directly and/or indirectly affect the brain via mechanisms such as tumor-induced neurogenesis, inflammation, and/or vascular changes, for example. Our results also have broader implications concerning the importance of the balance between structural and functional connectome properties as a potential biomarker of general neurologic deficit.

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

PubMed

Stewart, Arthur; Ledingham, Robert; Williams, Hector

2017-01-01

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

Exploring spatial evolution of economic clusters: A case study of Beijing

NASA Astrophysics Data System (ADS)

Yang, Zhenshan; Sliuzas, Richard; Cai, Jianming; Ottens, Henk F. L.

2012-10-01

An identification of economic clusters and analysing their changing spatial patterns is important for understanding urban economic space dynamics. Previous studies, however, suffer from limitations as a consequence of using fixed geographically areas and not combining functional and spatial dynamics. The paper presents an approach, based on local spatial statistics and the case of Beijing to understand the spatial clustering of industries that are functionally interconnected by common or complementary patterns of demand or supply relations. Using register data of business establishments, it identifies economic clusters and analyses their pattern based on postcodes at different time slices during the period 1983-2002. The study shows how the advanced services occupy the urban centre and key sub centres. The Information and Communication Technology (ICT) cluster is mainly concentrated in the north part of the city and circles the urban centre, and the main manufacturing clusters are evolved in the key sub centers. This type of outcomes improves understanding of urban-economic dynamics, which can support spatial and economic planning.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

NASA Astrophysics Data System (ADS)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.

PubMed

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L

2018-02-07

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Structural and electronic properties of U{sub n}O{sub m} (n=1-3,m=1-3n) clusters: A theoretical study using screened hybrid density functional theory

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

Yang, Yu; Liu, Haitao; Zhang, Ping, E-mail: zhang-ping@iapcm.ac.cn

The structural and electronic properties of small uranium oxide clusters U{sub n}O{sub m} (n=1-3, m=1-3n) are systematically studied within the screened hybrid density functional theory. It is found that the formation of U–O–U bondings and isolated U–O bonds are energetically more stable than U–U bondings. As a result, no uranium cores are observed. Through fragmentation studies, we find that the U{sub n}O{sub m} clusters with the m/n ratio between 2 and 2.5 are very stable, hinting that UO{sub 2+x} hyperoxides are energetically stable. Electronically, we find that the O-2p states always distribute in the deep energy range, and the U-5fmore » states always distribute at the two sides of the Fermi level. The U-6d states mainly hybridize with the U-5f states in U-rich clusters, while hybridizing with O-2p states in O-rich clusters. Our work is the first one on the screened hybrid density functional theory level studying the atomic and electronic properties of the actinide oxide clusters.« less

Deep spectroscopy of nearby galaxy clusters - II. The Hercules cluster

NASA Astrophysics Data System (ADS)

Agulli, I.; Aguerri, J. A. L.; Diaferio, A.; Dominguez Palmero, L.; Sánchez-Janssen, R.

2017-06-01

We carried out the deep spectroscopic observations of the nearby cluster A 2151 with AF2/WYFFOS@WHT. The caustic technique enables us to identify 360 members brighter than Mr = -16 and within 1.3R200. We separated the members into subsamples according to photometrical and dynamical properties such as colour, local environment and infall time. The completeness of the catalogue and our large sample allow us to analyse the velocity dispersion and the luminosity functions (LFs) of the identified populations. We found evidence of a cluster still in its collapsing phase. The LF of the red population of A 2151 shows a deficit of dwarf red galaxies. Moreover, the normalized LFs of the red and blue populations of A 2151 are comparable to the red and blue LFs of the field, even if the blue galaxies start dominating 1 mag fainter and the red LF is well represented by a single Schechter function rather than a double Schechter function. We discuss how the evolution of cluster galaxies depends on their mass: bright and intermediate galaxies are mainly affected by dynamical friction and internal/mass quenching, while the evolution of dwarfs is driven by environmental processes that need time and a hostile cluster environment to remove the gas reservoirs and halt the star formation.

Evolution of the real-space correlation function from next generation cluster surveys. Recovering the real-space correlation function from photometric redshifts

NASA Astrophysics Data System (ADS)

Sridhar, Srivatsan; Maurogordato, Sophie; Benoist, Christophe; Cappi, Alberto; Marulli, Federico

2017-04-01

Context. The next generation of galaxy surveys will provide cluster catalogues probing an unprecedented range of scales, redshifts, and masses with large statistics. Their analysis should therefore enable us to probe the spatial distribution of clusters with high accuracy and derive tighter constraints on the cosmological parameters and the dark energy equation of state. However, for the majority of these surveys, redshifts of individual galaxies will be mostly estimated by multiband photometry which implies non-negligible errors in redshift resulting in potential difficulties in recovering the real-space clustering. Aims: We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to detect and measure the redshift and mass evolution of the correlation length r0 and of the bias parameter b(M,z) as a function of the uncertainty on the cluster redshift estimate. Methods: We calculate the correlation function for cluster sub-samples covering various mass and redshift bins selected from a 500 deg2 light-cone limited to H < 24. In order to simulate the distribution of clusters in photometric redshift space, we assign to each cluster a redshift randomly extracted from a Gaussian distribution having a mean equal to the cluster cosmological redshift and a dispersion equal to σz. The dispersion is varied in the range σ(z=0)=\\frac{σz{1+z_c} = 0.005,0.010,0.030} and 0.050, in order to cover the typical values expected in forthcoming surveys. The correlation function in real-space is then computed through estimation and deprojection of wp(rp). Four mass ranges (from Mhalo > 2 × 1013h-1M⊙ to Mhalo > 2 × 1014h-1M⊙) and six redshift slices covering the redshift range [0, 2] are investigated, first using cosmological redshifts and then for the four photometric redshift configurations. Results: From the analysis of the light-cone in cosmological redshifts we find a clear increase of the correlation amplitude as a function of redshift and mass. The evolution of the derived bias parameter b(M,z) is in fair agreement with theoretical expectations. We calculate the r0-d relation up to our highest mass, highest redshift sample tested (z = 2,Mhalo > 2 × 1014h-1M⊙). From our pilot sample limited to Mhalo > 5 × 1013h-1M⊙(0.4 < z < 0.7), we find that the real-space correlation function can be recovered by deprojection of wp(rp) within an accuracy of 5% for σz = 0.001 × (1 + zc) and within 10% for σz = 0.03 × (1 + zc). For higher dispersions (besides σz > 0.05 × (1 + zc)), the recovery becomes noisy and difficult. The evolution of the correlation in redshift and mass is clearly detected for all σz tested, but requires a large binning in redshift to be detected significantly between individual redshift slices when increasing σz. The best-fit parameters (r0 and γ) as well as the bias obtained from the deprojection method for all σz are within the 1σ uncertainty of the zc sample.

Identifying and reducing error in cluster-expansion approximations of protein energies.

PubMed

Hahn, Seungsoo; Ashenberg, Orr; Grigoryan, Gevorg; Keating, Amy E

2010-12-01

Protein design involves searching a vast space for sequences that are compatible with a defined structure. This can pose significant computational challenges. Cluster expansion is a technique that can accelerate the evaluation of protein energies by generating a simple functional relationship between sequence and energy. The method consists of several steps. First, for a given protein structure, a training set of sequences with known energies is generated. Next, this training set is used to expand energy as a function of clusters consisting of single residues, residue pairs, and higher order terms, if required. The accuracy of the sequence-based expansion is monitored and improved using cross-validation testing and iterative inclusion of additional clusters. As a trade-off for evaluation speed, the cluster-expansion approximation causes prediction errors, which can be reduced by including more training sequences, including higher order terms in the expansion, and/or reducing the sequence space described by the cluster expansion. This article analyzes the sources of error and introduces a method whereby accuracy can be improved by judiciously reducing the described sequence space. The method is applied to describe the sequence-stability relationship for several protein structures: coiled-coil dimers and trimers, a PDZ domain, and T4 lysozyme as examples with computationally derived energies, and SH3 domains in amphiphysin-1 and endophilin-1 as examples where the expanded pseudo-energies are obtained from experiments. Our open-source software package Cluster Expansion Version 1.0 allows users to expand their own energy function of interest and thereby apply cluster expansion to custom problems in protein design. © 2010 Wiley Periodicals, Inc.

Root Structure and Functioning for Efficient Acquisition of Phosphorus: Matching Morphological and Physiological Traits

PubMed Central

LAMBERS, HANS; SHANE, MICHAEL W.; CRAMER, MICHAEL D.; PEARSE, STUART J.; VENEKLAAS, ERIK J.

2006-01-01

• Background Global phosphorus (P) reserves are being depleted, with half-depletion predicted to occur between 2040 and 2060. Most of the P applied in fertilizers may be sorbed by soil, and not be available for plants lacking specific adaptations. On the severely P-impoverished soils of south-western Australia and the Cape region in South Africa, non-mycorrhizal species exhibit highly effective adaptations to acquire P. A wide range of these non-mycorrhizal species, belonging to two monocotyledonous and eight dicotyledonous families, produce root clusters. Non-mycorrhizal species with root clusters appear to be particularly effective at accessing P when its availability is extremely low. • Scope There is a need to develop crops that are highly effective at acquiring inorganic P (Pi) from P-sorbing soils. Traits such as those found in non-mycorrhizal root-cluster-bearing species in Australia, South Africa and other P-impoverished environments are highly desirable for future crops. Root clusters combine a specialized structure with a specialized metabolism. Native species with such traits could be domesticated or crossed with existing crop species. An alternative approach would be to develop future crops with root clusters based on knowledge of the genes involved in development and functioning of root clusters. • Conclusions Root clusters offer enormous potential for future research of both a fundamental and a strategic nature. New discoveries of the development and functioning of root clusters in both monocotyledonous and dicotyledonous families are essential to produce new crops with superior P-acquisition traits. PMID:16769731

Human frataxin activates Fe-S cluster biosynthesis by facilitating sulfur transfer chemistry.

PubMed

Bridwell-Rabb, Jennifer; Fox, Nicholas G; Tsai, Chi-Lin; Winn, Andrew M; Barondeau, David P

2014-08-05

Iron-sulfur clusters are ubiquitous protein cofactors with critical cellular functions. The mitochondrial Fe-S assembly complex, which consists of the cysteine desulfurase NFS1 and its accessory protein (ISD11), the Fe-S assembly protein (ISCU2), and frataxin (FXN), converts substrates l-cysteine, ferrous iron, and electrons into Fe-S clusters. The physiological function of FXN has received a tremendous amount of attention since the discovery that its loss is directly linked to the neurodegenerative disease Friedreich's ataxia. Previous in vitro results revealed a role for human FXN in activating the cysteine desulfurase and Fe-S cluster biosynthesis activities of the Fe-S assembly complex. Here we present radiolabeling experiments that indicate FXN accelerates the accumulation of sulfur on ISCU2 and that the resulting persulfide species is viable in the subsequent synthesis of Fe-S clusters. Additional mutagenesis, enzyme kinetic, UV-visible, and circular dichroism spectroscopic studies suggest conserved ISCU2 residue C104 is critical for FXN activation, whereas C35, C61, and C104 are all essential for Fe-S cluster formation on the assembly complex. These results cannot be fully explained by the hypothesis that FXN functions as an iron donor for Fe-S cluster biosynthesis, and further support an allosteric regulator role for FXN. Together, these results lead to an activation model in which FXN accelerates persulfide formation on NFS1 and favors a helix-to-coil interconversion on ISCU2 that facilitates the transfer of sulfur from NFS1 to ISCU2 as an initial step in Fe-S cluster biosynthesis.

Human Frataxin Activates Fe–S Cluster Biosynthesis by Facilitating Sulfur Transfer Chemistry

PubMed Central

2015-01-01

Iron–sulfur clusters are ubiquitous protein cofactors with critical cellular functions. The mitochondrial Fe–S assembly complex, which consists of the cysteine desulfurase NFS1 and its accessory protein (ISD11), the Fe–S assembly protein (ISCU2), and frataxin (FXN), converts substrates l-cysteine, ferrous iron, and electrons into Fe–S clusters. The physiological function of FXN has received a tremendous amount of attention since the discovery that its loss is directly linked to the neurodegenerative disease Friedreich’s ataxia. Previous in vitro results revealed a role for human FXN in activating the cysteine desulfurase and Fe–S cluster biosynthesis activities of the Fe–S assembly complex. Here we present radiolabeling experiments that indicate FXN accelerates the accumulation of sulfur on ISCU2 and that the resulting persulfide species is viable in the subsequent synthesis of Fe–S clusters. Additional mutagenesis, enzyme kinetic, UV–visible, and circular dichroism spectroscopic studies suggest conserved ISCU2 residue C104 is critical for FXN activation, whereas C35, C61, and C104 are all essential for Fe–S cluster formation on the assembly complex. These results cannot be fully explained by the hypothesis that FXN functions as an iron donor for Fe–S cluster biosynthesis, and further support an allosteric regulator role for FXN. Together, these results lead to an activation model in which FXN accelerates persulfide formation on NFS1 and favors a helix-to-coil interconversion on ISCU2 that facilitates the transfer of sulfur from NFS1 to ISCU2 as an initial step in Fe–S cluster biosynthesis. PMID:24971490

Childhood asthma clusters and response to therapy in clinical trials.

PubMed

Chang, Timothy S; Lemanske, Robert F; Mauger, David T; Fitzpatrick, Anne M; Sorkness, Christine A; Szefler, Stanley J; Gangnon, Ronald E; Page, C David; Jackson, Daniel J

2014-02-01

Childhood asthma clusters, or subclasses, have been developed by computational methods without evaluation of clinical utility. To replicate and determine whether childhood asthma clusters previously identified computationally in the Severe Asthma Research Program (SARP) are associated with treatment responses in Childhood Asthma Research and Education (CARE) Network clinical trials. A cluster assignment model was determined by using SARP participant data. A total of 611 participants 6 to 18 years old from 3 CARE trials were assigned to SARP pediatric clusters. Primary and secondary outcomes were analyzed by cluster in each trial. CARE participants were assigned to SARP clusters with high accuracy. Baseline characteristics were similar between SARP and CARE children of the same cluster. Treatment response in CARE trials was generally similar across clusters. However, with the caveat of a smaller sample size, children in the early-onset/severe-lung function cluster had best response with fluticasone/salmeterol (64% vs 23% 2.5× fluticasone and 13% fluticasone/montelukast in the Best ADd-on Therapy Giving Effective Responses trial; P = .011) and children in the early-onset/comorbidity cluster had the least clinical efficacy to treatments (eg, -0.076% change in FEV1 in the Characterizing Response to Leukotriene Receptor Antagonist and Inhaled Corticosteroid trial). In this study, we replicated SARP pediatric asthma clusters by using a separate, large clinical trials network. Early-onset/severe-lung function and early-onset/comorbidity clusters were associated with differential and limited response to therapy, respectively. Further prospective study of therapeutic response by cluster could provide new insights into childhood asthma treatment. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

densityCut: an efficient and versatile topological approach for automatic clustering of biological data

PubMed Central

Ding, Jiarui; Shah, Sohrab; Condon, Anne

2016-01-01

Motivation: Many biological data processing problems can be formalized as clustering problems to partition data points into sensible and biologically interpretable groups. Results: This article introduces densityCut, a novel density-based clustering algorithm, which is both time- and space-efficient and proceeds as follows: densityCut first roughly estimates the densities of data points from a K-nearest neighbour graph and then refines the densities via a random walk. A cluster consists of points falling into the basin of attraction of an estimated mode of the underlining density function. A post-processing step merges clusters and generates a hierarchical cluster tree. The number of clusters is selected from the most stable clustering in the hierarchical cluster tree. Experimental results on ten synthetic benchmark datasets and two microarray gene expression datasets demonstrate that densityCut performs better than state-of-the-art algorithms for clustering biological datasets. For applications, we focus on the recent cancer mutation clustering and single cell data analyses, namely to cluster variant allele frequencies of somatic mutations to reveal clonal architectures of individual tumours, to cluster single-cell gene expression data to uncover cell population compositions, and to cluster single-cell mass cytometry data to detect communities of cells of the same functional states or types. densityCut performs better than competing algorithms and is scalable to large datasets. Availability and Implementation: Data and the densityCut R package is available from https://bitbucket.org/jerry00/densitycut_dev. Contact: condon@cs.ubc.ca or sshah@bccrc.ca or jiaruid@cs.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153661

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

PubMed

Chen, Vicky; Paisley, John; Lu, Xinghua

2017-03-14

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

MASSCLEANCOLORS-MASS-DEPENDENT INTEGRATED COLORS FOR STELLAR CLUSTERS DERIVED FROM 30 MILLION MONTE CARLO SIMULATIONS

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

Popescu, Bogdan; Hanson, M. M.

2010-04-10

We present Monte Carlo models of open stellar clusters with the purpose of mapping out the behavior of integrated colors with mass and age. Our cluster simulation package allows for stochastic variations in the stellar mass function to evaluate variations in integrated cluster properties. We find that UBVK colors from our simulations are consistent with simple stellar population (SSP) models, provided the cluster mass is large, M {sub cluster} {>=} 10{sup 6} M {sub sun}. Below this mass, our simulations show two significant effects. First, the mean value of the distribution of integrated colors moves away from the SSP predictionsmore » and is less red, in the first 10{sup 7} to 10{sup 8} years in UBV colors, and for all ages in (V - K). Second, the 1{sigma} dispersion of observed colors increases significantly with lower cluster mass. We attribute the former to the reduced number of red luminous stars in most of the lower mass clusters and the latter to the increased stochastic effect of a few of these stars on lower mass clusters. This latter point was always assumed to occur, but we now provide the first public code able to quantify this effect. We are completing a more extensive database of magnitudes and colors as a function of stellar cluster age and mass that will allow the determination of the correlation coefficients among different bands, and improve estimates of cluster age and mass from integrated photometry.« less

Testing Fundamental Physics with Distant Star Clusters: Analysis of Observational Data on Palomar 14

NASA Astrophysics Data System (ADS)

Jordi, K.; Grebel, E. K.; Hilker, M.; Baumgardt, H.; Frank, M.; Kroupa, P.; Haghi, H.; Côté, P.; Djorgovski, S. G.

2009-06-01

We use the distant outer halo globular cluster Palomar 14 as a test case for classical versus modified Newtonian dynamics (MOND). Previous theoretical calculations have shown that the line-of-sight velocity dispersion predicted by these theories can differ by up to a factor of 3 for such sparse, remote clusters like Pal 14. We determine the line-of-sight velocity dispersion of Palomar 14 by measuring radial velocities of 17 red giant cluster members obtained using the Very Large Telescope and Keck telescope. The systemic velocity of Palomar 14 is (72.28 ± 0.12) km s-1. The derived velocity dispersion of (0.38 ± 0.12) km s-1 of the 16 definite member stars is in agreement with the theoretical prediction for the classical Newtonian case according to Baumgardt et al. In order to exclude the possibility that a peculiar mass function might have influenced our measurements, we derived the cluster's main-sequence mass function down to 0.53 M sun using archival images obtained with the Hubble Space Telescope. We found a mass function slope of α = 1.27 ± 0.44, which is, compared to the canonical mass function, a significantly shallower slope. The derived lower limit on the cluster's mass is higher than the theoretically predicted mass in the case of MOND. Our data are consistent with a central density of ρ0 = 0.1 M sun pc-3. We need no dark matter in Palomar 14. If the cluster is on a circular orbit, our spectroscopic and photometric results argue against MOND, unless the cluster experienced significant mass loss. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Effects of levomilnacipran ER on noradrenergic symptoms, anxiety symptoms, and functional impairment in adults with major depressive disorder: Post hoc analysis of 5 clinical trials.

PubMed

Blier, Pierre; Gommoll, Carl; Chen, Changzheng; Kramer, Kenneth

2017-03-01

To evaluate the effects of levomilnacipran extended-release (LVM-ER; 40-120mg/day) on noradrenergic (NA) and anxiety-related symptoms in adults with major depressive disorder (MDD) and explore the relationship between these symptoms and functional impairment. Data were pooled from 5 randomized, double-blind, placebo-controlled trials (N=2598). Anxiety and NA Cluster scores were developed by adding selected item scores from the Montgomery-Åsberg Depression Rating Scale (MADRS) and 17-item Hamilton Depression Rating Scale (HAMD 17 ). A path analysis was conducted to estimate the direct effects of LVM-ER on functional impairment (Sheehan Disability Scale [SDS] total score) and the indirect effects through changes in NA and Anxiety Cluster scores. Mean improvements from baseline in NA and Anxiety Cluster scores were significantly greater with LVM-ER versus placebo (both P<0.001), as were the response rates (≥50% score improvement): NA Cluster (44% vs 34%; odds ratio=1.56; P<0.0001); Anxiety Cluster (39% vs 36%; odds ratio=1.19; P=0.041). Mean improvement in SDS total score was also significantly greater with LVM-ER versus placebo (-7.3 vs -5.6; P<0.0001). LVM-ER had an indirect effect on change in SDS total score that was mediated more strongly through NA Cluster score change (86%) than Anxiety Cluster score change (18%); the direct effect was negligible. NA and Anxiety Cluster scores, developed based on the face validity of individual MADRS and HAMD 17 items, were not predefined as efficacy outcomes in any of the studies. In adults with MDD, LVM-ER indirectly improved functional impairment mainly through improvements in NA symptoms and less so via anxiety symptoms. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Kinematical Focus on NGC 7086

NASA Astrophysics Data System (ADS)

Tadross, A. L.

2005-12-01

The main physical parameters; the cluster center, distance, radius, age, reddening, and visual absorbtion; have been re-estimated and improved for the open cluster NGC 7086. The metal abundance, galactic distances, membership richness, luminosity function, mass function, and the total mass of NGC 7086 have been examined for the first time here using Monet et al. (2003) catalog.

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.

Symptom clusters in patients with high-grade glioma.

PubMed

Fox, Sherry W; Lyon, Debra; Farace, Elana

2007-01-01

To describe the co-occurring symptoms (depression, fatigue, pain, sleep disturbance, and cognitive impairment), quality of life (QoL), and functional status in patients with high-grade glioma. Correlational, descriptive study of 73 participants with high-grade glioma in the U.S. Nine brief measures were obtained with a mailed survey. Participants were recruited from the online message board of The Healing Exchange BRAIN TRUST, a nonprofit organization dedicated to improving quality of life for people with brain tumors. Two symptom cluster models were examined. Four co-occurring symptoms were significantly correlated with each other and explained 29% of the variance in QoL: depression, fatigue, sleep disturbance, and cognitive impairment. Depression, fatigue, sleep disturbance, cognitive impairment, and pain were significantly correlated with each other and explained 62% of the variance in functional status. The interrelationships of the symptoms examined in this study and their relationships with QoL and functional status meet the criteria for defining a symptom cluster. The differences in the models of QoL and functional status indicates that symptom clusters may have unique characteristics in patients with gliomas.

GALAXY CLUSTER BULK FLOWS AND COLLISION VELOCITIES IN QUMOND

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

Katz, Harley; McGaugh, Stacy; Teuben, Peter

We examine the formation of clusters of galaxies in numerical simulations of a QUMOND cosmogony with massive sterile neutrinos. Clusters formed in these exploratory simulations develop higher velocities than those found in {Lambda}CDM simulations. The bulk motions of clusters attain {approx}1000 km s{sup -1} by low redshift, comparable to observations whereas {Lambda}CDM simulated clusters tend to fall short. Similarly, high pairwise velocities are common in cluster-cluster collisions like the Bullet Cluster. There is also a propensity for the most massive clusters to be larger in QUMOND and to appear earlier than in {Lambda}CDM, potentially providing an explanation for ''pink elephants''more » like El Gordo. However, it is not obvious that the cluster mass function can be recovered.« less

Finding Semirigid Domains in Biomolecules by Clustering Pair-Distance Variations

PubMed Central

Schreiner, Wolfgang

2014-01-01

Dynamic variations in the distances between pairs of atoms are used for clustering subdomains of biomolecules. We draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed. This reduces the computational load of clustering drastically, and we demonstrate results for several biomolecules relevant in immunoinformatics. Results are evaluated regarding the number of clusters, cluster size, cluster stability, and the evolution of clusters over time. Crisp clustering lends itself as an efficient tool to locate semirigid domains in the simulation of biomolecules. Such domains seem crucial for an optimum performance of subsequent statistical analyses, aiming at detecting minute motional patterns related to antigen recognition and signal transduction. PMID:24959586

Results from the REFLEX Cluster Survey

NASA Astrophysics Data System (ADS)

Bohringer, H.; Guzzo, L.; Collins, C. A.; Neumann, D. M.; Schindler, S.; Schuecker, P.; Cruddace, R.; Chincarini, G.; de Grandi, S.; Edge, A. C.; MacGillivray, H. T.; Shaver, P.; Vettolani, G.; Voges, W.

Based on the ROSAT All-Sky Survey we have conducted a large redshift survey as an ESO key programme to identify and secure redshifts for the X-ray brightest clusters found in the southern hemisphere. We present first results for a highly controlled sample for a flux limit of 3cdot 10^{-12} erg s^{-1} cm^{-2} (0.1 - 2.4 keV) comprising 475 clusters (87% with redshifts). The logN-logS function of the sample shows an almost perfect Euclidian slope and a preliminary X-ray luminosity function is presented.

Efficient Organometallic Spin Filter between Single-Wall Carbon Nanotube or Graphene Electrodes

NASA Astrophysics Data System (ADS)

Koleini, Mohammad; Paulsson, Magnus; Brandbyge, Mads

2007-05-01

We present a theoretical study of spin transport in a class of molecular systems consisting of an organometallic benzene-vanadium cluster placed in between graphene or single-wall carbon-nanotube-model contacts. Ab initio modeling is performed by combining spin density functional theory and nonequilibrium Green’s function techniques. We consider weak and strong cluster-contact bonds. Depending on the bonding we find from 73% (strong bonds) up to 99% (weak bonds) spin polarization of the electron transmission, and enhanced polarization with increased cluster length.

The Profile-Query Relationship.

ERIC Educational Resources Information Center

Shepherd, Michael A.; Phillips, W. J.

1986-01-01

Defines relationship between user profile and user query in terms of relationship between clusters of documents retrieved by each, and explores the expression of cluster similarity and cluster overlap as linear functions of similarity existing between original pairs of profiles and queries, given the desired retrieval threshold. (23 references)…

Star Cluster Formation in Cosmological Simulations. I. Properties of Young Clusters

NASA Astrophysics Data System (ADS)

Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.; Meng, Xi; Semenov, Vadim A.; Kravtsov, Andrey V.

2017-01-01

We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope is α ≈ 1.8{--}2, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. Comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.

AGeNNT: annotation of enzyme families by means of refined neighborhood networks.

PubMed

Kandlinger, Florian; Plach, Maximilian G; Merkl, Rainer

2017-05-25

Large enzyme families may contain functionally diverse members that give rise to clusters in a sequence similarity network (SSN). In prokaryotes, the genome neighborhood of a gene-product is indicative of its function and thus, a genome neighborhood network (GNN) deduced for an SSN provides strong clues to the specific function of enzymes constituting the different clusters. The Enzyme Function Initiative ( http://enzymefunction.org/ ) offers services that compute SSNs and GNNs. We have implemented AGeNNT that utilizes these services, albeit with datasets purged with respect to unspecific protein functions and overrepresented species. AGeNNT generates refined GNNs (rGNNs) that consist of cluster-nodes representing the sequences under study and Pfam-nodes representing enzyme functions encoded in the respective neighborhoods. For cluster-nodes, AGeNNT summarizes the phylogenetic relationships of the contributing species and a statistic indicates how unique nodes and GNs are within this rGNN. Pfam-nodes are annotated with additional features like GO terms describing protein function. For edges, the coverage is given, which is the relative number of neighborhoods containing the considered enzyme function (Pfam-node). AGeNNT is available at https://github.com/kandlinf/agennt . An rGNN is easier to interpret than a conventional GNN, which commonly contains proteins without enzymatic function and overly specific neighborhoods due to phylogenetic bias. The implemented filter routines and the statistic allow the user to identify those neighborhoods that are most indicative of a specific metabolic capacity. Thus, AGeNNT facilitates to distinguish and annotate functionally different members of enzyme families.

Spatial structure and electronic spectrum of TiSi{/n -} clusters ( n = 6-18)

NASA Astrophysics Data System (ADS)

Borshch, N. A.; Pereslavtseva, N. S.; Kurganskii, S. I.

2014-10-01

Results from optimizing the spatial structure and calculated electronic spectra of anion clusters TiSi{/n -} ( n = 6-18) are presented. Calculations are performed within the density functional theory. Spatial structures of clusters detected experimentally are established by comparing the calculated and experimental data. It is shown that prismatic and fullerene-like structures are the ones most energetically favorable for clusters TiSi{/n -}. It is concluded that these structures are basic when building clusters with close numbers of silicon atoms.

Hedgehog bases for A n cluster polylogarithms and an application to six-point amplitudes

DOE PAGES

Parker, Daniel E.; Scherlis, Adam; Spradlin, Marcus; ...

2015-11-20

Multi-loop scattering amplitudes in N=4 Yang-Mills theory possess cluster algebra structure. In order to develop a computational framework which exploits this connection, we show how to construct bases of Goncharov polylogarithm functions, at any weight, whose symbol alphabet consists of cluster coordinates on the A n cluster algebra. As a result, using such a basis we present a new expression for the 2-loop 6-particle NMHV amplitude which makes some of its cluster structure manifest.

The galaxy luminosity function around groups

NASA Astrophysics Data System (ADS)

González, R. E.; Padilla, N. D.; Galaz, G.; Infante, L.

2005-11-01

We present a study on the variations of the luminosity function of galaxies around clusters in a numerical simulation with semi-analytic galaxies, attempting to detect these variations in the 2dF Galaxy Redshift Survey. We subdivide the simulation box into equal-density regions around clusters, which we assume can be achieved by selecting objects at a given normalized distance (r/rrms, where rrms is an estimate of the halo radius) from the group centre. The semi-analytic model predicts important variations in the luminosity function out to r/rrms~= 5. In brief, variations in the mass function of haloes around clusters (large dark matter haloes with M > 1012h-1Msolar) lead to cluster central regions that present a high abundance of bright galaxies (high M* values) as well as low-luminosity galaxies (high α) at r/rrms~= 3 there is a lack of bright galaxies, which shows the depletion of galaxies in the regions surrounding clusters (minimum in M* and α), and a tendency to constant luminosity function parameters at larger cluster-centric distances. We take into account the observational biases present in the real data by reproducing the peculiar velocity effect on the redshifts of galaxies in the simulation box, and also by producing mock catalogues. We find that excluding from the analysis galaxies which in projection are close to the centres of the groups provides results that are qualitatively consistent with the full simulation box results. When we apply this method to mock catalogues of the 2dF Galaxy Redshift Survey (2dFGRS) and the 2PIGG catalogue of groups, we find that the variations in the luminosity function are almost completely erased by the Finger of God effect; only a lack of bright galaxies at r/rrms~= 3 can be marginally detected in the mock catalogues. The results from the real 2dFGRS data show a clearer detection of a dip in M* and α for r/rrms= 3, consistent with the semi-analytic predictions.

Structure, reactivity, and electronic properties of V-doped Co clusters

NASA Astrophysics Data System (ADS)

Datta, Soumendu; Kabir, Mukul; Saha-Dasgupta, Tanusri; Mookerjee, Abhijit

2009-08-01

Structures and physicochemical properties of V-doped Co13 clusters have been studied in detail using density-functional-theory-based first-principles method. We have found anomalous variation in stability of the doped clusters with increasing V concentration, which has been nicely demonstrated in terms of energetics and electronic properties of the clusters. Our study explains the nonmonotonic variation in reactivity of Co13-mVm clusters toward H2 molecules as reported experimentally [Nonose , J. Phys. Chem. 94, 2744 (1990)]. Moreover, it provides useful insight into the cluster geometry and chemically active sites on the cluster surface, which can help to design better catalytic processes.

Cluster analysis of obesity and asthma phenotypes.

PubMed

Sutherland, E Rand; Goleva, Elena; King, Tonya S; Lehman, Erik; Stevens, Allen D; Jackson, Leisa P; Stream, Amanda R; Fahy, John V; Leung, Donald Y M

2012-01-01

Asthma is a heterogeneous disease with variability among patients in characteristics such as lung function, symptoms and control, body weight, markers of inflammation, and responsiveness to glucocorticoids (GC). Cluster analysis of well-characterized cohorts can advance understanding of disease subgroups in asthma and point to unsuspected disease mechanisms. We utilized an hypothesis-free cluster analytical approach to define the contribution of obesity and related variables to asthma phenotype. In a cohort of clinical trial participants (n = 250), minimum-variance hierarchical clustering was used to identify clinical and inflammatory biomarkers important in determining disease cluster membership in mild and moderate persistent asthmatics. In a subset of participants, GC sensitivity was assessed via expression of GC receptor alpha (GCRα) and induction of MAP kinase phosphatase-1 (MKP-1) expression by dexamethasone. Four asthma clusters were identified, with body mass index (BMI, kg/m(2)) and severity of asthma symptoms (AEQ score) the most significant determinants of cluster membership (F = 57.1, p<0.0001 and F = 44.8, p<0.0001, respectively). Two clusters were composed of predominantly obese individuals; these two obese asthma clusters differed from one another with regard to age of asthma onset, measures of asthma symptoms (AEQ) and control (ACQ), exhaled nitric oxide concentration (F(E)NO) and airway hyperresponsiveness (methacholine PC(20)) but were similar with regard to measures of lung function (FEV(1) (%) and FEV(1)/FVC), airway eosinophilia, IgE, leptin, adiponectin and C-reactive protein (hsCRP). Members of obese clusters demonstrated evidence of reduced expression of GCRα, a finding which was correlated with a reduced induction of MKP-1 expression by dexamethasone Obesity is an important determinant of asthma phenotype in adults. There is heterogeneity in expression of clinical and inflammatory biomarkers of asthma across obese individuals. Reduced expression of the dominant functional isoform of the GCR may mediate GC insensitivity in obese asthmatics.

Structure and Function of 4-Hydroxyphenylacetate Decarboxylase and Its Cognate Activating Enzyme.

PubMed

Selvaraj, Brinda; Buckel, Wolfgang; Golding, Bernard T; Ullmann, G Matthias; Martins, Berta M

2016-01-01

4-Hydroxyphenylacetate decarboxylase (4Hpad) is the prototype of a new class of Fe-S cluster-dependent glycyl radical enzymes (Fe-S GREs) acting on aromatic compounds. The two-enzyme component system comprises a decarboxylase responsible for substrate conversion and a dedicated activating enzyme (4Hpad-AE). The decarboxylase uses a glycyl/thiyl radical dyad to convert 4-hydroxyphenylacetate into p-cresol (4-methylphenol) by a biologically unprecedented Kolbe-type decarboxylation. In addition to the radical dyad prosthetic group, the decarboxylase unit contains two [4Fe-4S] clusters coordinated by an extra small subunit of unknown function. 4Hpad-AE reductively cleaves S-adenosylmethionine (SAM or AdoMet) at a site-differentiated [4Fe-4S]2+/+ cluster (RS cluster) generating a transient 5'-deoxyadenosyl radical that produces a stable glycyl radical in the decarboxylase by the abstraction of a hydrogen atom. 4Hpad-AE binds up to two auxiliary [4Fe-4S] clusters coordinated by a ferredoxin-like insert that is C-terminal to the RS cluster-binding motif. The ferredoxin-like domain with its two auxiliary clusters is not vital for SAM-dependent glycyl radical formation in the decarboxylase, but facilitates a longer lifetime for the radical. This review describes the 4Hpad and cognate AE families and focuses on the recent advances and open questions concerning the structure, function and mechanism of this novel Fe-S-dependent class of GREs. © 2016 S. Karger AG, Basel.

Event-based cluster synchronization of coupled genetic regulatory networks

NASA Astrophysics Data System (ADS)

Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

2017-09-01

In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

Quantum chemical study of small AlnBm clusters: Structure and physical properties

NASA Astrophysics Data System (ADS)

Loukhovitski, Boris I.; Sharipov, Alexander S.; Starik, Alexander M.

2017-08-01

The structure and physical properties, including rotational constants, characteristic vibrational temperatures, collision diameter, dipole moment, static polarizability, the energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and formation enthalpy of the different isomeric forms of AlnBm clusters with n + m ⩽ 7 are studied using density functional theory. The search of the structure of isomers has been carried employing multistep hierarchical algorithm. Temperature dependencies of thermodynamic functions, such as enthalpy, entropy, and specific heat capacity, have been determined both for the individual isomers and for the ensembles with equilibrium and frozen compositions for the each class of clusters taking into account the anharmonicity of cluster vibrations and the contribution of their excited electronic states. The prospects of the application of small AlnBm clusters as the components of energetic materials are also considered.

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.

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

PubMed Central

Peng, Cheng; Shiu, Shin-Han

2016-01-01

Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

Genes encoding cuticular proteins are components of the Nimrod gene cluster in Drosophila.

PubMed

Cinege, Gyöngyi; Zsámboki, János; Vidal-Quadras, Maite; Uv, Anne; Csordás, Gábor; Honti, Viktor; Gábor, Erika; Hegedűs, Zoltán; Varga, Gergely I B; Kovács, Attila L; Juhász, Gábor; Williams, Michael J; Andó, István; Kurucz, Éva

2017-08-01

The Nimrod gene cluster, located on the second chromosome of Drosophila melanogaster, is the largest synthenic unit of the Drosophila genome. Nimrod genes show blood cell specific expression and code for phagocytosis receptors that play a major role in fruit fly innate immune functions. We previously identified three homologous genes (vajk-1, vajk-2 and vajk-3) located within the Nimrod cluster, which are unrelated to the Nimrod genes, but are homologous to a fourth gene (vajk-4) located outside the cluster. Here we show that, unlike the Nimrod candidates, the Vajk proteins are expressed in cuticular structures of the late embryo and the late pupa, indicating that they contribute to cuticular barrier functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probing the Structures and Electronic Properties of Dual-Phosphorus-Doped Gold Cluster Anions (AunP-2, n = 1–8): A Density functional Theory Investigation

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

Xu, Kang-Ming; Huang, Teng; Liu, Yi-Rong

2015-07-29

The geometries of gold clusters doped with two phosphorus atoms, (AunP-2, n = 1–8) were investigated using density functional theory (DFT) methods. Various two-dimensional (2D) and three-dimensional (3D) structures of the doped clusters were studied. The results indicate that the structures of dual-phosphorus-doped gold clusters exhibit large differences from those of pure gold clusters with small cluster sizes. In our study, as for Au6P-2, two cis–trans isomers were found. The global minimum of Au8P-2 presents a similar configuration to that of Au-20, a pyramid-shaped unit, and the potential novel optical and catalytic properties of this structure warrant further attention. Themore » higher stability of AunP-2 clusters relative to Au-n+2 (n = 1–8) clusters was verified based on various energy parameters, and the results indicate that the phosphorus atom can improve the stabilities of the gold clusters. We then explored the evolutionary path of (n = 1–8) clusters. We found that AunP-2 clusters exhibit the 2D–3D structural transition at n = 6, which is much clearer and faster than that of pure gold clusters and single-phosphorus-doped clusters. The electronic properties of AunP-2 (n = 1–8) were then investigated. The photoelectron spectra provide additional fundamental information on the structures and molecular orbitals shed light on the evolution of AunP-2 (n = 1–8). Natural bond orbital (NBO) described the charge distribution in stabilizing structures and revealed the strong relativistic effects of the gold atoms.« less

ADHD and Reading Disabilities: A Cluster Analytic Approach for Distinguishing Subgroups.

ERIC Educational Resources Information Center

Bonafina, Marcela A.; Newcorn, Jeffrey H.; McKay, Kathleen E.; Koda, Vivian H.; Halperin, Jeffrey M.

2000-01-01

Using cluster analysis, a study empirically divided 54 children with attention-deficit/hyperactivity disorder (ADHD) based on their Full Scale IQ and reading ability. Clusters had different patterns of cognitive, behavioral, and neurochemical functions, as determined by discrepancies in Verbal-Performance IQ, academic achievement, parent…

Ligand-protected gold clusters: the structure, synthesis and applications

NASA Astrophysics Data System (ADS)

Pichugina, D. A.; Kuz'menko, N. E.; Shestakov, A. F.

2015-11-01

Modern concepts of the structure and properties of atomic gold clusters protected by thiolate, selenolate, phosphine and phenylacetylene ligands are analyzed. Within the framework of the superatom theory, the 'divide and protect' approach and the structure rule, the stability and composition of a cluster are determined by the structure of the cluster core, the type of ligands and the total number of valence electrons. Methods of selective synthesis of gold clusters in solution and on the surface of inorganic composites based, in particular, on the reaction of Aun with RS, RSe, PhC≡C, Hal ligands or functional groups of proteins, on stabilization of clusters in cavities of the α-, β and γ-cyclodextrin molecules (Au15 and Au25) and on anchorage to a support surface (Au25/SiO2, Au20/C, Au10/FeOx) are reviewed. Problems in this field are also discussed. Among the methods for cluster structure prediction, particular attention is given to the theoretical approaches based on the density functional theory (DFT). The structures of a number of synthesized clusters are described using the results obtained by X-ray diffraction analysis and DFT calculations. A possible mechanism of formation of the SR(AuSR)n 'staple' units in the cluster shell is proposed. The structure and properties of bimetallic clusters MxAunLm (M=Pd, Pt, Ag, Cu) are discussed. The Pd or Pt atom is located at the centre of the cluster, whereas Ag and Cu atoms form bimetallic compounds in which the heteroatom is located on the surface of the cluster core or in the 'staple' units. The optical properties, fluorescence and luminescence of ligand-protected gold clusters originate from the quantum effects of the Au atoms in the cluster core and in the oligomeric SR(AuSR)x units in the cluster shell. Homogeneous and heterogeneous reactions catalyzed by atomic gold clusters are discussed in the context of the reaction mechanism and the nature of the active sites. The bibliography includes 345 references.

Catalysis applications of size-selected cluster deposition

DOE PAGES

Vajda, Stefan; White, Michael G.

2015-10-23

In this Perspective, we review recent studies of size-selected cluster deposition for catalysis applications performed at the U.S. DOE National Laboratories, with emphasis on work at Argonne National Laboratory (ANL) and Brookhaven National Laboratory (BNL). The focus is on the preparation of model supported catalysts in which the number of atoms in the deposited clusters is precisely controlled using a combination of gas-phase cluster ion sources, mass spectrometry, and soft-landing techniques. This approach is particularly effective for investigations of small nanoclusters, 0.5-2 nm (<200 atoms), where the rapid evolution of the atomic and electronic structure makes it essential to havemore » precise control over cluster size. Cluster deposition allows for independent control of cluster size, coverage, and stoichiometry (e.g., the metal-to-oxygen ratio in an oxide cluster) and can be used to deposit on any substrate without constraints of nucleation and growth. Examples are presented for metal, metal oxide, and metal sulfide cluster deposition on a variety of supports (metals, oxides, carbon/diamond) where the reactivity, cluster-support electronic interactions, and cluster stability and morphology are investigated. Both UHV and in situ/operando studies are presented that also make use of surface-sensitive X-ray characterization tools from synchrotron radiation facilities. Novel applications of cluster deposition to electrochemistry and batteries are also presented. This review also highlights the application of modern ab initio electronic structure calculations (density functional theory), which can essentially model the exact experimental system used in the laboratory (i.e., cluster and support) to provide insight on atomic and electronic structure, reaction energetics, and mechanisms. As amply demonstrated in this review, the powerful combination of atomically precise cluster deposition and theory is able to address fundamental aspects of size-effects, cluster-support interactions, and reaction mechanisms of cluster materials that are central to how catalysts function. Lastly, the insight gained from such studies can be used to further the development of novel nanostructured catalysts with high activity and selectivity.« less

Photoionization of rare gas clusters

NASA Astrophysics Data System (ADS)

Zhang, Huaizhen

This thesis concentrates on the study of photoionization of van der Waals clusters with different cluster sizes. The goal of the experimental investigation is to understand the electronic structure of van der Waals clusters and the electronic dynamics. These studies are fundamental to understand the interaction between UV-X rays and clusters. The experiments were performed at the Advanced Light Source at Lawrence Berkeley National Laboratory. The experimental method employs angle-resolved time-of-flight photoelectron spectrometry, one of the most powerful methods for probing the electronic structure of atoms, molecules, clusters and solids. The van der Waals cluster photoionization studies are focused on probing the evolution of the photoelectron angular distribution parameter as a function of photon energy and cluster size. The angular distribution has been known to be a sensitive probe of the electronic structure in atoms and molecules. However, it has not been used in the case of van der Waals clusters. We carried out outer-valence levels, inner-valence levels and core-levels cluster photoionization experiments. Specifically, this work reports on the first quantitative measurements of the angular distribution parameters of rare gas clusters as a function of average cluster sizes. Our findings for xenon clusters is that the overall photon-energy-dependent behavior of the photoelectrons from the clusters is very similar to that of the corresponding free atoms. However, distinct differences in the angular distribution point at cluster-size-dependent effects were found. For krypton clusters, in the photon energy range where atomic photoelectrons have a high angular anisotropy, our measurements show considerably more isotropic angular distributions for the cluster photoelectrons, especially right above the 3d and 4p thresholds. For the valence electrons, a surprising difference between the two spin-orbit components was found. For argon clusters, we found that the angular distribution parameter values of the two-spin-orbit components from Ar 2p clusters are slightly different. When comparing the beta values for Ar between atoms and clusters, we found different results between Ar 3s atoms and clusters, and between Ar 3p atoms and clusters. Argon cluster resonance from surface and bulk were also measured. Furthermore, the angular distribution parameters of Ar cluster photoelectrons and Ar atom photoelectrons in the 3s → np ionization region were obtained.

A novel complex networks clustering algorithm based on the core influence of nodes.

PubMed

Tong, Chao; Niu, Jianwei; Dai, Bin; Xie, Zhongyu

2014-01-01

In complex networks, cluster structure, identified by the heterogeneity of nodes, has become a common and important topological property. Network clustering methods are thus significant for the study of complex networks. Currently, many typical clustering algorithms have some weakness like inaccuracy and slow convergence. In this paper, we propose a clustering algorithm by calculating the core influence of nodes. The clustering process is a simulation of the process of cluster formation in sociology. The algorithm detects the nodes with core influence through their betweenness centrality, and builds the cluster's core structure by discriminant functions. Next, the algorithm gets the final cluster structure after clustering the rest of the nodes in the network by optimizing method. Experiments on different datasets show that the clustering accuracy of this algorithm is superior to the classical clustering algorithm (Fast-Newman algorithm). It clusters faster and plays a positive role in revealing the real cluster structure of complex networks precisely.

Cluster decomposition of full configuration interaction wave functions: A tool for chemical interpretation of systems with strong correlation

NASA Astrophysics Data System (ADS)

Lehtola, Susi; Tubman, Norm M.; Whaley, K. Birgitta; Head-Gordon, Martin

2017-10-01

Approximate full configuration interaction (FCI) calculations have recently become tractable for systems of unforeseen size, thanks to stochastic and adaptive approximations to the exponentially scaling FCI problem. The result of an FCI calculation is a weighted set of electronic configurations, which can also be expressed in terms of excitations from a reference configuration. The excitation amplitudes contain information on the complexity of the electronic wave function, but this information is contaminated by contributions from disconnected excitations, i.e., those excitations that are just products of independent lower-level excitations. The unwanted contributions can be removed via a cluster decomposition procedure, making it possible to examine the importance of connected excitations in complicated multireference molecules which are outside the reach of conventional algorithms. We present an implementation of the cluster decomposition analysis and apply it to both true FCI wave functions, as well as wave functions generated from the adaptive sampling CI algorithm. The cluster decomposition is useful for interpreting calculations in chemical studies, as a diagnostic for the convergence of various excitation manifolds, as well as as a guidepost for polynomially scaling electronic structure models. Applications are presented for (i) the double dissociation of water, (ii) the carbon dimer, (iii) the π space of polyacenes, and (iv) the chromium dimer. While the cluster amplitudes exhibit rapid decay with an increasing rank for the first three systems, even connected octuple excitations still appear important in Cr2, suggesting that spin-restricted single-reference coupled-cluster approaches may not be tractable for some problems in transition metal chemistry.

Procedure of Partitioning Data Into Number of Data Sets or Data Group - A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

The goal of clustering is to decompose a dataset into similar groups based on a objective function. Some already well established clustering algorithms are there for data clustering. Objective of these data clustering algorithms are to divide the data points of the feature space into a number of groups (or classes) so that a predefined set of criteria are satisfied. The article considers the comparative study about the effectiveness and efficiency of traditional data clustering algorithms. For evaluating the performance of the clustering algorithms, Minkowski score is used here for different data sets.

A new clustering strategy

NASA Astrophysics Data System (ADS)

Feng, Jian-xin; Tang, Jia-fu; Wang, Guang-xing

2007-04-01

On the basis of the analysis of clustering algorithm that had been proposed for MANET, a novel clustering strategy was proposed in this paper. With the trust defined by statistical hypothesis in probability theory and the cluster head selected by node trust and node mobility, this strategy can realize the function of the malicious nodes detection which was neglected by other clustering algorithms and overcome the deficiency of being incapable of implementing the relative mobility metric of corresponding nodes in the MOBIC algorithm caused by the fact that the receiving power of two consecutive HELLO packet cannot be measured. It's an effective solution to cluster MANET securely.

Young star clusters in the interacting galaxies of Hickson Compact Group 90

NASA Astrophysics Data System (ADS)

Miah, J. A.; Sharples, R. M.; Cho, J.

2015-03-01

Deep images of Hickson Compact Group 90 (HCG 90) have been obtained using the Advanced Camera for Surveys on the Hubble Space Telescope. We report results for star clusters observed in the interacting pair of galaxies NGC 7174 and NGC 7176. We present magnitude and colour distributions for the observed cluster population and find that the majority of objects show colours similar to intermediate/old age (>1 Gyr) globular clusters. However, a significant population of blue star clusters are also observed which may have formed from the tidal interaction currently occurring between the two galaxies. We find luminosity function turnover magnitudes of m^{TO}g = 25.1 ± 0.1 and m^{TO}z = 24.3 ± 0.1 for the g and z bands, respectively, implying distances of Dg = 28.8 ± 2.6 Mpc and Dz = 34.7 ± 3.1 Mpc to these galaxies, using the globular cluster luminosity function method. Lastly, we determine a total cluster population of approximately NGC ≃ 212 ± 10 over all magnitudes and a low specific frequency of SN ˜ 0.6 ± 0.1 for this pair of interacting elliptical and spiral galaxies. The small globular cluster population is likely due to tidal interactions taking place between the two galaxies which may have stripped many progenitor clusters away and formed the diffuse light observed at the core of HCG 90.

Epidemiology Analysis of Streptococcus pyogenes in a Hospital in Southern Taiwan by Use of the Updated emm Cluster Typing System.

PubMed

Chiang-Ni, Chuan; Zheng, Po-Xing; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong

2016-01-01

emm typing is the most widely used molecular typing method for the human pathogen Streptococcus pyogenes (group A streptococcus [GAS]). emm typing is based on a small variable region of the emm gene; however, the emm cluster typing system defines GAS types according to the nearly complete sequence of the emm gene. Therefore, emm cluster typing is considered to provide more information regarding the functional and structural properties of M proteins in different emm types of GAS. In the present study, 677 isolates collected between 1994 and 2008 in a hospital in southern Taiwan were analyzed by the emm cluster typing system. emm clusters A-C4, E1, E6, and A-C3 were the most prevalent emm cluster types and accounted for 67.4% of total isolates. emm clusters A-C4 and E1 were associated with noninvasive diseases, whereas E6 was significantly associated with both invasive and noninvasive manifestations. In addition, emm clusters D4, E2, and E3 were significantly associated with invasive manifestations. Furthermore, we found that the functional properties of M protein, including low fibrinogen-binding and high IgG-binding activities, were correlated significantly with invasive manifestations. In summary, the present study provides updated epidemiological information on GAS emm cluster types in southern Taiwan. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-11-17

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced.

Subject and Citation Indexing. Part I: The Clustering Structure of Composite Representations in the Cystic Fibrosis Document Collection. Part II: The Optimal, Cluster-Based Retrieval Performance of Composite Representations.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1991-01-01

Two articles discuss the clustering of composite representations in the Cystic Fibrosis Document Collection from the National Library of Medicine's MEDLINE file. Clustering is evaluated as a function of the exhaustivity of composite representations based on Medical Subject Headings (MeSH) and citation indexes, and evaluation of retrieval…

MMPI-2: Cluster Analysis of Personality Profiles in Perinatal Depression—Preliminary Evidence

PubMed Central

Grillo, Alessandra; Lauriola, Marco; Giacchetti, Nicoletta

2014-01-01

Background. To assess personality characteristics of women who develop perinatal depression. Methods. The study started with a screening of a sample of 453 women in their third trimester of pregnancy, to which was administered a survey data form, the Edinburgh Postnatal Depression Scale (EPDS) and the Minnesota Multiphasic Personality Inventory 2 (MMPI-2). A clinical group of subjects with perinatal depression (PND, 55 subjects) was selected; clinical and validity scales of MMPI-2 were used as predictors in hierarchical cluster analysis carried out. Results. The analysis identified three clusters of personality profile: two “clinical” clusters (1 and 3) and an “apparently common” one (cluster 2). The first cluster (39.5%) collects structures of personality with prevalent obsessive or dependent functioning tending to develop a “psychasthenic” depression; the third cluster (13.95%) includes women with prevalent borderline functioning tending to develop “dysphoric” depression; the second cluster (46.5%) shows a normal profile with a “defensive” attitude, probably due to the presence of defense mechanisms or to the fear of stigma. Conclusion. Characteristics of personality have a key role in clinical manifestations of perinatal depression; it is important to detect them to identify mothers at risk and to plan targeted therapeutic interventions. PMID:25574499

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

A Model for Protostellar Cluster Luminosities and the Impact on the CO–H2 Conversion Factor

NASA Astrophysics Data System (ADS)

Gaches, Brandt A. L.; Offner, Stella S. R.

2018-02-01

We construct a semianalytic model to study the effect of far-ultraviolet (FUV) radiation on gas chemistry from embedded protostars. We use the protostellar luminosity function (PLF) formalism of Offner & McKee to calculate the total, FUV, and ionizing cluster luminosity for various protostellar accretion histories and cluster sizes. We2 compare the model predictions with surveys of Gould Belt star-forming regions and find that the tapered turbulent core model matches best the mean luminosities and the spread in the data. We combine the cluster model with the photodissociation region astrochemistry code, 3D-PDR, to compute the impact of the FUV luminosity from embedded protostars on the CO-to-H2 conversion factor, X CO, as a function of cluster size, gas mass, and star formation efficiency. We find that X CO has a weak dependence on the FUV radiation from embedded sources for large clusters owing to high cloud optical depths. In smaller and more efficient clusters the embedded FUV increases X CO to levels consistent with the average Milky Way values. The internal physical and chemical structures of the cloud are significantly altered, and X CO depends strongly on the protostellar cluster mass for small efficient clouds.

Developmental analysis of the dopamine-containing neurons of the Drosophila brain

PubMed Central

Hartenstein, Volker; Cruz, Louie; Lovick, Jennifer K.; Guo, Ming

2016-01-01

The Drosophila dopaminergic (DA) system consists of a relatively small number of neurons clustered throughout the brain and ventral nerve cord. Previous work shows that clusters of DA neurons innervate different brain compartments, which in part accounts for functional diversity of the DA system. In this paper, we analyzed the association between DA neuron clusters and specific brain lineages, developmental and structural units of the Drosophila brain which provide a framework of connections that can be followed throughout development. The hatching larval brain contains six groups of primary DA neurons (born in the embryo), which we assign to six distinct lineages. We can show that all larval DA clusters persist into the adult brain. Some clusters increase in cell number during late larval stages while others do not become DA-positive until early pupa. Ablating neuroblasts with hydroxyurea (HU) prior to onset of larval proliferation (generates secondary neurons) confirms these added DA clusters are primary neurons born in the embryo, rather than secondary neurons. A single cluster that becomes DA-positive in the late pupa, PAM1/lineage DALcm1/2, forms part of a secondary lineage which can be ablated by larval HU application. By supplying lineage information for each DA cluster, our analysis promotes further developmental and functional analyses of this important system of neurons. PMID:27350102

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

Ortholog-based screening and identification of genes related to intracellular survival.

PubMed

Yang, Xiaowen; Wang, Jiawei; Bing, Guoxia; Bie, Pengfei; De, Yanyan; Lyu, Yanli; Wu, Qingmin

2018-04-20

Bioinformatics and comparative genomics analysis methods were used to predict unknown pathogen genes based on homology with identified or functionally clustered genes. In this study, the genes of common pathogens were analyzed to screen and identify genes associated with intracellular survival through sequence similarity, phylogenetic tree analysis and the λ-Red recombination system test method. The total 38,952 protein-coding genes of common pathogens were divided into 19,775 clusters. As demonstrated through a COG analysis, information storage and processing genes might play an important role intracellular survival. Only 19 clusters were present in facultative intracellular pathogens, and not all were present in extracellular pathogens. Construction of a phylogenetic tree selected 18 of these 19 clusters. Comparisons with the DEG database and previous research revealed that seven other clusters are considered essential gene clusters and that seven other clusters are associated with intracellular survival. Moreover, this study confirmed that clusters screened by orthologs with similar function could be replaced with an approved uvrY gene and its orthologs, and the results revealed that the usg gene is associated with intracellular survival. The study improves the current understanding of intracellular pathogens characteristics and allows further exploration of the intracellular survival-related gene modules in these pathogens. Copyright © 2018. Published by Elsevier B.V.

The devil is in the tails: the role of globular cluster mass evolution on stream properties

NASA Astrophysics Data System (ADS)

Balbinot, Eduardo; Gieles, Mark

2018-02-01

We present a study of the effects of collisional dynamics on the formation and detectability of cold tidal streams. A semi-analytical model for the evolution of the stellar mass function was implemented and coupled to a fast stellar stream simulation code, as well as the synthetic cluster evolution code EMACSS for the mass evolution as a function of a globular cluster orbit. We find that the increase in the average mass of the escaping stars for clusters close to dissolution has a major effect on the observable stream surface density. As an example, we show that Palomar 5 would have undetectable streams (in an SDSS-like survey) if it was currently three times more massive, despite the fact that a more massive cluster loses stars at a higher rate. This bias due to the preferential escape of low-mass stars is an alternative explanation for the absence of tails near massive clusters, than a dark matter halo associated with the cluster. We explore the orbits of a large sample of Milky Way globular clusters and derive their initial masses and remaining mass fraction. Using properties of known tidal tails, we explore regions of parameter space that favour the detectability of a stream. A list of high-probability candidates is discussed.

Simulations of the Formation and Evolution of X-ray Clusters

NASA Astrophysics Data System (ADS)

Bryan, G. L.; Klypin, A.; Norman, M. L.

1994-05-01

We describe results from a set of Omega = 1 Cold plus Hot Dark Matter (CHDM) and Cold Dark Matter (CDM) simulations. We examine the formation and evolution of X-ray clusters in a cosmological setting with sufficient numbers to perform statistical analysis. We find that CDM, normalized to COBE, seems to produce too many large clusters, both in terms of the luminosity (dn/dL) and temperature (dn/dT) functions. The CHDM simulation produces fewer clusters and the temperature distribution (our numerically most secure result) matches observations where they overlap. The computed cluster luminosity function drops below observations, but we are almost surely underestimating the X-ray luminosity. Because of the lower fluctuations in CHDM, there are only a small number of bright clusters in our simulation volume; however we can use the simulated clusters to fix the relation between temperature and velocity dispersion, allowing us to use collisionless N-body codes to probe larger length scales with correspondingly brighter clusters. The hydrodynamic simulations have been performed with a hybrid particle-mesh scheme for the dark matter and a high resolution grid-based piecewise parabolic method for the adiabatic gas dynamics. This combination has been implemented for massively parallel computers, allowing us to achive grids as large as 512(3) .

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...

2018-01-05

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

Comments on "The multisynapse neural network and its application to fuzzy clustering".

PubMed

Yu, Jian; Hao, Pengwei

2005-05-01

In the above-mentioned paper, Wei and Fahn proposed a neural architecture, the multisynapse neural network, to solve constrained optimization problems including high-order, logarithmic, and sinusoidal forms, etc. As one of its main applications, a fuzzy bidirectional associative clustering network (FBACN) was proposed for fuzzy-partition clustering according to the objective-functional method. The connection between the objective-functional-based fuzzy c-partition algorithms and FBACN is the Lagrange multiplier approach. Unfortunately, the Lagrange multiplier approach was incorrectly applied so that FBACN does not equivalently minimize its corresponding constrained objective-function. Additionally, Wei and Fahn adopted traditional definition of fuzzy c-partition, which is not satisfied by FBACN. Therefore, FBACN can not solve constrained optimization problems, either.

Subgroups of physically abusive parents based on cluster analysis of parenting behavior and affect.

PubMed

Haskett, Mary E; Smith Scott, Susan; Sabourin Ward, Caryn

2004-10-01

Cluster analysis of observed parenting and self-reported discipline was used to categorize 83 abusive parents into subgroups. A 2-cluster solution received support for validity. Cluster 1 parents were relatively warm, positive, sensitive, and engaged during interactions with their children, whereas Cluster 2 parents were relatively negative, disengaged or intrusive, and insensitive. Further, clusters differed in emotional health, parenting stress, perceptions of children, and problem solving. Children of parents in the 2 clusters differed on several indexes of social adjustment. Cluster 1 parents were similar to nonabusive parents (n = 66) on parenting and related constructs, but Cluster 2 parents differed from nonabusive parents on all clustering variables and many validation variables. Results highlight clinically relevant diversity in parenting practices and functioning among abusive parents. ((c) 2004 APA, all rights reserved).

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1993-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Possibilistic clustering for shape recognition

NASA Technical Reports Server (NTRS)

Keller, James M.; Krishnapuram, Raghu

1992-01-01

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, we cast the clustering problem into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We constructed an appropriate objective function whose minimum will characterize a good possibilistic partition of the data, and we derived the membership and prototype update equations from necessary conditions for minimization of our criterion function. In this paper, we show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance

PubMed Central

Camley, Brian A.; Zimmermann, Juliane; Levine, Herbert; Rappel, Wouter-Jan

2016-01-01

Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of “collective guidance” computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster’s size—clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion. PMID:27367541

A First Estimate of the X-Ray Binary Frequency as a Function of Star Cluster Mass in a Single Galactic System

NASA Astrophysics Data System (ADS)

Clark, D. M.; Eikenberry, S. S.; Brandl, B. R.; Wilson, J. C.; Carson, J. C.; Henderson, C. P.; Hayward, T. L.; Barry, D. J.; Ptak, A. F.; Colbert, E. J. M.

2008-05-01

We use the previously identified 15 infrared star cluster counterparts to X-ray point sources in the interacting galaxies NGC 4038/4039 (the Antennae) to study the relationship between total cluster mass and X-ray binary number. This significant population of X-Ray/IR associations allows us to perform, for the first time, a statistical study of X-ray point sources and their environments. We define a quantity, η, relating the fraction of X-ray sources per unit mass as a function of cluster mass in the Antennae. We compute cluster mass by fitting spectral evolutionary models to Ks luminosity. Considering that this method depends on cluster age, we use four different age distributions to explore the effects of cluster age on the value of η and find it varies by less than a factor of 4. We find a mean value of η for these different distributions of η = 1.7 × 10-8 M-1⊙ with ση = 1.2 × 10-8 M-1⊙. Performing a χ2 test, we demonstrate η could exhibit a positive slope, but that it depends on the assumed distribution in cluster ages. While the estimated uncertainties in η are factors of a few, we believe this is the first estimate made of this quantity to "order of magnitude" accuracy. We also compare our findings to theoretical models of open and globular cluster evolution, incorporating the X-ray binary fraction per cluster.

A FRAMEWORK FOR ATTRIBUTE-BASED COMMUNITY DETECTION WITH APPLICATIONS TO INTEGRATED FUNCTIONAL GENOMICS.

PubMed

Yu, Han; Hageman Blair, Rachael

2016-01-01

Understanding community structure in networks has received considerable attention in recent years. Detecting and leveraging community structure holds promise for understanding and potentially intervening with the spread of influence. Network features of this type have important implications in a number of research areas, including, marketing, social networks, and biology. However, an overwhelming majority of traditional approaches to community detection cannot readily incorporate information of node attributes. Integrating structural and attribute information is a major challenge. We propose a exible iterative method; inverse regularized Markov Clustering (irMCL), to network clustering via the manipulation of the transition probability matrix (aka stochastic flow) corresponding to a graph. Similar to traditional Markov Clustering, irMCL iterates between "expand" and "inflate" operations, which aim to strengthen the intra-cluster flow, while weakening the inter-cluster flow. Attribute information is directly incorporated into the iterative method through a sigmoid (logistic function) that naturally dampens attribute influence that is contradictory to the stochastic flow through the network. We demonstrate advantages and the exibility of our approach using simulations and real data. We highlight an application that integrates breast cancer gene expression data set and a functional network defined via KEGG pathways reveal significant modules for survival.

Solvatochromic shifts from coupled-cluster theory embedded in density functional theory

NASA Astrophysics Data System (ADS)

Höfener, Sebastian; Gomes, André Severo Pereira; Visscher, Lucas

2013-09-01

Building on the framework recently reported for determining general response properties for frozen-density embedding [S. Höfener, A. S. P. Gomes, and L. Visscher, J. Chem. Phys. 136, 044104 (2012)], 10.1063/1.3675845, in this work we report a first implementation of an embedded coupled-cluster in density-functional theory (CC-in-DFT) scheme for electronic excitations, where only the response of the active subsystem is taken into account. The formalism is applied to the calculation of coupled-cluster excitation energies of water and uracil in aqueous solution. We find that the CC-in-DFT results are in good agreement with reference calculations and experimental results. The accuracy of calculations is mainly sensitive to factors influencing the correlation treatment (basis set quality, truncation of the cluster operator) and to the embedding treatment of the ground-state (choice of density functionals). This allows for efficient approximations at the excited state calculation step without compromising the accuracy. This approximate scheme makes it possible to use a first principles approach to investigate environment effects with specific interactions at coupled-cluster level of theory at a cost comparable to that of calculations of the individual subsystems in vacuum.

Distinguishing Functional DNA Words; A Method for Measuring Clustering Levels

NASA Astrophysics Data System (ADS)

Moghaddasi, Hanieh; Khalifeh, Khosrow; Darooneh, Amir Hossein

2017-01-01

Functional DNA sub-sequences and genome elements are spatially clustered through the genome just as keywords in literary texts. Therefore, some of the methods for ranking words in texts can also be used to compare different DNA sub-sequences. In analogy with the literary texts, here we claim that the distribution of distances between the successive sub-sequences (words) is q-exponential which is the distribution function in non-extensive statistical mechanics. Thus the q-parameter can be used as a measure of words clustering levels. Here, we analyzed the distribution of distances between consecutive occurrences of 16 possible dinucleotides in human chromosomes to obtain their corresponding q-parameters. We found that CG as a biologically important two-letter word concerning its methylation, has the highest clustering level. This finding shows the predicting ability of the method in biology. We also proposed that chromosome 18 with the largest value of q-parameter for promoters of genes is more sensitive to dietary and lifestyle. We extended our study to compare the genome of some selected organisms and concluded that the clustering level of CGs increases in higher evolutionary organisms compared to lower ones.

Probing electronic wave functions of sodium-doped clusters: Dyson orbitals, anisotropy parameters, and ionization cross-sections

DOE PAGES

Gunina, Anastasia O.; Krylov, Anna I.

2016-11-14

We apply high-level ab initio methods to describe the electronic structure of small clusters of ammonia and dimethylether (DME) doped with sodium, which provide a model for solvated electrons. We investigate the effect of the solvent and cluster size on the electronic states. We consider both energies and properties, with a focus on the shape of the electronic wave function and the related experimental observables such as photoelectron angular distributions. The central quantity in modeling photoionization experiments is the Dyson orbital, which describes the difference between the initial N-electron and final (N-1)-electron states of a system. Dyson orbitals enter themore » expression of the photoelectron matrix element, which determines total and partial photoionization cross-sections. We compute Dyson orbitals for the Na(NH3)n and Na(DME)m clusters using correlated wave functions (obtained with equation-of-motion coupled-cluster model for electron attachment with single and double substitutions) and compare them with more approximate Hartree-Fock and Kohn-Sham orbitals. As a result, we also analyze the effect of correlation and basis sets on the shapes of Dyson orbitals and the experimental observables.« less

Rhodium clustering process on defective (8,0) SWCNT: Analysis of chemical and physical properties using density functional theory

NASA Astrophysics Data System (ADS)

Ambrusi, Ruben E.; Luna, C. Romina; Sandoval, Mario G.; Bechthold, Pablo; Pronsato, M. Estela; Juan, Alfredo

2017-12-01

The Spin-polarized density functional theory is used to study the effect of a single vacancy in a (8,0) single-walled carbon nanotube (SWCNT) on the Rh clustering process. The vacancy is considered oxygenated and non-oxygenated and, in each case, different Rhn cluster sizes (n = 1-4) are taken into account. For the analysis of these systems some physical and chemical properties are calculated, such as binding energy (Eb), work function (WF), magnetic moment, charge transfer, bond length, band gap (Eg), and density of state (DOS). From this analysis it can be concluded that: a single Rh atom and Rh2 dimer are adsorbed on vacancy without oxygen, whereas Rh3 and Rh4 clusters prefer to be adsorbed on oxygenated vacancy. In all cases, Rh adsorption induces a magnetic moment. When the Rh atom and Rh2 dimer are bonded to the defective SWCNT, it has been found that they show a semiconductor behavior that could be interesting to use in the spintronic area. In the case of Rh3 and Rh4 clusters our results show a metallic behavior suggesting that these systems are good candidates for nanotube contact.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

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

Böhringer, Hans; Chon, Gayoung; Trümper, Joachim

As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10{sup −12} erg s{sup −1} cm{sup −2} (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS IImore » cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z  = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ {sub 8} and Ω{sub m}, yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.« less

Long non-coding RNA H19 suppresses retinoblastoma progression via counteracting miR-17-92 cluster.

PubMed

Zhang, Aihui; Shang, Weiwei; Nie, Qiaoli; Li, Ting; Li, Suhui

2018-04-01

Long non-coding RNAs (lncRNAs) are frequently dysregulated and play important roles in many cancers. lncRNA H19 is one of the earliest discovered lncRNAs which has diverse roles in different cancers. However, the expression, roles, and action mechanisms of H19 in retinoblastoma are still largely unknown. In this study, we found that H19 is downregulated in retinoblastoma tissues and cell lines. Gain-of-function and loss-of-function assays showed that H19 inhibits retinoblastoma cell proliferation, induces retinoblastoma cell cycle arrest and cell apoptosis. Mechanistically, we identified seven miR-17-92 cluster binding sites on H19, and found that H19 directly bound to miR-17-92 cluster via these seven binding sites. Through binding to miR-17-92 cluster, H19 relieves the suppressing roles of miR-17-92 cluster on p21. Furthermore, H19 represses STAT3 activation induced by miR-17-92 cluster. Hence, our results revealed that H19 upregulates p21 expression, inhibits STAT3 phosphorylation, and downregulates the expression of STAT3 target genes BCL2, BCL2L1, and BIRC5. In addition, functional assays demonstrated that the mutation of miR-17-92 cluster binding sites on H19 abolished the proliferation inhibiting, cell cycle arrest and cell apoptosis inducing roles of H19 in retinoblastoma. In conclusion, our data suggested that H19 inhibits retinoblastoma progression via counteracting the roles of miR-17-92 cluster, and implied that enhancing the action of H19 may be a promising therapeutic strategy for retinoblastoma. © 2017 Wiley Periodicals, Inc.

Are pelvic adhesions associated with pain, physical, emotional and functional characteristics of women presenting with chronic pelvic pain? A cluster analysis.

PubMed

Cheong, Ying; Saran, Mili; Hounslow, James William; Reading, Isabel Claire

2018-01-08

Chronic pelvic pain is a debilitating condition. It is unknown if there is a clinical phenotype for adhesive disorders. This study aimed to determine if the presence or absence, nature, severity and extent of adhesions correlated with demographic and patient reported clinical characteristics of women presenting with CPP. Women undergoing a laparoscopy for the investigation of chronic pelvic pain were recruited prospectively; their pain and phenotypic characteristics were entered into a hierarchical cluster analysis. The groups with differing baseline clinical and operative characteristics in terms of adhesions involvement were analyzed. Sixty two women were recruited where 37 had adhesions. A low correlation was found between women's reported current pain scores and that of most severe (r = 0.34) or average pain experienced (r = 0.44) in the last 6 months. Three main groups of women with CPP were identified: Cluster 1 (n = 35) had moderate severity of pain, with poor average and present pain intensity; Cluster 2 (n = 14) had a long duration of symptoms/diagnosis, the worst current pain and worst physical, emotional and social functions; Cluster 3 (n = 11) had the shortest duration of pain and showed the best evidence of coping with low (good) physical, social and emotional scores. This cluster also had the highest proportion of women with adhesions (82%) compared to 51% in Cluster 1 and 71% in Cluster 2. In this study, we found that there is little or no correlation between patient-reported pain, physical, emotional and functional characteristics scores with the presence or absence of intra-abdominal/pelvic adhesions found during investigative laparoscopy. Most women who had adhesions had the lowest reported current pain scores.

Electronic medical records and physician stress in primary care: results from the MEMO Study

PubMed Central

Babbott, Stewart; Manwell, Linda Baier; Brown, Roger; Montague, Enid; Williams, Eric; Schwartz, Mark; Hess, Erik; Linzer, Mark

2014-01-01

Background Little has been written about physician stress that may be associated with electronic medical records (EMR). Objective We assessed relationships between the number of EMR functions, primary care work conditions, and physician satisfaction, stress and burnout. Design and participants 379 primary care physicians and 92 managers at 92 clinics from New York City and the upper Midwest participating in the 2001–5 Minimizing Error, Maximizing Outcome (MEMO) Study. A latent class analysis identified clusters of physicians within clinics with low, medium and high EMR functions. Main measures We assessed physician-reported stress, burnout, satisfaction, and intent to leave the practice, and predictors including time pressure during visits. We used a two-level regression model to estimate the mean response for each physician cluster to each outcome, adjusting for physician age, sex, specialty, work hours and years using the EMR. Effect sizes (ES) of these relationships were considered small (0.14), moderate (0.39), and large (0.61). Key results Compared to the low EMR cluster, physicians in the moderate EMR cluster reported more stress (ES 0.35, p=0.03) and lower satisfaction (ES −0.45, p=0.006). Physicians in the high EMR cluster indicated lower satisfaction than low EMR cluster physicians (ES −0.39, p=0.01). Time pressure was associated with significantly more burnout, dissatisfaction and intent to leave only within the high EMR cluster. Conclusions Stress may rise for physicians with a moderate number of EMR functions. Time pressure was associated with poor physician outcomes mainly in the high EMR cluster. Work redesign may address these stressors. PMID:24005796

Impulsivity profiles in pathological slot machine gamblers.

PubMed

Aragay, Núria; Barrios, Maite; Ramirez-Gendrau, Isabel; Garcia-Caballero, Anna; Garrido, Gemma; Ramos-Grille, Irene; Galindo, Yésika; Martin-Dombrowski, Jonatan; Vallès, Vicenç

2018-05-01

In gambling disorder (GD), impulsivity has been related with severity, treatment outcome and a greater dropout rate. The aim of the study is to obtain an empirical classification of GD patients based on their impulsivity and compare the resulting groups in terms of sociodemographic, clinical and gambling behavior variables. 126 patients with slot machine GD attending the Pathological Gambling Unit between 2013 and 2016 were included. The UPPS-P Impulsive Behavior Scale was used to assess impulsivity, and the severity of past-year gambling behavior was established with the Screen for Gambling problems questionnaire (NODS). Depression and anxiety symptoms and executive function were also assessed. A two-step cluster analysis was carried out to determine impulsivity profiles. According to the UPPS-P data, two clusters were generated. Cluster 1 showed the highest scores on all the UPPS-P subscales, whereas patients from cluster 2 exhibited only high scores on two UPPS-P subscales: Negative Urgency and Lack of premeditation. Additionally, patients on cluster 1 were younger and showed significantly higher scores on the Beck Depression Inventory and on the State-Trait Anxiety Inventory questionnaires, worse emotional regulation and executive functioning, and reported more psychiatric comorbidity compared to patients in cluster 2. With regard to gambling behavior, cluster 1 patients had significantly higher NODS scores and a higher percentage presented active gambling behavior at treatment start than in cluster 2. We found two impulsivity subtypes of slot machine gamblers. Patients with high impulsivity showed more severe gambling behavior, more clinical psychopathology and worse emotional regulation and executive functioning than those with lower levels of impulsivity. These two different clinical profiles may require different therapeutic approaches. Copyright © 2018 Elsevier Inc. All rights reserved.

Manifestation of α clustering in 10Be via α -knockout reaction

NASA Astrophysics Data System (ADS)

Lyu, Mengjiao; Yoshida, Kazuki; Kanada-En'yo, Yoshiko; Ogata, Kazuyuki

2018-04-01

Background: Proton-induced α -knockout reactions may allow direct experimental observation of α clustering in nuclei. This is obtained by relating the theoretical descriptions of clustering states to the experimental reaction observables. It is desired to introduce microscopic structure models into the theoretical frameworks for α -knockout reactions. Purpose: Our goal is to probe the α clustering in the 10Be nucleus by proton-induced α -knockout reaction observables. Method: We adopt an extended version of the Tohsaki-Horiuchi-Schuck-Röpke wave function of 10Be and integrate it with the distorted-wave impulse approximation framework for the calculation of (p ,p α ) -knockout reactions. Results: We make the first calculation for the 10Be(p ,p α )6He reaction at 250 MeV by implementing a microscopic α -cluster wave function, and we predict the triple-differential cross section (TDX). Furthermore, by constructing artificial states of the target nucleus 10Be with compact or dilute spatial distributions, the TDX is found to be highly sensitive to the extent of clustering in the target nuclei. Conclusions: These results provide reliable manifestation of α clustering in 10Be.

The study of structures and properties of PdnHm(n=1-10, m=1,2) clusters by density functional theory

NASA Astrophysics Data System (ADS)

Wen, Jun-Qing; Chen, Guo-Xiang; Zhang, Jian-Min; Wu, Hua

2018-04-01

The geometrical evolution, local relative stability, magnetism and charge transfer characteristics of PdnHm(n = 1-10, m = 1,2) have been systematically calculated by using density functional theory. The studied results show that the most stable geometries of PdnH and PdnH2 (n = 1-10) can be got by doping one or two H atoms on the sides of Pdn clusters except Pd6H and Pd6H2. It is found that doping one or two H atoms on Pdn clusters cannot change the basic framework of Pdn. The analysis of stability shows that Pd2H, Pd4H, Pd7H, Pd2H2, Pd4H2 and Pd7H2 clusters have higher local relative stability than neighboring clusters. The analysis of magnetic properties demonstrates that absorption of hydrogen atoms decreases the average atomic magnetic moments compared with pure Pdn clusters. More charges transfer from H atoms to Pd atoms for Pd6H and Pd6H2 clusters, demonstrating the adsorption of hydrogen atoms change from side adsorption to surface adsorption.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken; ...

2016-11-29

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

Ultra-small Ag clusters in zeolite A4: Antibacterial and thermochromic applications

NASA Astrophysics Data System (ADS)

Horta-Fraijo, P.; Cortez-Valadez, M.; Flores-Lopez, N. S.; Britto Hurtado, R.; Vargas-Ortiz, R. A.; Perez-Rodriguez, A.; Flores-Acosta, M.

2018-03-01

The physical and chemical properties of metal clusters depend on their atomic structure, therefore, it is important to determine the lowest-energy structures of the clusters in order to understand and utilize their properties. In this work, we use the Density Functional Theory (DFT) at the generalized gradient approximation level Becke's three-parameter and the gradient corrected functional of Lee, Yang and Puar (B3LYP) in combination with the basis set LANL2DZ (the effective core potentials and associated double-zeta valence) to determine some of the structural, electronic and vibrational properties of the planar silver clusters (Agn clusters n = 2-24). Additionally, the study reports the experimental synthesis of small silver clusters in synthetic zeolite A4. The synthesis was possible using the ion exchange method with some precursors like silver nitrate (AgNO3) and synthetic zeolite A4. The silver clusters in zeolite powder underwent thermal treatment at 450 °C to release the remaining water or humidity on it. The morphology of the particles was determined by Transmission Electron microscopy. The nanomaterials obtained show thermochromic properties. The structural parameters were correlated theoretically and experimentally.

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

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

Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Does reflective functioning mediate the relationship between attachment and personality?

PubMed

Nazzaro, Maria Paola; Boldrini, Tommaso; Tanzilli, Annalisa; Muzi, Laura; Giovanardi, Guido; Lingiardi, Vittorio

2017-10-01

Mentalization, operationalized as reflective functioning (RF), can play a crucial role in the psychological mechanisms underlying personality functioning. This study aimed to: (a) study the association between RF, personality disorders (cluster level) and functioning; (b) investigate whether RF and personality functioning are influenced by (secure vs. insecure) attachment; and (c) explore the potential mediating effect of RF on the relationship between attachment and personality functioning. The Shedler-Westen Assessment Procedure (SWAP-200) was used to assess personality disorders and levels of psychological functioning in a clinical sample (N = 88). Attachment and RF were evaluated with the Adult Attachment Interview (AAI) and Reflective Functioning Scale (RFS). Findings showed that RF had significant negative associations with cluster A and B personality disorders, and a significant positive association with psychological functioning. Moreover, levels of RF and personality functioning were influenced by attachment patterns. Finally, RF completely mediated the relationship between (secure/insecure) attachment and adaptive psychological features, and thus accounted for differences in overall personality functioning. Lack of mentalization seemed strongly associated with vulnerabilities in personality functioning, especially in patients with cluster A and B personality disorders. These findings provide support for the development of therapeutic interventions to improve patients' RF. Copyright © 2017 Elsevier B.V. All rights reserved.

Domain Evolution and Functional Diversification of Sulfite Reductases

NASA Astrophysics Data System (ADS)

Dhillon, Ashita; Goswami, Sulip; Riley, Monica; Teske, Andreas; Sogin, Mitchell

2005-02-01

Sulfite reductases are key enzymes of assimilatory and dissimilatory sulfur metabolism, which occur in diverse bacterial and archaeal lineages. They share a highly conserved domain "C-X5-C-n-C-X3-C" for binding siroheme and iron-sulfur clusters that facilitate electron transfer to the substrate. For each sulfite reductase cluster, the siroheme-binding domain is positioned slightly differently at the N-terminus of dsrA and dsrB, while in the assimilatory proteins the siroheme domain is located at the C-terminus. Our sequence and phylogenetic analysis of the siroheme-binding domain shows that sulfite reductase sequences diverged from a common ancestor into four separate clusters (aSir, alSir, dsr, and asrC) that are biochemically distinct; each serves a different assimilatory or dissimilatory role in sulfur metabolism. The phylogenetic distribution and functional grouping in sulfite reductase clusters (dsrA and dsrB vs. aSiR, asrC, and alSir) suggest that their functional diversification during evolution may have preceded the bacterial/archaeal divergence.

The metallicity of the intracluster medium over cosmic time: further evidence for early enrichment

NASA Astrophysics Data System (ADS)

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; Simionescu, Aurora; Urban, Ondrej; Werner, Norbert; Zhuravleva, Irina

2017-12-01

We use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev-Zel'dovich (SZ) effect surveys, spanning redshifts 0 < z < 1.2. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirts. We explore trends in these measurements as a function of cluster redshift, temperature and surface brightness 'peakiness' (a proxy for gas cooling efficiency in cluster centres). The data at large radii (0.5-1 r500) are consistent with a constant metallicity, while at intermediate radii (0.1-0.5 r500) we see a late-time increase in enrichment, consistent with the expected production and mixing of metals in cluster cores. In cluster centres, there are strong trends of metallicity with temperature and peakiness, reflecting enhanced metal production in the lowest entropy gas. Within the cool-core/sharply peaked cluster population, there is a large intrinsic scatter in central metallicity and no overall evolution, indicating significant astrophysical variations in the efficiency of enrichment. The central metallicity in clusters with flat surface brightness profiles is lower, with a smaller intrinsic scatter, but increases towards lower redshifts. Our results are consistent with other recent measurements of ICM metallicity as a function of redshift. They reinforce the picture implied by observations of uniform metal distributions in the outskirts of nearby clusters, in which most of the enrichment of the ICM takes place before cluster formation, with significant later enrichment taking place only in cluster centres, as the stellar populations of the central galaxies evolve.

Source clustering in the Hi-GAL survey determined using a minimum spanning tree method

NASA Astrophysics Data System (ADS)

Beuret, M.; Billot, N.; Cambrésy, L.; Eden, D. J.; Elia, D.; Molinari, S.; Pezzuto, S.; Schisano, E.

2017-01-01

Aims: The aims are to investigate the clustering of the far-infrared sources from the Herschel infrared Galactic Plane Survey (Hi-GAL) in the Galactic longitude range of -71 to 67 deg. These clumps, and their spatial distribution, are an imprint of the original conditions within a molecular cloud. This will produce a catalogue of over-densities. Methods: The minimum spanning tree (MST) method was used to identify the over-densities in two dimensions. The catalogue was further refined by folding in heliocentric distances, resulting in more reliable over-densities, which are cluster candidates. Results: We found 1633 over-densities with more than ten members. Of these, 496 are defined as cluster candidates because of the reliability of the distances, with a further 1137 potential cluster candidates. The spatial distributions of the cluster candidates are different in the first and fourth quadrants, with all clusters following the spiral structure of the Milky Way. The cluster candidates are fractal. The clump mass functions of the clustered and isolated are statistically indistinguishable from each other and are consistent with Kroupa's initial mass function. Hi-GAL is a key-project of the Herschel Space Observatory survey (Pilbratt et al. 2010) and uses the PACS (Poglitsch et al. 2010) and SPIRE (Griffin et al. 2010) cameras in parallel mode.The catalogues of cluster candidates and potential clusters are 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/597/A114

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

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn

Here, we use Chandra X-ray data to measure the metallicity of the intracluster medium (ICM) in 245 massive galaxy clusters selected from X-ray and Sunyaev–Zel'dovich (SZ) effect surveys, spanning redshifts 0 < z < 1.2. Metallicities were measured in three different radial ranges, spanning cluster cores through their outskirts. We explore trends in these measurements as a function of cluster redshift, temperature and surface brightness ‘peakiness’ (a proxy for gas cooling efficiency in cluster centres). The data at large radii (0.5–1 r500) are consistent with a constant metallicity, while at intermediate radii (0.1–0.5 r500) we see a late-time increase inmore » enrichment, consistent with the expected production and mixing of metals in cluster cores. In cluster centres, there are strong trends of metallicity with temperature and peakiness, reflecting enhanced metal production in the lowest entropy gas. Within the cool-core/sharply peaked cluster population, there is a large intrinsic scatter in central metallicity and no overall evolution, indicating significant astrophysical variations in the efficiency of enrichment. The central metallicity in clusters with flat surface brightness profiles is lower, with a smaller intrinsic scatter, but increases towards lower redshifts. Our results are consistent with other recent measurements of ICM metallicity as a function of redshift. They reinforce the picture implied by observations of uniform metal distributions in the outskirts of nearby clusters, in which most of the enrichment of the ICM takes place before cluster formation, with significant later enrichment taking place only in cluster centres, as the stellar populations of the central galaxies evolve.« less

On the mass of dense star clusters in starburst galaxies from spectrophotometry

NASA Astrophysics Data System (ADS)

Fleck, J.-J.; Boily, C. M.; Lançon, A.; Deiters, S.

2006-07-01

The mass of unresolved young star clusters derived from spectrophotometric data may well be off by a factor of 2 or more once the migration of massive stars driven by mass segregation is accounted for. We quantify this effect for a large set of cluster parameters, including variations in the stellar initial mass function (IMF), the intrinsic cluster mass, and mean mass density. Gas-dynamical models coupled with the Cambridge stellar evolution tracks allow us to derive a scheme to recover the real cluster mass given measured half-light radius, one-dimensional velocity dispersion and age. We monitor the evolution with time of the ratio of real to apparent mass through the parameter η. When we compute η for rich star clusters, we find non-monotonic evolution in time when the IMF stretches beyond a critical cut-off mass of 25.5Msolar. We also monitor the rise of colour gradients between the inner and outer volume of clusters: we find trends in time of the stellar IMF power indices overlapping well with those derived for the Large Magellanic Cloud cluster NGC 1818 at an age of 30Myr. We argue that the core region of massive Antennae clusters should have suffered from much segregation despite their low ages. We apply these results to a cluster mass function, and find that the peak of the mass distribution would appear to observers shifted to lower masses by as much as 0.2dex. The star formation rate derived for the cluster population is then underestimated by from 20 to 50 per cent.

Exploring the IMF of star clusters: a joint SLUG and LEGUS effort

NASA Astrophysics Data System (ADS)

Ashworth, G.; Fumagalli, M.; Krumholz, M. R.; Adamo, A.; Calzetti, D.; Chandar, R.; Cignoni, M.; Dale, D.; Elmegreen, B. G.; Gallagher, J. S., III; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Johnson, K. E.; Lee, J.; Tosi, M.; Wofford, A.

2017-08-01

We present the implementation of a Bayesian formalism within the Stochastically Lighting Up Galaxies (slug) stellar population synthesis code, which is designed to investigate variations in the initial mass function (IMF) of star clusters. By comparing observed cluster photometry to large libraries of clusters simulated with a continuously varying IMF, our formalism yields the posterior probability distribution function (PDF) of the cluster mass, age and extinction, jointly with the parameters describing the IMF. We apply this formalism to a sample of star clusters from the nearby galaxy NGC 628, for which broad-band photometry in five filters is available as part of the Legacy ExtraGalactic UV Survey (LEGUS). After allowing the upper-end slope of the IMF (α3) to vary, we recover PDFs for the mass, age and extinction that are broadly consistent with what is found when assuming an invariant Kroupa IMF. However, the posterior PDF for α3 is very broad due to a strong degeneracy with the cluster mass, and it is found to be sensitive to the choice of priors, particularly on the cluster mass. We find only a modest improvement in the constraining power of α3 when adding Hα photometry from the companion Hα-LEGUS survey. Conversely, Hα photometry significantly improves the age determination, reducing the frequency of multi-modal PDFs. With the aid of mock clusters, we quantify the degeneracy between physical parameters, showing how constraints on the cluster mass that are independent of photometry can be used to pin down the IMF properties of star clusters.

Global Identification of Genes Affecting Iron-Sulfur Cluster Biogenesis and Iron Homeostasis

PubMed Central

Hidese, Ryota; Kurihara, Tatsuo; Esaki, Nobuyoshi

2014-01-01

Iron-sulfur (Fe-S) clusters are ubiquitous cofactors that are crucial for many physiological processes in all organisms. In Escherichia coli, assembly of Fe-S clusters depends on the activity of the iron-sulfur cluster (ISC) assembly and sulfur mobilization (SUF) apparatus. However, the underlying molecular mechanisms and the mechanisms that control Fe-S cluster biogenesis and iron homeostasis are still poorly defined. In this study, we performed a global screen to identify the factors affecting Fe-S cluster biogenesis and iron homeostasis using the Keio collection, which is a library of 3,815 single-gene E. coli knockout mutants. The approach was based on radiolabeling of the cells with [2-14C]dihydrouracil, which entirely depends on the activity of an Fe-S enzyme, dihydropyrimidine dehydrogenase. We identified 49 genes affecting Fe-S cluster biogenesis and/or iron homeostasis, including 23 genes important only under microaerobic/anaerobic conditions. This study defines key proteins associated with Fe-S cluster biogenesis and iron homeostasis, which will aid further understanding of the cellular mechanisms that coordinate the processes. In addition, we applied the [2-14C]dihydrouracil-labeling method to analyze the role of amino acid residues of an Fe-S cluster assembly scaffold (IscU) as a model of the Fe-S cluster assembly apparatus. The analysis showed that Cys37, Cys63, His105, and Cys106 are essential for the function of IscU in vivo, demonstrating the potential of the method to investigate in vivo function of proteins involved in Fe-S cluster assembly. PMID:24415728

Prediction of CpG-island function: CpG clustering vs. sliding-window methods

PubMed Central

2010-01-01

Background Unmethylated stretches of CpG dinucleotides (CpG islands) are an outstanding property of mammal genomes. Conventionally, these regions are detected by sliding window approaches using %G + C, CpG observed/expected ratio and length thresholds as main parameters. Recently, clustering methods directly detect clusters of CpG dinucleotides as a statistical property of the genome sequence. Results We compare sliding-window to clustering (i.e. CpGcluster) predictions by applying new ways to detect putative functionality of CpG islands. Analyzing the co-localization with several genomic regions as a function of window size vs. statistical significance (p-value), CpGcluster shows a higher overlap with promoter regions and highly conserved elements, at the same time showing less overlap with Alu retrotransposons. The major difference in the prediction was found for short islands (CpG islets), often exclusively predicted by CpGcluster. Many of these islets seem to be functional, as they are unmethylated, highly conserved and/or located within the promoter region. Finally, we show that window-based islands can spuriously overlap several, differentially regulated promoters as well as different methylation domains, which might indicate a wrong merge of several CpG islands into a single, very long island. The shorter CpGcluster islands seem to be much more specific when concerning the overlap with alternative transcription start sites or the detection of homogenous methylation domains. Conclusions The main difference between sliding-window approaches and clustering methods is the length of the predicted islands. Short islands, often differentially methylated, are almost exclusively predicted by CpGcluster. This suggests that CpGcluster may be the algorithm of choice to explore the function of these short, but putatively functional CpG islands. PMID:20500903

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

PubMed Central

Aubry, Marc; Monnier, Annabelle; Chicault, Celine; de Tayrac, Marie; Galibert, Marie-Dominique; Burgun, Anita; Mosser, Jean

2006-01-01

Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions. PMID:16674810

Subaru Weak-lensing Survey of Dark Matter Subhalos in the Coma Cluster: Subhalo Mass Function and Statistical Properties

NASA Astrophysics Data System (ADS)

Okabe, Nobuhiro; Futamase, Toshifumi; Kajisawa, Masaru; Kuroshima, Risa

2014-04-01

We present a 4 deg2 weak gravitational lensing survey of subhalos in the very nearby Coma cluster using the Subaru/Suprime-Cam. The large apparent size of cluster subhalos allows us to measure the mass of 32 subhalos detected in a model-independent manner, down to the order of 10-3 of the virial mass of the cluster. Weak-lensing mass measurements of these shear-selected subhalos enable us to investigate subhalo properties and the correlation between subhalo masses and galaxy luminosities for the first time. The mean distortion profiles stacked over subhalos show a sharply truncated feature which is well-fitted by a Navarro-Frenk-White (NFW) mass model with the truncation radius, as expected due to tidal destruction by the main cluster. We also found that subhalo masses, truncation radii, and mass-to-light ratios decrease toward the cluster center. The subhalo mass function, dn/dln M sub, in the range of 2 orders of magnitude in mass, is well described by a single power law or a Schechter function. Best-fit power indices of 1.09^{+0.42}_{-0.32} for the former model and 0.99_{-0.23}^{+0.34} for the latter, are in remarkable agreement with slopes of ~0.9-1.0 predicted by the cold dark matter paradigm. The tangential distortion signals in the radial range of 0.02-2 h -1 Mpc from the cluster center show a complex structure which is well described by a composition of three mass components of subhalos, the NFW mass distribution as a smooth component of the main cluster, and a lensing model from a large scale structure behind the cluster. Although the lensing signals are 1 order of magnitude lower than those for clusters at z ~ 0.2, the total signal-to-noise ratio, S/N = 13.3, is comparable, or higher, because the enormous number of background source galaxies compensates for the low lensing efficiency of the nearby cluster. Based on data collected from the Subaru Telescope and obtained from SMOKA, operated by the Astronomy Data Center, National Astronomical Observatory of Japan.

Dynamic evolution of nearby galaxy clusters

NASA Astrophysics Data System (ADS)

Biernacka, M.; Flin, P.

2011-06-01

A study of the evolution of 377 rich ACO clusters with redshift z<0.2 is presented. The data concerning galaxies in the investigated clusters were obtained using FOCAS packages applied to Digital Sky Survey I. The 377 galaxy clusters constitute a statistically uniform sample to which visual galaxy/star reclassifications were applied. Cluster shape within 2.0 h-1 Mpc from the adopted cluster centre (the mean and the median of all galaxy coordinates, the position of the brightest and of the third brightest galaxy in the cluster) was determined through its ellipticity calculated using two methods: the covariance ellipse method (hereafter CEM) and the method based on Minkowski functionals (hereafter MFM). We investigated ellipticity dependence on the radius of circular annuli, in which ellipticity was calculated. This was realized by varying the radius from 0.5 to 2 Mpc in steps of 0.25 Mpc. By performing Monte Carlo simulations, we generated clusters to which the two ellipticity methods were applied. We found that the covariance ellipse method works better than the method based on Minkowski functionals. We also found that ellipticity distributions are different for different methods used. Using the ellipticity-redshift relation, we investigated the possibility of cluster evolution in the low-redshift Universe. The correlation of cluster ellipticities with redshifts is undoubtly an indicator of structural evolution. Using the t-Student statistics, we found a statistically significant correlation between ellipticity and redshift at the significance level of α = 0.95. In one of the two shape determination methods we found that ellipticity grew with redshift, while the other method gave opposite results. Monte Carlo simulations showed that only ellipticities calculated at the distance of 1.5 Mpc from cluster centre in the Minkowski functional method are robust enough to be taken into account, but for that radius we did not find any relation between e and z. Since CEM pointed towards the existence of the e(z) relation, we conclude that such an effect is real though rather weak. A detailed study of the e(z) relation showed that the observed relation is nonlinear, and the number of elongated structures grows rapidly for z>0.14.

Self-clarity and different clusters of insight and self-stigma in mental illness.

PubMed

Hasson-Ohayon, Ilanit; Mashiach-Eizenberg, Michal; Lysaker, Paul H; Roe, David

2016-06-30

The current study explored the self-experience of persons with Serious Mental Illness (SMI) by investigating the associations between different insight and self-stigma clusters, self-clarity, hope, recovery, and functioning. One hundred seven persons diagnosed with a SMI were administered six scales: self-concept clarity, self-stigma, insight into the illness, hope, recovery, and functioning. Correlations and cluster analyses were performed. Insight, as measured by a self-report scale was not related to any other variable. Self-stigma was negatively associated with self-clarity, hope, recovery and functioning. Three clusters emerged: moderate stigma/high insight (n=31), high stigma/moderate insight (n=28), and low stigma/low insight (n=42). The group with low stigma and low insight had higher mean levels of self-clarity and hope than the other two groups. There were no significant differences between cluster 1 (moderate stigma/high insight) and cluster 2 (high stigma/moderate insight) in all the variables beside self-clarity. The group with moderate stigma and high insight had significantly higher mean levels of self-clarity than the group with high stigma and moderate insight. Results reveal that when people diagnosed with SMI do not have high levels of self-stigma they often report a positive and clear sense of self accompanied with hope, regardless of having low insight. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The externally corrected coupled cluster approach with four- and five-body clusters from the CASSCF wave function.

PubMed

Xu, Enhua; Li, Shuhua

2015-03-07

An externally corrected CCSDt (coupled cluster with singles, doubles, and active triples) approach employing four- and five-body clusters from the complete active space self-consistent field (CASSCF) wave function (denoted as ecCCSDt-CASSCF) is presented. The quadruple and quintuple excitation amplitudes within the active space are extracted from the CASSCF wave function and then fed into the CCSDt-like equations, which can be solved in an iterative way as the standard CCSDt equations. With a size-extensive CASSCF reference function, the ecCCSDt-CASSCF method is size-extensive. When the CASSCF wave function is readily available, the computational cost of the ecCCSDt-CASSCF method scales as the popular CCSD method (if the number of active orbitals is small compared to the total number of orbitals). The ecCCSDt-CASSCF approach has been applied to investigate the potential energy surface for the simultaneous dissociation of two O-H bonds in H2O, the equilibrium distances and spectroscopic constants of 4 diatomic molecules (F2(+), O2(+), Be2, and NiC), and the reaction barriers for the automerization reaction of cyclobutadiene and the Cl + O3 → ClO + O2 reaction. In most cases, the ecCCSDt-CASSCF approach can provide better results than the CASPT2 (second order perturbation theory with a CASSCF reference function) and CCSDT methods.

Ensemble averaged structure–function relationship for nanocrystals: effective superparamagnetic Fe clusters with catalytically active Pt skin [Ensemble averaged structure-function relationship for composite nanocrystals: magnetic bcc Fe clusters with catalytically active fcc Pt skin

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

Petkov, Valeri; Prasai, Binay; Shastri, Sarvjit

Practical applications require the production and usage of metallic nanocrystals (NCs) in large ensembles. Besides, due to their cluster-bulk solid duality, metallic NCs exhibit a large degree of structural diversity. This poses the question as to what atomic-scale basis is to be used when the structure–function relationship for metallic NCs is to be quantified precisely. In this paper, we address the question by studying bi-functional Fe core-Pt skin type NCs optimized for practical applications. In particular, the cluster-like Fe core and skin-like Pt surface of the NCs exhibit superparamagnetic properties and a superb catalytic activity for the oxygen reduction reaction,more » respectively. We determine the atomic-scale structure of the NCs by non-traditional resonant high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Using the experimental structure data we explain the observed magnetic and catalytic behavior of the NCs in a quantitative manner. Lastly, we demonstrate that NC ensemble-averaged 3D positions of atoms obtained by advanced X-ray scattering techniques are a very proper basis for not only establishing but also quantifying the structure–function relationship for the increasingly complex metallic NCs explored for practical applications.« less

Scrutinizing human MHC polymorphism: Supertype analysis using Poisson-Boltzmann electrostatics and clustering.

PubMed

Mumtaz, Shahzad; Nabney, Ian T; Flower, Darren R

2017-10-01

Peptide-binding MHC proteins are thought the most variable across the human population; the extreme MHC polymorphism observed is functionally important and results from constrained divergent evolution. MHCs have vital functions in immunology and homeostasis: cell surface MHC class I molecules report cell status to CD8+ T cells, NKT cells and NK cells, thus playing key roles in pathogen defence, as well as mediating smell recognition, mate choice, Adverse Drug Reactions, and transplantation rejection. MHC peptide specificity falls into several supertypes exhibiting commonality of binding. It seems likely that other supertypes exist relevant to other functions. Since comprehensive experimental characterization is intractable, structure-based bioinformatics is the only viable solution. We modelled functional MHC proteins by homology and used calculated Poisson-Boltzmann electrostatics projected from the top surface of the MHC as multi-dimensional descriptors, analysing them using state-of-the-art dimensionality reduction techniques and clustering algorithms. We were able to recover the 3 MHC loci as separate clusters and identify clear sub-groups within them, vindicating unequivocally our choice of both data representation and clustering strategy. We expect this approach to make a profound contribution to the study of MHC polymorphism and its functional consequences, and, by extension, other burgeoning structural systems, such as GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.

The Evolution of the Globular Cluster System in a Triaxial Galaxy: Can a Galactic Nucleus Form by Globular Cluster Capture?

NASA Astrophysics Data System (ADS)

Capuzzo-Dolcetta, Roberto

1993-10-01

Among the possible phenomena inducing evolution of the globular cluster system in an elliptical galaxy, dynamical friction due to field stars and tidal disruption caused by a central nucleus is of crucial importance. The aim of this paper is the study of the evolution of the globular cluster system in a triaxial galaxy in the presence of these phenomena. In particular, the possibility is examined that some galactic nuclei have been formed by frictionally decayed globular clusters moving in a triaxial potential. We find that the initial rapid growth of the nucleus, due mainly to massive clusters on box orbits falling in a short time scale into the galactic center, is later slowed by tidal disruption induced by the nucleus itself on less massive clusters in the way described by Ostriker, Binney, and Saha. The efficiency of dynamical friction is such to carry to the center of the galaxy enough globular cluster mass available to form a compact nucleus, but the actual modes and results of cluster-cluster encounters in the central potential well are complicated phenomena which remains to be investigated. The mass of the resulting nucleus is determined by the mutual feedback of the described processes, together with the initial spatial, velocity, and mass distributions of the globular cluster family. The effect on the system mass function is studied, showing the development of a low- and high-mass turnover even with an initially flat mass function. Moreover, in this paper is discussed the possibility that the globular cluster fall to the galactic center has been a cause of primordial violent galactic activity. An application of the model to M31 is presented.

Star cluster formation in cosmological simulations. I. Properties of young clusters

DOE PAGES

Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.; ...

2017-01-03

We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope ismore » $$\\alpha \\approx 1.8\\mbox{–}2$$, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. As a result, comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.« less

Structural and electronic properties of Aun-xPtx (n = 2-14; x ⩽ n) clusters: The density functional theory investigation

NASA Astrophysics Data System (ADS)

Yuan, H. K.; Kuang, A. L.; Tian, C. L.; Chen, H.

2014-03-01

The structural evolutions and electronic properties of bimetallic Aun-xPtx (n = 2-14; x ⩽ n) clusters are investigated by using the density functional theory (DFT) with the generalized gradient approximation (GGA). The monatomic doping Aun-1Pt clusters are emphasized and compared with the corresponding pristine Aun clusters. The results reveal that the planar configurations are favored for both Aun-1Pt and Aun clusters with size up to n = 13, and the former often employ the substitution patterns based on the structures of the latter. The most stable clusters are Au6 and Au6Pt, which adopt regular planar triangle (D3h) and hexagon-ring (D6h) structures and can be regarded as the preferential building units in designing large clusters. For Pt-rich bimetallic clusters, their structures can be obtained from the substitution of Pt atoms by Au atoms from the Ptn structures, where Pt atoms assemble together and occupy the center yet Au atoms prefer the apex positions showing a segregation effect. With respect to pristine Au clusters, AunPt clusters exhibit somewhat weaker and less pronounced odd-even oscillations in the highest occupied and lowest unoccupied molecular-orbital gaps (HOMO-LUMO gap), electron affinity (EA), and ionization potential (IP) due to the partially released electron pairing effect. The analyses of electronic structure indicate that Pt atoms in AuPt clusters would delocalize their one 6s and one 5d electrons to contribute the electronic shell closure. The sp-d hybridizations as well as the d-d interactions between the host Au and dopant Pt atoms result in the enhanced stabilities of AuPt clusters.

Nature's polyoxometalate chemistry: X-ray structure of the Mo storage protein loaded with discrete polynuclear Mo-O clusters.

PubMed

Kowalewski, Björn; Poppe, Juliane; Demmer, Ulrike; Warkentin, Eberhard; Dierks, Thomas; Ermler, Ulrich; Schneider, Klaus

2012-06-13

Some N(2)-fixing bacteria prolong the functionality of nitrogenase in molybdenum starvation by a special Mo storage protein (MoSto) that can store more than 100 Mo atoms. The presented 1.6 Å X-ray structure of MoSto from Azotobacter vinelandii reveals various discrete polyoxomolybdate clusters, three covalently and three noncovalently bound Mo(8), three Mo(5-7), and one Mo(3) clusters, and several low occupied, so far undefinable clusters, which are embedded in specific pockets inside a locked cage-shaped (αβ)(3) protein complex. The structurally identical Mo(8) clusters (three layers of two, four, and two MoO(n) octahedra) are distinguishable from the [Mo(8)O(26)](4-) cluster formed in acidic solutions by two displaced MoO(n) octahedra implicating three kinetically labile terminal ligands. Stabilization in the covalent Mo(8) cluster is achieved by Mo bonding to Hisα156-N(ε2) and Gluα129-O(ε1). The absence of covalent protein interactions in the noncovalent Mo(8) cluster is compensated by a more extended hydrogen-bond network involving three pronounced histidines. One displaced MoO(n) octahedron might serve as nucleation site for an inhomogeneous Mo(5-7) cluster largely surrounded by bulk solvent. In the Mo(3) cluster located on the 3-fold axis, the three accurately positioned His140-N(ε2) atoms of the α subunits coordinate to the Mo atoms. The formed polyoxomolybdate clusters of MoSto, not detectable in bulk solvent, are the result of an interplay between self- and protein-driven assembly processes that unite inorganic supramolecular and protein chemistry in a host-guest system. Template, nucleation/protection, and catalyst functions of the polypeptide as well as perspectives for designing new clusters are discussed.

Star cluster formation in cosmological simulations. I. Properties of young clusters

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

Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.

We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope ismore » $$\\alpha \\approx 1.8\\mbox{–}2$$, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. As a result, comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.« less

Comprehensive cluster analysis with Transitivity Clustering.

PubMed

Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

2011-03-01

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

Noble gas cluster ions

NASA Astrophysics Data System (ADS)

Kaya, Yunus; Kalkan, Yalçin; Veenhof, Rob

2018-02-01

In this work, a reaction mechanism of formation of noble gas (Ng) cluster ions has been theoretically investigated in detail. The kinetic studies of formation of Xe+Xe cluster in Xe, Ar+Ar cluster ions in Ar, and Ne+Ne cluster ions in Ne have been made as theoretically. The optimized structures in the ground state were calculated using the density functional theory (DFT) by the B3LYP method combined with the Stuttgart/Dresden effective core potential basis set (SDD). In addition, we calculated the rate constants of all cluster formations. The results are 1.15 × 10-31, 3.58 × 10-31, 0.23 × 10-31cm6/s, respectively for Neon, Argon, Xenon cluster ions.

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

NASA Astrophysics Data System (ADS)

Pacaud, F.; Clerc, N.; Giles, P. A.; Adami, C.; Sadibekova, T.; Pierre, M.; Maughan, B. J.; Lieu, M.; Le Fèvre, J. P.; Alis, S.; Altieri, B.; Ardila, F.; Baldry, I.; Benoist, C.; Birkinshaw, M.; Chiappetti, L.; Démoclès, J.; Eckert, D.; Evrard, A. E.; Faccioli, L.; Gastaldello, F.; Guennou, L.; Horellou, C.; Iovino, A.; Koulouridis, E.; Le Brun, V.; Lidman, C.; Liske, J.; Maurogordato, S.; Menanteau, F.; Owers, M.; Poggianti, B.; Pomarède, D.; Pompei, E.; Ponman, T. J.; Rapetti, D.; Reiprich, T. H.; Smith, G. P.; Tuffs, R.; Valageas, P.; Valtchanov, I.; Willis, J. P.; Ziparo, F.

2016-06-01

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. The survey will ultimately uncover several hundreds of galaxy clusters out to a redshift of ~2 at a sensitivity of ~10-14 erg s-1 cm-2 in the [0.5-2] keV band. Aims: This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of 3 × 10-14 erg s-1 cm-2 on the source flux within a 1' aperture. Methods: The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results: The bright cluster sample consists of systems with masses between M500 = 7 × 1013 and 3 × 1014 M⊙, mostly located between z = 0.1 and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the prediction from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of σ8 and/or ΩM appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to z ~ 1. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. Based on observations made with ESO Telescopes at the La Silla and Paranal Observatories under programme ID 089.A-0666 and LP191.A-0268.The Master Catalogue is 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/592/A2

A Survey of Popular R Packages for Cluster Analysis

ERIC Educational Resources Information Center

Flynt, Abby; Dean, Nema

2016-01-01

Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…

VizieR Online Data Catalog: The Seven Sisters DANCe. I. Pleiades (Bouy+, 2015)

NASA Astrophysics Data System (ADS)

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

2015-02-01

Position, proper motion, multi-wavelength ugrizYJHK photometry and membership probability to the Pleiades cluster for 1972245 sources. Present-day system bolometric luminosity and mass-functions of the Pleiades cluster. Empirical sequence of the Pleiades cluster in ugrizYJHK and BT,VT,JHK photometric systems. (7 data files).

Functional Analytic Psychotherapy (FAP) for Cluster B Personality Disorders: Creating Meaning, Mattering, and Skills

ERIC Educational Resources Information Center

Pankey, Julieann

2012-01-01

There are ten identified personality disorders, broken into three clusters: A, B, and C. Individuals with a cluster B diagnosis may demonstrate marked displays of emotional instability, erratic and disruptive patterns around interpersonal relationships, a myopic and restricted range of affect, a pronounced lack of empathy and insight, barriers…

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

USDA-ARS?s Scientific Manuscript database

Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

A Database of Young Star Clusters for Five Hundred Galaxies

NASA Astrophysics Data System (ADS)

Whitmore, Brad

2009-07-01

We propose to use the source lists developed as part of the Hubble Legacy Archive {HLA: Data Release 1 - February 8, 2008} to obtain a large {N 50 galaxies for multi-wavelength, N 500 galaxies for ACS F814W}, uniform {ACS + WFPC2 + NICMOS: DAOphot used for object detection} database of super star clusters in nearby star-forming galaxies in order to address two fundamental astronomical questions: 1} To what degree is the cluster luminosity {and mass} function of star clusters universal ? 2} What fraction of super star clusters are "missing" in optical studies {i.e., are hidden by dust}? This database will also support comparisons with new Monte-Carlo simulations that have independently been developed in the past few years by co-I Larsen and PI Whitmore, and will be used to test the Whitmore, Chandar, Fall {2007} framework designed to understand the demographics of star clusters in all star forming galaxies. The catalogs will increase the number of galaxies with measured mass and luminosity functions by an order of magnitude, and will provide a powerful new tool for comparative studies, both ours and the community's.

Mixing and Matching Siderophore Clusters: Structure and Biosynthesis of Serratiochelins from Serratia sp. V4

PubMed Central

2012-01-01

Interrogation of the evolutionary history underlying the remarkable structures and biological activities of natural products has been complicated by not knowing the functions they have evolved to fulfill. Siderophores—soluble, low molecular weight compounds—have an easily understood and measured function: acquiring iron from the environment. Bacteria engage in a fierce competition to acquire iron, which rewards the production of siderophores that bind iron tightly and cannot be used or pirated by competitors. The structures and biosyntheses of “odd” siderophores can reveal the evolutionary strategy that led to their creation. We report a new Serratia strain that produces serratiochelin and an analog of serratiochelin. A genetic approach located the serratiochelin gene cluster, and targeted mutations in several genes implicated in serratiochelin biosynthesis were generated. Bioinformatic analyses and mutagenesis results demonstrate that genes from two well-known siderophore clusters, the Escherichia coli enterobactin cluster and the Vibrio cholera vibriobactin cluster, were shuffled to produce a new siderophore biosynthetic pathway. These results highlight how modular siderophore gene clusters can be mixed and matched during evolution to generate structural diversity in siderophores. PMID:22830960

Mixing and matching siderophore clusters: structure and biosynthesis of serratiochelins from Serratia sp. V4.

PubMed

Seyedsayamdost, Mohammad R; Cleto, Sara; Carr, Gavin; Vlamakis, Hera; João Vieira, Maria; Kolter, Roberto; Clardy, Jon

2012-08-22

Interrogation of the evolutionary history underlying the remarkable structures and biological activities of natural products has been complicated by not knowing the functions they have evolved to fulfill. Siderophores-soluble, low molecular weight compounds-have an easily understood and measured function: acquiring iron from the environment. Bacteria engage in a fierce competition to acquire iron, which rewards the production of siderophores that bind iron tightly and cannot be used or pirated by competitors. The structures and biosyntheses of "odd" siderophores can reveal the evolutionary strategy that led to their creation. We report a new Serratia strain that produces serratiochelin and an analog of serratiochelin. A genetic approach located the serratiochelin gene cluster, and targeted mutations in several genes implicated in serratiochelin biosynthesis were generated. Bioinformatic analyses and mutagenesis results demonstrate that genes from two well-known siderophore clusters, the Escherichia coli enterobactin cluster and the Vibrio cholera vibriobactin cluster, were shuffled to produce a new siderophore biosynthetic pathway. These results highlight how modular siderophore gene clusters can be mixed and matched during evolution to generate structural diversity in siderophores.

Clustering environments of BL Lac objects

NASA Technical Reports Server (NTRS)

Wurtz, Ronald; Ellingson, Erica; Stocke, John T.; Yee, H. K. C.

1993-01-01

We report measurements of the amplitude of the BL Lac galaxy spatial covariance function, B(gb), for the fields of five BL Lacertae objects. We present evidence for rich clusters around MS 1207+39 and MS 1407+59, and confirm high richness for the cluster containing H0414+009. We discuss the ease of 3C 66 A and find evidence for a poor cluster based on an uncertain redshift of z = 0.444. These data suggest that at least some BL Lac objects are consistent with being FR 1 radio galaxies in rich clusters.

Energy spectra of X-ray clusters of galaxies

NASA Technical Reports Server (NTRS)

Avni, Y.

1976-01-01

A procedure for estimating the ranges of parameters that describe the spectra of X-rays from clusters of galaxies is presented. The applicability of the method is proved by statistical simulations of cluster spectra; such a proof is necessary because of the nonlinearity of the spectral functions. Implications for the spectra of the Perseus, Coma, and Virgo clusters are discussed. The procedure can be applied in more general problems of parameter estimation.

Quantum Dynamics of Helium Clusters

DTIC Science & Technology

1993-03-01

the structure of both these and the HeN clusters in the body fixed frame by computing principal moments of inertia, thereby avoiding the...8217 of helium clusters, with the modification that we subtract 0.96 K from the computed values so that lor sufficiently large clusters we recover the...phonon spectrum of liquid He. To get a picture of these spectra one needs to compute the structure functions 51. Monte Carlo random walk simulations

On basis set superposition error corrected stabilization energies for large n-body clusters.

PubMed

Walczak, Katarzyna; Friedrich, Joachim; Dolg, Michael

2011-10-07

In this contribution, we propose an approximate basis set superposition error (BSSE) correction scheme for the site-site function counterpoise and for the Valiron-Mayer function counterpoise correction of second order to account for the basis set superposition error in clusters with a large number of subunits. The accuracy of the proposed scheme has been investigated for a water cluster series at the CCSD(T), CCSD, MP2, and self-consistent field levels of theory using Dunning's correlation consistent basis sets. The BSSE corrected stabilization energies for a series of water clusters are presented. A study regarding the possible savings with respect to computational resources has been carried out as well as a monitoring of the basis set dependence of the approximate BSSE corrections. © 2011 American Institute of Physics

Computational genomic identification and functional reconstitution of plant natural product biosynthetic pathways

PubMed Central

2016-01-01

Covering: 2003 to 2016 The last decade has seen the first major discoveries regarding the genomic basis of plant natural product biosynthetic pathways. Four key computationally driven strategies have been developed to identify such pathways, which make use of physical clustering, co-expression, evolutionary co-occurrence and epigenomic co-regulation of the genes involved in producing a plant natural product. Here, we discuss how these approaches can be used for the discovery of plant biosynthetic pathways encoded by both chromosomally clustered and non-clustered genes. Additionally, we will discuss opportunities to prioritize plant gene clusters for experimental characterization, and end with a forward-looking perspective on how synthetic biology technologies will allow effective functional reconstitution of candidate pathways using a variety of genetic systems. PMID:27321668

A density functional global optimisation study of neutral 8-atom Cu-Ag and Cu-Au clusters

NASA Astrophysics Data System (ADS)

Heard, Christopher J.; Johnston, Roy L.

2013-02-01

The effect of doping on the energetics and dimensionality of eight atom coinage metal subnanometre particles is fully resolved using a genetic algorithm in tandem with on the fly density functional theory calculations to determine the global minima (GM) for Cu n Ag(8- n) and Cu n Au(8- n) clusters. Comparisons are made to previous ab initio work on mono- and bimetallic clusters, with excellent agreement found. Charge transfer and geometric arguments are considered to rationalise the stability of the particular permutational isomers found. An interesting transition between three dimensional and two dimensional GM structures is observed for copper-gold clusters, which is sharper and appears earlier in the doping series than is known for gold-silver particles.

Excitons in Potassium Bromide: A Study using Embedded Time-dependent Density Functional Theory and Equation-of-Motion Coupled Cluster Methods

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

Govind, Niranjan; Sushko, Petr V.; Hess, Wayne P.

2009-03-05

We present a study of the electronic excitations in insulating materials using an embedded- cluster method. The excited states of the embedded cluster are studied systematically using time-dependent density functional theory (TDDFT) and high-level equation-of-motion coupled cluster (EOMCC) methods. In particular, we have used EOMCC models with singles and doubles (EOMCCSD) and two approaches which account for the e®ect of triply excited con¯gurations in non-iterative and iterative fashions. We present calculations of the lowest surface excitations of the well-studied potassium bromide (KBr) system and compare our results with experiment. The bulk-surface exciton shift is also calculated at the TDDFT levelmore » and compared with experiment.« less

An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems

PubMed Central

Salcedo-Sanz, S.; Del Ser, J.; Geem, Z. W.

2014-01-01

This paper presents a novel fuzzy clustering technique based on grouping genetic algorithms (GGAs), which are a class of evolutionary algorithms especially modified to tackle grouping problems. Our approach hinges on a GGA devised for fuzzy clustering by means of a novel encoding of individuals (containing elements and clusters sections), a new fitness function (a superior modification of the Davies Bouldin index), specially tailored crossover and mutation operators, and the use of a scheme based on a local search and a parallelization process, inspired from an island-based model of evolution. The overall performance of our approach has been assessed over a number of synthetic and real fuzzy clustering problems with different objective functions and distance measures, from which it is concluded that the proposed approach shows excellent performance in all cases. PMID:24977235

Onset of carbon-carbon bonding in Ta(5)C(y) (y = 0-6) clusters: a threshold photoionization and density functional theory study.

PubMed

Dryza, Viktoras; Alvino, Jason F; Metha, Gregory F

2010-04-01

We have used photoionization efficiency spectroscopy to determine ionization energies (IEs) of the gas-phase tantalum-carbide clusters Ta(5)C(y) (y = 0-6). The structures of the clusters observed in the experiment are assigned by comparing the experimental IEs with those of candidate isomers, calculated by density functional theory. Two competing geometries of the underlying Ta(5) cluster are found to be present in the assigned Ta(5)C(y) structures; either a "prolate" or "distorted oblate" trigonal bipyramid geometry. The onset of carbon-carbon bonding in the Ta(5)C(y) series is proposed to occur at y = 6, with the structure of Ta(5)C(6) containing two molecular C(2) units.

Alternative states of a semiarid grassland ecosystem: implications for ecosystem services

USGS Publications Warehouse

Miller, Mark E.; Belote, R. Travis; Bowker, Matthew A.; Garman, Steven L.

2011-01-01

Ecosystems can shift between alternative states characterized by persistent differences in structure, function, and capacity to provide ecosystem services valued by society. We examined empirical evidence for alternative states in a semiarid grassland ecosystem where topographic complexity and contrasting management regimes have led to spatial variations in levels of livestock grazing. Using an inventory data set, we found that plots (n = 72) cluster into three groups corresponding to generalized alternative states identified in an a priori conceptual model. One cluster (biocrust) is notable for high coverage of a biological soil crust functional group in addition to vascular plants. Another (grass-bare) lacks biological crust but retains perennial grasses at levels similar to the biocrust cluster. A third (annualized-bare) is dominated by invasive annual plants. Occurrence of grass-bare and annualized-bare conditions in areas where livestock have been excluded for over 30 years demonstrates the persistence of these states. Significant differences among all three clusters were found for percent bare ground, percent total live cover, and functional group richness. Using data for vegetation structure and soil erodibility, we also found large among-cluster differences in average levels of dust emissions predicted by a wind-erosion model. Predicted emissions were highest for the annualized-bare cluster and lowest for the biocrust cluster, which was characterized by zero or minimal emissions even under conditions of extreme wind. Results illustrate potential trade-offs among ecosystem services including livestock production, soil retention, carbon storage, and biodiversity conservation. Improved understanding of these trade-offs may assist ecosystem managers when evaluating alternative management strategies.

Combined Mössbauer spectroscopic, multi-edge X-ray absorption spectroscopic, and density functional theoretical study of the radical SAM enzyme spore photoproduct lyase.

PubMed

Silver, Sunshine C; Gardenghi, David J; Naik, Sunil G; Shepard, Eric M; Huynh, Boi Hanh; Szilagyi, Robert K; Broderick, Joan B

2014-03-01

Spore photoproduct lyase (SPL), a member of the radical S-adenosyl-L-methionine (SAM) superfamily, catalyzes the direct reversal of the spore photoproduct, a thymine dimer specific to bacterial spores, to two thymines. SPL requires SAM and a redox-active [4Fe-4S] cluster for catalysis. Mössbauer analysis of anaerobically purified SPL indicates the presence of a mixture of cluster states with the majority (40 %) as [2Fe-2S](2+) clusters and a smaller amount (15 %) as [4Fe-4S](2+) clusters. On reduction, the cluster content changes to primarily (60 %) [4Fe-4S](+). The speciation information from Mössbauer data allowed us to deconvolute iron and sulfur K-edge X-ray absorption spectra to uncover electronic (X-ray absorption near-edge structure, XANES) and geometric (extended X-ray absorption fine structure, EXAFS) structural features of the Fe-S clusters, and their interactions with SAM. The iron K-edge EXAFS data provide evidence for elongation of a [2Fe-2S] rhomb of the [4Fe-4S] cluster on binding SAM on the basis of an Fe···Fe scatterer at 3.0 Å. The XANES spectra of reduced SPL in the absence and presence of SAM overlay one another, indicating that SAM is not undergoing reductive cleavage. The X-ray absorption spectroscopy data for SPL samples and data for model complexes from the literature allowed the deconvolution of contributions from [2Fe-2S] and [4Fe-4S] clusters to the sulfur K-edge XANES spectra. The analysis of pre-edge features revealed electronic changes in the Fe-S clusters as a function of the presence of SAM. The spectroscopic findings were further corroborated by density functional theory calculations that provided insights into structural and electronic perturbations that can be correlated by considering the role of SAM as a catalyst or substrate.

Cluster formation in precompound nuclei in the time-dependent framework

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

Schuetrumpf, B.; Nazarewicz, W.

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N = Z . Furthermore, we study reactions with oxygen and carbonmore » ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O, 40Ca + 16O, 40Ca + 40Ca , and 16,18O + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12 C - 12 C- α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of 16,18O + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. Finally, the localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.« less

A point mutation in the [2Fe–2S] cluster binding region of the NAF-1 protein (H114C) dramatically hinders the cluster donor properties

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

Tamir, Sagi; Eisenberg-Domovich, Yael; Conlan, Andrea R.

2014-06-01

NAF-1 has been shown to be related with human health and disease, is upregulated in epithelial breast cancer and suppression of its expression significantly suppresses tumor growth. It is shown that replacement of the single His ligand with Cys resulted in dramatic changes to the properties of its 2Fe-2S clusters without any global crystal structural changes. NAF-1 is an important [2Fe–2S] NEET protein associated with human health and disease. A mis-splicing mutation in NAF-1 results in Wolfram Syndrome type 2, a lethal childhood disease. Upregulation of NAF-1 is found in epithelial breast cancer cells, and suppression of NAF-1 expression bymore » knockdown significantly suppresses tumor growth. Key to NAF-1 function is the NEET fold with its [2Fe–2S] cluster. In this work, the high-resolution structure of native NAF-1 was determined to 1.65 Å resolution (R factor = 13.5%) together with that of a mutant in which the single His ligand of its [2Fe–2S] cluster, His114, was replaced by Cys. The NAF-1 H114C mutant structure was determined to 1.58 Å resolution (R factor = 16.0%). All structural differences were localized to the cluster binding site. Compared with native NAF-1, the [2Fe–2S] clusters of the H114C mutant were found to (i) be 25-fold more stable, (ii) have a redox potential that is 300 mV more negative and (iii) have their cluster donation/transfer function abolished. Because no global structural differences were found between the mutant and the native (wild-type) NAF-1 proteins, yet significant functional differences exist between them, the NAF-1 H114C mutant is an excellent tool to decipher the underlying biological importance of the [2Fe–2S] cluster of NAF-1 in vivo.« less

Cluster formation in precompound nuclei in the time-dependent framework

DOE PAGES

Schuetrumpf, B.; Nazarewicz, W.

2017-12-15

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N = Z . Furthermore, we study reactions with oxygen and carbonmore » ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O, 40Ca + 16O, 40Ca + 40Ca , and 16,18O + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12 C - 12 C- α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of 16,18O + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. Finally, the localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.« less

THE CLUSTERING OF ALFALFA GALAXIES: DEPENDENCE ON H I MASS, RELATIONSHIP WITH OPTICAL SAMPLES, AND CLUES OF HOST HALO PROPERTIES

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

Papastergis, Emmanouil; Giovanelli, Riccardo; Haynes, Martha P.

We use a sample of ≈6000 galaxies detected by the Arecibo Legacy Fast ALFA (ALFALFA) 21 cm survey to measure the clustering properties of H I-selected galaxies. We find no convincing evidence for a dependence of clustering on galactic atomic hydrogen (H I) mass, over the range M{sub H{sub I}} ≈ 10{sup 8.5}-10{sup 10.5} M{sub ☉}. We show that previously reported results of weaker clustering for low H I mass galaxies are probably due to finite-volume effects. In addition, we compare the clustering of ALFALFA galaxies with optically selected samples drawn from the Sloan Digital Sky Survey (SDSS). We findmore » that H I-selected galaxies cluster more weakly than even relatively optically faint galaxies, when no color selection is applied. Conversely, when SDSS galaxies are split based on their color, we find that the correlation function of blue optical galaxies is practically indistinguishable from that of H I-selected galaxies. At the same time, SDSS galaxies with red colors are found to cluster significantly more than H I-selected galaxies, a fact that is evident in both the projected as well as the full two-dimensional correlation function. A cross-correlation analysis further reveals that gas-rich galaxies 'avoid' being located within ≈3 Mpc of optical galaxies with red colors. Next, we consider the clustering properties of halo samples selected from the Bolshoi ΛCDM simulation. A comparison with the clustering of ALFALFA galaxies suggests that galactic H I mass is not tightly related to host halo mass and that a sizable fraction of subhalos do not host H I galaxies. Lastly, we find that we can recover fairly well the correlation function of H I galaxies by just excluding halos with low spin parameter. This finding lends support to the hypothesis that halo spin plays a key role in determining the gas content of galaxies.« less

Cluster formation in precompound nuclei in the time-dependent framework

NASA Astrophysics Data System (ADS)

Schuetrumpf, B.; Nazarewicz, W.

2017-12-01

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N =Z . Furthermore, we study reactions with oxygen and carbon ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O,40Ca + 16O, 40Ca + 40Ca, and O,1816 + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12C - 12C-α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of O,1816 + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. The localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.

MicroRNA miR-23a cluster promotes osteocyte differentiation by regulating TGF-β signalling in osteoblasts

PubMed Central

Zeng, Huan-Chang; Bae, Yangjin; Dawson, Brian C.; Chen, Yuqing; Bertin, Terry; Munivez, Elda; Campeau, Philippe M.; Tao, Jianning; Chen, Rui; Lee, Brendan H.

2017-01-01

Osteocytes are the terminally differentiated cell type of the osteoblastic lineage and have important functions in skeletal homeostasis. Although the transcriptional regulation of osteoblast differentiation has been well characterized, the factors that regulate differentiation of osteocytes from mature osteoblasts are poorly understood. Here we show that miR-23a∼27a∼24-2 (miR-23a cluster) promotes osteocyte differentiation. Osteoblast-specific miR-23a cluster gain-of-function mice have low bone mass associated with decreased osteoblast but increased osteocyte numbers. By contrast, loss-of-function transgenic mice overexpressing microRNA decoys for either miR-23a or miR-27a, but not miR24-2, show decreased osteocyte numbers. Moreover, RNA-sequencing analysis shows altered transforming growth factor-β (TGF-β) signalling. Prdm16, a negative regulator of the TGF-β pathway, is directly repressed by miR-27a with concomitant alteration of sclerostin expression, and pharmacological inhibition of TGF-β rescues the phenotypes observed in the gain-of-function transgenic mice. Taken together, the miR-23a cluster regulates osteocyte differentiation by modulating the TGF-β signalling pathway through targeting of Prdm16. PMID:28397831

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

PubMed Central

Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin

2016-01-01

ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery. PMID:27451447

Hole localization in Fe2O3 from density functional theory and wave-function-based methods

NASA Astrophysics Data System (ADS)

Ansari, Narjes; Ulman, Kanchan; Camellone, Matteo Farnesi; Seriani, Nicola; Gebauer, Ralph; Piccinin, Simone

2017-08-01

Hematite (α -Fe2O3 ) is a promising photocatalyst material for water splitting, where photoinduced holes lead to the oxidation of water and the release of molecular oxygen. In this work, we investigate the properties of holes in hematite using density functional theory (DFT) calculations with hybrid functionals. We find that holes form small polarons and, depending on the fraction of exact exchange included in the PBE0 functional, the site where the holes localize changes from Fe to O. We find this result to be independent of the size and structure of the system: small Fe2O3 clusters with tetrahedral coordination, larger clusters with octahedral coordination, Fe2O3 (001) surfaces in contact with water, and bulk Fe2O3 display a very similar behavior in terms of hole localization as a function of the fraction of exact exchange. We then use wave-function-based methods such as coupled cluster with single and double excitations and Møller-Plesset second-order perturbation theory applied on a cluster model of Fe2O3 to shed light on which of the two solutions is correct. We find that these high-level quantum chemistry methods suggest holes in hematite are localized on oxygen atoms. We also explore the use of the DFT +U approach as a computationally convenient way to overcome the known limitations of generalized gradient approximation functionals and recover a gap in line with experiments and hole localization on oxygen in agreement with quantum chemistry methods.

Low-mass stars in globular clusters. III. The mass function of 47 Tucanae.

NASA Astrophysics Data System (ADS)

de Marchi, G.; Paresce, F.

1995-12-01

We have used the WFPC2 on board HST to investigate the stellar population in a field located 4'6 E of the center of the globular cluster 47 Tuc (NGC 104), close to the half-mass radius, through wide band imaging at 606 and 812nm. A total of ~3000 stars are accurately classified by two-color photometry to form a color-magnitude diagram extending down to a limiting magnitude m_814_=~m_I_=~24. A rich cluster main sequence is detected spanning the range from m_814_=~18 through m_814_=~23, where it spreads considerably due to the increasing photometric uncertainty and galaxy contamination. A secondary sequence of objects is also detected, parallel to the main sequence, as expected for a population of binary stars. The measured binary fraction in the range 195%. The main sequence luminosity function obtained from the observed CMD increases with decreasing luminosity following a power-law trend with index α=~0.15 in the range 5

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species

PubMed Central

Lind, Abigail L.; Wisecaver, Jennifer H.; Lameiras, Catarina; Wiemann, Philipp; Palmer, Jonathan M.; Keller, Nancy P.; Rodrigues, Fernando; Goldman, Gustavo H.

2017-01-01

Filamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns. PMID:29149178

Function and maturation of the Fe-S center in dihydroxyacid dehydratase from Arabidopsis.

PubMed

Gao, Huanyao; Azam, Tamanna; Randeniya, Sajini; Couturier, Jérémy; Rouhier, Nicolas; Johnson, Michael K

2018-03-23

Dihydroxyacid dehydratase (DHAD) is the third enzyme required for branched-chain amino acid biosynthesis in bacteria, fungi, and plants. DHAD enzymes contain two distinct types of active-site Fe-S clusters. The best characterized examples are Escherichia coli DHAD, which contains an oxygen-labile [Fe 4 S 4 ] cluster, and spinach DHAD, which contains an oxygen-resistant [Fe 2 S 2 ] cluster. Although the Fe-S cluster is crucial for DHAD function, little is known about the cluster-coordination environment or the mechanism of catalysis and cluster biogenesis. Here, using the combination of UV-visible absorption and circular dichroism and resonance Raman and electron paramagnetic resonance, we spectroscopically characterized the Fe-S center in DHAD from Arabidopsis thaliana ( At ). Our results indicated that At DHAD can accommodate [Fe 2 S 2 ] and [Fe 4 S 4 ] clusters. However, only the [Fe 2 S 2 ] cluster-bound form is catalytically active. We found that the [Fe 2 S 2 ] cluster is coordinated by at least one non-cysteinyl ligand, which can be replaced by the thiol group(s) of dithiothreitol. In vitro cluster transfer and reconstitution reactions revealed that [Fe 2 S 2 ] cluster-containing NFU2 protein is likely the physiological cluster donor for in vivo maturation of At DHAD. In summary, At DHAD binds either one [Fe 4 S 4 ] or one [Fe 2 S 2 ] cluster, with only the latter being catalytically competent and capable of substrate and product binding, and NFU2 appears to be the physiological [Fe 2 S 2 ] cluster donor for DHAD maturation. This work represents the first in vitro characterization of recombinant At DHAD, providing new insights into the properties, biogenesis, and catalytic role of the active-site Fe-S center in a plant DHAD. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Neutral and charged gallium clusters: structures, physical properties and implications for the melting features

NASA Astrophysics Data System (ADS)

Núñez, Sara; López, José M.; Aguado, Andrés

2012-09-01

We report the putative Global Minimum (GM) structures and electronic properties of GaN+, GaN and GaN- clusters with N = 13-37 atoms, obtained from first-principles density functional theory structural optimizations. The calculations include spin polarization and employ an exchange-correlation functional which accounts for van der Waals dispersion interactions (vdW-DFT). We find a wide diversity of structural motifs within the located GM, including decahedral, polyicosahedral, polytetrahedral and layered structures. The GM structures are also extremely sensitive to the number of electrons in the cluster, so that the structures of neutral and charged clusters differ for most sizes. The main magic numbers (clusters with an enhanced stability) are identified and interpreted in terms of electronic and geometric shell closings. The theoretical results are consistent with experimental abundance mass spectra of GaN+ and with photoelectron spectra of GaN-. The size dependence of the latent heats of melting, the shape of the heat capacity peaks, and the temperature dependence of the collision cross-sections, all measured for GaN+ clusters, are properly interpreted in terms of the calculated cohesive energies, spectra of configurational excitations, and cluster shapes, respectively. The transition from ``non-melter'' to ``magic-melter'' behaviour, experimentally observed between Ga30+ and Ga31+, is traced back to a strong geometry change. Finally, the higher-than-bulk melting temperatures of gallium clusters are correlated with a more typically metallic behaviour of the clusters as compared to the bulk, contrary to previous theoretical claims.We report the putative Global Minimum (GM) structures and electronic properties of GaN+, GaN and GaN- clusters with N = 13-37 atoms, obtained from first-principles density functional theory structural optimizations. The calculations include spin polarization and employ an exchange-correlation functional which accounts for van der Waals dispersion interactions (vdW-DFT). We find a wide diversity of structural motifs within the located GM, including decahedral, polyicosahedral, polytetrahedral and layered structures. The GM structures are also extremely sensitive to the number of electrons in the cluster, so that the structures of neutral and charged clusters differ for most sizes. The main magic numbers (clusters with an enhanced stability) are identified and interpreted in terms of electronic and geometric shell closings. The theoretical results are consistent with experimental abundance mass spectra of GaN+ and with photoelectron spectra of GaN-. The size dependence of the latent heats of melting, the shape of the heat capacity peaks, and the temperature dependence of the collision cross-sections, all measured for GaN+ clusters, are properly interpreted in terms of the calculated cohesive energies, spectra of configurational excitations, and cluster shapes, respectively. The transition from ``non-melter'' to ``magic-melter'' behaviour, experimentally observed between Ga30+ and Ga31+, is traced back to a strong geometry change. Finally, the higher-than-bulk melting temperatures of gallium clusters are correlated with a more typically metallic behaviour of the clusters as compared to the bulk, contrary to previous theoretical claims. Electronic supplementary information (ESI) available: Atomic coordinates (in xyz format and Å units) and point group symmetries for the global minimum structures reported in this paper. See DOI: 10.1039/c2nr31222k

Studies of the evolution of the x ray emission of clusters of galaxies

NASA Technical Reports Server (NTRS)

Henry, J. Patrick

1990-01-01

The x ray luminosity function of clusters of galaxies was determined at different cosmic epoches using data from the Einstein Observatory Extended Medium Survey. The sample consisted of 67 x ray selected clusters that were grouped into three redshift shells. Evolution was detected in the x ray properties of clusters. The present volume density of high luminosity clusters was found to be greater than it was in the past. This result is the first convincing evidence for evolution in the x ray properties of clusters. Investigations into the constraints provided by these data on various Cold Dark Matter models are underway.

The ROSAT Brightest Cluster Sample - I. The compilation of the sample and the cluster log N-log S distribution

NASA Astrophysics Data System (ADS)

Ebeling, H.; Edge, A. C.; Bohringer, H.; Allen, S. W.; Crawford, C. S.; Fabian, A. C.; Voges, W.; Huchra, J. P.

1998-12-01

We present a 90 per cent flux-complete sample of the 201 X-ray-brightest clusters of galaxies in the northern hemisphere (delta>=0 deg), at high Galactic latitudes (|b|>=20 deg), with measured redshifts z<=0.3 and fluxes higher than 4.4x10^-12 erg cm^-2 s^-1 in the 0.1-2.4 keV band. The sample, called the ROSAT Brightest Cluster Sample (BCS), is selected from ROSAT All-Sky Survey data and is the largest X-ray-selected cluster sample compiled to date. In addition to Abell clusters, which form the bulk of the sample, the BCS also contains the X-ray-brightest Zwicky clusters and other clusters selected from their X-ray properties alone. Effort has been made to ensure the highest possible completeness of the sample and the smallest possible contamination by non-cluster X-ray sources. X-ray fluxes are computed using an algorithm tailored for the detection and characterization of X-ray emission from galaxy clusters. These fluxes are accurate to better than 15 per cent (mean 1sigma error). We find the cumulative logN-logS distribution of clusters to follow a power law kappa S^alpha with alpha=1.31^+0.06_-0.03 (errors are the 10th and 90th percentiles) down to fluxes of 2x10^-12 erg cm^-2 s^-1, i.e. considerably below the BCS flux limit. Although our best-fitting slope disagrees formally with the canonical value of -1.5 for a Euclidean distribution, the BCS logN-logS distribution is consistent with a non-evolving cluster population if cosmological effects are taken into account. Our sample will allow us to examine large-scale structure in the northern hemisphere, determine the spatial cluster-cluster correlation function, investigate correlations between the X-ray and optical properties of the clusters, establish the X-ray luminosity function for galaxy clusters, and discuss the implications of the results for cluster evolution.

Monothiol Glutaredoxins Can Bind Linear [Fe3S4]+ and [Fe4S4]2+ Clusters in Addition to [Fe2S2]2+ Clusters: Spectroscopic Characterization and Functional Implications

PubMed Central

Zhang, Bo; Bandyopadhyay, Sibali; Shakamuri, Priyanka; Naik, Sunil G.; Huynh, Boi Hanh; Couturier, Jérémy; Rouhier, Nicolas; Johnson, Michael K.

2013-01-01

Saccharomyces cerevisiae mitochondrial glutaredoxin 5 (Grx5) is the archetypical member of a ubiquitous class of monothiol glutaredoxins with a strictly conserved CGFS active-site sequence that has been shown to function in biological [Fe2S2]2+ cluster trafficking. In this work, we show that recombinant S. cerevisiae Grx5 purified aerobically after prolonged exposure of the cell-free extract to air or after anaerobic reconstitution in the presence of glutathione, predominantly contains a linear [Fe3S4]+ cluster. The excited state electronic properties and ground state electronic and vibrational properties of the linear [Fe3S4]+ cluster have been characterized using UV-visible absorption/CD/MCD, EPR, Mössbauer and resonance Raman spectroscopies. The results reveal a rhombic S = 5/2 linear [Fe3S4]+ cluster with properties similar to those reported for synthetic linear [Fe3S4]+ clusters and the linear [Fe3S4]+ clusters in purple aconitase. Moreover, the results indicate that the Fe-S cluster content previously reported for many monothiol Grxs has been misinterpreted exclusively in terms of [Fe2S2]2+ clusters, rather than linear [Fe3S4]+ clusters or mixtures of linear [Fe3S4]+ and [Fe2S2]2+ clusters. In the absence of GSH, anaerobic reconstitution of Grx5 yields a dimeric form containing one [Fe4S4]2+ cluster that competent for in vitro activation of apo-aconitase, via intact cluster transfer. The ligation of the linear [Fe3S4]+ and [Fe4S4]2+ clusters in Grx5 has been assessed by spectroscopic, mutational and analytical studies. Potential roles for monothiol Grx5 in scavenging and recycling linear [Fe3S4]+ clusters released during protein unfolding under oxidative stress conditions and in maturation of [Fe4S4]2+ cluster-containing proteins are discussed in light of these results. PMID:24032439

Electron scattering in large water clusters from photoelectron imaging with high harmonic radiation.

PubMed

Gartmann, Thomas E; Hartweg, Sebastian; Ban, Loren; Chasovskikh, Egor; Yoder, Bruce L; Signorell, Ruth

2018-06-06

Low-energy electron scattering in water clusters (H2O)n with average cluster sizes of n < 700 is investigated by angle-resolved photoelectron spectroscopy using high harmonic radiation at photon energies of 14.0, 20.3, and 26.5 eV for ionization from the three outermost valence orbitals. The measurements probe the evolution of the photoelectron anisotropy parameter β as a function of cluster size. A remarkably steep decrease of β with increasing cluster size is observed, which for the largest clusters reaches liquid bulk values. Detailed electron scattering calculations reveal that neither gas nor condensed phase scattering can explain the cluster data. Qualitative agreement between experiment and simulations is obtained with scattering calculations that treat cluster scattering as an intermediate case between gas and condensed phase scattering.

The Radio Luminosity Function and Galaxy Evolution in the Coma Cluster

NASA Technical Reports Server (NTRS)

Miller, Neal A.; Hornschemeier, Ann E.; Mabasher, Bahram; Brudgesm Terrry J.; Hudson, Michael J.; Marzke, Ronald O.; Smith, Russell J.

2008-01-01

We investigate the radio luminosity function and radio source population for two fields within the Coma cluster of galaxies, with the fields centered on the cluster core and southwest infall region and each covering about half a square degree. Using VLA data with a typical rms sensitivity of 28 (mu)Jy per 4.4" beam, we identify 249 radio sources with optical counterparts brighter than r = 22 (equivalent to M(sub r) = -13 for cluster member galaxies). Comprehensive optical spectroscopy identifies 38 of these as members of the Coma cluster, evenly split between sources powered by an active nucleus and sources powered by active star formation. The radio-detected star-forming galaxies are restricted to radio luminosities between about 10(exp 21) and 10(exp 22) W/Hz, an interesting result given that star formation dominates field radio luminosity functions below about 10(exp 23) W/Hz. The majority of the radio-detected star-forming galaxies have characteristics of starbursts, including high specific star formation rates and optical spectra with strong emission lines. In conjunction with prior studies on post-starburst galaxies within the Coma cluster, this is consistent with a picture in which late-type galaxies entering Coma undergo a starburst prior to a rapid cessation of star formation. Optically bright elliptical galaxies (Mr less than or equals -20.5) make the largest contribution to the radio luminosity function at both the high (> approx. 3x10(exp 22) W/Hz) and low (< approx. 10(exp 21) W/Hz) ends. Through a stacking analysis of these optically-bright ellipticals we find that they continue to harbor radio sources down to luminosities as faint as 3x10(exp 19) W/Hz. However, contrary to published results for the Virgo cluster we find no evidence for the existence of a population of optically faint (M(sub r) approx. equals -14) dwarf ellipticals hosting strong radio AGN.

Order statistics applied to the most massive and most distant galaxy clusters

NASA Astrophysics Data System (ADS)

Waizmann, J.-C.; Ettori, S.; Bartelmann, M.

2013-06-01

In this work, we present an analytic framework for calculating the individual and joint distributions of the nth most massive or nth highest redshift galaxy cluster for a given survey characteristic allowing us to formulate Λ cold dark matter (ΛCDM) exclusion criteria. We show that the cumulative distribution functions steepen with increasing order, giving them a higher constraining power with respect to the extreme value statistics. Additionally, we find that the order statistics in mass (being dominated by clusters at lower redshifts) is sensitive to the matter density and the normalization of the matter fluctuations, whereas the order statistics in redshift is particularly sensitive to the geometric evolution of the Universe. For a fixed cosmology, both order statistics are efficient probes of the functional shape of the mass function at the high-mass end. To allow a quick assessment of both order statistics, we provide fits as a function of the survey area that allow percentile estimation with an accuracy better than 2 per cent. Furthermore, we discuss the joint distributions in the two-dimensional case and find that for the combination of the largest and the second largest observation, it is most likely to find them to be realized with similar values with a broadly peaked distribution. When combining the largest observation with higher orders, it is more likely to find a larger gap between the observations and when combining higher orders in general, the joint probability density function peaks more strongly. Having introduced the theory, we apply the order statistical analysis to the Southpole Telescope (SPT) massive cluster sample and metacatalogue of X-ray detected clusters of galaxies catalogue and find that the 10 most massive clusters in the sample are consistent with ΛCDM and the Tinker mass function. For the order statistics in redshift, we find a discrepancy between the data and the theoretical distributions, which could in principle indicate a deviation from the standard cosmology. However, we attribute this deviation to the uncertainty in the modelling of the SPT survey selection function. In turn, by assuming the ΛCDM reference cosmology, order statistics can also be utilized for consistency checks of the completeness of the observed sample and of the modelling of the survey selection function.

Evolution of the Black Hole Mass Function in Star Clusters from Multiple Mergers

NASA Astrophysics Data System (ADS)

Christian, Pierre; Mocz, Philip; Loeb, Abraham

2018-05-01

We investigate the effects of black hole (BH) mergers in star clusters on the black hole mass function (BHMF). As BHs are not produced in pair-instability supernovae, it is suggested that there is a dearth of high-mass stellar BHs. This dearth generates a gap in the upper end of the BHMF. Meanwhile, parameter fitting of X-ray binaries suggests the existence of a gap in the mass function under 5 solar masses. We show, through evolving a coagulation equation, that BH mergers can appreciably fill the upper mass gap, and that the lower mass gap generates potentially observable features at larger mass scales. We also explore the importance of ejections in such systems and whether dynamical clusters can be formation sites of intermediate-mass BH seeds.

Evolution of the cluster optical galaxy luminosity function in the CFHTLS: breaking the degeneracy between mass and redshift

NASA Astrophysics Data System (ADS)

Sarron, F.; Martinet, N.; Durret, F.; Adami, C.

2018-06-01

Obtaining large samples of galaxy clusters is important for cosmology: cluster counts as a function of redshift and mass can constrain the parameters of our Universe. They are also useful in order to understand the formation and evolution of clusters. We develop an improved version of the Adami & MAzure Cluster FInder (AMACFI), now the Adami, MAzure & Sarron Cluster FInder (AMASCFI), and apply it to the 154 deg2 of the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) to obtain a large catalogue of 1371 cluster candidates with mass M200 > 1014 M⊙ and redshift z ≤ 0.7. We derive the selection function of the algorithm from the Millennium simulation, and cluster masses from a richness-mass scaling relation built from matching our candidates with X-ray detections. We study the evolution of these clusters with mass and redshift by computing the i'-band galaxy luminosity functions (GLFs) for the early-type (ETGs) and late-type galaxies (LTGs). This sample is 90% pure and 70% complete, and therefore our results are representative of a large fraction of the cluster population in these redshift and mass ranges. We find an increase in both the ETG and LTG faint populations with decreasing redshift (with Schechter slopes αETG = -0.65 ± 0.03 and αLTG = -0.95 ± 0.04 at z = 0.6, and αETG = -0.79 ± 0.02 and αLTG = -1.26 ± 0.03 at z = 0.2) and also a decrease in the LTG (but not the ETG) bright end. Our large sample allows us to break the degeneracy between mass and redshift, finding that the redshift evolution is more pronounced in high-mass clusters, but that there is no significant dependence of the faint end on mass for a given redshift. These results show that the cluster red sequence is mainly formed at redshift z > 0.7, and that faint ETGs continue to enrich the red sequence through quenching of brighter LTGs at z ≤ 0.7. The efficiency of this quenching is higher in large-mass clusters, while the accretion rate of faint LTGs is lower as the more massive clusters have already emptied most of their environment at higher redshifts. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at Terapix available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS.The candidate cluster catalog is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/613/A67

The Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Dai, Xinyu

A key question in astrophysics is to constrain the evolution of the largest gravitationally bound structures in the universe. The serendipitous observations of Swift-XRT form an excellent medium-deep and wide soft X-ray survey, with a sky area of 160 square degrees at the flux limit of 5e-15 erg/s/cm^2. This survey is about an order of magnitude deeper than previous surveys of similar areas, and an order of magnitude wider than previous surveys of similar depth. It is comparable to the planned eROSITA deep survey, but already with the data several years ahead. The unique combination of the survey area and depth enables it to fill in the gap between the deep, pencil beam surveys (such as the Chandra Deep Fields) and the shallow, wide area surveys measured with ROSAT. With it, we will place independent and complementary measurements on the number counts and luminosity functions of X-ray sources. It has been proved that this survey is excellent for X-ray selected galaxy cluster surveys, based on our initial analysis of 1/4 of the fields and other independent studies. The highest priority goal is to produce the largest, uniformly selected catalog of X-ray selected clusters and increase the sample of intermediate to high redshift clusters (z > 0.5) by an order of magnitude. From this catalog, we will study the evolution of cluster number counts, luminosity function, scaling relations, and eventually the mass function. For example, various smaller scale surveys concluded divergently on the evolution of a key scaling relation, between temperature and luminosity of clusters. With the statistical power from this large sample, we will resolve the debate whether clusters evolve self-similarly. This is a crucial step in mapping cluster evolution and constraining cosmological models. First, we propose to extract the complete serendipitous extended source list for all Swift-XRT data to 2015. Second, we will use optical/IR observations to further identify galaxy clusters. These optical/IR observations include data from the SDSS, WISE, and deep optical follow-up observations from the APO, MDM, Magellan, and NOAO telescopes. WISE will confirm all z0.5 clusters. We will use ground-based observations to measure redshifts for z>0.5 clusters, with a focus of measuring 1/10 of the spectroscopic redshifts of z>0.5 clusters within the budget period. Third, we will analyze our deep Suzaku Xray follow-up observations of a sample of medium redshift clusters, and the 1/10 bright Swift clusters suitable for spectral analysis. We will also perform stacking analysis using the Swift data for clusters in different redshift bins to constrain the evolution of cluster properties.